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1. Recent reports on insect decline have highlighted the need for long-term data on insect communities towards identifying their trends and drivers.
2. With the launch of many new insect monitoring schemes to investigate insect communities over large spatial and temporal scales, Malaise traps have become one of the most important tools due to the broad spectrum of species collected and reduced capture bias through passive sampling of insects day and night. However, Malaise traps can vary in size, shape, and colour, and it is unknown how these differences affect biomass, species richness, and composition of trap catch, making it difficult to compare results between studies.
3. We compared five Malaise trap types (three variations of the Townes and two variations of the Bartak Malaise trap) to determine their effects on biomass and species richness as identified by metabarcoding.
4. Insect biomass varied by 20%–55%, not strictly following trap size but varying with trap type. Total species richness was 20%–38% higher in the three Townes trap models compared to the Bartak traps. Bartak traps captured lower richness of highly mobile taxa but increased richness of ground-dwelling taxa. The white roofed Townes trap captured a higher richness of pollinators.
5. We find that biomass, total richness, and taxa group specific richness are all sensitive to Malaise trap type. Trap type should be carefully considered and aligned to match monitoring and research questions. Additionally, our estimates of trap type effects can be used to adjust results to facilitate comparisons across studies.
Background: High numbers of consumable medical materials (eg, sterile needles and swabs) are used during the daily routine of intensive care units (ICUs) worldwide. Although medical consumables largely contribute to total ICU hospital expenditure, many hospitals do not track the individual use of materials. Current tracking solutions meeting the specific requirements of the medical environment, like barcodes or radio frequency identification, require specialized material preparation and high infrastructure investment. This impedes the accurate prediction of consumption, leads to high storage maintenance costs caused by large inventories, and hinders scientific work due to inaccurate documentation. Thus, new cost-effective and contactless methods for object detection are urgently needed.
Objective: The goal of this work was to develop and evaluate a contactless visual recognition system for tracking medical consumable materials in ICUs using a deep learning approach on a distributed client-server architecture.
Methods: We developed Consumabot, a novel client-server optical recognition system for medical consumables, based on the convolutional neural network model MobileNet implemented in Tensorflow. The software was designed to run on single-board computer platforms as a detection unit. The system was trained to recognize 20 different materials in the ICU, while 100 sample images of each consumable material were provided. We assessed the top-1 recognition rates in the context of different real-world ICU settings: materials presented to the system without visual obstruction, 50% covered materials, and scenarios of multiple items. We further performed an analysis of variance with repeated measures to quantify the effect of adverse real-world circumstances.
Results: Consumabot reached a >99% reliability of recognition after about 60 steps of training and 150 steps of validation. A desirable low cross entropy of <0.03 was reached for the training set after about 100 iteration steps and after 170 steps for the validation set. The system showed a high top-1 mean recognition accuracy in a real-world scenario of 0.85 (SD 0.11) for objects presented to the system without visual obstruction. Recognition accuracy was lower, but still acceptable, in scenarios where the objects were 50% covered (P<.001; mean recognition accuracy 0.71; SD 0.13) or multiple objects of the target group were present (P=.01; mean recognition accuracy 0.78; SD 0.11), compared to a nonobstructed view. The approach met the criteria of absence of explicit labeling (eg, barcodes, radio frequency labeling) while maintaining a high standard for quality and hygiene with minimal consumption of resources (eg, cost, time, training, and computational power).
Conclusions: Using a convolutional neural network architecture, Consumabot consistently achieved good results in the classification of consumables and thus is a feasible way to recognize and register medical consumables directly to a hospital’s electronic health record. The system shows limitations when the materials are partially covered, therefore identifying characteristics of the consumables are not presented to the system. Further development of the assessment in different medical circumstances is needed.
Driven by decreasing PV and energy storage prices, increasing electricity costs and policy supports from Thai government (self-consumption era), rooftop PV and energy storage systems are going to be deployed in the country rapidly that may disrupt existing business models structure of Thai distribution utilities due to revenue erosion and lost earnings opportunities. The retail rates that directly affect ratepayers (non-solar customers) are expected to increase. This paper focuses on a framework for evaluating impacts of PV with and without energy storage systems on Thai distribution utilities and ratepayers by using cost-benefit analysis (CBA). Prior to calculation of cost/benefit components, changes in energy sales need to be addressed. Government policies for the support of PV generation will also help in accelerating the rooftop PV installation. Benefit components include avoided costs due to transmission losses and deferring distribution capacity with appropriate PV penetration level, while cost components consist of losses in revenue, program costs, integration costs and unrecovered fixed costs. It is necessary for Thailand to compare total costs and total benefits of rooftop PV and energy storage systems in order to adopt policy supports and mitigation approaches, such as business model innovation and regulatory reform, effectively.
A local non-restrictive ramp metering strategy PRO is introduced. It is based on the stochasticity of capacity. The ramp metering algorithm shows innovative features:
• upstream time shifted measurements for anticipation
• measurements are actuated every second
• up to three vehicles per green are allowed
Details of the theory of this strategy are described in the first part. At freeway B27 three ramp meters with the PRO algorithm were installed. In the second part, based on extensive detailed traffic and accident data the effects on traffic flow and safety are described. The impact is positive regarding vehicle speed, queue duration and length as well as capacity and traffic safety. The improvements of speeds, travel times and capacities are statistically significant. The ramp metering systems are highly cost effective.
Purpose: The well-to-wheel (WTW) methodology is widely used for policy support in road transport. It can be seen as a simplified life cycle assessment (LCA) that focuses on the energy consumption and CO2 emissions only for the fuel being consumed, ignoring other stages of a vehicle’s life cycle. WTW results are therefore different from LCA results. In order to close this gap, the authors propose a hybrid WTW+LCA methodology useful to assess the greenhouse gas (GHG) profiles of road vehicles.
Methods: The proposed method (hybrid WTW+LCA) keeps the main hypotheses of the WTW methodology, but integrates them with LCA data restricted to the global warming potential (GWP) occurring during the manufacturing of the battery pack. WTW data are used for the GHG intensity of the EU electric mix, after a consistency check with the main life cycle impact (LCI) sources available in literature.
Results and discussion: A numerical example is provided, comparing GHG emissions due to the use of a battery electric vehicle (BEV) with emissions from an internal combustion engine vehicle. This comparison is done both according to the WTW approach (namely the JEC WTW version 4) and the proposed hybrid WTW+LCA method. The GHG savings due to the use of BEVs calculated with the WTW-4 range between 44 and 56 %, while according to the hybrid method the savings are lower (31–46 %). This difference is due to the GWP which arises as a result of the manufacturing of the battery pack for the electric vehicles.
Conclusions: The WTW methodology used in policy support to quantify energy content and GHG emissions of fuels and powertrains can produce results closer to the LCA methodology by adopting a hybrid WTW+LCA approach. While evaluating GHG savings due to the use of BEVs, it is important that this method considers the GWP due to the manufacturing of the battery pack.
Numerous research methods have been developed to detect anomalies in the areas of security and risk analysis. In healthcare, there are numerous use cases where anomaly detection is relevant. For example, early detection of sepsis is one such use case. Early treatment of sepsis is cost effective and reduces the number of hospital days of patients in the ICU. There is no single procedure that is sufficient for sepsis diagnosis, and combinations of approaches are needed. Detecting anomalies in patient time series data could help speed the development of some decisions. However, our algorithm must be viewed as complementary to other approaches based on laboratory values and physician judgments. The focus of this work is to develop a hybrid method for detecting anomalies that occur, for example, in multidimensional medical signals, sensor signals, or other time series in business and nature. The novelty of our approach lies in the extension and combination of existing approaches: Statistics, Self Organizing Maps and Linear Discriminant Analysis in a unique and unprecedented way with the goal of identifying different types of anomalies in real-time measurement data and defining the point where the anomaly occurs. The proposed algorithm not only has the full potential to detect anomalies, but also to find real points where an anomaly starts.
With less than 6% of total global water resources but one fifth of the global population, China is facing serious challenges for its water resources management, particularly in rural areas due to the long-standing urban-rural dualistic structure and the economic-centralized developmental policies. This paper addresses the key water crises in rural China including potable water supply, wastewater treatment and disposal, water for agricultural purposes, and environmental concerns, and then analyzes the administrative system on water resources from the perspective of characteristics of the current administrative system and regulations; finally, synthetic approaches to solve water problems in rural China are proposed with regard to institutional reform, regulation revision, economic instruments, technology innovation and capacity-building. These recommendations provide valuable insights to water managers in rural China so that they can identify the most appropriate pathways for optimizing their water resources, reducing the total wastewater discharge and improving their water-related ecosystem.
Background: Improving movement control might be a promising treatment goal during chronic non-specific low back pain (CLBP) rehabilitation. The objective of the study is to evaluate the effect of a single bout of game-based real-time feedback intervention on trunk movement in patients with CLBP.
Methods: Thirteen CLBP patients (8female;41 ± 16 years;173 ± 10 cm;78 ± 22 kg) were included in this randomized cross-over pilot trial. During one laboratory session (2 h), participants performed three identical measurements on trunk movement all including: first, maximum angle of lateral flexion was assessed. Secondly, a target trunk lateral flexion (angle: 20°) was performed. Main outcome was maximum angle ([°]; MA). Secondary outcomes were deviation [°] from the target angle (angle reproduction; AR) and MA of the secondary movement planes (rotation; extension/flexion) during lateral flexion. The outcomes were assessed by an optical 3D-motion-capture-system (2-segment-trunk-model). The measurements were separated by 12-min of intervention and/or resting (randomly). The intervention involved a sensor-based trunk exergame (guiding an avatar through virtual worlds). After carryover effect-analysis, pre-to-post intervention data were pooled between the two sequences followed by analyses of variances (paired t-test).
Results: No significant change from pre to post intervention for MA or AR for any segment occurred for the main movement plane, lateral flexion (p > .05). The upper trunk segment showed a significant decrease of the MA for trunk extension/flexion from pre to post intervention ((4.4° ± 4.4° (95% CI 7.06–1.75)/3.5° ± 1.29° (95% CI 6.22–0.80); p = 0.02, d = 0.20).
Conclusions: A single bout of game-based real-time feedback intervention lead to changes in the secondary movement planes indicating reduced evasive motion during trunk movement.
Concerns over climate change, air pollution, and oil supply have stimulated the market for battery electric vehicles (BEVs). The environmental impacts of BEVs are typically evaluated through a standardized life-cycle assessment (LCA) methodology. Here, the LCA literature was surveyed with the objective to sketch the major trends and challenges in the impact assessment of BEVs. It was found that BEVs tend to be more energy efficient and less polluting than conventional cars. BEVs decrease exposure to air pollution as their impacts largely result from vehicle production and electricity generation outside of urban areas. The carbon footprint of BEVs, being highly sensitive to the carbon intensity of the electricity mix, may decrease in the nearby future through a shift to renewable energies and technology improvements in general. A minority of LCAs covers impact categories other than carbon footprint, revealing a mixed picture. Up to date little attention is paid so far in LCA to the efficiency advantage of BEVs in urban traffic, the gap between on-road and certified energy consumption, the local exposure to air pollutants and noise and the aging of emissions control technologies in conventional cars. Improvements of BEV components, directed charging, second-life reuse of vehicle batteries, as well as vehicle-to-home and vehicle-to-grid applications will significantly reduce the environmental impacts of BEVs in the future.
Purification of mRNA with oligo(dT)-functionalized magnetic particles involves a series of magnetic separations for buffer exchange and washing. Magnetic particles interact and agglomerate with each other when a magnetic field is applied, which can result in a decreased total surface area and thus a decreased yield of mRNA. In addition, agglomeration may also be caused by mRNA loading on the magnetic particles. Therefore, it is of interest how the individual steps of magnetic separation and subsequent redispersion in the buffers used affect the particle size distribution. The lysis/binding buffer is the most important buffer for the separation of mRNA from the multicomponent suspension of cell lysate. Therefore, monodisperse magnetic particles loaded with mRNA were dispersed in the lysis/binding buffer and in the reference system deionized water, and the particle size distributions were measured. A concentration-dependent agglomeration tendency was observed in deionized water. In contrast, no significant agglomeration was detected in the lysis/binding buffer. With regard to magnetic particle recycling, the influence of different storage and drying processes on particle size distribution was investigated. Agglomeration occurred in all process alternatives. For de-agglomeration, ultrasonic treatment was examined. It represents a suitable method for reproducible restoration of the original particle size distribution.
Unternehmen verlassen sich bei der Entwicklung von Software und Lösungen häufig auf das Know-How externer Dienstleister. Moderne Arbeits- und Kollaborationsformen verändern gleichzeitig die Entwicklung von Produkten und Dienstleistungen. Wie beeinflussen diese Trends die Zusammenarbeit und Kooperation zwischen Unternehmen und ihren externen agilen Dienstleistern? Ziel dieser wissenschaftlichen Arbeit ist es herauszufinden, welche Schritte unternehmen müssen, um agiles Arbeiten und die Zusammenarbeit mit externen Dienstleistern umzusetzen. Daher wurde anhand einer Fallstudie inklusive einer qualitativen Befragung herausgefunden und aufgezeigt, welche Maßnahmen und Handlungen Unternehmen ergreifen müssen, um das Ziel einer effektiven Umsetzung einer agilen Zusammenarbeit und Kooperation zu erreichen. Drei Kernthemen wurden identifiziert, auf deren Grundlage die Forschungsfragen zu den Maßnahmen beantwortet werden: Erstens, welche Möglichkeiten Unternehmen haben, ein internes agiles Setup zu implementieren, um mit agilen Dienstleistern auf Augenhöhe zusammenzuarbeiten. Zweitens, welche Vertragsvarianten die agile Zusammenarbeit unterstützen und verbessern können und drittens, welche agilen Techniken und Methoden in der agilen Zusammenarbeit eingesetzt werden sollten. Die Ergebnisse der Fallstudien bestätigen die Annahme, dass die drei identifizierten Kernthemen für eine effektive Zusammenarbeit im agilen Umfeld essenziell sind. Während einerseits nachgewiesen wurde, dass sich die Vertragsanforderungen hinsichtlich ihrer Flexibilität und Anpassungsfähigkeit veränderten, wurde andererseits auch nachgewiesen, dass das interne Setup agile Treiber, Techniken und Methoden erfordert, um eine effektive Zusammenarbeit mit agilen Dienstleistern zu ermöglichen. Dieser Artikel gibt einen Überblick über die wichtigsten Inhalte innerhalb der drei genannten Kernthemen und gibt Unternehmen zudem Hinweise, wie sie eine Basis für eine effektive Zusammenarbeit schaffen können.
Containerization is one of the most important topics for modern data centers and web developers. Since the number of containers on one- and multi-node systems is growing, knowledge about the energy consumption behavior of single web-service containers is essential in order to save energy and, of course, money. In this article, we are going to show how the energy consumption behavior of single containerized web services/web apps changes while creating replicas of the service in order to scale and balance the web service.
This paper analyzed the characteristic of the tourism destination ecosystem from perspective of entropy in Dunhuang City. Given these circumstances, an evaluation index system that considers the potential of sustainable development was formed based on dissipative structure and entropy change for the tourism destination ecosystem. The sustainable development potential evaluation model for tourism destination ecosystem was built up based on information entropy. Then, we analyzed each indicator impact for the sustainable development potential and proposed some measures for the tourism destination ecosystem. The conclusions include: (a) the requirements of Dunhuang tourism destination ecosystem on the natural ecosystem continuously grew between 2000 and 2012; (b) The sustainable development potential of the Dunhuang tourism destination ecosystem was on an oscillation upward trend during the study period, which is dependent on government attention, and pollution problems were improved.
Background: Deficiency in musculoskeletal imaging (MI) education will pose a great challenge to physiotherapists in clinical decision making in this era of first-contact physiotherapy practices in many developed and developing countries. This study evaluated the nature and the level of MI training received by physiotherapists who graduate from Nigerian universities.
Methods: An online version of the previously validated Physiotherapist Musculoskeletal Imaging Profiling Questionnaire (PMIPQ) was administered to all eligible physiotherapists identified through the database of the Medical Rehabilitation Therapist Board of Nigeria. Data were obtained on demographics, nature, and level of training on MI procedures using the PMIPQ. Logistic regression, Friedman’s analysis of variance (ANOVA) and Kruskal-Wallis tests were used for the statistical analysis of collected data.
Results: The results (n = 400) showed that only 10.0% of the respondents had a stand-alone entry-level course in MI, 92.8% did not have any MI placement during their clinical internship, and 67.3% had never attended a MI workshop. There was a significant difference in the level of training received across MI procedures [χ2 (15) = 1285.899; p = 0.001]. However, there was no significant difference in the level of MI training across institutions of entry-level programme (p = 0.36). The study participants with transitional Doctor of Physiotherapy education were better trained in MI than their counterparts with a bachelor’s degree only (p = 0.047).
Conclusions: Most physiotherapy programmes in Nigeria did not include a specific MI module; imaging instructions were mainly provided through clinical science courses. The overall self-reported level of MI training among the respondents was deficient. It is recommended that stand-alone MI education should be introduced in the early part of the entry-level physiotherapy curriculum.
One key for successful and fluent human-robot-collaboration in disassembly processes is equipping the robot system with higher autonomy and intelligence. In this paper, we present an informed software agent that controls the robot behavior to form an intelligent robot assistant for disassembly purposes. While the disassembly process first depends on the product structure, we inform the agent using a generic approach through product models. The product model is then transformed to a directed graph and used to build, share and define a coarse disassembly plan. To refine the workflow, we formulate "the problem of loosening a connection and the distribution of the work" as a search problem. The created detailed plan consists of a sequence of actions that are used to call, parametrize and execute robot programs for the fulfillment of the assistance. The aim of this research is to equip robot systems with knowledge and skills to allow them to be autonomous in the performance of their assistance to finally improve the ergonomics of disassembly workstations.
Global vernetzte Supply Chains (SC) führen bei den Unternehmen zu geringeren Kosten, aber zugleich erhöhen diese auch die Abhängigkeit ggü. den Lieferanten und die Störanfälligkeit der SCs wird erhöht. In den vergangenen Jahren haben zudem die Unsicherheiten für die SCs stark zugenommen. Treiber waren hier u.a. der Brexit, Handelskonflikte oder auch die Corona-Pandemie. In diesem Zusammenhang steht verstärkt die Entwicklung neuer SC-Strategien im Fokus der Unternehmen. Dabei wird stark auf die Verbesserung der Resilienz der SCs geachtet, um dadurch u.a. die Risiken für die SCs zu reduzieren. Die Arbeit beschäftigt sich mit den Auswirkungen steigender Unsicherheiten auf das Design sowie die Resilienz von SCs und hat das Ziel zu ermitteln, ob es Änderungen in der SC bedarf, um auf die Auswirkungen steigender Unsicherheiten zu reagieren und wie die Resilienz zukünftig sichergestellt werden kann (Trade-off zwischen Resilienz und Kosteneffizienz). Im Rahmen der Untersuchung erfolgte eine qualitative Forschung in Form von Experteninterviews, da so u.a. spezifische Meinungen oder auch Begründungen und Einstellungen von bestimmten Personen zu den vorliegenden Thematiken ermittelt werden können. Die Ergebnisse zeigen, dass die Kosten weiterhin meist der entscheidende Aspekt sind und es mehr Transparenz, Flexibilität sowie ein besseres Risikomanagement nötig ist. Des Weiteren bedarf es zukünftig u.a. einer größeren Berücksichtigung von Unsicherheiten, eine Erhöhung von Sicherheitsbeständen sowie eine Verringerung der Komplexität der SCs und u.U. mehr Local Sourcing. Es empfiehlt sich eine weitere Untersuchung hinsichtlich der Kosten, die durch Resilienz-Instrumente sowie durch fehlende Resilienz entstehen können, durchzuführen.
Der Automobilhandel befindet sich in einer momentanen Phase des Umbruchs. Der Trend zum Kauferlebnis online, verstärkt durch die Pandemie, und die durch die Dieselproblematik entfachte Diskussion zum Emissionsausstoß und Fahrverboten für Verbrennungsmotoren im Fahrzeugbereich, treibt den Wandel zu elektrischen Antriebstechnologien an. Durch diese Umstellung ergeben sich neue Möglichkeiten für das Fahrzeug im Bereich der Digitalisierung. Die branchenübergreifende Digitalisierung findet sich auch in den neuen Vertriebssystemen der Automobilhersteller wieder. Hierbei ist zudem eine Veränderung der Absatzkanäle zu beobachten. Der Kunde weicht beim Autokauf davon ab, exklusiv zu dem Händler seines Vertrauens zu gehen und sich hier durch den gesamten Verkaufsprozess hinweg betreuen zu lassen. Vielmehr verschieben sich einzelne Teilbereiche in das Internet. So müssen etablierte Prozesse neugestaltet werden, um weiterhin im Markt und im Wettbewerb bestehen zu können.
Das Ziel dieser Arbeit ist die Beantwortung zweier Forschungsfragen. Zum einen soll der Status-Quo der Digitalisierung von Vertriebsinstrumenten im Autohaus untersucht werden. Konkret geht es dabei um die Frage, in welcher Art und Weise die Digitalisierung den Vertrieb beeinflusst und welche Effekte sich daraus ergeben. Zum anderen stellt sich die Frage wie die Digitalisierung in Form des Internets, als Absatzkanal für die Automobilindustrie geeignet ist, und ob derart komplexe Produkte wie ein Neufahrzeug über diesen Kanal abgesetzt werden können. Weiterhin soll betrachtet werden, welche Veränderungen in den Vertriebsstrukturen das beim stationären Autohändler verursacht.
Die Arbeit befasst sich ausschließlich mit der Digitalisierung bei Vertragshändlern mit Volumenzielen im Neuwagen-Bereich. Damit sind die Luxus- oder Premiummarken ausgeschlossen. Außerdem wird im Autohaus in zwei Kundenkategorien unterschieden. Es gibt die Großabnehmer und die Einzelkunden. Die Großabnehmer sind Unternehmen, die durch eine vordefinierte Anzahl an Mindestabnahmen einen besonderen Status und Konditionen genießen. Die Einzelkunden sind private Abnehmer oder gewerbliche Kunden, die die Mindestabnahme nicht erreichen. Die Arbeit beschränkt sich ausschließlich auf die Analyse und Auswirkungen der Veränderungen im Segment der Einzelkunden.
Deep brain stimulation (DBS) is an established therapy for movement disorders such as in Parkinson's disease (PD) and essential tremor (ET). Adjusting the stimulation parameters, however, is a labour-intensive process and often requires several patient visits. Physicians prefer objective tools to improve (or maintain) the performance in DBS. Wearable motion sensors (WMS) are able to detect some manifestations of pathological signs, such as tremor in PD. However, the interpretation of sensor data is often highly technical and methods to visualise tremor data of patients undergoing DBS in a clinical setting are lacking. This work aims to visualise the dynamics of tremor responses to DBS parameter changes with WMS while patients performing clinical hand movements. To this end, we attended DBS programming sessions of two patients with the aim to visualise certain aspects of the clinical examination. PD tremor and ET were effectively quantified by acceleration amplitude and frequency. Tremor dynamics were analysed and visualised based on setpoints, movement transitions and stability aspects. These methods have not yet been employed and examples demonstrate how tremor dynamics can be visualised with simple analysis techniques. We therefore provide a base for future research work on visualisation tools in order to assist clinicians who frequently encounter patients for DBS therapy. This could lead to benefits in terms of enhanced evaluation of treatment efficacy in the future.
Abstract: This paper is about detecting the difference between fully-random and semi-random shuffleing data sets, with the use of unsupervised learning algorithms. Because of the limits of the k-means algorithm alone, a recurrent autoencoder is used for feature extraction to improve the results of k-means. In the next step the autoencoder alone is used for clustering.
Introduction: In the last years, machine learning has been used more and more in different areas and it is also appropriate for for pattern recognition in data. Random data is characterized through the missing of defined patterns. Permutations without repetitions have the highest amount of entropy for a sequence of its length, which is similar to random data according to Andrei Kolmogorov, who states that random data have the highest amount of information and can’t be compressed. Therefore, this paper analyses the difference between random permutations and good shuffled permutations, which have some remaining patterns left. This is done via a recurrent autoencoder.
The services sector is also called “tertiary sector” and has become increasingly important in the last few decades. The process of this structural change occurrence is characterized by a significant increase in employment in the services sector. On the other hand, the former economic importance in traditional areas, such as agriculture and forestry, as well as manufacturing, is declining. In this article the research field of the service sector is shown beginning from the 70s up to the present. The goal of the article is to demonstrate the necessity of service engineering research.
A study of industry 4.0 technologies in the John Deere and Company and their impact on company operations is presented in this paper. Deere and Company’s implementation of Industry 4.0 to its factories and its factors was the focus of the research. The literature review with the systematic approach as well as a comprehensive review of current John Deere and Company’s developments is used in the current study. Also, it relied on freely available information on the company website. Public and investor relations have also been used as credible sources of information. An analysis found that adopting industry 4.0 technologies to agriculture manufacturing results in higher quality products, increased productivity, safety, and wider acceptance among stakeholders. This study assumes full implementation of these technologies in all agriculture manufacturing companies, and it also emphasizes up-to-date technologies. Studying this topic can be useful for engineers in mechanical and agricultural fields, managers in business, and marketers.
E-commerce has been keeping fast increasing worldwide since beginning of the 21st century. Rapid growth of e-commerce & parcel shipping is a booming business. However, how to handle with many hard-to-solve sustainability issues of transport in urban areas, is becoming a serious challenge for urban logistic sector and numerous stakeholders. The sustainability issues contain the problems of air pollution, congestion, and sub-contractors. This paper reported those issues in the context of growth of e-commerce and analyzed their efforts on the sustainable urban logistics development.
The implementation of single-use technologies offers several major advantages, e.g. prevention of cross-contamination, especially when spore-forming microorganisms are present. This study investigated the application of a single-use bioreactor in batch fermentation of filamentous fungus Penicillium sp. (IBWF 040-09) from the Institute of Biotechnology and Drug Research (IBWF), which is capable of intracellular production of a protease inhibitor against parasitic proteases as a secondary metabolite. Several modifications to the SU bioreactor were suggested in this study to allow the fermentation in which the fungus forms pellets. Simultaneously, fermentations in conventional glass bioreactor were also conducted as reference. Although there are significant differences in the construction material and gassing system, the similarity of the two types of bioreactors in terms of fungal metabolic activity and the reproducibility of fermentations could be demonstrated using statistic methods. Under the selected cultivation conditions, growth rate, yield coefficient, substrate uptake rate, and formation of intracellular protease-inhibiting substance in the single-use bioreactor were similar to those in the glass bioreactor.
Artificial light at night (ALAN) is a widespread alteration of the natural environment that can affect the functioning of ecosystems. ALAN can change the movement patterns of freshwater animals that move into the adjacent riparian and terrestrial ecosystems, but the implications for local riparian consumers that rely on these subsidies are still unexplored. We conducted a 2-year field experiment to quantify changes of freshwater-terrestrial linkages by installing streetlights in a previously light-naïve riparian area adjacent to an agricultural drainage ditch. We compared the abundance and community composition of emerging aquatic insects, flying insects, and ground-dwelling arthropods with an unlit control site. Comparisons were made within and between years using two-way generalized least squares (GLS) model and a BACI design (Before-After Control-Impact). Aquatic insect emergence, the proportion of flying insects that were aquatic in origin, and the total abundance of flying insects all increased in the ALAN-illuminated area. The abundance of several night-active ground-dwelling predators (Pachygnatha clercki, Trochosa sp., Opiliones) increased under ALAN and their activity was extended into the day. Conversely, the abundance of nocturnal ground beetles (Carabidae) decreased under ALAN. The changes in composition of riparian predator and scavenger communities suggest that the increase in aquatic-to-terrestrial subsidy flux may cascade through the riparian food web. The work is among the first studies to experimentally manipulate ALAN using a large-scale field experiment, and provides evidence that ALAN can affect processes that link adjacent ecosystems. Given the large number of streetlights that are installed along shorelines of freshwater bodies throughout the globe, the effects could be widespread and represent an underestimated source of impairment for both aquatic and riparian systems.
Companies have made considerable progress in assessing the sustainability of their processes and products, including the information and communication technology (ICT) sector. However, it is surprising that little attention has been given to the sustainability performance of software products. For this article, we chose a case study approach to explore the extent, to which software manufacturers have considered sustainability criteria for their products. We selected a manufacturer of sustainability management software on the assumption that they would be more likely to integrate elements of sustainability performance in their products. In the case study, we applied a previously developed set of criteria for sustainable software (SCSS) using a questionnaire and experiments, to assess a web-based sustainability management software product regarding its sustainability performance. The assessment finds that despite a sustainability conscious manufacturer, a systematic assessment of sustainability regarding software products is missing in the case study. This implies that sustainability assessment for software products is still novel, corresponding knowledge is missing and suitable tools are not yet being widely applied in the industry. The SCSS presents a suitable approach to close this gap, but it does require further refinement, for example regarding its applicability to web-based software on external servers.
Automated evaluation of contact angles in a three-phase system of selective agglomeration in liquids
(2020)
This study aims to an automated evaluation of contact angles in a three-phase system of selective agglomeration in liquids. Wetting properties, quantified by contact angles, are essential in many industries and their processes. Selective agglomeration as a three-phase system consists of a suspension liquid, a heterogeneous solid phase and an immiscible binding liquid. It offers the chance of establishing more efficient separation processes because of the shape-dependent wetting properties of fine particles (size ≤ 10 µm). In the present paper, an experimental setup for contact angle measurements of fine particles based on the Sessile Drop Method is described. Moreover, a new algorithm is discussed, which can be used to automatically compute contact angles from image data captured by a high-speed camera. The algorithm uses a marker-based watershed transform to segment the image data into regions representing the droplet, the carrier plate coated by fine particles, and the background. The main idea is a parametric modelling approach forthe time-dependent droplet’s contour by an ellipse.
The results show that the development of the dynamic contact angles towards a static contact angle can be efficiently determined based on this novel technique. These findings are useful for a detailed discrimination of wetting properties of spherical and irregularly shaped particles as well as their wetting kinetics. Also, a better understanding of selective agglomeration processes will be promoted by this user-friendly method.
In der seit 2009 andauernden Niedrigzinsphase ging der Anteil der Kapitaleinkommen am Volkseinkommen zurück. Da sich der Anteil des Faktors Arbeit nicht wesentlich veränderte, gewann der Produktionsfaktor Boden an Bedeutung. In der Volkswirtschaftlichen Gesamtrechnung spiegelt sich dies jedoch nicht wider, da der Boden dort nicht gesondert ausgewiesen wird. Mithilfe des Henry-George-Theorems wird versucht, eine Methode zu entwickeln, die den Anteil des Faktors Boden quantifiziert. Der explizite Ausweis des Bodeneinkommens in der Volkswirtschaftlichen Gesamtrechnung könnte dazu beitragen, die Rolle dieses vernachlässigten Faktors zu korrigieren.
Universities, as innovation drivers in science and technology worldwide, should attempt to become carbon-neutral institutions and should lead this transformation. Many universities have picked up the challenge and quantified their carbon footprints; however, up-to-date quantification is limited to use-phase emissions. So far, data on embodied impacts of university campus infrastructure are missing, which prevents us from evaluating their life cycle costs. In this paper, we quantify the embodied impacts of two university campuses of very different sizes and climate zones: the Umwelt-Campus Birkenfeld (UCB), Germany, and the Nanyang Technological University (NTU), Singapore. We also quantify the effects of switching to full renewable energy supply on the carbon footprint of a university campus based on the example of UCB. The embodied impacts amount to 13.7 (UCB) and 26.2 (NTU) kg CO2e/m2•y, respectively, equivalent to 59.2% (UCB), and 29.8% (NTU), respectively, of the building lifecycle impacts. As a consequence, embodied impacts can be dominating; thus, they should be quantified and reported. When adding additional use-phase impacts caused by the universities on top of the building lifecycle impacts (e.g., mobility impacts), both institutions happen to exhibit very similar emissions with 124.5–126.3 kg CO2e/m2•y despite their different sizes, structures, and locations. Embodied impacts comprise 11.0–20.8% of the total impacts at the two universities. In conclusion, efficient reduction in university carbon footprints requires a holistic approach, considering all impacts caused on and by a campus including upstream effects.
Carbon footprinting of universities worldwide: Part I — objective comparison by standardized metrics
(2021)
Background: Universities, as innovation drivers in science and technology worldwide, should be leading the Great Transformation towards a carbon–neutral society and many have indeed picked up the challenge. However, only a small number of universities worldwide are collecting and publishing their carbon footprints, and some of them have defined zero emission targets. Unfortunately, there is limited consistency between the reported carbon footprints (CFs) because of different analysis methods, different impact measures, and different target definitions by the respective universities.
Results: Comprehensive CF data of 20 universities from around the globe were collected and analysed. Essential factors contributing to the university CF were identified. For the first time, CF data from universities were not only compared. The CF data were also evaluated, partly corrected, and augmented by missing contributions, to improve the consistency and comparability. The CF performance of each university in the respective year is thus homogenized, and measured by means of two metrics: CO2e emissions per capita and per m2 of constructed area. Both metrics vary by one order of magnitude across the different universities in this study. However, we identified ten universities reaching a per capita carbon footprint of lower than or close to 1.0 Mt (metric tons) CO2e/person and year (normalized by the number of people associated with the university), independent from the university’s size. In addition to the aforementioned two metrics, we suggested a new metric expressing the economic efficiency in terms of the CF per $ expenditures and year. We next aggregated the results for all three impact measures, arriving at an overall carbon performance for the respective universities, which we found to be independent of geographical latitude. Instead the per capita measure correlates with the national per capita CFs, and it reaches on average 23% of the national impacts per capita. The three top performing universities are located in Switzerland, Chile, and Germany.
Conclusion: The usual reporting of CO2 emissions is categorized into Scopes 1–3 following the GHG Protocol Corporate Accounting Standard which makes comparison across universities challenging. In this study, we attempted to standardize the CF metrics, allowing us to objectively compare the CF at several universities. From this study, we observed that, almost 30 years after the Earth Summit in Rio de Janeiro (1992), the results are still limited. Only one zero emission university was identified, and hence, the transformation should speed up globally.
Following a quantitative analysis of adequate feedstock, comprising 11 woody biomass species, four biochars were generated using a Kon-Tiki flame curtain kiln in the state of Aguascalientes, Mexico. Despite the high quality (certified by European Biochar Certificate), the biochars contain substantial quantities of hazardous substances, such as polycyclic aromatic hydrocarbons, polychlorinated dibenzo-p-dioxins and dibenzofurans, polychlorinated biphenyls, and heavy metals, which can induce adverse effects if wrongly applied to the environment. To assess the toxicity of biochars to non-target organisms, toxicity tests with four benthic and zooplanktonic invertebrate species, the ciliate Paramecium caudatum, the rotifer Lecane quadridentata, and the cladocerans Daphnia magna and Moina macrocopa were performed using biochar elutriates. In acute and chronic toxicity tests, no acute toxic effect to ciliates, but significant lethality to rotifers and cladocerans was detected. This lethal toxicity might be due to ingestion/digestion by enzymatic/mechanic processes of biochar by cladocerans and rotifers of toxic substances present in the biochar. No chronic toxicity was found where biochar elutriates were mixed with soil. These data indicate that it is instrumental to use toxicity tests to assess biochars’ toxicity to the environment, especially when applied close to sensitive habitats, and to stick closely to the quantitative set-point values.
The data presented here contain information on cheating behavior from experiments and general self-reported attitudes related to honesty-related social norms and trust, together with individual-level demographic variables. Our sample included 493 university students in five countries, namely, Germany, Vietnam, Taiwan, China, and Japan. The experiment was monetarily incentivized based on the performance on a matrix task. The participants also answered a survey questionnaire. The dataset is valuable for academic researchers in sociology, psychology, and economics who are interested in honesty, norms, and cultural differences.
Purpose: Grounded in the theoretical concepts of utilitarianism and deontology, this paper aims to evaluate the issue of child labour from an ethics perspective. By linking utilitarianism with normative stakeholder theory, relevant stakeholder groups are being identified in order to examine their influence on and role in the occurrence of child labour allowing for a practical reference. The findings may serve companies in particular as a basis for decision-making in the development of their value chains.
Design/Methodology/Approach: The author uses a literature review in order to analyze the findings of existing literature on the topic of child labour in an ethics context, thereby drawing on literature, indexed in Web of Science and Google Scholar by employing forward and backward citation analysis.
Findings: The investigation of child labour in terms of ethics yields conflicting results. From a deontological perspective, child labour can never be ethical and should always be rejected as it is not wanted to become a general law. In contrast, according to a utilitarian sentiment, child labour is ethically justifiable as long as the beneficiaries of the labour are greater in number than the children working or suffering.
Originality/Value: The examination of child labour from the perspective of deontology and utilitarianism in conjunction with normative stakeholder theory constitutes a novelty in the ethics literature. The integration of theoretical findings into a practical business context provides additional value for managers and global supply chain managers.
A comprehensive overview is provided evaluating direct real-world CO2 emissions of both diesel and petrol cars newly registered in Europe between 1995 and 2015. Before 2011, European diesel cars emitted less CO2 per kilometre than petrol cars, but since then there is no appreciable difference in per-km CO2 emissions between diesel and petrol cars. Real-world CO2 emissions of diesel cars have not declined appreciably since 2001, while the CO2 emissions of petrol cars have been stagnant since 2012. When adding black carbon related CO2-equivalents, such as from diesel cars without particulate filters, diesel cars were discovered to have had much higher climate relevant emissions until the year 2001 when compared to petrol cars. From 2001 to 2015 CO2-equivalent emissions from new diesel cars and petrol cars were hardly distinguishable. Lifetime use phase CO2-equivalent emissions of all European passenger vehicles were modelled for 1995–2015 based on three scenarios: the historic case, another scenario freezing percentages of diesel cars at the low levels from the early 1990s (thus avoiding the observed “boom” in new diesel registrations), and an advanced mitigation scenario based on high proportions of petrol hybrid cars and cars burning gaseous fuels. The difference in CO2-equivalent emissions between the historical case and the scenario avoiding the diesel car boom is only 0.4%. The advanced mitigation scenario would have been able to achieve a 3.4% reduction in total CO2-equivalent emissions over the same time frame. The European diesel car boom appears to have been ineffective at reducing climate-warming emissions from the European transport sector.
Decoding the cellular network interaction of neurons and glial cells are important in the development of new therapies for diseases of the central nervous system (CNS). Electrophysiological in vivo studies in mice will help to understand the highly complex network. In this paper, the optimization of epidural liquid crystal polymer (LCP) electrodes for different platinum electroplating parameters are presented and compared. Constant current and pulsed current electroplating varied in strength and duration was used to decrease the electrode impedance and to increase the charge storage capacity (CSCc). In best cases, both methods generated similar results with an impedance reduction of about 99%. However, electroplating with pulsed currents was less parameter-dependent than the electroplating with constant current. The use of ultrasound was essential to generate platinum coatings without plating defects. Electrode model parameters extracted from the electrode impedance reflected the increase in surface porosity due to the electroplating processes.
Objective: The objective of the article highlight the significance of culture in the entrepreneurial landscape and provides entrepreneurs and (project) managers with a guidance tool to overcome previously unconsidered stumbling blocks while operating in the intercultural setting.
Research Design & Methods: The following article was prepared based on a critical study review devoted to existing approaches to intercultural impact in business life and used the archival technique from 1990-2020. The study review reflects on the identification of existing literature gaps in the implementation of a subcultural business environment. It addresses these by designing an appropriate model to bypass the apparent pitfalls of intercultural business communication and co-existence, if possible.
Findings: Culture impacts diverse sets of society and businesses, including entrepreneurship. This article underpins which pitfalls are advisable to consider when encountering the intercultural and entrepreneurship-driven workplace.
Implications & Recommendations: Based on the study review, startups, as well as big corporate companies’ projects of a creational nature, are advised to reconsider their perception and handling of culture applying The Building of Cultural and Entrepreneurial Force.
Contribution & Value Added: The added value of this article is to be found in the solid analysis of cultural essentialism, anti-essentialism, and implications to beware of in the managerial and entrepreneurial context related to The Building of Intercultural and Entrepreneurial Force that intends to ease to co-work of intercultural teams.
The increasing availability of off-the-shelf high-frequency components makes radar measurement become popular in mainstream industrial applications. We present a cooperative FM radar for strongly reflective environments, being devised for a range of up to approx. 120 m. The target is designed with an unambiguous signature method and satisfies coherence. A prototype is built with commercial semiconductor components that operates in the 24 GHz industrial, scientific and medical band. First experimental results taken in sewage pipes are presented, using the target prototype and a standard FMCW radio station. An overview on four data acquisition procedures is given.
Driven by falling photovoltaic (PV) installation costs and potential support policies, rooftop PV is expected to expand rapidly in Thailand. As a result, the relevant stakeholders, especially utilities, have concerns about the net economic impacts of high PV adoption. Using a cost–benefit analysis, this study quantifies the net economic impacts of rooftop PV systems on three utilities and on ratepayers in Thailand by applying nine different PV adoption scenarios with various buyback rates and annual percentages of PV cost reduction. Under Thailand’s current electricity tariff structure, Thai utilities are well-protected and able to pass all costs due to PV onto the ratepayers in terms of changes in retail rates. We find that when PV adoption is low, the net economic impacts on both the utilities and retail rates are small and the impacts on each utility depend on its specific characteristics. On the other hand, when PV adoption ranges from 9–14% in energy basis, five-year retail rate impacts become noticeable and are between 6% and 11% as compared to the projected retail rates in 2036 depending on the PV adoption level. Thus, it is necessary for Thailand to make tradeoffs among the stakeholders and maximize the benefits of rooftop PV adoption.
Background: On the way to a more sustainable society, transport needs to be urgently optimized regarding energy consumption and pollution control. While in earlier decades, Europe followed automobile technology leaps initiated in the USA, it has decoupled itself for 20 years by focusing research capacity towards the diesel powertrain. The resulting technology shift has led to some 45 million extra diesel cars in Europe. Its outcome in terms of health and environmental effects will be investigated below.
Results: Expected greenhouse gas savings initiated by the shift to diesel cars have been overestimated. Only about one tenth of overall energy efficiency improvements of passenger cars can be attributed to it. These minor savings are on the other hand overcompensated by a significant increase of supply chain CO2 emissions and extensive black carbon emissions of diesel cars without particulate filter. We conclude that the European diesel car boom did not cool down the atmosphere. Moreover, toxic NO x emissions of diesel cars have been underestimated up to 20-fold in officially announced data. The voluntary agreement signed in 1998 between the European Automobile industry and the European Commission envisaging to reduce CO2 emissions has been identified as elementary for the ensuing European diesel car boom. Four factors have been quantified in order to explain very different dieselization rates across Europe: impact of national car/supplier industry, ecological modernization, fuel tourism and corporatist political governance. By comparing the European diesel strategy to the Japanese petrol-hybrid avenue, it becomes clear that a different road would have both more effectively reduced CO2 emissions and pollutants.
Conclusion: Europe's car fleets have been persistently transformed from being petrol-driven to diesel-driven over the last 20 years. This paper investigates on how this came to be and why Europe took a distinct route as compared to other parts of the world. It also attempts to evaluate the outcome of stated goals of this transformation which was primarily a robust reduction in GHG emissions. We conclude that global warming has been negatively affected, and air pollution has become alarming in many European locations. More progressive development scenarios could have prevented these outcomes.
Cryotropic gelation is one of the most common approaches to design novel hydrogels with multifaceted technological and biological functionalities. In the present paper, we studied the ability of highly galactosyl-substituted galactomannans, i.e. fenugreek and alfalfa gum, to form physically crosslinked hydrogels via cryogenic processing. Cycling of the galactomannan solutions (0.25 to 4% wt) from 25 to −20 to 25 °C induced the physical crosslinking of the galactomannan chains leading to the formation of different cryogel structures, i.e. filamentous aggregates (c* < c < 1%), cellular-like gel networks (1 ≤ c < 4%) or a homogeneously swollen gel (c ≥ 4%), depending on the total biopolymer content. Alfalfa gum-based cryogels exhibited higher elasticity and stiffness, better uniformity of the structure and a lower macropore size than their fenugreek counterparts. The physical blending of alfalfa or fenugreek gum with locust bean gum (2% total biopolymer) led to the reinforcement of the mechanical properties of the cryogels without significantly altering their microstructural aspects.
Thailand’s power system has been facing an energy transition due to the increasing amount of Renewable Energy (RE) integration, prosumers with self-consumption, and digitalization-based business models in a Local Energy Market (LEM). This paper introduces a decentralized business model and a possible trading platform for electricity trading in Thailand’s Micro-Grid to deal with the power system transformation. This approach is Hybrid P2P, a market structure in which sellers and buyers negotiate on energy exchanging by themselves called Fully P2P trading or through the algorithm on the market platform called Community-based trading. A combination of Auction Mechanism (AM), Bill Sharing (BS), and Traditional Mechanism (TM) is the decentralized price mechanism proposed for the Community-based trading. The approach is validated through a test case in which, during the daytime, the energy import and export of the community are significantly reduced when 75 consumers and 25 PV rooftop prosumers participate in this decentralized trading model. Furthermore, a comparison analysis confirms that the decentralized business model outperforms a centralized approach on community and individual levels.
Gait analysis is a systematic study of human movement. Combining wearable foot pressure sensors and machine learning (ML) solutions for a high-fidelity body pose tracking from RGB video frames could reveal more insights into gait abnormalities. However, accurate detection of heel strike (HS) and toe-off (TO) events is crucial to compute interpretable gait parameters. In this work, we present an experimental platform to study the timing of gait events using a new wearable foot pressure sensor (ActiSense System, IEE S.A., Luxembourg), and Google’s open-source ML solution MediaPipe Pose. For this purpose, two StereoPi systems were built to capture stereoscopic videos and images in real time. MediaPipe Pose was applied to the synchronized StereoPi cameras, and two algorithms (ALs) were developed to detect HS and TO events for gait and analysis. Preliminary results from a healthy subject walking on a treadmill show a mean relative deviation across all time spans of less than 4% for the ActiSense device and less than 16% for AL2 (33% for AL1) employing MediaPipe Pose on StereoPi videos. Finally, this work offers a platform for the development of sensor- and video-based ALs to automatically identify the timing of gait events in healthy individuals and those with gait disorders.
In relation to the fast development of e-commerce and rapid increasing of parcels, urban logistic sector is facing the challenge of sustainability. Especially, last-mile delivery as the last step of goods transport, it connects to customers’ satisfaction, cost efficiency of logistic companies, and more and more public expectations to sustainability of urban logistics. To handle with the complexity of urban logistics conditions, governments and logistics companies should develop a co-operating strategy for sustainability of urban last-mile delivery. This paper is based on data collection from the long-term empirical research and a survey to the e-commerce users in Germany and China to develop a sustainable concept for the urban last-mile delivery. The key to the development of concept is to create a balance among the requirements of customers, the competition abilities of logistics companies and the public interest.
With a radar working in the 24 GHz ISM-band in a frequency modulated continuous wave mode the major vital signs heartbeat and respiration rate are monitored. The observation is hereby contactless with the patient sitting straight up in a distance of 1–2 m to the radar. Radar and sampling platform are components developed internally in the university institution. The communication with the radar is handled with MATLAB via TCP/IP. The signal processing and real-time visualization is developed in MATLAB, too. Cornerstone of this publication are the wavelet packet transformation and a spectral frequency estimation for vital sign calculation. The wavelet transformation allows a fine tuning of frequency subspaces, separating the heartbeat signal from the respiration and more important from noise and other movement. Heartbeat and respiration are monitored independently and compared to parallel recorded ECG-data.
Background: Stratified care approach involving use of the STarT-Back tool to optimise care for patients with low back pain is gaining widespread attention in western countries. However, adoption and implementation of this approach in low-and-middle-income countries will be restricted by context-specific factors that need to be addressed. This study aimed to develop with physiotherapists, tailored intervention strategies for the implementation of stratified care for patients with low back pain.
Methods: A two-round web-based Delphi survey was conducted among purposively sampled physiotherapists with a minimum of three years of clinical experience, with post-graduation certification or specialists. Thirty statements on barriers and enablers for implementation were extracted from the qualitative phase. Statements were rated by a Delphi panel with additional open-ended feedback. After each Delphi round, participants received feedback which informed their subsequent responses. Additional qualitative feedback were analysed using qualitative content analysis. The criteria for consensus and stability were pre-determined using percentage agreement (≥ 75%), median value (≥ 4), Inter-quartile range (≤ 1), and Wilcoxon matched-pairs test respectively.
Results: Participants in the first round were 139 and 125 of them completed the study, yielding a response rate of 90%. Participants were aged 35.2 (SD6.6) years, and 55 (39.6%) were female. Consensus was achieved in 25/30 statements. Wilcoxon’s test showed stability in responses after the 5 statements failed to reach consensus: ‘translate the STarT-Back Tool to pidgin language’ 71% (p = 0.76), ‘begin implementation with government hospitals’ 63% (p = 0.11), ‘share knowledge with traditional bone setters’ 35% (p = 0.67), ‘get second opinion on clinician’s advice’ 63% (p = 0.24) and ‘carry out online consultations’ 65% (p = 0.41). Four statements strengthened by additional qualitative data achieved the highest consensus: ‘patient education’ (96%), ‘quality improvement appraisals’ (96%), ‘undergraduate training on psychosocial care’ (96%) and ‘patient-clinician communication’ (95%).
Conclusion: There was concordance of opinion that patients should be educated to correct misplaced expectations and proper time for communication is vital to implementation. This communication should be learned at undergraduate level, and for already qualified clinicians, quality improvement appraisals are key to sustained and effective care. These recommendations provide a framework for future research on monitored implementation of stratified care in middle-income countries.
Many SMEs still face a problematic fact that their corporate structures and processes are not designed for efficient development and market positioning and there is a lack of appropriate methods and tools. SMEs are often inefficiently targeted to the internal or external demands for services. The goal of the research regarding contents and methodology was to investigate the practice of strategic planning and the implementation and application of service engineering in young SMEs on the one hand, and on the other hand specifically for young SMEs, whose performance and the probability of success can be increased by its application. These two goals have been achieved.
The aim of this work was to develop and evaluate the reinforcement learning algorithm VentAI, which is able to suggest a dynamically optimized mechanical ventilation regime for critically-ill patients. We built, validated and tested its performance on 11,943 events of volume-controlled mechanical ventilation derived from 61,532 distinct ICU admissions and tested it on an independent, secondary dataset (200,859 ICU stays; 25,086 mechanical ventilation events). A patient “data fingerprint” of 44 features was extracted as multidimensional time series in 4-hour time steps. We used a Markov decision process, including a reward system and a Q-learning approach, to find the optimized settings for positive end-expiratory pressure (PEEP), fraction of inspired oxygen (FiO2) and ideal body weight-adjusted tidal volume (Vt). The observed outcome was in-hospital or 90-day mortality. VentAI reached a significantly increased estimated performance return of 83.3 (primary dataset) and 84.1 (secondary dataset) compared to physicians’ standard clinical care (51.1). The number of recommended action changes per mechanically ventilated patient constantly exceeded those of the clinicians. VentAI chose 202.9% more frequently ventilation regimes with lower Vt (5–7.5 mL/kg), but 50.8% less for regimes with higher Vt (7.5–10 mL/kg). VentAI recommended 29.3% more frequently PEEP levels of 5–7 cm H2O and 53.6% more frequently PEEP levels of 7–9 cmH2O. VentAI avoided high (>55%) FiO2 values (59.8% decrease), while preferring the range of 50–55% (140.3% increase). In conclusion, VentAI provides reproducible high performance by dynamically choosing an optimized, individualized ventilation strategy and thus might be of benefit for critically ill patients.
Laboratory protocols using magnetic beads have gained importance in the purification of mRNA for vaccines. Here, the produced mRNA hybridizes specifically to oligo(dT)-functionalized magnetic beads after cell lysis. The mRNA-loaded magnetic beads can be selectively separated using a magnet. Subsequently, impurities are removed by washing steps and the mRNA is eluted. Magnetic separation is utilized in each step, using different buffers such as the lysis/binding buffer. To reduce the time required for purification of larger amounts of mRNA vaccine for clinical trials, high-gradient magnetic separation (HGMS) is suitable. Thereby, magnetic beads are selectively retained in a flow-through separation chamber. To meet the requirements of biopharmaceutical production, a disposable HGMS separation chamber with a certified material (United States Pharmacopeia Class VI) was developed which can be manufactured using 3D printing. Due to the special design, the filter matrix itself is not in contact with the product. The separation chamber was tested with suspensions of oligo(dT)-functionalized Dynabeads MyOne loaded with synthetic mRNA. At a concentration of cB = 1.6–2.1 g·L–1 in lysis/binding buffer, these 1 μm magnetic particles are retained to more than 99.39% at volumetric flows of up to 150 mL·min–1 with the developed SU-HGMS separation chamber. When using the separation chamber with volumetric flow rates below 50 mL·min–1, the retained particle mass is even more than 99.99%.
In 2019 at IBM, it was found that there is a strong dependence on a few large banks in bank sales, and the growth targets of the sales division cannot be achieved due to the existing business with these same customers. To counteract this dependency, an NCA-specific sales team for the banking industry was established to support small and medium-sized banks with personal commitment and expertise and to develop them into long-term business partners of IBM. This research focuses on the development of a performance measurement system for NCA-Sales teams. It postulates the hypothesis that more effective and better-suited performance measurement systems can be developed for NCA-Sales of information technology towards financial institutions. Authors use the methodology of expert interviews and Mayrings qualitative content analysis to gain insights into the relevant factors that need to be considered when evaluating the performance of such sales teams. The paper identifies stakeholders, challenges, and goals that should be integrated into a performance measurement system as well as KPIs to measure them. The results are being consolidated into a conceptual sketch for an NCA-sales optimized PMS. The paper distinguishes itself from other research through an approach that gives detailed guidance for the practical implementation of its findings. The research was conducted with professionals in the IT sector; however, all of them were working for the same company, and the data was collected in the short span of one week as it was part of a research. The outcome can be used for further studies on how to effectively measure performance in NCA-Sales teams.
Die vorliegende Ausarbeitung beschäftigt sich mit der Frage, ob weibliche Führungskräfte aufgrund spezieller Führungskompetenzen auf den langfristigen Unternehmenserfolg einzahlen. Besondere Beachtung findet hierbei der Faktor der Emotionalen Intelligenz. Nach wie vor ist der Anteil weiblicher Führungskräfte auf deutschen Managementebenen auffallend gering. Um ein Verständnis für die Hintergründe dieser Thematik zu entwickeln, werden zunächst die Ursachen geschlechtsbedingter Differenzierungen erläutert. Die wesentlichen Erkenntnisse entstammen dem Bereich der Geschlechterforschung. Im Anschluss werden diese im Kontext der Führung beleuchtet. Ein besonderes Augenmerk liegt auf der Frage, ob und inwiefern sich ein potentieller weiblicher Führungsstil von der als männlich geltenden Führung unterscheidet. Im weiteren Verlauf des Artikels wird das Phänomen der Emotionalen Intelligenz im Detail betrachtet. Dieses gilt im Kontext der Führung seit geraumer Zeit als Erfolgsfaktor. Ob und inwiefern diese Annahme tatsächlich Bestand hat, soll daher zunächst herausgestellt werden. Abschließend wird geprüft, ob es sich bei der Emotionalen Intelligenz um eine vorwiegend weibliche Kompetenz handelt
Sowohl der stationäre Handel als auch die Online Pure Player befinden sich durch die zunehmende Digitalisierung und die Beeinflussung durch die dynamisch veränderten Trends in einem Wandel. Insbesondere wird von der Möbelbranche ein adaptives Verhalten an die vorliegenden Entwicklungen verlangt. Durch die Intensivierung der Markt- und Wettbewerbslandschaften und die Veränderungen des Verbraucherverhaltens bezüglich der verlangten Verschmelzung der Einkaufskanäle wird ein Umdenken gefordert und notwendig. Zusätzlich wird diese Notwendigkeit durch aktuelle Gegebenheiten, wie die Covid-19-Pandemie dringlicher. Die Omnichannel-Strategie und deren Etablierung birgt für die Möbelbranche insbesondere hinsichtlich der logistischen Herausforderungen Gelegenheiten und Bedrohungen. Diese sind zu erkennen, zu nutzen und zu beheben.