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Local biodiversity trends over time are likely to be decoupled from global trends, as local processes may compensate or counteract global change. We analyze 161 long-term biological time series (15–91 years) collected across Europe, using a comprehensive dataset comprising ~6,200 marine, freshwater and terrestrial taxa. We test whether (i) local long-term biodiversity trends are consistent among biogeoregions, realms and taxonomic groups, and (ii) changes in biodiversity correlate with regional climate and local conditions. Our results reveal that local trends of abundance, richness and diversity differ among biogeoregions, realms and taxonomic groups, demonstrating that biodiversity changes at local scale are often complex and cannot be easily generalized. However, we find increases in richness and abundance with increasing temperature and naturalness as well as a clear spatial pattern in changes in community composition (i.e. temporal taxonomic turnover) in most biogeoregions of Northern and Eastern Europe.
Since tangible assets of companies are becoming increasingly insignificant, emphasis should rather be placed on human capital as an essential source of competitive edge. This paper, accordingly, pursues the purpose to shed light on the major demands that the Millenials place on their prospective employers. In consequence, the work aims to identify attractiveness factors that German retailers should particularly promote in order to succeed in the war for talents and attract the most promising candidates among the German Gen Y. This work is based on a mixed-methods approach. First, interviews with German retail experts as well as generational keynote speakers were conducted in order to obtain a deep understanding and assessment of the German retail landscape from a professional perspective. The insights gained were subsequently used to design a questionnaire, which distribution led to a final sample of 216 useable responses by Millenials. Furthermore, the data obtained by interviewing experts and the survey was subsequently compared in order to evaluate to what extent the expectations of the Millenials correspond to the experts’ assessment. This study reveals Millenials to be driven by the need for growth, such as wide offers of development opportunities or scope for decision when choosing an employer. Among the relatedness needs, a harmonious working environment is particularly important, whereas a weekend off ranks first among the existential needs. Moreover, male Millenials consider Media Markt being the most popular employer in the German retail sector, while dm is preferred from a female perspective. Overall, employers of the German retail sector provide the majority of factors required by the Millenials, yet are only considered the 4th most popular industry behind the automotive, IT, art and entertainment industries. Our findings provide valuable practical implications as the research results might serve companies to build up a target group specific employer brand. Marketing strategies can be aligned with the identified attractiveness factors to efficiently and cost-effectively attract and bind Millenials to the company. Customized recruiting campaigns enhance the appeal as well as the attractiveness of an employer driving the likelihood of obtaining the strived status: Employer of Choice. To the best of the author’s knowledge, no study has yet dealt specifically with the attractiveness factors demanded by the Millenials in the context of the German retail sector as well as their most aspired employers in this industry. Furthermore, the attractiveness factors identified in the literature were embedded in Aldefer’s ERG theory. This work also offers a bilateral perspective through the widely conducted survey carried out among Millenials, which was additionally expanded through the lens of experts.
Electrical stimulation is used for example to treat neuronal disorders and depression with deep brain stimulation or transcranial electrical stimulation. Depending on the application, different electrodes are used and thus different electrical characteristics exist, which have to be handled by the stimulator. Without a measuring device the user would have to rely on the stimulator being able to deliver the needed stimulation signal. Therefore, the objective of this paper is to present a method to increase the level of confidence with characterization and modelling of the electrical behavior by using the example of one channel of our stimulation device for experimental use. In several simulation studies with an electrode model with values in a typical range for cortical applications the influence of the load onto the stimulator and the possibility to pre-estimate measuring signals in complex networks are shown.
Multimodal meaning making: The annotation of nonverbal elements in multimodal corpus transcription
(2021)
The article discusses how to integrate annotation for nonverbal elements (NVE) from multimodal raw data as part of a standardized corpus transcription. We argue that it is essential to include multimodal elements when investigating conversational data, and that in order to integrate these elements, a structured approach to complex multimodal data is needed. We discuss how to formulate a structured corpus-suitable standard syntax and taxonomy for nonverbal features such as gesture, facial expressions, and physical stance, and how to integrate it in a corpus. Using corpus examples, the article describes the development of a robust annotation system for spoken language in the corpus of Video-mediated English as a Lingua Franca Conversations (ViMELF 2018) and illustrates how the system can be used for the study of spoken discourse. The system takes into account previous research on multimodality, transcribes salient nonverbal features in a concise manner, and uses a standard syntax. While such an approach introduces a degree of subjectivity through the criteria of salience and conciseness, the system also offers considerable advantages: it is versatile and adaptable, flexible enough to work with a wide range of multimodal data, and it allows both quantitative and qualitative research on the pragmatics of interaction.
The current work investigates the capability of a tailored multivariate curve resolution–alternating least squares (MCR-ALS) algorithm to analyse glucose, phosphate, ammonium and acetate dynamics simultaneously in an E. coli BL21 fed-batch fermentation. The high-cell-density (HCDC) process is monitored by ex situ online attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy and several in situ online process sensors. This approach efficiently utilises automatically generated process data to reduce the time and cost consuming reference measurement effort for multivariate calibration. To determine metabolite concentrations with accuracies between ±0.19 and ±0.96·gL−l, the presented utilisation needs primarily — besides online sensor measurements — single FTIR measurements for each of the components of interest. The ambiguities in alternating least squares solutions for concentration estimation are reduced by the insertion of analytical process knowledge primarily in the form of elementary carbon mass balances. Thus, in this way, the established idea of mass balance constraints in MCR combines with the consistency check of measured data by carbon balances, as commonly applied in bioprocess engineering. The constraints are calculated based on online process data and theoretical assumptions. This increased calculation effort is able to replace, to a large extent, the need for manually conducted quantitative chemical analysis, leads to good estimations of concentration profiles and a better process understanding.
Background: Recent shoulder injury prevention programs have utilized resistance exercises combined with different forms of instability, with the goal of eliciting functional adaptations and thereby reducing the risk of injury. However, it is still unknown how an unstable weight mass (UWM) affects the muscular activity of the shoulder stabilizers. Aim of the study was to assess neuromuscular activity of dynamic shoulder stabilizers under four conditions of stable and UWM during three shoulder exercises. It was hypothesized that a combined condition of weight with UWM would elicit greater activation due to the increased stabilization demand.
Methods: Sixteen participants (7 m/9 f) were included in this cross-sectional study and prepared with an EMG-setup for the: Mm. upper/lower trapezius (U.TA/L.TA), lateral deltoid (DE), latissimus dorsi (LD), serratus anterior (SA) and pectoralis major (PE). A maximal voluntary isometric contraction test (MVIC; 5 s.) was performed on an isokinetic dynamometer. Next, internal/external rotation (In/Ex), abduction/adduction (Ab/Ad) and diagonal flexion/extension (F/E) exercises (5 reps.) were performed with four custom-made-pipes representing different exercise conditions. First, the empty-pipe (P; 0.5 kg) and then, randomly ordered, water-filled-pipe (PW; 1 kg), weight-pipe (PG; 4.5 kg) and weight + water-filled-pipe (PWG; 4.5 kg), while EMG was recorded. Raw root-mean-square values (RMS) were normalized to MVIC (%MVIC). Differences between conditions for RMS%MVIC, scapular stabilizer (SR: U.TA/L.TA; U.TA/SA) and contraction (CR: concentric/eccentric) ratios were analyzed (paired t-test; p ≤ 0.05; Bonferroni adjusted α = 0.008).
Results: PWG showed significantly greater muscle activity for all exercises and all muscles except for PE compared to P and PW. Condition PG elicited muscular activity comparable to PWG (p > 0.008) with significantly lower activation of L.TA and SA in the In/Ex rotation. The SR ratio was significantly higher in PWG compared to P and PW. No significant differences were found for the CR ratio in all exercises and for all muscles.
Conclusion: Higher weight generated greater muscle activation whereas an UWM raised the neuromuscular activity, increasing the stabilization demands. Especially in the In/Ex rotation, an UWM increased the RMS%MVIC and SR ratio. This might improve training effects in shoulder prevention and rehabilitation programs.
Internet of Things (IoT) and Artificial Intelligence (AI) are one of the most promising and disruptive areas of current research and development. However, these areas require deep knowledge in multiple disciplines such as sensors, protocols, embedded programming, distributed systems, statistics and algorithms. This broad knowledge is not easy to acquire and the software used to design these systems is becoming increasingly complex. Small and medium-sized enterprises therefore have problems in developing new business ideas. However, node- and block-based software tools have also been released and are freely available as open source toolboxes. In this paper, we present an overview of multiple node- and block-based software tools to develop IoT- and AI-based business ideas. We arrange these tools according their capabilities and further propose extension and combinations of tools to design a useful open-source library for small and medium-sized enterprises, that is easy to use and helps with rapid prototyping, enabling new business ideas to be developed using distributed computing.
This study introduced an automated long-term fermentation process for fungals grown in pellet form. The goal was to reduce the overgrowth of bioreactor internals and sensors while better rheological properties in the fermentation broth, such as oxygen transfer and mixing time, can be achieved. Because this could not be accomplished with continuous culture and fed-batch fermentation, repeated-batch fermentation was implemented with the help of additional bioreactor internals (“sporulation supports”). This should capture some biomass during fermentation. After harvesting the suspended biomass, intermediate cleaning was performed using a cleaning device. The biomass retained on the sporulation support went through the sporulation phase. The spores were subsequently used as inocula for the next batch. The reason for this approach was that the retained pellets could otherwise cause problems (e.g., overgrowth on sensors) in subsequent batches because the fungus would then show undesirable hyphal growth. Various sporulation supports were tested for sufficient biomass fixation to start the next batch. A reproducible spore concentration within the range of the requirements could be achieved by adjusting the sporulation support (design and construction material), and an intermediate cleaning adapted to this.
The study traces the development of compulsory vaccination in Germany against the background of political discussion and legislative activities, focusing on the area of tension between state health protection and the right to medical self-determination in the context of constitutional balancing. It is based on the assumption that the right to medical self-determination traditionally dominates state decisions in a democratic constitutional state and that the scope for decision-making is constantly being further contoured in the face of current challenges.
In the single-processor scheduling problem with time restrictions there is one main processor and B resources that are used to execute the jobs. A perfect schedule has no idle times or gaps on the main processor and the makespan is therefore equal to the sum of the processing times. In general, more resources result in smaller makespans, and as it is in practical applications often more economic not to mobilize resources that will be unnecessary and expensive, we investigate in this paper the problem to find the smallest number B of resources that make a perfect schedule possible. We show that the decision version of this problem is NP-complete, derive new structural properties of perfect schedules, and we describe a Mixed Integer Linear Programming (MIP) formulation to solve the problem. A large number of computational tests show that (for our randomly chosen problem instances) only B=3 or B=4 resources are sufficient for a perfect schedule.