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Freedom of trade, occupation and profession in times of the Covid-19 pandemic in South Africa
(2022)
This paper evaluates the freedom of trade, occupation, and profession in South Africa from a Covid-19 pandemic context. It does that by focusing on the pertinent provisions and rights contained in the Constitution of the Republic of South Africa, 1996 (the Constitution) and relevant international and regional human rights instruments. It proceeds by discussing the interlinkage between (the freedom of trade, occupation, and profession and other pertinent fundamental) rights, limitation, enforcement, and interpretation of rights. This is followed by some final observations.
Purpose: In this article, the canvas used to simplify business modeling of a platform and its visual depiction are put into the entrepreneurial context, and critically reflected accordingly. Furthermore, it is discussed to what extent the canvas is advantageous, disadvantageous, applicable, not applicable, or even contradictory.
Methodology: The analysis is based on theoretical research. Additionally, qualitative interviews with business founders were conducted.
Results: The results conclude that the canvas employed to ease the business model sharpening process supplies founders with essential aspects to cover, yet they are part of a large set of factors that play in.
Conclusion: The limitations of this study are rooted in the chosen research design based on the conceptual review.
The objective investigation of the dynamic properties of vocal fold vibrations demands the recording and further quantitative analysis of laryngeal high-speed video (HSV). Quantification of the vocal fold vibration patterns requires as a first step the segmentation of the glottal area within each video frame from which the vibrating edges of the vocal folds are usually derived. Consequently, the outcome of any further vibration analysis depends on the quality of this initial segmentation process. In this work we propose for the first time a procedure to fully automatically segment not only the time-varying glottal area but also the vocal fold tissue directly from laryngeal high-speed video (HSV) using a deep Convolutional Neural Network (CNN) approach. Eighteen different Convolutional Neural Network (CNN) network configurations were trained and evaluated on totally 13,000 high-speed video (HSV) frames obtained from 56 healthy and 74 pathologic subjects. The segmentation quality of the best performing Convolutional Neural Network (CNN) model, which uses Long Short-Term Memory (LSTM) cells to take also the temporal context into account, was intensely investigated on 15 test video sequences comprising 100 consecutive images each. As performance measures the Dice Coefficient (DC) as well as the precisions of four anatomical landmark positions were used. Over all test data a mean Dice Coefficient (DC) of 0.85 was obtained for the glottis and 0.91 and 0.90 for the right and left vocal fold (VF) respectively. The grand average precision of the identified landmarks amounts 2.2 pixels and is in the same range as comparable manual expert segmentations which can be regarded as Gold Standard. The method proposed here requires no user interaction and overcomes the limitations of current semiautomatic or computational expensive approaches. Thus, it allows also for the analysis of long high-speed video (HSV)-sequences and holds the promise to facilitate the objective analysis of vocal fold vibrations in clinical routine. The here used dataset including the ground truth will be provided freely for all scientific groups to allow a quantitative benchmarking of segmentation approaches in future.
This article presents experience curves and cost-benefit analyses for electric and plug-in hybrid cars sold in Germany. We find that between 2010 and 2016, the prices and price differentials relative to conventional cars declined at learning rates of 23 ± 2% and 32 ± 2% for electric cars and 6 ± 1% and 37 ± 2% for plug-in hybrids. If trends persist, price beak-even with conventional cars may be reached after another 7 ± 1 million electric cars and 5 ± 1 million plug-in hybrids are produced. The user costs of electric and plug-in hybrid cars relative to their conventional counterparts are declining annually by 14% and 26%. Also the costs for mitigating CO2 and air pollutant emissions through the deployment of electrified cars tend to decline. However, at current levels, NOX and particle emissions are still mitigated at lower costs by state-of-the-art after-treatment systems than through the electrification of powertrains. Overall, the observation of robust technological learning suggests policy makers should focus their support on non-cost market barriers for the electrification of road transport, addressing specifically the availability of recharging infrastructure.
Fuzzy system based on two-step cascade genetic optimization strategy for tobacco tar prediction
(2019)
There are many challenges in accurately measuring cigarette tar constituents. These include the need for standardized smoke generation methods related to unstable mixtures. In this research were developed algorithms using fusion of artificial intelligence methods to predict tar concentration. Outputs of development are three fuzzy structures optimized with genetic algorithms resulting in genetic algorithm (GA)-FUZZY, GA-adaptive neuro fuzzy inference system (ANFIS), GA-GA-FUZZY algorithms. Proposed algorithms are used for the tar prediction in the cigarette production process. The results of prediction are compared with gas chromatograph (high-performance liquid chromatography (HPLC)) readings.
Introduction: Annually, 2 million sports-related injuries are reported in Germany of which athletes contribute to a large proportion. Multiple sport injury prevention programs designed to decrease acute and overuse injuries in athletes have been proven effective. Yet, the programs’ components, general or sports-specific, that led to these positive effects are uncertain. Despite not knowing about the superiority of sports-specific injury prevention programs, coaches and athletes alike prefer more specialized rather than generalized exercise programs. Therefore, this systematic review aimed to present the available evidence on how general and sports-specific prevention programs affect injury rates in athletes.
Methods: PubMed and Web of Science were electronically searched throughout April 2018. The inclusion criteria were publication dates Jan 2006–Dec 2017, athletes (11–45 years), exercise-based injury prevention programs and injury incidence. The methodological quality was assessed with the Cochrane Collaboration assessment tools.
Results: Of the initial 6619 findings, 15 studies met the inclusion criteria. In addition, 13 studies were added from reference lists and external sources making a total of 28 studies. Of which, one used sports-specific, seven general and 20 mixed prevention strategies. Twenty-four studies revealed reduced injury rates. Of the four ineffective programs, one was general and three mixed.
Conclusion: The general and mixed programs positively affect injury rates. Sports-specific programs are uninvestigated and despite wide discussion regarding the definition, no consensus was reached. Defining such terminology and investigating the true effectiveness of such IPPs is a potential avenue for future research.
Introduction: Injury prevention programs (IPPs) are an inherent part of training in recreational and professional sports. Providing performance-enhancing benefits in addition to injury prevention may help adjust coaches and athletes’ attitudes towards implementation of injury prevention into daily routine. Conventional thinking by players and coaches alike seems to suggest that IPPs need to be specific to one’s sport to allow for performance enhancement. The systematic literature review aims to firstly determine the IPPs nature of exercises and whether they are specific to the sport or based on general conditioning. Secondly, can they demonstrate whether general, sports-specific or even mixed IPPs improve key performance indicators with the aim to better facilitate long-term implementation of these programs?
Methods: PubMed and Web of Science were electronically searched throughout March 2018. The inclusion criteria were randomized control trials, publication dates between Jan 2006 and Feb 2018, athletes (11–45 years), injury prevention programs and included predefined performance measures that could be categorized into balance, power, strength, speed/agility and endurance. The methodological quality of included articles was assessed with the Cochrane Collaboration assessment tools.
Results: Of 6619 initial findings, 22 studies met the inclusion criteria. In addition, reference lists unearthed a further 6 studies, making a total of 28. Nine studies used sports specific IPPs, eleven general and eight mixed prevention strategies. Overall, general programs ranged from 29–57% in their effectiveness across performance outcomes. Mixed IPPs improved in 80% balance outcomes but only 20–44% in others. Sports-specific programs led to larger scale improvements in balance (66%), power (83%), strength (75%), and speed/agility (62%).
Conclusion: Sports-specific IPPs have the strongest influence on most performance indices based on the significant improvement versus control groups. Other factors such as intensity, technical execution and compliance should be accounted for in future investigations in addition to exercise modality.
Geometrieerzeugung von Evolventenzahntrieben: Profilverschobene schrägverzahnte Stirnzahnräder
(2022)
In dieser Arbeit wird die Zahnradgeometrie von Stirnrädern berechnet und formatiert, um sie in ein CAD-Programm zu übertragen. Dabei werden die Konturen der Evolvente und der Trochoide nach den gleichen Regel wie bei der Herstellung durch Wälzfräsen erzeugt. Der Anwender hat die Möglichkeit die Haupteigenschaften wie Modul, Zahnkopfspiel und Eckenverrundung einzugeben. Zusätzlich können auch schrägverzahnte, profilverschobene Stirnräder mit Hochverzahnung und Kopfkürzung erzeugt werden.
Per Datenausgabe werden die Koordinaten gespeichert und durch ein Makro in das CAD-Programm übertragen. Aus den beiden Konturzügen wird der 3D-Körper durch Austragen entlang der Helix erzeugt.
Zur Weiterverarbeitung wird die Zahnradgeometrie nach manueller Tesselierung in ein universales Dateiformat exportiert.
Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.
Electric drive systems are increasingly used in automobiles. However, the combination of comfort, dynamics and safety requirements places high demands on the torque accuracy. The complex interplay of battery, inverter and electrical machine causes a lot of system uncertainties based on parameter fluctuations and measurement errors that influence the system performance. In this paper these influences on the closed loop torque control are analyzed and quantified using a variance based sensitivity analysis. The method enables to connect the variance of the torque accuracy with the parameter uncertainties causing this variance. Moreover, it quantifies the influences of the parameters independent of the complexity of the analyzed system. In addition, two methods to ensure convergence of the estimated variance based sensitivity measures are proposed. The results of the analysis are presented for 19 static working points of an battery electric drive system.
Bauprojekte sind in der Regel komplexe Vorhaben. Sie werden mit Hilfe des Projektmanagements und dessen Verfahren, Prozessen und Techniken bewältigt. Dennoch sind deutsche Bauprojekte nicht selten von Kosten- und Terminüberschreitungen betroffen. Ziel dieser Arbeit ist es, mögliche Optimierungsfelder im Planungs- und Steuerungsprozess eines Unternehmens für Industriebauprojekte zu identifizieren und darauf aufbauende Verbesserungsansätze zu erarbeiten. Um die Ziele verfolgen zu können, wurde eine qualitative Sozialforschung mittels Experteninterviews durchgeführt. Die Expertenaussagen verdeutlichen weiterhin Optimierungspotenzial, sowohl im Planungs- als auch im Steuerungsprozess. Ausgewählte Techniken (hauptsächlich aus dem klassischen Projektmanagement) dienen indessen dazu, die Effektivität und Effizienz des Planungsprozesses zu erhöhen. Innerhalb des Steuerungsprozesses zeigt sich, dass viele Optimierungsbereiche der Steuerung auf den Defiziten der Planung beruhen.
Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical-In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p < 0.001). Notably, the exposure of HS resulted in the induction of necroptosis by tumor necrosis factor α and receptor interaction protein 3 (p < 0.05; p < 0.01) and, hence, an increased level of necrotic cardiomyocytes. In conclusion, using this novel Medical-In silico approach, our data suggest (i) that HS induces necroptosis in cardiomyocytes by phosphorylation (activation) of receptor-interacting protein 3, (ii) that HS is a therapeutic target in trauma- or sepsis-associated cardiomyopathy, and (iii) indicate that this proof-of-concept is a first step toward simulating the extent of activated components in the pro-apoptotic pathway induced by HS with only a small data set gained from the in vitro experiments by using machine learning algorithms.
This paper is structured into two parts, which are closely related: first, the analysis of the parlamentary and governmental measures against the covid-19 pandemic; and second, the future regulatory framework about freedom of movement and other rights in the European area, according to the new European pact on migration and asylum.
Hydrochar derived from Argan nut shell (ANS) was synthesized and applied to remove bisphenol A (BPA) and diuron. The results indicated that the hydrochar prepared at 200 °C (HTC@ANS-200) possessed a higher specific surface area (42 m2/g) than hydrochar (HTC@ANS-180) prepared at 180 °C (17 m2/g). The hydrochars exhibited spherical particles, which are rich in functional groups. The HTC@ANS-200 exhibited high adsorption efficiency, of about 92% of the BPA removal and 95% of diuron removal. The maximum Langmuir adsorption capacities of HTC@ANS-200 at room temperature were 1162.79 mg/for Bisphenol A and 833.33 mg/g for diuron (higher than most reported adsorbents). The adsorption process was spontaneous (− ΔG°) and exothermic (− ΔH°). Excellent reusability was reclaimed after five cycles, the removal efficiency showed a weak decrease of 4% for BPA and 1% for diuron. The analysis of Fourier transforms infrared spectrometry demonstrated that the aromatic C=C and OH played major roles in the adsorption mechanisms of BPA and diuron in this study. The high adsorption capacity was attributed to the beneficial porosity (The pore size of HTC@ANS-200 bigger than the size of BPA and diuron molecule) and surface functional groups. BPA and diuron adsorption occurred also via multiple adsorption mechanisms, including pore filling, π–π interactions, and hydrogen bonding interactions on HTC@ANS-200.
Since operational managers often monitor large numbers of wind turbines (WTs), they depend on a toolset to provide them with highly condensed information to identify and prioritize low performing WTs or schedule preventive maintenance measures. Power curves are a frequently used tool to assess the performance of WTs. The power curve health value (HV) used in this work is supposed to detect power curve anomalies since small deviations in the power curve are not easy to identify. It evaluates deviations in the linear region of power curves by performing a principal component analysis. To calculate the HV, the standard deviation in direction of the second principal component of a reference data set is compared to the standard deviation of a combined data set consisting of the reference data and data of the evaluated period. This article examines the applicability of this HV for different purposes as well as its sensitivities and provides a modified HV approach to make it more robust and suitable for heterogeneous data sets. The modified HV was tested based on ENGIE's open data wind farm and data of on- and offshore WTs from the WInD-Pool. It proved to detect anomalies in the linear region of the power curve in a reliable and sensitive manner and was also eligible to detect long term power curve degradation. Also, about 7 % of all corrective maintenance measures were preceded by high HVs with a median alarm horizon of three days. Overall, the HV proved to be a promising tool for various applications.
Big Data is now poised to mutate decision-making systems. Indeed, the decision is no longer based solely on the structured information that was hitherto collected and stored by the organization, but also on all data not structured outside the corporate straitjacket. The cloud and the information it contains impacts decisions and the industry is witnessing the emergence of business intelligence 3.0. With the growth of the internet, social networks, connected objects and communication information are now more abundant than ever before, along with rapid and substantial growth in their production. In 2012, 2.5 exabytes of data (one exabyte representing a million gigabytes of data) came every day to swell the ranks of big data (McAfee et al., 2012), which should weigh more than 40 zettabytes from 2020 (Valduriez, 2014) for 30 billion connected devices (The Internet Of Nothings, 2014) and 50 billion sensors (Davenport & Soulard, 2014). One of the most critical aspects of all of this information flow is the impact these will have on the way decisions are made. Indeed, in the part of an environment in which data was scarce and difficult to obtain, it was logical to let decision-making be conditioned by the intuition of the experienced decision-maker (Klein, Phillips, Rall, & Peluso, 2007). However, since information and knowledge are now available to everyone, the role of experts and decision-makers is gradually changing. Big data, in particular, makes it possible for analytical and decision-making systems to base their decision-making on global models. However, considering all the dimensions of the situations encountered, it was not until now that these systems were not within the reach of man, but were rationally limited (Simon & Newell, 1971). Big data and however, the processing of unstructured data requires modifying the architecture of decision support systems (DSS) of organizations. This paper is an inventory of developments undergone by aid systems decision-making, under the pressure of big data. Finally, it opens the debate on ethical questions raised by these new technologies, and it is observed that now, data analysis of personal data has become more debatable than in the past.
Covid-19 outbreak had a huge impact on the economy worldwide as businesses had to close or cease their activities due to the lockdown regulations. The “luckiest” firms were able to operate but under restricted conditions. In order to avoid what certain authors called “bankruptcy epidemic” European countries took economic and fiscal measures to help companies compensate their financial losses. In addition to Government Grants, emergency legislations have been adopted with the aim to adapt insolvency and restructuring procedures to the sanitary situation and specific rules relating to company Law have also been implemented. This paper deals with the measures taken by the state of Luxembourg and gives a brief overview of the legal amendments.
Implementation strategies of a modern showroom concept for retailers with a wide range of products
(2022)
This paper suggests a new business model based on modern technology for retail. In the age of digitalization, stationary retail is losing market shares to online retail. Therefore, there is an obvious need for change in businesses. The concept developed in this paper combines the strengths of online and stationary retail to benefit stationary retail. In the approach taken in this paper, the basis for change is modern technology. Finding innovative ways to use technologies like NFC, AI, and robotics is regarded as the key factor to sustainable success. As the implementation of modern technologies entails a particular investment, the customers’ opinion on structural changes like these has been included in the consideration. Therefore, a survey has been conducted to find out which level of innovation current customers are willing to accept thus emphasizing the need for certain changes and dissuading specific others. The result of this paper is the modern showroom concept which takes the customers’ opinion into account while implementing the right amount of technology that should pave the way to a sustainable future for stationary retail.
Aim: The aim of this scientific paper was to examine important trends and developments influencing the nursing care in order to forecast future opportunities and challenges and how to deal with them in the best possible way.
Background: The Corona-pandemic demonstrated the importance of nursing care in the entire world and had drawn attention to the issue of a well-educated and enough nursing staff. The nursing care will face opportunities and challenges due to current trends and developments, which are important to examine in order to provide the best possible nursing care.
Methods: To reach the above-mentioned aim, intensive research was done by using secondary sources and surveys.
Results/Findings: After a detailed analysis of the research it can be summarized that there are three important topics influencing the nursing care: The demographical development with an increasing life expectancy leading to an increasing amount of old people with a demand for care and decreasing birth rates leading to less working people. Cultural transformation and diversity imply many opportunities because the employment market can fill gaps with foreign workers and the immigrating people can compensate the decreasing birth rates. Nevertheless, it can imply many challenges and potential problems which need to be solved by the society and the immigrating people. Furthermore, the changing gender roles can lead to more men becoming a nurse, which might have a significant impact on the shortage of nursing staff. The third important topic influencing the nursing care is technological trends which can help to decrease physiological stress, by facilitating the nurses’ work and by taking over some work from them.
Conclusion: It can be concluded that the trends and developments influencing the nursing care are very diverse and imply many different opportunities as well as challenges.