Miracle-dz/UniFAR-FTUs huggingface dataset:
How can SMEs integrate themselves in Global Value Chains of Global Players in the automotive industry?An Italian – German comparative analysis.

Purpose – The purpose of this study is to highlight the efforts undertaken by four companies, two German and two Italian small and medium-sized enterprises, in order to explain how these firms managed to integrate themselves in global value chains of global players in the automotive industry from a value chain perspective. Design/ methodology/ approach – The approach used was two-sided, qualitative and quantitative research methods were combined. Four case studies were created after conducting interviews and a survey was applied to test critical success factors. Originality/ value – To the author’s knowledge, there has been no micro firm approach with a global value chain view in the automotive industry that applied qualitative and quantitative research up until now. Therefore, the study contributes to global value chain literature. Findings – The case studies suggest that firms can integrate themselves into global value chains by implementing different critical success factors such as a clear focus on its core competencies combined with a global supply structure and simultaneously fostering innovation. With a proactive strategy to improve its uniqueness, the study found small and medium-sized enterprises on every supply tier in the automotive value chain. Research limitations/ implications – Quantitative research was conducted with a low level of participation, thus the quantitative research can only be applied to the case studies. The study is based on specific case studies, therefore its recommendations may be successfully applied to other products with consideration to different settings and competitive environments. Practical implications – The ideas contained in this study can help entrepreneurs or CEOs of small and medium-sized enterprises to see how one can successfully sustain in a globally active and competitive environment like the automotive industry. Further, it highlights the mutual benefit between small and medium-sized enterprises and lead firms, suggesting competitive advantages through co-operation for the lead firms of the industry as well. Lastly, the study reflects what governments are able to do to support the growth of small and medium-sized enterprises and consequently improve their regional or national performance. Paper type – Case study.
Effect of a Combination of Magnesium, B Vitamins, Rhodiola, and Green Tea (L-Theanine) on Chronically Stressed Healthy Individuals—A Randomized, Placebo-Controlled Study

The effect of a combination of magnesium, vitamins B6, B9, B12, rhodiola and green tea/L-theanine (Mg-Teadiola) on stress was evaluated in chronically stressed, otherwise healthy individuals. Effects on stress-related quality-of-life parameters (sleep and perception of pain) were also explored. Adults with stress for ≥1 month, scoring ≥14 points on the Depression Anxiety Stress Scale (DASS)-42 questionnaire, were randomized (1:1) to receive oral Mg-Teadiola (n = 49) or a placebo (n = 51), for 28 days, with a follow-up assessment on Day 56 (NCT04391452). The primary endpoint was the change in the DASS-42 stress score from baseline to Day 28 with Mg-Teadiola versus placebo. The DASS-42 stress scores significantly decreased from baseline to Day 28 with Mg-Teadiola versus placebo (effect size, 0.29; 95% CI [0.01, 0.57]; p = 0.04). Similar reductions were observed on Day 14 (p = 0.006) and Day 56 (p = 0.02). A significant reduction in sensitivity to cold pain (p = 0.01) and a trend for lower sensitivity to warm pain was observed (p = 0.06) on Day 28. Improvements in daytime dysfunction due to sleepiness (Pittsburgh Sleep Quality Index-7 component score) were reported on Day 28, and were significant on Day 56 (p < 0.001). Mg-Teadiola is effective in managing stress in otherwise healthy individuals. Its beneficial effects on sleep and pain perception need further investigation.
Propagation Characteristics and Modeling of Traveling Lightning Surge Waveshapeson UHV Designed Transmission Line

An experimental investigation was performed on a UHV long distance transmission line model for the EMTP calculation of lightning overvoltage at substation. The various lightning surge propagation characteristics were measured on an actual UHV transmission line. In this paper, we present the traveling lightning surge waveshapes, propagation characteristics of peak voltage and front waveshapes and analyzed waveshapes by EMTP for insulation design of substation on UHV transmission line. In addition, we report on the relationships between peak voltage and propagation at 200km analyzed by EMTP.
A Residue Number System Based Time-to-Digital Converter Architecture and its FPGA Implementation

A time-to-digital converter (TDC) based on residue number system is presented. This architecture can reduce hardware and chip area as well as power significantly compared to a flash-type TDC while keeping comparable performance. Its proof-of-concept prototype was implemented on FPGA, and the measurement results validate the effectiveness of the proposed architecture
Non-contact automatic vital signs monitoring of neonates in NICU using video camera imaging

ABSTRACT Non-contact vital signs monitoring is desirable in both clinical and non-clinical sectors. However, there are limited camera-based studies to monitor the vital signs of neonatal infants in a clinical setting. In this study, a digital camera was used to remotely monitor the heart rate (HR) and respiratory rate (RR) of seven infants at Flinders Medical Centre Neonatal Intensive Care Unit (NICU). The region-of-interest (ROI) was automatically selected based on a skin detection method using skin hue. The experimental results have been validated with the reference data obtained from an ECG monitor, and they showed a strong correlation using the Pearson correlation coefficient, (PCC) . 9836 and . 9426 for HR and RR, respectively, and a lower error rate with RMSE 2.66 beats/min and 2.93 breaths/min between measured data and reference data. A Bland Altman analysis of the data also presented a close correlation between measured data and reference data for both HR and RR with a mean bias . 69 beats/min and . 28 breaths/min, and the lower and upper limit of agreement −4.4 to +5.8 beats/min and −5.5 to +6.1 breaths/min, respectively. Therefore, video camera imaging may replace conventional monitoring in NICU and has potential applications in other contexts such as home health monitoring.
Application of local mean decomposition in power quality disturbance detection

LMD(Local Mean Decomposition) is applied in the detection of power quality disturbance. The typical interharmonic interference signal,short-time harmonic signal,transient harmonic signal,time-varying harmonic signal,as well as the actual multi-frequency harmonic signals occurred in transformers,are selected and analyzed by LMD. Results of interharmonic signal simulation show that,the LMD method is better than the HHT method in the parameter fluctuation of transient characteristic parameter detection,the end effect,the detection accuracy and the running time. Results of harmonic distortion signal simulation show that,the frequency,amplitude,occurrence and recovery time of disturbance signal can be accurately detected by LMD.The sag and distortion of 35 kV-side phase-B voltage caused by the switch-in of a 35 kV-side capacitor in a 500 kV substation are analyzed,proving the correctness of the proposed method.
Generative Adversarial learning with Negative Data Augmentation for Semi-supervised Text Classification

In recent years, semi-supervised generative adversarial networks (SS-GANs) models such as GAN-BERT have achieved promising results on the text classification task. One of the techniques used in these models to mitigate the generator from mode collapse is feature matching (FM). Although FM addresses some of the critical issues of SS-GANs, these models still suffer from mode collapse with missing coverage outside the data manifold. Moreover, FM loosely tries to match the distribution between the real data and the fake generated samples. By doing this, the generator can generate fake samples inside high-density regions in the data manifold, where the discriminator learns to misclassify them as out-of-data-manifold regions. In this work, we employ the negative data augmentation (NDA) technique, for the first time in text classification, to alleviate the mentioned problems. NDA is a unique way of producing out-of-distribution fake examples by applying mixup transformation on the fake samples and augmented real data. In our new model (NDA-GAN), we produce NDA samples by combining the generator's output with the contextual representation of the real data. As a result of the mixing, NDA samples are less likely to place in the high-density regions, and due to blending with real data representations, these samples reasonably preserve a close distance to the data manifold. Consequently, the NDA samples increase the discriminator's power to find the optimal decision boundary. Our experimental results demonstrate that the negative augmented samples improve the overall accuracy of our proposed model and make it more confident when detecting out-of-distribution samples.
Influence of Environmental Aesthetic Value and Anticipated Emotion on Pro-Environmental Behavior: An ERP Study

Perceptual cues act as signals in the aesthetic value environment, which promote emotion regulation toward pro-environment behavior. This type of perception-emotion-behavior reactivity forms the core of human altruism. However, differences in pro-environmental behavior may result from variation across high-aesthetic-value (HAV) and low-aesthetic-value (LAV) environments. This study investigated the neural mechanisms underlying interaction effects between environmental context and emotion regulation on pro-environmental behavior by integrating behavioral and temporal dynamics of decision-making information processing with event-related potential (ERP) technique measures. The results indicated that changing anticipated emotions changes pro-environmental behavior. Regarding changing aesthetic value environments, while modulating emotion regulation, significant differences were found in brain regions and mean amplitudes of N1, P2, N2, and late positive potential (LPP) components, which anticipated emotion. The findings suggest that environmental aesthetic value and emotion regulation impact pro-environmental behavior.
Preparation for Capturing Human Skills during Tooling Tasks Using Redundant Markers and Instrumented Tool

In recent years, robots have found extensive applications in automating repetitive, defined, position dependent tasks such as painting and material handling. However, continuous contact type tasks (such as finishing, deburring and grinding) that require both position and force control are still carried out manually by skilled labor. Majorly, because it is difficult to program experienced user skills in a robotic setup without having clear knowledge of underlying model used by the operators. In this paper we present a preparation for capturing human operator’s dynamics using an instrumented hand-held tool and a motion capture setup. We first present the design of an instrumented tool and later present a method for reliably capturing kinematics using redundant markers removing effects of marker occlusions, and effect of gravity caused by the tool's mass. Kinematic information is used for deriving the forces/torques on the tool end effector.
Reliability and Validity Evidence of Two Distance Education Learning Environments Scales

ABSTRACT Students more than ever are completing their university studies online. At the onset of the Covid-19 pandemic, most higher education providers were required to move to exclusively deliver online curriculum. It is therefore imperative that educators have access to psychometrically sound measures of students’ online learning experiences. The reliability and validity properties of the Distance Education Learning Environments Scale (DELES) and Student Engagement in the e-Learning Environment Scale (SELES) were examined. A sample of 151 Australian undergraduate students completed the DELES and SELES after completing their studies online during 2020 due to Covid-19. Cronbach alpha coefficients, subscale item correlations and linear regression analyses were completed with bootstrapping. Cronbach alpha coefficients for the SELES subscales ranged from . 68 to . 93 and . 75 to . 96 for the DELES subscales. The within subscale correlations ranged from . 29 to . 66 for the SELES (p < .001) and . 30 to . 68 for the DELES (p < .001) and the between subscale correlations ranged from . 18 to . 75 (p < .001) respectively. Regression findings indicated that the SELES and DELES subscale models each accounted for 56.6% and 22.2% of the unique variance of the DELES Enjoyment, respectively. These findings present important psychometric evidence about the DELES and SELES.
IN THE PITS: A CRITICAL EXAMINATION OF PITEST

This paper examines a tool called PITest that aims to do mutation analysis for the Java programming language. The examination is aimed at answering the questions: 1) "is it implemented with sufficient quality? " and 2) "does it truly perform mutation analysis? " As such, the paper focuses on several important metrics such as the overall mutation score (i.e. how well its tests handle regressions and how well it is generally tested) among others. It also highlights several aspects that are specific to mutation analyzers, such as mutation operators and whether PITest’s set of mutation operators actually lead to an accurate indication of the quality of its targets. This paper illustrates that even tools that are intended to be objective instruments for code quality suffer the same as the average open source project in terms of implementation and design quality, thus highlighting the need for higher standards for such tools.
Safety and School Travel: How Does the Built Environment Relate to Correlates of Safety, Mode of Travel and Physical Activity Levels to and from School

Many children do not meet the physical activity targets necessary to accrue health benefits. Declines in active school travel over the past half century are one example of how opportunities for daily physical activity for children have been lost. Adult safety concerns may partially relate to the recent decreases in active school travel. This dissertation examines the connection between safety, the built environment and school travel behaviour. A mixed methods study design explores the links between safety, the environment, physical activity and school transport. Findings from the first results chapter suggest that safety in general is a concern for both parents and children but safety concerns are not uniform. Both parents and children were worried about strangers, while children identified additional concerns such as dogs and bullies. Traffic safety concerns related to street crossings, incomplete sidewalks and traffic around the school. Further analysis determined that objective measures of the environment such as street crossings, sidewalk, traffic and parking relate to mode of travel. Perceptions regarding the presence of strangers, street crossings and living in a safe neighbourhood, were also important
Thermophysiological models and their applications

The human body ’ s heat exchange and its interaction with the surrounding environment has in the past years been the research focus of a number of disciplines. As a result, a number of human thermoregulation models have been developed since the ﬁ rst was developed in 1970. The aim of this paper is to conduct a review of existing thermophysiological models for the whole body and isolated body segments. The course of the development from simple to more complex models is shown
Ultrafast and real-time physical random bit extraction with all-optical quantization

Optical chaos generated by perturbing semiconductor lasers has been viewed, over recent decades, as an excellent entropy source for fast physical random bit generation (RBG) owing to its high bandwidth and large random fluctuations. However, most optical-chaos-based random bit generators perform their quantization process in the electrical domain using electrical analog-to-digital converters, so their real-time rates in a single channel are severely limited at the level of Gb/s due to the electronic bottleneck. Here, we propose and experimentally demonstrate an all-optical method for RBG where chaotic pulses are quantized into a physical random bit stream in the all-optical domain by means of a length of highly nonlinear fiber. In our proof-of-concept experiment, a 10-Gb/s random bit stream is successfully generated on-line using our method. Note that the single-channel real-time rate is limited only by the chaos bandwidth. Considering that the Kerr nonlinearity of silica fiber with an ultrafast response of few femtoseconds is exploited for composing the key part of quantizing laser chaos, this scheme thus may operate potentially at much higher real-time rates than 100 Gb/s provided that a chaotic entropy source of sufficient bandwidth is available.
Experimental and Numerical Investigations on the Damage Induced in the Shearing Process for QP980 Steel

Ultra-high-strength quenching and partitioning (Q&P) steels have achieved remarkable lightweight effect in automotive manufacture due to the excellent mechanical performances. However, the problem of sheared-edge cracking greatly limits their application. In this work, the damage generated in the shearing process of QP980 steel is experimentally investigated via microstructure characterization and micro-/macromechanical property evaluation. Moreover, the shearing deformation is simulated with six widely used damage models. The experimental results reveal that microvoids, microcracks, and work-hardening behavior are the main damage factors affecting the formability of sheared edges. Microvoids mainly formed at phase interfaces have a small size (≤5 μm), while microvoids generated from inclusions with a small number have a large size (>5 μm). As deformation continuously grows, microvoids distributed around the sheared surface are split into microcracks, which act as crack initiators in the subsequent forming step. Additionally, the highest microhardness in the fracture zone further enhances the susceptibility of edge cracking. Furthermore, the optimum damage model for QP980 steel was determined by developing user-defined subroutine VUSDFLD in Abaqus, which can be used in the prediction of fracture behavior of QP980 steel to reduce the risk of edge cracking.
Residual Biomass Recovery in the Wine Sector: Creation of Value Chains for Vine Pruning

Waste management is a current and transversal problem in all production areas, including agriculture. Within this economic activity, wine production generates a large amount of waste, namely, that resulting from the winemaking activity itself, such as pomace and grape stalks, and waste resulting from the management of the vineyards, with operations such as vine pruning. The management of vine pruning residuals has traditionally been conducted by burning leftovers on-site, without any use for the energy produced. This research analyzed the potential for the valorization of residual biomass resulting from vine pruning by creating a business model based on value chains of local scale. For this analysis, several samples of residues resulting from the “Loureiro” vine variety planted in Ponte de Lima (northern Portugal) were collected and characterized. The objective of the small-scale business model created, in addition, to solving the environmental problems related to the disposal of waste from agricultural activities, a value chain can be established, contributing to increasing the income of the farmers while introducing a circular bioeconomy and sustainable rural development practices.
Nonlinear Model Predictive Controller Design for Path Following of Underactuated Ships

An analytic model predictive controller is presented for path following of an underactuated ship maneuvering along a predefined path.The mathematical model of ship motion is described by us-ing Serret-Frenet frame and the output-redefinition is introduced.As a result,the problem of ill-defined relative degree is avoided,and the original single-input multiple-output(SIMO) system is transformed into an equivalent single-input single-output(SISO) system.The proposed algorithm provides a systematic method to get appropriate controller parameters to guarantee the stability of the closedloop system.Numerical simulations demonstrate the validity of the proposed controller.
In-vitro dissolution of vitreous silicate fibres according to EURIMA test guideline: Results of two Round Robins

The EURIMA (The European Insulation Manufacturers Association) test guideline "In-vitro acellular dissolution of man-made vitreous silicate fibres" provides a state-of-the-art method for measuring in-vitro dissolution rates relevant for evaluating the biopersistence of insulation wool fibres and other vitreous silicate fibres. Based on this guideline two Round Robins were conducted as well as specific investigations on the influence of selected test parameters. Nine and six laboratories, respectively, participated in the two Round Robins. The standard deviation between K d i s results obtained by different laboratories was'slightly lower in the second Round Robin ranging from 24 to 61% (highest for the low-soluble fibres). The relatively high inter-laboratory variation suggests that the equipment, setup and procedures should be specified in much more detail in a future test method. Key parameters to be kept constant are flow rate/surface area and liquid composition, and care should be taken to maintain constant conditions and eliminate outlier measurements. A laboratory may use the method described in the guideline for quality assurance of maintained biosolubility and for development of alternative fibre modifications as the method is well suited for ranking different fibres with respect to dissolution coefficients within one laboratory. How-ever, caution should be exercised when comparing values obtained by one laboratory to values obtained by another.
An open workflow to gain insights about low‐likelihood high‐impact weather events from initialized predictions

Low‐likelihood weather events can cause dramatic impacts, especially when they are unprecedented. In 2020, amongst other high‐impact weather events, UK floods caused more than £300 million damage, prolonged heat over Siberia led to infrastructure failure and permafrost thawing, while wildfires ravaged California. Such rare phenomena cannot be studied well from historical records or reanalysis data. One way to improve our awareness is to exploit ensemble prediction systems, which represent large samples of simulated weather events. This ‘UNSEEN’ method has been successfully applied in several scientific studies, but uptake is hindered by large data and processing requirements, and by uncertainty regarding the credibility of the simulations. Here, we provide a protocol to apply and ensure credibility of UNSEEN for studying low‐likelihood high‐impact weather events globally, including an open workflow based on Copernicus Climate Change Services (C3S) seasonal predictions. Demonstrating the workflow using European Centre for Medium‐Range Weather Forecasts (ECMWF) SEAS5, we find that the 2020 March–May Siberian heatwave was predicted by one of the ensemble members; and that the record‐shattering August 2020 California‐Mexico temperatures were part of a strong increasing trend. However, each of the case studies exposes challenges with respect to the credibility of UNSEEN and the sensitivity of the outcomes to user decisions. We conclude that UNSEEN can provide new insights about low‐likelihood weather events when the decisions are transparent, and the challenges and sensitivities are acknowledged. Anticipating plausible low‐likelihood extreme events and uncovering unforeseen hazards under a changing climate warrants further research at the science‐policy interface to manage high impacts.