Miracle-dz/UniFAR-FTUs huggingface dataset:
COVID-19: A Game-changer to Equity Markets?

This article applies the effective transfer entropy methodology to quantify the information flow between equities in major global equity markets in Australia, Brazil, Canada, China, Germany, Iran, Japan, Qatar, Saudi Arabia, South Africa, South Korea, United Kingdom, and the United States – a pool of 2200 companies included. To account for COVID-19 impacts, the period of the study was extended over two years. The results show changes to the information flow pattern after COVID-19, with the largest changes being encountered in Australia, Brazil, Canada, Japan, and the United States – for their largest market participants (by market capitalization). In comparison, the Asian markets show less noticeable changes in their information flow pattern after COVID-19. On a sector level, most of the markets studied have seen substantial changes in the functionality of their sectors – in terms of being a transmitter or receiver of information – after COVID-19 appearance. The fraction of sectors with a complete change in their influencing role since COVID-19 has been over 70% in Australia, Canada, South Africa, and the United States. The financial services sector has retained its role - as being the most influencing sector - in 6 out of 13 markets considered after COVID-19. For most of the markets, the basic materials, communications, energy, and utilities sectors have retained an intermediate position in the information flow diagram, after COVID-19. The German market has been the only market, in which the main information transmitter and receiver sectors have remained unchanged, since COVID-19. The results suggest drastic moves in major global equity markets, which have been concurrent with the virus outbreak. Doi: 10.28991/HEF-2021-02-01-05 Full Text: PDF
Fingerprinting of skin cells by live cell Raman spectroscopy reveals melanoma cell heterogeneity and cell‐type‐specific responses to UVR

Raman spectroscopy is an emerging dermatological technique with the potential to discriminate biochemically between cell types in a label free and non-invasive manner. Here we use live single cell Raman spectroscopy and principal component analysis (PCA) to fingerprint mouse melanoblasts, melanocytes, keratinocytes and melanoma cells. We show the differences in their spectra are attributable to biomarkers in the melanin biosynthesis pathway and that melanoma cells are a heterogeneous population that sit on a trajectory between undifferentiated melanoblasts and differentiated melanocytes. We demonstrate the utility of Raman spectroscopy as a highly sensitive tool to probe the melanin biosynthesis pathway and its immediate response to UV irradiation revealing previously undescribed opposing responses to UVA and UVB irradiation in melanocytes. Finally, we identify melanocyte specific accumulation of β-carotene correlated with a stabilisation of the UVR response in lipids and proteins consistent with a β-carotene mediated photoprotective mechanism. In summary our data show that Raman spectroscopy can be used to determine the differentiation status of cells of the melanocyte lineage and describe the immediate and temporal biochemical changes associated with UV exposure which differ depending on cell type, differentiation status and competence to synthesise melanin.
Antisocial sexual behaviour online scale: validation and psychological and sociodemographic correlates

ABSTRACT This research aimed to validate the Antisocial Sexual Behaviour Online Scale, observing its relationships with sending explicit photos, gender, age, and personality. Study 1 (N = 215, 72.1% women, Mage = 26.58, SD = 7.84) evidenced a one-factor organisation (eigenvalue = 1.54, explained variance = 38.57%, ω = 0.71). Study 2 (N = 214, 71.5% women, Mage = 23.57, SD = 7.04) corroborated this structure (GFI = 0.97, CFI = 0.96, RMSEA = 0.05 (90% CI 0.01-0.15), SRMR = 0.10) and gender invariance. Study 3 (N = 397, 71% women, Mage = 29.3, SD = 8.54) showed correlations between ASBO, sending explicit photos (r = 0.25, p < 0.01), being a man (r = 0.13, p < 0.01), age (r = −0.17, p < 0.01), conscientiousness (r = −0.15, p < 0.01), agreeableness (r = −0.11; p < 0.05), and emotional stability (r = −0.14, p < 0.01). PRACTICE IMPACT STATEMENT The internet’s use to perpetuate antisocial sexual behaviours has become an increasingly present problem, requiring the development of tools to measure it. The present research proposed a brief and psychometrically adequate instrument for this purpose. Through the measure, it is possible to observe the prevalence of antisocial sexual behaviour online, as well as relate it to other psychosocial constructs.
Effects of Hand Vibration on Motor Output in Chronic Hemiparesis

Background. Muscle vibration has been shown to increase the corticospinal excitability assessed by transcranial magnetic stimulation (TMS) and to change voluntary force production in healthy subjects. Objectives. To evaluate the effect of vibration on corticospinal excitability using TMS and on maximal motor output using maximal voluntary contraction (MVC) in individuals with chronic hemiparesis. Methodology. Nineteen hemiparetic and 17 healthy control subjects participated in this study. Motor evoked potentials (MEPs) and MVC during lateral pinch grip were recorded at first dorsal interosseous muscle in a single session before, during, and after one-minute trials of 80 Hz vibration of the thenar eminence. Results. In hemiparetic subjects, vibration increased MEP amplitudes to a level comparable to that of control subjects and triggered a MEP response in 4 of 7 patients who did not have a MEP at rest. Also, vibration increased the maximal rate of force production ( ) in both control and hemiparetic subjects but it did not increase MVC. Conclusion. Motor response generated with a descending cortical drive in chronic hemiparetic subjects can be increased during vibration. Vibration could be used when additional input is needed to reveal motor responses and to increase rate of force generation.
Effects of Variety and Nitrogen Levels on the Performance of Pearl Millet: Pennisetum Glaucum (L.) R. BR.

The trials were conducted in 2010 and 2011 rainy seasons at Usmanu Danfodiyo University, Sokoto Teaching and Research Dry Land Farm, Dundaye, Nigeria to determine the effects of variety and nitrogen levels on performance of (SOSAT c-88 and Zango millet varieties). Data collected were on Stand count, tiller count, plant height and panicle length. Others included panicle weight and grain yield. All data collected were subjected to analysis of variance (ANOVA). The results SOSAT c-88 and Zango millet indicated that millet varieties have no significant effect on both stand and tiller production throughout the sampling periods though nitrogen levels has significant on tiller production at 6 weeks after planting of both 2010 and 2011 cropping seasons. Panicle length was affected by millet varieties and nitrogen levels in both cropping seasons. Improve millet variety Sosat c-88 gave higher grain yield while 80 kg ha-1 and 120 kg ha-1produced significant higher millet grain yield hence should be practiced. Doi: 10.28991/HEF-2020-01-04-04 Full Text: PDF
Application of Genetic Programming for Estimation of Soil Compaction Parameters

The aim of this study is to propose two numerical models by a well-known soft computing method, Genetic Programming (GP), for the estimation of soils compaction parameters. Genetic Programming is a pattern recognition approach that has the ability of modeling the non-linear behavior of complex engineering problems. The input variables were the soil classification properties, and the outputs were the Optimum Moisture Content (OMC) and Maximum Dry Density (MDD). To provide model, a database including properties of different soils classified as CH, CI, CL, GC, GM, MH, MI, ML and SC was used. In addition, a new Multiple Linear Regression (MLR) based formula using the database, compared with the GP based model. Study results revealed that the proposed formula by GP can predict the compaction parameters of soils in a highly precise manner, and its outputs were in satisfactory conformity with real test results. Performances of the proposed models evaluated using the regression statistical analyses. The proposed formulae can be useful for the preliminary design of engineering projects and are more useful for cases with time and financial limitations.
Ionospheric Plasma Vertical Drift and Zonal Wind Variations Cause Unusual Evolution of EPBs During a Geomagnetically Quiet Night

Previous studies show equatorial plasma bubbles (EPBs) mainly occur after sunset and usually drift from west to east. In this work, two EPBs occurred after midnight and lasted to sunrise, and were observed by multi‐instruments (two all‐sky imagers (ASIs), global positioning system, Swarm satellite, and a digisonde) during a geomagnetically quiet night of December 18–19, 2018. Our observations also show that plasma depletion structure (PDS) also occurred at that night. EPBs occurred in the region of PDS and showed a special evolution process during the night. Those PDS gradually disappeared with time, but strip‐like EPBs remained clearly in airglow images. Near sunrise, new PDS appeared to merge with those EPBs to form large PDS. Meanwhile, EPBs showed different zonal drifts within a very narrow longitudinal zone (∼2°). One EPB remained stationary while the other showed a small eastward drift. These results are different from post‐sunset EPBs in previous studies. During the lifetime of those ionospheric plasma irregularities, upward and downward motion of the peak height and virtual height of the ionospheric F region was observed by a digisonde, which indicates that the evolution of EPBs should be related to the vertical drift of ionospheric plasma. Besides, based Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model (TIE‐GCM) simulations, we suggest the different zonal drifts of those EPBs might related to plasma zonal drifts caused by zonal winds.
Teachers’ language politeness, students’ academic motivation and self-efficacy during school from home

This study aims to investigate the influence of teachers’ language politeness on students’ academic motivation and self-efficacy during online learning (school from home) and to examine the relationship between students’ academic motivation and self-efficacy during online learning. This study used a quantitative approach with the correlational method. The participants of the study were 150 elementary students (male: 47%; female: 53%). Three types of scales were used in this study, namely the teachers’ language politeness scale, the academic motivation scale and the self-efficacy scale. The hypothesis of the study was tested using analysis of variance assisted with SPSS version 26. The study found that teachers’ language politeness significantly influences students’ academic motivation and self-efficacy during online learning. Teachers’ language politeness was more likely to have greater influence on students’ self-efficacy than on students’ academic motivation. As shown in the model, the value of the relationship between students’ academic motivation and self-efficacy was 0.497. Keywords: Language politeness, academic motivation, self-efficacy, school from home.
Active fault-tolerant control of induction motor drives in EV and HEV against sensor failures using a fuzzy decision system

This paper describes an active fault-tolerant control system for a high performance induction motor drive that propels an electrical vehicle (EV) or a hybrid one (HEV). The proposed system adaptively reorganizes itself in the event of sensor loss or sensor recovery to sustain the best control performance given the complement of remaining sensors. Moreover, the developed system takes into account the controller transition smoothness in terms of speed and torque transients. For automotive application purposes two control techniques are chosen to illustrate the consistency of the proposed approach: sliding mode for encoder-based control and fuzzy logics for sensorless control. The system control reorganization is managed by a fuzzy decision system. Simulations tests, in term of speed and torque responses, have been carried out on a 4 kW induction motor drive to evaluate the consistency and the performance of the proposed fault-tolerant control approach.
Effects of nutrition education and counseling intervention on maternal weight and obstetric outcomes among pregnant women of Gedeo Zone, Southern, Ethiopia: A cluster randomized control trial

Background: Due to the scarcity of intervention trials, especially in Ethiopia, the effect of nutrition education and counseling intervention on pregnancy outcomes is not well studied. Aim: To assess the effect of nutrition education and counseling on the outcomes of pregnancy among pregnant mothers in public health care institutions of Gedeo Zone, Southern, Ethiopia. Methods: A cluster randomized control trial study design was undertaken. Simple random sampling followed by cluster sampling was used to reach eligible study participants. A total sample of 235 (115 intervention vs.120 control group) pregnant women who followed anti-natal care service in public health facilities of Gedeo Zone was included in the study. Independent t-test was used to analyze the group difference for continuous variable and chi-square test for categorical variables. The post-intervention values between the two groups were compared using analysis of covariance by adjusting to baseline variable. Results: After nutrition education, pregnant women in the control group had less weight gain than in the intervention. The proportion of LBW neonate was 17.8% in the intervention group and 38.2% in the control group (P < 0.001). Multivariable logistic regression analysis showed that the risk of LBW in the control group was 2.43 more likely than in the intervention group (AOR = 2.43; 95% CI: (1.2, 4.92)). Conclusion: Nutrition education delivered to pregnant women during pregnancy could reduce maternal malnutrition and low birth weight. Recommendation: The intervention is easy to implement in the health facilities of Gedeo zone and would be implemented without delay to achieve the sustainable development goals.
Decision-Making and Support Tools for Design of Transmission Systems

Transmission systems are crucial components of many machines and mechanisms. Ken Hurst (1998) highlights that whether you are designing power plants, cars, or washing machines, the power transmission system is an integral component responsible for product success or failure. The components that comprise a power transmission system include those that transfer power directly (coupling and shaft), speed and torque multiplication components (gears, belt drives, etc.), and the related mechanisms (clutches, brakes, etc.; see Freeman & Velinsky, 1995). Transmission system design is a multistage iterative process of sequential generation and modification of design decisions. These decisions define in many respects the technical and economic characteristics of future products. Searching for suitable design decisions is a highly complex and time-consuming problem due to the necessity to consider and analyze many heterogeneous functional, technical, and economic factors. However, extensive computations, including solving very complex optimization tasks, are needed. As a rule, the design procedures are provided only by a very competent and experienced designer. With ever more complex and combinatorial decisions to be made, even the best designer will need competent design support, of which there is little. Therefore, the design of transmission systems is a wide open area for development and application of decision-making and decision support technologies.
No-Reference Light Field Image Quality Assessment Using Four-Dimensional Sparse Transform

Light field imaging can simultaneously capture the intensity and direction information of light rays in the real world. Light field image (LFI) with four-dimensional (4D) data suffers from quality degradation in the process of compression, reconstruction and processing. How to evaluate the visual quality of LFI is thought-provoking. This paper proposes a no-reference LFI quality assessment metric based on high-dimensional sparse transform. Firstly, LFI's sub-aperture gradient image array (SAGIA), which is still a 4D signal, is generated by high-pass filtering between adjacent SAIs. Then, SAGIA is transformed with 4D discrete cosine transform (4D-DCT). 4D-DCT coefficients of SAGIA can characterize the angular and spatial information of LFI. And the logarithmic amplitudes of the coefficients at the same position of SAGIA? s transformed 4D blocks are averaged as the coefficient energy. Subsequently, the 4D-DCT coefficients of SAGIA are divided into the spatial-angular frequency bands and spatial-angular orientation bands, and the corresponding energy features are extracted by converging the coefficient energy of the same band. In addition, the coefficients' amplitudes at the same position of blocks are fitted by the Weibull distribution. Then, the fitted parameters of each position are concatenated, and cropped with principal component analysis to obtain the compact features. Finally, the extracted features are pooled to predict the visual quality of the distorted LFIs. The experimental results demonstrate that the proposed method is more consistent with the subjective evaluation on three LFI databases, compared with the state-of-the-art image quality assessment methods and LFI quality assessment methods.
Economic Analysis of the Digital Economy

As the cost of storing, sharing, and analyzing data has decreased, economic activity has become increasingly digital. But while the effects of digital technology and improved digital communication have been explored in a variety of contexts, the impact on economic activity—from consumer and entrepreneurial behavior to the ways in which governments determine policy—is less well understood. Economic Analysis of the Digital Economy explores the economic impact of digitization, with each chapter identifying a promising new area of research. The Internet is one of the key drivers of growth in digital communication, and the first set of chapters discusses basic supply-and-demand factors related to access. Later chapters discuss new opportunities and challenges created by digital technology and describe some of the most pressing policy issues. As digital technologies continue to gain in momentum and importance, it has become clear that digitization has features that do not fit well into traditional economic models. This suggests a need for a better understanding of the impact of digital technology on economic activity, and Economic Analysis of the Digital Economy brings together leading scholars to explore this emerging area of research.
Does innovation capability improve SME performance in Malaysia? The mediating effect of technology adoption

SMEs still need innovation to boost their performance in the age of globalisation and fierce market rivalry. Previous studies have identified that innovation capability is an essential driver in manufacturing industries for their survival. Yet, the featuring role of innovation capability has been considered theoretically in developed economies whereas empirical studies in emerging economies are still lacking. Therefore, the purpose of this study to examines the importance of innovation capability towards SME performance and the mediating role of technology-adoption. Structured questionnaires were used to collect the data from a sample size of 611 SMEs operating in the developing market of Malaysia. Derived hypotheses were verified through Structural Equation Modelling (SEM) using AMOS 21. The findings of the study indicated that innovation capability has a signiﬁcant positive impact on SME performance. Technology- adoption partially mediates the relationship between innovation capability and SME performance. SMEs are required to generate an operative innovation model to gain sustainable performance and competitive advantage in the Malaysian market.
Governance and Success in U.S. Equity Crowdfunding

We propose three governance mechanisms pertinent to equity crowdfunding and campaign success through mitigating pronounced information asymmetries and agency problems. First, unlike IPOs for which the effect of Delaware incorporation has declined or disappeared over time, we propose Delaware incorporation matters a great deal for success in the new setting of equity crowdfunding. Second, we propose that security design is a critical tool for equity crowdfunding success and even more important than the limited 2-year financial statement disclosure. Third, we propose that platforms as intermediaries between entrepreneurs and investors play an important role in mitigating and sometimes exacerbating information asymmetries and agency problems. The population of equity crowdfunding campaigns from market inception in May 2016 to Q2, 2021 in the United States provides strong support for these propositions.
Genetic risk prediction for common diseases : methodology and applications

textabstractThis thesis describes methodological and empirical studies of genetic risk prediction of common diseases. The methodological studies involved the evaluation of traditional and new methods of model performance, the evaluation of rare variants for risk prediction of common diseases, the assessment of simulations strategies for replication of empirical data, and the evaluation of reporting in empirical risk prediction studies. The empirical studies involved the evaluation of direct-to-consumer (DTC) genetic tests, the external validation of genetic risk prediction models across European samples, and the evaluation of differences in prediction performance in published genetic risk prediction models. Both simulated and empirical data were used to conduct these studies. By means of simulation, a population distribution of genetic variants was created starting from the effect size and frequency of individual variants and assuming that genetic variants are inherited independently and that their joint effects follow a multiplicative risk model. The empirical data came from the Rotterdam study, a prospective, population-based, cohort study among 7,983 inhabitants of a Rotterdam suburb, designed to investigate determinants of chronic diseases; and from a community-based cohort i.e., the combination of Atherosclerosis Risk in Communities Study, Cardiovascular Health Study and Framingham Heart Study.