Miracle-dz/UniFAR-FTUs huggingface dataset:
University of Groningen Uni-mode and partial uniqueness conditions for Candecomp/Parafac of three-way arrays with linearly dependent loadings. Guo,

In this paper, three sufficient conditions are derived for the three-way CANDECOMP/PARAFAC (CP) model, which ensure uniqueness in one of the three modes (“uni-modeuniqueness”). Based on these conditions, a partial uniqueness condition is proposed which allows collinear loadings in only one mode. We prove that if there is uniqueness in one mode, then the initial CP model can be uniquely decomposed in a sum of lower-rank tensors for which identifiability can be independently assessed. This condition is simpler and easier to check than other similar conditions existing in the specialized literature. These theoretical results are illustrated by numerical examples.
Total Antioxidant Activity And Phenolic Compound Of Some Roasted Food

Background: Roasting was found to affect the antioxidant and total phenolic content of food materials due to the formation of Maillard reaction products. Objective: The effect of roasting on phenolic compounds and antioxidant activities in roasted White yam, Groundnut, yellow maize and Plantain were investigated. Methods: The antioxidant capacity was determined in methanol extracts of roasted food samples using the stable radical DPPH⋅ (2,2-diphenyl-1-picrylhydrazyl) and the total polyphenols were quantified using the colorimetric method of Folin–Ciocalteau. Result: The total phenolic content (Folin Ciocalteu assay) and the free radical-scavenging activity (DPPH) were present in the roasted food samples. The roasting process did not reduce the total phenolic content significantly compared to the raw samples (p>0.05). However, roasting reduced the DPPH activity by approximately in the roasted food samples. Conclusion: In the present study a good correlation was recorded between TPC and radical scavenging capacity (r2=0.934) as well as TPC versus % inhibition of linoleic acid peroxidation (r2=0.849).
MENDELU Working Papers in Business and Economics

Jaroslav Bukovina: Sentiment of a society and large-cap stock liquidity. The impact of sentiment in the sample of small and young companies due to higher transaction and information costs is a generally agreed notion. On the contrary, such impact is less likely in the sample of large-cap stock companies. However, this paper goes beyond this notion and shows that we can study the influence of sentiment even at the level of large-cap companies due to the following reasons. Firstly, the paper is unique by employment of social media Facebook data as a proxy for the sentiment of a society related to the individual corporation. Such data have a potential to provide deeper insights in a society's behavior. Secondly, the author proposes the volume of trade or liquidity as a variable which incorporates sentiment in a society better than stock returns. Empirical results confirm this prediction. Overall, the paper shows the existence of the negative link between sentiment in the society and volume of trade at the level of large-cap corporations.
Pre-Service Teachers’ Attitudes Towards Including Students with Moderate Learning Difficulties in Mainstream Schools in the Context of Kuwait

Inclusive education has become a global trend in the provision of services for students with disabilities. While attitudes towards inclusion have been studied widely in some countries, little research in this area has been conducted in Kuwait. This study responds to this need by researching pre-service teachers’ attitudes towards inclusive education. This study examined Kuwaiti pre-service teachers’ attitudes towards including students with Moderate Learning Difficulties (MLD) in general education classrooms. Questionnaires were distributed to 452 Kuwaiti pre-service male and female teachers at the College of Basic Education. Several factors, such as teachers’ knowledge, were found to be related to pre-service teachers’ attitudes towards inclusion. The results of the study indicated that, overall, Kuwaiti pre-service teachers hold positive attitudes towards inclusion.
mechaniSmS Of Strategic management bY State JOint StOcK cOmPanieS: the eSSence anD VariantS

IThe article analyzes the essence of the mechanisms of strategic management of state-owned joint-stock companies in the modern market economy. For this purpose, the main approaches to the definitions of “strategic management”, “management mechanism”, as well as generalized views of domestic and foreign researchers regarding the functions of strategic management are investigated. Taking into account the fact that in state-owned joint-stock companies the subject of management act as authorized bodies of state power, which carry a long-term influence on the indicated companies, it is proved that under the integrated mechanism of strategic management of state-owned joint stock companies it is appropriate to understand the system of practical influence of state authorities on the development of joint stock companies public sector companies of the economy in order to coordinate and achieve the long-term goals of the main stakeholders of the partnership, in particular the state-Accident. It is determined that the mechanisms of strategic management of state joint stock companies can be classified according to various features, but their mechanisms of strategic management on a functional basis are the important kind of
Bias in data‐driven artificial intelligence systems—An introductory survey

Artificial Intelligence (AI)‐based systems are widely employed nowadays to make decisions that have far‐reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well‐grounded in a legal frame. In this survey, we focus on data‐driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth.
Investigating firms' involvement in corporate social irresponsibility: Are family owned MNEs better corporate citizens?

This paper aims at investigating how multiple antecedents of multinational enterprises (MNEs) involvement in Corporate Social Irresponsibility (CSIR) act in unison and create complex situations that are difficult to capture with a linear logic. To this end, we use fuzzy set qualitative comparative analysis (fsQCA) and find five configurations of antecedents leading to high levels of CSIR occurrence: (1) The resource-constrained MNE - a highly internationalized MNE, operating in high corruption host markets, facing low performance volatility, with low slack resources, which does not adopt Corporate Social Responsibility (CSR) policies; (2) The disinterested MNE – a lowly internationalized MNE, operating in low corruption host markets, facing low performance volatility, with high slack resources, which does not adopt CSR policies; (3) The calculated family MNE - a lowly internationalized family MNE, operating in high corruption host markets, facing high performance volatility, with high slack resources, which does not adopt CSR policies; (4) The resource-constrained family MNE - a lowly internationalized family MNE, operating in high corruption host markets, facing high performance volatility, with low slack resources, which adopts CSR policies; (5) The overreacting, decoupling family MNE – a lowly internationalized family MNE, operating in low corruption host markets, facing high performance volatility, with high slack resources, which adopts CSR policies.
'New Age' Preferential Trade Agreements (PTAs): Implications for Value Added Trade

The global economy witnessed an exceptional rise in the number and scope of PTAs, over the past 25 years. Their scope has been deepening, with inclusion of provisions such as investment, competition, services, IPRs etc as well as unprecedented participation by emerging economies. These 'deeper' PTAs are more desirable for developing nations as they act as a commitment device for them to lock-in domestic reforms and streamline their regulations and institutions to global standards. Alongside this proliferation, is another phenomenonthe emergence of international production networks (IPNs) and global value chains (GVCs), as firms have fragmented their production process across geographies. With the rising significance of GVCs, 'deeper integration' assumes importance. PTAs can play a significant part in standardizing rules and regulations across members since addressing 'behind the border measures' is easier in such preferential arrangements than through multilateral negotiations. However, there is a scarcity of studies analyzing the impact of PTAs on trade flows, taking into account its content as per the provisions of the agreement. Further, most studies, assess the impact of PTAs on gross trade flows and not on intermediate trade flows and trade in value added, thus not measuring the extent of GVC and IPN participation of countries. We aim to address aforementioned gaps by empirically assessing the impact of 'deeper PTAs' on intermediate trade flows, trade in value added at aggregated as well as disaggregated level for the automotive and textiles sector, using an augmented gravity equation, based on an extensively constructed panel dataset of trade in value added and PTAs.
Coursework on detection of objects in scenes using machine learning

In this paper, an algorithm for detection and classification of objects on the image is presented. It is based on supervised machine learning technique (SVM). An input image is separated into segments that are considered to be objects. So the problem reduces to the classification of those segments. Each of them is represented as a feature vector which components has been chosen in a way to be well discriminative. Vectors that correspond to the test data are fed to the input of the SVM classifier that was previously trained using pre-labeled vectors.
Isolation, Identification and Characterization of Bacillus subtilis CF-3, a Bacterium from Fermented Bean Curd for Controlling Postharvest Diseases of Peach Fruit

Biological control is an alternative to synthetic fungicides to avoid postharvest diseases which limit the storage period and marketing life of fruit and vegetables. Present investigation is focused on the isolation, identification and characterization of Bacillus subtilis CF-3 from fermented bean curd through the analyses of phenotype, physiological and biochemical characterization, 16S rDNA gene sequence based on its biocontrol effect against pathogens (Monilinia fructicola, Cephalothecium, Rhizoctonia and Alternaria) causing peach decay. With treatment of CF-3, the ratio of good fruit was 65% which was higher than 30% in the control group significantly after 36d storage at 10°C and 65% compared with 50% in the control group after 7d storage at 25°C;The optimal growth temperature and pH of CF-3 were 37°Cand 8;The results of antimicrobial stability indicated that CF-3’s antibiotics had good UV, pH and thermal stability (except at 121°C). Findings of the present study suggested that the antifungal properties of CF-3 may have a potential to be developed as fungicide which can contribute to the postharvest preservation of peach fruit and provide a theoretical basis for the further study of biological control.
Whitepaper Bluetooth Angle Estimation for Real-Time Locationing

Bluetooth Angle of Arrival (AoA) and Angle of Departure (AoD) are new technologies that establish a standardized framework for indoor locationing. With these technologies, the fundamental problem of locationing comes down to solving the arrival and departure angles of radio frequency signals. In this paper, we explain the basics of these technologies and give some theory for estimating direction of arrival.
Effect of Bainite Volume Fraction on Fatigue Properties of Bainite/Martensite Dual Phase EA4T Steel

Bainite/martensite dual phase EA4T steel with bainite volume fraction ranging from 21% to 70% was prepared by a process of isothermal quenching with the variation of isothermal holding time. Tensile tests and tensioncompression fatigue tests were conducted to investigate the effect of bainite volume fraction on tensile properties and fatigue damage behavior of the steel. The results show that fatigue strength varied in a quadratic relation with its tensile ultimate strength, and the specimens with bainite volume fraction of 49% have the highest fatigue strength and the best synergy of strength and ductility, which is contributed by the smaller hardness difference between bainite and martensite, better coordination of plastic deformation and higher fatigue crack propagation resistance of the specimens.
False Alarm Reduction in Self-Care by Personalized Automatic Detection of ECG Electrode Cable Interchanges

Introduction False alarm reduction is an important challenge in self-care, whereas one of the most important false alarm causes in the cardiology domain is electrodes misplacements in ECG recordings, the main investigations to perform for early and pervasive detection of cardiovascular diseases. In this context, we present and assess a new method for electrode reversals identification for Mason-Likar based 3D ECG recording systems which are especially convenient to use in self-care and allow to achieve, as previously reported, high computerized ischemia detection accuracy. Methods We mathematically simulate the effect of the six pairwise reversals of the LA, RA, LL, and C2 electrodes on the three ECG leads I, II, and V2. Our approach then consists in performing serial comparisons of the newly recorded 3D ECG and of the six derived ECGs simulating an electrode reversal with a standard, 12-lead reference ECG by means of the CAVIAR software. We further use a scoring method to compare these analysis results and then apply a decision tree model to extract the most relevant measurements in a learning set of 121 patients recorded in ICU. Results The comparison of the seven sets of serial analysis results from the learning set resulted in the determination of a composite criteria involving four measurements of spatial orientation changes of QRS and T and providing a reversal identification accuracy of 100%. Almost the same results, with 99.99% of sensitivity and 100% of specificity, were obtained in two test sets from 90 patients, composed of 2098 and 2036 representative ECG beats respectively recorded during PTCA balloon inflation, a procedure which mimics ischemia, and before PTCA for control. Conclusion Personalized automatic detection of ECG electrode cable interchanges can reach almost the maximal accuracy of 100% in self-care, and can be performed in almost real time.
Media Crate: A Tangible Interface for Live Media Production

Live media production – the presentation of audio-visual content at events such as conferences and concerts – is a high intensity task where a small production team must interact with an amalgamation of separate hardware tools to transform and direct a variety of media sources to outputs such as large screens, preview monitors, and web-casts. We present Media Crate, a tangible tabletop interface crafted in response to the key actions and needs of live media producers. In this poster we give a description of the Media Crate’s interface, from conception to evaluation, through construction. We also discuss how our experience of live media production impacted on the design.
Prompting Prosocial Human Interventions in Response to Robot Mistreatment

Inspired by the benefits of human prosocial behavior, we explore whether prosocial behavior can be extended to a Human-Robot Interaction (HRI) context. More specifically, we study whether robots can induce prosocial behavior in humans through a 1x2 between-subjects user study (N = 30) in which a confederate abused a robot. Through this study, we investigated whether the emotional reactions of a group of bystander robots could motivate a human to intervene in response to robot abuse. Our results show that participants were more likely to prosocially intervene when the bystander robots expressed sadness in response to the abuse as opposed to when they ignored these events, despite participants reporting similar perception of robot mistreatment and levels of empathy for the abused robot. Our findings demonstrate possible effects of group social influence through emotional cues by robots in human-robot interaction. They reveal a need for further research regarding human prosocial behavior within HRI. CCS Concepts •Human-centered computing→ Empirical studies in HCI; Empirical studies in collaborative and social computing ACM Reference Format: Joe Connolly, Viola Mocz, Nicole Salomons, Joseph Valdez, Nathan Tsoi, Brian Scassellati, and Marynel Vázquez. 2020. Prompting Prosocial Human Interventions in Response to Robot Mistreatment. In Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’20), March 23–26, 2020, Cambridge, United Kingdom. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/3319502.3374781
Screening for Cardio-Metabolic Risk Factors Among Student Nurses: A Cross-Sectional Study

Non-communicable diseases are a growing public health phenomenon in both developed and developing countries. This study examines the prevalence and correlates of cardio-metabolic risk factors among student nurses at a nursing college in East London, South Africa. The WHO STEPwise standardized questionnaire was used to collect information on socio-demographic data and behavioural characteristics (smoking, alcohol consumption, physical inactivity, and dietary intake) of 228 nursing students. Height, weight, waist circumference, blood pressure and fasting blood glucose were measured. The prevalence of overweight, obesity pre-diabetes and diabetes was 33%, 44%, 6% and 7%, respectively. Pre-hypertension and hypertension occurred in 44% and 11%, respectively. Female gender and increasing age were independent predictors of obesity. In the logistic regression model analysis, participants who were above 35 years [AOR=9.12, CI 3.37-24.68, p<0.000], female [AOR=4.10, CI 1.94-8.64, p=0.000], and do not meet the WHO sport criteria of physical activity participation [AOR=2.11, CI=1.10-4.07, p=0.025] had the likely odds of obesity. Interventions targeting physical activity and healthy lifestyle behavioural programmes to promote the health and wellness of the nursing students would improve the metabolic health of the nurses in the setting.
Study of Pap smear in Diabetic Patients

The infections of the genital tract are common in reproductive-age women and the associated cost is significant. Diabetes mellitus is commonly considered a predisposing factor for recurrent vulvovaginal candidiasis. Hyperglycemia enhances the ability of C. albicans to bind to vaginal epithelial cells. We analyse the prevalance of correlation of inflammation and Candida in particular in papsmear in women with diabetes mellitus in comparison to normal nondiabetic women. A retrospective study was carried out in Sree Balaji Medical College in which pap smears were reviewed in 100 non pregnant women enrolling for WOMEN CARE CHECK-UP.The study was carried out in 33 diabetic and 67 normal healthy women as controls,all in age range between 28-66 years. Inflammatory changes were seen both in diabetic and non diabetic women . Prevalance of candida was found to be more in diabetic women as compared to non diabetic women which was found to be statistically significant. Diabetes mellitus has been considered as one of the factors causing Candida vaginitis . It is mandatory to do periodic papsmear review for all diabetic females for early diagnosis and effective treatment of candidiasis.
A Quantile Regression Approach on Indian Adolescents

Least square estimation has typically been used in malnutrition research to determine the average relationship of particular household characteristics on a child’s height-for-age z-score. Results are similar across studies, not only in terms of size of coefficients but also in statistical significance. This study discusses the possibility that some of the observed variations in the estimated malnutrition status of a child may reflect the fact that the effect of these characteristics are not the same across a given distribution. To examine this issue, I employed a quantile regression on Young Lives panel data, with two birth cohorts of children of the same age in the Indian state of Andhra Pradesh. Although the constant catch-up effect along the distribution of HAZ could be rejected, the lower end of the quantile indicated a partial catch-up effect in children’s past nutritional deficiency. The results suggest no improvement in malnutrition recovery across the two birth cohorts.
Understanding the Performance of Small Convolution Operations for CNN on Intel Architecture

Convolution layers are prevalent in many classes of deep neural networks, including Convolutional Neural Networks (CNNs) which provide state-of-the-art results for tasks like image recognition, natural language processing, and speech recognition. The computationally expensive nature of a convolution operation has led to the proliferation of implementations including matrix-matrix multiplication formulation, FFT-formulation, Winograd transformation, and direct convolution primarily targeting GPUs. In this paper, we optimize a direct convolution and Winograd implementation for x86 architectures, in particular for XeonPhi systems, via a dynamic compilation approach. We then show how these JIT optimizations can be integrated in a high-level domain-specific language setting. We shed light on what is possible and what is not possible based on different data-formats and blocking techniques. Our JIT-based Ninja implementation shows close to theoretical peak results on modern x86 architectures, depending on setting and the CPU architecture at hand.