Miracle-dz/UniFAR-FTUs huggingface dataset:
High output triboelectric nanogenerator based on scotch tape for self-powered flexible electrics

ABSTRACT The development of wearable electronics has attracted wide publicity. However, conventional batteries will face environmental pollution and cyclic charging. In this work, we report a novel washable textile triboelectric nanogenerators (WT-TENG) based on the transparent tape film and the polytetrafluoroethylene (PTFE) film. The WT-TENG can still maintain stable output performance after being cleaned for many times. Meanwhile, due to the high hydrophobicity of the triboelectric materials, the WT-TENG has good humidity resistance. According to the results, the maximum Voc and Isc of WT-TENG (size: 3 cm × 3 cm) can reach 378 V and 63.6 µA, respectively. And the maximum output power can arrive at 3.325 mW. The WT-TENG can be directly used to drive some commercial light-emitting diodes (LEDs). With good stability, WT-TENG can harvest human motion mechanical energy. We think our work can open a new path for expanding self-powered wearable electronics.
Auroral Image Classification With Deep Neural Networks

Results from a study of automatic aurora classification using machine learning techniques are presented. The aurora is the manifestation of physical phenomena in the ionosphere‐magnetosphere environment. Automatic classification of millions of auroral images from the Arctic and Antarctic is therefore an attractive tool for developing auroral statistics and for supporting scientists to study auroral images in an objective, organized, and repeatable manner. Although previous studies have presented tools for detecting aurora, there has been a lack of tools for classifying aurora into subclasses with a high precision (>90%). This work considers seven auroral subclasses: breakup, colored, arcs, discrete, patchy, edge, and faint. Six different deep neural network architectures have been tested along with the well‐known classification algorithms: k‐nearest neighbor (KNN) and a support vector machine (SVM). A set of clean nighttime color auroral images, without clearly ambiguous auroral forms, moonlight, twilight, clouds, and so forth, were used for training and testing the classifiers. The deep neural networks generally outperformed the KNN and SVM methods, and the ResNet‐50 architecture achieved the highest performance with an average classification precision of 92%.
Prediction and Context Awareness in Agriculture: A Systematic Mapping

The advances in sensorial technology and its use in agriculture have been contributing to the acquisition and analysis of data regarding agricultural production. Studies propose the use of sensors to monitor production or even the use of cameras to obtain crop information, providing data, reminders, and alerts to farmers. Through the obtainment and analysis of these data, context awareness can be used to improve systems, mainly through the prediction techniques applied to agriculture. This article presents a systematic mapping of studies that use prediction and context awareness in agriculture. During the mapping, 10206 articles were initially identified and, after filtering by inclusion and exclusion criteria, 42 articles were selected. The results indicated that 35.7% (15/42) of the studies used one or more prediction techniques and 45.2% (19/42) used image processing through pictures of cameras to obtain information regarding planting. 23 sensors with different functionalities were found, those have been used in the collection of data for context formation in agriculture.
An empirical study of the Volkswagen recall crisis in China: Customer's risk perceptions and behavior responses based on an information flow

ABSTRACT Product-harm crises usually lead to product recalls, which would attract extensive public concern on the issue of product defects, but it is not yet clear how product recalls influence customers' risk perceptions and behavior responses. In this study, guided by the protective action decision model (PADM) and the heuristic-systematic model (HSM), and through an empirical study involving 467 participants drawn from the customers of Volkswagen, a conceptual model of information flow was developed, which starts from individuals' product experience, strengthening or weakening through information seeking and processing, then directly acts on the risk perception, and ultimately influences protective actions. By using structural equation modeling to test the model, and the results shown that customers' information need, seeking, and processing are significantly related to risk perception, their behavioral intentions (loyalty or boycott) are also significantly influenced by risk perception and product experience. Next, multiple-group analysis is employed to compare the distinctions between two groups of customers (those whose cars belong to the recall, and those not belonging to the recall). Unexpectedly, the role of information processing in the recall group is weaker than that in the not recalled group. At last, theoretical and practical implications and suggestions for further research are also discussed.
Parartemiopsis longicornis (Smirnov), senior synonym of P. mongolica Rogers (Crustacea: Branchiopoda: Anostraca), with remarks on the validity of the genus

Parartemiopsis mongolica Rogers, 2005 was described on the basis of two male specimens from Mongolia. Subsequent to publication, it was demonstrated that this taxon had previously been described as Chirocephalus longicornis (Smirnov, 1930). However, a comparison between the male genitalia of C. longicornis and those of other Chirocephalus species, as well as Artemiopsis, demonstrates that the genus Parartemiopsis Rogers, 2005 is still valid. Therefore, the correct name for this taxon is Parartemiopsis longicornis (Smirnov, 1930).
Hollow fibre membrane bioreactor functionalized with GO‐cryogel 3D matrix promotes liver cell anchoring and their functional maintenance

The extracorporeal bioartificial liver (BAL) support system with hepatocytes is one of the promising therapeutic approaches for acute liver failure patients to assist in the liver transplantation or facilitate the liver to regenerate (Zhang et al., 2014). The main features to improve the BAL include cell source, sustaining hepatocytes functions and efficient bioreactor design. Scarcity of human liver cells and their restricted ability to proliferate in vitro attract a better cell culture environment that can improve the primary cell expansion, immortalized cell lines or stem cell differentiation of stem cells. Thus, the combined features of the hepatocytes microenvironment and the design of the bioreactor can result in efficacious and scalable liver-centric functions (Allen & Bhatia, 2002). In tissue engineering, a three-dimensional (3D) matrix maintaining functional cells is a potential in vitro biomimetic system. In vitro system is preferred over in vivo models because it offers several advantages, which include evaluation of toxicity mechanism, analysis of drug response relationship, requires a minimal amount of a drug for accessible and direct screening, less expensive and time-saving. Immunoisolation is also an important aspect of BAL. There are different ways of immunoisolation, each offering its advantages DOI: 10.1002/mds3.10128
A Review of Physical Human Activity Recognition Chain Using
 Sensors

In the era of Internet of Medical Things (IoMT), healthcare monitoring has gained a vital role nowadays. Moreover, improving lifestyle, health behavior, and decreasing the chronic diseases are urgently required. However, tracking and monitoring critical events of elderly and patient people is a great challenge. Healthcare services for those people are crucial in order to achieve high safety consideration. Physical human activity recognition using wearable devices is used to monitor and recognize human activities for elderly and patient populations. The main aim of this review study is to highlight the human activity recognition chain, which includes, sensing technologies, preprocessing and segmentation, feature extractions methods, and classification techniques. Challenges and future trends are also highlighted. In the era of Internet of Medical Things (IoMT), healthcare monitoring has gained a vital role nowadays. Moreover, improving lifestyle, health behavior, and decreasing the chronic diseases are urgently required. However, tracking and monitoring critical events of elderly and patient people is a great challenge. Healthcare services for those people are crucial in order to achieve high safety consideration. Physical human activity recognition using wearable devices is used to monitor and recognize human activities for elderly and patient populations. The main aim of this review study is to highlight the human activity recognition chain, which includes, sensing technologies, preprocessing and segmentation, feature extractions methods, and classification techniques. Challenges and future trends are also highlighted.
A Lagrangian meshfree mesoscale simulation of powder bed fusion additive manufacturing of metals

We present a powder‐scale computational framework to predict the microstructure evolution of metals in powder bed fusion additive manufacturing (PBF AM) processes based on the hot optimal transportation meshfree (HOTM) method. The powder bed is modeled as discrete and deformable three‐dimensional bodies by integrating statistic information from experiments, including particle size and shape, and powder packing density. Tractions in Lagrangian framework are developed to model the recoil pressure and surface tension. The laser beam is applied to surfaces of particles and substrate dynamically as a heat flux with user‐specified beam size, power, scanning speed, and path. The linear momentum and energy conservation equations are formulated in the Lagrangian configuration and solved simultaneously in a monolithic way by the HOTM method to predict the deformation, temperature, contact mechanisms, and fluid‐structure interactions in the powder bed. The numerical results are validated against single track experiments. Various powder bed configurations, laser powers, and speed are investigated to understand the influence of dynamic contact and inelastic material behavior on the deformation, heat transfer, and phase transition of the powder bed. The formation of defects in the microstructure of 3D printed metals, including pores, partially, and unmelted particles, is predicted by the proposed computational scheme.
Healthier or bigger? Trade‐off mediating male dimorphism in the black scavenger fly Sepsis thoracica (Diptera: Sepsidae)

1. Life history trade‐offs emerge when limited resources are allocated to multiple functions of an organism. Under highly competitive conditions trade‐offs can result in alternative phenotypes that differ morphologically and physiologically. Such is the case in insect species that grow under high densities, where competition for resources but also the risk of disease contagion is high, prompting important adjustments in immune response and melanic cuticular pigmentation, with consequent sacrifices in other fitness‐related traits.
A Consistent Nonparametric Test for Granger Non-Causality Based on the Transfer Entropy

To date, testing for Granger non-causality using kernel density-based nonparametric estimates of the transfer entropy has been hindered by the intractability of the asymptotic distribution of the estimators. We overcome this by shifting from the transfer entropy to its first-order Taylor expansion near the null hypothesis, which is also non-negative and zero if and only if Granger causality is absent. The estimated Taylor expansion can be expressed in terms of a U-statistic, demonstrating asymptotic normality. After studying its size and power properties numerically, the resulting test is illustrated empirically with applications to stock indices and exchange rates.
Lower-order smoothed objective penalty functions based on filling properties for constrained optimization problems

In this article, a class of lower-order smoothed objective penalty functions is introduced to find locally optimal points for constrained optimization problems. The exactness of the new penalty functions is studied. Based on the current locally optimal points, a new class of penalty functions based on filling properties is proposed. This new penalty function can be used to find a better locally optimal point. The exactness and filling properties of this penalty function are proved in this paper. To do this, two algorithms are presented to find the locally and globally optimal points. Additionally, their convergence is proved under some mild conditions. Finally, numerical results are included to illustrate the applicability of the local and global optimization algorithms.
Role of Microglial α7 Nicotinic Acetylcholine Receptor Positive Allosteric Modulator in Neuroinflammatory Pain Models in Mice

ROLE OF MICROGLIAL α7 NICOTINIC ACETYLCHOLINE RECEPTOR POSITIVE ALLOSTERIC MODULATOR IN NEUROINFLAMMATORY PAIN MODELS IN MICE MUZAFFAR ABBAS 2016 Neuroinflammatory pain affects about 1.5% of the United States population. Around 20-40% patients having neurological disorders are affected with neuroinflammatory pain. As a part of the limbic system, hippocampus is known to play a critical role in pain perception and processing, and is densely populated with microglial cells and α7 nicotinic acetylcholine receptors (nAChRs). Given the role of microglial α7 nAChRs in neuroinflammation, the α7 nAChRs have emerged as potential target for neuroinflammatory pain treatment. We hypothesized that microglial α7 nAChRs positive allosteric modulation in the hippocampus will decrease neuroinflammatory pain at behavioral, cellular, biochemical, and molecular level. The primary objective of current study was to examine the role of an α7 nAChR positive allosteric modulator (PAM), TQS, in neuroinflammatory pain and to determine biochemical, cellular, and molecular mechanisms associated with neuroinflammatory pain in the hippocampus using mouse models. We demonstrated that TQS reduced neuroinflammatory pain-like symptoms, including tactile allodynia and thermal hyperalgesia in mice. Methyllcaconitine, an α7 nAChR antagonist, reversed antiallodynic and antihyperalgesic effects of TQS suggesting the involvement of α7 nAChR. The TQS decreased the expression of ionized calcium-
Radiomics-Based Prediction of Overall Survival in Lung Cancer Using Different Volumes-Of-Interest

Lung cancer accounts for the largest amount of deaths worldwide with respect to the other oncological pathologies. To guarantee the most effective cure to patients for such aggressive tumours, radiomics is increasing as a novel and promising research field that aims at extracting knowledge from data in terms of quantitative measures that are computed from diagnostic images, with prognostic and predictive ends. This knowledge could be used to optimize current treatments and to maximize their efficacy. To this end, we hereby study the use of such quantitative biomarkers computed from CT images of patients affected by Non-Small Cell Lung Cancer to predict Overall Survival. The main contributions of this work are two: first, we consider different volumes of interest for the same patient to find out whether the volume surrounding the visible lesions can provide useful information; second, we introduce 3D Local Binary Patterns, which are texture measures scarcely explored in radiomics. As further validation, we show that the proposed signature outperforms not only the features automatically computed by a deep learning-based approach, but also another signature at the state-of-the-art using other handcrafted features.
Impact of Proliferator-Activated Receptor γ Gene Polymorphisms on Risk of Schizophrenia: A Case-Control Study and Computational Analyses

Objective: Schizophrenia (SCZ) is a common psychiatric disorder characterized by a complex mode of inheritance. Peroxisome proliferator-activated receptor-γ (PPARG) mainly regulates lipid and glucose metabolisms while it is constitutively expressed in rat primary microglial cultures. This preliminary study was aimed to investigate the relationship of two polymorphisms in the PPARG gene, rs1801282 C/G, and rs3856806 C/T, to the risk of SCZ in the southeast Iranian population. Method : A total of 300 participants (150 patients with SCZ and 150 healthy controls) were enrolled. Genotyping was done using the amplification refractory mutation system polymerase chain reaction (ARMS–PCR) technique. Computational analyses were carried out to predict the potential effects of the studied polymorphisms. Results: A significant link was found between genotypes of rs1801282 and SCZ susceptibility. The G allele of rs1801282 in CG and GG form of the codominant model increased the risk of SCZ by 2.49 and 2.64 folds, respectively. With regards to rs3856806, enhanced risk of SCZ was also observed under different inheritance models except for the overdominant model. Also, the T allele of rs3856806 enhanced the risk of SCZ by 3.19 fold. Computational analyses predicted that rs1801282 polymorphism might alter the secondary structure of PPARG-mRNA and protein function. At the same time, the other variant created the binding sites for some enhancer and silencer motifs. Conclusion: Our findings showed that PPARG rs1821282 and rs3856806 polymorphisms associate with SCZ susceptibility. Replication studies in different ethnicities with a larger population are needed to validate our findings.
Meta-analysis on the Relationship between Parenting Style and Personality of Chinese College Students

There have been many studies on the relationship between parenting style and personality characteristics of college students, and there are many inconsistent conclusions on the direction and intensity of the correlation. In order to explore the relationship between parenting style and personality of college students in China, this systematic review and meta analysis included 12 studies with 4,984 college students. Results showed that: 1) Positive parenting style was significantly negatively correlated with neuroticism and positively correlated with extraversion; 2) Negative parenting style was significantly positively correlated with psychoticism and negatively correlated with neuroticism. Parenting style can significantly influence college students’ personality.
Leadership Styles and Customer Loyalty: A Lesson from Emerging Southeast Asia’s Airlines Industry

This study provides the empirical testing to test the influences of contemporary leadership styles (i.e., transactional and transformational) on job satisfaction and customer satisfaction as the mediating variable between job satisfaction and customer loyalty. The approach utilized in this study was a quantitative research design using a survey model. The participants of this study were recruited from 160 front-liners in the airline’s industry in Indonesia. This study employed 160 front liners (flight attendants, reservation/ticketing, and check-in-counter officers) who worked in Branch Office/General Sales Agent of Indonesian commercial airlines. The studied airlines serve domestic routes based at Soekarno-Hatta International Airport. Furthermore, the data were examined the four developed hypotheses by using Structural Equation Modeling (SEM). The primary results are: First, in the context of job satisfaction, both leadership styles (i.e., transactional and transformational) have similar influences; Second, job satisfaction affects customer satisfaction positively and significant, Third, customer loyalty is driven by passengers’ satisfaction when they are utilizing the airline services. The findings imply that the working-role encouragement is essential to maximize the productivity of front-liners to serve their customer well. This research supports on developing the general knowledge based on leadership styles in the context of the airline’s industry in managing the human resources strategically.
An Experimental and Characteristic Study of Abaca Fiber Concrete

The natural fibers can be an effective material to reinforce in concrete to improvedurability and strength, more compared to effect of synthetic materials on concrete. This study states about the effect of concrete with abaca fiber. The specimens of concrete were cast with the addition of 0.5, 1.0 and 1.5% of abaca fiber and the respective tests were carried out on 7, 14 and 28 days of healing to assess compressive strength, split tensile strength, flexural strength and impact strength. The addition of super plasticizer along with the fiber helped in reducing the water content to match the highwater absorption capability of the fiber in the concrete. Among the above mentioned fiber percentage added to the concrete, it was observed that 0.5% gives the maximum compressive strength, which concludes to be the optimum percentage of abaca fiber addition. Optimum percent of abaca fiber was achieved with the split tensile strength, flexural strength and impact strength. Scanning electron microscope and X-ray diffraction analysis was conducted on reinforced concrete with 0.5 percent abaca fiber to test the picture structure and elementary concrete composition.
The accuracy of a mobile phone application (Wulira app) compared to standard audiometry in assessing hearing loss among patients on treatment for multidrug-resistant tuberculosis in Uganda

OBJECTIVES: Our aim was to validate the “Wulira App” a mHealth application against gold standard audiometry as a pragmatic audiometry solution for under-served and vulnerable groups of patients at risk of hearing loss. The specific objectives were as follows: To compare hearing thresholds determined using the Wulira app to standard pure tone audiometry among patients on MDR-TB treatment. To determine the correlation between the measured hearing loss with the Wulira app and standard audiometry with patient reported hearing loss. To determine the proportion of patients on MDR-TB treatment that experience hearing loss? MATERIALS AND METHODS: We consecutively recruited patients ≥18 years old and receiving kanamycin in their treatment regimen between February and June 2019 for this study. Clinical and demographic data were obtained from each participant and documented in a secure database. Participants had hearing assessment performed once at enrolment with paired standard audiometry and the Wulira mobile phone app in a soundproof room. RESULTS: A total of 120 MDR-TB patients with a mean age of 34.0 (±9.6) years were recruited for this study and 69 (57.5%) were male. When compared to pure tone audiometry, the Wulira app was able to correctly detect 91.4% hearing loss in right ear and 88.4% in the left ear. The specificity of the Wulira app was equally high, reaching 93.2% in the right ear and 91.5% in the left ear. CONCLUSION: The Wulira app may be a useful alternative home-based tool for hearing assessment in MDR-TB patients, essentially for early detection of hearing loss following commencement of second-line injectable drugs.