Miracle-dz/UniFAR-FTUs huggingface dataset:
THE ADAPTATION STUDY OF THE Q-SPORT-14 SCALE FOR THE PRIVATE SPORT ESTABLISHMENTS

Amac: Q-SPORT-14 olceginin ozel spor isletmelerinin hizmet kalitesinin olculebilmesi icin uyarlanmasi bu calismanin amacini olusturmaktadir. Materyal ve Yontem: “Q-SPORT 14” olceginin orjinali “Q-SPORT 10” adi ile Rial ve digerleri (2010) tarafindan gelistirilmistir. Yildiz (2011) olcegin gecerlik ve guvenirlik calismasini yaparak olcegi Turkceye uyarlamis ve olcegi “Q-SPORT 14” olarak adlandirmistir. Calismada Toplam 585 olcek uygulamasi yapilmis, bu olceklerin 103 adeti yanlis veya eksik isaretlemelerden dolayi goz ardi edilmistir. Calisma, faktor analizi, dondurulmus bilesen matriks testi, KMO ve Barlet Sphericity testi, anti-imaj korelasyon testi ve guvenirlik analizleri uygulanarak gerceklestirilmistir. Anlam duzeyi p<0,05 kabul edilmis ve guven araligi %95 olarak alinmistir. Bulgular: Orneklem buyuklugunun uygunlugu icin gerceklestirilen KMO testi Cronbach’s alpha degeri 0,905 olarak tespit edilmistir. Barlet Sphericity test puani p<0,01 duzeyinde anlamli tespit edilmistir. Toplam varyans aciklamasinda oz degeri 1’den buyuk 2 deger tespit edilmis, bu degerlerin toplam varyansa yaptigi katkinin %55 oldugu gozlemlenmis ve olcegin 2 alt boyuttan olustugu sonucuna ulasilmistir. Dondurulmus Bilesen Matriksi Testi sonucu tum maddelerin degerleri 0,5’ten buyuk tespit edilmis ve bu madderlerin; 9 madde “program ve egitmen kalitesi”, 5 madde ise “fiziksel cevre kalitesi” olmak uzere iki alt boyuta dagildigi gozlemlenmistir. Anti-imaj Korelesyon Testi sonucunda tum maddelerin 0,5’ten buyuk oldugu gozlemlenmistir. 2 alt boyuta ve tum maddelere uygulanan guvenirlik analizi sonucunda tum maddelerin duzeltilmis maddeler toplam korelasyon degerlerinin 0,3’ten buyuk oldugu ve madelerin silinmesi durumunda Cronbach’s alpha degerlerinin 0,7’den buyuk oldugu tespit edilmistir. Sonuclar: Tum bu analizler ozel spor isletmeleri icin Q-SPORT 14 olceginin yuksek derecede guvenilir ve kullanilabilir oldugunu gostermektedir.
Application of Walls to Landslide Control Problems

The evolution of tieback restraint systems is presented. Case histories describe current practices for tieback design and construction and give examples of how the requirements were met for stabilizing specific slides. Topics include geologic aspects of landslide control using walls, analysis of wall supports to stabilize slopes, evaluation of landslide properties, and slide control by drilled cantilever pier walls and tangent pile walls. Site investigations, laboratory tests, design procedures, and construction methods are described.
Effects of socioeconomic status and its components on academic achievement: evidence from Beijing-Shanghai-Jiangsu-Zhejiang (China)

ABSTRACT The relationship between socioeconomic status (SES) and academic achievement can both reflect the degree to which students’ academic achievement is affected by SES and reveal detailed information about educational equity in a country/economy. Based on PISA 2018 data, this study investigated the effects of SES and its components on student academic achievement at both the student and school levels in a population of 15-year-old students from Beijing-Shanghai-Jiangsu-Zhejiang (China). Results showed the following: (1) B-S-J-Z (China) students’ academic achievement was positively related to their family SES and school SES. (2) The effects of different SES components on academic achievement varied, and the most predictive variables were the father’s occupational status, the father’s level of education, and the mother’s occupational status. (3) School disciplinary climate was shown to moderate the effects of SES on academic achievement. Drawing on the research findings, this study suggested that the government should (1) further promote education equity with a primary focus on disadvantaged student groups; (2) improve the enrolment policy and increase the diversity of student backgrounds; (3) promote teacher professional development and continuously improve school effectiveness.
The Effects of Political Attitudes on Affective Polarization: Survey Evidence from 165 Elections

How do individual-level political attitudes influence affective polarization on a global scale? This article contributes to the debate on the social distance of party affect by testing a set of hypotheses in 165 elections across the world. With a sample of over 170,000 voters, the results of multilevel mixed-effects regressions demonstrate that ideological radicalism, political knowledge, and external efficacy substantively affect how voters see the main political parties in electoral disputes taking place in 52 countries from 1996 to 2019. Satisfaction with democracy, however, is context-dependent; it positively influences affective polarization only when generalized democratic satisfaction is low. Furthermore, I show that these correlations remain stable regardless of the operationalization of affective polarization—that is, based on two dominant parties and weighted for multiparty competition. These findings provide robust inputs to the study of party preferences and social distance in a cross-national longitudinal perspective.
Backscatter Protocols and Energy-Efficient Computing for RF-Powered Devices

RF-powered computers operate using energy they harvest from radio frequency (RF) signals. Compared to battery powered devices, they have the advantages of being small and long-lived as they do not need to carry an onboard energy-store, and they can be embedded inside objects, structures and even the human body. In this dissertation, I explore how we can build networks of RF-powered computers that support rich functionality across a range of RF environments. Towards this goal, I identify the key challenges to running programs on RF-powered computers, and argue that devices must adapt their behavior to match their task energy consumption to the available power. To demonstrate this approach, I formulate the task scheduling problem for one class of RF-powered devices (computational-RFIDs), and implement Dewdrop, an energy-aware CRFID runtime. By waking tags at the right times, Dewdrop can complete tasks that previously could not complete, and at close to their maximum rate given the power that the RF environment provides. The second challenge I tackle is how to build networks using backscatter communication. Backscatter signaling is an ultra-low power form of communication, but the simplicity needed to achieve such low power operation makes clients prone to interference. To understand how this challenge can be overcome, I use measurement and simulation results to explore the mechanisms by which interference impacts network performance. I then use these insights to develop a network design that mitigates interference and enables backscatter networks to scale well. Experimental results show that this design improves both coverage and capacity in a building-scale network compared to existing designs. This dissertation supports my thesis that RF-powered computers can support rich tasks in a variety of RF environments, and networks of such devices can scale to building-sized deployments. As technology advances, RF-powered devices will only decrease in size and increase in computational power and operational range. By demonstrating that they can also support rich functionality and be used to build building-scale networks, this dissertation demonstrates their potential to provide deeply embedded and long-lived sensing and computation.
Immunogenic and antigenic analysis of recombinant NSP1 and NSP11 of PRRS virus

Abstract Background Porcine reproductive and respiratory syndrome virus (PRRSV) is an enveloped RNA virus in the order Nidovirales, family Arteriviridae, genus Betaarterivirus. Antibodies against nonstructural proteins (NSPs) from this virus can be found in pigs starting 4 days postinfection and they remain detectable for several months. Objective The goal of this study was to evaluate the immunogenicity and antigenic properties of recombinant proteins NSP1 and NSP11 expressed in Escherichia coli cells, as well as to assess the neutralization activity that they elicit. Methods We obtained the complete ORF‐1 genes coding for NSP1 and NSP11 from PRRSV using the VR‐2332 strain. Cloning was performed with the pET23a(+) vector with a histidine tag (His6), linearized by restriction enzyme digestion; the expression of the NSP1 and NSP11 clones was induced in OverExpress C41(DE3) chemically competent cells. Recombinant proteins were used to generate hyperimmune sera and we perform serological assays to confirm neutralizing antibodies. Results The expressed recombinant NSP1 and NSP11 were found to be immunogenic when injected in pigs, as well as demonstrated higher specificity in recognition of antigen in field sera from pigs positive infected with PRRSV. Furthermore, both NSP1 and NSP11 recombinant proteins elicited PRRSV neutralizing antibodies. Conclusions In this study, we demonstrated the immune humoral response to NSP 1 and NSP11, and neutralizing‐antibody response to PRRSV VR2332 strain in sera from hyperimmunized pigs.
DEFER: Distributed Edge Inference for Deep Neural Networks

Modern machine learning tools such as deep neural networks (DNNs) are playing a revolutionary role in many fields such as natural language processing, computer vision, and the internet of things. Once they are trained, deep learning models can be deployed on edge computers to perform classification and prediction on real-time data for these applications. Particularly for large models, the limited computational and memory resources on a single edge device can become the throughput bottleneck for an inference pipeline. To increase throughput and decrease per-device compute load, we present DEFER (Distributed Edge inFERence), a framework for distributed edge inference, which partitions deep neural networks into layers that can be spread across multiple compute nodes. The architecture consists of a single “dispatcher” node to distribute DNN partitions and inference data to respective compute nodes. The compute nodes are connected in a series pattern where each node's computed result is relayed to the subsequent node. The result is then returned to the Dispatcher. We quantify the throughput, energy consumption, network payload, and overhead for our framework under realistic network conditions using the CORE network emulator. We find that for the ResNet50 model, the inference throughput of DEFER with 8 compute nodes is 53% higher and per node energy consumption is 63 % lower than single device inference. We further reduce network communication demands and energy consumption using the ZFP serialization and LZ4 compression algorithms. We have implemented DEFER in Python using the TensorFlow and Keras ML libraries, and have released DEFER as an open-source framework to benefit the research community.
Displacement Visualization at Flexible Interface: A Coordinate Correction Scheme Applicable to High-Accuracy Pressure Distribution Mapping

This article reports on the first direct observation of a lateral displacement when normal pressure is applied at a flexible contact interface, using our laboratory’s self-developed displacement visualization system. A coordinate correction scheme that does not depend on specific sensing nodes or sensing units is proposed for lateral displacement introduced pressure distribution mapping. The relative difference between the pressure distribution with or without coordinate correction is up to 6%. As an example of technical and engineering implementation, a schematic of an array design with a feasible manufacturing process is further raised and discussed. The proposed correction scheme provides a theoretical and analytical basis for a variety of high-accuracy measurements of pressure distribution and other physical fields at flexible contact interfaces. Potential applications are believed to be found in the fields of robot tactile, object contour recognition, and other applications that require high-accuracy pressure distribution measurements.
Risk and destination perceptions of Wuhan, China since the COVID-19 pandemic

ABSTRACT The COVID-19 outbreak has the world gripped by fear and panic with its high velocity of infection. Based on the first three months of the global pandemic centred in Asia, this study investigates the relationship between the perception of COVID-19 on consumers’ destination image towards Wuhan and China, and how risk perceptions and changes in destination image affect travel intention to the destinations. Findings illuminated that perceptions of COVID-19 do not have a direct effect on destination image. Instead, risk perception of travelling during the pandemic mediated its effects on the destination image of Wuhan and China. Theoretical and practical implications concerning the management of destination image for the recovery of tourism are discussed with future possibilities of this research.
Multi-Fingered In-Hand Manipulation with Various Object Properties Using Graph Convolutional Networks and Distributed Tactile Sensors

Multi-fingered hands could be used to achieve many dexterous manipulation tasks, similarly to humans, and tactile sensing could enhance the manipulation stability for a variety of objects. However, tactile sensors on multi-fingered hands have a variety of sizes and shapes. Convolutional neural networks (CNN) can be useful for processing tactile information, but the information from multi-fingered hands needs an arbitrary pre-processing, as CNNs require a rectangularly shaped input, which may lead to unstable results. Therefore, how to process such complex shaped tactile information and utilize it for achieving manipulation skills is still an open issue. This paper presents a control method based on a graph convolutional network (GCN) which extracts geodesical features from the tactile data with complicated sensor alignments. Moreover, object property labels are provided to the GCN to adjust in-hand manipulation motions. Distributed tri-axial tactile sensors are mounted on the fingertips, finger phalanges and palm of an Allegro hand, resulting in 1152 tactile measurements. Training data is collected with a data-glove to transfer human dexterous manipulation directly to the robot hand. The GCN achieved high success rates for in-hand manipulation. We also confirmed that fragile objects were deformed less when correct object labels were provided to the GCN. When visualizing the activation of the GCN with a PCA, we verified that the network acquired geodesical features. Our method achieved stable manipulation even when an experimenter pulled a grasped object and for untrained objects.
Oxidative stress promotes liver cancer metastasis via a PKA-activated RNF25/ECAD/YAP circuit

Loss of E-cadherin (ECAD), often caused by epigenetic inactivation, is closely associated with tumor metastasis. However, how ECAD is regulated in response to oxidative stress during tumorigenesis is largely unknown. Here we identify RNF25 as a new E3 ligase of ECAD, whose activation by oxidative stress leads to ECAD protein degradation in hepatocellular carcinoma (HCC). Loss of ECAD activates YAP, which in turn promotes the transcription of RNF25, thus forming a positive feedback loop to sustain the ECAD downregulation. YAP activation mitigates oxidative stress in detached HCC cells by upregulating antioxidant genes, protecting detached HCC cells from ferroptosis, resulting in anoikis resistance. Mechanistically, we found that protein kinase A (PKA) senses oxidative stress by redox modification in its β catalytic subunit (PRKACB) at Cys200 and Cys344, which increases its kinase activity towards RNF25 phosphorylation at Ser450, facilitating RNF25-mediated degradation of ECAD. Moreover, RNF25 expression is associated with HCC metastasis and depletion of RNF25 is sufficient to diminish HCC invasion and metastasis in vitro and in vivo. Together, these results identify a dual role of RNF25 as a critical regulator of ECAD protein turnover, promoting both anoikis resistance and metastasis, and PKA is a necessary redox sensor to enable this process. Our study provides mechanistic insight into how tumor cells sense oxidative stress signals to spread while escaping cell death.
Comparative Study of Supervised Machine Learning Algorithms on Thoracic Surgery Patients based on Ranker Feature Algorithms

Thoracic surgery refers to the information gathered for the patients who have to suffer from lung cancer. Various machine learning techniques were employed in post-operative life expectancy to predict lung cancer patients. In this study, we have used the most famous and influential supervised machine learning algorithms, which are J48, Naïve Bayes, Multilayer Perceptron, and Random Forest (RF). Then, two ranker feature selections, information gain and gain ratio, were used on the thoracic surgery dataset to examine and explore the effect of used ranker feature selections on the machine learning classifiers. The dataset was collected from the Wroclaw University in UCI repository website. We have done two experiments to show the performances of the supervised classifiers on the dataset with and without employing the ranker feature selection. The obtained results with the ranker feature selections showed that J48, NB, and MLP’s accuracy improved, whereas RF accuracy decreased and support vector machine remained stable.
Clinical grade production of IL‐15 stimulated NK cells for early infusion in adult AML patients undergoing haploidentical stem cell transplantation with post‐transplant cyclophosphamide

Allogeneic stem cell transplantation is the treatment of choice for acute myeloid leukemia (AML) patients. Unmanipulated haploidentical transplantation (Haplo‐HSCT) is commonly used for those AML patients who need a timely transplant and do not have a suitable matched donor, but relapse rates are still high, and improvements are needed. Adoptive immunotherapy using natural killer cells (NK cells) could be a promising tool to improved Haplo‐HSCT but, to date, no optimal infusion and manufacturing protocols have been developed.
Removal of NO by carbon-based catalytic reduction bed loaded with Mn induced by dielectric barrier discharge at low temperature

The current paper reports on a newly developed DBD-Mn/FCRB hybrid system to explore the removal of NOx by reduction without adding reducing gas at low temperature (below 80°C). This technology was established with a fixed carbon-based reduction catalytic reduction bed loaded with manganese (Mn/FCRB) induced by dielectric barrier discharge (DBD). The NO conversion and N2 selectivity in the new hybrid system reached 90.9% and 79.9% respectively under 8% oxygen content, 1,200 J/L specific input energy (SIE), which were all higher than in the single DBD and DBD-FCRB systems, respectively. The Mn/FCRB was further characterized before and after activation by SEM, XRD and XPS. The possible reaction pathways of denitration were proposed through three processes based on the experimental results: direct denitration of active carbon atoms excited by plasma, reduction by adsorptive C(N) and C(O) complexes on the FCRB surface, and the reaction of nitrogen oxides with by-product CO. In addition, the results also showed that the new in-situ reduction denitration system had strong oxygen shock resistance and water resistance.
Ultrasound findings in lateral elbow tendinopathy: A retrospective analysis of radiological tendon features

Background: Lateral elbow tendinopathy (LET) is prevalent in the upper extremity, with various therapeutic options. Understanding the types and the relations between the radiological tendon features would help to develop more specific treatments. This study reviewed ultrasound exams of LET to investigate the types of degenerative findings and the relationships between them in one of the most prominent sports medicine clinics in Latin America. Methods: A retrospective study was performed. We evaluated 4335 ultrasonographic exams with LET from 2017 and 2018. Five principal degenerative ultrasound criteria with subtypes were selected: hypoechogenicity, neovascularity, calcification, enthesopathy, and intrasubstance tear. A multiple linear regression model was conducted to explore the association between the findings, sex, and age. Results: Overall, 4324 ultrasound exams were analyzed; 2607 (60.29%) were males. Multiple degenerative tendon findings were found in adults (≥18 years) with LET. Hypoechogenicity (67.77%) and neovascularity (37.8%) were the most frequent. The mean length of a tendon tear in both sexes was 4.44 (± 2.81) millimeters. Mild hypoechogenicity (P < .001), and depth intrasubstance tear (P < .01) were statistically significant between them. Severe hypoechogenicity was associated with an increase in all tendon tear dimensions for length 1.37 ([95% Confidence interval (CI), 0.57, 2.17]; P < . 001), for width 1.10 ([95% CI, 0.33, 1.87]; P < .01) and for depth 1.64 ([95% CI, 0.40, 2.88]; P < .01). Additional findings associated with an increase in the length dimension were 0.42 associated with focal neovascularity ([95% CI, 0.19, 0.65]; P < .001), and 0.71 associated with multiple neovascularity ([95% CI, 0.27, 1.15]; P < .01). Conclusions: Hypoechogenicity and neovascularity findings presented a positive association with the size of tendon tear in patients with LET. This study reaffirms the increased predominance of tendon tear during the 4th to 6th decades of life.