Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk and ambiguity of COVID-19 inhibit intentions for post-pandemic travel via reduced valuation of tourism

PurposeThis study aims to examine how the initial ambiguity of COVID-19 contributed to tourists' intentions for visiting a once-viral outbreak site in the future.Design/methodology/approachThe present study (N = 248) used partial least-squares structural equation modeling (PLS-SEM) to examine whether perceptions of ambiguity and mismanagement of COVID-19 are indirectly related to intentions to travel to Wuhan in a post-pandemic world through perceptions of risk and tourism value. Further, whether the model effects differed as a function of individual safety orientation was examined.FindingsPerceptions of COVID-19 risk and tourism value serially mediated the effects of perceived COVID-19 ambiguity on post-pandemic travel intentions. Safety orientation did not moderate any paths. Perceived risk was a negative direct correlate of post-pandemic travel intentions.Originality/valueThe current study's strength is rooted in its specific targeting of post-pandemic travel intentions to Wuhan—the first city to experience a widescale outbreak of COVID-19 and subsequent international stigma—compared to general travel inclinations.
On the residue of the Eisenstein series and the Siegel-Weil formula

Some residue of a Siegel Eisenstein series is expressed as a theta integral in some cases. This formula is a refinement of the Siegel-Weil formula for the residue of the Eisenstein series given by Kudla and Rallis. The proof of the formula is carried out by comparing the Fourier-Jacobi coefficients of the Eisenstein series and the theta integral.
Adaptive Time-Varying Barrier Lyapunov Function-Based Model-Free Hybrid Position/Force Control for Series Elastic Actuator-Based Manipulator

In this brief, an adaptive time-varying barrier Lyapunov function-based model-free hybrid position/force controller (ABLF-MFC) is designed for a series elastic actuator (SEA)-based 2-link manipulator. The proposed ABLF-MFC is designed based on impedance control and has a dual-loop structure, which is an outer force control loop and an inner position control loop. The outer force control loop converts the desired interaction force into a reference trajectory through the impedance model, which is later tracked by the inner position control loop to achieve hybrid position and force control. In order to simplify the inner position control loop design, an ultra-local model (ULM) is introduced to approximate the original system, and all the dynamic characteristics and uncertainties are lumped into an unknown term. And the time-delay estimator (TDE) is used to estimate the unknown term in ULM. Then, a time-varying barrier Lyapunov function is introduced in the inner position control loop, which can effectively improve the transient and steady responses. In addition, an adaptive term is added to compensate for the estimation error of TDE. The effectiveness of the proposed ABLF-MFC is verified by rigorous mathematical proofs and simulation results.
Rock Particle Image Segmentation Based on Improved Normalized Cut

Rock particle images are different and complex, which is depending on various situations, in most cases, traditional image segmentation methods often make under-segmentation and over-segmentation. In order to overcome the disadvantages, a new algorithm based on improved graph based algorithm (Normalized Cut) is proposed. In the algorithm, to denoise and reduce data size, an image is reduced by scale transformation; and image segmentation is made by an improved Normalized Cut algorithm. In experiments, different types of rock particle images were tested, and the new algorithm was compared with the traditional algorithms such as Threshold, Edge detection, Minimum spanning tree, Clustering analysis, Fuzzy C-Means and Watershed etc. The testing results show that the image segmentation effect of the new algorithm is better than that by the traditional image segmentation algorithms. The studied algorithm was applied into the rock blasting in a large open-pit mine, and the results were satisfactory.
The Effect of Xanthohumol Derivatives on Apoptosis Induction in Canine Lymphoma and Leukemia Cell Lines

Xanthohumol is a cancer chemopreventive agent that can interfere with the initiation, promotion, and progression phase of carcinogenesis via a variety of inhibitory mechanisms. Xanthohumol was reported as an effective agent against leukemia/lymphoma cells. In the present study, we investigated the effect of xanthohumol and its natural and semisynthetic derivatives against various canine leukemia/lymphoma cell lines. Xanthohumol, three hops minor prenylflavonoids (xanthohumol C, xanthohumol D, α,β-dihydroxanthohumol) and four derivatives obtained by biotransformation (xanthohumol 4′-O-β-D-(4‴-O-methyl)-glucopyranoside) as well as by chemical modification (1″,2″-dihydroxanthohumol K, 2,3-dehydroisoxanthohumol, (Z)-6,4′-dihydroxy-4-methoxy-7-prenylaurone) were tested for their antiproliferative and pro-apoptotic activities against the following canine leukemia/lymphoma cell lines: CLBL-1 (B-cell lymphoma), CLB70 (B-cell leukemia), and GL-1 (B-cell leukemia). The compounds were tested at a final concentration range of 0.1–30 µM for 48 h. All eight of the tested flavonoids exerted concentration-dependent cytotoxicity in the selected canine lymphoma/leukemia cell lines. Three compounds markedly decreased the viability of all cell lines with IC50 in the range of 0.5 to 8 μM. Double-staining of the treated cells with AnnexinV and propidium iodide revealed that the dying cells were mostly in the late apoptosis stage. ROS production and changes in mitochondrial potential were detected. Western blot analysis showed a decreased expression of Bcl-2. Canine lymphoma and leukemia cell lines are sensitive to xanthohumol derivatives, and the compounds acted through an apoptotic cell-death mechanism. These compounds, either used alone or in combination with other therapies, may be useful for the treatment of canine leukemia/lymphoma.
Lateral Electrochemical Metallization Cells for Reconfigurable Interconnect Systems

Lateral electrochemical metallization (ECM) cells are fabricated with a combined spacer/damascene process. The process allows the realization of nanoscale geometrical distances between the two electrodes independent of lithography. Such lateral ECM cells are an essential part in a reconfigurable interconnect system that may yield a strongly increased connectivity in artificial neural networks. The lateral cells show memristive properties comparable to vertical cells with switching voltages in the range of −1.5V to 2.5V. The influence of electrode line edge roughness on SET kinetics of such lateral cells is investigated via kinetic Monte Carlo simulations, finding a minor influence on SET time variability.
Optimal IPT Core Design for Wireless Electric Vehicles by Reinforcement Learning

In this article, optimal inductive power transfer (IPT) core structures for wireless electric vehicle (WEV), which can be derived by optimal reinforcement learning (RL) algorithms, are newly proposed. Because the IPT cannot be theoretically analyzed to find a maximum value of mutual inductance for the optimal core structure design, intuitive and iterative process based on finite element method analysis are usually implemented. This conventional method, however, is not preferred due to numerous possible combinations and computation times. For this reason, RL algorithms are designed to optimize nonlinear system design, enabling the WEV IPT to be efficiently designed with high mutual inductance, even in the presence of severe misalignment conditions. Contrary to the conventional RL algorithm for the IPT core design, the proposed RL algorithm can follow higher mutual inductance by shorter episodes; hence, 50% of computation time reduction and 2% of maximum mutual inductance were achieved. A prototype of WEV IPT system designed by the proposed RL algorithm was fabricated, satisfying the standard J2954 of the society of automotive engineers for WPT3/Z3 case. As a result, it is found that the proposed WEV IPT can be manufactured, considering the desired number of cores for reasonable cost and weight of the vehicle assembly.
Characterizations of *-DMP matrices over rings

Let R be a ring with involution ∗ . Rm×n denotes the set of all m× n matrices over R . In this paper, we give a characterization of the pseudo core inverse of A ∈ Rn×n in the form of A = GDH , Nr(G) = 0, Nl(H) = 0, D = D = D∗ , where Nl(A) = {x ∈ R1×m|xA = 0} and Nr(A) = {x ∈ Rn×1 | Ax = 0}. Then we obtain necessary and sufficient conditions for A ∈ Rn×n , in the form of A = GDH , Nr(G) = 0, Nl(H) = 0, D = D = D∗ , to be *-DMP. If R is a principal ideal domain (resp. semisimple Artinian ring), then matrices expressed as that form include all n × n matrices over R .
Investigating Vitreous Cytokines in Choroidal Melanoma

Simple Summary Uveal melanoma (UM) is a rare cancer highly prone to metastasis. Metastatic risk is currently predicted using clinical and/or tumor biopsy-based information. While tumor biopsy-based molecular information is helpful, there is an unmet need for a liquid biopsy-based approach as a more advantageous alternative to tumor biopsy. Given that UMs primarily arise in the posterior eye segment, vitreous (which fills the posterior eye cavity) represents a fluid source enriched in tumor-derived molecules. Inflammatory microenvironment indicates poor prognosis in UM and cytokines are key mediators of immune response/inflammation. Vitreous cytokine analysis may therefore increase our understanding of UM and inform future clinical strategies. In this study, we analyzed 41 vitreous cytokines in 32 eyes (18 with posterior UM and 14 controls) and identified 26 UM-associated and 6 prognosis-relevant cytokines. Our findings further support the value of vitreous cytokine analysis in UM and the need for additional studies to establish the best candidates for biomarker development and/or therapeutic targeting. Abstract Due to the close relationship between the vitreous and posterior eye layers, the microenvironment of these layers can affect the composition of the vitreous. Molecular analysis of the vitreous may therefore provide important insights into the pathogenesis of chorioretinal diseases. In this study, vitreous cytokines (n = 41) were evaluated to gain further insights into the tumor microenvironment in uveal melanoma (UM) arising from the choroid (CM). Cytokine levels were measured using a bead-based multiplex immunoassay panel in vitreous samples obtained from 32 eyes, including 18 with CM and 14 controls. Median fluorescence intensity values were extracted and used as relative quantification of the cytokine abundance. Vitreous cytokine levels were compared between the CM and non-CM groups and between different prognostic categories within the CM group (classified as having low or high metastatic risk using tumor biopsy-based gene expression profiling). Correlations between vitreous cytokine levels and tumor dimensions were also evaluated. Our analysis revealed twenty-six vitreous cytokines significantly upregulated in CM-affected eyes compared to the control eyes. Within the CM group, six vitreous cytokines showed altered levels (five upregulated and one downregulated) in eyes with high- vs. low-risk tumors. Levels of these six plus several other cytokines showed correlations with the tumor dimensions. In conclusion, our study has uncovered several UM-relevant vitreous cytokines, worthy of follow-up in larger studies as potential candidates for liquid biopsy-based biomarker development and/or new therapeutic targeting.
Health promotion programs in prison: attendance and role in promoting physical activity and subjective health status

Introduction Maintaining an inmate’s health can serve as a challenge due to unhealthy background, risky behavior, and long imprisonment. This study aimed to analyze the prevalence of participation in health promotion activities among Israeli inmates and its association with their physical activity levels and subjective health status. Methods A cross-sectional study was designed to examine 522 inmates (429 males, 93 females). The data were collected by trained face-to-face interviewers and self-report questionnaires. Results Most of the participants (82.37%) did not meet the recommended physical activity level. Half of the participants reported that their physical activity levels decreased since they were in prison compared with 29.50% who reported that their physical activity levels increased. Physical activity and subjective health status were significantly higher among younger male inmates. Furthermore, participation in health-promoting activities was associated with higher levels of physical activity and subjective health status. Discussion Health promotion activities may play an important role in addressing the challenges of maintaining inmate health. Implications of the findings are further discussed.
AraBig5: The Big Five Personality Traits Prediction Using Machine Learning Algorithm on Arabic Tweets

Personality trait prediction has attracted substantial academic interest in recent years as a consequence of its ability to characterize people’s distinctive personality features that distinguish them from others. These features help to anticipate how a person will interact with others in various situations and aid psychologists and therapists in building a profile of their clients. Personality traits are often measured through a traditional pencil-and-paper questionnaire. This questionnaire is considered expensive in terms of time and effort. Therefore, researchers have started using personality trait prediction that automatically analyzes users’ social media textual data by applying machine learning techniques. However, the majority of these studies have been predicted from English texts; only one study has predicted personality traits from Arabic (Egyptian dialect) texts. Furthermore, there is a significant gap between studies that predict personality from English and Arabic texts in terms of machine learning techniques and the dataset used. This study aims to reduce the gap by building a new Arabic dataset with Saudi dialect (AraBig5) and implementing different machine learning models on AraBig5 to predict Big Five personality traits. The results indicate that logistic regression and support vector machine yielded the best average F1 scores of 0.86 and 0.87, respectively.
Unwinding quantitative easing: state dependency and household heterogeneity

This paper studies the macroeconomic effect of the state dependency of central bank asset market operations and their interactions with household heterogeneity. We build a New Keynesian model with borrowers and savers in which quantitative easing and tightening operate through portfolio rebalancing between short-term and long-term government bonds. We quantify the aggregate impact of an occasionally binding zero lower bound in determining an asymmetry between the effects of asset purchases and sales. When close to the lower bound, raising the nominal interest rate prior to unwinding quantitative easing minimises the economic costs of monetary policy normalisation. Furthermore, our results imply that household heterogeneity in combination with state dependency amplifies the revealed asymmetry, while household heterogeneity alone does not amplify the aggregate effects of asset market operations.
A Novel Optimized iBeacon Localization Algorithm Modeling

The conventional methods for indoor localization rely on technologies such as RADAR, ultrasonic, laser range localization, beacon technology, and others. Developers in the industry have started utilizing these localization techniques in iBeacon systems that use Bluetooth sensors to measure the object’s location. The iBeacon-based system is appealing due to its low cost, ease of setup, signaling, and maintenance; however, with current technology, it is challenging to achieve high accuracy in indoor object localization or tracking. Furthermore, iBeacons’ accuracy is unsatisfactory, and they are vulnerable to other radio signal interference and environmental noise. In order to address those challenges, our study focuses on the development of error modeling algorithms for signal calibration, uncertainty reduction, and interfered noise elimination. The new error modeling is developed on the Curve Fitted Kalman Filter (CFKF) algorithms. The reliability, accuracy, and feasibility of the CFKF algorithms are tested in the experiments. The results significantly show the improvement of the accuracy and precision with this novel approach for iBeacon localization.
A Case of Severe, Difficult-to-Diagnose Legionnaires' Disease in a Young Welder

Legionellosis among welders and other metalworkers is a rare but potentially underappreciated occupational hazard. The same mechanisms that predispose welders to severe pneumonia from Streptococcus pneumoniae and Bacillus cereus may similarly predispose them to Legionella pneumophila infection. We present a case of a previously healthy, immunocompetent 31-year-old male welder presenting with three days of shortness of breath, hypoxia, high-grade fever, and blood-tinged sputum. Chest computed tomography (CT) revealed a lobar consolidation of the right middle and lower lobes. Laboratory evaluation showed borderline hyponatremia, hypophosphatemia, and elevated liver enzymes. The patient was ultimately intubated and started on broad-spectrum antibiotics. Multiple respiratory cultures were negative and Legionella urine antigen testing was also negative. Eventually, bronchial Legionella culture was positive for Legionella pneumophila, and a blood next-generation sequencing test also confirmed the diagnosis. He was extubated six days following admission and subsequently discharged.
Factors Influencing Customers’ Perception of Digital Banking Service Quality in Vietnam

Purpose: This paper examines the impacts of gender, education, and age on consumer’s perception of digital banking service quality in the case of a branch of Bank for Investment and Development of Vietnam. Theoretical framework: Inspired by Parasuraman‘s five dimensions of service quality, this research defined four criteria measured digital banking service quality including the security, the ability, the convenience, and the supported policies for customers. Among different factors influencing consumers’ perception, the authors selected to analyzed impacts of education, gender, and age of consumers. Design/Methodology/Approach: Primary data was collected from 200 customers who were randomly selected, then analyzed by descriptive statistics. The T-test, Cronbach Alpha, and ANOVA were used to test the differences of consumers’ perception of digital banking service quality by their gender, age, and education. Findings: The analysis showed that consumers’ perception of digital banking service quality clearly differed by their gender and age. Nevertheless, there was not a clear correlation between educational levels and their perception of security, convenience, and promotion policies of digital banking services. Research, Practical & Social implications: The findings imply that Vietnamese commercial banks need to improve the quality of digital banking services by: cooperating with Fintech companies to increase security, improving human resource quality, innovating technology and promoting communication activities. Originality/Value: This study indicated the differences of consumers’ perception of digital banking service quality by their age, gender, and education. All the respondents of the survey are digital banking service users.
Efficient Constrained Signal Reconstruction by Randomized Epigraphical Projection

This paper proposes a randomized optimization framework for constrained signal reconstruction, where the word "constrained" implies that data-fidelity is imposed as a hard constraint instead of adding a data-fidelity term to an objective function to be minimized. Such formulation facilitates the selection of regularization terms and hyperparameters, but due to the non-separability of the data-fidelity constraint, it does not suit block-coordinate-wise randomization as is. To resolve this, we give another expression of the data-fidelity constraint via epigraphs, which enables to design a randomized solver based on a stochastic proximal algorithm with randomized epigraphical projection. Our method is very efficient especially when the problem involves non-structured large matrices. We apply our method to CT image reconstruction, where the advantage of our method over the deterministic counterpart is demonstrated.
Sextic Number Fields with Discriminant −23

Complete lists of number fields, of given degree n and unramified outside a given finite set S of primes, are both of intrinsic interest and useful in some applications. For degrees n ≤ 5 and S = {∞, 2, 3}, the complete lists have appeared previously; there are in total 85 such fields. Here we give the complete list for n = 6 and S = {∞, 2, 3}, finding in particular exactly 398 such fields. We use a three-pronged approach to obtain this classification: an exhaustive computer search, sextic twinning, and class field theory. Also we completely identify the 2-adic and 3-adic completions of all these degree ≤ 6 fields, this information being one of the focal points of interest and essential in applications. There is a considerable literature on the classification of number fields by means of their discriminants. At present for n = 3, 4, 5, 6, 7 there are large tables, available at [B], giving all number fields of degree n and absolute discriminant less than certain bounds. It would also be interesting to have complete tables of number fields unramified outside a given finite set S of primes. For a given degree n, these sets of number fields are finite, by a classical theorem of Hermite. For a recent survey of the general subject of number fields with prescribed ramification, we recommend [H]; there it is made clear that very little is known about the set of non-solvable number fields unramified outside a given S. In this paper, we focus on the set S = {∞, 2, 3}. We present tables for degrees ≤ 6, the following chart giving an overview the situation. Degree n Sn An Hn Upper Bound for |D| Method 2 7 – – 23 = 24 Trivial 3 8 1 – 23 = 1,944 Old tables or CFT 4 22 1 39 23 = 497,664 Old tables or CFT 5 5 0 1 23 = 1,492,992 Old tables 6 54 8 336 23 = 2,902,376,448 New here 7 23 = 2,902,376,448 8 23 ≈ 1.1× 10 9 23 ≈ 5.5× 1
A study on enhancing EUV resist sensitivity

Studies have been carried out on developing a method for improving EUV resist sensitivity by enhancing EUV light absorption through the addition of metals having high EUV light absorption to the resist polymer in order to increase secondary electron emission, thereby enhancing PAG reactivity and improving acid generation efficiency[1-3]. To confirm whether the addition of metals having high EUV light absorption actually does enhance sensitivity, study efforts included transmittance measurements and sensitivity evaluations of resist samples doped with ZrO2 or TeO2 nanoparticles, which have low and high EUV light absorption, respectively, in molar quantities of 0-2 relative to PAG. The samples were subjected to EUV exposure at the NewSUBARU synchrotron radiation facility. While the ZrO2-doped resist showed no evident enhancement of sensitivity or transmittance, the TeO2-doped resist showed enhancement in both properties. Based on these results, we confirmed that the addition of metals having high EUV light absorption to the EUV resist enhances its EUV light absorption and increases secondary electron emission, thereby enhancing PAG reactivity and improving acid generation efficiency.