Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting communities by suspecting the maximum degree nodes

Detecting the natural communities in a real-world network can uncover its underlying structure and potential function. In this paper, a novel community algorithm SUM is introduced. The fundamental idea of SUM is that a node with relatively low degree stays faithful to its community, because it only has links with nodes in one community, while a node with relatively high degree not only has links with nodes within but also outside its community, and this may cause confusion when detecting communities. Based on this idea, SUM detects communities by suspecting the links of the maximum degree nodes to their neighbors within a community, and relying mainly on the nodes with relatively low degree simultaneously. SUM elegantly defines a similarity which takes into account both the commonality and the rejective degree of two adjacent nodes. After putting similar nodes into one community, SUM generates initial communities by reassigning the maximum degree nodes. Next, SUM assigns nodes without labels to the initial communities, and adjusts the border node to its most linked community. To evaluate the effectiveness of SUM, SUM is compared with seven baselines, including four classical and three state-of-the-art methods on a wide range of complex networks. On the small size networks with ground-truth community structures, results are visually demonstrated, as well as quantitatively measured with ARI, NMI and Modularity. On the relatively large size networks without ground-truth community structures, the performances of these algorithms are evaluated according to Modularity. Experimental results indicate that SUM can effectively determine community structures on small or relatively large size networks with high quality, and also outperforms the compared state-of-the-art methods.
Philanthropy's role in mediating the relationship between corporate social responsibility (CSR) and sustainable corporate performance (SCP) in Zimbabwe's service sector: Evidence from managerial cognitions

In this study, the philanthropic aspect of corporate social responsibility is looked at in relation to other aspects of corporate social responsibility and long-term business performance in Zimbabwe's service-based firm sector. Management perceptional data were collected from 650 senior managers in organisations within the service-based sector of the Harare region. The online questionnaire's measurement items draw from stakeholder, legitimacy, and triple-bottom-line theories. The empirical findings highlight the relative importance of environmental and philanthropic factors in promoting long-term competitiveness. The results suggest that philanthropy is a mediator in the connection between the corporate social responsibility dimensions of economic, ethical, and environmental responsibilities. The importance of philanthropy in elucidating the relationship between these variables is implied. The study emphasises that relying solely on philanthropy is insufficient to maintain long-term performance. Achieving sustainable corporate performance growth depends on the optimal interaction of different corporate social responsibility elements, which drive business growth. Investing in corporate social responsibility by collaborating with stakeholders and creating shared value is crucial for firms to succeed. This research adds to the current literature on corporate social responsibility and sustainability performance by offering valuable insights into the motivations, challenges, and strategies unique to Zimbabwe's service sector. The text underscores the significance of environmental and philanthropic factors in promoting long-term competitiveness. It also emphasises adopting a comprehensive corporate social responsibility approach to achieve sustainable performance.
Machine metaphors in 2020 USA electioneering campaign: a cognitive aspect

The conceptual metaphor is a major persuasive tool in political discourse. Therefore, the aim of the research is to analyze the realization of van Dijk’s Ideological Square strategies with the help of machine conceptual metaphors used by the presidential candidates during the 2020 electioneering campaign. The data of the research comprise 99 political speeches delivered by Donald Trump and Joe Biden at rallies. Consequently, the following methods of linguistic analysis were used: a Critical Discourse Analysis, a Conceptual Metaphor Analysis in the form of the method of the reconstruction of conceptual mappings, a comparative method, a contextual analysis, and statistical methods. As a result, the analysis demonstrated that conceptual metaphors, which were identified in the corpus, play an important role in realizing the Ideological Square strategies with persuasive goals. Apart from that, it was established that the conceptual metaphor ECONOMY IS A MACHINE is predominant in Donald Trump’s and Joe Biden's discourses. In addition, the data analysis showed that the majority of metaphors were used to highlight the candidate’s own positive sides while exaggerating his opponent’s disadvantages.
Enhancing oral squamous cell carcinoma prediction: the prognostic power of the worst pattern of invasion and the limited impact of molecular resection margins

Objective Oral squamous cell carcinoma (OSCC) originates from the mucosal lining of the oral cavity. Almost half of newly diagnosed cases are classified as advanced stage IV disease, which makes resection difficult. In this study, we investigated the pathological features and mutation profiles of tumor margins in OSCC. Methods We performed hierarchical clustering of principal components to identify distinct patterns of tumor growth and their association with patient prognosis. We also used next-generation sequencing to analyze somatic mutations in tumor and marginal tissue samples. Results Our analyses uncovered that the grade of worst pattern of invasion (WPOI) is strongly associated with depth of invasion and patient survival in multivariable analysis. Mutations were primarily detected in the DNA isolated from tumors, but several mutations were also identified in marginal tissue. In total, we uncovered 29 mutated genes, mainly tumor suppressor genes involved in DNA repair including BRCA genes; however none of these mutations significantly correlated with a higher chance of relapse in our medium-size cohort. Some resection margins that appeared histologically normal harbored tumorigenic mutations in TP53 and CDKN2A genes. Conclusion Even histologically normal margins may contain molecular alterations that are not detectable by conventional histopathological methods, but NCCN classification system still outperforms other methods in the prediction of the probability of disease relapse.
The Effect of Virtuality on Work Engagement through Social Presence: Moderated Mediation Effect of Team Members’ Perception of Identity Entrepreneurship

This study aims to verify the effects of virtuality in the workplace and social presence on work engagement and the moderated mediating effects of leaders’ identity entrepreneurship perceived by team members. This study used a quantitative approach to collect and analyze cross-sectional survey data of remote workers in South Korea. An online survey was conducted on remote workers and 300 questionnaires were analyzed. The research findings confirmed that social presence mediated the relationship between virtuality and work engagement. Fu rthermore, the moderating effect of leaders’ identity entrepreneurship was significant in the relationship between virtuality and social presence. As hypothesized, the moderating effect of the leaders’ identity entrepreneurship perceived by the team members was confirmed. Based on the result, this study proposes the necessity of the social presence of members in a remote work environment with high virtuality. Although this study overlooked causal relationships between the variables and remote workers’ home context, this study enlightens the importance of team leaders’ identity entrepreneurship quality in enhancing social presence among employees in the virtual working environment. The implications of the findings were facilitating virtual communication training programs and developing identity entrepreneurship training programs for team leaders. For virtual teams, it is necessary to find the most suitable virtual communication tool for each different task.
Multiview human action recognition via deep discriminant analysis network

Abstract. Homogeneous data fusion plays a crucial role in multiview human action recognition (MvHAR). However, most existing methods tend to employ the concatenate strategy, ignoring the underlying correlation among views and degrading the recognition performance. To this end, we propose a practical MvHAR framework based on a deep discriminant analysis network that excavates multiview video features to obtain a more discrimination representation, from which the view correlation can be explored. Specifically, the spatial–temporal features of multiview data are extracted by the convolution network, and then a deep multiview feature fusion network is proposed to project these features into an advanced subspace for efficient fusion. Traditional methods can lead to class overlap problems, but, to avoid this problem, we improve the separation between two classes by using pairwise between-class scatter. Experiments on five benchmark datasets indicate the efficiency of our framework compared with the advanced algorithms under four metrics.
The posttraumatic cognitive appraisal inventory (PTCAI): development and validation

Objective This study aims to develop and validate the Posttraumatic Cognitive Appraisal Inventory (PTCAI) for accidental trauma survivors. Method Based on interviews and expert feedback, the initial item pool was generated for the Negative Cognitive Appraisal Inventory of Loss and Feeling Threatened, and the Positive Cognitive Appraisal Inventory of Positively Face, Self-Sense, and Relationships. Then, we recruited two groups of accidental trauma survivors to examine the reliability and validity of the PTCAI. Item analysis and exploratory factor analysis (EFA) were conducted on Sample 1. Confirmatory factor analysis (CFA), Pearson correlation analysis, and internal consistency reliability analysis were applied to Sample 2. After 2 weeks, 20 survivors completed the PTCAI again to test temporal stability. Results Following item analysis, the PTCAI was reduced to 27 items. The results of the EFA demonstrated that the five-factor, 27-item solution of the PTCAI was appropriate, which accounted for 63.931% of the total variation. The CFA indicated that the five-factor second-order model offered an excellent fit to the data. Loss and Feeling threatened were equally important in the study participants’ negative cognitive appraisal of accidental traumas. Self-sence was the most important positive cognitive appraisal of accidental traumas by the study participants. Positively Face and Relationships were somewhat behind. Additionally, the PTCAI demonstrated high concurrent validity and reliability (test–retest and internal consistency). Conclusion The PTCAI appears to be a reliable and valid instrument for assessing cognitive appraisals of accidental trauma survivors.
Should videolaryngoscopy be routinely used for airway management? An approach from different scenarios in medical practice

During the past two decades, the videolaryngoscope (VDL) has become a valuable and effective tool for the management of the airway, not just in the realm of anesthesiology, but also in other medical specialties in clinical scenarios requiring tracheal intubation. In countries such as the United States, this represents over 15 million cases in the operating room and 650,000 outside the OR. The overall accumulated incidence of difficult airway is 6.8% events in routine practice and between 0.1 and 0.3 % of failed intubations, both associated with complications such as desaturation, airway injury, hemodynamic instability and death. Notwithstanding the fact that the VDL has proven advantages such as improved visualization of the glottis, higher first attempt success rates, and a shortened learning curve, most of the time its use is limited to rescue attempts or as a secondary option. The objective of this article is to review the advantages and limitations of the VDL vs. the direct laryngoscope in a wide range of clinical settings, including the operating room, intensive care units, emergency departments, pediatrics, obstetrics, and Covid-19 to consider its routine use.
CMOS Force Sensor with Scanning Signal Process Circuit for Vertical Probe Card

The constant advancement of semiconductor technology has prompted a further reduction in size and an increase in the density of integrated circuits. In order to meet the various requirements of the industry, higher accuracy, longer fatigue life, and a greater capability to withstand temperature extremes have become important criteria in the design of probe cards (Iscoff, 1994; Gilg, 1997). After a certain period of use, probe cards must be calibrated by a professional machine; several properties need to be verified, such as the probe’s maximum current, resistivity (contact resistance), and reaction force. This verification procedure may influence the efficiency of production lines, since it is performed offline. One crucial step in this procedure is monitoring the reaction force exerted by the probes on each other, in order to compute the average reaction force and complete coplanarity to ensure the efficient operation of the probe cards. To expedite this procedure, we designed an arraytype CMOS force sensor that is capable of monitoring the status of vertical probe cards online in both die-level and wafer-level applications. In the past, the fabrication of pressure sensors typically involved an MEMS process with backside etching adopted for its post process (Ghalichechian, 2002; Malhair & Barbier, 2003). However, in recent years, more and more researchers have proposed to combining the standard CMOS process with the MEMS process to manufacture both microsensors and integrated circuits (Yang et al., 2005; Peng et al., 2005; Wang et al., 2006). The combined process also has additional advantages, such as a reduction in the noise and number of pads. Our design also adopted the combined CMOS-MEMS process to fabricate force sensors and their signal conditioning circuits. Moreover, as the conventional post process can barely handle the increasingly smaller pitch between the probes (Wilson, 1999), we etched a cavity on the silicon substrate to deform the membrane in the post process (RLS dry etching).
The Role of Family Support in Enhancing Self-Confidence and Business Performance in Women Entrepreneurs

The performance of businesses owned or operated by women entrepreneurs encompasses the results and accomplishments of these ventures. Evaluating the success and positive impact of women entrepreneurs' managed businesses involves using various metrics and indicators. Factors like self-confidence and family support are potential influencers in shaping women entrepreneurs' business performance. This study explores the interconnection between family support, self-confidence, and business performance among women entrepreneurs. The empirical analysis involved 197 women entrepreneurs surveyed online. After ensuring reliability and validity through tests, the data underwent analysis using partial least squares structural equation modeling. The research findings reveal a significant positive direct impact of family support on self-confidence. Additionally, family support exhibits a notable positive direct influence on business performance. Moreover, self-confidence emerges as a significant positive factor directly affecting business performance.
APPLICATIONS OF COPPER-BASED FUNGICIDES AND INFESTATIONS OF Leucoptera coffeella (Guérin-Mèneville & Perrottet) IN COFFEE PLANTS

The present study aimed to evaluate the effects of applying fungicides with different sources of copper and of the number of applications on the occurrence of Leucoptera coffeella (Guérin-Menéville & Perrottet, 1842) (Lepidoptera: Lyonetiidae) and on the wax layer on leaves in a coffee plantation. Four applications of fungicides were carried out and the effects on the number of leaves mined by the insect and on the wax content on the leaf surface were evaluated. The copper-based fungicides increased the number of leaves mined by the leaf-miner and reduced the wax content on the coffee leaf surfaces in both periods studied.
A hierarchical Bayesian model for regionalized seasonal forecasts: Application to low flows in the northeastern United States

This study presents a regional, probabilistic framework for seasonal forecasts of extreme low summer flows in the northeastern United States conditioned on antecedent climate and hydrologic conditions. The model is developed to explore three innovations in hierarchical modeling for seasonal forecasting at ungaged sites: (1) predictive climate teleconnections are inferred directly from ocean fields instead of predefined climate indices, (2) a parsimonious modeling structure is introduced to allow climate teleconnections to vary spatially across streamflow gages, and (3) climate teleconnections and antecedent hydrologic conditions are considered jointly for regional forecast development. The proposed model is developed and calibrated in a hierarchical Bayesian framework to pool regional information across sites and enhance regionalization skill. The model is validated in a cross‐validation framework along with five simpler nested formulations to test specific hypotheses embedded in the full model structure. Results indicate that each of the three innovations improve out‐of‐sample summer low‐flow forecasts, with the greatest benefits derived from the spatially heterogeneous effect of climate teleconnections. We conclude with a discussion of possible model improvements from a better representation of antecedent hydrologic conditions at ungaged sites.
Maximizing Output Power Using a Magnetic Energy Harvesting System Considering the Relationship Between Harvesting Time and Induced Voltage Due to a Change of Airgap

Power transmission lines are equipped with various electronic devices, including power line inspection robots, safety sensors, and monitoring systems. However, providing power to devices installed on these lines often requires extensive construction and poses many challenges. Therefore, to solve such problems, active research is being conducted on Magnetic Energy Harvesters (MEHs) that harness the magnetic field generated by the current in the power lines to harvest electricity. A crucial design objective of the MEH is to maximize harvested power even if the saturated region is partially included, unlike a current transformer (CT), which must maintain an unsaturated state throughout the operating region. In this paper, design considerations of an MEH are discussed in comparison to the CT. Specifically, this paper formulates the relationship of the airgap between core cutting surfaces, the timing of power harvesting, and the amount of harvested power. It was observed that the MEH core should be designed to have a B-H curve close to the step function by minimizing the airgap and selecting magnetic material with high saturation magnetic flux density to achieve high harvesting power. An optimal MEH model for harvesting the maximum power for each given input current condition is presented. Furthermore, experiments were conducted to verify that 28 W of power was harvested under the input current condition of 150 Arms.
Clinical reliability and validity of a video-based markerless gait evaluation method

Objective To explore the reliability and validity of gait parameters obtained from gait assessment system software employing a human posture estimation algorithm based on markerless videos of children walking in clinical practice. Methods Eighteen typical developmental (TD) children and ten children with developmental dysplasia of the hip (DDH) were recruited to walk along a designated sidewalk at a comfortable walking speed. A 3-dimensional gait analysis (3D GA) and a 2-dimensional markerless (2D ML) gait evaluation system were used to extract the gait kinematics parameters twice at an interval of 2 h. Results The two measurements of the children's kinematic gait parameters revealed no significant differences (P > 0.05). Intra-class correlation coefficients (ICC) were generally high (ICC >0.7), showing moderate to good relative reliability. The standard error of measurement (SEM) values of all gait parameters measured by the two walks were 1.26°–2.91°. The system software had good to excellent validity compared to the 3D GA, with ICC values between 0.835 and 0.957 and SEM values of 0.87°–1.71° for the gait parameters measured by both methods. The Bland–Altman plot analysis indicated no significant systematic errors. Conclusions The feasibility of the markerless gait assessment method using the human posture estimation-based algorithm may provide reliable and valid gait analysis results for practical clinical applications.
Enhancing pain modulation: the efficacy of synchronous combination of virtual reality and transcutaneous electrical nerve stimulation

Introduction Virtual reality (VR) and transcutaneous electrical nerve stimulation (TENS) have emerged as effective interventions for pain reduction. However, their standalone applications often yield limited analgesic effects, particularly in certain painful conditions. Aims Our hypothesis was that the combination of VR with TENS in a synchronous manner could produce the best analgesic effect among the four experimental conditions. Methods To address this challenge, we proposed a novel pain modulation strategy that synchronously combines VR and TENS, aiming to capitalise on both techniques’ complementary pain modulation mechanisms. Thirty-two healthy subjects participated in the study and underwent three types of interventions: VR alone, a combination of VR with conventional TENS, and a combination of VR with synchronous TENS. Additionally, a control condition with no intervention was included. Perceived pain intensity, pain unpleasantness, positive and negative affect scores, and electroencephalographic (EEG) data were collected before and after the interventions. To delve into the potential moderating role of pain intensity on the analgesic efficacy of VR combined with synchronous TENS, we incorporated two distinct levels of painful stimuli: one representing mild to moderate pain (ie, low pain) and the other representing moderate to severe pain (ie, high pain). Results Our findings revealed that both combination interventions exhibited superior analgesic effects compared with the VR-alone intervention when exposed to low and high pain stimuli. Notably, the combination of VR with synchronous TENS demonstrated greater analgesic efficacy than the combination of VR with conventional TENS. EEG data further supported these results, indicating that both combination interventions elicited a greater reduction in event-related potential magnitude compared with the VR-alone intervention during exposure to low and high pain stimuli. Moreover, the synchronous combination intervention induced a more significant reduction in N2 amplitude than the VR-alone intervention during exposure to low pain stimuli. No significant differences in EEG response changes were detected between the two combination interventions. Both combination interventions resulted in a greater reduction in negative affect compared with the VR-alone intervention. Conclusions Altogether, our study highlights the effectiveness of the synchronous combination of VR and TENS in enhancing pain modulation. These findings offer valuable insights for developing innovative pain treatments, emphasising the importance of tailored and multifaceted therapeutic approaches for various painful conditions.