Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Workforce Diversity on Job Performance of hotels working in Jordan

Implementing workplace diversity has become a major focus in many Human Resource departments. Diversity workforce can contribute to the organization’s success by enabling access to a changing marketplace via the organization’s multicultural employees. This study aimed to examine the impact of workforce diversity on the job performance in hotels operating in Jordan. Four dimensions of workplace diversity were included in the study: Gender, Age, Nationality, and Education background, on the other hand, job performance was measured by two dimensions: task performance and contextual performance. The study population consists of all managers working at different managerial levels in hotels in Jordan; samples of 389 managers were selected to represent the study population. Data were collected using a questionnaire developed on the strength of previous studies. Both IMB SPSS 19.0 and AMOS 23.0 were run to examine and test measures, data and hypotheses. The results of the study supported the hypotheses that workforce diversity dimensions; Gender, age, nationality and educational background have a positive impact on job performance. Based on the study results the researchers recommend managers and decision makers of hotels in Jordan need to create better diversity management action plans in order to better accommodate the changing business environment.
Prospect Theory Based Comprehensive Decision-Making Method of Power Network Planning Schemes

The optimal selection of planning schemes for power grid with high penetration intermittent generations is one kind of random decision-making. In view of the fact that the preference and the risk trend of decision-maker cannot be accurately considered in traditional stochastic decision-making methods and the uncertainty information of planning schemes is not fully excavated, the prospect theory is led into the optimal selection of grid planning schemes and an evaluation index system of planning schemes for power grid with high penetration intermittent generations is built, in which the random factors in this kind of power grid are fully considered. On the basis of obtaining the probability distribution types that various kinds of indices obey and combining with the subjective preference and the risk trend of the decision-maker, the prospect value function and the weight function for each evaluation index are constructed. Prospect values of each index are treated as property values, which contains uncertainties and decision-maker's subjective preferences of indices. Finally the VIKOR method is utilized for the comprehensive decision-making of prospect value based schemes. The correctness and efficiency of the proposed method are validated by relevant examples.
New Algorithm for Finding Convex Hull Based on Coiling with a Minimum Lever Pitch in Single Domain and Single Direction

In this paper,an isomorphic improving and creating for the algorithm of finding convex hull of a 2D point set with gift wrapping is realized;and according to the isomorphic fundamental theorem of the convex hull construction,a more efficient new algorithm to find a convex hull based on coiling with a minimum lever pitch in single domain and single direction is advanced.The isomorphic characters of the new algorithm are: 1) find out the bottommost point on the convex hull as the initial vertex of the convex hull,which has the minimum coordinate value of the Y axis among all the points in given 2D point set(if the bottommost point is not only one,the bottommost and leftmost point should be selected);2) passing the last new vertex,make the vertex's half line paralleled by X axis along positive direction,and find out a current vertex with a minimum pitch to its vertex's half line to be the newest vertex in coiling side by side;3) delete all points in the current distributed domain of points set covered by the triangle(which is constructed by the initial vertex,the second-newest vertex and the newest vertex),and loop from "2)" to coil side by side continuingly while the reminded point set is not empty.
Moiré reducing two-dimensional diffractive optical low-pass filter made from molded plastic

A two dimensional sinusoid diffraction grating is developed for a moiré-reducing low-pass filter. Typical display units have image pixels arranged systematically in two dimensions, with non-illuminating regions between the image pixels. Using a conventional lens to view this display, the image pixels and the region between the pixels are both magnified, and the resulting image is unpleasant to the human eye, especially with color displays, called the screen door effect. This pixel problem is typically solved with a low-pass filter using a diffraction grating. However, depending on the period of the diffraction grating compared to the period of the image pixels, moiré can be seen. In recent years, organic electroluminescence displays with a small fill factor are growing popular, but such displays are usually more prone to the screen door effect and moiré. With conventional optical low-pass filters, only the pixel pitch in the vertical and horizontal directions are taken into account, but this is insufficient with small fill-factor pixels, and consideration for various diagonal periods is needed. A two dimensional sinusoid structure diffraction grating is developed for a moiré-reducing low-pass filter. The angle of the grating with the image pixel arrangement, the distance between the display and the grating, the grating depth, and the grating period are all chosen appropriately, and take into account multiple non-adjacent diagonal image pixel periods for all colors, consequently reducing moiré and the screen door effect. We present the calculations and evaluation results from plastic samples made by lithography tooled molds.
Efficient Optimization of -Measure with Cost-Sensitive SVM

-measure is one of the most commonly used performance metrics in classification, particularly when the classes are highly imbalanced. Direct optimization of this measure is often challenging, since no closed form solution exists. Current algorithms design the classifiers by using the approximations to the -measure. These algorithms are not efficient and do not scale well to the large datasets. To fill the gap, in this paper, we propose a novel algorithm, which can efficiently optimize -measure with cost-sensitive SVM. First of all, we present an explicit transformation from the optimization of -measure to cost-sensitive SVM. Then we adopt bundle method to solve the inner optimization. For the problem where the existing bundle method may have the fluctuations in the primal objective during iterations, an additional line search procedure is involved, which can alleviate the fluctuations problem and make our algorithm more efficient. Empirical studies on the large-scale datasets demonstrate that our algorithm can provide significant speedups over current state-of-the-art -measure based learners, while obtaining better (or comparable) precise solutions.
Mixed Supply Function and Quantity Bidding in Two-Stage Settlement Markets

Authors are encouraged to submit new papers to INFORMS journals by means of a style file template, which includes the journal title. However, use of a template does not certify that the paper has been accepted for publication in the named journal. INFORMS journal templates are for the exclusive purpose of submitting to an INFORMS journal and should not be used to distribute the papers in print or online or to submit the papers to another publication.
A computational model of responsibility judgments from counterfactual simulations and intention inferences

How responsible someone is for an outcome depends on what causal role their actions played, and what those actions reveal about their mental states, such as their intentions. In this paper, we develop a computational account of responsibility attribution that integrates these two cognitive processes: causal attri-bution and mental state inference. Our model makes use of a shared generative planning algorithm assumed to approximate people’s intuitive theory of mind about others’ behavior. We test our model on a variety of animated social scenarios in two experiments. Experiment 1 features simple cases of helping and hindering. Experiment 2 features more complex interactions that require recursive reasoning, including cases where one agent affects another by merely signaling their intentions without physically acting on the world. Across both experiments, our model accurately captures participants’ counterfactual simulations and intention inferences, and establishes that these two factors together explain responsibility judgments.
Identi�cation and validation of shared genes and key pathways in endometriosis and endometriosis-associated ovarian cancer by weighted gene co-expression network analysis and machine learning algorithms

Background: Endometriosis is a widespread disease in reproductive age. Epidemiological studies reported that patients with endometriosis had an increased risk of developing endometriosis-associated ovarian cancer (EAOC). The present study aimed to identify shared genes and key pathways that commonly interacted between EAOC and endometriosis. Methods: The expression matrix of ovarian cancer and endometriosis were collected from the Gene Expression Omnibus database. The weighted gene co-expression network analysis (WGCNA) was used to construct co-expression gene network. Functional enrichment analyses were conducted to clarify the potential regulatory mechanisms. Protein-protein interaction (PPI) network and machine learning algorithms were applied to identify characteristic genes. CIBERSORT deconvolution algorithm was used to explore the difference in tumor immune microenvironment. Receiver operating characteristic curves were utilized to assess the clinical diagnostic ability of hub genes. Furthermore, diagnostic nomogram was constructed and evaluated for supporting clinical practicality. Results: We identi�ed 262 shared genes between EAOCand endometriosis via WGCNA analysis. They were mainly enriched in cytokine-cytokine receptor interaction, which may be considered a common mechanism between EAOC and endometriosis. After PPI network and machine learning algorithms, we recognized two characteristic genes (EDNRA, OCLN) and established a nomogram that presented an outstanding predictive performance. The hub genes demonstrated remarkable associations with immunological functions. OCLN were highly upregulatedin ovarian cancer compared to non-tumor tissues, while expression levels of EDNRA were signi�cantly downregulated in ovarian cancer samples. Survival analysis indicated that dysregulated expressions of EDNRA and OCLNwere closely correlated with prognosis of ovarian cancer patients. GSEA analyses revealed that the two characteristic genes were mainly enriched in the cancer-and immune-related pathways. Gene drug interaction analysis found 15 drugs compound that interacted with the hub genes. Conclusion: We identi�ed two hub genes (EDNRA, OCLN) and constructed a nomogram to predict the risk of EAOC based on WGCNA analyses and machine learning algorithms. They can be used as effective predictive biomarkers for detecting EAOC. Our �ndings pave the way for further investigation of potential candidate genes and will aid in improving the diagnosis and treatment of EAOC in endometriosis patients
Extend that “job honeymoon:” acknowledging it is hard to start a job can help

Purpose The purpose of this study was to assess whether a simple intervention could sustain new hires’ high engagement levels beyond the first six months. This case study illustrates how a simple intervention can extend the “job honeymoon“ – a brief period of high engagement – up to a year post hire. Design/methodology/approach This study reports the results of a randomized, controlled study in one organization using a “wise intervention,” a method derived from social science research in educational settings. Findings This case study illustrates that it is possible to extend the job honeymoon up to a year post-hire. Acknowledging to new hires that transitions are challenging produced a statistically significantly higher sense of belonging and higher employee satisfaction up to 9+ months post-hire. Research limitations/implications This work was inspired by research from Gregory M. Walton, and it illustrates the potential value for application in the workplace. However, its generalizability to all organizations will require further study. Practical implications This work is most relevant for human resources leaders and managers who want to ensure new hires are well supported. This study found that acknowledging the difficulty of a transition increases the engagement of new team members substantially and likely enhances productivity and team effectiveness for months to come. Originality/value The highly counterintuitive but critically important idea of this study is that people need reassurance that transitions might feel hard but are a shared experience. Providing that reassurance is a simple, easy-to-apply approach to support the newest members of a team or organization and sustain their engagement for months to come.
Local Computation

The question of what can be computed, and how efficiently, is at the core of computer science. Not surprisingly, in distributed systems and networking research, an equally fundamental question is what can be computed in a distributed fashion. More precisely, if nodes of a network must base their decision on information in their local neighborhood only, how well can they compute or approximate a global (optimization) problem? In this paper we give the first polylogarithmic lower bound on such local computation for (optimization) problems including minimum vertex cover, minimum (connected) dominating set, maximum matching, maximal independent set, and maximal matching. In addition, we present a new distributed algorithm for solving general covering and packing linear programs. For some problems this algorithm is tight with the lower bounds, whereas for others it is a distributed approximation scheme. Together, our lower and upper bounds establish the local computability and approximability of a large class of problems, characterizing how much local information is required to solve these tasks.
Immunovirological discordance among people living with human immunodeficiency virus at a center in Western India: A retrospective study

Background and Objectives: Treatment of people living with human immunodeficiency virus (HIV) (PLHIV) is monitored using plasma HIV viral load levels and CD4 counts. Patients with either immunological nonresponse (virological suppression achieved) or virological nonresponse (immune reconstitution achieved) are termed as having a discordant response. These patients are at higher risk for acquired immunodeficiency syndrome (AIDS)-related infections/diseases/neoplasms, non-AIDS-related illnesses (cardiovascular, neurological, renal, hepatic diseases), and all-cause death. This study was conducted to assess the prevalence of immunovirological discordance among PLHIV after completion of at least 1 year of combination antiretroviral therapy (cART) at an antiretroviral therapy (ART) plus center in India and analyze contributory factors. Methods: The study was a retrospective study of PLHIV receiving cART at the ART plus clinic in Western India from January 18 to December 21. Four hundred and ninety-six patients were studied based on sample size calculated and assessed for CD4 and viral load response at 0, 6, and 12 months of ART. Results: Of the 496 patients, 48 patients (9.7%) had immunovirological discordance. Out of them, 36 patients (75%) had a virological response (immunological nonresponse) and 12 (25%) patients had an immunological response (virological nonresponse). The factors contributing to immunological nonresponse were as follows – low baseline CD4 levels (<100 cells) (36.1%), adherence <95% (33.3%), presence of opportunistic infections (16.6%), and failure on first-line therapy (11.1%). Other factors noted included higher baseline viral load (2.7%), chronic kidney disease (5.5%), and chronic hepatitis B virus co-infection (5.5%). Virological nonresponse was associated with poor adherence to therapy <95% (33%) and failure of first-line regimen (33%). Opportunistic infections were noted among 33% of patients and 8.3% of patients were found to have higher baseline viral load. Interpretation and Conclusion: Immunovirological discordance is an important factor influencing response to cART and is associated with many complications such as AIDS and non-AIDS-related events and even death. Improved adherence and timely identification and management of opportunistic infections are measures that are beneficial in reducing the incidence of immunovirological discordance.
Randomness-Based Saliency Arising in Naturally Designed Scene 1

A new framework is presented for contextual analysis of naturally designed scenes. In this framework, the random distribution of the scale-chromatic complexity is captured as environmental saliency for activating emotional perception mechanisms. The randomness-based saliency is articulated into contextual representations of the ground-object structure. Through experimental studies, the environmental saliency was demonstrated to provide a perceptual basis for the contextual identification and direct visualization of the unpredictable distribution of emotional expressions in complex scenes.
Fluorine 18-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Cardiac Viability Risk Stratification in Comparison with EuroSCORE II for Revascularization in Patients with Left Ventricular Dysfunction

Background: Diagnostic value of fluorine 18-fluorodeoxyglucose positron emission tomography/computed tomography (F18-FDG PET/CT) in the assessment of myocardial viable segments is well known; hence, it can identify patients with left ventricular (LV) systolic dysfunction who may benefit from revascularization. The presence of significant myocardial viable segments before revascularization will offer better prognosis with reduced mortality and morbidity. However, the usage of F18-FDG PET/CT myocardial viability study in the presurgical risk stratification is limited. Objective: The objective of the study is to predict perioperative mortality with hibernating viable myocardial (HVM) segments established by F18-FDG PET/CT in comparison with EuroSCORE II in patients with LV dysfunction undergoing coronary artery bypass grafting surgery. Materials and Methods: A prospective, observational study included 75 patients of chronic ischemic coronary artery disease with ejection fraction ≤40%. Tc-99m sesta-methoxyisobutylisonitrile myocardial perfusion single photon emission CT/CT and myocardial viability with F18-FDG PET/CT at rest were performed. Mortality risk stratification was done according to the EuroSCORE II. Patients were followed for post-coronary artery bypass graft surgery (CABG) 30-day mortality. Mortality observed by HVM segment groups were compared with EuroSCORE II predicted mortality. Results: Receiver operating curve for 30-day mortality prediction with HVM segments and EuroSCORE II was constructed. It showed that a cutoff of <4 HVM segments (area under the curve [AUC] = 0.7) had a sensitivity of 85%, whereas EuroSCORE II (AUC = 0.4) had only 28.6% sensitivity. EuroSCORE II underestimated perioperative risk in patients with <4 viable segments, that is 5 times higher risk was observed in patients with <4 viable segments. Conclusions: HVM segments established by F18-FDG PET/CT had independently predicted mortality postoperatively. Hence, including F18-FDG PET/CT for viability assessment along with EuroSCORE II in preoperative risk assessment for revascularization by CABG in patients with LV dysfunction provided better risk stratification.
High-grade gliomas – Is radical resection needed? Is radical resection possible? Is surgery necessary?

High‐grade gliomas (glioblastomas [GBMs]) are the most common malignant primary brain tumors. Identification of such a tumor in an individual spells doom and signals impending neurological sequel, progressive functional decline, and eventual death. The patient seeks treatment in a quest for relief from symptoms and attempts toward increasing longevity and improving the quality of life. Any kind of treatment that affects or threatens existing functions can have devastating implications both for the patient and the family. While complications can follow every neurosurgical endeavor, the challenge is pronounced in surgery for GBMs as any minor or major complication can seriously affect or cripple the remaining “short” lifespan of the patient, with little or no possibility or time for improvement. From my 40‐year experience in the subject of neurosurgery and dealing with a number of complex neurosurgical issues, I observe that complications following surgery for GBMs are “significantly” common and can happen after attempted radical tumor resection, after partial tumor resection, or even after a biopsy.
Efficiency of the Machining Process of Circular Shapes by Electrical Discharge Technology

Due to its high machining precision, EDM technology is nowadays very important in the production of highprecision parts for various industries. The high precision of the machined surface in combination with the ability to machine circular surfaces brings, in addition to several advantages, some negatives. The most significant negative of this machining technology is the relatively low productivity as well as the overall production efficiency. The latter is affected by many accompanying phenomena. The main accompanying phenomenon that contributes to the decline in the overall economic efficiency of EDM is the microgeometry errors that occur due to the non-homogeneity of the EDM process. Another accompanying negative phenomenon is the geometric accuracy errors of the machined surface, as a consequence of systematic destruction of the wire tool electrode, faulty interpolation in its guidance, and, last but not least, its vibration. These aspects consequently lead to the requirement for multiple applications of additional finishing cuts, which significantly reduces the overall economic efficiency of the machining process. Therefore, the experimental research aimed to search for options that can effectively help to achieve higher productivity but especially the overall economic efficiency of the machining process.
Megahertz Light Steering Without Moving Parts

We introduce a light steering technology that operates at megahertz frequencies, has no moving parts, and costs less than a hundred dollars. Our technology can benefit many projector and imaging systems that critically rely on high-speed, reliable, low-cost, and wavelength-independent light steering, including laser scanning projectors, LiDAR sensors, and fluorescence microscopes. Our technology uses ultrasound waves to generate a spatiotemporally-varying refractive index field inside a compressible medium, such as water, turning the medium into a dynamic traveling lens. By controlling the electrical input of the ultrasound transducers that generate the waves, we can change the lens, and thus steer light, at the speed of sound (1.5 km/s in water). We build a physical prototype of this technology, use it to realize different scanning techniques at megahertz rates (three orders of magnitude faster than commercial alternatives such as galvo mirror scanners), and demonstrate proof-of-concept projector and LiDAR applications. To encourage further innovation towards this new technology, we derive theory for its fundamental limits and develop a physically-accurate simulator for virtual design. Our technology offers a promising solution for achieving high-speed and low-cost light steering in a variety of applications.