Miracle-dz/UniFAR-FTUs huggingface dataset:
Christian nationalism: a stained-glass ceiling for LGBT candidates?

ABSTRACT Lesbian, gay, bisexual, and transgender (LGBT) candidates for public office generally perform better among traditional Democratic voters including women, progressives, young people, People of Color (POC), and the non-religious. Yet, LGBT candidates represent only a fraction of elected officials even in “liberal” states such as California. Using data from a representative sample of California voters, I examine the relationship between Christian nationalism and support for LGBT political candidates. I hypothesize Christian nationalism consolidates hetero- and cisnormative boundaries around American identity which exclude LGBT people and extend across groups who are traditionally supportive of LGBT rights. While the research design cannot demonstrate causation, I find adherence to Christian nationalism is associated with opposition to both lesbian/gay and transgender candidates. Furthermore, the negative effects of Christian nationalism are invariant across measures of partisanship, race, and religious affiliation. Other variables including gender identity, education, and age also predict support for LGBT candidates, but the results suggest Christian nationalism likely represents a stained-glass ceiling for candidates among potential constituents, even constituents from traditionally supportive groups.
Burnout Syndrome and Related Factors in Mexican Police Workforces

Burnout (BO) is a response to prolonged exposure to work-related stressors characterized by emotional exhaustion (EE), depersonalization (DP), and reduced personal accomplishment (PA). The police working environment includes continued critical life-threatening situations, violence, and injuries, among other related factors putting them at high risk of distress. The objective of this study was to evaluate the association between Burnout Syndrome and sociodemographic, occupational, and health factors in Mexican police officers. We applied the Maslach Burnout Inventory Human Services Survey (MBI-HSS) to 351 active members of the Mexican police workforce. In addition, a specific questionnaire identified the presence of chronic degenerative diseases, hypertension, diabetes, digestive diseases, self-perception of food quality, and hours of sleep. Furthermore, 23.36% of police workforces presented high levels of burnout; 44.16% of police were highly emotionally exhausted, 49.29% had lost empathy with people, and 41.03% presented low personal achievement. Moreover, the worst levels of the syndrome were present in people with a poor self-perceived health status, poor perception of diet quality, without regular mealtimes, bad sleep habits, and elevated Body Mass Index. Data suggest that in Mexican police officers, BO is dimensionally different from all other groups previously studied (DP > EE > PA).
How Much Burnout and Coping Influence Quality of Life among Young Oncology Providers in Romania during the COVID-19 Pandemic

This study aims to investigate the correlations between burnout, coping strategies, and quality of life among young oncology healthcare workers in Romania during the COVID-19 pandemic. We collected the data using an online questionnaire consisting of sociodemographic questions, the Maslach Burnout Inventory, the COPE questionnaire, and the 15D instrument. A total of 122 healthcare providers responded to our survey. We evaluated the differences in the scores among the three groups of healthcare workers in oncology under 40 years old: medical oncologists (n = 87), radiation oncologists (n = 11), and oncology nurses (n = 24). Finally, we conducted a correlation analysis between the dimensions of burnout, coping, and quality of life. Overall, the medical oncologists exhibited much higher burnout levels than nurses in the COVID-19 pandemic outbreak, having statistically significant higher levels of emotional exhaustion, depersonalization, and lack of personal achievement. Some factors were inversely associated with burnout: active approach, planning, positive interpretation and growth, and acceptance. Our findings illustrated a very good level of health-related quality of life (average = 0.93, SD = 0.06), and no statistically significant differences were found in the quality of life between the three groups. This study was the first to identify the profile of young oncology providers in Romania. Our findings may be relevant in creating preventive strategies for burnout and increasing the quality of life in Romanian young oncology providers in future crises.
First and second language sentence repetition: a screening measure for dual language learners?

Abstract The sentence repetition (SR) test is considered as a promising diagnostic tool for detecting language proficiency in monolingual learners, but less is known about its potential to identify dual language learners’ (DLLs) linguistic proficiency. Considering that challenges with language learning, such as developmental language disorders (DLDs), is evident in both first and second language (L1 and L2), it is important to use tools that can assess language functions in both languages whenever feasible. We found that students’ L1 and L2 SR performance levels draw upon their phonological short-term memory capacity, vocabulary and grammar skills in the language being assessed. We also found a positive relationship between students’ L1 phonological memory and L2 SR scores, suggesting that DLLs’ phonological short-term memory capacity assessed in their L1 indicates individual differences in short-term verbal memory that support SR performance, as assessed in L2. The results highlight a challenge in both research and clinical settings which often use monolingual assessment tools and associated norms to identify DLLs who might be at risk of developing DLDs or other learning difficulties.
Optimal Distributed MQTT Broker and Services Placement for SDN-Edge Based Smart City Architecture

A smart city is an urban area that collects data from various devices to effectively manage urban resources. The smart city IoT infrastructure connects numerous devices to an Internet-protocol-based low-power wireless network, shares massive amounts of data, and facilitates the development of new services. Message queuing telemetry transport (MQTT), a lightweight exchange protocol for the IoT environment, uses a publish and subscribe structure via a centralized broker to share data. The extent of edge computing provides distributed and closer resources to the data source while maintaining low transmission costs. However, a centralized MQTT data broker is unsuitable for distributed edge resources and could result in high latency, traffic, and bottleneck risk. Therefore, we proposed a distributed MQTT broker optimized architecture. A distributed MQTT broker for edge resources could reduce network traffic and data delivery latency by only managing consumed topics in the network. We formulate an integer non-linear program to optimize container placement and avoid wasting edge computing resources. We compared our proposed architecture to the existing distributed MQTT middleware architecture with greedy and random container placement through extensive simulation. Our methods show better performance in lowering deployment failure ratio, power consumption, network usage, and synchronization overhead.
Factors Motivating Binge-Watching of TV Series Among College Students

The Rapid growth of Internet-based TV companies has transformed the way of video consumption, Internet-Based TV companies are releasing an entire series of programmes at once, which leads consumers to watch the TV series at once or three to four episodes at one sitting. This phenomenon gained popularity due to the development of platforms such as Netflix, Hulu, HBO GO, Amazon Prime, Disney+, and Apple TV (Winland, 2012). Students are spending less time devoted to academic pursuits. Research studies have indicated that students are heavily distracted from their academic pursuits due to binge-watching, with many students spending almost 8 hours per week on binge-watching. Based on an extensive literature review, a glaring gap was noticed in assessing binge-watching behaviour among Indian students. Hence, the paper aims to explore various factors that influence college students’ attitudes towards binge-watching. The study is grounded on four different stimuli that influence Binge-watching: enjoyment, escapism, social influence and convenient access. Design/Methodology/Approach: The present study is a descriptive research design. Quantitative methods were used for the collection and analysis of data. A structured questionnaire based on pre-validated scales was used as a research instrument. The respondents were from the student community across India. Analysis was based on correlation and multiple regression analysis.Originality: The paper significantly contributes to the understanding of factors influencing binge-watching attitudes among students in India. There is a huge dearth of literature concerning binge-watching in India. Findings: The findings of the study indicate that escapism, enjoyment greatly motivate students to spend more time binge-watching. As per the survey, we found out that college students don`t binge-watch because of convenient access and social influence.
Closed Loop Transient Response from the Open Loop Frequency Response

A method is shown for relating the closed loop transient response to the open loop frequency response, which is based on the use of the contour of constant closed loop phase angle, α = −90°. The method primarily yields a second order model of the closed loop system which covers the full range of relative damping (0 < ζ < +∞). A first order model is recommended when prescribed conditions apply. The method is simpler and yields better results than currently used methods. In all cases it is assumed that the negative feedback loop has a transfer function of unity and that the closed loop system is stable.
Decomposition of Socioeconomic Inequality in Cardiovascular Disease Prevalence in the Adult Population: A Cohort-based Cross-sectional Study in Northwest Iran

Objectives The incidence of cardiovascular disease (CVD) mortality is increasing in developing countries. This study aimed to decompose the socioeconomic inequality of CVD in Iran. Methods This cross-sectional population-based study was conducted on 20 519 adults who enrolled in the Ardabil Non-Communicable Disease cohort study. Principal component analysis and multivariable logistic regression were used, respectively, to estimate socioeconomic status and to describe the relationships between CVD prevalence and the explanatory variables. The relative concentration index, concentration curve, and Blinder-Oaxaca decomposition model were used to measure and decompose the socioeconomic inequality. Results The overall age-adjusted prevalence of CVD was 8.4% in northwest Iran. Multivariable logistic regression showed that older adults, overweight or obese adults, and people with hypertension and diabetes were more likely to have CVD. Moreover, people with low economic status were 38% more likely to have CVD than people with high economic status. The prevalence of CVD was mainly concentrated among the poor (concentration index, −0.077: 95% confidence interval, −0.103 to −0.060), and 78.66% of the gap between the poorest and richest groups was attributed to differences in the distribution of the explanatory variables included in the model. Conclusions The most important factors affecting inequality in CVD were old age, chronic illness (hypertension and diabetes), marital status, and socioeconomic status. This study documented stark inequality in the prevalence of CVD, wherein the poor were more affected than the rich. Therefore, it is necessary to implement policies to monitor, screen, and control CVD in poor people living in northwest Iran.
Identification of sSIGLEC5 and sLAG3 as New Relapse Predictors in Lung Cancer

Lung cancer (LC) continues to be the leading cause of cancer-related deaths in both men and women worldwide. After complete tumour resection, around half of the patients suffer from disease relapse, emphasising the critical need for robust relapse predictors in this disease. In search of such biomarkers, 83 patients with non-microcytic lung cancer and 67 healthy volunteers were studied. Pre-operative levels of sSIGLEC5 along with other soluble immune-checkpoints were measured and correlated with their clinical outcome. Soluble SIGLEC5 (sSIGLEC5) levels were higher in plasma from patients with LC compared with healthy volunteers. Looking into those patients who suffered relapse, sSIGLEC5 and sLAG3 were found to be strong relapse predictors. Following a binary logistic regression model, a sSIGLEC5 + sLAG3 score was established for disease relapse prediction (area under the curve 0.8803, 95% confidence intervals 0.7955–0.9652, cut-off > 2.782) in these patients. Based on score cut-off, a Kaplan–Meier analysis showed that patients with high sSIGLEC5 + sLAG3 score had significantly shorter relapse-free survival (p ≤ 0.0001) than those with low sSIGLEC5 + sLAG3 score.Our study suggests that pre-operative sSIGLEC5 + sLAG3 score is a robust relapse predictor in LC patients.
Parameter Estimation for a Gas Lifting Oil Well Model Using Bayes' Rule and the Metropolis–Hastings Algorithm

Oil well models are frequently used in the oil production process. Estimation of unknown parameters of these models has long been a question of great interest in the oil industry ﬁeld. Data collected from an oil well system can be useful for identifying and characterizing the parameters in the corresponding model. In this article, we present a solution to estimate the parameters and uncertainty of a gas lifting oil well model by designing Bayesian inference and using the Metropolis-Hastings algorithm. To present and evaluate the estimation, the performance of the chains and the distributions of the parameters were shown, followed by posterior predictive distributions and sensitivity analysis. Compared with the conventional maximum likelihood estimation methods that tried to identify one optimum value for each parameter, more information of the parameters is obtained by using the proposed model. The insights gained from this study can beneﬁt the optimization and advanced control for the oil well operation.
C-Wall: Conflict-Resistance in Privacy-Preserving Cloud Storage

Following the success of cloud computing, it has been shown its importance to realize various access control models in the cloud storage setting. Chinese Wall is a traditional access control model in business for solving the conflict of interest (CoI) problem, and it would be very interesting to achieve conflict-resistant in cloud storage system. However, the access control model does not ensure the privacy of users, and it may reveal the user's interest, investment tendency, etc. Therefore, it raises a big challenge to implement the Chinese Wall without compromising the user's privacy. In this paper, we focus on the Chinese Wall model and apply it to the cloud storage while protecting the access patterns of users. Specifically, we first formulate the tree-based Chinese Wall access control and then propose the Chinese Wall Protocol (called C-Wall). We prove that our C-Wall not only realizes the conflict-resistant but also protects the user's privacy with universally composable security. Besides, we also apply C-Wall to privacy-preserving cloud storage and propose the C<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mn>2</mml:mn></mml:msup></mml:math><inline-graphic xlink:href="xiang-ieq1-3171772.gif"/></alternatives></inline-formula>-Wall, which not only maintains C-Wall's features, but also ensures the sensitive files from being touched by “honest-but-curious” cloud servers. Furthermore, we evaluate our C<inline-formula><tex-math notation="LaTeX">$^{2}$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mn>2</mml:mn></mml:msup></mml:math><inline-graphic xlink:href="xiang-ieq2-3171772.gif"/></alternatives></inline-formula>-Wall by theoretical analysis and experimental validation. Experimental results show its effectiveness and efficiency for practical deployment.
Perfusion Visualization during Ileal J-Pouch Formation—A Proposal for the Standardization of Intraoperative Imaging with Indocyanine Green Near-Infrared Fluorescence and a Postoperative Follow-Up in IBD Surgery

Background: An anastomotic leak (AL) after a restorative proctocolectomy and an ileal J-pouch increases morbidity and the risk of pouch failure. Thus, a perfusion assessment during J-pouch formation is crucial. While indocyanine green near-infrared fluorescence (ICG-NIRF) has shown potential to reduce ALs, its suitability in a restorative proctocolectomy remains unclear. We aimed to develop a standardized approach for investigating ICG-NIRF and ALs in pouch surgery. Methods: Patients undergoing a restorative proctocolectomy with an ileal J-pouch for ulcerative colitis at an IBD-referral-center were included in a prospective study in which an AL within 30 postoperative days was the primary outcome. Intraoperatively, standardized perfusion visualization with ICG-NIRF was performed and video recorded for postoperative analysis at three time points. Quantitative clinical and technical variables (secondary outcome) were correlated with the primary outcome by descriptive analysis and logistic regression. A novel definition and grading of AL of the J-pouch was applied. A postoperative pouchoscopy was routinely performed to screen for AL. Results: Intraoperative ICG-NIRF-visualization and its postoperative visual analysis in 25 patients did not indicate an AL. The anastomotic site after pouch formation appeared completely fluorescent with a strong fluorescence signal (category 2) in all cases of ALs (4 of 25). Anastomotic site was not changed. ICG-NIRF visualization was reproducible and standardized. Logistic regression identified a two-stage approach vs. a three-stage approach (Odds ratio (OR) = 20.00, 95% confidence interval [CI] = 1.37–580.18, p = 0.029) as a risk factor for ALs. Conclusion: We present a standardized, comparable approach of ICG-NIRF visualization in pouch surgery. Our data indicate that the visual interpretation of ICG-NIRF alone may not detect ALs of the pouch in all cases—quantifiable, objective methods of interpretation may be required in the future.
Emerging Potential of Plant Virus Nanoparticles (PVNPs) in Anticancer Immunotherapies

Cancer immunotherapies using plant virus nanoparticles (PVNPs) have achieved considerable success in preclinical studies. PVNP based nanoplatforms can be endogenous immune adjuvants and act as nanocarriers that stabilize and deliver cancer antigens and exogenous immune adjuvants. Although they do not infect mammalian cells, PVNPs are viruses and they are variably recognized by pathogen pattern recognition receptors (PRR), activate innate immune cells including antigen-presenting cells (APCs), and increase the expression of costimulatory molecules. Novel immunotherapy strategies use them as in situ vaccines (ISV) that can effectively inhibit tumor growth after intratumoral administration and generate expanded systemic antitumor immunity. PVNPs combined with other tumor immunotherapeutic options and other modalities of oncotherapy can improve both local and systemic anti-tumor immune responses. While not yet in clinical trials in humans, there is accelerating interest and research of the potential of PVNPs for ISV immune therapy for cancer. Thus, antitumor efficacy of PVNPs by themselves, or loaded with soluble toll-like receptor (TLR) agonists and/or cancer antigens, will likely enter human trials over the next few years and potentially contribute to next-generation antitumor immune-based therapies.
IFN-γ and TNF Induce Senescence and a Distinct Senescence-Associated Secretory Phenotype in Melanoma

Immune checkpoint blockade (ICB) therapy is a central pillar of melanoma treatment leading to durable response rates. Important mechanisms of action of ICB therapy include disinhibition of CD4+ and CD8+ T cells. Stimulated CD4+ T helper 1 cells secrete the effector cytokines interferon-gamma (IFN-γ) and tumor necrosis factor alpha (TNF), which induce senescence in tumor cells. Besides being growth-arrested, senescent cells are metabolically active and secrete a large spectrum of factors, which are summarized as senescence-associated secretory phenotype (SASP). This secretome affects the tumor growth. Here, we compared the SASP of cytokine-induced senescent (CIS) cells with the SASP of therapy-induced senescent (TIS) cells. Therefore, we established in vitro models for CIS and TIS in melanoma. The human melanoma cell lines SK-MEL-28 and WM115 were treated with the cytokines IFN-γ and TNF as CIS, the chemotherapeutic agent doxorubicin, and the cell cycle inhibitor palbociclib as TIS. Then, we determined several senescence markers, i.e., growth arrest, p21 expression, and senescence-associated β-galactosidase (SA-β-gal) activity. For SASP analyses, we measured the regulation and secretion of several common SASP factors using qPCR arrays, protein arrays, and ELISA. Each treatment initiated a stable growth arrest, enhanced SA-β-gal activity, and—except palbociclib—increased the expression of p21. mRNA and protein analyses revealed that gene expression and secretion of SASP factors were severalfold stronger in CIS than in TIS. Finally, we showed that treatment with the conditioned media (CM) derived from cytokine- and palbociclib-treated cells induced senescence characteristics in melanoma cells. Thus, we conclude that senescence induction via cytokines may lead to self-sustaining senescence surveillance of melanoma.
CLASSIFICATION AND DIGITAL RESTORATION OF DAMAGED ARABIC MANUSCRIPTS

This paper proposes a novel an effective approach to classify the damage in Ancient Arabic manuscripts through Damage Manuscripts Classification (DMC) Model; into two types, each type has spatial model. The first type is Fading Text Color (FTC) Model, and the second is Missing Part of Text (MPT) Model. For the first type, which is the Fading text color, it is done through (FTC) Model, where segmentation, contour strength and contour size algorithms were applied. As for the second type, we applied some segmentation algorithms to separate image of damaged manuscripts into foreground and background. Segmentation by thresholding applied on background to detect if there are missing in text to complete it based on database which we had prepared for this purpose including the handwritten Arabic fonts and the forms of letters in different styles such as Naskh , Reqaa,. etc. detection of style algorithm is also used to determine the style of missing text according to the same database , then digital restoration applied to the image. Applying Pre-processes on the used data yields good classifications’ results. The contribution of this work is the introduction of synthetic features that enhance the classification performance. For testing purposes, two famous books from the Islamic literature are used: 1) pages of the Ottoman Quran and 2) Some Quran verses in Naskh script .