Miracle-dz/UniFAR-FTUs huggingface dataset:
The Dark Triad of Personality: Is Psychopathy a Good Predictor of Workplace Stress?

Background: Psychopathy as an antisocial characteristic of an individual is characterized by a lack of empathy, guilt, inability to control impulsive behavior, irresponsibility, irritability and aggressive behavior. Because of the traits that underlie this factor, we hypothesized that psychopaths would experience more stress in the work environment. Stress, in this article, is operationalized within Karasek’s model of stress which consider that contextual variables (excessive demands on work, lack of social support, and lack of control at work) are responsible for experiencing stress at the workplace. This kind of work context, according to our assumption, can affect psychopaths to have a weaker response to stressful situations. Objective: To determine the predictive power of psychopathy as a factor in the dark triad in order to explain the workplace stress. Methods: We conducted the study in one company on a sample of 235 respondents. Data were collected using the Sociodemographic Characteristics Questionnaire, the Dark Triad Questionnaire (SD27) and the Copenhagen Questionnaire for measuring cognitive, behavioral and somatic stress. Results: The mean age of the respondents was 39.04±10.27 years. Using standard regression analysis, we found that the dark triad model is the only significant one in explaining cognitive stress, and a significant predictor is psychopathy. Conclusion: In majority of previous studies, psychopathy has not been associated with stress, and the findings are important for future research that should shed light on the complex relationship between psychopathy and stress.
Effect of Cooking Oil on the Fatty Acid Profile of Beef Sausage Fortified with Edible Deboned Meat Waste

Application of cooking oil during thermal processing can influence the nutritional qualities of meat products during consumption. This study determined the effect of frying with sunflower and olive oil on the fatty acid profile of sausage fortified with edible meat waste (EMW) as a fat replacer was evaluated. Fresh beef sausages were formulated in ratios of 30% lean meat (LM) and 70% EMW, 50% LM and 50% EMW, and 90% LM and 10% fat (control) and designated as T1, T2, and T3, respectively. The proximate analysis results revealed significant differences (P < 0.05) in fat, fat free dry matter (FFDM), and moisture contents across the treatment. Fresh beef sausage fortified with 70% EMW had the highest fat contents (25.7 ± 0.83%) while those fortified with 10% fat (T3) had the highest FFDM (55.85 ± 0.57%) and moisture content (69.15 ± 0.62) compared to other treatments. In addition, among individual saturated fatty acids, beef sausage fortified with 50% meat wastes (T1) revealed significantly higher palmitic acid (31.06 ± 0.13), stearic acid (22.52 ± 0.29), myristic acid (3.84 ± 0.05), and lauric acid (0.04 ± 0.05) and the lowest margaric (0.98 ± 0.02) contents as compared to treatments T2 and T3. Also, beef sausage containing 10% fat showed the lowest (P < 0.05) saturated fatty acid (SFA) and higher monounsaturated (MUFA), polyunsaturated fatty acid (PUFA), n-6, n-3, PUFA : SFA, PUFA/MUFA, n-6/n-3, and desaturase indexes (DI) compared to treatments T1 and T2. Frying with sunflower oil significantly increased PUFA, n-6, n-6/n-3, and desaturase indexes and lowered SFA, n-3, and PUFA/SFA compared to frying with olive oil. In relation to raw beef sausage, frying with oil substantially increased the amount of MUFA, PUFA, n-6, and PUFA/SFA but reduced SFA content across the treatments.
Effect of sitagliptin on proteinuria in patients with type 2 diabetes – A renoprotective effect of sitagliptin

Background: Diabetic nephropathy, the leading cause of chronic renal failure, is related to diabetes poor control. Some antihyperglycemic drugs like dipeptidyl peptidase-4 inhibitors have shown to prevent diabetic nephropathy. This study endeavors to assess the effect of sitagliptin on proteinuria in Iranian type 2 diabetics. Materials and Methods: A total of 90 type 2 diabetic patients aged between 30 and 80 years with glycated hemoglobin (HbA1C) <8.5 and normotensive under treatment of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers were randomly assigned into two groups. One group received 50 mg sitagliptin per day and the other group received placebo. The two groups were evaluated for albumin–creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR) at baseline and 3 months later. Results: Eighty-four patients, 38 (45%) males and 46 (55%) females, were enrolled in this study. The mean age was 58.47 ± 7.33. The two groups did not differ in baseline characteristics. After 3 months, in the sitagliptin group, HbA1C (7.89 ± 0.39 to 7.37 ± 0.61, P < 0.001), fasting blood sugar (FBS) (136.86 ± 22.51 to 130.53, P = 0.04), systolic blood pressure (BP) (124.39 ± 9.70 mmHg to 119.32 ± 9 mmHg), diastolic BP (76.44 ± 6.53 to 73.13 ± 5.34 mmHg, P < 0.001), and ACR (314.40 ± 414.64 to 293.49 ± 400.71, P < 0.001) were significantly decreased and eGFR was significantly increased (73.35 ± 10.73 to 76.86 ± 10.59, P < 0.001) at 3 months compared to the placebo group. ACR reduction was higher in macroalbuminuric (Ma) patients compared to microalbuminuric (Mi) patients in the sitagliptin group (−30.25 ± 35.57 vs. −11.12 ± 14.01, P = 0.02). No significant difference was observed between the Ma and Mi subgroups regarding changes in eGFR. Univariate analysis showed that changes in ACR correlated with FBS (r = 0.68, P < 0.0001), insulin (r = 0.44, P = 0.03), and homeostatic model assessment for insulin resistance (r = 0.69, P < 0.0001) and did not correlate with eGFR and BP. Conclusion: In conclusion, sitagliptin is a well-tolerated drug that improves glycemic control, lowers BP, and reduces urinary albumin excretion, especially in Ma type 2 diabetic patients.
Using climatic variables alone overestimate climate change impacts on predicting distribution of an endemic species

Plant species distribution is constrained by both dynamic and static environmental variables. However, relative contribution of dynamic and static variables in determining species distributions is not clear and has far reaching implications for range change dynamics in a changing world. Prunus eburnea (Spach) Aitch. & Hemsl. is an endemic and medicinal plant species of Iran. It has rendered itself as ecologically important for its functions and services and is currently in need of habitat conservation measures requiring investigation of future potential distribution range. We conducted sampling of 500 points that cover most of Iran plateau and recorded the P. eburnea presence and absence during the period 2015–2017. In this study, we evaluated impacts of using only climatic variables versus combined with topographic and edaphic variables on accuracy criteria and predictive ability of current and future habitat suitability of this species under climate change (CCSM4, RCP 2.6 in 2070) by generalized linear model and generalized boosted model. Models’ performances were evaluated using area under the curve, sensitivity, specificity and the true skill statistic. Then, we evaluated here, driving environmental variables determining the distribution of P. eburnea by using principal component analysis and partitioning methods. Our results indicated that prediction with high accuracy of the spatial distribution of P. eburnea requires both climate information, as dynamic primary factors, but also detailed information on soil and topography variables, as static factors. The results emphasized that environmental variable grouping influenced the modelling prediction ability strongly and the use of only climate variables would exaggerate the predicted distribution range under climate change. Results supported using both dynamic and static variables improved accuracy of the modeling and provided more realistic prediction of species distribution under influence of climate change.
Why do patients interrupt and return to antiretroviral therapy? Retention in HIV care from the patient’s perspective in Johannesburg, South Africa

Background Retention in care is required for optimal clinical outcomes in people living with HIV (PLHIV). Although most PLHIV in South Africa know their HIV status, only 70% are on antiretroviral therapy (ART). Improved retention in care is needed to get closer to sustained ART for all. In January 2019, Anova Health Institute conducted a campaign to encourage patients who had interrupted ART to return to care. Methods Data collection was conducted in one region of Johannesburg. This mixed methods study consisted of two components: 1) healthcare providers entered data into a structured tool for all patients re-initiating ART at nine clinics over a nine-month period, 2) Semi-structured interviews were conducted with a sub-set of patients. Responses to the tool were analysed descriptively, we report frequencies, and percentages. A thematic approach was used to analyse participant experiences in-depth. Results 562 people re-initiated ART, 66% were women, 75% were 25–49 years old. The three most common reasons for disengagement from care were mobility (30%), ART related factors (15%), and time limitations due to work (10%). Reasons for returning included it becoming easier to attend the clinic (34%) and worry about not being on ART (19%). Mobile interview participants often forgot their medical files and expressed that managing their ART was difficult because they often needed a transfer letter to gain access to ART at another facility. On the other hand, clinics that had flexible and extended hours facilitated retention in care. Conclusion In both the quantitative data, and the qualitative analysis, changing life circumstances was the most prominent reason for disengagement from care. Health services were not perceived to be responsive to life changes or mobility, leading to disengagement. More client-centred and responsive health services should improve retention on ART.
Management of adrenocortical carcinoma: are we making progress?

Adrenocortical carcinoma (ACC) is a rare malignancy characterized by aggressive biology and potential endocrine activity. Surgery can offer cure for localized disease but more than half of patients relapse and primary unresectable or metastasized disease is frequent. Prognosis of metastatic ACC is still limited, with less than 15% of patients alive at 5 years. Recent advances in understanding the molecular profile of ACC underline the high complexity of this disease, which is characterized by limited drugable molecular targets as well as by a complex interplay between a yet scarcely understood microenvironment and potential endocrine activity. Particularly steroid-excess further complicates therapeutic concepts such as immunotherapy, which have markedly improved outcome in other disease entities. To date, mitotane remains the only approved drug for adjuvant and palliative care in ACC. Standard chemotherapy-based protocols with cisplatin, doxorubicin and etoposide offer only marginal improvement in long-term outcome and the number of clinical trials conducted is low due to the rarity of the disease. In the current review, we summarize principles of oncological management for ACC from localized to advanced disease and discuss novel therapeutic strategies, including targeted therapies such as tyrosine kinase inhibitors and antibodies, immunotherapy with a focus on checkpoint inhibitors, individualized treatment concepts based on molecular characterization by next generation sequencing methods, the role of theranostics and evolvement of adjuvant therapy.
Alpha-single chains of collagen type VI inhibit the fibrogenic effects of triple helical collagen VI in hepatic stellate cells

The interaction of extracellular matrix (ECM) components with hepatic stellate cells (HSCs) is thought to perpetuate fibrosis by stimulating signaling pathways that drive HSC activation, survival and proliferation. Consequently, disrupting the interaction between ECM and HSCs is considered a therapeutical avenue although respective targets and underlying mechanisms remain to be established. Here we have interrogated the interaction between type VI collagen (CVI) and HSCs based on the observation that CVI is 10-fold upregulated during fibrosis, closely associates with HSCs in vivo and promotes cell proliferation and cell survival in cancer cell lines. We exposed primary rat HSCs and a rat hepatic stellate cell line (CFSC) to soluble CVI and determined the rate of proliferation, apoptosis and fibrogenesis in the absence of any additional growth factors. We find that CVI in nanomolar concentrations prevents serum starvation-induced apoptosis. This potent anti-apoptotic effect is accompanied by induction of proliferation and acquisition of a pronounced pro-fibrogenic phenotype characterized by increased α-smooth muscle actin, TGF-β, collagen type I and TIMP-1 expression and diminished proteolytic MMP-13 expression. The CVI-HSC interaction can be disrupted with the monomeric α2(VI) and α3(VI) chains and abrogates the activating CVI effects. Further, functional relevant α3(VI)—derived 30 amino acid peptides lead to near-complete inhibition of the CVI effect. In conclusion, CVI serves as a potent mitogen and activating factor for HSCs. The antagonistic effects of the CVI monomeric chains and peptides point to linear peptide sequences that prevent activation of CVI receptors which may allow a targeted antifibrotic therapy.
The influence of valence shifts in fear appeals on message processing and behavioral intentions: A moderated mediation model

Newer approaches in health communication research indicate that understanding the flow of emotional experiences during exposure to fear appeals can clarify their persuasive effects. In a laboratory experiment, the impact of valence shifts during exposure to fear appeals on determinants of health-relevant behaviors were examined. Continuous response measurement allowed gathering real-time data about participants’ experiences of valence shifts during exposure. Among the results, a shift from negative to positive valence promoted efficacy perceptions but only for people being personally affected by the health issue. Perceived efficacy, in turn, increased intentions to put recommended behaviors into practice. This suggests that inducing positive valence shifts in health messages improves their effectiveness, especially for relevant target groups.
Association between C-Maf-inducing protein gene rs2287112 polymorphism and schizophrenia

Background Schizophrenia is a severely multifactorial neuropsychiatric disorder, and the majority of cases are due to genetic variations. In this study, we evaluated the genetic association between the C-Maf-inducing protein (CMIP) gene and schizophrenia in the Han Chinese population. Methods In this case-control study, 761 schizophrenia patients and 775 healthy controls were recruited. Tag single-nucleotide polymorphisms (SNPs; rs12925980, rs2287112, rs3751859 and rs77700579) from the CMIP gene were genotyped via matrix-assisted laser desorption/ionization time of flight mass spectrometry. We used logistic regression to estimate the associations between the genotypes/alleles of each SNP and schizophrenia in males and females, respectively. The in-depth link between CMIP and schizophrenia was explored through linkage disequilibrium (LD) and further haplotype analyses. False discovery rate correction was utilized to control for Type I errors caused by multiple comparisons. Results There was a significant difference in rs287112 allele frequencies between female schizophrenia patients and healthy controls after adjusting for multiple comparisons (χ2 = 12.296, Padj = 0.008). Females carrying minor allele G had 4.445 times higher risk of schizophrenia compared with people who carried the T allele (OR = 4.445, 95% CI [1.788–11.046]). Linkage-disequilibrium was not observed in the subjects, and people with haplotype TTGT of rs12925980–rs2287112–rs3751859–rs77700579 had a lower risk of schizophrenia (OR = 0.42, 95% CI [0.19–0.94]) when compared with CTGA haplotypes. However, the association did not survive false discovery rate correction. Conclusion This study identified a potential CMIP variant that may confer schizophrenia risk in the female Han Chinese population.
A STUDY ON THE IMPACT OF CORPORATE SOCIAL RESPONSIBILITY ON SERVICE ORGANISATIONS WITH SPECIAL REFERENCE TO BRANDING AND BRAND VALUE

In recent years, corporate social responsibility has gained much attention. A number of studies have been conducted to determine the impact of corporate social responsibility on different dimensions of organizations that includes corporate image, sales and corporate branding and brand value. Brand image is considered the basic and an important part of brand equity. The process of branding and creating a brand strategy forms a critical component to CSR and authentic concern for the environment while remaining focused on profitability. There are several organizations that have been started with corporate social responsibility as an essential or primary strategic element that are extremely successful. Consider the brand image and brand messages these organizations are sending to the marketplace and the imagery these brands create. Brand image and brand messages energize an organization‟s brand focused on authenticity, shared values, and quality products or services.
Predictors of learning mathematics in 5-8 graded students

Purpose of the current study was to determine the relative contribution of the student’s motivation, fluid reasoning and working memory to the prediction of mathematics learning. The study was conducted at Durgapur KC high School in West Bengal. Out of all 5-8 graded students, only two hundred late childhood students aged 10-13 years were taken as sample by simple random sampling. In the 2019 academic session, three tools named Muthee achievement motivation inventory (Muthee & Thomas, 2009), Raven’s Standard Progressive Matrices (SPM), and Working Memory Index Digit Span and Letter-Number Sequencing (WISCIV) were administered to measure students’ motivation, fluid reasoning and working memory respectively. The test score for the whole year, including the final exam of the 2019 academic session, were taken as a dependent variable to measure how much students were learning math. The result showed that student’s motivation, fluid reasoning and working memory were predictor of math learning statistically significant. Cognitive abilities such as fluid & crystallized intelligence, working memory and mathematical memory (LTM), intrinsic motivation all work together when solving problems, resulting in math learning.
Face Proportions, and Analysis of Maxillary Anterior Teeth and Facial Proportions in a Thai Population

Esthetics is the primary consideration for patients looking for prosthetic treatment. Determining the facial types of Thai populations is important because most studies conducted in Caucasian populations mention their facial types, and describe the gender comparisons, and GP of the teeth. This study compared facial proportions, analyzed the maxillary anterior teeth proportions and determined the relationships between teeth with facial measurements using the Golden Proportion (GP) and Golden Standard (GS) in a Thai population. A total of 200 students (18-35 years) with well-aligned maxillary anterior teeth participated in this study. Face heights and widths were measured from the face using digital calipers and faces were classified as narrow, average, and broad. Teeth and face proportions were compared with GP and GS. One-way ANOVA was performed to compare maxillary anterior teeth proportions and facial proportions with different face types (α= 0.05). Pearson’s correlation was used (α= 0.05) to determine the correlation between facial proportion and teeth dimension among different facial types. The findings showed 82.50% narrow face, 13.50% average, and 4% broad face among Thai subjects. No GP or GS was found in the face and anterior teeth, but teeth and face proportions other than GP and GS were found. No significant correlation was found between the Width of the Central Incisor (WCI) with interpupillary distance and alar width. In this study, the GP was not found in the facial and teeth proportion. The data obtained from this study may help to provide guidelines for prosthetic and orthodontic management and help to select the proper size and form of the maxillary anterior teeth to achieve proper esthetic outcomes in the Thai population.
Hybrid Models for Control of Changing-Contact Manipulation Tasks

Many robot manipulation tasks involve discrete action sequences characterized by continuous dynamics, while the transitions between these discrete dynamic modes are characterized by discontinuous dynamics. The individual modes may represent different types of contacts, surfaces, or other factors, and each mode and transition between the modes may require a different control strategy. This paper describes a piece-wise continuous, hybrid control framework for such manipulation tasks. The underlying representation enables the robot to automatically and efﬁciently detect the transitions between known modes, recognize new modes, and incrementally learn a dynamics model for variable impedance (i.e., stiffness) control in each mode, invariant to the direction of motion and the magnitude of applied forces. The framework is evaluated on a robot manipulator sliding an object along a surface to achieve a desired motion trajectory in the presence of changes in surface friction, applied force, or the type of contact between the object and the surface.
IMPROVISED DEEP NEURAL NETWORK USING EAGLE STRATEGY OPTIMIZATION FOR AGRICULTURE LAND DROUGHT PREDICTION

: The advancement in the field of agriculture is more essential to forecast the yield loss and the drought monitoring to discover possible intervention areas. The machine learning models plays a vital role in the process of agriculture to detect the anomaly of droughts to avoid the crop yield loss by monitoring rainfall, temperature and moisture. Though there are many prediction models are available, deep knowledge about the pattern of climatic condition is very essential to improve the drought prediction. Thus, this paper concentrated on developing an enriched prediction model which optimize the performance of the Deep Neural Network by inducing the intelligence of the eagle strategy to fine tune the parameters values which influence the accuracy of prediction model. The simulation results proved that the Enriched Eagle Strategy based Deep Neural Network predict the presence of Drought in eight different districts all over India, compared to the other conventional prediction models.
Engineering plasmon modes and their loss in armchair graphene nanoribbons by selected edge-extended defects

The effect of edge modification of armchair graphene nanoribbons (AGNRs) on the collective excitations are theoretically investigated. The tight-binding method is employed in conjunction with the dielectric function. Unconventional plasmon modes and their association with the flat bands of the specially designed AGNRs are thoroughly studied. We demonstrate the robust relationship between the novel collective excitations and both the type and period of the edge modification. Additionally, we reveal that the main features displayed in the (momentum, frequency)-phase diagrams for both single-particle and collective excitations of AGNRs can be efficiently tuned by edge-extended defects. Our obtained plasmon modes are found to be analogous to magnetoplasmons associated with collective excitations of Landau-quantized electrons. This work provides a unique way to engineer discrete magnetoplasmon-like modes of AGNRs in the absence of magnetic field.