Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlates of cervical cancer prevention advocacy and cervical cancer screening in Uganda: Cross-sectional evaluation of a conceptual model

An approach to increasing cervical cancer (CC) screening is to empower women who have been screened to act as advocates and encourage other women they know to get screened. We examined correlates of CC screening advocacy and CC screening uptake among constructs in our conceptual model of factors driving engagement in advocacy. A cross-sectional, correlational analysis was conducted with survey data from 40 women (index participants) who had recently screened for CC, and 103 female members of their social network (alter participants) who had not been screened. Variables measured included CC prevention advocacy, as well as internalized CC stigma, sharing of CC screening result, CC knowledge, healthy bodily intake (i.e., diet; alcohol and cigarette use) and self-efficacy related to CC service utilization and CC prevention advocacy, which were hypothesized to be associated with advocacy. Bivariate and multivariable regression analyses, controlling for clustering, were conducted. Among index participants, greater engagement in advocacy was positively correlated with CC knowledge, sharing of CC screening result, and CC service utilization self-efficacy. Women who had screened positive and received treatment for precancerous lesions reported greater CC prevention advocacy, CC knowledge and healthy living, compared to those who screened negative. In multiple regression analyses, CC screening was positively associated with CC prevention advocacy and being age 36 or older, and CC prevention advocacy was also positively associated with CC service utilization self-efficacy. These findings support the validity of our conceptual model regarding factors associated with engagement in CC prevention advocacy among women screened for CC. The strong association between CC prevention advocacy and both CC screening uptake and CC service utilization self-efficacy suggests the potential value of advocacy promotion among women who have been screened, as well as for increasing screening uptake.
Correlation Between Employee Commitment and Organizational Capabilities of Nigerian Bottling Company

Purpose: This study focused on employee commitment and organizational capabilities of Nigerian Bottling Firms, South-East. Research Methodology: The study adopted correlational survey design and questionnaire as instrument for data collection. The total population of the study comprised of 610 participants from the cadre of senior level managers, middle level managers, and lower-level staff/subordinates of the firm. The sample size was determined using Taro Yamane formula and calculated as 242. Simple random sampling technique was adopted in the distribution of the survey. Out of 242 questionnaires administered only 226 were filled and returned while the remaining 16 were not utilized for the study. Result: The results of hypothesis confirmed a strong correlation between employee motivation and organizational competitiveness. Limitations: The data collected from the field survey are limited to Owerri and Enugu production plant. Contributions: The researchers contribute to knowledge in the literature through the use of new concepts in the research objective, use analytical tool, industry of study and geographic coverage. Practical Implications: The researchers recommend managers to routinely re-evaluate their organizational strengths and weaknesses and work with the human resources department to fill competency shortages. Novelty: The researchers developed a mathematical model representing employee commitment and organizational capabilities in the methodology.
Erving Goffman: The Social Science Maverick. Assessing the Interdisciplinary Impact of the Most Cited American Sociologist

Erving Goffman has a reputation as an intellectual maverick who did not fit neatly into any disciplinary mold. His failure to adhere to professional conventions and occasionally off-putting demeanor are mentioned as an aside that has little to do with his oversize influence on the science of society. This paper advances a thesis that Goffman’s status as the most cited American sociologist and widespread influence across social science is related to his principled refusal to fit his scholarship into prevailing scholarly canons. The argument is made that Goffman shared with his mentor, Everett Hughes, misgivings about the narrow professional focus in contemporary sociology, that his cross-disciplinary approach advanced social inquiry beyond its traditional confines, and that his colloquial style and penchant for long essays helped disseminate his ideas. The discussion starts with an overview of Goffman’s professional career, after which it moves to the reception of his ideas by fellow sociologists and the impact of his work on neighboring disciplines. The study draws on the interviews, correspondence, and other documents assembled in the Erving Goffman Archives, as well as on several social science citation indexes and datasets illuminating Goffman’s stature in various fields of scholarship.
Deep learning methods applied to digital elevation models: state of the art

Abstract Deep Learning (DL) has a wide variety of applications in various thematic domains, including spatial information. Although with limitations, it is also starting to be considered in operations related to Digital Elevation Models (DEMs). This study aims to review the methods of DL applied in the field of altimetric spatial information in general, and DEMs in particular. Void Filling (VF), Super-Resolution (SR), landform classification and hydrography extraction are just some of the operations where traditional methods are being replaced by DL methods. Our review concludes that although these methods have great potential, there are aspects that need to be improved. More appropriate terrain information or algorithm parameterisation are some of the challenges that this methodology still needs to face.
The Impact on Employment for Rural Cancer Patients and Their Caregivers Travelling to Major Cities for Treatment

Purpose. A cancer diagnosis significantly impacts daily life, particularly for those living outside of major cities who must travel to receive cancer treatment. This study investigated the impact of cancer and travelling for treatment on the employment of rural cancer patients and their caregivers. Methods. Cancer patients staying in subsidised accommodation lodges in Queensland, and their nominated caregivers, described employment status prior to diagnosis in a structured interview. Three months later, they answered several open-ended questions about the impact of cancer and travelling for treatment on their employment. Descriptive statistics and thematic analysis were used to report and analyse responses. Results. Of 308 rural cancer patients in paid employment prediagnosis, 70% reported a change in employment postdiagnosis, with 62% of these patients no longer working. Many of those still employed postdiagnosis required extended leave, flexible working arrangements, and a gradual return to work, particularly for those experiencing ongoing treatment side effects. Of the 102 rural caregivers in paid employment prior to the patient’s diagnosis, 56% reported a change in employment after diagnosis, with 37% of these caregivers no longer working. Many caregivers were unable to work while at the lodge, except for those with flexible or remote work arrangements and low caregiver burden. Financial stress from loss of income and limited support in returning to work were common experiences. Conclusions. Disruptions to employment are common for people in rural areas affected by cancer. Support from employers is vital, including offering tasks that can be completed remotely or require less physical effort.
Multi-Net Fusion: Exploring a Brain-Inspired Neural Network Model for Facial Expression Recognition

Brain-inspired facial expression recognition is a promising but challenging research direction with significant potential for applications in human-computer interaction and intelligent image analysis. However, current mainstream FER models, which are single-pathway and global feature-based, still have a long way to go to match the performance of the human brain in FER. To narrow this gap, this paper proposes a novel multi-net fused FER framework that incorporates specific FER mechanisms from the human brain into deep learning. Different from most FER model designers, we transfer our main focus from obtaining high-quality global features through data augmentation and network optimization to referring the cognitive processes involved in different facial expression classes, classification preference, and other factors that contribute to the human brain’s FER mechanisms. The framework includes data preprocessing, activeness estimation, multi-net classification, and fusion recognition. We validate and test the proposed framework using general datasets, and the results show that it performs well in FER tasks. The works in this paper provide exploratory ideas and a basis for future research in this direction.
Spatial heterogeneity of high-altitude phytocenoses and soil properties

Spatial variations in soil properties under four alpine plant communities are studied. With an increase in the distance between the points of soil sampling from 1 to 7 m, the differences in soil properties remain the same. Averaged characteristics of soil properties under different plant communities do not uniquely correlate with variance of these properties. A correlation between soil properties and the presence of particular plant species in phytocenoses is found only in a few cases.
Enhancing Positron Emission Tomography Image Reconstruction: A Bayesian Approach Incorporating Total Variation and Median Root Prior

Positron Emission Tomography (PET) holds substantial promise in biomedical research and clinical diagnostics. Nonetheless, PET imaging's constraints, typified by deficient sampling and considerable noise interference, often result in the production of inferior quality reconstructed images. These shortcomings can potentially undermine the clinical utility of the modality. To address this issue, this study introduces a novel image reconstruction algorithm underpinned by Bayesian theory that incorporates the total variation model and the median root prior (MRP) algorithm. The iterative resolution process of the algorithm comprises two stages. Initially, the MRP algorithm is employed for image reconstruction. Subsequently, the total variation model is applied to attenuate noise within the reconstructed image. Simulation outcomes reveal that the proposed algorithm effectively mitigates Poisson noise while preserving critical image details, such as edges. When contrasted with traditional reconstruction algorithms, the proposed approach enhances both the precision and reliability of PET imaging markedly. Thus, the algorithm carries significant potential for clinical application and could substantially improve the quality of PET imaging.
Harsh Childhood Discipline and Developmental Changes in Adolescent Aggressive Behavior: The Mediating Role of Self-Compassion

Harsh discipline during childhood (psychological aggression and corporal punishment) has been found to be an early risk factor for adolescent aggressive behavior. However, previous studies have mainly examined the relationship between harsh discipline as a whole and the level of adolescent aggressive behavior. This study investigates the effects of childhood psychological aggression and corporal punishment on the initial levels and rate of change in adolescent aggressive behavior, as well as the mediating role of self-compassion in this relationship. Using cluster sampling, a three-wave follow-up assessment was conducted on 1214 high-school students (60.7% boys; mean age at Wave 1 = 15.46 ± 0.71). The results showed that childhood psychological aggression and corporal punishment had a positive predictive effect on the development level of adolescent aggressive behavior. However, only childhood psychological aggression significantly directly attenuated the decline rate of adolescent aggressive behavior. In addition, both childhood psychological aggression and corporal punishment indirectly affected the initial levels and growth rate of adolescent aggressive behavior through self-compassion. These findings could provide potential targets for prevention and intervention programs aimed at improving aggressive behavior in Chinese adolescents.
Mathematical Model for Spread and Control of Cocoa Black Pod Disease

Black pod disease is a major threat to cocoa production worldwide. A mathematical model for the spread of cacao black pod disease is presented in this article. The model takes into account several variables that influence the spread of the disease. A set of differential equations that are numerically solved using Runge-Kutta method embedded in MATLAB software are used to simulate the dynamics of disease transmission which form the basis of the model. Utilizing information from the literature and ecological observations from cocoa fields in West Africa, where black pod disease poses a serious threat to the production of cocoa, the model was verified. The model's outcomes highlight the significance of early detection and rapid intervention in mitigating the severity of cocoa black pod disease outbreaks. Moreover, it emphasizes the importance of adopting integrated disease management approaches that consider fungicide administration and removal of infected pods. The usefulness of mathematical modeling as a tool for understanding and managing cocoa black pod disease is illustrated by this study.
Aplicación de algoritmos para el procesamiento de imágenes a la tecnología de microarreglos para el diagnóstico

Algorithms for the processing of Microarray images are presented in this work. A special emphasis is made on the stage of image segmentation presenting three segmentation methods: method of Court, method of Canny, and method of Segmentation for Region Growing (Seeded Region Growing). All of them are implemented with the corresponding adaptations to the Microarray technology for diagnosis. Several examples of the application of these methods are shown, and a discussion of the results obtained is carried out by means of a brief comparison among them; considering the computational speed of each method and the proximity of the results obtained with the prospective results.
Self-Healing Oxalamide Organogelators of Vegetable Oil

The aim of this study was to assess the gelling potential of chiral oxalamide derivatives in vegetable oils. Special emphasis was given to the potential applications of the examined oil gels as sustained delivery systems and as fat substitutes in food products. The applicability of oil gelators is envisaged in food, cosmetics, and the pharmaceutical industry. The regulations requiring the elimination of saturated fats and rising concerns among consumers health motivated us to investigate small organic molecules capable of efficiently transforming from liquid oil to a gel state. The oxalamide organogelators showed remarkable gelation efficiency in vegetable oils, thermal and mechanical stability, self-healing properties, and a long period of stability. The physical properties of the gels were analysed by TEM microscopy, DSC calorimetry, and oscillatory rheology. The controlled release properties of acetylsalicylic acid, ibuprofen, and hydrocortisone were analysed by the LC–MS method. The influence of the oil type (sunflower, soybean, and olive oil) on gelation efficiency of diverse oxalamide derivatives was examined by oscillatory rheology. The oxalamide gelators showed thermoreversible and thixotropic properties in vegetable oils with a minimum gelation concentration of just 0.025 wt%. The substitution of palm fats with gelled sunflower oil applied in cocoa and milk spreads at gelator concentrations lower than 0.2 wt% have shown promising viscoelastic properties compared to that of the original food products.
Inhaled therapies targeting prostacyclin pathway in pulmonary hypertension due to COPD: systematic review

Background Pulmonary hypertension due to chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) is classified as group 3 pulmonary hypertension. Inhaled treprostinil, a prostaglandin I2 analogue also known as prostacyclin, has recently been approved as a first drug for patients with pulmonary hypertension secondary to ILD. However, due to a lack of evidence, no therapies are currently approved for those with COPD-associated pulmonary hypertension. Thus, this systematic review aims to summarise the current evidence to assess the impact of inhaled prostaglandin I2 analogue use on the pulmonary hemodynamics, exercise function, lung function, and gas exchange in patients with pulmonary hypertension due to COPD. Methods We systematically searched the electronic databases of Medline, Embase, Scopus and Cochrane from inception to 1 February 2023. Studies of adult patients with a confirmed diagnosis of COPD-associated pulmonary hypertension who received inhaled drugs targeting the prostacyclin pathway were included in the systematic review. Case reports, systematic reviews, conference abstracts with no full text, non-full-text articles, non-English manuscripts and book chapters were excluded from this systematic review. A risk-of-bias assessment was carried out for the studies included in this review, using two different Cochrane risk-of-bias tools for randomised and non-randomised clinical trials. Results A total of four studies met our inclusion criteria and were included in this systematic review. The results of one prospective clinical trial showed an improvement in the pulmonary hemodynamics (e.g., cardiac index, cardiac output and mean pulmonary artery pressure) in response to inhaled prostacyclin use in patients with pulmonary hypertension secondary to COPD. However, the severity of dyspnoea, lung function, exercise capacity and gas exchange were not affected when inhaled prostacyclin was used for patients with COPD-related pulmonary hypertension. Conclusion This systematic review demonstrated that although inhaled prostacyclin does not seem to improve COPD-related outcomes (e.g., lung function and exercise capacity), short-term use of inhaled prostacyclin has the potential to reduce mean pulmonary artery pressure and pulmonary vascular resistance without impairing ventilation-perfusion mismatch. Further studies with larger sample sizes are warranted. Systematic review registration CRD42022372803, https://www.crd. york.ac. uk/prospero/display_record. php? RecordID=372803.
An efficient two-phase metaheuristic algorithm for the time dependent traveling Salesman problem

The Time Dependent Traveling Salesman Problem (TDTSP) is a class of NP-hard combinatorial optimization problems which has many practical applications. To the best of our knowledge, developing metaheuristic algorithm for the problem has not been studied much before, even though it is a natural and general extension of the Minimum Latency Problem (MLP) or Traveling Salesman Problem (TSP). In this paper, we propose an effective two-phase metaheuristic which combines the Insertion Heuristic (IH), Variable Neighborhood Search (VNS) and the tabu search (TS) to solve the problem. In a construction phase, the IH is used to create an initial solution that is good enough. In an improvement phase, the VNS is employed to generate diverse and various neighborhoods, while the main attribute of tabu search is to prohibit our algorithm from getting trapped into cycles, and to guide the search to escape local optima. Moreover, we introduce a novel neighborhoods’ structure in VNS and present a O(1) operation for calculating the cost of each neighboring solution in a special case of TDTSP where the TDTSP becomes the MLP. Extensive computational experiments on 355 benchmark instances show that our algorithm can find the optimal solutions for small instances with up to 100 vertices in a reasonable amount of time. For larger instances, our algorithm obtains the new best solutions in comparison with the state-of-the-art algorithm solutions.
Generation Differences in the Behaviour of Household Consumers in Romania Related to Voluntary Measures to Reduce Electric Energy Consumption

The Ukraine crisis, the sharp increase in the price of electricity and the excessive dependence of the European Union countries on fossil fuels from Russia have led to a series of actions in the direction of energy saving, clean energy production and diversification of energy sources. The REPoweEU plan, through related financial and legal measures, aims to build a new infrastructure and a new energy system at the EU level. The reduction of energy consumption represents an important orientation of this plan, and in this context, the present study investigates, based on a questionnaire, the behaviour of consumers (households) in Romania towards voluntary measures to reduce electricity energy consumption and identify the behavioural differences between four generations: Baby Boomers, X, Y, and Z. The analysis of the results was performed using ANOVA and Tukey statistical tests, using the SAS Studio software application. The results highlight some differences in the behaviour of generations and the patterns regarding the approach to behavioural integration for responsible energy consumption. The work is useful because it outlines the attitude and behaviour of Romanian consumers toward the national and European objectives of reducing energy consumption, energy waste, and increasing the share of alternative energy sources.
Legacy Facility: Decision-making Analysis. Case Study of a Pharma Company in Indonesia

PT. ABCD has faced the issue of legacy facilities that become findings in routine inspections of NRA. The issue can be escalated to shut down the production facility due to the legacy facility hardly complying with cGMP. The study aims to choose the best alternatives of building a new facility, renovating the current facility, and toll manufacturing with consideration of financial, regulation compliance, project completion speed, and strategy risk. The study is using Analytic Hierarchy Process (AHP) to get a decision from the experts in PT. ABCD. The respondents are seven experts in many fields, including finance, project management, GMP, operations, demand forecasting, technological transfer, business development, cGMP engineering, and the management representative. To analyze the group decision-making, the results of each respondent are aggregated with a geometric mean. Compliance with regulation (0.356) was found to be the top priority, followed by strategy risk (0.295), project completion speed (0.250), and financial aspect (0.098). Results show that (a) building a new facility (0.4563) is the best alternative among the other alternatives, followed by toll manufacturing (0.3251) and renovating the current facility (0.2186); and (b) building a new facility is the best alternative among the other alternatives (0.4563) followed by toll manufacturing (0.3251) and renovating current facility (0.2186) with consideration of criteria financial aspect, regulation aspect, project completion speed aspect, and strategy risk aspect. We recommend implementing the project plan to build a new facility.