Miracle-dz/UniFAR-FTUs huggingface dataset:
USE OF ENSEMBLE METHODS FOR SURVIVAL PREDICTION

Cox regression model is used for modelling censored data to investigate the association between the survival time and covariates. It is important to assess the fit of Cox regression model since it has a key assumption called proportional hazards. Violation of this assumption induces an invalid model and changes the interpretation of the results. When the objective is the risk prediction, various machine learning methods can be good alternatives to Cox regression model due to their flexible structure. In this study, Turkish breast cancer data set is used to compare the predictive performance of Cox regression model and ensemble machine learning methods. Integrated Brier score is used to measure the predictive performance of candidate models. Based on case study results, machine learning methods are promising alternatives for survival prediction.
Structural empowerment and organisational performance: the mediating role of employees’ well-being in Spanish local governments

Abstract We extend the ‘black box’ picture of public management and the ‘balanced view’ of HRM literature in the Spanish public context. Specifically, we explore the link between structural empowerment and organisational performance and the mediating role of three employee outcomes: job satisfaction and affective commitment as attitudinal variables related to eudaimonic well-being, and job anxiety as a variable related to hedonic well-being. Using a multilevel methodology with data on employees from 103 local authorities for 2016, results support the mutual gains perspective, but not as intensely as expected (empowerment does not affect attitudinal variables), since empowerment contributes to reducing job anxiety in Spanish local governments. Specifically, information and rewards are the structural empowerment dimensions that help to reduce job anxiety levels in employees and, thus, enhance performance. These results suggest that local government managers could usefully apply techniques such as disseminating information on the organisation’s aims among employees or paying bonuses for meeting targets.
Managing Private Labels Based on Psychographic Consumer Segments: Emerging European Market Perspective

This paper explores private labels in the context of Croatia, as a representative of a CEE and EU member countries, where their importance is continuously growing. It aims to reveal whether consumers’ psychographic characteristics impact their attitudes towards private labels, which are in the growth stage of the product life cycle. Findings show that price consciousness, consumer innovativeness, and store loyalty have a positive and statistically significant impact on consumers’ attitudes towards private labels. These three psychographic characteristics allow clustering of consumers prone to private labels (by applying K-means analysis) into three different clusters. Consumers belonging to cluster 2 exhibit the highest levels of innovativeness and price sensitivity and might be considered pioneers in accepting private labels. The paper contributes to a more comprehensive insight into private labels marketing management and offers managerial implications for retailers.
Design & Development of Curcumin Loaded Zinc Oxide Nanoparticles Decorated Mesoporous Silica Liquid Stitches: A Proof of Concept in Animals

ABSTRACT The present research was aimed at synthesising and characterising curcumin-loaded zinc oxide nanoparticle-decorated mesoporous silica as a tissue adhesive (Liquid Stitches). The mesoporous silica nanoparticles facilitate adhesion to tissues through the nanobridging effect. The mesoporous silica was synthesised using a sol–gel methodology, and the drug was incorporated using the wetness impregnation method. The platform that was prepared was characterised using infrared spectroscopy, TEM, DSC, XRD, particle size analysis, BET analysis, a tissue model adhesion test, an antimicrobial assay and a wound model in Sprague Dawley rats. The average particle size was found to be 72.4 nm, while the surface area was found to be 654 m2/g. The tissue model adhesion graphs showed significantly different values for the peak load, work done and deformation at peak load, which reflects a difference between the glue strengths of the mesoporous silica nanoparticles and the Cur-ZnO-MSN and the carrier medium (water). The animal study provided a proof of concept by glueing wounds in less than 1 minute and healing the wound within 5 days.
Multiscale gradient domain compression for astronomical high dynamic range imaging

Visualisation of high dynamic range images requires compression of the data to be properly displayed on media with more limited dynamic ranges. Astronomical images pose a difficult challenge for dynamic range compression algorithms, due to the nature of the imaged objects and to the lack of a reflectance illumination model based on spatial frequencies. As a result, most of the algorithms commonly used for daylight high dynamic range compression fail in achieving an optimal visualisation of astronomical targets. We propose an extended multiscale algorithm based on compression of the dynamic range in the gradient domain. Our algorithm effectively compresses the dynamic range, enhances local contrast and avoids noise amplification. This is achieved with a multiscale representation of the image and the use of luminance information. Our results show a significantly improved visualisation of astronomical images compared to the standard gradient domain compression, as well as more robustness to noise and better artefact suppression.
Breast Cancer Segmentation Recognition using Explored DCT-DWT based Compression

Background and objective: Breast cancer is a leading cause of death worldwide, and its early detection usually performed with low quality clinical images. Due to unpredictable structure of breast and characterization of the cancer, disease in early stages is yet a difficult issue for specialists and analysts. The accurate identification of breast cancer is an important step in its early stage to avoid survival rate. With the advancement in the field of medical science, advancements have created to a phase where the medicinal services industry demonstrates to give best outcomes most definitely. Methods: It is observed that the breast cancer images are analyzed after decompression during telecommunications. In this paper, first we aimed to compressed malignant cancer images so that it could illuminate the motivation behind the telemedicine by applying preprocessing techniques and second identification, classifications of breast cancer disease depend on segmentation using discrete cosine transformation and discrete wavelet transformation. Results: Segmentation addresses the problem to know the characteristics of malignant cancer. The segmented image eliminates the false positives, to obtain a clear-segmented image. Segmentation methods based on a structural approach to isolate the breast edge and a region approach to extract the malignant portion. The result of image quality index achieved the output based on fusion techniques. Conclusion: Because of the unpredictable structure of the breast and low quality of clinical images, a precise discovering, position, and characterization of the disease in early stages is yet a difficult issue for specialists and analysts. The breast cancer could detected and segmented if highly efficient image compression achieved successfully. The conclusion procedure of disease infection is time taking which required storage capacity limit in computer system. A large number of Magnetic Resonance Imaging assembled per understanding and an enormous assortment for each wiped out individual required huge space for capacity just as a wide transmission transfer speed for computer system framework and again additionally for transmission over the web. Our proposed method can be useful for accurate and automatic classification of malignant cells from medical images by the specialist. With the goal that genuine cases would be created novel outcomes and improved endurance rates.
Changes in biogeochemical cycling following forest defoliation by pine wilt disease in Kiryu experimental catchment in Japan

Changes in nutrient budgets and hydrological processes due to the natural disturbance of pine wilt disease (PWD) were monitored in a small, forested watershed in Japan. The disturbance caused changes in soil nitrogen transformations. Pre‐disturbance, mineralized nitrogen remained in the form of NH4+, whereas in disturbed areas most mineralized nitrogen was nitrified. Stream NO3− concentrations increased following PWD. There was a delay between time of disturbance and the increase of NO3− in ground and stream waters. Stream concentrations of NO3− and cations (Ca2+ + Mg2+) were significantly correlated from 1994 to 1996, whereas the correlation among NO3−, H+, and SO42− was significant only in 1995. Although both cation exchange and SO42− adsorption buffered protons, cation exchange was the dominant and continuous mechanism for acid buffering. SO42− adsorption was variable and highly pH dependent. The disturbance also resulted in slight delayed changes of input–output nutrient balances. The nitrogen contribution to PWD litter inputs was 7·39 kmol ha−1, and nitrogen loss from streamwater was less than 0·5 kmol ha−1 year−1 throughout the observation period. This large discrepancy suggested substantial nitrogen immobilization. Copyright © 2004 John Wiley & Sons, Ltd.
Backscatter technologies and the future of internet of things: Challenges and opportunities

Energy source and circuit cost are two critical challenges for the future development of the Internet of Things (IoT). Backscatter communications offer a potential solution to conveniently obtain power and reduce cost for sensors in IoT, and researchers are paying close attention to the technology. Backscatter technology originated from the Second World War and has been widely applied in the logistics domain. Recently, both the academic and industrial worlds are proposing a series of new types of backscatter technologies for communications and IoT. In this paper, we review the history of both IoT and backscatter, describe the new types of backscatter, demonstrate their applications, and discuss the open challenges.
Entrepreneurial education influence on the development of self-efficacy and entrepreneurial competences

Purpose: This study aimed to evaluate entrepreneurship classes' influence on entrepreneurial self-efficacy and entrepreneurial competences in health academics. Design/methodology/approach : The model by De Noble, Jung, and Ehrlich (1999) was used to measure entrepreneurial self-efficacy and the model by Cooley (1990, 1991) to measure entrepreneurial competences. It is a quantitative, descriptive, and survey research. Two hundred sixty-seven undergraduate health students participated in the study. Statistical analysis used descriptive and correlational statistics with comparison tests. Findings : The results showed that the students who studied entrepreneurship presented higher self-efficacy and entrepreneurial competences, but there were no significant differences between those who studied and those who did not. Originality/value : This study presents the potential for promoting entrepreneurship in HEI for courses that are not directly associated with business management, especially health science courses. When analyzing the participants' behavioral characteristics, we seek to deepen the discussion on the central themes of the study and promote reflections on the importance of entrepreneurial education for the development of future health professionals.
RESTful API Implementation in Making a Master Data Planogram Using the Flask Framework (Case Study: PT Sumber Alfaria Trijaya, Tbk)

One of developing retail company and is one of the biggest retail companies in Indonesia, namely Alfamart which is owned by PT. Sumber Alfaria Trijaya, Tbk. Alfamart must have the best marketing strategy and increase innovation for the satisfaction of customers in order to survive in high business competition. One strategy to improve marketing is the arrangement of product displays in stores known as planograms. Planogram is a concept that is used in planning the arrangement and placement of products according to certain categories based on consumer spending habits that aim to increase sales at retail. This research was conducted to create a web-based planogram master application using the Flask framework with the python programming language. The method used in this study is the RESTful API, which is the implementation of web services that work through HTTP links. This research produces a web-based master data application that can be used by users in entering data needed in making a planogram. Keywords : RESTful API, Python Flask, Planogram
Teachers candidates’ implementations of equitable mathematics teaching practices: An examination of divergent paths

In this multiple-case study, we track the diverging paths of two teacher candidates enrolled in an undergraduate elementary mathematics methods course as they developed their understanding of equitable teaching practices that were central to their course learning objectives. The cases were purposefully selected based upon our previous finding that, by the end of the course, Mary and Rose were extreme opposites in terms of their implementation of equitable mathematics teaching practices they attributed to the course. Teacher preparation programs are designed to help beginning teachers develop the skills to teach content equitably to diverse learners. Thus, methods instructors must consider the ways that teacher candidates use their knowledge and skills in their teaching.
Cultivating Trustworthy Artificial Intelligence in Digital Government

While there is growing consensus that the analytical and cognitive tools of artificial intelligence (AI) have the potential to transform government in positive ways, it is also clear that AI challenges traditional government decision-making processes and threatens the democratic values within which they are framed. These conditions argue for conservative approaches to AI that focus on cultivating and sustaining public trust. We use the extended Brunswik lens model as a framework to illustrate the distinctions between policy analysis and decision making as we have traditionally understood and practiced them and how they are evolving in the current AI context along with the challenges this poses for the use of trustworthy AI. We offer a set of recommendations for practices, processes, and governance structures in government to provide for trust in AI and suggest lines of research that support them.
RELATIONSHIP BETWEEN HOTELS' DESIGN ADEQUACY AND HOTELIERS' PERCEPTION OF SUSTAINABLE ENERGY MANAGEMENT IN ABUJA, NIGERIA

Energy is a sustainability issue receiving primary global concern. Improving energy efficiency and utilizing renewable resources are important in building energy sustainability. An energy-efficient design is a basis for controlling energy efficiency in buildings, and it is highly motivated by the sustainable energy management perception of relevant stakeholders. Hotels have high energy intensities and high working costs. This study investigates the relationship between hotel design adequacy and hoteliers' perception of sustainable energy management in Abuja, Nigeria. The investigation embraces quantitative structure utilizing exploratory and elucidating techniques. The mean ranking and Pearson product-moment correlation results revealed substantial and weak positive correlations (r = 0.601 and r. = 0.257) between design adequacy and hoteliers' perception of importance as well as barriers of sustainable energy management, respectively. However, a negligible negative correlation was found between hotel design adequacy and hoteliers' opinion advantages of sustainable energy management (r. = -0.088). The findings negate the theoretical argument in cognitive dissonance that although hoteliers are conscious of energy issues and the high cost of power generation from back-up generators, they are not interested in investing in sustainable energy management. This study recommends minimizing hotel energy demand through climateadaptive design and harnessing renewable energy to ensure comfortable and healthy hotel buildings with reduced operating and maintenance costs. Hotel design in the study area reasonably supports energy efficiency. Positive hoteliers' perception of the importance of sustainable energy management is related to improved design adequacy and thus responsible for a positive outcome.
Numerical and Experimental Analyses on Root Zone Temperature in Aeroponic Cultivation Box

Vegetable growth requires a relatively stable environment for the root zone. If the temperature in root zone environment is optimal, the aeroponic cultivation will be energy-efficient, and the aeroponic vegetables will grow well at high, normal, or low temperature. By computational fluid dynamics (CFD), this paper numerically simulates the root zone temperature of lettuce in the aeroponic cultivation box, after the box was sprayed with nutrient solutions of different temperatures. Then, the root zone environments of aeroponic lettuce were monitored through experiments at three different temperatures: high temperature, normal temperature, and low temperature. Through comparison, it was learned that the error between the simulated and measured values at each point was smaller than 1.35℃; the maximum error at a single point was within 7.4%; overall, the mean relative error was merely 5.8%. The results prove that the proposed CFD simulation model is reasonable and effective. Our research provides a theoretical reference for optimizing the root zone temperature, regulating the spray of nutrient solutions at different temperatures, and building an energy-efficient efficient aeroponic cultivation system.
A Continuous Model of Marital Relations with Stochastic Differential Equations

Marital relations depend on many factors which can increase the amount of satisfaction or unhappiness in the relation. A large percentage of marriages end up in divorce. While there are many studies about the causes of divorce and how to prevent it, there are very few mathematical models dealing with marital relations. In this paper, we present a continuous model based on the ideas presented by Gottman and coauthors. We show that the type of influence functions that describe the interaction between husband and wife is critical in determining the outcome of a marriage. We also introduce stochasticity into the model to account for the many factors that affect the marriage and that are not easily quantified, such as economic climate, work stress, and family relations. We show that these factors are able to change the equilibrium state of the couple.
TEKNOLOJİ HAZIRLIĞI

Technology Reading Index (TRI) has used to determine individuals’ willingness to use of technology. This study focuses on differences among belief and use new technology of academic staffs. The article examines how each dimension (optimism, innovativeness, discomfort, insecurity) of Technology Reading Index (TRI) influences Technology Acceptance Model (TAM) which have consumer perceived usefulness and perceived ease of use dimensions. The results show that of optimism dimension of TRI has a positive effect on both consumers perceived usefulness and perceived ease of use while innovativeness dimension has a positive effect on perceived ease of use. Researches on TRI and TAM have overlooked the potential role of technology readiness and acceptance in the development of academic staff. This study tests belief and use new technology of academic staffs.
CO 2 efflux and microbial activities in undisturbed soil columns in different nitrogen management

The surface carbon dioxide (CO2) fluxes together with the soil microbial biomass and activity in undisturbed soil columns were studied in three growing seasons. Soil columns had six treatments: (1) control without plants; (2) mineral fertilized without plants; (3) no fertilizer and maize plants; (4) mineral fertilized and maize plants; (5) manure and maize plants; (6) mineral fertilized plus manure and maize plants. Soil microbial biomass was measured by substrate-induced respiration (SIR) and microbial activity as fluorescein-diacetate hydrolysing activity (FDA). Treatments had a significant effect (P < 0.001) on CO2 fluxes, SIR and FDA. The presence of maize increased CO2 efflux, SIR and FDA compared to unplanted column. Fertilizer + manure treatment resulted in the greatest plant biomass and the greatest CO2 efflux. Significant correlation (r = 0.680; r = 0.586 in two consecutive years) between SIR and FDA was found.
Risk of Diabetes in Cameroonian Patients with Psychosis and Under Antipsychotic Therapy: A Cross-Sectional Study

Background: Diabetes is a public health problem worldwide and in sub-Saharan African countries such as Cameroon. According to many studies, the use of antipsychotic drugs increases the risk of developing diabetes mellitus by 2 to 3 times more in people with psychotic disorders than in the general population. The present study aimed to assess the influence of antipsychotic drugs used on the risk of developing diabetes and to identify other factors predictive of abnormal blood glucose levels in patients suffering from psychosis. Methods: A cross-sectional study was conducted from the 3rd to the 19th of January 2018. Patients aged at least 18 years old suffering from psychosis and undiagnosed as diabetic before initiation of antipsychotic treatment were recruited at the Jamot Hospital in Yaounde. A questionnaire was used to collect sociodemographic, anthropometric, and clinical data. The Chi-Square test was used to assess the relationship between hyperglycemia and categorical variables and the multivariate logistic regression model was used to determine independent predictors of hyperglycemia through the Statistical Package for the Social Sciences (SPSS) version 20.0. Results: A total of 82 patients were included in the study (41 males and 41 females). The fasting blood sugar ≥100 mg/dL appeared to be higher but not significant in patients on atypical antipsychotic therapy (124.74±23.31mg/dL) compared to patients on typical antipsychotic therapy (115.74±18.63 mg/dL); with a positive and non-significant correlation between hyperglycemia and duration of treatment (r=0.215; p=0.053). However, in both typical and atypical antipsychotic patients, fasting glucose sugar levels between 110-125mg/dL were observed at the same level (118.07±4.84 mg/dL and 118.09±3.41mg/dL respectively). Male sex (OR=1.41; 95% CI 0.54-3.64), age group < 35 years (OR=1.84; 95% CI 0.69-4.88), single (OR=2.18; 95% CI 0.83-5.67), typical antipsychotic drugs (OR=1.12; 95% CI 0.42-3.01), schizophrenia (OR=1.80; 95% CI 0.25-12.84) and bipolar disorder (OR=1.50; 95% CI 0.14-15.46) were independent predictors of hyperglycemia in those patients. Conclusion: Regular monitoring of anthropometric and clinical parameters should be assigned to people suffering from psychotic disorders and under treatment. Therefore, they should benefit from good management of the risk factors for diabetes to prevent the onset of the disease and avoid increased morbidity and mortality in this vulnerable population.