Miracle-dz/UniFAR-FTUs huggingface dataset:
Do fear and perceived knowledge of Covid-19 drive sustainable consumption behaviour in Muslims? The mediating role of religiosity

Purpose This research aims to investigate the impact of fear and perceived knowledge (PK) of Covid-19 on the sustainable consumption behaviour (SCB) of Muslim consumers and to test the mediating role of (intrinsic) religiosity. Design/methodology/approach A total of 417 responses were collected during Covid-19 lockdown through an online structured survey using the snowball technique. A two-step research approach was adopted. In Study 1, an exploratory factor analysis was performed on the SCB measurement scale through SPSS. In Study 2, hypothesised associations were analysed using SmartPLS-SEM. Findings PK of Covid-19 pandemic directly motivates SCB in Muslim consumers, whereas fear has no direct effect on any factor of SCB. Religiosity is found to be a significant driver of SCB. Indirect effects also depict that religiosity positively mediates the association between fear and SCB as well as PK and SCB. Practical implications The study may guide policymakers and marketers in using the current pandemic as a tool to inspire sustainable consumption. Religious values, teachings and knowledge about the pandemics can be publicised to create awareness and induce desired behaviour to cope with adverse events and adopt sustainable consumption patterns and lifestyles among Muslim consumers. Originality/value The article is the pioneer of its kind to present survey research about Covid-19 fear and PK’s impact on SCB through religiosity. It adds to the Islamic marketing literature about religiosity, coping theory, PK and fear of pandemics and their role in transitioning Muslim consumers towards SCB. Moreover, the use of partial least squares structural equation modelling in the context of Covid-19 research was extended.
Obesity Does Not Influence Delayed Gastric Emptying Following Pancreatoduodenectomy

Simple Summary Over the last decades the number of obese patients has been increasing. Not only is obesity associated with other diseases such as cardiovascular diseases, diabetes and asthma but obese patients are also at a higher risk for developing different types of cancers, for instance pancreatic cancer with a consecutive increased need for pancreatic surgery. Even though it is not life threatening, impaired gastric motility, also known as delayed gastric emptying, has still remained the most common complication after pancreatic surgery. However, the data about obesity on postoperative outcome after pancreatic surgery are inconsistent, specifically in relation to delayed gastric emptying. The goal of this study was to investigate the impact of obesity on postoperative outcome, specifically on delayed gastric emptying, after pancreatic surgery. Our data show no difference in the occurrence and severity of delayed gastric emptying in patients with obesity compared to non-obese patients. Moreover, the overall mortality rate did not differ between the two groups. In summary, our data show that obese patients are not put at a higher risk in regard to postoperative outcome, which makes pancreatic surgery a feasible procedure in the obese patient, specifically in relation to delayed gastric emptying. Abstract Background: The data about obesity on postoperative outcome after pancreatoduodenectomy (PD) are inconsistent, specifically in relation to gastric motility and delayed gastric emptying (DGE). Methods: Two hundred and eleven patients were included in the study and patients were retrospectively analyzed in respect to pre-existing obesity (obese patients having a body mass index (BMI) ≥ 30 kg/m2 vs. non-obese patients having a BMI < 30 kg/m2, n = 34, 16% vs. n = 177, 84%) in relation to demographic factors, comorbidities, intraoperative characteristics, mortality and postoperative complications with special emphasis on DGE. Results: Obese patients were more likely to develop clinically relevant pancreatic fistula grade B/C (p = 0.008) and intraabdominal abscess formations (p = 0.017). However, clinically relevant DGE grade B/C did not differ (p = 0.231) and, specifically, first day of solid food intake (p = 0.195), duration of intraoperative administered nasogastric tube (NGT) (p = 0.708), rate of re-insertion of NGT (0.123), total length of NGT (p = 0.471) or the need for parenteral nutrition (p = 0.815) were equally distributed. Moreover, mortality (p = 1.000) did not differ between the two groups. Conclusions: Obese patients do not show a higher mortality rate and are not at higher risk to develop DGE. We thus show that in our study, PD is feasible in the obese patient in regard to postoperative outcome with special emphasis on DGE.
Particle swarm optimization algorithm for dynamic synchronization of smart grid

ABSTRACT In recent decades, traditional energy generation and consumption have undergone a transformation to cleaner energy sources. The transition to a sustainable energy system based on efficiency and renewable energies will thus require the replacement of a complex and heavily implemented energy system with one based on concepts such as microgrids. A microgrid is a controlled small-scale power system and the elements that make up it are: distributed generation systems; energy storage systems; load management techniques; monitoring systems, etc. Consequently, since ac devices are used, synchronization criteria must be satisfied to switch operation between them. The synchronization criteria consist of making the values of the phase-angle difference, slip frequency, and voltage difference as small as possible. This is very important to ensure the correct operation of the grid. In the other hand, the use of Particle Swarm Optimization (PSO) algorithm has been increasing, because of their simplicity and efficiency in engineering optimization problems. Therefore, this paper proposes an active synchronizing control scheme that allows to synchronize a generator set to the grid and a particle swarm optimization algorithm, which makes the synchronizing control as efficient as possible. With the implemented control and with the help of the synchronization algorithm, improvements in the reduction of settling time (from 9 seconds to 3 seconds) are obtained in comparison to other controls in the literature.
Effectiveness of Rehabilitation for Cancer Patients with Bone Metastasis

ABSTRACT Objectives: Advances in cancer treatment have led to extended survival, and, as a result, the number of patients with bone metastases is increasing. Activities of daily living (ADL) decrease with bone metastasis and the need for rehabilitation is increasing. This study examined the effects of rehabilitation in patients with bone metastases. Methods: We retrospectively reviewed data of cancer patients with bone metastasis who received rehabilitation between 2016 and 2018. Efficacy of rehabilitation was evaluated in 92 patients as the change in the Functional Independence Measure (FIM) score divided by rehabilitation days (FIM change/day) and assessed by different metastatic sites. Results: Overall FIM scores significantly improved after rehabilitation. Moreover, FIM change/day improved in patients with pelvic metastases (n=44) more than in patients with other metastatic sites (n=48) (P=0.015). In FIM motor components, improvements in toilet, tub/shower, walk/wheelchair, and stairs were significantly greater in patients with pelvic metastasis than in those with other metastasis sites. Conclusions: Rehabilitation improved ADL status to a greater extent in patients with pelvic metastases than in those with other metastasis sites. Patients with pelvic metastases may fear fractures, limiting their ADL, but rehabilitation could eliminate this fear and improve FIM.
Artificial Dermal Scaffold Loaded with Platelet-Rich Plasma Promotes Wound Healing in Pigs by Favoring Angiogenesis

Background The development of artificial dermis provides a new therapeutic method for full-thickness skin defects. However, the slow regeneration of blood vessels in the wound site still cannot be solved perfectly. In our study, we combined platelet-rich plasma (PRP) with Lando® artificial dermal scaffold to promote vascular regeneration and wound healing in pigs. Material/Methods First, PRP was compounded with the artificial dermal scaffold. Then, this material was co-cultured with human vascular endothelial cells (HUVECs) and the growth and proliferation of HUVECs were assessed. Bama miniature pigs wound models were fabricated, the materials were transplanted into the skin defect, and wound healing and blood vessel regeneration were assessed by HE staining and CD31 immunohistochemistry. Results Scanning electron microscopy (SEM) showed that PRP formed round particles on the surface of the artificial dermis material. Cell co-culture experiments showed that the PRP composite artificial dermal scaffold can promote the growth and proliferation of HUVECs. CCK8 experiments demonstrated that the number of cells in the PRP composites group on days 2, 3, 4, and 5 was higher than that in the material alone group (P<0.01). The results of animal experiments showed that PRP composite artificial dermal material can promote wound healing. Histological staining and immunohistochemical staining indicated that the PRP composites group promoted epithelial tissue thickening and blood vessel regeneration in wounds (P<0.001). Conclusions Our experimental results showed that the artificial dermal scaffold loaded with platelet-rich plasma can promote the revascularization of wounds and accelerated wound healing.
Multi-Class CNN for Classification of Multispectral and Autofluorescence Skin Lesion Clinical Images

In this work, we propose to use an artificial neural network to classify limited data of clinical multispectral and autofluorescence images of skin lesions. Although the amount of data is limited, the deep convolutional neural network classification of skin lesions using a multi-modal image set is studied and proposed for the first time. The unique dataset consists of spectral reflectance images acquired under 526 nm, 663 nm, 964 nm, and autofluorescence images under 405 nm LED excitation. The augmentation algorithm was applied for multi-modal clinical images of different skin lesion groups to expand the training datasets. It was concluded from saliency maps that the classification performed by the convolutional neural network is based on the distribution of the major skin chromophores and endogenous fluorophores. The resulting classification confusion matrices, as well as the performance of trained neural networks, have been investigated and discussed.
Investigating The Status of Local Government Education Authority in Providing Quality Learning Environment in Gombe Local Government Area of Gombe State

This study investigated the status of Local Government Education Authority in providing quality Learning Environment in Gombe Local Government Area; two objectives were used to guide the study. The study adopted survey research design, the population of the study comprised of 2,244 total number of teaching staff and head teachers in which 327 respondents were selected using simple random sampling. A four-point rating scale questionnaire consisting of 14 items were used in collection of data. Data collected were analyzed using mean (X) and Standard deviation (Std.) The findings of the study revealed that the physical learning environment in primary schools is not sufficiently provided which may affect the quality of teaching and learning in primary school education. It’s also indicated a disagreement in the opinions of teachers and head teachers in GLEA in providing quality aesthetic learning environment at primary school. The Study among others, recommended that The LGEA should be supported and fully involved in decision making and funding of primary education through collaborative effort among all education stakeholders in providing quality attractive learning environment for children not just a supervisory role.
Simultaneous detection of viable Salmonella spp., Escherichia coli, and Staphylococcus aureus in bird's nest, donkey‐hide gelatin, and wolfberry using PMA with multiplex real‐time quantitative PCR

Abstract Salmonella spp. , Escherichia coli, and Staphylococcus aureus are common microbial contaminants within the homology of medicine and food that can cause serious food poisoning. This study describes a highly efficient, sensitive, specific, and simple multiplex real‐time quantitative PCR (mRT‐qPCR) method for the simultaneous detection of viable Salmonella spp. , E. coli, and S. aureus. Primers and probes were designed for the amplification of the target genes invA, uidA, and nuc. Dead bacterial genetic material was excluded by propidium monoazide (PMA) treatment, facilitating the detection of only viable bacteria. This method was capable of detecting Salmonella spp. , E. coli, and S. aureus at 102, 102, and 101 CFU/ml, respectively, in pure culture. PMA combined with mRT‐qPCR can reliably distinguish between dead and viable bacteria with recovery rates from 95.7% to 105.6%. This PMA‐mRT‐qPCR technique is a highly sensitive and specific method for the simultaneous detection of three pathogens within the homology of medicine and food.
Structural, optical, electrical, and DFT studies on polyvinyl pyrrolidone/polyethylene oxide polymer blend filled with MoO3 nanoplates for flexible energy‐storage devices

Nanocomposite films of PVP/PEO containing MoO3 nanoplates were prepared using a casting procedure. XRD results showed that the addition of MoO3 in the virgin PVP/PEO blend increases the amorphous domains of polymer nanocomposite (PNC) films. The DFT/FT‐IR results have established the miscibility and the interaction between PVP and PEO polymers via hydrogen bonds. Also, FTIR studies showed a coordination interaction between MoO3 nanoplates and the C=O group of PVP and/or the C‐O‐C group of PEO of the PVP/PEO blend. The optical band gap values of PNC films of PVP/PEO/MoO3 decreased with increasing MoO3 content. The relaxation processes and dielectric dispersion of the prepared PNC films were examined and discussed. The electrical conductivity was enhanced via the addition of MoO3 nanoplates because of an increase in the number density of the charge carriers. The dominated conduction mechanism of PNC films reveals the correlated barrier hopping model, while the type of relaxation process follows the non‐Debye one. These observations illustrate the applicability and potential uses of these PNC films as a nanodielectric material in ceramic capacitors and electrochemical applications such as devices of energy storage and separators in batteries.
Classificação de personalidade a partir de textos segundo a Tipologia de Myers-Briggs

Santos, Vitor Garcia dos. Personality classification from texts according to Myers-Briggs Typology. 2021. 73 p. Dissertation (Master of Science) – School of Arts, Sciences and Humanities, University of São Paulo, São Paulo, 2021. Personality is associated with human behavior through sensations, abilities, attitudes, thoughts, each of which is an individual combination. The Psychology field proposes models of human personality such as the Myers-Briggs Typology (MBTI), which will be the focus of this work. In this model, personality traits (extroversion or introversion, intuition or sensation, thought or feeling and perception or judgment) are determined based on the words that the individuals use when expressing themselves, and can thus be inferred from texts with the use of Natural Language Processing (PLN) methods. Based on these observations, this work presents the results of a master’s dissertation focused on the MBTI human personality recognition, from texts in several languages. The work aims the use of neural methods of supervised machine learning for this purpose and seeks in this way to advance the state-of-the-art in computational recognition of personality from texts.
Talento verde y cadenas de suministro verdes: ¿existe una relación significativa?

Introduccion : En este texto se presentan resultados estadisticos de la relacion entre directivos con caracteristicas de talento verde y la implementacion de practicas de cadena de suministro verde. Debido a que existen investigaciones sobre la importancia de la vision de la alta direccion para la adopcion de practicas verdes; y sin embargo ninguna da cuenta de las caracteristicas personales del directivo, ni tampoco de la relacion significativa entre estas caracteristicas y la puesta en marcha de practicas de cadena de suministro verde, esta es la aportacion de la presente investigacion. El trabajo se desarrollo en empresas manufactureras con mas de diez trabajadores de la zona oriente del estado de Morelos Mexico. La caracterizacion del termino talento verde se reporto en el articulo, Talento verde : caracterizacion y busqueda, publicado en el numero 14 de esta revista. Metodo : El metodo utilizado consistio en la construccion de una encuesta dividida en tres categorias que posteriormente se convirtieron en variables: practicas de cadena de suministro verde, presiones institucionales y talento verde . Las dos primeras se adaptaron de la encuesta de Zhu y Sarkis (2007) y la tercera surgio de la representacion social de talento verde , producto de una fase de esta investigacion. La encuesta se valido con un grupo de empresarios miembros de la Camara Nacional de la Industria de la Transformacion (CANACINTRA) capitulo Morelos. El instrumento validado se aplico a 26 directivos de empresas manufactureras con mas de diez trabajadores de la zona oriente de Morelos, con el fin de probar la relacion entre directivos con caracteristicas de talento ver de y la puesta en marcha de practicas de cadena de suministro verde. Para ello se utilizaron como herramientas estadisticas la correlacion de Pearson y la regresion lineal multiple. Resultados : Las practicas de cadena de suministro verde de las empresas manufactureras de la zona oriente del estado de Morelos se encuentran en etapa de planeacion. Los encuestados de las empresas reconocen caracteristicas de talento verde en sus directivos de mayor jerarquia. Las presiones institucionales (mercado, regulacion y competidores) son importantes para las companias que participaron en el estudio no obstante la dificultad estriba en ponerlas en marcha. Conclusion : Talento verde y practicas de cadena de suministro verde son variables que se correlacionan, es decir, existe una relacion estadisticamente significativa entre ambas variables. A traves del metodo de regresion lineal multiple se afirma que las presiones institucionales: mercado, regulacion y competidores, son causa de la implementacion de practicas de cadena de suministro verde. Estas presiones institucionales y la presencia de caracteristicas de talento verde en directivos, se combinan para la implementacion de practicas de cadena de suministro verde en las empresas manufactureras con mas de diez trabajadores de la zona oriente del estado de Morelos, Mexico.
Analytical modeling of distributed network functions virtualization architectures and the impact of the distribution on the packet sojourn time

Distribution of network functions virtualization (NFV) environment on multiple locations and datacenters is a hot topic in research and engineering communities. In this article, we are making analytical models to calculate the network packet sojourn time in three different scenarios: classical NFV environment where all NFV elements are on the same location, distributed architecture of the data plane with centralized management and orchestration (MANO) environment, and distributed environment where every location has its own data plane and MANO elements. The analytical models are tested and discussed through Matlab based simulations. Through the simulation results, we discuss the impact of changes of different parameters on the packet sojourn time, and we compare the architectures in order to see how they can be fitted in practical services provided in an NFV environment.
Difference in the Cobb Angle Between Standing and Supine Position as a Prognostic Factor After Vertebral Augmentation in Osteoporotic Vertebral Compression Fractures

Objective We retrospectively analyzed patients with osteoporotic vertebral compression fracture (OVCF) undergoing vertebral augmentation to compare the Cobb angle changes in the supine and standing positions and the clinical outcomes. Methods We retrospectively extracted the data of OVCF patients who underwent vertebral augmentation. Back pain was assessed using a visual analogue scale (VAS). Supine and standing radiographs were assessed before treatment to determine the Cobb angle and compression ratio. Receiver operating characteristic curve analysis was performed to determine the optimal cutoff to predict favorable outcomes after vertebral augmentation. Results A total of 249 patients were included. We observed a statistically significant increase in the VAS score change with increasing Cobb angle and compression ratio (p < 0.001), and multivariate logistic regression analysis showed that a difference in the Cobb angle (odds ratio [OR], 1.27) and compression ratio (OR, 1.12) were the independent risk factors for predicting short-term favorable outcomes after vertebral augmentation. In addition, we found that the difference in the Cobb angle (OR, 1.05) was the only factor for predicting midterm favorable outcomes after vertebral augmentation. The optimal cutoff value of the difference in the Cobb angle for predicting midterm favorable outcomes was 35.526°. Conclusion We found that the midterm clinical outcome after vertebral augmentation was better when there was a difference of approximately 35% or more in the Cobb angle between the standing and supine positions. Surgeons should pay attention to the difference in the Cobb angle depending on the posture when deciding to perform vertebral augmentation in patients with OVCFs.
Application of teaching strategies in grade 12 english second language classrooms in Mankweng Circuit, Limpopo Province

iv) CHAPTER 1: GENERAL INTRODUCTION 1 1.1 Background to the study 1 1.2 Statement of the problem 2 1.3 Purpose of the study 3 1.3. 1 Aim 3 1.3. 2 Objectives of the study 3 1.5 Significance of the study 3 CHAPTER 2: LITERATURE REVIEW 4
Fundamental theorems in the probability theory

Probability theory is an area of mathematics that deals with the subject of likelihood. Probability theory is the mathematical cornerstone of statistical reasoning, and it is vital for data scientists to analyze data that are impacted by randomness. It is important in machine learning since the design of learning algorithms frequently relies on probabilistic data assumptions. Probability is a concept that is used to quantify the degree of uncertainty. The goal of probability theory is to express uncertain phenomena using a set of axioms. To cut a long tale short, when a system’s probable outcomes cannot be certain of, mathematicians try to depict the situation by calculating the probability of various events and scenarios. Random variables, independence, entropy and Chebyshev inequality will all be discussed in this paper. These mathematical concepts and theorems are essential and fundamental for future study in other scientific areas.