Miracle-dz/UniFAR-FTUs huggingface dataset:
Intelligent Optimization Mechanism Based on an Objective Function for Efficient Home Appliances Control in an Embedded Edge Platform

In recent years the ever-expanding internet of things (IoT) is becoming more empowered to revolutionize our world with the advent of cutting-edge features and intelligence in an IoT ecosystem. Thanks to the development of the IoT, researchers have devoted themselves to technologies that convert a conventional home into an intelligent occupants-aware place to manage electric resources with autonomous devices to deal with excess energy consumption and providing a comfortable living environment. There are studies to supplement the innate shortcomings of the IoT and improve intelligence by using cloud computing and machine learning. However, the machine learning-based autonomous control devices lack flexibility, and cloud computing is challenging with latency and security. In this paper, we propose a rule-based optimization mechanism on an embedded edge platform to provide dynamic home appliance control and advanced intelligence in a smart home. To provide actional control ability, we design and developed a rule-based objective function in the EdgeX edge computing platform to control the temperature states of the smart home. Compared to cloud computing, edge computing can provide faster response and higher quality of services. The edge computing paradigm provides better analysis, processing, and storage abilities to the data generated from the IoT sensors to enhance the capability of IoT devices concerning computing, storage, and network resources. In order to satisfy the paradigm of distributed edge computing, all the services are implemented as microservices. The microservices are connected to each other through REST APIs based on the constrained IoT devices to provide all the functionalities that accomplish a trade-off between energy consumption and occupant-desired environment setting for the smart home appliances. We simulated our proposed system to control the temperature of a smart home; through experimental findings, we investigated the application against the delay time and overall memory consumption by the embedded edge system of EdgeX. The result of this research work suggests that the implemented services operated efficiently in the raspberry pi 3 hardware of IoT devices.
Membrane models for molecular simulations of peripheral membrane proteins

ABSTRACT Peripheral membrane proteins (PMPs) bind temporarily to the surface of biological membranes. They also exist in a soluble form and their tertiary structure is often known. Yet, their membrane-bound form and their interfacial-binding site with membrane lipids remain difficult to observe directly. Their binding and unbinding mechanism, the conformational changes of the PMPs and their influence on the membrane structure are notoriously challenging to study experimentally. Molecular dynamics simulations are particularly useful to fill some knowledge-gaps and provide hypothesis that can be experimentally challenged to further our understanding of PMP-membrane recognition. Because of the time-scales of PMP-membrane binding events and the computational costs associated with molecular dynamics simulations, membrane models at different levels of resolution are used and often combined in multiscale simulation strategies. We here review membrane models belonging to three classes: atomistic, coarse-grained and implicit. Differences between models are rooted in the underlying theories and the reference data they are parameterized against. The choice of membrane model should therefore not only be guided by its computational efficiency. The range of applications of each model is discussed and illustrated using examples from the literature. Graphical abstract
Single‐crystalline porous NiO nanobiscuits with prompt adsorption activity for Congo red

Single-crystalline two-dimensional (2D) nickel oxide (NiO) porous nanobiscuits with diameters of 100–210 nm, thicknesses of 10–20 nm and pore sizes of <20 nm are fabricated through a low-cost water bath combined with calcination treatment approach. The composition and morphology of the products are characterised by X-ray diffraction, field-emission scanning electron microscopy, transmission electron microscopy (TEM), high-resolution TEM, selected area electronic diffraction and N2 adsorption/desorption. The possible formation mechanism of single-crystalline porous NiO nanobiscuits is simply discussed. Served as adsorbent, the as-prepared single-crystalline porous NiO nanobiscuits exhibited excellent performance for the fast removal of Congo red from water, which is far beyond the adsorption rate of activated carbon. The results show that the adsorption isotherm fits well with Langmuir adsorption model. The maximum adsorption capacity is calculated to be 193.2 mg g−1, which is larger than that of other reported 2D NiO architectures.
Studies of the PTEN tumour suppressor in endometrial cancer

Somatic mutations in the PTEN gene (Phosphatase and Tensin Homologue Deleted on Chromosome Ten) have been found in many types of cancer, but most frequently in cancer of the endometrium.The PTEN gene encodes a D3 lipid phosphatase of the second messenger phosphatidylinositol 3,4,5-trisphosphate (PIP3), which activates protein kinase B/Akt. Constitutive activation of Akt has been found in cells that lack functional PTEN, thus by dephosphorylating PIP3, this enzyme modulates several cellular functions e.g. proliferation, differentiation and migration.The PTEN protein comprises a 403 amino acid, 55KDa protein which is present in the cytoplasm but has also been detected in the nucleus of some cells. The function of nuclear versus cytoplasmic PTEN has not yet been determined. Little is known about modulation of PTEN expression by molecules such as hormones and cytokines. It has been reported, however, that NGF, BDNF and vitamin D3 analogues can up-regulate PTEN. The steroid hormones oestrogen and progesterone have been proposed as mediators of PTEN transcription, since their expression in endometrium reflects the menstrual cycle. The role of TGF-beta1 in PTEN expression of PTEN in human cells has been also investigated, but the results are contradictory. Compounds which stimulate up-regulation of PTEN represent potential anti-tumour therapies and therefore merit investigation. To further investigate the role of PTEN in endometrial cancer the following approaches were taken. The effect of TGF-beta1 on two endometrial carcinoma cell lines, HEC-1B and Ishikawa were investigated. The cell lines were stimulated with TGF-beta1 in the presence or absence of serum, and changes in mRNA and protein levels of PTEN and other genes analysed by RT-PCR and Western blotting. The morphology, cell number and cell viability were also assessed. Modest up-regulation of PTEN mRNA was detected in both cell lines, but little change in protein levels was observed. In accordance with published data, TGF-beta1 suppressed the growth of, and changed the morphology of both cell lines.To study PTEN sub-cellular localisation, full-length human PTEN cDNA was used in RT-PCR to generate a 1.2Kb fragment which was cloned into a green fluorescent protein expression vector pEGFP-N1 to create pRC-2. Sequencing of pRC-2 confirmed the in-frame cloning of wild-type PTEN. Lipid-basedtransfection was used to transiently transfect HEC-1B, Ishikawa and Cos-7 cells. Strong perinuclear and cytoplasmic localisation was detected in these cell lines, and localisation to the endoplasmic reticulum was observed. Stimulation with TGF-beta and 17-beta-estradiol had no discernable effect on sub-cellular localisation of PTEN in either HEC-1B or Ishikawa cell lines.A mutational study was performed using a large repository of archival endometrial carcinomas and normal cervical controls. PCR was used to amplify PTEN exons 5 and 8 from extracted DNA and the fragments separated by single-strand conformation polymorphism (SSCP) analysis. A number of samples exhibiting bandshifts were detected in both exons.
Factors Contributing to Online Purchase Intention amongst Malaysian Consumers: A Case of Lazada

Online shopping activity amongst Malaysians increase unexpectedly ever since Malaysia had its first phase of Movement Control Order. In other words, the global pandemic COVID-19 provided more opportunities for e-commerce such as Lazada to grow. Therefore, this study intends to understand the factors that contribute to online purchase intention amongst Malaysians in the case of Lazada. This study used qualitative and quantitative method. The questionnaire used to collect the data from the respondents. There are 100 Malaysians that had previously purchased from Lazada have participated in the survey. The results showed that there is a positive correlation between product quality, product price, buying experience, after-sales service, and online consumer satisfaction.
Excess Risk of Mortality Due to Heatwaves in Dezful city, Southwest of Iran

Background: Recent studies show that heatwaves pose risks to human health. Iran is exposed to heatwaves, but the evidence for the health impact of heatwaves is scarce. We aimed to evaluate the impact of heatwaves on daily deaths from non-accidental, cardiovascular, and respiratory in the city of Dezful in Iran from 2013 to 2019.Method: We collected daily ambient temperature and mortality and defined two types of heatwaves by combining daily temperature ³90thin each month of the study period or since 30 years with duration ³2 and 3 days. We used a distributed lag non-linear model to investigate the association between each type of heatwave definition and deaths from non-accidental, cardiovascular, and respiratory with lags up to 13 days.Results: Heat waves of both definitions were associated with a higher risk of non-accidental mortality. The association between heat waves and mortality appeared acutely and lasted for 3 and 4 days. The main effect and added effect are more pronounced among male and older adults than their counterparts. We found no evidence of an association of cardiovascular and respiratory deaths with heat waves.Conclusion: Dezful is a city with a hot climate. However, the results showed that heatwaves could have detrimental effects on health, even in populations accustomed to the extreme heat. Therefore, early warning systems which monitor heat waves should provide the necessary warnings to all exposed groups, especially the elderly and the male groups.
Exploring the possibilities of FDM filaments comprising natural fiber-reinforced biocomposites for additive manufacturing

In recent years, with the recent advancements in the field of additive manufacturing, the use of biobased thermoplastic polymers and their natural fiber-reinforced biocomposite filaments have been rapidly emerging. Compared to their oil-based counterparts, they provide several advantages with their low carbon footprints, ease of reusability and recyclability and abundancy, and comparable price ranges. In consideration of their increasing usage, the present study focused on the development and analysis of biocomposite material blends and filaments by merging state-of-the-art manufacturing and material technologies. A thorough suitability study for fused deposition modeling (FDM), which is used to manufacture samples by depositing the melt layer-by-layer, was carried out. The mechanical, thermal, and microstructural characterization of birch fiber reinforced PLA composite granules, in-house extruded filaments, and printed specimens were investigated. The results demonstrated the printability of biocomposite filaments. However, it was also concluded that the parameters still need to be optimized for generic and flawless filament extrusion and printing processes. Thus, minimal labor and end-products with better strength and resolutions can be achieved.
Cardiovascular Risk and Hypertensive patients’ Knowledge, Attitudes and Practices on Modifiable Risk Factors in Kinshasa, the Democratic Republic of the Congo

Good practice on modifiable cardiovascular risk factors is based on good knowledge and a positive attitude. The study aims to assess cardiovascular risk and knowledge, attitudes and practices of hypertensive patients in Kinshasa on modifiable cardiovascular risk factors as well as their associated determinants. We conducted a cross-sectional study with 345 hypertensive patients followed at Monkole Hospital and at Saint-Joseph Hospital in the city of Kinshasa in the Democratic Republic of the Congo from September 2017 to February 2018. The participants were submitted to the WHO-Steps survey. Cardiovascular risk was assessed by the number of deleterious risk factors present in patients. Descriptive and inferential analyzes were performed. The statistical significance threshold was set at p<0.05. The average age of the participants was 62.1±11.2 years with a gender ratio of 1.1 in favor of women. In total, 61%, 56% and 60% of our respondents had, respectively, a low level of knowledge, a bad attitude and an insufficient practice on modifiable cardiovascular risk factors. Good knowledge was statistically significantly linked to education, the medical profession as a source of information, and employment. Only age ≥ 60 years was significantly associated with the right attitude in our patients while good practice was linked to the level of education. The majority of participants (80.3%) had a high cardiovascular risk. Poor knowledge (p: 0.032) and insufficient overall practice (p<0.001) were significantly associated with high cardiovascular risk. The present study showed that hypertension was associated with a high Cardiovascular risk underpinned by a low level of knowledge, a bad attitude and insufficient practice on modifiable cardiovascular risk factors. Therefore, education programs and strategies to positively influence attitudes and practices are essential to reduce the impact of cardiovascular disease and its risk factors in our environment.
Data mining techniques for predicting the financial performance of Islamic banking in Indonesia

Purpose The purpose of this paper is to apply various data mining techniques for predicting the financial performance of Islamic banking in Indonesia through the main exogenous determinants of profitability by choosing the best data mining technique based on the criteria of the highest accuracy score of testing and training. Design/methodology/approach This paper used data mining techniques to predict the financial performance of Islamic banking by applying all of LASSO regression, random forest (RF), artificial neural networks and k-nearest neighbor (KNN) over monthly data sets of all the full-fledged Islamic banks working in Indonesia from January 2011 until March 2020. This study used return on assets as a real measurement of financial performance, whereas the capital adequacy ratio, asset quality and liquidity management were used as exogenous determinants of financial performance. Findings The experimental results showed that the optimal task for predicting the financial performance of Islamic banking in Indonesia is the KNN technique, which affords the best-predicting accuracy, and gives the optimal knowledge from the financial performance of Islamic banking determinants in Indonesia. As well, the RF provides closer values to the optimal accuracy of the KNN, which makes it another robust technique in predicting the financial performance of Islamic banking. Research limitations/implications This paper restricted modeling the financial performance of Islamic banking to profitability through the main determinants of return of assets in Indonesia. Future research could consider enlarging the modeling of financial performance using other models such as CAMELS and Z-Score to predict the financial performance of Islamic banking under data mining techniques. Practical implications Owing to the lack of using data mining techniques in the Islamic banking sector, this paper would fill the literature gap by providing new effective techniques for predicting financial performance in the Islamic banking sector using data mining approaches, which can be efficient tools in business and management modeling for financial researchers and decision-makers in the Islamic banking sector. Originality/value According to the author’s knowledge, this paper is the first that provides data mining techniques for predicting the financial performance of the Islamic banking sector in Indonesia.
Akıllı Telefonlar için Birleştirme Modeli Tabanlı Görüntü Altyazılama

Image Captioning is the process of generating a textual description of an image by using both natural language processing and computer vision. Definition of the visual content of an image to the machine has attracted increasing attention in recent years due to its potential applications. In this study, an image captioning system based on an encoder-decoder merge model approach, applicable to smartphones, is proposed. In the proposed merge model, VGG16 convolutional neural networks are used to extract the image features and long-short term memory are used to extract the word features as encoder. After these two processes, the encoded forms of the images and the word features were merged in the proposed model. Image captioning was done successfully after the combination of these two encoded inputs had been used by a very simple decoder model to generate the next word in the sequence. The proposed system was tested using the BLEUn metric on the Flickr8k/30k dataset and its superiority was shown by comparing it with the studies in the literature. The proposed system was also integrated with our Android application called ImCap, which we have developed to generate captions without an internet connection, unlike other similar studies. With this application, image captioning is aimed to reach more users.
The Pre-Metaphase Stretch: A Re-Examination

Pre-metaphase stretch is a term first coined by the preeminent cell biologist Sally Hughes-Schrader in 1950 to describe an elongation of prometaphase chromosomes observed in the primary spermatocytes of phasmid insects and praying mantids. Research from many groups since Hughes-Schrader’s initial observation has revealed reasons for both how and why chromosomes might elongate prior to metaphase. In this review, we describe Hughes-Schrader’s initial findings and discuss how recent work illuminates and provides some mechanistic explanation for this long-ago observed phenomenon.
Modelling and discrete-event simulation for ski lifts service operations design

This research focuses on the preliminary planning and design of an Alpine skiing lift system in the Mount Carleton Provincial Park, in the province of New Brunswick, Canada. Linear programming (LP) model and discrete-event simulation are combined to design ski lifts selection alternatives and evaluate their service performances based on mountain valley topographical data, skier population features, and ski lift technical specifications. LP model is used to solve the ski lifts selection problem while discrete-event simulation is used to evaluate service quality indicators such as skier waiting times, ski lift queues length, and ski lift utilisation rates in the ski resort early design phase.
Teachers in Primary Education: The Choice between the New Contents Learned in Higher Education and the Same Old Methodologies

This paper presents a research carried out in the Amazon, specifically in the state of Para, Brazil, where the implementation of workshops in the field of elementary mathematics presented to teachers from Pedagogy degree. To develop such a proposal, the workshop is centered on two main issues: Discussion on triggering vectors of some topics in arithmetic and geometry that are part of the content taught to students from the first to the fifth year; questionnaire on which methods of these topics are taught to students or whether teachers choose only one method for each topic and/or whether they use new (active? ) methodologies learned during graduation. The results and the speeches indicate that traditional methods are widely used. On the other hand, teachers who participated in the workshops are strongly willing to change their strategies in teaching elementary mathematics to children.
Reconnecting waterfronts and central neighbourhoods: the lessons to be learned from user behaviour for the redesign of public spaces

ABSTRACT Waterfront redevelopment is one of the main categories of urban project in major cities since the 1980s. However, waterfronts are faced with issues of fragmented land ownership and a lack of integration with other central neighbourhoods. Using Montreal’s waterfront as a case study, this paper shows how the governance framework of urban design may undermine their integration. The observation of user behaviour within public spaces offers a new perspective for the redesign of these links between neighbourhoods, and seeks to contribute to a vision of waterfront precincts beyond the limits imposed by administrative constraints.
Computer-aided automatic approach for denoising of magnetic resonance images

ABSTRACT This paper proposes a dual path deep convolution network based on discriminative learning for denoising MR images. The noise in MR images causes problems in identifying the regions of interest. The proposed approach is incorporated using depthwise separable convolution and local response normalisation in one path. Another path of the network is implemented using depthwise separable convolution and group normalisation. The proposed network was used to denoise the images of different noise levels, and it yields better performance as compared with various networks. The network produces clinically relevant results without retraining the network on other datasets as depicted by the evaluation metrics. The evaluation metrics improved remarkably in the results obtained by the proposed model. The additional external clinical validation was performed by the senior radiologists, and the results were found to be satisfactory for medical diagnosis. The statistical analysis of the results proves the suitability of the results for medical analysis. Further, the images were segmented for checking the applicability of the results in the biomedical domain and a remarkable improvement of about (7 ± 0.03) % and (6.5 ± 0.02) was observed in mIoU and BF score.
Nano-HNS Particles: Mechanochemical Preparation and Properties Investigation

Nano-2,2′,4,4′,6,6′-hexanitrostilbene (HNS) particles were successfully prepared by a mechanochemical (i.e., high energy milling) process without an organic solvent, which can be viewed as a green technology. The particle size, morphology, specific area, crystal phase, thermal decomposition properties, impact sensitivity, and short duration shock initiation sensitivity were characterized and tested. The diameter of milling HNS is about 89.2 nm with a narrow size distribution and without agglomeration of particles. The formation mechanism of nano-HNS can be viewed as the transformation from thin HNS sheets with a one-dimensional nanostructure to three-dimensional nanoparticles. The nano-HNS particles present a much higher and lower impact sensitivity than purified HNS, revealing the outstanding safety properties. From the results of the short duration shock initiation sensitivity, 50% and 100% initiation voltages are decreased compared with those of HNS-IV, indicating the higher initiation sensitivity.
New product diffusion models

U radu se analiziraju neki poznati modeli difuzije novog proizvoda u odnosu na pretpostavke o kretanju stope rasta difuzije. Na toj osnovi predlaže se jedan novi model difuzije novog proizvoda. Za navedene modele analiziraju se također broj i vrsta potrosackih kategorija.