Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of Porous Titanium-Hydroxyapatite Composite Biological Coating on Polyetheretherketone (PEEK) by Vacuum Plasma Spraying

Titanium powders and hydroxyapatite powders were used to fabricate the titanium and hydroxyapatite composite coating (Ti/Ti/HA) on the Polyetheretherketone (PEEK) by vacuum plasma spraying (VPS). The phase composition and morphology of the Ti/Ti/HA coating were analyzed by XRD, SEM, industrial CT, and three-dimensional contour profiler (DEKTAK XT). The results showed that the phase composition of the Ti/Ti/HA coating was dominated by the HA phase and a small amount of the Ti phase. The Ti/Ti/HA composite coating presented an obvious three-layer structure with different roughness and porosity. The bottom was Ti coating with a porosity less than 10%; the middle was porous Ti coating with a porosity of 35% ± 10%; the surface coating was HA coating with the crystallinity near 95%, a porosity of 32% ± 10%, a roughness Ra = 30 ± 10 μm. Moreover, the TG-DSC and ATR-FTIR results showed that VPS coating has no effect on thermochemical properties of PEEK material. The average bond strength of the composite coating was achieved 32 MPa.
Association between Quality of Diets and the Risk of Obesity Complication among a Sample of Egyptian Obese Women

Abstract Background: The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. The aim of this study was to identify the awareness of a sample of Egyptian women about eating healthy diet, using Dietary Approaches to Stop Hypertension (DASH) diet as an example. Methods: This study is a cross-sectional study included 109 Egyptian women random chosen, with age range 25-60 years. Full clinical examinations, anthropometric parameters, dietary recalls, and socioeconomic parameters were recorded. Biochemical analysis was done including serum lipid profile. Results: Data showed that a large percentage of the participants (56.9%) were consuming a poor-quality diet, while 20.0% were consuming intermediate quality diet. Only 16.5% and 9.2% of them were aware of eating a good and high-quality healthy diet. Data shows that the calories, macronutrients, saturated fatty acids (SFAs), cholesterol and sodium intake among both poor and the intermediate groups were higher, while their intake of the monounsaturated fatty acids (MUFAs), poly unsaturated fatty acids (PUFAs), fiber, important vitamins and the minerals, was significantly low. The mean values of the BMI, body fat %, FFM (Fat Free Mass), waist circumference, visceral fat and LDL-C values showed significant differences between the groups at p≤ 0.05- 0.001, in favor of the good and high groups. Conclusions: Data of this study revealed that poor quality diet was widespread among studied Egyptian women sample; right food choice was associated with the educational level. So, helping individuals to make the right food choices will help in improve diet quality and health.
Detection of Forest Tree Losses in Côte d’Ivoire Using Drone Aerial Images

The fight against deforestation and forest degradation is now a major challenge for the preservation of global forest ecosystems. The remote sensing forest monitoring methods that are currently deployed are not always adapted to the Ivorian context because of the high cloud cover, diversity of shaded crops, and land clearing techniques. This study proposes a drone-based approach to assess intra-annual tree losses in the Bossématié classified forest. The method used is based on a detection analysis of tree losses in forest areas from a time series of aerial images acquired by drones from November 2018 to April 2019 on five sites in the studied forest. Based on photogrammetric models and photointerpretation, tree heights and tree crown sizes were estimated. Then, tree losses were detected based on the variation of tree heights during the study period. An analysis of the distribution of tree heights in Bossématié classified forest reveals that the maximum tree height was 65.06 m in November 2018 and 64.07 m in April 2019 with an average tree height of 34.29–37.00 m in November 2018 and 34.63–36.88 m in April 2019. The average tree crown area, meanwhile, was estimated to be 152 m². With an estimation accuracy of about 97%, these tree structural data indicate a minimum loss of 107 trees corresponding to a clearing area of 2 ha across all the surveyed sites from November 2018 to April 2019. This forest monitoring approach shows a considerable local loss of biodiversity and should be involved in the implementation of preservation, rehabilitation, and deployment strategies in an operational deforestation monitoring system in Côte d’Ivoire.
STGM: Vehicle Trajectory Prediction Based on Generative Model for Spatial-Temporal Features

For safe and efficient navigation in driving environment, autonomous vehicles are supposed to predict future trajectories of surrounding vehicles dynamically and tackle the uncertainty of environment. Early works view uncertainty as distributions in different modals, and perform this task by enumerating a mass of trajectories, but can hardly cover all the possible modal distributions. Recently, generative model has risen to hold promise for modelling such distributions, something that we will build upon here. Target at predefined modals of vehicle agents, this paper proposes Spatial-Temporal Generative Model (STGM), a new learning algorithm that leverages a stochastic generative model to mitigate modal distributions problem. To be more specific, a Conditional Variational Auto-Encoder (CVAE) is leveraged to construct the framework of STGM, in which the input is augmented into modal distributions to gain modality-wise trajectories. Besides, for the stability of prediction, we also come up with a new modal-wise sampling trick as an alternative of traditional random sampling in CVAE. Considering that multiple layer perception (MLP) based CVAE is incapable of extracting spatial and temporal features effectively, we use two respective encoders before CVAE: Spatial Encoder and Temporal Encoder, and align them with a closed modal set. Additionally, inspired by the Total Probability Formula, we adopt a Modal Prediction Model to refine the confidences of modal-wise trajectories. After empirical evaluation on two public datasets, we find that STGM almost outperforms the baselines, such as Covernet, MTP, and so on.
Dynamic Resource Allocation Using Improved Firefly Optimization Algorithm in Cloud Environment

ABSTRACT Today, cloud computing has provided a suitable platform to meet the computing needs of users. One of the most important challenges facing cloud computing is Dynamic Resource Allocation (DSA), which is in the NP-Hard class. One of the goals of the DSA is to utilization resources efficiently and maximize productivity. In this paper, an improved Firefly algorithm based on load balancing optimization is introduced to solve the DSA problem called IFA-DSA. In addition to balancing workloads between existing virtual machines, IFA-DSA also reduces completion time by selecting appropriate objectives in the fitness function. The best sequence of tasks for resource allocation is formulated as a multi-objective problem. The intended objectives are load balancing, completion time, average runtime, and migration rate. In order to improve the initial population creation in the firefly algorithm, a heuristic method is used instead of a random approach. In the heuristic method, the initial population is created based on the priority of tasks, where the priority of each task is determined based on the pay as you use model and a fuzzy approach. The results of the experiments show the superiority of the proposed method in the makespan criterion over the ICFA method by an average of 3%.
Estimate of the Biological Dose in Hadrontherapy Using GATE

Simple Summary This study presents the implementation of a biological dose module using the Monte Carlo software, GATE. Both mMKM and NanOx biophysics models of cell survival predictions were used as input. The code was validated in terms of biological dose, relative biological effectiveness and cell survival against experimental data from the HIMBC (Hyogo, Japan) ion beam line. Abstract For the evaluation of the biological effects, Monte Carlo toolkits were used to provide an RBE-weighted dose using databases of survival fraction coefficients predicted through biophysical models. Biophysics models, such as the mMKM and NanOx models, have previously been developed to estimate a biological dose. Using the mMKM model, we calculated the saturation corrected dose mean specific energy z1D* (Gy) and the dose at 10% D10 for human salivary gland (HSG) cells using Monte Carlo Track Structure codes LPCHEM and Geant4-DNA, and compared these with data from the literature for monoenergetic ions. These two models were used to create databases of survival fraction coefficients for several ion types (hydrogen, carbon, helium and oxygen) and for energies ranging from 0.1 to 400 MeV/n. We calculated α values as a function of LET with the mMKM and the NanOx models, and compared these with the literature. In order to estimate the biological dose for SOBPs, these databases were used with a Monte Carlo toolkit. We considered GATE, an open-source software based on the GEANT4 Monte Carlo toolkit. We implemented a tool, the BioDoseActor, in GATE, using the mMKM and NanOx databases of cell survival predictions as input, to estimate, at a voxel scale, biological outcomes when treating a patient. We modeled the HIBMC 320 MeV/u carbon-ion beam line. We then tested the BioDoseActor for the estimation of biological dose, the relative biological effectiveness (RBE) and the cell survival fraction for the irradiation of the HSG cell line. We then tested the implementation for the prediction of cell survival fraction, RBE and biological dose for the HIBMC 320 MeV/u carbon-ion beamline. For the cell survival fraction, we obtained satisfying results. Concerning the prediction of the biological dose, a 10% relative difference between mMKM and NanOx was reported.
Time-Specific Factors Influencing the Development of Asthma in Children

Susceptibility to asthma is complex and heterogeneous, as it involves both genetic and environmental insults (pre- and post-birth) acting in a critical window of development in early life. According to the Developmental Origins of Health and Disease, several factors, both harmful and protective, such as nutrition, diseases, drugs, microbiome, and stressors, interact with genotypic variation to change the capacity of the organism to successfully adapt and grow in later life. In this review, we aim to provide the latest evidence about predictive risk and protective factors for developing asthma in different stages of life, from the fetal period to adolescence, in order to develop strategic preventive and therapeutic interventions to predict and improve health later in life. Our study shows that for some risk factors, such as exposure to cigarette smoke, environmental pollutants, and family history of asthma, the evidence in favor of a strong association of those factors with the development of asthma is solid and widely shared. Similarly, the clear benefits of some protective factors were shown, providing new insights into primary prevention. On the contrary, further longitudinal studies are required, as some points in the literature remain controversial and a source of debate.
The Human Myelin Proteome and Sub-Metalloproteome Interaction Map: Relevance to Myelin-Related Neurological Diseases

Myelin in humans is composed of about 80% lipids and 20% protein. Initially, myelin protein composition was considered low, but various recent proteome analyses have identified additional myelin proteins. Although, the myelin proteome is qualitatively and quantitatively identified through complementary proteomic approaches, the corresponding Protein–Protein Interaction (PPI) network of myelin is not yet available. In the present work, the PPI network was constructed based on available experimentally supported protein interactions of myelin in PPI databases. The network comprised 2017 PPIs between 567 myelin proteins. Interestingly, structure-based in silico analysis revealed that 20% of the myelin proteins that are interconnected in the proposed PPI network are metal-binding proteins/enzymes that construct the main sub-PPI network of myelin proteome. Finally, the PPI networks of the myelin proteome and sub-metalloproteome were analyzed ontologically to identify the biochemical processes of the myelin proteins and the interconnectivity of myelin-associated diseases in the interactomes. The presented PPI dataset could provide a useful resource to the scientific community to further our understanding of human myelin biology and serve as a basis for future studies of myelin-related neurological diseases and particular autoimmune diseases such as multiple sclerosis where myelin epitopes are implicated.
Network Representation Learning Algorithm Based on Community Folding

Network representation learning is a machine learning method that maps network topology and node information into low-dimensional vector space, which can reduce the temporal and spatial complexity of downstream network data mining such as node classification and graph clustering. This paper addresses the problem that neighborhood information-based network representation learning algorithm ignores the global topological information of the network. We propose the Network Representation Learning Algorithm Based on Community Folding (CF-NRL) considering the influence of community structure on the global topology of the network. Each community of the target network is regarded as a folding unit, the same network representation learning algorithm is used to learn the vector representation of the nodes on the folding network and the target network, then the vector representations are spliced correspondingly to obtain the final vector representation of the node. Experimental results show the excellent performance of the proposed algorithm.
Google Trends data reveal a sharp trend: teeth and claws attract more interest than feathers, hooves or fins

Summary In nature conservation, the generation of public interest, attention or emotions is an important instrument for nature, biotope and species protection; in this, charismatic flagship species play an important role. In the present study, flagship-making affiliation to a taxonomic unit as well as morphological, ecological and conservation traits were identified by analysing vertebrate species from each of the five extant vertebrate classes (Mammalia, Aves, Reptilia, Amphibia and fishes). Google Trends data on the 20 most Googled species of each of the five classes were used, a representation index was derived and the body mass, diet and protection status of these species were analysed. A clear concentration of interest in mammalian species was evident with the help of the introduced representation index. Furthermore, species with a higher body mass were clearly overrepresented in the data. Overall, important patterns in the studied traits were determined: belonging to Mammalia, a large body mass and a carnivorous diet are frequently represented among these species. For conservation purposes, such popular species can be specifically selected as flagship species or ambassadors to help protect entire biomes, which will therefore benefit less charismatic species as well. Possible ways to use traits that are perceived to be flagship-making in order to further the global conservation endeavour are briefly discussed.
Classification of Solid Oxide Fuel Cells

Solid oxide fuel cells (SOFC) are promising, environmentally friendly energy sources. Many works are devoted to the study of materials, individual aspects of SOFC operation, and the development of devices based on them. However, there is no work covering the entire spectrum of SOFC concepts and designs. In the present review, an attempt is made to collect and structure all types of SOFC that exist today. Structural features of each type of SOFC have been described, and their advantages and disadvantages have been identified. A comparison of the designs showed that among the well-studied dual-chamber SOFC with oxygen-ion conducting electrolyte, the anode-supported design is the most suitable for operation at temperatures below 800 °C. Other SOFC types that are promising for low-temperature operation are SOFC with proton-conducting electrolyte and electrolyte-free fuel cells. However, these recently developed technologies are still far from commercialization and require further research and development.
The parameterization of microchannel‐plate‐based detection systems

The most common instrument for low‐energy plasmas consists of a top‐hat electrostatic analyzer (ESA) geometry coupled with a microchannel‐plate‐based (MCP‐based) detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Here we develop a comprehensive mathematical description of particle detection systems. As a function of instrument azimuthal angle, we parameterize (1) particle scattering within the ESA and at the surface of the MCP, (2) the probability distribution of MCP gain for an incident particle, (3) electron charge cloud spreading between the MCP and anode board, and (4) capacitive coupling between adjacent discrete anodes. Using the Dual Electron Spectrometers on the Fast Plasma Investigation on NASA's Magnetospheric Multiscale mission as an example, we demonstrate a method for extracting these fundamental detection system parameters from laboratory calibration. We further show that parameters that will evolve in flight, namely, MCP gain, can be determined through application of this model to specifically tailored in‐flight calibration activities. This methodology provides a robust characterization of sensor suite performance throughout mission lifetime. The model developed in this work is not only applicable to existing sensors but also can be used as an analytical design tool for future particle instrumentation.
Magnetic plucking of piezoelectric bimorphs for a wearable energy harvester

A compact and low-profile energy harvester designed to be worn on the outside of the knee-joint is presented. Frequency up-conversion has been widely adopted in recent times to exploit the high frequency response of piezoelectric transducers within environments where only low frequencies are present. Contactless magnetic plucking is here introduced, in a variable reluctance framework, with the aim of improving the mechanical energy transfer into the transducers, which is sub-optimal with contact plucking. FEA and experiments were used to design an optimal arrangement of ferromagnetic teeth to interact with the magnets fixed to the piezoelectric beams. A prototype was made and extensively tested in a knee-joint simulator controlled with gait data available in the literature. Energy and power produced were measured for walking and running steps. A power management unit was developed using off-the-shelf components, permitting the generation of a stable and regulated supply of 26 mW at 3.3 V during walking. Record levels of rectified (unregulated) electrical power of over 50 and 70 mW per walking and running steps, respectively, were measured.
Safety of radiation exposure during pregnancy in COVID-19 affected women

Radiologic imaging in the evaluation of pregnant patients has significantly grown with the outbreak of the severe acute respiratory syndrome related to SARS-CoV-2 pandemic. Lung ultrasound is an emerging non-invasive bedside technique used to diag-nose interstitial lung syndrome through evaluation and quantitation of the number of B-lines, pleural irregularities and nodules or consolidations. In pregnant COVID-19 patients, lung ultrasound should be considered on ac-count of its various strengths, such as its being easily carried out bedside by trained sonographers for the monitoring of lung involvement in follow-ups, and its repeatability and affordability. However, pregnant patients could need chest radiography or computed tomo-graphic (CT) examinations for the diagnosis of pneumonia. Concerns and mis-conceptions about potential radiation-related risks for the embryo or fetus are still widespread among clinicians and can lead to excessive anxiety among pa-tients. Several well-recognized guidance documents were published in the last years as to the safety of a single-phase CT or an X-ray chest and related carcino-genic and teratogenic risk. This paper summarizes the safety of radiological examination for pneumonia in pregnant women affected by COVID 19, based on the estimated embryo-fetal radiation absorption per procedure (mGy).
Serviks Dokularında HPV DNA Pozitifliği ve Osteopontin Düzeyi Arasındaki İlişkinin Araştırılması

Objective: This study aimed to investigate the osteopontin levels in HPV-positive and HPV-negative cervical tissues and evaluate the clinical significance of osteopontin as a prognostic biomarker. Methods: A total of 82 individuals admitted to the outpatient clinic of Obstetrics and Gynecology Department of Erzincan Binali Yıldırım University, Mengücek Gazi Training and Research Hospital in Turkey and underwent cervical cancer screening between June 2015 and April 2017 were included in the study. Cervicovaginal swabs were collected according to the standard procedure. A slide for traditional Pap cytology was prepared and stained according to standard protocols, and the results were categorized according to the 2004 Bethesda classification system. All cervical specimens were analyzed using the Digene® HC2 High-Risk HPV DNA Kit. Genotyping was performed on the samples with HPV DNA positivity with the Clark kit. Osteopontin levels of 41 HPV positive patients and 41 HPV negative control were investigated in tissue samples with an ELISA kit. Results: The osteopontin levels were found to be 31.55 ± 7.11 ng/ml and 28.81 ± 5.44 ng/ml in the study and control groups, respectively, which indicated a statistically significant difference between the groups (p=0.048). There was no statistically significant difference between the osteopontin level and age, delivery method, history of disease, surgical method, HPV type, preoperative and postoperative pathology, gravida and parity (p>0.05). Conclusion: The detection of cervical intraepithelial neoplasia in only five of 41 HPV-positive patients constitutes a limitation for this study. Although the level of osteopontin was high in HPV-positive patients, further studies with more cervical intraepithelial neoplasia cases are required.
ANALISIS MASALAH PADA DATA REVIEW APLIKASI TERHADAP LAYANAN E-COMMERCE MENGGUNAKAN METODE TEXT CLASSIFICATION

Shopee merupakan salah satu e-commerce model e-commerce Customer-To Customer (C2C) menggunakan aplikasi sebagai tempat untuk melakukan bisnis. Shopee memberikan beberapa pilihan akses kepada customer diantaranya melalui website dan mobile platform demi kemudahan kegiatan berbelanja online. Untuk mencari informasi tentang peluang yang dapat ditingkatkan dari layanan yang ada Shopee dapat memanfaatkan review dari customer untuk mengetahui masalah yang terjadi pada layanan yang diberikan kepada customer. Review dari customer e-commerce berbasis aplikasi tersebut dapat menjadi solusi yang lebih menjelaskan apa yang disukai dan tidak disukai customer sehingga bisa digunakan sebagai alat untuk menilai aspek-aspek pada layanan e-commerce yang dinilai bermasalah. Untuk mencari informasi tentang peluang yang dapat ditingkatkan pada layanan e-commerce dari komplain atau keluhan review customer. dilakukan dengan mengklasifikasi review kedalam beberapa aspek dengan menggunakan Text Classification untuk mengklasifikasikan aspek. Dari hasil tersebut didapat lah rangkuman masalah berdasarkan aspek yang bisa diperbaiki oleh pihak e-commerce untuk tetap meningkatkan layanan.