Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk factors of Pressure Ulcers in hospitalized elderly Egyptian people

Background Pressure ulcers (PUs) are increasing with aging of the population around the world and represent a common and frustrating problem affecting geriatric patients. Age-related skin changes increase the vulnerability to ulceration. Aging not only increases the risk of PU occurrence, but also affects healing of such ulcers. Also, frailty, associated comorbidities, impaired mobility, and cognitive impairment predispose many elderly populations to the development of PUs (1, 2). The prevalence of PUs peaks in those between age 70 and 80 years. They occur in hospitals, nursing homes, and even in community settings. The highest incidence of new ulcers occurs in hospitals and may be as high as 50% in acute care geriatric units, increasing health care expenditure and mortality rate, whereas the highest prevalence occurs in long-term care facilities (3). Also, the incidence of ulcers differs by the stage of ulceration. Stage 1 and 2 occur more frequently than later stages (4). Despite the progress in technology and medical advances, the cost of management of hospital acquired PU is increasing. The cost of treating these mainly preventable ulcers in the United Kingdom (UK) accounts for about 4% of the total National Health Service (NHS) expenditure (5). Therefore, the identification of people at risk for PUs is an important component of preventive care for the elderly (6). The National Pressure Ulcer Advisory Panel (NPUAP) has agreed that not all PUs are preventable and there are clinical situations in which the development of PUs can be unavoidable such as end stage dementia, severe congestive heart failure and forced immobilization (7). To our knowledge only few studies were done in Egypt, approaching mainly nurses’ knowledge and educational programs about PU and no studies searched for risk factors for PU in Egyptian population (8, 9, 10).
Bioreactor Rhamnolipid Production Using Palm Oil Agricultural Refinery By-Products

Palm fatty acid distillate (PFAD) and fatty acid methyl ester (FAME) are used by P. aeruginosa PAO1 to produce rhamnolipid biosurfactant. The process of fermentation producing of biosurfactant was structured in a 2 L bioreactor using 2% of PFAD and FAME as carbon sources in minimal medium and with a nitrogen concentration of 1 g L−1. Mass spectrometry results show the crude biosurfactant produced was predominantly monorhamnolipid (Rha-C10-C10) and dirhamnolipid (Rha-Rha-C10-C10) at 503 and 649 m/z value for both substrates. Maximum production of crude rhamnolipid for PFAD was 1.06 g L−1 whereas for FAME it was 2.1 g L−1, with a reduction in surface tension of Tris-HCl pH 8.0 solution to 28 mN m−1 and a critical micelle concentration (CMC) of 26 mg L−1 measured for both products. Furthermore, the 24 h emulsification indexes in kerosene, hexadecane, sunflower oil, and rapeseed oil using 1 g L−1 of crude rhamnolipid were in the range 20–50%. Consequently, PFAD and FAME, by-products from the agricultural refining of palm oil, may result in a product that has a higher added-value, rhamnolipid biosurfactant, in the process of integrated biorefinery.
Design of New Single-phase Multilevel Voltage Source Inverter

Multilevel inverters with more number of levels can produce high quality voltage waveforms. In this paper, a new single-phase structure for multilevel voltage source inverter is proposed which can generate a large number of levels with reduced number of IGBTs, gate driver circuits and diodes. Three algorithms for determination of dc voltage sources’ magnitudes are presented which provide odd and even levels at the output voltage waveform. A comparison is presented between proposed multilevel inverter and conventional cascade topology. The proposed topology is analyzed by the experimental and simulation results. DOI: http://dx.doi. org/10.11591/ijpeds.v5i1. 6218
Accuracy Assessment of the GlucoMen® Day CGM System in Individuals with Type 1 Diabetes: A Pilot Study

The aim of this study was to evaluate the accuracy and usability of a novel continuous glucose monitoring (CGM) system designed for needle-free insertion and reduced environmental impact. We assessed the sensor performance of two GlucoMen® Day CGM systems worn simultaneously by eight participants with type 1 diabetes. Self-monitoring of blood glucose (SMBG) was performed regularly over 14 days at home. Participants underwent two standardized, 5-h meal challenges at the research center with frequent plasma glucose (PG) measurements using a laboratory reference (YSI) instrument. When comparing CGM to PG, the overall mean absolute relative difference (MARD) was 9.7 [2.6–14.6]%. The overall MARD for CGM vs. SMBG was 13.1 [3.5–18.6]%. The consensus error grid (CEG) analysis showed 98% of both CGM/PG and CGM/SMBG pairs in the clinically acceptable zones A and B. The analysis confirmed that GlucoMen® Day CGM meets the clinical requirements for state-of-the-art CGM. In addition, the needle-free insertion technology is well tolerated by users and reduces medical waste compared to conventional CGM systems.
A study on higher‐order disturbance observer and robust stability

In earlier papers, it has been reported that a fast and precise servo system, which has low sensitivity to parameter variation and disturbance, can be realized with simple structure by using a high-order disturbance observer. However, no clear and simple design method satisfying specifications for robust stability, the influence of measurement noise, and relative stability (damping characteristics) for large parameter variation has been proposed. In this paper, we clarify the class of robust servo systems realized by adjusting the order of the disturbance observer and the control parameters. We apply this strategy to the design of a second delay system, such as a position servo system, and realize a high-performance robust servo system using a high-order disturbance observer. © 1999 Scripta Technica, Electr Eng Jpn, 128(1): 37–44, 1999
Synergistic PAHs biodegradation by a mixed bacterial community: Based on a multisubstrate enrichment approach

Polycyclic aromatic hydrocarbons (PAHs) are highly hard-biodegradable compounds. Therefore, in this work, a multisubstrate enrichment approach was proposed to develop a bacterial community named MBF from activated sludge of coking wastewater plant capable of degrading mixed-PAHs consisting of phenanthrene and pyrene (50 mg/L of each) by 98.8% and 73.3% within 5 days, respectively. The bacterial community could maintain its degradation ability to mixed PAHs relatively under temperatures (20°C–35°C), pH values (5.0–9.0), and salinities (0–10 g/L NaCl). Additionally, the bacterial community MBF degraded 58.9%, 79.9%, and 80.7% of mixed PAHs in the presence of catechol, salicylic acid, and phthalic acid, respectively within 5 days. High-throughput sequencing of 16S rRNA gene amplicon analysis showed that the bacterial community MBF was dominated by Pseudomonas in most treatments, and Burkholderia was predominant under both acidic condition and high salt concentrations. Furthermore, the composition of microbial communities of the bacterial community was significantly different with/without addition of pathway intermediate metabolites after biodegradation of mixed PAHs, revealing the metabolic burden may be distributed between members of this bacterial community. Those results demonstrate that the biodegradation ability of MBF could be maintained with the bacterial community structure altering when facing environmental variations or changes in composition of target contaminants.
Similarities and Differences in Psychophysiological Reactions Between Simulated and Real Air-to-Ground Missions

This study examines the similarities and differences in psychophysiological reactions in simulated and real flight. Five fighter pilots from the Swedish Air Force participated in the study, flying the same type of mission in a simulator and in real flight. Each pilot flew the same mission 3 times in the simulator and later 3 times in real flight. The pilots' heart rate, heart rate variability, and eye movements were continuously measured. Analyses of these data indicate that the pilots' psychophysiological reactions are very analogous in the simulator and in real flight.
Performance Analysis of Machine Learning Classification Algorithms for Breast Cancer Diagnosis

Machine Learning based learning algorithms gives the machine the power to learn on its own without being explicitly programmed by a programmer. It helps in automating the task like classification, clustering, etc. which previously required human intervention. Machine Learning-based classification algorithms today are being widely used for the diagnosis of various diseases such as Breast Cancer. Breast Cancer is one of the primary causes of death among women all over the world in the past recent years. In this paper, Random Forest, Logistics Regression, Decision Tree, Naive Bayes and SVM classification algorithms have been implemented. The experiment in this article has been conducted on the most popular Wisconsin Diagnosis Breast Cancer Dataset (WDBC)[l]. The main objective of conducting this experiment is to analyze the correctness and accuracy of classification algorithms used to classify cancer-causing tumours (Malignant) from non-cancerous tumours (Benign) with the highest precision and accuracy. The experiment results show that Random Forest gave the highest accuracy amongst all the classification algorithms.
Exact representation of antenna system diversity performance from input parameter description

A simple formulation to compute the envelope correlation of an antenna diversity system is derived. It is shown how to compute the envelope correlation from the S-parameter description of the antenna system. This approach has the advantage that it does not require the computation nor the measurement of the radiation pattern of the antenna system. It also offers the advantage of providing a clear understanding of the effects of mutual coupling and input match on the diversity performance of the antenna system.
Background Notes

Introduction This release updates the annual statistical series on Foreign Direct Investment (FDI) which was introduced in December 2003. The data presented show annual direct investment flows over the reference year along with end-year stocks (or positions) for Ireland broken down geographically by region and by country. The release includes tables with further analyses of the FDI flows and stocks broken down by the principal economic activity (using the NACE Rev.2 classification) of the resident direct investment enterprise. These results form part of the range of Balance of Payments (BOP), International Investment Position (IIP) and related statistics published by the CSO. The figures presented are methodologically consistent with the data already presented in the quarterly balance of payments and IIP releases.
Existing and Emerging Breast Cancer Detection Technologies and Its Challenges: A Review

Breast cancer is the most leading cancer occurring in women and is a significant factor in female mortality. Early diagnosis of breast cancer with Artificial Intelligent (AI) developments for breast cancer detection can lead to a proper treatment to affected patients as early as possible that eventually help reduce the women mortality rate. Reliability issues limit the current clinical detection techniques, such as Ultra-Sound, Mammography, and Magnetic Resonance Imaging (MRI) from screening images for precise elucidation. The capability to detect a tumor in early diagnosis, expensive, relatively long waiting time due to pandemic and painful procedure for a patient to perform. This article aims to review breast cancer screening methods and recent technological advancements systematically. In addition, this paper intends to explore the progression and challenges of AI in breast cancer detection. The next state of the art between image and signal processing will be presented, and their performance is compared. This review will facilitate the researcher to insight the view of breast cancer detection technologies advancement and its challenges.
Power quality indices for aperiodic voltages and currents

Summary form only given as follows. This paper addresses the subject of transient electric power quality problems. The quantification of power quality in terms of simple indices such as total harmonic distortion and other measures is revisited in terms of the windowed Fourier transform. This transform is a short term Fourier transform evaluated over a time window. The result is a set of new power quality indices which collapse to the familiar forms for the cases of periodic steady state, but which capture transient amplitudes for nonsteady state applications. Applications are suggested.
Study on the Stability and Motion Control of a Unicycle : Part I : Dynamics of a Human Riding a Unicycle and Its Modeling by Link Mechanisms

In this paper, the dynamic characteristics of a human riding a unicycle are analyzed following observation. From the observation and analysis, we found that the rider's trunk, thighs and shanks form two closed-link loops, and this special mechanism plays an important role in the stability of the unicycle. Based on this idea, we developed a new model with two closed-link mechanisms and one turntable to enable a robot to emulate a human riding a unicycle. Considering the nonholonomic constraint between the wheel and ground, and using a recently developed general method to compute the multi-closed-link mechanisms' dynamic motion, we obtained the dynamic equations of motion for this new model. With these equations, the simulation is conducted under the proposed control method. The simulation result indicates that both the longitudinal and lateral stability of a unicycle ridden by a human can be satisfactorily emulated by this new model.
Gear Fault Detection and Diagnosis Based on its Fabrication Material

A novel application of Hilbert-Huang transform method to fault diagnosis of gear crack is presented. The methodology developed in this paper decomposes the original times series data in intrinsic oscillation modes, using the empirical mode decomposition. Then the Hilbert transform is applied to each intrinsic mode function. Therefore, the time-frequency distribution is obtained.
Kinase Inhibitors’ Effects on Innate Immunity in Solid Cancers

Simple Summary In this review, we evaluate the updated data of the immunological effects of kinase inhibitors on the innate immune system and provide an in-depth analysis of the underlying mechanisms. We also discuss how this immunological effect can be harnessed to improve cancer treatment and highlight recent successes, such as the combination with anti-tumor immunotherapy. Last, we explore novel kinase targets and the incorporation of them with targeted drug delivery techniques as promising research areas. Abstract Innate immune cells constitute a plastic and heterogeneous cell population of the tumor microenvironment. Because of their high tumor infiltration and close interaction with resident tumor cells, they are compelling targets for anti-cancer therapy through either ablation or functionally reprogramming. Kinase inhibitors (KIs) that target aberrant signaling pathways in tumor proliferation and angiogenesis have been shown to have additional immunological effects on myeloid cells that may contribute to a protective antitumor immune response. However, in patients with malignancies, these effects are poorly described, warranting meticulous research to identify KIs’ optimal immunomodulatory effect to support developing targeted and more effective immunotherapy. As many of these KIs are currently in clinical trials awaiting approval for the treatment of several types of solid cancer, we evaluate here the information on this drug class’s immunological effects and how such mechanisms can be harnessed to improve combined treatment regimens in cancer.
Quasi-transversal synthesis of microwave chirped filters

A numerical synthesis procedure for surface acoustic wave (SAW) devices has been adapted for microwave delay-line filters. The effect of multiple reflections between taps is fully allowed for, and almost arbitrary phase and amplitude responses can be specified; linear chirp filters are reported. Modification of the SAW version has eliminated the third harmonic and thus permitted fractional bandwidths exceeding 100% to be demonstrated.
Electromechanical Events in Exercise-induced Remodeling of the Equine Heart

Analysis of synchronized phonocardiographic (PCG) and electrocardiographic (ECG) data provides insights into cardiac electromechanics that have previously not been investigated in the context of exercise-induced cardiac remodeling. This study aimed to obtain PCG data synchronized with ECG using an electronic stethoscope and an acoustic stethoscope with an add-on (microphone inserted into the stethoscope tube and connected to a smart device), both synchronized with the ECG, and simultaneous echocardiographic and ECG data in trained and untrained horses to assess the feasibility of the devices to obtain measurements of electromechanical durations in exercise-induced remodeling of the heart. A base-apex ECG synchronized with PCG was recorded in seven trotters. A complete echocardiographic examination was performed. The electromechanical durations measured by echocardiography were not consistent with those measured by a PCG synchronized to the ECG. The approach to obtain representative measurements of electromechanical intervals with the prototype device PCG synchronized to ECG proved feasible and provided precise measurements.
Diversity, antimicrobial activity, and susceptibility of culturable soil actinobacteria isolated from Sichang Island

: Actinobacteria are a promising source of novel antibiotics. The study of diverse actinobacteria from Sichang Island may lead to a discovery of new microbes with pharmaceutical applications. Some actinobacteria, especially those in the genus Nocardia , can cause infection in humans and animals. A total of 55 actinobacteria were isolated from six soil samples collected from Sichang Island, Chonburi Province, Thailand. Based on the morphological characteristics and 16S rRNA gene analysis, the actinobacterial isolates were classiﬁed into three genera including Streptomyces (32 isolates), Nocardia (22 isolates), and Saccharothrix (1 isolate). Most of the Streptomyces and the Saccharothrix isolates exhibited antimicrobial activity, with none observed among the Nocardia strains. The 16S rRNA gene similarity suggested three strains represented candidates of novel taxa. Moreover, most of the Nocardia were rare environmental species. Antimicrobial susceptibility testing revealed that amoxicillin / clavulanate (2 / 1), imipenem, and linezolid were active against Nocardia strains, but they were not susceptible to ceftriaxone, cefotaxime, clarithromycin, ciproﬂoxacin, and trimethoprim / sulfamethoxazole. The susceptibility proﬁles vary between strains and species.
Thinking Quantitatively of RNA-Based Information Transfer via Extracellular Vesicles: Lessons to Learn for the Design of RNA-Loaded EVs

Extracellular vesicles (EVs) are 50–1000 nm vesicles secreted by virtually any cell type in the body. They are expected to transfer information from one cell or tissue to another in a short- or long-distance way. RNA-based transfer of information via EVs at long distances is an interesting well-worn hypothesis which is ~15 years old. We review from a quantitative point of view the different facets of this hypothesis, ranging from natural RNA loading in EVs, EV pharmacokinetic modeling, EV targeting, endosomal escape and RNA delivery efficiency. Despite the unique intracellular delivery properties endowed by EVs, we show that the transfer of RNA naturally present in EVs might be limited in a physiological context and discuss the lessons we can learn from this example to design efficient RNA-loaded engineered EVs for biotherapies. We also discuss other potential EV mediated information transfer mechanisms, among which are ligand–receptor mechanisms.
LES of additive and non-additive pulsatile flows in a model arterial stenosis

Transition of additive and non-additive pulsatile flows through a simple 3D model of arterial stenosis is investigated by using a large eddy simulation (LES) technique. We find in both the pulsatile cases that the interaction of the two shear layers, one of which separates from the nose of the stenosis and the another one from its opposite wall, causes recirculation in the flow downstream of the stenosis where the nature of the transient flow becomes turbulent. The strength of this recirculation is found to be quite high from the non-additive pulsations when the flow Reynolds numbers, , for which both the pressure and shearing stresses take on an oscillating form at the post-stenotic region. Potential medical consequences of these results are discussed in the paper. In addition, some comparisons of the non-additive pulsatile results are given with those of both the additive pulsatile and steady flows. The capability of using LES to simulate the pulsatile transitional flow is also assessed, and the present results show that the smaller (subgrid) scales (SGS) contributes about 78% energy dissipation to the flow when the Reynolds number is taken as 2000. The level of SGS dissipation decreases as the Reynolds number is decreased. The numerical results are validated with the experimental data available in literature where a quite good agreement is found.
A Probabilistic Approach to Measuring Online User Extremism: A Case Study of a Novel Dataset from Breitbart News

The Internet has seen a dramatic increase in online toxicity commonly associated with far-right and extremist movements. In this paper, we mined a novel dataset of article information, alongside user comments from the right-wing political news site, Breitbart News Network. Toxicity levels of the article comments were assessed using an original, multi-regression-based metric called the “extremism score. ” Mean extremism scores among top commenters revealed (1) overlapping peaks of extreme comments over time and (2) an increase in the prevalence of extreme comments as the number of these top commenters increased. Subsequent entity recognition analysis found that speciﬁc Democratic ﬁgures were referenced more often than their Republican counterparts in articles with one or more extreme comments, while general references to Republicans increased across the same subset of articles compared to Democrats.
MoLGNN: Self-Supervised Motif Learning Graph Neural Network for Drug Discovery

AI-facilitated drug design has become a popular ﬁeld that has the potential to accelerate drug discovery dramatically. Generally speaking, training a generalized deep learning model needs a large amount of correctly labeled data. However, since it is usually much harder to label chemicals than images or natural languages, lack of high-quality training samples is often a critical barrier in AI-based drug screening. In this work, we have developed a self-supervised Motif Learning Graph Neural Network (MoLGNN) that can signiﬁcantly improve the performance of computational drug screening by exploiting unlabeled chemicals to pretrain the model. MoLGNN conducts self-learning by 1), utilizing the node features and network motifs of a graph as self-generated labels and 2), reconstructing edges using a Graph Isomorphism Network Variational Auto-Encoder (GINVAE). These two strategies are combined in a multi-task learning framework. Our experiment re-sults show MoLGNN achieves state-of-the-art performance in multiple benchmark datasets, and is robust when the number of labeled data is small. Furthermore, we have applied MoLGNN to screen drugs for JAK1/2/3, which are novel drug targets for