Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence and Risk Factors of Chronic Obstructive Pulmonary Disease Among Users of Primary Health Care Facilities in Morocco

Background Chronic obstructive pulmonary disease (COPD) is a major public health problem. In Morocco, few studies have focused on COPD in primary health care facilities, whose main mission is prevention. The aim of our work is thus to assess the prevalence of COPD and to study the factors associated with this silent disease among users of health care facilities in Morocco. Methods This is a cross-sectional observational study of participants aged 40 and over. Data were collected by questionnaire. Pulmonary function testing was conducted using a spirometer before and after administration of a bronchodilator. COPD was defined as fixed ratio of the post‐bronchodilator forced expiratory volume in 1 second / forced vital capacity less than 0.7. Logistic regression models were applied to define factors associated with COPD. Results From 550 participants aged 40 and over, we selected only 477 patients with exploitable spirometry results for inclusion in the final analysis. The mean age of participants was 54.91±11.92 years, and the female/male ratio was 1.59. The prevalence of COPD was 6.7% (95% CI; 4.6 to 9.3%), and was higher in men than in women (11.4% vs 3.8%, p=0.002). The prevalence of COPD increased significantly with age, from 3.3% in those aged 40 to 49 to 16.9% in those aged 70 and over (p=0.001). Current smokers had a higher prevalence of COPD than former and never smokers. Age, smoking, asthma diagnosis and childhood hospitalization for lung disease were risk factors associated with the development of COPD. Only 6.25% of participants identified as having COPD had previously been diagnosed with COPD. Conclusion COPD remains largely under-diagnosed among primary care consultants in Morocco. Efforts for early detection and promotion of prevention of the main risk factors need to be intensified in order to reduce the burden of this silent pathology on a national scale.
Deep Optimal Isolation Forest with Genetic Algorithm for Anomaly Detection

Anomaly detection is one of the crucial research topics in artificial intelligence, encompassing various fields such as health monitoring, network intrusion detection, and fraud detection in financial transactions. Deep anomaly detection (DAD) methods are considered as the effective approaches for addressing complex anomaly detection problems. Among them, the deep isolation forest methods have gained rapid development recently due to their simplicity in parameter turning and efficiency in model training. The existing deep isolation forest approaches are all based on representation learning, while OptiForest theoretically proves the crucial role of the tree structure in isolation forest based methods. In this paper, we analyse the search space of isolation trees under specific data instances and address the challenges in finding optimal isolation forest. Based on the theoretical underpinning and genetic algorithm, we design a deep model DOIForest with two mutation schemes and solution selection, which learns the optimal isolation forest and optimises the parameters in data partitioning. Extensive experiments on both synthetic dataset and a series of real-world datasets demonstrate that our approach can achieve better detection accuracy and robustness than the state-of-the-arts.
Nerve Regeneration and Gait Function Recovery with Implantation of Glucose/Mannose Conduits Using a Rat Model: Efficacy of Glucose/Mannose as a New Neurological Guidance Material

Therapy with clinical nerve guidance conduits often causes functional incompleteness in patients. With the aim of better therapeutic efficacy, nerve regeneration and gait function were investigated in this study using a novel nerve guidance conduit consisting of glucose/mannose. The glucose/mannose nerve guidance conduits were prepared by filling the conduits with the glucose/mannose aqueous solutions for different kinematic viscosity, which were applied to sciatic nerve defects (6 mm gap) in a rat model. The nerve regeneration effect and the gait function recovery with the fabricated nerve guidance conduits were examined. From the results of the XRD measurement, the glucose/mannose conduits were identified as crystal structures of cellulose type II. Young’s modulus and the maximum tensile strength of the crystalline glucose/mannose conduits demonstrated good strength and softness for the human nerve. Above 4 weeks postoperative, macroscopic observation revealed that the nerve was regenerated in the defective area. In various staining results of the nerve tissue removed at 4 weeks postoperative, myelinated nerves contributing to gait function could not be observed in the proximal and distal sites to the central nerve. At 8–12 weeks postoperative, myelinated nerves were found at the proximal and distal sites in hematoxylin/eosin staining. Glia cells were confirmed by phosphotungstic acid–hematoxylin staining. Continuous nerve fibers were observed clearly in the sections of the regenerated nerves towards the longitudinal direction at 12 weeks postoperative. The angle between the metatarsophalangeal joint and the ground plane was approximately 93° in intact rats. At 4 weeks postoperative, walking was not possible, but at 8 weeks postoperative, the rats were able to walk, with an angle of 53°. At 12 weeks postoperative, the angle increased further, reaching 65°, confirming that the rats were able to walk more quickly than at 8 weeks postoperative. These results demonstrated that gait function in rats treated with glucose/mannose nerve guidance conduits was rapidly recovered after 8 weeks postoperative. The glucose/mannose nerve guidance conduit could be applied as a new promising candidate material for peripheral nerve regeneration.
Niosomes: Composition, Formulation Techniques, and Recent Progress as Delivery Systems in Cancer Therapy

Niosomes are vesicular nanocarriers, biodegradable, relatively non-toxic, stable, and inexpensive, that provide an alternative for lipid-solid carriers (e.g., liposomes). Niosomes may resolve issues related to the instability, fast degradation, bioavailability, and insolubility of different drugs or natural compounds. Niosomes can be very efficient potential systems for the specific delivery of anticancer, antioxidant, anti-inflammatory, antimicrobial, and antibacterial molecules. This review aims to present an overview of their composition, the most common formulation techniques, as well as of recent utilizations as delivery systems in cancer therapy.
Rolling shutter speckle plethysmography for quantitative cardiovascular monitoring

We propose a new speckle-based plethysmography technique, termed rolling shutter speckle plethysmography (RSSPG), which can quantitatively measure the velocity and volume fluctuations of blood flow during the cardiac cycle. Our technique is based on the rolling shutter speckle imaging, where the short row-by-row time differences in the rolling shutter image sensors are used to measure the temporal decorrelation behavior of vertically elongated speckles from a single image capture. Temporal analysis of the speckle field provides rich information regarding the dynamics of the scattering media, such as both the dynamic scattering fraction and the speckle decorrelation time. Using a sequence of images, RSSPG can monitor fluctuations in the blood flow dynamics while separating velocity and volume changes in blood vessels and obtaining high-quality plethysmography waveforms compared to regular photoplethysmography. We demonstrate the quantitative RSSPG based on accurate fitting of the speckle dynamics model, as well as the qualitative RSSPG based on simple row-by-row correlation (RIC) calculation for fast and robust analysis. Based on exploratory in vivo experiment, we show that RSSPG can reliably measure pulsatile waveforms and heart rate variations in various conditions, potentially providing physiologically relevant information for cardiovascular monitoring.
An Improved Dark-Object Subtraction Technique for Atmospheric Scattering Correction of Multispectral Data*

Digital analysis of remotely sensed data has become an important component of many earth-science studies. These data are often processed through a set of preprocessing or "clean-up" routines that includes a correction for atmospheric scattering, often called haze. Various methods to correct or remove the additive haze component have been developed, including tho "- ",~ely used dark-object subtraction technique. A problem with most o1 these methods is that the haze values for each spectral band are selected independently. This can create problems because atmospheric scattering is highly wavelength-dependent in the visible part of the electromagnetic spectrum and the scattering values are correlated with each other. Therefore, multispectral data such as from the Landsat Thematic Mapper and Multispectral Scanner must be corrected with haze values that are spectral band dependent. An improved dark-object subtraction technique is demonstrated that allows the user to select a relative atmospheric scattering model to predict the haze values for all the spectral bands from a selected starting band haze value. The improved method normalizes the predicted haze values for the different gain and offset parameters used by the imaging system. Examples of haze value dif|erenees between the old and improved methods for Thematic Mapper Bands 1, 2, 3, 4, 5, and 7 are 40.0, 13.0, 12.0, 8.0, 5.0, and 2.0 vs. 40.0, 13.2, 8.9, 4.9, 16.7, and 3.3, respectively, using a relative scattering model of a clear atmosphere. In one Landsat multispectral scanner image the haze value differences for Bands 4, 5, 6, and 7 were 30.0, 50.0, 50.0, and 40.0 for the old method vs. 30.0, 34.4, 43.6, and 6.4 for the new method using a relative scattering model o£ a hazy atmosphere.
Determinants of poor glycemic control among type 2 diabetes in Ethiopia: a systematic review and meta-analysis

Introduction Prior primary studies have examined the prevalence and factors associated with glycaemic control among patients with type 2 diabetes mellitus, but studies with evidence-based synthesis of the primary data remained unknown. Hence, we aimed to determine the prevalence of poor glycemic control and identify determinants of poor glycemic control in patients with type 2 diabetes in Ethiopia. Methods We performed searches in the online databases of PubMed, Google Scholar, Scopus, Science Direct, and the Cochrane Library. Microsoft Excel was used to extract data, and STATA statistical software (v. 16) was used for analysis. Publication bias was explored by forest plots, Begg’s rank test, and Egger’s regression test. To check for heterogeneity, I2 was computed. Subgroup analysis was conducted based on region and publication year. In addition, the pooled odds ratio for associated factors was calculated. Results Out of 1,045 studies assessed, 23 studies were included fulfilling our inclusion criteria. In all, 6,643 individuals were enrolled in the study. It was estimated that 61.11% of type 2 diabetes patients had poor glycemic control (95% CI, 57.14–65.19). The subgroup analysis by study region and publication year revealed that the highest prevalence was observed in the Addis Ababa region (68.57%) and studies published before 2019 (61.76%), respectively. Poor glycemic control was associated with older age > 50 years (AOR = 2.12; 95% CI: 1.27–2.97), not attending formal education (AOR = 3.60; 95% CI: 2.75, 4.46), having diabetes for longer duration (10 years; AOR = 2.57; 95% CI: 1.65–3.49), having comorbidity (AOR = 2.43; 95% CI: 2.05–2.80), and low adherence to diabetes management (AOR = 3.67; 95% CI: 2.41–4.92). Conclusion Our findings indicate a high prevalence of poor glycemic control among people with type 2 diabetes in Ethiopia. Being older, not attending formal education, having a longer duration of diabetes, having comorbidity, and having low adherence to diabetes management were all associated. Therefore, we recommend health organizations implement measures to monitor and control patients’ blood glucose levels. Patient education and training of healthcare professionals could serve as a short-term strategy to achieve adequate glycemic control. Systematic review registration PROSPERO, identifier CRD42022349792, https://www.crd. york.ac. uk/prospero/display_record. php? ID=CRD42022349792.
Selective Negotiations for Scaling Stochastic Dynamic Games

This paper presents asocial agents for selective negotiations in stochastic dynamic games. Game-theoretic frameworks in the belief-space show promise in modeling complex interactions in scenarios such as surveillance, herding, and racing. Stochastic dynamic games can be solved as a continuous POMDP to find a local Nash Equilibrium solution of all agents using a game-theoretic belief-space variant of iLQG. However, the scalability of this method suffers due to the large dimensionality of beliefs which the iLQG must propagate, and fails to consider environmental features such as dynamic obstacles. We introduce asocial agents models, which follow fixed input trajectories in the planning horizon. Ego agents can selectively toggle which agents it considers asocial, thereby reducing computational overhead. Simulations demonstrate that our approach to selective negotiations can help scale stochastic dynamic games with faster computation times and minimal performance decline.
Electromagnetic Fields in Full-Parameter Uniaxial Anisotropic Planar-Stratified Media

In this article, we present a derivation for analytical expressions of the electromagnetic (EM) fields radiated by triaxial magnetic/electric point sources in planar-stratified media. The permittivity, permeability, and conductivity of each layer may exhibit uniaxial anisotropy. First, a hybrid potential method is adopted to solve the Maxwell’s equations in homogeneous anisotropic medium. Based on those hybrid potentials, the explicit expressions of field components are presented in spatial domain. Those algebraic solutions will be beneficial to character analysis and numerical computation. Second, the spectral-domain EM field in planar-stratified media is divided into the upgoing and downgoing waves. We solve them using the generalized reflection/transmission method, where the generalized transmission plays an important role in the recurrence relation. The discrete complex image method (DCIM) is implemented to the numerical integral of the field from spectral domain to spatial domain. The proposed method allows forward modeling and data processing in EM logging. Finally, a rapid apparent conductivity extraction method is presented for triaxial induction logging.
Distributed Energy-Efficient Multi-UAV Navigation for Long-Term Communication Coverage by Deep Reinforcement Learning

In this paper, we aim to design a fully-distributed control solution to navigate a group of unmanned aerial vehicles (UAVs), as the mobile Base Stations (BSs) to fly around a target area, to provide long-term communication coverage for the ground mobile users. Different from existing solutions that mainly solve the problem from optimization perspectives, we proposed a decentralized deep reinforcement learning (DRL) based framework to control each UAV in a distributed manner. Our goal is to maximize the temporal average coverage score achieved by all UAVs in a task, maximize the geographical fairness of all considered point-of-interests (PoIs), and minimize the total energy consumptions, while keeping them connected and not flying out of the area border. We designed the state, observation, action space, and reward in an explicit manner, and model each UAV by deep neural networks (DNNs). We conducted extensive simulations and found the appropriate set of hyperparameters, including experience replay buffer size, number of neural units for two fully-connected hidden layers of actor, critic, and their target networks, and the discount factor for remembering the future reward. The simulation results justified the superiority of the proposed model over the state-of-the-art DRL-EC<inline-formula><tex-math notation="LaTeX">$^3$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mn>3</mml:mn></mml:msup></mml:math><inline-graphic xlink:href="tang-ieq1-2908171.gif"/></alternatives></inline-formula> approach based on deep deterministic policy gradient (DDPG), and three other baselines.
A Comprehensive Comparison of Different Wafer/Channel Orientations for Ultrascaled Nanosheet FETs

In this article, we evaluate various crystal orientation configurations for silicon ultrascaled nanosheet FETs (NSFETs) to explore the optimum combination of wafer surface and channel orientations. The increasingly prominent physical phenomena, including quantum confinement and quasi-ballistic transport, are captured physically by advanced simulation methodology. The carrier density profile and transport-related parameters exhibit a strong dependence on the crystallographic orientations of the channel and the wafer directions. The quantum confinement effects are least pronounced in the n-type NSFETs with a (100) surface, and the p-type NSFETs with a (110) surface. The <inline-formula> <tex-math notation="LaTeX">$\langle {100} \rangle $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\langle {111} \rangle $ </tex-math></inline-formula> channel orientations demonstrate the largest ballistic injection velocity for electrons and holes, respectively. Uniaxial stress technology, as an efficient performance booster, may further improve the transport properties, but the enhancement may saturate at high stress level. In the ballistic limit, we predict that the homo-oriented CMOS inverter of <inline-formula> <tex-math notation="LaTeX">${(}{110}{)}/\langle {111} \rangle $ </tex-math></inline-formula> configuration has a more balanced N/P current, and the hetero-oriented CMOS inverter, comprising a <inline-formula> <tex-math notation="LaTeX">$5\,\,{\times }\,\,10$ </tex-math></inline-formula> nm n-type NSFET of <inline-formula> <tex-math notation="LaTeX">${(}{100}{)}/\langle {100} \rangle $ </tex-math></inline-formula> and a <inline-formula> <tex-math notation="LaTeX">$5\,\,{\times }\,\,10$ </tex-math></inline-formula> nm p-type NSFET of <inline-formula> <tex-math notation="LaTeX">${(}{110}{)}/\langle {111} \rangle $ </tex-math></inline-formula>, will yield a speed enhancement exceeding 20% when compared with the prevailing industry standard of the <inline-formula> <tex-math notation="LaTeX">${(}{100}{)}/\langle {110} \rangle $ </tex-math></inline-formula> configuration.
Outcomes of external and endonasal dacryocystorhinostomy according to a modified Lacrimal Symptom Questionnaire (Lac-Q)

Background: Nasolacrimal duct obstruction is usually treated using endoscopic or external dacryocystorhinostomy (DCR). The anatomic outcomes of both the endoscopic and external approaches are considered excellent. However, anatomic success does not translate into patient satisfaction. The current study assessed pre- and postoperative lacrimal problems using the symptom-based Lacrimal Symptom Questionnaire (Lac-Q) and investigated patient satisfaction depending on the choice of surgical technique. Methods: A total of 112 eligible patients with lacrimal problems treated using external or endonasal DCR at the ophthalmology and ear, nose, and throat clinics at Skane University Hospital, Scania, Sweden, over a four-year period, were enrolled in this retrospective study. Patients were considered eligible if they experienced preoperative epiphora and had lacrimal duct stenosis. They were offered treatment using either external or endonasal DCR and were allowed to freely choose the technique. Exclusion criteria consisted of previous ipsilateral DCR, congenital NLDO, age < 18 years, presence of cancer, previous orbital trauma, or noncompliance with postoperative follow-up. After surgery, the patients were sent the Lac-Q to evaluate their lacrimal symptoms pre- and postoperatively. Complementary questions were added pertaining to the operative scar and the patients’ overall satisfaction with the operation. Results: In total, 67 (60%) patients with ages ranging from 18 to 88 years completed the questionnaire, 33 (49%) of whom underwent external DCR and 34 (51%) endonasal DCR. Of the 67 respondents, 51 (76%) were women and 16 (24%) were men. Patients scored preoperative lacrimal problems highly on the Lac-Q, reporting both symptomatic and social problems due to epiphora. Following surgery, the group that underwent external DCR remained home from work for 2 – 14 days (median, 3.5 days). However, 17 (52%) were retired. After the endonasal DCR, the patients remained home for 0 – 7 days (median, 2 days). Most patients were satisfied after DCR surgery, with both techniques significantly improving total, lacrimal symptom, and social impact scores (all P < 0.001). No differences in postoperative satisfaction were observed between the external DCR and endonasal DCR groups (P > 0.05). A small number of patients expressed scar-related concerns after external DCR. Conclusions: The patients perceived lacrimal problems as a significant symptomatic and social burden. Postoperative satisfaction and symptom relief were good regardless of the surgical approach. Further prospective studies assessing patient satisfaction and its correlation with anatomical and functional success rates after external and endonasal DCR could provide robust, practical, real-world implications.
Elaeagnus umbellata Fruit Extract Protects Skin from Ultraviolet-Mediated Photoaging in Hairless Mice

Photoaging refers to the accumulation of skin damage which includes wrinkle formation, loss of elasticity, and epidermal thickening due to repeated ultraviolet (UV) irradiation. The present study investigated the protective effects of Elaeagnus umbellata fruit extract (Elaea) on UV-mediated photoaged skin of SKH1 hairless mice and compared the effects of Elaea with ascorbic acid. Although there was no difference in body weight between groups during experimental period, oral administration of 50–200 mg/kg Elaea once daily for 15 weeks significantly prevented an increase in skin weight, epithelial thickening of epidermis, and apoptosis caused by UV irradiation. Skin replica and histopathological analyses revealed that Elaea dose-dependently decreased wrinkle and microfold formation. In addition, Elaea administration restored UV-mediated reduction in type I collagen and hyaluronan through the inhibition of matrix metalloproteinases and p38 mitogen-activated protein kinase expression. Moreover, Elaea suppressed UV-dependent increases in superoxide anion production, fatty acid oxidation, and protein nitration by up-regulating antioxidant system. Furthermore, Elaea alleviated infiltration of inflammatory cells in UV-irradiated skin. The preventive effects of 100 mg/kg Elaea administration against UV-induced photoaging were similar to those by 100 mg/kg ascorbic acid. Collectively, the present study suggests that the E. umbellata fruit is a promising edible candidate to prevent skin photoaging.
Holistic approach to AI-assisted student development cycles in higher education using the example of the West Saxon University Zwickau

AI has become a real gamechanger in many areas of daily life. Tools such as ChatGPT are also generating rapidly growing interest in AI technologies. At the same time, AI is already being used today in various forms in a wide range of industries, as well as the education sector.This paper starts with a short introduction to the topic of AI in general, and then turns to the possible applications of AI in the field of higher education. Here, examples of use in AI are first presented. This is followed by a presentation of West Saxon University Zwickau and its holistic concept for the use of AI. The paper ends with the presentation of different possibilities for digitization and the use of AI at Zwickau University. In particular, the possibility of using conversational AI to increase the bond between prospective students and the university is discussed.