Miracle-dz/UniFAR-FTUs huggingface dataset:
An update on mobile applications collecting data among subjects with or at risk of Alzheimer's disease

Smart mobile phone use is increasing worldwide, as is the ability of mobile devices to monitor daily routines, behaviors, and even cognitive changes. There is a growing opportunity for users to share the data collected with their medical providers which may serve as an accessible cognitive impairment screening tool. Data logged or tracked in an app and analyzed with machine learning (ML) could identify subtle cognitive changes and lead to more timely diagnoses on an individual and population level. This review comments on existing evidence of mobile device applications designed to passively and/or actively collect data on cognition relevant for early detection and diagnosis of Alzheimer's disease (AD). The PubMed database was searched to identify existing literature on apps related to dementia and cognitive health data collection. The initial search deadline was December 1, 2022. Additional literature published in 2023 was accounted for with a follow-up search prior to publication. Criteria for inclusion was limited to articles in English which referenced data collection via mobile app from adults 50+ concerned, at risk of, or diagnosed with AD dementia. We identified relevant literature (n = 25) which fit our criteria. Many publications were excluded because they focused on apps which fail to collect data and simply provide users with cognitive health information. We found that although data collecting cognition-related apps have existed for years, the use of these apps as screening tools remains underdeveloped; however, it may serve as proof of concept and feasibility as there is much supporting evidence on their predictive utility. Concerns about the validity of mobile apps for cognitive screening and privacy issues remain prevalent. Mobile applications and use of ML is widely considered a financially and socially viable method of compiling symptomatic data but currently this large potential dataset, screening tool, and research resource is still largely untapped.
Innovative biomaterials for the treatment of periodontal disease

Periodontitis is a multifactorial disease that involves the destruction of hard and soft tissues surrounding the tooth. Routine periodontal treatment includes mechanical debridement (surgical and non-surgical) and the systemic administration of antibiotics. In contrast, severe and chronic periodontitis involves aggressive tissue destruction and bone resorption, and the damage is usually irreversible. In these severe cases, bone grafts, the delivery of growth hormones, and guided tissue regeneration can all be used to stimulate periodontal regeneration. However, these approaches do not result in consistent and predictable treatment outcomes. As a result, advanced biomaterials have evolved as an adjunctive approach to improve clinical performance. These novel biomaterials are designed to either prolong the release of antibacterial agents or osteogenic molecules, or to act as immunomodulators to promote healing. The first half of this review briefly summarizes the key immune cells and their underlying cellular pathways implicated in periodontitis. Advanced biomaterials designed to promote periodontal regeneration will be highlighted in the second half. Finally, the limitations of the current experimental design and the challenges of translational science will be discussed.
Computed tomography of the spleen in chickens

The avian spleen is an important immune organ in birds and its size can be used as an index of immune system responses in different conditions. Based on the lack of knowledge in computed tomography of the spleen in chickens, the present study was conducted to assess the inter-and intraobserver reliability in the measurement of the spleen dimensions and attenuation, as well as the feasibility of utilization of these measurements as a predictor of different diseases. For these purposes, the spleens of 47 chickens were included in the study. Two observers measured the dimensions and attenuations of the spleen, which were finally compared with the clinical diagnosis. The results showed an excellent interobserver reliability in the length, width, and height of the spleen (ICC: 0.944, 0.906, and 0.938, retrospectively), and a good interobserver reliability was observed during the evaluation of the average Hounsfield units of the spleen (ICC: 0.818). The intraobserver reliability was excellent in all the measurements (ICC > 0.940). Additionally, no statistical differences were detected in the spleen size and attenuation between the normal and diseased groups. Based on the present results, the computed tomographic measurements of the spleen could not predict the clinical diseases of the chickens; however, the low rates of the inter- and intraobserver variability suggest the reliable utilization of these computed tomographic measurements in routine clinical application and follow-up examinations.
Dismissal informs the priorities of endometriosis patients in New Zealand

Introduction Endometriosis is a common condition with average delays to diagnosis in New Zealand of almost 9 years. Methods In total, 50 endometriosis patients participated in anonymous, asynchronous, online group discussions about their priorities, and their experiences with the development of symptoms, seeking a diagnosis, and receiving appropriate treatment. Results Higher subsidy of care was the top change endometriosis patients wanted, followed by more research funding. When asked to choose whether research should be focused on improving diagnosis or improving treatment methods, the results were evenly split. Within this cohort, patients highlighted that they did not know the difference between normal menstrual discomfort and pathological endometriotic pain. If, upon seeking help, medical practitioners classified their symptoms as “normal,” these dismissals could instill doubt in patients, which made it more difficult for them to continue to seek a diagnosis and effective treatments. Patients who did not express dismissal had a significantly shorter delay from symptom onset to diagnosis of 4.6 ± 3.4 years vs. 9.0 ± 5.2 years. Conclusion Doubt is a frequent experience for endometriosis patients in New Zealand, which was reinforced by some medical practitioners who were dismissive of their pain and thus prolonged the patient's delay to diagnosis.
The relationship between self-efficacy and self-management in post stroke patients at Home Stroke Rehabilitation Malang

Background: Stroke is a neurological disorder characterized by blockage of blood vessels. The effects of stroke cause problems with motor, sensory and cognitive functions. These problems result in patients often complaining and feeling useless, so patients experience a decrease in self-efficacy. Low self-efficacy will cause a low level of self-acceptance and motivation that affects the patient's confidence in performing functional activities and self-management related to the healing process in stroke patients. Objective: This study aimed to analyze the relationship between self-efficacy and self-management in stroke patients. Methods: The research design used a cross-sectional study method conducted in December 2022 with a population of all stroke patients at Home Stroke Rehabilitation Malang who met the criteria to become participants in this study. Measurement of self-efficacy using The Stroke Self Efficacy Quetionnaire (SSEQ) and self-management using The Southampton Stroke Self Management Quetionnaire (SSSMQ). Rank Spearman was used to determining the relationship between the two variables showed that out of 49 respondents, there was a relationship between self-efficacy and self-management using the Rank Spearman test. Results: The study’s result (p = 0.000, r = 0.949) shows a very strong correlation. It can be concluded that there is a very strong relationship between self-efficacy and self-management in stroke patients because high confidence is very influential on the actions or attitudes of patients so that patients can move and prevent recurrent strokes and carry out rehabilitation programs properly. Conclusion: The higher the self-efficacy, the higher the self-management in post-stroke patients and vice versa. These two crucial components will affect the rehabilitation phase of post-stroke patients.
PERFORMANCE COMPARISON OF NEURAL NETWORKS IN GRAVITATIONAL LENSING DETECTION

A gravitational lens is a distribution of matter, such as dark matter halos, galaxies, or quasars, between a distant light source and an observer that can bend the light from the source as the light travels toward the observer. Nowadays, it is slightly complicated to identify gravitational lenses without powerful computing devices and groups of scientists working together. In addition, future surveys will have orders of magnitude more data and more lenses to find. With up-to-date algorithms such as neural networks, detecting and classifying them for a single human being will be possible. The neural networks described in this paper make the first steps in that direction. The primary purpose of this work was to develop three different neural networks and determine which one could detect gravitational lensing more quickly and precisely. For training, testing, and validation we used a dataset of 2000 images. Half of these images were downloaded from Bologna Lens Factory, a database of simulated gravitational lenses based on galaxies lensed by galaxies (i.e., no clusters and no quasars). We simulated the second half of the images using Python-based code to simulate mock strong lensed galaxies. We used Python-based code to mock strong lensing with different source parameters. Next, we built three types of artificial neural networks and compared their efficiency. Firstly, we developed a fully convolutional neural network (CNN) and a fully connected neural network (FCNN). The third neural network was a combination of these two approaches. In this algorithm, the FCNN layer replaced the last layer of CNN. Next, we compared the learning rates of these algorithms and applied all neural networks to validation images. As a result of the study, we determined which of the developed neural networks fit better for searching gravitational lenses.
Exploring Risk Management Issues in the Technological Sector: The Effect of the Use of Derivatives Hedging on Technology Firms’ Value

Entrepreneurship is synonymous with “bearing risk”. In a technological context, the risks are much higher. The implementation of risk management instruments is therefore essential for entrepreneurs in the technological industry. However, how the use of derivatives hedging impacts the market value of technology firms remains unaddressed. To expand upon entrepreneurship literature in terms of risk management, we develop a new multidisciplinary theory that integrates risk management theories with entrepreneurship. By applying various methodologies (fixed-effect, pooled OLS, and system GMM) to our sample of 81 firms — listed between 2007-2020 in the Stoxx Europe 600 and operating in the Telecommunication and Information Technology industries — we reveal that the use of this risk management instrument does not impact upon technology firm value, measured as Tobin’s Q. These results offer entrepreneurs a better understanding of the uselessness of using derivatives hedging to increase technology firm value in the technological industry.
ON QUASI-EQUATIONS IN LOCALLY PRESENTABLE CATEGORIES II: A LOGIC

Les quasi-equations, donnees par des paires paralleles de morphismes finitaires, representent des proprietes des objets: un objet satisfait la propriete si son foncteur hom contravariant fusionne les morphismes de la paire. Recemment Adamek et Hebert ont caracterise les sous-categories des categories localement de presentation finie specifiees par des quasi-equations. Nous presentons ici une logique de quasi-equations proche de la logique classique equationnelle de Birkhoff. Nous prouvons qu'elle est consistante et complete dans toute categorie localement presentation finie avec relations d'equivalence effectives.
Radio Frequency EMF Measurements and Exposure Assessment from 5G Outdoor Base Stations

This paper presents preliminary results of radio-frequency electromagnetic field (RF-EMF) measurements in outdoor environments. The purpose is to measure and evaluate the exposure levels of general public from fifth generation (5G) base stations, and compare them with the enforced national and international guidelines. Frequency selective measurements have been performed in diverse urban and rural locations between 27 MHz and 6 GHz, comparing the 5G emissions with other cellular or broadcast exposure levels. The electric field, explicitly from 5G emissions, varies in the range of 0.14-0.57 V/m, and 0.19-4.10 V/m, in urban and rural locations, respectively. The maximum 5G emission, in terms of power density (44.6 mW/m2), is measured in rural areas and corresponds to about 0.4% of the legislated limits in the European Union. The inherent structure of the 5G networks corroborate the observed difference in exposure levels between urban and rural areas. The maximum recorded Total Exposure Ratio (TER) is about (27.71±12.06)∙10-3, being consistent with the enforced limits. Finally, 5G emissions are found to contribute about 12% to the total exposure levels.
Magnetics Analysis and Optimization Techniques for a 2 MHz GaN-based Active-Clamped Isolated SEPIC Converter

This paper presents the magnetics optimization of the 2 MHz, 12 V, 600 mA, GaN-based Active-Clamped Isolated SEPIC Converter (ACISC) discussed in [1], which supports full Zero- Voltage Switching (ZVS) operation throughout the 9 V-18 V automotive range and provides isolation and power interface between the 12V battery and the low-power subnet. Since the converter leverages the high switching frequency enabled by GaN devices, it is crucial to create ad-hoc PCBs for the involved magnetics, realized here as a planar structure, to reduce both the significant winding losses and the inter-winding capacitance which is a critical parasitic capacitance of the converter in the common mode noise perspective. Both the theoretical model specifically developed for full ZVS resonant Discontinuous Con-duction Mode (DCM) operation, as well as the design and step- by -step optimization of the magnetics, are discussed. The analysis, which is verified through simulations and experimental measurements taken on a 7.2 W GaN-based prototype, reveals a peak efficiency of 89.2 % for the optimized ACISC operating in nominal conditions, approximately 2 % higher than the one illustrated in [1].
Investigation for Unsteady Cavitation and Re-entrant Jet on a Foil Section

The mechanism of cloud cavitation generation from a sheet cavity on a foil section has been studied by several researchers. It has been revealed that re-entrant jet cuts the leading edge of sheet cavity and breaks the clear vapour structure into small bubble clusters as cloud cavity. However, the detailed picture of the sheet cavity cut-off phenomenon is still missing. In this study, we carried out experimental observations of sheet-cloud cavity on a NACA0015 foil section using high speed video and hot wires mounted on a foil surface in order to clarify quantitative characteristics of re-entrant jet and its role in sheet cavity cut-off phenomenon.The results of experiments have shown that there were several patterns in the sheet cavity cut-off phenomenon, and that the thickness of re-entrant jet is an important factor.We have also carried out numerical simulations for the same test case. The numerical simulation was performed using a commercial CFD code STAR-CD and the Bubble Two Phase Flow cavitation model implemented in the code. The simulation reproduced unsteady shedding of cloud cavity, although some differences were found in the detailed features of the flow.
Multimodal analysis of glide-symmetric dielectric/magnetic structures

In this contribution, we propose the use of the multimodal transfer matrix approach to investigate two-dimensional dielectric and magnetic periodic structures that possess glide symmetries. This method allows for the calculation of the attenuation constant in bandgaps, leaky structures, and material losses. In addition, this method enables a fundamental understanding of the operation of periodic structures. The method is also used to explain the differential response produced by dielectric/magnetic glide symmetries.
Tropospheric Scintillation and Simultaneous Rain Attenuation at 19.7 GHz and 39.4 GHz for Tito Scalo and Spino d’Adda

Beacon power levels measured in 2015 in the framework of the Alphasat Aldo Paraboni propagation experiment at the two receiving stations in Tito Scalo and Spino d’Adda, for beacon frequencies of 19.7 GHz and 39.4 GHz, are calibrated to extract total attenuation timeseries. These timeseries are then used to perform an analysis on scintillations during rain events. The analysis shows that there is some deviation (23% and 38% at Ka band and Q band, respectively) in the slope of the power law fitted to the data, with respect to the slope of the power law provided in the thin layer model. Furthermore, it was found that the scintillation intensity ratio at Spino d’Adda and Tito Scalo are 22.2% and 21.1% smaller, respectively, than the theoretical one.
Backward bifurcation for some general recovery functions

We consider an epidemic model for the dynamics of an infectious disease that incorporates a nonlinear function h(I), which describes the recovery rate of infectious individuals. We show that in spite of the simple structure of the model, a backward bifurcation may occur if the recovery rate h(I) decreases and the velocity of the recovery rate dh(0)dI is below a threshold value in the beginning of the epidemic. These functions would represent a weak reaction or slow treatment measures because, for instance, of limited allocation of resources o sparsely distributed populations. This includes commonly used functionals, as the monotone saturating Michaelis–Menten, and non monotone recovery rates, used to represent a recovery rate limited by the increasing number of infected individuals. We are especially interested in control policies that can lead to recovery functions that avoid backward bifurcation. Copyright © 2016 John Wiley & Sons, Ltd.
A Physically Realizable Metasurface Incorporating Auxiliary Surface Waves for Power Redistribution

The allowable electromagnetic wave transformations supported by lossless and passive metasurfaces are typically constrained by the enforcement of local power conservation (LPC) at each of the metasurface unit-cells. Incorporating auxiliary surface waves tangential to the metasurface in the design procedure provides a means for power redistribution along the metasurface, thus permitting a wider variety of possible field transformations. This paper utilizes a previously developed integral-equation-based solver to incorporate such auxiliary surface waves into the design of omega-bianisotropic Huygens' metasurfaces. Subsequently, a physically realizable metasurface that utilizes such auxiliary surfaces waves is designed and simulated to verify the performance of this solver. The proposed design includes a three-layer copper trace design supported by practical dielectric substrates and bondply.
A Design Feasibility Investigation for a Pulmonary ePTFE Transcatheter Pediatric Heart Valve

The most replaced valve in the congenital heart defects population is the pulmonary valve. Current treatments require multiple invasive, open-heart surgeries to replace the pulmonary valve as the patient grows. Minimally-invasive procedures, such as transcatheter pulmonary valve replacement, circumvent open heart surgery, which benefits patients and physicians. ePTFE valves have gained prominence recently because they allow cardiothoracic pediatric surgeons to tailor the valve size to the patient. Clinical studies point to the high patency of ePTFE valves. Currently, there are no FDA-approved transcatheter valves made with ePTFE. The purpose of this paper is to offer a preliminary design feasibility investigation of developing a transcatheter ePTFE pulmonary valve. We used an existing FDA-approved Medtronic Ensemble II delivery system to test and evaluate the feasibility of fitting an ePTFE pediatric valve to this existing deployment system. The prototyping and testing goals were: (1) to evaluate stent expansion, (2) to explore anchoring mechanisms, (3) to collapse the stent with the ePTFE conduit down to a size that would fit into a catheter, and (4) to expand and deploy the ePTFE stent-conduit pulmonary valve. Testing revealed that ePTFE conduits with wall thicknesses of 1 mm and 0.5 mm did not collapse to a small enough diameter to fit in the sheath of the Medtronic Ensemble II delivery system. However, expansion of anchored stents showed that valves upheld circular cross-sections when deployed. For the valve to be widely distributed, the product must follow FDA and ISO 5840 standards to ensure appropriate performance. There remains considerable future work to deliver a well-functioning ePTFE transcatheter pulmonary heart valve solution for pediatric patients.
CT-PET Based Image Fusion Algorithm for Medical Applications

Medical images are very important in the clinical environment for detection, diagnosis, staging, response assessment, and survival rate prediction. There are many invasive and non-invasive ways to obtain medical images. Each single image acquired will results different image modalities, such as CT, MRI, PET, and SPET, considered in the different diagnosis information pertaining to either structural or functional issues. Image fusion is defined as the process to combine multiple input images of different modalities such as CT, PET, MRI, etc. into one image with the goal of creating single image, that has more description and detailing than the one provided by any of the single images. The fused CT and PET results, better detailing of structural and functional information in a single frame, which in turn helps the doctors for proper diagnosis. Here, we discussed and compared various medical image fusion technics, like Simple averaging, Principal Component Analysis PCA, Fast-Filtering, Guided Image Filter, and Discrete Wavelet Transforms (DWT), for the purpose to fuse CT and PET Images modalities. Finally analyzed the resultant fused image in terms of quantitative and qualitative metrics, for determine the performance of each algorithm. DWT is showing the promising results in terms of both qualitative and quantitative parameters, in terms of Q MI (Normalized Mutual Information)-0.697, QG (Gradient-based fusion performance) -0.529, and QM (Multi-scale Scheme) -0.365). were as simple averaging filter yields lowest and best Q NCIE (Nonlinear correlation information entropy) value- 0.808, and Guided Image Filter method results higher value of the Q CB (ChenBlum Metric) -0.620.
Beam-Steering Antenna Technologies for Space-Related Applications

The dramatic growth in the satellite terminal market up to a cumulative total of billions of US dollars by 2030 has been predicted by market analysts. Motivated by these predictions and based on customer feedback, established geostationary-orbit (GEO) satellite operators are investing in new high-throughput technologies. And new satellite operators have committed billions of dollars to low-earth-orbit (LEO) and medium-earth-orbit (MEO) satellite constellations. The beam-steering antenna is the most challenging and expensive subsystem in the ground segment of a modern satellite communication (SATCOM) terminal. New innovative beam- steering methods are required to meet the demands of the many new high-volume markets, such as low cost, low power consumption and aesthetically appealing shape.Both industry and academia have recognized these challenges and are developing and inventing innovative antenna beam-steering technologies that disrupt the way beam-steering antennas are designed. This paper outlines the challenges and briefly reviews some disruptive antenna beam- steering technologies for the next generation of SATCOM terminals.