Miracle-dz/UniFAR-FTUs huggingface dataset:
To evaluate the efficacy and safety profile of rosuvastatin, simvastatin and atorvastatin in newly diagnosed type 2 diabetic patients with dyslipidaemia

Dyslipidemia is one of the major risk factors for cardiovascular disease in diabetes mellitus. The lipid changes associated with diabetes mellitus are attributed to increased free fatty acid flux secondary to insulin resistance. Newly diagnosed 90 cases of patients of Type II Diabetes Mellitus well controlled on oral hypoglycemic drugs were randomly divided into 3 groups of 30 each. The mean difference of Triglycerides between baseline versus after 6 months was 65.04 mg/dl in Group A, 39.99 mg/dl in Group B and 37.04 mg/dl in Group C. The mean difference of HDL between baseline versus after 6 months was 10.04 mg/dl in Group A, 10.26 mg/dl in Group B and 9.13 mg/dl in Group C. The mean difference of LDL between baseline versus after 6 months was 79.4 mg/dl in Group A, 67.6 mg/dl in Group B and 33.82 mg/dl in Group C. The mean difference of VLDL between baseline versus after 6 months was 13.01 mg/dl in Group A, 7.58 mg/dl in Group B and 7.41 mg/dl in Group C.
Design and control of model based steering feel reference in an electric power assisted steering system

Electric power assisted steering (EPAS) system is a current state of the art technol-ogy for providing the steering torque support. The interaction of the steering system with the driver is principally governed by the EPAS control method. This paper proposes a control concept for designing the steering feel with a model based approach. The reference steering feel is defined in virtual dynamics for tracking. The layout of the reference model and the control architecture is discussed at first and then the decoupling of EPAS motor dynamics using a feedback control is shown. An example of how a change in steering feel reference (as desired by the driver) creates a change in steering feedback is further exhibited. The ultimate goal is to provide the driver with a tunable steering feel. For this, the verification is performed in simulation environment.
Policing, Democratic Participation, and the Reproduction of Asymmetric Citizenship

Can democratic participation reduce inequalities in citizenship produced by policing? We argue that citizen participation in policing produces a paradox, which we call asymmetric citizenship. For some citizens, expanding participation in policing expands citizenship by enhancing state responsiveness to demands. Yet citizen participation in policing often produces demands to repress marginalized groups, thereby contracting their citizenship rights. We theorize that formal spaces for citizen participation in policing produce asymmetric citizenship through three mechanisms: (1) defining some groups as “virtuous citizens” and labeling marginalized groups as “security threats,” (2) gatekeeping to amplify the voice of “virtuous citizens” while silencing marginalized groups, and (3) articulating demands for police repression of marginalized groups to protect the rights of “virtuous citizens. ” We illustrate the framework through a qualitative analysis of São Paulo’s Community Security Councils. Our analysis elucidates mechanisms through which democratic participation can reproduce, rather than ameliorate, inequality in policing.
Strategi Pemasaran Destinasi Wisata Yang di Pengaruhi Ekuitas Merek, Marketing, dan Motivasi Perjalanan (Studi pada Pantai Klayar Pacitan Jawa Timur)

Pantai Klayar merupakan salah satu wisata bahari yang menjadi pilihan wisatawan untuk dikunjungi di Kabupaten Pacitan Propinsi Jawa Timur. Pantai Klayar menjadi salah satu tempat pariwisata yang merupakan salah satu sektor penggerak perekonomian terutama bagi masyarakat lokal yang ada di sekitar pantai Klayar. Keberadaan kawasan wisata sendiri berpotensi mendatangkan nilai ekonomi sebagai penghasil jasa wisata. Keberadaan objek wisata Pantai Klayar berperan dalam menggerakkan perekonomian masyarakat lokal melalui pendirian unit-unit usaha dan penyerapan tenaga kerja. Tujuan dari penelitian ini adalah mengidentifikasi faktor-faktor yang memengaruhi niat berkunjung ke wisata pantai Klayar, mengetahui motivasi perjalan yang dilakukan ke pantai Klayar, serta menganalisis ekuitas merek dari pantai Klayar pada wisatawan yang berkunjung.
GPS-Denied Global Visual-Inertial Ground Vehicle State Estimation via Image Registration

Robotic systems such as unmanned ground vehicles (UGVs) often depend on GPS for navigation in outdoor environments. In GPS-denied environments, one approach to maintain a global state estimate is localizing based on preexisting georeferenced aerial or satellite imagery. However, this is inherently challenged by the significantly differing perspectives between the UGV and reference images. In this paper, we introduce a system for global localization of UGVs in remote, natural environments. We use multi-stereo visual inertial odometry (MSVIO) to provide local tracking. To overcome the challenge of differing viewpoints we use a probabilistic occupancy model to generate synthetic orthographic images from color images taken by the UGV. We then derive global information by scan matching local images to existing reference imagery and then use a pose graph to fuse the measurements to provide uninterrupted global positioning after loss of GPS signal. We show that our system generates visually accurate orthographic images of the environment, provides reliable global measurements, and maintains an accurate global state estimate in GPS-denied conditions.
A Review on Medicinal Uses, Nutritional Value, and Antimicrobial, Antioxidant, Anti-Inflammatory, Antidiabetic, and Anticancer Potential Related to Bioactive Compounds of J. regia

ABSTRACT Juglans regia is a medicinal plant widely used in traditional medicine and it. It is applied for healing a numerous ailment such us diabetes, digestive problems, hypertension, and gout diseases. This review aims to highlight the importance of Juglans regia as source of nutritional and bioactive compounds. Mechanisms of antimicrobial, antioxidant, anti-inflammatory, antidiabetic, and anticancer activities of Juglans regia leaves, fruit, septum kernels, flowers, bark, and husk have been discussed. Juglans regia fruits have an important nutritive value allowed by their richness in lipids and proteins. Medicinal properties of Juglans regia are certainly due to its bioactive compounds. Indeed, Juglans regia leaves, husks, flowers, bark, and roots contain several secondary metabolites including polyphenols, flavonoids, and glycosides. Pharmacological investigations reported by the literature demonstrated that Juglans regia exhibit different biological activities such as antioxidant, anti-inflammatory, anti-diabetic, antitumoral, antifungal, and antibacterial effects, in vitro, in vivo and in clinical trials. Mechanisms of bioactive compound action include ROS neutralization, proinflammatory mediators and enzyme inhibition, insulin levels increase, regulation of apoptosis, and cell cycle disruption. Biological properties were remarkably correlated with bioactive compounds containing in Juglans regia. Therefore, with its important nutritive values and its bioactive compounds, Juglans regia could be considered as a relevant functional food. GRAPHICAL ABSTRACT
Prevalence and Associated Factors of Gastric and Intestinal Ulcers in Companion and Exotic Animal Patients at a University Veterinary Teaching Hospital in Nigeria – A Preliminary Report

Gastric and intestinal ulceration with or without perforation poses a global health challenge in both human and animal populations. In animal species, it is often associated with patients presenting with hematemesis, abdominal pain, melena and anorexia, with erratic vomiting. The definitive diagnoses with imaging modalities are less feasible in poor resource settings due to lack of adequate facilities. This study investigated the prevalence and associated factors of gastric and intestinal ulcers in companion and exotic animal patients presented at the Veterinary Teaching Hospital, University of Ibadan, Nigeria, between 2009 and 2019 using hospital case records. Thirty-six cases of gastric and intestinal ulcer were recorded. They were mostly in canine (80.55%), few in exotic species [2 monkeys (5.55%), 1 lion (2.78%), 1 gazelle (2.78%), 1 dwarf crocodile (2.78%) and 1 fox (2.78%)] and one in an unspecified species (2.78%). Females (47.22%) and older animals (>1 year/69.45%) had higher occurrence than males (38.89%) and younger animals (<1 year/19.44%). All the patients were diagnosed with different pre-existing systemic conditions including: leptospirosis (19 cases/52.78%), chronic malnutrition (7 cases/19.44%), ehrlichiosis (2 cases/5.56%), trypanosomosis (2 cases/5.56%), babesiosis (2 cases/5.56%), hepatic tumor (1 case/2.78%), infectious canine hepatitis (1 case/2.78%), canine acute renal failure (1 case/2.78%) and granulomatous pneumonia (1 case/2.78%). There is therefore need to institute gastric and intestinal ulcer preventive and curative measures while treating predisposing primary disease conditions.
Satellite Image for Cloud and Snow Recognition Based on Lightweight Feature Map Attention Network

Cloud and snow recognition technology is of great significance in the field of meteorology, and is also widely used in remote sensing mapping, aerospace, and other fields. Based on the traditional method of manually labeling cloud-snow areas, a method of labeling cloud and snow areas using deep learning technology has been gradually developed to improve the accuracy and efficiency of recognition. In this paper, from the perspective of designing an efficient and lightweight network model, a cloud snow recognition model based on a lightweight feature map attention network (Lw-fmaNet) is proposed to ensure the performance and accuracy of the cloud snow recognition model. The model is improved based on the ResNet18 network with the premise of reducing the network parameters and improving the training efficiency. The main structure of the model includes a shallow feature extraction module, an intrinsic feature mapping module, and a lightweight adaptive attention mechanism. Overall, in the experiments conducted in this paper, the accuracy of the proposed cloud and snow recognition model reaches 95.02%, with a Kappa index of 93.34%. The proposed method achieves an average precision rate of 94.87%, an average recall rate of 94.79%, and an average F1-Score of 94.82% for four sample recognition classification tasks: no snow and no clouds, thin cloud, thick cloud, and snow cover. Meanwhile, our proposed network has only 5.617M parameters and takes only 2.276 s. Compared with multiple convolutional neural networks and lightweight networks commonly used for cloud and snow recognition, our proposed lightweight feature map attention network has a better performance when it comes to performing cloud and snow recognition tasks.
An Overview on Coinage Metal Nanocluster-Based Luminescent Biosensors via Etching Chemistry

The findings from the synthetic mechanism of metal nanoclusters yield the etching chemistry based on coinage metal nanoclusters. The utilization of such chemistry as a tool that can alter the optical properties of metal nanoclusters has inspired the development of a series of emerging luminescent biosensors. Compared with other sensors, the luminescent biosensors have the advantages of being more sensitive, saving time and saving cost. We reviewed topics on the luminescent sensors based on the etching of emissive coinage metal nanoclusters. The molecules possessing varied etching ability towards metal nanoclusters were categorized with discussions of corresponding etching mechanisms. The understanding of etching mechanisms favored the discussions of how to use etching methods to detecting biochemical molecules. The emerging luminescent biosensors via etching chemistry also provided challenges and new opportunities for analytical chemistry and sensors.
The Challenges of Technology Transfer in the Industry 4.0 Era Regarding Anthropotechnological Aspects: A Systematic Review

The fast pace of advances within the Industry 4.0 era has had a direct impact on the process of technology transfer, as well as brought forth new and hitherto unknown challenges. This study pursues the goal to delineate the challenges and/or limitations of the I4’s process of technology transfer in terms of anthropotechnological aspects. For this purpose, the combination of two methodologies, PRISMA and Methodi Ordinatio, was carried out. The final portfolio analysis was divided into quantitative and qualitative sections. As a result, the current and recurring challenges of this interaction were reported in an overlap. Moreover, it was demonstrated that most studies have been focusing their attention on what involves a more holistic issue of the whole scenario, be they in the organizational, educational, cultural, governmental, security, human capital, technologies, innovations, or sustainable development issues. Finally, this research can serve as a starting point for further researches, as well as contribute to the understanding of industries during the implementation of the Industry 4.0 and their challenges regarding processes of technology transfer.
Olfactory Bulb Integrity in Frontotemporal Dementia and Alzheimer's Disease.

BACKGROUND Olfactory dysfunction is highly prevalent in dementia syndromes, including Alzheimer's disease (AD) and frontotemporal dementia (FTD). The structural integrity of the olfactory bulb (OB) is thought to play a critical role in odor detection and identification, but no MRI study has measured OB volume in FTD, or measured OB volume longitudinally in AD. OBJECTIVE To measure OB volume in FTD and AD patients longitudinally using MRI. METHODS This study measured OB volumes using MRI in patients diagnosed with behavioral-variant FTD (n = 55), semantic dementia (n = 34), progressive non-fluent aphasia (n = 30), AD (n = 50), and healthy age-matched controls (n = 55) at their first visit to a dementia research clinic ('baseline'). Imaging data in patients 12-months later were analyzed where available (n = 84) for longitudinal assessment. Volumes of subcortical and cortical olfactory regions ('olfactory network') were obtained via surface-based morphometry. RESULTS Results revealed that in AD and FTD at baseline, OB volumes were similar to controls, whereas volumes of olfactory network regions were significantly reduced in all patient groups except in progressive non-fluent aphasia. Longitudinal data revealed that OB volume became significantly reduced (10-25% volume reduction) in all dementia groups with disease progression. CONCLUSION Olfactory dysfunction is common in patients diagnosed with AD or FTD, but our results indicate that there is no detectable volume loss to the OBs upon first presentation to the clinic. Our findings indicate that the OBs become detectably atrophied later in the disease process. OB atrophy indicates the potential usefulness for OBs to be targeted in interventions to improve olfactory function.
Sustainable and Eco-Friendly Packaging Films Based on Poly (Vinyl Alcohol) and Glass Flakes

The majority of food packaging materials are petroleum-based polymers, which are neither easily recyclable nor ecologically friendly. Packaging films should preferably be transparent, light in weight, and easy to process, as well as mechanically flexible, and they should meet the criteria for food encapsulation. In this study, poly (vinyl alcohol) (PVA)-based films were developed by incorporating glass flakes into the films. The selection of PVA was based on its well-known biodegradability, whereas the selection of glass flakes was based on their natural impermeability to oxygen and moisture. The films were processed using the blade coating method and were characterized in terms of transparency, oxygen transmission rate, mechanical strength, and flexibility. We observed that the incorporation of glass flakes into the PVA matrix did not significantly change the transparency of the PVA films, and they exhibited a total transmittance of around 87% (at 550 nm). When the glass flakes were added to the PVA, a significant reduction in moisture permeation was observed. This reduction was also supported and proven by Bhardwaj’s permeability model. In addition, even after the addition of glass flakes to the PVA, the films remained flexible and showed no degradation in terms of the water vapor transmission rate (WVTR), even after bending cycles of 23,000. The PVA film with glass flakes had decent tensile characteristics, i.e., around >50 MPa. Increasing the concentration of glass flakes also increased the hardness of the films. Finally, a piece of bread was packaged in a well-characterized composite film. We observed that the bread packaged in the PVA film with glass flakes did not show any degradation at all, even after 10 days, whereas the bread piece packaged in a commercial polyethylene bag degraded completely. Based on these results, the developed packaging films are the perfect solution to replace commercial non-biodegradable films.
Variability of roughness parameters calculated using data obtained by TLS depending on scan resolution and beam's angle of incidence

Spatial data obtained by Terrestrial Laser Scanning (TLS) can be used in order to create various inventories and analyses of the surveyed surfaces. This paper presents a use of orthogonal regression line in order to identify the beam's incidence angle on the surveyed surface as well as identification of roughness parameters using data obtained by terrestrial laser scanning. Accuracy of the visualisation of the surface and roughness parameters, in particular Ra (mean arithmetic deviation of surface roughness profile forming the average line) are closely correlated to the scan resolution of the evaluated area. Presented analyses indicate a need to identify areas with uniform visualisation [1,2] in the compared scans.
Performance Measurements for the CREWES Project

ABSTRACT Performance measurements are a useful tool for measuring and encouraging progress towards desired goals. The mandate of the CREWES Project is to educate students, and to produce valuable research results. We have designed a quantity that encapsulates our progression towards these two aims. Research results are evaluated primarily on the basis of publications, as documented studies of research organizations indicate that this is amongst the most reliable indicators of output. Numbers of graduates are the foundation of the measure of meeting the educational goals. The output measure, as a function of time, shows that The CREWES Project appears to be on track with respect to succeeding in its two-fold mandate. In addition, while output has risen steadily over the lifetime of the project, productivity has remained fairly constant. Additional financial analysis suggests that diffusion of CREWES technology has followed a pattern typical for new technology offerings in the marketplace, and that both revenue and costs can be correlated to external factors.
Improved ant colony algorithm for adaptive frequency-tracking control in WPT system

When the distance between resonators is low enough for the coupling condition to be greater than the critical coupling, the single resonant peak at the load splits to form double peaks. This frequency-splitting phenomenon results in a reduction in the power transferred. In this study, an adaptive frequency-tracking control (AFTC) approach based on a closed-loop control scheme is implemented to overcome this problem. An improved ant colony algorithm (IACA) was proposed in AFTC to track the maximum power point in real time. Then, simulations were performed to test the real-time characteristics of IACA. Finally, a wireless power transfer system with AFTC is demonstrated experimentally to validate the IACA results and the tracking of the optimal frequency.
Magnetism in spin-1 Bose-Einstein condensates with antiferromagnetic interactions

In this thesis we study experimentally the magnetic properties of spin-1 Bose-Einstein condensate of Sodium at equilibrium. In this system the atoms can occupy any of the three Zeeman states characterized by their spin projection on the quantization axis m=+1,0,-1. We measure the many-body spin state of the system as a function of the applied magnetic field and of the magnetization (difference between the populations of the spin states m=+1 and m=-1) of the atomic sample. We find that our measurements reproduce very well the mean-field prediction, and we identify two magnetic phases expressing the competition between the antiferromagnetic inter-particle interactions and the effect of the magnetic field. We describe these phases in terms of a spin nematic order characterizing the symmetry of the many-body spin state. In a second part we focus on the properties of condensates of very low magnetization under a weak magnetic field. In these conditions, the symmetry of the system manifests itself in huge spin fluctuations. This phenomenon is not explainable by a naive mean-field theory and we develop a more elaborate statistical approach to describe the spin state of the condensate. We measure the spin fluctuations and are able from their analysis to infer the temperature characterizing the spin degree of freedom of the condensate. We find that this temperature differs from the temperature of the thermal fraction surrounding the condensate. We interpret this difference as a consequence of the weak coupling between these two systems.
Attention for Vision-Based Assistive and Automated Driving: A Review of Algorithms and Datasets

Driving safety has been a concern since the first cars appeared on the streets. Driver inattention has been singled out as a major cause of accidents early on. This is hardly surprising, as drivers routinely perform other tasks in addition to controlling the vehicle. Decades of research into what causes lapses or misdirection of drivers’ attention resulted in improvements in road safety through better design of infrastructure, driver training programs, in- vehicle interfaces, and, more recently, the development of driving assistance systems (ADAS) and driving automation. This review focuses on the methods for modeling and detecting spatio-temporal aspects of drivers’ attention, i. e. where and when they look, for the two latter categories of applications. We start with a brief theoretical background on human visual attention, methods for recording and measuring attention in the driving context, types of driver inattention, and factors causing it. We then discuss machine learning approaches for 1) modeling gaze for assistive and self-driving applications and 2) detecting gaze for driver monitoring. Following the overview of state-of-the-art models, we provide an extensive list of publicly available datasets that feature recordings of drivers’ gaze and other attention-related annotations. We conclude with a general overview of the remaining challenges, such as data availability and quality, evaluation methods, and the limited scope of attention modeling, and outline steps toward rectifying some of these issues. Categorized and annotated lists of the reviewed models and datasets are available at https://github.com/ykotseruba/attention_and_driving