Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of chitosan–tungsten composite coating obtained by electrophoretic deposition on the corrosion resistance of Ni–Ti alloy in physiological medium

Ni–Ti shape memory alloys (Nitinol) are suitable for biomedical applications such as orthodontic, orthopedic, and cardiovascular implants. However, to avoid local inflammatory processes, efforts are being made to functionalize the surface of the Ni–Ti alloy with bioactive materials. Chitosan-based composite coatings can be applied to improve the properties of Ni–Ti alloys due to their excellent properties, such as low toxicity, biocompatibility, biodegradability, and good film-forming ability. In this work, the chitosan–tungsten composite (Chit–W) was evaluated as a protective coating for Ni–Ti alloy in a physiological medium (Ringer's solution). The results of surface morphology and chemical composition (SEM and EDX) confirmed the formation of the composite coating formed by a chitosan matrix impregnated with tungsten oxide nanoparticles. Corrosion resistance results proved the efficiency of the composite coating, acting as a protective barrier between the surface of the substrate (Ni–Ti) and the corrosive environment. Therefore, the results point to a possible system candidate (Ni–Ti alloy coated with Chit–W composite) suitable for applications in orthopedic implants.
New Generation Electric Tail Rotor Performance Analyses

The electric tail rotor is an anti-torque system that is used to balance the torque effect generated by the main rotor of rotary-wing aircraft and provides its power requirement from batteries. The new generation electric tail rotors have many differences in terms of drive system, exposed loudness, and power consumption. Considering all, a comparison of the electric tail rotor conceptual design performance and conventional tail rotor performance in the UH-60 helicopter was made. By considering nonlinear effects due to viscous flow, profile drag effects and blade tip losses, the formulation was modified to give results closer to the experimental data. Calculus method with help of Blade Element Momentum Theory (BEMT) was created to observe from root to end the change in thrust and power consumption of blade. Thus, the power consumption and thrust generation values of the two rotor systems were compared and the relevant results were presented in various tables and graphics.
Analyzing and Interacting with Voting Records from Historical Documents

Citing this paper Please note that where the full-text provided on King's Research Portal is the Author Accepted Manuscript or Post-Print version this may differ from the final Published version. If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections.
Research on Multiparty Participation Collaborative Supervision Strategy of AIGC

The emergence and popularity of ChatGPT has sparked a new wave of “artificial intelligence” worldwide. AIGC is a true industrial revolution-level artificial intelligence technology revolution that will bring significant changes to the entire country, the world, and humanity. Like all technologies, the development of AIGC technology not only brings convenience and innovation to people, but also brings many risks and challenges. By studying the principle of AIGC technology and combining with typical cases, this paper analyzes the causes of security problems caused by the model defects and abuse propagation, focusing on the analysis of privacy Data breach, prejudice and discrimination, copyright disputes caused by data collection, processing, output and other links, as well as the impact of controlled, malicious application, abuse, misuse and other propagation on personal privacy, social stability, national security and international order. From the perspective of both security issues inherent to AIGC and those caused by its application, a multi-party collaborative regulatory strategy is proposed to safeguard the innovative development of AIGC technology, provide theoretical support for the healthy and standardized development of related industries, and help with economic and social transformation and development.
Vegetative plaque on the left superior eyelid

Abstract Herein we present case report of a 73‐year‐old female who developed a rapidly growing, ulcerated lesion on her left superior eyelid. Despite treatment for suspected infection, symptoms only marginally improved. Physical examination revealed a diffusely ulcerated multinodular tumour with overlying haemorrhagic and serosanguineous exudate. A shave biopsy led to a diagnosis of primary cutaneous anaplastic large cell lymphoma (pcALCL), a rare CD30+ lymphoproliferative disorder. The patient had no extracutaneous involvement on PET‐CT and her prognosis is good given the indolent nature of pcALCL. Differential diagnoses included merkel cell carcinoma, periocular sebaceous carcinoma, lymphomatoid papulosis, and extranodal natural killer/T cell lymphoma. Prognosis for pcALCL is generally good. Treatment recommendation for pcALCL is surgical excision with negative margins for localised disease, while intravenous brentuximab vedotin is suggested for widespread, relapsed, and refractory disease.
Evaluation of the Physicochemical and Techno-functional Properties of Gelatin Extracted from Fish Processing Waste

The current research was completed at the Indian Council of Agricultural Research - Central Institute of Fisheries Technology (ICAR-CIFT), Cochin, Kerala, India from August 2021 to August 2022 as a modified thermal extraction protocol for deriving gelatin from processing waste of skipjack tuna (Katsuwonus pelamis) skin. The study evaluated the effect of chemical composition and molecular weight contributing to the techno-functional attributes of the resulting gelatin. In the present study, we followed warm water-coupled NaCl pre-treatment to reduce the lipid content of the extracted gelatin. The extracted gelatin was characterized for Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE). The amount of gelatin extracted from the fish skin was 9.30±0.22%. The protein pattern of extracted gelatin on SDS-PAGE was identical to commercial grade gelatin, which implies the purity of extracted gelatin is comparable to that of commercial one. The physicochemical and functional properties were evaluated and pose remarkable techno-functional properties. Therefore, fish processing skin waste of skipjack tuna could be effectively exploited for the preparation of commercial gelatin. The extraction protocol remains environment friendly and this approach remains optimal for food technological applications. The effective exploration contributed to nutritional benefits, technological, functional, and biological functionalities for a large fraction of applications in the area of food technology, nutraceuticals, pharmaceutics, and numerous others as a future line of research.
Opportunistic Division and Allocation of Machine Learning Task for WSN

Machine learning (ML)-applied sensing systems are widely deployed in real environments in the research and development of wireless sensor networks (WSNs). However, in these systems, the central server must deal with the large amounts of sensing data and high processing costs to execute ML tasks. To deal with these issues, in-network processing methods of ML tasks have been proposed for WSNs. However, their main focus is to decide the division points and allocation strategy of ML tasks, and therefore they do not consider the routing algorithm in distributed environments. This paper proposes an opportunistic division and allocation method of ML tasks in distributed WSN environments that does not rely on a specific path. In the proposed method, each node autonomously makes a forwarding decision based on the remaining computational resource and hop count to distribute the computational load while considering the number of relays. A simulation was performed, and it revealed that the proposed method can appropriately allocate the computational processes of ML tasks and distribute them to WSN nodes.
Input-Parallel Output-Series High Step-Up DC/DC Converter With Coupled Inductor and Switched Capacitor

In this study, the authors propose a non-isolated high step-up interleaved DC/DC converter that can be applied to sustainable energy system. The proposed converter achieves high voltage gain by employing a coupled inductor and switched capacitor method based on an interleaved boost converter. The two coupled inductors connected in parallel with the input side have a distinct structure. Specifically, a single coupled inductor has a primary side and a secondary side connected in series, and it is further connected in parallel with an output side switched capacitor circuit. The switched capacitor circuit increases the voltage gain by being charged in parallel and discharged in series through the coupled inductor. The leakage inductor energy of the coupled inductor can be regenerated to the output side through the passive clamp circuit’s performance. Moreover, it is possible to select devices with low voltage stress and on-state resistance of the switches, which results in reduced loss and size while alleviating the reverse recovery problem of diodes. The steady-state analysis and operation principle of the proposed converter are thoroughly explained and verified through a prototype circuit with 20V input voltage, 400V output voltage, and 320W level output power.
Effect of Benaglutide on Gut Microbiota and Fecal Metabolites in Patients with Type 2 Diabetes Mellitus

Objective Benaglutide is a glucagon-like peptide-1 receptor agonist (GLP-1RA) that has been approved in the treatment of type 2 diabetes mellitus (T2DM). It is known to lead to significant weight loss, and it is hypothesized that changes in gut microbiota may play a significant role in such weight loss. However, it is unclear how gut microbiota and metabolites change as a result of benaglutide treatment. Methods Healthy participants and patients with T2DM were included in this study. They received differentiated treatments, and stool specimens were collected separately. These stool specimens were subjected to 16S ribosomal RNA amplicon and metagenomic sequencing to create fecal metabolomic profiles. The diversity of gut microbiota and metabolic products in the stools of each participant was analyzed. Results The data showed that Faecalibacterium prausnitzii was abundant in the gut microbiota of the control group, which was entirely made up of healthy individuals; however, it showed a statistically significant decrease in patients with T2DM treated with metformin alone, while no significant decrease was observed in patients treated with metformin combined with benaglutide. A metagenomic analysis revealed that benaglutide could improve the fecal microbiota diversity in patients with T2DM. Furthermore, there was a statistically significant correlation between the changes in the metabolites of patients with T2DM and the changes in their gut microbiota (including F. prausnitzii) after treatment with metformin and benaglutide. Conclusion These findings suggest that the weight-reducing effect of benaglutide is attributed to its ability to normalize the gut microbiota of patients with T2DM, particularly by increasing the abundance of F. prausnitzii.
Evaluating methods to account for the greenhouse gas emissions from Land Use Changes in agricultural LCA

Approaches to account for land use change-related GHG emissions (LUCE), differing on the basis of the spatial allocation of the emissions, were compared in this study, and the justification of their application was evaluated based on generally accepted criteria from ISO 14040, PAS 2050 and IPCC guidelines. In general, most methods technically fulfilled those criteria, with exception of the “Worst case” or marginal approach which resulted in multiple counting of global emissions. The selection amongst the acceptable methods still remains rather subjective. The conclusions of agricultural LCA studies, related for example to the GHG emissions from livestock feed, are strongly dependent on the selected method, and for this reason a universally accepted single method is needed. One solution might be an application of a modified “Top down” method, which takes into account emissions from indirect LUC and the actual drivers affecting them.
Differences in the Stool Metabolome between Vegans and Omnivores: Analyzing the NIST Stool Reference Material

To gain confidence in results of omic-data acquisitions, methods must be benchmarked using validated quality control materials. We report data combining both untargeted and targeted metabolomics assays for the analysis of four new human fecal reference materials developed by the U.S. National Institute of Standards and Technologies (NIST) for metagenomics and metabolomics measurements. These reference grade test materials (RGTM) were established by NIST based on two different diets and two different samples treatments, as follows: firstly, homogenized fecal matter from subjects eating vegan diets, stored and submitted in either lyophilized (RGTM 10162) or aqueous form (RGTM 10171); secondly, homogenized fecal matter from subjects eating omnivore diets, stored and submitted in either lyophilized (RGTM 10172) or aqueous form (RGTM 10173). We used four untargeted metabolomics assays (lipidomics, primary metabolites, biogenic amines and polyphenols) and one targeted assay on bile acids. A total of 3563 compounds were annotated by mass spectrometry, including 353 compounds that were annotated in more than one assay. Almost half of all compounds were annotated using hydrophilic interaction chromatography/accurate mass spectrometry, followed by the lipidomics and the polyphenol assays. In total, 910 metabolites were found in at least 4-fold different levels in fecal matter from vegans versus omnivores, specifically for peptides, amino acids and lipids. In comparison, only 251 compounds showed 4-fold differences between lyophilized and aqueous fecal samples, including DG O-34:0 and methionine sulfoxide. A range of diet-specific metabolites were identified to be significantly different between vegans and omnivores, exemplified by citrinin and C17:0-acylcarnitine for omnivores, and curcumin and lenticin for vegans. Bioactive molecules like acyl alpha-hydroxy-fatty acids (AAHFA) were differentially regulated in vegan versus omnivore fecal materials, highlighting the importance of diet-specific reference materials for dietary biomarker studies.
Magnetic Power Distribution Using Controlled Permeability Bypass and Its Multiple Output Investigation

An alternative wireless power transfer (WPT) using near-field magnetic power distribution is proposed. The new method is characterized by using a low permeability path in serial with a high permeability path as the main unit or the basic cell. The output can be tapped into the main unit by paralleling the low permeability path. The magnetic cores are integrated with different permeability to form a multiple-transmitter geometry. Every transmitter corresponds to more than one receiver that is integrated with back-end circuits such as rectifiers to convert ac voltage into dc voltage. The receiver can be easily installed in the electrical devices, and hence power is transferred wirelessly to drive the devices. Analysis of the working mechanisms of the proposed WPT system is given in detail and design considerations are also investigated. Power loss distributions for the converter and coupler are also analyzed fully. Experimental results show that a basic cell driven by an 80 kHz pulse wave, supplying three resistive loads at 321 W achieves 86.6% efficiency. The system efficiency can be maintained at a high level over a wide output power range. Finally, a magnetic panel comprising seven basic cells supplying multiple loads is demonstrated. Results show the feasibility of the proposed system by lighting up multiple LED loads.
Fokas Based Dirichlet-to-Neumann Operators for Accurate Signal Integrity Assessment of Interconnects

In this contribution, we present a new approach to fully characterize interconnects composed out of arbitrary polygonal cross-sections and containing piecewise homogeneous material parameters. The complex per-unit-of-length inductance and capacitance matrices are obtained through the application of pertinent Dirichlet-to-Neumann operators, which are computed by means of an extended Fokas method, that are integrated in a boundary integral equation approach. As the complete RLGC-data of the structures under study is computed, we are able to assess relevant properties such as signal attenuation and cross-talk while the support for polygonal shapes allows for the inclusion of manufacturing effects such as etching.
Edge-based Analysis for Network Intrusion Detection using a GNN Approach

Anomaly detection is an essential task in detecting fraud and identifying faults in various areas, including network security. Network Intrusion Detection Systems (NIDS) have traditionally been used to detect known threats; however, machine learning models such as Graph Neural Networks (GNN) are gaining popularity with the increasing complexity of cyberattacks. This paper presents an implementation of a NIDS based on a GNN machine learning model for anomaly detection in network traffic, focusing on the edges of the input graphs. Moreover, the modules incorporated into the system are detailed. Finally, the results and analysis obtained from the experiment are presented, demonstrating the effectiveness of the proposed GNN-based anomaly detection approach.
First record of the orb-weaving spider genus Homalometa Simon, 1897 (Araneae, Tetragnathidae) in Colombia

Homalometa is a Neotropical spider genus in the family Tetragnathidae with only three described species: two are known from Central America and the Caribbean (H. chiriqui Levi, 1986 and H. nigritarsis Simon, 1897), and one from Brazil (H. nossa Levi, 1986). We report the presence of H. nigritarsis in the Andes of Colombia, thus extending its known distribution to northern South America. Individu- als were collected at coffee plantations at several localities between 1462 and 1834 m, 85 km west from Bogota.
Pneumonia Detection Using X-Ray Images

The primary cause of mortality in youngsters aged below five is pneumonia, a lung condition. In 2016, a UNICEF survey found that infants under the five-year-old limit made up around 16% of fatalities. Most of the afflicted children, who were under two years old, were impacted. The treatment procedure can be sped considerably by finding pneumonia in youngsters. In order for medical professionals to effectively treat pneumonia in the real world, this research proposes CNN models to precisely diagnose pneumonic lungs through chest X-rays. The Chest X-Ray Pictures (Pneumonia) dataset from Kaggle is the subject of a study. So, the main objective of this research is to develop a software system that uses chest x-ray images to recognize the pneumonia condition. The chest x-ray pictures are trained, tested, and verified in one or even more convolutional neural networks layers to do this. The software system's classification of the diseased and non-infected photos is the outcome. Consequently, our study can accurately identify the condition from chest x-ray scans more than 90% of the time.
Classification of EEG Signals Using a Common Spatial Pattern Based Motor-Imagery for a Lower-limb Rehabilitation Exoskeleton

This article presents a lower-limb exoskeleton rehabilitation integrated with an electroencephalogram (EEG) based brain-computer interface (BCI). The BCI is used to record signals collected using the EEG interface during resting, a motor imagery (MI) and a motor execution (ME) tasks. The MI data is generated when a subject imagines the movement of a limb. Therefore, the signals were characterized by Common Spatial Pattern (CSP), Power Spectrum Density (PSD) and Discrete Wavelet Transform (DWT) in the specific Mu band of Auto Regressive model (AR). In the case of the lower-limb representation, there is a problem of reliably distinguishing leg movement intentions. The study shows how the combined use of multi-model signals can improve the accuracy and reliability of the human-machine interface. The signals induced by CSP, PSD, and DWT+AR are used for the lower-limb exoskeleton control commands to drive the movement in real time. With using the support vector machine (SVM), the signals are tested the classification precision. The classification of the control system permits one to drive the lower limb rehabilitation exoskeleton effectively.
A Self-Sealing Modular Microfluidic System Using PDMS Blocks With Magnetic Connections

A modular microfluidic system can be used to quickly set up an individually adaptable microfluidic network by linking and delinking different functional building blocks. We present a convenient and reliable connection technology, which is based on magnets and casted O-ring-like structures leading to a sealed connection without the need of additional sealing materials. Based on an improved, previously presented fabrication technology, modular microfluidic polydimethylsiloxane (PDMS) blocks using a polyurethane (PU) mold, 3D printed acrylonitrile butadiene styrene (ABS) channel structures and a magnetic connection system in combination with a casted O-ring link, featuring various integration technologies have now been designed and experimentally evaluated. In particular, this paper will address the realization of directional valves, reciprocating pumps, finger pumps, directly-cast check- and Tesla-valves, fluidic flow sensors, fluidic mixers, commercial valves, and various sensors. By using different measurement setups, the feasibility of these devices is demonstrated. Moreover, limitations and issues encountered during fabrication as well as future work are discussed.
Three-Dimensional Integration of Switching and Light-Sensitive Organic Transistors in Solution Processes for Flexible High-Resolution Active-Matrix Optical Imager

A three-dimensional (3D) integration architecture composed of a top-gate organic thin-film transistor (OTFT) as pixel switch and a bottom-gate organic phototransistor (OPT) for photo-sensing is proposed to construct flexible active-matrix optical imager. The two devices in one pixel can be separately optimized for functions of pixel switching and photo-sensing, respectively. Low temperature (<inline-formula> <tex-math notation="LaTeX">$ < 150 ^{\circ }$ </tex-math></inline-formula>) solution-based integration processes are developed to achieve high-resolution 3D stacking on plastic substrate. A flexible active-matrix imager of <inline-formula> <tex-math notation="LaTeX">${100}\times {100}$ </tex-math></inline-formula> pixels (127 ppi) is implemented based on such integration architecture, and demonstrated for fingerprint imaging under ambient light condition.
Latihan Menelan terhadap Kemampuan Menelan Pasien Stroke yang Mengalami Disfagia

This study aims to identify and compare the effect of interventional swallowing exercises on swallowing ability in stroke patients who experience dysphagia. The method used is a quantitative method with a one-group pre-test-post-test approach. Respondents in this study were stroke patients who underwent moderate category of dysphagia, totaling 35 respondents. Initial data collection was started using the Nursing Bedside Swallowing Screening dysphagia assessment sheet. Then, the researcher used the Mann Assessment of Swallowing Ability (MASA) to assess the patient's swallowing ability. The results showed a significant difference (p<0.05) in the swallowing capacity of the respondents before and after the swallowing training intervention. The conclusion of this study, swallowing exercises are effective in improving the swallowing ability of stroke patients who experience dysphagia. Keywords: Dysphagia, Swallowing Ability, Stroke