bluuebunny/crossref_metadata_2025 huggingface dataset:
Association Between Rapid Antigen Detection Tests and Real-Time Reverse Transcription–Polymerase Chain Reaction Assay for SARS-CoV-2: A Systematic Review and Meta-Analyses
Authors: Yang Yu-Pei , Jiesisibieke Zhu Liduzi , Tung Tao-Hsin
Published: August 2023

Objectives: We aimed to assess the association between rapid antigen detection tests and real-time reverse transcription-polymerase chain reaction assay for severe acute respiratory syndrome coronavirus 2.

Methods: We searched PubMed, Cochrane Library, EMBASE, and the Web of Science from their inception to 31 May 2023. A random-effects meta-analysis was used to estimate false positives in the RADTs group, relative to those in the RT-PCR group, and subgroup analyses were conducted based on the different Ct value cut-offs (<40 or ≥40). We performed this study in accordance with the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).

Results: Fifty-one studies were included and considered to be of moderate quality. We found a satisfactory overall false positive rate (0.01, 95% CI: 0.00–0.01) for the RADTs compared to RT-PCR. In the stratified analysis, we also found that the false positive rates of the RADTs did not increase when Ct values of RT-PCR (Ct < 40, 0.01, 95% CI: 0.00–0.01; Ct ≥ 40, 0.01, 95% CI: 0.00–0.01).

Conclusion: In conclusion, the best available evidence supports an association between RADTs and RT-PCR. When Ct-values were analyzed using cut-off <40 or ≥40, this resulted in an estimated false positive rate of only 1%.
A Novel Strain Wave Gear Reducer with Double Flexsplines
Authors: Ling Zilong , Zhao Lei , Xiao Dong , Zhou Yi , Ma Cui , He Kai , Liu Guanyi
Published: August 2023

Strain wave gear reducers, also known as harmonic drives, are widely used in industrial robots and collaborative robots. The zero-backlash feature is very important for these applications. However, this places extremely high demands on the machining accuracy of the strain wave gear reducer. Excessive manufacturing errors will lead to excessive backlash, affecting transmission accuracy or making installation difficult, and the flexible spline (or flexspline) is prone to wear, resulting in reduced accuracy with use. This study proposes a novel strain wave gear reducer with a double flexspline structure. The original “circular spline” which was rigid will be redesigned to be slightly flexible and deformable with an additional deformation adjustment structure, which reduces the requirements for machining accuracy, and realizes the same zero-backlash characteristic of traditional structure. The experimental results show that the new strain wave gear reducer has extremely low lost motion, hysteresis loss, and high torsional rigidity. The new strain wave gear reducer provides a more economical way to realize the zero-backlash reducer and helps to solve the problem of the accuracy decline of the strain wave gear reducer due to the wear of the flexspline.
Entrepreneurial Attributes and Venture Creation among Undergraduate Students of Selected Universities in Southwest, Nigeria
Authors: Dada Augustina E. , Adegbuyi Omotayo A. , Ogbari Mercy E.
Published: August 2023

This study examined the effect of entrepreneurial attributes on venture creation among undergraduate students of selected universities in Southwest, Nigeria. The study measures the presence of entrepreneurial attributes (creativity, critical thinking, risk taking, leadership skills and resilience) among undergraduate students of selected public and private universities in Southwest, Nigeria. A total of 751 copies of questionnaires were distributed and 616 copies were returned and deemed suitable for analysis. A structural equation model (PLS 3.0) was used for the analysis. The result showed that entrepreneurial attributes contribute more to business opportunity identification, business planning and business startups. This implies that universities in Nigeria should develop these attributes (creativity, critical thinking, risk taking, leadership skills and resilience) through entrepreneurship education to reduce the rate of graduate unemployment in Nigeria.
Agricultural Wastewater Treatment Using Oil Palm Waste Activated Hydrochar for Reuse in Plant Irrigation: Synthesis, Characterization, and Process Optimization
Authors: Jagaba Ahmad Hussaini , Bashir Faizah Mohammed , Lawal Ibrahim Mohammed , Usman Abdullahi Kilaco , Yaro Nura Shehu Aliyu , Birniwa Abdullahi Haruna , Hamdoun Haifa Youssef , Shannan Nahla M.
Published: August 2023

The best possible use of natural resources and the large amounts of trash produced by industrial and human activity is necessary for sustainable development. Due to the threat of global climate change and other environmental challenges, waste management systems are changing, leading to more instances of water resource management. The waste generated must be controlled from a sustainability point of view. Typically, the conventional disposal of Agricultural Wastewater (AW) and biomass can be achieved by recycling, reusing, and converting them into a variety of green products. To improve the AW quality for the purposes of environmental sustainability, Sustainable Development Goals (SDGs) 6 and 14, dealing with clean water, sanitation, and life below water, are very important goals. Therefore, the present investigation evaluates the effectiveness of a Bench-scale Activated Sludge Reactor (BASR) system for AW treatment. The BASR was designed to focus on getting the maximum possible utilization out of a biosorbent derived from oil palm waste activated hydrochar (OPAH). This is in accordance with SDG 9, which targets inorganic and organic waste utilization for added value. An experiment was developed using the Response Surface Methodology (RSM). A Hydraulic Retention Time (HRT) of 1–3 days was used in the bioreactor’s setup and operation, and Mixed Liquor Suspended Solids (MLSS) concentrations of 4000–6000 mg/L were used. BASR was fed with AW with initial mean concentrations of 4486 ± 5.63 mg/L and 6649 ± 3.48 for the five-day Biochemical Oxygen Demand (BOD5) and Chemical Oxygen Demand (COD) experiments, respectively. The results obtained showed that maximum reductions of 84.66% and 72.07% were recorded for BOD5 and COD, respectively. Through RSM optimization, the greatest reductions in the amounts of organic materials were achieved with a 2-day HRT and an MLSS dosage of 5000 mg/L. Substrate elimination thresholds were assessed using the first-order, the Grau second-order, and the modified Stover–Kincannon models. The reported observations were found to be perfectly fit by the modified Stover–Kincannon model, with high R2 values of 0.9908 and 0.9931 for BOD5 and COD, respectively. As a result, the model may be used to design the BASR system and forecast how the reactor would behave. The findings from this study suggest that the developed OPAH has promising potential to be applied as eco-friendly material for the removal of BOD5 and COD from AW. Consequently, the study findings additionally possess the ability to address SDGs 6, 9, and 14, in order to fulfil the United Nations (UN) goals through 2030.
Novel Curve Fitting Analysis of NDVI Data to Describe Turf Fertilizer Response
Authors: Carey Ken , Powers Jacqueline E. , Ficht Alexandra , Dance Tim , Gharabaghi Bahram , Lyons Eric M.
Published: August 2023

Evaluating the effectiveness of fertilizers on crops without traditional yield is difficult, as clipping collection is time-consuming and not indicative of the desired response to the fertilizer. Remote sensing techniques, like the normalized difference vegetation index (NDVI), have emerged as an effective tool to combat these issues. Canopy reflectance, measured by NDVI, is commonly used to differentiate turfgrass response to nitrogen (N) fertilization treatments; however, advancements in data processing are needed for greater differentiation between treatments and better testing of the effects of fertilizer responses. Presented here is an advancement in the processing of NDVI data by applying a compound exponential (pulse peak) function to changes in NDVI over time, relative to a control. This method’s effectiveness in differentiating between fertilizers was evaluated by applying polymer-coated urea (PCU), an enhanced efficiency fertilizer (EEF), and urea on turfgrass to show the usefulness of the novel curve fitting in highlighting differences in fertilizer response. The field study was carried out on an established Kentucky bluegrass (Poa pratensis L.) blend on a sandy loam soil rootzone maintained with a typical home lawn maintenance regime. Ratios of PCU to urea ranging from 100% urea to 100% PCU with increments of 20% of PCU were used to observe a continuum of response between the two fertilizer types. The N rate for all blends was 73 kg ha−1, with unfertilized plots used as a control to set baseline measurements for the curve fitting. Turfgrass response to N fertilization treatments was assessed through visual turfgrass quality ratings, dry matter yield, and canopy reflectance, where higher urea content resulted in the shortest time to maximum ∆NDVI (24 days), while 100% EEF reached maximum ∆NDVI at 56 days. The novel curve fitting analysis of the NDVI data allowed for differentiation between treatments, provided a measure of fertilizer effects, and differentiated between urea and enhanced efficiency fertilizers.
Returning to Nature for the Next Generation of Antimicrobial Therapeutics
Authors: MacNair Craig R. , Tsai Caressa N. , Rutherford Steven T. , Tan Man-Wah
Published: August 2023

Antibiotics found in and inspired by nature are life-saving cures for bacterial infections and have enabled modern medicine. However, the rise in resistance necessitates the discovery and development of novel antibiotics and alternative treatment strategies to prevent the return to a pre-antibiotic era. Once again, nature can serve as a source for new therapies in the form of natural product antibiotics and microbiota-based therapies. Screening of soil bacteria, particularly actinomycetes, identified most of the antibiotics used in the clinic today, but the rediscovery of existing molecules prompted a shift away from natural product discovery. Next-generation sequencing technologies and bioinformatics advances have revealed the untapped metabolic potential harbored within the genomes of environmental microbes. In this review, we first highlight current strategies for mining this untapped chemical space, including approaches to activate silent biosynthetic gene clusters and in situ culturing methods. Next, we describe how using live microbes in microbiota-based therapies can simultaneously leverage many of the diverse antimicrobial mechanisms found in nature to treat disease and the impressive efficacy of fecal microbiome transplantation and bacterial consortia on infection. Nature-provided antibiotics are some of the most important drugs in human history, and new technologies and approaches show that nature will continue to offer valuable inspiration for the next generation of antibacterial therapeutics.
S-Adenosylmethionine Decreases Bacterial Translocation, Proinflammatory Cytokines, Oxidative Stress and Apoptosis Markers in Hepatic Ischemia-Reperfusion Injury in Wistar Rats
Authors: Valdés Sergio , Paredes Sergio D. , García Carreras Carmen , Zuluaga Pilar , Rancan Lisa , Linillos-Pradillo Beatriz , Arias-Díaz Javier , Vara Elena
Published: August 2023

Hepatic ischemia/reperfusion injury (IRI) can seriously impair liver function. It is initiated by oxidative stress, resulting in inflammation and apoptosis-induced cellular damage. Glutathione (GSH) prevents oxidative stress. S-Adenosylmethionine (SAMet) is a GSH synthesis precursor that avoids the deficit in SAMet-synthetase activity and contributes to intracellular ATP repletion. It also acts as a methyl group donor, stabilizing hepatocyte membranes, among other functions. This study investigated the effect of SAMet on bacterial translocation and levels of proinflammatory cytokines, oxidative stress and apoptosis markers in male Wistar rats subjected to hepatic IRI. Animals were randomly divided into six groups: (1) sham operation, (3) animals undergoing 60 min of ischemia of the right lateral lobe for temporary occlusion of the portal vein and hepatic artery plus 10 min of reperfusion, and (5) the same as (3) but with a reperfusion period of 120 min. Groups 2, 4 and 6, respectively, are the same as (1), (3) and (5), except that animals received SAMet (20 mg/kg) 15 min before ischemia. GSH, ATP, lipid peroxidation (LPO), TNF-α, IL-1β, IL-6, total caspase-1 and caspase-9, total and cleaved caspase-3, and phosphatidylcholine were determined in the liver. Endotoxin, TNF-α, IL-1β, IL-6, IL-10 and LPO in vena cava and portal vein blood samples were also measured. Endotoxin and LPO levels as well as proinflammatory cytokines and apoptotic markers increased significantly in animals undergoing IRI, both after 10 and 120 min of reperfusion. IRI produced a significant decrease in GSH, ATP, portal IL-10 and phosphatidylcholine. SAMet treatment prevented these effects significantly and increased survival rate. The study suggests that SAMet exerts protective effects in hepatic IRI.
Grammar Correction for Multiple Errors in Chinese Based on Prompt Templates
Authors: Wang Zhici , Yu Qiancheng , Wang Jinyun , Hu Zhiyong , Wang Aoqiang
Published: August 2023

Grammar error correction (GEC) is a crucial task in the field of Natural Language Processing (NLP). Its objective is to automatically detect and rectify grammatical mistakes in sentences, which possesses immense application research value. Currently, mainstream grammar-correction methods primarily rely on sequence labeling and text generation, which are two kinds of end-to-end methods. These methods have shown exemplary performance in areas with low error density but often fail to deliver satisfactory results in high-error density situations where multiple errors exist in a single sentence. Consequently, these methods tend to overcorrect correct words, leading to a high rate of false positives. To address this issue, we researched the specific characteristics of the Chinese grammar error correction (CGEC) task in high-error density situations. We proposed a grammar-correction method based on prompt templates. Firstly, we proposed a strategy for constructing prompt templates suitable for CGEC. This strategy transforms the CGEC task into a masked fill-in-the-blank task compatible with the masked language model BERT. Secondly, we proposed a method for dynamically updating templates, which incorporates already corrected errors into the template through dynamic updates to improve the template quality. Moreover, we used the phonetic and graphical resemblance knowledge from the confusion set as guiding information. By combining this with BERT’s prediction results, the model can more accurately select the correct characters, significantly enhancing the accuracy of the model’s prediction correction results. Our methods were validated through experiments on a public grammar-correction dataset. The results indicate that our method achieves higher correction performance and lower false correction rates in high-error density scenarios.
Enhanced Steganography for High Dynamic Range Images with Improved Security and Capacity
Authors: Chen Tzung-Her , Yan Jing-Ya
Published: August 2023

High-dynamic-range (HDR) images are widely regarded as the ideal format for digital images due to their ability to accurately render a wider range of luminance values. Recently, research has focused on introducing data-hiding techniques to HDR images, but these studies often suffer from a low hiding capacity. In 2011, a steganography scheme was proposed, which utilizes homogeneity in RGBE (red, green, blue, and exponent) format, a popular HDR format, and results in cover images with only slight and ignorable distortions after embedding. However, the capacity of the scheme is limited, and their steganography process may raise suspicions due to the abnormal distribution of pixel values caused by the multiplication and division in the embedding process. There is no denying that security is always the main concern for steganography. A major potential problem became clear after a careful revisiting of the scheme. This paper presents an enhanced steganography scheme that improves embedding capacity by modifying non-embeddable pixels to become embeddable in cover images and avoids potential security weaknesses by using additional random numbers to alter pixel values. The proposed scheme improves the embedding capacity of HDR images while maintaining their visual quality and security against statistical analysis attacks. The experimental result shows that the capacity increases 10 times without visual distortion.
Internet of Medical Things Healthcare for Sustainable Smart Cities: Current Status and Future Prospects
Authors: Mishra Priyanka , Singh Ghanshyam
Published: August 2023

The concept of smart and connected healthcare has emerged in response to the growing demand for the improvement of healthcare systems and the increasing prevalence of chronic diseases. Looking towards the future, smart healthcare holds great potential to transform the healthcare industry by providing more efficient, personalized, and accessible healthcare services. This paper delves into the concept of intelligent, interconnected, and customized healthcare systems within the Internet of Medical Things (IoMT) framework. It explores the utilization of cutting-edge technologies, including the IoMT, in conjunction with big data, cloud computing, artificial intelligence, and blockchain to provide healthcare services that are not only more efficient but also more convenient and personalized. It draws on existing literature, bibliometric data, and global marketing analysis to gain a deeper understanding of these technologies and their impact on the healthcare system. We have explored several upcoming features of the Healthcare 5.0 paradigm, which represents the next evolution in healthcare systems focusing on a more personalized and patient-centric approach. We introduce a healthcare architecture specifically designed for the IoMT that prioritizes the security considerations associated with devices. Finally, we have focused on addressing open research challenges, particularly those related to fundamental social needs, such as ensuring equitable access to smart and connected healthcare systems.
An Overview of Minimally Invasive Surgery Robots from the Perspective of Human–Computer Interaction Design
Authors: Sun Bowen , Li Dijia , Song Bowen , Li Saisai , Li Changsheng , Qian Chao , Lu Qian , Wang Xia
Published: August 2023

In order to streamline and summarize the status quo of human–computer interaction (HCI) design research in minimally invasive surgery robots, and to inspire and promote in-depth design research in related fields, this study utilizes literature research methods, inductive summarizing methods, and comparative analysis methods to analyze and organize the usage scenarios, users, interaction content and form, and relevant design methods of minimally invasive surgery robots, with the purpose of arriving at a review. Through a summary method, this study will obtain outcomes such as design requirements, interaction information classification, and the advantages and disadvantages of different interaction forms, and then make predictions of future trends in this field. Research findings show that the HCI design in the relevant field display a highly intelligent, human-centered, and multimodal development trend through the application of cutting-edge technology, taking full account of work efficiency and user needs. However, meanwhile, there are problems such as the absence of guidance by a systematic user knowledge framework and incomplete design evaluation factors, which need to be supplemented and improved by researchers in related fields in the future.
Model-Based and Model-Free Point Prediction Algorithms for Locally Stationary Random Fields
Authors: Das Srinjoy , Zhang Yiwen , Politis Dimitris N.
Published: August 2023

The Model-Free Prediction Principle has been successfully applied to general regression problems, as well as problems involving stationary and locally stationary time series. In this paper, we demonstrate how Model-Free Prediction can be applied to handle random fields that are only locally stationary such as pixel values over an image or satellite data observed on an ocean surface, i.e., they can be assumed to be stationary only across a limited part over their entire region of definition. We construct novel one-step-ahead Model-Based and Model-Free point predictors and compare their performance using synthetic data as well as images from the CIFAR-10 dataset. In the latter case, we demonstrate that our best Model-Free point prediction results outperform those obtained using Model-Based prediction.
Simultaneous Tracking and Recognizing Drone Targets with Millimeter-Wave Radar and Convolutional Neural Network
Authors: Solaiman Suhare , Alsuwat Emad , Alharthi Rajwa
Published: August 2023

In this paper, a framework for simultaneous tracking and recognizing drone targets using a low-cost and small-sized millimeter-wave radar is presented. The radar collects the reflected signals of multiple targets in the field of view, including drone and non-drone targets. The analysis of the received signals allows multiple targets to be distinguished because of their different reflection patterns. The proposed framework consists of four processes: signal processing, cloud point clustering, target tracking, and target recognition. Signal processing translates the raw collected signals into spare cloud points. These points are merged into several clusters, each representing a single target in three-dimensional space. Target tracking estimates the new location of each detected target. A novel convolutional neural network model was designed to extract and recognize the features of drone and non-drone targets. For the performance evaluation, a dataset collected with an IWR6843ISK mmWave sensor by Texas Instruments was used for training and testing the convolutional neural network. The proposed recognition model achieved accuracies of 98.4% and 98.1% for one and two targets, respectively.
Solving Some Integral and Fractional Differential Equations via Neutrosophic Pentagonal Metric Space
Authors: Mani Gunaseelan , Subbarayan Poornavel , Mitrović Zoran D. , Aloqaily Ahmad , Mlaiki Nabil
Published: August 2023

In this paper, we first introduce the notion of neutrosophic pentagonal metric space. We prove several interesting results for some classes contraction mappings and prove some fixed point theorems in neutrosophic pentagonal metric space. Finally, we prove the uniqueness and existence of the integral equation and fractional differential equation to support our main result.
The Application of Cellulose Nanofibrils in Energy Systems
Authors: Li Ruoyu , Tian Dong , Chen Lei , Zhuang Bocheng , Feng Hui , Li Qiang , Yu Lianghao , Ling Yihan
Published: August 2023

Nanocellulose has emerged as a highly promising and sustainable nanomaterial due to its unique structures, exceptional properties, and abundance in nature. In this comprehensive review, we delve into current research activities focused on harnessing the potential of nanocellulose for advanced electrochemical energy storage applications. We commence with a brief introduction to the structural features of cellulose nanofibers found within the cellulose resources’ cell walls. Subsequently, we explore various processes that have been investigated for utilizing cellulose in the realm of energy storage. In contrast to traditional binders, we place significant emphasis on the utilization of solid electrolytes and 3D printing techniques. Additionally, we examine different application areas, including supercapacitors, lithium-ion batteries, and Zn-ion batteries. Within this section, our primary focus lies in integrating nanocellulose with other active materials to develop flexible substrates such as films and aerogels. Lastly, we present our perspectives on several key areas that require further exploration in this dynamic research field in the future.
Recent Progress and Prospects in Liquid Cooling Thermal Management System for Lithium-Ion Batteries
Authors: Liu Jiahao , Chen Hao , Huang Silu , Jiao Yu , Chen Mingyi
Published: August 2023

The performance of lithium-ion batteries is closely related to temperature, and much attention has been paid to their thermal safety. With the increasing application of the lithium-ion battery, higher requirements are put forward for battery thermal management systems. Compared with other cooling methods, liquid cooling is an efficient cooling method, which can control the maximum temperature and maximum temperature difference of the battery within an acceptable range. This article reviews the latest research in liquid cooling battery thermal management systems from the perspective of indirect and direct liquid cooling. Firstly, different coolants are compared. The indirect liquid cooling part analyzes the advantages and disadvantages of different liquid channels and system structures. Direct cooling summarizes the different systems’ differences in cooling effectiveness and energy consumption. Then, the combination of liquid cooling, air cooling, phase change materials, and heat pipes is examined. Later, the connection between the cooling and heating functions in the liquid thermal management system is considered. In addition, from a safety perspective, it is found that liquid cooling can effectively manage thermal runaway. Finally, some problems are put forward, and a summary and outlook are given.
The Progress in Bioprinting and Its Potential Impact on Health-Related Quality of Life
Authors: Yaneva Antoniya , Shopova Dobromira , Bakova Desislava , Mihaylova Anna , Kasnakova Petya , Hristozova Maria , Semerdjieva Maria
Published: August 2023

The intensive development of technologies related to human health in recent years has caused a real revolution. The transition from conventional medicine to personalized medicine, largely driven by bioprinting, is expected to have a significant positive impact on a patient’s quality of life. This article aims to conduct a systematic review of bioprinting’s potential impact on health-related quality of life. A literature search was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive literature search was undertaken using the PubMed, Scopus, Google Scholar, and ScienceDirect databases between 2019 and 2023. We have identified some of the most significant potential benefits of bioprinting to improve the patient’s quality of life: personalized part production; saving millions of lives; reducing rejection risks after transplantation; accelerating the process of skin tissue regeneration; homocellular tissue model generation; precise fabrication process with accurate specifications; and eliminating the need for organs donor, and thus reducing patient waiting time. In addition, these advances in bioprinting have the potential to greatly benefit cancer treatment and other research, offering medical solutions tailored to each individual patient that could increase the patient’s chance of survival and significantly improve their overall well-being. Although some of these advancements are still in the research stage, the encouraging results from scientific studies suggest that they are on the verge of being integrated into personalized patient treatment. The progress in bioprinting has the power to revolutionize medicine and healthcare, promising to have a profound impact on improving the quality of life and potentially transforming the field of medicine and healthcare.
Deep Learning-Based Recognition of Periodontitis and Dental Caries in Dental X-ray Images
Authors: Chen Ivane Delos Santos , Yang Chieh-Ming , Chen Mei-Juan , Chen Ming-Chin , Weng Ro-Min , Yeh Chia-Hung
Published: August 2023

Dental X-ray images are important and useful for dentists to diagnose dental diseases. Utilizing deep learning in dental X-ray images can help dentists quickly and accurately identify common dental diseases such as periodontitis and dental caries. This paper applies image processing and deep learning technologies to dental X-ray images to propose a simultaneous recognition method for periodontitis and dental caries. The single-tooth X-ray image is detected by the YOLOv7 object detection technique and cropped from the periapical X-ray image. Then, it is processed through contrast-limited adaptive histogram equalization to enhance the local contrast, and bilateral filtering to eliminate noise while preserving the edge. The deep learning architecture for classification comprises a pre-trained EfficientNet-B0 and fully connected layers that output two labels by the sigmoid activation function for the classification task. The average precision of tooth detection using YOLOv7 is 97.1%. For the recognition of periodontitis, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve is 98.67%, and the AUC of the precision-recall (PR) curve is 98.38%. For the recognition of dental caries, the AUC of the ROC curve is 98.31%, and the AUC of the PR curve is 97.55%. Different from the conventional deep learning-based methods for a single disease such as periodontitis or dental caries, the proposed approach can provide the recognition of both periodontitis and dental caries simultaneously. This recognition method presents good performance in the identification of periodontitis and dental caries, thus facilitating dental diagnosis.
Encrypt with Your Mind: Reliable and Revocable Brain Biometrics via Multidimensional Gaussian Fitted Bit Allocation
Authors: Li Ming , Qi Yu , Pan Gang
Published: August 2023

Biometric features, e.g., fingerprints, the iris, and the face, have been widely used to authenticate individuals. However, most biometrics are not cancellable, i.e., once these biometric features are cloned or stolen, they cannot be replaced easily. Unlike traditional biometrics, brain biometrics are extremely difficult to clone or forge due to the natural randomness across different individuals, which makes them an ideal option for identity authentication. Most existing brain biometrics are based on electroencephalogram (EEG), which is usually demonstrated unstable performance due to the low signal-to-noise ratio (SNR). For the first time, we propose the use of intracortical brain signals, which have higher resolution and SNR, to realize the construction of the high-performance brain biometrics. Specifically, we put forward a novel brain-based key generation approach called multidimensional Gaussian fitted bit allocation (MGFBA). The proposed MGFBA method extracts keys from the local field potential of ten rats with high reliability and high entropy. We found that with the proposed MGFBA, the average effective key length of the brain biometrics was 938 bits, while achieving high authentication accuracy of 88.1% at a false acceptance rate of 1.9%, which is significantly improved compared to conventional EEG-based approaches. In addition, the proposed MGFBA-based keys can be conveniently revoked using different motor behaviors with high entropy. Experimental results demonstrate the potential of using intracortical brain signals for reliable authentication and other security applications.
Hypoxic State of Cells and Immunosenescence: A Focus on the Role of the HIF Signaling Pathway
Authors: Troise Dario , Infante Barbara , Mercuri Silvia , Netti Giuseppe Stefano , Ranieri Elena , Gesualdo Loreto , Stallone Giovanni , Pontrelli Paola
Published: August 2023

Hypoxia activates hypoxia-related signaling pathways controlled by hypoxia-inducible factors (HIFs). HIFs represent a quick and effective detection system involved in the cellular response to insufficient oxygen concentration. Activation of HIF signaling pathways is involved in improving the oxygen supply, promoting cell survival through anaerobic ATP generation, and adapting energy metabolism to meet cell demands. Hypoxia can also contribute to the development of the aging process, leading to aging-related degenerative diseases; among these, the aging of the immune system under hypoxic conditions can play a role in many different immune-mediated diseases. Thus, in this review we aim to discuss the role of HIF signaling pathways following cellular hypoxia and their effects on the mechanisms driving immune system senescence.
Pharmacometabolomic Approach to Investigate the Response to Metformin in Patients with Type 2 Diabetes: A Cross-Sectional Study
Authors: Naja Khaled , Anwardeen Najeha , Al-Hariri Moustafa , Al Thani Asmaa A. , Elrayess Mohamed A.
Published: August 2023

Metformin constitutes the foundation therapy in type 2 diabetes (T2D). Despite its multiple beneficial effects and widespread use, there is considerable inter-individual variability in response to metformin. Our objective is to identify metabolic signatures associated with poor and good responses to metformin, which may improve our ability to predict outcomes for metformin treatment. In this cross-sectional study, clinical and metabolic data for 119 patients with type 2 diabetes taking metformin were collected from the Qatar Biobank. Patients were empirically dichotomized according to their HbA1C levels into good and poor responders. Differences in the level of metabolites between these two groups were compared using orthogonal partial least square discriminate analysis (OPLS-DA) and linear models. Good responders showed increased levels of sphingomyelins, acylcholines, and glutathione metabolites. On the other hand, poor responders showed increased levels of metabolites resulting from glucose metabolism and gut microbiota metabolites. The results of this study have the potential to increase our knowledge of patient response variability to metformin and carry significant implications for enabling personalized medicine.
Electrochemical Impedance Spectroscopy-Based Sensing of Biofilms: A Comprehensive Review
Authors: Ameer Sikander , Ibrahim Hussam , Yaseen Muhammad Usama , Kulsoom Fnu , Cinti Stefano , Sher Mazhar
Published: August 2023

Biofilms are complex communities of microorganisms that can form on various surfaces, including medical devices, industrial equipment, and natural environments. The presence of biofilms can lead to a range of problems, including infections, reduced efficiency and failure of equipment, biofouling or spoilage, and environmental damage. As a result, there is a growing need for tools to measure and monitor levels of biofilms in various biomedical, pharmaceutical, and food processing settings. In recent years, electrochemical impedance sensing has emerged as a promising approach for real-time, non-destructive, and rapid monitoring of biofilms. This article sheds light on electrochemical sensing for measuring biofilms, including its high sensitivity, non-destructive nature, versatility, low cost, and real-time monitoring capabilities. We also discussed some electrochemical sensing applications for studying biofilms in medical, environmental, and industrial settings. This article also presents future perspectives for research that would lead to the creation of reliable, quick, easy-to-use biosensors mounted on unmanned aerial vehicles (UAVs), and unmanned ground vehicles (UGVs), utilizing artificial intelligence-based terminologies to detect biofilms.
The Role of circTmeff-1 in Morphine Addiction Memory of Mice
Authors: Yu Hailei , Wen Boyang , Lu Yun , Xie Bing , Yu Feng , Zhang Minglong , Ma Chunling , Cong Bin , Wen Di , Bi Haitao
Published: August 2023

In addition to the essential pharmacological effects of opioids, situational cues associated with drug addiction memory are key triggers for drug seeking. CircRNAs, an emerging hotspot regulator in crown genetics, play an important role in central nervous system-related diseases. However, the internal mediating mechanism of circRNAs in the field of drug reward and addiction memory remains unknown. Here, we trained mice on a conditional place preference (CPP) model and collected nucleus accumbens (NAc) tissues from day 1 (T0) and day 8 (T1) for high-throughput RNA sequencing. QRT-PCR analysis revealed that circTmeff-1 was highly expressed in the NAc core but not in the NAc shell, suggesting that it plays a role in addiction memory formation. Meanwhile, the down-regulation of circTmeff-1 by adeno-associated viruses in the NAc core or shell could inhibit the morphine CPP scores. Subsequently, the GO and KEGG analyses indicated that circTmeff-1 might regulate the addiction memory via the MAPK and AMPK pathways. These findings suggest that circTmeff-1 in NAc plays a crucial role in morphine-dependent memory formation.
A Longitudinal Investigation on the Effects of Sodium and Potassium Intake on the Development of Hypertension and Abdominal Obesity from Childhood to Young Adulthood amongst Ellisras Rural Population, South Africa
Authors: Raphadu Thato Tshepo , Mphekgwana Peter Modupi , Matshipi Moloko , Monyeki Kotsedi Daniel
Published: August 2023

Background: Hypertension (HT) and obesity have both been on the rise in children. Each is associated with an increase in cardiovascular disease risk, and both track into adulthood. Objectives: This study aimed to identify the association of sodium intake (Na), potassium (K) intake, and sodium-to-potassium (Na/K) ratio with the development of HT and abdominal obesity amongst the Ellisras rural population over time. Methods: In this longitudinal study, data on dietary intake of Na and K were collected using a 24 h recall questionnaire from a total of 325 participants tracked from 1999 (5–12 years), 2001 (7–14 years), and 2015 (18–30 years). The averages of Na and K intake were analysed using local food tables and the South African Food Composition Database System (SAFOODS). In addition, blood pressure (BP) and anthropometric measurements (waist circumference (WC) and height) were also examined. Parametric (independent t-test) and Chi-square/Fishers exact tests were conducted to determine the difference between the years for numerical data and categorical variables. A generalised estimating equation (GEE) was used to assess the association of Na intake, K intake and their ratio on BP, WC, and waist-to-height ratio (WHtR). Results: Our results indicate a significant positive association between K intake and WHtR, and even though the model was adjusted for age and sex, there was still an association with WHtR. The Na/K ratio was associated with both BP measurements and abdominal obesity, respectively. Furthermore, Na/K was shown to be associated with an increased risk of developing HT and abdominal obesity. Conclusions: In our study, we observed that an increase in the Na/K ratio is a predictor of HT and abdominal obesity over time compared to Na and K alone. However, more studies are required to further prove this.
Heart Rate Variability Analysis of Healthy Individuals and Patients with Ischemia and Arrhythmia
Authors: Georgieva-Tsaneva Galya , Gospodinova Evgeniya
Published: August 2023

This article presents the results of a study of the cardiac activity of patients diagnosed with arrhythmia and ischemic heart disease. The obtained results were compared with the results obtained from a healthy control group. The studies were conducted on long-term cardiac recordings (approximately 24 h) registered by means of Holter monitoring, and the observations were made in the daily activities of the individuals. All processing, analysis and evaluations on the registered signals were performed by means of an established information demonstration cardiology system. The mathematical analysis included linear, non-linear and graphical methods for estimating and analyzing heart rate variability (HRV). Re-examinations were carried out on some of the observed individuals after six months of treatment. The results show an increase in the main time domain parameters of the HRV, such as the SDNN (from 86.36 ms to 95.47 ms), SDANN (from 74.05 ms to 82.14 ms), RMSSD (from 5.1 ms to 6.92 ms), SDNN index (from 52.4 to 58.91) and HRVTi (from 12.8 to 16.83) in patients with ischemia. In patients with arrhythmia, there were increases in the SDNN (from 88.4 ms to 96.44 ms), SDANN (from 79.12 ms to 83.23 ms), RMSSD (from 6.74 ms to 7.31 ms), SDNN index (from 53.22 to 59.46) and HRVTi (from 16.2 to 19.42). An increase in the non-linear parameter α (from 0.83 to 0.85) was found in arrhythmia; and in α (from 0.80 to 0.83), α1 (from 0.88 to 0.91) and α2 (from 0.86 to 0.89) in ischemia. The presented information system can serve as an auxiliary tool in the diagnosis and treatment of cardiovascular diseases.
Eosinophilic Cholecystitis and Eosinophils in Gallbladder Injuries: A Clinicopathological Analysis of 1050 Cholecystectomies
Authors: Memis Bahar , Saka Burcu , Roa Juan Carlos , Bandyopadhyay Sudeshna , Reid Michelle , Bagci Pelin , Aktas Berk Kaan , Armutlu Ayse , Basturk Olca , Adsay N. Volkan
Published: August 2023

“Eosinophilic cholecystitis” has been an elusive concept. Around 1050 consecutive cholecystectomies with chronic (CC, n = 895), subacute (SAC, n = 100), and acute cholecystitis (AC, n = 55) were reviewed for eosinophilic infiltration. Eosinophilic hot spots (>40 eosinophils/HPF) were seen in 63% of SAC and 35% of AC (vs. 6% of CC, p < 0.001). Eosinophils were mostly encountered in areas of wall thickening, revealing edema with early collagenization and young tissue-culture-type fibroblasts. However, in ten chronic cholecystitis patients (<1%), prominent eosinophilia with eosinophil-rich foci (>100 eosinophils/HPF) was noted. These ten cases, classified as “eosinophilic cholecystitis”, were analyzed further: The patients were relatively young (mean age = 43 years), with a 9:1 female:male ratio. None had blood eosinophilia/eosinophilia syndromes. Although one had ulcerative colitis, others did not have any autoimmune diseases. The mean gallbladder wall thickness was 3.5 mm (vs. 4.2 mm in ordinary CC). In conclusion, eosinophils are a part of especially subacute injuries in the gallbladder. They are typically condensed in the areas of healing and appear to signify a distinctive state of injury in which there are erosions leading to slow/sustained exposure of the mural tissues to the bile contents that induce chemical injury/recruit eosinophils. Eosinophilic cholecystitis is a very uncommon occurrence and appears to be an exaggerated response in allergic patients who are prone to recruit eosinophils in reaction to injury.
Eliminating Vertical Transmission of HIV in South Africa: Establishing a Baseline for the Global Alliance to End AIDS in Children
Authors: Haeri Mazanderani Ahmad F. , Murray Tanya Y. , Johnson Leigh F. , Ntloana Mathilda , Silere-Maqetseba Tabisa , Guo Sufang , Sherman Gayle G.
Published: August 2023

To gain a detailed overview of vertical transmission in South Africa, we describe insights from the triangulation of data sources used to monitor the national HIV program. HIV PCR results from the National Health Laboratory Service (NHLS) were analysed from the National Institute of Communicable Diseases (NICD) data warehouse to describe HIV testing coverage and positivity among children <2 years old from 2017–2021. NICD data were compared and triangulated with the District Health Information System (DHIS) and the Thembisa 4.6 model. For 2021, Thembisa estimates a third of children living with HIV go undiagnosed, with NICD and DHIS data indicating low HIV testing coverage at 6 months (49%) and 18 months (33%) of age, respectively. As immunisation coverage is reported at 84% and 66% at these time points, better integration of HIV testing services within the Expanded Programme for Immunization is likely to yield improved case findings. Thembisa projects a gradual decrease in vertical transmission to 450 cases per 100,000 live births by 2030. Unless major advances and strengthening of maternal and child health services, including HIV prevention, diagnosis, and care, can be achieved, the goal to end AIDS in children by 2030 in South Africa is unlikely to be realised.
Research Progress of Neural Synapses Based on Memristors
Authors: Li Yamin , Su Kang , Chen Haoran , Zou Xiaofeng , Wang Changhong , Man Hongtao , Liu Kai , Xi Xin , Li Tuo
Published: August 2023

The memristor, characterized by its nano-size, nonvolatility, and continuously adjustable resistance, is a promising candidate for constructing brain-inspired computing. It operates based on ion migration, enabling it to store and retrieve electrical charges. This paper reviews current research on synapses using digital and analog memristors. Synapses based on digital memristors have been utilized to construct positive, zero, and negative weights for artificial neural networks, while synapses based on analog memristors have demonstrated their ability to simulate the essential functions of neural synapses, such as short-term memory (STM), long-term memory (LTM), spike-timing-dependent plasticity (STDP), spike-rate-dependent plasticity (SRDP), and paired-pulse facilitation (PPF). Furthermore, synapses based on analog memristors have shown potential for performing advanced functions such as experiential learning, associative learning, and nonassociative learning. Finally, we highlight some challenges of building large-scale artificial neural networks using memristors.
Artificial Intelligence Methods for Analysis and Optimization of CHP Cogeneration Units Based on Landfill Biogas as a Progress in Improving Energy Efficiency and Limiting Climate Change
Authors: Gaska Krzysztof , Generowicz Agnieszka , Gronba-Chyła Anna , Ciuła Józef , Wiewiórska Iwona , Kwaśnicki Paweł , Mala Marcin , Chyła Krzysztof
Published: August 2023

Combined heat and power generation is the simultaneous conversion of primary energy (in the form of fuel) in a technical system into useful thermal and mechanical energy (as the basis for the generation of electricity). This method of energy conversion offers a high degree of efficiency (i.e., very efficient conversion of fuel to useful energy). In the context of energy system transformation, combined heat and power (CHP) is a fundamental pillar and link between the volatile electricity market and the heat market, which enables better planning. This article presents an advanced model for the production of fuel mixtures based on landfill biogas in the context of energy use in CHP units. The search for optimal technological solutions in energy management requires specialized domain-specific knowledge which, using advanced algorithmic models, has the potential to become an essential element in real-time intelligent ICT systems. Numerical modeling makes it possible to build systems based on the knowledge of complex systems, processes, and equipment in a relatively short time. The focus was on analyzing the applicability of algorithmic models based on artificial intelligence implemented in the supervisory control systems (SCADA-type systems including Virtual SCADA) of technological processes in waste management systems. The novelty of the presented solution is the application of predictive diagnostic tools based on multithreaded polymorphic models, supporting making decisions that control complex technological processes and objects and solving the problem of optimal control for intelligent dynamic objects with a logical representation of knowledge about the process, the control object, and the control, for which the learning process consists of successive validation and updating of knowledge and using the results of this updating to determine control decisions.