bluuebunny/crossref_metadata_2025 huggingface dataset:
EspB and HtpG interact with the type III-A CRISPR/Cas system of Mycobacterium tuberculosis
Authors: Shi Mingmin , Zhang Hongtai , Fleming Joy , Wei Wenjing , Chen Hong , Dai Xiaowei , Liu Yi , Li Chuanyou , Ran Fanlei , Wu Zhilong , Wang Yaguo , Zhang Xilin , Zhang Huizhi , Bi Lijun
Published: November 2023

Introduction:Mycobacterium tuberculosis (MTB) has a type III-A clustered regularly interspaced short palindromic repeat/CRISPR-associated protein (CRISPR/Cas) system consisting of a Csm1-5 and CRISPR RNA (crRNA) complex involved in the defense against invading nucleic acids. However, CRISPR/Cas system in the MTB still is clearly unknown and needs to be further explored.

Methods: In our work, two non-Cas system proteins EspB and HtpG protein were found and identified by LC-MS/MS. The effect of EspB and HtpG on Type III-A CRISPR/Cas System of M. tuberculosis was examined by using Plasmid interference assay and Co-immunoprecipitation analyses. We explored that EspB could interact with the crRNA RNP complex, but HtpG could inhibit the accumulation of the MTB Csm proteins and defense the mechanism of CRISPR/Cas system.

Results: The proteins ESAT-6 secretion system-1(Esx-1) secreted protein B (EspB) and high-temperature protein G (HtpG), which were not previously associated with CRISPR/Cas systems, are involved in mycobacterial CRISPR/Cas systems with distinct functions.

Conclusion: EspB is a novel crRNA-binding protein that interacts directly with the MTB crRNP complex. Meanwhile, HtpG influences the accumulation of MTB Csm proteins and EspB and interferes with the defense mechanism of the crRNP complex against foreign DNA in vivo. Thereby, our study not only leads to developing more precise clinical diagnostic tool to quickly detect for MTB infection, but also knows these proteins merits for TB biomarkers/vaccine candidates.
Development of automated patch clamp assays to overcome the burden of variants of uncertain significance in inheritable arrhythmia syndromes
Authors: Ma Joanne G. , Vandenberg Jamie I. , Ng Chai-Ann
Published: November 2023

Advances in next-generation sequencing have been exceptionally valuable for identifying variants in medically actionable genes. However, for most missense variants there is insufficient evidence to permit definitive classification of variants as benign or pathogenic. To overcome the deluge of Variants of Uncertain Significance, there is an urgent need for high throughput functional assays to assist with the classification of variants. Advances in parallel planar patch clamp technologies has enabled the development of automated high throughput platforms capable of increasing throughput 10- to 100-fold compared to manual patch clamp methods. Automated patch clamp electrophysiology is poised to revolutionize the field of functional genomics for inheritable cardiac ion channelopathies. In this review, we outline i) the evolution of patch clamping, ii) the development of high-throughput automated patch clamp assays to assess cardiac ion channel variants, iii) clinical application of these assays and iv) where the field is heading.
Development and validation of Child-Friendly School Environment Questionnaire from Chinese culture
Authors: Xiao Erping , Sun Mengju , Lv Kexin , Zhu Xinyi , Jia Wenbin
Published: November 2023

In the context of building Child-Friendly Cities in China, child-friendly school environments are considered as having a profound impact on children’s development and growth. This study presents the development and validation of the Child-Friendly School Environment Questionnaire for assessing a child-friendly school environment. Utilizing open-ended questions and interviews, an initial questionnaire on the child-friendly school environment was compiled. An exploratory factor analysis of the preliminary test results with 696 primary school children in grades three to six was conducted to refine the questionnaire into a formal 19-item questionnaire. Subsequently, a confirmatory factor analysis was performed to analyze the evaluation results of 807 primary school children in grades three to six. The results indicated that a child-friendly school environment is a multi-dimensional construct encompassing Environment Friendly, Teaching Friendly, Peer Friendly, and Children Participation, with good reliability and validity. The promising outcomes of this study suggest that the Child-Friendly School Environment Questionnaire can be widely used as a powerful evaluation tool for the child-friendly school education practice in the future.
Distinguishing infectivity in patients with pulmonary tuberculosis using deep learning
Authors: Gao Yi , Zhang Yiwen , Hu Chengguang , He Pengyuan , Fu Jian , Lin Feng , Liu Kehui , Fu Xianxian , Liu Rui , Sun Jiarun , Chen Feng , Yang Wei , Zhou Yuanping
Published: November 2023

Introduction

This study aimed to develop and assess a deep-learning model based on CT images for distinguishing infectivity in patients with pulmonary tuberculosis (PTB).

Methods

We labeled all 925 patients from four centers with weak and strong infectivity based on multiple sputum smears within a month for our deep-learning model named TBINet's training. We compared TBINet's performance in identifying infectious patients to that of the conventional 3D ResNet model. For model explainability, we used gradient-weighted class activation mapping (Grad-CAM) technology to identify the site of lesion activation in the CT images.

Results

The TBINet model demonstrated superior performance with an area under the curve (AUC) of 0.819 and 0.753 on the validation and external test sets, respectively, compared to existing deep learning methods. Furthermore, using Grad-CAM, we observed that CT images with higher levels of consolidation, voids, upper lobe involvement, and enlarged lymph nodes were more likely to come from patients with highly infectious forms of PTB.

Conclusion

Our study proves the feasibility of using CT images to identify the infectivity of PTB patients based on the deep learning method.
Reconnection in a pinch
Authors: Moore T. E. , Burch J. L. , Wendel D. E.
Published: November 2023

A recently published analysis of current sheets has updated the classic Harris 1D static solution by considering multiple classes of charged particle trajectories in a generalized and dynamic current sheet. It uses a 1D PIC simulation to describe dynamic pinching and bifurcation of the current sheet. These 1D results strongly suggest that properties of the inflowing plasma, including the plasma beta, have an important effect on the equilibrium thickness of the pinched current sheet. Since 1D studies cannot describe magnetic reconnection, the time appears right to carry such 1D studies over to 2D or 3D simulations to explore current sheet thickness effects on reconnection. The Magnetospheric Multiscale Mission (MMS), with its well-resolved multipoint measurements of collisionless plasma and fields, has found that collisionless reconnection is accompanied by non-adiabatic motions of electrons that only occur in magnetic structures with a narrow scale comparable to electron inertial lengths (de). The recent 1D studies suggest that a plasma pinch to such scales may only occur for inflowing magnetized plasmas with relatively low plasma beta. We conclude that a parametric exploration of simulated and observed reconnection inflow conditions, particularly plasma beta, should shed light on the enablement of reconnection in collisionless plasmas.
Critical Sample-Size Analysis for Uncertainty Aerodynamic Evaluation of Compressor Blades with Stagger-Angle Errors
Authors: Wang Haohao , Gao Limin , Wu Baohai
Published: November 2023

Many probability-based uncertainty quantification (UQ) schemes require a large amount of sampled data to build credible probability density function (PDF) models for uncertain parameters. Unfortunately, the amounts of data collected as to compressor blades of aero-engines are mostly limited due to the expensive and time-consuming tests. In this paper, we develop a preconditioner-based data-driven polynomial chaos (PDDPC) method that can efficiently deal with uncertainty propagation of limited amounts of sampled data. The calculation accuracy of a PDDPC method is closely related to the sample size of collected data. Therefore, the influence of sample size on this PDDPC method is investigated using a nonlinear test function. Subsequently, we consider the real manufacturing errors in stagger angles for compressor blades. Under three different operating conditions, the PDDPC method is applied to investigate the effect of stagger-angle error on UQ results of multiple aerodynamic parameters of a two-dimensional compressor blade. The results show that as the sample-size of measured data increases, UQ results regarding aerodynamic performance obtained by the PDDPC method gradually converge. There exists a critical sample size that ensures accurate UQ analysis of compressor blades. The probability information contained in the machining error data is analyzed through Kullback–Leibler divergence, and the critical sample size is determined. The research results can serve as a valuable reference for the fast and cheap UQ analysis of compressor blades in practical engineering.
Numerical Simulation on Primary Breakup Characteristics of Liquid Jet in Oscillation Crossflow
Authors: Zhang Tao , Song Xinyu , Kai Xingping , He Yeguang , Li Rundong
Published: November 2023

In order to understand the breakup characteristics of a transverse liquid jet flow in an actual combustion chamber, a numerical study was conducted using the Volume of Fluid (VOF) method combined with grid adaptation technology. The study focused on the primary breakup characteristics of liquid jets under the conditions of a steady and oscillating air crossflow. The simulated mediums were set to water and air. The research findings revealed that fluctuations in the incoming gas velocity can influence the development speed of surface waves and the mode of jet breakup during the initial stage of jet development as compared to the steady condition. In both conditions, the surface waves were initially observed to appear within 1/4 T–2/4 T. The surface wave of the jet develops faster under steady conditions because the average velocity of the steady flow is higher than that of the oscillation flow during this stage. As a result, the fragmentation of the jet is primarily influenced by the surface wave. Under an oscillating flow, the rear of the jet begins to break up earlier due to the slower development of surface waves. The velocity of the oscillating air inflow increases over time, and the speed of surface wave development also increases, gradually leading to the dominance of surface-wave-induced jet breakup. In the second stage of air inflow oscillation, an “up and down slapping” phenomenon occurs at the tail of the jet. Additionally, increasing the air inflow velocity leads to a longer jet breakup length and a higher number of droplets near the jet column. Surface waves are observed on both the windward and leeward sides of the jet. The penetration depth of the jet fluctuates with changes in the crossflow velocity, and the response of the jet penetration depth to the velocity fluctuations in the transverse air is delayed by half a period.
Design of In-Orbit Sample Container Transfer Mechanism for Chang’E-5 Lunar Sample Return Mission
Authors: Wang Weijun , Cui Yuxin , Qi Chenkun , Cao Yanyan , Zhang Yuhua , Zhang Chongfeng , Wang Shigang
Published: November 2023

In this paper, a pawl composite linkage transfer mechanism is designed for the automatic in-orbit sample transfer mission of Chang’E-5 lunar sample return mission, which can realize the sample container in-orbit transfer under various critical constraints such as lightweight, miniaturization, and narrow working space. Resistance during the whole process as well as the sensitive factors that affect the resistance during the sample container transfer process are investigated and designed. The sample container transfer process has been verified by the test system on the ground, indicating that the design can satisfy the requirements of the sample transfer mission. The developed transfer mechanism completed the Chang’E-5 sample return mission successfully with good consistency between space and ground, verifying the correctness and effectiveness of the design.
A Dynamic Air Combat Situation Assessment Model Based on Situation Knowledge Extraction and Weight Optimization
Authors: Xi Zhifei , Kou Yingxin , Li You , Li Zhanwu , Lv Yue
Published: November 2023

Air combat situation assessment is the basis of target assignment and maneuver decisions. The current air combat situation assessment models, whether nonparametric or parametric, ignore the continuity and timing of situation changes, making the situation assessment results lose tactical significance. Aimed at the shortcomings of current air combat situation assessment, a dynamic air combat situation assessment model based on situation knowledge extraction and weight optimization was proposed by combining a multiple regression model of hidden logic process, a weight optimization model based on grey prospect theory, a weight mapping model based on autoencoder and extreme learning machine (AE-ELM) and an air combat situation characteristic parameter prediction model based on dynamic weight online extreme learning machine (DWOSELM). Firstly, considering the timing and continuity of air combat situation change, a hidden logic process multiple regression model was introduced to realize the segmentation of air combat situation time series data and the extraction of air combat situation primitives. Secondly, the weight optimization method based on grey prospect theory was used to obtain the weight of the evaluation index under different air combat situations. On this basis, the dynamic mapping model between air combat situation characteristic parameters and the weight of index was constructed by using AE-ELM. Then, the dynamic weighted extreme learning machine was used to build the target maneuver trajectory prediction model, and the future position information of the target was predicted. On this basis, the future situation information between the enemy and us was obtained. Finally, the time weight calculation model based on normal cumulative distribution was used to determine the importance of the situation at each time. The situation information at multiple times in the air combat process was fused to obtain the comprehensive air combat situation assessment results at the current time. The simulation results show that the model can fully exploit the influence of historical information, effectively integrate the air combat situation information at multiple moments, and generate the air combat situation assessment results with practical tactical significance according to the individual differences of different pilots.
Rumen Solubility of Copper, Manganese and Zinc and the Potential Link between the Source and Rumen Function: A Systematic Review
Authors: Vigh Antal , Criste Adriana Dalila , Corcionivoschi Nicolae , Gerard Christine
Published: November 2023

The dietary inclusion of trace minerals (TMs), such as copper (Cu), manganese (Mn) and zinc (Zn), is of importance to cover the ever-evolving requirements for growth, production and reproduction in ruminants. Various sources of TMs are commercially available, such as inorganic (ITM), organic (OTM) or hydroxy (HTM) forms; however, their bioavailability and efficiency to improve ruminant zootechnical parameters may be highly influenced by ruminal solubility and effects on the rumen environment. The objective of this review was to compile the most up-to-date information on the ruminal solubility of ITMs, OTMs and HTMs and their effects on fermentation parameters and rumen microbiota, aiming to support specialists from the animal feed industry when choosing TM products for ruminant supplementation. Some commonly used ITM sources, like sulfates, have a high ruminal solubility, while oxides are less soluble. The ruminal solubility of OTMs is mostly found to be high; however, data on these TM forms are still lacking. Regarding HTMs, ruminal solubility is reported to be low; nevertheless, results are inconsistent. Considering rumen fermentation, ITMs show a negative effect, OTMs might improve, while HTMs do not affect parameters like dry matter degradability, volatile fatty acid production, pH or microbial protein synthesis. As for rumen microbiota, ITMs do not affect microbial populations; OTMs could decrease the abundance of some specific bacteria, like fibrolytic microorganisms, while studies with HTMs are missing or inconclusive. Further research is necessary to better understand the ruminal solubility kinetics of TM sources and the different interactions with fermentation parameters and rumen microbiota to successfully apply the precision TM supplementation of ruminants, tackling deficiency occurrences.
Design and Experiment of a Breakpoint Continuous Spraying System for Automatic-Guidance Boom Sprayers
Authors: Li Chengqian , Wu Jianguo , Pan Xiaoyong , Dou Hanjie , Zhao Xueguan , Gao Yuanyuan , Yang Shuo , Zhai Changyuan
Published: November 2023

Repeated and missed spraying are common problems during the working of boom sprayers, especially in the breakpoint continuous process. Therefore, the present study investigated a breakpoint continuous spraying system for automatic-guidance boom sprayers based on a hysteresis compensation algorithm for spraying. An operational breakpoint identification algorithm, which combines a real-time kinematic global navigation satellite system (RTK-GNSS) and wheel odometer, was proposed; a pre-adjusted proportional-integral-derivative (PID) control algorithm for the opening degree of the proportional control valve was designed in thus study. Tests were conducted to establish equations correlating the opening degree of the proportional control valve, pump output flow rate, and main pipeline flow rate, with an R2 ≥ 0.9525. The time to adjust to the target flow rate was experimentally tested. The breakpoint identification accuracy of the RTK-GNSS and RTK-GNSS + wheel odometer was experimentally assessed. A field spraying deposition variation experiment was conducted. According to the results, the system effectively eliminated missed spraying, with a maximum repeated spraying distance of ≤3.3 m, and it achieved a flow control error within 3%. This system also reduced the repeated spraying area and enhanced the pesticide spraying quality of breakpoint continuous spraying for automatic-guidance boom sprayers.
Analysis of Resistance Gene Diversity in the Intestinal Microbiome of Broilers from Two Types of Broiler Farms in Hebei Province, China
Authors: Liang Chuncai , Wei Yujie , Wang Xiaolan , Gao Jinduo , Cui Huan , Zhang Cheng , Liu Juxiang
Published: November 2023

The crucial reservoir of antibiotic resistance genes (ARGs) within the chicken intestinal microbiome poses a serious threat to both animal and human health. In China, the overuse of antibiotics has significantly contributed to the proliferation of ARGs in the chicken intestinal microbiome, which is a serious concern. However, there has been relatively little research on the diversity of resistance genes in the chicken intestinal microbiome since the implementation of the National Pilot Work Program for Action to Reduce the Use of Veterinary Antimicrobial Drugs in China. The objective of this study was to analyze the diversity of antibiotic resistance genes carried by the chicken intestinal microbiome in both standard farms (SFs), which implement antibiotic reduction and passed national acceptance, and nonstandard farms (NSFs), which do not implement antibiotic reductions, in Hebei Province. Fresh fecal samples of broiler chickens were collected from SFs (n = 4) and NSF (n = 1) and analyzed using high-throughput qPCR technology. Our findings revealed that all five farms exhibited a wide range of highly abundant ARGs, with a total of 201 ARGs and 7 MGEs detected in all fecal samples. The dominant ARGs identified conferred resistance to aminoglycosides, macrolide-lincosamide-streptomycin B (MLSB), and tetracycline antibiotics. Cellular protection mechanisms were found to be the primary resistance mechanism for these ARGs. The analysis of the co-occurrence network demonstrated a significant positive correlation between the abundance of MGEs and ARGs. The SF samples showed a significantly lower relative abundance of certain ARGs than the NSF samples (p < 0.05). The results of this study show that the abundance of ARGs demonstrated a downward trend after the implementation of the National Pilot Work Program for Action to Reduce the Usage of Veterinary Antimicrobial Drugs in Hebei Province, China.
High Diversity but Monodominance of Multidrug-Resistant Bacteria in Immunocompromised Pediatric Patients with Acute Lymphoblastic Leukemia Developing GVHD Are Not Associated with Changes in Gut Mycobiome
Authors: Sardzikova Sara , Andrijkova Kristina , Svec Peter , Beke Gabor , Klucar Lubos , Minarik Gabriel , Bielik Viktor , Kolenova Alexandra , Soltys Katarina
Published: November 2023

Graft-versus-host disease (GvHD) is a severe complication after hematopoietic stem cell transplantation (HSCT). Our study focused on identifying multidrug-resistant (MDR) gut bacteria associated with GvHD-prone guts and association with gut microbiota (GM) diversity, bacteriome, and mycobiome composition in post-HSCT patients. We examined 11 pediatric patients with acute lymphoblastic leukemia (ALL), including six with GvHD, within three time points: seven days pre-HSCT, seven days post-, and 28 days post-HSCT. The gut microbiome and its resistome were investigated using metagenomic sequencing, taxonomically classified with Kraken2, and statistically evaluated for significance using appropriate tests. We observed an increase in the abundance of MDR bacteria, mainly Enterococcus faecium strains carrying msr(C), erm(T), aac(6′)-li, dfrG, and ant(6)-la genes, in GvHD patients one week post-HSCT. Conversely, non-GvHD patients had more MDR beneficial bacteria pre-HSCT, promoting immunosurveillance, with resistance genes increasing one-month post-HSCT. MDR beneficial bacteria included the anti-inflammatory Bacteroides fragilis, Ruminococcus gnavus, and Turicibacter, while most MDR bacteria represented the dominant species of GM. Changes in the gut mycobiome were not associated with MDR bacterial monodominance or GvHD. Significant α-diversity decline (Shannon index) one week and one month post-HSCT in GvHD patients (p < 0.05) was accompanied by increased Pseudomonadota and decreased Bacteroidota post-HSCT. Our findings suggest that MDR commensal gut bacteria may preserve diversity and enhance immunosurveillance, potentially preventing GvHD in pediatric ALL patients undergoing HSCT. This observation has therapeutic implications.
Extracellular Vesicles and Their Renin–Angiotensin Cargo as a Link between Metabolic Syndrome and Parkinson’s Disease
Authors: Pedrosa Maria A. , Labandeira Carmen M. , Lago-Baameiro Nerea , Valenzuela Rita , Pardo Maria , Labandeira-Garcia Jose Luis , Rodriguez-Perez Ana I.
Published: November 2023

Several studies showed an association between metabolic syndrome (MetS) and Parkinson’s disease (PD). The linking mechanisms remain unclear. MetS promotes low-grade peripheral oxidative stress and inflammation and dysregulation of the adipose renin–angiotensin system (RAS). Interestingly, brain RAS dysregulation is involved in the progression of dopaminergic degeneration and PD. Circulating extracellular vesicles (EVs) from MetS fat tissue can cross the brain–blood barrier and may act as linking signals. We isolated and characterized EVs from MetS and control rats and analyzed their mRNA and protein cargo using RT-PCR and the ExoView R200 platform, respectively. Furthermore, cultures of the N27 dopaminergic cell line and the C6 astrocytic cell line were treated with EVs from MetS rats. EVs were highly increased in MetS rat serum, which was inhibited by treatment of the rats with the angiotensin type-1-receptor blocker candesartan. Furthermore, EVs from MetS rats showed increased pro-oxidative/pro-inflammatory and decreased anti-oxidative/anti-inflammatory RAS components, which were inhibited in candesartan-treated MetS rats. In cultures, EVs from MetS rats increased N27 cell death and modulated C6 cell function, upregulating markers of neuroinflammation and oxidative stress, which were inhibited by the pre-treatment of cultures with candesartan. The results from rat models suggest EVs and their RAS cargo as a mechanism linking Mets and PD.
Preparation of Nanoemulgels Containing Lemon Essential Oil and Pectin: Physical Stability and Rheological Properties
Authors: Muñoz José , Alfaro-Rodríguez María-Carmen , Prieto-Vargas Paula , Lobo Carlos , Garcia María Carmen
Published: November 2023

Nanoemulgels are novel formulations of great interest for their use as dual-release systems and as fat substitutes in foods. Lemon essential oil, with a large number of benefits due to its antimicrobial, antifungal, and medicinal properties, and low methoxyl pectin, a natural polysaccharide capable of gelling by adding divalent ions such as calcium, are very appropriate ingredients to produce nanoemulgels with potential applications in industries such as cosmetics, agrochemistry, pharmaceuticals, or food. In this work, lemon-essential-oil-in-water nanoemulgels containing low methoxyl pectin derived from citrus peels were prepared following a three-step process that involves the preparation of a nanoemulsion, a pectin gel, and the mixture of both. In the first stage, the stirring time and the rotational rate employed during the mixing step were assessed. Once the preparation protocol was established, the pectin gel/nanoemulsion mass ratio was investigated. Different techniques were combined to evaluate the influence of the processing and the composition variables on the particle size distribution, mean diameters, flow curves, and physical stability of different emulgels obtained. It was found that the processing variables studied, stirring time, and rotational rate, do not influence the mean particle size of the emulgel, with values matching those of the starting nanoemulsion. However, 3 min and 200 rpm were selected for exhibiting the lowest TSI values. Regarding the composition, a higher content of pectin gel caused a higher viscosity, and therefore a higher physical stability, with the 75P/25E emulgel being the most stable. Aggregation of gel particles, because the pectin gel was really a sheared gel, was the main responsible contributor to the results obtained. This work highlights the importance of the preparation and formulation variables to develop stable, innovative formulations based on nanoemulgels.
Printing Information Modeling (PIM) for Additive Manufacturing of Concrete Structures
Authors: Peralta Abadia Patricia , Ahmad Muhammad E. , Smarsly Kay
Published: November 2023

In the context of Industry 4.0, construction processes are shifting towards automation by implementing additive manufacturing (AM) of concrete structures, also referred to as concrete printing. Adapting concrete as a printing material entails complex material–process interactions between concrete and manufacturing processes that require specialized data modeling. However, data modeling for the AM of concrete structures has not kept up with concrete printing research and development. Aiming to enhance data modeling for the AM of concrete structures, this paper proposes a semantic modeling approach, referred to as “printing information modeling” (PIM). The PIM approach defines input parameters and material–process interaction in a generic printing information model for designing and planning concrete printing projects. Exchange requirements for concrete printing are identified and evaluated, serving as the basis for the printing information model. The printing information model, as a semantic (or meta) model, is conceptualized using object-oriented modeling concepts, formalized as an ontology, verified as an instantiable semantic model, and validated with a software tool developed as a plug-in for BIM platforms. As a result, a printing information model is developed to serve as a generally valid semantic model for the AM of concrete structures and has the potential to improve data modeling concepts currently deployed for concrete printing.
An Experimental Evaluation of Path-Based Product Line Integration Testing and Test Coverage Metrics
Authors: Lee Jihyun
Published: November 2023

Product line testing is significant because any faults in a product line platform can lead to widespread impacts on multiple products configured from that platform within a product line. Due to the shared platform, certain testing can be repeatedly performed across different products, leading to unnecessary costs. To enhance quality and reduce costs in product line testing, it is essential to minimize redundant testing of the products in a product line. Because test coverage provides a way to explicitly state the extent to which a software item has been tested, having a clear understanding of test coverage helps avoid unnecessary repetition of tests and ensures that the testing efforts are focused on areas that require attention, ultimately leading to more efficient and effective product line testing. It is necessary to define appropriate test coverage metrics of product line testing that enable testers to identify redundancies in their testing efforts. Path-based integration testing has been proven to be an effective approach to product line integration testing. This paper defines coverage metrics for path-based product line integration testing and demonstrates their effectiveness in preventing redundant testing between platform testing and testing for individual products, while also effectively detecting faults. The experiment results highlight the coverage metrics’ effectiveness in avoiding redundant testing, reducing costs, and covering interfacing across different modules.
An Overview of Transcranial Magnetic Stimulation and Its Application in Multiple Sclerosis
Authors: Sy Alex , Thebault Simon , Aviv Richard I. , Auriat Angela M.
Published: November 2023

Transcranial magnetic stimulation (TMS) is a flexible, non-invasive technique that involves the production of a brief magnetic field to stimulate the conductive structures of the brain. When TMS is specifically employed as a single- or paired-pulse over the motor cortex, the function and integrity of the descending motor pathways can be assessed through the generation of a motor evoked potential (MEP). Important MEP-derived measures include the motor threshold, MEP amplitude and latency, central motor conduction time, silent period, intracortical inhibition, and intracortical facilitation. These functional measures may have use in individuals with multiple sclerosis (MS), a common chronic autoimmune disorder of the central nervous system, due to their useful diagnostic and prognostic implications. As a representation of excitability and conductivity, TMS measures may have the potential to serve as objective markers of corticospinal tract integrity, which is a major aspect of clinical disability in MS. Additionally, TMS may be employed to help monitor and provide insight on the effects of therapies for patients with MS over a longitudinal timeframe. In this review, we focus on the application of TMS in the context of MS, with an emphasis on the relationship between TMS measures and widely used clinical assessment measures used for patients with MS.
Mechanical and Tribological Performance of Carbon Fiber-Reinforced PETG for FFF Applications
Authors: Batista Moises , Lagomazzini Jose Miguel , Ramirez-Peña Magdalena , Vazquez-Martinez Juan Manuel
Published: November 2023

With the increasing adoption of Additive Manufacturing in the industry, driven by its efficiency, productivity, and project profitability, materials have undergone significant evolution to enhance process performance and part properties. One of the processes employed to enhance these properties involves the incorporation of various types of reinforcements. This aims to ensure that the material acquires a proportion of the properties of the added reinforcement. Consequently, the options for material selection expand depending on the application. Hence, there is a need to understand how specific reinforcements modify the properties of these materials. For this reason, this study investigates the modification of mechanical properties in a PETG matrix through the incorporation of short carbon fiber (CF) reinforcements, driven by their industrial relevance. To achieve this, the Fused Filament Fabrication (FFF) process will be utilized to produce a series of standardized specimens made of both PETG and CF-reinforced PETG, with variations in layer height and extrusion temperature. Subsequently, these specimens will undergo mechanical evaluation in tension and compression, following the relevant standards for each case. Finally, distinctions between both materials will be analyzed, based on the data obtained from tensile and compression tests. The incorporation of carbon fiber reinforcement shows a detrimental effect, leading to a decrease in the material’s stress (39.23 N/mm2 vs. 48.41 N/mm2 for the conventional material). As expected, due to the nature of the reinforcement (short fibers), the deformation of the material also decreases (2.13% compared to 2.9%).
Providing a Common Approach to Designing Dataset-Based Learning Activities Based on a Literature Review
Authors: Díaz-Pérez Lucía , Lopez-Pellicer Francisco J. , Brufau Pilar , Lacasta Javier , Trillo-Lado Raquel , Yagüe-Fabra José A. , Zarazaga-Soria Francisco Javier
Published: November 2023

While there are references available in the literature regarding learning experiences with Dataset-Based Learning (DBL) approaches, there is a noticeable absence of a standardized model for designing DBL activities. This gap was identified in this work after performing a systematic literature review (SLR). In contrast to other active learning methodologies, the lack of a common framework for the DBL methodology makes it challenging to compare different DBL approaches. This paper highlights the knowledge gap in the methodology for designing DBL activities and aims to provide a common approach for sharing the view and details about what DBL entails in higher education and how to design a DBL activity. Additionally, we illustrate these concepts with three case studies in different engineering fields. Based on the SLR results and the review of additional literature, this work defines DBL as an active teaching methodology that focuses on using datasets to promote the learning and understanding of specific concepts and skills. These datasets should contain real data presented in different formats. As a common starting point, in a DBL lesson, the dataset not only provides information and context in the activity statement but also serves as the material to work with, and the solution to the activity is entirely extracted from the information contained in the dataset.
Optimization of Ca–Al–Mn–Si Substitution Level for Enhanced Magnetic Properties of M-Type Sr-Hexaferrites for Permanent Magnet Application
Authors: Lim Jun-Pyo , Yun Eel-Ho , Kang Young-Min
Published: November 2023

Enhanced hard magnetic properties were achieved in M-type hexaferrite by optimizing the substitution levels of Mn, Al, and Si for Fe, and Ca for Sr within SrFe12O19. The addition of Al–Si–Mn effectively controlled crystallite growth, resulting in an increased coercivity (HC), while causing a decrease in the remanent magnetization (4πMr). A higher Ca content exhibited a trend of increasing the sintered density but decreasing the 4πMr and HC. The optimized composition, considering both the 4πMr and HC, was determined to be Sr0.8Ca0.2Fe10.2Mn0.1Al0.2Si0.1O19−d, with a sintered density of 4.84 g/cm3, 4πMr = 2.22 kG, and HC = 5.10 kOe. This result demonstrates the achievement of isotropic magnets with controlled crystal growth and densification without additional sintering additives. This development is promising, as this enhancement could be achieved without the use of cobalt, an expensive but essential ingredient in high-performance permanent magnets.
Effects of Freeze-Drying on Sensory Characteristics and Nutrient Composition in Black Currant and Sea Buckthorn Berries
Authors: Kamanova Svetlana , Temirova Indira , Aldiyeva Akmaral , Yermekov Yernaz , Toimbayeva Dana , Murat Linara , Muratkhan Marat , Khamitova Dina , Tultabayeva Tamara , Bulashev Berdibek , Ospankulova Gulnazym
Published: November 2023

Fresh berries contain numerous components that can undergo complex changes during the drying process. This study aims to investigate the effect of freeze-drying on the sensory and chemical properties of black currant and sea buckthorn berries. Freeze-drying was performed at a shelf temperature of 35–55 °C with a step of 5 °C and durations of 18, 20, 22, and 24 h. Comparing the final freeze-dried berries with their fresh counterparts, it was observed that at a shelf temperature of 50 °C and a drying time of 18 to 20 h, there was a minimal loss in the content of vitamins, organic acids, and carbohydrates. However, based on organoleptic evaluations, the best results were achieved after drying for 20 h. Furthermore, the preservation of citric and malic acids in black currant berries, along with citric, tartaric acids, and sucrose in sea buckthorn berries, was only at 45.6% when the freeze-drying time was extended to 22 h. Considering the physical and chemical properties of listed freeze-dried berries, the optimal parameters were identified as a shelf temperature of 50 °C and a drying time of 20 h. The findings from this study serve as a foundation for selecting appropriate freeze-drying parameters for various types of berries.
Transformer-Based Visual Object Tracking with Global Feature Enhancement
Authors: Wang Shuai , Fang Genwen , Liu Lei , Wang Jun , Zhu Kongfen , Melo Silas N.
Published: November 2023

With the rise of general models, transformers have been adopted in visual object tracking algorithms as feature fusion networks. In these trackers, self-attention is used for global feature enhancement. Cross-attention is applied to fuse the features of the template and the search regions to capture the global information of the object. However, studies have found that the feature information fused by cross-attention does not pay enough attention to the object region. In order to enhance cross-attention for the object region, an enhanced cross-attention (ECA) module is proposed for global feature enhancement. By calculating the average attention score for each position in the fused feature sequence and assigning higher weights to the positions with higher attention scores, the proposed ECA module can improve the feature information in the object region and further enhance the matching accuracy. In addition, to reduce the computational complexity of self-attention, orthogonal random features are introduced to implement a fast attention operation. This decomposes the attention matrix into the product of a random non-linear function between the original query and key. This module can reduce the spatial complexity and improve the inference speed by avoiding the explicit construction of a quadratic attention matrix. Finally, a tracking method named GFETrack is proposed, which comprises a Siamese backbone network and an enhanced attention mechanism. Experimental results show that the proposed GFETrack achieves competitive results on four challenging datasets.
A Self-Adapting IoT Network Configuration Supported by Distributed Graph Transformations
Authors: Jaskierny Leszek , Kotulski Leszek
Published: November 2023

The research described in this article aims to propose the creation of a framework that would enable the self-optimization of IoT device networks. The work is based on two foundations: distributed graph transformations and a flexible IoT network supported by the several standards and definitions proposed by The Open Group, such as the definition of microservices architecture (MSA) as well as IoT and semantic interoperability standards, providing a broader context for the research. It introduces the concept of capabilities, both at the individual device and network levels, which are used to describe the desired functions that will be performed by the given system. The network of distributed IoT devices is visualized as a graph, and graph transformations are used to specify and optimize the network in response to events like degraded performance, failures, or configuration changes. These actions are automatically performed in order to restore the original set of capabilities defined for the system. Validation of these capabilities is used to assess the success rate of the performed actions. The document describes a practical implementation of an IoT network for managing and monitoring an indoor greenhouse. Thanks to the introduction of formal representation of capabilities, the programming effort required to build the system was significantly reduced. Furthermore, automation related to the validation of capabilities and the performance of automated actions reduces the effort by a factor of a hundred compared with a manual action.
Isotropic ΙoT-Based Magnetic Flux Density Meter Implementation for ELF Field Measurements
Authors: Tampouratzis Manolis G. , Adamidis George A. , Vouyioukas Demosthenes , Yioultsis Traianos , Stratakis Dimitrios
Published: November 2023

This article presents the basic principles for an Extremely Low Frequency (ELF) IoT-based isotropic meter implementation, which can measure magnetic flux density from 100 nT up to 10 μT. The identical sensor probes are used for isotropic field measurements in the X, Y, and Z planes. The prototype has a flat response across the frequency range from 40 Hz to 10 kHz, detecting and measuring several magnetic field sources. The proposed low-cost meter can measure fields from the power supply network and its harmonic frequencies in the operating frequency band. The proposed magnetic flux density meter circuit is simple to implement and the measured field can be displayed on any mobile device with Wi-Fi connectivity. An Arduino board with the embedded Wi-Fi Nina module is responsible for data transferring from the sensor to the cloud as a complete IoT solution, supported by the Blynk application via Android and iOS operating systems or web interface. In addition, an ELF energy harvesting (EH) circuit was also proposed in our study for the utilization of the alternating magnetic fields (50 Hz) derived from the operation of several consumer devices such as transformers, power supplies, hair dryers, etc. using low-consumption applications. Experimental measurements showed that the (DC) harvesting voltage can reach up to 4.2 volts from the magnetic field of 33 μΤ, caused by the operation of an electric hair dryer and can fully charge the 100 μF storage capacitor (Cs) of the proposed EH system in about 3 min.
Path Planning for Automatic Berthing Using Ship-Maneuvering Simulation-Based Deep Reinforcement Learning
Authors: Vo Anh Khoa , Mai Thi Loan , Yoon Hyeon Kyu
Published: November 2023

Despite receiving much attention from researchers in the field of naval architecture and marine engineering since the early stages of modern shipbuilding, the berthing phase is still one of the biggest challenges in ship maneuvering due to the potential risks involved. Many algorithms have been proposed to solve this problem. This paper proposes a new approach with a path-planning algorithm for automatic berthing tasks using deep reinforcement learning (RL) based on a maneuvering simulation. Unlike the conventional path-planning algorithm using the control theory or an advanced algorithm using deep learning, a state-of-the-art path-planning algorithm based on reinforcement learning automatically learns, explores, and optimizes the path for berthing performance through trial and error. The results of performing the twin delayed deep deterministic policy gradient (TD3) combined with the maneuvering simulation show that the approach can be used to propose a feasible and safe path for high-performing automatic berthing tasks.
Genomic Approaches for Monogenic Kidney Diseases: A Comparative Review of Diagnostic Methods and Precision Medicine Implications
Authors: Giovanella Silvia , Ligabue Giulia , Chester Johanna , Magistroni Riccardo
Published: November 2023

Chronic kidney disease is a long-term condition with significant implications for quality of life and health care costs. To uncover the etiology in selected cases suspected of monogenicity, a genomic approach can be employed. There are multiple technologies available, but there is currently no consensus on the most effective diagnostic approach. This review provides a comparison of currently available diagnostic methods in terms of diagnostic yield. However, the heterogeneity of patient cohort inclusion criteria limits direct comparisons. Our review identified three studies which compared a targeted gene panel and whole-exome sequencing for the same patient population. However, the results are inconclusive due to the different sizes and specificity of the targeted panels employed. The contribution of a whole-genome sequencing approach is highly debated. It is noteworthy that a large number of data are generated by these sequencing technologies. This allows for rapid analysis of coding and non-coding regions. However, the interpretation of variants is a significant burden, and the reporting of incidental findings is still challenging. Therefore, the identification of the most efficient technology is pivotal but still controversial. To conclude, an objective comparison of the three methods for the same population could overcome the limits of these studies’ heterogeneity and highlight the weaknesses and the strengths of individual approaches.
When Wireless Localization Meets Artificial Intelligence: Basics, Challenges, Synergies, and Prospects
Authors: Cha Kyeong-Ju , Lee Jung-Bum , Ozger Mustafa , Lee Woong-Hee
Published: November 2023

The rapid development of information communication and artificial intelligence (AI) technology is driving innovation in various new application fields such as autonomous driving, augmented reality, and the metaverse. In particular, the advancement of wireless localization technology plays a great role in these cutting-edge technologies. However, traditional wireless localization systems rely on the global navigation satellite system (GNSS), which is ineffective in indoor or underground environments. To overcome this issue, indoor positioning systems (IPS) have gained attention, and various localization techniques utilizing wireless communication were studied. Subsequently, AI technologies are improving the performance of wireless localization and addressing problems that were previously difficult to solve. In this paper, we summarize wireless localization techniques and define the factors that impede their performance. Furthermore, we categorize AI algorithms and present examples of how they can be used to address these hindering factors. Finally, we propose open research directions and prospects for AI-assisted wireless localization.
Effect on Ionic Composition and Tonic Parameters of Sweeteners Used in the Production of Functional Beverages
Authors: Mroczek Karolina , Saletnik Bogdan , Bajcar Marcin , Saletnik Aneta , Puchalski Czesław , Zaguła Grzegorz
Published: November 2023

Excessive sugar consumption is a risk factor for becoming overweight. Due to the increase in consumer nutritional awareness, functional beverages with reduced caloric content have attracted great interest in recent years. The current state of knowledge on the feasibility of using low- and no-calorie sweeteners (LNCS) as substitutes for traditional sugar in the production of functional beverages while maintaining their osmolality properties is limited. Selected sweeteners were examined for the presence of five selected macronutrients (calcium, potassium, magnesium, sodium, and sulfur) and iron by ICP-OES, osmolality, total dissolved solids (TDS), and electrical conductivity (EC) in their solutions. The obtained results formed the basis for evaluating the applicability of the studied sweeteners in the production of functional beverages.