bluuebunny/crossref_metadata_2025 huggingface dataset:
Robust Adaptive Beamforming Based on a Convolutional Neural Network
Authors: Liao Zhipeng , Duan Keqing , He Jinjun , Qiu Zizhou , Li Binbin
Published: June 2023

To address the advancements in jamming technology, it is imperative to consider robust adaptive beamforming (RBF) methods with finite snapshots and gain/phase (G/P) errors. This paper introduces an end-to-end RBF approach that utilizes a two-stage convolutional neural network. The first stage includes convolutional blocks and residual blocks without downsampling; the blocks assess the covariance matrix precisely using finite snapshots. The second stage maps the first stage’s output to an adaptive weight vector employing a similar structure to the first stage. The two stages are pre-trained with different datasets and fine-tuned as end-to-end networks, simplifying the network training process. The two-stage structure enables the network to possess practical physical meaning, allowing for satisfying performance even with a few snapshots in the presence of array G/P errors. We demonstrate the resulting beamformer’s performance with numerical examples and compare it to various other adaptive beamformers.
Virtual Network Function Migration Considering Load Balance and SFC Delay in 6G Mobile Edge Computing Networks
Authors: Yue Yi , Tang Xiongyan , Zhang Zhiyan , Zhang Xuebei , Yang Wencong
Published: June 2023

With the emergence of Network Function Virtualization (NFV) and Software-Defined Networks (SDN), Service Function Chaining (SFC) has evolved into a popular paradigm for carrying and fulfilling network services. However, the implementation of Mobile Edge Computing (MEC) in sixth-generation (6G) mobile networks requires efficient resource allocation mechanisms to migrate virtual network functions (VNFs). Deep learning is a promising approach to address this problem. Currently, research on VNF migration mainly focuses on how to migrate a single VNF while ignoring the VNF sharing and concurrent migration. Moreover, most existing VNF migration algorithms are complex, unscalable, and time-inefficient. This paper assumes that each placed VNF can serve multiple SFCs. We focus on selecting the best migration location for concurrently migrating VNF instances based on actual network conditions. First, we formulate the VNF migration problem as an optimization model whose goal is to minimize the end-to-end delay of all influenced SFCs while guaranteeing network load balance after migration. Next, we design a Deep Learning-based Two-Stage Algorithm (DLTSA) to solve the VNF migration problem. Finally, we combine previous experimental data to generate realistic VNF traffic patterns and evaluate the algorithm. Simulation results show that the SFC delay after migration calculated by DLTSA is close to the optimal results and much lower than the benchmarks. In addition, it effectively guarantees the load balancing of the network after migration.
Fabric–Metal Barrier for Low Specific Absorption Rate and Wide-Band Felt Substrate Antenna for Medical and 5G Applications
Authors: Hashim Fatimah Fawzi , Mahadi Wan Nor Liza Binti Wan , Abdul Latef Tarik Bin , Othman Mohamadariff Bin
Published: June 2023

This study proposed the dimensions of 55 mm × 34 mm × 1 mm for wearable antenna; the copper Y-slot patch and copper partial ground are attached to a felt substrate. The partial ground has the higher impact in antenna gain enhancement compared with the full ground, making it the most suitable candidate for wearable applications and suitable for embedding in fabrics for use in medical applications. In addition, the proposed antenna design combined a fabric–metal barrier operated at 2.4 GHz 65.4% with a low specific absorption rate (SAR) of 0.01 watts per kilogramme (W/kg) and 0.006 W/kg per 10 g and a gain of 6.48 dBi. The proposed antenna has an omnidirectional radiation pattern. The two-layer barrier is designed to achieve high electromagnetic (EM) absorption and reduce the antenna’s absorption coefficient (SAR) for safe use in applications involving human activities. Simulation and measurement results on the arm and the head of the human body indicated that the antenna has excellent performance. In addition, the measurement results agreed well with the simulation results, making the proposed wearable antenna reliable for medical and 5G applications.
Reducing CO2 Emissions during the Operation of Unmanned Transport Vessels with Diesel Engines
Authors: Szelangiewicz Tadeusz , Żelazny Katarzyna
Published: June 2023

Environmental protection is one of the most challenging tasks facing mankind. Reducing CO2 emissions in the global economy, including maritime transport, is being pursued in various ways, one of them being the design work leading to the construction and operation of unmanned ships. Unmanned vessels operating on longer routes will still have internal combustion propulsion. However, they will not have the superstructure and the various systems and equipment necessary for the crew. This will result in an unmanned vessel having less weight, less displacement and, therefore, less size, resistance and propulsion power than a manned vessel for the same transport capacity. Consequently, the unmanned vessel will emit less CO2. This paper presents a novel method for predicting fuel consumption and CO2 emissions for unmanned container ships. The method uses regression relationships of geometric and operational parameters for manned container ships developed for this purpose to determine such relationships for unmanned ships. On this basis, it is shown what the level of CO2 reduction will be compared to manned container ships.
Interpretable Hybrid Experiment Learning-Based Simulation Analysis of Power System Planning under the Spot Market Environment
Authors: Liao Wei , Yang Yi , Wang Qingwei , Wang Ruoyu , Fu Xieli , Xie Yinghua , Zhao Junhua
Published: June 2023

The electricity spot market plays a significant role in promoting the self-improvement of the overall resource utilization efficiency of the power system and advancing energy conservation and emission reduction. This paper analyzes and compares the potential impacts of spot market operations on system planning, considering the differences between planning methods in traditional and spot market environments through theoretical analysis and model comparison. Furthermore, we conduct research and analysis on grid planning methods under the spot market environment with the goal of maximizing social benefits. Unlike the pricing approach based on historical price data in traditional market simulation processes, a data-driven approach that combines experimental economics and machine learning is proposed, specifically using mixed empirical learning to simulate unit bidding strategies in market transactions. A simulation model for electricity spot market trading is constructed to analyze the performance of the planning results in the spot market environment. The case study results indicate that the proposed planning methods can enable the grid to operate well in the spot market environment, maintain relatively stable nodal prices, and ensure the integration of a high proportion of clean energy.
An Adaptive Centralized Protection and Relay Coordination Algorithm for Microgrid
Authors: Kannaian Regin Bose , Joseph Belwin Brearley , Ramachandran Raja Prabu
Published: June 2023

To meet the increased customer demands, microgrid evolved. The structure of microgrid changes dynamically due to the intermittent nature of renewable-based generation, status of the distributed generator and opening of breakers for fault/maintenance. Hence, the magnitude of fault current is dynamic in nature. In order to deal with these dynamic changes, this paper addresses an adaptive central microgrid controller-based protection and relay coordination scheme, which revises the relay settings dynamically (both radial and looped configuration) for every change in topology. In the proposed algorithm, the primary relay responds to a fault immediately since the individual relays are given with fault level setting. For any abnormality in the network, the fault location is determined both via local relay and microgrid central controller (MCC). Hence, even though the local relay fails to identify the fault due to high fault impedance, the MCC locates the fault accurately and isolates the minimum faulty part. The coordination between relays is carried out by MCC in a time-graded manner based on microgrid central protection and relay coordination algorithm. The proposed algorithm is tested using Matlab in a microgrid built based on the IEEE 33 bus distribution network.
Linking Cost Decline and Demand Surge in the Hydrogen Market: A Case Study in China
Authors: Xu Danlu , Liu Zhoubin , Zhu Jiahui , Fang Qin , Shan Rui
Published: June 2023

Hydrogen is crucial in achieving global energy transition and carbon neutrality goals. Existing market estimates typically presume linear or exponential growth but fail to consider how market demand responds to the declining cost of underlying technologies. To address this, this study utilizes a learning curve model to project the cost of electrolyzers and its subsequent impact on hydrogen market, aligning with a premise that the market demand is proportional to the cost of hydrogen. In a case study of China’s hydrogen market, projecting from 2020 to 2060, we observed substantial differences in market evolution compared to exponential growth scenarios. Contrary to exponential growth scenarios, China’s hydrogen market experiences faster growth during the 2020–2040 period rather than later. Such differences underscore the necessity for proactive strategic planning in emerging technology markets, particularly for those experiencing rapid cost decline, such as hydrogen. The framework can also be extended to other markets by using local data, providing valuable insights to investors, policymakers, and developers engaged in the hydrogen market.
Enhancing the Levelized Cost of Hydrogen with the Usage of the Byproduct Oxygen in a Wastewater Treatment Plant
Authors: Hönig Franziska , Rupakula Ganesh Deepak , Duque-Gonzalez Diana , Ebert Matthias , Blum Ulrich
Published: June 2023

In order to harmonizFranziska Hönige the supply and demand of green energy, new future-proof technologies are needed. Here, hydrogen plays a key role. Within the current framework conditions, the production of green hydrogen is not yet economically viable. The use of the oxygen produced and the possible increase in efficiency associated with it mostly remain unconsidered. The aim is to demonstrate that the economic efficiency of a power-to-gas (PtG) project can be increased by using the byproduct oxygen. In this research project, a water electrolyzer connected to grid is powered to supply hydrogen to a hydrogen refueling station. By utilizing the byproduct oxygen from water electrolysis for a wastewater treatment plant (WWTP), it is shown that the net present value (NPV) of the project can be improved by up to 13% compared to the initial scenario. If a photovoltaic (PV) system is used in addition to grid electricity for higher green hydrogen production, the NPV can be further improved by up to 58%. The levelized cost of hydrogen (LCOH) is calculated for different scenarios with and without oxygen configuration. A sensitivity analysis is then performed to find important parameters.
Role of Altitude in Influencing the Spray Combustion Characteristics of a Heavy-Duty Diesel Engine in a Constant Volume Combustion Chamber. Part I: Free Diesel Jet
Authors: Wang Chengguan , Qi Xiaozhi , Wang Tao , Lou Diming , Tan Piqiang , Hu Zhiyuan , Fang Liang , Yang Rong
Published: June 2023

Heavy-duty diesel engines operating in plateau regions experience deteriorated combustion. However, the lack of up-to-date information on the spray-combustion process limits the fundamental understanding of the role of altitude. In this work, the in-cylinder thermodynamic conditions of a real diesel engine operating under different altitudes were reproduced in a constant-volume combustion chamber (CVCC). The liquid spray, ignition, and combustion processes were visualized in detail using different optical diagnostics. Apart from predictable results, some interesting new findings were obtained to improve the understanding of free spray-combustion processes with different altitudes. The spatial distributions of ignition kernels provided direct evidence of higher peak pressure rise rates for high-altitude diesel engines. The percent of stoichiometric air was calculated to confirm that the net effect of altitude was an increase in the amount of air-entrained upstream of the lifted flame; therefore, the soot levels deduced from flame images were inconsistent with those from real engines, revealing that accelerating the soot oxidation process could effectively reduce engine soot emissions in plateau regions. Finally, a novel schematic diagram of the spray flame structure was proposed to phenomenologically describe the role of altitude in influencing the spray-combustion process of a free jet.
Torque Ripple Minimization of Variable Reluctance Motor Using Reinforcement Dual NNs Learning Architecture
Authors: Alharkan Hamad
Published: June 2023

The torque ripples in a switched reluctance motor (SRM) are minimized via an optimal adaptive dynamic regulator that is presented in this research. A novel reinforcement neural network learning approach based on machine learning is adopted to find the best solution for the tracking problem of the SRM drive in real time. The reference signal model which minimizes the torque pulsations is combined with tracking error to construct the augmented structure of the SRM drive. A discounted cost function for the augmented SRM model is described to assess the tracking performance of the signal. In order to track the optimal trajectory, a neural network (NN)-based RL approach has been developed. This method achieves the optimal tracking response to the Hamilton–Jacobi–Bellman (HJB) equation for a nonlinear tracking system. To do so, two neural networks (NNs) have been trained online individually to acquire the best control policy to allow tracking performance for the motor. Simulation findings have been undertaken for SRM to confirm the viability of the suggested control strategy.
Geometry-Based Deep Learning in the Natural Sciences
Authors: Friedman Robert
Published: June 2023

Nature is composed of elements at various spatial scales, ranging from the atomic to the astronomical level. In general, human sensory experience is limited to the mid-range of these spatial scales, in that the scales which represent the world of the very small or very large are generally apart from our sensory experiences. Furthermore, the complexities of Nature and its underlying elements are not tractable nor easily recognized by the traditional forms of human reasoning. Instead, the natural and mathematical sciences have emerged to model the complexities of Nature, leading to knowledge of the physical world. This level of predictiveness far exceeds any mere visual representations as naively formed in the Mind. In particular, geometry has served an outsized role in the mathematical representations of Nature, such as in the explanation of the movement of planets across the night sky. Geometry not only provides a framework for knowledge of the myriad of natural processes, but also as a mechanism for the theoretical understanding of those natural processes not yet observed, leading to visualization, abstraction, and models with insight and explanatory power. Without these tools, human experience would be limited to sensory feedback, which reflects a very small fraction of the properties of objects that exist in the natural world. As a consequence, as taught during the times of antiquity, geometry is essential for forming knowledge and differentiating opinion from true belief. It not only provides a framework for understanding astronomy, classical mechanics, and relativistic physics, but also the morphological evolution of living organisms, along with the complexities of the cognitive systems. Geometry also has a role in the information sciences, where it has explanatory power in visualizing the flow, structure, and organization of information in a system. This role further impacts the explanations of the internals of deep learning systems as developed in the fields of computer science and engineering.
Physiological and Gene Expression Response of Interspecific Hybrids of Fraxinus mandshurica × Fraxinus americana to MJ or SNP under Drought
Authors: Cao Yang , He Liming , Song Fei , Li Chuanzhou , Ji Qitian , Liu Jianfei , Peng Guangzhou , Li Boyao , Zeng Fansuo , Zhan Yaguang
Published: June 2023

Drought affects the growth and production of Fraxinus tree species, such as the precious woody plant Fraxinus mandshurica. Based on interspecific hybrid F1 combinations, D110 plants of F. mandshurica × F. americana with strong drought resistance were selected for this study. To further reveal their heterosis mechanism under drought, in this study, an analysis was conducted pertaining to the physiological indexes and gene expression of related key gene changes in materials of 5 yr D110 seedlings and their female and male parental controls (D113 and 4–3) in response to drought, as well as to the addition of sodium nitrate (SNP, a donor of nitric oxide) and methyl jasmonate (MJ, a donor of jasmonate) signal molecules after drought. The results showed that under drought stress, hybrid D110 plants performed significantly better than their parents, especially compared to D113, in plant growth (the plant height growth was 29.48% higher), photosynthesis (the net photosynthetic rate was 38.4% higher), peroxidation (the increase in MDA content was 71.77% lower), defense enzyme activity (SOD and POD activities were 36.63% and 65.58% higher), hormone contents (ABA, IAA and GA were 33.9%~51.2% higher) and gene expression (the LHY and TOC1 rhythmic genes were 131.97%~165.81% higher). When an exogenous additive agent (SNP or MJ) was applied after drought, the negative effects of drought on growth were effectively alleviated (the tree height growth of D110 increased from 22.76% to 22.32% in comparison to drought conditions); meanwhile, the height growth of D110 plants was significantly higher than that of their parents. Further results of physiological indexes and the expression of related key gene changes in response to SNP or MJ also indicated that D110 plants can recover faster from drought than their parents after application of SNP or MJ. This article provides new ideas for revealing the heterosis mechanism of the drought resistance of interspecific F1 hybrids and supplies effective measures for improving drought resistance in F. mandshurica.
Neural Network Exploration for Keyword Spotting on Edge Devices
Authors: Bushur Jacob , Chen Chao
Published: June 2023

The introduction of artificial neural networks to speech recognition applications has sparked the rapid development and popularization of digital assistants. These digital assistants constantly monitor the audio captured by a microphone for a small set of keywords. Upon recognizing a keyword, a larger audio recording is saved and processed by a separate, more complex neural network. Deep neural networks have become an effective tool for keyword spotting. Their implementation in low-cost edge devices, however, is still challenging due to limited resources on board. This research demonstrates the process of implementing, modifying, and training neural network architectures for keyword spotting. The trained models are also subjected to post-training quantization to evaluate its effect on model performance. The models are evaluated using metrics relevant to deployment on resource-constrained systems, such as model size, memory consumption, and inference latency, in addition to the standard comparisons of accuracy and parameter count. The process of deploying the trained and quantized models is also explored through configuring the microcontroller or FPGA onboard the edge devices. By selecting multiple architectures, training a collection of models, and comparing the models using the techniques demonstrated in this research, a developer can find the best-performing neural network for keyword spotting given the constraints of a target embedded system.
Effects of Dietary Lentinus edodes Fermentation Supplementation on Digestive Enzyme Activity, Antioxidant Capacity and Morphology of the Liver and Intestine in Largemouth Bass (Micropterus salmoides) Fed High Plant Protein Diets
Authors: Xu Jiaming , Yu Zhoulin , Liu Guangye , Li Sijie , Zhou Guoyong , Wang Hanhua , Dong Yewei , You Cuihong , Bai Weidong , Zhou Meng , Huang Yanhua , Tan Xiaohong
Published: June 2023

This study evaluated the effect of Lentinus edodes fermentation (LEF) on digestive enzyme activity, antioxidant capacity and morphology of the liver and intestine in largemouth bass (Micropterus salmoides) fed high plant protein diets (HPPD). LEF was supplemented in HPPD with 0 g kg−1 (LEF0), 10 g kg−1 (LEF1), 20 g kg−1 (LEF2), 30 g kg−1 (LEF3), 40 g kg−1 (LEF4), 50 g kg−1 (LEF5), respectively, and then the six diets were fed to largemouth bass with a body weight of 28.8 ± 0.05 g for eight weeks. Juvenile fish were randomized into 6 groups and each group had 4 replicates with 40 fish. Dietary LEF supplementation alleviated the liver inflammatory reaction of largemouth bass caused by HPPD and improved liver morphology. Goblet cells multiplied and the gut muscle layer thickened after LEF supplementation. The LEF significantly increased amylase activity in the liver and intestine of largemouth bass in individual experimental groups. The LEF could increase the activity of catalase in the liver and intestine of largemouth bass (p < 0.05). The content of malondialdehyde was significantly lower than that in the control group (p < 0.05). Dietary LEF supplementation had no significant effect on the intestinal flora of largemouth bass. These findings imply that LEF supplementation can reduce liver inflammation, enhance intestinal tissue morphology, and eventually benefit largemouth bass health.
The Second Record of Gymnesigobius medits Kovačić, Ordines, Ramirez-Amaro & Schliewen, 2019, the Deepest Benthic Gobiiform Species, and the Additional Records of Gobius xoriguer Iglésias, Vukić & Šanda, 2021 (Actinopterygii: Gobiiformes: Gobiidae)
Authors: Kovačić Marcelo , Ramírez-Amaro Sergio , Farriols Maria Teresa , Ordines Francesc
Published: June 2023

Gymnesigobius medits is reported for the first time after a recent description recorded from the Balearic Islands and from the slope of the Gulf of Vera on the Iberian Peninsula coast. The record from the Emile Baudot seamount on the Balearic Islands represents the deepest positive benthic gobiiform species record in general. The presence of the membrane connection between the pelvic fins in Gymnesigobius medits, presumed on the damaged fin in the original description, was confirmed. The recently described Gobius xoriguer is the first record from the Pitiusas and Columbretes islands and from the Iberian Peninsula coast. It appears to be widely distributed in the circalittoral bottoms, preferentially in red algae beds. Morphological identification of both species was confirmed using molecular analyses based on the sequencing of the mitochondrial cytochrome c oxidase subunit I (DNA barcode) gene. The deepest records of gobiiform fishes in oceans and seas are reviewed. The European seas, a well-studied area with eight gobiid species recorded deeper than 200 m, show high bathyal gobiid species richness compared to other areas. The real worldwide diversity of bathyal gobies, although only a fraction of the shallow water species richness of this taxon, is probably much larger than presently known.
Comparative Analysis of Machine Learning, Hybrid, and Deep Learning Forecasting Models: Evidence from European Financial Markets and Bitcoins
Authors: Ampountolas Apostolos
Published: June 2023

This study analyzes the transmission of market uncertainty on key European financial markets and the cryptocurrency market over an extended period, encompassing the pre-, during, and post-pandemic periods. Daily financial market indices and price observations are used to assess the forecasting models. We compare statistical, machine learning, and deep learning forecasting models to evaluate the financial markets, such as the ARIMA, hybrid ETS-ANN, and kNN predictive models. The study results indicate that predicting financial market fluctuations is challenging, and the accuracy levels are generally low in several instances. ARIMA and hybrid ETS-ANN models perform better over extended periods compared to the kNN model, with ARIMA being the best-performing model in 2018–2021 and the hybrid ETS-ANN model being the best-performing model in most of the other subperiods. Still, the kNN model outperforms the others in several periods, depending on the observed accuracy measure. Researchers have advocated using parametric and non-parametric modeling combinations to generate better results. In this study, the results suggest that the hybrid ETS-ANN model is the best-performing model despite its moderate level of accuracy. Thus, the hybrid ETS-ANN model is a promising financial time series forecasting approach. The findings offer financial analysts an additional source that can provide valuable insights for investment decisions.
A Non-Local Problem for the Fractional-Order Rayleigh–Stokes Equation
Authors: Ashurov Ravshan , Mukhiddinova Oqila , Umarov Sabir
Published: June 2023

A nonlocal boundary value problem for the fractional version of the Rayleigh–Stokes equation, well-known in fluid dynamics, is studied. Namely, the condition u(x,T)=βu(x,0)+φ(x), where β is an arbitrary real number, is proposed instead of the initial condition. If β=0, then we have the inverse problem in time, called the backward problem. It is well-known that the backward problem is ill-posed in the sense of Hadamard. If β=1, then the corresponding non-local problem becomes well-posed in the sense of Hadamard, and moreover, in this case a coercive estimate for the solution can be established. The aim of this work is to find values of the parameter β, which separates two types of behavior of the semi-backward problem under consideration. We prove the following statements: if β≥1, or β<0, then the problem is well-posed; if β∈(0,1), then depending on the eigenvalues of the elliptic part of the equation, for the existence of a solution an additional condition on orthogonality of the right-hand side of the equation and the boundary function to some eigenfunctions of the corresponding elliptic operator may emerge.
Dynamic Changes in the Global Transcriptome of Postnatal Skeletal Muscle in Different Sheep
Authors: Ai Yue , Zhu Yaning , Wang Linli , Zhang Xiaosheng , Zhang Jinlong , Long Xianlei , Gu Qingyi , Han Hongbing
Published: June 2023

Sheep growth performance, mainly skeletal muscle growth, provides direct economic benefits to the animal husbandry industry. However, the underlying genetic mechanisms of different breeds remain unclear. We found that the cross-sectional area (CSA) of skeletal muscle in Dorper (D) and binary cross-breeding (HD) was higher than that in Hu sheep (H) from 3 months to 12 months after birth. The transcriptomic analysis of 42 quadriceps femoris samples showed that a total of 5053 differential expression genes (DEGs) were identified. The differences in the global gene expression patterns, the dynamic transcriptome of skeletal muscle development, and the transcriptome of the transformation of fast and slow muscles were explored using weighted correlation network analysis (WGCNA) and allele-specific expression analysis. Moreover, the gene expression patterns of HD were more similar to D rather than H from 3 months to 12 months, which might be the reason for the difference in muscle growth in the three breeds. Additionally, several genes (GNB2L1, RPL15, DVL1, FBXO31, etc.) were identified as candidates related to skeletal muscle growth. These results should serve as an important resource revealing the molecular basis of muscle growth and development in sheep.
Identification and Characterization of Novel SPHINX/BMMF-like DNA Sequences Isolated from Non-Bovine Foods
Authors: Habermann Diana , Klempt Martin , Franz Charles M. A. P.
Published: June 2023

Sixteen novel circular rep-encoding DNA sequences with high sequence homologies to previously described SPHINX and BMMF sequences were isolated for the first time from non-bovine foods (pork, wild boar, chicken meat, Alaska pollock, pangasius, black tiger shrimp, apple, carrot, and sprouts from alfalfa, radish, and broccoli). The phylogenetic analysis of the full-length circular genomes grouped these together with previously described representatives of SPHINX/BMMF group 1 and 2 sequences (eight in each group). The characterization of genome lengths, genes present, and conserved structures confirmed their relationship to the known SPHINX/BMMF sequences. Further analysis of iteron-like tandem repeats of SPHINX/BMMF group 1-related genomes revealed a correlation with both full-length sequence tree branches as well as Rep protein sequence tree branches and was able to differentiate subtypes of SPHINX/BMMF group 1 members. For the SPHINX/BMMF group 2 members, a distinct grouping of sequences into two clades (A and B) with subgroups could be detected. A deeper investigation of potential functional regions upstream of the rep gene of the new SPHINX/BMMF group 2 sequences revealed homologies to the dso and sso regions of known plasmid groups that replicate via the rolling circle mechanism. Phylogenetic analyses were accomplished by a Rep protein sequence analysis of different ssDNA viruses, pCRESS, and plasmids with the known replication mechanism, as this yielded deeper insights into the relationship of SPHINX/BMMF group 1 and 2 Rep proteins. A clear relation of these proteins to the Rep proteins of plasmids could be confirmed. Interestingly, for SPHINX/BMMF group 2 members, the relationship to rolling circle replication plasmids could also be verified. Furthermore, a relationship of SPHINX/BMMF group 1 Rep proteins to theta-replicating plasmid Reps is discussed.
Genotypic Determination of Extended Spectrum β-Lactamases and Carbapenemase Production in Clinical Isolates of Klebsiella pneumoniae in Southwest Nigeria
Authors: Odewale Gbolabo , Jibola-Shittu Motunrayo Yemisi , Ojurongbe Olusola , Olowe Rita Ayanbolade , Olowe Olugbenga Adekunle
Published: June 2023

Introduction: Klebsiella pneumoniae is a major pathogen implicated in healthcare-associated infections. Extended-spectrum β-lactamase (ESBL) and carbapenemase-producing K. pneumoniae isolates are a public health concern. This study investigated the existence of some ESBL and carbapenemase genes among clinical isolates of K. pneumoniae in Southwest Nigeria and additionally determined their circulating clones. Materials and Methods: Various clinical samples from 420 patients from seven tertiary hospitals within Southwestern Nigeria were processed between February 2018 and July 2019. These samples were cultured on blood agar and MacConkey agar, and the isolated bacteria were identified by Microbact GNB 12E. All K. pneumoniae were confirmed by polymerase chain reaction (PCR) using the 16s rRNA gene. Antibiotic susceptibility testing (AST) was done on these isolates, and the PCR was used to evaluate the common ESBL-encoding genes and carbapenem resistance genes. Genotyping was performed using multi-locus sequencing typing (MLST). Results: The overall prevalence of K. pneumoniae in Southwestern Nigeria was 30.5%. The AST revealed high resistance rates to tetracyclines (67.2%), oxacillin (61.7%), ampicillin (60.2%), ciprofloxacin (58.6%), chloramphenicol (56.3%), and lowest resistance to meropenem (43.0%). All isolates were susceptible to polymyxin B. The most prevalent ESBL gene was the TEM gene (47.7%), followed by CTX-M (43.8%), SHV (39.8%), OXA (27.3%), CTX-M-15 (19.5%), CTX-M-2 (11.1%), and CTX-M-9 (10.9%). Among the carbapenemase genes studied, the VIM gene (43.0%) was most detected, followed by OXA-48 (28.9%), IMP (22.7%), NDM (17.2%), KPC (13.3%), CMY (11.7%), and FOX (9.4%). GIM and SPM genes were not detected. MLST identified six different sequence types (STs) in this study. The most dominant ST was ST307 (50%, 5/10), while ST258, ST11, ST147, ST15, and ST321 had (10%, 1/10) each. Conclusion: High antimicrobial resistance in K. pneumoniae is a clear and present danger for managing infections in Nigeria. Additionally, the dominance of a successful international ST307 clone highlights the importance of ensuring that genomic surveillance remains a priority in the hospital environment in Nigeria.
Clarifying the Heterogeneity in Response to Vitamin D in the Development, Prevention, and Treatment of Type 2 Diabetes Mellitus: A Narrative Review
Authors: Hands Jacob M. , Corr Patrick G. , Frame Leigh A.
Published: June 2023

In this review, we explore the potential drivers of heterogeneity in response to Vitamin D (VitD) therapy, such as bioavailability, sex-specific response, and autoimmune pathology, in those at risk for and diagnosed with T2DM. In addition, we propose distinct populations for future interventions with VitD. The literature concerning VitD supplementation in the prevention, treatment, and remission of type 2 diabetes mellitus (T2DM) spans decades, is complex, and is often contradictory with mixed findings upon intervention. By association, VitD status is powerfully predictive with deficient subjects reporting greater risk for T2DM, conversion to T2DM from prediabetes, and enhanced response to VitD therapy. Preclinical models strongly favor intervention with VitD owing to the pleiotropic influence of VitD on multiple systems. Additional research is crucial as there remain many questions unanswered that are related to VitD status and conditions such as T2DM. Future research must be conducted to better understand the potentially spurious relationships between VitD status, supplementation, sun exposure, health behaviors, and the diagnosis and management of T2DM. Public health practice can greatly benefit from a better understanding of the mechanisms by which we can reliably increase VitD status and how this can be used to develop education and improve health behaviors.
Racial and Ethnic Disparities in Chronic Stress among Male Caregivers
Authors: Unson Christine , Njoku Anuli , Bernard Stanley , Agbalenyo Martin
Published: June 2023

Whereas research on caregiving is well documented, less is known about gender inequalities in caregiver stress, coping mechanisms, and health outcomes, all of which may vary by race, ethnicity, and socioeconomic status. This scoping review investigated racial and ethnic disparities using the Stress Process Model among male caregivers. Several databases were searched including Academic Search Premier, Medline Complete, APA PsycInfo, CINHAL, Google, ProQuest, and Web of Science. Included were peer-reviewed articles in English, published from 1990 to 2022. A total of nine articles fulfilled inclusion criteria. Most of the articles indicated that compared to White male caregivers, African American male caregivers provided more hours of care, assisted with more activities of daily living (ADLs) and instrumental activities of daily living (IADLs), and experienced more financial stress. In terms of coping style, one study found African American male caregivers, compared to White male caregivers, held negative religious beliefs. Another study showed that they were at a higher risk for stroke than their White counterparts. The search revealed a dearth of studies on racial disparities in stress, coping, and health outcomes among male caregivers. Further research is needed on the experiences and perspectives of male minority caregivers.
A Study of the Impact of COVID-19 on Urban Contact Networks in China Based on Population Flows
Authors: Zhang Xuejie , Zhao Jinli , Liu Haimeng , Miao Yi , Li Mengcheng , Wang Chengxin
Published: June 2023

The emergence and enduring diffusion of COVID-19 has had a dramatic impact on cities worldwide. The scientific aim of this study was to introduce geospatial thinking to research related to infectious diseases, while the practical aim was to explore the impact on population movements and urban linkages in the longer term following a pandemic outbreak. Therefore, this study took 366 cities in China as the research subjects while exploring the relationship between urban contact and the outbreak of the pandemic from both national and regional perspectives using social network analysis (SNA), Pearson correlation analysis and multi-scale geographically weighted regression (MGWR) modeling. The results revealed that the number of COVID-19 infections in China fluctuated with strain variation over the study period; the urban contact network exhibited a significant trend of recovery. The pandemic had a hindering effect on national urban contact, and this effect weakened progressively. Meanwhile, the effect exhibited significant spatial heterogeneity, with a weakening effect in the eastern region ≈ northeast region > central region > western region, indicating a decreasing phenomenon from coastal to inland areas. Moreover, the four major economic regions in China featured border barrier effects, whereby urban contact networks constituted by cross-regional flows were more sensitive to the development of the pandemic. The geostatistical approach adopted in this study related to infectious disease and urban linkages can be used in other regions, and its findings provide a reference for China and other countries around the world to respond to major public health events.
Network Pharmacology, Molecular Docking and Molecular Dynamics to Explore the Potential Immunomodulatory Mechanisms of Deer Antler
Authors: Liu Lingyu , Jiao Yu , Yang Mei , Wu Lei , Long Guohui , Hu Wei
Published: June 2023

The use of deer antlers dates back thousands of years in Chinese history. Deer antlers have antitumor, anti-inflammatory, and immunomodulatory properties and can be used in treating neurological diseases. However, only a few studies have reported the immunomodulatory mechanism of deer antler active compounds. Using network pharmacology, molecular docking, and molecular dynamics simulation techniques, we analyzed the underlying mechanism by which deer antlers regulate the immune response. We identified 4 substances and 130 core targets that may play immunomodulatory roles, and the beneficial and non-beneficial effects in the process of immune regulation were analyzed. The targets were enriched in pathways related to cancer, human cytomegalovirus infection, the PI3K-Akt signaling pathway, human T cell leukemia virus 1 infection, and lipids and atherosclerosis. Molecular docking showed that AKT1, MAPK3, and SRC have good binding activity with 17 beta estradiol and estrone. Additionally, the molecular dynamics simulation of the molecular docking result using GROMACS software (version: 2021.2) was performed and we found that the AKT1–estrone complex, 17 beta estradiol–AKT1 complex, estrone–MAPK3 complex, and 17 beta estradiol–MAPK3 complex had relatively good binding stability. Our research sheds light on the immunomodulatory mechanism of deer antlers and provides a theoretical foundation for further exploration of their active compounds.
Characterization of the LysP2110-HolP2110 Lysis System in Ralstonia solanacearum Phage P2110
Authors: Chen Kaihong , Guan Yanhui , Hu Ronghua , Cui Xiaodong , Liu Qiongguang
Published: June 2023

Ralstonia solanacearum, a pathogen causing widespread bacterial wilt disease in numerous crops, currently lacks an optimal control agent. Given the limitations of traditional chemical control methods, including the risk of engendering drug-resistant strains and environmental harm, there is a dire need for sustainable alternatives. One alternative is lysin proteins that selectively lyse bacteria without contributing to resistance development. This work explored the biocontrol potential of the LysP2110-HolP2110 system of Ralstonia solanacearum phage P2110. Bioinformatics analyses pinpointed this system as the primary phage-mediated host cell lysis mechanism. Our data suggest that LysP2110, a member of the Muraidase superfamily, requires HolP2110 for efficient bacterial lysis, presumably via translocation across the bacterial membrane. LysP2110 also exhibits broad-spectrum antibacterial activity in the presence of the outer membrane permeabilizer EDTA. Additionally, we identified HolP2110 as a distinct holin structure unique to the Ralstonia phages, underscoring its crucial role in controlling bacterial lysis through its effect on bacterial ATP levels. These findings provide valuable insights into the function of the LysP2110-HolP2110 lysis system and establish LysP2110 as a promising antimicrobial agent for biocontrol applications. This study underpins the potential of these findings in developing effective and environment-friendly biocontrol strategies against bacterial wilt and other crop diseases.
Immunogenicity Analysis of PCV3 Recombinant Capsid Protein Virus-like Particles and Their Application in Antibodies Detection
Authors: Cao Xuyang , Huang Min , Wang Ying , Chen Yanzhi , Yang Hanwen , Quan Fusheng
Published: June 2023

Porcine circovirus type 3 is a newly emerging pathogen of porcine circovirus associated disease (PCVAD). Currently, there is no commercially available vaccine, resulting in huge economic losses to the pig industry. Porcine circovirus type 3 capsid protein (Cap) can self-assemble into virus-like particles (VLPs). Therefore, the expression of the recombinant Cap protein is of great significance for the prevention, diagnosis and control of porcine circovirus type 3 associated diseases. In this study, the recombinant Cap protein was successfully expressed in Escherichia coli by deleting the nuclear localization sequence (NLS). The VLPs were observed by transmission electron microscopy. To evaluate the immunogenicity of the recombinant Cap protein, mice were immunized. As a result, the recombinant Cap protein can induce higher levels of humoral and cellular immune responses. A VLP-based ELISA method was developed for the detection of antibodies. The established ELISA method has good sensitivity, specificity, repeatability and clinical applicability. These results demonstrate the successful expression of the PCV3 recombinant Cap protein and the preparation of recombinant Cap protein VLPs, which can be used for the preparation of subunit vaccines. Meanwhile, the established I-ELISA method lays a foundation for the development of the commercial PCV3 serological antibody detection kit.
Lactobacillus fermentum HY7302 Improves Dry Eye Symptoms in a Mouse Model of Benzalkonium Chloride-Induced Eye Dysfunction and Human Conjunctiva Epithelial Cells
Authors: Lee Kippeum , Jeong Ji Woong , Shim Jae Jung , Hong Hyun Sook , Kim Joo Yun , Lee Jung Lyoul
Published: June 2023

(1) We investigated the effects of the Lactobacillus fermentum HY7302 (HY7302) in a mouse model of benzalkonium chloride (BAC)-induced dry eye, and the possibility of using HY7302 as a food supplement for preventing dry eye. (2) The ocular surface of Balb/c mice was exposed to 0.2% BAC for 14 days to induce dry eye (n = 8), and the control group was treated with the same amount of saline (n = 8). HY7302 (1 × 109 CFU/kg/day, 14 days, n = 8) was orally administered daily to the mice, and omega-3 (200 mg/kg/day) was used as a positive control. To understand the mechanisms by which HY7302 inhibits BAC-induced dry eye, we performed an in vitro study using a human conjunctival cell line (clone-1-5c-4). (3) The probiotic HY7302 improved the BAC-induced decreases in the corneal fluorescein score and tear break-up time. In addition, the lactic acid bacteria increased tear production and improved the detached epithelium. Moreover, HY7302 lowered the BAC-induced increases in reactive oxygen species production in a conjunctival cell line and regulated the expression of several apoptosis-related factors, including phosphorylated protein kinase B (AKT), B-cell lymphoma protein 2 (Bcl-2), and activated caspase 3. Also, HY7302 alleviated the expression of pro-inflammatory cytokines, such as interleukin-1β (IL-1β), IL-6, and IL-8, and also regulated the matrix metallopeptidase-9 production in the conjunctival cell line. (4) In this study, we showed that L. fermentum HY7302 helps prevent dry eye disease by regulating the expression of pro-inflammatory and apoptotic factors, and could be used as a new functional food composition to prevent dry eye disease.
Single-Droplet Microsensor for Ultra-Short Circulating EFGR Mutation Detection in Lung Cancer Based on Multiplex EFIRM Liquid Biopsy
Authors: Wei Fang , Yu Peter , Cheng Jordan , Li Feng , Chia David , Wong David T. W.
Published: June 2023

Liquid biopsy is a rapidly emerging field that involves the minimal/non-invasive assessment of signature somatic mutations through the analysis of circulating tumor DNA (ctDNA) shed by tumor cells in bodily fluids. Broadly speaking, the unmet need in liquid biopsy lung cancer detection is the lack of a multiplex platform that can detect a mutation panel of lung cancer genes using a minimum amount of sample, especially for ultra-short ctDNA (usctDNA). Here, we developed a non-PCR and non-NGS-based single-droplet-based multiplexing microsensor technology, “Electric-Field-Induced Released and Measurement (EFIRM) Liquid Biopsy” (m-eLB), for lung cancer-associated usctDNA. The m-eLB provides a multiplexable assessment of usctDNA within a single droplet of biofluid in only one well of micro-electrodes, as each electrode is coated with different probes for the ctDNA. This m-eLB prototype demonstrates accuracy for three tyrosine-kinase-inhibitor-related EGFR target sequences in synthetic nucleotides. The accuracy of the multiplexing assay has an area under the curve (AUC) of 0.98 for L858R, 0.94 for Ex19 deletion, and 0.93 for T790M. In combination, the 3 EGFR assay has an AUC of 0.97 for the multiplexing assay.
BSR1, a Rice Receptor-like Cytoplasmic Kinase, Positively Regulates Defense Responses to Herbivory
Authors: Kanda Yasukazu , Shinya Tomonori , Maeda Satoru , Mujiono Kadis , Hojo Yuko , Tomita Keisuke , Okada Kazunori , Kamakura Takashi , Galis Ivan , Mori Masaki
Published: June 2023

Crops experience herbivory by arthropods and microbial infections. In the interaction between plants and chewing herbivores, lepidopteran larval oral secretions (OS) and plant-derived damage-associated molecular patterns (DAMPs) trigger plant defense responses. However, the mechanisms underlying anti-herbivore defense, especially in monocots, have not been elucidated. The receptor-like cytoplasmic kinase Broad-Spectrum Resistance 1 (BSR1) of Oryza sativa L. (rice) mediates cytoplasmic defense signaling in response to microbial pathogens and enhances disease resistance when overexpressed. Here, we investigated whether BSR1 contributes to anti-herbivore defense responses. BSR1 knockout suppressed rice responses triggered by OS from the chewing herbivore Mythimna loreyi Duponchel (Lepidoptera: Noctuidae) and peptidic DAMPs OsPeps, including the activation of genes required for biosynthesis of diterpenoid phytoalexins (DPs). BSR1-overexpressing rice plants exhibited hyperactivation of DP accumulation and ethylene signaling after treatment with simulated herbivory and acquired enhanced resistance to larval feeding. As the biological significance of herbivory-induced accumulation of rice DPs remains unexplained, their physiological activities in M. loreyi were analyzed. The addition of momilactone B, a rice DP, to the artificial diet suppressed the growth of M. loreyi larvae. Altogether, this study revealed that BSR1 and herbivory-induced rice DPs are involved in the defense against chewing insects, in addition to pathogens.