bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficient Thermoelectric Cooler for Localized Cooling in Electronic Devices
Authors: Kumar Rishikesh , Khan Mohd. Kaleem , Pathak Manabendra
Published: April 2023

Modern electronic devices operate at high power density due to increased processing speeds and the miniaturization of electronic chips. Conventional fan cooling alone is not effective. The thermoelectric cooler (TEC) is one of the most viable substitutes, providing site-specific, rapid, and precise cooling. In the present work, we propose an efficient thermoelectric cooler design for mitigating the cooling demand of high-end electronic components such as microprocessors, semiconductor lasers, etc. A 3D numerical model is developed using the finite element method (FEM)-based commercial software COMSOL Multiphysics to investigate the effect of various geometric and operating parameters on the cooling performance of the thermoelectric cooler. The parameters such as fill factor, leg dimensions, heat sink size, and phase change material (PCM) filling pattern in the inter-fin spacings/gaps are optimized. Two heat sink PCM designs, M1 (alternate fin gaps filled) and M2 (all fin gaps filled), are investigated for hotspot mitigation. For no-load conditions, the thermoelectric cooler module with a 20% fill factor produces a cooling of 20.5 °C with an average cooling per unit input power of 37.5 °CW−1. When a heating load of 625 W/cm2 is applied, its cold-side temperature reaches 91 °C. TEC module with n-eicosane PCM (M2 design) provides an effective cooling of 37 °C and an average cooling per unit input power of 42.3 °CW−1.
Regulation Mechanism of Nicotine Catabolism in Sphingomonas melonis TY by a Dual Role Transcriptional Regulator NdpR
Authors: Wang Haixia , Wang Xiaoyu , Tang Qi , Wang Lvjing , Mei Chengyu , Shao Yunhai , Xu Ying , Lu Zhenmei , Zhong Weihong
Published: April 2023

Gene regulation is critical for microorganisms in the environment in which they may encounter various kinds of organic pollutants. Our study revealed that transcription of

ndpA
S
A
L

,
ndpTB
, and
ndpHFEGD
is negatively regulated by NdpR, and NdpR also exhibits a positive regulatory effect on P

ndpHFEGD

.
Quantitative
1
H Nuclear Magnetic Resonance Assay for the Rapid Detection of Pyrazinamide Resistance in Mycobacterium tuberculosis from Sputum Samples
Authors: Lopez Juan M. , Zimic Mirko , Vallejos Katherine , Sevilla Diego , Quispe-Carbajal Mariella , Roncal Elisa , Rodríguez Joseline , Rodríguez Jhojailith , Antiparra Ricardo , Arteaga Héctor , Gilman Robert H. , Maruenda Helena , Sheen Patricia
Published: April 2023

Tuberculosis (TB), caused by
Mycobacterium tuberculosis
, is one of the 10 leading killer diseases in the world. At least one-quarter of the population has been infected, and there are 1.3 million deaths annually.
Multicenter Evaluation of an MIC-Based Aztreonam and Ceftazidime-Avibactam Broth Disk Elution Test
Authors: Harris Harley , Tao Lili , Jacobs Emily B. , Bergman Yehudit , Adebayo Ayomikun , Tekle Tsigedera , Lewis Shawna , Dahlquist Ashley , Abbey Taylor C. , Wenzler Eric , Humphries Romney , Simner Patricia J.
Published: April 2023

Due to limited therapeutic options, there is a clinical need to assess the
in vitro
activity of the combination of aztreonam (ATM) and ceftazidime-avibactam (CZA) to guide the therapeutic management of multidrug-resistant (MDR) Gram-negative organism infections. We set out to develop a practical MIC-based broth disk elution (BDE) method to determine the
in vitro
activity of the combination ATM-CZA using readily available supplies and compare it to reference broth microdilution (BMD).
Pandemic Demand for SARS-CoV-2 Testing Led to Critical Supply and Workforce Shortages in U.S. Clinical and Public Health Laboratories
Authors: Cornish Nancy E. , Bachmann Laura H. , Diekema Daniel J. , McDonald L. Clifford , McNult Peggy , Stevens-Garcia Jonathan , Raphael Brian H. , Miller Melissa B.
Published: April 2023

COVID-19 has brought unprecedented challenges to clinical and public health laboratories. While U.S. laboratories have continued striving to provide quality test results during the pandemic, the uncertainty and lack of supplies became a significant hurdle, hindering day-to-day laboratory operations and the ability to increase testing capacity for both SARS-CoV-2 and non-COVID-19 testing.
Genome Sequences of Seven Clade B2 Escherichia coli Strains Associated with Recurrent Urinary Tract Infections in Postmenopausal Women
Authors: Hogins Jacob , Zimmern Philippe E. , Reitzer Larry
Published: April 2023

We report the genome sequences of seven recently isolated
Escherichia coli
strains from symptomatic postmenopausal women with a history of recurrent urinary tract infections. We have observed rapid laboratory evolution of strains after isolation. These strains were minimally passaged before analysis to prevent changes during culturing.
Complete Genome Sequence of Klebsiella pneumoniae Bacteriophage KpS110, Encoding Five Tail-Associated Proteins with Putative Polysaccharide Depolymerase Domains
Authors: Volozhantsev Nikolay V. , Verevkin Vladimir V. , Krasilnikova Valentina M. , Kislichkina Angelina A. , Popova Anastasia V.
Published: April 2023

We report the genome sequence of bacteriophage KpS110, which infects
Klebsiella pneumoniae
, a multidrug-resistant encapsulated bacterium that causes severe community-acquired and hospital-acquired infections. The phage genome is 156,801 bp, with 201 open reading frames. KpS110 is most closely related to phages of the family
Ackermannviridae
at the genome and proteome levels.
Slow Time Phenomena in Heterogeneous Materials: from Microscopic Fluctuations to Macroscopic Relaxation
Authors: Lebedev A. V.
Published: April 2023

Slow time relaxation of elastic moduli with typically logarithmic time dependence is observed in many media interesting for materials science. This phenomenon is related to internal structure and is, hence, important for the development of present-day materials. Here, we provide a general explanation showing a close link between slow time phenomena and fluctuations on the microscopic and mesoscopic scales. We look for the origin of slow time phenomena in random walk or diffusion processes on microscopic scales. Some bonds occurring in the metastable state make a transition through the energy barriers due to small fluctuations slightly perturbing the statistical equilibrium. If the number of the excited bonds is small compared to the total number of bonds in a heterogeneous material, the process of the transition as a whole can be considered as mesoscopic fluctuations. Averaging over all transient bonds or states is revealed in the observed macroscopic relaxation of elastic moduli, velocities, and others. The functional dependence on time in the relaxation process has been shown to be controlled by the profile of energy barriers. The results obtained point to their possible applications in materials science.
Consensus definition of sludge and microlithiasis as a possible cause of pancreatitis
Authors: Żorniak Michal , Sirtl Simon , Beyer Georg , Mahajan Ujjwal Mukund , Bretthauer Katharina , Schirra Jörg , Schulz Christian , Kohlmann Thomas , Lerch Markus M , Mayerle Julia
Published: April 2023

Objective

In up to 20% of patients, the aetiology of acute pancreatitis (AP) remains elusive and is thus called idiopathic. On more detailed review these cases can often be explained through biliary disease and are amenable to treatment. Findings range from biliary sludge to microlithiasis but their definitions remain fluid and controversial.

Design

A systematic literature review (1682 reports, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines) analysed definitions of biliary sludge and microlithiasis, followed by an online international expert survey (30 endoscopic ultrasound/hepatobiliary and pancreatic experts; 36 items) which led to definitions of both. These were consented by Delphi voting and clinically evaluated in a retrospective cohort of patients with presumed biliary pancreatitis.

Results

In 13% of original articles and 19.2% of reviews, microlithiasis and biliary sludge were used synonymously. In the survey, 41.7% of experts described the term ‘sludge’ and ‘microlithiasis’ as identical findings. As a consequence, three definitions were proposed, agreed on and confirmed by voting to distinctly discriminate between biliary sludge (hyperechoic material without acoustic shadowing) and microlithiasis (echorich calculi of ≤5 mm with acoustic shadowing) as opposed to larger biliary stones, both for location in gallbladder and bile ducts. In an initial attempt to investigate the clinical relevance in a retrospective analysis in 177 confirmed cases in our hospital, there was no difference in severity of AP if caused by sludge, microlithiasis or stones.

Conclusion

We propose a consensus definition for the localisation, ultrasound morphology and diameter of biliary sludge and microlithiasis as distinct entities. Interestingly, severity of biliary AP was not dependent on the size of concrements warranting prospective randomised studies which treatment options are adequate to prevent recurrence.
Postcancer treatment support programme: an evaluation
Authors: Murray Charlotte , Makinson Jenny , Brown Lauren , Allan Julia
Published: April 2023

Objectives

As the number of people living beyond cancer treatment has increased, supportive post-treatment interventions have become increasingly important. The present study investigates whether participation in the Maggie’s ‘Where Now?’ post-cancer support programme is associated with improvements in healthy eating, quality of life, self-efficacy (confidence) or cancer worry.

Methods

In a pre–post design, 88 people who had completed cancer treatment and were enrolled in the 7-week ‘Where Now?’ programme at Maggie’s centres across the UK rated their diet, activity, quality of life, self-efficacy and cancer worries before and after programme participation. Programme content was coded to identify the techniques used to create change (‘behaviour change techniques’).

Results

Programme participation was associated with significant improvements in general self-efficacy (p=0.01), self-efficacy about engaging in physical activity (p<0.01), quality of life (p<0.01) and cancer worry (p=0.04) but not with changes in healthy eating (p=0.23).

Conclusion

Participation in the ‘Where Now?’ programme is associated with significant improvements in several key psychological outcomes in people living beyond cancer. The techniques most commonly used in the programme to create change were giving participants instructions about how to perform a particular behaviour, encouraging problemsolving to overcome barriers and setting goals.
The Boltzmann equation and equilibrium thermodynamics in Lorentz-violating theories
Authors: Potting Robertus
Published: April 2023

In this work, we adapt the foundations of relativistic kinetic theory and the Boltzmann equation to particles with Lorentz-violating dispersion relations. The latter are taken to be those associated to two commonly considered sets of coefficients in the minimal Standard-Model Extension. We treat both the cases of classical (Maxwell–Boltzmann) and quantum (Fermi–Dirac and Bose–Einstein) statistics. It is shown that with the appropriate definition of the entropy current, Boltzmann’s H-theorem continues to hold. We derive the equilibrium solutions and then identify the Lorentz-violating effects for various thermodynamic variables, as well as for Bose–Einstein condensation. Finally, a scenario with nonelastic collisions between multiple species of particles corresponding to chemical or nuclear reactions is considered.
Detecting topological phases in the square–octagon lattice with statistical methods
Authors: Wunderlich Paul , Ferrari Francesco , Valentí Roser
Published: April 2023

Electronic systems living on Archimedean lattices such as kagome and square–octagon networks are presently being intensively discussed for the possible realization of topological insulating phases. Coining the most interesting electronic topological states in an unbiased way is however not straightforward due to the large parameter space of possible Hamiltonians. A possible approach to tackle this problem is provided by a recently developed statistical learning method (Mertz and Valentí in Phys Rev Res 3:013132, 2021. https://doi.org/10.1103/PhysRevResearch.3.013132), based on the analysis of a large data sets of randomized tight-binding Hamiltonians labeled with a topological index. In this work, we complement this technique by introducing a feature engineering approach which helps identifying polynomial combinations of Hamiltonian parameters that are associated with non-trivial topological states. As a showcase, we employ this method to investigate the possible topological phases that can manifest on the square–octagon lattice, focusing on the case in which the Fermi level of the system lies at a high-order van Hove singularity, in analogy to recent studies of topological phases on the kagome lattice at the van Hove filling.
An Efficient and Accurate Cross-Domain Object Detection Method Using One-Level Feature and Domain Adaptation
Authors: Zhang Tianyuan , Song Xudong , Zhu Chen , Liang Pan , Sun Jialiang , Wang Shuo , Cui Yunxian , Li Changxian
Published: April 2023

To improve the accuracy of cross-domain object detection, the existing unsupervised domain adaptation (UDA) object detection methods mostly use Feature Pyramid Network (FPN), multiple Region Proposal Network (RPN), and multiple domain classifier, but these methods lead to complex network structures, slow model convergence, and low detection efficiency. To solve the above problems, this paper proposes an Efficient and Accurate Cross-domain Object Detection Method Using One-level Feature and Domain Adaptation (OFDA). This method realizes one-level feature object detection through feature fusion and divide-and-conquer technology; realizes overfitting feature suppression and unsupervised domain adaptation through domain-specific suppression and domain feature alignment technology; realizes background feature suppression through the Objectness branch, which replaces the time-consuming Region Proposal Network (RPN) structure and improves the efficiency of unsupervised adaptive detection. The paper verifies the feasibility and superiority of the proposed method by the comparative experiments and ablation experiments of multiple datasets. The proposed OFDA method not only improves the efficiency of object detection, but also ensures the accuracy of cross-domain detection.
The Lightweight Count System of Intensive Jellyfish Based on Deep Learning
Authors: Jin Yun , Zhang Haidong , Li Jiaxin , Bi Weihong
Published: April 2023

The number of jellyfish outbreaks is on the rise around the world, and they have been considered a serious ecological disaster. As part of the emergency response plan for jellyfish disasters, in-situ detection research that can distinguish jellyfish species and quantities is urgently required to support accurate data collection. As a typical fully supervised regression task, counting is usually regarded as requiring a large number of labeled datasets in conventional counting methods. To treat counting as a few-shot regression task that is semi-supervised, a novel adaptation strategy based on deep learning is presented in this paper. The method combines the test image with several example objects from the test image and takes advantage of the strong similarities present in the test image and the example objects contained in the image. Effective counting can be achieved without training the target object. Prediction of the density map of the test image’s objects of interest is the objective of the test. This method has been shown to be more robust than the method of detection first and counting later, and its accuracy can exceed 95%.
CHAOTIC DYNAMICS OF A STAGE-STRUCTURED PREY–PREDATOR SYSTEM WITH HUNTING COOPERATION AND FEAR IN PRESENCE OF TWO DISCRETE DELAYS
Authors: PAL SOUMITRA , GUPTA ASHVINI , MISRA ARVIND KUMAR , DUBEY BALRAM
Published: April 2023

Depending on behavioral differences, reproductive capability and dependency, the life span of a species is divided mainly into two classes, namely immature and mature. In this paper, we have studied the dynamics of a predator–prey system considering stage structure in prey and the effect of predator-induced fear with two discrete time delays: maturation delay and fear response delay. We consider that predators cooperate during hunting of mature prey and also include its impact in fear term. The conditions for existence of different equilibria, their stability analysis are carried out for non-delayed system and bifurcation results are presented extensively. It is observed that the fear parameter has stabilizing effect whereas the cooperative hunting factor having destabilizing effect on the system via occurrence of supercritical Hopf-bifurcation. Further, we observe that the system exhibits backward bifurcation between interior equilibrium and predator free equilibrium and hence the situation of bi-stability occurs in the system. Thereafter, we differentiate the region of stability and instability in bi-parametric space. We have also studied the system’s dynamics with respect to maturation and fear response delay and observed that they also play a vital role in the system stability and occurrence of Hopf-bifurcation is shown with respect to both time delays. The system shows stability switching phenomenon and even higher values of fear response delay leads the system to enter in chaotic regime. The role of fear factor in switching phenomenon is discussed. Comprehensive numerical simulation and graphical presentation are carried out using MATLAB and MATCONT.
Ferroelectricity in biological building blocks: Slipping on a banana peel?
Authors: Tofail Syed A. M.
Published: April 2023

Ferroelectricity in biological system has been anticipated both theoretically and experimentally over the past few decades. Claims of ferroelectricity in biological systems have given rise to confusion and methodological controversy. Over the years, a “loop” of induced polarization in response to a varying applied electrical field and a consequent polarization reversal has prompted many researchers to claim ferroelectricity in biological structures and their building blocks. Other observers were skeptical about the methodology adopted in generating the data and questioned the validity of the claimed ferroelectricity as such, “loop” can also be obtained from linear capacitors. In a paper with somewhat tongue-in-cheek title, Jim Scott showed that ordinary banana peels could exhibit closed loops of electrical charge which closely resemble and thus could be misinterpreted as ferroelectric hysteresis loops in barium sodium niobate, BNN paraphrasing it as “banana”. In this paper, we critically review ferroelectricity in biological system and argue that knowing the molecular and crystalline structure of biological building blocks and experimenting on such building blocks may be the way forward in revealing the “true” nature of ferroelectricity in biological systems.
A Multi-Temporal Analysis of Archaeological Site Destruction using Landsat Satellite Data and Machine Learning, Moche Valley, Peru
Authors: Payntar Nicole D.
Published: April 2023

The destruction of archaeological sites and the loss of archaeological landscapes remains a global concern as populations and urban areas continue to expand. Archaeological sites are not only significant to local communities, national identities, and modern tourist economies but also provide critical knowledge of past sociocultural interactions, settlement patterns, human-environment relationships, and risk mitigation strategies. While archaeological landscapes and site destruction have remained outside of traditional land use land cover change (LULCC) studies, they are a form of urban and agricultural land use. By conceptualizing archaeological site destruction within land change science, this study provides an innovative approach for assessing “what's left” of historically surveyed archaeological landscapes. Using a Random Forest algorithm and Landsat satellite data, this study quantifies archaeological site destruction attributed to LULCC in Peru's lower Moche Valley between 1985 and 2020. More than 400 archaeological sites previously recorded during the Chan Chan-Moche Valley Project (CCMVP, 1969–1974) are analyzed. Results indicate that less than a quarter of the original CCMVP sites remain on the landscape. The primary drivers of LULCC in the lower Moche Valley include population growth, migration, and government policies, while secondary drivers include heritage values. Positioning archaeological survey data within land change science and integrating machine learning techniques can benefit historic survey reassessments globally and provides significant knowledge of archaeological site destruction and the socioeconomic conditions that underly dynamic landscape changes.
Hardware IP Assurance against Trojan Attacks with Machine Learning and Post-processing
Authors: Gaikwad Pravin , Cruz Jonathan , Chakraborty Prabuddha , Bhunia Swarup , Hoque Tamzidul
Published: April 2023

System-on-chip (SoC) developers increasingly rely on pre-verified hardware intellectual property (IP) blocks often acquired from untrusted third-party vendors. These IPs might contain hidden malicious functionalities or hardware Trojans that may compromise the security of the fabricated SoCs. Lack of golden or reference models and vast possible Trojan attack space form some of the major barriers in detecting hardware Trojans in these third-party IP (3PIP) blocks. Recently, supervised machine learning (ML) techniques have shown promising capability in identifying nets of potential Trojans in 3PIPs without the need for golden models. However, they bring several major challenges. First, they do not guide us to an optimal choice of features that reliably covers diverse classes of Trojans. Second, they require multiple Trojan-free/trusted designs to insert known Trojans and generate a trained model. Even if a set of trusted designs are available for training, the suspect IP can have an inherently very different structure from the set of trusted designs, which may negatively impact the verification outcome. Third, these techniques only identify a set of suspect Trojan nets that require manual intervention to understand the potential threat. In this article, we present VIPR, a systematic machine learning (ML)-based trust verification solution for 3PIPs that eliminates the need for trusted designs for training. We present a comprehensive framework, associated algorithms, and a tool flow for obtaining an optimal set of features, training a targeted machine learning model, detecting suspect nets, and identifying Trojan circuitry from the suspect nets. We evaluate the framework on several Trust-Hub Trojan benchmarks and provide a comparative analysis of detection performance across different trained models, selection of features, and post-processing techniques. We demonstrate promising Trojan detection accuracy for VIPR with up to 92.85% reduction in false positives by the proposed post-processing algorithm.
Layered–Control Approach to Tune The Mobility of Perovskite SrTiO3: A Density Functional Theory Prospects
Authors: Ali Salamat , Parkash Anand , Alothman Asma A. , Almarhoon Zainab M. , Ouladsmane Mohamed , Qi Jing
Published: April 2023

The advancement of epitaxial technology has enabled the simulation of oxide heterostructures (HS) with unique interfacial material characteristics not found in bulk materials. Recent discoveries of emergent phenomena of definite oxide interfaces have attracted much attention to oxide HS. This work explored the possibility of tuning the electron mobility of SrTiO3 (STO) through CaSnO3/SrTiO3 and ZnSnO3/SrTiO3 HSs, based on density functional theory (DFT). Own to the Sn–5s states of CSO and ZSO with more substantial band dispersion than Ti–3d states of STO, near conduction band minimum (CBM), our simulated results suggest that the bandgaps of CSO/STO (0.502 eV) and ZSO/STO (0.349 eV) HS systems are much smaller than bulk STO (1.802 eV). The effective electron masses also show much smaller values (0.31 and 0.40 m0) and (0.38 and 0.52 m0) for (CSO)7/(STO)4 and (ZSO)1/(STO)4 for HS systems compared to bulk STO (7.03 and 0.94 m0) along Γ–X and Γ–M direction. The bandgap and effective electron masses results suggest that the bandgap of STO can be well controlled and tuned by the thin film layer numbers of CSO and ZSO with better electron transportability.
Graded Cladding Layers in Infrared III-Arsenide Separate Confinement Heterostructure Laser Diodes
Authors: Saeed Sana , Usman Muhammad , Aamir Muhammad , Islam Safiqul
Published: April 2023

Graded aluminum composition in AlGaAs n-cladding and p-cladding layers have been shown to exhibit improved optoelectronic performance in the single quantum well separate confinement heterostructure laser diode (SQW SCH LD) in the infrared region. The output power of the laser diode is increased up to 45 mW by using graded aluminum composition in n-/p- cladding layers. In addition, the lasing threshold current density is also lowered which results in a significant optical gain. The stimulated emission rate also improves due to improved electron-hole recombination and, thus, resulting in improved lasing.
Novel Nonlinear Control Method for First‐Order Systems and Its Implementation in a Temperature System
Authors: Chapa Ricardo , Ibarra Efrain , Guzman Valentin
Published: April 2023

In this work, a novel nonlinear control theory design for first‐order systems is developed, contributing to the improvement of the existing theory. The theory will allow a design of the open loop and closed‐loop controllers that ensure the tracking of any reference, constant, or variant in time with a free initial condition where the Laplace transform was used to find all the analytical solutions, avoiding the transfer function theory. Moreover, the closed‐loop control will be the best option to speed up or slow down the reference convergence rate in the desired finite time. Then, an algorithm indicating the steps for designing a closed‐loop controller and achieving proper tuning for a real‐time application is shown. Finally, this manuscript presents the results and discussions of the theory implemented in a prototype tank of a liquid temperature control system, where the effectiveness of the applied temperature control can be seen.
Investigation of Mechanical, Tribological, and Electrical Properties of Silk Reinforced Polymeric Composite
Authors: Ranjan Chikesh , Sarkhel Gautam , Kumar Kaushik
Published: April 2023

The continuous demand of today’s scenario and ecological consciousness has made the researchers think about the utilization of alternate sources of materials without compromising the mechanical behavior and characteristics while focusing on the fulfillment of the desired requirements in the wide range of industrial applications. The present work is a noble attempt and a step towards the development of silk fibre composites (SFCs) reinforced with the vinyl ester matrix material. The processing and fabrication of SFRCs have been carried out using the traditional hand layup technique using untreated silk fibres (SFs) and silk cloths (SCs) in the form of single, double, and triple layers of SFs and SCs laminates oriented in uniaxial and biaxial directions. For the prepared composite samples, the density and void contents in the sample, mechanical characteristics in terms of their tensile and flexural strength, and tribological characteristics as well as the electrical impedance have been investigated. The percentage void content was found to be within the acceptance limit. The tensile and flexural test results show a considerable increment which indicates proper stress transfer from matrix phase to fibre with triple-layer cloths showing the highest tensile and flexural properties. In the tribological test, the coefficient of friction is higher in the case of cloth loading as fibre concentration increases significantly. In the impedance test, almost for all samples, the trend of change in conductivity with applied frequency is the same. From the economic perspective, the proposed composite is suitable for a wide range of applications in industries as well as this can be utilized as an alternate source of traditionally used floor tiles currently using ceramic materials. Also, the proposed composite has a biodegradable characteristic that is completely in accordance with the demand and consciousness involved in environmental and ecological perspectives.
Satisfaction-Based Multiobjective Optimization of the Design of a 65 GHz Millimeter-Wave Connector
Authors: Li Xiang , Tong Lijun , Kong Zheng , Lu Wenju , Xie Qian
Published: April 2023

It is difficult to simultaneously ensure the radio frequency (RF) performance and mechanical strength of 65 GHz millimeter-wave connectors. To address this, satisfaction-based multiobjective method for connector design optimization is proposed. An optimization model is developed for the structural dimensions of 65 GHz millimeter-wave connectors to minimize the voltage standing wave ratio, insertion loss, and deflection and maximum stress of the center conductor. The proposed optimization model concurrently satisfies the design requirements in terms of characteristic impedance, transmission frequency, and dielectric withstanding voltage. The model is optimized by innovatively using the multiobjective chaotic optimization algorithm in microwave finite-element simulations. The resulting optimal structure satisfies all performance requirements, thereby proving the rationality and feasibility of the proposed method. Moreover, this study establishes a novel design for other microwave devices to solve the problem of multiple performance index restrictions.
A Loewner-Based System Identification and Structural Health Monitoring Approach for Mechanical Systems
Authors: Dessena Gabriele , Civera Marco , Zanotti Fragonara Luca , Ignatyev Dmitry I. , Whidborne James F.
Published: April 2023

Data-driven structural health monitoring (SHM) requires precise estimates of the target system behaviour. In this sense, SHM by means of modal parameters is strictly linked to system identification (SI). However, existing frequency-domain SI techniques have several theoretical and practical drawbacks. This paper proposes using an input-output system identification technique based on rational interpolation, known as the Loewner framework (LF), to estimate the modal properties of mechanical systems. Pioneeringly, the Loewner framework mode shapes and natural frequencies estimated by LF are then applied as damage-sensitive features for damage detection. To assess its capability, the Loewner framework is validated on both numerical and experimental datasets and compared to established system identification techniques. Promising results are achieved in terms of accuracy and reliability.
VM-Studio: A Universal Crosschain Smart Contract Verification and Execution Scheme
Authors: Han Tianxu , Mao Jian , Xie Sipeng , Gao Qiyuan , Wang Qin , Zhang Pinge , Fang Yijia
Published: April 2023

Blockchain interoperability promotes value delivery, application expansion, and ecological compatibility across heterogeneous blockchain systems. However, the contract framework and virtual machine construction in these systems are significantly different, and crosschaining becomes a challenging issue for system universality and compatibility. Starting from this problem, in this study, we propose VM-Studio, a crosschain smart contract verification and execution scheme to migrate the virtual machines (VMs) from the origin blockchain to the target blockchain. In our scheme, the migrated VMs are loaded as independent components enclosed in containers. We also design a unified system schedule to enable VM-Studio to allocate transactions into different containers. Loaded with origin blockchain VMs, these containers can accordingly solve crosschain transaction execution and smart contract verification. We implement VM-Studio and evaluate the transaction execution performance in the origin environment with multiple blockchains and the container environment. Experiment results demonstrate that VM-Studio achieves broad universality without compromising the execution performance of original blockchain transactions.
Daily Prediction Model of Photovoltaic Power Generation Using a Hybrid Architecture of Recurrent Neural Networks and Shallow Neural Networks
Authors: Castillo-Rojas Wilson , Bekios-Calfa Juan , Hernández César
Published: April 2023

In recent years, photovoltaic energy has become one of the most implemented electricity generation options to help reduce environmental pollution suffered by the planet. Accuracy in this photovoltaic energy forecasting is essential to increase the amount of renewable energy that can be introduced to existing electrical grid systems. The objective of this work is based on developing various computational models capable of making short-term forecasting about the generation of photovoltaic energy that is generated in a solar plant. For the implementation of these models, a hybrid architecture based on recurrent neural networks (RNN) with long short-term memory (LSTM) or gated recurrent units (GRU) structure, combined with shallow artificial neural networks (ANN) with multilayer perceptron (MLP) structure, is established. RNN models have a particular configuration that makes them efficient for processing ordered data in time series. The results of this work have been obtained through controlled experiments with different configurations of its hyperparameters for hybrid RNN-ANN models. From these, the three models with the best performance are selected, and after a comparative analysis between them, the forecasting of photovoltaic energy production for the next few hours can be determined with a determination coefficient of 0.97 and root mean square error (RMSE) of 0.17. It is concluded that the proposed and implemented models are functional and capable of predicting with a high level of accuracy the photovoltaic energy production of the solar plant, based on historical data on photovoltaic energy production.
On the Principles and Decisions of New Word Translation in Sino-Japan Cross-Border e-Commerce: A Study in the Context of Cross-Cultural Communication
Authors: Sulun Gaowa
Published: April 2023

In the context of the rapid development of multimedia and information technology, machine translation plays an indispensable role in cross-border e-commerce between China and Japan. However, due to the complexity and diversity of natural languages, a single neural machine translation model tends to fall into local optimality, leading to poor accuracy. To solve this problem, this paper proposes a general multimodal machine translation model based on visual information. First, visual information and text information are used to generate a visual representation of perceptual text information. Then, the two modal information are encoded separately, and the proportion of visual information in the whole multimodal information is controlled by a gating network. Finally, experiments are conducted on the image description datasets MSCOCO, Flickr30k, and video dataset VATEX, respectively. The results show that the algorithm in this paper achieves the best performance on both the BLEU and METEOR evaluation metrics.
Multi-Criteria Decision-Making with Novel Pythagorean Fuzzy Aggregation Operators
Authors: Al-Shamiri Mohammed M. , Ismail Rashad , Mazher Qurashi Saqib , Dilawar Fareeha , Ahmed Shami Faria
Published: April 2023

Unpredictability and fuzziness coexist in decision-making analysis due to the complexity of the decision-making environment. “Pythagorean fuzzy numbers” (PFNs) outperform “intuitionistic fuzzy numbers” (IFNs) when dealing with unclear data. The “Pythagorean fuzzy set” (PFS) is a useful tool because it removes the restriction that the sum of membership degrees be less than or equal to one by substituting the square sum for the sum of membership degrees. This study proposes two aggregating operators (AOs). The recommended operators outperform the already specified PFN operators. The proposed operator is utilised in the multicriteria decision-making process to identify the best candidate for instruction (MCDM).
Automatic Scoring Model of English Interpretation Based on Semantic Scoring
Authors: Ma Hua
Published: April 2023

In order to explore how English interpreting can achieve automatic scoring, the author proposes an automatic scoring model for English interpreting based on semantic scoring. This method recommends key technical problems and solutions based on information represented by semantic scoring, and explores the research on how interpreting can achieve automatic scoring of oral examinations. Research has shown that, the automatic scoring of English interpretation based on semantic scoring is faster than traditional methods, and the efficiency is improved by about 75%. However, the current automatic scoring of interpreters faces huge challenges. It needs to be tested and improved in more teaching, learning, and testing practice. The automatic scoring of interpretation should consider multiple dimensions such as semantic accuracy, content integrity, expressive fluency, and language authenticity.
Increased Rates of Hospitalized Children with Type 1 and Type 2 Diabetes Mellitus in Central Brooklyn during the COVID-19 Pandemic
Authors: Miller Assia , Joseph Shalu , Badran Ahmed , Umpaichitra Vatcharapan , Bargman Renee , Chin Vivian L.
Published: April 2023

Following reports of increased new-onset diabetes and worse severity of DKA for children with diabetes following SARS-CoV-2 infection, we studied hospitalization rates for children with type 1 diabetes (T1DM) and type 2 diabetes (T2DM) in our center during the citywide shutdown. Methods. We conducted a retrospective chart review of children admitted to our two hospitals from January 1, 2018, to December 31, 2020. We included ICD-10 codes for diabetic ketoacidosis (DKA), hyperglycemic hyperosmolar syndrome (HHS), and hyperglycemia only. Results. We included 132 patients with 214 hospitalizations: 157 T1DM, 41 T2DM, and 16 others (14 steroid induced, 2 MODY). Overall admissions rates for patients with all types of diabetes were 3.08% in 2018 to 3.54% in 2019 (

p
=
0.0120

) and 4.73% in 2020 (

p
=
0.0772

). Although there was no increase of T1DM admissions across all 3 years, T2DM admission rates increased from 0.29% to 1.47% (

p
=
0.0056

). Newly diagnosed T1DM rates increased from 0.34% in 2018 to 1.28% (

p
=
0.002

) in 2020, and new-onset T2DM rates also increased from 0.14% in 2018 to 0.9% in 2020 (

p
=
0.0012

). Rates of new-onset diabetes presenting with DKA increased from 0.24% in 2018 to 0.96% in 2020 (

p
=
0.0014

). HHS increased from 0.1% in 2018 to 0.45% in 2020 (

p
=
0.044

). The severity of DKA in newly diagnosed was unaffected (

p
=
0.1582

). Only 3 patients tested positive for SARS-CoV-2 infection by PCR. Conclusion. Our urban medical center is located in Central Brooklyn and serves a majority who are Black. This is the first study investigating pediatric diabetes cases admitted to Brooklyn during the first wave of the pandemic. Despite the overall pediatric admissions declining in 2020 due to the citywide shutdown, overall hospitalization rates in children with T2DM and in new-onset T1DM and T2DM increased, which is not directly associated with active SARS-CoV-2 infection. More studies are needed to elucidate the reason for this observed increase in hospitalization rates.
Stress Interferences between Fractures and Fracturing Stages of a Horizontal Well in a Sandy Conglomerate Reservoir in Junggar Basin, Northwest China
Authors: Li Jianmin , Du Binghui , Ma Junxiu , Liu Ruining , Shi Can , Lin Botao
Published: April 2023

The sandy conglomerate reservoirs in the Mahu oilfield located in the Junggar Basin of Northwest China are featured by a significant horizontal stress difference between two directions, making formations easy to form double-wing fractures upon hydraulic fracturing instead of creating a complex fracture network. In addition, as the well spacing or interval cluster spacing decreases, the stress interferences between hydraulic fractures strengthen accordingly, leading to more difficulties in the prediction of fracture propagation patterns. Given the geological characteristics in the study area, an extended finite element method (XFEM) based hydraulic fracture model that can handle fracturing fluid flow distribution was proposed to evaluate the seepage, stress, and damage of the formation under hydraulic fracturing. The influences of the initial stress difference, cluster spacing, and fracturing stage sequence on the hydraulic fracture stress interference and the fracture propagation were investigated, producing discoveries that include: (1) as the fractures propagate, the stress difference between two fractures changes as well, and such change is also affected by the initial stress difference and the fracture distance; (2) the postfracturing stress difference first decreases but then increases with the increase in cluster spacing; (3) as the cluster spacing increases, the interfracture stress interference decreases. In addition, the outer fractures suppress the length of the middle fractures, thus limiting the stimulated reservoir area (SRA); (4) for the cases of creating multistage fractures, the later fracturing stage experiences both the interfracture and the interstage stress interferences from the prefracturing stage. As the fracture width changes with time, the nonplanar fracture feature of the later fracturing stage becomes more evident while the corresponding SRA decreases.
COVID-19 in Cyanotic Congenital Heart Disease
Authors: Ammar Lama A , Nassar Joseph E , Bitar Fadi , Arabi Mariam
Published: April 2023

Congenital heart disease (CHD) is the most prevalent congenital defect in newborn infants. Due to the various types of heart abnormalities, CHD can have a wide range of symptoms. Cardiac lesions comprise a range of different types and accordingly varying severities. It is highly helpful to classify CHD into cyanotic and acyanotic heart diseases. In this review, we are investigating the course of Coronavirus disease 2019 (COVID-19) in cyanotic CHD patients. The infection may directly or indirectly affect the heart by affecting the respiratory system and other organs. The effect on the heart that is pressure- or volume-overloaded in the context of CHD is theoretically more severe. Patients with CHD are at a higher risk of mortality from COVID-19 infection or suffering worse complications. While the anatomic complexity of CHD does not seem to predict the severity of infection, patients with worse physiological stages are more susceptible such as cyanosis and pulmonary hypertension. Patients with CHD exhibit continuous hypoxemia and have lower oxygen saturations because of a right-to-left shunt. Such individuals run the danger of rapidly deteriorating in the event of respiratory tract infections with inadequate oxygenation. Additionally, these patients have a higher risk of paradoxical embolism. Hence, critical care should be given to cyanotic heart disease patients with COVID-19 in comparison to acyanotic patients and this is through proper management, close observation, and adequate medical therapy.
Optimization of Rare Ginsenosides and Antioxidant Activity Quality of Ginseng Jiaosu Based on Probiotic Strains and Fermentation Technology
Authors: Xu Yuqing , Tang Yuqian , Liu Tao , Liu Haocheng , Yang Jiguo , Meng Li
Published: April 2023

The primary active components of plant ginseng are saponins, and rare saponins play a specific antitumor action. In this study, Lactobacillus that can efficiently transform rare saponins were screened as fermentation strains of ginseng enzymes. The fermentation process was optimized to investigate the changes in various biochemical indicators and antioxidant activities of the enzymes before and after fermentation. The results showed that Lactiplantibacillus plantarum had the highest conversion efficiency for diol saponins, among which the content of rare ginsenoside-CK increased by 256%. The optimum optimizing method was a 1 : 1 : 10 ratio of ginseng extract/concentrated apple juice/water, fermentation time of 16 days, initial pH of 6.0, fermentation temperature of 37°C, and sterilization amount of 1.0%. The contents of rare ginsenoside-Rh1, ginsenoside-F2, ginsenoside-Rg3, and ginsenoside-CK increased by 18.48%, 135.73%, 343.03%, and 441.80%, respectively, and the process was stable and controllable. After fermentation, the scavenging rates for hydroxyl radical, DPPH radical, and superoxide anion radical were increased by more than 9%, and new organic acids were produced. In general, this study established an efficient, stable, and controllable ginseng fermentation process to improve the rare saponin content and biological activity of ginseng enzymes, which can provide new ideas for traditional Chinese medicine and medicinal health food in China.
α-Synuclein Attenuates Maneb Neurotoxicity through the Modulation of Redox-Sensitive Transcription Factors
Authors: Conde M. A. , Alza N. P. , Funk M. I. , Maniscalchi A. , Benzi Juncos O. N. , Berge I. , Uranga R. M. , Salvador G. A.
Published: April 2023

The accumulation and aggregation of α-synuclein is a pathognomonic sign of Parkinson’s disease (PD). Maneb (MB) exposure has also been reported as one environmental triggering factor of this multifactorial neurodegenerative disease. In our laboratory, we have previously reported that mild overexpression of α-synuclein (200% increase with respect to endogenous neuronal levels) can confer neuroprotection against several insults. Here, we tested the hypothesis that α-synuclein can modulate the neuronal response against MB-induced neurotoxicity. When exposed to MB, cells with endogenous α-synuclein expression displayed increased reactive oxygen species (ROS) associated with diminished glutamate-cysteine ligase catalytic subunit (GCLc) and hemeoxygenase-1 (HO-1) mRNA expressions and upregulation of the nuclear factor erythroid 2-related factor 2 (NRF2) repressor, BTB domain and CNC homolog 1 (BACH1). We found that α-synuclein overexpression (wt α-syn cells) attenuated MB-induced neuronal damage by reducing oxidative stress. Decreased ROS found in MB-treated wt α-syn cells was associated with unaltered GCLc and HO-1 mRNA expressions and decreased BACH1 expression. In addition, the increased SOD2 expression and catalase activity were associated with forkhead box O 3a (FOXO3a) nuclear compartmentalization. Cytoprotective effects observed in wt α-syn cells were also associated with the upregulation of silent information regulator 1 (SIRT1). In control cells, MB-treatment downregulated glutathione peroxidase 4 mRNA levels, which was coincident with increased ROS content, lipid peroxidation, and mitochondrial alterations. These deleterious effects were prevented by ferrostatin-1, an inhibitor of ferroptosis, under conditions of endogenous α-synuclein expression. The overexpression of α-synuclein attenuated MB toxicity by the activation of the same mechanisms as ferrostatin-1. Overall, our findings suggest that mild overexpression of α-synuclein attenuates MB-induced neurotoxicity through the modulation of NRF2 and FOXO3a transcription factors and prevents cell death probably by intervening in mechanisms associated with ferroptosis. Thus, we postulate that early stages of α-synuclein overexpression could be potentially neuroprotective against MB neurotoxicity.