bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effect of vacuum preheating on the structure, electric, and optical properties of W-doped VO2 films prepared from thermal oxidation
Authors: Zheng Tao , Zhou Lincan , Huang Fei , Liu Baoshun , Tapasa Kanit , Termkoa Krongtip , Meechoowas Ekarat , Plermjai Kittiya 
Published: March 2023

Abstract
The effect of vacuum preheating on the structure, electric, and optical properties of the thermally oxidized W-doped VO2 films was studied. The results show that the film crystalline orientation and the inhomogeneous distribution of W increase after preheating. It was found that preheating at 700 °C and 800 °C reduces the metal-insulator transition (MIT) hysteresis because of the preferable orientation of the film along the (011) direction. The film preheated at 900 °C exhibits an undoped-like MIT due to a great increase in the inhomogeneous distribution of W. Preheating can affect the apparent activation energy of the cool-state resistances and increase the cool-state IR transmittances. By means of the Lorentz–Drude model, the conductance electron density (n
c) and energy band gaps (E
g) were obtained and discussed. It was shown that preheating can decrease the cool-state n
c and affect the E
g, indicating that the electronic band structure is changed by W doping.
Segmented silicon-based solid-state detector with thin dead layer for superheavy element research
Authors: Kuramoto Kosaku , Morimoto Kouji , Kaji Daiya , Brionnet Pierre , Takeyama Mirei , Kosugi Kazumasa , Tokanai Fuyuki 
Published: March 2023

Abstract
Silicon-based solid-state detectors (SSDs) are crucial for investigating the properties of superheavy elements (SHEs), since they measure the energy of SHEs and charged particles that are emitted as successive decay events of the SHEs. We have developed a segmented SSD for SHE studies using the new gas-filled recoil ion separators (GARIS-II and GARIS-III) at RIKEN. It is based on a back-illuminated Si PIN photodiode in which the irradiation is through the N+ layer. The detector is introduced as a side one for the GARIS focal plane detection system. To investigate the characteristics of the SSD, 241Am α particles were irradiated by automatically moving and rotating the α source for each segmented portion of the SSD. A Monte Carlo simulation was also performed to estimate the dead layer thickness of the segmented SSD.
Robust Decision Making for Autonomous Vehicles at Highway On-Ramps: A Constrained Adversarial Reinforcement Learning Approach
Authors: He Xiangkun , Lou Baichuan , Yang Haohan , Lv Chen 
Published: March 2023

<p>Reinforcement learning has demonstrated its potential in a series of challenging domains.</p>
<p>However, many real-world decision making tasks involve unpredictable environmental changes or unavoidable perception errors that are often enough to mislead an agent into making suboptimal decisions and even cause catastrophic failures.</p>
<p>In light of these potential risks, reinforcement learning with application in safety-critical autonomous driving domain remains tricky without ensuring robustness against environmental uncertainties (e.g., road adhesion changes or measurement noises). </p>
<p>Therefore, this paper proposes a novel constrained adversarial reinforcement learning approach for robust decision making of autonomous vehicles at highway on-ramps.</p>
<p>Environmental disturbance is modelled as an adversarial agent that can learn an optimal adversarial policy to thwart the autonomous driving agent.</p>
<p>Meanwhile, observation perturbation is approximated to maximize the variation of the perturbed policy through a white-box adversarial attack technique.</p>
<p>Furthermore, a constrained adversarial actor-critic algorithm is presented to optimize an on-ramp merging policy while keeping the variations of the attacked driving policy and action-value function within bounds.</p>
<p>Finally, the proposed robust highway on-ramp merging decision making method of autonomous vehicles is evaluated in three stochastic mixed traffic flows with different densities, and its effectiveness is demonstrated in comparison with the competitive baselines.</p>
On the Stability and Homogeneous Ensemble of Feature Selection for Predictive Maintenance: A Classification Application to Tool Condition Monitoring in Milling
Authors: Assafo Maryam , Städter J. Philipp , Meisel Tenia , Langendörfer Peter 
Published: March 2023

<p>Feature selection (FS) represents an essential step for many machine learning-based predictive maintenance (PdM) applications, including various industrial processes, components, and monitoring tasks. The selected features do not only serve as inputs to the learning models, but also they can influence further decisions and analysis, e.g., sensor selection, understandability of the PdM system. Hence, before deploying the PdM system, it is crucial to examine the reproducibility and robustness of the selected features under variations in the input data. This is particularly critical for the real-world datasets with a low sample-to-dimension ratio (SDR). However, to the best of our knowledge, stability of the FS methods under data variations has not been considered yet in the field of PdM. This paper addresses this issue with an application to tool condition monitoring in milling, where classifiers based on support vector machine and random forest were employed. We used a 5-fold cross-validation to evaluate three popular filter-based FS methods, namely Fisher score, maximum relevance minimum redundancy (mRMR), and ReliefF, in terms of both stability and macro-F1. Further, for each method, we investigated the impact of the homogeneous FS ensemble on both performance indicators. To gain broad insights, we used four (2:2) milling datasets generated from our experiments and NASA’s repository, which differ in the operating conditions, sensors, SDR, number of classes, etc. Among the findings: 1) Different FS methods can yield comparable macro-F1, yet considerably different FS stability values. 2) Fisher score (single and/or ensemble) is the superior in most of the cases. 3) mRMR’s stability is overall the lowest, the most variable over different settings, e.g., sensor(s), subset cardinality, and the one most benefiting from the ensemble. </p>
Multidimensional Hosting Capacity Region in Dutch MV Grid Congestion Management
Authors: Gong Sicheng , Cuk Vladimir , Cobben Sjef 
Published: March 2023

<p>The hosting capacity determines the grid ability to host integrated installations, where mutual-limitations among points of connection (POCs) are important and formulate a combinational feasible region. Intended to assess such interdependence for defining the region, this paper proposes a multidimensional hosting capacity region derivation scheme in a radial grid. As this scheme can be designed conservative, from a risk-averse viewpoint, it gains significant acceptance in the industrial sector. This multidimensional region not only exploits grid power delivery potential, but also aids in making grid congestion management decisions. A typical 10.5kV Dutch grid case has been tested accordingly, and corresponding results have confirmed the conservative property preservation of the region. The case study demonstrates that compared to the original hosting capacity concept, the region hypervolume gain ratio remains higher than 1.94. With proper measure selection, the estimated region occupation ratio can keep up to 92.50%. The congestion management decision computation time can also be reduced by 58.0% compared to that using the monolithic model. The effectiveness of the proposed scheme and its advantages in grid congestion management have been successfully confirmed. </p>
Navigating the Ethical Landscape of AI in Healthcare: Insights from a Content Analysis
Authors: Wu Yin , Liu Xiang Michelle 
Published: March 2023

<p>Rapid development of artificial intelligence (AI) has permeated various aspects of our lives. Its usage in the field of healthcare has shown significant improvement in the efficiency and efficacy of numerous aspects of healthcare services. However, wide applications of AI technologies in healthcare are also joined by ethical challenges threatening the privacy and security of public health. This study conducts a content analysis on primary organization and government documents related to ethical issues of AI in healthcare. While the transparency and explainability of AI technologies have been granted a great amount of focus, more region-specific discussions are in need. Inclusiveness and equity of access to AI technology in healthcare should also be considered more by regulators and practitioners when proposing future standards and legislation frameworks. </p>
A Novel Pumping Principle for a Total Artificial Heart
Authors: Bierewirtz Tim , Narayanaswamy Krishnaraj , Giuffrida Rosario , Rese Tim , Bortis Dominik , Zimpfer Daniel , Kolar Johann Walter , Kertzscher Ulrich , Granegger Marcus 
Published: March 2023

<p><strong>Objective:</strong> Total artificial hearts (TAH) are used as a temporary treatment for severe biventricular heart failure. Long-term cardiac replacement is hampered by limited durability and complication rates, which may be attributable to the modus operandi of state-of-the-art pumping systems. The aim of this study was to assess the feasibility of a novel valveless pumping principle for a durable pulsatile TAH (ShuttlePump). </p>
<p><strong>Methods</strong>: With a rotating and linearly shuttling piston within a cylindrical housing with 2 in- and outlets, the pump features only one single moving part and delivers pulsatile flow to both systemic and pulmonary circulation. The pump and actuation system were designed iteratively based on analytical and in silico methods, utilizing finite element methods (FEM) and computational fluid dynamics (CFD) Pump characteristics were evaluated experimentally in a mock circulation loop mimicking the cardiovascular system, while hemocompatibility related parameters were calculated numerically. </p>
<p><strong>Results:</strong> Pump characteristics cover the entire required operating range for a TAH (2.5 - 9L/min at 50 - 160mmHg arterial pressures) at stroke frequencies of 1.5 - 5Hz while balancing left and right atrial pressures. FEM analysis showed a mean overall copper losses of 8.84W, resulting in local blood temperature rise of < 2k. The CFD results of normalized index of hemolysis was 3.57 mg/100L and 95% of the pumps blood volume was exchanged after 1.42s. </p>
<p><strong>Conclusion:</strong> This study indicates feasibility of a novel pumping system for a TAH with numerical and experimental results substantiating further development of the ShuttlePump.</p>
Stock market prediction based on machine learning and social sentiment analysis
Authors: Zaman Noor , Ghazanfar Mustansar Ali , Anwar Madiha , Lee Sin Wee , Qazi Nadeem , Karimi Amin , Javed Ali 
Published: March 2023

<p>Precise stock market prediction is crucial for investors, but the volatility of the stock market is influenced by multiple factors such as public sentiments, business news, and related product volatility. While several algorithms have been proposed to predict the stock exchange index based on historical data, they are not ideal as external factors play a critical role in market volatility. To address this issue, we proposed a machine learning model that incorporates historical data with external factors such as social media sentiments, oil and gold trends, and financial news data to enhance prediction accuracy. Our study used HPQ, IBM, ORCL, and MSFT stock market datasets to validate the effectiveness of the proposed model, including an analysis of the impact of Covid19 on companies. Our experimental results showed the highest accuracy of 87.2% using oil and sentiment datasets. Additionally, we identified that social media significantly affects IBM stocks, and the GBM (Gradient Boosting Classifier) classifier produced consistent results. </p>
Inherently Decoupled Dc-Link Capacitor Voltage Control of Multilevel Neutral-Point-Clamped Converters
Authors: Garcia-Rojas Gabriel , Busquets-Monge Sergio , Griñó Robert , Campos-Salazar José M. 
Published: March 2023

<p>This letter derives and discusses the superiority of a simple dc-link capacitor voltage control configuration for multilevel neutral-point-clamped converters with any number of levels. The control involves <em>n</em>−2 control loops regulating the difference between the voltage of neighbor capacitors. These control loops are inherently decoupled; i.e., they are independent and the control action of one loop does not affect the others. The good performance of such control is confirmed through simulations and experiments. </p>
Ultrasound Concave 2D Ring Array for Retinal Stimulation
Authors: Lu Jian-yu , Lu Gengxi , Thomas Biju , Humayun Mark , Zhou Qifa 
Published: March 2023

<p>This paper developed an ultrasound concave 2D ring array transducer for retinal visual stimulation of the brain to restore vision in blind people. Theory, simulation, and experiment were presented. </p>
Prediction of Nocturnal Hypoglycaemia in Adults with Type 1 Diabetes using Machine Learning Classifiers
Authors: Afentakis Ioannis , Unsworth Rebecca , Herrero Pau , Oliver Nick , Reddy Monica , Georgiou Pantelis 
Published: March 2023

<p>1st dataset</p>
<ul>
<li>6-months randomized controlled, cross-over study</li>
<li>37 participants wearing CGM sensors and using MDI regimen</li>
<li>smartphone app where to record administered insulin and meal macronutrient information</li>
<li>diagnosed with T1D for more than 3 years</li>
</ul>
<p>2nd dataset</p>
<ul>
<li>head-to-head glucose monitoring study, comparing CGM and flash glucose monitoring</li>
<li>40 high- risk adult participants using MDI for their insulin treatment </li>
</ul>
Tandem Neural Network based Design of Multi-band Antennas
Authors: Gupta Aggraj , Karahan Emir , Bhat Chandan , Sengupta Kaushik , Khankhoje Uday 
Published: March 2023

<p>We present a deep neural network-based framework for designing multi-band microstrip antennas given a desired impedance matching spectrum. The approach enables a design methodology that generates the desired antenna structures rapidly (under a second) through an effective deep learning- enabled search of a large design space and eliminates the need for extensive domain knowledge of antenna design. The framework is built on our innovations in tandem neural networks consisting of two cascaded neural networks. Our structures are parameterized in an exponentially large design space of discrete variables (pixels), leading to the realization of nonintuitive structures. This end-to-end synthesis in terms of discrete variables is enabled by introducing a new type of “smooth thresholding” activation function, which, along with crucial regularization terms in the network loss function, aids in designing our structures. We perform extensive neural network optimizations and study various trade-offs in the design process. We demonstrate the efficacy of our methods by generating single and dual-band resonant structures, which can be up to 50% more compact in terms of area, and up to 18 % thinner in terms of substrate height than conventional structures, while retaining competitive performance parameters in terms of gain, polarization properties, radiation efficiency, and fractional bandwidth. </p>
MySQL Select Query Optimization Using Self-Join
Authors: Jain Vedant 
Published: March 2023

<p> The challenge of query execution in MySQL involves the efficient and accurate processing of SQL queries to retrieve, manipulate, and store data in a database. It requires optimizing the query execution plan, identifying and resolving performance issues, and ensuring data integrity and security. The challenge lies in balancing the trade-offs between query complexity, database size, system resources, and user requirements. Choosing the right approach depends on the specific characteristics of the data and workload. Therefore, in this paper, we have applied various techniques to get optimized results. </p>
Qualitative Systematic Review in Applied Linguistics: A Synthesis
Authors: Zhang Jinpei 
Published: March 2023

Qualitative Systematic Review (QSR) is the second-generation literature review that aims to synthesize primary qualitative studies. Its use is growing rather rapidly in medicine, nursing, education and other fields, but it remains underutilized in applied linguistics. In order to invite more qualitative systematic reviews in applied linguistics, this paper first provides the definition of QSR, outlines the key steps for its conduct, elaborates on the core procedure, i.e., synthesis methods, then illustrates with published examples of qualitative systematic reviews in applied linguistics, and finally explores the future directions.
Widely used drugs as radioprotectors and radiomitigators
Authors: Dykan I.N. , Alekseyenko A. , Kolotilov N.N. , Andrushchenko I.V. , Anton S. , Tuz E.V. , Loboda A.V. 
Published: March 2023

The purpose of the review is to briefly list the widely used 43 drugs that can be used as readily available non-toxic radioprotectors and radiomitigators in GDR and relevant situations.	Caffeine, acetylcysteine, ceruloplasmin, ibuprofen, acetylsalicylic acid, carnosine, cyclosporine, metformin, cholecalciferol, amifostine, artemisinin, theaflavin, succinic acid, chlorophyllin, diltiazem, ferulic acid, glutathione, glycyrrhizic acid, indomethacin, hesperidin, sulfasalazine, silymarin, thymol, kanamycin A, turmeric, troxerutin, lycopene, lipoic acid, enalapril, ursol acid, resveratrol, baicalein, valproic acid, pentoxifylline, melatonin, trehalose, palifermin, vitamin E, beta-carotene, vitamin A, vitamin C, heparin, chondroitin sulfate.
The frequency of detection of comorbid broncho-obstructive pathology in patients with arterial hypertension admitted to a specialized cardiological hospital
Authors: Klimova A. A. , Ambatello L. G. , Smolyakova E. V. , Zykov K. A. , Chazova I. E. 
Published: March 2023

Objective: To determine the frequency of detection of chronic obstructive pulmonary disease (COPD) and Asthma in patients who are admitted to specialized cardiological hospital with arterial hypertension (AH), including AH with chronic heart failure (CHF), coronary heart disease (CHD), cardiac arrhythmias. Analyze the possibility of early diagnosis and the validity of the modified questionnaire for screening risk factors and symptoms of broncho-obstructive pathology in patients with arterial hypertension.Materials and methods: The sample (n = 1000) consisting of individuals over the age of 18 who continuously arrive for inpatient treatment at the admission department of the National Medical Research Center of Cardiology with arterial hypertension, incl. AH with CHF, IHD and arrhythmias in the period from 2018 to 2019. Active identification of broncho-obstructive pathology among all persons was carried out (history taking, complaints), analysis of medical documents provided by patients (conclusions from outpatient and reference cards of the patient), screening of risk factors and symptoms of broncho-obstructive pathology (a modified questionnaire was used), external respiration function was assessed (computer spirometry), filled out the specialized respiratory questionnaires (CAT, mMRC, ACT).Results: The undiagnosed broncho-obstructive diseases was demonstrated against the background of their high occurrence in patients with hypertension, incl. CHF, coronary artery disease, NRS entering a specialized cardiological hospital. The study established the most likely predictors of airway obstruction in patients with hypertension, which signal the need to assess the function of external respiration (computed spirometry).Conclusions: The development and validation of a modified questionnaire makes it possible to identify specific symptoms and risk factors for bronchoobstructive diseases against the backdrop of their high prevalencre among patients who are admitted to cardiology hospital with arterial hypertension.
Doppler Constraints on Planetary Companions to Nearby Sun-like Stars: An Archival Radial Velocity Survey of Southern Targets for Proposed NASA Direct Imaging Missions*
Authors: Laliotis Katherine , Burt Jennifer A. , Mamajek Eric E. , Li Zhexing , Perdelwitz Volker , Zhao Jinglin , Butler R. Paul , Holden Bradford , Rosenthal Lee , Fulton B. J. , Feng Fabo , Kane Stephen R. , Bailey Jeremy , Carter Brad , Crane Jeffrey D. , Furlan Elise , Gnilka Crystal L. , Howell Steve B. , Laughlin Gregory , Shectman Stephen A. , Teske Johanna K. , Tinney C. G. , Vogt Steven S. , Wang Sharon Xuesong , Wittenmyer Robert A. 
Published: March 2023

Abstract
Directly imaging temperate rocky planets orbiting nearby, Sun-like stars with a 6 m class IR/O/UV space telescope, recently dubbed the Habitable Worlds Observatory, is a high-priority goal of the Astro2020 Decadal Survey. To prepare for future direct imaging (DI) surveys, the list of potential targets should be thoroughly vetted to maximize efficiency and scientific yield. We present an analysis of archival radial velocity data for southern stars from the NASA/NSF Extreme Precision Radial Velocity (EPRV) Working Group’s list of high-priority target stars for future DI missions (drawn from the HabEx, LUVOIR, and Starshade Rendezvous studies). For each star, we constrain the region of companion mass and period parameter space we are already sensitive to based on the observational baseline, sampling, and precision of the archival radial velocity (RV) data. Additionally, for some of the targets, we report new estimates of magnetic activity cycle periods, rotation periods, improved orbital parameters for previously known exoplanets, and new candidate planet signals that require further vetting or observations to confirm. Our results show that for many of these stars we are not yet sensitive to even Saturn-mass planets in the habitable zone, let alone smaller planets, highlighting the need for future EPRV vetting efforts before the launch of a DI mission. We present evidence that the candidate temperate super-Earth exoplanet HD 85512b is most likely due to the star’s rotation, and report an RV acceleration for δ Pav that supports the existence of a distant giant planet previously inferred from astrometry.
Efficient Electron Acceleration Driven by Flux Rope Evolution during Turbulent Reconnection
Authors: Wang Z. , Vaivads A. , Fu H. S. , Cao J. B. , Liu Y. Y. 
Published: March 2023

Abstract
Magnetic flux ropes or magnetic islands are important structures responsible for electron acceleration and energy conversion during turbulent reconnection. However, the evolution of flux ropes and the corresponding electron acceleration process still remain open questions. In this paper, we present a comparative study of flux ropes observed by the Magnetospheric Multiscale mission in the outflow region during an example of turbulent reconnection in Earth's magnetotail. Interestingly, we find the farther the flux rope is away from the X-line, the bigger the size of the flux rope and the slower it moves. We estimate the power density converted at the observed flux ropes via the three fundamental electron acceleration mechanisms: Fermi, betatron, and parallel electric field. The dominant acceleration mechanism at all three flux ropes is the betatron mechanism. The flux rope that is closest to the X-line, having the smallest size and the fastest moving velocity, is the most efficient in accelerating electrons. Significant energy also returns from particles to fields around the flux ropes, which may facilitate the turbulence in the reconnection outflow region.