bluuebunny/crossref_metadata_2025 huggingface dataset:
The factors that influence protostellar multiplicity
Authors: Murillo N. M. , Fuchs C. M. , Harsono D. , Sakai N. , Hacar A. , Johnstone D. , Mignon-Risse R. , Zeng S. , Hsieh T. H. , Yang Y. L. , Tobin J. J. , Persson M. V.
Published: August 2024

Context. Protostellar multiplicity is common at all stages and mass ranges. However, the factors that determine the multiplicity of protostellar systems have not been systematically characterized through their molecular gas.

Aims. We characterize the physical properties of the Perseus molecular cloud at ≥5000 AU scales by mapping the diagnostic molecular lines.

Methods. We used Nobeyama 45m Radio Observatory (NRO) on-the-fly maps of HCN, HNC, HCO+, and N2H+ (J=1–0) toward five subregions in Perseus, complemented with single-pointing Atacama Pathfinder Experiment (APEX) observations of HNC (J = 4–3), to derive the physical parameters of the dense gas. The spatial resolutions of both observations were ~18″, which is equivalent to ~5000 AU scales at the distance of Perseus. The kinetic gas temperature was derived from the I(HCN)/I(HNC) J ratio, and the H2 density was obtained from the HNC J=4–3/J=1–0 ratio. These parameters were used to obtain the N2H+ (cold) and HCO+ (warm) gas masses. The inferred and derived parameters were then compared to source the parameters, including protostellar multiplicity, bolometric luminosity, and dust envelope mass.

Results. The inferred mean kinetic gas temperature (I(HCN)/I(HNC) J=1–0 ratio; ranging between 15 and 26 K), and H2 volumetric density (HNC J=4–3/J=1–0; 105−106 cm−3) are not correlated with multiplicity in Perseus. The derived gas and dust masses, 1.3 to 16 × 10−9 M⊙ for the cold-gas mass (N2H+), 0.1 to 25 M⊙ for the envelope dust masses (850 μm), and 0.8 to 10 × 10−10 M⊙ for the warm-gas mass (HCO+), are correlated to multiplicity and to the number of protostellar components. The warm-gas masses are lower by a factor of 16 than the cold-gas masses.

Conclusions. The gas and dust mass is correlated to multiplicity at ~5000 AU scales in Perseus. Higher-order multiples tend to have higher gas and dust masses in general, while close binaries (separations ≤7″) and single protostars have similar gas and dust mass distributions. On the other hand, the H2 density and kinetic gas temperature are not correlated with multiplicity.
Unveiling the HD 95086 system at mid-infrared wavelengths with JWST/MIRI
Authors: Mâlin Mathilde , Boccaletti Anthony , Perrot Clément , Baudoz Pierre , Rouan Daniel , Lagage Pierre-Olivier , Waters Rens , Güdel Manuel , Henning Thomas , Vandenbussche Bart , Absil Olivier , Barrado David , Cossou Christophe , Decin Leen , Glauser Adrian M. , Pye John , Olofsson Goran , Glasse Alistair , Lahuis Fred , Patapis Polychronis , Royer Pierre , Scheithauer Silvia , Whiteford Niall , Serabyn Eugene , Choquet Elodie , Colina Luis , Ostlin Göran , Ray Tom P. , Wright Gillian
Published: August 2024

Context. Mid-infrared imaging of exoplanets and disks is now possible with the coronographs of the Mid-InfraRed Instrument (MIRI) on theJames WebbSpace Telescope (JWST). This wavelength range unveils new features of young directly imaged systems and allows us to obtain new constraints for characterizing the atmosphere of young giant exoplanets and associated disks.

Aims. These observations aim to characterize the atmosphere of the planet HD 95086 b by adding mid-infrared information so that the various hypotheses about its atmospheric parameters values can be unraveled. Improved images of cirsumstellar disks are provided.

Methods. We present the MIRI coronagraphic imaging of the system HD 95086 obtained with the F1065C, F1140, and F2300C filters at central wavelengths of 10.575 µm, 11.3 µm, and 23 µm, respectively. We explored the method for subtracting the stellar diffraction pattern in the particular case when bright dust emitting at short separation is present. Furthermore, we compared different methods for extracting the photometry of the planet. Using the atmospheric modelsExo-REMandATMO, we measured the atmospheric parameters of HD 95086 b.

Results. The planet HD 95086 b is detected at the two shortest MIRI wavelengths F1065C and F1140C. The contribution from the inner disk of the system is also detected. It is similar to that in the HR 8799 system. The outer colder belt is imaged at 23 µm. Background objects are observed in all filters. The mid-infrared photometry provides better constraints on the atmospheric parameters. We evaluate a temperature of 800–1050 K, consistent with one previous hypothesis that only used near-infrared data. The radius measurement of 1.0–1.14 RJupis better aligned with evolutionary models, but still smaller than predicted. These observations allow us to refute the hypothesis of a warm circumplanetary disk.

Conclusions. HD 95086 is one of the first exoplanetary systems to be revealed at mid-infrared wavelengths. This highlights the interests and challenges of observations at these wavelengths.
NEOROCKS color survey: Final results
Authors: Birlan M. , Barucci M. A. , Belskaya I. , Fulchignoni M. , Hromakina T. , Sonka A. , Nedelcu A. , Colas F. , Fornasier S. , Merlin F. , Anghel S. , Poggiali G. , Perna D. , Dotto E. ,   the NEOROCKS team
Published: August 2024

Context. Near-Earth objects (NEOs) are the most accessible small Solar System bodies by both spacecrafts and ground-based telescopes. Close encounters of these objects with Earth represent opportunities to characterize their physical and mineralogical properties. They are also a constant threat to humanity due to possible impact events with Earth. In this context, the NEOROCKS project has been financed by the European Union’s Horizon 2020 research and innovation program.

Aims. We present the final results on photometry of the NEOROCKS project, with the aim of extending the dataset of surface colors for small NEOs with unknown properties and, when possible, characterizing newly discovered NEOs.

Methods. Photometric observations were performed using the 1.2 m telescope at the Haute-Provence observatory (in France) in the BVRI filters of the Johnson-Cousins photometric systems between May 2022 and June 2023. The stability and dynamics of objects from the NEOROCKS database was investigated by numerical integration.

Results. We obtained new surface colors for 83 NEOs. Overall, the NEOROCKS color database contains 170 objects. The majority of the objects in the dataset with diameters D<500 m belong to a group of silicate bodies. We estimated the unbalanced percentage between S- and C-type objects as an observational bias due to reflective proprieties of the surface of objects. The average of Lyapunov time of about 100 years is evidence of highly chaotic orbits of objects from the color database of NEOROCKS. Asteroid 2011 OL51 has a reasonable probability of being a parent body contributor to the October Capricornidis meteor shower. Asteroids 2004 HK33, 2022 VV (D-type), 2003 WR21, and 2017 SE1 (A-type) belong to end-member classes and have ΔV<7 km/s; thus, they are possible candidates for in situ investigations.
Suppression of giant planet formation around low-mass stars in clustered environments
Authors: Huang Shuo , Portegies Zwart Simon , Wilhelm Maite J. C.
Published: August 2024

Context. Current exoplanet formation studies tend to overlook the birth environment of stars in clustered environments. However, the effects of this environment on the planet formation process are important, especially in the earliest stage.

Aims. We investigate the differences in planet populations forming in star-cluster environments through pebble accretion and compare these results with planet formation around isolated stars. We strive to provide potential signatures of the young planetary systems to guide future observations.

Methods. We present a new planet population synthesis code designed for clustered environments. This planet formation model is based on pebble accretion and includes migration in the circumstellar disk. The disk’s gas and dust have been evolved via 1D simulations, while considering the effects of photo-evaporation of the nearby stars.

Results. Planetary systems in a clustered environment are different than those born in isolation; the environmental effects are important for a wide range of observable parameters and the eventual architecture of the planetary systems. Planetary systems born in a clustered environment lack cold Jupiters, as compared to isolated planetary systems. This effect is more pronounced for low-mass stars (≲0.2 M⊙). On the other hand, planetary systems born in clusters show an excess of cold Neptune around these low-mass stars.

Conclusions. In future observations, finding an excess of cold Neptunes and a lack of cold Jupiters could be used to constrain the birth environments of these planetary systems. Exploring the dependence of cold Jupiter’s intrinsic occurrence rate on stellar mass offers insights into the birth environment of their proto-embryos.
Existence, uniqueness and L2t(H2x) ∩ L∞t(H1x) ∩ H1t(L2x) regularity of the gradient flow of the Ambrosio–Tortorelli functional
Authors: Cortopassi Tommaso
Published: August 2024

We consider the gradient flow of the Ambrosio–Tortorelli functional, proving existence, uniqueness and L2t(H2x) ∩ L∞t(H1x) ∩ H1t(L2x) regularity of the solution in dimension 2. Such functional is an approximation in the sense of Γ-convergence of the Mumford–Shah functional often used in problems of image segmentation and fracture mechanics. The strategy of the proof essentially follows the one of []Feng and Prohl, M2AN Math. Model. Numer. Anal. 38 (2004) 291–320] but the crucial estimate is attained employing a different technique, and in the end it allows to prove better estimates than the ones obtained in [Feng and Prohl, M2AN Math. Model. Numer. Anal. 38 (2004) 291–320]. In particular we prove that if U ⊂ ℝ2 is a bounded C2 domain, the initial data (u0, z0) ∈ [H1(U)]2 with 0 ≤ z0 ≤ 1, then for every T > 0 there exists a unique gradient flow (u(t), z(t)) of the Ambrosio–Tortorelli functional such that (u, z) ∈ [L2(0, T; H2(U)) ∩ L∞(0,T;H1(U)) ∩H1(0,T;L2(U)]2 while previously such regularity was known only for short times.
Automatic berthing systems: a review on artificial intelligence methods for marine ship
Authors: Pitchaimuthu  , Vijayakumar K. , Pitchaimuthu Jeyasri
Published: August 2024

One of the most challenging issues in the world of ship control is automatic ship berthing. In order for the berthing to be completed automatically and safely, the control systems must account for the ship’s dynamics at low speeds. Artificial neural networks (ANNs) are frequently used to address this need because of their capacity to mimic and carry out all the functions of the human brain throughout the ship berthing procedure. However, there are still certain drawbacks when employing this theory to create the automatic system for ship berthing, and this makes it more challenging to develop the control system for practical ship applications. This study reviews the pros and cons of employing ANNs along with some other deep learning algorithms in automatic ship berthing systems. Some directions for further research into automatic ship-berthing systems are also suggested.
A novel bagging- XGBoost ensemble model for attaining high accuracy and computational efficiency in network intrusion detection
Authors: Nzuva Silas Mutie , Nder Lawrence , Mwalili Tobias
Published: August 2024

The study focuses on enhancing network intrusion detection to enhance network security and prevent potential data breaches. We propose B-XGBoost, an ensemble learning model that combines bagging and boosting, using 10k cross-validation and Bayesian optimization for binary network intrusion classification. The proposed model was trained and tested on the CIC-ID2017 dataset. Decision Trees, Random Forests, Support Vector Machines, Naive Bayes, k-Nearest Neighbors, and Neural Networks were trained and tested on the same dataset for performance comparison purposes. The results show that the BXGBoost algorithm had the highest F1 Score (0.982), Precision (0.975), Recall (0.990), Cohen’s Kappa (0.978), and ROC AUC (0.983). The other algorithms had varying levels of performance, with the Decision Trees having the second-highest F1 Score (0.950). Bayesian optimization significantly reduced the time, computational efficiency, and cost of hyperparameter tuning by using a probabilistic model to predict hyperparameters that resulted in high performance. The high scores in F1, precision, recall, agreement with human annotators, and ability to distinguish between positive and negative instances demonstrate the effectiveness of this approach in enhancing network security. For the best results of the B-XGBoost to be obtained, the hyperparameters of the base model need to be tuned to achieve maximum computational efficiency in light of the available resources.
Exploring the frontiers of school environmental health and artificial intelligence for sustainability
Authors: Nuryana Zalik , Nurcahyati Indah , Ichsan Yazida , Kurniawan Muh. Alif , Hanafiah Yusuf , Fadhlurrahman Fadhlurrahman , Rachmaningtyas Nur Anisyah , Aji Atqo Darmawan
Published: August 2024

This article examines the intersection of school environmental health and artificial intelligence (AI) in the context of sustainability. A bibliometric analysis was conducted using data from Scopus to explore publication trends, citation patterns, and thematic evolutions in the field. The study identifies key themes, influential authors, and significant publications shaping this area. Results show a strong focus on integrating AI in educational settings, highlighting the importance of sustainable practices in schools. The research emphasizes the role of AI in monitoring environmental parameters, managing energy resources, and supporting sustainable educational tools. Future research recommendations include further exploring the applications of AI in school environments for sustainability and health and investigating the potential of AI-driven educational tools in promoting sustainable behaviors among students.
Analyzing and Visualizing Knowledge Structures of Research and Development Trends in Internet of Things for Smart Agriculture: A Decade Overview
Authors: Maulana Fairuz Iqbal , Prasetyo Adi Puput Dani , Arifin Mohammad Nazir , Hamim Miftahul , Pramono Andi
Published: August 2024

Internet of Things (IoT) has become an increasingly important technology in Agriculture, has revolutionized the agricultural industry by providing farmers with real-time data on crop yields, soil moisture, and weather patterns. This research aims to provide a comprehensive overview of the latest developments in Scopus-based research on Internet of Things for Smart Agriculture over the last decade (2013-2022). A rigorous search method was used to identify IoT-related research publications in the Scopus database from 2013 to 2022. The study also identified research collaborations between various institutions, and countries and noted leading research contributions in this field. The top authors in this field are Kamienski, C., Suciu, G., and Debauche, O., while the top institutions are Vellore Institute of Technology, Universidade Federal do ABC, and Chandigarh University. The India, China, and United States were the most productive countries, with 356, 110, and 59 articles. The results of network visualization using VOSviewer found that there were 4 clusters based on their respective colours. The results of this study have the potential to provide valuable insights for scholars, practitioners, politicians, and funding organizations seeking to gain a comprehensive grasp of the current trends and objectives within this particular subject. The authors and institutions selected as the top performers in this study can provide excellent opportunities for cooperation and facilitate the acquisition of up-to-date knowledge in Smart Agriculture.
Applications of artificial intelligence in renewable energy: a bibliometric analysis of the scientific production indexed in scopus
Authors: Maulana Fairuz Iqbal , Prasetyo Adi Puput Dani , Hari Nirwana Haidar , Hamim Miftahul , Lestari Dian
Published: August 2024

The integration of Artificial Intelligence (AI) into renewable energy systems represents atransformative approach to addressing the challenges of energy sustainability and climate change. This paper conducts a comprehensive bibliometric analysis of the scientific production related to AI applications inrenewable energy, as indexed in Scopus over the last decade (2014-2023). The study identified research collaborations between various institutions, and countries and noted leading research contributions in this field. The famous authors in this specific field include of Olabi, A.G., Abdelkareem, M.A., and Zhou, Y., while the notable institutions include University of Sharjah, Ministry of Education of the People’s Republic of China, and Tsinghua University. The China, India, and United States were the most productive countries, with 103, 83, and 49 articles. The network visualisation analysis conducted with VOS viewer revealed the presence of 4 distinct clusters, each identified by its respective hue. The findings of this research have the capacity to offer significant understanding for academics, professionals, policymakers, and funding institutions aiming to get a comprehensive understanding of the present patterns and goals within this specific field. The findings obtained from this study offer a helpful structure for future research paths and emphasise the need for ongoing investment in Application of Artificial Intelligence to attain in Renewable Energy future.
Advancing computer science in education: integrating digital music technology into elementary school music programs
Authors: Sularso Sularso , Yu Qinyu , Pranolo Andri , Hardiyanti P Cicin
Published: August 2024

This article explores the transformative impact of integrating computer music technology into education, synthesizing evidence from diverse studies. The results underscore the positive influence on student engagement, skill development, and classroom dynamics. Innovative pedagogical approaches, incorporating interactive software, gamified learning experiences, and collaborative projects, empower students to actively participate in the learning process, fostering a dynamic and inclusive environment. Teachers play a pivotal role as facilitators in this paradigm shift, adapting their roles to guide students through technology-driven, personalized learning journeys. Despite the evident benefits, challenges such as limited access to technology and varying levels of technical proficiency present ongoing considerations for educators. Long-term impact assessments reveal the continuity of learning outcomes, trajectories of skill development, and the enduring influence on students’ lifelong learning habits. The synthesis of these findings contributes to a comprehensive understanding of the multifaceted effects of computer music technology in education. Future research directions should focus on refining strategies to address challenges, exploring sustained impacts on lifelong learning, and informing robust educational policies to harness the full potential of technology in shaping the future of music education.
Full overlap ship security model: an integrative approach to shipboard equipment information security
Authors: Melnyk Oleksiy , Onyshchenko Svitlana , Koskina Yuliia , Aleksandrovska Nadiia , Drozhzhyn Oleksii , Maluha Eduard , Pulyaev Igor , Bondaryuk Mykola
Published: August 2024

In the ever-changing landscape of maritime operations, securing critical shipboard equipment is of paramount importance. This paper propose the Full overlap ship security model (FOSM), a system designed to protect the critical equipment on board the ships. The model is a holistic combination of various security aspects, including physical protection, robust tamper protection, vigilant monitoring and incident detection, advanced anti-virus protection, fault-tolerant backup and recovery protocols, and comprehensive training modules. What makes the model unique is that it is seamlessly integrated with the very lifeblood of ships their critical equipment. This symbiotic relationship strengthens the foundation for safe operation even in the challenging and dynamic conditions of the high seas. With the (FOSM), maritime security goes beyond mere caution and becomes an assurance that allows vessels to navigate the seas with confidence, reliability and security.
Round key formation algorithm for symmetric block encryption algorithms
Authors: Umarovich Jurayev Gayrat , Xaitmurotovich Bozorov Askar , Boykoziyev
Published: August 2024

In this work, an algorithm for generating round keys of any length for symmetric block encryption algorithms was developed. The degree of randomness of the sequences generated using the key and initialization vector was evaluated. It has been shown to pass all 15 NIST statistical tests. The proposed algorithm can be used to generate round keys for block encryption algorithms.
Evaluation of user experience: a systematic literature review
Authors: Syahrozad Najwa Fionillah , Subriadi Apol Pribadi
Published: August 2024

System evaluation research on user experience applied in using mobile applications. Systematic review of papers taken from the last 6 years, papers published in conference publications or journals, and papers available in English. The strategy used in searching for 30 articles was to create research questions, search for keywords appropriate to the topic, carry out inclusion and exclusion and ensure the quality of the paper assessment. From various studies that evaluate application user experience, I found that there are many factors that have not been fully successful, so researchers use the questionnaire method more because they think this method is easier to reach users widely. This literature review aims to explore users’ experiences with system services, and why users who are experienced with mobile applications are likely to continue using those applications. This systematic review is a methodology for identifying, evaluating, and defining relevant research on this topic answering several research questions and using a replicable and verifiable process that aims to find out what has not met user expectations. The main findings of this literature review are the percentage results of factors that influence user experience, techniques used to evaluate user experience and the benefits of evaluating user experience.
Behavioral factors of intention to use pay later services. A systematic literature review
Authors: Fitriyah Nur Windiana , Nadlifatin Reny
Published: August 2024

One of the current phenomena that plays a key role in digital transformation is commerce via mobile devices, known as m-commerce. Financial transactions involve selling or buying m-commerce service products using digital payments; one of them is to pay later. This research aims to determine the factors influencing customers’ behavioral intentions to use Paylater in m-commerce applications. This study analyzes 30 accessible articles from well-known publishers in Scopus-indexed journals or the Web of Science. The result is 10 dimensions, that influence the intention to use pay later, namely behavior intention, social influence, information quality, perceived ease of use, financial literacy, hedonic values, perceived risk, perceived usefulness, trust, and habit. This paper produces a dimensional mapping model that will be used for further research.
Churn prediction analysis of telecom customers using svm, random forest and logistic regression models using orange data mining tools
Authors: Nurtriana Ana , Rachmawati Devi Dwi , Artiyasa Marina , Sidiq Deni Syahrudin Zapar
Published: August 2024

This research aims to apply classification algorithms to telecommunication customer churn data using Orange Data Mining. The methods used include Support Vector Machine (SVM), Random Forest and Logistic Regression. The dataset used is secondary data, the dataset is downloaded from the kaggle website with a total of 7,043 customer data and 21 variables that will be used to predict telecommunication churn and in this study Exploratory Data Analysis (EDA) was conducted to understand the characteristics of the data and identify patterns and trends that can be used to improve the performance of classification algorithms. The results of EDA show that telecommunication customer churn data has several characteristics, namely unbalanced churn data, with the number of customers who churn less than customers who do not churn. With the results of the accuracy value, namely Random Forest 76% followed by Logistic Regression 79% and SVM 74%. The best accuracy is obtained by Logistic Regression with an accuracy value of 79%. These results show that logistic regression has a better ability to classify telecommunication customer churn data compared to other classification algorithms, this research shows that Orange Data Mining can be used to classify telecommunication customer churn data.
A robust family of exponential attractors for a linear time discretization of the Cahn-Hilliard equation with a source term
Authors: Dor Dieunel , Pierre Morgan
Published: August 2024

We consider a linear implicit-explicit (IMEX) time discretization of the Cahn-Hilliard equation with a source term, endowed with Dirichlet boundary conditions. For every time step small enough, we build an exponential attractor of the discrete-in-time dynamical system associated to the discretization. We prove that, as the time step tends to 0, this attractor converges for the symmetric Hausdorff distance to an exponential attractor of the continuous-in-time dynamical system associated with the PDE. We also prove that the fractal dimension of the exponential attractor (and consequently, of the global attractor) is bounded by a constant independent of the time step. The results also apply to the classical Cahn-Hilliard equation with Neumann boundary conditions.
Protection during radiotherapy: selenium
Authors: Yan J. , Li D.
Published: August 2024

The multifaceted applications of nuclear technology, especially in cancer treatment through radiotherapy, bring considerable benefits to our daily lives but also necessitate the imperative for effective strategies to effectively mitigate radiation-induced issues. While strict compliance with usage specifications is essential, ensuring proper protection against radiation-induced damages is crucial. Selenium, in its various forms including selenomethionine, Ebselen, and sodium selenite, emerges as a promising radioprotective agent with demonstrated efficacy across diverse radiation-injured organs, highlighting its significance as an effective and potent antioxidant that affordable for most patients. Abundant experiments have exhibited the capacity of selenium-containing compounds and metabolites to function as valuable radioprotective adjuvants, emphasizing their potential in safeguarding against the adverse effects of radiation exposure. To harness the full radioprotective potential of selenium, further research is needed to optimize selenium supplementation strategies, taking into account factors such as timing and dosage, particularly in the context of radiotherapy.
Thermoluminescence dosimetry in small animal digital radiography, the dose to animals, and their adopters
Authors: Saeedian E. , Shakerian M. , ZarifSanayei A. , Rakeb Z. , Alizadeh F. N. , Sina S.
Published: August 2024

In veterinary radiology, The dose to radiation workers, animals, and the public should be reduced as low as reasonably achievable. Immobilization of the pets is necessary for obtaining images with acceptable image quality. The adopters are usually asked to immobilize their pets during the imaging. Therefore the dose equivalent values received by the animal adopters are also important. This study aims to assess the dose to the hands and whole body of the adopter and the entrance skin dose (ESD) to the animals undergoing radiographic imaging using LiF: Mg, Ti (TLD 100) for one month of work in a veterinary hospital in Shiraz. The results showed that the dose received by the animals varied from 0.20 mSv to 0.53 mSv. The average dose equivalent values to hands, Hp(0.07), and body, Hp(10) of adopters are 0.35, and 0.14 mSv Respectively.
Psychokardiologie – aus praktischer und klinischer
Sicht
Authors: Langheim Eike , Langner Peter , Köllner Volker
Published: August 2024

Um Entstehung, Verlauf, Therapie und Prävention kardiologischer und
psychosomatischer Störungen und deren Wechselwirkungen zu behandeln und zu
erforschen, hat sich in den letzten Jahren das Fachgebiet der Psychokardiologie
etabliert. In diesem Artikel sollen klinische und praktische Aspekte der
Psychokardiologie und die wichtigsten psychischen Komorbiditäten im Zusammenhang
mit Herzerkrankungen vermittelt sowie gezeigt werden, welche therapeutischen
Angebote es gibt.
Practical Synthesis of N-Anilinylphenothiazines Using a Cyclic Hypervalent Iodine Coupling Reagent
Authors: Morimoto Koji , Kita Yasuyuki , Yanase Kana , Dohi Toshifumi
Published: August 2024

An improved protocol for the synthesis of N-anilinylphenothiazines based on the coupling reaction of anilines with phenothiazines using cyclic iodine(III) reagent is presented. In the improved method, the product can be isolated and purified without using column chromatography, and the cyclic hypervalent iodine reagent can be quantitatively recovered by aliquot manipulation. The workup procedure presented here is simpler compared to previously reported ones, facilitating large-scale synthesis. The para-selective phenothiazination of nitrogen-containing heterocycles such as hydroquinoline, which is important in pharmacology, was also successfully performed.
Complete Closed-Loop Ventilatory Circuit Delays the Onset of Ventilator-Associated Pneumonia in Mechanically Ventilated Neurological Patients in the ICU: A Single-Center Prospective Preliminary Study
Authors: Raichurkar Archana K. , Ramesh V.J. , Surve Rohini M. , Kumari H.B. Veena , Chakrabarti Dhritiman
Published: August 2024

Background Ventilator-associated pneumonia (VAP) is preventable yet its incidence remains high. We compared conventional ventilator circuit with open suction and dual heated wire circuit (DHWC) with closed suction on the incidence of VAP.

Methods This is a single-center, prospective cohort study conducted at a tertiary care hospital in neurological patients admitted to the neuro-intensive care unit (neuro-ICU) and requiring mechanical ventilation (MV) for more than 48 hours. Patients were ventilated using either conventional ventilator circuit with open suction (open group) or DHWC with closed suction (closed group) and were observed for VAP during the first 14 days of MV. The incidence and day of onset of VAP, duration of MV, duration of neuro-ICU and hospital stay, and mortality was noted in each group.

Results A total of 63 patients were included (32 in open and 31 in closed group). The incidence of VAP was 9.3% in the open group and 12.9% in the closed group (p = 0.8). All the patients developed late VAP, that is, > 96 hours after intubation. However, as compared to the open group, VAP was observed much later in the closed group (day 7 vs. day 11). Duration of MV, neuro-ICU stay, hospital stay, and mortality did not differ significantly.

Conclusion In this study, VAP incidences are similar in both the groups. However, neurological patients requiring MV for a short period might benefit from the usage of DHWC with closed suction system as VAP was seen to occur later in this group. Further, a randomized controlled trial with larger sample size is desired to confirm our findings.
Anesthetic Challenges in Hirayama Disease Patients Undergoing Cervical Spine Surgery—A Case Series
Authors: Naskar Sreyashi , Chakrabarti Soumya , Dawn Dipanjan , Pahari Amita A.
Published: August 2024

Hirayama disease (HD) is a rare disease, resulting from cervical compressive myelopathy, manifesting as upper limb muscular atrophy, and rarely autonomic and upper motor neuron signs. Anesthesia management is challenging—careful neck positioning during bag-mask ventilation and endotracheal intubation, avoidance of drugs that release histamine, multimodal monitoring to avoid delayed recovery, anticipation of hypotension, and blood loss due to autonomic dysfunction—all this is necessary for successful outcome of general anesthesia in HD patients. This case series demonstrates that preexisting autonomic dysfunction in HD patients should alert the anesthesiologists regarding higher likelihood of hemodynamic perturbations and blood loss, compared with patients who have normal autonomic functions, and henceforth take appropriate precautionary measures.
Design of an fNIRS–EEG hybrid terminal for wearable BCI systems
Authors: Jeong Eugene , Seo Minseok , Kim Kyung-Soo
Published: August 2024

The importance of brain–computer interfaces (BCI) is increasing, and various methods have been developed. Among the developed BCI methods, functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) are favored due to their non-invasive feature and compact device sizes. EEG monitors the electrical potentials generated by the activation of neurons, and fNIRS monitors the blood flow also generated by neurons, resulting in signals with different properties between the two methods. As the two BCI methods greatly differ in the characteristics of the acquired neural activity signals, for cases of estimating the intention or thought of a subject by BCI, it has been proven that further accurate information may be extracted by utilizing both methods simultaneously. Both systems are powered by electricity, and as EEG systems are greatly sensitive to electrical noises, application of two separate fNIRS and EEG systems together may result in electrical interference as the systems are required to be in contact with the skin and stray currents from the fNIRS system may flow along the surface of the skin into the EEG system. This research proposes a wearable fNIRS–EEG hybrid BCI system, where a single terminal is capable of operating both as a continuous wave fNIRS emitter and as a detector, and also as an EEG electrode. The system has been designed such that the fNIRS and EEG components are electrically separated to avoid electrical interference between each other. It is expected that by utilizing the developed fNIRS–EEG hybrid terminals, the development of BCI analysis may be further accelerated in various fields.
Comprehensive study of interface state via the time-dependent second harmonic generation
Authors: Zhang Libo , Ye Li , Zhao Weiwei , Huang Chongji , Li Tao , Min Tai , Yang Jinbo , Tian Mingliang , Chen Xuegang
Published: August 2024

Electric field induced time-dependent second harmonic generation (TD-SHG) is an emerging sensitive and non-contact method for qualitatively/quantitatively probing semiconductor parameters. The TD-SHG signal is related to the evolution of the built-in electric field due to laser-induced electron generation and transportation. Here, we conducted a comprehensive study of fixed charge density (Qox) and interface state density (Dit) using the conventional conductance method to compare them with the SHG signal from TD-SHG. The extracted Qox is around 2.49 × 1010 cm−2 regardless of SiO2 thickness, corresponding to the constant SHG intensity at the minimum of TD-SHG. The extracted Dit linearly decreases with the SiO2 thickness, which is related to the linear change of extracted time constant from TD-SHG. Therefore, the TD-SHG, being a sensitive and non-contact method as well as simple and fast, can serve as an alternative approach to test the semiconductor parameters, which may facilitate semiconductor testing.
Enhanced non-viral gene delivery via calcium phosphate/DNA co-precipitates with low-voltage pulse electroporation in NK-92 cells for immunocellular therapy
Authors: Kuan Che-Yung , Yang I-Hsuan , Chang Chia-Ting , Chen Zhi-Yu , Lin Jhih-Ni , Kuo Wei-Ting , Lin Yu-Ying , Yueh Andrew , Lin Feng-Huei
Published: August 2024

Achieving high cell transfection efficiency is essential for various cell types in numerous disease applications. However, the efficient introduction of genes into natural killer (NK) cells remains a challenge. In this study, we proposed a design strategy for delivering exogenous genes into the NK cell line, NK-92, using a modified non-viral gene transfection method. Calcium phosphate/DNA nanoparticles (pDNA-CaP NPs) were prepared using co-precipitation methods and combined with low-voltage pulse electroporation to facilitate NK-92 transfection. The results demonstrated that the developed pDNA-CaP NPs exhibited a uniform diameter of approximately 393.9 nm, a DNA entrapment efficiency of 65.8%, and a loading capacity of 15.9%. Furthermore, at three days post-transfection, both the transfection efficiency and cell viability of NK-92 were significantly improved compared to standalone plasmid DNA (pDNA) electroporation or solely relying on the endocytosis pathway of pDNA-CaP NPs. This study provides valuable insights into a novel approach that combines calcium phosphate nanoparticles with low-voltage electroporation for gene delivery into NK-92 cells, offering potential advancements in cell therapy.
A new two-dimensional intrinsic ferrovalley material: Janus CeIBr monolayer
Authors: Li Shujing , Lv JiaPeng
Published: August 2024

The successful synthesis and discovery of unique properties in two-dimensional Janus materials have positioned them as promising candidates for applications in sensors, field-effect transistors, and ultrasensitive detectors. In this study, we utilized first-principles calculations to predict a novel Janus CeIBr monolayer. Our calculations show that Janus CeIBr monolayer behaves as a bipolar magnetic semiconductor, demonstrating both mechanical and thermodynamic stability, along with a high Curie temperature of 242 K and in-plane magnetic anisotropy (102.92 meV). A notable intrinsic valley splitting of 66 meV is also evident in CeIBr, highlighting its distinctive valley contrast characteristic. Furthermore, the application of biaxial strain effectively transforms the magnetic ground state of CeIBr from a ferromagnetic state to an antiferromagnetic state and alters the direction of the easy magnetization axis from in-plane to out-of-plane. Our findings offer a theoretical foundation for the design of novel anomalous valley Hall effect-based electronic devices utilizing the Janus CeIBr monolayer.
Particle swarm algorithm-based identification method of optimal measurement area of coordinate measuring machine
Authors: Chen Hongfang , Wu Huan , Gao Yi , Shi Zhaoyao , Wen Zhongpu , Liang Ziqi
Published: August 2024

A particle swarm algorithm-based identification method for the optimal measurement area of large coordinate measuring machines (CMMs) is proposed in this study to realize the intelligent identification of measurement objects and optimize the measurement position and measurement space using laser tracer multi-station technology. The volumetric error distribution of the planned measurement points in the CMM measurement space is obtained using laser tracer multi-station measurement technology. The volumetric error of the specified step distance measurement points is obtained using the inverse distance weighting (IDW) interpolation algorithm. The quasi-rigid body model of the CMM is solved using the LASSO algorithm to obtain the geometric error of the measurement points in a specified step. A model of individual geometric errors is fitted with least squares. An error optimization model for the measurement points in the CMM space is established. The particle swarm optimization algorithm is employed to optimize the model, and the optimal measurement area of the CMM airspace is determined. The experimental results indicate that, when the measurement space is optimized based on the volume of the object being measured, with dimensions of (35 × 35 × 35) mm3, the optimal measurement area for the CMM, as identified by the particle swarm algorithm, lies within the range of 150 mm < X < 500 mm, 350 mm < Y < 700 mm, and −430 mm < Z < −220 mm. In particular, the optimal measurement area is defined as 280 mm < X < 315 mm, 540 mm < Y < 575 mm, and −400 mm < Z < −365 mm. Comparative experiments utilizing a high-precision standard sphere with a diameter of 19.0049 mm and a sphericity of 50 nm demonstrate that the identified optimal measurement area is consistent with the results obtained through the particle swarm algorithm, thereby validating the correctness of the method proposed in this study.
Simulation of nuclear isomer production in laser-induced plasma
Authors: Ma Zhiguo , Wang Yumiao , Yang Yi , Wang Youjing , Zhao Kai , Li Yixin , Fu Changbo , He Wanbing , Ma Yugang
Published: August 2024

Nuclear isomers play essential roles in various fields, including stellar nucleosynthesis, nuclear clocks, nuclear batteries, clean nuclear energy, and γ-ray lasers. Recent technological advances in high-intensity lasers have made it possible to excite or de-excite nuclear isomers using table-top laser equipment. Utilizing a particle-in-cell code, we investigate the interaction of a laser with a nanowire array and calculate the production rates of the 73mGe (E1 = 13.3 keV) and 107mAg (E1 = 93.1 keV) isomers. For 73m1Ge, production by Coulomb excitation is found to contribute a peak efficiency of 1.0 × 1019 particles s−1 J−1, while nuclear excitation by electron capture (NEEC) contributes a peak of 1.65 × 1011 particles s−1 J−1. These results indicate a high isomeric production ratio, as well as demonstrating the potential for confirming the existence of NEEC, a long-expected but so far experimentally unobserved fundamental process.
Loads experienced by a Francis turbine during short and fast transient under part load operation
Authors: Zhou Xing , Dai Xiangyu , Huang Quanshui , Tang Xiaodan , Bai Zhipeng , Cervantes Michel J.
Published: August 2024

As hydropower is integrated into the renewable energy system, the turbine components are liable to many loads variation for regulation. The loads experienced under transient operation need to be accounted for and understood to develop adequate mitigation technique and strategies. To identify possible risks occurring during such short and fast transients, we investigate the nonlinear growth and time delay effects of pressure fluctuations, as well as the unsteady flow field evolution for a Francis turbine under load reduction in the part load regime. A two-stage transient process analytical framework is proposed via signal processing and vortex identification methods, including main transient and post-transient stages. In the main transient stage, the dominant frequency of pressure fluctuations within the draft tube shifts from 0.32·fn to 0.24·fn, accompanied by a fivefold increase in the amplitude. Furthermore, low-frequency pressure fluctuations in a wider range are identified (0–2·fn), source of possible resonance of power plant structures. The maximum pressure is reached in the post-transient stage after the end of the guide vane closure and is 50% larger than the maximum value in the main transient stage. When comparing the two components of pressure fluctuations within the draft tube, the synchronous component increases slowly but reaches the peak faster, which can be explained by the evolution of instantaneous vortex structure investigated with proper orthogonal decomposition. The findings are useful to ascertain possible risk factors along with the investigation of the evolution of non-stationary flow field in the context of frequent turbine load variations.
Colossal barocaloric effect of phase-change fatty acids
Authors: Xiong Tingjiao , Lin Jianchao , Zhou Tingting , Shi Guoyou , Ye Tingting , Pan Xiaomei , Liu Keke , Jiang Runjian , Zhang Ranran , Song Wenhai , Tong Peng , Sun Yuping
Published: August 2024

Materials exhibiting caloric effects can serve as green alternatives in place of the gas refrigerants used in traditional vapor refrigeration systems, which are facing rising energy usage and environmental issues. This study investigates the barocaloric effect of fatty acids, which are typical phase-change materials. Fatty acids exhibit a reversible isothermal entropy change of about 600 J kg−1 K−1 and an adiabatic temperature change of about 10 K at a pressure less than 60 MPa, resulting from the pressure-driven liquid–solid phase transition. In the solid state, the adiabatic temperature change of fatty acids is larger than that of the n-alkanes with similar transition temperatures. Raman analysis indicates that the population of the distorted molecular chains in fatty acids is remarkably decreased when they are transformed from liquid to solid state, leading to the colossal entropy change. For solid fatty acids, the intermolecular interactions characterized by the hydrogen bonds are significantly strengthened under pressure, which explains their large adiabatic temperature change. This study suggests fatty acids are promising refrigerants for eco-friendly barocaloric cooling.
Enhanced fracture toughness in NbxTiZrHf high-entropy alloys by metastability engineering
Authors: Li Qingze , Li Yuan , Zhang Nanqiu , Xu Xuanzhu , Wang Yipeng , Zhou Cangtao , Zou Yongtao
Published: August 2024

Compositional tuning of refractory high-entropy alloys (HEAs) is a powerful strategy to modulate their structural stability and mechanical properties. In this study, we investigate the sound velocities, elasticity, and mechanical properties of NbxTiZrHf (x = 0, 0.2, 0.4, 0.6, 0.8, and 1.0) HEAs using ultrasonic interferometry combined with Vickers hardness measurements. Notably, the metastable bcc Nb0.2TiZrHf HEAs exhibits exceptional fracture toughness, reaching up to 12.2 MPa·m1/2, which is 1.7–3.3 times higher than that of other bcc NbxTiZrHf counterparts. The mechanism for the abnormal strengthening in fracture toughness of Nb0.2TiZrHf HEAs is primarily attributed to the stress-induced bcc-to-hcp phase transition, which promotes plasticity/ductility strengthening and crack deflection. These findings provide deep insights into “metastability engineering” for designing refractory HEAs with superior fracture toughness and high strength.
Reduced-order model to approximate response matrices for filter stack spectrometers
Authors: Wong C.-S. , Luedtke S. V. , Broughton D. P. , Strehlow J. , Alvarado Alvarez M. , Bogale A. , Huang C.-K. , Wolfe B. , Schmidt T. R. , Reinovsky R. E. , Albright B. J. , Batha S. H. , Palaniyappan S.
Published: August 2024

We present a reduced-order model to calculate response matrices rapidly for filter stack spectrometers (FSSs). The reduced-order model allows response matrices to be built modularly from a set of pre-computed photon and electron transport and scattering calculations through various filter and detector materials. While these modular response matrices are not appropriate for high-fidelity analysis of experimental data, they encode sufficient physics to be used as a forward model in design optimization studies of FSSs, particularly for machine learning approaches that require sampling and testing a large number of FSS designs.
Mechanism of quantum chaos in molecular nonadiabatic electron dynamics
Authors: Takatsuka Kazuo , Arasaki Yasuki
Published: August 2024

The quantum nuclear kinematic interactions with electrons (or nonadiabatic interactions) are the inherent driving force that possibly causes a mixture of the adiabatic electronic states in molecules. Particularly in systems whose electron wavepackets lie in a densely quasi-degenerate electronic-state manifold where many-dimensional and many-state nonadiabatic interactions last continually, we have found before that those extensive mixings can lead to a quantum electronic-state chaos [K. Takatsuka and Y. Arasaki, J. Chem. Phys. 159, 074110 (2023)]. This chaos of electron dynamics is a new kind yet generic. This Communication identifies the mathematical/physical mechanism of this class of chaos by means of the collective coordinate analysis of the nonadiabatic interactions, along with the numerical applications to excited states of boron clusters. Some physical consequences of the present chaos are also discussed.