bluuebunny/crossref_metadata_2025 huggingface dataset:
Financial Feasibility Analysis of llisha elongata Cracker Processing Businesses at Fish Processing Unit in Bengkalis, Riau
Authors: Harahap Kurnia Sada , Primyastanto M. , Soemarno  , Rudianto
Published: February 2024

This study analyzes the financial feasibility of fish cracker processing trades in Bengkalis Regency, Riau Province. The short-term and long-term feasibility analysis were used to determine the business feasibility. The data collected consists of primary and secondary data obtained through interviews, observations, and documentation. The analysis showed that the fish crackers processing business is profitable with an average monthly profit of Rp. 9,599,700. Therefore, the llisha elongata crackers processing business at the fish processing unit in Bengkalis is worth continuing.
Cropable - The Crop Disease Detection WebApp
Authors: Kumar Shashwat , Kumar Archisa , Goyal Disha , Chuli Anannya , Maniktalia Riddhi , Deepa K.
Published: February 2024

AbstractAccording to estimates, every year 10% of global production, goes waste due to pests and crop pathogens. For instance, India is a leading producer of many crops, including wheat, rice, lentils, sugarcane, and cotton. But a majority of the farmers are unable to detect whether a crop is infected or not simply by looking at it. As crop pathogens develop greater resistance to fungicides and pesticides, there is an urgent need to find new antifungal compounds to effectively combat them, which over time are rendered useless as the pathogens again develop resistance to these compounds. Thus, the food security of any country is always at risk due to the vulnerability of the current agricultural systems to climate, pests, pathogens, and associated diseases. To solve this problem, we have developed Cropable, The Crop Protection App. In the proposed work, we have used Deep Convolution Neural Networks( CNN) models to detect the disease and further created a web app using flask. Cropable is an Artificially Intelligent Web Application that can help to identify whether the crop is infected or not. We also provide farmers with a treatment for the detected disease, which not only helps them in identifying a disease but also assists them in solving it.
Enhancing Dimensional Geometry Casting using Computer Modeling
Authors: V Janakiraman , Arulpandy P. , Al-Fatlawy Ramy Riad , Ranganayaki S. , Singh Rajesh
Published: February 2024

Sand casting method is used to produce many useful products for many applications. The aim of the study is to manufacture a product with excellent dimensional geometry is achieved in sand casting process at low cost. We would expect manuscripts to show how design and/or manufacturing problems have been solved using computer modeling, simulation and analysis. In this work, the important mechanical properties of hardness and surface roughness are investigated on Aluminum 6063 cast material with and without incorporating the copper tubes as a vent hole in sand casting process. Since copper has high thermal conductivity when compared to other metals, the heat transfer rate will be varying from existing system. The copper tubes have made different diameters of holes on outer surfaces with selective distance of intervals. The specific number of copper tubes with various diameters are designed by CATIA modeling software and analyzed with Taguchi Design of Experiment. Taguchi L9 orthogonal array is used proficiently in the optimal value of hardness and surface roughness. The results are revealed that the maximum hardness value of 104 BHN is attained for 10mm distance of holes made on copper tube with an angle of 90o degree. The minimum surface roughness of 2.11 micron is achieved for 20mm distance of holes made on copper tube with 45o of angle as a vent hole in sand casting process.
Towards efficiently solving the rubik’s cube with deep reinforcement learning and recursion
Authors: Roshan M. Mahindra , Rakesh S. , Gnana Guru T. Sri , Rohith B. , Hemalatha J.
Published: February 2024

The Rubik’s cube is a prototypical combinatorial puzzle that has a large state space with a single goal state. The goal state is unlikely to be retrieved using orders of randomly generated moves, posing unique challenges for machine learning. The proposed work is above to solve the Rubik’s cube with recursion and DeepCubeA, a deep reinforcement learning approach that learns how to solve increasingly difficult states in reverse from the goal state without any specific domain knowledge. DeepCubeA solves 100% of all test patterns, finding a shortest path to the goal state 60.3% of the time. Deep Cube A generalizes to other combinatorial puzzles andis able to solve the 15 puzzle, 24 puzzle, 35 puzzle, 48 puzzle, Lights Out and Sokoban, finding a shortest path in the majority of verifiable cases. These models were trained with 1 4 GPUs and 20 30 CPUs. This varies throughout training as the training is often stopped and started again to make room for other processes. Further our experimentation compares the results of Rubik’s cube solving among both recursion and DeepCubeA and also with the state of art models. Later, we intend to develop a new deep learning model with an application.
Revolutionizing Agriculture: The Impact of AI and IoT
Authors: Ayad Alkhafaji Mohammed , Ramadan Ghazi Mohamad , Jaffer Zain , Jasim Laith
Published: February 2024

This review comprehensively examines the role of Artificial Intelligence (AI) and the Internet of Things (IoT) in revolutionizing agricultural practices. It highlights how these technologies are pivotal in enhancing crop productivity, optimizing resource use, and ensuring sustainability in response to the challenges of a growing global population and environmental concerns. The article synthesizes key studies to showcase advancements in smart aquaponics and marine farming, emphasizing the the importance of implementation of AI and IoT in agriculture faces significant challenges, including high costs, a digital skills gap among farmers, data management issues, and the need for robust technology. The review also addresses the socio-economic impacts, such as potential job displacement due to automation. Looking ahead, the article suggests that overcoming these challenges will require concerted efforts in technological innovation, policy-making, and education. The future of AI and IoT in agriculture is seen as promising, with potential for further advancements and wider adoption. The integration of these technologies with emerging fields like blockchain could lead to more secure, efficient, and transparent agricultural practices, contributing significantly to global food security and environmental sustainability.
Experimental and Statistical Study of Flexural Strength in Ternary Blended High-Performance Concrete using Alcofine
Authors: Durga Maligi , Sujaatha Anbuchozhan , Ramakrishnan Subramaniam , Harishankar Sooriakumar , Nasar Ali Razack
Published: February 2024

The primary aim of this research is to conduct a comprehensive comparative experimental and statistical study on the flexural strength of a novel ternary blended high-performance M30 grade concrete incorporating 20% Alcofine in comparison to traditional concrete.The components employed in the experimental investigation of high-performance M30 concrete incorporating Alcofine, in contrast to conventional concrete, comprise cement, fine aggregate, coarse aggregate, water, Alcofine, and additional cementitious materials like fly ash and silica fume. The Flexural Strength of high-performance M30 concrete containing Alcofine significantly influences the performance of concrete structures, rendering it a critical mechanical property for examination in the comparative analysis. The mean flexural strength of the Conventional Concrete group measured 8.1111 N/mm^2, with a standard deviation of 0.75840 and a standard error of the mean of 0.17876. In contrast, the Ternary Blended Concrete group exhibited a higher mean flexural strength of 12.5000 N/mm^2, coupled with a larger standard deviation of 2.09341 and a standard error of the mean of 0.49342. The statistical power analysis, involving parameters such as alpha (α) and beta (β), with commonly used values of 0.05 or 0.01, indicates a significance level of 5% or 1%, respectively. Further research could delve into refining the optimal percentage of Alcofine and exploring its long-term performance under varying environmental conditions. Keywords: Ternary Blended Concrete; Alcofine; Flexural Strength; Comparative Analysis; Statistical Study
Consumer perception application services among working women
Authors: Naveena R. , Mathan Kumar V.
Published: February 2024

Consumers have changed their shopping habits; consumers are shifted from offline to online shopping. In all sectors traditional system is replaced by technology. Food industries also developed their sector by adopting the technology online ordering. Consumers can order their foods without steeping out of their home and it makes convenience and easy for the consumers. Nowadays, a greater number of women are entering into working environment. So, the food delivery application will make the women work easier and convenience. This study is conducted to know the working women perception towards food application in Coimbatore city.
Study of modified thermoplastic elastomers based on polyethylene chlorinated with thiokol rubbers
Authors: Nurkulov F. , Ziyamukhamedov J. , Bakirov L. , Rakhmatov E. , Shoazimova U.
Published: February 2024

In this paper has been examined the mechanical properties of thermoelastoplastic polymer materials derived from polyethylene chlorinated with secondary polyethylene. In order to ensure the good performance of the thermoelastoplasts obtained in the external environment, attempts were made to increase their resistance to external influences by modifying them with 1% mass of polysulfide rubbers, and resistance to deformation was determined when studying the properties of the polymer material under UV light for 10 hours.
Sustainable Agriculture Practices: AI and IoT's Vital Contribution
Authors: Obaid Mohammed Kadhim , K.Alazzai Waleed , Sh.Z.Abood Baydaa , Al-Farouni Mohammed
Published: February 2024

The evolving landscape of agriculture has undergone a significant shift towards a technology-driven and data-centric approach, mainly propelled by the advent of Artificial Intelligence (AI) and the Internet of Things (IoT). This short review talks about numerous studies exploring the transformative impact of these cutting-edge technologies in sustainable agriculture practices. It outlines how the traditional statistical methods have given way to a more data-driven and quantitative approach, reshaping every facet of farming. The article emphasizes the immense potential of IoT in revolutionizing agriculture, shedding light on the challenges encountered when integrating these technologies into conventional farming systems. It explores the diverse applications of sensors and IoT devices across various agricultural stages, from land preparation and irrigation systems to pest control and harvesting techniques, while also highlighting the integration of advanced tools like unmanned aerial vehicles (UAVs) for crop monitoring and yield optimization. Overall, it emphasizes the urgency to embrace these innovative technologies, addressing key challenges for their seamless integration into traditional farming and aquaculture practices to ensure a sustainable and efficient future for agriculture.
Exploring the roles of AI-Assisted ChatGPT in the field of data science
Authors: Valli Latha Narayanan , Sujatha N. , Mech Mukul , V.S. Lokesh
Published: February 2024

In this study, we explore the roles of AI-assisted ChatGPT (Generative Pre-trained Transformer) in the field of data science. AI-assisted ChatGPT, a powerful language model, is fine-tuned using domain-specific data for specialised data science tasks, such as sentiment analysis and named entity recognition (NER). The results reveal significant reductions in model size and memory usage with minor trade-offs in inference time, providing valuable resource-efficient deployment. Various data augmentation methods, including back-translation, synonym replacement, and contextual word embeddings, are employed to augment the training dataset. The study's results are subjected to rigorous statistical analysis, including paired t-tests and ANOVA tests, to determine the significance of the findings. The research concludes with insightful suggestions and future scope, including advanced fine-tuning strategies, model optimization techniques, and ethical considerations.
An approach for crowd funding using blockchain
Authors: Anandkumar K.M. , Vignesh Shravan , Sivakumaar E M. , Adnaan I Syed
Published: February 2024

Contributing to charity is universally regarded as the moral thing to do. Moreover, billions of dollars are contributed every year as a result. Since the methods used by charitable organisations to collect donations are not always transparent to the public, they frequently struggle to gain the trust and attention of donors. This emphasises how crucial it is to address these problems to improve the transparency of the fundraising process and spending for contributors. A system built on the blockchain might be the solution to this issue. The shortcomings of the current distribution system served as the inspiration for this idea. We present a blockchain-based crowdfunding platform that we believe will be effective, open, and safe. This approach enables recognised charities to post their identities for investor verification in order to aid donors in avoiding funding to fake organisations. This is because blockchain limits other parties' capacity to tamper with, or even view, data, which is crucial for any organisation looking to increase the trust of its donor base. Nobody other than the trusted entity can edit or remove data once it has been stored in a blockchain. Investors, fundraisers, and fundraising platforms are all involved. Through the site, fundraising and charitable efforts are facilitated.
Interrelation of Migration and Employment Issues in Economics of New Uzbekistan Policy
Authors: Filimonova Liliya , Ismatullaeva Iroda , Saydivaliyeva Barno
Published: February 2024

This study focuses on the intricate issue of labour migration in Uzbekistan, characterised by both beneficial and detrimental effects. It underscores the role of migration in alleviating rural unemployment and bolstering market relations, but also notes the consequent 'brain drain' of young, skilled personnel, potentially undermining the nation's economic development. Drawing on research from the President's Office, the study evidences the overall positive impact of labour migration on rural socio-economic conditions, including unemployment reduction, income growth, and improved living standards. However, the study also uncovers a significant annual loss of about a million young individuals due to migration. Despite government interventions, such as policies encouraging the repatriation of skilled workers, the study concludes by emphasising the need for more comprehensive strategies to address the multifaceted ramifications of labour migration in Uzbekistan effectively.
Enhancing the Compressive Strength of M30 Grade of Concrete Using Pumice With 50% GGBS and Metakaolin Comparing with
Conventional Concrete
Authors: S. Manoj , T.S. Lakshmi
Published: February 2024

The aim is to compare the conventional concrete by employing a mix of M30 grade concrete, a novel pumice aggregate is used to partially replace the coarse aggregate to create lightweight concrete. All groups were prepared at the composition of 40% Cement and replacing 50% GGBS, 10% Metakaolin is kept constant in our concrete. Coarse aggregate replaced by novel pumice stone and M-sand as Fine aggregate. The group of 6 cubes was formed according to the curing dates of 28 days. Metakaolin and GGBS are procured from Scientific Company and Novel Pumice Aggregate are arranged from online traders. Cement and M sand were arranged from the local shop. The group of 18 cubes was formed according to the Curing date for 28 days. To determine the compressive strength, two groups and a total of 36 cubes were constructed. The average compressive strength test result for conventional concrete of grade M30 at 28 days is 30.28 N/mm2. The average result for Group I and for 18 cubes for the M30 grade of concrete @ 28 days Compressive Strength test result of Concrete with Novel Pumice Aggregate stone and Partial Replacement of GGBS and Metakaolin by the weight of cement is 35.19 N/mm2. From the independent t-test analysis p=0.000, i.e., smaller than p=0.05(p<0.05) which indicates that there is a noteworthy statistical distinction between the two groups. The compressive strength of concrete of M30 grade at 28 days of compressive strength test results of concrete with new pumice aggregate stone and partial replacement of GGBS and Metakaolin by the weight of cement is increased.
Study of Impact of Lifestyle Modification on Diabetes and Prediabetes in an Urban Population
Authors: Gode Yogesh , Patond Swapnil , Wankhade Vishwajit , Ghodki Sarang , Jadhav Deepali , Dhawade Manish Ramdas , Wankhade Yashwant
Published: February 2024

Diabetes mellitus has emerged as a prevalent noncommunicable disease worldwide. It ranks among the top causes of mortality in high-income countries and has reached epidemic proportions in newly developing nations.1 Continuous medical care and monitoring is required in Diabetes mellitus along with multi-factorial risk reduction strategies along associated with glycemic control. Due to population aging, growth, urbanization, a lack of physical exercise, and a high incidence of obesity, there are more persons with DM. Lifestyle factors include eating patterns, exercise routines, alcohol consumption, and smoking. An improvement in these parameters would lead to better adherence to hypoglycemic medications. An epidemiological study on diabetes and prediabetes in an urban area with reference to lifestyle modification. An interventional community-based study was conducted in an urban setup. Personal interviews using a semi-structured, pretested questionnaire were the main technique of data gathering. Detailed information has been taken on the demographic and socio-economic characteristics at both the individual and household levels. All responders provided their willingly given consent. Every second household was visited by systematic random sampling procedure to select 400 respondents. Finally, analysis was carried out on 346 respondents. All respondents were questioned using structured a pretested, questionnaire after taking informed consent. Significant difference was observed with positive family history of diabetes, obesity, physical activities in male, high calorie intake, stress, chewable tobacco and blood pressure level with diabetes and pre-diabetes. Compared to responders with normal level of blood glucose, pre diabetics and diabetics individual showed more positive family histories. Compared to responders with normal blood glucose levels, pre-diabetics and diabetics were more likely to be overweight. With regard to personal habits of the respondents, smoking was associated with more than 1-fold increase risk of obtaining serum glucose level >110 mg/dl as compared to non-smokers.The current research was an attempt to examine the effect of intervention with reference to life style modification. From the study, it is evident that overall awareness about diabetes has been found low and no awareness has been found about pre-diabetes. The present study also demonstrated that education is the fundamental tool to make the population aware of their health issues. Awareness about pre-diabetes and diabetes, which can make them beneficial for community and nation and so, they can play an innovative role for prevention of diabetes.
Was wissen Sie über … Gehirn und Nervensystem?
Authors: Schmid Eva C.
Published: February 2024

Liebe Leser, testen Sie Ihr Wissen und frischen Sie Ihre Kenntnisse auf. Bitte kreuzen Sie jeweils eine Antwort an. Viel Spaß beim Beantworten wünscht Ihnen HP Eva C. Schmid!
Analyse des Verantwortungs- und Tätigkeitsbereichs des
Berufsbilds „Sonographer“ und Möglichkeiten der
Umsetzung in Deutschland
Authors: Paetzold Katrin
Published: February 2024

Hintergrund Traditionell ist die Durchführung von
Ultraschalluntersuchungen in vielen europäischen Ländern
ärztliche Aufgabe. Im weltweiten Vergleich werden diese Untersuchungen
auch durch andere Berufe, sog. Sonographer, durchgeführt. Sonographer
sind medizinisch und technisch ausgebildete Fachleute, welche diagnostische
Ultraschalluntersuchungen unterschiedlicher Disziplinen durchführen. Im
deutschsprachigen Raum ist dieses Berufsfeld noch wenig bekannt und wird in
Fachkreisen kritisch diskutiert.

Ziel Das Ziel der Untersuchung war es, durch die Analyse der verschiedenen
Sonographer-Modelle einen möglichen Nutzen für die
Krankenversorgung in Deutschland zu erkennen und ein geeignetes
Ausbildungsmodell abzuleiten.

Methoden In 4 Datenbanken wurden Studien, Leitlinien, Standards und
Fachartikel mit einem Bezug zum Verantwortungs- und Tätigkeitsbereich
der Sonographer in den Ländern Australien, Großbritannien,
Japan, Kanada und den USA analysiert. Zur Herleitung von berufspolitischen
Zusammenhängen erfolgte ein Leitfaden-Interview mit einer Expertin.

Ergebnisse Anhand des Reviews wurde deutlich, dass die untersuchten
Länder unterschiedliche Schwerpunkte in den Ausbildungs- und
Tätigkeitsbereichen der Sonographer aufweisen. Die akademische
Ausrichtung des britischen Konzepts und die Berufsorganisationen führten
in Großbritannien zu einer starken Professionalisierung der Sonographer.
Australische Sonographer sehen im britischen Modell ein Vorbild und streben nach
einer ähnlichen beruflichen Autonomie. Alle betrachteten Modelle weisen
einen stark teamorientierten Ansatz sowie verschiedene
Berufszulassungsmodalitäten auf.

Schlussfolgerung Die Etablierung des Sonographers kann für eine
Verbesserung der Versorgung von Patient*innen in Deutschland sinnvoll
sein, unter der Prämisse, den Beruf auf hohen, akademischen Standards zu
gründen, Strukturen für eine interprofessionelle Zusammenarbeit
zu schaffen und die gesetzlichen Rahmenbedingungen festzulegen.
Themenreihe Praxishygiene – Teil 2
Authors: Handke Denis Maximilian
Published: February 2024

Erfahren Sie, wie Sie die zahlreichen gesetzlichen Vorgaben, Richtlinien und Empfehlungen in ein individuelles, an Ihrem Bedarf orientiertes Hygienemanagement umsetzen. Um dabei Maßnahmen festzulegen, müssen deren einzelnen Bausteine verstanden und gegebenenfalls der aktuellen Lage angepasst werden. Hier gilt es zum Beispiel auch, Nutzen und Risiken eingesetzter Mittel abzuwägen. Lesen Sie, mit welchen Verfahrensweisen Praxishygiene wirksam, praktikabel, akzeptabel und auch wirtschaftlich umgesetzt werden kann.
Vergleich hospitalisierter Patienten mit SARS-CoV-2-Infektion in zwei Phasen der Pandemie
Authors: Strehl Jan Eberhard , Ewig Santiago , Schaaf Bernhard
Published: February 2024

Ziel der Untersuchung Das Ziel dieser Untersuchung war ein Vergleich der hospitalisierten Patienten mit einer SARS-CoV-2-Infektion in den Zeiträumen 2020–2021 versus 2022 im Hinblick auf den Grund der Hospitalisation, der Schweregrade bei Aufnahme und im Verlauf und des klinischen Ausgangs.

Methoden Die Daten aller während dieser Zeit in einem großen Dortmunder Krankenhaus hospitalisierten Patienten mit SARS-CoV-2-Infektion wurden erfasst. Schweregrade bei Aufnahme sowie im Verlauf wurden verglichen bei Patienten, bei denen der Einweisungsgrund eine SARS-CoV-2-Infektion war.

Ergebnisse Im Zeitraum von 2020/2021 wurden n=1281 Patienten, in 2022 n=580 Patienten mit SARS-CoV-2-Infektion hospitalisiert, davon 90% bzw. 42% aufgrund der SARS-CoV-2-Infektion. Der Anteil der nosokomialen Übertragungen stieg von 5% auf 18%. Der Schweregrad der SARS-CoV-2-Erkrankung bei Aufnahme und im Verlauf war im ersten Zeitraum in allen Altersgruppen höher, ebenso wurden mehr Patienten auf der Intensivstation aufgenommen (25% versus 4%). Entsprechend bestand eine höhere Krankenhausletalität (17% versus 10%). Intubierte Patienten hatten in beiden Phasen eine gleich hohe Letalität (74% versus 80%).

Schlussfolgerungen Im ersten Zeitraum bestand ein deutlich höherer Schweregrad bei Aufnahme und im Verlauf. Wesentliche Treiber der Belastung der Gesundheitssysteme waren 2022 weniger der Schweregrad der SARS-CoV-2-Infektionen, sondern die Notwendigkeit der Isolation und nosokomiale Infektionen. Die Letalität bei intubierten Patienten war hoch.
miR-2467-3p/ABLIM1 Axis Mediates the Formation and Progression of Deep Vein Thrombosis by Regulating Inflammation and Oxidative Stress
Authors: Qiu Yu , Yang Meiying , Che Xinting , Yu Xinming , Zhi Kangkang
Published: February 2024

Deep vein thrombosis (DVT) is a common postoperative complication of orthopaedic surgery with a complex pathogenesis mechanism. The effect of the miR-2467-3p/acting-binding LIM protein 1 (ABLIM1) axis on thrombus formation and human vascular endothelial cells (HUVECs) progression was evaluated aiming to identify a novel potential biomarker of DVT. DVT rat models were established by inferior vena cava stenosis. The expression of the miR-2467-3p/ABLIM1 axis was analyzed by PCR. HUVECs were induced with oxidative low-density lipoprotein (ox-LDL). Cell growth and motility were assessed by cell counting kit 8 (CCK8) and Transwell assay. The inflammation and oxidative stress were estimated by proinflammatory cytokines and generation of MDA and reactive oxygen species (ROS). ABLIM1 was downregulated in DVT rats. Overexpressing ABLIM1 could suppress the formation of thrombosis and alleviate inflammation and oxidative stress. In HUVECs, ox-LDL induced significantly increased miR-2467-3p and decreased ABLIM1, and miR-2467-3p could negatively regulate ABLIM1. The knockdown of miR-2467-3p could alleviate the inhibited cell growth and motility by ox-LDL, and the inflammation and oxidative stress were also attenuated. While silencing could reverse the effect of miR-2467-3p on ox-LDL-induced HUVECs. The miR-2467-3p/ABLIM1 axis regulates the occurrence and development of DVT through modulating HUVECs inflammation and oxidative stress.
A Bridge Not Too Far: Toward Efficient Asset Management and Maintenance
Authors:   American Society of Civil Engineers, Larbi Jelian
Published: February 2024

It is crucial to assist stakeholders and state Department of Transportation (DOTs) in asset management and bridge maintenance to maximize use of this funding
A computational model of the human colon for use in medical robotics
Authors: Evans M. , Dogramadzi S.
Published: February 2024

This paper reports on the results of modeling the human colon and analyzes its effectiveness as a finite element analysis (FEA) tool for testing conventional and robotic colonoscope technologies. FEA has been used to model colon tissue before, but these analyses have been carried out on smaller tissue samples, such as to fit strain energy functions to mechanical testing data or to explore the inflation-extension response of a section of the colon. The full colon has not yet been modeled in this way, and this study aims to show the usefulness of such a tool for testing endoscopic devices for diagnostic and therapeutic purposes in the colon. Data from the literature and databases have been used to approximate the stress response of the tissues, and a critical analysis of the limitations of the approximations has been carried out. Characteristic colonoscope loops were created to analyze the mechanical response of the colon and provide comparable results to conventional colonoscopy. The results showed how stress would be propagated along the length of the colon and how neighboring structures can affect the stresses and strains experienced by the colon wall, demonstrating the need for and capabilities of a full FEA model of the colon to test endoscopic devices.
Biosignal-integrated robotic systems with emerging trends in visual interfaces: A systematic review
Authors: Lee Jaeho , Miri Sina , Bayro Allison , Kim Myunghee , Jeong Heejin , Yeo Woon-Hong
Published: February 2024

Human–machine interfaces (HMI) are currently a trendy and rapidly expanding area of research. Interestingly, the human user does not readily observe the interface between humans and machines. Instead, interactions between the machine and electrical signals from the user's body are obscured by complex control algorithms. The result is effectively a one-way street, wherein data is only transmitted from human to machine. Thus, a gap remains in the literature: how can information be effectively conveyed to the user to enable mutual understanding between humans and machines? Here, this paper reviews recent advancements in biosignal-integrated wearable robotics, with a particular emphasis on “visualization”—the presentation of relevant data, statistics, and visual feedback to the user. This review article covers various signals of interest, such as electroencephalograms and electromyograms, and explores novel sensor architectures and key materials. Recent developments in wearable robotics are examined from control and mechanical design perspectives. Additionally, we discuss current visualization methods and outline the field's future direction. While much of the HMI field focuses on biomedical and healthcare applications, such as rehabilitation of spinal cord injury and stroke patients, this paper also covers less common applications in manufacturing, defense, and other domains.
Enhancement of photon–magnon coupling strength by inverted split-ring resonator at GHz
Authors: Girich A. , Nedukh S. , Polevoy S. , Sova K. , Tarapov S. , Vakula A.
Published: February 2024

A series of inverse split-ring resonators (ISRR) loaded with an yttrium iron garnet (YIG) film were numerically and experimentally studied to provide strong photon–magnon coupling strength and cooperativity enhancement. An increase in the photon–magnon coupling strength and cooperativity has been achieved due to the simultaneous increase in the spatial overlapping between the ISRR microwave electromagnetic field magnetic component and the uniform magnon mode in the YIG, and the appearance of spatial areas with higher ISRR electromagnetic field magnetic component strength. Practically, this was reached for the ISRR by increasing the conducting gap length and changing the conducting gap shape by protrusions forming. Higher values of spin-number-normalized photon–magnon coupling strength gN and cooperativity C were reached in all cases for the ISRR with protrusion (compared with ISSR with identical conducting gap length but without protrusion). All resonators presented in this paper seem to be more prospective for the realization in quantum hybrid systems than conventional split-ring resonators and ISRR.
Study of the breathing mode development in Hall thrusters using hybrid simulations
Authors: Petronio Federico , Alvarez Laguna Alejandro , Bourdon Anne , Chabert Pascal
Published: February 2024

We use a 2.5D hybrid simulation to study the breathing mode (BM) dynamics in Hall thrusters (HTs). This involves a 1D Euler fluid simulation for neutral dynamics in the axial direction, coupled with a 2D axial–azimuthal Particle-in-Cell (PIC) simulation for charged species. The simulation also includes an out-of-plane virtual dimension for wall losses. This setup allows us to replicate the BM’s macroscopic features observed in experiments. A comprehensive analysis of plasma parameters in BM’s phases divides it into two growth and two decay sub-phases. Examining 1D axial profiles of electron temperature, gas and plasma densities, and particle creation rate shows that an increase in electron temperature alone cannot sustain ionization. Ionization seems to be influenced by the spatial correlation between electron and gas densities and the ionization rate coefficient. Investigating ion back-flow reveals its impact on modulating neutral flux entering the ionization region. The hybrid simulation’s outcomes let us assess the usual 0D predator–prey model’s validity and identify its limitations. The ionization and ion convection term approximations hold, but the gas convective term approximation does not. Introducing an alternative gas convective term approximation involving constant density ejection from the ionization region constructs an unstable BM model consistent with simulation results. In addition, this paper explores how varying the imposed voltage and mass flow rate impacts the BM. The BM frequency increases with imposed voltage, aligning with theoretical predictions. The mass flow rate variation has a limited effect on BM frequency, following the theoretical model’s trend.
Polyethylene glycol-stabilized cationic liposome encapsulating glucosamine sulfate: A promising nanoformulation for osteoarthritis therapy
Authors: Liu Xiaodong , Dai Hongbin , Wang Zhiqing , Huang Chunyan , Huang Kai
Published: February 2024

Osteoarthritis (OA) is a common orthopedic chronic disease, and the use of nanomaterials as carriers is an effective way to realize slow and controlled release therapy for OA drugs. In this study, we synthesized a polyethylene glycol-stabilized bilayer-decorated cationic liposome (CLis) as a drug delivery system for delivering glucosamine sulfate (GS) drug to achieve the treatment of OA in rats. The CLis encapsulated with GS drug (GS-CLis) was prepared by a reverse evaporation method, and its physical properties, encapsulation rate, and drug release performance were evaluated. The biological properties of GS-CLis were evaluated in vitro. The therapeutic effect of GS-CLis on osteoarthritis was evaluated in vivo, and the in vivo biosafety of the drug was assessed by hematology, blood biochemistry, and hematoxylin-eosin staining. GS-CLis had a particle size of (236.28 ± 4.76) nm, a potential of (27.35 ± 4.86) mv, and a spherical shape. The encapsulation rate was (96.18 ± 5.77)% and the drug-loading capacity was (9.61 ± 0.28)%, which provided a good slow drug release. GS-CLis has low cytotoxicity, low hemolysis rate, and good biocompatibility. GS-CLis can more effectively alleviate joint surface damage and inhibit the expression of inflammatory factors, and has no significant effect on the body weight of rats, with good biological safety. In this study, we successfully synthesized novel GS-CLis for the treatment of OA, which improved the retention time and therapeutic effect of GS in OA and provided a research basis for its development as an OA nanoformulation.
Polynomial chaos expansion for sensitivity analysis of two types of transmission line models
Authors: Chen Weiwei , Qi Ziyang , Ji Yuhang , Yan Liping , Zhao Xiang
Published: February 2024

This paper presents two sensitivity analyses, one of which is for the time-domain transmission line (TL) model using the latest weight-based algorithm that is a combination of the coherence-optimal sampling (COS) and the l1-minimum problem (l1-M) and the other is for the high-frequency field line coupling model based on the algorithm that combines the Latin hypercube sampling (LHS) with the l1-M for the first time, where the COS and the LHS are employed to draw samples and the polynomial chaos expansion (PCE) coefficients are obtained by solving the l1-M. Both algorithms are within the PCE framework. The results show that for the time-domain TL model, the capacitance has the greatest impact on the voltage response, followed by the resistance. The height and the radius have the least impact, while there is little difference between them. For the high-frequency field line coupling model, the azimuth angle has the greatest impact on the current in the TL, followed by the elevation angle. The terminal load, the conductivity, the field amplitude, the relative permittivity, and the TL radius have the least effect, and there is little difference among them. Additionally, both algorithms only require no more than 0.60% of the total Monte Carlo (MC) computation time when yielding solutions with almost identical accuracy. Compared to performing a sensitivity analysis using the MC method, the use of two algorithms significantly improves efficiency.
Parallel pumping of magnons in inhomogeneous spin textures probed through NV spin relaxometry
Authors: Trimble J. , Gould B. , Heremans F. J. , Zhang S. S.-L. , Awschalom D. D. , Berezovsky J.
Published: February 2024

We combine micromagnetic simulations and nitrogen-vacancy (NV) defect center spin relaxometry measurements to study magnon modes in inhomogeneous spin textures. A thin, micrometer-scale ferromagnetic disk is magnetized in a vortex state in which the magnetization curls around a central core. Micromagnetic simulations show that at zero applied field, the magnetization dynamics of the disk consist of a low frequency gyrotropic mode and higher frequency azimuthal magnon modes, all far detuned from the NV spin transition frequencies. An in-plane static magnetic field breaks the azimuthal symmetry of the vortex state, resulting in the magnon modes transforming in frequency and spatial profile as the field increases. Experimentally, we probe the dynamics of vortex magnetization as a function of applied in-plane static field and ac driving frequency by optically monitoring a nearby NV defect center spin. At certain values of the applied magnetic field, we observe enhanced spin relaxation when driving at twice the frequency of the NV ground state spin transition in optically detected magnetic resonance measurements. We attribute this effect to parallel pumping of a magnon mode in the disk producing magnons at half the excitation frequency. Micromagnetic simulations support this finding, showing spatial and spectral overlap of a confined magnon mode and an NV spin transition, with sufficient interaction strength to explain the observed signal.
Some statistical properties of aeolian saltation
Authors: Wang Zhen-Ting
Published: February 2024

Aeolian sediment transport is a process that commonly occurs on celestial bodies with atmospheric layers and solid surfaces. At present, it is very difficult to predict the instantaneous mass flux accurately. For the purpose of statistical prediction, the near-surface saltating grain count and the wind velocity above the saltation layer are synchronously measured in two dune fields. The duration and intensity of the saltation event obey exponential distribution, whereas sand transportation via saltation events with a smaller probability for a longer duration is significant. It is found for the first time that the Hilbert marginal energy spectrum of mass flux density follows the “−1” power law in a wide frequency range. In addition, the timescales of the energy-containing mass flux density mode and the strong wind–sand interaction of fluctuations are determined.
Optimization of the double-slot blown airfoil with jet at the leading and trailing edges of the flap
Authors: Xiang Songlin , Wen Qing , Wei Meng , Jia Zhongren
Published: February 2024

An active lift augmentation technique combining trailing edge blowing and blown flap is explored in this study. A double-slot blown flap airfoil is designed based on NACA23015. By optimizing the configuration parameters via the neural network surrogate model and particle swarm optimization algorithm, the lift coefficient at the 8° angle of attack reaches ∼5.14, which is approximately a 24% increasement relative to the baseline single-slot blown flap airfoil. In the configuration optimization, a longer flap facilitates lower pressure on the upper airfoil surface. Additionally, the aerodynamic flap effect caused by the double-slot jet flow intensifies the lift peaks and the pressure decreases over the airfoil. Ultimately, redistributing the jet momentum to the two slots achieves a highly efficient blown flap airfoil design.
Multiscale Flow for robust and optimal cosmological analysis
Authors: Dai Biwei , Seljak Uroš
Published: February 2024

We propose Multiscale Flow, a generative Normalizing Flow that creates samples and models the field-level likelihood of two-dimensional cosmological data such as weak lensing. Multiscale Flow uses hierarchical decomposition of cosmological fields via a wavelet basis and then models different wavelet components separately as Normalizing Flows. The log-likelihood of the original cosmological field can be recovered by summing over the log-likelihood of each wavelet term. This decomposition allows us to separate the information from different scales and identify distribution shifts in the data such as unknown scale-dependent systematics. The resulting likelihood analysis can not only identify these types of systematics, but can also be made optimal, in the sense that the Multiscale Flow can learn the full likelihood at the field without any dimensionality reduction. We apply Multiscale Flow to weak lensing mock datasets for cosmological inference and show that it significantly outperforms traditional summary statistics such as power spectrum and peak counts, as well as machine learning–based summary statistics such as scattering transform and convolutional neural networks. We further show that Multiscale Flow is able to identify distribution shifts not in the training data such as baryonic effects. Finally, we demonstrate that Multiscale Flow can be used to generate realistic samples of weak lensing data.
The early macrophage response to pathogens requires dynamic regulation of the nuclear paraspeckle
Authors: Azam Sikandar , Armijo Kaitlyn S. , Weindel Chi G. , Chapman Morgan J. , Devigne Alice , Nakagawa Shinichi , Hirose Tetsuro , Carpenter Susan , Watson Robert O. , Patrick Kristin L.
Published: February 2024

To ensure a robust immune response to pathogens without risking immunopathology, the kinetics and amplitude of inflammatory gene expression in macrophages need to be exquisitely well controlled. There is a growing appreciation for stress-responsive membraneless organelles (MLOs) regulating various steps of eukaryotic gene expression in response to extrinsic cues. Here, we implicate the nuclear paraspeckle, a highly ordered biomolecular condensate that nucleates on the
Neat1
lncRNA, in tuning innate immune gene expression in murine macrophages. In response to a variety of innate agonists, macrophage paraspeckles rapidly aggregate (0.5 h poststimulation) and disaggregate (2 h poststimulation). Paraspeckle maintenance and aggregation require active transcription and MAPK signaling, whereas paraspeckle disaggregation requires degradation of
Neat1
via the nuclear RNA exosome. In response to lipopolysaccharide treatment,
Neat1
KO macrophages fail to properly express a large cohort of proinflammatory cytokines, chemokines, and antimicrobial mediators. Consequently,
Neat1
KO macrophages cannot control replication of
Salmonella enterica
serovar Typhimurium or vesicular stomatitis virus. These findings highlight a prominent role for MLOs in orchestrating the macrophage response to pathogens and support a model whereby dynamic assembly and disassembly of paraspeckles reorganizes the nuclear landscape to enable inflammatory gene expression following innate stimuli.
Lutetium texaphyrin: A photocatalyst that triggers pyroptosis via biomolecular photoredox catalysis
Authors: Xu Yunjie , Chau Calvin V. , Lee Jieun , Sedgwick Adam C. , Yu Le , Li Mingle , Peng Xiaojun , Kim Jong Seung , Sessler Jonathan L.
Published: February 2024

Photon-controlled pyroptosis activation (PhotoPyro) is a promising technique for cancer immunotherapy due to its noninvasive nature, precise control, and ease of operation. Here, we report that biomolecular photoredox catalysis in cells might be an important mechanism underlying PhotoPyro. Our findings reveal that the photocatalyst lutetium texaphyrin (
MLu
) facilitates rapid and direct photoredox oxidation of nicotinamide adenine dinucleotide, nicotinamide adenine dinucleotide phosphate, and various amino acids, thereby triggering pyroptosis through the caspase 3/GSDME pathway. This mechanism is distinct from the well-established role of
MLu
as a photodynamic therapy sensitizer in cells. Two analogs of
MLu
, bearing different coordinated central metal cations, were also explored as controls. The first control, gadolinium texaphyrin (
MGd
), is a weak photocatalyst but generates reactive oxygen species (ROS) efficiently. The second control, manganese texaphyrin (
MMn
), is ineffective as both a photocatalyst and a ROS generator. Neither
MGd
nor
MMn
was found to trigger pyroptosis under the conditions where
MLu
was active. Even in the presence of a ROS scavenger, treating MDA-MB-231 cells with
MLu
at concentrations as low as 50 nM still allows for pyroptosis photo-activation. The present findings highlight how biomolecular photoredox catalysis could contribute to pyroptosis activation by mechanisms largely independent of ROS.
The role of situation in individual style
Authors: Gracheva Marianna
Published: February 2024

The study adopts a cross-register approach to style, examining style with relation to the situation of use. While
register tends to be avoided by style research as a confounding variable, this investigation of the styles of four American
presidents in memoirs, official letters, and public addresses illustrates that adding a register dimension leads to a more
accurate, nuanced analysis. The study identifies linguistic features associated with register vs. style variation in the corpus
and analyzes intraspeaker differences across registers with regard to the following functional categories: information density,
oral style, situation-dependent discourse, and narration vs. immediacy. The results indicate that even authors with a well-defined
individual style consistently adjust their language to the demands of the situation, with the most noticeable differences lying
between strictly regimented literate registers and the more oral, less conventionalized ones.
Polyp segmentation with interference filtering and dynamic uncertainty mining
Authors: Zhang Yunhua , Yang Gang , Gong Congjin , Zhang Jianhao , Wang Shuo , Wang Yutao
Published: February 2024

Objective. Accurate polyp segmentation from colo-noscopy images plays a crucial role in the early diagnosis and treatment of colorectal cancer. However, existing polyp segmentation methods are inevitably affected by various image noises, such as reflections, motion blur, and feces, which significantly affect the performance and generalization of the model. In addition, coupled with ambiguous boundaries between polyps and surrounding tissue, i.e. small inter-class differences, accurate polyp segmentation remains a challenging problem. Approach. To address these issues, we propose a novel two-stage polyp segmentation method that leverages a preprocessing sub-network (Pre-Net) and a dynamic uncertainty mining network (DUMNet) to improve the accuracy of polyp segmentation. Pre-Net identifies and filters out interference regions before feeding the colonoscopy images to the polyp segmentation network DUMNet. Considering the confusing polyp boundaries, DUMNet employs the uncertainty mining module (UMM) to dynamically focus on foreground, background, and uncertain regions based on different pixel confidences. UMM helps to mine and enhance more detailed context, leading to coarse-to-fine polyp segmentation and precise localization of polyp regions. Main results. We conduct experiments on five popular polyp segmentation benchmarks: ETIS, CVC-ClinicDB, CVC-ColonDB, EndoScene, and Kvasir. Our method achieves state-of-the-art performance. Furthermore, the proposed Pre-Net has strong portability and can improve the accuracy of existing polyp segmentation models. Significance. The proposed method improves polyp segmentation performance by eliminating interference and mining uncertain regions. This aids doctors in making precise and reduces the risk of colorectal cancer. Our code will be released at https://github.com/zyh5119232/DUMNet.