bluuebunny/crossref_metadata_2025 huggingface dataset:
Uremia as an immunosuppressive factor in a patient with acquired immunodeficiency syndrome: A case report and review
Authors:   Hospital das Clinicas da Faculdade de Medicina da Universidade de Sao Paulo, Brazil., Ferreira Mauricio Domingues
Published: October 2023

We report a case of a patient with AIDS and non-dialytic renal failure who presented a spontaneous abscess in the thigh and progressed with sepsis. Non-typical infectious disease of a cellular immunodeficiency characteristic of AIDS, but rather from a phagocytic disorder and very probably caused by uremia
A family educational therapy for a 15 months-old child with polydipsia
Authors:   Paediatric Department, Sandro Pertini Hospital, Rome, Italy., Paola Cipriano
Published: October 2023

Polydipsia is a condition characterized by excessive water intake and can be caused by several conditions. We present a case report of a child who was admitted in our department for persistent fever, but during the recovery a primary polydipsia was accidentally found through laboratory exams.
Lingual abscess, an uncommon cause of tongue oedema: Case series
Authors:   Otorhinolaryngology Department, General Hospital of Volos, Greece., Georgia Tsiouma
Published: October 2023

Lingual abscess is a rare but potentially life-threatening medical entity. Consequently, it requires high medical suspicion in order to prevent misdiagnosis. Unilateral tongue oedema constitutes the characteristic clinical feature.
Multitarget-Multisensor Information-driven Planning via Finite Set Statistics (FISST)
Authors: Ferrari Silvia
Published: October 2023

Recent work on information-driven sensor path planning has shown that the performance of mobile and remote sensors can be significantly improved by planning their motions based on probabilistic sensor models and the geometric characteristics of the sensor field-of-view (FOV). This talk discusses a general framework by which the expected information gain of future sensor measurements, positions, and orientations can be described by information theoretic functions in closed form, and, then, used to derive motion planning and control laws for active sensing and information gathering. Recent applications, such as underwater target detection and classification by active sonar and active scene perception by mobile cameras, have shown that the approach can greatly improve upon the quality of the sensor data, while decreasing the resources required, including time, computation, and energy consumption. This talk will present information-driven planning for space situational awareness (SSA), whereby information-driven sensor planning strategies are derived using finite set statistics (FISST). In this case, information-driven sensor planning seeks to optimize the information gain associated with tracking many moving targets by means of many space-based sensors. In addition to developing new FISST information gain functions, this talk will show how distributed optimal control (DOC) can be used to control large numbers of collaborative agents by providing solutions that scale up to hundreds of satellite-based sensors.
Importance of Linking Inertia and Frequency Response Procurement: The Great Britain Case
Authors: MB Aimon
Published: October 2023

In order to decarbonise the electricity sector, the future Great Britain (GB) power system will be largely dominated by non-synchronous renewables. This will cause low levels of inertia, a key parameter that could lead to frequency deterioration. Therefore, the requirement for ancillary services that contain frequency deviations will increase significantly, particularly given the increase in size of the largest possible loss with the commissioning of large nuclear plants in the near future. In this paper, an inertia-dependent Stochastic Unit Commitment (SUC) model is used to illustrate the benefits of linking inertia and frequency response provision in low-inertia systems. We demonstrate that the cost of procuring ancillary services in GB could increase by 165% if the level of inertia is not explicitly considered when procuring frequency response. These results highlight the need to re-think the structure of ancillary-services markets, which in GB are nowadays held one month ahead of delivery.
Mars Entry, Descent, and Landing guidance under dynamic uncertainty
Authors: Amato Davide
Published: October 2023

Future Mars exploration missions require improvements of one order of magnitude in landed mass and of two orders of magnitude in landing accuracy with respect to current (Mars 2020) capabilities. These stringent requirements pose significant challenges to current Entry, Descent, and Landing (EDL) guidance algorithms. In addition, the behaviour of the dynamical system is highly uncertain due to the partial knowledge of the Martian atmosphere and of its interaction with the entry vehicle. In this talk, I will give an overview of some recent advances in EDL guidance under dynamic uncertainty.

First, I will present a novel approach to reconstruct and predict Martian atmospheric density and wind using a Long Short-Term Memory Network (LSTM), a particular class of recurrent neural networks. The LSTM is trained on simulated inertial measurements from a large number of entry trajectories, in which the controls are computed by the Fully Numerical Predictor-corrector Guidance (FNPEG) algorithm. I show that the network is able to reconstruct atmospheric quantities with very high accuracy, and I am currently working on a generalization of the method to improve the accuracy of the controls obtained through the FNPEG algorithm.

I also expound on a stochastic guidance method applying corrections to the controls computed during powered descent to minimize the expected value of the error at landing. The method is based on the observation that, in nonlinear systems, the mean of the propagated pdf does not coincide with the propagated mean. Thus, we feed to the baseline guidance algorithm a corrected target designed to minimize the expected value of the navigation pdf at the surface; with the latter propagated through an Unscented Transform. Both approaches are of significant import for improving the accuracy and robustness of state-of-the-art EDL algorithms.
Emission Spectroscopy Measurements in High Enthalpy Flows
Authors: Hermann Tobias
Published: October 2023

During spacecraft entry into planetary atmospheres, the gas around the space capsule is strongly compressed as the large kinetic energy of the hypervelocity flow is transferred into internal energy. This leads to very high surface heat transfer to the vehicle which is compensated by a heat shield.

To date, these thermal protection systems are oversized due to the uncertainty we encounter in predicting the flowfield.

One way to improve our understanding is to conduct ground-based experiments in wind tunnels which simulate the real high enthalpy flow of a flight case. A major challenge in using these experiments to improve our understanding are the complex measurement techniques and the interpretation of the data gathered through them.

Many traditional aerodynamic measurement techniques are difficult to employ due to the extreme high temperature and high pressure environment.

Emission spectroscopy uses the natural radiation from these flows to investigate the thermodynamic flow state. The technique separates the light emitted from the flow into its spectral components. The resulting spectra are collected and used to infer thermodynamic parameters without the need for intrusive measurement devices.

Through the use of statistical thermodynamic theory, temperatures and particle densities can be inferred from an in-depth analysis of these spectra by assessing the population density of exited quantum states of atoms and molecules.
Thank You for the Music – 53 Years!
Authors: Stearns Ann
Published: October 2023

There were ashtrays on desks in the classrooms. I taught with chalk in one hand and a cigarette in the other. Students lined up under trees, waiting to register for classes in a trailer house on wheels. In September 1970, there were just 2 permanent buildings on the Essex campus. Some of my courses were in the newly built library or administration building. Most were in prefab rectangular classrooms sitting atop concrete blocks: It was like teaching in an oversized shoebox with a door and windows. Except it was fun. I fell in love with teaching right away.
The Role and Impact of Employee Resource Groups in Higher Education
Authors: Crefton Christine , Miller Paul
Published: October 2023

Montgomery College (MC) is an educational institution known for its diverse student body and broad range of programs. Established in 1946 in Montgomery County, Maryland, MC is home to over 50,000 credit and noncredit students from more than 155 countries. Alongside its student body, MC prides itself on its highly dedicated faculty and staff, over 3,500 in total, who are instrumental in driving the college’s commitment to academic excellence and inclusivity.

Workplace belonging is a cornerstone for a productive, positive, and cohesive work environment. Studies have shown that feelings of belonging can directly contribute to increased job satisfaction, happiness at work, and reduced chances of burnout (Black et al., 2019). These feelings also foster institutional commitment and stability and spur creativity and innovation, elements crucial for the continued success of an educational institution (Zambrana, 2018). MC is no different and has emphasized fostering a strong sense of community within its ranks.

One of the ways MC achieves this is through the Montgomery College Rising Professionals Association (MCRPA). Established in 2011, MCRPA is an employee resource group (ERG) developed for employees by employees, and it seeks to empower its members and support them in their professional journey. The association nurtures a sense of belonging for employees and promotes collegiality, community engagement, and collaboration and, through these efforts, promotes and contributes to student success and productivity.
ChatGPT in the English Classroom
Authors: Murray Nancy
Published: October 2023

18 students engaged in learning about artificial intelligence, specifically ChatGPT 3 (CHAT), to respond to the question of whether it is ethical or practical for students to use CHAT in college-level classrooms to complete assignments. A thematic unit was created and taught in 2 face-to-face English 101 classes to explore the topic of CHAT. The unit was created with and designed to be completed by CHAT. After reflecting on 3 readings, 2 videos, and completing various related assignments, students were expected to write a 5-page essay about CHAT using CHAT in whatever way they wanted to complete the work while still maintaining the specific requirements of the English 101 objectives. The essays were examined by the students using the same peer review process that we used for 2 essays written without using CHAT before the thematic unit, with the addition of 2 instructions: to check the veracity of the sources, and to evaluate the essays for consistency of tone, accuracy of information, and originality. Data collection for this qualitative study was based on hand-written reflections by 18 of the students in the classroom, quick polls at the end of each lesson, and semi-structured, recorded interviews with 9 of the participating students who volunteered to be recorded. The students were charged with the dual roles of tester and consultant, and it gave them the opportunity to understand and test CHAT in a classroom and to share their insights with faculty. Reflections and interviews were transcribed, coded, analyzed, and categorized into the 3 strongest recommendations for faculty considering using CHAT in their curriculum: (1) faculty should be open-minded and well trained in what CHAT is and how to use it safely before attempting to allow their students to use it in class; (2) students should be given specific instructions for how to use CHAT for specific tasks that will help them reach their potential and then allowed to decide for themselves how to proceed; (3) students should be tested to demonstrate comprehension of the material and classroom objectives both before and after the use of CHAT.
Build Hospital Management System using PHP framework
Authors: Fayaq Mahabat
Published: October 2023

Service institutions are considered one of the most important institutions in our time, and they have become a great place in our lives The health institutions are considered the most important, because they provide many types of necessary health services And related to the safety of the health of individuals, and through cooperation between the academic study and the health sector, which was represented by Khanaqeen General Hospital, where this research paper presented a proposal hospital management system project is primarily focused on managing medical-related records within a hospital. More precisely, this system helps track medical reports. The system also displays all available employees and patients. In additionally, the system can aggregate inventory and pharmacy records, this system consists of two major sections: database structure, and GUI (Graphical User Interface) frames (created in environments utilizing PHP, HTML, and CSS). The database constructed with MYSQL and the GUI frame make it easier for novice users to utilize the suggested system. at the latest this paper describes a hospital management system that can be used to manage and analyze hospital information related to patients, treatments, and sales. The practical implications of this system are:
It can help hospitals to manage their operations more efficiently by providing a centralized system for managing patient information, treatment records, The system can be of assistance hospital administrators to make data-driven decisions by providing them with real-time information about hospital operations, and improve patient care by providing doctors and nurses with easy access to patient information and treatment records, The system can be beneficial to reduce errors and improve accuracy by automating many of the manual processes involved in managing hospital information.
Overall, the HMS described in this paper has the ability to increase efficiency, accuracy, and quality of hospital operations, which can ultimately lead to better patient outcomes.
Nachhaltigkeit als transformatorischer Bildungsprozess
Authors: Loparics James Ian Simon
Published: October 2023

Der Beitrag diskutiert entlang der Theorie transformatorischer Bildung, wie die Frage der Bildung für nachhaltige Entwicklung (BNE) bildungstheoretisch integriert werden könnte. Während einerseits Programme und Interventionen der BNE Kompetenzsteigerungen bewirken, muss gleichzeitigt festgestellt werden, dass es zu wenig gesellschaftlicher Transformation kam. Daher wird für einen bildungstheoretischen Diskurs plädiert, der sich diesem Thema abseits von d Kompetenzaneignung annimmt. Dafür werden analog zu Koller die Theorien von Bourdieu, Ricoeur, Lacan und Butler befragt. Als Ergebnis kann festgehalten werden, dass sich der Anlass der Transformation als ausreichend widersprüchlich zum aktuellen (konsumorientierten) Habitus erweisen muss – unter anderem, indem damit einhergehende Ängste nicht abgewehrt werden. Eine solche Abwehr kann sich durch selbstgesteuerte soziale Prozesse wie durch die selbstbestimmte und stetige Veränderung performativer Sprechakte vermindert werden. Eine solche Perspektive auf die Bildungsprozesse ermöglicht eine erziehungswissenschaftliche Beschreibung von nachhaltiger Transformation der Selbst- und Weltverhältnisse, welche nicht selbst Subjektivation oder Indoktrinierung ist.
Curriculumsbasiertes Historisches Lernen in der Primarstufe
Authors: Bilewicz Wolfgang , Bernauer Egbert
Published: October 2023

Im vorliegenden Beitrag wird der Frage nachgegangen, welchen Stellenwert das historische Lernen und die Ausprägung eines reflektierten Geschichtsbewusstseins in der curricularen Entwicklung des Unterrichtsgegenstandes Sachunterricht in den Jahren 1945 bis 2023 einnehmen. In diesem Kontext werden die seit 1945 veröffentlichten Lehrpläne einer deskriptiven Betrachtung unterzogen. Im Fokus steht dabei die Entwicklung des traditionellen Heimatkundeunterrichts hin zu einem modernen, Schüler*innenzentrierten Sachunterricht, der das historische Lernen kompetenzorientiert zu vermitteln versucht. Was die analytische Betrachtung der curricularen Entwicklung anbelangt, wird angesichts der Tatsache, dass es sich hierbei um einen theoretischen Beitrag handelt, ein Literaturvergleich vollzogen, in dem die seit 1945 publizierten Lehrpläne für den Unterrichtsgegenstand Sachunterricht in Bezug auf den Bereich des historischen Lernens untersucht werden. Im Kontext eines verstärkten Kompetenzerwerbs werden die bisher im Sachunterricht geltenden Erfahrungsbereiche ab 2023 durch Kompetenzbereiche ersetzt. So fördert der ab dem Schuljahr 2023/24 geltende Lehrplan die historische Frage-, Methoden- und Orientierungskompetenz, in dem anhand von ausgewählten Quellen vergangene Ereignisse als Geschichte kritisch rekonstruiert beziehungsweise dekonstruiert werden. Möglichkeiten zur historischen Orientierung sollen ebenfalls durch eine eingehende Befassung mit Quellen und Darstellungen generiert werden.
Globalisierungsnarrative aus der Perspektive transformativer historisch-politischer Bildung
Authors: Filko Christian
Published: October 2023

Der Beitrag erörtert ausgehend von der Notwendigkeit einer transformativen Bildung die Potentiale und Perspektiven globalgeschichtlicher Ansätze und der Global Citizenship Education für eine (Weiter-) Entwicklung der historisch-politischen Bildung in Richtung einer zukunftsfähigen und global orientierten Bildung. Am Beispiel des Konzepts der globalgeschichtlichen Perspektivierung nach Susanne Popp sowie der Global Citizenship Education nach Wintersteiner und Kolleginnen folgt eine geschichts- und politikdidaktische Auseinandersetzung mit dem Themenbereich Globalisierung. Anschließend werden die Ergebnisse einer Analyse des Lehrplans der Sekundarstufe I für das Unterrichtsfach Geschichte und Sozialkunde/Politische Bildung hinsichtlich der Repräsentation globaler Räume präsentiert und darauf aufbauend die zentralen Erkenntnisse einer Schulbuchanalyse des entsprechenden Schulbuchkapitels zur Globalisierung im Kontext der beiden vorgestellten didaktischen Ansätze diskutiert. Die Studienergebnisse zeigen auf, dass der Themenbereich Globalisierung in den untersuchten Lehrwerken der Sekundarstufe I zwar durchaus umfangreich in den Schulbüchern verankert ist, die Auseinandersetzung jedoch stark eurozentristisch erfolgt und zahlreiche aus geschichts- und politikdidaktischer Perspektive zu problematisierende Aspekte, wie beispielsweise die die unzureichende Behandlung von globalisierungskritischen Positionen sowie die Reproduktion kolonialer Denkmuster und Weltordnungskonzepte, beinhaltet.
Rezension von: Quarthal, Franz; Faix, Gerhard (Hrsg.), Adel am oberen Neckar
Authors: Setzler Wilfried , Quarthal Franz , Faix Gerhard
Published: October 2023

Franz Quarthal und Gerhard Faix (Hrsg.): Adel am oberen Neckar. Beiträge zum 900jährigen Jubiläum der Familie von Ow. Bibliotheca academica Verlag Tübingen 1995. 600 Seiten mit über 100 Abbildungen, Stammtafeln und Diagrammen. Leinen DM 89,- ISBN 3-928471-12-0
Rezension von: Keyler, Hanna, Eine Schwäbin in Hohenlohe
Authors: Mattern Hans , Keyler Hanna
Published: October 2023

Hanna Keyler: Eine Schwäbin in Hohenlohe. Verlag Robert Baier Crailsheim 1998. 91 Seiten mit 44 Abbildungen. Kartoniert DM 34,- ISBN 3-929233-10-X
Estudio comparativo de los años de escolaridad en Nicaragua, 2009 y 2014
Authors: López García Henry Luis
Published: October 2023

Este estudio tiene como objetivo central estimar los años de escolaridad en la población nicaragüense entre el periodo 2009 y 2014, bajo un enfoque comparado. El alcance de la investigación es asociativo, donde se han utilizado datos abiertos provenientes de dos Encuestas de Medición de Nivel de Vida (EMNV) 2009 y 2014. El muestreo se realizó en dos etapas, en el caso de ambas encuestas, las inferencias se realizaron utilizando una muestra de 7,520 viviendas, aplicando dos formularios, el de precio y el de hogares. Las variables sobre las que se construyó el indicador fueron: nivel de estudio (S4P12A) y grado o año aprobado (S4P12B). Los resultados demostraron que la población nicaragüense, en su mayoría, es joven y se concentra en la macro región de Managua, con un alto porcentaje de mujeres. De la misma forma, se comprobó una mayor concentración de personas entre los 6, 11 y 16 años de escolaridad (primaria, secundaria y universidad, respectivamente). Para el año 2014, en comparación con la EMNV-2009, se observó un mayor promedio en los años de escolaridad en la macro región de Managua. Se determinó que existe una dependencia de los años de escolaridad y la incidencia de la pobreza, lo que evidencia que la pobreza se reduce cuando una persona termina la educación secundaria.
Apuntes para la sistematización del quehacer educativo con enfoque por competencia en la Carrera de Historia
Authors: Ramos Escobar Urías Wilfredo
Published: October 2023

En el presente trabajo se realiza una sistematización del quehacer educativo que emplea el nuevo enfoque por competencias. Se ha tomado como referencia la Carrera de Historia de la Facultad de Humanidades y Ciencias Jurídicas de la UNAN-Managua, con el objetivo de poder organizar y describir el trabajo educacional en el contexto de las aulas de clase. De la misma forma, se busca visibilizar los resultados obtenidos desde los aprendizajes adquiridos por lo estudiantes dentro de este nuevo modelo establecido a partir del año 2021. Partiendo de las premisas anteriores, el estudio sistematiza los resultados obtenidos en el Integrador I e Integrador III, que corresponden al primero y segundo año de la carrera de Historia, respectivamente. En cuanto a los resultados obtenidos, se pudo notar que con respecto a la retención estudiantil en ambos casos fue muy satisfactoria, según consta en los registros y seguimientos que se pudieron obtener por medio de las actas de califi cación, actas de reuniones evaluativas y seguimiento grupal e individual. De la misma forma, el rendimiento académico se mantuvo en un rango razonable. El seguimiento y acompañamiento permitió que los estudiantes obtuvieran resultados cuantitativos y cualitativos, logrando desarrollar una formación integral.
Diseño didáctico b-learning como forma de aprendizaje de la asignatura Automatización de Unidades de la Información II
Authors: López Tórrez Ángela
Published: October 2023

Esta investigación se desarrolló tomando como escenario el entorno donde se imparte la asignatura Automatización de Unidades de la Información II, en la carrera de Gestión de la Información adscrita a la Facultad de Humanidades y Ciencias Jurídicas de la UNAN Managua. Se enfoca en la creación de un diseño didáctico b-learning para la asignatura, cuyo fin es facilitar el aprendizaje de los estudiantes de dicha carrera. Surge como una propuesta de solución para solventar las dificultades de aprendizaje que presentaron los estudiantes durante el II semestre de 2021, debido a la falta de laboratorios de informática. El enfoque es cualitativo porque fue necesario analizar la opinión de los informantes clave. Se aplicaron instrumentos como la entrevista, grupo focal y observación. La investigación es de tipo no experimental y descriptiva porque busca especificar las características y perfiles de las personas que se someten al análisis. En el análisis de resultados se encontró que la implementación del diseño didáctico b-learning para la asignatura es viable, puesto que la Facultad cuenta con las condiciones en infraestructura tecnológica para llevar a cabo esta propuesta. Además, los estudiantes no han logrado apropiarse del uso y manejo de los sistemas de bases de datos, porque en los encuentros sabatinos el tiempo de uso de laboratorios es limitado. De igual manera, los servidores de prácticas están configurados localmente y solo se accede a estos por medio de la red en UNAN-Managua. Así mismo, en la Facultad existe una plataforma Moodle de grado; sin embargo, los docentes de la asignatura en estudio no hacen uso de esta.
Regulación jurídica del teletrabajo en Nicaragua, Costa Rica y Panamá (Análisis comparativo)
Authors: Gaitán Baltodano Mabel Catalina , Acevedo Cerda Yaoska María
Published: October 2023

El acceso a las nuevas tecnologías, los cambios en el sistema de mercado y, desde el 2020, la crisis sanitaria del COVID-19, han hecho que el teletrabajo sea una modalidad laboral adoptada por empresarios en muchas partes del mundo. Esta nueva modalidad de trabajo y otras transformaciones sociales que la globalización ha venido imponiendo, exige contar con una regulación jurídica de esta y otras formas de trabajo, llamadas también como “trabajo en casa”. Este ensayo hace un análisis argumental de las garantías laborales contempladas en la legislación nicaragüense a partir del derecho comparado. Esta perspectiva, permite cotejar de manera análoga las normas laborales, desde el análisis e interpretación hermenéuticojurídica, a fi n de problematizar acerca de la necesidad de reglamentar la modalidad de teletrabajo, acorde con los avances socio-jurídicos internacionales en materia laboral. En este sentido, en el trabajo se hace una relación comparativa con experiencias legislativas en Costa Rica y Panamá. De igual manera, este trabajo se inscribe dentro de las líneas de investigación de la UNAN Managua relacionadas con el quehacer del Estado y la sociedad, al mismo tiempo hace un aporte, a partir del Plan Nacional de Lucha Contra la Pobreza y el Desarrollo Humano (PNLCP-DH 2022-2026), con el propósito de incentivar la creación de una propuesta o iniciativa de ley que regule el teletrabajo en el país.
The Principle of Human Electric Shock and Several Main Types of Electric Shock
Authors: Lin Shixin
Published: October 2023

In the modern production process and daily life, people use a lot of various types of electrical equipment. However, in the process of use due to the illegal operation of the operator, it will inevitably cause electric shock accidents. Study the principle of electric shock type and preventive measures are important. Through the in-depth study of electric shock, this paper analyzes the principle and different types of electric shock, and the harm of electric shock to human body. In the research, Multisim software is used to simulate the human body being electrocuted by lightning, and the specific value of the external resistance required to ensure the safety current of the human body is obtained through the experiment. The significance of this study is to increase the public's awareness and understanding of the problem of electric shock, and to provide the public with important information about the hazards of electric shock and preventive measures. At the same time, to improve the accuracy of the study and for the consideration of human safety, simulation software is chosen to study the experiment, which provides methods and ideas for further research on electric shock.
Prediction of China Stock returns under the COVID-19 Pandemic based on the LSTM Model
Authors: Guo Sijie
Published: October 2023

The Coronavirus disease 2019, which is also known as the COVID-19, was first initiated in Wuhan, China, and then spread throughout the world, leading to an enormous quantity of reported cases and deaths. Accompanying the spread of the disease was the shrink in the economic markets. As one of the most important financial markets, the stock market was negatively impacted by the COVID-19, where many stock prices sharply decreased, and the performance of the stocks tended to be more unpredictable, compared to the performance of the stock market before the COVID-19 pandemic. China, as one of the most important economic entities, is also facing a decline in the stock returns in its stock market. This paper utilized the LSTM model to predict the China stock returns under the Coronavirus disease pandemic since 2019. The model is fitted by training on 12621 sequences, which were obtained during the Covid-19, and is tested with another 1260 sequences. The accuracy of the prediction in this paper is measured by MSE. The mean MSE after running the model fifty times is 0.0043.
Visual Design of User Emotion for Online Chat Based on Pattern Recognition
Authors: Shi Yichen
Published: October 2023

This paper analyzes the emotions that often appear in daily chats, in order to facilitate people to quickly identify each other's emotions in daily chats, a comprehensive user research is done, and the corresponding emotion recognition presentation methods are designed.
Research and Optimization Design of Thermal Management for LED
Authors: Jiang Bowen
Published: October 2023

LED, a lighting source that has gained popularity in the 21st century, possesses characteristics such as energy efficiency, eco-friendliness, compactness, and durability. However, its electro-optical conversion efficiency remains relatively low, as approximately 80% to 90% of the input power is dissipated as thermal energy. Consequently, the temperature of the LED rises, leading to a decrease in its luminous efficiency. Hence, it is crucial to conduct research on efficient heat dissipation methods for LEDs. We have compiled research plans from various scientific institutions and observed that through optimized design, the heat dissipation capability of LEDs has significantly improved. This improvement has resulted in reduced thermal stress within the chips and packaging, ultimately enhancing their reliability.
Bayesian Neural Network-Based Demand Forecasting for Express Transportation
Authors: Chen Rongbo , Zhong Xiaoming , Xu Xinyuan
Published: October 2023

The rapid development of e-commerce in recent years has driven the growth of the logistics service industry, which in turn has led to a significant increase in express delivery volume. Predicting express delivery volume accurately and in advance can help companies allocate various resources reasonably and provide the basis for predicting express delivery demand. To predict the specific transport volume of XX Express Company's logistics routes on April 28th and 29th, 2023, this article builds two Bayesian prediction models based on the company's historical transportation data as the training set, one for predicting the opening of logistics routes and the other for predicting express delivery quantity. This approach reduces the impact of inaccurate predictions due to logistics routes not being opened properly and improves the accuracy of the prediction model. It provides decision support for optimizing resource layout for express delivery companies.
Classification of ancient glass artifacts based on logistic regression and k-means clustering
Authors: Gao Jiahe
Published: October 2023

Chinese glass products have a long history. In this paper, for the weathering process and heritage components of ancient glass, we firstly established a logistic regression model to analyze the role of each class of chemical components on glass classification; then, in this paper, we identified the key elements with the greatest influence on glass classification: potassium oxide and lead oxide by gradually adding regression elements; subsequently, for each class of high potassium and lead barium glass, we Then, for each type of glass of high potassium and lead-barium, we selected some chemical components to establish a K-means clustering model, and after calculation, the high potassium glass was divided into four subclasses of GJ-1, GJ-2, GJ-3, and GJ-4, and the lead-barium glass was divided into four subclasses of QB-1, QB-2, QB-3, and QB-4, and the characteristics of each subclass were described. Finally, reasonableness and sensitivity tests were conducted to prove the reasonableness and robustness of the classification results.
A research on the Prediction of Wordle Based on Machine Learning
Authors: Yin Yitian , Jin Junzhe
Published: October 2023

This paper investigated the popularity and difficulty level of Wordle, an online daily puzzle game. The study examined the number of players reporting scores, the number of players on hard mode, and the percentage of players who guessed the word. After removing outliers and misspelling words, the study used time series analysis to predict future numbers of reported results. We found that Wordle had entered the decline period and recommended the last 150 days' smooth data for more accurate prediction interval results. Furthermore, the study developed the Wordle Word n-tries Percentage Prediction Model, which accurately predicts the associated percentages of tries required to solve a given word. The model uses the Regressor Chain algorithm to correlate independent variables such as word frequency, lexical properties, number of common letter combinations, and date with dependent variables. Based on the Decision Tree, the model predicts the associated percentages of tries required to solve a given word.
Word Embedding for Cross-lingual Natural Language Analysis
Authors: Hu Yukun
Published: October 2023

Word embedding, a distributed representation of natural language based on deep neural networks, has made significant breakthroughs in many natural language processing tasks and has gradually become a hot subject in research and application. Word embedding methods can capture more complex and valuable semantic information than existing methods. However, existing methods of word embedding often rely on large-scale annotation resources, which are often difficult to obtain, especially for resource-poor languages. In response to this problem, researchers have explored different research routes, such as unsupervised learning from untagged data, semi-supervised learning that integrates tagged and untagged data, or crowdsourcing. At the same time, many scholars have proposed to improve the analysis accuracy of target tasks by integrating the annotation resources of different languages and enabling knowledge from foreign languages to be transferred or merged with models. This paper discusses the development and prospects of word embedding.
Medical Equipment Supply Chain Optimization and Stability Study using Deep Reinforcement Learning
Authors: Chen Zhuoxun
Published: October 2023

Medical equipment is a critical resource during the COVID-19 pandemic. An efficient and stable supply chain of medical equipment (masks, goggles, protective coveralls, etc.) enables medical workers and first responders to effectively and safely fight against this highly contagious disease. In my research, I design and investigate two agents based on the traditional (s,Q) policy and the Deep Reinforcement Learning (DRL) algorithm and apply them respectively to optimize a two-echelon medical equipment supply chain where one distribution center and multiple retailers are involved. To my knowledge, this is the first implementation of DRL algorithm for medical supply chain optimization. I implement the DRL algorithm in Python using Ray and RLlib packages and conduct experiments using Google Colab with GPU support. To maximize the DRL algorithm’s potential, I optimize the reward function and the hyperparameters of this algorithm. By testing the agents in different environment initializations, I find that the DRL algorithm outperforms the static (s, Q) agent, which is one of the most commonly used methods in many inventory optimization systems, by returning a 17.33% greater cumulative reward on average. Additionally, the relative standard deviation of baseline (s,Q) Policy is 1.97% and that of DRL is 2.49% based on ten repeated trials. Thus, the DRL approach is not only stable but can also significantly improve the retailer’s profit. My DRL model can be further applied to more complicated multi-echelon supply chain systems and lays a solid foundation for optimizing large-scale medical supply chains [TF18].
Research on the Re-Optimizing Food Systems
Authors: Xin Meiyao , Hu Qixuan , Cai Fangshuo
Published: October 2023

Because the current food system prioritizes efficiency and profitability without considering equity and sustainability, the system is already very unstable. Therefore, we put forward optimization policies without changing the free market, and based on this, we established the food system evaluation model, the food system optimization model, and the time prediction model. We use data to analyze major issues and estimate the benefits of these policies. Because the current food system prioritizes efficiency and profitability without considering equity and sustainability, the system is already very unstable. Therefore, we put forward optimization policies without changing the free market, and based on this, we established the food system evaluation model, the food system optimization model, and the time prediction model. We use data to analyze major issues and estimate the benefits of these policies. We use the R language to perform correlation analysis on factors that may affect the food system. Then we use principal component analysis and factor analysis to find direct connections between different variables and establish comprehensive indicators to evaluate the food system. We evaluate from the perspectives of market, industrial foundation, technology, and adjustment capabilities, and analyze changes in the food system through changes in indicators related to equity and sustainability. Then we establish the SI model to estimate the time required to implement the system.
An ECAPA-TDNN Based Network for Hand Gesture Recognition on Skeletal Data
Authors: Yin Yirui
Published: October 2023

Due to the high variety of sign languages, it is essential to present a model that could recognize the hand gesture recognition. The state-of-art model is mainly driven by convolution neural networks (known as CNN), and researches are on optimizing CNN architectures. The CNN networks are too large and require long time to train. To address these challenges, we developed a more accurate and robust ECAPA-TDNN structure for recognition. The ECAPA-TDNN is a structure of multiple one- dimensional neural networks with one-dimensional convolution, activation layers, and batch normalization. On the challenging SHREC 2017 3D Shape Retrieval Contest dataset, the ECAPA-TDNN achieved an accuracy of 92.9%, which is 2% higher than the state-of-the-art accuracy achieved by CNNs.
The Role of Situational Leadership in the Management of Small and Medium-sized Enterprises Among Durban Trucking Companies
Authors: Kapotwe Jeremiah M. , Bamata Herman N.
Published: October 2023

The present research study is focused on the analysis of the role of situational leadership in the context of small and medium-sized enterprise management. The main purpose of this research is to examine and to critically evaluate the use of different situational leadership styles in the management of SMEs. This study has sought to review leader obligations and the evolution of these leadership styles in SME management. The study has intended to provide the fundamental empirical evaluation of the role played by situational leadership in SME management. The sample for the present research has been identified from the population of registered trucking companies in Durban. A sample has been drawn from the SMEs within the registered trucking companies, using convenient sampling techniques and methods.The findings of this research have shown the positive impact that situational leadership theory has in SME management. In fact, SME owners and managers will be inspired to understand the managerial role of the appropriateness behavioural style in the contextual business situations. Also, the study recommended that owners and leaders of SMEs should ameliorate leader sovereignty and follower skills, as these often interact in predicting poor follower performance and attitudinal responses. In addition, the present study has provided the tools necessary for SME owners and managers, to guide the improvement and effectiveness of personal leadership.
Description of multiparametric targeting techniques for stereotactic arrhythmia radioablation in refractory ventricular tachycardia: A quaternary medical center experience
Authors: M.G. Trombetta , E. Liu , S. Oh , G. Shaw , A. Thosani , M. Doyle , M. Gupta , R. Biederman
Published: October 2023

Background: Ventricular tachycardia (VT) is a potentially life-threatening arrhythmia which remains a major contributor to cardiac morbidity and mortality worldwide. Recently the use of stereotactic radiation has demonstrated efficacy, although standardization of methodology is lacking and variations in technique exist. In this paper, we discuss our outcomes as well as the various options available and the proposed indications for each.Methods: 12-lead EKGs and device-obtained tracings were used to approximately localize the arrhythmogenic origin and to define the arrhythmic mechanism. When feasible, electrophysiology studies (EPS) with 3-D electroanatomic (EA) mapping during which a 3-D electroanatomic substrate map was created to delineate cardiac structures, identify areas of low voltage scar and confirm arrhythmic circuits. A 4-D cardiac magnetic resonance imaging (cMRI) or cardiac computed tomography (cCT) was performed to delineate cardiac geometry and structures. The Stereotactic arrhythmia radioablation (STAR) treatment plans delivered a total dose of 25 Gy in a single treatment fraction covering the entire arrhythmogenic target.Results: Six of the nine patients showed a reduction in VT events at 6 weeks post STAR. One patient underwent cardiac transplantation two weeks following STAR. Excluding this patient from the analysis, all but one patient had a dramatic diminution in VT events (to 0) at 6 months post-procedure, including both patients with an LVAD. Six of the nine patients survived at least 4 months post procedure event free and 6 patients survive to date. The lone patient who did not respond died 13 months post procedure, however he had no further defibrillator discharges. Another patient died two months post procedure from uncontrolled multiple myeloma. One patient developed an asymptomatic pleural effusion, but no serious STAR-induced postoperative complications occurred.Conclusions: STAR appears to be an effective therapy for refractory ventricular tachycardia, although long term data are still developing. Additional clinical trials and techniques are in development and STAR programs should be encouraged for additional well-equipped centers with experienced multidisciplinary clinicians.
Nghiên cứu các nhân tố ảnh hưởng đến kết quả kinh doanh của doanh nghiệp: tình huống của các doanh nghiệp nhỏ và vừa tỉnh Thanh Hoá
Authors: Bùi Văn Huyền , Đỗ Thị Mẫn , Đỗ Tuấn Vũ
Published: October 2023

Nghiên cứu này tập trung xác định ảnh hưởng của các nhân tố đến kết quả kinh doanh của doanh nghiệp nhỏ và vừa tỉnh Thanh Hoá theo các biến kiểm soát thuộc về đặc điểm doanh nghiệp, gồm loại hình doanh nghiệp, quy mô lao động của doanh nghiệp và thời gian hoạt động của doanh nghiệp. Kết quả nghiên cứu chỉ ra rằng kết quả kinh doanh của doanh nghiệp bị ảnh hưởng rất lớn bởi nguồn lực tài chính đối với hầu hết các nhóm doanh nghiệp, ngoại trừ doanh nghiệp có số lao động từ 10 đến 50 lao động. Trong khi đó, các yếu tố như chiến lược Marketing, khả năng chuyển đổi số và khả năng quản lý và điều hành của lãnh đạo doanh nghiệp đều có tác động tích cực đến kết quả kinh doanh của các doanh nghiệp trên 100 lao động. Bên cạnh đó, các nhân tố như nguồn lực tài chính và nguồn nhân lực đều có tác động tích cực đến kết quả kinh doanh của các doanh nghiệp từ mới thành lập đến các doanh nghiệp hoạt động trên 10 năm. Kết quả nghiên cứu cũng cho thấy đối với từng loại hình doanh nghiệp thì tác động của các nhân tố đến kết quả kinh doanh cũng khác nhau.
Các yếu tố ảnh hưởng đến ý định sử dụng thuốc bảo vệ thực vật sinh học trong sản xuất rau an toàn tại các hợp tác xã trên địa bàn Hà Nội
Authors: Trần Hoàng Hà , Thanh Kim
Published: October 2023

Trong thời gian qua, do việc sử dụng quá nhiều thuốc bảo vệ thực vật hóa học, môi trường và sức khỏe con người đang bị đe dọa nghiêm trọng. Nghiên cứu này sử dụng lý thuyết hành vi dự định (TPB) để phát hiện các yếu tố ảnh hưởng đến việc sử dụng thuốc bảo vệ thực vật sinh học trong sản xuất rau an toàn. Mô hình được đề xuất bao gồm 4 biến quan sát: chuẩn chủ quan, thái độ dẫn đến hành vi, nhận thức kiểm soát hành vi và sự trung thành với thương hiệu. Kết quả nghiên cứu đã chỉ ra rằng có 3 yếu tố thái độ, nhận thức kiểm soát hành vi và chuẩn mực chủ quan, tất cả đều có tác động tích cực đến ý định của nông dân trong lựa chọn thuốc bảo vệ thực vật sinh học. Biến số sự trung thành với thương hiệu thuốc bảo vệ thực vật sinh học được đề xuất mới trong mô hình nghiên cứu nhưng khi phân tích EFA, biến này không tồn tại độc lập mà bị gộp cùng với biến thái độ dẫn đến hành vi. Đây là điểm hạn chế của nghiên cứu này nhưng cũng là hướng nghiên cứu tiếp theo khi mở rộng mô hình TPB trong nghiên cứu hành vi dự định của người nông dân trong sử dụng thuốc bảo vệ thực vật sinh học.
Bộ tiêu chí đo lường hoạt động đại lý hải quan tại Việt Nam: Nghiên cứu áp dụng phương pháp so sánh thứ bậc mờ Fuzzy AHP
Authors: Phan Thu Hiền , Lý Nguyên Ngọc
Published: October 2023

Nghiên cứu áp dụng phương pháp khoa học nhằm xây dựng bộ tiêu chí đo lường hoạt động cung ứng dịch vụ đại lý làm thủ tục hải quan tại Việt Nam. Nghiên cứu áp dụng phương pháp so sánh thứ bậc mờ Fuzzy AHP với cơ sở dữ liệu về thực tiễn hoạt động đại lý hải quan tại Việt Nam cũng như kết quả phỏng vấn trực tiếp với các doanh nghiệp có uy tín và là đối tác tin cậy của Hải quan Việt Nam. Nghiên cứu xây dựng và đo lường sự đóng góp của các yếu tố ảnh hưởng hoạt động cung ứng dịch vụ đại lý làm thủ tục hải quan từ chính quan điểm, nhận thức và thực tiễn tác nghiệp của các đại lý hải quan. Kết quả cho thấy tiêu chuẩn nghiệp vụ, tuân thủ pháp luật và sự chuyên nghiệp là những tiêu chí quan trọng nhất để xếp hạng đại lý hải quan cũng như chất lượng dịch vụ đại lý hải quan. Nghiên cứu cũng chỉ ra rằng để nâng cao uy tín và khẳng định vị trí là cầu nối giữa doanh nghiệp xuất nhập khẩu hàng hoá và cơ quan hải quan, đại lý hải quan cần quan tâm nhiều hơn đến văn hoá doanh nghiệp, đạo đức nghề nghiệp và liêm chính của đội ngũ nhân viên, đồng thời phát triển quan hệ đối tác với các bên liên quan trong chuỗi cung ứng quốc tế. Từ kết quả nghiên cứu, tác giả cũng đề xuất một số khuyến nghị nhằm phát triển hoạt động đại lý hải quan tại Việt Nam hướng tới sự chuyên nghiệp, hiệu lực và hiệu quả.
Ảnh hưởng của hiểu biết và thái độ với rủi ro tới quyết định sử dụng dịch vụ ví điện tử: Nghiên cứu trường hợp người dân thành phố Cần Thơ
Authors: Khưu Thị Phương Đông , Khổng Tiến Dũng , Hồ Thị Huỳnh Giao , Đỗ Gia Linh , Nguyễn Minh Đức
Published: October 2023

Mục tiêu của nghiên cứu này nhằm phân tích ảnh hưởng của thái độ đối với rủi ro đến quyết định sử dụng dịch vụ ví điện tử của người dân tại Thành phố Cần Thơ. Dữ liệu từ 199 đáp viên có sử dụng và không có sử dụng ví điện tử được khảo sát từ tháng 6 đến tháng 7 năm 2022. Trong đó, thái độ đối với rủi ro của người dân được đo lường bằng trò chơi thực nghiệm. Mô hình hồi quy Binary Logistics được sử dụng nhằm ước lượng ảnh hưởng của hiểu biết và thái đô đối với rủi ro đến quyết định sử dụng ví điện tử của đáp viên. Kết quả nghiên cứu đã chỉ ra rằng đáp viên có thái độ ưa thích rủi ro sẽ có khả năng quyết định sử dụng ví điện tử cao hơn nhóm e ngại và bàng quan với rủi ro (P < 0,1). Ngoài ra, hiểu biết về rủi ro có thể gặp phải trong thanh toán ví điện tử và thu nhập cũng được tìm thấy là yếu tố làm xác suất quyết định sử dụng ví điện tử của đáp viên cao hơn (P < 0,5). Dựa trên cơ sở kết quả nghiên cứu, một số giải pháp và hàm ý quản trị đã được đề xuất bao gồm xây dựng các gói bảo hiểm an toàn thanh toán điện tử, tăng cường bảo mật và đảm bảo quyền lợi của người dùng, gia tăng tiện ích của dịch vụ, phát triển sản phẩm theo từng nhóm đối tượng khách hàng nhằm phát triển của các phương thức thanh toán qua ví điện tử nói riêng và thanh toán không dùng tiền mặt nói chung.