bluuebunny/crossref_metadata_2025 huggingface dataset:
Isolation and Characterization of Multidrug Resistant Bacterial Pathogens Present in Hospital Environment within Awka Metropolis
Authors:   Department of Applied Microbiology and Brewing Faculty of Biosciences Nnamdi Azikiwe University, Awka., Okwudili; Anyamene Christopher , Chukwusom Godwin Victor ,   Department of Applied Microbiology and Brewing Faculty of Biosciences Nnamdi Azikiwe University, Awka., Uzoamaka Ezebialu Chinenye ,   Department of Applied Microbiology and Brewing Faculty of Biosciences Nnamdi Azikiwe University, Awka.
Published: May 2023

The contamination of hospital environment by bacterial organisms plays a vital role in the spread of nosocomial infections. This study was conducted to determine bacterial contamination, bacterial profiles, antibiotic susceptibility pattern and plasmid profiles of bacterial isolates from hospital air, water and fomite environment within Awka. This cross-sectional study was conducted at Crest Specialist Hospital, Regina Caeli Specialist Hospital and Nnamdi Azikiwe University (UNIZIK) Medical Centre, Awka. Using random sampling techniques (surface, air and water), culturing, Gram staining, antibiotic susceptibility test, biochemical tests and molecular identification, bacterial organisms from surrounding air, water and fomites were isolated and identified. A total of 112 samples were collected from the three hospitals. Of all the samples, 110 (98.2%) showed positive for bacterial growth. A total of 40 bacterial isolates underwent antibiotic sensitivity testing, of which 6 (15%) showed multidrug resistance. Bacterial organisms isolated from Regina Caeli Hospital showed the most resistance to the antibiotic drugs (41.8%), followed by Crest Specialist Hospital (30.9%) and then UNIZIK Medical Centre (27.3%). Interestingly, there was 100% sensitivity of isolates to ciprofloxacin, levofloxacin, ofloxacin, augmentin (amoxicillinclavulanate), rifampicin and septrin. Out of the six multidrug resistant isolates, Staphylococcus hominis strain PCP01, Myroides odoratimimus subsp. xuanwuensis strain M2S3B6 and Bacillus cereus strain DS-2 were identified using DNA sequencing and PCR. The three identified microorganisms are opportunistic pathogens. While S. hominis has no plasmid, both M. odoratimimus and B. cereus showed the presence of plasmids. With proper prevention practices such as; disinfection of hospital surfaces, proper personal hygiene of health care workers, special air handling and ventilation and wearing of facemask within the hospital environment, possibilities of nosocomial infections can be reduced drastically, especially in Africa. Keywords: Isolation, Characterization, Multidrug Resistant and Bacterial
Participación comunitaria en la reducción de la inseguridad, revisión sistemática de la literatura 2016-2022
Authors: Sánchez-Mendoza Víctor Raúl
Published: May 2023

Siendo la participación comunitaria una de las herramientas que implementan los Estados a nivel mundial para enfrentar el fenómeno de la inseguridad en sus espacios urbanos y rurales, mediante el presente artículo se buscó identificar la existencia de evidencia empírica respecto a la implementación de los mecanismos de participación de los ciudadanos, casi siempre por los órganos policiales, a la expectativa de la población por dichos programas y sobre la posible efectividad de tales esfuerzos. Se exploró la existencia de artículos publicados en revistas científicas recopilados a través de repositorios y bases de datos en un número de 1 282 en base a ciertos criterios iniciales, a partir de los cuales se determinaron condiciones incluyentes y excluyentes, para finalmente evaluar un total de 33 artículos publicados en revistas indexadas en Scopus, PubMed, ProQuest y Tandfonline. Del análisis de la data recopilada se pudo concluir que la participación comunitaria es una reacción de autodefensa de los ciudadanos que rara vez surge espontáneamente de los mismos, sino que es impulsado por los gobiernos u otros organismos, lo que lo hace sensible a diversas limitantes que le restan efectividad, por lo que se genera un camino por investigar.
Management of esophageal neoplasms by endoscopic submucosal dissection: experience over 100 consecutive procedures
Authors: Ramos Josué Aliaga , Morita Yoshinori , Toyonaga Takashi , Carvalho Danilo , Pedrosa Moises Salgado , Arantes Vitor N.
Published: May 2023

Background/Aims: Endoscopic submucosal dissection (ESD) is currently considered the first-line treatment for the eradication of superficial neoplasms of the esophagus in Eastern countries. However, in the West, particularly in Latin America, the experience with esophageal ESD is still limited because of the high technical complexity required for its execution. This study aimed to present the results of the clinical application of ESD to manage superficial esophageal neoplasms in a Latin American center in over 100 consecutive cases.Methods: This retrospective study included consecutive patients who underwent endoscopic ESD for superficial esophageal neoplasms between 2009 and 2022. The following clinical outcomes were assessed: en bloc, complete, and curative resection rates, local recurrence, adverse events, and procedure-related mortality.Results: Esophageal ESD was performed mainly for squamous cell carcinoma (66.6%), high-grade intraepithelial neoplasia (17.1%), and adenocarcinoma (11.4%). En bloc and complete resection rates were 96.2% and 81.0%, respectively. The curative resection rate was 64.8%. Adverse events occurred in six cases (5.7%). Endoscopic follow-up was performed for an average period of 29.7 months.Conclusions: ESD performed by trained operators is feasible, safe, and clinically effective for managing superficial neoplastic lesions of the esophagus in Latin America.
Feature Extraction in Music information retrival using Machine Learning Algorithms
Authors: Karthik V  , Savita Chaudhary  , Radhika A D
Published: May 2023

Music classification is essential for faster Music record recovery. Separating the ideal arrangement of highlights and selecting the best investigation technique are critical for obtaining the best results from sound grouping. The extraction of sound elements could be viewed as an exceptional case of information sound information being transformed into sound instances. Music division and order can provide a rich dataset for the analysis of sight and sound substances. Because of the great dimensionality of sound highlights as well as the variable length of sound fragments, Music layout is dependent on the overpowering computation. By focusing on rhythmic aspects of different songs, this article provides an introduction of some of the possibilities for computing music similarity. Almost every MIR toolkit includes a method for extracting the beats per minute (BPM) and consequently the tempo of each music. The simplest method of computing very low-level rhythmic similarities is to sort and compare songs solely by their tempo There are undoubtedly far better and more precise solutions.  work discusses some of the most promising ways for computing rhythm similarities in a Big Data framework using machine Learning algorithms.
Melanoma classification using deep transfer learning
Authors: Mounika Nookala  , Bhumireddy yasaswi  , Chindanooru Sai Joshna  , Illuru Vandana
Published: May 2023

Melanoma is the most lethal type of skin cancer, despite the fact that individuals who are discovered early have a decent chance of recovering. A few creators have looked at various strategies to deal with programmed location and conclusion using design recognition and AI technology. Anticipating an infection so that it does not spread It is often helpful when doctors can diagnose an illness early on and spread throughout the body. Early disease detection is quite difficult due to the small number of screening populations. Whatever the case, it will take time to determine if it is harmless or hazardous. Assume the afflicted person sees a critical specialist for analysis, unaware that the critical specialist's knowledge has resulted in a cancerous development. This is where AI and deep learning technologies become a vital component of an effective mechanised determination framework, which might help doctors forecast infections much more swiftly and even ordinary people analyse a sickness. Our study endeavour addresses the issues of increased clinical expenditures associated with discovery, lower Precision in recognition and the manual discovery framework's mobility. System for Detecting Malignant Growths in Melanoma is a deep learning-based predictive model that leverages thermoscope pictures.
Performance of re-ranking techniques used for recommendation method to the user CF- Model
Authors: N. Thangarasu  , R. Rajalakshmi  , G. Manivasagam  , V. Vijayalakshmi
Published: May 2023

The recent research work for addressed to the aims at a spectrum of item ranking techniques that would generate recommendations with far more aggregate variability across all users while retaining comparable levels of recommendation accuracy. Individual users and companies are increasingly relying on recommender systems to provide information on individual suggestions. The recommended technologies are becoming increasingly efficient because they are focusing on scalable sorting-based heuristics that make decisions based solely on "local" data (i.e., only on the candidate items of each user) rather than having to keep track of "national" data, such as items have been all user recommended at the time. The real-world rating datasets and various assessments to be the prediction techniques and comprehensive empirical research consistently demonstrate the proposed techniques' diversity gains. Although the suggested approaches have primarily concentrated on improving recommendation accuracy, other critical aspects of recommendation quality, such as recommendation delivery, have often been ignored.
Detection of Covid-19 from X-ray Images using Deep Learning Techniques
Authors: Aviral Srivastava  , V Vineeth Kumar  , Mahesh T R
Published: May 2023

Machine Learning (ML) based forecast systems have demonstrated their significance results in detecting several diseases. ML models have for some time been utilized in numerous application regions requiring the ID and prioritization of troublesome variables for a danger. Understanding and characterizing chest x-beam (CXR) and figured tomography (CT) pictures are critical for the finding of COVID19. To resolve these issues, the CNN Vggnet19 has been utilized to analyze Corona virus in light of CXR lung pictures. Such a device can save time in deciphering chest x-beams and increment exactness and consequently work on our clinical capacity to identify and analyze COVID19. In this work, arrangement of clinical x-beam lung pictures (which incorporate typical pictures, contaminated with microorganisms, and tainted infections including COVID19) were utilized to frame a profound CNN that could make the differentiation among clamour and helpful data, then utilize this preparation to decipher new pictures by perceiving designs that show specific sicknesses, for example, Covid disease in individual pictures.
Clustering Techniques for Recommendation of Movies
Authors: Mahesh T R  , V Vinoth Kumar
Published: May 2023

A recommendation system employs a variety of algorithms to provide users with recommendations of any kind. The most well-known technique, collaborative filtering, involves users with similar preferences although it is not always as effective when dealing with large amounts of data. Improvements to this approach are required as the dataset size increases. Here, in our suggested method, we combine a hierarchical clustering methodology with a collaborative filtering algorithm for making recommendations. Additionally, the Principle Component Analysis (PCA) method is used to condense the dimensions of the data to improve the accuracy of the outcomes. The dataset will receive additional benefits from the clustering technique when using hierarchical clustering, and the PCA will help redefine the dataset by reducing its dimensionality as needed. The primary elements utilized for recommendations can be enhanced by applying the key elements of these two strategies to the conventional collaborative filtering recommendation algorithm. The suggested method will unquestionably improve the precision of the findings received from the conventional CFRA and significantly increase the effectiveness of the recommendation system. The total findings will be applied to the combined dataset of TMDB and Movie Lens, which is utilized to suggest movies to the user in accordance with the rating patterns that each individual user has generated.
Data Breach – Its Effects on Industry
Authors: Manju Bargavi  , M.Senbagavalli  , Tejashwini.K.R  , Tejashvar.K.R
Published: May 2023

In this Digital world, Data has become one of the most crucial parts in every field. To protect this sensitive piece of information many methods and technologies are coming into existence. A data breach reveals sensitive, protected and confidential information to an unauthorized person. Increasingly opportunities exist for information to leak out as our computers and mobile devices become more associated. Data leaks pose a serious threat to companies and can cost them significantly either financially and reputationally. The long-term effects of a data breach can spread throughout a company, having an effect on all parties involved, including the user base, staff, and cybersecurity teams in charge of repair. By giving priority to the most frequently attacked industries, this article will advance understanding about data hacking incidents and aid in securing corporate data.
A Systematic Survey of Classification Algorithms for Cancer Detection
Authors: Ashish Kumar Pandey  , Prabhdeep Singh
Published: May 2023

Cancer is a fatal disease induced by the occurrence of a count of inherited issues and also a count of pathological changes. Malignant cells are dangerous abnormal areas that could develop in any part of the human body, posing a life-threatening threat. To establish what treatment options are available, cancer, also referred as a tumor, should be detected early and precisely. The classification of images for cancer diagnosis is a complex mechanism that is influenced by a diverse of parameters. In recent years, artificial vision frameworks have focused attention on the classification of images as a key problem. Most people currently rely on hand-made features to demonstrate an image in a specific manner. Learning classifiers such as random forest and decision tree were used to determine a final judgment. When there are a vast number of images to consider, the difficulty occurs. Hence, in this paper, we analyze, review, categorize, and discuss current breakthroughs in cancer detection utilizing machine learning techniques for image recognition and classification. We have reviewed the machine learning approaches like logistic regression (LR), Naïve Bayes (NB), K-nearest neighbors (KNN), decision tree (DT), and Support Vector Machines (SVM).
A Review on Cloud Data Security Challenges and existing Countermeasures in Cloud Computing
Authors: Prabhdeep Singh  , Ashish Kumar Pandey
Published: May 2023

Cloud computing (CC) is among the most rapidly evolving computer technologies. That is the required accessibility of network assets, mainly information storage with processing authority without the requirement for particular and direct user administration. CC is a collection of public and private data centers that provide a single platform for clients throughout the Internet. The growing volume of personal and sensitive information acquired through supervisory authorities demands the usage of the cloud not just for information storage and for data processing at cloud assets. Nevertheless, due to safety issues raised by recent data leaks, it is recommended that unprotected sensitive data not be sent to public clouds. This document provides a detailed appraisal of the research regarding data protection and privacy problems, data encrypting, and data obfuscation, including remedies for cloud data storage. The most up-to-date technologies and approaches for cloud data security are examined. This research also examines several current strategies for addressing cloud security concerns. The performance of each approach is then compared based on its characteristics, benefits, and shortcomings. Finally, go at a few active cloud storage data security study fields.
Information Security: A Coordinated Strategy to Guarantee Data Security in Cloud Computing
Authors: Kofi Immanuel Jones  , R. Suchithra
Published: May 2023

This paper discusses different techniques and specialized procedures which can be used to effectively protect data from the owner to the cloud and then to the user. The next step involves categorizing the data using three encryption parameters provided by the user, which are Integrity, Availability, and Confidentiality (IAC). The data is secured through various methods such as SSL and MAC protocols to ensure data integrity checks, searchable encryption, and splitting the data into three parts for cloud storage. Dividing the data into three portions not only enhances security but also facilitates easier access. Access to the encrypted data requires the user to provide the login information and password of the owner. This paper also studies critical security issues like unauthorized servers, brute force attacks, threats from cloud service providers, and loss of user identity and password.
Cryptographic Interweaving of Messages
Authors: Jagadeesh Sai D  , Krishnaraj P M
Published: May 2023

During the past several decades, the information and communication technology sector has advanced significantly, enabling extensive information interchange over the internet, including message sharing and electronic transactions. These days, the main issue is how to transmit information securely. From ancient times, there has been interest in the field of cryptography research. A masterwork of cryptography is Muni Kumudendu's original work, Siribhoovalaya. His study served as the basis for the method suggested in this publication. Several messages can be sent using different keys utilising a single matrix. Encryption uses a variety of matrix traversal techniques, making it challenging for cryptanalysis to map the plaintext and ciphertext.
Using Federated Artificial Intelligence System of Intrusion Detection for IoT Healthcare System Based on Blockchain
Authors: Priyanka Tyagi  , S.K. Manju bargavi
Published: May 2023

Recently Internet of things (IoT)-based healthcare system has expanded significantly, however, they are restricted by the absence of an intrusion detection mechanism (IDS). Modern technologies like blockchain (BC), edge computing (EC), and machine learning (ML) provide a robust security solution that is well-suited to protecting patients' medical information. In this study, we offer an intelligent intrusion detection mechanism FIDANN that protects the confidentiality of medical data by completing the intrusion detection task by utilising Dwarf mongoose-optimized artificial neural networks (DMO-ANN) through a federated learning (FL) technique. In the context of recent developments in blockchain technology, such as the elimination of contaminating attacks and the provision of complete visibility and data integrity over the decentralized system with minimal additional effort. Using the model at the edges secures the cloud from attacks by limiting information from its gateway with less computing time and processing power as FL works with fewer datasets. The findings demonstrate that our suggested models perform better when dealing with the diversity of data produced by IoT devices.
Dynamic Mobile Cloud Eco System Security - A Review
Authors: M.Anitha  , M. Senbagavalli
Published: May 2023

Mobile cloud computing is the technique of using cloud technology and various rich mobile applications are intended to be able to run on a variety of mobile devices using the technique called mobile cloud computing. In recent years, huge amounts of data are stored by the clients which are much more easily to the integration of cloud platforms into mobile systems. The ways of security used in portable device settings are one of the key challenges in this respect as the number of people using smartphones continues to rise. None of the models that have been developed with confidence and privacy for precaution of data in mobile cloud systems are impervious to destructive attacks, despite countless attempts. While mobile cloud computing has great potential, security, privacy, viability, and accessibility concerns must still be considered by both consumers and businesses. Additionally, it emphasizes the use of Canny Card Web Services (CCWS) competition to enhance mobile cloud computing security with IOT. This paper has been presented with more than one user application: a smart house and a smart parking in an educational institution, in the inclusion of IOT with cloud computing for demonstrating various admittance control and endorsement requirement. A review regarding this paper concentrated on a little model that is intended the security and privacy ensureability of data in mobile clouds. Additionally, to manage mobile cloud security difficulties and challenges, it is important to look at the current situation with regard to cloud security breaches, the weaknesses of mobile cloud devices, and the best ways to address these issues in the near future with regard to mobile device management and mobile data protection.
Cloud Computing with Artificial Intelligence Techniques for Effective Disease Detection
Authors: Arvind Kumar Shukla  , V. Suresh Kumar
Published: May 2023

With the current rapid advancement of cloud computing (CC) technology, which enabled the connectivity of many intelligent objects and detectors and created smooth data interchange between systems, there is now a strict need for platforms for data processing, the Internet of Things (IoT), and data management. The field of medicine in CC is receiving a lot of attention from the scientific world, as well as the private and governmental sectors. Thousands of individuals now have a digital system due to these apps where they may regularly obtain helpful medical advice for leading a healthy life. The use of artificial intelligence (AI) in the medical field has several advantages, including the ability to automate processes and analyze large patient databases to offer superior medicine more quickly and effectively. IoT-enabled smart health tools provide both internet solutions and a variety of features. CC infrastructure improves these healthcare solutions by enabling safe storage and accessibility. We suggest a novel Cloud computing and artificial intelligence (CC-AI) premised smart medical solution for surveillance and detecting major illnesses to provide superior solutions to the users. For disease detection, we suggested AI-based whale optimization (WO) and fuzzy neural network (FNN) (WO-FNN). Patients' IoT wearable sensor data is gathered for detection. The accuracy, sensitivity, specificity, and computation time are evaluated and compared with existing techniques.
Towards Designing a Planet Walk Simulation in a Controlled Environment
Authors: Justus Selwyn  , Prasanna Ranjith Christodoss
Published: May 2023

Planet Walk Simulation involves several parametric readings like physical human body conditions, geographic and atmospheric conditions, etc. In this work, we have set goals including system state monitoring, terrain mapping, and user navigation. Specific objectives are displaying the user’s telemetry, elevating their spatial awareness through short range object detection, and displaying their location relative to origin using wi-fi routers. The experimental results showed navigation motion paths for astronauts and identify obstacles in the path with the help of LiDAR and Hololens.
Rodent population dynamics and crop loss estimation due to rodent pests in finger millet based crop lands
Authors:   UAS, Bangalore, Naik Mohan I Naik , Binny Vipin Chaudhary ,   ICAR, A V Basavadarshan ,   UAS, Bangalore
Published: May 2023

Ragi (Eleusine coracana Gaertn ) also known as finger millet is an important millet widely grown in Asia and is the major staple food in southern Karnataka. Rodents are critical vertebrate pests and are regarded as big chaos to agricultural production. In the present studies the rodent population and crop loss due to rodent pest in finger millet crop was analyzed during the year 2022. The studies revealed that with mean trap index of 20.28 the rodent activity in the finger millet crop lands was observed throughout the year and the peak rodent activity was recorded in Kharif and Rabi crop seasons and was less in the dry (summer) seasons. The population was male and adult dominant with a male female ratio of 1:0.92 and adult infant ratio of 1:0.56, respectively. The Shannon index (Hǀ) in finger millet crop lands found to be 1.08 and the peak Shannon index was recorded in the month of August with a highest relative abundance of Bandicota bengalensis, Tatera indica and Mus platythrix rodent species in the finger millet crop lands. The yield loss estimation studies indicated that there was a grain loss of 2.98 q ha-1 in finger millet crop lands with a monetary value of Rs. 10, 662 (US $129.48) per hectare.
Identifying and Verifying Functional Communication Behaviour in Two Hong Kong Chinese Children with Autism
Authors:   Department of Education Studies, Macquarie University, Sydney, NSW, Australia, Tait Kathleen
Published: May 2023

This study examined the idiosyncratic and subtle behaviours of two young children with Autism living in Hong Kong SAR by combining the theoretical areas of prelinquistic communication and functional behaviour. It examined how Chinese mothers interpret the behaviour of their children as communicative. The forms and functions of prelinguistic communicative behaviour of the participants were assessed using the Inventory of Potential Communicative Acts (IPCA). The children’s mothers completed the IPCA and the results were analyzed to provide a systematic inventory and objective description of the communicative forms and functions present in the children’s repertoire. The respondents reported a wide variety of communicative forms and functions. An innovative aspect of this study was the use of intra-subject replication as a method of verifying the accuracy of the respondents’ predictions. Problematic topographies were screaming and non-compliance. From an applied perspective there is a critical need to develop empirically validated and translated functional assessment procedures to enhance communication ability in children with Autism in Hong Kong SAR.
Factors affecting attitudes of Secondary School Educational Practitioners towards Inclusive Education in Mauritius
Authors:   Open University of Mauritius, Mauritius, Dhuny Nazia Abdoula
Published: May 2023

Inclusive education, as an educational reform to achieve education for all is referred to as educating students with special education needs in regular schools. This relatively new concept in Mauritius seems to be facing a number of challenges. Given the worldwide interest for IE, unfavourable attitudes would be a major hurdle in the implementation of IE in Mauritius. A positive attitude of education stakeholders in Mauritius is vitally important to complement inclusive efforts. The study endeavoured to determine the relationship of demographic factors, beliefs and self-efficacy on attitudes in the Mauritian context. A quantitative non-experimental descriptive survey research design was used in this study and respondents included 588 educators and 42 rectors/deputy rectors in 21 secondary schools (state and private). Investigating respondents’ attitudes was conducted through a specifically designed survey instrument. Results indicated an overall neutral attitudes towards IE. Training in inclusive education was found to significantly influence attitudes and a positive correlation of self-efficacy and beliefs on attitudes was found. These findings support the need for capacity building that could help nurture positive attitudes and foster inclusive environments in Mauritius. The study provides insights for future research to further the understanding of attitudes towards IE in Mauritius.
Tutoring Students with Autism in Online Mode during the Pandemic: Survey on Special Educators of Kolkata and its vicinity
Authors:   University of Calcutta, Mukherjee Roshni , Halder Santoshi ,   University of Calcutta
Published: May 2023

The study aims to explore the teaching milieu through the lens of special educators during the pandemic when students with autism shifted to online mode in special schools. This survey was done on 100 special educators from in and around Kolkata City (West Bengal, Eastern part of India). Graphical univariate exploratory data analysis is used to interpret the results. The results reveal the challenges (viz., from the behavioral problems of students to network issues) and facilitators (viz., software used for the effective Online evaluation or assessment) of the online mode of teaching extensively during the pandemic time. The future directions for the online mode concerning teaching-learning for learners with autism are also suggested.
The Influence of Traditional Music on Cultural Preservation and Identity: A Study of the Kora in West Africa
Authors: Huynh Quang Long
Published: May 2023

This study investigates the function of traditional music in maintaining cultural identity. In particular, the study focuses on the Kora, a stringed instrument from West Africa that is essential to the Manding people's music and cultural customs. The essay examines how the Kora has been used throughout history to uphold and advance cultural customs as well as how it has helped to shape and preserve Manding cultural identity.
Ao Dai as a Symbol of Vietnamese Traditions
Authors: Huynh Van Quang
Published: May 2023

The Ao Dai is a type of traditional Vietnamese clothing that has evolved into a recognizable icon that represents the culture and history of Vietnam. This paper examines the history of the Ao Dai as well as its cultural significance, tracing its evolution from its beginnings in the 18th century to its current status as a popular fashion item and national symbol. The origins of the Ao Dai can be traced back to the 18th century. This paper argues, through an analysis of academic literature, media articles, and popular culture, that the Ao Dai embodies a complex range of cultural values and beliefs in Vietnamese society, and that it serves as a reflection of the country's history, politics, and social norms.
A Short Overview of French's Colonialism in Vietnam and its Impacts
Authors: Skokan Josef
Published: May 2023

This article explores the complex and multi-faceted legacy of Vietnam's colonial era, which lasted from the late 19th century to the mid-20th century. The article reviews important literature that investigates the political, economic, and cultural impact of colonialism on Vietnam. The economic impact of colonialism resulted in the severe exploitation of Vietnam's resources and widespread poverty among its inhabitants. The political impact of colonialism led to persecution, and imprisonment of those who opposed the French colonial regime. The cultural impact of colonialism introduced Western culture to Vietnam, resulting in the decline of traditional cultural practices and values. Despite these negative impacts, Vietnam has restored its cultural legacy and built a distinct national identity through its fight for freedom and independence. This article highlights the lasting impact of colonialism on a country's society, economy, and culture.
Performance et monde du travail : analyser autrement la performance contextuelle en lien avec la santé psychologique
Authors: Parenteau Chloé , Séguin‐Lemire Ariane , Dagenais‐Desmarais Véronique
Published: May 2023

Les études sur la thèse du travailleur heureux‐productif sont contradictoires. On présume l’existence d’un lien linéaire entre la performance et la santé psychologique. De plus, on constate que le type de performance et ses effets varient selon les études. Cet article vise une meilleure compréhension du lien entre la performance et la santé psychologique des travailleurs. L’association non linéaire entre la performance contextuelle, le bien‐être psychologique au travail et l’épuisement professionnel a été examinée. Les résultats d’un questionnaire administré à 978 travailleurs canadiens démontrent que le pourcentage de variance du bien-être psychologique au travail et de l’épuisement professionnel expliquée par la performance contextuelle est plus important lors de l’ajout de termes quadratiques aux analyses.
Mesurer l’intention de rester ou l’intention de quitter… telle est la question !
Authors: Lafrenière-Carrier Benjamin , Lauzier Martin , Yelle Martin
Published: May 2023

Cette étude évalue deux manières de formuler la mesure d’intention de départ (c.-à-d. de rester ou de quitter) chez des membres des Forces Armées Canadiennes (FAC). Deux objectifs sont poursuivis : (1) déterminer la variance partagée par ces deux mesures et (2) comparer la force des corrélations qu’entretiennent chacune des formulations avec des indices de satisfaction (c.-à-d. au travail et dans la vie). Cette étude exploite 5069 questionnaires recueillis au sein des FAC. Les résultats montrent que les deux formulations de la mesure d’intention ne partagent qu’une faible part de variance. On y observe également que les différentes formulations de la mesure d’intention entretiennent des corrélations semblables avec les deux indices de satisfaction. Malgré le caractère exploratoire de cette étude, les résultats observés invitent praticiens et chercheurs à la réflexion ainsi qu’à la nuance le moment venu de mesurer l’intention à maintenir (ou non) le lien d’emploi.
Trois approches d’apprentissage collaboratif dans l’action pour soutenir le développement du leadership
Authors: Baron Charles , Baron Louis
Published: May 2023

En cette ère de complexité et de changements accélérés, la survie et le développement des organisations semblent reposer sur leurs capacités à apprendre et à innover (Heifetz, Grashow & Linsky, 2009). Cet article présente trois approches d’apprentissage collaboratif dans l’action qui permettent à des professionnels, à des gestionnaires et à des dirigeants de se développer professionnellement tout en contribuant au développement de leur organisation. Favorisant un leadership plus efficient, efficace ou légitime, ces approches ne répondent toutefois pas toutes aux mêmes besoins et présupposent des conditions de succès particulières.
L’insécurité linguistique chez des locuteurs de français langue étrangère au Brésil : une étude exploratoire
Authors: Nazzari Gomes Janaína , Freisleben Larissa Colombo , Dorneles Matheus , de Marins Macedo Wesley
Published: May 2023

De nature exploratoire, cet article investigue une dimension sociolinguistique souvent délaissée dans le domaine de la didactique du français langue étrangère : l’insécurité linguistique chez des locuteurs n’ayant pas le français comme langue maternelle. À partir du concept d’insécurité linguistique normative et d’un examen du contexte sociodiscursif entourant le français au Brésil, sont analysées des données issues du projet de conversationFrançais d’occasion. Cette analyse fournit des pistes pour déterminer les traits du sentiment d’insécurité en français au Brésil.
Transforming the delivery of chiropractic education through the strategic integration of educational technology in a chiropractic college program
Authors: Harrington Billie G.
Published: May 2023

Objective

Chiropractic institutions face the challenging quandary of how to prepare future doctors for entry into a society completely transformed by technology. At an increasing rate, the incoming student profile is representative of a digital generation with a high affinity for technology use. The aim of this study was 2-fold: (1) outline the basic elements of a technology integration program at our institution and (2) determine if a potential relationship exists between ongoing training and acceptance of such a programmatic shift among faculty and students.

Methods

At each phase of technology integration, electronic survey instruments were deployed to participating students and faculty members. Survey instruments included question items assessed through Likert-type scales and open-ended questions to provide students and faculty members with a vehicle for providing specific feedback. To ensure anonymity of student and faculty survey respondents, the response collection source was a different department than the deployment of the survey emails. Participants were encouraged, but not required, to complete the surveys.

Results

Analysis of survey responses generally found increases in overall participant satisfaction and acceptance of the technology integration with the provision of ongoing support systems.

Conclusion

As suggested in similar scholarship in the field, the results of this study underscored the value of support systems for faculty members and students in an academic community. The systems that provided ongoing training and other support mechanisms seemed more accepted when tailored to myriad skill levels. Creating a culture in which faculty members and students felt adequately supported fostered the acceptance necessary for forward momentum of a campus initiative of significant change.
Intravitreal Glioma in a Boy Aged 7 Years
Authors: Dentel Alexandre , Bremond-Gignac Dominique , Robert Matthieu P.
Published: May 2023

This case report discusses a diagnosis of intravitreal glioma in a boy aged 7 years with neurofibromatosis type 1.
Unraveling the folding and dimerization properties of the human FoxP subfamily of transcription factors
Authors: Villalobos Pablo , Carvajal Alonso I. , Castro‐Fernández Víctor , Babul Jorge , Ramírez‐Sarmiento César A. , Medina Exequiel
Published: May 2023

Human FoxP proteins share a highly conserved DNA‐binding domain that dimerizes via three‐dimensional domain swapping, although showing varying oligomerization propensities among its members. Here, we present an experimental and computational characterization of all human FoxP proteins to unravel how their amino acid substitutions impact their folding and dimerization mechanism. We solved the crystal structure of the forkhead domain of FoxP4 to then perform a comparison across all members, finding that their sequence changes impact not only the structural heterogeneity of their forkhead domains but also the protein–protein association energy barrier. Lastly, we demonstrate that the accumulation of a monomeric intermediate is an oligomerization‐dependent feature rather than a common aspect of monomers and dimers in this protein subfamily.
Analyzing the role of cancer‐associated fibroblast activation on macrophage polarization
Authors: Bruch‐Oms Marina , Olivera‐Salguero Rubén , Mazzolini Rocco , del Valle‐Pérez Beatriz , Mayo‐González Paula , Beteta Ángel , Peña Raúl , García de Herreros Antonio
Published: May 2023

Snail1 is a transcriptional factor required for cancer‐associated fibroblast (CAF) activation, and mainly detected in CAFs in human tumors. In the mouse mammary tumor virus‐polyoma middle tumor‐antigen (MMTV‐PyMT) model of murine mammary gland tumors, Snai1 gene deletion, besides increasing tumor‐free lifespan, altered macrophage differentiation, with fewer expressing low levels of MHC class II. Snail1 was not expressed in macrophages, and in vitro polarization with interleukin‐4 (IL4) or interferon‐γ (IFNγ) was not altered by Snai1 gene depletion. We verified that CAF activation modified polarization of naïve bone‐marrow‐derived macrophages (BMDMΦs). When BMDMΦs were incubated with Snail1‐expressing (active) CAFs or with conditioned medium derived from these cells, they exhibited a lower cytotoxic capability than when incubated with Snail1‐deleted (inactive) CAFs. Gene expression analysis of BMDMΦs polarized by conditioned medium from wild‐type or Snai1‐deleted CAFs revealed that active CAFs differentially stimulated a complex combination of genes comprising genes that are normally induced by IL4, downregulated by IFNγ, or not altered during the two canonical differentiations. Levels of RNAs relating to this CAF‐induced alternative polarization were sensitive to inhibitors of factors specifically released by active CAFs, such as prostaglandin E2 and TGFβ. Finally, CAF‐polarized macrophages promoted the activation of the immunosuppressive regulatory T cells (T‐regs). Our results imply that an active CAF‐rich tumor microenvironment induces the polarization of macrophages to an immunosuppressive phenotype, preventing the macrophage cytotoxic activity on tumor cells and enhancing the activation of T‐reg cells.
Direct effect of 2‐palmitoyl glycerol on promotion of gamma aminobutyric acid synthesis in normal human fetal‐derived astrocytes
Authors: Tsuboi Misato , Nakamura Yoshitaka , Sakuma Hiroshi
Published: May 2023

Breast milk contains constituents, such as 1,3‐dioleoyl‐2‐palmitoylglycerol (OPO), that are beneficial for infants. Herein, we hypothesized that 2‐palmitoyl glycerol (2‐PG), a derivative of OPO, is advantageous to infants' development. Gamma aminobutyric acid (GABA) is a major neurotransmitter involved in neural development. Although GABA is generally known to be produced in neurons, astrocytes can also produce it in immature brains. In this study, we used expression analysis techniques to show that 2‐PG upregulates the mRNA and protein expression of glutamate decarboxylases (GAD1 and GAD2) in normal human fetal‐derived astrocytes. Our data suggest that 2‐PG promotes GABA synthesis in astrocytes, which may contribute to brain development because GABA is involved in neural development in the developing brain. This may help to elucidate the mechanism by which breast milk affects infant brain development.
Glow Stick‐Inspired Multilayered Composites with Damage Self‐Reporting and Self‐Healing Properties for Aquatic Environments
Authors: Xiao Jing , Jia Liangying , Zhang Kaiqiang , Wang Xu
Published: May 2023

Materials are inevitable to suffer from mechanical damage such as scratches or cuts when they are exposed to the marine environment. Herein, a hierarchical composite material is fabricated, which demonstrates the self‐reporting and self‐healing behaviors in aquatic environments including deionized water, seawater, acidic, and basic aqueous solutions. The composite material is constructed of a five‐layer structure and shows excellent responsiveness to water molecules. After the material is damaged underwater, the chemiluminescence reaction comes into being quickly and the luminescence signal can last for over 3 h, allowing for timely and rapid reporting of damage. Furthermore, materials demonstrate high stretchability and self‐healing behavior, making them possible to serve as soft products used in underwater environments.
Buckling Metamaterials for Extreme Vibration Damping
Authors: Dykstra David M.J. , Lenting Coen , Masurier Alexandre , Coulais Corentin
Published: May 2023

Damping mechanical resonances is a formidable challenge in an increasing number of applications. Many passive damping methods rely on using low stiffness, complex mechanical structures or electrical systems, which render them unfeasible in many of these applications. Herein, a new method for passive vibration damping, by allowing buckling of the primary load path in mechanical metamaterials and lattice structures, is introduced, which sets an upper limit for vibration transmission: the transmitted acceleration saturates at a maximum value in both tension and compression, no matter what the input acceleration is. This nonlinear mechanism leads to an extreme damping coefficient tanδ≈ 0.23 in a metal metamaterial—orders of magnitude larger than the linear damping coefficient of traditional lightweight structural materials. This principle is demonstrated experimentally and numerically in free‐standing rubber and metal mechanical metamaterials over a range of accelerations. It is also shown that damping nonlinearities even allow buckling‐based vibration damping to work in tension, and that bidirectional buckling can further improve its performance. Buckling metamaterials pave the way toward extreme vibration damping without mass or stiffness penalty, and, as such, could be applicable in a multitude of high‐tech applications, including aerospace, vehicles, and sensitive instruments.
Electrochemical‐Memristor‐Based Artificial Neurons and Synapses—Fundamentals, Applications, and Challenges
Authors: Chen Shaochuan , Zhang Teng , Tappertzhofen Stefan , Yang Yuchao , Valov Ilia
Published: May 2023

Artificial neurons and synapses are considered essential for the progress of the future brain‐inspired computing, based on beyond von Neumann architectures. Here, a discussion on the common electrochemical fundamentals of biological and artificial cells is provided, focusing on their similarities with the redox‐based memristive devices. The driving forces behind the functionalities and the ways to control them by an electrochemical‐materials approach are presented. Factors such as the chemical symmetry of the electrodes, doping of the solid electrolyte, concentration gradients, and excess surface energy are discussed as essential to understand, predict, and design artificial neurons and synapses. A variety of two‐ and three‐terminal memristive devices and memristive architectures are presented and their application for solving various problems is shown. The work provides an overview of the current understandings on the complex processes of neural signal generation and transmission in both biological and artificial cells and presents the state‐of‐the‐art applications, including signal transmission between biological and artificial cells. This example is showcasing the possibility for creating bioelectronic interfaces and integrating artificial circuits in biological systems. Prospectives and challenges of the modern technology toward low‐power, high‐information‐density circuits are highlighted.
In Situ Polymerization on a 3D Ceramic Framework of Composite Solid Electrolytes for Room‐Temperature Solid‐State Batteries
Authors: Nguyen An‐Giang , Verma Rakesh , Song Geon‐Chang , Kim Jaekook , Park Chan‐Jin
Published: May 2023

Solid‐state batteries (SSBs) are ideal candidates for next‐generation high‐energy‐density batteries in the Battery of Things era. Unfortunately, SSB application is limited by their poor ionic conductivity and electrode‐electrolyte interfacial compatibility. Herein, in situ composite solid electrolytes (CSEs) are fabricated by infusing vinyl ethylene carbonate monomer into a 3D ceramic framework to address these challenges. The unique and integrated structure of CSEs generates inorganic, polymer, and continuous inorganic–polymer interphase pathways that accelerate ion transportation, as revealed by solid‐state nuclear magnetic resonance (SSNMR) analysis. In addition, the mechanism and activation energy of Li+ transportation are studied and visualized by performing density functional theory calculations. Furthermore, the monomer solution can penetrate and polymerize in situ to form an excellent ionic conductor network inside the cathode structure. This concept is successfully applied to both solid‐state lithium and sodium batteries. The Li|CSE|LiNi0.8Co0.1Mn0.1O2 cell fabricated herein delivers a specific discharge capacity of 118.8 mAh g−1 after 230 cycles at 0.5 C and 30 °C. Meanwhile, the Na|CSE|Na3Mg0.05V1.95(PO4)3@C cell fabricated herein maintains its cycling stability over 3000 cycles at 2 C and 30 °C with zero‐fading. The proposed integrated strategy provides a new perspective for designing fast ionic conductor electrolytes to boost high‐energy solid‐state batteries.