bluuebunny/crossref_metadata_2025 huggingface dataset:
Single intranasal immunization with attenuated Wuhan-like SARS-CoV-2 provides highly effective cross-protection against Delta and Omicron variants of concern
Authors: Faizuloev Evgeny B. , Gracheva Anastasiia V. , Korchevaya Ekaterina R. , Ammour Yulia I. , Smirnova Daria I. , Khokhlova Darya M. , Drokov Andrey O. , Pankratov Andrey A. , Trunova Galina V. , Khokhlova Varvara A. , Vorontsova Maria S. , Leneva Irina A. , Svitich Oksana A. , Zverev Vitaly V.
Published: March 2024

Introduction. Despite the end of the COVID-19 pandemic, the problem of vaccine prevention of this disease appears highly relevant. The emergence and widespread distribution of the Omicron SARS-CoV-2 variant of concern (VOC) and its sublineages has dramatically reduced the efficacy of vaccination. The possible approach to solving this problem is to develop a nasal live attenuated vaccine capable of activating humoral, mucosal, and cell-mediated immunity, providing a prolonged immune response and cross-protection against different VOCs.
The aim of the study was to determine the immunization efficacy with attenuated cold-adapted Wuhan-like SARS-CoV-2 D-D2 strain against homologous and heterologous challenges.
Materials and methods. The study was conducted on an animal model of coronavirus pneumonia in golden Syrian hamsters. The efficacy of immunization was assessed by comparing the dynamics of weight, viral load in organs and histopathological changes in the lungs in immunized and unimmunized animals.
Results. Single intranasal immunization of golden Syrian hamsters with D-D2 strain showed its high immunogenicity: seroconversion was evident in all immunized animals. Wuhan-like D-D2 strain provides highly effective protection of hamsters against the development of productive infection and pneumonia when challenged both with ancestral virus and heterologous strains related to Delta (AY.122) and Omicron (sublineages BA.1.1 and BA.5.2) variants.
Conclusion. SARS-CoV-2 attenuation is a promising strategy for the development of a highly effective nasal live COVID-19 vaccine.
Keratosis Follicularis Spinulosa Decalvans: Case Report
Authors: Hafsa Hamraoui , Hanane Baybaye , Zakia Douhi , Meryem Soughi , Sara Elloudi , Zahra Mernissi Fatima
Published: March 2024

Follicular spinulosic decalvans keratosis is a rare X-linked disease affecting both the skin and eyes. The aim of this report is to describe this pathology which manifests itself as progressive scarring alopecia of the scalp, with keratosis pilaris.
CONSTRUÇÃO E VALIDAÇÃO DO JOGO MEMÓRIA ANATÔMICA COMO PROPOSTA METODOLÓGICA DE ENSINO E APRENDIZAGEM NA DISCIPLINA DE ANATOMIA HUMANA
Authors: Samuel Murilo Miranda Amador  , Taísa Rodrigues dos Santos  , Ana Júlia Cunha Brito  , George Alberto da Silva Dias  , Biatriz Araújo Cardoso Dias
Published: March 2024

Introdução: A tecnologia educacional, especialmente por meio da gamificação, se destaca como uma abordagem inovadora e eficaz no ensino-aprendizagem. Ao utilizar jogos como ferramentas pedagógicas, os alunos se envolvem de forma mais ativa, promovendo a prática e consolidação do conhecimento de maneira lúdica. Objetivo: Construir e validar o Jogo Memória Anatômica como proposta metodológica de ensino e aprendizagem na disciplina de anatomia humana. Metodologia: Foi realizado um estudo exploratório-metodológico de produção e validação de tecnologia educacional. A pesquisa foi feita no período de agosto a outubro de 2023. A construção do jogo da memória dedicado ao sistema ósseo e aplicado na aula de anatomia humana dos cursos de graduação em enfermagem, odontologia, biomedicina, radiologia e educação física. Todos os 68 discentes participaram da gamificação e foram convidados a participar da validação do produto. Foi realizado a validação semântica com 26 questões específicas, quanto a objetivos, organização, estilo da escrita, aparência e motivação. E adotou-se Indice de Validação Semântica maior que 0,80. Resultados: O Índice de Validação Semântica (IVS) total de 0,87, superando o mínimo recomendado de 0,70. Ao analisar por item, verificou-se que o item objetivo atingiu um IVS de 0,88, para o item organização foi de 0,87, para o item estilo de escrita foi de 0,88, para o item aparência foi de 0,88 e para motivação foi de 0,86. Conclusão: O desenvolvimento do jogo “Memória Anatômica” representa um avanço significativo no ensino de anatomia, oferecendo uma abordagem interativa e envolvente para a compreensão e retenção de conceitos anatômicos. Sua implementação prática demonstrou consistentes melhorias no desempenho dos alunos, evidenciando sua eficácia como ferramenta pedagógica facilitadora. A natureza lúdica do jogo promove uma prática repetida e consolidação do conhecimento, enquanto a interatividade permite uma aplicação prática dos conceitos, resultando em uma compreensão mais profunda e duradoura. Esses resultados positivos incentivam a busca contínua por métodos pedagógicos que maximizem o potencial de cada aluno.
Recycling HPLC for the Isolation of Styryl Lactone from Goniothalamus lanceolatus Miq
Authors: Yaakop Seri Arisha , Bihud Nur Vicky
Published: March 2024

A unique plant from the rainforest of Sarawak, Malaysia, Goniothalamus lanceolatus Miq., was chosen for a phytochemical study based on its ethnomedicinal characteristics amongst the locals. Isolation and purification of a minor compound exhibiting similar retention characteristics was made possible by using preparative Recycling HPLC. Due to a recycle valve in the HPLC system, this method enables the unresolved peaks to recirculate into the column repeatedly until the peaks were successfully separated as pure entity. During the recycling process, solvent consumption is not needed. Recycling HPLC expediates the isolation and purification of complex mixtures in such a sustainable way. One styryl lactone was successfully isolated and identified as 6S,7S,8S-(-)-goniodiol.
Assessing the Impact of Organizational Climate, Human Resources Quality, Work Ethos, and Job Satisfaction on Employee Performance
Authors: Kinasih Wiwit
Published: March 2024

The company has human resources that have a high level of competence, so several problems within the company must be prevented and resolved by the company, one of which is the performance of employees within the company. With this research it is intended to obtain or collect data and then process it into information about the influence of organizational climate, quality of human resources, work ethic, and job satisfaction on employee performance. To answer the following objectives, a quantitative scientific method is needed, with a sample of 95 employees. The data analysis method used in conducting this research is instrument test, classical assumption test and linear regression analysis. So the results obtained in this study are that there is a significant influence of organizational climate, quality of human resources, work ethic, and job satisfaction simultaneously on employee performance.
An Extension Proof of Riemann Hypothesis by a Logical Entails Truth Table
Authors: Lam Kai Shun
Published: March 2024

There were many mathematicians who tried to prove or disprove the statement of Riemann Hypothe-sis. However, none of them have been successfully approved by the Clay Mathematical Institute. In addition, to the best of this author’s knowledge, these mathematicians haven’t employed the technique of logical truth table during their proofs. With reference to this author’s previous proof in [1], this author have employed the method of multiplicative telescope together with the prime boundary gaps. In this extended version of my proof to the Riemann Hypothesis, this author tries to show that RH statement is true through the four cases of the conditional statements in the truth table. Three of the cases (I, II, IV) are found to be true for the conditional statement in the Riemann Hypothesis while only one (case III) is found to be false (and acts as the disproof by a counter-example). Moreover, there are also three sub-cases (i, ii, iii) [1] among these four tabled cases. The main idea is that the we may disproof the hypothesis statement that is similar to the RH one by first find a counter-example which is obviously a disproof (case III) to the (Riemann) hypothesis. But it is NOT compatible with the GÖdel’s Incompleteness Theorem. Otherwise either the disproof to the statement or the Gödel is incorrect which is impossible. Hence, the disproof is said to be incompatible with the Gödel. On the other hand, all of the other truth cases (I, II, IV) for the statement are indeed the examples for the pos-itive results to the Riemann Hypothesis statement and are compatible with the Gödel. Therefore, the only way to make a conclusion is to say or force the Riemann Hypothesis statement to be correct.In general, for any hypothesis with the conditional statements structure like the Riemann one, we may also prove them by the similar techniqe and the arguments of the truth table for their conditional statements together with the Gödel’s Incompleteness theorem to force the positive result for the hy-pothesis statement. Actually, there are many applications for the truth tables especially in the fields like language (structure & modeling) or in engineering (logic gates & programming) etc during our everyday usage.
Farklı sulama ve azotlu gübreleme koşulları altında yetiştirilen patates yumrusunun depolama sırasında protein içeriği değişimi
Authors: Akkamış Mustafa , Çalışkan Sevgi
Published: March 2024

Su ve azotun kontrolsüz kullanımı hem üretim maliyetlerinin artmasına hem de su kaynaklarının tüketilmesine neden olmaktadır. Ayrıca su ve azotun etkili kullanımı depo dayanımı ve kalitesini de artırır. Bu çalışmanın amacı; farklı sulama ve azotlu gübre miktarlarının depolama süresince patates yumrusunun protein içeriğine etkisini araştırmaktır. Çalışma Niğde Ömer Halisdemir Üniversitesi Tarım Bilimleri ve Teknolojileri Fakültesi araştırma arazisinde altı farklı azot dozu (N0= 0 kg/da, N1= 10 kg/da, N2= 20 kg/da, N3= 30 kg/da, N4= 40 kg/da, N5= 50 kg/da) ana parsellere ve üç farklı sulama uygulaması (I1= Tam sulamanın % 66 azaltılmasıyla yapılan sulama, I2= Tam sulamanın % 33 azaltılmasıyla yapılan sulama, I3= Tam sulama= Tarla kapasitesi % 30 azaldığında sulama yapılan uygulama) alt parsellere gelecek şekilde tesadüf bloklarında bölünmüş parseller deneme desenine göre kurulmuştur. Sonuçlara göre azot miktarının artmasıyla yumrudaki protein içeriği artış göstermiştir. Bununla beraber sulama miktarının artması protein içeriğinde azalmaya neden olmuştur. Diğer yandan, depolama süresi arttıkça protein içeriği artış göstermiştir. Niğde bölgesinde Agria patates çeşidi özelinde yapılan bu çalışmada su, gübre yönetimi ve depolama süresinin patateste yumru proteini açısından büyük önem taşıdığı sonucuna varılmıştır.
Determination of genetic diversity of edible-seeded watermelon genotypes using SRAP markers
Authors: Coşkun Ömer Faruk , Toprak Seher , Mavi Kazım
Published: March 2024

The watermelon (Citrullus lanatus L.) is one of the most commonly grown and consumed vegetables in the world. Some genotypes of watermelon, which have significant variations, have a snack potential due to their seed characteristics. In this study, SRAP (Sequence Related Amplified Polymorphism) marker technique was used to determine the genetic relationship between some edible-seeded watermelon genotypes. A total of 166 bands were obtained in 24 genotypes and the polymorphism rate was calculated as 97.4%. Four main clusters were observed in the cluster analysis. It was determined that genotypes 2 and 7 clustered separately from the others. Structure analysis revealed that the genotypes consisted of two subpopulations. It was concluded that the edible-seeded watermelon genotypes can be genetically differentiated by the SRAP techniques. The results of this study can be used in breeding strategies for the improvement of the edible-seeded watermelon cultivars.
Isolation and identification of Podospora flexuosa (syn. Cladorrhinum flexuosum), a potential biocontrol agent detected in sugar beet cultivation areas in Türkiye
Authors: Avan Meltem , Kaya Rıza
Published: March 2024

Sugar beet (Beta vulgaris L.) is widely cultivated in Konya province of Türkiye and about one third of Türkiye’s sugar beet production is obtained from this province. As a result of the isolations made from plants showing severe root rot and desiccation symptoms in sugar beet fields in the region in 2015-2017, a new endophytic fungal isolate was obtained from leaves along with soil and foliar disease agents belonging to different fungal species. The fungal isolate has dull yellow, light olive to light brown, fast growing colony-like, flexible conidiophores and septate branched hyphae. The representative fungal isolate did not cause disease symptoms on host plant leaves. Molecular identification of the fungal isolate was carried out using primers specific to the ITS gene region, and it was identified as Podospora flexuosa (syn. Cladorrhinum flexuosum) based on morphological and molecular characteristics. Since P. flexuosa is reported to be a biological control agent living as a saprophyte in soil and plant materials, it is thought that the fungal isolate obtained in our study can be used as a potential biocontrol agent in the biological control of plant disease agents in the future. To the best of our knowledge, this fungal species is reported for the first time for Türkiye.
Complexité des objectifs et rémunération des vendeurs
Authors: Mongrolle Eric
Published: March 2024

La rémunération des vendeurs et de leur encadrement a, depuis toujours, été considérée comme un élément délicat de l’activité commerciale et donc controversé. Cet article montre l’évolution des systèmes de rémunération face à la complexité croissante et à la multiplication des objectifs quantitatifs et qualitatifs donnés à la force de vente .
La méthode Delphi
Authors: Vernette Éric
Published: March 2024

La méthode est issue des travaux de la Rand Corporation (2) et a vu le jour aux Etats-Unis au début des années 1960. Elle a eu très vite un succès considérable auprès de managers parce qu’elle offrait une démarche simple et structurée permettant la prévision d’évènements à un horizon de 5 à 10 ans. Fortement popularisée par plus de 500 publications, ses applications ont touché des disciplines aussi variées que les sciences physiques, l’économie, la sociologie,… le marketing. Pas toujours utilisée de manière sérieuse, la méthode Delphi a donné lieu à quelques désillusions. Pourtant cette technique constitue un instrument précieux pour la prévision marketing, à condition de respecter quelques principes de base présentés dans le premier encadré.
L’analyse de la contribution des éléments du service à la satisfaction : un modèle tétraclasse
Authors: Llosa Sylvie
Published: March 2024

L’objectif de cet article est d’étudier la manière dont se construit la satisfaction d’un client d’une entreprise de service. Plus précisément, on souhaite constater et vérifier que tous les éléments d’une expérience de service ne contribuent pas à la satisfaction globale du client en suivant la même logique. Un modèle intégrant deux logiques principales de contribution est proposé : le poids de certains éléments dans la satisfaction globale du client est fluctuant et dépend du niveau de performance perçu par le client de ces éléments; d’autres éléments contribuent à la satisfaction du client de façon stable, quelle que soit l’évaluation qui en est faite. Cet article définit rapidement le cadre conceptuel servant d’ancrage au modèle de contribution proposé. Ces propos sont illustrés par une application réalisée dans le domaine bancaire, la souscription d’un crédit automobile. En conclusion, les implications managériales de cette recherche sont discutées.
Vers des procès pour contrefaçon de magasins spécialisés ?
Authors: Nabec Lydiane , Hyvernat Claire , Rieunier Sophie
Published: March 2024

La conception du magasin, de son design intérieur et de son atmosphère, font aujourd’hui l’objet de lourds investissements intellectuels et financiers de la part des distributeurs qui cherchent par ce biais à se positionner sur le marché et à se différencier de leurs concurrents. Pourtant, certains magasins se contentent d’imiter leurs concurrents plutôt que d’innover, portant ainsi préjudice à l’enseigne copiée. Comment protéger un magasin de la copie question Quels sont les recours juridiques pour les magasins victimes d’imitations ? Cet article, au travers du rappel de la législation en vigueur et de l’analyse de six procès ayant opposé des magasins sur le motif d’imitation de magasins, apporte des éléments de réponse à ces questions.
Le pilotage des forces de vente
Authors: Rouziès Dominique , Besson Madeleine
Published: March 2024

L’objectif de cette première étude consiste à étudier le comportement des vendeurs à la lumière du mode de pilotage adopté par leur entreprise. Plus précisément, le but de cet article est de confirmer la diversité de ces modes de pilotage et d’identifier les dysfonctionnements issus de leurs incohérences. L’analyse d’une série d’entretiens approfondis avec directeurs commerciaux et vendeurs permet d’avancer de nouvelles propositions susceptibles d’améliorer les performances commerciales. Finalement, les implications managériales sont détaillées.
Mesurer l’efficacité des cartes de fidélité
Authors: Benavent Christophe , Crié Dominique
Published: March 2024

Cet article propose une méthode de mesure de l’efficacité d’un programme de diffusion d’une carte de fidélité. Il discute également des conditions d’application de ces programmes notamment en terme de segmentation. Il s’appuie sur une analyse de panel effectuée sur le cas d’une enseigne de distribution spécialisée et d’une vingtaine de points de vente .
Vers une 4 ème génération : les études de marché « on-line »
Authors: Galan Jean-Philippe , Vernette Éric
Published: March 2024

Après les études manuelles, informatisées, automatisées, l’Internet offre la possibilité d’un nouveau saut technologique pour le recueil et le traitement des données nécessaires à la réalisation d’une étude de marché. Cet article présente et évalue les différentes techniques quantitatives et qualitatives disponibles pour conduire ce nouveau type d’étude on-line .
De l’utilité des sigles pour la dénomination sociale
Authors: Delattre Eric
Published: March 2024

Les nombreux changements de dénomination sociale de ces dernières années semblent remettre en cause l’utilité des sigles, pour des raisons d’internationalisation et de visibilité commerciale. Or, le choix d’un sigle en tant que nom d’entreprise, mais aussi nom de produit, présente encore un réel intérêt. Dans cette optique, les objectifs de notre étude sont les suivants : – exposer la diversité des marques-sigles au sens large du terme et en proposer une typologie ; – expliquer les avantages spécifiques des sigles ; – analyser l’évolution des sigles, notamment au travers des récents changements de nom d’entreprise .
Vers un modèle d’opérationalité des études Usages & Attitudes
Authors: Salles Jean-Christophe , Zeitoun Helen
Published: March 2024

Les études Usages & Attitudes ne peuvent se contenter de décrire un marché, elles doivent être un outil d’aide à la décision. Dans ce sens nous proposons une méthodologie spécifique qui à travers la proposition d’un schéma théorique permet d’appréhender la diversité des problématiques liées aux études Usages & Attitudes, et ce sous un angle “ pour action ” . Dès lors, il s’agit de donner une valeur explicative à l’approche traditionnelle descriptive : non seulement déterminer les facteurs clés qui sous tendent la démarche d’achat (Quoi faire ?), mais aussi mettre en évidence des opportunités pour l’entreprise (Comment faire ?) auprès de cibles de clientèles opérationnelles (Auprès de qui ?)
Des concessions automobiles en quête d’une stratégie marketing
Authors: Donada Carole , Vidal Olivier
Published: March 2024

La distribution d’automobiles neuves en Europe est régie par un règlement d’exemption aux règles de la concurrence qui protège les concessionnaires . Ce règlement arrive à échéance et sa reconduction est âprement souhaitée par les concessionnaires qui risquent de perdre leur position d’acteurs incontournables du marché. Cette menace est amplifiée par l’arrivée de nouveaux entrants (grande distribution et acteurs du e-business) qui affinent leur stratégie marketing avant de pénétrer en force le marché . Dans ce contexte, les concessionnaires doivent repenser leur métier de distributeurs automobiles pour transformer les menaces en opportunités .
Les acheteurs impulsifs : proposition d’une typologie
Authors: Giraud Magali
Published: March 2024

L’acheteur impulsif a longtemps été considéré comme un consommateur irrationnel répondant de manière incontrôlée et irréfléchie aux tentations d’achat qui s’offrent à lui en magasin. Cet article tend à montrer que le mode d’achat impulsif n’est pas toujours irrationnel et qu’il existe une forme d’impulsivité fonctionnelle dans l’achat qui explique que les achats faits sur une impulsion puissent se révéler des choix de qualité et même parfois des choix optimums pour le consommateur. L’objectif de cet article est de proposer une typologie des acheteurs de 20 à 30 ans en fonction de la nature de leur impulsivité dans l’achat .
Le marketing écartelé entre le client, le gestionnaire et l’actionnaire
Authors: Ollivier Alain
Published: March 2024

Encore une fois, j’aimerais rappeler ici que cette rubrique est ouverte à tous . Elle a pour but de susciter la réflexion sur la pratique du marketing. Si vous avez des idées personnelles à exprimer, n’hésitez pas à me faire parvenir, si possible par e-mail, une proposition de sujet. Je vous répondrai le plus vite possible .
Les mondes authentiques et les stratégies d’authentification
Authors: Camus Sandra
Published: March 2024

A travers leur politique de communication, les distributeurs affichent clairement leur soucis de transparence, de sincérité et d’honnêteté. La crise de la vache folle, par exemple, a conduit les consommateurs à revendiquer des produits d’origine, correspondant à leur désignation, et non dénaturés. D’où la mise en exergue implicite d’une authenticité au sein du monde marchand. Pénalisés par la difficulté de rationaliser directement le processus d’authentification, les industriels se contentent généralement d’une opérationnalisation intuitive et commode. D’où l’urgence, nous semble t’il, de poser les principes clés qui définissent les mondes authentiques et qui régissent les stratégies d’authentification .
Le placement des bannières publicitaires sur le web
Authors: Galan Jean-Philippe , Fontaine Isabelle
Published: March 2024

Cet article a pour objectif de mieux comprendre l’intérêt et le fonctionnement des bannières publicitaires sur Internet. Quelle est l’efficacité des bannières ? Les mesures actuellement utilisées sont-elles réellement les plus adéquates ? Le fonctionnement de la bannière est lié à la compréhension de certaines variables : il s’agit des dimensions de la bannière, de son placement sur le site et de variables individuelles. Après avoir rappelé les outils de mesure existants et discuté de leur efficacité, une analogie avec le placement de produits est proposée afin d’établir une typologie des bannières. Celle-ci, qui s’appuie notamment sur les concepts d’intégration et de proéminence, permet de proposer nouvelles mesures d’efficacité .
Le “ Online ” bat le “ Offline ”
Authors: Dussart Christian
Published: March 2024

Cette rubrique a pour but de susciter la réflexion sur la pratique du marketing. Si vous avez des idées personnelles à exprimer, n’hésitez pas à me faire parvenir, si possible par e-mail, une proposition de sujet. Je vous répondrai le plus vite possible .
YIELD MANAGEMENT et marketing des services
Authors: Dubois Pierre-Louis , Frendo Marie-Christine
Published: March 2024

Le yield management est an système d‘optimisation du rendement qui connaît un fort développement en Europe. Les auteurs proposent une définition et indiquent les caractéristiques communes aux situations auxquelles il s’applique. Deux aspects marketing sont étudiés : le caractère aléatoire du déplacement de la demande et l’impact du système sur la qualité du service. La conclusion met l’accent sur les enjeux stratégiques que représentent le développement et la maîtrise du yield management pour les entreprises de service. L’article s’appuie sur les témoignages de plusieurs yield managers.
Télé-achat
Authors: Paché Gilles , Pontier Suzanne
Published: March 2024

Home Shopping Service (HSS) est le producteur de M6 Boutique. Son directeur Général, Roland Kruger, explique à Gilles Paché et Suzanne Pontier sa stratégie compte-tenu de la concurrence, et sa perception de l’avenir du téléachat
Le data-mining et alternative modèles classiques /réseaux neuronaux
Authors: Ainslie Andrew , Drèze Xavier
Published: March 2024

L’extraction de données (“Data-Mining”, littéralement “Forage de Données”) est une nouvelle façon de tirer des informations de grosses bases de données qui gagne actuellement la faveur de grandes entreprises. Après avoir décrit le processus d’extraction de données, les auteurs proposent une méthodologie permettant de combiner les techniques d’extraction de données et l’analyse plus traditionnelle de régression, afin de parvenir à une meilleure compréhension des informations contenues dans une base de données d’entreprise. Deux exemples, l’un tiré de l’industrie automobile et l’autre de l’industrie télévisuelle, viennent illustrer ces concepts.
Sondages automatisés par téléphone : La troisième génération de collecte des données
Authors: Delacotte Olivier , Vernette Éric
Published: March 2024

Après une brève revue des différentes méthodes d’interviews téléphoniques, l’article expose les caractéristiques, les avantages et les limites d’un nouveau type de sondage téléphonique automatisé.
Innovation et partenariat: Facteurs clés de succès
Authors: Perraud Éric , Xuereb Jean-Marc
Published: March 2024

Les partenariats sont un des moyens les plus utilisés pour répondre au rythme croissant d’obsolescence technologique (4) (5). Néanmoins bien que leur nombre augmente, les partenariats entre entreprises sont notoirement instables, connaissent peu de succès et sont difficiles à gérer (6). Cet article montre qu’un partenariat entre une PME et une grande entreprise présente de fortes chances de succès. Dans un tel cas, la grande entreprise apporte ses différentes ressources, et des facilités d’accès tant à des sites de production qu’à des réseaux de distribution. La PME apporte des connaissances spécifiques, une proximité avec le marché et les consommateurs potentiels et une volonté d’atteindre les objectifs du partenariat. Dans un partenariat entre grandes entreprises, l’existence de différences stratégiques, organisationnelles, managériales et culturelles entre les firmes partenaires réduit fortement les avantages attendus d’un développement commun.
Les stratégies du distributeur
Authors: Lhermie Christian
Published: March 2024

Assez peu abordée par la communauté scientifique, la stratégie des distributeurs et particulièrement des distributeurs de grande consommation, commence à fournir un large champ de réflexion et de recherche. La réussite exemplaire de certains groupes, notamment français, y est pour beaucoup. A partir d’exemples, cet article propose un panorama des stratégies adoptées dans ce domaine. En somme, une petite révision des termes et concepts de stratégie.
Le commerce électronique
Authors: Misse Brigitte
Published: March 2024

Aujourd’hui, avec le développement d’Internet et de l’EDI, le commerce électronique devient une réalité. Deux traits essentiels le caractérisent, à savoir le caractère national ou international des transactions et l’offre à distance. De ces deux caractéristiques découle une réglementation spécifique : les commerçants électroniques vont devoir s’adapter aux règles particulières des pays où ils vont choisir de mener leurs transactions. D’ores et déjà, en France, existe une réglementation pour toutes les transactions à distance qui s’appliquera notamment aux consommateurs et toute une jurisprudence encadrant cette activité.
Effective vague soft environment-based decision-making
Authors: Sakr Hanan H. , Alanazi Bader S.
Published: March 2024

The soft idea has a crucial impact on facing uncertainty, but extending soft, fuzzy soft, and vague soft settings is more comprehensive in expressing the problem ambiguity parameters than the soft set. Despite this advancement, the vague soft set falls short in addressing certain decision-making issues. This occurs when we have some external factors that can impact our final decision. These external factors can be represented in the effective parameter set. So, the objective of the current article is to incorporate the new concept of effectiveness into the concept of vague sets. This approach leads the researchers to create a novel and expanded framework for effective decision-making, surpassing any previously introduced methods in applicability. The article also provides an exploration of the types, concepts, and operations of effective vague soft sets, each illustrated with examples. Furthermore, the study delves into the examination of properties like De Morgan's laws, distributive, commutative, absorption, and associative properties for those new sets. Moreover, the framework of effective vague soft sets is used to develop a decision-making methodology. This technique simplifies the process of determining whether a student meets the requirements for a particular level of education or if a patient has a specific disease, among other applications. Additionally, to clarify the proposed algorithm, a detailed case study representing how to classify students toward specializations is examined in detail. Using matrix processes in this example, in addition to $ Wolfram \; Mathematica^{\circledR} $, not only renders computations simpler and quicker but also results in more precise optimum effective decisions. In the end, a detailed comparison with existing techniques is performed and summed up in a chart to illustrate the difference between them and the present one.
Zemljepisna imena Slovenskega Porabja
Authors: Geršič Matjaž , Kumin Horvat Mojca , Logar Erik , Perko Drago , Pipan Primož
Published: March 2024

Geographical names are an important part of the cultural heritage of every nation. They are a fundamental building block of all civilizations or cultures, filling space with meaning and developing spatial identities. Geographical names in languages with few speakers, such as Slovenian, are often endangered, but this is even more true for the geographical names of ethnic minorities, including the Slovenians of Hungary, the smallest cross-border Slovenian minority. The far western edge of Hungary, which lies between Slovenia and Austria, is called the Rába Valley. It includes seven settlements in which bilingualism is officially present. An outward sign of this bilingualism is bilingual road signs with the names of settlements. The main subject of this research was microtoponyms. The result of the research, a volume with a map and a dictionary, is based on extensive fieldwork and a review of archival sources. It is hoped that the results will help preserve these microtoponyms in people’s minds. In addition to a comprehensive monograph, the map of microtoponyms in the Rába Valley was published as a result of the project.
Ethics of information and the metaverse
Authors: Haynes David
Published: March 2024

Recent promotion of use of the metaverse has raised concerns about the risks faced by users. These include fraud, identity theft, loss of privacy and online abuse. By considering the ethical issues we can begin to consider suitable avenues for regulation.
Réunir Grecs et Barbares à travers l’image
Authors: Medjkoune Inès
Published: March 2024

Alors que la littérature d’époque classique semble présenter les corps, vêtements et attitudes des Barbares sous un jour particulièrement négatif, faisant d’eux des anti-modèles, l’iconographie vasculaire permet une lecture différente qui conduit à nuancer le caractère antinomique de la corporéité de l’Autre. L’analyse de certaines séries d’images ambigües – celles de Pâris, du Grand Roi et de jeunes barbares nus – et la prise en compte de leurs effets dans leur contexte d’utilisation, le symposion, nous permettra d’envisager ces images sous le prisme de l’érotisme. Il apparait que, dans ces représentations, l’altérité attribuée à ces personnages n’est pas totalement dénuée de qualités pensées comme grecques, telles que la beauté ou l’érotique, et les parures attribuées à ces personnages tout autant que le contexte de la scène permettent d’envisager l’Autre autrement que dans sa simple différence.
Pour la mémoire de César
Authors: Nicolleau Mathias
Published: March 2024

Après les funérailles de César, déjà marquées par des débordements populaires, une foule se réunit pendant plusieurs semaines sur le Forum pour honorer le défunt et réclamer vengeance contre ses meurtriers. Il s’agit d’une des rares occurrences (à l’exception des émeutes frumentaires) où le peuple agit de manière autonome pour imposer dans l’espace public ses revendications, sans qu’il soit guidé par un magistrat : nos sources ne désignent comme meneur qu’un imposteur, le faux Marius, qui n’avait à ce titre aucune légitimité pour s’exprimer publiquement. En se réunissant pour défendre la mémoire de César, les manifestants protestaient contre la politique de conciliation d’Antoine, qui les laissait sans chef. Ils affirmaient aussi leurs identités collectives particulières, qui se cristallisaient sur la figure du défunt : grâce aux liens qu’il avait tissés avec la plèbe et les vétérans, César était devenu une figure de référence à laquelle ils pouvaient s’identifier.
METHODOLOGY FOR IMPROVING DEEP LEARNING-BASED CLASSIFICATION FOR CT SCAN COVID-19 IMAGES
Authors: Vijayalakshmi D. , Elangovan Poonguzhali , Nath Malaya Kumar
Published: March 2024

Early identification of COVID-19 necessitates a precise interpretation of computed tomography (CT) chest images. Consistent and accurate photographs are critical for the correct diagnosis. In this paper, a novel pre-processing approach (mainly improves the contrast) based on gradient enhancement method (GCE) is proposed for prominent visualization of the diagnostic features from the COVID-19 CT images. This pre-processing stage helps in preserving the diagnostic information in the disease affected area. Edge information in the CT images helps the physicians and classification model for better classification. The edge features are preserved by improving the contrast by using multi-scale dependent dark pass filter. From the edge features and pixel intensities, cumulative distribution function (CDF) is computed. It is then mapped to a uniform distribution, resulting in contrast enhanced COVID-19 CT images. These pre-processed images are fed to the customized deep convolutional neural networks (CNNs) like AlexNet, VGG-19, ResNet-101, DenseNet-201, GoogleNet, MobileNet-v2, SqueezeNet, Inception-v3, Xception, and EfficientNet-b0 for classification. Introducing GCE as a pre-processing stage improves the COVID-19 classification accuracy by nearly 6%. Evaluation of the contrast enhancement by GCE technique is carried out on the CT images by contrast improvement index (CII), discrete entropy (DE), and Kullback–Leibler distance (KL-Distance) measures. The experimental findings reveal that the GCE method produces higher CII and DE values than the other enhancement methods available.
A Secure and Fast Range Query Scheme for Encrypted Multi-Dimensional Data
Authors: Mei Zhuolin , Zou Huilai , Huang Jinzhou , Zhang Caicai , Wu Bin , Shi Jiaoli , Cheng Zhengxiang
Published: March 2024

In recent years, more and more data has been stored on the cloud to provide various services. These data often contain users' private information, which inevitably raises concerns about data security. Encryption before outsourcing is a direct solution to mitigate these concerns. However, traditional encryption schemes such as block encryption make basic data services hard to support. Therefore, this paper proposes a secure and fast range query scheme for encrypted multi-dimensional data, called SFRQ. The scheme constructs a secure index over the ciphertexts of multi-dimensional data, utilizing the R-tree index, Bloom filter, and 0-1 encoding techniques. This secure index enables the cloud to provide fast range query services over the ciphertexts of multi-dimensional data. The authors have evaluated SFRQ through extensive experiments, which demonstrate its high efficiency. Additionally, the security analysis shows that no external entity, including the cloud, can obtain additional information during the entire query process.
An Exploration of the Computer Big Data Mining Service Model Under Resource Sharing
Authors: Hu WeiWei , Sun Lina , Li Lijie
Published: March 2024

In order to meet the diverse needs of users for data mining services and improve resource utilization and enterprise competitiveness, this article aims to construct a Big Data Analytics (BDA) data mining service model based on resource sharing mechanisms. This article designs a customized data mining service model for BDA based on its characteristics. In this model, the authors apply the improved Apriori algorithm to determine the optimization plan and improve the ant colony optimization algorithm to improve the efficiency and accuracy of data mining. By analyzing the experimental results, the scientificity and rationality of the proposed data mining service model for BDA were demonstrated, and the implementation strategy of the data mining model was improved. These research findings provide important references for BDA's data mining service model based on response surface modeling and also provide guidance for enterprises on how to better utilize resources and improve competitiveness when facing big data.
Fog Cloud Computing and IoT Integration for AI enabled Autonomous Systems in Robotics
Authors: Kiran Deep Singh  , Singh Prabhdeep
Published: March 2024

Fog Cloud Computing and the Internet of Things are transforming robotics by empowering AI-enabled autonomous systems. This study analyzes the benefits, drawbacks, and uses of this integration. AI-enabled autonomous robots can use edge computing and cloud resources for real-time data processing and decision-making, improving their performance and adaptability. Communication protocols, data management, security, and scalability are examined in the ecosystem. Case studies reveal how this confluence affects robotics applications. This research shows how FCC, IoT, and AI may improve robotic systems' efficiency, intelligence, and autonomy. The article covers AI-enabled autonomous systems in transportation, manufacturing, healthcare, agriculture, and smart cities. These technologies can improve productivity and safety in many fields, from self-driving automobiles to surgical robots. Integrating these technologies raises safety, ethical decision-making, data privacy, and security concerns. The report emphasizes transparent and ethical AI algorithms, unbiased decision-making, and regulatory frameworks to enable responsible integration and mitigate dangers. In the future, AI-enabled autonomous systems will be shaped by improved AI algorithms, multi-modal sensing, human-robot collaboration, and edge intelligence. It emphasizes the necessity of interdisciplinary collaboration and ethical considerations in responsible technology development. This study concludes with a detailed analysis of fog/cloud computing, IoT, and AI in robotics, revealing the immense promise and problems of AI-enabled autonomous systems. Responsible development and collaboration can help us negotiate this transformational frontier and create a safer, more efficient, and innovative society with AI-driven autonomous systems.
Prediction of Intermittent Demand Occurrence using Machine Learning
Authors: Singh Ashish K , Simha J B , Agarwal Rashmi
Published: March 2024

Demand forecasting plays a pivotal role in modern Supply Chain Management (SCM). It is an essential part of inventory planning and management and can be challenging at times. One of the major issues being faced in demand forecasting is insufficient forecast accuracy to predict the expected demand and fluctuation in actual vs. the predicted demand results in fore-casting errors. This problem is further exaggerated with slow-moving and intermittent demand items.
Every organization encounters large proportions of items that have small ir-regular demand with long periods of zero demand, which are known as intermittent demand Items. Demand for such items occur sporadically and with considerable fluctuation in the size of the demand. Forecasting of the intermittent demand entails the prediction of demand series that is characterized by the time interval between demand being significantly greater than the unit forecast period. Because of this there are multiple periods of no demand in the intermittent demand time series. The challenge with these products with low irregular demand is that these items need to be stocked and replenished at regular interval irrespective of the demand cycle, thus adding to the cost of holding the inventory. Since the demand is not continuous, Traditional Forecasting models are unable to provide reliable estimate of required inventory level and replenishment point. Forecast errors would resulting in obsolescent stock or unfulfilled demand.
The current paper presents a simple yet powerful approach for generating a demand forecasting and replenishment process for such low volume intermittent demand items to come up with a recommendation for dynamic re-order point, thus, improving the inventory performance of these items. Currently, the demand forecast is generally based on past usage patterns. The rise of Artificial Intelligence/Machine Learning (AI/ML) has provided a strong alternative to solve the problem of forecasting Intermittent Demand. The intention is to highlight that machine learning algorithm is more efficient and accurate than traditional forecasting method. As we move forward to industry 4.0, the digital supply chain is considered as the most essential com-ponent of the value chain wherein the inventory size is controlled, and the demand predicted.
Proper Weather Forecasting Internet of Things Sensor Framework with Machine Learning
Authors: Turukmane Anil V , Pande Sagar Dhanraj
Published: March 2024

Recent times have seen a rise in the amount of focus placed on the configurations of big data and the Internet of Things (IoT). The primary focus of the researchers was the development of big data analytics solutions based on machine learning. Machine learning is becoming more prevalent in this sector because of its ability to unearth hidden traits and patterns, even within exceedingly complicated datasets. This is one reason why this is the case. For the purpose of this study, we applied our Big Data and Internet of Things (IoT)-based system to a use case that involved the processing of weather information. We put climate clustering and sensor identification algorithms into practice by using data that was available to the general public. For this particular application, the execution information was shown as follows:every single level of the construction. The training method that we've decided to use for the package is a k-means cluster that's based on Scikit-Learn. According to the results of the information analyses, our strategy has the potential to be utilized in usefully retrieving information from a database that is rather complicated.
Machine Learning Based Stroke Predictor Application
Authors: Kishore Kanna R , Rami Reddy Ch. Venkata , Panigrahi Bhawani Sankar , Behera Naliniprava , Mohanty Sarita
Published: March 2024

When blood flow to the brain stops or slows down, brain cells die because they don't get enough oxygen and nutrients. This condition is known as an ischemic stroke. It is now the biggest cause of death in the whole planet. Examining the afflicted people has shown a number of risk variables that are thought to be connected to the stroke's origin. Numerous studies have been conducted to predict the illnesses associated with stroke using these risk variables. The prompt identification of various warning symptoms associated with stroke has the potential to mitigate the severity of the stroke. The utilization of machine learning techniques yields prompt and precise predictive outcomes. Although its uses in healthcare are expanding, certain research domains have a stronger need for more study. We think that machine learning algorithms may aid in a deeper comprehension of illnesses and make an excellent healthcare partner. The textual dataset of numerous patients, which includes many medical variables, is gathered for this study. The missing values in the dataset are located and dealt with during processing. The dataset is used to train machine learning algorithms including Random Forest, Decision Tree classifier, and SVM. The method that delivers the greatest accuracy for our dataset is then selected once the accuracy of the algorithms has been determined. This aids patients in determining the likelihood of a brain stroke and ensuring they get the right medical attention.
Wavelet Transform and SVM Based Heart Disease Monitoring for Flexible Wearable Devices
Authors: Han Binbin , Zhang Fuliang , Zhao Lin
Published: March 2024

INTRODUCTION: Heart disease has been a major health challenge globally, therefore the development of reliable and real-time heart disease monitoring methods is crucial for the prevention and management of heart health. The aim of this study is to explore a flexible wearable device approach based on wavelet transform and support vector machine (SVM) to improve the accuracy and portability of heart disease monitoring. OBJECTIVES: The main objective of this study is to develop a wearable device that combines wavelet transform and SVM techniques to achieve accurate monitoring of physiological signals of heart diseases. METHODS: An integrated method for heart disease monitoring was constructed using flexible sensor technology combined with a wavelet transform and support vector machine. The Marr wavelet transform was applied to the ECG signals, and the feature vectors were constructed by feature parameter extraction. Then, the radial basis kernel SVM was utilized to identify the three ECG signals. The performance of the algorithm was optimized by adjusting the SVM parameters to improve the accurate monitoring of heart diseases. RESULTS: The experimental results show that the proposed wavelet transform and SVM-based approach for flexible wearable devices achieves satisfactory results in heart disease monitoring. In particular, the algorithm successfully extracted feature vectors and accurately classified different ECG signals by skillfully combining the wavelet transform and SVM techniques for the processing of premature beat signals. CONCLUSION: The potential application value of the wavelet transform and SVM-based flexible wearable device approach in heart disease monitoring is emphasized. By efficiently processing ECG signals, the method provides an innovative and comfortable solution for real-time monitoring of cardiac diseases.
Rainfall Prediction using XGB Model with the Australian Dataset
Authors: Vinta Surendra Reddy , Peeriga Rashika
Published: March 2024

Rainfall prediction is a critical field of study with several practical uses, including agriculture, water management, and disaster preparedness. In this work, we examine the performance of several machine learning models in forecasting rainfall using a dataset of Australian rainfall observations from Kaggle. Six models are compared: random forest (RF), logistic regression (LogReg), Gaussian Naive Bayes (GNB), k-nearest neighbours (kNN), support vector classifier (SVC), and XGBoost (XGB). Missing value imputation and feature selection were used to preprocess the dataset. To analyse the models, we employed cross-validation and performance indicators such as accuracy, precision, recall, and F1-score. According to our findings, the RF and XGB models fared the best, with accuracy ratings of 87% and 85%, respectively.
With accuracy ratings below 70%, the GNB and SVC models performed the poorest. Our findings imply that machine learning algorithms can be useful tools for predicting rainfall, but careful model selection and evaluation are required for reliable results.