bluuebunny/crossref_metadata_2025 huggingface dataset:
La population française devrait continuer de vieillir d’ici un demi-siècle
Authors: Toulemon Laurent , Algava Élisabeth , Blanpain Nathalie , Pison Gilles
Published: February 2022

Selon les projections de l’Insee publiées en 2021, la France comptera entre 58 et 79 millions d’habitants en 2070. Le scénario central conduit à une population de 68 millions d’habitants. Il annonce une population plus vieille qu’aujourd’hui, et en légère diminution à partir de 2044 alors que les projections précédentes tablaient sur un maintien de la croissance. L’excédent des décès sur les naissances ne serait en effet plus compensé par un solde migratoire positif. L’écart avec le chiffre annoncé pour 2070 par les projections précédentes (publiées en 2016), 76 millions, est important. Il vient de la révision à la baisse à la fois de l’effectif de la population de 2021 et des hypothèses de fécondité, d’espérance de vie et de migrations.
Attente et attention : de saint Augustin au bébé d’aujourd’hui
Authors: Golse Bernard
Published: February 2022

Après avoir rappelé les positions de saint Augustin quant au concept d’attente, l’article rappelle la distinction proposée par Didier Anzieu entre l’attente et l’attention. Après quoi attente et attention sont mises en perspective avec le fonctionnement du bébé susceptible d’inspirer la méthodologie de nos pretocoles de recherche le concernant.
L’attention portée au mouvement in utero : des chorégraphies plurielles
Authors: Laera Angela , Missonnier Sylvain
Published: February 2022

Le mouvement de l’embryon puis du fœtus constitue pour les professionnels de l’échographie obstétricale une cible sémiologique essentielle, à laquelle ils accordent une grande attention. Simultanément, c’est fréquemment pour les devenant parents un jaillissement visuel décisif dans le processus de parentalisation. La motricité fœtale et les pulsations cardiaques y sont interprétées comme la première signature de la vie de l’être conçu, avant toute proprioception maternelle et exteroception conjugale. Cette authentification médicale et parentale de l’immersion de l’enfant virtuel dans la rivière du mouvement ouvre sur les possibles de son épigenèse ontologique, dont la mort (l’absence de mouvement) constitue désormais l’ombre indissociable. La clinique des consultations parents-fœtus/bébé illustre bien l’amplitude des variations de cette chorégraphie périnatale entre Éros et Thanatos. Dans cet article nous illustrons notre propos grâce à plusieurs consultations, qui vont de situations « paranormales » à des situations plus psychopathologiques, en déclinant l’ attention portée aux mouvements fœtaux.
Prêter attention à la dimension culturelle en période périnatale pour mieux accompagner les parents et leurs bébés
Authors: Radjack Rahmethnissah , Guessoum Selim Benjamin , Ogrizek Anaïs , Moro Marie Rose
Published: February 2022

L’impact de la culture est utile à prendre en compte pour optimiser l’accompagnement des soignants en période périnatale. En effet, les femmes enceintes migrantes primo-arrivantes sont sujettes à une vulnérabilité psychique liée à leur isolement et à la confrontation à d’autres manières de s’occuper des bébés. L’objectif de cet article est de transmettre des compétences transculturelles utiles pour tout soignant accompagnant une famille en période périnatale, en mettant en lumière les aspects culturels auxquels prêter attention dans la représentation d’une grossesse, les besoins d’un enfant, les complications obstétricales ou les problématiques postnatales.
Les enjeux subjectifs d’une compétence professionnelle
Authors: Tissot Pascaline
Published: February 2022

À partir d’entretiens menés auprès d’enseignants stagiaires, ce texte interroge la façon dont les professeurs des écoles traduisent, dans leurs pratiques, la compétence six du référentiel de compétence des métiers du professorat et de l’éducation « Agir en éducateur responsable et selon des principes éthiques ». Ces entretiens sont mis en perspective avec quelques éléments de discussion situant les questions éthiques liées à la responsabilité éducative dans deux déclinaisons de l’acte de répondre : répondre de soi et répondre à l’autre. Dans une approche référée à la psychanalyse, toutefois articulée à la philosophie, cet article tend à montrer qu’au-delà d’une compétence complexe à évaluer, la position éthique se déploie dans un processus de subjectivation mettant en jeu la relation à l’autre.
Substrate composition effect on growth ofCotinis mutabilis (Scarabaeidae) larvae: a case for detritivore scarabs in the insect agriculture industry
Authors: Slagle M.L. , Davidowitz G.
Published: February 2022

Insect farming has potential to help alleviate food insecurities, which are increasing globally. Insect farming can also help reduce landfill loading with food loss and waste, which is nearly 33% of all food produced globally. Farming of detritivore insect species, those that can consume decaying organic material including manures, increases the economic and environmental sustainability of the insect agriculture industry. The green fig beetle (Cotinis mutabilis, Scarabaeidae) is a native to the Sonoran Desert in the United States and Mexico. This study explored the effects of ten organic waste diets differing in the ratios of four waste types, dairy cow manure, mushroom spent substrate, spent brewer’s grain, and leaves, on the growth and survivorship of the larvae. Results show that this species yielded highest grub peak weights when fed a diet containing spent beer grains. However, these grubs also had low survivorship. Highest food efficiency conversions were found in grubs that were fed a diet dominated by spent mushroom media. Manure-based compost yielded poor growth and survivorship in these grubs, despite observations of wild beetles laying eggs in compost. A correlation between diet density and peak weight of the grubs suggests that a low-density diet is a more suitable substrate. Scarabs are found world wide and can become an important component in the insect as food and feed industry.
Aflatoxin B1 in the egg chain: monitoring with specific indirect competitive ELISA in northern Paraná, Brazil
Authors: Silva F.G. , Zanin L.M.M. , Shimizu C.F. , Lopes D.D. , Ribeiro J.C. , Ishikawa A.T. , Itano E.N. , Kawamura O. , Hirooka E.Y.
Published: February 2022

An indirect competitive immunoassay (ic-ELISA) was developed using monoclonal antibody produced by hybridoma AF4, which showed high specificity and reactivity with aflatoxin B1 (AFB1) and aflatoxicol, but low cross-reactivity to other analogs. This low cost reliable method was applied for AFB1 monitoring in the poultry chain of a high agribusiness potential region (northern Paraná state, Brazil). Maize, laying hens feed and egg samples were collected from two poultry farms (with production above 200,000 eggs/day) and evaluated by intralaboratory validated ic-ELISA. The sensitivity of such a validated assay, detecting picogram levels of aflatoxins, demonstrated to be proper for surveying daily ingested cumulative toxins and estimating risks. Additionally, more than 61.00% of positive egg samples ranged between the limit of quantification (LOQ – 0.035 ng/g) and 1.00 ng/g, values commonly not covered by commercial kits. Positive data (>LOQ) occurred in 22 maize (56.40%), 34 feed (85.00%) and 192 (48.00%) egg samples. Mean contamination in maize was 1.51±0.94 ng/g (range 0.11-3.91 ng/g), 1.26±0.96 ng/g in feed (0.10-3.58 ng/g), and 1.01±0.77 ng/g in egg (0.05-3.85 ng/g). No statistical difference was observed between farms (P>0.05) for any of the matrices analysed. However, the difference between median values in maize (0.98 ng/g – Farm A; 1.76 ng/g – Farm B) indicated a higher contamination trend in farm B, possibly due to inadequate local storage. Although there is no limit stipulated for AFB1 contamination in eggs, the levels detected in samples were low and do not represent an immediate risk to animal production or human consumption. Nevertheless, the high frequency of positive maize and feed samples in this field of agribusiness should be highlighted. Sensitive aflatoxin monitoring procedures must be strategically carried out from raw materials to animal derived products, aiming harmless production, which also assures human health.
Assessing the Efficacy of Four Diagnostic Devices and Four Nomograms in Posterior Chamber Phakic Intraocular Lens Size Selection
Authors: Moshirfar Majid , Placide John , Neves da Silva Helio V. , Durnford Kathryn M. , Ronquillo Yasmyne C. , McCabe Shannon E. , Hoopes Phillip C.
Published: February 2022

PURPOSE:

To assess the efficacy of different devices and nomograms in predicting the most optimal Implantable Collamer Lens (ICL) (STAAR Surgical) size.

METHODS:

This retrospective study includes 73 patients (142 eyes) who underwent ICL placement surgery. Anterior segment measurements were obtained by the OPD-Scan III (Marco), the Lenstar LS 900 (Haag-Streit AG/Alcon Laboratories, Inc), the Galilei G4 (Ziemer), and the VuMax ultrasound biomicroscopy device (UBM) (Sonomed Escalon). The efficacy of the four devices and four nomograms was assessed by comparing the indicated ICL sizes to the patient's postoperative vault measurements.

RESULTS:

Using white-to-white (WTW) measurements obtained by the Lenstar LS 900 and Galilei G4 coupled with the U.S. Food and Drug Administration's (FDA) (also called the manufacturer's) nomogram predicted the highest percentage (33% and 43%) of the 13.7 mm ICL sizes, respectively. Using the VuMax UBM coupled with the Dougherty nomogram indicated the highest percentage (80%) of the 12.6 mm ICL size. The ICL sizes predicted by UBM using the Parkhurst nomogram were comparable to those deemed ideal according to postoperative vault measurements.

CONCLUSIONS:

The Parkhurst nomogram predicted the most appropriate ICL size. When using WTW measurements, the optimized WTW nomogram showed promising results, especially in eyes whose preoperative calculations suggest low postoperative vaults. Moreover, clinicians should use caution when using the FDA nomogram because it showed a propensity toward indicating oversized ICLs.

[
J Refract Surg
. 2022;38(2):106–111.]
Increased Rate of Infectious Keratitis After PRK in the COVID-19 Era: The Possible Role of Face Masks
Authors: Soleimani Mohammad , Masoumi Ahmad , Farrokhpour Hossein , Keykhaei Mohammad , Zeidabadinejad Haniyeh , Tabatabaei Seyed Ali
Published: February 2022

PURPOSE:

To evaluate the rate of infectious keratitis after photorefractive keratectomy (PRK) before and during the coronavirus disease 2019 (COVID-19) pandemic.

METHODS:

A retrospective chart review was performed on patients who were diagnosed as having infectious keratitis after PRK between January 2015 and January 2021.

RESULTS:

The study period was divided into the pre-COVID-19 era (between January 2015 and February 2020) and the COVID-19 era (between February 2020 and January 2021). A total of 47 patients were diagnosed as having infectious keratitis after PRK: 22 were diagnosed in the pre-COVID-19 era and 25 were diagnosed in the COVID-19 era. The rate ratio for infectious keratitis after PRK was 5.68 during the COVID-19 pandemic (CI: 3.20 to 10.07,
P
< .001). The odds ratio for the ratio of cases of infectious keratitis after PRK to all cases of infectious keratitis was 9.00 during the COVID-19 pandemic (CI: 5.05 to 16.05,
P
< .001). To better understand the change in the rate of infectious keratitis after PRK during the COVID-19 pandemic, the analysis was narrowed to the patients with infectious keratitis who had their procedure in Farabi Eye Hospital. Of the 8 patients who were diagnosed as having infectious keratitis after PRK, 4 were diagnosed in the pre-COVID-19 era and 4 were diagnosed in the COVID-19 era. The risk ratio of infectious keratitis after PRK was 9.11 in our department in the COVID-19 era (95% CI limit: 2.28 to 36.46,
P
= .005).

CONCLUSIONS:

The rate of infectious keratitis after PRK increased during the COVID-19 pandemic. This may be due to the increased use of face masks in this era.

[
J Refract Surg
. 2022;38(2):78–81.]
Long-term Outcomes of Bowman's Membrane Relaxation for Enhancement of Femtosecond Intrastromal Lenticule Implantation Performed for the Management of High Hyperopia
Authors: Brar Sheetal , Ganesh Sri , Sriganesh Skanda Samak , Dorennavar Laxmi
Published: February 2022

PURPOSE:

To evaluate the feasibility and report long-term outcomes with Bowman's membrane relaxation (BMR) for enhancing the residual refractive error following femtosecond intrastromal lenticule implantation (FILI).

METHODS:

BMR was performed using a Hessburg-Barron trephine to create a circular incision into the Bowman's membrane and anterior corneal fibers up to the depth of approximately 120 to 130 µm. After enhancement, clinical outcomes were analyzed for a mean period of 36 months (range: 14 to 57 months).

RESULTS:

Four eyes of 3 patients (mean age: 29 years) underwent enhancement with BMR for a significant residual refractive error of +2.25 diopters (D) spherical equivalent following FILI for high hyperopia (mean spherical equivalent: +7.00 D). After BMR, the residual refraction reduced to +0.31 D, resulting in improvement in uncorrected distance visual acuity from 0.55 to 0.33 logMAR. The mean front keratometry values increased from 46.20 to 49.30 D, and the mean back keratometry values increased from −5.90 to −6.30 D following BMR, the latter returning to the baseline (pre-FILI) value of −6.30 D. An increase in Q-value with a corresponding increase in higher order aberrations was observed. Corneal biomechanics indicated reduction of stiffness and other parameters after enhancement. No intraoperative or postoperative complications were noted.

CONCLUSIONS:

BMR may be an effective technique for enhancement of residual hyperopia following tissue addition techniques such as FILI. BMR may reverse the posterior curvature changes, negating the steepening effect of the anterior cornea following tissue addition, potentially aiding in the enhancement.

[
J Refract Surg
. 2022;38(2):134–141.]
The Role of Anti–IL-1 Medications in Autoinflammatory Disease
Authors: Semo-Oz Rotem , Biton Bar , Tesher Melissa S.
Published: February 2022

The interleukin (IL) -1 family of cytokines are involved in different aspects of inflammation with IL-1 beta being the best known and most powerful proinflammatory cytokine. Dysregulation of IL-1 beta and other family members results in autoinflammatory conditions such as systemic juvenile idiopathic arthritis and familial Mediterranean fever. The growing understanding and knowledge of the pathophysiology of many autoinflammatory diseases have led to the development and use of IL-1 blocking medications for many chronic and disabling diseases. In this article, we present the anti–IL-1 agents and their major indications in pediatric rheumatology.

[
Pediatr Ann
. 2022;51(2):e72–e76.]
The complex Hessian quotient flow on compact Hermitian manifolds
Authors: Zhou Jundong ,   School of Mathematics and Statistics, Fuyang Normal University, Fuyang 236037, China, Chu Yawei
Published: February 2022

In this paper, we consider the parabolic Hessian quotient equation on compact Hermitian manifolds. By setting up a priori estimates of the admissible solutions, we prove the long-time existence of the solution to the parabolic Hessian quotient equation and its convergence. As an application, we show the solvability of a class of complex Hessian quotient equations, which generalizes the relevant results.
A quintuple integral involving the product of Hermite polynomial $ H_{n}(\beta x) $ and parabolic cylinder function $ D_{v}(\alpha t) $: derivation and evaluation
Authors: Reynolds Robert ,   Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, M3J1P3, Canada, Stauffer Allan
Published: February 2022

In this paper, we derive an integral transform involving the product of Hermite polynomial $ H_{n}(\beta x) $ and parabolic cylinder function $ D_{v}(\alpha t) $. These integral transforms will be evaluated in terms of Lerch function. Various formulae are also evaluated in terms of special functions to complete this paper. All the results in this paper are new.
Characterization of extension map on fuzzy weakly cut-stable map
Authors: Ma Nana ,   School of Statistics, Xi'an University of Finance and Economics, Xi'an 710100, China, Luo Qingjun , Xu Geni
Published: February 2022

In this paper, based on a complete residuated lattice, we propose the definition of fuzzy weakly cut-stable map and prove the extension property of the fuzzy weakly cut-stable map. Following this, it is explored the conditions under which the extension map to be fuzzy order isomorphism.
Mathematical foundations based statistical modeling of software source code for software system evolution
Authors: Althar Raghavendra Rao ,   Department of Data Science, CHRIST University, Bangalore, Karnataka, India, Alahmadi Abdulrahman , Samanta Debabrata , Khan Mohammad Zubair , Alahmadi Ahmed H. ,   Specialist-QMS, First American India Private Ltd., Bangalore, Karnataka, India,   Department of Computer Science and Information, Taibah University, Madinah, Saudi Arabia,   Department of Computer Science, CHRIST University, Bangalore, India
Published: February 2022

Source code is the heart of the software systems; it holds a wealth of knowledge that can be tapped for intelligent software systems and leverage the possibilities of reuse of the software. In this work, exploration revolves around making use of the pattern hidden in various software development processes and artifacts. This module is part of the smart requirements management system that is intended to be built. This system will have multiple modules to make the software requirements management phase more secure from vulnerabilities. Some of the critical challenges bothering the software development community are discussed. The background of Machine Learning approaches and their application in software development practices are explored. Some of the work done around modeling the source code and approaches used for vulnerabilities understanding in software systems are reviewed. Program representation is explored to understand some of the principles that would help in understanding the subject well. Further deeper dive into source code modeling possibilities are explored. Machine learning best practices are explored inline with the software source code modeling.
A new MAGDM method with 2-tuple linguistic bipolar fuzzy Heronian mean operators
Authors: Naz Sumera ,   Department of Mathematics, Division of Science and Technology, University of Eduction, Lahore, Pakistan, Akram Muhammad , Al-Shamiri Mohammed M. Ali , Khalaf Mohammed M. , Yousaf Gohar ,   Department of Mathematics, University of the Punjab, New Campus, Lahore, Pakistan,   Department of Mathematics, Faculty of Science and Arts, Muhayl Asser, King Khalid University, Kingdom of Saudi Arabia,   Department of Mathematics and Computer, Faculty of Science, Ibb University, Ibb, Yemen,   Faculty of Engineering, Arab Academy for Science & Technology and Maritime Transport (AASTMT), Aswan Branch, Egypt,   School of Mathematics, Minhaj University Lahore, Pakistan
Published: February 2022

In this article, we introduce the 2-tuple linguistic bipolar fuzzy set (2TLBFS), a new strategy for dealing with uncertainty that incorporates a 2-tuple linguistic term into bipolar fuzzy set. The 2TLBFS is a better way to deal with uncertain and imprecise information in the decision-making environment. We elaborate the operational rules, based on which, the 2-tuple linguistic bipolar fuzzy weighted averaging (2TLBFWA) operator and the 2-tuple linguistic bipolar fuzzy weighted geometric (2TLBFWG) operator are presented to fuse the 2TLBF numbers (2TLBFNs). The Heronian mean (HM) operator, which can reflect the internal correlation between attributes and their influence on decision results, is integrated into the 2TLBF environment to analyze the effect of the correlation between decision factors on decision results. Initially, the generalized 2-tuple linguistic bipolar fuzzy Heronian mean (G2TLBFHM) operator and generalized 2-tuple linguistic bipolar fuzzy weighted Heronian mean (G2TLBFWHM) operator are proposed and properties are explained. Further, 2-tuple linguistic bipolar fuzzy geometric Heronian mean (2TLBFGHM) operator and 2-tuple linguistic bipolar weighted geometric Heronian mean (2TLBFWGHM) operator are proposed along with some of their desirable properties. Then, an approach to multi-attribute group decision-making (MAGDM) based on the proposed aggregation operators under the 2TLBF framework is developed. At last, a numerical illustration is provided for the selection of the best photovoltaic cell to demonstrate the use of the generated technique and exhibit its adequacy.
Neural architecture search via standard machine learning methodologies
Authors: Franchini Giorgia ,   Department of Mathematics and Computer Science, University of Ferrara, Via Machiavelli, 30, 44121 Ferrara (FE), Italy, Ruggiero Valeria , Porta Federica , Zanni Luca ,   Department of Physics, Informatics and Mathematics, University of Modena and Reggio Emilia, Via Campi 213/B, 41121 Modena (MO), Italy
Published: February 2022

In the context of deep learning, the more expensive computational phase is the full training of the learning methodology. Indeed, its effectiveness depends on the choice of proper values for the so-called hyperparameters, namely the parameters that are not trained during the learning process, and such a selection typically requires an extensive numerical investigation with the execution of a significant number of experimental trials. The aim of the paper is to investigate how to choose the hyperparameters related to both the architecture of a Convolutional Neural Network (CNN), such as the number of filters and the kernel size at each convolutional layer, and the optimisation algorithm employed to train the CNN itself, such as the steplength, the mini-batch size and the potential adoption of variance reduction techniques. The main contribution of the paper consists in introducing an automatic Machine Learning technique to set these hyperparameters in such a way that a measure of the CNN performance can be optimised. In particular, given a set of values for the hyperparameters, we propose a low-cost strategy to predict the performance of the corresponding CNN, based on its behavior after only few steps of the training process. To achieve this goal, we generate a dataset whose input samples are provided by a limited number of hyperparameter configurations together with the corresponding CNN measures of performance obtained with only few steps of the CNN training process, while the label of each input sample is the performance corresponding to a complete training of the CNN. Such dataset is used as training set for a Support Vector Machines for Regression and/or Random Forest techniques to predict the performance of the considered learning methodology, given its performance at the initial iterations of its learning process. Furthermore, by a probabilistic exploration of the hyperparameter space, we are able to find, at a quite low cost, the setting of a CNN hyperparameters which provides the optimal performance. The results of an extensive numerical experimentation, carried out on CNNs, together with the use of our performance predictor with NAS-Bench-101, highlight how the proposed methodology for the hyperparameter setting appears very promising.
Analysis of COVID-19 epidemic model with sumudu transform
Authors: Farman Muhammad ,   Department of Mathematics and Statistics, The University of Lahore, Lahore, Pakistan, Azeem Muhammad , Ahmad M. O.
Published: February 2022

In this paper, we develop a time-fractional order COVID-19 model with effects of disease during quarantine which consists of the system of fractional differential equations. Fractional order COVID-19 model is investigated with ABC technique using sumudu transform. Also, the deterministic mathematical model for the quarantine effect is investigated with different fractional parameters. The existence and uniqueness of the fractional-order model are derived using fixed point theory. The sumudu transform can keep the unity of the function, the parity of the function, and has many other properties that are more valuable. Solutions are derived to investigate the influence of fractional operator which shows the impact of the disease during quarantine on society.
À propos des foyers protohistoriques à pierres chauffantes en Provence-Alpes-Côte d’Azur
Authors: Dubesset Denis
Published: February 2022

Cet article est consacré à la question des foyers à pierres chauffantes protohistoriques à la lumière des découvertes effectuées depuis le début des années 2000 en Provence-Alpes-Côte d’Azur. Vingt-huit sites ont été étudiés depuis cette date, portant à trente le nombre d’établissements connus pour cette période. La région s’avère ainsi de première importance pour la compréhension globale de ces aménagements et de leur chronologie. Les exemples provençaux sont également comparés à d’autres cas semblables extérieurs à la région. Un inventaire global a permis de référencer 168 sites et 763 foyers à pierres chauffantes. Si certains sont retrouvés isolés ou en petits groupes, d’autres sont agencés en batteries pouvant compter jusqu’à plusieurs dizaines d’exemplaires. Les établissements pour lesquels les foyers sont les plus nombreux doivent désormais être considérés comme des marqueurs territoriaux forts, vraisemblablement communs à plusieurs unités d’habitat.
Corps réel et virtuel à l’épreuve de l’intermédialité. Exemple des pièces de théâtre 180 degrés et N’enterrez pas trop vite Big Brother de Driss Ksikes
Authors: Belghit Imad
Published: February 2022

Le théâtre marocain contemporain s’accommode d’une esthétique scénique qui fait la part belle à l’intrusion de la machine dans la performance. Cet article examine l'impact de l’intermédialité sur le jeu des acteurs et s'intéresse à la manière dont la culture numérique combine la scène traditionnelle avec les interfaces médiatiques et les réseaux sociaux. L'un des principaux objectifs de ce papier est d’analyser les multiples interrelations des corps réels et virtuels dans la performance théâtrale contemporaine au Maroc, à travers un corpus de deux pièces : 180 degrés et N’enterrez pas trop vite Big Brother du dramaturge Driss Ksikes. Dans ces performances, l’écriture fonctionne comme élément du processus créatif aux côtés d’autres médiums, ce qui contribue au croisement du texte avec la machine tout en soumettant la scène au processus d’hybridation.
Une république mélancolique des lettres ? La dominance de la mélancolie dans l’espace littéraire en Europe
Authors: Ellison Ian
Published: February 2022

Cet essai examine la prédominance des modes d’écriture mélancoliques dans la littérature européenne et met ces observations en dialogue avec la notion de Pascale Casanova d’une « république mondiale des lettres ». Publiée à la fin du millénaire en 1999, l’étude de Casanova possède une influence jusqu’ici méconnue sous la forme d’une mélancolie millénaire, qui est liée à la construction d’une république mondiale des lettres, tout en qualifiant le caractère européen perçu de cette république. En rassemblant des traits distinctifs particuliers des discours sur la république mondiale des lettres et sur la mélancolie esthétique comme affect de « tardiveté » culturelle fin-de-siècle, cet article vise à proposer que – dans au moins une partie de la culture européenne (occidentale) vers la fin du XXe siècle – on pourrait parler d’une république mélancolique des lettres investissant l’espace littéraire européen. La mélancolie agit ainsi comme un « méridien de Greenwich » littéraire (pour reprendre les termes de Casanova) dans la littérature européenne moderne ainsi qu’un idiome littéraire européen. Si la mélancolie peut servir de modèle herméneutique pour la relation entre la littérature et l’histoire, ce qui est le propos de cet article, n’est-ce pas, en fin de compte, parce qu’elle n’est pas seulement une condition historique, mais une partie intégrante de l’idée de la littérature européenne en tant que telle ?
Risk Analysis for Human-Mediated Movement of Pests and Pathogens
Authors: Meissner Heike E. , Cook Gericke , Neeley Alison D. , Portacci Katie , Miller Ryan S. , Hallman Clayton , Derda Sarah
Published: February 2022

Humans have always played an important role in dispersing plants, animals, and other organisms—either intentionally or inadvertently. Over the last several decades, rapid developments in infrastructure and transportation have led to dramatic increases in trade, travel, and mass migration; this in turn has accelerated the human-mediated spread of organisms across the globe. In their new environments, introduced species may thrive and cause severe economic and ecological impacts. Mitigating the entry, establishment, and spread of exotic pests and pathogens is crucial for protecting agriculture, ecosystems, and people. To do this, it is important to understand the pathways by which invasive species spread, assess the associated risks, and develop effective mitigation measures. This chapter describes the role of risk analysis for understanding human-mediated pathways of pest introduction and spread and provides case studies from both the plant and animal health arenas.
Global Fintech Market
Authors: Tsanis Konstantinos , Stouraitis Vasilios
Published: February 2022

The FinTech industry has been growing rapidly and significantly, becoming the go-to service provider for some of the most important financial services, such as lending and payments. Since 2020, the onset of COVID-19 has substantially impacted the industry, both positively and negatively. This chapter discusses the recent performance of the FinTech industry based on a large-scale survey across the globe. The chapter then focuses on analysing the ‘new normal' in banking, after the pandemic era, based on the findings of the global survey, with explicit focus on the FinTech sector, followed by further implications on the impact that the pandemic had in the traditional banking sector. The chapter concludes by providing an overview of the emerging opportunities that appear in the FinTech sector.
“Where the Next Meal Is Coming From”
Authors: Hai-Jew Shalin
Published: February 2022

Given the intimacy of food preparation and service, the close proximity of diners and staff, the general inability to eat comfortably while masked, the warm emotional atmospherics of restaurants, and the limits to restaurant ventilation, the current SARS-CoV-2/COVID-19 pandemic has meant shutdowns of restaurants across the United States early in the pandemic and then partial re-openings later with public health constraints. Some restaurants applied for the Small Business Administration (SBA)'s Paycheck Protection Program's funds in March 2020 to cover 2.5 months maximum of costs. Huge swaths of the restaurant industry have closed permanently, and many others are slated to close in the near future. Based on a content analysis, this work explores the plight of restaurant workers in the academic research and mass media literature and applies abductive reasoning to propose an approach for a policy mix that may better inform the present challenges with social justice considerations.
Leveraging Virtual Professional Development Experiences to Prepare to Teach Young Children Online
Authors: Wolfe Kimberly , Henehan Shelli , Haynes Ronnette
Published: February 2022

The authors share the impact from trainings and free curriculum options offered to teachers, administrators, and parents on pedagogy in the early childhood classroom. The authors employ a mixed methods data collection process utilizing extant data to include pre- and post-tests and evaluations of trainers to support the findings of the research. Furthermore, the authors share strategies and implications for learning, access, and equity when professional development is offered in the synchronous online format. They highlight the importance of effectively shifting modalities to provide continuous accessibility to high quality trainings for adult learners. Creative instructional strategies focused on student engagement ensure that learning objectives are met.
Studying the Adoption of Blockchain Technology in the Manufacturing Firms
Authors: Mukherjee Subhodeep , Baral Manish Mohan , Chittipaka Venkataiah
Published: February 2022

This chapter studies blockchain technology logistics and supply chain adoption in four manufacturing firms. Semi-structured interviews are conducted, and the results are analyzed using case study methods. Four manufacturing firms are selected for the study. First firms deal with consumer electronics manufacturing, second firms deal with auto components manufacturing, third firms deal with paint manufacturing, and fourth firms deal with consumer electronics, manufacturing, wearables manufacturing. The case study is analysed using cross-case analysis and withing case analysis.
Mutual Recognition Mechanism Based on DVCS Oracle in the Blockchain Platform
Authors: Kustov Vladimir Nikolaevich , Selanteva Ekaterina Sergeevna
Published: February 2022

The main purpose of this chapter is to present the need to use the mutual recognition mechanism (MRM) of electronic signatures based on the DVCS oracle in the blockchain platform for the global supply chain. The authors begin their research by comparing a single-domain traditional supply chain with a multi-domain global supply chain. In the second case, the necessity of using an MRM electronic signature based on the DVCS oracle is justified. Various options for constructing MRM are discussed. The chapter provides a comparative assessment of the electronic signature validation protocols and the rationale for using the DVCS protocol to implement the blockchain oracle. As a result, the authors propose to use a well-tested software and hardware complex of the Litoria DVCS as a DVCS oracle and illustrate its use with practical examples.
Integration of IoT and Blockchain for Smart and Secured Supply Chain Management
Authors: Yu Poshan , Liu Zhiruo , Hanes Emanuela , Mumtaz Jabir
Published: February 2022

This chapter will focus on the combination of supply chain management and digital technology. Starting from the popular digital terms in the current market, the authors examine the current environment of the development, including Chinese government policies and the industry situation, and then compare the different characteristics of Industry 4.0 before and after digitization by combining the two digital technologies (i.e., blockchain and internet of things [IoT]). Moreover, the advantages of the integration of internet of things and blockchain in supply chain management will be highlighted. At the same time, according to the changes brought by digitization, the added value of IoT and blockchain integration will be analyzed from the perspective of different stakeholders. In addition, some Chinese case studies will be introduced to show the innovative performance of and benefits for enterprises, to provide references for enterprises, and to implement IoT for smart economic growth.
Augmenting Mental Healthcare With Artificial Intelligence, Machine Learning, and Challenges in Telemedicine
Authors: Avasthi Sandhya , Sanwal Tanushree , Sareen Puja , Tripathi Suman Lata
Published: February 2022

Artificial intelligence is a huge part of the healthcare industry, having applications and uses in oncology, cardiology, dermatology, and many other fields. Another area where AI is constantly attempting to improve is mental healthcare by integrating machine learning to evaluate data generated by mobile and IoT devices. AI aids in the diagnosis and tailoring of therapy for mentally ill individuals at various stages. The artificial intelligence and machine learning methods utilize electronic health records, mood rating scales, brain images, mobile devices monitoring data in prediction, classification, and grouping of mental health issues, mainly psychiatric illness, suicide attempts, schizophrenia, and depression. The goal of this chapter is to review the literature on artificial intelligence and machine learning algorithms for detecting a person's mental health by utilizing patient health records. In addition, the chapter explains the use of artificial intelligence in curing and monitoring a patient with mental illness through telemedicine.
Leadership in a Post-Pandemic World
Authors: Robertson Robert W. , Eira de Aquino Carlos Tasso
Published: February 2022

The skills gap has increasingly been identified as a growing concern that may negatively impact the economic growth of nations across the globe. Indeed, the future of work is changing, and there is a growing need for employees and employers to recognize the fact that the skills of today will not be sufficient to operate in the technology-driven economy of the future. This chapter discusses the challenges faced by the workforce in addressing diversity and inclusion issues and the skills gap in the global marketplace. It explores and highlights the importance of a structured method of addressing conflict via an effective negotiation using a seven-step theoretical model, while dealing with diversity and inclusion in the workforce.
A New Normal Multigenerational Leadership Model for Leaders in the COVID Era
Authors: Journey Grace Christian
Published: February 2022

During the COVID era, diverse industries require persons willing to go towards another level of transformational leadership. This author proposes multigenerational leadership as a valuable addition. Five generations in the modern workforce described as the Silent Generation (1928-1945), Baby-Boomers (1946-1964), Generation X (1965-1980), Generation Y also known as Millennials (1981-1996), and Generation Z (1997-2012) are creating history! Each generation demonstrates unique perspectives, attitudes, and behaviors. The purpose of this chapter is to encourage the addition of multigenerational leadership to established leadership approaches that will require commitment to intentional learning about representatives of each generation, multigenerational challenges, change management styles, multiple intelligences, and effective soft skills. This chapter would emerge as an initial guide during the COVID-19 pandemic and envisions transformation during the post-pandemic era.
Implementation of a Visual Telerehabilitation Protocol During the COVID-19 Pandemic
Authors: Perasso Giulia , Baghino Chiara , Capris Elisabetta , Cocchi Elena , Dini Silvia , Facchini Valentina , Panizzi Antonella , Salvagno Valentina
Published: February 2022

In March 2020, the Italian Government declared a state of lockdown to curb the spread of the COVID-19 pandemic. This led to many challenges in the provision of rehabilitation services to people with disabilities. Consequently, there was a transition to the telematic provision of healthcare as an adaptive approach to the constraints posed by the pandemic. In the visual rehabilitation field, the lack of international guidelines for telematic rehabilitation led to pioneering interventions, which were challenged by difficulties in the use of technological devices by visually impaired individuals. The purpose of this chapter is to identify the peculiar features that could enable the provision of visual telerehabilitation during the pandemic by analyzing the procedures followed in the implementation of a visual telerehabilitation protocol in Italy and the outcomes thereof.
Importance of Deep Learning Models in the Medical Imaging Field
Authors: Sharma Preeti , Bhatt Devershi Pallavi
Published: February 2022

Medical imaging applications like MRI, CT scan, x-ray, PET, ultrasound, etc. provide health experts fast and comprehensive information of the internal organs and tissues of the human body. MRI of the brain is used to get inside information of any sort of brain injury, tumor, stroke, or wound in a blood vessel. The complex structure of the brain makes it a challenging responsibility for the researcher to design a model to precisely segment the brain region from the skull and to find any abnormality in the tissue. This chapter helps to understand the importance of deep learning to perform segmentation on MRI (magnetic resonance imaging) scans of the brain by reviewing previous studies and also presents brief knowledge of different brain imaging techniques, digital image segmentation techniques, and deep learning.
Overview and Analysis of Present-Day Diabetic Retinopathy (DR) Detection Techniques
Authors: Das Smita , Majumder Swanirbhar
Published: February 2022

Diabetic retinopathy (DR) detection techniques is a biometric modality that deserves systematic review and analysis of the connected algorithms for further improvement. The ophthalmologist uses retinal fundus images for the early detection of DR by segmenting the images. There are several segmentation algorithms reported as earlier. This chapter presents a comprehensive review of the methodology associated with retinal blood vessel extraction presented to date. The vessel segmentation techniques are divided into four main categories depending on their underlying methodology as pattern recognition, vessel tracking, model based, and hybrid approaches. A few of these methods are further classified into subsections. Finally, a comparative analysis of a few of the DR detection techniques will be presented here based on their merits, demerits, and other parameters like sensitivity, specificity, and accuracy and provide detailed information about its significance, present status, limitations, and future scope.
Computational Statistics on Stress Patients With Happiness and Radiation Indices by Vedic Homa Therapy
Authors: Rastogi Rohit , Sagar Sheelu , Tandon Neeti , Singh Bhavna , Rajeshwari T.
Published: February 2022

The happiness programs and seeking their various means are popular across the globe. Many cultures and races are using them in different ways through carnivals, festivals, and occasions. In India, the Yajna, Mantra, Pranayama, and Yoga-like alternate therapies are now drawing attention of researchers, socio behavioral scientists, and philosophers by their scientific divinity. The chapter is an honest effort to identify the logical progress on happiness indices and reduction in radiation of electronic gadgets. The visualizations propound evidence that the ancient Vedic rituals and activities were effective in maintaining the mental balance. The data set was collected after a specified protocol followed and analyzed through various scientific data analysis tools.
Sentiment Analysis
Authors: Nkomo Larian M. , Alm Antonie
Published: February 2022

With people constantly expressing themselves on various online platforms, there are multitudes of data available that can be used in research. In most cases, these data are unstructured and can be intimidating to analyse due to the large volumes. However, techniques such as sentiment analysis can be used to analyse these data and obtain insights that are useful for researchers. Without the academic and emotional support typically found in a classroom, informal language learners control their own learning environment. This study illustrates how sentiment analysis can be utilised to obtain insights on the experiences of informal L2 learners when they engage with chatbots for L2 learning. Data were collected from various online platforms to reflect experiences with four language learning applications with chatbot features over several years. Results suggest informal L2 learners have mixed sentiments on their experiences and sentiment analysis being a viable approach to analysing informal L2 learner qualitative data.
Being Brave in a MOOC World
Authors: Utku Bilici Özlem , Çetin Köroğlu Zeynep
Published: February 2022

Massive open online courses (MOOCs) have been a growing trend recently because thanks to them, many people can be enrolled in a course just through the internet, and it can be noted that they are generally preferred and in use to a great extent. However, the number of studies on the use of MOOCs in blended learning environments is relatively limited. For this specific reason, the current study was carried out as a convergent mixed-method study to provide insights into the pros and cons of using MOOCs for educational purposes. Twenty-four student teachers enrolled in the Department of English Language Teaching participated in the present study. The data were collected through learning journals and an inventory. Thematic analysis was utilised to analyse the qualitative data, whereas descriptive statistics were calculated for the analysis of quantitative data. The results were motivating for extending the use of MOOCs as self-guided learning tools.
COVID-19
Authors: St. Hilaire Kendall , Adrian Todd , Clay Leigh , Mello Lucimara , Profeta Katherine E. , Martabano Veronica
Published: February 2022

This case study describes how a global campus team at a mid-sized state college helped facilitate the institutional shift to remote functionality during the COVID-19 pandemic. The college's strategies include interdepartmental partnerships, frequent communication, professional development, student and staff support, and technology implementation. The chapter provides a reflection on the lessons learned, a retrospective realization that the team employed Kotter's eight-step process for leading change, and recommendations for advancing best practices. In addition, the narrative highlights the attention placed on the global team's efforts to humanize technology during the transition process. Humanization helps mitigate the challenges that can result from change and can be beneficial in the learning process. The team infused this characteristic throughout trainings and webinars to ease the disruption of system-wide adjustment.
The Future of Online Learning After COVID
Authors: Babaria Pratham , Bandyopadhyay Arkasama , LaDue Matt , Yildirim Yetkin
Published: February 2022

As education institutions struggled to adapt to the COVID-19 pandemic, many of their fundamental problems were brought to the surface. Emergency adjustments to online learning were intended to minimize the disruption to learning as much as possible in the midst of a global pandemic. But now that schools in the US are beginning to reopen for in-person instruction, it is time to critically assess these changes to higher-education and consider their long-term impact on the future of college learning. This chapter will confront these issues and explore how education resources can be used to ensure student engagement and prevent social isolation in future modes of hybrid and online learning.
Alt-Instruction
Authors: Bondad-Brown Beverly , Haras Catherine
Published: February 2022

This chapter highlights a strategic faculty development effort to address equity issues when a university campus pivoted to emergency remote instruction during the COVID-19 pandemic. The authors describe the development of an online faculty development summer program, ‘Alt-Instruction', targeted to help all campus faculty make the rapid pivot to remote learning, while keeping student equity issues front and center. This COVID-19 program was not designed haphazardly but rather based on years of designing and offering educational development that 1) assumed the necessity for collocating instructional technology support with teaching resources, 2) considered teaching from a student-centered perspective, and 3) anticipated the need to carefully model best practices for faculty. The 2020 Alt-Instruction program, which close to 1,000 faculty participated in, used a highly structured approach to educational development, including the employment of online resources and modeling templates. These contributed to a relatively fast, if unprecedented, campus migration to remote learning.