Instrumental Tools Research Articles

Mapping Egyptian Translations of Israeli Literatures: Evolution, Attitudes, and Themes

This study delves into the intricate realm of Egyptian translations of Hebrew and Israeli literatures, illuminating the various attitudes of the Egyptian government, intellectual elite, and educated populace toward cultural normalization with Israel. Analyzing a corpus of over a hundred translations spanning different genres, this research outlines turning points in the evolution of translation practices from the establishment of Israel to the present day. The study unveils a complex interplay between politics, culture, and public sentiment, illustrating how translations serve various roles, ranging from instrumental polemic tools in the Israeli–Arab conflict to avenues for cultural openness and familiarity. While the prevailing norm involves refraining from publicly endorsing normalization with Israel, government policy reflects a nuanced approach that balances anti-normalization sentiments at the official level with private sector flexibility. By exploring the selection criteria governing translation, the research provides valuable insights into the preferences of the Egyptian reading public and its perceptions of Israel, peace, and intercultural exchange.

Middle Lobe Syndrome: A Case Report and Literature Review

Background: Middle lobe syndrome (MLS) is a distinct clinical and radiographic entity characterized by recurrent or chronic collapse of the middle lobe of the right lung, but it can also involve the lingula of the left lung. Case Study: This study presents a rare case of MLS caused by a vascular ring never described in the literature until now and provides physicians with the clinical and instrumental tools in order to early recognize and promptly treat this condition. The case report was reported according to CARE guidelines. A literature research on PubMed/MEDLINE was also performed using the MeSH terms “Middle lobe syndrome OR MLS AND double aortic arch” “Middle lobe syndrome OR MLS AND vascular rings”. No case described in the literature was found. In most cases, MLS presents non-specific respiratory symptoms, which unfortunately is responsible for the diagnostic delay that patients with this pathology often suffer. The diagnostic delay is estimated to be 8 months (range 3 to 36 months). A history of dysphagia and regurgitation can be indirect signs of a vascular compression, such as vascular rings, which can cause MLS. Conclusion: To date, the reported case is the only case in the literature of MLS caused by double aortic arch. The key point for the diagnosis of MLS is diagnostic suspicion. Early recognition of MLS is essential to quickly start a targeted therapeutic program avoiding the persistence of vicious circle atelectasis-recurrent respiratory infections, and this could significantly improve the long-term outcome of these patients.

Digital Mental Health Interventions for Adolescents in Low- and Middle-Income Countries: Scoping Review.

Digital mental health interventions (DMHIs) are increasingly recognized as potential solutions for adolescent mental health, particularly in low- and middle-income countries (LMICs). The United Nations' Sustainable Development Goals and universal health coverage are instrumental tools for achieving mental health for all. Within this context, understanding the design, evaluation, as well as the barriers and facilitators impacting adolescent engagement with mental health care through DMHIs is essential. This scoping review aims to provide insights into the current landscape of DMHIs for adolescents in LMICs. The Joanna Briggs Institute scoping review methodology was used, following the recommendations of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). Our search strategy incorporated 3 key concepts: population "adolescents," concept "digital mental health interventions," and context "LMICs." We adapted this strategy for various databases, including ACM Digital Library, APA PsycINFO, Cochrane Library, Google Scholar (including gray literature), IEEE Xplore, ProQuest, PubMed (NLM), ScienceDirect, Scopus, and Web of Science. The articles were screened against a specific eligibility criterion from January 2019 to March 2024. We analyzed 20 papers focusing on DMHIs for various mental health conditions among adolescents, such as depression, well-being, anxiety, stigma, self-harm, and suicide ideation. These interventions were delivered in diverse formats, including group delivery and self-guided interventions, with support from mental health professionals or involving lay professionals. The study designs and evaluation encompassed a range of methodologies, including randomized controlled trials, mixed methods studies, and feasibility studies. While there have been notable advancements in DMHIs for adolescents in LMICs, the research base remains limited. Significant knowledge gaps persist regarding the long-term clinical benefits, the maturity and readiness of LMIC digital infrastructure, cultural appropriateness, and cost-effectiveness across the heterogeneous LMIC settings. Addressing these gaps necessitates large-scale, co-designed, and culturally sensitive DMHI trials. Future work should address this.

Machine Learning Empowered Breast Cancer Diagnosis: Insights from Coimbra Dataset

Aim: The aim of this work is to succinctly communicate the key aspects of a research study on breast cancer. This includes highlighting the global impact and prevalence of breast cancer, emphasizing the challenges of early diagnosis, discussing the potential of technological advancements, and showcasing the role of machine learning algorithms in the context of liver cancer diagnosis. Background: Cancer, notably breast cancer, represents a global health challenge, claiming a significant toll with 12.5% of new cancer cases annually. The prevalence of breast cancer among women worldwide is alarming, resulting in 2.26 million incidents and the unfortunate loss of 685,000 lives. Objective: This article focuses on the critical aspect of early breast cancer diagnosis, acknowledging its heightened difficulty in developing nations compared to developed counterparts. The potential for advancements in technology to serve as a beacon of hope lies in early identification and timely treatment, offering salvation to numerous women and significantly elevating survival chances. Method: In this intricate landscape, machine learning algorithms, particularly in diagnosing liver cancer at its nascent stages, emerge as instrumental tools. The study employs the latest Coimbra dataset, encompassing nine key attributes and a binary classification attribute, with values 1 and 2 signifying benign and malignant cases, respectively. Result: Supervised machine learning algorithms, including Bayes net, multilayer perceptron, IBK, random committee, and random tree, are meticulously applied. Certain models exhibit superior accuracy, precision, recall, and performance, positioning them as promising cornerstones for breast cancer analysis. Conclusion: This structured abstract highlights the urgent need for effective screening and prevention strategies, emphasizing the potential of advanced technology and machine learning algorithms to play a pivotal role in the early detection and analysis of breast cancer, offering hope for improved outcomes and survival rates.

Preprocessing Text Data for the Doc2Vec Model in the Automatic Classification of Tickets in Support Centers of Software Providers

Leading software providers typically implement customer technical support functions, which are crucial for promoting and enhancing the competitiveness of their products and services in global markets. The high volume and heterogeneity of support tickets (functional, temporal, linguistic, etc.) highlight the importance of efficient classification systems. Effective classification optimizes the distribution of these tickets among support center specialists and automates their processing using an established knowledge base. However, classifying these tickets is a loosely formalized task. For companies that have accumulated substantial data on customer requests, automating classification through machine learning methods and natural language processing models, such as Word2Vec, FastText, BERT, and GPT, becomes feasible. It is generally accepted that classification effectiveness primarily depends on the model employed. Nevertheless, the quality of these models is significantly influenced by the nature of the training data. Literature review of the reveals significant research interest in methods for the automatic classification of tickets specifically tailored to the operational conditions of software provider support centers. However, there is a noticeable gap in the literature regarding the impact of data preprocessing on the quality of these models. The article aims to clarify the techniques of data preprocessing and analyze their impact on the effectiveness of text classification, considering the specificity of software provider support centers. This study examines the stages of the automatic classification process for tickets, accounting for the unique characteristics of the data (customer text requests). A relevant set of specified methodological and instrumental tools was developed and tested using open data from a global software provider (DevExpress). The testing involved a database of 165,000 tickets. The study's results indicate that preprocessing can improve classification metrics such as F-measure, Precision, and Recall from 77% to 79%. Additionally, preprocessing significantly reduces the dimensionality of text data (by 48.2%) and increases model training speed (by 26.5%) without loss of accuracy, ensuring cost-efficiency and operational efficiency in the use of computational resources.

Portfolio practices in the principal evaluation process: A qualitative case study

BackgroundThe portfolio is a vital component of the evaluation of principals and serves as a repository of evidence of achievements, skills, and capabilities. It facilitates the meticulous recording and documentation of experiences undertaken. Furthermore, the portfolio is instrumental in the refinement of conceptual ideas over time, while simultaneously offering a panoramic vista of a school's operational ethos and its alignment with professional benchmarks. ObjectiveThis study delves into the practices surrounding the principal portfolio and the formative and summative evaluation of principals by their evaluating supervisors. It aims to uncover principals’ perceptions regarding the obligatory nature of portfolios and other evaluative methodologies throughout both assessments. In light of the pivotal role that portfolios occupy in the realm of professional development and evaluation for school principals, the Abu Dhabi Education Council has mandated the compilation of principal portfolios within public schools. This mandate requires a detailed accounting of principals' proficiencies, achievements, and developmental trajectories. Markedly, this exploration stands as one of a scant number of inquiries probing the application of portfolios by school principals, with a particular focus on the context of the United Arab Emirates. It is poised to enrich the discourse on the utility of portfolios as instrumental tools for fostering leadership acumen and evaluative competency within the spheres of educator and principal preparation over the preceding two decades. The critical examination of these practices is vital for a nuanced understanding of their operational dynamics, the efficacy and challenges of e-portfolios, the array of opportunities they unveil, the identities of the involved stakeholders, and their ultimate objectives. MethodsThis study adopted a qualitative research approach to gather and analyze non-numerical data in the form of concepts, opinions, and experiences presented by principals and their supervisors within the Al-Ain School District (overseen by the Abu Dhabi Education Council). The cohort of participants comprised nine individuals endowed with extensive portfolio experience, six principals and three cluster managers. All worked in public educational institutions and were meticulously selected based on predefined criteria. This study relied on several data collection methods to obtain participants’ perspectives on their experiences with portfolio practices, including face-to-face interviews and documents from their portfolios. ResultsA thematic analysis of the participant data yielded five salient themes reflecting the experiences of the principals: (1) inconsistent expectations for portfolio evidence; (2) portfolios summoned in response to rising tensions at the summative evaluation; (3) portfolios promoting reflective practices in formative evaluation; (4) portfolios susceptible to manipulation or falsification; and (5) excessive time spent building and developing portfolios. In order to maximize the utility of portfolios, this result invites school principals to unleash the latent potential inherent in their actions by leveraging portfolios as mirrors for reflective leadership and ongoing self-assessment. ConclusionsThis research delineates both practical and theoretical ramifications for the application of professional portfolios. It elucidates the nature of evidence principals ought to incorporate within their portfolios. Furthermore, it endeavors to better inform principals of the evidence collection process, including what artifacts and documentation to gather and how to do so.

PECULIARITIES OF THE APPLICATION OF EVENTS IN THE MARKETING TOOLS SYSTEM IN UKRAINE

The article examines the distinctive characteristics of the utilisation of events within the marketing tools system in Ukraine. Furthermore, it analyses the prevailing global trends in the deployment of events within the marketing tools system. In particular, the annual increase in event budgeting is highlighted as a key trend, enabling organisations to plan more significant and better events in order to achieve their marketing goals. The implementation of technology in event marketing, whereby companies invest in events and utilise technology to create memorable experiences for customers and facilitate long-term growth, represents a significant trend. However, there is a shortage of qualified professionals in the field of event marketing, which presents a challenge for organisations seeking to engage with target audiences. Research indicates that 40% of event organisers perceive attracting new participants as their primary marketing challenge. Additionally, the popularity of remote and combined events, alongside the recognition of the effectiveness of live offline events in event marketing, represent noteworthy developments. It has been demonstrated that marketing tools have undergone substantial modifications and adaptations in the context of the ongoing conflict in Ukraine. One of the most instrumental tools to emerge in this context is that of events. Notwithstanding the challenging circumstances, event marketing continues to represent a potent instrument for communication and persuasion among target audiences. The organisation of events in the context of armed conflict necessitates a high degree of vigilance and consideration for the safety of all participants. Those responsible for organising such events are compelled to give due consideration to the potential risks and to devise contingency plans in the event of unforeseen circumstances. Concurrently, such occurrences serve as a conduit for bolstering the populace's morale, disseminating crucial intelligence, and fortifying national unity. It is imperative to acknowledge that the war has compelled businesses to reassess their marketing strategies, resulting in the implementation of more adaptable and flexible approaches to event organisation. Online and hybrid formats have become indispensable tools for enabling continuous customer engagement despite physical constraints. Consequently, events in Ukraine's marketing tool system during wartime have been demonstrated to be highly efficient, flexible, and adaptable. Such events play a pivotal role in sustaining business stability, fostering new forms of audience interaction, and strengthening social bonds.

Cutaneous Squamous Cell Carcinoma: From Diagnosis to Follow-Up.

Cutaneous squamous cell carcinoma (SCC) is the second most frequent skin cancer, accounting for approximately 20% of all cutaneous malignancies, and with an increasing incidence due to the progressive increment of the average age of life. The diagnosis is usually firstly suspected based on clinical manifestations; however, dermoscopic features may improve diagnostic sensitivity in cases of an uncertain diagnosis and may guide the biopsy, which should be performed to histopathologically prove the tumor. New diagnostic strategies may improve the sensitivity of the cutaneous SCC, such as reflectance confocal microscopy and line-field confocal optical coherence, for which increasing data have been recently published. Imaging has a central role in the staging of the diseases, while its exact role, as well as the choice of the best techniques, during the follow-up are not fully clarified. The aim of this literature review is to describe diagnostic clinical and instrumental tools of cutaneous SCC, with an insight into the role of imaging in the diagnosis and follow-up of cutaneous SCC.

Evaluating the quality of radiomics-based studies for endometrial cancer using RQS and METRICS tools.

To assess the methodological quality of radiomics-based models in endometrial cancer using the radiomics quality score (RQS) and METhodological radiomICs score (METRICS). We systematically reviewed studies published by October 30th, 2023. Inclusion criteria were original radiomics studies on endometrial cancer using CT, MRI, PET, or ultrasound. Articles underwent a quality assessment by novice and expert radiologists using RQS and METRICS. The inter-rater reliability for RQS and METRICS among radiologists with varying expertise was determined. Subgroup analyses were performed to assess whether scores varied according to study topic, imaging technique, publication year, and journal quartile. Sixty-eight studies were analysed, with a median RQS of 11 (IQR, 9-14) and METRICS score of 67.6% (IQR, 58.8-76.0); two different articles reached maximum RQS of 19 and METRICS of 90.7%, respectively. Most studies utilised MRI (82.3%) and machine learning methods (88.2%). Characterisation and recurrence risk stratification were the most explored outcomes, featured in 35.3% and 19.1% of articles, respectively. High inter-rater reliability was observed for both RQS (ICC: 0.897; 95% CI: 0.821, 0.946) and METRICS (ICC: 0.959; 95% CI: 0.928, 0.979). Methodological limitations such as lack of external validation suggest areas for improvement. At subgroup analyses, no statistically significant difference was noted. Whilst using RQS, the quality of endometrial cancer radiomics research was apparently unsatisfactory, METRICS depicts a good overall quality. Our study highlights the need for strict compliance with quality metrics. Adhering to these quality measures can increase the consistency of radiomics towards clinical application in the pre-operative management of endometrial cancer. Both the RQS and METRICS can function as instrumental tools for identifying different methodological deficiencies in endometrial cancer radiomics research. However, METRICS also reflected a focus on the practical applicability and clarity of documentation. The topic of radiomics currently lacks standardisation, limiting clinical implementation. METRICS scores were generally higher than the RQS, reflecting differences in the development process and methodological content. A positive trend in METRICS score may suggest growing attention to methodological aspects in radiomics research.

Amniotic Membrane-Derived Multichannel Hydrogels for Neural Tissue Repair.

In the pursuit of advancing neural tissue regeneration, biomaterial scaffolds have emerged as promising candidates, offering potential solutions for nerve disruptions. Among these scaffolds, multichannel hydrogels, characterized by meticulously designed micrometer-scale channels, stand out as instrumental tools for guiding axonal growth and facilitating cellular interactions. This study explores the innovative application of human amniotic membranes modified with methacryloyl domains (AMMA) in neural stem cell (NSC) culture. AMMA hydrogels, possessing a tailored softness resembling the physiological environment, are prepared in the format of multichannel scaffolds to simulate native-like microarchitecture of nerve tracts. Preliminary experiments on AMMA hydrogel films showcase their potential for neural applications, demonstrating robust adhesion, proliferation, and differentiation of NSCs without the need for additional coatings. Transitioning into the 3D realm, the multichannel architecture fosters intricate neuronal networks guiding neurite extension longitudinally. Furthermore, the presence of synaptic vesicles within the cellular arrays suggests the establishment of functional synaptic connections, underscoring the physiological relevance of the developed neuronal networks. This work contributes to the ongoing efforts to find ethical, clinically translatable, and functionally relevant approaches for regenerative neuroscience.

Utilizing global-local neural networks for the analysis of non-linear aerodynamics

In addressing the computational challenges pervasive in engineering where time and cost limitations are key concerns, particularly within the Computational Fluid Dynamics (CFD) domain, Reduced Order Models (ROMs) have emerged as instrumental tools. Focused on reducing computational complexity without intrusively modifying the computational model, this study centres on the strategic application of aerodynamic ROMs, which provide efficient computation of distributed quantities and aerodynamic forces. This work presents ROMs for non-linear aerodynamic applications, integrating principal component analysis (PCA) with Global Local Neural Networks (GLNN). The effectiveness of the proposed methodology is demonstrated by leveraging dependency on the parameter space created with non-linear high-fidelity CFD data, incorporating viscous simulation for a comprehensive approach. Results are first presented for a two-dimensional airfoil case and then for a three-dimensional test case featuring a transonic wing-body-tail transport aircraft configuration (NASA Common Research Model). In transonic flows, the proposed ROMs demonstrate the ability to accurately capture both the location and strength of shocks, as well as forces and moments for unseen prediction points. This highlights the efficiency of the proposed method in navigating complex aerodynamic scenarios, achieving comparable accuracy to full-order modelling but at orders of magnitude less computational time, for unseen parameters outside the ROM training set within the parameter space.

DEVELOPMENT OF A COMPUTER-BASED EDUCATIONAL PROGRAM ON THE SUBJECT "FUNDAMENTALS OF COMPUTER MODELING"

In the conditions of technological progress and rapid development of information technologies, it is very challenging to prepare specialists in the field of information and communication technologies who would fully possess the knowledge and skills to work with the diverse range of instrumental and software tools and equipment used in the field. This is due to the continuous improvement and updating of programming languages, frameworks, software environments, shells, and hardware. One of the ways to address this issue is through computer-based educational programs, allowing the individualization of the learning process while preserving it’s quality. Currently, there is a large number of computer-based educational programs used in the study of various disciplines. This paper presents the design of a computer-based educational program on the subject "Fundamentals of Computer Modeling," which enables the modeling of random patterns of various natures, ranging from random events to random streams. The educational program consists of three modules, which include a theoretical part on methods of modeling random patterns, testing after each topic, and a calculator for all modeling methods. In each modeling method, you can input any initial data, such as the number of trials, probabilities of events, functions, and parameters of distribution laws. The results of modeling random patterns can be saved as a file. The program interface is available in three languages: Russian, English, and Kazakh. The currently developing educational program aims to improve the learning process in the "Fundamentals of Computer Modeling" discipline and allows learners to study it independently without any interventions from a professor.

Instrumental and sensory tools to evaluate the production potential of a new type of sparkling wine from umbu (Spondias tuberosa)

Umbu is a native fruit from the Brazilian Caatinga Biome, which is a source of income for families involved in extractivism. This fruit is highly perishable and production losses have been experienced. The production of sparkling wine can be a strategy for better use and to add value to this fruit. Furthermore, consumers have been attracted to innovative beverages, produced with alternative raw materials and with an exotic and pleasant aroma. The potential for producing sparkling wine from umbu was evaluated through physical-chemical, instrumental (gas chromatography with detection by mass spectrometry and olfactometry) and sensory analyses (acceptance test, Just-about-right (JAR) scale, and penalty analysis). Both the base wine and the sparkling wine meet all regulatory physicochemical parameters. The volatile profile of umbu pulp contains mainly terpenes (55%), while esters predominated in the base and sparkling wines (32 and 33%, respectively). In sparkling wines, hexanoic acid (3114 mg L−1) and linalool (1266 mg L−1) were the major compounds. Among the 26 odor-active compounds of sparkling wines are mainly ethyl esters with fruity aroma (acetate, decanoate, and 2-phenylacetate; OSME area: 4.8, 4.8, and 5.0%, respectively), and terpenes with floral notes (p-cymene, geranic oxide and linalool; OSME area: 8.5, 7.4, and 6.9%, respectively). The acceptance and purchase intention tests endorsed the commercialization expectation, although JAR scale and penalty analysis showed that the umbu aroma and sweetness may be improved. The potential of umbu for the production of sparkling wines has been proven, which satisfies the current market demand for innovative beverages.

Low-temperature creep performance of additive manufactured Ti–6Al–4V

Abstract Additive manufacturing enables the fabrication of versatile and cost-effective metallic-alloy components from a digital data model. This study explores the prospects of selective laser melting (SLM), an additive manufacturing technique, for fabricating Ti6Al4V alloy components from Ti6Al4V alloy powders. Selective laser melting parameters, such as laser power, scanning speed, powder thickness, hatching space, and scanning strategy, are carefully selected through a series of experiments. The metallurgical characteristics (microstructure, grain orientation, and phase composition), microhardness, and creep performance of the as-fabricated specimens are tested and analyzed. The kinetics of phase transformation and rupture mechanism are determined using advanced instrumental characterization tools, such as field emission scanning electron microscope, energy dispersive X-ray spectroscope, X-ray diffractometer, and transmission electron microscope.

The bismar scale and elastic collisions: a geometrical analogy

Throughout history, scales have served as instrumental tools for quantifying the weight of objects, relying on a comparative assessment against a specified reference weight. Scales featuring uneven arms, such as the bismar scale, have proven particularly adept at gauging masses within a specific range relative to a predetermined reference mass. On the other hand, the kinematics of elastic collisions hinge on the inertial masses of the colliding entities. By observing the aftermath of a collision between a known reference mass and an object of unknown mass, one can deduce the latter’s mass. In this contribution, we highlight a fascinating and clear analogy between these two methodologies. We do so by adapting a geometric approach, initially applicable to the bismar scale, to both non-relativistic and relativistic elastic collisions, encompassing phenomena such as Compton scattering.

COMPLEX MATHEMATICAL MODEL OF THE PROCESS OF LOADING A MULTICOMPONENT CHARGE INTO A BLAST FURNACE

The rational mode of loading the blast furnace is the most important condition for its highly efficient operation. The selection of rational values of the control parameters of the load mode is carried out on the basis of information obtained with the help of instrumental tools and mathematical models. Mathematical models of the process of blast furnace loading are necessary components of expert (intelligent) control systems for blast furnace melting. The presented complex mathematical model of the process of loading a multicomponent charge into a blast furnace differs from known developments taking into account the redistribution of components into the volume of loaded portions during movement along the path "charge feed - blast furnace", which provides the possibility of obtaining calculated characteristics of the distribution of each component of the charge and determining the composition of the formed mixtures of charge materials in any given zone of the furnace. The existence of such a model opens up new opportunities in the management of the blast furnace smelting process, as well as in conducting analytical studies of the conditions of slag formation and the distribution of properties of melts across the section of the blast furnace.

Hedges and Boosters in Academic Writing of ASEAN EFL Learners

Hedges and boosters in general, and academic writing in particular, assume significant role in allowing writers to mitigate opposing claims while strengthening their arguments supported by reliable data. This study aimed to quantify the frequencies of hedges and boosters used by second language (L2) learners of English in ten ASEAN countries, including China, Hong Kong, Indonesia, Japan, Korea, Pakistan, Philippines, Singapore, Thailand, and Taiwan. Research samples were collected from the ICNALE learner corpus comprising 5,400 two different, determined topics of academic writings. Lancsbox 6.0 was utilized to analyse the sample texts. The results elucidate a notable trend wherein ASEAN English as a Foreign Language (EFL) learners exhibit a preference for boosters over hedges Among the identified overused boosters are completely, really, and always, while overused hedges include usually, often, and maybe. This inclination suggests that EFL learners express confidence in articulating their perspectives. Boosters serve as instrumental tools to reinforce confidence and certainty, emphasize significance and relevance, strengthen persuasiveness, enhance coherence and flow, and establish authority and academic voice. Nevertheless, it is imperative for L2 learners to recognize the importance of hedges in denoting tentativeness, softening criticism, acknowledging limitations, and establishing expertise.

Harnessing of carboxy containing starch nanoparticles as an adsorbent for Cd (II) ions and methylene blue from waste water effluent: synthesis, metrological characterization and properties

Purpose The novelty addressed here is undertaken by using tailor-made and fully characterized starch nanoparticles (SNPs) having a particle size ranging from 80 to 100 nm with a larger surface area, biodegradability and high reactivity as a starting substrate for cadmium ions and basic dye removal from wastewater effluent. This was done via carboxylation of SNPs with citric acid via esterification reaction using the dry preparation technique, in which a simple, energy-safe and sustainable process concerning a small amount of water, energy and toxic chemicals was used. The obtained adsorbent is designated as cross-linked esterified starch nanoparticles (CESNPs). Design/methodology/approach The batch technique was used to determine the CESNPs adsorption capacity, whereas atomic adsorption spectrometry was used to determine the residual cadmium ions concentration in the filtrate before and after adsorption. Different factors affecting adsorption were examined concerning pH, contact time, adsorbent dose and degree of carboxylation. Besides, to validate the esterification reaction and existence of carboxylic groups in the adsorbent, CESNPs were characterized metrologically via analytical tools for carboxyl content estimation and instrumental tools using Fourier-transform infrared spectroscopy (FTIR) spectra and scanning electron microscopy (SEM) morphological analysis. Findings The overall adsorption potential of CESNPs was found to be 136 mg/g when a 0.1 g adsorbent dose having 190.8 meq/100 g sample carboxyl content at pH 5 for 60 min contact time was used. Besides, increasing the degree of carboxylation of the CESNPs expressed as carboxyl content would lead to the higher adsorption capacity of cadmium ions. FTIR spectroscopy analysis elucidates the esterification reaction with the appearance of a new intense peak C=O ester at 1,700 cm−1, whereas SEM observations reveal some atomic/molecules disorder after esterification. Originality/value The innovation addressed here is undertaken by studying the consequence of altering the extent of carboxylation reaction expressed as carboxyl contents on the prepared CESNPs via a simple dry technique with a small amount of water, energy and toxic chemicals that were used as a sustainable bio nano polymer for cadmium ions and basic dye removal from wastewater effluent in comparison with other counterparts published in the literature.

Adaptive Lifting Index (aLI) for Real-Time Instrumental Biomechanical Risk Assessment: Concepts, Mathematics, and First Experimental Results.

When performing lifting tasks at work, the Lifting Index (LI) is widely used to prevent work-related low-back disorders, but it presents criticalities pertaining to measurement accuracy and precision. Wearable sensor networks, such as sensorized insoles and inertial measurement units, could improve biomechanical risk assessment by enabling the computation of an adaptive LI (aLI) that changes over time in relation to the actual method of carrying out lifting. This study aims to illustrate the concepts and mathematics underlying aLI computation and compare aLI calculations in real-time using wearable sensors and force platforms with the LI estimated with the standard method used by ergonomists and occupational health and safety technicians. To reach this aim, 10 participants performed six lifting tasks under two risk conditions. The results show us that the aLI value rapidly converges towards the reference value in all tasks, suggesting a promising use of adaptive algorithms and instrumental tools for biomechanical risk assessment.

Climate anxiety, environmental attitude, and job engagement among nursing university colleagues: a multicenter descriptive study

BackgroundClimate change, a pervasive global phenomenon, exerts discernible impacts on the physical, social, and psychological dimensions of well-being. The apprehension surrounding this complex environmental issue has reached a critical juncture, with over 76,000 individuals across more than thirty nations expressing profound levels of concern, characterizing their anxiety as either "very" or "extremely" pronounced. This surge in awareness regarding the potential consequences of climate change has given rise to an emergent and escalating challenge known as climate anxiety. This distinctive form of anxiety manifests through profound feelings of fear, helplessness, and despair elicited by the impending repercussions of climate change. Notably, the intersection of climate anxiety with occupational domains, particularly within the context of Nursing University Colleagues, suggests a nuanced relationship with job engagement, wherein the psychological responses to climate change may influence professional commitment and involvement.Aim of the studyTo examine the correlation among Climate Anxiety, Environmental Attitude, and Job Engagement among Nursing University Colleagues comprising eight distinct nursing faculties.DesignA multicenter descriptive, cross-sectional research design study followed.SubjectThree hundred fifty-nine participants from the Centre, Delta, West, Suez Canal, and Upper regions of Egypt using a stratified random cluster sampling technique.MeasurementsSocial and health related to climate data structured questionnaire, climate anxiety scale, environmental attitude inventory, and job engagement scale.ResultsThe influence of demographics on climate anxiety, environmental attitude, and job involvement was not observed. Nevertheless, geographical variations emerged as a noteworthy factor. A statistically significant inverse correlation was identified between climate anxiety, job engagement dimensions, and the overall score of environmental attitudes.ConclusionClimate anxiety was strongly associated with environmental attitudes and job engagement among nursing university colleagues. Higher climate anxiety is associated with a lower attitude towards the environment and decreased job engagement. Additionally, a higher attitude towards the environment is associated with decreased overall engagement in participants’ jobs.ImplicationsThe study's patterns make it clear how important it is to provide targeted psycho-educational interventions to help reduce climate anxiety among the group of nursing university colleagues. The imperative lies not only in alleviating the immediate psychological distress associated with heightened climate anxiety but also in fostering adaptive coping mechanisms. By doing so, these interventions serve as instrumental tools in nurturing resilience, thereby fortifying the mental well-being of nursing professionals amidst the evolving landscape of climate-related concerns.