bluuebunny/crossref_metadata_2025 huggingface dataset:
Manuscripts on the Warfare from the Collection of the Asiatic Museum
Authors: Zaitseva D. V.
Published: February 2024

In the article a short survey of ϐive works on warfare from the collection of the Institute of Oriental Manuscripts of the Russian Academy of Sciences is given. Those manuscripts were received by the Asiatic Museum (AM) from AD 1825 to AD 1934 and originate in such well-known collections, as that of J.-B. L. J. Rousseau, the Library of the Institute of Oriental Languages of the Ministry of Foreign Affairs, the Lake Van gathering. The latest receipt took place from the Archaeographic Mission of the Institute of Oriental Studies of the Academy of Sciences of the USSR in the Volga region. The copy known ubder shelf-mark C 686 was a donation of the Russian diplomat Apollinaire P. Bouteneff (AD 1834). The main goal of the article consists in formulating the most complete idea of time and circumstances of entering the above-mentioned works into the collection of the AM, of the history of their occurrence and in creating the codicological description of every manuscript on the basis of materials and documents from the Archives of Orientalists of the Institute of Oriental Studies of the Russian Academy of Sciences and St. Petersburg Branch of the Archives of the Russian Academy of Sciences, including those which have not been published yet.
The History by Shanbal as the Earliest Specimen of the Historiography of Hadramawt
Authors: Khamidova N. S.
Published: February 2024

The historiographical tradition of Hadramawt, the autonomous historical and cultural region of South Arabia, began its formation in the IX/XV century. The works of Hadramawt historiography appeared in great numbers following “The History of Hadramawt” by Ahmad bin ‘Abdullah Shanbal. “The History of Hadramawt» belongs to the biographical genre of narrative characterized by a concise form of reporting. It was under the inϐluence of Muslim law and, to a lesser extent, theology, that the history of various branches of knowledge was compiled as a collection of biographies of authoritative ϐigures. Thus, the genre of biography in Arab-Muslim historiography became the most enduring of all forms of historical expression. Shanbal through the prism of biographies of ulems, fakikhs, qadis, rulers and commanders gave us the basis for constructing the history of medieval Hadramawt. This article identiϐies features of the Hadramawt historiographic tradition based on an analysis of the text of Ahmad bin ‘Abdullah Shanbal’s work. In compiling his chronicle, Shanbal apparently relied on Ba Hasan, Ba Shurahbil, ‘Abd al-Rahman al-Khatib, Ba Makhrama, genealogies and family hagiologies of sayyids and mashayyih.
On the question of dating Arabic texts on papyrus and paper
Authors: Trepnalova E. V.
Published: February 2024

Dating is one of the most important stages of working with a document, along with its deciphering. When working with Arabic documents on papyrus and paper, we do not have information about their provenance, or whether they were part of an archive. Their often poor preservation does not increase a researcher’s chances of dating the document at least within a century as well. Conditionally dividing the dating mechanisms into “external” and “internal,” we can argue that prosopography provides the most accurate data about when the document was written; the formulas and structure of documents may indicate a certain historical period; paleographic analysis provides the least accurate data. Based on paleographic data, documents on papyrus are tentatively dated to the 3rd/9th century, and documents on paper - to the period from the 4th/10th to the 7th/13th centuries.
The Dispute between the Nestorian Patriarch Timothy I and the Caliph al-Mahdi: Versions, Manuscripts, Editions and Translations
Authors: Khizhniakova S. O.
Published: February 2024

This paper serves as an introduction to the forthcoming translation of the disagreement between Patriarch Timothy I of the Church of the East and the Abbasid Caliph al-Mahdi. It provides the historical context of the text, discusses the importance of the debate for the study of Arab-Muslim polemics, and explores its dating. Author provided additional information about Syriac and Arabic manuscript traditions and presented an updated stemma of these manuscripts containing the dialogue text. Additionally, she thoroughly reviewed editions and translations of the dispute in both Syriac and Arabic, and systematically analyzed differences between all existing versions. A general comparison is presented between the Syrian original and the nearest Arabic translation, which serve as the foundational versions of this text.
The situation of the Russian Palestine Society in the second half of the 1920s based on materials from the Archive of Orientalists of the Institute of Oriental Studies of the Russian Academy of Sciences
Authors: Rozov V. A.
Published: February 2024

The activities of the Russian Palestine Society after its restoration in 1926 faced numerous problems that were of chronic and systemic character. The lack of its own location, limited access to its archive, insufϐicient funding, and lack of foreign travel presented great difϐiculty for the Society and its members. The article provides archival materials, which illustrate these problems. Based on the analysis of the Archival materials, one could conclude that all the difϐiculties originated from the reluctance of Soviet authorities to provide support to the Society. As a result, the research activity of the Society in the 1930s was curtailed. It resumed only in the 1950s in connection with the growing role of the Palestine question in the post-war politics. Due to the lack of funds and stagnation the scholarly potential of the Society, as well as valuable research projects, had already been lost. The lack of potentially important results could not positively contribute to the assessment of the political situation in the Middle East in the second half of the 20th century.
Nāṣir Xusraw and his Rawšanā’ī-nāmа (“The Book of Enlightenment”) (beyts 456–590). Translation from Persian into Russian, comments and introduction
Authors: Prigarina N. I. , Shakarbekova M. A.
Published: February 2024

This article contains a commentary translation of the final parts of the poem Rawshanā’i-nama (bayts 456–590) by the outstanding poet and philosopher of the 11th century, Isma’ili preacher Nasir Xusraw Kubadiyani. The previous parts of the poem were published at different times, the last two in the journal Orientalistica for 2020 and 2022. The translation is based on the Tehran edition of 2001. Combining all parts of the translation into a single text is a matter of the future, especially since over the years of work the translators’ vision of the text and understanding of its meaning in the history of Persian literature and philosophy has undergo definite changes. Nevertheless, the appearance of a complete translation — the first in Russian and still not available in Western languages — will expand the perception of the of Nasir Xusraw’s work and then may be useful not only to narrow specialists. The translation is provided with the possibly complete commentary on the text, but leaves outside its interpretation. The text is preceded by an introductory article concerning a discussion of some aspects of the implication of religious and philosophical views in poetic narrative aimed at “education of morals” and “improvement of the soul”.
Effectiveness of Employing the English Language as a Medium of Instruction in ESL Learning in the Pakistani Educational System
Authors: Jeevan Salma , Maitlo Sonal Khan , Jalbani Athar Nawaz
Published: February 2024

The present research was an effort to explore the effectiveness of the English language as a medium of instruction in ESL learning in the Pakistani educational system. By using a quasi-experimental research design a purposive sample of 72 students equally from both genders was selected from the population of a government primary school in district Kasur. Pretest and posttest were used as research instrumentation. The ESL learners were separated equally into 2 groups termed experimental and control groups. Each group contained 18 male and 18 female ESL learners. The first one was trained in the old-style method while the second one was treated by employing the English medium of instruction for all subjects. The treatment was given for two months. The results of the pretest and post-test showed a significant difference between the scores of both groups. The results revealed that English as a medium of instruction is better for ESL learning.
Role of Collaborative Strategies in Enhancing ESL Learners' Motivation: A Critical Discourse Analysis
Authors: Jalalzai Nargis Noor , Jameel Mehwish , Ranra Bibi
Published: February 2024

This study investigates the role of Collaborative Strategies in enhancing ESL learners' motivation. Through critical discourse analysis, three key strategies emerge - group projects and cooperative learning, interactive language games and simulations, and encouraging peer feedback and assessment. These strategies align with sociocultural theory, gamification, task-based language teaching, and social learning theory. The findings reveal that these Collaborative Strategies positively influence ESL learners' motivation, fostering a deeper commitment to language learning and promoting language proficiency and communication skills. The study offers valuable insights for teachers and policymakers to optimize ESL education, creating an empowering and engaging learning environment that empowers ESL learners for a brighter future in an interconnected world.
Tajikistan-Kyrgyzstan Conflict: Causes and Pathways to Peace
Authors: Shahid Muneeba , Ashfaq Kashif , Ishfaq Uroosa
Published: February 2024

The undefined frontiers in Central Asia have long been a source of conflict. There is a lengthy and complicated history of the Tajik-Kyrgyz war. Despite being about 1000 km long, only about half of the border between the two states has been marked since 1991. This article explains the reasons for the war between two former Soviet Socialist States. And the role of Russia in this scenario. Also, this research will come up with some policy suggestions to resolve this border dispute between two neighboring states. The long-standing disagreement over the boundaries became a major reason for the war. Due to the violent situation of both states, many clashes erupted in the region which became a reason for the loss of a huge number of people.
CYBERSECURITY: RESEARCH ON METHODS FOR DETECTING DDOS ATTACKS
Authors: CHORNOBUK Maksym , DUBROVIN Valeriy , DEINEHA Larysa
Published: February 2024

This article describes the problem of DDoS attacks, analyzing their nature and consequences. The paper covers common DDoS attack types, such as SYN flood, ICMP flood, UDP flood. Existing methods for detecting attacks from literature are reviewed, including machine learning approaches, including artificial neural networks, support vector machines and decision trees. The paper introduces a decision tree-based machine learning model for the detection of DDoS attacks. The model is trained and tested on a publicly available dataset. The dataset consists of 1,04,345 rows of data, where every row includes 23 features, such as source IP, destination IP, port number, number of bytes transferred from the switch port, etc. A similar set of characteristics can be obtained on a real network hardware using simple calculations, which makes it possible to approximate the model evaluation to real operating conditions. SYN flood, ICMP flood and UDP flood attack types are present in the data, as well as legitimate traffic. To avoid overfitting, only some columns were used, and columns such as IP addresses were discarded. The field “label” in each row of the dataset contains either 0 or 1 where 0 corresponds to legitimate traffic and 1 to malicious one. The problem of DDoS attack detection is therefore formally reduced to the task of binary classification of each row from the dataset. The constructed model achieves an average classification accuracy of 0.94 with a standard deviation at the level of 0.06 in detecting the above mentioned types of attacks. To objectively assess the effectiveness of the model and avoid distortion of the results, stratified 5-fold cross-validation was used. The developed model can be applied in the real world network hardware to filter malicious packets or as a tool for warning the administrator about an attack. This research advances cybersecurity by enhancing DDoS attack detection.
CONNECTIONIST-METAHEURISTIC APPROACH TO THE ANALYSIS OF THE GLOBAL ECONOMY’S INVESTMENT ENVIRONMENT INDICATORS
Authors: LESHCHENKO Maryna , FEDOROV Eugen , KIBALNYK Liubov , DANYLCHUK Hanna
Published: February 2024

The connectionist-metaheuristic approach solved the urgent task of using new approaches to analyze the foreign direct investment and macroeconomic indicators that affect the volume of their attraction to a particular country in the world economy. The proposed connectionist-metaheuristic system makes it possible to improve the quality of the approximation due to: the simplification of structural identification through the use of only one hidden layer of neural network models; reduction of the computational complexity of parametric identification and the ensuring good scalability through the use of batch mode for non-recurrent neural network models and multi-agent metaheuristics for recurrent neural network models; descriptions of non-linear dependencies through the use of neural network models; high approximation accuracy due to the use of recurrent neural network models; resistance to data incompleteness and data noise due to the use of metaheuristics for parametric identification of recurrent neural network models; lack of requirements for knowledge of distribution, homogeneity, weak correlation, and optimal factors’ choice. In the case of a GPU, an LSTM-based neural network with the highest approximation accuracy should be chosen. For LSTM, the coefficient of determination using the gradient method is 0.785, and using metaheuristics (modified wasp colony optimization) is 0.835. The proposed approach makes it possible to expand the scope of approximation methods’ application based on artificial neural networks and metaheuristics, which is confirmed by its adaptation for an economic problem and contributes to an increase in intelligent computer systems efficiency for general and special purposes.
Pengendalian Intern Pendapatan Pada Layanan Jasa Pospay Loket PT Pos Indonesia KCU Jember
Authors: Umattul Khoiriyah Julaikha , Reviandani Wasti
Published: February 2024

Efficient internal control is essential for companies. The main objective of internal control is to build efficient control systems within a company or organisation to improve operational procedures. The aim of this study is to determine the payment system and methods for bill payment utilising Pospay in order to improve internal control. Furthermore, it aims to examine the calibre of Pospay services provided by PT Pos Indonesia KCU Jember and evaluate the internal control mechanisms implemented for funds produced from Pospay counter services. This study utilises descriptive qualitative research approaches. Data or information collection procedures are executed by the process of observation, interviews, and documentation to authenticate the obtained information or data.
Exploring the lived experiences and perspectives of individuals with communication and swallowing difficulties associated with Long-COVID
Authors: Gilheaney Órla , Rogers Naomi , McTiernan Kathleen
Published: February 2024

BACKGROUND: Long-COVID occurs in individuals with a history of probable or confirmed SARS CoV-2 infection. Long-COVID can affect individuals who experience both mild and severe acute COVID-19 and can involve and affect multiple body systems. Research thus far acknowledges swallowing and communication difficulties as a characteristic of Long-COVID, however, this research lacks detail and does not address the psychosocial impact of these problems. OBJECTIVES: To establish an understanding of the presence, severity, and trajectory of swallowing and communication difficulties as a symptom of Long-COVID among adults. To investigate the psychosocial impact of these characteristics and explore supports and barriers to recovery. METHODS: The objectives were addressed by utilizing a qualitative research design. Semi-structured interviews were carried out with participants using online Zoom sessions. The interviews were recorded and transcribed and reflexive thematic analysis was used to analyse the data. RESULTS: Seven participants from Ireland, Scotland and Australia were interviewed. Four main themes were identified including dysphagia-related issues, communication-related issues, psychosocial impact of dysphagia and communication disorders, and accessing Long-COVID related healthcare for dysphagia and communication disorders. The presentation of swallowing and communication problems was diverse and had significant psychosocial and mental health consequences. Furthermore, access to healthcare services to effectively treat these issues was challenging. CONCLUSIONS: The lack of recognition of swallowing and communication as a symptom of Long-COVID and its adverse effects is a pertinent issue which warrants further research and updated guidelines for individuals living with Long-COVID and healthcare professionals alike.
Characteristics of Changes in Caregiver Burden during Follow-up at a Memory Clinic: A Retrospective Cohort Study
Authors: Takechi Hajime , Yoshino Hiroshi , Suzuki Megumi , Maeda Akiko , Suzumura Shota , Kamiya Eiko
Published: February 2024

Background:

Because dementia is a long-term condition, the appropriate involvement of health-care professionals is considered important. However, little is known about the factors associated with changes in family caregiver burden.

Objective:

To clarify changes in family caregiver burden and associated factors during follow-up at a memory clinic.

Methods:

A retrospective cohort study was conducted, enrolling 495 pairs of patients with dementia or mild cognitive impairment and their family caregivers. A total of 120 pairs completed the second evaluation. The caregiver burden was assessed using the Zarit Burden Interview (ZBI). Data at the initial visit and after an average follow-up of about 2 years were compared and analyzed.

Results:

At initial visit, the patients’ mean age, Mini-Mental State Examination (MMSE) and ZBI scores were 78.6±5.6 years, 23.3±3.5, and 22.6±16.7, respectively. At follow-up, MMSE scores decreased (21.4±4.5, p < 0.001), but ZBI scores remained similar (22.5±13.6). When the difference in ZBI scores between the two time points was defined as ΔZBI, and the related factors were analyzed by multiple regression analysis, ZBI scores at the initial visit, start of psychotropic drug, and decrease of neuropsychiatric symptoms were identified as significant factors ( p < 0.001, p = 0.003, p < 0.001, respectively). A significant negative correlation was found between ZBI scores at the initial visit and ΔZBI ( r = –0.588, p < 0.001).

Conclusions:

These findings suggest the importance of assessing changes in the burden experienced by family caregivers during the disease follow-up.
The Paintings Reveal the Story: Case Study of a Well-Known Swedish Artist Suffering from Alzheimer’s Disease
Authors: Holmbom Larsen Axel , Londos Elisabet
Published: February 2024

Background:

Creativity is a multifaceted, complex, activity, and as such is an overarching function of the brain rather than being confined to a specific structure or region. Alzheimer’s disease effects several cognitive domains involved in the creative process of producing art.

Objective:

We analyze the art of a well-known Swedish visual artist who suffered from Alzheimer’s disease to determine if, and in what way, his art and creative process might have been influenced by the disease.

Methods:

We compared his artistic process and artwork along with information from his spouse, medical r ecords, and cognitive tests as well as reviews of exhibitions written by art critics.

Results:

We show that not only did the artist continue to produce artwork well into a major decline in cognitive function, according to commonly used tests, but he could continue to do so for even longer with some assistance from his spouse. However, the artwork changed considerably as the disease progressed. We hypothesize that there is a substantial lack of representation of creative ability and function in cognitive tests.

Conclusions:

Signs of the Alzheimer’s disease can be seen in the early artwork if viewed by critics and those with more specialized knowledge into the artist’s production. Further analysis of the complex interaction between complex neural activities, such as artistic creativity, and cognitive diseases is warranted and might provide insight in the field of neurological degenerative disease.
Quantitative MRI Evidence for Cognitive Reserve in Healthy Elders and Prodromal Alzheimer’s Disease
Authors: Fingerhut Hannah , Gozdas Elveda , Hosseini S.M. Hadi
Published: February 2024

Background: Cognitive reserve (CR) has been postulated to contribute to the variation observed between neuropathology and clinical outcomes in Alzheimer’s disease (AD). Objective: We investigated the effect of an education-occupation derived CR proxy on biological properties of white matter tracts in patients with amnestic mild cognitive impairment (aMCI) and healthy elders (HC). Methods: Educational attainment and occupational complexity ratings (complexity with data, people, and things) from thirty-five patients with aMCI and twenty-eight HC were used to generate composite CR scores. Quantitative magnetic resonance imaging (qMRI) and multi-shell diffusion MRI were used to extract macromolecular tissue volume (MTV) across major white matter tracts. Results: We observed significant differences in the association between CR and white matter tract MTV in aMCI versus HC when age, gender, intracranial volume, and memory ability were held constant. Particularly, in aMCI, higher CR was associated with worse tract pathology (lower MTV) in the left and right dorsal cingulum, callosum forceps major, right inferior fronto-occipital fasciculus, and right superior longitudinal fasciculus (SLF) tracts. Conversely higher CR was associated with higher MTV in the right parahippocampal cingulum and left SLF in HC. Conclusion: Our results support compensatory CR mechanisms in aMCI and neuroprotective mechanisms in HC and suggest differential roles for CR on white matter macromolecular properties in healthy elders versus prodromal AD patients.
Diabetic Retinopathy Predicts Risk of Alzheimer’s Disease: A Danish Registry-Based Nationwide Cohort Study
Authors: Pedersen Frederik Nørregaard , Stokholm Lonny , Pouwer Frans , Hass Rubin Katrine , Peto Tunde , Frydkjær-Olsen Ulrik , Thykjær Anne Suhr , Andersen Nis , Andresen Jens , Bek Toke , La Cour Morten , Heegaard Steffen , Højlund Kurt , Kawasaki Ryo , Hajari Javad Nouri , Ohm Kyvik Kirsten , Laugesen Caroline Schmidt , Schielke Katja Christina , Simó Rafael , Grauslund Jakob
Published: February 2024

Background: Retinal neurodegeneration is evident in early diabetic retinopathy (DR) which may be associated with other neurodegenerative diseases like Alzheimer’s disease (AD). Objective: To investigate diabetes and DR as a risk marker of present and incident AD. Methods: A register-based cohort study was performed. We included 134,327 persons with diabetes above 60 years of age, who had attended DR screening, and 651,936 age- and sex-matched persons without diabetes. Results: At baseline, the prevalence of AD was 0.7% and 1.3% among persons with and without diabetes, respectively. In a multivariable regression model, persons with diabetes were less likely to have AD at baseline (adjusted OR 0.63, 95% CI 0.590.68). During follow-up, incident AD was registered for 1473 (0.35%) and 6,899 (0.34%) persons with and without diabetes, respectively. Compared to persons without diabetes, persons with diabetes and no DR had a lower risk to develop AD (adjusted HR 0.87, 95% CI 0.810.93), while persons with diabetes and DR had higher risk of AD (adjusted HR 1.24, 95% CI 1.081.43). When persons with diabetes and no DR were used as references, a higher risk of incident AD was observed in persons with DR (adjusted HR 1.34, 95% CI 1.181.53). Conclusion: Individuals with diabetes without DR were less likely to develop AD compared to persons without diabetes. However, individuals with DR had a 34% higher risk of incident AD, which raise the question whether screening for cognitive impairment should be done among individuals with DR.
Longitudinal Patterns of Brain Changes in a Community Sample in Relation to Aging and Cognitive Status
Authors: Chwa Won Jong , Lopez Oscar L. , Longstreth Jr W.T. , Dai Weiying , Raji Cyrus A.
Published: February 2024

Background: Aging and Alzheimer’s disease (AD) are characterized by widespread cortical and subcortical atrophy. Though atrophy patterns between aging and AD overlap considerably, regional differences between these two conditions may exist. Few studies, however, have investigated these patterns in large community samples. Objective: Elaborate longitudinal changes in brain morphometry in relation to aging and cognitive status in a well-characterized community cohort. Methods: Clinical and neuroimaging data were compiled from 72 participants from the Cardiovascular Health Study-Cognition Study, a community cohort of healthy aging and probable AD participants. Two time points were identified for each participant with a mean follow-up time of 5.36 years. MRI post-processing, morphometric measurements, and statistical analyses were performed using FreeSurfer, Version 7.1.1. Results: Cortical volume was significantly decreased in the bilateral superior frontal, bilateral inferior parietal, and left superior parietal regions, among others. Cortical thickness was significantly reduced in the bilateral superior frontal and left inferior parietal regions, among others. Overall gray and white matter volumes and hippocampal subfields also demonstrated significant reductions. Cortical volume atrophy trajectories between cognitively stable and cognitively declined participants were significantly different in the right postcentral region. Conclusion: Observed volume reductions were consistent with previous studies investigating morphometric brain changes. Patterns of brain atrophy between AD and aging may be different in magnitude but exhibit widespread spatial overlap. These findings help characterize patterns of brain atrophy that may reflect the general population. Larger studies may more definitively establish population norms of aging and AD-related neuroimaging changes.
Recent Advances in Nanomaterials-Based Adsorbents for Organophosphorus Contaminant Removal in Water: An Overview
Authors: Rudi Faris , Abu Bakar Nor Kartini , Mohd Kassim Noor Azilah , Knight Victor Feizal , Shukor Muhammad Faizan A. , Norrrahim Mohd Nor Faiz
Published: February 2024

The presence of organophosphorus contaminants (OPCs) in water is a major concern due to their toxicity and adverse effects on human health and the environment. Traditional water treatment methods such as coagulation, sedimentation, and filtration are not always effective in removing OPCs from water, making it necessary to explore alternative methods. Nanomaterials, due to their unique physical, chemical and biological properties, have emerged as promising adsorbents for the removal of OPCs from water. This review article focusses on the recent developments in the use of nanomaterials as adsorbents for the removal of OPCs from water. The article covers various types of nanomaterials, including carbon-based nanomaterials, metal-based nanomaterials and other hybrid nanomaterials. The mechanisms of OPC adsorption by nanomaterials, such as electrostatic interactions, hydrogen bonding, and Van der Waals forces, are also discussed. The article further highlights the factors affecting the adsorption capacity of nanomaterials, such as pH, temperature, and concentration of OPCs. Additionally, the article examines the challenges associated with the application of nanomaterials in water treatment, such as the potential release of nanomaterials into the environment and the need for cost-effective and scalable synthesis methods.
Synthesis of a Green Adsorbent Surface Gels: Development of Ratio Preparation of Polymer SA/Bentonite Bead, and its Industrial Applications for Removal of Aqueous Pollutants
Authors: Mossa Zaied A. , Mohammed Faris Hamood , Aljeboree Aseel M. , Alkaim Ayad F.
Published: February 2024

In this research, polymer gels sodium alginate/bentonite clay adsorbent beads (SA/Ben) were prepared via encapsulating natural bentonite (Bn) in sodium alginate (SA). The ratio of Polymer Gels SA/Bn was used during preparation bead to yield beads (1/1 w/w), SA-Bn2 (1/2 w/w), and SA-Bn3 (1/3 w/w), respectively. These adsorbents were characterized via different characterisation FESEM, TEM, XRD and EDX to give high confidence of the prepared surface. The adsorption of Clonazepam drug (CLZ) from aqueous solution on the SA/Bn beads was investigated as a function of different factors, including the initial concentration of CLZ, the weight of SA/Bn beads gel, pH solution, temperature of solution and equilibrium time. Adsorption models of Langmuir and Freundlich isotherms were applied and were found to be well described via the isotherm of Freundlich model. The results showed that among the three types of prepared surfaces SA/Bn beads, SA-Bn1 presented the greatest CLZ adsorption capacity. Thermodynamic parameters were calculated including change free of Gibbs energy (ΔG), change entropy (ΔS), and change enthalpy. The change enthalpy of CLZ drug adsorption was found to be positive for the SA/Bn bead and the reaction of adsorption spontaneous and exothermic. After the adsorption proses the SA/Bn beads can easily be regenerated via water and re-used within four cycles.
The Cause and Effects of a Sudden Blackening of the River Kameng/Jiya Bharali in October 2021
Authors: Baroi S. , Ali A.A. , Saikia R. , Das T. , Baishya S. , Dutta R.K.
Published: February 2024

A disastrous sudden blackening of the river Kameng in Arunachal Pradesh, known as the river Jiya Bharali in Assam, was studied to find its cause and effects. The water of the river suddenly turned turbid and black on October 29, 2021, causing a large-scale death of fish for several days creating panic among the surrounding people. Samples of water and sediment were collected from different locations of the river and were analysed. The results indicate an increase in TSS consisting of aluminosilicates and oxides of Fe, Mn, Co, Ni, etc., mixed with water due to landslides. Coloured metal oxides were found to cause the blackening while toxicity and suffocation due to excess of suspended microscopic particles may have led to the death of fish. Preventive and curative measures for the disaster have been suggested.
Risk of Ceftriaxone (Antibiotic) in the Tigris River Water, Iraq
Authors: Al-Sudani Ibrahim , Abed Al-Razzaq Hamsa , Audy Roaa , Al-Khayat Asmaa
Published: February 2024

There are several causes of hemolytic diseases, such as viral or bacterial contamination, enlarged spleen, and typhoid fever, which can be transmitted through contaminated water. Polluted wastewater samples were collected for the period of June-2022 to (May-2023) from five stations in Baghdad City such as Al- Gureat, Al-Ahdamyah, Bab Al-Muhadum, Bab Al-Sharqy and Al-Jadryah stations on the Tigris Riverbanks for the studying of Ceftriaxone antibiotic risk. The concentrations of ceftriaxone have been detected using high-performance liquid chromatography (HPLC). The results reveal that concentrations of ceftriaxone in the water fluctuated via sampling stations and seasons; so the highest concentration was 8 × 10-5 ppm in site 2 at Ahdamyah station, while the lowest concentrations was 1 × 10-7 ppm in site 5 sites at Al-Jadryah station during wet season 2023. The results of the statistical analysis showed that there were no significant differences between the study stations, except for the control station. The detection of ceftriaxone in raw surface water confirms that sewage from health institutions reaches the river without any effective treatment.
Speech Acts as a Window to the Difficulties in Instrumental Activities of Daily Living: A Qualitative Descriptive Study in Mild Neurocognitive Disorder and Healthy Aging
Authors: Filiou Renée-Pier , Brambati Simona Maria , Lussier Maxime , Bier Nathalie
Published: February 2024

Background:

Executive functions (EF) are central to instrumental activities of daily living (IADL). A novel approach to the assessment of the impact of EF difficulties on IADL may be through the speech acts produced when performing IADL-inspired tasks in a laboratory-apartment. Speech acts may act as a window to the difficulties encountered during task performance.

Objective:

We aim to 1) qualitatively describe the speech acts produced by participants with mild neurocognitive disorder (mild NCD) and healthy controls (HC) as they performed 4 IADL-inspired tasks in a laboratory-apartment, and to then 2) compare their use in both groups.

Methods:

The participants’ performance was videotaped, and speech acts produced were transcribed. Qualitative description of all speech acts was performed, followed by a deductive-inductive pattern coding of data. Statistical analyses were performed to further compare their use by mild NCD participants and HC.

Results:

Twenty-two participants took part in the study (n mild NCD = 11; n HC = 11). Meta-categories of data emerged from pattern coding: strategies, barriers, reactions, and consequences. Mild NCD participants used significantly more strategies and barriers than did HC. They were more defensive of their performance, and more reactive to their difficulties than HC. Mild NCD participants’ verification of having completed all tasks was less efficient than controls.

Conclusions:

An assessment of speech acts produced during the performance of IADL-inspired tasks in a laboratory-apartment may allow to detect changes in the use of language which may reflect EF difficulties linked to cognitive decline.
Review of the potential benefits and challenges of artificial intelligence in clinical laboratory
Authors: Tiwade Yugeshwari R. , Bankar Nandkishor , Mishra Vaishnavi , Sajjanar Anita
Published: February 2024

Over the past few years, medical artificial intelligence (AI) has been extensively utilized within the healthcare industry. However, the deployment of AI raises complicated social and ethical issues related to security, privacy, and human rights. While the use of artificial intelligence (AI) has the potential to improve healthcare outcomes and operational efficiency, this article gives a detailed assessment of current cutting-edge AI breakthroughs in clinical laboratories. It focuses on the potential benefits of AI and its application in clinical laboratory. The use of AI in clinical laboratory is rapidly growing, with the potential to alter patient care in the near future. Furthermore, it has the potential to democratize modern laboratory services, making them available to people all around the world.
Multi-objective hybrid job-shop scheduling with multiprocessor task (HJSMT) problem with cooperative effect
Authors: Fan Kun , Zhang Dingran , Lv Yuanyuan , Zhou Lang , Qu Hua
Published: February 2024

In order to solve the problem of discrete manufacturing customization and personalized production scheduling, considering the influence of manual labor on processing time, we propose a multi-objective Hybrid Job-shop Scheduling with Multiprocessor Task(HJSMT) problem with cooperative effect model. Based on the actual production, two optimization objectives are set, i. e. minimizing the maximum completion time and the total tardiness. Firstly, considering the situation where workers’ cooperation reduces job processing time, the cooperative effect of workers co-processing is considered by referring to the learning effect curve in the model. Subsequently, we develop an Improved Non-dominated Sorting Genetic Algorithm-II (INSGA-II) to solve the multi-objective HJSMT problem by improving Precedence Operation Crossover (POX) and Multiple Mutations (MM) operations. Finally, the scheduling results and the C values are compared with other algorithms to verify the effectiveness of the algorithm. Simultaneously, the multi-objective HJSMT problem with the cooperative effect is solved by the INSGA-II algorithm, and the experimental results also demonstrate the superior performance of the algorithm.
Multi-attribute three-way decision making based on interval-valued intuitionistic fuzzy sets
Authors: Xiao Yongxia , Tang Xiao
Published: February 2024

In the interval-valued intuitionistic fuzzy environment, a new multi-attribute three-way decision-making model is proposed to address the problems that the relative loss function in the existing multi-attribute three-way decision-making model does not consider the degree of hesitancy, and the alternative conditional probabilities are given subjectively by the authors, which lacks objectivity. First, three types of ideal solutions are introduced, and the correlation coefficients between the evaluated values and ideal solutions are utilized to construct alternative relative loss functions. Second, the ELECTRE-I method is generalized to the interval-valued intuitionistic fuzzy environment to establish the outranking relation and a method for estimating the conditional probability of alternatives is given. Finally, the model is used to experimentally analyze examples to illustrate the effectiveness and rationality of the model.
A novel bilateral stream neural network for melt pool monitoring during laser direct energy deposition
Authors: Wang Zhongan , Li Honghai , Pang Minghao , Wu Yingna , Yang Rui , Wu Zhiwei , Cai Guoshuang
Published: February 2024

Detection and classification methods for the melt pool state in laser direct energy deposition (L-DED) can significantly help predict defects and mechanical properties of L-DED metal parts. Although traditional machine learning algorithms based on physical modeling methods and convolutional neural networks have recently been introduced into melt pool state identification, these methods rely on complex artificially designed features or cannot simultaneously detect defects in multiple dimensions. In this paper, a novel bilateral stream neural network was designed for melt pool identification, which performs defect identification in two label dimensions simultaneously. Two sets of single-channel experiments were designed to collect the dataset captured by a high-speed camera. By cutting the metal parts and marking them with professional equipment operated by professionals, the dataset was labeled according to the bonding condition and dilution rate criteria. Without an additive model structure, the model achieved 95.2% accuracy in identifying defects in the bonding condition and 92.8% in determining deficiencies in the dilution rate. In order to explain the identification mechanism of the model, the CAM method was utilized for the visual display of the model recognition process, which provides a potential application solution for the online monitoring method of the L-DED.
High utility itemsets mining based on hybrid harris hawk optimization and beluga whale optimization algorithms
Authors: Gao Zhihui , Han Meng , Liu Shujuan , Li Ang , Mu Dongliang
Published: February 2024

The commonly used high utility itemsets mining method for massive data is the intelligent optimization algorithm. In this paper, the WHO (Whale-Hawk Optimization) algorithm is proposed by integrating the harris hawk optimization (HHO) algorithm with the beluga whale optimization (BWO) algorithm. Additionally, a whale initialization strategy based on good point set is proposed. This strategy helps to guide the search in the initial phase and increase the diversity of the population, which in turn improve the convergence speed and algorithm performance. By applying this improved algorithm to the field of high utility itemsets mining, it provides new solutions to optimization problems and data mining problems. To evaluate the performance of the proposed WHO, a large number of experiments are conducted on six datasets, chess, connect, mushroom, accidents, foodmart, and retail, in terms of convergence, recall rates, and runtime. The experimental results show that the convergence of the proposed WHO is optimal in five datasets and has the shortest runtime in all datasets. Compared to PSO, AF, BA, and GA, the average recall rate in the six datasets increased by 32.13%, 49.95%, 12.15%, and 16.24%, respectively.
Text summarization using modified generative adversarial network1
Authors: Srivastava Jyoti , Srivastava Ashish Kumar , Muthu Kumar B. , Anandaraj S.P.
Published: February 2024

Text summarizing (TS) takes key information from a source text and condenses it for the user while retaining the primary material. When it comes to text summaries, the most difficult problem is to provide broad topic coverage and diversity in a single summary. Overall, text summarization addresses the fundamental need to distill large volumes of information into more manageable and digestible forms, making it a crucial technology in the era of information abundance. It benefits individuals, businesses, researchers, and various other stakeholders by enhancing efficiency and comprehension in dealing with textual data. In this paper, proposed a novel Modified Generative adversarial network (MGAN) for summarize the text. The proposed model involves three stages namely pre-processing, Extractive summarization, and summary generation. In the first Phase, the Text similarity dataset is pre-processed using Lowering Casing, Tokenization, Lemmatization, and, Stop Word Removal. In the second Phase, the Extractive summarization is done in three steps Generating similarity metrics, Sentence Ranking, and Sentence Extractive. In the third stage, a generative adversarial network (GAN) employs summary generation to jointly train the discriminative model D and the generative model G. To classify texts and annotate their syntax, Generative Model G employs a convolutional neural network called Bidirectional Gated Recursive Unit (CNN-BiGRU). The performance analysis of the proposed MGAN is calculated based on the parameters like accuracy, specificity, Recall, and Precision metrics. The proposed MGAN achieves an accuracy range of 99%. The result shows that the proposed MGAN improves the overall accuracy better than 9%, 6.5% and 5.4% is DRM, LSTM, and CNN respectively.
A composite entropy-based uncertainty measure guided attribute reduction for imbalanced mixed-type data
Authors: Shu Wenhao , Li Shipeng , Qian Wenbin
Published: February 2024

In real-world scenarios, datasets generally exhibit containing mixed-type of attributes and imbalanced classes distribution, and the minority classes in the data are the primary research focus. Attribute reduction is a key step in the data preprocessing process, but traditional attribute reduction methods commonly overlook the significance of minority class samples, causing the critical information possessed in minority class samples to damage and decrease the performance of classification. In order to address this issue, we develop an attribute reduction algorithm based on a composite entropy-based uncertainty measure to handle imbalanced mixed-type data. To begin with, we design a novel oversampling method based on the three-way decisions boundary region to synthesize the samples of minority class, for the boundary region to contain more high-quality samples. Then, we propose an attribute measure to select candidate attributes, which considers the boundary entropy, degree of dependency and weight of classes. On this basis, a composite entropy-based uncertainty measure guided attribute reduction algorithm is developed to select the attribute subset for the imbalanced mixed-type data. Experimental on UCI imbalanced datasets, as well as the results indicate that the developed attribute reduction algorithm is significantly outperforms compared to other attribute reduction algorithms, especially in total AUC, F1-Score and G-Mean.
An efficient hybrid bert model for brain tumor classification
Authors: Selvin Prem Kumar S. , Agees Kumar C. , Venugopal Anita , Sharma Aditi
Published: February 2024

The central nervous system can develop complex and deadly neoplastic growths called brain tumors. Despite being relatively uncommon in comparison to other cancers, brain tumors pose particular challenges because of their delicate anatomical placement and interactions with critical brain regions. The data are taken from TCIA (The Cancer Image Archive) and Kaggle Datasets. Images are first pre-processed using amplified median filter techniques. The pre-processed images are then segmented using the Grabcut method. Feature extraction is extracted using the Shape, ABCD rule, and GLCM are the features were retrieved. The MRI images are then classified into several classes using the Bi-directional Encoder Representations from Transformers-Bidirectional Long Short Term Memory (BERT-Bi-LSTM) model. Kaggle and TICA datasets are used to simulate the proposed approach, and the results are evaluated in terms of F1-score, recall, precision and accuracy. The proposed model shows improved brain tumour identification and classification. To evaluate the expected technique’s efficacy, a thorough comparison of the current techniques with preceding methods is made. The trial results showed that an efficient hybrid bert model for brain tumor classification suggested strategy provided precision of 98.65%, F1-score of 98.25%, recall of 99.25%, and accuracy of 99.75%.
Safety assessment of marine high-end equipment based on evidential reasoning approach under fuzzy uncertainty
Authors: Zhou Mi , Xiong Xue-Di , Pei Feng
Published: February 2024

Marine high-end equipment reflects a country’s comprehensive national strength. The safety assessment of it is very important to avoid accident either from human or facility factors. Attribute structure and assessment approach are two key points in the safety assessment of marine high-end equipment. In this paper, we construct a hierarchical attribute structure based on literature review and text mining of reports and news. The hierarchical attribute structure includes human, equipment, environment and management level. The correlations among these attributes are analyzed. The assessment standards of attributes are described in details. Different evaluation grades associated with attributes are transformed to a unified one by the given rules. As for the assessment approach, the evidential reasoning approach is applied for uncertain information fusion. Group analytical hierarchical process is used to generate attribute weights from a group of experts, where process aggregation method and result aggregation method are combined in a comprehensive way. The importance of expert is computed by the uncertainty measure of expert’s subjective judgment. A drilling platform is finally assessed by the proposed attribute structure and assessment approach to illustrate the effectiveness of the assessment framework.