bluuebunny/crossref_metadata_2025 huggingface dataset:
The Future of Adaptive Machine Learning Algorithms in High-Dimensional Data Processing
Authors: Wilson Anne , Anwar Muhammad Rehan
Published: November 2024

This study investigates the potential of adaptive machine learning algorithms for processing high-dimensional data across various fields, directly supporting the advancement of the United Nations Sustainable Development Goals (SDGs) such as healthcare, economic growth, and sustainable cities. The core objectives are to critically review existing methods, tackle the challenges posed by large datasets, and project future developments in adaptive machine learning technologies. Through a comprehensive analysis of diverse algorithms including autoencoders, deep learning, reinforcement learning, and ensemble methods this research evaluates their efficacy in managing the complexities of large-scale data. Results demonstrate that while deep learning models provide the highest accuracy, they also demand considerable computational resources. Conversely, ensemble methods and autoencoders show competitive performance with greater efficiency, although reinforcement learning exhibits adaptability at the cost of reduced scalability. The findings advocate for enhanced focus on improving the efficiency, generalization capabilities, and interpretability of these algorithms to better accommodate the increasing complexity of data-driven environments. Promising applications identified include enhancing diagnostic accuracy in healthcare, optimizing financial analytics, and advancing autonomous system technologies. The study concludes that significant progress in adaptive machine learning will be crucial for achieving SDGs by enabling more effective and efficient data analysis solutions, thereby fostering sustainable development across multiple domains.
Amyloid, A Jekyll and Hyde Molecule, Induces Neuronal Decline and Cognitive Dysfunction but is also a Unique Molecular Template used in Nano-Electronics, Light Capture Photovoltaics, Biosensors and in Neuromorphic Computing
Authors:   Raymond Purves Bone and Joint Research Laboratory, Kolling Institute, St. Leonards, NSW 2065, Australia, M Smith Margaret ,   Arthropharm/Sylvan Scientific Pty Ltd, Bondi Junction,Sydney, NSW 2022, Australia, Melrose James ,   Raymond Purves Bone and Joint Research Laboratory, Kolling Institute, St. Leonards, NSW 2065, Australia,   School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney at Royal North Shore Hospital, St. Leonards, NSW 2065, Australia,   Graduate School of Biomedical Engineering, Faculty of Engineering, University of New South Wales, Sydney, NSW 2052, Australia
Published: November 2024

This study, examined the self-assembly of amyloid peptides β-40 or β-42 to form neurotoxic plaque and neurofibrillary
tangles, neuronal dysfunction and diseases of cognitive decline (e.g. Alzheimer’s, Parkinson’s and Huntington's
disease). However, not all amyloids are toxic, functional amyloids are non-toxic ordered structures that have been
used in tissue engineering applications. Long and hollow amyloid fibres and flattened tube and spiral ribbon-like
structures are diverse self-assembling structures that have found application in the development of next generation
computers and biosensors, ultracapacitors, memristors, actuators, molecular switches, artificial synapses and in
photoelectric photon capture light harvesting technologies in nano-photoelectronics, photovoltaics and photopharmacological drug regulation. Hybrid Aβ(16–22)-α-synuclein amyloid fibrils also exhibits light-harvesting
and electron-transfer properties. Engineered amyloid assemblies are thus driving futuristic developments in nanotechnology. With a better understanding of amyloid fibril assembly clues are also being uncovered as to how the
toxic build up of amyloid deposits in brain tissues and resultant diseases of cognitive decline may be prevented. The
elevated incidence of neurological diseases in the ageing general global population, points to a clear need to find a
remedy for these debilitating conditions.
Chimeric Antigen Receptor (car) Therapy: A Precision Medicine Approach to Rheumatoid Arthritis
Authors:   Medical Microbiology, Department of Medical Microbiology, Medicine Collage, Karbala University, Iraq, Alwaeely Farah A. , AL-Aziz Yousif Zahra'a Abdul ,   Sina University of Medical and Pharmaceutical sciences, Baghdad, Iraq
Published: November 2024

The therapeutic landscape for autoimmune illnesses has been completely transformed by the novel immune cell therapy
that known as (chimeric antigen receptor) T cell (CAR-T) therapy. Many patients do not respond to the current medications,
despite significant advancements in the therapeutic management of autoimmune illnesses. Autoreactive B cells have
a significant role in the development of autoimmune diseases including rheumatoid arthritis. Autoimmune illnesses are
difficult to treat with rituximab and other B-cell-depleting monoclonal antibodies, because autoreactive B cells persist in
inflammatory tissues and lymphatic systems. Adoptive transplantation of T cell that have genetically altered to target the
tumor cells by using chimeric antigen receptors, is one possible treatment option for B-cell malignancies. Autologous CAR
T cell therapy targeting the CD19 antigen has been incorporated into the management of autoimmune illnesses throughout
the past two years. Circulating B cells were rapidly and steadily reduced by CD19 CAR T cells. This study looks at the new
techniques for targeting autoreactive B cells with CAR T cells, which could result in focused treatment for autoimmune
diseases. Notable response including improved the clinical symptoms, lowered autoantibody levels in serum, and prolonged
reductions in progression of the disease. In vitro and preclinical studies using animal as well as human clinical samples
support the important efficacy of CAR-T cells and offer additional information on special mechanisms of action against
rheumatoid arthritis and anti-neutrophil cytoplasmic antibody-associated vasculitis.
Identification of a clinicopathologic prognostic index for newly diagnosed large B cell lymphoma patients treated with R-CHOP
Authors: Ni Vincent , Nasta Sunita D. , Barta Stefan K. , Schuster Stephen J. , Chong Elise A. , Svoboda Jakub , Morrissette Jennifer J.D. , Barlev Ashley , Bagg Adam , Priore Salvatore F. , Landsburg Daniel J.
Published: November 2024

Not available.
Chapter 10 PLANY APROWIZACJI WOJSKA POLSKIEGO W CHLEB NA CZAS WOJNY W 1939 ROKU
Authors: Jasinski Grzegorz Jakub
Published: November 2024

Making use of the literature on the subject, but first and foremost of numerous, hitherto overlooked in research, accounts of the officers of the Polish Army's intendant service written down during the Second World War operations, the author presents issues related to the planning of the Polish Army's victualling during the war in the basic food product, namely bread. Describing this subject in a chronological and problematic order, the author shows that the victualling system created in the 1930s proved successful to a limited extent, namely only in terms of accumulating the supply of rye necessary for baking bread in the first stage of military operations. Using concrete examples, he goes on to demonstrate that the preparations made in connection with the storage of rye, its processing and bread baking, as well as its distribution, were inadequate and insufficient even in peacetime, and that these problems were significantly exacerbated during the war. This, in turn, had a direct impact on the collapse of bread supplies to numerous units of the Polish Army as early as the first week of the September battles, and consequently contributed to a decline in their combat capability and morale. The short-lived war did not reveal all the shortcomings associated with the army's bread supply preparations, although even so, by the end of the first decade of September it was not a regular item on the daily menu of fighting soldiers in the field. With each passing day, however, the situation worsened. Therefore, the problem described would certainly have been particularly acute in a prolonged conflict.
Chapter 14. CONSCIENTIAL WAR AS A FACTOR IN THE FORMATION AND TRANSFORMATION OF HISTORICAL MEMORY
Authors: Perederii Iryna , Hula Ruslan
Published: November 2024

The priority of the information confrontation in the postmodern era is the change of the nation’s mentality and the deformation of the patterns of national memory, which is vividly reflected in the events of the Russian-Ukrainian war. Complex transformational processes in the development of the modern library system, the problem of determining its role and place in the protection of national cultural heritage, countering attempts to purposefully plant enemy cultural values to the Ukrainian state in the conditions of the complex use of information warfare’s means are given in conditions of the conscientious war.

The purpose of our scientific research is to reveal the essence of the sociocultural dimension of conscientious war (war for consciousness) in its components. This is an archaeological war and a falsification of history. To reveal and determine the potential of the functioning of library, archive and museum systems in the context of conscious war in the conditions of the armed aggression of the Russian Federation against Ukraine.

It is proven that archival, library and museum systems, as a traditional collector and translator in time and space of documented knowledge, a guardian of the national cultural heritage, become an object of influence and manipulation in the conditions of conscientious war. At the same time, they can and should be an effective tool of informational and psychological confrontation. The role and place of cultural heritage institutions in the war for consciousness – the archaeological war and the rewriting of history – is revealed. A number of forms of conscientious war in the confrontation of the Russian-Ukrainian war are characterized.

For the first time, an attempt was made to comprehensively analyze the role of archives, libraries, and museums in the war of consciousness. The tasks and functions of archives, libraries, museums as an effective tool for protecting the national information space in the conditions of the Russian-Ukrainian war are specified.
An Evaluation of Ruler-Ruled Relations in the Perspective of Siyasatnamas
Authors: Önder Saliha Gizem
Published: November 2024

The term "siyasatnama" is used to describe didactic works written in both prose and verse that provide guidance to rulers and state officials on the principles of administration. The siyasatnamas, which reflect a diverse geographical range from Andalusia-Maghreb to Transoxiana, provide a comprehensive account of the administrative relationship between the ruler and the ruled. The authors of siyasatnamas anticipated the categorization of the ruled, enabling the ruler to identify and administrate those under his authority. The works posit that the people should reflect the rulers and that rulers should reflect the people. They also emphasize that both the rulers and the ruled have rights over each other. The siyasatnamas emphasize the importance of not oppressing the ruled, maintaining constant communication with them and meeting their needs. They demonstrate the sustainability of these relationships and how the ruler can dominate the ruled masses. In this context, ensuring balance in the relationship between the ruler and the ruled is of great importance in administration processes.
A Systematic Review of the Studies on WebQuest: Reflections to Mathematics
Authors: Sak Buse , Kobak Demir Mevhibe
Published: November 2024

The aim of this study is to determine the general trends of the studies on WebQuest in the field of mathematics education. This systematic review was conducted on 46 published studies from the beginning until 2023. The results after thematic analysis were presented through frequency and percentage values, tables and graphs. According to the results of the research, the first study on WebQuest in the field of mathematics education belongs to 2001. Half of the studies were published after 2014. It was concluded that the majority of the studies examined were in English and article type, the effect of WebQuest on academic achievement and the opinions on WebQuest were mostly examined. It was determined that the WebQuests prepared within the scope of the studies were on geometry and measurement. Methodologically, while the majority of the studies were prepared with a quantitative approach, adopting an experimental design, scales were used to collect data and inferential analysis for analysing, purposive sampling method was preferred in the selection of participants, and the participants were frequently composed of pre-service teachers. From the results related to the distribution of research topics according to sample types; it was determined that there was no study on the effect of WebQuest on the academic achievement of primary school students, the studies investigating the attitude towards mathematics and the effect of motivation were carried out only with secondary school students. At the end of the study, the benefits and limitations of WebQuest in the field of mathematics education were revealed.
A GLOBAL RISK IN THE COVID-19 PANDEMIC: ANALYSIS OF WOMEN'S UNMET NEEDS FOR MODERN CONTRACEPTIVE
Authors: Kahyaoğlu Süt Hatice , Elkan Kiyat Zeliha
Published: November 2024

The unmet need for contraception in the COVID-19 pandemic is a global risk. This study analyzed the unmet modern contraceptive needs of Turkish women in the COVID-19 pandemic. This cross-sectional study was conducted with 263 Turkish women of reproductive age who were reached through social media channels between February and December 2022. Categorical data on unmet family planning needs were compared using Chi-square tests, and the effects of risk factors were analyzed through multivariate logistic regression. Women were administered a web-based online questionnaire with data. During the COVID-19 pandemic, the risk of unmet needs increased 5.29 times in women aged 30-39 years compared to women aged
Probiotic-induced changes in intestinal microbiome inhibits Toxoplasma gondii infection
Authors: Lee Hak-Jae , Ham Do-Won , Seo Seung-Hwan , Cha Guang-Ho , Shin Eun-Hee
Published: November 2024

Toxoplasma gondii primarily invades the central nervous system, causing latent infections. Cysts persist in the host for life and there is currently no effective treatment. T. gondii infects human hosts through contaminated meat, invading the intestinal tissue and leading to changes in the number and composition of the gut microbiota. Since probiotic ingestion modulates intestinal microbiota changes, we hypothesized that intestinal microbiota dysbiosis caused by T. gondii infection would be restored following probiotic supplementation. To this end, we orally infected C57BL/6 mice with 10 T. gondii cysts and administered supplemental probiotics daily. We analyzed the levels of T. gondii B1 gene DNA, indicative of T. gondii infection, in brain tissue. We investigated alterations in the gut microbiota composition and functional pathways between the probiotic and non-probiotic treatment groups via next-generation sequencing analysis of each fecal sample. The infection level in the probiotic-treated group was significantly reduced after 4 weeks (p<0.05). Probiotic supplementation notably changed the gut microbiota after 2 weeks of infection, increasing the relative abundance of Intestinimonas massiliensis and Lawsonibacter asaccharolyticus. Probiotic supplements appear to modulate the gut microbiota, activating functional pathways involved in intestinal short-chain fatty acid production and strengthening the intestinal barrier, thereby impeding T. gondii infection and subsequent proliferation. Our findings provide valuable insights into T. gondii infection control and future study directions.
Respiratory Viral Infections: Highlights from IDWeek 2024
Authors: Bloch Karen C
Published: November 2024

IDWEEK 2024, held in Los Angeles, California, October 16th–19th, was an opportunity for the >12,000 attendees to hear about state-of-the-art scientific updates in infectious diseases. Respiratory viral infections were prominently featured, with myriad presentations on the epidemiology, prevention, and management of several important and emerging pathogens. Highlights of the program are listed below.
Issues in training the TreeTagger for Georgian
Authors: Daraselia Sophiko
Published: November 2024

The paper describes the process of retraining the TreeTagger program ( Schmid, 1994 ) for the Georgian language. This includes considering some general procedures such as designing a training corpus, creating a tagging lexicon, and training the TreeTagger on Georgian texts. I use a novel katag tagset and enclitic tokenisation approach in part-of-speech tagging. The katag tagset is based on a new morphosyntactic language model (Daraselia and Hardie, forthcoming). In this paper, I address some major disambiguation considerations that were revealed when training the TreeTagger on Georgian texts. I discuss some ways to get around these matters, such as implementing a workaround to the tagging lexicon. I report on the performance of the TreeTagger program and compare how different parameters such as the size of the training lexicon or context and affix lengths affect the Tagger’s performance.
Design and construction of an openly available Urdu web corpus
Authors: Jehangir Humaira , Hardie Andrew
Published: November 2024

Urdu corpus linguistics is in its infancy, partly because the field lacks large, openly and freely accessible corpora. General purpose Urdu corpora created to date are unsuitable as shared reference data for the field due to barriers of cost or copyright. The novel Lancaster Urdu Web Corpus (luwc) is designed to fill this gap. It encompasses data from three news websites and an online chat forum. The corpus contains 24 million tokens, and is part-of-speech (pos) tagged. To overcome problems with distributing a corpus whose texts’ intellectual property belongs to other parties, the luwc is available through a cqpweb server, disallowing access to full underlying data. However, the accessibility of source urls as text-level metadata gives users a means by which to see the full original context. In spite of issues of balance/representativeness the luwc can fulfil the role of a shared reference point for Urdu corpus analysis.
PENILAIAN PROSES PENGANGGARAN KEUANGAN DESA KEMUNING LOR KABUPATEN JEMBER
Authors: Ardhiarisca Oryza , Wijayanti Rahma Rina , Putra Rediyanto , Sumadi Sumadi
Published: November 2024

Tujuan penelitian ini adalah untuk menentukan dan menilai proses penganggaran keuangan Desa Kemuning Lor, Kecamatan Arjasa, Kabupaten Jember, Provinsi Jawa Timur. Penelitian ini adalah penelitian kualitatif dengan menggunakan data primer dan sekunder yakni observasi, wawancara, dan analisis dokumen. Hasil penelitian menunjukkan bahwa proses penganggaran keuangan Desa Kemuning Lor sudah sesuai dengan Peraturan Menteri Dalam Negeri Nomer 20 Tahun 2018. Selain itu, program kerja Desa Kemuning Lor telah telah mencapai serapan 100%, walaupun ada realokasi anggaran yang terjadi selama covid-19.
Exploring EFL students’ preferences and practices of study strategies: repeated reading versus testing
Authors: Aljabri Sameer
Published: November 2024

The aim of this study was to investigate both the hypothetical study strategy (preferences) and actual study (practices) of Saudi EFL undergraduate students regarding rereading versus retrieval practice. A total of 202 EFL students were presented with a scenario where they had studied a textbook chapter once and then asked to choose the learning strategy that best reflected their typical approach during different stages of the learning process: the beginning, middle, and end. Then they read a text and responded to both open-ended and forced report questionnaires to explore their actual study behaviors when studying the text. Results showed a consistent preference for restudying throughout all stages of the learning process (36.5, 39.8, 53.6% respectively). Across the learning processes, retesting strategy has been chosen increasingly as the learning process proceeds (16–18.2 - 28.2%) while rereading is decreasing (35.9–23.8 - 13.3%). In the actual study behaviors, the majority of participants reported tendency to rely excessively on restudying and rereading strategies (55.6 and 24.6% respectively) rather than more effective testing strategies (19.8%). Teachers need to educate students that retrieval practice strategies aid in monitoring their learning progress, enhancing learning, strengthening memory recall, and promoting long-term retention.
Enhancing the oxidation of polystyrene through a homogeneous liquid degradation system for effective microbial degradation
Authors: Kim Hong Rae , Koh Hye Yeon , Shin Hyeyoung , Suh Dong-Eun , Lee Sukkyoo , Choi Donggeon
Published: November 2024

Plastics play a crucial role in modern industries; however, their resistance to natural degradation contributes to environmental pollution, and microplastics pose a health threat. The hydrophobic nature of microplastics poses a considerable challenge, rendering them resistant to dissolving in water. In this study, we conducted a comparative analysis of the microbial biodegradation capabilities of polystyrene in solid and liquid states. Polystyrene in its solid foam form, along with polystyrene converted into a liquid state using ethyl-ester oil, was biodegraded by microorganisms. Subsequently, the liquid plastic was re-extracted into its solid form, and the degree of degradation was assessed using weight loss measurement, XPS, FT-IR, GPC, and TGA. Liquid-state polystyrene exhibited a higher degradation rate than that reported previously. Furthermore, liquid polystyrene undergoes more pronounced oxidation than its solid counterpart, leading to an increased oxygen atom ratio. Chemical structure analysis highlighted the distinct formation of –OH and C=O functional groups in the liquid state compared to those in the solid state. Additionally, notable changes in the molecular weight and thermal stability of polystyrene were observed during biodegradation in the liquid state. This study suggests that a heterogeneous reaction (solid plastic-liquid medium) might impede plastic biodegradation, while indicating the potential to enhance the degradation efficiency through a homogeneous reaction (liquid plastic-liquid medium). The follow-up study identifies appropriate solvents and optimizes cultivation conditions, offering potential to enhance the efficiency of biological plastic degradation.
Modeling the determinants of smoking behavior among young adults in Khuzestan province: a two-level count regression approach
Authors: Satyar Homayoun , Ahmadi Angali Kambiz , Ghorbani Somayeh , Kamyari Naser , Seyedtabib Maryam
Published: November 2024

Purpose

This study investigates the determinants of smoking behavior among young adults in Khuzestan province, southwest Iran, using two-level count regression models. Given the high prevalence of smoking-related diseases and the social impact of smoking, understanding the factors influencing smoking habits is crucial for effective public health interventions.

Methods

We conducted a cross-sectional analysis of 1,973 individuals aged 18–35 years, using data from the Daily Smoking Consumption Survey (DSCS) in Khuzestan province collected in 2023. A variety of count regression models, including Poisson, Negative Binomial, Conway–Maxwell Poisson, and their zero-inflated counterparts, were evaluated. The best-fitting model was selected based on goodness-of-fit indices.

Results

Approximately 90% of participants were non-smokers. Among smokers, the prevalence of light, moderate, and heavy smoking was 47.7, 19.0, and 33.3%, respectively. The two-level Zero-Inflated Conway–Maxwell Poisson (ZICMP) model provided the appropriate fit for the data. Key determinants of daily cigarette consumption included gender, age, education, and Body Mass Index (BMI). Men consumed 3.24 times more cigarettes per day than women. Higher education levels were inversely related to smoking intensity, with MSc/PhD holders having significantly lower smoking rates. Age and BMI also significantly influenced smoking behavior, with younger and obese individuals showing lower smoking rates.

Conclusion

The use of advanced count models capable of handling numerous zeros and overdispersion is crucial for accurately analyzing trends in cigarette consumption across different population groups. The results indicate that factors such as older age, lower education levels, and gender differences influence smoking behavior. Therefore, prevention strategies aimed at delaying the onset of smoking, particularly among men, and promoting education among adolescents can effectively reduce smoking rates. However, further research should consider additional socioeconomic variables and encompass a broader age range to enhance the understanding of smoking behavior.
Trade-off between fitness and experience: insights from historical data on ODI cricket
Authors: Jain Vipra , Banerjee Subrato , Kothari Priyanka
Published: November 2024

A healthy mix of younger and senior players is often desirable for any team involved in a sports-tournament. It is often argued that the experience of senior players and fitness of the younger players could complement each other. How an athlete performs is determined by the accumulation of experience that grows with age and physical fitness that declines with age. Therefore, fitness and experience are competing forces that move in opposite directions. We explore the age-range of peak-performance in the lifetime of a sportsperson where the marginal benefits from experience and fitness are on balance. Using a unique data-set of all one-day international (ODI) cricket matches played from 1971 to 2000, we find that there is an inverted U-shaped performance-age curve where performance first gets better with age, then reaches a peak before finally declining (when experience can no longer undo the effects of declining fitness). This peak-performance is attained for bowlers at around 22–26 years and for batters at about 27–30 years. These results remain robust to different specifications and controls. We employ a theoretical framework for policy analyses of actual selection decisions made during our period of study. These analyses build on the empirical section of our paper.
A Bayesian Network Approach to Lung Cancer Screening: Assessing the Impact of Data Quantity, Quality, and the Combination of Data from Danish Electronic Health Records
Authors: Daalen Florian van , Henriksen Margrethe Høstgaard Bang , Hansen Torben Frøstrup , Jensen Lars Henrik , Brasen Claus Lohman , Hilberg Ole , Andersen Martin Ask Klausholt , Humerfelt Elise , Wee Leonard , Bermejo Inigo
Published: November 2024

Background/Objectives: Lung cancer (LC) is the leading cause of cancer mortality, making early diagnosis essential. While LC screening trials are underway globally, optimal prediction models and inclusion criteria are still lacking. This study aimed to develop and evaluate Bayesian Network (BN) models for LC risk prediction using a decade of data from Denmark. The primary goal was to assess BN performance on datasets varying in size and completeness, simulate real-world screening scenarios, and identify the most valuable data sources for LC screening. Methods: The study included 38,944 patients evaluated for LC, with 11,284 (29%) diagnosed. Data on comorbidities, medications, and general practice were available for the entire cohort, while laboratory results, smoking habits, and other variables were only available for subsets. The cohort was divided into four subsets based on data availability, and BNs were trained and validated across these subsets using cross-validation and external validation. To determine the optimal combination of variables, all possible data combinations were evaluated on the samples that contained all the variables (n = 5587). Results: A model trained on the small, complete dataset (AUC 0.78) performed similarly on a larger dataset with 21% missing data (AUC 0.78). Performance dropped when 39% of data were missing (AUC 0.67), resulting in informative variables missing completely in the dataset. Laboratory results and smoking data were the most informative, significantly outperforming models based only on age and smoking status (AUC 0.70). Conclusions: BN models demonstrated moderate to strong predictive performance, even with incomplete data, highlighting the potential value of incorporating laboratory results in LC screening programs.
Patient-Specific Circulating Tumor DNA for Monitoring Response to Menin Inhibitor Treatment in Preclinical Models of Infant Leukemia
Authors: Doculara Louise , Evans Kathryn , Gooding J. Justin , Bayat Narges , Lock Richard B.
Published: November 2024

Background: In infant KMT2A (MLL1)-rearranged (MLL-r) acute lymphoblastic leukemia (ALL), early relapse and treatment response are currently monitored through invasive repeated bone marrow (BM) biopsies. Circulating tumor DNA (ctDNA) in peripheral blood (PB) provides a minimally invasive alternative, allowing for more frequent disease monitoring. However, a poor understanding of ctDNA dynamics has hampered its clinical translation. We explored the predictive value of ctDNA for detecting minimal/measurable residual disease (MRD) and drug response in a patient-derived xenograft (PDX) model of infant MLL-r ALL. Methods: Immune-deficient mice engrafted with three MLL-r ALL PDXs were monitored for ctDNA levels before and after treatment with the menin inhibitor SNDX-50469. Results: The amount of ctDNA detected strongly correlated with leukemia burden during initial engraftment prior to drug treatment. However, following SNDX-50469 treatment, the leukemic burden assessed by either PB leukemia cells through flow cytometry or ctDNA levels through droplet digital polymerase chain reaction (ddPCR) was discrepant. This divergence could be attributed to the persistence of leukemia cells in the spleen and BM, highlighting the ability of ctDNA to reflect disease dynamics in key leukemia infiltration sites. Conclusions: Notably, ctDNA analysis proved to be a superior predictor of MRD compared to PB assessment alone, especially in instances of low disease burden. These findings highlight the potential of ctDNA as a sensitive biomarker for monitoring treatment response and detecting MRD in infant MLL-r ALL.
Blackfordia virginica in Non-Native Distribution Range: A Potential Food Source for Humans?
Authors: Cruz Mariana , Dias Ester , Custódio Luísa , Encarnação João , Cruz Joana , Baptista Vânia , Teodósio Maria Alexandra
Published: November 2024

The seasonal occurrence of the Black Sea jellyfish Blackfordia virginica Mayer, 1910 blooms is a reason of concern in the Guadiana estuary in the South of Portugal (South-West Europe), causing considerable economic and ecological impacts to fisheries. Due to jellyfish biochemical properties, they may represent an opportunity as an alternative food source for humans. In this context, this work evaluated the nutritional profile of B. virginica (proximate composition, amino acids, minerals, and fatty acids methyl ester content). Blackfordia virginica biomass may be adequate for human consumption, as it has nutritional properties resembling other edible jellyfish species, with relevant levels of minerals, moderate content in crude protein, low-fat content, and a low energetic value. The high Cd levels in the biomass of B. virginica from the Guadiana Estuary may compromise its safety as a food source. Moreover, if these jellyfishes are proven as an edible invasive species, their management through fisheries should evaluate the cost effectiveness of investments.
River Water Quality Monitoring Using LoRa-Based IoT
Authors: Pires Luís Miguel , Gomes José
Published: November 2024

Water pollution presents one of the biggest challenges in the world today, as the degradation of water quality of rivers in many instances is increasing so fast and poses a big danger to all forms of life, eventually causing many aquatic species and other species that depend on them to be endangered. Hence, with the development of Internet of Things (IoT) and Wireless Sensor Networks (WSNs), there arises a need to monitor river waters for a timely response in protecting the rivers, which is the aim of this paper. With respect to this project, we searched a little bit for some existing IoT technologies and other related work. In this paper, we propose a practical low-cost solution based on Long Range (LoRa) technology to obtain real-time observations of, with certain sensors, such water parameters as temperature, pH, conductivity and turbidity. Data gathered at a sensor node are transmitted via LoRa modulation to a gateway for processing and local storage on a Message Queuing Telemetry Transport (MQTT) server, visualization on a Node-RED interface, or transmission to the cloud. The prototype system created is employed in the actual field and demonstrates that the water quality monitoring in the river can be carried out effectively within a small scale of the area of roughly 20 km2 depending on the location of the study site.
Fractal Conditional Correlation Dimension Infers Complex Causal Networks
Authors: Canlı Usta Özge , Bollt Erik M.
Published: November 2024

Determining causal inference has become popular in physical and engineering applications. While the problem has immense challenges, it provides a way to model the complex networks by observing the time series. In this paper, we present the optimal conditional correlation dimensional geometric information flow principle (oGeoC) that can reveal direct and indirect causal relations in a network through geometric interpretations. We introduce two algorithms that utilize the oGeoC principle to discover the direct links and then remove indirect links. The algorithms are evaluated using coupled logistic networks. The results indicate that when the number of observations is sufficient, the proposed algorithms are highly accurate in identifying direct causal links and have a low false positive rate.
Two-Dimensional Analysis of Absorber Plates in Solar Collectors with a Nonlinear Plate Temperature at the Tube Section
Authors: Mahakud Jayanarayan , Kundu Balaram
Published: November 2024

Many investigators have investigated flat-plate solar collector absorber plates based on one-dimensional heat flows. However, the shape of the absorber plate may always create a two-dimensional temperature distribution if it has a thin thickness. Hence, an analysis of the two-dimensional heat flow in absorber plates is always required. The current paper determines a closed-form solution for the energy equation to establish a two-dimensional energy flow for an absorber plate by considering a nonlinear temperature variation at the plate–tube section. The separation of the established variable method solves the energy equation. The same energy equation was also solved numerically using the finite difference method for validation purposes. It emphasizes demonstrating that the analytical and numerical results match closely with each other. Finally, this work concludes by developing an analytical model for the practicable thermal analysis of absorber plates in solar collectors, providing error-free implementation results.
Comparison of Different Numerical Models for Solidification of Paraffin-Based PCMs and Evaluation of the Effect of Variable Mushy Zone Constant
Authors: Tajik Jamalabad Milad , Cortes Cristobal , Pallarés Javier , Gil Antonia , Arauzo Inmaculada
Published: November 2024

The impact of the mushy zone parameter (Amushy) and the chosen numerical model during the solidification of a commercial paraffin-type phase change material (PCM) in a vertical cylinder under T-history conditions was examined through numerical simulations. The cooling process was modeled using three methods implemented in the CFD software ANSYS Fluent 2020 R2: the enthalpy–porosity method, the apparent heat capacity (AHC) method, and a new model proposed by the authors which incorporates heat capacity directly into ANSYS Fluent. To accurately define the boundary conditions, radiative heat transfer between surfaces was taken into account. Furthermore, the influence of the mushy zone parameter on the simulation accuracy and solidification rate was investigated, with the parameter being treated as a function of the liquid fraction. The results indicate that the proposed model aligns closely with experimental data regarding cooling temperature, offering better predictions compared to the other models. It was observed that temperature varies with time but not with position, suggesting that this model more effectively satisfies the lumped system condition—an essential characteristic of the T-history experiment—compared to the other methods. Additionally, the analysis showed that a higher mushy zone parameter enhances the accuracy of simulations and predicts a shorter solidification time; approximately 11% for the E-p and 7% for the AHC model. Using a variable mushy zone parameter based on the liquid fraction also produced similar results, resulting in an increased solidification rate.
Role of AI and IoT in Advancing Renewable Energy Use in Agriculture
Authors: Morkūnas Mangirdas , Wang Yufei , Wei Jinzhao
Published: November 2024

This paper discusses how integrating renewable energy, AI, and IoT becomes important in promoting climate-smart agriculture. Due to the changing climate, rise in energy costs, and ensuring food security, agriculture faces unprecedented challenges; therefore, development toward innovative technologies is emerging for its sustainability and efficiency. This review synthesizes existing literature systematically to identify how AI and IoT could optimize resource management, increase productivity, and reduce greenhouse gas emissions within an agricultural context. Key findings pointed to the importance of managing resources sustainably, the scalability of technologies, and, finally, policy interventions to ensure technology adoption. The paper further outlines trends in the global adoption of renewable energy and smart agriculture solutions, indicating areas of commonality and difference and emphasizing the need for focused policies and capacity-building initiatives that will help, particularly in the developing world, the benefits of such innovations. Eventually, this research covers some gaps in understanding how AI, IoT, and renewable energy could jointly contribute to driving towards a greener and more resilient agriculture sector.
Optimized Operation of Integrated Cooling-Electricity-Heat Energy Systems with AA-CAES and Integrated Demand Response
Authors: Ma Tiannan , Peng Lilin , Wu Gang , Chen Danhao , Zou Xin
Published: November 2024

Integrated energy systems (IESs) have been implemented with the objective of enhancing the efficiency of energy utilization and facilitating the sustainable transition of society and energy systems. To further explore the multi-energy coupling capacity and carbon reduction potential of the IESs, this study presents the design of an integrated cold-electricity-heat energy system (ICEHS) with advanced adiabatic compressed air energy storage (AA-CAES). AA-CAES has the capacity to not only store and release electric energy, but also to provide cold and heat energy, which makes it an ideal choice for this application. The main work of this study is fourfold: (1) the energy hub concept is employed to describe the energy transformations within AA-CAES, thereby reducing the modeling complexity; (2) integrated demand response (IDR) for cooling, heating, and electric loads, including shiftable loads, adjustable loads, interruptible loads, and replaceable loads, is considered; (3) Latin hypercubic sampling in conjunction with K-means clustering is employed to address the issue of source-load uncertainty; and (4) an ICEHS operation optimization model is developed with the objective of minimizing the daily operating cost, where the possible cost terms include energy purchase cost, operation and maintenance cost, demand response cost, and carbon emission cost. A typical community integrated energy system is employed as an illustrative example, and four different scenarios are established to validate the effectiveness of the proposed model. The results indicate that AA-CAES and IDR can effectively reduce the daily operating cost and carbon emissions of an ICEHS. In comparison to the scenario that did not incorporate AA-CAES and IDR, the daily operating cost and carbon emissions are reduced by 4.8% and 10.3%, respectively.
Climate Change and Potential of Agroforestry in Uganda: Youth Perceptions and Willingness to Participate in Adaptation and Transition Efforts
Authors: Bamwesigye Dastan , Yeboah Evans , Ozbalci Seval , Fialova Jitka , Kupec Petr , Verter Nahanga , Asamoah Obed
Published: November 2024

Climate change remains a pressing global issue, affecting sectors including agriculture and forest resources, in countries such as Uganda. This research focused on exploring the viewpoints of youth in Uganda concerning adapting to climate change, and their interest in becoming involved in agroforestry transition, by conducting a survey involving 1138 participants from the youth demographic group aiming to gather information about their level of hopefulness towards climate adaptation efforts and how they perceive the impact of farming practices and deforestation. Furthermore, the study aimed to evaluate youth willingness to participate in agroforestry (WTPA) initiatives. The study used descriptive statistics as well as Ordinary Least Squares (OLS) to analyze the collected data. We found that most participants are hopeful about adapting to climate change (89%). This positive and highly significant outlook is closely related to their willingness to participate in agroforestry adaptation efforts (0.000). Moreover, a high percentage of participants (92%) acknowledged how farming practices, such as cultivation and livestock rearing, could degrade land significantly. Whereas Gender, Age and Employment were found to be highly and positively significant regarding youth’s WTPA (0.000), income was not. Other determinants, such as saving nature, soil conservation, water regulation and protection, financial/income, forest-related foods and fruits, and firewood, influenced youth willingness to participate in agroforestry activities. Incorporating indigenous practices and encouraging meaningful involvement from policymakers can empower youth and strengthen community-led initiatives to address environmental decline effectively. This research highlights the capacity of youth engagement in steering successful climate resilience measures via agroforestry practices in Uganda.
Seizures Triggered by Systemic Administration of 4-Aminopyridine in Rats Lead to Acute Brain Glucose Hypometabolism, as Assessed by [18F]FDG PET Neuroimaging
Authors: Gómez-Oliver Francisca , Fernández de la Rosa Rubén , Brackhan Mirjam , Bascuñana Pablo , Pozo Miguel Ángel , García-García Luis
Published: November 2024

4-aminopyridine (4-AP) is a non-selective blocker of voltage-dependent K+ channels used to improve walking in multiple sclerosis patients, and it may be useful in the treatment of cerebellar diseases. In animal models, 4-AP is used as a convulsant agent. When administered intrahippocampally, 4-AP induces acute local glucose hypermetabolism and significant brain damage, while i.p. administration causes less neuronal damage. This study aimed to investigate the effects of a single i.p. administration of 4-AP on acute brain glucose metabolism as well as on neuronal viability and signs of neuroinflammation 3 days after the insult. Brain glucose metabolism was evaluated by [18F]FDG PET neuroimaging. [18F]FDG uptake was analyzed based on volumes of interest (VOIs) as well as by voxel-based (SPM) analyses. The results showed that independently of the type of data analysis used (VOIs or SPM), 4-AP induced acute generalized brain glucose hypometabolism, except in the cerebellum. Furthermore, the SPM analysis normalized by the whole brain uptake revealed a significant cerebellar hypermetabolism. The neurohistochemical assays showed that 4-AP induced hippocampal astrocyte reactivity 3 days after the insult, without inducing changes in neuronal integrity or microglia-mediated neuroinflammation. Thus, acute brain glucose metabolic and neuroinflammatory profiles in response to i.p. 4-AP clearly differed from that reported for intrahippocampal administration. Finally, the results suggest that the cerebellum might be more resilient to the 4-AP-induced hypometabolism.
Plateau Pika Disturbance Changes Soil Bacterial Functions and Exoenzyme Abundance to Modulate the C Cycle Pathway in Alpine Grasslands
Authors: Li Jing , Wang Qing , Zhu Baolong , Yang Min
Published: November 2024

Plateau pika (Ochotona curzoniae) is crucial to soil organic carbon (SOC) storage in the Qinghai–Tibetan plateau (QTP), but its role in bacterial SOC metabolisms across different degraded alpine grasslands remains unclear. In this study, we investigated the soil physicochemical properties and the composition and function of the bacterial communities in control and pika-disturbed grasslands experiencing different degradation levels (undegraded, UDM; lightly, LDM; moderately, MDM and severely, SDM). The results demonstrate that (i) the primary bacterial phyla include Proteobacteria, Acidobacteriota, Actinobacteriota, Bacteroidota and Verrucomicrobiota. Soil physicochemical properties significantly impact the composition of the bacterial communities and determine the influence of pika disturbance. Pika disturbance increases bacterial OTUs by 7.5% in LDP (p > 0.05) and by 50.5% in MDP (p < 0.05), while decreases OTUs by 21.4% in SDP (p < 0.05). (ii) Pika disturbance downregulates the exoenzyme abundance associated with simple and complex organic matter decomposition by 9.5% and 13.9% in LDP, and 29.4% and 26.3% in MDP (p < 0.05), while upregulates these exoenzymes by 23.6% and 37.9% in SDP (p < 0.05). These changes correspond to the increase in TC and SOC in LDP and MDP but declines in SDP. (iii) Plateau pika disturbance can enhance SOC accumulation through upregulating the C cycle pathway of ethanol production in LDP and MDP. However, it upregulates the pathway of pyruvate to CO2 conversion in SDP, leading to negative influence on SOC storage.
Resveratrol-Loaded Pluronic Micelles Ameliorate Scopolamine-Induced Cognitive Dysfunction Targeting Acetylcholinesterase Activity and Programmed Cell Death
Authors: Lazarova Maria , Stefanova Miroslava , Tsvetanova Elina , Georgieva Almira , Tasheva Krasimira , Radeva Lyubomira , Yoncheva Krassimira
Published: November 2024

Numerous experimental studies suggest the potential for resveratrol (RVT) to be useful in the Alzheimer’s disease treatment, but its low bioavailability limits its application. This study aimed to assess the potential of resveratrol-loaded micelles as a neuronal delivery platform to protect rats from scopolamine-induced memory impairment. Resveratrol was incorporated into Pluronic micelles, and the effects of micellar (mRVT) and pure resveratrol (RVT) were compared in the model of scopolamine-induced dementia in male Wistar rats. Memory performance was assessed by a T maze test. The effect of the treatment on specific neurotransmitter levels and protein expression in the cortex and the hippocampus were evaluated biochemically. Our results revealed that the polymeric micelles were in nanoscale (approximately 33 nm) and reached 79% encapsulation efficiency. The treatment with mRVT demonstrated better spatial memory protective effect. The biochemical assays showed that mRVT in a dose of 10 mg/kg enhanced the effects of the pure drug in regard to noradrenalin neurotransmission and acetylcholinesterase inhibitory activity in the hippocampus. Furthermore, micellar resveratrol increased the cAMP-response element-binding protein expression in the cortex and hippocampus of rats as well as the Bcl2/BAX ratio, which indicated an anti-apoptotic effect in the experimental dementia model. In conclusion, our results indicated the potential of a micellar system loaded with resveratrol for neurodegenerative diseases treatment.