bluuebunny/crossref_metadata_2025 huggingface dataset:
A Multi-Stratal Model of Language Processing (MSMLP)
Authors: Elleuch Dalia
Published: January 2024

This article presents the Multi-Stratal Model of Language Processing (MSMLP) as an innovative neurolinguistic approach. The MSMLP is a framework that aims to advance the understanding of language processing (henceforth LP) in the human brain. A systematic review of the available models from various linguistic disciplines, cognitive psychology, and neuroscientific research was conducted to critically explore and synthesize the current trends and identify the theoretical gap regarding the technical modeling of the phenomenon under investigation (LP). The article provides a detailed overview of the theoretical foundations and key components of the MSMLP. It highlights the importance of studying language processing from a multi-stratal perspective, acknowledging the interconnectedness and mutual influence of different linguistic strata. The MSMLP integrates multiple strata of analysis: phonological, morphosyntactic, semantic, and pragmatic. By considering these interdependencies, the MSMLP offers a neurolinguistic explanation of naturalistic language processing. Furthermore, the article discusses the implications and potential applications of the MSMLP in the field of medical research and clinical practice. It emphasizes the model's relevance in studying language disorders, such as aphasia, and its potential to inform diagnostic and therapeutic approaches.
A reformulation of the FLQ approach to computing regional input-output coefficients
Authors: Flegg Anthony T. , Pereira-López Xesús , Sánchez-Chóez Napoleón , Cuevas Fernando de la Torre , Tohmo Timo
Published: January 2024

In this paper, we examine alternative methods of computing regional input−output (IO) coefficients, with an emphasis on their relative accuracy and the complexity of the computations required. We propose a novel way of implementing the well-known FLQ (Flegg’s location quotient) approach. Although the FLQ formula often yields very satisfactory results, the need to specify values of the unknown parameter δ in this formula presents an obstacle to its implementation. Here we develop a fresh approach to the use of the FLQ that substantially simplifies its application, while simultaneously enhancing its performance. We focus on how regional size, R, is incorporated in this formula and simplify the way in which R affects the allowance made for imports from other regions. We call this new formula the reformulated FLQ or RFLQ. We also show how the unknown parameter in the RFLQ can be computed. We test our proposal using the 2005 and 2015 Korean survey-based interregional IO datasets and contrast our estimates with both survey-based values and the results from several other techniques. We also examine two different information scenarios: with and without industry-specific information. The results suggest that the RFLQ can yield more accurate estimates of regional IO coefficients, and in a more straightforward way, than is possible with the traditional FLQ.
Sex differences and fecal incontinence among Japanese patients with ulcerative colitis: A cross-sectional study
Authors: Hanayama Masakazu , Furukawa Shinya , Miyake Teruki , Yoshida Osamu , Shiraishi Kana , Tange Kazuhiro , Hashimoto Yu , Kitahata Shogo , Ninomiya Tomoyuki , Yagi Sen , Suzuki Seiyuu , Shibata Naozumi , Murakami Hidehiro , Ohashi Katsuhisa , Tomida Hideomi , Yamamoto Yasunori , Takeshita Eiji , Ikeda Yoshio , Hiasa Yoichi
Published: January 2024

Background
Several differences in sex and clinical features among patients with ulcerative colitis (UC) have been reported. Fecal incontinence (FI) is closely associated with quality of life; however, the evidence regarding sex differences and FI in patients with UC is limited and inconsistent.
Aims
This study aims to examine the relationship between sex, delivery history, and FI in Japanese patients with UC.
Methods
A total of 288 Japanese UC patients participated in this study. FI was defined based on self-reported incontinence frequency. Information on sex, delivery history, smoking status, and alcohol intake status was collected through a self-reported questionnaire. Medication, disease activity, and body mass index (BMI) information was collected from medical records.
Results
The female-to-male ratio and FI prevalence were 48.0% and 13.9%, respectively. FI was significantly more prevalent in female patients (21.5%) compared to male patients (8.4%). Female sex was significantly and positively associated with FI (adjusted odds ratio [OR], 2.99 [95% CI 1.51–6.16]). Drinking status, smoking status, and BMI were not associated with FI. In female UC patients, the percentages for no history of delivery, one delivery, and two or more deliveries were 33.1%, 13.2%, and 53.7%, respectively. However, history of delivery was not significantly associated with FI.
Conclusions
In Japanese patients with UC, female sex was independently and inversely associated with FI. Furthermore, in female patients, history of delivery was not significantly associated with FI.
Robust graph representation learning via out-of-distribution detection approach
Authors: Bastami Esmaeil , Soltanizadeh Hadi , Rahmanimanesh Mohammad , Keshavarzi Parviz , Asadpour Masoud
Published: January 2024

Graph neural networks (GNNs) are powerful models capable of learning from graph-structured data and performing various tasks. GNNs are susceptible to poisoning attacks, in which sophisticated attackers inject malicious nodes or edges into the graph topology to degrade their performance. The existing defense mechanisms, such as adversarial training, are ineffective in improving the robustness of GNN models. Fake nodes can be utilized creatively to deceive traditional GNN neural functions. In this paper, we propose a robust GNN model empowered by a reliable aggregation function based on the OOD detection concept and a novel method. A key idea of RGRO is to train a model that maps the nodes to a latent space in which we can measure the distance between the nodes and their distribution. The Mahalanobis distance is proposed as a superior alternative to cosine distance in order to exploit the homophily rule better and to consider the contextual information of the nodes. The Mahalanobis distance, which considers the covariance of the data and is scale-invariant, allows for a more effective application of the homophily rule. Mahalanobis distance is explored in this study to enhance the robustness and accuracy of outlier detection in graph data, thus contributing to a better understanding of homophily. The RGRO model can improve accuracy by removing poisoned data without knowing any types of poisoning attacks or GNN algorithms. RGRO is evaluated with four typical defense strategies based on two types of poisoning attacks implemented on different realistic datasets. Based on the results, RGRO can detect poisoned data against attacks effectively and efficiently. In the best scenario, RGRO improves the accuracy of the GNN model by 0.86.
Carbon sequestration and carbon stock inventory under different land use systems of Semi-Arid region of Bundelkhand of Uttar Pradesh
Authors: Kant Shiva , Kumar Sanjeev , Pandey Ankit , Gupta Dinesh
Published: January 2024

The study was conducted in different land use systems in Badokhar Khurd block Banda district Bundelkhand region of Uttar Pradesh. The experiment was laid out randomized block design using seven land use systems four soil layers (L) and each different land use system replicated thrice. The results have revealed that different land use system have significant influence on the production of above ground biomass, belowground biomass and total biomass, which affect the carbon stock and CO2 mitigation potential the maximum aboveground biomass carbon stock (8.30 t ha-1), belowground biomass carbon stock (2.16 t ha-1) and total biomass carbon stock (10.46 t ha-1) was exhibited by (SPS). While minimum above ground biomass carbon stock (0.51 t ha-1), belowground carbon stock (0.13 t ha-1) and total biomass carbon stock (0.65 t ha-1) was found in (NGS). Maximum bulk density was recorded in agriculture crop-based land-use (1.45g cm-3) followed by (ASS) and (AHS) while minimum bulk density was recorded in (SPS) (1.36g cm-3). Maximum soil organic carbon stock was recorded in (SPS) (4.97 t ha-1) followed by (HPS), while minimum soil organic carbon stock agriculture crop-based land-use (2.63 t ha-1). As a result, the maximum total carbon stock was recorded (SPS) (29.35 t ha-1) followed by (HPS), (ASS), (AHS) and agriculture crop-based land use while minimum total carbon stock was recorded in (NGS) (11.87 t ha-1).
Assessment of knowledge, attitude, and practices toward malaria in the Lunglei district, Mizoram, North-East India
Authors: Vanlalhriata C , . Lalpianpuii , Wankhar Phibahunglang T , Prakash Pooja T , Amarthaluri Christiana , Pautu Lalfakzuala , . Vanramliana , Lalmalsawma Pachuau , Balasubramani Karuppusamy , Nina Praveen Balabaskaran
Published: January 2024

Background
The western districts of Mizoram (Lunglei, Mamit, and Lawngtlai) are malaria hotspots. The porous boundaries between Mizoram’s western districts and the Chittagong hill tracts of Bangladesh hamper malaria control strategies in the state. Understanding the knowledge, attitudes, and practices of the tribal communities in Mizoram’s western districts will aid the development of specific interventions.
Methodology:
An explanatory mixed-method study was conducted from April to November 2023 in the Lunglei district. In a community-based cross-sectional survey of 353 participants, the knowledge, attitude, practices, and care-seeking behavior toward malaria were assessed using a semi-structured questionnaire. This was followed by an in-depth telephonic interview of twelve participants, and the data was analyzed in NVivo.
Results
Out of the 353 respondents, 77.9%, 82.7%, 55.5% and 63.2% of the participants had good knowledge, attitude, practices, and care-seeking behavior, respectively. The responses in the in-depth qualitative interview highlighted the good knowledge about malaria among the villagers in this setting. The respondents were aware of the importance of IRS and insecticide-treated bed nets in malaria control; 11 and 10 respondents (out of 12) were using IRS and insecticide-treated bed nets, respectively.
Conclusion
The overall good knowledge, attitude, and practices toward malaria among the villagers reflect the strong healthcare system at the grassroots level in Mizoram. For effective dissemination, the Information, Education, and Communication material on malaria could be in the Chakma language as the members of this community were not able to understand and communicate effectively in the local Mizo language. The ecological niche and the agricultural practices, where the villagers are constantly exposed to mosquito bites in the forest greatly facilitate malaria transmission in this region. In addition to vector control measures, active parasite surveillance is key to malaria control in this region.
Crossover from attractive to repulsive induced interactions and bound states of two distinguishable Bose polarons
Authors: Theel Friethjof , Mistakidis Simeon I. , Schmelcher Peter
Published: January 2024

We study the impact of induced correlations and quasiparticle properties by immersing two distinguishable impurities in a harmonically trapped bosonic medium. It is found that when the impurities couple both either repulsively or attractively to their host, the latter mediates a two-body correlated behavior between them. In the reverse case, namely the impurities interact oppositely with the host, they feature anti-bunching. Monitoring the impurities relative distance and constructing an effective two-body model to be compared with the full many-body calculations, we are able to associate the induced (anti-) correlated behavior of the impurities with the presence of attractive (repulsive) induced interactions. Furthermore, we capture the formation of a bipolaron and a trimer state in the strongly attractive regime. The trimer refers to the correlated behavior of two impurities and a representative atom of the bosonic medium and it is characterized by an ellipsoidal shape of the three-body correlation function. Our results open the way for controlling polaron induced correlations and creating relevant bound states.
Deep Learning-Based Ovitrap Spatial Dynamics Analysis for Arbovirus Vector Monitoring
Authors: Sanchez-Gendriz Ignacio , Diniz Matheus , Dória Neto Adrião Duarte , Pedreira Rodrigo Moreira , Andrade Ion , Valentim Ricardo
Published: January 2024

Dengue is a significant global health issue, affecting millions of people annually and imposing substantial socioeconomic burdens. Effective disease control relies on monitoring the population of Aedes aegypti mosquitoes, the primary vector of dengue. One surveillance method involves counting the eggs laid by these mosquitoes in spatially distributed ovitraps. This study focuses on the application of computational methods to forecast dengue vector populations. We analyze a four-year (2016- 2019) database from 397 ovitraps distributed across Natal, RN, Brazil, with a weekly sampling frequency. Our objective is to develop accurate machine learning (ML) models that can predict the egg density index (EDI) at a fine-grained spatial resolution, aligned with zoonosis interventions. To preprocess the dataset obtained from the ovitraps, we employ spatial smoothing techniques and aggregation. The preprocessed data is then used to train ML models, including recurrent deep learning (DL) models, enabling accurate forecasting of the EDI. This approach shows promise for monitoring and preventing arbovirus outbreaks. Our findings demonstrate the effectiveness of spatial smoothing and aggregation as preprocessing steps for reducing randomness and noise in the dataset. The recurrent DL models exhibit high forecasting accuracy, thereby validating their utility in arbovirus monitoring and prevention efforts.
Utilização de Curvas Principais na triagem de pacientes com tuberculose
Authors: Castro Davi Horner , Ferreira Danton Diego , Rodriguez Demostenes Zegarra , Lacerda Wiliam , Borges Fernando , Silva Cecilia
Published: January 2024

A pandemia de COVID-19 mostrou que a velocidade e precisão no diagnóstico e essencial para um bom tratamento médico. Para acelerar o diagnóstico, o setor médico está se modernizando cada vez mais de forma a procurar soluções automatizadas, incrementando o uso de inteligência artificial. Uma doença extremamente negligenciada e a Tuberculose que, se não for diagnosticada no início, ela pode ser fatal ou pode causar sequelas graves que podem perdurar por muitos anos. Este trabalho visa demonstrar um método para identificar pacientes com Tuberculose (TB) por meio de Curvas Principais (CP). Para isso, utilizou-se um banco de dados disponível na literatura dividido nas seguintes classes: Pacientes com TB, pacientes com outras doenças e pacientes saudáveis. No pré-processamento foi utilizada uma Rede Neural Convolucional (CNN) ja treinada, visando usar o conhecimento previo adquirido por transferência de aprendizado, com uma Transfer Learning (TL), para extração de características e consequentemente facilitar a classificação. Essas características serão ent ao analisadas usando uma validação cruzada K-fold, e o algoritmo k-segmentos, para criar e treinar Curvas Principais que, então, ser ao utilizadas na classificação das imagens. Os resultados obtidos mostraram potencial para o uso do método em futuras predições automatizadas, atingindo índices de desempenho próximos a 0,90, (90%) de acurácia.
Classificação de Sons Pulmonares com Técnica de Few-Shot Learning
Authors: Santos Rafael , Fortunato Danielle , Ferreira Danton Diego , Barbosa Bruno
Published: January 2024

A pandemia em decorrência da COVID-19 evidenciou para a humanidade a gravidade que uma doença pulmonar pode ter e a consequência se a mesma não for diagnosticada e contida o mais rápido possível. Dessa maneira, o reconhecimento de doenças pulmonares, o tratamento e a contenção são alvos de estudo ha anos. Porém, as limitações de identificação manual utilizando os estetoscopios nos procedimentos de auscultas pulmonares acarreta na necessidade de outros exames, e consequentemente mais tempo para discernir a doença, e em casos graves onde isso não é imediato pode provocar a morte do paciente. Por esse motivo, este trabalho visa a elaboração de dois modelos de classificação de sons pulmonares utilizando o banco de dados ICBHI 2017 e as técnicas Random Forest e Rede Siamesa, comparando seus resultados e seus métodos. Utilizando o criterio de validação cruzada k-fold, tais modelos obtiveram acurácias médias de 84.84% e 85.74% nos melhores métodos, respectivamente, mostrando ser viável a identificação de doenças a partir da análise de sinais de áudio de ausculta pulmonar.
Thyroid Syndrome Detection using Machine Learning Algorithms: A Comparative Analysis
Authors: Cavalcante Caio , Almeida Vinicius , Barros Marcos , Lima Nathalee , Rego Rosana
Published: January 2024

A thyroid syndrome necessitates early and proper diagnosis to facilitate adequate treatment. However, subjectivity in analyzing test results poses a challenge. In this work, we explored and analyzed the potential of machine learning algorithms. These algorithms include decision trees, random forest, logistic regression, naive Bayes, XGBoost, LightGBM, and a stacking ensemble model. The goal was to classify the euthyroid syndrome, which is a medical condition impacting the thyroid gland, by utilizing attributes obtained from blood tests. These attributes encompass thyroxine, thyroid stimulating hormone, free thyroxine index, total thyroxine, and triiodothyronine. The findings indicate the efficacy of employing these algorithms in accurately classifying the syndrome and providing diagnostic support.
Pancreatic Cancer Classification Using Missing Data Imputation And Cluster-Based Undersampling Methods: A Comparative Analysis With Multiple Machine Learning Algorithms
Authors: Sena Wanessa , Neves Renata
Published: January 2024

Missing values and class imbalance are issues frequently found in databases from real-world scenarios, including cancer classification. Impacts on the performance of Machine Learning (ML) models can be observed if these issues are not properly addressed prior to the analysis. In this paper, a combined solution with missing data imputation using kNN and cluster-based undersampling using k-means is proposed, focusing on pancreatic cancer classification. Different data subsets were generated by combining different preprocessing methods and the performance was analyzed using a ML analysis pipeline from a previous study. This pipeline implements ten ML classifiers, including Random Forest (RF), Support Vector Machine (SVM) and Artificial Neural Network (ANN). All data subsets presented a significant improvement (p<0.05 with Students T-Test) in the performance of most ML algorithms when compared with the results obtained when the pipeline was first evaluated. Results suggest that kNN and k-means can be used in the data preprocessing phase to overcome missing values and class imbalance issues and improve the classification accuracy.
Ciência de Dados na Indústria Vitivinícola: compreensão, pesquisa e maturação tecnológica
Authors: Sá Priscila , Prates Ricardo
Published: January 2024

Este trabalho descreve a trajetória de um projeto de extensão e pesquisa em Ciência de Dados Aplicada ao setor industrial da vitivinicultura. O processo de compreender um problema de negócio, o uso da pesquisa bibliográfica como ferramenta para a escolha de tecnologia mais adequada para uma solução idealizada, assim como a avaliação de sua maturidade tecnológica até a pré-incubação de uma startup. Explora como ambientes de inovação impulsionam o processo de maturação de novas tecnologias e startups, promovendo colaboração e competitividade entre os setores produtivos e as instituições de ensino e pesquisa.
Inclusion of Children with Special Needs: Dyslexia Knowledge and Competence Factors of Preschool Teachers
Authors: Atalay Derya
Published: January 2024

Introduction: The study was conducted to examine the factors that affect the competencies of preschool teachers towards inclusion of children with special needs and their level of dyslexia knowledge.
Method: The study was designed in descriptive and relational survey model. The study group consisted of 350 preschool teachers. “Personal Information Form, Knowledge and Belief Scale about Dyslexia and Teacher Competency Scale for Inclusion of Children with Special Needs” were used to collect the data. In the analyses, frequencies and percentages of personal information were given, descriptive analyses were conducted on the scale scores, and Spearman Brown correlation coefficient was used to determine the relationship between the two scale scores. CHAID analysis, which is one of the classification analyses, was used to determine the factors affecting the scores of teachers’ teacher competency scale for inclusion of children with special needs and dyslexia knowledge and belief scale scores.
Findings: As a result of the study, it was observed that as preschool teachers’ dyslexia knowledge, diagnosis, treatment and general knowledge levels increased, their level of law, knowledge, perception and general competence for inclusion of children with special needs also increased. The most important factors affecting the competencies of preschool teachers towards the inclusion of children with special needs were found to be the status of having a special education certificate, the status of receiving training on learning disabilities, the type of institution and gender. It was found that preschool teachers who received training on learning disabilities and had a special education certificate had higher competency towards inclusion of children with special needs.
Discussion: While there is a lack of specific studies exploring the competencies of preschool teachers for the inclusion of children with special needs and their dyslexia knowledge levels, there are studies showing the importance of inclusive education.
Identifying yield and growing season precipitation gaps for maize and millet in Cameroon
Authors: Epule Terence Epule , Poirier Vincent , Etongo Daniel , Andriamasinoro Jessica
Published: January 2024

Climate change drives huge differences between the actual and projected yield and growing season precipitation. Therefore, this work identifies yield and precipitation gaps for maize and millet at the national and subnational scales as well as policy considerations for agricultural policy experts that can mitigate these gaps. Yield data for the national and subnational scale analyses were obtained for the period 1961–2021 from the FAOSTAT and the Ministry of Agriculture (MINAGRI)/IRAD of Cameroon, respectively. Growing season precipitation data for the national and subnational scales were collected from the World Bank climate change portal and the Climate Research Unit (CRU). Various machine learning algorithms were used to bias-adjust the data and to compute the potential yield and growing season precipitation from which the yield and precipitation gaps were computed. The results show a positive correlation between yield and precipitation gaps, with millet depicting the strongest correlation. The average yield gap for maize is 0.55 t/ha, higher than the average yield gap for millet that is 0.28 t/ha. Not all years with yield gaps are correlated with precipitation gaps. The average precipitation gap for maize is 108 mm/year, and it is higher than the 101 mm/year recorded for millet.
Field study of an arsenic removal plant for drinking water using activated carbon and iron in a rural community in the province of Pisco, Peru
Authors: Chavez Manuel , Ruffner Betsabé Ana
Published: January 2024

The presence of arsenic in Peru is a serious public health problem due to the geographical extension of populations that consume water with arsenic concentrations above the value recommended by the World Health Organization (WHO). An arsenic removal plant has been studied in a community of 50 families located in the province of Pisco, Peru, a filter media of activated carbon impregnated with iron (AC-Fe) was applied, the adsorption capacity of the material was studied against As(V) and As(III) species, also, a possible decrease in the adsorption capacity of chloride and sulfate ions. Modifications were made to the plant layout based on filtration columns and workflows. The arsenic level was reduced to levels recommended by the WHO, the plant production was estimated at 9,000 volumes of water bed until reaching its breakpoint. An optimum working flow rate of 1.8 m3 h−1 was found, it was also found that the zeolite column used for suspended solids removal did not contribute to the reduction of arsenic concentration, and the presence of ions did not reduce the arsenic removal capacity.
Application of Quercetin and its Novel Formulations in the Treatment
of Malignancies of Central Nervous System: An Updated Review of
Current Evidence based on Molecular Mechanisms
Authors: Jamshidi-Mouselou Mohammad Saleh , Hashemi Amirhossein , Jamshidi-Mouselou Mohammad Sobhan , Farkhondeh Tahereh , Pourhanifeh Mohammad Hossein , Samarghandian Saeed
Published: January 2024

Quercetin, a naturally occurring polyphenolic compound found in abundance
in vegetables and fruits, has emerged as a compelling subject of study in cancer treatment.
This comprehensive review delves into the significance and originality of quercetin's
multifaceted mechanisms of action, with a particular focus on its application in various
brain tumors such as glioblastoma, glioma, neuroblastoma, astrocytoma, and medulloblastoma.
This review scrutinizes the distinctive facets of quercetin's anti-cancer properties,
highlighting its capacity to modulate intricate signaling pathways, trigger apoptosis,
impede cell migration, and enhance radiosensitivity in brain tumor cells. Significantly,
it synthesizes recent research findings, providing insights into potential structure-activity
relationships that hold promise for developing novel quercetin derivatives with
heightened effectiveness. By unraveling the unique attributes of quercetin's anti-brain tumor
effects and exploring its untapped potential in combination therapies, this review
contributes to a deeper comprehension of quercetin's role as a prospective candidate for
advancing innovative treatments for brain cancer.
Recent Progress in the Synthetic Methods of Pyrazoloquinoline Derivatives
Authors: Borik Rita M. , Mostafa Mohamed S. , Behalo Mohamed S. , Khidre Rizk E.
Published: January 2024

The focus of this review is on the synthetic routes available for different types of
pyrazoloquinoline derivatives. There are three types of synthetic methods: i) from pyrazole
derivatives; ii) from quinoline derivatives; and iii) miscellaneous methods. The position of
the linkage between pyrazole and quinoline rings determines the seven isomers of pyrazoloquinolines.
The purpose of this review is to provide a guide for both synthetic and medicinal
chemists to discover and design new pyrazoloquinolines for medical purposes.
Targeted Inhibition of the PI3K/Akt/mTOR Signaling Axis: Potential for
Sarcoma Therapy
Authors: Wani Atif Khurshid , Singh Reena , Akhtar Nahid , Prakash Ajit , Nepovimova Eugenie , Oleksak Patrik , Chrienova Zofia , Alomar Suliman , Chopra Chirag , Kuca Kamil
Published: January 2024

Sarcoma is a heterogeneous group of malignancies often resistant to conventional chemotherapy
and radiation therapy. The phosphatidylinositol-3-kinase/ protein kinase B /mammalian target
of rapamycin (PI3K/Akt/mTOR) signaling pathway has emerged as a critical cancer target due
to its central role in regulating key cellular processes such as cell growth, proliferation, survival, and
metabolism. Dysregulation of this pathway has been implicated in the development and progression
of bone sarcomas (BS) and soft tissue sarcomas (STS). PI3K/Akt/mTOR inhibitors have shown
promising preclinical and clinical activity in various cancers. These agents can inhibit the activation
of PI3K, Akt, and mTOR, thereby reducing the downstream signaling events that promote tumor
growth and survival. In addition, PI3K/Akt/mTOR inhibitors have been shown to enhance the efficacy
of other anticancer therapies, such as chemotherapy and radiation therapy. The different types
of PI3K/Akt/mTOR inhibitors vary in their specificity, potency, and side effect profiles and may be
effective depending on the specific sarcoma type and stage. The molecular targeting of
PI3K/Akt/mToR pathway using drugs, phytochemicals, nanomaterials (NMs), and microbe-derived
molecules as Pan-PI3K inhibitors, selective PI3K inhibitors, and dual PI3K/mTOR inhibitors have
been delineated. While there are still challenges to be addressed, the preclinical and clinical evidence
suggests that these inhibitors may significantly improve patient outcomes. Further research is
needed to understand the potential of these inhibitors as sarcoma therapeutics and to continue developing
more selective and effective agents to meet the clinical needs of sarcoma patients.
Prognostic Significance and Functional Mechanism of UTS2 in Glioblastoma Multiforme
Authors: Wang Yanfei , Shen Langping , Sun Mingzhong
Published: January 2024

Aim:

We aimed to explore the role of urotensin 2 (UTS2) in glioblastoma (GBM).

Background:

GBM is the most malignant primary brain cancer with a poor prognosis. Previous
studies have suggested that GBM vessels undergo dynamic remodeling modulated by tumor vasodilation
and vasoconstriction instead of tumor angiogenesis.

Objective:

Here, we have first investigated the expression and function of UTS2, a potent vasoconstrictor,
in GBM.

Methods:

The mRNA expression profiles and clinical information of GBM patients were obtained
from the TCGA database. The clinical relevance of UTS2 was explored by the Mann-Whitney U
test and Cox hazard regression survival test. We further explored the role of UTS2 in GBM cell
proliferation, migration, and tumor immune microenvironment. Moreover, we established the in
vivo mice model to validate its oncogenic effects on GBM progression.

Results:

Although we did not find significant correlations between UTS2 expression and patients’
clinical characteristics, UTS2 was identified as a valid independent prognostic indicator according
to multivariate survival analysis. Knockdown of UTS2 resulted in decreased GBM cell proliferation
and migration. In addition, functional enrichment analysis implied UTS2 to be involved in the
regulation of the immune microenvironment. In vivo studies showed that UTS2 knockdown suppressed
GBM xenograft growth, highlighting the tumor-promoting effects of UTS2 on GBM.

Conclusion:

Our study identified that UTS2 could predict the prognosis of GBM patients and provided
evidence regarding its oncogenic effects both in vitro and in vivo.
Type 2 Diabetes Prevalence, Control and Management within Fiji,
Kiribati, Samoa, the Solomon Islands, Tonga, and Vanuatu: A Scoping
Review with a Systematic Approach
Authors: Kuek Timothy
Published: January 2024

Background:

Type 2 diabetes (T2D) causes significant morbidity and is disproportionately
prevalent in Pacific Island Countries (PICs). The socio-political demographics of PICs
are rapidly changing, and health services must adapt to match the needs of their population.

Objectives:

The objective of this study was to review the literature published within the last 15
years relating to T2D prevalence, control, and management, with a specific focus on targetable
areas for future funding and research projects.

Methods:

This review was conducted using the PRISMA guidelines. Inclusion criteria were: discussion
on T2D in the six PICs. Results were limited to those published between 1st January,
2006, and 27th July, 2023.

Results:

A total of 6,640 publications were retrieved, and 110 met the inclusion criteria. Nineteen
additional studies were identified through hand-searching. T2D prevalence differed between
countries but was predicted to increase in the coming decades, with projections of up to 31.2%
by 2030 in Tonga. Factors associated with T2D varied between countries, including Indian-Fijian
ethnicity in Fiji and tuberculosis in Kiribati. Control was generally poor, with high rates of undiagnosed
diabetes and microvascular complications. Epidemiological data was limited in some
cases, as was information describing the structure and function of diabetes services.

Conclusion:

The prevalence, control, and management of T2D varied between Fiji, Kiribati,
Samoa, the Solomon Islands, Tonga, and Vanuatu. Significant gaps remain in the data describing
these domains; however, there are clearly targetable areas for future research and diabetes management
programs.
Empagliflozin-A Sodium Glucose Co-transporter-2 Inhibitor: Overview of
its Chemistry, Pharmacology, and Toxicology
Authors: Yadav Jyoti , Ahsan Farogh , Panda Prabhudatta , Mahmood Tarique , Ansari Vaseem Ahamad , Shamim Arshiya
Published: January 2024

Background:

Empagliflozin is a sodium glucose co-transporter-2 (SGLT2) inhibitor
that has gained significant attention in the treatment of type 2 diabetes mellitus. Understanding its
chemistry, pharmacology, and toxicology is crucial for the safe and effective use of this medication.

Objective:

This review aims to provide a comprehensive overview of the chemistry, pharmacology, and toxicology of empagliflozin, synthesizing the available literature to present a concise
summary of its properties and implications for clinical practice.

Methods:

A systematic search of relevant databases was conducted to identify studies and articles
related to the chemistry, pharmacology, and toxicology of empagliflozin. Data from preclinical
and clinical studies, as well as post-marketing surveillance reports, were reviewed to provide a
comprehensive understanding of the topic.

Results:

Empagliflozin is a selective SGLT2 inhibitor that works by constraining glucose reabsorption in the kidneys, causing increased urinary glucose elimination. Its unique mechanism of
action provides glycemic control, weight reduction, and blood pressure reduction. The drug's
chemistry is characterized by its chemical structure, solubility, and stability. Pharmacologically,
empagliflozin exhibits favorable pharmacokinetic properties with rapid absorption, extensive
protein binding, and renal elimination. Clinical studies have demonstrated its efficacy in improving glycemic control, reducing cardiovascular risks, and preserving renal function. However,
adverse effects, for instance, urinary tract infections, genital infections, and diabetic ketoacidosis
have been reported. Toxicological studies indicate low potential for organ toxicity, mutagenicity,
or carcinogenicity

Conclusion:

Empagliflozin is a promising SGLT2 inhibitor that offers an innovative approach to
the treatment of type 2 diabetes mellitus. Its unique action mechanism and favorable pharmacokinetic profile contribute to its efficacy in improving glycemic control and reducing cardiovascular
risks. While the drug's safety profile is generally favorable, clinicians should be aware of potential adverse effects and monitor patients closely. More study is required to determine the longterm safety and explore potential benefits in other patient populations. Overall, empagliflozin
represents a valuable addition to the armamentarium of antidiabetic medications, offering significant benefits to patients suffering from type 2 diabetes mellitus. This study covers all aspects of
empagliflozin, including its history, chemistry, pharmacology, and various clinical studies, case
reports, and case series.
Insights into the Therapeutic uses of Plant Derive Phytocompounds on
Diabetic Nephropathy
Authors: Mitra Palash , Jana Sahadeb , Roy Suchismita
Published: January 2024

Diabetic nephropathy (DN) is one of the primary consequences of diabetes mellitus,
affecting many people worldwide and is the main cause of death under the age of sixty. Reactive
oxygen species (ROS) production rises during hyperglycemia and is crucial to the development of
diabetic complications. Advanced glycation end products (AGEs) are produced excessively in a
diabetic state and are accumulated in the kidney, where they change renal architecture and impair
renal function. Another important targeted pathway for the formation of DN includes nuclear factor
kappa-B (NF-kB), Nuclear factor E2–related factor 2 (Nrf2), NLR family pyrin domain containing
3 (NLRP3), protein kinase B/mammalian target of rapamycin (Akt/mTOR), and autophagy. About
40% of individuals with diabetes eventually acquire diabetic kidney disease and end-stage renal
disease that needs hemodialysis, peritoneal dialysis, or kidney transplantation to survive. The current
state of acceptable therapy for this kidney ailment is limited. The studies revealed that some
naturally occurring bioactive substances might shield the kidney by controlling oxidative stress,
renal fibrosis, inflammation, and autophagy. In order to provide new potential therapeutic lead
bioactive compounds for contemporary drug discovery and clinical management of DN, this review
was designed to examine the various mechanistic pathways by which conventional plants
derive phytocompounds that are effective for the control and treatment of DN.
Intranasal Route an Alternative Approach for Systemic Drug Delivery: Recent Strategies and Progression
Authors: Bala Rajni , Malik Deepinder Singh , Madan Reecha , Jindal Shammy , Kaur Vimanpreet
Published: January 2024

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Intranasal administration has proven to be a viable alternative for local and systemic delivery of varied therapeutic agents. This route has been potentially researched for delivering polar compounds, vaccines, hormones, peptides, proteins, etc. Being non-invasive and painless with a fast onset of action (both local and systemic), intranasal has become an ideal route for medication to children. This route is specifically employed for the delivery of drugs that are unstable in GIT, which gets significantly degraded or metabolized by the first-pass effect. The nasal route's high absorption and permeability profile has led to its exploration as a substitute for parenteral delivery. This paper reviews the feasibility and potentials of intranasal administration, discussing its benefits, drawbacks, market analysis, factors affecting nasal drug delivery system, conventional and novel strategies (polymeric and nano-carrier-based delivery systems) to improve nasal ab-sorption and its clinical management of varied systemic and topical disorders viz. neurodegenerative, pulmonary, microbial, neoplastic, etc.
Project-based learning
Authors: Quinapallo-Quintana Arnaldo Miguel , Baldeón-Zambrano Alicia Ximena
Published: January 2024

In the degree in Pedagogy in Experimental Sciences at ULEAM Chone extension, the effectiveness of the project-based learning methodology has not been evaluated, so it is necessary to determine its uses and advantages at the university level. The objective of the study is to analyze project-based learning among students of the Pedagogy in Experimental Sciences career. It is developed through a mixed approach that integrates qualitative and quantitative data, the inductive method is used, and the study population is made up of students of the degree. The survey technique is used. The results demonstrate that PBL contributes to the development of research and problem-solving skills, collaboration and teamwork, the application of theoretical knowledge to practical situations, and the motivation and commitment of students, with a positive experience in its use.
Qualities of Diabetic Food Developed from Brown Rice and Oyster Mushroom
Authors: Sulistyowati Etik , Kristianto Yohanes , Handayani Dian , Kusumastuty Inggita , Videlia Videlia , Kuncoro Safiratuz Zahra ‘Aisy
Published: January 2024

The prevalence of diabetes mellitus has been increasing. This study aimed to develop Food for Special Dietary Use (FSDU) for individuals with diabetes. Different combinations of food ingredients were added to the basic formula, consisting of brown rice and mushroom flour in a ratio of 70% and 11%. The combinations used in the formulation were F1 = 9% moringa and fish flour, F2 = 10% carrot and fish flour, F3 = 11% moringa and tempeh flour, and F4 = 12% tempeh flour. The results showed that the FSDU contained energy, fat, and fiber ranging from 391.33–404.33 Kcal, 5.53–7.75 g, and 4.22–7.60 g per 100 g product, respectively. These values were slightly higher than the respective value of a commercial product. The panelists expressed positive acceptance of the developed FSDU products, with F2 chosen as the most preferred. The developed FSDU exhibited lower scores for feeling of hunger, desire to eat, and prospective food consumption compared to the commercial product. The product provided a feeling of fullness similar to the commercial counterpart. In conclusion, the FSDU based on brown rice and oyster mushroom with an additional 10% carrot fish flour would be the most preferred option for further use as FSDU for diabetics.
Exploring Organoleptic, Chemical, and Physical Properties of Foxtail Millet (Setaria italica) and Snakehead Fish (Channa striata) Cookies as Emergency Food Alternatives
Authors: Widiati Aloisia Lovy , Astutik Rini Duwi , Abbas Marwati , Nastaina Hayu Iyaka , Widyanto Rahma Micho
Published: January 2024

High disaster risk in Indonesia necessitates the development of emergency food products (EFP). One potential EFP is cookies made from foxtail millet and snakehead fish. This study aimed to examine the sensory, chemical, and physical properties of EFP cookies with different formulations. This research used a completely randomized design. Variations in the composition of wheat flour, foxtail millet flour, and snakehead fish flour were P0(100:0:0), P1(8:76:16), P2(8:66:26), and P3(8:56:36). All treatments were analyzed for organoleptic quality using hedonic tests and proximate analysis, water activity analysis using an aw meter, and physical quality analysis using tensile strength. The Zeleny method was applied to identify the most optimal treatment, revealing that P1 emerged as the best formulation. P1 has the color, aroma, and taste that the panelists like, while maintaining a neutral rating in texture. P1 contains 241.51 kcal/50 grams of energy, 10.97% protein, 41.16% fat, 47.86% carbohydrates, 1.93% ash content, 4.93% water content, 0.55 water activity, and 17.16 N breaking strength. These results are in accordance with EFP and SNI 2973:2011 standards. The recommended daily consumption is 18 pieces (each piece weighing 25 grams) if not accompanied by any other food, or only 4-5 pieces if consumed as a snack.
Abortion Article Debate and Discussion Process in Act No. 36 Year 2019 About Health
Authors: Afriana Wendra , Mariyah Chusnul , Azis Harry Azhar
Published: January 2024

AbstractThis article examines the process of discussing the health bill specifically relating to abortion. The pros and cons of the substance of abortion gave birth to two factions, namely pro choice and pro life. The pro life faction considers the discussion on abortion should not be submitted in the ruling. Those belong to this faction include the NGO National Movement for life, Pro life Indonesia as well as a number a mps from the PDS party in the Commission IX of the House of Representative. In opposition, the pro choice group, who support the abortion article to be included in the Bill, includes NGO Yayasan Kesehatan Erempuan, Perkumpulan Keluarga Berencana Indonesia and the majority MPs within the Commission IX from PDIP, Golkar, Demokrat, PKS, PPP, PKB, BPD, and PAN. MPs from PBR accepts the abortions article with a condition that rulings on rape victims should not be included. There are three ideological groupings based on religion, feminism, and secularism. The decision making process on the substance of the material was held privately through the lobby forum because a meeting failed to reach a settlement or approved. That the two factions finally reach on compromise agreement through lobby forum pursued by factions in order to accelerate the decision making.Â Key words: Deliberation, debate, ideology, abortion.
New Public Service In Bandung Through The Concept Of Smart City
Authors: Alim Syahirul , Nisa Arie Kumala , Hair Abdul
Published: January 2024

New Public Service is a paradigm of governance that prioritizes public services in a democratic, fair and equitable manner. Bandung City Government should provide good public services along with the development of the current digital era. Smart City is one way for the Bandung City Government to organize its government. The results of this study indicate that the public services of the city of Bandung are carried out in various ways such as providing services to the community easily through applications, wifi parks, online complaint services, official websites, e-budgeting, and so on.Keywords: New Public Service, Smart City, Bandung
Creep of a closed cylindrical tank at hydrostatic pressure
Authors: Gatiev M. Sh. , Yazyev B. M. , Ivanova Yu. P. , Klyuev S. V.
Published: January 2024

Objective. When constructing the resolving relations of the theory of shells, the validity of the basic assumptions about the material of the structure under consideration is assumed, which is considered homogeneous, isotropic and viscoelastic, i.e. obeying the Maxwell-Gurevich law. The subject to study is a polymer cylindrical shell, rigidly clamped at the base and subject to internal hydrostatic pressure. Method. The problem is reduced to an inhomogeneous differential equation of the fourth degree with respect to the displacement of the middle surface w along the z axis. Since the closed form representation of the solution to this equation is extremely difficult, the search for it is presented numerically, in particular, using the grid method. The creep strain components ε*x, ε*θ, γ*xθ were determined as a linear approximation of the velocity by the Runge-Kutta method. Result. In the process of calculating the shell using moment theory, it was found that as a result of shell creep, tangential stresses increased by more than 12 percent. Conclusion. The proposed technique makes it possible to simulate changes in the mechanical properties of the shell (for example, indirect heterogeneity) caused by the influence of physical fields.
Numerical Analysis of Infill Plate Performance on Steel Plate Shear Wall (SPSW)
Authors: Yobelita Naomi , Siswosukarto Suprapto , Muslikh Muslikh , Purba Ronny
Published: January 2024

Steel Plate Shear Wall (SPSW) is one of the systems that can be used to minimize the effect of earthquakes on buildings. The main energy-absorbing element of the steel plate shear wall system is on the thin steel plate that are located on the center of the steel frame. This thin steel plate is called infill plates. This infill plate will later experience buckling and form a series of tension field action. This paper will prove that the infill plates in the steel plate shear wall system provides significant strength contribution in resisting lateral loads.The analysis was carried out by comparing the strength provided by steel plate shear wall system and simple beam-column steel frame system (without infill plate) with some aspect ratio variation (width per height). The material used for the infill plates was low yield strength (LYS) steel plate of 1.30 mm thick, while the column (vertical boundary element) used WF 400.200.8.12, and the beam (horizontal boundary element) used WF 350.175.7.11. The loading used a monotonic pushover loading of 2% drift (68.8 mm) for each specimen.The analysis result proved that the steel plate shear wall system (frame with infill plates) had significant strength advantage compared to the plateless frame system. The aspect ratio (L/h) on infill plates were also affects the strength of the entire system, where the greater the aspect ratio, the greater the strength. The strength value of the SPSW specimen at 2% drift loading on aspect ratio L/h = 1.00, 1.50, 2.00, 2.50 respectively was 614.95 kN, 634.88 kN, 646.69 kN, and 688.03 kN. Meanwhile, the strength increment percentage between steel plate shear wall systems compared to plateless frame systems in each aspect ratio was 21.67%, 32.39%, 42.48%, and 54.20%.