bluuebunny/crossref_metadata_2025 huggingface dataset:
On the use of Machine Learning for predictive maintenance of power transformers
Authors: Pacheco Carla , Paes Vagner , Carvalho Marcelo , Lopes Felipe , Machado Gabriel , Garcia Alex , Neto Edmilson , Santos Jefferson , Haeusler Edward , Marotti Ana
Published: February 2024

This paper focuses on the use of machine learning algorithms to assist predictive maintenance aiming at reducing downtime and maintenance costs associated with power transformers. The paper presents two ML predictive indicators, Chromatographic Assay Indicator (CAI) and Electrical Failure Risk Indicator (EFRI), which use chromatographic and sensors data, respectively. The CAI evaluation showed a significant improvement in predicting failures compared with classical methods, whereas the EFRI tests showed it can be helpful to help maintenance team in identifying potential problems. The proposed solution integrates classical chromatographic analysis techniques with these ML indicators and aims at supporting maintenance specialists in decision-making processes, leading to more efficient maintenance management and reduced costs associated with equipment downtime.
Análise Multicritério e Rede Neurais Artificiais para prever ações na bolsa de valores
Authors: Conte Bruno Nicolau , Limão Oliveira Roberto Célio
Published: February 2024

Este artigo apresenta uma abordagem inovadora que combina o método Analytic Hierarchy Process (AHP) com Redes Neurais Artificiais (RNAs) para prever o desempenho de ações na Bolsa de Valores. O AHP é utilizado para atribuir pesos às variáveis relevantes, considerando sua importância relativa, enquanto as redes neurais são empregadas para modelar e prever o comportamento das ações. Ao combinar essas duas técnicas, a precisão das previsões é aprimorada, superando métodos tradicionais como análise fundamentalista e análise técnica. O desempenho da abordagem foi avaliado utilizando dados históricos de empresas listadas na Bolsa de Valores, métricas como o erro médio absoluto (MAE), erro quadrático médio (MSE) e a Raiz do erro quadrático médio (RMSE) foram aplicadas.
Aplicação de Técnicas de Otimização de Hiperparâmetros em Modelos de Machine Learning na Tarefa de Classificar Bons e Maus Clientes
Authors: Pontes Júnior Armando , Fagundes Roberta
Published: February 2024

A indústria financeira necessita de soluções rápidas, de menor custo e mais assertivas na classificação de risco de crédito. Métodos de machine learning estão cada vez mais sendo incorporados para executar essa tarefa. Além disso, técnicas de otimização de hiperparâmetros podem melhorar o desempenho de classificadores. Neste trabalho foram aplicadas duas importantes técnicas de otimização com cinco classificadores distintos, são eles: Decision Tree (DT), Random Forest (RF), MultiLayer Perceptron (MLP), eXtreme Gradient Boost (XGBoost) e Light Gradient Boost Machine (LGBM). Para medir o desempenho dos classificadores foram utilizadas as seguintes métricas: Accuracy, Precison, Recall e F1-Score. Os modelos foram treinados e testados com informações de duas bases de dados. Inicialmente foram utilizadas as configurações padrões dos hiperparâmetros, e, posteriormente, foram aplicadas as otimizações bayesiana e por Particle Swarm Optimization (PSO) para alcançar melhores resultados. A otimização bayesiana apresentou melhorias nas métricas de todos os modelos, com destaque para o Recall, chegando a uma assertividade de 91,4% no classificador MLP. Porém, a otimização por PSO não apresentou melhoria no desempenho.
Ensemble of Artificial Neural Networks and AutoML for Predicting Steel Properties
Authors: Silva Krigor , Serpa Pedro , Sgrott Douglas , Cerqueira Fabricio , Miranda Fabiano , Silva Filho José Francisco , Parpinelli Rafael
Published: February 2024

The design of new steel grades is a continuous pursuit in the metallurgical industry, aiming to develop lighter and stronger materials for diverse industries. This study explores the use of an ensemble of artificial neural networks, named EANN, to model the relationships between chemical composition, process parameters, and mechanical properties of five types of steels. Auto-Keras, an automated machine learning framework, is employed to identify the best configurations for the ANNs and create the ensemble model. The best ANN, named B-ANN, obtained through the same AutoML process, and the one model ANN generated by Auto-Keras, named ANN, are used as a benchmark to evaluate the E-ANN performance. The results obtained show that the E-ANN model is competitive in terms of predictive capability. Sensitivity analysis provides insights into the influence of input parameters on mechanical properties, while Shapley Value analysis highlights the relative importance of these parameters. The findings contribute to the understanding of steel behavior and provide guidance for steel design processes. This study demonstrates the effectiveness of E-ANN in predicting mechanical properties and emphasizes the value of data-driven techniques and automated machine learning in steel design.
Deepfake audio as a data augmentation technique for training automatic speech to text transcription models
Authors: Ferreira Alexandre , Campelo Cláudio
Published: February 2024

To train transcriptor models that produce robust results, a large and diverse labeled dataset is required. Finding such data with the necessary characteristics is a challenging task, especially for languages less popular than English. Moreover, producing such data requires significant effort and often money. Therefore, a strategy to mitigate this problem is the use of data augmentation techniques. In this work, we propose a framework that approaches data augmentation based on deepfake audio. To validate the produced framework, experiments were conducted using existing deepfake and transcription models. A voice cloner and a dataset produced by Indians (in English) were selected, ensuring the presence of a single accent in the dataset. Subsequently, the augmented data was used to train speech to text models in various scenarios.
Evaluation of satellite rainfall estimates using PERSIANN-CDR and TRMM over three critical cells in Jordan
Authors: Al-Sheriadeh Mohanned , Al-Sharman Anas Riyad
Published: February 2024

Effective management of water resources is heavily dependent on accurate knowledge of rainfall patterns. Satellite rainfall estimates (SREs) have become increasingly popular due to their ability to provide spatial rainfall data. However, the accuracy of SREs is limited by a variety of factors including a lack of observations, inadequate evaluation techniques, and the use of short evaluation durations. To improve our understanding of SREs, this study evaluated the long-term performance of Tropical Rainfall Measuring Mission (TRMM) and PERSIANN-CDR by analyzing their spatiotemporal patterns. Daily, monthly, seasonal, and annual precipitation estimates were evaluated using statistical measures and data from 71 rain gauges across three critical cells in Jordan from 2000 to 2013. The results showed that while both SREs had low accuracy on a daily scale, TRMM 3B43 performed better than PERSIANN-CDR at the monthly level. Additionally, TRMM 3B43 exhibited superior performance during the heavy rainy season, whereas PERSIANN-CDR showed better results during other seasons. In annual studies, TRMM 3B43 was found to be more accurate than PERSIANN-CDR for the north and south cells, while PERSIANN-CDR had a higher correlation coefficient for the middle cell. These findings can contribute to the development of more reliable and accurate SREs, thereby improving water resource management studies.
The impact of government support and farmers’ pro-environmental intention on water-saving irrigation techniques adoption: Evidence using propensity score matching
Authors: Zhang Jingwen , Song Jianfeng
Published: February 2024

Agricultural water-saving irrigation (WSI) techniques becomes the main way to build drought resilience in rural areas. The effectiveness of government support in promoting the adoption of water-saving technologies is controversial. There is a research gap concerning farmers with different pro-environmental intentions to the adoption of water-saving behaviors under the influence of government support. This study is based on a survey in Yulin, Shaanxi, China, using 404 sample households. Pro-environmental intentions have been introduced into this paper by using the entropy weight method, and propensity score matching has been used to overcome the confounding between government support and farmers' adoption. Our findings reveal that farmers who received government support exhibit a significantly higher probability of adopting WSI techniques, ranging from 80 to 81.6%, representing a notable increase of 29.0–30.7% compared to those without government support. Furthermore, government support significantly affects farmers with weak pro-environmental intentions by 40.5%, but it does not have a significant impact on farmers with stronger pro-environmental intentions. These insights emphasize the significance of subsidies and advocate for an approach that tailors policies based on varying levels of pro-environmental intentions. This is particularly crucial considering that farmers with weaker intentions may be inclined to adopt the technology but face higher efficiency risks.
Modeling of aquifer geo-hydraulic characteristics with geo-electrical methods at a major coastal aquifer system in Uyo, southern Nigeria
Authors: Udosen Ndifreke I. , Ekanem Aniekan M. , George Nyakno J.
Published: February 2024

Characterization of aquifer geo-hydraulic properties is essential for groundwater management and conservation. This work demonstrates the use of electrical resistivity surveying data in the characterization of important geo-hydraulic properties within a major coastal aquifer in southern Nigeria. Geo-electrical data acquired along profile lines with the use of Schlumberger array configuration were used to determine the aquifer geo-hydraulic parameters such as aquifer resistivity ρb, water resistivity ρw, porosity Φ, formation factor F, hydraulic conductivity K, transmissivity T, permeability Kp, and tortuosity τ. The resistivity inversion models delineated the occurrence of four lithological layers, with resistivity of the geo-layers ranging from 2.4 to 4,393 Ω m. Contour maps were created to show the distribution of the various geo-electrical and geo-hydraulic parameters over the study area. Regression curves showing the relationship between the geo-hydraulic parameters were generated and used to generate empirical relationships between the parameters. The empirical formulas developed for these geo-hydraulic parameters will aid in future work seeking to characterize aquifer zones and model aquifer geo-hydraulic units. In all, electrical resistivity surveying was found to be a noninvasive, cost-effective, and efficient method of characterizing aquifer geo-hydraulic properties via nonpoint geo-electrical data collected over the earth's surface.
Enhancing drought prediction precision with EEMD-ARIMA modeling based on standardized precipitation index
Authors: Rezaiy Reza , Shabri Ani
Published: February 2024

This study introduces ensemble empirical mode decomposition (EEMD) coupled with the autoregressive integrated moving average (ARIMA) model for drought prediction. In the realm of drought forecasting, we assess the EEMD-ARIMA model against the traditional ARIMA approach, using monthly precipitation data from January 1970 to December 2019 in Herat province, Afghanistan. Our evaluation spans various timescales of standardized precipitation index (SPI) 3, SPI 6, SPI 9, and SPI 12. Statistical indicators like root-mean-square error, mean absolute error (MAE), mean absolute percentage error (MAPE), and R2 are employed. To comprehend data features thoroughly, each SPI series initially computed from the original monthly precipitation time series. Subsequently, each SPI undergoes decomposition using EEMD, resulting in intrinsic mode functions (IMFs) and one residual series. The next step involves forecasting each IMF component and residual using the corresponding ARIMA model. To create an ensemble forecast for the initial SPI series, the predicted outcomes of the modeled IMFs and residual series are finally added. Results indicate that EEMD-ARIMA significantly enhances drought forecasting accuracy compared to conventional ARIMA model.
FRANCIS KÉRÉ: ARQUITETURA COMO LUGAR AMENO NOS TRÓPICOS ENSOLARADOS
Authors: Sobreira Fabiano José Arcadio
Published: February 2024

Brasil e Burkina Faso: territórios ao mesmo tempo distantes e próximos em cultura, geografia e arquitetura. Este ensaio trata de aproximações e propõe uma leitura das obras do arquiteto burquinês Francis Kéré, a partir do roteiro proposto em 1976 pelo pernambucano Armando de Holanda, sobre a "arquitetura como lugar ameno nos trópicos ensolarados". Grande parte do território brasileiro, em especial a região Nordeste e parte das regiões Centro-Oeste e Norte, se inserem na mesma faixa climática do território de Burkina Faso, áreas que podem ser identificadas pelo que Holanda definiu como "trópicos ensolarados". Apesar de incluírem variações e peculiaridades - que vão do tropical ao semiárido e o equatorial úmido, no caso do Brasil, e das savanas, estepes e desertos no caso do país africano - apresentam características que demandam estratégias comuns de projeto, construção e relação com a natureza, como aquelas recomendadas por Holanda e praticadas por Kéré. Este ensaio propõe um percurso a partir dos nove passos do roteiro proposto por Armando de Holanda, como meio de aproximação sobre as obras de Francis Kéré: (1) criar uma sombra; (2) recuar as paredes; (3) vazar os muros; (4) proteger as janelas; (5) abrir as portas; (6) continuar os espaços; (7) construir com pouco; (8) conviver com a natureza; (9) construir frondoso.
Association of miRNA and Bone Tumors: Future Therapeutic Inroads
Authors: Al-Shibli Rashid , AlSuleimani Mohammed , Ahmed Ibrahim , Al Lawati Abdullah , Das Srijit
Published: February 2024

Small endogenous non-coding RNA molecules known as micro-ribonucleic
acids (miRNAs) control post-transcriptional gene regulation. A change in miRNA expression
is related to various diseases, including bone tumors. Benign bone tumors are
categorized based on matrix production and predominant cell type. Osteochondromas
and giant cell tumors are among the most common bone tumors. Interestingly, miRNAs
can function as either tumor suppressor genes or oncogenes, thereby determining the
fate of a tumor. In the present review, we discuss various bone tumors with regard to
their prognosis, pathogenesis, and diagnosis. The association between miRNAs and
bone tumors, such as osteosarcoma, Ewing’s sarcoma, chondrosarcoma, and giant-cell
tumors, is also discussed. Moreover, miRNA may play an important role in tumor proliferation,
growth, and metastasis. Knowledge of the dysregulation, amplification, and deletion
of miRNA can be beneficial for the treatment of various bone cancers. The miRNAs
could be beneficial for prognosis, treatment, future drug design, and treatment of resistant
cases of bone cancer.
Role of TBK1 Inhibition in Targeted Therapy of Cancer
Authors: Yang Xueqing , Liu Zongliang
Published: February 2024

TANK-binding kinase 1 (TBK1) is a serine/threonine protein that plays a crucial role in
various biological processes like immunity, autophagy, cell survival, and proliferation. The level
and kinase activity of the TBK1 protein is regulated through post-translational modifications
(PTMs). TBK1 mainly mediates the activation of IRF3/7 and NF-κB signaling pathways while also
participating in the regulation of cellular activities such as autophagy, mitochondrial metabolism,
and cell proliferation. TBK1 regulates immune, metabolic, inflammatory, and tumor occurrence and
development within the body through these cellular activities. TBK1 kinase has emerged as a promising
therapeutic target for tumor immunity. However, its molecular mechanism of action remains
largely unknown. The identification of selective TBK1 small molecule inhibitors can serve as valuable
tools for investigating the biological function of TBK1 protein and also as potential drug candidates
for tumor immunotherapy. The current research progress indicates that some TBK1 inhibitors
(compounds 15,16 and 21) exhibit certain antitumor effects in vitro culture systems. Here, we summarize
the mechanism of action of TBK1 in tumors in recent years and the progress of small molecule
inhibitors of TBK1.
Abdomen Malignant Myxoid Leiomyosarcoma with PDGFRA and TP53
Missense Mutation: A Case Report
Authors: Li Yao-xuan , Yu Jian-ping , Gong Yan-qing , Huang Hai-fu , Wu Xian-lin
Published: February 2024

Background:

Malignant myxoid leiomyosarcoma (MMLS) is most commonly found in
the uterus but can also occur in other areas, such as the extremities, vulva, chest wall, and abdominal
cavity. This cancer is more prevalent in women and has a poor prognosis with a high rate of recurrence
and a significant percentage of metastasis.

Case Representation:

Herein, we report the case of a 64-year-old female patient who presented with
3-month history of left lower abdominal mass. The patient underwent abdominal malignancy resection
and was subsequently diagnosed with myxoid leiomyosarcoma. The patient experienced a recurrence
and metastasis with significant ascites after the initial surgery and did not respond to treatment
with oral Anrotinib in combination with Tislelizumab immunotherapy. Further genetic testing using
next-generation sequencing (NGS) identified missense mutations in the PDGFRA and TP53 genes in
the patient's plasma, but no mutations in the KIT gene were detected. Immunohistochemical analysis
of the tumor tissue also revealed a negative expression of PD-L1. As a result, we altered her targeted
therapy to Avapritinib, which resulted in significant improvement in her symptoms, including abdominal
distension and pain, a decrease in ascites, and the KPS score increased from 60 points before
treatment to 90 points after treatment SD (stable disease) was achieved for three months after treatment.

Conclusion:

In this case report, we present the instance of a patient with malignant myxoid leiomyosarcoma
with a missense mutation in both the PDGFRA and TP53 genes. We found that targeted
therapy with Avapritinib was effective in achieving a positive outcome in this patient. Our findings
suggest that genetic detection is possible to better understand the biological behavior, genetic characteristics,
and patient's response and tolerance to certain drugs, thus selecting the best treatment plan
for the patient. Avapritinib may be a promising new treatment option for leiomyosarcoma patients
with similar genetic mutations.
Improved Hybrid Approach for Enhancing Protein-Coding Regions Identification in DNA Sequences
Authors: Hassan Emad S. , Dessouky Ahmed M. , Fathi Hesham , Salama Gerges M. , Oshaba Ahmed S. , El-Emary Atef , Abd El‑Samie Fathi E.
Published: February 2024

Introduction:

Identifying and predicting protein-coding regions within DNA sequences
play a pivotal role in genomic research. This paper introduces an approach for identifying proteincoding
regions in DNA sequences by employing a hybrid methodology that combines digital bandpass
filtering with wavelet transform and various spectral estimation techniques to enhance exon
prediction. Specifically, the Haar and Daubechies wavelet transforms are applied to improve the accuracy
of protein-coding region (exon) prediction, enabling the extraction of intricate details that
may be obscured in the original DNA sequences.

Methods:

This research work showcases the utility of Haar and Daubechies wavelet transforms,
both non-parametric and parametric spectral estimation techniques, and the deployment of a digital
bandpass filter for detecting peaks in exon regions. Additionally, the application of the Electron-Ion
Interaction Potential (EIIP) method for converting symbolic DNA sequences into numerical values
and the utilization of Sum-of-Sinusoids (SoS) mathematical model with optimized parameters further
enrich the toolbox for DNA sequence analysis, ensuring the success of the proposed approach
in modeling DNA sequences, optimally, and accurately identifying genes.

Results:

The outcomes of this approach showcase a substantial enhancement in identification accuracy
for protein-coding regions. In terms of peak location detection, the application of Haar and
Daubechies wavelet transforms enhances the accuracy of peak localization by approximately (0.01,
3-5 dB). When employing non-parametric and parametric spectral estimation techniques, there is an
improvement in peak localization by approximately (0.01, 4 dB) compared to the original signal.
The proposed approach also achieves higher accuracy, when compared with existing ones.

Conclusion:

These findings not only bridge gaps in DNA sequence analysis but also offer a promising
pathway for advancing exonic region prediction and gene identification in genomics research.
The hybrid methodology presented stands as a robust contribution to the evolving landscape of genomic
analysis techniques.
Network Reorganization for Neurophysiological and Behavioral Recovery
Following Stroke
Authors: Qi Yuan , Xu Yujie , Wang Huailu , Wang Qiujia , Li Meijie , Han Bo , Liu Haijie
Published: February 2024

Stroke continues to be the main cause of motor disability worldwide. While rehabilitation
has been promised to improve recovery after stroke, efficacy in clinical trials has been mixed. We
need to understand the cortical recombination framework to understand how biomarkers for neurophysiological
reorganized neurotechnologies alter network activity. Here, we summarize the principles
of the movement network, including the current evidence of changes in the connections and function
of encephalic regions, recovery from stroke and the therapeutic effects of rehabilitation. Overall,
improvements or therapeutic effects in limb motor control following stroke are correlated with the effects
of interhemispheric competition or compensatory models of the motor supplementary cortex.
This review suggests that future research should focus on cross-regional communication and provide
fundamental insights into further treatment and rehabilitation for post-stroke patients.
Estimating Hidden Population Size of COVID-19 using Respondent-Driven
Sampling Method - A Systematic Review
Authors: SeyedAlinaghi SeyedAhmad , Afzalian Arian , Dashti Mohsen , Ghasemzadeh Afsaneh , Parmoon Zohal , Shahidi Ramin , Varshochi Sanaz , Pashaei Ava , Mohammadi Samaneh , Akhtaran Fatemeh Khajeh , Karimi Amirali , Nasiri Khadijeh , Mehraeen Esmaeil , Hackett Daniel
Published: February 2024

Introduction:

Currently, the ongoing COVID-19 pandemic is posing a challenge to
health systems worldwide. Unfortunately, the true number of infections is underestimated due to
the existence of a vast number of asymptomatic infected individual’s proportion. Detecting the
actual number of COVID-19-affected patients is critical in order to treat and prevent it. Sampling
of such populations, so-called hidden or hard-to-reach populations, is not possible using conventional
sampling methods. The objective of this research is to estimate the hidden population size
of COVID-19 by using respondent-driven sampling methods.

Methods:

This study is a systematic review. We have searched online databases of PubMed, Web
of Science, Scopus, Embase, and Cochrane to identify English articles published from the beginning
of December 2019 to December 2022 using purpose-related keywords. The complete texts
of the final chosen articles were thoroughly reviewed, and the significant findings are condensed
and presented in the table

Results:

Of the 7 included articles, all were conducted to estimate the actual extent of COVID-
19 prevalence in their region and provide a mathematical model to estimate the asymptomatic
and undetected cases of COVID-19 amid the pandemic. Two studies stated that the prevalence of
COVID-19 in their sample population was 2.6% and 2.4% in Sierra Leone and Austria, respectively.
In addition, four studies stated that the actual numbers of infected cases in their sample
population were significantly higher, ranging from two to 50 times higher than the recorded reports.

Conclusions:

In general, our study illustrates the efficacy of RDS sampling in the estimation of
undetected asymptomatic cases with high cost-effectiveness due to its relatively trouble-free and
low-cost methods of sampling the population. This method would be valuable in probable future
epidemics.
The Possible Protective Effect of Taurine on Bisphenol Induced
Structural Changes on the Cerebral Cortex of Rats: Histological and
Immunohistochemical Study
Authors: Kandeel Samah , Abd-Elsalam Marwa M. , Abd-Elsalam Sherief , Elkaliny Heba Hassan
Published: February 2024

Introduction:

Bisphenol A (BPA) is a chemical compound that has been used in many
industries, such as paints and dental sealants. Taurine is a semi-essential amino acid with antioxidant,
anti-inflammatory, and anti-apoptotic actions.

Aim:

This study aimed to evaluate the possible protective effect of taurine on BPA-induced structural
changes in the cerebral cortex of rats using histological and immunohistochemical methods.

Methods:

35 Wistar rats (180-200 gm) were divided into control: 10 rats; Group I: 5 rats received
corn oil (0.5 mL/day); Group II (Bisphenol low dose; BPAL): 5 rats received a low dose of BPA
(25 mg/kg/three times/week); Group III (Bisphenol high dose; BPAH): 5 rats received a high dose
of BPA (100 mg/kg/three times/week; Group IV: (BPAL + taurine): 5 rats received taurine 100
mg/kg/day and BPAL (25 mg/kg/three times/week); Group V: (BPAH + taurine): 5 rats received
taurine 100 mg/kg/day and BPH (100 mg/kg/ three times/week).

Results:

BPAL& BPAH groups showed significant dose-dependent histological changes of the neuropil,
pyramidal, and neuroglial cells at H&E stained sections, significantly increased GFAP, caspase-
3 immunohistochemical reaction with cells positive for Ki67 with many mitotic figures. BPAL +
taurine and BPAH + taurine groups showed amelioration of the previously mentioned results.

Conclusion:

Taurine ameliorated the structural changes induced by BPA in the cerebral cortex of
rats.
Topology Optimization of Additive – Manufactured Autonomous Ground Vehicle Mount
Authors: Al-Fahoum Amjed , Elsaaideh Hamzah A.
Published: February 2024

Introduction:

The existence of substantial amounts of comparatively unused material
inside a certain section indicates a deficiency in resource utilization. The existence of stress concentrations leads to a decrease in both the rigidity and durability of the component

Method:

Using finite element analysis (FEA), additive manufacturing (AM), and topology optimization (TO) together in this work led to a new patent for making a lightweight part for an unmanned ground vehicle (UGV). Topology optimization is crucial for improving the performance of
additive manufacturing and achieving design goals. The process of engineering design frequently
leads to mechanical design being characterized by heightened complexity and improved efficiency,
owing to its need for exploration and iteration. Employing additive manufacturing and topological
optimization methodologies, we developed the optimal prototype. Using ANSYS software makes it
possible to change the engineering principle of topology optimization so that it works with additive
manufacturing. At the same time, we are doing a full evaluation to see if adding topology optimization is possible, taking into account its pros and cons.

Result:

The results of the study reveal that the proposed intervention has the potential to address
other stress-related illnesses. The preliminary design proposal projected a cost of 400 Jordanian
dinars (JD).

Conclusion:

However, through the process of optimization, we successfully achieved the ultimate
design at a reduced cost of 200 JD. The revised design not only provides cost savings but also exhibits greater eco-friendliness.
Last Decades’ Overview on Tandem Catalysis: Intrigue in Organo-metallic Chemistry
Authors: Kuchhadiya Jyoti , Kapadiya Khushal
Published: February 2024

Catalytic transformations have been observed in every reaction to provide a specific
product and to formulate regio and stereo-selective adducts in well-defined pathways. Among
various catalytic processes used in current chemistry, tandem catalysis has been proven to be an
effective technology by applying the technology for better and time-saving ways of production. It
has shown its usability in various fields of research like organic reactions, inorganic salt
extractions, isolation, and purification of intermediates, photoprotection of dye, pigment, and
polymer chemistry, specifically in paint industries, biological sequencing and natural product
chemistry. Ideally, it is a single molecule conversation to the desired product (beneficial to both
research and industries) with many competing effects in spatial arrangement with almost no major
equipment in operation. The advantages of tandem catalysis in the field of chemistry (Organic/Biochemistry/
Polymer chemistry etc.) by utilizing the positive side is a newer way for energetic and
favourable technology.
Bioactive Constituents and the Molecular Mechanism of Melastoma
dodecandrum Lour. in the Treatment of Inflammation Based on Network
Pharmacology and Molecular Docking
Authors: Shuang Liu , Weiwen Qiu , Qizhao Yin , Meilu Zhao , Mingrong Mei , Houxing Lei , Xiaoqin Zhang
Published: February 2024

Background:

Melastoma dodecandrum Lour. (MD) is a component used in traditional
Chinese medicine that is widely distributed in southern China. MD has long been used clinically to
treat various diseases, such as inflammation. However, the potential anti-inflammatory mechanism of
MD remains to be elucidated.

Objective:

In this study, network pharmacology and experimental validation have been used to explore
the underlying mechanism of MD in inflammation.

Methods:

The chemical composition of MD was determined using ultra-high performance liquid
chromatography-electrospray ionization-high resolution mass spectrometry (UHPLC-ESI-HRMS).
The effects of MD on pro-inflammatory cytokines, such as NO, i-NOS, IL-1β, and TNF-α, in
RAW264.7 cells stimulated by lipopolysaccharide (LPS) were determined by ELISA and QRT-PCR.
Through the analysis of multiple databases, targets for the treatment of inflammation with MD were
identified. Other extensive analyses included PPI, GO, and KEGG pathway enrichment, which were
completed through the use of the STRING database, Cytoscape software, and the DAVID database.
Key targets and key components have been selected for molecular docking.

Results:

A total of 33 active components were identified in MD, and 134 common targets were obtained
and used to construct the networks. Of these, 10 core components and 10 core targets of MD
in the treatment of inflammation were identified. The GO and KEGG enrichment analyses revealed
that the common targets were involved in multiple signaling pathways, including the PI3K-Akt signaling
pathway, NOD-like receptor signaling pathway, chemokine signaling pathway, and IL-17
signaling pathway. The molecular docking methods confirmed the high affinity between bioactive
molecules of MD and their targets in inflammation. Two core targets (PIK3CA and AKT) and three
core components (asiatic acid, apigenin, and kaempferol) were found to be closely related to MD in
the treatment of inflammation. In vitro, MD exerted a significant effect on LPS-stimulated NO, IL-
1β, and TNF-α secretion, and iNOS, IL-1β, and TNF-α expressions in macrophages.

Conclusion:

This study has demonstrated the bioactive constituents and mechanisms of MD in inhibiting
the secretion of inflammatory factors and the multicomponent, multitarget, and multipathway
treatment characteristics involved in inflammation, but this still needs further in vivo/in
vitro experiments.
Biochar Amendment and its Impacts on Medicinal and Aromatic Plants in
Sustainable Agriculture
Authors: Shahrajabian Mohamad Hesam , Sun Wenli
Published: February 2024

Introduction:

Biochar application and research have experienced a significant increase in
recent decades. It can produce different kinds of organic materials, and it can be employed for different
purposes, such as soil conditioning, carbon sequestration and filtration of pollutants from gas and
aqueous media. Biochar is a C-rich material, which can be obtained from different types of organic
feedstock, such as animal manure, sewage sludge, wood and crop residues and other organic waste.
It is also considered an environmentally friendly and resource-saving approach in medicinal and
aromatic plants production. Biochar can lead to plant growth improvement and influence on chemical
components of medicinal plants, stimulate the growth of soil microflora, increase soil carbonsequestration,
bioremediation of soil, regulate carbon fluxes between atmosphere and biosphere,
reduce biotic stress in plants, improve soil nutrient availability, decrease abiotic stress in plants,
wastewater treatment, immobilization and sorption of soil heavy metal contaminants.

Methods:

Relevant literature has been obtained using the keywords “biochar”, “organic amendment”,
“soil quality”, “medicinal Plants”, “natural products”, “soil quality”, “macronutrient”, and
“chemical components” in scientific databases, such as “PubMed”, “SciFinder”, “Elsevier”, and
“Web of Science”.

Results:

The aim of this literature review is to study the impact of different kinds of biochars on
medicinal and aromatic plants, soil quality and soil fertility by considering case studies of successful
paradigms.

Conclusion:

Conclusively, we consider our review article will provide an appropriate guide for practitioners
and researchers for future studies as well as large-scale field applications.
To Study the Effect of Confining Walls on Permeable, Flexible Planktonic
Particle using Immersed Boundary Method
Authors: Panghal Rekha , Yadav Pooja , Ghosh Sudeshna
Published: February 2024

Objective:

The main goal of the current research was to investigate the influence of a wall-bounded medium on the settling behaviour of flexible planktonic
particles. The particles are permeable and immersed in a Newtonian, incompressible,
and viscous fluid.

Method:

This study employed the Immersed Boundary Method to analyze the interaction between the fluid and the flexible planktonic particles.

Results:

The research findings revealed a notable correlation between the terminal
(fall) velocity of the particles and distance amongst the confining walls, referred to as
the "wall gap." Specifically, as the wall gap increased, the terminal velocity of the
particle also increased. Additionally, the study demonstrated that the degree of distortion experienced by the flexible planktonic particles increased with the expansion of
the wall gap.

Conclusion:

In conclusion, the distance between the confining walls plays a significant role in determining the terminal velocity of the flexible planktonic particles during settling. This study highlights the importance of considering the wall gap as a
crucial factor when examining the behaviour of these particles in a wall-bounded medium.
Esperança queer na última poesia de Ana Luísa Amaral
Authors: Haysom-Rodriguez Peter
Published: February 2024

Following the death of the Portuguese writer Ana Luísa Amaral (1956-2022), this essay analyses the hopeful aspects of her final poetry collection, Mundo (2021). Using the poet’s own concept of queerente [queerful], alongside several comments made by international theorists regarding ‘queer optimism’, this text examines three particularly relevant poems from Mundo, concentrating on their (almost) positive messages. It highlights Ana Luísa Amaral’s ironic and non-definitive use of hope, aiming to celebrate her ethical and poetic project of diversity in terms of sexuality and identity.
Analisis Banjir akibat Keruntuhan Bendungan Kedung Bendo dengan Menggunakan HEC-RAS
Authors: Putra Damarendro Wihandaru , Juwono Pitojo Tri , Suprijanto Heri
Published: February 2024

Bendungan Kedung Bendo yang berlokasi di Desa Gunungsari, Kecamatan Kasreman, Kabupaten Ngawi, Jawa Timur, memiliki kapasitas 2,46 juta m3 (per 2016) yang bertujuan untuk memberikan suplai air irigasi di kabupaten tersebut.  Karena kapasitasnya yang besar, potensi bahaya yang dihadapinya juga fatal dan dapat menyebabkan kerugian material di wilayah permukiman sekitarnya. Oleh karena itu, penelitian ini ditujukan untuk analisa dan simulasi keruntuhan bendungan Kedung Bendo menggunakan program HEC-RAS dengan mengacu dalam dua kondisi. Simulasi pada waduk dalam kondisi normal yaitu piping dan kondisi ketika terjadi hujan dengan intensitas paling tinggi yang menyebabkan debit rancangan PMF (Probable Maximum Flood) dan menyebabkan overtopping. Simulasi keruntuhan karena debit PMF ini diakibatkan overtopping dan piping. Berdasarkan hasil simulasi menggunakan software HEC-RAS, ditemukan bahwa debit banjir rancangan PMF mencapai 291,296 m³/det dan luasan banjir mencapai 12,976 km², dengan kedalaman banjir maksimum mencapai 28,025 m. Akibat keruntuhan Bendungan Kedung Bendo, sebanyak 14 desa yang berada pada hilir bendungan terdampak dengan jumlah penduduk yang terkena risiko mencapai 6.570 jiwa. Dampak ini mengakibatkan konsekuensi serius bagi masyarakat dan lingkungan yang berada di wilayah terdampak.
Intelligence Collection Priorities in an Age of Renewed Superpower Conflict: Toward a More Expansive Perspective
Authors: Johnson Loch K.
Published: February 2024

The new global setting of the post-Cold War allowed the United States and its intelligence agencies to broaden the nation’s mandate to include the environment, health, the global economy, and terrorism, among other considerations---although the military might of Russia and China had by no means disappeared and considerable resources would remain focused on military threat assessments.  This article explores the commitment of the United States to the ongoing mission of knowing about and thwarting military attacks, while at the same time taking into account a new host of once ignored worldwide threats to national security.
INTERNATIONAL POLICE COOPERATION: REDUCING GLOBAL CRIME AND HARM
Authors: O'Brien Bruce
Published: February 2024

On November 14, 2023, Assistant Commissioner Bruce O’Brien, New Zealand Police, presented International Police Cooperation: Reducing Global Crime and Harm for this year’s West Coast Security Conference. The key points discussed were the advantages and challenges of collaborative international policing, upcoming challenges due to technological advancements, and the significance of advancing through consent, legitimacy, and evidence-based global policing practices.

 

Received: 12-19-2023

Revised: 01-26-2024
CANADIAN POLICE KNOWLEDGE NETWORK TRAINING THE POLICE AND SECURITY PROFESSIONALS IN THE PROFESSIONAL DEVELOPMENT FOR POLICING
Authors: Duffy Barrington
Published: February 2024

On November 14, 2023, Barrington Duffy, Business Development Representative for the Canadian Police Knowledge Network (CPKN), presented Training the Police and Security Professionals in the professional development for policing for this year’s West Coast Security Conference. The key points discussed were the role of CPKN in training policies and professional development in policing, the issues and key focuses of the policing sector in Canada, and the need for ongoing investment in technology, collaboration, and education in overcoming challenges in the policing sector.

 

Received: 01-17-2024

Revised: 01-29-2024
2023 WEST COAST SECURITY CONFERENCE: OPENING REMARKS DAY 2
Authors: Gilmour John
Published: February 2024

On November 14, 2023, Dr. John Gilmour delivered the opening remarks for the second day of this year’s West Coast Security Conference. The key points discussed were the structure of the day, the value and mission of CASIS, and contemporary challenges and opportunities faced by law enforcement communities.

 

Received: 01-10-2024

Revised: 01-26-2024
MARITIME SECURITY LESSONS LEARNED FROM INTERNATIONAL SECURITY INITIATIVES IN THE CARIBBEAN
Authors: Kelshall Jason
Published: February 2024

On November 15th, 2023, Jason Kelshall, Regional Coordinator, SEACOP EU, presented Maritime Security Lessons Learned from International Security Initiatives in the Caribbean for this year’s West Coast Security Conference. The key points discussed were increasing illicit trade and its effects, rising crime and drug availability, and challenges in maritime and energy resource security.

 

Received: 01-15-2024

Revised: 01-26-2024
THE RUSSO-UKRAINIAN WAR: WHAT DOES IT MEAN FOR RUSSIA, UKRAINE, AND THE WEST?
Authors: Muradov Ibrahim
Published: February 2024

On November 16, 2023, Dr. Ibrahim Muradov presented The Russo-Ukrainian War: What Does it Mean for Russia, Ukraine, and the West? at this year’s West Coast Security Conference. The presentation was followed by a question-and-answer period with questions from the audience and CASIS Vancouver executives. The key points discussed were that Ukrainian society's push for a pro-Western policy has shaped its foreign relations, despite international reluctance to integrate Ukraine into Western structures; Ukraine's strong protest culture, especially in western regions, has significantly influenced its political direction and resistance to Russian dominance; and Ukraine developed a long-term strategy for economic, military and identity strengthening  and this long-term strategy precipitated the full-scale invasion and forced the Kremlin to act before the strategy was complete.

 

Received: 01-07-2024

Revised: 01-26-2024
Acceptance Factors and Barriers to the Implementation of a Digital Intervention With Older Adults With Dementia or Caregivers: Protocol for an Umbrella Review (Preprint)
Authors: Madeira Ricardo , Esteves Dulce , Pinto Nuno , Vercelli Alessandro , Vaz Patto Maria
Published: February 2024

BACKGROUND

The increase in average life expectancy, aging, and the rise in the number of people living with dementia contribute to growing interest from the scientific community. As the disease progresses, people with dementia may need help with most daily activities and need to be supervised by their carer to ensure their safety. With the help of technology, health care provides new means of self-managing health that support active aging, allowing older people and people with dementia to live independently in their homes for a longer period of time. Although some systematic reviews have revealed some of the impacts of using digital interventions in this area, a broad systematic review that examines the overall results of the effect of this intervention type is mandatory.

OBJECTIVE

The aim of this review is to further investigate and understand the acceptability and barriers to using technology to monitor and manage health conditions of people living with dementia and their caregivers.

METHODS

A review of systematic reviews on acceptability factors and barriers for people with dementia and caregivers was carried out. Interventions that assessed acceptability factors and barriers to the use of technology by people with dementia or their carers were included. Each potentially relevant systematic review was assessed in full text by a member of a team of external experts.

RESULTS

The analysis of the results will be presented in the form of a detailed table of the characteristics of the reviews included. It will also describe the technologies used and factors of acceptability and barriers to their use. The search and preliminary analysis were carried out between May 5, 2023, and August 1, 2024.

CONCLUSIONS

This review will play an important role as a comprehensive, evidence-based summary of the barriers and facilitators to the use of digital interventions. This review may help to establish effective policy and clinical guideline recommendations.
Development of Magnetic-Silica Particles and In-house Buffers Kit for SARS-CoV-2 and CDV RNA Extraction
Authors: Prasetya Ahadi Damar , Muflikhah Muflikhah , Lubis Wildan Zakiah , Insani Andon , Sulungbudi Grace Tjungirai , Mujamilah Mujamilah , Saepulloh Uus
Published: February 2024

Since the end of 2019, COVID-19 pandemic caused by the novel SARS-CoV-2 has become a serious problem for the world. Accurate and rapid techniques in testing and tracing are needed to control the virus spreading. Molecular diagnostics through gene amplification techniques, especially PCR, still become the gold standard for SARS-CoV-2 detection, which requires the first step of RNA extraction and purification. The limitations of commercial RNA extraction-purification kits during the pandemic caused a big problem in testing and tracing, especially for developing countries. A simple RNA extraction-purification kit based on magnetic-silica (MAGSi) beads and non-guanidine in-house buffers for RNA virus extraction-purification has been developed. Two types of MAGSi beads with different magnetic nanoparticles (MNPs) content were synthesized through a modified Stöber’s method using the sonication technique. The PCR result shows that both the MAGSi beads and the buffer can be used as a kit for RNA extraction-purification, tested for SARS-CoV-2 and Canine Distemper Virus. Further study shows that MAGSi-1 has better RNA extraction ability, and a higher concentration of RNA has been extracted. This is likely because of the smaller particle size distribution (50–1,500 nm distribution) and higher magnetization (20.2 emu/g) of MAGSi-1 compared to MAGSi-2 with 100–1,700 nm size distribution and 14.2 emu/g magnetization.
Characteristic and Performance of Ni, Pt, and Pd Monometal and Ni-Pd Bimetal onto KOH Activated Carbon for Hydrotreatment of Castor Oil
Authors: Trisunaryanti Wega , Triyono Triyono , Falah Iip Izul , Wicaksono Dwi Bagus , Sumbogo Satriyo Dibyo
Published: February 2024

The preparation of highly efficient hydrotreating catalysts has presented a significant challenge in the field of catalysis. In this study, chemically activated carbon (AC) was prepared using potassium hydroxide (KOH) as an activator and Merbau wood as a lignocellulosic source for the AC. The AC was then impregnated with mono-metallic species (nickel, platinum, and palladium) as well as a bimetallic NiPd combination. The results revealed that the optimal KOH impregnation weight ratio was determined to be 2:1, resulting in a remarkably high iodine value of 751.94 mg/g. Subsequently, AC was employed as a support material for the hydrotreating of castor oil. Among the catalysts tested, the NiPd/AC catalyst demonstrated superior performance, yielding a liquid fraction comprising 88.80 wt.%. Within this fraction, C5-C12 hydrocarbons accounted for 15.16 wt.%, alcohol compounds constituted 71.69 wt.%, while the remaining 0.87 wt.% consisted of other components. Furthermore, the NiPd/AC catalyst exhibited remarkable stability, as its performance remained largely unchanged even after being used three times consecutively. This finding suggests that coking had minimal impact on the active sites of the mentioned catalyst, indicating its robustness and potential for prolonged application.
Migración y movilidad: mercados de trabajo, redes de difusión y estrategias en Acacoyagua, Chiapas (2000-2022)
Authors: Ramírez Ramos Yoame
Published: February 2024

En este artículo se describen los fenómenos de migración y movilidad laboral en dos localidades rurales del municipio de Acacoyagua, región Soconusco, Chiapas. En el siglo XXI, los habitantes se incorporan a mercados de trabajo internacionales (como Estados Unidos) y nacionales (principalmente en el norte de México), lo que da origen a estrategias múltiples de sobrevivencia. Esto conduce al surgimiento de redes de difusión que orientan a que quienes migran se dediquen principalmente a trabajar como jornaleros en las áreas agroindustriales y como obreros en las maquiladoras de las regiones indicadas. Los resultados derivan de la aplicación de una encuesta en 120 hogares, de entrevistas y de etnografía multilocal.