bluuebunny/crossref_metadata_2025 huggingface dataset:
The effect of port integration policy on port green efficiency: Evidence from Zhejiang (China)
Authors: Liao Qingmei , Zhen Hong , Han Tong
Published: July 2024

Zhejiang (China) has several large ports and is an early province in implementing port integration policy. This study evaluates the green efficiency of major ports in Zhejiang (China) for 2019–2022 using the Super-slack-based measure (Super-SBM) model with CO2 emissions. This study provides theoretical and empirical analyses of the effect of integration policy on port green efficiency. The results show that Ningbo and Zhoushan ports have high green efficiency. However, the green efficiency of Taizhou, Jiaxing Inland and Wenzhou Ports needs to be improved urgently because of the massive investment in coastline and berths and high carbon emissions. The port green efficiency can be improved by implementing an integration policy between ports geographically close, such as Ningbo, Zhoushan and Jiaxing ports. Higher port city levels and fixed asset investment positively impact port green efficiency. The findings provide a reference for policymakers to improve the green efficiency of ports.
Electrodeposited polyaniline-carbon felt anode promotes electroactive biofilm for the improved energy recovery in microbial fuel cells using phenol containing wastewater
Authors: Bhandari Subhendu , Pandit Soumya , Pandit Chetan , Ranjan Nishant
Published: July 2024

In the present study, Polyaniline (PANI)/ Carbon Felt (CF) composite electrodes were developed to be used as an anode in a Microbial Fuel Cell (MFC) for the enrichment of specific electroactive organisms on the anode. Comparative analysis of two approaches of Phenol degradation namely adsorption & biodegradation and for simultaneous generation of bio-electricity. Sulfuric acid-doped PANI was electrochemically synthesized in aqueous medium and deposited in-situ on the carbon felt anode followed by its characterization using SEM, XRD, and CV. To use these in MFC, different concentrations of PANI ranging from 0.25 mg/cm2 to 1.25 mg/cm2, was deposited onto CF via potentiostatic electrodeposition technique and compared. The morphological analysis using FESEM of the anode revealed homogenous deposition of nanostructured PANI onto the surface of CF. Further characterization of PANI/CF composite shows that PANI has improved the surface area of the anode, thereby, increasing the conductivity of the anode and promoting biofilm attachment to the anode. The PANI/ CF composite anode with loading rate of 1.0 mg/cm2 showed the best results with maximum power density of 584.2 mW m-2 and lowest charge transfer resistance of 49.6 Ω. The reduction of COD and total phenol of wastewater were 73% and 88% respectively. The obtained results from this study show that the power production and efficiency of the MFCs can be improved greatly by using Sulphate containing PANI/ CF composite as an anode material. The CLSM results indicated that PANI facilitates in promoting EAB biofilm which in turn helps in achieving enhanced power output.
Electret Integrated Magnetic Field Sensor Based on Magnetostrictive Polymer Composite with nT Resolution
Authors: Zimoch Lukas , Schröder Stefan , Elzenheimer Eric , Kaps Sören , Strunskus Thomas , Faupel Franz , Höft Michael , Adelung Rainer
Published: July 2024

The pursuit for advanced magnetoelectric field sensors has gained momentum, driven by applications in various fields, ranging from biomedical applications to soft robotics and the automotive sector. In this context, a capacitive read-out based magnetostrictive polymer composite (MPC) sensor element is introduced, offering a new perspective on magnetic field detection. The sensor element's unique feature is the possibility to independently tailor its mechanical and magnetic properties. When compared to other composite-based magnetic field sensors, the limit of detection (LoD) is three orders of magnitude lower (95.6 nT/√Hz at a resonance frequency of 160.5 Hz). In contrast to other electret-based ME sensors, the LoD is reduced by a factor of 20. To the best of the authors' knowledge, this work marks the first comprehensive attempt to characterize a sensor magnetically, aligning with the thorough assessment standards of ME sensors. This study aims to narrow the disparity between established magnetic field sensors, featuring consistent characterization protocols, and the novel MPC sensors, which often undergo limited magnetic characterization as part of their evaluation. The presented sensor, built from readily available materials, offers a versatile and tuneable platform for magnetic field detection, and ongoing research aims to unlock its full potential in diverse applications.
Nonlinear Modeling And Analysis Of A Metatronic Amplifier Using Harmonic Balance-Finite Difference Frequency Domain Method
Authors: Fadafan Ali Allahpour , Abdipour Abdolali , Askarpour Amir Nader
Published: July 2024

This study introduces a novel numerical method for analyzing the nonlinear behavior of intricate electromagnetic structures, with a specific focus on a metatronic amplifier as a case study. We propose a modified approach that integrates Harmonic Balance (HB) and Finite Difference Frequency Domain (FDFD) methods, tailored for structures featuring anisotropic materials. The combined application of HB-FDFD enables a comprehensive investigation of spatial electromagnetic field distributions and harmonic responses within such structures. Moreover, this method effectively addresses the challenges associated with complex architectures. Additionally, we emphasize the incorporation of effective boundary conditions, as discussed in the paper, to enhance the accuracy of our analysis. Through a comparison with conventional methods, we demonstrate the efficacy of our approach and underscore its broad applicability to various nonlinear electromagnetic devices.
Recognition of Miner Action and Violation Behavior Based on the ANODE-GCN Model
Authors: Yang Chaoyu , Hou Linpeng , Aktar Mst.Mahbuba
Published: July 2024

In response to the challenge of limited accuracy in skeleton-based action recognition algorithms due to missing key points in complex environments under coal mines, enhancements were made to the Info-GCN++ model architecture. We proposed a miner action recognition model named ANODE-GCN, which integrated neural ordinary differential equations (NODE) with graph convolutional networks (GCN). The model predicted future motion sequences by analytically solving NODE in a dimensionally upgraded ODE space and combined these predictions with the actual observed motion states, thereby enhancing the recognition robustness of the model in handling partially missing skeleton sequences. Additionally, we designed a graph convolutional network SC-GC that integrated self-attention and coordinate attention mechanisms to differentiate between similar motion sequences in distinct actions. Ultimately, the miners' basic actions identified were correlated with environmental information to recognize more complex violation behaviors accurately. Experimental results demonstrated that on the public dataset NTU RGB+D120, with skeleton sequences completeness of 40% and 60%, accuracies of 71.96%/78.93% and 77.43%/81.29% were achieved, respectively, based on X-Sub/X-Set evaluation protocols. Ablation experiments based on the X-Sub evaluation protocol indicated that ANODE-GCN had an AUC of 67.13%, 10.75% higher than the Info-GCN++ baseline. On a self-built dataset, ANODE-GCN achieved an action recognition accuracy of up to 89.12% on the low-quality skeleton action test set. When the action information was matched with the environmental information, the average accuracy of miners' violation behavior recognition reached 91.7%, which was 6.7% higher than Info-GCN++.
Effect of Selenium Application on Quality, Phytochemical Composition and Mineral Content Properties of Red Currant (Ribes rubrum L.) and Jostaberry (Ribes ×nidigrolaria Bauer)
Authors: Erdem Sinem Öztürk
Published: July 2024

Selenium is an essential mineral for both humans and animals. Around 0.5–1 billion individuals globally suffer from selenium deficiency, which can result in a range of illnesses. Hence, the cultivation of selenium-enriched agricultural items can serve as a potent strategy to mitigate selenium deficiency. This study aimed to examine the effect of selenium on the quality, and phytochemical and mineral content of red currant (Red Lake) and jostaberry. The study was conducted in 2022 and 2023. Different doses of selenium (0, 4, and 8 mg⋅kg−1) were sprayed on the fruits three times with 10-days intervals starting from the first formation of the fruits after flowering. Upon completion of the study, various factors were assessed including cluster and berry properties, water-soluble dry matter content, pH levels, titratable acid content, ascorbic acid levels, antioxidant activity, and total phenolics content. The mineral composition of the fruit peel, pulp, and seed was also measured. In jostaberry, the highest values of cluster weight, cluster height, and 100-berry weight were obtained with 8 mg⋅kg−1 selenium application. As the selenium dosage increased, the levels of ascorbic acid, antioxidant activity, and total phenolic content increased, with the highest values determined to be 0.063 mg⋅mL−1, 63.23% DPPH, and 3752.22 mg⋅g−1, respectively, at 8 mg⋅kg−1. In the Red Lake variety, it has been determined that the 4 mg⋅kg−1 dose is effective in terms of cluster weight, cluster width, and cluster height attributes. The highest values for ascorbic acid, antioxidant activity, and total phenolic content were determined to be 0.029 mg⋅mL−1, 53.42% DPPH, and 3117.17 mg⋅g−1, respectively, at the 4 mg⋅kg−1 dose. The selenium content was found to be highest in the peel and pulp of jostaberry at 8 mg⋅kg−1, and in Red Lake, it was obtained at the 4 mg⋅kg−1 application. As a result, an 8 mg⋅kg−1 dose of selenium could be recommended for jostaberry, and a 4 mg⋅kg−1 dose could be recommended for Red Lake.
Glimpses of the Use of Generative AI and ChatGPT in Medical Education
Authors: Mitra Nilesh Kumar ,   Human Biology Division, School of Medicine, IMU University, Kuala Lumpur, MALAYSIA, Chitra Ebenezer ,   School of Health Sciences, IMU University, Kuala Lumpur, MALAYSIA
Published: July 2024

Artificial intelligence (AI) refers to computer systems that can perform tasks that typically require human intelligence. This is achieved by using algorithms and neural networks for machine learning (ML) and deep learning. ChatGPT is an AI-powered chatbot that can generate responses on any topic based on the user’s input or queries. In this review, the focus is on the potential applications of generative AI and ChatGPT in the fields of medical and health professions education. It is important to educate both educators and students about the impact of using generative AI, such as ChatGPT, which is widely used through generative adversarial networks (GANs). In the field of healthcare, GANs can analyse vast datasets to assist in diagnosis, patient data management, and analysis. Students use ChatGPT to obtain factual answers, write papers and translate languages. It can help students with their assignments by summarising literature reviews and generating new ideas. In medical education, educators use ChatGPT to develop learning activities, assessments, and curricula, enhance student learning, and even generate research papers for publication. However, students need to use generative AI carefully so that it does not impede their ability to think critically or write effectively. Guidelines are being formulated in different institutions to regulate the use of this immensely powerful tool. This review could highlight the scope of incorporating ChatGPT into the field of medical education.
Integration of LBDD and SBDD Studies on Drug Design: A Fatty Acid Amide Hydrolase (FAAH) Case Study
Authors: Santana Pedro , Ruas Marina , Veríssimo Gabriel , Terra Ana , de Oliveira Renata , Maltarollo Vinícius
Published: July 2024

The inhibition of the fatty acid amide hydrolase (FAAH), an endocannabinoid system component, emerged as a potentially new therapeutic target for a range of clinical disorders such as acute and chronic pain. Some α-ketoheterocycle derivatives demonstrated interesting analgesic and antiinflammatory activities in vitro. Ligand-Based Drug Design techniques such as knowledge graph convolutional networks (kGCN) and hologram quantitative structure-activity relationship (HQSAR) using α-ketoheterocycle derivatives from five different datasets were generated to discover the relation between the chemical structures and the inhibition activity. Meanwhile, structure-based drug design simulations as interaction fields (MIF), molecular docking, and ligand sites studies (LSI) from FAAH were performed using Autogrid software and FTmap/FTsite servers. The results of both studies were merged to propose predictive models. The resulting kGCN model demonstrated adequate accuracy area under the curve by receiver operating characteristic (AUC-ROC 0.7922). From contribution maps of the Ligand-Based Drug Design (LBDD) models and the generated probes using MIF and LSI, it was observed that the oxazole ring, the ketone group, and the apolar chain present in the structures of the inhibitors are important, besides the evidence of the Cys269 and Val270 residues importance for the potential interaction, confirmed by carried docking studies. These fragments and structural information can be used to carry out new FAAH potential inhibitors studies and report kGCN as an accurate classification technique.
Integrated multi-objective chance-constrained fuzzy interval linear programming model with principal component analysis for optimizing agricultural water resource management under uncertainties
Authors: Yin Ruoyu , Jin Lei , Fu Haiyan , Fan Yurui , Zhang Xi , Wang Li
Published: July 2024

This study addresses the pivotal challenge of water resource allocation in urban environments by introducing a novel approach – a multi-objective chance-constrained fuzzy interval linear programming model integrated with principal component analysis (PCA). This innovative model aims to alleviate subjectivity in urban water management processes, particularly in adjusting water demands across various sectors. The proposed model incorporates correlation analysis to identify dimensionality-reducing factors of multitarget components, determining the proportion of each target component relative to the total components. Fuzzy sets are applied to irrigation water resource allocation quantity, segmented into six levels of fuzzy membership to analyze the stochasticity of water supply. Results demonstrate the model's efficacy, revealing that variations in risk probabilities impact water supply, necessitating positive water management strategies to enhance agricultural efficiency and negative strategies to mitigate the risk of inadequate water supply. Key findings emphasize the significance of agricultural water availability and the structure of irrigation water use in optimal resource allocation. Importantly, the study showcases the enhanced precision achieved through the proposed multi-objective chance-constrained fuzzy interval linear programming with PCA, thereby refining the optimization outcomes for water management under multifaceted objectives.
Research on urban water demand prediction based on machine learning and feature engineering
Authors: Yan Dongfei , Tao Yi , Zhang Jianqi , Yang Huijia
Published: July 2024

Urban water demand prediction is not only the foundation of water resource planning and management, but also an important component of water supply system optimization and scheduling. Therefore, predicting future water demand is of great significance. For univariate time series data, the issue of outliers can be solved through data preprocessing. Then, the data input dimension is increased through feature engineering, and finally, the LightGBM (Light Gradient Boosting Machine) model is used to predict future water demand. The results demonstrate that cubic polynomial interpolation outperforms the Prophet model and the linear method in the context of missing value interpolation tasks. In terms of predicting water demand, the LightGBM model demonstrates excellent forecasting performance and can effectively predict future water demand trends. The evaluation indicators MAPE (mean absolute percentage error) and NSE (Nash–Sutcliffe efficiency coefficient) on the test dataset are 4.28% and 0.94, respectively. These indicators can provide a scientific basis for short-term prediction of water supply enterprises.
capitalismo está engolindo a democracia
Authors: Santos Jefferson Dantas
Published: July 2024

Resenha de FRASER, Nancy. Cannibal Capitalism: How our system is devouring democracy, care, and the planet and what we can do about it. London: Verso, 2022.
Submissão: 11 mar. 2024 ⊶ Aceite: 3 jun. 2024
“Precisa anotar tudo nesse caderninho?"
Authors: Fragoso Mariana Pitasse
Published: July 2024

Este artigo tem como objetivo comparar formas de escrita próprias do Jornalismo e da Antropologia a fim de discutir distâncias e aproximações entre as duas construções textuais. Busco, com isso, pensar sobre o desenvolvimento de uma etnografia e de uma notícia ao detalhar processos de escolha, de montagem e de edição que apontam como se apresentam questões metodológicas na rotina das duas práticas. As reflexões partem de minha experiência como jornalista e como antropóloga. Assim, o material empírico é um desdobramento de minha tese de doutorado - fruto da observação participante e das reflexões do meu caderno de campo - e também da sequente pesquisa desenvolvida em meu pós-doutorado.
Submissão: 26 fev. 2024 ⊶ Aceite: 18 mai. 2024
The Gut Microbiota-Brain Axis: A New Frontier in Alzheimer's Disease Pathology
Authors: Dhanawat Meenakshi , Malik Garima , Wilson Kashish , Gupta Sumeet , Gupta Nidhi , Sardana Satish
Published: July 2024

Dr. Aloysius Alzheimer, a German neuropathologist and psychiatrist, recognized the
primary instance of Alzheimer's disease (AD) for a millennium, and this ailment, along with its related
dementias, remains a severe overall community issue related to health. Nearly fifty million individuals
worldwide suffer from dementia, with Alzheimer's illness contributing to between 60 and
70% of the instances, estimated through the World Health Organization. In addition, 82 million individuals
are anticipated to be affected by the global dementia epidemic by 2030 and 152 million by
2050. Furthermore, age, environmental circumstances, and inherited variables all increase the likelihood
of acquiring neurodegenerative illnesses. Most recent pharmacological treatments are found in
original hypotheses of disease, which include cholinergic (drugs that show affective cholinergic system
availability) as well as amyloid-accumulation (a single drug is an antagonist receptor of Nmethyl
D-aspartate). In 2020, the FDA provided approval on anti-amyloid drugs. According to
mounting scientific data, this gut microbiota affects healthy physiological homeostasis and has a
role in the etiology of conditions that range between obesity and neurodegenerative disorders like
Alzheimer's. The microbiota-gut-brain axis might facilitate interconnection among gut microbes as
well as the central nervous system (CNS). Interaction among the microbiota-gut system as well as
the brain occurs through the “two-way” microbiota-gut-brain axis. Along this axis, the stomach as
well as the brain develop physiologically and take on their final forms. This contact is constant and
is mediated by numerous microbiota-derived products. The gut microbiota, for instance, can act as
non-genetic markers to set a threshold for maintaining homeostasis or getting ill. The scientific
community has conducted research and found that bowel dysbiosis and gastrointestinal tract dysregulation
frequently occur in Alzheimer's disease (AD) patients. In this review, the effects of the microbiota-
gut-brain axis on AD pathogenesis will be discussed.
Unveiling Anthraquinones: Diverse Health Benefits of an Essential Secondary Metabolite
Authors: Khatoon Mushfa , Dubey Amita , Janhvi Km
Published: July 2024

Since ancient times, plants have been used as a remedy for numerous diseases.
The pharmacological properties of plants are due to the presence of secondary metabolites
like terpenoids, flavonoids, alkaloids, etc. Anthraquinones represent a group of naturally
occurring quinones found generously across various plant species. Anthraquinones
attract a significant amount of attention due to their reported efficacy in treating a wide
range of diseases. Their complex chemical structures, combined with inherent medicinal
properties, underscore their potential as agents for therapy. They demonstrate several
therapeutic properties such as laxative, antitumor, antimalarial, antibacterial, antifungal,
antioxidant, etc. Anthraquinones are found in different forms (derivatives) in plants, and
they exhibit various medicinal properties due to their structure and chemical nature. The
precursors for the biosynthesis of anthraquinones in higher plants are provided by different
pathways such as plastidic hemiterpenoid 2-C-methyl-D-erthriol4-phosphate (MEP),
mevalonate (MVA), isochorismate synthase and polyketide. Anthraquinones possess several
medicinal properties and a complex biosynthetic pathway, making them good candidates
for patenting new products, synthesis methods, and biotechnological production
advancements. By conducting a thorough analysis of scientific literature, this review provides
insights into the intricate interplay between anthraquinone biosynthesis and its
broad-ranging contributions to human health.
A Preparative-HPLC Method Development and Validation for the Estimation and Identification of Laccaic Acid-A, Laccaic Acid-B, and Laccaic Acid-D
Authors: Ghosh Manik , Dey Suddhasattya , Mondal Arijit , Ranjan Lal Uma , Choudhury Avijit , Kumar Mandal Sudip , Sharma Sanjana
Published: July 2024

Objective:

Lac is derived from Laccifer lacca Kerr and has historically been used as a dye due to its coloring qualities. It is now widely utilised in the food and colouring indus-tries. Lac dye was isolated for the first time with the help of preparative HPLC. Further char-acterization was also performed using NMR and MS spectroscopy techniques.

Methods:

The column used for the isolation was the Inertsil ODS-3 reverse-phase C18 column. The wavelength of the PDA detector was set between 275 nm and 410 nm. Data acquisition was carried out for Empower 2.0 (Waters Ltd., United States). For the mobile phase, Methanol: acetonitrile (85:15) is the ideal solvent system A, while 0.15% perchloric acid in water is the ideal solvent system B. Ultimately, a 0.22 μm membrane filter was used to filter the mobile phase. We conducted an effective gradient run after the runtime of 33 minutes, setting the flow rate at 15 mL/min. We set up the fraction collector to operate on a time basis, with a maximum collection volume of 5 ml per vial and a period of 0.41 min for each vial.

Results:

After the chromatographic run, three single elution peaks were observed with reten-tion times (Rt) of 15.19, 25.09, and 30.54 min, respectively. The compounds associated with Rt 15.19 were effectively collected in vials nos. 13, 22, 31, and 40, respectively, in the fraction collector. The compound with a retention time of 25.09 was collected in vials no. 24, 33, 42, and 51, respectively, whereas the compound with a retention time of 30.54 was collected in vials no. 52, 61, 70, and 79, respectively, in the fraction collector.

Conclusion:

A sufficient amount of the samples was collected, and the Rota evaporator (Bu-chi, Germany) was used to evaporate the solvents. After lyophilization, the dried product was stored at 4oC for further analysis. The compound having an Rt of 15.19 min revealed that it is laccaic acid A. The compound having an Rt of 25.09 indicated that it is laccaic acid B. Finally, the compound having an an Rt of 30.54 min indicated that the compound is laccaic acid D.

result:

After the chromatographic run, three single elution peaks were observed having retention time (Rt) 15.19, 25.09 and 30.54 min, respectively. The compounds associated with Rt 15.19 was effectively collected in vial no 13, 22, 31 and 40 respectively in the fraction collector. The compound having retention time 25.09 was collected in the vial no 24, 33, 42 and 51 respectively, whereas compound having Rt 30.54 was collected in vial no 52, 61, 70 and 79 respectively in the fraction collector.
Exploring the Potential of Carotenoids in Obesity Management: A Comprehensive Overview
Authors: Rastogi Vanshika , Soni Shashank
Published: July 2024

Obesity is a global health concern with numerous comorbidities, including cardiovascular diseases, type 2 diabetes, and certain cancers. Carotenoids, found in a variety of natural sources like fruits and vegetables, are known for their potential health benefits. Emerging research suggests that certain carotenoids may play a major role in combating obesity through mechanisms involving inflammation, oxidative stress, and lipid metabolism. Understanding the influence of carotenoids on metabolic health could offer valuable revelation about obesity management strategies.
To summarize the main findings on carotenoids that help in the management and prevention of obesity, exploring their potential benefits in weight management, metabolic health, and overall well-being.
An extensive literature survey was done on the management of obesity using PubMed, Elsevier, ScienceDirect, and Springer. The results were then filtered based on the titles, abstracts, and accessibility of the complete texts. The search engine Google Scholar was accessed for the literature data mining.
This review highlights the diverse functions of carotenoids, such as their antioxidant properties, anti-inflammatory effects, and regulation of lipid metabolism, which contribute to their potential role in combating obesity. Studies suggest that carotenoids may help reduce adiposity, lipid accumulation, improve insulin sensitivity, and promote overall metabolic health, making them promising candidates for obesity management.
Obesity is synonymous with the appearance of major diseases and an overall decline in physical and mental performance. Overall, the findings of this review endorse the possible application of carotenoids as a nutritional supplement for the management and prevention of obesity. Further research is needed to clarify the mechanisms underlying the beneficial impacts of carotenoids on obesity-related consequences and to optimize their utilization in clinical practice and public health campaigns.
A CNN-based Machine Learning Model for the Identification of Herbal Drugs: A Case Study on Cumin
Authors: Naman Subh , Sharma Sanyam , Baldi Ashish
Published: July 2024

Background:

This research paper showcases the creation and assessment of a machine
learning model utilizing the Efficient Net B4 architecture for the identification of cumin herbs
and any potential adulterants. The research presents a comprehensive overview of the model's
structure, emphasizing the different layers, their output dimensions, and the number of parameters.

Methods:

The trained model consists of a grand total of 17,684,581 parameters, out of which
10,758 have been found eligible for training. The model has been found to exhibit exceptional
performance on the training dataset, with an accuracy of 98.73%, a recall score of 0.95, and an
F1 score of 0.93. This demonstrates its usefulness in accurately identifying cumin herbs. A confusion
matrix has also been developed, which has showcased the model's remarkable proficiency
in accurately detecting cumin herbs. Although there have been few occurrences of misclassification,
the model has consistently shown exceptional accuracy by accurately identifying the majority
of cases in both the "cumin" and "not cumin" categories.

Results:

Upon comparing our model's performance to prior research, it has been found notable
for its high accuracy and the potential to be applied more broadly in the field of herbal identification.
This work offers an innovative way for recognizing cumin plants using machine learning,
despite the little research existing in this area. It also establishes a basis for future research on
identifying other important herbal items.

Conclusion:

In conclusion, the machine learning model based on EfficientNet B4 has been found
to exhibit exceptional accuracy and show potential for practical use in identifying cumin herbs.
This study can significantly contribute to improving the authentication and quality assurance processes
in the herbal product business, paving the way for future advancements in this field.
Arthropods Diversity on Soybean Fields with Integrated Pest Management and Conventional Systems in Gandusari District, Blitar Regency
Authors: Mahendra Niko , Rahardjo Bambang Tri , Widjayanti Tita
Published: July 2024

Various negative impacts of pesticides must be avoided by applying management principles that have as little negative impact on the environment as possible using an integrated pest management (IPM) approach. This study aimed to examine the diversity of arthropods and the feasibility of farming in IPM and conventional fields on soybeans. Arthropod sampling was carried out in September–December 2021 using a yellow pan trap, yellow sticky trap, and visual methods. The arthropod population found was analyzed using the T-test, and the level of arthropod diversity was calculated based on the diversity index (H'), species richness index (R), evenness index (E), and dominance index (C). The feasibility of farming on both fields was calculated using the R/C ratio and BEP prices. The results showed that the number of arthropods in IPM and conventional fields was significantly different. In both fields, the diversity index value was in the medium category, the species richness index value and the evenness index value were in the high category, and there was no dominance in both fields. Even though it belonged to the same category, the index value of arthropod diversity in the IPM field was higher than in the conventional field. In IPM and conventional fields, the R/C ratio values were 1.01 and 1.06, respectively, while the BEP value in IPM and conventional fields was IDR 10,601.44 and IDR 10,075.14.
LEPTIN AND VISFATIN AS PREDICTORS OF GESTATIONAL HYPERTENSIVE COMPLICATIONS IN OVERWEIGHT WOMEN
Authors: Henyk Natalia , Bihun Ruslana , Maksymenko Lesya , Ostafiichuk Svitlana , Perhulyn Oksana , Neiko Olha , Levitskyi Ihor , Kinash Natalia
Published: July 2024

Background. Over the past decades, fatty tissue has ceased to be just an energy depot, but as a source of hormone-like peptides - adipokines, such as leptin and visfatin. There is a direct correlation between body weight and the risk of developing gestational complications. Aim of this study was to determine prognostic value of leptin and visfatin in predicting gestational hypertensive complications in overweight women.
Materials and methods. We examined 117 women divided into two groups: the main group included 68 overweight women, the control group included 49 women with normal body weight. Serum leptin and visfatin was established before pregnancy, in the first and third trimester.
Results. In overweight women, gestational hypertension was observed in 20 women (29.4%) and preeclampsia in 25 women (36.8%). The concentration of leptin in the third trimester during gestational hypertension increased by 21.9%, by 20.2% in preeclampsia compared before pregnancy (p<0.05) and exceeded the value in uncomplicated pregnancy by 1.3 times (p<0.05). In main group during third trimester in case of gestational hypertensive complications, the concentration of visfatin was higher than in women without complications (p<0.05). In the groups of women with hypertensive conditions, we observed significantly higher concentrations of visfatin compared with the woman without complications. In main group in case of gestational hypertensive complications, the concentration of visfatin was higher than in women without complications on the third trimester.
Conclusions. In overweight patients who developed hypertensive complications, leptin found to be 3.0 times higher before pregnancy and 2.0 times higher in the first trimester. Visfatin were found to be 1.2 times higher at both stages compared with control group. Leptin and visfatin may serve as qualitative predictors of hypertensive complications before pregnancy and during early gestation in overweight women.
ВЗАЄМОЗВ’ЯЗОК МІЖ КАРДІАЛЬНОЮ АВТОНОМНОЮ НЕЙРОПАТІЄЮ ТА ЕКСПРЕСІЄЮ ГЕНА МОЗКОВОГО НЕЙРОТРОФІЧНОГО ФАКТОРУ (BDNF) У ПАЦІЄНТІВ З ВПЕРШЕ ВИЯВЛЕНИМ ЦУКРОВИМ ДІАБЕТОМ 2 ТИПУ
Authors: Степура Олена , Древицька Тетяна , Тодуров Іван , Жердьова Надія
Published: July 2024

Кардіальна автономна нейропатія (КАН) – фактор ризику серцево-судинної захворюваності і смертності у хворих на цукровий діабет (ЦД) та предіабет. Нейротрофічний мозковий фактор (BDNF) регулює нейрогенез.
Метою нашого дослідження було визначення частоти виявлення кардіальної автономної нейропатії та взаємозв’язку між наявністю даного ускладнення і рівнем експресії гену BDNF у пацієнтів з вперше виявленим цукровим діабетом 2 типу.
Матеріали та методи. У дослідженні брали участь 52 хворих з вперше виявленим ЦД 2 типу (36 жінок і 16 чоловіків). Середній вік хворих становив 60,9±1,55 років, індекс маси тіла – 32,98±0,73 кг/м2, рівень систолічного артеріального тиску – 148,27±3,3 мм рт. ст., діастолічного артеріального тиску – 90,08±2,14 мм рт. ст., рівень глюкози натще – 8,72±0,36 ммоль/л, HbA1c – 7,77±0,18%, розрахункова швидкість клубочкової фільтрації (рШКФ) – 78,98±2,19 мл/хв/1,73 м2 (дані представлені як середнє значення ± похибка середнього). Всім пацієнтам було проведено п’ять кардіовагальних тестів по D. Ewing з оцінкою варіативності серцевого ритму, дослідження діабетичної периферичної нейропатії (ДПН) за шкалою Торонто, а також визначення рівня експресії BDNF за допомогою полімеразної ланцюгової реакції у реальному часі. Діагноз КАН встановлювали при 2 і більше патологічних пробах. Статистичний аналіз даних проводили за допомогою програми SPSS, версія 25 для Windows.
Результати. Під час обстеження пацієнтів з вперше виявленим ЦД 2 типу КАН з 2 патологічними кардіовагальними тестами було виявлено у 50% хворих, 3 патологічні проби у – 34,6%. Легку ДПН за шкалою Торонто було виявлено у 28,8% пацієнтів, середньої тяжкості – у 19,2% та тяжку ДПН – у 19,2%. Нами виявлено зворотний кореляційний зв'язок між загальною сумою балів п'яти кардіовагальних тестів та рівнем експресії гену BDNF В (95% ДІ) -28,5 (-55,79/-1,21), р=0,01. Також виявлено зворотний кореляційний зв'язок між рівнем експресії гену BDNF та загальною оцінкою ДПН за шкалою Торонто В (95% ДІ) -0,007 (-0,013/-0,002), р=0,011.
Висновок. Нами досліджено зворотний взаємозв'язок між рівнем експресії гену BDNF та загальною сумою балів при оцінці п'яти кардіовагальних тестів по D. Ewing як «золотого стандарту» виявлення кардіальної автономної нейропатії, що свідчить про ймовірну роль впливу гену BDNF на розвиток та прогресування кардіальної автономної нейропатії у пацієнтів з вперше виявленим цукровим діабетом 2 типу.
РІДКІСНИЙ КЛІНІЧНИЙ ВИПАДОК ВРОДЖЕНОЇ ГІПЕРПЛАЗІЇ КОРИ НАДНИРКОВИХ ЗАЛОЗ
Authors: Кравчун Нонна , Пчельнікова Ольга , Романова Ірина , Дорош Олена , Мірошніченко Оксана , Буряковська Олена , Щербатих Марія
Published: July 2024

Представлений рідкісний випадок вродженої гіперплазії кори надниркових залоз у пацієнта з класичним варіантом недостатності 21-гідроксилази. Внаслідок антенатальної гіперандрогенії розвинувся хибний жіночий гермафродитизм. Таким чином, при народженні, було помилково зареєстровано чоловічу стать.
Діагноз встановлено у тримісячному віці, але, через відмову батьків, патогенетичне лікування не проводилось впродовж багатьох років. Пацієнт виховувався, як хлопчик, гендерної дисфорії не мав. Систематична замісна гормонотерапія преднізолоном розпочата тільки з 31 року після проведеного оперативного втручання – видалення матки з придатками.
Додавання до терапії тестостерону та симптоматичних препаратів забезпечило задовільний стан пацієнта, збереження працездатності і чоловічої потенції. Однак вимушена відміна тестостерону та зміна дозування преднізолону привела до декомпенсації та погіршення загального і психо-емоційного стану. Це обумовлено симптомами гіпокортизолемії, зниженням потенції та, як наслідок, напруженими стосунками зі статевим партнером. Корекція замісної терапії забезпечила повернення пацієнта до відносно нормального життя. Звертає на себе увагу той факт, що після видалення матки з придатками та відновлення гормональної терапії у хворого зникли епілептичні скарги. Крім того, на момент теперішнього обстеження виявлено утворення лівого наднирника, що потребує верифікації та спостереження.
The Association Between Depressive Symptoms and the Weekly Duration of Physical Activity Subset by Intensity and Domain: Population-Based, Cross-Sectional Analysis of the National Health and Nutrition Examination Survey From 2007 to 2018
Authors: Boparai Josheil K , Dunnett Sarah , Wu Michelle , Tassone Vanessa K , Duffy Sophie F , Zuluaga Cuartas Valentina , Chen Ziming , Jung Hyejung , Sabiston Catherine M , Lou Wendy , Bhat Venkat
Published: July 2024

Background

Prior literature suggests a dose-response relationship between physical activity (PA) and depressive symptoms. The intensity and domain of PA are suggested to be critical to its protective effect against depression; however, existing literature has shown mixed results.

Objective

The purpose of this population-based study is to examine the associations between depressive symptoms and weekly duration of (1) total PA and (2) PA subset by intensity, domain, or both.

Methods

A cross-sectional analysis of National Health and Nutrition Examination Survey data from 2007 to 2018 was conducted using multivariable logistic and linear regression models and survey weights. Participants (N=29,730) were 20 years and older and completed the Physical Activity Questionnaire and Depression Screener. The primary outcome was the presence of depressive symptoms, and the secondary outcomes were cognitive-affective and somatic symptoms of depression.

Results

Participants (N=29,730) had a weighted mean age of 47.62 (SD 16.99) years, and 15,133 (51.34%) were female. On average, participants without depressive symptoms engaged in 10.87 hours of total PA per week, whereas participants with depressive symptoms engaged in 8.82 hours (P<.001). No significant associations were seen between the weekly duration of total PA and depressive symptom odds, somatic, or cognitive-affective symptoms (all P>.05). Participants with an increased weekly duration of recreational PA had decreases in depressive symptom odds (adjusted odds ratio [aOR] 0.965, 95% CI 0.944-0.986) and in somatic (adjusted coefficient [aβ]=–0.016, 95% CI –0.022 to –0.009) and cognitive-affective (aβ=–0.015, 95% CI –0.023 to –0.007) symptoms. When recreational PA was subset by intensity, participants with an increased weekly duration of vigorous-intensity recreational PA had decreases in depressive symptom odds (aOR 0.926, 95% CI 0.883-0.972) and in somatic (aβ=–0.021, 95% CI –0.032 to –0.010) and cognitive-affective (aβ=–0.022, 95% CI –0.035 to –0.009) symptoms. However, significant associations were not seen for the weekly duration of work-related, moderate- or vigorous-intensity PAs (all P>.05).

Conclusions

Findings suggest that recreational, not work-related PA is associated with reduced symptoms of depression. Future studies should explore the impact of the different types and contexts of PA on depressive symptomatology.
Media Use and Its Associations With Paranoia in Schizophrenia and Bipolar Disorder: Ecological Momentary Assessment
Authors: Paquin Vincent , Ackerman Robert A , Depp Colin A , Moore Raeanne C , Harvey Philip D , Pinkham Amy E
Published: July 2024

Background

Paranoia is a spectrum of fear-related experiences that spans diagnostic categories and is influenced by social and cognitive factors. The extent to which social media and other types of media use are associated with paranoia remains unclear.

Objective

We aimed to examine associations between media use and paranoia at the within- and between-person levels.

Methods

Participants were 409 individuals diagnosed with schizophrenia spectrum or bipolar disorder. Measures included sociodemographic and clinical characteristics at baseline, followed by ecological momentary assessments (EMAs) collected 3 times daily over 30 days. EMA evaluated paranoia and 5 types of media use: social media, television, music, reading or writing, and other internet or computer use. Generalized linear mixed models were used to examine paranoia as a function of each type of media use and vice versa at the within- and between-person levels.

Results

Of the 409 participants, the following subgroups reported at least 1 instance of media use: 261 (63.8%) for using social media, 385 (94.1%) for watching TV, 292 (71.4%) for listening to music, 191 (46.7%) for reading or writing, and 280 (68.5%) for other internet or computer use. Gender, ethnoracial groups, educational attainment, and diagnosis of schizophrenia versus bipolar disorder were differentially associated with the likelihood of media use. There was a within-person association between social media use and paranoia: using social media was associated with a subsequent decrease of 5.5% (fold-change 0.945, 95% CI 0.904-0.987) in paranoia. The reverse association, from paranoia to subsequent changes in social media use, was not statistically significant. Other types of media use were not significantly associated with paranoia.

Conclusions

This study shows that social media use was associated with a modest decrease in paranoia, perhaps reflecting the clinical benefits of social connection. However, structural disadvantage and individual factors may hamper the accessibility of media activities, and the mental health correlates of media use may further vary as a function of contents and contexts of use.
Đề xuất bộ tiêu chí cho dạy học trực tuyến nhằm giải quyết những thách thức của chuyển đổi số trong giảng dạy đại học
Authors: Lê Nguyễn Vân An
Published: July 2024

Chuyển đổi số trong giáo dục đang trở thành yêu cầu bức thiết của xã hội. Tuy nhiên, quá trình này cần được thực hiện một cách cẩn trọng nhằm tránh những rủi ro liên quan đến việc sử dụng công nghệ phi đạo đức, dẫn đến những mặt tiêu cực của quá trình chuyển đổi. Các phương pháp dạy học trực tuyến đang làm tăng nhu cầu về các cơ chế kỹ thuật số trong các trường đại học. Do đó, các cơ sở giáo dục đại học cần có sự định hướng, hỗ trợ cùng các tiêu chuẩn nhất định để tránh những tác động không mong muốn trên. Dựa trên việc phân tích các tài liệu có liên quan, bài viết hướng đến việc giới thiệu một bộ khung tiêu chí về quá trình thực hiện phương pháp dạy học trực tuyến đến các cơ sở giáo dục đại học vẫn còn chủ yếu sử dụng hình thức học tập trực tiếp. Tác giả cũng đề xuất việc áp dụng và quản lý cơ sở hạ tầng cùng các quy trình liên quan, nhằm đảm bảo việc sử dụng dữ liệu một cách có đạo đức trong việc phân tích dữ liệu học tập và nghiên cứu.
Nghiên cứu sử dụng bột vỏ trứng làm tá dược trong viên nén chứa hoạt chất acetaminophen
Authors: Nguyễn Quốc Châu Thanh , Nguyễn Hửu Khiêm , Trần Quang Đệ , Lê Minh Nhân
Published: July 2024

Phế phẩm vỏ trứng là nguồn nguyên liệu thô hữu ích và có thể sử dụng như một thành phần tá dược thay thế trong các sản phẩm thuốc dạng viên nén. Trong nghiên cứu này, bột vỏ trứng (BVT) được tiến hành xử lý bề mặt và phối trộn với acetaminophen bằng phương pháp dập trực tiếp. Đặc trưng cấu trúc của sản phẩm được làm rõ qua quang phổ hồng ngoại biến đổi Fourier (FT-IR). Khả năng giải phóng hoạt chất của các công thức viên nén khác nhau được khảo sát trong môi trường mô phỏng sinh lý (đệm phosphate pH 5,8) và môi trường dạ dày (pH 1,2) sang ruột non (pH 6,8). Kết quả cho thấy, acetaminophen giải phóng nhanh trong viên nén chứa BVT chưa qua xử lý trong các điều kiện khảo sát. Mặt khác, viên nén chứa 15% thành phần khối lượng BVT đã qua xử lý với nước khử ion phóng thích hoạt chất kéo dài tương đồng với thuốc thành phẩm. Tóm lại, vỏ trứng có thể được tái sử dụng như một tá dược thay thế, kiểm soát sự giải phóng các hoạt chất khác nhau trong viên nén.
Nhận thức và phấn đấu trở thành Đảng viên của sinh viên Trường Đại học Cần Thơ
Authors: Lê Ngọc Triết , Nguyễn Thị Thúy Lựu , Nguyễn Văn Pha , Trần Văn Phú
Published: July 2024

Trường Đại học Cần Thơ (ĐHCT) là trung tâm đào tạo, nghiên cứu khoa học chuyển giao công nghệ hàng đầu của quốc gia, có đóng góp hữu hiệu vào sự nghiệp đào tạo nhân lực chất lượng cao, bồi dưỡng nhân tài và phát triển khoa học phục vụ phát triển kinh tế - xã hội của vùng Đồng bằng sông Cửu Long và của quốc gia. Việc quan tâm, phát triển đảng viên trong sinh viên là rất cần thiết và quan trọng, nhằm bổ sung nguồn nhân lực trẻ vừa “hồng” vừa “chuyên” cho các tỉnh, thành phố của Vùng nói riêng và cả nước nói chung. Trên cơ sở nội hàm về vấn đề nhận thức và phấn đấu trở thành đảng viên của sinh viên, bài tham luận làm rõ thực trạng và đề xuất một số giải pháp chủ yếu nhằm nâng cao nhận thức và thúc đẩy quá trình phấn đấu đứng vào hàng ngũ của Đảng trong sinh viên Trường Đại học Cần Thơ
Hiện trạng rừng ngập mặn tỉnh Sóc Trăng thay đổi như thế nào từ năm 2016 đến 2022 – phân tích từ ảnh vệ tinh
Authors: Huỳnh Trung Tính , Võ Quốc Tuấn , Lý Trung Nguyên , Lê Quang Tâm
Published: July 2024

Nghiên cứu này được thực hiện nhằm đánh giá diễn biến hiện trạng rừng ngập mặn (RNM) tỉnh Sóc Trăng trong khoảng thời gian từ năm 2016 đến năm 2022. Phương pháp phân loại dựa vào đối tượng trên ảnh vệ tinh Sentinel-2 được sử dụng để thành lập các bản đồ hiện trạng RNM. Để xác thực kết quả phân loại trên ảnh Sentinel-2, nghiên cứu đã tiến hành khảo sát thực địa tại 134 điểm ở các huyện ven biển như Trần Đề, Cù Lao Dung và Vĩnh Châu. Kết quả đánh giá cho thấy độ chính xác của phương pháp phân loại dựa vào đối tượng là 91% với hệ số Kappa đạt 0,82. Điều này chứng tỏ việc sử dụng ảnh vệ tinh Sentinel-2 kết hợp phương pháp phân loại dựa vào đối tượng đạt hiệu quả cao và phù hợp trong việc thành lập các bản đồ hiện trạng RNM. Kết quả các bản đồ hiện trạng và so sánh giữa các năm từ 2016 đến 2022 cho thấy diện tích RNM đã tăng khoảng 907,21 ha. Kết quả nghiên cứu là nguồn tài liệu tham khảo về hiện trạng RNM, cần thực hiện những nghiên cứu phân tích chuyên sâu hơn về sinh khối rừng, đa dạng loài, tác động môi trường góp phần năng cao hiệu quả quản lý, bảo vệ và phát triển rừng bền vững.
Phân lập, tuyển chọn các dòng vi khuẩn có khả năng chuyển hóa nitơ và tích lũy poly-phosphate từ nước thải sản xuất bún
Authors: Huỳnh Ngọc Thanh Tâm , Huỳnh Yến Nhi , Trần Bích Thùy
Published: July 2024

Nghiên cứu được thực hiện nhằm tuyển chọn dòng vi khuẩn có khả năng chuyển hóa nitơ và tích lũy poly-phosphte từ nước thải sản xuất bún tại quận Bình Thủy (Thành phố Cần Thơ). Ba mươi hai dòng vi khuẩn phân lập có khuẩn lạc dạng hình tròn, màu vàng, trắng ngà hoặc trắng đục, độ nổi mô hoặc lài, bìa nguyên, chia thùy hoặc răng cưa, kích thước dao động từ 0,5 đến 3,5 mm, tế bào vi khuẩn có dạng hình cầu hoặc que ngắn, Gram dương hoặc Gram âm, catalase dương tính. Nghiên cứu đã tuyển chọn được năm dòng vi khuẩn T10, T11, T13 và T17 có khả năng chuyển hóa amonia, nitrate (100 mM, 200 mM và 300 mM) và nitrite (10 mM, 20 mM và 30 mM). Dòng vi khuẩn T11 có khả năng tích lũy poly-phosphate cao với hàm lượng 1,79 mg/L P2O5. Dòng vi khuẩn này được xác định là dòng Bacillus velezensis với độ tương đồng 100% bằng phương pháp giải trình tự gene 16S rRNA. Dòng vi khuẩn T11 có tiềm năng cao cho việc ứng dụng nguồn vi sinh vật trong xử lý nước thải ở tương lai.