bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of high-standard farmland construction (HSFC) on China's agricultural resilience
Authors: Ren Feiwu , Xia Zihan , Huang Yi , Chi Jiangtao , He Gai , Wang Yanwei
Published: July 2024

The development of high-standard farmland (HSF) constitutes a crucial strategy for enhancing agricultural infrastructure, which significantly contributes to increasing agricultural production and catalyzing agroeconomic growth. The present study devises an index system to evaluate agricultural resilience (AR) in China, anchored in the DPSIR framework, and analyzes data from 28 Chinese provinces over 2011–2021 to ascertain the effects of HSFC on AR employing fixed-effects and mediation-effects models. The study reveals that the HSFC markedly enhances AR. Specifically, in key grain production regions or the central area, the positive influence of such construction on resilience is more substantial than in non-key grain production or east-west regions. HSF fortifies AR chiefly by boosting labor productivity and increasing farmers’ income. Analysis of correlation coefficients and overall context confirms that enhanced income of farmers is the key driver in this equation. Although HSF encourages urbanization within the agricultural community, this trend may inadvertently hinder resilience improvements. While the indispensable role of HSF in promoting agricultural progress is recognized, it is crucial to address the concurrent issue of population outflow from agricultural sectors. This study contributes uniquely by integrating the DPSIR model into the exploration of AR, thereby offering a novel, proactive approach to sustainable agricultural development. Furthermore, it elucidates the mechanisms through which HSF impacts AR across three dimensions: labor productivity, farmer incomes, and population urbanization, from the farmers’ vantage point. This insight enables policymakers to refine resource allocation, enhancing the planning, design, and stewardship of sustainable agriculture.
Demographic Inaccuracies and Biases in the Depiction of Patients by Artificial Intelligence Text-to-Image Generators
Authors: Wiegand Tim , Jung Leonard , Schuhmacher Luisa , Gudera Jonas , Moehrle Paulina , Rischewski Jon , Velezmoro Laura , Kruk Linus , Dimitriadis Konstantinos , Koerte Inga
Published: July 2024

The wide usage of artificial intelligence (AI) text-to-image generators raises concerns about the role of AI in amplifying misconceptions in healthcare. This study therefore evaluated the demographic accuracy and potential biases in the depiction of patients by two commonly used text-to-image generators. A total of 4,580 images of patients with 29 different diseases was generated using the Bing Image Generator and Meta Imagine. Eight independent raters determined the sex, age, weight group, and race and ethnicity of the patients depicted. Comparison to the real-world epidemiology showed that the generated images failed to depict demographical characteristics such as sex, age, and race and ethnicity accurately. In addition, we observed an over-representation of White as well as normal weight individuals. Inaccuracies and biases may stem from non-representative and non-specific training data as well as insufficient or misdirected bias mitigation strategies. In consequence, new strategies to counteract such inaccuracies and biases are needed.
Multi-strategy Enhanced Artificial Rabbits Optimization for Prediction of Grades in Tourism Service Communication Courses
Authors: Jia Zhuyin , Qu Xiaodan
Published: July 2024

Predicting students' grades through their classroom behavior is a longstanding concern in education. Recently, artificial intelligence has shown remarkable potential in this area. In this paper, the Artificial Rabbits Optimization Algorithm (ARO) is chosen to enhance the predictor's capabilities. ARO is a recently proposed and popular metaheuristic algorithm known for its simple and straightforward structure. However, like other metaheuristic algorithms, ARO often falls into local optima and, as iterations increase, the convergence speed slows down, leading to lower convergence accuracy. To address this issue, we introduce a Multi-Strategy Enhanced Artificial Rabbits Optimization Algorithm (MEARO). In MEARO, we first employ a Nonlinear exploration and exploitation transition factor (NL) to improve the balance between exploration and exploitation in ARO. we employ a Stochastic Dynamic Centroid Backward Learning approach (SOBL) to improve both the quality and diversity of the population. This ensures a broader optimization of the search area and boosts the chances of locating the global optimum. Lastly, we incorporate a Dynamic Changing Step Length Development strategy to enhance the randomness and development capability of ARO. To confirm the efficiency of MEARO, we compared its performance with eight other sophisticated algorithms using the CEC2017 benchmark. Our findings indicate that MEARO outperforms the other algorithms we tested. Furthermore, we optimized two critical parameters of the Kernel Extreme Learning Machine (KELM) using the MEARO algorithm, boosting its classification performance. Moreover, experimental results on the collected student performance dataset show that the KELM model optimized by MEARO outperforms other benchmarked models in terms of various metrics. Finally, we also find that interest in the course, frequency of classroom discussion, and access to extra knowledge and information related to the course are significant factors affecting performance.
Phytochemical profiling, antioxidant and nephroprotective activities of Ziziphus lotus Lam. leaf extract in paracetamol-induced renal toxicity in rats and molecular docking analysis
Authors: Ukwubile Cletus Anes , Menkiti Nnamdi David , Ahuchaogu Ahamefula Anslem , Malgwi Troy Salvia , Dibal Nathan Isaac , Umeokoli Blessing Ogechukwu
Published: July 2024

Ziziphus lotus Lam. is a medicinal plant that is used mostly in Nigeria and parts of Africa for treating many diseases. The study was aimed at assessing the phytoconstituents, evaluating antioxidant and nephroprotective activities against paracetamol-induced renal toxicity in rats and molecular docking analysis of leaf extract. Liquid-liquid partitioning was carried out for most active fraction while column chromatography was used for the isolation of bioactive compounds and analyzed by the GC-MS. Total phenolic and total flavonoid contents were determined using standard methods, antioxidant activity by DPPH (2-2-diphenyl-1-picrylhydrazyl) and ABTS (2,2’azinobis (3ethyl-benzothiazoline-6sulfonic acid) scavenging assays and nephroprotective activity was evaluated at various extract doses in rats. Molecular docking studies were carried out using AutoDock Vina software. The GC-MS profiling of the extract revealed the presence of 18 compounds with five compounds showing the strongest activities. Molecular docking studies of the most bioactive compounds predicted potential antioxidant and nephroprotective effects. The results further revealed a total phenolic content of 408.12 mg GAE/g and a flavonoid content of 88.01 mg QE/g. It also showed significant (p < 0.05) antioxidant activities against DPPH and ABTS radical scavenging at concentrations 0 to 800 µg/mL. There were significant abnormal increases in the biochemical parameters before the treatment of rats, and these increases were reduced significantly on administration of the leaf extract. Our study showed that Z. lotus extract possessed antioxidant activity and reversed kidney toxicity, thus, justifying its uses as an ethnomedicinal remedy for kidney problems.
Analyzing Knowledge Networks in Sustainability: Towards Achieving Sustainable Development Goals
Authors: Kim Yong Jin
Published: July 2024

Background: Increasing interest in sustainability has prompted the need for targeted research to achieve Sustainable Development Goals (SDGs). This study aims to identify key research areas (RAs) within sustainability knowledge networks.
Methods: We analyzed 535 papers published between 2015 and 2020 in the “Green and Sustainable Science and Technology” category of the Web of Science. Employing co-occurrence, cluster, and topological analyses, we established a network of 73 keywords and 103 links.
Results: Cluster analysis revealed three primary RAs: renewable energy (aligned with SDG 7: Affordable and Clean Energy), circular economy (aligned with SDG 12: Responsible Consumption and Production), and carbon emissions (aligned with SDG 13: Climate Action). Topological analysis, through a matrix based on weighted degree centrality and weighted closeness centrality, further identified influential topics within each RA.
Conclusions: The findings highlight the critical role of targeted goal setting in sustainability initiatives and provide actionable insights for policymakers to advance the SDGs effectively.
A lightweight enhanced branching attention model for remote sensing scene image classification
Authors: Wang Huiyue , Wang Xinyu , Xu Haixia , Yuan LiMing , Wen Xianbin
Published: July 2024

Unlike natural images, remote sensing images exhibit significant spatial complexity and minimal intra-class differences, presenting considerable challenges in the field of remote sensing scene image classification (RSSC). Although existing convolutional neural networks have achieved some progress in this domain, they often fail to fully account for the unique characteristics of remote sensing images. Additionally, these networks typically suffer from excessive parameter redundancy, resulting in substantial computational burdens. This is particularly problematic given the difficulty in obtaining and labeling remote sensing data. To address these issues, this paper proposes a lightweight method (AEBANet) featuring an attention branching structure specifically designed for RSSC. First, we construct an overall feature extraction framework based on depth-wise separable convolution (DS-Conv) to ensure efficient feature extraction while maintaining accuracy. Then, we propose the Adaptive Enhanced Branch Attention (AEBA) module, a lightweight structural design that enhances the model's capability to capture key features in both channel and spatial domains. Second, we develop the Multi-Level Feature Fusion (MLFF) module to integrate features at different levels, thereby improving information flow between features and utilizing detailed shallow information to supervise the deep global information. Finally, the proposed AEBANet achieves the highest overall accuracy of 93.12%, 96.76%, and 99.52% on the NWPU, AID, and UCM datasets, respectively. Ablation studies on these datasets validate the effectiveness and necessity of each module. Additionally, the proposed method is characterized by low complexity and computational cost.
Peptidomics Characteristics of Pediatric Sepsis
Authors: Yan Haipeng , Li Xun , Luo Ting , Zeng Xiaohui , Li Xiao , Xie Longlong , Wang Xiangyu , Yang Yufan , Zhang Xinping , Huang Jiaotian , Liu Pingping , Luo Lan , Cao Jianshe , Zhou Haiyin , Lu Xiulan , Xiao Zhenghui
Published: July 2024

This study explores the significant differential expression of peptides in sepsis patients compared to healthy controls and those with common infections using plasma peptidomics analysis. Blood samples were collected from 10 pediatric sepsis patients admitted to Hunan Children's Hospital in 2021, along with 20 age- and sex-matched healthy controls and 5 children with common infections. Differential peptide precursor proteins underwent GO and KEGG pathway enrichment analyses and protein-protein interaction analysis using the STRING database. A total of 3149 endogenous peptides corresponding to 480 precursor proteins were identified. Compared to the healthy group, the sepsis group exhibited 1113 differential peptides, with 880 upregulated and 233 downregulated. Compared to the common infection group, the sepsis group showed 181 upregulated and 86 downregulated peptides. These differences were primarily in humoral immune response and complement and coagulation cascades. The peptide RSFFSFLGEA, associated with the precursor protein SAA1, had the highest LogFC values between sepsis and healthy groups, and sepsis and common infection groups, with values of 6.828 and 5.580, respectively. This study reveals specific changes in peptide expression in sepsis patients' plasma, particularly significant alterations in peptides related to SAA1, complement C3, HB, and HP. These peptides are involved in acute inflammatory response, complement system, and free hemoglobin pathways, indicating their crucial roles in sepsis pathology. These findings provide new insights into the mechanisms of sepsis and suggest potential applications of these peptides in sepsis diagnosis and treatment, aiming to improve early diagnosis and therapeutic outcomes.
Evaluation of insecticides performance for the management of leaf miners in Fenugreek (Trigonella foenum-graecum L.)
Authors: Shinde Sojwal , Patil Chidanand , Pawar Somnath , Deore Bhaidas , Oftadeh Marziye
Published: July 2024

Fenugreek (Trigonella foenum-graecum L.), an ancient leguminous crop with medicinal properties, is widely consumed as green leaves, pods, and seeds. Leaf miner infestation, causing white tunnels in leaves, significantly reduces leaf vigor and productivity. An experiment using a Randomized Complete Block Design with seven chemical treatments and three replications aimed to combat this pest. Observations were made on three leaves of five plants per plot, assessing percent leaf infestation before treatment and at 1, 3, and 7 days post-treatment over two years (Rabi-2020 and Rabi-2021). Results showed that Chlorantraniliprole at 30 g a.i. ha-1 was most effective, with the lowest leaf miner infestation (19.16%) and highest yield increase (58.38%), achieving an Incremental Cost Benefit Ratio (ICBR) of 1:9.1. Following this, cyantraniliprole at 90 g a.i. ha-1, thiamethoxam at 25 g a.i. ha-1, and chlorantraniliprole + thiamethoxam (soil drench) at 150 g a.i. ha-1 also showed effectiveness. Notably, thiamethoxam at 25 g a.i. ha-1 had the highest ICBR due to its lower cost. Farmers are advised to use newer insecticides like chlorantraniliprole and cyantraniliprole to mitigate yield losses from leaf miner infestations. These insecticides demonstrated significant efficacy in protecting fenugreek crops, particularly where the economic value lies in the leaves.
Constraint-Depentdent Switching Event-Triggered Control for UncertainNonlinear Systems with State Constraints
Authors: Liu Yuang , Duan NA , Li Can , Liu Xuemei , Wan Changhui , Ge Quanbo
Published: July 2024

This paper investigates the event-triggered control problem for a class of strict-feedback uncertain nonlinear systems with switching state constraints. The main challenges of such work arise from two aspects: (1) The state is not constrained at all moments, so the constraints on the state are not fixed, resulting in switches between bounded and unbounded constraints. The existing research is more suitable for bounded constraints. (2) Due to the presence of switching constraints, we aim to address these scenarios with varying control performance, existing research addresses this solely via offline tuning of the controller and its parameters. To solve the above problems, we develop a new exponential nonlinear state-dependent function (ENSDF). The ENSDF transforms the constraint problem of the original state into the boundedness problem of the new state, independent of the boundedness of the constraint boundaries. Then, a new constraint-dependent switching event-triggered controller is developed. The switching event-triggered controller based on ENSDF can dynamically adjust the controller and its parameters online to adapt to switching constraints. It is theoretically shown that the state does not violate the constraints, all closed-loop signals are globally bounded, and the tracking error converges towards an adjustable compact set.
Delay in Return to Fertility after Discontinuation of Using Depo-Provera and Associated Factors Among Currently Pregnant Women Attending Antenatal Care in Public Health Facilities in Gindeberet District, Oromia, Ethiopia, 2021
Authors: Tolera Tilahun Negero , Kubela Andinet Tesema , Obssie Gadisa Fitala
Published: July 2024

Background: One of the of methods to control fertility is use of injectable Depo-Provera which has the side effect of delaying return to fertility after discontinuation of it. Delay of fertility return after the method termination remains a major concern for women who use it. This fear poses a negative impact on utilization and continuation of Depo-Provera in developing nations including Ethiopia. Therefore, determining the median delay of fertility return after discontinuation of Depo-Provera and identifying the associating factors are important for developing solutions to the issues of clients and health care providers
Objective: To assess delay in fertility return after discontinuation Depo-Provera and associated factors among pregnant women attending ANC in public health facilities in Gindeberet district, Oromia, Ethiopia ,2021
Methods: Facility based cross sectional study was conducted on 415 pregnant women attending Antenatal care in Public Health Facilities in Gindeberet district from August 10-October 10/2021.Consecutive sampling technique was used. pretested structured Interviewer-administered questionnaire was used to collect data.Data were entered into Epi infoversion 7 and then exported to SPSS version 25 for cleaning ,analysis and summarized using descriptive statistics of Frequencies and median. Bivariate and multivariable logistic regression was applied to estimate the crude and adjusted odds ratios with 95% CI to determine the presence and strength of association and P- value < 0.05 as cut off point
Result: The median delay of fertility return in this study was found to be 10 months from date of Depo-Provera discontinuation. The magnitude of fertility delay in this study was 45.5%[95%CI=38.4.4%,52.6%].Multivariable analysis showed that being lower income ≤2500 ETB [AOR:0.09 (0.042,0.21)],Age group from 15-24years [AOR:0.04 (0.006, 0.23)], Age group from 30-34yearsAOR:[0.23(0.083,0.66)],Age at first sex 19-23years [AOR:0.4(0.17,0.93)],Being sexually active1day/week[AOR:5.5(1.4,20.8)] sexually active 2-3days/week [AOR:4.2 (1.7,14.9)] had significant association with delay in return to fertility after discontinuation of using Depo-Provera.
Conclusion and recommendation: After discontinuation of Depo-Proverathere is significant delay in return to fertility. Therefore, Women should be counseled that there is a potential for delay in return to fertility following discontinuation of the method.Being older age, being higher income, infrequent sexual intercourse and delayed age at first sex were predictors of fertility delay after discontinuation of Depo-Provera.
Integration of Photovoltaic Module with Inductive Power Transfer Using a Single Buck-Boost Converter
Authors: de Lacerda Macklyster Lãnucy S. S. , Viera Leonardo A. Brum , Rech Cassiano , Santos Walbermark M. dos
Published: July 2024

Inductive power transfer (IPT) systems, when integrated with photovoltaic (PV) generation, traditionally necessitate the inclusion of a DC-DC converter to uncouple the generation and transmission stages. This conventional approach requires dual converters: one dedicated to PV's MPPT and the other to adjust the IPT's operational point, raising system costs and complexity. Thus, this study examines a system composed of a PV directly attached to an SS IPT using a single buck-boost converter for control purposes. The operational points of PV-IPT are described in terms of resistance values. Findings indicate that the implemented MPPT control identifies an intermediate operational point between the PV and IPT power peaks. Experimental data was acquired using a 100 W PV. The overall efficiency was mainly constrained by the IPT's efficiency, with experimental observations indicating maximum transferred power and overall efficiency of about 40 W and 60%, respectively.
The cyclic diagnosability of star grraphs *
Authors: Li Yalan , Ma Xiujuan
Published: July 2024

Connectivity and diagnosability are two important parameters for the tolerance of an interconnection network. The cyclic diagnosability ct(G) is the maximum number of faulty vertices that the graph can be guaranted to identify under the condition that the remaining graph has at least two components contain a cycle. In this paper, we study the problem about the cyclic diagnosability ct(G) of star graphs and obtain probability analysis of its cyclic diagnosability.
A Robust Approach for Deepfake Detection Using SWIN Transformer
Authors: Mishra Soumya Ranjan , Mohapatra Hitesh , Gourisaria Mahendra Kumar
Published: July 2024

The widespread use of deepfake technology in recent years has made it extremely difficult to differentiate between real and fake images, usually AI-generated images. Effective detection techniques are desperately needed because one can generate fake images and spread them with ease. In response to the situation, this research paper explores the effectiveness of employing SWIN Transformer, a cutting-edge transformer-based architecture, for deep fake image detection. The foundation of the suggested detection framework is an architecture made up of bottleneck, encoder, and decoder parts which is a type of SWIN transformer. It uses various self-attention mechanisms and advanced features to analyse the images closely whether it is a real image or a deepfake one. It relies on the concept of shifted windows during the processing of the images and is considered more effective than the traditional CNN methods. Our test results show how well the SWIN Transformer-based method performs in precisely recognizing deep fake images. The accuracy is found to be 97.91% for CelebDF dataset and 95.715% for FF++ dataset. The AUC for the newly modelled SWIN transformer is 0.99 and 0.9625 for CelebDF and FF++ datasets respectively. The Log Loss has been calculated to be 0.034 for CelebDF dataset and 0.1573 for FF++ dataset. The proposed methodology not only enhances the accuracy of detecting manipulated images but also offers potential for scalable and efficient deployment in real-world scenarios where the proliferation of deepfakes presents significant challenges to maintaining trust and authenticity in visual media.
Acceleration of Near Field Computation in MLFMA Algorithm on a single GPU by Generating Redundancy in Data
Authors: Torabi Abdolreza , Sadeghi Morteza
Published: July 2024

The Multilevel Fast Multipole Algorithm (MLFMA) has known applications in scientific modeling in the fields of telecommunications, physics, mechanics, and chemistry. Accelerating calculation of far-field using GPUs and GPU clusters for large-scale problems has been studied for more than a decade. The acceleration of the Near Field Computation (P2P operator) however was less of a concern because it does not face the challenges of distributed processing which does far field. This article proposes a modification of the P2P algorithm and uses performance models to determine its optimality criteria. By modeling the speedup, we found that making threads independence by creating redundancy in the data makes the algorithm for lower dense problems nearly 13 times faster than non-redundant mode.
Complex Oxides Synthesized via Arc Furnace: a Fast, Direct and Effective Approach to Obtain Functional Materials
Authors: Macedo Nadia , Galante Miguel , Soares Leonardo , Alvim Jéssica , Lima Vanderlei , Sangali Marcio , Rodrigues João , Caram Jr. Rubens , Longo Claudia
Published: July 2024

Complex oxides can present interesting semiconductor properties since the simultaneous presence of different metallic cations can modulate the conduction and valence band edges, affecting the bandgap energy, the onset potential for reactions and also the photocatalyst long-term stability. Here, we demonstrated that the synthesis of multinary oxides, very challenging using “traditional” methodologies, can be fast achieved by melting the precursor binary oxides in an arc furnace. As a proof of concept, arc-melting a mixture of Bi2O3 and V2O5 (Bi:V molar ratio of 1:1.05) resulted in almost pristine BiVO4 (97.3% from Rietveld refinement of X-ray diffraction (XRD) data); photoelectrochemical (PEC) measurements indicated a promising application as a photoanode for O2 evolution reaction. Conversely, the arc-melting of Bi2O3 and WO3 mixture (Bi:W molar ratio of 2:1.15) resulted in the biphasic Bi2WO6/Bi2W2O9; preliminary PEC analysis revealed characteristics of n-type semiconductor electrode with photoactivity under UV irradiation. Finally, the hierarchical Ag@α-AgVO3/Fe2O3 consisted of micrometric Fe2O3 particles decorated by AgVO3 nanoribbons and Ag nanoparticles, was obtained from melting Ag2O, Fe2O3 and V2O5 as precursors (Ag:Fe:V molar ratio of 3:1:2); PEC measurements also revealed possible application as a photoanode. The results for these three materials demonstrated the arc-synthesis as a fast, effective and scalable methodology for synthesizing complex oxides.
Effectiveness of behaviour change interventions to reduce the risk of faecal contamination in urban irrigated vegetable value chains – applying the COM-B behavioural framework
Authors: Galibourg David , Scott Rebecca E. , Gough Katherine V. , Drechsel Pay , Evans Barbara E.
Published: July 2024

In low- and middle-income countries, inadequate sanitation results in faecal contamination of the water used by urban farmers for irrigation. Consumers of raw contaminated vegetables run the risk of developing diarrhoeal diseases and helminth infections, which are a leading cause of under-five mortality and impact the well-being and productivity of millions of adults. This review identifies the evidence base for assessing which factors determine the success and/or failure of interventions that aim to manage the risk of faecal contamination in the urban irrigated vegetable value chain. We carried out a systematic search of the literature from the perspective of the COM-B behaviour framework (Capability + Opportunity + Motivation = Behaviour). Our results reveal that most interventions address stakeholders’ opportunity or capability to adopt safe practices without adequately considering their motivation. Interventions often focus on one sector rather than on the whole value chain (sanitation, agriculture, trade, consumption). To effectively change hygiene and food safety practices in the urban irrigated vegetable value chain, stakeholders’ intrinsic motivations need to be identified. Where WHO's multi-barrier approach is the best option, we recommend building on local multistakeholder platforms and adopting a behaviour change framework to support the largely technical change from farm to fork.
Cisplatin-based Liposomal Nanocarriers for Drug Delivery in Lung Cancer Therapy: Recent Progress and Future Outlooks
Authors: Mohammad-Jafari Kave , Naghib Seyed Morteza , Mozafari M.R.
Published: July 2024

:

In order to improve the treatment of lung cancer, this paper looks at the development of cisplatinbased
liposomal nanocarriers. It focuses on addressing the drawbacks of conventional cisplatin therapy, including
systemic toxicity, inadequate tumor targeting, and drug resistance. Liposomes, or spherical lipid vesicles,
offer a potentially effective way to encapsulate cisplatin, enhancing its transport and minimizing harmful
effects on healthy tissues. The article discusses many liposomal cisplatin formulations, including pH-sensitive
liposomes, sterically stabilized liposomes, and liposomes coupled with specific ligands like EGFR antibodies.
These novel formulations show promise in reducing cisplatin resistance, optimizing pharmacokinetics, and
boosting therapeutic results in the two in vitro and in vivo models. They also take advantage of the enhanced
permeability and retention (EPR) effect in the direction of improved tumor accumulation. The study highlights
the need for more investigation to move these liposomal formulations from experimental to clinical settings,
highlighting their potential to offer less harmful and more effective cancer therapy alternatives.
Recent Advances in N-Arylation of Heterocycles in the Past Decade
Authors: Yang Xun , Li Haiyan , Jiang Quan , Lei Zhiguo , Xiao Yuxuan , Liu Jialing , Duan Wengui , Yu Lin
Published: July 2024

:

N-arylated heterocycles are a significant class of core scaffolds in medicinal
chemistry, materials science, and agrochemistry, highlighting their importance in various
fields. The development of innovative methodologies for synthesizing these fundamental
structures has been a central focus in organic synthesis. Over the past few decades, numerous
approaches have been established to synthesize N-aryl heterocycles efficiently. Among
these methods, the direct N-arylation of N-H heterocycles stands out as one of the most
straightforward and robust strategies for accessing N-arylated heterocycles. This review
provides a comprehensive review of the recent advances in the synthesis of N-arylated heterocycles,
encompassing the relevant literature from the past decade. The review summarizes
the N-arylation of N-H heterocycles using various catalytic systems, including palladium,
nickel, copper, visible light-induced metal-catalyzed, and metal-free catalyzed methodologies. These
advances highlighted the continuous evolution and optimization of synthetic strategies to create diverse and
complex N-arylated heterocycles, which are pivotal for furthering research and development in multiple scientific
domains.
Spectrophotometric Determination of Curcumin using 3-Methyl-2-benzothiazolinone Hydrazone Hydrochloride Hydrate as Electrophilic Coupling Agent
Authors: Ayesha Syeda
Published: July 2024

Introduction:

Nutraceuticals are products derived from food sources that provide
extra health benefits in addition to the basic nutritional value found in foods. Spectrophotometric
methods for the determination of curcumin were developed, which are
simple, sensitive, selective, rapid, and reliable.

Methods:

The methods are based on the reduction of iron (III) to iron (II) by 3-Methyl-2-
benzothiazolinone hydrazone hydrochloride hydrate (MBTH), which is an electrophilic
coupling agent and subsequent reaction with curcumin in mild hydrochloric acid medium.
Spectrophotometric methods for the determination of curcumin were developed, which
are simple, sensitive, selective, rapid, and reliable. The methods are based on the reduction
of iron (III) to iron (II) by 3-Methyl-2-benzothiazolinone hydrazone hydrochloride
hydrate (MBTH), which is an electrophilic coupling agent and subsequent reaction with
curcumin in mild hydrochloric acid medium.

Result:

The reaction produces a bluish–green complex with maximum absorbance at 670
nm. The colour complex can be extracted into chloroform. The methods obey Beer’s law
in the range 0.3-7.0 and 0.2-7.0 (μg mL-1).

Conclusion:

10 common anions and cations were added, and the method was tested, and
no interference was observed. The proposed methods offered the advantages of having
good reproducibility and were satisfactorily worked out to estimate the amount of curcumin
in various turmeric samples.
Recomendaciones técnicas para la producción de semilla de cebada, trigo y avena en el altiplano cundiboyacense
Authors: Castillo Sierra Javier , Avellaneda Avellaneda Yesid , Mayorga Cubillos Franklin , Mancipe Muñoz Edgar , Albarracín Arias Luis Orlando , Rodríguez Molina John Fredy , Baquero Cubillos Edison Ferney , Atencio Solano Liliana , García Gómez Gustavo
Published: July 2024

La producción de semillas de cereales como la avena, la cebada y el trigo constituye una estrategia fundamental para promover la sostenibilidad de los sistemas de producción bovina en el trópico alto colombiano. En este contexto, el presente manual presenta las investigaciones y experiencias acumuladas por AGROSAVIA en el ámbito de la producción de semillas, con el objetivo primordial de incrementar la productividad y garantizar la calidad de la semilla, especialmente orientada a pequeños y medianos productores. El manual abarca de manera integral la descripción, generalidades, importancia y principales características de la avena, la cebada y el trigo. A continuación, se detalla el proceso de producción de semillas, desde la planeación del cultivo hasta el almacenamiento de esta, incluyendo la selección y preparación del terreno, el establecimiento del cultivo, su desarrollo y mantenimiento, la cosecha, la poscosecha y el almacenamiento adecuado de la semilla. Finalmente, el documento realiza un análisis exhaustivo de los costos de producción de semilla de acuerdo con el proceso descrito. Toda la información contenida en este manual se sustenta en la amplia experiencia e investigación desarrollada por AGROSAVIA en el campo de los cereales, con un enfoque particular en el altiplano cundiboyacense.
Quality Improvement Initiatives for Outpatient Management of COVID-19 in Community Hospitals in Uganda (Preprint)
Authors: Ikiriza Antony
Published: July 2024

BACKGROUND

The coronavirus disease (COVID-19) dramatically disrupted outpatient care delivery. Guidelines for HCPs and refresher courses have been developed to boost their skills and knowledge of the disease though not effectively disseminated through training due to physical distancing and unprecedented disruptions to traditional avenues for delivery of medical education leaving many HCPs with apparent lack of knowledge and skills hence an urgent need to fill knowledge and training gaps.

OBJECTIVE

Our goal was to improve COVID-19 outpatient management through use of a mobile-based decision support system (DDC19) in COVID-19 patient risk stratification in community hospitals in Uganda.

METHODS

The project was implemented in 139 community hospitals in Uganda, the patients were assessed for the risk of COVID-19 and stratified as either Low, Moderate or High risk using the adopted excel sheet based on the DDC19 principle to assist HCPs in real time data collection, dynamic risk assessment, triage management, and follow-ups of COVID-19. We ran an 8 months training using an International Virtual COVID-19 Critical Care Training Forum for Healthcare Workers and five-days QI trainings for hospital leaders using a QI training curriculum developed by USAID and Ministry of Health Uganda QI Frame Work and Strategic Plan (2021-2025).

RESULTS

A total of 319 patients were tested for COVID-19 and stratified as low risk 195(61.1%), moderate risk 102(32.0%) and high risk 22(6.9%), 21(6.6%), a total of 854 HCPs were trained their knowledge score improved from 42.69% to 72.70%, knowledge scores of 139 hospitals leaders in QI projects increased from 59.99% to 70.04%.

CONCLUSIONS

COVID-19 patient risk stratification was achieved, The knowledge and skills of HCPs in application of best practices for management of COVID-19 increased from 42.69% to 72.70%, The knowledge and skills of leaders in design and implementation of outpatient QI projects improved from 59.99% to 70.04%.
The innovative nature of the project improved the COVID-19 patient risk stratification was achieved despite the non-approval of use of DDC19 in Africa and the improvement in the knowledge and skills of the HCPs and hospital leaders is key for improved diagnosis, risk stratification and outpatient management of COVID-19 patients
Typical course of hippocampal sclerosis. Literature review
Authors: Pryima M.Yu. , Studeniak T.O.
Published: July 2024

The article reviews the problem of hippocampal sclerosis as the main cause of pharmacoresistant temporal lobe epilepsy. Clinical manifestations, diagnostic criteria, recommended methods of examination and treatment of hippocampal sclerosis are given. The effectiveness of surgical and medical treatments was analyzed. The relevance of this article is due to a general increase in the detection of this disease, primarily owing the improvement of neuroimaging methods. Given that this disease is relatively rare, and that surgical treatment is often delayed for many years, a review of this topic is useful for early diagnosis and improved treatment outcomes. Modern literary sources on hippocampal sclerosis were studied. The studied material is summarized and presented in the form of a literature review in this article. A search for literary sources was carried out in two main scientific databases: Scopus and PubMed. The review included original articles, research, and official guidelines from medical associations.
Influence of the anatomical level of spinal cord injury on the severity of neurological impairments in spinal cord trauma
Authors: Nekhlopochyn O.S. , Nikiforova A.N. , Verbov V.V. , Yovenko T.A. , Cheshuk Ie.V.
Published: July 2024

Background. Traumatic spinal cord injury is a significant medical and social issue. Despite numerous studies, substantial success in reducing neurological consequences in such patients has not yet been achieved, and several aspects remain understudied, particularly the response of the spinal cord to injury at different anatomical levels. The purpose is to analyze the influence of the anatomical level of injury, the patient’s gender, and the mechanism of injury on the pattern of functional disorders in the acute period of spinal cord trauma using the largest publicly available database of patients with traumatic spinal cord injuries. Materials and methods. A statistical analysis of data from the National Spinal Cord Injury Model Systems Database (version 2021 ARPublic) was conducted. It included 21,343 cases containing information on gender, age at the time of injury, circumstances of injury, the degree of neurological disorders at hospitalization, and the anatomical level of traumatic injury (with precision down to the spinal cord segment). Results. The data analysis revealed significant differences in the pattern of distribution of functional classes according to the American Spinal Injury Association scale depending on the anatomical level of spinal cord injury. For the cervical region, the distribution of frequencies for A, B, C, and D classes was as follows: 43.06 % (95% confidence interval (CI): 42.15–43.97 %), 14.99 % (95% CI: 14.35–15.66 %), 16.17 % (95% CI: 15.50–16.86 %) and 25.78 % (95% CI: 24.98–26.59 %), respectively, for the thoracic region — 70.97 % (95% CI: 69.94–71.97 %), 10.27 % (95% CI: 9.60–10.97 %), 9.92 % (95% CI: 9.26–10.61 %) and 8.85 % (95% CI: 8.23–9.51 %), for the lumbar region — 21.29 % (95% CI: 19.57–23.12 %), 15.87 % (95% CI: 14.35–17.52 %), 24.43 % (95% CI: 22.62–26.34 %) and 38.40 % (95% CI: 36.32–40.52 %). Conclusions. The pattern of distribution of functional classes of neurological impairments significantly depends on the anatomical level of spinal cord injury. Thoracic segment injuries are characterized by the most clinically severe symptoms, whereas lumbar segment injuries are the least severe. The patient’s gender does not have a statistically significant influence, while the circumstances of the injury correlate with the frequency of neurological impairments in cervical segments and do not affect this indicator in the lumbar region.
A case report of a hemorrhagic stroke with atrial fibrillation in combination with hypertension
Authors: Samoilova H.P. , Markovska O.V. , Tovazhnyanska O.L. , Myroshnychenko M.S. , Bibichenko V.O. , Sakal H.O.
Published: July 2024

Background. Stroke is a heterogeneous syndrome, and identification of risk factors and treatment depends on the specific pathogenesis of the disease. Cardiovascular diseases are risk factors for the development of acute disorders of cerebral circulation. According to recent studies, one third of all ischemic strokes are cardioembolic. The main pathoetiology of a hemorrhagic stroke in the form of intracerebral hemorrhages is chronic hypertension and cerebral amyloid angiopathy. The occurrence of a hemorrhagic stroke against the background of atrial fibrillation in combination with hypertension is a rather rare phenomenon and poses a problem in the choice of treatment for such patients. The aim was to determine the optimal treatment for a complex case of a hemorrhagic stroke with atrial fibrillation in combination with hypertension. Materials and methods. We present the clinical case of an 84-year-old woman who developed a hemorrhagic stroke on the background of atrial fibrillation in combination with hypertension. The main issue the cardio-neurological team faced was the administration of oral anticoagulants. On the one hand, the patient had indications for their administration according to current clinical guidelines (CHA2DS2-VASc score of 6 points); on the other hand, the presence of a hemorrhagic stroke is a contraindication. Results. This case demonstrates the solution to the difficult issue of choosing treatment for a hemorrhagic stroke and prevention of secondary complications of atrial fibrillation in combination with hypertension. After medical cardioversion, using clinical recommendations for the treatment of a hemorrhagic stroke, as well as given the positive dynamics of the neurological status, the patient was prescribed apixaban at a dose of 2.5 mg twice a day under the control of a coagulogram from the 7th day of the disease onset. Conclusions. We believe it is necessary to perform a thorough neurological examination and assessment of cognitive functions in all patients with atrial fibrillation, as well as to consider neuroimaging prior to the prescription of anticoagulant therapy. We recommend considering the administration of oral anticoagulants to patients with a low risk of recurrence and a high risk of thromboembolic complications after intracerebral hemorrhage
Impoliteness Strategies in John Mulaney's Stand-Up Comedy
Authors: Arlivia Zitta , Sembodo Thomas Joko Priyo
Published: July 2024

An analytical study on comedy provides significant insight into comedy as a complex and pervasive medium of expression penetrating everyday life. This study investigates the impoliteness strategies in John Mulaney’s stand-up comedy and how the most frequently used strategy entertains the audience through five sources of pleasure. The data gathered are the utterances containing impoliteness strategies from John Mulaney’s stand-up comedy specials: New in Town (2012), The Comeback Kid (2015), Kid Gorgeous (2018), and Baby J (2023). The impoliteness strategies found in the stand-up comedy were then classified using the theory of impoliteness strategies proposed by Culpeper (1996). The data containing the most frequently used impoliteness strategy are then classified based on Culpeper’s (2011) theory of five sources of pleasure of entertaining impoliteness function. The result shows 344 impoliteness strategies, with the positive impoliteness strategy being the most frequently used, with 163 occurrences (47.4%). From the 163 occurrences of positive impoliteness strategies, 105 entertain the audience through emotional pleasure (64%), followed by the pleasure of being superior with 33 occurrences (20.1%), the pleasure of feeling secure with 14 occurrences (8.5%), voyeuristic pleasure with ten occurrences (6.1%), and aesthetic pleasure with two occurrences (1.2%). The findings indicated that throughout his stand-up comedy performances, John Mulaney employs various impoliteness strategies, especially positive impoliteness strategies, to entertain the audience, primarily by evoking their emotional pleasure.
UNAM. La universidad de la nación
Authors: Trigo Tavera Francisco José
Published: July 2024

Obra en la que se hace un recuento puntual y actualizado de la presencia y los alcances de la Universidad Nacional Autónoma de México en los ámbitos nacional e internacional. En sus páginas se da testimonio de las principales actividades cotidianas en investigación, docencia y difusión de la cultura y se refleja el compromiso adquirido con la sociedad mexicana, con la formación de un capital humano libre y responsable, y con los logros y desafíos que han beneficiado a la comunidad.
Harnessing Deep Learning for Accurate Detection of Breast Cancer in Histopathological Imagery
Authors: Bhavani Dhanikonda Ratna
Published: July 2024

Abstract: Breast cancer, the most common cancer among women after skin cancer, significantly contributes to the rising mortality rate. Screening mammography is an effective method for detecting masses and abnormalities related to breast cancer. Digital mammograms are especially useful for early cancer detection in asymptomatic women and diagnosing cancer in women with symptoms such as lumps or nipple discharge, thereby reducing mortality and increasing survival rates. Clinicians often face time constraints that can lead to medical errors and incorrect diagnoses due to insufficient time to review patient history thoroughly.
APLICACIÓN DEL DESPLIEGUE DE LA FUNCIÓN DE LA CALIDAD PARA EL DISEÑO Y DESARROLLO DE UN SISTEMA DE ENVASE Y EMPAQUE PARA ARTESANÍAS
Authors: Lara Hernández Rafael , Ríos Ponce Juan , Conejo Magaña Gilberto Daniel , Albarrán Cruz Brenda Isamar
Published: July 2024

Las artesanías mexicanas son admiradas y valoradas en todo el mundo siendo algunas de ellas patrimonio cultural de la humanidad. Uno de los problemas que tienen los artesanos mexicanos es el empaque y embalaje, ya que no han profesionalizado este proceso fundamental para la exportación, pues evitan que las mercancías se dañen.
El envase, empaque y embalaje de las artesanías presentan un reto debido a la delicadeza de las figuras, la fragilidad de los materiales y el bajo margen de ganancia, por lo que se deben optimizar a fin de no incrementar el precio.
Para el desarrollo del envase, empaque y embalaje se utilizó el QFD con el fin de proponer un sistema eficiente partiendo de las necesidades de los artesanos.
El diseño de envases y empaques para la artesanía “Catrina” de Capula, Michoacán; se plantea como una necesidad para mejorar la presentación, facilitar su manejo, transporte, almacenaje, manipulación y distribución.
Actualmente, la industria cultural es del interés de muchas personas, organismos y gobiernos, ya que existe preocupación de que se pierdan los conocimientos ancestrales; siendo México un país con basta riqueza cultural existe el interés del gobierno por su conservación, así como del impacto que genera en la región.
Privacy-preserving machine learning with tensor networks
Authors: Pozas-Kerstjens Alejandro , Hernández-Santana Senaida , Pareja Monturiol José Ramón , Castrillón López Marco , Scarpa Giannicola , González-Guillén Carlos E. , Pérez-García David
Published: July 2024

Tensor networks, widely used for providing efficient representations of low-energy states of local quantum many-body systems, have been recently proposed as machine learning architectures which could present advantages with respect to traditional ones. In this work we show that tensor-network architectures have especially prospective properties for privacy-preserving machine learning, which is important in tasks such as the processing of medical records. First, we describe a new privacy vulnerability that is present in feedforward neural networks, illustrating it in synthetic and real-world datasets. Then, we develop well-defined conditions to guarantee robustness to such vulnerability, which involve the characterization of models equivalent under gauge symmetry. We rigorously prove that such conditions are satisfied by tensor-network architectures. In doing so, we define a novel canonical form for matrix product states, which has a high degree of regularity and fixes the residual gauge that is left in the canonical forms based on singular value decompositions. We supplement the analytical findings with practical examples where matrix product states are trained on datasets of medical records, which show large reductions on the probability of an attacker extracting information about the training dataset from the model's parameters. Given the growing expertise in training tensor-network architectures, these results imply that one may not have to be forced to make a choice between accuracy in prediction and ensuring the privacy of the information processed.