bluuebunny/crossref_metadata_2025 huggingface dataset:
Parameterized model for trace-element partitioning between apatite and silicate melt: effect of apatite/melt composition and temperature with implications for lunar basalts
Authors: Jirků Markéta , Špillar Václav , Fabbrizio Alessandro
Published: December 2023

We present new parameterized lattice strain models to predict the apatite/silicate melt partition coefficients of the rare earth elements (REE) and Y in natural magmatic systems as a function of temperature and melt composition with high accuracy and precision. We collected published experimental REE and Y partition coefficients for apatite coexisting with melt ranging from picrobasaltic to rhyolitic and phonolitic composition. Resulting dataset was analysed using the lattice strain model to assess the data quality. The three lattice strain parameters (D0, r0, and E) were subjected to a multivariate nonlinear least-squares analysis as a function of intensive variables, and we attempted to develop two independent models, on the basis of melt and apatite composition. In melt composition-based model, it was found that the D0 parameter increases with increasing melt polymerization as a proxy of which we have chosen the melt CaO. The D0 parameter is thus best expressed as a power law function of melt CaO. Through extensive search of the parameter space, the E and r0 variables were found to correlate strongly with linear combination of melt CaO, P2O5 and of reciprocal temperature, 1/T. Based on the apatite composition, we could not find any dependence of the partitioning parameters on compositional variables that would outperform solely a reciprocal temperature-based fit. The new parameterization was applied to predict REE and Y partition coefficients in lunar basalts and suggests that lunar apatite could only equilibrate with evolved melt at late stages of fractional crystallization.
Anthracnose changes the diversity and composition of rhizosphere soil microbial community in common vetch
Authors: Wang Qiong , Zhu Rui , Li Faxi , Li Yingde , Bai Meiting , Duan Tingyu
Published: December 2023

Anthracnose caused by Colletotrichum is an increasingly severe disease of common vetch that reduces plant yield and quality. In this study, the effects of anthracnose on the rhizosphere soil microbial community of common vetch were studied via high-throughput sequencing. The relationship among the rhizosphere soil microbes and soil properties were analyzed. Lower fungal diversity was observed in rhizosphere soils of diseased plants. Variations in relative abundance were observed in the fungal phyla Mortierellomycota and Glomeromycota and in the bacterial phyla Acidobacteria, Oxyphotobacteria, and Verrucomicrobia. Gammaproteobacteria and Deltaproteobacteria were significantly more abundant in the rhizosphere soil of healthy plant. The bacterial community in the rhizosphere soil of diseased plant was involved in the synthesis of amino acids (glycine, serine, threonine, alanine, aspartate, and glutamate). Results of a redundancy analysis (RDA) showed that Colletotrichum was negatively correlated with soil available potassium (AK) and the content of soil organic matter (SOC), however it was positively correlated with soil pH. The relative abundances of Bacillus showed a negative correlation with soil pH and a positive correlation with AK and SOC content. The present study demonstrated that anthracnose could affect the rhizosphere soil microbial communities in common vetch, and soil properties have a close relationship with the rhizosphere soil microbes of common vetch.
Breast Cancer Comorbidities Network Analysis: Break the Code with Optimum Community Detection Algorithms
Authors: Permana Angga A. , Yaputra Reynard M.
Published: December 2023

Breast cancer is a prominent global health concern, as the data from the International Agency for Research on Cancer (IARC) shows that breast cancer is the leading cancer type with new cases in 2020 and among the Top 5 cancer types with the most deaths. This research aims to discover the breast cancer comorbidity diseases community with community detection algorithms, evaluate them based on modularity and similarity, suggest the best semantic similarity measurement and the optimal threshold value, and validate the data of breast cancer comorbidities with several data from research papers. The Wang algorithm, with a threshold value of 0.5, is chosen to build the network. Leiden, Louvain, RBER Pots, RB Pots, and Walktrap are the best five community detection algorithms. Similarity measurements with the best three fitness functions (edges inside, scaled density, and size) suggest that the Leiden-Louvain algorithm and RBER Pots-RB Pots algorithm are two pairs of algorithms with similar results. Other similarity measurements with the V-measure heatmap suggest that Louvain-Leiden (0.99), RB Pots-Leiden (0.97), and RB Pots-RBER Pots (0.96) results are similar. Comorbidity is then evaluated using the best five community detection algorithms and four centrality algorithms. As a result, fourteen diseases are agreed upon by the best five community detection algorithms, five diseases are agreed upon by four algorithms, two diseases are agreed upon by three algorithms, a disease is agreed upon by two algorithms, and ten diseases are agreed upon by an algorithm.
“Nevertheless, it is still painful”: Use of Over-the-Counter analgesics, pain, stress, and HRQOL in Norwegian adolescents: a cross sectional study.
Authors: Skarstein Siv , Helseth Sølvi , Cvancarova Milada Smaastuen , Haraldstad Kristin , Rohde Gudrun , Mikkelsen Hilde Timenes , Grasaas Erik
Published: December 2023

Background
Approximately 20% of Norwegian adolescents are frequently using over-the-counter analgesics (OTCA). The WHO emphasizes the need for research to identify the key determinants of health problems in adolescence. Thus, our purpose is to study and describe pain, stress, and health-related quality-of-life (HRQOL) in Norwegian adolescents and investigate possible associations between these two variables upon high/low usage of OTCA.
Methods
This cross-sectional study included 315 adolescents (92 boys, 223 girls) with an average age of 14.1 years (13–15 years). All participants reported using OTCA. Weekly usage was categorized as high and less than weekly as low. Using a validated questionnaire, we explored the following variables: pain, as measured using the Brief Pain Inventory, stress (Perceived Stress Questionnaire) and HRQOL (KIDSSCREEN-27). Binary logistic regression models were conducted using SPSS software.
Results
Our descriptive findings revealed that high users of OTCA reported higher pain intensity of 3.4 (SD = 1.9) and perceived stress of 0.38 (SD = 0.18) than low users (2.5 (SD = 1.9) and 0.32 (SD = 0.16) respectively. OTCA high users reported lower average scores than low users across all HRQOL subscales. Binary logistic regression revealed 30% higher odds for higher levels of pain intensity (95% CI [1.11 to 1.51]) and 14 times higher odds of perceived stress (95% CI [1.03 to 204.) associated with being a high user of OTCA compared to a low user.
Conclusions
This study shows significant higher odds for experiencing pain and stress among adolescents using OTCA daily-to-weekly, compared to those seldom using such medicines. Health professionals should be aware of young people who have a high consumption of OTCA and investigate whether the use is related to pain or stress. This might be important in designing a personalized and appropriate intervention. Parents and caregivers have an important responsibility in supporting adolescents appropriate pain management. More observational and longitudinal studies are needed to understand predicative factors for adolescents OTCA usage.
Partitioned Problem Space (PaPS) Ensemble For Zero-day Intrusion Detection
Authors: Tiwary Priya , Madhubalan Akshayraj , Gautam Amit
Published: December 2023

The low cost and easy availability of cloud data storage have led to a massive increase in data being generated and stored for analytics, simultaneously amplifying challenges in data security. Detecting and stopping a data breach before it can cause any material damage and legal repercussions has become crucial. The volume and speed of data moving around the clouds make traditional intrusion detection systems ineffective. However, deep learning ensembles are a type of machine learning technique that combines the predictions of multiple deep learning models to produce a more accurate and reliable prediction. Particularly adept at identifying novel or sophisticated intrusions, these ensembles uncover patterns overlooked by individual models. In this work, we propose a novel partitioned problem space deep-learning ensemble approach wherein the base model’s problem space is constrained by limiting the number of classes and number of features visible to each during their training. The output probabilities of these base models are fed as input to the final meta-learner model along with a selective subset of important features. Our exper- imentation demonstrates that this ensemble approach outperforms known approaches in zero-day intrusion detection tasks. Our work aims to partition a complex problem space into smaller, more manageable sub-spaces. We propose a multi-stage deep learning ensemble model where base models are trained on a subset of classes and features, and their predictions are aggregated by a meta-learner model. This approach improves the model’s ability to generalize to unseen data, including zero-day attacks.
Associations between Body Mass Index (BMI) and Dyslipidemia: Results from the PERSIAN Guilan cohort study (PSCS)
Authors: Shahraz Jahangir , Joukar Farahnaz , Yeganeh Sara , Sheida Fateme , Maroufizadeh Saman , Baghaei Masood , Naghipour Mohammadreza , Mansour-Ghanaei Fariborz
Published: December 2023

Background: Given the high prevalence of obesity and its relationship with dyslipidemia, both as risk factors for cardiovascular diseases, this study was conducted with the aim of investigating the relationship between BMI and dyslipidemia in the Prospective Epidemiological Research Studies in Iran (PERSIAN) Guilan cohort study (PGCS) population.
Methods: In this cross-sectional study, demographic and biochemical data were collected from 10519 participants of the PGCS population aged 35-70 years in Some’e Sara County, Guilan, Iran. Participants were divided into two groups with and without dyslipidemia and were compared based on different levels of BMI. All data were analyzed using SPSS version 16 software with a significance level<0.05.
Results: The average age of the participants is 51.52 ± 8.90 years. The prevalence of dyslipidemia in all participants was equal to 75.8 %. Most of the people with dyslipidemia were in the age group of 45-54 years. Among those with dyslipidemia, 41.2 % and 35.5 % had overweight and obesity, respectively. Furthermore, individuals with dyslipidemia demonstrated higher proportions of women, employed individuals, rural residents, those with higher socio-economic status, elevated BMI, and lower levels of physical activity, (P<0.001). In the unadjusted model, there was a positive association between BMI and the prevalence of dyslipidemia (OR=1.09, 95% confidence interval (CI): 1.08-1.10), indicating that for one-unit increase in participants' BMI, the probability of having dyslipidemia increased by 9%, which was remained statistically significant even after adjusting (OR=1.07, 95% CI: 1.06-1.08) (P<0.001).
Conclusion: The risk of dyslipidemia increases in the group with high BMI and low physical activity compared to others. Therefore, weight loss should be recommended for all those with a high BMI. Also, community-based education would be helpful to increase public knowledge.
Effect of sodium pyruvate on inflammation, peroxidative damage, and energy metabolism in scalded wounds of diabetic rats
Authors: Meng Xiang-Xi , Mi Qian , He Ze , Sun Kui
Published: December 2023

Objective
The aim of our study was to determine the effect of sodium pyruvate solution on the healing, inflammation, peroxidative damage, and energy metabolism of deep second-degree scald wounds in diabetic rats.
Methods
Fifty male Sprague Dawley (SD) rats were randomly divided into the scald normal salinegroup(SN group), the diabetes scald normal saline group(DSN group), the diabetes scald low-dose sodium pyruvate group(DSL group), the diabetes scald medium-dose sodium pyruvate group(DSM group), the diabetes scald high-dose sodium pyruvategroup(DSH group). The diabetic rat model was replicated by intraperitoneal injection of streptozotocin (STZ), and after successful modelling, a 4 cm diameter deep second-degree wound was prepared on the back of the rat. Different doses of sodium pyruvate were administered by gavage in the sodium pyruvate groups, and equal amounts of normal saline were administered once a day in the SN and DSN group. At 1, 3, 7, 14 and 21d after scald, the wound healing rate, body weight and blood glucose level of rats were observed, and the levels of NAD+/NADH, malondialdehyde (MDA), superoxide dismutase (SOD), interleukin 6 (IL-6), and tumour necrosis factor alpha (TNF-α) were detected in the wound tissue by ELISA.
Results
Compared with SN group, the levels of blood glucose, MDA, IL-6, and TNF-α were significantly higher and the level of SOD was significantly lower from 1d post-injury, the body weight was significantly reduced and the level of NAD+/NADH was significantly lower from 3d post-injury, and the healing rate of wounds was significantly lower from 14d post-injury in DSN group; compared with DSN group, sodium pyruvate treatment improved the blood glucose level, increased the metabolic level, inhibited the inflammatory response and peroxidative damage in the wound tissue, and significantly increased the wound healing rate.
Conclusion
Sodium pyruvate can promotes healing of deep second-degree scald wound in diabetic rats and may play a role via inhibiting wound tissue inflammation, peroxidative damage, and improving energy metabolism
Enhanced upgrading of lignocellulosic substrates by coculture of Saccharomyces cerevisiae and Acinetobacter baylyi ADP1
Authors: Liu Changshuo , Choi Bohyun , Efimova Elena , Nygård Yvonne , Santala Suvi
Published: December 2023

Background: Lignocellulosic biomass as feedstock has a huge potential for biochemical production. Still, efficient utilization of hydrolysates derived from lignocellulose is challenged by their complex and heterogeneous composition and the presence of inhibitory compounds, such as furan aldehydes. Using microbial consortia where two specialized microbes complement each other could serve as a potential approach to improve the efficiency of lignocellulosic biomass upgrading.
Results: This study describes the simultaneous inhibitor detoxification and production of lactic acid and wax esters from a synthetic lignocellulosic hydrolysate by a defined coculture of engineered Saccharomyces cerevisiaeand Acinetobacter baylyi ADP1. A. baylyi ADP1 showed efficient bioconversion of furan aldehydes present in the hydrolysate, namely furfural and 5-hydroxymethyl furfural, and did not compete for substrates with S. cerevisiae, highlighting its potential as a coculture partner. Furthermore, the remaining carbon sources and byproducts of S. cerevisiae were directed to wax ester production by A. baylyi ADP1. The lactic acid productivity of S. cerevisiae was improved approximately 1.5-fold (to 0.41 ± 0.08 g/L/h) in the coculture with A. baylyi ADP1, compared to a monoculture of S. cerevisiae.
Conclusions: The coculture of yeast and bacteria was shown to improve the consumption of lignocellulosic substrates and the productivity of lactic acid from a synthetic lignocellulosic hydrolysate. The high detoxification capacity and the ability to produce high-value products by A. baylyi ADP1 demonstrates the strain to be a potential candidate for coculture to increase production efficiency and economics of S. cerevisiaefermentations.
Effect and Mechanism of Anlotinib on the Malignant Biological Behavior of Cisplatin-resistant Cells in Cervical Cancer
Authors: Xia Nana , Chen Siying , Li Yu , Yu， Minmin
Published: December 2023

Purpose
To explore the effect of anlotinib on the proliferation, apoptosis, migration and invasion of cisplatin-resistant cervical cancer cells and study the changes of gene transcriptome of cisplatin-resistant cervical cancer cell lines after intervention with anlotinib.
Materials and Methods
In this study, cisplatin was used to induce the establishment of a drug-resistant cervical cancer cell line Siha/DDP. Then we use CCK-8 test, cell cloning test, flow cytometry test and western blotting test to explore the effect of anlotinib on the proliferation and apoptosis of Siha/DDP cells. Cell scratch test and transwell test were used to explore the effect of anlotinib on the migration and invasion of Siha/DDP cells. Finally transcriptome sequencing was used to detect changes in the gene expression profile of Siha/DDP cells under the action of anlotinib.
Results
Compared with the control group, the anlotinib group was able to dose-dependently inhibit Siha/DDP cell proliferation, migration, and invasion and significantly inhibit Siha/DDP cell clone formation; it was also able to dose-dependently promote Siha/DDP cell apoptosis and block Siha/DDP cells in the G2/M phase. Anlotinib significantly upregulated Bax, P21, E-cadherin protein expression and significantly downregulated Bcl-2, CDK1 and CyclinB1, VEGF, MMP-9 protein and drug resistance-associated protein P-gp protein expression in Siha/DDP cells. The gene expression profile of Siha/DDP cells caused changes after treatment with anlotinib. SQLE, MSMO1, LSS, FDFT1 and HMGCS1 were obtained as key hub gene
Conclusion
Anlotinib can inhibit the proliferation, migration and invasion of Siha/DDP cells and promote their apoptosis. The gene expression profile of Siha/DDP cells was altered after treatment with anlotinib, causing differential expression of several genes including SQLE, MSMO1, LSS, FDFT1 and HMGCS1.
Bioinformatics Analysis Of Hub Genes And Pathways In Congenital Hypothyroidism
Authors: Shan Mingliang , Zhuo Xiumei , Sui Lili , Sun Ping , Liu Shiguo , Cui Zhaoqing
Published: December 2023

Background:
We have found hub genes and dysregulation pathways in congenital hypothyroidism (CH).
Methods:
We found the required samples from the GEO and UCSC Xena databases respectively. The limma and pheatmap packages in R were used for differential gene searching and volcano and heat map mapping. The R package was used to generate GO enrichment analysis plots. Protein interaction network analysis was performed on the dataset through the STRING website, and a confidence level of 0.4 was selected to obtain the protein interaction relationships, and the interaction relationship data were downloaded; First, the genes with the top 20 expressions were screened by R as the core gene set gene1, and secondly, the data were then imported into Cytoscape, manually delete the outlier data, and use the algorithm in cytoHubba to screen out the core gene set gene2, and finally take the intersection of the two parts of gene set gene1 and gene2 obtained earlier by using jvenn to the final hub genes were obtained. Subsequently, Cytoscape was used to map the co-expression network of hub genes with other genes. The WGCNA package in R was used to perform WGCNA analysis on the differential data, and the selected hub genes were tagged, and then Cytoscape was used to map the co-expression network of the hub genes with other genes.
Results:
We identified a total of 250 DEGs, of which 174 genes were up-regulated and 76 genes were down-regulated. GO enrichment analysis showed that CH DEGs were significantly enriched in the trans-Golgi network and the Golgi apparatus subcompartment. The PPI network of the hub DEG has 209 nodes and 257 edges.WGCNA analysis showed that most of the genes were clustered in three major modules and confirmed by experimental analysis that there were close interactions between the screened hub genes, which were all clustered in the same module (blue module).
Conclusion:
HSPB1, PABPC1, and APP - these three hub genes are closely associated with the occurrence of congenital hypothyroidism and may influence the synthesis and secretion of T3 and T4 by affecting the synthesis of proteins in the Golgi apparatus of thyroid cells.
Simulation of Self-Tuning Fuzzy PI Controller for Micro Hydro Power Plants, which are implemented in the Ethiopian Rural Land
Authors: Mengesha Daniel Arega
Published: December 2023

This article addresses the underdeveloped state of micro hydropower in Ethiopia and the absence of locally manufactured, low-cost frequency controllers. To overcome this, the research proposes a novel approach using a fuzzy logic controller in conjunction with a PI controller for precise frequency control in micro hydropower plants. The designed fuzzy logic-based system proves to be simple, cost-effective, and responsive, safeguarding the power system components during low flow rates by isolating loads. Ethiopia's abundance of irrigation dams and water resources offers a strategic opportunity for implementing micro hydropower plants with minimal investment and time, particularly on existing dams. This article emphasizes the significance of parameter variations in micro hydropower systems and employs a detailed dynamic model to develop a fuzzy logic controller. Simulation results demonstrate the superiority of the fuzzy controller over the traditional PI controller, exhibiting significantly reduced overshoot (0.9% for a 35% load change) and faster settling times (26.85s). Even under more challenging conditions, the fuzzy controller outperforms the PI controller, showcasing its efficiency across varying operating conditions. The findings underscore the potential of the proposed fuzzy controller in advancing affordable micro hydropower solutions for rural areas in Ethiopia.
Existence of non-unique neighbor-joining phylogenetic trees of microsatellite markers
Authors: Segura-Alabart Natàlia , Serratosa Francesc , Fernández Alberto
Published: December 2023

Background:
Neighbor-joining (NJ) is a distance-based method used to analyse and visualise data that generates a phylogenetic tree. It is found in a wide range of scientific research and is upstream of all areas of bioinformatics and computational biology. NJ's drawback is the generation of different binary phylogenetic trees if more than two clusters of elements have the same distance in any step of the phylogenetic tree generation process. We analyse the extent of this problem in a particular context: the clustering of microsatellite markers with NJ. For this purpose, we calculate the proportion of publications in the Scopus database in which more than one binary phylogenetic tree is possible.
Results:
We have observed that 13% of articles can produce more than one binary phylogenetic tree; thus, results shown in these articles would have to be deeply analysed or their conclusions revised. To illustrate the problem from a practical point of view, we have selected an example where more than one binary phylogenetic tree solution is possible.
Conclusion:
Articles that show only one phylogenetic tree, although NJ could generate several of them, are somewhat biased and hard to reproduce. The percentage of publications with non-unique NJ phylogenetic trees is large enough to be considered a general problem in our scientific community.
A Performance of Hardened Properties of GGBFS and Micro Silica-Based High-Strength Self- Compacting Concrete
Authors: M Naveen Kumar S , M M Rame Gowda
Published: December 2023

The building construction industry is continuously exploring innovative methods to advance the properties of concrete and ensure its durability and strength. Self-compacting concrete (SCC) has gained considerable attention due to its ability to flow and compact under its weight, resulting in reduced labour requirements and improved structural integrity. In present investigate the prediction of critical properties of self-compacting concrete using an artificial neural network approach (ANN), and the compressive and split tensile strength of SCC were predicted in the current study. The data from seven sets of a total of concrete samples and the experimentally generated data for self-compacting concrete were used in this study. ANNs are regarded as nonlinear statistical data modeling tools for identifying patterns or modeling complex interactions between inputs and outputs. Eight input parameters are employed in the current ANN model to forecast the compressive and split tensile strength of self-compacting concrete. Cement, M-sand, coarse aggregate, GGBS, Micro silica (MS), water, Super Plasticizer (SP), and Age (days) are among these materials in variable proportions. The concrete's compressive and split tensile strengths are both included in the single output parameter. The study covered the significance of various input parameters for utilizing neural networks to predict strengths at various ages. The compressive strength of SCC predicted by ANN is a perfect match with experimental data and extremely low Mean Square Errors (M.S.E.). Additionally, the ANN model's effectiveness is higher than that of multiple regression analysis (MRA).The ANN model has greater promise than the MRA model for creating an ideal mix percentage for predicting the compressive strength and split tensile strength of concrete without suffering a significant loss in material or time.
Decomposition and insect succession of pig and rabbit cadavers’ corpses buried in the northern Sudanese zone of Burkina Faso
Authors: Zongo David , Romba Rahim , Joseph Kinda  , Waongo Antoine , Drabo Samuel Fogné , Gnankine Olivier
Published: December 2023

Forensic entomology is a science that studies insects and other arthropods in relation to forensic investigations. This study aimed to examine the presence of insects on pig and rabbit carcasses buried at two different depths, 100 and 50 cm, respectively, along nine sampling dates to establish an insect succession database on buried cadavers in the north sudanian zone of Burkina Faso. In addition, we investigated whether environmental parameters influence both the decomposition of buried corpses and the abundance of insects. Nine pigs and nine rabbits were buried at 100 and 50 cm respectively, at two different sites. Carcasses were exhumed after 14, 28, 42, 56, 70, 84, 98, 112 and 126 days of burial, respectively. Approximately 668 larvae, pupae, cocoons and adults of insects were surveyed on the two substrates during the 2020 and 2021 study periods, divided into 5 main orders, Diptera, Coleoptera, Hymenoptera, Dermaptera and Orthoptera. Accarinae and a few spiders were also inventoried. Succession of insects varied with depth. No significant difference in soil temperature (P = 0.9; 0.12) between the 50 and 100 cm depths was observed. However, significant differences were observed between the temperatures of depths and ambient air (P = 2.3e-07; 0.00027). Necrophagous insects were more abundant on the pig substrate than the rabbit. Our data provided precious information in terms of assessing the postburial interval.
MisCaltral: Reducing Numeric Hallucinations of Mistral with Precision Numeric Calculation
Authors: Chen Shih-Wen , Hsu Hsien-Jung
Published: December 2023

This paper introduces MisCaltral, an innovative enhancement to the Mistral 7B large language model (LLM), which integrates an external numeric calculator to address the challenge of numerical precision. Traditional LLMs, including Mistral 7B, struggle with accurately processing numeric data, a limitation that significantly hampers their application in fields requiring exact numeric computations. MisCaltral overcomes this by leveraging a specialized calculator module for precise mathematical operations, synergizing linguistic understanding with numerical accuracy. Through extensive experiments, MisCaltral demonstrates a notable improvement in numeric calculation accuracy, particularly in complex financial scenarios, compared to the un-augmented Mistral model. The study not only highlights the enhanced numeric capabilities of MisCaltral but also discusses the broader implications of such integrations in real-world applications and future LLM development. This research marks a significant step forward in the evolution of LLMs, paving the way for more sophisticated and reliable AI models that can adeptly handle a blend of linguistic and numeric data.
Comparative Study on the Fresh & Hardened Properties of SCC with C&D Waste Recycled Aggregates
Authors: Sneha J , Thulasi Anju
Published: December 2023

The majority of the solid waste produced worldwide comes from construction and demolition (C&D) debris, which is then dumped in landfills. But there is a possibility of appropriately treating and reusing such waste as aggregate in new concrete. Self-Compacting Concrete (SCC) is a high- performance concrete mixture that flows under its own weight while yet exhibiting enough segregation resistance. C&D waste recycled coarse aggregates (RCA) use in SCC has the potential to lessen the cost and environmental impact of concrete. In order to test the impact of RCA on the characteristics of SCC, RCA is employed in the manufacturing of SCC in varied percentage replacements of natural coarse aggregate (NCA).
A Study on Frameworks for an Energy Efficient Wireless Sensor Network
Authors: Anand V J , Benita J
Published: December 2023

Wireless sensor networks (WSNs) have found substantial notice due their use in multi-disciplinary domains. Main constraints faced by these networks are availability of less memory space, limitation in the power supply and bandwidth available for communication. The problem of energy management in Wireless Sensor Networks is vital in the stationing of the nodes. The energy issue shall be classified in to three main areas: (i) conserving the energy; (ii) Sharing of energy resources; and (iii) energy-harvesting techniques. In the paper, a survey is performed on the main contributions in methods for Wireless sensor networks to achieve competency in energy management.
Exercise Trainer
Authors: Jayan Aleena , Godwin George U , Muhammed Juvail P , Saranya R
Published: December 2023

Frequent physical activities may significantly improve someone’s health and well-being, but if not done properly, they can also be useless and even dangerous. A frequent error committed by users might be inappropriate exercise posture, which results from the wrong form or posture. This study introduces Exercise Trainer, a system that analyses a user’s posture during exercise and offers tailored advice on how to improve form. The system collects motion data from users using an optical camera, assesses their posture, contrasts it with ideal postures, and then offers suggestions for improving their posture. The suggested model makes use of the TensorFlow MoveNet model, which forecasts 17 key points or coordinates of different body parts using the JSON file produced by TensorFlow.js. TensorFlow.js generates a JSON file that interfaces with the web application, enabling the system to provide the user with real- time feedback on the correctness of their workout posture. This feature makes sure that the user gets instant feedback so they may correct their form as needed while exercising.
Land Surveying Robot
Authors: Saji Anju , Shajahan Risana , Jose Judin , Paulose Suja , Sasi Nisha M , Babu Banjo C
Published: December 2023

A land survey is a detailed study or observation of a land, in detail it analyses the data’s in supporting of planning, designing and land surveying is also used to find out the property boundaries. This information’s are collected through continuous observations, field measuring or research of legal instruments. This paper discusses about land surveying using a robot. Here a robot is a used to calculate the area of land which is divided into subplots. In current scenario for calculating the area of the land the surveyor has to use different instruments to obtain the land measurements. We are designing these robots keeping in mind the current complexities in land surveying techniques. This robot will help in reducing the carrying of different tools for land surveying. The robot can be operated easily and consume less time for the calculating the area of a given plot. With the help of a camera module the navigation of the robot can be easily made. The proposed system can be give accurate value of area of particular land and can be easily implemented and operated. The information of the land survey can be obtained with the help of IoT.
Automated Paralysis Patient Assistant Glove
Authors: Arun Lija , Sumi M , Meera  , Krishnan Anjana , Sivadas Keerthana B , Mohan Namitha
Published: December 2023

The paper discusses the high incidence of paralysis in India and the challenges faced by individuals with mobility impairments. Paralysis is a condition where a person loses the ability to move a section of their body due to damage to the nervous system. Individuals with paralysis often require assistance in daily activities and may have difficulty communicating their needs effectively. The system aims to assist those who are partially paralysed or have other mobility impairments who have some mobility in their fingers or hands, through a wearable glove equipped with flex sensors, a voice processor, a speaker, and a GSM module. The glove enables patients to communicate their needs through voice commands and send text messages to their caregivers. The sensors in the glove detect the patient's movements, which are mapped to predetermined input data provided to the Arduino. Also, other sensors like temperature sensors and pulse sensors are embedded in the glove to monitor patients' health. This allows the patient to be self-sufficient and helps monitor their health efficiently even in the absence of a caregiver. The suggested method is straightforward and does not require sophisticated hardware setups or extensive software development.
Image Segmentation using Optimization Algorithm: A Survey
Authors: Paulose Suja , Vanitha D Veera
Published: December 2023

Image segmentation has proven to be an important step in the processing of images, computer vision algorithms, etc. It splits an image into different regions. This survey reviews major contributions in the healthcare l field using deep learning, including the common problems published over the last few years, and also explains the basics of deep learning concepts applicable to medical image segmentation. To solve current problems and improve the development of medical image segmentation problems, the Efficient Net Atrous convolutional encoder & and decoder can be used for segmentation in future research. Efficient Nets have much better accuracy & and efficiency than conv-Nets. The advantage of Efficient-Net is that it can balance the model's depth, width, and image resolution through composite coefficients.
Review on UHF RFID Tag Antenna
Authors: Shahanas K S , Sruthy R , Rahna K R , Sumi M , Harikrishnan A I
Published: December 2023

This paper presents a comprehensive review of ultra-high frequency (UHF) radio frequency identification (RFID) tag antennas. Due to multiple benefits, RFID technology has supplanted conventional methods of identification like barcodes, magnetic stripe cards, and smart cards. The size of the antenna plays a crucial role in determining the overall dimensions of the RFID tag, making antennas typically low profile and compact. It is acknowledged as an innovative approach for tracking because of its affordable price, passive wireless power transfer capabilities, versatility, and non-line-of-sight communication. UHF RFID tag antennas find widespread use in various applications such as supply chain management, asset tracking, and vehicle identification. The UHF antennas are favoured because they enable simultaneous detection of more tags, provide greater read ranges and faster reading rates, and necessitate fewer antennas than low frequency and high frequency antennas. Establishing the application requirements, choosing the ideal antenna design and substrate material, developing, and optimizing the antenna, manufacturing the antenna, and connecting the antenna to the RFID tag are all essential processes in implementing an UHF RFID tag antenna. This paper will cover the overview UHF RFID tag antenna, few applications, and its limitations.
Solar And Wind Powered Hybrid System for Electric Vehicles using MPPT
Authors: Mohan Aswathy Mariam , Nair Lekshmi R , Aiswarya S , Chandran Reena , Divya G
Published: December 2023

As the world's energy demand rises, the search for fossil fuels becomes more urgent. These fuels are not environmentally friendly and harm the environment. Due to a lack of fossil fuel supplies and harmful environmental effects, the usage of Non-conventional sources like solar energy and wind energy has become critical. Solar and wind energy are non- depletable natural resources that are increasingly popular. Solar and wind power have emerged as viable alternative energy sources due to their accessibility and ease of use, the combination of solar and wind energy has led to the development of a renewable energy system known as a Solar-Wind Hybrid Power System (SWHPS). This system harnesses the power generation capabilities of both solar and wind energy technologies. Optimized utilization of these natural resources is required to produce power in order to lessen the power demand on the conventional power producing industry. Solar-wind hybrid systems with MPPT are becoming increasingly popular as a sustainable and efficient solution for generating renewable energy. For maximal power transfer, the constant voltage approach is used. This approach should include a few critical aspects to improve its stability and efficiency.
Effect of Graphene Addition on Sisal-Glass Epoxy Composite
Authors: Sooraj S , Sankar S Hari , Krishnarjun K G , Das Dileep K
Published: December 2023

Natural fiber or synthetic fiber can be utilized separately as reinforcing fiber in traditional composites. Sisal is a natural fiber which possesses high strength to weight ratio, durability, ability to stretch in which they are primarily used in applications where the materials must withstand extreme environments such as aerospace, automotive industries. To enhance the natural fiber reinforced composite's (NFRC) mechanical qualities A sisal-glass hybrid composite made from graphene was created using woven glass fiber. Glass and sisal fibers serve as reinforcement materials, and epoxy L-12 serves as the matrix phase. The matrix is also injected together with reduced graphene oxide (rGO). Chemical processing was used to remove the cellulose from raw sisal fiber. The compositions used for the tests are (85% - 15%) with 0.5 weight percent, 1 weight percent, and 5 weight percent rGO added by compression moulding process. In order to assess the mechanical qualities, tests for impact, hardness, and thermal conductivity are performed.
A Study on the Fresh and Hardened Properties and Cost-Analysis of High-Volume Fly Ash Self-Compacting Concrete
Authors: Surendran Athira , Riyana M S
Published: December 2023

Concrete was prevailed in construction since ancient times. Over the years, numerous developments have been carried out to upgrade the concrete. One such development is Concrete that self-compacts and binds to itself is known as Self Compacting Concrete (SCC) and is used in areas where reinforcements are crowded and conventional compaction is difficult. However, the increased use of cement has led to a significant amount of CO2 emissions into the atmosphere. The cement manufacturing industry alone accounts for 5%-7% of global CO2 emissions. To reduce these emissions, pozzolanic materials can replace cement in concrete. By employing fly ash (FA) in SCC is common because it enhances the ability to flow. To further reduce the carbon footprint from cement production, High-Volume Fly Ash Self Compacting Concrete (HVFA SCC) uses more than 30% FA in place of cement. This increases the durability of concrete by reducing chloride penetration but reduces compressive strength. The addition of FA increases the rheology too. The work aims in understanding the rheological and hardened state behaviour of HVFA SCC and comparing the cost of construction of HVFA SCC with Normal concrete.
XANTHOGRANULOME JUVENILE SIMULANT UN HYGROMA DU COUDE : A PROPOS DUN CAS ET REVUE DE LA LITTERATURE
Authors:   Universite Mohamed V, Laboratoire Danatomie Pathologique, CHU Ibn Sina, Rabat, Maroc., Benbella Leila , Sassi Samia ,   Universite Mohamed V, Laboratoire Danatomie Pathologique, CHU Ibn Sina, Rabat, Maroc., Lamalmi Najat ,   Universite Mohamed V, Laboratoire Danatomie Pathologique, CHU Ibn Sina, Rabat, Maroc.
Published: December 2023

Juvenile xanthogranuloma is a non-Langerhansian histiocytosis that is clinically manifested by a yellowish nodule. The objective of this work is to discuss the anatomo-clinical aspects of this condition and its differential diagnoses. We report the case of a 38-year-old patient with juxta-articular swelling of the elbow clinically simulating hygroma. Xanthogranuloma is a benign, self-involutive form of non-Langerhansian histiocytosis that appears early in life. Diagnosis is usually clinical in the most typical forms. In other cases, histological analysis is necessary to support the diagnosis by the demonstration of a dense dermal infiltrate delimiting foamy histiocytes mixed with very characteristic Touton giant cells. The differential diagnosis is made with the other etiologies of histiocytic proliferations namely langerhansian histiocytosis, papularxanthoma and dermato fibroid hence the interest of carrying out an immunohistochemical supplement before retaining the histological diagnosis of xanthogranuloma. To conclude, the diagnosis of juvenile xanthogranuloma is often clinical in the most typical forms. In other cases, histological study is essential to support the diagnosis. The immunohistochemical study, as well as the comparison with clinical and paraclinical data are of great help in eliminating differential diagnoses.
RISK FACTORS OF ACUTE RESPIRATORY INFECTION AMONG UNDER FIVE CHILDREN IN RURAL COMMUNITY OF NORTH DELHI
Authors:   Ph. DScholar, College of Nursing, Swami Rama Himalayan University, Dehradun, Uttarakhand, India., Bajwan Deepika , Prakash Kamli ,   Professor, College of Nursing, SwamiRama Himalayan University Dehradun, Uttarakhand, India., Semwal Jayanti ,   Professor, Dept of CommunityHealth Medicine, SwamiRama Himalayan University Dehradun, Uttarakhand, India., Pugazhendi Sanchita ,   Professor, College of Nursing, Swami Rama Himalayan University Dehradun, Uttarakhand, India.
Published: December 2023

Introduction: Children are mankinds seeds for the future and God given gift or hope. They deserve the almost care from us. Children are as a clay material. Acute respiratory infection (ARI) is a serious public health issue especially in developing nations like India where the majority of people are impoverished, live in slums and exposed to deadly diseases. Children under the age of five are particularly vulnerable to infection at an early stage. So, for the maintenance of best healthy status of children and identification of risk factors of acute respiratory infection among under five children is essential. Aim:To explore risk factors of acute respiratory infection among under five children in rural community of NorthDelhi region Methodology:An exploratory research design was adopted for this study. A total 430 one to five years age of children were selected with the help of consecutive sampling technique in randomly selected villages of North Delhi region. Semi structured interview schedulewas used for data collection. Results: The prevalence of acute respiratory infection was 35% (150 out of 430 children). It was identified that preterm delivery, Low birth weight, birth order of children, overcrowding in the house, indoor smoking, smoky fuel used for cooking, house location near by dusty main road, open drainage system, Family history of respiratory infection leading to cause of occurrence of ARI among children. Conclusion: Multivariate factors are responsible for acute respiratory infection among children which can be modified to prevent morbidity and mortality rate of under five children due to acute respiratory infection.
PEOPLE WITH INTELLECTUAL DISABILITIES-AN APPROACH TOWARDS MANAGEMENT ISSUES
Authors:   Associate Professor in Mental Health Nursing Department, Indian Nursing Council, M.M. College of Nursing, Maharishi Markandeshwar (Deemed to be University), Mullana-Ambala, Haryana, India., a Sonia , Sarju Devi Sarungbam ,   Associate Professor in Medical Surgical Nursing Department, Indian Nursing Council, M.M. College of Nursing, Maharishi Markandeshwar (Deemed to be University), Mullana-Ambala, Haryana, India.
Published: December 2023

Intellectual disability (ID), formerly known as mental retardation is a disability of intellectual functioning and adaptive behavior that arises during the period of time from conception to the beginning of adulthood. With ID, the individual has significant limitations in both intellectual ability and adaptive behavior, which are manifest before the age of 18. People with intellectual disability have varying degrees of impairment, classified from mild to profound. Every person who has intellectual disability is a unique individual and as such they face many barriers when it comes to school, relationships, and daily living. Supporting individuals in need of Mental Health Care and fostering a relationship with them are ways to embrace diversity in communities.
EXPLORING THE SOCIAL MEDIA LANDSCAPE OF NURSING STUDENTS: A DESCRIPTIVE ANALYSIS OF SOCIAL MEDIA ADDICTION AT SMT. NAGARATHNAMMA COLLEGE OF NURSING, BENGALURU
Authors: Malagi Vasantha , Nanjappan Devi , Hussain Noorul , Nitik Onimang , Sah Pinky , Maity Paramita , Biswas Priya , Mathew John Praisen
Published: December 2023

Social media addiction has become a growing concern worldwide, affecting individual across various age groups and professions. The nursing students, being digitally connected and frequently engaged with social media platforms, are not exempt from the potential risks associated with excessive social media use. In research findings, approximately 36% of Indian adolescents and 28.3% of nursing students in Mangalore, India, showed symptoms or signs of social media addiction, according to surveys conducted by AIIMS in 2021 and by Nandini and Nayak in 2019, respectively. This study aimed to assess the prevalence of social media addiction among nursing students in Smt. Nagarathnamma College of Nursing. Materials and Methods: A convenient sampling technique was employed to collect data from 256 nursing students enrolled in a nursing college. The participants were provided with a standardized questionnaire (social networking addiction scale) to assess their level of social media addiction. The questionnaire included items that assessed various dimensions of social media addiction, such as salience, mood modification, tolerance, withdrawal, conflict, and relapse. Results: The analysis of the collected data revealed that 40% (104) of the nursing students exhibited symptoms of social media addiction, while 60% (152) did not show addiction towards social media. These results indicate a considerable propotion of social media addiction among nursing students in the nursing college under study. Conclusions: The findings of this study highlight the significance of addressing social media addiction among nursing students. The high prevalence of addiction indicates the need for preventive measures and interventions to promote healthy social media use and mitigate the potential negative consequences on academic performance and mental well- being.