bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of the 4CL family in cassava and expression pattern analysis of the Me4CL32 gene
Authors: ran Fangfang , Wang Changyi , Zang Yuwei , Liu Liangwang , Wu Shuwen , Wang Congcong , Wang dayong , Min Yi 
Published: December 2023

Abstract

The 4-coumarate coenzyme A ligase (4CL) plays a critical role in the phenylpropane metabolic pathway and is a key enzyme in plant growth metabolism and stress responses. In this study, 50 Me4CLs were identified within the cassava genome utilizing bioinformatics methods, and a comprehensive analysis of the cassava 4CL gene family was conducted. The results showed that the 50 4CL proteins were divided into four subfamilies, and members within the same subfamily share similar or identical gene structures. Co-linearity analysis revealed that cassava and rubber trees have the highest number of homologous genes, indicating a close homologous relationship between them. Analysis of 15 cis-acting elements in the promoter region of Me4CL32 reveals the presence of hormone-responsive elements such as gibberellin, auxin, abscisic acid, and as well as elements related to meristematic tissue regulation. The results of quantitative real-time PCR (qRT-PCR) showed alterations in Me4CL32 gene expression in response to abiotic stressors (drought, salt, cold, heat) as well as GA3 and ABA hormonal stimuli, implying the capacity of Me4CL32 to react to both environmental pressures and hormone stimuli. The RNA-seq transcriptome and single-cell transcriptome were opted to analyze the expression pattern of Me4CLs. Additionally, the subcellular localization of the Me4CL32 demonstrated the confinement of the Me4CL32 protein within cassava leaf chloroplasts. Delving into the functionality of this gene family aids in comprehending the growth, development, and stress resistance mechanisms within plants. Furthermore, it furnishes a theoretical underpinning for future investigations concerning resilient cassava germplasm and the enhancement of cassava's environmental tolerance.
Investigation the role of Plasma-Activated Water Washing and Storage on the Shelf Life of Cestrum nocturnum L. (Night-Blooming Jasmine) Flowers
Authors: Vikas  , Kumar Sudhir 
Published: December 2023

Abstract
This study investigates the impact of Plasma-Activated Water (PAW) washing and storage on the shelf life of Night-Blooming Jasmine (NBJ) flowers (Cestrum nocturnum L.). NBJ flowers, known for their fragrant properties and diverse applications, have a short natural shelf life. PAW is generated using a pencil plasma jet with varying plasma treatment times (10 to 30 minutes) and is utilized for washing and storing NBJ flowers. The flowers undergo microbial analysis, sensory evaluation, weight loss assessment, spoilage evaluation, color analysis, and antioxidant activity measurement after PAW washing and storage.
PAW exhibits an increasing acidity and oxidative potential, along with a higher concentration of reactive species (NO3ˉ ions, NO2ˉ ions, H2O2, dissolved O3) with longer plasma treatment times. Washing NBJ flowers with PAW significantly reduces microbial growth, weight loss, and spoilage, maintaining better sensory properties compared to control-washed flowers. However, PAW, when used as a storage medium, negatively impacts the flowers, causing oxidative damage, compromised membrane integrity, and higher spoilage. PAW-washed NBJ flowers retain color intensity and delay browning while preserving antioxidant activity.
PAW, as a washing medium, proves effective in preserving the quality of flowers. Caution is advised when using PAW as a storage medium, as prolonged exposure leads to oxidative damage and compromises the overall quality of flowers. Further optimization of plasma treatment times is crucial for balancing the positive and negative effects of PAW on flower preservation.
Impact, coping, and Reciprocity: A Phenomenological Study on the Symbiotic Experience of Residents with and without Dementia Co-Living in Taiwan's Long-term Care Facilities
Authors: Fang Chan-Chuan , Liu Yi-Hsun , Huang Shu-He 
Published: December 2023

Abstract

Background: In Taiwan, residents with and without dementia mostly co-live in long-term care facilities. However, information on the symbiotic experiences of residents without dementia with behavioral and psychological symptoms of residents with dementia is lacking. This study explored the symbiotic experiences of residents without dementia co-living with those with dementia in long-term care facilities in Taiwan.
Methods: This study employed a phenomenological design. Semi-structured face-to-face interviews were conducted with 30 residents without dementia from three long-term care institutions in Taiwan. Colaizzi's data processing steps were used for analysis.
Results: Analysis of interview transcripts revealed the experiences of residents who lived with those with dementia were that of a “symbiosis.” Three core themes were found: “the impact of co-living,” “facing difficulties and coping,” and “companionship and reciprocity.”
Conclusion: This study showed that residents without dementia may be affected by the behavioral and psychiatric symptoms of residents with dementia when they co-live in long-term care facilities. However, there are positive and mutually beneficial interactions between them. By helping people with dementia in their daily lives, residents without dementia feel happy and accomplished and their self-worth is enhanced. By contrast, residents with dementia have more opportunities for social engagement and co-living interactions. These results can guide long-term care facilities without dementia special care units to support residents without dementia, reduce the interference of behavioral and psychiatric symptoms of residents with dementia, and promote mutual benefits. However, these findings warrant further investigation.
Dehydrocostus lactone from Echinops kebericho Mesfin synergizes the antibacterial effects of gentamicin and ciprofloxacin
Authors: Deyno Serawit , Bazira Joel , Makonnen Eyasu , Alele Paul E. 
Published: December 2023

Abstract
Background: Combination therapy is becoming an appealing solution to the emergence of antimicrobial resistance (AMR). This study investigated the combinatory effects of dehydrocostus lactone (DCL) and essential oil (EO) from Echinops kebericho when combined with selected standard antibacterial antibiotics.
Methods: The minimum inhibitory concentration (MIC) was determined using broth microdilution. Checkerboard analyses were used to determine the interactive effect. Eight serials, two-fold dilutions of conventional antibiotics and DCL/EO were prepared by diluting in broth. Dilutions of 50μl of antibiotic were dispensed in rows; while those of the EO/ DCL were dispensed in columns (1:1 v/v) of different concentrations ranging from 1/32 × MIC to 4 × MIC. In isobole analysis the EO/ DCL were combined with conventional antibiotics in nine different ratios. Isobolograms of the combination of DCL/EO with antibiotics were constructed.
Results:Out of a total of 90 different combinations evaluated, only five (5.55%) showed a synergistic effect; the majority (80%) showed no interaction, while 14.44% showed an additive effect. No antagonistic effect was observed in all combinations tested.
Beta-lactam antibiotics were non-interactive range of ΣFIC with DCL with the exception of a 3:7 DCL to penicillin combination with ∑FIC =1, in the additive range. All combinations of EO with selected beta-lactam antibiotics were in the non-interactive range. In this study, isobole analyses have shown the dependence of interactive effects on the ratio of combining agents. The DCL combination ratios of gentamicin or ciprofloxacin showed a synergistic effect.
Conclusion: Dehydrocostus lactone showed a synergistic effect against methicillin resistant Staphylococcus aureus (MRSA) when combined with ciprofloxacin or gentamicin. The observed synergistic effect could be useful for combating resistant strains. Further investigations are required on the mechanism of synergism and reversing resistance.
The Parallel Fuzzy C-Median Clustering Algorithm Using the Spark for the Big Data
Authors: Mallik Moksud Alam 
Published: December 2023

Abstract
Big data for sustainable development is a global issue due to the explosive growth of data and according to the forecasting of International Data Corporation(IDC), the amount of data in the world will double every 18 months, and the Global Data-sphere is expected to more than double in size from 2022 to 2026. The analysis, processing, and storing of big data is a challenging research concern due to data imperfection, massive data size, computational difficulty, and lengthy evaluation time. Clustering is a fundamental technique in data analysis and data mining, and it becomes particularly challenging when dealing with big data due to the sheer volume, velocity, and variety of the data. When the size of the data is exceedingly enormous, clustering has a scalability issue that causes it to utilize more memory and take longer to process data. Big Data frameworks like Hadoop MapReduce and Spark are potent tools that provide an effective way to analyze huge datasets that are being processed by the Hadoop cluster. But Hadoop reads and writes data from the Hadoop Distributed File System (HDFS) for each iteration, which consumes considerable time. Apache Spark is one of the most widely used large-scale data processing engines due to its speed, low latency in-memory computing, and powerful analytics. Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using the Spark for the Big Data that can handle large datasets while maintaining high accuracy and scalability. The algorithm employs a distance-based clustering approach to determine the similarity between data points and group them in combination with sampling and partitioning techniques. In the sampling phase, a representative subset of the dataset is selected, and in the partitioning phase, the data is partitioned into smaller subsets that can be clustered in parallel across multiple nodes. The suggested method, implemented in the Databricks cloud platform provides high clustering accuracy, as measured by clustering evaluation metrics such as the silhouette coefficient, cost function, partition index, and clustering entropy. The experimental results show that c = 5, which is consistent for cost function with the ideal silhouette coefficient of 1, is the optimal number of clusters for this dataset. For the validation of the proposed algorithm, a comparative study is done by implementing the other contemporary algorithms for the same dataset. The comparison analysis exhibits that our suggested approach outperforms the others, especially for computational time. The developed approach is the benchmarked with the existing methods such as MiniBatchKmeans, AffinityPropagation, SpectralClustering, Ward, OPTICS, and BRICH in terms of silhouette index and cost function.
Increasing Profitability and Confidence by using Interpretable Model for Investment Decisions
Authors: Arshad Sahar , Latif Seemab , Salman Ahmad , Irfan Saadia 
Published: December 2023

Abstract

Financial forecasting plays an important role in making informed decisions for financial stakeholders, specifically in the stock exchange market. In a traditional setting, investors commonly rely on the equity research department for valuable reports on market insights and investment recommendations. The equity research department, however, faces challenges in effectuating decision-making due to the demanding cognitive effort required for analyzing the inherently volatile nature of market dynamics. Furthermore, financial forecasting systems employed by analysts pose potential risks in terms of interpretability and gaining the trust of all stakeholders. This paper presents an interpretable decision-making model leveraging the SHAP-based explainability technique to forecast investment rec- ommendations. The proposed solution not only provides valuable insights into the factors that influence forecasted recommendations but also caters the investors of varying types, including those interested in daily and short-term investment opportunities. To ascertain the efficacy of the proposed model, a case study is devised that demonstrates a notable enhancement in investor’s portfolio value, employing our trading strategies. The results highlight the significance of incor- porating interpretability in forecasting models to boost stakeholders’ confidence and foster transparency in the stock exchange domain.
From Paychecks to Plates: Tracing the Impact of Layoffs on Food Access in the United States
Authors: Le Kiet , Nguyen Thanh , Rutledge Nina 
Published: December 2023

Abstract
The COVID-19 pandemic resulted in the numerous closures of businesses, caused widespread job losses, and negatively impacted the food security of US families. This study measures the extent to which food expenditure, food consumption, and the quality of food consumed by individuals were affected by layoffs. We estimated the treatment effect of involuntary job losses on these food security items using difference-in-difference regression, logistic regression, and augmented inverse propensity weighted estimation, and found that involuntary job losses caused Americans to be more vulnerable to food insecurity. Particularly, we found statistically significant evidence suggesting that layoffs caused people to eat less and switch to lower-quality food and unbalanced meals. The main purpose of this study is to shed light on the immediate economic implications of job loss on food security, which is having a ripple effect across public health, community development, and employment policies. We emphasize the importance of the social safety net and welfare programs that can provide immediate assistance to those who are directly impacted by layoffs.
Underwater Acoustic Target Recognition Using Spectrogram ROI Approximation with Mobilenet One-dimensional and Two-dimensional Networks
Authors: Akbarian Hassan , Sedaaghi Mohammad hosein 
Published: December 2023

Abstract

Underwater acoustic target recognition (UATR) in ship acoustic data poses significant challenges. Today, deep learning methods is widely employed to extract various types of information from underwater audio data. This paper explores the application of one-dimensional and two-dimensional convolution methods for detection. The raw acoustic data captured by hydrophones undergoes necessary pre-processing. Subsequently, regions of interest (ROI) that contain ship-emitted noise are extracted from spectrogram images. These regions are then fed into convolutional layers for model validation and classification. One-dimensional methods have faster processing time, but two-dimensional methods provide more accurate results. To significantly reduce the computational costs, in this paper, three effective algorithms based on deep learning for object detection are presented, which can be found by searching for the most informative features from the labeled data and then continuous training of the model of integration. New labeled samples with pre-labeled samples at each epoch will increase the accuracy of recognition and reduce losses. Through the combination of diverse pre-processing steps and modified deep learning methods, the proposed method achieves a recognition accuracy of 97.34% when tested on a dataset consisting of four types of ship-radiated noise. The method demonstrates superior performance compared to other deep learning methods.
Right Hypochondrial Abscess in a Middle-Aged Diabetic Woman: A Case Report
Authors: Jayte Mohamed 
Published: December 2023

Abstract
Introduction and importance:
Hypochondrial abscesses are rare intra-abdominal abscesses often diagnosed with computed tomography (CT). In resource-limited settings, ultrasound may be used instead.
Case Presentation:
A 52-year-old diabetic woman presented with abdominal pain and fever. Abdominal ultrasound showed a multiloculated abscess in the right hypochondrial region. She underwent ultrasound-guided percutaneous drainage and was treated with antibiotics as per culture sensitivity.
Clinical Discussion:
Hypochondrial abscesses are rare, accounting for only 1–4% of intra-abdominal abscesses. Risk factors include diverticulitis, appendicitis and diabetes mellitus. Ultrasound can accurately diagnose abscesses when CT is unavailable. Percutaneous drainage with subsequent antibiotics is the standard treatment approach.
Conclusion:
This case demonstrates that hypochondrial abscess can be diagnosed and managed with ultrasound guidance and percutaneous drainage when CT is unavailable, with excellent treatment outcome achieved.
Time Series Analysis of Groundwater-Quality Parameters of Tiruchirappalli District, Tamil Nadu
Authors: Lakshmi Y. Naga , Jenifer M. Annie , Jha Madan K. 
Published: December 2023

Abstract

Groundwater, an essential natural resource that plays a crucial role in sustaining life and supporting various socio-economic activities. The study area, Tiruchirappalli district located in Tamil Nadu, India, has experienced an increased demand for groundwater due to rapid growth in population, industrial development and urbanization. The present study focuses on identification of trends in the concentration of nine groundwater-quality parameters in the unconfined aquifers, across 11 blocks located in this district from 1980 to 2013. To achieve this, the analysis utilized three statistical trend tests namely Linear Regression Test (LR), Mann-Kendall test (MK) along with Sen’s slope estimator test and Innovative Trend Test (IT). The results revealed significant increasing trends in the concentrations of SO42-, Mg2+, Na+ EC, TH, Cl-, F- and NO3--N whereas significant decreasing trends were found in the concentration of Ca2+ in almost all parts of the district. Among the three tests, MK Test and LR Test has shown the similar trend at significance level (α = 5%) for all the parameters across the study area. However, the IT Test showed increasing or decreasing time series for the same groundwater-quality parameters, even in cases where the LR and MK tests did not show statistically significant trends. This indicates that the IT test is comparatively more sensitive to variations in the data as compared to LR and MK trend tests.
Issues related to qualification of the crime, provided for by Art. 166 of the Criminal Code of Ukraine, in decisions of the court of cassation
Authors: Zaytsev Oleksiy Volodymyrovych , Filipenko Valeriia Ruslanivna 
Published: December 2023

The paper is devoted to the issues related to qualification of a malicious failure to take care of a child or a person in respect of whom guardianship or custody is established (Art. 166 of the Criminal Code of Ukraine). Children have a right to a special care and assistance, a child needs to grow up in a family environment, in an atmosphere of happiness, love and understanding for his/her full and harmonious personality development. A duty of their care is imposed on their parents or persons in loco parentis, guardians (custodians). Commission of a crime of non-fulfillment of these duties is a quite common phenomenon in Ukraine. In order to determine the elements of this crime it is necessary to determine the maliciousness of the act and availability of severe consequences, which are caused by any omission of parents or persons in loco parentis. However, no specific types of consequences are prescribed by law; their availability or absence shall be established by the investigator, prosecutor and court in each specific case. This has led to different approaches in law enforcement practices that is accompanied by essential errors in qualification both at the beginning of criminal proceedings and during subsequent investigation.
The paper contains a critical comprehension of the legal opinions, contained in the decisions of the court of cassation (the Highest Specialized Court of Ukraine for Civil and Criminal cases, the Supreme Court of Ukraine, the Supreme Court) with regard to qualification of a malicious failure to take care of a child or a person in respect of whom guardianship or custody is established. Subject to the criminal law doctrine and law enforcement practices the author’s vision of the reasonableness of these findings and their importance in the criminal legal qualification of this crime is given.
General Principles of Criminal law Qualification of Smuggling of Timber or Sawn Timber
Authors: Pysmenskyi Yevhen Oleksandrovych 
Published: December 2023

The article is devoted to establishing the general principles of criminal law qualification of the offence under Article 201-1 of the Criminal Code of Ukraine, namely, transportation across the customs border of Ukraine outside the customs control or with concealment from customs control of timber or sawn timber of valuable and rare tree species, unprocessed timber, and other timber prohibited for export outside the customs territory of Ukraine (smuggling of timber or sawn timber).
The article deals with the issues related to the result of criminal law qualification of timber or sawn timber smuggling, and determination of the specifics of such qualification, if it is carried out officially. The attention is focused on recording the process and the result of criminal law qualification of timber or sawn timber smuggling, in the context of which the peculiarities of its substantiation, specification of the qualification formula and formulation of suspicion (accusation) are determined. It is analysed the grounds for criminal law qualification of timber or sawn timber smuggling. The recommendations on criminal law qualification are illustrated with examples from court practice.
The author distinguishes and characterises the types of criminal law qualification of the offence under Article 201-1 of the Criminal Code of Ukraine, depending on the specifics of the corpus delicti of a criminal offence, other criteria and taking into account the peculiarities of the initial stage of criminal procedure.
Based on the results of the research, it is drawn a conclusion about the general principles underlying the criminal law qualification of smuggling of timber or sawn timber. On this basis, the author formulates scientifically based recommendations aimed at ensuring effective application of Article 201-1 of the Criminal Code of Ukraine in the course of pre-trial investigation.
Evaluation of the hardness and wear behavior of date seed powder/epoxy composites as potential biomaterials
Authors: K. Hassan Mohamed , Assas Mohammd 
Published: December 2023

The date palm, or Phoenix dactylifera, is a crop that is grown for food and is used by many people on a regular basis. The cultivation of date palms, their processing, and consumer demand all produce tons of waste. Date palm seeds can account for up to 10 % of the total weight of the fruits. A topic of interest for research is the application of date seed waste in the fields of engineering, nutrition, and cosmetics. This work aims to show that epoxy/palm seed date composites are suitable for use as biomaterials by examining their wear behavior. Give a brief introduction to a few ideas before going over the fundamental idea of wear resistance. Future wear resistance improvements in biomedical applications and other industries that might benefit from this addition will continue to be achieved through the use of date palm seed microparticles in epoxy. In this study, epoxy composites containing palm seed particles are made by the mixing procedure. The studied composites made from date palm seed powder particles has micron particle size of 150 which is mixed with epoxy as a matrix. The percentages of date palm seeds are varying from 5 % to 20 %. The 20 percent sample had the best results, losing 7.03 percent of their starting weight. The 10 percent group, which lost 9.4 percent, the 15 percent group, which lost 12.2 percent, and the 5 percent sample, which lost 19.95 percent, were the next in line. Each of the four samples had 1 kg to 5 kg of weight applied to them at five different rotation speeds. Upon analysis of all the samples under investigation, it was discovered that the date palm seeds enhanced and increased wear resistance, leading to better outcomes.