bluuebunny/crossref_metadata_2025 huggingface dataset:
Macrophage Migration Inhibitory Factor (MIF) suppresses mitophagy through disturbing the protein interaction of PINK1-Parkin in sepsis-associated acute kidney injury
Authors: Peng Zhiyong , Li Tianlong , Qu Jiachen , Hu Chang , Pang Jingjing , Qian Yaoyao , Li Yi-Ming
Published: December 2023

Renal tubular epithelial cells (RTECs) injury foreboded the occurrence and development of sepsis-associated acute kidney injury (SA-AKI). Recent studies of mitochondria have demonstrated that mitophagy was an indispensable physiological function of alleviating RTECs injury. Mitophagy was suppressed progressively by the inflammation response in SA-AKI. However, the mechanism of inflammation modulating mitophagy remains poor understood. We investigated the role of macrophage migration inhibitory factor (MIF, a pro-inflammation protein) in the PINK1-Parkin pathway of mitophagy through identifying the protein-protein interactions under the condition of inhibiting or over-expressing MIF. Unexpectedly, increasing MIF directly bound with PINK1 and disturbed the interaction of PINK1 and Parkin, which restrained the Parkin recruitment to mitochondria and the occurrence of mitophagy. Furthermore, this effect caused severe RTECs apoptosis, but which could be reversed by a MIF inhibitor ISO-1 or/and a new mitophagy activator T0467. These findings identified a critical renodamaged effect of MIF on disturbing the interaction of PINK1-Parkin and a therapeutic effect of ISO-1 and T0467 on protecting against SA-AKI. This study provided a novel insight of treating SA-AKI through targeting MIF and mitophagy.
Identification of stripe rust resistance gene YrBDT in Chinese landrace wheat Baidatou using BSE-seq and BSR-seq
Authors: Wu Jingchun , Cheng Yukun , Hao Weihao , Bai Bin , Fu Luping , Ren Yan , Hao Yuanfeng , Wang Fengju , Lin Ruiming , Si Hongqi , Ma Chuanxi , He Zhonghu , Xia Xianchun , Chen Jiansheng , Chen Can
Published: December 2023

Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is a devastating foliar disease of wheat. Chinese landrace wheat Baidatou has shown high resistance to a broad spectrum of Pst races at both the seedling and adult-plant stages for decades in the Longnan region of Gansu province, a hotspot for stripe rust epidemics. Here, we report fine mapping and candidate gene analysis of stripe rust resistance gene YrBDT in Baidatou. Analysis of F1, F2 plants and F2:3 lines indicated that resistance in Baidatou to Pst race CYR31 was conferred by a single dominant gene, temporarily designated YrBDT. Bulked segregant exome capture sequencing (BSE-seq) analysis revealed 61 high-confidence polymorphic SNPs concentrated in a 5.4 Mb interval at the distal of chromosome arm 6DS. Several SNPs and InDels were also identified by genome mining of DNA sampled from the parents and contrasting bulks. The YrBDT locus was finally mapped to a 943.6 kb (4,658,322–5,601,880 bp) genomic region spanned by markers STS2 and STS3 based on IWGSC RefSeq v2.1, including five putative disease resistance genes. There was high collinearity of the target interval among Chinese Spring RefSeq v2.1, Ae. tauschii AL8/78 and Fielder genomes. The expression level of TraesCS6D03G0027300 showed significant association with Pst infection, and a gene-specific marker CAPS3 developed from TraesCS6D03G0027300 co-segregated with YrBDT suggesting this gene as a candidate of YrBDT. The resistance gene and flanking markers can be used in marker-assisted selection for improvement of stripe rust resistance.
The feasibility of an online intergenerational co-parenting program for mother-father- grandmother triad on the intergenerational co-parenting relationship in the perinatal period: a pilot Randomized Controlled Trial
Authors: XIAO XIAO , LEUNG Doris Y.P. , NGAI Fei-wan , Zhu Shening , Chen Siqi
Published: December 2023

Aims To assess the effectiveness of an online intergenerational co-parenting program on intergenerational co-parenting families during the perinatal period.
Methods This was a pilot randomized controlled trial. A convenience sample of 60 intergenerational co-parenting family units, including 60 first-time parents and 60 grandmothers was recruited from the obstetric clinic in the study hospital. The recruited families were randomly assigned to the intervention (n=30) or control group (n=30). Participants in the intervention group received the online intergenerational co-parenting program in addition to usual care, including three weekly antenatal sessions and two weekly postnatal sessions.
Results The intervention did not find significant differences on the observed outcomes between the two groups. Some negative effects were found on mother reported intergenerational co-parenting relationship with their mother-in-law and their parenting satisfaction, but some positive effects were found on the depressive symptoms of mothers both at 6 weeks postpartum (Vargha and Delaney's A =0.65) and 3 months postpartum (Vargha and Delaney's A =0.56). It could protect the decline of mother-reported co-parenting relationships with their husband (Cohen’s d=0.12) and was also helpful to reduce mothers’ parenting stress (Cohen’s d=0.14). The intervention could also improve the parenting self-efficacy of mothers with a moderate effect size (Cohen’s d=0.36).
Conclusion The program found some negative effects on the intergenerational co-parenting relationship between mothers and grandmothers and mothers’ parenting satisfaction, the intervention may reduce the depressive symptoms, parenting stress of mothers, benefit their parenting self-efficacy and co-parenting relationship between couples.
A dynamic subset of network interactions underlies tuning to natural movements in marmoset sensorimotor cortex
Authors: Hatsopoulos Nicholas , Moore Dalton , MacLean Jason , Walker Jeffrey
Published: December 2023

Mechanisms of computation in sensorimotor cortex must be flexible and robust to support skilled motor behavior. Patterns of neuronal coactivity emerge as a result of computational processes. Pairwise spike-time statistical relationships, across the population, can be summarized as a functional network (FN) which retains single-unit properties. We record populations of single-unit neural activity in forelimb sensorimotor cortex during prey-capture and spontaneous behavior and use an encoding model incorporating kinematic trajectories and network features to predict single-unit activity during forelimb movements. The contribution of network features depends on structured connectivity within strongly connected functional groups. We identify a context-specific functional group that is highly tuned to kinematics and reorganizes its connectivity between spontaneous and prey-capture movements. In the remaining context-invariant group, interactions are comparatively stable across behaviors and units are less tuned to kinematics. This suggests different roles in producing natural forelimb movements and contextualizes single-unit tuning properties within population dynamics.
Association between watching eating broadcast “Mukbang and Cookbang” and body mass index status in South Korean adolescents
Authors: Park Sang-yeon , Eom Jeongha , Choi Sangyoun , Kim Jinhyun , Park Eun-Cheol
Published: December 2023

Background
It has been suggested that Mukbang and Cookbang, a type of eating broadcast originating from Korea and gaining popularity, may contribute to obesity. However, despite suggestions that Mukbang might contribute to obesity, studies investigating the impact of watching Mukbang on obesity is lacking. The goal of this study is to analyze the relationship between watching Mukbang and Cookbang and body mass index (BMI) status in Korean adolescents.
Methods
This study utilized data from the 2022 Korea Youth Risk Behavior Web-based Surveys. Participants reported the frequency of watching Mukbang and Cookbang per week over the previous 12 months. BMI was categorized into four subgroups based on percentiles: underweight (< 5th percentile), normal (5th − 85th percentiles), overweight (85th − 95th percentiles), and obese (> 95th percentile). This study used multinomial logistic regression for analysis.
Results
The likelihood of being obese was significantly higher in Mukbang-watching boys compared to those who never watched Mukbang and Cookbang (adjusted odds ratio [aOR]: 1.22, 95% confidence interval [CI]: 1.12–1.32). A dose-dependent association was found between the frequency of Mukbang and Cookbang watching and the likelihood of obesity among boys (p-for-trend < 0.0001). Subgroups that currently smoke, currently drink alcohol, frequently consume fast food, or drink sweetened beverages showed significantly higher odds of being obese in the “Ever” group than those in the “Never” group.
Conclusion
This study found a relationship between watching Mukbang and Cookbang and obesity in boys. Appropriate interventions should be considered for boys watching Mukbang and Cookbang.
A Real-Time PCB Defect Detection Model Based on Enhanced Semantic Information Fusion
Authors: Ji Tangyu , Zhao Qian , An Kang , Liu Dandan , Yu Wentao , Liang Shuang
Published: December 2023

Aiming at the problem of poor balance between real-time and performance of existing PCB board defect detection algorithms, this paper proposes a fast PCB board detection model based on enhanced semantic information fusion, i.e., the Ghost-YOLOv8 (G-YOLOv8) model. GhostConv is used for feature extraction in the backbone network part, which reduces the complexity of network operation; the SPPFCSPCS structure is proposed and applied to the deepest layer of the backbone network to strengthen the model’s fusion ability for deep multi-scale semantic information. In addition, after the feature fusion large-scale detection head, the low parameter number A 2 attention mechanism is added to improve the model’s attention to high-dimensional valid semantic information and optimize the detection results of the network; the Wise-IoU loss function is used for iteration in the training process to strengthen the model’s fitting ability. The experimental results show that the G-YOLOv8 model can detect up to 125FPS on the Peking University open-source PCB board defect detection dataset and Deep PCB dataset, which is an improvement of 1.5FPS compared to the pre-improvement period; and the mAP0.5 on the Deep PCB dataset improves by 0.8%. The performance and detection speed balance of the network has been improved.
Balancing the books of nature: Accounting for ecosystem condition following ecological restoration
Authors: Parkhurst Tina , Standish Rachel , Prober Suzanne , Kobryn Halina , Vardon Michael
Published: December 2023

Ecological restoration is critical for recovering biodiversity, functionality, and resilience of degraded ecosystems. Global restoration targets have been set to ensure that 30% of all degraded ecosystems are under effective restoration by 2030. Natural Capital Accounting (NCA) quantifies the biophysical and socioeconomic characteristics of ecosystems. As humanity faces pressing sustainability challenges and increasing environmental degradation, NCA can potentially assist public and private-sector decision-makers to catalogue effects of restoration interventions to drive investment, improvement to practice, and ultimately, to better protect the Earth's ecosystems. To test its suitability, we populated the leading global NCA framework with ecological data to quantify changes in ecosystem condition after restoration. We found that in principle, NCA is fit for purpose, however, requires methodological refinements and ecological expertise to capture restoration outcomes. These tweaks will facilitate adoption and standardisation of reporting as efforts ramp up to meet ambitious global restoration targets by 2030.
Malaysian Patient Perspectives on Clinical Trial Participation: Willingness, Knowledge, Perceptions, Confidence, and Religious Barriers
Authors: King Teck Long , Tan Shirin H , Tan Shirley SN , Lai Wei Hong , Bujang Mohamad Adam , Voon Pei Jye
Published: December 2023

Despite the expanding landscape of clinical trials, there is a lack of study concerning Malaysian patients’ participation and perspectives. This study addresses these gaps by assessing patients’ willingness, knowledge, perceptions, confidence, and religious barriers related to clinical trial participations in a clinical trial hospital in Malaysia. We conducted a cross-sectional survey at Sarawak General Hospital from March to September 2022, encompassing 763 cancer and non-cancer patients. We collected patients’ responses and calculated scores for domains such as willingness to participate (40.5/100), clinical trial knowledge (29.9/100), perceived benefits (66.5/100) and risks (72.4/100) of participations, confidence in clinical trial conducts (66.3/100), and religious barriers (49.8/100). Cancer patient demonstrated significantly greater willingness for trials involving new drugs (scores: 31.9/100 vs 27.4/100, p = 0.021) but slightly higher religious barriers compared to non-cancer cohort (scores: 51.4/100 vs 48.3/100, p = 0.006). Multivariable logistic regression identified female gender, unemployment, poor knowledge, low perceived benefits, high perceived risks, and low confidence as significant factors negatively associated with willingness to participate in clinical trials (p < 0.05). This study underscores the challenges in engaging Malaysian patients in clinical trials, emphasising the need for targeted strategies to raise awareness, effective communication on benefits and risks, and enhancing public confidence to promote clinical trial participation.
Comparison of quality of working life of nurses of Covid-19 and non-Covid-19 wards
Authors: Shamsi Afzal , ghaderi musab , Sadrmomtaz Fatemeh
Published: December 2023

Background
The aim of this study was to determine and compare the quality of work-life (QOWL) of nurses of Covid-19 and non-Covid-19 wards.
Methods
This cross-sectional study performed on 400nurses in 2022. The subjects were first selected by multi-stage random sampling method and within the clusters by a purposeful method including 2groups (Covid-19 wards, non-Covid-19 wards). Data were collected using the Walton Demographic and QOWL Questionnaire. Data-analysis was performed using SPSS-v23 software; descriptive and inferential statistical tests.
Results
The score of all subscales of QOWL in the group working in Covid-19 wards was lower than non-Covid-19 wards. The lowest scores of subscales in both groups were related to the dimension of "safe and healthy work environment" (p < 0.001).
Conclusions
The QOWL of Covid-19 wards nurses are lower than those of non-Covid-19 wards. Therefore, planning is needed to improve the QOWL of nurses, especially those working in Covid-19 wards.
A sex-structured mathematical model of mosquito infection with Microsporidia MB: model reduction and release strategies
Authors: Temfack Dhorasso , Tsanou Berge , Lubuma Jean , Diaby Mouhamadou
Published: December 2023

Malaria remains a significant public health burden in Sub-Saharan African countries, hindering their development. A promising strategy to combat this disease involves the use of the bacterium Microsporidia MB to reduce/replace disease-transmitting wild mosquito population. In this paper, we develop a dynamic model to analyze the transmission dynamics of Microsporidia MB within the wild mosquito population, considering both imperfect maternal and horizontal transmissions. We calculate the basic reproduction rate (R0 ) of the model to assess the invasive potential of Microsporidia MB-infected mosquito in the wild population. By establishing conditions for the local stability of equilibrium points based on the level of maternal transmission, we gain insights into the control of Microsporidia MB spread. Simplifying the model to a 2-dimensional system, we formulate and solve an optimal control problem that involves releasing infected mosquitoes to replace the wild population or achieve mosquito coexistence with sufficiently reduced wild mosquito population. Through theoretical analysis and numerical simulations, our findings contribute to the understanding and development of effective strategies for malaria control using Microsporidia MB.
Diet quality in young adulthood and sleep at midlife: a prospective analysis in the Bogalusa Heart Study
Authors: Potts Kaitlin S. , Gustat Jeanette , Wallace Maeve , Ley Sylvia , Qi Lu , Bazzano Lydia A.
Published: December 2023

Background
Diet and sleep are both established risk factors for cardiometabolic diseases. Prior evidence suggests a potential link between these behaviors, though evidence for how they associate with each is scarce. This study aimed to determine the association between diet quality in young adulthood and multiple sleep outcomes at midlife in the Bogalusa Heart Study (BHS).
Methods
This prospective study included 593 BHS subjects with dietary assessment at the 2001–2002 visit and sleep questionnaire responses from the 2013–2016 visit, after an average of 12.7 years (baseline mean age: 36 years, 36% male, 70%/30% White and Black persons). A culturally tailored, validated food frequency questionnaire assessed usual diet. Diet quality was measured with the Alternate Healthy Eating Index (AHEI) 2010, the Healthy Eating Index (HEI) 2015, and the alternate Mediterranean (aMed) dietary score. Robust Poisson regression with log-link function estimated risk ratios (RR) for insomnia symptoms, high sleep apnea score, and having a healthy sleep pattern by quintile and per standard deviation (SD) increase in dietary patterns. Models adjusted for potential confounders including multi-level socioeconomic factors, depression, and body mass index. Trends across quintiles and effect modification by sex, race, and education were tested.
Results
Higher diet quality in young adulthood, measured by both AHEI and HEI, was associated with lower risk of having insomnia symptoms at midlife. In the adjusted model, each SD-increase in AHEI (7.8 points; 7% of score range) conferred 15% lower risk of insomnia symptoms at follow-up (RR [95% confidence interval CI]: 0.85 [0.77, 0.93]), those in Q5 of AHEI had 0.54 times the risk as those in Q1 (95% CI: 0.39, 0.75), and there was a significant decreasing risk trend across quintiles (trend p = 0.001). There were no significant associations between young adult diet quality and having a high sleep apnea risk or a healthy sleep pattern at follow-up.
Conclusions
A healthy diet was associated with a lower risk of future insomnia symptoms. If replicated, these findings could have implications for chronic disease prevention strategies incorporating the lifestyle behaviors of sleep and diet.
Extended cluster-based network modeling for coherent structures in turbulent flows
Authors: Colanera Antonio , Reumschüssel Johann Moritz , Beuth Jan Paul , Chiatto Matteo , de Luca Luigi , Oberleithner Kilian
Published: December 2023

This study introduces the Extended Cluster-based Network Modeling (eCNM), a methodology to analyze complex fluid flows. The eCNM focuses on characterizing dynamics within specific subspaces or subsets of variables, providing valuable insights into complex flow phenomena. The effectiveness of the eCNM is demonstrated on a swirl flame in unforced conditions, characterized by a precessing vortex core (PVC), using synchronized data from PIV measurements, UV-images filtered around the OH* chemiluminescence wavelength, featuring the heat release rate distribution, and pressure signals from jet inlet probes.The analysis starts with choosing the distance metric for the coarse-graining process and the number of clusters of the model. This has been pursued by designing a filtered distance metric based on the filtered correlation matrix and minimizing the Bayesian information criterion (BIC) score, balancing the goodness of the fit of a model with its complexity. The standard cluster-based network model on the velocity fluctuations allowed for determining the characteristic frequency of the PVC. The construction of extended cluster centroids of the heat release rate reveals a rotating flame pattern, predominantly localized within regions influenced by PVC's vortices roll-up. Spatial subdomain analysis is carried out, demonstrating the benefits of focusing on specific regions of interest within the fluid system and providing significant computational savings. Furthermore, eCNM allows for the handling of different sampling frequencies among datasets. Leveraging high-resolution pressure measurements as a reference dataset and velocity components as undersampled data, extended cluster centroids for velocity are successfully estimated, even when the velocity sampling frequency is artificially reduced. This study showcases the adaptability and robustness of eCNM as a valuable tool for comprehending and analyzing coherent structures in complex fluid flows.
Structural insights into RNA cleavage by a novel family of bacterial RNases
Authors: Wu Ruoxi , Barnes Sarah A. , Dahlin Heather R. , Khamrui Susmita , Ingle Shakti , Xiang Yufei , Shi Yi , Bechhofer David H. , Lazarus Michael B.
Published: December 2023

Processing of RNA is a key regulatory mechanism for all living systems. We recently discovered a novel family of endoribonucleases that is conserved across all bacteria. Here, using crystallography, cryo-EM microscopy, biochemical, biophysical, and mass spectrometry techniques, we are able to shed light on a novel RNA cleavage mechanism in bacteria. We show that YicC, the prototypical member of this family, forms a hexameric channel that closes down on a 26-mer RNA substrate, and find that it cleaves across an RNA hairpin to generate several short fragments.
Quantum implementation of the guided image filtering algorithm
Authors: Mu Jiale , Li Xiao-Fei , Zhang Xiang-Hua , Wang Pinghe
Published: December 2023

Image filtering involves the application of window operations that perform valuable functions, such as noise removal, image enhancement, high dynamic range (HDR) compression, and so on. Guided image filtering is a new type of explicit image filter with multiple advantages. Here, we report a quantum implementation of guided image filtering algorithm, based on the novel enhanced quantum representation (NEQR) model, and the corresponding quantum circuit has been designed. We find the quality of filtering is consistent with that of the classical one and the time complexity is reduced exponentially from $O(2^{2q})$ to $O(q^2)$ due to the quantization.
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

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

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

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

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

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

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

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

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

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

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.
The Impact of Foreign Direct Investment from the Nordic Countries on the Structure of Lithuania’s Economy
Authors: Tvaronaviciene Manuela , Simelyte Agne , Stirblyte Gerda
Published: December 2023

Foreign direct investment is considered a driving force for economic growth, boosting trade and reducing unemployment. The recipient country benefits from technology transfer. The host economy develops and changes its economic structure. The Baltic states, including Lithuania, attracted high volumes of Nordic FDI. The aim of the study is to evaluate the impact of inwards Nordic FDI on the economic structure of Lithuania. The research employed descriptive statistics, correlation regression and the Granger causality test. The stationarity of the data was checked by the augmented Dickey–Fuller test to evaluate the impact on the structural changes. The sectors were divided into primary, secondary and tertiary. The data have been structured according to the economic activities corresponding to the Nomenclature statistique des activités économiques dans la Communauté européenne (NACE) classification of economic activities in the European Union. The primary sector includes agriculture, forestry and mining. The secondary factors included manufacturing, construction, water and electricity supply, tertiary cover services and trade. Furthermore, for our research, we chose GDP per capita and gross value added (GVA). The GVA was chosen to evaluate the impact of each Nordic country’s FDI on different sectors. The sectoral contribution to the economy is expressed as GVA. This research was performed from three perspectives. The first is focused on the analysis of the flows and distribution of FDI in Lithuania by economic sector in the Nordic countries. Furthermore, we have analysed the impact of foreign direct investment in the Nordic countries on Lithuania’s economic growth. The final subsection is devoted to estimating the causal link between the distribution of FDI by economic sector in the Nordic European countries and the causal link between economic indicators in these sectors. Our study contributes to internationalization theory by extending it from a sectoral angle. In particular, the need to understand the impact of FDI from a single country on the host economy and its economic structure should be emphasized. We claim that inwards FDI might change the economic structure of the host economy in a positive or negative way. In addition, FDI should contribute to the economic advancement of host countries, which means that the tertiary sector should expand. The results of our study might be useful for improving FDI promotion policy in Lithuania while seeking long-term results in the expansion of the tertiary sector, especially knowledge-intensive activities. Main conclusion. We can conclude that Lithuania has the potential to benefit from inwards Nordic FDI; however, it still does not take all the advantages of these opportunities, as some FDI has no impact on the expansion of the tertiary sector or any sector at all.
Anti-crisis Management Mechanism in the Digital Age
Authors: Gavkalova Nataliia , Akimova Liudmyla , Akimov Oleksandr
Published: December 2023

This paper conducts a comprehensive theoretical exploration of the anti-crisis management mechanism within the context of local governance, with a specific focus on the integration of digital solutions. Theoretical underpinnings of “crisis” and “anti-crisis management” are expounded upon and synthesized, defining “crisis” as a transformative process that marks a pivotal juncture in system development, entailing irreversible changes. “Anti-crisis management” is considered a multifaceted concept encompassing systemic, process-oriented, and mechanistic dimensions. The examination of local-level crisis phenomena underscores the imperative for effective anti-crisis management aimed at stabilizing regional conditions and devising strategies to mitigate crisis risks. In this context, local-level anti-crisis management is characterized as “a comprehensive system of measures for diagnosing, preventing, neutralizing, and surmounting regional crises”. To inform strategic decision-making for anti-crisis management, an in-depth analysis of local budget revenues and expenditures is conducted, serving as the foundation for judicious tool selection in crisis mitigation. Emphasizing a critical assessment of core concepts and the intricacies of anti-crisis management mechanisms, the paper delineates key objectives for its implementation at the regional level. With regional development as the focal point of anti-crisis management, this paper explores the applicability of digital tools for crisis regulation. However, these findings underscore the paramount importance of tailoring these mechanisms to the unique characteristics and latent potential of each region. The paper concludes with a comprehensive assessment of the efficacy of city budget fund utilization and proposes an approach to optimize the allocation and structure of local budget expenditures by incorporating digital elements to enhance decision-making and crisis response.
Interspecific Hybrid Rootstocks Improve Productivity of Tomato Grown under High-temperature Stress
Authors: Hashem Ahmed , Bayoumi Yousry , El-Zawily Abd El-Shafik , Tester Mark , Rakha Mohamed
Published: December 2023

Grafting can be a useful technology to improve productivity of vegetable crops, including tomato, particularly under the serious challenges of climate change for agricultural systems. This study aimed to evaluate the impact of some local tomato interspecific hybrid rootstocks along with Maxifort on the vegetative growth, productivity, and fruit quality of tomato under field production conditions. Heat-tolerant tomato hybrid 023 F1 was used as a scion over the two late summer seasons of 2021 and 2022. Grafting 023 F1 onto Maxifort or KFS-16 rootstocks resulted in the maximum plant growth. Similarly, Maxifort and KFS-16 rootstocks significantly increased the fruit setting percentage from 22.2% to 23.5% and 17.8% to 24.6%, total fruit yield from 33.5% to 53.7% and 29.6% to 51.6%, and marketable yields from 34.1% to 56.0% and 27.3% to 56.7%, respectively, during both seasons compared with nongrafted plants. These two rootstocks enhanced nutrient (nitrogen, phosphorus, potassium) uptake compared with nongrafted planted. However, grafting with the interspecific hybrid rootstocks (KFS-8 and KWS-9) significantly decreased the content of catalase, peroxidase, and proline, which might be associated with lower plant vigor and yield in these rootstocks. All rootstocks had an impact on fruit chemical composition; however, generally, Maxifort and KFS-16 had greater contents of vitamin C, β-carotene, and total antioxidants than nongrafted plants. KFS-16 had also greater lycopene content than nongrafted plants. These results demonstrate the potential use of Maxifort and local rootstock KFS-16 to boost the growth and yield of tomato plants under high-temperature stress in the late summer season.