bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intelligent Transportation Storage Condition Assessment System For Fruits and Vegetables Supply Chain Using Internet of Things Enabled Sensor Network
Authors: Kumar Saureng , Sharma S C 
Published: March 2024

Abstract

Efficient transportation of fruits and vegetables is crucial for proper storage, handling, and distribution directly influencing their quality, shelf life, and ultimately the price. Maintaining optimal storage conditions during the transport of fruits and vegetables is of utmost importance to preserve their freshness and quality. Therefore, there is a pressing need for a real-time assessment system that can ensure the highest quality and safety of fruits and vegetables throughout the supply chain network. This paper introduces an Internet of Things (IoT)-enabled sensor network designed to address these challenges. The sensors are strategically deployed within the storage containers that continuously assessing real-time critical environmental parameters, such as temperature, humidity, pH, and air quality. These parameters significantly affect the storage of fruits and vegetables throughout the supply chain network. Furthermore, we have employed machine learning algorithms, such as decision trees, k-nearest neighbors, logistic regression, and Support Vector Machine, to measure performance in terms of accuracy, F1-score, precision, sensitivity, and specificity. The results indicate that the Support Vector Machine algorithm outperforms with the other algorithms with an impressive accuracy of 98.05%. Future research endeavors will focus on optimizing food supply chain loss.
Transforming Agricultural Living Labs Into Lighthouses Contributing to Sustainable Development as Defined by the UN-SDGs.
Authors: Bouma Johan , Reijneveld Arjan , (BSc). Mark Geling , (BSc) Edwin Geling 
Published: March 2024

Abstract

The UN Sustainable Development Goals (SDGs) were intended to be met by 2030 but recent reviews show that this will not be achieved and recommendations are made to Heads of State, Governments, the International Community and Member States to strengthen their efforts. Focusing on agriculture, we argue that a bottom-up effort is also needed in Living Labs, truly involving farmers that are now confused and rebellious about topdown rules and regulations. To provide clarity, we suggest: (i) selection of key SDGs by considering the proportionality principle, and: (ii) defining ecosystem services in terms of indicators and thresholds for income, production of healthy food, protection of water quality, contribution to energy preservation and climate mitigation and life on land, including soil health (SDGs 1,2,3,6,7,13,15). Indicators and thresholds have to be clear and measurable at reasonable cost. Introduction of innovative sensing techniques allowed rapid generation of relevant soil data in a field of a Living Lab being studied. When meeting all thresholds, a “Lighthouse” is established acting as an inspiring example for farmers with similar soils in a given region. Policies should focus on achieving thresholds of a set of indicators rather than on topdown prescribing certain management measures.
Lived Experiences and Coping Strategies among Cancer Patients in the Volta Region of Ghana: A Health Facility-Based Qualitative Study
Authors: Bonsra Emmanuel Abu , Morrison Leslie Kwesi , Anderson Haddiyat Offeibea , Ananga Mark Kwame , Amu Hubert 
Published: March 2024

Abstract

Background
Cancer is a global health challenge, impacting millions of lives annually. In Ghana, like many other countries, cancer remains a significant public health concern. This qualitative study explored the lived experiences of cancer patients, their coping strategies, and the availability of mental services for cancer patients.
Methods
This was a qualitative exploratory study which recruited 11 cancer patients and two health professionals from the Ho Teaching Hospital using in-depth interview guides. Data collected were analysed thematically using Atlas Ti 7.5.7.
Results
Regarding the lived experiences of cancer patients, the study unveiled profound emotional impact of receiving a cancer diagnosis, leading to a sense of devastation, fear, and even suicidal ideation among patients. Ongoing emotional challenges, including persistent depression, treatment-induced stress, and constant anxiety were prevalent throughout the cancer journey. Coping strategies adopted by patients included seeking support from loved ones, immersing themselves in work and avoidance-focused coping mechanisms, such as isolation and denial. We found that while specialized mental health support was mainly lacking for many cancer patients, the role of nurses in providing emotional support was crucial.
Conclusion
Living with cancer presents profound emotional challenges. Our study underscores the need for comprehensive mental health support services tailored to the unique needs of cancer patients. By addressing barriers which include stigma, limited availability of services, and a shortage of mental health professionals, the country would be making enormous progress towards Sustainable Development Goals (SDGs), particularly SDG 3 and 10 for ‘Good Health and Well-being’ and ‘Reduced Inequalities.’
Effects of cutaneous leishmaniasis on patients' quality of life
Authors: Yizengaw Endalew , Nibret Endalkachew 
Published: March 2024

Abstract

Introduction: Cutaneous Leishmaniasis (CL) is caused by protozoan parasite called Leishmania. It is endemic in more than 100 countries globally. Despite its vast prevalence and impact on quality of life, it is one of the most neglected tropical dermatological diseases. The CL burden has often been expressed based on the physical disfigurement caused by the disease. However, considering the impact of the disease beyond physical impairment and changes in patients’ appearance would help to better understand the disease as a public health problem. The effect of CL on patients' quality of life was determined in this study.
Methods: The data that were related to quality of life were collected using Standard one-week Dermatology Life Quality Index (DLQI) questionnaire. The questions were categorized under seven domains: symptoms & feelings, daily activities, work and school, leisure, personal relationships, and treatment. Each question was scored on a three-point scale: Very much (3), A lot (2), A little (1), Undecided (0), and Not at all (0). The sum of the scores lied between 0 to 48. A higher score shows worse quality of life. The data were entered and analysed using Statistical Package for Social Science 23. Frequencies and proportions were used to describe the data. Differences were considered statistically significant at p < 0.05.
Results: The lives of the majority of CL patients (60.7%) were significantly affected by CL. The quality of life of patients was moderately impacted by CL in 25% of the CL patients. In 32.1% of the CL patients, the effect of CL on patients' quality of life was very large. The quality of one CL patient's life was extremely largely affected. The disease had a small effect on 32.1% of the CL patients. The domain related with personal relationships was the most affected domain followed by symptoms and feelings, treatment, and leisure.
Conclusion: The Dermatology Life Quality Index demonstrates that CL has a small to extremely very large negative effect on the quality of life of patients.
Parallel chart writing and resilience impact the narrative competence of medical staff: a cross-sectional study in China
Authors: Xu Yun , Guo Hongkai , Ge Guomei , Shu Jing , Liu Li , Jin Qi , Jia Junjun 
Published: March 2024

Abstract

Narrative competence is essential for building a good communication relationship between medical staffs and patients. It is a powerful instrument for the delivery of holistic healthcare. However, there is little research focusing on the influencing factors of narrative competence and the relationships among resilience, self-efficacy, and narrative competence. The aim of the study is to explore the influence factors of narrative competence of medical staff and confirm the relationships among self-efficacy, resilience and narrative competence. A cross-sectional survey was conducted among 606 medical staffs from two affiliated hospitals, from Zhejiang and Heilongjiang province, respectively. The participants were scored by the Chinese narrative competence scale, the brief Chinese version of the resilience scale, and the Chinese version of self-efficacy scale. Results showed that the score of narrative competence was 149.76 ± 28.70, including the scores of listening dimension (48.01 ± 9.36), understanding dimension (67.75 ± 13.55), and reflecting dimension (34.00 ± 6.77). High narrative competence score was associated with hospital location and parallel chart writing (p<0.01). Pearson correlation analysis showed resilience and self-efficacy were positive related to narrative competence.
The influence of pyrazinamide resistant associated gene mutations on multidrug-resistant mycobacterium tuberculosis in China
Authors: Zhang Yuzhen , Li Yifan , Liu Yao , Kong Xianglong , Li Huaichen , Wang Tingting , Li Yameng , Zhu Xuehan , An Qiqi , Han Qilin , Fang Weiwei , Li Yingying , Long Fei , Tao Ningning 
Published: March 2024

Abstract
Background
Pyrazinamide (PZA) is essential for the treatment of drug-susceptible and drug-resistant tuberculosis (TB), especially multidrug-resistant (MDR) TB, but the condition of PZA resistance (PZA-R) across China is unknown. Our aim is to clarify the genetic mutations of PZA-R and the relationship between PZA-R and MDR-TB in China, from 2007 to 2019.
Methods
A total of 3202 TB strains with gene sequences results in China were included, among which 1447 strains were sequenced and 1775 were download from the European Nucleic Acid Sequence Database. Drug resistance was investigated by detecting resistance-conferring mutations. A phylogenetic tree was constructed to illustrate the genetic structure of the TB strains. Fisher's exact or Pearson's chi-square tests, as well as logistic regression analysis were used for correlation analysis. Those were calculated by SPSS software.
Results
All the 3202 strains were divided into four lineages (L1, L2, L3, L4), most belonged to L2 (2745, 85.7%), followed by L4 (443, 13.8%), the rest L1 plus L3 (14, 0.4%). About 45.6% (n = 1459) strains referred to isoniazid resistance (INH-R), 43.4% (n = 1389) rifampicin resistance (RIF-R), and 40.5% (n = 1296) MDR. There were 591 isolates resistant to PZA, among which 96.1% (n = 568) were also MDR. The rate of PZA-R was 43.8% (568/1296) among MDR isolates. The trends of PZA-R fluctuated in accordance with the trends of MDR, INH-R, RIF-R during 2007–2019. Up to 254 kinds of mutations associated with PZA-R were found, with 16.5% (n = 42) isolates harboring ≥ 2 PZA-R associated mutations. Codons 11 (encoding pncA_c.011A > G, n = 30, 11.8%), 76 (encoding pncA_p.Thr76Pro, n = 13, 5.1%), and 139 (encoding pncA_p.Val139Leu, n = 13, 5.1%) were the top three PZA-R associated mutation sites. All PZA-R mutation sites accounting at least 1% were included to analyse the influence of PZA-R on other drug resistance (MDR, INH-R, RIF-R). Finally, three PZA-R related mutations (pncA_p.Val139Ala, pncA_p.Thr47Ala, pncA_p.Leu85Pro) were associated with MDR, four were associate with (pncA_p.Thr76Pro, pncA_p.Val139Ala, pncA_p.Thr47Ala, pncA_p.Leu85Pro) INH-R and none was associated with RIF-R.
Conclusion
PZA-R especially gene mutation referred to pncA region may promote MDR, this phenomenon mainly associated with the function of PZA-R on INH-R. It is important to consider PZA-R particularly the three associated mutations (pncA region associated mutations) into consideration in treating MDR-TB and explore its mechanism.
Predicting anastomotic leak in patients with esophageal squamous cell cancer treated with neoadjuvant chemoradiotherapy using a nomogram based on CT radiomic and clinicopathologic factors
Authors: Zhao Junfeng , Yang Guanli , Li Ying , Li Shanshan , Luo Haining , Han Dan , Li Baosheng , Cao Qiang 
Published: March 2024

Abstract
Background
Anastomotic leak (AL) is a common complication in patients with operable esophageal squamous cell carcinoma (ESCC) treated with neoadjuvant chemoradiotherapy (NCRT) and radical esophagectomy. Therefore, this study aimed to establish and validate a nomogram to predict the occurrence of AL.
Methods
Between March 2016 and December 2022, 231 eligible patients with ESCC who underwent NCRT and radical esophagectomy were divided into training (n = 159) and validation cohorts (n = 72). Clinicopathologic and radiomics characteristics were included in the univariate logistic regression analysis, and statistically significant factors were enrolled to develop the nomogram, which was evaluated by the area under the curve (AUC) of the receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA).
Results
Univariate and multivariate analyses revealed that dose at the anastomosis ≥ 24 Gy, gross tumor volume ≥ 60 cm3, postoperative albumin < 35 g/L, comorbidities, duration of surgery ≥ 270 mins, and computed tomography-based radiomics characteristics were independent predictors of AL. The nomogram AUC in the training and validation cohorts was 0.845 (95% confidence interval [CI]: 0.770–0.920) and 0.839 (95% CI: 0.718–0.960), respectively, indicating good discriminatory ability. The calibration curves showed good agreement between the predicted and actual AL occurrence and the DCA demonstrated favorable clinical outcomes.
Conclusions
We developed and validated a nomogram based on radiomics and clinicopathologic characteristics. This predictive model could be a powerful tool to predict AL occurrence in patients with ESCC treated with NCRT.
Molecular simulation study of adsorption-diffusion of CH4, CO2 and H2O in gas-fat coal
Authors: Jia Jinzhang , Xing Yinghuan , Li Bin , Wu Yumo , Wang Dongming 
Published: March 2024

Abstract

In order to clarify the microscopic dynamics mechanism of CH4, CO2 and H2O adsorption and diffusion in coal, and to reveal the mechanism of the influence of different temperatures and pressures on the adsorption and diffusion characteristics of coal adsorbed CH4, CO2 and H2O molecules. In this paper, the macromolecular structure model of Jixi gas-fat coal was constructed, based on the Giant Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) methods. The adsorption-diffusion characteristics of CH4,CO2 and H2O single-component gases in the gas-fat coal macromolecule model at temperatures ranging from 273.15K to 313.15K and pressures ranging from 0.01MPa to 15MPa were investigated by using Material Studio software. The research results indicated that: The adsorption of three gases, CH4, CO2 and H2O, increased with the increase of equilibrium pressure, and the adsorption isotherms conformed to Langmuir type I isotherms. The amount of saturated adsorption of CH4 ranged from 11.18 to 14.37ml/g, the saturated adsorption of CO2 ranged from 20.40 to 24.70ml/g, and the saturated adsorption of H2O ranged from 66.61 to 84.21ml/g. With the increase of temperature, the saturated adsorption of CH4 and CO2 both decreased, and the saturated adsorption of H2O firstly increased and then decreased, and the adsorption of H2O by low temperature and high temperature had both an inhibitory effect on the adsorption of H2O. The potential energy distributions of CH4, CO2 and H2O molecules are poisson distributed. The absolute values of the most available interaction energies are, from highest to lowest: H2O > CO2 > CH4; the activation energies for diffusion of CH4, CO2 and H2O are 12.20kJ/mol, 3.36kJ/mol, and 8.47kJ/mol, respectively, and the diffusion of CO2 is the more likely to occur. The adsorption of CH4 and CO2 in coal is physical adsorption, while the adsorption process of H2O molecules is beyond the scope of physical adsorption. The absolute value of the interaction energy is H2O > CO2 > CH4 in descending order.
The logic of coronavirus infection: revealing the heterogeneity of disease progression and treatment outcomes in COVID patients
Authors: Yu Guozhi , Huang Houhui 
Published: March 2024

Abstract

Pneumonia caused by coronavirus infection is a self-limiting disease. Its progression and prognosis are highly heterogeneous among people of different ages, genders, and living with different life styles. Such heterogeneity also exists in treatment outcomes of different patients. Various physiological and pathological factors, such as renewal of pulmonary cell, number of entry receptor and viral replication, have been identified linking to the development of the disease. However, it is still unclear how these factors collectively establish a causal relationship in the course of disease progression. In this study, we built a mechanistic model to explain the dynamics of infection and progression of coronavirus disease. We modeled how the interaction of pulmonary cells determine the dynamics of disease progression by characterizing the temporal dynamics of viral load, infected and health alveolar cells, and dysfuctional alveolar cells. The viral and cellular dynamics captured different stages of clinical manifestations in individual patient during disease progression: the incubation period, mild symptom period, and severe period. We further simulated clinical interference at different stages of disease progression. The results showed that some medical interventions show no improvement either in reducing the recovery rate nor shortening the recovery time. Our theoretical framework may provide a mechanistic explanation at the systems level for the progression and prognosis of coronavirus disease as well as other similar respiratory tract diseases.
Detecting Post-fire Burn Severity Level using Sentinel-2 and MODIS Satellite data
Authors: Shabbir Aqsa , Zia Sahar , Kazim Ali Hussain , Kasi Mumraiz , Jamshed Muhammad Ali , Waseem Liaqat Ali , Iqbal Naveed , Abbasi Qammer H , Ur-Rehman Masood 
Published: March 2024

Abstract

Background
Forest fires adversely affect forest ecosystem by altering its composition, structure, regeneration, and recovery potential of its landscape. The present study investigates forest fire hotspots and examines the relationship between these fire events and deforestation in Tehsil Dhansar, District Sherani, Balochistan. This study proposed a three-step research methodology to achieve its objectives. Firstly, it aims to assess the severity level of the forest burn resulting from the fire event. Secondly, it analyzes the extent of vegetation loss caused by the fire. Thirdly, the study identifies forest fire hotspots using Sentinel-2A images and MODIS Fire Radiative Power (FRP) data. The analysis involves utilizing Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), and Hot Spot Analysis (Getis-Ord Gi*) to gain comprehensive insights into the pre- and post-fire situation accurately. By defining classes, the study achieves a better understanding of the extent of burnt areas and vegetation loss.
Results
The findings show that 0.03% of Tehsil Dhansar is found to have low to medium burn severity levels during any forest fire event. It is also revealed that the forest remained dominant in the same region and frequency of occurrence of forest fire events is increasing by 1.6% with each passing year.
Conclusion
The current study's findings in the region famous for the world's oldest forest have significant potential for similar landscapes worldwide, primarily characterized by dry deciduous forests and juniper forests well adapted to arid and semi-arid environments. Given these findings, further studies in the same location should prioritize obtaining precise in-situ measurements to deepen our understanding of the situation.
Gastric Cancer Tumor Immune Microenvironment Landscape: Clinical Implications for Patient Outcome and Response to PD-1 Immune Checkpoint Blockade
Authors: Shah Manish , Sarkar Sandipto , Melikhova Daria , Thakkar Prashant , Kudryashova Olga , Shin Nara , Love Anna , Samarina Naira , Postovalova Ekaterina , Tychinin Dmitry , Podsvirova Svetlana , Degryse Sandrine , Bagaev Alexander , Zavodovskaya Marianna , Elboudwarej Emon , Frenkel Felix , Yantiss Rhonda , Betel Doron , Fowler Nathan 
Published: March 2024

Abstract
Although gastric cancer (GC) may be classified into molecular subtypes based on the TCGA1 or ACRG2 classification, the tumor immune microenvironment (TME) remains under-evaluated in both systems. Using unsupervised clustering of gene expression signatures that describe the TME composition and properties of malignant cells from an integrated collection of 11 public cohorts, we identified five TME-based GC subtypes: mesenchymal (Mes), fibrotic (F), immune-enriched (IE), B-cell inflamed (BI), and immune-depleted (D). The GC TME subtypes provide important clinical annotation and are prognostic for patient survival. Mes and F GC were both stroma-enriched, although Mes GC also demonstrated WNT activation. Both stromal subtypes carry the worst survival, whereas alternatively, IE GC featured enhanced immune infiltration and is associated with the best prognosis. Although BI GC also demonstrated increased immune infiltration, it was associated with increased B cell signatures. The D subtype exhibited a cold immune TME with strong malignant cell properties, and with BI, these TME subtypes have intermediate survival. Microsatellite instable (MSI) GC that was IE exhibited significantly better survival than MSI GC that was not IE. The GC TME subtypes were also predictive of immune checkpoint blockade response. These newly defined GC TME molecular clusters provide a novel framework to inform clinical practice.
Laboratory Assessment of the Effect of Rice Husk, Groundnut Shells and Rha on the Shear, Permeability and Consolidation of Clayey Sands
Authors: K.L. Maithili , M.S. Nagakumar 
Published: March 2024

Abstract
Utilizing waste materials to improve soil properties can result in cost savings and environmental benefits. This study aims to determine the effect of adding agricultural wastes like rice husk ash (RHA), rice husk (RH), and groundnut shells (GS) to clayey sands from Mysore district, India. The study focused on the undrained strength, permeability and volume change behaviour of soils mixed with RHA, RH and GS. The soil samples were mixed with varying amounts of RHA (5%, 10%, 15%, and 20% by weight) and RH-GS (1%, 2%, 3%, 4%, and 5% by weight) and cured for 1, 7, 14 and 21 days. These blended specimens were then used to determine the maximum dry density (MDD), optimum moisture content (OMC) and unconfined compressive strength (UCS). The soil mixture containing 5% RHA and 4% (RH + GS) yielded optimal results in the UCS test. Further tests, including unconsolidated undrained (UU) triaxial, permeability and consolidation tests, were conducted on the parent soil and the soil composite with 5% RHA and 4%(RH + GS). From the undrained test, the strength increased for the soil admixture, with a reduction in the cohesion and an increment in the friction angle, compared to that of the parent soil. The experimental results also showed improvement in the permeability and consolidation characteristics of the blended soil.