bluuebunny/crossref_metadata_2025 huggingface dataset:
How to assess the accuracy of volume conduction models? A validation study with stereotactic EEG data
Authors: Piastra Maria Carla , Oostenveld Robert , Homölle Simon , Han Biao , Chen Qi , Oostendorp Thom
Published: February 2024

Introduction

Volume conduction models of the human head are used in various neuroscience fields, such as for source reconstruction in EEG and MEG, and for modeling the effects of brain stimulation. Numerous studies have quantified the accuracy and sensitivity of volume conduction models by analyzing the effects of the geometrical and electrical features of the head model, the sensor model, the source model, and the numerical method. Most studies are based on simulations as it is hard to obtain sufficiently detailed measurements to compare to models. The recording of stereotactic EEG during electric stimulation mapping provides an opportunity for such empirical validation.

Methods

In the study presented here, we used the potential distribution of volume-conducted artifacts that are due to cortical stimulation to evaluate the accuracy of finite element method (FEM) volume conduction models. We adopted a widely used strategy for numerical comparison, i.e., we fixed the geometrical description of the head model and the mathematical method to perform simulations, and we gradually altered the head models, by increasing the level of detail of the conductivity profile. We compared the simulated potentials at different levels of refinement with the measured potentials in three epilepsy patients.

Results

Our results show that increasing the level of detail of the volume conduction head model only marginally improves the accuracy of the simulated potentials when compared to in-vivo sEEG measurements. The mismatch between measured and simulated potentials is, throughout all patients and models, maximally 40 microvolts (i.e., 10% relative error) in 80% of the stimulation-recording combination pairs and it is modulated by the distance between recording and stimulating electrodes.

Discussion

Our study suggests that commonly used strategies used to validate volume conduction models based solely on simulations might give an overly optimistic idea about volume conduction model accuracy. We recommend more empirical validations to be performed to identify those factors in volume conduction models that have the highest impact on the accuracy of simulated potentials. We share the dataset to allow researchers to further investigate the mismatch between measurements and FEM models and to contribute to improving volume conduction models.
Therapeutic biomarkers in acute myeloid leukemia: functional and genomic approaches
Authors: Bhatia Karanpreet , Sandhu Vedant , Wong Mei Hsuan , Iyer Prasad , Bhatt Shruti
Published: February 2024

Acute myeloid leukemia (AML) is clinically and genetically a heterogeneous disease characterized by clonal expansion of abnormal hematopoietic progenitors. Genomic approaches to precision medicine have been implemented to direct targeted therapy for subgroups of AML patients, for instance, IDH inhibitors for IDH1/2 mutated patients, and FLT3 inhibitors with FLT3 mutated patients. While next generation sequencing for genetic mutations has improved treatment outcomes, only a fraction of AML patients benefit due to the low prevalence of actionable targets. In recent years, the adoption of newer functional technologies for quantitative phenotypic analysis and patient-derived avatar models has strengthened the potential for generalized functional precision medicine approach. However, functional approach requires robust standardization for multiple variables such as functional parameters, time of drug exposure and drug concentration for making in vitro predictions. In this review, we first summarize genomic and functional therapeutic biomarkers adopted for AML therapy, followed by challenges associated with these approaches, and finally, the future strategies to enhance the implementation of precision medicine.
Exploration of potential biomarkers for early bladder cancer based on urine proteomics
Authors: Zhou Xu , Xue Fei , Li Tingmiao , Xue Jiangshan , Yue Siqi , Zhao Shujie , Lu Hezhen , He Chengyan
Published: February 2024

Background

Bladder cancer is a common malignant tumor of the urinary system. The progression of the condition is associated with a poor prognosis, so it is necessary to identify new biomarkers to improve the diagnostic rate of bladder cancer.

Methods

In this study, 338 urine samples (144 bladder cancer, 123 healthy control, 32 cystitis, and 39 upper urinary tract cancer samples) were collected, among which 238 samples (discovery group) were analyzed by LC−MS. The urinary proteome characteristics of each group were compared with those of bladder cancer, and the differential proteins were defined by bioinformatics analysis. The pathways and functional enrichments were annotated. The selected proteins with the highest AUC score were used to construct a diagnostic panel. One hundred samples (validation group) were used to test the effect of the panel by ELISA.

Results

Compared with the healthy control, cystitis and upper urinary tract cancer samples, the number of differential proteins in the bladder cancer samples was 325, 158 and 473, respectively. The differentially expressed proteins were mainly related to lipid metabolism and iron metabolism and were involved in the proliferation, metabolism and necrosis of bladder cancer cells. The AUC of the panel of APOL1 and ITIH3 was 0.96 in the discovery group. ELISA detection showed an AUC of 0.92 in the validation group.

Conclusion

This study showed that urinary proteins can reflect the pathophysiological changes in bladder cancer and that important molecules can be used as biomarkers for bladder cancer screening. These findings will benefit the application of the urine proteome in clinical research.
Comparison of machine learning models to predict the risk of breast cancer-related lymphedema among breast cancer survivors: a cross-sectional study in China
Authors: Du Jiali , Yang Jing , Yang Qing , Zhang Xin , Yuan Ling , Fu Bing
Published: February 2024

Objective

The aim of this study was to develop and validate a series of breast cancer-related lymphoedema risk prediction models using machine learning algorithms for early identification of high-risk individuals to reduce the incidence of postoperative breast cancer lymphoedema.

Methods

This was a retrospective study conducted from January 2012 to July 2022 in a tertiary oncology hospital. Subsequent to the collection of clinical data, variables with predictive capacity for breast cancer-related lymphoedema (BCRL) were subjected to scrutiny utilizing the Least Absolute Shrinkage and Selection Operator (LASSO) technique. The entire dataset underwent a randomized partition into training and test subsets, adhering to a 7:3 distribution. Nine classification models were developed, and the model performance was evaluated based on accuracy, sensitivity, specificity, recall, precision, F-score, and area under curve (AUC) of the ROC curve. Ultimately, the selection of the optimal model hinged upon the AUC value. Grid search and 10-fold cross-validation was used to determine the best parameter setting for each algorithm.

Results

A total of 670 patients were investigated, of which 469 were in the modeling group and 201 in the validation group. A total of 174 had BCRL (25.97%). The LASSO regression model screened for the 13 features most valuable in predicting BCRL. The range of each metric in the test set for the nine models was, in order: accuracy (0.75–0.84), sensitivity (0.50–0.79), specificity (0.79–0.93), recall (0.50–0.79), precision (0.51–0.70), F score (0.56–0.69), and AUC value (0.71–0.87). Overall, LR achieved the best performance in terms of accuracy (0.81), precision (0.60), sensitivity (0.79), specificity (0.82), recall (0.79), F-score (0.68), and AUC value (0.87) for predicting BCRL.

Conclusion

The study established that the constructed logistic regression (LR) model exhibits a more favorable amalgamation of accuracy, sensitivity, specificity, recall, and AUC value. This configuration adeptly discerns patients who are at an elevated risk of BCRL. Consequently, this precise identification equips nurses with the means to undertake timely and tailored interventions, thus averting the onset of BCRL.
A bibliometric analysis of literatures on uterine leiomyosarcoma in the last 20 years
Authors: Huang Jinhua , Chen Yu , Li Ziyin , Chen Mimi , Huang Dingwen , Zhu Peixin , Han Xintong , Zheng Yi , Chen Xiaochun , Yu Zhiying
Published: February 2024

Background

Uterine leiomyosarcoma(uLMS) is a rare malignant tumor with low clinical specificity and poor prognosis.There are many studies related to uLMS, however, there is still a lack of metrological analyses with generalization. This study provides a bibliometric study of uLMS.

Methods and materials

We chose the Web of Science (WoS) as our main database due to its extensive interdisciplinary coverage. We specifically focused on the literature from the last 20 years to ensure relevance and practicality. By utilizing the WOS core dataset and leveraging the R package “bibliometric version 4.1.0” and Citespace, we performed a comprehensive bibliometric analysis. This allowed us to pinpoint research hotspots and create visual representations, resulting in the retrieval of 2489 pertinent articles.

Results

This literature review covers 2489 articles on uterine leiomyosarcoma (uLMS) from the past 20 years. Key findings include an average annual publication rate of 8.75, with a 6.07% yearly growth rate and an average citation count of 17.22. Core+Zone 2 sources contributed 1079 articles and 207 reviews, displaying a 4.98% annual growth rate. The analysis identified top journals, influential authors, and core sources, such as the prevalence of publications from the United States and the dominance of GYNECOLOGIC ONCOLOGY and HENSLEY ML. Bradford’s Law and Lotka’s Law highlighted core sources and author productivity, respectively. Thematic mapping and factorial analysis revealed research clusters, including etiology, diagnosis, treatment advancements, and surgical approaches, with prominent themes such as gemcitabine and docetaxel. Overall, this comprehensive analysis provides insights into uLMS literature trends and influential factors.

Conclusion

This thorough bibliometric analysis, in its whole, illuminates the field’s guiding principles while also revealing the subtle patterns within the uLMS literature. The knowledge gained here contributes to the current discussion in uLMS and related scientific fields and provides a solid basis for future research paths.
Could sex-specific subtypes of hand osteoarthritis exist? A retrospective study in women presenting to secondary care
Authors: Gulati Malvika , Brewer Gretchen , Judge Andrew , Kennedy Donna , Vincent Tonia L. , Watt Fiona E.
Published: February 2024

Introduction

Hand osteoarthritis is more common in women, and its risk increases around the time of the menopause. We set out to describe the timing between menopause and the onset of symptomatic hand osteoarthritis (OA), and associations with the use of hormone replacement therapy (HRT) or its discontinuation, describing any identifiable subgroups of women.

Methods

Retrospective healthcare-records study of sequential women referred to a specialist hand OA clinic, 2007–2015. Confirmation of hand OA diagnosis was by clinican, by accepted criteria. Demographics and clinical variables were from healthcare-records, recorded by standardised proforma. Outcomes of interest were reported age of onset of hand symptoms, reported age at final menstrual period (FMP), time from FMP to reported onset of hand symptoms and time from cessation of HRT to reported onset of hand symptoms. Exposure categories for systemic HRT use were never users, current users, previous users. Analysis of Variance compared groups; linear regression analysed associations of exposure with outcome.

Results

82/92(89%) of eligible women were post-menopausal, mean age at FMP 49.9 years (SD5.4). In these post-menopausal women, median time from FMP to hand symptom onset was 3 years. 48/82 (59%) developed hand symptoms within the defined peri-menopausal period (FMP ± 4 years), whilst some women developed their symptoms before or after (range −25, 30 years). In women who discontinued HRT prior to symptom onset, the median time from HRT cessation to onset of hand symptoms was 6 months. Past HRT users were older at hand symptom onset than women who had not taken HRT [coeff.4.7 years (0.92, 8.39); P = 0.015].

Conclusions

This study adds to evidence associating the menopause/sex hormone deficiency with hand OA symptom onset in a sizeable subgroup of women (but not all). HRT use/cessation appears to influence the timing of onset of hand OA symptoms. It is not possible to interpret from this type of study whether sex hormone deficiency is causative of disease or modulates its symptoms. It is also not possible to judge whether painful hand osteoarthritis in post-menopausal women is a subtype of disease. Further investigation is indicated of sex-specific subtypes and potential for personalised medicine for post-menopausal women with hand osteoarthritis, as a clearly definable high-risk subgroup.
Viral meningoencephalitis in pediatric solid organ or hematopoietic cell transplant recipients: a diagnostic and therapeutic approach
Authors: Thomas Sanya J. , Ouellette Christopher P.
Published: February 2024

Neurologic complications, both infectious and non-infectious, are frequent among hematopoietic cell transplant (HCT) and solid organ transplant (SOT) recipients. Up to 46% of HCT and 50% of SOT recipients experience a neurological complication, including cerebrovascular accidents, drug toxicities, as well as infections. Defects in innate, adaptive, and humoral immune function among transplant recipients predispose to opportunistic infections, including central nervous system (CNS) disease. CNS infections remain uncommon overall amongst HCT and SOT recipients, compromising approximately 1% of total cases among adult patients. Given the relatively lower number of pediatric transplant recipients, the incidence of CNS disease amongst in this population remains unknown. Although infections comprise a small percentage of the neurological complications that occur post-transplant, the associated morbidity and mortality in an immunosuppressed state makes it imperative to promptly evaluate and aggressively treat a pediatric transplant patient with suspicion for viral meningoencephalitis. This manuscript guides the reader through a broad infectious and non-infectious diagnostic differential in a transplant recipient presenting with altered mentation and fever and thereafter, elaborates on diagnostics and management of viral meningoencephalitis. Hypothetical SOT and HCT patient cases have also been constructed to illustrate the diagnostic and management process in select viral etiologies. Given the unique risk for various opportunistic viral infections resulting in CNS disease among transplant recipients, the manuscript will provide a contemporary review of the epidemiology, risk factors, diagnosis, and management of viral meningoencephalitis in these patients
Advances in light system engineering across the phototrophic spectrum
Authors: Dennis Galen , Posewitz Matthew C.
Published: February 2024

Current work in photosynthetic engineering is progressing along the lines of cyanobacterial, microalgal, and plant research. These are interconnected through the fundamental mechanisms of photosynthesis and advances in one field can often be leveraged to improve another. It is worthwhile for researchers specializing in one or more of these systems to be aware of the work being done across the entire research space as parallel advances of techniques and experimental approaches can often be applied across the field of photosynthesis research. This review focuses on research published in recent years related to the light reactions of photosynthesis in cyanobacteria, eukaryotic algae, and plants. Highlighted are attempts to improve photosynthetic efficiency, and subsequent biomass production. Also discussed are studies on cross-field heterologous expression, and related work on augmented and novel light capture systems. This is reviewed in the context of translatability in research across diverse photosynthetic organisms.
ZjHXK5 and ZjHXK6 negatively regulate the sugar metabolism of Ziziphus jujuba Mill.
Authors: Tong Panpan , Liao Guanglian , Lu Dengyang , Zhou Xiaofeng , Zhang Wang , Xu Qiang , Wu Cuiyun , Wang Jiangbo
Published: February 2024

Hexokinase (HXK) plays a crucial role in plants, catalyzing the phosphorylation of hexose substances, which is one of the key steps in sugar metabolism and energy production. While HXK genes have been well-studied in model plants, the evolutionary and functional characteristics of HXK gene family in jujube is unknow. In this study, the HXK gene family members were identified by bioinformatics methods, the key members regulating glucose metabolism were identified by transcriptome data, and finally the function of the key genes was verified by instantaneous and stable genetic transformation. Our results showed that seven HXK genes were identified in the jujube genome, all of which were predict located in the chloroplast and contain Hexokinase-1 (PF00349) and Hexokinase-2 (PF03727) conserved domains. Most of HXK proteins were transmembrane protein with stable, lipid-soluble, hydrophilic. The secondary structure of ZjHXK proteins main α-helix, and contains two distinct tertiary structure. All ZjHXK genes contain nine exons and eight introns. Predictions of cis-regulatory elements indicate that the promoter region of ZjHXK contains a large number of MeJA responsive elements. Finally, combined with the analysis of the relationship between the expression and glucose metabolism, found that ZjHXK5 and ZjHXK6 may the key genes regulating sugar metabolism. Transient overexpression of ZjHXK5 and ZjHXK6 on jujube, or allogeneic overexpression of ZjHXK5 and ZjHXK6 on tomato would significantly reduce the content of total sugar and various sugar components. Transient silencing of ZjHXK5 and ZjHXK6 genes results in a significant increase in sucrose and total sugar content. Interestingly, the expression of ZjHXK5 and ZjHXK6 were also affected by methyl jasmonate.
Alfalfa MsbHLH115 confers tolerance to cadmium stress through activating the iron deficiency response in Arabidopsis thaliana
Authors: Zhang Miao , Gao Jing-Yun , Dong Shi-Chen , Chang Meng-Han , Zhu Jing-Xuan , Guo Dong-Lin , Guo Chang-Hong , Bi Ying-Dong
Published: February 2024

Cadmium (Cd) pollution severely affects plant growth and development, posing risks to human health throughout the food chain. Improved iron (Fe) nutrients could mitigate Cd toxicity in plants, but the regulatory network involving Cd and Fe interplay remains unresolved. Here, a transcription factor gene of alfalfa, MsbHLH115 was verified to respond to iron deficiency and Cd stress. Overexpression of MsbHLH115 enhanced tolerance to Cd stress, showing better growth and less ROS accumulation in Arabidopsis thaliana. Overexpression of MsbHLH115 significantly enhanced Fe and Zn accumulation and did not affect Cd, Mn, and Cu concentration in Arabidopsis. Further investigations revealed that MsbHLH115 up-regulated iron homeostasis regulation genes, ROS-related genes, and metal chelation and detoxification genes, contributing to attenuating Cd toxicity. Y1H, EMSA, and LUC assays confirmed the physical interaction between MsbHLH115 and E-box, which is present in the promoter regions of most of the above-mentioned iron homeostasis regulatory genes. The transient expression experiment showed that MsbHLH115 interacted with MsbHLH121pro. The results suggest that MsbHLH115 may directly regulate the iron-deficiency response system and indirectly regulate the metal detoxification response mechanism, thereby enhancing plant Cd tolerance. In summary, enhancing iron accumulation through transcription factor regulation holds promise for improving plant tolerance to Cd toxicity, and MsbHLH115 is a potential candidate for addressing Cd toxicity issues.
Composition considerations for fluid teams: a review
Authors: Driskell Tripp , Funke Gregory , Tolston Michael , Capiola August , Driskell James
Published: February 2024

The need exists to better understand how to comprise fluid teams—teams that are assembled on short notice, from members with little to no familiarity, who come together to carry out a time-limited task, and then disband. Due to the ever-increasing complexity of the modern workplace, the demand for these types of fluid teams is growing in task domains such as the military, aviation, healthcare, and industry. The aim of this paper is to review the team composition literature to shed light on composition considerations for forming fluid teams.
Frequency of SARS-CoV-2 variants identified by real-time PCR in the AUNA healthcare network, Peru
Authors: Ortiz-Gómez Tamin , Gomez Andrea C. , Chuima Brigitte , Zevallos Alejandra , Ocampo Karen , Torres Diana , Pinto Joseph A.
Published: February 2024

Introduction

In Peru, on 11 February 2023, the Ministry of Health registered 4 million patients infected with COVID-19 and around 219,260 deaths. In 2020, the SARS-CoV-2 virus was acquiring mutations that impacted the properties of transmissibility, infectivity, and immune evasion, leading to new lineages. In the present study, the frequency of COVID-19 variants was determined during 2021 and 2022 in patients treated in the AUNA healthcare network.

Methods

The methodology used to detect mutations and identify variants was the Allplex™ SARS-CoV-2 Variants Assay I, II, and VII kit RT-PCR. The frequency of variants was presented by epidemiological weeks.

Results

In total, 544 positive samples were evaluated, where the Delta, Omicron, and Gamma variants were identified. The Delta variant was found in 242 (44.5%) patients between epidemiological weeks 39 and 52 in 2021. In the case of Gamma, it was observed in 8 (1.5%) patients at weeks 39, 41, 43, 45, and 46 of 2021. The Omicron variant was the most frequent with 289 (53.1%) patients during weeks 49 to 52 of 2021 and 1 to 22 of 2022. During weeks 1 through 22 of 2022, it was possible to discriminate between BA. 1 (n = 32) and BA.2 (n = 82).

Conclusion

The rapid identification of COVID-19 variants through the RT-PCR methodology contributes to timely epidemiological surveillance, as well as appropriate patient management.
Surveillance of noise exposure level in industrial enterprises—Jiangsu Province, China, 2022
Authors: Zhang Cuicui , Wang Jianfeng , Wang Huan , Zhang Hengdong
Published: February 2024

Occupational noise exposure is the most prominent problem in industrial enterprises in Jiangsu Province. Since 2019, China has established the National Surveillance System for Occupational Hazards in the workplace to grasp the current occupational hazards in critical industries, including occupational noise. According to the Work Plan for Surveillance of Occupational Hazards in the Workplace (2022) issued by the National Health Commission of the People’s Republic of China, the noise exposure level of 3,142 enterprises in our province was monitored, the median and interquartile range (IQR) were calculated, and the distribution of noise exposure level was described by industry classification, enterprise-scale and ownership type of the enterprise. The railway, shipping, aerospace, and other transportation equipment manufacturing industries exhibited the highest proportion (42.9%) of individual noise exposure levels exceeding 85 dB(A), followed by the motor vehicles manufacturing industry (36.4%). The proportion of individual noise exposure levels exceeding 85 dB(A) was higher in medium and small enterprises, with rates of 28.1 and 28.6%, respectively. The highest proportion of personal noise exposure levels exceeding 85 dB(A) was observed in Hong Kong, Macao and Taiwan investment enterprises (37.5%), followed by incorporated companies (34.6%) and limited liability companies (28.1%), the lowest was state-owned enterprises(15.5%). The areas with excessive noise are primarily concentrated in grinding, welding, machining, cutting, and other related operations, accounting for 61.2% of the total. Among these operations, grinding accounts for 29.8%. The highest environmental noise and individual noise intensity were found in sandblasting and grinding positions, with individual noise intensities of 115.5 dB(A) and 108.4 dB(A), respectively. The noise exposure risk is so high that cannot be ignored in the manufacturing industry, especially in Hong Kong, Macao, and Taiwan investment enterprises, incorporated companies and medium and small enterprises.
Sex-specific association of low-renin hypertension with metabolic and musculoskeletal health in Korean older adults
Authors: Lee Seunghyun , Chang Jae Seung , Park Kyu-Sang , Koh Sang-Baek , Kim Moon Young , Lim Jung Soo
Published: February 2024

Introduction

Low-renin hypertension (LRH) accounts for approximately one-third of patients with hypertension and are more prevalent in women and the older adult population. Previous study has found a link between the renin-angiotensin-aldosterone system (RAAS) and sex hormones. However, there are insufficient data on the relationship between LRH and metabolic or musculoskeletal outcomes in older adults.

Methods and materials

Among the 343 participants from a population-based cohort study conducted between May 2018 and August 2019, a total of 256 (86 men older than 50 years and 170 postmenopausal women) were included. The presence of LRH was defined as plasma renin activity (PRA) <1 ng/mL/h and systolic blood pressure (BP) ≥130 or diastolic BP ≥80 mmHg based on the 2017 ACC/AHA guidelines. Individuals with missing data, and those who had used medications that could affect PRA within the past six months were excluded. Bone mineral density (BMD), trabecular bone score (TBS), and appendicular lean mass (ALM) index were assessed using dual-energy X-ray absorptiometry; degraded TBS was defined as partially degraded to degraded levels (≤1.350). Muscle function was assessed according to the Asian Working Group for Sarcopenia guidelines. PRA was measured using radioimmunoassay.

Results

The median age was 66 [61–72] years, and the body mass index (BMI) was 24.7 [23.0–26.4] kg/m2. Individuals with LRH, accounting for 34.8%, had lower diabetes mellitus; more dyslipidemia; and poorer muscle function, BMD, and TBS than those in the non-LRH group. In addition, PRA was positively correlated with C-peptide, HOMA-IR, TBS, and ALM index. After adjusting for covariates including age and BMI, LRH was negatively associated with femur neck T-score (adjusted β = −0.30, 95% CI [−0.55 to −0.05], p = 0.021) and the presence of LRH was significantly associated with degraded TBS in women (adjusted odds ratio = 3.00, 95% CI [1.36–6.58], p = 0.006).

Conclusion

Our findings suggest that LRH can influence clinical features and metabolic risk in older adults. Notably, LRH in postmenopausal women was linked to lower femur neck T-scores and degraded TBS, indicating sex-specific effects of LRH on bone health. Larger prospective studies are required to elucidate how changes in the RAAS affect metabolic and musculoskeletal outcomes in older adults.
Police discrimination and police distrust among ethnic minority adolescents in Germany
Authors: Kogan Irena , Weißmann Markus , Dollmann Jörg
Published: February 2024

In light of ongoing debates about racially motivated police violence, this paper examines two separate but interrelated phenomena: instances of police discrimination and mistrust in police and the judicial system among ethnic minorities in Germany. Analyses are carried out based on waves 1, 3, and 5 of the CILS4EU-DE data collected among 14 to 20 year-old respondents in Germany. The focus of the paper lies on young men from the Middle East, as well as Northern and Sub-Saharan Africa, who—as our study demonstrates—tend to disproportionally more often report discrimination experiences and particularly low levels of trust in police and courts compared to other ethnic minorities and the majority populations in Germany, and partially also in comparison to their female counterparts. We also show that more frequent experiences of police discrimination are associated with greater distrust of the police and partially also with courts among young men from the Middle East, North and Sub-Saharan Africa. Female adolescents from similar backgrounds are also more distrustful of the police, but this is not explained by their own experiences of police discrimination.
Short review of the main achievements of the scalar field, fuzzy, ultralight, wave, BEC dark matter model
Authors: Matos Tonatiuh , Ureña-López Luis A. , Lee Jae-Weon
Published: February 2024

The Scalar Field Dark Matter model has been known in various ways throughout its history; Fuzzy, BEC, Wave, Ultralight, Axion-like Dark Matter, etc. All of them consist in proposing that dark matter of the universe is a spinless field Φ that follows the Klein-Gordon (KG) equation of motion □Φ −dV/dΦ = 0, for a given scalar field potentialV. The difference between different models is sometimes the choice of the scalar field potentialV. In the literature we find that people usually work in the non-relativistic, weak-field limit of the Klein-Gordon equation, where it transforms into the Schrödinger equation and the Einstein equations into the Poisson equation, reducing the KG-Einstein system, to the Schrödinger-Poisson system. In this paper, we review some of the most interesting achievements of this model from the historical point of view and its comparison with observations, showing that this model could be the last answer to the question about the nature of dark matter in the universe.
Data-driven review on gender and rice varietal trait preferences in Bangladesh
Authors: Khan Md Sahed , Sarkar Md Abdur Rouf , Islam Mohammad Rafiqul , Bhandari Humnath
Published: February 2024

In Bangladesh, farmers adapt to changing conditions through the adoption of improved varieties containing new or combined traits. The diverse varietal adoption decisions among farmers stem from gender-based differences in trait preferences. This review synthesizes existing knowledge to assess the nature, extent, and causes of gendered disparities in rice varietal trait preferences among farmers and consumers in Bangladesh. To enhance the data-driven nature of this review, we not only scrutinized secondary articles (45 documents) and databases but also incorporated and analyzed primary data on varietal adoption and trait preferences. The analysis revealed a pronounced need for rice breeding programs in Bangladesh to integrate both market and climate-smart traits, aligning with gender-specific needs in developing optimal rice product profiles. Analysis of primary data unveiled substantial variations in women and men farmers’ varietal trait preferences, influenced by factors like income, access to farming information, household size, land size, and decision-making. Consequently, addressing gender-differentiated trait preferences in the development of improved rice varieties is crucial to curtail farmers’ varietal adoption lag in Bangladesh. The findings underscore the necessity of systematic identification and integration of gender-differentiated varietal trait preferences into rice breeding programs. Failure to account for such preferences may disadvantage the gender-responsiveness of developed varieties and limit the anticipated impact. Therefore, understanding the biophysical, social, and cultural dynamics of diverse farmer groups from a gender perspective is imperative for achieving gender-responsive rice variety development in the context of Bangladesh. This process involves identifying key gender concerns for integration into rice breeding programs, ensuring a comprehensive approach to sustainable agriculture.
Assessing Mental Workload in Dual STEM–Air Force Language Listening Practice
Authors: Roca-González José Luis , Vera-López Juan-Antonio , Navarro Pérez Margarita
Published: February 2024

Cognitive workload analysis is an important aspect of safety studies at the Spanish Air Force Academy where students must complete a dual academic curriculum based on military pilot training combined with an industrial engineering degree. Recently, a mental workload assessment (MWA) and forecasting model based on Shannon’s law from information theory (IT) has been published; it proposes a new mathematical procedure (MWA-IT) that defines a workload index that could be extrapolated to other case studies. The aim of this study was to adapt this model to the Spanish University Centre of Defence to calculate the mental workload caused by the listening practice in English as a foreign language. In addition, a contrasting methodology, the NASA task load index (NASA-TLX), was applied to validate the proposed model using the error study provided by SMAPE and MSE. The results established an expected reference baseline for MWA-IT in English listening that is between 36 and 92 at the end of the four courses, which corresponds to the students that start with the lowest English level (higher workload = 92) and the ones with the highest English level certification (lowest workload = 36); meanwhile, the NASA-TLX result was between 49.8 and 193.7 for the same circumstances. The main difference is that MWA-IT can be predicted with 41% less deviation than can NASA-TLX and does not require the completion of a questionnaire following the activities. Finally, the study also highlights the fact that that nearly 65% of the workload was caused by the first two courses, when the advanced STEM subjects were taught and the pilot learning and practice program had not yet begun. This methodology may help the teachers in charge to redesign or add new content depending on the expected workload reference.
Automatic Detection of Rice Blast Fungus Spores by Deep Learning-Based Object Detection: Models, Benchmarks and Quantitative Analysis
Authors: Zhou Huiru , Lai Qiang , Huang Qiong , Cai Dingzhou , Huang Dong , Wu Boming
Published: February 2024

The severity of rice blast and its impacts on rice yield are closely related to the inoculum quantity of Magnaporthe oryzae, and automatic detection of the pathogen spores in microscopic images can provide a rapid and effective way to quantify pathogen inoculum. Traditional spore detection methods mostly rely on manual feature extraction and shallow machine learning models, and are mostly designed for the indoor counting of a single spore class, which cannot handle the interference of impurity particles in the field. This study achieved automatic detection of rice blast fungus spores in the mixture with other fungal spores and rice pollens commonly encountered under field conditions by using deep learning based object detection techniques. First, 8959 microscopic images of a single spore class and 1450 microscopic images of mixed spore classes, including the rice blast fungus spores and four common impurity particles, were collected and labelled to form the benchmark dataset. Then, Faster R-CNN, Cascade R-CNN and YOLOv3 were used as the main detection frameworks, and multiple convolutional neural networks were used as the backbone networks in training of nine object detection algorithms. The results showed that the detection performance of YOLOv3_DarkNet53 is superior to the other eight algorithms, and achieved 98.0% mean average precision (intersection over union > 0.5) and an average speed of 36.4 frames per second. This study demonstrated the enormous application potential of deep object detection algorithms in automatic detection and quantification of rice blast fungus spores.
Rural Depopulation in Spain: A Delphi Analysis on the Need for the Reorientation of Public Policies
Authors: Martínez-Carrasco Pleite Federico , Colino Sueiras José
Published: February 2024

In recent years, various plans have been implemented by the central government with the aim of promoting more coordinated policies to address depopulation. The severity of this challenge in Spain, which has continued to intensify, underscores the need for more decisive action. The information presented in this research is derived from a survey conducted in two rounds with 35 experts in the field, following the Delphi methodology. The general objective was to assess the opinions of an expert panel on relevant aspects concerning policies to combat depopulation in Spain. Firstly, confirming the significance of the depopulation challenge; secondly, evaluating whether the actions taken so far have been insufficient and poorly coordinated, necessitating a reconsideration; and finally, establishing a prioritization of actions that should be implemented without further delay, encompassing various areas (financing, taxation, coordination, etc.), are among the many measures advocated by the Spanish Federation of Municipalities and Provinces (FEMP) and proposed in the recent diagnoses by highly authoritative institutions such as the Bank of Spain or the Economic and Social Council of Spain (CES).
Synchronous Retrieval of Wheat Cab and LAI from UAV Remote Sensing: Application of the Optimized Estimation Inversion Framework
Authors: Ji Jiangtao , Wang Xiaofei , Ma Hao , Zheng Fengxun , Shi Yi , Cui Hongwei , Zhao Shaoshuai
Published: February 2024

Chlorophyll a and b content (Cab) and leaf area index (LAI) are two key parameters of crops, and their quantitative inversions are important for growth monitoring and the field management of wheat. However, due to the close correlation between the spectral signals of these two parameters and the effects of soil and atmospheric conditions, as well as modeling errors, synchronous retrieval of LAI and Cab from remote sensing data is still a challenging task. In a previous study, we introduced the optimal estimation theory and established the inversion framework by coupling the PROSAIL (PROSPECT + SAIL) model with the unified linearized vector radiative transfer model (UNL-VRTM). The framework fully utilizes the simulated radiance spectra for synchronous retrieval of Cab and LAI at the UAV observation scale and has good convergence and self-consistency. In this study, based on this inversion framework, synchronized retrieval of Cab and LAI was carried out by real wheat UAV observation data and validated with the ground-measured data. By comparing with the empirical statistical model constructed by the PROSAIL model and coupled model, least squares support vector machine (LSSVM), and random forest (RF), the proposed method has the highest accuracy of Cab and LAI estimated from UAV multispectral data (for Cab, R2 = 0.835, RMSE = 14.357; for LAI, R2 = 0.892, RMSE = 0.564). Our proposed method enables the fast and efficient estimation of Cab and LAI in multispectral data without prior measurements and training.
Development of Assessment Criteria for Managing the Quality of Taishan Black Tea
Authors: Wen Xiaochen , Xie Tongtong , Chen Xinying , Li Jie , Han Xiaoyang , Sun Haiwei
Published: February 2024

In order to obtain the quality information of Taishan black tea and provide data support for the establishment of assessment criteria for quality control of Taishan black tea, in this study, 45 samples of Taishan black tea were collected during the summer to investigate their quality characteristics. The results showed that the Taishan black tea typically exhibited a dark-brown, curly appearance and a uniform texture. The tea soup displayed a bright orange-red color. The tea was mainly described as having a fruity aroma, followed by a caramel flavor, sweet aroma, flowery flavor, and clean aroma, with a strong and enduring fragrance. The taste profile was mostly heavy and mellow or heavy and strong, with fewer samples exhibiting slight bitterness and astringency. The tea leaves were characterized by a reddish-auburn color, a soft texture, and an even appearance. The main biochemical components of the Taishan black tea fell within the following ranges: water extracts (38.65–43.35%), free amino acids (1.41–3.45%), tea polyphenols (9.80–15.05%), catechins (6.11–9.03%), and caffeine (1.65–3.05%). The phenolic acid/amino acid ratio was 2.31–6.65%. Catechins and tea polyphenols emerged as critical indicators influencing taste quality, followed by amino acids, water extracts, and caffeine. The aroma analysis identified common compounds, such as 3-methyl-butanal, 2-methyl-butanal, decanal, 2-methyl-propanal, 1-octen-3-ol, and β-ionone, in most samples. These compounds exhibited relatively high contents and high odor activity values, making them the primary contributors to the tea’s aroma. This investigation into the quality of Taishan black tea offers valuable scientific insights, providing a foundation for the standardization of Taishan black tea’s quality.
Modeling of Cotton Yield Estimation Based on Canopy Sun-Induced Chlorophyll Fluorescence
Authors: Wang Hongyu , Ding Yiren , Yao Qiushuang , Ma Lulu , Ma Yiru , Yang Mi , Qin Shizhe , Xu Feng , Zhang Ze , Gao Zhe
Published: February 2024

Cotton yield estimation is of great practical significance to producers, allowing them to make rational management decisions. At present, crop yield estimation methods mainly comprise traditional agricultural yield estimation methods, which have many shortcomings. As an ideal “probe” for detecting crop photosynthesis, sun-induced chlorophyll fluorescence (SIF) can directly reflect the dynamics of actual crop photosynthesis and has the potential to predict crop yield, in order to realize cotton yield estimation based on canopy SIF. In this study, we set up field trials with different nitrogen fertilizer gradients. The changes of canopy SIF and the physiological parameters of cotton in different growth periods were analyzed. To investigate the effects of LAI and AGB on canopy SIF estimation of cotton yield, four algorithms, Ada Boost (Adaptive Boosting), Bagging (Bootstrap Aggregating), RF (Random Forest), and BPNN (Backpropagation Neural Network), were used to construct cotton yield estimation models based on the SIF and SIFy (the normalization of SIF by incident photosynthetically active radiation) for different time and growth periods. The results include the following: (1) The effects of the leaf area index (LAI) and aboveground biomass (AGB) on cotton canopy SIF and cotton yield were similar. The correlation coefficients of LAI and AGB with cotton yield and SIF were significantly positively correlated with each other starting from the budding period, reaching the maximum at the flowering and boll period, and decreasing at the boll period; (2) In different monitoring time periods, the R2 of the cotton yield estimation model established based on SIF and SIFy showed a gradual increase from 10:00 to 14:00 and a gradual decrease from 15:00 to 19:00, while the optimal observation time was from 14:00 to 15:00. The R2 increased with the progression of growth from the budding period to the flowering and boll period and decreased at the boll period, while the optimum growth period was the flowering and boll period; (3) Compared to SIF, SIFy has a superior estimation of yield. The best yield estimation model based on the RF algorithm (R2 = 0.9612, RMSE = 66.27 kg·ha−1, RPD = 4.264) was found in the canopy SIFy of the flowering and boll period at 14:00–15:00, followed by the model utilizing the Bagging algorithm (R2 = 0.8898) and Ada Boost algorithm (R2 = 0.8796). In summary, SIFy eliminates the effect of PAR (photosynthetically active radiation) on SIF and can further improve the estimation of SIF production. This study provides empirical support for SIF estimation of cotton yield and methodological and modeling support for the accurate estimation of cotton yield.
Epichloë bromicola Enhances Elymus dahucirus Plant Growth and Antioxidant Capacity under Cadmium Stress
Authors: Shi Qian , Simpson Wayne R. , Li Yuling , Xu Chengti , De Kejia , Li Xiuzhang
Published: February 2024

Elymus dahucirus is an essential plant for ecological restoration in fragile ecological areas and mining area restoration. As lawn grass, it can quickly cover soil and prevent soil erosion, so it is commonly used as a pioneer grass for lawn greening and slope protection. In recent years, with the development of mineral resources, Qinghai–Tibet Plateau soil is facing the threat of heavy metal cadmium (Cd) pollution. E. dahuricus can host the filamentous fungus Epichloë bromicola. To make better use of the advantages that Epichloë bring to host plants to alleviate heavy metal pollution in soil, plant growth and antioxidant capacity effects on E. bromicola infected (E+) and uninfected (E−) E. dahuricus were determined under Cd stress. During Cd treatment, plant growth was decreased by Cd stress, while E+ plants exhibited equal or better growth compared to E− plants. Cd treatment induces a proline and antioxidant enzyme burst in infected plants, while malondialdehyde (MDA) increases. E. bromicola improved plant growth and antioxidant capacity. E. dahuricus breeding strategies could use the information here in efforts to improve the performance of E. dahuricus in both environmental protection and agronomic contexts.
Prevalence, Genetic Diversity, and Quantification of the RNA Genome of the Hepatitis E Virus in Slaughtered Pigs in Serbia
Authors: Milojević Lazar , Velebit Branko , Janković Vesna , Mitrović Radmila , Betić Nikola , Simunović Sara , Dimitrijević Mirjana
Published: February 2024

The goal of this study conducted in Serbia was to detect HEV in pig liver samples from slaughterhouses, retail outlets, and environmental swabs over the course of a year. All positive HEV samples were measured and expressed as HEV gene copy numbers per gram of sample, and a representative number of samples were sequenced using the Sanger approach. A total of 45 HEV-positive samples were re-amplified using nested RT-PCR employing CODEHOP primers targeting ORF2 (493 nucleotides). The average prevalence of the HEV genotype 3 in all pig liver samples from the slaughterhouses was 29%, while HEV prevalence was 44% in liver samples from animals younger than 3 months. HEV RNA was found in thirteen out of sixty (22%) environmental swab samples that were taken from different surfaces along the slaughter line. Our findings confirmed seasonal patterns in HEV prevalence, with two picks (summer and winter periods) during the one-year examination. Among HEV-positive samples, the average viral particles for all positive liver samples was 4.41 ± 1.69 log10 genome copies per gram. Phylogenetic analysis revealed the majority of HEV strains (43/45) from Serbia were grouped in the HEV-3a subtype, while two strains were classified into the HEV-3c subtype, and one strain could not be classified into any of the HEV-3 subtypes.