bluuebunny/crossref_metadata_2025_split huggingface dataset:
Students’ Perception and Gender Differences in Digital Learning During COVID-19: A consensus Based Approach
Authors: Ahmad Masroor , Haq Anam Ul , Raina Shahid Hamid , Pala Saqib Mushtaq , Khan Aaqila Ishaque 
Published: July 2023

Abstract
Although online learning is not a novel phenomenon in education institutions, especially at higher levels, but the onset of covid-19 utterly disrupted the traditional mode of learning and forced a hasty shift towards its wider adoption. In the developing countries like India, while on the one hand, it has led to a significant surge in the use of online learning tools and softwares, on the other hand, it has also brought to fore the ill-preparedness of institutions for such a mode of learning. Further, given the country's current scenario, the readiness of all the stakeholders (instructors, students, parents) and the effectiveness of online learning cannot be assumed to be the same at all levels, for all age groups, and across gender. In this study, we focus on understanding secondary school students' perceptions and preferences regarding online learning. Besides looking for possible gender discrepancies in the impact of Covid 19, we tried to identify major benefits and bottlenecks from students’ perspectives. To overcome the limitations of Shenon entropy and other measures of dispersion for ordinal data, we made use of consensus/dissention measurement for a meaningful comparison of mean ranks. For the robustness of rankings in case of major benefits and bottlenecks, we used Friedman’s ranking along with Garret ranking. The results reveal, with a good degree of agreement/consensus, online learning improves technical skills, saves time, and encourages more self-study. Nevertheless, respondents highlighted a number of challenges during their online courses, including weak internet connectivity, insufficient number of devices at home, and disruptions caused by family members. Also, females were more affected than males as they had fewer learning resources at home, and in some cases, the burden of household chores prevented them from studying. We suggest a greater focus towards the bottlenecks (identified in this study) while making online learning an integral part of school education so as to reap its benefits.
Single-cell RNA sequencing reveals cellular and molecular landscape of fetal cystic hygroma
Authors: Fu Fang , Yang Xin , Li Ru , Li Yingsi , Zhou Hang , Cheng Ken , Huang Ruibin , Wang You , Guo Fei , Zhang Lina , Pan Min , Han Jin , Zhen Li , Li Lushan , Lei Tingying , Li Dongzhi , Liao Can 
Published: July 2023

Abstract

Background
The molecular mechanism of fetal cystic hygroma (CH) is still unclear, and no study has previously reported the transcriptome changes of single cells in CH. In this study, single-cell transcriptome sequencing (scRNA-seq) was used to investigate the characteristics of cell subsets in the lesion tissues of CH patients.
Methods
The lesions of CH patients and controls were collected for scRNA-seq analysis. The distribution of CH cell subsets and transcriptome characteristics were analyzed. Differentially expressed gene enrichment in major cell subpopulations as well as cell-cell communication were analyzed. At the same time, the expression and interaction of important VEGF signaling pathway molecules were analyzed, and the potential transcription factors of KDR were predicted.
Results
The results of scRNA-seq showed that fibroblasts accounted for the largest proportion in the lymphatic lesions of CH patients. There was a significant increase in the proportion of lymphatic endothelial cell subsets between the cases and controls. The VEGF signaling pathway is enriched in lymphatic endothelial cells and participates in the regulation of cell-cell communication between lymphatic endothelial cells and other cells .The key regulatory gene KDR in the VEGF signaling pathway is highly expressed in CH patients and interacts with other differentially expressed EDN1, TAGLN and CLDN5 Finally, we found that STAT1 could bind to the KDR promoter region, which may play an important role in promoting KDR up-regulation.
Conclusion
Our comprehensive delineation of the cellular composition in tumor tissues of CH patients using single-cell RNA-sequencing identified enrichment of lymphatic endothelial cells in CH and highlighted activation of the VEGF signaling pathway in lymphoid endothelial cells as a potential modulator..
Molecular Crosstalk Between MUC1 and STAT3 influences the anti-proliferative effect of Napabucasin in epithelial cancers
Authors: Bose Mukulika , Sanders Alexa , Handa Aashna , Vora Aabha , Brouwer Cory , Mukherjee Pinku 
Published: July 2023

Abstract
MUC1 is a transmembrane glycoprotein that is overexpressed and aberrantly glycosylated in epithelial cancers. The cytoplasmic tail of MUC1 (MUC1 CT) aids in tumorigenesis by upregulating the expression of multiple oncogenes. Signal transducer and activator of transcription 3 (STAT3) plays a crucial role in several cellular processes and is aberrantly activated in many cancers. In this study, we focus on recent evidence suggesting that STAT3 and MUC1 regulate each other’s expression in cancer cells in an auto-inductive loop and found that their interaction plays a prominent role in mediating epithelial-to-mesenchymal transition (EMT) and drug resistance. The STAT3 inhibitor Napabucasin was in clinical trials but was discontinued due to futility. We found that higher expression of MUC1 increased the sensitivity of cancer cells to Napabucasin. Therefore, high-MUC1 tumors may have a better outcome to Napabucasin therapy. We report how MUC1 regulates STAT3 activity and provide a new perspective on repurposing the STAT3-inhibitor Napabucasin to improve clinical outcome of epithelial cancer treatment.
Dual inoculation of ACC deaminase-producing Pseudomonas and Bradyrhizobium: A synergistic approach to N2-fixation and salt stress mitigation in soybean
Authors: Win Khin Thuzar , Wasai-Hara Sawa , Tanaka Fukuyo , Oo Aung Zaw , Minamisawa Kiwamu , Shimoda Yoshikazu , IMAIZUMI-ANRAKU Haruko 
Published: July 2023

Abstract
We investigated the potential dual application of two Bradyrhizobium strains (B. diazoefficiens USDA110 and B. ottawaense SG09) and plant growth-promoting bacteria, PGPB (Pseudomonas spp.: OFT2 and OFT5), to improve nodulation and N2-fixation in soybean plants. The growth-promoting effects of dual inoculation were observed on plant growth, physiology, and nodulation of soybean under normal conditions compared with plants individually inoculated with either USDA110 or SG09. Both OFT2 and OFT5 promoted N2-fixation by 11% and 56%, respectively, when dual inoculation with USDA110 and by 76% and 81%, respectively, when dual inoculation with SG09. Salinity stress significantly reduces soybean growth, physiology, nutrient uptake, nodulation, and N2-fixation. However, these adverse effects were attenuated by the dual inoculation of PGPB and rhizobia depending on the combination of inoculants. In particular, dual inoculation of PGPB with SG09 was more effective in enhancing the salt tolerance of soybean by reducing salt-induced ethylene production and improving nutrient uptake. However, no such effect was observed with the combined inoculation of USDA110 and OFT5. An effective symbiotic association between SG09 and two Pseudomonas bacteria can be considered a beneficial approach to improve the symbiotic efficiency of nodulation and mitigate salinity stress in soybeans.
Proteomic Discovery of Prognostic Protein Biomarkers for Persisting Problems After Mild Traumatic Brain Injury
Authors: Lee Min-Yong , Son Minsoo , Lee Hyun Haeng , Kang Min-Gu , Yun Seo Jung , Seo Han Gil , Kim Youngsoo , Oh Byung-Mo 
Published: July 2023

Abstract
Some individuals with mild traumatic brain injury (mTBI), also known as concussion, have neuropsychiatric and physical problems that last longer than a few months. Symptoms following mTBI are not only impacted by the kind and severity of the injury but also by the post-injury experience and the individual's responses to it, making the persistence of mTBI particularly difficult to predict. We aimed to identify prognostic blood-based protein biomarkers predicting 6-month outcomes, in light of the clinical course after the injury, in a longitudinal mTBI cohort (N = 42). Among 420 target proteins quantified by multiple-reaction monitoring-mass spectrometry assays of blood samples, 31, 43, and 15 proteins were significantly associated with the poor recovery of neuropsychological symptoms at < 72 hours, 1 week, and 1 month after the injury, respectively. Sequential associations among clinical assessments (depressive symptoms and cognitive function) affecting the 6-month outcomes were evaluated. Then, candidate biomarker proteins indirectly affecting the outcome via neuropsychological symptoms were identified. Using the identified proteins, prognostic models that can predict the 6-month outcome of mTBI were developed. These protein biomarkers established in the context of the clinical course of mTBI are anticipated to have a wide clinical application.
Estimating Changes of Forest Carbon Storage in China for 70 years (1949-2018)
Authors: Zeng WeiSheng , Chen XinYun , Yang XueYun 
Published: July 2023

Abstract
Stand level biomass carbon model is an important tool for forest resource inventory and monitoring. Developing biomass carbon models for major forest types in China not only provide a scientific basis for estimating forest carbon storage changes at national level, but also provide an important reference for estimating forest carbon storage and carbon sequestration potential at regional and global levels. In this paper, based on the measured data of 52,700 permanent plots from the 9th national forest inventory (NFI) of China, the biomass and carbon storage per hectare were firstly calculated according to the tree biomass models and carbon factors of 35 tree species groups. Then, stand level volume-derived biomass and carbon storage models were developed for 20 forest types by using the approach of simultaneous equations with error-in-variables. Secondly, based on the developed biomass and carbon models of 20 forest types, using the data of 1st to 9th NFIs of China and the area and volume data of different forest types in 1949 and 1950-1962, the forest carbon storages in different periods in the past 70 years and the carbon storages of planted forest in the past 40 years were estimated. Results showed that the determination coefficients (R2) of the developed biomass and carbon models of 20 forest types were more than 0.87, the total relative errors (TREs) were close to 0, and the mean prediction errors (MPEs) were less than 3% (less than 1% for 8 forest types). From the results of independent cross-validation, the TREs were within ±3% except one model, and the average systematic errors (ASEs) were all within ±5%. China's forest carbon storage was 5.89Pg in 1949, and decreased to the lowest level of 4.90Pg in the late 1970s. With the implementation of large-scale afforestation and key forestry programs such as natural forest protection, China's forest carbon storage gradually increased to 8.69Pg in the 9th NFI. Over the past 40 years, China's forest carbon storage has increased by 3.79Pg, of which 2.25Pg was from natural forest and 1.54Pg from planted forest. The applicability of three sets of published biomass models were tested with the data from this study, and it was found that there were large biases for all models, but the estimated results would be improved with the increase of modeling sample size. The biomass and carbon storage models of 20 forest types in China developed in this study would provide a quantitative basis for accurately estimating status and changes of forest carbon storage at national and regional levels. In the past 70 years, China's forest carbon storage has shown a U-shaped development trend. Both afforestation and natural forest protection have made great contributions to the increase of forest carbon storage in China.
Multimodal Kernel-based Discriminant Correlation Analysis Data-Fusion Approach: An Automated Autism Spectrum Disorder Diagnostic System
Authors: Wadhera TANU 
Published: July 2023

Abstract
Autism Spectrum Disorder (ASD) diagnostic systems based on association of multimodal tools such as combination of Electroencephalogram (EEG) and eye-tracking have emerged as an analytical to provide objective biomarkers. However, the existing systems lack in providing robust feature set and knowledge of fusion approaches employed for feature redundancy. The present paper aims to reduce disorder homogeneity by proposing a multimodal diagnostic system that can incorporate cognitive data of ASD individuals. The paper fused computational, neural and visual cognitive data collected from three modalities-laptop-performance tool, EEG machine, and Eye-tracker, respectively. The multimodal features are analyzed via proposed Multimodal Kernel-based Discriminant Correlation Analysis (MKDCA) fusion approach. The proposed framework considered the distinct cardinality of the feature vectors and fused the group structure among multiple samples after ranking them in increasing order. The acquired fused feature set is evaluated using state-of-the-art machine-learning based classifiers to provide influential features and reduce adversarial features in ASD. The results reflected that proposed multimodal system with SVM classifier provided reduced fused feature set of 11 features from total 39 features that diagnosed ASD with 96% accuracy and 0.988 AUC(ROC). The correlation of reduced feature set identified by SVM with ASD clinical symptoms accounted by ADOS and MoCA reflected clinical relevance of proposed multimodal features. The proposed automated fusion-based system has the potential to classify disorder by reducing the disorder heterogeneity and stratifying ASD individuals into homogeneous sub-groups.
Entire Expressed Peripheral Blood Transcriptome in Pediatric Severe Malarial Anemia
Authors: Anyona Samuel , Cheng Qiuying , Guo Yan , Raballah Evans , Hurwitz Ivy , Onyango Clinton , Seidenberg Philip , Schneider Kristan , Lambert Christophe , McMahon Benjamin , Ouma Collins , Perkins Douglas 
Published: July 2023

Abstract

This study on severe malarial anemia (SMA: Hb < 6.0 g/dL), a leading global cause of childhood morbidity and mortality, analyzed the entire expressed transcriptome in whole blood from children with non-SMA (Hb ≥ 6.0 g/dL, n = 41) and SMA (n = 25). Analyses revealed 3,420 up-regulated and 3,442 down-regulated transcripts, signifying impairments in host inflammasome activation, cell death, innate immune responses, and cellular stress responses in SMA. Immune cell profiling showed a decreased antigenic and immune priming response in children with SMA, favoring polarization toward cellular proliferation and repair. Enrichment analysis further identified altered neutrophil and autophagy-related processes, consistent with neutrophil degranulation and altered ubiquitination and proteasome degradation. Pathway analyses highlighted SMA-related alterations in cellular homeostasis, signaling, response to environmental cues, and cellular and immune stress responses. Validation with a qRT-PCR array showed strong concordance with the sequencing data. These findings identify key molecular themes in SMA pathogenesis, providing potential targets for new malaria therapies.
Spider Monkey Inspired Optimization Algorithm Based Clustering For Face Recognition
Authors: Gopal Veni devi , G Shree Devi , Geetha Angelina 
Published: July 2023

Abstract

Face recognition is a fast-growing technology that is widely used in forensics such as criminal identification, secure access and prison security.It contrasts from other classification issues in that there are normally a more number of classes in face recognition. Thus, the validation accuracy of the conventional subsystem face recognition is unsuitable. In order to overcome those problems the suggested method utilizes the spider monkey inspired optimization (SMO) algorithm for face clustering and recognition. At first feature reduction is done by advance principal component analysis (APCA) which is a hybridization of PCA and linear discriminant analysis (LDA). After reducing the features, the selected features are grouped and faces are recognized by means of SMO algorithm. From the food search behavior of spider monkeys, SMO algorithm is developed. The proposed performance is evaluated by means of sensitivity, specificity and accuracy. Here the proposed method accomplishes 98.66% accuracy. Using the MATLAB platform, the recommended technique is implemented.
Prioritization strategies for environmental cognition in dogs: spatial memory or olfactory memory
Authors: FANG Shao-Qin , LI Jie , CHEN Chao , ZHANG Zhi , XU Hu , CAO Jian , WAN Kui , QIU Shi , LI Xi-Gu , HUANG Qiu-Yue 
Published: July 2023

Abstract
Memory is the main basis for animal cognition of the environment and its composition, and more and more studies show that memory plays a key role in the cognitive development of dogs, but there are few studies on whether spatial memory or olfactory memory plays a dominant role in the cognitive process of the environment in dogs. This study aims to further identify the preferred strategy of dogs in the cognitive process of the environment, to provide scientific support for the behavioral research and training of dogs, and also, to un The present study aimed to further confirm the preferential strategy of dogs in environmental cognition to provide scientific support for dog behavioral research and training, and also to provide a reference for human cognitive modeling studies. To test this, a group of dogs was selected to participate in the same learning task in this study, and then, seven Kunming and seven Malinois were randomly selected by breed and sex to perform three rounds of scent recognition tests in the behavior laboratory, with each round of tests being conducted twice a day for a ten-day period. The first two tests (N1S1 and N1S2) both entered the laboratory from the same direction to search for the target, the second two tests (N2S1 and N2S2) entered the laboratory from different directions to search for the target, and the third two tests (N3S1 and N3S2) entered the laboratory from different directions to search for the target, while adding distractors. The test results showed that the difference in search time between N1S1 and N2S1 was not significant, and the dog's search trajectory showed no regularity; N1S2 and N1S2, N2S1 and N2S2 all showed highly significant differences in search time, and the dog's search trajectory showed regularity; N3S1 showed highly significant differences in search time with N1S1 and N2S1, and N3S1 and N3S2 showed no significant differences, and the dog's search The dog's search trajectory showed no regularity. It shows that: in a simple environment without distractors, dogs can form a spatial memory similar to geometric coordinates in the brain for the location of target objects, and they will use spatial memory as the priority strategy for search, but this spatial memory ability is more effective in the short term, and in the long term, it does not accumulate with time; the presence of distractors changed the search strategy derived from spatial memory in N1 and N2, and dogs established a preferential strategy derived from olfactory memory to search and match target objects based on olfactory source odor memory, meanwhile, the dog's odor memory ability and learning time showed a positive correlation.
Characterizing the contributions of cue familiarity for the retrieval of autobiographical memories
Authors: Gurguryan Lauri , Yang Haopei , Köhler Stefan , Sheldon Signy 
Published: July 2023

Abstract

Retrieving an autobiographical memory requires a cue to initiate processes related to accessing and then elaborating on a past personal experience. Prior work has shown that the familiarity of a cue can influence the autobiographical memory retrieval process. Extending on this work, we tested how different aspects of cue familiarity—i.e., amount of past exposure and amount of semantic knowledge associated with the cue concept—can affect how we access and remember in detail autobiographical memories. In Experiment 1, we measured reaction times to access and retrieve memories in response to cue words. In Experiment 2 we examined the details with which participants described memories in response to cues. For both experiments, participants provided estimates of lifetime exposure and semantic knowledge associated with each cue. In Experiment 1, we found lifetime exposure, independently of estimates of semantic knowledge, led to quicker memory access and in Experiment 2, we found both lifetime exposure and semantic knowledge interactively enhanced the ability to described detailed memories. These results provide new evidence that distinct features of familiar cues—lifetime exposure and semantic knowledge—differently contribute to how autobiographical memories are retrieved and described.
The Socio-economic, Demographic, and Contextual Predictors of Malnutrition among Children aged 6-59 months in Nigeria
Authors: Obasohan Phillips Edomwonyi , Walters Stephen J. , Jacques Richard , Khatab Khaled 
Published: July 2023

Abstract
Malnutrition has remained a global public health issue, particularly in low- and middle-income countries (LMICs). Researchers have committed to studying malnutrition (especially in children under the age of five) to address the nine malnutrition targets, set by the WHO to be achieved by 2025. With barely three years to the end of target date, there is so much yet undone to meet the target especially in developing countries. In fact, there can be no effective interventions without a strong evidence base. This study seeks to evaluate the prevalence of malnutrition among children aged 6–59 months across Nigeria and its states, as well as its individual and contextual factors. Two separates, independently collected, nationally representative cross-sectional surveys, the National Human Development Report (NHDR 2018) and the 2018 Nigeria Demographic and Health Survey (2018 NDHS) were linked for the study. Spatial map was used to describe the prevalence of malnutrition, a 3-level multivariate multilevel logistic regression models were fitted where children/individuals (at level 1) were nested in communities/clusters (at level 2) and nested in states (at level 3). The results showed that an estimated 43.6% of children aged 6–59 months are poorly nourished in Nigeria. The proportions of poorly nourished children were generally highest in the Northern Nigeria. Child’s gender, age, birth size, preceding birth order, anaemia status, maternal education, work status, body weight, household wealth status, number of bedrooms were among individual/household predictors of malnutrition. On the community level, being from community with high wealth index, distance to nearest health facilities is no big problem. Regional variations and gender inequality index were state level predictors of malnutrition among children in Nigeria. This study has shown that two-third of children aged 6–59 months in Nigeria were poorly nourished. The high rates of constant insecurities that have distorted farming activities in the northern part of the country should be addressed urgently.