bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mamas in Harmony: protocol for a pilot RCT and process evaluation of a music and social support intervention establishing the feasibility of reducing anxiety and stress in postnatal mothers
Authors: Colella Corinna , McNeill Jenny , McCann Una , Lynn Fiona A. 
Published: May 2024

Abstract

Background
Postnatal mothers can experience anxiety, stress, and difficulty with mother-infant attachment with potential to lead to an anxiety disorder/depression. There has been an increase in interest in non-pharmacological interventions involving music, with limited evidence assessing effectiveness in this population within randomised controlled trials (RCTs). Mamas in Harmony is a novel music/social support intervention. The objective is to assess the feasibility/acceptability of conducting a full RCT to test the effect and cost-effectiveness of Mamas in Harmony compared with usual care.
Methods
The pilot RCT aims to recruit 60 mother-infant dyads through social media, community organisations and stakeholder networks, randomly allocated on a 2:1 ratio to the intervention and control group. The intervention group will receive eight one hour weekly Mamas in Harmony sessions plus usual care and the control group will receive usual care only. Feasibility measures include recruitment, retention, and attendance at intervention sessions. The process evaluation aims to establish acceptability of the intervention involving survey evaluation and semi-structured interviews. A priori guidelines have been agreed to establish criteria for progression to a definitive RCT.
Discussion
The current evidence supports the use of music in reducing anxiety and stress with the recommendation for inclusion of social support. This study has potential to provide robust evidence of the feasibility and acceptability of a music and social support mother-infant group intervention in preparation for a future definitive trial, should progression criteria be met.
Trial registration
ClinicalTrials.gov ID: NCT05930990. Registered retrospectively on 5 July 2023. Recruitment commenced on 16 March 2023. https://classic.clinicaltrials.gov/ct2/show/NCT05930990?term=music+and+social+support&draw=2&rank=1
Protocol version
30/10/2023 Vn 1.0
Land use and Land cover Analysis using Geographical information system (GIS) and Principal component analysis (PCA)
Authors: Raj Saket , Rawat Kishan Singh 
Published: May 2024

Abstract

Activities of humanoid made on Land Use (LU) indicate an effect on the Land Cover (LC) geographical and for the time being in the presently found in the surroundings. Changes are made continuously made in our study area which is identified by the use of Land-Use/Land-Cover. The purpose of finding areas to identified Land-Use/Land-Cover (LULC) transforms is to start relationships between significant activities, policy declarations, and associated LULC plans. In order to determine the type and extent of changes that have taken place, various dates of satellite photos are connected in a process known as identification of change. The use of LUL Cchange detection in "remote sensing" and “geographic information systems" (GIS) provides crucial learning tools. In order to resolve environmental issues, reliable data planned the evaluation of nature using various methodologies is crucial. By NDVI using as well as PCA parameter to measures land cover changes is main objective of this paper. Landsat 5 (TM) & Landsat 8, OLI/TIRS satellite images are used from 2000 to 2020 prove the thought of LC Change in Muzaffarpur region, Bihar. The four classes of LULC are known to produce the statistics of vegetation area, land area, water bodies, and Grass land. The research analysis revealed that vegetation is reduced about 28% where vegetation, land, Overall accuracy (OA) and kappa coefficient are improved, and Waterland grass and land are improved by 10%, 23%, and 1%, respectively.
Gold Nanosystem Catalyzed Precise Bromination of Aromatic Feedstock Enabled by Global-Vertexes Stabilization
Authors: Tang Cen , Wang Mengyue , Zhang Shengye , Gong Yue , Zhang Wangyang , Wang Yu , Zheng Qiang , Chen yupeng , Liu Zhi-Pan 
Published: May 2024

Abstract

Ligand advancements have propelled the development of sophisticated ligand strategies for nanocatalysis. These strategies offer the tantalizing prospect of nanoparticles to achieve remarkable selectivity for catalytic process. However, achieving electronic/steric control and realizing selectivity regulation in nanocatalysis remains a formidable challenge, as the dynamic nature of metal-ligand interfaces, including dissolution and structural reconstruction, poses significant obstacles. Herein, we disclose carboranyls (CBs) as carbon-bonded global vertexes coordinating ligands (Eads.c−Au(111) = -2.90 eV, Eads.BHs−Au(111) = -0.54 eV) for gold nanoparticles (AuNPs), showcasing their exceptional inherent stabilization capability and the unique core (Aun)-satellite (CB2Au−) structure of the resulting NPs. Leveraging these distinct features, CB@AuNPs accomplished regio-selective bromination of aromatic feedstocks including chlorobenzene (p:o > 30:1) and phenyl acrylate, a prominent transformation in chemical industry suffered from selectivity issue. Systematic investigations unveiled the advantages of CB@AuNPs, including: 1) the global coordinating capability of ligands in their vicinity, and 2) the presence of inert counterions. These characteristics enable selectivity regulation through counterion manipulation and harness the substituent effect arising from the stabilized catalytic micro-environment at nanoscale. The effective control of regio-selectivity achieved through the global coordination of carboranyls offers valuable insights into expanding current strategy with heterocatalysts via ligand approach.
Subcellular Systems Observe Onsager Reciprocity
Authors: Horowitz Arie 
Published: May 2024

Abstract

The complexity of prokaryotic and, exceedingly, of eukaryotic cells, challenges the implementation of methodologies to determine causality and quantify intracellular dynamics. Although stochastic thermodynamics can be used to effectively quantify the dynamics of single proteins or complexes, there is no statistical approach that can be used to generalize subcellular microstates to determine the macrostates of a whole cell. Onsager reciprocity, a coupling between thermodynamic flows, has not been used systematically to quantify and establish causality among cellular dynamics. A prototypical thermodynamic profile of the cell is formulated as a model system to enable representation of its dynamics as force-driven thermodynamic flows. The explanatory potential of the methodology of thermodynamic reciprocity is demonstrated on molecular mechanisms in which coupling between internal fluxes is evident. Its predictive potential is then tested against mechanisms wherein coupling is unacknowledged, ruling out reciprocity between the contractile ring of the bacterial ortholog of tubulin, which facilitates the separation of dividing Escherichia colicells, and the bacterial actin ortholog, which polymerizes along the cell walls. In contrast, reciprocity is identified, albeit with a large margin of error, between the actomyosin ring, which facilitates the division of fission yeast cells and treadmilling longitudinal microtubules. Directly pertinent to the definition of the cell's prototypical thermodynamic profile, the reciprocity that was suggested between AMP-regulated kinase (AMPK) and mechanistic target of rapamycin (mTORC1) in the regulation of the cell cycle is confirmed. These findings support wider implementation of thermodynamic reciprocity to quantify and establish causal relationships among cellular dynamics.
Investigation on Possibility of Mangrove Regeneration: A Case Study from Indian Sundarbans
Authors: Chatterjee Sweta , Bhandari Gupinath 
Published: May 2024

Abstract

Mangroves are the biotic fence of estuarine belts consisting of salt-tolerant trees and shrubs that grow in intertidal zones can be regenerated naturally as well as artificially. Mangrove regeneration refers to the process of restoring or rebuilding mangrove ecosystems that have been already degraded, damaged, or lost from their native place through the monitoring of geomorphological, taxonomical, pedological, ecological aspects. Primary objective of this study lays on the remote sensing application through several important health monitoring indices (NDVI, SAVI, OSAVI & VCCI) over the minute part of Indian Sundarbans to get proved on the possibility of mangrove regeneration. Change detection analysis on indices proves that there is possible growth and development in mangrove colonization over the same. Secondary objective is to comprehend the association of field related study with the remotely sensed data on species diversity assessment over the same where, the native species are Peyara Bain, Jat Bain, Kalo Bain, Tora, Horgoj Kanta, Kankra, Goran, Khalisi. Latter objective is associated with the tertiary one that unveils the correlation between several physico-chemical properties of soil samples taken from the field with the species accommodation. Textural classes are ranged between clay to silty clay that helps to get foundation of hard wood based species (Bain type) specifically with the salinity ranges between 200ppt (Site 2) to 633ppt (Site 1) approximately that presents the zone is highly saline zone as specifically Bain types can sustain high salinity. Importance Value Index (IVI) & species diversity indices have been run to support whether the zone is diversified or not. Equilibrium between deforestation and regeneration through reforestation has to be attained in near future as deforestation for the livelihood purposes exist so that this newly born island named Dorabagda forest, upper part (Gopalganj) of Kaikhali village would be the best example of mangrove regeneration site.
Refracturing time optimization considering the effect of induced stress by pressure depletion in the shale reservoir
Authors: Wang Qiang , Yang Yu , Wang Yufeng , Zhao Jinzhou , Zhao Jin , Jiang Fangfang 
Published: May 2024

Abstract

Refracturing is an important technology for tapping remaining oil and gas areas and enhancing recovery in old oilfields. However, a complete and detailed refracturing timing optimization scheme has not yet been proposed. In this paper, based on the finite volume method and the embedded discrete fracture model, a new coupled fluid-flow/geomechanics pore-elastic-fractured reservoir model is developed. The COMSOL commercial software was used to verify the accuracy of our model, and by studying the influence of matrix permeability, initial stress difference, cluster spacing and fracture half-length on the orientation of maximum horizontal stress, a timing optimization method for refracturing is proposed. The results of this paper show that the principle of optimizing the refracturing timing is to avoid the time window where the percentage of type-I (Type I indicates that stress inversion has occurred, \({0^ \circ } \leqslant \alpha \leqslant {20^ \circ }\); Type II indicates that the turning degree is strong, \({20^ \circ }<\alpha \leqslant {70^ \circ }\); and Type III indicates less stress reorientation, \({70^ \circ }<\alpha \leqslant {90^ \circ }\).) stress reorientation area is relatively large, so that the fractures can extend perpendicular to the horizontal wellbore. At the same time, the simulation results show that with the increase of production time, the percentage of type-I and type-II increases first and then decreases, while the percentage of type III decreases first and then increases. When the reservoir permeability, stress difference and cluster spacing are larger, the two types of refracturing measures can be implemented earlier. But With the increase of fracture half-length, the timing of refracturing method I is earlier, and the timing of refracturing method II is later. The research results of this paper are of great significance to the perfection of the refracturing theory and the optimization of refracturing design.
Effects of planned relocation on communities’ future coastal inundation risk
Authors: Bower Erica , Epifantseva Sonya , Schmitter Sydney , Wong-Parodi Gabrielle , Kulp Scott , Field Christopher 
Published: May 2024

Abstract

The planned, permanent relocation of entire communities away from areas facing sea level rise (SLR) and coastal floods is an increasingly recognized strategy for climate change adaptation. Yet, planned relocations may or may not reduce risk. We assess projections of future coastal flooding in all the completed or underway relocations that met our criteria for inclusion from a global dataset. Most of the 17 cases achieved exposure reduction with less future inundation in destinations than origin sites, but the extent varies across time and emissions scenario. In all cases, origin sites are projected to be exposed to SLR combined with a once-per-year flooding event. In nine cases, even destination sites are projected to be exposed to SLR plus a once-a-year flooding event under some scenarios. Small island-to-small island relocations had more projected inundation in destinations than moves from a small island-to-mainland, or from mainland-to-mainland.
Development of a Multimodal Deep Learning Model for Predicting Microsatellite Instability in Colorectal Cancer by Integrating Histopathological Images and Clinical Data
Authors: He Binsheng , Qiu Wenjing , Wang Bing , Yang Jingya , Mao Jinyang , Tian Geng , Xu Tao , He Jianjun , Wang Peizhen , Yang Jiasheng 
Published: May 2024

Abstract

Microsatellite instability (MSI) arises from defective DNA mismatch repair (MMR) systems and is prevalent in various cancer types. MSI is classified as MSI-High (MSI-H), MSI-Low (MSI-L), or Microsatellite Stable (MSS), with the latter two occasionally combined into a single designation called MSI-L/MSS. Identifying the MSI status (i.e., MSI-H vs. MSI-L/MSS) in colorectal cancer (CRC) is critical for guiding immunotherapy and assessing prognosis. Conventional molecular tests for MSI are expensive, time-consuming, and limited by experimental conditions. Advancements in MSI detection have been made using deep learning methods with histopathological images, yet efforts to improve MSI detection's predictive accuracy by integrating histopathological images and clinical data remain limited. This study initially analyzed clinical information variation between the MSI-H and MSI-L/MSS groups, discovering significant differences in cancer stages N and M. Subsequently, texture features were extracted using the Gray-level co-occurrence matrix (GLCM) from both groups, disclosing noteworthy disparities in mean feature information. Finally, a multimodal compact bilinear pool (MCB) was employed to merge histopathological images with clinical data. By applying this analysis framework to the cancer genome atlas (TCGA) CRC data, a prediction area under the curve (AUC) of 0.833 was achieved through 5-fold cross-validation in predicting MSI status. The results demonstrated higher accuracy in determining MSI compared to existing unimodal MSI prediction methods and other contemporary techniques. Additionally, significant regions in whole-slide images (WSI) for determining MSI labels were visualized. To summarize, this study presents an accurate multimodal deep learning model for predicting microsatellite instability in colorectal cancer by integrating histopathological images and clinical data, together with a method to visualize important regions in WSI to determine MSI status.
Design, synthesis and biological evaluation of new isoxazole derivatives as Hsp90 inhibitors
Authors: keshavarzipour fariba , Abbasi Maryam , Khorsandi Zahra , Ardestani Mina , Sadeghi-Aliabadi Hojjat 
Published: May 2024

Abstract

Heat shock protein 90 (Hsp90), a molecular chaperone, contributes to the preservation of folding, structure, stability, and function proteins. In this study, novel compounds comprising isoxazole structure were designed, synthesized and their potential ability as Hsp90 inhibitors was validated through docking studies. The active site-based compounds were prepared through a multi-step synthesis process and their chemical structures were characterized employing FT-IR, NMR, and mass spectrometry analysis. Cytotoxic and Hsp90 inhibition activities of synthesized compounds were assessed by MTT assay and ELISA kit, respectively. Based on the obtained results, compound 5 was the most cytotoxic derivative (IC50; 14 µM) against cancer cells and reduced Hsp90 expression from 5.54 ng/ml in untreated (normal cells) to 1.56 ng/ml in cancer cells. Moreover, molecular dynamics (MD) simulation results indicated its high affinity to target protein and approved its excellent stability which is essential for exerting an inhibitory effect on cancer cell proliferation.
Advancing Real-time Pandemic Forecasting Using Large Language Models: A COVID-19 Case Study
Authors: Yang Hao Frank , Du Hongru , Zhao Jianan , Zhao Yang , Xu Shaochong , Lin Xihong , Chen Yiran , Gardner Lauren 
Published: May 2024

Abstract

Forecasting the short-term spread of an ongoing disease outbreak is a formidable challenge due to the complexity of contributing factors, some of which can be characterized through interlinked, multi-modality variables such as epidemiological time series data, viral biology, population demographics, and the intersection of public policy and human behavior. Existing forecasting model frameworks struggle with the multifaceted nature of relevant data and robust results translation, which hinders their performances and the provision of actionable insights for public health decision-makers. Our work introduces PandemicLLM, a novel framework with multi-modal Large Language Models (LLMs) that reformulates real-time forecasting of disease spread as a text reasoning problem, with the ability to incorporate real-time, complex, non-numerical information -- such as textual policies and genomic surveillance data -- previously unattainable in traditional forecasting models. This approach, through a unique AI-human cooperative prompt design and time series representation learning, encodes multi-modal data for LLMs. By redefining the forecasting process as an ordinal classification task, PandemicLLM yields more robust and trustworthy predictions, facilitating public health decision-making. The model is applied to the COVID-19 pandemic, and trained to utilize textual public health policies, genomic surveillance, spatial, and epidemiological time series data, and is subsequently tested across all 50 states of the U.S. for a duration of 16 weeks. Empirically, PandemicLLM is shown to be a high-performing pandemic forecasting framework that effectively captures the impact of emerging variants and can provide timely and accurate predictions. The proposed PandemicLLM opens avenues for incorporating various pandemic-related data in heterogeneous formats and exhibits performance benefits over existing models. This study illuminates the potential of adapting LLMs and representation learning to enhance pandemic forecasting, illustrating how AI innovations can strengthen pandemic responses and crisis management in the future.
Menstrual hygiene management practice and associated factors among rural and urban primary school adolescent girls in Gondar city administration and Gondar zuriya district, northwest Ethiopia,2021
Authors: Kassa Woynareg , Mihiret Misganaw , Yenus Hedija 
Published: May 2024

Abstract

Background
Menstrual hygiene management is the practice done by girls or women through; using a clean material, changing a private way body using water with soap,and having disposal facilities. It is insufficiently acknowledged among adolescent school girls in Ethiopia. Therefore, understanding the level of hygiene management practice and identifying determinant factors is a crucial first step to taking appropriate interventions
Method
An -institution-based cross-sectional study design was employed among 335 urban adolescent girls from March to April 2021.Study participants were selected by using a multistage stratified sampling technique. Aninterviewer-administered structured questionnaire was used for data collection. The data were entered by using EPI INFO version 7.2 and analyzed by using STATA version 14.1 software.
Bivariate and multivariable logistic regression analysis with a 95% confidence interval was employed. A P-value< 0.05 was considered as statistically significant and AOR with a 95% confidence interval was considered to show the strength of the association.
Result
Overall, prevalence of menstrual hygiene practice among adolescents’ girls were 66.0% (95% CI: 60.7, 70.9) among urban school girls. urban residence [AOR= 3.41(95% CI: 1.1, 10.58), media exposure for SNP advertisement [AOR=2.43 (95%CI; 1.08, 5.48)], good menstrual knowledge [AOR=3.68 (95% CI: 1.76, 7.69)], female toilet inside locked [AOR=2.66 (95%CI; 1.1, 6.45)], girls who have private room at home [AOR=3.53(95% CI: 1.46, 8.5)], good water accessibility (AOR=3.35(95% CI:(1.62,6.95), gain information from friends [AOR=3.35(95%CI:1.04,10.77)] were found to be significantly associated with good MHP among overall school adolescent girls,
Conclusion
Though the overall prevalence of the study was low.it was relatively better among urban school girls. It shows a significant variation between the urban and rural study groups. Therefore,Implementation of girl friendly WASH services in all schools should be applied, health education should be strengthened, WASH facilities constructed at school levels, free discussion with parents and teachers in order to practice safe MHM.
The latitudinal migration of the sunspot groups
Authors: Takalo Jouni Juhani 
Published: May 2024

Abstract

We analyse the monthly sunspot group (SG) data for Solar Cycles C8 - C23 and calculate the average latitude of the drift path for the northern and southern hemisphere of the Sun. We find that exponential function fits slightly better than the second-order polynomial to the average drift of the SGs. The drift velocities are are 0.30 and 0.27 degrees/month (meridional speed approximately 1.41 and 1.27 m/s) in the beginning and 0.071 and 0.069 degrees/month (approximately 0.33 and 0.32 m/s) at the end of the average cycle for northern and southern hemisphere, respectively.
We do also bi-linear fits (first-order polynomial fits in two fractions), because they tell us the crossing point were the drift velocity changes the most. This crossing point for the Cycles C8 - C23 is at 50 months and 15.4 degrees of latitude for the northern hemisphere and 54 months and -14.4 degrees for the southern hemisphere. The drift velocities calculated from the slopes of the bi-linear fits are 0.233 and 0.216 degrees/month (approximately 1.10 and 1.02 m/s) before the crossing point and 0.118 and 0.101 degrees/month (approximately 0.55 and 0.47 m/s) after the crossing point.
We find a slight dependence of the migration on the strength of the cycle such that the drift path of the stronger cycles follow slightly higher latitudes than those of the weaker cycles. The areas of the sunspot groups affect also slightly to the drift path such that large area SGs have path at somewhat lower latitudes in the ascending phase and higher latitudes in the descending phase of the cycle than the smaller area SGs.