bluuebunny/crossref_metadata_2025_split huggingface dataset:
A prediction model of rubber content in the dried root of Taraxacum kok-saghyz Rodin based on near-infrared spectroscopy
Authors: Chen Runfeng , Yan Qingqing , Tuoheti Tuhanguli , Xu Lin , Gao Qiang , Zhang Yan , Ren Hailong , Zheng Lipeng , Wang Feng , Liu Ya 
Published: May 2024

Abstract
Background
Taraxacum kok-saghyz Rodin (TKS) is a highly potential source of natural rubber (NR) due to its wide range of suitable planting areas, strong adaptability, and suitability for mechanized planting and harvesting. However, current methods for detecting NR content are relatively cumbersome, necessitating the development of a rapid detection model. This study used near-infrared spectroscopy technology to establish a rapid detection model for NR content in TKS root segments and powder samples. The K445 strain at different growth stages within a year and 129 TKS samples hybridized with dandelion were used to obtain their near-infrared spectral data. The rubber content in the root of the samples was detected using the alkaline boiling method. The Monte Carlo sampling method (MCS) was used to filter abnormal data from the root segments of TKS and powder samples, respectively. The SPXY algorithm was used to divide the training set and validation set in a 3:1 ratio. The original spectrum was preprocessed using moving window smoothing (MWS), standard normalized variate (SNV), multiplicative scatter correction (MSC), and first derivative (FD) algorithms. The competitive adaptive reweighted sampling (CARS) algorithm and the corresponding chemical characteristic bands of NR were used to screen the bands. Partial least squares (PLS), random forest (RF), Lightweight gradient augmentation machine (LightGBM), and convolutional neural network (CNN) algorithms were employed to establish a model using the optimal spectral processing method for three different bands: full band, CARS algorithm, and chemical characteristic bands corresponding to NR. The model with the best predictive performance for high rubber content intervals (rubber content > 15%) was identified.

Result
The results indicated that the optimal rubber content prediction models for TKS root segments and powder samples were MWS–FD CASR–RF and MWS–FD chemical characteristic band RF, respectively. Their respective $${\text{R}}_{{\text{P}}}^{2}$$

R

P

2

, RMSEP, and RPDP values were 0.951, 0.979, 1.814, 1.133, 4.498, and 6.845. In the high rubber content range, the model based on the LightGBM algorithm had the best prediction performance, with the RMSEP of the root segments and powder samples being 0.752 and 0.918, respectively.

Conclusions
This research indicates that dried TKS root powder samples are more appropriate for constructing a rubber content prediction model than segmented samples, and the predictive capability of root powder samples is superior to that of root segmented samples. Especially in the elevated rubber content range, the model formulated using the LightGBM algorithm has superior predictive performance, which could offer a theoretical basis for the rapid detection technology of TKS content in the future.
Compression algorithm for colored de Bruijn graphs
Authors: Rahman Amatur , Dufresne Yoann , Medvedev Paul 
Published: May 2024

AbstractA colored de Bruijn graph (also called a set of k-mer sets), is a set of k-mers with every k-mer assigned a set of colors. Colored de Bruijn graphs are used in a variety of applications, including variant calling, genome assembly, and database search. However, their size has posed a scalability challenge to algorithm developers and users. There have been numerous indexing data structures proposed that allow to store the graph compactly while supporting fast query operations. However, disk compression algorithms, which do not need to support queries on the compressed data and can thus be more space-efficient, have received little attention. The dearth of specialized compression tools has been a detriment to tool developers, tool users, and reproducibility efforts. In this paper, we develop a new tool that compresses colored de Bruijn graphs to disk, building on previous ideas for compression of k-mer sets and indexing colored de Bruijn graphs. We test our tool, called ESS-color, on various datasets, including both sequencing data and whole genomes. ESS-color achieves better compression than all evaluated tools and all datasets, with no other tool able to consistently achieve less than 44% space overhead. The software is available at http://github.com/medvedevgroup/ESSColor.
Hierarchical Identity-Based Authenticated Encryption with Keyword Search over encrypted cloud data
Authors: Shiraly Danial , Eslami Ziba , Pakniat Nasrollah 
Published: May 2024

AbstractWith the rapid development of cloud computing technology, cloud storage services are becoming more and more mature. However, the storage of sensitive data on remote servers poses privacy risks and is presently a source of concern. Searchable Encryption (SE) is an effective method for protecting sensitive data while preserving server-side searchability. Hierarchical Public key Encryption with Keyword Search (HPEKS), a new variant of SE, allows users with higher access permission to search over encrypted data sent to lower-level users. To the best of our knowledge, there exist only four HPEKS schemes in the literature. Two of them are in traditional public-key setting, and the remaining ones are identity-based public key cryptosystems. Unfortunately, all of the four existing HPEKS schemes are vulnerable against inside Keyword Guessing Attacks (KGAs). Moreover, all of the existing HPEKS schemes are based on the computationally expensive bilinear pairing operation which dramatically increases the computational costs. To overcome these issues, in this paper, we introduce the notion of Hierarchical Identity-Based Authenticated Encryption with Keyword Search (HIBAEKS). We formulate a security model for HIBAEKS and propose an efficient pairing-free HIBAEKS scheme. We then prove that the proposed HIBAEKS scheme is secure under the defined security model and is resistant against KGAs. Finally, we compare our proposed scheme with related constructions regarding security requirements, computational and communication costs to indicate the overall superiority of our proposed scheme.
A modified persian version of the self-stigma of depression scale among the Iranian population: a methodological study in 2023
Authors: Jafari Alireza , Moshki Mahdi , Naddafi Fatemehzahra , Lael-Monfared Elaheh , Nejatian Mahbobeh 
Published: May 2024

Abstract
Introduction
This cross -sectional research evaluated the psychometric properties of the Self-Stigma of Depression Scale (SSDS) among Iranian people.

Methods
This methodological study was conducted among 881 people in 2023, Iran. The method of proportional stratified sampling was used to select participants. To evaluate the validity, face, content, construct, convergent, and discriminant were evaluated. The reliability of SSDS was assessed with the McDonald’s omega coefficient, Cronbach α coefficient, and test– retest (Intraclass Correlation Coefficient).

Results
In confirmatory factor analysis, the factor loading of all items of SSDS was more than 0.5, and two items had low factor loading. After deleted these items, goodness of fit indexes (such as GFI = 0.945, RMSEA = 0.067, AGFI = 0.917, CFI = 0.941, RFI = 0.905) confirmed the final model with 14 items and four factors of social inadequacy (3 items), help-seeking inhibition (4 questions), self-blame (3 questions), and shame (4 questions). In the reliability phase, for all items of SSDS, Cronbach α coefficient was 0.850, the McDonald omega coefficient was 0.853, and the intraclass correlation coefficient was 0.903.

Conclusion
The Persian form of SSDS was approved with 14 items and four factors: social inadequacy, help-seeking inhibition, self-blame, and shame. This tool can be used to check the status of self-stigmatization of depression in different groups.
The sense of coherence scale: psychometric properties in a representative sample of the Czech adult population
Authors: Tušl Martin , Šípová Ivana , Máčel Martin , Cetkovská Kristýna , Bauer Georg F. 
Published: May 2024

AbstractBackgroundSense of coherence (SOC) is a personal resource that reflects the extent to which one perceives the world as comprehensible, manageable, and meaningful. Decades of empirical research consistently show that SOC is an important protective resource for health and well-being. Despite the extensive use of the 13-item measure of SOC, there remains uncertainty regarding its factorial structure. Additionally, a valid and reliable Czech version of the scale is lacking. Therefore, the present study aims to examine the psychometric properties of the SOC-13 scale in a representative sample of Czech adults.MethodsAn online survey was completed by 498 Czech adults (18–86 years old) between November 2021 and December 2021. We used confirmatory factor analysis to examine the factorial structure of the scale. Further, we examined the variations in SOC based on age and gender, and we tested the criterion validity of the scale using the short form of the Mental Health Continuum (MHC) scale and the Generalized Anxiety Disorder (GAD) scale as mental health outcomes.ResultsSOC-13 showed an acceptable one- and three-factor fit only with specified residual covariance between items 2 and 3. We tested alternative short versions by systematically removing poorly performing items. The fit significantly improved for all shorter versions with SOC-9 having the best psychometric properties with a clear one-factorialstructure. We found that SOC increases with age and males score higher than females. SOC showed a moderately strong positive correlation with MHC, and a moderately strong negative correlation with GAD. These findings were similar for all tested versions supporting the criterion validity of the SOC scale.ConclusionOur findings suggest that shortened versions of the SOC-13 scale have better psychometric properties than the original 13-item version in the Czech adult population. Particularly, SOC-9 emerges as a viable alternative, showing comparable reliability and validity as the 13-item version and a clear one-factorial structure in our sample.
A TVP-VAR assessment of the spillover effects of geopolitical risk shocks on macroeconomic variability: a study of the Ghanaian economy
Authors: Asomaning Kwame Ofori , Hamayoon Shah , Uche Emmanuel 
Published: May 2024

AbstractOur study verified the implications of the spillover of geopolitical risk (GPR) shocks to the economic crisis in Ghana. Our analysis employed the VAR-based spillover models by Diebold and Yilmaz (Int J Forecast 28:57–66, 2012; J Econ 182:119–134, 2014) and the Time-Varying Parameter Vector Autoregressive (TVP-VAR) connectedness approach by Gabauer and Antonakakis (Munich personal RePEc archive refined measures of dynamic connectedness based on TVP-VAR refined measures of dynamic connectedness based on TVP-VAR*, 2017). We scrutinized the interconnections and transmission mechanisms among key macro-financial variables spanning from 2000 to 2022. Our findings indicate that GPR is a fundamental source of shocks to the foreign exchange reserve (FXI), real exchange rate (REER), consumer price index (CPI), and debt. Other significant contributors include export (EXP) and import (IMP), with EXP standing out as the main shock transmitter. On the receiving end, CPI is most impacted by transmissions from IMP and GPR. Our study demonstrates that EXP and IMP are the top shock contributors, while FXI and CPI are the major recipients of these shocks. Such findings provide policymakers with valuable insights into the ramifications of geopolitical risk on the macroeconomic environment. Hence, policymakers are expected to provide necessary buffers to curb the influence of geopolitical risks on the economy.
Evaluation of sugar content and bioethanol production of Ethiopian local varieties “Nech Tinkish” and “Hawaye” sweet sorghum (Sorghum bicolor (L.))
Authors: Kasegn Melaku Mekonen , Simachew Addis , Redda Yisehak Tsegaye , Gebremedhn Hailay Mehari , Berhanu Addisu Desalegn , Mossa Mohammed Mebrahtu 
Published: May 2024

AbstractDiversifying the use of climate-smart crops such as sweet sorghum has the potential to solve integrated food, bioenergy, feed, and land management problems. The study’s purpose is to quantify the sugar content of Nech Tinkish (v1) and Hawaye (v2) Ethiopian sweet sorghum varieties and investigate the interaction effect of fermentation parameters to determine their capacity for ethanol production. Sweet sorghum varieties were analyzed to determine their difference in °Brix content by extracting their juices. The juice was clarified using milk lime. Its total soluble sugars, total carbohydrates, and reducing sugars were determined using a digital refractometer, phenol sulfuric acid, and 3,5-dinitrosalicylic acid, respectively. A completely randomized factorial was employed to evaluate ethanol production capacity, and the ethanol content was estimated using a potassium dichromate solution. The °Brix results revealed that v2 had a higher sugar concentration than v1. Additionally, the estimated carbohydrate content of the juice ranged from 37.402 to 157.641 g/L. The estimated reducing sugar also varied from 4.644 to 33.412 g/L. Therefore, the estimated reducing sugar showed the hydrolysis of sweet sorghum juice by invertase and sulfuric acid produced more fermentable sugars. Fermentation at 30 °C with pH 4.5 incubated for 4 days yields the highest ethanol, and v2 yields higher (15.31%) ethanol, compared to v1 produced 14.85%. This study showed a basis for the existence of two sugar-rich climate smart sweet sorghum varieties with an extraordinary amount of sugar used as a source of biofuel and food simultaneously in a single plot of land.
Green nanotechnology: illuminating the effects of bio-based nanoparticles on plant physiology
Authors: Verma Sunil Kumar , Kumar Prashant , Mishra Anshu , Khare Renu , Singh Devendra 
Published: May 2024

AbstractThe use of bio-based nanoparticles in agriculture has gained significant attention due to their potential to enhance plant development, growth, and differentiation. This review aims to provide a comprehensive overview of the impact of bio-based nanoparticles on plant physiology. In this review paper, the various types of bio-based nanoparticles, including cellulose, chitosan, and lignin nanoparticles, and their effects on plant growth and development were discussed. The mechanisms by which these nanoparticles interact with plants at the cellular and molecular levels were also examined. Furthermore, the potential applications of bio-based nanoparticles in agriculture, such as improving nutrient uptake, enhancing stress tolerance, and promoting sustainable crop production, are also highlighted. Overall, this review provides valuable insights into the potential benefits of utilizing bio-based nanoparticles for enhancing plant growth and development while also considering their potential environmental impacts.
Graphical Abstract
Advancements in the biopolymer films for food packaging applications: a short review
Authors: Shah Yasir Abbas , Bhatia Saurabh , Al-Harrasi Ahmed , Khan Talha Shireen 
Published: May 2024

AbstractPlastic-based films that are commonly used in the food packaging industry are tough to recycle due to their sorting issue and these films do not decay as they photodegrade into microplastics. These microplastics transport from the air and accumulate in soil, storm drains, and waterways. Recent initiatives in the food packaging industry have led to the development of edible and biodegradable films as sustainable alternatives to synthetic polymer-based plastics. These films, which are biocompatible, biodegradable, and serve as protective coatings on food surfaces, are designed to enhance shelf life by guarding against oxidation, moisture, and microbial spoilage. Recent advancements in polymeric films resulted in the development of high-performance, UV-blocking, nano-engineered, and intelligent pH-sensitive films, along with multilayer, heat-sealable, and active variants. These advanced materials not only prevent food deterioration but also facilitate the early detection of spoilage. However commercial success of these films which have been developed at a lab scale is still challenging due to unsatisfactory mechanical, barrier, thermal, and optical properties than synthetic films. Furthermore, an in-depth understanding related to human interaction, biodegradability, safety studies, scalability, and machinability is required to develop sustainable bioplastic films.
Graphical Abstract
An evaluation of the reliability of the Weather Research Forecasting (WRF) model in predicting wind data: a case study of Burundi
Authors: Placide Gatoto , Lollchund Michel Roddy 
Published: May 2024

Abstract
Background
The Weather Research and Forecasting (WRF) Model is an exceptional software for mesoscale climate modeling. It is extensively used to simulate key meteorological variables, including temperature, rainfall, and wind.

Methods
This study thoroughly examined the effectiveness of the WRF model in generating precise wind data for assessing the potential of wind power in Burundi. A meticulous evaluation of various combinations of model physics parameterization schemes was conducted to ensure accuracy.
By comparing the simulated data with measurements from four meteorological stations and utilizing statistical metrics such as root-mean-square error (RMSE) and bias, the accuracy of the WRF model was determined.

Results
The findings of the study uncovered that utilizing WRF Single-Moment 3-Class (WSM3) for microphysics, Grell-Devenyi ensemble for cumulus physics, and Yonsei University for planetary boundary layer yields highly accurate wind data results for Burundi.
Furthermore, the WRF model was utilized to create detailed seasonal and annual mean wind maps with a high resolution.

Conclusion
These maps demonstrated that the western part of Burundi experiences higher wind speeds (ranging from 4 to 9.7 m/s) during the dry seasons revealing the potential for wind energy harvesting in the different areas of Burundi.
Comparative survival analysis of patients with HER2-low and HER2-positive metastatic breast cancer with or without brain metastases treated with trastuzumab deruxtecan.
Authors: Podder Vivek , Ranjan Tulika , Bardhan Mainak , McCracken Andrea , Hurmiz Charlie , Ganiyani Mohammad Arfat , Ahmad Shahzaib , Mahtani Reshma L. , Ahluwalia Manmeet Singh 
Published: May 2024

1036 Background: Breast cancer outcomes vary among HER2-amplified and HER2 low-expression patients, particularly in the presence of brain metastases (BM). Trastuzumab deruxtecan (T-DXd) is FDA approved for the treatment of adult patients with unresectable or metastatic human epidermal growth factor receptor 2 (HER2)-low and HER2-positive (HER2+) patients (pts). This study aims to evaluate the impact of T-DXd treatment on overall survival among HER2 low and HER2-positive metastatic breast cancer (MBC) patients with and without brain metastases (BM). Methods: A retrospective analysis was conducted by using de-identified data available from seven US-based health systems part of Guardian Research Network (GRN). Patients treated with T-DXd from December 2019 to December 2023 with a diagnosis of HER2 low (immunohistochemistry [IHC] 1 + or IHC 2+/negative with HER2 FISH non-amplified) and HER2+ (IHC 3+ or HER2+ and FISH amplified MBC were included. Median overall survival (mOS), calculated from the initiation of T-DXd treatment, was assessed using Kaplan-Meier Curve analysis and Log-rank test. Results: A total of 380 MBC pts were identified. Among these 231 (61.1%) were stratified as having HER2 low and 149 (38.9%) HER2+ MBC. Pts with HER2+ disease had a higher prevalence of BM (n=70; 47%) compared to HER2-low pts (n=55;23.8%). The median age at BM diagnosis was 60.5 years, range: 21.6 to 87.1 years. Within the entire BM group (n=125), there were more pts with ER+ disease (81.9%) in the HER2 low group compared to HER2+ group (55.8%, p=0.01). The majority of these patients had multiple prior lines of therapy. HER2+ BM pts had a median overall survival (mOS) of 9.3 months [CI: 6.79-11.88, log rank p <0.001], compared to 4.3 months [CI: 1.89-6.82, log rank p <0.001] in the HER2-low pts. Without BM, HER2+ pts had a mOS of 10.7 months [CI: 0.71-20.82, log rank p <0.001], compared to 6 months [CI: 3.47-8.67, log rank p <0.001] in the HER2-low pts. Conclusions: In this retrospective study of heavily pretreated MBC patients with multiple prior lines of therapy, pts with HER2+ MBC with and without BM had a longer mOS compared to those with HER2- low disease, suggesting HER2 expression as a key determinant of T-DXd efficacy. Poor survival in MBC patients without BM was attributed to pre-treatment with multiple lines of therapy. Future research should explore combination therapies and predictive biomarkers while conducting clinical trials to optimize treatment strategies for HER2+ metastatic breast cancer patients.
Dissecting racial/ethnic disparities in non-small cell lung cancer staging at diagnosis: Intra-ethnic and geographic differences.
Authors: Liu Qinran , Koru-Sengul Tulay , Lopes Gilberto , Pinheiro Paulo S. 
Published: May 2024

1575 Background: Lung cancer outcomes significantly rely on accurate and early detection. This population-based study aims to identify factors contributing to disparities in the stage of non-small cell lung cancer (NSCLC) diagnoses, focusing on Hispanic ethnic subgroups. Methods: Incident cases diagnosed from 2005–2018 were extracted from the Florida State Cancer Registry. Stage was categorized as resectable (Stage I-IIIA) or nonresectable (Stage IIIB/IIIC/IV) NSCLC. Multivariable logistic regression models were used to assess the association between race/ethnicity and stage at diagnosis, adjusted for socioeconomic, smoking status, and clinical factors. Regional stratification involved separate analyses for heavily Hispanic South Florida and the rest of Florida. Results: Among 157,034 NSCLC patients, with a racial distribution of 81.0% White, 8.3% Black, and 9.2% Hispanic, 43.2% were diagnosed at a resectable stage. Age-adjusted models showed Black patients had 22% higher odds (odds ratio [OR]=1.22; 95% CI: 1.21-1.23) and Hispanic patients had 11% higher odds (OR=1.11; 95% CI: 1.10-1.12) of non-resectable stage across all subgroups diagnoses compared to White patients. However, after further adjustment, higher odds were significant only for NHB (ORadj=1.12; 95% CI: 1.11-1.14) and Central American Hispanics (ORadj=1.41; 95% CI: 1.35-1.47). Regional differences were significant, with Hispanic patients in South Florida showing more favorable staging outcomes than Whites (ORadj=0.95; 95% CI: 0.94-0.97), while in the rest of Florida, Hispanic patients were at a disadvantage (ORadj=1.09; 95% CI: 1.07-1.10). Conclusions: Pronounced NSCLC staging disparities are manifest in Black and Hispanic populations, coupled with striking regional variations among Florida's Hispanic groups which underscores the necessity for targeted research to dissect and address the underlying causes of these inequities in the cancer care continuum.