bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blockchain in the age of industrial revolution: A systematic literature review using bibliometric analysis
Authors: Gupta Rishabh , Meena Abhilasha , Dhir Sanjay 
Published: December 2023

AbstractThe emergence of blockchain technology has spurred research and industrial advances, presenting potential benefits and practical solutions for various industries and their communities. Blockchain technology enables the efficient distribution, sharing, and secure storage of transactional data, leading to increased transparency and productivity in supply chains. While blockchain is seen as a disruptive technology, it is essential to explore its applicability to various industries. To this end, this study conducts a bibliometric analysis of the extant blockchain literature to better understand its potential applications. The study presents a systematic literature review that highlights the practical application of blockchain technology transfer in various industries, such as pharmaceuticals, banking and financial services, and media and entertainment.
The Middle‐Out Approach to reconceptualizing, assessing, and analyzing traumatic stress reactions
Authors: Adams Shane W. , Layne Christopher M. , Contractor Ateka A. , Allwood Maureen A. , Armour Chérie , Inslicht Sabra S. , Maguen Shira 
Published: December 2023

AbstractAlternative models of traumatic stress and broader psychopathology have been proposed to address issues of heterogeneity, comorbidity, clinical utility, and equitable representation. However, systematic and practical methods and guidelines to organize and apply these models remain scarce. The Middle‐Out Approach is a novel, integrative, contextually informed framework for organizing and applying existing empirical methods to evaluate current and alternative traumatic stress reactions. Rather than beginning to identify traumatic stress reactions from the top‐down (i.e., disorder‐first approach) or bottom‐up (i.e., symptom‐first approach), constructs are evaluated from the middle out (i.e., presentation‐first approach), unconstrained by higher‐order disorders or lower‐order diagnostic symptoms. This approach provides innovation over previous methods at multiple levels, including the conceptualization of traumatic stress reactions as well as the type of assessments and data sources used and how they are used in statistical analyses. Conceptualizations prioritize the identification of middle‐order phenotypes, representing person‐centered clinical presentations, which are informed by the integration of multidimensional, transdiagnostic, and multimodal (e.g., psychosocial, physiological) assessments and/or data sources. Integrated data are then analyzed concurrently using person‐centered statistical models to identify precise, discrete, and representative health outcomes within broader heterogeneous samples. Subsequent variable‐centered analyses are then used to identify culturally sensitive and contextually informed correlates of phenotypes, their clinical utility, and the differential composition within and between broader traumatic stress reactions. Examples from the moral injury literature are used to illustrate practical applications that may increase clinical utility and the accurate representation of health outcomes for diverse individuals and communities.
Spectrally Efficient Integrated Silicon Photonic Phase‐Diverse DD Receiver with Near‐Ideal Phase Response for C‐Band DWDM Transmission
Authors: Zhang Jinsong , Li Xueyang , Hu Yixiang , Alam Md Samiul , Plant David V. 
Published: December 2023

AbstractIn this paper, a spectrally efficient silicon photonics phase‐diverse direct‐detection receiver based on asymmetric self‐coherent detection is proposed. The receiver is hardware efficient and composed of only two photodiodes and two analog‐to‐digital channels to accurately recover complex double‐sideband signals by leveraging an optimized integrated silicon racetrack resonator with near‐ideal phase responses. Moreover, the periodicity of the resonator response enables the receiver to support multi‐channel transmission such as dense wavelength‐division multiplexing. The receiver circuit is fabricated and characterized. In 40‐km transmission experiments, a record net electrical spectral efficiency of 7.10 bit s−1Hz−1per wavelength and per polarization is achieved, where a net 208‐Gb s−132QAM transmission is demonstrated using 29.3‐GHz electrical bandwidth. Furthermore, the receiver achieves net 220‐Gb s−116QAM transmissions in 14 channels from 1527 to 1550 nm with 205‐GHz spacing, and a maximum 240‐Gb s−1net capacity at a single channel. Such a performance is reached with only standard coherent digital signal processing stacks including all‐linear equalization.
Approach to consider self‐corrosion in corrosion monitoring of reinforced concrete structures exposed to chlorides
Authors: Fraundorfer Andreas , Dauberschmidt Christoph , Gehlen Christoph 
Published: December 2023

AbstractCorrosion processes of steel in concrete contaminated with chlorides take place as macrocell corrosion as well as self‐corrosion (i.e., microcell corrosion). While macrocell corrosion can be detected by element current measurement, self‐corrosion cannot be precisely determined electrochemically. This results in deviations in corrosion investigations between the mass losses calculated coulometrically from macrocell current measurements and the actual, corrosion‐related gravimetric mass losses. This is relevant in practice as part of corrosion monitoring. In the following, a simple approach is presented by considering this self‐corrosion current mathematically in the macrocell current measurement. The empirical regression functions determined for this purpose can be applied to a large number of different influencing parameters and allow the determination of the cumulative steel degradation at time‐varying macrocell current densities under consideration of different safety levels. This allows a much more accurate estimation of the actual corrosion‐induced mass losses during corrosion monitoring than previously possible.
Cathepsin V is correlated with the prognosis and tumor microenvironment in liver cancer
Authors: Liu Junyu , Zhang Wen , Wang Zhijie , Wang Yichuan , Li Tianxing , Wang Yaping , Ding Jin , Ning Beifang 
Published: December 2023

AbstractRecent studies have shown that high cell cycle activity negatively correlates with antitumor immunity in certain cancer types. However, a similar correlation has not been proven in liver cancer. We downloaded transcriptomic profiles of the cancer genome atlas‐liver hepatocellular carcinoma (TCGA‐LIHC) and assessed the cell cycle distribution of samples using single sample gene set enrichment analysis (ssGSEA), termed the cell cycle score (CCS). We obtained cell cycle‐related differentially expressed prognostic genes and identified CENPA, CDC20, and CTSV using LASSO regression. We studied the effect of CTSV on clinical features and immune alterations in liver cancer based on TCGA‐LIHC data. In vitro and in vivo experiments were performed to validate the role of CTSV in liver cancer using liver cancer cell lines and tissues. We found that the CCS closely correlated with the clinical features and prognosis of patients in TCGA‐LIHC. Analysis of differentially expressed genes (DEGs), univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression identified cathepsin V (CTSV) with prognostic significance in LIHC. Importantly, single‐gene survival analysis of CTSV using microarray and sequencing data indicated that high levels of CTSV expression correlated with an unfavorable prognosis in various cancers. Gene set enrichment analysis revealed that high CTSV expression closely correlated with decreased expression of metabolic genes and increased expression of cell cycle genes. Furthermore, difference and correlation analyses of the relationship between CTSV expression and immune infiltrates, determined using CIBERSORT and TIMER algorithms, revealed that CTSV expression correlated with macrophages and CD4+ T cells. In vitro and in vivo experiments revealed that knockdown of CTSV inhibited liver cancer cells proliferation. Immunohistochemical staining showed that high CTSV expression correlated with macrophage infiltration in liver cancer tissues, predicted a poor prognosis, and is associated with the effectiveness of hepatocellular carcinoma treatment. In couclusion, CTSV is a novel cell cycle‐associated gene with clinical significance in HCC.
Calculation method and mathematical model of projectile echo power of active laser detection target
Authors: Tong Xiaogang , Li Hanshan , Zhang Xiaoqian 
Published: December 2023

AbstractTo meet the requirements for parameter testing within the projectile test system, a computational model for calculating the echo power of the projectile passing through the detection screen based on the principle of active laser detection target is established in this paper. On the basis of the fundamental formula of echo energy in laser detection, and by combining the energy distribution function of the detection screen, the light scattering cross‐section formula specific to the projectile, and the illuminated area formula when the projectile intersects the detection screen, the formula for calculating the echo power of projectile is derived and analyzed. Furthermore, taking into account the parameters of the laser detection target, a computational model is constructed to calculate the voltage amplitude associated with the echo power of the projectile. Combining the atmospheric transmission optical characteristics, distance variations, and changes in the projectile's reflection attitude in the test environment, we conducted a simulation analysis to assess the accuracy of the established calculation model. Additionally, experimental analysis of the echo power calculation model was performed. In both simulation and experimental analyses, the trends in the impact of atmospheric transmission optical characteristics, distance conditions, and changes in projectile attitude upon the calculation of projectile echo power were consistent. Moreover, the width of the projectile echo waveform obtained in experiments was equal to the calculated projectile duration time. These research findings can serve as a reference basis for the development of theories in laser detection target.
A longitudinal investigation of job demands‐resources theory in volunteer firefighters working for the nonprofit sector
Authors: Huynh Jasmine , Xanthopoulou Despoina , Windsor Tim 
Published: December 2023

AbstractMany nonprofit emergency service organizations rely heavily on volunteers. With the recent decline in volunteer numbers and the associated economic cost, it is important for nonprofit organizations to develop strategies aimed at improving volunteer retention. To this end, we applied job demands‐resources theory to examine how volunteer demands and resources explain volunteers' well‐being (i.e., exhaustion and engagement) and consequently, retention and mental health (i.e., depressive symptoms). Specifically, we hypothesized that: (1) exhaustion mediates the positive relationship between demands and depressive symptoms, and the negative relationship between demands and retention; (2) engagement mediates the positive relationship between resources and retention; (3) resources buffer the positive relationship between demands and exhaustion; and (4) demands boost the positive relationship between resources and engagement. Volunteer firefighters (N = 126) were asked to complete a self‐report questionnaire twice over a 1‐year period. Results showed that increases in engagement mediated the positive relationship between resources and retention over time. Contrary to expectations, volunteer resources boosted the positive relationship between volunteer demands and increases in exhaustion. Namely, demands related positively with exhaustion particularly when resources were high (instead of low). Collectively, the study results have important theoretical implications since they suggest that demands do not always have long‐term, unfavorable consequences for volunteer firefighters. In contrast, resources enhance volunteer engagement and consequently, promote retention in the long run. Therefore, it is important for volunteer organizations to provide relevant resources to their members to keep them engaged and enhance their willingness to remain in the force.
Birds are not the only ones impacted by guidance to cease bird feeding
Authors: Dayer Ashley A. , Pototsky P. Christy , Hall Richard J. , Hawley Dana M. , Phillips Tina B. , Bonter David N. , Dietsch Alia M. , Greig Emma , Hochachka Wesley M. 
Published: December 2023

Abstract

Humans have a particularly strong connection with birds, driving the enormous popularity of residential bird feeding in much of the world.

We conducted a web search to document US state wildlife management agency responses to two recent avian disease outbreaks, finding that 23 agencies made recommendations to cease feeding wild birds in 2021–2022.

The psychological benefits of bird feeding for humans are well‐documented but often overlooked in management decisions in response to avian disease outbreaks.

Likewise, ecological evidence does not necessarily support ceasing bird feeding to reduce the spread of every avian disease.

Ecological and social science need to be applied in tandem to ensure that well‐intended guidance to cease feeding of birds does not have unintended consequences.
Predictors of social emotional learning in after‐school programming: The impact of relationships, belonging, and program engagement
Authors: Fisher Amy E. , Johnson Liat R. , Minnes Sonia , Miller Emily K. , Riccardi Jessica S. , Dimitropoulos Anastasia 
Published: December 2023

AbstractAfter‐school youth development programs support social‐emotional functioning which leads to better academic and behavioral outcomes. This article examines three common predictors of social‐emotional functioning individually and concurrently to better understand the role of these predictors in the after‐school setting. The common predictors are staff/student relationships, sense of belonging, and program engagement. That data came from 144, 3rd through 8th grade, students across 9 different elementary and middle school sites who regularly attended a large youth development program. Regression analyses were run and the results indicated that each variable was an individually significant predictor of social‐emotional functioning. Results from multiple regression analyses demonstrated that there was a better model fit when including all three variables in the same model. Interestingly, the results indicated that program engagement was a strong predictor above and beyond staff/student relationships and sense of belonging on self‐management and self‐efficacy. Sense of belonging and program engagement both predicted social awareness. Implications of these findings for after‐school program planning and development are discussed.
A systematic review of mixed methods studies published in six school psychology journals: Prevalence, characteristics, and trends from 2011 to 2020
Authors: Wang Jiayi , Hida Rahma M. , Park Jeongsoo , Kim Eui Kyung , Begeny John C. 
Published: December 2023

AbstractMixed methods (MM) designs have gained more recognition in psychology in recent years due to the complementary strengths of integrating both quantitative and qualitative approaches. The central elements of a MM design can be particularly useful in the field of school psychology, where both generalizations of group characteristics and exploration of individual perspectives are valued. Given the advantages of MM and their potential benefits in school psychology research, it is important to know the extent to which MM studies are published in school psychology journals and the general characteristics of such studies. This study examined articles published from 2011 to 2020 in six well‐known school psychology journals to (a) document the prevalence of MM articles published in each journal and in each year, (b) examine the characteristics of the identified MM studies, and (c) explore possible trends of MM publications in the 10‐year period. Findings revealed that although there is a significant increasing trend of MM studies published from the first 5 years (2011–2015) to the second 5 years (2016–2020), the percentage of MM studies is still very small in the journals assessed. Explanations, future study directions, and practical implications are provided to call for more attention and effort in facilitating the training and application of MM research.
The effect of perfectionism on relative deprivation among nursing students: The role of interpersonal sensitivity and resilience
Authors: Ding Yueming , Lu Guangli , Chen Shuyu , Liang Yipei , Zhang Yiming , Peng Qianwen , Liang Shuang , Chen Chaoran 
Published: December 2023

AbstractThis study investigated the relationship between perfectionism and relative deprivation among nursing students in China as well as the mediating role of interpersonal sensitivity and the moderating role of resilience in this relationship. A cross‐sectional study design involved 682 nursing students participants from two universities in Henan Province, China, using questionnaires about demographics, perfectionism, relative deprivation, interpersonal sensitivity, and resilience. Descriptive statistics, Pearson's correlation analysis and the PROCESS macro in regression analysis were used for data analysis. Adaptive perfectionism was not significantly correlated with relative deprivation, while maladaptive perfectionism was significantly positively correlated with interpersonal sensitivity, relative deprivation, and resilience. Interpersonal sensitivity mediated the relationship between maladaptive perfectionism and relative deprivation, accounting for 41.07% of the total effect. Moreover, the first half path and direct path of this process were moderated by resilience. These results show that targeted interventions to reduce maladaptive perfectionism, reduce interpersonal sensitivity and improve resilience of nursing students could help reduce their relative deprivation.
Exploring social and environmental predictors of school engagement among first‐ and second‐generation Latino youth: A multidimensional approach
Authors: Bjugstad Arlene , Cardoso Jodi Berger , Chen Tzuan A. , Brabeck Kalina M. , Borja Sharon 
Published: December 2023

AbstractUsing a multidimensional, integrative approach this study examined the influence of social position factors (nativity, economic hardship, and language) and environmental contexts (community trauma, geographic location, and discrimination) on three domains of school engagement (cognitive, behavioral, and relational) among a community sample of first‐ and second‐generation Latino adolescents. Findings from this study reveal that both social position and environmental contexts significantly and differentially predicted each of the three domains of school engagement. Participants (n = 306) included students from 11 high schools in two US cities. Fifty‐three percent were first‐generation immigrants and 80% were born, or had a parent from, Mexico or Central America. Results indicated that all three social position factors (nativity, economic hardship, and language) and two of the three environmental contexts (community trauma exposure and discrimination) significantly and differentially predicted each of the three domains of school engagement. Findings emphasize the direct effects of student's social positionality and environmental contexts on their engagement in school.
Prediction of interactions between cell surface proteins by machine learning
Authors: Su Zhaoqian , Griffin Brian , Emmons Scott , Wu Yinghao 
Published: December 2023

AbstractCells detect changes in their external environments or communicate with each other through proteins on their surfaces. These cell surface proteins form a complicated network of interactions in order to fulfill their functions. The interactions between cell surface proteins are highly dynamic and, thus, challenging to detect using traditional experimental techniques. Here, we tackle this challenge using a computational framework. The primary focus of the framework is to develop new tools to identify interactions between domains in the immunoglobulin (Ig) fold, which is the most abundant domain family in cell surface proteins. These interactions could be formed between ligands and receptors from different cells or between proteins on the same cell surface. In practice, we collected all structural data on Ig domain interactions and transformed them into an interface fragment pair library. A high‐dimensional profile can then be constructed from the library for a given pair of query protein sequences. Multiple machine learning models were used to read this profile so that the probability of interaction between the query proteins could be predicted. We tested our models on an experimentally derived dataset that contains 564 cell surface proteins in humans. The cross‐validation results show that we can achieve higher than 70% accuracy in identifying the PPIs within this dataset. We then applied this method to a group of 46 cell surface proteins in Caenorhabditis elegans. We screened every possible interaction between these proteins. Many interactions recognized by our machine learning classifiers have been experimentally confirmed in the literature. In conclusion, our computational platform serves as a useful tool to help identify potential new interactions between cell surface proteins in addition to current state‐of‐the‐art experimental techniques. The tool is freely accessible for use by the scientific community. Moreover, the general framework of the machine learning classification can also be extended to study the interactions of proteins in other domain superfamilies.
Phytochemicals in regulating PD‐1/PD‐L1 and immune checkpoint blockade therapy
Authors: Zhang Qi , Yang Chenying , Gao Xingsu , Dong Ju , Zhong Caiyun 
Published: December 2023

AbstractClinical treatment and preclinical studies have highlighted the role of immune checkpoint blockade in cancer treatment. Research has been devoted to developing immune checkpoint inhibitors in combination with other drugs to achieve better efficacy or reduce adverse effects. Phytochemicals sourced from vegetables and fruits have demonstrated antiproliferative, proapoptotic, anti‐migratory, and antiangiogenic effects against several cancers. Phytochemicals also modulate the tumor microenvironment such as T cells, regulatory T cells, and cytokines. Recently, several phytochemicals have been reported to modulate immune checkpoint proteins in in vivo or in vitro models. Phytochemicals decreased programmed cell death ligand‐1 expression and synergized programmed cell death receptor 1 (PD‐1) monoclonal antibody to suppress tumor growth. Combined administration of phytochemicals and PD‐1 monoclonal antibody enhanced the tumor growth inhibition as well as CD4+/CD8+ T‐cell infiltration. In this review, we discuss immune checkpoint molecules as potential therapeutic targets of cancers. We further assess the impact of phytochemicals including carotenoids, polyphenols, saponins, and organosulfur compounds on cancer PD‐1/programmed cell death ligand‐1 immune checkpoint molecules and document their combination effects with immune checkpoint inhibitors on various malignancies.