bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictors of Interruptions in Antiretroviral Therapy among People Living with HIV in Nigeria: A Retrospective Cohort Study Using the Nigeria National Data Repository
Authors: Ikpe Sunday , Gambo Aliyu , Nowak Rebecca , Sorkin John , Charurat Manhattan , O’Connor Timothy , Stafford Kristen 
Published: March 2024

AbstractThis study aimed to identify predictors of time to first interruption in treatment (IIT) and predictors of ever being interrupted in ART treatment among PLHIV in Nigeria using a national longitudinal dataset that covers all PEPFAR-funded implementing partners to inform national strategies to prevent IIT. This retrospective cohort study used data from Nigeria’s National Data Repository (NDR). The NDR is a de-identified longitudinal database of over 1.9 million PLHIV who received ART in Nigeria beginning in 2004 and is owned by the Federal Ministry of Health (FMoH). The NDR contains patient-level demographics, clinic visits, laboratory, and ART prescription and refill data uploaded at least monthly. The data extracted for this study were obtained from electronic medical record systems of 2,226 public facilities offering HIV care in the country. In this study, we investigated the predictors of treatment interruption using data from the national HIV treatment program. We identified sets of predictors of first interruption in treatment using the logistic regression and these to be consistent in predicting time to first interruption including sex, non NRTI drug in ART regimen, recorded HIV viral load, recorded CD4 cell count, WHO clinical staging, functional status, last measured weight, highest education attained, occupation, marital status, year enrolled in care, pre and post surge, pre and post-COVID and residing in a state capital, Lagos, FCT (urban) versus other locations (rural). Age grouping was the only variable that was predictive only for time to first interruption but not for having a first interruption. To reduce the risk of IIT it is important to target interventions preemptively. We have highlighted the need for tailored interventions that address the unique needs of PLHIV in Nigeria. Targeted interventions focusing on those with a combination of risk factors could include education, counseling, supportive services, and monitoring and outreach.
A Regularized Cox Hierarchical Model for Incorporating Annotation Information in Predictive Omic Studies
Authors: Shen Dixin , Lewinger Juan Pablo , Kawaguchi Eric 
Published: March 2024

AbstractBackgroundAssociated with high-dimensional omics data there are often “meta-features” such as biological pathways and functional annotations, summary statistics from similar studies that can be informative for predicting an outcome of interest. We introduce a regularized hierarchical framework for integrating meta-features, with the goal of improving prediction and feature selection performance with time-to-event outcomes.MethodsA hierarchical framework is deployed to incorporate meta-features. Regularization is applied to the omic features as well as the meta-features so that high-dimensional data can be handled at both levels. The proposed hierarchical Cox model can be efficiently fitted by a combination of iterative reweighted least squares and cyclic coordinate descent.ResultsIn a simulation study we show that when the external meta-features are informative, the regularized hierarchical model can substantially improve prediction performance over standard regularized Cox regression. We illustrate the proposed model with applications to breast cancer and melanoma survival based on gene expression profiles, which show the improvement in prediction performance by applying meta-features, as well as the discovery of important omic feature sets with sparse regularization at meta-feature level.ConclusionsThe proposed hierarchical regularized regression model enables integration of external meta-feature information directly into the modeling process for time-to-event outcomes, improves prediction performance when the external meta-feature data is informative. Importantly, when the external meta-features are uninformative, the prediction performance based on the regularized hierarchical model is on par with standard regularized Cox regression, indicating robustness of the framework. In addition to developing predictive signatures, the model can also be deployed in discovery applications where the main goal is to identify important features associated with the outcome rather than developing a predictive model.
Scalable summary statistics-based heritability estimation method with individual genotype level accuracy
Authors: Jeong Moonseong , Pazokitoroudi Ali , Liu Zhengtong , Sankararaman Sriram 
Published: March 2024

AbstractSNP heritability, the proportion of phenotypic variation explained by genotyped SNPs, is an important parameter in understanding the genetic architecture underlying various diseases and traits. Methods that aim to estimate SNP heritability from individual genotype and phenotype data are limited by their ability to scale to Biobank-scale datasets and by the restrictions in access to individual-level data. These limitations have motivated the development of methods that only require summary statistics. While the availability of publicly accessible summary statistics makes them widely applicable, these methods lack the accuracy of methods that utilize individual genotypes.Here we present a SUMmary statistics-based Randomized Haseman-Elston regression (SUM-RHE), a method that can estimate the SNP heritability of complex phenotypes with accuracies comparable to approaches that require individual genotypes, while exclusively relying on summary statistics. SUM-RHE employs Genome-Wide Association Study (GWAS) summary statistics and statistics obtained on a reference population, which can be efficiently estimated and readily shared for public use. Our results demonstrate that SUM-RHE obtains estimates of SNP heritability that are substantially more accurate compared to other summary statistic methods and on par with methods that rely on individual-level data.
Nucleomorph phylogenomics suggests a deep and ancient origin of cryptophyte plastids within Rhodophyta
Authors: Novak Lukas V. F. , Muñoz-Gómez Sergio A. , van Beveren Fabian , Ciobanu Maria , Eme Laura , López-García Purificación , Moreira David 
Published: March 2024

AbstractThe evolutionary origin of red algae-derived complex plastids remains obscure. Cryptophyta, one of four eukaryotic lineages harboring these plastids, still contain nucleomorphs, highly reduced remnants of red algal nuclei. The genes present on nucleomorph genomes can be used for phylogenomic reconstruction in order to unravel the evolutionary origin of all red complex plastids and provide data independent from previously analyzed plastid-encoded datasets. Here, we leverage these genes in a first attempt at pinpointing the position of cryptophyte nucleomorphs within a comprehensive diversity of Rhodophyta, including new sequence representatives from seven deep-branching red algae. Our analyses place cryptophyte nucleomorphs as sister to the extremophilic subphylum Cyanidiophytina. This conflicts with published analyses based on plastidial genes that placed red complex plastids closer to the mesophilic Rhodophytina. Our results reject a nucleomorph origin within any known subgroup of Rhodophyta, instead suggesting a deep and possibly freshwater origin of complex red plastids.
Defect-Induced Low-Energy Majorana Excitations in the Kitaev Magnet
α−RuCl3
Authors: Imamura K. , Mizukami Y. , Tanaka O. , Grasset R. , Konczykowski M. , Kurita N. , Tanaka H. , Matsuda Y. , Yamada M. G. , Hashimoto K. , Shibauchi T. 
Published: March 2024

The excitations in the Kitaev spin liquid (KSL) can be described by Majorana fermions, which have characteristic field dependence of bulk gap and topological edge modes. In the high-field state of layered honeycomb magnet α−RuCl3, experimental results supporting these Majorana features have been reported recently. However, there are challenges due to sample dependence, and the impact of inevitable disorder on the KSL is poorly understood. Here, we study how low-energy excitations are modified by introducing point defects in α−RuCl3 using electron irradiation, which induces site vacancies and exchange randomness. High-resolution measurements of the temperature dependence of specific heat C(T) under in-plane fields H reveal that, while the field-dependent Majorana gap is almost intact, additional low-energy states with C/T=A(H)T are induced by introduced defects. At low temperatures, we obtain the data collapse of C/T∼H−γ(T/H) expected for a disordered quantum spin system but with an anomalously large exponent γ. This leads us to find a power-law relationship between the coefficient A(H) and the field-sensitive Majorana gap. These results are consistent with the picture that the disorder induces low-energy linear Majorana excitations, which may be considered as a weak localization effect of Majorana fermions in the KSL.

Published by the American Physical Society
2024
Study on the urban digital transformation gyroscope model
Authors: Mei Yanshuang , Xu Xin , Zhang Xupin 
Published: March 2024

Purpose
Urban digital transformation has become a key strategy in global countries. This study aims to provide a comprehensive and dynamic exploration of the intrinsic traits associated with urban digital transformation, in order to yield detailed insights that can contribute to the formulation of well-informed decisions and strategies in the field of urban development initiatives.

Design/methodology/approach
Through analysis of parallels between urban digital transformation and gyroscope motion in physics, the study developed the urban digital transformation gyroscope model (UDTGM), which comprises of seven core elements. With the balanced panel dataset from 268 cities at and above the prefecture level in China, we validate the dynamic mechanism of this model.

Findings
The findings of this study underscore that the collaboration among infrastructure development, knowledge-driven forces and economic operations markedly bolsters the urban digital transformation gyroscope’s efficacy.

Practical implications
This research introduces a groundbreaking framework for comprehending urban digital transformation, potentially facilitating its balanced and systemic practical implementation.

Originality/value
This study pioneers the UDTGM theoretically and verifies the dynamic mechanism of this model with real data.
Effect of stress coping strategies on comfort foods consumption: evidence from older Americans
Authors: Shen Anyuan , Liu Shuguang 
Published: March 2024

PurposeComfort foods consumption and linkages to stress coping strategies have received little attention in the business research on food products and services. This paper aims to explore comfort foods consumption among older Americans and how stress-coping strategies are related to their consumption frequency and variety of comfort foods.Design/methodology/approachOlder Americans aged 50–99 years (N = 1,428) in the Health and Retirement Study were surveyed on their frequency and variety of comfort foods consumption and their consumption coping strategies. Data were analyzed and regression models were estimated.FindingsDemographically, baby boomer, male, and non-Hispanic whites reported higher frequency and variety of comfort foods consumption. Comfort foods consumption in frequency and variety was significantly higher (lower) when “eat more” (“use alcohol”) was the endorsed coping strategy.Originality/valueResearch findings furthered research on the consumption of comfort foods among older American adults and added new insights into their coping behavior, both of which may help businesses be more targeted in serving comfort foods to the mature market and the public sector to tailor their services to older adults.
From carbon-neutral to climate-neutral supply chains: a multidisciplinary review and research agenda
Authors: Guntuka Laharish , Mukandwal Prabhjot S. , Aktas Emel , Paluvadi Vamsi Sai Krishna 
Published: March 2024

PurposeWe conduct a multidisciplinary systematic literature review on climate neutrality in the supply chain. While carbon neutrality has gained prominence, our study argues that achieving carbon neutrality alone is not enough to address climate change effectively, as non-CO2 greenhouse gases (GHG) are potent contributors to global warming.Design/methodology/approachWe used multiple databases, including EBSCO, ProQuest, Science Direct, Emerald and Google Scholar, to identify articles related to climate neutrality in the context of non-CO2 gases. A total of 71 articles in environmental science, climate change, energy systems, agriculture and logistics are reviewed to provide insights into the climate neutrality of supply chains.FindingsWe find that, in addition to CO2, other GHG such as methane, nitrous oxide, ozone and fluorinated gases also significantly contribute to climate change. Our literature review identified several key pillars for achieving net-zero GHG emissions, including end-use efficiency and electrification, clean electricity supply, clean fuel supply, “GHG capture, storage and utilization,” enhanced land sinks, reduced non-CO2 emissions and improved feed and manure management.Originality/valueWe contribute to the literature on climate neutrality of supply chains by emphasizing the significance of non-CO2 GHG along with CO2 and highlighting the need for a comprehensive approach to climate neutrality in addressing climate change. This study advances the understanding of climate neutrality of supply chains and contributes to the discourse on effective climate change mitigation strategies. It provides clear future research directions.
Does future tuna landing stock meet the target? Forecasting tuna landing in Malaysia using seasonal ARIMA model
Authors: Nasir Aslina , Kamaruzzaman Yeny Nadira 
Published: March 2024

PurposeThis study was conducted to forecast the monthly number of tuna landings between 2023 and 2030 and determine whether the estimated number meets the government’s target.Design/methodology/approachThe ARIMA and seasonal ARIMA (SARIMA) models were employed for time series forecasting of tuna landings from the Malaysian Department of Fisheries. The best ARIMA (p, d, q) and SARIMA(p, d, q) (P, D, Q)12 model for forecasting were determined based on model identification, estimation and diagnostics.FindingsSARIMA(1, 0, 1) (1, 1, 0)12 was found to be the best model for forecasting tuna landings in Malaysia. The result showed that the fluctuation of monthly tuna landings between 2023 and 2030, however, did not achieve the target.Research limitations/implicationsThis study provides preliminary ideas and insight into whether the government’s target for fish landing stocks can be met. Impactful results may guide the government in the future as it plans to improve the insufficient supply of tuna.Practical implicationsThe outcome of this study could raise awareness among the government and industry about how to improve efficient strategies. It is to ensure the future tuna landing meets the targets, including increasing private investment, improving human capital in catch and processing, and strengthening the system and technology development in the tuna industry.Originality/valueThis paper is important to predict the trend of monthly tuna landing stock in the next eight years, from 2023 to 2030, and whether it can achieve the government’s target of 150,000 metric tonnes.
Fintech adoption and financial well-being of persons with disabilities: the mediating role of financial access, financial knowledge and financial behaviour
Authors: Gafoor Abdul , Amilan S. 
Published: March 2024

PurposeThe prime purpose of the study is to analyse the effect of fintech adoption on the financial well-being of persons with disabilities (PWDs), considering the intervening role of financial behaviour, financial access and financial knowledge.Design/methodology/approachA self-administered survey schedule collected primary data on fintech adoption and financial well-being among 205 PWD, through snowball sampling from January to May 2023. Researchers used exploratory factor analysis to identify reliable factors and PLS-SEM for testing mediation and research hypotheses.FindingsThe study’s outcome found that fintech adoption does not directly impact the financial well-being of PWDs. Instead, the impact on financial well-being is explained by mediating factors like financial access, financial knowledge and financial behaviour. Financial access is the most significant among these mediating factors.Research limitations/implicationsThe study demonstrates the significance of mediating factors in comprehending the influence of fintech adoption on financial well-being. These results underpin existing literature on determinants of financial well-being.Practical implicationsFindings evidenced that developing disabled-friendly fintech tools can enhance financial access, reduce inequality and improve the financial well-being of PWDs, which would be helpful for public policymakers.Originality/valueThere has been no comprehensive study conducted on this topic, particularly among PWDs. In the current study, an effort is being made to examine the relative effects of fintech adoption on financial well-being directly and indirectly through mediating variables.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2023-0596
Responsible living labs: what can go wrong?
Authors: Habibipour Abdolrasoul 
Published: March 2024

Purpose
This study aims to investigate how living lab (LL) activities align with responsible research and innovation (RRI) principles, particularly in artificial intelligence (AI)-driven digital transformation (DT) processes. The study seeks to define a framework termed “responsible living lab” (RLL), emphasizing transparency, stakeholder engagement, ethics and sustainability. This emerging issue paper also proposes several directions for future researchers in the field.

Design/methodology/approach
The research methodology involved a literature review complemented by insights from a workshop on defining RLLs. The literature review followed a concept-centric approach, searching key journals and conferences, yielding 32 relevant articles. Backward and forward citation analysis added 19 more articles. The workshop, conducted in the context of UrbanTestbeds.JR and SynAir-G projects, used a reverse brainstorming approach to explore potential ethical and responsible issues in LL activities. In total, 13 experts engaged in collaborative discussions, highlighting insights into AI’s role in promoting RRI within LL activities. The workshop facilitated knowledge sharing and a deeper understanding of RLL, particularly in the context of DT and AI.

Findings
This emerging issue paper highlights ethical considerations in LL activities, emphasizing user voluntariness, user interests and unintended participation. AI in DT introduces challenges like bias, transparency and digital divide, necessitating responsible practices. Workshop insights underscore challenges: AI bias, data privacy and transparency; opportunities: inclusive decision-making and efficient innovation. The synthesis defines RLLs as frameworks ensuring transparency, stakeholder engagement, ethical considerations and sustainability in AI-driven DT within LLs. RLLs aim to align DT with ethical values, fostering inclusivity, responsible resource use and human rights protection.

Originality/value
The proposed definition of RLL introduces a framework prioritizing transparency, stakeholder engagement, ethics and sustainability in LL activities, particularly those involving AI for DT. This definition aligns LL practices with RRI, addressing ethical implications of AI. The value of RLL lies in promoting inclusive and sustainable innovation, prioritizing stakeholder needs, fostering collaboration and ensuring environmental and social responsibility throughout LL activities. This concept serves as a foundational step toward a more responsible and sustainable LL approach in the era of AI-driven technologies.
Engage to co-create! The drivers of brand co-creation on social commerce
Authors: Nibras Saiyara , Gunawan Tjong Andreas , Tan Garry Wei-Han , Lo Pei-San , Aw Eugene Cheng-Xi , Ooi Keng-Boon 
Published: March 2024

PurposeConsumers nowadays are no longer bystanders in the process of production but are proactive collaborators with the power to co-create value with brands. This study aims to explore the impact of social commerce on the co-creation process of brand value in a social commerce setting.Design/methodology/approachA questionnaire survey was conducted online to gather 300 eligible responses. The data were empirically validated using the partial least squares structural equation modelling (PLS-SEM) method.FindingsThe results indicated that brand engagement (BEN) is vital to brand co-creation (BCC) in social commerce, which could be driven by social-hedonic value (SHV) and social information sharing (SIS).Research limitations/implicationsThis study stresses the influence of consumer autonomy in the process of BCC by probing the role of SIS. Moreover, by considering the prevailing trend in social media, this study offers a nuanced perspective on the values of social commerce from the viewpoint of SHV.Practical implicationsThis study may serve as a useful guide for practitioners to improve their digital outreach strategy on social commerce to forge stronger relationships, encourage further engagements and promote value co-creation within their brand community.Originality/valueThis examines the effect of relationship quality (RQU) and BEN on BCC through a relational viewpoint.
For sustained digital advantage, find a huge customer problem and create the processes that will solve it
Authors: Wood Robert Chapman 
Published: March 2024

Purpose
New technologies may offer special opportunities for others to achieve very large returns with approaches to technology development like those of Amazon, Tesla, and Walmart. This paper summarizes those firms' overall approach and offers guidelines for carrying out similar efforts.

Design/methodology/approach
The paper is a multi-firm case study, examining long-term technology development processes of Amazon, Tesla, Walmart, Varian Medical, and Deere.

Findings
The firms were able to create huge amounts of value (or in Deere's case, seems to be creating a huge amount of value today) because their leaders recognized a huge problem that limited customers greatly and spent decades solving it with digital technology. The approach appears to be replicable by others.

Research limitations/implications
This is an initial review. Further study of these firms and others that have similar long-term digital achievements is warranted.

Practical implications
The paper describes a practical approach to achieving sustained competitive advantage that may be effective for those willing to pursue solution to a large problem over many years.

Originality/value
The most successful users of digital technology have followed a difficult but straightforward path to revolutionizing customer experience: Focus for decades on making something important work really well. This paper identifies similarities among the long-term strategies of the greatest producers of long-term value for the first time and identifies a path through which others may follow them.