bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aripiprazole once monthly as a maintenance treatment for patients with schizophrenia and alcohol/substance use disorder: an observational, real-world study
Authors: Chiappini Stefania , Mosca Alessio , Miuli Andrea , Di Carlo Francesco , d'Andrea Giacomo , Napolitano Alessandra , Santangelo Monica , Esposito Corradina , Rosazza Anna , Haefele Elena , Di Petta Gilberto , Pettorruso Mauro , Sensi Stefano L. , Martinotti Giovanni 
Published: June 2023

Purpose
This paper aims to investigate the role of aripiprazole once monthly as a maintenance treatment in a sample of patients with schizophrenia comorbid with alcohol and substance use disorder (AUD/SUD).

Design/methodology/approach
A sample of 24 Italian adult patients has been recruited and treated with aripiprazole once monthly after clinical stabilization with oral aripiprazole during May 2021 and June 2022. Clinical evaluations have been performed at the baseline (T0) and after 12 (T1) and 24 (T2) weeks.

Findings
During the study period, an improvement of both the clinical condition and general health from baseline was observed, as well as a reduction of craving for alcohol/substances. However, from T0, the number of patients who continued with this study decreased at T1 (n = 8) and then at T2 (n = 4). No serious adverse events were reported, including changes in weight, lipid/glucose metabolism, electrocardiogram and extra-pyramidal side effects.

Originality/value
Although limited by the high number of drop outs, this observational real-world study provided insights into the use of aripiprazole once monthly among a sample of patients with schizophrenia and comorbid SUD/AUD. Further studies of longer duration and on a larger sample are needed.
A multi-level modeling approach for predicting real-estate dynamics
Authors: Gude Vinayaka 
Published: June 2023

Purpose
This research developed a model to understand and predict housing market dynamics and evaluate the significance of house permits data in the model’s forecasting capability.

Design/methodology/approach
The research uses a multilevel algorithm consisting of a machine-learning regression model to predict the independent variables and another regressor to predict the dependent variable using the forecasted independent variables.

Findings
The research establishes a statistically significant relationship between housing permits and house prices. The novel approach discussed in this paper has significantly higher prediction capabilities than a traditional regression model in forecasting monthly average prices (R-squared value: 0.5993), house price index prices (R-squared value: 0.99) and house sales prices (R-squared value: 0.7839).

Research limitations/implications
The impact of supply, demand and socioeconomic factors will differ in various regions. The forecasting capability and significance of the independent variables can vary, but the methodology can still be applicable when provided with the considered variables in the model.

Practical implications
The resulting model is helpful in the decision-making process for investments, house purchases and construction as the housing demand increases across various cities. The methodology can benefit multiple players, including the government, real estate investors, homebuyers and construction companies.

Originality/value
Existing algorithms and models do not consider the number of new house constructions, monthly sales and inventory in the real estate market, especially in the United States. This research aims to address these shortcomings using current socioeconomic indicators, permits, monthly real estate data and population information to predict house prices and inventory.
Uncovering the gamified customer experience in the retail environment
Authors: Disse Isabel Kittyma , Olsson Marcus 
Published: June 2023

PurposeRetailers increasingly are using gamification to make the customer experience (CX) more exciting and encourage favourable customer outcomes. This paper aims to conceptualise the gamified customer experience (GCX), including relevant affordances, and investigate its effects on key customer outcomes, as well as its influential factors.Design/methodology/approachThe authors conducted a qualitative interview study with retail customers and gamification experts, plus a scenario-based experiment to test the hypotheses.FindingsFive distinct affordances induced by game elements in retail have led to a more exciting CX. The connections between these affordances and the holistic CX have led to a GCX that influences customer engagement, satisfaction and brand attitude. This effect is dependent on different factors, e.g. retail brand personality, customers' shopping motivation and fear of manipulation.Originality/valueThis study contributes to retail research by conceptualising the GCX phenomenon and providing a summary of relevant affordances. It further provides insights into the GCX's effects on customer outcomes and influential factors, some of which have been ignored in previous research.
Drivers and consequences of strategic leader indecision: an exploratory study in a complex case
Authors: Motloung Musa , Lew Charlene 
Published: June 2023

PurposeThe research explores indecision of strategic leaders in a complex case organization. This research offers new insights into the drivers of indecision of upper echelons decision-makers and explores the perceived consequences of the decision-makers' indecision.Design/methodology/approachFollowing a review of literature on upper echelons theory and strategic decision-making, indecision and the antecedents and consequences of indecision, the research follows a qualitative exploratory design. Semi-structured interviews were conducted among 20 upper echelons decision-makers with responsibility across 19 Sub-Saharan African countries in a case company. Thematic analysis was used to analyze the data.FindingsThe findings reveal that specific organizational, interpersonal and personal factors work together to drive strategic leader indecision in a complex organization. Strategic leader indecision brings about several negative organizational consequences and demotivates team members.Research limitations/implicationsThe findings are based on a single-case exploratory design but represent geographical diversity.Practical implicationsThe research cautions organizations to deal with the drivers of strategic leader indecision to help avoid potential negative consequences of stifled organizational performance and team demotivation.Originality/valueThe study offers previously unknown insights into strategic leader indecision. This study builds on current literature on the antecedents and consequences of indecision and has a new research setting of strategic leader indecision in a complex organization.
Additive manufacturing of Inconel-625: from powder production to bulk samples printing
Authors: Ur Rehman Asif , Karakas Burak , Mahmood Muhammad Arif , Başaran Berkan , Ur Rehman Rashid , Kirac Mertcan , Khraisheh Marwan , Salamci Metin Uymaz , Ünal Rahmi 
Published: June 2023

Purpose
For metal additive manufacturing, metallic powders are usually produced by vacuum induction gas atomization (VIGA) through the breakup of liquid metal into tiny droplets by gas jets. VIGA is considered a cost-effective technique to prepare feedstock. In VIGA, the quality and the morphology of the produced particles are mainly controlled by the gas pressure used during powder production, keeping the setup configuration constant.

Design/methodology/approach
In VIGA process for metallic additive manufacturing feedstock preparation, the quality and morphology of the powder particles are mainly controlled by the gas pressure used during powder production.

Findings
In this study, Inconel-625 feedstock was produced using a supersonic nozzle in a close-coupled gas atomization apparatus. Powder size distribution (PSD) was studied by varying the gas pressure.

Originality/value
The nonmonotonic but deterministic relationships were observed between gas pressure and PSD. It was found that the maximum 15–45 µm percentage PSD, equivalent to 84%, was achieved at 29 bar Argon gas pressure, which is suitable for the LPBF process. Following on, the produced powder particles were used to print tensile test specimens via LPBF along XY- and ZX-orientations by using laser power = 475 W, laser scanning speed = 800 mm/s, powder layer thickness = 50 µm and hatch distance = 100 µm. The yield and tensile strengths were 9.45% and 13% higher than the ZX direction, while the samples printed in ZX direction resulted in 26.79% more elongation compared to XY-orientation.
Exploring the relationship between digital trails of social signals and bitcoin returns
Authors: Yelkenci Tezer , Dobrucalı Yelkenci Birce , Vardar Gülin , Aydoğan Berna 
Published: June 2023

Purpose
This study aims to empirically investigate the linkages between digital trails of social signals (content and profile features of bitcoin-related tweets) and bitcoin price return using a VAR-BEKK-GARCH model.

Design/methodology/approach
Bitcoin-related tweets were collected every hour for six months from September 1, 2020, to February 29, 2021. The analysis involved two steps: first, examining tweet content, profiles, sentiment and emotions; and second, investigating the relationship between social signal volatility and hourly bitcoin price return.

Findings
Results indicate that bitcoin price changes can impact the sentiment expressed in tweets about bitcoin, and vice versa. While sadness exhibits a bidirectional volatility spillover with bitcoin, fear and anger display a one-period lag. Quartile analyses reveal that only fear in the second quartile shows a bidirectional spillover effect with bitcoin, while all other emotions except sadness demonstrate a unidirectional spillover effect in all remaining quartiles.

Originality/value
The study uses a novel two-step approach to analyze volatility spillovers between social signals and bitcoin price returns. Findings can guide investors and portfolio managers in making better allocation decisions and assist policymakers and regulators in reducing the adverse effects of bitcoin’s volatility on financial system stability.
Simultaneous random noise attenuation and three‐dimensional seismic‐data interpolation with faster adaptive rank reduction
Authors: Wang Jianhua , Wang Yandong , Niu Cong , Sun Wenbo 
Published: June 2023

AbstractRank‐reduction‐based simultaneous random noise attenuation and three‐dimensional seismic‐data interpolation has recently become a hot topic in reflection seismology. However, the rank of traditional methods is fixed without considering the variation of signal‐to‐noise ratio on different frequency components, leading to serious residual noise and further affecting the following processing and interpretation tasks. In addition, traditional methods also heavily rely on the application of singular value decomposition technique for rank reduction, which is proven to be computationally expensive for large‐scale data. Thus, a fast‐adaptive rank‐reduction method is proposed in this study. First, the information entropy theory is introduced to adaptively select the optimal rank at various frequencies by calculating the increment of singular entropy. Second, we propose a fast Random Block Krylov algorithm and a subspace multiplexing technique to replace the singular value decomposition algorithm used in traditional methods. The proposed method can significantly improve computational efficiency and yield better seismic‐data reconstruction performance than traditional methods. Applications of the proposed approach on both synthetic and field seismic data demonstrate its superior performance over a well‐known rank‐reduction‐based method, that is the random multi‐channel singular spectrum analysis, in terms of recovered signal‐to‐noise ratio and visual view.
A meta‐analysis reveals that dragonflies and damselflies can provide effective biological control of mosquitoes
Authors: Priyadarshana Tharaka S. , Slade Eleanor M. 
Published: June 2023

AbstractDragonfly/damselfly naiads have the potential to control mosquitoes, and indirectly the diseases they carry, due to their extensive predation on mosquito larvae. Experimental studies have measured the effectiveness of individual dragonfly/damselfly naiads in controlling mosquitoes by introducing them to mosquito larvae and counting the number of larvae eaten in a given time period (i.e. predation success).Without a quantitative synthesis, however, such individual measures are unable to provide a generalized estimation about the effectiveness of dragonflies/damselflies as biological mosquito control agents. To achieve this, we assembled a database containing 485 effect sizes across 31 studies on predation successes of 47 species of commonly found dragonfly/damselfly naiads on nine species of mosquito larvae belonging toAedes,AnophelesandCulex. These studies covered 14 countries across Asia, Africa and South and North America, where mosquitoes are the vectors of Chikungunya, Dengue, Japanese encephalitis, Lymphatic filariasis, Malaria, Rift Valley fever, West Nile fever, Yellow fever and Zika.Using this database, we conducted a meta‐analysis to estimate the average predation success per day by a single individual dragonfly/damselfly naiad on these mosquito larvae as a generalized measure of the effectiveness of dragonflies/damselflies for mosquito control. We also built an interaction network for predator‐dragonflies/damselflies and prey‐mosquitoes and the diseases they vector to understand the functioning of this important predator‐prey network.Our results showed that mosquito larvae were significantly reduced through predation by dragonfly/damselfly naiads. Within experimental containers, a single individual dragonfly/damselfly naiad can eat on average 40 (95% confidence intervals [CIs] = 20, 60) mosquito larvae per day, equivalent to a reduction of the mosquito larval population by 45% (95% CIs = 30%, 59%) per day. The average predation success did not significantly vary amongAedes,AnophelesandCulexmosquitoes or among the four (I–IV) mosquito larval stages.These results provide strong evidence that dragonflies/damselflies can be effective biological control agents of mosquitoes, and environmental planning to promote them could lower the risk of spreading mosquito‐borne diseases in an environmentally friendly and cost‐effective manner.
The implications of seasonal climatic effects for managing disturbance dependent populations under a changing climate
Authors: Hindle Bethan J. , Quintana‐Ascencio Pedro F. , Menges Eric S. , Childs Dylan Z. 
Published: June 2023

Abstract

The frequency of ecological disturbances, such as fires, is changing due to changing land use and climatic conditions. Disturbance‐adapted species may thus require the manipulation of disturbance regimes to persist.

However, the effects of changes in other abiotic factors, such as climatic conditions, are frequently disregarded in studies of such systems. Where climatic effects are included, relatively simple approaches that disregard seasonal variation in the effects are typically used.

We compare predictions of population persistence using different fire return intervals (FRIs) under recent and predicted future climatic conditions for the rare fire‐dependent herb Eryngium cuneifolium. We used functional linear models (FLMs) to estimate the cumulative effect of climatic variables across the annual cycle, allowing the strength and direction of the climatic impacts to differ over the year. We then estimated extinction probabilities and minimum population sizes under past and forecasted future climatic conditions and a range of FRIs.

Under forecasted climate change, E. cuneifolium is predicted to persist under a much broader range of FRIs, because increasing temperatures are associated with faster individual growth. Climatic impacts on fecundity do not result in a temporal trend in this vital rate due to antagonistic seasonal effects operating through winter and summer temperatures. These antagonistic seasonal climatic effects highlight the importance of capturing the seasonal dependence of climatic effects when forecasting their future fate.

Synthesis. Awareness of the potential effects of climate change on disturbance‐adapted species is necessary for developing suitable management strategies for future environmental conditions. However, our results suggest that widely used simple methods for modelling climate impacts, that disregard seasonality in such effects, may produce misleading inferences.
Determinants of stillbirths in sub‐Saharan Africa: A systematic review
Authors: Mukherjee Ankita , Di Stefano Lydia , Blencowe Hannah , Mee Paul 
Published: June 2023

AbstractBackgroundSub‐Saharan African (SSA) countries have high stillbirth rates compared with high‐income countries, yet research on risk factors for stillbirth in SSA remain scant.ObjectivesTo identify the modifiable risk factors of stillbirths in SSA and investigate their strength of association using a systematic review.Search StrategyCINAHL Plus, EMBASE, Global Health and MEDLINE databases were searched for literature.Selection CriteriaObservational population‐ and facility‐level studies exploring stillbirth risk factors, published in 2013–2019 were included.Data Collection and AnalysisA narrative synthesis of data was undertaken and the potential risk factors were classified into subgroups.Main ResultsThirty‐seven studies were included, encompassing 20 264 stillbirths. The risk factors were categorised as: maternal antepartum factors (0–4 antenatal care visits, multiple gestations, hypertension, birth interval of >3 years, history of perinatal death); socio‐economic factors (maternal lower wealth index and basic education, advanced maternal age, grand multiparity of ≥5); intrapartum factors (direct obstetric complication); fetal factors (low birthweight and gestational age of <37 weeks) and health systems factors (poor quality of antenatal care, emergency referrals, ill‐equipped facility). The proportion of unexplained stillbirths remained very high. No association was found between stillbirths and body mass index, diabetes, distance from the facility or HIV.ConclusionsThe overall quality of evidence was low, as many studies were facility based and did not adjust for confounding factors. This review identified preventable risk factors for stillbirth. Focused programmatic strategies to improve antenatal care, emergency obstetric care, maternal perinatal education, referral and outreach systems, and birth attendant training should be developed. More population‐based, high‐quality research is needed.
FOXA1‐induced LINC00621 promotes lung adenocarcinoma progression via activating the TGF‐β signaling pathway
Authors: Wei Jingjing , Yu Haiyang , Liu Tan , Wang Ziming , Lang Chuandong , Pan Yueyin 
Published: June 2023

AbstractBackgroundLung adenocarcinoma (LUAD) is highly malignant and associated with poor prognoses in patients worldwide. There has been widespread recognition that lncRNAs are tightly linked to LUAD tumorigenesis and development. Here, we identified that the LINC00621 level was increased in LUAD tissues and concerned with the poor prognoses in LUAD patients.MethodsBioinformatical analysis and RT‐qPCR determined the level of LINC00621 in LUAD tissues and cell lines. The admeasurement of the proliferation, migration, and invasion abilities of LUAD cells was utilized in the CCK8 and Transwell formulas. Luciferase reporter assay was used to corroborate the downstream target genes of LINC00621. The phosphorylated SMAD3 protein was tested by Western blotting assay. The impression of LINC00621 knockdown on LUAD tumor growth and metastasis put into effect by murine models. ChIP‐qPCR assay was carried out to verify the transcriptional regulation by FOXA1 on LINC00621.ResultsIn vitro, the knockdown of LINC00621 significantly reduced the proliferative, migrating, and invasive abilities, the same was true for tumorigenesis and metastasis in vivo. MiR‐34a‐5p as a straight target of LINC00621 was ascertained, and LUAD patients with inferior miR‐34a‐5p levels had undesirable prognoses. Furthermore, TGFBR1 is an immediate and functional connection site of miR‐34a‐5p. Collectively, LINC00621 can sponge miR‐34a‐5p and upregulate TGFBR1 levels, which further sensitized TGF‐β signaling pathway. Finally, it was revealed that FOXA1 transcriptionally upregulated LINC00621.ConclusionThis study uncovered that FOXA1‐induced LINC00621 promotes LUAD progression via the miR‐34a‐5p/TGFBR1/TGF‐β axis, and is one novel therapeutic target that may be used in LUAD treatment.
A species richness estimator for sample‐based incidence data sampled without replacement
Authors: Chiu Chun‐Huo 
Published: June 2023

Abstract

The accurate estimation of species richness in a target region is still a statistical challenge, especially in a highly heterogeneous community. Most richness estimators have been developed based on the assumption that data are randomly sampled with replacement or that data are sampled from an infinite population. However, in reality, most sampling schemes in the field are implemented as sampling without replacement (SWOR). As such, estimators derived based on sampling with replacement may cause overestimation as the sampling fraction increases and not converge to the true richness as the sampling fraction approaches one. Sample‐based incidence data, in which the sampling unit is a plot, and only the presence or absence of a species in each chosen plot is recorded, is one of the most commonly used data types for assessing species diversity in ecological studies.

In this manuscript, according to sample‐based incidence data collected through SWOR, a new richness estimator is proposed using a truncated beta‐binomial mixture model. The new estimator was obtained through the moment approach, which avoids using iterative numerical algorithms for parameter estimation and presents a closed‐form estimator as an alternative to the maximum likelihood method. Although the newly proposed method is a parametric‐based richness estimator, similar to nonparametric estimators, only the rare species in the sample (i.e. the frequencies of uniques and duplicates) are required to estimate undetected richness.

Based on the hypothetical models, the statistical performances of the proposed estimator are evaluated under varying degrees of heterogeneity and different mean species detection rates. Compared to other widely used nonparametric and parametric estimators, the simulation results indicate that the proposed estimator has a smaller bias and lower root mean square error when the sampling fraction is greater than 10%, particularly in highly heterogeneous communities.

In addition, one ForestGEO permanent forest plot dataset is used to evaluate and compare the proposed approach with other estimators discussed in the study. The results demonstrate that the proposed estimator, in comparison to other widely used estimators, produces less biased estimate of true richness, along with more accurate 95% confidence interval.