bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep Learning-Enhanced Portable Chemiluminescence Biosensor: 3D-Printed, Smartphone-Integrated Platform for Glucose Detection
Authors: Singhal Chirag M. , Kaushik Vani , Awasthi Abhijeet , Zalke Jitendra B. , Palekar Sangeeta , Rewatkar Prakash , Srivastava Sanjeet Kumar , Kulkarni Madhusudan B. , Bhaiyya Manish L.
Published: January 2025

A novel, portable chemiluminescence (CL) sensing platform powered by deep learning and smartphone integration has been developed for cost-effective and selective glucose detection. This platform features low-cost, wax-printed micro-pads (WPµ-pads) on paper-based substrates used to construct a miniaturized CL sensor. A 3D-printed black box serves as a compact WPµ-pad sensing chamber, replacing traditional bulky equipment, such as charge coupled device (CCD) cameras and optical sensors. Smartphone integration enables a seamless and user-friendly diagnostic experience, making this platform highly suitable for point-of-care (PoC) applications. Deep learning models significantly enhance the platform’s performance, offering superior accuracy and efficiency in CL image analysis. A dataset of 600 experimental CL images was utilized, out of which 80% were used for model training, with 20% of the images reserved for testing. Comparative analysis was conducted using multiple deep learning models, including Random Forest, the Support Vector Machine (SVM), InceptionV3, VGG16, and ResNet-50, to identify the optimal architecture for accurate glucose detection. The CL sensor demonstrates a linear detection range of 10–1000 µM, with a low detection limit of 8.68 µM. Extensive evaluations confirmed its stability, repeatability, and reliability under real-world conditions. This deep learning-powered platform not only improves the accuracy of analyte detection, but also democratizes access to advanced diagnostics through cost-effective and portable technology. This work paves the way for next-generation biosensing, offering transformative potential in healthcare and other domains requiring rapid and reliable analyte detection.
Advances in Huntington’s Disease Biomarkers: A 10-Year Bibliometric Analysis and a Comprehensive Review
Authors: Aqel Sarah , Ahmad Jamil , Saleh Iman , Fathima Aseela , Al Thani Asmaa A. , Mohamed Wael M. Y. , Shaito Abdullah A.
Published: January 2025

Neurodegenerative disorders (NDs) cause progressive neuronal loss and are a significant public health concern, with NDs projected to become the second leading global cause of death within two decades. Huntington’s disease (HD) is a rare, progressive ND caused by an autosomal-dominant mutation in the huntingtin (HTT) gene, leading to severe neuronal loss in the brain and resulting in debilitating motor, cognitive, and psychiatric symptoms. Given the complex pathology of HD, biomarkers are essential for performing early diagnosis, monitoring disease progression, and evaluating treatment efficacy. However, the identification of consistent HD biomarkers is challenging due to the prolonged premanifest HD stage, HD’s heterogeneous presentation, and its multiple underlying biological pathways. This study involves a 10-year bibliometric analysis of HD biomarker research, revealing key research trends and gaps. The study also features a comprehensive literature review of emerging HD biomarkers, concluding the need for better stratification of HD patients and well-designed longitudinal studies to validate HD biomarkers. Promising candidate wet HD biomarkers— including neurofilament light chain protein (NfL), microRNAs, the mutant HTT protein, and specific metabolic and inflammatory markers— are discussed, with emphasis on their potential utility in the premanifest HD stage. Additionally, biomarkers reflecting brain structural deficits and motor or behavioral impairments, such as neurophysiological (e.g., motor tapping, speech, EEG, and event-related potentials) and imaging (e.g., MRI, PET, and diffusion tensor imaging) biomarkers, are evaluated. The findings underscore that the discovery and validation of reliable HD biomarkers urgently require improved patient stratification and well-designed longitudinal studies. Reliable biomarkers, particularly in the premanifest HD stage, are crucial for optimizing HD clinical management strategies, enabling personalized treatment approaches, and advancing clinical trials of HD-modifying therapies.
Exploring the Enigmatic Spread and Spatial Dynamics of Bursatella leachii in the Mediterranean Sea
Authors: Castriota Luca , Falautano Manuela , Maggio Teresa , Perzia Patrizia
Published: January 2025

The invasion history of the gastropod mollusk Bursatella leachii in the Mediterranean Sea demonstrates a dynamic progression through distinct phases, comprising arrival, establishment, and expansion phases. Initial records in the 1930s trace its entry through the Suez Canal, likely followed by larval transport to the Aegean Sea facilitated by natural currents. The subsequent spread to Maltese and Italian waters suggests secondary dispersion favored by maritime traffic or aquaculture activities. The establishment phase shows a significant increase in occurrences and spatial dispersion, with aggregated nuclei in the central Mediterranean. The expansion phase was characterized by rapid dispersal and intensified densities, particularly in the Aegean, Adriatic, and Spanish coasts. These findings underscore the species’ capability to invade from multiple fronts, driven by both natural and human-mediated processes. A new location in the Strait of Sicily, i.e., the island of Lampedusa, is reported in the present paper for the species. Given the low number of observations, its establishment with a viable population on the island is not confirmed, although its detection validates the Straits of Sicily as a key area of intense settlement of the species.
CXCL12 as a Potential Hub Gene for N-Acetylcysteine Treatment of T1DM Liver Disease
Authors: Zhao Menglong , Han Mingzheng , Guo Shuaihao , Tang Zhaoxin
Published: January 2025

The etiology of type 1 diabetes mellitus (T1DM) is intricate, leading to its classification as an autoimmune metabolic disorder. T1DM often coexists with various visceral diseases. N-acetylcysteine (NAC) is widely acknowledged for its potent antioxidant properties. Studies have demonstrated that the combination of NAC and insulin can effectively alleviate iron-induced nephropathy in T1DM and mitigate oxidative stress injury in skeletal muscle associated with the condition. However, the potential impact of NAC alone on liver disease in individuals with T1DM remains uncertain. In this study, a beagle model was established to simulate T1DM, enabling investigation into the role of NAC in liver disease using RNA-seq biogenic analysis and subsequent validation through molecular biological methods. The findings revealed suppressed expression of CXCL12 chemokine in the livers of individuals with T1DM, while treatment with NAC induced specific activation of CXCL12 within the liver affected by T1DM. These results suggest that CXCL12 may serve as a regulatory factor involved in the therapeutic effects of NAC on liver disease associated with TIDM. This discovery holds significant implications for utilizing NAC as an adjunctive therapy for managing complicated liver diseases accompanying type 1 diabetes mellitus.
Protein Arginine Methyltransferase 1: A Multi-Purpose Player in the Development of Cancer and Metabolic Disease
Authors: de Korte Daphne , Hoekstra Menno
Published: January 2025

Protein arginine methyltransferase 1 (PRMT1) is the main PRMT family member involved in the formation of monomethylarginine and asymmetric dimethylarginine on its protein substrates. Many protein substrates of PRMT1 are key mediators of cell proliferation and oncogenesis. As such, the function of PRMT1 has been most prominently investigated in the context of cancer development. However, recent in vitro and in vivo studies have highlighted that PRMT1 may also promote metabolic disorders. With the current review, we aim to present an in-depth overview of how PRMT1 influences epigenetic modulation, transcriptional regulation, DNA damage repair, and signal transduction in cancer. Furthermore, we summarize the current knowledge regarding the role of PRMT1 in metabolic reprogramming, lipid metabolism, and glucose metabolism and describe the association of PRMT1 with numerous metabolic pathologies such as obesity, liver disease, and type 2 diabetes. It has become apparent that inhibiting the function of PRMT1 will likely serve as the most beneficial therapeutic approach, since several PRMT1 inhibitors have already been shown to exert positive effects on both cancer and metabolic disease in preclinical settings. However, pharmacological PRMT1 inhibition has not yet been shown to be therapeutically effective in clinical studies.
Phospholipase C Beta 2 as a Key Regulator of Tumor Progression and Epithelial-Mesenchymal Transition via PI3K/AKT Signaling in Renal Cell Carcinoma
Authors: Wang Shijin , Xie Deqian , Yue Hongzhe , Li Guandu , Jiang Bowen , Gao Yaru , Zheng Zunwen , Zheng Xu , Wu Guangzhen
Published: January 2025

Background: Renal cell carcinoma (RCC) represents the most common form of invasive kidney cancer in adults. Among the components critical to cellular regulation is Phospholipase C Beta 2 (PLCB2), a member of the phospholipase C enzyme family. This enzyme plays a vital role in managing key cellular functions such as growth, differentiation, migration, and survival. Despite its significant importance, the specific expression patterns and molecular mechanisms of PLCB2 in the progression of RCC are not well understood. Methods: This investigation employed a combination of bioinformatics analyses, scRNA-seq, functional assays, transcriptome sequencing, real-time quantitative PCR (RT-PCR), immunofluorescence, rescue experiments, and Western blotting to explore the regulatory function of PLCB2 in driving the epithelial-mesenchymal transition (EMT) in RCC through the PI3K/AKT signaling pathway. Results:PLCB2 expression is significantly elevated in RCC samples, and this increase is inversely correlated with patient prognosis. The knockdown of PLCB2 in RCC cell lines leads to a marked reduction in cell proliferation, invasion, migration, and EMT. Transcriptome sequencing further revealed that PLCB2 is significantly associated with the PI3K/AKT pathway. Notably, the PI3K activator 740Y-P was able to reverse the reductions in migration, invasion, and EMT caused by the PLCB2 knockdown. Conclusions: Our findings underscore the pivotal role of PLCB2 in regulating RCC invasion and metastasis by modulating the EMT via the PI3K/AKT signaling pathway. This highlights PLCB2 not only as a key prognostic biomarker, but also as a promising therapeutic target in the treatment of advanced-stage RCC, offering new avenues for more effective interventions.
Novel Insights into the Pathogenesis of Inflammatory Bowel Diseases
Authors: Calvez Valentin , Puca Pierluigi , Di Vincenzo Federica , Del Gaudio Angelo , Bartocci Bianca , Murgiano Marco , Iaccarino Jacopo , Parand Erfan , Napolitano Daniele , Pugliese Daniela , Gasbarrini Antonio , Scaldaferri Franco
Published: January 2025

Inflammatory bowel diseases (IBDs), encompassing Crohn’s disease and ulcerative colitis, are complex chronic disorders characterized by an intricate interplay between genetic predisposition, immune dysregulation, gut microbiota alterations, and environmental exposures. This review aims to synthesize recent advances in IBD pathogenesis, exploring key mechanisms and potential avenues for prevention and personalized therapy. A comprehensive literature search was conducted across major bibliographic databases, selecting the most recent and impactful studies on IBD pathogenesis. The review integrates findings from multi-omics analyses, single-cell transcriptomics, and longitudinal cohort studies, focusing on immune regulation, gut microbiota dynamics, and environmental factors influencing disease onset and progression. Immune dysregulation, including macrophage polarization (M1 vs. M2) and Th17 activation, emerges as a cornerstone of IBD pathogenesis. Dysbiosis, as a result of reduced alpha and beta diversity and overgrowth of harmful taxa, is one of the main contributing factors in causing inflammation in IBD. Environmental factors, including air and water pollutants, maternal smoking, and antibiotic exposure during pregnancy and infancy, significantly modulate IBD risk through epigenetic and microbiota-mediated mechanisms. While recent advances have supported the development of new therapeutic strategies, deeply understanding the complex dynamics of IBD pathogenesis remains challenging. Future efforts should aim to reduce the burden of disease with precise, personalized treatments and lower the incidence of IBD through early-life prevention and targeted interventions addressing modifiable risk factors.
Evaluating TcAs for Use in Biotechnology Applications
Authors: Martin Cole L. , Hill John H. , Wright Brian D. , Fernandez Solana R. , Miller Aubrey L. , Yoon Karina J. , Lapi Suzanne E. , Aller Stephen G.
Published: January 2025

ABC toxin complexes (Tcs) are tripartite complexes that come together to form nano-syringe-like translocation systems. ABC Tcs are often compared with Bacillus thuringiensis (Bt) toxins, and as such, they have been highly studied as a potential novel pesticide to combat growing insect resistance. Moreover, it is possible to substitute the cytotoxic hypervariable region with alternative peptides, which promise potential use as a novel peptide delivery system. These toxins possess the unique ability to form active chimeric holotoxins across species and display the capability to translocate a variety of payloads across membrane bilayers. Additionally, mutagenesis on the linker region and the receptor binding domains (RBDs) show that mutations do not inherently cause a loss of functionality for translocation. For these reasons, Tcs have emerged as an ideal candidate for targeted protein engineering. However, elucidation of the specific function of each RBD in relation to target receptor recognition currently limits the use of a rational design approach with any ABC Tc. Additionally, there is a distinct lack of targeting and biodistribution data for many Tcs among mammals and mammalian cell lines. Here, we outline two separate strategies for modifying the targeting capabilities of the A subunit (TcA) from Xenorhabdus nematophilus, Xn-XptA2. We identify novel structural differences that make Xn-XptA2 different than other characterized TcAs and display the modular capabilities of substituting RBDs from alternative TcAs into the Xn-XptA2 scaffold. Finally, we show the first, to our knowledge, biodistribution data of any TcA in mice.
Exploring Motor–Cognitive Interference Effects and the Influence of Self-Reported Physical Activity on Dual-Task Walking in Parkinson’s Disease and Healthy Older Adults
Authors: Klotzbier Thomas Jürgen , Schott Nadja , Park Soo-Yong , Almeida Quincy J.
Published: January 2025

Introduction: Parkinson’s disease (PD) is characterized by motor and cognitive impairments that often manifest as distinct motor subtypes: Postural Instability Gait Difficulty (PIGD) and Tremor-Dominant (TD). Motor–cognitive interference, especially under dual-task (DT) walking conditions, may vary by subtype, providing insights into specific impairments. This study explored DT interference effects in PD subtypes, focusing on the potential impact of self-reported physical activity, which may help mitigate subtype-specific impairments and improve motor–cognitive function. Methods: PD patients classified as PIGD or TD and healthy controls completed single-task (ST) and DT walking assessments involving different cognitive tasks (Serial Subtraction, Auditory Stroop, and Clock Task). Physical activity levels were evaluated using the CHAMPS questionnaire, analyzing the self-reported frequency and duration of weekly exercise-related activities. Results: Interference effects were significantly different between PD patients and controls, with the PIGD group showing greater motor impairment under high cognitive load, primarily affecting gait, than the TD and control groups. Performance differences between groups diminished as cognitive load increased. Self-reported physical activity does not significantly moderate motor performance under DT conditions, suggesting that activity levels in this sample are insufficient to offset motor–cognitive interference. However, like group affiliation, physical activity directly influences motor performance during DT conditions, indicating that both factors independently impact motor–cognitive function in PD. Discussion: These findings suggest that DT assessments help differentiate PD motor subtypes, as group differences were minimal in ST conditions. While physical activity is associated with general improvements in motor ST and DT performance in PD and controls, the lack of a significant moderating effect from self-reported exercise-related physical activity indicates that current activity levels may not be high enough to counter motor–cognitive interference. More intensive or DT-specific exercise may be required to reduce interference effects. Future research should examine the role of structured physical activity programs, potentially incorporating DT training, to evaluate their impact on motor–cognitive interference in PD.
The Place of Local Field Potentials in Deep Brain Stimulation Programming for Parkinson’s Disease: A Review
Authors: Leung Chun Him Shelton , Simpson Hugh D. , Thyagarajan Dominic
Published: January 2025

Background/Objections: The pharmacological management of Parkinson’s Disease (PD) is often supplemented by deep brain stimulation (DBS) to tackle problems of advanced disease such as motor fluctuation, dyskinesias or medication-resistant tremor. DBS uses high-frequency stimulation with spatially distributed electrodes to produce electrical fields that influence neuronal networks. The programming of such stimulation is complex and time-consuming. Recent technological advancements have enabled DBS systems to record local field potentials (LFPs). In conjunction with biomarker discovery, such as beta oscillations, this shows promise in streamlining the DBS programming process. This review aims to synthesize the current literature investigating LFP characteristics in PD in order to understand the place of LFPs in assisting with DBS programming. Methods: A comprehensive literature search was conducted using databases including OVID MEDLINE, Scopus, and Cochrane Library, resulting in 738 identified articles; 122 studies remained after screening and 87 studies were selected for detailed analysis. Results: Analyzing LFPs clearly has the potential to assist or streamline DBS programming in clinical practice, but there are knowledge gaps and challenges to overcome, especially in the utilization of intraoperative LFPs. Conclusions: More research is required to compare different algorithms that utilize LFPs in DBS programming to identify a simple, practical and time-saving algorithm incorporating reliable LFP biomarkers that will enhance the DBS programming experience for both patients and clinicians.
Circulating Growth Factors and Cytokines Correlate with Temperament and Character Dimensions in Adolescents with Mood Disorders
Authors: Terczynska Maria , Bargiel Weronika , Grabarczyk Maksymilian , Kozlowski Tomasz , Zakowicz Przemyslaw , Bojarski Dawid , Wasicka-Przewozna Karolina , Kapelski Pawel , Rajewska-Rager Aleksandra , Skibinska Maria
Published: January 2025

Background/Objectives: The incidence of mood disorders in adolescents is increasing. Bipolar disorder is often misdiagnosed in the early stages of the disease due to the prevalence of depressive symptoms, while manic episodes occur later. Identifying predictors of diagnosis conversion could facilitate timely and appropriate treatment. Our study aimed to find correlations of selected peripheral protein levels with temperament and character traits in adolescents diagnosed with major depressive disorder and bipolar disorder. Methods: A group of adolescents and young adults diagnosed with major depressive disorder (MDD, n = 50) or bipolar disorder (BD, n = 24) was enrolled in the study during the exacerbation of symptoms and followed up over two years. Diagnosis conversion from MDD to BD was monitored. The Temperament and Character Inventory was applied, and BDNF, proBDNF, EGF, MIF, SCF, S100B, TNF-alpha, and IL-8 serum levels were measured. Spearman’s rank correlation analysis was conducted. Results: We found different patterns of correlations in MDD (TNF-alpha, IL-8, EGF, S100B with reward-dependence, self-directedness, and empathy) and BD (BDNF and EGF with persistence novelty-seeking and self-transcendence). Significant correlations were found in a group with diagnosis conversion. Conclusions: The findings of our study have the potential to significantly impact our understanding and treatment of mood disorders. Correlations obtained in the subgroup with diagnosis conversion may contribute to the development of prognostic markers in the future. Evaluating temperament and character traits alongside established biomarkers may offer a valuable method for predicting the conversion of mood disorders in adolescents, facilitating early and effective pharmacotherapy.
Computer- and Smart-Tablet-Based Self-Administered Treatments in Chronic Post-Stroke Aphasia: A Systematic Review
Authors: Ericson Célia , Latysheva Alisa , Poirier Sarah-Ève , Fossard Marion
Published: January 2025

Background: In current clinical practice, resources remain limited and are insufficient to address the needs of people with chronic post-stroke aphasia. To improve access to speech therapy, self-administered therapies using computers or smart tablets are increasingly recommended. In addition to enabling more intensive and prolonged treatment, computer- and smart-tablet-delivered therapies can be highly enjoyable and motivating for patients. Aims: This systematic review aimed to identify computer- and smart-tablet-based self-administered treatments and analyze the proposed interventions in terms of treatment targets, effectiveness (considering specificity, generalization, transfer, and maintenance), and clinician involvement (during and/or prior self-administered therapies). Methods: Terms encompassing three main concepts (rehabilitation, self-administration, and aphasia) were used to search three electronic databases (Scopus, PubMed, and PsycINFO). Two reviewers independently screened titles and abstracts against eligibility criteria. Data extraction of included studies was completed by three reviewers. Results: Thirty-nine studies were included in this study. In terms of treatment targets, anomia is the most treated symptom in published studies (n = 24), but the existence of promising studies for other disorders means that the targets can be broadened. Therapies are effective for trained items, and gains are maintained. There is some evidence of transfer effects for treatments targeting the sentence level. Most studies offer training sessions, previous self-administered therapy, and/or observation and monitoring sessions during therapy; more rarely, self-administered therapy is supplemented with face-to-face therapy. Conclusions: This systematic review is the first to focus specifically on self-administered technology-based therapies. It provides important evidence-based information for clinical practice in self-administered therapies via computer or smart tablet.
CLTNet: A Hybrid Deep Learning Model for Motor Imagery Classification
Authors: Gu He , Chen Tingwei , Ma Xiao , Zhang Mengyuan , Sun Yan , Zhao Jian
Published: January 2025

Background: Brain–computer interface (BCI) technology opens up new avenues for human–machine interaction and rehabilitation by connecting the brain to machines. Electroencephalography (EEG)-based motor imagery (MI) classification is a key component of BCI technology, which is capable of translating neural activity in the brain into commands for controlling external devices. Despite the great potential of BCI technology, the challenges of extracting and decoding brain signals limit its wide application. Methods: To address this challenge, this study proposes a novel hybrid deep learning model, CLTNet, which focuses on solving the feature extraction problem to improve the classification of MI-EEG signals. In the preliminary feature extraction stage, CLTNet uses a convolutional neural network (CNN) to extract time series, channel, and spatial features of EEG signals to obtain important local information. In the deep feature extraction stage, the model combines the long short-term memory (LSTM) network and the Transformer module to capture time-series data and global dependencies in the EEG. The LSTM explains the dynamics of the brain activity, while the Transformer’s self-attention mechanism reveals the global features of the time series. Ultimately, the CLTNet model classifies motor imagery EEG signals through a fully connected layer. Results: The model achieved an average accuracy of 83.02% and a Kappa value of 0.77 on the BCI IV 2a dataset, and 87.11% and a Kappa value of 0.74 on the BCI IV 2b dataset, both of which outperformed the traditional methods. Conclusions: The innovation of the CLTNet model is that it integrates multiple network architectures, which offers a more comprehensive understanding of the characteristics of the EEG signals during motor imagery, providing a more comprehensive perspective and establishing a new benchmark for future research in this area.
Exploring the Impact of Workplace Hazing on Deviant Behavior in the Hospitality Sector: The Roles of Emotional Exhaustion and Hope and Optimism
Authors: Aljaier Osama , Alzubi Ahmad , Khadem Amir , Iyiola Kolawole
Published: January 2025

Workplace hazing remains a critical concern in the hospitality sector, known for its high-pressure environments and hierarchical dynamics. Drawing on transactional stress theory, this study explores the intricate relationships between workplace hazing, emotional exhaustion, and deviant behavior, with a focus on the moderating roles of hope and optimism. The research aims to examine how these psychological factors buffer the negative impacts of workplace hazing on employee behavior. Using a quantitative approach, data were collected from 494 valid responses comprising employees and supervisors from four- and five-star hotels in Aqaba, Amman, and Petra, Jordan. Convenience sampling was employed, and the data were analyzed using SPSS 29 and AMOS 26. The findings reveal that workplace hazing significantly predicts emotional exhaustion and deviant behavior, with emotional exhaustion mediating this relationship. Hope and optimism were found to moderate these effects, suggesting employees who maintain an optimistic outlook are better equipped to handle stress, which, in turn, reinforces their positive mindset, ultimately fostering healthier workplace cultures. The study offers both theoretical and practical implications. Theoretically, it extends the transaction theory of stress by integrating emotional exhaustion and deviant behavior. Practically, it suggests that hospitality organizations should focus on mitigating hazing practices, addressing emotional exhaustion through support mechanisms, and fostering positive psychological traits like hope and optimism to enhance employee well-being and minimize deviant behavior.
Behavioural Systems Mapping of Solid Waste Management in Kisumu, Kenya, to Understand the Role of Behaviour in a Health and Sustainability Problem
Authors: Davan Wetton Joanna , Santilli Micaela , Gitau Hellen , Muindi Kanyiva , Zimmermann Nici , Michie Susan , Davies Michael
Published: January 2025

Poor solid waste management in Kisumu, Kenya, contributes to adverse health, social, and environmental outcomes as a result of open burning, illegal dumping, and reliance on landfills. Taking Kisumu as a case study, we use behavioural systems mapping (BSM) for the purpose of understanding the role of behaviour in this complex problem. We qualitatively analysed transcripts from focus groups and interviews with 45 stakeholders in Kisumu to construct a BSM of the perceived actors, behaviours, and behavioural influences affecting waste management, as well as causal links. Influences were analysed using the capability, opportunity, and motivation model of behaviour (COM-B). The resulting BSM connects 24 behaviours by 12 different actors and 49 unique influences (30 related to opportunity, 16 to motivation, and 3 to capability). It reflects three sub-systems: policy-making, public waste management, and the policy–public interface. Six key feedback loops are described, which suggest that cycles of underfunding are interlinked with problematic practices around the build-up, handling, and segregation of waste and conflicting public and political views around responsibility. We demonstrate how the BSM method can be used with transcript data and provide steps that others can follow to inform the design of systemic behaviour change interventions. Further research to validate and adapt this approach may extend the learnings to other countries and health and sustainability challenges.
Working Memory as the Focus of the Bilingual Effect in Executive Functions
Authors: Chen Jiejia , Li Zitong , Xiong Zhiheng , Liu Guangyuan
Published: January 2025

The bilingual effect on executive functions (EFs) has garnered considerable attention, with most studies focusing on the visual domain and largely overlooking the auditory domain. Furthermore, research has predominantly concentrated on specific subcomponents of executive functions, with few studies systematically examining all three key subcomponents. This raises two important questions: (a) Is the bilingual effect specific to certain modalities (modality-specific), or a more general phenomenon (modality-general)? (b) Is the bilingual effect concentrated in a specific component of executive functions (process-specific), or does it extend to all three components (process-general)? To explore these questions, this study recruited monolingual Chinese and bilingual Chinese–English participants, using matched visual and auditory Stroop, N-back, and task-switching tasks to assess inhibitory control, working memory, and cognitive flexibility in both groups. The results showed that, after controlling for variables like intelligence, socioeconomic status, and age, bilingualism significantly predicted performance in both auditory and visual working memory tasks, explaining 34% and 19% of the variance, respectively. However, no evidence was found to support a bilingual effect in inhibitory control or cognitive flexibility. In conclusion, these results suggest that bilingual effects are not only process-specific (affecting only working memory) but also modality-general (providing advantages in both visual and auditory modalities).
Therapeutic Interventions for Music Performance Anxiety: A Systematic Review and Narrative Synthesis
Authors: Kinney Caitlin , Saville Phoebe , Heiderscheit Annie , Himmerich Hubertus
Published: January 2025

The aim of this systematic review was to summarise and evaluate the published literature on interventions for treating music performance anxiety (MPA). Adhering to the PRISMA guidelines, a comprehensive literature search of three electronic databases was conducted: PubMed, Web of Science, and PsychInfo (Ovid). Records were included in this review if they were quantitative pre–post interventional studies that utilised a recognised outcome measure or a clinical diagnosis for evaluating MPA. A narrative synthesis was orchestrated on 40 extracted studies assessing 1365 total participants. The principal intervention types observed included cognitive behavioural therapy, acceptance and commitment therapy, music therapy, yoga and/or mindfulness, virtual reality, hypnotherapy, biofeedback, and multimodal therapy. Although most of the reviewed studies demonstrated encouraging improvements in musicians’ MPA following delivered interventions, the current evidence base remains in its infancy, and numerous methodological weaknesses exist across studies. Small sample sizes, heterogeneity amongst treatment programmes, lack of follow-up data, a scarcity of standardised MPA assessments, and few randomised controlled designs render it imprudent to draw definitive recommendations concerning the interventions’ efficacy.
Prediction of Strength Properties of Reinforced and Stabilized Sandy Soil as a Building Foundation Material
Authors: Jafari Mohammad Mostafa , Bagheripour Mohammad Hossein , Yaghoubi Ehsan
Published: January 2025

Sandy soils are a type of geomaterial that may require improvements due to lack of cohesion. In this study, first, the lack of cohesion of sand was resolved using clay, and the soil was stabilized with cement and lime (4% and 3% of the dry weight of materials, respectively) and finally reinforced with recycled tire fibers of 20 to 30 mm in length for improved strength and ductility. Next, 747 samples with different fiber contents at different curing temperatures and ages were prepared and a unconfined compressive strength (UCS) test was carried out. Next, a novel approach employing multivariate nonlinear regression techniques and obtained empirical data was applied to formulate a mathematical model for predicting the UCS and the modulus of elasticity (Es) of the reinforced and stabilized soil. This model can serve as a valuable tool for building engineers in designing building foundations. The comparison of the obtained UCS and Es results and those predicted using the proposed model showed a correlation of >95% (R2 ≥ 0.95). The fibers effectively increased the failure strain, thus resulting in the greater ductility of the samples. As an example, in 14-day samples cured at 60 °C with 0%, 0.4%, 1%, 1.7%, and 2.5% fibers, the failure strain showed an incremental trend of 1.47%, 1.87%, 2.08%, 2.20%, and 2.92%, respectively. Scanning electron microscopy (SEM) was used to study the microstructure of the samples and to explain the strength experimental outcomes. SEM images showed a desirable interaction between the fiber surfaces with the soil mass and the reduction in porosity and the occurrence of pozzolanic reactions through stabilization. The results also showed that the reinforcement effectively improved the ductility, as desired for building foundations; however, it resulted in reduced strength, although a greater strength compared to the untreated soil was achieved. Although soil stabilization has been widely studied, limited research focuses on stabilizing soil with clay, lime, cement, and recycled tire fibers. This study offers design engineers an estimation scheme of the strength properties of stabilized and reinforced foundations.
Dementia Friendly Buildings—Approach on Architectures
Authors: Ghamari Mehrdad , Suvish  , Dehkordi Agaah Ashrafi , See Chan Hwang , Sami Ashkan , Yu Hongnian , Sundaram Senthilarasu
Published: January 2025

Dementia’s escalating incidence, coupled with its economic burden, highlights the need for architectural designs and forms that benefit people living with dementia. This research explores strategies and design principles that focus on establishing supportive spaces for the prolonged autonomy, well-being, and safety of dementia patients. Contemporary research emphasizes the implementation of effective navigational techniques, via visual cues, familiar landmarks, and simplified layouts. For greater navigational signage, the intentional use of contrasting colors, textures, and lighting are recommended to demarcate functional areas within a structure. Incorporating familiar objects in personalized areas enhances treatment outcomes, e.g., reminiscence therapy leverages familiar objects, environmental cues, scents, sounds, and tactile features to trigger and retain memory. Integrating safety precautions such as slip-resistant flooring, handrails, and accessible bathrooms helps mitigate falls for the cognitively impaired. From a therapeutic perspective, this study draws attention towards incorporating gardens and outdoor spaces, which offers sensory stimulation, encourages physical activity, and fosters social engagement. Additionally, the integration of scents, sounds, and tactile features enriches the sensory experience for individuals with dementia. Through comprehensive consideration of design elements, this research highlights how intentionally crafted, dementia-friendly environments can convert spaces into empowering therapeutic settings tailored to address the unique need of this vulnerable group. This architectural approach acts as a valuable complement to the medical and therapeutic interventions in the treatment and care of people living with dementia and their families.
The Application of Variable Weight Theory on the Suitability Evaluation of Urban Underground Space Development and Utilization for Urban Resilience and Sustainability
Authors: Chen Hongnian , Tan Xianfeng , Zhang Yan , Hu Bo , Xu Shuming , Dai Zhenfen , Zhang Zhengxuan , Xiong Hanxiang , Song Xiaoqing , Luo Danyuan
Published: January 2025

Urban underground space (UUS) is a significant natural resource to support many aspects of city development, but it is not sustainably developed and utilized during the urbanization process. This study considered 11 conditional and two sensitive factors and combined analytic hierarchy process (AHP) and variable weight theory (VWT) for the suitability evaluation of UUS development and utilization (SEUUSD&U) by taking the Jining city planning zone (JNPZ) as a case study. The results show that mining subsidence and groundwater-related factors are critical factors, which align with the real conditions. A significant increase in the weight of shallow groundwater can be observed after applying the VWT, rising from 0.1586 to 0.2544. This may result from significant extreme values, which WVT accurately identified and therefore increased the weights. From shallow to deep UUS, both the most suitable and least suitable areas increase, rising from 32.91% to 68.20% and from 0.57% to 3.01%, respectively. Based on two sensitive factors (key urban development and ecological protection), the study area was divided into four management zones. These sensitive factors often exhibit a “barrel effect”, showing the power to either definitively affirm or veto the outcomes. More importantly, this study proposes a generalized SEUUSD&U framework comprising six key steps, with particular emphasis on three aspects: “local conditions”, “barrel effect integration”, and “adaptive management strategies aligned with the United Nations sustainable development goals (SDGs)”. We strongly recommend that this framework be highly promoted in future research and strongly encourage future studies to place greater emphasis on the ultimate goal of achieving the SDGs by 2030 during updates to models, variable weight functions, factors, and frameworks.
A Systematic and Objective Framework for Evaluating Subcontractor Performance Using Monte Carlo Simulation Coupled with the Analytic Hierarchy Process and a Linear Additive Utility Model
Authors: Al Hasan Iyad , Hammad Ahmed
Published: January 2025

The general contractor (GC)–subcontractor (SC) relationship is a crucial aspect of construction supply chain management, heavily influencing project outcomes. This study investigates a method for assessing SC performance and underscores its essential role in construction projects. Traditionally, SC assessments are based on subjective evaluations, which can lead to biased decision-making. To counter this, this study introduces a comprehensive framework that employs objective indices and a systematic evaluation method. The study begins with a comprehensive literature review and expert consultations to identify key indices for SC evaluation: time, cost, quality, safety, resources, satisfaction, and leadership. A hybrid method combining Monte Carlo simulation and the Analytic Hierarchy Process (AHP) is employed to assign weights to these indices through the development of probability distributions, thereby reducing judgment uncertainty. The developed evaluation model incorporates normalization and a linear additive utility model (LAUM) to calculate a performance index (PI) that quantifies SC performance across various levels, from outstanding to poor. The normalization process is applied with three tolerance levels (high, medium, and low). A real case study with a three-scenario sensitivity analysis demonstrates the model’s effectiveness. This approach provides general contractors with a more objective and transparent assessment process, minimizing bias in evaluations.
Integration of Emerging Technologies with Construction Practices in Australia
Authors: Chaaya Mia L. , Sarkis Lucia M. , Tahmasebinia Faham
Published: January 2025

Although the construction sector significantly bolsters the Australian economy, it is widely recognised for lagging behind other industries in adopting emerging technologies. This study reviews existing literature to explore the current state of technology integration in the Australian construction industry, focusing on its impact on safety, cost, quality, and project timelines. The research methodology involved conducting interviews and surveys with industry stakeholders to collect qualitative and quantitative data regarding technology integration. The analysis of survey data provided insights into the current and anticipated future adoption of emerging technologies in Australia, identifying significant obstacles that impede the industry’s digital transformation. Based on the survey results, a specialised system was developed for Tier 1 and Tier 2 construction firms, enabling them to evaluate their present and predicted future use of emerging technologies. Additionally, this system helps university graduates gauge their understanding and awareness of emerging technologies to meet the expectations of leading industry professionals. The findings of this study aim to enhance the understanding and implementation of emerging technologies within the construction sector, thereby fostering a new generation of professionals who recognise the significant potential of these technologies to revolutionise construction practices.
Research on Real-Time Energy Consumption Prediction Method and Characteristics of Office Buildings Integrating Occupancy and Meteorological Data
Authors: Lian Huihui , Wei Haosen , Wang Xinyue , Chen Fangyuan , Ji Ying , Xie Jingchao
Published: January 2025

A method based on Long Short-Term Memory (LSTM) networks is proposed to forecast hourly energy consumption. Using an office building in Shanghai as a case study, hourly data on occupancy, weather, and energy consumption were collected. Daily energy consumption was analyzed using single-link clustering, and days were classified into three types. The key input variables significantly influencing energy consumption, solar radiation, occupancy, and outdoor dry bulb temperature are identified by the Pearson correlation coefficient. By comparing five algorithms, it was found that the LSTM model performed the best. After considering the occupancy, the hourly MAPE was reduced from 11% to 9%. Accuracy improvements for each day type were noted as 1% for weekdays, 4% for Saturday, and 7% for Sunday. Further analysis indicated that the model started to predict the time (1:00) and commute time (7:00 and 17:00) with large errors. The model was optimized by varying the time step. For the times 1:00, 7:00, and 17:00, the best optimization of the model was achieved when the time step values were set to 6 h, 24 h, and 18 h with an MAPE of 3%, 6%, and 5%, respectively. As the model time step increased (≤2 weeks), the accuracy of the model decreased to 6%.
Optimization of Thermal Insulation Parameters for Vertical Perimeters in Buildings with Single-Layer Walls
Authors: Jezierski Walery , Szczepaniak Paula , Leszczyński Cezary
Published: January 2025

This article presents the results of a study on the impact of selected parameters of a building’s ground-floor zone (the junction of the external and foundation walls, the ground floor slab, and the ground itself) on the temperature field within the external envelope. This study aims to analyze the influence and optimize the parameters of vertical perimeter insulation in the ground-floor zone of the building. Mathematical modeling was selected as the research method. This paper analyzes the relationships between the temperature ϑimg on the inner surface of the wall at the analyzed node and the linear thermal transmittance coefficient ψim of the thermal bridge occurring in this location, as influenced by the following parameters: dp—thickness of the insulation layer in the ground floor slab; df—thickness of the vertical perimeter insulation layer in the foundation wall; t—location of the insulation layer in the ground floor slab relative to the “external wall-foundation wall” contact surface; r—location of the vertical perimeter insulation layer in the foundation wall; and λs—thermal conductivity of the single-layer external wall material. The analysis was conducted under the climatic conditions of Białystok, Poland. Using THERM 7.6 software for computational experiments, data were obtained to develop deterministic mathematical models of these relationships. The models enabled the assessment of the degree and nature of the influence of the studied factors on ϑimg and ψim, optimization of selected parameters, and mathematical description of safe operating conditions for external walls in the ground-floor zone of heated buildings. It was found that the parameters dp, df, and r have favorable effects, increasing ϑimg by 2.57%, 2.51%, and 4.17%, respectively, when varying from their minimum to maximum levels. Conversely, the parameters t and λs negatively impact ϑimg, contributing reductions of −12.01% and −4.66%, respectively, with a cumulative effect of −16.67%. Optimal parameter values were determined based on energy efficiency criteria. This information may be useful for researchers, designers, engineers, and decision-makers when making informed decisions during the design phase of heated buildings.
TiO2/SWCNts: Linear and Nonlinear Optical Studies for Environmental Applications
Authors: Helali Saloua
Published: January 2025

A series of single-walled carbon nanotube/titanium dioxide (SWCNTs/TiO2) composites were prepared by the incorporation of various concentrations (0, 5, 10, 20 V.%) of SWCNTs in TiO2. The prepared solutions were successfully formed on silicon and quartz substrates using the sol–gel spin-coating approach at 600 °C in ambient air. The X-ray diffraction method was used to investigate the structure of the samples. The absorbance and transmittance data of the samples were measured using a UV–vis spectrophotometer. Through the analysis of these data, both the linear and nonlinear optical properties of the samples were examined. Wemple–DiDomenico’s single-oscillator model was used to calculate the single-oscillator energy and dispersion energy. Finally, all samples’ photocatalytic performance was studied by the photodegradation of methylene blue (MB) in an aqueous solution under UV irradiation. It is found that the photocatalytic efficiency increases when increasing the SWCNT content. This research offers a new perspective for the creation of new photocatalysts for environmental applications.