bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Short-Term Rockburst Risk Severity Using Machine Learning Methods
Authors: Jin Aibing , Basnet Prabhat , Mahtab Shakil
Published: November 2023

In deep engineering, rockburst hazards frequently result in injuries, fatalities, and the destruction of contiguous structures. Due to the complex nature of rockbursts, predicting the severity of rockburst damage (intensity) without the aid of computer models is challenging. Although there are various predictive models in existence, effectively identifying the risk severity in imbalanced data remains crucial. The ensemble boosting method is often better suited to dealing with unequally distributed classes than are classical models. Therefore, this paper employs the ensemble categorical gradient boosting (CGB) method to predict short-term rockburst risk severity. After data collection, principal component analysis (PCA) was employed to avoid the redundancies caused by multi-collinearity. Afterwards, the CGB was trained on PCA data, optimal hyper-parameters were retrieved using the grid-search technique to predict the test samples, and performance was evaluated using precision, recall, and F1 score metrics. The results showed that the PCA-CGB model achieved better results in prediction than did the single CGB model or conventional boosting methods. The model achieved an F1 score of 0.8952, indicating that the proposed model is robust in predicting damage severity given an imbalanced dataset. This work provides practical guidance in risk management.
The Diagnostic, Therapeutic and Prognostic Relevance of Neutrophil Extracellular Traps in Polytrauma
Authors: Rogers Emily , Pothugunta Shevani , Kosmider Veronika , Stokes Natasha , Bonomini Layla , Briggs Gabrielle D. , Lewis Daniel P. , Balogh Zsolt J.
Published: November 2023

Neutrophil extracellular traps (NETs) represent a recently discovered polymorphonuclear leukocyte-associated ancient defence mechanism, and they have also been identified as part of polytrauma patients’ sterile inflammatory response. This systematic review aimed to determine the clinical significance of NETs in polytrauma, focusing on potential prognostic, diagnostic and therapeutic relevance. The methodology covered all major databases and all study types, but was restricted to polytraumatised humans. Fourteen studies met the inclusion criteria, reporting on 1967 patients. Ten samples were taken from plasma and four from whole blood. There was no standardisation of methodology of NET detection among plasma studies; however, of all the papers that included a healthy control NET, proxies were increased. Polytrauma patients were consistently reported to have higher concentrations of NET markers in peripheral blood than those in healthy controls, but their diagnostic, therapeutic and prognostic utility is equivocal due to the diverse study population and methodology. After 20 years since the discovery of NETs, their natural history and potential clinical utility in polytrauma is undetermined, requiring further standardisation and research.
Low-Entropy Hydration Shells at the Spike RBD’s Binding Site May Reveal the Contagiousness of SARS-CoV-2 Variants
Authors: Yang Lin , Guo Shuai , Hou Chengyu , Jiang Shenda , Shi Liping , Ma Xiaoliang , Zheng Bing , Fang Yi , Ye Lin , He Xiaodong
Published: November 2023

The infectivity of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is primarily determined by the binding affinity between the receptor-binding domain (RBD) of the spike protein and the angiotensin-converting enzyme 2 (ACE2) receptor. Here, through screening off pseudo hydrophilic groups on protein surfaces, the distribution of low-entropy regions on hydration shells of the ACE2 receptor and the RBDs of multiple SARS-CoV-2 variants was demonstrated. Shape matching between the low-entropy hydration shells of multiple SARS-CoV-2 variants and the ACE2 receptor has been identified as a mechanism that drives hydrophobic attraction between the RBDs and the ACE2 receptor, which estimates the binding affinity. Low-entropy regions of the hydration shells, which play important roles in determining the binding of other viruses and their receptors, are demonstrated. The RBD–ACE2 binding is thus found to be guided by hydrophobic collapse between the shape-matched low-entropy regions of the hydration shells of the proteins. A measure of the low-entropy status of the hydration shells can be estimated by calculating genuine hydrophilic groups within the binding sites. An important indicator of the contagiousness of SARS-CoV-2 variants is the low-entropy level of its hydration shells at the spike protein binding site.
Good Cop, Bad Cop: Profiling the Immune Landscape in Multiple Myeloma
Authors: Sharma Niyati Seshagiri , Choudhary Bibha
Published: November 2023

Multiple myeloma (MM) is a dyscrasia of plasma cells (PCs) characterized by abnormal immunoglobulin (Ig) production. The disease remains incurable due to a multitude of mutations and structural abnormalities in MM cells, coupled with a favorable microenvironment and immune suppression that eventually contribute to the development of drug resistance. The bone marrow microenvironment (BMME) is composed of a cellular component comprising stromal cells, endothelial cells, osteoclasts, osteoblasts, and immune cells, and a non-cellular component made of the extracellular matrix (ECM) and the liquid milieu, which contains cytokines, growth factors, and chemokines. The bone marrow stromal cells (BMSCs) are involved in the adhesion of MM cells, promote the growth, proliferation, invasion, and drug resistance of MM cells, and are also crucial in angiogenesis and the formation of lytic bone lesions. Classical immunophenotyping in combination with advanced immune profiling using single-cell sequencing technologies has enabled immune cell-specific gene expression analysis in MM to further elucidate the roles of specific immune cell fractions from peripheral blood and bone marrow (BM) in myelomagenesis and progression, immune evasion and exhaustion mechanisms, and development of drug resistance and relapse. The review describes the role of BMME components in MM development and ongoing clinical trials using immunotherapeutic approaches.
Exploiting TLK1 and Cisplatin Synergy for Synthetic Lethality in Androgen-Insensitive Prostate Cancer
Authors: Bhoir Siddhant , Ogundepo Oluwatobi , Yu Xiuping , Shi Runhua , De Benedetti Arrigo
Published: November 2023

Cellular organisms possess intricate DNA damage repair and tolerance pathways to manage various DNA lesions arising from endogenous or exogenous sources. The dysregulation of these pathways is associated with cancer development and progression. Synthetic lethality (SL), a promising cancer therapy concept, involves exploiting the simultaneous functional loss of two genes for selective cell death. PARP inhibitors (PARPis) have demonstrated success in BRCA-deficient tumors. Cisplatin (CPT), a widely used chemotherapy agent, forms DNA adducts and crosslinks, rendering it effective against various cancers, but less so for prostate cancer (PCa) due to resistance and toxicity. Here, we explore the therapeutic potential of TLK1, a kinase upregulated in androgen-insensitive PCa cells, as a target for enhancing CPT-based therapy. TLK1 phosphorylates key homologous recombination repair (HRR) proteins, RAD54L and RAD54B, which are critical for HRR alongside RAD51. The combination of CPT with TLK1 inhibitor J54 exhibits SL in androgen-insensitive PCa cells. The formation of double-strand break intermediates during inter-strand crosslink processing necessitates HRR for effective repair. Therefore, targeting TLK1 with J54 enhances the SL of CPT by impeding HRR, leading to increased sensitivity in PCa cells. These findings suggest a promising approach for improving CPT-based therapies in PCa, particularly in androgen-insensitive cases. By elucidating the role of TLK1 in CPT resistance, this study provides valuable insights into potential therapeutic targets to overcome PCa resistance to CPT chemotherapy. Further investigations into TLK1 inhibition in combination with other DNA-damaging agents may pave the way for more effective and targeted treatments for PCa and other cancers that exhibit resistance to traditional chemotherapy agents.
Less Is More? Combined Approaches to Improve Mortality and Morbidity after Aortic Valve Replacement
Authors: Mikus Elisa , Fiorentino Mariafrancesca , Sangiorgi Diego , Calvi Simone , Tenti Elena , Cavallucci Andrea , Tremoli Elena , Tripodi Alberto , Pin Maurizio , Savini Carlo
Published: November 2023

Background: Nowadays, one of the main goals of aortic valve surgery is to reduce the biological impact, mortality, and complications. It is well-known that long operative times in terms of the extracorporeal circulation, but above all, of the aortic cross-clamp time (ACC), represent a risk factor for mortality in patients undergoing cardiac surgery. In order to shorten the aortic cross-clamp time, many technological improvements, such as sutureless prostheses, have been introduced, but their actual effectiveness has not been proven yet. The aim of this study was to assess the 30-day outcomes of patients undergoing aortic valve replacement surgery, focusing on the ACC length. Methods: All 3139 patients undergoing aortic valve replacement between January 2013 and July 2022 at our institution were enrolled. The data were retrospectively collected and the baseline characteristics and intraoperative variables were recorded. In order to adjust the results according to the differences in the baseline characteristics, propensity score matching was performed and four groups of 351 patients were obtained based on the first, second, third, and fourth quartile of the ACC time. Results: The patient population included 132 redo surgeries (9.4%) and 61 cases of active endocarditis (4.3%), with an overall median EuroSCORE II of 1.8 (IQR 1.2–3.1). An increase across the groups was observed in terms of the acute kidney failure (p < 0.001) incidence, the number of blood transfusions (p = 0.022), prolonged hospital stays (p < 0.001), the and respiratory failure (p < 0.001) incidence. A p of < 0.1 was found for the 30-day mortality (p = 0.079). The predictors of an early 30-day mortality were standard full sternotomy (OR 2.48, 95% CI 1.14–5.40, p = 0.022), EuroSCORE II (OR 1.10, 95% CI 1.05–1.16, p < 0.001), and a trend for a longer ACC time (Q4 vs. Q1: OR 2.62, 95% CI 0.89–7.68, p = 0.080). Conclusions: Shortening the operative times resulted in marked improvements of the patients’ outcomes. The combined use of minimally invasive approaches and sutureless aortic valve prostheses allows for a lower 30-day events rate. New technologies should be assessed to obtain the best results with the least risk.
Enteroscopy versus Video Capsule Endoscopy for Automatic Diagnosis of Small Bowel Disorders—A Comparative Analysis of Artificial Intelligence Applications
Authors: Popa Stefan Lucian , Stancu Bogdan , Ismaiel Abdulrahman , Turtoi Daria Claudia , Brata Vlad Dumitru , Duse Traian Adrian , Bolchis Roxana , Padureanu Alexandru Marius , Dita Miruna Oana , Bashimov Atamyrat , Incze Victor , Pinna Edoardo , Grad Simona , Pop Andrei-Vasile , Dumitrascu Dinu Iuliu , Munteanu Mihai Alexandru , Surdea-Blaga Teodora , Mihaileanu Florin Vasile
Published: November 2023

Background: Small bowel disorders present a diagnostic challenge due to the limited accessibility of the small intestine. Accurate diagnosis is made with the aid of specific procedures, like capsule endoscopy or double-ballon enteroscopy, but they are not usually solicited and not widely accessible. This study aims to assess and compare the diagnostic effectiveness of enteroscopy and video capsule endoscopy (VCE) when combined with artificial intelligence (AI) algorithms for the automatic detection of small bowel diseases. Materials and methods: We performed an extensive literature search for relevant studies about AI applications capable of identifying small bowel disorders using enteroscopy and VCE, published between 2012 and 2023, employing PubMed, Cochrane Library, Google Scholar, Embase, Scopus, and ClinicalTrials.gov databases. Results: Our investigation discovered a total of 27 publications, out of which 21 studies assessed the application of VCE, while the remaining 6 articles analyzed the enteroscopy procedure. The included studies portrayed that both investigations, enhanced by AI, exhibited a high level of diagnostic accuracy. Enteroscopy demonstrated superior diagnostic capability, providing precise identification of small bowel pathologies with the added advantage of enabling immediate therapeutic intervention. The choice between these modalities should be guided by clinical context, patient preference, and resource availability. Studies with larger sample sizes and prospective designs are warranted to validate these results and optimize the integration of AI in small bowel diagnostics. Conclusions: The current analysis demonstrates that both enteroscopy and VCE with AI augmentation exhibit comparable diagnostic performance for the automatic detection of small bowel disorders.
Dopamine in the Regulation of Glucose Homeostasis, Pathogenesis of Type 2 Diabetes, and Chronic Conditions of Impaired Dopamine Activity/Metabolism: Implication for Pathophysiological and Therapeutic Purposes
Authors: Lisco Giuseppe , De Tullio Anna , Iovino Michele , Disoteo Olga , Guastamacchia Edoardo , Giagulli Vito Angelo , Triggiani Vincenzo
Published: November 2023

Dopamine regulates several functions, such as voluntary movements, spatial memory, motivation, sleep, arousal, feeding, immune function, maternal behaviors, and lactation. Less clear is the role of dopamine in the pathophysiology of type 2 diabetes mellitus (T2D) and chronic complications and conditions frequently associated with it. This review summarizes recent evidence on the role of dopamine in regulating insular metabolism and activity, the pathophysiology of traditional chronic complications associated with T2D, the pathophysiological interconnection between T2D and chronic neurological and psychiatric disorders characterized by impaired dopamine activity/metabolism, and therapeutic implications. Reinforcing dopamine signaling is therapeutic in T2D, especially in patients with dopamine-related disorders, such as Parkinson’s and Huntington’s diseases, addictions, and attention-deficit/hyperactivity disorder. On the other hand, although specific trials are probably needed, certain medications approved for T2D (e.g., metformin, pioglitazone, incretin-based therapy, and gliflozins) may have a therapeutic role in such dopamine-related disorders due to anti-inflammatory and anti-oxidative effects, improvement in insulin signaling, neuroinflammation, mitochondrial dysfunction, autophagy, and apoptosis, restoration of striatal dopamine synthesis, and modulation of dopamine signaling associated with reward and hedonic eating. Last, targeting dopamine metabolism could have the potential for diagnostic and therapeutic purposes in chronic diabetes-related complications, such as diabetic retinopathy.
Getting Good Sleep with Family Support: The Role of Fear of Crime and Loneliness
Authors: Xia Chun , Xu Jia , Wang Yaya
Published: November 2023

Sleep problems in middle-aged and older people can threaten their physical and mental health. Family support is regarded as a key factor that affects sleep quality, but the influence mechanism remains underexplored. This study analyzes the mediating effects of fear of crime (FOC) and loneliness in the relationship between family support and sleep quality, and explores whether gender plays a moderating role between family support and FOC. A questionnaire survey was conducted among 1043 Chinese middle-aged and older people aged 45–93 years. Using 10,000 bootstrapped samples, the study shows that middle-aged and older people who receive more family support have better sleep quality, and FOC and loneliness play mediating role in this association. Gender moderates the relationship between family support and FOC. Compared with men, family support for females has a greater impact on their FOC condition, and the mediating effect of family support on sleep quality through FOC is also greater among women. Family support can affect sleep quality through the chain mediating effect of FOC and loneliness for women. This study provides an in-depth understanding of the relationship between family support and sleep quality.
Effects of Psychological Interventions on Performance Anxiety in Performing Artists and Athletes: A Systematic Review with Meta-Analysis
Authors: Niering Marc , Monsberger Teresa , Seifert Johanna , Muehlbauer Thomas
Published: November 2023

Levels of state and trait anxiety are relevant for performing artists and professional athletes to obtain optimal performance outcomes. However, evidence-based knowledge regarding the effectiveness of psychological interventions on performance anxiety is currently minimal. Thus, the objective of this systematic review with meta-analysis was to characterize, aggregate, and quantify intervention effects on measures of state and trait performance anxiety in performing artists and professional athletes. A systematic search of the literature according to the PRISMA guidelines was conducted on the databases PubMed, Medline, SPORTDiscus, PsycInfo, Embase, and Web of Science from 1 January 1960 to 9 November 2022. The search only included controlled studies employing pre–post measures and excluded performing arts fields that do not depend on fine motor skills. Initially, 1022 articles were identified; after removing duplicates and assessing abstracts and full texts, 20 articles were used to calculate weighted standardized mean differences (SMDs). In terms of state performance anxiety, our results revealed a large overall effect (SMD = 0.88), a medium effect (SMD = 0.62) for studies using scales with total scores (i.e., MPAI-A, STAI), and large effects (cognitive anxiety: SMD = 0.93, somatic anxiety: SMD = 0.92, self-confidence: SMD = 0.97) for studies applying scales with sub-scores (i.e., CSAI-2R)—all in favour of the intervention groups. Regarding trait performance anxiety (e.g., SCAT), we detected a small effect (SMD = 0.32), also favouring the intervention groups. Interventions to reduce performance anxiety in performing artists and professional athletes revealed varying levels of effectiveness ranging from small (trait) to large (state). Therefore, future studies should investigate modalities to increase intervention efficacy, especially for the small-sized changes in trait performance anxiety.
Financing Brownfield Redevelopment and Housing Market Dynamics: Evidence from Connecticut
Authors: Gibilaro Lucia , Mattarocci Gianluca
Published: November 2023

Brownfield redevelopment projects are often perceived as more risky than greenfield investment, and financing opportunities may be more limited and expensive. Different financial support projects have been developed to support regeneration projects, and empirical evidence has shown that all buildings near the intervention area may benefit from an increase in prices once the brownfield project is complete. The article considers the Connecticut market and evaluates the characteristics of the brownfield projects that had access to a financial support program (loan or grant), the impact of the regeneration process on the liquidity of the housing market, and the gap between the price and the appraisal value of the residential unit. Target areas for this type of financing program are mainly characterized by low income, a high density of population, a high incidence of homeowners, and a high crime rate. Once completed, the brownfield requalification has an impact on the housing market because the brownfield recovery reduces the number of house sales due to the increase in the average price in the surrounding area and makes the selling price more consistent with the appraisal valuation. The empirical evidence provided may be useful for public institutions that are suffering from budget constraints and have to prioritize areas for financial support solutions.
The ANN Architecture Analysis: A Case Study on Daylight, Visual, and Outdoor Thermal Metrics of Residential Buildings in China
Authors: Wang Shanshan , Yi Yun Kyu , Liu Nianxiong
Published: November 2023

Selecting an appropriate ANN model is crucial for speeding up the process of building performance simulation during the design phase of residential building layouts, particularly when evaluating three or more green performance metrics simultaneously. In this study, daylight, visual, and outdoor thermal metrics were selected as main green performance. To find the suitable ANN model, sensitivity analysis was used to obtain a set of proper parameters applied to the ANN structure. To train the ANN model with a higher predicting accuracy, this paper tested four different scenarios of ANN parameter setups to find some general guidelines about how to set up an ANN model to predict DF, sunlight hours, QuVue and UTCI. The results showed that an ANN model with a combined output variable demonstrated better average prediction accuracy than ANN models with a separated output variable. Having two times the number of training samplings compared to the number of input variables can lead to a high accuracy of prediction. The ideal number of neurons in the hidden layer was approximately 1.5 times the number of input variables. These findings of how to improve the ANN model may provide guidance for modeling an ANN for building performance.
Solar Chimney Performance Driven Air Ventilation Promotion: An Investigation of Various Configuration Parameters
Authors: Hassan Asmaa M.
Published: November 2023

Climate change represents a vital public health challenge, resulting in serious impacts that require passive strategies in the built environment sector to mitigate such impacts. Such strategies are associated with the Sustainable Development Goals (SDGs), which present a vital need. Consequently, the solar chimney (SC) can be considered as an effective passive strategy to provide energy, thermal comfort, and air ventilation performance. Therefore, this study focused on SC performance and its related significance on air ventilation. This study aimed to bridge the gap in previous studies and indicates the hotspot topics to conduct a conceptual framework with three phases that can integrate various configurations of a SC with various buildings by considering the recent tools of numerical analysis. Thus, a bibliometric analysis based on the Biblioshiny and VOSviewer tools within the scope of the SC and air ventilation promotion was accomplished. Then, various configuration parameters related to SC performance-driven air ventilation are provided. The results indicate that further studies are required to develop themes like the “building design” of SC and its associated effects such as air quality and ventilation, in addition to “numerical analysis” and “optimization” in terms of hotspot topics and the potential for future consequences. Additionally, limited configurations of previous studies provide promising investigations resulting in several applications including many zones and floors that can be achieved by the proposed conceptual framework. Various insights and possibilities can promote numerous configuration parameters related to SC performance-driven air ventilation promotion, which serves as research guidance for designers and specialists toward the mitigation of climate change impacts and attaining the SDGs.
Moving the Needle Forward in Genomically-Guided Precision Radiation Treatment
Authors: Tam Andrew , Mercier Benjamin D. , Thomas Reeny M. , Tizpa Eemon , Wong Irene G. , Shi Juncong , Garg Rishabh , Hampel Heather , Gray Stacy W. , Williams Terence , Bazan Jose G. , Li Yun R.
Published: November 2023

Radiation treatment (RT) is a mainstay treatment for many types of cancer. Recommendations for RT and the radiation plan are individualized to each patient, taking into consideration the patient’s tumor pathology, staging, anatomy, and other clinical characteristics. Information on germline mutations and somatic tumor mutations is at present rarely used to guide specific clinical decisions in RT. Many genes, such as ATM, and BRCA1/2, have been identified in the laboratory to confer radiation sensitivity. However, our understanding of the clinical significance of mutations in these genes remains limited and, as individual mutations in such genes can be rare, their impact on tumor response and toxicity remains unclear. Current guidelines, including those from the National Comprehensive Cancer Network (NCCN), provide limited guidance on how genetic results should be integrated into RT recommendations. With an increasing understanding of the molecular underpinning of radiation response, genomically-guided RT can inform decisions surrounding RT dose, volume, concurrent therapies, and even omission to further improve oncologic outcomes and reduce risks of toxicities. Here, we review existing evidence from laboratory, pre-clinical, and clinical studies with regard to how genetic alterations may affect radiosensitivity. We also summarize recent data from clinical trials and explore potential future directions to utilize genetic data to support clinical decision-making in developing a pathway toward personalized RT.
The Effectiveness of Ni-Based Bimetallic Catalysts Supported by MgO-Modified Alumina in Dry Methane Reforming
Authors: Ibrahim Ahmed A. , Fakeeha Anis H. , Abasaeed Ahmed E. , Wazeer Irfan , Bentalib Abdulaziz , Siva Kumar Nadavala , Abu-Dahrieh Jehad K. , Al-Fatesh Ahmed S.
Published: November 2023

Syngas is produced through the carbon dioxide reforming of methane. The traditional nickel-based catalysts are substantially destroyed by carbon deposition. The reforming reaction was conducted in a tubular microreactor at 700 °C using bimetallic Ni catalysts supported over 37% Al2O3 and 63% MgO mixtures. The impregnation process formed the catalysts, which were subsequently examined by N2-physisorption, XRD, H2-TPR, TGA, and Raman spectroscopy. The 2.5Ni+2.5Co/37%Al2O3+63%MgO bimetallic catalyst, which displayed 72% and 76% conversions of CH4 and CO2 over the course of a seven-hour procedure, was discovered to be the most active in DRM. The bimetallic catalyst with the largest weight loss in TGA, 2.5Ni+2.5Fe-MG63, had a loss of 61.3%, a difference of 26% and 21% in the activity performance of CH4 and CO2, respectively, of the tested bimetallic Ni catalysts was recorded. The long-time of 30 h on-stream CH4 and CO2 conversion reactions for 2.5Ni+2.5Co-MG63 and 2.5Ni+2.5Ce-MG63 catalysts showed the catalysts’ high stability. The TPO analysis for the 2.5Ni+2.5Cs-MG63 catalyst showed a peak at 650 °C, attributed to the oxidation of the filamentous carbon, whereas the TPO analysis for the 2.5Ni+2.5Co-MG63 catalyst depicted a peak at 540 °C, ascribed to the presence of amorphous/graphite carbon.
Catalytic Performance of Bimetallic Cobalt–Nickel/Graphene Oxide for Carbon Dioxide Reforming of Methane
Authors: Bakar Sharifah Nur Sorfina Syed Abu , Alsaffar May Ali , Abdullah Bawadi , Shaharun Maizatul Shima , Abdullah Sureena , Ayodele Bamidele Victor
Published: November 2023

The design of economical and robust catalysts is a substantial challenge for the dry reforming of methane (DRM). Monometallic nickel-based catalysts used for DRM reactions had comparable activity to noble metals. However, they turned out to be less stable during the reactions. As a continuation of the interest in synthesizing catalysts for DRM, this paper evaluates the catalytic performance of bimetallic Co–Ni catalysts regarding their synergy effect, with graphene oxide (GO) as support for the first time. The synthesized bimetallic catalysts prepared via the wet-impregnation method were characterized using N2 physisorption analysis, scanning electron microscopy (SEM), thermogravimetric analysis (TGA), and X-ray diffraction (XRD). The catalytic test was performed in a stainless-steel tubular reactor in atmospheric conditions with a reaction temperature of 800 °C, time-on-stream (TOS) of 300 min and CH4: CO2 being fed with a ratio of 1:1. The bimetallic 10 wt%Co–10 wt%Ni/GO and 20 wt%Co–10 wt%Ni/GO catalysts had a similar BET specific surface area in N2 physisorption analysis. The XRD pattern displayed a homogeneous distribution of the Co and Ni on the GO support, which was further validated through SEM–EDX. The conversion of CO2, CH4, and H2 yield decreased with reaction time due to the massive occurrence of side reactions. High conversions for CO2 and CH4 were 94.26% and 95.24%, respectively, attained by the bimetallic 20 wt%Co–10 wt%Ni/GO catalyst after 300 min TOS, meaning it displayed the best performance in terms of activity among all the tested catalysts.
Olfactory Evaluation of Geisha Coffee from Panama Using Electronic Nose
Authors: Santamaría Nohely , Meléndez Félix , Arroyo Patricia , Calvo Patricia , Sánchez Francisco , Lozano Jesús , Sánchez Ramiro
Published: November 2023

Geisha arabica coffee from Panama is featured in the world specialty coffee market. Its quality is assessed by sensory analysis with a panel of experts over several days. However, there is a risk of commercial fraud where cheaper coffees are mixed with pure specialty coffees. For these reasons, having an electronic nose (EN) device proves advantageous in supporting the cupping panel. It allows a greater number of fragrance and aroma analyses to be conducted per day, providing more objective results. In this study, an experimental EN equipped with a metal oxide semiconductor (MOS) gas sensor array was used. Olfactory evaluation of ground and infused Geisha coffee of different roast levels, brewing process, and purity was studied by EN, sensory analysis and chromatography. The sensory analysis perceived significant differences in fragrance and aromas in the light and dark roast levels of the samples. A total of 57 volatile organic compounds (VOC) were studied by gas chromatography. The EN data were analyzed chemometrically with principal component analysis (PCA) and predictive partial least squares (PLS). The data variances for two components were explained with values greater than 82%. The EN demonstrated its ability to differentiate the three levels of roasting, two production processes, and adulteration in the analyzed samples.
Combining Cardiorespiratory Signals and Video-Based Actigraphy for Classifying Preterm Infant Sleep States
Authors: Zhang Dandan , Peng Zheng , Van Pul Carola , Overeem Sebastiaan , Chen Wei , Dudink Jeroen , Andriessen Peter , Aarts Ronald , Long Xi
Published: November 2023

The classification of sleep state in preterm infants, particularly in distinguishing between active sleep (AS) and quiet sleep (QS), has been investigated using cardiorespiratory information such as electrocardiography (ECG) and respiratory signals. However, accurately differentiating between AS and wake remains challenging; therefore, there is a pressing need to include additional information to further enhance the classification performance. To address the challenge, this study explores the effectiveness of incorporating video-based actigraphy analysis alongside cardiorespiratory signals for classifying the sleep states of preterm infants. The study enrolled eight preterm infants, and a total of 91 features were extracted from ECG, respiratory signals, and video-based actigraphy. By employing an extremely randomized trees (ET) algorithm and leave-one-subject-out cross-validation, a kappa score of 0.33 was achieved for the classification of AS, QS, and wake using cardiorespiratory features only. The kappa score significantly improved to 0.39 when incorporating eight video-based actigraphy features. Furthermore, the classification performance of AS and wake also improved, showing a kappa score increase of 0.21. These suggest that combining video-based actigraphy with cardiorespiratory signals can potentially enhance the performance of sleep-state classification in preterm infants. In addition, we highlighted the distinct strengths and limitations of video-based actigraphy and cardiorespiratory data in classifying specific sleep states.
Surgical Management of Adult Brainstem Gliomas: A Systematic Review and Meta-Analysis
Authors: Ius Tamara , Lombardi Giuseppe , Baiano Cinzia , Berardinelli Jacopo , Romano Andrea , Montemurro Nicola , Cavallo Luigi Maria , Pasqualetti Francesco , Feletti Alberto
Published: November 2023

The present review aims to investigate the survival and functional outcomes in adult high-grade brainstem gliomas (BGSs) by comparing data from resective surgery and biopsy. MEDLINE, EMBASE and Cochrane Library were screened to conduct a systematic review of the literature, according to the PRISMA statement. Analysis was limited to articles including patients older than 18 years of age and those published from 1990 to September 2022. Case reports, review articles, meta-analyses, abstracts, reports of aggregated data, and reports on multimodal therapy where surgery was not the primary treatment were excluded. The ROBINS-I tool was applied to evaluate the risk of bias. Six studies were ultimately considered for the meta-analysis. The resective group was composed of 213 subjects and the bioptic group comprised 125. The analysis demonstrated a survival benefit in those patients in which an extensive resection was possible (STR HR 0.59 (95% CI 0.42, 0.82)) (GTR HR 0.63 (95% CI 0.43, 0.92)). Although surgical resection is associated with increased survival, the significantly higher complication rate makes it difficult to recommend surgery instead of biopsy for BSGs. Future investigations combining volumetric data and molecular profiles could add important data to better define the proper indication between resection and biopsy.
Advances and Future Directions in Hepatobiliary Malignancies
Authors: Taura Kojiro
Published: November 2023

I am delighted to present this Special Issue of our journal, focusing on “Hepatobiliary Malignancies: Recent Advancements and Future Directions” [...]
Prognostic 18F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer
Authors: Travaglio Morales Daniela , Huerga Cabrerizo Carlos , Losantos García Itsaso , Coronado Poggio Mónica , Cordero García José Manuel , Llobet Elena López , Monachello Araujo Domenico , Rizkallal Monzón Sebastián , Domínguez Gadea Luis
Published: November 2023

High-grade serous ovarian cancer (HGSOC) is an aggressive disease with different clinical outcomes and poor prognosis. This could be due to tumor heterogeneity. The 18F-FDG PET radiomic parameters permit addressing tumor heterogeneity. Nevertheless, this has been not well studied in ovarian cancer. The aim of our work was to assess the prognostic value of pretreatment 18F-FDG PET radiomic features in patients with HGSOC. A review of 36 patients diagnosed with advanced HGSOC between 2016 and 2020 in our center was performed. Radiomic features were obtained from pretreatment 18F-FDGPET. Disease-free survival (DFS) and overall survival (OS) were calculated. Optimal cutoff values with receiver operating characteristic curve/median values were used. A correlation between radiomic features and DFS/OS was made. The mean DFS was 19.6 months and OS was 37.1 months. Total Lesion Glycolysis (TLG), GLSZM_ Zone Size Non-Uniformity (GLSZM_ZSNU), and GLRLM_Run Length Non-Uniformity (GLRLM_RLNU) were significantly associated with DFS. The survival-curves analysis showed a significant difference of DSF in patients with GLRLM_RLNU > 7388.3 versus patients with lower values (19.7 months vs. 31.7 months, p = 0.035), maintaining signification in the multivariate analysis (p = 0.048). Moreover, Intensity-based Kurtosis was associated with OS (p = 0.027). Pretreatment 18F-FDG PET radiomic features GLRLM_RLNU, GLSZM_ZSNU, and Kurtosis may have prognostic value in patients with advanced HGSOC.
Is Dental Anxiety Associated with Oral Health-Related Quality of Life? Assessment of Statistical Significance and Clinical Meaningfulness in a Sample of Russian Medical and Dental Students
Authors: Heyeraas Christine Nordbø , Jensen Silje Nyborg , Stabell Vilde Bjørkli , Johnsen Jan-Are K. , Drachev Sergei N.
Published: November 2023

Information about oral health-related quality of life (OHRQoL) and dental anxiety (DA) in Russian young adults is scarce. We investigated how DA is associated with OHRQoL in a group of medical and dental students in North-West Russia. The study had a cross-sectional design and included 807 students aged 18–25 years who attended the Northern State Medical University in Arkhangelsk. OHRQoL and DA were measured by the Oral Health Impact Profile (OHIP-14) and Corah’s Dental Anxiety Scale (DAS), respectively. A questionnaire collected information on socio-demographics and self-reported oral health (OH) characteristics. A dental examination was executed to assess dental caries and oral hygiene. We observed differences in the OHIP-14 scores between dentally anxious and non-anxious students: unadjusted incidence rate ratio [IRR] = 1.65, 95% confidence interval [CI]: 1.29–2.12; after adjustment for socio-demographics and clinically assessed OH: IRR = 1.58, 95% CI: 1.23–2.02; after adjustment for socio-demographics, clinically assessed OH, and self-reported OH characteristics: IRR = 1.27, 95% CI: 0.99–1.63. The differences between estimated marginal means for the DAS categories in the models were 2.92, 2.51, and 1.24, respectively. Minimal clinically important differences of OHIP-14 fell between 1.68 and 2.51. We found a negative statistical association between DA and OHRQoL in our study sample, but after adjustment for potential confounders, the association lost its clinical importance.
Covariance Representations and Coherent Measures for Some Entropies
Authors: Zuo Baishuai , Yin Chuancun
Published: November 2023

We obtain covariance and Choquet integral representations for some entropies and give upper bounds of those entropies. The coherent properties of those entropies are discussed. Furthermore, we propose tail-based cumulative residual Tsallis entropy of order α (TCRTE) and tail-based right-tail deviation (TRTD); then, we define a shortfall of cumulative residual Tsallis (CRTES) and shortfall of right-tail deviation entropy (RTDS) and provide some equivalent results. As illustrated examples, the CRTESs of elliptical, inverse Gaussian, gamma and beta distributions are simulated.
Comparison of Coverage-Prediction Models for Modern Mobile Radio Networks
Authors: Mlinar Tomi , Podgrajšek Urban , Batagelj Boštjan
Published: November 2023

The accurate prediction of a signal’s attenuation is essential for the development of reliable, modern, mobile radio-communication networks. In this study, the accuracies of four propagation models in diverse terrains and environments were analyzed using field measurements along a comprehensive test route. We evaluated the ability of the models—Egli, Okumura, Hata–Davidson, and Longley–Rice—to predict signal propagation in the Very-High-Frequency (VHF) and Ultra-High-Frequency (UHF) bands. Based on a meticulous comparison, we present valuable insights into the strengths and limitations of these models, enhancing coverage-prediction methodologies for evolving mobile radio networks. The Egli model, despite its simplicity, introduces significant inaccuracies due to its assumptions and a lack of consideration for the terrain. The Okumura model, which is widely used in urban areas, requires careful correction selection, while the Hata–Davidson model improves upon the former’s weaknesses. The Longley–Rice model excels in flexibility and accuracy, especially in the VHF bands, using topographical data, though it can overestimate the attenuation in shadowed areas. The study concluded that no single model was universally accurate, as each model has its strengths and limitations. It highlights the need for informed model selection based on the terrain’s characteristics and specific requirements. The results will be useful to network planners, helping them to design efficient, mobile communication networks with reliable coverage and optimal spectrum utilization. The Longley–Rice model emerged as particularly powerful, offering detailed predictions across diverse environments.
A Roadheader Positioning Method Based on Multi-Sensor Fusion
Authors: Wang Haoran , Li Zhenglong , Wang Hongwei , Cao Wenyan , Zhang Fujing , Wang Yuheng
Published: November 2023

In coal mines, accurate positioning is vital for roadheader equipment. However, most roadheaders use a standalone strapdown inertial navigation system (SINS) which faces challenges like error accumulation, drift, initial alignment needs, temperature sensitivity, and the demand for high-quality sensors. In this paper, a roadheader Visual–Inertial Odometry (VIO) system is proposed, combining SINS and stereo visual odometry to adjust to coal mine environments. Given the inherently dimly lit conditions of coal mines, our system includes an image-enhancement module to preprocess images, aiding in feature matching for stereo visual odometry. Additionally, a Kalman filter merges the positional data from SINS and stereo visual odometry. When tested against three other methods on the KITTI and EuRoC datasets, our approach showed notable precision on the EBZ160M-2 Roadheader, with attitude errors less than 0.2751° and position discrepancies within 0.0328 m, proving its advantages over SINS.
Puppis: Hardware Accelerator of Single-Shot Multibox Detectors for Edge-Based Applications
Authors: Vrbaski Vladimir , Josic Slobodan , Vranjkovic Vuk , Teodorovic Predrag , Struharik Rastislav
Published: November 2023

Object detection is a popular image-processing technique, widely used in numerous applications for detecting and locating objects in images or videos. While being one of the fastest algorithms for object detection, Single-shot Multibox Detection (SSD) networks are also computationally very demanding, which limits their usage in real-time edge applications. Even though the SSD post-processing algorithm is not the most-complex segment of the overall SSD object-detection network, it is still computationally demanding and can become a bottleneck with respect to processing latency and power consumption, especially in edge applications with limited resources. When using hardware accelerators to accelerate backbone CNN processing, the SSD post-processing step implemented in software can become the bottleneck for high-end applications where high frame rates are required, as this paper shows. To overcome this problem, we propose Puppis, an architecture for the hardware acceleration of the SSD post-processing algorithm. As the experiments showed, our solution led to an average SSD post-processing speedup of 33.34-times when compared with a software implementation. Furthermore, the execution of the complete SSD network was on average 36.45-times faster than the software implementation when the proposed Puppis SSD hardware accelerator was used together with some existing CNN accelerators.
Distributed Ensemble Clustering in Networked Multi-Agent Systems
Authors: Ilić Nemanja , Punt Marija
Published: November 2023

Ensemble clustering, a paradigm that deals with combining the results of multiple clusterings into a single solution, has been widely studied in recent years. The goal of this study is to propose a novel distributed ensemble clustering method that is applicable for use in networked multi-agent systems. The adopted setting supports both object-distributed and feature-distributed clusterings. It is not limited to specific types of algorithms used for obtaining local data labels. The method assumes local processing of local data by the individual agents and neighbor-wise communication of the processed information between the neighboring agents in the network. Using the proposed communication scheme, all agents are able to achieve reliable global results in a fully decentralized way. The network communication design is based on the multi-agent consensus averaging algorithm applied to clustering similarity matrices. It provably results in the fastest convergence to the desired asymptotic values. Several simulation examples illustrate the performance of the proposed distributed solution in different scenarios, including diverse datasets, networks, and applications within the multimedia domain. They show that the obtained performance is very close to that of the corresponding centralized solution.
RoBERTa-Based Keyword Extraction from Small Number of Korean Documents
Authors: Kim So-Eon , Lee Jun-Beom , Park Gyu-Min , Sohn Seok-Man , Park Seong-Bae
Published: November 2023

Keyword extraction is the task of identifying essential words in a lengthy document. This process is primarily executed through supervised keyword extraction. In instances where the dataset is limited in size, a classification-based approach is typically employed. Therefore, this paper introduces a novel keyword extractor based on a classification approach. The proposed keyword extractor comprises three key components: RoBERTa, a keyword estimator, and a decision rule. RoBERTa encodes an input document, the keyword estimator calculates the probability of each token in the document becoming a keyword, and the decision rule ultimately determines whether each token is a keyword based on these probabilities. However, training the proposed model with a small dataset presents two challenges. One problem is the case that all tokens in the documents are not a keyword, and the other problem is that a single word can be composed of keyword tokens and non-keyword tokens. Two novel heuristics are thus proposed to tackle these problems. To address these issues, two novel heuristics are proposed. These heuristics have been extensively tested through experiments, demonstrating that the proposed keyword extractor surpasses both the generation-based approach and the vanilla RoBERTa in environments with limited data. The efficacy of the heuristics is further validated through an ablation study. In summary, the proposed heuristics have proven to be effective in developing a supervised keyword extractor with a small dataset.
Enhancing Wayfinding Experience in Low-Vision Individuals through a Tailored Mobile Guidance Interface
Authors: Jo Taewoo , Yeo Dohyeon , Kim SeungJun
Published: November 2023

Individuals with low vision (LV) face daily wayfinding challenges, struggling with route establishment, direction recognition, and obstacle avoidance. Mobile navigation, though commonly relied upon, often clashes with LV visual conditions, particularly central scotomas from diseases like age-related macular degeneration (AMD), hindering the relay of crucial wayfinding information. Addressing this, we introduced a novel guidance interface post-literature review. In a VR-based user study involving 25 participants simulating LV experience, our map guidance interface enabled quicker navigation, improving system usability and presence. The resulting performance paralleled that of normal-vision individuals. This study demonstrated that modifying familiar navigation interfaces effectively addresses visual impairment conflicts, enhancing outdoor navigation for individuals with LV. The modifications extend benefits, enabling comparable wayfinding ease to individuals with normal vision.