bluuebunny/crossref_metadata_2025 huggingface dataset:
BACH: A Tool for Analyzing Blockchain Transactions Using Address Clustering Heuristics
Authors: Caringella Michele , Violante Francesco , De Lucci Francesco , Galantucci Stefano , Costantini Matteo
Published: July 2024

Cryptocurrencies have now become an emerging blockchain-based payment technology. Users’ identities on such networks are pseudo-anonymous in that all transactions made from an address are transparent and searchable by anyone; to preserve their privacy, users often use many different addresses. In recent years, some studies have been conducted regarding analyzing clusters of Bitcoin addresses that, according to certain heuristics, belong to the same entity. Such action allows law enforcement to have relevant information in cases where cryptocurrencies are used for illegal trafficking. Clustering methods based on a single heuristic do not allow the clustering of many addresses in a complete and accurate manner. This paper proposes Bitcoin Address Clustering based on multiple Heuristics (BACH), a tool that uses three different clustering heuristics to identify clusters of Bitcoin addresses, which are displayed through a three-dimensional graph. Based on the results, several analyses were conducted, including a comparison with Wallet Explorer, an address clustering tool similar to BACH. BACH, in addition to introducing the innovative feature of graphical visualization of the internal structure of clusters, is shown to improve address aggregation through the joint use of three heuristics for clustering.
Geometric Tiling in Spinal Fusion Cages
Authors: Young Christopher
Published: July 2024

The increasing prevalence of spinal disorders and the subsequent rise in spinal fusion surgeries stress the necessity for optimizing spinal fusion cages, crucial for stabilizing the spine and supporting osseointegration. Despite the widespread attempts at material modifications and surface enhancements to improve these devices, failure rates and complications remain significant. This research explores an imaginitive approach to enhancing spinal fusion cages through the application of geometric tiling designs, a method scarcely employed . The study systematically investigates the potential of triangular, diamond, and hexagonal tiling patterns to improve the structural integrity and capability for osseointegration of spinal fusion cages. Through a finite element analysis simulation, each design's ability to withstand multi-directional loads and effectively distribute stress was tested under simulated conditions that mimic the complexities of spinal motion. Preliminary findings in fields of engineering indicate that geometric tiling can significantly enhance the load-bearing capabilities and stress distribution of spinal fusion cages, potentially reducing the likelihood of implant subsidence and failure. The triangular and hexagonal designs, in particular, demonstrate superior performance in maintaining structural stability under axial and anterior compressive forces compared to traditional cage designs. This research opens a new pathway for the development of more durable and efficient spinal fusion cages. By leveraging the structural advantages of geometric tiling, future spinal implants could achieve better clinical outcomes, leading to improved patient recovery and reduced rates of complications.
Synthesis and Biological Study of New Cu(II) and Au(III) Com-Plexes of 2,4-Dithiouracil and Its Derivatives
Authors: Marinova Petya Emilova , Stoitsov Dimitar Genchev , Burdzhiev Nikola Tomov , Tsoneva Slava Hristova , Blazheva Denica Eliyanova , Slavchev Aleksandar Krasimirov , Varbanova Evelina Konstantinova , Penchev Plamen Nikolov
Published: July 2024

The goal of this study is to synthesize, determine the structure, and examine the antimicrobial properties of novel metal complexes of 2,4-dithiouracil and its derivatives. These complexes were obtained by mixing aqueous solutions of the corresponding metal salts with the ligand dissolved in DMSO and aqueous NaOH, using a metal-to-ligand ratio of 1:4:2. The structures of the new compounds were analyzed by melting point determination, microwave plasma atomic emission spectrometry (MP-AES) for Cu and Au, inductively coupled plasma optical emission spectrometry (ICP-OES) for S, ATR, solution and solid-state NMR and Raman spectroscopy. The interpretation of the complex spectra was aided by data for 2,4-dithiouracil obtained from 1H-1H COSY, DEPT-135, HMBC, and HMQC spectra. Additionally, the antimicrobial activity of these complex-es and the free ligands was evaluated against Gram-positive and Gram-negative bacteria, as well as yeasts.
Free Vibration Analysis of Curvilinearly Tapered Axially Functionally Graded Material Beams
Authors: Burlayenko Vyacheslav N. , Kouhia Reijo , Dimitrova Svetlana D.
Published: July 2024

The study focuses on the free vibration analysis of beams made of axially functionally graded materials (AFGM) with curvilinear variable cross-sections along their length. The beams encompass various shapes, including concave and convex conic sections, with axial material properties varying according to polynomial and exponential laws. The equations of motion are derived using Hamilton's principle within the framework of Timoshenko beam theory. These governing equations, subjected to various boundary conditions, are solved using the differential transform method (DTM). The proposed solution technique is validated by comparing computed natural frequencies with existing in literature results and those obtained through three-dimensional finite element analysis in ABAQUS. The incorporation of material gradients into the beam finite element models was achieved through the user-defined material subroutine (UMAT). Additionally, a comprehensive study is conducted to examine the influence of various factors on the natural frequencies of functionally graded beams. These factors include parameters of material laws, types of variable beam shapes, slenderness ratio, and specific boundary conditions. This study provides a thorough understanding of the modal dynamics of the considered beams, offering valuable insights into the behavior of FGM structures.
QuickPic AAC: An AI-Based Application to Enable Just-in-Time Generation of Topic-Specific Displays for Persons Who Are Minimally Speaking
Authors: Yu Christina , Schlosser Ralf , Fontana de Vargas Maurício , White Leigh Anne , Koul Rajinder , Shane Howard
Published: July 2024

As artificial intelligence (AI) makes significant headway in various arenas, the field of Speech-Language Pathology is at the precipice of experiencing a transformative shift towards automation. This study introduces QuickPic AAC, an AI-driven application designed to generate topic-specific displays from photographs in a "just-in-time" manner. Using QuickPic AAC, this study aimed to (a) determine which of two AI algorithms (NLG-AAC and GPT-3.5) results in greater specificity of vocabulary (i.e., percentage of vocabulary kept/deleted by clinician relative to vocabulary generated by QuickPic AAC; percentage of vocabulary modified); and to (b) evaluate perceived usability of QuickPic AAC among practicing speech-language pathologists. Results revealed that the GPT-3.5 algorithm consistently resulted in greater specificity of vocabulary and that speech-language pathologists expressed high user satisfaction for the QuickPic AAC application. These results support continued study of the implementation of QuickPic AAC in clinical practice and demonstrate the possibility of utilizing topic-specific displays as just-in-time supports.
Digital Twin Technology in Built Environment: A Review of Applications, Capabilities and Challenges
Authors: Mousavi Yalda , Gharineiat Zahra , Aghakarimi Armin , McDougall Kevin , Rossi Adriana , Gonizzi Barsanti Sara
Published: July 2024

Digital Twin (DT) technology is a pivotal innovation within the built environment industry, facilitating digital transformation through advanced data integration and analytics. DTs have demonstrated significant benefits in building design, construction, and asset management, including optimizing lifecycle energy use, enhancing operational efficiency, enabling predictive maintenance, and improving user adaptability. By integrating real-time data from IoT sensors with advanced analytics, DTs provide dynamic and actionable insights for better decision-making and resource management. Despite these promising benefits, several challenges impede the widespread adoption of DT technology, such as technological integration, data consistency, organisational adaptation, and cybersecurity concerns. Addressing these challenges requires inter-disciplinary collaboration, standardization of data formats, and the development of universal design and development platforms for DTs. This paper provides a comprehensive review of DT definitions, applications, capabilities, and challenges within the Architecture, Engineering, and Construction (AEC) industries. This paper provides important insights for researchers and professionals, helping them gain a more comprehensive and detailed view of DT. The findings also demonstrate the significant impact that DTs can have on this sector, contributing to advancing DT implementations and promoting sustainable and efficient building management practices. Ultimately, DT technology is set to revolutionize the AEC industries by enabling autonomous, data-driven decision-making and optimizing building operations for enhanced productivity and performance.
UsingTask Support Requirements During Socio-Technical Systems Design
Authors: Gregoriades Andreas , Sutcliffe Alistair
Published: July 2024

Critical phases in socio-technical systems (STS) design are the definition of functional requirements for automated or software supported human activities while also addressing social and human interaction issues. To define automation support for human operations, STS designers need to ensure that specifications will satisfy not only non-functional requirements (NFR) of the system but also of its human actors such as human reliability/workload. However, such human factors aspects are not addressed sufficiently with traditional STS design approaches which could lead to systems failure or rejection. This paper proposes a new STS design method that addresses this problem and introduces a novel type of requirements namely Task Support Requirements (TSR) that assists in specifying the functionality that the system should have to support human agents in undertaking their tasks by addressing human limitations. The proposed method synthesizes a requirements/software engineering approach to STS design with functional allocation and an HCI perspective which facilitate application of human factors knowledge in conceptual models and evaluation through VR simulation. A case study methodology is employed in this work that allows in-depth, multi-faceted explorations of the complex issues that characterize STS.
Periodic and Quasi periodic Orbits in the Collinear Four-Body Problem: A Variational Analysis
Authors: Mansur Abdalla , Shoaib Muhammad , Szücs-Csillik Iharka , Offin Daniel , Brimberg Jack , Fgaier Hedia
Published: July 2024

This paper investigates the periodic and quasi-periodic orbits in the symmetric collinear four-body problem through a variational approach. In Section 3, we analyze the conditions under which homographic solutions minimize the action functional. We demonstrate that these solutions for four equal masses arranged in a linear configuration are indeed the minimizers of the action functional and compute the minimum value of the action functional for these solutions. Additionally, we employ numerical experiments using Poincaré sections to explore the existence and stability of periodic and quasi-periodic solutions within this dynamical system. Our results provide a deeper understanding of the variational principles in celestial mechanics and reveal complex dynamical behaviors that are crucial for further studies in multi-body problems. The findings have significant implications for theoretical research and practical applications in astrodynamics and space mission planning.
Assessment of Adolescent Soccer Players' Physical Performance Using Inertial Measurement Units and Principal Component Analysis
Authors: Villa Giacomo , Papaioannou Foivos , Galli Manuela , Cimolin Veronica
Published: July 2024

Despite soccer popularity, comparatively little scientific information is available concerning the assessment of youth players’ physiological characteristics. The use of medical software integrating wearable sensors to provide accurate and objective data is necessary. In the present study, the objective assessment of physical performance of 128 adolescent soccer players at two timepoints (pre-season and end-season) has been performed. Participants completed a comprehensive test battery including stability, countermovement jumps (CMJ), plyometric jumps (PJ), agility, and quick feet tests. A single Inertial Measurement Unit (IMU) sensor provided quantitative data on various performance metrics. Principal Component Analysis (PCA) reduced the dataset to four principal components (PCs) explaining over 80% of the variance: power (PC1), balance (PC2), speed/agility (PC3), and stiffness (PC4). Paired samples t-test between the two timepoints showed no significant differences in the PCs between the two timepoints, indicating that the training program did not significantly alter the assessed physical attributes. However, subtle individual changes may still inform personalized training adjustments. The study highlights the importance of continuous monitoring and individualized training strategies to optimize athlete performance and reduce injury risk.
Nanopore Sequencing Allows Recovery of High-Quality Completely Closed Genomes of All Cronobacter Species From Powdered Infant Formula Overnight Enrichments
Authors: Gonzalez-Escalona Narjol , Kwon Hee Jin , Chen Yi
Published: July 2024

Precision metagenomic approaches using Oxford Nanopore Technology (ONT) sequencing has been shown to allow recovery of complete genomes of Escherichia coli O157:H7 from overnight enrichments of agricultural waters. This study tests the applicability of a similar approach for Cronobacter genome recovery from powdered infant formula (PIF) overnight enrichments, where Cronobacter typically dominates the overall microbiome (>90%). In this study, we aimed to test whether using ONT sequencing of overnight PIF enrichments could recover a completely closed Cronobacter genome for further genomic characterization. Ten PIF samples, each inoculated with different Cronobacter strains, covering Cronobacter sakazakii, C. muytjensii, C. dublinensis, C. turicensis, and C. universalis, were processed according to the Bacteriological Analytical Manual (BAM) protocol. qPCR was used for initial screening (detection and quantification) of the overnight enrichments and confirmed that the spiked PIF samples after the overnight enrichment have high levels of Cronobacter (107 to 109 CFU/mL). DNA from overnight PIF enrichments was extracted from the enrichment broth and sequenced using ONT. Results showed that ONT sequencing could accurately identify, characterize, and close the genomes of Cronobacter strains from overnight PIF enrichments in 3 days, much faster than the nearly two weeks required by the current BAM method. Complete genome recovery and species differentiation were achieved. This suggests that combining qPCR with ONT sequencing provides a rapid, cost-effective alternative for detecting and characterizing Cronobacter in PIF, enabling timely corrective actions during outbreaks.
In situ treatment of refractory canine perianal fistulas with low-dose allogeneic adipose tissue-derived mesenchymal stem cells
Authors: Enciso Nathaly , Enciso-Benavides Javier , Sandoval Juan , Enciso Javier
Published: July 2024

Stem cell therapy in canines has increased considerably in recent years; however, there are few publications on the treatment of perianal fistulas (PF) in this species, and there is no agreed protocol for the number of cells per dose and their repetitions, nor for the in situ delivery methodology and follow-up period after cell therapy. The aim of this open-label clinical trial was to demonstrate the efficacy and safety of a new protocol for in situ administration of low-dose, expanded and cryopreserved allogeneic adipose-derived stem cells for the treatment of refractory spontaneous perianal fistula. The methodology consisted of intralesional application of 1 to 3 doses - depending on evidence of clinical signs of recurrence - of 5x106 cryopreserved allogeneic adipose-derived allogeneic stem cells in each fistula. The study was conducted in 14 dogs regardless of sex, breed or age with a clinical diagnosis of refractory PF presented between January 2019 and December 2023. Cells were diluted in 1 mL of phosphate-buffered saline and this volume was applied to five sites at the edge of the FP in an amount of 1x106 per application site. The evolution of the fistula was followed for 12 to 48 months. Efficacy was determined by complete healing as evidenced by complete closure of the fistula, which was observed in 100% of the cases studied one month after therapy, with a subsequent follow-up of 12 to 48 months after therapy. In addition, there were no local or systemic adverse effects assessed by clinical examination, complete blood count and blood biochemistry. In conclusion, the protocol used in this work demonstrates the efficacy without adverse effects of in situ application of allogeneic adipose-derived adipose stem cells in low doses and cell replicates to treat canine refractory PF, providing a simple, non-invasive, long-lasting and low-cost therapeutic option.
Therapeutic Advancement of Adiponectin in Age-Related Macular Degeneration and Other Metabolic Disorders.
Authors: Singh Anusha , Bora Nalini , Bora Puran
Published: July 2024

Adiponectin (APN) has been thoroughly investigated for its role in various human disorders. It is fascinating to note that this peptide plays an essential role as a therapeutic agent to cure a plethora of disorders. Our aim is to elucidate the applications and therapeutic potential of this peptide, demonstrating its involvement in age-related macular degeneration (AMD) and other metabolic disorders. APN has been correlated with many ocular disorders and metabolic disorders. The localization and expression of APN in various tissues were the first markers of its local actions. Screening this peptide on a wider platform helps to confirm its application as a novel peptide in various diseases. Altered levels of APN have been well elucidated in the progression of metabolic disorders, and its targeted administration has resulted in combating dysregulation of biochemical and molecular pathways involved in disease pathology. A close association of oxidative stress is also known to contribute to the onset of retinal disorders. Among so many APN has been shown to have a promising response in the context of wet AMD, but further studies are needed to elucidate its full potential in humans.
The Hydroxyapatite-Filled Acrylonitrile-Butadiene Rubber Composites with Improved Cure Characteristics and Reduced Flammability
Authors: Maciejewska Magdalena , Rybiński Przemysław , Sowińska-Baranowska Anna
Published: July 2024

The goal of this work was to develop the acrylonitrile-butadiene (NBR) elastomer composites filled with hydroxyapatite (HAP), which were characterized with improved cure characteristics and burning resistance. Silane, i.e., (3-aminopropyl)-triethoxysilane, ionic liquid, i.e., 1-decyl-3-methylimidazolium bromide and surfactant, i.e., cetyltrimethylammonium bromide, were used to improve the filler’s dispersibility in the elastomer matrix and to reduce the time and temperature of vulcanization. The effect of HAP and dispersants on the cure characteristics, crosslink density and physico-chemical properties of NBR composites was explored. The additives used, especially the ionic liquid and surfactant, effectively improved the dispersion of HAP in NBR matrix. The amount of HAP and the dispersant used strongly affected the cure characteristics and crosslink density of NBR. The optimal vulcanization time significantly increased with HAP content and was pronouncedly reduced when ionic liquid and surfactant were applied. In addition, ionic liquid and surfactant significantly lowered the onset vulcanization temperature, improved the crosslink density and hardness of the vulcanizates, while impairing their elasticity. HAP and dispersants did not significantly affect the damping properties and chemical resistance of NBR vulcanizates. Above all, application of HAP considerably enhanced the resistance of vulcanizates to thermo-oxidative aging and reduced their flammability compared to the unfilled NBR.
Crossing the “European Green Deal” Maritime Measures and the Unfair Competition on the ETS Tax Regime—The Deviation Traffic Danger Between EU and Non-EU Hub Ports
Authors: LYNCE DE FARIA DUARTE
Published: July 2024

The maritime industry contributes to over 80% of global trade and ranks as the sixth-largest emitter of greenhouse gases. The International Maritime Organization has taken strides to reduce these emissions, while the European Union spearheads efforts to establish sustainable maritime transport. However, meeting decarbonisation targets poses significant challenges, with the potential implications of adopting an EU Emission Trading System (ETS) on shipping allowances, particularly at specific borders. If not managed effectively, this could result in diversifying regular container shipping routes away from EU ports, potentially leading to increased shipping emissions and disrupting the logistics trade and security chain. These challenges are exacerbated by the International Maritime Organization's lack of a carbon fee on bunkering, which creates an imbalance. The ETS Directive has fostered unfair competition between EU and non-EU ports due to discrepancies in applying emission unit allowances. It is imperative to implement preventive measures to contain and prevent the shift of operations from EU ports to nearby ports, ensure equitable treatment of EU transhipment ports and their competitors, and thwart carbon leakage. Additionally, the recent Houthis attacks on the Red Sea have significantly impacted shipping costs on the Cape of Good Hope route to Europe, necessitating increased allowances to and from Europe.
Sparse Modelling for Feature Learning in High Dimensional Data
Authors: Neelam Harish , Veerella Koushik Sai , Biswas Souradip
Published: July 2024

This paper presents an innovative approach to dimensionality reduction and feature extraction in high-dimensional datasets, with a specific application focus on wood surface defect detection. The proposed framework integrates sparse modeling techniques, particularly Lasso and proximal gradient methods, into a comprehensive pipeline for efficient and interpretable feature selection. Leveraging pre-trained models such as VGG19 and incorporating anomaly detection methods like Isolation Forest and Local Outlier Factor, our methodology addresses the challenge of extracting meaningful features from complex datasets. Evaluation metrics such as accuracy and F1 score, alongside visualizations, are employed to assess the performance of the sparse modeling techniques. Through this work, we aim to advance the understanding and application of sparse modeling in machine learning, particularly in the context of wood surface defect detection.
The Nigerian Dietary Screening Tool: A Step Toward Improved Patient-Clinician Communication in Nigerian Hospitals: A Pilot Implementation Study
Authors: Batubo Nimisoere P , Auma Carolyn I , Moore J. Bernadette , Zulyniak Michael A
Published: July 2024

Implementing dietary screening tools into clinical practice has been challenging, including in Nigeria. This study evaluated the impact of the Nigerian dietary screening tool (NiDST) on patient-clinician communication and barriers to and facilitators of implementation. Mixed methods approach was used to collect data from patients (n=151) and clinicians (n=20) from outpatient clinics in Nigeria. Patients completed the validated 25-item NiDST prior to outpatient consultations. Both patients and clinicians completed the Measurement Instrument for Determinants of Innovations (MIDI) questionnaire to assess implementation determinants post-consultation. Semi-structured interviews were conducted for in-depth feedback. Fidelity of implementation was 92% for NiDST-reported dietary discussion, with a mean completion time of < 6 minutes and an accepted marginal increase in consultation time (< 10 mins). For clinicians, 25% reported time constraints and their additional nutritional knowledge as barriers, while facilitators of NiDST implementation were the clarity and completeness of the NiDST, clinical relevance and improved patient-clinician communication, as reported by all the clinicians. Over 96% of patients reported the NiDST as quick to complete, with 90.7% reporting self-reflection on dietary intake. This study demonstrated the NiDST's potential to enhance patient-clinician communication and highlighted major facilitators of implementation in clinical practice to improve dietary discussion in Nigeria.
Assessment of Earthquake Damage and Economic Recovery in Hatay Province, Turkey Using Nighttime Light Data
Authors: Li Feng , Liao Shunbao , Zhang Xiaobo , Liu Tianxuan
Published: July 2024

The catastrophic twin earthquakes that struck southern Turkey and northern Syria on February 6 2023, caused massive casualties and extensive damage to infrastructure, with the province of Hatay bearing the brunt of the impact. To investigate the potential of nighttime light (NTL) data for earthquake disaster assessment, we performed an analysis of pre- and post-earthquake NPP-VIIRS and SDGSAT-1 NTL data. The NTL change ratio (NCR) was employed to identify the extent of damage in Hatay Province following the earthquake to assess the impact on affected buildings and populations. NPP-VIIRS daily NTL Time-series data was used to establish an economic recovery framework for earthquake disasters in Hatay Province, assessing regional economic recovery after earthquake. The results revealed a strong correlation between the total reduced NTLs of NPP-VIIRS and SDGSAT-1 and the presence of severely and moderately damaged buildings. Conversely, the correlation with slightly damaged buildings was relatively weaker. Furthermore, the reduced NTLs of NPP-VIIRS provide a more precise identification of all earthquake damage compared to the SDGSAT-1 data, achieving an overall accuracy of 86.21% in earthquake damage identification and a Kappa coefficient of 0.72. In accordance with the earthquake economic recovery framework, as of the end of March 2024, neither the provincial economy nor any of its districts have fully restored to their pre-earthquake levels. The findings offered new and valuable insights into earthquake disaster assessment, assisting decision-makers in accurately assessing the level of disaster risk following an earthquake and efficiently allocating post-earthquake relief funds.
Prediction of Immune Checkpoint Inhibitors Treatment Response of Non-small Cell Lung Cancer Patients from Serial Computed Tomography Scans Based on Global Self-Attention Mechanism
Authors: Wu Yuemin , Guan Runwei , Liang Xiao , Zhang Wei , Jiang Yuqin , Cui Yanan , Zhou Wenxin , Liang Qi , Zhang Pengpeng , Chen Yi , Dai Jiali , Zhang Chen , Xu Jiali , Li Jun , Yu Tongfu , Guo and Renhua
Published: July 2024

The aim of the present study was to predict the response of non-small cell lung cancer (NSCLC) patients to immune checkpoint inhibitors (ICIs) by leveraging computed tomography (CT) images using deep learning techniques. Retrospectively, 624 sequential CT images were gathered from 156 patients at Jiangsu Province Hospital, along with their clinical data. The dataset was subsequently partitioned into three groups: training (n=547), validation (n=64), and test (n=64). Moreover, an external validation cohort included 37 CT images from patients at Nanjing Pukou Peoples' Hospital, accompanied by comprehensive clinical data. An advanced Video Vision Transformer (ViViT) model incorporating global self-attention was utilized to analyse patients treated with ICIs and predict their response. The ViViT model's efficacy was evaluated using a confusion matrix and a receiver operating characteristic curve (ROC). Notably, the ViViT model demonstrated predictive prowess for ICIs response, yielding respective areas under the receiver operating characteristic curve (AUC) of 0.74 (95% CI: 0.69-0.78), 0.74 (95% CI: 0.61-0.86), 0.76 (95% CI: 0.62-0.88), and 0.69 (95% CI: 0.5-0.87) in the training, validation, test, and external validation cohorts. The present study illustrates how a deep learning model can provide a non-invasive means to predict clinical outcomes in NSCLC patients undergoing ICIs, potentially transforming personalized treatment approaches for individuals with NSCLC.
Development and Performance Assessment of Low-Cost Sensors for Pollutants Concentration Measurement
Authors: Russi Luigi , Guidorzi Paolo , Semprini Giovanni , Trentini Arianna , Pulvirenti Beatrice
Published: July 2024

The use of low cost sensors has dramatically increased in recent years in all the engineering sectors. In the field of buildings and automotive, low cost sensors open very interesting perspectives, because they allow to monitor temperature and humidity distributions together with air quality, in a widespread and punctual way and allow control of all energy parameters. The main issue still open remains the validation of the measurements. In this work, we propose an innovative approach to verify the measurements given by some low-cost systems built ad hoc for automotive applications. Two independent low-cost measurement systems have been set to measure Particulate air Matter (PM) concentration, TVOC concentration, CO2 concentration, formaldehyde concentration, air temperature, relative humidity, pressure, air flow velocity and GPS position. These systems have been calibrated by the comparison with standard and certified sensors used by the regional authority of Emilia-Romagna region (ARPAE, Italy) for characterising the air-quality. The innovation of this approach lies in both the in-field comparison of low-cost and high quality sensors and the use of proper conversion approaches for mass concentration measurements. A quantitative analysis of the sensors performance is given, with a focus on effects of time-granularity, relative humidity, mass conversion from particle counts and size detection response. The results show that the low-cost sensors measurements of air temperature, relative humidity and particle number concentration are in a good agreement with high quality sensors measurements, with a strong impact of relative humidity on performance indicators. Overall, a good quality and consistency of the data among the sensors has been achieved.
Spontaneously Hypertensive Rats Present Exacerbated Focal Stroke Behavioral Outcomes
Authors: Moreira João Victor Matos e , Bernardi Luis Pedro , Teixeira Fernanda Cardoso , Paniago Jerônimo , Teixeira Luciele Varaschini , Bifi Felippo , de Souza Diogo Onofre , Rohden Francieli
Published: July 2024

This study aimed to compare the effects of a permanent ischemic stroke model (focal ischemia by thermocoagulation of pial vessels) on sensorimotor function (cylinder test and adhesive removal test), behavioral tasks (novelty habituation memory-open field task), and cerebral infarct size in adult male spontaneously hypertensive rats (SHR) and normotensive Wistar Kyoto (WKY) rats over 42 days after the occurrence of stroke. We observed that the stroke caused asymmetry in the front paws and delayed adhesive removal. These effects were spontaneously reduced in WKY rats, but not in SHR. Short- and long-term novelty habituation memories were abolished by stroke in WYK and SHR. On the 3rd day after stroke, the size of the focal cerebral infarct was the same in WKY and SHR. However, on the 7th day, the infarct size decreased in WKY rats, but not SHR. These results suggested that SAH impairment of sensorimotor recovery in rats subjected to cerebral ischemia could be related to augmented focal cerebral infarct size. Moreover, the behavioral tasks used in this study were unaffected by Systemic Arterial Hypertension. Our results highlight the need for animal models of comorbidities in stroke research.
Direct Solar Thermal Water Splitting Using Iron Electrodes at High Temperatures - A Review
Authors: Fuentes Manuel , Pulido Diego , Fuentealba Edward , Soliz Alvaro , Toro Norman , Sagade Atul , Galleguillos Madrid Felipe M.
Published: July 2024

Green hydrogen is a fuel that in the coming years will play a very important role in the energy transition process in developed countries, especially those seeking to reach a level of zero emis-sions, for which reason its demand is expected to increase significantly. This article analyzes the fundamentals to produce hydrogen, with a focus on the oxidation reaction of a thermochemical solar cycle for the dissociation of water vapor. Solar thermochemical cycles have been extensively investigated, but it is still in the development stage by groups of researchers who have focused on finding the right materials and conditions to improve the efficiency of the process, especially at high temperatures. The theoretical foundations are analyzed, compiled from exhaustive scientific investigations related to the oxidation of iron in water vapor, the relationship with the activation energy of the corrosive process, thermodynamic aspects and the kinetic model according to a heterogeneous reaction. In addition, some high temperature oxidation mechanisms, pH effects, reactors and materials (fluidized beds) used are presented. The scientific review indicates that the production of hydrogen through a thermochemical cycle is more efficient than electrochemical processes (electrolysis), if the limitations of the reduction stage of the cycle are overcome.
Pediatric Obesity and Non-Hepatobiliary Gastrointestinal Disorders: A Comprehensive Review
Authors: Sen Sandipan , Misra Sudipta
Published: July 2024

Background and Aims: Obesity is a pervasive health issue in children. It affects multiple systems in the body including the gastrointestinal tract. Research on obesity-related gastrointestinal diseases has focused mostly on hepatobiliary disorders. However, non-hepatic gastrointestinal diseases such as gastroesophageal reflux, constipation, and functional abdominal pain, though common and debilitating, have not been highlighted in the context of obesity. These entities can downgrade the already compromised lifestyle of obese children. Some of these disorders are more difficult to treat in these children compared to their peers with normal body mass index. Method: We reviewed the available literature on the association between obesity and these three common gastrointestinal disorders.
Results: - There appears to be a strong correlation between childhood obesity and constipation and gastroesophageal reflux, and a probable correlation with functional abdominal pain.
Conclusion: We suggest that given the available literature, weight management should be an integral part of the management of gastroesophageal reflux, constipation, and functional abdominal pain in obese children. This gains relevance especially because of the recent availability of medications for the treatment of obesity in children.
Physics of Superconductors Polycyclic Aromatic Hydrocarbons (PAH)
Authors: Escobar Martín David
Published: July 2024

In this work, we will study metallic clusters equivalent to the organic ones intercalated with metals, of solid benzene type, Ba anthracene and K3.45picene; and we will try to calculate its superconducting Tc, for each of these compounds, from electronic correlations at room temperature. We will also study metal hydrides and clusters, totally composed of metals, which adopt forms analogous to molecular organic picene and anthracene; also calculating its TC.
Innovative Bio-Vehicle For Resveratrol And Tocopherol Based On Quinoa 11s Globulin. Nanocomplexes Design And Characterization
Authors: Rubinstein Alejandra , Garcia Liñares Guadalupe , Boeris Valeria , Perez Oscar
Published: July 2024

The objective of the present contribution was to design and characterize resveratrol (RSV) and tocopherol (TOC) loaded 11S quinoa seed protein nanocomplexes. Firstly, molecular docking was performed to describe the probable binding sites between protein and ligands. Isothermal titration calorimetry allowed to obtain the thermodynamic parameters that described the molecular interactions between RSV or TOC with the protein. 11S globulin intrinsic fluorescence spectra showed a quenching effect exerted by RSV and TOC, demonstrating protein-bioactive compounds interactions. Stern-Volmer, Scatchard and Förster resonance energy transfer models application confirmed static quenching and allowed to obtain parameters that described the 11S-RSV or 11S-TOC complexation process. Secondly, protein aggregation induced by bioactive compounds interactions was confirmed by dynamic light scattering and atomic force microscopy with diameters <150 nm, detected by both techniques. Finally, it was found that antioxidant capacity of single 11S globulin did not decrease, meanwhile was additive for 11S-RSV. These nanocomplexes could constitute a real platform for the design of nutraceutical products.
Using Ultrasonography to Definitively Diagnose Indeterminate Thyroid Nodules
Authors: Guerreiro Sofia , Mourão Mariana , Loureiro Isabel , Eusébio Rosário , Pinto Marques Hugo
Published: July 2024

Introduction: Thyroid nodules are extremely common and require complex management to prevent unnecessary surgical intervention and ensure that no malignant disease is overlooked. Several diagnostic tools and scoring systems are available to evaluate the Risk of Malignancy (ROM). The goal is to assess variables that can aid and support the clinical recommendations suggested by the updated Bethesda System for Reporting Thyroid Cytopathology (TBSRTC), such as the ultrasonographic features of thyroid nodules, particularly for indeterminate categories III (atypia of undetermined significance) and IV (follicular neoplasm). Methods: We retrospectively analysed the correlation of the demographic and ultrasonographic characteristics of thyroid nodules with the cytopathological and histopathological diagnoses of TBSRTC categories III (atypia of undetermined significance), IV (follicular neoplasm), V (suspicious for malignancy), and VI (malignant) in patients who underwent surgery in a single Portuguese centre over a 10-year period. Results: In total, 360 nodules were evaluated in 341 patients and 57% were histopathologically malignant or borderline. The majority were included in the TBSRTC indeterminate categories III and IV with an ROM of 44% and 43%, respectively. The ultrasonographic characteristics associated with a higher TBSRTC category and a greater ROM value were hypoechogenicity, presence of microcalcifications, irregular margins, and the presence of cervical adenopathy. When correlating with a malignant histology, only adenopathy and the presence of microcalcifications were observed to be statistically significant. Discussion: The indeterminate categories of the TBSRTC have been the most challenging ones to manage. The new TBSRTC (2023) guidelines as well as the ultrasonographic characteristics of a patient can be helpful in assessing the ROM and deciding on an appropriate course of treatment. Other resources, such as molecular tests, are also gaining a more important role in the clinical decision process and may become crucial in the future. Conclusion: The clinical management of thyroid nodules requires a careful analysis of clinical history and an evaluation of demographic details, the symptoms of the patient, comorbidities, personal and family history, ultrasonographic features, and the results of cytopathology, thyroid function, and molecular/genetic tests to provide the best care possible. Patients with thyroid nodules of an indeterminate character can obtain a definitive diagnosis through surgery. However, by employing a complete analysis of all relevant data, some patients may be suitable for active surveillance instead of a surgical intervention.
IoT Wearable Sensors for Automatic Boxing Punch Recognition and Classification Based on Upper Limb Biomechanics
Authors: Manoharan Saravanan , Warburton John , Hegde Ravi Sadananda , Srinivasan Ranganathan , Srinivasan Babji
Published: July 2024

Identifying punch types as part of punch kinematic analysis is a key component for both coaches and players, providing critical insights into the variety and effectiveness of punches, which are essential for refining overall performance. Existing research indicates that punch type classification typically relies on data from either wearables or video data. Both approaches have their merits and demerits but require a significant amount of labeled data for modeling the classification algorithm. In this work, we propose a novel approach that significantly reduces the labeling effort by one-sixth by leveraging video data to enhance the training information of sensor data. This enriched training phase enables more accurate punch classification with reduced labeled data. Subsequently, the real-time punch identification and classification use only the wearable data. On a real dataset, with 15% of the labeling efforts, our approach achieved an accuracy rate of 91.41% for rear hand punch recognition and 91.91% for lead hand punch recognition, along with 92.33% and 94.56% for punch classification, respectively. Through the development of our Smart Boxer system, we aim to revolutionize punch analytics in boxing, providing comprehensive insights while enhancing the overall training and competitive experience for athletes and enriching fan engagement with the sport.
Impact of Image Size and Image Overlap on the Prediction Performance of Convolutional Neural Networks Trained for Road Classification
Authors: Cira Calimanut-Ionut , Manso Callejo Miguel Angel , Yokota Naoto , Sălăgean Tudor , Badea Ana-Cornelia
Published: July 2024

Popular geo-computer vision works make use of aerial imager with sizes ranging from 64 × 64 to 1024 × 1024 pixels without any overlap, although the learning process of deep learning models can be affected by the reduced semantic context or the lack of information near image boundaries. In this work, the impact of three image sizes (256 × 256, 512 × 512, and 1024 × 1024 pixels) and two image overlap levels (no overlap and 12.5% overlap) on the performance of road classification models was statistically evaluated. For this, two convolutional neural networks used in various tasks of geospatial object extraction were trained (using the same hyperparameters) on a large dataset (containing aerial image data covering 8650 km² of the Spanish territory that was labelled with binary road information) under twelve different scenarios, each scenario featuring a different combination of tile size and overlap. To assess their generalisation capacity, the performance of all resulting models was evaluated on a data from novel areas covering approximately 825 km². The performance metrics obtained were analysed using appropriate descriptive and inferential statistical techniques to evaluate the impact of the performance at distinct levels of the fixed factors (tile size, tile overlap, neural network architecture). Statistical tests were applied to study the main and interaction effects of the fixed factors on the performance. A significance level of 0.05 was applied to all the null hypothesis tests. The results were highly significant for the main effects (p-values lower than 0.001), while the two-way and three-way interaction effects among them had different levels of significance. The results indicate that the training of road classification models on images with a higher tile size (more semantic context) and tile overlap (additional border context and continuity) significantly impacts their performance. The best model was trained on a dataset featuring tiles with a size of 1024 × 1024 pixels and a 12.5% overlap and achieved a loss value of 0.0984, an F1 score of 0.8728, and an ROC-AUC score of 0.9766, together with an error rate of 3.5% on the test set.
Photovoltaic Power Generation Systems MPPT Controller Optimization Using IWOA and P&O: A Hybrid Approach under Various Operating Conditions
Authors: Liu Tan , Liu Sisi , Yu Hexv , Wu Zhiyi , Tong Jiaqi , Yuan Qingyun
Published: July 2024

This paper proposes a novel approach called Multi-strategy Improved Chaotic Whale fused with Perturbation Observation method (IWOA-PO) for Maximum Power Point Tracking (MPPT) con-trol, to address the challenge of low efficiency in photovoltaic (PV) power generation under local shadows, according to the features of whale optimization algorithm (WOA) and perturbation observation (P&O) method. In the early stage of control algorithm, IWOA is used for global search to quickly locate the position of the Maximum Power Point (MPP). In the later stage of control algorithm, P&O is used for fine-grained local search to quickly, accurately and low oscillation track the position of the global maximum power point (GMPP). In order to verify the correctness, the tracking performance of IWOA-PO is comprehensively compared with WOA-PO、WOA、PSO under four conditions including uniform illumination, static partial shade, dynamic irradiance mutation and sudden changes in temperature and irradiance. In the above four conditions, the IWOA-PO algorithm has faster convergence and less power oscillations compared to the re-maining three algorithms, indicating that the IWOA-PO algorithm is effective. Finally, a physical verification experiment process is built to verify the correctness and effectiveness of the algorithm proposed in this paper.
Growth Performance and Survival of African Catfish (Clarias gariepinus) Larvae Fed on Locally Formulated Feeds
Authors: Melaku Abelneh Yimer
Published: July 2024

The lack of quality formulated feeds as supplements or replacements for live feeds has negatively impacted the growth performance and survival rates in the larvae of many fish species, notably African catfish (C. gariepinus). Successful larval rearing relies on the availability of suitable diets that are readily consumed, easily digested, and provide the essential nutrients necessary for optimal growth and health of the fish. This study evaluated the growth performance and survival rates of C. gariepinus larvae when fed locally formulated diets. The experiment was conducted using 12 basins, each with a capacity of 20 liters. Each basin was stocked with 60 larvae in four replicates, averaging 0.03 g in weight. The experimental diets were formulated to contain three different levels of crude protein: 40%, 45%, and 50%. The larvae were fed these diets at a rate of 10-20% of their body weight over 70 days. Initially, the larvae were fed artemia at the onset of feeding in hatchling basins immediately after yolk sac absorption for the first seven days. This was followed by a blend of artemia and formulated feeds for 14 days. After 28 days, the larvae were transitioned to be exclusively fed the formulated dry feeds. The results indicated that the larvae fed on diets containing 45% and 50% crude protein exhibited significantly better overall growth performance compared to those fed on a 40% crude protein diet. Specifically, the larvae that received the 45% and 50% crude protein diets showed higher final mean weight, increased daily weight gain, and improved survival rates, which ranged from 80% to 81.5%. Notably, there was no significant difference in growth performance and survival rates between the larvae fed on 45% and 50% crude protein diets, suggesting that a 45% crude protein-formulated diet is sufficient to achieve the best growth performance and survival rates for C. gariepinus larvae. This study supports the recommendation of feeding C. gariepinus larvae with a dry diet containing 45% crude protein starting from 14 days post-hatching to enhance their growth and survival rates. However, further research is recommended to explore the effects of this feeding regimen across different agroecological zones and aquaculture systems to validate and potentially refine these findings.