bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced Mechanical Properties of Ceramic Rod Reinforced TWIP Steel Composites: Fabrication, Microstructural Analysis, and Heat Treatment Optimization
Authors: Sun Guojin , Li Zhenggui , Wang Qi
Published: August 2024

This study explores the development and characterization of ceramic rod reinforced TWIP (Twinning Induced Plasticity) steel matrix composites, fabricated using a lost foam casting process. The incorporation of ceramic rods aims to enhance the mechanical properties of TWIP steel, which is known for its excellent plasticity. Mechanical testing demonstrated a significant improvement in flexural strength and ductility, with the composite exhibiting over double the strength of the unreinforced TWIP steel. Heat treatment at 500°C for 60 minutes further enhanced these properties, increasing the composite's flexural strength to 1023 MPa and improving its ductility. The observed improvements are attributed to the synergistic effects of the hard ceramic reinforcement and the ductile matrix, as well as the microstructural modification conferred by heat treatment. These findings suggest that ceramic rod reinforced TWIP steel composites are promising materials for applications requiring a combination of high strength and ductility.
Mass Spectrometry in Clinical Chemistry: Advancing Biomarker Discovery and Personalized Medicine
Authors: Son Ahrum , Kim Woojin , Park Jongham , Park Yongho , Lee Wonseok , Lee Sangwoon , Kim Hyunsoo
Published: August 2024

Mass spectrometry (MS) has revolutionized clinical chemistry, offering unparalleled capabilities for biomolecule analysis. This review explores the growing significance of MS, particularly when coupled with liquid chromatography (LC-MS), in identifying disease biomarkers and quantifying biomolecules for diagnostic and prognostic purposes. The unique advantages of MS in accurately identifying and quantifying diverse molecules have positioned it as a cornerstone in personalized medicine advancement. MS-based technologies have transformed precision medicine, enabling comprehensive understanding of disease mechanisms and patient-specific treatment responses. LC-MS has shown exceptional utility in analyzing complex biological matrices, while high-resolution MS has expanded analytical capabilities, allowing detection of low-abundance molecules and elucidation of complex biological pathways. The integration of MS with other techniques, such as ion mobility spectrometry, has opened new avenues for biomarker discovery and validation. As we progress towards precision medicine, MS-based technologies will be crucial in addressing the challenges of individualized patient care, driving innovations in disease diagnosis, prognosis, and treatment strategies.
The Indissociable Triad: Vascular Impairment, Muscle Atrophy, and Cognitive Decline
Authors: de Lima Enzo Pereira , Tanaka Masaru , Lamas Caroline Barbalho , Quesada Karina , Detregiachi Claudia Rucco P. , Araújo Adriano Cressoni , Guiguer Elen Landgraf , Catharin Virgínia Maria Cavallari Strozze , de Castro Marcela Vialogo Marques , Junior Edgar Baldi , Ferraz Bruna Fidencio Rahal , Catharin Vitor Cavallari Strozze , Laurindo Lucas Fornari , Barbalho Sandra Maria
Published: August 2024

The triad of vascular impairment, muscle atrophy, and cognitive decline represents critical age-related conditions that significantly impact health. Vascular impairment disrupts blood flow, precipitating muscle mass reduction seen in sarcopenia and the decline of neuronal functions characteristic of neurodegeneration. Our limited understanding of the intricate relationships within this triad hinders accurate diagnosis and effective treatment strategies. This review ana-lyzes the interrelated mechanisms that contribute to these conditions, with a specific focus on ox-idative stress, chronic inflammation, and impaired nutrient delivery. The aim is to understand the common pathways involved and to suggest comprehensive therapeutic approaches. Vascular dysfunctions hinder the circulation of blood and the transportation of nutrients, resulting in sar-copenia characterized by muscle atrophy and weakness. Vascular dysfunction and sarcopenia have a negative impact on physical function and quality of life. Neurodegenerative diseases exhibit comparable pathophysiological mechanisms that affect cognitive and motor functions. Preventive and therapeutic approaches encompass lifestyle adjustments, addressing oxidative stress, in-flammation, and integrated therapies that focus on improving vascular and muscular well-being. Better understanding of these links can refine therapeutic strategies and yield better patient out-comes. This study emphasizes the complex interplay between vascular dysfunction, muscle de-generation, and cognitive decline, highlighting the necessity for multidisciplinary treatment ap-proaches. Advances in this domain promise improved diagnostic accuracy, more effective thera-peutic options, and enhanced preventive measures, all contributing to a higher quality of life for the elderly population.
Generalised Modules for Membrane Antigens (GMMA) Do Not Elicit Concerning Local Reactogenicity after Intramuscular Injection in Absence of Aluminum Salt Adjuvant
Authors: Cecchi Raffaella , Maccari Silvia , Alfini Renzo , Di Benedetto Roberta , Gallorini Simona , Cartocci Elena , Marchi Sara , Romagnoli Giacomo , Bartolini Erika , Micoli Francesca , Piccioli Diego
Published: August 2024

Generalised Modules for Membrane Antigens (GMMA) are outer membrane vesicles derived from Gram-negative bacteria that can be used to design affordable subunit vaccines. GMMA are highly immunogenic and capable to induce an optimal antigen-specific humoral immune response both in animals and humans. Despite their potent immunogenicity, GMMA are usually formulated with aluminum salts (Alum) to reduce their potential systemic reactogenicity. GMMA, in fact, contain agonists of Toll-Like Receptor 4 (TLR4) and TLR2 that possess pro-inflammatory activity. The adsorption of GMMA onto Alum is believed to reduce their systemic exposure. However, it has been found that GMMA formulated without Alum did not induce concerning signs of systemic reactogenicity in the rabbit model. Here we asked whether GMMA promote local reactogenicity. We immunized mice intramuscularly with GMMA alone or formulated with Alum and we analyzed the injection site during 7 days after treatment. We found that GMMA alone promoted only mild inflammation within the muscle, whereas Alum induced severe muscle inflammation, as expected. Thus, in the mouse model, GMMA demonstrated to possess mild reactogenic potential locally, while Alum is confirmed a major driver of local reactogenicity. Our results further support the idea to investigate the reactogenicity of GMMA formulated without Alum in clinical studies.
Validation of OLCI Sentinel-3 water products in the Baltic Sea and evaluating the effect of System Vicarious Calibration (SVC)
Authors: O’Kane Sean , McCarthy Tim , Fealy Rowan , Kratzer Susanne
Published: August 2024

The monitoring of coastal waters using satellite data, from sensors including Sentinel-3 OLCI, has become a vital tool in the management of these water environments; especially when it comes to improving our understanding of the effects of climate change on these regions. In this study, Level-2 water products derived from different OLCI Sentinel-3 processors were validated against a comprehensive in situ dataset from the NW Baltic Sea proper region. The products validated were those of the regionally adapted Case-2 Regional Coast Colour (C2RCC) OLCI processor (v1.0 and v2.1), as well as the latest standard Level-2 OLCI case 2 (Neural Network) products from Sentinel-3’s processing baseline: Baseline Collection 003 (BC003), including “CHL_NN”, “TSM_NN”, and “ADG443_NN”. Furthermore, the effect of the current EUMETSAT system vicarious calibration (SVC) on the Level-2 water products was also validated. Results showed that the system vicarious calibration (SVC) reduces the reliability of the Level-2 OLCI products. For example, the application of these SVC gains to the OLCI data for the regionally adapted v2.1 C2RCC products resulted in RMSD increases of 36% for “conc_tsm”; 118% for “conc_chl”; 33% for “iop_agelb”; 50% for “iop_adg”; and 10% for “kd_z90max” using a ±3h validation window. The findings indicate that the current EUMETSAT SVC gains should be applied and interpreted with caution in the region of study at present. A key outcome of the paper recommends the development of a regionally specific SVC against AERONET-OC data for the region.
Impact of the COVID-19 Pandemic on Inpatient Antibiotic and Antifungal Drug Prescribing Volumes in Germany
Authors: Kern Winfried V. , Steib-Bauert Michaela , Baumann Jürgen , Kramme Evelyn , Först Gesche , de With Katja
Published: August 2024

Background: Previous studies have found variable impact of the coronavirus disease 2019 (COVID-19) pandem-ic on the consumption of antimicrobial drugs in human medicine, with trends in several European countries differing between community and inpatient prescribing.
Aim: This study analysed changes in the volumes and use density of antibacterial and antifungal drugs dis-pensed in acute care hospitals in Germany between 2019 and 2022.
Methods: Surveillance data for the four years available from 279 hospitals, among them 272 for antifungals, were expressed as the total volumes of daily doses or as use density (daily doses per 100 patient/occupied bed days) per year and analysed descriptively, using recommended hospital-adapted daily dose definitions (RDD) and (as sensitivity analysis) WHO/ATC-defined daily dose definitions (DDD). Hospitals were stratified according to size (number of beds) and university affiliation, and location (East, West, South).
Results: There were significant decreases both in the total number of patient days and antibacterial drug vol-umes in 2020 through 2022 compared with 2019. The relative changes between 2019 and 2020, 2021 and 2022 were -12.8%, -13.5%, and -13.3% for patient days, and -9.7%, -11.0%, and -10.1% for antibacterial RDD, respec-tively. Broad-spectrum betalactams, notably piperacillin-tazobactam and carbapenems, increased in volume unlike most other drug classes. The resulting antibacterial drug use density was slightly but significantly increas-ing with pooled means (and medians) of 43.3 (40.0) RDD/100 in 2019 compared to 44.8 (41.7), 44.5 (40.80), and 44.9 (41.7) RDD/100 in the years 2020 through 2022, respectively. Antifungal drug volumes and use density increased after 2019 and peaked 2021 (differences between 2019 and 2021 for total volumes +6.4%, and for pooled mean use density values +22.9%, respectively). These trends were similar in the different hospital strata and comparable when DDD instead of RDD were used.
Conclusions: Similar to what has been observed in a majority of European countries the total volume of antibac-terial drug use in German acute care hospitals decreased with the pandemic without a rebound phenomenon in 2022. In association with restricted hospital capacities and presumably more immunocompromised general medi-cine patients, however, inpatient prescribing of (primarily broad-spectrum) antibacterials and of antifungal drugs increased.
The Paradox of the ‘Care’ of London’s Children: Discourses of ‘Safety’ and ‘Respect’ in England’s Ministry of Justice Inspection Reports
Authors: Holligan Chris , McLean Robert
Published: August 2024

Using English prison inspectorate reports the article reports a Goffmanesque-informed discourse analysis of official accounts about the younger inmates of London’s Feltham prison and the conditions characterizing their lived experiences in this prison environment. The construction of this prison estate captures dilapidation, unhygienic conditions, and endless social danger. The stigmatizing construction of the child prisoner intimates a pervasive culture of violence and bullying resulting in their aversion to purposive activities. While, at first blush, prison inspec-torate reporting is based on the policy of ensuring a safe and rehabilitative prison experience for youth it is argued that the nature of the reporting of incarceration obviates a critique of the wider political fabric that custodial interventions reproduce. The Inspectorate operates within the state’s dominant class stratified political ideology. The adoption of a generic labelling discourse in the reports minimizes the communication of harms inflicted on children by criminal ‘justice’ that can only worsen their wellbeing and reproduce the harmful intensity of their imported marginality.
Short Cycle Therapy with Bictegravir/Emtricitabine/Tenofovir Alafenamide in a Small Cohort of Virally Suppressed People Living with HIV: A Long-Term Follow-Up
Authors: Lanzafame Massimiliano , Lattuada Emanuela , Delama Andrea , Mori Giovanni , Vento Sandro
Published: August 2024

Short-cycle therapy has proven to be a safe and effective alternative to standard everyday antiretroviral treatment for virally suppressed people living with HIV. Here we report a favorable long-term virological and immunological outcome in 12 virally suppressed people on short cycle therapy with bictegravir/emtricitabine/tenofovir alafenamide administered five days a week (Monday to Friday).
Smart Agriculture: IoT and Deep Learning for Precision Crop Management
Authors: Najeeb Hooriya , Naseer Asma , Tamoor Maria
Published: August 2024

Pakistan is an agricultural country, and an exporter of crops in many countries. The crop production is an important factor to earn revenue for the country. But the agriculture of Pakistan is still not revolutionized and no modern system has been deployed commonly. Whereas the farmers face difficulty in growing some crops because those crops needs more care and calculated steps. Moreover the farmers face difficulty at different stages of the crop growth like to check fertility of soil and if the soil is non-fertile then which chemical property is lacking. The objective of this research is to provide digitize the agriculture of Pakistan. An emerging technology IoT and Deep learning based system will be developed. The IoT part contains some devices like sensors,gateways and communication technologies whereas the software part consists of Deep learning models that can make predictions about the fertility of the soil. The motive of this system is to provide best results in term of accuracy. Whereas the dataset used is publicly available on kaggle but it was of non-fertile values, so data augmentation is also performed to generate data for fertile values. We have implemented LSTM,RNN,CNN among them LSTM performed best for the prediction of soil fertility.
Recurrent Neural Networks: A Comprehensive Review of Architectures, Variants, and Applications
Authors: Mienye Ibomoiye Domor , Swart Theo G. , Obaido George
Published: August 2024

Recurrent Neural Networks (RNNs) have significantly advanced the field of machine learning by enabling the effective processing of sequential data. This paper provides a comprehensive review of RNNs and their applications, highlighting advancements in architectures such as Long Short-Term Memory (LSTM) networks, Gated Recurrent Units (GRUs), Bidirectional LSTM (BiLSTM), and stacked LSTM. The study examines the application of RNNs in different domains, including natural language processing (NLP), speech recognition, financial time series forecasting, bioinformatics, autonomous vehicles, and anomaly detection. Additionally, the study discusses recent innovations, such as the integration of attention mechanisms and the development of hybrid models that combine RNNs with convolutional neural networks (CNNs) and transformer architectures. This review aims to provide machine learning researchers and practitioners with a comprehensive overview of the current state and future directions of RNN research.
Highly Sensitive and Flexible Capacitive Pressure Sensors Combined with Porous Structure and Holes Array by Sacrificial Templates and Laser Ablation
Authors: Zhao Yibin , Zhou Jingyu , Jiang Chenkai , Xu Tianlong , Li Kaixin , Zhang Dawei , Sheng Bin
Published: August 2024

Flexible wearable pressure sensors offer numerous benefits, including superior sensing capabilities, a lightweight and compact design, and exceptional conformal properties, making them highly sought after in various applications including medical monitoring, human-computer interaction, and electronic skin. Because of their excellent characteristics, such as simple fabrication, low power consumption, and short response time, capacitive pressure sensors have received widespread attention. As a flexible polymer material, polydimethylsiloxane (PDMS) is widely used in the preparation of dielectric layers for capacitive pressure sensors. The Young's modulus of the flexible polymer can be effectively decreased through the synergistic application of sacrificial template and laser ablation techniques, thereby improving the functionality of capacitive pressure sensors. In this study, a novel sensor was developed through a series of processes including sacrificial template method using NaCl microparticles, CO₂ laser ablation, and sandwiching a porous PDMS dielectric layer between two flexible electrodes to create a capacitive pressure sensor. The sensor demonstrates a sensitivity of 0.694 kPa-1 within the pressure range of 0-1 kPa, and can effectively detect pressures ranging from 3 Pa to 200 kPa. The sensor demonstrates stability for up to 500 cycles, with a rapid response time of 96ms and a recovery time of 118ms, coupled with a low hysteresis of 6.8%. Furthermore, our testing indicates that the sensor possesses limitless potential for use in detecting human physiological activities and signaling emergencies.
Sustainable Extraction and Recovery of Copper from PCBs Using Aqua Regia and Its Constituents
Authors: Irtiza Tanjim , Nishu Susmita Das , Das Sajib , Safin Ahamed Mohtasin , Sakib Abdullah
Published: August 2024

The growing use of electronic devices in modern society has sparked concerns about managing e-waste on a global level. Coupled with ever-increasing copper demand, it poses both challenges and potential opportunities for sustainable resource management. The study reinspects the established process of recycling copper with aqua regia from waste PCB & also optimizes the extraction procedure of different aqua regia samples. This research also analyzes the impacts of temperature leaching duration and stirring speed. The results reveal that using a stirring speed of 500 rpm and a leaching time of one hour, the results show that a 1:3 ratio of HNO₃ to HCl in aqua regia produces the best copper extraction efficiency, reaching 72.2% at 180°C. Reduced extraction efficiencies were observed when compared with separate HCl and HNO₃ applications, essentially highlighting the joint effects of utilizing both acids encompassed in the aqua regia solution. Variations suggested by discrepancies found in the temperature range of 140°C to 150°C and overlapping error margins in data on extraction time call for further research. The study also raises concerns about the potential environmental impacts of traditional copper mining and refining processes & attempts to mitigate these effects by recycling copper more efficiently using optimum aqua regia solution. Aqua regia can be the economic & sustainable solution in countries where copper and other valuable metal recovery is rare due to the expensive and complex nature of existing technologies. Developing safer and more sustainable extraction technologies, optimizing process conditions, & researching the selective recovery of other important metals from WPCB should be emphasized in future studies. Addressing these problems will be critical for developing the practical applicability of copper extraction from electronic waste
Zika Virus in Extracellular Vesicles: Insights from Integrated Proteomic and Metabolomic Dependent Regulation of B Cell and PI3K/AKT/mTOR Signaling Pathway
Authors: Gomes-de-Pontes Leticia , Barreiros Lucila Akune , Gomes Lillian Nunes , Salgado Ranieri Coelho , Napoleão Sarah Maria da Silva , Soeiro-Pereira Paulo V , Passos Saulo Duarte , Condino-Neto Antonio
Published: August 2024

Background; Cell-released extracellular vesicles (EVs) acting as 'metabolically and proteolytically active machines,' show potential in metabolomic and proteomic analysis of serum EVs. Despite diverse challenges, post-isolation omics characterization EVs offers crucial insights for effective analysis; (2) Methods: The research, involved children with Congenital Zika Syndrome, utilizing mass spectrometry for proteomics and GC-MS for metabolite identification. Vesicles were isolated using Izon qEV columns, quantified, and characterized by NTA and TEM. Data analysis employed Cytoescape/String and MetaboAnalyst, revealing variations in metabolic and proteomic profiles among groups through PCA and volcano plots. Proteins and Metabolite set enrichment analysis provided biologically meaningful patterns to enriched metabolites; (3) Results: Using molecular exclusion chromatography, the EVs were characterized, revealing size variations. Protein analysis identified 13 significantly altered proteins, including upregulated (e.g., AOM8Q6 - IGLC7) and downregulated (e.g., Q8TD86 - CALML6) ones. Metabolite analysis indicated involvement in the PI3K-AKT-mTOR pathway and suggested a role in Angiotensin inhibition in CZS+. Upstream of mTOR, Akt is the central signaling molecule in the PI3K pathway and plays critical roles in brain development as well as synaptic plasticity important for Zika Virus. The study provides insights into molecular mechanisms associated with CZS; (4) Conclusions: The study pinpointed valuable possible biomarkers, specifically proteins and metabolites, in Zika virus (ZIKV) infection. It stresses the necessity for broader investigations with advanced techniques to uncover molecular targets, potentially advancing pharmacological strategies.
Aircraft Electrification: Insights from a Cross-Sectional Thematic and Bibliometric Analysis
Authors: Bridgelall Raj
Published: August 2024

Electrifying aircraft, a crucial advancement in the aviation industry, aims to cut pollutive emissions and boost energy efficiency. Traditional aircraft depend on fossil fuels, which contribute significantly to greenhouse gas emissions and environmental pollution. Despite progress in electric propulsion and energy storage technologies, challenges such as low energy density and integration issues persist. This paper provides a comprehensive thematic and bibliometric analysis to map the research landscape in aircraft electrification, identifying key research themes, influential contributors, and emerging trends. The study applies natural language processing to unstructured bibliographic data and cross-sectional statistical methods to analyze publications, citations, and keyword distributions across various categories related to aircraft electrification. The findings reveal significant growth in research output, particularly in energy management and multidisciplinary design analysis. Collaborative networks highlight key international partnerships, with the United States and China being key research hubs, while citation metrics highlight the impact of leading researchers and institutions in these countries. This study provides valuable insights for researchers, policymakers, and industry stakeholders, guiding future research directions and collaborations.
Exogenous Melatonin Improves Oocyte Competence and Blastocyst Development in Indigenous Donor Cattle During Summer
Authors: Solanki Anupama , Jangra Hitesh , Saini Pradeep , Kumar Sandeep , Kaushik Ramakant , Virmani Meenakshi , Joshi Vinay Ganeshrao , Kumar Rajesh , Verma Rahul , Grakh Kushal , Kognole Satish , Bangar Yogesh , Pandey Anand Kumar
Published: August 2024

The elevated environment temperature in summer plays adverse effects on bovine fertility. Antioxidant treatment may have positive impact to enhance oocyte competence could be possible strategy for alleviating the summer effects on bovine fertility. The present study was aimed to investigate the effects of exogenous melatonin treatment on oocyte development competence, blastocyst development rate, activity of antioxidant enzymes, expression profiles of development related genes and pregnancy rates in cattle during summer. The experiment was conducted in 44 non-lactating indigenous Sahiwal cattle divided into control and treatment group. Treatment group received (day 0) inj. Melatonin @ 18mg/50kg body weight while control group received inj. Corn oil, 4ml i.m. On day 4, all the cows were subjected to ovum pickup (OPU) to aspirate oocytes for in-vitro embryo production. Blood samples were used to determine lipid peroxidation (MDA) and antioxidant enzymes concentration (SOD, GSH), and also for plasma hormonal concentration analysis. The results revealed that blastocyst development rate (%) was higher in treatment group (p<0.05). Treatment group had increased (p<0.05) antioxidant enzymes (SOD and GSH), plasma melatonin and estradiol concentrations, and decreased (p<0.05) MDA concentrations than controls. The mRNA expression level of SOD2, HSPB1, BCL2, MT2 and STAR in oocytes, cumulus cells, COCs (immature and mature) and blastocyst were found to be higher, however, BAX was downregulated in melatonin-treated than control group. In conclusion, the results suggesting probable beneficial role of exogenous melatonin administration in reducing heat stress and enhancing blastocyst developmental competence in indigenous cattle.
NIR-HSI/2B-CNN Algorithmic Scheme for Early Detection of Anthracnose on Mango Fruits
Authors: Phanomsophon Thitima , Sirisomboon Panmanas , Jongyingcharoen Jiraporn Sripinyowanich , Junto Apiwat , Pokhrel Dharma Raj , Sharma Sneha , Posom Jetsada , Sirisomboon Cheewanun Dachoupakan , Rerngsamran Panan , Pornchaloempong Pimpen , Hashim Norhashila , Terdwongworakul Anupun , Chongstitvatana Prabhas
Published: August 2024

This research proposes a near-infrared hyperspectral imaging/two-branch convolutional neural network (NIR-HSI/2B-CNN) algorithmic scheme to detect mango anthracnose of the species Colletotrichum asianum at the early stages of disease development. In the algorithmic model development, root mean square propagation was used as the solver to train the neural network, given 150 epochs. In addition, spectral raw data was preprocessed to transform it into an understandable and efficient format. The optimal classification model was the 2B-CNN model with 1st-derivative preprocessing, achieving an accuracy of 0.94 for the calibration set and 0.71 for the prediction set. The proposed NIR-HSI/2B-CNN scheme could detect anthracnose mangoes since the the first day of inoculation of the spore suspension (i.e., day 0) through to day 3, achieving a moderate classification accuracy. Meanwhile, the accuracy of conventional convolutional neural networks (CNN) were within a range of 0.66-0.67 for the calibration set and 0.55-0.57 for the prediction set. The results indicated that incorporating spatial features in the 2B-CNN modeling enhanced the prediction performance of the algorithm. The proposed NIR-HSI/2B-CNN algorithmic scheme needs refinements to be able to reliably sort mango fruits into those suitable for premium fresh consumption and export without anthracnose and those for domestic consumption or processing. The novelty of this research lies in the use of NIR-HSI and 2B-CNN algorithm to detect plant pathogens at the early stages of disease development. In addition, the new method of natural simulation to deposit the fungal spores onto the mango surface by spraying spore suspension onto the mango surface where the conidia penetrated unaided into the underneath of the mango peel is proposed.
Application of 2D Modification of Hjorth Descriptors to Distinguish Defined Classes of Bee Pollen Images
Authors: Tkacz Ewaryst , Rujna Przemysław , Więcławek Wojciech , Lewandowski Bartosz , Mika Barbara , Sieciński Szymon
Published: August 2024

Adulteration of food products, including honey, is a serious problem in today’s economy. Honey has become the third most counterfeited food product in the world, which requires effective authentication methods. This article presents considerations regarding the development of meteorology to test the quality of honey based on the analysis of bee pollen. The justification for conducting such analyses is the relatively high need for the authentication of honey and its derivatives. It turns out that the honey market and honey itself are the third products in the world in which undesirable, inappropriate, and quality-reducing components may appear, affecting the final quality of a product such as honey. The analyses mentioned above thus come down to issues related to the analysis and processing of images. A certain novelty of the approach to this analysis is an attempt to parameterize them using the so-called Hjorth descriptors, which have been a tool known for almost 50 years from the analysis of electroencephalographic (EEG) signals. In this paper, after an introduction to the issues related to testing honey, the issues related to the method of obtaining bee pollen images, improving their quality by applying appropriate filtration, performing normalization, and finally calculating Hjorth distributors such as: Activity, Mobility, and Complexity will be discussed. In the next stage described in this article, the authors perform a detailed statistical analysis leading to the initial construction of a simple classifier that distinguishes defined gropus of bee pollen images.
Isometric Force-Time Curve Assessment: Accuracy, Precision and Repeatability of a Mobile Application and Portable and Lightweight Device—The DINABANG®
Authors: Santos Dario , Bravo-Sánchez Alfredo , Peyré-Tartaruga Leonardo Alexandre , Simini Franco , Zacca Rodrigo
Published: August 2024

Background: Strength assessment is one of the main fields in sports performance, physical rehabilitation, physical activity and health. Purpose: To compare maximal voluntary isometric contractions (MVIC) and paired voluntary isometric contractions (VIC) of knee extensors between an isokinetic dynamometer (BIODEX) and a portable and lightweight device (DINABANG). Methods: From 19 volunteers (age: 28.7±7 y; body mass: 72±10 kg and height: 173±7 cm) we obtained 114 paired MVIC measures and, from the force-time curves of these repetitions, 22507 paired VIC measures of knee extensors. Results: We observed “excellent” repeatability for MVIC (ICC:1.00; p<0.001) between BIODEX (247±79.5 Nm) and DINABANG (247±74.8 Nm), with “trivial” effect (mean difference: 0.12 Nm (0.02%); 95%CI: -0.13 to 0.23 Nm; p=0.606; d=0.048). Bland-Altman plots revealed high accuracy for MVIC (bias: 0.12 Nm) and consistent distribution (precision) inside the limits of agreement (-4.81 to 5.06 Nm) and respective 95%CI. “Excellent” repeatability was also observed for VIC (ICC:1.00; p<0.001) between BIODEX (219±84.1 Nm) and DINABANG (218±84.0 Nm), with “trivial” effect (0.24 Nm (0.11%); 0.08 to 0.11 Nm; p<0.001; d=0.100). Bland-Altman plots revealed high accuracy for VIC (bias: 0.24 Nm) and consistent distribution (precision) inside the limits of agreement (-4.5 to 4.9 Nm) and respective 95%CI. Conclusion: DINABANG is accurate, precise and reliable for torque measurement.
Identifying Key Parameters in Building Energy Models: Sensitivity Analysis Applied to Residential Typologies
Authors: Gervaz Sofía , Favre Federico
Published: August 2024

Building energy modelling tools play a crucial role in quantifying and comprehending the energy performance of buildings. These tools demand substantial amounts of data, which can be challenging to acquire and are often associated with significant uncertainties. The incorporation of Sensitivity Analysis represents a relevant step towards developing reliable models, as it identifies the most critical parameters that require a meticulous characterization. In this study, a Sensitivity Analysis based on Morris method was conducted to assess the relevance of 14 input parameters affecting thermal loads across four dwelling typologies modelled in EnergyPlus. Different number of Morris trajectories and levels were considered to analyse the impact of the user-defined values of r and p when employing Morris method. Convergence was achieved from r=200 and p=12, which are higher than the typically employed values (r=10 and p=4). Setpoint temperatures, orientation, roof solar absorptivity and roof conductance rank among the most relevant parameters affecting thermal loads, however variations are observed for the four case studies.
Recent Advances in Ammonia Synthesis Modeling and Experiments on Metal Nitrides and Other Catalytic Surfaces
Authors: Elahi Numair , Zeinalipour-Yazdi Constantinos D.
Published: August 2024

In this review we explore the recent progress in catalytic materials for ammonia synthesis that are based on metal nitrides and other catalytic surfaces. It comprises a detailed overlook of various techniques used in ammonia synthesis research and the state-of-the-art modeling techniques employed to investigate new reaction mechanisms and more efficient processes for sustainable ammonia synthesis production. The review is discussed in the context of reaction mechanisms developed and recent progress that has been made with respect to thermal, electrochemical and photocatalytic ammonia synthesis.
Kinetic Studies on the Interaction of HIV-1 Gag Protein with the HIV-1 RNA Packaging Signal
Authors: Rink Constance , Kroupa Tomas , Datta Siddhartha A.K. , Rein Alan
Published: August 2024

During HIV-1 virus assembly the genomic RNA (vRNA) is selected for packaging by the viral protein Gag because it contains a specific packaging signal, Psi. While there have been numerous studies of Gag-Psi interactions, there is almost no information on kinetic aspects of this interaction. We have investigated the kinetics of Gag binding to different RNAs using switchSENSE DRX2 technology. We measured the association rate of Gag binding to monomeric Psi, to a “Multiple Binding Site Mutant” Psi that is inactive for genome packaging in vivo, and to a scrambled Psi. We discovered that Gag binds more rapidly to Psi RNA than to the mutant or scrambled RNAs. Furthermore, rapid Gag association kinetics are retained within sub-regions of Psi: Gag associates more rapidly with RNA containing only the 3’ two of the three Psi stem-loops than with monomeric RNA containing the 5’ two stem-loops or a scrambled RNA. No differences were detectable with individual Psi stem-loops. Interestingly, the rate of binding of Gag molecules to Psi increases with increasing Gag concentration, suggesting cooperativity in binding. The results are consistent with the hypothesis that selectivity in packaging derives from kinetic differences in initiation of particle assembly.
Appropriateness of Ketoanalogues of Aminoacids, Calcium Citrate, and Inulin Supplementation for CKD Management: A RAND/UCLA Consensus
Authors: Saavedra-Fuentes Nadia , Carmona-Montesinos Enrique , Castañeda-Hernández Gilberto , Campos Israel , Castillo-Salinas Juan Carlos , Castillo-Tapia Javier Alberto , Del Castillo-Loreto Karla Guadalupe , Falcón-Martínez Juan Carlos , Fuentes-García Raquel , Guerrero Miguel Ángel García de León , García-García Victor , Gómez-García Erika F. , González-Toledo Rafael , Jaime Angélica , Rely Kely , Lerma Claudia , Morales-Buenrostro Luis E. , Quilantan-Rodriguez Mateo , Rodriguez-Matías Adrián , Rojas-Rodriguez F. Octavio , Valdez-Ortiz Rafael , Wasung Michael , Ceron-Trujullo Berenice , Ramirez-Ramirez Edgar
Published: August 2024

Background: Current treatment for Chronic Kidney Disease (CKD) focuses on improving manifestations and delaying progression. Nutritional approaches play a crucial role in CKD management, and various supplements have become available. Ketoanalogues of amino acids (KA), calcum citrate, and inulin have been proposed as suitable supplements, yet their widespread use has been limited due to insufficient evidence. This study aimed to generate general guidance statements on the appropriateness of these supplements through a RAND/UCLA consensus process; Methods: A RAND/UCLA consensus panel was convened to evaluate the appropriateness of these supplements in different clinical scenarios. In this study, we present a subgroup analysis focusing on a panel of eleven clinical nephrologists from among the experts; Results: Supplementation of low protein diets (LPD) and very low protein diets (VLPD) with KA was considered appropriate to reduce manifestations and delay CKD outcomes, supplementation with calcium citrate is considered appropriate to reduce CKD manifestations, and supplementation with inulin is considered appropriate to delay CKD outcomes and manage comorbidities; Conclusions: Based on a combination of clinical experience and scientific evidence , the panel reached a consensus that KA supplementation of LPD and VLPD, calcium citrate, and inulin are appropriate in patients with CKD across various scenarios.
First Responders on Ships: Technological and Legislative Developments
Authors: Santamaría-Barrios Manuel Antonio , Rey-Charlo Raquel Esther
Published: August 2024

The use of fuel material and different sources of ignition causes unwanted fires, producing and spreading in different spaces. Fire fighting. systems are measures taken to minimize the effects of fire. This struggle is not only on land, but also in the maritime world, through maritime security that has become a very important element for the International Maritime Organization (IMO). Therefore, maritime accidents caused by fire are one of the challenges to be taken into account, because they require immediate control and response. This article presents a historical interpretation of the concept of maritime safety through first responders on ships. It will be demonstrate how the technological advances of such equipment have been very important for their arrival on ships. In addition, the article reveals the legislative changes of International Convention for the Safety of Life at Sea (SOLAS), which reflects the IMO requirements to prevent fire risks on board, requiring a reading of the primary documents. Finally, the importance of the evolution of first intervention equipment for safety on board has been shown.
Spectral Reflectance Estimation from Camera Response Using Local Optimal Dataset and Neural Networks
Authors: Tominaga Shoji , Sakai Hideaki
Published: August 2024

In this study, a novel method is proposed to estimate surface-spectral reflectance from camera responses that combines model-based and training-based approaches. An imaging system is modeled using the spectral sensitivity functions of an RGB camera, spectral power distributions of multiple light sources, unknown surface-spectral reflectance, additive noise, and a gain parameter. The estimation procedure comprises two main stages: (1) selecting the local optimal reflectance dataset from a reflectance database and (2) determining the best estimate by applying a neural network to the local optimal dataset only. In stage (1), the camera responses are predicted for the respective reflectances in the database, and the optimal candidates are selected in the order of lowest prediction error. In stage (2), most reflectance training data are obtained by a convex linear combination of local optimal data using weighting coefficients based on random numbers. A feed-forward neural network with one hidden layer is used to map the observation space onto the spectral reflectance space. In addition, the reflectance estimation is repeated by generating multiple sets of random numbers, and the median of a set of estimated reflectances is determined as the final estimate of the reflectance. Experimental results show that the estimation accuracies exceed those of other methods.
The Confluence Analysis Program: A User-Friendly Tool for Automated Cell Confluence Measurement and Visualization
Authors: Lobsenz Abraham , Seidler Paul
Published: August 2024

Measuring cell confluence in high-throughput screening of pharmaceutics, cell culture monitoring, cancer research, and industrial applications requires quantitative and standardizable measures to minimize subjective observations and increase throughput1-12 . Over the past half-century, non-invasive specialized programs have been created to quantitatively assess cell confluence, and some software tools exist to meet these needs1,4,5,6,7,8,9 . However, many of these tools are expensive, computationally-demanding, or inaccessible to non-experts1,6. With the assistance of generative artificial intelligence, we have developed the Confluence Analysis Program (CAP), a modern tool designed to be precise, interactive, and user-friendly. CAP is written entirely in Python and runs in any command-line interface (CLI), including Terminal (OS) and Command Prompt (Windows). In addition to fetching all necessary external libraries automatically and prompting drag-and-drop image retrieval, CAP features live visual comparison of cell mass identification to the original image assay. Our results demonstrate robust performance of CAP on fluorescent micrographs of varying confluences ranging from low to high. CAP is provided as a free resource, accessible in the Supplementary Materials.
Physical Vulnerability and Landslide Risk Assessment in Tegucigalpa City, Honduras
Authors: Suárez Ginés , Domínguez-Cuesta María José
Published: August 2024

Tegucigalpa, the capital city of Honduras, has the highest number of landslides recorded in the country. In a previous study, landslides were found to be mainly concentrated in areas with colluvium and residual soils. The present study focused on assessing the physical vulnerability of houses and the risk linked to landslides in these types of soils. As an input for this assessment, the study generated landslide risk vulnerability functions based on empirical data. The study's findings suggest that the estimated Annual Average Losses associated with landslides in this region is USD 7.26 million. Moreover, the study developed a novel approach for the spatial and temporal estimation of landslide hazard probability, which overcomes some of the limitations identified in previous landslide risk assessment studies.
Development and Validation of a Liquid Chromatographic Method for CasiopeinaIII-ia ® in Rabbit Blood and Its Application to a Preclinical Pharmacokinetic Study
Authors: Gama Nancy Vara , Carrasco Kenneth Rubio , Jarquin Julia Antonio , Morales † Hector Ariel Rico , Azuara Lena Ruiz , Noriega Inés Fuentes
Published: August 2024

A rapid and simple high-performance liquid chromatography (HPLC) method using extraction with zinc sulfate has been developed for the determination of Casiopeina III-ia (Cas III-ia) and validated over the linear range 10-120 g/mL in 200 L of rabbit blood. Previously we have reported a HPLC method to quantify CasIII-ia in plasma, but in distribution studies in total blood [20], the Cas III-ia concentrations were higher in total blood that in plasma [19]. The analysis was performed on a Symmetry C (18) (5 microm) column. The mobile phase was Methanol-sodium phosphate buffer (pH 6.5; 0.01 M) (40:60 v/v) was kept at a flow-rate of 0.8 ml/min. The analyses were performed at room temperature. The column effluent was monitored at 262 nm. Acetaminophen was used as internal standard. The results showed that the assay is sensitive at 10 g/mL. Maximum intra-day coefficient of variation was 5.10%. The average recovery obtained in blood was 94.51%. The applicability of this method for distribution in vitro and pharmacokinetic studies in rabbits was demonstrated. Conclusions: the present assay is rapid, simple, precise, and accurate. The pharmacokinetic study was carried out in rabbits and the following pharmacokinetic parameters were obtained: (kel) = 0.0150 min-1, half-life time (T1/2) = 53.92 min, apparent volume of distribution (Vd) = 202.81 mL, clearance (Cl) = 2.08 mL /mi and area under the curve (AUC)=23163.85 µg/mL.min. Contributing to the preclinical characterization of the Cas III-ia.
Selectivities of Carbon Dioxide Over Ethane in Three Methylimidazolium- Based Ionic Liquids: Experimental Data and Modeling
Authors: Henni Nadir , Henni Amr , Ibrahim Hussameldin
Published: August 2024

This work focused on the solubility of ethane in three promising ionic liquids {1-Hexyl-3-methylimidazolium bis(trifluormethylsulfonyl) imide [HMIM][Tf2N], 1-Butyl-3-methyl-imidazolium dimethyl-phosphate [BMIM][DMP] and 1-Propyl-3- methylimidazolium bis(trifluoromethyl-sulfonyl)-imide [PMIM][Tf2N]}. The solubilities were measured at 303.15 K to 343.15 K and pressures up to 1.4 MPa using a gravimetric microbalance. The overall ranking of ethane solubility in the ionic liquids from highest to lowest is the following: [HMIM][Tf2N] > [PMIM][Tf2N] > [BMIM][DMP]. The Peng- Robinson equation of state was used to model the experimental data using three different mixing rules: van der Waals one, van der Waals two and Wong-Sandler mixing rules combined with the Non-Random Two-Liquid model. The average absolute deviations for the three mixing rules for the ionic liquids at the three temperatures were (4.39, 2.45 and 2.45) %, respectively. Henry’s Law constants for ethane in [BMIM] [DMP] were the highest (lowest solubility) amongst other ionic liquids studied in this work. The selectivity of CO2 over C2H6 was estimated at the three temperatures and the overall ranking of the selectivity was in the following order: [PMIM][Tf2N] > [BMIM][DMP] > [HMIM][Tf2N]> Selexol. Selexol, a widely used physical solvent in gas sweetening has better selectivity than the three ionic liquids studied. [PMIM][Tf2N], a promising solvent, has the highest selectivity among the three ILs studied, and would therefore be the best choice if in addition to carbon dioxide capture, ethane co-absorption was to be avoided. The enthalpy and entropy of solvation at infinite dilution were also estimated.
Securing the Internet of Things (IoT) in the Quantum Era: Challenges and Future Directions for Quantum-Resistant Cryptography
Authors: Alwashahi Maryam , Jassim Hothefa , Abdelfattah fadi
Published: August 2024

Internet of thing (IoT) has been used in different aspect of life as industry, and daily life. Aligned with IoT, Quantum computers have been generated with high features that can accomplish complicated tasks with high speed. IoT and Quantum computers don’t match in resources and due to this collaboration between the two terms, it was found there are many challenges with quantum computers brought some security concerns. This paper will examine all challenges and future direction that face the use of IoT through using different quantum cryptograph methods. The first part on the paper discussed the vulnerabilities of existing cryptographic methods like RSA and ECC. these two methods were used as basic level for IoT security protocols. These cryptographic algorithms could be easily attacked by quantum computers so to ensure that IoT devices are secure must develop quantum resistant cryptographic algorithms. Next this paper will examine the challenges in implementing quantum resistant cryptographic algorithm in any IoT device through quantum resistant cryptographic algorithms such as lattice-based cryptography, code-based cryptography, multivariate cryptography, and hash-based signatures. Then, the paper discussed the future direction of securing IoT in quantum computing. In conclusion, securing IoT devices in quantum presents many challenges that require to be addressed where quantum resistant algorithms can be a solution that mitigate threats.