bluuebunny/crossref_metadata_2025 huggingface dataset:
Perceived factors informing the pre-acceptability of digital health innovation by aging respiratory patients: a case study from the Republic of Ireland
Authors: Byrne Tara , Murray Niall , McDonnell-Naughton Mary , Rowan Neil J.
Published: October 2023

It is appreciated that digital health is increasing in interest as an important area for efficiently standardizing and developing health services in Ireland, and worldwide. However, digital health is still considered to be in its infancy and there is a need to understand important factors that will support the development and uniform uptake of these technologies, which embrace their utility and ensure data trustworthiness. This constituted the first study to identify themes believed to be relevant by respiratory care and digital health experts in the Republic of Ireland to help inform future decision-making among respiratory patients that may potentially facilitate engagement with and appropriate use of digital health innovation (DHI). The study explored and identified expert participant perceptions, beliefs, barriers, and cues to action that would inform content and future deployment of living labs in respiratory care for remote patient monitoring of people with respiratory diseases using DHI. The objective of this case study was to generate and evaluate appropriate data sets to inform the selection and future deployment of an ICT-enabling technology that will empower patients to manage their respiratory systems in real-time in a safe effective manner through remote consultation with health service providers. The co-creation of effective DHI for respiratory care will be informed by multi-actor stakeholder participation, such as through a Quintuple Helix Hub framework combining university-industry-government-healthcare-society engagements. Studies, such as this, will help bridge the interface between top-down digital health policies and bottom-up end-user engagements to ensure safe and effective use of health technology. In addition, it will address the need to reach a consensus on appropriate key performance indicators (KPIs) for effective uptake, implementation, standardization, and regulation of DHI.
Multi-Objective Order Scheduling via Reinforcement Learning
Authors: Chen Sirui , Tian Yuming , An Lingling
Published: October 2023

Order scheduling is of a great significance in the internet and communication industries. With the rapid development of the communication industry and the increasing variety of user demands, the number of work orders for communication operators has grown exponentially. Most of the research that tries to solve the order scheduling problem has focused on improving assignment rules based on real-time performance. However, these traditional methods face challenges such as poor real-time performance, high human resource consumption, and low efficiency. Therefore, it is crucial to solve multi-objective problems in order to obtain a robust order scheduling policy to meet the multiple requirements of order scheduling in real problems. The priority dispatching rule (PDR) is a heuristic method that is widely used in real-world scheduling systems In this paper, we propose an approach to automatically optimize the Priority Dispatching Rule (PDR) using a deep multiple-objective reinforcement learning agent and to optimize the weighted vector with a convex hull to obtain the most objective and efficient weights. The convex hull method is employed to calculate the maximal linearly scalarized value, enabling us to determine the optimal weight vector objectively and achieve a balanced optimization of each objective rather than relying on subjective weight settings based on personal experience. Experimental results on multiple datasets demonstrate that our proposed algorithm achieves competitive performance compared to existing state-of-the-art order scheduling algorithms.
Paper Thin? The Evidence for 12th-Century Gothic Design Drawings
Authors: Bork Robert
Published: October 2023

No Gothic design drawings on paper or parchment have survived from the 12th century, and only a few have survived from the 13th century. For this reason, most recent scholars tend to concur at least broadly with Robert Branner, who argued in an influential 1963 article that such drawings were first produced only after 1200. This conclusion deserves critical re-examination, however, for two principal reasons. First, the continuity of the Gothic architectural tradition in both time and space strongly suggests that early Gothic builders used similar techniques to those used by their late Gothic successors. From this perspective, the lack of surviving design drawings from before 1200 seems likely to reflect their disappearance over time, rather than their not being used in the crucial period when the conventions of Gothic design and construction were first coming into focus. A second argument for the use of drawings in the 12th century comes from consideration of early Gothic buildings, whose complex and carefully calibrated forms would be literally inconceivable without such graphic aids. Churches such as Saint-Denis Abbey and Notre-Dame in Paris, for example, already display a level of geometrical sophistication and coherence that argues strongly for the use of scaled drawings in their original conception.
Response Assessment in Brain Metastases Managed by Stereotactic Radiosurgery: A Reappraisal of the RANO-BM Criteria
Authors: Douri Keiss , Iorio-Morin Christian , Mercure-Cyr Rosalie , Figueiredo Gabrielle , Touchette Charles Jean , Masson-Côté Laurence , Mathieu David
Published: October 2023

Background: Brain metastases (BM) are increasingly being treated using stereotactic radiosurgery (SRS). Standardized response criteria are necessary to improve research and treatment protocols. This study’s goal was to validate the RANO-BM criteria thresholds for tumor progression in a cohort of patients with brain metastases managed using SRS. Methods: We performed a retrospective analysis of patients treated at least twice with SRS for brain metastases. Local progression, as defined by RANO-BM criteria, was compared to our multidisciplinary tumor board’s treatment recommendation. A ROC curve was generated using varying diameter thresholds to assess the sensitivity and specificity of current RANO-BM criteria. Results: 249 metastases in 67 patients were included in the analysis. RANO-BM criteria current progression thresholds yielded a sensitivity of 38%, a specificity of 95%, a positive predictive value of 71%, and a negative predictive value of 84% relative to our tumor board’s treatment recommendation. Modified RANO-BM criteria using absolute diameter differences of 2.5 mm yielded a sensitivity of 83%, a specificity of 87%, a positive predictive value of 67% and a negative predictive value of 94%. Conclusions: Current RANO-BM criteria unreliably identifies clinically relevant tumor progression. The use of absolute diameter differences thresholds appears superior in our BM cohort.
Breaking Down Barriers to Detection and Care in Early-Age-Onset Colorectal Cancer in Canada
Authors: Raphael Michael J. , Wildgoose Petra , Servidio-Italiano Filomena , De Vera Mary A. , Brenner Darren , D’Angelo Monika Slovinec , McGee Robin , Berry Scott , Wong Clarence , Gill Sharlene
Published: October 2023

The second Early-Age-Onset Colorectal Cancer Symposium, convened in October 2022, sought solutions to the barriers to early detection and care for colorectal cancer in Canada. This meeting built on a previous symposium, held in 2021 and reported in this journal. Early-age-onset colorectal cancer (EAOCRC) affects increasing numbers of people under the age of 50 in Canada and throughout the developed world. Two main themes emerged from the meeting: the importance of timely detection, and the need for a tailored approach to the care of EAOCRC. Early detection is crucial, especially in light of the later stage at diagnosis and unique tumour characteristics. Symposium participants were strongly in favour of reducing the age of eligibility for screening from 50 to 45, and promoting the development of non-invasive screening techniques such as testing for circulating tumour DNA and biomarkers. Leading approaches to care were described and discussed, which meet the unique treatment needs of younger CRC patients. Multidisciplinary practices within and outside Canada address such factors as fertility, family roles, education, careers and financial responsibilities. These models can be applied in treatment centres across the country.
The Gut Microbiome from a Biomarker to a Novel Therapeutic Strategy for Immunotherapy Response in Patients with Lung Cancer
Authors: Duttagupta Sreya , Hakozaki Taiki , Routy Bertrand , Messaoudene Meriem
Published: October 2023

The gastrointestinal microbiome has been shown to play a key role in determining the responses to cancer immunotherapy, including immune checkpoint inhibitor (ICI) therapy and CAR-T. In patients with non-small cell lung cancer (NSCLC), increasing evidence suggests that a microbiome composition signature is associated with clinical response to ICIs as well as with the development of immune-related adverse events. In support of this, antibiotic (ATB)-related dysbiosis has been consistently linked with the deleterious impact of ICI response, shortening the overall survival (OS) among patients on ATBs prior to ICI initiation. In parallel, several preclinical experiments have unravelled various strategies using probiotics, prebiotics, diet, and fecal microbiota transplantation as new therapeutic tools to beneficially shift the microbiome and enhance ICI efficacy. These approaches are currently being evaluated in clinical trials and have achieved encouraging preliminary results. In this article, we reviewed the recent studies on the gut microbiome as a potential biomarker and an adjuvant therapy to ICIs in NSCLC patients.
Population-Based Survival Analysis of Stage IVB Small-Cell Neuroendocrine Carcinoma in Comparison to Major Histological Subtypes of Cervical Cancer
Authors: Mabuchi Seiji , Komura Naoko , Sasano Tomoyuki , Sakata Mina , Matsuzaki Shinya , Hisa Tsuyoshi , Kamiura Shoji , Morishima Toshitaka , Miyashiro Isao
Published: October 2023

The aim of the current study is to investigate the survival outcome of stage IVB SCNEC of the uterine cervix in comparison to major histological subtypes of cervical cancer. A population-based retrospective cohort study was conducted using the Osaka Cancer Registry data from 1994 to 2018. All FIGO 2009 stage IVB cervical cancer patients who displayed squamous cell carcinoma (SCC), adenocarcinoma (A), adenosquamous cell carcinoma (AS), or small-cell neuroendocrine carcinoma (SCNEC) were first identified. The patients were classified into groups according to the types of primary treatment. Then, their survival rates were examined using the Kaplan–Meier method. Overall, in a total of 1158 patients, clearly differential survival rates were observed according to the histological subtypes, and SCNEC was associated with shortest survival. When examined according to the types of primary treatments, SCNEC was associated with significantly decreased survival when compared to SCC or A/AS, except for those treated with surgery. In patients with FIGO 2009 stage IVB cervical cancer, SCNEC was associated with decreased survival when compared to SCC or A/AS. Although current treatments with either surgery, chemotherapy or radiotherapy have some therapeutic efficacies, to improve the prognosis, novel effective treatments specifically targeting cervical SCNEC need to be developed.
Reinforcement-Learning-Based Localization of Hippocampus for Alzheimer’s Disease Detection
Authors: Raj Aditya , Mirzaei Golrokh
Published: October 2023

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder primarily impacting memory and cognitive functions. The hippocampus serves as a key biomarker associated with AD. In this study, we present an end-to-end automated approach for AD detection by introducing a reinforcement-learning-based technique to localize the hippocampus within structural MRI images. Subsequently, this localized hippocampus serves as input for a deep convolutional neural network for AD classification. We model the agent–environment interaction using a Deep Q-Network (DQN), encompassing both a convolutional Target Net and Policy Net. Furthermore, we introduce an integrated loss function that combines cross-entropy and contrastive loss to effectively train the classifier model. Our approach leverages a single optimal slice extracted from each subject’s 3D sMRI, thereby reducing computational complexity while maintaining performance comparable to volumetric data analysis methods. To evaluate the effectiveness of our proposed localization and classification framework, we compare its performance to the results achieved by supervised models directly trained on ground truth hippocampal regions as input. The proposed approach demonstrates promising performance in terms of classification accuracy, F1-score, precision, and recall. It achieves an F1-score within an error margin of 3.7% and 1.1% and an accuracy within an error margin of 6.6% and 1.6% when compared to the supervised models trained directly on ground truth masks, all while achieving the highest recall score.
Deep Learned Segmentations of Inflammation for Novel ⁹⁹mTc-maraciclatide Imaging of Rheumatoid Arthritis
Authors: Cobb Robert , Cook Gary J. R. , Reader Andrew J.
Published: October 2023

Rheumatoid arthritis (RA) is an autoimmune disease that causes joint pain, stiffness, and erosion. Power Doppler ultrasound and MRI are imaging modalities used in detecting and monitoring the disease, but they have limitations. ⁹⁹mTc-maraciclatide gamma camera imaging is a novel technique that can detect joint inflammation at all sites in a single examination and has been shown to correlate with power Doppler ultrasound. In this work, we investigate if machine learning models can be used to automatically segment regions of normal, low, and highly inflamed tissue from 192 ⁹⁹mTc-maraciclatide scans of the hands and wrists from 48 patients. Two models were trained: a thresholding model that learns lower and upper threshold values and a neural-network-based nnU-Net model that uses a convolutional neural network (CNN). The nnU-Net model showed 0.94 ± 0.01, 0.51 ± 0.14, and 0.76 ± 0.16 modified Dice scores for segmenting the normal, low, and highly inflamed tissue, respectively, when compared to clinical segmented labels. This outperforms the thresholding model, which achieved modified Dice scores of 0.92 ± 0.01, 0.14 ± 0.07, and 0.35 ± 0.21, respectively. This is an important first step in developing artificial intelligence (AI) tools to assist clinicians’ workflow in the use of this new radiopharmaceutical.
Investigation of the Water-Invasion Gas Efficiency in the Kela-2 Gas Field Using Multiple Experiments
Authors: Han Donghuan , Xiong Wei , Jiang Tongwen , Gao Shusheng , Liu Huaxun , Ye Liyou , Zhu Wenqing , An Weiguo
Published: October 2023

Although improving the recovery of water-invaded gas reservoirs has been extensively studied in the natural gas industry, the nature of the efficiency of water-invaded gas recovery remains uncertain. Low-field nuclear magnetic resonance (NMR) can be used to clearly identify changes in water saturation in the core during high-pressure water-invasion gas. Here, we provide four types of water-invasion gas experiments (spontaneous imbibition, atmospheric pressure, high-pressure approximate equilibrium, and depletion development water-invasion gas) to reveal the impact of the water-invasion gas efficiency on the recovery of water-invasion gas reservoirs. NMR suggested that imbibition mainly occurs in medium to large pores and that residual gas remains mainly in large pores. The amount of gas driven out from the large pores by imbibition was much greater than that driven out from the small pores. Our findings indicate that the initial gas saturation, contact surface, and permeability are the main factors controlling the residual gas saturation, suggesting that a reasonable initial water saturation should be established before the water-invasion gas experiments. Additionally, the water-invasion gas efficiency at high pressures can be more reliably obtained than that at normal pressures. After the high-pressure approximate equilibrium water invasion for gas displacement, a large amount of residual gas remains in the relatively larger pores of the core, with a residual gas saturation of 42%. In contrast to conventional experiments, the residual gas saturation and water displacement efficiency of the high-pressure approximate equilibrium water invasion for gas displacement did not exhibit a favorable linear relationship with the permeability. The residual gas saturation ranged from 34 to 43% (avg. 38%), while the water displacement efficiency ranged from 32 to 45% (avg. 40%) in the high-pressure approximate equilibrium water invasion for gas displacement. The residual gas saturation in the depletion development water-invasion gas experiment was 26–40% (average: 33%), with an efficiency ranging from 45 to 50% (average: 48%), indicating that the depletion development experiment is closer to the actual development process of gas reservoirs. Our findings provide novel insights into water-invasion gas efficiency, providing robust estimates of the recovery of water-invasion gas reservoirs.
Conventional Dissolved Gases Analysis in Power Transformers: Review
Authors: Rangel Bessa Alcebíades , Farias Fardin Jussara , Marques Ciarelli Patrick , Frizera Encarnação Lucas
Published: October 2023

Transformers insulated with mineral oil tend to form gases, which might be caused by system faults or extended use. Based on an evaluation of the main failure analysis techniques using combustible gases, this study reviewed the conventional techniques for Dissolved Gas Analysis (DGA), present in the norms IEC 60599 and IEEE Std C57.104, and their failure analysis tendency. Furthermore, to illustrate distinct technique performances and failures, the performance of the following techniques was analyzed based on the IEC TC10 database: Dornenburg, Duval Triangle, Duval Pentagon, IEC ratio method, Key Gas, and Rogers. The objective of this work was to present relevant information to support students and professionals who work in failure analysis and/or assist in the development of new tools in the DGA field.
Optimal Sizing of Renewable Energy Communities: A Multiple Swarms Multi-Objective Particle Swarm Optimization Approach
Authors: Faria João , Marques Carlos , Pombo José , Mariano Sílvio , Calado Maria do Rosário
Published: October 2023

Renewable energy communities have gained popularity as a means of reducing carbon emissions and enhancing energy independence. However, determining the optimal sizing for each production and storage unit within these communities poses challenges due to conflicting objectives, such as minimizing costs while maximizing energy production. To address this issue, this paper employs a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm with multiple swarms. This approach aims to foster a broader diversity of solutions while concurrently ensuring a good plurality of nondominant solutions that define a Pareto frontier. To evaluate the effectiveness and reliability of this approach, four case studies with different energy management strategies focused on real-world operations were evaluated, aiming to replicate the practical challenges encountered in actual renewable energy communities. The results demonstrate the effectiveness of the proposed approach in determining the optimal size of production and storage units within renewable energy communities, while simultaneously addressing multiple conflicting objectives, including economic viability and flexibility, specifically Levelized Cost of Energy (LCOE), Self-Consumption Ratio (SCR) and Self-Sufficiency Ratio (SSR). The findings also provide valuable insights that clarify which energy management strategies are most suitable for this type of community.
Assessing the Impact of Shallow Renovation on Energy Poverty: A Primary Data Study
Authors: Barrella Roberto , Romero José Carlos , Laguillo Almudena , Sevilla Ester
Published: October 2023

One of the main identified causes of energy poverty (EP) is the low energy efficiency of housing. In this line, since 2018, public administrations and NGOs collaborating with the Naturgy Foundation’s Energy Renovation Solidarity Fund have implemented several shallow renovation interventions in 3660 Spanish vulnerable households. However, the effects of these measures on domestic energy affordability were not evaluated before because of a lack of a proper method. This paper presents a methodology to objectively assess the impact of these interventions on EP. In particular, this work proposes calculating a hidden EP indicator using data from a primary survey and applies it to a local case study (54 vulnerable households in Catalonia—10% of dwellings renovated by the Fund in the region) by processing their characteristics and energy bills before and after the implementation of the interventions. Considering the whole sample of households analysed, the hidden EP indicator drops by 10% in absolute terms (11.2% in relative terms) after the retrofit, and the average EP gap goes from 423 €/year to 313 €/year, thus marking a significant positive effect of the analysed interventions on the EP situation of this population. Eventually, extrapolating the results to the vulnerable population in Spain, this paper points out a series of recommendations that could be useful for decision-makers and organisations when designing and implementing shallow renovation interventions.
Principal Component Analysis of Alternative Splicing Profiles Revealed by Long-Read ONT Sequencing in Human Liver Tissue and Hepatocyte-Derived HepG2 and Huh7 Cell Lines
Authors: Sarygina Elizaveta , Kozlova Anna , Deinichenko Kseniia , Radko Sergey , Ptitsyn Konstantin , Khmeleva Svetlana , Kurbatov Leonid K. , Spirin Pavel , Prassolov Vladimir S. , Ilgisonis Ekaterina , Lisitsa Andrey , Ponomarenko Elena
Published: October 2023

The long-read RNA sequencing developed by Oxford Nanopore Technology provides a direct quantification of transcript isoforms. That makes the number of transcript isoforms per gene an intrinsically suitable metric for alternative splicing (AS) profiling in the application to this particular type of RNA sequencing. By using this simple metric and recruiting principal component analysis (PCA) as a tool to visualize the high-dimensional transcriptomic data, we were able to group biospecimens of normal human liver tissue and hepatocyte-derived malignant HepG2 and Huh7 cells into clear clusters in a 2D space. For the transcriptome-wide analysis, the clustering was observed regardless whether all genes were included in analysis or only those expressed in all biospecimens tested. However, in the application to a particular set of genes known as pharmacogenes, which are involved in drug metabolism, the clustering worsened dramatically in the latter case. Based on PCA data, the subsets of genes most contributing to biospecimens’ grouping into clusters were selected and subjected to gene ontology analysis that allowed us to determine the top 20 biological processes among which translation and processes related to its regulation dominate. The suggested metrics can be a useful addition to the existing metrics for describing AS profiles, especially in application to transcriptome studies with long-read sequencing.
Natural Compounds Purified from the Leaves of Aristotelia chilensis: Makomakinol, a New Alkaloid and the Effect of Aristoteline and Hobartine on NaV Channels
Authors: Pérez Rebeca , Figueredo Claudia , Burgos Viviana , Cabrera-Pardo Jaime R. , Schmidt Bernd , Heydenreich Matthias , Koch Andreas , Deuis Jennifer R. , Vetter Irina , Paz Cristian
Published: October 2023

Aristotelia chilensis or “maqui” is a tree native to Chile used in the folk medicine of the Mapuche people as an anti-inflammatory agent for the treatment of digestive ailments, fever, and skin lesions. Maqui fruits are black berries which are considered a “superfruit” with notable potential health benefits, promoted to be an antioxidant, cardioprotective, and anti-inflammatory. Maqui leaves contain non-iridoid monoterpene indole alkaloids which have previously been shown to act on nicotinic acetylcholine receptors, potassium channels, and calcium channels. Here, we isolated a new alkaloid from maqui leaves, now called makomakinol, together with the known alkaloids aristoteline, hobartine, and 3-formylindole. Moreover, the polyphenols quercetine, ethyl caffeate, and the terpenes, dihydro-β-ionone and terpin hydrate, were also obtained. In light of the reported analgesic and anti-nociceptive properties of A. chilensis, in particular a crude mixture of alkaloids containing aristoteline and hobartinol (PMID 21585384), we therefore evaluated the activity of aristoteline and hobartine on NaV1.8, a key NaV isoform involved in nociception, using automated whole-cell patch-clamp electrophysiology. Aristoteline and hobartine both inhibited Nav1.8 with an IC50 of 68 ± 3 µM and 54 ± 1 µM, respectively. Hobartine caused a hyperpolarizing shift of the voltage-dependence of the activation, whereas aristoteline did not change the voltage-dependence of the activation or inactivation. The inhibitory activity of these alkaloids on NaV channels may contribute to the reported analgesic properties of Aristotelia chilensis used by the Mapuche people.
Differences in Mechanical, Electrical and Calcium Transient Performance of the Isolated Right Atrial and Ventricular Myocardium of Guinea Pigs at Different Preloads (Lengths)
Authors: Lisin Ruslan , Balakin Alexandr , Mukhlynina Elena , Protsenko Yuri
Published: October 2023

There are only a few studies devoted to the comparative and simultaneous study of the mechanisms of the length-dependent regulation of atrial and ventricular contractility. Therefore, an isometric force-length protocol was applied to isolated guinea pig right atrial (RA) strips and ventricular (RV) trabeculae, with a simultaneous measurement of force (Frank–Starling mechanism) and Ca2+ transients (CaT) or transmembrane action potentials (AP). Over the entire length-range studied, the duration of isometric contraction, CaT and AP, were shorter in the RA myocardium than in the RV myocardium. The RA myocardium was stiffer than the RV myocardium. With the increasing length of the RA and RV myocardium, the amplitude and duration of isometric contraction and CaT increased, as well as the amplitude and area of the “CaT difference curves” (shown for the first time). However, the rates of the tension development and relaxation decreased. No contribution of AP duration to the heterometric regulation of isometric tension was found in either the RA or RV myocardium of the guinea pig. Changes in the degree of overlap of the contractile proteins of the guinea pig RA and RV myocardium mainly affect CaT kinetics but not AP duration.
Changes in Plasma Pyruvate and TCA Cycle Metabolites upon Increased Hepatic Fatty Acid Oxidation and Ketogenesis in Male Wistar Rats
Authors: Dankel Simon Nitter , Kalleklev Tine-Lise , Tungland Siri Lunde , Stafsnes Marit Hallvardsdotter , Bruheim Per , Aloysius Thomas Aquinas , Lindquist Carine , Skorve Jon , Nygård Ottar Kjell , Madsen Lise , Bjørndal Bodil , Sydnes Magne Olav , Berge Rolf Kristian
Published: October 2023

Altered hepatic mitochondrial fatty acid β-oxidation and associated tricarboxylic acid (TCA) cycle activity contributes to lifestyle-related diseases, and circulating biomarkers reflecting these changes could have disease prognostic value. This study aimed to determine hepatic and systemic changes in TCA-cycle-related metabolites upon the selective pharmacologic enhancement of mitochondrial fatty acid β-oxidation in the liver, and to elucidate the mechanisms and potential markers of hepatic mitochondrial activity. Male Wistar rats were treated with 3-thia fatty acids (e.g., tetradecylthioacetic acid (TTA)), which target mitochondrial biogenesis, mitochondrial fatty acid β-oxidation, and ketogenesis predominantly in the liver. Hepatic and plasma concentrations of TCA cycle intermediates and anaplerotic substrates (LC-MS/MS), plasma ketones (colorimetric assay), and acylcarnitines (HPLC-MS/MS), along with associated TCA-cycle-related gene expression (qPCR) and enzyme activities, were determined. TTA-induced hepatic fatty acid β-oxidation resulted in an increased ratio of plasma ketone bodies/nonesterified fatty acid (NEFA), lower plasma malonyl-CoA levels, and a higher ratio of plasma acetylcarnitine/palmitoylcarnitine (C2/C16). These changes were associated with decreased hepatic and increased plasma pyruvate concentrations, and increased plasma concentrations of succinate, malate, and 2-hydroxyglutarate. Expression of several genes encoding TCA cycle enzymes and the malate–oxoglutarate carrier (Slc25a11), glutamate dehydrogenase (Gdh), and malic enzyme (Mdh1 and Mdh2) were significantly increased. In conclusion, the induction of hepatic mitochondrial fatty acid β-oxidation by 3-thia fatty acids lowered hepatic pyruvate while increasing plasma pyruvate, as well as succinate, malate, and 2-hydroxyglutarate.
Activated Screen-Printed Boron-Doped Diamond Electrode for Rapid and Highly Sensitive Determination of Curcumin in Food Products
Authors: Kozak Jędrzej , Tyszczuk-Rotko Katarzyna , Keller Aleksy , Wójciak Magdalena , Sowa Ireneusz
Published: October 2023

Due to a great interest in the beneficial properties of polyphenolic antioxidant curcumin (CCM), sensitive and accurate methods for determining CCM are needed. The purpose of our research was to develop a very simple, fast, and sensitive differential pulse adsorptive stripping voltammetric (DPAdSV) procedure using an electrochemically activated screen-printed boron-doped diamond electrode (aSPBDDE) for the determination of CCM. The activation of the SPBDDE was accomplished in a solution of 0.1 mol/L NaOH by performing five cyclic voltammetric scans in the range of 0–2 V, at ν of 100 mV/s. The changes in surface morphology and the reduction of the charge transfer resistance due to the activation of the electrode resulted in the amplification of the CCM analytical signal on the aSPBDDE. As a result, an extremely sensitive measurement tool was formed, which under optimized conditions (0.025 mol/L PBS of pH = 2.6, Eacc of 0.3 V, tacc of 90 s, ΔEA of 100 mV, ν of 150 mV/s, and tm of 10 ms) allowed us to obtain a limit of detection (LOD) of 5.0 × 10−13 mol/L. The aSPBDDE has proven to be a highly effective tool for the direct determination of CCM in food samples with high accuracy and precision. The results are in agreement with those obtained using ultra-high-performance liquid chromatography coupled with mass spectrometry and electrospray ionization (UHPLC-ESI/MS).
Exploring the BiFeO3-PbTiO3-SrTiO3 Ternary System to Obtain Good Piezoelectrical Properties at Low and High Temperatures
Authors: Tuluk Anton , van der Zwaag Sybrand
Published: October 2023

In this work, we investigated the piezoelectric properties of BiFeO3-rich (1 − (y + x)) BiFeO3–y PbTiO3–x SrTiO3 (0.1 ≤ x ≤ 0.35; 0.1 ≤ y ≤ 0.3) bulk piezoceramics, as this system could potentially lead to the development of bulk piezoelectric ceramics that are suitable for high-temperature applications (>200 °C). Samples with various levels of PbTiO3 and SrTiO3 were prepared via a conventional solid-state route. X-ray diffraction confirmed a pure perovskite phase for the compositions, which was explored without secondary phases. It was found that the addition of comparable levels of PbTiO3 and SrTiO3 to the BiFeO3 ceramic resulted in higher piezoelectric properties compared to those of the pure BiFeO3 and binary systems. The Curie temperature was significantly reduced by dual doping, with SrTiO3 and PbTiO3 additions resulting in comparable Curie temperature depressions. The locations of the phase boundaries between the cubic, pseudocubic, and rhombohedral crystal structures were determined. The highest piezoelectric properties, including a d33 value of 250 pC/N at room temperature, were obtained for the samples with the composition x = 0.3, y = 0.25, which was close to the cubic–pseudocubic phase boundary in the phase diagram. The temperature dependence of the piezoelectric properties varied depending on the previous thermal history, yet an appropriate heat treatment resulted in an almost temperature-stable d33 value. The ceramic with the lowest temperature sensitivity and a high Curie temperature of 350 °C was found for x = 0.1, y = 0.2 with a d33 value of 60 pC/N at RT and 71 pC/N at 300 °C (after poling at 60 kV/cm and a stabilizing heat treatment). However, the materials developed were still unsuitable for applications at high temperatures due to a rapidly increasing electrical conductivity with increasing temperature.
Paradox of Book and Claim for Carbon Emission Reduction in Maritime Operations Management: Mathematical Models and Numerical Experiments
Authors: Wang Shuaian , Liu Yuan , Wang Haoqing , Du Yuquan
Published: October 2023

In recent years, the maritime industry’s carbon emissions have garnered increasing attention, leading to the proposal of various policy measures aimed at mitigating emissions and fostering a green and sustainable maritime sector. Among these measures, the book and claim mechanism, which allows shippers to access low or zero-emission bunkering by purchasing such fuels without physically participating in the refueling process, has emerged as a crucial catalyst for fuel conversion within the maritime industry. While book and claim has gained widespread recognition and facilitated the sale of clean fuels by some bunker suppliers, there has been limited research focused on evaluating its practical efficacy. Thus, we construct two distinct Mixed-Integer Linear Programming (MILP) models—one with the inclusion of the book and claim mechanism and one without—and conduct an analytical comparison of optimal decisions made by bunker suppliers and shippers under different model scenarios. Through numerical experiments, we have uncovered a noteworthy insight: with book and claim, bunker suppliers may set higher prices to maximize total profits due to various price sensitivities among shippers towards clean fuels, thus promoting low-price-sensitive shippers to purchase clean fuels while making it challenging for high-price-sensitive shippers to do so. Consequently, when compared to a scenario without book and claim, the total quantity of clean fuels purchased by shippers in the presence of book and claim may decrease, giving rise to a paradox where the implementation of book and claim inadvertently increases societal carbon emissions. This underscores the imperative for policymakers to conduct comprehensive market research, understand different shippers’ price sensitivities towards clean fuels, and make scientifically sound decisions when considering the implementation of the book and claim mechanism.
A Robust and Integrated Visual Odometry Framework Exploiting the Optical Flow and Feature Point Method
Authors: Qiu Haiyang , Zhang Xu , Wang Hui , Xiang Dan , Xiao Mingming , Zhu Zhiyu , Wang Lei
Published: October 2023

In this paper, we propose a robust and integrated visual odometry framework exploiting the optical flow and feature point method that achieves faster pose estimate and considerable accuracy and robustness during the odometry process. Our method utilizes optical flow tracking to accelerate the feature point matching process. In the odometry, two visual odometry methods are used: global feature point method and local feature point method. When there is good optical flow tracking and enough key points optical flow tracking matching is successful, the local feature point method utilizes prior information from the optical flow to estimate relative pose transformation information. In cases where there is poor optical flow tracking and only a small number of key points successfully match, the feature point method with a filtering mechanism is used for posing estimation. By coupling and correlating the two aforementioned methods, this visual odometry greatly accelerates the computation time for relative pose estimation. It reduces the computation time of relative pose estimation to 40% of that of the ORB_SLAM3 front-end odometry, while ensuring that it is not too different from the ORB_SLAM3 front-end odometry in terms of accuracy and robustness. The effectiveness of this method was validated and analyzed using the EUROC dataset within the ORB_SLAM3 open-source framework. The experimental results serve as supporting evidence for the efficacy of the proposed approach.
Quantification of the Risk of Musculoskeletal Disorders of the Upper Limb Using Fuzzy Logic: A Study of Manual Wheelchair Propulsion
Authors: Marchiori Claire , Gagnon Dany H. , Pradon Didier
Published: October 2023

Background: For manual wheelchair users, overuse of the upper limbs can cause upper limb musculoskeletal disorders, which can lead to a loss of autonomy. The main objective of this study was to quantify the risk level of musculoskeletal disorders of different slope propulsions in manual wheelchair users using fuzzy logic. Methods: In total, 17 spinal cord injury participants were recruited. Each participant completed six passages on a motorized treadmill, the inclination of which varied between (0° to 4.8°). A motion capture system associated with instrumented wheels of a wheelchair was used. Using a biomechanical model of the upper limb and the fuzzy logic method, an Articular Discomfort Index (ADI) was developed. Results: We observed an increase in articular discomfort during propulsion on a slope with increasing discomfort at the shoulder, elbow and wrist, due to an increase in kinetics. There was a kinetically significant change in the kinetic global ADI (22 to 25%) and no change in the kinematic. The ADI increased from 14 to 36% during slope propulsion for each joint. Conclusion: The quantification of the level of discomfort helps us to highlight the situations with the most high-risk exposures and to identify the parameters responsible for this discomfort.
Toward Structural Health Monitoring with the MyShake Smartphone Network
Authors: Patel Sarina C. , Günay Selim , Marcou Savvas , Gou Yuancong , Kumar Utpal , Allen Richard M.
Published: October 2023

The field of structural health monitoring (SHM) faces a fundamental challenge related to accessibility. While analytical and empirical models and laboratory tests can provide engineers with an estimate of a structure’s expected behavior under various loads, measurements of actual buildings require the installation and maintenance of sensors to collect observations. This is costly in terms of power and resources. MyShake, the free seismology smartphone app, aims to advance SHM by leveraging the presence of accelerometers in all smartphones and the wide usage of smartphones globally. MyShake records acceleration waveforms during earthquakes. Because phones are most typically located in buildings, a waveform recorded by MyShake contains response information from the structure in which the phone is located. This represents a free, potentially ubiquitous method of conducting critical structural measurements. In this work, we present preliminary findings that demonstrate the efficacy of smartphones for extracting the fundamental frequency of buildings, benchmarked against traditional accelerometers in a shake table test. Additionally, we present seven proof-of-concept examples of data collected by anonymous and privately owned smartphones running the MyShake app in real buildings, and assess the fundamental frequencies we measure. In all cases, the measured fundamental frequency is found to be reasonable and within an expected range in comparison with several commonly used empirical equations. For one irregularly shaped building, three separate measurements made over the course of four months fall within 7% of each other, validating the accuracy of MyShake measurements and illustrating how repeat observations can improve the robustness of the structural health catalog we aim to build.
A Novel Hybrid Convolutional Neural Network- and Gated Recurrent Unit-Based Paradigm for IoT Network Traffic Attack Detection in Smart Cities
Authors: Gupta  Brij B. , Chui Kwok Tai , Gaurav  Akshat , Arya  Varsha , Chaurasia  Priyanka
Published: October 2023

Internet of Things (IoT) devices within smart cities, require innovative detection methods. This paper addresses this critical challenge by introducing a deep learning-based approach for the detection of network traffic attacks in IoT ecosystems. Leveraging the Kaggle dataset, our model integrates Convolutional Neural Networks (CNNs) and Gated Recurrent Units (GRUs) to capture both spatial and sequential features in network traffic data. We trained and evaluated our model over ten epochs, achieving an impressive overall accuracy rate of 99%. The classification report reveals the model’s proficiency in distinguishing various attack categories, including ‘Normal’, ‘DoS’ (Denial of Service), ‘Probe’, ‘U2R’ (User to Root), and ‘Sybil’. Additionally, the confusion matrix offers valuable insights into the model’s performance across these attack types. In terms of overall accuracy, our model achieves an impressive accuracy rate of 99% across all attack categories. The weighted- average F1-score is also 99%, showcasing the model’s robust performance in classifying network traffic attacks in IoT devices for smart cities. This advanced architecture exhibits the potential to fortify IoT device security in the complex landscape of smart cities, effectively contributing to the safeguarding of critical infrastructure
Farmers’ Cognition of and Satisfaction with Policy Affect Willingness of Returning Straw to Field: Based on Evolutionary Game Perspective
Authors: Chen Hong , Wang Haoyan , Zhou Sishu
Published: October 2023

As an important measure to promote the black soil protection strategy, returning straw to the fields is the choice of government policy to affect the decision-making behavior of farmers, and the policy implementation process is a dynamic game equilibrium process between farmers and the government. In order to explore the influence of policies on farmers’ straw-returning decision-making and stability processes, this paper used a logit model to analyze the influencing factors on farmers’ straw-returning decision-making behavior based on the survey data of 397 farmers in Hailun City, Heilongjiang Province. This study also constructs the evolutionary game model between farmers and government, carrying out a stability strategy analysis and numerical simulation. The results evidence that farmers’ cognition of fertilization technology, ecological protection, policy satisfaction and cognition of straw returning recipients have a significant negative influence on their willingness to return to the field, and the effect intensity decreases successively. What is more, cognition of crop disease resistance has a positive effect on the willingness of returning straw to the field. It is found that the game balancing process of farmers’ behavior and government straw returning policy evolution can be divided into three stages. At present, China’s straw returning policy is in the intermediate stage, and government needs to provide comprehensive compensation for returning straw to the field according to local conditions such as farmers’ willingness, crop conditions and so on.
Re-Evaluating Human Cytomegalovirus Vaccine Design: Prediction of T Cell Epitopes
Authors: Barry Peter A. , Iyer Smita S. , Gibson Laura
Published: October 2023

HCMV vaccine development has traditionally focused on viral antigens identified as key targets of neutralizing antibody (NAb) and/or T cell responses in healthy adults with chronic HCMV infection, such as glycoprotein B (gB), the glycoprotein H-anchored pentamer complex (PC), and the unique long 83 (UL83)-encoded phosphoprotein 65 (pp65). However, the protracted absence of a licensed HCMV vaccine that reduces the risk of infection in pregnancy regardless of serostatus warrants a systematic reassessment of assumptions informing vaccine design. To illustrate this imperative, we considered the hypothesis that HCMV proteins infrequently detected as targets of T cell responses may contain important vaccine antigens. Using an extant dataset from a T cell profiling study, we tested whether HCMV proteins recognized by only a small minority of participants encompass any T cell epitopes. Our analyses demonstrate a prominent skewing of T cell responses away from most viral proteins—although they contain robust predicted CD8 T cell epitopes—in favor of a more restricted set of proteins. Our findings raise the possibility that HCMV may benefit from evading the T cell recognition of certain key proteins and that, contrary to current vaccine design approaches, including them as vaccine antigens could effectively take advantage of this vulnerability.
Features of the organization of medical and medical-psychological rehabilitation in the FSBI Evpatoria Military Children’s Clinical Sanatorium named after E. P. Glinka of the Ministry of Defense of the Russian Federation
Authors:   Moscow Scientific and Practical Center of Medical Rehabilitation, Rehabilitation and Sports Medicine. Moscow, Russia, Razumov A. N. ,   I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia, Dolgikh S. V. ,   Main Military Medical Directorate of the Ministry of Defense of the Russian Federation Moscow, Russia, Kirsanova A. A. ,   Main Military Medical Directorate of the Ministry of Defense of the Russian Federation Moscow, Russia, Kovlen D. V. ,   Federal State Budgetary Educational Institution of Higher Education "Military Medical Academy named after S. M. Kirov" of the Russian Ministry of Defense; Russia, Ponomarenko Yu. N. ,   FSBI Evpatoria Military Children’s Clinical Sanatorium named after E. P. Glinka of the Ministry of Defense of the Russian Federation, Evpatoria, Russia
Published: October 2023

The experience of conducting medical and medical-psychological rehabilitation in the FSBI Evpatoria Military Children’s Clinical Sanatorium named after E. P. Glinka of the Ministry of Defense of the Russian Federation is analyzed. Purpose of the study: an analysis of the implementation of medical and medical-psychological rehabilitation activities in the FSBI Evpatoria Military Children’s Clinical Sanatorium named after E. P. Glinka of the Ministry of Defense of the Russian Federation and a scientific substantiation of approaches to their improvement. Material and methods. An analysis of rehabilitation measures for 3,795 military personnel. Results. Based on the analysis of rehabilitation activities carried out over the past 5 years among 3,795 military personnel, the trends in changes in the structure of contingents sent for rehabilitation are presented. The need to develop individual rehabilitation programs based on standards and clinical recommendations is emphasized.