bluuebunny/crossref_metadata_2025 huggingface dataset:
Direct Detection of KPC Peak from Positive Blood Cultures Using MALDI-TOF MS: Are We There Yet?
Authors: Moreira Natália Kehl , Wilhelm Camila Mörschbächer , Echevarria Aymê Duarte , Volpato Fabiana Caroline Zempulski , Wink Priscila Lamb , Barth Afonso Luís , Caierão Juliana
Published: March 2023

Detecting carbapenemase-associated carbapenem resistance is a subject of major clinical and epidemiological concern as it influences therapeutic choice. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been proposed as a means to assess bacterial resistance mechanisms. We aimed to detect the KPC enzyme directly from positive blood cultures using MALDI-TOF MS. To do so, 102 clinical Enterobacteria were evaluated, including 59 blaKPC positives. Proteins were extracted using formic acid, isopropyl alcohol, and water (17:33:50) and spotted onto a steel target plate using the double-layer sinapinic acid technique. Two parameters were considered: (i) the visual detection of a clear peak with the expected KPC m/z and (ii) the evaluation of the relative intensity of the ions in the peak. A peak was observed in 56/59 blaKPC-positive isolates (94.9% sensitivity), with no false-positive results (100% specificity). When considering intensity, with a cut-off ≥120 (a.u.), sensitivity was 94.9% and specificity was 95.3%. We proposed a “buffer” zone, with intermediate values of intensity (115 to 125) reaching 100% sensitivity and specificity. The detection of KPC peaks directly from positive blood cultures using MALDI-TOF MS is feasible and rapid, which may improve appropriate patient therapy and antimicrobial stewardship.
Links between Vitamin K, Ferroptosis and SARS-CoV-2 Infection
Authors: Nuszkiewicz Jarosław , Sutkowy Paweł , Wróblewski Marcin , Pawłowska Marta , Wesołowski Roland , Wróblewska Joanna , Woźniak Alina
Published: March 2023

Ferroptosis is a recently discovered form of programmed cell death. It is characterized by the accumulation of iron and lipid hydroperoxides in cells. Vitamin K is known to have antioxidant properties and plays a role in reducing oxidative stress, particularly in lipid cell membranes. Vitamin K reduces the level of reactive oxygen species by modulating the expression of antioxidant enzymes. Additionally, vitamin K decreases inflammation and potentially prevents ferroptosis. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leading to coronavirus disease 2019 (COVID-19) is associated with oxidant–antioxidant imbalance. Studies have shown that intensified ferroptosis occurs in various tissues and cells affected by COVID-19. Vitamin K supplementation during SARS-CoV-2 infection may have a positive effect on reducing the severity of the disease. Preliminary research suggests that vitamin K may reduce lipid peroxidation and inhibit ferroptosis, potentially contributing to its therapeutic effects in COVID-19 patients. The links between ferroptosis, vitamin K, and SARS-CoV-2 infection require further investigation, particularly in the context of developing potential treatment strategies for COVID-19.
TNF-α-Mediated Endothelial Cell Apoptosis Is Rescued by Hydrogen Sulfide
Authors: Diaz Sanchez Lorena , Sanchez-Aranguren Lissette , Wang Keqing , Spickett Corinne M. , Griffiths Helen R. , Dias Irundika H. K.
Published: March 2023

Endothelial dysfunction is implicated in the development and aggravation of cardiovascular complications. Among the endothelium-released vasoactive factors, hydrogen sulfide (H2S) has been investigated for its beneficial effects on the vasculature through anti-inflammatory and redox-modulating regulatory mechanisms. Reduced H2S bioavailability is reported in chronic diseases such as cardiovascular disease, diabetes, atherosclerosis and preeclampsia, suggesting the value of investigating mechanisms, by which H2S acts as a vasoprotective gasotransmitter. We explored whether the protective effects of H2S were linked to the mitochondrial health of endothelial cells and the mechanisms by which H2S rescues apoptosis. Here, we demonstrate that endothelial dysfunction induced by TNF-α increased endothelial oxidative stress and induced apoptosis via mitochondrial cytochrome c release and caspase activation over 24 h. TNF-α also affected mitochondrial morphology and altered the mitochondrial network. Post-treatment with the slow-releasing H2S donor, GYY4137, alleviated oxidising redox state, decreased pro-caspase 3 activity, and prevented endothelial apoptosis caused by TNF-α alone. In addition, exogenous GYY4137 enhanced S-sulfhydration of pro-caspase 3 and improved mitochondrial health in TNF-α exposed cells. These data provide new insights into molecular mechanisms for cytoprotective effects of H2S via the mitochondrial-driven pathway.
Modulation of Nrf2/HO-1 by Natural Compounds in Lung Cancer
Authors: Ghareghomi Somayyeh , Moosavi-Movahedi Faezeh , Saso Luciano , Habibi-Rezaei Mehran , Khatibi Ali , Hong Jun , Moosavi-Movahedi Ali A.
Published: March 2023

Oxidative stresses (OSs) are considered a pivotal factor in creating various pathophysiological conditions. Cells have been able to move forward by modulating numerous signaling pathways to moderate the defects of these stresses during their evolution. The company of Kelch-like ECH-associated protein 1 (Keap1) as a molecular sensing element of the oxidative and electrophilic stress and nuclear factor erythroid 2 (NF-E2)-related factor 2 (Nrf2) as a master transcriptional regulator of the antioxidant response makes a master cytoprotective antioxidant pathway known as the Keap1/Nrf2 pathway. This pathway is considered a dual-edged sword with beneficial features for both normal and cancer cells by regulating the gene expression of the array of endogenous antioxidant enzymes. Heme oxygenase-1 (HO-1), a critical enzyme in toxic heme removal, is one of the clear state indicators for the duality of this pathway. Therefore, Nrf2/HO-1 axis targeting is known as a novel strategy for cancer treatment. In this review, the molecular mechanism of action of natural antioxidants on lung cancer cells has been investigated by relying on the Nrf2/HO-1 axis.
Polystyrene Microplastics of Varying Sizes and Shapes Induce Distinct Redox and Mitochondrial Stress Responses in a Caco-2 Monolayer
Authors: Saenen Nelly D. , Witters Margo S. , Hantoro Inneke , Tejeda Inés , Ethirajan Anitha , Van Belleghem Frank , Smeets Karen
Published: March 2023

Currently, we lack crucial knowledge on how the physicochemical properties of particles affect cellular health, resulting in an important gap in our understanding of the human toxicity of microplastics (MPs). Our aim was to evaluate the impact of the size and the shape of MPs on uptake and the intracellular effects in a human epithelial colorectal adenocarcinoma (Caco-2) cell line. Spherical (200 nm and 2 µm) and fibre-/fragment-shaped (8.9 ± 10.1 µm by 1.14 ± 0.97 µm) polystyrene microplastics (PS-MPs) were used to study their uptake and the potential to induce redox and mitochondrial stress responses after 24 h of exposure. We demonstrated the cellular uptake of both spherical and fibre-/fragment-shaped MPs in a size-dependent manner. In response to 2 µm spheres, we observed differential expressions of redox-related genes, including HMOX1, CAT, and GPX1. All PS-MPs decreased the intracellular H2O2 levels, which can be attributed to mitochondrial stress responses, such as increased mitochondrial DNA content, footprint, and morphology. Altogether, we demonstrated uptakes and changes in redox and mitochondrial parameters for all PS-MPs, with the 200 nm spheres showing the most profound effects. This suggests that the induction of defensive responses in Caco-2 cells mainly correlates with the number of particles taken up.
Keap1-Nrf2 Heterodimer: A Therapeutic Target to Ameliorate Sickle Cell Disease
Authors: Chauhan Waseem , Zennadi Rahima
Published: March 2023

Sickle cell disease (SCD) is a monogenic inheritable disease characterized by severe anemia, increased hemolysis, and recurrent, painful vaso-occlusive crises due to the polymerization of hemoglobin S (HbS)-generated oxidative stress. Up until now, only four drugs are approved for SCD in the US. However, each of these drugs affects only a limited array of SCD pathologies. Importantly, curative therapies, such as gene therapy, or hematopoietic stem cell transplantation are not available for every patient because of their high costs, availability of donor matching, and their serious adverse effects. Therefore, there is an unmet medical need for novel therapeutic strategies that target broader SCD sequelae. SCD phenotypic severity can be alleviated by increasing fetal hemoglobin (HbF) expression. This results in the inhibition of HbS polymerization and thus sickling, and a reduction in oxidative stress. The efficacy of HbF is due to its ability to dilute HbS levels below the threshold required for polymerization and to influence HbS polymer stability in RBCs. Nuclear factor-E2-related factor 2 (Nrf2)/Kelch-like ECH-associated protein-1 (Keap1)-complex signaling is one of the most important cytoprotective signaling controlling oxidative stress. Nrf2 is present in most organs and, after dissociation from Keap1, it accumulates in the cytoplasm, then translocates to the nucleus where it binds to the antioxidant response element (ARE) sequences and increases the expression of various cytoprotective antioxidant genes. Keeping this in mind, various researchers have proposed a role of multiple agents, more importantly tert-Butylhydroquinone (tBHQ), curcumin, etc., (having electrophilic properties) in inhibiting keap1 activity, so that Nrf2 can translocate to the nucleus to activate the gamma globin gene, thus maintaining alpha-hemoglobin-stabilizing protein (AHSP) and HbF levels. This leads to reduced oxidative stress, consequently minimizing SCD-associated complications. In this review, we will discuss the role of the Keap-1–Nrf2 complex in hemoglobinopathies, especially in SCD, and how this complex might represent a better target for more effective treatment options.
Model Experimental Study on De-Icing Method of Bridge Pylon Beam Based on Electric Heating
Authors: Yang Zhiyong , Bao Tian , Chen Zhi , Xiao Henglin , Zhou Xinlong , Zhang Jiacheng , Liu Yin
Published: March 2023

The icing of bridge pylon crossbeams is a problem that could pose a serious threat to traffic during a cold winter. However, little research has been carried out on the problem and few corresponding countermeasures have been provided. This paper aims to propose a novel heating system, and to study the feasibility of beam de-icing and the related de-icing strategies so as to provide a reference scheme for the practical application of beam de-icing. A number of icing and de-icing tests were carried out on a scale model of Wuhan Yangtze River Second Bridge in the cold chamber. The de-icing effects of the beam in different environments and different de-icing methods were compared, and the recommended pre-heating time, applicable environment range, and heating method were given. The results of the model experiments show that pre-heating the heating system can prevent the surface of the beam from freezing and that the anti-icing method is more suitable for beam de-icing than the passive de-icing method. When the pre-heating time exceeds 7 min, the entire anti-icing process can be ice-free. When the wind velocity exceeds 5 m/s, it is safer to shut down the heating system, and using the passive de-icing method at the end of the icing can also eliminate the hidden danger of beam icing.
The Influence of Axial Compressive Stress and Internal Pressure on a Pipeline Network: A Review
Authors: Arumugam Thibankumar , Vijaya Kumar Suria Devi , Karuppanan Saravanan , Ovinis Mark
Published: March 2023

Due to their exceptional structural integrity, steel pipelines are the main component for oil and gas transmission. However, these pipelines are often affected by corrosion, despite corrosion protection, because of harsh working conditions. In addition to corrosion defects, pipelines are often subjected to multiple external loads. The combination of corrosion defects and external loads can significantly reduce the failure pressure, resulting in various failure behaviors. This reduction in failure pressure is especially critical in pipe bends as they are the weakest link in a pipeline. This paper presents an overview of the failure behavior of corroded steel pipe components subjected to internal pressure and axial compressive stress.
Revisiting the Role of Knee External Rotation in Non-Contact ACL Mechanism of Injury
Authors: Santos Carla F. , Bastos Ricardo , Andrade Renato , Pereira Rogério , Parente Marco P. L. , Jorge Renato Natal , Espregueira-Mendes João
Published: March 2023

An anterior cruciate ligament (ACL) tear is a severe sports injury that often occurs in young athletes. Besides the strong cumulative evidence on noncontact ACL tears, the injury mechanism (especially the contribution of external rotation) is still not well understood. The present work aims to evaluate which knee kinetics result in higher ACL stress and strain. A finite element model of the ACL was developed with a detailed geometry; the two distinct bundles (anteromedial and posterolateral) and the surrounding connective tissue were modelled based on medical anatomic measures and images. The model was validated using computational and cadaveric external data. Sixteen simulations were performed using different combinations of moments and axial loads applied to the knee model as boundary conditions. The results demonstrated that the peak stress (11.00 MPa) and strain (0.048) occurred at the midportion of the anteromedial bundle with the higher values being obtained under a combined knee valgus, flexion, tibial external rotation and high axial load. Anterior load showed low sensitivity in ACL stress and strain peaks. The tibial external rotation showed a higher contribution to the peak ACL stress and strain as compared to internal rotation. These results reinforce the role of axial load and highlight the importance of external rotation on ACL stress and strain, which may be suggestive of the ACL tear mechanism. The role of external rotation is often neglected and should be further explored in future cadaveric and experimental studies. The findings of this study provide data-driven insights to optimize the indications for prevention, diagnosis and treatment of ACL injuries in clinical practice and contribute to raising awareness of the injury mechanism among all relevant stakeholders.
An Approach Based on Simulation and Optimisation for the Intermodal Dispatching of Public Transport and Ride-Pooling Services
Authors: Lorente Ester , Codina Esteve , Barceló Jaume , Nökel Klaus
Published: March 2023

This paper provides a simulation and optimisation-based system to combine public transport (PT) with ride-pooling services (RP). According to the International Transport Forum (ITF), the RP could be established as a feeder of PT and included as the first or last leg of the journey with the option of transferring to/from PT in between. The system contains a dispatching core that uses an optimisation model with heuristic parameters to quickly analyse the potential permutations for each request. This topic is frequently based on simplistic modelling in the literature, and it has not been extensively tested in major urban regions. The whole metropolitan region of Barcelona is employed in this study, with a large realistic simulation model encompassing a 20 × 15 km area with a PT network of about 3000 stations and 300 route lines and nearly 114,000 traffic links. This enables for a more accurate evaluation of system performance and trip quality computation.
Flux Behaviour, Rejection and Concentration Factors, and Energy Demand during Ultrafiltration of Sweet Buttermilk
Authors: Dushkova Mariya , Ivanova Mihaela , Trublet Luca , Petkova Zhana , Teneva Olga , Miteva-Petrova Milena , Desseva Ivelina , Mihaylova Dasha
Published: March 2023

This work aimed to study the flux behavior, rejection and concentration factors, and energy demand to establish the optimal conditions during ultrafiltration of sweet buttermilk to produce ice cream. The experiments were conducted with a UF25-PAN membrane at a transmembrane pressure of 0.2, 0.35 and 0.5 MPa, and a volume reduction ratio (VRR) of 2, 3, 4, and 5. Total protein, fat, ash, and dry matter contents, phospholipid composition, and acidity of retentates and permeate were determined. The increase in the VRR led to a decrease in the permeate flux and an increase in the energy demand, rejection, and concentration factors of the main components of sweet buttermilk. The highest values of rejection and concentration factors established for fat were 98.65% and 4.93, respectively. The permeate flux and energy demand increased with the rise in the transmembrane pressure. The total phospholipids increased 2.8 times at VRR 5 compared to the initial buttermilk. The use of VRR 3 gave the best ratio between the permeate flux, the energy demand, and relatively high values of concentration and rejection factors. The use of VRR 5 will enrich the ice cream to the greatest extent to obtain a product with the highest level of biologically active substances (proteins, phospholipids, minerals).
A Universal Privacy-Preserving Multi-Blockchain Aggregated Identity Scheme
Authors: Sun Nigang , Zhang Yuanyi , Liu Yining
Published: March 2023

Cryptocurrencies offer various benefits in terms of privacy protection and cross-border transactions, but they have also been used for illicit activities such as money laundering due to their anonymous nature and the difficulty of cross-border regulation. Additionally, the unethical actions of some virtual asset service providers (VASPs), such as rug pulls and the embezzlement of user funds, have further eroded the trust between users and VASPs. Implementing identity management on blockchains can help restore trust between users and VASPs. However, current solutions have privacy concerns as identity providers have access to the asset balances and transaction records of each user’s wallet account, and no solution can support all public blockchains unconditionally. To address these issues, this paper proposes a multi-chain aggregated identity scheme. In this scheme, the identity provider will issue a non-fungible token (NFT) for users who have undergone verification, and wallet accounts from different blockchains will be added to a cryptographic accumulator. The accumulator value is then bound to the identity NFT through a smart contract by the user. This allows the user to prove to others that the identity of the wallet account owner has been verified. The use of accumulators also allows users to combine proof for multiple wallets into a single proof, which significantly improves the efficiency and provides a way for VASPs such as centralized exchanges to demonstrate Proof of Reserves (PoR) to users. Importantly, this scheme preserves privacy as neither the identity provider nor the VASPs can link the user’s real identity with the wallet accounts. Only regulators can access the user’s identity data held by the identity provider and the user’s wallet account held by the VASP to link real identities with wallet accounts for the purpose of sanctions or criminal investigations. Additionally, the scheme supports all blockchains by allowing wallet accounts from any public blockchain to be added to the accumulator. Furthermore, the NFT implementation in the scheme helps prevent identity loss or theft, as it can only be transferred by the identity provider.
Methodology to Identify and Prioritise the Sustainability Aspects to Be Considered in the Design of Brazilian Healthcare Buildings
Authors: Costa Marília , de Fátima Castro Maria , Mateus Ricardo
Published: March 2023

The evidence of climate change has increased the necessity for actions to avoid severe consequences for future generations. Recognising the benefits of sustainable and energy-efficient buildings has led to the development of several methods to estimate and rate the performance of building. Healthcare buildings are functional and dynamic structures that support their occupants’ healing processes and comfort. They have a significant role in society and specific goals in merging their strategic planning requirements (cost reduction, regulatory compliance, social responsibility, and performance improvement) with Sustainable Development Goals. Therefore, this paper addresses critical issues regarding the sustainability of the Brazilian healthcare sector by analysing the suitability of the most common international healthcare building sustainability assessment methods to the specific social, economic, and environmental contexts of the Brazilian healthcare sector. The paper analyses the HBSAtool-PT, a sustainability assessment method developed for this type of building, and identifies the possibilities for adapting to the Brazilian context. As a result, this research proposes a framework to assess the sustainability of healthcare buildings in Brazil. In the framework’s definition, a survey was conducted to determine the opinion of building stakeholders regarding the importance of indicators. A weighing system for the proposed sustainability indicators was developed using the AHP method.
Artificial Intelligence Approach for Early Detection of Brain Tumors Using MRI Images
Authors: Aleid Adham , Alhussaini Khalid , Alanazi Reem , Altwaimi Meaad , Altwijri Omar , Saad Ali S.
Published: March 2023

Artificial intelligence (AI) is one of the most promising approaches to health innovation. The use of AI in image recognition considerably extends findings beyond the constraints of human sight. The application of AI in medical imaging, which relies on picture interpretation, is beneficial for automatic diagnosis. Diagnostic radiology is evolving from a subjective perceptual talent to a more objective science thanks to AI. Automatic object detection in medical images is an essential AI technology in medicine. The problem of detecting brain tumors at an early stage is well advanced with convolutional neural network (CNN) and deep learning algorithms (DLA). The problem is that those algorithms require a training phase with a big database of more than 500 images and time-consuming with a complex computational and expensive infrastructure. This study proposes a classical automatic segmentation method for detecting brain tumors in the early stage using MRI images. It is based on a multilevel thresholding technique on a harmony search algorithm (HSO); the algorithm was developed to suit MRI brain segmentation, and parameters selection was optimized for the purpose. Multiple thresholds, based on the variance and entropy functions, break the histogram into multiple portions, and different colors are associated with each portion. To eliminate the tiny arias supposed as noise and detect brain tumors, morphological operations followed by a connected component analysis are utilized after segmentation. The brain tumor detection performance is judged using performance parameters such as Accuracy, Dice Coefficient, and Jaccard index. The results are compared to those acquired manually by experts in the field. The results were further compared with different CNN and DLA approaches using Brain Images dataset called the “BraTS 2017 challenge”. The average Dice Index was used as a performance measure for the comparison. The results of the proposed approach were found to be competitive in accuracy to those obtained by CNN and DLA methods and much better in terms of execution time, computational complexity, and data management.
Use of Sample Entropy to Assess Sub-Maximal Physical Load for Avoiding Exercise-Induced Cardiac Fatigue
Authors: Lai Yu-Han , Huang Po-Hsun , Hsiao Tzu-Chien
Published: March 2023

Sub-maximal physical load (sub-max) training is optimal for athletes. However, few methods can directly assess whether training is sub-max. Therefore, this study aimed to identify metrics that could assess sub-max training by predicting maximal physical load, helping athletes to avoid the risks associated with maximal training. Physiological data were collected from 30 participants in a bicycle incremental exercise experiment, including the R-R interval (RR), stroke volume (SV), breath-to-breath interval (BB), and breathing rate (BR). Sample Entropy (SampEn) analysis was used to assess the complexity of the physiological data. BR increased with exercise time but could not be used to identify the sub-max stage; however, SampEn BB could effectively identify the sub-max stage (p < 0.05), as could the novel indicators SampEn SV and cardiac output (p < 0.01). This study also identified the threshold value of each SampEn value in sub-max, which can be used as a sports science indicator to assess the load of athletes. The results suggest that SampEn-based indicators can be used to assess sub-max and maximal physical load. These findings can be used as a guide for quantitative exercise healthcare.
Fractional Sliding Mode Harmonic Control of an Active Power Filter
Authors: Fei Wesley , Hua Mingang
Published: March 2023

A sliding mode control (SMC) strategy with a fractional-order scheme is developed to provide an effective way to compensate for the harmonic current and strengthen the performance of an active power filter (APF). The formulation of a fractional-order sliding mode controller (FOSMC) is incorporated in the current control of an APF control system, obtaining an extra degree of freedom over integer-order ones to improve the dynamic property. The simulation results of the APF utilizing the designed strategy confirm the satisfactory performance and smaller total harmonic distortion (THD) by comparative study.
On the Melting Thresholds of Semiconductors under Nanosecond Pulse Laser Irradiation
Authors: Beránek Jiří , Bulgakov Alexander V. , Bulgakova Nadezhda M.
Published: March 2023

In this work, a unified numerical model is used to determine the melting thresholds and to investigate the early stages of melting of several crystalline semiconductors (Si, Ge, GaAs, CdTe and InP) irradiated by nanosecond laser pulses. A molten fraction approach is used for continuous transition over the melting point. The results are compared with previously published theoretical and experimental data. A survey on the thermophysical and optical properties of the selected materials has been carried out to gather the most relevant data on temperature dependent properties for the solid and liquid states of these semiconductors where such data are available. A generalization of the obtained results is established that enables evaluation of the melting thresholds for different semiconductors based on their properties and irradiation conditions (laser wavelength, pulse duration).
Characterization of Pterygomaxillary Suture Morphology: A CBCT Study
Authors: Tunis Tatiana Sella , Dratler Shaked , Kats Lazar , Allon Dror Michael
Published: March 2023

One of the most challenging procedures during maxillary osteotomy is pterygomaxillary suture (PMS) separation, due to the difficulty of directly inspecting this suture and the anatomical complexity of the adjacent structures. Knowing the precise anatomical dimensions and the position of the PMS, namely, the angle at which to approach this structure, may help in determining the proper osteotome. It will also help the oral and maxillofacial surgeon to perform this sensitive procedure more precisely and to minimize surgical complications (e.g., internal maxillary artery injury and unfavorable fracture during separation). The current study aimed to evaluate the morphology of PMS in an adult Israeli population using CBCT scans of the maxilla. Fifty CBCTs of healthy males (n = 27) and females (n = 23) were collected and analyzed. The vertical height, maximal thickness, and angulation of the PMS relative to the midsagittal plane of the skull were evaluated on both the right and left sides of the patient. An independent samples t-test was carried out to determine PMS morphological differences between males and females. A related samples t-test was conducted to determine the PMS morphological differences between the right and left sides. No significant differences in PMS parameters were found between sides in males and females (p > 0.225). Both males and females exhibited similar height and angulation of the PMS (p > 0.486). Interestingly, the PMS thickness was statistically greater in males (p = 0.029); however, this difference was clinically insignificant. The mean dimensions of the PMS in a healthy Israeli adult population are presented and discussed, as well as the clinical and methodological implications.
Fouling of Polyalkylmethylsiloxane Composite Membranes during Pervaporation Separation of ABE-Fermentation Mixtures
Authors: Rokhmanka Tatyana N. , Grushevenko Evgenia A. , Arapova Olga V. , Bondarenko Galina N. , Golubev George S. , Borisov Ilya L. , Volkov Alexey V.
Published: March 2023

Production of bio-alcohols is one of the approaches used in the development of alternative energy. Pervaporation is a promising option for the separation of bio-alcohols from the fermentation mixture. A serious problem in the process of continuous extraction of biobutanol from the fermentation broth is the contamination of the membrane, which leads to a decrease in its permeability over time. In this work, the transport properties of composite membranes based on polyheptylmethylsiloxane (PHeptMS), polydecylmethylsiloxane (PDecMS), and a commercial membrane MDK-3 were studied during separation of a real ABE-fermentation broth in vacuum pervaporation mode. The study was performed before and after continuous contact of the membranes with the fermentation broth for one month. Visually and by scanning electron spectroscopy, the presence of membrane surface residue and its effect on the wettability of the membrane selective layer by the components of the ABE broth were determined. The sediment composition was evaluated by energy dispersive analysis and infrared spectroscopy. According to the pervaporation separation of the ABE-broth using PHeptMS, PDecMS, and MDK-3 membranes, the butanol flux was 0.029, 0.012, and 0.054 kg/(m2·h), respectively. The butanol-water partition factor was 41, 22, and 13 for PHeptMS, PDecMS, and MDK-3, respectively. After one month of incubation of the membranes in ABE-fermentation broth during the separation of the model mixture, a decrease of 10 and 5% in permeate flux and separation factor, respectively, was observed for all membranes. Temperature dependences (30–60 °C) of permeate flux, permeability, and selectivity were obtained for the membranes after clogging. The most promising in terms of minimal negative changes as a result of fouling was demonstrated by the PHeptMS membrane. For it, the clogging dynamics during separation of the real fermentation broth for 216 h were investigated. Two characteristic steps of decrease in transport and separation properties were observed, after 28 and 150 h of the experiment. After 216 h of experiment, a 1.28-fold decrease in total flux through the membrane, a 9% decrease in butanol permeability, and a 10% decrease in n-butanol selectivity were found for PHeptMS.
Hybrid Deep Learning Approach for Automatic DoS/DDoS Attacks Detection in Software-Defined Networks
Authors: Elubeyd Hani , Yiltas-Kaplan Derya
Published: March 2023

This paper proposes a hybrid deep learning algorithm for detecting and defending against DoS/DDoS attacks in software-defined networks (SDNs). SDNs are becoming increasingly popular due to their centralized control and flexibility, but this also makes them a target for cyberattacks. Detecting DoS/DDoS attacks in SDNs is a challenging task due to the complex nature of the network traffic. To address this problem, we developed a hybrid deep learning approach that combines three types of deep learning algorithms. Our approach achieved high accuracy rates of 99.81% and 99.88% on two different datasets, as demonstrated through both reference-based analysis and practical experiments. Our work provides a significant contribution to the field of network security, particularly in the area of SDN. The proposed algorithm has the potential to enhance the security of SDNs and prevent DoS/DDoS attacks. This is important because SDNs are becoming increasingly important in today’s network infrastructure, and protecting them from attacks is crucial to maintaining the integrity and availability of network resources. Overall, our study demonstrates the effectiveness of a hybrid deep learning approach for detecting DoS/DDoS attacks in SDNs and provides a promising direction for future research in this area.
Development and Operation of Track Condition Monitoring System Using In-Service Train
Authors: Tsunashima Hitoshi , Ono Hironori , Takata Tetsuya , Ogata Seigo
Published: March 2023

Railway tracks must be managed appropriately because their conditions significantly affect railway safety. Safety is ensured through inspections by track maintenance staff and maintenance based on measurements using dedicated track geometry cars. However, maintaining regional railway tracks using conventional methods is becoming difficult because of their poor financial condition and lack of manpower. Therefore, a track condition diagnostic system is developed, wherein onboard sensing devices are installed on in-service vehicles, and the vibration acceleration of the car body is measured to monitor the condition of the track. In this study, we conduct long-term measurements using the system and evaluate changes in the track conditions over time using car-body vibration data. Filed test results showed that sections with degraded tracks were identified using car-body vibration data. The track degradation trend can be constructed using the results obtained. Furthermore, this study demonstrated that the track maintenance effect could be confirmed. A method for improving train position using the yaw angular velocity is proposed. The track irregularity position can be shown more clearly by monitoring the track condition using position-corrected data using the proposed method. It is also shown that the time-frequency analysis of measured car-body vertical acceleration is effective for evaluating the track condition more clearly.
Reverse Knowledge Distillation with Two Teachers for Industrial Defect Detection
Authors: Pei Mingjing , Liu Ningzhong , Gao Pan , Sun Han
Published: March 2023

Industrial defect detection plays an important role in smart manufacturing and is widely used in various scenarios such as smart inspection and product quality control. Currently, although utilizing a framework for knowledge distillation to identify industrial defects has achieved great progress, it is still a significant challenge task to extract better image features and prevent overfitting for student networks. In this study, a reverse knowledge distillation framework with two teachers is designed. First, for the teacher network, two teachers with different architectures are used to extract the diverse features of the images from multiple models. Second, considering the different contributions of channels and different teacher networks, the attention mechanism and iterative attention feature fusion idea are introduced. Finally, to prevent overfitting, the student network is designed with a network architecture that is inconsistent with the teacher network. Extensive experiments were conducted on Mvtec and BTAD datasets, which are industrial defect detection datasets. On the Mvtec dataset, the average accuracy values of image-level and pixel-level ROC achieved 99.43% and 97.87%, respectively. On the BTAD dataset, the average accuracy values of image-level and pixel-level ROC reached 94% and 98%, respectively. The performance on both datasets is significantly improved, demonstrating the effectiveness of our method.
Wavelet Analysis for Studying Rainfall Variability and Regionalizing Data: An Applied Study of the Moulouya Watershed in Morocco
Authors: Addou Rachid , Hanchane Mohamed , Krakauer Nir Y. , Kessabi Ridouane , Obda Khalid , Souab Majda , Achir Imad Eddine
Published: March 2023

This study analyzes the spatiotemporal variability of precipitation at the scale of the Moulouya watershed in eastern Morocco, which is very vulnerable to the increasing water shortage. For this purpose, we opted for wavelet transformation, a method based on the spectral analysis of data which allows for periodic components of a rainfall time series to change with time. The results obtained from this work show spectral power across five frequency ranges of variability: 1 to 2 years, 2 to 4 years, 4 to 8 years, 8 to 16 years, and 16 to 32 years. The duration of significant power at these frequencies is generally not homogeneous and varies from station to station. The most widespread frequency over the entire study area was found in the 4- to 8-year range. This mode of variability can last up to 27 consecutive years. In most of the basin, this mode of variability was observed around the period between 1990 and 2010. Oscillations at 8 to 16 years in frequency appear in only five series and over different time periods. The 16- to 32-year mode of variability appears in 15 stations and extends over the period from 1983 to 2008. At this level, signal strength is very weak compared to other higher-frequency modes of variability. On the other hand, the mode of variability at the 1- to 2-year frequency range appeared to be continuous in some stations and intermittent in others. This allowed us to regionalize our study basin into two homogeneous clusters that only differ in variability and rainfall regime.
Localized Damage Analysis of Cement Mortar Using X-ray Computed Tomography In Situ Compressive Loading and Digital Volume Correlation
Authors: Li Na , Zhao Yanru , Xing Yongming , He Xiaoyan
Published: March 2023

In this study, X-ray computed tomography (X-ray CT) in situ compressive loading was used, in combination with digital volume correlation (DVC), to analyze the localized damage behavior of cement mortar, the cracking process, microstructural changes, and strain distribution. By using X-ray CT, it was possible to identify the three-dimensional structure and two-dimensional internal morphology of compressed cement mortar. The development of localized damage was significantly influenced by the unhydrated cement. Cracks in the material did not always expand with an increasing load, and the formation of new cracks made old ones become extruded. After conducting a DVC calculation, it was found that the loading procedure contained bias. The bias during loading and the non-homogeneity of the material can cause uneven strain distribution. The maximum principal strains are all tensile, causing tensile damage. To reflect the damage inside the specimen, the gray value of the CT image and the damage index determined by the maximum primary strain were used. A localization factor was introduced to characterize the damage failure process in three dimensions. The internal localization damage of the material occurred earlier than that on the surface, and the damage develops from the inside out, according to the results of the CT image’s gray value, damage index, and localization factor. The damage develops from the inside out, which may be caused by the phenomenon of a compression load or bias pressure. In order to reach a reliable conclusion, more research is required.
Emissions and CO2 Concentration—An Evidence Based Approach
Authors: Dengler Joachim , Reid John
Published: March 2023

The relation between CO2 emissions and atmospheric CO2 concentration has traditionally been treated with more or less complex models with several boxes. Our approach is motivated by the question of how much CO2 must necessarily be absorbed by sinks. This is determined by accepted measurements and the global carbon budget. Observations lead to the model assumption that carbon sinks, similar to oceans or the biosphere, are linearly dependent on CO2 concentration on a decadal scale. In particular, this implies the falsifiable hypothesis that oceanic and biological CO2 buffers have not significantly changed in the past 70 years and are not saturated in the foreseeable future. A statistical model with two parameters is built from the global carbon budget and two testable assumptions. This model explains the relation between CO2 emission and historical CO2 concentration data very well. The model gives estimates of the natural emissions, the pre-industrial CO2 equilibrium concentration levels, the half-life time of an emission pulse, and the future CO2 concentration level from a given emission scenario. It is validated by an ex-post forecast of the last 20 years. The important result is that, with the stated polices emission scenario of the International Energy Agency (IEA), the future CO2 concentrations will not rise above 475 ppm. The model is compared with the carbon module of the Bern model, mapping their complex impulse response functions (IRFs) to a single time variant absorption parameter.
A Gridded Solar Irradiance Ensemble Prediction System Based on WRF-Solar EPS and the Analog Ensemble
Authors: Alessandrini Stefano , Kim Ju-Hye , Jimenez Pedro A. , Dudhia Jimy , Yang Jaemo , Sengupta Manajit
Published: March 2023

The WRF-Solar Ensemble Prediction System (WRF-Solar EPS) and a calibration method, the analog ensemble (AnEn), are used to generate calibrated gridded ensemble forecasts of solar irradiance over the contiguous United States (CONUS). Global horizontal irradiance (GHI) and direct normal irradiance (DNI) retrievals, based on geostationary satellites from the National Solar Radiation Database (NSRDB) are used for both calibrating and verifying the day-ahead GHI and DNI predictions (GDIP). A 10-member ensemble of WRF-Solar EPS is run in a re-forecast mode to generate day-ahead GDIP for three years. The AnEn is used to calibrate GDIP at each grid point independently using the NSRDB as the “ground truth”. Performance evaluations of deterministic and probabilistic attributes are carried out over the whole CONUS. The results demonstrate that using the AnEn calibrated ensemble forecast from WRF-Solar EPS contributes to improving the overall quality of the GHI predictions with respect to an AnEn calibrated system based only on the deterministic run of WRF-Solar. In fact, the calibrated WRF-Solar EPS’s mean exhibits a lower bias and RMSE than the calibrated deterministic WRF-Solar. Moreover, using the ensemble mean and spread as predictors for the AnEn allows a more effective calibration than using variables only from the deterministic runs. Finally, it has been shown that the recently introduced algorithm of correction for rare events is of paramount importance to obtain the lowest values of GHI from the calibrated ensemble (WRF-Solar EPS AnEn), qualitatively consistent with those observed from the NSRDB.
The Variations of Outgoing Longwave Radiation in East Asia and Its Influencing Factors
Authors: Tang Chaoli , Liu Dong , Tian Xiaomin , Zhao Fengmei , Dai Congming
Published: March 2023

Outgoing longwave radiation (OLR) data are one of the key factors in studying the radiation balance of the earth–atmosphere system in East Asia. It is of great significance to explore the influence factors on OLR. This paper processes the data of nearly 19 years, from September 2002 to February 2022, and conducts in-depth research using the exponential smoothing method, empirical orthogonal decomposition (EOF), correlation analysis, and other methods. We found that the spatial distribution of OLR is zonal symmetry and gradually decreases with the increase of latitude. Using EOF analysis, it is found that the total variance contribution of the first four decomposed spatial features exceeds 70%, and the overall change trend of the four-time coefficients in the past 19 years all show a downward trend. OLR is positively correlated with total column water vapor (TCWV), air temperature (AT), and cloud top temperature (CTT), but negatively correlated with cloud top pressure (CTP). OLR has a similar spatial correlation distribution with TCWV and AT, while the spatial correlation between OLR and CTP is opposite to the first two parameters. In most parts of East Asia, the spatial correlation with CTT exceeds 0.8. The change in OLR value is affected by various meteorological parameters. In East Asia, the positive correlation between 30° N and 60° N is significantly affected by TCWV, AT, and CTT; and the negative correlation is more significantly affected by CTP. At 0–25° N, the positive correlation is significantly affected by CTP and CTT, while the negative correlation is significantly affected by TCWV and AT.
Research on PDF Shape Control for Nonlinear Stochastic System Using an Approximate Solution of FPK Equation
Authors: Wang Lingzhi , Zhang Kun , Qian Fucai , Zhang Xiaoli
Published: March 2023

In this paper, we developed a probability density function (PDF) shape control method for non-linear stochastic systems using a hybrid logistic function (HLF) as an approximate PDF of the state variable. First, the functional relationship between the hybrid logistic probability density function and the controller was established based on the Fokker–Planck–Kolmogorov (FPK) equation. Then, the optimal PDF shape controller derivation was completed using the optimization method and the inner product definition of Hilbert space. This approach is suitable for any non-linear stochastic system. To evaluate the effectiveness and performance of the proposed method, we conducted a comparison experiment with the multi-Gaussian closure (MGC) method and the exponential polynomial (EP) method. The experimental results show that, for different types of targeted PDFs (symmetric unimodal, asymmetric unimodal, bimodal, and trimodal shapes), the PDF shape controller obtained using the HLF approach can make the PDF shape of the state variable track the targeted PDF effectively. In particular, when the targeted PDF has an asymmetric or complex trimodal shape, the proposed technique has comparatively better control effects. Compared with the EP method, our method requires a much smaller number of parameters, greatly reducing the computational complexity while achieving the same control effects. This study provides another approach for controlling the PDF shape of state variables in non-linear stochastic systems, which has important research significance.
An IND-CPA Analysis of a Cryptosystem Based on Bivariate Polynomial Reconstruction Problem
Authors: Yusof Siti Nabilah , Kamel Ariffin Muhammad Rezal , Lau Terry Shue Chien , Salim Nur Raidah , Yip Sook-Chin , Yap Timothy Tzen Vun
Published: March 2023

The Polynomial Reconstruction Problem (PRP) was introduced in 1999 as a new hard problem in post-quantum cryptography. Augot and Finiasz were the first to design a cryptographic system based on a univariate PRP, which was published at Eurocrypt 2003 and was broken in 2004. In 2013, a bivariate PRP was proposed. The design is a modified version of Augot and Finiasz’s design. Our strategic method, comprising the modified Berlekamp–Welch algorithm and Coron strategies, allowed us to obtain certain secret parameters of the bivariate PRP. This finding resulted in us concluding that the bivariate PRP is not secure against Indistinguishable Chosen-Plaintext Attack (IND-CPA).