bluuebunny/crossref_metadata_2025 huggingface dataset:
Design Theory and Experimental Research of Ultrasonic Fatigue Test
Authors: Feng Ning , Wang Xin , Guo Jiazheng , Li Qun , Yu Jiangtao , Zhang Xuecheng
Published: August 2022

Ultrasonic fatigue testing is a key technology that is more efficient and energy saving compared to conventional fatigue testing. In order to investigate the behavior of metallic materials at ultra-high frequencies and to verify the validity of ultrasonic fatigue test results, this paper builds a test apparatus that can be used to conduct ultrasonic fatigue tests, and this paper proposes a complete procedure from theoretical analysis to the investigation of test laws for 20 kHz tensile and the compression test. Firstly, the initial sizes of the sample are calculated with an analytical method, then the three-dimensional model is simulated and optimized with finite element software, and the optimum result for the sample size is then obtained according to the sensitivity of the sample size to the effect of frequency. The next step is to analyze the influenced trend of the sample size, including L1, L2, L3, R1 and R2, on the resonant frequency and maximum stress of the sample. According to the optimized results, the sample was processed, and an ultrasonic fatigue test was carried out to ensure the sample fatigue fracture finally occurred. Finally, the S-N curve of the material was plotted based on the data recorded in the test and compared with the conventional fatigue life curve to verify the feasibility of the ultrasonic fatigue test device and test method. The fracture of the sample was observed using an optical microscope, and its macroscopic fracture morphology was analyzed. The fracture morphology of the sample can be divided into three typical zones: the fatigue crack source zone, the extension zone and the transient zone, where the fatigue cracks all originate from on the surface of the sample. The results demonstrate the validity of the ultrasonic fatigue test results and provide new ideas for the design and optimization of ultrasonic fatigue samples and shorter processing times, providing a reference for subsequent ultrasonic fatigue tests on typical materials.
A Novel IBA-DE Hybrid Approach for Modeling Sovereign Credit Ratings
Authors: Jelinek Srđan , Milošević Pavle , Rakićević Aleksandar , Poledica Ana , Petrović Bratislav
Published: August 2022

Nowadays, the sovereign credit rating is not only an index of a country’s economic performance and political stability but also an overall indicator of development and growth, as well as the trust factor that is associated with the country. Due to its importance, the vast amount of available information, and the lack of a closed-form solution, prediction models based on machine learning (ML) and computation intelligence (CI) techniques are being increasingly used to complement traditional financial approaches. In this paper, we aim to introduce a novel ML-CI approach for sovereign credit rating prediction based on a differential evolution (DE) algorithm and interpolative Boolean algebra (IBA). In fact, the proposed approach is based on a pseudo-logical function in the IBA framework derived from the historical data of publicly available indicators using the DE algorithm. Such functions are easily interpreted and enable a subtle gradation among countries. It is shown that the IBA-DE approach outperforms back-propagation neural networks on the observed problem while also providing a deeper insight into each of the indicators used for prediction and its respective influence on the prediction rating on the other.
The Binomial Distribution: Historical Origin and Evolution of Its Problem Situations
Authors: García-García Jaime Israel , Fernández Coronado Nicolás Alonso , Arredondo Elizabeth H. , Imilpán Rivera Isaac Alejandro
Published: August 2022

The increase in available probabilistic information and its usefulness for understanding the world has made it necessary to promote probabilistic literate citizens. For this, the binomial distribution is fundamental as one of the most important distributions for understanding random phenomena and effective decision making, and as a facilitator for the understanding of mathematical and probabilistic notions such as the normal distribution. However, to understand it effectively, it is necessary to consider how it has developed throughout history, that is, the components that gave it the form and meaning that we know today. To address this perspective, we identify the problem situations that gave origin to the binomial distribution, the operational and discursive practices developed to find solutions, and the conflicts that caused a leap in mathematical and probability heuristics, culminating in what is now known as the binomial distribution formula. As a result, we present five historical links to the binomial phenomenon where problem situations of increasing complexity were addressed: a case study using informal means (such as direct counting), the formalization of numerical patterns and constructs related to counting cases, specific probability calculus, the study and modeling of probability in variable or complex phenomena, and the use of the distribution formula as a tool to approaching notions such as the normal distribution. The periods and situations identified correspond to a required step in the design of binomial distribution learning from a historical epistemological perspective and when solving conflicts.
Upper and Lower Bounds for the Spectral Radius of Generalized Reciprocal Distance Matrix of a Graph
Authors: Ma Yuzheng , Gao Yubin , Shao Yanling
Published: August 2022

For a connected graph G on n vertices, recall that the reciprocal distance signless Laplacian matrix of G is defined to be RQ(G)=RT(G)+RD(G), where RD(G) is the reciprocal distance matrix, RT(G)=diag(RT1,RT2,⋯,RTn) and RTi is the reciprocal distance degree of vertex vi. In 2022, generalized reciprocal distance matrix, which is defined by RDα(G)=αRT(G)+(1−α)RD(G),α∈[0,1], was introduced. In this paper, we give some bounds on the spectral radius of RDα(G) and characterize its extremal graph. In addition, we also give the generalized reciprocal distance spectral radius of line graph L(G).
Analytic Valuation Formula for American Strangle Option in the Mean-Reversion Environment
Authors: Jeon Junkee , Kim Geonwoo
Published: August 2022

This paper investigates the American strangle option in a mean-reversion environment. When the underlying asset follows a mean-reverting lognormal process, an analytic pricing formula for an American strangle option is explicitly provided. To present the pricing formula, we consider the partial differential equation (PDE) for American strangle options with two optimal stopping boundaries and use Mellin transform techniques to derive the integral equation representation formula arising from the PDE. A Monte Carlo simulation is used as a benchmark to validate the formula’s accuracy and efficiency. In addition, the numerical examples are provided to demonstrate the effects of the mean-reversion on option prices and the characteristics of options with respect to several significant parameters.
Optimization of Turbulence Model Parameters Using the Global Search Method Combined with Machine Learning
Authors: Barkalov Konstantin , Lebedev Ilya , Usova Marina , Romanova Daria , Ryazanov Daniil , Strijhak Sergei
Published: August 2022

The paper considers the slope flow simulation and the problem of finding the optimal parameter values of this mathematical model. The slope flow is modeled using the finite volume method applied to the Reynolds-averaged Navier–Stokes equations with closure in the form of the k−ωSST turbulence model. The optimal values of the turbulence model coefficients for free surface gravity multiphase flows were found using the global search algorithm. Calibration was performed to increase the similarity of the experimental and calculated velocity profiles. The Root Mean Square Error (RMSE) of derivation between the calculated flow velocity profile and the experimental one is considered as the objective function in the optimization problem. The calibration of the turbulence model coefficients for calculating the free surface flows on test slopes using the multiphase model for interphase tracking has not been performed previously. To solve the multi-extremal optimization problem arising from the search for the minimum of the loss function for the flow velocity profile, we apply a new optimization approach using a Peano curve to reduce the dimensionality of the problem. To speed up the optimization procedure, the objective function was approximated using an artificial neural network. Thus, an interdisciplinary approach was applied which allowed the optimal values of six turbulence model parameters to be found using OpenFOAM and Globalizer software.
Diverse Properties and Approximate Roots for a Novel Kinds of the (p,q)-Cosine and (p,q)-Sine Geometric Polynomials
Authors: Sharma Sunil Kumar , Khan Waseem Ahmad , Ryoo Cheon-Seoung , Duran Ugur
Published: August 2022

Utilizing p,q-numbers and p,q-concepts, in 2016, Duran et al. considered p,q-Genocchi numbers and polynomials, p,q-Bernoulli numbers and polynomials and p,q-Euler polynomials and numbers and provided multifarious formulas and properties for these polynomials. Inspired and motivated by this consideration, many authors have introduced (p,q)-special polynomials and numbers and have described some of their properties and applications. In this paper, using the (p,q)-cosine polynomials and (p,q)-sine polynomials, we consider a novel kinds of (p,q)-extensions of geometric polynomials and acquire several properties and identities by making use of some series manipulation methods. Furthermore, we compute the p,q-integral representations and p,q-derivative operator rules for the new polynomials. Additionally, we determine the movements of the approximate zerosof the two mentioned polynomials in a complex plane, utilizing the Newton method, and we illustrate them using figures.
Cloudformer V2: Set Prior Prediction and Binary Mask Weighted Network for Cloud Detection
Authors: Zhang Zheng , Xu Zhiwei , Liu Chang’an , Tian Qing , Zhou Yongsheng
Published: August 2022

Cloud detection is an essential step in optical remote sensing data processing. With the development of deep learning technology, cloud detection methods have made remarkable progress. Among them, researchers have started to try to introduce Transformer into cloud detection tasks due to its excellent performance in image semantic segmentation tasks. However, the current Transformer-based methods suffer from training difficulty and low detection accuracy of small clouds. To solve these problems, this paper proposes Cloudformer V2 based on the previously proposed Cloudformer. For the training difficulty, Cloudformer V2 uses Set Attention Block to extract intermediate features as Set Prior Prediction to participate in supervision, which enables the model to converge faster. For the detection of small clouds, Cloudformer V2 decodes the features by a multi-scale Transformer decoder, which uses multi-resolution features to improve the modeling accuracy. In addition, a binary mask weighted loss function (BW Loss) is designed to construct weights by counting pixels classified as clouds; thus, guiding the network to focus on features of small clouds and improving the overall detection accuracy. Cloudformer V2 is experimented on the dataset from GF-1 satellite and has excellent performance.
Synthesis, Characterization, and the Antioxidant Activity of Phenolic Acid Chitooligosaccharide Derivatives
Authors: Sun Yan , Ji Xia , Cui Jingmin , Mi Yingqi , Zhang Jingjing , Guo Zhanyong
Published: July 2022

A series of phenolic acid chitooligosaccharide (COS) derivatives synthesized by two mild and green methods were illuminated in this paper. Seven phenolic acids were selected to combine two kinds of COS derivatives: the phenolic acid chitooligosaccharide salt derivatives and the phenolic-acid-acylated chitooligosaccharide derivatives. The structures of the derivatives were characterized by FT-IR and 1H NMR spectra. The antioxidant experiment results in vitro (including DPPH-radical scavenging activity, superoxide-radical scavenging activity, hydroxyl-radical scavenging ability, and reducing power) demonstrated that the derivatives exhibited significantly enhanced antioxidant activity compared to COS. Moreover, the study showed that the phenolic acid chitooligosaccharide salts had stronger antioxidant activity than phenolic-acid-acylated chitooligosaccharide. The cytotoxicity assay of L929 cells in vitro indicated that the derivatives had low cytotoxicity and good biocompatibility. In conclusion, this study provides a possible synthetic method for developing novel and nontoxic antioxidant agents which can be used in the food and cosmetics industry.
Comparison of Modified Johnson–Cook Model and Strain–Compensated Arrhenius Constitutive Model for 5CrNiMoV Steel during Compression around Austenitic Temperature
Authors: Bu Hengyong , Li Qin , Li Shaohong , Li Mengnie
Published: July 2022

Isothermal compression behaviors of 5CrNiMoV steel were studied at temperatures of 870, 800, 750, and 700 °C, with strain rates of 0.001, 0.005, 0.01, 0.05, and 0.1 s−1, the compression temperatures 870 and 800 °C are above Ac3, as well as 750 and 700 °C below Ac3 temperature. The Modified Johnson–Cook (MJC) model and the Strain–Compensated Arrhenius (SCA) model were employed to demonstrate the relationship between the flow stress and the compression parameters. The correlation coefficient (R) and average absolute relative error (AARE) between the calculational and experimental flow stress were used to evaluate the accuracy of the two models. The results show that the effect of dynamic softening on flow stress is much more significant at higher temperatures and lower strain rates, while this effect is not obvious when the strain rate exceeds 0.005 s−1 with the temperature below Ac3. The MJC model has a good accuracy close to the reference conditions (0.001 s−1 and 700 °C), and it is suitable to predict the plastic behavior when the flow stress is lower than 200 Mpa. The unbiased AARE values were 6.82 and 5.71 for MJC model and SCA model, respectively, which implied the SCA model has a higher accuracy than the MJC model. The SCA model was believed to be capable of being used to illustrate the thermomechanical behavior of 5CrNiMoV tool steel in a wide range of plastic deformation conditions.
An In Situ Study to Understand Community Structure of Estuarine Microbes on the Plastisphere
Authors: Sosa Ana , Chen Feng
Published: August 2022

Microplastics are defined as pieces of plastic that are smaller than 5 mm and they are now considered one of the most abundant ubiquitous plastic debris. Microbial communities that settle on particles can potentially lead to the transport of pathogenic and harmful bloom-forming species, as well as have an impact on global biogeochemical cycles. However, little is known about the acclimation of microbes to different types of microplastic in the estuarine environment. In this study, 16S ribosomal RNA sequencing and analysis was performed on biofilm samples from three different types of microplastic beads placed in Baltimore’s Inner Harbor. Microbial communities associated with microplastic particles and glass bead control were monitored throughout the 28-day incubation time. A significant taxonomic composition dissimilarity was observed between particles-associated and free-living communities, suggesting a unique microbial adaptation to these biofilms. The polymer types, however, did not significantly influence the microbial community composition. Some families with interesting potential metabolism were identified in the plastisphere samples, including Cyanobacteria, Planctomycetes, Desulfobacteriota, and Firmicutes, leading into speculation of their ecological responses and metabolic roles in the estuarine environment. It is crucial to understand the microorganisms that inhabit plastic debris in estuarine systems and their potential metabolic capacity and how it may differ from its marine counterparts in order to assess their roles in global nutrient cycles and if they have ability to be utilized in bioremediation for plastic pollution.
A Novel Approach of Antiviral Drugs Targeting Viral Genomes
Authors: Hoang Phuong Thi , Luong Quynh Xuan Thi , Ayun Ramadhani Qurrota , Lee Yongjun , Vo Thuy Thi Bich , Kim Taehyun , Lee Sukchan
Published: August 2022

Outbreaks of viral diseases, which cause morbidity and mortality in animals and humans, are increasing annually worldwide. Vaccines, antiviral drugs, and antibody therapeutics are the most effective tools for combating viral infection. The ongoing coronavirus disease 2019 pandemic, in particular, raises an urgent need for the development of rapid and broad-spectrum therapeutics. Current antiviral drugs and antiviral antibodies, which are mostly specific at protein levels, have encountered difficulties because the rapid evolution of mutant viral strains resulted in drug resistance. Therefore, degrading viral genomes is considered a novel approach for developing antiviral drugs. The current article highlights all potent candidates that exhibit antiviral activity by digesting viral genomes such as RNases, RNA interference, interferon-stimulated genes 20, and CRISPR/Cas systems. Besides that, we introduce a potential single-chain variable fragment (scFv) that presents antiviral activity against various DNA and RNA viruses due to its unique nucleic acid hydrolyzing characteristic, promoting it as a promising candidate for broad-spectrum antiviral therapeutics.
Recent Advances in Nanostructured Inorganic Hole-Transporting Materials for Perovskite Solar Cells
Authors: Huang Dingyan , Xiang Huimin , Ran Ran , Wang Wei , Zhou Wei , Shao Zongping
Published: July 2022

Organic-inorganic halide perovskite solar cells (PSCs) have received particular attention in the last decade because of the high-power conversion efficiencies (PCEs), facile fabrication route and low cost. However, one of the most crucial obstacles to hindering the commercialization of PSCs is the instability issue, which is mainly caused by the inferior quality of the perovskite films and the poor tolerance of organic hole-transporting layer (HTL) against heat and moisture. Inorganic HTL materials are regarded as promising alternatives to replace organic counterparts for stable PSCs due to the high chemical stability, wide band gap, high light transmittance and low cost. In particular, nanostructure construction is reported to be an effective strategy to boost the hole transfer capability of inorganic HTLs and then enhance the PCEs of PSCs. Herein, the recent advances in the design and fabrication of nanostructured inorganic materials as HTLs for PSCs are reviewed by highlighting the superiority of nanostructured inorganic HTLs over organic counterparts in terms of moisture and heat tolerance, hole transfer capability and light transmittance. Furthermore, several strategies to boost the performance of inorganic HTLs are proposed, including fabrication route design, functional/selectively doping, morphology control, nanocomposite construction, etc. Finally, the challenges and future research directions about nanostructured inorganic HTL-based PSCs are provided and discussed. This review presents helpful guidelines for the design and fabrication of high-efficiency and durable inorganic HTL-based PSCs.
SV40 miR-S1 and Cellular miR-1266 Sequester Each Other from Their Targets, Enhancing Telomerase Activity and Viral Replication
Authors: Takahashi Tetsuyuki , Ichikawa Hirona , Okayama Yukiko , Seki Manami , Hijikata Takao
Published: July 2022

Virus-encoded microRNAs (miRNAs) target viral and host mRNAs to repress protein production from viral and host genes, and regulate viral persistence, cell transformation, and evasion of the immune system. The present study demonstrated that simian virus 40 (SV40)-encoded miRNA miR-S1 targets a cellular miRNA miR-1266 to derepress their respective target proteins, namely, T antigens (Tags) and telomerase reverse transcriptase (TERT). An in silico search for cellular miRNAs to interact with viral miR-S1 yielded nine potential miRNAs, five of which, including miR-1266, were found to interact with miR-S1 in dual-luciferase tests employing reporter plasmids containing the miRNA sequences with miR-S1. Intracellular bindings of miR-1266 to miR-S1 were also verified by the pull-down assay. These miRNAs were recruited into the Ago2-associated RNA-induced silencing complex. Intracellular coexpression of miR-S1 with miR-1266 abrogated the downregulation of TERT and decrease in telomerase activity induced by miR-1266. These effects of miR-S1 were also observed in miR-1266-expressing A549 cells infected with SV40. Moreover, the infected cells contained more Tag, replicated more viral DNA, and released more viral particles than control A549 cells infected with SV40, indicating that miR-S1-induced Tag downregulation was antagonized by miR-1266. Collectively, the present results revealed an interplay of viral and cellular miRNAs to sequester each other from their respective targets. This is a novel mechanism for viruses to manipulate the expression of viral and cellular proteins, contributing to not only viral lytic and latent replication but also cell transformation observed in viral infectious diseases including oncogenesis.
Cerebral Folate Deficiency Syndrome: Early Diagnosis, Intervention and Treatment Strategies
Authors: Ramaekers Vincent Th. , Quadros Edward V.
Published: July 2022

Cerebral folate deficiency syndrome (CFDS) is defined as any neuropsychiatric or developmental disorder characterized by decreased CSF folate levels in the presence of normal folate status outside the nervous system. The specific clinical profile appears to be largely determined by the presence or absence of intrauterine folate deficiency as well as postnatal age at which cerebral folate deficiency occurs. The primary cause of CFDS is identified as the presence of serum folate receptor-alpha (FRα) autoantibodies impairing folate transport across the choroid plexus to the brain whereas, in a minority of cases, mitochondrial disorders, inborn errors of metabolism and loss of function mutations of the FRα (FOLR1) gene are identified. Early recognition and diagnosis of CFDS and prompt intervention is important to improve prognosis with successful outcomes. In this article we focus on FRα autoimmunity and its different age-dependent clinical syndromes, the diagnostic criteria, and treatments to be considered, including prevention strategies in this at-risk population.
Dietary Essential Amino Acid Intake Is Associated with High Muscle Strength in Korean Older Adults
Authors: Im Jihyun , Park Hyoungsu , Park Kyong
Published: July 2022

The relationship between daily dietary intake of an individual or all essential amino acids (EAAs) and muscle strength in older adults is still inadequately characterized. This population-based cross-sectional study included 5971 participants aged ≥65 years from the 2014–2019 Korea National Health and Nutrition Examination Survey. Dietary information was derived from the 24 h recall data. Total essential amino acid score (EAAS) was calculated with an intake that satisfied the recommended nutrient intake (RNI) in each essential amino acid (EAA). The mean handgrip strength was estimated from triplicate measurements obtained using the dominant hand, and high muscle strength was defined as handgrip strength ≥28 kg for men and ≥18 kg for women. Multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression models. After multivariable adjustment, we found that a high total EAAS was associated with high muscle strength in Korean older adults (OR: 1.38, 95% CI: 1.07–1.79). High muscle strength was significantly enhanced with increased total EAA intake from animal sources (OR: 1.27, 95% CI: 1.02–1.58), but there was no significant association with total EAA intake from non-animal sources. EAA intake and high muscle strength are associated based on a positive dose-response relationship in which high muscle strength is further increased when the overall EAA intake meets the RNI. Thus, Korean older adults should ensure an adequate intake of all EAAs from various food sources (especially animal sources) to meet the RNI as a prerequisite for achieving high muscle strength.
Preterm Infants on Early Solid Foods and Vitamin D Status in the First Year of Life—A Secondary Outcome Analysis of a Randomized Controlled Trial
Authors: Thanhaeuser Margarita , Eibensteiner Fabian , Kornsteiner-Krenn Margit , Gsoellpointner Melanie , Brandstetter Sophia , Koeller Ursula , Huf Wolfgang , Huber-Dangl Mercedes , Binder Christoph , Thajer Alexandra , Jilma Bernd , Berger Angelika , Haiden Nadja
Published: July 2022

Preterm birth places infants at high risk for mineral and micronutrient deficiencies important for bone health. The aim of this study was to examine whether two timepoints for the introduction of solid foods in preterm infants have an impact on vitamin D status in the first year of life. This is a secondary outcome analysis of a prospective, randomized trial on very low birth weight (VLBW) infants, randomized to an early (10–12th week corrected age) or a late (16–18th week corrected age) complementary-feeding group. Vitamin D status was assessed by blood samples taken at 6 weeks, 6, and 12 months corrected age. In total, 177 infants were randomized (early group: n = 89, late group: n = 88). There was a tendency toward lower levels of serum 25-OH-vitamin D in the early group throughout the first year of life (p = not significant (n.s.)); no differences were detected in the other parameters. At 6 months corrected age, infants of the early group had a significantly higher incidence of vitamin D deficiency. The timepoint of the introduction of solid foods had no impact on the serum 25-OH-vitamin D levels and other parameters important for bone health but showed a tendency toward lower levels in the early-feeding group.
A Methodological Approach to Water Concentration to Investigate the Presence of SARS-CoV-2 RNA in Surface Freshwaters
Authors: Tesauro Marina , Terraneo Mara , Consonni Michela , Fappani Clara , Colzani Daniela , Stevanin Caterina , Amendola Antonella , Masseroni Daniele , Tanzi Elisabetta
Published: July 2022

During the COVID-19 public health emergency, an increasing number of studies reported the occurrence of SARS-CoV-2 in wastewaters worldwide, but little is known about the presence of the virus in surface freshwaters. The aim of the current study was to develop and validate an appropriate and scalable methodological approach for the concentration and detection of SARS-CoV-2 from surface freshwater samples, collected within the Milan rural network subjected to flood spillways activity. Overall, both surface water and distilled water samples spiked with inactivated SARS-CoV-2 were used to validate the concentration method for pathogens determination. Two pre-filtration systems, filter paper and Sartolab® P20 (Sartorius, Germany) and two concentration methods, two-phase (PEG-dextran method) separation and tangential flow ultrafiltration (UF), were compared. The effects of pre-filtration and concentration on viral nucleic acid recovery were assessed through real time RT-PCR targeting SARS-CoV-2 and the internal viral control PMMoV (Pepper Mild Mottle Virus). Our results showed that UF is more sensitive than the PEG-dextran method in viral acid nucleic recovery from surface water samples. Better results were obtained pre-filtering samples with Sartolab® P20 and extracting the nucleic acids with undiluted silica, rather than diluted as required by the standard protocol. The proposed method will be used for the monitoring of surface waters in the Milan area.
Within-Household Transmission and Bacterial Diversity of Staphylococcus pseudintermedius
Authors: Wegener Alice , Duim Birgitta , van der Graaf-van Bloois Linda , Zomer Aldert L. , Visser Caroline E. , Spaninks Mirlin , Timmerman Arjen J. , Wagenaar Jaap A. , Broens Els M.
Published: July 2022

Staphylococcus pseudintermedius can be transmitted between dogs and their owners and can cause opportunistic infections in humans. Whole genome sequencing was applied to identify the relatedness between isolates from human infections and isolates from dogs in the same households. Genome SNP diversity and distribution of plasmids and antimicrobial resistance genes identified related and unrelated isolates in both households. Our study shows that within-host bacterial diversity is present in S. pseudintermedius, demonstrating that multiple isolates from each host should preferably be sequenced to study transmission dynamics.
Characterization of Lymphocyte Subsets in Lymph Node and Spleen Sections in Fatal Pediatric Malaria
Authors: Mandala Wilson L. , Ward Steve , Taylor Terrie E. , Wassmer Samuel C.
Published: July 2022

Secondary lymphoid tissues play a major role in the human immune response to P. falciparum infection. Previous studies have shown that acute falciparum malaria is associated with marked perturbations of the cellular immune system characterized by lowered frequency and absolute number of circulating T cell subsets. A temporary relocation of T cells, possibly by infiltration to secondary lymphoid tissue, or their permanent loss through apoptosis, are two proposed explanations for this observation. We conducted the present study to determine the phenotype of lymphocyte subsets that accumulate in the lymph node and spleen during acute stages of falciparum malaria infection in Malawian children, and to test the hypothesis that lymphocytes are relocated to lymphoid tissues during acute infection. We stained tissue sections from children who had died of the two common clinical forms of severe malaria in Malawi, namely severe malarial anemia (SMA, n = 1) and cerebral malaria (CM, n = 3), and used tissue sections from pediatric patients who had died of non-malaria sepsis (n = 2) as controls. Both lymph node and spleen tissue (red pulp) sections from CM patients had higher percentages of T cells (CD4+ and CD8+) compared to the SMA patient. In the latter, we observed a higher percentage of CD20+ B cells in the lymph nodes compared to CM patients, whereas the opposite was observed in the spleen. Both lymph node and spleen sections from CM patients had increased percentages of CD69+ and CD45RO+ cells compared to tissue sections from the SMA patient. These results support the hypothesis that the relocation of lymphocytes to spleen and lymph node may contribute to the pan-lymphopenia observed in acute CM.
New Strategies for Volume Control in Patients with Diabetes Mellitus, a Narrative Review
Authors: Gérard Alexandre O. , Laurain Audrey , Sicard Antoine , Merino Diane , Pathak Atul , Drici Milou-Daniel , Favre Guillaume , Esnault Vincent L. M.
Published: July 2022

Sodium is reabsorbed all along the renal tubules. The positive impacts of sodium-glucose cotransporter-2 inhibitors (SGLT2i), angiotensin receptor neprilysin inhibitor (ARNI) and mineralocorticoid receptor antagonists (MRA) on hard renal and/or cardiac endpoints calls for the role of diuretics in nephroprotection and cardioprotection in patients with diabetes mellitus to be reviewed. Here, we review: (a) the mechanisms of action of the available natriuretics; (b) the physiological adaptations to chronic loop diuretic usage that lead to increased sodium reabsorption in the proximal and distal convoluted tubules; (c) the physiology of sodium retention in patients with diabetes mellitus; and (d) the mechanisms of aldosterone breakthrough. We show the rationale for combined diuretics to target not only the loop of Henle, but also the proximal and distal convoluted tubules. Indeed, higher residual proteinuria in patients treated with renin-angiotensin-aldosterone system (RAAS) blockers portends poorer renal and cardiovascular outcomes. Diuretics are known to optimize the reduction of proteinuria, in addition to RAAS blockers, but may favor aldosterone breakthrough in the absence of MRA. The aim of our study is to support a combined diuretics strategy to improve the management of patients with diabetes mellitus and chronic kidney disease or heart failure.
Multifunctional and Smart Wound Dressings—A Review on Recent Research Advancements in Skin Regenerative Medicine
Authors: Rani Raju Nithya , Silina Ekaterina , Stupin Victor , Manturova Natalia , Chidambaram Saravana Babu , Achar Raghu Ram
Published: July 2022

The healing of wounds is a dynamic function that necessitates coordination among multiple cell types and an optimal extracellular milieu. Much of the research focused on finding new techniques to improve and manage dermal injuries, chronic injuries, burn injuries, and sepsis, which are frequent medical concerns. A new research strategy involves developing multifunctional dressings to aid innate healing and combat numerous issues that trouble incompletely healed injuries, such as extreme inflammation, ischemic damage, scarring, and wound infection. Natural origin-based compounds offer distinct characteristics, such as excellent biocompatibility, cost-effectiveness, and low toxicity. Researchers have developed biopolymer-based wound dressings with drugs, biomacromolecules, and cells that are cytocompatible, hemostatic, initiate skin rejuvenation and rapid healing, and possess anti-inflammatory and antimicrobial activity. The main goal would be to mimic characteristics of fetal tissue regeneration in the adult healing phase, including complete hair and glandular restoration without delay or scarring. Emerging treatments based on biomaterials, nanoparticles, and biomimetic proteases have the keys to improving wound care and will be a vital addition to the therapeutic toolkit for slow-healing wounds. This study focuses on recent discoveries of several dressings that have undergone extensive pre-clinical development or are now undergoing fundamental research.
Performance Enhancement of DWDM Optical Fiber Communication Systems Based on Amplification Techniques
Authors: Zdravecký Norbert , Ovseník Ľuboš , Oravec Jakub , Lapčák Maroš
Published: August 2022

This paper deals with improving transmission properties of a DWDM system based on amplification techniques. Parameter values change due to a change in the type of optical amplifier or an adjustment of the parameters of the optical amplifiers. Optimization summarizes the knowledge of the systems and software that are used. These assumptions are verified by a set of simulations and the obtained numerical values are compared with the values given in the relevant articles. The proposed design, which uses a larger number of EDFA amplifiers over long distances, has been found to perform better than single amplifier systems. In addition, the proposed solution is better in transmission characteristics than other approaches with a similar purpose.
Tutorial on Development of 3D Vasculature Digital Phantoms for Evaluation of Photoacoustic Image Reconstruction Algorithms
Authors: Ranjbaran Seyed Mohsen , Khan Azam , Manwar Rayyan , Avanaki Kamran
Published: August 2022

A synthetic phantom model is typically utilized to evaluate the initial performance of a photoacoustic image reconstruction algorithm. The characteristics of the phantom model (structural, optical, and acoustic) are required to be very similar to those of the biological tissue. Typically, generic two-dimensional shapes are used as imaging targets to calibrate reconstruction algorithms. However, these structures are not representative of complex biological tissue, and therefore the artifacts that exist in reconstructed images of biological tissue vasculature are ignored. Real data from 3D MRI/CT volumes can be extrapolated to create high-quality phantom models; however, these sometimes involve complicated pre-processing and mostly are challenging, due to the inaccessibility of these datasets or the requirement for approval to utilize the data. Therefore, it is necessary to develop a 3D tissue-mimicking phantom model consisting of different compartments with characteristics that can be easily modified. In this tutorial, we present an optimized development process of a generic 3D complex digital vasculature phantom model in Blender. The proposed workflow is such that an accurate and easily editable digital phantom can be developed. Other workflows for creating the same phantom will take much longer to set up and require more time to edit. We have made a few examples of editable 3D phantom models, which are publicly available to test and modify.
Utilizing Pyrolysis–Gas Chromatography/Mass Spectrometry for Monitoring and Analytical Characterization of Microplastics in Polychaete Worms
Authors: Anuar Sabiqah Tuan , Altarawnah Raad Shaher , Mohd Ali Ahmad Ammarluddin , Lee Bai Qin , Khalik Wan Mohd Afiq Wan Mohd , Yusof Ku Mohd Kalkausar Ku , Ibrahim Yusof Shuaib
Published: July 2022

Microplastics (the term for plastics at sizes of <5 mm) might be introduced into the environment from domestic or agricultural activities or from the breakdown of plastic pieces, particles, and debris that are bigger in size. Their presence in the aquatic environment has caused accumulation problems, as microplastics do not easily break down and can be digested by some aquatic organisms. This study was conducted to screen and monitor the level of microplastic pollution in polychaete worms using pyrolysis–gas chromatography/mass spectrometry (Py-GC/MS). The study was conducted in Setiu Wetlands, Malaysia from November 2015 to January 2017 at five-month intervals and covered all monsoon changes. Results from physical and visual analyses indicated that a total number of 371.4 ± 20.2 items/g microplastics were retrieved from polychaete for all seasons, in which, the majority comprised transparent microplastics (49.87%), followed by brown with 138.3 ± 13.6 items/g (37.24%), 21.7 ± 1.9 items/g for blue (5.84%), and 12.9 ± 1.1 items/g for black (3.47%), while the remaining were green and grey-red colors. Statistical analysis using Kruskal–Wallis showed insignificant differences (p > 0.05) between the sampling station and period for the presence of a microplastics amount. Most of the microplastics were found in fiber form (81.5%), whereas the remaining comprised fragment (18.31%) and film (0.19%) forms. Further analysis with Py-GC/MS under a selective ion monitoring mode indicated that pyrolytic products and fragment ions for a variety of polymers, such as polyvinyl chloride, polypropylene, polyethylene, polyethylene terephthalate, polyamide, and polymethylmethacrylate, were detected. This study provides an insightful application of Py-GC/MS techniques for microplastics monitoring, especially when dealing with analytical amounts of samples.
Membrane–Fresnel Diffractive Lenses with High-Optical Quality and High-Thermal Stability
Authors: Liu Xin , Li Min , Li Bincheng , Fan Bin
Published: July 2022

The membrane–Fresnel diffractive lens (M-FDL) has great potential in the field of high-resolution and lightweight imaging in orbit. However, the M-FDL with high-optical quality and high-thermal stability cannot be fabricated to a standard by the existing processing methods. In this paper, we propose a method for fabricating an M-FDL composed of three steps: the improved repeated spin-coating of the polyimide (PI) membrane, the secondary mucosal method of silica-framed membrane mirror, and the high-precision fabrication of a multi-level microstructure on a flexible, ultrathin membrane substrate. The results show that the root mean square (RMS) of the wave-front error for M-FDL obtained by the above method is 1/28λ (F# = 8.7 at 632.8 nm) with an 80 mm clear aperture, the average diffraction efficiency is more than 70%, the silica-framed membrane mirror possesses approximately 40 times the overall thermal stability of the traditional metal-framed mirror, and the weight is less than 40 g. The measurement results indicate that the M-FDL has high-optical quality and high-thermal stability and can satisfy the imaging requirements.
A Hybrid Recommendation Approach for Medical Services That Incorporates Knowledge Graphs
Authors: Ma Chao , An Qi , Yang Zhenguo , Zhang Hongguo , Qu Jiaxing
Published: August 2022

At present, there are a large number of growing medical applications in the application market. It is difficult for users to find satisfactory medical services conveniently and efficiently. The classical collaborative filtering algorithm has some problems, such as cold start, unsatisfactory recommendation results, and so on. This paper proposes a hybrid medical service recommendation approach based on knowledge graph to solve the above problems. This approach introduces the open knowledge graph and establishes the semantic link relationship between the mobile application and the knowledge graph entity. It not only enhances the semantic feature of single application for improving the accuracy of recommendation results, but also realizes the in-depth analysis of the semantic relationship among multiple application entities in the knowledge graph through the TransHR model which can alleviate the cold start problem. Then we design a hybrid recommendation algorithm based on multi-dimensional similarity fusion. This algorithm uses the entropy method to organically integrate the calculation results of multi-dimensional semantic similarity, such as feature vector similarity, entity relation similarity, and user rating similarity. It is convenient and efficient to recommend satisfactory medical application services to target users. Finally, we test and analyze the accuracy and effectiveness of our proposed approach by experiment.
Amelioration of Organic Carbon and Physical Health of Structurally Disturbed Soil through Microbe–Manure Amalgam
Authors: Jiang Wenjia , Gondal Aqarab Husnain , Shahzad Haroon , Iqbal Muhammad , Bustamante Mary Amelia Cardenas , Yapias Rafael Julian Malpartida , Marcos Ruggerths Neil De La Cruz , Areche Franklin Ore , Victorio Jimmy Pablo Echevarría , Cotrina Cabello Guillermo Gomer , Nieto Dante Daniel Cruz
Published: August 2022

Less precipitation, high temperature, and minimal natural vegetation are characteristic of regions having an arid climate. The harsh environment massively destructs the soil structure of that area by burning soil organic carbon, leading to deteriorated soil nutritional quality, creating a significant threat to agricultural production and food security. Direct application of organic wastes not only substitutes lost organic carbon but also restores soil structure and fertility. This study was conducted to assess the impact of organic amendments, i.e., farm manure (FM), poultry manure (PM), molasses (MO), and Exo-Poly Saccharides (EPS) producing rhizobacterial strains i.e., M2, M19, M22 amalgams as treatments. To assess the impact of treatments on soil carbon and structure restoration to hold more water and nutrients, a 42-day incubation experiment using a completely randomized design (CRD) under the two-factor factorial arrangement was conducted. Macro aggregation (0.25 to >1 mm), carbon retention in macro aggregates, active carbon (dissolved organic carbon, a mineral-associated organic carbon, microbial biomass carbon), total organic carbon, the carbon mineralization activities, and water retention capacities were observed to be highest in soils that were treated with (FM + M2, FM + M22, PM + M19, and MO + M19). Finally, we conclude that organics mineralization by microbial actions releases organic glues that not only impart particle aggregation but also conserve organics as aggregate entrapped carbon. Amalgamated application of microbe–manure combinations directly impacts soil structure and organic carbon contents, but in an indirect scenario, it improves the fertility and productivity of the soil. Therefore, it is strongly recommended to use organic manures and microbes in combination to restore structurally degraded lands.
Driving Mode Selection through SSVEP-Based BCI and Energy Consumption Analysis
Authors: Wu Juai , Wang Zhenyu , Xu Tianheng , Sun Chengyang
Published: July 2022

Background: The brain–computer interface (BCI) is a highly cross-discipline technology and its successful application in various domains has received increasing attention. However, the BCI-enabled automobile industry is has been comparatively less investigated. In particular, there are currently no studies focusing on brain-controlled driving mode selection. Specifically, different driving modes indicate different driving styles which can be selected according to the road condition or the preference of individual drivers. Methods: In this paper, a steady-state visual-evoked potential (SSVEP)-based driving mode selection system is proposed. Upon this system, drivers can select the intended driving modes by only gazing at the corresponding SSVEP stimuli. A novel EEG processing algorithm named inter-trial distance minimization analysis (ITDMA) is proposed to enhance SSVEP detection. Both offline and real-time experiments were carried out to validate the effectiveness of the proposed system. Conclusion: The results show that a high selection accuracy of up to 92.3% can be realized, although this depends on the specific choice of flickering duration, the number of EEG channels, and the number of training signals. Additionally, energy consumption is investigated in terms of which the proposed brain-controlled system considerably differs from a traditional driving mode selection system, and the main reason is shown to be the existence of a detection error.
Best of Both Worlds: Detecting Application Layer Attacks through 802.11 and Non-802.11 Features
Authors: Chatzoglou Efstratios , Kambourakis Georgios , Smiliotopoulos Christos , Kolias Constantinos
Published: July 2022

Intrusion detection in wireless and, more specifically, Wi-Fi networks is lately increasingly under the spotlight of the research community. However, the literature currently lacks a comprehensive assessment of the potential to detect application layer attacks based on both 802.11 and non-802.11 network protocol features. The investigation of this capacity is of paramount importance since Wi-Fi domains are often used as a stepping stone by threat actors for unleashing an ample variety of application layer assaults. In this setting, by exploiting the contemporary AWID3 benchmark dataset along with both shallow and deep learning machine learning techniques, this work attempts to provide concrete answers to a dyad of principal matters. First, what is the competence of 802.11-specific and non-802.11 features when used separately and in tandem in detecting application layer attacks, say, website spoofing? Second, which network protocol features are the most informative to the machine learning model for detecting application layer attacks? Without relying on any optimization or dimensionality reduction technique, our experiments, indicatively exploiting an engineered feature, demonstrate a detection performance up to 96.7% in terms of the Area under the ROC Curve (AUC) metric.