bluuebunny/crossref_metadata_2025 huggingface dataset:
“What’s Past Is Prologue”: Vegetation Model Calibration with and without Future Climate
Authors: Kutschera Ellynne , Kim John B. , Pitts G. Stephen , Drapek Ray
Published: May 2023

Many models are designed to generate future predictions under climate-change scenarios. Such models are typically calibrated for a study area with climate data that represent historical conditions. However, future projections of the model may include outputs for which the model has not been calibrated. Ideally, a climate-change-impacts model would be calibrated for recent conditions and also for possible future climate conditions. We demonstrate an approach, where a vegetation model is subjected to two calibrations: conventionally to the study area and separately to the study area plus additional areas representing analogues of potential future climate. We apply the dynamic vegetation model MC2 to a mountainous ecosystem in the Pacific Northwest, USA. We compare the conventional model calibration with the extra-study-area calibration and future projections. The two calibrations produce different outputs in key ecosystem variables, where some differences vary with time. Some model output trends for net primary productivity and plant functional type are more influenced by climatic input, while for others, the calibration area has greater consequence. Excluding areas representing potential future climate may be an important omission in model calibration, making the inclusion of such areas a decisive consideration in climate-change-impact simulations.
Landslide Susceptibility Mapping Based on Deep Learning Algorithms Using Information Value Analysis Optimization
Authors: Ji Junjie , Zhou Yongzhang , Cheng Qiuming , Jiang Shoujun , Liu Shiting
Published: May 2023

Selecting samples with non-landslide attributes significantly impacts the deep-learning modeling of landslide susceptibility mapping. This study presents a method of information value analysis in order to optimize the selection of negative samples used for machine learning. Recurrent neural network (RNN) has a memory function, so when using an RNN for landslide susceptibility mapping purposes, the input order of the landslide-influencing factors affects the resulting quality of the model. The information value analysis calculates the landslide-influencing factors, determines the input order of data based on the importance of any specific factor in determining the landslide susceptibility, and improves the prediction potential of recurrent neural networks. The simple recurrent unit (SRU), a newly proposed variant of the recurrent neural network, is characterized by possessing a faster processing speed and currently has less application history in landslide susceptibility mapping. This study used recurrent neural networks optimized by information value analysis for landslide susceptibility mapping in Xinhui District, Jiangmen City, Guangdong Province, China. Four models were constructed: the RNN model with optimized negative sample selection, the SRU model with optimized negative sample selection, the RNN model, and the SRU model. The results show that the RNN model with optimized negative sample selection has the best performance in terms of AUC value (0.9280), followed by the SRU model with optimized negative sample selection (0.9057), the RNN model (0.7277), and the SRU model (0.6355). In addition, several objective measures of accuracy (0.8598), recall (0.8302), F1 score (0.8544), Matthews correlation coefficient (0.7206), and the receiver operating characteristic also show that the RNN model performs the best. Therefore, the information value analysis can be used to optimize negative sample selection in landslide sensitivity mapping in order to improve the model’s performance; second, SRU is a weaker method than RNN in terms of model performance.
The Characteristics of Soil C, N and P and Stoichiometric Ratios as Affected by Land-Use in a Karst Area, Southwest China
Authors: Ma Yang , Zhang Chunlai , Yang Hui , Xu Yikai , Chen Yan , Ning Jing
Published: May 2023

Chemometric analysis is often used as an effective indicator of the supply capacity of nutrients in soil–plant systems and their biogeochemical cycles. Understanding ecological stoichiometric characteristics of C, N and P in soils under various land uses is crucial to guide ecological restoration and agricultural cultivation in karst rocky desertification region. However, data on ecological stoichiometry at different land uses in karst areas is limited. This study aimed to evaluate the effects of different land uses on soil ecological stoichiometric ratios and further identify the factors that influence soil ecological stoichiometric ratios. The topsoil from forest, shrub and cultivated land (paddy field and dry land) both in a karst area and non-karst area (as a reference) of Mashan County was sampled to investigate the spatial variance of the ecological stoichiometric characteristics of C, N and P under different land uses. The results show that: (1) Land-use types significantly determined the spatial heterogeneity of soil ecological stoichiometry in karst areas. (2) Soil organic carbon (SOC) was not significantly different between shrubs in the karst area and forests in the non-karst area (p = 0.595), but there were virtual differences in total nitrogen (TN), total phosphorus (TP), C:N, C:P and N:P between shrubs in the karst area and forests in the non-karst area (p < 0.01). (3) The contents of SOC, TN, and C:P, N:P in the study area were all generally higher in forests than those in cultivated land, and the content of TP was lower in forests than cultivated land, while C:N in cultivated land was higher than in shrubs in karst areas, and C:N was higher in forests than in cultivated land in non-karst areas. (4) Available nitrogen (AvN) was the main factor influencing stoichiometry in shrubs in karst areas, while pH, AvN, available phosphorus and elevation were the main factors in forests in non-karst areas, indicating that these factors significantly affect the soil ecological stoichiometric ratio during land-use changes. This study helps to understand the variations in soil ecological stoichiometric ratios under land-use changes. It provides guidance for the sustainable management of revegetation in karst regions in southwest China.
Municipal and Industrial Urban Waste: Legal Aspects of Safe Management
Authors: Ivanova Svetlana , Lisina Natalia
Published: May 2023

Competent management of the production and consumption of waste is the foundation for ensuring a favorable environment in cities and comfortable living conditions for the population. Laws and regulations play a key role in this process since they determine measures aimed at creating conditions for safe waste management, an effective management system in the field of environmental protection from waste pollution. In the cities of many developing countries, including Russia, despite the efforts being made, there is an increase in the volume of municipal solid waste. Solving the problems of waste management has been set as a national task. The article analyzes the current condition of solid waste management systems in developed and developing countries and identifies the features and prospects of waste management, including the one in Russia. It is established that the existing set of organizational, sanitary, and legal measures, and legal regulation of relations and law enforcement practices in the field of solid municipal waste management in many developing countries is still in the forming stage. The positive experiences of countries in implementing sustainable systems of safe waste management and the positions of judicial bodies on controversial issues of waste management in cities can be used as the basis for an environmental policy of safe waste management at all levels of public authority, as well as improving legislation in the field of waste management.
Validation of the NAT Chagas IVD Kit for the Detection and Quantification of Trypanosoma cruzi in Blood Samples of Patients with Chagas Disease
Authors: Moreira Otacilio C. , Fernandes Alice Gomes , Gomes Natalia Lins da Silva , dos Santos Carolina Messias , Jacomasso Thiago , Costa Alexandre Dias Tavares , Nascimento Lucas de O. Rossetti , Hasslocher-Moreno Alejandro Marcel , do Brasil Pedro Emmanuel Alvarenga Americano , Morello Luis Gustavo , Marchini Fabricio Klerynton , Krieger Marco Aurelio , Britto Constança
Published: May 2023

In the absence of validated biomarkers to control the cure of Chagas disease, PCR-based diagnosis is being used as the main tool for an early indication of therapeutic failure. However, since it is considered a technique of complex reproducibility, mainly due to difficulties in establishing accurate controls to guarantee the quality of the reaction, the use of PCR for Chagas disease diagnosis is restricted to specialized centers. In an effort to disseminate the molecular diagnosis of Chagas disease and its applications, new diagnostic kits based on qPCR have been made available in the market in recent years. Here, we show the results of the validation of the NAT Chagas kit (Nucleic Acid Test for Chagas Disease) for the detection and quantification of T. cruzi in blood samples of patients suspected of Chagas disease infection. The kit, composed of a TaqMan duplex reaction targeting the T. cruzi satellite nuclear DNA and an exogenous internal amplification control, presented a reportable range from 104 to 0.5 parasite equivalents/mL and a limit of detection (LOD) of 0.16 parasite equivalents/mL of blood. In addition, the NAT Chagas kit detected T. cruzi belonging to all six discrete typing units (DTUs—TcI to TcVI), similarly to the in-house real-time PCR performed with commercial reagents, which has been selected as the best performance assay in the international consensus for the validation of qPCR for Chagas disease. In the clinical validation presented here, the kit showed 100% sensitivity and 100% specificity when compared to the consensus in-house real-time PCR assay. Thus, the NAT Chagas kit, which is produced entirely in Brazil under the international standards of good manufacturing practices (GMP), appears as an excellent alternative to enable the molecular diagnosis of Chagas disease in public and private diagnostic centers, as well as to facilitate the monitoring of patients under etiological treatment participating in clinical trials.
Effects of Dehydroepiandrosterone (DHEA) Supplementation on Ovarian Cumulus Cells following In Vitro Fertilization (IVF)/Intra-Cytoplasmic Sperm Injection (ICSI) Treatment—A Systematic Review
Authors: Yuan Woon Shu , Abu Muhammad Azrai , Ahmad Mohd Faizal , Elias Marjanu Hikmah , Abdul Karim Abdul Kadir
Published: May 2023

Despite many studies exploring the effects of DHEA supplementation, its application in IVF procedure continues to be a subject of debate owing to the inconsistent findings and the lack of rigorously designed, large-scale, randomized trials. Our review aims to explore the effectiveness of DHEA supplementation in ovarian cumulus cells following IVF/ICSI treatment. We conducted a literature search of Pub-Med, Ovid MEDLINE, and SCOPUS (inception to June 2022) for all relevant articles, including the keywords of “dehydroepiandrosterone/DHEA”, “oocyte”, and “cumulus cells”. From the preliminary search, 69 publications were identified, and following a thorough screening process, seven studies were ultimately incorporated into the final review. Four hundred twenty-four women were enrolled in these studies, with DHEA supplementation being administered exclusively to women exhibiting poor ovarian response/diminished ovarian reserve or belonging to an older age demographic. The intervention in the studies was DHEA 75–90 mg daily for at least 8–12 weeks. The only randomized controlled trial showed no difference in clinical or cumulus cell-related outcomes between the control and treatment groups. However, the remaining six studies (two cohorts, four case-controls) showed significant beneficial effects of DHEA in cumulus cell-related outcomes compared to the group (older age or POR/DOR) without DHEA supplementation. All studies revealed no significant difference in stimulation and pregnancy outcomes. Our review concludes that DHEA supplementation did show beneficial effect on ovarian cumulus cells in improving oocyte quality for women of advanced age or with poor ovarian responders.
Early Endothelial Signaling Transduction in Developing Lung Edema
Authors: Miserocchi Giuseppe
Published: May 2023

The lung promptly responds to edemagenic conditions through functional adaptations that contrast the increase in microvascular filtration. This review presents evidence for early signaling transduction by endothelial lung cells in two experimental animal models of edema, hypoxia exposure, and fluid overload (hydraulic edema). The potential role of specialized sites of the plasma membranes considered mobile signaling platforms, referred to as membrane rafts, that include caveolae and lipid rafts, is presented. The hypothesis is put forward that early changes in the lipid composition of the bilayer of the plasma membrane might trigger the signal transduction process when facing changes in the pericellular microenvironment caused by edema. Evidence is provided that for an increase in the extravascular lung water volume not exceeding 10%, changes in the composition of the plasma membrane of endothelial cells are evoked in response to mechanical stimuli from the interstitial compartment as well as chemical stimuli relating with changes in the concentration of the disassembled portions of structural macromolecules. In hypoxia, thinning of endothelial cells, a decrease in caveolae and AQP-1, and an increase in lipid rafts are observed. The interpretation of this response is that it favors oxygen diffusion and hinder trans-cellular water fluxes. In hydraulic edema, which generates greater capillary water leakages, an increase in cell volume and opposite changes in membrane rafts were observed; further, the remarkable increase in caveolae suggests a potential abluminal–luminal vesicular-dependent fluid reabsorption.
Alternative Enzyme Inhibition Assay for Safety Evaluation of Food Preservatives
Authors: Esimbekova Elena N. , Asanova Anastasia A. , Kratasyuk Valentina A.
Published: May 2023

While food additives are widely used in the modern food industry and generally are important in maintaining the ability to provide food for the increasing world population, the progress occurring in this field is much ahead of the evaluation of their possible consequences for human health. The present study suggests a set of single- and multi-enzyme assay systems for revealing toxic effects of the most widely spread food preservatives, such as sorbic acid (E200), potassium sorbate (E202), and sodium benzoate (E211) at the primary molecular level of their interaction with enzymes. The assay is based on the inhibition of enzyme activity by toxic substances proportional to the amount of the toxicants in the sample. The single-enzyme assay system based on NAD(P)H:FMN oxidoreductase (Red) proved to be most sensitive to the impact of food additives, with the IC50 values being 29, 14, and 0.02 mg/L for sodium benzoate, potassium sorbate, and sorbic acid, respectively, which is considerably lower than their acceptable daily intake (ADI). No reliable change in the degree of inhibition of the enzyme assay systems by food preservatives was observed upon elongating the series of coupled redox reactions. However, the inhibition of activity of the multi-enzyme systems by 50% was found at a preservative concentration below the maximum permissible level for food. The inhibition effect of food preservatives on the activity of butyrylcholinesterase (BChE), lactate dehydrogenase (LDH), and alcohol dehydrogenase (ADH) was either absent or found in the presence of food preservatives at concentrations significantly exceeding their ADI. Among the preservatives under study, sodium benzoate is considered to be the safest in terms of the inhibiting effect on the enzyme activity. The results show that the negative effect of the food preservatives at the molecular level of organization of living things is highly pronounced, while at the organismal level it may not be obvious.
Tensins in Kidney Function and Diseases
Authors: Huang Chien-Wei , Lo Su Hao
Published: May 2023

Tensins are focal adhesion proteins that regulate various biological processes, such as mechanical sensing, cell adhesion, migration, invasion, and proliferation, through their multiple binding activities that transduce critical signals across the plasma membrane. When these molecular interactions and/or mediated signaling are disrupted, cellular activities and tissue functions are compromised, leading to disease development. Here, we focus on the significance of the tensin family in renal function and diseases. The expression pattern of each tensin in the kidney, their roles in chronic kidney diseases, renal cell carcinoma, and their potentials as prognostic markers and/or therapeutic targets are discussed in this review.
A Critical Perspective on the Supplementation of Akkermansia muciniphila: Benefits and Harms
Authors: Chiantera Vito , Laganà Antonio Simone , Basciani Sabrina , Nordio Maurizio , Bizzarri Mariano
Published: May 2023

Akkermansia muciniphila is a mucin-degrading bacterium of the intestinal niche, exerting beneficial effects on the host metabolic profile. Accumulating evidence indicated Akkermansia as a promising therapeutic probiotic against metabolic disorders such as obesity, type 2 diabetes and cardiovascular diseases. However, in specific intestinal microenvironments, its excessive enrichment may be not beneficial. Conditions like inflammatory bowel disease (IBD), Salmonella typhimurium infection or post-antibiotic reconstitution may not benefit from Akkermansia supplementation. Furthermore, using Akkermansia in patients with endocrine and gynecological disorders—such as polycystic ovary syndrome (PCOS) or endometriosis—that have a higher risk of developing IBD, should be critically evaluated. In addition, a cautionary note comes from the neurological field, as the gut microbiota of patients suffering from Parkinson’s disease or multiple sclerosis exhibits a characteristic signature of Akkermansia municiphila abundance. Overall, considering these controversial points, the use of Akkermansia should be evaluated on an individual basis, avoiding risking unexpected effects.
Extraction, HPTLC Analysis and Antiobesity Activity of Jatropha tanjorensis and Fraxinus micrantha on High-Fat Diet Model in Rats
Authors: Srivastava Swati , Virmani Tarun , Haque Md. Rafiul , Alhalmi Abdulsalam , Al Kamaly Omkulthom , Alshawwa Samar Zuhair , Nasr Fahd A.
Published: May 2023

The accumulation of body fat due to an imbalance between calorie intake and energy expenditure is called obesity. Metabolic syndrome increases the risk of heart disease, type 2 diabetes, and stroke. The purpose of this study was to determine the effect of Jatropha tanjorensis (J.T.) and Fraxinus micrantha (F.M.) leaf extracts on high-fat diet-induced obesity in rats. Normal control, high-fat diet (HFD) control, orlistat standard, and test groups were created using male Albino Wistar rats (n = 6 per group) weighing 190 ± 15 g. Except for the control group, all regimens were administered orally and continued for 6 weeks while on HFD. Evaluation criteria included body weight, food intake, blood glucose, lipid profile, oxidative stress, and liver histology. High-Performance Thin Layer Chromatography (HPTLC) analysis was performed using a solvent system (7:3 hexane: ethyl acetate for sitosterol solution and Jatropha tanjorensis extracts and 6:4 hexane: ethyl acetate: 1 drop of acetic acid for esculetin and Fraxinus micrantha extracts). There were no deaths during the 14 days before the acute toxicity test, indicating that aqueous and ethanolic extracts of both J.T. and F.M. did not produce acute toxicity at any dose (5, 50, 300, and 2000 mg/kg). The ethanolic and aqueous extracts of J.T. and F.M. leaves at 200 and 400 mg/kg/orally showed a reduction in weight gain, feed intake, and significant decreases in serum glucose and lipid profile. As compared to inducer HFD animals, co-treatment of aqueous and ethanolic extract of both J.T. and F.M. and orlistat increased the levels of antioxidant enzymes and decreased lipid peroxidation. The liver’s histological findings showed that the sample had some degree of protection. These results indicate that ethanolic samples of J.T. have antidiabetic potential in diabetic rats fed an HFD. The strong antioxidant potential and restoration of serum lipid levels may be related to this. Co-treatment of samples JTE, JTAQ, FME, FMAQ and orlistat resulted in an increase in antioxidant enzymes and reduction in lipid peroxidation as compared to inducer HFD animals. We report, for the first time, on using these leaves to combat obesity.
Expression of Bone Morphogenetic Protein 14 in Liver Disease and Cancer
Authors: Sommer Judith , Thasler Wolfgang E. , Bosserhoff Anja , Hellerbrand Claus
Published: May 2023

The activation of hepatic stellate cells (HSCs) is the key event of hepatic fibrosis. Furthermore, activated HSCs also play an important role in the progression of hepatocellular cancer (HCC). Bone morphogenetic protein 14 (BMP14) is a member of the TGF-β/BMP superfamily. So far, most studies have analyzed BMP14 in the context of bone and cartilage formation and homeostasis. The aim of this study was to assess the expression and function of BMP14 in liver fibrosis and HCC. The BMP14 expression increased during the in vitro activation of primary human HSCs and also in mouse models of liver fibrosis. In human HCC, as well as non-tumorous liver tissues, there was a significant correlation between the expression of BMP14 and alpha-smooth-muscle actin (α-SMA), an established marker for HSC activation. RNAi-mediated BMP14 suppression in activated HSCs resulted in the reduced expression of the transcription factors inhibitor of differentiation 1 (ID1) and ID2, known targets of BMP signaling. Interestingly, α-SMA and collagen expression was also reduced in BMP14-depleted cells, while treatment with recombinant BMP14 induced ID1, ID2, α-SMA and collagen expression. In human HCC cell lines, treatment with recombinant BMP14 induced proliferation, migratory activity and colony formation. In summary, our data indicate activated HSCs as a major cellular source of enhanced BMP14 expression in fibrotic liver disease and HCC, and show that BMP14 exhibits pro-fibrogenic as well as pro-tumorigenic effects. Future analyses will reveal the potential of this soluble growth factor as a therapeutic target or prognostic marker for the progression of fibrosis and HCC in patients with chronic liver disease.
Phytochemical Synthesis of Silver Nanoparticles and Their Antimicrobial Investigation on Cotton and Wool Textiles
Authors: Lite Mihaela Cristina , Constantinescu Roxana , Tănăsescu Elena Cornelia , Kuncser Andrei , Romanițan Cosmin , Mihaiescu Dan Eduard , Lacatusu Ioana , Badea Nicoleta
Published: May 2023

The use of bio-based reagents for silver nanoparticle (AgNP) production has gained much attention among researchers as it has paved the way for environmentally friendly approaches at low cost for synthesizing nanomaterials while maintaining their properties. In this study, Stellaria media aqueous extract was used for silver nanoparticle phyto-synthesis, and the resulting treatment was applied to textile fabrics to test its antimicrobial properties against bacteria and fungi strains. The chromatic effect was also established by determining the L*a*b* parameters. For optimizing the synthesis, different ratios of extract to silver precursor were tested using UV-Vis spectroscopy to observe the SPR-specific band. Moreover, the AgNP dispersions were tested for their antioxidant properties using chemiluminescence and TEAC methods, and the phenolic content was evaluated by the Folin-Ciocâlteu method. For the optimal ratio, values of average size, 50.11 ± 3.25 nm, zeta potential, −27.10 ± 2.16 mV, and polydispersity index, 0.209, were obtained via the DLS technique and zeta potential measurements. AgNPs were further characterized by EDX and XRD techniques to confirm their formation and by microscopic techniques to evaluate their morphology. TEM measurements revealed cvasi-spherical particles with sizes in the range of 10–30 nm, while SEM images confirmed their uniform distribution on the textile fiber surface.
Numerical Study of Ti6Al4V Alloy Tube Heated by Super-Frequency Induction Heating
Authors: Liu Cheng , Han Jingtao , Lu Ruilong , Liu Jiawei , Ma Xiaoyan
Published: May 2023

Ti6Al4V alloys have a narrow processing window, which complicates temperature control, especially during large-scale production. Therefore, a numerical simulation and experimental study on the ultrasonic induction heating process of a Ti6Al4V titanium alloy tube were conducted to obtain stable heating. The electromagnetic and thermal fields in the process of ultrasonic frequency induction heating were calculated. The effects of the current frequency and current value on the thermal and current fields were numerically analyzed. The increase in current frequency enhances the skin and edge effects, but heat permeability was achieved in the super audio frequency range, and the temperature difference between the interior and exterior of the tube was less than 1%. An increase in the applied current value and current frequency caused an increase in the tube’s temperature, but the influence of current was more prominent. Therefore, the influence of stepwise feeding, reciprocating motion, and stepwise feeding superimposed motion on the heating temperature field of the tube blank was evaluated. The coil reciprocating with the roll can maintain the temperature of the tube within the target temperature range during the deformation stage. The simulation results were validated experimentally, which demonstrated good agreement between the results. The numerical simulation method can be used to monitor the temperature distribution of Ti6Al4V alloy tubes during the super-frequency induction heating process. This is an economical and effective tool for predicting the induction heating process of Ti6Al4V alloy tubes. Moreover, online induction heating in the form of reciprocating motion is a feasible strategy for processing Ti6Al4V alloy tubes.
Advances in Computational Techniques for Bio-Inspired Cellular Materials in the Field of Biomechanics: Current Trends and Prospects
Authors: Pais A. , Belinha J. , Alves J.
Published: May 2023

Cellular materials have a wide range of applications, including structural optimization and biomedical applications. Due to their porous topology, which promotes cell adhesion and proliferation, cellular materials are particularly suited for tissue engineering and the development of new structural solutions for biomechanical applications. Furthermore, cellular materials can be effective in adjusting mechanical properties, which is especially important in the design of implants where low stiffness and high strength are required to avoid stress shielding and promote bone growth. The mechanical response of such scaffolds can be improved further by employing functional gradients of the scaffold’s porosity and other approaches, including traditional structural optimization frameworks; modified algorithms; bio-inspired phenomena; and artificial intelligence via machine learning (or deep learning). Multiscale tools are also useful in the topological design of said materials. This paper provides a state-of-the-art review of the aforementioned techniques, aiming to identify current and future trends in orthopedic biomechanics research, specifically implant and scaffold design.
Tackling Modeling and Kinematic Inconsistencies by Fixed Point Iteration-Based Adaptive Control
Authors: Atinga Awudu , Tar József K.
Published: May 2023

The Fixed Point Iteration-based Adaptive Control design methodology is an alternative to the Lyapunov function-based technology. It contains higher-order feedback terms than the standard resolved acceleration rate control. This design approach strictly separates the kinematic and dynamic issues. At first, a purely kinematic prescription is formulated for driving the components of the tracking error to zero. Then an available approximate dynamic model is used to calculate the approximated necessary control forces. Before exerting on the controlled system, these forces are adaptively deformed in order to precisely obtain the prescribed kinematic behavior. The necessary deformation is iteratively found by the use of a contractive map that results in a sequence that converges to the unique fixed point of this map. In the case of underactuated systems, when the relative order of the control task also increases, the highest-order time-derivative depends on the lower-order ones according to the dynamic model of the system. This makes it impossible to realize the arbitrarily constructed kinematic design. In the paper, a resolution to this discrepancy is proposed. The method is demonstrated using two non-linear paradigms, a three-degree-of-freedom robot arm, and a two-degree-of-freedom system, i.e., two coupled non-linear springs. The operation of the method was investigated via simulations made by the use of Julia language and simple sequential programs. It was found that the suggested solution could be considered as a new variant of the fixed point iteration-based model reference adaptive control that is applicable for underactuated systems even if the relative order of the task is increased.
Remaining Useful Life Estimation of Spindle Bearing Based on Bearing Load Calculation and Off-Line Condition Monitoring
Authors: Sova Jiri , Kolar Petr , Burian David , Vozabal Petr
Published: May 2023

Spindles are key components of machine tools. An efficient estimation of the spindle condition and its prognosis can improve production efficiency and quality due to predictive maintenance planning. This paper proposes a method for predicting the remaining useful life (RUL) of machine tool spindle bearings using a combined calculation and experimental approach. The calculation model based on the ISO 281 standard uses monitored real loading conditions caused by the machining process and the machine tool operation. The model enables the updated calculation of the spindle lifetime L10h using real load distribution. Since the operation hours of the spindle are also monitored, the remaining useful life (RUL) of the spindle can be calculated. This RUL value is corrected using a bearing condition assessment based on the effective value of the vibration velocity RMS according to the ISO 20816 standard and measured data from the machine tool control system. The proposed method is tested on two different spindle types featuring three pieces of every type. The experimental results of six spindles are compared and validated with a concurrent blind evaluation conducted by a skilled expert. The validation shows a very good match of the proposed method and the expert opinion. The method combining a calculation of the spindle lifetime using monitored real load distribution and subsequent result correction using vibration signal enables the implementation of a full automated estimation of the spindle RUL.
Enriched Finite Element Method Based on Interpolation Covers for Structural Dynamics Analysis
Authors: Gu Qiyuan , Han Hongju , Zhou Guo , Wu Fei , Ju Zegang , Hu Man , Chen Daliang , Hao Yaodong
Published: May 2023

This work proposes a novel enriched finite element method (E-FEM) for structural dynamics analysis. We developed the enriched 3-node triangular and 4-node tetrahedral displacement-based elements (T-elements). The standard linear shape functions of these T-elements were enriched using interpolation cover functions over each patch of elements. We also introduced and compared different orders of cover functions; higher-order functions obtained higher computational performance. Subsequently, the forced and free vibration analyses were performed on various typical numerical examples. The proposed enriched finite element method generated more precise numerical results and ensured faster convergence than the original linear elements.
Hydrothermal Synthesis and Magnetic Properties of Zn/Mn Oxides Nano Particles
Authors: Kuryliszyn-Kudelska Izabela , Dobrowolski Witold , Arciszewska Monika , Hadžić Branka , Romčević Nebojsa , Romčević Maja , Sibera Daniel , Narkiewicz Urszula
Published: May 2023

The aim of this study was to investigate the magnetic properties of mixed nanocrystalline Zn/manganese oxide compounds synthesized by a hydrothermal method. These compounds are designed as (ZnO)1−n(MnO)n, where index n ranges from 0.05 to 0.60. The results of magnetic measurements, including AC magnetic susceptibility as a function of temperature (up to 160 K) and frequency (from 7 Hz up to 9970 Hz), as well as DC magnetization in magnetic fields up to 9 T and temperature up to 50 K, are reported. We observed various types of magnetic behavior depending on the nominal weight content of MnO. Samples with a low nominal content (up to n = 0.10) of MnO exhibited Curie–Weiss behavior at higher temperatures. For samples with high nominal weight contribution (from n = 0.30 to 0.60), spin-glass-like or/and weak ferromagnetic behavior is observed.
Advances on External Machine Computing Power Focusing on Internal Personal Value: A Case Study on the New Digital Currency
Authors: Qian Yiming , Zhang Hao , Liu Jiahao , Ma Hanran , Li Xinyu , Xi Xi
Published: May 2023

As global inflation escalates and geopolitical conflicts exacerbate, the world’s economy confronts an intensified degree of instability. In this volatile environment, blockchain currencies emerge as a potential bulwark, offering both value preservation and liquidity benefits. However, the conventional “mining” process introduces significant challenges, such as high energy consumption, data security risks, and detachment from the real economy, which potentially facilitate financial capital manipulation. This research endeavors to mitigate these issues, constructing an innovative blockchain cryptocurrency framework that integrates mining and distribution with intelligent big data. It also incorporates social contributions from individuals in domains such as health, knowledge, and ecological conservation. Consequently, the efficiency of cryptocurrency production and distribution correlates with the individual’s societal contribution. The more substantial the contribution, the higher the intrinsic value of the individual and the more efficient the access. Utilizing a comprehensive framework of mathematical modeling, computer numerical simulation, and fuzzy integrated evaluation, we propose a novel endogenous-value blockchain cryptocurrency system. We quantify and optimize variables such as individual intrinsic value, community efficiency, redistribution weights, and total monetary potential. We introduce an innovative method for accumulating time-decaying values such as knowledge contribution and establish an anti-cheating framework. Our results indicate that this pioneering approach can significantly enhance mining efficiency and optimize cryptocurrency distribution. This counters traditional criticisms of blockchain currencies and paves the way for a more sustainable, fair, and efficient model for future blockchain currency systems.
The Poisson–Lindley Distribution: Some Characteristics, with Its Application to SPC
Authors: Al-Nuaami Waleed Ahmed Hassen , Heydari Ali Akbar , Khamnei Hossein Jabbari
Published: May 2023

Statistical process control (SPC) is a significant method to monitor processes and ensure quality. Control charts are the most important tools in SPC. As production processes and production parts become more complex, there is a need to design control charts using more complex distributions. One of the most important control charts to monitor the number of nonconformities in production processes is the C-chart, which uses the Poisson distribution as a quality characteristic distribution. However, to fit the Poisson distribution to the count data, equality of mean and variance should be satisfied. In some cases, such as biological and medical sciences, count data exhibit overdispersion, which means that the variance of data is greater than the mean. In such cases, we can use the Poisson–Lindley distribution instead of the Poisson distribution to model the count data. In this paper, we first discuss some important characteristics of the Poisson–Lindley distribution. Then, we present parametric and bootstrap control charts when the observations follow the Poisson–Lindley distribution and analyze their performance. Finally, we provide a simulated example and a real-world dataset to demonstrate the implementation of control charts. The results show the good performance of the proposed control charts.
Simulation of Light Scattering in Automotive Paints: Role of Particle Size
Authors: Ershov Sergey , Voloboy Alexey , Galaktionov Vladimir
Published: May 2023

Nowadays, computer simulation is being used to develop new materials. Many of them are dispersed media (e.g., paints, and 3D printer inks). Modern automotive paints are of great interest in research works. They contain colorant particles and thin flat metallic or pearlescent flakes distributed in a clear varnish. There are two main approaches to simulation of light scattering in a dispersed media. The first one is based on the continuous medium model. This model is faster but less accurate. The second approach is the simulation of light propagation through an ensemble of paint flakes and particles represented as an explicit geometry. This model correctly calculates light scattering but is rather time-consuming. In our study, we investigated the dependence of the painted surface luminance on particle size and compared both the approaches. We prove that the effect of coarse particles can emerge even in a model where positions of these particles are not correlated; this is different from the mainstream studies which have only concentrated on the role of these correlations. Then, we suggest a semi-analytical model of dependence on particle size. This model not only allows to more accurately simulate visual appearance but also admits intuitive comprehension of how it is affected by various medium parameters. In case of the divergence between the results of LTE and accurate approaches, we propose a simple approximation that allows to improve the accuracy of the LTE results for coarse particles.
A Modified Gradient Method for Distributionally Robust Logistic Regression over the Wasserstein Ball
Authors: Wang Luyun , Zhou Bo
Published: May 2023

In this paper, a modified conjugate gradient method under the forward-backward splitting framework is proposed to further improve the numerical efficiency for solving the distributionally robust Logistic regression model over the Wasserstein ball, which comprises two phases: in the first phase, a conjugate gradient descent step is performed, and in the second phase, an instantaneous optimization problem is formulated and solved with a trade-off minimization of the regularization term, while simultaneously staying in close proximity to the interim point obtained in the first phase. The modified conjugate gradient method is proven to attain the optimal solution of the Wasserstein distributionally robust Logistic regression model with nonsummable steplength at a convergence rate of 1/T. Finally, several numerical experiments to validate the effectiveness of theoretical analysis are conducted, which demonstrate that this method outperforms the off-the-shelf solver and the existing first-order algorithmic frameworks.
Hermite–Hadamard-Type Inequalities for Coordinated Convex Functions Using Fuzzy Integrals
Authors: Amer Latif Muhammad
Published: May 2023

In this paper, some estimates of third and fourth inequalities in Hermite–Hadamard-type inequalities for coordinated convex functions are proved using the non-additivity of the integrals and Fubini’s theorem for fuzzy integrals. That is, the results are obtained in the fuzzy context and using the Lebesgue measure. Several examples are provided on how to evaluate these estimates in order to illustrate the obtained results.
A More Efficient and Practical Modified Nyström Method
Authors: Zhang Wei , Sun Zhe , Liu Jian , Chen Suisheng
Published: May 2023

In this paper, we propose an efficient Nyström method with theoretical and empirical guarantees. In parallel computing environments and for sparse input kernel matrices, our algorithm can have computation efficiency comparable to the conventional Nyström method, theoretically. Additionally, we derive an important theoretical result with a compacter sketching matrix and faster speed, at the cost of some accuracy loss compared to the existing state-of-the-art results. Faster randomized SVD and more efficient adaptive sampling methods are also proposed, which have wide application in many machine-learning and data-mining tasks.
Generalized Universality for Compositions of the Riemann Zeta-Function in Short Intervals
Authors: Laurinčikas Antanas , Macaitienė Renata
Published: May 2023

In the paper, the approximation of analytic functions on compact sets of the strip {s=σ+it∈C∣1/2<σ<1} by shifts F(ζ(s+iu1(τ)),…,ζ(s+iur(τ))), where ζ(s) is the Riemann zeta-function, u1,…,ur are certain differentiable increasing functions, and F is a certain continuous operator in the space of analytic functions, is considered. It is obtained that the set of the above shifts in the interval [T,T+H] with H=o(T), T→∞, has a positive lower density. Additionally, the positivity of a density with a certain exceptional condition is discussed. Examples of considered operators F are given.
Key Factors for a Successful OBM Transformation with DEMATEL–ANP
Authors: Nguyen Tien Son , Chen Jen-Ming , Tseng Shih-Hsien , Lin Li-Fen
Published: May 2023

Production costs and global competition have increased sharply in recent years, forcing manufacturers to upgrade to the original brand manufacturer (OBM) to survive and thrive and capture more profit margins. However, studies that explore key factors that affect the success of such an important transition are lacking. Therefore, this study aims to investigate the key factors that will influence the success of contract manufacturers to upgrade to the OBM on the basis of a decision-making trial and evaluation laboratory with an analytic network process. Our results identify six key factors that exhibit a cause-and-effect relationship among the key criteria. Moreover, organizational innovation will determine the difference between the success and the failure of an OBM transition apart from material and component stability. Our findings can help researchers, policy makers, and practitioners increase their understanding of how to upgrade manufacturers successfully in global value chains.
Correlations in Quantum Network Topologies Created with Cloning
Authors: Shukla Manish Kumar , Huang Minyi , Chakrabarty Indranil , Wu Junde
Published: May 2023

With progress in quantum technologies, the field of quantum networks has emerged as an important area of research. In the last few years, there has been substantial progress in understanding the correlations present in quantum networks. In this article, we study cloning as a prospective method to generate three party quantum networks which will help us to create larger networks. We analyze various quantum network topologies that can be created using cloning transformations. This would be useful in situations wherever the availability of entangled pairs is limited. In addition to that, we focus on the problem of distinguishing networks created by cloning from those that are created by distributing independently generated entangled pairs. We find that there are several states that cannot be distinguished using the Finner inequalities in the standard way. For such states, we propose an extension to the existing Finner inequality for triangle networks by further increasing the number of observers from three to four or six depending on the network topology. This takes into account the additional correlations that exist in the case of cloned networks. In the last part of the article, we use tripartite mutual information to distinguish cloned networks from networks created by independent sources and further use squashed entanglement as a measure to quantify the amount of dependence in the cloned networks.
Neuroevolution of Convolutional Neural Networks for Breast Cancer Diagnosis Using Western Blot Strips
Authors: Llaguno-Roque José-Luis , Barrientos-Martínez Rocio-Erandi , Acosta-Mesa Héctor-Gabriel , Romo-González Tania , Mezura-Montes Efrén
Published: May 2023

Breast cancer has become a global health problem, ranking first in incidences and fifth in mortality in women around the world. In Mexico, the first cause of death in women is breast cancer. This work uses deep learning techniques to discriminate between healthy and breast cancer patients, based on the banding patterns obtained from the Western Blot strip images of the autoantibody response to antigens of the T47D tumor line. The reaction of antibodies to tumor antigens occurs early in the process of tumorigenesis, years before clinical symptoms. One of the main challenges in deep learning is the design of the architecture of the convolutional neural network. Neuroevolution has been used to support this and has produced highly competitive results. It is proposed that neuroevolve convolutional neural networks (CNN) find an optimal architecture to achieve competitive ranking, taking Western Blot images as input. The CNN obtained reached 90.67% accuracy, 90.71% recall, 95.34% specificity, and 90.69% precision in classifying three different classes (healthy, benign breast pathology, and breast cancer).
Total Hip Arthroplasty—Current Challenges
Authors: Bastian Johannes Dominik
Published: May 2023

In 1891, Professor Themistocles Glück in Germany was the first to replace a femoral head in hip joints destroyed by tuberculosis using ivory [...]
Latent Tuberculosis in Psoriasis Patients on Biologic Therapies: Real-World Data from a Care Center in Romania
Authors: Lupea-Chilom Doriana-Sorina , Solovan Caius Silviu , Farcas Simona Sorina , Gogulescu Armand , Andreescu Nicoleta Ioana
Published: May 2023

Background and Objectives: Psoriasis is a chronic and inflammatory condition that has a huge impact on the patient’s quality of life. Biological treatment improved psoriasis therapy, with impressive results seen in the evolution of the disease and the patient’s quality of life. However, the risk of mycobacterium tuberculosis (MTB) infection reactivation is well-known to biological therapy, which raises problems especially in an endemic country. Materials and Methods: In this study, we followed moderate to severe psoriasis patients who had latent tuberculosis infection (LTBI) following treatment with a biological therapy approved in Romania. Results: The patients were evaluated at baseline and then followed-up with Mantoux tests and chest X-rays every year, resulting in 54 patients being diagnosed with LTBI. At the initial evaluation, 30 patients with LTBI were identified, and 24 more were identified during biological therapy. These patients were given prophylactic treatment. Out of the 97 participants in this retrospective study, 25 required association of methotrexate (MTX) alongside biological therapy. We compared the prevalence of positive Mantoux tests in patients with combined therapy with that of patients only on biological treatment, and the results were higher in the combined therapy group. Conclusion: All the patients in the study were vaccinated against tuberculosis (TB) after birth, and none were diagnosed with active tuberculosis (aTB) before or after the start of therapy according to the pulmonologist.