bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of a multi-epitope vaccine against brucellosis fused to IgG-fc by an immunoinformatics approach
Authors: Wu Aodi , Wang Yueli , Ali Adnan , Xu Zhenyu , Zhang Dongsheng , Zhumanov Kairat , Sheng Jinliang , Yi Jihai
Published: October 2023

Introduction

Brucella, a type of intracellular Gram-negative bacterium, has unique features and acts as a zoonotic pathogen. It can lead to abortion and infertility in animals. Eliminating brucellosis becomes very challenging once it spreads among both humans and animals, putting a heavy burden on livestock and people worldwide. Given the increasing spread of brucellosis, it is crucial to develop improved vaccines for susceptible animals to reduce the disease’s impact.

Methods

In this study, we effectively used an immunoinformatics approach with advanced computer software to carefully identify and analyze important antigenic parts of Brucella abortus. Subsequently, we skillfully designed chimeric peptides to enhance the vaccine’s strength and effectiveness. We used computer programs to find four important parts of the Brucella bacteria that our immune system recognizes. Then, we carefully looked for eight parts that are recognized by a type of white blood cell called cytotoxic T cells, six parts recognized by T helper cells, and four parts recognized by B cells. We connected these parts together using a special link, creating a strong new vaccine. To make the vaccine even better, we added some extra parts called molecular adjuvants. These included something called human β-defensins 3 (hBD-3) that we found in a database, and another part that helps the immune system called PADRE. We attached these extra parts to the beginning of the vaccine. In a new and clever way, we made the vaccine even stronger by attaching a part from a mouse’s immune system to the end of it. This created a new kind of vaccine called MEV-Fc. We used advanced computer methods to study how well the MEV-Fc vaccine interacts with certain receptors in the body (TLR-2 and TLR-4).

Results

In the end, Immunosimulation predictions showed that the MEV-Fc vaccine can make the immune system respond strongly, both in terms of cells and antibodies.

Discussion

In summary, our results provide novel insights for the development of Brucella vaccines. Although further laboratory experiments are required to assess its protective effect.
Case report: Fundic gland polyps caused by long-term omeprazole use in a Maltese dog
Authors: Lee Haemin , Kim Sanggu , Lee Dohee , Chae Yeon , Yun Taesik , Yang Mhan-Pyo , Kang Byeong-Teck , Kim Soochong , Kim Hakhyun
Published: October 2023

Long-term use of proton-pump inhibitors can induce fundic gland polyps in the human stomach. However, this phenomenon has not been described in the veterinary literature. A 5-year-old intact female Maltese dog was referred to our hospital with chronic intermittent vomiting. The dog had been administered omeprazole (0.7–1.0 mg/kg PO q24 h) for the management of hydrocephalus for over 4 years; the omeprazole dose was increased to 10 mg/kg PO q24 h 8 months prior to presentation at referring hospital. Abdominal ultrasonography revealed marked thickening of the gastric wall with multi-lobulated, thickened folds. Subsequent endoscopy revealed marked polypoid lesions, and histological examination of the biopsy samples was consistent with the fundic gland polyps associated with proton-pump inhibitor use in humans. The lesions resolved after cessation of omeprazole, as assessed by ultrasonography. This report describes a case of fundic gland polyps following the long-term administration of omeprazole in a dog.
Ground Fire Legacy Effects on Water-Dynamics of Volcanic Tropical Soils
Authors: Olivares-Martinez Luis D. , Gomez-Tagle Alberto , Mataix-Solera Jorge
Published: October 2023

The forest floor is a critical component in maintaining the life cycles of forest ecosystems. It normally includes organic soil horizons, known as duff and litter, which are prone to be rapidly consumed after flaming and smoldering fires. This work aims to understand the legacy effects of surface and ground fires on the infiltration capacity of a volcanic forest soil. We studied five sites with fires recorded in the last 20 years. All of them are located in pine-oak forests of the volcanic mountain region in central Mexico with a temperate climate and Andic soil properties. Tension-infiltration tests were carried out to determine hydraulic conductivity and the number of active macropores. After each test, cores were taken to evaluate in a laboratory setting, where soil water repellency at different moisture concentrations and the integrative dynamic repellency index were determined. Field-saturated hydraulic conductivity was moderately high in all sites, with mean values of 13 and 42 mm·h−1 for burned and control plots, respectively. A non-linear relationship was found between recurrence and type of fires with the concentration of active pores and several dynamic water repellency parameters. This work confirmed the presence of latent combustion in these temperate neotropical forests. The changes in soil water repellency and hydraulic conductivity detected do not necessarily imply an exceeded soil infiltration capacity. However, many of the fires in this region are associated with increasing agricultural activities, so further studies are needed to determine if higher fire frequencies could exceed the resilience capacity of the soils triggering land degradation.
Shelved–Retrieved Method for Weakly Balanced Constrained Clustering Problems
Authors: Hou Xinxiang , Qiu Andong , Yang Lu , Yang Zhouwang
Published: October 2023

Clustering problems are prevalent in areas such as transport and partitioning. Owing to the demand for centralized storage and limited resources, a complex variant of this problem has emerged, also referred to as the weakly balanced constrained clustering (WBCC) problem. Clusters must satisfy constraints regarding cluster weights and connectivity. However, existing methods fail to guarantee cluster connectivity in diverse scenarios, thereby resulting in additional transportation costs. In response to the aforementioned limitations, this study introduces a shelved–retrieved method. This method embeds adjacent relationships during power diagram construction to ensure cluster connectivity. Using the shelved–retrieved method, connected clusters are generated and iteratively adjusted to determine the optimal solutions. Further, experiments are conducted on three synthetic datasets, each with three objective functions, and the results are compared to those obtained using other techniques. Our method successfully generates clusters that satisfy the constraints imposed by the WBCC problem and consistently outperforms other techniques in terms of the evaluation measures.
Remote Sensing of Snow Parameters: A Sensitivity Study of Retrieval Performance Based on Hyperspectral versus Multispectral Data
Authors: Pachniak Elliot , Li Wei , Tanikawa Tomonori , Gatebe Charles , Stamnes Knut
Published: October 2023

Snow parameters have traditionally been retrieved using discontinuous, multi-band sensors; however, continuous hyperspectral sensors are now being developed as an alternative. In this paper, we investigate the performance of various sensor configurations using machine learning neural networks trained on a simulated dataset. Our results show improvements in the accuracy of retrievals of snow grain size and impurity concentration for continuous hyperspectral channel configurations. Retrieval accuracy of snow albedo was found to be similar for all channel configurations.
Simulating Flight Crew Workload Settings to Mitigate Fatigue Risk in Flight Operations
Authors: Bartulović Dajana , Steiner Sanja , Fakleš Dario , Mavrin Jeličić Martina
Published: October 2023

In flight operations, the workload settings refer to the shift work, duty time, flight time, number of sectors, rest periods, time of day, duty patterns, number of time-zone transitions, number of consecutive duty days, and changes in the schedule. Workload factors, together with the biological mechanisms (the circadian rhythm, homeostatic sleep pressure, sleep inertia), can lead to the appearance of fatigue. Fatigue affects numerous tasks, such as performing inaccurate flight procedures, missing radio calls, missing or being too slow to pick up system warnings, forgetting or performing routine tasks inaccurately, and others. The focus of this paper is to determine which flight crew workload settings elements impact the appearance of fatigue. The process of collecting data regarding flight crew workload settings and fatigue is conducted on a sample of four airline pilots using an electronic CRD system of standardized chronometric cognitive tests and subjective self-assessment scales. Causal modeling tools of the IBM SPSS Statistics were used to detect correlations among flight crew workload settings, indicators of the subjective perception of fatigue, and measured fatigue indicators. In the final step, a set of simulations was created using simulation tools of the IBM SPSS Statistics to show how modifications of flight crew workload settings, such as modified duty time, number of days off, and others, can impact the level of fatigue. The obtained results can help improve the future planning of flight crew workload set-up and mitigate or prevent the appearance of fatigue in flight operations.
Co-Inoculation with Bradyrhizobium and Humic Substances Combined with Herbaspirillum seropedicae Promotes Soybean Vegetative Growth and Nodulation
Authors: Canellas Luciano Pasqualoto , Silva Rakiely Martins , Barbosa Lucas José da Silva , Sales Fernando Soares , Ribeiro Rafael Chaves , Mota Gabriela Petroceli , Olivares Fábio Lopes
Published: October 2023

The effect of humic substances (HSs) in combination with or without plant-growth-promoting bacteria on soybean vegetative growth and root nodulation was examined in this study. Seeds were inoculated with Bradyrhizobium japonicum SEMIA 5079 in the presence of HSs from leonardite and Herbaspirillum seropedicae HRC54. Additional HSs and H. seropedicae application at the substrate surface was conducted at the V3 stage. The experiment was carried out in a greenhouse using pots filled with a top layer of an Oxisol soil, and plants were harvested at the R1 stage. The HS and H. seropedicae treatments significantly promoted plant shoot and root growth. The number and weight of soybean nodules were higher in the treated plants when compared to a control. The plant nodulation process was affected by the treatments that included activities of malate dehydrogenase (MDH), nitrate reductase (NR) and plasma membrane H+-ATPase (MHA). At low concentrations, the HSs and H. seropedicae increased the nodule quantity, size and weight, favoring plant growth. Combining humic substances and plant-growth-promoting bacteria (PGPB) could be a promising approach to promoting soybean nodulation and increasing crop production.
A Molecular Identification and Resistance Evaluation of the Blast Resistance Genes in Japonica Rice in Northern China
Authors: Ma Zuobin , Wang Lili , Zhang Liangkun , Gu Shuang , Wang Hui , Sui Guomin , Zheng Wenjing
Published: October 2023

Rice blast is a fungal disease that seriously threatens rice production. It is of great significance to identify blast resistance genes and clarify their functions in rice varieties. In this study, 11 rice blast resistance genes in 80 Japonica rice varieties in northern China were investigated, including their resistance to rice blast. The results demonstrated that Pita, Ptr, Pib, Pik, and Piks were most widely found, accounting for 48.8, 48.8, 41.3, 20.0, and 18.8% of the tested varieties, respectively. Pi5-G2 at the Pi5 locus and Pik-G5 and Pik-G8 at the Pik locus were also commonly found, and these alleles accounted for 30.0, 10.0, and 3.8% of all the tested varieties, respectively. Pizt was identified only in two cultivars, and alleles Pi2, Pi9, and Pigm at the Piz locus on chromosome 6 were not detected. We found that Pi5 and Pita were relatively conserved, but the alleles of Pik were abundant. Besides Pik, Pikm, and Piks, we also found 10 new haplotypes, and Pikp and Pikh were not found in the japonica rice varieties in northern China. Among the tested varieties, 5 did not carry any of the tested genes, 30 carried only one blast resistance gene, 27 carried two, 14 carried three, and 4 carried four. The resistance of varieties carrying three or four resistance genes was better than those carrying none of the resistance genes or only one or two. There were no significant differences in the resistance characteristics among varieties from different provinces. Our study provided a reference for the molecular breeding of rice blast resistance.
Effects of Dietary Acacia nilotica Fruit, Zinc Oxide Nanoparticles and Their Combination on Productive Performance, Zinc Retention, and Blood Biochemistry of Rabbits
Authors: Abdel-Wareth Ahmed A. A. , El-Sayed Hazem G. M. , Abdel-Warith Abdel-Wahab A. , Younis Elsayed M. , Hassan Hamdi A. , Afifi Afifi S. , El-Chaghaby Ghadir A. , Rashad Sayed , Amer Shimaa A. , Lohakare Jayant
Published: October 2023

This study aims to examine the effects of supplementing male rabbit diets with nanoparticles of zinc oxide (Nano-ZnO) and Acacia nilotica fruit powder (ANFP) on production sustainability under hot climatic conditions. Eighty Californian male rabbits aged 40 days old (average body weight 738.5 ± 11 g) were divided into four treatment groups and administered one of the following diets: control diet, Nano-ZnO (50 mg/kg), ANFP (5 g/kg), or a combination of Nano-ZnO (50 mg/kg) and ANFP (5 g/kg) for a period of 60 days. Each of the 20 rabbits used in a treatment was regarded as a replicate. The results showed that adding Nano-ZnO and ANFP individually or in combination to rabbits’ diets improved (p < 0.05) growth performance in comparison to control. In addition, zinc contents in serum or the testis tissues in the Nano-ZnO- and ANFP-treated rabbits were significantly greater (p < 0.05) than those in the control group. In addition, serum levels of creatinine, alanine aminotransferase, and aspartate aminotransferase were decreased (p < 0.05) by supplementation of Nano-ZnO, ANFP, or their combination. Carcass criteria did not differ among the treatments. Overall, the findings of the present study indicate that rabbits fed diets containing Nano-ZnO and ANFP, as well as their combination, showed improvements in growth performance, kidney and liver functions, as well as zinc retention in tissues under hot climatic conditions. The combination of Nano-ZnO and ANFP exhibited the best performance in the rabbits. More research on the synergistic effects of Nano-ZnO and ANFP in the sustainable production of rabbit meat is required.
Fatty Acid Profile and Lipid Quality Indexes of the Meat and Backfat from Porkers Supplemented with EM Bokashi Probiotic
Authors: Goluch Zuzanna , Rybarczyk Artur , Poławska Ewa , Haraf Gabriela
Published: October 2023

The study aimed to assess the effect of supplementation of pig diet with the Bokashi probiotic on the fatty acid profile of longissimus lumborum (LL) muscles and backfat. The research involved 120 hybrid pigs deriving from Naïma sows and P-76 boars. The experimental group’s pigs received probiotics in their feed (containing Saccharomyces cerevisiae, Lactobacillus casei, and Lactobacillus plantarum). To analyze the fatty acid profile in intramuscular fat (IMF) of LL and backfat, 24 pig carcasses from the control group and 26 from the probiotic-supplemented group were randomly selected. Probiotic supplementation increased the Atherogenic Index, reduced the proportion of C20:4, and increased C12:0 and C18:2 n-6 in IMF LL, without affecting ΣSFA, ΣMUFA, and ΣPUFA. In backfat, probiotic supplementation decreased C18:1 and C18:2 n-6 proportion and increased C18:3 n-3, C20:3 n-6, and C20:4 n-6. These changes resulted in significantly higher ΣMUFA, ΣPUFA, PUFA Σn-3/Σn-6, and lower Saturation Index (SI). From a consumer health and technological point of view, probiotic supplementation improved the lipid profile of backfat to a greater extent than LL muscle. Bokashi, at a dose of 3 g/kg of feed in the last stage of pig production, had no significant effect on the fatty acid profile of the meat.
Impact of Ocean Acidification on the Gut Histopathology and Intestinal Microflora of Exopalaemon carinicauda
Authors: Wang Chao , Han Wanyu , Cheng Weitao , Liu Dexue , Wang Weili , Yan Binlun , Gao Huan , Hu Guangwei
Published: October 2023

Marine crustaceans are severely threatened by environmental factors such as ocean acidification, but, despite the latter’s negative impact on growth, molting, and immunity, its effects on intestinal microflora remain poorly understood. This work studied the gut morphology and intestinal microflora of Exopalaemon carinicauda, grown in seawater of different pH levels: 8.1 (control group), 7.4 (AC74 group), and 7.0 (AC70 group). Ocean acidification was found to cause intestinal damage, while significantly altering the microflora’s composition. However, the α-diversity did not differ significantly between the groups. At the phylum level, the relative abundance of Proteobacteria decreased in the acidification groups, while at the genus level, the relative abundance of Sphingomonas decreased. Babeliales was a prominent discriminative biomarker in the AC74 group, with Actinobacteriota, Micrococcales, Beijerinckiaceae, Methylobacterium, and Flavobacteriales being the main ones in the AC70 group. The function prediction results also indicated an enrichment of pathways related to metabolism for the acidification groups. At the same time, those related to xenobiotics’ biodegradation and metabolism were inhibited in AC74 but enhanced in AC70. This is the first study examining the impact of ocean acidification on the intestinal microflora of crustaceans. The results are expected to provide a better understanding of the interactions between shrimp and their microflora in response to environmental stressors.
Effects of Extraction Process Factors on the Composition and Antioxidant Activity of Blackthorn (Prunus spinosa L.) Fruit Extracts
Authors: Drăghici-Popa Ana-Maria , Boscornea Aurelian Cristian , Brezoiu Ana-Maria , Tomas Ștefan Theodor , Pârvulescu Oana Cristina , Stan Raluca
Published: October 2023

This study aimed at establishing the optimal conditions for the classic extraction of phenolic compounds from Prunus spinosa L. fruits. The effects of different parameters, i.e., ethanol concentration in the extraction solvent (mixture of ethanol and water), operation temperature, and extraction time, on process responses were evaluated. Total phenolic content (TPC), total anthocyanin content (TAC), antioxidant capacity (AC), and contents of protocatechuic acid (PA), caffeic acid (CA), vanillic acid (VA), rutin hydrate (RH), and quercetin (Q) of fruit extracts were selected as process responses. A synergistic effect of obtaining high values of TPC, TAC, AC, PA, and VA was achieved for the extraction in 50% ethanol at 60 °C for 30 min. At a higher level of process temperature, the extraction of protocatechuic acid and vanillic acid was enhanced, but the flavonoids, i.e., rutin hydrate and quercetin, were degraded. A lower temperature should be used to obtain a higher amount of flavonoids. TPC, TAC, AC, and phenolic acid contents (PA, CA, and VA) in the extract samples obtained at an ethanol concentration of 50–100%, a temperature of 30–60 °C, and an extraction time of 30 min were strongly directly correlated.
Anti-Wrinkling Effect of 3,4,5-tri-O-caffeoylquinic Acid from the Roots of Nymphoides peltata through MAPK/AP-1, NF-κB, and Nrf2 Signaling in UVB-Irradiated HaCaT Cells
Authors: Kim Tae-Young , Park No-June , Jo Beom-Geun , Lee Bum Soo , Keem Min-Ji , Kwon Taek-Hwan , Kim Ki Hyun , Kim Su-Nam , Yang Min Hye
Published: October 2023

Nymphoides peltata has been widely used pharmacologically in traditional Chinese medicine to treat heat strangury and polyuria. The aim of this study was to isolate the bioactive components from N. peltata and evaluate their potential use as antioxidant and anti-wrinkle agents. Phytochemical investigation of the methanolic extract of N. peltata roots led to the isolation of 15 compounds (1–15), which were structurally determined as α-spinasterol (1), 3-O-β-D-glucopyranosyl-oleanolic acid 28-O-β-D-glucuronopyranoside (2), 4-hydroxybenzoic acid (3), protocatechuic acid (4), vanillic acid (5), p-coumaric acid (6), caffeic acid (7), ferulic acid (8), neochlorogenic acid (neo-CQA) (9), chlorogenic acid (CQA) (10), cryptochlorogenic acid (crypto-CQA) (11), isochlorogenic acid B (3,4-DCQA) (12), isochlorogenic acid A (3,5-DCQA) (13), isochlorogenic acid C (4,5-DCQA) (14), and 3,4,5-tri-O-caffeoylquinic acid (TCQA) (15). Of these 15 compounds, compound 2 was a new oleanane saponin, the chemical structure of which was characterized by 1D and 2D nuclear magnetic resonance (NMR) spectroscopic data and high-resolution electrospray ionization mass spectrometry (HRESIMS), as well as chemical reaction. Biological evaluation of the isolated compounds revealed that 3,4,5-tri-O-caffeoylquinic acid (TCQA) significantly improved Nrf2 levels in an Nrf2–ARE reporter HaCaT cell screening assay. TCQA was found to potently inhibit the Nrf2/HO-1 pathway and to possess strong anti-wrinkle activity by modulating the MAPK/NF-κB/AP-1 signaling pathway and thus inhibiting MMP-1 synthesis in HaCaT cells exposed to UVB. Our results suggest that TCQA isolated from N. peltata might be useful for developing effective antioxidant and anti-wrinkle agents.
Recurrent Embedded Topic Model
Authors: Vargas Carlos , Ponce Hiram
Published: October 2023

In this paper we propose the Recurrent Embedded Topic Model (RETM) which is a modification of the Embedded Topic Modelling (ETM) by reusing the Continuous Bag of Words (CBOW) that the model had implemented and applying it to a recurrent neural network (LSTM), using the order of the words of the text, in the CBOW space as the recurrency of the LSTM, while calculating the topic–document distribution of the model. This approach is novel because the ETM and Latent Dirichlet Allocation (LDA) do not use the order of the words while calculating the topic proportions for each text, making worse predictions in the end. The RETM is a topic-modelling technique that vastly improves (by more than 15 times in train data and between 10% and 90% better based on test dataset values for perplexity) the quality of the topics that were calculated for the datasets used in this paper. This model is explained in detail throughout the paper and presents results on different use cases on how the model performs against ETM and LDA. The RETM can be used with better accuracy for any topic model-related problem.
Air-Polishing Powders’ Effect on the Color of CAD/CAM Restorative Materials
Authors: Turunç Oğuzman Rana , Yüzbaşıoğlu Emir
Published: October 2023

Air-polishing powders are used to remove stains from the enamel and various restorative materials, but their effect on the discoloration of CAD/CAM blocks remains scarce. Therefore, this study investigated the effect of various air-polishing powders on the color changes in different CAD/CAM blocks to predict the esthetic outcomes. Specimens were prepared from CAD/CAM blocks (Vita Mark II, Paradigm MZ100, Lava Ultimate, Cerasmart, Vita Enamic) and divided into five groups (n = 10) according to the air-polishing powder: sodium bicarbonate; aluminum trihydroxide; calcium carbonate; glycine; and erythritol. Color parameters were measured with a spectrophotometer before and after air-polishing. The color difference was calculated with the ΔE00 formula. Data were statistically evaluated with one-way ANOVA, Tukey, and two-way ANOVA tests (α = 0.05). The CAD/CAM block type and the air-polishing powder type significantly influenced the ΔE00 value, whereas their interactions did not affect it significantly. Calcium carbonate and aluminum trihydroxide significantly increased the ΔE00 values of Lava Ultimate and Cerasmart. Although none of the groups exceeded the acceptability threshold (ΔE00 = 1.8), most exceeded the perceptibility threshold (ΔE00 = 0.8). Consequently, dentists should avoid air-polishing or should repolish with care, depending on restorative material knowledge, to maintain color stability when uncertain about the material encountered clinically.
Curved-Line Path-Following Control of Fixed-Wing Unmanned Aerial Vehicles Using a Robust Disturbance-Estimator-Based Predictive Control Approach
Authors: Qi Weiwei , Tong Mingbo , Wang Qi , Song Wei , Ying Hunan
Published: October 2023

In this research, the design of a robust curved-line path-following control system for fixed-wing unmanned aerial vehicles (FWUAVs) affected by uncertainties on the latitude plane is studied. This is undertaken to enhance closed-loop system robustness under unknown uncertainties and derive the control surface deflection angle directly used to control FWUAVs, which has rarely been studied in previous works. The system is formed through the mass center position control (MCPC) and yaw angle control (YAC) subsystems. In the MCPC, the desired yaw angle, which is treated as the reference signal for the YAC subsystem, is calculated analytically using path-following errors, current flow angles, and the yaw angle. In the YAC, a disturbance estimator is designed to estimate uncertainties such as nonlinearities, couplings, time variations, model parameter perturbations, and unmodeled dynamics. Predictive functional controllers are designed to target nominal systems in the absence of uncertainties, such that the estimations of the uncertainties can be incorporated through feedback for closed-loop system robustness enhancement. The simulation results show that higher path-following precision and stronger robustness for the FWUAVs based on the proposed approach can be achieved using only rough model parameters compared with the conventional nonlinear dynamic inversion, which requires detailed model information.
Performance Analysis of Interval Type-2 Fuzzy X¯ and R Control Charts
Authors: Almeida Túlio S. , dos Santos Mendes Amanda , Rocha Rizol Paloma M. S. , Machado Marcela A. G.
Published: October 2023

Statistical process control (SPC) is one of the most powerful techniques for improving quality, as it is able to detect special causes of problems in processes, products and services with a remarkable degree of accuracy. Among SPC tools, X¯ and R control charts are widely employed in process monitoring. However, scenarios involving vague, imprecise and even subjective data require a type-2 fuzzy set approach. Thus, X¯ and R control charts should be coupled with interval type-2 triangular fuzzy numbers (IT2TFN) in order to add further information to traditional control charts. This paper proposes a performance analysis of IT2TFN and X¯ and R control charts by means of average run length (ARL), standard deviation of the run length (SDRL) and RL percentile. Computer simulations were carried out considering 10,000 runs to obtain ARL, SDRL and the 5th, 25th, 50th, 75th and 95th RL percentiles. Simulation results reveal that the proposed control charts increased fault detection capability (speed of response) and slightly reduced the number of false alarms in processes under control. Moreover, it was observed that, in addition to superior performance, IT2TFN X¯-R control charts proved to be more robust and flexible when compared to traditional control charts.
Calibration of Model Parameters for Soda Saline Soil-Subsoiling Component Interaction Based on DEM
Authors: Liu Min , Wang Jingli , Feng Weizhi , Jing Haiyang , Wang Yang , Guo Yingjie , Xu Tianyue
Published: October 2023

To apply the discrete element method (DEM) to simulate the interaction process between soda saline–alkali soil and subsoiling component in Northeast China, establishing the soda saline–alkali soil particle model and selecting more accurate simulation parameters are important. In this paper, we studied the soda saline–alkali soil of the Songnen Plain in China. First, we studied the geometric shape of soda saline–alkali soil particles and proposed a modeling method for single soil particles based on the multisphere combination method. Considering the cohesion of soda saline–alkali soil particles, the Hertz–Mindlin with JKR (JKR) model was used as the contact model between soil particles. Then, the calibration method was used to obtain simulation parameters of soils that are difficult to obtain experimentally. We conducted soil angle of repose (AoR) tests, the Plackett–Burman (PB) tests, and steepest ascent (SA) tests in turn to perform a sensitivity analysis for microscopic contact parameters and select the parameters that have a significant effect on the response value (static AoR), i.e., soil surface energy, soil–soil static friction coefficient, and soil–soil rolling friction coefficient. Then, the optimal combination of simulation parameters was obtained via the Box–Behnken (BB) tests, using ANOVA to optimize the multiple regression equation. Finally, the optimal parameter combination was verified by the AoR test and the direct shear (DS) test. The results showed that the parameters had good adaptability for the AoR test. However, the simulation results of the DS test were significantly different from the experimental values. Therefore, the contact model needs to be further modified by adding Bonding bonds between soil particles based on the JKR model and further correcting for Rayleigh time step, shear modulus, and surface energy. By comparing the simulation and the experimental results, it was found that the simulation results obtained from both the DS test and AoR test had relatively small errors relative to physical tests, the two trends are the same, and the values are similar. This verified the feasibility and effectiveness of the soda saline–alkali soil particle modeling method and parameter selection proposed in this paper.
Study on the Nonlinear Permeability Mechanism and Pore Structure Characteristics of Deep Confined Aquifers
Authors: Peng Shilong , Li Zhijun , Xu Yuhao , Cao Guangyong
Published: October 2023

The study of deep soil mechanics is the basis of deep shaft construction. Exploring the nonlinear permeability mechanism of deep confined aquifers in depth is the prerequisite and foundation for carrying out calculations of the hydrophobic consolidation settlement of thick alluviums and preventing and controlling deep-well-damage disasters. Against the background of shaft damage caused by hydrophobic consolidation settlement of the bottom aquifer of thick alluviums, a joint HPLTC-HPPNP (high-pressure long-term consolidation and high-pore-pressure nonlinear permeability) test was carried out on the bottom aquifer of thick alluviums based on the ETAS test system. This paper studied the evolution law of the permeability coefficient (kv) of bottom aquifers under different heads of confined water, confining pressures (σr), permeability hydraulic gradients (i) and loading–unloading methods. The internal pore structure characteristics of clayey sand were obtained by using low-field nuclear magnetic resonance (NMR) technology to explore the clayey sand’s nonlinear permeability micro-mechanism. The research results showed that the bottom aquifer seepage volume (ΔQi) under high stress is affected by the head pressure difference and pore water dissipation, and kv decreases with an increasing σr according to the power function relationship. The influence of the hydraulic gradient (i) on kv is significantly influenced by σr. When σr  < 4 MPa, kv decreased with an increasing i, and when σr  > 4 MPa, kv increased with an increasing i first, then decreased, before then tending to be stable. Under different stress states, the T2 spectrum of clayey sand showed a bispectrum peak type, and the adsorbed water content decreased linearly with an increasing σr, while the capillary water decreased according to the power function. The content of capillary water in the permeable pores plays a key role in the permeability of clayey sand, and it has a power function relationship with σr. The research results of this paper provide a good experimental method for the study of deep soil permeability characteristics and parameter determination, provide a theoretical basis for deep alluvial hydrophobic consolidation and settlement, and further make up for the shortcomings of existing deep soil mechanics in permeability characteristics.
Adaptive Smoothing for Visual Improvement of Image Quality via the p(x)-Laplacian Operator Effects of the p(x)-Laplacian Smoothing Operator on Digital Image Restoration: Contribution to an Adaptive Control Criterion
Authors: Henry Jean-Luc , Nagau Jimmy , Velin Jean , Moussa Issa-Paul
Published: October 2023

This article concerns the improvement of digital image quality using mathematical tools such as nonlinear partial differential operators. In this paper, to perform smoothing on digital images, we propose to use the p(x)-Laplacian operator. Its smoothing power plays a main role in the restoration process. This enables us to dynamically process certain areas of an image. We used a mathematical model of image regularisation that is described by a nonlinear diffusion Equation (this diffusion is modelled by the p(x)-Laplacian operator). We implemented the continuous model in order to observe the steps of the regularisation process to understand the effects of the different parameters of the model on an image. This will enable parameters to be used and adapted in order to provide a proposed solution.
A Data-Driven Digital Twin of Electric Vehicle Li-Ion Battery State-of-Charge Estimation Enabled by Driving Behavior Application Programming Interfaces
Authors: Issa Reda , Badr Mohamed M. , Shalash Omar , Othman Ali A. , Hamdan Eman , Hamad Mostafa S. , Abdel-Khalik Ayman S. , Ahmed Shehab , Imam Sherif M.
Published: October 2023

Accurately estimating the state-of-charge (SOC) of lithium-ion batteries (LIBs) in electric vehicles is a challenging task due to the complex dynamics of the battery and the varying operating conditions. To address this, this paper proposes the establishment of an Industrial Internet-of-Things (IIoT)-based digital twin (DT) through the Microsoft Azure services, incorporating components for data collection, time synchronization, processing, modeling, and decision visualization. Within this framework, the readily available measurements in the LIB module, including voltage, current, and operating temperature, are utilized, providing advanced information about the LIBs’ SOC and facilitating accurate determination of the electric vehicle (EV) range. This proposed data-driven SOC-estimation-based DT framework was developed with a supervised voting ensemble regression machine learning (ML) approach using the Azure ML service. To facilitate a more comprehensive understanding of historical driving cycles and ensure the SOC-estimation-based DT framework is accurate, this study used three application programming interfaces (APIs), namely Google Directions API, Google Elevation API, and OpenWeatherMap API, to collect the data and information necessary for analyzing and interpreting historical driving patterns, for the reference EV model, which closely emulates the dynamics of a real-world battery electric vehicle (BEV). Notably, the findings demonstrate that the proposed strategy achieves a normalized root mean square error (NRMSE) of 1.1446 and 0.02385 through simulation and experimental studies, respectively. The study’s results offer valuable insights that can inform further research on developing estimation and predictive maintenance systems for industrial applications.
Machine Learning-Based Measurement of Regional and Global Spinal Parameters Using the Concept of Incidence Angle of Inflection Points
Authors: Nguyen Thong Phi , Kim Ji-Hwan , Kim Seong-Ha , Yoon Jonghun , Choi Sung-Hoon
Published: October 2023

This study delves into the application of convolutional neural networks (CNNs) in evaluating spinal sagittal alignment, introducing the innovative concept of incidence angles of inflection points (IAIPs) as intuitive parameters to capture the interplay between pelvic and spinal alignment. Pioneering the fusion of IAIPs with machine learning for sagittal alignment analysis, this research scrutinized whole-spine lateral radiographs from hundreds of patients who visited a single institution, utilizing high-quality images for parameter assessments. Noteworthy findings revealed robust success rates for certain parameters, including pelvic and C2 incidence angles, but comparatively lower rates for sacral slope and L1 incidence. The proposed CNN-based machine learning method demonstrated remarkable efficiency, achieving an impressive 80 percent detection rate for various spinal angles, such as lumbar lordosis and thoracic kyphosis, with a precise error threshold of 3.5°. Further bolstering the study’s credibility, measurements derived from the novel formula closely aligned with those directly extracted from the CNN model. In conclusion, this research underscores the utility of the CNN-based deep learning algorithm in delivering precise measurements of spinal sagittal parameters, and highlights the potential for integrating machine learning with the IAIP concept for comprehensive data accumulation in the domain of sagittal spinal alignment analysis, thus advancing our understanding of spinal health.
Weak Genetic Isolation and Putative Phenotypic Selection in the Wild Carnation Dianthus virgineus (Caryophyllaceae)
Authors: Franzoni Jacopo , Astuti Giovanni , Peruzzi Lorenzo
Published: October 2023

By relating genetic divergence at neutral loci, phenotypic variation, and geographic and environmental distances, it is possible to dissect micro-evolutionary scenarios involving natural selection and neutral evolution. In this work, we tested the patterns of intraspecific genetic and phenotypic variation along an elevational gradient, using Dianthus virgineus as study system. We genotyped genome-wide SNPs through ddRAD sequencing and quantified phenotypic variation through multivariate morphological variation. We assessed patterns of variation by testing the statistical association between genetic, phenotypic, geographic, and elevational distances and explored the role of genetic drift and selection by comparing the Fst and Pst of morphometric traits. We revealed a weak genetic structure related to geographic distance among populations, but we excluded the predominant role of genetic drift acting on phenotypic traits. A high degree of phenotypic differentiation with respect to genetic divergence at neutral loci allowed us to hypothesize the effect of selection, putatively fuelled by changing conditions at different sites, on morphological traits. Thus, natural selection acting despite low genetic divergence at neutral loci can be hypothesized as a putative driver explaining the observed patterns of variation.
Untargeted Lipidomic Approach for Studying Different Nervous System Tissues of the Murine Model of Krabbe Disease
Authors: Alabed Husam B. R. , Del Grosso Ambra , Bellani Valeria , Urbanelli Lorena , Carpi Sara , De Sarlo Miriam , Bertocci Lorenzo , Colagiorgio Laura , Buratta Sandra , Scaccini Luca , Frongia Mancini Dorotea , Tonazzini Ilaria , Cecchini Marco , Emiliani Carla , Pellegrino Roberto Maria
Published: October 2023

Krabbe disease is a rare neurodegenerative disease with an autosomal recessive character caused by a mutation in the GALC gene. The mutation leads to an accumulation of psychosine and a subsequent degeneration of oligodendrocytes and Schwann cells. Psychosine is the main biomarker of the disease. The Twitcher mouse is the most commonly used animal model to study Krabbe disease. Although there are many references to this model in the literature, the lipidomic study of nervous system tissues in the Twitcher model has received little attention. This study focuses on the comparison of the lipid profiles of four nervous system tissues (brain, cerebellum, spinal cord, and sciatic nerve) in the Twitcher mouse compared to the wild-type mouse. Altogether, approximately 230 molecular species belonging to 19 lipid classes were annotated and quantified. A comparison at the levels of class, molecular species, and lipid building blocks showed significant differences between the two groups, particularly in the sciatic nerve. The in-depth study of the lipid phenotype made it possible to hypothesize the genes and enzymes involved in the changes. The integration of metabolic data with genetic data may be useful from a systems biology perspective to gain a better understanding of the molecular basis of the disease.
Hierarchical Cluster Analysis Based on Clinical and Neuropsychological Symptoms Reveals Distinct Subgroups in Fibromyalgia: A Population-Based Cohort Study
Authors: Maurel Sara , Giménez-Llort Lydia , Alegre-Martin Jose , Castro-Marrero Jesús
Published: October 2023

Fibromyalgia (FM) is a condition characterized by musculoskeletal pain and multiple comorbidities. Our study aimed to identify four clusters of FM patients according to their core clinical symptoms and neuropsychological comorbidities to identify possible therapeutic targets in the condition. We performed a population-based cohort study on 251 adult FM patients referred to primary care according to the 2010 ACR case criteria. Patients were aggregated in clusters by a K-medians hierarchical cluster analysis based on physical and emotional symptoms and neuropsychological variables. Four different clusters were identified in the FM population. Global cluster analysis reported a four-cluster profile (cluster 1: pain, fatigue, poorer sleep quality, stiffness, anxiety/depression and disability at work; cluster 2: injustice, catastrophizing, positive affect and negative affect; cluster 3: mindfulness and acceptance; and cluster 4: surrender). The second analysis on clinical symptoms revealed three distinct subgroups (cluster 1: fatigue, poorer sleep quality, stiffness and difficulties at work; cluster 2: pain; and cluster 3: anxiety and depression). The third analysis of neuropsychological variables provided two opposed subgroups (cluster 1: those with high scores in surrender, injustice, catastrophizing and negative affect, and cluster 2: those with high scores in acceptance, positive affect and mindfulness). These empirical results support models that assume an interaction between neurobiological, psychological and social factors beyond the classical biomedical model. A detailed assessment of such risk and protective factors is critical to differentiate FM subtypes, allowing for further identification of their specific needs and designing tailored personalized therapeutic interventions.
Endometriosis-Related Chronic Pelvic Pain
Authors: Song Soo Youn , Jung Ye Won , Shin WonKyo , Park Mia , Lee Geon Woo , Jeong Soohwa , An Sukjeong , Kim Kyoungmin , Ko Young Bok , Lee Ki Hwan , Kang Byung Hun , Lee Mina , Yoo Heon Jong
Published: October 2023

Endometriosis, which is the presence of endometrial stroma and glands outside the uterus, is one of the most frequently diagnosed gynecologic diseases in reproductive women. Patients with endometriosis suffer from various pain symptoms such as dysmenorrhea, dyspareunia, and chronic pelvic pain. The pathophysiology for chronic pain in patients with endometriosis has not been fully understood. Altered inflammatory responses have been shown to contribute to pain symptoms. Increased secretion of cytokines, angiogenic factors, and nerve growth factors has been suggested to increase pain. Also, altered distribution of nerve fibers may also contribute to chronic pain. Aside from local contributing factors, sensitization of the nervous system is also important in understanding persistent pain in endometriosis. Peripheral sensitization as well as central sensitization have been identified in patients with endometriosis. These sensitizations of the nervous system can also explain increased incidence of comorbidities related to pain such as irritable bowel disease, bladder pain syndrome, and vulvodynia in patients with endometriosis. In conclusion, there are various possible mechanisms behind pain in patients with endometriosis, and understanding these mechanisms can help clinicians understand the nature of the pain symptoms and decide on treatments for endometriosis-related pain symptoms.
Open Hardware for Microfluidics: Exploiting Raspberry Pi Singleboard Computer and Camera Systems for Customisable Laboratory Instrumentation
Authors: Sarıyer Rüya Meltem , Edwards Alexander Daniel , Needs Sarah Helen
Published: October 2023

The integration of Raspberry Pi miniature computer systems with microfluidics has revolutionised the development of low-cost and customizable analytical systems in life science laboratories. This review explores the applications of Raspberry Pi in microfluidics, with a focus on imaging, including microscopy and automated image capture. By leveraging the low cost, flexibility and accessibility of Raspberry Pi components, high-resolution imaging and analysis have been achieved in direct mammalian and bacterial cellular imaging and a plethora of image-based biochemical and molecular assays, from immunoassays, through microbial growth, to nucleic acid methods such as real-time-qPCR. The control of image capture permitted by Raspberry Pi hardware can also be combined with onboard image analysis. Open-source hardware offers an opportunity to develop complex laboratory instrumentation systems at a fraction of the cost of commercial equipment and, importantly, offers an opportunity for complete customisation to meet the users’ needs. However, these benefits come with a trade-off: challenges remain for those wishing to incorporate open-source hardware equipment in their own work, including requirements for construction and operator skill, the need for good documentation and the availability of rapid prototyping such as 3D printing plus other components. These advances in open-source hardware have the potential to improve the efficiency, accessibility, and cost-effectiveness of microfluidic-based experiments and applications.
The Subjective Experiences of Driving Cessation and Life Satisfaction
Authors: Kim Young-Sun , Shin Hyeri , Um Sarang
Published: October 2023

Compared to the driving group, the driving cessation group in this study was found to be a high-risk population in terms of their life satisfaction. This study evaluated data from 315 older adults, aged 55 or older, using the 2018 Korean Older Adults Driving and Mobility Service Trend Survey. These data were collected from 17 representative cities and provinces in South Korea. To minimize the potential for selection bias and the confounding factors inherent in observational studies, this study employed the propensity score matching (PSM) method. Following the matching, multivariate regression analyses were conducted to compare the driving cessation group (n = 65) with the driving group (n = 50) in terms of their life satisfaction. After adjusting for demographic and health-related variables, the older adults who had ceased driving were found to have lower life satisfaction (Coef. = −1.39, p-value = 0.018). Our results highlight the importance of establishing preliminary evidence to guide the development of tailored programs for older adults—especially for those likely to experience diminished life satisfaction and heightened risk—to address the mobility challenges stemming from driving cessation.