bluuebunny/crossref_metadata_2025 huggingface dataset:
Case report: Immune remission from generalized myasthenia gravis in a dog with a thymoma and cholangiocellular carcinoma
Authors: Mignan Thomas , White Robert , Stee Kimberley , Bonanno Giuseppe , Targett Mike , Lowrie Mark
Published: March 2023

A 9-year-old male neutered Cockapoo was presented with an acute and progressive history of exercise induced weakness involving all limbs, and bilateral decreased ability to blink. Investigations revealed generalized myasthenia gravis alongside the presence of a thymoma and a cholangiocellular carcinoma. Symptomatic treatment through pyridostigmine bromide was used to control clinical signs, and complete surgical removal of the thymoma and cholangiocellular carcinoma was performed. Serum acetylcholine receptor antibody concentration was measured serially. Clinical remission defined as resolution of clinical signs alongside discontinuation of treatment was achieved by day 251 (8.2 months). Immune remission defined as normalization of serum acetylcholine receptor antibody concentration alongside resolution of clinical signs and discontinuation of treatment was achieved by day 566 (18.5 months). Neurological examination was normal, and the owners did not report any clinical deterioration during the final follow-up appointment on day 752 (24 months), hence outcome was considered excellent. This is the first report describing the temporal evolution of serum acetylcholine receptor antibody concentration in a dog with thymoma-associated myasthenia gravis which achieved immune remission following thymectomy. Treatment was successfully discontinued without any evidence of clinical deterioration thereafter despite serum acetylcholine receptor antibody concentration not normalizing for another 315 days (10 months).
Associations of Passive Drinking with Perceived Health Status, Mental Health, and Family Wellbeing in Hong Kong Chinese Adolescents: A Cross-Sectional Study
Authors: Chau Siu Long , Wu Yongda , Wang Man Ping , Ho Sai Yin
Published: March 2023

Passive drinking is prevalent in adolescents worldwide, but its prevalence and harm are understudied. Secondary students (n = 5840, grades 7–12) from 23 selected schools in Hong Kong participated in the survey from 2015–16. Students reported the harm of passive drinking, perceived health status (Patient Health Questionnaire-2 and Perceived Stress Scale-4), perceived happiness, and family health, happiness, and harmony in the questionnaire. The associations were analyzed using multivariable logistic regression (odds ratio, OR) and linear regression (unstandardized coefficient, b), adjusted for confounders. It was found that 29.1% (95% CI 27.8 to 30.5%) of students experienced passive drinking in the past 30 days. The past 30-day parental passive drinking was associated with a higher level of depressive symptoms (AOR 1.63, 95% CI 1.26 to 2.10), stress (adjusted b 0.76, 0.42 to 1.10), and lower level of perceived happiness (adjusted b −0.52, −0.72 to −0.33). The past 30-day parental passive drinking was associated with a lower level of family health (adjusted b −1.39, 95% CI −1.66 to −1.11), family happiness (adjusted b −1.36, −1.64 to −1.08), and family harmony (adjusted b −1.40, −1.70 to −1.10). Passive drinking was associated with poorer mental health, family wellbeing, and a lower level of happiness among Hong Kong Chinese adolescents.
A Multi-View Vision System for Astronaut Postural Reconstruction with Self-Calibration
Authors: Gan Shuwei , Zhang Xiaohu , Zhuge Sheng , Ning Chenghao , Zhong Lijun , Li You
Published: March 2023

Space exploration missions involve significant participation from astronauts. Therefore, it is of great practical importance to assess the astronauts’ performance via various parameters in the cramped and weightless space station. In this paper, we proposed a calibration-free multi-view vision system for astronaut performance capture, including two modules: (1) an alternating iterative optimization of the camera pose and human pose is implemented to calibrate the extrinsic camera parameters with detected 2D keypoints. (2) Scale factors are restricted by the limb length to recover the real-world scale and the shape parameters are refined for subsequent postural reconstruction. These two modules can provide effective and efficient motion capture in a weightless space station. Extensive experiments using public datasets and the ground verification test data demonstrated the accuracy of the estimated camera pose and the effectiveness of the reconstructed human pose.
Base Editing of EUI1 Improves the Elongation of the Uppermost Internode in Two-Line Male Sterile Rice Lines
Authors: Wang Yakun , Tang Shengjia , Guo Naihui , An Ruihu , Ren Zongliang , Hu Shikai , Wei Xiangjin , Jiao Guiai , Xie Lihong , Wang Ling , Chen Ying , Zhao Fengli , Hu Peisong , Sheng Zhonghua , Tang Shaoqing
Published: March 2023

The use of male sterile lines (MSLs) of rice is essential for heterosis utilization. However, MSLs have a common defect in the elongation of the uppermost internode, eventually leading to incomplete panicle exsertion, blocking pollination, and reducing the hybrid rice seed yield. Previously, the elongated uppermost internode 1 (EUI1) was identified as an active gibberellin-deactivating enzyme that plays a key role in panicle exsertion from the flag leaf sheath in rice (Oryza sativa L.). We used an adenine base editor to edit EUI1 and obtained two types of homozygous transgenic plants (eui1-1 and eui1-2). The transcription and translation levels of EUI1 in the two mutants were significantly lower than in the wild type, as was the oxidation activity of EUI1 to active gibberellins (GAs), which also decreased. The contents of the plant hormones GA1, GA3, and GA4 in eui1-1 (1.64, 1.55, and 0.92 ng/g) and eui1-2 (0.85, 0.64, and 0.65 ng/g) panicles were significantly higher than the wild type (0.70, 0.57, and 0.42 ng/g). The uppermost internode lengths of the mutant were 26.5 and 23.6 cm, which were significantly longer than that of the wild type (18.0 cm), and the cell lengths of the mutant were 161.10 and 157.19 μm, which were longer than that of the wild type (89.28 μm). Our results indicate that the adenine base editing system could increase the content of endogenous bioactive GAs in young panicles by fine-tuning EUI1 activity, reduce the defect of panicle enclosure in MSLs and increase the yield of hybrid rice seed production.
Agronomic, Physiological, Genetic and Phytochemical Characteristics of Onion Varieties Influenced by Daylength Requirements
Authors: Kiani Zahra , Mashayekhi Kambiz , Golubkina Nadezhda , Mousavizadeh Seyyed Javad , Nezhad Khalil Zaynali , Caruso Gianluca
Published: March 2023

The evaluation of A. cepa biodiversity provides onion breeders with great prospects to obtain plants with high resistance to environmental factors, remarkable yield, and product quality. Genetic diversity assessment of a collection of nine short- and long-day onion landraces and varieties originated from different Iranian regions, using ISSR markers and UPGMA dendrograms, was carried out for the first time. Short-day landraces (Sarze, Sarkoreh, and Kerman) originated from low latitude and short-day hybrids (Mirela and Soberana) demonstrated high genetic similarity, in terms of physiological responses to day length and temperature during the crop cycle and bulbing stage initiation. Contrarily, high latitude landraces (Azarshahr, White Gorgan, Kurdistan, and Esfahan) showed low biometrical, agronomic and genetic similarity with commercial short-day onions. Specific differences in morphological reactions between these two groups displayed diverse responses of plants to day length and temperature. Long- and short-day cultivars displayed significant differences in the dynamics of leaf and scale number, leaf and root length, dry and fresh weight, and bulbing ratio and bulb diameter, which were in accordance with ISSR data. The local landraces Azarshahr, Kurdistan, and Esfahan had high antioxidant status, suggesting high prospects for their utilization as an alternative to foreign F1 hybrid varieties.
Rhizobium tropici and Riboflavin Amendment Condition Arbuscular Mycorrhiza Colonization in Phaseolus vulgaris L.
Authors: Banuelos Jacob , Martínez-Romero Esperanza , Montaño Noé Manuel , Camargo-Ricalde Sara Lucía
Published: March 2023

Phaseolus vulgaris L. (Fabaceae) forms symbioses with arbuscular mycorrhizal fungi (AMF) and nitrogen-fixing rhizobia (NFB). The tripartite relationship uses molecular singals to establish intracellular symbioses in roots. The goal of this study was to determine if Rhizobium tropici CIAT 899 and exogenous riboflavin (vitamin B2) have an effect on AMF species selection and root colonization of P. vulgaris. Using SSU rRNA fragment amplification of DNA extracted from P. vulgaris roots, we found that the presence of R. tropici altered the relative distribution of AMF species. Dominikia bernensis (Ohel) was the most abundant AMF species in P. vulgaris roots but when R. tropici was co-inoculated, Glomus species dominated. Rhizobacteria such as R. tropici, secrete riboflavin and could affect AMF symbiosis. Addition of 50 μM riboflavin to P. vulgaris, increased plant growth (28%), dry nodule weight (18%), AMF colonization (248%) and mycorrhizal vesicle frequency (56%) in bean roots. 3.12 and 12.5 µM riboflavin favored the presence of Glomus macrocarpum in P. vulgaris roots. This work provides the basis to further study of rhizobial and mycorrhizal co-inoculation of Phaseolus vulgaris bean.
Effects of Carbon-Based Fertilizer on Soil Physical and Chemical Properties, Soil Enzyme Activity and Soil Microorganism of Maize in Northeast China
Authors: Wang Xuerui , Wang Bin , Gu Wanrong , Li Jian
Published: March 2023

The soil environment is an important factor that affects the growth of maize. Our study discusses the effect of carbon-based fertilizer on the rhizosphere soil microenvironment. Xianyu 335 and Jingke 968 maize varieties were selected, and six treatments were set up as follows: no fertilizer, chemical fertilizer, or carbon-based fertilizer (3 t/hm2, 3.75 t/hm2, 4.5 t/hm2, and 5.25 t/hm2). The results showed that the carbon-based fertilizer significantly reduced the soil pH value in the late growth stage. Carbon-based fertilizer can significantly improve the conductivity of soil solution. On 8 July (jointing stage), the conductivity of the two varieties of soil was the highest at 3.75 t treatment, 259.38% and 169.26% higher than that of chemical fertilizer, respectively. Carbon-based fertilizer significantly increased the soil carbon flux. The soil carbon flux of Jingke 968 showed a trend of first rising and then falling with the increase in the application amount of carbon-based fertilizer. On 8 July (jointing stage) and 28 July (tasseling stage), the 4.5 t treatment reached the maximum value, and on 16 August (early filling stage) and 4 September (waxy stage), the 3.75 t treatment reached the maximum value. Carbon-based fertilizer significantly increased the content of nitrate nitrogen, ammonium nitrogen, available phosphorus, and available potassium in the topsoil. Carbon-based fertilizer had a significant effect on soil enzyme activity and significantly increased soil neutral phosphatase activity in the late growth stage. On 16 August (early stage of grouting), β-Glucosidase activity was significantly higher in 3 t and 3.75 t treatments than other treatments in Xianyu 335 and Jingke 968. The activity of α-Xylosidase reached the highest at 3.75 t. The activities of polyphenol oxidase and catalase reached their maximum at 5.25 t treatment on 4 September (waxy ripening) and 26 September (full ripening). Carbon-based fertilizer significantly increased the soil bacterial diversity index (Shannon index, ACE index and Chao1 index), but had no significant impact on the fungal diversity index, and significantly increased the abundance of soil bacterial and fungal populations.
Plough Tillage Maintains High Rice Yield and Lowers Greenhouse Gas Emissions under Straw Incorporation in Three Rice-Based Cropping Systems
Authors: Danso Frederick , Bankole Oluwaseyi Oyewale , Zhang Nan , Dong Wenjun , Zhang Kun , Lu Changying , Shang Ziyin , Li Gexing , Deng Aixing , Song Zhenwei , Zheng Chengyan , Zhang Jun , Zhang Weijian
Published: March 2023

Straw incorporation promotes rice productivity and soil fertility. However, the effects of tillage practice with straw on GHG emissions in paddy fields are not well documented. Under three rice-based cropping systems of China (single rice, double rice and rice-wheat cropping systems), we investigated rice yield, CH4, N2O, area and yield-scaled emissions arising from different straw-incorporated tillage patterns. Tillage with straw affected rice yield by −6.8~3.2%, −9.1~9.0% and −9.8~2.1% in single rice, rice-wheat and double rice cropping systems respectively. Straw impacted CH4 emission but tillage influenced its impact irrespective of the rice cropping system. The highest CH4 emissions occurred in RedT + S, RoT + S and RoT + S under single rice, rice-wheat and double rice cropping systems respectively. Cumulative CH4 emission of PT + S decreased by 46.8% (p < 0.05) compared to RedT + S in the single cropping system, while under rice-wheat and double rice cropping systems, cumulative CH4 emission of PT + S decreased by 19.0% (p < 0.05) and 13.2% (p > 0.05) respectively compared with RoT + S. Lower methanogenic abundance of PT + S translated into the lowest cumulative CH4, area and yield scaled emissions in single rice and double rice cropping systems. To maintain high rice yield and reduce GHG emissions from straw incorporation, PT + S is recommended for a rice-based cropping system.
The Changes of Tolerance, Accumulation and Oxidative Stress Response to Cadmium in Tobacco Caused by Introducing Datura stramonium L. Genes
Authors: Wei Keqiang , Guo Tingting
Published: March 2023

Whether it is possible to create suitable plants for cadmium phytoremediation by introducing Datura stramonium L. genes into tobacco (Nicotiana tabacum L.) remains unclear. Hydroponic experiments were performed on N. tabacum L. var. MTLY, a newly developed hybrid variety, and the parents. Seedlings at the six-leaf stage were treated with 0 (control), 10 µM, 180 µM and 360 µM CdCl2 for 7 days, and their differences in Cd tolerance and accumulation and physiological and metabolic responses were evaluated. When subjected to 360 µM Cd, the growth of “MTLY”, in terms of the dry weight, plant height and root length, was obviously better than N. tabacum L. var. LY2 (female parent). In contrast to D. stramonium (male parent) and “LY2”, “MTLY” accumulated more Cd in shoots (127.6–3837.1 mg kg−1) and roots (121.6–1167.7 mg kg−1). Moreover, unlike “LY2”, “MTLY” could accumulate more Cd in its shoots than roots. Its bioconcentration factor (BCF) and translocation factor (TF) values reached 95.9–149.7 and 1.0–3.5, respectively, which were far greater than those of “LY2”. High-dose Cd stress significantly increased reactive oxygen species (ROS) and malondialdehyde (MDA) levels and decreased chlorophyll contents in tobacco seedlings, especially in “LY2”. Various enzymatic and non-enzymatic antioxidants in the three materials showed different responses to Cd stress. The change of the phenolic compounds and alkaloids in “MTLY” was basically similar to that in D. stramonium, but their levels were apparently higher than those in “LY2”. Results indicated that distant hybridization could be one of the effective methods for introducing metal-hyperaccumulator genes into a high biomass species, which contributed to enhancing the Cd tolerance, accumulation and detoxification in tobacco. This study has great significance in obtaining elite germplasm for phytoremediation. The exact mechanisms in molecules and genetics and the practical effectiveness in cadmium-contaminated soil remain to be further elucidated.
Improving Deep Learning Classifiers Performance via Preprocessing and Class Imbalance Approaches in a Plant Disease Detection Pipeline
Authors: Ojo Mike O. , Zahid Azlan
Published: March 2023

The foundation of effectively predicting plant disease in the early stage using deep learning algorithms is ideal for addressing food insecurity, inevitably drawing researchers and agricultural specialists to contribute to its effectiveness. The input preprocessor, abnormalities of the data (i.e., incomplete and nonexistent features, class imbalance), classifier, and decision explanation are typical components of a plant disease detection pipeline based on deep learning that accepts an image as input and outputs a diagnosis. Data sets related to plant diseases frequently display a magnitude imbalance due to the scarcity of disease outbreaks in real field conditions. This study examines the effects of several preprocessing methods and class imbalance approaches and deep learning classifiers steps in the pipeline for detecting plant diseases on our data set. We notably want to evaluate if additional preprocessing and effective handling of data inconsistencies in the plant disease pipeline may considerably assist deep learning classifiers. The evaluation’s findings indicate that contrast limited adaptive histogram equalization (CLAHE) combined with image sharpening and generative adversarial networks (GANs)-based approach for resampling performed the best among the preprocessing and resampling techniques, with an average classification accuracy of 97.69% and an average F1-score of 97.62% when fed through a ResNet-50 as the deep learning classifier. Lastly, this study provides a general workflow of a disease detection system that allows each component to be individually focused on depending on necessity.
A Novel Surgical Hybrid Approach to Neoplastic Lesions in the Distal Part of the Urethra: A Pilot Series of Clinical Cases
Authors: Prządka Przemysław , Antończyk Agnieszka , Liszka Bartłomiej , Borawski Wojciech , Dzimira Stanisław , Kiełbowicz Zdzisław , Gąsior Ludwika
Published: March 2023

All the surgical approaches described to date for the removal of distal urethral tumors have some technical difficulties that make these tumors difficult to treat. The article presents for the first time the treatment results of three female dogs, diagnosed with transitional cell carcinomas of the distal urethra, operated with a newly developed hybrid surgical method—a combination of laparoscopy and open surgery. This technique uses vulvovaginectomy, combined with resection of the distal urethra and prepubic urethrostomy. All of the procedures were possible to perform, without the need to carry out a laparotomy conversion. Histopathology revealed transitional cell carcinoma in all cases, with a margin of healthy tissues maintained in two out of three cases, which meant reoperation of the urethrostomy site in the remaining one case. The mean survival time was nine months. Among minor complications, recurrent cystitis was found. After the first surgery, all dogs retained full control over urination immediately after recovery from anesthesia. In one case that required reoperation, complete urinary incontinence occurred after the second procedure. The present findings suggest that hybrid surgery can be used to treat distal urethral tumors. Qualification for surgery must be limited to bitches with tumors of the distal urethra and without metastases, without the possibility of using other surgical methods, and with the owner’s full acceptance of the risk of complications.
Transcriptomic Analysis Reveals mRNA and Alternative Splicing Events in Ovine Skeletal Muscle Satellite Cells during Proliferation and Differentiation
Authors: Chen Qian , Huang Chang , Su Yinxiao , Zhao Qian , Pu Yabin , He Xiaohong , Jiang Lin , Ma Yuehui , Zhao Qianjun , Ye Shaohui
Published: March 2023

Skeletal muscle satellite cells (SMSCs), which are highly multifunctional muscle-derived stem cells, play an essential role in myogenesis and regeneration. Here, the transcriptional profile of SMSCs during proliferation and differentiation were constructed using the RNA-Seq method. A total of 1954 differentially expressed genes (DEGs) and 1092 differentially alternative splicing genes (DAGs) were identified including 1288 upregulated genes as well as 666 downregulated genes. GO and KEGG analyses showed that the DEGs and DAGs were enriched in the MAPK (mitogen-activated protein kinase) signaling pathway, the PI3K-Akt (phosphatidylinositol-tris-phosphate kinase 3/protein kinase B) signaling pathway, the Wnt signaling pathway, and the Ras signaling pathway. In total, 1479 alternative splice events (AS) were also identified during SMSC proliferation and differentiation. Among them, a unique AS event was the major per-mRNA splicing type, and SE was the predominant splicing pattern. Furthermore, transcription factors with AS were scanned during SMSC differentiation such as myocyte enhancer factor-2C (MEF2C) and the nuclear receptor subfamily 4 group A member 2 (NR4A2). Our results imply that MEF2C and NR4A2 can interact, and we speculate that NR4A2 and MEF2C might regulate the myogenesis of ovine SMSCs through interaction. Together, our study provides useful information on the transcriptional regulation of SMSCs during proliferation and differentiation at the transcriptional level, and provides a valuable resource for understanding the molecular mechanism of myogenesis and muscle development.
Fungal-Mediated Silver Nanoparticle and Biochar Synergy against Colorectal Cancer Cells and Pathogenic Bacteria
Authors: Alqaraleh Moath , Khleifat Khaled M. , Abu Hajleh Maha N. , Farah Husni S. , Ahmed Khaled Abdul-Aziz
Published: March 2023

Background: Silver nanoparticles (AgNPs) are attractive substrates for new medicinal treatments. Biochar is pyrolyzed biomass. Its porous architecture allows it to hold and gather minuscule particles, through which nanoparticles can accumulate in its porous structure. This study examined AgNPs’ antibacterial and anticancer properties alone and combined with biochar. Methods: The fungus Emericella dentata was responsible for biosynthesis of AgNPs. The characterization of AgNPs using STEM images and a Zetasizer was carried out. Accordingly, the antibacterial and antiproliferation activity of AgNPs and biochar was studied using MIC and MTT assays, respectively. To evaluate the antiangiogenic and anti-inflammatory effects of AgNPs with biochar, VEGF and cytokines including TNF alpha, IL-6 and IL-beta were tested using an ELISA assay. Results: The size of the AgNPs ranged from 10 to 80 nm, with more than 70% of them being smaller than 40 nm. The combination of AgNPs and biochar enhanced the antibacterial activity against all tested bacteria. Furthermore, this combination showed antiproliferative properties against HT29 cancer cells with high selectivity to fibroblasts at low concentrations. AgNPs with biochar significantly reduced VEGF and proinflammatory cytokine expression levels. Conclusions: Biochar and AgNPs may be novel treatments for bacteria and colorectal cancer cells, according to the current findings.
Characteristics of Previous Tuberculosis Treatment History in Patients with Treatment Failure and the Impact on Acquired Drug-Resistant Tuberculosis
Authors: Soedarsono Soedarsono , Mertaniasih Ni Made , Kusmiati Tutik , Permatasari Ariani , Ilahi Wiwik Kurnia , Anggraeni Amelia Tantri
Published: March 2023

Tuberculosis (TB) treatment failure is a health burden, as the patient remains a source of infection and may lead to the development of multi-drug resistance (MDR). Information from cases of treatment failure that develop into MDR, which is related to a history of previous TB treatment, in accordance with the pharmacokinetic aspect, is one important thing to prevent TB treatment failure and to prevent drug resistance. This was an observational descriptive study in an acquired MDR-TB patient who had a prior history of treatment failure. A structured questionnaire was used to collect information. The questionnaire consisted of a focus on the use of TB drug formulas during the treatment period, as well as when and how to take them. This study included 171 acquired MDR-TB patients from treatment failure cases. An amount of 64 patients received the separated TB drug, and 107 patients received the fixed dose combination (FDC) TB drug. An amount of 21 (32.8%) patients receiving separated TB drug and six (5.6%) patients receiving FDC TB drug took their drug in divided doses. In addition, three (4.7%) patients receiving separated TB drug and eight (7.5%) patients receiving FDC TB drug took their drug with food. An amount of 132 out of 171 (77.2%) patients had a history of incorrect treatment that developed into MDR-TB. Education on how to take the correct medication, both the separate version and the FDC TB drug, according to the pharmacokinetic aspect, is important before starting TB treatment.
The Increased Release Kinetics of Quercetin from Superparamagnetic Nanocarriers in Dialysis
Authors: Mandić Lucija , Matković Marija , Baranović Goran , Šegota Suzana
Published: March 2023

The actual cumulative mass of released quercetin from nanoparticles within the dialysis membrane was determined under the influence of external stationary and alternating magnetic fields. We have shown that the control of the release kinetics of quercetin from MNPs, i.e., the distribution of quercetin between the nanoparticles and the suspension within the membrane, can be tuned by the simple combination of stationary and alternating magnetic fields. Under non-sink conditions, the proportion of quercetin in the suspension inside the membrane is increased toward the nanoparticles, resulting in the increased release of quercetin. The results obtained could be applied to the release of insoluble flavonoids in aqueous suspensions in general.
Vitamin D from UV-Irradiated Mushrooms as a Way for Vitamin D Supplementation: A Systematic Review on Classic and Nonclassic Effects in Human and Animal Models
Authors: Rondanelli Mariangela , Moroni Alessia , Zese Marco , Gasparri Clara , Riva Antonella , Petrangolini Giovanna , Perna Simone , Mazzola Giuseppe
Published: March 2023

Recent literature has shown that vitamin D, in addition to its well-known activity on the skeleton, has many positive effects on health. Unfortunately, it is not easy to meet intake needs solely with food. Mushrooms could provide a valid way to achieve this goal, because they are one of the few sources of vitamin D. The aim of this systematic review was to summarize what has been reported in the literature on the treatment of animal and human models with irradiated commercial mushrooms, with particular attention paid to the effects on clinical outcomes associated with the classical and nonclassical vitamin D functions. A total of 18 articles were selected. Six studies were conducted on human samples, while twelve were focused on animal models. The six studies conducted in humans involved a large number of subjects (663), but the treatment period was relatively short (1–6 months). Furthermore, the treatment dosage was different in the various groups (600–3800 IU/day). Probably for this reason, the studies did not demonstrate clinical efficacy on the parameters evaluated (cognitive functions, muscle system/function, metabolic syndrome). Indeed, those studies demonstrated an efficacy in increasing the blood levels of 25(OH)D2, but not in increasing the levels of 25(OH)D total. In 9 of 12 studies conducted on the animal model, however, a clinical efficacy on bone metabolism, inflammation, and cognitive performance was demonstrated. The results of this systematic review indicate that the intake of vitamin D from irradiated mushrooms could possibly help to meet vitamin D needs, but the dosage and the time of treatment tested need to be evaluated. Therefore, studies conducted in humans for longer periods than the studies carried out up to now are necessary, with defined dosages, in order to also evaluate the clinical efficacy demonstrated in animal models both for the classical (bone metabolism) and nonclassical (muscle function, cognitive performance, anti-inflammatory, and antioxidant activities) effects of vitamin D.
Single-Cell Kinetic Modeling of β-Lapachone Metabolism in Head and Neck Squamous Cell Carcinoma
Authors: Raddatz Andrew D. , Furdui Cristina M. , Bey Erik A. , Kemp Melissa L.
Published: March 2023

Head and neck squamous cell carcinoma (HNSCC) cells are highly heterogeneous in their metabolism and typically experience elevated reactive oxygen species (ROS) levels such as superoxide and hydrogen peroxide (H2O2) in the tumor microenvironment. Tumor cells survive under these chronic oxidative conditions by upregulating antioxidant systems. To investigate the heterogeneity of cellular responses to chemotherapeutic H2O2 generation in tumor and healthy tissue, we leveraged single-cell RNA-sequencing (scRNA-seq) data to perform redox systems-level simulations of quinone-cycling β-lapachone treatment as a source of NQO1-dependent rapid superoxide and hydrogen peroxide (H2O2) production. Transcriptomic data from 10 HNSCC patient tumors was used to populate over 4000 single-cell antioxidant enzymatic network models of drug metabolism. The simulations reflected significant systems-level differences between the redox states of healthy and cancer cells, demonstrating in some patient samples a targetable cancer cell population or in others statistically indistinguishable effects between non-malignant and malignant cells. Subsequent multivariate analyses between healthy and malignant cellular models pointed to distinct contributors of redox responses between these phenotypes. This model framework provides a mechanistic basis for explaining mixed outcomes of NAD(P)H:quinone oxidoreductase 1 (NQO1)-bioactivatable therapeutics despite the tumor specificity of these drugs as defined by NQO1/catalase expression and highlights the role of alternate antioxidant components in dictating drug-induced oxidative stress.
Classification of Micromobility Vehicles in Thermal-Infrared Images Based on Combined Image and Contour Features Using Neuromorphic Processing
Authors: Stahl Bastian , Apfelbeck Jürgen , Lange Robert
Published: March 2023

Trends of environmental awareness, combined with a focus on personal fitness and health, motivate many people to switch from cars and public transport to micromobility solutions, namely bicycles, electric bicycles, cargo bikes, or scooters. To accommodate urban planning for these changes, cities and communities need to know how many micromobility vehicles are on the road. In a previous work, we proposed a concept for a compact, mobile, and energy-efficient system to classify and count micromobility vehicles utilizing uncooled long-wave infrared (LWIR) image sensors and a neuromorphic co-processor. In this work, we elaborate on this concept by focusing on the feature extraction process with the goal to increase the classification accuracy. We demonstrate that even with a reduced feature list compared with our early concept, we manage to increase the detection precision to more than 90%. This is achieved by reducing the images of 160 × 120 pixels to only 12 × 18 pixels and combining them with contour moments to a feature vector of only 247 bytes.
Influence and Optimization of Geometric Parameters for Small-Radius Curved Tunnel Based on Response Surface Method
Authors: Feng Xiaojiu , Xie Yongtian , Liu Shaofeng , Yang Fujian
Published: March 2023

Compared with straight tunnels, small-radius curved tunnels are more common and have more complex influencing factors in urban underground traffic. Therefore, the seismic evaluation of small-radius curved tunnels is of great significance for the safe operation of underground structures. This paper used numerical analysis and the response surface method to analyze the influence of buried depth, curve angle and curve radius on the seismic response of a small-radius curved tunnel. For this purpose, seventeen three-dimensional (3D) numerical analysis models of the small-radius curved tunnel considering different geometric parameters are established. In addition, the optimal geometric parameters of displacement response and acceleration response of the small-radius curved tunnel are studied by using the method of multi-objective optimization design. The results show that buried depth has a pronounced influence upon the displacement response of the small-radius curved tunnel, whilst the buried depth and curve radius are the key parameters affecting the acceleration response of the small-radius curved tunnel. The optimal parameter configuration of the small-radius curved tunnel is the maximum buried depth, the maximum curve angle and the maximum curve radius within the value domain.
Fish Detection and Classification for Automatic Sorting System with an Optimized YOLO Algorithm
Authors: Kuswantori Ari , Suesut Taweepol , Tangsrirat Worapong , Schleining Gerhard , Nunak Navaphattra
Published: March 2023

Automatic fish recognition using deep learning and computer or machine vision is a key part of making the fish industry more productive through automation. An automatic sorting system will help to tackle the challenges of increasing food demand and the threat of food scarcity in the future due to the continuing growth of the world population and the impact of global warming and climate change. As far as the authors know, there has been no published work so far to detect and classify moving fish for the fish culture industry, especially for automatic sorting purposes based on the fish species using deep learning and machine vision. This paper proposes an approach based on the recognition algorithm YOLOv4, optimized with a unique labeling technique. The proposed method was tested with videos of real fish running on a conveyor, which were put randomly in position and order at a speed of 505.08 m/h and could obtain an accuracy of 98.15%. This study with a simple but effective method is expected to be a guide for automatically detecting, classifying, and sorting fish.
Point–Line-Aware Heterogeneous Graph Attention Network for Visual SLAM System
Authors: Lian Yuanfeng , Sun Hao , Dong Shaohua
Published: March 2023

Simultaneous localization and mapping (SLAM), as an important research topic in robotics, is useful but challenging to estimate robot pose and reconstruct a 3-D map of the surrounding environment. Despite recent success of several deep neural networks for visual SLAM, those methods cannot achieve robust results in complex industrial scenarios for constructing accurate and real-time maps due to the weak texture and complex geometric structure. This paper presents a novel and efficient visual SLAM system based on point–line-aware heterogeneous graph attention network, which combines points and line segments to solve the problem of the insufficient number of reliable features in traditional approaches. Firstly, a simultaneous feature extraction network is constructed based on the geometric relationships between points and points and points and lines. To further improve the efficiency and accuracy of the geometric association features of key regions, we design the point–line-aware attention module to guide the network to pay attention to the trivial features of both points and lines in images. Moreover, the network model is optimized by a transfer-aware knowledge distillation strategy to further improve the system’s real-time performance. Secondly, to improve the accuracy of the point–line matching, we design a point–line heterogeneous graph attention network, which combines an edge aggregation graph attention module and a cross-heterogeneous graph iteration module to conduct learning on the intragraph and intergraph. Finally, the point–line matching process is transformed into an optimal transport problem, and a near-iterative method based on a greedy strategy is presented to solve the optimization problem. The experiments on the KITTI dataset and a self-made dataset demonstrate the better effectiveness, accuracy, and adaptability of our method than those of the state of the art in visual SLAM.
Operation Optimization of Medium-Depth Ground Source Heat Pump (MD-GSHP) Systems Based on the Improved Particle Swarm Algorithm
Authors: Zhu Chao , Li Biao , Wang Yueshe , Zhang Jian , Quan Chen
Published: March 2023

In recent years, the medium-depth ground source heat pump (MD-GSHP) has become a promising and potential geothermal energy heating technology. This is due to the superior characteristics of buried pipes with a small diameter, the high energy efficiency of the heat pump, the insensitivity to the ground climate, and other conditions. Among currently available studies, both the variable operating conditions and the addition of thermal storage devices have rarely been considered. Despite this, the optimization methods applied to the medium-depth GSHP system are relatively simple. In this paper, an MD-GSHP system, including the thermal storage device with variable operating conditions, was fabricated. The operation strategies of the system were optimized by employing the improved particle swarm algorithm after applying the operating costs, the coefficient of performance of the system (COP) and the geothermal energy utilization coefficient to the objective functions, and the optimization results were compared and analyzed. The results show that the predictions of the optimized operating costs, the COP of the system, and the geothermal energy utilization coefficient were found to be CNY 279.27, 6.4420, and 0.8527, respectively. The effect of the COP on the optimization effect was opposite to that of operating costs, but analogous to that of the geothermal energy utilization coefficient.
A Novel Object Detection Method of Pointer Meter Based on Improved YOLOv4-Tiny
Authors: Xu Wenliang , Wang Wei , Ren Jianhua , Cai Chaozhi , Xue Yingfang
Published: March 2023

Pointer meters have been widely used in industrial field due to their strong stability; it is an important issue to be able to accurately read the meter. At present, patrol robots with computer vision function are often used to detect and read meters in some situations that are not suitable for manual reading of the meter. However, existing object detection algorithms are often misread and miss detection due to factors such as lighting, shooting angles, and complex background environments. To address these problems, this paper designs a YOLOv4-Tiny-based pointer meter detection model named pointer meter detection-YOLO (PMD-YOLO) for the goal of practical applications. Firstly, to reduce weight of the model and ensure the accuracy of object detection, a feature extraction network named GhostNet with a channel attention mechanism is implemented in YOLOv4-Tiny. Then, to enhance feature extraction ability of small- and medium-sized targets, an improved receptive field block (RFB) module is added after the backbone network, and a convolutional block attention module (CBAM) is introduced into the feature pyramid network (FPN). Finally, the FPN is optimized to improve the feature utilization, which further improves the detection accuracy. In order to verify the effectiveness and superiority of the PMD-YOLO proposed in this paper, the PMD-YOLO is used for experimental research on the constructed dataset of the pointer meter, and the target detection algorithms such as Faster region convolutional neural network (RCNN), YOLOv4, YOLOv4-Tiny, and YOLOv5-s are compared under the same conditions. The experimental results show that the mean average precision of the PMD-YOLO is 97.82%, which is significantly higher than the above algorithms. The weight of the PMD-YOLO is 9.38 M, which is significantly lower than the above algorithms. Therefore, the PMD-YOLO not only has high detection accuracy, but can also reduce the weight of the model and can meet the requirements of practical applications.
SSKM_DP: Differential Privacy Data Publishing Method via SFLA-Kohonen Network
Authors: Chu Zhiguang , He Jingsha , Li Juxia , Wang Qingyang , Zhang Xing , Zhu Nafei
Published: March 2023

Data publishing techniques have led to breakthroughs in several areas. These tools provide a promising direction. However, when they are applied to private or sensitive data such as patient medical records, the published data may divulge critical patient information. In order to address this issue, we propose a differential private data publishing method (SSKM_DP) based on the SFLA-Kohonen network, which perturbs sensitive attributes based on the maximum information coefficient to achieve a trade-off between security and usability. Additionally, we introduced a single-population frog jump algorithm (SFLA) to optimize the network. Extensive experiments on benchmark datasets have demonstrated that SSKM_DP outperforms state-of-the-art methods for differentially private data publishing techniques significantly.
Optimizing Aviation Maintenance through Algorithmic Approach of Real-Life Data
Authors: Korba Peter , Šváb Patrik , Vereš Michal , Lukáč Ján
Published: March 2023

The aviation industry has been undergoing significant changes in recent years, driven by technological advancements and the increasing demand for safe and efficient air transportation. One area that has seen significant advancements is aircraft maintenance, with the implementation of progressive technologies playing a crucial role. The use of digital technologies has revolutionized the way aircraft maintenance is carried out. For instance, the adoption of predictive maintenance algorithms has enabled airlines to predict when their aircraft will require maintenance, reducing downtime and increasing operational efficiency. This has been made possible by the integration of real-time data. Another technology that has transformed aircraft maintenance is the use of augmented reality and virtual reality. These technologies allow maintenance engineers to carry out procedures with greater accuracy and efficiency, as they can see instructions and parts overlaid on their real-world view. This has been particularly useful for complex and critical tasks, where human error could result in significant consequences. The algorithmization and digitalization of processes is one of the many pillars of the Industry 4.0 concept, which, if used correctly, can dramatically enhance the execution of processes. The algorithmic approach presented in this study can be easily adapted to other industries, and could potentially lead to similar optimizations in other fields. Overall, the implementation of progressive technologies in aircraft maintenance has improved safety, reduced downtime, and increased operational efficiency.
A Data-Driven Indirect Approach for Predicting the Response of Existing Structures Induced by Adjacent Excavation
Authors: Li Liyun , Sun Qingxi , Wang Yichen , Gao Yunhao
Published: March 2023

A data-driven indirect approach for predicting the response of existing structures induced by excavation is hereby proposed based on making full use of monitoring data during excavation, which can predict the deformation history of the research object during excavation. In this article, a machine-learning-based model framework for implementing the proposed approach is constructed and the treatment of key issues in the design and implementation of the proposed method is described in detail including the theoretical framework, the implementation mode of the method, the dimensionality reduction of the model parameters, and the normalization of data for model. On this basis, three models are provided to predict the settlement of buildings induced by adjacent excavation, namely the SVM model, BP model, and BP–SVM model. Relying on an excavation project for a subway in Xuzhou, Jiangsu Province, China, the proposed method is verified, and some conclusions are obtained.
Examining Interactions of Uranyl(VI) Ions with Amino Acids in the Gas Phase
Authors: Lucena Ana F. , Maria Leonor , Gibson John K. , Marçalo Joaquim
Published: March 2023

Gas-phase experiments, using electrospray ionization quadrupole ion trap mass spectrometry (ESI-QIT/MS), were conducted to probe basic interactions of the uranyl(VI) ion, UO22+, with selected natural amino acids, namely, L-cysteine (Cys), L-histidine (His), and L-aspartic acid (Asp), which strongly bind to metal ions. The simplest amino acid, glycine (Gly), was also studied for comparison. Cys, His, and Asp have additional potentially coordinating groups beyond the amino and carboxylic acid functional groups, specifically thiol in Cys, imidazole in His, and a second carboxylate in Asp. Gas-phase experiments comprised collision-induced dissociation (CID) of uranyl–amino acid complexes and competitive CID to assess the relative binding strength of different amino acids in the same uranyl complex. Reactivity of selected uranyl–amino acid complexes with water provided further insights into relative stabilities. In positive ion mode, CID and ensuing reactions with water suggested that uranyl–neutral AA binding strength decreased in the order His > Asp > Cys > Gly, which is similar to amino acid proton affinities. In negative ion mode, CID revealed a decreasing dissociation tendency in the order Gly >> His ≈ Cys > Asp, presumably reflecting a reverse enhanced binding to uranyl of the doubly deprotonated amino acids formed in CID.
DevEmo—Software Developers’ Facial Expression Dataset
Authors: Manikowska Michalina , Sadowski Damian , Sowinski Adam , Wrobel Michal R.
Published: March 2023

The COVID-19 pandemic has increased the relevance of remote activities and digital tools for education, work, and other aspects of daily life. This reality has highlighted the need for emotion recognition technology to better understand the emotions of computer users and provide support in remote environments. Emotion recognition can play a critical role in improving the remote experience and ensuring that individuals are able to effectively engage in computer-based tasks remotely. This paper presents a new dataset, DevEmo, that can be used to train deep learning models for the purpose of emotion recognition of computer users. The dataset consists of 217 video clips of 33 students solving programming tasks. The recordings were collected in the participants’ actual work environment, capturing the students’ facial expressions as they engaged in programming tasks. The DevEmo dataset is labeled to indicate the presence of the four emotions (anger, confusion, happiness, and surprise) and a neutral state. The dataset provides a unique opportunity to explore the relationship between emotions and computer-related activities, and has the potential to support the development of more personalized and effective tools for computer-based learning environments.
Urban Wind Corridors Analysis via Network Theory
Authors: Nevat Ido , Adelia Ayu Sukma
Published: March 2023

We develop a new model for urban wind corridors analysis and detection of urban wind ventilation potential based on concepts and principles of network theory. Our approach is based solely on data extracted from spatial urban features that are easily obtained from a 3D model of the city. Once the spatial features have been extracted, we embed them onto a graph topology. This allows us to use theories and techniques of network theory, and in particular graph theory. Utilizing such techniques, we perform end-to-end network flow analysis of the wind potential across the city and, in particular, estimate the locations, strengths, and paths of the wind corridors. To calibrate our model, we use a dataset generated by a meso-scale climate model and estimate the model parameters by projecting the wind vector field of the climate model onto a graph, thus providing a meaningful comparison of the two models under a new metric. We illustrate our modeling approach on the city of Singapore and explain how the results are useful for climate-informed urban design.