bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Fermented Bamboo Powder Supplementation on Serum Biochemical Parameters, Immune Indices, and Fecal Microbial Composition in Growing–Finishing Pigs
Authors: Liu Zhengqun , Li Ning , Zhou Xiaoqiao , Zheng Zi , Zhang Chunhua , Liang Shiyue , Li Yuanming , Yan Jun , Li Qianjun , Mu Shuqin
Published: November 2022

This experiment aimed to investigate the effects of fermented bamboo powder (FBP) on the growth performance, serum biochemical parameters, immunoglobulins and inflammatory cytokines, and fecal microbial composition of growing–finishing pigs. A total of 108 barrows (initial body weight, 56.30 ± 0.55 kg) were randomly allocated to three dietary treatments in a 75 d trial, including a control (CON) diet and two FBP supplementation diets. The CON diet was formulated to three-phase diets according to the body weight of pigs, and the FBP diets were formulated used 5.00% (FBP1) or 10.00% (FBP2) FBP to replace the wheat bran in the CON diet, respectively. The results showed that there were no influences on growth performances between the CON diet and FBP addition diets, whereas the 5% FBP addition decreased the feed:gain of pigs compared to the pigs fed the FBP2 diet from d 0–75 (p < 0.05). Meanwhile, the FBP addition increased the high-density lipoprotein cholesterol (HDLC) and immunoglobulin A (IgA) content in serum (linear, p < 0.05), and pigs fed the FBP1 diet had greater HDLC and IgA contents in serum than those in the pigs fed the CON diet (p < 0.05). Microbial analysis showed that the FBP addition diets decreased the abundance of Spirochaetes, and the FBP2 diet increased the abundance of Firmicutes more than the CON diet (p < 0.05). In addition, the pigs fed the FBP2 diet increased the abundance of uncultured_bacterium_f_Lachnospiraceae, Ruminococcaceae_UCG-005, Prevotellaceae_UCG-003, Lachnospiraceae_XPB1014_group, and Lactobacillus more than the CON group (p < 0.05). In conclusion, the FBP supplementation to the diet had no negative effects on the growth performance and exerted beneficial effects on promoting serum biochemical and immune indices, as well as modulating the fecal microbiota of pigs. Therefore, these results showed that the fermented bamboo powder could be one potential fiber-rich ingredient for growing–finishing pigs, and that the recommended addition proportion in the growing–finishing pigs’ diet is 5%.
Feeding Strategies for Adapting Lake Sturgeon (Acipenser fulvescens) Larvae to Formulated Diets at Early Life Stages
Authors: Lee Seunghyung , Zhai Shaowei , Deng Dong-Fang , Li Yuquan , Blaufuss Patrick Christopher , Eggold Bradley T. , Binkowski Fred
Published: November 2022

Cost-effective feeding management is required to support conservation hatcheries for lake sturgeon (Acipenser fulvescens), an ecologically important species in the Great Lakes region. This study investigated an approach to transition lake sturgeon larvae from live feed (Artemia) to formulated feed and its effect on growth performance, survival, and response to acute hypoxia stress. The first experiment showed that sturgeon had similar (p > 0.05) growth and survival when fed Artemia or the combined feeding of Artemia with the commercial diet (crude protein, 551 g/kg diet). Feeding solely on the commercial or lab-made (crude protein, 491 g/kg diet) diet significantly reduced growth and survival (p < 0.05). In the second experiment, the growth performance of sturgeon (14 days post-hatch, DPH) fed with either Artemia only or combined feeding different feeding durations of two, three, and four weeks followed by a complete transition to the commercial diet. At the end of six weeks, the 3- and 4-week combined feeding periods resulted in significantly higher body weight and survival compared to the 2-week combined and the Artemia only feeding treatments. In the last experiment, sturgeons (27 DPH) were fed only with Artemia or combined feeding of Artemia with the commercial diet for four weeks followed by the complete transition to the commercial diet for two weeks. Eighteen fish from each treatment were investigated the response to acute hypoxic conditions (gradual decrease in dissolved oxygen level from 8 to 2.3 mg/L at the rate of 1 mg/L per hour). When the dissolved oxygen was between 3 and 4 mg/L, the mortality rate of the combination-fed sturgeon (11.7%) was significantly lower than those fed only Artemia (83.3%). These results clearly demonstrate that a commercial diet can partially replace Artemia at early life stages to improve growth, survival, and hypoxia tolerance and thus its co-feeding with Artemia is recommended.
Breeding Thin-Billed Prions Use Marine Habitats Ranging from Inshore to Distant Antarctic Waters
Authors: Quillfeldt Petra , Bange Andreas , Boutet Aude , Orben Rachael A. , Baylis Alastair M. M.
Published: November 2022

Pelagic seabirds cover large distances efficiently and thus may reach a variety of marine habitats during breeding. Previous studies using stable isotope data and geolocators suggested that Thin-billed Prions breeding in the Falkland Islands in the Southwest Atlantic may forage in temperate waters over the Patagonian Shelf or cross the Drake Passage to forage in Antarctic waters south of the Polar Front. We deployed miniature GPS dataloggers to track Thin-billed prions in the Falkland Islands during incubation (3 seasons) and chick-rearing (2 seasons). Thin-billed Prions had a wide distribution during incubation, covering latitudes between 43 and 60° S, with trip lengths of ca. 2000 km over seven days, on average. Thin-billed Prions from two nearby sites (60 km apart) were spatially segregated in their incubation trips, with New Island Thin-billed Prions foraging over the Patagonian Shelf, compared to Thin-billed Prions from Bird Island, that foraged in the region of the Polar Front. During chick-rearing, Thin-billed Prions from New Island undertook both long trips to the Patagonian Shelf and south of the Polar Front (30% of trips were 5–11 days), and short trips (70% of trips were 1–4 days) when they foraged more locally, including in inshore waters around the Falkland Islands. Females carried out more trips to distant sites. Thus, Thin-billed showed a high flexibility in foraging areas, habitats and foraging trip durations, which enable them to benefit from both, temperate and Antarctic environments.
Virulence Genes and In Vitro Antibiotic Profile of Photobacterium damselae Strains, Isolated from Fish Reared in Greek Aquaculture Facilities
Authors: Lattos Athanasios , Giantsis Ioannis A. , Tsavea Eleni , Kolygas Markos , Athanassopoulou Fotini , Bitchava Konstantina
Published: November 2022

Bacteria belonging to the species Photobacterium damselae are pathogens of cultured marine fish, causing diseases of high importance, such as Pasteurellosis. Thus, they are considered a major threat to the aquaculture sector. Despite the great importance of fish mariculture for the Greek economy, the distribution and abundance of these bacteria are not well documented in aquaculture units in Greece. Keeping this in mind, the scope of the present study was to investigate the presence, antibiotic profile, and virulence of Photobacterium bacteria originating from a representative sample of mariculture units throughout Greece. Samples were collected from diseased fish belonging to three different cultured fish species, namely Sparus aurata, Dicentrarchus labrax, and Pagrus pagrus, from both the Aegean and the Ionian Sea. Tissue samples were cultured in agar media, and bacteria were molecularly identified using both bacterial universal and species-specific primer pairs for Photobacterium spp. Additionally, the identified strains were characterized for the presence of virulence genes as well as antibiotic profiles. According to the results, the aforementioned bacteria are distributed in the Greek aquaculture units and are characterized by high pathogenicity based on the abundance of virulence genes. Furthermore, the majority of the detected strains exhibit some level of antibiotic resistance. In summary, our results indicate the need for systematic surveillance and study of their antibiotic profiles in Greek aquaculture since these bacteria constitute a major threat to the sector.
Secondary Infections in Critically Ill Patients with COVID-19: A Retrospective Study
Authors: Caiazzo Luca , Temperoni Chiara , Canovari Benedetta , Simonetti Oriana , Montalti Roberto , Barchiesi Francesco
Published: November 2022

Patients with severe COVID-19, especially those followed in the ICU, are at risk for developing bacterial and fungal superinfections. In this study, we aimed to describe the burden of hospital-acquired superinfections in a cohort of consecutive, severe COVID-19 patients hospitalized between February and May 2021 in the intensive care unit (ICU) department of San Salvatore Hospital in Pesaro, Italy. Among 89 patients considered, 68 (76.4%) acquired a secondary infection during their ICU stay. A total of 46 cases of ventilator-associated pneumonia (VAP), 31 bloodstream infections (BSIs) and 15 catheter-associated urinary tract infections (CAUTIs) were diagnosed. Overall mortality during ICU stay was 48%. A multivariate analysis showed that factors independently associated with mortality were male gender (OR: 4.875, CI: 1.227–19.366, p = 0.024), higher BMI (OR: 4.938, CI:1.356–17.980, p = 0.015) and the presence of VAP (OR: 6.518, CI: 2.178–19.510, p = 0.001). Gram-negative bacteria accounted for most of the isolates (68.8%), followed by Gram-positive bacteria (25.8%) and fungi (5.3%). Over half of the infections (58%) were caused by MDR opportunistic pathogens. Factors that were independently associated with an increased risk of infections caused by an MDR pathogen were higher BMI (OR: 4.378, CI: 1.467–13.064, p = 0.0008) and a higher Charlson Comorbidity Index (OR: 3.451, 95% CI: 1.113–10.700, p = 0.032). Secondary infections represent a common and life-threatening complication in critically ill patients with COVID-19. Efforts to minimize the likelihood of acquiring such infections, often caused by difficult-to-treat MDR organisms—especially in some subgroups of patients with specific risk factors—must be pursued.
Metabolism Profile of Mequindox in Sea Cucumbers In Vivo Using LC-HRMS
Authors: Mao Xin , Zhou Xiaozhen , He Jun , Liu Gongzhen , Liu Huihui , Zhao Han , Luo Pengjie , Wu Yongning , Li Yanshen
Published: November 2022

In this work, the metabolism behavior of mequindox (MEQ) in sea cucumber in vivo was investigated using LC-HRMS. In total, nine metabolites were detected and identified as well as the precursor in sea cucumber tissues. The metabolic pathways of MEQ in sea cucumber mainly include hydrogenation reduction, deoxidation, carboxylation, deacetylation, and combinations thereof. The most predominant metabolites of MEQ in sea cucumber are 2-iso-BDMEQ and 2-iso-1-DMEQ, with deoxidation and carbonyl reduction as major metabolic pathways. In particular, this work first reported 3-methyl-2-quinoxalinecarboxylic acid (MQCA) as a metabolite of MEQ, and carboxylation is a major metabolic pathway of MEQ in sea cucumber. This work revealed that the metabolism of MEQ in marine animals is different from that in land animals. The metabolism results in this work could facilitate the accurate risk assessment of MEQ in sea cucumber and related marine foods.
Comparison of Patient-Reported Outcomes Measures and Quality-Adjusted Life Years Following One- and Two-Stage Septic Knee Exchange
Authors: Budin Maximilian , Abuljadail Salahulddin , Traverso Giacomo , Ekhtiari Seper , Gehrke Thorsten , Sommer Rachel , Citak Mustafa
Published: November 2022

(1) Background: Periprosthetic joint infection (PJI) can be managed with one- or two-stage revision surgery protocol. Despite several studies analyzing the eradication rates between both procedures, there are no comparative studies that analyze patient-reported outcome measures (PROMs) and quality-adjusted life years (QALYs) in both treatment strategies. (2) Methods: All patients who underwent a two-stage knee revision between January 2017 to December 2018, due to a periprosthetic joint infection were included in the study. From the time interval, we selected a comparative group with the one-stage septic procedure. All patients received the following questionnaires: Oxford Knee Score, EQ-5D-5L, SSQ-8, and the SF-36. Additionally, demographic patient data were collected. The quality-adjusted life years (QALY) were calculated using the EQ-5D-5L. (3) Results: A total of 35 patients with a mean age of 67.7 years (SD = 8.9) were included in the final evaluation. The mean follow-up period was 54.5 months (SD = 5.5). There was no statistically significant difference regarding the Charlson Comorbidity Index (CCI), postoperative complications, or all evaluated questionnaires. There was no statistically significant difference in QALYs between the one- and two-stage revision. (4) Conclusion: Our study results show that the one-stage revision for PJI achieves similar PROMs compared to two-stage revision.
Investigating the Antibacterial Activity and Safety of Zinc Oxide Nanoparticles versus a Commercial Alcohol-Based Hand-Sanitizer: Can Zinc Oxide Nanoparticles Be Useful for Hand Sanitation?
Authors: Ismail Aliaa , Raya Nermeen R. , Orabi Ahmed , Ali Alaa M. , Abo-zeid Yasmin
Published: November 2022

Hand hygiene is the key factor to control and prevent the spread of infections, for example, hospital-acquired infections (HAIs). People commonly use alcohol-based hand sanitizers to assure hand hygiene. However, frequent use of alcohol-based hand sanitizers in a pandemic situation (e.g., COVID-19) was associated with serious drawbacks such as skin toxicity including irritation, skin dermatitis, and skin dryness or cracking, along with peeling, redness, or itching with higher possibility of infection. This demands the development of alternative novel products that are effective as alcohol-based hand sanitizers but have no hazardous effects. Zinc oxide nanoparticles (ZnO-NPs) are known to have broad-spectrum antimicrobial activity, be compatible with the biological system and the environment, and have applicable and economic industrial-scale production. Thus, ZnO-NPs might be a good candidate for hand sanitation. To the best of our knowledge, the antibacterial activity of ZnO-NPs in comparison to alcohol-based hand sanitizers has not yet been studied. In the present work, a comparative study of the antibacterial activity of ZnO-NPs vs. Sterillium, a commercial alcohol-based hand sanitizer that is commonly used in Egyptian hospitals, was performed against common microorganisms known to cause HAIs in Egypt, including Acinetobacter baumannii, Klebsiella pneumoniae, Methicillin-resistant Staphylococcus aureus (MRSA), and Staphylococcus aureus. The safety profiles of ZnO-NPs and Sterillium were also assessed. The obtained results demonstrated the superior antibacterial activity and safety of ZnO-NPs compared to Sterillium. Therefore, ZnO-NPs could be a promising candidate for hand sanitation in comparison to alcohol-based hand sanitizers; however, several studies related to long-term toxicity and stability of ZnO-NPs and investigations into their antimicrobial activity and safety in healthcare settings are still required in the future to ascertain their antimicrobial activity and safety.
Exploring the Antibiotic Resistance Profile of Clinical Klebsiella pneumoniae Isolates in Portugal
Authors: Oliveira Ricardo , Castro Joana , Silva Sónia , Oliveira Hugo , Saavedra Maria José , Azevedo Nuno Filipe , Almeida Carina
Published: November 2022

While antibiotic resistance is rising to dangerously high levels, resistance mechanisms are spreading globally among diverse bacterial species. The emergence of antibiotic-resistant Klebsiella pneumoniae, mainly due to the production of antibiotic-inactivating enzymes, is currently responsible for most treatment failures, threatening the effectiveness of classes of antibiotics used for decades. This study assessed the presence of genetic determinants of β-lactam resistance in 102 multi-drug resistant (MDR) K. pneumoniae isolates from patients admitted to two central hospitals in northern Portugal from 2010 to 2020. Antimicrobial susceptibility testing revealed a high rate (>90%) of resistance to most β-lactam antibiotics, except for carbapenems and cephamycins, which showed antimicrobial susceptibility rates in the range of 23.5–34.3% and 40.2–68.6%, respectively. A diverse pool of β-lactam resistance genetic determinants, including carbapenemases- (i.e., blaKPC-like and blaOXA-48-like), extended-spectrum β-lactamases (ESBL; i.e., blaTEM-like, blaCTX-M-like and blaSHV-like), and AmpC β-lactamases-coding genes (i.e., blaCMY-2-like and blaDHA-like) were found in most K. pneumoniae isolates. blaKPC-like (72.5%) and ESBL genes (37.3–74.5%) were the most detected, with approximately 80% of K. pneumoniae isolates presenting two or more resistance genes. As the optimal treatment of β-lactamase-producing K. pneumoniae infections remains problematic, the high co-occurrence of multiple β-lactam resistance genes must be seen as a serious warning of the problem of antimicrobial resistance.
Phytochemicals in the Prevention and Treatment of SARS-CoV-2—Clinical Evidence
Authors: Bijelić Katarina , Hitl Maja , Kladar Nebojša
Published: November 2022

The first case of SARS-CoV-2 infection was reported in December 2019. Due to the rapid spread of the disease and the lack of adequate therapy, the use of plants that have a long history in the treatment of viral infections has often been considered. The aim of this paper is to provide a brief review of the literature on the use of phytochemicals during the new pandemic. An extensive search of published works was performed through platforms Google Scholar, PubMed, Science Direct, Web of Science and Clinicaltrials.gov. Numerous preclinical studies on the use of phytochemicals (quercetin, curcumin, baicalin, kaempferol, resveratrol, glycyrrhizin, lycorine, colchicine) against SARS-CoV-2 have shown that these components can be effective in the prevention and treatment of this infection. Clinical research has proven that the use of black cumin and green propolis as well as quercetin has positive effects. As for other phytochemicals, in addition to preclinical testing which has already been carried out, it would be necessary to conduct clinical tests in order to assert their effectiveness. For those phytochemicals whose clinical efficacy has been proven, it would be necessary to conduct research on a larger number of patients, so that the conclusions are more representative.
The Genetic Characteristics and Carbapenem Resistance Mechanism of ST307 Klebsiella pneumoniae Coharbouring blaCMY-6, blaOXA-48, and a Truncated blaNDM-1
Authors: Shi Qiucheng , Han Xinhong , Huang Qin , Meng Yan , Zhang Ping , Wang Zhengan , Hu Huangdu , Jiang Yan , Du Xiaoxing , Yu Yunsong
Published: November 2022

Carbapenem-resistant Klebsiella pneumoniae (CRKP) is a common nosocomial pathogen causing severe infectious diseases, and ST307 CRKP is an emerging clone. In this study, we collected five ST307 CRKP isolates, evaluated their antimicrobial susceptibility using microbroth dilution, and their clonality and population structure by PFGE, cgMLST, and SNP-based phylogenetic analysis. Then, the genome characteristics, such as antimicrobial resistance genes and plasmid profiles, were studied by subsequent genomic analysis. The plasmid transfer ability was evaluated by conjugation, and the carbapenem resistance mechanism was elucidated by gene cloning. The results showed that all five ST307 CRKP isolates harboured blaCMY-6, blaOXA-48, and blaNDM-1; however, the end of the blaNDM-1 signal peptide was interrupted and truncated by an IS10 element, resulting in the deactivation of carbapenemase. The ST307 isolates were closely related, and belonged to the globally disseminated clade. blaOXA-48 and blaNDM-1 were located on the different mobilisable IncL/M- and IncA/C2-type plasmids, respectively, and either the pOXA-48 or pNDM-1 transconjugants were ertapenem resistant. Gene cloning showed that blaCMY-6 could elevate the MICs of carbapenems up to 64-fold and was located on the same plasmid as blaNDM-1. In summary, ST307 is a high-risk clone type, and its prevalence should be given additional attention.
Advances in Surface Modification of the Materials
Authors: Chmielewski Tomasz
Published: November 2022

The surfaces of engineering materials play key roles in interactions with the environment and very often influence durability under external conditions [...]
Prediction of Prospecting Target Based on ResNet Convolutional Neural Network
Authors: Gao Le , Huang Yongjie , Zhang Xin , Liu Qiyuan , Chen Zequn
Published: November 2022

In recent years, with the development of geological prospecting from shallow ore to deep and hidden ore, the difficulty of prospecting is increasing day by day, so the application of computer technology and new methods of geological and mineral exploration is paid more and more attention. The mining and prediction of geological prospecting information based on deep learning have become the frontier field of earth science. However, as a deep artificial intelligence algorithm, deep learning still has many problems to be solved in the big data mining and prediction of geological prospecting, such as the small number of training samples of geological and mineral images, the difficulty of building deep learning network models, and the universal applicability of deep learning models. In this paper, the training samples and convolutional neural network models suitable for geochemical element data mining are constructed to solve the above problems, and the model is successfully applied to the prediction research of gold, silver, lead and zinc polymetallic metallogenic areas in South China. Taking the Pangxidong research area in the west of Guangdong Province as an example, this paper carries out prospecting target prediction research based on a 1:50000 stream sediment survey original data. Firstly, the support vector machine (SVM) model and statistical method were used to determine the ore-related geochemical element assemblage. Secondly, the experimental data of geochemical elements were augmented and a dataset was established. Finally, ResNet-50 neural network model is used for data training and prediction research. The experimental results show that the areas numbered 9, 29, 38, 40, 95, 111, 114, 124, 144 have great metallogenic potential, and this method would be a promising tool for metallogenic prediction. By applying the ResNet-50 neural network in metallogenic prediction, it can provide a new idea for the future exploration of mineral resources. In order to verify the generality of the research method in this paper, we conducted experimental tests on the geochemical dataset of B area, another deposit research area in South China. The results show that 100% of the prediction area obtained by using the proposed method covers the known ore deposit area. This model also provides method support for further delineating the prospecting target area in study area B.
Characterizing the Tensile Behaviour of Woven and Composite Fabrics under UV Exposure
Authors: Jie Soon Yuan , Hoe Leow Zhi , Paul Suvash Chandra , Anggraini Vivi
Published: November 2022

Geotextiles exposed to sunlight undergo a certain degree of UV degradation. In this study, woven and composite geotextiles were subjected to outdoor weathering tests at various exposure levels (i.e., 1, 2, 3, 4, and 5 months) to characterize their tensile behaviour. Each month, geotextiles were subjected to tensile tests according to modified ISO 13934 standards. Later, micro-scale approaches were undertaken to analyze the microstructure characteristics of the geotextiles and confirm the experimental results using scanning electron microscopy (SEM) and Fourier-transform infrared (FTIR) spectroscopy. Results indicated that woven geotextiles underwent tensile strength degradation and became more brittle after 5 months of UV exposure, which showed the highest degradation of 69.55% for strength retained, followed by composite geotextiles that only indicated a minimal degradation of 94.19% for strength retained. The corresponding strain indicated a more pronounced degradation, with retained strain percentages of 80.74% and 82.63% after 5 months of UV exposure for woven and composite geotextiles, respectively. Surface micrographs of composite geotextiles indicated that the remarkable microcracks began to develop on the polymer surface after the second month and continued to develop after that. Surface degradation of woven geotextiles under SEM was characterized by the loosening of fibre alignment, and this phenomenon was found to become significant after the first month of UV exposure. FTIR analysis of geotextiles revealed a notable chemical structure alteration in the polymer (i.e., polypropylene) that was observed through the formation of peak absorbance in the 1713 cm−1 wavenumber after UV exposure. Overall, the results from all laboratory tests agreed well with each other and this study thus provides clear evidence of the UV degradation of geotextiles in response to outdoor weathering.
Study on Interior Aerodynamic Noise Characteristics of the High-Speed Maglev Train in the Low Vacuum Tube
Authors: Liu Jiali , Yu Mengge , Chen Dawei , Yang Zhigang
Published: November 2022

As the next-generation high-speed transportation system, the low vacuum tube high-speed maglev system combines the tube with a certain degree of vacuum with the high-speed maglev train, which can realize high-speed operation under low aerodynamic resistance and noise mode. In order to study the interior aerodynamic noise characteristics of the high-speed maglev train in the low vacuum tube, a computational model of the external flow field of the high-speed maglev train in a low vacuum tube was established, and the computational model of the interior aerodynamic noise of the high-speed maglev train was established using the statistical energy analysis method; then the interior aerodynamic noise characteristics of the high-speed maglev train in the low vacuum tube were studied. The research results show that in the low vacuum tube, the distribution of the interior aerodynamic noise of the high-speed maglev train shows the characteristics of large head car and tail car and small middle car, and the aerodynamic noise on the top of the car is smaller than that on the floor. With the increase in frequency, the sound pressure level of the interior aerodynamic noise of the high-speed maglev train has the tendency of increasing first and then decreasing, and the main energy of the interior aerodynamic noise is distributed in the range of 200–1000 Hz. From the perspective of the total sound pressure level of the interior aerodynamic noise, the interior aerodynamic noise of the tail car is the greatest, followed by the head car, and the interior aerodynamic noise of the middle car is the smallest. As the direction of the travel of the maglev train will change, the optimization design of the interior aerodynamic noise of the head and tail cars should be emphasized.
Experimental Study on the Permeability of Microbial-Solidified Calcareous Sand Based on MICP
Authors: Li Yanjun , Chen Jianwen
Published: November 2022

In the construction of artificial islands in distant seas, calcareous sand has been widely used as a foundation filler due to its excellent mechanical properties and extensive availability in the marine environment. How to store more fresh water on the artificial islands by reducing its permeability is currently a great challenge. Microbial-induced carbonate precipitation (MICP) has always been considered as a great potential method to improve the cemented properties of calcareous sand, but the effect of grain gradation on the permeability of MICP-improved calcareous sand remains unclear. In this research, a self-made device was developed to conduct MICP grouting and permeability tests, where the permeability coefficient (k) under different grain gradations (curvature coefficient (Cc) and uniformity coefficient (Cu)) was measured. A CT scan was conducted to investigate the variation in the porosity (n) of sand samples before and after MICP treatment. The weighting method was adopted to measure the content of induced calcium carbonate (M). A scanning electron microscopy (SEM) technique was used to further study the micromechanism of the MICP treatment. Finally, the correlations between the k of MICP-treated sand and Cu, as well as Cc, were semiquantitively analyzed. The results show that the magnitude of M, k and n changes are closely related to Cc and Cu. The reduction amount of k and n increased with the rise in Cc and Cu, and the increased amount of M increased with the rise in Cc and Cu. The SEM results show that the particle surface became rough due to the coating effect of CaCO3 crystals, and the pore spaces were reduced because of the partially filling effect of the crystals, which was responsible for the decrease in permeability and porosity. Furthermore, k fitted well with Cu and Cc, respectively, and the fitting curve reveals that larger Cu (Cu ≥ 6.0) and smaller Cc (2.0 > Cc > 0.5) were more suitable for MICP treatments and lead to a large reduction in permeability. The above results indicate that the grain gradation of calcareous sand had a significant influence on its permeability improved by MICP.
A Linear Discriminant Analysis and Classification Model for Breast Cancer Diagnosis
Authors: Adebiyi Marion Olubunmi , Arowolo Micheal Olaolu , Mshelia Moses Damilola , Olugbara Oludayo O.
Published: November 2022

Although most cases are identified at a late stage, breast cancer is the most public malignancy amongst women globally. However, mammography for the analysis of breast cancer is not routinely available at all general hospitals. Prolonging the period between detection and treatment for breast cancer may raise the likelihood of proliferating the disease. To speed up the process of diagnosing breast cancer and lower the mortality rate, a computerized method based on machine learning was created. The purpose of this investigation was to enhance the investigative accuracy of machine-learning algorithms for breast cancer diagnosis. The use of machine-learning methods will allow for the classification and prediction of cancer as either benign or malignant. This investigation applies the machine learning algorithms of random forest (RF) and the support vector machine (SVM) with the feature extraction method of linear discriminant analysis (LDA) to the Wisconsin Breast Cancer Dataset. The SVM with LDA and RF with LDA yielded accuracy results of 96.4% and 95.6% respectively. This research has useful applications in the medical field, while it enhances the efficiency and precision of a diagnostic system. Evidence from this study shows that better prediction is crucial and can benefit from machine learning methods. The results of this study have validated the use of feature extraction for breast cancer prediction when compared to the existing literature.
Fully Attentional Network for Low-Resource Academic Machine Translation and Post Editing
Authors: Sel İlhami , Hanbay Davut
Published: November 2022

English is accepted as an academic language in the world. This necessitates the use of English in their academic studies for speakers of other languages. Even when these researchers are competent in the use of the English language, some mistakes may occur while writing an academic article. To solve this problem, academicians tend to use automatic translation programs or get assistance from people with an advanced level of English. This study offers an expert system to enable assistance to the researchers throughout their academic article writing process. In this study, Turkish which is considered among low-resource languages is used as the source language. The proposed model combines the transformer encoder-decoder architecture model with the pre-trained Sci-BERT language model via the shallow fusion method. The model uses a Fully Attentional Network Layer instead of a Feed-Forward Network Layer in the known shallow fusion method. In this way, a higher success rate could be achieved by increasing the attention at the word level. Different metrics were used to evaluate the created model. The model created as a result of the experiments reached 45.1 BLEU and 73.2 METEOR scores. In addition, the proposed model achieved 20.12 and 20.56 scores, respectively, with the zero-shot translation method in the World Machine Translation (2017–2018) test datasets. The proposed method could inspire other low-resource languages to include the language model in the translation system. In this study, a corpus composed entirely of academic sentences is also introduced to be used in the translation system. The corpus consists of 1.2 million parallel sentences. The proposed model and corpus are made available to researchers on our GitHub page.
Intelligent Decision Making Based on the Combination of Deep Reinforcement Learning and an Influence Map
Authors: Lu Xiaofeng , Xue Ao , Lio Pietro , Hui Pan
Published: November 2022

Almost all recent deep reinforcement learning algorithms use four consecutive frames as the state space to retain the dynamic information. If the training state data constitute an image, the state space is used as the input of the neural network for training. As an AI-assisted decision-making technology, a dynamic influence map can describe dynamic information. In this paper, we propose the use of a frame image superimposed with an influence map as the state space to express dynamic information. Herein, we optimize Ape-x as a distributed reinforcement learning algorithm. Sparse reward is an issue that must be solved in refined intelligent decision making. The use of an influence map is proposed to generate the intrinsic reward when there is no external reward. The experiments conducted in this study prove that the combination of a dynamic influence map and deep reinforcement learning is effective. Compared with the traditional method that uses four consecutive frames to represent dynamic information, the score of the proposed method is increased by 11–13%, the training speed is increased by 59%, the video memory consumption is reduced by 30%, and the memory consumption is reduced by 50%. The proposed method is compared with the Ape-x algorithm without an influence map, DQN, N-Step DQN, QR-DQN, Dueling DQN, and C51. The experimental results show that the final score of the proposed method is higher than that of the compared baseline methods. In addition, the influence map is used to generate an intrinsic reward to effectively resolve the sparse reward problem.
Dynamic Community Detection Based on Evolutionary DeepWalk
Authors: Qu Song , Du Yuqing , Zhu Mu , Yuan Guan , Wang Jining , Zhang Yanmei , Duan Xiangyu
Published: November 2022

To fully characterize the evolution process of the topological structure of dynamic communities, we propose a dynamic community detection based on Evolutionary DeepWalk (DEDW) for the high-dimensional data and dynamic characteristics. First, DEDW solves the problem of data sparseness in the process of dynamic network data representation through graph embedding. Then, DEDW uses the DeepWalk algorithm to generate node embedding feature vectors based on the characteristics of the stable change of the community structure; finally, DEDW integrates historical network structure information to generate evolutionary graph features and implements dynamic community detection with the K-means algorithm. Experiments show that DEDW can mine the time-smooth change characteristics of dynamic communities, solve the problem of data sparseness in the process of node embedding, fully consider historical structure information, and improve the accuracy and stability of dynamic community detection.
Effects of an Ozone-Based Domestic Clothes Washer/Dryer on Indoor Air Quality: A Probabilistic Risk Assessment Study
Authors: Davoli Enrico , Paiano Viviana , Fattore Elena
Published: November 2022

New technologies are facing the market to overcome high energy costs and efficiency regulations. Among these, the use of ozone in domestic appliances has been recently proposed for a cold-water sanitizing system for clothes or even a no-water cycle to refresh clothes. Ozone is a contaminant in indoor environments and its toxicity is mainly due to the strong oxidizing action on cellular components that can reduce lung function and increase respiratory symptoms. This study illustrates a risk assessment for ozone emissions released from new domestic clothes washer/dryer during normal operation and in the case of a failure. Indoor ozone concentrations were measured, and a mass-balance model was applied, considering ozone released from the appliance during the no-water cycle and the outdoor ozone contribution. Monte Carlo analysis was used to derive the probability of exceeding the air quality standards established by the main international organizations for the protection of human health. This study indicated the most suitable ozone generator and the best refresh cycle to minimize health risks. This method can be generally used to assess the potential health risk for the indoor environment, due to the release of harmful emissions from household appliances.
Guest Molecules with Amino and Sulfhydryl Groups Enhance Photoluminescence by Reducing the Intermolecular Ligand-to-Metal Charge Transfer Process of Metal–Organic Frameworks
Authors: Zhao Yuewu , Wang Jine , Pei Renjun
Published: November 2022

Micron-sized metal–organic framework (MOF) sheets were prepared using organic molecules with aggregation-induced emission (AIE) properties as ligands. The intermolecular ligand-to-metal charge transfer (LMCT) process occurs in MOF structures, resulting in the disappearance of the matrix coordination-induced emission (MCIE) effect and emergence of the aggregation-caused quenching (ACQ) effect. Here, we demonstrate that molecules with electron donors can compete with the LMCT process in MOF structures, thereby changing the transfer path of the excitation energy and returning it to the ground state, mainly in the form of fluorescence. Organic molecules with amino or sulfhydryl groups can act as effective electron donors, reducing the LMCT process and causing the MCIE effect of the MOF sheet. The coexistence of amino and sulfhydryl groups will strongly inhibit the LMCT process of the MOF sheet, thereby greatly enhancing the MCIE effect. Therefore, these types of molecules can be used to regulate the photoluminescence intensity of AIE-based MOF materials. In addition, there are some organic molecules with multiple carboxyl or hydroxyl groups which can produce similar effects. Finally, it was confirmed that the intermolecular LMCT process is highly sensitive, and the MOF sheet showed distinguishable fluorescence results even with the addition of small molecules in the amount of 10−9 M. Thus, it is a feasible idea to use the fluorescence changes induced by the LMCT process as a sensitive sensing method for small molecules.
Insulated Gate Bipolar Transistor Solder Layer Defect Detection Research Based on Improved YOLOv5
Authors: Ling Qiying , Liu Xiaofang , Zhang Yuling , Niu Kai
Published: November 2022

The expanding market scale of the insulated gate bipolar transistor as a new type of power semiconductor device has higher insulated gate bipolar transistor soldering requirements. However, there are some small bubbles difficult to detect. The accuracy and speed of existing detection algorithms are difficult to meet the requirements of automated quality monitoring. For solving these problems, a detection data set of solder layer images captured by X-ray and labeled was made and an improved algorithm based on YOLOv5 was proposed, which can detect defects accurately and at a fast speed. The main contributions of this research are as follows: (1) a tiny bubble detection layer that further integrates the deep feature information and shallow feature information is added to improve the model’s ability to detect small bubbles; (2) to speed up model convergence by optimizing anchor frame parameters; (3) we change the EIoU loss function as the bounding box loss function to solve the sample imbalance of the dataset; (4) combine the Swin Transformer structure to improve the convolution module and form a new feature extraction module, and introduce it into the backbone layer to improve the detection accuracy. The results of the experiment show that the overall performance of the improved network is better than the original and mainstream detection algorithms. The accuracy of the improved YOLOv5_SEST has reached 94.5% and 5.6% improvement in mAP for common bubble defect detection compared to the original algorithm. Our model size is only 5.3 MB, and the detection speed reaches 110 f/s. Therefore, the improved YOLOv5_SEST can well meet the requirements of automated quality monitoring of insulated gate bipolar transistors.
Mode of Action of the Natural Product Allicin in a Plant Model: Influence on the Cytoskeleton and Subsequent Shift in Auxin Localization
Authors: Noll Ulrike , Schreiber Miriam , Hermanns Monika , Mertes Christopher A. , Slusarenko Alan J. , Gruhlke Martin C. H.
Published: November 2022

Allicin is a defense substance produced by garlic cells when they are injured. It is a redox-active thiosulfinate showing redox-activity with a broad range of dose-dependent antimicrobial and biocidal activity. It is known that allicin efficiently oxidizes thiol-groups, and it has been described as a redox toxin because it alters the redox homeostasis in cells and triggers oxidative stress responses. Allicin can therefore be used as a model substance to investigate the action of thiol-specific prooxidants. In order to learn more about the effect of allicin on plants, we used pure synthetized allicin, and studied the influence of allicin on organelle movement in Tradescantia fluminensis as a cytoskeleton-dependent process. Furthermore, we investigated cytoplasmic streaming in sterile filaments of Tradescantia fluminensis, organelle movement using transgenic Arabidopsis with organelle-specifics GFP-tags, and effects on actin and tubulin in the cytoskeleton using GFP-tagged lines. Tubulin and actin were visualized by GFP-tagging in transgenic lines of Arabidopsis thaliana to visualize the influence of allicin on the cytoskeleton. Since auxin transport depends on recycling and turnover of the PIN protein involving cytoskeletal transport to and from the membrane localization sites, auxin distribution in roots was investigated using of transgenic PIN1–GFP, PIN3–GFP, DR5–GFP and DII–VENUS Arabidopsis reporter lines. Allicin inhibited cytoplasmic streaming in T. fluminensis, organelle movement of peroxi-somesperoxisomes, and the Golgi apparatus in a concentration-dependent manner. It also destroyed the correct root tip distribution of auxin, which probably contributed to the observed inhibition of root growth. These observations of the disruption of cytoskeleton-dependent transport processes in plant cells add a new facet to the mechanism of action of allicin as a redox toxin in cells.
Fault Detection and Isolation of Load Mutation Caused by Electrical Interference of Single-Shaft Combined Cycle Power Plant
Authors: Yao Kun , Wang Ying , Li Zongjie , Li Jiajia , Wan Jie , Cao Yong
Published: November 2022

Because the generator power-measuring equipment is often accompanied by electrical interference in a complex electromagnetic environment in an actual thermal power plant, the output signal will change or even distort while it passes through the devices of acquisition and conversion. Several practical cases have found that the abnormal generation change phenomenon, impulse or oscillation caused by electrical interference, has different effects on the load regulation of steam turbines. These faults also exist in combined-cycle power plants (CCPPs). However, the insufficient installed capacity and operating life of CCPPs domestically cause similar load mutation failures that are scarcely found. We had to acknowledge that CCPPs and steam turbine regulation characteristics differ. It is of great value to study the influence of differences in load mutation on the load regulation of single-shaft CCPPs. We extracted the fault characteristics of two sudden load change phenomena using the operation data of an actual steam turbine and analyzed them through simulation. Furthermore, a fault detection and isolation method for sudden load changes in a single-shaft CCPP was proposed and the simulation results verified the method’s effectiveness.
Auxiliary Decision-Making System for Steel Plate Cold Straightening Based on Multi-Machine Learning Competition Strategies
Authors: Dai Zhen-Hu , Wang Rui-Hua , Guan Ji-Hong
Published: November 2022

In the process of steel plate production, whether cold straightening is required is significant to reduce costs and improve product qualification rates. It is not effective by adopting classic machine learning judgment algorithms. Concerning the effectiveness of ensemble learning methods on improving traditional machine learning methods, a steel plate cold straightening auxiliary decision-making algorithm based on multiple machine learning competition strategies is proposed in this paper. The algorithm firstly adopts the rough set method to simplify the attributes of the conditional factors for affecting whether the steel plate cold straightening is required, and reduce the attribute dimensions of the steel plate cold straightening auxiliary decision-making data set. Secondly, the competition of training multiple different learners on the data set produces the optimal base classifier. Finally, the final classifier is generated by training weights on the optimal base classifier and combining it with a centralized strategy. While the hit rate of good products of the final classifier is 97.9%, the hit rate of defective products is 90.9%. As such, the accuracy rate is better than the single kind of simple machine learning algorithms, which effectively improves the product quality of steel plates in practical production applications.
Influence Law of Foundation Pit Excavation on Stress of Surrounding Tunnel Bolt
Authors: Hu Shengbin , Zhou Tianzhong , Zhong Youxin , Ji Xuebin , Sun Shuangxi , Lin Jing , Zhang Rui , Wang Zhongzheng , Guo Chun , Lin Hang
Published: November 2022

Due to the existence of a tunnel next to the foundation pit, the soil surrounding the foundation pit deforms into the foundation pit due to the excavation unloading during the process of foundation pit excavation, which causes the deformation of the tunnel. The supporting structure of the tunnel can ensure the deformation stability of the tunnel, so it is necessary to study the stress of the tunnel bolt supporting structure caused by the excavation of the foundation pit. In this paper, the numerical simulation method was adopted to study the influence of the distance between the foundation pit and tunnel and the width and depth of foundation pit excavation on the stress of the tunnel bolt, and the following results were obtained: (1) When the distance between the tunnel and the foundation pit changes, the axial force of the bolt changes accordingly. The axial force of the left bolt first increases and then decreases, and the largest axial force is located in the middle of the bolt. (2) With the increase in the excavation width of the foundation pit, the stress of the left bolt does not change much. For the left bolt, with the increase in excavation depth, the stress of the left bolt does not increase monotonically but shows a trend of increasing first and then decreasing. When the excavation depth exceeds a certain value, the influence of excavation depth on lateral soil displacement gradually decreases. With the increase in excavation depth, the axial force of the top bolt decreases first and then increases.