bluuebunny/crossref_metadata_2025 huggingface dataset:
Microplastic-Contaminated Feed Interferes with Antioxidant Enzyme and Lysozyme Gene Expression of Pacific White Shrimp (Litopenaeus vannamei) Leading to Hepatopancreas Damage and Increased Mortality
Authors: Niemcharoen Songsak , Haetrakul Thanida , Palić Dušan , Chansue Nantarika
Published: November 2022

Microplastic pollution can interfere with aquatic animal health and nonspecific immunity, increasing the potential for pathogen infection in crustaceans. However, the long-term effects of microplastics on crustacean immunity are less understood, especially regarding their toxicity in Pacific white shrimp (Litopenaeus vannamei). Effects of high-density polyethylene microplastics (HDPE-MPs) in feed on the mortality rate, hepatopancreas, and nonspecific immune system gene expression of Pacific white shrimp are presented. The LC50 at day 28 of HDPE-MP exposure was determined as 3.074% HDPE-MP in feed. A significant upregulation of the superoxide dismutase (SOD) and glutathione peroxidase (GPx) genes was observed in shrimp that were fed with 0.1 and 0.5% of HDPE-MP; then, they were downregulated significantly, except for the SOD gene expression of shrimp fed with 0.1% of HDPE-MP. The lysozyme (LYZ) gene was upregulated significantly in shrimp that were fed with 0.5, 1, and 3% HDPE-MP for 7 days and downregulated significantly in HDPE-receiving groups for at least 14 days. Significant histopathological changes in the hepatopancreas were observed in the treatment groups. The histopathological score of each lesion was correlated with the increase in HDPE-MP concentration. This study shows that the ingestion of HDPE microplastics can alter the expression of nonspecific immune system genes and damage the hepatopancreas in Pacific white shrimp.
Plasma Amino Acids in Horses Suffering from Pituitary Pars Intermedia Dysfunction
Authors: Stoeckle Sabita Diana , Timmermann Detlef , Merle Roswitha , Gehlen Heidrun
Published: November 2022

Pituitary pars intermedia dysfunction is one of the most common diseases of aged horses and ponies. In Parkinson’s disease, which is, similar to PPID, a disease that involves oxidative damage to dopaminergic pathways but with different clinical signs, alterations to the serum amino acid profile have been reported. To examine changes in the plasma amino acid profile in horses with PPID, EDTA plasma of horses that were presented for various reasons that required laboratory examinations of blood anticoagulated with EDTA was collected. With this plasma, the basal ACTH concentration as well as the amino acid profile was determined. Horses were considered PPID patients if the ACTH concentration was ≥ 100 pg/mL, i.e., they would be considered affected at any time. Horses were defined as non-PPID (nPPID) patients if the ACTH concentration was below 30 pg/mL. Horses receiving pergolide with ACTH ≤ 30 pg/mL were allocated to the group PPIDrr (PPID, ACTH in reference range) and horses receiving pergolide with ACTH ≥ 100 pg/mL to the group PPIDarr (PPID, ACTH above reference range). In total, 93 horses were examined, including 88 horses at the clinic and 5 horses at a private practice. Of these, 53 horses fulfilled the inclusion criteria (ACTH ≤ 30 pg/mL or ACTH ≥ 100 pg/mL). A total of 25 horses were diagnosed as nPPID, 20 as PPID, 5 as PPIDrr, and 3 as PPIDarr. Arginine was significantly higher in PPIDrr than in PPID and nPPID, asparagine was significantly higher in PPID, PPIDrr, and PPIDarr than in nPPID, citrulline was significantly higher in PPIDrr than in nPPID and PPID, cysteine was significantly lower in PPIDrr than in PPID, nPPID, and PPIDarr, and glutamine was significantly higher in PPID and PPIDarr than in nPPID. Especially, asparagine, citrulline, and glutamine may be potential diagnostic markers and may offer interesting approaches for research regarding amino supplementation in PPID.
The Risk of Pyelonephritis Following Uncomplicated Cystitis: A Nationwide Primary Healthcare Study
Authors: Jansåker Filip , Li Xinjun , Vik Ingvild , Frimodt-Møller Niels , Knudsen Jenny Dahl , Sundquist Kristina
Published: November 2022

Background: The risk of pyelonephritis following uncomplicated lower urinary tract infection (cystitis) in women has not been studied in well-powered samples. This is likely due to the previous lack of nationwide primary healthcare data. We aimed to examine the risks of pyelonephritis following cystitis in women and explore if antibiotic treatment, cervical cancer, parity, and sociodemographic factors are related to these risks. Methods: This was a nationwide cohort study (2006–2018) of 752,289 women diagnosed with uncomplicated cystitis in primary healthcare settings. Of these, 404 696 did not redeem an antibiotic prescription within five days from cystitis. Logistic regression models were used to calculate odds ratios for pyelonephritis within 30 days and 90 days following the cystitis event. Results: Around one percent (7454) of all women with cystitis were diagnosed with pyelonephritis within 30 days, of which 78.2% had not redeemed an antibiotic for their cystitis. Antibiotic treatment was inversely associated with both outpatient registration and hospitalization due to pyelonephritis, with odds ratios of 0.85 (95% CI 0.80 to 0.91) and 0.65 (95% CI 0.55 to 0.77), respectively. Sociodemographic factors, parity, and cervical cancer were, with few exceptions (e.g., age and region of residency), not associated with pyelonephritis. Conclusions: Antibiotic treatment was inversely associated with pyelonephritis, but the absolute risk reduction was low. Non-antibiotic treatment for cystitis might be a safe option for most women. Future studies identifying the women at the highest risks will help clinicians in their decision making when treating cystitis, while keeping the ecological costs of antibiotics in mind.
Molecular Epidemiology of Carbapenem-Resistant K. pneumoniae Clinical Isolates from the Adult Patients with Comorbidities in a Tertiary Hospital, Southern Saudi Arabia
Authors: Alshahrani Abdullah M. , Ibrahim Mutasim E. , Aldossary Ahmed K. , Alghamdi Mushabab A. , Ahmed Omar B. , Bin Abdulhak Aref A.
Published: November 2022

Hospitalized patients are likely to have chronic illnesses and are at an increased risk of mortality due to infection caused by MDR bacteria. We aimed to identify carbapenem-resistant genes carrying Klebsiella pneumoniae (K. pneumoniae) isolates and their risk factors recovered from adult patients with comorbidities. A cross-sectional study was carried out between April 2021 and December 2021 at King Abdullah Hospital (KAH) in Bisha province, Saudi Arabia. Seventy-one multi-drug resistant K. pneumoniae recovered from clinical samples and screened for carbapenemase genes of blaOXA-48-like, blaNDM-1, blaKPC, blaVIM, and blaIMP. Of 71 MDR K. pneumoniae examined, 47 (66.2%) isolates harbored various carbapenemase genes. The most prevalent single resistance gene was blaOXA-48-like (62.5%; n = 25), and 33.3% of them were recovered from sputum isolates. The blaNDM-1 gene was detected in 12 (30.0%) isolates, and eight of them were recovered from urine (n = 4) and blood (n = 4). Two (5.0%) single blaKPC genes were recovered from the sputum (n = 1) and blood (n = 1) isolates. In contrast, no blaIMP- and blaVIM-carrying isolates were detected. The co-existence of two resistance genes between blaOXA-48-like and blaNDM-1 was found in six strains, whereas only one strain was found to be produced in the three genes of blaNDM-1, blaKPC, and blaOXA-48-like. There were statistically significant associations between the presence of carbapenem-gene-carrying K. pneumoniae and patients’ gender (χ2(1) = 5.94, p = 0.015), intensive care unit admission (χ2(1) = 7.649, p = 0.002), and chronic obstructive pulmonary disease (χ2(1) = 4.851, p = 0.028). The study highlighted the existence of carbapenemase-producing K. pneumoniae, particularly blaOXA-48-like and blaNDM-1, in patients with comorbidities. Our findings emphasize the importance of the molecular characterization of resistance-determinant-carrying bacterial pathogens as a part of infection control and prevention in hospital settings.
Clinical Impact of Vancomycin Treatment in Ampicillin-Susceptible Enterococci Bloodstream Infections
Authors: Hemapanpairoa Jatapat , Changpradub Dhitiwat , Santimaleeworagun Wichai
Published: November 2022

Enterococci are major causes of bacteremia. Although the mortality rate of ampicillin- susceptible enterococci (ASE) bloodstream infections (BSI) is lower, compared with that of ampicillin-resistant enterococci BSI, the role of treatment regimens in ASE BSI remains to be determined. This retrospective study aimed to evaluate the treatment outcomes and factors associated with mortality among patients with ASE BSI. The charts of 145 enrolled patients with ASE BSI between January 2013 and April 2022 at Phramongkutklao Hospital were reviewed. The 30-day and in-hospital mortality rates were 28.8 and 41.9%, respectively. The 30-day mortality rate was higher in the vancomycin treatment group than in the beta-lactam treatment group (61.5 vs. 26%; p = 0.02). Pitt bacteremia score (OR 1.44, 95% CI 1.20–1.71); age-adjusted Charlson Comorbidity Index (OR 1.34, 95% CI 1.14–1.58); and vancomycin treatment (OR 4.07, 95% CI 1.02–16.22) were independent factors associated with 30-day mortality. The severity of illness, comorbidity and definitive therapy with vancomycin increased the mortality rate of patients with ASE BSI. Anti-enterococcal beta-lactams remain the first line antibiotics for ASE bacteremia.
Exposure to Heated Tobacco Products Aerosol Causes Acute Stress Responses in the Lung of Mouse
Authors: Koike Shin , Sato Kohei , Sawa Marie , Inaba Yohei , Hattori Kenji , Nakadate Kazuhiko , Ushiyama Akira , Ogasawara Yuki
Published: November 2022

In the present study, we evaluated the acute response of mice exposed to IQOS aerosol, a brand-name heated tobacco product (HTP), in the lung tissue. First, the thiobarbituric acid-reactive substances (TBA-RS) value was measured as an index to assess oxidative stress, and a significant increase was observed after exposure, followed by a significant increase in the total lung GSH concentration. The stress responses induced by IQOS aerosols was then analyzed by focusing on the changes in Nrf2 and ATF4, which are transcription factors that induce the expression of genes involved in GSH biosynthesis or metabolism. Although Nrf2 activation was not observed, significant accumulation of ATF4 in the nuclear fraction was noted three hours after exposure to IQOS aerosols. Upon an examination of changes in factors in the GSH biosynthetic system, a significant increase in cystine concentration in the lung tissue was measured, and an increase in xCT expression level was observed in the cell membrane fraction three–six hours after IQOS exposure. Furthermore, characteristic changes in HO-1, a stress-response protein regulated by ATF4, was discovered six hours after IQOS exposure. Moreover, analysis of the upstream ATF4 regulatory system revealed that phosphorylation of eIF2α was enhanced in the lung cytoplasmic fraction three hours after exposure to IQOS aerosols. These findings suggest that ER stress might be induced as an early response to IQOS aerosol exposure, accompanied by the activation of the eIF2α-ATF4 axis. These intracellular changes have also been reported after exposure to combustible cigarette smoke. Thus, the acute response found in the lungs of mice in the present study demonstrate that the inhalation of aerosols from IQOS elicits a biological response similar to that of combustible cigarette smoke. In conclusion, our results provide evidence that the biological effects of HTPs, such as IQOS, cannot be ignored in the lungs.
A Feasibility Study of the Use of PZT Actuators for Active Control to Enrich Engine Sound
Authors: Lee Young-Sup , Ryu Seokhoon , Lim Jihea , Yoo Eunsuk
Published: November 2022

This study examines the feasibility of a novel active sound enrichment (ASE) system using piezoelectric actuators as sound generators and an inverse control filter to supplement poor engine sound at the driver’s ear location in a passenger car instead of using an interior audio system. The proposed ASE algorithm is developed as a purely feedforward control strategy to track the pre-defined target engine sound (three engine orders). Theoretical and experimental analyses are investigated in-depth on the vibro-acoustic characteristics of a PZT (lead zirconate titanate) actuator bonded on a steel plate and a dedicated control filter to supplement sound using an inverse method to compensate for the secondary path. The location of the PZT-plate actuator was carefully chosen to satisfy the causality condition and robustly stable control of the ASE algorithm. The experimental ASE system was set up in a test car, and the ASE algorithm was implemented in a real-time controller. The real-time ASE experiment results showed that the measured sound of the three orders was well supplemented as the tracking of the target sound was achieved robustly with small errors without any divergent instability. Thus, this study suggests that the proposed ASE system using the PZT-plate actuator and the dedicated control filter is a feasible method for enriching sound in cars, and this approach can be considered as a masking tool against some exotic noise frequently observed in various vehicles including electric vehicles.
A Projection-Based Augmented Reality System for Medical Applications
Authors: Chien Jong-Chih , Lee Jiann-Der , Chang Chai-Wei , Wu Chieh-Tsai
Published: November 2022

The aim of this paper was to present the development of an Augmented Reality (AR) system which uses a 2D video projector to project a 3D model of blood vessels, built by combining Computed Tomography (CT) slices of a human brain, onto a model of a human head. The difficulty in building this system is that the human head contains, not flat surfaces, but non-regular curved surfaces. Using a 2D projector to project a 3D model onto non-regular curved 3D surfaces would result in serious distortions of the projection if the image was not uncorrected first. This paper proposed a method of correcting the projection, not only based on the curvatures of the surfaces, but also on the viewing position of the observer. Experimental results of this system showed that an average positional deviation error of 2.065 mm could be achieved under various test conditions.
Can Bioelectrical Impedance Analysis (BIA) Be Used to Predict Pig’s Meat Quality In Vivo?
Authors: Przybylski Wiesław , Jaworska Danuta , Sot Magdalena , Sieczko Leszek , Niemyjski Stanisław , Dukaczewska Karina , Wojtasik-Kalinowska Iwona
Published: November 2022

The aim of the current study was to evaluate the possibility of application of bioelectrical impedance analysis (BIA) in order to estimate pork quality. The BIA measurements were tested on 18 living animals for the prediction of the meat quality. The absolute resultant electrical resistance (Rz) and reactance (Xc) of the body was measured with a set of disposable surface electrodes at the frequency of 50 kHz and the current intensity of 400 µA. The characteristics of meat quality, pH measured 1 h and 24 h after slaughter, meat color parameters represented in CIE L*a*b* system, glycolytic potential, intramuscular fat, and natural drip loss, were assessed on the samples of the Longissimus dorsi (LD) muscle. The slaughter value of pigs was characterized on the basis of hot carcass weight (HCW) and percent of meat in carcass. The results showed a significant Pearson correlation between bioelectrical impedance parameter Rz and pH1 (r = 0.48*, p < 0.05). A significant Spearman correlation was showed between color b* value and the Rz/Xc/HCW ratio (r = −0.62*, p < 0.05) and Xc (r = −0.51*, p < 0.05), as well as between the Rz/Xc ratio with pH1 (r = 0.48*, p < 0.05). The multivariate statistical method (principal component analysis and cluster analysis) showed that bioimpedance measurements combined with meat quality traits make it possible to distinguish groups with different quality parameters. However, the relationships between them are complex and still require analysis.
A Maximum Efficiency-86% Hybrid Power Modulator for 5G New Radio(NR) Applications
Authors: Cui Xingli , Qiu Xin , Leng Yongqing , Liu Xiaotian , Wu Tianyu
Published: November 2022

A hybrid power modulator is presented for the radio frequency (RF) power amplifiers of 5th generation mobile communication technology (5G) new radio (NR) applications. A hybrid power modulator utilizing a two-level switching converter and a broadband and high-efficiency linear amplifier is presented. A further improvement in the efficiency of the circuit is achieved by using an optimized supply voltage of the two-level switching converters of 4.5 V. In this way, the overall efficiency is improved by more than 5% compared to using a 5 V supply voltage. The linear amplifier consists of four stages. In order to improve bandwidth and circuit stability, a compensation circuit is added to the linear amplifier that eliminates the poles of the main amplifier by introducing additional zeros, indirectly pushing the pole distribution out of the bandwidth. Using this approach, the linear amplifier achieves a 3-dB bandwidth of 180 MHz and an efficiency of 51%. The hybrid power modulator achieves a maximum output power of 2.4 W and an efficiency of 86% when tracking a 100 MHz 5G-NR signal under a 4 Ω load in a 180 nm CMOS package.
Three-Dimensional Anatomical Analysis of Muscle–Skeletal Districts
Authors: Paccini Martina , Patanè Giuseppe , Spagnuolo Michela
Published: November 2022

This work addresses the patient-specific characterisation of the morphology and pathologies of muscle–skeletal districts (e.g., wrist, spine) to support diagnostic activities and follow-up exams through the integration of morphological and tissue information. We propose different methods for the integration of morphological information, retrieved from the geometrical analysis of 3D surface models, with tissue information extracted from volume images. For the qualitative and quantitative validation, we discuss the localisation of bone erosion sites on the wrists to monitor rheumatic diseases and the characterisation of the three functional regions of the spinal vertebrae to study the presence of osteoporotic fractures. The proposed approach supports the quantitative and visual evaluation of possible damages, surgery planning, and early diagnosis or follow-up studies. Finally, our analysis is general enough to be applied to different districts.
On the Svelteness as an Engineering Tool in Constructal Design: A Critical Review
Authors: Clemente Miguel R. , Panão Miguel R. O.
Published: November 2022

The application of Constructal theory to the flow design in engineering applications connects the channels’ architecture with their freedom to morph. Assessing the evolution of the flow architecture in Constructal Design requires a core parameter. Svelteness is the best candidate, given its definition as a flow architecture’s intrinsic global geometric property. However, despite the broad applicability range of Constructal theory, research has restricted the use of Svelteness to fluid flow, focusing on using it to justify disregarding local pressure losses compared to distributed friction losses, connecting the design of the flow to its survival. This work reviews the application of Svelteness, from the intuitive perception of its meaning to its use in engineering design, namely understanding the difference between assuming the impact of Svelteness versus considering the effects of its evolution in time. This understanding allows exploring the depth and validity of applying Svelteness as a universal criterion, comparing the different methods that define it, and discussing its relevance to explaining freedom to morph in a flow. Using two types of configurations (serpentine and canopy-to-canopy), the review shows the relevance of using the configuration area for the external length scale in the presence of ramifications and a relation between the configuration area and the path followed by what flows in the absence of configurations. Finally, we discuss the establishment of Svelteness as an engineering design tool using the law of diminishing returns.
Soil Moisture Retrieval by Integrating SAR and Optical Data over Winter Wheat Fields
Authors: Wang Zhaowei , Sun Shuyi , Jiang Yandi , Li Shuguang , Ma Hongzhang
Published: November 2022

Soil moisture (SM) retrieval over agricultural fields using synthetic aperture radar (SAR) data is often hindered by the vegetation layer and soil roughness. Most SM inversion algorithms require in situ SM data for a calibration to eliminate these two disturbing factors, while collecting in situ data is a project that consumes a lot of manpower and resources. This paper aims to tentatively develop an inversion algorithm for retrieving SM in the absence of in situ SM in areas covered by winter wheat vegetation. Based on the analysis of the data set simulated by the Michigan Microwave Canopy Scattering (MIMICS) model, an improved ratio model is proposed to remove the effect of the vegetation layer. Through the parameterization of the advanced integral equation model (AIEM), the effect of the soil roughness on the inversion of soil moisture is eliminated. The spatial distribution of SM in winter wheat fields is obtained using the Sentinel-1 SAR and Sentinel-2 images. The comparison results between the inverted SM and the in situ measured data reveal a good correlation (R = 0.85, RMSE = 0.032 cm3·cm−3), and the result confirms that the algorithm developed only based on theoretical models can also effectively monitor the spatial changes of SM over winter wheat fields.
E3W—A Combined Model Based on GreedySoup Weighting Strategy for Chinese Agricultural News Classification
Authors: Xiao Zeyan , Yang Senqi , Duan Xuliang , Tang Dezhao , Guo Yan , Li Zhiyong
Published: November 2022

With the continuous development of the internet and big data, modernization and informatization are rapidly being realized in the agricultural field. In this line, the volume of agricultural news is also increasing. This explosion of agricultural news has made accurate access to agricultural news difficult, and the spread of news about some agricultural technologies has slowed down, resulting in certain hindrance to the development of agriculture. To address this problem, we apply NLP to agricultural news texts to classify the agricultural news, in order to ultimately improve the efficiency of agricultural news dissemination. We propose a classification model based on ERNIE + DPCNN, ERNIE, EGC, and Word2Vec + TextCNN as sub-models for Chinese short-agriculture text classification (E3W), utilizing the GreedySoup weighting strategy and multi-model combination; specifically, E3W consists of four sub-models, the output of which is processed using the GreedySoup weighting strategy. In the E3W model, we divide the classification process into two steps: in the first step, the text is passed through the four independent sub-models to obtain an initial classification result given by each sub-model; in the second step, the model considers the relationship between the initial classification result and the sub-models, and assigns weights to this initial classification result. The final category with the highest weight is used as the output of E3W. To fully evaluate the effectiveness of the E3W model, the accuracy, precision, recall, and F1-score are used as evaluation metrics in this paper. We conduct multiple sets of comparative experiments on a self-constructed agricultural data set, comparing E3W and its sub-models, as well as performing ablation experiments. The results demonstrate that the E3W model can improve the average accuracy by 1.02%, the average precision by 1.62%, the average recall by 1.21%, and the average F1-score by 1.02%. Overall, E3W can achieve state-of-the-art performance in Chinese agricultural news classification.
A Modified Gaussian Model for Spectral Amplitude Variability of the SMART 1 Array Records
Authors: Qin Han , Li Luyu
Published: November 2022

Artificial ground motions, particularly conditional simulated artificial ground motions, are an essential complement to actual earthquake records when designing large-span structures, while considering the spatially varying properties of ground motions. Most existing methods, both conditional and unconditional forms, consider only the simulated ground motion complying with the power spectral densities and the coherence between the spectra of actual ground motions. In this study, the SMART 1 array’s records are regarded as conditional simulated ground motions from its central station. Their periodograms’ amplitude variation processes with the increased separation distance between two locations are studied. The analysis shows that the Gaussian model underestimates the periodograms’ amplitude variation, which can cause significant relative motions between structural supports and is detrimental to large-span structures. A random local power coefficient (LPC) is involved in modifying the Gaussian method. The LPC exhibits a noncentral Wishart distribution. Its statistical model as a function of the separation distance is derived. The LPC preserves the random field’s power spectral density and the spectral coherence relationships of the conventional Gaussian model. Simultaneously, the simulated random field’s periodogram variation complies with that of the SMART1 records. Monte Carlo simulations were conducted in the analysis and validated the modified Gaussian method.
Asphalt Mixtures and Flexible Pavement Construction Degradation Considering Different Environmental Factors
Authors: Mączka Eryk , Mackiewicz Piotr
Published: November 2022

Water, frost, and road salt are counted as environmental factors. They affect the pavement structure, particularly during the winter or in regions located above sea level. In the article, a literature review related to water, frost, and road salt impacts was performed. The main problem of evaluating asphalt mixture degradation and its influence on pavement fatigue life via environmental factors was stated. Four types of asphalt concrete (AC22) road mixes were prepared for laboratory tests. They differed in production technology and the type of binder applied. One binder content level was tested. To investigate the impact of water, frost, and road salt on mineral-asphalt mixtures utilized in flexible constructions, two proprietary experimental methods were applied. Methods allowed for determining the mixtures’ degradation level using the measured stiffness modulus in the 4-PB-PR test. Based on the obtained results, it was found that both interactions cause a significant decrease in the value of the stiffness modulus. In the article, a degradation ratio was proposed. The ratio expressed the impact of water, frost, and road salt on the stiffness mix variability. Its value was considered for pavement fatigue life based on the AASHTO 2004 fatigue criterion. The article demonstrates that the type of binder used influences the mix’s resistance to water, frost, or road salt impact. The highest resistance was reached by a mixture with highly modified asphalt (hot technology), and the worst was with asphalt WMA (warm technology). It has also been proven that the impact of water, frost, or road salt on pavement fatigue life is significant. The drop was significant, amounting to a few dozen percent. It was stated that environmental impacts (such as water, frost, or road salt) should be considered in asphalt mixture and pavement construction design.
Pose Detection and Automatic Deviation Correction Control Strategy of Crawler Walking Equipment in Coal Mines
Authors: Ma Ying , Chen Hongyan , Yang Wei , Zhang Desheng , Chen Hongyue
Published: November 2022

Autonomous navigation technology is the basis of underground crawler walking equipment automation. Based on research of the sector laser pose parameter detection method, a pose detection system based on a cross laser is proposed. The mathematical model between pose parameters, laser receiver measurement data and tilt sensor measurement data is established by vector algorithm and the expression of key pose parameters is deduced. This paper studies the deviation correction control strategy of crawler walking equipment and puts forward the point deviation correction control strategy based on roadway excavation technology. Firstly, the end position of the path is determined according to the initial pose of the roadheader. Then, Bessel curve is used to plan the path between the starting point and the endpoint, and the pure tracking algorithm is used to track the planned path. The measurement errors of X and Y coordinates and yaw angle of roadheader within 10 80 m shall not exceed 10 mm, 32 mm and 0.65°. Using the point deviation correction strategy, the positioning error of the roadheader at the end of the path is less than 13 mm, and the yaw angle error is less than 0.16°. In the deviation correction process, the maximum angular velocity of the roadheader is 0.07 rad/s, which is less than 0.82 rad/s of the conventional deviation correction strategy. The results show that the point deviation correction strategy can not only ensure the accuracy of motion control, but also improve the stability of equipment motion.
Computer-Aided Detection of Hypertensive Retinopathy Using Depth-Wise Separable CNN
Authors: Qureshi Imran , Abbas Qaisar , Yan Junhua , Hussain Ayyaz , Shaheed Kashif , Baig Abdul Rauf
Published: November 2022

Hypertensive retinopathy (HR) is a retinal disorder, linked to high blood pressure. The incidence of HR-eye illness is directly related to the severity and duration of hypertension. It is critical to identify and analyze HR at an early stage to avoid blindness. There are presently only a few computer-aided systems (CADx) designed to recognize HR. Instead, those systems concentrated on collecting features from many retinopathy-related HR lesions and then classifying them using traditional machine learning algorithms. Consequently, those CADx systems required complicated image processing methods and domain-expert knowledge. To address these issues, a new CAD-HR system is proposed to advance depth-wise separable CNN (DSC) with residual connection and a linear support vector machine (LSVM). Initially, the data augmentation approach is used on retina graphics to enhance the size of the datasets. Afterward, this DSC approach is applied to retinal images to extract robust features. The retinal samples are then classified as either HR or non-HR using an LSVM classifier as the final step. The statistical investigation of 9500 retinograph images from two publicly available and one private source is undertaken to assess the accuracy. Several experimental results demonstrate that the CAD-HR model requires less computational time and fewer parameters to categorize HR. On average, the CAD-HR achieved a sensitivity (SE) of 94%, specificity (SP) of 96%, accuracy (ACC) of 95% and area under the receiver operating curve (AUC) of 0.96. This confirms that the CAD-HR system can be used to correctly diagnose HR.
Attitude Error and Contact Influencing Characteristic Analysis for a Composite Docking Test Platform
Authors: Zhang Yuan , Shao Junpeng , Zhang Jingwei , Zhou Enwen
Published: November 2022

The design and analysis of a new type of three-jaw docking mechanism capable of space rendezvous and docking are presented. In addition, a composite docking test platform capable of both vertical and horizontal docking is created. On the basis of kinematics theory, a global coordinate system is built, and the attitude error is assessed based on the error angle. On the basis of dynamic theory, the multi-body dynamic differential equation of the composite docking platform is derived, and the impact-induced interaction state of the locking pawls is studied. The simulation software is then used to jointly simulate the test platform and the docking mechanism under the two conditions of frontal and oblique docking, and to analyze the attitude law caused by the change of docking impact force. This provides a solid foundation for future research into the application of space rendezvous theory to small spacecraft.
Comparison of Cartilage Conduction Hearing Aid, Bone Anchored Hearing Aid, and ADHEAR: Case Series of 6 Patients with Conductive and Mixed Hearing Loss
Authors: Kitama Tsubasa , Nishiyama Takanori , Iwabu Kaho , Wakabayashi Takeshi , Shimanuki Marie N. , Hosoya Makoto , Oishi Naoki , Ozawa Hiroyuki
Published: November 2022

Cartilage conduction hearing aids (CC-HA), bone anchored hearing aids (Baha), and ADHEAR are good choices to improve hearing in patients who cannot use air conduction hearing aids because of aural atresia or continuous otorrhea. As there are many overlaps in the characteristics of these devices, we conducted a comparative trial of CC-HA, Baha, and ADHEAR. We provided patients with the opportunity to select their devices. The data of 6 patients who underwent comparative trials in our department between October 2021 and August 2022 were retrospectively examined. The gains of Baha and CC-HA outweighed those of ADHEAR. Regarding the sound localization test, there was no significant tendency for any of the hearing devices. Regarding the Glasgow Benefit Inventory, there was no clear tendency among the three devices in the quality of life evaluation. The most satisfactory model was the one subjectively chosen by the patient, regardless of the gain and score of the sound source localization test. Therefore, we believe that it is necessary to provide an opportunity for comparative trials and a consultation with each patient in the process of selecting a device.
A Combined Safety Monitoring Model for High Concrete Dams
Authors: Gu Chongshi , Wang Yanbo , Gu Hao , Hu Yating , Yang Meng , Cao Wenhan , Fang Zheng
Published: November 2022

When applying reliability analysis to the monitoring of structural health, it is very important that gross errors–which affect prediction accuracy–are included within the monitoring information. An approach using gross errors identification and a dam safety monitoring model for deformation monitoring data of concrete dams is proposed in this paper. It can solve the problems of strong nonlinearity and the difficulty of identifying and eliminating gross errors in deformation monitoring data in concrete dams. This new method combines the advantages of an incremental extreme learning machine (I-ELM) method to seek an optimal network structure, the Least Median Squares (LMS) method with strong robustness to multiple failure points, the robust estimation IGG method with the good robustness to outliers (gross errors) and extreme learning machine (ELM) method with high prediction efficiency and handling of nonlinear problems. The proposed method can eliminate gross errors and be utilized to predict the behavior of concrete dams. The deformation monitoring data of an existing 305 m-high concrete arch dam is acquired by combining remote sensing technology with other monitoring methods. The LMS-IGG-ELM method is utilized to eliminate outliers from the dam monitoring sequence and is compared with the processing result from a DBSCAN clustering algorithm, Romanovsky criterion and the 3σ method. The results show that the proposed method has the highest gross errors identification rate, the strongest generalization ability and the best prediction effect.
Seismic Retrofit of Existing Structures Based on Digital Surveying, Non-Destructive Testing and Nonlinear Structural Analysis: The Case of Gjirokastra Castle in Albania
Authors: Núñez García Marieta , Saloustros Savvas , Mateos Redondo Felix , Alonso Campanero José Alberto , Ortega Javier , Greco Federica , Aranha Chrysl , Martínez Cuart Irene
Published: November 2022

The present paper showcases the work carried out as part of the seismic retrofit of the Ottoman fortress of Gjirokastra, a UNESCO World Heritage site located in Albania. The need for strengthening and retrofitting the structure stems from the fact that it is situated in a region of high seismicity and showed signs of structural distress at the time of investigation. The hill on which the castle is built also has stability issues. The seismic retrofit focused on a damaged stone masonry tower of the fortress and was designed following a comprehensive methodology for the inspection, diagnosis and geotechnical and structural analyses. Through the use of non-destructive tests, the existing soil conditions, the material properties and composition and the dynamic behaviour of the tower were assessed. Nonlinear finite element analysis was used to establish the cause of the existing damage and to determine the most effective strengthening solutions. The findings of the investigation revealed potential causes of the observed damage as well as the need to carry out retrofitting works at the tower beyond ground improvement solutions to bring the performance of the structure up to the code-specified level. This paper highlights the importance of planning and coordination between all the relevant disciplines involved in the project, so that apt inspection and diagnostic tools can be used to fill in the gaps where information is missing and to design optimal and integrated structural interventions in historic structures. Satisfactory seismic performance can be obtained by using a combination of retrofitting techniques, which specifically target the weak elements identified via the analyses.
A0 Lamb Mode Tracking to Monitor Crack Evolution in Thin Aluminum Plates Using Acoustic Emission Sensors
Authors: Dris El yamine , Bentahar Mourad , Drai Redouane , El Mahi Abderrahim
Published: November 2022

This paper presents a real time monitoring methodology to identify the location of acoustic emission (AE) sources generated by microcracks created within an aluminum plate when submitted to a tensile load. The real time detection of the AE hits was performed by means of a network of piezoelectric sensors distributed on the surface of the plate. The proposed localization approach is based on the combination of the time-frequency analysis of the detected AE hits with an extended Kalman filter (EKF). The spatial coordinates of the AE sources were determined by solving a set of nonlinear equations, where the extended Kalman filter is based on an iterative calculation. By considering the statistics related to the estimation of the coordinates’ errors, results show that the proposed method is in agreement with the experimental observations related to the propagation of the crack when the aluminum plate is under load.
Parallel-to-Grain Compressive and Tensile Behavior of Paulownia Wood at Elevated Temperatures
Authors: Zhang Lingfeng , Chen Kaixi , Xu Biao , Liu Yan , Guo Kai
Published: November 2022

Fast-grown Paulownia wood is extensively used as construction material in China. The mechanical properties of Paulownia wood at room temperature are well known. However, investigations of its mechanical behavior at elevated temperatures are very limited. To address this issue, thermal analysis was conducted to investigate the mass loss and reaction heat during water evaporation and thermal decomposition. Moreover, parallel-to-grain compressive and tensile tests were conducted on clear Paulownia wood specimens at temperatures ranging from 20 °C to 220 °C. It was found that kinking is the main failure mode of the compressive specimens, while transverse rupture was frequently observed in the tensile specimens. At 220 °C, the retention rates of the average parallel-to-grain compressive and tensile strengths were 38% and 42%, respectively. However, the strengths significantly increased as the temperature increased from 100 °C to 140 °C, due to the moisture evaporation and the hardening of the dry lignin. The design curve suggested by EN 1995-1-2 was very conservative (as much as 76%) at estimating the parallel-to-grain compressive strengths. However, the design curve was slightly nonconservative (less than 6%) at predicting the parallel-to-grain tensile strengths when the temperature was below 60 °C. Furthermore, a significant reduction (approximately 40%) in the deformation capacity was found when the temperature was higher than 180 °C.
A Comparative Study of the Treatment Efficiency of Floating and Constructed Wetlands for the Bioremediation of Phenanthrene-Contaminated Water
Authors: Asghar Iqra , Younus Salman , Islam Ejazul , Iqbal Samina , Afzal Muhammad , Boopathy Ramaraj , Amin Mahwish , Jambi Ebtihaj J. , Mehmood Muhammad Aamer
Published: November 2022

Employing floating treatment wetlands (FTWs) and constructed wetlands (CWs) is one of the most eco-friendly strategies for the bioremediation of water contaminants. Here, the efficiency of FTWs and CWs was compared for the degradation of phenanthrene-contaminated water for the first time. The FTWs and CWs were established by vegetated Phragmites australis in phenanthrene (1000 mg L−1)-contaminated water. Both wetlands were augmented with a bacterial consortium of four bacterial strains: Burkholderia phytofirmans PsJN, Pseudomonas anguiliseptica ITRI53, Arthrobacter oxydans ITRH49, and Achromobacter xylosoxidans ITSI70. Overall, the wetlands removed 91–93% of the phenanthrene whilst the augmentation of the bacterial strains had a synergistic effect. In comparison, the CWs showed a better treatment efficiency, with a 93% reduction in phenanthrene, a 91.7% reduction in the chemical oxygen demand, an 89% reduction in the biochemical oxygen demand, and a 100% reduction in toxicity. The inoculated bacteria were found growing in the shoots, roots, and water of both wetlands, but were comparatively better adapted to the CWs when compared with the FTWs. Similarly, the plants vegetated in the CWs exhibited better growth than that observed in the FTWs. This study revealed that the FTWs and CWs vegetated with P. australis both had promising potential for the cost-effective bioremediation of phenanthrene-contaminated water.
The Relatively Stable Seepage Field: A New Concept to Determine Seepage Field in the Design of a Dry-Stack Tailings Pond
Authors: Li Qiang , Wu Bi-Ze , Li Xin , Jia Sen , Zhen Feng-Hao , Gao Song
Published: November 2022

The determination of seepage field is the basis to design seepage drainage facilities and dam slopes in tailings pond. However, in the design of a dry-stack tailings pond with a long service life, previous research has been mostly limited to the influence of short-term rainfall, and a proper concept has not been formed to guide the calculation of the seepage field in the design of a dry-stack tailings pond under the cumulative effect of long-term periodic rainfall. The objective of this study is to propose a new concept to concisely determine the seepage field for the design of a dry-stack tailings pond under multi-year periodic rainfall. To this end, the calculation model of the seepage field of a dry-stack tailings pond under multiyear rainfall was established. The evolution process of the seepage field was studied by numerical simulation based on the calculation model and the final form of the seepage field evolution of a dry-stack tailings pond was found. Accordingly, a new concept, the relatively stable seepage field (RSSF) which can be used as the basis for seepage drainage facilities and the dam slope design of a dry-stack tailings pond, was proposed and named. Furthermore, the influencing factors of a relatively stable seepage field were studied by numerical simulation. The results show that: (1) the cumulative infiltration of long-term periodic rainfall is the main reason for the formation of the RSSF, and (2) under the condition of constant annual rainfall, the distribution of the RSSF has little to do with the selection of rainfall mode. Therefore, a new understanding has been formed from this article whereby the RSSF is an essential basis to be considered in the design of the dam slope and drainage system of a dry-stack tailings pond.
Development and Application of Intelligent Temperature Control System for Large Aqueduct
Authors: Shi Yanke , Wang Zhangyao , Zhang Shuo , Zhang Duoxin , Sun Kai
Published: November 2022

When the temperature rise and fall rates of a large-scale aqueduct with traditional water-cooling technology exceeds the standard, it is difficult to avoid the temperature change of aqueduct concrete deviating from its control curve in the process of temperature rise and fall by adjusting the water flow rate or cooling the water temperature of a water pipe only by manual experience. Aiming at such problems, an intelligent temperature control system for a large aqueduct body is developed and applied, which is composed of an information processing and decision-making module, simulation calculation module and information collection and control module, with real-time interactive information and real-time update of the temperature change control curve. The system is applied to the 1:30 Dongjia Village Aqueduct model experiment. The model experiment results show that the system can automatically adjust the water flow velocity of concrete according to the temperature variation control curve, and update the temperature variation control curve according to the changes of environmental parameters and cooling water parameters.
Modeling Health Data Using Machine Learning Techniques Applied to Financial Management Predictions
Authors: Leon Sanz Rafael , Leon-Sanz Pilar
Published: November 2022

Health management has steadily improved in performance and accuracy using IT technology. Hospitals and health institutions hold an enormous number of data in their software applications, which can be used with Big Data methodologies to extract useful information. One of the most challenging aspects of health institutional management is financial management; billing prediction is a key aspect to maintain a predictable service level for patients, avoiding unpleasant surprises and anticipating treasury management. Using patient data from public patient databases and applying a machine learning approach, this article offers a model that helps to make more precise and detailed financial plans.
A Binaural MFCC-CNN Sound Quality Model of High-Speed Train
Authors: Ruan Peilin , Zheng Xu , Qiu Yi , Hao Zhiyong
Published: November 2022

The high-speed train (HST) is one of the most important transport tools in China, and the sound quality of its interior noise affects passengers’ comfort. This paper proposes a HST sound quality model. The model combines Mel-scale frequency cepstral coefficients (MFCCs), the most popular spectral-based input parameter in deep learning models, with convolutional neural networks (CNNs) to evaluate the sound quality of HSTs. Meanwhile, two input channels are applied to simulate binaural hearing so that the different sound signals can be processed separately. The binaural MFCC-CNN model achieves an accuracy of 96.2% and outperforms the traditional shallow neural network model because it considers the time-varying characteristics of noise. The MFCC features are capable of capturing the characteristics of noise and improving the accuracy of sound quality evaluations. Besides, the results suggest that the time and level differences in sound signals are important factors affecting sound quality at low annoyance levels. The proposed model is expected to optimize the comfort of the interior acoustic environment of HSTs.