Characteristics Of Different Types Research Articles

Analysis of clinical characteristics of different types of lung function impaiement in TDL patients

AimThe clinical characteristics associated with pulmonary function decline in patients with Tuberculosis-destroyed lung (TDL) remain uncertain. We categorize them based on the pattern of pulmonary function impairment, distinguishing between restrictive spirometric pattern (RSP) and obstructive spirometric pattern (OSP). We aim to compare the severity of these patterns with the clinical characteristics of TDL patients and analyze their correlation.MethodWe conducted a retrospective analysis on the clinical data of TDL patients who underwent consecutive pulmonary function tests (PFT) from November 2002 to February 2023. We used the lower limit formula for normal values based on the 2012 Global Lung Function Initiative. We compared the clinical characteristics of RSP patients with those of OSP patients. The characteristics of RSP patients were analyzed using the tertiles of forced vital capacity percentage predicted (FVC% pred) decline based on PFT measurements, and the characteristics of OSP patients were analyzed using the tertiles of forced expiratory volume in 1 s percentage predicted (FEV1% pred) decline.ResultAmong the RSP patients, those in the Tertile1 group (with lower FVC% pred) were more likely to have a higher of body mass index (BMI), spinal deformities, and C-reactive protein (CRP) compared to the other two groups (P for trend < 0.001, 0.027, and 0.013, respectively). Among OSP patients, those in the Tertile1 group (with lower FEV1% pred) showed an increasing trend in cough symptoms and contralateral lung infection compared to the Tertile 2–3 group (P for trend 0.036 and 0.009, respectively).ConclusionFor TDL patients, we observed that Patients with high BMI, a higher proportion of spinal scoliosis, and abnormal elevation of CRP levels were more likely to have reduced FVC. Patients with decreased FEV1% pred have more frequent cough symptoms and a higher proportion of lung infections on the affected side.

Fundamental diagram of mixed traffic flow of CAVs with different connectivity and automation levels

This paper proposes the fundamental diagram model for a mixed traffic flow environment that considers different car-following modes under various levels of automation and connectivity. First, the SAE classification of vehicle automation levels, from L0 to L5, has been further divided into connectivity and automation levels. Second, the car-following modes that affect car-following characteristics are analyzed in mixed traffic flow with different levels of connectivity and automation. Different car-following models are used to describe the car-following characteristics of different types of modes. Third, the fundamental diagram model of mixed traffic flow is further derived based on the different levels of automation and connectivity. Finally, a numerical experiment is designed to evaluate the impact of different penetration rates (PRs) of the car-following modes on the traffic capacity of the mixed traffic flow. The results show that (1) with a higher PR of the automation level of the vehicle, the greater the traffic capacity. At the same time, as the automation levels increase, the change in the penetration rate of high automation levels has a more and more significant impact on traffic capacity. (2) Traffic capacity increases with increased PR of higher automation levels, representing an increase of approximately 11.1 % (3) Compared with connectivity, the PR of automation levels significantly impacts traffic capacity, which is approximately 52.6 %.

Elucidating the role of rice straw biochar in modulating Helianthus annuus L. antioxidants, secondary metabolites and soil post-harvest characteristics in different types of microplastics

The emergence of microplastics (MPs) as pollutants in agricultural soils is increasingly alarming, presenting significant threats to soil ecosystems. Given the widespread contamination of ecosystems by various types of MPs, including polystyrene (PS), polyvinyl chloride (PVC), and polyethylene (PE), it is crucial to understand their effects on agricultural productivity. The present study was conducted to investigate the effects of different types of MPs (PS, PVC, and PE) on various aspects of sunflower (Helianthus annuus L.) growth with the addition of rice straw biochar (RSB). This study aimed to examine plant growth and biomass, photosynthetic pigments and gas exchange characteristics, oxidative stress indicators, and the response of various antioxidants (enzymatic and non-enzymatic) and their specific gene expression, proline metabolism, the AsA–GSH cycle, cellular fractionation in the plants and post-harvest soil properties. The research outcomes indicated that elevated levels of different types of MPs in the soil notably reduced plant growth and biomass, photosynthetic pigments, and gas exchange attributes. Different types of MPs also induced oxidative stress, which caused an increase in various enzymatic and non-enzymatic antioxidant compounds, gene expression and sugar content; notably, a significant increase in proline metabolism, AsA–GSH cycle, and pigmentation of cellular components was also observed. Favorably, the addition of RSB significantly increased plant growth and biomass, gas exchange characteristics, enzymatic and non-enzymatic compounds, and relevant gene expression while decreasing oxidative stress. In addition, RSB amendment decreased proline metabolism and AsA-GSH cycle in H. annuus plants, thereby enhancing cellular fractionation and improving post-harvest soil properties. These results open new avenues for sustainable agriculture practices and show great potential for resolving the urgent issues caused by microplastic contamination in agricultural soils.

Речевой акт призыва как компонент англоязычного политического дискурса (на материале специального обращения Урсулы фон дер Ляйен, Давос, 2023 г.)

The aim of the research is to reveal the features of the functioning of direct, indirect and hidden appeals in English-language political discourse on the basis of the statements of the speech act theory. The scientific novelty of the study consists in disclosing the essential characteristics of different types of appeals in a socially significative political speech in English. The differentiation of direct, indirect and hidden appeals is revealed when being investigated in juridical and linguistic aspects. An appeal, inducing the addressee to perform a socially political action, is treated as part of social-political communication. This property turns appeals into an important tool that is often used in speeches by Western political leaders in order to influence the opinion and actions of the addressee. The results showed that indirect and hidden appeals are used in the studied political text, in which the illocutionary force of motivation is transmitted by formal means expressing other functional semantics. The use of indirect and hidden appeals is a feature of modern English-language political discourse, which is especially evident in the speeches of politicians calling for action against Russia.

A novel multi-feature fusion attention neural network for the recognition of epileptic EEG signals.

Epilepsy is a common chronic brain disorder. Detecting epilepsy by observing electroencephalography (EEG) is the main method neurologists use, but this method is time-consuming. EEG signals are non-stationary, nonlinear, and often highly noisy, so it remains challenging to recognize epileptic EEG signals more accurately and automatically. This paper proposes a novel classification system of epileptic EEG signals for single-channel EEG based on the attention network that integrates time-frequency and nonlinear dynamic features. The proposed system has three novel modules. The first module constructs the Hilbert spectrum (HS) with high time-frequency resolution into a two-channel parallel convolutional network. The time-frequency features are fully extracted by complementing the high-dimensional features of the two branches. The second module constructs a grayscale recurrence plot (GRP) that contains more nonlinear dynamic features than traditional RP, fed into the residual-connected convolution module for effective learning of nonlinear dynamic features. The third module is the feature fusion module based on a self-attention mechanism to assign optimal weights to different types of features and further enhance the information extraction capability of the system. Therefore, the system is named HG-SANet. The results of several classification tasks on the Bonn EEG database and the Bern-Barcelona EEG database show that the HG-SANet can effectively capture the contribution degree of the extracted features from different domains, significantly enhance the expression ability of the model, and improve the accuracy of the recognition of epileptic EEG signals. The HG-SANet can improve the diagnosis and treatment efficiency of epilepsy and has broad application prospects in the fields of brain disease diagnosis.

Features of epithelial-mesenchymal transition in ectopic endometrium in patients with extragenital endometriosis of various localizations. Observational study

Background. Epithelial-mesenchymal transition (EMT) is a conserved mechanism in the process of morphogenesis and organogenesis. EMT provides cells with migratory and invasive properties, which is a necessary condition for the formation of endometrioid heterotopias. Aim. To confirm the presence of EMT features in different types of endometriosis. Materials and methods. During a period of five years (2012–2017) we analyzed 43 cases of extragenital endometriosis: appendix (3 case), colon (5 cases), ileum (1 case), abdominal scar endometriosis after caesarean section (24 cases), and inguinal hernia (10 cases). The material was processed according to histological and immunohistochemical technique using monoclonal E-cadherin and polyclonal Vimentin antibodies to assess local invasiveness. Results. In peritoneal endometriosis, the ratio of E-cadherin to Vimentin expression was 10.3, in the colon = 9.1, in the appendix 8.6, in the ileum 5.5, in the hernial sac 4.2. Thus, in diffuse infiltrative forms of endometriosis, the lesion phenotype is characterized by low expression of E-cadherin, while expression of Vimentin is at a high level (p0.05). Conclusion. The results of our study confirmed involvement of the epithelial-mesenchymal transition process in the pathogenesis of extragenital endometriosis lesions, on the one hand, and they certify its invasive potential in these localizations, on the other hand.

Deep learning for enhanced index tracking

We develop a novel deep learning method for the enhanced index tracking problem, which aims to outperform an index while effectively controlling the tracking error. We generate a dynamic trading policy from a neural network that accepts a set of features as inputs. We design four blocks in the neural network architecture to handle different types of features, including regimes of the index and stocks, their short-term characteristics, and the current allocation. Outputs from the blocks are integrated into the final output that changes the portfolio allocation. We test our model on several indexes in empirical studies based on real market data. Out-of-sample results reveal the importance of different features and demonstrate the ability of our method in obtaining excess returns while effectively controlling the tracking error, downside risk, and transaction costs.

Description and Characterization of Different Types of Lymphoma in Cats in Hong Kong.

This study aimed to characterize and describe the different lymphoma types and anatomical forms in cats in Hong Kong. The clinical and histopathological data of cats diagnosed with lymphoma by cytology and/or histopathology were collected from a large diagnostic laboratory in Hong Kong. In total, 444 cats were diagnosed with lymphoma over four years (2019-2022). Like other countries where there is a low prevalence of FeLV infection, the predominant form of lymphoma was gastrointestinal (abdominal). Nasopharyngeal and peripheral nodal lymphoma were the second and third most common forms of lymphoma. The large cell/high-grade lymphoma type was much more common than the low-grade/small cell lymphoma in the study population. Domestic short hair was the most commonly affected breed in our study (n = 259/444). Among the cats with identified T/B-cell status, B-cell lymphoma (n = 61/81) prevailed as the most common phenotype. This study describes and characterizes the different types of feline lymphoma in cats in Hong Kong, adding valuable information to the body of knowledge.

DCNeT: A disease comorbidity network-based temporal deep learning framework to predict cardiovascular risk in patients with mental disorders

Patients with mental disorders (MDs) are at higher subsequent risk of developing cardiovascular diseases (CVDs) than the general population. Early identification of cardiovascular risk in patients with MDs is beneficial for timely intervention and reducing disease burden. Recently, deep learning approaches have been increasingly applied in CVDs risk prediction. However, these methods have three major issues: 1) mostly relying on multiple types of clinical data, 2) not sufficiently mining and utilizing comorbidity patterns hidden in complex correlations among various diseases, and 3) not fully leveraging the time information, including the irregular intervals. To address these issues, we propose a disease comorbidity network-based temporal deep learning framework (DCNeT) to predict the subsequent CVDs risk for patients with MDs based on routinely collected administrative health data. Firstly, to identify the comorbidity patterns of MDs, we construct a disease comorbidity network (DCN) for MDs and apply graph embedding method to generate disease embeddings for each disease in the DCN. Then, a code attention mechanism is proposed to obtain the weight of each disease which is embedded into dense vectors based on the structure of DCN. We present a view attention mechanism to compute the attention weights of different types of features including disease embeddings, basic features, and disease indicators for generating the final representations of patients’ hospitalizations. Furthermore, to fully utilize the information on the irregular time intervals between hospitalizations, a time encoding module is designed, and the time-aware LSTM is adopted to model the irregular time intervals and capture the temporal patterns of patients’ hospitalizations. The experimental results show that DCNeT outperforms the state-of-the-art methods, with the area under the receiver operating characteristic curve of 0.7658, 0.8143, 0.8110, and 0.7839 on four datasets, respectively. The ablation experiments further demonstrate that each module of DCNeT, including the code attention, view attention, and time encoding module, contributes to its superior performance, with average improvements of 1.20 %, 1.65 %, and 1.13 % in accuracy, respectively. Our DCNeT could be utilized as an efficient framework for identifying high-risk groups of CVDs among patients with MDs that may benefit from screening and preventive strategies.

Classification of Biomedical Images with Mined Statistical Features and Dynamic Programming

Background:: In the research and practice of medical sciences, accurate classification of biomedical images with computer programs may provide an important basis for the study and diagnosis of many diseases. Methods:: This paper proposes a new statistical approach that can accurately classify biomedical images based on their statistical features. In the first step of the proposed approach, a number of SIFT features of different types are computed for each pixel in a biomedical image and a statistical feature that describes the distribution of each type of SIFT features is obtained for the image. In the second step, a dynamic programming approach is used to efficiently analyze the dependence among different statistical features associated with an image and compute the probability for an image to belong to each possible class; the class with the largest probability is determined as the result of classification. Results:: Experimental results show that the proposed approach can lead to classification results with accuracy higher than that of a few state-of-the-art approaches for the classification of biomedical images Conclusion:: The proposed approach can achieve classification accuracy comparable to that of several state-of-the-art classification approaches. It is thus potentially useful for applications where large models are not appropriate for classification tasks due to limitations in computational or communication resources

Investigation of key morphological parameters of pores in different grades of asphalt mixture based on CT scanning technology

The internal pore structure of asphalt mixtures directly influences their permeability characteristics. Current research has not yet clarified the quantitative characterization of different types of meso-pore structures and their impact mechanisms on permeability characteristics. Therefore, this study, based on the acquisition of the internal pore structure of asphalt mixtures through CT non-destructive scanning technology, classifies pores according to their characteristics. It conducts a multi-dimensional and multi-scale qualitative and quantitative analysis of the meso-pore structures of asphalt mixtures in terms of pore distribution, equivalent radius of pore throats, inclination angle of pore throats, tortuosity of pore throats, and pore connectivity. The results indicate that the internal pore distributions of AC-16, SMA-16, OGFC-13, and OGFC-16 gradation asphalt mixtures are uniform, without noticeable segregation. The results of porosity obtained through non-destructive CT scanning technology demonstrate good consistency with those of macroscopic experiments. This demonstrates that analyzing CT images can accurately acquire pores and quantify pore characteristics. The number of pores in AC-16 gradation specimens is approximately 3–5 times that of other groups of gradation specimens, but the average volume of the pores is only 0.98 mm3. The average pore volume for SMA-16 gradation is 5.1 mm3, while for OGFC-13 and OGFC-16 gradation, the average pore volumes are 28.3 mm3 and 29.6 mm3, respectively. In SMA-16 grade specimens, the volume of open pores accounts for 95% of the total pore volume, despite the fact that open pores make up only 1% of the total number of pores. In the OGFC-13 and OGFC-16 graded asphalt mixtures, the volumes of interconnected pores account for 88.7% and 88.9% of the total pore volume, respectively. The number and volume proportion of pore throats decrease with the increase in pore throats angle, indicating that there are more pore throats with smaller angles, which are conducive to longitudinal drainage, and fewer pore throats with larger angles, which are conducive to lateral drainage. This suggests that the vertical permeability of samples formed by traditional Marshall compaction is usually greater than their horizontal permeability.

Analysis of Two Kinds of MV Trailer Creation Content

MV trailer is the MV inside the more eye-catching or eye-catching, to attract everyone's attention, it is a very effective way to promote the MV. This paper focuses on two different types of MV trailer type creation features, and analyzes the visual effect of MV trailer to attract the public with theoretical and practical significance. Using two representative female groups thumb amount of the first five MV forecast data in this paper found: (1) dance type MV forecast play characteristic is the music of chorus accompaniment with a short dance and different perspective scene to catch the public eye; (2) Story type MV forecast is characterized by some specific scene and perspective transformation suggested that the subsequent MV story. This paper aims to analyze the theoretical and practical significance of the visual effects of MV trailers in attracting the public by studying the creative characteristics of different types of MV trailers, and provide reference for the subsequent MV releases for better publicity.

Different types of tumor microvessels in stage I-IIIA squamous cell lung cancer and their clinical significance.

Lung cancer (LC) is the leading cause of morbidity and mortality among malignant neoplasms. Improving the diagnosis and treatment of LC remains an urgent task of modern oncology. Previously, we established that in gastric, breast and cervical cancer, tumor microvessels (MVs) differ in morphology and have different prognostic significance. The connection between different types of tumor MVs and the progression of LC is not well understood. To evaluate the morphological features and clinical significance of tumor MVs in lung squamous cell carcinoma (LUSC). A single-center retrospective cohort study examined medical records and archival paraffin blocks of 62 and 180 patients with stage I-IIIA LUSC in the training and main cohorts, respectively. All patients underwent radical surgery (R0) at the Orenburg Regional Cancer Clinic from May/20/2009 to December/14/2021. Tumor sections were routinely processed, and routine Mayer's hematoxylin and eosin staining and immunohistochemical staining for cluster of differentiation 34 (CD34), podoplanin, Snail and hypoxia-inducible factor-1 alpha were performed. The morphological features of different types of tumor MVs, tumor parenchyma and stroma were studied according to clinicopathological characteristics and LUSC prognosis. Statistical analysis was performed using Statistica 10.0 software. Univariate and multivariate logistic regression analyses were performed to identify potential risk factors for LUSC metastasis to regional lymph nodes (RLNs) and disease recurrence. Receiver operating characteristic curves were constructed to discriminate between patients with and without metastases in RLNs and those with and without disease recurrence. The effectiveness of the predictive models was assessed by the area under the curve. Survival was analyzed using the Kaplan-Meier method. The log-rank test was used to compare survival curves between patient subgroups. A value of P < 0.05 was considered to indicate statistical significance. Depending on the morphology, we classified tumor vessels into the following types: normal MVs, dilated capillaries (DCs), atypical DCs, DCs with weak expression of CD34, "contact-type" DCs, structures with partial endothelial linings, capillaries in the tumor solid component and lymphatic vessels in lymphoid and polymorphocellular infiltrates. We also evaluated the presence of loose, fine fibrous connective tissue (LFFCT) and retraction clefts in the tumor stroma, tumor spread into the alveolar air spaces (AASs) and fragmentation of the tumor solid component. According to multivariate analysis, the independent predictors of LUSC metastasis in RLNs were central tumor location (P < 0.00001), the presence of retraction clefts (P = 0.003), capillaries in the tumor solid component (P = 0.023) and fragmentation in the tumor solid component (P = 0.009), whereas the independent predictors of LUSC recurrence were tumor grade 3 (G3) (P = 0.001), stage N2 (P = 0.016), the presence of LFFCT in the tumor stroma (P < 0.00001), fragmentation of the tumor solid component (P = 0.0001), and the absence of tumor spread through the AASs (P = 0.0083). The results obtained confirm the correctness of our previously proposed classification of different types of tumor vessels and may contribute to improving the diagnosis and treatment of LUSC.

Magnetic resonance imaging features and classification of intraductal papillary neoplasm of the bile duct

Objective: To explore the magnetic resonance imaging (MRI) features and classification of intraductal papillary neoplasm of the bile duct (IPNB). Methods: Data from 90 patients with intraductal papillary neoplasm of the bile duct confirmed pathologically between June 2010 and January 2023 were retrospectively analyzed. The image analysis included the shape and location of the tumor, whether bile ducts had dilatation and the degree of dilation, whether there was a history of liver disease, whether there was a history of schistosomiasis, whether there was cancerous transformation, whether there were concurrent bile duct stones, whether there was hepatic lobe atrophy, whether there was hilar or abdominal lymph node enlargement, whether there was invasion of the bile duct wall, whether there was invasion of surrounding blood vessels, whether the tumor appears on T1-and T2 weighted imaging (T(1)WI and T(2)WI), whether the diffusion was limited, whether there was concurrent bleeding, enhancement rate, and whether there was abdominal fluid accumulation. Intraductal papillary neoplasms of the bile duct were divided into four types according to the morphological classification standards: type I (local bile duct dilation), type II (cystic), type III (free tumor), and type IV (dilated bile duct). The differences in the clinical and MRI features of the four groups of lesions were analyzed. Statistical analysis was performed with a t-test, an analysis of variance, and an χ(2)-test according to the different data. Results: Among the 90 cases with hepatic IPNB, there were 31 cases of type I, 15 cases of type II, 16 cases of type III, and 28 cases of type IV, 41 cases of liver left lobe, 11 cases of right and left lobe liver span, 7 cases of liver right lobes, 2 cases of liver caudate lobe, and 13 cases of hepatic hilar. There were statistically significant differences between the four groups (P < 0.05) in terms of age, clinical symptoms, direct bilirubin, γ-glutamyltransferase, whether they were cancerous, whether they were combined with bile duct stones, whether the liver lobes were atrophying, whether there was limited diffusion, intrahepatic bile duct diameter, and common bile duct diameter. However, there were no statistically significant differences among the four groups in gender, location, carbohydrate antigen 19-9, history of liver disease, history of schistosomiasis, carcinoembryonic antigen, alanine aminotransferase, aspartate aminotransferase, total bilirubin, whether hemorrhage was associated, lesion enhancement rate, whether the hilar/retroperitoneal lymph node was enlarged, whether the bile duct wall was invaded, whether blood vessels were invaded, and whether abdominal fluid was accumulated (P > 0.05). Conclusion: MRI manifestations have certain features for different types of intraductal papillary neoplasm of the bile duct tumors; hence, MRI aids in the diagnosis and differential diagnosis of this disease.

Characteristics of fibres based on secondary raw materials and their use in concrete technology

Different types of fibres in cementitious composites, particularly in concrete, are currently used for a number of reasons. Fibres are being added to improve mechanical properties (especially steel and glass fibres), to increase the durability – to reduce occurrence of microcracks during the concrete aging (mainly synthetic and cellulose fibres), or to increase the fire resistance (polypropylene fibres). Within the study, characterization of different types of alternative fibres (fibres generated during waste recycling that would otherwise end in incinerators or landfills) with possible use in cementitious composites. These were fibres from recycled PET bottles, paper, and mineral wool, whose properties were compared to the traditionally used cellulose and polypropylene fibres. In the experimental part, the thickness, length, shape, and surface of individual fibres were monitored by an optical microscope. Furthermore, the amount of heat of combustion was determined by the calorimetric method, and the differential thermal analysis (DTA) was carried out for determination of the impact of high temperature on monitored fibres. The microstructure of fibres was monitored using a scanning electron microscope. The focus of the experimental study was on fibres usable in concrete and capable of enduring high temperature stress.

Identification and morphological characterization of different types of plastic microparticles

The knowledge of the polymeric composition of microplastics (MPs) is interesting because offers useful information on the resistance, durability, and degradability of these materials, also allowing progress in the control of this contamination. However, there is currently a lack of reliable standardized methods for the identification, and characterization of the plastic microparticles. This work uses different techniques in a complementary manner for the identification, and characterization of MPs that more frequently are found in the environment. A total of 10 types of plastics were collected (polystyrene (PS), polyethylene terephthalate (PETE), polyethylene (PE), high- and low-density polyethylene (HDPE and LDPE, respectively), polyvinyl chloride (PVC), polypropylene (PP), polytetrafluoroethylene (PTFE), Polyamide (PA, Nylon 6,6) and poly-carbonate (PC)) and their chemical identification were analyzed by reflectance-attenuated infrared (FTIR-ATR). Furthermore, the samples were observed using light microscopy, and scan-ning electron microscopy (SEM). Also, staining with 12 different dyes was performed to improve the identification of microplastics. The results of this study revealed that PETE, PE, HDPE and LDPE, whose SEM images exhibited smoothness and flat uniformity of their surface, were not (or less) susceptible to adsorb staining solutions while PP, PA, PVC, and PTFE, were capable of adsorbing the dye solutions.

Definition of the Change Regulations in the Porosity of Semi-permeable Membranes After the Separation of Dairy Raw Materials

Topicality. The article provides a methodology for calculating structural and physical characteristics of semi-permeable membranes after their use in the technological process. During the operation of the membranes, the permeability decreases due to the clogging of their pores with colloidal substances. As a result, it is necessary to obtain data on the distribution of pores on the surface of the investigated ultrafiltration membrane. The aim of the article is to determine the change regularities in the porosity of the semi-permeable membrane, which is used in the technological process of separating dairy raw materials. This will make it possible to predict hydrodynamic properties of the ultrafiltration membrane. Research methods. A strain-measuring (statistical) method is offered, as well as structural and physical characteristics of semi-permeable membranes are determined in the process of membrane filtration of skimmed dairy raw materials. The possibility of constructing mathematical dependencies and methods for determining physical properties and structural analysis of the semi-permeable membrane is highlighted. This technique makes it possible to define not only the surface of the semi-permeable membrane, but also the surface of the polarisation layer of high molecular weight substances. Results. Based on the research results, the dependences of physical properties and structural components of the semi-permeable membrane after the processing of dairy raw materials are constructed. The results of the conducted study show that after ultrafiltration of skimmed dairy raw materials, the pore sizes undergo significant changes. Conclusions and discussion. An increase in the number of pores with a diameter of less than 10 nm is established. The spectrum of the radii of microcapillaries shifts towards decreasing, which occurs as a result of the deposition of particles of the dispersed phase in the microcapillaries. The implementation of research results can take place in industrial conditions, in order to determine the structural and physical characteristics of different types of membranes during the concentration of liquids of different origins for the development of new modifications of filter elements. The conditions for the industrial use of the obtained results are the resolution of issues relating to the laboratory studies of structural and physical characteristics with production results.

MulTFBS: A Spatial-Temporal Network with Multichannels for Predicting Transcription Factor Binding Sites.

Revealing the mechanisms that influence transcription factor binding specificity is the key to understanding gene regulation. In previous studies, DNA double helix structure and one-hot embedding have been used successfully to design computational methods for predicting transcription factor binding sites (TFBSs). However, DNA sequence as a kind of biological language, the method of word embedding representation in natural language processing, has not been considered properly in TFBS prediction models. In our work, we integrate different types of features of DNA sequence to design a multichanneled deep learning framework, namely MulTFBS, in which independent one-hot encoding, word embedding encoding, which can incorporate contextual information and extract the global features of the sequences, and double helix three-dimensional structural features have been trained in different channels. To extract sequence high-level information effectively, in our deep learning framework, we select the spatial-temporal network by combining convolutional neural networks and bidirectional long short-term memory networks with attention mechanism. Compared with six state-of-the-art methods on 66 universal protein-binding microarray data sets of different transcription factors, MulTFBS performs best on all data sets in the regression tasks, with the average R2 of 0.698 and the average PCC of 0.833, which are 5.4% and 3.2% higher, respectively, than the suboptimal method CRPTS. In addition, we evaluate the classification performance of MulTFBS for distinguishing bound or unbound regions on TF ChIP-seq data. The results show that our framework also performs well in the TFBS classification tasks.

Experimental study on the damage characteristics of cyclic disturbance and acoustic emission characteristics of different types of sandstones under high stress in deep mines

AbstractThree sandstone specimens common in rock engineering were selected to study the differences in the mechanical properties of rocks with different lithologies. The development and expansion of the internal cracks in the specimens were observed by combining the simulation system with the acoustic emission system. Through the combination of dynamic and static stresses, the deformation and damage of rocks under deep rock excavation and blasting were simulated. As the results show, the acoustic emission events of specimens with different lithologies under combined static and dynamic cyclic loading can be roughly divided into three phases: weakening, stabilizing, and surging periods. In addition, the acoustic emission characteristics of specimens with different lithologies show general consistency in different compression phases. The degree of fragmentation of specimens increases with the applied stress level; therefore, the stress level is one of the important factors influencing the damage pattern of specimens. The acoustic emission system was used to simulate the deformation and damage of rocks subjected to deep rock body excavation and engineering blasting. Cyclic dynamic perturbations under sinusoidal waves with a frequency of 5 Hz, a loading rate of 0.1 mm/min, a cyclic amplitude of 5 MPa, and a loading rate of 0.1 mm/min were applied to the three rock samples during the experiments. Among them, the fine‐grained sandstones are the most sensitive to the sinusoidal cyclic perturbation, followed by the muddy siltstone and the medium‐grained sandstones. On this basis, the acoustic emission energy release characteristics were analyzed, and the waveform characteristics in the damage evolution of the specimen under dynamic perturbation were studied by extracting the key points and searching for the main frequency eigenvalues.

Experimental Study on the Establishment of Sports Fat Reduction Events for College Students under the Healthy Background

With the continuous increase in the obesity rate among college students, exploring effective strategies for weight loss has become particularly urgent. This article conducts a systematic theoretical analysis and experimental research on the obesity problem among college students in a national health context, deeply analyzing the current health status of college students and elaborating on the negative impacts of obesity on students. By summarizing and analyzing the characteristics of different types of weight loss events, the positive role of exercise in improving students' physical health is highlighted. This study designs and implements a series of exercise weight loss events, using scientific research methods, and systematically analyzes the data collected during the experimental process. The research results show that targeted exercise weight loss events can effectively promote student weight loss, as well as improve their health awareness and quality of life. This article has important theoretical and practical significance for college national health education and weight loss interventions, and plays a positive role in promoting student health.