Variable Characteristics Research Articles

Experimental Study of Mechanical Wave Propagation in Solidifying Cement-Based Composites.

In this paper, a new measurement procedure is presented as an experimental study. In this experimental study, a measurement system using the pass-through pulsed ultrasonic method was used. The pilot application of the measurement setup was to monitor mechanical wave changes during the solidification and hardening of fine-grained cement-based composites. The fine-grained composites had different water-cement ratios. The measured results show apparent differences in the recorded mechanical wave parameters. Significant differences were observed in the waveforms of the amplitude increase in the passing mechanical waves. At the same time, the frequency spectra of the five most dominant frequencies are presented, where the frequency lines are clear, indicating the quality of the hydration process. Based on the results, it can be concluded that the new method is usable for fine-grained cement-based materials but is not limited to that. The advantages of this method are its high variability and non-destructive character. The experimental study also outlines the possible future applications of the pulsed passage ultrasonic method.

Genetic Characteristics of the Env Regions in HIV-1-Infected Subjects in Baoding City, Hebei Province, China.

The envelope glycoprotein (Env) on the surface of the human immunodeficiency virus (HIV-1) is a crucial protein that mediates binding to host cell receptors and subsequent membrane fusion. Env, as the sole target for neutralizing antibodies, holds unique importance in vaccine design. Therefore, analyzing the genetic characteristics of the Env region offers reference data for vaccine and drug design. From December 2021 to December 2022, 145 newly diagnosed, HIV-1-infected individuals in Baoding City were recruited into this study. The HIV-1 env gene sequence was successfully obtained from 142 of the 145 blood specimens, and the sequences were submitted to the Quality Control Tool (http//:HIV-DB Sequence Quality Control Tool (lanl.gov)) to analyze the viral subtype. The coreceptor tropism was predicted using the Geno2pheno web tool with falsepositive rate (FPR) values of 5%-15%, and the net charges of the third variable (V3) loop were calculated by Variable Region Characteristics (lanl.gov). The results showed that half of the patients were infected with the CCR5-tropic virus (50.0%, 71/142). In HIV-1 subtype CRF01_AE infection, the use of CXCR4 is expected to predominate, while in HIV-1 subtype CRF07_BC infection, CCR5 coreceptors are expected to be used predominantly. Sequence analysis of the V3 loop region revealed that subtypes CRF01_AE and CRF07_BC have similar median net charges (~3.0). Furthermore, GPGQ was found to be the major terminal tetrapeptide of the CRF07_ BC and CRF01_AE strains in this study. These findings enhance our understanding of the characteristics of the HIV-1 epidemic and provide important implications for HIV-1 vaccine design and clinical treatment.

Monitoring individualized glucose levels predicts risk for bradycardia in type 2 diabetes patients with chronic kidney disease: a pilot study

Patients with diabetes mellitus (DM) and chronic kidney disease (CKD) exhibit an elevated risk for cardiac arrhythmias, such as bradycardia, which may potentially lead to sudden cardiac death (SCD). While hypoglycemia, defined as a critical drop in glucose levels below the normal range, has long been associated with adverse cardiovascular events, recent studies have highlighted the need for a comprehensive reevaluation of its direct impact on cardiovascular outcomes, particularly in high-risk populations such as those with DM and CKD. In this study, we investigated the association between glucose levels and bradycardia by simultaneously monitoring interstitial glucose (IG) and ECG for 7 days in insulin-treated patients with DM and CKD. We identified bradycardia episodes in 19 of 85 patients (22%) and associated these episodes with personalized low, medium, and high relative glucose levels. Our analysis revealed a significant increase in bradycardia frequency during periods of lowest relative glucose, particularly between 06:00-09:00 and 12:00-15:00. Furthermore, leveraging a Random Forests classifier, we achieved a promising area under the curve (AUC) of 0.94 for predicting bradyarrhythmias using glucose levels and heart rate variability features. Contrary to previous findings, only 4% of bradycardia episodes in our study population occurred at glucose levels of 70 mg/dL or lower, with 28% observed at levels exceeding 180 mg/dL. Our findings not only highlight the strong correlation between relative glucose levels, heart rate parameters, and bradycardia onset but also emphasize the need for a more personalized definition of hypoglycemia to understand its relationship with bradyarrhythmias in high-risk DM and CKD patient populations.

Healthcare resource utilization and related cost of non-HIV comorbidity management in people with HIV in a Spanish cohort from 2007-2016

Objective To estimate the cost and healthcare resource utilization (HRU) associated with the prevalence of comorbidities in people living with HIV (PLWH) in a Spanish cohort over ten years. Methods: Cohort study carried out at the HIV outpatient clinic of the University Hospital Virgen del Rocío based on data collected during 2007-2016. PLWH with at least one follow-up visit were included. Comorbidities were determined by examining diagnostic codes in the electronic medical records. Costs were estimated from hospitalizations, emergency and non-HIV visits, laboratory tests for conditions unrelated to HIV infection, HIV antiretroviral therapy, and other non-HIV diagnostic tests. A linear regression was performed with non-ART costs as the dependent variable and patient characteristics (sex, HIV transmission route, age, CD4, comorbidities, and infection duration) as independent variables. Results: The study included 2,798 PLWH; 83% were men with a mean age of 38.6 years. Overall, 52.5% of PLWH had at least one non-HIV comorbidity and 21.2% had ≥3 comorbidities. The most prevalent comorbidities were hepatitis C (25.3%) and hypertension (22.9%). The presence of comorbidities increased the total healthcare cost up to 80% in PLWH with ≥3 comorbidities compared with those without comorbidities (over a 10-year period (115,867.3€vs 64,290.7€, p < 0.001). The number of comorbidities was linked to higher healthcare costs in PLWH in the adjusted model. Conclusion: Comorbidities raised the total healthcare costs for PLWH, with a greater impact on those with multiple comorbidities compared to those with few or none. Both clinical and economic decision-makers must consider and assess the cost of comorbidities when evaluating HIV treatment guidelines or recommendations.

Research on Force-Saving Mechanism of Cutting Tool with Variable Curvature Directrix Rake Face Configuration

Optimizing the geometric configuration of the tool cutting surface, reducing the resistance in the cutting process and energy consumption, are always a concern. Through the method of bionic design, the directrix function of the longitudinal section of the beaver tooth rake face is extracted, and its variable curvature characteristics are analyzed. Based on this, a turning tool with variable curvature directrix configuration rake face is designed. The cutting force experiment and machining surface quality analysis experiment were carried out with the designed tool and the linear directrix configuration rake face tool respectively. The measured data of the variable curvature directrix configuration rake face tool is better than the linear directrix configuration rake face tool and its drag reduction performance of the tool is verified by experiments. Through the analysis of the working rake angle and shear angle of the tool with variable curvature directrix configuration rake face, the relationship between the parameters of the variable curvature directrix function and the working rake angle, and shear angle has been obtained. By the method of finite element simulation analysis, the stress field in the cutting zone of two different configuration tools has been analyzed. It has been found that the tool with variable curvature directrix rake face has a ‘bending moment’ effect on the tool-chip interface due to its curved surface configuration, and a ‘prying’ effect at the tool tip. These two effects promote the separation of chips from the workpiece and make the cutting process more force-saving. The research of this paper will have reference significance for the design and application of the curved surface configuration rake face tool.

Comparing total suspended solids sensors for improved dewatering of wastewater from non-sewered sanitation

Almost half of the global population relies on non-sewered sanitation, wherein wastewater is treated directly at source or stored onsite and transported by road to treatment facilities (i.e., fecal sludge management). For the protection of public health and environmental ecosystems, efficient non-sewered sanitation systems are needed, in particular in urban areas where infrastructure lags behind rapid urbanization. Wastewater delivered to treatment plants in non-sewered areas has highly variable characteristics, as it arrives in batches from variable infrastructure. Established systems to handle this variability are often land- or energy-intensive, while operation of low-footprint alternatives strongly depends on the wastewater characteristics, making them difficult to implement for highly variable wastewater. The use of sensors could improve process control and increase the robustness of treatment technologies, while reducing the required footprint. However, there are no studies comparing the effectiveness of different sensor methods to measure solids in non-sewered wastewater. We therefore chose six sensors for predicting solids in wastewater and evaluated their performance in variable wastewater with a range of solids content, inorganic particles, salts, and fats. This work demonstrated that the sensors were affected differently by the variable wastewater. Micro-wave and Coriolis-flow technologies were strongly impacted by the addition of fat, oil, and grease as well as salts and inorganics, whereas optical sensors were mostly affected by inorganics, with optical light-attenuation having the lowest overall error, making it the best option for variable wastewater. A low-cost optical light-attenuation sensor had similar accuracy as a more expensive one when the solids content was low, indicating its value for inexpensive monitoring of effluent solids in decentralized settings. Additionally, three sensors were applied for process control of chemically enhanced dewatering with conditioners and geotextiles. Controlling conditioner dosing with sensors in the flocculation tank improved performance with 77% solids reduction, which is in the range of the alternative, time-intensive jar-test method (83% reduction). This study reveals that sensors can be useful in non-sewered wastewater management when the type of input wastewater is accounted for and that even low-cost sensors (<100 USD) can be suitable for many applications.

FORECAST OF THE RESERVOIR DISTRIBUTION ON THE I GAZANBULAG HORIZON OF THE GAZANBULAG FIELD USING ATTRIBUTE ANALYSIS OF 3D SEISMIC DATA

Using of attribute analysis on the 3D seismic cube to predict the distribution area of reservoirs on the I Gazanbulag horizon in the Gazanbulag field of the Ganja Oil and Gas Region has been considered. The article also gives brief information about the region's history of geological and geophysical studies. Also, more perspective attributes were identified to achieve the set goal. This was done by analyzing the obtained results based on the sensitivity of the applied attributes to the separation of the zones selected by the variable characteristics of the wave field. Some longitudinal and transverse attribute sections are presented, to ensure the accuracy of the calculations, well data were also used. As a result, I Gazanbulag horizon is divided into three facies. Keywords: seismic horizon, 3D seismic survey, seismic attribute, attribute cube, facies.

Comparison of various liver cancer staging systems in predicting prognosis after initial transcatheter arterial chemoembolization: a retrospective study from China.

Hepatocellular carcinoma (HCC) constitutes approximately 75-85% of primary liver cancers and is a heavy burden on public health. Many innovative prediction systems have integrated radiomics, artificial intelligence, pathological information, or even genetic information for the stratification and prognosis prediction of patients with HCC. However, these systems still lack practical and clinical applications. Classical HCC staging systems remain the mainstream tool for stratification and prediction of treatment efficacy to date; although, variable characteristics and emphases between different classical HCC staging systems render its clinical selection inconsistent and therefore may be unreliable. In this study, we aimed to compare the predictive performance of classical liver cancer staging systems, including China Liver Cancer (CNLC), Barcelona Clinic Liver Cancer (BCLC), Hong Kong Liver Cancer (HKLC), modified Japanese Integrated Staging (mJIS), modified Cancer of the Liver Italian Program (mCLIP), and Tumor-Node-Metastasis (TNM) staging system, for the efficacy and prognosis of transcatheter arterial chemoembolization (TACE) in HCC patients. A total of 148 patients with HCC who received TACE as the initial therapy between 02/01/2019 and 08/31/2022 were retrospectively included. Patients' clinical information, laboratory and imaging data, were collected. Cox regression analysis was applied to identify independent risk factors for progression-free survival (PFS) and overall survival (OS). Six liver cancer staging systems, including the CNLC, BCLC, HKLC, mJIS, mCLIP, and TNM staging system, were applied for the staging of every enrolled patient. The PFS and OS of patients with HCC following initial TACE in different staging systems were assessed, and the predictive performance of different systems was evaluated using the concordance index. The presence of portal vein tumor thrombus (PVT), alpha fetoprotein (AFP) ≥400 ng/mL, and ineffective initial TACE treatment were independent risk factors for overall disease progression, while the presence of PVT and ineffective initial TACE treatment were independent risk factors for death. In the prediction of PFS and OS, CNLC, BCLC, HKLC, mJIS, and mCLIP all showed good predictive ability, but the predictive ability of the TNM staging system was relatively poor. The CNLC, BCLC, HKLC, mJIS, and mCLIP staging systems provide comparable predictive value for the prognosis after the initial TACE, while the TNM staging system has poor predictive ability due to its exclusion of hepatic function.

Hybrid data-driven and physics-informed regularized learning of cyclic plasticity with neural networks

Abstract An extendable, efficient and explainable Machine Learning approach is proposed to represent cyclic plasticity and replace conventional material models based on the Radial Return Mapping algorithm. High accuracy and stability by means of a limited amount of training data is achieved by implementing physics-informed regularizations and the back stress information. The off-loading of the neural network (NN) is applied to the maximal extent. The proposed model architecture is simpler and more efficient compared to existing solutions from the literature using approximately only half the amount of NN parameters, while representing a complete three-dimensional material model. The validation of the approach is carried out by means of results obtained with the Armstrong–Frederick kinematic hardening model. The mean squared error is assumed as the loss function which stipulates several restrictions: deviatoric character of internal variables, compliance with the flow rule, the differentiation of elastic and plastic steps and the associativity of the flow rule. The latter, however, has a minor impact on the accuracy, which implies the generalizability of the model for a broad spectrum of evolution laws for internal variables. Numerical tests simulating several load cases are presented in detail. The validation shows cyclic stability and deviations in normal directions of less than 2% at peak values which is comparable to the order of measurement inaccuracies.

Fast and Flexible Inference Framework for Continuum Reverberation Mapping Using Simulation-based Inference with Deep Learning

Continuum reverberation mapping (CRM) of active galactic nuclei (AGN) monitors multiwavelength variability signatures to constrain accretion disk structure and supermassive black hole (SMBH) properties. The upcoming Vera Rubin Observatory’s Legacy Survey of Space and Time will survey tens of millions of AGN over the next decade, with thousands of AGN monitored with almost daily cadence in the deep drilling fields. However, existing CRM methodologies often require long computation time and are not designed to handle such large amounts of data. In this paper, we present a fast and flexible inference framework for CRM using simulation-based inference (SBI) with deep learning to estimate SMBH properties from AGN light curves. We use a long short-term memory summary network to reduce the high dimensionality of the light curve data and then use a neural density estimator to estimate the posterior of SMBH parameters. Using simulated light curves, we find SBI can produce more accurate SMBH parameter estimation with 103–105 times speed up in inference efficiency compared to traditional methods. The SBI framework is particularly suitable for wide-field CRM surveys as the light curves will have identical observing patterns, which can be incorporated into the SBI simulation. We explore the performance of our SBI model on light curves with irregular-sampled, realistic observing cadence and alternative variability characteristics to demonstrate the flexibility and limitation of the SBI framework.

Analyzing variable characteristics effects on an unsteady hybrid nanofluid flow over a rotating sphere near a stagnation point with thermal stratification — A comparative study

Analyzing variable characteristics effects on an unsteady hybrid nanofluid flow over a rotating sphere near a stagnation point with thermal stratification — A comparative study

A crawling robot with temperature-controlled variable stiffness feet: strong surface adaptability

Abstract Existing soft robots have not shown the same level of adaptability on diverse terrains when compared to natural animals that possess variable stiffness characteristics. In this paper, utilizing the mutual transformation between the glassy and molten states of rosin materials, temperature-controlled variable stiffness feet (TVSF) are achieved by filling the rosin into an array of soft cavity villi. A single motor is utilized as the vibration-driven actuator of the robot. It is found that the feet stiffness can be changed ranging from 0.6227 N/mm to 0.9611 N/mm, which has a significant impact on the robot’s velocity and follows a nonlinear relationship. A smooth motion surface requires a high-stiffness foot to provide support and stability for the robot, while a rough motion surface necessitates a low-stiffness foot to reduce friction and resistance allowing for quick movement for the driving voltage of 1.6 V. Furthermore, the TVSF enable stable operation on complex surfaces, including a 30°slope, pipes, and pothole surfaces. This research provides a new technological approach to designing and manufacturing variable stiffness robots with enhanced surface adaptability.

Reactive chlorine-, sulfur-, and nitrogen-containing volatile organic compounds impact atmospheric chemistry in the megacity of Delhi during both clean and extremely polluted seasons

Abstract. Volatile organic compounds (VOCs) significantly impact the atmospheric chemistry of polluted megacities. Delhi is a dynamically changing megacity, and yet our knowledge of its ambient VOC composition and chemistry is limited to few studies conducted mainly in winter before 2020 (all pre-COVID-19). Here, using a new extended volatility range high-mass-resolution (10 000–15 000) proton transfer reaction time-of-flight mass spectrometer, we measured and analysed ambient VOC mass spectra acquired continuously over a 4-month period, covering “clean” monsoon (July–September) and “polluted” post-monsoon seasons, for the year 2022. Out of 1126 peaks, 111 VOC species were identified unambiguously. Averaged total mass concentrations reached ∼ 260 µg m−3 and were &gt; 4 times in the polluted season relative to the cleaner season, as driven by enhanced emissions from biomass burning and reduced atmospheric ventilation (∼ 2). Among 111, 56 were oxygenated, 10 contained nitrogen, 2 chlorine, 1 sulfur, and 42 were pure hydrocarbons. VOC levels during polluted periods were significantly higher than most developed world megacities. Methanethiol, dichlorobenzenes, C6 amides, and C9 organic acids/esters, which have previously never been reported in India, were detected in both the clean and polluted periods. The sources were industrial for methanethiol and dichlorobenzenes, purely photochemical for the C6 amides, and multiphase oxidation and partitioning for C9 organic acids. Aromatic VOC / CO emission ratio analyses indicated additional biomass combustion/industrial sources in the post-monsoon season, along with year-round traffic sources in both seasons. Overall, the unprecedented new information concerning ambient VOC speciation, abundance, variability, and emission characteristics during contrasting seasons significantly advances current atmospheric composition understanding of highly polluted urban atmospheric environments like Delhi.

Enhanced Photocatalytic Degradation of Environmental Pollutants Using a Triphenylamine-Based Polymer: Synthesis, Characterization, and Mechanistic Insights.

Conjugated porous organic polymers have sparked growing research attention as photocatalysts owing to their high surface area, tunable pores, and capacity to collect and transfer light energy via their delocalized backbone. However, the synthesis methods for preparing these polymers require difficult experimental setups, such as high polymerization temperature, inert atmosphere, and use of transition metal catalysts. In the present work, a triphenylamine-based conjugated porous polymer (TPA-BPA) has been synthesized employing tris(4-aminophenyl)amine (TPA) and biphenyldicarboxaldehyde (BPA) as precursors via a one-pot Schiff base reaction in ambient conditions in the absence of the metal catalyst. The synthesized TPA-BPA polymer has been characterized using Fourier transform infrared spectroscopy, 13C cross-polarization magic angle spinning nuclear magnetic resonance, Brunauer-Emmett-Teller (BET), thermogravimetric analysis, field emission scanning electron microscopy, high-resolution transmission electron microscopy, valence band X-ray photoelectron spectroscopy, X-ray photoelectron spectroscopy, cyclic voltammetry, powder X-ray diffraction, electron paramagnetic resonance (EPR), and diffuse reflectance spectroscopy (DRS) techniques. The DRS analysis revealed that TPA-BPA has an optical band gap of 2.1 eV, demonstrating its semiconductive nature. The EPR study has shown that the synthesized polymer exhibits an intense radical signal at g = 2.00, confirming free radical generation upon photoexcitation and facilitating the breakdown of organic contaminants by photocatalysis. TPA-BPA possesses an exceptional porous structure with a surface area of 36 m2/g, as confirmed by BET studies, and high thermal stability up to 420 °C. It has been confirmed by photocatalytic studies that TPA-BPA shows effective degradation of methyl orange (92%), Congo red (91.5%), tobramycin (96%), and hydroquinone (85%) under visible light irradiation in 60 min. Owing to these observations, TPA-BPA can be an excellent candidate as a photocatalyst for environmental remediation. These findings pave the way for large-scale manufacturing of metal-free conjugated porous polymers as photocatalysts with variable photoelectrical characteristics.

Probing the High-frequency Variability of NGC 5044: The Key to Active Galactic Nucleus Feedback

The active galactic nucleus (AGN) feeding and feedback process in the centers of galaxy clusters and groups is still not well understood. NGC 5044 is the ideal system in which to study AGN feedback. It hosts the largest known reservoir of cold gas in any cool-core galaxy group, and features several past epochs of AGN feedback imprinted as cavities in the X-ray-bright intragroup medium, as well as parsec-scale jets. We present Submillimeter Array, Karl G. Jansky Very Large Array, James Clerk Maxwell Telescope, and Atacama Large Millimeter/submillimeter Array high-frequency observations of NGC 5044 to assess the time variability of the millimeter-wave band emission from the accretion disk, and quantify the spectral energy distribution (SED) from the radio to submillimeter band. The SED is well described by an advection-dominated accretion flow (ADAF) model and self-absorbed jet emission from an aging plasma with τ ∼ 1 kyr. We find a characteristic variability timescale of 150 days, which constrains the ADAF emission region to about 0.1 pc, and the magnetic field to ∼4.7 mG in the jets and 870 G in the accretion disk. Longer monitoring/sampling will allow to understand if the underlying process is truly periodic in nature.

Correlation Analysis of Soil Microbial Communities and Physicochemical Properties with Growth Characteristics of Sageretia thea Across Different Habitats.

This study aimed to investigate the growth characteristics of Sageretia thea and analyze the correlations between soil physicochemical properties and microbial communities in its native habitats. Soil physicochemical properties were characterized by organic matter (0.37-36.43%), available phosphate (57.96-315.90 mg/kg), potassium (0.11-1.17 cmol+kg-1), calcium (1.23-25.97 cmol+kg-1), magnesium (0.43-15.01 cmol+kg-1), sodium (0.04-6.16 cmol+kg-1), and pH (4.68-7.05), indicating slightly acidic to neutral conditions. S. thea exhibited variable growth characteristics across habitats; leaf length and width were largest in Jangnam-ri and Hacka-ri, respectively, whereas Docheong-ri promoted higher fruit growth. The soil microbial community composition was dominated by Proteobacteria, Actinobacteria, and Acidobacteria at the phylum level (76.09%) and by Alphaproteobacteria, Actinobacteria_c, and Vicinamibacter_c at the class level (40%). Soil physicochemical properties were significantly correlated with Actinobacteria, Acidobacteria, and Chloroflexi at the phylum level, and all microbial groups except Spartobacteria at the class level. Furthermore, growth characteristics were significantly correlated with all microbial communities except Acidobacteria and Firmicutes at the phylum level, and Acidobacteria, Thermoleophilia, and Rubrobacteria at the class level. These findings provide a foundation for developing efficient cultivation techniques for S. thea based on its soil microbiome and habitat conditions.

Multiple Keratoacanthomas Associated with Genetic Syndromes: Narrative Review and Proposal of a Diagnostic Algorithm.

Keratoacanthoma (KA) is a relatively common, fast-growing epithelial tumour, with characteristic behaviour and clinical variability. Although it appears as a solitary lesion in a majority of cases, multiple KAs do occur, secondary to skin exposure to ultraviolet radiation, chemical carcinogens or certain medications, but may also be associated with various genetic syndromes. Thus, multiple KAs may serve as an early clinical alarm sign. Prompt diagnosis of the underlying cause and identification of the mechanism of development are critical for the secondary prevention of associated organ disorders or neoplasias, the improvement of patient quality of life and familial counselling. Although researchin this field has seen important progress in the last few years, there are still many pathogenic processes that have not been elucidated. Additionally, the literature on this topic is limited to individual case reports and small case series, making it difficult for clinicians to parse available data and select the essential information. Therefore, this work aims to review current knowledge, summarizing existing studies, with focus on multiple KAs associated with genetic syndromes, and proposes a diagnostic algorithm for these rare cases to help guide clinicians in their practice. Lastly, we aim to highlight the main gaps in understanding the underlying mechanisms and suggest further research avenues.

Trends, Patterns and Determinants of Family Structure in India: A Perspective of Three Decades

In India, the existing knowledge on family structure is based on small-scale studies or research before 2000 and indicates remarkable changes from the widely perceived notion of the family system in the country. The present study assesses the trends, patterns, and determinants of family structure in India using large-scale nationally representative National Family Health Surveys (NFHS) data over the last three decades (1992/93–2019/21). Data from all five rounds of NFHS were analyzed, keeping the family structure as the dependent variable and several socio-economic characteristics as independent variables. Univariate, bivariate, and multivariate analyses were performed using Stata. In the last three decades, single-person, nuclear pair, lineally extended, and lineally broken extended families had increased, while nuclear, supplemented nuclear, broken nuclear, and collaterally extended families had declined in the country. Gender, schooling, caste, and religion of the household head, wealth status of the household, household ownership of agricultural land, place of residence, and region of the household were significantly associated with the prevalence of single person, nuclear pair and collaterally extended family in India.

Heat transfer from a cylindrical heater to a medium with variable thermophysical characteristics and heat source power

The formulation and solution of the problem of non-stationary thermal conductivity in a composite material with variable thermophysical characteristics are considered. Density, heat capacity, thermal conductivity, as well as the power of the heat source due to the hydration reactions of the binder components change during the concrete hardening process. The heat transfer problem is formulated for the general case when there are no calculation formulas for thermophysical transfer coefficients. The “microprocess method” was used to calculate the dynamics of the temperature field. According to this method, the space from the outer surface of the heater is modeled by a system of successively located “rings”. When moving from the previous “ring” to the next one, the charge in the transfer coefficients and the power of the volumetric heat source were taken into account. At the same time, the initial and boundary conditions were corrected. The boundary value problems are formulated in the form of a differential equation of non-stationary heat transfer with an arbitrary initial distribution of transfer potentials, Dirichlet boundary conditions, and a heat source in the form Po=f(Fo).The obtained solutions are analyzed for some particular cases. Prospects for further theoretical and experimental research are determined.

ALFusion: Adaptive fusion for infrared and visible images under complex lighting conditions

In the task of infrared and visible image fusion, source images often exhibit complex and variable characteristics due to scene illumination. To address the challenges posed by complex lighting conditions and enhance the quality of fused images, we develop the ALFusion method, which combines dynamic convolution and Transformer for infrared and visible image fusion. The core idea is to utilize the adaptability of dynamic convolution coupled with the superior long-range modeling capabilities of the Transformer to design a hybrid feature extractor. This extractor dynamically and comprehensively captures features from source images under various lighting conditions. To enhance the effectiveness of mixed features, we integrate an elaborate multi-scale attention enhancement module into the skip connections of the U-Net architecture. In this module, we use convolutional kernels of various sizes to expand the receptive field and incorporate an attention mechanism to enhance and highlight the combined use of dynamic convolution and the Transformer. Considering the performance in advanced visual tasks, an illumination detection network is integrated into the loss function, strategically balancing the pixel fusion ratio and optimizing visual impacts under varied lighting conditions, leveraging information from different source images. The fusion results indicate that our method consistently delivers superior background contrast and enhanced texture and structural features across diverse lighting conditions. Ablation and complementary experiments have been conducted, further affirming the effectiveness of our proposed method and highlighting its potential in advanced visual tasks.