The current work investigates the auxetic tensile deformation behavior of the inversehoneycomb structure with 5 × 5 cells made of biodegradable poly(butylene adipate-coterephthalate) (PBAT). Fused deposition modeling, an additive manufacturing method, produced such specimens. Residual stress (RS) and warpage, more or less, always exist in such specimens due to layer-by-layer fabrication, i.e., repeated heating and cooling. The RS influences the auxetic deformation behavior, but its measurement is challenging due to the very fine structure. Instead, the finite-element(FE)-based process simulation realized by an ABAQUS plug-in numerically predicts the RS and warpage. The predicted warpage shows a negligible slight deviation compared to the design topology. This process simulation also delivers the temperature evolution of a small volume material, revealing the local cyclic heating and cooling. The achieved RS serves as the initial condition for the FE model used to investigate the auxetic tensile behavior. With the outcomes from FE calculation without considering RS at hand, the effect of the RS on the deformation behavior is discussed for the global force-displacement curve, the structural Poisson’s ratio evolution, the deformed structural status, the stress distribution, and evolution, where the first three and the warpage are also compared with experimental results. Furthermore, the FE simulation can easily provide the global stress-strain flow curve with the total stress calculated from the elemental ones.

The weakness of the dispersion-managed link combined with optical phase conjugation to compensate for optical signal distortion caused by chromatic dispersion and nonlinear Kerr effect of standard single mode fiber is its limited structural flexibility. We propose dispersion map that can simultaneously compensate for the distorted wavelength division multiplexed signal while increasing the configurational flexibility. Each residual dispersion per span (RDPS) in the former half of the proposed link is randomly determined, and in the latter half, the arrangement order of RDPS is the same as or inverted in the former half. We confirm that the dispersion maps in which the RDPS distribution pattern in the latter half is opposite to the arrangement order in the former half are more effective in compensation, and rather, the compensation effect is better than in the dispersion map of the conventional scheme. The notable result of this paper is that the increase of flexibility can be achieved through random arrangement of RDPS in the former half, and the compensation improvement can be achieved by through inverse arrangement in the latter half which make the distribution profile of each half link roughly symmetric with respect to the midway optical phase conjugator.

With the increasing availability of large digitized fine art collections, automated analysis and classification of paintings is becoming an interesting area of research. However, due to domain specificity, implicit subjectivity, and pervasive nuances that vaguely separate art movements, analyzing art using machine learning techniques poses significant challenges. Residual networks, or variants thereof, are one the most popular tools for image classification tasks, which can extract relevant features for well-defined classes. In this case study, we focus on the classification of a selected painting 'Portrait of the Painter Charles Bruni' by Johann Kupetzky and the analysis of the performance of the proposed classifier. We show that the features extracted during residual network training can be useful for image retrieval within search systems in online art collections.

Benign Paroxysmal Positional Vertigo (BPPV) represents the most frequent cause of peripheral vertigo. In most cases it is successfully treated by canalith repositioning procedure (CRP), but it is often followed by a continuous lightheadedness in absence of vertigo or nystagmus (residual dizziness, RD). Our aim is to describe the clinical effectiveness and the urine metabolomics profile treating these patients by a polyphenol compound supplementation. We enrolled 30 patients reporting RD after BPPV successfully treated using CRP. A supplementation with a Polyphenol compound was administered for 60 days, and patients were evaluated after 30 and 60 days of treatment by a self-administered questionnaires (Visual Analog Scales for Dizziness and Nausea, Dizziness Handicap Inventory, DHI) and by urine metabolomics analysis performed by 1H-NMR spectroscopy and multivariate followed by univariate analysis. Most patients reported an excellent or good efficacy of RD with a significant decrease for VAS and DHI values. The metabolomics analysis identified six significant metabolites related to the treatment: 1-methylnicotinamide, anserine, Hippurate, lysine, methyl succinate, and urea indicating an inflammatory activities and antioxidant properties of the polyphenol compound. These preliminary data suggest that supplementation with a polyphenol compound cold induces some metabolic changes that can help recover RD. However, the future steps will require confirmation with a more significant cohort of patients and an extension of the metabolomic evaluation to other problems concerning the different clinical aspects of BPPV, such as the high relapse found in a high percentage of patients.

In this paper, we introduce ResNetMF, a groundbreaking approach that harnesses the power of residual network matrix factorization to revolutionize recommendation systems. ResNetMF integrates residual networks, renowned for their ability to capture intricate patterns and features, with matrix factorization techniques that excel in modelling user-item interactions. This fusion presents a novel solution that surpasses the limitations of traditional recommendation systems. Through comprehensive experimentation and evaluation of diverse datasets, ResNetMF demonstrates remarkable enhancements in recommendation accuracy and efficiency. By effectively capturing both linear and nonlinear relationships in user-item interactions, ResNetMF provides superior recommendation quality. The outcomes from experiments unequivocally highlight the superiority of ResNetMF over existing state-of-the-art recommendation approaches, thereby validating its innovative nature and underscoring its potential to shape the future of recommendation systems. Through the integration of the deep residual network, ResNetMF approach facilitates the training of neural networks, enabling them to explore the underlying data layers more comprehensively. Extensive experimentation and evaluation across various datasets provide compelling evidence for the superiority of ResNetMF. Moreover, the proposed method utilized natural language processing (NLP) techniques for targeted information dissemination in recommendation systems, emphasizing the importance of personalized and relevant recommendations for user satisfaction and engagement.

Infrared and visible image fusion technologies are used to characterize the same scene by diverse modalities. However, most existing deep learning-based fusion methods are designed as symmetric networks, which ignore the differences between modal images and lead to the source image information loss during feature extraction. In this paper, we propose a new fusion framework for the different characteristics of infrared and visible images. Specifically, we design a dual-stream asymmetric network with two different feature extraction networks to extract infrared and visible feature maps respectively. The transformer architecture is introduced in the infrared feature extraction branch, which can force the network to focus on the local features of infrared images while still obtaining their contextual information. And the visible feature extraction branch uses residual dense blocks to fully extract the rich background and texture detail information of visible images. In this way, it can provide better infrared targets and visible details for the fused image. Experimental results on multiple datasets indicate that DSA-Net outperforms state-of-the-art methods in both qualitative and quantitative evaluations. In addition, we also apply the fusion results to the target detection task, which indirectly demonstrates the fusion performances of our method.

This paper investigates the effect of shot peening on the strength and corrosion properties of EN AW 6082-T651 aluminium alloy. Surface roughness, microhardness, residual stresses and corrosion performance were investigated and compared with the untreated aluminium alloy. Cracks and delaminations in the surface layer can only be seen on the treated specimens at a working pressure of 4 bar and 8 bar, while no such effect was observed at a working pressure of 1.6 bar. The effect of dislocation densification was confirmed by the microhardness measurement of the hardened layer, where microhardness increased by up to 23 % compared to the untreated aluminium alloy. Shot peening also results in a deeper layer with higher compressive residual stresses compared to untreated specimens. With higher working pressure, surface roughness increases, which can promote localized pitting corrosion. However, all treated specimens improve the corrosion resistance and have a lower degree of anodic dissolution. The current density of the shot peened specimen with the lowest surface roughness was more than twice lower than that of the untreated specimen.

The inverse finite element method (iFEM) is a novel method for reconstructing the full-field displacement of structures by discrete measurement strain. In practical engineering applications, the accuracy of iFEM is reduced due to the positional offset of strain sensors during installation, and errors in structural installation. Therefore, coarse and fine two-stage calibration (CFTSC) method is proposed to enhance the accuracy of the reconstruction of structures. Firstly, the coarse calibration is based on a single-objective particle swarm optimization algorithm to optimize the displacement-strain transformation matrix related to the sensor position. Secondly, as selecting different training data can affect the training effect of self-constructed fuzzy networks, this paper proposes to screen the appropriate training data based on residual analysis. Finally, the experiments of the wing integrated antenna structure verify the efficient of the method on the reconstruction accuracy of the structural body displacement field.

Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of death worldwide and the risk of a major cardiovascular event is highest among those with established disease. Ongoing management of these patients relies on the accurate assessment of their response to any prescribed therapy, and their residual risk, in order to optimize treatment. Recent international guidelines and position statements concur that the plasma concentration of apolipoprotein B (apoB) is the most accurate measure of lipoprotein associated ASCVD risk. This is especially true for the growing number of individuals with diabetes, obesity or the metabolic syndrome, and those on statin therapy. Most guidelines, however, continue to promote LDL-C as the primary risk marker due to uncertainty as to whether the greater accuracy of apoB is sufficient to warrant a paradigm shift. Recommendations regarding apoB measurement vary, and the information provided on how to interpret apoB results is sometimes insufficient, particularly for the non-lipid specialist. Misinformation regarding the reliability of the assays is also frequently repeated despite its equivalent or better standardization than many other diagnostic assays. Thus, demand for apoB testing is relatively low, which means there is little incentive to increase its availability or reduce its cost. In this review, we examine the results of recent clinical outcomes studies and meta-analyses on the relative values of apoB, LDL-C and non-HDL-C as markers of ASCVD risk. Although there is seemingly minimal difference among these markers when only population-based metrics are considered, it is evident from our analysis that, from a personalized or precision medicine standpoint, a great many individuals would benefit, at a negligible total cost, if apoB measurement were better integrated into the diagnosis and treatment of ASCVD.

Grapevine leafroll disease (GLRD) is the most globally prevalent and destructive disease complex responsible for significant reductions in grape yield and quality as well as wine production. GLRD is associated with several positive-strand RNA viruses of the family Closteroviridae, designated grapevine leafroll-associated viruses (GLRaVs). However, the specific etiological role of any of these GLRaVs in GLRD has not been demonstrated. Even though GLRaV-3 is considered the chief GLRD agent, little is known about the molecular, cellular and pathological properties of this virus. Such knowledge gap is due to multiple factors, including unavailability of biologically active virus cDNA clones and the lack of reliable experimental systems for launching grapevine infection using such clones. In this work, we have tested four methods for inoculating tissue cultured grapevine plantlets with cDNA clones of GLRaV-3: i) vacuum agro-infiltration; ii) agro-pricking; iii) agro-drenching and iv) agro-injection. We have shown that vacuum agro-infiltration was the most effective among these methods. Further, we examined the impacts of different experimental conditions on the survival and infectivity rate of grapevines after infiltration. To verify the infectivity rate for different treatments, we used RT-PCR, RT-qPCR, and Western blotting. We have found that humidity plays a critical role in the survival of plantlets after agro-infiltration and that the use of RNA silencing suppressor, and dormancy treatment both had strong effects on the infection rates. To our best knowledge, the experimental protocol reported here is the most effective system for launching infection of grapevine using cDNA clones of grapevine viruses featuring up to 70% infection rate. This system has strong potential to facilitate grapevine virology research including fulfillment of Koch’s postulates for GLRD and other major virus diseases as well as the molecular, cellular, and pathological properties of GLRaVs and potentially other important grapevine viruses.

ABSTRACT Heavy metals have been classified as dangerous environmental pollutants. Interest in feasible ways to reduce heavy metals pollution is a noble goal. Adsorption is an effective method based on its effectiveness and low- cost. Nowadays, low-cost bio-sorbents have been utilized to replace costly expensive adsorbents. Rich cellulose materials are effective heavy metal adsorbents, and their performance can be enhanced via chemical modification. The present work reviews the steady progress in the utilization of agriculture by-product wastes as heavy metal bio-sorbent. The unique advantages of these by-products such as renewability, abundance, simple processing, and low cost, justifier this work. The results confirm that the chemically treated agro-wastes exhibit high- removal efficiency (reaches 95% in most cases). The adsorption isotherm studies indicate that the concentration of the metal ions has a significant effect on the adsorption process. The Freundlich model provides a physical adsorption model of the metal ions on the bio-sorbent surface. Langmuir isotherm offers an estimate of the effect of different factors on the efficiency of the process. The adsorption kinetics studies offer an idea of reaction pathways including the adsorption mechanism and the efficiency of the metal ion removal. Applying the pseudo-first-order and pseudo-second-order models describes the adsorption kinetics. This information can be utilized in developing effective strategies to remove heavy metal ions using chemically treated agro-waste. The data confirmed that chemical modification is a significant parameter in the efficiency of metal ion removal. The feasibility and effectiveness of using these cellulosic by-products as bio-sorbent should be given attention and encouraged.

The popularity and development of social media has made it more and more convenient to spread rumors, and it has become especially important to detect rumor information from massive amounts of information. Most of the traditional rumor detection methods use content characteristics or propagation structure to mine rumor characteristics, ignoring the fusion characteristics of content and structure and their interaction characteristics. Therefore, a novel rumor detection method based on heterogeneous convolutional networks is proposed. Firstly, this paper constructs a heterogeneous map of joint rumor content and propagation structure to explore the interaction between content and propagation structure during rumor propagation and obtain rumor representation. On that basis, this paper uses the deep residual graph convolutional neural network to construct the content and structure interaction information of the current network propagation model. Finally, this paper uses the two datasets of Twitter15 and Twitter16 to verify the proposed method. Experimental results show that the proposed method has higher detection accuracy than the traditional rumor detection method.

The article is devoted to the analytical and numerical study of the pattern of propagation and attenuation, due to Coulomb friction, of shear waves in an infinite thin elastic plate with a circular orifice of radius lying on a rough base. In the field of motion, an exact analytical solution of a nonlinear boundary value problem for tangential stresses and transversal velocities is obtained in quadratures by the method of Laplace transformations. It turned out that the complete exhaustion of the wave front of a strong rupture occurs at a finite distance from the center of the hole and an elementary formula is given for this distance (the case of tangential forces instantly applied to the orifice boundary, and then constant in time, is considered). For various ratios of the magnitude of the limiting friction force to the amplitude of the applied load, the trailing wave fronts are obtained, after which a state of static equilibrium between the elastic and friction forces with a nonlinear distribution of residual deformations is established in the region .

Residual sugars (RS) in wine are the sugars that remain in a wine after fermentation is complete. In some wine styles, such as semi-dry wines, the accurate measurement of the RS concentration is critical for both qualitative and legislative reasons. Brix, measured by a simple refractometer, can give a good estimation of the RS concentration in the must, but during fermentation, the presence of alcohol leads to inaccurate sugar measurements. In order to measure the RS accurately, other more precise techniques are used, most of which are expensive or require professional skills. Therefore, novel approaches for rapid, easy, and practical measurements for estimating the sugar content were suggested over the years. However, most of these methods do not supply an actual measurement of RS but rather give brix values, and those that measure RS involve special equipment, which is less relevant for small wineries. This study suggests a novel model for predicting and controlling the wine's residual sugar. The data the model uses is the initial brix of the must before fermentation and its density during fermentation. The model was created by measuring actual residual sugars during the fermentation of natural and synthetic musts, with various degrees of initial brix levels, while simultaneously measuring their densities and correlating the two measurements. Linear regression between the residual sugar of the wine and its density was obtained for all treatments and repetitions (i.e., different values of must initial brix) with R² values above 0.97. Using the model, one can calculate (before commencing the fermentation) the density values at which the fermentation will reach a particular desired residual sugar value for a specific initial brix level; the model is applicable for the fermentation conditions used in this work, i.e., brix levels of 18-27˚Bx, Saccharomyces cerevisiae strains (fx-33 and fx-10) in common conditions of fermentation regarding temperature and aeration.

Effects and interactions of incubation time and chick preplacement holding time on mortality at placement, utilization of yolk sac, crop filling rate, early feeding–drinking behavior and broiler live performance were investigated. Ross 308 broiler hatching eggs from a 39-week-old flock were set in two identical setters in a commercial hatchery,with setting time 12 hours earlier in one machine. At the end of incubation, chicks were removed from the hatchers at the same time. Thus, incubation times were either 504 h (normal incubation time (NIT) treatment) or 516 h (longer incubation time (LIT) treatment). After pull time, chicks from each incubation time group were subjected to either 6, 24, 48, 60 or 72 h preplacement holding times. At placement, chicks were given access to feed and water. In total, 19,200 chicks were randomly assigned to a total of 10 subtreatment groups (2 incubation times × 5 preplacement holding times). Therefore, a total of 1,920 chicks were used in each subtreatment group for the grow-out period in a commercial broiler house. An interaction was found between incubation time and preplacement holding time for residual yolk sac (RYS) weight (g, %) (p < 0.001). RYS weight was greater at pull time and at 6 and 24 h of preplacement holding time in the NIT treatment compared to the LIT treatment, while differences were no longer evident at 48–72 h. The lowest percentage of chicks with full crops and eating activity was observed in the shortest preplacement holding time (6 h) group at 3 h after placement. As expected, the initial BW at placement clearly decreased with increasing duration after the pull time (p < 0.05) with the highest and lowest weights were found in the 6 and 72 h holding time treatments respectively. This BW difference was still evident at 35 d after placement and chicks held for the longest period after the pull time (72 h) showed the lowest BW (p < 0.001). However, there was no significant difference between the 6 and 60 h preplacement holding times. Mortality during the first 7 d after placement increased only when the preplacement holding time was extended to 72 h (p = 0.031). Similar to the 7 d results, chicks held for 72 h exhibited higher 0-35 day mortality compared to those held for 6 or 24 h (p = 0.028). Neither BW nor mortality was affected by incubation time treatment at 35 d after placement (p > 0.05). It can be concluded that there were no significant differences in average BW and mortality, up to and including a 60-h holding time under thermal comfort conditions, but a 72-h preplacement holding time resulted in final BW and mortality being negatively affected. In addition, LIT tended to have a beneficial effect on BW and mortality compared to NIT when the preplacement holding time was shorter (6–24 h) but had a negative effect for extended holding times (48–72 h).

With the rise of piano teaching in recent years, many people have joined the team of piano learners. However, the expensive cost of manual instruction and the unique one-on-one teaching model have made piano learning an extravagant event. Most existing approaches based on the audio modality aim to evaluate piano players' skills. Unfortunately, these methods ignored the information contained in the video, which led to a one-sided and simplistic evaluation of the piano player's skills. More recently, multimodal-based methods are proposed to assess the skill level of piano players using both video and audio information. However, existing multimodal approaches use shallow networks to extract video and audio features, which are deficient in extracting complex spatio-temporal and time-frequency features from piano performance. Furthermore, the fingering and the pitch-rhythm information of the piano performance is contained in the spatio-temporal and time-frequency features, respectively. In the paper, we propose a ResNet-based audio-visual fusion model that combines video and audio features to assess the skill level of piano players. Firstly, ResNet18-3D is used as the backbone network for our visual branches, which can extract feature information from the video data. Then, we consider ResNet18-2D as the backbone network of the aural branch and extract the feature information from the audio data. The extracted video features are fused with the audio features to generate multimodal features for the final piano skill evaluation. The experimental results on the PISA dataset show that our proposed audio-visual fusion model, with a validation accuracy of 70.80%, outperforms the state-of-the-art methods in both performance and efficiency. Then, we also explore the impact of different layers of ResNet on model performance, and the experimental results show that the audio-visual fusion model dealing with the piano skill assessment problem can make full use of both feature information when the number of video features is close to the number of audio features.

Temporal downscaling of gridded geophysical data is essential for improving climate models, weather forecasting, and environmental assessments. However, existing methods often could not accurately capture multi-scale temporal features, affecting their accuracy and reliability. To address this issue, we introduce an Enhanced Residual U-Net architecture for temporal downscaling. The architecture, which incorporates residual blocks, allows for deeper network structures without the risk of overfitting or vanishing gradients, thus capturing more complex temporal dependencies. The U-Net design inherently could capture multi-scale features, making it ideal for simulating various temporal dynamics. Moreover, we implement a flow regularization technique with advection loss to ensure that the model adheres to physical laws governing geophysical fields. Our experimental results across various variables within the ERA5 dataset demonstrate an improvement in downscaling accuracy, outperforming other methods.

In this study, the autofrettage method, which is used to increase the durability of cylindrical parts, was applied to a barrel made of steel material according to the AISI 4340 standard. Assuming that the barrel works continuously under the pressure of 400 MPa, optimum autofrettage was performed. The stresses occurring on the barrel before and after autofretage were calculated. Additionally, analytical equivalent stress values (Von-Mises) formed on the part's wall were compared with numerical analysis results obtained with a commercial finite element program ANSYS®, and their compatibility was examined. As a result of the calculations and analysis performed, it was observed that autofretage has positive effect on increasing the pressure carrying capacity of the barrel. After autofrettage the cylindrical part, it was determined that the Von-Mises stress values formed in the part wall changed and these stresses took the lowest value at a point (elastic-plastic interface). It has been evaluated that this point gives the optimal autofretage pressure value for a certain operating pressure. After the autofrettage application, it was determined that the Von-Mises Stress value in the barrel wall decreased by 25.27 % and the pressure carrying capacity of the barrel increased without any design or dimensional change. It has been seen that the analytical and numerical analysis results are consistent with each other, and it is expected that this study will guide and contribute to the studies to be conducted on increasing the strength or lightening the weight of the parts.

The chromatographic conditions were optimized using headspace gas chromatography, and a simple and rapid method was established for the simultaneous determination of five residual solvents in ursodeoxycholic acid raw materials. The corresponding quality standards were revised. The results showed that the concentration of methanol ranged from 0.06mg/ml to 0.3mg/ml, and the concentrations of acetone, tert butanol, ethyl acetate, and triethylamine showed a good linear relationship with the peak area within the range of 0.1mg/ml to 0.5mg/ml (r=0.999); The quantitation limits for methanol, acetone, tert-butanol, ethyl acetate, and triethylamine were 4.2, 0.9, 1.5, 1, and 0.1 μg/ml, respectively, with detection limits of 1.2, 0.25, 0.025, 0.3, and 0.025 μg/ml, respectively. The recovery rates of each solvent ranged from 92.9% to 106.0%, with RSD% (n=9) less than 3.8%; The method exhibited good repeatability, with RSD% (n=6) less than 2.5%. Furthermore, the durability is good. The established method is simple, accurate, specific, and highly sensitive, and can be used for the simultaneous and rapid determination of five residual solvents in ursodeoxycholic acid raw materials.

Climate change impacts threaten sustainable development efforts. The magnitude of the impacts, however, varies with socio-ecological characteristics of locations. This is the reason there is con-sensus on the necessity for climate change adaptive capacity building that is country driven, based on and responsive to local needs. However, information on context specific capacity building needs in developing countries is not readily available. The objective of this study was to establish location specific awareness, training, educational, research and technology capacity building needs for climate change adaptation among small-holder farmers in Uganda. Structured interviews were undertaken with 465 households from five agro-ecological zones selected based on the level of vulnerability of agricultural systems to the main climate variation and change hazards. Results reveal substantial capacity building needs in all the zones. Majority of the farmers needed capacity building for interventions on soil water conservation practices for adapting to drought and un-predictable rainfall. For all zones, education, research, and technology were perceived as key needs. However, the needs varied among zones. These results demonstrate the importance of context specificity in adaptation efforts. The study provides agro-ecological and social system specific in-formation for climate change adaptation planning and policy interventions for effective capacity building

This study examined the impact of Vibration-Assisted Drilling (VAD) on hole quality and residual stress in Ti-6Al-4V ELI material. Ti-6Al-4V ELI possesses excellent mechanical properties but presents challenges in machining, including chip evacuation, burr formation, and elevated cutting temperatures. VAD, particularly Low-Frequency Vibration-Assisted Drilling (LF-VAD), has been explored as a potential solution to address these issues. The research com-pares LF-VAD with conventional drilling (CD) under various cutting and cooling conditions. LF-VAD exhibits higher maximum cutting forces under specific conditions, which result in accel-erated tool wear. However, it also demonstrates lower RMS (Root Mean Square) forces com-pared to CD, offering better control over chip formation, reduced burr formation, and improved surface roughness within the hole. Furthermore, LF-VAD generates greater compressive residual stresses on the hole's inner surface compared to CD, suggesting enhanced fatigue performance. These findings indicate that LF-VAD holds promise for improving hole quality, fatigue life, and overall component durability in Ti-6Al-4V machining applications.

Large aluminum alloy ring forgings are the core components of heavy-duty rocket fuel storage tanks, and the large residual stress inside the rings leads to poor shape accuracy of large thin-walled parts. The initial stress of the 2219 aluminum alloy ring blank was tested using the drilling method, and the creep constitutive coefficient of the 2219 aluminum alloy was determined through stress relaxation tests. The numerical simulation processes of thermal stress relief (TSR), vibration stress relief (VSR), and thermal-vibration stress relief (TVSR) were compared and established. Through the correlation analysis between the actual measurement results of residual stress and the simulation results, it can be seen that the strong correlation in three directions at each measurement point accounts for over 37.5%, and the moderate correlation accounts for over 62.5%. This indicates that the numerical simulation model of 2219 aluminum alloy ring containing initial residual stress can accurately reflect the size and distribution of residual stress inside the actual ring. The simulation results show that the derived constitutive model can describe the stress relaxation process of TVSR by combining a single thermal time effect stress relaxation constitutive theory with a VSR plastic deformation material model. The simulation models established above were used to calculate the residual stress homogenization ability of three types of aging. The results showed that VSR, TSR, and TVSR can homogenize and reduce the residual stress field inside the ring, improve the distribution of residual stress inside the ring, and have a better overall homogenization ability of TVSR. The VSR control has a certain effect on reducing and homogenizing residual stress, but compared with TSR and TVSR, the reduction and homogenization ability of residual stress control is limited. The homogenization control effect TVSR>TSR>VSR, and the maximum equivalent stress homogenization rates of VSR, TSR, and TVSR are 52.8%, 80.6%, and 82.2%, respectively. Then, numerical simulation technology is used to study how the initial residual stress in the blank will cause the deformation of the ring during the thin-walled machining process. The roundness error theory of the minimum containment area method is applied to evaluate the deformation degree during the thin-walled numerical machining process, and the TVSR method is used for stress regulation. The deformation law of the thin-walled machining of the ring under different aging parameters is studied.

Single image deraining (SID) has shown its importance in many advanced computer vision tasks. Though many CNN based image deraining methods have been proposed, how to effectively remove raindrops while maintaining background structure remains a challenge that needs to be overcome. Most of the deraining work focuses on removing rain streaks, but in heavy rain images, the dense accumulation of rainwater or the rain curtain effect significantly interferes with the effective removal of rain streaks, and often introduces some artifacts that make the scene more blurry. In this paper, we propose a new network structure R-PReNet for single image deraining with good background structure maintaining. This framework fully utilizes the cyclic recursive structure of PReNet. Moreover, we introduce residual channel prior (RCP) and feature fusion modules for better deraining performance by focusing on background feature information. Compared with the previous methods, our method has significantly improvement effect on the rainstorm image with the artifacts removing and good visual detail restoring.

The cassava whitefly, Bemisia tabaci, causes direct damage to cassava in the tropics by feeding on the phloem of leaves, inducing leaf chlorosis and abscission which can result in considerable yield loss of up to about 50% on susceptible varieties. The pest is also known to impart its indirect damage through sooty mold formation. Most of the improved cassava varieties in Uganda were developed for CMD resistance and CBSD tolerance and little is known about their reaction to whitefly infestation. A study was conducted to evaluate the reaction of 24 improved cassava varieties which were sourced from 5 different countries in the region (Uganda, Kenya, Tanzania, Malawi, and Mozambique) to whitefly infestation. These varieties were evaluated in three agro-ecological zones of Uganda, namely; North-Western Savannah Grassland, Lake Victoria Crescent and the Kyoga Plains in the second rains of 2016. Monthly data were taken on adult and nymph counts, whitefly and sooty mold damage, CMD and CBSD severities from 2 up-to 9 Months after planting (MAP). Results show that the whitefly population was highly significantly (P

Due to its economic benefits and the ability to reduce carbon emissions on a large scale, the CCUS-EOR project has been widely promoted and implemented globally. By using carbon dioxide flooding, oil water transition zone reservoirs that were once considered worthless may have new potential for development because of its rich geological reserves and high quality carbon sequestration conditions. Unlike water flooded layer, the oil in the TZ is unsaturated rather than residual oil after water flooding, which would lead to special oil-water seepage law of initial oil saturation. It is necessary to clarify special oil-water seepage law of oil-water transition zone to evaluate its production & storage potential. In this paper, we present a series of experiments to characterize the relationship between residual oil saturation and initial oil saturation. Cores in four different permeability and oil in four different viscosity are used to simulate different reservoir conditions, and that CO2 immiscible flooding experiments for each cores permeability and oil viscosity are performed with four different initial oil saturation. A total of 36 sets of CO2 flooding experiment data are used to draw the initial oil saturation & residual oil saturation chart. The results show that the residual oil saturation depends on the initial oil saturation rather than constant under certain conditions of core and oil. Under the condition of low permeability and high oil viscosity, the influence of initial oil saturation on residual oil saturation is relatively strong. The initial oil saturation & residual oil saturation chart can accurately calculate the residual oil saturation, initial water cut and final recovery based on the core permeability, oil viscosity and the initial oil saturation which is the first time to put forward this kind of chart and of the great significance to evaluate the recovery potential of the TZ.

Natural fibers have attracted increasing interest as an alternative to produce environmentally friendly and sustainable materials. Particularly, hemp fibers have revealed to be widely used in various industrial applications due to their extremely unique properties. However, hemp can generate a large amount of agro-waste, and results in an attractive source of biopolymers for the development of low-cost materials in alternative to the raw materials and conventional petroleum-based plastics. In addition, deep eutectic solvents (DESs), a new type of truly green solvents, have been tested to remove gums, lignin, and other non-cellulosic components from hemp fibers. Reusing these components dissolved into the DESs to fabricate new materials directly by electrospinning is a very attractive but still unexplored endeavor. Thus, this innovative research to venture new upcycling pathways is focused on the fabrication of composite nanofibers by electrospinning of a gel-based blend of Poly(vinyl alcohol) (PVA) and hemp agro-waste (HW) dissolved into choline chloride (ChCl) : Glycerol (1:2) and ChCl : Urea (1:2) DES mixtures. The results obtained revealed that the produced nanofibers displayed uniform appearance with diameters ranging from 257.72 ± 65.63 nm to 380.78 ± 133.98 nm. In addition, the mechanical properties of the electro-spun composite nanofibers produced from the gel-based blends of HW dissolved in DESs and PVA (HW-DESs_PVA) were found to be superior, resulting in an enhanced tensile strength and Young’s modulus. Furthermore, the incorporation of HW into the nanofibers was able to provide bioactive antioxidant and antibacterial properties. Overall, this study demonstrated a promising, more sustainable, and eco-friendly way to produce electrospun composite nanofibers using HW in a circular economy perspective.

Запропонована методика спрямована на визначення та прогнозування технічного стану елементів мосту, що може слугувати прогресивним інженерним інструментом для оцінки надійності та довговічності. Розроблено на основі фундаментальних досліджень, які узагальнюють досвід вивчення фізико-механічних і фізико-хімічних властивостей матеріалів мостових конструкцій, що експлуатуються в реальних умовах. Теоретичною основою методики є модель надійності та прогнозування залишкового ресурсу елементів мосту на основі теорії Маркова. Розроблена методика призначена для оцінки технічного стану окремих елементів мосту з подальшою комплексною оцінкою всієї конструкції. За показник технічного стану прийнята надійність при експлуатації. Цей кількісний показник надійності в моделі є критерієм для: оцінки рівня безпеки елементів мосту; ранжування елементів мосту за необхідністю для конкретних видів ремонту, реконструкції або заміни; стратегічне планування витрат на ремонт або реконструкцію в умовах обмеженого фінансування; прогнозування залишкового ресурсу елементів. Для застосування розробленої методики запропоновано алгоритм оцінки та прогнозування технічного стану мостів. Було проведено математичний експеримент розробленої методики, який підтвердив адекватність висунутої гіпотези, тобто використання моделі надійності та прогнозування залишкового ресурсу елементів мосту. По-перше, запропоновано триступеневий механізм уточнення технічного стану мосту, суттєво підвищення точності розрахунків. Тому розроблена методика має практичне значення і може слугувати основою для інформаційно-аналітичних систем управління станом мостів.

The Bacillus megaterium LVN01 species native to Colombia has demonstrated the ability to metabolize different co-products or industrial waste (such as fique juice, cane molasses, residual glycerol) and accumulate polyhydroxybutyrate (PHB), giving it potential in the bioplastics industry. In this research, the potential of liquid digestate as a carbon source for the production of PHA in fermentation processes with this bacterial strain was evaluated. Favorably, it was found that B. megaterium utilizes the nutrients from this residual substrate to multiply appropriately and efficiently synthesize poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV). Bench scale aerobic batch fermentation, under the operational conditions of this research [Volume: 3L; Temperature: 30.8°C; Agitation: 400 rpm; pH: 7.0 ± 0.2; Disolved Oxygen: 100% saturation; Antifoam 10% (v/v)], generated maximum values of DCW (0.56 g cell L-1) at 60 h, while the maximum PHB yield (360 mg PHB L-1) occurred at 16 h, which is very favorable for sustainable degradable bioplastics production. Additionally, GC-MS and NMR analyses confirmed that the PHBV copolymer synthesized by B. megaterium is made up of the monomers 3-hydroxybutyrate (3HB) and 3-hydroxyvalerate (3HV). Furthermore, the thermal properties determined by TGA (Tonset=283.1 ºC, Tendset= 296.98 ºC. Td =290.114 °C) and DSC (Tm= ºC155.7 °C, ΔHf= 19.80 J g-1, Xcr = 18.17%), indicate that it is a thermally stable biopolymer with low percentages of crystallinity, providing flexibility that facilitates molding, adaptation, and application in various industrial sectors.

Remote sensing imagery is of great significance for policy decisions, especially for disaster assessment and disaster relief. To ensure the privacy and inviolability of personal buildings, the information containing these buildings must be anonymized during the remote sensing mapping process. Traditional processing methods for these targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Deep learning provides a new direction for target hiding. Although the image inpainting method based on deep learning is faster than the manual method, the cost of training calculation is a disadvantage. And the element-wise product operation used in the model increases the risk of vanished or exploded gradients. We propose a Residual Attention Target Hiding (RATH) model for remote sensing target hiding based on deep learning. RATH uses residual attention modules to replace gated convolutions, reducing parameters and mitigating gradient issues. The residual attention module preserves gated convolution performance but provides an adjustable kernel size. RATH retains gated convolutions for dynamic feature selection and balances model depth and width. Furthermore, this paper modifies the contextual attention layer by adjusting the fusion process to enlarge the fusion patch size. Finally, we extend the edge-guided function to preserve the original target information and confound viewers. Ablation studies on an open dataset prove RATH’s efficiency for image inpainting and target hiding. RATH achieves state-of-the-art results with lower complexity. And it has the highest similarity for edge-guided target hiding. RATH enables robust, efficient target hiding for privacy protection in remote sensing imagery while balancing performance and complexity. Experiments show RATH's superiority over existing methods in hiding arbitrary-shaped targets.

Image stitching is a crucial aspect of image processing. However, factors like perspective and environment often lead to irregular shapes in stitched images. Cropping or completion methods typically result in substantial loss of information. This paper proposes a method for rectifying irregularly images into rectangles using deformable meshes and residual networks. The method utilizes a convolutional neural network to quantify rigid structures of images. Choosing the most suitable mesh structure based on the extraction results, offering options such as triangular, rectangular, and hexagonal. Subsequently, the irregularly image, predefined mesh structure, and predicted mesh structure are input into a wide residual neural network for regression. The loss function comprises local and global, aimed at minimizing the loss of image information within the mesh and global target. This method not only significantly reduces information loss during rectification but also adapting to different images with various rigid structures. Validation on the DIR-D dataset shows this method outperforms state-of-the-art methods in image rectification.

The 1060 aluminium alloy is widely applied to electronic industry, construction area, aerospace field, traffic engineering, decoration and consumption goods market for its good chemical, physical and mechanical properties. In general, excellent processing property is necessary and important for manufacturing of complicated panels. In this paper, a special 2D ultrasonic vibration incremental forming method is designed to improve its plasticity and mechanical properties. Three kind of processing methods including traditional single point incremental forming, longitudinal ultrasonic vibration incremental forming and 2D ultrasonic vibration incremental forming are conducted for flexible manufacture of conical parts of 1060 aluminium alloy sheet. Then micro-hardness tests, residual stress tests and scanning electron microscopy tests are carried out to probe its revolution of micro-structure and mechanical properties and to analysis the effects of different types of ultrasonic vibration on plasticity and fracture characteristic of 1060 aluminium alloy. It is proved that 2D ultrasonic vibration is facilitated to improvement of plasticity and surface qualities of 1060 aluminium alloy than the other two processing methods. So, the novel 2D ultrasonic vibration incremental forming possesses substantial application values on flexible and rapid manufacturing of complicated thin-walled component of aluminium alloy.

This research investigates the fatigue behaviour and fracture mechanics of high-performance concrete (HPC), including various compositions such as HPC with basalt aggregates (HPC-B), HPC with gravel (HPC-G), and high-strength coarse mortar (CM) static and cyclic tensile loading within the special priority program SPP 2020. The study aims to integrate fracture mechanics into structural analysis to enhance design guidelines for slender cross-sections and safety-related high-performance structural components. The experimental investigations reveal HPC-B's re-markable superiority, displaying higher compressive strength, modulus of elasticity, and tensile strength compared to HPC-G and CM. A modified disk-shaped compact tension (MDCT) based on ASTM standards, aided by digital image correlation (DIC) unveils fracture behaviour, empha-sizing fracture energy as a crucial parameter. HPC-B exhibits improved crack resistance and notch sensitivity reduction attributed to crushed basalt aggregates and enhanced interfacial transition zone (ITZ). The research scrutinizes factors like material characterization, aggregate morphology, stress levels, and displacement rate on crack formation. High-cycle fatigue tests show HPC-B's superior performance, and post-fatigue analysis reveals enhanced residual fracture toughness attributed to nano-level structural changes, stress redistribution and aggregate-matrix interac-tion. 3D image analysis via Computed Tomography (CT) scans captures mesostructural crack propagation and provide quantitative insights. This study advances the understanding of HPC fatigue behaviour, emphasizing the interplay of aggregate types, morphologies, and their dy-namic response to cyclic loading, offering valuable insights for optimizing design guidelines and fostering innovation in structural engineering.

Thrombosis is characterized by the pathological formation of fibrin clots within a blood vessel, leading to the obstruction of blood flow. Fibrinolytic enzymes from microorganisms have exhibited promising effects to dissolve clots in a more efficient and safe way. Then, the aim of this study was to evaluate the biomass and fibrinolytic enzyme production of Tetradesmus obliquus under autotrophic and mixotrophic conditions using different concentration of corn steep liquor (CSL). Different extraction and precipitating methods were tested, and the enzyme was purified by ion exchange chromatography. More advantageous culture condition was mixotrophic using 0.25% CSL, showing the highest values of biomass productivity (Px = 169.3 ± 44.36 mg∙L-1day-1) and specific growth rate (µmax = 0.17 ± 0.00 day-1), and significant fibrinolytic production (391.34 ± 40.03 U∙mg-1). Moreover, fibrinolytic activity was higher when extracted by homogenization and precipitated using acetone, which exhibited clear zone of fibrin degradation in the fibrinolytic plate assay. Additionally, the purified enzyme showed specific activity of 1176.90 ± 140.37 U∙mg-1 and molecular weight around 97 kDa. Finally, the enzyme has higher enzymatic activity than various fibrinolytic enzymes, and the obtained enzyme has potential to be developed as a therapeutic agent in thrombosis treatment. Additional studies are need to investigate the biochemical properties and biological profile of this enzyme.

The paper shows that it is possible to obtain reliable information on the dependence of radial distribution of longitudinal birefringence in glass cylindrical elements with radial distribution of refractive index (GRIN lenses) on the basis of transverse polarization tomography data of residual stresses. This does not require complicated procedures of sample preparation, as is necessary in the case of longitudinal translucency measurements. The approach developed was verified in the experiments with a set of different GRIN lenses formed with ion exchange technique, and the closeness of the data obtained from transversal and conventional longitudinal transmission measurements was demonstrated.

The biomethane accumulation of several combinations of whey and sugarcane molasses, inoculated with sludge from a treatment facility of one of the dairy enterprises of Imbabura, was assessed in the current experiment at a concentration of 0.5 g/l COD. The whey: molasses (W: M) ratios for each treatment were 0:100, 25:75, 50:50, 75:25, and 100:0, with a constant temperature of 37°C and an initial pH adjustment of 7.5. Half a litre of total mixes was used for each treatment in duplicate. Six kinetic models were evaluated to account biomethane accumulation in anaerobic co-digestion processes in batch of whey and sugarcane molasses. Five of these have been tested by other researchers, and one was developed by modifying a first-order model to consider changes in the biomethane accumulation profile. This proposed model, along with the modified two-phase Gompertz model, resulted in the ones that were best able to adjust the experimental data, obtaining in all cases an R² ≥ 0.949, indicating the accuracy of both models. In addition, the proposed here model has five parameters, one less than the modified two-phase Gompertz model, making it more straightforward and robust.

Background: PFO (Patent foramen ovale) is a common defect that affects about 25% of the population. Although its presence is asymptomatic in the majority of the cases, the remaining part becomes overt with different symptoms, including cryptogenic stroke. The PFO closure procedure is widely available to date with the most used Amplatzer PFO Occluder, also in complex anatomy, but the performance of another device, the GORE Septal Occluder (GSO), has not been completely explored with regard to different septal anatomies. Methods: From March 2012 to June 2020, 118 consecutive patients with an indication for PFO closure were treated using the GSO system and included in a prospective analysis and followed. After 12 months, every patient underwent transcranial Doppler to evaluate the effectiveness of treatment. Results: of 111 patients evaluated, 107 showed effective PFO closure (96,4%) and 4 showed a residual shunt (3,6%). To better evaluate the device performance, the overall population was sorted into 2 clusters based on the echocardiographic characteristics. The main difference between groups was for PFO width (4,85 ± 1,8 vs 2,9 ± 1 mm, p <0,001) and PFO tunnel length (12,6 ± 3,8 vs 7,2 ± 2 respectively, p <0,001), allowing identification of complex anatomy and simple anatomy, respectively. Regardless of the aforementioned cluster, the GSO performance to reach an effective closure was independent of anatomy type and the chosen device size. Conclusion: GSO device showed efficacy and safety at 1-year follow-up in patients with at least 1 anatomical factor of complexity of PFO, irrespectively from the level of complexity itself.

Rigid pavements at military airfields experience surface deterioration within 6-18 months of construction. The cause of this degradation is mainly due to combined exposure to repeated heat shocks from jet engine exhaust and spilled aviation oils (hydrocarbons). Surface degradation occurs in the form of disintegration of aggregates and cement paste into small pieces that pose severe risks of physical injury to maintenance crews or damage to an aircraft engine. Since coarse aggregates typically occupy 60-80% of the concrete volume, aggregates' thermal properties and microstructure should play a crucial role in the degrading mechanism. At high temperatures, concrete with lightweight aggregates is reported to have better performance compared to concrete with normal-weight aggregate. Thus, the present study carried out a detailed investigation of the mechanical and thermal performance of lightweight aggregate concrete exposed to the combined effects of high temperature and hydrocarbon oils simultaneously. To identify the resistance of different concrete with various lightweight coarse aggregates, pumice, perlite, lytag (sintered fly ash), and crushed brick were used as lightweight coarse aggregates in concrete. Also, basalt aggregate concrete was used as a reference. After cyclic exposures, all specimens were tested for residual mechanical, thermal, chemical, and microstructural properties. Overall, concrete with crushed brick aggregate and LYTAG used in this study showed superior resistance to the simulated airfield conditions.

The (Ti, Nb)(C, B)/IN625 composite coating with both homogeneous and defect-free microstructure were successfully prepared by in situ on the surface of 42CrMo steel using the coupling of the ultra-high-speed laser cladding (EHLA in German) technology with the direct reaction synthesis (DRS) technology, and were comparatively analyzed with the IN625 coating prepared by the EHLA. The microstructure of the fused cladding layer was investigated by selected scanning electron microscopy (SEM), energy dispersive spectrometer (EDS) and double spherical aberration transmission electron microscopy (DSA-TEM). The residual stress distribution on both sides of the fused cladding interface was characterised by nanoindentation stress test based on the modified O&P method and the G&S energy method. The results show that the interface of (Ti, Nb)(C, B)/IN625 composite coatings is affected by about 670 kJ Joule heat released from the in-situ reaction, and the interfacial width reaches 24 μm, so that it is 6 times higher than that of IN625 coating prepared by EHLA, which effectively reduces the stress gradient in the interfacial region and alleviates the stress mismatch on both sides of the interface. However, the surface hardness of (Ti, Nb)(C, B)/IN625 composite coating is lower than that of the IN625 coating, with a value of about 240 HV0.2, and the average wear weight loss was only 10% of that of the IN625 coating, which is on the one hand attributed to the in-situ authigenic TiCB, TiC, NbMo3B4, and NbMo2B2 phases supporting the (Ti, Nb)(C, B)/IN625 composite coating substrate to achieve the abrasion reduction and wear resistance. On the other hand, it is attributed to the formation of nano-equiaxial ultrafine grains in the depth range of 250 nm below the wear surface area by the coupling of the three fields of plastic rheology-heat-force, which dynamically strengthens the wear surface.

In this paper, we concentrate on the study of the properties of residual Tsallis entropy for order statistics. Order statistics have an important role in reliability structural engineering for example for modelling lifetimes of series and parallel systems. The residual Tsallis entropy of ith order statistic from a continuous distribution function and its deviation from the residual Tsallis entropy of ith order statistics from a uniform distribution is investigated. In a mathematical framework, a method to express the residual Tsallis entropy of the ith order statistic from a continuous distribution in terms of the residual Tsallis entropy of the ith order statistic from a uniform distribution is provided. This approach may provide insight into the behavior and properties of the residual Tsallis entropy for order statistics. Further, we study the monotonicity properties of the residual Tsallis entropy of order statistics under dierent conditions. By studying these properties, deeper understanding of the relationship between the position of order statistics and the resulting residual Tsallis entropy is gained.

Chromium-nickel austenitic stainless steels are widely used due to their high corrosion resistance, good weldability and deformability. To some extent, their application is limited by their mechanical characteristics. As a result of their austenitic structure, increasing the static and dynamic strength of the components can be achieved by surface cold work. Due to the tendency of these steels to undergo intercrystalline corrosion, another approach to improve their mechanical characteristics is the use of low-temperature thermo-chemical diffusion processes. This article proposes a new combined process based on sequentially applied diamond burnishing (DB) and low-temperature gas nitriding (LTGN) to optimally improve the fatigue strength of 304 steel. The essence of the proposed approach is to combine the advantages of the two processes (DB and LTGN) to create a zone of residual compressive stresses in the surface and subsurface layers–the enormous surface residual stresses (axial and hoop) introduced by LTGN, with the significant depth of the compressive zone characteristic of static surface cold working processes. DB (both smoothing and single-pass hardening), in combination with LTGN, achieves a fatigue limit of 600 MPa, an improvement of 36.4% compared to untreated specimens. Individually, smoothing DB, single-pass DB and LTGN achieve 540 MPa, 580 MPa and 580 MPa, respectively. It was found that as the degree of plastic deformation of the surface layer introduced by DB increases, the content of the S-phase in the nitrogen-rich layer formed by LTGN decreases, with resultant increased content of -phase, and a new (also hard) phase: stabilized nitrogen-bearing martensite.

Keywords: Fatigue crack propagation; Welding residual stress; Plastic re-distribution; Stress ratio effect

Thermoplastic composites are continuously replacing thermosetting composites in lightweight structures. However, the accomplished work on the fatigue behavior of thermoplastics is quite limited. In the present work, we propose a numerical modeling approach for simulating fatigue delamination growth and predicting the residual tensile strength of quasi-isotropic TC 1225 LM PAEK thermoplastic coupons. The approach is supported and validated by tension and fatigue (non-interrupted and interrupted) tests. Fatigue delamination growth is simulated using a mixed-mode fatigue crack growth model, which is based on the cohesive zone modeling method. All interfaces between the thermoplastic plies were modelled using cohesive elements. Quasi-static tension analyses on pristine and fatigued coupons were performed using a progressive damage model implementing a set of Hashin-type strain-based failure criteria and a damage mechanics-based material property degradation module. Using the fatigue model, delamination growth was predicted as a function of number of cycles at all interfaces. The results agree well with C-scan images taken on fatigued coupons during interruptions of fatigue tests. An unequal and unsymmetric delamination growth was predicted due to the quasi-isotropic lay-up. Moreover, the combined models capture the decrease in the residual tensile strength of the coupons. In the quasi-static tension analysis of the fatigued coupons, the driving failure mechanisms are the fast propagation of the pre-existing delamination and the severe matrix cracking.

The main purpose of this work was to tests of form and size of fatigue wear of the top layer of oil gear pump wheel (3PW-BPF-24). The object of tests was operated during a determined number of hours at strictly controlled operational and environmental parameters. A microscope of focal differentiation by Alicona InfiniteFocus G4 (with Focus-Variation optical measuring technology) was used for an identification, measurement and description of noticed superficial defects, which resulted from the fatigue process of the top layer and an earlier thermochemical treatment. The work was finished with an analysis of obtained results (based on the analysis of 3D scans) and conclusions concerning about optimization of the thermal treatment. Taking into consideration the presented results (suggestions) in the technology of improving strength properties of gear wheels (of this type oil pumps) may render it possible to obtain an appropriate fatigue endurance of the top layer, i.e. a minimization of observed superficial defects.

Asymptotic theories for fractional cointegrations have been extensively studied in the context of time series data, with numerous empirical studies and tests developed. However, most of the previously developed testing procedures for fractional cointegration were primarily designed for time series data. This paper proposes a generalized residual-based test for fractionally cointegrated panels with fixed effects. The test development is based on bivariate panel series with the regressor assumed to be fixed across cross-sectional units. The proposed test procedure accommodates any integration order between [0,1], and it is asymptotically normal under the null hypothesis. Monte Carlo experiments demonstrate that the test exhibits better size and power compared to a similar residual-based test across varying sample sizes.

Ecological stoichiometry is an important index to reflect ecological interaction and the balance of various elements in ecological processes. At present, the stoichiometric spatial distribution of soil carbon (C), nitrogen (N), phosphorus (P) and potassium (K) in farmland and grassland of Inner Mongolia and its influencing factors are still unclear. In this study, the spatial distribution of soil nutrient content and stoichiometry and the effects of environmental factors on soil C:N:P:K stoichiometry were analyzed under different land use patterns in four agro-pastoral areas. The results showed that there was a geographical gradient in the ecological stoichiometric relationship between farmland and grassland. RCN, RCP, RCK, RNP and RNK showed an "N" distribution from west to east, while RPK showed a "V" distribution. The difference in spatial distribution was more significant than the difference in land use pattern. The ecological stoichiometric relationship of grassland was mainly affected by the content of C and N, and was related to the similarity of soil properties. The field ecological stoichiometry was mainly affected by the content of nitrogen and phosphorus, and had a great relationship with fertilization. The effects of MAT and MAP on soil ecological stoichiometry were related to the inter-regional environmental heterogeneity. The influence of MAP on farmland and MAT on grassland was more significant. It was of great significance for field management according to local conditions, rational utilization of land resources and sustainable development of agriculture to clarify the ecological stoichiometric characteristics of farmland and grassland in agro-pastoral ecotone.

The paper presents the results of experimental studies and mathematical modeling of the effect of stress accumulation in thermosetting epoxy polymer "hot" curing on anhydride hardener. Stress accumulation occurs under cyclic thermomechanical action in a locked rod, similar effects are observed, for example, in thermoplastic elements subjected to the combined effect of mechanical loads and variable temperatures. Experimental results have shown that under cyclic thermomechanical loading during exploitation it is possible to accumulate residual stresses in the thermosetting polymer. A multi-element structural mathematical model with memory for thermomechanical load, which allows to consider the accumulation of residual thermal stresses, has been proposed. The results of modeling and experiment are compared. Based on the results, corrections are made in the approach to the application of this model to thermosetting polymers such as the epoxy resin under study. Considering the corrections, a good agreement (the difference is from 1 to 6%) with the results of experimental determination of stresses under complex cyclic thermomechanical load was obtained.

The incidence and mortality of cervical cancer are high in Romania compared to other European countries, particularly for locally advanced cervical cancer cases, which are predominant at the time of diagnosis. Widely accepted therapeutic guidelines indicate that the treatment for locally advanced cervical cancer consists of concurrent chemoradiotherapy (total dose 85-90Gy at point A), with surgery not being necessary as it does not lead to improved survival and results in significant additional morbidity. In Romania, the treatment for locally advanced cervical cancer differs, involving lower-dose chemotherapy (total dose 60-65Gy at point A), followed by surgery which, under these circumstances, ensures better local control. In this regard, we attempted to evaluate the role and necessity of surgery in Romania, considering that in our study, residual lesions were found in 55.84% of cases on resected specimens, especially in cases with unfavorable histology (adenocarcinoma and adenosquamous carcinoma). This type of surgery was associated with significant morbidity (28.22%) in our study. The recurrence rate was 24.21% for operated patients compared to 62% for non-operated patients receiving suboptimal concurrent chemotherapy alone. In conclusion, In Romania, surgery will continue to play a predominant role until radiotherapy achieves the desired effectiveness for local control.

In recent decade water pollution by micropollutants is an increasing environmental concern. Since 2019, due to COVID-19 pandemic, increased stormwater pollution by chlorine based disinfectants has been determined. Research aimed to treat of chlorine contaminated stormwater after outdoors spaces disinfection are very limited. Runoff from disinfected areas and residual chlorine present in stormwater are transported to surface water bodies. Residual chlorine reacts with dissolved organic compounds in water and results the formation of environmentally toxic disinfection by-products. Studies present event low residual chlorine concentrations may pose a risk to aquatic flora and fauna. In this study the efficiency of different filter materials, including peat, wood chips, sawdust (column tests) and ceramzites Leca, Pollytag, Polski, Ceski (batch tests), in retaining residual chlorine were tested in laboratory scale batch and flow through experiment. The best efficiency to retain chlorine presented sawdust (96 %) and ceramzite Leca (76 %). The plants abilities to reduce pollution by chlorine was analyzed in raised garden bed. Research results will contribute to future studies aimed to retain various micropollutants in stormwater using remediation technologies.

The results of numerical experiments with the chemistry-climate model of the Institute of Numerical Mathematics of the Russian Academy of Sciences - Russian State Hydro-Meteorological University (INM-RSHU CCM) in comparison with the MERRA2 reanalysis data are presented. To assess the impact of sea surface temperature (SST) on stratospheric processes and the ozone layer, numerical experiments were carried out for scenarios corresponding to the El Niño and La Niña Southern Oscillation phases. It is shown that the El Niño phase contributes to the enhancement of heat and mass transfer to the polar stratosphere, which strengthen the Brewer-Dobson circulation and the flux of wave activity that affect the zonal wind. As a result, during El Niño, the probability of sudden stratospheric warming increases and the stratospheric polar vortex (SPV) weakens, re-sulting in an increase in total polar stratospheric ozone. The La Niña phase, on the contrary, is accompanied by a weakening of heat and mass transfer from the troposphere to the stratosphere, as a result of which the stratospheric polar vortex strengthens and the total column ozone decreases. It is shown that the effect associated with the Southern Oscillation is more pronounced in the Northern Hemisphere than in the Southern Hemisphere. Numerical experiments were also carried out for scenarios in which the sea surface temperature was set corresponding to the early 1980s, and the results were compared with calculations in which the SST was set corresponding to the late 2010s. This allowed us to assess the influence of the multiyear trend in the SST increase on stra-tospheric processes and the ozone layer. It was shown that the SST increase is most pronounced in the Arctic, which corresponds to the phenomenon of "Arctic amplification", and therefore, the heat and mass transfer to the stratosphere increases in the Northern Hemisphere, which contributes to some weakening of the SPV and increase of the total column ozone. But, compared to the Southern Oscillation, the influence of the SST trend on the SPV and total column ozone is much weaker and is observed mainly in the Northern Hemisphere.

The ex situ conservation and sustainable exploitation of neglected or underutilized plant species (NUPs) is urgent and paramount. To this end, we focused on Petromarula pinnata (Campanu-laceae), a vulnerable local endemic of Crete (Greece) garnering interest for its agro-alimentary, medicinal, and ornamental value. A GIS ecological profile was established herein based on its natural distribution in Crete containing detailed information on the climatic conditions (mini-mum, maximum, mean temperature, and precipitation) as well as information on 19 bioclimatic variables shaping its natural adaptation. This profiling contributed to better understanding of the species' ecological requirements and facilitated the germination trials employing stored seeds from four distinct populations (two from lowlands and two from semi-mountainous areas) tested at four temperatures (10, 15, 20 and 25oC) and two light condition treatments. The results herein showed that both temperatures and population as well as their interaction significantly affected seed germination rates. Incubation temperatures of 10 and 15oC were the most appro-priate for the successful seed germination of this species (> 81.25% for both temperatures in three out of four populations), with light conditions not affecting seed germination (86% in light and 80% in darkness). The successful germination protocol of P. pinnata seeds opens avenues for fur-ther sustainable exploitation of this valuable yet vulnerable NUP as a new Greek native crop.

Empirical equations representing, interpolating and smoothing groups of measurement results by regression methods are in widespread use in metrology and other fields of science and engineering. Standard equations for the propagation of measurement uncertainties to values computed from such equations are available but suffer from a lack of general acceptance and are only infrequently applied in practice. One reason for the slow uptake is the lack of clear methods to account for systematic error. In this paper, uncertainty propagation equations in terms of covariance matrices are generalized to allow for systematic errors in least-squares regression, and effects of the resulting uncertainties are investigated analytically. A stochastic ensemble model of systematic error is proposed for the computation of the non-diagonal elements of the weight matrix of the Generalized Least-Squares method (GLS) from the measurement uncertainty. A GLS projector formalism is described which separates the effects of measurement scatter on values calculated by the equation from those on the related “residuals”, i.e., the residual errors in the fitted data. The same projectors act similarly on the associated uncertainties and covariance matrices and permit the effects of systematic errors on the simulation covariance to be quantified. It is demonstrated that, in order to include systematic errors in the uncertainty estimates of GLS, covariance matrices may be substituted by novel, specifically defined dispersion matrices that are not specified yet by the GUM[1]. Systematic measurement errors may be estimated from various sources; a particularly easy way suggested here involves analyzing the structure in the regression residuals. It is demonstrated that GLS projectors exhibit inherent features of “error blindness” also with respect to systematic errors. [1] GUM: Guide to the Expression of Uncertainty in Measurement, http://www.bipm.org/en/publications/guides

JIS SUJ2 is most widely used in bearing steels. The advantages are good hardenability, excellent fatigue, wear resistance and comprehensive mechanical properties. For wear resistance and fatigue resistance of the steel are getting more and more attention, the residual stress state and its distribution on the surface of the heat affect zone are critical factors affecting the fatigue life and wear resistance of the parts. In this study, using the SUJ2 as the material to talk about the surface residual stress and retained austenite distribution. Doing the quenching and tempering treatment to obtain different microstructures, using the induction method to re-quench the case region. After the heat treatment, measuring the residual stress and retained austenite volume on the surface by X-ray diffraction, observing the microstructure and comparing the hardness. The results show that the microstructure after heat treatment contains unsolidified carbides, tempered martensite and retained austenite. The residual stress on the surface is the tensile state. In the re-hardened area after induction quenching, the residual stress is all compressive, and the values are more than -800 MPa. In conclusion, in the same output power condition can be observed that the microstructure of the specimens before induction hardening has a significant impact on the effective case depth. The surface residual stress has changed from a tensile to a compressive state. In the re-hardened area, the maximum of the residual compressive stress increased with the austenitized temperature increase.

This paper presents geometric analyses of welded frames after free relaxing and vibratory stress relief (VSR). Respected frames were tested components of a prototype packaging machine. Two types of relaxation were carried out to remove stresses introduced as a result of welding process. One of the frame was subjected to free relaxing, while the other one to accelerated vibration relaxing. Detection of the frame geometry changes was performed using a photogrammetric system. In addition, an evaluation of the geometry change was conducted for fifteen variants of steel frame support. A comparative analysis of the geometric deviations of the frames after free and vibratory stress relief confirmed the assumption that the frame after vibration stress relief better reproduces the nominal dimensions. Nevertheless, it should be emphasized that after vibratory stress relief the frame is not subject to further deformation, which is a desirable effect. In the case of free relaxing, the frame undergoes dimensional changes in a random manner. In summary, carrying out accelerated vibratory stress relief allows control of spontaneous dimensional changes in the designed frame of a packaging machine resulting from spontaneous relaxation of stresses arising from the welding process. The shortening of the relaxation process of the welded frame is also an unquestionable advantage.

The microscopic pore structure of tight sandstone reservoir significantly influences the characteris-tics of CO2 flooding after water flooding. The research was conducted using various techniques such as casting thin sections, high pressure mercury injection, scanning electron microscopy, Nu-clear magnetic resonance (NMR) testing, and a self-designed high-temperatures and high-pressures microscopic visualization displacement system. Three type cores with different pore structures were selected for the flooding experiments and the microscopic visualization displace-ment experiments, including CO2 immiscible flooding, near-miscible flooding, and miscible flood-ing after the conventional water flooding. The characteristics of CO2 flooding and the residual oil distribution after water flooding were quantitatively analyzed and evaluated. The results show that: (1) During the water flooding process, the oil produced from type I and type III samples mainly comes from large and some medium pores. Oil utilization of all pores is significant for type II samples. The physical properties and pore types have a greater impact on water flooding. Type I and II samples are more suitable for near-miscible flooding after water flooding. Type III samples are more suitable for miscible flooding after water flooding. (2) In the CO2 flooding, oil recovery increases gradually with increasing pressure for all three types of samples. Type II core samples have the highest recovery. Before miscibility, the oil recovered from type I and type II samples was primarily from large pores, however, the oil recovery mainly comes from medium pores when reaching miscibility. As for the type III samples, the oil produced in the immiscible state mainly comes from large and medium pores, and the enhanced oil recovery mainly comes from medium and small pores after reaching the near-miscible phase. (3) It can be seen from the microscopic re-sidual oil distribution that oil recovery will increase as the petrophysical properties of the rock model improve. The oil recovery of near-miscible flooding after water flooding regarding the type II model is up to 68.11%. The oil recovery of miscible flooding after water flooding about type III model is the highest at 74.57%. With increasing pressure, the proportion of flake residual oil grad-ually decreases, while the proportion of droplet-like and film-like residual oil gradually increases. Type II samples have a relatively large percentage of reticulated residual oil in the near-miscible stage.

Image stitching is a crucial aspect of image processing. However, factors like perspective and environment often lead to irregular shapes in stitched images. Cropping or completion methods typically result in substantial loss of information. This paper proposes a method for rectifying irregularly images into rectangles using deformable meshes and residual networks. The method utilizes a convolutional neural network to quantify rigid structures of images. Choosing the most suitable mesh structure based on the extraction results, offering options such as triangular, rectangular, and hexagonal. Subsequently, the irregularly image, predefined mesh structure, and predicted mesh structure are input into a wide residual neural network for regression. The loss function comprises local and global, aimed at minimizing the loss of image information within the mesh and global target. This method not only significantly reduces information loss during rectification but also adapting to different images with various rigid structures. Validation on the DIR-D dataset shows this method outperforms state-of-the-art methods in image rectification.

Fastener holes are among the most common natural stress concentrators in metal structures. The life cycles of various structural elements, such as those in aircraft structures, automobiles, and rail-end bolt joints are limited by fatigue damage around the holes. An effective approach to delay the formation and growth of fatigue macrocracks is to introduce residual hoop compressive stresses around the holes. Two methods have become established in the prestressing of fastener holes in aircraft components: split sleeve and split mandrel, which implement one-sided processes. The common disadvantage of both methods is the complex procedure due to the need for high accuracy of the initial holes. This article presents a new modified split mandrel method providing the same tightness (interference fit) with a wide tolerance of the pre-drilled hole diameters reducing the number of technological cycle steps and production costs. То implement the new method, a functionally connected tool and a device with a hydraulic drive were developed. An extensive experimental study of 2024-T3 AA specimens was carried out to evaluate the effectiveness of the method under a high scattering of the pre-drilled holes. The new method provided a deep zone of residual hoop compressive stresses on both faces of the specimens after cold working and after hole final reaming. The removal of a plastically deformed layer around the hole of suitable thickness during the final reaming decreased the axial gradient of residual hoop stress distribution. Fatigue tests on a tensile pulsating cycle verified the effectiveness of the modified split mandrel method to significantly increase the fatigue life by 6.6 times based on cycle fatigue strength compared to the conventional case of machining the holes. The obtained S-N curves for three groups of samples with initial hole diameters of 8.0, 8.1, and 8.2 mm which were cold worked with the same tightness of 0.32 mm and final reamed, aligned well indicating that the new method can provide constant fatigue strength for a given stress amplitude.

This paper discusses the theoretical and experimental correlations between fatigue and static strength statistical distributions. We use a two-parameter residual strength model that obeys the qualitative Strenght-Life Equal-Rank (SLERA) assumption for guidance. The modeling approach consists of recovering the model's parameters by best fitting the constant amplitude (CA) fatigue data at a given stress ratio, R, and the experimental Weibull parameters of the static strength distribution function. Once the model's parameters are fixed, its capabilities, potential, and limits are discussed by comparing its predictions with residual strength and fatigue data obtained at different stress ratios, R. Moreover, from a preliminary analysis, the theoretical extension of the model's capabilities to variable amplitude loadings is conceptualized. The application of Miner's rule is also discussed and compared with a new damage rule to analyze the fatigue responses under variable amplitude loadings.

With the advancement of technology, signal modulation types are becoming increasingly diverse and complex. The phenomenon of signal time-frequency overlap during transmission poses significant challenges for the classification and recognition of mixed signals, including poor recognition capabilities and low generality. This paper presents a recognition model for fine-grained analysis of mixed signal characteristics, proposing a Geometry Coordinate attention mechanism and introducing a low-rank bilinear pooling module to more effectively extract signal features for classification. The model employs a residual neural network as its backbone architecture and utilizes the Geometry Coordinate attention mechanism for time-frequency weighted analysis based on information geometry theory. This analysis targets multiple-scale features within the architecture, producing time-frequency weighted features of the signal. These weighted features are further analyzed through a low-rank bilinear pooling module, combined with the backbone features, to achieve fine-grained feature fusion. This results in a fused feature vector for mixed signal classification. Experiments were conducted on a simulated dataset comprising 39,600 mixed signal time-frequency plots. The model was benchmarked against a baseline using a residual neural network. The experimental outcomes demonstrated an improvement of 9% in the exact match ratio and 5% in the Hamming score. These results indicate that the proposed model significantly enhances the recognition capability and generalizability of mixed signal classification.

This literature review provides an in-depth exploration of the research conducted on the investigation and measurement of residual stress (RS) in Wire Arc Additive Manufacturing (WAAM) products, particularly focusing on how process parameters influence the phenomenon. RS plays a crucial role in determining the mechanical behavior and structural integrity of WAAM components. This review article gives an understanding of the relationship between process parameters and RS to optimize the WAAM processes and ensure the durability of the final products. It also summarizes key findings, measurement techniques, challenges, and future directions in this evolving field. The review also analyzes a measurement of RS in the products of WAAM as a function of process parameters depending on examining various research studies, techniques, and methodologies employed in their studies. Experimental measuring techniques and numerical analysis of RS to determine the impacts of RS in mechanical response in products of WAAM were discussed. By offering a comprehensive overview of current research trends and insights, this review serves as a valuable resource to guide future investigations, fostering the advancement of WAAM as a robust and efficient manufacturing technology.

Outliers seriously affect the accuracy in geometric model fitting. Previous works in coping with outliers involve threshold selection and scale estimation. However most scale estimators suppose the inlier distribution as a Gaussian model, which usually poorly meets the cases in geometric model fitting. Outliers, considered as the points with big residuals to all the true models, share common items with big values in quantized residual preferences, thus making the outliers gather away from the inliers in quantized residual preference space. In this paper we make use of this outlier consensus in quantized residual preference space by extending the usage of energy minimization to combine the model error and the spatial smoothness in quantized residual preference space for outlier detection. The energy minimization based outlier detection process follows an alternate sampling and labeling framework. After the outlier detection, an ordinary energy minimization method is employed to optimize the inlier labels, which also follows the framework of alternate sampling and labeling. The experimental results in this study show that the energy minimization based outlier detection method can detect most of the outliers in the data. Furthermore, the proposed energy minimization based inlier segmentation process segments the inliers into different models quite accurately. Overall, the performance of the proposed method is better than most of the state-of-the-art methods.