This study investigates the effects of home-based Kakao health care breathing exercises and stretching on respiratory function and fatigue in COVID-19 cured patients. A total of 35 participants performed four movements of home-based breathing exercise and five respiratory muscle stretching exercises four times a week for four weeks. Respiratory function was measured using FVC, FEV1, FEV1/FVC, and PEF. Fatigue was assessed using the Fatigue Severity Scale (FSS). Data analysis was performed using Independent Samples and Paired Samples T-tests in SPSS 24, with a significance level set at p < 0.05. After four weeks of Home based Kakao health care Breathing Exercise, there were significant increases in respiratory FVC, FEV1, FEV1/FVC, and PEF function values observed in the training group (T.G.) after the exercise intervention (p < 0.05). Such an increase was observed when comparing these values with the pre-exercise measurements. In contrast, there was no statistically significant difference in respiratory function outcomes before and after exercise in the control group (C.G.) (p > 0.05). The FSS scores were statistically significant within the training group (T.G.). (p >0.05). The 4-week Kakao health care Breathing Exercise was found to be capable of improving some respiratory functions in COVID-19-recovered patients, but it showed no significant improvement in fatigue levels.

In this work, we introduce a new and generalized concept (herein referred to as Caputo fractional delta derivative and Caputo fractional delta dini derivative of order $\alpha\in(0,1)$) for Caputo fractional derivatives on an arbitrary time domain $\mathbb{T}$ which is a closed subset of $\mathbb{R}$. Combining the continuous and discrete time domains, we create a unified framework for stability analysis on time scales. Comparison results and stability criteria for the considered Caputo fractional dynamic equations are presented based on a new definition for Caputo fractional delta derivative of a Lyapunov function, contributing to the broader understanding of fractional calculus on time scales. The work also incorporates an illustrative example to demonstrate the relevance, effectiveness and applicability of the established stability results over that of the integer order.

In the ground-based infrared optical remote sensing system, the target signal is very weak due to the dynamic strong light background and the movement of small and small targets. In order to improve the limit detection capability, the background suppression and target enhancement methods are required to be more suitable for this scene. To solve this problem, we first analyze the image features in the current scene, and propose a more perfect point target and noise model. Then, we propose a new WY distribution function based on the Fermi Dirac distribution function, and propose an anisotropic filtering method based on this function, and further suppress the back-ground through the difference results of two steps. Then, based on the distribution function, we further designed an energy concentration accumulation strategy in 9 scale directions, through which the SNR of the target is effectively improved and the suppression ability of the background is enhanced. Through quantitative and qualitative experimental analysis, compared with the same type of algorithms, the proposed method has better robustness against extremely weak targets and dynamic backgrounds.

According to the ECCB, cancer represents the transition of a genomically damaged multicellular cell to a lower level of cell organization, controlled by the ancestral gene regulatory network (GRN) from the ancestral compartment of human and metazoan genomes. Cancer adopts ancient mechanisms and rules of the common ancestor, similar to those observed in parasitic amoebae. In cancer, the productive cell line generating CSCs is a non-gametogenic cancer germline. This germline proliferates through asymmetric cell division (ACD phenotype). CSCs lack proliferative capacity; they persist in hypoxic niches in a quiescent cell state or transition to an amplifying cell state that performs cyst-like polyploidization cycles, giving rise to precursors and CSCs capable of differentiation. Malignization arises from genomically dysfunctional tetraploid germline cells (DSCD phenotype) that proliferate in a precancerous stage through symmetric cell cycles. DSCD progeny undergo homotypic fusion, forming multinucleated genome repair syncytia (MGRS pathway) driving carcinogenesis. During tumorigenesis, metastasis, and recurrence, subsequent germline clones initiate a cascade of increasingly pathogenic CSCs through mechanisms such as heterotypic cell fusion, soma-to-germ transition, and polyploid giant cell structures (PGCCs). Irradiation and chemotherapies drive some of the very few surviving but dysfunctional CSCs through a PGCC repair pathway homologous to the MGRS pathway of carcinogenesis. The large number of PGCCs during metastasis and recurrence results from the perpetual germline cell damage and CSC poverty induced by oxygen levels above 6.0% O2 (germline hyperoxia).

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.

Post-ovulatory aging (POA) is an inevitable factor during some assisted reproduction technology procedures, and results in poor fertilization rates and impaired embryo development. This study used RNA sequencing analysis and experimental validation to study the similarities and differences between in vivo- and in vitro-matured porcine oocytes before and after POA. Differentially expressed genes (DEGs) between fresh in vivo-matured oocyte (F_vivo) and aged in vivo-matured oocyte(A_vivo) and DEGs between fresh in vitro-matured oocyte (F_vitro) and aged in vitro-matured oocyte(A_vitro) were intersected to explore the co-effects of POA. It was found that "organelles", especially "mitochondria", were significantly enriched GO terms. The expression of genes related to the “electron transport chain” and “cell redox homeostasis” pathways related to mitochondrial function significantly showed low expression patterns in both A_vivo and A_vitro groups. WGCNA analysis to explore gene expression modules specific to A_vivo. Trait-modules association analysis showed that the red modules were most associated with in vivo aging. There are a total of 959 genes in the red module, which are mainly enriched in “RNA binding”, “mRNA metabolic process”, etc. GO terms, and “spliceosome” and “nucleotide excision repair” pathways. DNAJC7, IK, and DDX18 were at the hub of the gene regulatory network. And these genes were all expressed higher in A_vivo. In summary, POA affects the organelle function of oocytes. A_vivo oocytes have some unique gene expression patterns. These genes may be potential anti-aging targets. This study helps us understand the detailed mechanism of POA and provides strategies for researching oocyte aging.

Background: In 2020, the incidence of cancer was 844,778 cases among the population aged 0 to 19 years. Ninety percent of the population under 18 years of age lives in low- and middle-income countries, where cancer survivors report adverse outcomes. disease, which negatively impacts individuals’ general health, emotional state and external factors such as academic performance. Therefore, the objective of this article was to report the performance of the WCST and the sociodemographic characteristics of oncopediatric patients from Cali, Colombia. We report the reliability of the WCST instrument and indicate the association between the type of cancer and executive functioning in patients. Methods: In a cross-sectional observational study, 24 oncopediatric patients were interviewed and evaluated via the WCST. Results: The mean age was 12.08 years (3.98), 20.8% were women, 70.8% had a diagnosis of leukemia, 8 patients had acquired brain deficits, and more than 75% had adequate functioning in terms of the indicators of executive functions. Robust statistics were used to explore the differences between the types of diagnoses and performance in executive functions, and no statistically significant differences were found (p = 0.156). We accumulated evidence that the WCST has a reliable Cronbach's α of 0.804 and that oncopediatric patients without brain deficits had high scores for executive functions (p = 0.002) with a moderate effect size (0.727). Conclusions: The WCST is reliable for discriminating executive function among pediatric cancer patients. The evidence suggests that there are no differences between the types of cancer evaluated and executive functioning in the participants.

This review provides an overview of advancements in plant genomics, emphasizing key stages in genomics projects and addressing associated challenges. Long read sequencing enables the cost-effective sequencing of plant DNA and assembly of highly continuous genome sequences - often even separating haplophases. Incorporating external hints, such as cDNA sequences from RNA-seq or full length cDNA sequencing, enhances the identification of gene models. While these steps enable high-throughput exploration of numerous plant genomes, a significant bottleneck lies in elucidating gene functions. The classical approach based on wet lab methods is impractical when dealing with thousands of genes in a new genome sequence. To overcome this challenge, computational tools harnessing existing information for cross species knowledge transfer are essential for expediting the functional annotation process. In support of researchers entering the field of plant genomics, a collection of recommended tools has been curated and is accessible at https://github.com/bpucker/ToolOverview.

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.

Vectorial Boolean functions and codes are closely related, and each corresponding domain gives been to each other. On the one hand, various requirements of binary linear codes are needed for their theatrical interests but, more importantly, for their practical applicants (such as few-weight codes or minimal codes for secret sharing, locally recoverable codes for storage, etc.). On the other hand, various criteria and tables have been introduced to analyse the security of S-boxes that are related to vectorial Boolean functions, such as the Differential Distribution Table (DDT), the Boomerang Connectivity Table (BCT), and the Differential-Linear Connectivity Table (DLCT). In previous years, two new tables have been proposed for which the literature was pretty abundant: the $c$-DDT to extend the DDT and the $c$-BCT to extend the BCT. In the same vein, we propose extended concepts to study further the security of vectorial Boolean functions, especially the $c$-Walsh transform, the $c$-autocorrelation, and the $c$-differential-linear uniformity, and its accompanying table, the $c$-Differential-Linear Connectivity Table ($c$-DLCT). We study these properties of the novel functions at their optimal level concerning these concepts and describe the $c$-DLCT of the crucial inverse vectorial (Boolean) function case. Finally, the derived functions could lead to new families of binary minimal codes, as the recent achievements on minimal codes from low differential uniformity. We draw new avenues for future research toward linear code designs.

Street view images can help us better understand the city environment and potential characteristics. With the development of computer vision and deep learning, the technology of semantic segmentation algorithms has become more mature. However, DeeplabV3+, which is commonly used in semantic segmentation, has shortcomings such as a large number of parameters, high requirements for computing resources, and easy loss of detailed information. Therefore, this paper proposes LM-DeeplabV3+, which aims to greatly reduce parameters and computations of the model while ensuring the segmentation accuracy. Firstly, the lightweight network MobileNetV2 is selected as the backbone network, and the ECA attention mechanism is introduced after MobileNetV2 extracts shallow features to improve the ability of feature representation; secondly, the ASPP module is improved, and on its basis, the EPSA attention mechanism is introduced to achieve cross-dimensional channel attention and important feature interaction; thirdly, a loss function named CL loss is designed to balance the training offset of multiple categories and better indicate the segmentation quality. This paper conducted experimental verification on the Cityspaces dataset, and the results showed that the mIoU reached 74.9%, which was an improvement of 3.56% compared to DeeplabV3+; the mPA reached 83.01%, which was an improvement of 2.53% compared to DeeplabV3+.

This work presents a new type of chaotic dynamical system originated from Dirichlet Eta function. Although the exposition describes only a bidimensional instance, it is certainly possible to construct higher dimensional such models. The novelty resides in the multitude of interesting characteristics concentrated in only one kind of dynamical system, mainly because of its simple abstract definition - it provokes dissipative, chaotic and itinerant behavior, and its paths typically display nonrecurring quasi-attractors and associate regions of ruin. In addition, it is discrete and nonautonomous, being additively driven by a simple real vector sequence. Also, the defining formulas have parameters which permit to activate bifurcatory effects, mainly related to setting the number of quasi-attractors and overall geometric complexity and diversity. In this fashion, it holds a certain similarity with classical itinerant chaotic systems, but it is a completely different object. One of its parameters is very influential and may be intuitively compared to a type of "potential energy", capable of changing the duration of sojourns etc. In this fashion, there is a potential opportunity to employ artificial inference techniques for designing specific structures on paths. Of course, the other parameters are also relevant, but not necessarily in the control of the number of quasi-attractors and the permanence periods near them. It is important to state that the described system was found during a previous investigation about certain features of the Riemann hypothesis, using the Dirichlet Eta function instead of the Riemann Zeta function - the components of the system under study here were part of certain series whose convergence had to be established, and that scenario produced this very positive side effect. The text also suggests an atypical, but important, potential application in philosophy: the representation of the Hindu concepts of Samsara and Moksha.

The purpose of this study was to investigate the effect of circuit training on β-amyloid, BDNF, and cognitive function in untrained obese elderly Korean women. The subjects for the study were aged 65–70 years, composed of the circuit training group(n=12) and control group(n=11). The 60-minute combined exercise was performed 3 times per week for 16 weeks. Exercise intensity was progressively increased from 40% HRR to 70% HRR. The test data were analyzed by paired t-test, independent t-test, and two-way repeated measures ANOVA, and the alpha level of .05 was set for all tests of significance. The findings of this study were as follows: β-amyloid significantly decreased after the exercise group had compared to before the exercise and BDNF and cognitive function significantly increased after the exercise group had compared to before the exercise. However, there were no significant changes in β-amyloid, BDNF, and cognitive function in the control group Therefore, it is suggested that the circuit training used in this study could be an effective exercise method for improving the risk factors of cognitive impairment in obese elderly Korean women.

The two main strategies used in this study are the binary representation and the decomposition of a natural number into many compound functions of odd function and even function. The Collatz conjecture regarding odd even numbers in number theory can be examined and discussed using them in this way: The sequence created by the finite iterations of the Collatz function becomes the ultimately periodic sequence if any natural number is the beginning value, proving the conjecture that has been held for 85 years.

Backgrounds Linear association has widely been assumed for prediction of aging-related fractional anisotropy (FA) decline in white matter of the brain. While useful for testing significance of the aging effect, it fails to identify a threshold age before and after which the age-FA association changes. Identification of such a threshold is often of clinical interest for timely intervention. Methods We employed a sigmoidal growth function to test a threshold effect in age triggering onset of cerebral decline in 21 white matter tracts, and compared its fitting performance to those of linear, and power regression. The study sample was a normal healthy cohort of 106 participants with ages in mid-life ranging from 18 to 60 years. Results Of the 21 white matter tracts analyzed, the posterior thalamic radiation showed better fit with sigmoidal curve model, compared to a linear or power regression. The estimated threshold age in years (95% confidence interval) were 47.2 (44.1-48.4). Conclusion While available evidence regarding the presence of a specific age threshold for cerebral decline in mid-life based on FA was limited, the posterior thalamic radiation exhibited a threshold age of 47.2. Beyond this age point, we observed a significant change in the FA risk pattern.

Two-dimensional (2D) bismuth oxyhalides (BiOX) have attracted much attention as potential optoelectronic materials. Expecting for their application diversity, we herewith systematically investigate the tunable properties of 2D BiOX by using first principles calculations. Their electronic and optical properties can be modulated by changing the number of monolayers, applying strain, and/or varying the halogen composition. The bandgap shrinks monotonically and approaches the bulk value, the optical absorption coefficient increases, and the absorption spectrum redshifts, as the layer number of 2D BiOX increases. Carrier transport property can be improved by applying tensile strain, and the ability of photocatalytic hydrogen evolution can be obtained by applying compressive strain. General strain engineering will be effective in linearly tune the bandgap of BiOX in a wide strain range. Strain together with halogen composition variation can tune the optical absorption spectrum to be on demand in the range from visible to ultraviolet. It suggests that that 2D BiOX materials have potential serving as tunable novel photodetectors, can be used to improve clean energy techniques, and are prospective in the field of flexible optoelectronics.

Nanoparticles are of great importance for various scientific and technological applications, drug discovery, ecology, molecular biology, etc. Size is a basic characteristic of any particle, and dynamic light scattering is beyond competition when measuring particle size in dispersions ranging from nanometers to micrometers. Unfortunately, this method has a serious problem in processing and interpreting experimental data. Instrument noise and polydispersity of the sample lead to the situation when one initial autocorrelation function corresponds to several different particle size distributions. Sometimes these different solutions of the inverse task can be found by changing parameters in the software. Sometimes the scientist cannot be suspicious of possible other solutions, having one result from the program. In this article I demonstrate the problem on model and experimental data using three known programs: CONTIN, the Malvern Zetasizer and DynaLS. I also present my own free program Autocor, which allows to test our own hypotheses about the modality and shape of the particle size distribution by optimizing the parameters of our own models with a small number of degrees of freedom.

Edge computing has emerged as a significant computing trend alongside the rapid expansion of the Internet of Things (IoT). Computing operations at the network’s edge offer a solution to the high latency and service overload challenges often associated with cloud computing. Additionally, the Secure Hash Algorithm-3 (SHA-3) plays a crucial role in ensuring data integrity and is implemented for numerous applications in the IoT field. Therefore, integrating the SHA-3 accelerator into edge computing is essential. Moreover, recent studies about SHA-3 have primarily focused on achieving high performance and optimizing resource utilization for SHA-3. However, these studies have overlooked the crucial aspect of data transfer between the external memory and the hash function block, as transfer time plays a significant role. This paper proposes an efficient SHA-3 architecture designed for System-on-Chip (SoC) Field Programmable Gate Array (FPGA) to address the aforementioned challenges and be suitable for real edge computing. The architecture contains three key techniques. First, the harmony of padding and Direct Memory Access (DMA) for managing the data transfer process and enhancing performance efficiency based on Serial Input to Parallel Output (SIPO) and a barrel shifter. Secondly, implementing internal pipelining within the Round Function (RF) to reduce critical path delays and optimize resource utilization. Finally, designing four modes (SHA3-224, SHA3-256, SHA3-384, and SHA3-512) to cater to various applications. Our architecture is implemented and tested on the DE10-Standard Development Kit (Cyclone V SX SoC-5CSXFC6D6F31C6N), which is integrated into the FPGA and is controlled by a Dual-Core ARM Cortex-A9 processor. The result is up to 38.34 Gbps in throughput and 5.61 Mbps/ALM in efficiency for the RF computation, 28.02 Gbps in throughput, and 3.63 Mbps/ALM for the full proposed architecture.

In applied mathematics, statistics, operation research, physics, and engineering mathematics, confluent representations of hypergeometric functions in one and two variables are known to exist, and their occurrence in a variety of applications is also well recognised. In this article, we intend to present a new derivation of the extended Watson summation theorem for the Kim et al. given series 4F3. We assessed four attractive integrals involving generalized hypergeometric function as an application. With a few particular cases, this note will come to an end. In the results given above, symmetry appears on its own.

It is estimated that about 50% of geriatric rehabilitation patients suffer from sarcopenia. Thereby, malnutrition is frequently associated with sarcopenia and dietary intake is the main modifiable risk factor. During hospitalization, older adults are recommended to consume more dietary protein than the current recommended dietary allowance of 0.8 g/kg body weight per day to optimize the recovery of muscular strength and physical function. This prospective study examined the effect of a short-term protein supplementation with protein-enriched foods and drinks on hand-grip strength, nutritional status and physical function in older patients at risk of malnutrition during a three week inpatient orthopedic rehabilitation stay. The Mini Nutritional Assessment (MNA) was used to assess malnutrition. Patients with a MNA score ≤ 23.5 points were randomly assigned to an intervention group (goal: to consume 1.2–1.5 g protein/kg body weight per day) or a control group (standard care). Both groups carried out the same rehabilitation program. Physical recovery parameters were determined at admission and discharge. There was a trend for participants in the intervention group to consume more protein than the control group (P = 0.058): 95.3 (SD 13.2) g/day as compared to 77.2 (SD 24.2) g/day, which corresponds to a mean protein intake of 1.6 (SD 0.3) g/kg/day vs. 1.3 (SD 0.5) g/kg/day. Dietary protein supplementation increased body weight by an average of 0.9 (SD 1.1) kg and fat mass by an average of 0.9 (SD 1.2) kg as compared with baseline (P = 0.039 and P = 0.050, respectively). There was no significant change in hand-grip strength, body composition and physical function. In conclusion, a short-term intervention with protein-enriched foods and drinks enabled older patients at risk of malnutrition to increase their protein intake to levels that are higher than their required intake. In these older individuals with appropriate protein intake, dietary protein supplementation did not result in a greater improvement in physical recovery outcomes during short-term inpatient rehabilitation. The intervention improved dietary protein intake, but further research (e.g., a full-scale randomized controlled trial with sufficient power) is required to determine the effects on physical function outcomes.

Transcatheter aortic valve replacement (TAVI) improves event-free survival in patients with severe aortic stenosis, but patients’ exercise capacity remains poor after the procedure. Therefore, we sought to compare the effects of supervised centre-based exercise training program and unsupervised exercise routine on exercise capacity and vascular function in patients after TAVI. Patients were randomised to either centre-based exercise training (12-24 sessions of combined aerobic and low-weight resistance training twice weekly for 8-12 weeks) or unsupervised home-based exercise routine (initial appraisal with detailed recommendations and monthly follow-up). Exercise capacity (cardiopulmonary testing) and vascular function (ultrasonographic measurement of flow-mediated vasodilation [FMD] and arterial stiffness) were assessed at baseline and after the study period. We included 23 patients (mean age 81 years, 61% women), with higher-than-expected drop-out rates (41%) because of the coronavirus-19 pandemic outbreak. Exercise capacity improved over time, irrespective of intervention group: 0.09 ml/min/kg increase in peak oxygen uptake (95%CI [0.01-0.16]; p=0.02), 8.2 Watts increase in workload (95%CI [0.6-15.8]; p=0.034), and 47 seconds increase in cumulative exercise time (95% CI [5.0-89.6]; p=0.029). A between-group difference in change over time (treatment effect) was detected only for FMD (4.49%; 95% CI [2.35; 6.63], p < 0.001), but not for other outcome variables. Both supervised and unsupervised exercise training improve exercise capacity and vascular function in patients after TAVI, with supervised exercise training possibly yielding larger improvements in vascular function, as determined by FMD.

Within Data Science scenario both Machine Learning (ML) and Neural Networks (NNs) are widely used for a plethora of applications, spanning from engineering to biology, from finance to medicine. Meanwhile, the pure analytical analysis of related models used often lacks of detailed description. Trying to close this gap, during recent years the theory of Optimal Transport start becoming more a more popular within the Data Science arena, since it allows for efficient and scalable solutions about what can be broadly referred as Artificial Intelligence tasks, particularly by using approximate solvers through linear programming. More precisely, let us recall that both in ML and statistics, minimizing an objective function over the space of probability measures is fundamental problem. Along this line, the training of a Neural Network through Stochastic Gradient Descent has been shown to be equivalent to a gradient flow in Wasserstein space. Moreover, in many applications, it is crucial to consider the causal structure of the data generating process. In view of providing a possibly unifying as well as efficient approach to latter questions, we consider the Adapted Optimal Transport (AOT) method which allows to incorporate causality constraints into the optimization of the Wasserstein distance. AOT is particularly useful when dealing with laws of stochastic processes, being exploitable to encode an adapted (non-anticipative) constraint into the allocation of mass of the classical OT problem. Accordingly, we provide an in depth exploration of the connections between supervised learning and AOT, providing theoretical insights into the benefits of including causality constraints for developing more robust, scalable and accurate algorithms, while maintainig their computational efforts at minimum possible levels.

The transverse momentum distribution of J/ψ mesons produced in pp collisions at the center-of-mass energy 5 TeV, 7 TeV，and 13 TeV is described by the modified Hagedorn function which is based on the Tsallis function and Hagedorn function. The calculated results by the modified Hagedorn function are in accord with experimental data measured by the LHCb Collaboration at LHC. The related parameters are obtained and analyzed.

This paper is a response to the EPR paper titled: "Can quantum-mechanical description of physical reality be considered complete?", published in Physical Review in 1935. A quantum-mechanical (QM) measurement function describes a distribution of local results, while each empirical measurement process produces one result as exact as allowed by a measuring instrument calibrated to a non-local unit standard. Repeating these empirical measurements produces a Gaussian distribution of measurement results. The QM and empirical measurement result distributions can be compared. To precisely compare a QM measurement function describing a distribution of eigenvectors to a distribution of repetitive empirical measurement results, it is necessary to determine, by calibration, the precision of the eigenvectors to the same standard as the empirical results, because each eigenvector evidences uncertainty relative to a standard. When the calibration process is recognized as formal as well as empirical, QM measurement function results and metrology measurement process results are unified.

The innate immune system is the first line of host defense sensing viral infection. Manganese (Mn) has recently been found to be involved in the activation of innate immune DNA sensing cGAS-STING pathway and subsequent anti-DNA virus function. However, whether Mn2+ mediates host defense against RNA viruses is still unclear. In the current study, we demonstrated that Mn2+ exhibited antiviral effects against various animal and human viruses including RNA viruses such as PRRSVs and the VSV as well as a DNA virus such as the HSV1 in a dose-dependent manner. Moreover, cGAS and STING were both investigated in the Mn2+ mediated antiviral roles using the knockout cells made by CRISPR-Cas9 approach. Unexpectedly, the results revealed that neither cGAS knockout nor STING knockout had any effect on Mn2+ mediated antiviral functions. Nevertheless, we verified that Mn2+ promoted the activation of cGAS-STING signaling pathway. These findings suggest that Mn2+ has broad spectrum antiviral activities in a cGAS-STING pathway independent manner. This study also provides significant insights into redundant mechanisms participating in the Mn2+ antiviral functions and also indicates new target for Mn2+ antiviral therapeutics.

Bright morning light (BML) entrains the body clock, modulates circadian rhythm, and improves sleep-wake disturbances. However, its impact on the autonomic nervous system (ANS) at night remains unclear. Hence, we investigated the effects of BML exposure on activities of the parasympathetic nervous system (PSNS) and sympathetic nervous system (SNS) at night. This non-randomized controlled pilot study included participants ≥60 years, diagnosed with a type of dementia or cognitive disorder. We excluded participants with pacemakers. The treatment group received 2500 lx BML, whereas the control group received approximately 200 lx of general lighting. We measured the heart rate variability to quantify ANS activity. The treatment group displayed significantly increased high-frequency (HF) power (Roy's largest root=2.44; P<.01) and insignificantly decreased normalized low-frequency (LF%) power. The corresponding low-frequency/high-frequency ratio (LF/HF), insignificant decrease, and cognitive function were correlated with PSNS activity (Roy's largest root=3.92; P<.01), which is effective for moderate dementia. BML exposure reduced SNS activity and enhanced PSNS activity at night, which consequently affected cognitive function. Furthermore, the light washout intervention markedly increased SNS activity at night. BML therapy may be a useful clinical tool for alleviating the deterioration of cognitive function.

Increased definite power, reduced cost, and dynamic construction are the important features required by electric motors for various applications. One such motor accommodating all the requisites mentioned above is Switched reluctance. Applications pertaining to small, commercial, and EV find Switched reluctance machine as a developing competitor to the conventional induction and permanent magnet motors. Though SRMS contribute a considerable number of advantages over induction motors and permanent magnet motors, the primary disadvantages pertaining to SRMs are the torque ripple, especially at high-speed operation, and the resulting acoustic noise. These disadvantages may not always be detrimental to the systems in entirely all cases, but depending on the application to be employed, torque ripple and acoustic noise form are detrimental to the system. This paper reviews the technology status and recent trends in the minimization of torque ripples switched reluctance machines.

The estimation of ecological service system value of water resources in Tarim river basin is of great significance for resource allocation management and ecological protection. However, there is still no unified and complete evaluation method for ecological service system value of inland river in China. Based on the perspective of the whole value chain, the study classifies its ecological service functions, and divides 11 sub-categories into 4 categories (supply, regulation, culture and support) as evaluation indicators to carry out quantitative evaluation. The results showed that the total value of ecological service system in Tarim river basin in 2018 was 4156.5247×108 Yuan, and the value of regulating function, cultural function, supporting function and supply function were successively from high to low, which were as follows: 2565.6825×108 Yuan, 1009.5471×108 Yuan, 884.0770×108 Yuan, 20.3350×108 Yuan, among which the value of regulation function is dominant.

This study reports a computational investigation on the antioxidant activity of five plant food benzoic acid derivatives, namely gallic acid (GA), para-hydroxybenzoic acid (PHBA), protocatechuic acid (PCA), syringic acid (SA), and vanillic acid (VA). Based on computed thermodynamics parameters, a detailed comparative debate is developed concerning their free radical scavenging activity in the gas phase and polar solutions (in water and methanol solvents). This discussion goes on to elucidate both the most preferred mechanism and the order of antioxidant activity for these molecules in each environment. Paradoxically, calculations using the harmonic oscillator model of aromaticity (HOMA) suggest that H abstraction radicals gain in stability as the central benzene ring loses in structural aromaticity. Finally, spin densities and fukui function f⁰ seem to be good indicators of the local reactivity of these compounds towards free radicals.

The problem of reliable function computation is extended by imposing privacy, secrecy, and storage constraints on a remote source whose noisy measurements are observed by multiple parties. The main additions to the classic function computation problem include 1) privacy leakage to an eavesdropper is measured with respect to the remote source rather than the transmitting terminals’ observed sequences; 2) the information leakage to a fusion center with respect to the remote source is considered as a new privacy leakage metric; 3) the function computed is allowed to be a distorted version of the target function, which allows to reduce the storage rate as compared to a reliable function computation scenario in addition to reducing secrecy and privacy leakages; 4) two transmitting node observations are used to compute a function. Inner and outer bounds on the rate regions are derived for lossless and lossy single-function computation with two transmitting nodes, which recover previous results in the literature. For special cases that include invertible and partially-invertible functions, and degraded measurement channels, exact lossless and lossy rate regions are characterized, and one exact region is evaluated for an example scenario.

After proposing the Principle of Minimum Gravitational Potential, in a pursuit to find the explanation behind the correction to Newton's gravitational potential that accounts for Mercury's orbit, by finding all the higher-order corrections it is shown that the consequences of the existence of speed of light for gravity are not yet fully explored.

In light of Liu \emph{at el.}'s original works, this paper revisits the solution of Burgers's nonlinear equation $u_t=a(u_x)^2+bu_{xx} $. The study found two exact and explicit solutions for groups $G_4$ and $G_6$, as well as a general solution. A numerical simulation is carried out. In the appendix a Maple code is provided

The gastrointestinal (GI) tract is a continuous channel through the body that consists of the esophagus, the stomach, the small intestine, the large intestine, and the rectum. Its primary functions are to move the intake of food for digestion before storing and ultimately expulsion of feces from the rectum through the anal sphincter. The mechanical behavior of GI tissues thus plays a crucial role for GI function in health and disease. The mechanical properties are typically characterized by a constitutive biomechanical model, which is a mathematical representation of the relation between load and deformation in a tissue. Hence, validated biomechanical constitutive models are essential to characterize and simulate the mechanical behavior of the GI tract under physiological and pathological conditions. Numerous constitutive models have consequently been proposed over the past three decades, mainly inspired by work done in cardiovascular tissues. Here, a comprehensive review of these constitutive models is provided. This review is limited to studies where a model of the strain energy function is proposed to characterize the stress-strain relation of a GI tissue. Several needs are identified for more advanced modeling of GI biomechanics including: 1) Microstructural models that provide actual structure-function relations; 2) Validation of coupled electro-mechanical models accounting for active muscle contractions; 3) Human data under physiological and pathological conditions to develop and validate models. The findings from this review provide guidelines for using existing constitutive models as well as perspective and directions for future studies aimed at establishing new constitutive models for GI tissues.

In this paper, we examine two strategies for boosting the performance of ensembles of Siamese networks (SNNs) for image classification using two loss functions (Triplet and Binary Cross Entropy) and two methods for building the dissimilarity spaces (FULLY and DEEPER). With FULLY, the distance between a pattern and a prototype is calculated by comparing two images using the fully connected layer of the Siamese network. With DEEPER, each pattern is described using a deeper layer combined with dimensionality reduction. The basic design of the SNNs takes advantage of supervised k-means clustering for building the dissimilarity spaces that train a set of support vector machines, which are then combined by sum rule for a final decision. The robustness and versatility of this approach are demonstrated on several cross-domain image data sets, including a portrait data set, two bioimage and two animal vocalization data sets. Results show that the strategies employed in this work to increase the performance of dissimilarity image classification using SNN is closing the gap with standalone CNNs. Moreover, when our best system is combined with an ensemble of CNNs, the resulting performance is superior to an ensemble of CNNs, demonstrating that our new strategy is extracting additional information.

This document introduces a new cryptosystem mixing two improvement standards generally used for text encryption, in order to give birth a new color image encryption algorithm capable of dealing with known attacks. Firstly, two substitution matrixes attached to a strong replacement function will be generated for advanced Vigenere technique application. At the end of this first round, the output vector is subdivided into size blocks according to the used chaotic map, for acting a single enhanced Hill circuit insured by a large inversible matrix. A detailed description of such a large involutive matrix constructed using Kronecker products will be given. accompanied by a dynamic translation vector to eliminate any linearity. A solid chaining is established between the encrypted block and the next clear block to avoid any differential attack. Simulations carried out on a large volume of images of different sizes and formats ensure that our approach is not exposed to any known attacks.

This studies the plasmonic properties of the bimetallic quantum dot Ag@Au core-shell nanostructures embedded in the non-absorbent host medium. Local field enhancement factor and coefficient of absorption of Ag-core and Au-shell are primarily studied based on quasi-static approximation of classical electrodynamics for 6-10 nm composite radius. In this quantum dot geometry, two set of plasmonic resonances in visible spectral region are observed: the first resonance associated with inner interface of gold (Ag@Au) and the second resonance associated with outer interface of gold (Au@medium). The two plasmonic resonances are close each other and enhanced when the size of composite decreased for a fixed core size while shifted to in opposite direction and the amplitude of peak decreased when the core size is increased for a fixed composite size. For the optimized size of core/composite or shell thickness and other parameters to the desired values, such type of composites are recommended for various applications like; photocatalysis, biomedical, nano-optoelectronics.

To characterize the mechanisms by which the highly-conserved exocyst trafficking complex regulates eye physiology in zebrafish and mice, we focused on exoc5 (aka sec10), a central exocyst component. We analyzed both exoc5 zebrafish mutants and retinal pigmented epithelium (RPE)-specific Exoc5 knockout mice. Exoc5 is present in both the non-pigmented epithelium of the ciliary body and in the RPE. In this study we set out to establish an animal model to study the mechanisms underlying the ocular phenotype and to establish if loss of visual function is induced by postnatal RPE Exoc5-deficiency. Exoc5-/- zebrafish showed smaller eyes, with decreased number of melanocytes in the RPE and shorter photoreceptor outer segments. At 3.5 days post fertilization, loss of rod and cone opsins were observed in zebrafish Tg:exoc5 mutants. Mice with postnatal RPE-specific loss of Exoc5 showed retinal thinning associated with compromised visual function, and loss of visual photoreceptor pigments. This retinal phenotype in Exoc5-/- mice was present at 20-weeks, and the phenotype was more severe at 27-weeks, indicating progressive disease phenotype. We previously showed that the exocyst is necessary for photoreceptor ciliogenesis and retinal development. Here, we report that exoc5 mutant zebrafish and mice with RPE-specific genetic ablation of Exoc5 develop abnormal RPE pigmentation, resulting in retinal cell dystrophy and loss of visual pigments associated with compromised vision. As RPE cells are “downstream” of photoreceptor cells in the visual process, these data suggest exocyst-mediated retrograde communication and dependence between the RPE and photoreceptors.

Recent studies suggest that the developmental curves in adolescence, related to the development of executive functions, could be fitted to a non-linear trajectory of development with progressions and retrogressions. Therefore, the present study proposes to analyze the pattern of development in Perceptual Inhibition (PI), considering all stages of adolescence (early, middle, and late) in intervals of one year. To this aim, we worked with a sample of 275 participants between 10 and 25 years, who performed a joint visual and search task (to measure PI). We have fitted exGaussian functions to the probability distributions of the mean response time across the sample and performed a covariance analysis (ANCOVA). The results showed that the 10- to 13-year-old groups performed similarly in the task and differ from the 14- to 19-year-old participants. We found significant differences between the older group and all the rest of the groups. We discuss the important changes that can be observed in relation to the nonlinear trajectory of development that would show the PI during adolescence.

In this work, we treat a prediction problem via the conditional hazard function of a scalar response variable Y given a functional random variable X by using the local linear technique. The main purpose of this paper is to investigate the asymptotic normality of the nonparametric estimator of the conditional hazard function, under some general conditions. A simulation study, conducted to assess finite sample behavior, demonstrates the superiority of our method than the standard kernel method

In real financial market, the delayed market feedback and the delayed effect of government macro-control are inevitable. And both the delay of market feedback and the delay of macro-control effect bring about the mathematical difficulties in studying stabilization and synchronization of the hyper-chaotic financial system. However, employing Lyapunov function method, differential mean value theorem, suitable bounded hypotheses and pulse control technology results in the globally asymptotical stabilization and synchronization criteria. It is the first paper to drive the stabilization and synchronization criteria under the assumptions of the double delays. Finally, numerical examples illuminate the effectiveness of the proposed methods.

Epigenetic aging has been found associated with a number of phenotypes and diseases. Few studies investigated its effect on lung function in relatively older people. However, this effect has not been explored in younger population. This study examines whether lung function at adolescent can be predicted with epigenetic age accelerations (AAs) using machine learning techniques. DNA methylation based AAs were estimated in 326 matched samples at two time points (at 10 years and 18 years) from the Isle of Wight Birth Cohort. Five machine learning regression models (linear, lasso, ridge, elastic net, and Bayesian ridge) were used to predict FEV1 (Forced Expiratory Volume in one second) and FVC (Forced Vital Capacity) at 18 years from feature selected predictor variables (based on mutual information) and AA changes between the two time points. The best models were ridge regression (R2 = 75.21% ± 7.42%; RMSE = 0.3768 ± 0.0653) and elastic net regression (R2 = 75.38% ± 6.98%; RMSE = 0.445 ± 0.069) for FEV1 and FVC, respectively. This study suggests that the application of machine learning in conjunction with tracking changes in AA over life span can be beneficial to assess the lung health in adolescence.

The corrected mechanism model of battery voltammetric function is helpful to guide the development and application of battery. There are two scientific issues that need to be answered: First, how many mechanisms do batteries have; Second, how to establish the mechanism model separately under the overlapping of these mechanisms. Volt-ampere characteristics of both linear state and nonlinear state exist; the monotonic decreasing of volt-ampere characteristics indicates that the battery have only three kinds of mechanisms. Without changing the basic form of the function and under the principle of the mechanism function’s working region considered, we propose a mechanism function which satisfies the monotonic decreasing characteristic of the voltammetric curve of battery, via the derivative law of each mechanism function in the voltammetric function of battery. By using the voltammetric data, the obtained cell mechanism function can accurately predict the potential (current or voltage) when the independent variable of the cell is zero, and provide the theoretical basis for the internal working mechanism of the cell, which can guide the practice.

The Nocturnal Bottleneck explains how mammals evolved from their reptilian ancestors after inverting the chronotype, form diurnal to nocturnal. Pre-mammals traded-off the excellent visual system of their ancestors for improvements in audition and in olfactory telencephalon, needed for efficient orientation in the dark. This was how the mammalian nocturnal telencephalic wakefulness was born. However, the modified visual system of those pre-mammals became sensitive to the dangerous diurnal light and the exposure would involve a high risk of blindness and death. Therefore, pre-mammals had to remain immobile with closed eyes hidden in lightproof burrows during light time. This was the birth of the mammalian sleep. Typical reptiles distribute their wake time cycling between Basking Behavior, to attain the preferred body temperature, and poikilothermic Goal Directed Behavior, to perform life sustaining tasks. These cycles persisted during the new mammalian sleep. However, as the behavioral output had to be blocked during light time, the paralyzed reptilian Basking Behavior and Goal Directed Behavior cycles became the NREM and REM cycles, respectively. This was how NREM and REM cycles remained incorporated within the mammalian sleep. After the Cretaceous-Paleogene extinction, the environmental pressure for nocturnal life was softened, allowing high variability in chronotype and sleeping patterns. This permitted some mammalian groups, e.g., primates, to begin the quest for diurnal wake.Concluding, sleep constituted an additional bottleneck in the mammalian evolution. The reduced population of pre-mammals that was able to develop sleep during light time, including NREM and REM, became full mammals and survived; the remainder perished.

In [18], Kim et al. introduced the degenerate poly-Bernoulli polynomials by using polyexponential function. In this paper, we study the degenerate poly-Frobenius-Genocchi polynomials, which are called the type 2 degenerate poly-Frobenius-Genocchi polynomials, by means of polyexponential function. Then, we derive some useful relations and properties. We derive type 2 degenerate poly-Frobenius-Genocchi polynomials equal a linear combination of the degenerate Frobenius-Genocchi polynomials and Stirling numbers of the first kind. Furthermore, we introduce type 2 degenerate unipoly-Frobenius-Genocchi polynomials by means of unipoly function and derive explicit multifarious properties.

We have presented a controllable and human-readable polynomial neural network (CR-PNN) that is the first human-readable neural network. One can imagine its influence on system identification. Subsequently, we developed a relation spectrum in a medical application, which is likely to stand alongside the Fourier spectrum. However, the system analysis methodology is incomplete in contrast to signal processing methodology. Here, we presented the system filters for the first time. In this paper, we used the simulation system to verify the availability of the system analysis methodology. The system analysis methodology showed great properties in system identification and filter. The contribution of this paper is the system analysis methodology: transform method (CR-PNN), relation spectrum, and system filter design.

Modularity is arguably one of the most influential theses guiding research on brain and cognitive function since phrenology. This paper considers the following question: is modularity entailed by recent Bayesian models of brain and cognitive function, especially the predictive processing framework? It starts by considering three of the most well-articulated arguments for the view that modularity and predictive processing work well together. It argues that all three kinds of arguments for modularity come up short, albeit for different reasons. The analysis in this paper, although formulated in the context of predictive processing, speaks to broader issues with how to understand the relationship between functional segregation and integration and the reciprocal architecture of the predictive brain. These conclusions have implications for how to study brain and cognitive function. Specifically, when cognitive neuroscience works within an acyclic Markov decision scheme, adopted by most Bayesian models of brain and cognitive function, it may very well be methodologically misguided. This speaks to an increasing tendency within the cognitive neurosciences to emphasise recurrent and reciprocal neuronal processing captured within newly emerging dynamical causal modelling frameworks. The conclusions also suggest that functional integration is an organising principle of brain and cognitive function.

There is an important complementarity between experimental methods for the study of high-temperature viscoelasticity in the time and frequency domains, that has not always been fully exploited. Here we show that parallel processing of forced-oscillation data and microcreep records, involving consistent use of either Andrade or extended Burgers creep-function models, yields a robust composite modulus-dissipation dataset spanning a broader range of periods than either technique alone. In fitting this dataset, the alternative Andrade and extended Burgers models differ in their partitioning of strain between the anelastic and viscous contributions. The extended Burgers model is preferred because it involves a finite range of anelastic relaxation times, and accordingly a well-defined anelastic relaxation strength. The new strategy offers the prospect of better constraining the transition between transient and steady-state creep, or equivalently, between anelastic and viscous behaviour.

In this work, we establish some new Hermite-Hadamard type inequalities for convex functions via conformable fractional integral. Moreover, we show that through the conformable fractional integral we can find some new Hermite-Hadamard type inequalities for convex functions via the classical integrals.

Phenomenon of vacuum fluctuations of virtual particles in high energy physics has been mathematically modeled by a third order differential equation. Aim of present theory is to unravel underlying mathematical equation capable of explaining microscopic phenomenon of vacuum fluctuations. Solution of such a differential equation after applying appropriate boundary conditions gives an acceptable wave function i.e. . Operation of energy and time operator on this wave function proves that these operators do not hold commutative property. Time energy uncertainty principle has been derived by calculating variance of energy and time for the same wave function.

As the problem of light pollution becomes more serious, more and more scholars pay attention to this issue and carry out related research. In the perspective of cities, the measurements of light pollution mainly focus on the brightness of the sky or artificial lighting on the ground. However, there is lack of research on the whole urban space. With the two-dimensional brightness analyses, this paper processes the changes of the light environment of the whole urban space into image quantization. It gets the 3D and 2D light environment changes of luminance distribution, color temperature distribution and chromaticity in the three space layers, the ground layer, the urban canopy layer and the sky layer, from dusk with natural light to night with artificial lighting completely. It is found that the brightness difference between the light environments among the three city levels gradually reduces with the measuring time, and the final values maintain at 0.11~0.25 cd/m². In the ground layer, the light environment is mainly affected by the lighting facilities, and vegetation can prevent the light from scattering up. The light environment of the urban canopy layer is the brightest in the whole city space and has the largest influence on the sky layer. The color concentrates in the range of yellow and red. The color temperature near the ground distributes in 3000K~15000K, and near the sky distributes in 2300K~2700K which is warmer than the natural night sky. The sky brightness of Dalian city is about 951 times than the natural night sky.

We explore the use of inverse multiquadratic (IMQ) functions as basis functions when solving the vibrational Schrödinger equation with the rectangular collocation method. The quality of the vibrational spectrum of formaldehyde (in six dimensions) is compared to that obtained using Gaussian basis functions when using different numbers of width-optimized IMQ functions. The effects of the ratio of the number of collocation points to the number of basis functions and of the choice of the IMQ exponent are studied. We show that the IMQ basis can be used with parameters where the IMQ function is not integrable. We find that the quality of the spectrum with IMQ basis functions is somewhat lower that that with a Gaussian basis when the basis size is large and for a range of IMQ exponents. The IMQ functions are, however, advantageous when a small number of functions is used or with a small number of collocation points e.g. when using square collocation.

In this paper, we use the Principal Components Logistic Regression as a technique to reduce the variables being used in Credit Scoring Modeling. Specifically, we construct two models in which greek enterprises are classified, through their credit behavior and we evaluate them, relying on real data. In general, we propose a general way to use PC Regression, in case that we have high correlations and categorical variables in the sample.

This paper employs the two-step procedure developed by Cheung and Ng (1996) to analyze the causality-in-mean and causality-in-variance between the housing and stock markets of the UK. The empirical findings make two key contributions. First, although previous studies have indicated a one-way causal relation from the housing market to the stock market in the UK, this paper discovered a two-way causal relation between them. Second, a causality-in-variance as well as a causality-in-mean was detected from the housing market to the stock market.

In this paper, we pursue and investigate the solutions for fractional kinetic equations, involving Bessel-Struve function by means of their Sumudu transforms. In the process, one Important special case is then revealed, and analyzed. The results obtained in terms of Bessel-Struve function are rather general in nature and can easily construct various known and new fractional kinetic equations.

Recently, representation formulae and monotonicity properties of generalized k-Bessel functions, Wk v,c., were established and studied by SR Mondal [24]. In this paper, we pursue and investigate some of their image formulae. We then extract solutions for fractional kinetic equations, involving Wk v,c, by means of their Sumudu transforms. In the process, Important special cases are then revealed, and analyzed.

In the note, the authors find several simple and explicit forms for a family of inhomogeneous linear ordinary differential equations studied in "D. Lim, Differential equations for Daehee polynomials and their applications, J. Nonlinear Sci. Appl. 10 (2017), no. 4, 1303-1315; Available online at http://dx.doi.org/10.22436/jnsa.010.04.02".

Proteomics research has become one of the most important topics in the fields of life science and natural science. At present, research on protein–protein interaction networks (PPINs) mainly focuses on detecting protein complexes or function modules. However, existing approaches are either ineffective or incomplete. In this paper, we investigate function module detection mechanisms in PPIN, including open databases, existing detection algorithms and recent solutions. After that, we describe the proposed solution based on simplified swarm optimization (SSO) algorithm and gene ontology knowledge. The proposed solution implements SSO algorithm for clustering proteins with similar function, and imports biological gene ontology knowledge for further identifying function complexes and improving detection accuracy. Furthermore, we use four different categories of species dataset for experiment: Fruitfly, Mouse, Scere, and Human. The testing and analysis result show that the proposed solution is feasible, efficient and could achieve a higher accuracy of prediction than existing approaches.

The purpose of this paper is to provide empirical evidence to water policy-makers and the evaluation of the application of economic instruments such as price and other factors affecting demand, they contribute to improved decision-making around water management in the Biosphere Reserve El Vizcaino, Mexico. It was estimated a dynamic function with average price specification and other price perception specification. The findings show that consumers react to average price perceived and not the marginal price; long-run price elasticity is higher than short-run and both elasticities are inelastic. Elasticities inelastic with rising prices generate high incomes to improve water planning, supply quality and expand service coverage. The results suggest that the level of knowledge of users on the price is key to take into account restructuring rates in a scenario where the consumer has asymmetric information and themselves achieve goals of economic efficiency, social equity and environmental sustainability.

This paper focuses on the problem of finite-time stabilization of homogeneous, non-Lipschitz systems with dilations. A key contribution of this paper is the design of a virtual recursive Hölder, non-Lipschitz state feedback which renders the non-Lipschitz systems in the special case dominated by a lower-triangular nonlinear system, finite-time stable. The proof is based on a recursive design algorithm developed recently, to construct the virtual Hölder continuous, finite-time stabilizer as well as a C¹ positive definite and proper Lyapunov function that guarantees finite-time stability of the non-Lipschitz non-linear systems.

Endolysin of bacteriophage T5 (EndoT5) is a Zn2+-dependent and Ca2+-activated L-alanyl-D-glutamate peptidase that hydrolyses peptidoglycans during the destruction of the cell wall of the phage host bacterium Escherichia coli. To elucidate the mechanism of calcium activation, the spatial solution structure of EndoT5 in a complex with two ions - catalytic Zn2+ and regulatory Ca2+ (EndoT5-Zn2+Ca2+, PDB ID: 8P3A) was determined by high-resolution NMR and deposited in the Protein Data Bank. We show that coordination of the Ca2+ ion fix the spatial position of polar amino acid residues D113, N115 and S117. As a result, the intramolecular mobility of extended protein loops (residues 40-70 and 111-132) is significantly reduced compared to the mobility of these loops in the structure of an enzyme containing only a catalytic a Zn2+ ion (EndoT5-Zn2+, PDB ID: 2MXZ). In the stabilized EF-like calcium-binding loop (residues 111-132), the number of van der Waals interactions with amino acid residues of the globular core of the protein increases. The binding of the Ca2+ ion is accompanied by the selection of the functional states of both extended loops of the enzyme (residues 40-70 and 111-132), because of which EndoT5-Zn2+Ca2+ acquires the structural integrity necessary for catalysis. Therefore, the mechanism of activation of L-alanyl-D-glutamate peptidase of bacteriophage T5 by Ca2+ ions involves stabilization of the enzyme molecule in a catalytically active “open” conformation. This work sheds light on the structural grounds of the ion-dependent functional proteoforms of this interesting protein.

The cellular behavior of Voronoi tessellation has generated interest due to its applicability in various fields and its notable structural properties. Controlling factors such as the gradient of the cells, the position of seed points and the thickness of the arms allows for adjusting rigidity and flexibility according to specific needs. This article analyzes the state of the art of this technique, exploring its modification for applications in engineering and design, complemented with information on natural structural properties. This comprehensive analysis provides a complete overview of Voronoi tessellation and its potential in engineering and design, categorizing methodologies according to selected processing methods and highlighting techniques for altering structural behavior. Additionally, it emphasizes the integration of biomimetic approaches, connecting nature with technology to foster continuous innovation. Finally, the article addresses encountered limitations, offering future perspectives for the cellular technique and highlights the complexity of reproducibility due to reserved or generalized steps, despite the significant diversity in implemented techniques.

Chikungunya virus (CHIKV) is a mosquito borne RNA virus that poses an emerging threat to humans. As other RNA viruses, CHIKV encodes an error-prone RNA polymerase which, in addition to full-length genomes, gives rise to truncated, non-functional genomes coined defective viral genomes (DVGs). DVGs have been intensively studied in the context of therapy, as they can inhibit viral replication and dissemination in their hosts. In this work, we interrogate the influence of viral RNA secondary structures on the production of CHIKV DVGs. We experimentally map RNA secondary structures of CHIKV genome using selective 2′-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP), which couples chemical labelling with next-generation sequencing. We correlate the inferred secondary structure with preferred deletion sites of CHIKV DVGs. We document an increased probability of DVG generation with truncations at unpaired nucleotides within the secondary structure. We then generated a CHIKV mutant bearing synonymous changes at the nucleotide level to disrupt existing RNA secondary structure (CHIKV-D2S). We show that CHIKV-D2S presents altered DVG generation compared to wild-type virus, correlating with its change in RNA secondary structure obtained by SHAPE-MaP. Our work thus demonstrates that RNA secondary structure impacts CHIKV DVG production during replication.

Tertiary lymphoid structures (TLSs) have become the focus of antitumor immunity. However, the prognostic significance of TLSs in epithelial ovarian cancer (EOC) treated with primary debulking surgery (PDS) or interval debulking surgery (IDS) remains unelucidated. This retrospective study examined the prognostic value of TLSs in tumor tissues obtained during PDS and IDS. Pathological specimens were collected from patients with EOC who underwent PDS or IDS between 2017 and 2020 at the National Cancer Center Hospital East. The correlation of tumor-infiltrating lymphocyte frequency, TLS presence, and PD-L1 expression with progression-free survival (PFS) and overall survival (OS) and the correlation between TLS and PD-L1 expression were analyzed. Overall, 25 specimens (15 from PDS and 10 from IDS) were analyzed. The presence of TLS was associated with a significantly longer OS in patients who underwent PDS but not in patients who underwent IDS. No correlation was identified between TLS and PFS in patients with PDS or with IDS. However, TLS was positively correlated with PD-L1 positivity. The prognostic impact of TLS, specifically in pre-chemotherapy specimens, and a positive correlation between TLS and PD-L1 indicate the potential of TLS as a meaningful biomarker for understanding antitumor immunity and developing immunotherapy for EOC.

This study analyzes the relevance of governance structure for efficiency in revenue collection by Brazilian Water Utilities (WUs). Data was collected from the National Information System on Sanitation (SNIS) for 127 Brazilian WUs, covering a balanced longitudinal panel from 2018 to 2022. Governance structures evaluated included Ownership (public or private) and Corporatization (publicly traded or not). In scientific databases, we did not find studies on the efficiency of specific WUs in collecting customer bills for services rendered and its relationships with this type of governance; thus, this would be the main innovative contribution of the study to the previous literature. In the first stage, the study utilized the Dynamic Slack Based Model (DSBM) to assess revenue collection efficiency. In the second stage, an econometric model with Generalized Estimating Equations (GEE) to explain the efficiency. The findings revealed a global average inefficiency of 50.47% in revenue collection. Corporatization was linked to higher collection efficiencies, while ownership type was significant, but with lower collection efficiency. Factors such as tariff accessibility, urbanization, and the COVID-19 pandemic also influenced efficiency. The study suggests regulatory bodies should consider these insights to implement policies that prevent inefficiencies from affecting the tariff system for services.

Micro elastofluidics is a transformative branch of microfluidics, leveraging fluid-structure interaction (FSI) at the microscale to enhance the functionality and efficiency of various microdevices. This review paper elucidates the critical role of advanced computational FSI methods in the field of micro elastofluidics. By focusing on the interplay between fluid mechanics and structural responses, these computational methods facilitate the intricate design and optimisation of microdevices such as microvalves, micropumps, and micromixers, which rely on the precise control of fluidic and structural dynamics. In addition, these computational tools extend to the development of biomedical devices, enabling precise particle manipulation and enhancing therapeutic outcomes in cardiovascular applications. Furthermore, this paper addresses the current challenges in computational FSI and highlights the necessity for further development of tools to tackle complex, time-dependent models under microfluidic environments and varying conditions. Our review highlights the expanding potential of FSI in micro elastofluidics, offering a roadmap for future research and development in this promising area.

Thermal expansion of four alkaline-earth borates, namely Ca3B2O6 (0D), CaB2O4 (1D), Sr3B14O24 (2D) and CaB4O7 (3D), have been studied by in situ high-temperature powder X-ray diffraction (HTXRD). Strong anisotropy of thermal expansion is observed for the structures of Ca3B2O6 (0D) and CaB2O4 (1D) built up from BO3 triangles only: these borates exhibit the maximal expansion perpendicular to the BO3 plane, i.e. along the direction of weaker bonding in the crystal structure. Layered Sr3B14O24 (2D) and framework CaB4O7 (3D) built up from various B-O groups expand less anisotropically. Thermal properties of the studied compounds compared to the other alka-line-earth borates are summarized depending on the selected structural characteristics like anion dimensionality, residual charge per one polyhedron (BO3 BO4), cationic size, and structural com-plexity. For the first time these dependencies were established as an average for both types of polyhedra (triangle and tetrahedron) occurring in the same structure at the same time. The most common trends were identified for : (i) Melting temperature decreases as the dimensionality of the borate polyanion, and more precisely, as the residual charge per one polyhedron (triangle or tetrahedron) decreases; (ii) volumetric expansion decreases while the degree of anisotropy in-creases weakly when the residual charge decreases; (iii)both trends (i) and (ii) are most steady within borates built by the triangles only, while the borates built by both triangles and tetrahedra show a larger scatter in values.

(S)-1-Methyl-2-oxoimidazolidine-4-carboxylic acid 1 is an analog of (S)-pyroglutamic acid, a key component of naturally occurring peptide hormones and synthetic pharmaceutical candidates. Reaction of (S)-2-amino-3-(methylamino)propionic acid with COCl2 and aqueous NaHCO3 followed by ion exchange afforded 1, which was recrystallized from acetonitrile and then characterized by IR, 1H NMR, 13C NMR, polarimetry, elemental microanalysis, high resolution mass spectrometry and single crystal X-ray diffraction. The acid 1 crystallized in the orthorhombic chiral space group P212121 with cell constants a = 6.2275(4) Å, b = 8.3963(5) Å, c = 24.9490(14) Å. The X-ray crystal structure reveals that two distinct conformers of 1 occur at alternating positions within helices which are supported by hydrogen-bonding. Each molecule of 1 is linked to its two neighbors in the helix by a total of three hydrogen bonds and four molecules of 1 are contained within each turn of the helix. The pattern of hydrogen bonds illustrates a preference for the carboxylic acid group to act as a hydrogen bond donor and for the urea unit to be a hydrogen bond acceptor.

The growing interest in benchtop NMR systems is visible in a vast number of applications in science and industry. Low-field nuclear magnetic resonance (LF-NMR) became an instant in technologies that productions are dependent on the reliable structure identification, grade and purity control, chemical process inspection or reaction monitoring. Beyond the benefits of being cost-, space-, maintenance- and user friendly, insufficient sensitivity and low signal resolution are the main drawbacks, due to which the low-field NMR (LF-NMR) in the fields of organic chemistry and synthesis remains limited to solely academic teaching purposes. Herein, we discuss the possibilities of LF-NMR for the needs of organic chemistry and synthesis on a set of compounds 1-4 achieved as the products of student’s laboratory course and organic derivatives 5-8 that are from our research interests. Chemical structure determination of all compounds 1-8 presented herein was performed using the benchtop-type NMR instrument operating at 60 MHz (Pulsar Oxford Ltd.). Structure of novel compounds 5-7 prepared under the aims of our research was characterized by combined 1H/19LF-NMR and compared with an appropriate high-field NMR data from Bruker Ascend Instrument (400 MHz). Finally, possibilities of the low-field NMR as an analytical tool for the research purposes in the fields of organic chemistry and synthesis are documented on a set of 1H and 2D 1H-1H COSY for azomethine 8.

Coastal cliffs erode in response to short- and long-term environmental changes but predicting these changes continues to be a challenge. In addition to a chronic lack of data on the cliff face, vegetation presence and growth can bias our erosion measurements and limit our ability to detect geomorphic erosion by obscuring the cliff face. This paper builds on past research segmenting vegetation in 3-band red, green, blue (RGB) imagery and presents two approaches to segmenting and filtering vegetation from the bare cliff face in dense point clouds constructed from RGB images and structure-from-motion (SfM) software. Vegetation indices were computed from previously published research and their utility in segmenting vegetation from bare cliff face were compared against machine learning (ML) models for point cloud segmentation. Results demonstrate that, while existing vegetation indices and ML models are both capable of segmenting vegetation and bare cliff face sediments, ML models can be more efficient and robust across different growing seasons. ML model accuracy quickly reached an asymptote with only two layers and RGB images only (i.e., no vegetation indices), suggesting that these more parsimonious models may be more robust to a range of environmental conditions than existing vegetation indices which vary substantially from one growing season to another with changes in vegetation phenology.

This paper explores the application of Random Matrix Theory (RMT) as a methodological enhancement for portfolio selection within financial markets. Traditional approaches to portfolio optimization often rely on historical estimates of correlation matrices, particularly susceptible to instability. To address this challenge, we combine a data preprocessing technique based on the Hilbert transformation of returns with RMT to refine the accuracy and robustness of correlation matrix estimation. By contrasting empirical correlations with those derived from random matrices, we uncover non-random properties and underlying relationships within financial data. We then utilize this methodology to construct the correlation network dependence structure used in portfolio optimization. The empirical analysis presented in this paper validates the effectiveness of RMT in enhancing portfolio diversification and risk management strategies. This research contributes by offering investors and portfolio managers with methodological insights to construct portfolios that are more stable, robust, and diversified. At the same time, it advances our comprehension of the intricate statistical principles underlying multivariate financial data.

Soybean is one of the world’s most economically significant crops and is widely utilized as an essential source of vegetable protein and edible oil. Cultivated soybean is domesticated from its annual counterpart, wild soybean, which is considered valuable germplasm for soybean breeding. However, wild soybean accessions generally produce seeds with impermeable coats, a trait known as hard seededness (HS), which is beneficial for long-term seed survival but is undesirable for the uniform water absorption and germination of seeds, thus limiting the utilization of wild soybeans in breeding. However, moderate HS can isolate the embryo from the surrounding environment and is thus beneficial for long-term seed storage and germplasm preservation. The HS trait is primarily associated with the structure and chemical composition of the seed coat. However, its development is also influenced by various environmental conditions, such as water and temperature. Genetic analysis has revealed that HS of soybean is a complex quantitative trait controlled by multiple genes or minor quantitative trait loci (QTL), with many QTLs and several causal genes currently identified. Investigating the physiological and molecular mechanisms underlying this trait is crucial for soybean breeding, production, and food processing. For this article, the literature was reviewed and condensed to create a well-rounded picture of the current understanding of internal and external factors, QTLs, causal genes, and the regulatory mechanisms related to the HS of soybean, with the aim of providing reference for future research and utilization of this trait.

A reliable and efficient rail track defect detection system is essential for maintaining rail track integrity and avoiding safety hazards and financial losses. Eddy current (EC) testing is a non-destructive technique that can be employed for this purpose. The trade-off between spatial resolution and lift-off should be carefully considered in practical applications to distinguish closely spaced cracks such as those caused by rolling contact fatigue (RCF). A multi-channel eddy current sensor array has been developed to detect defects on rails. Based on the sensor scanning data, defect reconstruction along the rails is achieved using an inverse algorithm that includes both direct and iterative approaches. In experimental evaluations, the EC system with the developed sensor is used to measure defects on a standard test piece of rail with a probe lift-off of 4-6 mm. The reconstruction results clearly reveal cracks at various depths and spacings on the test piece.

The study of rare diseases is important not only for the individuals affected but also for the advancement of medical knowledge and a deeper understanding of human biology and genetics. The wide repertoire of structural information now available from reliable and accurate prediction methods provides the opportunity to investigate the molecular origins of most of the rare diseases reviewed in the Orpha.net database. Thus, it has been possible to analyze the topology of the missense mutations found in the 2,535 proteins involved in Mendelian rare diseases (MRD), which form the database for our structural bioinformatics study. The amino acid substitutions responsible for MRD show different mutation site distributions at different three-dimensional protein depths. We then predicted the depth-dependent effects of mutations for the 20,248 pathogenic variants that are present in our database. The results of this structural bioinformatics investigation are relevant, as they provide additional clues to mitigate the damage caused by MRD.

: The crystallization conditions from the solution play an important role in determining the mor-phology, phase composition, and photovoltaic properties of perovskite films. Post-processing of the obtained films can have a crucial role in increasing the grain size of perovskite and enhancing its crystallinity. It has been shown that the formation of crystal nuclei can be utilized to accelerate crystallization. In this case, crystallization occurs through the growth of seed crystals created in the solution, enabling the formation of relatively large crystals. For the deposition of CH3NH3PbI3 hybrid halide perovskite films from a solution of the perovskite in dimethylformamide the spin coating technique was employed. Pre-crystallization was achieved by annealing the films at a temperature of 100 or 110 °C. The dissolution process involved adding a drop of dimethylformamide onto the substrate surface and allowing it to partially dissolve the perovskite film. Subsequently, residual solvent was removed through spin coating. The mor-phological analysis of the perovskite film surface after recrystallization at temperatures ranging from 80 to 130 °C was performed. The infrared transmission spectra of the obtained perovskite films were investigated, and their light absorption characteristics were studied through transmission spectra. The perovskite structure in the obtained films was confirmed by the peaks observed in the X-ray diffraction patterns.

This paper delves into the application of digital twin monitoring techniques for enhancing offshore floating wind turbine performance, with a detailed case study. We explore the practical implementation of digital twins and their efficacy in optimizing operations and predictive maintenance. Our findings emphasize digital twins' potential as a valuable tool for renewable energy, driving efficiency and sustainability in offshore floating wind installations.

While the underwater submersible encounters internal solitary wave (ISW), its loadings and motions would be seriously disturbed. To investigate the interaction effect between the suspended submersible and ISW, a three dimensional ISW-submersible interaction numerical model was established based on the Computational Fluid Dynamics (CFD) method. The generation and propagation of ISW was simulated in a two-layer fluid numerical wave tank according to the eKdV theory. The standard operation equation of submersible was introduced to simulate the six degree of freedom (6DoF) motions of submersible combined with the overset dynamic mesh method. The motion simulation method of submersible was effectively validated by comparing with published experimental results on the motion responses of the slender body under the ISW. Based on the constructed numerical model, the dynamic mechanism between the suspended submersible and ISW were studied, and the effects of the initial submerged depths and the ISW amplitudes on the dynamic responses of the submersible were revealed. According to the numerical results, the motions of the submersible have been significantly determined by its initial submerged depths. The submersible located above the ISW interface has a significant motion along the propagation direction of ISW and its motion trajectory resembles a counterclockwise semi ellipse. The motions of the submersible located below the ISW interface follows with the trace of the lower layer fluid which presented as an unclosed clockwise ellipse. The corresponding motions of the submersible would be increased as the increase of the ISW amplitudes.

Bactrocera dorsalis Hendel is a highly invasive horticultural pest of major economic importance worldwide. In Burkina Faso, it is one of the main insect pests constraining the mango production and export. Understanding the biology and the genetic dynamics of this insect pest provide cru-cial information for the development of effective control measures. The aim of this study was to understand the distribution, diversity and genetic structure of B. dorsalis in Burkina Faso. Male flies were collected transversally in Burkina Faso and analyzed by PCR using 10 microsatellite markers. The results showed an abundance of B. dorsalis varying from 87 to 2986 flies per trap per day in the different sampling sites. Genetic diversity was high in all sites with an average Shan-non's Information Index (I) of 0.72 per site. Gene flow was high between study populations and ranged from 10.62 to 27.53 number of migrants. Bayesian admixture analysis showed no evi-dence of structure while Discriminant Analysis of Principal Components identified three weakly separated clusters in the population of B. dorsalis in Burkina Faso. The results of this study could be used to optimize the effectiveness of current control interventions and to guide the imple-mentation of new, innovative and sustainable strategies.

To investigate the impact of electrode structure on Electrical Stimulation Therapy (EST) for chronic wound healing, this study designed three variants of flexible microelectrodes (FMs) with Ag-Cu coverings (ACCs), each exhibiting distinct geometrical configurations: hexagonal, cross-shaped, and serpentine. These were integrated with PPY@PDA/PANI (3/6) hydrogel dressings. Comprehensive animal studies, coupled with detailed electrical and mechanical modeling and simulations, were conducted to assess their performance. Results indicated that the serpentine-shaped FM outperformed its counterparts in terms of flexibility and safety, exhibiting minimal thermal effects and a reduced risk of burns. Notably, FMs with metal coverings under 3% demonstrated promising potential for optoelectronic self-powering capabilities. Additionally, simulation data highlighted the significant influence of hydrogel non-uniformity on the distribution of electrical properties across the skin surface, providing critical insights for optimizing EST protocols when employing hydrogel dressings.

A novel process design for damage-free and highly accurate positional integration of an optical multi-axial force sensor into a hollow tube by means of rotary swaging is introduced. Numerical simulations reveal relevant process phenomena of thin disc joining inside a pre-toothed hollow tube and help to find an optimal process design. Experimental trials show a significant effect of axial material flow and the number of tools in a rotary swaging process. By taking these effects into account, a successful form- and force-fit joining of the sensor carrying discs into the tube can be achieved. A successful joining of an optical sensor for bending forces and torque measurement shows hysteresis-free sensory behavior and thus backlash-free joining of the sensor carrier discs. The paper finishes with presenting an approach for closed-loop position controlling during the joining process and numerically investigation of the process design.

In this review, we summarize recent progress in crystal growth and understanding the influence of crystal structure on the superconductivity in pure and Pb-doped Bi2Sr2CuOy (Bi-2201) materials belonging to the overdoped region of high temperature cuprate superconductors. The crystal growth of Bi-2201 superconductors faces challenges due to intricate materials chemistry and lack of knowledge of corresponding phase diagrams. Historically, a crucible-free floating zone method has emerged as the most promising growth approach for these materials, resulting in high-quality single crystals. This review outlines the described in the literature and the authors' synthesis endeavors, encompassing Pb-doped Bi-2201 crystals, detailed structural characterization of as-grown and post-growth annealed samples, and highlights optimal growth conditions that yield large-size, single-phase, and compositionally homogeneous Bi-2201 single crystals.

Prosthetic device is designed to function as a replacement for a missing limb and typically consists of suspension, liner, socket, pylon and foot components. The objectives of this research are to design a pylon component of a transtibial prosthetics by implementing auxetic metamaterial and to also validate performance of the designed pylon under quasi-static and dynamic conditions. The design and analysis processes are conducted using the finite element analysis and its effectiveness is validated by experimental testing of the prototype pylon sample. In the design process, the pylon structure is formulated by rearranging 2D re-entrant hexagon model into 3D model. It is identified from the design evaluation that the pylon exhibits the stiffness of the value of 79.24, 2371.6, and 13344 kN/m for the ligament thickness variation of 0.3 mm, 1 mm, and 2 mm, respectively. This directly indicates a capability of the stiffness tuning of the pylon by changing the ligament thickness. It is evaluated that the pylon with the ligament thickness of 0.3 mm causes the deformation of 0.53 cm during a single period of gait cycle, while the ligament thickness of the 1 mm causes the deformation of 0.4 cm. The deformation physically indicates the energy absorption of the pylon structure and hence the thinner ligament, the higher energy absorption provides. It is also found from the deformation transition of the primary and secondary bends, the negative Poisson’s ratio is occurred in 3D model transformed from 2D re-entrant hexagon.

: AliCPT-1 is the first Cosmic Microwave Background (CMB) experiment in China, dedicated to achieve accurate measurements of B-mode polarization. Situated in Ali of Tibet, China, this telescope is currently undergoing deployment and will operate in two frequency bands centered at 90 and 150 GHz. The Far-Field Flat Mirror（FFF）is a calibration device of AliCPT-1 telescope for far-field beam mapping. The design of FFF is optimized for easy assembly and adjustment. Meteorological station data reveals that the maximum wind speed near FFF is 17.5 m/s, while the maximum wind speed on the windward side is 8 m/s. The wind pressure on FFF was analysed using a maximum wind speed of 17.5m/s as the input condition, based on the fluid-structure coupling method in ANSYS. The results demonstrate that it is safe and reliable when withstanding combined gravity and wind pressure loads. The torque on the mount is within the motor rated torque. The flatness of the FFF reflective surface can be adjusted to an RMS value of 0.05 mm when taken into account the effect of gravity and assembly accuracy. The deformation caused by the maximum wind loads is approximately 0.0587 mm under the protection of wind-proof wall. The combined deformation is 0.077 mm in RMS value combining the two influences, which is less than 1/20 of wavelength. The FFF mirror assembly is stable and precisely for telescope calibration.

To improve the adaptability of aerial reflective opto-mechanical structures to low-temperature environments, an optimized thermal control design is proposed. Firstly, the relationship be-tween conventional heating methods and axial/radial temperature differences of mirrors with different shapes is analyzed. Based on heat transfer analyses, it is pointed out that optimized thermal control design is necessary to ensure the temperature uniformity of the fused silica mirror and take into account the temperature level when working in low temperature environ-ments. A thermal control scheme based on temperature negative feedback variable power zone heating is proposed for the characteristics of aerial electro-optics systems. Using the thermal control scheme at low temperatures ensures that the average temperature of the mirror fluctu-ates slowly and slightly around 20℃. At the same time, the temperature differences within a mirror and between the primary mirror and the secondary mirror can be controlled within 5℃. Thereby, satisfactory image quality is obtained.

The digital economy (DE) has become a major force driving the optimization and upgrading of industrial structures (ISOU), and research on the driving mechanism has yet to be verified. To this end, the driving influence of DE on the ISOU is targeted, and the role played by economic resilience (ER) and innovation is explored. Based on the panel data of 31 provinces in China from 2011 to 2020, the driving influence of the DE on the ISOU is analyzed using a two-way fixed-effects model. The empirical study finds that the DE presents a positive driving effect on both industrial structure advancement and rationalization, and the driving effect is still significant after the addition of control variables and the robust-type test with one period of lag; the DE presents regional differences in ISOU, with the driving effect of the DE on industrial structure advancement in the eastern region having a more significant performance than that of the central and western regions, and the driving influence on the rationalization of industrial structure in the eastern and western regions exceeds that in the central region; the impact of DE on the ISOU has a mediating role through innovation, ER has a moderating role in the process, and innovation as a partial mediator also has a threshold effect, and finally countermeasure suggestions are put forward.

The main development direction of energy efficiency technologies in construction is the creation of various materials with a complex structure and unique strength, thermal and other properties. The aerogel is a material with high porosity and excellent thermal insulation properties. This paper provides the state-of-the-art of aerogel applications for the additive manufacturing of energy efficient buildings. This work provides the experimental and numerical assessment results of thermal conductivity of aerogel-enhanced blanket, the experimental assessment results of thermal performance of aerogel-enhanced building structure, the experimental assessment results of the aerogel application as mixture powder component of the concrete mixture to printing building and the experimental assessment results of the aerogel application as parget powder component. Experimental results show the effect of aerogel powder component application: thermal conductivity decreased by 25%.

Ceramic composites have good strength, fracture toughness and hardness characteristics and are widely used in industry, medicine. The properties of ceramic composites can be controlled at the production stage by setting the internal structure. This is made possible by the development of additive manufacturing. However, not all properties are well understood, especially dynamic fracture resistance and fracture toughness. In order to predict the mechanical behavior of ceramic composites in the manufacturing phase with a controlled structure under dynamic loads, it is convenient to use methods of numerical analysis. The aim of this work was to investigate the influence of loading speed and internal structure on dynamic resistance and fracture toughness of ATZ nanocomposites. Within the framework of the study physical and mathematical model that is used in computational mechanics of materials is developed. In the paper is shown the influence of the loading rate on the strain rate in the region of the shock transition for materials based on ZrO2 - Al2O3 system. The research shows nonlinear effects under intense dynamic loads in the shown composite materials are bound up with either the processes of self-organisation of deformation modes at the mesoscopic level or the occurrence of martensitic phase transformations in matrix volumes adjacent to the strengthening particles.

We have found a region in the northwestern Japan Sea near the Subpolar Front where mesoscale eddies regularly form and circulate. The anticyclonic eddy with a strong dynamic feature, vertically extended to the bottom (~3500 m), multilayer core structure and extreme values of temperature and salinity was sampled there in the cruise in May 2004. The altimetry-based eddy tracking showed that it had a life span of nine months with the size reaching 120 km. CTD observational data were used to explore the eddy’s features and vertical structure. The eddy had a multilayer core with different thermohaline characteristics which could be originated by eddy interaction with the surrounding waters during its life. The evolution of the eddy has been studied and analyzed with the help of altimetry-based Lagrangian indicators of water motion. Performing the particle-tracking numerical experiments, we computed the Lagrangian maps that contain information on the origin of water inside the eddy core and its ‘age’ on every day of the eddy’s life. Inspecting daily-computed Lagrangian maps, we documented the essential events in the evolution of the eddy including its formation, splitting, merger, entrainment and detrainment of water, erosion and eventual decay. All these observations have been verified with the infrared satellite images. The new Lagrangian technique has been applied to calculate day by day the content of water of various origin (coastal, subtropical and subarctic) entrained into the eddy core. It has been found that the surface core has been filled mainly with subtropical water originated in the southern flank of the Subpolar Front. The episodes with cardinal changes of ratio of different water types have been recorded and verified with the infrared satellite images and maps of the origin of water inside the eddy core.

Bacteria are engaged in a constant battle against preying viruses, called bacteriophages (or phag-es). These remarkable nano-machines pack and store their genomes in a capsid and inject it into the cytoplasm of their bacterial prey following specific adhesion to the host cell surface. Tailed phages possessing dsDNA genomes are the most abundant phages in the bacterial virosphere, particularly those with long, non-contractile tails. All tailed phages possess a nano-device at their tail tip that specifically recognizes and adheres to a suitable host cell surface receptor, being pro-teinaceous and/or saccharidic. Adhesion devices of tailed phages infecting Gram-positive bacte-ria are highly diverse and, for the majority, remain poorly understood. Their long, flexible and multi-domain encompassing tail limits experimental approaches to determine their complete structure. We have previously shown that the recently developed protein structure prediction program AlphaFold2 can overcome this limitation by predicting the structures of phage adhesion devices with confidence. Here, we extend this approach and employ AlphaFold2 to determine the structure of a complete phage, the lactococcal P335 phage TP901-1. Herein we report the structures of its capsid and neck, its extended tail, and the complete adhesion device, the baseplate, which was previously partially determined by X-ray crystallography.

Biomimetic materials are substances that replicate natural structures. There are several methods for producing such materials with highly developed surfaces from a wide range of polymers, but electrospinning is of particular interest due to its simplicity of implementation and the ability to modify the produced fibrous materials resembling structures found in living organisms. This study explores new biomimetic materials based on polyhydroxyalkanoates, specifically poly-3-hydroxybutyrate, modified with chlorophyll derivatives. The research investigates the impact of chlorophyll derivatives on the morphology, supramolecular structure, and key properties of nonwoven materials. The obtained results are of interest for the development of new biomimetic environmentally friendly materials for biomedicine with special properties.

This article investigates on the radial and non-radial geodesic structures of the generalized K-essence Vaidya spacetime. Within the framework of K-essence geometry, it is important to note that the metric does not possess conformal equivalence to the conventional gravitational metric. This study employs a non-canonical action of the Dirac-Born-Infeld kind. In this work, we categorize the generalized K-essence Vaidya mass function into two distinct forms. Both the forms of the mass functions have been extensively utilized to analyze the radial and non-radial time-like or null geodesics in great details inside the comoving plane. Indications of the existence of wormhole can be noted during the extreme phases of spacetime, particularly in relation to black holes and white holes, which resemble the Einstein-Rosen bridge. In addition, we have also detected the distinctive indication of the quantum tunneling phenomenon around the central singularity.

Glycosaminoglycans (GAGs) with unique structures from marine animals show intriguing pharmacological activities and negligible biological risks, providing more options for us to explore safer agents. Swim bladder is a tonic food and folk medicine, and its GAGs show good anticoag-ulant activity. In this study, two GAGs SJG-1.0 and GMG-1.0 have been extracted and isolated from the swim bladder of Sphyraena jello and Gadus morhua. The physicochemical properties, pre-cise structural characteristics, and anticoagulant activities of these GAGs were determined. The analysis results of the SJG-1.0 and GMG-1.0 showed that they were chondroitin sulfate (CS)/dermatan sulfate (DS) hybrid chains with molecular weights of 109.32 kDa and 123.13 kDa, respectively. They were mainly composed of the repeating disaccharide unit of -{IdoA-α1,3-GalNAc4S-β1,4-}- (DS-A). The DS-B disaccharide unit of -{IdoA2S-α1,3-GalNAc4S-β1,4-}- also existed in both SJG-1.0 and GMG-1.0. SJG-1.0 had a higher proportion of CS-O disaccharide unit -{-GlcA-β1,3-GalNAc-β1,4-}-, while GMG-1.0 contained higher proportion of CS-E disaccha-ride unit -{-GlcA-β1,3-GalNAc4S6S-β1,4-}-. The disaccharide compositions of the GAGs varied in a species-specific manner. Anticoagulant activity assay revealed that both SJG-1.0 and GMG-1.0 had potent anticoagulant activity, which can significantly prolong activated partial thrombosis time. GMG-1.0 also can prolong the thrombin time. SJG-1.0 showed no intrinsic tenase inhibition ac-tivity, while GMG-1.0 can obviously inhibit intrinsic tenase with EC50 of 58 nM. Their significantly different anticoagulant activities may be due to their different disaccharide structural units and proportions. These findings suggested that the swim bladder CS/DS hybrid chains with well-defined structure may be safer anticoagulants with low bleeding risk.

Biological function depends on the composition as well as structure of the organism, that is the organization of interactions between its parts. In multicellular organisms, the complex communication between cells is crucial for the coordination of cellular functions (growth, differentiation, apoptosis), compartmentalization of cellular processes within the organism, and the integration of cells into functioning higher levels of structural organization. Here we focus on the interaction among cells, as the basic level of biological organization, capable of a remarkable degree of autonomy and self-maintenance. While a wealth of data on putative cell interactions has recently become available, its biological interpretation depends on expectations we have for the structure of these interaction networks. This contribution is an attempt at formulating basic questions we may ask about cell interaction data. We build on the understanding that cells fulfill two general functions: the integrity-maintaining and the organismal service function. We derive the expected patterns of cell interactions considering two intertwined aspects: the immediate functional and the evolutionary. Based on these, we propose several guidelines for analysis and interpretation of transcriptional cell-interactome data.

The combined efect of shape and electrostatic complementarities (Sc, EC) at the interface of the interacting protein partners (PPI) serves as the physical basis for such associations and is a strong detterminant of their binding energetics. EnCPdock (https://www.scinetmol.in/EnCPdock/) presents a comprehensive web-platform for the direct conjoint comparative analyses of complementarity and binding energetics in PPIs. It elegantly interlinks the dual nature of local (Sc) and non-local complementarity (EC) in PPIs using the Complementarity Plot. It further derives an AI-based ∆G_binding with a prediction accuracy comparable to the state-of-the-art. This book-chapter presents a practical manual to conceptualize and implement EnCPdock with its various features and functionalities, collectively having the potential to serve as a valuable protein engineering tool in the design of novel protein interfaces.

The mechanical properties, structure, and morphology of milled and 3D printed Ti-6Al-4V alloys produced by selective laser melting were investigated in this study. The mechanical properties were investigated by means of nanoindentation, a tensile test, and a three-point bending test. The Atomic Force Microscope (AFM) was used to study the surface topography and roughness of both titanium alloys. The surface structure and phase analysis were studied by a scanning electron microscope (SEM) and through powder X-ray diffraction (XRD). The results from the nanoindentation experiments showed that the 3D-printed sample has higher indentation hardness and modulus than the milled one. The AFM observation of the surface topography of the samples showed that the milled sample has a higher roughness than the 3D-printed one. The tensile test results showed that the 3D printed sample by means of Selective Laser Melting (SLM) technology has about 26% higher tensile strength and smaller elongation than the milled one. The 3-point bending test revealed that the 3D printed Ti-6Al-4V sample has higher flexural strength than the milled one. It was found that the 3D-printed sample has a smaller crystal size than the milled one, which, according to the Hall-Petch relationship, leads to its higher indentation hardness.

A new copper(I) complex, [Cu2(L)2dppm](PF6)2 (1) [L = 3-(2-Pyridyl)-5,6-diphenyl-1,2,4-triazine and dppm: Bis(diphenylphosphino)methane] was prepared and characterized by IR, 1H-NMR, 31P-NMR spectroscopy, elemental and thermogravimetric analysis, and single-crystal X-ray diffraction technique. Complex 1 is a dinuclear compound, showing that L and dppm act as tridentate and bidentate chelating ligands, respectively. The two Cu(I) atoms exhibit a distorted tetrahedral coordination sphere embedded in N3P environments. The supramolecular interactions in the solid-state structure are characterized by C−H···N, C−H···F, C-H···π and π···π intermolecular interactions that were analyzed by inspection of the Hirshfeld surface and fingerprint plots. Additionally, the complex was studied experimentally in solution by UV–Vis spectroscopy and cyclic voltammetry; also, theoretical studies with Time-Dependent Density Functional Theory (TD-DFT) were performed. Moreover, the optical and electrochemical properties have been studied, focusing on the band gap. Compound 1 has been used as a co-sensitizer in a dye-sensitized solar cell, showing good activity.

The crystallization conditions from the solution play an important role in determining the mor-phology, phase composition, and photovoltaic properties of perovskite films. Post-processing of the obtained films can have a crucial role in increasing the grain size of perovskite and enhancing its crystallinity. It has been shown that the formation of crystal nuclei can be utilized to accelerate crystallization. In this case, crystallization occurs through the growth of seed crystals created in the solution, enabling the formation of relatively large crystals. For the deposition of CH3NH3PbI3 hybrid halide perovskite films from a solution of the perovskite in dimethylformamide the spin coating echnique was employed. Pre-crystallization was achieved by heating films at a temperature of 100 or 110 °C. The dissolution process involved adding a drop of dimethylformamide onto the substrate surface and allowing it to partially dis-solve the perovskite for 30-40 seconds. Subsequently, residual solvent was removed through spin coating. The recrystallization process was carried out by heating films at the temperature range of 80 to 130 °C. The morphological analysis of the perovskite film surfaces after recrystallization at tem-peratures ranging from 80 to 130 °C was performed. The infrared transmission spectra of the obtained perovskite films were investigated, and their light absorption characteristics were studied through transmission spectra. The perovskite structure in the obtained films was con-firmed by the peaks observed in the X-ray diffraction patterns.

Parametric form findings of free-form space structures and qualitative assessment of their aesthetics are among the concerns of architects. This study aims to evaluate the aesthetic aspect of these structures using ML algorithms based on the expert's experiences. First, various datasets of forms were produced using a parametric algorithm of free-form space structures written in Grasshopper. Then, three multilayer perceptron ANN models were adjusted in their most optimal modes using the results of the preference test based on the aesthetic criteria including simplicity, complexity, and practicality. The results indicate that the ANN models can quantitatively evaluate the aesthetic value of free-form space structures.

We present three reduced integrable hierarchies of nonlocal integrable NLS type equations from a vector integrable hierarchy associated with a matrix Lie algebra, not being A type. Three similarity transformations are taken to keep the invariance of the transformed zero curvature equations. The key step is to formulate a solution to a reduced stationary zero curvature equation so that the zero curvature formulation works for a reduced case.

In recent times, the soft robotics field is gaining numerous research focus owing to its high level of manipulation capabilities unlike traditional rigid robots, which gives room for an increasing use in other areas. However, compared to traditional rigid gripper robots, being capable of controlling/obtaining overall body stiffness when required is yet to be further explored since soft gripper robots have inherently less rigid properties. unlike previous designs with very complex variable stiffness systems, this paper demonstrates a soft gripper design with minimum system complexity while being capable of varying the stiffness of a continuum soft robotic actuator and proves to have potential applications in gripping objects of various shapes, weights &amp; sizes. The soft gripper actuator comprises two separate mechanisms; the pneumatic mechanism for bending control and the mechanical structure for stiffness variation by pulling tendons using stepper motors which compresses the actuator, thereby changing the overall stiffness. The pneumatic mechanism was first fabricated and then embedded into another silicon layer during which it was as well merged with the mechanical structure for stiffness control. By first pneumatically actuating the actuator which causes bending and then pulling the tendons, we found out that the actuator stiffness value can be increased up to 145 % its initial value, and the gripper can grasp &amp; lift a weight of up to 2.075 kg.

The porous structure is an important three-dimensional morphological feature of the peripheral nerve guidance conduit (NGC), which permits infiltration of cells, nutrients, and molecular signals, and the discharge of metabolic waste. Porous structures with precisely customised pore sizes, porosities, and connectivities were used to construct fully permeable, semi-permeable, and asymmetric peripheral NGCs to replace traditional nerve autografts in treatment of long-segment peripheral nerve injury. In this review, the features of porous structures and classification of NGCs based on these characteristics are discussed. Common methods for constructing 3D porous NGCs in current research are described, as well as the pore characteristics and the parameters used to tune the pores. The effects of the porous structure on the physical properties of NGCs including biodegradation, mechanical performance, and permeability were analysed. Pore structure affects the biological behaviour of Schwann cells, macrophages, fibroblasts, and vascular endothelial cells during peripheral nerve regeneration. Construction of ideal porous structures is a significant advancement in the regeneration of peripheral nerve tissue engineering materials. The purpose of this review is to generalise, summarise, and analyse the preparation methods for porous NGCs and their biological functions in promoting peripheral nerve regeneration to guide development of medical nerve repair materials.