The minimum dominating tree (MDT) problem consists of finding a minimum weight sub-graph from an undirected graph, such that each vertex not in this sub-graph is adjacent to at least one of the vertices in it, and the sub-graph is connected without any ring structures. This paper presents a Dual Neighborhoods Search (DNS) algorithm for solving the MDT problem, which integrates several distinguishing features, such as two neighborhoods collaboratively working for optimizing the objective function, a fast neighborhood evaluation method to boost the searching effectiveness, and several diversification techniques to help the searching process jump out of the local optimum trap thus obtaining better solutions. DNS improves the previous best-known results for 4 public benchmark instances while providing competitive results for the remaining ones. Several ingredients of DNS are investigated to demonstrate the importance of the proposed ideas and techniques.

This paper deals with developing a new class of quaternions, called hyper-dual Horadam quaternions which are constructed from the quaternions whose components are hyper-dual Horadam numbers. We investigate the algebraic properties of these quaternions.

Frames are more stable as compared to bases under the action of a bounded linear operator. Sums of different frames under the action of a bounded linear operator are studied with the help of analysis, synthesis and frame operators. A simple construction of frames from the existing ones under the action of such an operator is presented here. It is shown that a frame can be added to its alternate dual frames, yielding a new frame. It is also shown that the sum of a pair of orthogonal frames is a frame. This provides an easy construction of a frame where the frame bounds can be computed easily. Moreover, for a pair of orthogonal frames, the necessary and sufficient condition is presented for their alternate dual frames to be orthogonal. This allows for an easy construction of a large number of new frames.

Recent years have seen a massive increase in research on mindfulness as both a therapeutic practice as well as a protective health factor. While many associations have been made between mindfulness and clinical outcomes, understanding of the underlying mechanistic processes is still in its infancy. In this review, associations between mindfulness and other established frameworks in cognitive control are explored—in particular the dual modes of control framework in cognitive control theory. Studies in mindfulness providing evidence towards a dual-mode mindfulness model are reviewed and compared with the proactive and reactive modes of cognitive control to identify common underlying principles. Studies involving cognitive testing, advanced neuroimaging, and neurotransmitter levels and their associations with proactive and reactive control are reviewed in the context of the dual modes of mindfulness. While evidence supporting relationships between proactive and reactive modes of mindfulness and cognitive control are preliminary, existing literature on mindfulness already supports the notion of two components of mindfulness and is in line with the hypothesis that cognitive control and mindfulness are closely related. Since preliminary evidence suggests that proactive forms of mindfulness are more associated with improvement in clinical outcomes, mindfulness programs could be modified to target proactive mindfulness practices to maximize outcomes. The implications of proactive and reactive mindfulness on therapy, limitations of the framework, and necessity of studies providing direct evidence are further discussed.

In this contribution, different lane-keeping control strategies for Autonomous Ground Vehicles (AGV) have been analyzed and compared. The AGV must be oriented and kept within a given reference path using the front wheel steering angle as the control action for a specific longitudinal velocity. While non-linear models can describe the lateral dynamics of the vehicle in an accurate manner, they might lead to difficulties when computing some real-time control laws such as Model Predictive Control (MPC). Linear Parameter Varying (LPV) models can provide a trade-off between computational complexity and model accuracy. Another way to reduce computational complexity is to explore other control strategies, for example, the one based on the Inverse Kinematic Bicycle model (IKIBI). Additionally, AGV sensors typically work at different measurement acquisition frequencies so that Kalman Filters (KF) are usually needed for sensor fusion. If these frequencies are slower than the actuation rate, a multi-rate KF may be needed. The two control strategies (MPC using a LPV model and IKIBI) have been compared in simulations over a circuit path in the presence of process and measurement Gaussian noise. The MPC controller has shown to provide a more accurate lane-keeping behavior than an IKIBI control strategy. Finally, it has been seen that Dual-Rate Extended Kalman Filters (DREKF) constitute an essential tool when only slow and noisy sensor feedback is available in an AGV lane-keeping application.

The modern era of polarimetric radar begins with radiowave propagation research starting in the early 1970s with applications to measurement and modeling of wave attenuation in rain and depolarization due to ice particles along satellite-earth links. While there is a rich history of radar in meteorology after World War II, the impetus provided by radiowave propagation requirements lead to high quality antennas and feeds. Our journey starts by describing the key institutions and personnel responsible for development of weather radar polarimetry. The early period was dominated by circularly polarized radars for propagation research and at S-band for hail detection. By the mid-to late 70s, a paradigm shift occurred which led to the dominance of linear polarizations with applications to slant path attenuation prediction as well as estimation of rain rates and inferences of precipitation physics. The period from early 1980s to 1995 can be considered as the “golden” period of rapid research that brought in meteorologists, cloud physicists and hydrologists. This article describes the evolution of this technology from the vantage point of the authors. Their personal reflections and “behind the scenes” descriptions offer a glimpse into the inner workings at several key institutions which cannot be found elsewhere.

The goal of this paper is to propose a dual version of the direct cosine simplex algorithm (DDCA) for general linear problems. Unlike the two-phase and the big-M methods, our technique does not involve artificial variables. Our technique solves the dual Klee-Minty problem in two iterations and solves the dual Clausen’s problem in four iterations. The utility of the proposed method is evident from the extensive computational results on test problems adapted from NETLIB. Preliminary results indicate that this dual direct cosine simplex algorithm (DDCA) reduces the number of iterations of two-phase method.

Brain tumor being one of the major health hazards always needs a prompt diagnosis for the early treatment options to improve the chances of the survival of the patients. Traditional manual assessment of MRI (magnetic resonance imaging) to identify these conditions is a common practice. Hence, automation of the diagnosis practices can considerably improve the quality of the treatment procedures. In recent years almost every method for the automated diagnosis of brain tumor detection uses a deep learning technique. Despite decent works current techniques need a significant improvement to produce better results. Along with failure to produce decent results, the current deep learning models present very complex architectures which sometimes require huge computational resources. Therefore, in this paper we present a novel method that uses a lightweight dual-stream model with dual-input to detect brain tumors on MRI images. Both the inputs use different pre-processing mechanisms based on Contrast Limited Adaptive Histogram Equalization (CLAHE) and White Patch Retinex algorithm in order to enhance the feature learning capabilities of the proposed model. In addition, the proposed method uses a two-fold margin loss to boost training process for better feature learning. The proposed method produces state-of-the-art results for the detection of Glioma, Meningioma and Pituitary tumors. The model presents accuracy of 99%, 98% and 99% respectively for Glioma, Meningioma and Pituitary tumor detection.

In this paper, we introduce the generalized dual hyperbolic Fibonacci numbers. As special cases, we deal with dual hyperbolic Fibonacci and dual hyperbolic Lucas numbers. We present Binet's formulas, generating functions and the summation formulas for these numbers. Moreover, we give Catalan's, Cassini's, d'Ocagne's, Gelin-Cesàro's, Melham's identities and present matrices related with these sequences.

This paper provides a comprehensive overview of the potential applications of dual energy CT (DECT) in improving image quality and diagnostic capabilities of CT arthrography (CTA) in clinical practice. The paper covers the use of virtual non contrast (VNC) images, in which the injected contrast medium is reduced from the articular cavity, in order to better analyze 2D and 3D images of the bone. Moreover , virtual monoenergetic imaging (VMI) applications and their potential use for the reduction of metal artifacts and improving image contrast are reviewed. The role of virtual non calcium (VNCa) in detecting bone marrow edema surrounding the imaged joint will be discussed. Furthermore , the role of iodine map to enhance the contrast between soft tissues, optimizing the visualization of contrast material, and to distinguish contrast material from calcifications is described. Finally, a case series including different joints is provided to underline the additional advantages of high spatial resolution dual energy CT reconstructed images.

Based on the principle of Pancharatnam-Berry phase, we propose an approach to construct dual-functional dielectric metasurface doublets. This type of doublet, which is composed of a substrate and two metasurface layers, performs two different functionalities at two different operating wavelengths. The simulated results of the examples show that the designed dual-functional doublet works well as expected. The proposed approach can be used to design dielectric meta-structures with more layers of meta-surface and thereby with more functionalities, and would be of interest for miniaturization and integration.

The superharmonic imaging of tissue has the potential for high spatial and contrast resolutions, compared to the fundamental and second harmonic imaging. For this technique, the spectral bandwidth of an ultrasound transducer is divided for transmission of ultrasound and reception of its superharmonics (i.e., higher than the second harmonic). Due to the spectral division for the transmission and reception, transmitted ultrasound energy is not sufficient to induce superharmonics in media without using contrast agents, and it is difficult that a transducer has a -6-dB fractional bandwidth of higher than 100%. For the superharmonic imaging of tissue, thus, multi-frequency array transducers are the best choice if available; transmit and receive elements are separate and have different center frequencies. However, the construction of a multi-frequency transducer for intravascular ultrasound (IVUS) imaging is particularly demanding because of its small size of less than 1 mm. Here, we report a recently developed dual-element focused IVUS transducer for the third harmonic imaging of tissue, which consists of a 35-MHz element for ultrasound transmission and a 105-MHz element for third harmonic reception. For high quality third harmonic imaging, both elements were fabricated to have the same focus at 2.5 mm. The results of tissue mimicking phantom tests demonstrated that the third harmonic images produced by the developed transducer had higher spatial resolution and deeper imaging depth than the fundamental images.

Three monoruthenium complexes 1(PF6)23(PF6)2 bearing a N(CH3)-bridged ligand have been synthesized and characterized. These complexes have a general formula of [Ru(bpy)2(L)](PF6)2, where L is a 2,5-di(N-methyl-N-(pyrid-2-yl)amino)pyrazine (dapz) derivative with various substituents and bpy is 2,2′-bipyridine. The photophyscial and electrochemical properties of these compounds have been examined. The solid-state structure of complex 3(PF6)2 is studied by single crystal X-ray analysis. These complexes show two well-separated emission bands centered at 451 and 646 nm (max = 195 nm) for 1(PF6)2, 465 and 627 nm (max = 162 nm) for 2(PF6)2, and 455 and 608 nm (max = 153 nm) for 3(PF6)2 in dilute acetonitrile solution, respectively. The emission maxima of the higher-energy emission bands of these complexes are similar, while the lower-energy emission bands are dependent on the electronic nature of substituents. These complexes display two consecutive redox couples owing to the stepwise oxidation of the N(CH3)-bridged ligand and ruthenium component. In addition, density functional theory (DFT) and time-dependent density functional theory (TD-DFT) calculations are carried out to elucidate these experimental findings.

Digital technology makes energy systems more dynamic, efficient, reliable and sustainable. Promoting the digital governance of renewable energy is not only a key part of energy transformation, but also an important initiative to cope with the global energy crisis, which provides a new impetus for realizing the goal of net-zero emissions. In order to achieve the "dual-carbon" goal, China has been actively promoting energy reform and enhancing the wide application of digital technologies in the development and utilization of renewable energy. The digital governance system and governance capacity of renewable energy is an important support for the modernization of the national governance system and governance capacity. Although the digital governance of renewable energy in China has better policy support and advantages, the dilemmas it faces are still relatively prominent, including unsound laws and policies, insufficient governance capacity, and security loopholes in digital technology, etc. Therefore, this paper proposes a problem-oriented approach to the digital governance of renewable energy. Therefore, this paper puts forward problem-oriented optimization suggestions to innovate the legal system of renewable energy digital governance, promote the digital transformation of China's renewable energy industry, provide development space for renewable energy digital governance in a diversified mode, and enhance the digital governance capacity by improving the renewable energy security system.

For developmental processes we know most of the gene networks controlling specific cell responses. We still have to determine how these networks cooperate and how signals become integrated. The JNK pathway is one of the key elements modulating cellular responses during development. Yet, we still know little on how the core components of the pathway interact with additional regulators or how this network modulates cellular responses in the whole organism in homeostasis or during tissue morphogenesis. We have performed a promoter analysis searching for potential regulatory sequences of puc and identified different specific enhancers directing gene expression in different tissues and at different developmental times. Remarkably, some of these domains respond to the JNK activity, but not all. Altogether, these analyses show that puc expression regulation is very complex and that JNK activities participate in non-previously known processes during the development of Drosophila.

Recombinant laboratory plasmids (RLPs) are common in biological research and freely shared among academic research laboratories (ARLs), a practice required by many research funding agencies. However, the generation of accurate, reproducible results in experiments utilizing RLPs can be hampered by a lack of accompanying sequence information and metadata. This culture of RLP sharing without knowledge of sequence or etiology is accepted by publishers, not regulated by governments, and outside the realm of bio-industry. In addition, no centralized infrastructure currently exists to collate such data, which at the moment is fragmented across companies, non-profits, and governments and thus is not easily accessed or enacted toward threat assessment. The ubiquity, free exchange, and dual-use risk of RLPs exemplifies a biosecurity threat and elevates the need to characterize their composition to facilitate improved biorisk management by the academic community. A number of common sense solutions are available to create a culture that addresses the biosecurity gap posed by RLP sharing. Culture shift in RLP management will require new norms, effective data management for collation of RLP sequences and metadata, and an incentive structure that encourages sequencing by stakeholders. The next generation of researchers must initiate and champion this shift with support from funding agencies and endorsement from governments and international organizations. Coordination of efforts and stakeholders will require international public/private collaboration, a structure that will be critical to ensure widespread utility as well as the ability of lower-resourced partners to participate, contribute, and benefit.

Secondary prevention after SCA (acute coronary syndrome) is of paramount importance to reduce the incidence of MACE and improve prognosis in follow-up. The control of avoidable risk factors, lifestyle modifications, but especially careful control of cholesterolemia (with a target of LDL-C

This study explored differences in student-athletes’ symptoms of depression, anxiety, and stress pre- to post-COVID-19 pandemic. The WHO reported a 25% increase in depression and anxiety rates worldwide with young people disproportionately affected. Student-athletes face many stressors related to their sporting and academic feats but what is not known is how the COVID-19 pandemic affected their experiences of mental illness. A multiple cohort cross-sectional study design was employed, and data collected using physical and online surveys. Participants (M age = 19.98 years, SD = 1.50) were recruited from UK universities (N = 807; 427 pre-pandemic cohort, 380 post-pandemic cohort). Results revealed statistically significant differences in mean depression, anxiety, and stress scores between cohorts. Scores for the post-pandemic cohort were significantly higher than pre-pandemic, suggesting a worsening of symptom severity. Distributions of student-athletes across categories of symptom severity also worsened for depressive and anxiety symptoms post-pandemic and were skewed towards more severe categories. Symptoms of de-pression, anxiety, and stress were a concern pre-pandemic. Rates are higher in the post-pandemic cohort, suggesting a worsening of symptoms. This data adds to evidence on student-athletes’ symptoms of mental illness by exploring a UK sample and comparing scores pre- and post-pandemic.

Nowadays, considering the growing tendency of companies towards e-commerce as well as green production, and dual-channel green supply chain management has become particularly important. This paper investigates pricing decisions within a dual-channel green supply chain framework while considering the capital constraints faced by risk-averse manufacturer. Simultaneously, the impact of the degree of risk aversion, consumer green preferences, and channel preferences on the optimal decision-making process of green supply chain members is analyzed. We address the issue of financial constraints faced by manufacturer through bank loans and trade credit financing and compare the two cases. Our findings illustrate that trade credit financing outperforms bank loan financing in the dual-channel green supply chain. Moreover, pricing decisions under different models are influenced by consumer preferences and risk aversion. Specifically, the greenness of the product, wholesale price, and sale price exhibit negative correlations with manufacturers' risk aversion but positive correlations with consumer preferences.

Dual-energy CT (DECT) imaging has broadened the potential of CT imaging by offering multiple postprocessing datasets with a single acquisition at more than one energy level. DECT shows profound capabilities to improve diagnosis based on its superior material differentiation and its quantitative value. However, the potential of dual energy imaging remains relatively untapped, possibly due to its intricate workflow and intrinsic technical limitations of DECT. Knowing the clinical advantages of dual-energy imaging and recognizing its limitations and pitfalls is neces-sary for an appropriate clinical use. The aims of this paper are to review physical and technical basis of DECT acquisition and analysis, to discuss advantages and limitations of DECT in dif-ferent clinical scenarios, to review technical constraints in material labeling and quantification, and to evaluate cutting-edge applications of DECT imaging, including artificial intelligence, qualitative and quantitative imaging biomarkers, and DECT-derived radiomics and radioge-nomics

The p53 tumor suppressor protein is an activator of transcription. Diverse stress factors lead to various sets of posttranslational modifications of p53 what results in different sets of upregulat-ed genes. We noticed that actinomycin D and nutlin-3a (A+N) synergize in inducing activating phosphorylations of p53 and upregulation of selected p53-target genes. Here we found that one of these genes is DUSP13, which codes for poorly-studied, dual-specificity phosphatase having at least two isoforms, one expressed in testis and the other in skeletal muscles. In cancer cells ex-posed to A+N, DUSP13 is expressed from an alternative promoter in intron, what results in ex-pression of isoform named TMDP-L1. The luciferase reporter tests demonstrated that this pro-moter is activated by both endogenous and ectopically expressed p53. We showed for the first time that mRNA expressed from this promoter actually produces the protein, which can be de-tected by Western blotting in all examined cancer cell lines with wild-type p53 exposed to A+N. In some cell lines it is also induced by clinically relevant camptothecin or by nutlin-3a acting alone. This isoform, fused with green fluorescent protein localizes in perinuclear region of cells. Thus, TMDP-L1 isoform may be an important element of p53-regulated stress response system.

Clinical screening tests for balance and mobility often fall short of predicting fall risk. Cognitive distractors and unpredictable external stimuli, common in busy natural environments, contrib-ute to this risk, especially in the elderly. Less is known about the effects of upper sensory-motor coordination such as coordinating one’s hand with an external stimulus. We combined move-ment sonification and affordable inertial motion sensors to develop a task for the precise meas-urement and manipulation of full-body interaction with stimuli in the environment. In a double-task design, we studied how a supra-postural activity affected quiet stance. The supra-postural task consisted of rhythmic synchronization with a repetitive auditory stimulus. The stimulus was attentionally demanding because it was being modulated continuously. The participant’s hand movement was sonified in real-time, and their goal was to synchronize their hand move-ment with the stimulus. In the unpredictable condition, the tempo changed at random points in the trial. A separate sensor recorded postural fluctuations. Young healthy adults were compared to elderly participants without known risk of falling. Results supported the hypothesis that su-pra-postural coordination would entrain postural control. The effect was stronger in the elderly, supporting the idea that diminished reserve capacities reduce the ability to isolate postural con-trol from sensory-motor and cognitive activity.

The limitations of conventional sensors have made phased array antennas increasingly crucial for gathering information and communication applications in intelligent transportation systems. Compact cylindrical arrays, in particular, are favored for their ability to achieve azimuth angle scan. However, the substantial mutual coupling effect between elements on curved surfaces and its implication in these arrays remains unclear, which is a crucial factor to consider when such arrays are used for multibeam applications. This study investigated the effect of mutual coupling in a dual-slant-polarized cylindrical array. The results showed that mutual coupling is essential for achieving an ultra-wide bandwidth. Mutual coupling is predominantly observed among elements that are closely positioned. The study also analyzes the impact of mutual coupling on scan impedance and radiation characteristics for multibeam applications and reveals that these arrays exhibit robust multibeam capability, hence having great potential for use in intelligent transportation systems.

Although hundreds of keV in energy gain have already been demonstrated in dielectric laser accelerators (DLAs), there remains challenge in creating structures that can confine electrons for multiple millimeters. We focus here on dual gratings with single sided drive, which have experimentally demonstrated energy modulation numerous times. Using a FTDT simulation to find the fields within various DLA structures and correlating these results with particle tracking simulation, we look at the impact of teeth height and width, as well as gap and offset, on the performance of these structures. We find a tradeoff between electron throughput and acceleration, but that for any given grating geometry there is a gap and offset that will allow some charge acceleration. For our 780 nm laser wavelength, this results in a 1200 nm optimal gap size for most gratings.

Objective: To analyze the clinical efficacy and safety of monotherapy and dual therapy in patients with early ischemic stroke. Methods: The study was conducted from August 2020 to August 2021, and 80 patients with early ischemic stroke who received treatment at our hospital during this period were selected as the study population. They were randomly divided into a control group and an observation group, with 40 patients in each group. The control group received conventional monotherapy, while the observation group received conventional dual therapy. The efficacy and safety indicators of the two groups were compared.Results: The treatment efficacy, functional recovery, blood indicators, and inflammation markers in the observation group were all superior to those in the control group (all, P<0.05); there was no significant difference in the drug safety profile between the two groups (P>0.05).Conclusion: The dual antiplatelet therapy is more ideal than monotherapy for treating patients with early ischemic stroke. It can further promote the recovery of neurological and cognitive function, improve hematological and inflammatory response indicators in patients, and the safety of this regimen is comparable to monotherapy.

To maintain a healthy lifestyle, adults rely on their ability to walk while simultaneously managing multiple tasks that challenge their coordination. This study investigates the impact of cognitive dual-task on lower limb muscle activities in 21 healthy young adults during both gait initiation and steady-state gait. We utilized wireless electromyography sensors to measure muscle activities, along with a 3D motion capture system and force plates to detect the phases of gait initiation and steady-state gait. Participants were asked to walk at their self-selected pace, and we compared single-task and dual-task conditions. We analyzed mean muscle activation and co-contraction in the biceps femoris, vastus lateralis, gastrocnemius, and tibialis anterior muscles. The findings revealed that during gait initiation with the dual-task condition, there was a decrease in mean muscle activation and an increase in mean muscle c-contraction between the swing and stance limb compared to the single-task condition. In steady-state gait, there was also a decrease in mean muscle activation in the dual-task condition compared to the single-task condition. When participants performed dual-task activities during gait initiation, early indicators of reduced balance capability were observed. Additionally, during dual-task steady-state gait, knee stabilizer muscles exhibited signs of altered activation, contributing to balance instability.

A multispectral superconducting nanowire single photon detector sensitive to different incident photon wavelength bands, is proposed. The SNSPD consists of a Distributed Bragg Reflector, a gold mirror, and two regions employing four NbN nanowires. Using the DBR both as a filter and a reflector, two distinct detection bands are created. The first detection band has a peak absorbance of > 0.75 at a wavelength of 1143 nm, while the second band has an absorbance of > 0.70 in the wavelength range 1440 to 2000 nm. The design of the device can be tuned to provide sensitivity in different wavelength bands. While SNSPDs do not typically provide photon wavelength sensitivity, the band-selection design proposed in this work opens up potential applications for future quantum communication technology.

Vehicle re-identification research under surveillance cameras has yielded impressive results. However, the challenge of Unmanned Aerial Vehicle (UAV)-based vehicle re-identification (ReID) presents a high degree of flexibility, mainly due to complicated shooting angles, occlusions, low discrimination of top-down features, and significant changes in vehicle scales. To address this, we propose a novel Dual Mixing Attention Network (DMANet) to extract discriminative features robust to variations in viewpoint. Specifically, we first present a plug-and-play Dual Mixing Attention Module (DMAM) to capture pixel-level pairwise relationships and channel dependencies, where DMAM is composed of Spatial Mixing Attention (SMA) and Channel Mixing Attention (CMA). First, the original feature is divided according to the dimensions of spatial and channel to obtain multiple subspaces. Then, a learnable weight is applied to capture the dependencies between local features in the mixture space. Finally, the features extracted from all subspaces are aggregated to promote their comprehensive feature interaction. Moreover, the DMAM can be readily inserted into backbone networks at any depth to improve vehicle discrimination. The experiments show that the proposed structure gains a better performance compared with the representative methods in the UAV-based vehicle ReID task. Our code and models will be publicly released.

Background: Patients undergoing dual antiplatelet therapy (DAPT) may experience recurrent gastrointestinal bleeding (GIB). We investigated the clinical characteristics and risk factors for recurrent non-variceal upper gastrointestinal bleeding (NVUGIB) in patients who had experienced NVUGIB during receiving DAPT. Methods: We enrolled patients diagnosed with NVUGIB during receiving DAPT between 2006 and 2020. Definite bleeding was confirmed by esophagogastroduodenoscopy in all NVUGIB patients. Results: A total of 124 patients were diagnosed with NVUGIB during receiving DAPT. Male was predominant (n = 103, 83.1%), bleeding mostly from the stomach (n = 94, 75.8%) and peptic ulcers (n = 72, 58.1%). After successful hemostasis of NVUGIB, 36 patients (29.0%) experienced at least one episode of recurrent upper GIB, 19 patients (15.3%) died, and 7 (5.6%) patients had a bleeding-related death. Multivariate analysis showed that age was a significant factor for re-bleeding (odds ratio [OR],1.050; 95% confidence interval [CI]:1.001-1.102, P-value:0.047), all-cause mortality (OR,1.096; 95% CI:1.020-1.178, P=0.013), and re-bleeding related mortality (OR,1.187; 95% CI:1.032-1.364, P-value:0.016). In Kaplan-Meier analysis, the cumulative probabilities of re-bleeding, death, and bleeding-related death were significantly higher in patients aged 70 and older (P=0.008, &lt;0.001, and 0.009, respectively). Conclusion: Clinicians should be cautious about re-bleeding and mortality when elderly patients who experienced NVUGIB during receiving DAPT.Keywords: dual antiplatelet therapy; upper gastrointestinal tract; bleeding; mortality

Percutaneous coronary intervention(PCI) with stenting for the treatment of acute coronary syndrome(ACS) is the contemporary standard of care. Such treatment is followed by Dual anti-platelet therapy(DAPT) comprising of aspirin and a P2Y12 inhibitor. The efficacy of this therapy has been well established but the optimal duration of DAPT remains elusive, and has thus far attracted a prodigious deal of scientific attention. Decision regarding DAPT duration can be challenging clinically in the modern era with the evolution of newer stents, more potent antiplatelet agents and novel anticoagulant drugs in addition to an older patient population with multiple comorbidities. Major societal guidelines have emphasized comprehensive assessment of ischemic and bleeding risk, in turn recommending individualization of DAPT duration, thus encouraging "shared decision making". The following review is aimed at critically evaluating the available evidence to help make these crucial clinical decisions regarding duration of DAPT and triple therapy.

We report a novel dual-band barrier infrared detector (DBIRD) design using type-II superlattices (T2SLs). The DBIRD structure consists of back-to-back barrier diodes: a "blue channel" (BC) diode which has an nBp architecture, an n-type layer of larger bandgap for absorbing blue band infrared/barrier/p-type layer, and a "red channel" (RC) diode which has an pBn architecture, a p-type layer of smaller bandgap for absorbing red band infrared/barrier/n-type layer. Each has a unipolar barrier using a T2SL lattice matched to a GaSb substrate to impede the flow of majority carriers from the absorbing layer. Each channel in the DBIRD can be independently accessed with a low bias voltage, as is preferable for high-speed thermal imaging. Device modeling of DBIRDs and simulation results of the current-voltage characteristics under dark and illuminated conditions are also presented. They predict that dual-band operation of the DBIRD will produce low dark currents and 27-33% quantum efficiencies for the in-band photons in the BC with λc=5.58 μm, and a nearly-constant 33% in the RC with λc=8.05 μm. The spectral quantum efficiency of the BC for 500 K blackbody radiation is approximately 20% over the range of λ=3 − 4.2 μm, while that of the RC has a peak of 42% at 5.7 μm. The DBIRD may provide improved high-speed dual-band imaging in comparison with NBn dual-band detectors.

Hydrazine (N2H4) plays an important role in industrial production, but it is highly toxic, leakage or exposure will pollute the environment and cause serious harm to the human body. Sulfur dioxide (SO2) is an important gas signaling molecule, but its excessive intake can cause a variety of diseases. However, due to the lack of two-color probes capable of detecting both N2H4 and SO2, the ability to monitor the crosstalk of these substances is limited. Therefore, it is necessary to find a simple and effective method for dual-response detection of N2H4 and SO2 in environmental systems and organisms. Here, we developed a two-response fluorescence probe PI-CO-NH based on FRET regulation to detect N2H4 and SO2. The experimental results show that the probe has high selectivity and sensitivity, excellent stability, low cytotoxicity and high cell permeability, can visualize N2H4 and SO2 in living cells, and has good mitochondrial targeting ability. It is worth noting that the ability of the probe to detect N2H4 in different soil samples and test strips was successfully verified. PI-CO-NH provides a platform for the analysis and visualization of two biologically active and environmentally important species, which has great potential in the analysis and monitoring of environmental pollutants.

Duchenne Muscular Dystrophy (DMD) is a pediatric disorder characterized by progressive muscle degeneration and premature death, with no cure at the moment. The currently most promising therapeutic avenue is based on gene replacement mediated by adeno-associated viruses (AAVs) using a shortened, but still functional, version of Dystrophin, known as microdystrophin (µDys), to fit AAV capacity. The limited improvements observed in clinical trials suggest a sub-optimal performance of µDys in the human context, that could be due to the lack of key domains in the protein. Therefore, expressing larger dystrophin proteins may be necessary for a more complete correction of the disease phenotype. In this study, we developed three novel Midi-Dystrophin constructs using a dual-AAV approach, leveraging split intein-based protein trans-splicing. The midi-dystrophins include additional domains compared to µDys, such as the central cytoskeleton-binding domain, nNOS and Par1b interacting domains, and a complete C-terminal region. Given the limited capacity of each AAV vector, we strategically partially reduced hinge regions while ensuring that the structural stability of the protein remains intact. We predicted the interactions between the two halves of the split Midi-Dys proteins thanks to the deep-learning algorithm AphaFold3. We observed strong associations between the N- and C-termini in Midi-Dys 1 and 2, while a weaker interaction in Midi-Dys 3 was revealed. Our subsequent experiments confirmed the efficient protein trans-splicing both in vitro and in vivo in DBA2/mdx mice of the Midi-Dys 1 and 2 and not in Midi-Dy3 as expected from the structural prediction. Additionally, we demonstrated that Midi-Dys 1 and 2 exhibit significant therapeutic efficacy in DBA2/mdx mice, highlighting their potential as therapeutic agents for DMD. Overall, these findings highlight the potential of deep learning-based structural modeling for the generation of intein-based dystrophin versions and pose the basis for further investigation of these new midi-dystrophins versions for clinical studies.

With the global objectives of achieving a ‘carbon peak’ and ‘carbon neutrality’, along with the implementation of carbon reduction policies, China’s industrial structure has undergone significant adjustments, resulting in constraints on high-energy consumption and high-emission industries while promoting the rapid growth of green industries. Consequently, these changes have led to an increasingly complex power system structure and presented new challenges for electricity demand forecasting. To address this issue, this study proposes a 24-step multivariate time series short-term load forecasting algorithm model based on KNN data imputation and BiTCN bidirectional temporal convolutional networks combined with BiGRU bidirectional gated recurrent units and attention mechanism. The Kepler adaptive optimization algorithm (KOA) is employed for hyperparameter optimization to effectively enhance prediction accuracy. Furthermore, using real load data from a wind farm in Xinjiang as an example, this paper predicts the electricity load from January 1st to December 30th in 2019. Experimental results demonstrate that our comprehensive short-term load forecasting model exhibits lower prediction errors and superior performance compared to traditional methods, thus holding great value for practical applications.

Staphylococcus aureus and Pseudomonas aeruginosa are opportunistic pathogens commonly associated with burn wound infections. These bacteria can form biofilm and contribute a high-level drug resistance to available antibiotics. This study focused on the bacteriolytic activity of phages vB_SAnS_SADP1 and vB_PAnP_PADP4 on 24 h old single or dual-species biofilms of Staphylococcus aureus and Pseudomonas aeruginosa in alone and in combination. Scanning and confocal laser scanning microscopic studies confirmed the structural organization of biofilms in single or dual-species combinations in in-vitro conditions. Single species biofilms are more robust and densely packed at 24 h of incubation. In contrast, dual-species biofilms (0.67± 0.02) are weakly associated due to their inter-species competition and are easily affected by phage cocktails (0.16 ± 0.02). In Invitro conditions, dual-species biofilms were more easily affected by phage cocktail than single phage. Scanning electron microscopic studies revealed the complete diminishment of biofilm formation by four h treatment with single phage or phage cocktails on single species or dual-species biofilms. Confocal laser scanning microscopic images with stains Syto®9 and propidium iodide revealed that phage treatment showed significant uptake of propidium iodide, indicating massive cell death mediated by respective phage or phage cocktail.

Background/Objectives: Population aging is rapidly increasing, and the importance of preventive medicine has been stressed. Health checkup, diet, and exercise are of paramount importance. This study aimed to evaluate the effectiveness of a personalized dual-task intervention that combined exercise with cognitive tasks in improving physical and cognitive functions among independently living elderly individuals. Methods: Participants were aged &gt;65 years who were mostly independent in their activities of daily living, divided into 2 groups. The group receiving the 20-min robot-assisted session was compared to the group receiving traditional functional restoration training. This randomized trial assessed the impact of this intervention on the 30-s chair stand test score and Montreal Cognitive Assessment-Japanese version score of the participants. Results: Both scores significantly improved in the intervention group, indicating enhanced lower-limb function and cognitive capabilities. Conclusions: These findings suggest that integrating cognitive tasks with physical exercise can be a potent strategy to improve overall well-being in the elderly, offering valuable insights for designing comprehensive preventive health programs tailored to this demographic.

In this paper, we establish the necessary and sufficient conditions for solving a dual split quaternion matrix equation AXB=C, and present the general solution expression when solvability is achieved. As an application, we delve into the necessary and sufficient condition for the existence of Hermitian solution to this equation by using a newly defined real representation method. Furthermore, we obtain the solutions for the dual split quaternion matrix equations AX=C and XB=C. Finally, we provide a numerical example to demonstrate the findings of this paper.

Hydrogen is considered as an ideal substitute to the traditional fossil fuels because of its widespread sources, high calorific value of combustion, and zero carbon emissions. The electrocatalytic water-splitting to produce hydrogen is also deemed to be the best approach, however, it is a challenge to make high-efficient and low-cost electrocatalysts. Single-atom catalysts (SACs) are considered the most promising candidate to replace the traditional noble-metal catalysts. Compared with SACs, the dual-atom catalysts (DACs) are of greater attraction including higher metal loading, more versatile active sites, and excellent catalytic activity. In the review, several general synthetic strategies and structural characterization methods of DACs are introduced, and the mechanisms of hydrogen evolution reaction (HER) and oxygen evolution reactions (OER) are discussed. The authors hope that the review has given some insights and inspiration to the researchers about DACs in electrocatalytic water-splitting.

Endoscopic medical images can suffer from uneven illumination, low contrast, and lack of texture information due to the use of point directional light sources and the presence of narrow tissue structures, posing diagnostic difficulties for physicians. In this paper, a deep learning-based su-pervised illumination enhancement network is designed for low-light endoscopic images, aiming to improve both global illumination and local details. Initially, a global illumination enhancement module is formulated utilizing a higher-order curve function to improve global illumination. Sec-ondly, a local feature extraction module incorporating dual attention is designed to capture local detailed features. Considering the significance of color fidelity in biomedical scenarios, the designed loss function prioritizes introducing color loss to alleviate image color distortion. Compared with seven state-of-the-art enhancement algorithms on Endo4IE endoscopic datasets, experimental re-sults show that the proposed method can better enhance low-light endoscopic images and avoid image color distortion. It provides an efficient method to enhance images captured by endoscopes which can effectively assist clinical diagnosis and treatment.

The groundbreaking Advanced Forest-Based Tagging Framework (AFTF) represents a paradigm shift in the domain of information extraction from medical texts. AFTF introduces a novel dual-binary tree structure that redefines how entity-relation triples are extracted. This innovative approach directly tackles the limitations of traditional linear and graph-based methods, effectively addressing challenges related to overlapping triples and computational efficiency. The AFTF model stands as a beacon of excellence, surpassing established baselines by significant margins in comprehensive evaluations on two pivotal medical datasets. Notably, AFTF achieves remarkable improvements in F1 scores, showcasing its prowess in accurate information extraction from complex medical narratives. Beyond its exceptional performance in the medical domain, AFTF exhibits remarkable versatility. This adaptability is vividly demonstrated through its robust performance across three diverse public datasets, further affirming its position as a versatile and reliable solution for information extraction tasks. This paper provides a comprehensive exposition of the AFTF architecture, shedding light on its innovative design principles and its efficient handling of intricate medical texts. AFTF represents a groundbreaking step forward in the realm of information extraction, promising enhanced accuracy, efficiency, and adaptability for a wide range of applications.

Micro-gyroscopes based on the Coriolis principle are widely employed in inertial navigation, motion control, and vibration analysis applications. This paper presents our main contributions which include a novel dual-frame optomechanical gyroscope, a unique photonic crystal cavity design, and advanced numerical simulation and optimization methods. The proposed design utilizes an optical cavity formed between dual oscillating frames, whereby input rotation induces a measurable phase shift via optomechanical coupling. Actuation of the frames is achieved electrostatically via an interdigitated comb-drive design. Through theoretical modeling based on cavity optomechanics and finite element simulation, the operating principle and performance parameters are evaluated in detail. Results indicate an expected angular rate sensitivity of 22.8 mV/°/s and angle random walk of 7.1×10-5 °/h1/2, representing superior precision than to existing micro-electromechanical systems gyroscopes of comparable scale. Detailed analysis of the optomechanical transduction mechanism suggests this dual-frame approach could enable angular vibration detection with resolution exceeding state-of-the-art solutions.

Bovine lactoferrin (bLf) is a milk-derived protein that exhibits multiple biological activities and has been explored towards different therapeutic applications. Since this molecule is susceptible to degradation and some of its properties depend on its tertiary structure, the encapsulation of bLf in stimuli-responsive therapeutic formulations provides an added value to potentiate its biological activities when administered. Plasmonic magnetoliposomes emerge as promising nanosystems for dual hyperthermia (magneto-photothermia) and local therapy, since the combination of magnetic and gold nanoparticles (NPs) in a single nanosystem (multifunctional liposomes) enables the targeting and controlled release of encapsulated drugs. In this work, plasmonic magnetoliposomes (PMLs) containing manganese ferrite nanoparticles (28 nm size) and gold nanoparticles (~ 5 nm size) functionalized with 11-mercaptoundecanoic acid or octadecanethiol, were synthesized and loaded with bLf. The structural, magnetic and optical properties of the nanoparticles were measured by TEM, SQUID and UV/vis/NIR absorption spectroscopy. Specific Absorption Rate was determined to assess the capabilities for magnetic and photothermal hyperthermia. Finally, Saccharomyces cerevisiae was used as an eukaryotic cellular model to assess the biological activity and the mechanism of entry of bLf-loaded PMLs, through counting of colony forming units and fluorescence microscopy, respectively. The results demonstrate that PMLs are mainly internalized through an energy- and temperature-dependent endocytic process, though the contribution of a diffusion component cannot be discarded. Most notably, only bLf-loaded PMLs exhibit cytotoxicity with an efficiency similar to free bLf, attesting their promising potential for bLf delivery in the context of therapeutic interventions.

Fractals offer the ability to generate fascinating geometric shapes with all sorts of unique characteristics (for instance, fractal geometry provides a basis for modelling infinite detail found in nature). While fractals are non-euclidean mathematical objects which possess an assortment of properties (e.g., attractivity and symmetry), they are also able to be scaled down, rotated, skewed and replicated in embedded contexts. Hence, many different types of fractals have come into limelight since their origin discovery. One particularly popular method for generating fractal geometry is using Julia sets. Julia sets provide a straightforward and innovative method for generating fractal geometry using an iterative computational modelling algorithm. In this paper, we present a method that combines Julia sets with dual-quaternion algebra. Dual-quaternions are an alluring principal with a whole range interesting mathematical possibilities. Extending fractal Julia sets to encompass dual-quaternions algebra provides us with a novel visualize solution. We explain the method of fractals using the dual-quaternions in combination with Julia sets. Our prototype implementation demonstrate an efficient methods for rendering fractal geometry using dual-quaternion Julia sets based upon an uncomplicated ray tracing algorithm. We show a number of different experimental isosurface examples to demonstrate the viability of our approach.

Despite the popularity of Zumba in several countries, research is scarce about its impact on older adults. Meanwhile, the integration of cognitive tasks with physical exercises, known as dual-tasking, is an evolving strategy to facilitate activities for older people. This study investigated the perceptions of older adults regarding Zumba and the potential of implementing it in a dual-task program. We conducted a qualitative-descriptive research involving 44 Filipino older adults from August to November 2020. Content analysis was employed to analyze the data. Four themes were identified: moving towards match or mismatch; balancing benefits with burdens; dual-tasking as innovative yet potentially challenging; and overcoming barriers with enablers. While Zumba is an inclusive and beneficial activity, individual and contextual limitations could hinder its suitability for older people. Dual-tasking in Zumba was also recognized as an innovative approach, although challenges should be addressed to promote its utility. Several strategies could support the design of these programs in communities. This is the first study to explore older adults’ perceptions towards Zumba and its potential utilization as a dual-tasking program. Findings could guide the implementation of appropriate Zumba and dual-tasking activities that seek to integrate cognitive and physical training for older adults.

Current therapeutic protocols for the treatment of HIV infection consist of the combination of diverse anti-retroviral drugs in order to reduce the selection of resistant mutants and to allow for the use of lower doses of each single agent to reduce toxicity. However, avoiding drugs interactions and patient compliance are issues not fully accomplished so far. In this respect the identification of single agents with multitarget potential might represent the ideal solution. Accordingly, a small library of biphenylhydrazo 4-arylthiazoles derivatives has been synthesised and evaluated to investigate the ability of the new derivatives to simultaneously inhibit both associated functions of HIV reverse transcriptase. All compounds were active towards the two functions, although at different concentrations. The substitution pattern on the biphenyl moiety appears relevant to determine the activity.

In this paper, we study singularities of the spherical indicatrix and evolute of spacelike ruled surface with spacelike ruling. Finally, we give an example to illustrate our results.

The etiology of ‘dual harm’ (the co-occurrence of self-harm and externalized violence in the same individual) is under-researched. Risk factors have mostly been investigated for each behavior separately. We aimed to examine adversities experienced between birth and age 15 years among adolescents and young adults with histories of self-harm and violent criminality, with a specific focus on dual harm. Three nested case-control studies were delineated using national interlinked Danish registers; 58,409 cases in total aged 15-35 were identified: 28,956 with a history of violent criminality (but not self-harm), 25,826 with a history of self-harm (but not violent criminality), and 3987 with dual harm history. Each case was matched by date of birth and gender to 20 controls who had not engaged in either behavior. We estimated exposure prevalence for cases vs. controls for each of the three behavior groups, and incidence rate ratios (IRRs). Experiencing 5 or more childhood adversities was more prevalent among individuals with dual harm history (19.3%; 95% CI 18.0, 20.8%) versus self-harm (10.9%; 10.5, 11.3%) and violence (11.4%; 11.0%, 11.8%) histories. The highest IRRs for dual harm were linked with parental unemployment (5.15; 95% CI 4.71, 5.64), parental hospitalization following self-harm (4.91; 4.40, 5.48) or assault (5.90; 5.07, 6.86), and parental violent criminality (6.11; 5.57, 6.70). Growing up in environments that are characterized by poverty, violence and substance misuse, and experiencing multiple adversities in childhood, appear to be especially strongly linked with elevated dual harm risk. These novel findings indicate potential etiologic pathways to dual harm.

In this paper, the design process of BLDC adopting the dual rotor method that can reduce the overall size of the motor while generating the same torque as the conventional Permanent Magnet BLDC is analyzed. A simple size is selected by obtaining the torque per rotor volume (TRV), and a method of matching the counter electromotive force by selecting the pole arc of the magnet through a magnetic equivalent circuit is analyzed. Since the efficiency is low because the 120-degree commutation method is selected, the middle stator is optimized through detailed design through the experimental design method. Afterwards, it has the advantage of being able to shift without stopping due to the characteristic of a dual rotor. For this, an analysis of the driving characteristics for each mode is performed.

Single nanowires (NWs) are of great importance for optoelectronic applications, especially solar cells serving as powering nanoscale devices. However, weak off-resonant absorption can limit its light-harvesting capability. Here, we propose a single NW coated with the graded-index dual shells (DSNW). We demonstrate that with appropriate thickness and refractive index of the inner shell, the DSNW exhibits significantly enhanced light trapping compared with the bare NW (BNW), and the NW only coated with the outer shell (OSNW) and the inner shell (ISNW), which can be attributed to the optimal off-resonant absorption mode profiles due to the improved coupling between the reemitted light of the transition modes of the leak mode resonances of the Si core and the nanofocusing light from the dual shells with the graded refractive index. We found that the light absorption can be engineered via tuning the thickness and the refractive index of the inner shell, the photocurrent density is significantly enhanced by 134% (56%, 12%) in comparison with that of the BNW (OSNW, ISNW). This work advances our understanding of how to improve off-resonant absorption by applying graded dual-shell design and provides a new choice for designing high-efficiency single NW photovoltaic devices.

This paper presents a configuration of dual output single phase current source inverter with 6 switches for microgrid applications. The inverter is capable of delivering power to two independent set of loads of equal voltages or different voltages at the load end. The control strategy is based on Integral Sliding Mode Control (ISMC). The remote monitoring of the inverter is performed with cyber infrastructure. The cyber physical test bench is developed based on Reconfigurable I/O processor (NI MyRIO-1900) for control and monitoring of the inverter. The inverter prototype is tested in cyber physical test bench in laboratory conditions. The performance of the inverter is analyzed and monitored through the remote system. Also, the inverter is analyzed with different voltage conditions.

Continuous object tracking in WSNs, such as monitoring of mud-rock flows, forest fires etc., is a challenging task due to characteristic nature of continuous objects. They can appear randomly in the network field, move continuously, and can change in size and shape. Monitoring such objects in real-time generally require tremendous amount of messaging between sensor nodes to synergistically estimate object’s movement and track its location. In this paper, we propose a novel twofold-sink mechanism, comprising of a mobile and a static sink node. Both sink nodes gather information about boundary sensor nodes, which is then used to uniformly distribute energy consumption across all network nodes, thus helping in saving residual energy of network nodes. Numerous object tracking schemes, using mobile sink, have been proposed in the literature. However, existing schemes employing mobile sink cannot be applied to track continuous objects, because of momentous variation of network topology. Therefore, we present in this paper a mechanism, transformed from K-means algorithm, to find the best sensing location of the mobile sink node. It helps to reduce transmission load on the intermediate network nodes situated between static sink node and the ordinary network sensing nodes. The simulation results show that the proposed scheme can distinctly improve life time of the network, compared to one-sink protocol employed in continuous object tracking.

Although mammography has been the gold standard for early detection of breast cancer, if a woman has dense breast tissue, a false negative diagnosis may occur. Breast ultrasound, whether hand-held or automated, is a useful adjunct to mammography but adds extra time and cost. The primary aim was to demonstrate that our second-generation Aceso system, which combines full-field digital mammography (FFDM) and automated breast ultrasound (ABUS) in a single platform, is able to produce improved quality images that provide clinically meaningful results. Aceso was first tested using two industry standards: a CDMAM phantom to assess the FFDM images; and the CIRS 054GS phantom to evaluate the ABUS images. In addition, 25 women participated in a clinical trial: 14 were healthy volunteers while 11 were patients referred by the breast clinic at Groote Schuur Hospital. The CDMAM phantom results showed the FFDM results were better than EUREF’s standard of “acceptable” and were approaching “achievable”. The ABUS results showed lateral and axial spatial resolution of 0.5 mm and adequate depth penetration of 80 mm. Our second-generation Aceso system, with its improved quality of clinical FFDM and ABUS images, has demonstrated its potential for early detection of breast cancer in a busy clinic.

This article develops duality principles applicable to originally non-convex primal variational formulations. More specifically, as a first application, we establish a convex dual approximate variational formulation for a non-linear Kirchhoff-Love plate model. The results are obtained through basic tools of functional analysis, calculus of variations, duality and optimization theory in infinite dimensional spaces. We emphasize such a convex dual approximate formulation obtained may be applied to a large class of similar models in the calculus of variations. Finally, in the last section, we present a duality principle and respective convex dual formulation for a Ginzburg-Landau type equation.

Dual generalized commutative quaternions have broad application prospects in many fields. Additionally, the matrix equation AXB = C has important applications in mathematics and engineering, especially in control systems, economics, computer science, and other disciplines. However, research on the matrix equation AXB = C over the dual generalized commutative quaternions remains relatively insufficient. In this paper, we derive the necessary and sufficient conditions for the solvability of the dual generalized commutative quaternion matrix equation AXB = C. Furthermore, we provide the general solution expression for this matrix equation, when it is solvable. Finally, a numerical algorithm and an example are provided to confirm the reliability of the main conclusions.

Streptococcus agalactiae is a highly contagious Gram- positive bacterium that causes mastitis, has a high infectivity for mammary epithelial cells, and is challenging to treat. However, the molecular interactions between it and mammary epithelial cells remains poorly understood. This study analyzed differential gene expression in mammary epithelial cells with varying levels of S. agalactiae infection using UID- Dual Seq and bioinformatics tools. This study identified 211 differentially expressed mRNAs (DEmRNAs) and 452 differentially expressed lncRNAs (DElncRNAs) in host cells, primarily enriched in anti-inflammatory responses, immune responses, and cancer-related processes. Additionally, 854 pathogen differentially expressed mRNAs (pDEmRNAs) were identified, mainly enriched in protein metabolism, gene expression, and biosynthesis processes. Mammary epithelial cells activate pathways, such as the ERK1/2 pathway to produce, to produce reactive oxygen species (ROS) to eliminate bacteria. However, the bacteria disrupt the host's innate immune mechanisms by interfering with the alternative splicing processes of mammary epithelial cells. Specifically, the bacterial genes of tsf, prfB, and infC can interfere with lncRNAs targeting RUNX1 and BCL2L11 in mammary epithelial cells, affecting the alternative splicing of target genes and altering normal molecular regulation.

A comprehensive multi-jet physics program is anticipated for experiments at future colliders. Key physics processes necessitate detectors that can distinguish signals from W and Z bosons and the recently discovered Higgs boson. Typical examples include channels with W^{+}W^{-} or Z^{o}Z^{o} pairs and processes involving New Physics, in those cases where neutral particles must be disentangled from charged ones due to the presence of W or Z bosons in their final states. Such a physics program demands calorimetric energy resolution at or beyond the limits of traditional calorimetric techniques. Multiple-readout calorimetry, which aims to reduce fluctuations in energy measurements of hadronic showers, is a promising approach. The first part of this article reviews dual and triple readout calorimetry within a mathematical framework describing the underlying compensating mechanism. The second part proposes a potential implementation using an integrally active and total absorption detector. This model serves as the basis for several Monte Carlo studies, illustrating how the response of a multiple-readout calorimeter depends on construction parameters. Among the layouts considered, one configuration operating in triple-readout mode shows the potential to achieve an energy resolution approaching 20\%/\sqrt{E}.

Background: Bioelectrical impedance (BIA) and ultrasound (US) have become popular for estimating body fat percentage (BF%) due to their low cost and clinical convenience. However, agreement of these devices with gold standard method still require investigation. The aim was to analyze the agreement between a gold standard %BF assessment method with BIA and US devices. Methods: Twenty-three men (age 30.1 ± 7.7 years, 82.5 ± 14.9 kg, 1.77 ± 0.05 m) underwent Dual Energy X-Ray Absorptiometry (DXA), BIA (tetrapolar) and US (three-site method) %BF assessment. Pearson and concordance correlations were analyzed. T-test compared means between methods, and Bland Altman plots analyzed agreement and proportional bias. Alpha was set at &lt; .05. Results: Pearson coefficients between BIA and US with DXA were high (BIA = 0.94; US = 0.89; both p &lt; .001). Concordance coefficient was high for BIA (0.80) and moderate for US (0.49). BF% measured by BIA (24.5 ± 7.5) and US (19.4 ± 7.0) were on average 4.4% and 9.6% lower than DXA (29.0 + 8.5%), respectively (p &lt; .001). Lower and upper agreement limits between DXA and BIA were -1.45 and 10.31, while between DXA and US were 2.01 and 17.14, respectively. There was a tendency of both BIA (p = .09) and US (p = .057) to present proportional bias and underestimate BF%. Conclusions: Despite the correlation, the mean difference between the methods were significant, and the agreement limits are very wide. This indicate that BIA and US, as measured in this study, have limited potential to accurately measure %BF compared to DXA, especially in individuals with higher body fat.

Utilizing lignocellulosic biosourced platforms, we synthesized novel cyanostilbene (CS) deriva-tives featuring the 3,4-dimethoxyphenyl moiety. These derivatives were investigated for their emission properties in both solution and solid states. The two simple CS derivatives exhibit very weak luminescence in solution but significant luminescence in the solid state, indicating distinct Aggregation-Induced Emission (AIE) characteristic. Furthermore, combining these two CS units, without conjugation and with quasi perpendicular orientation, results in Dual-State Emission (DSE) fluorophore showing luminescence both in solution and solid states. X-ray crys-tallography studies on the solid-state compounds reveal a structure-emission relationship, demonstrating that the colour emission correlates with the conformations adopted by the mol-ecules in the solid state, which influence the type of stacking.

This paper presents a wideband dual-polarized dipole antenna structure operating at 1.7-3.8 GHz (76.4%). For a traditional 4G dipole antenna which covers the band 1.71 GHz- 2.69 GHz, it’s difficult to maintain the satisfactory impedance matching and normal stable radiation patterns within the 5G sub-6 GHz band 3.3-3.8 GHz, which mainly due to the fixed antenna height is no longer a quarter-wavelength. To solve this, a connected-ring-shaped metasurface structure is proposed and deployed to operate as an artificial magnetic conductor (AMC). As a result, stable antenna radiation patterns are obtained within the whole band 1.7-3.8 GHz. For verification, this wideband dipole antenna using AMC is implemented and tested. The measured results show that the proposed antenna has an impedance bandwidth of 80.7% (1.7-4.0 GHz). It has an average measured in-band realized gain of 7.0±1.0 dBi and a stable 70∘±5∘ half power beam width (HPBW) within the 4G/5G-sub 6GHz bands 1710-2690 MHz and 3300-3800 MHz.

Dual quaternions have wide applications in automatic differentiation, computer graphics, mechanics and others. Due to its application in control theory, the matrix equation AXB=C has been extensively studied. However, there is currently limited information on matrix equation AXB=C over the dual quaternion algebra. In this paper, we provide the necessary and sufficient conditions for the solvability of the dual quaternion matrix equation AXB=C, and present the expression for the general solution when it is solvable. As an application, we derive the ϕ-Hermitian solutions for the dual quaternion matrix equation AXAϕ=C, where the ϕ-Hermitian extends the concepts of Hermiticity and η-Hermiticity. Lastly, we present a numerical example to verify the main research results of this paper.

The co-occurrence of substance use disorders (SUDs) and psychiatric conditions, often referred to as comorbidity or concurrent disorders, presents intricate challenges in both diagnosis and treatment. This comprehensive narrative review aims to synthesize and critically evaluate the existing evi-dence surrounding the management of individuals with comorbid SUDs and psychiatric disorders. Comorbidity in these domains carries profound implications for clinical practice, research, and policymaking, emphasizing the need for a holistic understanding of the intricate dynamics that arise when these conditions coexist. This review explores recent research findings, evidence-based guidelines, and emerging trends within the field, offering valuable insights for clinicians, re-searchers, and policymakers seeking to navigate the complex terrain of comorbidity in substance use and psychiatric disorders.

FV (finger vein) identification is a biometric identification technology that extracts the features of FV images for identity authentication. To address the limitations of CNN-based FV identification, particularly the challenge of small receptive fields and difficulty in capturing long-range dependencies, an FV identification method Let-Net(Large kernel and attention mechanism Network) was introduced, which combines local and global information. Firstly, Let-Net employs large kernels to broaden the receptive field and incorporates depthwise convolution with residual connections to reduce parameter count. Secondly, Let-Net integrates an attention mechanism to enhance the information flows in channels and spaces for more comprehensive and distinctive FV feature extraction. The experimental results on nine public datasets show that Let-Net has excellent identification performance, and the EER and accuracy rate on the FV_USM dataset can reach 0.04% and 99.77%. The parameter number and FLOPs of Let-Net are only 0.89M and 0.25G, which means that the time cost of training and reasoning of the model is low, and it is easier to deploy and integrate into various applications.

Intrauterine adhesions (IUA) has become one of the main causes of female infertility, how to effectively prevent postoperative re-adhesion has been a clinical challenge. In this study, a mussel-inspired dual-network hydrogel was proposed for postoperative anti-adhesion of IUA. First, calcium alginate/polyacrylamide (CA-PAM) hydrogel was prepared by covalent and Ca2+ cross-linking. Benefiting from abundant phenolic hydroxyl groups, polydopamine (PDA) was introduced to further enhance the adhesion ability and biocompatibility. This CA-PAM hydrogel immersed in 10 mg/mL dopamine solution possessed remarkable mechanical strength (elastic modulus > 5 kPa) and super stretchability (with a breaking elongation of 720%). At the same time, it shown excellent adhesion more than 6 kPa. Surprisingly, the coagulation index of the hydrogel was 27.27 ± 4.91, demonstrating attractive coagulation performance in vitro and the potential for rapid hemostasis after surgery.

The utilization of dual-potential mode of integrated array (IDA) electrodes and other two-electrode systems has revolutionized electrochemical detection by enabling the simultaneous and independent detection of two species, accompanied by the exhibition of unique characteristics. In contrast to conventional dual-potential electrodes, the rotating ring disk electrodes (RRDE), IDA electrodes demonstrate analogous yet vastly improved performance metrics, characterized by remarkable collection efficiency and sensitivity. Notably, due to the distinctive microscale structure of IDA electrode, the special “feedback” effect makes IDA a unique signal amplifier. In recent decades, the research surrounding IDA electrodes has garnered escalating interest due to their attractive attributes. This review centers its focus on the fabrication and applications of IDA electrodes. In the realm of fabrication, two critical breakthroughs are poised for realization: the achievement of reduced dimensions and the diversification of materials. Established fabrication methods for IDA electrodes encompass photolithography, inkjet printing, and direct laser writing, each affording distinct advantages in terms of size and precision in IDA construction. Predominantly employed materials for IDA electrodes include gold, platinum, and carbon, with the selection of fabrication methods guided by considerations such as material properties, desired dimensions, cost-efficiency, and specific application requisites. Within the domain of applications, IDA electrodes, capitalizing on their distinctive attributes, have found utility in diverse fields. This review summarizes the applications of IDA electrodes based on their fundamental working principles, encompassing redox cycling, resistance modulation, capacitance variations, and more. The potential for further development of this specialized tool to exhibit enhanced properties holds substantial promise.

Stevia rebaudiana (Bert.) is a natural sweetener with diterpenic glycosides, offering 300 times more sweetness than sucrose, and boasting low-calorie content, along with medicinal and therapeutic properties. To address a limited genetic diversity, a germplasm bank comprising 115 segregated lines of stevia was established in Colombia. Notwithstanding, the fungus Athelia rolfsii adversely impacted key stevia lines, leading to wilting and plant mortality. For this reason our study aimed to explore the biocontrol potential of native strains of Trichoderma spp., isolated from productive lots in Colombia's Cordoba department, as a solution to manage A. rolfsii. Soil samples underwent serial dilution technique (103 conidia.mL-1) to obtain Trichoderma spp. isolates, which were thoroughly morphologically and molecularly characterized. A total five native strains were identified through sequencing the PCR products using universal ITS primers, and comparisons with the GENBANK database confirmed their identity (OK310695.1, ON237703.1, ON238106.1, ON237737.1, and ON237923.1). Their biocontrol efficacy against A. rolfsii was evaluated using the dual culture technique. Remarkably, all strains exhibited significant biocontrol capacity against the A. rolfsii isolate INVEPAR-05 (OK271308.1), except for Trichoderma viride INVEPAR-T10 (ON237923.1). These findings suggest that Trichoderma spp. could be a potential option to manage the fungus in stevia.

The present paper provides a new definition for dual spline curves in a geometric intuitive way based on adaptive curve refinement techniques. The dual spline is an implementation of the interpolatory subdivision scheme for curve modeling, which is comprised of polynomial segments of different degrees. Specially, the dual spline curves are mainly aims to solve the difficult geometry defeaturing problems in the existing computer-aided technology. Dual spline curves maintain various desirable properties of conventional curve modeling methods, such as local adaptive subdivision, high interpolation accuracy and convergence, continuous and discontinuous boundary approximation. By adding fictitious and intrinsic nodes inside or at the vertices of interpolation elements, the dual spline is flexible and convenient for approximating a set of ordered points or discrete segments. Combined with the Lagrange interpolation polynomial and meshless method, the proposed approach is capable of approximating the non-smooth boundary for geometry defeaturing. Experimental results are given to verify the validity, robustness, and accuracy of the proposed method.

Duchenne muscular dystrophy (DMD) is a yet incurable rare genetic disease that affects the skeletal and cardiac muscles, leading to progressive muscle wasting and premature death. DMD is caused by the lack of dystrophin, a muscle protein essential for the biochemical support and integrity of muscle fibers. Gene replacement strategies for Duchenne muscular dystrophy (DMD) employing the adeno-associated virus (AAV) face the challenge imposed by the limited packaging capacity of AAV, only allowing the accommodation of a short version of dystrophin (µDys) that is still far removed from correcting human disease. The need to develop strategies leading to the expression of a best performing dystrophin variant led to only few studies reporting on the use of dual vectors, but none reported on a method to assess in vivo transgene reconstitution efficiency, the degree of which directly affects the use of safe AAV dosing. We report here on the generation of a dual AAV vector approach for the expression of a larger dystrophin version (quasidystrophin) based on homologous recombination, and the development of a methodology employing a strategic droplet digital PCR design, to determine the recombination efficiency as well as the occurrence of unwanted concatemerization events or aberrant expression from the single vectors. We demonstrated that, upon systemic delivery in the dystrophic DBA2mdx mice, our dual AAV approach led to high transgene reconstitution efficiency and negligible ITR-dependent concatemerization, with consequent remarkable protein restoration in muscles and improvement of muscle pathology. This evidence supports the suitability of our system for gene therapy application and the potential of this methodology to assess and improve the feasibility for therapeutic translation of multiple vector approaches

The study presents the synthesis and characterization of dual-layer sulfonated polyphenylenesulfone (SPPSu) nanocomposite hollow fiber nanofiltration membranes incorporating titanium dioxide (TiO2) nanoparticles using the phase inversion technique. The newly developed membranes were systematically characterized using advanced tools and methods to evaluate their properties and performance. The study focused on investigating the effects of TiO2 addition in the SPPSu inner layer on pure water permeability, and salt rejection. The nanocomposite hollow fiber nanofiltration membranes exhibited a significant enhancement in pure water permeability, with a three-fold increase compared to the pristine membranes, achieving a flux of 5.4 L/m2h.bar. The addition of TiO2 also led to an improvement in the mechanical properties of the membranes, as evidenced by the increase in the expected tensile strength from 2.4 to 3.9 MPa. To evaluate the salt rejection performance, rejection tests were conducted using a laboratory-scale filtration setup in recycle mode. Aqueous solutions containing different divalent ions, specifically magnesium sulfate (Mg2SO4) and sodium sulfate (Na2SO4) at a concentration of 500 ppm, were used as the feed solution. The modified dual-layer hollow fiber nanocomposite membranes exhibited a maximal rejection of 95% for Mg2SO4, demonstrating their effective separation capabilities for divalent ions. The findings of this study highlight the successful synthesis and characterization of dual-layer SPPSu nanocomposite hollow fiber nanofiltration membranes incorporating TiO2 nanoparticles. The incorporation of TiO2 resulted in improved pure water flux, mechanical strength, and salt rejection performance. These enhanced properties make the developed nanocomposite membranes promising candidates for applications in nanofiltration processes, particularly for the selective separation of divalent ions from aqueous solutions.

Objective: To evaluate two different DECT postprocessing protocols for detection of MSU deposits in foot tendons of cadavers with verification by polarizing light microscopy as gold standard.Material and Methods: A total of 40 embalmed cadavers (15 male; 25 female; median age, 82 years; mean, 80 years; range, 52 - 99; SD ± 10.9) underwent DECT to assess MSU deposits in foot tendons.Two postprocessing DECT protocols with different Hounsfield unit (HU) thresholds 150/500 (=established) versus 120/500 (= modified) HU were applied to dual source acquisition with 80 kV for tube A and 140 kV for tube B.Six fresh cadavers (4 male; 2 female; median age, 78; mean, 78,5; range 61 - 95 ) were examined by DECT. Tendon dissection of 2/6 fresh cadavers with positive DECT 120 and negative DECT 150 studies were used to verify MSU deposits by polarizing light microscopy.Results: The tibialis anterior tendon was found positive in 57.5%/100% (DECT 150/120), peroneus tendon in 35%/100%, achilles tendon in 25%/90%, flexor halluces longus tendon in 10%/100%, and tibialis posterior tendon in 12.5%/97.5%. DECT 120 resulted in increased tendon MSU deposit detection, when DECT 150 was negative, with an overall agreement between DECT 150 and DECT 120 of 80 % (P = 0.013). Polarizing light microscope confirmed MSU deposits detected only by DECT 120 in tibialis anterior, achilles, flexor halluces longus and peroneal tendons.Conclusion: The DECT 120 protocol showed a higher sensitivity when compared to DECT 150.

In this nano era, nanomaterials and nanostructures are popular in developing novel functional materials. However, the combinations of nanoproducts with materials at micro and macro scale can open new routes for conceiving novel materials with an improved or even new functional performances. In this study, a brand-new hybrid, containing both nanofibers and particles having a microsize, was fabricated using a sequential electrohydrodynamic atomization (EHDA) process. Firstly, the microparticles loaded with drug (berberine hydrochloride, BH) molecules in the cellulose acetate (CA) were fabricated using a solution electrospraying process. Later, these microparticles were suspended into a co-dissolved solution containned BH and a hydrophilic polymer (polypyrrolidone, PVP), and were co-electrospun into the nanofiber/microparticle hybrids. The EHDA processes were clearly recorded, and the resultant products showed a typical hybrid topography, with microparticles distributed all over the nanofibers, which was demonstrated by SEM assessments. FTIR and XRD demonstrated that the components within the hybrids were presented in an amorphous state and have fine compatibility with each other. In vitro dissolution tests verified that the hybrids were able to provide the designed dula-step drug release profiles, a combination of the fast release step of BH from the hydrophilic PVP nanofibers through an erosion mechanism and the sustained release step of BH from the insoluble CA microparticles via a typical Fickian diffusion mechanism. The present protocols pave a new way for developing trans-scale functional materials.

A low-profile broadband dual-polarized antenna is investigated for base station applications. It consists of two orthogonal dipoles, fork-shaped feeding lines, an artificial magnetic conductor (AMC), and parasitic strips. By utilizing the dispersion Brillouin diagram, the AMC is designed as the antenna reflector. It has a wide in-phase reflection bandwidth of 54.7% (1.54-2.70 GHz) and a surface wave bound range of 0-2.65 GHz. This design effectively reduces the antenna profile by over 50% compared to traditional antennas without an AMC. For demonstration, a prototype is fabricated for 2G/3G/LTE base station applications. Good agreement between simulations and measurements is observed. The measured -10-dB impedance bandwidth of our antenna is 55.4% (1.58 –2.79 GHz), with a stable gain of 9.5 dBi and high isolation of more than 30 dB across the impedance passband. As a result, this antenna is an excellent candidate for miniaturized base station antenna applications.

Human induced pluripotent stem cells (hiPSCs) have two characteristic abilities 1) self-renewal and 2) differentiation into all cell types in the human body. It is this ability of iPSCs to differentiate into any desired cell type that makes them amenable to disease modeling. iPSCs can further be engineered to carry a disease-specific mutation or be derived from patients to phenocopy the disease. To model neurodegenerative/neurodevelopmental disorders iPSCs are differentiated into neurons. This chapter describes protocols for two different approaches to generate neurons from iPSCs, first using dual SMAD inhibition to generate neural progenitor cells which are then differentiated into neurons, and second using single transcription factor (NGN2) over-expression to drive differentiation of iPSCs directly into neurons.

To promote low-carbon and green travel, this study proposes a tripartite evolutionary game model among new energy vehicle manufacturers, consumers, and government agencies. The game strategy combinations of each party and the stability conditions of the equilibrium point in the evolutionary game system are analyzed, and the validity of the conclusions is verified through simulation results. The study shows a strong correlation between the three parties in the evolutionary game system. From the perspective of car manufacturers, the probability of producing new energy vehicles is positively proportional to the subsidy received from new energy policy, the additional revenue gained from the management of the carbon trading scheme, and the fine received for producing conventional fuel vehicles. However, from the consumer perspective, the likelihood that consumers purchase new energy vehicles is positively related to the utility value to consumers and the coverage of public charging points in the city, and inversely related to the sales price of new energy vehicles. From the government perspective, a combination of direct subsidy policies and indirect support strategies should be considered to stimulate the rapid development of the new energy vehicle industry.

Nowadays, many Muslim-majority countries have implemented a dual banking system, namely the sharia and conventional systems. The development of Islamic banks is to fulfill the Muslims' need for the existence of halal transactions in financial institutions. However, in some countries, it turns out that conventional banks still dominate the country's economy. Because of that, it is necessary to see whether there are differences in financial risk and Earnings management between Islamic and conventional banks. The samples are conventional and Islamic banks in Southeast Asia, analyzed by the purposive sampling method from 2010-2019. The analytical tool used is the statistical difference test and economometrics analysis using generalized least square (GLS) regression with panel data (time series and cross-sectional data). These models are intended to forecasting the macroeconomics effects in applying dual banking system in one country or region. The results using non parametrics means difference test showed that the first hypothesis is accepted It means that Earnings management in conventional banks is greater than in Islamic banks. The Random Model Effect (REM) for second and third hypotheses testing on Conventional banks shows the Bankruptcy Risk and NPL do not affect the dependent variable Earnings Management (LLP). While fixed effect model testing on Islamic banks, the second and third hypothesis testing is rejected. Therefor Islamic Banks the value of Bankruptcy Risk (z-score) and the value of Non-Performing Loans (NPL) do not affect Earnings management. It also means that hypothesis 2 and 3 are rejected both in conventional as well as Islamic Banking. Sensitivity analysis for conventional as well as Islamic banking altogether using fixed effect model shows that the second and third hypotheses show that the independent variables (Bankruptcy Risk and NPL) do not affect the dependent variable Earnings Management (LLP). These results can be concluded that Islamic bank are enganged in less earnings management. Therefor in the the long run there are still more research that should conduct in comparing dual banking system in one region.

Introduction: A dual malignancy with both Ewing Sarcoma and Prostate Adenocarcinoma has not been reported in the English literature. We report a case of simultaneous diagnosis of Ewing sarcoma and prostate adenocarcinoma with profound clinical manifestation. Case presentation: A 53-year-old male with advanced metastatic prostate cancer (Gleason-9) admitted with classical presentation of cauda equina syndrome including incontinence, back pain, and paresis following bilateral nephrostomy insertion for the treatment of bilateral renal hy-dronephrosis. The patient was diagnosed with an epidural abscess at the level of L5-S1 and an emergency surgical spine decompression was performed. No abscess was found, and pathology results showed a concomitant primary Ewing sarcoma in the spine. Conclusions: Very rare occurrences of a dual primary malignancy, in this case, Ewing sarcoma and prostate adenocarcinoma, should be kept in mind in patients suffering from complex clinical course of malignancies.

Aims: In late December 2019, early reports predicted the onset of a potential Coronavirus outbreak in china, given the estimate of a reproduction number for the 2019 Novel Coronavirus (COVID-19). Because of high ability of transmission and widespread prevalence, the mortality of COVID-19 infection is growing fast worldwide. Absent of an anti-COVID-19 has put scientists on the urge to repurpose already approved therapeutics or to find new active compounds against coronavirus. Here in this study, a set of computational approaches were performed in order to repurpose antivirals for dual inhibition of the frontier proteases involved in virus replication, papain-like protease (PLpro; corresponding to nsp3) and a main protease (Mpro), 3C‑like protease (3CLpro; corresponding to nsp5). Materials and Methods: In this regard, a rational virtual screening procedure including exhaustive docking techniques was performed for a database of 160 antiviral agents over 3CLpro and PLpro active sites of SARS-CoV-2. The compounds binding energies and interaction modes over 3CLpro and PLpro active sites were analyzed and ranked with the aid of free Gibbs binding energy. The most potent compounds, based on our filtering process, are then proposed as dual inhibitors of SARSC-CoV-2 proteases. Key findings: Accordingly, seven antiviral agents including two FDA approved (Nelfinavir, Valaganciclovir) and five investigational compounds (Merimepodib, Inarigivir, Remdesivir, Taribavirine and TAS106-106) are proposed as potential dual inhibitors of the enzymes necessary for RNA replication in which Remdesivir as well as Inagrivir have the highest binding affinity for both of the active sites. Significance: The mentioned drug proposed to inhibit both PLpro and 3CLpro enzymes with the aim of finding dual inhibitors of SARSC-CoV-2 proteases.

Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new dynamic programming for seamlessly stitching UAV images using optical flow. Our solution consists of two steps: Firstly, an image-matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is develop based on the concept of a stereo dual-channel energy accumulation using optical flow. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for adjacent image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching. Beyond that, our solution is also direction-independent, which has more adaptability and robustness for UAV images.

In order to correct attenuated millimeter-wavelength (Ka-band) radar data and address the problem of instability, an attenuation correction methodology (attenuation correction with variation trend constraint; VTC) was developed. Using synchronous observation conditions and multi-band radars, the VTC method adopts the variation trends of reflectivity in X-band radar data captured with wavelet transform as a constraint to adjust reflectivity factors of millimeter-wavelength radar. The correction was evaluated by comparing reflectivities obtained by millimeter-wavelength cloud radar and X-band weather radar. Experiments showed that attenuation was a major contributory factor in the different reflectivities of the two radars when relatively intense echoes exist, and the attenuation correction developed in this study significantly improved data quality for millimeter-wavelength radar. Reflectivity differences between the two radars were reduced and reflectivity correlations were enhanced. Errors caused by attenuation were eliminated, while variation details in the reflectivity factors were retained. The VTC method is superior to the bin-by-bin method in terms of correction amplitude and can be used for attenuation correction of shorter wavelength radar assisted by longer wavelength radar data.

Durability monitoring of insecticide-treated nets (ITNs) containing a pyrethroid in combination with a second active ingredient (AI) must be adapted so that the insecticidal bioefficacy of each AI can be monitored independently. An effective way to do this is to measure rapid knock down of a pyrethroid-susceptible strain of mosquitoes to assess the bioefficacy of the pyrethroid component and to use a pyrethroid-resistant strain to measure the bioefficacy of the second ingredient. To allow robust comparison of results across tests within and between test facilities, and over time, protocols for bioefficacy testing must include either characterisation of the resistant strain, standardisation of the mosquitoes used for bioassays, or a combination of the two. Through a series of virtual meetings, key stakeholders and practitioners explored different approaches to achieving these goals. Via an iterative process we decided on the preferred approach and produced a protocol consisting of characterising mosquitoes used for bioefficacy testing before and after a round of bioassays, for example at each time point in a durability monitoring study. We present the final protocol and justify our approach to establishing a standard methodology for durability monitoring of ITNs containing pyrethroid and a second AI.

The purpose of this study was to investigate the effects of cognitive dual-tasking on gait initiation and sit-to-walk. Twenty-eight healthy young adults performed gait initiation and sit-to-walk under two conditions: while engaging in serial subtraction (dual-task) and without any additional task (single-task). Motion data were collected using a 10-camera optoelectronic motion capture system, synchronized with force plates and surface electromyography. We analyzed spatiotemporal parameters, center of mass displacement, center of pressure trajectory, and lower limb muscle activation patterns. We found that dual-task conditions significantly affected both gait initiation and sit-to-walk patterns, increasing the duration of transitions and mediolateral center of mass displacements, while reducing vertical center of mass displacements and forward propulsion. We also observed a more constrained and less efficient center of pressure path, with reduced posterior displacement during the weight shift phase. Muscle activation, particularly in the tibialis anterior and biceps femoris, decreased during dual-task conditions, indicating altered neuromuscular strategies. These findings suggest a shift in postural control demands and motor performance during dual-task transitions.

In recent years, electroencephalogram (EEG) emotion recognition has emerged as a research hotspot in the field of artificial intelligence (AI). Despite advancements in EEG-based emotion recognition, room for enhancing performance persists due to EEG signal redundancy and limitations in feature extraction, leading to inefficient models and emotional information loss. To fully utilize EEG's emotional information and improve recognition accuracy while reducing computational costs, this paper proposes a Convolutional-Recurrent Hybrid Network with a dual-stream adaptive approach and an attention mechanism (CSA-SA-CRTNN). Firstly, the model utilizes a CSAM module to assign corresponding weights to EEG channels. Then, an adaptive dual-stream convolutional-recurrent network (SA-CRNN and MHSA-CRNN) is applied to extract local spatial-temporal features. After that, the extracted local features are concatenated and fed into a temporal convolutional network with a multi-head self-attention mechanism (MHSA-TCN) to capture global information. Finally, the extracted EEG information is used for emotion classification. We conducted binary and ternary classification experiments on the DEAP dataset, achieving 99.26% and 99.15% accuracy for arousal and valence in binary classification, and 97.69% and 98.05% in ternary classification, surpassing relevant algorithms. Additionally, the model's efficiency is significantly higher than other models, achieving better accuracy with lower resource consumption.

Human development encompasses the integration of neuromotor, psychological, social-emotional, and cognitive processes across time. However, a better understanding of the interconnectedness of motor and cognitive development throughout the lifespan is needed. The integrative and dynamic nature of short-term motor skill acquisition and long-term developmental processes may foster executive functions. Unfortunately, assessments of motor competence have traditionally focused on skillfulness from a movement perspective, using restrictive task protocols that decontextualize performance and limit cognitive involvement. Additionally, traditional motor-cognitive dual-task assessments centered on cognitive involvement during specific movement protocols, have minimized impacts of task complexity and motor competence on cognitive performance. To gain a more ecologically valid understanding of the relation between motor and cognitive development, a novel assessment paradigm using an integrative approach to motor-cognitive dual-tasking is needed. The purpose of the present paper is to: 1) provide a conceptual bridge, based on multidisciplinary evidence, to effectively link the concurrent development of motor competence and executive functions via learning-related and exercise-related neurotrophic mechanisms, and 2) use this conceptual bridge to inform the development of novel motor-cognitive dual-task assessments that account for the role of task complexity, current levels of motor competence, and the continuous decision-making inherent in “real world” performance environments.

Background: Recent studies have found forward head posture (FHP) to be associated with altered physiology, however, there is a lack of research into whether FHP is associated with altered gait parameters when cognitively challenged. The current study was undertaken to investigate the changes in gait parameters in asymptomatic individuals with FHP when a cognitive dual task is introduced during walking. Methods: Ninety asymptomatic participants were recruited, 45 having FHP defined as having a craniovertebral angle (CVA) &lt; 50, and 45 sex and age-matched controls having normal head posture (NHP) defined as CVA &gt; 55. All participants walked along a 10 meter platform under a control condition (no cognitive load) with 3 consecutive trials while an optical motion-capture system consisting of 8 infrared cameras was used to assess gait kinematics. Secondly, participants were assessed under a dual task cognitive load condition (3 trials while performing simple addition, counting backwards, and answering yes or no questions) to identify the impact on gait kinematics compared to the control condition. Results: Under the single task condition, there were no significant differences for any gait parameter, however, under the dual task condition, 12/13 gait parameters were significantly altered for the FHP group compared to the NHP group (p &lt; .01). A calculation of dual task cost (DTC) percentage showed significant increases in all gait parameters in participants with FHP (p &lt; .02). Correlations between the CVA and gait parameters were not significant for the single task condition, but all gait parameters were correlated to CVA for the dual task condition (p &lt; .01). The correlation between CVA and DTC for all gait variables were also significant (p &lt; .04). Conclusions: This study demonstrates that FHP significantly increases the cognitive cost during walking, highlighting the importance of proper postural alignment for maintaining cognitive function under a dual task condition. Addressing FHP through targeted interventions could improve both physical and cognitive health, enhancing overall well-being and daily functioning.

Sleep quality is known to affect automatic and executive brain functions such as gait control and cognitive processing. This study aimed to assess the effect of dual tasks on gait spatiotemporal parameters among young adults with good and poor sleep quality in the United Arab Emirates. In total, 65 young adults with a mean age of 21.1±2.5 were assessed for gait analysis during single-task and dual-task conditions. The participants’ sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), and gait was assessed using the BTS Gaitlab System. The participants were asked to walk at natural speed as a single-task condition, followed by walking while performing a cognitive task as a dual-task condition. The parameters assessed included the gait velocity (m/s), cadence (steps/min), step width (m), and stride length (m). The DTC on each gait parameter was calculated. The Mann–Whitney U test was used to compare the differences in the DTC on gait variables between the good and poor sleep quality groups, and the Spearman correlation test was used to assess the correlation between total PSQI scores and the DTC. At a significance level of p&lt;0.05, a significant difference in cadence between the two sleep quality groups was observed, in addition to a positive correlation between sleep quality and the DTC effect on gait mean velocity, cadence, and stride length. Our findings also revealed a greater DTC on participants with poorer sleep quality. These findings contribute to our understanding of the significance of sleep quality in gait performance while multitasking in younger populations.

Computational simulations of three-dimensional flow around a NACA 0018 wing with an aspect ratio of AR=5 are carried out using the Unsteady Reynolds-Averaged Navier-Stokes (URANS) equations with the Shear-Stress Transport turbulence model closure. Simulations were performed to capture the aerodynamic stall hysteresis using a developed Pseudo-Transient Continuation (PTC) method based on a dual time step approach in the CFD code OpenFOAM. The flow was characterized by an incompressible Mach number of M=0.12 and a moderate Reynolds number Re=0.67×10^6. The results obtained indicate the presence of a noticeable aerodynamic hysteresis in the static dependencies of the force and moment coefficients, as well as the manifestation of bi-stable flow separation patterns, accompanied by the development of asymmetry in the stall zone. The URANS simulation results are in good agreement with the experimental data obtained for the NACA 0018 finite aspect ratio wing from the low-speed wind tunnel under the same test conditions. A new phenomenological bifurcation model of aerodynamic stall hysteresis under static and dynamic conditions is formulated, which is proven to be able to closely match the experimental data.

The dual-station Interferometric Synthetic Aperture Radar (InSAR) system can overcome the physical limitations imposed by the baseline of single-station dual-antenna InSAR. It provides greater flexibility and can enhance elevation measurement accuracy through a well-designed baseline configuration.Unmanned aerial vehicles (UAV) equipped with dual-station InSAR, with relatively low cost and high flexibility, are useful for mapping and land resource exploration. However, due to challenges including spatiotemporal synchronization and motion errors, there are limited reports on UAV-borne dual-station InSAR. This paper proposes a comprehensive method for processing data from small UAV-borne dual-station InSAR by integrating two-way synchronization chain signals. The proposed method includes compensation for time and phase synchronization errors, trajectory refinement with synchronized chain and Position and Orientation System (POS) data, high-precision dual-station InSAR imaging and interferometric processing. Height inversion results based on the proposed method is also provided, demonstrating the effectiveness of the proposed method and improving interferometric accuracy at calibration points from 0.66 meters to 0.42 meters.

The dual leucine zipper kinase (DLK) alias mitogen-activated protein 3 kinase 12 (MAP3K12) has gained much attention in recent years. DLK belongs to the mixed lineage kinases, characterized by homology to serine/threonine and tyrosine kinase but exerts serine/threonine kinase activity. DLK has been implicated in many diseases including several neurodegenerative diseases, glaucoma, and diabetes mellitus. As a MAP3K, it is generally assumed that DLK becomes phosphorylated and activated by upstream signals and phosphorylates and activates itself, the downstream serine/threonine MAP2K, and ultimately MAPK. In addition, other mechanisms such as protein-protein interactions, proteasomal degradation, dephosphorylation by various phosphatases, palmitoylation, and subcellular localization have been shown to be involved in the regulation of DLK activity or its fine-tuning. In the present review, the diverse mechanisms regulating DLK activity will be summarized to provide a better insight into DLK action and possibly new targets to modulate DLK function.

Pesticides are chemical products are used to protect crops to prevent or eliminate undesirable organisms. Pesticides can contaminate continental waters, air, soil and food products. The presence of pesticide residues must therefore be monitored in water and food using sensitive, reliable and broad-spectrum analytical methods, as there is a huge variety of pesticides. Biosensors are one of the screening methods with great potential for detecting residues below the maximum residue limits. The different sensing principles of enzymatic biosensors for pesticide analysis will be described. This review highlights the great potential of colorimetric, enzymatic biosensors for detecting pesticide residues in water and food. Moreover the development of dual colorimetric and fluorimetric sensors during the past years is presented. These methods are most often based on the enzyme acetylcholinesterase, whose activity is inhibited by pesticides. The different approaches used in the development of these biosensors will be detailed, based on different chemical substrates, fluorophores and nanomaterials. The advantages and disadvantages of each approach will be discussed. Finally, the development prospects for improving these biosensors will be presented.

Measuring pulmonary nodules accurately can help with early diagnosis of lung cancer, which can improve a patient’s chances of survival. Many methods for segmenting nodules have been developed, but they all rely on input from radiologists in the form of a 3D volume of interest (VOI) or use a constant region of interest (ROI) and only consider the presence of nodule within the given VOI. These approaches limit the networks’ ability to detect nodules outside the given VOI and can also include unnecessary structures in the VOI, leading to potentially inaccurate segmentation. In this work, we propose a novel approach for 3D lung nodule segmentation by using 2D region of interest (ROI) inputted from radiologist or computer-aided detection (CADe) system. Particularly, we design a dual-encoder-based hard attention network (DEHA-Net) which incorporates the full slice of thoracic computed tomography scan along with the ROI mask to produce an accurate segmentation mask of lung nodule in the given slice. The proposed architecture exploits the adaptive region of interest (A-ROI) algorithm to automatically investigates the penetration of lung nodule into surrounding slices while eliminating the need to drawing separate ROIs in each slice. Further, the framework performs the multi-view analysis, i.e., in sagittal and coronal views, to improve the segmentation performance. The proposed scheme has been rigorously evaluated on the lung image database consortium and image database resource initiative (LIDC/IDRI) dataset and an extensive analysis of results have been performed. The quantitative analysis shows that the proposed method not only improves the existing state-of-the-art in term of dice score but also, significantly robust against the different types, shape and dimensions of lung nodules.

In this paper a microstrip Wilkinson power divider with a 90^° phase delay at one output port is proposed to obtain circular polarization to feed a dual port RFID antenna. The 90^° phase delay was obtained by embedding an extra quarter wavelength at one port of the Wilkinson power divider. The feeding circuit is then mounted on the ground plane of the microstrip antenna feeding the radiating patch directly through the ground plane and dielectric layer thus reducing any fringing effect and resulting a mechanically compact unit. The proposed feeding method offers better expectation of antenna performance with minimal attenuation and coupling losses. The design process generalizes geometric pa- rameters of the Wilkinson power divider for variable port distances. The paper considers both UK and US RFID center frequencies, 870 MHz and 915 MHz respectively. Numeri- cally computed values for geometric design parameters for both frequencies are tabled as future design tools for port distances varying from 18 mm up to 34 mm at 870 MHz and 17 mm up to 32 mm at 915 MHz. Simulation results indicate a return loss (S11) of -20 dB and -26 dB at 870 MHz and 915 MHz operational frequencies respectively at 270^° angled quarter wavelength.

The kinetics and modeling of dual-wavelength controlled photopolymerization confinement (PC) are presented and measured data are analyzed by analytic formulas and numerical data. The UV-light initiated inhibition effect is strongly monomer-dependent and different monomers have different C=C bond rate constants and conversion efficacy. Without the UV-light, for a given blue-light intensity, higher initiator concentration (C₁₀) and rate constant (k’) lead to higher conversion, as also predicted by analytic formulas, in which the total conversion rate (R_T) is an increasing function of k’R, which is proportional to k[gB₁C₁]^0.5. However, the coupling factor b₁ plays a different role that higher b₁ leads to higher conversion only in the transient regime; whereas higher b₁ leads lower steady-state conversion. For a fixed initiator concentration C₁₀, higher inhibitor concentration (C₂₀) leads to lower conversion due to stronger inhibition effect. However, same conversion reduction was found for the same H-factor of H₀ = [b₁C₁₀ - b₂C₂₀]. Conversion of blue-only are much higher than that of UV-only and UV-blue combined, in which high C₂₀ results a strong reduction of blue-only-conversion, such that the UV-light serves as the turn-off (trigger) mechanism for the purpose of spatial confirmation within the overlap area of UV and blue light. For example, UV-light controlled methacrylate conversion of a glycidyl dimethacrylate resin formulated with a tertiary amine co-initiator, and butyl nitrite, subject to a continuous exposure of a blue light, but an on-off exposure of a UV-light. Finally, we developed a theoretical new finding for the criterion of a good material/candidate governed by a double ratio of light-intensity and concentration, [I₂₀C₂₀.]/[I₁₀C₁₀].

Lung cancer remains the leading cancer killer worldwide. Early diagnosis can effectively increase the patient cure rate but existing diagnostic methods limit early lung cancer diagnosis. Therefore, development of a simple but efficient lung cancer screening method is important to improvement of both the diagnosis rate and the survival rate of lung cancer patients. In this study, ten photosensitive materials with high sensitivity and high specificity were screened accurately to construct a microarray sensor that can rapidly identify six types of lung cancer biomarkers in exhaled breath. Results from hierarchical cluster analysis (HCA), principal component analysis (PCA) and difference maps showed that the classification of the analytes agreed with structure similarity laws. The detection results from parallel experiments and structurally similar analytes, in turn, cluster into a group; the fingerprints of the different analytes have specific response regions. The well-screened sensor chip fabrication workload and cost were both reduced by approximately two thirds, while the microfluidic device sensitivity and stability increased by approximately 1.3 times their corresponding values before optimization. The dual-channel device also offers real-time contrast detection and synchronous parallel detection functions and has potential application prospects for use in extensive screening of high-risk populations for lung cancer.

This study evaluates the effectiveness of adaptive binaural beamforming in a realistic cafeteria noise environment. The motivation stems from the common challenge faced by hearing aid users in such environments, where communication often demands significant mental effort. The study employed a combination of behavioural, neurophysiological, and self-reported measures to assess speech intelligibility and listening effort. Results showed that the adaptive binaural beamformer improved speech-in-noise intelligibility at signal-to-noise ratios (SNRs) yielding 80% and 95% intelligibility. Additionally, when this technology was enabled, listening effort was reduced across various metrics: faster reaction times on a dual task, decreased pre-stimulus alpha power (8-12 Hz), indicating less inhibition was needed, and increased alpha power during the encoding and retention phases, consistent with greater working memory load due to improved intelligibility. Self-reports indicated lower perceived effort in the more challenging SNR condition. The use of realistic background noise enhances the ecological validity of the findings, contributing to a better understanding of how this hearing aid technology performs in real-world listening environments. Overall, the study demonstrates that adaptive binaural beamforming can ease the cognitive burden on users in noisy, everyday environments, thereby enhancing their overall auditory experience.

Substance abuse and psychiatric disorders are two prevalent and interrelated public health concerns that often coexist, leading to complex clinical scenarios. This comorbidity poses significant challenges in diagnosis, treatment, and understanding the causal relationships between the two conditions. Frequently, one disorder is neglected in favor of the other, and misconceptions abound regarding which condition precipitates the other. This article explores the common comorbidity of substance abuse and psychiatric disorders, delving into the prevalence, diagnostic challenges, treatment implications, and the bidirectional nature of causality. By examining current research and clinical practice, we aim to shed light on the misconceptions and emphasize the need for integrated approaches to effectively address both conditions concurrently.

Traffic sign detection plays a pivotal role in autonomous driving systems. The intricacy of the detection model necessitates high-performance hardware. Real-world traffic environments exhibit considerable variability and diversity, posing challenges for effective feature extraction by the model. Therefore, it is imperative to develop a detection model that is not only highly accurate but also lightweight. In this paper, we proposed YOLO-ADual, a novel lightweight model. Our method leverages the C3Dual and Adown lightweight modules as replacements for CPS and CBL modules in YOLOv5. The Adown module effectively mitigates feature loss during downsampling while reducing computational costs. Meanwhile, C3Dual optimizes the processing power for kernel feature extraction, enhancing computation efficiency while preserving network depth and feature extraction capability. Furthermore, the inclusion of the CBAM module enables the network to focus on salient information within the image, thus augmenting its feature representation capability. Our proposed algorithm achieves a mAP@0.5 of 70.1% while significantly reducing the number of parameters and computational requirements to 51.83% and 64.73% of the original model, respectively. Compared to various lightweight models, our approach demonstrates competitive performance in terms of both computational efficiency and accuracy.

Incorporating knowledge graphs as auxiliary information to enhance recommendation systems can improve the representations learning of users and items. Recommendation methods based on knowledge graph can introduce user-item interaction learning into the item graph, focusing only on learning the node vector representations within a single graph; alternatively, they can treat user-item interactions and item graphs as two separate graphs and learn from each graph individually. Learning from two graphs has natural advantages in exploring original information and interaction information, but faces two main challenges: 1) in complex graph connection scenarios, how to adequately mine the self-information of each graph, and 2) how to merge interaction information from the two graphs while ensuring that user-item interaction information predominates. Existing methods do not thoroughly explore the simultaneous mining of self-information from both graphs and effective interaction information, leading to the loss of valuable insights. Considering the success of contrastive learning in mining self-information and auxiliary information, this paper proposes a dual-graph contrastive learning recommendation method based on knowledge graphs (KGDC) to explore a more accurate representations of users and items in recommendation systems based on external knowledge graphs. In the learning process within the self-graph, KGDC has strengthened and represented the information of different connecting edges in both graphs, and extracted the existing information more fully. In interactive information learning, KGDC reinforces the interaction relationship between users and items in the external knowledge graph, realizing the leading role of the main task. We have conducted a series of experiments on three standard datasets, and the results show that the proposed method can achieve better results.

Insulin-like Growth Factor 2 mRNA binding Protein 1 (IGF2BP1) is a promising candidate gene for influencing economic traits in livestock and poultry. The second intronic region of IGF2BP1 is closely related to growth traits, although the exact mechanism remains unclear. The preliminary resequencing results of goats in our laboratory demonstrated that the IGF2BP1 gene region was subject to strong selection, then we selected multiple single nucleotide polymorphisms (SNPs) to identify. Seven SNPs were located in the conserved region of the second intron, and their functions and relationship with growth traits require further clarification. This study selected 348 Nanjiang Yellow goats as experimental subjects, and chose Time of Flight Mass Spectrometer (MALDI-TOF) as the main method. Our results showed that six SNPs were significantly correlated with the growth traits of the Nanjiang yellow goat by association analysis. Among them, the rs652062749(A>G) was identified as the primary locus affecting the later stage of growth traits of Nanjiang yellow goat. Moreover, there was a strong linkage among three SNPs, and the rs638185407 (T>A) mutant type was observed to increase the luciferase activity in H293T cells extremely significantly. The TTAACT, TTCCCC, and ATCACT combination genotypes were dominant combination genotypes, which provided theoretical references for further genetic co-breeding. The results of our study demonstrate the potential role of the IGF2BP1 gene as a functional genetic marker in the breeding programs of Nanjiang Yellow goats.

Understanding the distribution of rock glaciers provides key information for investigating and recognizing the status and changes of the periglacial environment. Deep learning algorithms and red-green-blue (RGB) bands from high-resolution satellite images have been extensively employed to map rock glaciers. However, the near-infrared (NIR) band offers rich spectral information and sharp edge features that could significantly contribute to semantic segmentation tasks, but it is rarely utilized in constructing rock glacier identification models due to the limitation of three input bands for classical semantic segmentation networks, like DeeplabV3+. In this study, a dual-encoder DeeplabV3+ network (DEDNet) was designed to overcome the flaws of classical DeeplabV3+ network (CDNet) when identifying rock glaciers using multispectral remote sensing images by extracting spatial and spectral features from RGB and NIR bands, respectively. This network, trained with manually labeled rock glacier samples from QiLian Mountains, established a model with accuracy, precision, recall, specificity, and mIoU (Mean Intersection over Union) of 0.9131, 0.9130, 0.9270, 0.9195, and 0.8601, respectively. The well-trained model was applied to identify new rock glaciers in a test region, achieving a producer's accuracy of 93.68% and a user's accuracy of 94.18%. Furthermore, the model was employed to two study areas in northern Tien Shan (Kazakhstan) and Daxue Shan (Hengduan Shan, China) with high accuracy, which proved that the DEDNet offers an innovative solution to more accurately map rock glaciers on a larger scale due to its robustness across diverse geographic regions.

A two-year experiment was conducted with a local maize hybrid under full irrigation (F), deficit irrigation (D) and rainfed conditions (R) to estimate maize evapotranspiration in Bosnia and Herzegovina. Three approaches (Allen & Pereira (A&P), SIMDualKc (SD), and Vegetation Index (VI)) were used to estimate the actual crop coefficient (Kc act), actual basal crop coefficient (Kcb act), and actual crop evapotranspiration (ETc act) were applied with the dual crop coefficient method and remote sensing (RS) data. While Kcb act from all approaches matched FAO56 tabulated values, SD showed differences, in comparison to A&P, of up to 0.24 in D and R conditions, especially in initial and mid-season stages. VI demonstrated very good performance in all treatments. In F, the obtained Kc act for all approaches during the initial and end stages were higher than the tabulated values, ranging from 0.71-0.87 for Kc ini act and from 0.80-1.06 for Kc end act, while the mid-season period showed very good agreement with the literature. Maize crop evapotranspiration range is 769-813 mm, 480-752 mm, and 332-618 mm for F, D and R, respectively. The results confirmed the suitability of both approaches (SD and VI) to estimate maize crop evapotranspiration under F, with the VI approach demonstrating an advantage in calculating Kcb act, Kc act, and ETc act values under water stress conditions. The 67.6% increase in grain yields with irrigation emphasizes the need to transition from rainfed to irrigation-dependent agriculture, even for drought-resistant crops like maize.

Osteoporosis is considered a serious public health problem, particularly affecting the postmenopausal period. In 2018, in the Republic of Kazakhstan the total and primary incidence was 10 and 3.7 cases per 100,000 adults, respectively. The objective is to study osteoporosis prevalence and indicate main factors affecting low bone mineral density by screening adult population of Abay region, Kazakhstan. The target group were 641 respondents aged between 18 and 65 years old, Kazakh population living in Abay region since birth. All participants filled out questionnaire and had a bone mineral density measurement by dual energy X-ray absorptiometry (DXA) between July 15, 2023 and February 29, 2024. Logistic regression analysis was conducted to assess the association between low bone mineral density and key demographic characteristics, aforementioned lifestyle factors and nutrition habits. We identified the prevalence of low bone density and osteoporosis at the level of 34.1% with the highest prevalence in the older population group (50+ years) - 48.3%. Regression analysis revealed a number of indicators associated with the likelihood of bone sparing. However, only 4 of these showed significance in the final multivariate model (R2=22.4%). These included age (AOR 1.05), body mass index (AOR 0.92), fracture history (AOR 1.64), consumption of nuts and dried fruits were associated with lower prevalence of osteoporosis (AOR 0.48). Our study was the first in Kazakhstan that investigates the association of key demographic, behavior and anamnestic factors with low mineral density.