In this paper, we consider the optimal control problem for stochastic system driven by fractional Brownian motion with Hurst parameter H>1/2 and standard Brownian motion. The state equation is described by stochastic differential delayed equations involving both delays in the state variable and the control variable. We obtain the maximum principle for optimal control of this problem by virtue of the duality method and the anticipated backward stochastic differential equations. As an application, the linear quadratic case is investigated to illustrate the main results.

Major Depressive Disorder (MDD) is a prevalent psychiatric condition that affects millions of people worldwide and is a leading cause of disability. Chronic stress is a key factor in the development of MDD, leading to hyperactivation of the hypothalamic-pituitary-adrenal (HPA) axis and elevated glucocorticoid levels, which in turn affect brain function and structure. Astrocytes, crucial for maintaining central nervous system (CNS) homeostasis, play a significant role in the pathophysiology of MDD. Dysregulation of glucocorticoid signaling in astrocytes contributes to changes in astrocyte survival, reactivity, metabolism, neurotrophic support, gliotransmitter release, and neuroinflammation, exacerbating depressive symptoms. This review explains the necessity for exploring the effects of glucocorticoid in astrocytes and subsequent MDD progression. Firstly, we briefly explore the glucocorticoid signaling and the multifaceted function of astrocytes. Then, this study discusses the mechanisms by which chronic stress and glucocorticoid exposure induce astrocyte-mediated neurodegenerative changes including inflammation, metabolic dysfunction, and neurotoxic mechanisms, highlighting the importance of targeting glucocorticoid-related signaling of astrocytes in developing therapeutic interventions for MDD. Understanding these mechanisms could lead to the development of more effective treatments aimed at restoring astrocyte function and alleviating MDD.

Endometriosis is a gynecological and painful condition affecting women of reproductive age. It is characterized by dysfunctional endometrium-like implants outside of uterine.The purpose of this study was to investigate the effect of Paeoniflorin on pain relief and explore its mechanism in alleviating pain. Methods：An animal model of endometriosis (EM) was established in rats through autologous transplantation. The rats were divided into six groups: blank group, sham group, EMS group, Paeoniflorin low-dose group, Paeoniflorin high-dose group and positive control group. The rats received treatment for weeks. The thermal radiation and mechanical pain thresholds were measured every 7 days. The recovery rate of estrus period,ovarian index, uterine index were assessed. HE staining was utilized to observe pathological changes and serum levels of GSH, SOD, ROS, PGE2, IL-6, and TGF-αwere measured using ELISA. The expression levels of TRPV1, JAK2, STAT3 in the endometrium and endometriotic lesions were measured using WB and qPCR. Results：The model group exhibited degeneration and necrosis of endometrial epithelial cells, along with inflammatory cell infiltration. Treatment with Paeoniflorin and danazol mitigated these pathological changes, leading to a decrease in ROS and an increase in SOD, CAT, and GSH. Among the groups, the high-dose Paeoniflorin group demonstrated the most significant efficacy in alleviating pain. Paeoniflorin decreased the expression of TRPV1, p-TRPV1 and JAK2. Conclusions：Paeoniflorin demonstrates the potential to inhibit the progression of endometriosis and alleviate pain. These effects may be achieved by reducing the inflammatory response and impacting the STAT3 signaling pathway in ectopic tissues.

The attachment oscillator, a crucial system in nanophysics and nanotechnology, plays an essential role in nano/micro-electromechanical systems, molecular devices, and the formation of nanofiber membranes. Traditional analytical approaches to deducing the amplitude-frequency relationship (AFR) for such oscillators, including energy balance theory (EBT) and homotopy perturbation methods (HPM), often show limitations in predicting frequency behavior while comparing with the numerical results. This paper presents an analytical solution derived using the energy balance method, which provides a more accurate AFR for low-amplitude oscillations than existing models. Our result shows excellent agreement with numerical simulations, while other contemporary approaches exhibit significant deviations. This advancement offers a more robust understanding of attachment oscillators and their applications in nanotechnology, providing a new analytical framework that surpasses previous works.

A document by Balakrishnan Kamaraj. Click on the document to view its contents.

A document by biao cheng. Click on the document to view its contents.

Fluid antenna multiple access (FAMA) is a concept capable of massive connectivity on the same physical channel without the need of precoding or interference cancellation, by exploiting a super-high dimensional received signal in the spatial domain from fluid antenna system (FAS). This letter investigates the use of 5G New Radio (NR) Modulation Coding Scheme (MCS) for FAMA systems to improve its connectivity over block fading channels. In particular, we propose an iterative decoding receiver with iterative interference covariance estimation for the coded FAMA system. Extrinsic information transfer (EXIT) chart is used to analyze the performance of the proposed iterative receiver. Both EXIT chart analysis and numerical results show that the proposed receiver outperforms the one that uses fixed covariance in the block fading channel. Also, the results indicate that coded FAMA can serve 100 user terminals (UTs) at the rate of 0.5 bit/s/Hz under rich scattering.

The use of steroids, along with chemotherapy in the management of Acute Myeloid Leukemia (AML), is not a part of any standard regimen. Studies from various sources claimed diverse opinions about its role in AML. Based on the case reports of two children with AML, we have shown how steroids (Prednisolone and Dexamethasone) in a case of AML-M7 with RAM phenotype helped in progression and unmasking the myeloid blasts whilst causing cytoreduction and tumor lysis in another case of non-promyelocytic AML who presented with hyperleucocytosis. We hereby present two such cases with contrasting findings to understand the role of steroids in AML.

Immune thrombocytopenia (ITP) is an autoimmune condition born of platelet destruction and impaired production typically resulting in bleeding symptoms with paradoxical risk of thrombosis. The latter is not yet fully understood. Here, we describe a pediatric patient who developed multiple cerebral sinus venous thromboses (CSVTs) while receiving romiplostim in combination with a steroid requiring simultaneous management of both ITP and significant thromboses.

Preclinical animal research plays a crucial role in studying colorectal cancer (CRC). Mouse models allow for testing the efficacy of potential medications and understanding the mechanisms behind CRC development. Carcinogens like DMH and AOM are used to induce CRC in these models, enabling researchers to investigate various treatment approaches. The availability of diverse animal strains facilitates the study of CRC progression and metastasis. By examining literature on animal models, researchers can assess the accuracy of reproducing different stages of CRC, from crypts to polyps and tumors. Animal models are essential for studying the tumour microenvironment and its impact on colorectal cancer (CRC). These models replicate key features of human CRC, including angiogenesis and immune responses. Both immunocompetent and immunocompromised rodents are used to evaluate immunotherapeutic drugs. This review summarizes common murine models for CRC and their applications in translational research. Future trends in this field likely include further advancements in animal models for studying tumour biology.

Estimates of the percentage of moderate to large crustal earthquakes (mainshocks) that have foreshocks (the foreshock rate) vary widely: recent estimates in Southern California using an enhanced catalog range between 19 and 72%. Enhanced catalogs seem to reveal more foreshocks, possibly providing new constraints on nucleation mechanisms, but precise, commonly-accepted foreshock definitions are lacking. To investigate the observed range we quantify the sensitivity of foreshock rates to mainshock selection method, catalog (standard and enhanced), foreshock definition, geographical restriction and magnitude cut-offs. We compare two foreshock definitions: type A - any earthquakes above a magnitude threshold in a space-time window; and type B - an earthquake count in a space-time window that exceeds the 99th percentile of a statistical representation of past seismicity rates (using three distributions: Poisson, Gamma and Empirical). Foreshock rate estimates are increased by (in order of influence): Poisson distribution, type A definition, fixed mainshock selection, and restricting to mainshocks with minimum background rates or spatial completeness magnitudes. Rates are lowered by: magnitude-dependent mainshock selection, Gamma and Empirical distributions, and applying a magnitude cut-off. A large increase in foreshock rate between the standard and enhanced catalog is only observed when using Poisson distributed background rates for type B foreshocks. A lower magnitude of completeness may thus not lead to significantly more mainshocks with detected foreshocks. Our preferred method, using a more robust mainshock selection and quality-controlled data, estimates ~25% of M4+ “mainshocks” in Southern California have foreshocks.

This case report highlights the prenatal diagnosis of a rare saccular inferior vena cava (IVC) aneurysm. A 25-year-old gravida 4 para 1 patient underwent detailed ultrasonography at 20 weeks of gestation, revealing a 15 x 10 x 14 mm infrarenal IVC aneurysm. Genetic analysis identified a de novo 2p16.3 deletion of uncertain significance. Serial imaging showed progressive aneurysm dilation and mild cardiomegaly. Postnatal CT angiography confirmed the aneurysm, and anticoagulant therapy was initiated. This report underscores the importance of detailed prenatal imaging and genetic evaluation in the identification and management of rare vascular anomalies, contributing to the understanding of their clinical implications.

Livestock morbidity and death from Q-fever have been high, endangering local farmers’ livelihoods and affecting food security in Ghana. It is essential to understand the transmission dynamics of Q-fever to protect both the health of the animals and the main source of income for the community. A non-linear ordinary differential equation incorporating a vaccinated compartment was formulated and analyzed to gain insights into the spread of Q-fever. Routh Hurwitz criterion and Lyapunov function were used respectively to analyze the local and global stability of the disease-free equilibrium ( Q 0 ) . We analyzed the behavior of the model compartments and discovered that many key factors significantly influence the persistence or eradication of Q-fever. Increased vaccination rates decrease the susceptible livestock while increasing the vaccinated livestock, potentially reducing the risk of outbreaks and limiting the spread of infections. A higher recovery rate leads to a quicker recovery, which aids in epidemic control by boosting population immunity and reducing the infectious time. The infection level rises when R 0 > 1 , indicating a typical transcritical bifurcation behavior, but this growth stays steady and does not result in unbounded advancement.

A document by Xuan Wang. Click on the document to view its contents.

This paper presents an analytical approach for designing three component T matching networks by using a direct and generic network impedance analysis. This approach is proposed as an alternative technique to designing such networks using either a graphical approach via an impedance-admittance Smith Chart, back-to-back L section-based T matching network design or the phase-shift-based approach. The proposed approach provides all the possible T matching network configurations and their respective component values with a high accuracy by analytical solving three equations as shown via the implemented algorithm.

ABSTRACT Introduction Extant literature has highlighted the role of the gut microbiome on various health conditions, including mood disorders and neurodegenerative diseases. Notwithstanding, the effects of glucagon-like peptide-1 (GLP-1) and GLP-1 receptor agonists (GLP-1RAs) on the gut microbiome have been inadequately investigated. Changes in the gut microbiome are characterized by changes in microbial abundance, microbial genomes, and microbial diversity. Herein, we conducted a comprehensive synthesis of the role of GLP-1 and GLP-1RAs on the gut microbiome. Methods Relevant articles were retrieved from OVID (MedLine, Embase, AMED, PsycInfo, JBI EBP Database), PubMed, and Web of Science from the database inception to August 19, 2024. Primary research evaluating the role of GLP-1 and GLP-1RAs on the gut microbiome were included for analysis. Results GLP-1 is associated with changes in microbial abundance, including, but not limited to Akkermansia, Sutterella, Bifidobacterium. GLP-1 was not associated with changes in microbial gene count. Additionally, dulaglutide was positively correlated to the relative abundance of Bacteroides. Similarly, liraglutide was associated with varied changes in microbial diversity, community richness. Additionally, liraglutide was associated with varied changes in microbial abundance, including, but not limited to Akkermansia, Sutterella, Bacteroides, Ruminococcus, and Actinomyces. Discussion Both GLP-1 and GLP-1RAs are associated with overlapping and discrete changes in the gut microbiome. Included studies predominantly involved persons with diabetes and were limited by sample sizes. Future research should be directed to examining how GLP-1 and GLP-1RA mediated changes in the gut microbiome may subserve potential therapeutic effects and health conditions in a more diverse population.

Conventional methods for manufacturing rotor blades, such as composite construction and die casting, are hindered by high costs due to expensive molds, while 3D printing often results in poor quality or high production costs with unfavorable cost-per-part scaling. Moreover, conventional airfoil designs perform poorly at Reynolds numbers below 100,000, necessitating larger rotors. This becomes especially problematic in wind tunnel studies, where multiple rotors must fit within a single wind tunnel for wake or multirotor research, significantly increasing both building costs and wind tunnel requirements. To address these challenges, this study develops high-performance rotor blades for micro wind turbines that are aerodynamically efficient under low Reynolds number conditions and easy to manufacture. Using cambered plate airfoils, the optimization process employed a class shape transformation and seventh-degree Bernstein polynomials. Aerodynamic performance was analyzed using XFOIL, with evaluations conducted at Reynolds numbers of 30,000, 40,000, and 50,000 to ensure robust performance across realistic operating scenarios. The iterative optimization employed both single-objective and (genetic) multi-objective algorithms, targeting both aerodynamic efficiency and manufacturability. The blade tested with the optimized MB-LR2-7.5 airfoil exhibited superior performance in wind tunnel tests, closely matching Blade Element Momentum (BEM) simulations. This research highlights the potential of cambered plate airfoils to improve micro wind turbine performance while maintaining ease of manufacturing, with potential applications in UAVs, drone propellers, and HVAC systems. The findings advance the understanding of aerodynamic optimization in low Reynolds number environments, paving the way for more efficient and cost-effective rotor designs.

Subsistence hunting, or “country food,” is essential for Indigenous Peoples who face high food insecurity and is critical for Indigenous Food Sovereignty. For many First Nations of Canada, subsistence hunting is also inextricably linked to traditional conservation practices, as hunting is an important way of engaging with nature. In the boreal of Canada, large game such as moose (Alces alces) are a primary source of protein for many First Nations. However, resource extraction, including forestry practices and oil and gas extraction, has shifted large game distributions and affected the availability and abundance of food resources. Here, we used remote camera trap data and generalized linear models to evaluate moose habitat use and spatial-numerical response to possible stressors in north-central Alberta, including fire, harvest, oil and gas extraction, and other disturbances. We also examined the effects of human-caused stressors on habitat use by sex and age class data. The proportion of various land cover types and human land use for resource extraction were important in moose habitat use. Overall, adult moose avoided burned areas and grasslands. Notably, male, female, and young moose all used habitat differently and at different spatial scales. However, young moose (with their mothers) strongly selected natural forest disturbances such as burned areas but avoided human-created disturbances such as petroleum exploration “seismic” lines. Female moose with young attempting to maximize forage opportunities do not use human-disturbed forests in the same ways they use naturally disturbed areas. This also aligns with observations from Indigenous communities, which have linked human disturbance to declines in moose densities and displacement from traditional hunting grounds. Understanding and predicting shifts in large game distributions is critical to supporting Indigenous Food Sovereignty and identifying where industries operating on First Nations lands can better engage responsibly with First Nations.

This work proposes a transfer learning-based encoder-decoder framework to predict the relationship between loading conditions and residual stiffness in composites and adhesives. The encoder, built from a convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM), extracts time-series loading signals into latent variables and captures their dependencies. The decoder employs a multilayer perceptron (MLP) to map these latent features to residual stiffness. Transfer learning strategy is used to account for individual variability and further improve accuracy. The model’s effectiveness and robustness are validated through random and constant loading fatigue experiments from two different material systems. Under random fatigue data, the model demonstrates strong learning capabilities, achieving a residual stiffness prediction error of less than 0.5 GPa. In constant amplitude fatigue datasets, the model accurately identifies different materials and exhibits satisfactory robustness when reasonable training dataset size is used.

Tissue-resident memory T cells (TRMs) reside in peripheral tissues and provide rapid immune defense against local infection and tumor. Tumor-associated TRMs share common tissue-resident features and formation mechanisms, representing some unique subsets of tumor-infiltrating lymphocytes (TILs). However, differences in the tumor microenvironment (TME) and tumor evolution stage result in TRMs exhibiting temporal and spatial heterogeneity of phenotype and function not only at different stages, before and after treatment, but also between tumors origin from different tissue, primary and metastasis cancer, and tumor and adjacent normal tissue. The infiltration of TRMs is often associated with immunotherapy response and favorable prognosis, however, due to different definition, it has been shown that some subtypes of TRMs can also have a negative impact. Therefore, it is crucial to precisely characterize the TRM subpopulations that can influence the therapeutic efficacy and clinical prognosis of various solid tumors. Here, we review the spatiotemporal heterogeneity of tumor-associated TRMs, as well as the differences of their impact on the clinical outcomes. We also explore the relationship between TRMs and immune checkpoint blockade (ICB) and TIL therapy, providing insights into potential new targets and strategies of immunotherapy.

Background:Simultaneous radiotherapy and chemotherapy are the core treatment for nasopharyngeal carcinoma; however, the damage caused by this treatment can seriously affect immune function and quality of life of patients. These effects may lead to treatment interruption, ultimately impacting treatment effectiveness. Methods: This retrospective study analyzed the role of thymic neoadjuvant immunotherapy in improving the immune function and quality of life in patients with nasopharyngeal carcinoma undergoing concurrent radiotherapy and chemotherapy between January and December 2023. Among 24 patients (14 men and 10 women, median age 53 years), the pathological type was non-keratinizing squamous cell carcinoma, undifferentiated, with staging ranging from T2N1 to T3N0M0 (stage II–III). All patients were administered concurrent radiochemotherapy and were randomly assigned into two groups based on whether thymus neoadjuvant therapy was administered. The experimental group included 12 patients who received thymic neoadjuvant immunotherapy during radiotherapy and chemotherapy until within 3 months of the end of the treatment. The control group comprised 12 patients who did not receive thymic neoadjuvant therapy during treatment. The radiation-induced oral mucositis, CD4+ T cell, CD8+ T cell, neutrophil count/lymphocyte count (NLR), lactate dehydrogenase (LDH), Epstein-Barr virus (EBV) DNA, and quality of life (QOL) of these patients was compared between the adjuvant treatment groups before, during, and 1 and 3 months after treatment. Results: At baseline, sex, age, pathological type, stage, NLR, LDH, EBV DNA, CD4+, CD8+, and quality of life scores did not differ significantly between the two groups before treatment. In the treatment group, during the same period of radiotherapy and chemotherapy, 12 patients with radiation-induced oral mucositis were mainly grade 1-2, and only 2 patients developed grade 3. However, all 12 patients in the control group developed grade 3-4 radiation-induced oral mucositis, which was significantly more severe than that in the treatment group. After 1 and 3 months of treatment, the CD4+ and CD8+ T cell counts were significantly higher in patients in the experimental group than those in the control group. Additionally, the experimental group also showed larger decreases in NLR, LDH, and EBV DNA compared with the control group. Moreover, the recovery of quality of life in the experimental group was significantly better than in the control group (P<0.05). Conclusion: These results demonstrated that thymic neoadjuvant immunotherapy can improve the adverse side effects of concurrent radiotherapy and chemotherapy and enhance immune function and quality of life of patients with nasopharyngeal carcinoma.

Note: Metal alloys or bimetallic nanoparticles have a high superparamagnetic property  , which makes them suitable for  electromagnetic nanomolecules or electromagnetic nanocarriers  . In addition to this, the electromagnetic property  of the surface of these nanoparticles allows surface active substances to  be placed  on the surface of the nanoparticles,  which can be used to dissolve the nanoparticles  .Surface coating is an inseparable component of electromagnetic nanoparticles so that they can be  used. Although nanoparticles  are not attracted to each other due to their super paramagnetic properties,  but due to the high energy of the surfaces, electromagnetic nanoparticles tend to accumulate  . The electrostatic stability of nanomolecules  is not suitable for nanoparticles; Although the repulsion of charges on  the surface of nanoparticles can prevent their accumulation,  but in the presence of a catalyst or other electrolytes in the  internal environment of electromagnetic nanoparticles, these charges are neutralized. 

The proliferation of sophisticated cyber threats necessitates the development of advanced detection mechanisms capable of identifying and mitigating ransomware attacks. The Adaptive Ransomware Detection (ARD) framework employs dynamic behavior profiling and machine learning techniques to enhance detection accuracy and reduce false positive rates. Comprehensive evaluations demonstrate the framework's efficacy in identifying a wide array of ransomware variants, including polymorphic and metamorphic strains, while maintaining efficient resource utilization and scalability across diverse network environments. The ARD framework's adaptability to evolving threat landscapes demonstrates its potential as a robust solution in the cybersecurity domain.

Chloroplast DNA (cpDNA) is a valuable tool for studying plant population genetics and gene flow by pollen in conifers, particularly through the application of chloroplast DNA microsatellite markers (cpSSRs). This study focuses on Chilgoza pine (Pinus gerardiana L.), an economically and ecologically significant tree species in Afghanistan. Despite its importance, comprehensive genetic research on Chilgoza pine has been limited. To address this gap, we developed novel cpSSR markers based on the Chilgoza pine’s chloroplast genome to assess genetic diversity, population structure, and pollen dispersal in a population from Gardiz, Afghanistan. Needle samples from 199 trees across four subpopulations and two age cohorts (young and old) were collected and analyzed. Our findings revealed 27 chloroplast microsatellite markers, of which six exhibited polymorphism. Haplotype analysis identified 32 unique haplotypes, with one most prevalent haplotype. Genetic diversity analysis showed comparatively high levels of diversity, with no genetic differentiation between young and old tree cohorts. Fine-scale spatial genetic structure (FSGS) analysis revealed significant but weak family structure and relatedness in young cohorts, suggesting distance-dependent gene flow. Our study underscores the utility of cpSSRs in characterizing genetic diversity and structure, which is crucial for the conservation and sustainable management of Chilgoza pine forests. These findings provide insights for developing conservation strategies and highlight the importance of genetic marker studies to aid the preservation of biodiversity that supports local livelihoods.