Interference Model Research Articles

Crucial Role of c-Myc/Monocarboxylate Transporter 4 Signaling in Capsaicin Induced Apoptotic and Anti-Warburg Effects in Hepatocellular Carcinoma.

Though Capsaicin from chili peppers was known to have antitumor effects in several cancers, the underlying antitumor pathogenesis of Capsaicin is not clear to date. Thus, the antitumor mechanism of Capsaicin was explored in Hep3B and Huh7 hepatocellular carcinoma (HCC) cells in relation to c-Myc/monocarboxylate transporter 4 (MCT4) signaling. To elucidate the antitumor mechanism of capsaicin, cytotoxicity assay, cell cycle analysis, Western blotting, RT-qPCR, RNA interference, ELISA, immunoprecipitation, and mouse xenograft model were used in this work. Capsaicin increased the cytotoxicity, subG1 population, and the number of TUNEL-positive bodies in Huh7 and Hep3B cells. Consistently, Capsaicin diminished the expression of pro-PARP, HK2, PKM2, LDHA, glucose transporter type 1 (Glut1), c-Myc, and monocarboxylate transporter 4 (MCT4) in Huh7 and Hep3B cells, along with decreased production of glucose, lactate, and ATP. However, a glycolysis end product pyruvate treatment reversed the capacity of Capsaicin to attenuate the expression of pro-PARP, HK2, c-Myc, and MCT4 in Hep3B cells. Furthermore, Capsaicin reduced c-Myc stability in the presence of cycloheximide and induced c-Myc ubiquitination in Hep3B cells, while c-Myc directly binds to MCT4 as a lactate transporter and downstream of c-Myc in Hep3B cells by immunoprecipitation and correlation factor (Spearman efficient = 0.0027). Furthermore, a preliminary analysis of an animal study reveals that Capsaicin significantly suppressed the growth of Hep3B cells inoculated in BALB/c nude mice without hurting body weight, liver, and spleen. Our findings provide novel evidence that Capsaicin exerts apoptotic and anti-Warburg effect via c-Myc/MCT4 signaling axis as a potent anticancer candidate for liver cancer therapy.

Rapid source forgetting across modalities: A problem for working memory models.

Working memory is a cognitive system that enables the temporary retention (usually a few seconds) of a limited amount of information. However, recent evidence has posed challenges to the conventional understanding of working memory's persistence. Chen et al. (Psychological Science, 29(4), 645-655, 2018) demonstrated that participants can easily make judgments using a stimulus's identity but cannot recall from which source the information came (presented either as a written word or a color patch) just milliseconds earlier. This "Source Amnesia" carries substantial implications for working memory models but has yet to be explored within the realm of verbal information. We fill this gap by investigating the robustness and generalizability of this rapid forgetting phenomenon. We first replicate the observed effect within the visual domain (Experiment 1) and subsequently extend it to the verbal domain (Experiment 2). Finally, we test the idea that participants may instead encode a positional context (Experiment 3), in line with the Interference model (Oberauer & Lin, Psychological Review, 124(1), 21, 2017). Aligning with the work of Chen et al. (Psychological Science, 29(4), 645-655,2018), our results consistently reveal a pronounced tendency for rapid forgetting, for both visual and verbal information regardless of whether the information is elicited for recall by format or position cues. The theoretical implications of these findings for current memory models are discussed.

Arginine–NO pathway modulated energy metabolism in the hepatopancreas and muscle of female Litopenaeus vannamei

Currently, the regulational effect of arginine on the energy metabolism is unknown in broodstock shrimp nutrition. Accordingly, an eight-week feeding trial was conducted to confirm it in female Litopenaeus vannamei. Six diets were formulated to contain graded levels of arginine (2.90 %, 3.58 %, 4.08 %, 4.53 %, 5.04 % and 5.55 %). A total of 540 shrimp (with an initial weight of approximately 14 g) were allocated at random to six treatments, each of which consisted of three tanks with 30 shrimp each. The results showed that with the rise in the level of dietary arginine supplementation, growth performance showed an increasing trend, reaching the highest value in the 5.55 % arginine group. The gene expression of cellular energy sensor AMP-activated protein kinase was up-regulated in muscle and hepatopancreas. Dietary arginine supplementation decreased hemolymph glucose content and hepatopancreas crude lipid content, increased muscle crude lipid content, glycogen content in muscle and hepatopancreas. Dietary arginine increased muscle crude protein content, decreased hepatopancreas crude protein content and activated the target of rapamycin 1 pathway. Above results were further confirmed by gene expression. In addition, shrimp were injected with dsGFP and dsNOS for 48 h and successfully constructed the RNA interference model. The findings showed that the levels of nos, cgmp, ampk (a, b, c), genes involved in glucose metabolism, lipid metabolism and amino acid metabolism were inhibited. In the conclusion, arginine supplementation could promote growth performance through modulating energy metabolism. Arginine–NO pathway modulated energy metabolism in hepatopancreas and muscle to promote tissue glycogen synthesis, muscle protein and lipid deposition in female L. vannamei.

Treatment Couch Path Planning for Proton Therapy Systems

In the treatment process of proton radiation therapy, the patient needs to be positioned and immobilized before being moved into the treatment position. In this study, the patient was primarily positioned using the 6R robotic treatment couch as the patient support system (PSS). A simplified three-dimensional model of the treatment room was developed based on the relative motion within the treatment room. The forward and inverse kinematics of the 6R robotic treatment couch were analyzed using an improved Denavit-Hartenberg (D-H) representation. A collision interference model was created based on the actual treatment process. The motion path of the treatment couch was planned and simulated in MATLAB using an improved artificial potential field method for obstacle avoidance. The results indicate that the robotic treatment couch can smoothly navigate around obstacles to reach the target point, satisfying the positioning requirements for proton therapy.

Multiple-Input Multiple-Output Synthetic Aperture Radar Waveform and Filter Design in the Presence of Uncertain Interference Environment

Multiple-input multiple-output synthetic aperture radar (MIMO-SAR) anti-jamming waveform design relies on accurate prior information about the interference. However, it is difficult to obtain accurate prior knowledge about uncertain intermittent sampling repeater jamming (ISRJ), leading to a severe decline in the detection performance of MIMO-SAR systems. Therefore, this article studies the robust joint design problem of MIMO radar transmit waveform and filter against uncertain ISRJ. We characterize two categories of uncertain interference, including sample length uncertainty and sample-time uncertainty, modeled as Gaussian distribution in different range bins. Based on the uncertain interference model, we formulate the maximizing SINR as a figure of merit, which is a non-convex quadratic optimization problem under specific waveform constraints. Based on the alternating direction method of multipliers (ADMM) framework, a novel joint design algorithm of waveform and filter is proposed. In order to improve the convergence performance of ADMM, the difference in convex functions (DC) programming is applied to the ADMM iterations framework to solve the problem of waveform energy inequality constraint. Finally, numerical results demonstrate the effectiveness and robustness of the proposed method, compared to the existing methods that utilize deterministic interference models in the uncertain ISRJ environment. Moreover, the spaceborne SAR real scene imaging simulations are conducted to evaluate the anti-ISRJ performance.

Secondary causal mediation analysis of a pragmatic clinical trial to evaluate the effect of chiropractic care for US active-duty military on biopsychosocial outcomes occurring through effects on low back pain interference and intensity

ObjectiveWe evaluate change in low back pain (LBP) intensity and interference as the mechanism by which chiropractic care affects other biopsychosocial factors in US active-duty military members.DesignWe conducted secondary, exploratory...

High-Frequency Modeling and Analysis of Single-Layer NiZn Ferrite Inductors for EMI Filtering in Power Electronics Applications

In the high-frequency (HF) region, specifically within the 150 kHz to 30 MHz range for conducting electromagnetic interference (EMI) modeling, NiZn inductors exhibit enhanced efficiency due to their low core losses and stable permeability. Consequently, the accurate modeling of NiZn ferrite toroidal inductors is essential, given their widespread applications in the HF domain, with the aim of addressing existing knowledge gaps. Previous inductor models often relied on the perfect electric conductor (PEC) assumption, which simplifies the analysis but does not fully represent the electromagnetic behavior of the cores to which the PEC assumption cannot be applied. This study investigates the actual electromagnetic behavior of NiZn cores, treating them as dielectrics, which diverges from the traditional PEC-based models. Furthermore, this research fully considers the actual geometry of the inductors, proposing a comprehensive and precise analytical model for NiZn ferrite toroidal inductors. The impact of various winding methods on core capacitance is also explored. The paper provides a detailed explanation of the physical significance underlying the proposed model. A comparative analysis of both modeling methods is presented, and the efficacy of the suggested approach is validated through simulations and experimental results in several distinct scenarios.

Anterior cruciate ligament reconstruction in a translational model in sheep using biointegrative mineral fiber reinforced screws

Anterior cruciate ligament reconstruction (ACLR) is one of the more common procedures performed worldwide and perhaps the most widely studied construct in orthopedic literature. Interference screws are reliable and frequently used for ligament reconstruction, providing rigid fixation and facilitates graft incorporation allowing for the physiologic loads of early rehabilitation. The purpose of this study was to determine the bio-integration profile and quality of soft tissue graft when using mineral fiber-reinforced screws in an ACLR interference model. Nine sheep underwent ACLR using harvested autologous tendon graft fixated with 4.75 mm screws made of continuous mineral fibers. Histopathology and imaging evaluation at 28, 52, 104, 132-weeks (W) demonstrated mesenchymal tissue ingrowth into implant wall at 28 W, which increased at 52 W and peaked at 104 W. At 132 W, implants fully replaced by newly remodeled bone. Graft cellularity was evident at 28 W and continued to increase through 132 W as the tendon ossified at sites of bone contact. Pro-healing M2-macrophages and giant cells remained infrequent, with minor increases between 52 W and 104 W, attributed to expected phagocytic response. Pro-inflammatory cells (i.e., M1-macrophages, polymorphonuclears) were absent through the entire study course. In conclusion, bio-integrative screws provide secure soft tissue fixation with replacement by bone demonstrating graft cellularization over time.

Unraveling Key Amino Acid Residues Crucial for PxGSTs1 Conferring Benzoylurea Insecticide Resistance in Plutella xylostella.

The widespread use of benzoylurea insecticides (BUs) has led to significant resistance issues in various agricultural pests. Previous studies have demonstrated that the overexpression of sigma glutathione S-transferase 1 (PxGSTs1) can confer resistance to novaluron in Plutella xylostella; however, the underlying molecular mechanism remains unclear. This study investigates the role of glutathione S-transferase PxGSTs1 in mediating resistance to BUs in P. xylostella. Using a combination of RNA interference and transgenic Drosophila models, we demonstrated that the overexpression of PxGSTs1 significantly contributes to the resistance against BUs. Functional assays revealed that PxGSTs1 binds to these insecticides with varying affinities. Structural analysis through homology modeling and molecular docking identified the importance of hydrogen bonding and pi-pi stacking in resistance mechanisms. Site-directed mutagenesis confirmed the critical role of Ser65 and Tyr97 in these interactions. Our findings provide a molecular basis for the development of novel BUs and inform strategies for managing BU resistance in P. xylostella.

Research on path planning in UAV-assisted emergency communication

The rapid development of UAV communication technology makes it have application potential in wireless systems. However, for the optimization problem of UAV base station providing communication for ground personnel in the disaster area under special natural disasters, traditional deep reinforcement learning is used. Algorithms cannot solve such problems well. This article proposes the AD3QN algorithm combined with the attention mechanism, which can communicate with disaster victims on the ground better and more quickly, providing better information collection for rescue missions and completing the task of communication optimization. In the mission simulation environment, in order to make the environment more realistic, we innovatively designed the ground user distribution model, air-to-ground communication model, and electromagnetic interference model. Finally, the effect of the proposed algorithm is evaluated by comparing different deep reinforcement learning algorithms. The results show that the algorithm we proposed can provide communication services faster and has higher practicability in terms of algorithm.

Numerical Modeling of Hydraulic Fracturing Interference in Multi-Layer Shale Oil Wells

Multi-layer horizontal well development and hydraulic fracturing are key techniques for enhancing production from shale oil reservoirs. During well development, the fracturing performance and well-pad production are affected by depletion-induced stress changes. Previous studies generally focused on the stress and fracturing interference within the horizontal layers, and the infilled multi-layer development was not thoroughly investigated. This study introduces a modeling workflow based on finite element and displacement discontinuity methods that accounts for dynamic porous media flow, geomechanics, and hydraulic fracturing modeling. It quantitatively characterizes the in situ stress alteration in various layers caused by the historical production of parent wells and quantifies the hydraulic fracturing interference in infill wells. In situ stress changes and reorientation and the non-planar propagation of hydraulic fractures were simulated. Thus, the workflow characterizes infill-well fracturing interferences in shale oil reservoirs developed by multi-layer horizontal wells. Non-planar fracturing in infill wells is affected by the parent-well history production, infilling layers, and cluster number. They also affect principal stress reorientations and reversal of the fracturing paths. Interwell interference can be decreased by optimizing the infilling layer, infill-well fracturing timing, and cluster numbers. This study extends the numerical investigation of interwell fracturing interference to multi-layer development.

Request Deadline Split and Interference‐Aware Request Migration in Edge Cloud

ABSTRACTEdge computing extends computing resources from the data center to the edge of the network to better handle latency‐sensitive tasks. However, with the rise of the Internet of Things, edge devices with limited processing capabilities face difficulties in executing requests with fluctuating request peaks. In order to meet the deadline constraints of latency‐sensitive tasks, a feasible solution is to offload some latency‐sensitive tasks to other nearby edge devices. This article studies the problem of request migration in edge computing systems and minimizes the request deadline violation rate based on actual online arrival patterns, performance interference phenomena, and deadline constraints. Since a request contains multiple services and request migration will lead to changes in server resource competition pressure, we split the problem into three sub‐problems, dividing the request deadline to determine the maximum response time of the service, determining the performance of the service under different resource pressures and the request migration strategies. To this end, we propose two deadline splitting methods, a performance interference model under multi‐resource pressure, and two heuristic request migration strategies. Since this article considers online edge scenarios, the number and type of requests are black boxes. We conduct simulation experiments and find that our method has only one‐third the number of request violations of other methods.

Interference length reveals regularity of crossover placement across species

Crossover interference is a phenomenon that affects the number and positioning of crossovers in meiosis and thus affects genetic diversity and chromosome segregation. Yet, the underlying mechanism is not fully understood, partly because quantification is difficult. To overcome this challenge, we introduce the interference length Lint that quantifies changes in crossover patterning due to interference. We show that it faithfully captures known aspects of crossover interference and provides superior statistical power over previous measures such as the interference distance and the gamma shape parameter. We apply our analysis to empirical data and unveil a similar behavior of Lint across species, which hints at a common mechanism. A recently proposed coarsening model generally captures these aspects, providing a unified view of crossover interference. Consequently, Lint facilitates model refinements and general comparisons between alternative models of crossover interference.

Route Planning Method of UAV Patrol Based on High Precision Tower Model

The high-precision positioning technology of industrial Unmanned Aerial Vehicle (UAV) plays a vital role in intelligent trajectory planning in power inspection. First, the information on power facilities is collected and processed to form a planning grid to optimize the flight path and correct the trajectory of UAV. However, the preparatory work is more complex, and the algorithm model which needs more detailed and complex terrain database data is not universal enough. To improve the safety of UAV and the efficiency of path planning, we establish a three-dimensional model of the power tower, calculate the coordinate position of the inspection work according to the information of the high-voltage transmission tower, and then determine the corresponding relationship between the inspection point and the flight trajectory combined with the safe distance. Based on the set of random interference semaphores and model rasterization, the discrete error strategy and Euler method are introduced to improve the performance. In each iteration, the best solution is first updated using the execution strategy. We continue to calculate the spatial coordinates of all reference points and provide the coordinate position distribution for the flight mission. The solution of equipment inspection trajectory optimization is realized by using dynamic obstacle perception. The proposed discrete measurement error self-correction algorithm is deployed on the flight platform to guide UAV inspection tasks according to the point cloud coordinate model of transmission equipment in the power system and to correct the flight route in time. To verify the research results, the Algorithm Artemisinin optimization and Whale Optimization Algorithm test verify that the ability of the proposed algorithm to get rid of local optimization is improved by 8.94% and, 12.42% respectively compared with other optimization algorithms. The convergence accuracy is 12.4% and 7.9% higher than other schemes, and it has a better effect in solving numerical problems. The research results using the embedded system to complete the task deployment and unloading provide a reference for trajectory planning and task design in different application scenarios.

Irisin improves ROS‑induced mitohormesis imbalance in H9c2 cells.

Abnormal mitohormesis is a key pathogenic mechanism that induces a variety of cardiac diseases, including cardiac hypertrophy and heart failure. Irisin as a muscle factor serves a cardioprotective role in response to cellular oxidative stress injury. Rat cardiomyocyte cells (H9c2) were treated with 40 µM exogenous H2O2 to establish an oxidative stress model, followed by addition of 75 nM exogenous irisin for experiments to determine mitochondrial membrane potential, reactive oxygen species, and Mitohormesis‑related factors by attrition cytometry. Subsequently, the expression of mitochondrial membrane potential, reactive oxygen species and Mitohormesis‑related factors were continued to be determined by establishing a peroxisome proliferator‑activated receptor γ coactivator‑1 alpha (PGC‑1α) siRNA interference model and continuing the treatment with the addition of 75 nM irisin 12 h before the end of interference. When H9c2 cells underwent oxidative stress, irisin partially improved mitochondrial membrane potential and reactive oxygen species levels and partially restored mitochondrial energy metabolism by upregulating fusion proteins optic atrophy 1 (OPA1) mitochondrial dynamin‑like GTPase and mitofusin 2 and downregulating fission protein dynamin‑related protein 1. Following interference with PGC‑1α, irisin promoted mitochondrial biosynthesis by increasing the mRNA levels of OPA1 and protein levels of cytochrome c oxidase subunit 4. These results suggested that irisin acted partially independently of the PGC‑1α signaling pathway to regulate mitohormesis imbalance due to oxidative stress and maintain energy metabolism by improving mitochondrial structure.

Analysis of interference fringes in a long-wave infrared full Stokes polarimeter based on rotating waveplates

In the long-wave infrared (LWIR, 8–15 µm) band, the interference effect of polarization elements becomes an issue in polarimetry due to defects in the anti-reflective coatings. The paper describes an analysis and optimization method for the rotating-waveplates-based Stokes polarimeter, to eliminate interference fringes and improve polarization measurement accuracy in LWIR. An interference model was established based on the theory of polarized light and thin-film optics. Different modulation schemes were simulated and analyzed to obtain an optimized Stokes polarimeter, reducing the instrumental polarization to less than 1E-3. Furthermore, experimental validation was conducted by the Accurate Infrared Magnetic Field Measurements of the Sun (AIMS) telescope. The result shows that the instrumental polarization was less than 2E-3, consistent with the simulation.

Broadband nonlinear refraction transients in C-doped GaN based on absorption spectroscopy

Optical nonlinear response and its dynamics of wide-bandgap materials are key to realizing integrated nonlinear photonics and photonic circuit applications. However, those applications are severely limited by the unavailability of both dispersion and dynamics of nonlinear refraction (NLR) via conventional measurements. In this work, the broadband NLR dynamics with extremely high sensitivity (λ/1000) can be obtained from absorption spectroscopy in GaN:C using the refraction-related interference model. Both the absorption and refraction kinetics are found to be significantly modulated by the C-related defects. Especially, we demonstrate that the refractive index change Δn of GaN:C is negative and can be used to realize all-optical switching applications owing to the large NLR and ultrafast switching time. The NLR under different non-equilibrium carrier distributions originates from the capture of electrons by CN+ defect state, while the absorption modulation originates from the excitation of tri-carbon defects. We believe that this work provides a better understanding of the GaN:C nonlinear properties and an effective solution to broadband NLR dynamics of transparent thin films or heterostructure materials.

Deep reinforcement learning-based spectrum resource allocation for the web of healthcare things with massive integrating wearable gadgets

With the development of the future Web of Healthcare Things (WoHT), there will be a trend of densely deploying medical sensors with massive simultaneous online communication requirements. The dense deployment and simultaneous online communication of massive medical sensors will inevitably generate overlapping interference. This will be extremely challenging to support data transmission at the medical-grade quality of service level. To handle the challenge, this paper proposes a hypergraph interference coordination-aided resource allocation based on the Deep Reinforcement Learning (DRL) method. Specifically, we build a novel hypergraph interference model for the considered WoHT by analyzing the impact of the overlapping interference. Due to the high complexity of directly solving the hypergraph interference model, the original resource allocation problem is converted into a sequential decision-making problem through the Markov Decision Process (MDP) modeling method. Then, a policy and value-based resource allocation algorithm is proposed to solve this problem under simultaneous online communication and dense deployment. In addition, to enhance the exploration ability of the optimal allocation strategy for the agent, we propose a resource allocation algorithm with an asynchronous parallel architecture. Simulation results verify that the proposed algorithms can achieve higher network throughput than the existing algorithms in the considered WoHT scenario.

Facile synthesis of Co/rGO, Au/rGO, and CoAu/rGO nanocomposites for precise determination of Arsenic(III) in water systems

Cobalt (Co), gold (Au), and cobalt-gold (CoAu) nanoparticles were deposited on reduced graphene oxide (rGO) by a facile and scalable procedure. The synthesised nanocomposites (Co/rGO, Au/rGO, and CoAu/rGO) were used as electrode materials for detecting trace amounts of arsenic (As(III)) ions in water samples. All three electrodes responded to the presence of As(III) in an acidic medium (different acids of the same concentration, then chosen acid at different concentrations). A detailed optimization of the conditions was continued with the CoAu/rGO electrode which showed the best response in terms of the best defined peak indicating the oxidation of As(0) to As(III) and the highest current. The electrode was tested in a wide range of concentrations (30–1000 µM), where two areas of linearity and limits of detection were obtained (for low- and high- concentrations). Moreover, this electrode showed the ability to detect As(III) ions in the presence of Cu(II), as an interference model as well as a satisfactory electrochemical response, in terms of a clear peak corresponding to the oxidation of As(0) to As(III) in a real sample.

Short-term temperature changes affected the predation ability of Orius similis on Bemisia tabaci nymphs

Abstract Bemisia tabaci (Gennadius), a major pest that can adversely affect economies and agriculture globally, is particularly sensitive to climate change-induced temperature fluctuations, which can intensify its outbreaks. Orius similis Zheng, a primary natural predator of B. tabaci, also experiences temperature-related effects that influence its biocontrol efficacy. Thus, understanding the response of O. similis to temperature changes is pivotal for optimizing its biocontrol potential. Herein, our investigations showed that the functional response of O. similis to both high- and low-instar nymphs of B. tabaci adheres to the type II model at temperatures of 19, 22, 25, 28, and 31 °C. At 28 °C, O. similis exhibits the highest instantaneous attack rate (high-instar: 1.1580, low-instar: 1.2112), and the shortest handling time per prey (high-instar: 0.0218, low-instar: 0.0191). The efficacy of O. similis in controlling B. tabaci nymphs follows the sequence: 28 °C > 25 °C > 31 °C > 22 °C > 19 °C. Additionally, search efficiency inversely correlates with prey density. Simulations using the Hessell–Varley interference model indicate that increased density of O. similis under any temperature condition leads to reduced predation rates. Moreover, O. similis shows a predation preference for low-instar nymphs of B. tabaci, with higher predation level observed at the same temperature. In conclusion, for effective control of B. tabaci in field releases, O. similis should be optimally released at temperatures between 25 and 28 °C to preferably target the egg or early nymph stages of B. tabaci and determining the appropriate number of O. similis is important to minimize interference among individuals and enhance biocontrol efficacy.