Search Time Research Articles

A Self-Adaptive Memetic Algorithm for Distributed Job Shop Scheduling Problem

Distributed scheduling has become a common manufacturing mode, and the distributed job scheduling problem (DJSP) has attracted more manufacturers and researchers in the field of operation research. For the distributed scheduling problem, it emphasizes the flexibility of factory assignment and determines the sequence of operation related to each machine in related factories. In this paper, a mixed-integer linear programming model for the DJSP is formulated to be optimized by an SMA. Also in this paper, a self-adaptive memetic algorithm (SMA) is proposed to obtain a near-optimal solution in a limited time for the DJSP. To strengthen the effectiveness of the SMA, an independent encoding is designed with jobs assigned to factories and the sequence of operation. In the proposed algorithm, various local search strategies related to the critical path in the critical factory are designed to enhance the quality of the solution. Moreover, the self-adaptive scheme for solution improvement is formulated to reduce the search time and avoid prematurity effectively. To demonstrate the performance of the proposed algorithm, numerical experiments are carried out on 120 different instances extended from the well-known job shop scheduling benchmarks. The proposed SMA has updated 30 instance records in 120 instances and it has obtained the 91 best records in 120 instances. According to the comparison, an SMA is a more effective algorithm that could update several records of benchmarks.

Efficacy of acupuncture and rehabilitation therapy on brain function activation area and neurological function in ischemic stroke: A systematic review and meta-analysis.

The probability of motor deficits after stroke is relatively high. At the same time many studies have reported that acupuncture and rehabilitation therapy have a significant effect on the treatment of stroke. This systematic review and meta-analysis aimed to evaluate the clinical value of acupuncture and rehabilitation therapy on brain eloquent areas and neurological function in ischemic stroke. Seven databases were electronically searched to screen randomized controlled trials (RCTs) of different intervention methods (acupuncture, rehabilitation) in the treatment of ischemic stroke. The search time is from January 1, 2000 to April 20, 2023, and the search languages are limited to Chinese and English. Two researchers independently screened literature and extracted data. The methodological quality of the studies was assessed using the Cochrane Handbook for Systematic Reviews of Interventions. A total of 17 randomized controlled studies were included, including 699 patients, with a maximum sample size of 144 cases and a minimum sample size of 11 cases. Among them, 3 studies reported the brain function in SM1 area. The effective rate of the experimental group was higher than that of the control group [relative risk (OR) = 3.24, 95%CI: 1.49 to 7.05, P < 0.05]. The FMA score of patients in the experimental group was higher than that in the control group [mean difference (MD) = 4.79, 95% CI: 3.86 to 5.71, P < 0.00001]. The NIHSS score of patients in the experimental group was lower than that in the control group [mean difference (MD) = -4.12, 95% CI: -6.99 to -1.26, P < 0.05].None of studies reported adverse events. Acupuncture rehabilitation for ischemic stroke can activate corresponding brain functional areas and improve neurological deficits. The therapeutic effect of acupuncture rehabilitation treatment is better than that of basic western medicine treatment, and it is more effective in improving neurological deficits. At the same time, clinical research needs to use high-quality randomized double-blind controlled trials with more detailed and larger sample designs, long-term efficacy evaluation and evidence-based research methods.

The effects of an electronic head-mounted display in vision rehabilitation for patients with tunnel vision

PurposeTo investigate the effect of a new head-mounted electronic visual aid-Acesight on improving visual function and daily activities in patients with tunnel vision.Methods57 patients with tunnel vision participated in this study. The visual field (VF), visual acuity (VA), search ability, time of finding people from the side (TFPS), walking ability, and the subjective feelings of patients with and without Acesight were measured.Results15 (36%) patients thought Acesight was “helpful”, 16 (28%) thought it was “a little help”, and 26 (46%) believed that it was “not helpful.” The proportion of people aged < 60 years found Acesight helpful was higher. When wearing Acesight, the average horizontal VF diameter (°) (35.54[8.72]) and vertical VF diameter (°) (26.63[5.38]) were larger than those without visual aids (20.61[9.22], 18.19[6.67]) (P all < 0.001). The average TFPS before and while wearing the Acesight was 1.77s(0.32) and 1.19s(0.29), respectively (t = 14.28, P < 0.001). The average search times, number of collisions, walking speeds when wearing the Acesight were not statistically different from those without visual aids (P all > 0.05).ConclusionMore than half of patients with tunnel vision found the Acesight helpful, and a higher proportion of those aged < 60 years old found it helpful. Acesight can expand the horizontal and vertical VF of patients with tunnel vision and can enable patients to detect objects coming from the side earlier.Trial registrationChiCTR2000028859; Date of registration: 2020/1/5; URL: http://www.chictr.org.cn/showproj.aspx?proj=47129

Enhanced Robot Motion Block of A-Star Algorithm for Robotic Path Planning.

An optimized robot path-planning algorithm is required for various aspects of robot movements in applications. The efficacy of the robot path-planning model is vulnerable to the number of search nodes, path cost, and time complexity. The conventional A-star (A*) algorithm outperforms other grid-based algorithms because of its heuristic approach. However, the performance of the conventional A* algorithm is suboptimal for the time, space, and number of search nodes, depending on the robot motion block (RMB). To address these challenges, this paper proposes an optimal RMB with an adaptive cost function to improve performance. The proposed adaptive cost function keeps track of the goal node and adaptively calculates the movement costs for quickly arriving at the goal node. Incorporating the adaptive cost function with a selected optimal RMB significantly reduces the searches of less impactful and redundant nodes, which improves the performance of the A* algorithm in terms of the number of search nodes and time complexity. To validate the performance and robustness of the proposed model, an extensive experiment was conducted. In the experiment, an open-source dataset featuring various types of grid maps was customized to incorporate the multiple map sizes and sets of source-to-destination nodes. According to the experiments, the proposed method demonstrated a remarkable improvement of 93.98% in the number of search nodes and 98.94% in time complexity compared to the conventional A* algorithm. The proposed model outperforms other state-of-the-art algorithms by keeping the path cost largely comparable. Additionally, an ROS experiment using a robot and lidar sensor data shows the improvement of the proposed method in a simulated laboratory environment.

Efficacy of physical exercise intervention on children with acute lymphoblastic leukemia during treatment and rehabilitation: a systematic review and meta-analysis.

To systematically evaluate the impact of physical exercise intervention on children with acute lymphoblastic leukemia (ALL) during the treatment and rehabilitation consolidation periods. Randomized controlled trials (RCTs) were retrieved from PubMed, Scopus, Web of Science, CNKI, and Cochrane databases, with a search time range from database establishment to September 1, 2023. The quality of the included RCTs was evaluated using the Cochrane risk assessment tool, and a systematic evaluation was conducted using RevMan 5.4. The study has been registered with INPLASY (registration number: 202390100). A total of 12 RCTs including 423 subjects was included. The meta-analysis results showed that long-term exercise intervention can effectively improve the endurance performance (SMD = 1.37, 95% CI 0.45 to 2.29, p = 0.004), functional mobility (MD = - 1.17, 95% CI - 1.85 to - 0.49, p = 0.0008), cancer-related fatigue (CRF) (MD = - 1.25, 95% CI - 1.69 to - 0.80, p < 0.00001), and quality of life (QOL) (MD = 4.93, 95% CI 1.80 to 8.05, p = 0.002) of ALL children during the treatment and rehabilitation consolidation periods. Its promoting effect on the muscle strength (SMD = 0.53, 95% CI - 0.33 to 1.39, p = 0.23) and bone mineral density (BMD) (SMD = 0.48, 95% CI 0.20 to 0.77, p = 0.05) of the subjects was not significant. Further meta-analysis showed that exercise intervention with a duration of less than 1year (SMD = 0.91, 95% CI 0.55 to 1.28, p < 0.00001) rather than more than 1year (SMD = - 0.16, 95% CI - 0.61 to 0.29, p = 0.49) can effectively reduce subject BMD, while in terms of strength, exercise intervention can effectively improve strength during the treatment period (SMD = 0.97, 95% CI 0.40 to 1.54, p = 0.0008) rather than the consolidation period (SMD = - 0.27, 95% CI - 1.08 to 0.53, p = 0.51). Long-term regular exercise can effectively improve the endurance, functional mobility, CRF, and QOL of children with ALL in the rehabilitation and treatment consolidation stages. Their strength and BMD may be influenced by the timing of treatment and the intervention cycle, respectively. Considering the limited number of included literature and the instability of some outcome indicators, it is necessary to design more comprehensive and rigorous high-quality RCTs in the future to test the exercise efficacy of ALL children.

Efficient spiking neural network design via neural architecture search

Spiking neural networks (SNNs) are brain-inspired models that utilize discrete and sparse spikes to transmit information, thus having the property of energy efficiency. Recent advances in learning algorithms have greatly improved SNN performance due to the automation of feature engineering. While the choice of neural architecture plays a significant role in deep learning, the current SNN architectures are mainly designed manually, which is a time-consuming and error-prone process. In this paper, we propose a spiking neural architecture search (NAS) method that can automatically find efficient SNNs. To tackle the challenge of long search time faced by SNNs when utilizing NAS, the proposed NAS encodes candidate architectures in a branchless spiking supernet which significantly reduces the computation requirements in the search process. Considering that real-world tasks prefer efficient networks with optimal accuracy under a limited computational budget, we propose a Synaptic Operation (SynOps)-aware optimization to automatically find the computationally efficient subspace of the supernet. Experimental results show that, in less search time, our proposed NAS can find SNNs with higher accuracy and lower computational cost than state-of-the-art SNNs. We also conduct experiments to validate the search process and the trade-off between accuracy and computational cost.

Enhancing Fixation and Pursuit: Optimizing Field of View and Number of Targets for Selection Performance in Virtual Reality

Gaze interaction in virtual reality (VR) offers promising advantages in speed and hands-free operation. However, selecting a suitable selection mechanism in VR interfaces with different visual encodings remains a challenge. This research compares two visual input techniques and explores specific visual elements, including field of view (FOV), design style, and number of targets, with the goal of alleviating these problems. The pilot study identifies two search stages, and it also demonstrates a significant effect of FOV on search time. In the formal experiment, a gaze-based trigger experiment is employed to examine the selection performance of fixation and smooth pursuit. The results reveal that optimizing FOV and number of targets improves the triggering efficiency. Furthermore, fixation outperforms pursuit in terms of triggering time and accuracy under the same conditions, while cognitive load during triggering process remains relatively similar. These findings are expected to propose design recommendations to enhance fixation and pursuit within VR interfaces.

Three-Dimensional Path Planning Based on Six-Direction Search Scheme.

In order to solve the problem of how to perform path planning for AUVs with multiple obstacles in a 3D underwater environment, this paper proposes a six-direction search scheme based on neural networks. In known environments with stationary obstacles, the obstacle energy is constructed based on a neural network and the path energy is introduced to avoid a too-long path being generated. Based on the weighted total energy of obstacle energy and path energy, a six-direction search scheme is designed here for path planning. To improve the efficiency of the six-direction search algorithm, two optimization methods are employed to reduce the number of iterations and total path search time. The first method involves adjusting the search step length dynamically, which helps to decrease the number of iterations needed for path planning. The second method involves reducing the number of path nodes, which can not only decrease the search time but also avoid premature convergence. By implementing these optimization methods, the performance of the six-direction search algorithm is enhanced in favor of path planning with multiple underwater obstacles reasonably. The simulation results validate the effectiveness and efficiency of the six-direction search scheme.

Medical Student Research Activity in Otolaryngology.

To investigate medical student research productivity by institutions associated with otolaryngology residency programs and identify correlates of productivity. Retrospective review. N/A. A systematic search for articles indexed on PubMed published by 116 programs from January 1, 2016 to February 28, 2021 was conducted. Primary outcomes were number of faculty publications, first-author medical student publications and medical students from each institution. Secondary outcomes included geographic region, number of otolaryngology faculty members, and program rankings. Nationally, the mean number of faculty per institution was 21.7 at the time of search. Over a 5-year period, there was a mean 98.7 total publications and 15.8 medical student first-author publications per institution consisting of a mean of 10.03 distinct medical students. One-way analysis of variance showed no statistically significant difference in medical student productivity (P = .09) or department size (P = .12) between regions. Number of medical student first-author publications positively correlated to number of faculty (R = .43, P < .05) and number of faculty publications (R = .63, P < .05). The top 30 programs ranked by United States News & World Report or National Institute of Health for funding had a statistically significantly greater mean number of medical student first-author publications and distinct medical student first authors than all other programs (P < .05). Greater numbers of faculty members likely provide more mentorship and opportunities that allow medical students to engage in projects that lead to first-author publications. These findings allow institutions to reflect on efforts in medical student engagement and provide data to students for career planning.

Experiences of financial toxicity among caregivers of cancer patients: a meta-synthesis of qualitative studies.

The purpose of this study was to explore the experience of financial toxicity among caregivers of cancer patients and to provide recommendations for subsequent intervention strategies. Computer searches of PubMed, EmBase, The Cochrane Library, Web of Science, CINAHL (EBSCO), CNKI, Wanfang database, and SinoMed for qualitative studies experience of financial toxicity among caregivers cancer patients. The search time frame was from the establishment of the database to May 2023. The quality of included studies was assessed using the Qualitative Research Checklist from the Joanna Briggs Institute (JBI) Reviewer's Manual. The meta-synthesis was integrated following the meta-aggregation method proposed by the Joanna Briggs Institute (JBI) and reported following the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) guidelines. A total of nine studies were included, distilling 25 qualitative findings into nine new categories and synthesizing three synthesized findings: caregivers have strong negative experiences that affect their family relationships, daily work and life; caregivers use different strategies to cope with financial toxicity; needs and expectations of caregivers coping with financial toxicity. Financial toxicity among caregivers of cancer patients affects their daily lives. Receiving timely recognition of this financial burden and providing assistance to enhance their coping skills are crucial in mitigating its impact. Healthcare professionals should focus on the financial toxicity experienced by caregivers of people with cancer, address their supportive needs, and develop a comprehensive support system to improve caregivers' coping abilities and quality of life.

Visual search patterns during exploration of naturalistic scenes are driven by saliency cues in individuals with cerebral visual impairment

We investigated the relative influence of image salience and image semantics during the visual search of naturalistic scenes, comparing performance in individuals with cerebral visual impairment (CVI) and controls with neurotypical development. Participants searched for a prompted target presented as either an image or text cue. Success rate and reaction time were collected, and gaze behavior was recorded with an eye tracker. A receiver operating characteristic (ROC) analysis compared the distribution of individual gaze landings based on predictions of image salience (using Graph-Based Visual Saliency) and image semantics (using Global Vectors for Word Representations combined with Linguistic Analysis of Semantic Salience) models. CVI participants were less likely and were slower in finding the target. Their visual search behavior was also associated with a larger visual search area and greater number of fixations. ROC scores were also lower in CVI compared to controls for both model predictions. Furthermore, search strategies in the CVI group were not affected by cue type, although search times and accuracy showed a significant correlation with verbal IQ scores for text-cued searches. These results suggest that visual search patterns in CVI are driven mainly by image salience and provide further characterization of higher-order processing deficits observed in this population.

WeStore or AppStore: How Customers Shop Differently in Mobile Apps vs. Social Commerce

In the dynamic e-commerce environment, social commerce has emerged as a revolutionary force, transforming how consumers interact and transact online. This paper investigates the differences in customers’ search and purchase patterns between a prominent online retailer’s burgeoning social commerce channel, the WeChat mini-program, and its native mobile app. We analyze the customers’ entire journey through a sequential search model that encapsulates decisions from channel selection to product search, search termination, and the final purchase. This study contributes to the search model literature by being the first to estimate both fixed and marginal search costs in a sequential search model in an omnichannel retail environment. We calculate fixed search costs, marginal search costs, and preferences for each channel, revealing differences in customers’ behaviors across channels. Our analysis shows that customers’ fixed search costs are higher, but marginal costs are lower on WeChat channel compared to the App channel. Also, customer characteristics like historical spending levels and search timing influence their search costs. From these insights, we suggest strategies tailored to each channel capitalizing on the differences in customers’ search costs. The first strategy encourages search initiation by lowering fixed search costs through peer-to-peer link sharing in the WeChat channel. The second strategy aims to minimize marginal search costs using search-triggering coupons in the App channel. Implementing these strategies significantly boosts conversion rates and profits for the online retailer. This research is one of the first to explore the differences between traditional retail channels and emerging social commerce channels.

Efficacy and safety of eszopiclone combined with drug therapy in the treatment of insomnia after stroke: A network meta-analysis and systematic review.

To evaluate the efficacy and safety of multi-drug therapy based on eszopiclone in the treatment of insomnia after stroke using a network meta-analysis method and to provide evidence for clinical practice. Computer searches of PubMed, Excerpt Medica Database (Embase), Cochrane Library Central Register of Controlled Trials, APA PsycInfo, CNKI, WanFang, Sinomed and other databases were performed to search for clinical randomized controlled studies (RCTs) on multi-drug therapy based on eszopiclone in the treatment of insomnia patients after stroke. The search time was from the establishment of each database until July 2023. The bias risk assessment tool recommended by Cochrane was used to evaluate the quality of the included RCTs. Stata 14.0 was applied to perform network meta-analysis using Review Manager 5.3 software for traditional meta-analysis. Eighteen RCTs and 1646 patients were ultimately included, involving 11 treatment options. The results of the network meta-analysis showed that the ranking of Pittsburgh Sleep Quality Index (PSQI) decline was eszopiclone combined with sweet dream oral liquid (ESZ+SDOL)>eszopiclone combined with a shugan jieyu capsule (ESZ+SGJYC)>eszopiclone combined with agomelatine (ESZ+AGO)>eszopiclone combined with flupentixol and melitracen tablets (ESZ+FMT)>eszopiclone combined with yangxue qingnao granules (ESZ+YXQNG)>eszopiclone combined with mirtazapine (ESZ+MIR)>ESZ>FMT; the modified Edinburgh Scandinavia Stroke Scale (MESSS) decline ranking was ESZ+SDOL>ESZ+AGO>ESZ; and the clinical total effective rate ranking was eszopiclone combined with a xuefu zhuyu capsule (ESZ+XFZYC)>ESZ+MIR>ESZ+SGJYC>ESZ+SDOL> ESZ+FMT>ESZ+YXQNG>ESZ>FMT. In terms of clinical adverse reactions, in addition to ESZ therapy, ESZ+ESC had the highest number of adverse reactions, with abdominal pain being the most common. ESZ+YXQNG had the most types of adverse reactions, with 8 types. Multi-drug therapy based on eszopiclone can effectively improve the sleep quality of patients with insomnia after stroke, and ESZ+SDOL has significant efficacy and safety. However, due to the limitations of this study, efficacy ranking cannot fully explain the superiority or inferiority of clinical efficacy. In the future, more multicentre, large sample, double-blind randomized controlled trials are needed to supplement and demonstrate the results of this study.

Path planning of water surface garbage cleaning robot based on improved immune particle swarm algorithm

In order to effectively improve the efficiency of surface garbage cleaning robot, an intelligent control algorithm was applied to plan the robot path. To do so, an improved immune particle swarm algorithm was developed based on the robot model. This algorithm introduced the adaptive information dynamic adjustment strategy to dynamically adjust the main link indices, which improved the global searchability and convergence of particles and facilitated the quick identification of the optimal path by the robot. Through comparative simulation experiments with the particle swarm optimization algorithm, genetic algorithm, and immune particle swarm optimization algorithm, it was found that the robot based on the Adaptive Immune Particle Swarm Optimization (AIPSO) algorithm had the shortest planning path and search time, the lowest energy consumption, and the highest efficiency. A robot prototype platform was built. Compared to other algorithms, the efficiency of the robot space search based on the AIPSO algorithm was the highest, the search time was the shortest, and the energy consumption was also the lowest. Especially in the complex level 4 wave water environment, the AIPSO algorithm had the best adaptability and robustness, and the robot had the highest working efficiency and comprehensive performance. The experimental results revealed that the AIPSO algorithm effectively improved the path search and garbage cleaning efficiency of the robots and reduced the working time, which further verified the reliability and accuracy of the designed algorithm.

Haptic search asymmetry does not occur due to different-shaped tactile symbols on capsule paper.

Previous research on haptic search using sandpaper with different roughness levels as a target and distractors showed that rough sandpaper among fine "pops out" and can be searched for in a shorter time than when the roles of the target and distractors are reversed. However, it is not clear whether the same search asymmetry occurs with differences in the shapes of tactile symbols on capsule paper. To explore this possibility, we conducted a haptic search experiment using circles with or without a dot on capsule paper as a target and distractors, which are often used as point symbols in tactile maps for the blind. Contrary to our expectations, haptic search asymmetry did not occur between these two tactile symbols. Regardless of target type, the search times increased in proportion to the number of items (distractors plus target), as participants tended to adopt serial search strategy in which they placed their index or middle finger on the tactile symbol to distinguish it every time they found a new one. The ratio of the search times for target-absent to target-present trials is precise alignment with the occurrence rate of repetitive search trials.

Integration of Deep Reinforcement Learning with Collaborative Filtering for Movie Recommendation Systems

In the era of big data, effective recommendation systems are essential for providing users with personalized content and reducing search time on online platforms. Traditional collaborative filtering (CF) methods face challenges like data sparsity and the new-user or cold-start issue, primarily due to their reliance on limited user–item interactions. This paper proposes an innovative movie recommendation system that integrates deep reinforcement learning (DRL) with CF, employing the actor–critic method and the Deep Deterministic Policy Gradient (DDPG) algorithm. This integration enhances the system’s ability to navigate the recommendation space effectively, especially for new users with less interaction data. The system utilizes DRL for making initial recommendations to new users and to generate optimal recommendation as more data becomes available. Additionally, singular value decomposition (SVD) is used for matrix factorization in CF, improving the extraction of detailed embeddings that capture the latent features of users and movies. This approach significantly increases recommendation precision and personalization. Our model’s performance is evaluated using the MovieLens dataset with metrics like Precision, Recall, and F1 Score and demonstrates its effectiveness compared with existing recommendation benchmarks, particularly in addressing sparsity and new-user challenges. Several benchmarks of existing recommendation models are selected for the purpose of model comparison.

Shake it or light it! The effects of cueing in desktop‐VR learning environments on search time and learning

AbstractBackgroundVirtual reality (VR) offers much potential for learning, but it challenges learners' orientation.ObjectivesThis paper investigates whether it is possible to use light or movement cues to facilitate orientation in a search task in a desktop‐VR environment so that participants can better attend to the learning content presented simultaneously.MethodsIn two pre‐registered online experiments, we investigated the effects of cueing (light and movement) on search time, learning, and several evaluation variables. Participants were asked to find tools in a virtual workshop, while information about the respective tool was narrated. Experiment 1 (N = 60) used a within‐subject design, that is, the objects were alternately highlighted by light, movement or not. For Experiment 2 (N = 159) the narration was substantially shortened, and a between‐subject design was used. Cognitive load and presence were measured additionally.Results and conclusionsIn Experiment 1, only the movement cue decreased search time, indicating automatic guidance of learners' attention. There was no effect of cueing on learning, which may be due to the average search time being substantially shorter than the narration, leaving sufficient time to attend to the narration exclusively. In Experiment 2 search times were significantly faster for both cueing methods, but only the light cue resulted in better learning outcomes, which could be explained by the slightly lower presence in the movement cue condition.ImplicationsResults imply that it is important to develop cues that automatically guide attention without reducing presence.

Acupoint herbal patching for postherpetic neuralgia: A systematic review and meta-analysis.

This study aimed to systematically evaluate the clinical effectiveness and safety of acupoint herbal patching in the treatment of postherpetic neuralgia. Eight databases including PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wan-Fang Database, China Biomedical Literature Service System, and Chongqing VIP Chinese Science were searched. The search time was set to October 2023. Two researchers independently screened the literature according to the inclusion and exclusion criteria; extracted the basic information, acupoints, Chinese herbal medicine, pain score, sleep score, depression score, and other information of the subjects, and independently assessed the risk of bias by 2 researchers. Meta-analysis of the included studies was performed using the StataMP 16 software. Fifteen studies with 1362 participants were included in this meta-analysis. Ashi is the acupoint frequency at the forefront, and Borneol is the Chinese herbal medicine frequency at the forefront. The acupoint herbal patching group showed significant improvements in visual analog score (SMD: -2.09; 95% Cl: -2.77, -1.42; P < .001), sleep score (SMD: -1.58; 95% Cl: -2.11, -1.05; P < .001), depression score (SMD: -1.61; 95% Cl: -2.22, -0.99; P < .001), Chinese medicine syndrome score (SMD: -2.32; 95% Cl: -2.84, -1.80; P = .06), dermatology life quality index (weighted mean differences: -4.11; 95% Cl: -4.58, -3.63; P = .98), and related laboratory indicators compared to the control group, and the total effective rate was significantly higher (relative risk: 1.20; 95% confidence interval: 1.15, 1.26; P = .99) than the control group. Two studies reported adverse reactions, but the 2 groups were not statistically significant. Acupoint herbal patching intervention in postherpetic neuralgia is effective in improving the pain, sleep, anxiety, depression, quality of life of patients, and related laboratory indicators.

Symptom effects and central mechanism of acupuncture in patients with functional gastrointestinal disorders: a systematic review based on fMRI studies

BackgroundFunctional gastrointestinal disorders (FGIDs) are closely related to disorders of brain-gut interaction. FGIDs are the dominant disease of acupuncture treatment, which can improve the symptoms and emotional state.AimTo evaluate the results and quality of the available clinical evidence and to summarize the central mechanism and effect of acupuncture on FGIDs.MethodsPubMed, EMBASE, Web of science, Cochrane Library, China National Knowledge Infrastructure (CNKI) were searched by computer to collect the randomized controlled trials (RCTs), which contained central mechanisms via fMRI research of acupuncture in the treatment of FGIDs patients. The search time limit was from the establishment of the database to June 22, 2022. Two researchers independently screened the literature, extracted data, and evaluated the quality.ResultsTen RCTs involving fMRI data were included in this study, including 4 Functional dyspepsia (FD) studies, 3 irritable bowel syndrome (IBS) studies, and 3 functional constipation (FC) studies. The score of improvements in both gastrointestinal symptoms and psychological symptoms showed that acupuncture could significantly improve the clinical symptoms of FGIDs patients, including abdominal pain, abdominal distension, frequency of defecation, and stool characteristics, and could relieve anxiety and depression symptoms of patients. Acupuncture could regulate brain functional connections and functional activity in FGIDs patients, mainly including insula, anterior cingulate cortex, prefrontal cortex, thalamus, hippocampus, amygdala and other brain regions.ConclusionAcupuncture can improve gastrointestinal symptoms and psychological status in FGIDs patients, and regulate functional connectivity and activity of brain regions such as insula, ACC, PFC, thalamus, HIPP, amygdala, etc. These changes in brain activity may related to visceral sensation, pain regulation, emotion, but further studies of high quality are still necessary.

Random search processes on complex networks: From a static target to a moving object

We investigate the transition behavior of search time from visiting a static target to hunting a moving one on complex networks. This is achieved by introducing a relative moving speed ratio that quantifies how the time scale of a searcher differs from that of a mobile target. We adopt mean first encounter time to quantify the search time required to capture a time-moving target and derive its analytical expression. Remarkably, we find that with the increase of their relative speed ratio, the expected search time increases gradually and finally approaches that of visiting a static target. This interesting transition behavior keeps invariant even changing the associated navigation strategies of the searcher and the moving object. These findings are confirmed by numerical results on various synthetic and real networks. Our work, for the first time, reveals the increasing pattern of search time from a static target to a moving one on networks.