Multisensory mechanisms of gait and balance in Parkinson’s disease:an integrative review

Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have on our aging population.Posture and gait control does not happen automatically,as previously believed,but rather requires continuous involvement of central nervous mechanisms.To effectively exert control over the body,the brain must integrate multiple streams of sensory information,including visual,vestibular,and somatosensory signals.The mechanisms which underpin the integration of these multisensory signals are the principal topic of the present work.Existing multisensory integration theories focus on how failure of cognitive processes thought to be involved in multisensory integration leads to falls in older adults.Insufficient emphasis,however,has been placed on specific contributions of individual sensory modalities to multisensory integration processes and cross-modal interactions that occur between the sensory modalities in relation to gait and balance.In the present work,we review the contributions of somatosensory,visual,and vestibular modalities,along with their multisensory intersections to gait and balance in older adults and patients with Parkinson’s disease.We also review evidence of vestibular contributions to multisensory temporal binding windows,previously shown to be highly pertinent to fall risk in older adults.Lastly,we relate multisensory vestibular mechanisms to potential neural substrates,both at the level of neurobiology(concerning positron emission tomography imaging)and at the level of electrophysiology(concerning electroencephalography).We hope that this integrative review,drawing influence across multiple subdisciplines of neuroscience,paves the way for novel research directions and therapeutic neuromodulatory approaches,to improve the lives of older adults and patients with neurodegenerative diseases.

Some Construction Methods of Optimum Chemical Balance Weighing Designs III

Methods of constructing the optimum chemical balance weighing designs from symmetric balanced incomplete block designs are proposed with illustration. As a by-product pairwise efficiency and variance balanced designs are also obtained.

Theoretical study of particle and energy balance equations in locally bounded plasmas

In this study,new particle and energy balance equations have been developed to predict the electron temperature and density in locally bounded plasmas.Classical particle and energy balance equations assume that all plasma within a reactor is completely confined only by the reactor walls.However,in industrial plasma reactors for semiconductor manufacturing,the plasma is partially confined by internal reactor structures.We predict the effect of the open boundary area(A′_(L,eff))and ion escape velocity(u_(i))on electron temperature and density by developing new particle and energy balance equations.Theoretically,we found a low ion escape velocity(u_(i)/u_(B)≈0.2)and high open boundary area(A′_(L,eff)/A_(T,eff)≈0.6)to result in an approximately 38%increase in electron density and an 8%decrease in electron temperature compared to values in a fully bounded reactor.Additionally,we suggest that the velocity of ions passing through the open boundary should exceedω_(pi)λ_(De)under the condition E^(2)_(0)?(Φ/λ_(De))^(2).

On the Use of Monotonicity-Preserving Interpolatory Techniques in Multilevel Schemes for Balance Laws

Cost-effective multilevel techniques for homogeneous hyperbolic conservation laws are very successful in reducing the computational cost associated to high resolution shock capturing numerical schemes.Because they do not involve any special data structure,and do not induce savings in memory requirements,they are easily implemented on existing codes and are recommended for 1D and 2D simulations when intensive testing is required.The multilevel technique can also be applied to balance laws,but in this case,numerical errors may be induced by the technique.We present a series of numerical tests that point out that the use of monotonicity-preserving interpolatory techniques eliminates the numerical errors observed when using the usual 4-point centered Lagrange interpolation,and leads to a more robust multilevel code for balance laws,while maintaining the efficiency rates observed forhyperbolic conservation laws.

Systematic Review:Load Balancing in Cloud Computing by Using Metaheuristic Based Dynamic Algorithms

Cloud Computing has the ability to provide on-demand access to a shared resource pool.It has completely changed the way businesses are managed,implement applications,and provide services.The rise in popularity has led to a significant increase in the user demand for services.However,in cloud environments efficient load balancing is essential to ensure optimal performance and resource utilization.This systematic review targets a detailed description of load balancing techniques including static and dynamic load balancing algorithms.Specifically,metaheuristic-based dynamic load balancing algorithms are identified as the optimal solution in case of increased traffic.In a cloud-based context,this paper describes load balancing measurements,including the benefits and drawbacks associated with the selected load balancing techniques.It also summarizes the algorithms based on implementation,time complexity,adaptability,associated issue(s),and targeted QoS parameters.Additionally,the analysis evaluates the tools and instruments utilized in each investigated study.Moreover,comparative analysis among static,traditional dynamic and metaheuristic algorithms based on response time by using the CloudSim simulation tool is also performed.Finally,the key open problems and potential directions for the state-of-the-art metaheuristic-based approaches are also addressed.

Hybrid model for BOF oxygen blowing time prediction based on oxygen balance mechanism and deep neural network

The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based on oxygen balance mechanism (OBM) and deep neural network (DNN) was established for predicting oxygen blowing time in converter. A three-step method was utilized in the hybrid model. First, the oxygen consumption volume was predicted by the OBM model and DNN model, respectively. Second, a more accurate oxygen consumption volume was obtained by integrating the OBM model and DNN model. Finally, the converter oxygen blowing time was calculated according to the oxygen consumption volume and the oxygen supply intensity of each heat. The proposed hybrid model was verified using the actual data collected from an integrated steel plant in China, and compared with multiple linear regression model, OBM model, and neural network model including extreme learning machine, back propagation neural network, and DNN. The test results indicate that the hybrid model with a network structure of 3 hidden layer layers, 32-16-8 neurons per hidden layer, and 0.1 learning rate has the best prediction accuracy and stronger generalization ability compared with other models. The predicted hit ratio of oxygen consumption volume within the error±300 m^(3)is 96.67%;determination coefficient (R^(2)) and root mean square error (RMSE) are0.6984 and 150.03 m^(3), respectively. The oxygen blow time prediction hit ratio within the error±0.6 min is 89.50%;R2and RMSE are0.9486 and 0.3592 min, respectively. As a result, the proposed model can effectively predict the oxygen consumption volume and oxygen blowing time in the converter.

Unveiling evapotranspiration patterns and energy balance in a subalpine forest of the Qinghai-Tibet Plateau:observations and analysis from an eddy covariance system

Evapotranspiration is an important parameter used to characterize the water cycle of ecosystems.To under-stand the properties of the evapotranspiration and energy balance of a subalpine forest in the southeastern Qinghai-Tibet Plateau,an open-path eddy covariance system was set up to monitor the forest from November 2020 to October 2021 in a core area of the Three Parallel Rivers in the Qing-hai-Tibet Plateau.The results show that the evapotranspira-tion peaked daily,the maximum occurring between 11:00 and 15:00.Environmental factors had significant effects on evapotranspiration,among them,net radiation the greatest(R^(2)=0.487),and relative humidity the least(R^(2)=0.001).The energy flux varied considerably in different seasons and sensible heat flux accounted for the main part of turbulent energy.The energy balance ratio in the dormant season was less than that in the growing season,and there is an energy imbalance at the site on an annual time scale.

Distributed Graph Database Load Balancing Method Based on Deep Reinforcement Learning

This paper focuses on the scheduling problem of workflow tasks that exhibit interdependencies.Unlike indepen-dent batch tasks,workflows typically consist of multiple subtasks with intrinsic correlations and dependencies.It necessitates the distribution of various computational tasks to appropriate computing node resources in accor-dance with task dependencies to ensure the smooth completion of the entire workflow.Workflow scheduling must consider an array of factors,including task dependencies,availability of computational resources,and the schedulability of tasks.Therefore,this paper delves into the distributed graph database workflow task scheduling problem and proposes a workflow scheduling methodology based on deep reinforcement learning(DRL).The method optimizes the maximum completion time(makespan)and response time of workflow tasks,aiming to enhance the responsiveness of workflow tasks while ensuring the minimization of the makespan.The experimental results indicate that the Q-learning Deep Reinforcement Learning(Q-DRL)algorithm markedly diminishes the makespan and refines the average response time within distributed graph database environments.In quantifying makespan,Q-DRL achieves mean reductions of 12.4%and 11.9%over established First-fit and Random scheduling strategies,respectively.Additionally,Q-DRL surpasses the performance of both DRL-Cloud and Improved Deep Q-learning Network(IDQN)algorithms,with improvements standing at 4.4%and 2.6%,respectively.With reference to average response time,the Q-DRL approach exhibits a significantly enhanced performance in the scheduling of workflow tasks,decreasing the average by 2.27%and 4.71%when compared to IDQN and DRL-Cloud,respectively.The Q-DRL algorithm also demonstrates a notable increase in the efficiency of system resource utilization,reducing the average idle rate by 5.02%and 9.30%in comparison to IDQN and DRL-Cloud,respectively.These findings support the assertion that Q-DRL not only upholds a lower average idle rate but also effectively curtails the average response time,thereby substantially improving processing efficiency and optimizing resource utilization within distributed graph database systems.

Transverse momentum balance of dijets in Xe+Xe collisions at the LHC

We present a theoretical study of the medium modifications of the p_(T)balance (x_(J)) of dijets in Xe+Xe collisions at■.The initial production of dijets was carried out using the POWHEG+PYTHIA8 prescription,which matches the next-toleading-order (NLO) QCD matrix elements with the parton shower (PS) effect.The SHELL model described the in-medium evolution of nucleus–nucleus collisions using a transport approach.The theoretical results of the dijet xJin the Xe+Xe collisions exhibit more imbalanced distributions than those in the p+p collisions,consistent with recently reported ATLAS data.By utilizing the Interleaved Flavor Neutralisation,an infrared-and-collinear-safe jet flavor algorithm,to identify the flavor of the reconstructed jets,we classify dijets processes into three categories:gluon–gluon (gg),quark–gluon (qg),and quark–quark (qq),and investigated the respective medium modification patterns and fraction changes of the gg,qg,and qq components of the dijet sample in Xe+Xe collisions.It is shown that the increased fraction of qg component at a small x_(J)contributes to the imbalance of the dijet;in particular,the q_(1)g_(2)(quark-jet-leading) dijets experience more significant asymmetric energy loss than the g_(1)q_(2)(gluon-jet-leading) dijets traversing the QGP.By comparing the■of inclusive,■ dijets in Xe+Xe collisions,we observe■.Moreover,ρ_(Xe),P_(b),the ratios of the nuclear modification factors of dijets in Xe+Xe to those in Pb+Pb,were calculated,which indicates that the yield suppression of dijets in Pb+Pb is more pronounced than that in Xe+Xe owing to the larger radius of the lead nucleus.

Joint position optimization,user association,and resource allocation for load balancing in UAV-assisted wireless networks

Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency.To tackle this problem,we propose an Unmanned Aerial Vehicle(UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its adjacent underloaded cell.To fully exploit its potential,we jointly optimize the UAV position,user association,spectrum allocation,and power allocation to maximize the sum-log-rate of all users in two adjacent cells.To tackle the complicated joint optimization problem,we first design a genetic-based algorithm to optimize the UAV position.Then,we simplify the problem by theoretical analysis and devise a low-complexity algorithm according to the branch-and-bound method,so as to obtain the optimal user association and spectrum allocation schemes.We further propose an iterative power allocation algorithm based on the sequential convex approximation theory.The simulation results indicate that the proposed UAV-assisted wireless network is superior to the terrestrial network in both utility and throughput,and the proposed algorithms can substantially improve the network performance in comparison with the other schemes.

Regulating metal-acid double site balance on mesoporous SiO_(2)-Al_(2)O_(3) composite oxide for supercritical n-decane cracking

The balance between metal and acid sites directly affects the preparation of high-performance cracking catalysts with high heat sink and low coking.Nevertheless,how to control acid-metal sites balance and its relationship with cracking performance are reported scarcely.In this work,a series of Pt/Al_(2)O_(3)-SiO_(2) dual sites catalysts with different metal to acid active sites ratio(C_(M)/C_(SA))were constructed by ethanolassisted impregnation method and the impact on n-decane cracking under supercritical conditions was systematically and deeply investigated.The results showed that the conversion and carbon deposition increased gradually with varied C_(M)/C_(SA)and reached the balance at C_(M)/C_(SA)of 0.13.The proper ratio C_(M)/C_(SA)(0.13)can balance the deep dehydrogenation coking over metal active sites and high heat sink of cracking over acid active sites,the chemical heat sink reaches amazing 1.75 MJ/kg and carbon deposition is only22.03 mg/cm^(2) at 750℃.Meanwhile,the few metal sites at low C_(M)/C_(SA)and the few strong acid sites at high C_(M)/C_(SA)are the main factors limiting the cracking activity.Low C_(M)/C_(SA)limit the activation of C-H bond and deep dehydrogenation of coking precursor,resulting in relative low cracking activity and carbon deposition,while high C_(M)/C_(SA)limit the activation of C-C bond and increase the deep dehydrogenation.In this contribution,design and construction of metal-acid dual sites can not only provide the technical solution for the preparation of high heat sink and low coking cracking catalyst,but also deepen the understanding of the cracking path of hydrocarbon fuel.

Harmonic balance simulation of the influence of component uniformity and reliability on the performance of a Josephson traveling wave parametric amplifier

A Josephson traveling wave parametric amplifier(JTWPA),which is a quantum-limited amplifier with high gain and large bandwidth,is the core device of large-scale measurement and control systems for quantum computing.A typical JTWPA consists of thousands of Josephson junctions connected in series to form a transmission line and hundreds of shunt LC resonators periodically loaded along the line for phase matching.Because the variation of these capacitors and inductors can be detrimental to their high-frequency characteristics,the fabrication of a JTWPA typically necessitates precise processing equipment.To guide the fabrication process and further improve the design for manufacturability,it is necessary to understand how each electronic component affects the amplifier.In this paper,we use the harmonic balance method to conduct a comprehensive study on the impact of nonuniformity and fabrication yield of the electronic components on the performance of a JTWPA.The results provide insightful and scientific guidance for device design and fabrication processes.

Euler’s First-Order Explicit Method–Peridynamic Differential Operator for Solving Population Balance Equations of the Crystallization Process

Using Euler’s first-order explicit(EE)method and the peridynamic differential operator(PDDO)to discretize the time and internal crystal-size derivatives,respectively,the Euler’s first-order explicit method–peridynamic differential operator(EE–PDDO)was obtained for solving the one-dimensional population balance equation in crystallization.Four different conditions during crystallization were studied:size-independent growth,sizedependent growth in a batch process,nucleation and size-independent growth,and nucleation and size-dependent growth in a continuous process.The high accuracy of the EE–PDDO method was confirmed by comparing it with the numerical results obtained using the second-order upwind and HR-van methods.The method is characterized by non-oscillation and high accuracy,especially in the discontinuous and sharp crystal size distribution.The stability of the EE–PDDO method,choice of weight function in the PDDO method,and optimal time step are also discussed.

Fast and Balanced Charge Transport Enabled by Solution-Processed Metal Oxide Layers for Efficient and Stable Inverted Perovskite Solar Cells

Metal oxide charge transport materials are preferable for realizing long-term stable and potentially low-cost perovskite solar cells(PSCs).However,due to some technical difficulties(e.g.,intricate fabrication protocols,high-temperature heating process,incompatible solvents,etc.),it is still challenging to achieve efficient and reliable all-metal-oxide-based devices.Here,we developed efficient inverted PSCs(IPSCs)based on solution-processed nickel oxide(NiO_(x))and tin oxide(SnO_(2))nanoparticles,working as hole and electron transport materials respectively,enabling a fast and balanced charge transfer for photogenerated charge carriers.Through further understanding and optimizing the perovskite/metal oxide interfaces,we have realized an outstanding power conversion efficiency(PCE)of 23.5%(the bandgap of the perovskite is 1.62 eV),which is the highest efficiency among IPSCs based on all-metal-oxide charge transport materials.Thanks to these stable metal oxides and improved interface properties,ambient stability(retaining 95%of initial PCE after 1 month),thermal stability(retaining 80%of initial PCE after 2 weeks)and light stability(retaining 90%of initial PCE after 1000 hours aging)of resultant devices are enhanced significantly.In addition,owing to the low-temperature fabrication procedures of the entire device,we have obtained a PCE of over 21%for flexible IPSCs with enhanced operational stability.

Multi-Objective Optimization of Multi-Product Parallel Disassembly Line Balancing Problem Considering Multi-Skilled Workers Using a Discrete Chemical Reaction Optimization Algorithm

This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle time.Based on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is designed.To enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular individuals.The established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,respectively.Introducing a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.

Multi-Model Approach for Assessing the Influence of Calibration Criteria on the Water Balance in Ouémé Basin

Hydrological models are very useful tools for evaluating water resources, and the hydroclimatic hazards associated with the water cycle. However, their calibration and validation require the use of performance criteria which choice is not straightforward. This paper aims to evaluate the influence of the performance criteria on water balance components and water extremes using two global rainfall-runoff models (HBV and GR4J) over the Ouémé watershed at the Bonou and Savè outlets. Three (3) Efficacy criteria (Nash, coefficient of determination, and KGE) were considered for calibration and validation. The results show that the Nash criterion provides a good assessment of the simulation of the different parts of the hydrograph. KGE is better for simulating peak flows and water balance elements than other efficiency criteria. This study could serve as a basis for the choice of performance criteria in hydrological modelling.

Separate-layer balanced waterflooding development technology for thick and complex carbonate reservoirs in the Middle East

Based on the waterflooding development in carbonate reservoirs in the Middle East,in order to solve the problem of the poor development effects caused by commingled injection and production,taking the thick bioclastic limestone reservoirs of Cretaceous in Iran-Iraq as an example,this paper proposes a balanced waterflooding development technology for thick and complex carbonate reservoirs.This technology includes the fine division of development units by concealed baffles and barriers,the combination of multi well type and multi well pattern,and the construction of balanced water injection and recovery system.Thick carbonate reservoirs in Iran-Iraq are characterized by extremely vertical heterogeneity,development of multi-genesis ultra-high permeability zones,and highly concealed baffles and barriers.Based on the technologies of identification,characterization,and sealing evaluation for concealed baffles and barriers,the balanced waterflooding development technology is proposed,and three types of balanced waterflooding development modes/techniques are formed,namely,conventional stratigraphic framework,fine stratigraphic framework,and deepened stratigraphic framework.Numerical simulations show that this technology is able to realize a fine and efficient waterflooding development to recover,in a balanced manner,the reserves of thick and complex carbonate reservoirs in Iran and Iraq.The proposed technology provides a reference for the development optimization of similar reservoirs.

Jianpi-Huatan-Huoxue-Anshen formula ameliorates gastrointestinal inflammation and microecological imbalance in chemotherapytreated mice transplanted with H22 hepatocellular carcinoma

BACKGROUND Jianpi-Huatan-Huoxue-Anshen formula[Tzu-Chi cancer-antagonizing&lifeprotecting II decoction(TCCL)]is a Chinese medical formula that has been clinically shown to reduce the gastrointestinal side effects of chemotherapy in cancer patients and improve their quality of life.However,its effect and mechanism on the intestinal microecology after chemotherapy are not yet clear.AIM To discover the potential mechanisms of TCCL on gastrointestinal inflammation and microecological imbalance in chemotherapy-treated mice transplanted with hepatocellular carcinoma(HCC).METHODS Ninety-six mice were inoculated subcutaneously with HCC cells.One week later,the mice received a large dose of 5-fluorouracil by intraperitoneal injection to establish a HCC chemotherapy model.Thirty-six mice were randomly selected before administration,and feces,ileal tissue,and ileal contents were collected from each mouse.The remaining mice were randomized into normal saline,continuous chemotherapy,Yangzheng Xiaoji capsulestreated,and three TCCL-treated groups.After treatment,feces,tumors,liver,spleen,thymus,stomach,jejunum,ileum,and colon tissues,and ileal contents were collected.Morphological changes,serum levels of IL-1β,IL-6,IL-8,IL-10,IL-22,TNF-α,and TGF-β,intestinal SIgA,and protein and mRNA expression of ZO-1,NF-κB,Occludin,MUC-2,Claudin-1,and IκB-αin colon tissues were documented.The effect of TCCL on the abundance and diversity of intestinal flora was analyzed using 16S rDNA sequencing.RESULTS TCCL treatment improved thymus and spleen weight,thymus and spleen indexes,and body weight,decreased tumor volumes and tumor tissue cell density,and alleviated injury to gastric,ileal,and colonic mucosal tissues.Among proteins and genes associated with inflammation,IL-10,TGF-β,SIgA,ZO-1,MUC-2,and Occludin were upregulated,whereas NF-κB,IL-1β,IL-6,TNF-α,IL-22,IL-8,and IκB-αwere downregulated.Additionally,TCCL increased the proportions of fecal Actinobacteria,AF12,Adlercreutzia,Clostridium,Coriobacteriaceae,and Paraprevotella in the intermediate stage of treatment,decreased the proportions of Mucipirillum,Odoribacter,RF32,YS2,and Rikenellaceae but increased the proportions of p_Deferribacteres and Lactobacillus at the end of treatment.Studies on ileal mucosal microbiota showed similar findings.Moreover,TCCL improved community richness,evenness,and the diversity of fecal and ileal mucosal flora.CONCLUSION TCCL relieves pathological changes in tumor tissue and chemotherapy-induced gastrointestinal injury,potentially by reducing the release of pro-inflammatory factors to repair the gastrointestinal mucosa,enhancing intestinal barrier function,and maintaining gastrointestinal microecological balance.Hence,TCCL is a very effective adjuvant to chemotherapy.

Risk-Balanced Routing Strategy for Service Function Chains of Cyber-Physical Power System Considering Cross-Space Cascading Failure

Cyber-physical power system(CPPS)has significantly improved the operational efficiency of power systems.However,cross-space cascading failures may occur due to the coupling characteristics,which poses a great threat to the safety and reliability of CPPS,and there is an acute need to reduce the probability of these failures.Towards this end,this paper first proposes a cascading failure index to identify and quantify the importance of different information in the same class of communication services.On this basis,a joint improved risk-balanced service function chain routing strategy(SFC-RS)is proposed,which is modeled as a robust optimization problem and solved by column-and-constraint generation(C-CG)algorithm.Compared with the traditional shortest-path routing algorithm,the superiority of SFC-RS is verified in the IEEE 30-bus system.The results demonstrate that SFC-RS effectively mitigates the risk associated with information transmission in the network,enhances information transmission accessibility,and effectively limits communication disruption from becoming the cause of cross-space cascading failures.

Stochastic Air Traffic Flow Management for Demand and Capacity Balancing Under Capacity Uncertainty

This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.