α-Synuclein pathology from the body to the brain:so many seeds so close to the central soil

α-Synuclein is a protein that mainly exists in the presynaptic terminals.Abnormal folding and accumulation of α-synuclein are found in several neurodegenerative diseases,including Parkinson’s disease.Aggregated and highly phospho rylated a-synuclein constitutes the main component of Lewy bodies in the brain,the pathological hallmark of Parkinson s disease.For decades,much attention has been focused on the accumulation of α-synuclein in the brain parenchyma rather than considering Parkinson s disease as a systemic disease.Recent evidence demonstrates that,at least in some patients,the initial α-synuclein pathology originates in the peripheral organs and spreads to the brain.Injection of α-synuclein preformed fibrils into the gastrointestinal tra ct trigge rs the gutto-brain propagation of α-synuclein pathology.However,whether α-synuclein pathology can occur spontaneously in peripheral organs independent of exogenous α-synuclein preformed fibrils or pathological α-synuclein leakage from the central nervous system remains under investigation.In this review,we aimed to summarize the role of peripheral α-synuclein pathology in the pathogenesis of Parkinson’s disease.We also discuss the pathways by which α-synuclein pathology spreads from the body to the brain.

Design of a Heuristic Topology Generation Algorithm in Multi-Domain Optical Networks

Designing an excellent original topology not only improves the accuracy of routing, but also improves the restoring rate of failure. In this paper, we propose a new heuristic topology generation algorithm—GA-PODCC (Genetic Algorithm based on the Pareoto Optimality of Delay, Configuration and Consumption), which utilizes a genetic algorithm to optimize the link delay and resource configuration/consumption. The novelty lies in designing the two stages of genetic operation: The first stage is to pick the best population by means of the crossover, mutation, and selection operation;The second stage is to select an excellent individual from the best population. The simulation results show that, using the same number of nodes, GA-PODCC algorithm improves the balance of all the three optimization objectives, maintaining a low level of distortion in topology aggregation.

Mesh generation and optimization from digital rock fractures based on neural style transfer

The complex geometric features of subsurface fractures at different scales makes mesh generation challenging and/or expensive.In this paper,we make use of neural style transfer(NST),a machine learning technique,to generate mesh from rock fracture images.In this new approach,we use digital rock fractures at multiple scales that represent’content’and define uniformly shaped and sized triangles to represent’style’.The 19-layer convolutional neural network(CNN)learns the content from the rock image,including lower-level features(such as edges and corners)and higher-level features(such as rock,fractures,or other mineral fillings),and learns the style from the triangular grids.By optimizing the cost function to achieve approximation to represent both the content and the style,numerical meshes can be generated and optimized.We utilize the NST to generate meshes for rough fractures with asperities formed in rock,a network of fractures embedded in rock,and a sand aggregate with multiple grains.Based on the examples,we show that this new NST technique can make mesh generation and optimization much more efficient by achieving a good balance between the density of the mesh and the presentation of the geometric features.Finally,we discuss future applications of this approach and perspectives of applying machine learning to bridge the gaps between numerical modeling and experiments.

SAC-TA: A Secure Area Based Clustering for Data Aggregation Using Traffic Analysis in WSN

Clustering is the most significant task characterized in Wireless Sensor Networks (WSN) by data aggregation through each Cluster Head (CH). This leads to the reduction in the traffic cost. Due to the deployment of the WSN in the remote and hostile environments for the transmission of the sensitive information, the sensor nodes are more prone to the false data injection attacks. To overcome these existing issues and enhance the network security, this paper proposes a Secure Area based Clustering approach for data aggregation using Traffic Analysis (SAC-TA) in WSN. Here, the sensor network is clustered into small clusters, such that each cluster has a CH to manage and gather the information from the normal sensor nodes. The CH is selected based on the predefined time slot, cluster center, and highest residual energy. The gathered data are validated based on the traffic analysis and One-time Key Generation procedures to identify the malicious nodes on the route. It helps to provide a secure data gathering process with improved energy efficiency. The performance of the proposed approach is compared with the existing Secure Data Aggregation Technique (SDAT). The proposed SAC-TA yields lower average energy consumption rate, lower end-to-end delay, higher average residual energy, higher data aggregation accuracy and false data detection rate than the existing technique.

Re-Use of Hospital Plastic Waste in Asphalt Mixes as Partial Replacement of Coarse Aggregate

About 1.3 billion tons of waste is being generated in the world annually. This waste is a cause of various diseases. Open dumping of waste also destroys valuable agricultural land. Various researchers have beneficially used plastic waste in cement concrete and asphalt concrete in the past. This study aims at the use of aggregates, made from different types of plastic waste, as partial replacement of coarse aggregates in asphalt mixes. For this purpose waste is collected from different hospitals of the city. Sorted plastic from the waste consists of 64% low density polyethene, 32% high density polyethene and 4% of polypropylene. Plastic waste is shredded, heated and after cooling, pulverizes manually and mechanically. Specific gravity of plastic aggregates is 0.96. Water absorption and soundness values are 4.68% and 7.68% respectively. Impact, crushing and Loss Angeles values of plastic aggregates are 0.7%, 0.5%, and 1.1% respectively. Replacement of natural aggregates by plastic aggregates in asphalt mixes is done up to 25% with 5% incremental increase. Density of asphalt mixes decreases to 2060 kg/m3. Consequently flow increases to 5.73 mm. Maximum stability is at 20% replacement i.e. 34.57 KN. Cost analysis of the study indicates that 205% increase in stability are observed with 219% increase in cost.

Distributed generation planning for diversified participants in demand response to promote renewable energy integration

In modern distribution system,the distribution system operator(DSO)acts as a market facilitator and data manager as well as an energy supplier and operation controller.In this circumstance,the DSO should comprehensively consider the diversified participants of the modern distribution system when making investment decisions of distributed generation(DG).This paper proposes a DG planning model considering the behavior of the diversified participants,which are motivated to cooperate with distributed renewable energy resources to promote their integration,and to achieve the optimal DG investment plan.The optimization model takes a centralized structure but fully considers the preferences,profits and comfort levels of the aggregators and consumers.The model is linearized into a mixed-integer linear programming(MILP)problem and is solved by CPLEX.Results of the case study show that when the DSO spares subsidies to the aggregators and consumers to encourage their participation in demand response(DR)programs,it earns more compared with providing no subsidies for DR participation.It is also demonstrated that the overall profit increases as the subsidies increase within a certain range,but decreases when the subsidies exceed this range.Therefore,the DSO needs to carefully choose the subsidization level to achieve the optimal utilization of renewable energy and demand flexibility.The optimal subsidization level is derived from the model proposed in this paper.Therefore,this paper puts forward a new pattern to utilize the distributed renewable energy sources,and provides guidance in policy making and DR program implementation.

Integration of Utility Distributed Energy Resource Management System and Aggregators for Evolving Distribution System Operators

With the rapid integration of distributed energy resources(DERs),distribution utilities are faced with new and unprecedented issues.New challenges introduced by high penetra-tion of DERs range from poor observability to overload and reverse power flow problems,under-/over-voltages,maloperation of legacy protection systems,and requirements for new planning procedures.Distribution utility personnel are not adequately trained,and legacy control centers are not properly equipped to cope with these issues.Fortunately,distribution energy resource management systems(DERMSs)are emerging software technologies aimed to provide distribution system operators(DSOs)with a specialized set of tools to enable them to overcome the issues caused by DERs and to maximize the benefits of the presence of high penetration of these novel resources.However,as DERMS technology is still emerging,its definition is vague and can refer to very different levels of software hierarchies,spanning from decentralized virtual power plants to DER aggregators and fully centralized enterprise systems(called utility DERMS).Although they are all frequently simply called DERIMS,these software technologies have different sets of tools and aim to provide different services to different stakeholders.This paper explores how these different software technologies can complement each other,and how they can provide significant benefits to DSOs in enabling them to successfully manage evolving distribution networks with high penetration of DERs when they are integrated together into the control centers of distribution utilities.

Structure and principles of self-assembly of giant“sea urchin”type sulfonatophenyl porphine aggregates

Principles of molecular self-assembly into giant hierarchical structures of hundreds of micrometers in size are studied in aggregates of meso-tetra(4-sulfonatophenyl)porphine(TPPS_(4)).The aggregates form a central tubular core,which is covered with radially protruding filamentous non-branching aggregates.The filaments cluster and orient at varying angles from the core surface and some filaments form bundles.Due to shape resemblance,the structures are termed giant sea urchin(GSU)aggregates.Spectrally resolved fluorescence microscopy reveals J-and H-bands of TPPS_(4)aggregates in both the central core and the filaments.The fluorescence of the core is quenched while filaments exhibit strong fluorescence.Upon drying,the filament fluorescence gets quenched while the core is less affected,showing stronger relative fluorescence.Fluorescencedetected linear dichroism(FDLD)microscopy reveals that absorption dipoles corresponding to J-bands are oriented along the filament axis.The comparison of FDLD with scanning electron microscopy(SEM)reveals the structure of central core comprised of multilayer ribbons,which wind around the core axis forming a tube.Polarimetric second-harmonic generation(SHG)and thirdharmonic generation microscopy exhibits strong signal from the filaments with nonlinear dipoles oriented close to the filament axis,while central core displays very low SHG due to close to centrosymmetric organization.Large chiral nonlinear susceptibility points to helical arrangement of the filaments.The investigation shows that TPPS_(4)molecules form distinct aggregate types,including chiral nanotubes and nanogranular aggregates that associate into the hierarchical GSU structure,prototypical to complex biological structures.The chiral TPPS_(4)aggregates can serve as harmonophores for nonlinear microscopy.

Spectroscopic Detection of Chiral Aggregation at Liquid-Liquid Interfaces

Two new spectroscopic methods to detect the optical activity of liquid-liquid interfaces have been developed. The first one is the centrifugal liquid membrane （CLM） method combined with a conventional circular dichroism （CD） spectropolarimetry and the second one is a more interfacial specific second harmonic generation CD （SHG-CD） spectrometry. In the CLM-CD method, a cylindrical glass cell containing small amounts of organic and aqueous phases was rotated at about 7000 r/min in a sample chamber of a CD spectropolarimeter to generate an interface with a high specific interfacial area between the two-phase liquid membranes. The CD spectra of the J-aggregate of protonated 5,10,15, 20-tetraphenylporphyrin formed at the toluene-sulfuric acid interface have been measured, As for the SHG-CD, a circularly polarized wavelength-variable fs-laser system was constructed to measure the interfacial SHG spectra of a flat liquid-liquid interface. The ion-associated aggregation of a water-soluble anionic porphyrin promoted with a cationic amphiphile at the heptane-water interface was observed by this technique and the observed SHG-CD spectra proved the generation of a characteristic oPtical activity accompanied by the formation of the interfacial aggregate of inherently achiral porphyrin molecules. These methods will pioneer a new field of interfacial chiral chemistry in the studies of solvent extraction mechanisms.

THE COMPACTION OF TIME-DEPENDENT VISCOUS GRANULAR MATERIALS CONSIDERING INERTIAL FORCES

In the present paper, compactions of time-dependent viscous granular materials are simulated step by step using the automatic adaptive mesh generation schemes. Inertial forces of the viscous incompressible aggregates axe taken into account. The corresponding conservation equations, the weighted-integral formulations, and penalty finite element model are investigated. The fully discrete finite element equations for the simulation are derived. Polygonal particles of aggregates are simplified as mixed three-node and four-node elements. The automatic adaptive mesh generation schemes include contact detection algorithms, and mesh upgrade schemes. Solu- tions of the numerical simulation axe in good agreement with some results from literatures. With minor modification, the proposed numerical model can be applied in several industries, including the pharmaceutical, ceramic, food, and household product manufacturing.

Local Energy and Planned Ramping Product Joint Market Based on a Distributed Optimization Method

High penetration of renewable energy generation(REG)in the distribution system increases both the power uncertainty at a given interval and the power variation between two intervals.Reserve markets addressing power uncertainty have been widely investigated.However,there is a lack of market mechanisms regarding the power variation of the load and REGs.This paper thus defines a planned ramping(PR)product to follow the net load variation and extends the local energy market to include the trading of PR products.Players are economically compensated for their PR products.Bidding models of dispatchable generators and flexible load aggregators in the joint market are investigated.To solve the market problem in polynomial time,a distributed market clearing method is developed based on the ADMM algorithm.The joint market is tested on a modified IEEE 33-bus system.It verifies that introducing the PR market can encourage flexible loads to provide more PR service to accommodate the net load variation.As such,the ramping cost of dispatchable generators is reduced by 29.09%in the test case.The planned energy curtailment from REG is also reduced.The computational efficiency of the proposed distributed clearing method is validated by comparing it with a centralized method.