A Review of the Common Neurodegenerative Disorders: Current Therapeutic Approaches and the Potential Role of Nanotherapeutics

Neurodegenerative disorders are primarily characterized by neuron loss. The most common neurodegenerative disorders include Alzheimer’s and Parkinson’s disease. Although there are several medicines currently approved for managing neurodegenerative disorders, a large majority of them only help with associated symptoms. This lack of pathogenesis-targeting therapies is primarily due to the restrictive effects of the blood–brain barrier (BBB), which keeps close to 99% of all “foreign substances” out of the brain. Since their discovery, nanoparticles have been successfully used for targeted delivery into many organs, including the brain. This review briefly describes the pathophysiology of Alzheimer’s, Parkinson’s disease, and amyotrophic lateral sclerosis, and their current management approaches. We then highlight the major challenges of brain-drug delivery, followed by the role of nanotherapeutics for the diagnosis and treatment of various neurological disorders.     

Biofuels (alcohols and biodiesel) applications as fuels for internal combustion engines

The increasing industrialization and motorization of the world has led to a steep rise for the demand of petroleum-based fuels. Petroleum-based fuels are obtained from limited reserves. These finite reserves are highly concentrated in certain regions of the world. Therefore, those countries not having these resources are facing energy/foreign exchange crisis, mainly due to the import of crude petroleum. Hence, it is necessary to look for alternative fuels which can be produced from resources available locally within the country such as alcohol, biodiesel, vegetable oils etc. This paper reviews the production, characterization and current statuses of vegetable oil and biodiesel as well as the experimental research work carried out in various countries. This paper touches upon well-to-wheel greenhouse gas emissions, well-to-wheel efficiencies, fuel versatility, infrastructure, availability, economics, engine performance and emissions, effect on wear, lubricating oil etc.     

Consequence-based structural design approach for black swan events

The metaphor of black swan refers to unpredictable events like 9/11, the Indian Ocean tsunami, or the Oklahoma City Federal Building bombing, that cause catastrophic consequences for structural system safety. The likelihood of occurrence for such unforeseen events cannot be estimated from the observed data or prognosticated by experts. The absence of event and likelihood information renders futile the application of usual risk-based methods for design. Therefore, a shift from the probabilistic approach to consequence-based structural design is necessary for coping with the unexpected demands. This is accomplished through the conceptual development of a system capacity oriented design approach, where structural members are designed for variable reliabilities based upon their contribution to causing adverse system consequences. Information about general structural integrity encoded in the stiffness matrix is applied, using member consequence factors ranging from 0 to 1, for determining a member’s contribution towards system response. The structural system is designed using member consequence factors as additional partial factors on the resistance side of the design equations. The consequence-based scheme does not need a triggering hazard event (or its likelihood) and is an apt structural design approach for black swan events.     

Synthesis of CaCO3–P(MMA–BA) nanocomposite and its application in water based alkyd emulsion coating

As part of broader effort to synthesize a new class of water-based composite, hybrid emulsion polymerization was carried out with acrylic monomers [methyl methacrylate (MMA), n-butyl acrylate (BA)]. Nanocomposite of P(MMA–BA)/nano CaCO₃ was synthesized by in situ emulsion polymerization. Water-based alkyd coating with various proportions nano CaCO₃, P(MMA–BA) and its nanocomposite was formulated. Extent of polymerization with and without nano CaCO₃ was measured using gravimetric method. Thermal properties of neat polymer, nanocomposite and coating films were evaluated by TGA and DSC, DTA analysis. Uniform dispersion of nano CaCO₃ in polymer matrix was ensured from SEM/TEM images. Incorporation of nanoparticles to hybrid polymer and nanocomposite to alkyd emulsion showed significant enhancement in mechanical and thermal properties. Dual role of nanocomposite in coating; as a partial binder and a filler to improve property profile of neat coating has been reported.     

Design of a high-speed optical interconnect for scalable shared-memory multiprocessors

Large-scale distributed shared-memory multiprocessors (DSMs) provide a shared address space by physically distributing the memory among different processors. A fundamental DSM communication problem that significantly affects scalability is an increase in remote memory latency as the number of system nodes increases. Remote memory latency, caused by accessing a memory location in a processor other than the one originating the request, includes both communication latency and remote memory access latency over I/O and memory buses. The proposed architecture reduces remote memory access latency by increasing connectivity and maximizing channel availability for remote communication. It also provides efficient and fast unicast, multicast, and broadcast capabilities, using a combination of aggressively designed multiplexing techniques. Simulations show that this architecture provides excellent interconnect support for a highly scalable, high-bandwidth, low-latency network.     

γ-δ Routh approximation for interval systems

The paper presents the γ-δ Routh approximation for interval systems. The interval γs and δs are evaluated for the higher order interval systems, and then an rth-order approximant is obtained by retaining the first r, interval δs, and γs. A numerical example illustrates the procedure     

Visual perception-based criminal identification: a query-based approach

Abstract

The visual perception of eyewitness plays a vital role in criminal identification scenario. It helps law enforcement authorities in searching particular criminal from their previous record. It has been reported that searching a criminal record manually requires too much time to get the accurate result. We have proposed a query-based approach which minimises the computational cost along with the reduction of search space. A symbolic database has been created to perform a stringent analysis on 150 public (Bollywood celebrities and Indian cricketers) and 90 local faces (our data-set). An expert knowledge has been captured to encapsulate every criminal’s anatomical and facial attributes in the form of symbolic representation. A fast query-based searching strategy has been implemented using dynamic decision tree data structure which allows four levels of decomposition to fetch respective criminal records. Two types of case studies - viewed and forensic sketches have been considered to evaluate the strength of our proposed approach. We have derived 1200 views of the entire population by taking into consideration 80 participants as eyewitness. The system demonstrates an accuracy level of 98.6% for test case I and 97.8% for test case II. It has also been reported that experimental results reduce the search space up to 30 most relevant records.