Animal models in the study of Alzheimer's disease and Parkinson's disease:A historical perspective

Alzheimer's disease and Parkinson's disease are two of the most prevalent and disabling neurodegenerative diseases globally.Both are proteinopathic conditions and while occasionally inherited,are largely sporadic in nature.Although the advances in our understanding of the two have been significant,they are far from complete and neither diagnosis nor the current practices in treatment and rehabilitation is adequately helpful.Animal models have historically found application as testing beds for novel therapeutics and continue to be valuable aids in pharmacological research.This review chronicles the development of those models in the context of Alzheimer's and Parkinson's disease,and highlights the shifting paradigms in studying two humanspecific conditions in non-human organisms.

Performance evaluation of deep neural networks for forecasting time-series with multiple structural breaks and high volatility

The problem of automatic and accurate forecasting of time-series data has always been an interesting challenge for the machine learning and forecasting community.A majority of the real-world time-series problems have non-stationary characteristics that make the understanding of trend and seasonality difficult.The applicability of the popular deep neural networks(DNNs)as function approximators for non-stationary TSF is studied.The following DNN models are evaluated:Multi-layer Perceptron(MLP),Convolutional Neural Network(CNN),and RNN with Long Short-Term Memory(LSTM-RNN)and RNN with Gated-Recurrent Unit(GRU-RNN).These DNN methods have been evaluated over 10 popular Indian financial stocks data.Further,the performance evaluation of these DNNs has been carried out in multiple independent runs for two settings of forecasting:(1)single-step forecasting,and(2)multi-step forecasting.These DNN methods show convincing performance for single-step forecasting(one-day ahead forecast).For the multi-step forecasting(multiple days ahead forecast),the methods for different forecast periods are evaluated.The performance of these methods demonstrates that long forecast periods have an adverse effect on performance.

In vitro and in vivo evaluation of gastroretentive floating drug delivery system of ofloxacin

This study aimed to develop hydrophilicmatrix based controlled release gastroretentive drug delivery system of ofloxacin and conducting its in vitro and in vivo evaluations.Effervescent floating gastroretentive drug delivery system of ofloxacin was prepared utilizing Boxe Behnken statistical design with 3 factors,3 levels and 15 experimental trials.Formulation optimization was done by setting targets on selected responses.In vivo studies were carried out for the optimized formulation with 12 healthy human volunteers and obtained pharmacokinetic parameters were compared with themarketed once daily formulation,“Zanocin OD”.Optimized formulation showed satisfactory controlled in vitro drug release for more than 12 h with excellent buoyancy properties(floating lag time<1 min,floating duration>16 h).Optimized and marketed formulations were found to have similar in vitro release profile(f2¼79.22)and also were found to be bioequivalent.Serum ofloxacin concentration was well maintained above its reported minimum inhibitory concentrations for most of the pathogens for sufficiently longer duration.Cmax and AUC values of optimized formulation were found to be significantly higher than of marketed product despite their bioequivalence.Bettertherapeutic effect can be expected since ofloxacin exhibits concentration dependent killing.Hence,gastroretention can be a promising approach to enhance bioavailability of ofloxacin with narrow absorption window in upper GIT.

System Identification of Heritage Structures Through AVT and OMA:A Review

In this review article,the past investigations carried out on heritage structures using Ambient Vibration Test(AVT)and Operational Modal Analysis(OMA)for system identification(determination of dynamic properties like frequency,mode shape and damping ratios)and associated applications are summarized.A total of 68 major research studies on heritage structures around the world that are available in literature are surveyed for this purpose.At first,field investigations carried out on heritage structures prior to conducting AVT are explained in detail.Next,specifications of accelerometers,location of accelerometers and optimization of accelerometer networks have been elaborated with respect to the geometry of the heritage structures.In addition to this,ambient vibration loads and data acquisition procedures are also discussed.Further,the state of art of performing OMA techniques for heritage structures is explained briefly.Furthermore,various applications of system identification for heritage structures are documented.Finally,conclusions are made towards errorless system identification of heritage structures through AVT and OMA.

Synthesis of Luminescent CdTe Nanorods on Anodized Aluminum Oxide Template and Their Utility in Divalent Heavy Metal Ion Sensing

A simple one-pot hydrothermal method to grow luminescent CdTe nanorods on porous anodized aluminum oxide (AAO) template is described. These CdTe nanorods on the AAO template were further applied as an optical probe to detect divalent heavy metal ions such as Hg, Pb, Mg and Zn, by examining its photoluminescence (PL) responses. The presence of Pb and Hg ions quenched the photoluminescence (PL) of the CdTe nanorods where as Zn and Mg ions enhanced it with the effect of red shift in the peak position respectively. These PL enhancements/quenching of the nanorods after exposing to the divalent ions were explained on the basis of the active surface related recombination, which depends on the direction of carrier transfer mechanism i.e. from nanorods to the surface adsorbed metal ions or vice-versa and is attributed to the alignment of bands thus formed. The luminescent CdTe nanorods grown on AAO template was found to be effective in sensing metal ions (Pb, Hg, Zn and Mg) up to a micro-molar concentration.

Support vector regression modeling in recursive just-in-time learning framework for adaptive soft sensing of naphtha boiling point in crude distillation unit

Prediction of primary quality variables in real time with adaptation capability for varying process conditions is a critical task in process industries.This article focuses on the development of non-linear adaptive soft sensors for prediction of naphtha initial boiling point(IBP)and end boiling point(EBP)in crude distillation unit.In this work,adaptive inferential sensors with linear and non-linear local models are reported based on recursive just in time learning(JITL)approach.The different types of local models designed are locally weighted regression(LWR),multiple linear regression(MLR),partial least squares regression(PLS)and support vector regression(SVR).In addition to model development,the effect of relevant dataset size on model prediction accuracy and model computation time is also investigated.Results show that the JITL model based on support vector regression with iterative single data algorithm optimization(ISDA)local model(JITL-SVR:ISDA)yielded best prediction accuracy in reasonable computation time.

Study of the distribution profile of piperidine alkaloids in various parts of Prosopis juliflora by the application of Direct Analysis in Real Time Mass Spectrometry(DART-MS)

Direct Analysis in Real Time Mass Spectrometry(DART-MS)was applied to identify and study the distribution profile of piperidine alkaloids in different parts of Prosopis juliflora,without isolation and separation of the compounds by standard chromatographic techniques.With the help of DART-MS,chemical fingerprint of raw plant parts were generated,which revealed the presence of piperidine alkaloids in leaf,pod and flower.A comparative study of the distribution pattern,showed variation in the presence and distribution of these alkaloids in various parts of P.juliflora.The leaves and pod displayed the largest alkaloid pattern with a total of 12 different alkaloids in each part,whereas only 4 alkaloids were present in flower.Alkaloids:julifloridine,prosopine,prosopinine and prosafrinine were ubiquitously distributed in all the alkaloid rich plant parts.Juliprosopine was pre-eminet alkaloid in leaf,whereas pod and flower displayed copious amounts of julifloridine.

Peristaltic flow of MHD Jeffrey fluid through finite length cylindrical tube

The present investigation studies the peristaltic flow of the Jeffrey fluid through a tube of finite length. The fluid is electrically conducting in the presence of an applied magnetic field. Analysis is carried out under the assumption of long wavelength and low Reynolds number approximations. Expressions of the pressure gradient, volume flow rate, average volume flow rate, and local wall shear stress are obtained. The effects of relaxation time, retardation time, Hartman number on pressure, local wall shear stress, and mechanical efficiency of peristaltic pump are studied. The reflux phenomenon is also investigated. The case of propagation of a non-integral number of waves along the tube walls, which are inherent characteristics of finite length vessels, is also examined.

Delivery strategies for CRISPR/Cas genome editing tool for retinal dystrophies:challenges and opportunities

CRISPR/Cas,an adaptive immune system in bacteria,has been adopted as an efficient and precise tool for site-specific gene editing with potential therapeutic opportunities.It has been explored for a variety of applications,including gene modulation,epigenome editing,diagnosis,mRNA editing,etc.It has found applications in retinal dystrophic conditions including progressive cone and cone-rod dystrophies,congenital stationary night blindness,X-linked juvenile retinoschisis,retinitis pigmentosa,age-related macular degeneration,leber’s congenital amaurosis,etc.Most of the therapies for retinal dystrophic conditions work by regressing symptoms instead of reversing the genemutations.CRISPR/Cas9 through indel could impart beneficial effects in the reversal of gene mutations in dystrophic conditions.Recent research has also consolidated on the approaches of using CRISPR systems for retinal dystrophies but their delivery to the posterior part of the eye is a major concern due to high molecular weight,negative charge,and in vivo stability of CRISPR components.Recently,non-viral vectors have gained interest due to their potential in tissue-specific nucleic acid(miRNA/siRNA/CRISPR)delivery.This review highlights the opportunities of retinal dystrophies management using CRISPR/Cas nanomedicine.

Computational Study on Effect of Variation of Pitch-Chord on Secondary Losses in Rectilinear Turbine Cascade

Losses in turbine cascade are categorized as profile loss, secondary loss, tip clearance loss and annulus loss. Profile loss occurs due to development of boundary layer on surface of blade [1]. Increase in thickness of boundary layer and adverse pressure gradient increases profile loss. Secondary loss occurs due to turning of flow through flow passage which results in blowing of energy from pressure side to suction side. In turbine rotor blade suction surface leads and tip clearance loss occurs due to leakage of air from pressure side to suction side of the blade through tip clearance. Annulus loss occurs due to development of boundary layer on stationary row of blade. It also occurs in moving row of blade but in moving row of blades boundary layer is scraped by flow over the blades. This paper presents effects of variation of pitch-chord ratio on secondary loss.

Torsional wave frequency in heterogeneous earth crust lying over dry sandy semi-infinite substratum

The present study is carried out to investigate the transference of torsional surface waves in a heterogeneous anisotropic crust lying over a dry sandy half-space. The rigidities and densities as well as the initial stress are assumed varying as a function of depth in both the media. These variations are the product of the polynomial function of depth in degree n (n ∈ R) and the exponential function of depth. Following the theory of elastic waves, the mathematical model is established. Separation of variables is used to obtain the displacement in the layer and the half-space. Intrinsic boundary conditions are imposed to derive the dispersion equation. The inhomogeneity parameters associated with the rigidity, the density, and the initial stress of the medium are found to have substantial influence on the phase velocity of the torsional surface wave. The graphical presentations are drawn to exhibit the findings. The results thus obtained are significant for the investigation and characterization of torsional surface wave in the heterogeneous anisotropic layer.

Calcium chloride linked camel milk derived casein nanoparticles for the delivery of sorafenib in hepatocarcinoma cells

Sorafenib,a multikinase inhibitor used for the treatment of hepatocellular carcinoma,is limited by its low oral bioavailability.To overcome this drawback,we have developed novel camel milk casein-derived nanoparticles as a drug delivery system.Camel milk casein is not only biocompatible on oral administration but is actually a dietary protein of pharmaceutical relevance.Casein is used because of its amphiphilic nature,self-assembling property,ability to show sustained release,and capability of encapsulating both hydrophilic and hydrophobic drugs.In this study,camel milk casein nanoparticles loaded with sorafenib were developed and characterized.Characterization of casein nanoparticles was done by dynamic light scattering(DLS),zeta potential analysis,scanning light microscopy(SEM),and FTIR.The drug content in nanoparticle and drug-protein binding studies were conducted by UV spectroscopy.The cytotoxicity and cellular uptake efficiency studies were performed in HepG2 cell lines.It was observed that the cytotoxic effect of sorafenib loaded camel milk casein nanoparticles was more than free sorafenib in HepG2 cells.This work suggests camel milk casein as a suitable drug delivery molecule for sorafenib.In the future,it may also be used in enhancing the efficacy and specific distribution of other water-insoluble anticancer drugs.

Magnetohydrodynamics hemodynamics hybrid nanofluid flow through inclined stenotic artery

The present study aims to perform computational simulations of twodimensional(2D)hemodynamics of unsteady blood flow via an inclined overlapping stenosed artery employing the Casson fluid model to discuss the hemorheological properties in the arterial region.A uniform magnetic field is applied to the blood flow in the radial direction as the magneto-hemodynamics effect is considered.The entropy generation is discussed using the second law of thermodynamics.The influence of different shape parameters is explored,which are assumed to have varied shapes(spherical,brick,cylindrical,platelet,and blade).The Crank-Nicolson scheme solves the equations and boundary conditions governing the flow.For a given critical height of the stenosis,the key hemodynamic variables such as velocity,wall shear stress(WSS),temperature,flow rate,and heat transfer coefficient are computed.

Assessment of bone condition by acoustic emission technique: A review

The paper deals with the review of acoustic emission technique in biomedical field. The re-view is done with the aim to provide an overview of the use of AE technique in biomedical field, mainly concentrated on the AE behavior of bone under different loading conditions, its depend-ence on strain rate, in osteoporosis, monitoring the fracture healing process of bone. The over-all conclusion from the review was that almost all the studies in bone indicated that the initial AE occurs only in the plastic region and just prior to yield. That means the use of AE tech-nique for clinical application cannot be consid-ered as a safe technique, but the early occur-rence of AE events from callus promises the application of AE technique for monitoring the fracture healing process. The negligible effect of soft tissues on AE response of bone prom-ises AE to become a non-invasive method for assessment of bone condition.

Optimization of ECM Process Parameters Using NSGA-II

Electrochemical machining (ECM) could be used as one of the best non-traditional machining technique for machining electrically conducting, tough and difficult to machine material with appropriate machining parameters combination. This paper attempts to establish a comprehensive mathematical model for correlating the interactive and higher-order influences of various machining parameters on the predominant machining criteria, i.e. metal removal rate and surface roughness through response surface methodology (RSM). The adequacy of the developed mathematical models has also been tested by the analysis of variance (ANOVA) test. The process parameters are optimized through Nondominated Sorting Genetic Algorithm-II (NSGA-II) approach to maximize metal removal rate and minimize surface roughness. A non-dominated solution set has been obtained and reported.

Investigation of the factors affecting the consistency of short-period traffic counts

The main intent of this study is to investigate the accuracy of short-duration traffic counts conducted during winter months. The investigation is based on 11-year sample data collected using permanent traffic counters at various locations in Alberta, Canada. Four types of road sites： commuter, regional commuter, rural long-distance, and recreational sites are studied. The sample data consti- tute six different durations of counts （12-, 24-, 48-, 72-, 96-h, and 1 week） taken during summer and winter months. The coefficient of variation （CV） is used as the relative measure of deviation for counts of different dura- tions to measure the accuracy of short-period traffic counts. The study results indicate that 48-h count seems to be the most cost-effective counting interval during both summer and winter months. It is also found that the lowest values of CV result for counts taken at commuter sites, and the highest values are observed for recreational sites. Frequent changes in temperature and other weather events cause significant variation in traffic volume, which results in an increase in CV values for counts taken during winter months. The application of an adjustment factor to remove the effect of cold and snow from short-period counts is also included in this study. Introduced adjustment factors can reduce the values of CV for all counts taken during winter months. The findings of this study can lead highway agencies to improve the cost-effectiveness of their short- period traffic counting programs.

Phonon Dispersion for Armchair and Zigzag Carbon Nanotubes

In this paper we present calculations of phonon dispersion of different types of single walled carbon nanotubes (SWCNT). In these calculations, the starting point has been the phonon dispersion of graphene. Zone folding scheme is then applied to obtain the phonon dispersion of CNT from that of graphene. Since the radial breathing modes in the phonon dispersion are not obtained by the zone-folding method, certain modifications are made in the lower branches to obtain these modes. These modifications produce results similar to those obtained by more sophisticated ab-initio methods.

Multifault diagnosis in WSN using a hybrid metaheuristic trained neural network

Wireless sensor networks are susceptible to failures of nodes and links due to various physical or computational reasons.Some physical reasons include a very high temperature,a heavy load over a node,and heavy rain.Computational reasons could be a third-party intrusive attack,communication conflicts,or congestion.Automated fault diagnosis has been a well-studied problem in the research community.In this paper,we present an automated fault diagnosis model that can diagnose multiple types of faults in the category of hard faults and soft faults.Our proposed model implements a feed-forward neural network trained with a hybrid metaheuristic algorithm that combines the principles of exploration and exploitation of the search space.The proposed methodology consists of different phases,such as a clustering phase,a fault detection and classification phase,and a decision and diagnosis phase.The implemented methodology can diagnose composite faults,such as hard permanent,soft permanent,intermittent,and transient faults for sensor nodes as well as for links.The proposed implementation can also classify different types of faulty behavior for both sensor nodes and links in the network.We present the obtained theoretical results and computational complexity of the implemented model for this particular study on automated fault diagnosis.The performance of the model is evaluated using simulations and experiments conducted using indoor and outdoor testbeds.

Combined effects of Joule heating and nonuniform heat source/sink on unsteady MHD mixed convective flow over a vertical stretching surface embedded in a Darcy-Forchheimer porous medium

This paper deals with an unsteady magnetohydrodynamics(MHD)heat and masstransfer for a viscous incompressible fluid through a vertical stretching surface embedded ina Darcy-Forchheimer porous medium in the presence of a non-uniform heat source/sink andfirst-order chemical reaction.The porous surface is subjected to a uniform transverse magneticfield.The influence of velocity,thermal,and concentration slip is also investigated.The governing equations are coupled non-linear partial differential equations,which have been converted via similarity transformation into a set of ordinary differential equations.The resultantsystem of non-linear ordinary differential equations has been solved numerically with the helpof the“MATLAB”BVP4C Solver.Results are presented graphically to analyze the effects ofvarious physical parameters discovered in the problem such as Hartmann number(M),Forchheimer number(Fr),Grashof number(Gr),solutal Grashof number(Gc),suction parameter(S),porosity parameter(el),dimensionless velocity slip(Sv),Prandtl number(Pr),dimensionless thermal slip(St),space-dependent heat source/sink parameter(eA
1),temperature-dependent heat source/sink(eB)1),Eckert number(Ec),Schmidt number(Sc),chemical reaction parameter(g),unsteadiness parameter(A),and dimensionless concentration slip(Sc)on non-dimensionalvelocity ec0ðhÞ,temperature zðhÞ,and concentration efðhÞprofiles.The influence of these parameters on skin-friction coefficient(C)f),Nusselt number(Nu)x),and Sherwood number(Sh)x)areexpressed in tabular form.It is observed that an enhancement in Fr and el results in the declination of the velocity profile.There is an enhancement in temperature with an increment in theeA)1 and eB)1.The physical representation of flow characteristics that appeared in the problem ispresented using various graphs to depict real-world applications in industrial and engineeringoperations.The results were compared to previous studies,revealing that the two are in goodagreement.The novelty of the present investigation is:To interpret the combined effects ofviscous dissipation and Joule heating on a vertical stretching surface embedded in a highlyporous medium modeled using the Darcy-Forchheimer model.The findings could be valuablein understanding the flow of oil,gas,and water through an oil or gas field reservoir,as well asgroundwater migration and filtering and purification procedures.

Synthesis of Ag/AgCl-mesoporous silica nanocomposites using a simple aqueous solution-based chemical method and a study of their antibacterial activity on E. coli

Simple aqueous solution-based chemical methods have been developed for the synthesis of Ag/AgCI nanoparticle-mesoporous silica nanocomposites. Ag loading in the mesoporous silica was accomplished using a wet-impregnation method. The AgCl-mesoporous silica nanocomposite material （AgCl-mSi） was synthesized by using a ＇one pot method. Synthesized materials were characterized using X-ray diffraction, N2 adsorption-desorption analysis and high-resolution transmission electron microscopy. Antibacterial activity of the synthesized materials was investigated against Escherichia coil （E. coil） using the conventional plate-count method. All the materials showed high antibacterial activity even when the percentage loading of Ag in the nanocomposite was as low as 10wt%.