Firework inspired load balancing approach for wireless sensor networks

Wireless Networks - In Wireless Sensor Networks (WSNs), where power consumption is a huge concern, the improvement of the network’s lifetime is an area of constant study and innovation. The...     

Role of Post-translational Modifications in Alzheimer's Disease

The global burden of Alzheimer's disease (AD) is growing. Valiant efforts to develop clinical candidates for treatment have continuously met with failure. Currently available palliative treatments are temporary and there is a constant need to search for reliable disease pathways, biomarkers and drug targets for developing diagnostic and therapeutic tools to address the unmet medical needs of AD. Challenges in drug-discovery efforts raise further questions about the strategies of current conventional diagnosis; drug design; and understanding of disease pathways, biomarkers and targets. In this context, post-translational modifications (PTMs) regulate protein trafficking, function and degradation, and their in-depth study plays a significant role in the identification of novel biomarkers and drug targets. Aberrant PTMs of disease-relevant proteins could trigger pathological pathways, leading to disease progression. Advancements in proteomics enable the generation of patterns or signatures of such modifications, and thus, provide a versatile platform to develop biomarkers based on PTMs. In addition, understanding and targeting the aberrant PTMs of various proteins provide viable avenues for addressing AD drug-discovery challenges. This review highlights numerous PTMs of proteins relevant to AD and provides an overview of their adverse effects on the protein structure, function and aggregation propensity that contribute to the disease pathology. A critical discussion offers suggestions of methods to develop PTM signatures and interfere with aberrant PTMs to develop viable diagnostic and therapeutic interventions in AD.     

Fabrication of Wear-Resistant Ti3AlC2/Al3Ti Hybrid Aluminum Composites by Friction Stir Processing

Metallurgical and Materials Transactions A - Hybrid nanocomposites have potential as wear-resistant materials. However, synthesizing these nanocomposites by conventional molten state methods result...     

Length–weight relationships of five catfish species (Siluriformes) from the Ganga River,India

Knowledge of the length–weight relationships (LWRs) of fish is an important tool to understand fish body form, growth pattern, stock management and their conservation. The present study focused on investigating the length–weight relationships for five catfish species, Pachypterus atherinoides (Bloch, 1794), belonging to family Horabagridae; Batasio batasio (Hamilton, 1822) family Bagridae; Bagarius yarrelli (Sykes, 1839), family Gogangra viridescens (Hamilton, 1822); and Sisor rhabdophorus (Hamilton, 1822) belonging to family Sisoridae. Specimens were collected from the middle stretch of the Ganga River in India from November 2016 to May 2018. A total of 174 specimens of five fish species were collected, and their total lengths were measured to the nearest centimetre and the body weight to the nearest gram. The value of the parameter slope (b) of LWRs of the five species ranged from 2.86 (B. yarrelli) to 3.16 (G. viridescens), with a mean value of 2.99. The results of the present study documented the new maximum total length (TL) for P. atherinoides and S. rhabdophorus. The present study also provides the first reference regarding LWRs for S. rhabdophorus.     

Properties of ligno‐cellulose fiber Hildegardia

Studies on some properties such as the density, the degradation temperatures, the morphology and the spectral features of the ligno‐cellulose fiber Hildegardia were carried out in both untreated and alkali treated form. The fibers are found to have good morphology and moderate initial and final degradation temperatures. On alkali treatment, the lignin was found to be eliminated. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 84: 2216–2221, 2002     

Multi-objective optimization of feature selection using hybrid cat swarm optimization

With the pervasive generation of information from a wide range of sensors and devices, there always exist a large number of input features in databases, thus complicating machine learning problem formulation. However, certain features are relatively impertinent to specific problems, which may degrade the performances of classifiers in terms of prediction accuracy, sensitivity,specificity, and recall rate. The main goal of a multi-objective optimization problem is to identify the subsets of the given features. To this end, a hybrid cat swarm optimization(HCSO) algorithm is proposed in our paper for performance improvement of the basic cat swarm optimization(CSO) that incorporates guided and competitive inherent characteristics into the original CSO. The performance of HCSO has been tested by finding the optimal feature subset for 15 benchmark datasets. The number of class labels for these datasets varies between 2 and 40. The time complexity analysis of both CSO and HCSO has also been evaluated. Moreover, the performance of the proposed algorithm has been compared with that of simple CSO and other state-ofthe-art techniques. The performances obtained by HCSO have an average 2.68% improvement with a standard deviation of 2.91.The maximum performance improvement is up to 10.09% in prediction accuracy. Tested on the same datasets, CSO has yielded improvements within the range of-7.27% to 8.51% with an average improvement 0.9% and standard deviation 3.96. The statistical tests carried out in the experiments prove that HCSO manifests a moderately better feature selection capacity than that of its counterparts.     

Supramolecular π–π assembly of a neutral [Cu(salen)] complex via the templating effect of an ionic inorganic complex Na2[Cu(mnt)2] forming a framework type material having well-defined channels

A classical ionic inorganic complex Na₂[Cu(mnt)₂] (mnt²⁻ = maleonitriledithiolate = 1,2-dicyanoethylenedithiolate), that acts as a template in assembling neutral [Cu(salen)] (salen = bis(salicylidene)ethylenediamine) complexes forming a framework type arrangement, is accommodated in the channel formed in the crystal structure of a new type of host–guest compound [Cu(salen)]₄ · Na₂[Cu(mnt)₂] (1). The non-covalent supramolecular interactions among [Cu(salen)] complexes and between [Cu(salen)] and [Cu(mnt)₂]²⁻ complexes in the crystal lattice of 1 result in weak antiferromagnetic coupling.     

2-Transitivity is Insufficient for Local Testability

A basic goal in property testing is to identify a minimal set of features that make a property testable. For the case when the property to be tested is membership in a binary linear error-correcting code, Alon et al. (Trans Inf Theory, 51(11):4032–4039, 2005) had conjectured that the presence of a single low-weight codeword in the dual, and “2-transitivity” of the code (i.e., the code being invariant under a 2-transitive group of permutations on the coordinates of the code) suffice to get local testability. We refute this conjecture by giving a family of error-correcting codes where the coordinates of the codewords form a large field of characteristic two, and the code is invariant under affine transformations of the domain. This class of properties was introduced by Kaufman & Sudan (STOC, 2008) as a setting where many results in algebraic property testing generalize. Our result shows a complementary virtue: This family also can be useful in producing counterexamples to natural conjectures.     

Malware detection using assembly and API call sequences

One of the major problems concerning information assurance is malicious code. To evade detection, malware has also been encrypted or obfuscated to produce variants that continue to plague properly defended and patched networks with zero day exploits. With malware and malware authors using obfuscation techniques to generate automated polymorphic and metamorphic versions, anti-virus software must always keep up with their samples and create a signature that can recognize the new variants. Creating a signature for each variant in a timely fashion is a problem that anti-virus companies face all the time. In this paper we present detection algorithms that can help the anti-virus community to ensure a variant of a known malware can still be detected without the need of creating a signature; a similarity analysis (based on specific quantitative measures) is performed to produce a matrix of similarity scores that can be utilized to determine the likelihood that a piece of code under inspection contains a particular malware. Two general malware detection methods presented in this paper are: Static Analyzer for Vicious Executables (SAVE) and Malware Examiner using Disassembled Code (MEDiC). MEDiC uses assembly calls for analysis and SAVE uses API calls (Static API call sequence and Static API call set) for analysis. We show where Assembly can be superior to API calls in that it allows a more detailed comparison of executables. API calls, on the other hand, can be superior to Assembly for its speed and its smaller signature. Our two proposed techniques are implemented in SAVE) and MEDiC. We present experimental results that indicate that both of our proposed techniques can provide a better detection performance against obfuscated malware. We also found a few false positives, such as those programs that use network functions (e.g. PuTTY) and encrypted programs (no API calls or assembly functions are found in the source code) when the thresholds are set 50% similarity measure. However, these false positives can be minimized, for example by changing the threshold value to 70% that determines whether a program falls in the malicious category or not.