Miracle-dz/UniFAR-FTUs huggingface dataset:
Geometric Criteria and Experimental Validation of the Auxetic Interval in a Three Dimensional Periodic Framework

Auxetic behavior refers to lateral widening upon stretching or, in reverse, lateral shrinking upon compression. When an initially auxetic structure is actuated by compression or extension, it will not neccesarily remain auxetic for larger deformations. In this paper, we investigate the auxetic range in the deformation of a periodic framework with one degree of freedom. We use geometric criteria to identify the interval where the deformation is auxetic and validate these theoretical findings with compression experiments on sample structures with 10 × 10 × 10 unit cells.
Novel Online Vehicle Toll Payment System for Indian National Highways

In this paper, a design for automatic license plate number recognition system is to be developed. A novel genetic algorithm is introduced to detect and extract the license plate. This performs two levels of segmentation process. Then Connected Component Analysis technique is used to extract individual characters, i.e. numbers and alphabets, in the image. Then followed by template matching method with loaded database, where the database consist of 10 to 15 image samples of all possible numeric values and alphabets of different size and font. As a result of the template matching system we will get the recognized numbers from image to text format.
Does College Education Make Us Act Healthier? Evidence from a Japanese Superstition

We investigated the causal effect of college education on smoking, drinking, sleeping, and cancer screening behavior in Japan. To estimate said effect, we leveraged a unique instrument in which a mismatch between Japanese superstition and school year in 1967 leading to an increase in college attainment. We found that a longer year of college education was associated with reductions in smoking and drinking and improvements in sleeping and the use of cancer screening. We also explored heterogeneity across genders and found that women drive the causal relationship between college education and health behavior in Japan.
Preparation, Microencapsulation, and Characterization of CA-PA Eutectic (PCM) as Thermal Energy Storage System

This work is focused on the synthesis of a eutectic mixture of capric and palmitic acid (CA-PA) as phase change material (PCM) for human comfort temperature (25±1oC) and microencapsulation with crosslinked-polystyrene using emulsion polymerization. Chemical interactions of shell material with PCM and morphology of prepared microencapsulated PCM (MEPCM) were examined using Fourier transform infrared spectroscopy (FTIR) and field emission scanning electron microscopy (FESEM) respectively. The melting (25.53oC) enthalpy based on differential scanning calorimetry (DSC) measurement was found 134.61 J·g-1 while the same for MEPCM (25.10oC) was 96.98 J·g-1. The encapsulation ratio estimated based on DSC analysis was found to be 72.05%. The thermal durability of MEPCM was investigated using thermogravimetric analysis (TGA). Degradation of MEPCM took place in three different steps with 69.10% evaporation loss of PCM which supported the DSC results. Particle size distribution (PSD) ranged between 3.3 μm and 23.6 μm. Hence, MEPCM of CA-PA eutectic mixture with their large latent heat storage ability with higher thermal stability would be useful in energy storage applications.
Study on Sentiment & Opinion for 'Review Text' Corpus

Now a days, microscopic blogs became a very distinguished and famed communicating tool among different internet users. Millions of users share their opinions on different aspects everyday. Thus, microblogging websites play a significant role as a group of mixed resources of data for analysing opinion and sentiment. The main aim of Sentiment Analysis is to determine the sensibility of a speaker or a writer with respect to different topics for the overall contingent polarity of the document. Sentiment Analysis is also one of the major tasks in Natural Language Processing (NLP). The major challenges are focused on the edge of 4 V’s (Velocity, Variety, Volume &amp; Veracity) where the data are purely unstructured. In this paper, a particular product reviews for different companies and categories are scanned for opinion mining purposes which may further be extended to different products also. Using the corpus, we build a classifier, used to determine positive, negative &amp; neutral sentiments for a specified document. A conventional process for illustration of sentiment classification is proposed with a comprehensive procedure.
Hybrid Modality Level Challenges Faced in Multi-Modal Sentiment Analysis

Aspects and sentiments expressed by human beings through behavior is computed systematically by neural networks and this approach have been tremendously appreciated throughout the research scientists nowadays. Multi modal sentiment analysis is the currently appreciated work in the deep learning field. Diverse modalities among image, videos, text, audio or fusion of the modalities here are through which human beings express their desirable information. Physically handicapped or the insecurity forces in the border of the nation can be the victims prone to be under vigilance monitoring for identifying the sentiment of actions they express. The paper provides the data sets available for various application areas under implementation and algorithms proposed till date to solve the application problems under implementation and followed by scientific challenges faced during fusion of two or modalities expressed here. The paper also includes the discussion about the implementation criteria for constructing the deep learning networks for various fusion levels of modality.
Effect of Chloride Concentrations and Temperature on Prestressed Austenitic Stainless Steel 304 Based on Pressure Vessel in Oil and Gas Industry

Chloride-induced stress corrosion cracking (CISCC) of austenitic stainless steel type 304 (SS 304) under thermal insulation is a classical pressure vessel failure case, but recurrent failures require further analysis of possible mechanisms which lead to the damage particularly on the effect of leachable chloride from the thermal insulation. The objective of the research was to investigate the effect of chloride leached from thermal insulation material on CISCC of SS 304. The study was based on actual pressure vessel failure case sample whereby proposed parameters such as temperature and chloride concentrations were derived. SS 304 samples were immersed in sodium chloride solution to identify the pitting corrosion mechanism which leads to CISCC failure of a pressure vessel. CISCC test was carried out by using ASTM G30 standard for the U-bend sample preparations to simulate CISCC of SS 304 under chloride environment. The test parameters used were various chloride concentrations of 200 to 30,000 ppm as per ASTM C692 at 40, 60, and 85°C temperature as per ASME B31.3 standard [1]. Visual and stereomicroscope results revealed no external surface macro-crack appearance found on the U-bend SS 304 samples tested at 40, 60 and 85°C in chloride concentrations of 200 to 30,000 ppm. FESEM and EDX analysis revealed the surface morphology micro-void cracks on the corrosion products at 40 and 60°C and revealed CISCC initiation at 85°C of the SS 304 U-bend samples. The metallographic examination in cross-section revealed transgranular cracking across the grain boundaries by film dissolution mechanism has occurred only in the U-bend SS 304 tested at 85°C (3000, 8000 and 30,000 ppm chloride concentrations of 9 months duration). In conclusion, general corrosion has occurred at 40°C, localized pitting corrosion has occurred in a failed vessel at 60°C and the CISCC was initiated by the leachable chloride from the insulation material perlite at temperature above 85°C in the presence of moisture. Corrosion consideration in materials selection for vessel operating above 85°C is crucial and suggested to install a hydrophobic waterproofing thermal insulation material to minimize the accumulated chloride ions over years in-service.
Improving ERP Software Selection Process by Integrating QFD With AHP Approach

Many organizations have realized the importance of establishing a reliable connection with their customers to identify their requirements, identify IT failures, answer customer queries, and provide real-time customer support in technical issues. CRM software vendors have provided various solution packages to meet companies' requirements and needs, but choosing the best one requires a full understanding of the elements involved and considering them in the decision-making process. Many decision-making approaches have been introduced to solve complicated selection problems; each method used has advantages and disadvantages. This article presents an integrated model of one of the most efficient decision-making methods, the AHP "Analytic Hierarchy Process" combined with the QFD tool. <br><br>AHP has a consistency tool to measure the reliability of decisions but does not consider stakeholders’ needs. In contrast, QFD does, and it provides a full overview of the technical parameters and areas for possible improvements. The integration of these two methods will eliminate the disadvantages of using each alone and create a reliable model to help in complex decisions that may define a new enterprise's success or failure.
Optimization of saccharification of enzymatically pretreated sugarcane tops by response surface methodology for ethanol production

ABSTRACT The world's concern over its dependency on non-renewable fossil fuels has drawn our focus towards renewable fuels such as bioethanol from lignocellulosic biomass. The present study investigated the potential of sugarcane tops as a potent source for bioethanol production. Enzymatically pretreated sugarcane tops were subjected to saccharification process using a cellulase-xylanase concoction produced from Trichoderma reesei Rut C30. Statistical analysis using response surface methodology (RSM) was adopted for optimizing the process parameters in order to obtain maximum reducing sugar. Under the optimized conditions of pH 5, incubation 7 h, enzyme titre of 19.33 IU ml–1, temperature 50°C and solid loading of 14% (w/v), maximum reducing sugar of 508.92 ± 0.02 mg g–1 was obtained. Changes in the functional group and calorific content after saccharification was also evaluated using FTIR and bomb calorimeter. The hydrolysate obtained after saccharification was further subjected to fermentation using Saccharomyces cerevisiae which was able to produce an ethanol yield of 27.2 g l–1.
Cyber Attacks Mitigation: Detecting Malicious Activities in Network Traffic – A Review of Literature

Cyber-attacks are becoming more common and over the last decade, many attacks have made top news, targeting manufacturing firms and governmental organisations. Such attacks have triggered substantial financial damage and they've been trying to obstruct key public sector operations. Furthermore, as the Internet of Things (IoT) has arisen, the number of Internetconnected devices is increasingly growing and being an easy target of cyber-attacks. To counter cyber-attacks, information security researchers rely extensively on intrusion detection systems (IDSs) that can identify suspicious activities by comparing patterns of documented attacks or detecting anomaly-based activities. This survey aims to tackle Trust, Protection, identification and activity on wide scale networks and Internet of Things. The proposed research aims at developing a practically deployable cyber security solution to one or more of the cyber-attacks. Multi-Stage Attacks (MSAs), APT, DoS attacks, wireless injection attacks, botnets or other malicious activities will be investigated. In this literature survey, we are highlighting the work Performed throughout the area of cyber security by various researchers, various types of cyber-attacks and its stages, various approaches to prevent cyber-attacks, different challenges faced by a preventer, and some gaps in the research. This literature review is carried out by using the secondary data obtained from peer-reviewed journals and other sources on the web. This review aims to explain Detecting Malicious Activities in Network Traffic.
Analysis of Two Phase Query Optimization Algorithm for Generating Optimal Query Plan using Randomized Algorithm

The environment in which large numbers of distributed sites are connected with each other, without sharing their physical memory is called distributed database system. The database systems that execute on each distributed sites are independent of each other. Replication and fragmentation are the two important techniques used in the development of distributed database. The replicas of the data are stored in different distributed sites for promoting the availability of data at all the distributed sites. Thus with the help of replication each distributed site can request for the replica of the data and can store the entire copy of the same. The concept of fragmentation is commonly used for flooding the data to various distributed sites. In this paper an attempts have been made to compare the results of Iterative Improvement (II), Simulated Annealing (SA) and 2 Phase Optimization (2PO) algorithms. The 2PO algorithm is also known as hybrid approach since it is a combination of II and SA. It is called 2 PO because it executes in two phase, in the first phase the II algorithm is applied, then in the second phase the SA algorithm is applied. The results of the experiments obtained after implementing II, SA and 2PO algorithms are compared. Based on the experimental result obtained it is oblivious that 2PO performs better than II and SA.
Coherently Scattering Domain Size vs. Grain Size in Thin Metallic Films: A Comparative Study by X-Ray Diffraction and Transmission Electron Microscopy

Grazing incidence x-ray diffraction (GID) and transmission electron microscopy (TEM) were used in a comparative investigation of nanometric Cu and W thin films. In the GID study, the in-plane grain size and microstrain present in the films were determined using established x-ray diffraction peak profile analysis. These results were compared to the TEM investigation in which hollow cone dark field (HCDF) imaging, conical dark field (CDF) imaging and precession electron diffraction (PED) were used to determine grain size. The spatial variation of crystallographic orientation within the films obtained via PED was used to determine the intragrain misorientations. For highly strained grains differences between the GID and TEM analysis are observed and are attributed to large intra-grain misorientations due to microstrain arising from lattice rotations resulting from the presence of dislocations. The combination of both characterization techniques on a common set of samples allowed for a quantitative review of Ungár's modified Williamson-Hall analysis: An additional broadening term, proportional to the product of microstrain and grain size broadening, is proposed.
An Atomistic-Informed Phase-Field Model for Non-Isothermal Phase Transformation and Plasticity in Yttria-Stabilized Tetragonal Zirconia

We propose an elastoplastic phase-field (PF) model to investigate the mechanics of tetragonal-to-monoclinic phase transformation (TMPT) and elastoplastic deformation of yttria-stabilized tetragonal zirconia (YSTZ). A Landau polynomial with non-vanishing chemical energy at the equilibrium temperature is introduced to account for the actual formation energies of the phases. The effects of different grain orientations, grain boundaries, latent heat, and temperature on TMPT and deformation mechanisms are considered. The simulation results for single crystals demonstrate the capability of the model to reproduce the orientation-dependent compressive deformation of YSTZ similar to atomistic simulations and micropillar experiments. The single crystal with [100] crystallographic orientation along the loading direction (SC[100]) displays both TMPT and plasticity, SC[101] experiences only phase transformation, while SC[001] undergoes only plastic yielding. The TMPT induced by compressive loading exhibits shape memory effect (SME) below the equilibrium transformation temperature and pseudoelasticity above it, while the critical transformationstress increases when the loading temperature increases. The irrecoverable plastic strain is found to trap part of the monoclinic phase, which prevents a complete reverse transformation. The polycrystalline cases also display SME and PE, respectively, at low and high temperatures. Due to the orientation differences between grains and the stress concentrations at geometric nonlinearities, plastic deformation occurs in polycrystalline YSTZ for an applied load less than the yield stress. The results suggest a possible limitation of plasticity and an improvement of the shape recovery of YSTZ if one can control the orientation of the grains and/or increase the density of stacking faults at the grain boundaries during material processing.
A Discretized Peierls-Nabarro Model: Its Application to Peierls Stresses of Dislocations in a Variety of Crystals

We have computed Peierls stresses of dislocations in a variety of crystals by applying a new discretized Peierls-Nabarro model (D-PN model) of the dislocation using the calculated ab-initio γ-surface. In the D-PN model, the disregistry distribution of atomic-row pairs facing at the glide plane is determined by the balance between the restoring stress due to the disregistry and the internal stress by an array of small dislocations placed at every intermediate position of atomic-row pairs, instead of continuous distribution of infinitesimal dislocations in the original PN model. Peierls stresses have been obtained by applying the shear stress to the model under which the structure is allowed to relax. The calculated Peierls stresses are largely reduced compared with those previously obtained by the original PN model (Y. Kamimura et al., Acta Mater. 148 (2018) 355-362), although the dislocation widths of the two models are almost the same. They have a good correlation with those experimentally estimated by Y. Kamimura et al. (Acta Mater. 61 (2013) 294-306) except for some very soft crystals, though the calculated Peierls stresses are generally still larger than those of experiments by a few factor.
Effect of Boundary Conditions on the Hydrogen Absorption in a Metal Hydride Reactor

In this paper, a numerical study of the heat and mass transfer in a metal hydride reactor is presented. The reaction within the metal hydride reactor is exothermic. That makes the hydriding process less effective. Thus, a cooling system is needed to reduce the temperature in order to increase the amount of the absorbed hydrogen. The geometry of the studied reactor is cylindrical with (H=3cm) of height and (R=5cm) of radius. A heat exchanger is considered in the lateral and base walls. The transfer is considered two-dimensional and transient. The governing equations of the transfer phenomenon are based on the conservation principle of mass, momentum and energy. Using the finite volume method, a CFD code has been worked out in the Fortran language to solve the mathematical model. The numerical results show a good agreement with the litterature. The results show the contribution of the cooling process in the enhancement of the hydrogen absorption rate. The results analysis shows a great consistency between the temperature of the cooling fluid, the pressure of hydrogen and the total mass of absorbed hydrogen. <br>
Remodeling Periodontitis Microenvironment for Osteogenesis by Using a Reactive Oxygen Species-Cleavable Nanoplatform

Modestly removing the excessive reactive oxygen species (ROS) plays&nbsp;a crucial part in regulating the microenvironment&nbsp;of periodontitis&nbsp;and provides a favorable&nbsp;condition for osteogenesis. &nbsp;However, the current strategy in scavenging&nbsp;ROS is&nbsp;incontrollable, greatly limiting the outcome of periodontitis. Herein, we introduced&nbsp;a controllable ROS-scavenging nanoplatform by encasing&nbsp;N-Acetylcysteine (NAC, (a famous ROS scavenger) into a tailor-made ROS-cleavable&nbsp;amphiphilic polymer nanoparticles (PEG-ss-PCL NSs) as an intracellular delivery carrier. The existing ROS in the inflammatory microenvironment facilitated the polymer degradation via breakage of the thioketal bonds, then led to the encapsulated&nbsp;NAC&nbsp;release. &nbsp;The NAC eliminated all ROS induced by LPS, while PssL-NAC adjusted the ROS level&nbsp;to a litter higher than the control group. The percentage of apoptotic cells cultured with NAC and PssL-NAC decreased observably&nbsp;compared with cells cultured with 10 µg/ml&nbsp;LPS. The microenvironment regulated by PssL-NAC was very suitable for osteogenic differentiation from the results of PCR and&nbsp;Western blot, which exhibited a higher expression level of BMP2, Runx2, and PKA. The ALP activity and Alizarin red S staining showed consistent results. Additionally, the injection of NAC and&nbsp;PssL-NAC into the periodontitis area could alleviate the tissue destruction induced by ligation of the maxillary second molar. The PssL-NAC showed a better ability to decrease the osteoclast activity and inflammation, consequently improving&nbsp;the restoration&nbsp;of destructed tissue. Our study suggests that ROS responsive polymer nanoparticles loading NAC (PssL-NAC)&nbsp;can be new promising material for periodontitis treatment.
A Review of Vision-Based Pedestrian Detection Techniques

The problem of pedestrian detection has been considered as a vital one in the domain of Computer Vision and Pattern Recognition. It is formulated as the problem of automatically identifying and locating the pedestrians in images or videos. In the past many techniques have been proposed to solve this problem accurately and efficiently. However, the variations in images such as body attire and pose, occlusion, different illumination parameters in different scenarios and clutter present in the background poses challenges in attaining high accuracy. This paper provides a review of some well-known existing techniques for pedestrian detection in images. Few benchmarked datasets are discussed, performance evaluation metrics are also presented. Furthermore, this paper also discusses the interesting observations of the experiments and potential research direction for the pedestrian detection problem.
Sahaj-Krishi: Wireless Swarm Agro Bot System With Data Analytics

Agriculture is commonly referred to as a labor intensive sector. Thus there is a need to automate the various processes involved with proper monitoring. Swarm robotics is one form of network architecture implementation in which multiple robots can communicate among them wirelessly so that the task assigned to each mobile robot can be executed synchronously. This paper proposes the formation of a WSN (Wireless Sensor Network) using Radio Frequency transceiver modules which makes each robot to act as a node in this sensor network. Each robot will be assigned a particular functionality such as Ploughing, Seeding, Watering and many more, which will be executed through actuators controlled by a microcontroller development board, which acts as the interface between the network commands and the actuators. This paper also presents the data analytics tools that can be used for predicting the most suitable crop in the given conditions through classification, as well as to predict the optimum soil moisture content for a given crop and surrounding conditions using Supervised Learning