Effect of water and air flow on concentric tubular solar water desalting system.

This work reports an innovative design of tubular solar still with a rectangular basin for water desalination with flowing water and air over the cover. The daily distillate output of the system is increased by lowering the temperature of water flowing over it (top cover cooling arrangement). The fresh water production performance of this new still is observed in Sri Ramakrishna Mission Vidyalaya College of Arts and Science, Coimbatore (11° North, 77° East), India. The water production rate with no cooling flow was 2050ml/day (410ml/trough). However, with cooling air flow, production increased to 3050ml/day, and with cooling water flow, it further increased to 5000ml/day. Despite the increased cost of the water cooling system, the increased output resulted in the cost of distilled water being cut in roughly half. Diurnal variations of a few important parameters are observed during field experiments such as water temperature, cover temperature, air temperature, ambient temperature and distillate output

Efficient E-Wastage Management in Information Technology for Sustainable Growth

The exponential growth of manufacturing industry is mainly driven by electronic industry which in turn produces e wastage as a by-product. The term "waste" is defined for materials, objects which is dumped by the customer rather than recycled, which includes residue from reuse and recycling operations. Electronic waste [1], or e-waste, is a term coined for electronic products that have turned as unnecessary, non-working, unusable or have become obsolete, and have effectively reached the end of their functional life. As the technology is growing at high speed, much of electronic devices become e-waste after a very short period from the day when the product is manufactured. In fact, the collection of old electronic substances is the largest contributor to the e-waste. E-waste consists of computers, laptops and mobile phones with obsolete hardware and software, monitors, printers, TVs, CD players etc. The management of e-waste is essential and need of the hour as electronic devices often contain dangerous substances which can be life threatening and environmental unfriendly. Solving the e–waste management problem begins with schooling and the habit changes as a result of gaining the knowledge. In this paper an attempt is made to address the problem by an efficient work flow model

Design of vehicle using Ackermann steering with IoT concept

Electric vehicles are becoming more demanding these days. In this project the possibility of using Ackerman steering with electric drive servomotor is explained. Scalability is the advantage of using this mechanism which can be adopted for four-wheel vehicle system as well. The objective of this project is to do design a system using Ackerman steering which determines the maximum and minimum angle of the turning of the wheels. It also avoids the front tire slippage and activates pure rolling. Ackermann steering geometry is a geometric arrangement of linkages in the steering of a car or other vehicle designed to solve the problem of wheels on the inside and outside of a turn needing to trace out circles of different radii. The geometrical solution to this is for all wheels to have their axles arranged as radii of circles with a common centre point. As the rear wheels are fixed, this centre point must be on a line extended from the rear axle. Intersecting the axes of the front wheels on this line as well requires that the inside front wheel be turned, when steering, through a greater angle than the outside wheel. The microcontroller used in this project is ATMega16 andlmax232 is used for the serial data transmission

PFP-LHCINCA: Pyramidal Fixed-Size Patch-Based Feature Extraction and Chi-Square Iterative Neighborhood Component Analysis for Automated Fetal Sex Classification on Ultrasound Images.

OBJECTIVES: Fetal sex determination with ultrasound (US) examination is indicated in pregnancies at risk of X-linked genetic disorders or ambiguous genitalia. However, misdiagnoses often arise due to operator inexperience and technical difficulties while acquiring diagnostic images. We aimed to develop an efficient automated US-based fetal sex classification model that can facilitate efficient screening and reduce misclassification. METHODS: We have developed a novel feature engineering model termed PFP-LHCINCA that employs pyramidal fixed-size patch generation with average pooling-based image decomposition, handcrafted feature extraction based on local phase quantization (LPQ), and histogram of oriented gradients (HOG) to extract directional and textural features and used Chi-square iterative neighborhood component analysis feature selection (CINCA), which iteratively selects the most informative feature vector for each image that minimizes calculated feature parameter-derived k-nearest neighbor-based misclassification rates. The model was trained and tested on a sizeable expert-labeled dataset comprising 339 males' and 332 females' fetal US images. One transverse fetal US image per subject zoomed to the genital area and standardized to 256 × 256 size was used for analysis. Fetal sex was annotated by experts on US images and confirmed postnatally. RESULTS: Standard model performance metrics were compared using five shallow classifiers-k-nearest neighbor (kNN), decision tree, naïve Bayes, linear discriminant, and support vector machine (SVM)-with the hyperparameters tuned using a Bayesian optimizer. The PFP-LHCINCA model achieved a sex classification accuracy of ≥88% with all five classifiers and the best accuracy rates (>98%) with kNN and SVM classifiers. CONCLUSIONS: US-based fetal sex classification is feasible and accurate using the presented PFP-LHCINCA model. The salutary results support its clinical use for fetal US image screening for sex classification. The model architecture can be modified into deep learning models for training larger datasets

Convergent recombination suppression suggests role of sexual selection in guppy sex chromosome formation.

Sex chromosomes evolve once recombination is halted between a homologous pair of chromosomes. The dominant model of sex chromosome evolution posits that recombination is suppressed between emerging X and Y chromosomes in order to resolve sexual conflict. Here we test this model using whole genome and transcriptome resequencing data in the guppy, a model for sexual selection with many Y-linked colour traits. We show that although the nascent Y chromosome encompasses nearly half of the linkage group, there has been no perceptible degradation of Y chromosome gene content or activity. Using replicate wild populations with differing levels of sexually antagonistic selection for colour, we also show that sexual selection leads to greater expansion of the non-recombining region and increased Y chromosome divergence. These results provide empirical support for longstanding models of sex chromosome catalysis, and suggest an important role for sexual selection and sexual conflict in genome evolution

Effect of multiwalled carbon nanotubes on improvement of fracture toughness of spark-plasma-sintered yttria-stabilized zirconia nanocomposites

Highly dense yttria-stabilized zirconia (YSZ) nano-ceramics reinforced with TC-CVD-synthesized multiwall carbon nanotubes (MWCNTs) were fabricated using spark plasma sintering at a temperature of 1350°C, the heating rate of 100 °C/min and pressure of 50MPa with a dwell time of 10 minutes. The identical parameters were utilized for fabricating composites with a varying weight ratio of YSZ and MWNCTs. The samples were characterized for their phase transformation, microstructure and elemental composition using x-ray diffraction (XRD), scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS). The physical and mechanical properties such as density, porosity, hardness, fracture toughness and wear were also investigated. The increase in the MWCNTs concentration has resulted in the deterioration of the hardness due to CNT agglomerations. The wear resistance of the composites revealed MWNCTs enhanced wear resistance of YSZ nanocomposite by undergoing MWNCTs pull-out and crack branching mechanisms. Further indentation method and single-beam V-notch beam (SEVNB) methods were utilized to study the effect of MWCNTs on the fracture toughness of the nanocomposites. The fracture toughness of YC1 (6.58 ± 0.3 MPa m1/2) was 21% higher than the YSZ (5.21 ± 0.2 MPa m1/2) due to the toughening mechanisms attributable to crack deflection, branching and bridging of MWCNTs

MOLECULAR CHARACTERIZATION OF MMP-9 GENE IN CYSTIC FLUID OF CYSTICERCUS TENUICOLLIS BY REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION (RT-PCR)

ABSTRACT The present study was carried out to confirm the presence of MMP-9 gene in the cystic fluid of Cysticercus tenuicollis. Collection of cyst was made from goats slaughtered at local abattoirs and washed thoroughly with PBS (pH 7.4). The cystic fluid was aspirated, centrifuged at 10,000 rpm for 15 minutes at 4°C and the supernatants were used for further study. Total RNA was isolated from the cystic fluid of Cysticercus tenuicollis. The total cellular RNA was obtained from 400 µL of cystic fluid was 0.214 µg and the concentration of the RNA was 0.535 µg/mL. The RT-PCR product, 204 bp propeptide domain of MMP-9 was detected through agarose gel electrophoresis, which confirmed the presence of MMP-9 in the cystic fluid of Cysticercus tenuicolli

Automated detection of pain levels using deep feature extraction from shutter blinds-based dynamic-sized horizontal patches with facial images.

Pain intensity classification using facial images is a challenging problem in computer vision research. This work proposed a patch and transfer learning-based model to classify various pain intensities using facial images. The input facial images were segmented into dynamic-sized horizontal patches or "shutter blinds". A lightweight deep network DarkNet19 pre-trained on ImageNet1K was used to generate deep features from the shutter blinds and the undivided resized segmented input facial image. The most discriminative features were selected from these deep features using iterative neighborhood component analysis, which were then fed to a standard shallow fine k-nearest neighbor classifier for classification using tenfold cross-validation. The proposed shutter blinds-based model was trained and tested on datasets derived from two public databases-University of Northern British Columbia-McMaster Shoulder Pain Expression Archive Database and Denver Intensity of Spontaneous Facial Action Database-which both comprised four pain intensity classes that had been labeled by human experts using validated facial action coding system methodology. Our shutter blinds-based classification model attained more than 95% overall accuracy rates on both datasets. The excellent performance suggests that the automated pain intensity classification model can be deployed to assist doctors in the non-verbal detection of pain using facial images in various situations (e.g., non-communicative patients or during surgery). This system can facilitate timely detection and management of pain

Design of bio-nanosystems for oral delivery of functional compounds

Nanotechnology has been referred to as one of the most interesting topics in food technology due to the potentialities of its use by food industry. This calls for studying the behavior of nanosystems as carriers of biological and functional compounds aiming at their utilization for delivery, controlled release and protection of such compounds during food processing and oral ingestion. This review highlights the principles of design and production of bio-nanosystems for oral delivery and their behavior within the human gastrointestinal (GI) tract, while providing an insight into the application of reverse engineering approach to the design of those bio-nanosystems. Nanocapsules, nanohydrogels, lipid-based and multilayer nanosystems are discussed (in terms of their main ingredients, production techniques, predominant forces and properties) and some examples of possible food applications are given. Phenomena occurring in in vitro digestion models are presented, mainly using examples related to the utilization of lipid-based nanosystems and their physicochemical behavior throughout the GI tract. Furthermore, it is shown how a reverse engineering approach, through two main steps, can be used to design bio-nanosystems for food applications, and finally a last section is presented to discuss future trends and consumer perception on food nanotechnology.Miguel A. Cerqueira, Ana C. Pinheiro, Helder D. Silva, Philippe E. Ramos, Ana I. Bourbon, Oscar L. Ramos (SFRH/BPD/72753/2010, SFRH/BD/48120/2008, SFRH/BD/81288/2011, SFRH/BD/80800/2011, SFRH/BD/73178/2010 and SFRH/BPD/80766/2011, respectively) are the recipients of a fellowship from the Fundacao para a Ciencia e Tecnologia (FCT, POPH-QREN and FSE Portugal). Maria L. Flores-Lopez thanks Mexican Science and Technology Council (CONACYT, Mexico) for PhD fellowship support (CONACYT Grant number: 215499/310847). The support of EU Cost Actions FA0904 and FA1001 is gratefully acknowledged