Microcontroller Based Smart Energy Meter with Data Logger System

Recent advancements in power system ensure that energy being generated is efficiently delivered to meet the growing demand for electricity in many countries. However, determining the proper energy usage by the consumers has become a major challenge to utility companies. Metering is an important aspect of electricity distribution, it helps to accurately measure and bill customers for their electricity consumption. In this project, a prototype for an electricity monitoring system using ATMEGA328P as the microcontroller was proposed and developed. The display parameter values are voltage, current, power factor, active and apparent power. A ZMPT101B voltage sensor is used to measure the AC voltage, while an SCT-013 100A current sensor is used to measure the AC current flowing through meter. In addition, a rotary encoder is used to converts the rotational motion into an electrical signal which is used to measure and control various parameters in a system. Real time clock module is based on an internal clock that generates pulses at a fixed frequency. variety of tests to verify that the system can handle the expected volume of data, can communicate reliably and that can secure data were performed such as logging the energy data to memory card, testing input sensors, The voltage and current errors for the energy meter are ±0.1% and ±0.3%, respectively while the power value error of ±0.04%, which is acceptable for most metering devices, The use of smart metering system lead to a more sustainable and efficient energy system for achieving a more sustainable future.       &nbsp

OPTIMAL ROUTE DETERMINATION FOR POSTAL DELIVERY USING ANT COLONY OPTIMIZATION ALGORITHM

There are a lot of optimization challenges in the world, as we all know. The vehicle routing problem is one of the more complex and high-level problems. Vehicle Routing Problem is a real-life problem in the Postal Delivery System logistics and, if not properly attended to, can lead to wastage of resources that could have been directed towards other things. Several studies have been carried out to tackle this problem using different techniques and algorithms. This study used the Ant Colony Optimization Algorithm along with some powerful APIs to find an optimal route for the delivery of posts to customers in a Postal Delivering System. When Ant Colony Optimization Algorithm is used to solve the vehicle routing problem in transportation systems, each Ant's journey is mere “part” of a feasible solution. To put it in another way, numerous ants' pathways might make up a viable solution. Routes are determined for a delivery vehicle, with the objective of minimizing customer waiting time and operation cost. Experimental results indicate that the solution is optimal and more accurat

A HYBRIDIZED ENCRYPTION SCHEME BASED ON ELLIPTIC CURVE CRYPTOGRAPHY FOR SECURING DATA IN SMART HEALTHCARE

Recent developments in smart healthcare have brought us a great deal of convenience. Connecting common objects to the Internet is made possible by the Internet of Things (IoT). These connected gadgets have sensors and actuators for data collection and transfer. However, if users' private health information is compromised or exposed, it will seriously harm their privacy and may endanger their lives. In order to encrypt data and establish perfectly alright access control for such sensitive information, attribute-based encryption (ABE) has typically been used. Traditional ABE, however, has a high processing overhead. As a result, an effective security system algorithm based on ABE and Fully Homomorphic Encryption (FHE) is developed to protect health-related data. ABE is a workable option for one-to-many communication and perfectly alright access management of encrypting data in a cloud environment. Without needing to decode the encrypted data, cloud servers can use the FHE algorithm to take valid actions on it. Because of its potential to provide excellent security with a tiny key size, elliptic curve cryptography (ECC) algorithm is also used. As a result, when compared to related existing methods in the literature, the suggested hybridized algorithm (ABE-FHE-ECC) has reduced computation and storage overheads. A comprehensive safety evidence clearly shows that the suggested method is protected by the Decisional Bilinear Diffie-Hellman postulate. The experimental results demonstrate that this system is more effective for devices with limited resources than the conventional ABE when the system’s performance is assessed by utilizing standard model

Influence of neighborhood environment and social support on physical activity among patients with diabetes mellitus

This study was aimed to determine the relationship of physical activity (PA) with the neighborhood environment and social support for PA among patients with diabetes mellitus (DM). A total of 193 consenting individuals with DM attending endocrinology clinic in a Nigerian tertiary hospital participated in this cross-sectional study. The international physical activity questionnaire short form, physical activity neighborhood environment scale (PANES), and physical activity and social support scale (PASSS) were used to assess the PA level (low, moderate, and high), neighborhood environment and social support for PA, respectively. The results of bivariate analyses showed that all elements of built environment and social support were significantly associated with PA. Regression model analyses indicate that PANES score was associated with moderate (adjusted odds ratio [aOR]: 10.76; 95% confidence interval [CI]: 3.82-30.32) to high (aOR: 45.73; 95% CI: 12.14-172.27) PA. In addition, easy access to quality walking facilities (aOR: 46.53; 95% CI: 3.89-557.32; aOR: 46.13; 95% CI: 2.65-802.40) and easy access to recreation infrastructure (aOR: 46.89; 95% CI: 3.95-487.83; aOR: 17.99; 95% CI: 1.28-252.98) were associated with moderate to high PA, respectively, while safety from crime (aOR: 0.21; 95% CI: 0.07-0.64) and easy access to services and shops (aOR: 21.90; 95% CI: 1.83-262.59) were associated with moderate and high PA. Informational social support was associated with moderate PA (aOR: 1.44; 95% CI: 1.04-2.00). In conclusion, the neighborhood environmental and social support factors were associated with the PA activity level among Nigerian patients with DM

Awareness of warning signs among suburban Nigerians at high risk for stroke is poor: A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Although stroke is a leading cause of morbidity and mortality in Nigeria, there is no information on awareness of its warning signs. This study was designed to assess awareness of stroke warning signs in Nigerians at increased risk.</p> <p>Methods</p> <p>A hospital-based cross-sectional study conducted at Irrua Specialist Teaching Hospital, in southern Nigeria. Patients with a diagnosis of hypertension, diabetes or both were interviewed for the warning signs of stroke in the outpatient clinic by trained interviewers. The main outcome measure was ability to identify at least one stroke warning sign.</p> <p>Results</p> <p>There were 225 respondents with a mean age of 58.0 ± 11.7 years. Only 39.6% could identify at least one stroke warning sign while the commonest sign identified was sudden unilateral limb weakness (24.4%). On multivariate logistic regression analysis, male sex (β = 0.26, 95% CI = 0.14–0.39, p < 0.001) and 11 or more years of education (β = 0.16, 95% CI = 0.03–0.29, p = 0.02) emerged the independent predictors of ability to identify at least one warning sign.</p> <p>Conclusion</p> <p>Awareness of stroke warning signs is poor among Nigerians at increased risk for the disease. Efforts should be made to improve on the level of awareness through aggressive health education.</p

Modulation of Bax and mTOR for Cancer Therapeutics.

A rationale exists for pharmacologic manipulation of the serine (S)184 phosphorylation site of the proapoptotic Bcl2 family member Bax as an anticancer strategy. Here, we report the refinement of the Bax agonist SMBA1 to generate CYD-2-11, which has characteristics of a suitable clinical lead compound. CYD-2-11 targeted the structural pocket proximal to S184 in the C-terminal region of Bax, directly activating its proapoptotic activity by inducing a conformational change enabling formation of Bax homooligomers in mitochondrial membranes. In murine models of small-cell and non-small cell lung cancers, including patient-derived xenograft and the genetically engineered mutant KRAS-driven lung cancer models, CYD-2-11 suppressed malignant growth without evident significant toxicity to normal tissues. In lung cancer patients treated with mTOR inhibitor RAD001, we observed enhanced S184 Bax phosphorylation in lung cancer cells and tissues that inactivates the propaoptotic function of Bax, contributing to rapalog resistance. Combined treatment of CYD-2-11 and RAD001 in murine lung cancer models displayed strong synergistic activity and overcame rapalog resistanc

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment