Analysis of Power Consumption in Base Station in Massive MIMO Systems

The concept of massive MIMO enables high quality of service, Efficiency, and scalability. Therefore, a dense network has been established to enable services using the massive MIMO. But rapidly increasing deployment of cellular base stations increases the electricity energy consumption and increases the green house effect. Therefore, the balance between energy efficiency and high network performance is expected from the communication infrastructure. In this paper, the energy efficiency of the massive MIMO systems has been investigated in mainly two key scenarios i.e. single cell configuration and multi-cell configuration. In order to conduct experiments MATLAB based simulator has been used. Additionally, with the increasing number of User Equipments (UEs) the simulation has been done. Finally the configured network has been used to measure the optimal combination of antenna and UEs and the optimal energy consumption. Additionally the experiment also demonstrates how the different preprocessing technique will influence the massive MIMO energy efficiency. Finally the conclusion has been drawn and the future work has been proposed

A Study on the Cytological Effects of Myrobalan (Fruit of \u3cem\u3eTerminalia chebula\u3c/em\u3e) in \u3cem\u3eAllium\u3c/em\u3e Tests

The present study was aimed to find the cytogenetic effects of myrobalan using Allium cepa as a model system. The onion bulbs were grown in the suspension of myrobalan in tap water at various concentrations (0.01, 0.10, 1.0, 10.0 and 30 mg/ml) for 96 hours. The mean root length, the colour of growing roots as well as the mitotic index and chromosomal aberrations were observed in the presence of myrolaban, in order to assess the cytological effects of myrobalan. The colour of growing roots was not affected at 0.01 and 0.1 mg/ml myrobalan concentrations, while it appeared pale at 1 mg and 10 mg/ml and black at 30 mg/ml concentrations. The root length was not affected at low concentrations of myrobalan, however, concentrations 1 mg/ml and above inhibited root length. The mitotic index, i.e., percentage of dividing root tip cells did not change at 0.01 and 0.10 mg/ml myrobalan concentration, however, it decreased significantly at 1 mg/ml and no mitosis was observed at 10 mg/ml and above, as the cells were seen in interphase with nucleoli. Abnormal mitosis and chromosomal aberrations like sticky chromosomes, C–mitosis, laggards, multipolar anaphases, chromosome bridge, micronucleated cells and polykaryocytes were not seen in dividing and non-dividing cells among roots grown at various concentrations of myrobalan. The present finding reveals that myrobalan does not exert any cytotoxic effects in Allium model

Prevention of Aluminium Chloride-Induced Mitodepression with Myrobalan (Fruit of \u3cem\u3eTerminalia chebula\u3c/em\u3e, Retz, Combretaceae) in \u3cem\u3eAllium cepa\u3c/em\u3e Model

Allium cepa bulbs were grown in pure tap water (Group I), in five concentrations (10-1M to 10-5M) of aluminium chloride in the absence (Group II) and in the presence (Group III) of myrobalan (fruit of Terminalia chebula) at a fix concentration of 0.10 mg/ml. Parameters of study were mean root length (after 72 hr) and mitotic index, abnormal mistosis, chromosomal aberrations and nucleolar morphology (after 48 hr). AlCl3 at all concentrations except at 10-1M where roots did not grew at all, significantly lowered root growth and mitotic index, effect appeared concentration dependent (Group II). In the presence of myrobalan (Group III) AlCl3 induced mitodepression could be checked significantly only at 10-4M and 10-5M. No morphological i.e. shape and colour changes, abnormal mitosis and any type of chromosomal aberrations could be detected in any group. AlCl3 induced hypertrophy of nucleoli at 10-2M-10-5M which could be remedied at 10-4M and 10-5M in (Group III). Probable toxic action of AlCl3 and possible protective role of myrobalan are discussed

A Novel Deep Learning Strategy for Classifying Different Attack Patterns for Deep Brain Implants

Deep brain stimulators (DBSs), a widely used and comprehensively acknowledged restorative methodology, are a type of implantable medical device which uses electrical stimulation to treat neurological disorders. These devices are widely used to treat diseases such as Parkinson, movement disorder, epilepsy, and psychiatric disorders. Security in such devices plays a vital role since it can directly affect the mental, emotional, and physical state of human bodies. In worst-case situations, it can even lead to the patient's death. An adversary in such devices, for instance, can inhibit the normal functionality of the brain by introducing fake stimulation inside the human brain. Nonetheless, the adversary can impair the motor functions, alter impulse control, induce pain, or even modify the emotional pattern of the patient by giving fake stimulations through DBSs. This paper presents a deep learning methodology to predict different attack stimulations in DBSs. The proposed work uses long short-term memory, a type of recurrent network for forecasting and predicting rest tremor velocity. (A type of characteristic observed to evaluate the intensity of the neurological diseases) The prediction helps in diagnosing fake versus genuine stimulations. The effect of deep brain stimulation was tested on Parkinson tremor patients. The proposed methodology was able to detect different types of emulated attack patterns efficiently and thereby notifying the patient about the possible attack. - 2013 IEEE.This work was supported by the Qatar National Research Fund (a member of Qatar Foundation) through NPRP under Grant 8-408-2-172.Scopu

Reno-Protective Effects of Angiotensin Receptor Blockers in Hypertensive Rodent Models: A systematic review.

Background and objective: Essential hypertension is a leading risk factor for chronic kidney disease, yet there is no conclusive evidence that lowering blood pressure alone improves renal outcome measures. Angiotensin-II receptor blockers (ARBs) proposed to have renal-protective effects independent of their antihypertensive effect. This systematic review of animal studies aims to collect available information from the published literature about the ARBs' consequences in murine models and analyze it in a structured way to provide a pre-clinical baseline for future analysis of similar clinical investigations. Methods: Following the PRISMA checklist, we conducted a systematic review for quasi non-randomized controlled studies using PubMed, Embase, Science-Direct, SCOPUS, and Google Scholar to determine the effects of ARBs on kidney functions. Eligible articles report the ARBs' effect on proteinuria, albuminuria, and glomerular filtration rate in murine models of hypertension. Outcomes were present as Mean ± Standard Error of Mean (SEM) with 95% confidence intervals (CIs). Results: This preliminary analysis includes ten out of 56 total eligible articles after quality assessment, reporting twelve renal outcome measures. Two studies showed improvement in CrCl versus one study showing no difference. Four out of five studies showed a reduction in proteinuria compared to the control group. All three studies showed a significant reduction in albuminuria compared to control and other antihypertensives. A study Evaluating BUN showed no difference. Nine outcomes supported the reno-protective effect of ARBs on different hypertensive models with various ARBs and different follow-up durations. Low dose valsartan 10mg/kg was showing no significant effect across two different studies. Conclusion: Preliminary results are encouraging. ARBs contribute to improvement in renal biomarkers in different hypertensive models regardless of their BP-lowering effect

Malic enzyme 1 absence in synovial sarcoma shifts antioxidant system dependence and increases sensitivity to ferroptosis induction with ACXT-3102

PURPOSE: To investigate the metabolism of synovial sarcoma (SS) and elucidate the effect of malic enzyme 1 absence on SS redox homeostasis. EXPERIMENTAL DESIGN: ME1 expression was measured in SS clinical samples, SS cell lines, and tumors from an SS mouse model. The effect of ME1 absence on glucose metabolism was evaluated utilizing Seahorse assays, metabolomics, and C13 tracings. The impact of ME1 absence on SS redox homeostasis was evaluated by metabolomics, cell death assays with inhibitors of antioxidant systems, and measurements of intracellular reactive oxygen species (ROS). The susceptibility of ME1-null SS to ferroptosis induction was interrogated in vitro and in vivo. RESULTS: ME1 absence in SS was confirmed in clinical samples, SS cell lines, and an SS tumor model. Investigation of SS glucose metabolism revealed that ME1-null cells exhibit higher rates of glycolysis and higher flux of glucose into the pentose phosphate pathway (PPP), which is necessary to produce NADPH. Evaluation of cellular redox homeostasis demonstrated that ME1 absence shifts dependence from the glutathione system to the thioredoxin system. Concomitantly, ME1 absence drives the accumulation of ROS and labile iron. ROS and iron accumulation enhances the susceptibility of ME1-null cells to ferroptosis induction with inhibitors of xCT (erastin and ACXT-3102). In vivo xenograft models of ME1-null SS demonstrate significantly increased tumor response to ACXT-3102 compared with ME1-expressing controls. CONCLUSIONS: These findings demonstrate the translational potential of targeting redox homeostasis in ME1-null cancers and establish the preclinical rationale for a phase I trial of ACXT-3102 in SS patients. See related commentary by Subbiah and Gan, p. 3408

Polygenic Risk Score for Cardiovascular Diseases in Artificial Intelligence Paradigm

Cardiovascular disease (CVD) related mortality and morbidity heavily strain society. The relationship between external risk factors and our genetics have not been well established. It is widely acknowledged that environmental influence and individual behaviours play a significant role in CVD vulnerability, leading to the development of polygenic risk scores (PRS). We employed the PRISMA search method to locate pertinent research and literature to extensively review artificial intelligence (AI)-based PRS models for CVD risk prediction. Furthermore, we analyzed and compared conventional vs. AI-based solutions for PRS. We summarized the recent advances in our understanding of the use of AI-based PRS for risk prediction of CVD. Our study proposes three hypotheses: i) Multiple genetic variations and risk factors can be incorporated into AI-based PRS to improve the accuracy of CVD risk predicting. ii) AI-based PRS for CVD circumvents the drawbacks of conventional PRS calculators by incorporating a larger variety of genetic and non-genetic components, allowing for more precise and individualised risk estimations. iii) Using AI approaches, it is possible to significantly reduce the dimensionality of huge genomic datasets, resulting in more accurate and effective disease risk prediction models. Our study highlighted that the AI-PRS model outperformed traditional PRS calculators in predicting CVD risk. Furthermore, using AI-based methods to calculate PRS may increase the precision of risk predictions for CVD and have significant ramifications for individualized prevention and treatment plans

A Pharmaceutical Paradigm for Cardiovascular Composite Risk Assessment Using Novel Radiogenomics Risk Predictors in Precision Explainable Artificial Intelligence Framework: Clinical Trial Tool

Cardiovascular disease (CVD) is challenging to diagnose and treat since symptoms appear late during the progression of atherosclerosis. Conventional risk factors alone are not always sufficient to properly categorize at-risk patients, and clinical risk scores are inadequate in predicting cardiac events. Integrating genomic-based biomarkers (GBBM) found in plasma/serum samples with novel non-invasive radiomics-based biomarkers (RBBM) such as plaque area, plaque burden, and maximum plaque height can improve composite CVD risk prediction in the pharmaceutical paradigm. These biomarkers consider several pathways involved in the pathophysiology of atherosclerosis disease leading to CVD.This review proposes two hypotheses: (i) The composite biomarkers are strongly correlated and can be used to detect the severity of CVD/Stroke precisely, and (ii) an explainable artificial intelligence (XAI)-based composite risk CVD/Stroke model with survival analysis using deep learning (DL) can predict in preventive, precision, and personalized (aiP3) framework benefiting the pharmaceutical paradigm.The PRISMA search technique resulted in 214 studies assessing composite biomarkers using radiogenomics for CVD/Stroke. The study presents a XAI model using AtheroEdgeTM 4.0 to determine the risk of CVD/Stroke in the pharmaceutical framework using the radiogenomics biomarkers.Our observations suggest that the composite CVD risk biomarkers using radiogenomics provide a new dimension to CVD/Stroke risk assessment. The proposed review suggests a unique, unbiased, and XAI model based on AtheroEdgeTM 4.0 that can predict the composite risk of CVD/Stroke using radiogenomics in the pharmaceutical paradigm

Identification and multi-environment validation of resistance to Fusarium oxysporum f. sp. ciceris in chickpea

Chickpea wilt incited by Fusarium oxysporum f. sp. ciceris is one of the most important constraints to chickpea production worldwide and best managed through host plant resistance. The aim of this work was to find new sources of resistance to wilt disease and validate their stability across different environments. One-hundred and twenty three lines with wilt incidence <10% were selected from preliminary evaluation of 948 lines including germplasm and breeding lines from the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) for wilt resistance in the sick plot during 2003/2004 crop season at ICRISAT, Patancheru, India. Sixty lines were selected for second round of evaluation (2005/2006) and from those 57 lines were selected for third round of evaluation (2006/2007). In order to validate resistance stability, a Chickpea Wilt Nursery was constituted with 27 lines (7 germplasm accessions, 19 breeding lines and a highly susceptible check) and further tested in multi-location experiment for wilt resistance at 9 locations in India for three years (2007/2008–2009/2010). Variability in wilt incidence due to genetic differences among the genotypes, among the environments, and that due to genotype × environment interaction was highly significant (P < 0.001). Although complete resistance across the locations was not found, the genotype and genotype × environment (GGE) biplot analyses allowed the selection of three breeding lines (ICCV 05527, ICCV 05528 and ICCV 96818) and one germplasm accession (ICC 11322) with moderate level of disease resistance and stable performance across the environments. Genotype × environment (G × E) interaction contributed 36.7% of total variation of the multi-environment evaluation, revealing instability of the phenotypic expression across environments. The identified resistant sources should be useful to chickpea disease resistance breeding programs

Gas-phase and particulate products from the atmospheric degradation of the organothiophosphorus insecticide chlorpyrifos-methyl

The phosphorothioate structure is highly present in several organophosphorus pesticides. However, there is insufficient information about its degradation process after the release to the atmosphere and the secondary pollutants formed. Herein, the atmospheric reaction of chlorpyrifos-methyl (o,o-dimethyl o-(3,5,6-trichloropyridin-2-yl) phosphorothioate), is described for semi-urban or rural locations. The photo-oxidation under low NOx conditions (5-55 ppbV) was reproduced in a large outdoor simulation chamber, observing a rapid degradation (lifetime<3.5 h). The formation of gaseous products and particulate matter (aerosol yield 2-8%) was monitored. The chemical composition of minor products (gaseous and particulate) was studied, identifying 15 multi-oxygenated derivatives. The most abundant products were ring-retaining molecules such as o,o-dimethyl o-(3,5,6-trichloropyridin-2-yl) phosphorothioate, dimethyl 3,5,6-trichloropyridin-2-yl phosphate, o-methyl o-(3,5,6-trichloropyridin-2-yl) hydrogen phosphorothioate, 3,5,6-trichloropyridin-2-yl dihydrogen phosphate, 3,5,6-trichloropyridin-2-ol, and 3,5,6-trichloropyridine-2,4-diol. An atmospheric degradation mechanism has been proposed based on an oxidation started with OH-nucleophilic attack to P=S bond. The results have been extrapolated to other organothiophosphorus molecules, such as malathion, parathion, diazinon and methidathion, among many others, to estimate their photo-oxidative degradation and the expected products.The authors wish to thank the EUPHORE staff and J.T.B. The authors wish to acknowledge Ministerio de Economia y Competitividad for IMPLACAVELES (CGL2013-49093-C2-1-R) and IMPESTAT (CGL2010-18474/CLI) projects, and Generalitat Valenciana for the DESESTRES- Prometeo II project. The Fundacion CEAM is partly supported by Generalitat Valenciana - Spain. EUPHORE instrumentation is partly funded by MINECO - Spain, through INNPLANTA Project: PCT-440000-2010-003 and the projects FEDER CEAM10-3E-1301 and CEAM10-3E-1302.Borrás García, EM.; Tortajada-Genaro, LA.; Ródenas, M.; Vera, T.; Coscollá, C.; Yusá, V.; Muñoz, A. (2015). Gas-phase and particulate products from the atmospheric degradation of the organothiophosphorus insecticide chlorpyrifos-methyl. Chemosphere. 138:888-894. https://doi.org/10.1016/j.chemosphere.2014.11.067S88889413