Multivariate statistical analysis of some traits of bread wheat for breeding under rainfed conditions

In order to evaluate several agro-morphological traits in 56 wheat genotypes, an experiment based on randomized complete block design with three replications was carried out. Principal component analysis (PCA) and factor analysis were used for understanding the data structure and trait relations. The PCA showed that five components explained 69% of the total variation among traits. The first PCA was assigned 28% and the second PCA was assigned 13% of total variation among traits. The first PCA was more related to grain number, floret number, tiller number, stem diameter, leaf width and spikelet number. Therefore, the selection may be done according to the first component and it was helpful for a good breeding program for development of high yielding cultivars. The correlation coefficient between any two traits is approximated by the cosine of the angle between their vectors in the plot of the first two PCAs and the most prominent relations were between grain diameter and grain yield; and between grain length and 1,000 seed weight. The factor analysis divided the eighteen traits into five factors and the first factor included stem diameter, leaf width, tiller number, spike length, floret number, spikelet number, grain number and grain yield. The second factor was composed of some morphological traits and indicated the importance of the grain diameter, grain length, 1,000 seed weight and grain yield. The two PCA and factor analysis methods were found to give complementary information, and therefore such knowledge would assist the plant breeders in making their selection. In other words, this data reduction would let the plant breeder reduce field costs required to obtain the genetic parameter estimates necessary to construct selection indices

Multi-Tenancy in Decentralised IoT

International audience—Since the Internet of Things (IoT) has become more and more important, new solutions should be proposed in order to adapt the specificities introduced by this interconnection of the physical world (Sensors and Actuators) and the public networks (The Internet). Some of these solutions use a Cloud approach. The amount of data collected by Things rises the interest of the Big-Data community. The main design chosen for the IoT is the centralisation of all data collected and a central treatment of these data. But another approach is to decentralise the data processing, in order to dramatically lighten the network and limit the exchange to a reduced set of semantic messages. This decentralised architecture has assets in term of confidentiality, data ownership and energy saving. But then, how to share things among users, and keep the control? If computing is done on each object, how a user can integrate public objects in its own application, as these objects are used by some other users? How to organise access to the sensors and actuators provided by these objects? This paper proposes an architecture that gives multi-tenant capability to IoT decentralised applications, in which users are using and sharing their objects. A generic architecture is described, and integrated in our IoT platform as an example

BeC3: a Crowd-Centric Composition Testbed for the Internet of Things

International audience—With the emergence of IoT devices, such as smart-phones, temperature and light devices, etc., the ways of creating IoT applications has changed. IoT applications are often created and managed by a set of central points (orchestration) for different users. However, users may desire to create and manage their own applications based on their own logic in a decentralized way (choreography). Hence, in this paper, we demonstrate BeC3, a tool for creating and deploying Crowd-based applications using the choreography method. BeC3 is based on D-LiTE, a lightweight RESTful virtual machine designed for IoT devices. The users could then compose the D-LiTe-enabled devices using the BeC3 tool. BeC3 provides a simple and intuitive way to compose interaction between IoT components

Prenatal diagnosis and postnatal findings of cloacal malformation: a case report

Introduction: Cloacal malformation is an extremely rare fetal pathological condition but an important anomaly that presents as a variety of defects. It predominantly affects females, with prevalence of 1 in 50,000 births. Prenatal ultrasonography usually showed oligohydramnios and the fetus having a large cystic mass in the lower abdomen with a single septum, bilateral hydronephrosis, ambiguous genitalia and a single umbilical artery. Postnatal finding including ambiguous genitalia and rectal atresia with a single perineal opening. Case report: The purpose of this case series was to illustrate characteristic prenatal sonographic features of cloacal malformation by using imaging from 3 cases seen in all academic centers to augment published data. The imaging feature common to all cases was a central cystic pelvic mass containing a characteristic fluid-fluid level. Conclusions: The children were followed at regular intervals by an urologist, surgeon and nephrologist throughout life. Medical teams were committed to providing long-term care for children with cloacal anomalies

High frequency of vancomycin resistant Enterococcus faecalis in children: an alarming concern

Introduction: Enterococcus spp. is considered as important etiological agents of nosocomial infections. However, a little is known about the epidemiology of vancomycin resistant Enterococcus faecalis (VREF). The aim of this study was to investigate the frequency of  VREF and detecting of two prevalent resistance genes (vanA, vanB) in pediatric population in an Iranian referral pediatric Hospital.Material and methods: During January 2013 to December 2013, 180 E. faecalis was isolated from clinical samples of hospitalized children at Children Medical Center Hospital, tertiary care and teaching hospital in Tehran, Iran. Antimicrobial testing was performed by Kirby-Bauer disk diffusion and E-test method according to Clinical Laboratories Standards Institute (CLSI). Two prevalent resistance genes (vanA, vanB) were investigated in VREF isolates.Results: Cephalosporin resistance was found in majority of E. faecalis isolates. There were no linezolid-resistant E. faecalis among all isolates. Teicoplanin resistance was observed in 13.8% of E. faecalis (n=25). MIC ≥32 µg/ml for vancomycin was found in 29 isolates (16%) and vanA gene was detected in 21 (72%) VREF strains, while vanB gene was not detected in any of these isolates. The mortality rate of all cases was 3.4% and 10% of patients with VREF infection died.Conclusion: This study reveals high rate of multidrug-resistant as well as vancomycin resistance in E. faecalis strains. Thus periodic surveillance of antibacterial susceptibilities is recommended to detect emerging resistance.

Detecting the Presence of COVID-19 Vaccination Hesitancy from South African Twitter Data Using Machine Learning

Very few social media studies have been done on South African user-generated content during the COVID-19 pandemic and even fewer using hand-labelling over automated methods. Vaccination is a major tool in the fight against the pandemic, but vaccine hesitancy jeopardizes any public health effort. In this study, sentiment analysis on South African tweets related to vaccine hesitancy was performed, with the aim of training AI-mediated classification models and assessing their reliability in categorizing UGC. A dataset of 30000 tweets from South Africa were extracted and hand-labelled into one of three sentiment classes: positive, negative, neutral. The machine learning models used were LSTM, bi-LSTM, SVM, BERT-base-cased and the RoBERTa-base models, whereby their hyperparameters were carefully chosen and tuned using the WandB platform. We used two different approaches when we pre-processed our data for comparison: one was semantics-based, while the other was corpus-based. The pre-processing of the tweets in our dataset was performed using both methods, respectively. All models were found to have low F1-scores within a range of 45$\%$-55$\%$, except for BERT and RoBERTa which both achieved significantly better measures with overall F1-scores of 60$\%$ and 61$\%$, respectively. Topic modelling using an LDA was performed on the miss-classified tweets of the RoBERTa model to gain insight on how to further improve model accuracy

Comparison of diagnosis of VUR nephropathy by urinary level of ceruloplasmin with DMSA-Scan in children

Background: Children with vesicoureteral reflux (VUR) are at risk of recurrent pyelonephritis, kidney scars, hypertension, and renal failure. Currently, VUR complications can be diagnosed by different imaging methods such as sonography, intravenous pyelography and dimercaptosuccinic acid (DMSA) scan, having certain limitations. Urinary level of ceruloplasmin (Cp) might be an effective non-radiological method. The aim of this study was to compare the urinary level of Cp with DMSA scan in the diagnosis of VUR complications. Methods: The present cross-sectional study was conducted in Pediatric Research Center of Qom University of Medical Sciences and Health Services, Iran. Subjects consisted of 61 children with VUR, diagnosed by voiding cystoureterography (VCUG) and undergone either DMSA scan or urine Cp measurement. VUR stages and complications of the cases were evaluated using serum and urinary renal parameters. Data were analyzed using SPSS 22. Results: Among them, 80.3% were girls with a mean age of 7.2±3.8 years. Mean Cp urine level was statistically different between VUR sides in DMSA scan (unilateral: 269.56 vs. bilateral: 450.42 µg/dL) (P=0.034, r =0.273), but was not statistically different among various VUR degrees (P=0.102, r=0.211), different ages and genders (P>0.05). Conclusions: Urinary level of Cp was not statistically different among VUR degrees, but was higher in bilateral VUR cases, indicating Cp can be used as a safe, non-invasive, and cheap measurement tool for screening test. Further studies are required to confirm Cp as an effective method