Entropy per rapidity in Pb-Pb central collisions using Thermal and Artificial neural network(ANN) models at LHC energies

The entropy per rapidity $d S/d y$ produced in central Pb-Pb ultra-relativistic nuclear collisions at LHC energies is calculated using experimentally observed identified particle spectra and source radii estimated from Hanbury Brown-Twiss (HBT) for particles, $\pi$, $k$, $p$, $\Lambda$, $\Omega$, and $\bar{\Sigma}$, and $\pi$, $k$, $p$, $\Lambda$ and $K_s^0$ at $\sqrt{s}$ $=2.76$ and $5.02$ TeV, respectively. Artificial neural network (ANN) simulation model is used to estimate the entropy per rapidity $d S/d y$ at the considered energies. The simulation results are compared with equivalent experimental data, and good agreement is achieved. A mathematical equation describes experimental data is obtained. Extrapolating the transverse momentum spectra at $p_T$ $=0$ is required to calculate $d S/d y$ thus we use two different fitting functions, Tsallis distribution and the Hadron Resonance Gas (HRG) model. The success of ANN model to describe the experimental measurements will imply further prediction for the entropy per rapidity in the absence of the experiment

Texture analysis of magnetic resonance images of rat muscles during atrophy and regeneration

OBJECTIVES: The goals of the current study were (i) to introduce texture analysis on magnetic resonance imaging (MRI-TA) as a noninvasive method of muscle investigation that can discriminate three muscle conditions in rats; these are normal, atrophy and regeneration; and (ii) to show consistency between MRI-TA results and histological results of muscle type 2 fibers\u27 cross-sectional area. METHOD: Twenty-three adult female Wistar rats were randomized into (i) control (C), (ii) immobilized (I) and (iii) recovering (R) groups. For the last two groups, the right hind limb calf muscles were immobilized against the abdomen for 14 days; then, the hind limb was remobilized only for the R group for 40 days. At the end of each experimental period, MRI was performed using 7-T magnet Bruker Avance DRX 300 (Bruker, Wissembourg); T1-weighted MRI acquisition parameters were applied to show predominantly muscle fibers. Rats were sacrificed, and the gastrocnemius muscle (GM) was excised immediately after imaging. (A) Histology: GM type 2 fibers (fast twitch) were selectively stained using the adenosine triphosphatase (ATPase) technique. The mean cross-sectional areas were compared between the three groups. (B) Image analysis: regions of interest (ROIs) were selected on GM MR images where statistical methods of texture analysis were applied followed by linear discriminant analysis (LDA) and classification. RESULTS: Histological analysis showed that the fibers\u27 mean cross-sectional areas on GM transversal sections represented a significant statistical difference between I and C rats (ANOVA, P<.001) as well as between R and I rats (ANOVA, P<.01), but not between C and R rats. Similarly, MRI-TA on GM transversal images detected different texture for each group with the highest discrimination values (Fisher F coefficient) between the C and I groups, as well as between I and R groups. The lowest discrimination values were found between C and R groups. LDA showed three texture classes schematically separated. CONCLUSION: Quantitative results of MRI-TA were statistically consistent with histology. MRI-TA can be considered as a potentially interesting, reproducible and nondestructive method for muscle examination during atrophy and regeneration

Semi-supervised multi-layered clustering model for intrusion detection

A Machine Learning (ML) -based Intrusion Detection and Prevention System (IDPS) requires a large amount of labeled up-to-date training data, to effectively detect intrusions and generalize well to novel attacks. However, labeling of data is costly and becomes infeasible when dealing with big data, such as those generated by IoT (Internet of Things) -based applications. To this effect, building a ML model that learns from non- or partially-labeled data is of critical importance. This paper proposes a novel Semi-supervised Multi-Layered Clustering Model (SMLC) for network intrusion detection and prevention tasks. The SMLC has the capability to learn from partially labeled data while achieving a comparable detection performance to supervised ML-based IDPS. The performance of the SMLC is compared with well-known supervised ensemble ML models, namely, RandomForest, Bagging, and AdaboostM1 and a semi-supervised model (i.e., tri-training) on a benchmark network intrusion dataset, the Kyoto 2006+. Experimental results show that the SMLC outperforms all other models and can achieve better detection accuracy using only 20% labeled instances of the training data

Molecular diagnosis in recessive pediatric neurogenetic disease can help reduce disease recurrence in families.

BackgroundThe causes for thousands of individually rare recessive diseases have been discovered since the adoption of next generation sequencing (NGS). Following the molecular diagnosis in older children in a family, parents could use this information to opt for fetal genotyping in subsequent pregnancies, which could inform decisions about elective termination of pregnancy. The use of NGS diagnostic sequencing in families has not been demonstrated to yield benefit in subsequent pregnancies to reduce recurrence. Here we evaluated whether genetic diagnosis in older children in families supports reduction in recurrence of recessive neurogenetic disease.MethodsRetrospective study involving families with a child with a recessive pediatric brain disease (rPBD) that underwent NGS-based molecular diagnosis. Prenatal molecular testing was offered to couples in which a molecular diagnosis was made, to help couples seeking to prevent recurrence. With this information, families made decisions about elective termination. Pregnancies that were carried to term were assessed for the health of child and mother, and compared with historic recurrence risk of recessive disease.ResultsBetween 2010 and 2016, 1172 families presented with a child a likely rPBD, 526 families received a molecular diagnosis, 91 families returned to the clinic with 101 subsequent pregnancies, and 84 opted for fetal genotyping. Sixty tested negative for recurrence for the biallelic mutation in the fetus, and all, except for one spontaneous abortion, carried to term, and were unaffected at follow-up. Of 24 that genotyped positive for the biallelic mutation, 16 were electively terminated, and 8 were carried to term and showed features of disease similar to that of the older affected sibling(s). Among the 101 pregnancies, disease recurrence in living offspring deviated from the expected 25% to the observed 12% ([95% CI 0·04 to 0·20], p = 0·011).ConclusionsMolecular diagnosis in an older child, coupled with prenatal fetal genotyping in subsequent pregnancies and genetic counselling, allows families to make informed decisions to reduce recessive neurogenetic disease recurrence

Centre-level variation in speech outcome and interventions, and factors associated with poor speech outcomes in 5-year-old children with non-syndromic unilateral cleft lip and palate:the Cleft Care UK study. Part 4

Objectives: To investigate centre-level variation in speech intervention and outcome and factors associated with a speech disorder in children in Cleft Care UK (CCUK). Setting and Sample Population: Two hundred and sixty-eight 5-year-old British children with non-syndromic unilateral cleft lip and palate recruited to CCUK. Materials and Methods: Centre-based therapists undertook audio-video recordings. Perceptual analysis was undertaken using the CAPS-A tool. Speech outcomes were based on structural and articulation scores, and intelligibility/distinctiveness. Between-centre variation in treatment and outcomes were examined using multilevel models. These models were extended to estimate the association between a range of factors (hearing loss, speech intervention, fistula, secondary speech surgery for velopharyngeal insufficiency, socio-economic status, gender, and parental happiness with speech) and speech outcomes. Results: There was centre-level variation in secondary speech surgery, speech intervention, structure and intelligibility outcomes. Children with a history of speech intervention had a lower odds of poor intelligibility/distinctiveness, 0.1 (95% CI: 0.0-0.4). Parental concern was associated with a higher odds of poor intelligibility/distinctiveness, 13.2 (95% CI: 4.9-35.1). Poor speech outcomes were associated with a fistula, secondary speech surgery and history of hearing loss. Conclusions: Within the centralized service there is centre-level variation in secondary speech surgery, intervention and speech outcomes. These findings support the importance of early management of fistulae, effective management of velopharyngeal insufficiency and hearing impairment, and most importantly speech intervention in the preschool years. Parental concern about speech is a good indicator of speech status

Addition-Deletion Networks

We study structural properties of growing networks where both addition and deletion of nodes are possible. Our model network evolves via two independent processes. With rate r, a node is added to the system and this node links to a randomly selected existing node. With rate 1, a randomly selected node is deleted, and its parent node inherits the links of its immediate descendants. We show that the in-component size distribution decays algebraically, c_k ~ k^{-beta}, as k-->infty. The exponent beta=2+1/(r-1) varies continuously with the addition rate r. Structural properties of the network including the height distribution, the diameter of the network, the average distance between two nodes, and the fraction of dangling nodes are also obtained analytically. Interestingly, the deletion process leads to a giant hub, a single node with a macroscopic degree whereas all other nodes have a microscopic degree.Comment: 8 pages, 5 figure

Epidemiology of Stroke in the MENA Region: A Systematic Review.

Introduction: Stroke is a major burden on the health system due to high fatality and major disability in survivors. Whilst Stroke incidence has declined in the developed world, it continues to increase in developing nations, including the MENA (Middle East and North Africa) region. This may reflect different risk factors and strategies to treat and manage patients prior to and after Stroke. Methods: We have conducted a systematic review of the prevalence, incidence and mortality of Stroke in the 23 countries of MENA region following the PRISMA guidelines. Results: 8,874 published papers were retrieved through both PubMed and Embase. Of those, 38 studies were found to be eligible for inclusion in this review. Only thirteen countries in the MENA region had data points for the critical stroke parameters. Of these qualified studies, 14 were prospective, population-based studies. In the age-adjusted studies, incidence ranged widely between 16/100,000 in a prospective population-based in Iran to 162/100,000 in Libya. Age-adjusted prevalence was available only from Tunisia at 184/100,000. Mortality for all strokes from the eight countries reporting this measure found the 30 day-case fatality ranged from 9.3% in Qatar to 30% in Pakistan. Most stroke studies in the MENA region were small sized, hospital-based, lacked confidence intervals and did not provide prevalence and mortality figures. Conclusion: National policymakers, public health and medical care stakeholders need more reliable epidemiologic studies on Stroke from the MENA region to plan more effective preventive and therapeutic strategies

Small and medium-sized enterprises in the digital business sector

The chapter is a systematic literature review of fundamental theories about small and medium business (SME) success. The chapter examines how they specifically impact digital SMEs. The chapter examined six theories: dynamic capability view (DCV), composition-based view of firm growth (CBV), resourcebased view (RBV), resource dependence theory (RDT), upper echelon theory (UET), strategic contingency theory (SCT). The results showed that RBV, DCV, and UET become relevant in articulating the value inherent to the internal resources in SMEs (which render their capabilities dynamic). In contrast, the SCT framework and the RDT model show more significance in relation to uncertainty and contingency. CBV was found to be a more pertinent framework to predict the success of SMEs. The results support CBV’s hypothesis that SMEs (including digital SMEs) are able to be competitive without extensive resource advantage, too complicated technologies, or market power. The increased deployment of CBV can be advocated as a critical determinant of digital SME success

A wideband linear tunable CDTA and its application in field programmable analogue array

This document is the Accepted Manuscript version of the following article: Hu, Z., Wang, C., Sun, J. et al. ‘A wideband linear tunable CDTA and its application in field programmable analogue array’, Analog Integrated Circuits and Signal Processing, Vol. 88 (3): 465-483, September 2016. Under embargo. Embargo end date: 6 June 2017. The final publication is available at Springer via https://link.springer.com/article/10.1007%2Fs10470-016-0772-7 © Springer Science+Business Media New York 2016In this paper, a NMOS-based wideband low power and linear tunable transconductance current differencing transconductance amplifier (CDTA) is presented. Based on the NMOS CDTA, a novel simple and easily reconfigurable configurable analogue block (CAB) is designed. Moreover, using the novel CAB, a simple and versatile butterfly-shaped FPAA structure is introduced. The FPAA consists of six identical CABs, and it could realize six order current-mode low pass filter, second order current-mode universal filter, current-mode quadrature oscillator, current-mode multi-phase oscillator and current-mode multiplier for analog signal processing. The Cadence IC Design Tools 5.1.41 post-layout simulation and measurement results are included to confirm the theory.Peer reviewedFinal Accepted Versio