Recent results on event-by-event fluctuations in ALICE at the LHC

Non-statistical event-by-event fluctuations in relativistic heavy-ion collisions have been proposed as a probe of the phase transition of hadronic matter to a deconfined phase of quarks and gluons, the so-called Quark-Gluon Plasma. In a thermodynamical picture of the strongly interacting system formed in heavy-ion collisions, the dynamical fluctuations of net-charge, fluctuations of the mean transverse momentum, mean multiplicity and balance functions are related to the fundamental properties of the system, hence they may reveal information about the QCD phase transition. In this article, recent results on event-by-event measurements of net-charge fluctuations, the measurement of the balance function and mean transverse momentum fluctuations are discussed.Comment: 8 pages, 8 figures, Proceedings of 9th International Workshop on Critical Point and Onset of Deconfinement - CPOD2014,17-21 November 2014, ZiF (Center of Interdisciplinary Research), University of Bielefeld, German

Constructing probability density function of net-proton multiplicity distributions using Pearson curve method

The probability density functions of net-proton multiplicity distributions are constructed from the Beam Energy Scan results of the STAR experiment using the Pearson curve method for two different transverse momentum windows. The $6^{th}$ and $8^{th}$ order cumulants of net-proton multiplicity distributions are estimated from the constructed probability density functions. The beam energy dependence of $C_{6}/C_{2}$ and $C_{8}/C_{2}$ are found to be sensitive to the acceptance window. This method provides a unique opportunity to study the O(4) criticality near the chiral crossover transition and estimating the higher-order cumulants. In general, it is useful to determine the probability density function uniquely of a frequency data if the first four cumulants are known.Comment: 8 pages, 6 figures, text modifie

Data Aggregation and Security Issues in Wireless Sensor Networks:A Survey

Wireless sensor networks (WSNs) are normally composed of low powered, inexpensive device that is constrained in terms of memory, computation and communication. To reduce communication overhead and resource consumption in WSN, data aggregation is used to increase network lifetime. Hence, the design of an efficient data aggregation protocol is an important issues and inherently challenging task of robust WSN. In this paper, various types of Data Aggregation in WSN, security issues are studied and also author presented possible key research issues of WSN data aggregation

Detection of Sybil attack in vehicular ad hoc networks by analyzing network performance

Vehicular ad hoc network (VANET) is an emerging technology which can be very helpful for providing safety and security as well as for intelligent transportation services. But due to wireless communication of vehicles and high mobility it has certain security issues which cost the safety and security of people on the road. One of the major security concerns is the Sybil attack in which the attacker creates dummy identities to gain high influence in the network that causes delay in some services and fake voting in the network to misguide others. The early detection of this attack can prevent people from being misguided by the attacker and save them from getting into any kind of trap. In this research paper, Sybil attack is detected by first applying the Poisson distribution algorithm to predict the traffic on the road and in the second approach, analysis of the network performance for packet delivery ratio (PDR) is performed in malign and benign environment. The simulation result shows that PDR decreases in presence of fake vehicles in the network. Our approach is simple and effective as it does not require high computational overhead and also does not violate the privacy issues of people in the network

PAARGAMAN: Passenger Demand Provoked (On-The-Fly) Routing Of Intelligent Public Transport Vehicle with Dynamic Route Updation, Generation, and Suggestion

Demand-based public bus service meets the need of passengers with less money, time, and resources by reducing the number of private vehicles on the road. In contrast, dynamic real-time demand-based routing faces challenges like elevated travel time due to the requested assignment based on the paths and vehicle availability. Hence, this research introduces a novel framework named Passenger Influence Bus Service-Intelligent Public Transport System (PIBS-IPTS) for efficient routing of available vehicles based on the demand of passengers. For this, optimal paths are elected from the known routes of the general vehicle through the Cuckoo Search (CS) optimization algorithm. Then efficient route prediction is employed by the Artificial Neural Network (ANN) for passenger flow. Here, the unavailability of the passenger request, such as source location or Destination locations, or the unavailability of both locations is updated while employing the path generation process. The path generation process ensures the reduction of request drops generated by the passenger, which elevates the usage of the general bus service. Here, for the optimal selection of routes from the identified routing paths, a multi-objective function based on traffic density, route condition, and route mobility is employed for the selection of a near-optimal global solution. The method’s performance is analyzed using MAE, RMSE, and MAPE and obtained the best values of 0.69, 0.72, and 0.74, respectively

Correlation of acute physiological parameters with immediate outcome among neonates transported to special care newborn unit: A prospective study

Background: Several sick neonates require transfer to tertiary level care neonatal unit for treatment. The facilities of neonatal transport in India are not optimal and the newborn thus transported can become hypothermic, hypoxic, and/or hypoglycemic which can affect the neonatal outcome. These parameters can be maintained during transport by adopting simple measures. Aim: Study impact of acute physiological parameters during transfer of neonates on their immediate outcome by using TOPS score. TOPS Score -temperature, oxygensaturation, perfusion (assessed by capillary refill time), blood Sugar. Materials and Methods: This prospective observational study was conducted at the special care newborn unit, Indore enrolling 513 transported neonates. TOPS scoring for each neonate was done at admission, and then the parameters of the TOPS score were correlated with the outcome at 48 h of admission. Results: A total of 513 transported newborns were assessed, 48.73% newborns were hypothermic, 33.91% had poor perfusion, 28.46% were hypoxemic, and 22.22% were hypoglycemic. Hypoxemia and hypoglycemia had the highest sensitivity (93.39% and 80.18%, respectively) while hypoglycemia had the highest specificity (92.87%). Conclusion: TOPS score is a useful and easy to use the method to assess the physiological status and predict early mortality in transported neonates

Noncoding-RNA-Based Therapeutics with an Emphasis on Prostatic Carcinoma-Progress and Challenges.

Noncoding RNAs (ncRNAs) defy the central dogma by representing a family of RNA molecules that are not translated into protein but can convey information encoded in their DNA. Elucidating the exact function of ncRNA has been a focus of discovery in the last decade and remains challenging. Nevertheless, the importance of understanding ncRNA is apparent since these molecules regulate gene expression at the transcriptional and post-transcriptional level exerting pleiotropic effects critical in development, oncogenesis, and immunity. NcRNAs have been referred to as the dark matter of the nucleus , and unraveling their role in physiologic and pathologic processes will provide vast opportunities for basic and translational research with the potential for significant therapeutic progress. Consequently, strong efforts are underway to exploit the therapeutic utility of ncRNA, some of which have been approved by the US Food and Drug Administration and the European Medicines Agency. The use of ncRNA therapeutics (or vaccines if defined as anti-disease agents) may result in improved curative strategies when used alone or in combination with existing treatments. This review will focus on the role of ncRNA therapeutics in prostatic carcinoma while exploring basic biological aspects of these molecules that represent about 97% of the transcriptome in humans