Extreme events and event size fluctuations in biased random walks on networks

Random walk on discrete lattice models is important to understand various types of transport processes. The extreme events, defined as exceedences of the flux of walkers above a prescribed threshold, have been studied recently in the context of complex networks. This was motivated by the occurrence of rare events such as traffic jams, floods, and power black-outs which take place on networks. In this work, we study extreme events in a generalized random walk model in which the walk is preferentially biased by the network topology. The walkers preferentially choose to hop toward the hubs or small degree nodes. In this setting, we show that extremely large fluctuations in event-sizes are possible on small degree nodes when the walkers are biased toward the hubs. In particular, we obtain the distribution of event-sizes on the network. Further, the probability for the occurrence of extreme events on any node in the network depends on its 'generalized strength', a measure of the ability of a node to attract walkers. The 'generalized strength' is a function of the degree of the node and that of its nearest neighbors. We obtain analytical and simulation results for the probability of occurrence of extreme events on the nodes of a network using a generalized random walk model. The result reveals that the nodes with a larger value of 'generalized strength', on average, display lower probability for the occurrence of extreme events compared to the nodes with lower values of 'generalized strength'

Technical note: Measuring tropospheric OH and HO₂ by laser-induced fluorescence at low pressure. A comparison of calibration techniques

International audienceThe hydroxyl radical (OH) is one of the most important oxidants in the atmosphere, as it is involved in many reactions that affect regional air quality and global climate change. Because of its high reactivity, measurements of OH radical concentrations in the atmosphere are difficult, and often require careful calibrations that rely on the production of a known concentration of OH at atmospheric pressure. The Indiana University OH instrument, based on the Fluorescence Assay by Gas Expansion technique (FAGE), has been calibrated in the laboratory using two different approaches: the production of OH from the UV-photolysis of water-vapor, and the steady-state production of OH from the reaction of ozone with alkenes. The former technique relies on two different actinometric methods to measure the product of the lamp flux at 184.9 nm and the photolysis time. This quantity derived from N2O actinometry was found to be 1.5 times higher than that derived from O2 actinometry. The water photolysis and ozone-alkene techniques are shown to agree within their experimental uncertainties (respectively 17% and 44%), although the sensitivities derived from the ozone-alkene technique were systematically lower by 40% than those derived from the water-vapor UV- photolysis technique using O2 actinometry. The agreement between the two different methods improves the confidence of the water-vapor photolysis method as an accurate calibration technique for HOx instruments. Because several aspects of the mechanism of the gas phase ozonolysis of alkenes are still uncertain, this technique should be used with caution to calibrate OH instruments

Open Source Software Use in Indian Libraries: A Survey.

The term “Open Source” is a trending topic at present among LIS professionals in India. Open Source applications in libraries progressed as a matter of serious discussion among the library professionals. Stakeholders of Indian Library sector now a day’s realize the advantages of embracing Open Source softwares. This Paper attempts to find out the usage of Open Source software in Indian Libraries. It is found that there is a positive attitude from the part of library professionals towards the acceptance of Open Source softwares.The study also underscores the necessity of orientation Programmes for making Professionals more familiar for adoption of Open Source software in libraries

On a Class of Generalized Elliptic-type Integrals

The aim of this paper is to study a generalized form of elliptic-type integrals which unify and extend various families of elliptic-type integrals studied recently by several authors. In a recent communication [1] we have obtained recurrence relations and asymptotic formula for this generalized elliptic-type integral. Here we shall obtain some more results which are single and multiple integral formulae, differentiation formula, fractional integral and approximations for this class of generalized elliptic-type integrals

A statistical approach for the production of thermostable and alklophilic alpha-amylase from Bacillus amyloliquefaciens KCP2 under solid-state fermentation

The bacterial strain producing thermostable, alklophilic alpha-amylase was identified as Bacillus amyloliquefaciens KCP2 using 16S rDNA gene sequencing data (NCBI Accession No: KF112071). Medium components were optimized through the statistical approach for the synthesis of alpha-amylase by the organism under solid-state fermentation using wheat bran as the substrate. The medium components influencing the enzyme production were identified using a two-level fractional factorial Plackett–Burman design. Among the various variables screened, starch, ammonium sulphate and calcium chloride were found to be most significant medium components. The optimum levels of these significant parameters were determined employing the response surface Central Composite design which significantly increased the enzyme production with the supplementation of starch 0.01 g, ammonium sulphate 0.2 g and 5 mM calcium chloride in the production medium. Temperature and pH stability of the alpha-amylase suggested its wide application in the food and pharmaceutical industries

Automatic generation control of a hydro - thermal and thermal - thermal systems in a deregulated environment

This paper deals with the applications of automatic generation control (AGC) of a hydro —thermal and thermal—thermal systems in a power system deregulated environment and makes an attempt to provide a new practical AGC model to fulfill the needs of a modern restructured hydro-thermal and thermal -thermal power system. Several Distribution Company, distribution Participation Matrix,and area participation factor have been tried out and dynamic responses for frequency, tie line flow and power generations are obtained to examine the performance of the system in deregulated environment considering integral controllers. Investigations have been also carried out to study the effect of generation rate constraint and the importance of APF in deregulated environment. Study also reveals that the conventional integral controllers are quite robust than PI and PID controllers and the optimum integral gains once set for nominal condition need not be changed for +25% variations in system parameters and +20% variations in operating load condition from their nominal values

Right ventricular dysfunction after resuscitation predicts poor outcomes in cardiac arrest patients independent of left ventricular function.

OBJECTIVE: Determination of clinical outcomes following resuscitation from cardiac arrest remains elusive in the immediate post-arrest period. Echocardiographic assessment shortly after resuscitation has largely focused on left ventricular (LV) function. We aimed to determine whether post-arrest right ventricular (RV) dysfunction predicts worse survival and poor neurologic outcome in cardiac arrest patients, independent of LV dysfunction. METHODS: A single-center, retrospective cohort study at a tertiary care university hospital participating in the Penn Alliance for Therapeutic Hypothermia (PATH) Registry between 2000 and 2012. PATIENTS: 291 in- and out-of-hospital adult cardiac arrest patients at the University of Pennsylvania who had return of spontaneous circulation (ROSC) and post-arrest echocardiograms. MEASUREMENTS AND MAIN RESULTS: Of the 291 patients, 57% were male, with a mean age of 59 ± 16 years. 179 (63%) patients had LV dysfunction, 173 (59%) had RV dysfunction, and 124 (44%) had biventricular dysfunction on the initial post-arrest echocardiogram. Independent of LV function, RV dysfunction was predictive of worse survival (mild or moderate: OR 0.51, CI 0.26-0.99, p CONCLUSIONS: Echocardiographic findings of post-arrest RV dysfunction were equally prevalent as LV dysfunction. RV dysfunction was significantly predictive of worse outcomes in post-arrest patients after accounting for LV dysfunction. Post-arrest RV dysfunction may be useful for risk stratification and management in this high-mortality population

A Reliable Peer-to-Peer Platform for Adding New Node Using Trust Based Model

In order to evaluate the trustworthiness of participating peers in unstructured peer-to-peer networks, Reputation aggregation methods are used in this method. Each and every peer of the network will collect the local scores of each transaction and will compute global scores by aggregating all the local scores with the help of global scores, each individual peer can interact with its suitable peers. But the existing method will not consider the score of the new peer. In this condition, requests are handled by existing peers who leads to failure in downloading process. To rectify this, NP-TRUST model is used to distribute the request to all peers including the newly joined peers. The proposed method is compared with gossip and DFR-TRUST model in Transaction Success rate and variation in file request

Legume leaf disease classification via attention-enhanced Swin transformer with feature pyramid fusion (AE-SwinFPF)

Legume crops are vital to global agriculture due to their high nutritional value, ability to fix atmospheric nitrogen and role in promoting sustainable farming practices. However, these crops are susceptible to various foliar diseases that adversely impact productivity and crop quality. Accurate and early disease identification is essential for effective disease control and yield protection. This study proposed an Attention-Enhanced Swin Transformer integrated with Feature Pyramid Fusion (AE-SwinFPF) to effectively capture multi-scale spatial and semantic features for legume leaf disease classification. For enhanced interpretability, Grad-CAM visualizes the model’s focus on disease-relevant regions in the output, providing insights into the decision-making process. The proposed model was evaluated on publicly available legume crop leaf image datasets comprising peas, beans and black gram, achieving classification accuracies of 97.16 %, 98.50 % and 99.99 % respectively. It also consistently yielded high precision, recall and F1-score, demonstrating its reliable and effective performance across all three legume types. Comparative analysis against several baseline Convolutional Neural Network (CNN) models and previously published methods revealed consistent improvements in classification performance. The integration of hierarchical attention with interpretable feature fusion highlights the model\u27s effectiveness and reliability for real-world deployment. However, further validation across diverse crop types and field conditions is recommended to ensure broader applicability