Patterns of Antibiotic Drug Resistance among Salmonella Typhi Isolates of Enteric Fever in Pediatric Population at a Tertiary Care Hospital

Objective: To determine patterns of antibiotic drug resistance among Salmonella typhi isolates of enteric fever in pediatric population at a tertiary care hospital. Material and methods: Consecutive 161 children with enteric fever were included in this study. This cross – sectional study was done at Department of Pediatric Medicine, Nishtar Medical University and Hospital, Multan from June 2015 to December 2016. Venous blood sample (3-5 ml) was drawn and it was immediately transported to Microbiology laboratory of Pathology Department, Nishtar Hospital Multan for blood culture and sensitivity test. Antibiotic drug resistance was determined after measuring diameter of zone of inhibition of a specific drug on Salmonella isolates on Mueller Hinton agar plates by modified Kirby baur disc diffusion method. Coated tongue, pain abdomen, anorexia and headache was assessed clinically. All the data were entered and analyzed using SPSS-11. Results: Of these 161 study cases, 91 (56.5%) were boys and 70 (43.5%) were girls. Mean age of our study cases was 5.79 ± 2.45 years (with minim age was 2 years while 12 years was maximum age). Previous history of use of antibiotics before 48 hours of the culture and sensitivity test was present in 93 (57.8%) of our study cases. Majority of our study cases having enteric fever presented with abdominal pain 65 (40.4%), headache 28 (17.4%) and diarrhea 17.4 % of our study cases. Chloramphenicol was sensitive in 40 (24.8%) of the Salmonella typhi isolates, Ampicillin was sensitive in 20 (12.4%), Co-trimoxazole in 20 (12.4%), Ciprofloxacin was sensitive in 88 (54.7%) isolates, Ofloxacin was sensitive in 101 (62.7%), Gentamycin was sensitive in 28 (17.4 %), Amoxycillin was sensitive in 36 (22.4 %). Conclusion: Our study results have indicated that S. typhi isolates of enteric fever showed higher degree of antibiotic drug resistance. Multidrug resistant strains were more prevalent in our study which points towards well directed efforts of our health policy makers to adopt certain guidelines regarding use of these drugs in our population. Keywords: Enteric fever, drug resistance, children

DIAMOnDS - DIstributed Agents for MObile & Dynamic Services

Distributed Services Architecture with support for mobile agents between services, offer significantly improved communication and computational flexibility. The uses of agents allow execution of complex operations that involve large amounts of data to be processed effectively using distributed resources. The prototype system Distributed Agents for Mobile and Dynamic Services (DIAMOnDS), allows a service to send agents on its behalf, to other services, to perform data manipulation and processing. Agents have been implemented as mobile services that are discovered using the Jini Lookup mechanism and used by other services for task management and communication. Agents provide proxies for interaction with other services as well as specific GUI to monitor and control the agent activity. Thus agents acting on behalf of one service cooperate with other services to carry out a job, providing inter-operation of loosely coupled services in a semi-autonomous way. Remote file system access functionality has been incorporated by the agent framework and allows services to dynamically share and browse the file system resources of hosts, running the services. Generic database access functionality has been implemented in the mobile agent framework that allows performing complex data mining and processing operations efficiently in distributed system. A basic data searching agent is also implemented that performs a query based search in a file system. The testing of the framework was carried out on WAN by moving Connectivity Test agents between AgentStations in CERN, Switzerland and NUST, Pakistan.Comment: 7 pages, 4 figures, CHEP03, La Jolla, California, March 24-28, 200

Modelling and Analysis of a Measles Epidemic Model with the Constant Proportional Caputo Operator

Despite the existence of a secure and reliable immunization, measles, also known as rubeola, continues to be a leading cause of fatalities globally, especially in underdeveloped nations. For investigation and observation of the dynamical transmission of the disease with the influence of vaccination, we proposed a novel fractional order measles model with a constant proportional (CP) Caputo operator. We analysed the proposed model’s positivity, boundedness, well-posedness, and biological viability. Reproductive and strength numbers were also verified to examine how the illness dynamically behaves in society. For local and global stability analysis, we introduced the Lyapunov function with first and second derivatives. In order to evaluate the fractional integral operator, we used different techniques to invert the PC and CPC operators. We also used our suggested model’s fractional differential equations to derive the eigenfunctions of the CPC operator. There is a detailed discussion of additional analysis on the CPC and Hilfer generalised proportional operators. Employing the Laplace with the Adomian decomposition technique, we simulated a system of fractional differential equations numerically. Finally, numerical results and simulations were derived with the proposed measles model. The intricate and vital study of systems with symmetry is one of the many applications of contemporary fractional mathematical control. A strong tool that makes it possible to create numerical answers to a given fractional differential equation methodically is symmetry analysis. It is discovered that the proposed fractional order model provides a more realistic way of understanding the dynamics of a measles epidemic.This research was funded by Basque Government: Grants: IT1555-22 and KK-2022/00090; MCIN/AEI 269.10.13039/501100011033: Grant PID2021-1235430B-C21/C22

Seasonal influence, heat unit accumulation and heat use efficiency in relation to maize grain yield in Pakistan

Variations in ambient temperature affect crop yield by modifying the duration of phenological phases and physiologicalprocesses. An experimental study was carried out at the Maize and Millets Research Institute (MMRI),Yusafwala, Sahiwal, Pakistan, to determine the seasonal effects of temperature on indigenous and exotic maize(Zea mays L.) hybrids based on morphological, phenological, physiological and grain quality traits in four differentgrowing seasons: kharif 2016 and 2017, and spring 2017 and 2018. Seven indigenous and three exotic hybridswere sown in a randomized complete block design with a split plot arrangement, in three replications. Significantdifferences between hybrids and growing seasons were found for grain yield, related traits and temperature indices(cumulative heat units, photothermal index and heat use efficiency). Correlation analysis disclosed a significantpositive relationship between grain yield and net photosynthetic rate (0.854, P≤0.01), number of grains per ear(0.624, P≤0.01) and heat use efficiency (0.980, P≤0.01) in spring seasons. During kharif, net photosynthetic rate(0.675, P≤0.01) and heat use efficiency (0.996, P≤0.01) contributed significantly to grain yield, whereas number ofgrains per ear (−0.146, not significant) had no significant impact on grain yield. Cumulative heat units and heat useefficiency resulted the temperature indices with the greatest influence on grain yield, and should be consideredduring the selection of parents to develop high-yielding, climate-smart maize hybrids. Indigenous maize hybridsshowed higher yields and were more heat tolerant than exotic hybrids, and the spring sowing season appearedto be the most suitable for the cultivation of maize crops

Classification of EEG Signals for Prediction of Epileptic Seizures

Epilepsy is a common brain disorder that causes patients to face multiple seizures in a single day. Around 65 million people are affected by epilepsy worldwide. Patients with focal epilepsy can be treated with surgery, whereas generalized epileptic seizures can be managed with medications. It has been noted that in more than 30% of cases, these medications fail to control epileptic seizures, resulting in accidents and limiting the patient’s life. Predicting epileptic seizures in such patients prior to the commencement of an oncoming seizure is critical so that the seizure can be treated with preventive medicines before it occurs. Electroencephalogram (EEG) signals of patients recorded to observe brain electrical activity during a seizure can be quite helpful in predicting seizures. Researchers have proposed methods that use machine and/or deep learning techniques to predict epileptic seizures using scalp EEG signals; however, prediction of seizures with increased accuracy is still a challenge. Therefore, we propose a three-step approach. It includes preprocessing of scalp EEG signals with PREP pipeline, which is a more sophisticated alternative to basic notch filtering. This method uses a regression-based technique to further enhance the SNR, with a combination of handcrafted, i.e., statistical features such as temporal mean, variance, and skewness, and automated features using CNN, followed by classification of interictal state and preictal state segments using LSTM to predict seizures. We train and validate our proposed technique on the CHB-MIT scalp EEG dataset and achieve accuracy of 94%, sensitivity of 93.8% , and 91.2% specificity. The proposed technique achieves better sensitivity and specificity than existing methods.publishedVersio

An Ensemble Learning Method for Emotion Charting Using Multimodal Physiological Signals

publishedVersio

Corrosion behavior of copper, aluminium, and stainless steel 316L in chicken fat oil based biodiesel-diesel blends

This study investigates the corrosion behavior of automotive materials in bio-based fuels. The Response Surface Methodology is employed to evaluate the corrosion rates of materials such as copper, aluminium, and stainless steel when they are exposed to chicken fat-based biodiesel. Copper, aluminium, and stainless steel showed minimum corrosion rate at a blend percentage of 5.86 % when they were immersed for 920 h and maximum corrosion rate at blend percentage 34.14 % when these were immersed for 920 h. Meanwhile, the maximum corrosion rate was observed at a blend percentage of 34.14 % corresponding to the same immersion period. Optimum values indicated by RSM for copper and aluminium were noted at a blend percentage of 10 % and an immersion period of 720 h. Similarly, for stainless steel 316 l, these were 10.91 % and 754.44 h, respectively. Additionally, trials using the B100 for 920 h were conducted on copper, aluminium, and stainless steel 316 l, and the results showed considerably higher corrosion rates than those previously found. The surface morphology of the materials was investigated by X-ray Diffraction and Scanning Electron Microscopy, and it was revealed that copper was the most corrosive material in chicken fat oil-based biodiesel followed by aluminium and stainless steel 316 l

Probiotics: mechanism of action, health benefits and their application in food industries

Probiotics, like lactic acid bacteria, are non-pathogenic microbes that exert health benefits to the host when administered in adequate quantity. Currently, research is being conducted on the molecular events and applications of probiotics. The suggested mechanisms by which probiotics exert their action include; competitive exclusion of pathogens for adhesion sites, improvement of the intestinal mucosal barrier, gut immunomodulation, and neurotransmitter synthesis. This review emphasizes the recent advances in the health benefits of probiotics and the emerging applications of probiotics in the food industry. Due to their capability to modulate gut microbiota and attenuate the immune system, probiotics could be used as an adjuvant in hypertension, hypercholesterolemia, cancer, and gastrointestinal diseases. Considering the functional properties, probiotics are being used in the dairy, beverage, and baking industries. After developing the latest techniques by researchers, probiotics can now survive within harsh processing conditions and withstand GI stresses quite effectively. Thus, the potential of probiotics can efficiently be utilized on a commercial scale in food processing industries