Resource-Efficient Widely-Linear Collaborative Wind Forecasting for Renewable Energy Generation

Wind is an important source of renewable energy with abundant availability at many places of the world. The integration of wind energy into the electricity grid brings new challenges on the system reliability due to its intermittent nature. A robust tool with good accuracy for wind power forecasting is an essential part of wind based power system. Wind power is directly related to the cube of wind speed and hence a small improvement in the forecasting of wind speed provides larger improvement in wind power forecasts. The accuracy of a wind speed forecasting model depends upon the characteristics of wind signal incorporated in the model. Wind direction has significant effect on wind speed forecasts and the complex representation of wind signal provides a convenient tool to include the effect of direction. The complex wind signal is non-circular, and widely-linear modeling of the complex wind signal provides optimal results. Wind signal has strong temporal and spatial correlations as well. Most of the wind forecasting models at present do not incorporate all of these characteristics of the wind signal. In this thesis work, we will develop a widely-linear collaborative wind forecasting model which takes into account the non-circular nature of the complex wind signal and its temporal and spatial correlations as well. The parameters of the model are updated using recursive least squares approach. The forecasting model is further optimized for efficient resource utilization by using a set-membership formulation. A data model for the complex wind signal is developed and the algorithm is tested on the simulated wind data. Simulation results show better forecasting performance with the developed approach. Real world wind data is also used to verify the results

Demonstrating competence in endoscopic retrograde cholangiopancratico graphy (ERCP): Recently credentialed operator\u27s performance for deep biliary cannulation over 1 year period from a tertiary care hospital in Pakistan

Objective: To measure the success rate of endoscopic retrograde cholangiopancreaticography biliary cannulation of a recently credentialed endoscopist at a tertiary hospital.Methods: The clinical audit was conducted at the Aga Khan University Hospital. Karachi, and comprised data of all patients who underwent endoscopic retrograde cholangiopancreaticography under the care of a single operator during 2016. Data was retrospectively extracted from patient charts by an assistant blinded to the study. Data extracted included demographics, admission type, details and indication for the procedure, diagnosis, cannulation outcome, duct clearance, complications, follow-up surgical intervention, radiological imaging and mortality post-endoscopy. Data was analysed using SPSS 19.Results: Of 143 procedures performed, 102(71.3%) were included. The mean age was 52±17 years and 54(52.9%) of them were females. Most common indication was choledocholithiasis in 70(68.6%). The average procedure time was 41.5±5.5 minutes. Cannulation success rate was 96(94.1%). Complications included post-procedure pancreatitis in 5(4.9%), minimal bleeding in 8(7.8%) and oesophageal perforation in 1(0.98%). There was no procedure-related mortality.Conclusions: The success rate was high and complications were low with zero mortality

Impact of Capital Structure on Firms’ Financial Performance: Evidence from Pakistan

This research examines the impact of capital structure on firms’ financial performance in Pakistan of top 100 consecutive companies in Karachi Stock Exchange for a period of four years from 2006 to 2009. Exponential generalized least square regression is used to test the relationship between capital structure and firms’ financial performance. The results show that all the three variables of capital structure, Current Liabilities to Total Asset, Long Term Liabilities to Total Asset, Total Liabilities to Total Assets, negatively impacts the Earning before Interest and Taxes, Return on Assets, Earning per Share and Net Profit Margin whereas Price Earning ratio shows negative relationship with Current Liabilities to Total Asset and positive relationship is found with Long Term Liabilities to Total Asset where the relationship is insignificant with , Total Liabilities to Total Assets. The results also indicate that Return on Equity has an insignificant impact on Current Liabilities to Total Asset and Total Liabilities to Total Assets but a positive relationship exists with Long Term Liabilities to Total Asset. These results, in general, lead to the conclusion that capital structure choice is an important determinant of financial performance of firms. This is the first study in Pakistan examining the relationship between firms’ performance and capital structure of top 100 consecutive companies in Karachi Stock Exchange for a period of four years. Keywords: Capital Structure, Firms’ Performance, Performance Measures, Profit, Pakistan

CEFHRI: A Communication Efficient Federated Learning Framework for Recognizing Industrial Human-Robot Interaction

Human-robot interaction (HRI) is a rapidly growing field that encompasses social and industrial applications. Machine learning plays a vital role in industrial HRI by enhancing the adaptability and autonomy of robots in complex environments. However, data privacy is a crucial concern in the interaction between humans and robots, as companies need to protect sensitive data while machine learning algorithms require access to large datasets. Federated Learning (FL) offers a solution by enabling the distributed training of models without sharing raw data. Despite extensive research on Federated learning (FL) for tasks such as natural language processing (NLP) and image classification, the question of how to use FL for HRI remains an open research problem. The traditional FL approach involves transmitting large neural network parameter matrices between the server and clients, which can lead to high communication costs and often becomes a bottleneck in FL. This paper proposes a communication-efficient FL framework for human-robot interaction (CEFHRI) to address the challenges of data heterogeneity and communication costs. The framework leverages pre-trained models and introduces a trainable spatiotemporal adapter for video understanding tasks in HRI. Experimental results on three human-robot interaction benchmark datasets: HRI30, InHARD, and COIN demonstrate the superiority of CEFHRI over full fine-tuning in terms of communication costs. The proposed methodology provides a secure and efficient approach to HRI federated learning, particularly in industrial environments with data privacy concerns and limited communication bandwidth. Our code is available at https://github.com/umarkhalidAI/CEFHRI-Efficient-Federated-Learning.Comment: Accepted in IROS 202

Role of heat stress in migration decisions : a case study of Faisalabad

This study explores the relation between migration decisions and heat stress, its impact on livelihoods and thermal comfort levels both at home and at work. Many developing countries face declining worker productivity due to heat stress. Migration provides an opportunity to reduce risk and diversify livelihoods. Extreme heat stress is associated with migration because it affects livelihood and reduces farm and non-farm income. The paper is based on a household survey using a structured questionnaire to compare two study sites 1) Rural areas of Faisalabad district 2) Peri-urban areas of Faisalabad city.UK Government’s Department for International Development (DfID)International Development Research Centre (IDRC

PIN1 and PIN4 inhibition via parvulin impeders Juglone, PiB, ATRA, 6,7,4′-THIF, KPT6566, and EGCG thwarted hepatitis B virus replication

IntroductionHuman parvulin peptidyl prolyl cis/trans isomerases PIN1 and PIN4 play important roles in cell cycle progression, DNA binding, protein folding and chromatin remodeling, ribosome biogenesis, and tubulin polymerization. In this article, we found that endogenous PIN1 and PIN4 were upregulated in selected hepatocellular carcinoma (HCC) cell lines.MethodsIn this study, we inhibited PIN1 and PIN4 via parvulin inhibitors (Juglone, PiB, ATRA, 6,7,4′-THIF, KPT6566, and EGCG). The native agarose gel electrophoresis (NAGE) immunoblotting analysis revealed that upon PIN1 and/ or PIN4 inhibition, the HBc protein expression and core particle or capsid synthesis reduced remarkably. The effects of PIN4 inhibition on hepatitis B virus (HBV) replication were more pronounced as compared to that of PIN1. The Northern and Southern blotting revealed reduced HBV RNA and DNA levels.ResultsDuring the HBV course of infection, Juglone, PiB, ATRA, 6,7,4′-THIF, KPT6566, and EGCG-mediated inhibition of PIN1 and PIN4 significantly lowered HBV transcriptional activities without affecting total levels of covalently closed circular DNA (cccDNA). Similar to the inhibitory effects of PIN1 and PIN4 on HBV replication, the knockdown of PIN1 and PIN4 in HBV infection cells revealed significantly reduced amounts of intracellular HBc, HBs, HBV pgRNA, SmRNAs, core particles, and HBV DNA synthesis. Similarly, PIN1 and PIN4 KD abrogated extracellular virion release, naked capsid levels, and HBV DNA levels. In comparison with PIN1 KD, the PIN4 KD showed reduced HBc and/or core particle stabilities, indicating that PIN4 is more critically involved in HBV replication. Chromatin immunoprecipitation (ChIP) assays revealed that in contrast to DNA binding PIN4 proteins, the PIN1 did not show binding to cccDNA. Similarly, upon PIN1 KD, the HBc recruitment to cccDNA remained unaffected. However, PIN4 KD significantly abrogated PIN4 binding to cccDNA, followed by HBc recruitment to cccDNA and restricted HBV transcriptional activities. These effects were more pronounced in PIN4 KD cells upon drug treatment in HBV-infected cells.ConclusionThe comparative analysis revealed that in contrast to PIN1, PIN4 is more critically involved in enhancing HBV replication. Thus, PIN1 and PIN4 inhibition or knockdown might be novel therapeutic targets to suppress HBV infection. targets to suppress HBV infection

Extent of liver inflammation in predicting response to interferon alpha & Ribavirin in chronic hepatitis C patients: a cohort study

Background: Liver inflammation due to HCV infection leads to fibrosis, which is an independent predictor of treatment response to interferon therapy in Chronic Hepatitis C (CHC) patients. This relationship has not been studied for liver inflammation on pretreatment liver biopsy and End of Treatment Response (ETR). ALT is a less invasive test than liver biopsy for measuring liver inflammation. Aim of this study was to compare ETR to Interferon alpha (recombinant Interferon) & Ribavirin in CHC patients having higher and lower grades of liver inflammation and to determine the diagnostic accuracy of pretreatment ALT for grades of liver inflammation.Methods: A retrospective cohort of 876 naive CHC patients, who completed Interferon alpha & Ribavirin for 24weeks, was studied for ETR. Pretreatment grade of inflammation on liver biopsy was taken as the exposure variable. It was classified as high if there was moderate or severe and low if there was minimal or mild. Multivariable logistic regression modeling was performed. Diagnostic accuracy of pretreatment ALT for liver inflammation grades was determined by computing Area Under the Receiver Operator Curve (AUROC).Results: Of all patients, 672 having diagnostic liver biopsy and ETR available were analyzed. Among them, 103 had high and 569 had low grades of liver inflammation. Mean age was 36.9 (SD 9.1) years, with patients with high grades being older than those with low grades inflammation (p=0.03). High grades of liver inflammation was associated with ETR (RR 1.17, 95% CI 1.12-1.18) adjusting for age, Total Leukocyte count (TLC) and pretreatment levels of ALT, irrespective of liver fibrosis. This relation remained significant for \u27bridging fibrosis and cirrhosis\u27 and not for \u27no\u27 or \u27portal fibrosis\u27. AUROC of pretreatment ALT for males and females was moderately accurate for severe inflammation compared to minimal inflammation and less accurate for high grades compared to low grades.CONCLUSIONS: ETR in patients with higher grades of liver inflammation was 17% higher than those with lower grades irrespective of fibrosis and 9% higher for bridging fibrosis and cirrhosis. Pretreatment ALT was moderately accurate for severe inflammation only on liver biopsy in both males and females

Synergistic mixed-layer height retrieval method using microwave radiometer and lidar ceilometer observations

This paper tackles synergistic mixed-layer height (MLH) estimation via a combination of microwave radiometer (MWR) and lidar ceilometer (LC)-based estimates. While MLH-MWR estimates rely on potential temperature retrievals, MLH-LC estimates rely on aerosol gradients. The pros and cons of MLH retrievals obtained from MWR via the parcel method and from LC via an extended Kalman filter (EKF)-based method are used to motivate the synergistic algorithm. The synergistic algorithm is introduced as a maximum-likelihood combination of MLH-MWR and MLH-LC. Two case examples from the 2013 HOPE campaign at Jülich, Germany, are used to show the robustness of the synergistic method and the effect of surface temperature measurement error. Doppler wind lidar retrievals and radiosonde reference MLH estimates are used for validation.This research is part of the projects PGC2018-094132-B-I00 and MDM-2016-0600 (“CommSensLab” Excellence Unit) funded by Ministerio de Ciencia e Investigación (MCIN)/ Agencia Estatal de Investigación (AEI)/ 10.13039/501100011033/ FEDER. Data were provided by Julich Observatory for Cloud Evolution (JOYCE-CF), a core facility funded by Deutsche Forschungsgemeinschaft via grant DFG LO 901/7-1. The work of M.P.A.S was supported under Grant PRE2018-086054 funded by MCIN/AEI/ 10.13039/501100011033 and FSE “El FSE invierte en tu futuro”. The European Commission collaborated under projects H2020 ACTRIS-IMP (GA871115) and H2020 ATMO-ACCESS (GA-101008004).Peer ReviewedPostprint (author's final draft