Search

The precision of process monitoring often encounters challenges in determining the exact shift size. Therefore, combined control charts have gained considerable attention because of their excellent speed to detect simultaneously small-to-moderate and large-size shifts. The effectiveness of the applied quality control methods strongly depends on the performance of the measurement system. Measurement error presence contributes significantly negatively toward the performance of the usual control charting schemes. This article proposes novel two-sided combined Shewhart-Cumulative EWMA-sum (Shewhart-CUESUM) control charts designed to efficiently monitor the mean of normally distributed processes. In addition, to address measurement errors, the M-Shewhart-CUESUM chart is proposed, incorporating an additive measurement error model. Evaluation of the charts through Monte-Carlo simulations, considering metrics such as average run length (ARL), extra quadratic loss, relative ARL, and performance comparison index. It is found that the combined Shewhart-CUESUM outperforms than CUESUM chart. The results show that the presence of measurement errors can significantly diminish the charts’ performance, which can be mitigated by utilizing a multiple measurements scheme. Among the different well-established combined charts examined, the M-Shewhart-CUESUM chart shows considerably more sensitive to detecting simultaneously detect small and large size shifts. To employ simulated datasets to illustrate the impact of measurement errors and demonstrate the implications of the proposed charts on process mean shifts.

The COVID-19 pandemic has great effects for economies internationally. This study studies the interconnection between COVID-19 metrics and Pakistan's premier stock exchange, the Karachi Stock Exchange (KSE) with the object of identifying the most effective machine learning (ML) model for predicting KSE developments in the pandemic. Our investigation periods the peak COVID-19 period from March 1, 2020, to November 26, 2021, applying data from both the KSE 100 index and COVID-19 associated variables. Five various ML methods were applied involving Linear Regression (LR), K-Nearest Neighbors (KNN), Random Forest (RF), Regression Tree (Rtree), and Support Vector Machine (SVM) and measured their performance employing critical accuracy metrics such as Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), Mean Absolute Error (MAE), and R-squared (R2). The outcomes discover that the RF model outperformed its equivalents realizing an R2 of 0.91 with k = 5. These results conflict with a previous study that supported a negative impact of COVID-19 on improved stock markets. The visions from this study can assist investors in managing strategic investment decisions and assist policymakers in making measures to reduce the pandemic's effects on the stock market.

Abstract Background Considering the rapidly spreading monkeypox outbreak, WHO has declared a global health emergency. Still in the category of being endemic, the monkeypox disease shares numerous clinical characters with smallpox. This study focuses on determining the most effective combination of autoregressive integrated moving average model to encapsulate time dependent flow behaviour of the virus with short run prediction. Methods This study includes the data of confirmed reported cases and cumulative cases from eight most burdened countries across the globe, over the span of May 18, 2022, to December 31, 2022. The data was assembled from the website of Our World in Data and it involves countries such as United States, Brazil, Spain, France, Colombia, Mexico, Peru, United Kingdom, Germany and Canada. The job of modelling and short-term forecasting is facilitated by the employment of autoregressive integrated moving average. The legitimacy of the estimated models is argued by offering numerous model performance indices such as, root mean square error, mean absolute error and mean absolute prediction error. Results The best fit models were deduced for each country by using the data of confirmed reported cases of monkeypox infections. Based on diverse set of performance evaluation criteria, the best fit models were then employed to provide forecasting of next twenty days. Our results indicate that the USA is expected to be the hardest-hit country, with an average of 58 cases per day with 95% confidence interval of (00—400). The second most burdened country remained Brazil with expected average cases of 23 (00—130). The outlook is not much better for Spain and France, with average forecasts of 52 (00—241) and 24 (00—121), respectively. Conclusion This research provides profile of ten most severely hit countries by monkeypox transmission around the world and thus assists in epidemiological management. The prediction trends indicate that the confirmed cases in the USA may exceed than other contemporaries. Based on the findings of this study, it remains plausible to recommend that more robust health surveillance strategy is required to control the transmission flow of the virus especially in USA.

This research is based on the analysis of Monkeypox transmission, from may 7, 2022 to October 11, 2022, in 30 most affected countries around the globe. The most affected countries are selected through the cut point of at least 100 reported confirmed cases of infected persons over the aforementioned time span. We novely argue the exhibition of distributional similarities between the viral flow and well known power law in context of this neglected zoonotic disease. Moreover, model-based evidence suggesting the capability of pathogen to spread far and wide around its nucleus, are collected and presented. It is estimated that 70 % of the reported confirmed cases belonged to 20 % of the top most affected countries. Also, 70 % of the reported transmission was inflicted in 34 % of the days of reporting at least one case, on average.

Introduction Adverse events are a major cause of patient harm in the hospitalised setting. Low-income and middle-income countries account for a disproportionate share of the global burden of adverse events. However, patient safety research is still centred around high-income countries and high-resource health systems. The methods and data produced from these efforts are ill-suited to low-income and middle-income systems due to the social and technical differences between these settings. We aim to use our pilot-tested, locally developed methodology to estimate the frequency and characteristics of adverse events in hospitalised patients in a lower-middle-income country to inform patient safety policies and initiatives.Methods and analysis This multi-centre study will employ a two-step chart review methodology to identify adverse events in a representative sample of patients admitted at five hospitals between 1 January 2019 and 31 December 2019. The first step will include assessing patient files against a list of triggers to detect adverse events and the second step will involve an in-depth review of the events to capture pertinent characteristics. The triggers have been adapted from validated tools used in other studies. The reviewing team will be trained on the use of research tools and operational definitions to ensure that data are collected uniformly. The main outcome of interest is the rate at which adverse events occur in hospitalised patients. Further analysis will look to identify and quantify associations between the main outcome of interest and a variety of variables such as patient age and gender using tests of independence and regression techniques.Ethics and dissemination This study protocol has been approved by the Ethics Review Committee at Aga Khan University (Reference number: 2023-6324-24566). The findings of this study will be published in a peer-reviewed journal and disseminated to the public through national and international conferences, workshops, websites and social media.

In this manuscript, the mean of the study and the auxiliary variable, as well as the rank of the auxiliary variable, were needed to develop a new, improved ratio-in-regression type estimator for population mean. Up to the first order of approximation, expressions for the bias and mean square error of the existing and proposed estimators are computed. The effectiveness and stability of our new, enhanced estimator are evaluated using simulation and two actual data sets. The suggested estimator's superior performance to all other considered estimators is shown both conceptually and numerically. The mean square error is the lowest, and PREs out-performs other known estimators by a factor of more than one hundred. Overall, we draw the conclusion that the suggested new improved estimator outperforms all its predecessors.

Abstract Background In response to the COVID-19 pandemic, concerted efforts were made by provincial and federal governments to invest in critical care infrastructure and medical equipment to bridge the gap of resource-limitation in intensive care units (ICUs) across Pakistan. An initial step in creating a plan toward strengthening Pakistan’s baseline critical care capacity was to carry out a needs-assessment within the country to assess gaps and devise strategies for improving the quality of critical care facilities. Methods To assess the baseline critical care capacity of Pakistan, we conducted a series of cross-sectional surveys of hospitals providing COVID-19 care across the country. These hospitals were pre-identified by the Health Services Academy (HSA), Pakistan. Surveys were administered via telephonic and on-site interviews and based on a unique checklist for assessing critical care units which was created from the Partners in Health 4S Framework, which is: Space, Staff, Stuff, and Systems. These components were scored, weighted equally, and then ranked into quartiles. Results A total of 106 hospitals were surveyed, with the majority being in the public sector (71.7%) and in the metropolitan setting (56.6%). We found infrastructure, staffing, and systems lacking as only 19.8% of hospitals had negative pressure rooms and 44.4% had quarantine facilities for staff. Merely 36.8% of hospitals employed accredited intensivists and 54.8% of hospitals maintained an ideal nurse-to-patient ratio. 31.1% of hospitals did not have a staffing model, while 37.7% of hospitals did not have surge policies. On Chi-square analysis, statistically significant differences (p

Background Patient safety is a top priority for many healthcare organisations worldwide. However, most of the initiatives aimed at the measurement and improvement of patient safety culture have been undertaken in developed countries. The purpose of this study was to measure the patient safety culture at a tertiary care hospital in Pakistan using the Hospital Survey on Patient Safety Culture (HSOPSC).Methods The HSOPSC was used to measure the patient safety culture across 12 dimensions at Aga Khan University Hospital, Karachi. 2,959 individuals, who had been working at the hospital, were administered the HSOPSC in paper form between June and September 2019.Results The response rate of the survey was 50%. In the past 12 months, 979 respondents (33.1%) had submitted at least one event report. Results showed that the personnel viewed the patient safety culture at their hospital favourably. Overall, respondents scored highest in the following dimensions: ‘feedback and communication on error’ (91%), ‘organisational learning and continuous improvement’ (85%), ‘teamwork within units’ (83%), ‘teamwork across units’ (76%). The dimensions with the lowest positive per cent scores included ‘staffing’ (40%) and ‘non-punitive response to error’ (41%). Only the reliability of the ‘handoffs and transitions’, ‘frequency of events reported’, ‘organisational learning’ and ‘teamwork within units’ was higher than Cronbach’s alpha of 0.7. Upon regression analysis of positive responses, physicians and nurses were found to have responded less favourably than the remaining professional groups for most dimensions.Conclusion The measurement of safety culture is both feasible and informative in developing countries and could be broadly implemented to inform patient safety efforts. Current data suggest that it compares favourably with benchmarks from hospitals in the USA. Like the USA, high staff workload is a significant safety concern among staff. This study lays the foundation for further context-specific research on patient safety culture in developing countries.

In statistical process monitoring, it is often assumed that the sequential observations generated by processes are independent and identically distributed (iid). However, in real practice, these observations tend to exhibit an autocorrelation pattern. Thus, an autocorrelated process yields misleading results in terms of a high false alarm rate and slow detection of process changes if employing iid-based designed monitoring schemes. Therefore, in this article, we propose the dual cumulative sum (DCUSUM) and dual Crosier’s CUSUM (DCCUSUM) mean charts for monitoring the autocorrelated processes using a first-order autoregressive model. Monte Carlo simulations are extensively used to compute the performance measures: the average run length, standard deviation run length, extra quadratic loss, and relative average run length of the two-sided DCUSUM and DCCUSUM charts under both the zero-state and steady state cases. It is observed that as the level of autocorrelation increases, the performance of the studied charts deteriorates. Thus, a s-skipping sampling scheme is incorporated to reduce the negative effect of autocorrelation. To demonstrate the effect of autocorrelation and highlight implications further, a simulated dataset with a shift in the process mean is considered.

Clostridium perfringens produces core virulence factors that are responsible for causing hemorrhagic abomasitis and enterotoxemia making food, animals, and humans susceptible to its infection. In this study, C. perfringens was isolated from necropsied intestinal content of buffalo and cattle belonging to four major bovine-producing regions in the Punjab Province of Pakistan for the purpose offind out the genetic variation. Out of total 160 bovine samples (n: 160), thirty-three (n: 33) isolates of C. perfringens were obtained from buffalo (Bubales bubalis) and cattle (Bos indicus) that were further subjected to biochemical tests; 16S rRNA based identification and toxinotyping was done using PCR (Polymerase Chain Reaction) and PFGE (Pulse Field Gel Electrophoresis) pulsotypesfor genetic diversity. Occurrence of C. perfringens was found to be maximum in zone-IV (Bhakkar and Dera Ghazi Khan) according to the heatmap. Correlation was found to be significant and positive among the toxinotypes (α-toxin, and ε-toxin). Response surface methodology (RSM) via central composite design (CCD) and Box-Behnken design (BBD) demonstrated substantial frequency of C. perfringens based toxinotypes in all sampling zones. PFGE distinguished all isolates into 26 different pulsotypes using SmaI subtyping. Co-clustering analysis based on PFGE further decoded a diversegenetic relationship among the collected isolates. This study could help us to advance toward disease array of C. perfringens and its probable transmission and control. This study demonstrates PFGE patterns from Pakistan, and typing of C. perfringens by PFGE helps illustrate and mitigate the incidence of running pulsotypes.

The Internet of Things (IoT) is the network of physical objects embedded with sensors, software, electronics, and online connectivity systems. This study explores the role of IoT in clinical laboratory processes; this systematic review was conducted adhering to the PRISMA Statement 2020 guidelines. We included IoT models and applications across preanalytical, analytical, and postanalytical laboratory processes. PubMed, Cochrane Central, CINAHL Plus, Scopus, IEEE, and A.C.M. Digital library were searched between August 2015 to August 2022; the data were tabulated. Cohen’s coefficient of agreement was calculated to quantify inter-reviewer agreements; a total of 18 studies were included with Cohen’s coefficient computed to be 0.91. The included studies were divided into three classifications based on availability, including preanalytical, analytical, and postanalytical. The majority (77.8%) of the studies were real-tested. Communication-based approaches were the most common (83.3%), followed by application-based approaches (44.4%) and sensor-based approaches (33.3%) among the included studies. Open issues and challenges across the included studies included scalability, costs and energy consumption, interoperability, privacy and security, and performance issues. In this study, we identified, classified, and evaluated IoT applicability in clinical laboratory systems. This study presents pertinent findings for IoT development across clinical laboratory systems, for which it is essential that more rigorous and efficient testing and studies be conducted in the future.

We explored the contribution and effectiveness of state and non-state institutions in rural development efforts in highlands (Khyber Pakhtunkhwa [KPK] province) of Pakistan. This study employed mixed-methods research design and data were collected from 300 household heads, randomly selected from six villages from two purposively selected districts Mansehra and Nowshehra. Findings showed people in KPK were deprived of due to conflicts, conspiracies and terrorism, poor governance, small landholdings and subsistence farming followed by sluggish marketing system, insufficient education and training for people, and inadequate employment opportunities. Regarding contribution, non-state institutions had more contribution as compared to state institutions. T -test analysis showed that the non-state institutions had an effective provision of agricultural extension and forestry advisory services, education, health services in remote areas, skill development, and provision of microcredit schemes. The results of F -test statistics showed highly significant difference among the perceived effectiveness of rural development activities of different types of non-state actors (localite, cosmopolite, and religious/faith-based) working in the research area. This study recommends state-owned rural development departments revisit their working mechanism and develop synergistic working relationship with the non-state institutions in discharging rural development efforts.

Clostridium perfringens is a Gram-positive bacterium that possess seven toxinotypes (A, B, C, D, E, F, and G) that are responsible for the production of six major toxins, i.e., α, β, ε, ι, CPE, and NetB. The aim of this study is to find out the occurrence of toxinotypes in buffalo and cattle of Punjab province in Pakistan and their corresponding toxin-encoding genes from the isolated toxinotypes. To accomplish this aim, six districts in Punjab province were selected (i.e., Lahore, Sahiwal, Cheecha Watni, Bhakkar, Dera Ghazi Khan, and Bahawalpur) and a total of 240 buffalo and 240 cattle were selected for the collection of samples. From isolation and molecular analysis (16S rRNA), it was observed that out of seven toxinotypes (A–G), two toxinotypes (A and D) were found at most, whereas other toxinotypes, i.e., B, C, E, F, and G, were not found. The most frequently occurring toxinotype was type A (buffalo: 149/240; cattle: 157/240) whereas type D (buffalo: 8/240 cattle: 7/240) was found to occur the least. Genes encoding toxinotypes A and D were cpa and etx, respectively, whereas genes encoding other toxinotypes were not observed. The occurrence of isolated toxinotypes was studied using response surface methodology, which suggested a considerable occurrence of the isolated toxinotypes (A and D) in both buffalo and cattle. Association between type A and type D was found to be significant among the isolated toxinotypes in both buffalo and cattle (p ≤ 0.05). Correlation was also found to be positive and significant between type A and type D. C. perfringens exhibits a range of toxinotypes that can be diagnosed via genotyping, which is more reliable than classical toxinotyping.

Rural women in Pakistan, under a small holding system offarming, play a pivotal role in farming. They actively participatein a range of activities related to crop production and livestockmanagement. Rural women remain busy from dawn to dusk invarious agricultural activities, including pre-harvest, post-harvestand livestock management. Their participation is well dispersedbut less perceived because of insufficient data to show their activeinvolvement in various agricultural activities. Keeping these pointsin mind, this study was designed to explore the extent of women’sparticipation in various agricultural activities in district Bahawalpur(Southern Punjab, Pakistan). A total of 125 rural women wereselected through multistage random sampling technique and interviewed with a well-designed, pre-tested interview schedule,and the data was analyzed using SPSS. The results of the dataanalysis revealed that rural women’s participation level was at thetop (M = 2.87 and SD = 0.42) in picking of cotton while their participation level was found low (M = 1.78 and SD = 0.88) inbroadcasting of seed/fertilizer among different crop productionand management related activities. While on the other hand theirextent of participation was found at the top (M = 2.90 and SD =0.30) in cleaning of animal’s sheds and found low (M = 2.02 andSD = 0.83) in calf rearing among different livestock productionand management which were being performed by rural women.Regarding daily time given by rural women to perform variouscrop production, livestock production and household activitiesmajority of rural women they devote > than 8 hours in a day toperform these activities as reported by 27.2%, 32.8% and 76.8%of the respondents, respectively. It is recommended that nationalcommission should be established to recognize and documentedthe participation of rural women at various national and internationalforums. It is also recommended that women training wing shouldbe established at national level under the supervision of districtadministration to train rural women in different areas of crop andlivestock production so that they can contribute in a better way inthe national economy.

A research can also reveal the cooperative effectiveness ofagencies such as evaluation will lead to discover theweakness and strengths for further improvement of this program.The present study was designed in 2009 especially to see theeffectiveness of the working of agricultural extension staff asperceived by farmers in district Okara-Pakistan. The data werecollected with the help of a specifically designed and pre-testedinterview schedule and total sample was 300 respondents. Theresults showed that most 45.0% of the respondents belongedto the old age (31-40 years) category and most 30% of therespondents were above illiterate. An overwhelming majority77.33% of the respondents was in fall radio category. Whereas,only 29.33% of the respondents reported that they had contactwith Extension Field Staff. An overwhelming majority 74.33%of the respondents indicated lack of mobility as the majorconstraints in approaching agricultural extension educationservices. It was concluded that different mass media were notfully utilized in the area which hindered not only awarenesslevel of the respondents but also adversely effect the adoptionlevel regarding the latest production technology relatedagriculture sector. On the basis of conclusions it was recommendedthat for first of all the educational level of the study areashould be increased and Government should ensure adequateavailability of rural infrastructure facilities to enable more ofthe dwellers cultivate the habit of utilizing medias channels assource of information in agriculture production.

World has a new mania of ENGLISH learning. English as a language of learning or scholarly production and advanced studies, as well as the language of business and diplomacy has increased throughout the world but in China, its increasing trend as the language of instruction and learning in the last quarter century has received much more importance. Moreover, major developments and modifications in English language teaching have been made in last three decades. As we know, that China stood as political, social, most importantly economic and powerful socialist state throughout the world, due to the reason, Chinese leadership felt the need of the hour to have a grip on western languages especially English to compete with the contemporary super power countries. This review paper discusses a historical overview of Development and prospects of English, as language of Instruction and Learning, in Chinese Educational System and touches the present issues and trends. It originates that Chinese academia and students are giving much importance towards the communicative proficiency in their daily life. This scientific paper also dig out a logical finding that how Chinese educational System is evolving itself to meet up with the outer world and to open ways for their learners to utilize the opportunities in first world for the purpose of gaining English language proficiency.

The right information is important in farming and it plays a critical role for the farmers to gain maximum productivity with the effective utilization of available resources. The agricultural extension ensures that each farmer has equal and timely access to the best information. The traditional extension system is under huge criticism and the newness has become inevitable. The door-to-door extension needs to be replaced with a powerful e-extension system that can easily cover the limitations of a traditional extension. This study was conducted in the district Khanewal of Punjab, Pakistan to explore the potential of e-extension services among farmers. A total of 234 randomly selected respondents were interviewed on a structured interview schedule. Results indicated that different types of ICT tools like computers (20.5%), mobile phones (41.0%), Radio (2.1%), Mobile apps (12.3%) and social media gadgets (22.2%) were being used for infotainment. The maximum time spent by the farmers on ICT tools was 3.27 hours and 2.48 hours on mobile phones and TV respectively. T-test of comparison showed a positive statistically significant difference in swing time for different crops (t= 11.328), seed varieties, treatment and rate (t= -6.336), weather update (t= 17.114), application of different fertilizer (t= 7.302) and marketing (t= 8.433). Based on the results, e-extension could be considered the future extension approach. Government and other agencies should channelise e-extension services for the timely dissemination of needed information. [ABSTRACT FROM AUTHOR]

The right information is important in farming and it plays a critical role for the farmers to gain maximum productivity with the effective utilization of available resources. The agricultural extension ensures that each farmer has equal and timely access to the best information. The traditional extension system is under huge criticismandthe newness has become inevitable. The door-to-door extension needs to be replaced with a powerful e-extension system that can easily cover the limitations of a traditional extension. This study was conducted in the district Khanewal of Punjab, Pakistan to explore the potential of e-extension services among farmers. A totalof 234 randomly selected respondents were interviewed on a structured interview schedule. Results indicated that different types of ICT tools like computers (20.5%), mobile phones (41.0%), Radio (2.1%), Mobile apps (12.3%) and socialmediagadgets (22.2%) were being used for infotainment. The maximum time spent by the farmers on ICT tools was 3.27 hours and 2.48 hours on mobile phones and TV respectively. T-test of comparison showed a positive statistically significant difference in swing time for different crops (t= 11.328), seed varieties, treatment and rate (t= -6.336), weather update (t= 17.114), application of different fertilizer (t= 7.302) and marketing (t= 8.433). Based on the results, e-extension could be considered the future extension approach. Government and other agencies should channelise eextension services for the timely dissemination of needed information. [ABSTRACT FROM AUTHOR]