Big Data Testing Techniques: Taxonomy, Challenges and Future Trends

Big Data is reforming many industrial domains by providing decision support through analyzing large data volumes. Big Data testing aims to ensure that Big Data systems run smoothly and error-free while maintaining the performance and quality of data. However, because of the diversity and complexity of data, testing Big Data is challenging. Though numerous research efforts deal with Big Data testing, a comprehensive review to address testing techniques and challenges of Big Data is not available as yet. Therefore, we have systematically reviewed the Big Data testing techniques evidence occurring in the period 2010-2021. This paper discusses testing data processing by highlighting the techniques used in every processing phase. Furthermore, we discuss the challenges and future directions. Our findings show that diverse functional, non-functional and combined (functional and non-functional) testing techniques have been used to solve specific problems related to Big Data. At the same time, most of the testing challenges have been faced during the MapReduce validation phase. In addition, the combinatorial testing technique is one of the most applied techniques in combination with other techniques (i.e., random testing, mutation testing, input space partitioning and equivalence testing) to find various functional faults through Big Data testing.Comment: 32 page

Efficacy and safety of sofosbuvir based antiviral therapy for chronic hepatitis C infection in patients with advanced chronic kidney disease

Background: Screening studies for hepatitis C have proved that it is more prevalent in patients with renal diseases. Chronic hepatitis C infection in patients with kidney disease not only accelerates renal deterioration but also adversely effects morbidity and mortality. Availability of direct acting antiviral drugs has revolutionized treatment of hepatitis C even in difficult patients. In advanced kidney diseases, selection of treatment is difficult. Aim of this study was to evaluate the efficacy and safety of Sofosbuvir based DAAs in patients with advanced CKD.Methods: In this Quasi experimental study, CHC patients with or without cirrhosis having advance CKD (eGFR <30 ml/min per 1.73 m2) and/or on dialysis were enrolled. End points of the study were documentation of SVR 12 or discontinuation of therapy. Different regimens of oral DAAs with or without Ribavirin were used.Results: 86 patients with a median age of 53 years were enrolled. 37 patients were on maintenance dialysis and 49 were not on dialysis with eGFR <30 ml/min per 1.73 m2. Virological response was 92.68% at the end of treatment and SVR was achieved by 90.2% twelve weeks after therapy. Insomnia 14%, headache 11% and anemia 7% were main dverse effects. Mean eGFR and creatinine before and after treatment remained the same. Only 2 patients relapsed, both were on dialysis thrice weekly.Conclusions: All Sofosbuvir based regimens used for the treatment of CHC in patients with end stage renal disease are effective and well tolerated. Close follow up is advised to monitor side effects

Association Between Diabetic Control And Anti-Diabetic Medication Adherence Using 8-Point Morisky Medication Adherence Scale In Local Population Of Khyber Pakhtunkhwa

Abstract: Background: Drug adherence to medications in diabetes is very necessary for strict glycemic control. Many factors in diabetics are associated with low adherence to drugs resulting in complications. Methods: This research was conducted as an observational study with cross-sectional study design. It was scheduled between July 2022 to December 2022 in medical outpatient department of Combined Military Hospital, Peshawar Results: 115 individuals were inducted over a period of 6 months from medical OPD ex Combined Military Hospital Peshawar. Five patients failed to follow-up with research team resulting in a total of 110 participants included in results. Average age across the study sample was 50.25 ± 11.97 years with 58 (52.73%) males and 52 (47.27%) females. Most participant in our study sample were educated up to matriculation with BMI &lt;25kg/m2. Average duration of diabetes across the sample was 6.1 ± 3.69 years. In treatment options, 53 (48.18%) individuals were only managed with oral therapy, 16 (14.55%) on insulin only while 41 (37.27%) were prescribed with both oral hypoglycemic drugs and insulin. Most common comorbid across study population was hypertension, seen in 59 (53.94%) diabetic patients, followed by cataract in 41 (37.47%) and IHD in 33 (30%) patients. &nbsp;In all 110 individuals, only 29 (26.36%) individuals had good glycemic control i.e., HbA1c &lt;7% with average glycosylated hemoglobin percentage measuring 8.29% ± 1.59%. As per MMAS-8 score, 25 (22.73%) patients reported good adherence, 31 (28.18%) patients reported fair adherence while rest 54 (49.09%) were found to have bad adherence. Average MMAS-8 score was 5.17. Conclusion: There is a correlation between medication adherence as measured by MMAS-8 score with control of diabetes as measured by HbA1c score in the range of 1.824% across the range of MMAS-8 score from 0-8. Sleep quality, BMI and multiple comorbid conditions were also linked with raised HbA1c. Key words: Drug adherence, Morisky Medication Adherence Scale, Diabetes, Non-diabetes, diabetic medication

Comparison Of Quality Of Sleep Between Diabetic And Non-Diabetic Population Using Pittsburgh Sleep Quality Index

Background: Sleep is an essential event that effects quality of life and hormonal balance in human body. The association between sleep and diabetes is bi-directional. Methods: This study was conducted with a case control design in the Department of Medicine of Combined Military Hospital Peshawar between June 2022 to November 2022. Results: . Mean age of study population was 51.1±12.94 years with 46% females and 54% males. Majority population was educated up to matriculation with BMI in normal (18.5-24.9 kg/m2) range. There was no statistical difference in demographic data amongst diabetic and control group . Avg HbA1c was 8.546% ± 1.57% in the diabetic group and 5.712% ± 0.49% in control group. As per PSQI questionnaire 47 (47%) participants were good sleeper across the study population, which included 17 out 50 (34%) individuals in the diabetic and 30 out of 50 (60%) in control group. This equated to statistically significant difference amongst two group with a p value 0.007. A statistically significant difference (p = 0.001) was also seen in PSQI score between diabetic and control groups (9.40 ± 5.82 vs 5.98 ± 4.85 respectively). Diabetics had 2.9 times odds (95% confidence interval 1.29-6.57, p = 0.01) of having bad quality sleep as compared to controls. In the diabetic group majority were males educated up to matriculate having medium adherence treated with both oral hypoglycemic drugs and insulin having 3 or more comorbid condition with hypertension being most prevalent single comorbid disease. Conclusion: By strict glycemic control in diabetics we can imove their quality of sleep Interventions to improve sleep hygiene can be suggested to patients by diabetes educators as part of diabetes self-management education programs

A Meta-Analysis on Clinical Outcomes of Ceftolozane versus Piperacillin in Combination with Tazobactam in Patients with Complicated Urinary Tract Infections

Objective. To evaluate efficacy and adverse events of ceftolozane/tazobactam in complicated UTI including acute pyelonephritis. Method. Databases that include PubMed, Embase, Scopus, and TRIP were searched. All randomized controlled trials and cohort studies were considered for the study. Statistical analysis was done using a fixed effects model, and results were expressed in proportion for dichotomous data and risk ratio for continuous data with 95% confidence intervals (CI). Results. A clinical cure of ceftolozane/tazobactam was found to be 92% with 95% CI of 90-94 while that of piperacillin/tazobactam was only 78% (95% CI, 74-82) in patients with complicated UTI. Microbiological eradication was still higher in the ceftolozane/tazobactam group (83%, 95% CI 81-88) when compared with piperacillin/tazobactam (63% 95% CI, 58.77-65.2). Ceftolozane/tazobactam was more effective in the treatment of complicated urinary tract infections other than acute pyelonephritis as compared to piperacillin/tazobactam (RR=1.21, 95% CI, 1.07-1.23). Serious adverse events were found comparable in both groups (RR=1.15, 95% CI, 0.64-2.09). Conclusion. The analysis showed that ceftolozane/tazobactam has better clinical outcomes including cure rates and low resistance for the treatment of complicated urinary tract infection

Humanity's Last Exam

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai

Humanity's Last Exam

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 3,000 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai