Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing giga-scale memory systems with stt-ram

Spin-Transfer Torque RAM (STT-RAM) is an emerging non-volatile memory technology with the potential to be used as universal memory. The near-SRAM endurance and CMOS compatibility makes it suitable for use throughout the memory and storage hierarchies. However, the density is significantly lower than Flash, and the high write-currents limit the performance and energy-efficiency of STT-RAM caches. This dissertation presents tools and techniques for modeling and optimizing STT-RAM for use in high-speed memory system design. This makes it possible to compare published magnetic tunnel junction (MTJ) designs and perform first-order evaluations of cache and memory designs. Augmenting a Flash-based Solid-State Disk with a STT-RAM merge cache can reduce the response time by more than 75%, while sacrificing the retention-time of the memory cells improves both the performance and energy-efficiency of STT-RAM caches. Detailed error modeling makes it possible to design a refreshing scheme that maintains the reliability of the system, and dynamically adjusting the refresh rate according to current temperature reduces the refresh overhead. This adaptive refreshing can reduce the cell area by more than 28%, compared to STT-RAM with error, while simultaneously limiting the impact of performance and consumption.
Application of screening test for obstructive sleep apnoea detection in systemic hypertensive patients

Obstructive sleep apnoea (OSA) is prevalent in patients with hypertension (HTN). There is a lack of OSA screening in patients with HTN. Diagnosis and treatment of OSA in patients with HTN may improve blood pressure control and avoid complications of undiagnosed and untreated OSA. Hence, this study was conducted with the aim to screen OSA suspects in high risk groups of patients with hypertension using Stop Bang Questionnaire and Epworth sleepiness Scale (ESS). This was a cross sectional study carried out in OPD and IPD in Department of Respiratory Medicine, Lata Mangeshkar hospital, Hingna after obtaining approval from institutional ethics committee. Total 100 patients fulfilling the inclusion criteria were included after taking informed consent. The patients were screened according to ESS and Stop Bang Questionnaire. Out of 100 , 53% of hypertensive patients were overweight / obese with mean BMI of 25.49 ± 5.43 kg/m 2 . According to Stop bang questionnaire, 56% and 34% of patients had high risk and intermediate risk of OSA respectively with mean score of 4.69 ± 1.68. According to ESS, 61% patients had low probability of OSA, 15% patient on borderline and 24% abnormal patients with mean score of 8.38 ± 4.688. BMI along with stop bang score showed high probability of OSA which was statistically significant. Screening with Stop bang questionnaire and ESS is helpful for diagnosing OSA in case of strong clinical suspicion with high BMI. This will avoid complications of undiagnosed OSA in patients with hypertension. Keywords: Obstructive sleep apnoea, Stop Bang Questionnaire, Systemic hypertension.
The Effects of Chemotherapy and Radiation Therapy Treatment on Influenza Vaccine Antibody Response of Cancer Survivors

The immune response of cancer patients is depressed in comparison to healthly individuals. Previous studies have shown that many components of B and T cell immunity are deficient during the active phase of cancer treatment, and some cancer patients are at twice the risk of being infected with influenza virus in comparison to the general population. In this study, the antibody response of cancer patients to H1N1 influenza virus was analyzed and compared to non-cancer participants matched by race, age, and BMI. Serum samples were collected from study participants pre and post influenza vaccination. Hemagglutination inhibition assay was performed to determine pre vaccination antibody titer, post vaccination antibody titer, fold increase of antibodies, and percent of participants protected from influenza virus. It was determined that cancer survivors who were exposed to chemotherapy and radiation therapy in the past had significantly lower H1N1 influenza virus antibody response in comparison to their non-cancer matches. Post vaccination antibody titers and fold increase of cancer survivors showed no significant difference in comparison to the control group. However, cancer survivors still had difficulty reaching an antibody titer considered protective against influenza virus, as half of this group was unable to develop an adequate antibody immune response post vaccination. This suggests that dysregulation in the immune system of cancer survivors caused by previous chemotherapy and radiation therapy treatment and/or cancer itself could be inhibiting the ability of cancer survivors to develop adequate protection from influenza vaccination.
Predicting 72-hour and 9-day return to the emergency department using machine learning

Abstract Objectives To predict 72-h and 9-day emergency department (ED) return by using gradient boosting on an expansive set of clinical variables from the electronic health record. Methods This retrospective study included all adult discharges from a level 1 trauma center ED and a community hospital ED covering the period of March 2013 to July 2017. A total of 1500 variables were extracted for each visit, and samples split randomly into training, validation, and test sets (80%, 10%, and 10%). Gradient boosting models were fit on 3 selections of the data: administrative data (demographics, prior hospital usage, and comorbidity categories), data available at triage, and the full set of data available at discharge. A logistic regression (LR) model built on administrative data was used for baseline comparison. Finally, the top 20 most informative variables identified from the full gradient boosting models were used to build a reduced model for each outcome. Results A total of 330 631 discharges were available for analysis, with 29 058 discharges (8.8%) resulting in 72-h return and 52 748 discharges (16.0%) resulting in 9-day return to either ED. LR models using administrative data yielded test AUCs of 0.69 (95% confidence interval [CI] 0.68–0.70) and 0.71(95% CI 0.70–0.72), while gradient boosting models using administrative data yielded test AUCs of 0.73 (95% CI 0.72–0.74) and 0.74 (95% CI 0.73–0.74) for 72-h and 9-day return, respectively. Gradient boosting models using variables available at triage yielded test AUCs of 0.75 (95% CI 0.74–0.76) and 0.75 (95% CI 0.74–0.75), while those using the full set of variables yielded test AUCs of 0.76 (95% CI 0.75–0.77) and 0.75 (95% CI 0.75–0.76). Reduced models using the top 20 variables yielded test AUCs of 0.73 (95% CI 0.71–0.74) and 0.73 (95% CI 0.72–0.74). Discussion and Conclusion Gradient boosting models leveraging clinical data are superior to LR models built on administrative data at predicting 72-h and 9-day returns.
Study on the importance of medical treatment and physical methods in recovering patients with knee osteoarthritis

Abstract Intrduction.Etoricoxibum belongs to the group of non-steroidal anti-inflammatory inhibitors selective of cyclooxygenase-2. The non-steroidal anti-inflammatory drugs are used to treat acute musculoskeletal disorders as they result in pain-relieving therapeutical effect. Etoricoxibum intervenes by blocking cyclooxygenase-2 and by reducing the painful and inflammatory phenomena. Material and method. The trial focused on the evolution of patients diagnosed with knee osteoarthritis after making the treatment by etoricoxibum. This study was conducted in the ambulatory regime for a period of 6 months and included 77 patients. Results and discussions It was assessed the efficacy of the complex recovery treatment for the patients diagnosed by knee osteoarthritis wich use of Etoricoxibum, in a dose of 60 mg /day, in order to improve the pain and the inflammation. The pursued objectives were: the assessment of the effects by using Etoricoxibum for the reduction of the pain and inflammation, the increase of the articular mobility and stability, the recovery of the walk and motor control, the decrease of the body weight, the increase of the quality of life. Conclusions. This trial show that, by making a combined treatment of medication and recovery, there was an reducing the pain and the inflammation as well as increasing the articular mobility. Key words: osteoarthritis, pain, ultrasound, recovery, disability,
Influence of Adenosine-5-Triphosphogluconate-Magnesium Trisodium Salt and Levocarnitine on Clinical Course, Structural and Functional Changes and Myocardial Fibrosis in Patients with Myocardial Infarction

Modern strategies of STEMI/NSTEMI management, that include revascularization by coronary stenting, bypass grafting, nowadays are used in 30-40% of urgent patients of such category. The prevalent part of patients is treated by administration of the optimal drug therapy. The objective of the research was to study the influence of adenosine-5-triphosphogluconate-magnesium trisodium salt and levocarnitine on the clinical course of STEMI/NSTEMI. Materials and methods. 100 patients with STEMI/NSTEMI were included into the research. Depending on the therapy scheme, patients were divided into three groups and the control one. Determination of the key parameters was performed initially after hospitalization and at the day of patient discharge. Results. Promising results were shown while slowing the myocardial fibrosing. Limiting of the infarcted and `stunned` myocardium area resulted in ejection fraction increase, increase of the myocardial reserve, measured by echocardiographic indexes. Conclusions. Decreasing of myocardial fibrosing can be potentiated by the pharmacological postconditioning as well as limiting of the necrotic myocardium area and increase of viable myocardium area. Pharmacological postconditioning is effective and save, that can be proved by the absence of any serious complications.
Optimal Configuration of a Downward-Facing Monocular Camera for Visual Odometry

Background/Objectives: An accurate estimation of a robot’s pose is critical for autonomous mobile vehicles. Monocular vision-based odometry is one of the robust methods used for estimating the relative motion of vehicles by using only a stream of images acquired from a camera mounted on the vehicle. Methods: The location of the camera and its configuration can affect the quality of the localization process and the maximum permissible vehicle driving speed. In this work, the elements that can affect the permissible vehicle driving speed were recognized and the equations for this allowable speed were derived. Moreover, the optimal location and configuration of a downward-facing monocular camera that ensures the success of Visual Odometry for car-like ground vehicles in low-textured environment are presented after an extensive analysis. Findings: The results show that the suggested optimal camera configuration increases the permissible vehicle driving speed. Furthermore, the percentage of correlation mismatching between image frames is decreased as the suggested camera location avoids the negative consequences of shadows and directional sunlight that can add noise to image frames and interrupt the estimation of image pixel displacement. Application/Improvements: The suggested camera configuration could be implemented in various commercial mobile robotic applications, which utilize visual odometry for improved accuracy, efficiency and cost effectiveness.
Security of information processing based on grid environment

Grid computing architecture was defined to be a complete physical layer. Based on the grid computing architecture, we divided grid nodes into supervisor grid node and execute grid nod. The data transfer in network must be in secure. In this study, we propose the encryption and decryption algorithm in each grid node to keep information processing in security. We create user information database both in supervisor and execute grid nodes. We use them to verify user processing in system. When these algorithms install in all grid nodes, we can keep processing be
Characterization of T-Cell Receptor Repertoire in Patients with Rheumatoid Arthritis Receiving Biologic Therapies

Rheumatoid arthritis (RA) is a systematic autoimmune disease, predominantly causing chronic polyarticular inflammation and joint injury of patients. For the treatment of RA, biologic disease-modifying antirheumatic drugs (bDMARDs) have been used to reduce inflammation and to interfere with disease progression through targeting and mediating the immune system. Although the therapeutic effects of bDMARDs in RA patients have been widely reported, whether these drugs also play important roles in T-cell repertoire status is still unclear. We therefore designed the study to identify the role of T-cell repertoire profiles in RA patients with different types of bDMARD treatments. A high-throughput sequencing approach was applied to profile the T-cell receptor beta chain (TCRB) repertoire of circulating T lymphocytes in eight patients given adalimumab (anti-TNF-α) with/without the following use of either rituximab (anti-CD20) or tocilizumab (anti-IL6R). We subsequently analyzed discrepancies in the clonal diversity and CDR3 length distribution as well as usages of the V and J genes of TCRB repertoire and interrogated the association between repertoire diversity and disease activities followed by the treatment of bDMARDs in these RA patients. All groups of patients showed well-controlled DAS28 scores (<2.6) after different treatment regimens of drugs and displayed no significant statistical differences in repertoire diversity, distribution of CDR3 lengths, and usage of V and J genes of TCRB. Nonetheless, a trend between overall TCRB repertoire diversity and disease activity scores in all bDMARD-treated RA patients was observed. Additionally, age was found to be associated with repertoire diversity in RA patients treated with bDMARDs. Through the profiling of the TCR repertoire in RA patients receiving different biologic medications, our study indicated an inverse tendency between TCR repertoire diversity and disease activity after biologic treatment in RA patients.
Impact of crizotinib on long-term survival of ALK-positive advanced non-small-cell lung cancer: A Chinese multicenter cohort study

Objective Crizotinib has demonstrated promising efficacy in patients with anaplastic lymphoma kinase (ALK)-positive non-small-cell lung cancer (NSCLC) in clinical trials. We conducted this retrospective multicenter study to assess the outcomes of crizotinib therapy in, to our knowledge, a large sample cohort of patients with ALK-positive advanced NSCLC. Methods We reviewed the medical records of 484 unselected ALK-positive NSCLC patients treated with crizotinib at 5 cancer centers in China from January 2013 to November 2017. Clinical data were collected from the initiation of crizotinib therapy to Response Evaluation Criteria in Solid Tumors (RECIST)-defined progressive disease (PD). Results A total of 428 eligible ALK-positive NSCLC patients were enrolled, 273 (63.8%) of whom received crizotinib as first-line treatment. The median progression-free survival (PFS) and overall survival (OS) from the initiation of crizotinib treatment were 14.4 [95% confidence interval (95% CI), 12.4−16.4] months and 53.4 (95% CI, 33.7−73.1) months, respectively. In subgroup analyses, patients who received crizotinib as first-line treatment showed a higher disease control rate (DCR) and a longer median OS compared with second-/later-line crizotinib treatment (94.8% and OS not reachedvs. 89.0% and 40.5 months, respectively). For 261 patients with RECIST-defined PD, multivariate Cox analysis revealed that in patients who received first-line crizotinib therapy, continued crizotinib beyond progressive disease (CBPD) and next-generation ALK inhibitors after crizotinib failure were associated with improved survival. Conclusions This study has demonstrated the clinically meaningful benefit of crizotinib treatment in a large cohort of Chinese ALK-positive NSCLC patients. CBPD and next-generation ALK inhibitor treatment may provide improved survival after RECIST-defined progression on crizotinib.
Discrete Time State-Space Modeling of A Wireless Control System With MATLAB

This work has been carried out to demonstrate the performances of two different state space models of a process simulator that was used for the wireless control. Wireless input/output data obtained from the Cussons P3005 type process control simulator which three different temperatures (T2, T3 and T4) were selected as the controlled variables while the heater capacity was chosen as the manipulated variable. Wireless temperature experiments were achieved by using MATLAB/Simulink program and wireless data transfer during the experiments were carried out with radio waves at a frequency of 2.4 GHz. The state space models of the process simulator were developed with the aid of System Identification Toolbox of MATLAB using the data acquired from a unit step change between % 10-80 values on the heater capacity of the process simulator. The model orders used for the estimation of the model coefficients were determined with the aid MATLAB. The comparison between the experimental and two different state space model simulated temperatures of T2, T3 and T4 temperatures on the process simulator have revealed that the n4sid state space model can be used to represent the this wireless control system. Compared to the pem model investigated, the best step responses without any oscillations, fastest rise time and response time and higher calculated fit values obtained from n4sid model showed that it had the good performance. Keywords—State-Space Modeling (SSM), System identification, MATLAB/Simulink, wireless measurement and control, discrete time
ENHIDE telehealth primary care support of adults with diabetes and chronic kidney disease

Diabetes and chronic kidney disease (CKD) commonly coexist and management is complex with frequent cardiovascular, retinal, foot and bone multi-morbidity, and increased risks of hospitalisation. The East and North Hertfordshire Clinical Commissioning Group (CCG) commissioned a pilot service to help identify and then provide a holistic virtual review of high-risk patients with diabetes and CKD, by specialist diabetes consultants, followed by Skype case-based discussions with general practitioner (GP) practices, providing an opportunity to educate and upskill primary care colleagues to help manage vulnerable patients with type 2 diabetes and CKD. In addition the project was designed to recognise the large burden of unmet clinical need and the priority to develop alternatives to …
Hybrid Web Service Selection based on Functional and Non-Functional Properties

Web service composition enables seamless and dynamic integration of business application on the web. The performance of the composed application is determined by the performance of the involved web services. Therefore, the selection of composite services is a very complex and challenging task, it becomes a decision problem on which component services should be selected so that user's preferences are satisfied, especially when it has to consider not only the user's QoS preferences (non-functional aspect) but also user's functional Preferences (functional aspect). In this paper we address this problem and present a solution that combines local selection with global optimization. The proposed solution consists of two steps: First, in the local selection, we take into account both of users' preferences and QoS requirements and use dominance relationship to select the top-k services and reduce the services involved in the composition. Second, we use a global optimization to fulfil the global requirement and select the Optimal composition by using the Tabu Search Algorithm. The experimental evaluation indicates that our approach significantly outperforms existing solutions in terms of optimality.
Text Summarization Using Demographic Algorithm with Clustering Method

Text summarization is a data mining process of extracting the summary or zest from one or more documents. A summary is nothing but the actual theme of the document or set of documents. Most commonly document summery is considered to be the sentences or words from set of documents or a single document that appear more number of times in the document with corresponding to the other words. But a report on solar power may emphasis on several aspects of solar energy and may not actually have the term solar power repeated many a times. Therefore sophisticated algorithms are needed to extract the summary from the documents. There have been several algorithms on Text and Document summarizations, utilization various aspects of similarity measures, clustering, lexical rules and distance measures. It is understood from the literature that no single technique can give best interpretation or desired result in the summarization process. Therefore in this work we propose a summarization technique with document clustering and to improve its efficiency we will include demographic algorithm in this technique.
Efficacy of Live Z-Score Neurofeedback Training for Chronic Insomnia: A Single-Case Study

Objective/Background: Insomnia is the most common sleep disorder in the general population. Pharmacological treatments have shown efficacy in the short term, yet the symptoms return once the treatment has been withdrawn. In the search for treatment options with long-lasting effects, neurofeedback (NF) has arisen as a therapeutic option. Neurofeedback is the application of operant conditioning to brain activity. The aim of this work is to show the effectiveness of Live Z-Score NF training (LZT), a paradigm within the field of NF, in a case of insomnia. Participants: A 32-year-old male with chronic insomnia since his adolescence. Methods: Thirty 35-min sessions of qEEG-guided LZT using patient’s highly preferred feedback. The main outcomes of this study were the patient’s qEEG metrics and a visual analog scale of sleep quality throughout the intervention. Results: qEEG-guided LZT showed an improvement of 90.63% of the patient’s qEEG metrics and an 82.55% relief of the clinical symptoms after 30 NF sessions. Conclusions: Although more research is needed to establish that NF based on Live Z-Score is effective for insomnia, our results suggest that NF might be a therapeutic alternative for the treatment of insomnia.
Depression and Primary Headache Symptoms Comorbidity

Introduction: Having depression is common in patients with headache, but research on this issue in Iran is limited. Objective: Investigating depression and Primary headache symptoms comorbidity Materials and Methods: Study of depression and headache comorbidity and some influential factors such as age, gender and type of headache is the goal of this case-observation study. 131client patients of nerves and mental clinic of Kermanshah Farabi Hospital, and 131 people as a control group were selected among general population of Kermanshah city randomly. Data were collected by clinical interview and based on criteria of International Headache Society (IHS) and with Beck Depression Inventory. Results: We found comorbidity of depression and headache in 58.8% of cases, with the average depression score larger than that in the control group (p<0.001). 3.8 times of depression raises the risk of primary headaches. The relationship between depression and headaches in all age groups except the 45-64 year age group was significant (p<0.05). Conclusion: Data analysis indicated a correlation between depression and headaches Conflict of interest: none declared