ІНКРЕМЕНТНИЙ ЦИФРОВИЙ КВАЗІІДЕАЛ ІНТЕГРАТОР ЗАЯВКИ ПОПЕРЕДНЬОГО ПОТОКУ ОЦІНКИ КЕРУЮЧОЇ ІНДУКЦІЙНОЇ МАШИНИ

The performance of the speed controlled induction machine principally depends on the accuracy of the estimated flux. The proposed method compensates the error produced by the inherent problem in the “pure” integrator and measurement error. This paper describes the problem associated with a quasi-ideal digital integrator in particularly a modern DDA-type (Digital Differential Analyzer) – an incremental digital integrator (IDI). The paper essentially discusses the development of the approach to the total error correction of DDA-type IDI. It is an element for processing incremental digital input-output signals using DDA principles. The basic types of errors of the incremental digital integrator are presented and then the reasons for their appearance are examined. The differential equation dY=aYdx as an example the quantitative relation of errors is investigated. The IDI error from the analytical solution is not exceeding one increment (quant) of sub-integral function Y even during a very long interval of integration variable x. This means that the IDI becomes a practically ideal integrator. The suggested methods of correcting IDI errors can be applied in simulation, modeling, especially for dynamic systems control, etc. This method is easily applied in a DSP based induction machine control to estimate the flux.The performance of the speed controlled induction machine principally depends on the accuracy of the estimated flux. The proposed method compensates the error produced by the inherent problem in the “pure” integrator and measurement error. This paper describes the problem associated with a quasi-ideal digital integrator in particularly a modern DDA-type (Digital DifferentialAnalyzer) – an incremental digital integrator (IDI). The paper essentially discusses the development of the approach to the total error correction of DDA-type IDI. It is an element for processing incremental digital input-output signals using DDA principles. The basic types of errors of the incremental digital integrator are presented and then the reasons for their appearance are examined. The differential equation dY=aYdx as an example the quantitative relation of errors is investigated. The IDI error from the analytical solution is not exceeding one increment (quant) of sub-integral function Y even during a very long interval of integration variable x. This means that the IDI becomes a practically ideal integrator. The suggested methods of correcting IDI errors can be applied in simulation, modeling, especially for dynamic systems control, etc. This method is easily applied in a DSP based induction machine control to estimate the flux

Quantifying Model Complexity via Functional Decomposition for Better Post-Hoc Interpretability

Post-hoc model-agnostic interpretation methods such as partial dependence plots can be employed to interpret complex machine learning models. While these interpretation methods can be applied regardless of model complexity, they can produce misleading and verbose results if the model is too complex, especially w.r.t. feature interactions. To quantify the complexity of arbitrary machine learning models, we propose model-agnostic complexity measures based on functional decomposition: number of features used, interaction strength and main effect complexity. We show that post-hoc interpretation of models that minimize the three measures is more reliable and compact. Furthermore, we demonstrate the application of these measures in a multi-objective optimization approach which simultaneously minimizes loss and complexity

Incremental digital quasi-ideal integrator application for advance flux estimation of controled induction machine

The performance of the speed controlled induction machine principally depends on the accuracy of the estimated flux. The proposed method compensates the error produced by the inherent problem in the “pure” integrator and measurement error. This paper describes the problem associated with a quasi-ideal digital integrator in particularly a modern DDA-type (Digital Differential Analyzer) – an incremental digital integrator (IDI). The paper essentially discusses the development of the approach to the total error correction of DDA-type IDI. It is an element for processing incremental digital input-output signals using DDA principles. The basic types of errors of the incremental digital integrator are presented and then the reasons for their appearance are examined. The differential equation dY=aYdx as an example the quantitative relation of errors is investigated. The IDI error from the analytical solution is not exceeding one increment (quant) of sub-integral function Y even during a very long interval of integration variable x. This means that the IDI becomes a practically ideal integrator. The suggested methods of correcting IDI errors can be applied in simulation, modeling, especially for dynamic systems control, etc. This method is easily applied in a DSP based induction machine control to estimate the flux.Эффективность управления скоростью индукционной машины (ИМ – асинхронной машины) преимущественно зависит от точности измерения текущего значения её магнитного потока. Данная статья развивает проблему, связанную с квази-идеальным цифровым интегратором в форме современного цифрового дифференциального анализатора (ЦДА) – инкементнего цифрового интегратора ИЦИ. Предложенный метод компенсирует общую погрешность, возникающую собственно в "чистом" интеграторе и в результате ошибки измерения. В работе подробно рассматривается разработка метода полного исправления (коррекции) погрешности ИЦИ типа цифрового дифференциального анализатора. ИЦИ это – элемент для обработки цифровых сигналов ввода-вывода, используя принцип ЦДА. В первую очередь представлены основные типы погрешностей ИЦИ, а также исследованы причины их появления. Исследовано типовое дифференциальное уравнение dY=aYdx, как пример для анализа количественного соотношения погрешностей. Погрешность ИЦИ по сравнению с аналитическим решением не превышает одного кванта подинтегральной функции Y даже для очень длинного интервала интегрирования переменной x. Это означает, что ИЦИ становится фактически идеальным интегратором. Предложенные методы коррекции погрешностей ИЦИ могут быть применены в имитации, моделировании, и особенно для управления динамическими системами, и т.д. Этот метод легко применим в устройствах управления скоростью индукционной машины основанных на косвенном способе измерении магнитного потока машины

Computer-assisted Electrodynamic Modeling System for Oil and Gas Industry Electric Drives Study

Electrodynamics models of the oil and gas equipment that mainly consist of several controlled electric drives mechanisms and autonomous generators are considered. Applications of the model to drilling and pumping drives are presented.Рассмотрены электродинамические модели автоматизированного нефтяного и газового оборудования, состоящие преимущественно из управляемых электрических механизмов и автономных генераторов. Приведены примеры использования моделей для буровых и насосных установок.Розглянуто електродинамічні моделі автоматизованого нафтового і газового обладнання, які складаються переважно з керованих електричних механізмів і автономних генераторів. Наведено приклади використання моделей для бурових та насосних установок

Monosomal Karyotype at the Time of Diagnosis or Transplantation Predicts Outcomes of Allogeneic Hematopoietic Cell Transplantation in Myelodysplastic Syndrome

AbstractVarious cytogenetic risk scoring systems may determine prognosis for patients with myelodysplastic syndromes (MDS). We evaluated 4 different risk scoring systems in predicting outcome after allogeneic hematopoietic cell transplantation (alloHCT). We classified 124 patients with MDS using the International Prognostic Scoring System (IPSS), the revised International Prognostic Scoring System (R-IPSS), Armand's transplantation-specific cytogenetic grouping, and monosomal karyotype (MK) both at the time of diagnosis and at alloHCT. After adjusting for other important factors, MK at diagnosis (compared with no MK) was associated with poor 3-year disease-free survival (DFS) (27% [95% confidence interval, 12% to 42%] versus 39% [95% confidence interval, 28% to 50%], P = .02) and overall survival (OS) (29% [95% confidence interval, 14% to 44%] versus 47% [95% confidence interval, 36% to 59%], P = .02). OS but not DFS was affected by MK at alloHCT. MK frequency was uncommon in low-score R-IPPS and IPSS. Although IPSS and R-IPSS discriminated good/very good groups from poor/very poor groups, patients with intermediate-risk scores had the worst outcomes and, therefore, these scores did not show a progressive linear discriminating trend. Cytogenetic risk score change between diagnosis and alloHCT was uncommon and did not influence OS. MK cytogenetics in MDS are associated with poor survival, suggesting the need for alternative or intensified approaches to their treatment

Dopamine replacement therapy, learning and reward prediction in Parkinson’s disease: Implications for rehabilitation

The principal feature of Parkinson’s disease (PD) is the impaired ability to acquire and express habitual-automatic actions due to the loss of dopamine in the dorsolateral striatum, the region of the basal ganglia associated with the control of habitual behavior. Dopamine replacement therapy (DRT) compensates for the lack of dopamine, representing the standard treatment for different motor symptoms of PD (such as rigidity, bradykinesia and resting tremor). On the other hand, rehabilitation treatments, exploiting the use of cognitive strategies, feedbacks and external cues, permit to “learn to bypass” the defective basal ganglia (using the dorsolateral area of the prefrontal cortex) allowing the patients to perform correct movements under executive-volitional control. Therefore, DRT and rehabilitation seem to be two complementary and synergistic approaches. Learning and reward are central in rehabilitation: both of these mechanisms are the basis for the success of any rehabilitative treatment. Anyway, it is known that “learning resources” and reward could be negatively influenced from dopaminergic drugs. Furthermore, DRT causes different well-known complications: among these, dyskinesias, motor fluctuations, and dopamine dysregulation syndrome (DDS) are intimately linked with the alteration in the learning and reward mechanisms and could impact seriously on the rehabilitative outcomes. These considerations highlight the need for careful titration of DRT to produce the desired improvement in motor symptoms while minimizing the associated detrimental effects. This is important in order to maximize the motor re-learning based on repetition, reward and practice during rehabilitation. In this scenario, we review the knowledge concerning the interactions between DRT, learning and reward, examine the most impactful DRT side effects and provide suggestions for optimizing rehabilitation in PD. � 2016 Ferrazzoli, Carter, Ustun, Palamara, Ortelli, Maestri, Y�cel and Frazzitta

Selective inhibition of FLT3 by gilteritinib in relapsed or refractory acute myeloid leukaemia: a multicentre, first-in-human, open-label, phase 1-2 study.

BackgroundInternal tandem duplication mutations in FLT3 are common in acute myeloid leukaemia and are associated with rapid relapse and short overall survival. The clinical benefit of FLT3 inhibitors in patients with acute myeloid leukaemia has been limited by rapid generation of resistance mutations, particularly in codon Asp835 (D835). We aimed to assess the highly selective oral FLT3 inhibitor gilteritinib in patients with relapsed or refractory acute myeloid leukaemia.MethodsIn this phase 1-2 trial, we enrolled patients aged 18 years or older with acute myeloid leukaemia who either were refractory to induction therapy or had relapsed after achieving remission with previous treatment. Patients were enrolled into one of seven dose-escalation or dose-expansion cohorts assigned to receive once-daily doses of oral gilteritinib (20 mg, 40 mg, 80 mg, 120 mg, 200 mg, 300 mg, or 450 mg). Cohort expansion was based on safety and tolerability, FLT3 inhibition in correlative assays, and antileukaemic activity. Although the presence of an FLT3 mutation was not an inclusion criterion, we required ten or more patients with locally confirmed FLT3 mutations (FLT3mut+) to be enrolled in expansion cohorts at each dose level. On the basis of emerging findings, we further expanded the 120 mg and 200 mg dose cohorts to include FLT3mut+ patients only. The primary endpoints were the safety, tolerability, and pharmacokinetics of gilteritinib. Safety and tolerability were assessed in the safety analysis set (all patients who received at least one dose of gilteritinib). Responses were assessed in the full analysis set (all patients who received at least one dose of study drug and who had at least one datapoint post-treatment). Pharmacokinetics were assessed in a subset of the safety analysis set for which sufficient data for concentrations of gilteritinib in plasma were available to enable derivation of one or more pharmacokinetic variables. This study is registered with ClinicalTrials.gov, number NCT02014558, and is ongoing.FindingsBetween Oct 15, 2013, and Aug 27, 2015, 252 adults with relapsed or refractory acute myeloid leukaemia received oral gilteritinib once daily in one of seven dose-escalation (n=23) or dose-expansion (n=229) cohorts. Gilteritinib was well tolerated; the maximum tolerated dose was established as 300 mg/day when two of three patients enrolled in the 450 mg dose-escalation cohort had two dose-limiting toxicities (grade 3 diarrhoea and grade 3 elevated aspartate aminotransferase). The most common grade 3-4 adverse events irrespective of relation to treatment were febrile neutropenia (97 [39%] of 252), anaemia (61 [24%]), thrombocytopenia (33 [13%]), sepsis (28 [11%]), and pneumonia (27 [11%]). Commonly reported treatment-related adverse events were diarrhoea (92 [37%] of 252]), anaemia (86 [34%]), fatigue (83 [33%]), elevated aspartate aminotransferase (65 [26%]), and increased alanine aminotransferase (47 [19%]). Serious adverse events occurring in 5% or more of patients were febrile neutropenia (98 [39%] of 252; five related to treatment), progressive disease (43 [17%]), sepsis (36 [14%]; two related to treatment), pneumonia (27 [11%]), acute renal failure (25 [10%]; five related to treatment), pyrexia (21 [8%]; three related to treatment), bacteraemia (14 [6%]; one related to treatment), and respiratory failure (14 [6%]). 95 people died in the safety analysis set, of which seven deaths were judged possibly or probably related to treatment (pulmonary embolism [200 mg/day], respiratory failure [120 mg/day], haemoptysis [80 mg/day], intracranial haemorrhage [20 mg/day], ventricular fibrillation [120 mg/day], septic shock [80 mg/day], and neutropenia [120 mg/day]). An exposure-related increase in inhibition of FLT3 phosphorylation was noted with increasing concentrations in plasma of gilteritinib. In-vivo inhibition of FLT3 phosphorylation occurred at all dose levels. At least 90% of FLT3 phosphorylation inhibition was seen by day 8 in most patients receiving a daily dose of 80 mg or higher. 100 (40%) of 249 patients in the full analysis set achieved a response, with 19 (8%) achieving complete remission, ten (4%) complete remission with incomplete platelet recovery, 46 (18%) complete remission with incomplete haematological recovery, and 25 (10%) partial remission INTERPRETATION: Gilteritinib had a favourable safety profile and showed consistent FLT3 inhibition in patients with relapsed or refractory acute myeloid leukaemia. These findings confirm that FLT3 is a high-value target for treatment of relapsed or refractory acute myeloid leukaemia; based on activity data, gilteritinib at 120 mg/day is being tested in phase 3 trials.FundingAstellas Pharma, National Cancer Institute (Leukemia Specialized Program of Research Excellence grant), Associazione Italiana Ricerca sul Cancro

Explanations of Black-Box Model Predictions by Contextual Importance and Utility

The significant advances in autonomous systems together with an immensely wider application domain have increased the need for trustable intelligent systems. Explainable artificial intelligence is gaining considerable attention among researchers and developers to address this requirement. Although there is an increasing number of works on interpretable and transparent machine learning algorithms, they are mostly intended for the technical users. Explanations for the end-user have been neglected in many usable and practical applications. In this work, we present the Contextual Importance (CI) and Contextual Utility (CU) concepts to extract explanations that are easily understandable by experts as well as novice users. This method explains the prediction results without transforming the model into an interpretable one. We present an example of providing explanations for linear and non-linear models to demonstrate the generalizability of the method. CI and CU are numerical values that can be represented to the user in visuals and natural language form to justify actions and explain reasoning for individual instances, situations, and contexts. We show the utility of explanations in car selection example and Iris flower classification by presenting complete (i.e. the causes of an individual prediction) and contrastive explanation (i.e. contrasting instance against the instance of interest). The experimental results show the feasibility and validity of the provided explanation methods

Estimated Risk of HIV Acquisition and Practice for Preventing Occupational Exposure: A Study of Healthcare Workers at Tumbi and Dodoma Hospitals, Tanzania.

Health care workers (HCWs) are at risk of acquiring human immuno-deficiency virus (HIV) and other infections via exposure to infectious patients' blood and body fluids. The main objective of this study was to estimate the risk of HIV transmission and examine the practices for preventing occupational exposures among HCWs at Tumbi and Dodoma Hospitals in Tanzania. This study was carried out in two hospitals, namely, Tumbi in Coast Region and Dodoma in Dodoma Region. In each facility, hospital records of occupational exposure to HIV infection and its management were reviewed. In addition, practices to prevent occupational exposure to HIV infection among HCWs were observed. The estimated risk of HIV transmission due to needle stick injuries was calculated to be 7 cases per 1,000,000 HCWs-years. Over half of the observed hospital departments did not have guidelines for prevention and management of occupational exposure to HIV infections and lacked well displayed health and safety instructions. Approximately, one-fifth of the hospital departments visited failed to adhere to the instructions pertaining to correlation between waste materials and the corresponding colour coded bag/container/safety box. Seventy four percent of the hospital departments observed did not display instructions for handling infectious materials. Inappropriate use of gloves, lack of health and safety instructions, and lack of use of eye protective glasses were more frequently observed at Dodoma Hospital than at Tumbi Hospital. The poor quality of the hospital records at the two hospitals hampered our effort to characterise the risk of HIV infection acquisition by HCWs. Greater data completeness in hospital records is needed to allow the determination of the actual risk of HIV transmission for HCWs. To further reduce the risk of HIV infection due to occupational exposure, hospitals should be equipped with sufficient personal protective equipment (PPE) and HCWs should be reminded of the importance of adhering to universal precautions

Minimal residual disease prior to allogeneic hematopoietic cell transplantation in acute myeloid leukemia: a meta-analysis

Minimal residual disease prior to allogeneic hematopoietic cell transplantation has been associated with increased risk of relapse and death in patients with acute myeloid leukemia, but detection methodologies and results vary widely. We performed a systematic review and meta-analysis evaluating the prognostic role of minimal residual disease detected by polymerase chain reaction or multiparametric flow cytometry before transplant. We identified 19 articles published between January 2005 and June 2016 and extracted hazard ratios for leukemia-free survival, overall survival, and cumulative incidences of relapse and non-relapse mortality. Pre-transplant minimal residual disease was associated with worse leukemia-free survival (HR=2.76 [1.90-4.00]), overall survival (HR=2.36 [1.73-3.22]), and cumulative incidence of relapse (HR=3.65 [2.53-5.27]), but not non-relapse mortality (HR=1.12 [0.81-1.55]). These associations held regardless of detection method, conditioning intensity, and patient age. Adverse cytogenetics was not an independent risk factor for death or relapse. There was more heterogeneity among studies using flow cytometry-based than WT1 polymerase chain reaction-based detection (I(2)=75.1% vs. <0.1% for leukemia-free survival, 67.8% vs. <0.1% for overall survival, and 22.1% vs. <0.1% for cumulative incidence of relapse). These results demonstrate a strong relationship between pre-transplant minimal residual disease and post-transplant relapse and survival. Outcome heterogeneity among studies using flow-based methods may underscore site-specific methodological differences or differences in test performance and interpretation