Total Cost of Ownership of melting furnaces: application of a prototypal model to aluminum die casting producers

After reviewing current literature on the Total Cost of Ownership (TCO) methodology and its application to manufacturing contexts, we propose an application of this methodology to secondary aluminum melting furnaces. A prototypal calculation model is created and tested through three case studies of aluminum die casting companies. We illustrate the model structure and input data used to calculate the studied furnaces TCO. At last, results of the model test are presented and possible developments of the prototypal model are briefly discussed

Peri-Procedural Management of Direct-Acting Oral Anticoagulants (DOACs) in Transcatheter Miniaturized Leadless Pacemaker Implantation

INTRODUCTION: Data on peri-operative management of direct-acting oral anticoagulants (DOACs) during transcatheter pacing leadless system (TPS) implantations remain limited. This study aimed to evaluate a standardized DOAC management regime consisting of interruption of a single dose prior to implantation and reinitiation within 6-24 h; also, patient clinical characteristics associated with this approach were identified. METHOD: Consecutive patients undergoing standard TPS implantation procedures from two Swiss tertiary centers were included. DOAC peri-operative management included the standardized approach (Group 1A) or other approaches (Group 1B). RESULTS: Three hundred and ninety-two pts (mean age 81.4 ± 7.3 years, 66.3% male, left ventricular ejection fraction 55.5 ± 9.6%) underwent TPS implantation. Two hundred and eighty-two pts (71.9%) were under anticoagulation therapy; 192 pts were treated with DOAC; 90 pts were under vitamin-K antagonist. Patients treated with DOAC less often had structural heart disease, diabetes mellitus, and advanced renal failure. The rate of major peri-procedural complications did not differ between groups 1A (n = 115) and 1B (n = 77) (2.6% and 3.8%, p = 0.685). Compared to 1B, 1A patients were implanted with TPS for slow ventricular rate atrial fibrillation (AF) (p = 0.002), in a better overall clinical status, and implanted electively (<0.001). CONCLUSIONS: Standardized peri-procedural DOAC management was more often implemented for elective TPS procedures and did not seem to increase bleeding or thromboembolic adverse events

A patient-centered multidisciplinary cardiac rehabilitation program improves glycemic control and functional outcome in coronary artery disease after percutaneous and surgical revascularization

Background: Cardiac rehabilitation (CR) is strongly associated with all-cause mortality reduction in patients with coronary artery disease (CAD). The impact of CR on pathological risk factors, such as impaired glucose tolerance (IGT), and functional recovery remains under debate. The aim of the present study is to determine whether CR has a positive effect on physical exercise improvement and on pathological risk factors in IGT and diabetic patients with CAD. Methods: One hundred and seventy-one consecutive patients participating in a 3-month CR from January 2014 to June 2015 were enrolled. The primary endpoint was defined as an improvement of peak workload and VO2-peak; glycated hemoglobin (HbA1c) reduction was considered as a secondary endpoint. Results: Euglycemic patients presented a significant improvement in peak workload compared to diabetic patients (from 5.75 ± 1.45 to 6.65 ± 1.84 METs, p = 0.018 vs. 4.8 ± 0.8 to 4.9 ± 1.4 METs). VO2-peak improved in euglycemic patients (VO2-peak from 19.3 ± 5.3 mL/min/kg to 22.5 ± 5.9, p = 0.003), while diabetic patients did not present  a  statistically significant trend (VO2-peak from 16.9 ± 4.4 mL/min/kg to 18.0 ± 3.8, p &lt; 0.056). Diabetic patients have benefited more in terms of blood glucose control compared to IGT patients (HbA1c from 7.7 ± 1.0 to 7.4 ± 1.1 compared to 5.6 ± 0.4 to 5.9 ± 0.5, p = 0.02, respectively). Conclusions: A multidisciplinary CR program improves physical functional capacity in CAD setting, particularly in euglycemic patients. IGT patients as well as diabetic patients may benefit from a CR program, but long-term outcome needs to be clarified in larger studies

Extracellular Vesicles From Perinatal Cells for Anti-inflammatory Therapy

Perinatal cells, including cells from placenta, fetal annexes (amniotic and chorionic membranes), umbilical cord, and amniotic fluid display intrinsic immunological properties which very likely contribute to the development and growth of a semiallogeneic fetus during pregnancy. Many studies have shown that perinatal cells can inhibit the activation and modulate the functions of various inflammatory cells of the innate and adaptive immune systems, including macrophages, neutrophils, natural killer cells, dendritic cells, and T and B lymphocytes. These immunological properties, along with their easy availability and lack of ethical concerns, make perinatal cells very useful/promising in regenerative medicine. In recent years, extracellular vesicles (EVs) have gained great interest as a new therapeutic tool in regenerative medicine being a cell-free product potentially capable, thanks to the growth factors, miRNA and other bioactive molecules they convey, of modulating the inflammatory microenvironment thus favoring tissue regeneration. The immunomodulatory actions of perinatal cells have been suggested to be mediated by still not fully identified factors (secretoma) secreted either as soluble proteins/cytokines or entrapped in EVs. In this review, we will discuss how perinatal derived EVs may contribute toward the modulation of the immune response in various inflammatory pathologies (acute and chronic) by directly targeting different elements of the inflammatory microenvironment, ultimately leading to the repair and regeneration of damaged tissues

Combined HW/SW Drift and Variability Mitigation for PCM-based Analog In-memory Computing for Neural Network Applications

Matrix-Vector Multiplications (MVMs) represent a heavy workload for both training and inference in Deep Neural Networks (DNNs) applications. Analog In-memory Computing (AIMC) systems based on Phase Change Memory (PCM) has been shown to be a valid competitor to enhance the energy efficiency of DNN accelerators. Although DNNs are quite resilient to computation inaccuracies, PCM non-idealities could strongly affect MVM operations precision, and thus the accuracy of DNNs. In this paper, a combined hardware and software solution to mitigate the impact of PCM non-idealities is presented. The drift of PCM cells conductance is compensated at the circuit level through the introduction of a conductance ratio at the core of the MVM computation. A model of the behaviour of PCM cells is employed to develop a device-aware training for DNNs and the accuracy is estimated in a CIFAR-10 classification task. This work is supported by a PCM-based AIMC prototype, designed in a 90-nm STMicroelectronics technology, and conceived to perform Multiply-and-Accumulate (MAC) computations, which are the kernel of MVMs. Results show that the MAC computation accuracy is around 95% even under the effect of cells drift. The use of a device-aware DNN training makes the networks less sensitive to weight variability, with a 15% increase in classification accuracy over a conventionally-trained Lenet-5 DNN, and a 36% gain when drift compensation is applied

Decoding Algorithms and HW Strategies to Mitigate Uncertainties in a PCM-Based Analog Encoder for Compressed Sensing

Analog In-Memory computing (AIMC) is a novel paradigm looking for solutions to prevent the unnecessary transfer of data by distributing computation within memory elements. One such operation is matrix-vector multiplication (MVM), a workhorse of many fields ranging from linear regression to Deep Learning. The same concept can be readily applied to the encoding stage in Compressed Sensing (CS) systems, where an MVM operation maps input signals into compressed measurements. With a focus on an encoder built on top of a Phase-Change Memory (PCM) AIMC platform, the effects of device non-idealities, namely programming spread and drift over time, are observed in terms of the reconstruction quality obtained for synthetic signals, sparse in the Discrete Cosine Transform (DCT) domain. PCM devices are simulated using statistical models summarizing the properties experimentally observed in an AIMC prototype, designed in a 90 nm STMicroelectronics technology. Different families of decoders are tested, and tradeoffs in terms of encoding energy are analyzed. Furthermore, the benefits of a hardware drift compensation strategy are also observed, highlighting its necessity to prevent the need for a complete reprogramming of the entire analog array. The results show &gt;30 dB average reconstruction quality for mid-range conductances and a suitably selected decoder right after programming. Additionally, the hardware drift compensation strategy enables robust performance even when different drift conditions are tested

Long-Term Outcome and Risk Stratification in Dilated Cardiolaminopathies

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A novel LMNA mutation (R189W) in familial dilated cardiomyopathy: evidence for a 'hot spot' region at exon 3: a case report

We describe a case of a patient with idiopathic dilated cardiomyopathy and cardiac conduction abnormalities who presented a strong family history of sudden cardiac death. Genetic screening of lamin A/C gene revealed in proband the presence of a novel missense mutation (R189W), near the most prevalent lamin A/C mutation (R190W), suggesting a "hot spot" region at exon 3