Balancing reconstruction error and Kullback-Leibler divergence in Variational Autoencoders

In the loss function of Variational Autoencoders there is a well known tension between two components: the reconstruction loss, improving the quality of the resulting images, and the Kullback-Leibler divergence, acting as a regularizer of the latent space. Correctly balancing these two components is a delicate issue, easily resulting in poor generative behaviours. In a recent work, Dai and Wipf obtained a sensible improvement by allowing the network to learn the balancing factor during training, according to a suitable loss function. In this article, we show that learning can be replaced by a simple deterministic computation, helping to understand the underlying mechanism, and resulting in a faster and more accurate behaviour. On typical datasets such as Cifar and Celeba, our technique sensibly outperforms all previous VAE architectures

Targeting Brutons Tyrosine Kinase in Chronic Lymphocytic Leukemia at the Crossroad between Intrinsic and Extrinsic Pro-survival Signals

Chemo immunotherapies for chronic lymphocytic leukemia (CLL) showed a positive impact on clinical outcome, but many patients relapsed or become refractory to the available treatments. The main goal of the researchers in CLL is the identification of specific targets in order to develop new therapeutic strategies to cure the disease. The B cell receptor-signalling pathway is necessary for survival of malignant B cells and its related molecules recently become new targets for therapy. Moreover, leukemic microenvironment delivers survival signals to neoplastic cells also overcoming the apoptotic effect induced by traditional drugs. In this context, the investigation of Bruton\u2019s tyrosine kinase (Btk) is useful in: i) dissecting CLL pathogenesis; ii) finding new therapeutic approaches striking simultaneously intrinsic as well as extrinsic pro-survival signals in CLL. This paper will review these main topics

Speed Finite Control Set Model Predictive Control of a PMSM fed by Matrix Converter

This paper presents a new speed Finite Control Set Model Predictive Control (FCS-MPC) algorithm which has been applied to a Permanent Magnet Synchronous Motor (PMSM) driven by a Matrix Converter (MC). This method replaces the classical cascaded control scheme with a single control law that controls the motor currents and speed. Additionally, unlike classical MC modulation methods, the method allows direct control of the MC input currents. The performance of the proposed work has been verified by simulation studies and experimental results

Fixed frequency finite-state model predictive control for indirect matrix converters with optimal switching pattern

Finite States Model Predictive Control (MPC) has been recently applied to several converters topologies for the many advantages it can provide such as fast dynamics, multi-target control capabilities, easy implementation on digital control board and capability of including constraints in the control law. However, its variable switching frequency and lower steady state waveform quality, with respect to standard control plus modulator systems, represents a limitation to its applicability. Modulated Model Predictive Control (M²PC) combines all the advantages of the simple concept of MPC together with the fixed switching frequency characteristic of PWM algorithms. In particular this work focuses on the Indirect Matrix Converter (IMC), where the tight coupling between rectifier stage and inverter stage has to be taken into account in the M²PC design. This paper proposes an M²PC solution, suitable for IMC, with an optimal switching pattern to emulate the desired waveform quality features of Space Vector Modulation (SVM). In the optimal pattern, the switching sequences of the rectifier stage and inverter stage are rearranged in order to always achieve zero-current switching on the rectifier stage, thus simplifying its commutation strategy. In addition, the optimal pattern enables M²PC to produce sinusoidal source current, sinusoidal output current and maintain all desirable characteristics of MPC

Self-efficacy for coping. Utility of the Cancer behavior inventory (Italian) for use in palliative care

Background: Newer models of palliative and supportive cancer care view the person as an active agent in managing physical and psychosocial challenges. Therefore, personal efficacy is an integral part of this model. Due to the lack of instruments in Italian to assess coping self-efficacy, the present study included the translation and validation of the Italian version of the Cancer Behavior Inventory-Brief (CBI-B/I) and an initial analysis of the utility of self-efficacy for coping in an Italian sample of palliative care patients. Methods: 216 advanced cancer patients who attended palliative care clinics were enrolled. The CBI-B/I was administered along with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30), the Mini Mental Adjustment to Cancer Scale (Mini-MAC), the Cancer Concerns Checklist (CCL), and the Hospital Anxiety and Depression Scale (HADS). The Eastern Cooperative Oncology Group Performance Status (ECOG-PS) ratings of functional capacity were completed by physicians. Results: Factor analysis confirmed that the structure of the CBI-B/I was consistent with the English version. Internal consistency reliability and significant correlations with the EORTC QLQ-C30, Mini-MAC, and HADS supported the concurrent validity of the CBI-B/I. Differences in CBI-B/I scores for high versus low levels of the CCL and ECOG-PS supported the clinical utility of the CBI-B/I. Conclusions: The CBI-B/I has strong psychometric properties and represents an important addition to newer model of palliative and supportive care. In order to improve clinical practice, the CBI-B/I could be useful in identifying specific self-efficacy goals for coping in structured psychosocial intervention

On the Foamability of AlSi12 Precursors Prepared by High Velocity Compaction

High Velocity Compaction (HVC) has been proposed as a cost-effective method to prepare foamable precursors and the feasibility of the process has been demonstrated. The impact energy results a key parameter to control the final precursor density. Increasing values of impact energy leads to a continuous enhancement of performances in terms of maximum expansion and stability of the foam up to values comparable to those of commercial Alulight® precursors

Bendamustine plus rituximab is an effective first-line treatment in hairy cell leukemia variant: A report of three cases

Hairy cell leukemia variant (HCLv) is a chronic lymphoproliferative disorder classified as a provisional entity in the 2016 WHO Classification of Lymphoid Tumors. HCLv is characterized by unfavorable prognosis, low complete remission rates and limited disease control following classical hairy cell leukemia-based regimens. In this study, we report 3 cases of elderly patients with treatment-naive, TP53 un-mutated HCLv, who were effectively treated with four cycles of bendamustine plus rituximab. The regimen was completed in all the patients with acceptable toxicity. All patients achieved a complete clinical response with no evidence of residual disease at bone marrow biopsy and flow-cytometry examination. After a median follow-up of 19 months, the 3 subjects are still in complete remission. In this work, bendamustine plus rituximab proved to be an effective and feasible first-line treatment strategy for elderly patients with TP53 un-mutated HCLv

Modulated predictive control for indirect matrix converter

Finite State Model Predictive Control (MPC) has been recently applied to several converter topologies as it can provide many advantages over other MPC techniques. The advantages of MPC include fast dynamics, multi-target control capability and relatively easy implementation on digital control platforms. However, its inherent variable switching frequency and lower steady state waveform quality, with respect to standard control which includes an appropriate modulation technique, represent a limitation to its applicability. Modulated Model Predictive Control (M2PC) combines all the advantages of MPC with the fixed switching frequency characteristic of PWM algorithms. The work presented in this paper focuses on the Indirect Matrix Converter (IMC), where the tight coupling between rectifier stage and inverter stage has to be taken into account in the M2PC design. This paper proposes an M2PC solution, suitable for IMC, with a switching pattern which emulates the desired waveform quality features of Space Vector Modulation (SVM) for matrix converters. The switching sequences of the rectifier stage and inverter stage are rearranged in order to always achieve zero-current switching on the rectifier stage, thus simplifying the current commutation strategy