1,721,286 research outputs found
ESPERIENZE CLINICHE NELLE PAZIENTI CON OSTEOPOROSI : PAZIENTE CON OSTEOPOROSI E ALMENO UNA FRATTURA PREGRESSA TRATTATA CON RANELATO DI STRONZIO
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Free Bits: Latency Optimization of Mixed-Precision Quantized Neural Networks on the Edge
Full text linkMixed-precision quantization, where a deep neural
network’s layers are quantized to different precisions, offers
the opportunity to optimize the trade-offs between model size,
latency, and statistical accuracy beyond what can be achieved
with homogeneous-bit-width quantization. To navigate the in-
tractable search space of mixed-precision configurations for a
given network, this paper proposes a hybrid search methodology.
It consists of a hardware-agnostic differentiable search algorithm
followed by a hardware-aware heuristic optimization to find
mixed-precision configurations latency-optimized for a specific
hardware target. We evaluate our algorithm on MobileNetV1
and MobileNetV2 and deploy the resulting networks on a family
of multi-core RISC-V microcontroller platforms with different
hardware characteristics. We achieve up to 28.6 % reduction of
end-to-end latency compared to an 8-bit model at a negligible
accuracy drop from a full-precision baseline on the 1000-class
ImageNet dataset. We demonstrate speedups relative to an 8-bit
baseline, even on systems with no hardware support for sub-byte
arithmetic at negligible accuracy drop. Furthermore, we show
the superiority of our approach with respect to differentiable
search targeting reduced binary operation counts as a proxy for
latency
Diabetes and bone fragility: A dangerous liaison
No full textPatients with diabetes are at greater risk of fractures not only for bone mineral density (BMD) decrease, showed for type 1 diabetes mellitus (T1DM), but also for bone tissue alterations that reduce bone quality and strength; thus, BMD values do not reflect bone fragility in diabetics. Higher rates of fracture in diabetic patients can be related both to changes in bone quality and in long standing diabetes to microvascular complications that lead to a greater risk of falling. Diabetes leads to impaired bone formation through many mechanisms: insulin deficiency and hyperglycemia, prevalently by AGE/RAGE axis alteration, insulin growth factors reduction, and alterations in osteocalcin and/or Wnt signaling pathways. Therefore, an adequate glycemic control is mandatory in diabetes to preserve bone health. Metformin, incretins, and DPP-4 inhibitors have a potentially positive effect on bone status, while close attention should be paid to a long-term therapy with thiazolidinediones, because they are associated to an increased risk of fracture. © 2013 Springer International Publishing Switzerland
Transverse-momentum-dependent parton distributions in a spectator diquark model
No full textWithin the framework of a spectator diquark model of the nucleon, involving both scalar and axial-vector diquarks, we calculate all the leading-twist transverse-momentum-dependent parton distribution functions (TMDs). Naive Time-odd densities are generated through a one-gluon-loop rescattering mechanism, simulating the final state interactions required for these functions to exist. Analytic results are obtained for all the TMDs, and a connection with the light-cone wave functions formalism is also established. The model parameters are fixed by reproducing the phenomenological parametrizations of unpolarized and helicity parton distributions at the lowest available scale. Predictions for the other parton densities are given and, whenever possible, compared with available parametrizations
ViT-LR: Pushing the Envelope for Transformer-Based On-Device Embedded Continual Learning
No full textState-of-the-Art Edge Artificial Intelligence (AI) is currently mostly targeted at a train-then-deploy paradigm: edge devices are exclusively responsible for inference, whereas training is delegated to data centers, leading to high energy and CO2 impact. On-Device Continual Learning could help in making Edge AI more sustainable by specializing AI models directly on-field. We deploy a continual image recognition model on a Jetson Xavier NX embedded system, and experimentally investigate how Attention influences performance and its viability as a Continual Learning backbone, analyzing the redundancy of its components to prune and further improve our solution efficiency. We achieve up to 83.81% accuracy on the Core50's new instances and classes scenario, starting from a pre-trained tiny Vision Transformer, surpassing AR1*free with Latent Replay, and reach performance comparable and superior to the SoA without relying on growing Replay Examples
Hypophosphatasia. clinical manifestation and burden of disease in adult patients
Full text linkHypophosphatasia (HPP) is a rare inherited disease with a heterogeneous clinical expression. The adult form of HPP is often difficult to be recognized with a delayed diagnosis and inappropriate treatments. Though severity of HPP decreases with age at onset, important complications could occur at any age and the burden of HPP among adult patients is found to be significant. Adult patients with HPP suffer of chronic pain, recurrent fractures and other orthopedics problems, with severe disability that have a serious negative impact on all aspects of their life. The aim of this paper is to summarize the main aspects of HPP in adult patients reviewing the literature and focusing on its burden for patients suffering from this condition
On the Construction of Group Equivariant Non-Expansive Operators via Permutants and Symmetric Functions
Full text linkGroup Equivariant Operators (GEOs) are a fundamental tool in the research on neural networks, since they make available a new kind of geometric knowledge engineering for deep learning, which can exploit symmetries in artificial intelligence and reduce the number of parameters required in the learning process. In this paper we introduce a new method to build non-linear GEOs and non-linear Group Equivariant Non-Expansive Operators (GENEOs), based on the concepts of symmetric function and permutant. This method is particularly interesting because of the good theoretical properties of GENEOs and the ease of use of permutants to build equivariant operators, compared to the direct use of the equivariance groups we are interested in. In our paper, we prove that the technique we propose works for any symmetric function, and benefits from the approximability of continuous symmetric functions by symmetric polynomials. A possible use in Topological Data Analysis of the GENEOs obtained by this new method is illustrated
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