How does it really feel to act together? : Shared emotions and the phenomenology of we-agency

Research on the phenomenology of agency for joint action has so far focused on the sense of agency and control in joint action, leaving aside questions on how it feels to act together. This paper tries to fill this gap in a way consistent with the existing theories of joint action and shared emotion. We first reconstruct Pacherie’s (Phenomenology and the Cognitive Sciences, 13, 25–46, 2014) account on the phenomenology of agency for joint action, pointing out its two problems, namely (1) the necessary trade-off between the sense of self- and we-agency; and (2) the lack of affective phenomenology of joint action in general. After elaborating on these criticisms based on our theory of shared emotion, we substantiate the second criticism by discussing different mechanisms of shared affect—feelings and emotions—that are present in typical joint actions. We show that our account improves on Pacherie’s, first by introducing our agentive model of we-agency to overcome her unnecessary dichotomy between a sense of self- and we-agency, and then by suggesting that the mechanisms of shared affect enhance not only the predictability of other agents’ actions as Pacherie highlights, but also an agentive sense of we-agency that emerges from shared emotions experienced in the course and consequence of joint action.Peer reviewe

A Flexible LDPC/Turbo Decoder Architecture

Low-density parity-check (LDPC) codes and convolutional Turbo codes are two of the most powerful error correcting codes that are widely used in modern communication systems. In a multi-mode baseband receiver, both LDPC and Turbo decoders may be required. However, the different decoding approaches for LDPC and Turbo codes usually lead to different hardware architectures. In this paper we propose a unified message passing algorithm for LDPC and Turbo codes and introduce a flexible soft-input soft-output (SISO) module to handle LDPC/Turbo decoding. We employ the trellis-based maximum a posteriori (MAP) algorithm as a bridge between LDPC and Turbo codes decoding. We view the LDPC code as a concatenation of n super-codes where each super-code has a simpler trellis structure so that the MAP algorithm can be easily applied to it. We propose a flexible functional unit (FFU) for MAP processing of LDPC and Turbo codes with a low hardware overhead (about 15% area and timing overhead). Based on the FFU, we propose an area-efficient flexible SISO decoder architecture to support LDPC/Turbo codes decoding. Multiple such SISO modules can be embedded into a parallel decoder for higher decoding throughput. As a case study, a flexible LDPC/Turbo decoder has been synthesized on a TSMC 90 nm CMOS technology with a core area of 3.2 mm2. The decoder can support IEEE 802.16e LDPC codes, IEEE 802.11n LDPC codes, and 3GPP LTE Turbo codes. Running at 500 MHz clock frequency, the decoder can sustain up to 600 Mbps LDPC decoding or 450 Mbps Turbo decoding.NokiaNokia Siemens Networks (NSN)XilinxTexas InstrumentsNational Science Foundatio

Moving forward during major goal blockage: situational goal adjustment in women facing infertility

Individuals confronting chronic medical conditions often face profound challenges to cherished life goals. The primary aim of this study was to examine the associations of goal adjustment with psychological adjustment in the context of infertility. At study entry (T1; n = 97) and 6 months later (T2; n = 47), women in fertility treatment completed measures of goal blockage, goal adjustment ability, and psychological adjustment. At T1, greater perceived and actual goal blockage were related to negative psychological adjustment. Ability to disengage from the goal of biological parenthood was associated with less infertility-specific thought intrusion, whereas engagement with other goals was related to fewer depressive symptoms and greater positive states of mind. Greater general goal engagement was protective against the negative relationships between low goal disengagement and the dependent variables. Promoting letting go of the unattainable and investing in the possible may be a useful intervention to foster well-being among individuals experiencing profound goal blockage

DecGPU: distributed error correction on massively parallel graphics processing units using CUDA and MPI

<p>Abstract</p> <p>Background</p> <p>Next-generation sequencing technologies have led to the high-throughput production of sequence data (reads) at low cost. However, these reads are significantly shorter and more error-prone than conventional Sanger shotgun reads. This poses a challenge for the <it>de novo </it>assembly in terms of assembly quality and scalability for large-scale short read datasets.</p> <p>Results</p> <p>We present DecGPU, the first parallel and distributed error correction algorithm for high-throughput short reads (HTSRs) using a hybrid combination of CUDA and MPI parallel programming models. DecGPU provides CPU-based and GPU-based versions, where the CPU-based version employs coarse-grained and fine-grained parallelism using the MPI and OpenMP parallel programming models, and the GPU-based version takes advantage of the CUDA and MPI parallel programming models and employs a hybrid CPU+GPU computing model to maximize the performance by overlapping the CPU and GPU computation. The distributed feature of our algorithm makes it feasible and flexible for the error correction of large-scale HTSR datasets. Using simulated and real datasets, our algorithm demonstrates superior performance, in terms of error correction quality and execution speed, to the existing error correction algorithms. Furthermore, when combined with Velvet and ABySS, the resulting DecGPU-Velvet and DecGPU-ABySS assemblers demonstrate the potential of our algorithm to improve <it>de novo </it>assembly quality for <it>de</it>-<it>Bruijn</it>-graph-based assemblers.</p> <p>Conclusions</p> <p>DecGPU is publicly available open-source software, written in CUDA C++ and MPI. The experimental results suggest that DecGPU is an effective and feasible error correction algorithm to tackle the flood of short reads produced by next-generation sequencing technologies.</p

High Differentiation among Eight Villages in a Secluded Area of Sardinia Revealed by Genome-Wide High Density SNPs Analysis

To better design association studies for complex traits in isolated populations it's important to understand how history and isolation moulded the genetic features of different communities. Population isolates should not “a priori” be considered homogeneous, even if the communities are not distant and part of a small region. We studied a particular area of Sardinia called Ogliastra, characterized by the presence of several distinct villages that display different history, immigration events and population size. Cultural and geographic isolation characterized the history of these communities. We determined LD parameters in 8 villages and defined population structure through high density SNPs (about 360 K) on 360 unrelated people (45 selected samples from each village). These isolates showed differences in LD values and LD map length. Five of these villages show high LD values probably due to their reduced population size and extreme isolation. High genetic differentiation among villages was detected. Moreover population structure analysis revealed a high correlation between genetic and geographic distances. Our study indicates that history, geography and biodemography have influenced the genetic features of Ogliastra communities producing differences in LD and population structure. All these data demonstrate that we can consider each village an isolate with specific characteristics. We suggest that, in order to optimize the study design of complex traits, a thorough characterization of genetic features is useful to identify the presence of sub-populations and stratification within genetic isolates

Effect of Exercise Interventions on Health-Related Quality of Life After Stroke and Transient Ischemic Attack: A Systematic Review and Meta-Analysis

Exercise interventions have been shown to help physical fitness, walking and balance after stroke, but data is lacking on whether such interventions lead to improvements in health-related quality of life (HRQoL). In this systematic review and meta-analysis, thirty randomised controlled trials (n=1,836 patients) were found from PubMed, OVID MEDLINE, Web of Science, CINAHL, SCOPUS, The Cochrane Library and TRIP databases when searched from 1966 to Feb 2020, that examine the effects of exercise interventions on HRQoL after strokem or transient ischaemic attack (TIA). Exercise interventions resulted in small to moderate beneficial effects on HRQoL at intervention end (standardised mean difference (SMD) -0.23; 95% CI -0.40 to -0.07) that appeared to diminish at longer term follow up (SMD -0.11; 95%CI -0.26 to 0.04). Exercise was associated with moderate improvements in physical health (SMD -0.33; 95% CI -0.61 to -0.04) and mental health (SMD -0.29; 95% CI -0.49 to -0.09) domains of HRQoL while effects on social or cognitive composites showed little difference. Interventions that were initiated within 6 months, lasted at least 12 weeks in duration, involved at least 150 minutes per week, and included resistance training appeared most effective. Exercise can lead to moderate beneficial effects on HRQoL and should be considered an integral part of stroke rehabilitatio