Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Creativity and Consciousness: Unintended Consequences of the Brain’s Extraordinary Energy Efficiency?

It is proposed that both human creativity and human consciousness are (unintended) consequences of the human brain’s extraordinary energy efficiency. The topics of creativity and consciousness are treated separately, though have a common sub-structure. It is argued that creativity arises from a synergy between two cognitive modes of the human brain (which broadly coincide with Kahneman’s Systems 1 and 2). In the first, available energy is spread across a relatively large network of neurons, many of which are small enough to be susceptible to thermal (ultimately quantum decoherent) noise. In the second, available energy is focussed on a smaller subset of larger neurons whose action is deterministic. Possible implications for creative computing in silicon are discussed. Starting with a discussion of the concept of free will, the notion of consciousness is defined in terms of an awareness of what are perceived to be nearby counterfactual worlds in state space. It is argued that such awareness arises from an interplay between memories on the one hand, and quantum physical mechanisms (where, unlike in classical physics, nearby counterfactual worlds play an indispensable dynamical role) in the ion channels of neural networks, on the other. As with the brain’s susceptibility to noise, it is argued that in situations where quantum physics plays a role in the brain, it does so for reasons of energy efficiency. As an illustration of this definition of consciousness, a novel proposal is outlined as to why quantum entanglement appears to be so counter-intuitive.
Cyclic Boosting - An Explainable Supervised Machine Learning Algorithm

Supervised machine learning algorithms have seen spectacular advances and surpassed human level performance in a wide range of specific applications. However, using complex ensemble or deep learning algorithms typically results in black box models, where the path leading to individual predictions cannot be followed in detail. In order to address this issue, we propose the novel "Cyclic Boosting" machine learning algorithm, which allows to efficiently perform accurate regression and classification tasks while at the same time allowing a detailed understanding of how each individual prediction was made.
Burst-induced coronal cooling in GS 1826–24

Type I X-ray bursts in GS 1826–24, and in several other systems, may induce cooling of the hot inner accretion flow that surrounds the bursting neutron star. Given that GS 1826–24 remained persistently in the hard state over the period 2003–2008 and presented regular bursting properties, we stacked the spectra of the X-ray bursts detected by INTEGRAL (JEM-X and ISGRI) and XMM-Newton (RGS) during that period to study the effect of the burst photons on the properties of the Comptonizing medium. The extended energy range provided by these instruments allows the simultaneous observation of the burst and persistent emission spectra. We detect an overall change in the shape of the persistent emission spectrum in response to the burst photon shower. For the first time, we observe simultaneously a drop in the hard X-ray emission, together with a soft X-ray excess with respect to the burst blackbody emission. The hard X-ray drop can be explained by burst-induced coronal cooling, while the bulk of the soft X-ray excess can be described by fitting the burst emission with an atmosphere model, instead of a simple blackbody model. Traditionally, the persistent emission was assumed to be invariant during X-ray bursts, and more recently to change only in normalization but not in spectral shape; the observed change in the persistent emission level during X-ray bursts may thus trigger the revision of existing neutron star mass-radius constraints, as the derived values rely on the assumption that the persistent emission does not change during X-ray bursts. The traditional burst fitting technique leads to up to a 10% overestimation of the bolometric burst flux in GS 1826–24, which significantly hampers the comparisons of the KEPLER and MESA model against this “textbook burster”.
Engineering and Experimentally Benchmarking a Container-based Edge Computing System

While edge computing is envisioned to superbly serve latency sensitive applications, the implementation-based studies benchmarking its performance are few and far between. To address this gap, we engineer a modular edge cloud computing system architecture that is built on latest advances in containerization techniques, including Kafka, for data streaming, Docker, as application platform, and Firebase Cloud, as realtime database system. We benchmark the performance of the system in terms of scalability, resource utilization and latency by comparing three scenarios: cloud-only, edge-only and combined edge-cloud. The measurements show that edge-only solution outperforms other scenarios only when deployed with data located at one edge only, i.e., without edge computing wide data synchronization. In case of applications requiring data synchronization through the cloud, edge-cloud scales around a factor 10 times better than cloudonly, until certain number of concurrent users in the system, and above this point, cloud-only scales better. In terms of resource utilization, we observe that whereas the mean utilization increases linearly with the number of user requests, the maximum values for the memory and the network I/O heavily increase when with an increasing amount of data.
Deep Underground Neutrino Experiment (DUNE), Far Detector Technical Design Report, Volume III DUNE Far Detector Technical Coordination

The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay -- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. Volume III of this TDR describes how the activities required to design, construct, fabricate, install, and commission the DUNE far detector modules are organized and managed. This volume details the organizational structures that will carry out and/or oversee the planned far detector activities safely, successfully, on time, and on budget. It presents overviews of the facilities, supporting infrastructure, and detectors for context, and it outlines the project-related functions and methodologies used by the DUNE technical coordination organization, focusing on the areas of integration engineering, technical reviews, quality assurance and control, and safety oversight. Because of its more advanced stage of development, functional examples presented in this volume focus primarily on the single-phase (SP) detector module.
Constraining the Einstein equivalence principle with multi-wavelength observations of polarized blazars

In this paper, we present a novel method to test the Einstein's Equivalence Principle (EEP) using (simultaneous) multi-wavelength radio observations of polarized blazars. We analyze simultaneous multi-wavelength polarization observations of 3C 279 at 22, 43, and 86 GHz obtained by two antennas of the Korean VLBI Network. We obtained 15 groups of polarization data, and applied the Metropolis-Hastings Markov Chain (MHMC) to simulate the parameters when considering the EEP effect and the simplest form of Faraday rotation (single external Faraday screen). The final results show the constraint of the parameterized post-Newtonian (PPN) parameter $\gamma$ discrepancy as $\Delta \gamma_{p} = (1.91\pm0.34)\times10^{-20}$. However, the single external Faraday screen is an oversimplification for blazars because there are numerous observations show complex Faraday rotation behavior for blazars due to internal/external Faraday dispersion, beam depolarization, etc. The value $\Delta \gamma_{p}$ results of this paper can only be considered as upper limits. Only if all other effects are revealed and considered, should the result be taken as a direct measurement of the violation of the EEP.
The impact of projection effects on cluster observables: stacked lensing and projected clustering

An optical cluster finder inevitably suffers from projection effects, where it misidentifies a superposition of galaxies in multiple halos along the line-of-sight as a single cluster. Using mock cluster catalogs built from cosmological N-body simulations, we quantify the impact of these projection effects with a particular focus on the observables of interest for cluster cosmology, namely the cluster lensing and the cluster clustering signals. We find that "observed" clusters, i.e. clusters identified by our cluster finder algorithm, exhibit lensing and clustering signals that deviate from expectations based on a statistically isotropic halo model -- while both signals agree with halo model expectations on small scales, they show unexpected boosts on large scales, by up to a factor of 1.2 or 1.4 respectively. We identify the origin of these boosts as the inherent selection bias of optical cluster finders for clusters embedded within filaments aligned with the line-of-sight, and show that a minority ($\sim 30\%$) of such clusters within the entire sample is responsible for this observed boost. We discuss the implications of our results on previous studies of optical cluster, as well as prospects for identifying and mitigating projection effects in future cluster cosmology analyses.
The Deep Learning Compiler: A Comprehensive Survey

The difficulty of deploying various deep learning (DL) models on diverse DL hardware has boosted the research and development of DL compilers in the community. Several DL compilers have been proposed from both industry and academia such as Tensorflow XLA and TVM. Similarly, the DL compilers take the DL models described in different DL frameworks as input, and then generate optimized codes for diverse DL hardware as output. However, none of the existing survey has analyzed the unique design architecture of the DL compilers comprehensively. In this article, we perform a comprehensive survey of existing DL compilers by dissecting the commonly adopted design in details, with emphasis on the DL oriented multi-level IRs, and frontend/backend optimizations. We present detailed analysis on the design of multi-level IRs and illustrate the commonly adopted optimization techniques. Finally, several insights are highlighted as the potential research directions of DL compiler. This is the first survey article focusing on the design architecture of DL compilers, which we hope can pave the road for future research towards DL compiler.
Multisensory Audiovisual Processing in Children With a Sensory Processing Disorder (I): Behavioral and Electrophysiological Indices Under Speeded Response Conditions

Background Maladaptive reactivity to sensory inputs is commonly observed in neurodevelopmental disorders (e.g., autism, ADHD). Little is known, however, about the underlying neural mechanisms. For some children, atypical sensory reactivity is the primary complaint, despite absence of another identifiable neurodevelopmental diagnosis. Studying Sensory Processing Disorder (SPD) may well provide a window into the neuropathology of these symptoms. It has been proposed that a deficit in sensory integration underlies the SPD phenotype, but objective quantification of sensory integration is lacking. Here we used neural and behavioral measures of multisensory integration (MSI), which would be affected by impaired sensory integration and for which there are well accepted objective measures, to test whether failure to integrate across the senses is associated with atypical sensory reactivity in SPD. An autism group served to determine if observed differences were unique to SPD. Methods We tested whether children aged 6–16 years with SPD (N = 14) integrate multisensory inputs differently from age-matched typically developing controls (TD: N = 54), or from children with an autism spectrum disorder (ASD: N = 44). Participants performed a simple reaction-time task to the occurrence of auditory, visual, and audiovisual stimuli presented in random order, while high-density recordings of electrical brain activity were made. Results Children with SPD showed large reductions in the extent to which they benefited from multisensory inputs compared to TDs. The ASD group showed similarly reduced response speeding to multisensory relative to unisensory inputs. Neural evidence for MSI was seen across all three groups, with the multisensory response differing from the sum of the unisensory responses. Post hoc tests suggested the possibility of enhanced MSI in SPD in timeframes consistent with cortical sensory registration (∼60 ms), followed by reduced MSI during a timeframe consistent with object formation (∼130 ms). The ASD group also showed reduced MSI in the later timeframe. Conclusion Children with SPD showed reduction in their ability to benefit from redundant audio-visual inputs, similar to children with ASD. Neurophysiological recordings, on the other hand, showed that major indices of MSI were largely intact, although post hoc testing pointed to periods of potential differential processing. While these exploratory electrophysiological observations point to potential sensory-perceptual differences in multisensory processing in SPD, it remains equally plausible at this stage that later attentional processing differences may yet prove responsible for the multisensory behavioral deficits uncovered here.
Defective Gating and Proteostasis of Human ClC-1 Chloride Channel: Molecular Pathophysiology of Myotonia Congenita

The voltage-dependent ClC-1 chloride channel, whose open probability increases with membrane potential depolarization, belongs to the superfamily of CLC channels/transporters. ClC-1 is almost exclusively expressed in skeletal muscles and is essential for stabilizing the excitability of muscle membranes. Elucidation of the molecular structures of human ClC-1 and several CLC homologs provides important insight to the gating and ion permeation mechanisms of this chloride channel. Mutations in the human CLCN1 gene, which encodes the ClC-1 channel, are associated with a hereditary skeletal muscle disease, myotonia congenita. Most disease-causing CLCN1 mutations lead to loss-of-function phenotypes in the ClC-1 channel and thus increase membrane excitability in skeletal muscles, consequently manifesting as delayed relaxations following voluntary muscle contractions in myotonic subjects. The inheritance pattern of myotonia congenita can be autosomal dominant (Thomsen type) or recessive (Becker type). To date over 200 myotonia-associated ClC-1 mutations have been identified, which are scattered throughout the entire protein sequence. The dominant inheritance pattern of some myotonia mutations may be explained by a dominant-negative effect on ClC-1 channel gating. For many other myotonia mutations, however, no clear relationship can be established between the inheritance pattern and the location of the mutation in the ClC-1 protein. Emerging evidence indicates that the effects of some mutations may entail impaired ClC-1 protein homeostasis (proteostasis). Proteostasis of membrane proteins comprises of biogenesis at the endoplasmic reticulum (ER), trafficking to the surface membrane, and protein turn-over at the plasma membrane. Maintenance of proteostasis requires the coordination of a wide variety of different molecular chaperones and protein quality control factors. A number of regulatory molecules have recently been shown to contribute to post-translational modifications of ClC-1 and play critical roles in the ER quality control, membrane trafficking, and peripheral quality control of this chloride channel. Further illumination of the mechanisms of ClC-1 proteostasis network will enhance our understanding of the molecular pathophysiology of myotonia congenita, and may also bring to light novel therapeutic targets for skeletal muscle dysfunction caused by myotonia and other pathological conditions.
Cellular Senescence in Neurodegenerative Diseases

Cellular senescence is a homeostatic biological process characterized by a permanent state of cell cycle arrest that can contribute to the decline of the regenerative potential and function of tissues. The increased presence of senescent cells in different neurodegenerative diseases suggests the contribution of senescence in the pathophysiology of these disorders. Although several factors can induce senescence, DNA damage, oxidative stress, neuroinflammation, and altered proteostasis have been shown to play a role in its onset. Oxidative stress contributes to accelerated aging and cognitive dysfunction stages affecting neurogenesis, neuronal differentiation, connectivity, and survival. During later life stages, it is implicated in the progression of cognitive decline, synapse loss, and neuronal degeneration. Also, neuroinflammation exacerbates oxidative stress, synaptic dysfunction, and neuronal death through the harmful effects of pro-inflammatory cytokines on cell proliferation and maturation. Both oxidative stress and neuroinflammation can induce DNA damage and alterations in DNA repair that, in turn, can exacerbate them. Another important feature associated with senescence is altered proteostasis. Because of the disruption in the function and balance of the proteome, senescence can modify the proper synthesis, folding, quality control, and degradation rate of proteins producing, in some diseases, misfolded proteins or aggregation of abnormal proteins. There is an extensive body of literature that associates cellular senescence with several neurodegenerative disorders including Alzheimer’s disease (AD), Down syndrome (DS), and Parkinson’s disease (PD). This review summarizes the evidence of the shared neuropathological events in these neurodegenerative diseases and the implication of cellular senescence in their onset or aggravation. Understanding the role that cellular senescence plays in them could help to develop new therapeutic strategies.
Toward Enhanced Teleoperation Through Embodiment

Telerobotics aims to transfer human manipulation skills and dexterity over an arbitrary distance and at an arbitrary scale to a remote workplace. A telerobotic system that is transparent enables a natural and intuitive interaction. We postulate that embodiment (with three sub-components: sense of ownership, agency, and self-location) of the robotic system leads to optimal perceptual transparency and increases task performance. However, this has not yet been investigated directly. We reason along four premises and present findings from the literature that substantiate each of them: (1) the brain can embody non-bodily objects (e.g., robotic hands), (2) embodiment can be elicited with mediated sensorimotor interaction, (3) embodiment is robust against inconsistencies between the robotic system and the operator's body, and (4) embodiment positively correlates to dexterous task performance. We use the predictive encoding theory as a framework to interpret and discuss the results reported in the literature. Numerous previous studies have shown that it is possible to induce embodiment over a wide range of virtual and real extracorporeal objects (including artificial limbs, avatars, and android robots) through mediated sensorimotor interaction. Also, embodiment can occur for non-human morphologies including for elongated arms and a tail. In accordance with the predictive encoding theory, none of the sensory modalities is critical in establishing ownership, and discrepancies in multisensory signals do not necessarily lead to loss of embodiment. However, large discrepancies in terms of multisensory synchrony or visual likeness can prohibit embodiment from occurring. The literature provides less extensive support for the link between embodiment and (dexterous) task performance. However, data gathered with prosthetic hands do indicate a positive correlation. We conclude that all four premises are supported by direct or indirect evidence in the literature, suggesting that embodiment of a remote manipulator may improve dexterous performance in telerobotics. This warrants further implementation testing of embodiment in telerobotics. We formulate a first set of guidelines to apply embodiment in telerobotics and identify some important research topics.
Incidence and Risk Factors for Hypoglycemia During Fetal-to-Neonatal Transition in Premature Infants

Objective: To determine the incidence and risk factors associated with neonatal hypoglycemia in the premature population <33 weeks' gestation. Methods: This was a secondary retrospective analysis from previous infants enrolled in randomized controlled trials. A total of 255 infants <33 weeks' gestation were born during the study period. Eight infants were excluded due to missing glucose or maternal data and 175 infants were analyzed. Main outcome measures: Primary outcome was hypoglycemia (blood glucose <2.6mmol/L) determined via glucose oxidase method on arterial or venous blood gas. Birth weight subgroups: small for gestational age (SGA, birth weight <10%ile for gestational age) and large for gestational age (LGA, birth weight >90%ile for gestational age). Maternal hypertension was systolic blood pressure >140mmHg. Results: 175 infants <33 weeks' gestational age (89 male, 84 female) were analyzed. Hypoglycemia occurred in 59 infants (33.7%). Maternal hypertension (OR 3.07, 95% CI 1.51–6.30, p = 0.002) was the sole risk factor for neonatal hypoglycemia. Protective factors for hypoglycemia included labor at time of delivery (OR 4.51, 95% CI 2.29–9.18, p <0.0001) and antenatal magnesium sulfate (OR 2.53, 95% CI 1.23–5.50, p = 0.01). There were no significant differences between hypoglycemic and euglycemic infants in sex, gestational age, LGA infants, antenatal steroids, vaginal birth, or maternal diabetes. SGA infants were excluded from analysis due to sample size. Conclusions: Premature infants <33 weeks' gestation have increased risk of hypoglycemia. Maternal hypertension increases hypoglycemia risk. Antenatal magnesium sulfate administration or labor at time of delivery decrease hypoglycemia risk.