Miracle-dz/UniFAR-FTUs huggingface dataset:
Alexithymia as a risk factor for poor emotional outcomes in adults with acquired brain injury

ABSTRACT Emotional disorders are pervasive in the acquired brain injury (ABI) population, adversely affecting quality of life and rehabilitation. This study aimed to explore the unique associative effects of alexithymia as measured by the Perth Alexithymia Questionnaire (PAQ; i.e., difficulty identifying positive/negative feelings, difficulty describing positive/negative feelings, and externally orientated thinking), on emotional outcomes as measured by the Depression Anxiety Stress Scale-21 (DASS-21) and Mayo-Portland Adaptability Inventory (MPAI-4) Adjustment index, in 83 adults with ABI. The addition of alexithymia to hierarchical multiple regression models (controlling for demographic, injury-related, and functional outcome variables) yielded statistically significant changes in R2 for all emotional outcome measures (i.e., Depression, Anxiety, Stress, and Adjustment). Difficulty identifying negative feelings was found to be a significant unique predictor of Depression (β = .43 p = <.001), Anxiety (β = .40, p <.001), Stress (β = .49, p <.001), and Adjustment (β = .26, p = .001). Externally oriented thinking was found to be a significant unique predictor of Adjustment (β = -.15, p = .033). These findings strengthen the argument that alexithymia, especially difficulties identifying negative feelings, may be an important risk factor for psychological distress in ABI and should be considered during early rehabilitation.
Face Thermal Map of the Mexican Population in the Basal State

There has been a wide use of thermal images of the human body in recent years, specifically images with thermal information of regions of interest (ROI) in the face; this information can be used for epidemiological, clinical, and/or psychological purposes. Due to this, it is important to have plenty of information on temperature in these ROIs in the basal state that allows their use as a reference in terms of their thermal analysis. In this work, a face thermal map of the Mexican population in the basal state (n = 196) is created, adding the comparison between different population groups, such as gender, age, and clinical status, obtaining results of great interest for future research. The t-test for independent samples was applied to the ROIs with normal distribution and Mann–Whitney u-test to the ones that did not present normal distribution. Statistically significant differences were found in some of the ROI comparisons like the corrugator, the supraorbitals, and the chin between the control and clinical groups, as well as in the differentiation by age (p < 0.05).
Changes in Richness and Species Composition after Five Years of Grazing Exclusion in An Endemic Pasture of Northern Mexico

A well-managed grazing system improves the productivity and health, and it is important to promote sustainability. We analyzed the impact of grazing on the Sierra de Zapalinamé protected area in north Mexico. Our hypothesis was that grazing modifies species composition, richness, and nutrients after grazing exclusion for five years. In this area, eight plots were excluded from grazing, and species richness, evenness, and plant functional types for five years were monitored. This monitoring was also carried out on eight control plots adjacent to the excluded plots. Soil samples were collected from each plot in the fifth year of exclusion for nutrient content analysis. Grazing discriminated plant species composition after five years between excluded and control plots, but not species richness and evenness. In addition, exclusion increased grass cover and decreased forb cover. Indicator species for excluded and control sites were identified. It was concluded that part of the pastures can be excluded from grazing as a way to analyze changes in this protected area and promote greater plant diversity.
Anomaly Detection in Batch Manufacturing Processes Using Localized Reconstruction Errors From 1-D Convolutional AutoEncoders

Multivariate batch time-series data sets within Semiconductor manufacturing processes present a difficult environment for effective Anomaly Detection (AD). The challenge is amplified by the limited availability of ground truth labelled data. In scenarios where AD is possible, black box modelling approaches constrain model interpretability. These challenges obstruct the widespread adoption of Deep Learning solutions. The objective of the study is to demonstrate an AD approach which employs 1-Dimensional Convolutional AutoEncoders (1d-CAE) and Localised Reconstruction Error (LRE) to improve AD performance and interpretability. Using LRE to identify sensors and data that result in the anomaly, the explainability of the Deep Learning solution is enhanced. The Tennessee Eastman Process (TEP) and LAM 9600 Metal Etcher datasets have been utilised to validate the proposed framework. The results show that the proposed LRE approach outperforms global reconstruction errors for similar model architectures achieving an AUC of 1.00. The proposed unsupervised learning approach with AE and LRE improves model explainability which is expected to be beneficial for deployment in semiconductor manufacturing where interpretable and trustworthy results are critical for process engineering teams.
Distributed Deep Learning Model for Intelligent Video Surveillance Systems with Edge Computing

In this paper, we propose a Distributed Intelligent Video Surveillance (DIVS) system using Deep Learning (DL) algorithms and deploy it in an edge computing environment. We establish a multi-layer edge computing architecture and a distributed DL training model for the DIVS system. The DIVS system can migrate computing workloads from the network center to network edges to reduce huge network communication overhead and provide low-latency and accurate video analysis solutions. We implement the proposed DIVS system and address the problems of parallel training, model synchronization, and workload balancing. Task-level parallel and model-level parallel training methods are proposed to further accelerate the video analysis process. In addition, we propose a model parameter updating method to achieve model synchronization of the global DL model in a distributed EC environment. Moreover, a dynamic data migration approach is proposed to address the imbalance of workload and computational power of edge nodes. Experimental results showed that the EC architecture can provide elastic and scalable computing power, and the proposed DIVS system can efficiently handle video surveillance and analysis tasks.
Faster Arctic Sea Ice Retreat in CMIP5 than in CMIP3 due to Volcanoes

AbstractThe downward trend in Arctic sea ice extent is one of the most dramatic signals of climate change during recent decades. Comprehensive climate models have struggled to reproduce this trend, typically simulating a slower rate of sea ice retreat than has been observed. However, this bias has been widely noted to have decreased in models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) compared with the previous generation of models (CMIP3). Here simulations are examined from both CMIP3 and CMIP5. It is found that simulated historical sea ice trends are influenced by volcanic forcing, which was included in all of the CMIP5 models but in only about half of the CMIP3 models. The volcanic forcing causes temporary simulated cooling in the 1980s and 1990s, which contributes to raising the simulated 1979–2013 global-mean surface temperature trends to values substantially larger than observed. It is shown that this warming bias is accompanied by an enhanced rate of Arctic sea ic.
Stellar Oscillations in Tensor-Vector-Scalar Theory

An alternative theory of gravity has recently been proposed by Bekenstein, named tensor-vector-scalar (TeVeS) theory, which can explain many galactic and cosmological observations without the need for dark matter. While this theory passes basic Solar System tests, and has been scrutinized with considerable detail in other weak-field regimes, comparatively little has been done in the strong-field limit of the theory. In this article, with Cowling approximation, we examine the oscillation spectra of neutron stars in TeVeS. As a result, we find that the frequencies of fundamental modes in TeVeS could become lager than those expected in general relativity, while the dependence of frequency of higher overtone on gravitational theory is stronger than that of lower modes. These imprints of TeVeS make it possible to distinguish the gravitational theory in strong-field regime via the observations of gravitational waves, which can provide unique confirmation of the existence of scalar field.
Solar fusion cross sections II: the pp chain and CNO cycles

The available data on nuclear fusion cross sections important to energy generation in the Sun and other hydrogen-burning stars and to solar neutrino production are summarized and critically evaluated. Recommended values and uncertainties are provided for key cross sections, and a recommended spectrum is given for {sup 8}B solar neutrinos. Opportunities for further increasing the precision of key rates are also discussed, including new facilities, new experimental techniques, and improvements in theory. This review, which summarizes the conclusions of a workshop held at the Institute for Nuclear Theory, Seattle, in January 2009, is intended as a 10-year update and supplement to 1998, Rev. Mod. Phys. 70, 1265.
GFEM study of magnetohydrodynamics thermo-diffusive effect on nanofluid flow over power-law stretching sheet along with regression analysis

The present paper uses the Galerkin Finite Element Method to numerically study the triple diffusive boundary layer flow of homogenous nanofluid over power-law stretching sheet with the effect of external magnetic field. The fluid is composed of nanoparticles along with dissolved solutal particles in the base fluid. The chief mechanisms responsible for enhancement of convective transport phenomenon in nanofluids - Brownian Motion, Diffusiophoresis and Thermophoresis have been considered. The simulations performed in this study are based on the boundary layer approach. Recently proposed heat flux and nanoparticle mass flux boundary conditions have been imposed. Heat transfer, solutal mass transfer and nanoparticle mass transfer are investigated for different values of controlling parameters i.e. Brownian-motion parameter, Thermophoresis parameter, magnetic influence parameter and stretching parameter. Multiple regression analysis has been performed to verify the relationship among transfer rate parameters and controlling parameters. The present study finds application in insulation of wires, manufacture of tetra packs, production of glass fibres, fabrication of various polymer and plastic products, rubber sheets etc. where the quality merit of desired product depends on the rate of stretching, external magnetic field and composition of materials used.
Next-Generation Sequencing of Four Mitochondrial Genomes of Dolichovespula (Hymenoptera: Vespidae) with a Phylogenetic Analysis and Divergence Time Estimation of Vespidae

Simple Summary Mitochondria are vital organelles found in most eukaryotes that are involved in energy metabolism. The mitochondrial genome (mtgenome) is the genetic material of mitochondria, which is responsible for the coding and translation of proteins needed by organelles. By studying the mtgenomes of insects, we can better comprehend the phylogenetic relationships and molecular evolution of insects. The mtgenomes of four wasps are described in this paper, along with comparative genomic analyses. There are gene rearrangement events and 37 genes in each of the four mtgenomes. The subfamily Stenogastrinae is the sister group to the remaining Vespidae family, and according to our concluding analysis, the genus Vespa is more closely linked to the genus Vespula than to the genus Dolichovespula. We provide new evidence for the two-origin hypothesis of eusociality in the Vespidae. This work will aid us in future research on species evolution and phylogeny in the family Vespidae. Abstract The wasp genus Dolichovespula (Hymenoptera: Vespidae: Vespinae) is a eusocial wasp group. Due to the taxonomic and phylogenetic issues with the family Vespidae, more genetic data should be gathered to provide efficient approaches for precise molecular identification. For this work, we used next-generation sequencing (also known as high-throughput sequencing) to sequence the mitochondrial genomes (mtgenomes) of four Dolichovespula species, viz. D. flora, D. lama, D. saxonica, and D. xanthicincta 16,064 bp, 16,011 bp, 15,682 bp, and 15,941 bp in length, respectively. The mitochondrial genes of the four species are rearranged. The A + T content of each mtgenome is more than 80%, with a control region (A + T-rich region), 13 protein-coding genes (PCGs), 22 tRNA genes, and two rRNA genes. There are 7 to 11 more genes on the majority strands than on the minority strands. Using Bayesian inference and Maximum-Likelihood methodologies as well as data from other species available on GenBank, phylogenetic trees and relationship assessments in the genus Dolichovespula and the family Vespidae were generated. The two fossil-based calibration dates were used to estimate the origin of eusociality and the divergence time of clades in the family Vespidae. The divergence times indicate that the latest common ancestor of the family Vespidae appeared around 106 million years ago (Ma). The subfamily Stenogastrinae diverged from other Vespidae at about 99 Ma, the subfamily Eumeninae at around 95 Ma, and the subfamily Polistinae and Vespinae diverged at approximately 42 Ma. The genus Dolichovespula is thought to have originated around 25 Ma. The origin and distribution pattern of the genus Dolichovespula are briefly discussed.
Design and Performance of a Spatial 6-RRRR Compliant Parallel Nanopositioning Stage

Piezoelectric actuators (PEAs) and compliant parallel mechanisms (CPMs) are advantageous for designing nanopositioning stages (NPSs) with multiple degrees of freedom (multi-DOFs). This paper proposes a new NPS that uses PEAs and CPMs with multiple spatial DOFs. First, the design of the mechanism is introduced. Six parallel kinematics revolute-revolute-revolute-revolute (RRRR) branched chains were used to create a 6-RRRR CPM for superior mechanical performance. Three in-plane and three out-of-plane chains were combined using a two-in-one structure to ensure fabrication feasibility. A two-in-one 6-RRRR CPM was employed to build the proposed NPS. Second, the mechanical performance was analyzed. High-efficiency finite-element modeling approaches were derived using the compliance-based matrix method (CMM) and a pseudo-rigid body model (PRBM). The model included both 6-RRRR CPM and NPS. The simulation results validated the static and dynamic performance, and the experimental results verified the kinematics. Based on the newly designed mechanism and verified mechanical performance, the proposed 6-RRRR NPS contributes to the development of spatial multi-DOF NPSs using PEAs and CPMs.
Classical and quantum cosmology of the little rip abrupt event

We analyze from a classical and quantum point of view the behavior of the universe close to a little rip, which can be interpreted as a big rip sent towards the infinite future. Like a big rip singularity, a little rip implies the destruction of all bounded structure in the Universe and is thus an event where quantum effects could be important. We present here a new phantom scalar field model for the little rip. The quantum analysis is performed in quantum geometrodynamics, with the Wheeler-DeWitt equation as its central equation. We find that the little rip can be avoided in the sense of the DeWitt criterion, that is, by having a vanishing wave function at the place of the little rip. Therefore our analysis completes the answer to the question: can quantum cosmology smoothen or avoid the divergent behavior genuinely caused by phantom matter? We show that this can indeed happen for the little rip, similar to the avoidance of a big rip and a little sibling of the big rip.
On semilinear Tricomi equations in one space dimension

For 1-D semilinear Tricomi equation $\partial_t^2 u-t\partial_x^2u=|u|^p$ with initial data $(u(0,x), \partial_t u(0,x))$ $=(u_0(x), u_1(x))$, where $t\ge 0$, $x\in\mathbb{R}$, $p>1$, and $u_i\in C_0^\infty(\mathbb{R})$ ($i=0,1$), we shall prove that there exists a critical exponent $p_{\rm crit}=5$ such that the small data weak solution $u$ exists globally when $p>p_{\rm crit}$; on the other hand, the weak solution $u$, in general, blows up in finite time when $1 1$. By this paper and \cite{HWYin1}-\cite{HWYin3}, we have given a systematic study on the blowup or global existence of small data solution $u$ to the equation $\partial_t^2 u-t\Delta u=|u|^p$ for all space dimensions. One of the main ingredients in the paper is to establish a crucial weighted Strichartz-type inequality for 1-D linear degenerate equation $\partial_t^2 w-t\partial_x^2 w=F(t,x)$ with $(w(0,x), \partial_t w(0,x))=(0,0)$, i.e., an inequality with the weight $(\frac{4}{9}t^3-|x|^2)^{\alpha}$ between the solution $w$ and the function $F$ is derived for some real numbers $\alpha$.
Management of Patients With Drug Packet Ingestion (Body Packers): A Narrative Review

Context: Due to the increased freight traffic and illicit movement of drug packages disguised inside the body, as well as the shortage of adequate surgical textbook references regarding the management, we aimed to utilize our clinical experience and collect relevant content to present a plausible solution. Evidence Acquisition: The PubMed, Scopus, Web of Sciences, and Google Scholar databases were systematically searched for related articles. Results: Of the overall 294 retrieved articles, 37 articles remained for review after the exclusion of duplicates and unrelated papers. Imaging is beneficial in several cases of body packing. Abdominopelvic computed tomography without contrast, which is likely the best diagnostic tool for identifying the existence and quantity of packets in these patents, can help doctors avoid common diagnostic mistakes. Whether it be opioids, cocaine, or amphetamines, each drug class should have a customized course of action. Conclusion: Although conservative treatment is often employed for these individuals, early surgical intervention for packet removal is advised in the cases of ingesting cocaine and amphetamine packets due to the lack of an appropriate antagonist.
Numerical implementation of lepton-nucleus interactions and its effect on neutrino oscillation analysis

We discuss the implementation of the nuclear model based on realistic nuclear spectral functions in the GENIE neutrino interaction generator. Besides improving on the Fermi gas description of the nuclear ground state, our scheme involves a new prescription for Q2 selection, meant to efficiently enforce energy-momentum conservation. The results of our simulations, validated through comparison to electron scattering data, have been obtained for a variety of target nuclei, ranging from carbon to argon, and cover the kinematical region in which quasielastic scattering is the dominant reaction mechanism. We also analyze the influence of the adopted nuclear model on the determination of neutrino oscillation parameters.
PROSPECTS FOR CONSTRAINING THE SPIN OF THE MASSIVE BLACK HOLE AT THE GALACTIC CENTER VIA THE RELATIVISTIC MOTION OF A SURROUNDING STAR

In this paper, we investigate the quality of constraining the spin of the massive black hole (MBH) at the Galactic center (GC) by using full general relativistic simulations of the motion of a surrounding star. We obtain the dependence mapping of the spin-induced signals on any spin direction of the MBH for given example stars, which indicates the feasibility to test whether the spin direction is the same as the normal of the young stellar disk located at the GC, and, further, to provide insights into the assembly history of the MBH. We demonstrate the quality of constraining the MBH spin that may be achieved, given any set of the astrometric and the redshift precisions of observational facilities. We find that in the ranges of the astrometric and the velocity precisions with 1–30 μas and 0.1–10 , an improvement in astrometric precision would be more effective at improving the quality of constraining the spin than an improvement in velocity precision. We obtain the parameter space of the semimajor axis and the eccentricity for the orbit of the target star that a high-precision constraint on the GC MBH spin can be obtained via the motion of the star. Our results show that the spin of the GC MBH can be constrained with a 1σ error ≲0.1 or even ≲0.02 by monitoring the orbital motion of a star, if existing as expected, with a semimajor axis ≲300 au and eccentricity ≳0.95 over a period shorter than a decade through future facilities.
Four-dimensional photonic lattices and discrete tesseract solitons

We theoretically study discrete photonic lattices in more than three dimensions and point out that such systems can exist in continuous three-dimensional space. We study discrete diffraction in the linear regime and demonstrate the existence of four-dimensional (4D) tesseract solitons in nonlinear 4D periodic photonic lattices. Finally, we propose a design towards a potential realization of such periodic 4D lattices in experiments.
Artificial intelligence and decision problems: The need for an ethical context

Computers process information and make decisions. Until recently, the decisions they made were not complex, but due to the incessant technological advances that are taking place, systems based on artificial intelligence are achieving levels of competence in decision-making that in many contexts equal or surpass those of humans. These are autonomous decision-making systems that, although they can increase the capacity and efficiency of people in their fields of action, they could also replace them, something that is of concern to society as a whole. Avoiding dysfunctions in these systems is a priority social, scientific and technological objective, which requires theoretical models that include all the richness and variety of decision problems, that precisely define the elements that characterize them and that address the ethical principles that should guide their operation. This article describes each of these aspects in separate sections.
A Decade of MRI Compatible Robots: Systematic Review

Magnetic resonance imaging (MRI) offers better visualization for diagnosis, interventional radiology, and surgery from other imaging modalities without X-ray exposure. Medical robots have provided solutions for many surgical and rehabilitation procedures. A symbiosis of MRI and robotics can allow manipulation in closed MR-gantry, decrease trauma, operation, and recovery time for patients and improve the dexterity, convenience, and surgical outcome for physicians. However, the inherent properties and limitations of MR scanners had hindered their development. Technological advancements in the field of computers, additive manufacturing, and sensing in the past decade have changed robotics and the focus shifted again toward MRI-compatible robots. This article provides a compendium of the state-of-the-art literature on robotic systems developed for the MRI environment presented between 2009 and 2021. The systematic review discusses surgical and fMRI study robots, the actuation, and sensing solutions developed to assist such robots, recent research emphasis, current limitations, and prospects.
Non-Markovian models of the growth of a polymer chain

Using simple exactly solvable models, we show that event-dependent time delays may lead to significant non-Poisson effects in the statistics of polymer chain growth. The results are confirmed by stochastic simulation of various growth scenarios. Our interest in mathematical aspects of non-Markovian growth arises from recent successful application of delayed probability density functions in stochastic modelling of controlled radical polymerization.