Miracle-dz/UniFAR-FTUs huggingface dataset:
Acta Polytechnica

The use of precast steel fibre reinforced concrete (SFRC) for tunnel segments is a relatively new application of this material. It was first applied in Italy in the 1980s. However, it did not begin to be widely applied until after 2000. The Czech Technical University in Prague (CTU), together with Metrostav, carried out a study to evaluate the use of this new technology for tunnels in the Czech Republic. The first tests were carried out on small samples (beams and cubes) produced from SFRC to find an appropriate type and an appropriate dosage of fibres. The tests were also used to verify other factors affecting the final product (e.g. production technology). Afterwards, SFRC segments were produced and then tested at the Klokner Institute of CTU. Successful test results confirmed that it was possible to use SFRC segments for Czech transport tunnels. Consequently a 15 m-long section of segmental lining generated from SFRC without steel rebars was constructed as part of line A of the Prague metro.
AdaBlock: SGD with Practical Block Diagonal Matrix Adaptation for Deep Learning

We introduce AdaBlock , a class of adaptive gradient methods that extends popular approaches such as Adam by adopting the simple and natural idea of using block-diagonal matrix adaption to eﬀectively utilize structural characteristics of deep learning architectures. Unlike other quadratic or block-diagonal approaches, AdaBlock has complete freedom to select block-diagonal groups, providing a wider trade-oﬀ applicable even to extremely high-dimensional problems. We provide convergence and generalization error bounds for AdaBlock , and study both theoretically and empirically the impact of the block size on the bounds and advantages over usual diagonal approaches. In addition, we propose a randomized layer-wise variant of Adablock to further reduce computations and memory footprint, and devise an eﬃcient spectrum-clipping scheme for AdaBlock to beneﬁt from Sgd ’s superior generalization performance. Extensive experiments on several deep learning tasks demonstrate the bene-ﬁts of block diagonal adaptation compared to adaptive diagonal methods, vanilla Sgd , as well as modiﬁed versions of full-matrix adaptation.
PAC Learning of Quantum Measurement Classes : Sample Complexity Bounds and Universal Consistency

We formulate a quantum analogue of the fundamental classical PAC learning problem. As on a quantum computer, we model data to be encoded by modifying speciﬁc attributes - spin axis of an electron, plane of polarization of a photon - of sub-atomic particles. Any interaction, including reading oﬀ, extracting or learning from such data is via quantum measurements, thus leading us to a problem of PAC learning Quantum Measurement Classes. We propose and analyze the sample complexity of a new ERM algorithm that respects quantum non-commutativity. Our study entails that we deﬁne the VC di-mension of Positive Operator Valued Measure(ments) (POVMs) concept classes. Our sample complexity bounds involve optimizing over partitions of jointly measurable classes. Finally, we identify universally consistent sequences of POVM classes. Technical components of this work include computations involving tensor products, trace and uniform convergence bounds.
Reinforcement Learning with Fast Stabilization in Linear Dynamical Systems

In this work, we study model-based reinforcement learning (RL) in unknown stabilizable linear dynamical systems. When learning a dynamical system, one needs to stabilize the unknown dynamics in order to avoid system blow-ups. We propose an algorithm that certifies fast stabilization of the underlying system by effectively exploring the environment with an improved exploration strategy. We show that the proposed algorithm attains $\tilde{\mathcal{O}}(\sqrt{T})$ regret after $T$ time steps of agent-environment interaction. We also show that the regret of the proposed algorithm has only a polynomial dependence in the problem dimensions, which gives an exponential improvement over the prior methods. Our improved exploration method is simple, yet efficient, and it combines a sophisticated exploration policy in RL with an isotropic exploration strategy to achieve fast stabilization and improved regret. We empirically demonstrate that the proposed algorithm outperforms other popular methods in several adaptive control tasks.
Unifying Importance Based Regularisation Methods for Continual Learning

Continual Learning addresses the challenge of learning a number of diﬀerent tasks sequentially. The goal of maintaining knowledge of earlier tasks without re-accessing them starkly conﬂicts with standard SGD training for artiﬁ-cial neural networks. An inﬂuential method to tackle this problem without storing old data are so-called regularisation approaches. They measure the importance of each parameter for solving a given task and subsequently protect important parameters from large changes. In the literature, three ways to measure parameter importance have been put forward and they have inspired a large body of follow-up work. Here, we present strong theoretical and empirical evidence that these three meth-ods, Elastic Weight Consolidation (EWC), Synaptic Intelligence (SI) and Memory Aware Synapses (MAS), are surprisingly similar and are all linked to the same theoretical quantity. Concretely, we show that, despite stemming from very diﬀerent motivations, both SI and MAS approximate the square root of the Fisher Information, with the Fisher being the theoretically justiﬁed basis of EWC. Moreover, we show that for SI the relation to the Fisher – and in fact its performance – is due to a previously unknown bias. On top of uncovering unknown similarities and unifying regularisation approaches, we also demonstrate that our insights enable practical performance improvements for large batch training.
Investigation of mechanical, physicochemical, and thermal properties of new fiber from Silybum marianum bark fiber

The present investigation aimed to understand the physicochemical properties of the new cellulosic fiber extracted from the bark of Silybum marianum (SM), in view of using it as a potential reinforcement for polymer composites. The morphological and anatomy, physical, thermal and mechanical properties of fibers were firstly discussed in this paper. The Silybum marianum fibers (SMF) were characterized by scanning electron microscopy, Fourier transform infrared, thermogravimetric analysis (TGA), optical microscope, X-ray diffraction (XRD), and single fiber tensile test. The average Young’s modulus and the breaking stress data presented by the fibers are 15.97 GPa and 201.16 MPa, respectively. XRD reveals the presence of cellulose with a crystallinity index of 45%. Thermal stability (250°C) and maximum degradation temperature (357.72°C) of the SMF are established by the thermogravimetric analysis. An analysis of the mechanical properties was carried out on a population of 35 samples using Weibull statistics with two and three parameters.
Nonparametric Relational Models with Superrectangulation

This paper addresses the question, “What is the smallest object that contains all rectangular partitions with n or fewer blocks? ” and shows its application to relational data analysis using a new strategy we call super Bayes as an alternative to Bayesian nonparametric (BNP) methods. Conventionally, standard BNP methods have combined the Aldous-Hoover-Kallenberg representation with parsimonious stochastic processes on rectangular partitioning to construct BNP relational models. As a result, conventional methods face the great difficulty of searching for a parsimonious random rectangular partition that fits the observed data well in Bayesian inference. As a way to essentially avoid such a problem, we propose a strategy to combine an extremely redundant rectangular partition as a deterministic (non-probabilistic) object. Specifically, we introduce a special kind of rectangular partitioning, which we call super-rectangulation , that contains all possible rectangular partitions. Delightfully, this strategy completely eliminates the difficult task of searching around for random rectangular partitions, since the superrectangulation is deterministically fixed in inference. Experiments on predictive performance in relational data analysis show that the super Bayesian model provides a more stable analysis than the existing BNP models, which are less likely to be trapped in bad local optima.
Long divergent haplotypes introgressed from wild sheep are associated with distinct morphological and adaptive characteristics in domestic sheep

The worldwide sheep population comprises more than 1000 breeds. Together, these exhibit a considerable morphological diversity, which has not been extensively investigated at the molecular level. Here, we analyze whole-genome sequencing individuals of 1,098 domestic sheep from 154 breeds, and 69 wild sheep from seven Ovis species. On average, we detected 6.8%, 1.0% and 0.2% introgressed sequence in domestic sheep originating from Iranian mouflon, urial and argali, respectively, with rare introgressions from other wild species. Interestingly, several introgressed haplotypes contributed to the morphological differentiations across sheep breeds, such as a RXFP2 haplotype from Iranian mouflon conferring the spiral horn trait, a MSRB3 haplotype from argali strongly associated with ear morphology, and a VPS13B haplotype probably originating from urial and mouflon possibly associated with facial traits. Our results reveal that introgression events from wild Ovis species contributed to the high rate of morphological differentiation in sheep breeds, but also to individual variation within breeds. We propose that long divergent haplotypes are a ubiquitous source of phenotypic variation that allows adaptation to a variable environment, and that these remain intact in the receiving population due to reduced recombination.
Radon/thoron and progeny levels in dwellings: Regional variations and effect of dwelling characteristics – A case study in Jalandhar district of Punjab, India

An extensive survey to measure natural radioactivity in human environment in Jalandhar district of Punjab was undertaken. Results of measurements of indoor radon/thoron and their progeny concentrations are being presented here. Single-entry, pin-hole dosemeters were used for the measurement of radon/thoron concentrations. Deposition-based direct radon/thoron progeny sensors were used for measurement of progeny concentrations. The results have been analysed on the basis of regional characteristics, type of construction and building material used. The radon concentration was found to vary from 6.64 ± 1.72 Bq/m3 to 47.18 ± 4.43 Bq/m3 with geometric mean value of 17.9 ± 2.91 Bq/m3 while the thoron concentration varies from 7.75 ± 2.54 Bq/m3 to 82.68 ± 8.33 Bq/m3 with geometric mean value of 33.54 ± 5.09 Bq/m3. The geometric mean value of equilibrium factor for indoor radon and thoron was found to be 0.43 and 0.02, respectively. The estimated annual inhalation dose varies from 0.22 mSv to 1.76 mSv with geometric mean value of 0.66 mSv. Correlation of indoor radon and air gamma dose rate was also studied.
INVESTIGATION OF WORK RELATED HEALTH HAZARDS PREVALENT AMONG METAL FABRICATION WORKERS IN NIGERIA

The consideration of facility engineering principles in the design of sustainable workstations in manufacturing industries remains inadequate with the increasing intensity of observed misfit between facility arrangement and human demand for comfort, safety and effective operation of work system. Associated with these inadequacies are the problems resulting from improper workplace design, ill structured jobs, chaotic workplace, adverse environment, poor human-machine system design and inappropriate management programmes. This study investigates the work related health hazards among fabrication workers in Nigeria. Participatory Ergonomic Intervention Approach (PEIA) and analytical method were employed to drive the investigation towards achieving a safe, productive and ergonomic workstation which provides significant shift in the existing paradigm in metal fabrication industry. Poor work posture such as bending, twisting, over reaching, kneeling, under hazardous environment of heat, noise, smoke, dust and optical radiation were identified as hindrances to effective operation. Likewise, health related issues as pains on the neck, back, wrist, knee, elbow, shoulder, wrist, as well as leg muscle cramp assumed significant prevalence accounting for 29% of the workforce. The study therefore suggests the development of standard anthropometric dimensions for the construction of assembly workstation for metal fabrication industry. Such workstation is capable of boosting workers’ morale, reduced Work Related Musculoskeletal Disorder (WRMD) and enhanced productivity with the support of enforced legislative instrumentality
Adult Attachment, Loneliness, Covid-19 Risk Perception and Perceived Stress During Covid-19 Pandemic

The Covid-19 pandemic has spread throughout the world, affecting the psychological well-being of individuals. Drawing on the attachment theory perspective, the present work sought to understand individual differences in response to the Covid-19 pandemic, analyzing the emotional and cognitive factors involved. A cross-sectional study was conducted to examine the complex relationship between attachment anxiety and avoidance, loneliness, Covid-19 risk perception, and perceived stress during the Covid-19 pandemic. Seven hundred sixty-one participants were involved. Data were analyzed using path analysis. Consistent with attachment theory, results showed a direct relationship between attachment anxiety and perceived stress during the Covid 19 pandemic, mediated in part by loneliness and Covid 19 risk perception. Similarly, attachment avoidance was directly related to perceived stress during the Covid-19 pandemic;this relationship was partially mediated by loneliness but not by Covid-19 risk perception. Our results demonstrate the influence of adult attachment on perceived stress during the Covid-19 pandemic through its effect on emotional and cognitive variables, providing useful information for implementing interventions to promote individual well-being during these times of health emergency © 2022. by the Author(s);licensee Mediterranean Journal of Clinical Psychology, Messina, Italy. This article is an open access article, licensed under a Creative Commons Attribution 4.0 Unported License
Cervical Spinal Lesion, Completeness of Injury, Stress, and Depression Reduce the Efficiency of Mental Imagery in People With Spinal Cord Injury

Objectives The aims of this study were to assess the relationships of (1) clinical variables (age, level of injury, time since injury [TSI], and completeness of injury) and (2) psychological variables (stress and depression) with mental imagery ability in individuals with spinal cord injury. Study Design This was a cross-sectional study. Participants with spinal cord injury (N = 130) were requested to fill the Kinesthetic and Visual Imagery Questionnaire and Vividness of Motor Imagery Questionnaire. They also completed the Perceived Stress Scale and Patient Health Questionnaire 9 for the assessment of stress and depression, respectively. Results Mental imagery scores were found to be significantly low in cervical injuries (P < 0.001) as compared with thoracic injuries (P < 0.001). Furthermore, higher levels of spinal injuries resulted in lower mental imagery scores. Completeness of injury (according to Asia Impairment Scale) also had a significant relationship (P < 0.001) with the mental imagery ability among spinal cord injury participants. Presence of stress (P < 0.001) and depression (P < 0.001) also associated with reduced efficiency of mental imagery in these individuals. Conclusions Injury type and psychological factors were associated with mental imagery in SCI patients. Imagery-based interventions should be designed after consideration of identified factors yielding effect on their outcomes. To Claim CME Credits Complete the self-assessment activity and evaluation online at http://www.physiatry. org/JournalCME CME Objectives Upon completion of this article, the reader should be able to: (1) Determine the impact of clinical variables such as level of injury, completeness and chronicity of injury on mental imagery ability in spinal cord injury; (2) Discuss the role of stress and depression on mental imagery ability in spinal cord injury; and (3) Describe the various dimensions of mental imagery ability and its variability among individuals who have spinal cord injury. Level Advanced Accreditation The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.
The Well: A Story of Love, Death & Real Life in the Seminal Online Community

From the Publisher: "It was the Orwellian year of 1984, when Stewart Brand, originator of the Whole Earth Catalog, and Larry Brilliant, a philanthropic doctor, created The Whole Earth 'Lectric Link, or The Well. Yet, rather than heralding Big Brother, it soon became a liberating cultural innovation that has helped change our world. A balky VAX computer and a rack of modems in ramshackle offices in Sausalito, California, The Well provided a place in the virtual world for people to discuss myriad topics online. It also had a dual existence as members organized parties and rallied to give emotional and financial support to fellow members in crisis. The Well quickly became a community as cherished by its denizens as any small town in America. " "This fascinating chronicle of an innovative business venture is also a moving story of interconnected lives. Well Beings ranged from commune-dwellers to technologists to business people to Deadheads. But all members adhered to founder Brand's original credo of personal responsibility, "You own your own words. " As revealing as diary entries, dozens of verbatim electronic postings provide unique windows into such events as: Maurice Weitman's reunion with his biological mother: "After over twelve years of searching, and almost forty years of wondering, I've located the woman who gave birth to me and then relinquished me for adoption"; a brutal lovers' quarrel between Tom Mandel and Maria Syndicus that dominated conversation on The Well for weeks, followed months later by his farewell, amid a tragic bout with cancer: "So, thank you all, my best wishes and prayers to each and everyone of you. It's been a fabulous life and it wouldn't have been the same without you. ""--BOOK JACKET.
Dielectric Properties of GNPs@MgO/CuO@PVDF Composite Films ve Dielektrik Özellikleri

: In this study, it is aimed to develop dielectric materials with high dielectric coefficient for flexible capacitors. For this purpose, MgO/CuO nanoparticles were first synthesized by precipitation reactions. Then, these particles were added together with graphene nanoplates (GNPs) into PVDF in different compositions to form a composite mixture. After this process, flexible composite films of 30 μm thickness were formed with doctor blade and phase inversion methods. In the characterization processes, it was determined that MgO/CuO particles were successfully produced with an average size of 282 nm. On the other hand, the highest capacitance and dielectric coefficient values of the composite films were determined in the GNPs@MgO/CuO@PVDF sample as 2.8 nF and 42.6 at 100 Hz frequency, respectively. As a result, it was concluded that the dielectric properties were significantly improved with the use of graphene and metal oxides together, and PVDF was very successful in terms of flexibility and binding role.
A new approach for investigating spatial relationships of ichnofossils: a case study of Ediacaran–Cambrian animal traces

Abstract. Trace fossils record foraging behaviors, the search for resources in patchy environments, of animals in the rock record. Quantification of the strength, density, and nature of foraging behaviors enables the investigation of how these may have changed through time. Here, we present a novel approach to explore such patterns using spatial point process analyses to quantify the scale and strength of ichnofossil spatial distributions on horizontal bedding planes. To demonstrate the utility of this approach, we use two samples from the terminal Ediacaran Shibantan Member in South China (between 551 and 543 Ma) and the early Cambrian Nagaur Sandstone in northwestern India (between 539 and 509 Ma). We find that ichnotaxa on both surfaces exhibited significant nonhomogeneous lateral patterns, with distinct levels of heterogeneity exhibited by different types of trace fossils. In the Shibantan, two ichnotaxa show evidence for mutual positive aggregation over a shared resource, suggesting the ability to focus on optimal resource areas. Trace fossils from the Nagaur Sandstone exhibit more sophisticated foraging behavior, with greater niche differentiation. Critically, mark correlation functions highlight significant spatial autocorrelation of trace fossil orientations, demonstrating the greater ability of these Cambrian tracemakers to focus on optimal patches. Despite potential limitations, these analyses hint at changes in the development and optimization of foraging at the Ediacaran/Cambrian transition and highlight the potential of spatial point process analysis to tease apart subtle differences in behavior in the trace fossil record.
Online In-Tube Solid-Phase Microextraction Coupled with Liquid Chromatography–Tandem Mass Spectrometry for Automated Analysis of Four Sulfated Steroid Metabolites in Saliva Samples

Accurate measurement of sulfated steroid metabolite concentrations can not only enable the elucidation of the mechanisms regulating steroid metabolism, but also lead to the diagnosis of various related diseases. The present study describes a simple and sensitive method for the simultaneous determination of four sulfated steroid metabolites in saliva, pregnenolone sulfate (PREGS), dehydroepiandrosterone sulfate (DHEAS), cortisol sulfate (CRTS), and 17β-estradiol-3-sulfate (E2S), by online coupling of in-tube solid-phase microextraction (IT-SPME) and stable isotope dilution liquid chromatography–tandem mass spectrometry (LC–MS/MS). These compounds were extracted and concentrated on Supel-Q PLOT capillary tubes by IT-SPME and separated and detected within 6 min by LC–MS/MS using an InertSustain swift C18 column and negative ion mode multiple reaction monitoring systems. These operations were fully automated by an online program. Calibration curves using their stable isotope-labeled internal standards showed good linearity in the range of 0.01–2 ng mL−1 for PREGS, DHEAS, and CRTS and of 0.05–10 ng mL−1 for E2S. The limits of detection (S/N = 3) of PREGS, DHEAS, CRTS, and E2S were 0.59, 0.30, 0.80, and 3.20 pg mL−1, respectively. Moreover, intraday and interday variations were lower than 11.1% (n = 5). The recoveries of these compounds from saliva samples were in the range of 86.6–112.9%. The developed method is highly sensitive and specific and can easily measure sulfated steroid metabolite concentrations in 50 μL saliva samples.