Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting the compressive strength of a quaternary blend concrete using Bayesian regularized neural network

ABSTRACT Concrete produced with ordinary Portland cement (OPC) along with insertion of supplementary materials increases the level of nonlinearity. Due to this increased non-linearity and difficulty in modeling numerically, the focus has increased on the exploration of computational intelligent models like artificial neural network (ANN) to estimate different concrete properties. In this study, a quaternary blend concrete was developed with OPC, fly ash (FA), metakaolin (MK) and rice husk ash (RHA). The experimental data were further used in training the proposed ANN models to approximate its compressive strength. The proposed neural network models were trained and optimized using three different regularization algorithms; the scaled conjugate gradient “trainsc” (SCG), Levenberg–Marquardt “trainlm” (LM) and Bayesian regularized “trainbr” (BR) algorithms. The percent proportion of OPC, FA, MK and RHA making up the quaternary blends and curing days are the five features used as input variables, while the compressive strength of each of the individual concrete mixture is the output variable (target). It was found out that ANN optimized with Bayesian regularization function performed best with the highest correlation coefficient, and lowest MAE, MSE and RMSE. The results obtained from the ANN approach show significant improvement with the experimental observations.
Osteohistology and Paleobiological Inferences of Proterochampsids (Eucrocopoda: Proterochampsia) from the Chañares Formation (Late Ladinian–Early Carnian), La Rioja, Argentina

ABSTRACT Proterochampsids were a group of stem archosaurs from the Middle–Late Triassic of South America. Using for the first time in proterochampsids quantitative microanatomical and morphological data and an inference model, we analyze the microstructure of postcranial bones of proterochampsids to infer life-history traits dealing with growth dynamics, ontogenetic changes, dermal armor histogenesis and lifestyle. We studied proterochampsid individuals from the Middle–Late Triassic Chañares Formation: three specimens of Chanaresuchus bonapartei: PVL 4575 (osteoderms and femur), CRILAR-Pv 80 (osteoderm) and CRILAR-Pv 81 (humerus), and a femur of a non-identified Rhadinosuchinae specimen (CRILAR-Pv 488). The osteoderms show a compact-uniform composition of parallel-fibered bone and lines of arrested growth (LAGs). The long bones are composed mainly of highly vascularized, parallel-fibered bone and isolated areas of woven-fibered bone in the innermost portion of cortex (only in C. bonapartei PVL 4575). The absence of an external fundamental system (EFS) indicates that all of the sampled individuals were somatically immature at time of death. The absence of mineralized bundles of collagenous fibers supports intramembranous ossification as the developmental origin for the osteoderms. With an inference model used for the first time in proterochampsids, the lifestyle inferred for C. bonapartei is terrestrial. Histological evidence indicates that sexual maturity is reached before both somatic and skeletal maturity. The growth patterns among proterochampsids exhibit some degree of variation even within a single species. Such variation can be due to different causes, including possibly phenotypic plasticity.
Thermal aging behavior characteristics of asphalt binder modified by nano-stabilizer based on DSR and AFM

Abstract In order to clarify the effect of thermal aging on the nano-stabilized modified asphalt binder, TINUVIN 770 (T770) hindered amine light stabilizer of nanoscale was selected as aging modifying agent to prepare modified asphalt. The impact of thermal aging on the rheological properties of T770-modified asphalt was investigated using dynamic shear rheological test of frequency sweep and multiple stress creep recovery test. The surface roughness variation of T770-modified asphalt was characterized by using atomic force microscope throughout the thermal aging process. Furthermore, the typical morphology and parameter features of T770-modified asphalt were identified. The results showed that with the extension of thermal aging time, the high temperature rutting resistance of T770-modified asphalt was improved, while the unrecoverable creep compliance was degraded. When the thermal aging time exceeded 6 h, the bee structure appeared on the surface of T770-modified asphalt. Meanwhile, with the increase in thermal aging time, the special structure formed on the surface of asphalt gradually became smaller. The surface fluctuation difference of T770-modified asphalt reflected the better thermal aging resistance property of T770-modified asphalt than 70# asphalt.
Immersive audio, capture, transport, and rendering: a review

Immersive audio has received significant attention in the past decade. The emergence of a few groundbreaking systems and events (Dolby Atmos, MPEG-H, VR/AR, AI) contributes to reshaping the landscape of this field, accelerating the mass market adoption of immersive audio. This review serves as a quick recap of some immersive audio background, end to end workflow, covering audio capture, compression, and rendering. The technical aspects of object audio and ambisonic will be explored, as well as other related topics such as binauralization, virtual surround, and upmix. Industry trends and applications are also discussed where user experience ultimately decides the future direction of the immersive audio technologies.
Scaring People is Not Enough: An Examination of Fear Appeals within the Context of Promoting Good Password Hygiene

Fear appeals have been used for thousands of years to scare people into engaging in a specific behavior or omitting an existing one. From religion, public health campaigns, political ads, and most recently, cybersecurity, fear appeals are believed to be effective tools. However, this assumption is often grounded in intuition rather than evidence. We know little about the specific contexts within which fear appeals may or may not work. In this study, we begin to examine various components of a fear appeal within the context of password hygiene. A large-scale randomized controlled experiment was conducted with one control and three treatment groups: (1) fear only; (2) measures needed and the efficacy of such measures, and (3) fear combined with measures needed and the efficacy of such measures. The results suggest that the most effective way to employ a fear appeal within the cybersecurity domain is by ensuring that fear is not used on its own. Instead, it is important that information on the measures needed to address the threat and the efficacy of such measures is used in combination with information about the nature of the threat. Since many individuals that enter the information technology profession become the de facto security person, it is important for information technology education programs to distill in students the inadequacy of fear, on its own, in motivating secure actions.
Block-based Programming Enabling Students to Gain and Transfer Knowledge with a No-code Approach

In this article, we describe our experience designing and teaching a curriculum on mobile software development that has benefitted from the no-code philosophy leveraging the power of block-based programming tools. We review a journey of 10 years using block-based programming platforms to lay foundations on software development skills, and empower the creative potential of high school students. Our objective is to provide a review of the evolution, capabilities and technical coverage of the block-based software platforms, and to discuss the impact that we have observed on users and developers who have become acquainted on the use of block-based programming tools through our courses
Social Robots for the Care of Persons with Dementia

Intelligent assistive robots can enhance the quality of life of people with dementia and their caregivers. They can increase the independence of older adults, reduce tensions between a person with dementia and their caregiver, and increase social engagement. This article provides a review of assistive robots designed for and evaluated by persons with dementia. Assistive robots that only increased mobility or brain-computer interfaces were excluded. Google Scholar, IEEE Digital Library, PubMed, and ACM Digital Library were searched. A final set of 53 articles covering research in 16 different countries are reviewed. Assistive robots are categorized into five different applications and evaluated for their effectiveness, as well as the robots’ social and emotional capabilities. Our findings show that robots used in the context of therapy or for increasing engagement received the most attention in the literature, whereas the robots that assist by providing health guidance or help with an activity of daily living received relatively limited attention. PARO was the most commonly used robot in dementia care studies. The effectiveness of each assistive robot and the outcome of the studies are discussed, and particularly, the social/emotional capabilities of each assistive robot are summarized. Gaps in the research literature are identified and we provide directions for future work.
Pleiotropy drives repeatability in the genetic basis of adaptation

29 Studies of trait-mapping and local adaptation often identify signatures of genetically repeated 30 evolution, where different species independently evolve similar phenotypes using the same 31 genes. Such patterns appear incongruent with current estimations of quantitative trait 32 architecture: with hundreds or thousands or genes contributing to a trait, why would selection 33 make repeated use of the same genes? This incongruence is particularly puzzling in light of the 34 Fisher-Orr model, which predicts that repeated use of the same gene should decrease with 35 increasing trait dimensionality, as alleles of large-effect are unlikely to be beneficial when there 36 is high pleiotropy. When adaptation occurs for a single trait in spatially heterogeneous 37 environments, large-effect alleles are more strongly favoured, but it is unclear whether this 38 result would generalize to multiple traits, especially if there are trade-offs between them. Here, 39 we explore this question using individual-based simulations of a two-patch model with 40 quantitative traits and pleiotropy. We first confirm that repeatability is lower in spatially 41 homogeneous environments, and then explore the effect of trait dimensionality and pleiotropy in 42 a spatially heterogeneous environment. While repeatability decreases with increasing trait 43 dimensionality, trade-offs in mutation effects on traits do not strongly limit the contribution of a 44 locus of large effect to repeated adaptation, particularly under increased migration. These 45 results suggest that evolutionary convergence will be more pronounced for local rather than 46 global adaptation. Whereas pleiotropy limits repeatability in a single-population model, when 47 there is local adaptation with gene flow, repeatability can be increased if some loci are able to 48 produce alleles of large effect, even with pleiotropic trade-offs. 49
Disrupting the CmP signaling network unveils novel biomarkers for triple negative breast cancer in Caucasian American women

Triple-negative breast cancer (TNBC) constitutes ∼15 percent of all diagnosed invasive breast cancer cases with limited options for treatment since immunotherapies that target the ER, PR and HER2 receptors are ineffective. Progesterone (PRG) is capable of inducing its effects through either classic, non-classic, or combined responses by binding to classic nuclear PRG receptors (nPRs) or non-classic membrane PRG receptors (mPRs). Under PRG-induced actions, we previously demonstrated that the CSC (CCM signaling complex) can couple both nPRs and mPRs into a CmPn signaling network which plays an important role in nPR(+) breast cancer tumorigeneses. We recently defined the novel CmP signaling network in TNBC cells, which overlapped with our previously defined CmPn network in nPR(+) breast cancer cells. In this study, we were able to demonstrate alterations to key tumorigenesis pathways in Caucasian American Women (CAW)-TNBC cells, under mPRs-specific steroid actions. These results suggest that even though TNBC diagnoses in AAW are associated with more aggressive forms of the disease, and experience a higher mortality rate, TNBC in CAW share similar altered signaling pathways, under mPRs-specific steroid actions, demonstrating the overall aggressive nature of TNBCs, regardless of racial differences. Furthermore, in this report, we have identified 21 new CAW-TNBC specific candidate biomarkers that reinforce the definitive role of the CmP signaling network in TNBC tumorigenesis, initially identified in our previous studies with AAW-TNBCs. This new set of potential prognostic biomarkers may revolutionize molecular mechanisms and currently known concepts of tumorigenesis in CAW-TNBCs, leading to hopeful new therapeutic strategies.
A 3D Semantic Visual SLAM in Dynamic Scenes

Simultaneous Localization and Mapping (SLAM) are the core function of mobile robots. At present, the mainstream visual SLAM technology is mainly based on static scene assumptions, which only contains some geometric information. Especially in the dynamic scene, it is susceptible to the influence of moving targets and leading to mismatches of attitude estimation, resulting in poor system robustness and positioning accuracy. In this paper, a visual semantic map construction framework named Dynamic Visual Semantic SLAM (DVS_SLAM) in dynamic scenes is proposed under the Oriented FAST and Rotated BRIEF SLAM2 (ORB_SLAM2) framework, which can run on ordinary PC with high real-time performance and localization accuracy. Firstly, the improved multi-view geometry and region growing algorithm are used in the tracking thread to detect moving targets, which could remove dynamic feature points to improve the localization accuracy. Secondly, the SSD-MobileNetV2 lightweight deep learning network is added to obtain 2D information, fusion based on color bumpy supervoxel clustering algorithm is selected to realize 3D target information extraction. Finally, a new 3D map construction thread is also added to build a 3D semantic map suitable for navigation by Octo-Map. Experiments were carried on the TUM RGB-D Datasets and self-built robot platform. It demonstrates that the DVS_SLAM is much better than ORB_SLAM2 in dynamic scenes. Meanwhile, a dense semantic octree map is established to improve the environment perception ability of mobile robots.
L-based DC-DC Boost Regulator Using Voltage-to-Time Converter for Self-powered Devices

This paper presents an L-based DC-DC boost regulator using an ultra-low voltage-to-time (VTC) converter designed for self-powered devices. The VTC operates as a pulse width modulation (PWM) that converts the voltage levels linearly into corresponding delays resulting in modulated pulse signals connected to the power switch of the L-based boost regulator. When the desired voltage is achieved by the proposed VTC, a pulse skip modulation (PSM) is enabled to stop the pulse generation. The boost regulator is implemented and simulated in 65 nm CMOS technology. It has an input voltage of 50 mV coming from the thermoelectric generator and generates an output voltage of 0.6 V, 0.8 V, and 1 V for a load current range 1-10 µA. The VTC supports a wide duty cycle range from 0.15 to 0.5 with a gain of 11.5 µs/V and power consumption of 6.7 µW. The VTC achieves high linearity with a low mean square error of 2.04e–6.
The Virtuous Circle of 5G, IoT and Energy Harvesting

The Internet of Things (IoT) offers disruptive potential to address the most urgent challenges of our world - from climate change to ensuring clean energy, safe food and caring for our health and well-being. Wireless IoT sensory devices can be placed on, in or near people, equipment, infrastructure and our environment to gather and enable such services. Analysts predict a 1 trillion sensor economy by the year 2025 [1]. However, to achieve this vision we need to address the 'power IoT' gap, i.e. batteries that outlive the IoT devices they power. At present a typical battery life is ~2 years or less. With most devices operating for >10 years, it leads to multiple battery replacements resulting in device downtime and maintenance trade-offs as well as major economic and environmental issues related to the manufacture and disposal of hundreds of millions of batteries every single day. In addition, there are many untapped IoT applications due to the downtime implications and extreme costs and logistics of battery replacement throughout the device lifetime including medical technologies, implantables, and installations in harsh environments (Figure 1).
Control of a Soft Medical Exoskeleton via a Bio-inspired Approach

It has been proved that continued training recovery for the patients who suffer limb movement disorder helps them in therapy protocols. However, the specialty and numbers of therapist often limit the rehabilitation to these patients. Thus, employing robotic equipment to provide the treatment capability is a way out of this dilemma. Considering the compliance and continuous deformation capacity, a robotic exoskeleton actuated by Pneumatic Arti? cial Muscles (PAMs) is designed as the rehabilitation equipment for elbow joint. Moreover, to precisely control the PAM soft actuator of the proposed equipment, a bio-inspired control approach is explored. Finally, several simulations have been conducted to verify the effectiveness of the proposed system.
Temperature Dependence of the Impact Ionization Coefficients in AlAsSb Lattice Matched to InP

The temperature dependence of the ionization coefficients of AlAsSb has been determined from 210 K to 335 K by measuring the avalanche multiplication in a series of three <italic>p<sup>+</sup>-i-n<sup>+</sup></italic> and two <italic>n<sup>+</sup>-i-p<sup>+</sup></italic> diodes. Both electron and hole ionization coefficients reduce at approximately the same rate as the temperature increases but much less so than in InAlAs or InP. This results in a significantly smaller breakdown voltage variation with temperature of 13 mV/K in a 1.55 μm thick <italic>p<sup>+</sup>-i-n<sup>+</sup></italic> structure and a calculated 15.58 mV/K for a 10 Gb/s InGaAs/AlAsSb separate absorption and multiplication avalanche photodiode (SAM-APD). Monte-Carlo modelling suggests that the primary reason for this reduced temperature dependence is the increased alloy scattering in the Sb containing alloy, reducing the impact of variation in phonon scattering rate with temperature.
Observer-Based Control for Markovian Jump Fuzzy Systems Under Mismatched Fuzzy Basis Functions

This paper investigates the observer-based dissipative control problem for a class of discrete-time Markovian jump fuzzy systems under mismatched fuzzy basis functions. In the practical implementation of the observer-based control scheme, the system state variable can be measured with uncertainties and disturbances, which acts as a factor that prevents accurate measurement of the premise variable. Thus, in this case, it is necessary to explore the phenomenon that the system premise variable cannot be reflected in the design of the fuzzy-basis-dependent observer and controller. In response to this need, this paper proposes a method to deal with the mismatch phenomenon in the observer-based stabilization problem of MJFSs by devising a two-step approach to solve the inherent decoupling problem and by providing a useful relaxation technique for the error of mismatched fuzzy basis functions.
Mechanism Design of an Extraterrestrial Regolith-boring Robot

Penetrating planetary subsurface regolith is extremely significant to explore the secrets insight extraterrestrial planets. The concept considerations and mechanism design of a planetary regolith-boring robot were proposed in this work. The robot has two degrees of freedom, including a rotational cutting head to break regolith and a penetration mechanism to move the robot along the drilled borehole. The serrated cutters are designed on the cutter head to improve the adaptability of regolith with different strengths, and high-pressure pneumatic gas is utilized to remove drilled cuttings. The penetration mechanism relies on the friction force with the borehole to provide torque balance generated by the rotational cutting movement and achieve downward penetration.
Privacy-Preserving Audio Classification Using Variational Information Feature Extraction

In this paper we investigate and tackle the privacy risks of deep-neural-network-based feature extraction for sound classification in acoustic sensor networks. To this end, we analyze a single-label domestic activity monitoring and a multi-label urban sound tagging scenario. We show that in both cases, the feature representations designed for sound classification also carry a significant amount of speaker-dependent data, thus posing serious privacy risks for speaker recognition attacks based on feature interception. We then propose to mitigate the aforementioned privacy risks by introducing a variational information feature extraction scheme that allows sound classification while, concurrently, minimizing the feature representation’s level of information and hence, inhibiting speaker recognition attempts. We control and analyze the balance between the performance of the trusted and attacker tasks via the resulting model’s composite loss function, its budget scaling factor, and latent space size. It is empirically demonstrated that the proposed privacy-preserving feature representation generalizes well to both single-label and multi-label scenarios with vast as well as reduced training-dataset resources. Furthermore, it exhibits robustness against x-vector-based, state-of-the-art speaker recognition attacks.
Analysis and System Construction of Ideological and Political Education Teaching Mode Based on Wechat Platform

To solve the problem that students can only passively receive the education content under the traditional ideological and political teaching mode, and the effect is low, this paper develops the ideological and political teaching system based on Wechat platform combined with information technology. It uses Java language to write the system, and through Servlet, Hiberbat, Web Service and other technologies to complete the system framework, and to achieve the information processing of Ideological and political education. At the same time, in the registration part of the text content of the teaching materials, the paper puts forward the scheme of developing digital learning resources of Ideological and political teaching materials combined with augmented reality technology. In the design work, the data storage and management of the program are also designed in the database. Finally, through the programming communication interface and software development architecture, the specific function coding of the system is realized. After testing, all functions of the platform can be used normally and meet the design requirements.