Miracle-dz/UniFAR-FTUs huggingface dataset:
Interaction of layered double hydroxide phases with chloride ions

For the sustainable transition of the construction sector, the durability of cementitious materials needs to be guaranteed. This requires a fundamental understanding of the deterioration mechanisms for example how the ingress of potentially detrimental ions affects the composition of the pore solution as well as the phase assemblage. This contribution links results from several research projects investigating the changes in layered double hydroxides (LDH) composition upon exposure to chlorides. The Cl/Al ratio in chloride‐containing AFm phases depends on the chloride concentration as well as on the pH of the liquid phase. In addition, the amount of AFm phases is affected by the pH. Another member of the LDH group, hydrotalcite (Ht), can also incorporate chloride ions into the interlayer and exhibit a similar chloride‐binding capacity as stoichiometric Friedel's salt. However, the chloride‐binding capacity of Ht also depends on the composition of the pore solution. These findings aid the fundamental understanding of chloride‐binding mechanisms of cementitious materials. This is especially important, as the pH and calcium availability in the pore solution of hydrated cement may be altered during its service life. Moreover, the results may help to accurately predict the durability performance of samples in the laboratory.
A Lightweight Haptic Feedback Glove Employing Normal Indentation, Lateral Skin Stretch and both Softness and Hardness Rendering

Current haptic devices often provide tactile feedback via only vibrations and kinesthetic feedback based on heavy and cumbersome exoskeletons hindering users’ motion. This paper presents an innovative, lightweight, flexible and easy-to-wear haptic glove providing realistic tactile feedback through normal indentation and lateral skin stretch in addition to vibrations, as well as high-fidelity kinesthetic feedback through strings pulled by servo motors. Unlike current systems, it is inexpensive and tactile feedback is achieved through small vibration motors embedded on the fingertips of the glove. Normal indentation and shear forces are created through moving platforms applying pressure to the skin. Kinesthetic feedback is provided by small strings attached to the glove and pulled to simulate, unlike previous systems, both soft and hard virtual object manipulation. The glove is controlled by a small microcontroller receiving input from a computer sending commands to the motors and actuators. Study results suggest that the user is capable to perceive better directional information and surface geometry when vibration is added to the fingertip. Users perform better at distinguishing softness levels when the differences in softness are distinct.
Impact of Emotional Intelligence on College Instructors’ Work Management

This research aimed to explore the relationship between Emotional Intelligence (EI) and Work Management (WM) among Filipino College Instructors at the University of Cebu – Main Campus during the academic year. Employing a descriptive-correlational quantitative design, the study sampled 113 out of 157 College Instructors using Stratified Random Sampling. Standardized questionnaires were administered to gather data on emotional intelligence and work management. The analysis, encompassing Frequency, Percentage, Mean, Standard Deviation, Wilcoxon signed-rank test, and Chi-Square, indicated a significant positive relationship between emotional intelligence and work management. The results suggest that higher emotional intelligence correlates with more effective work management for college instructors. Interestingly, no significant relationships were found between demographic profiles and emotional intelligence or work management. The study's insights and recommendations focus on enhancing practices that foster emotional intelligence and work management among college instructors.
Adaptive Volumetric Anatomy Visualization in VR with Tangible Control

High-quality visualization of medical image data is essential for preoperative planning of complex and critical surgical procedures. Controllable 3D volume rendering in virtual reality (VR) is particularly useful to display depth and spatial relationships in volumetric data, and thus to identify specific anatomical landmarks and structural dependencies. However, intuitive control over the medical volume itself, the selection of sectional planes, transfer functions or the rotation or zooming has yet to be explored in depth. In this work, we demonstrate a real-time VR direct volume rendering application for medical images with tangible and intuitive interaction. Our system is real-time capable by the use of efficient volume rendering and foveated rendering techniques. We evaluated the system regarding its performance and gained first insight into the usefulness of a freely grabbable section slice in a preliminary user study.
An eye tracking - based system for capturing visual strategies in reading of children with dyslexia

Dyslexia is a learning disability that makes reading and language-related tasks more challenging. In recent years, the use of eye tracking to analyze eye movements during reading in children with dyslexia has gained popularity and received increased attention in the community. However, most previous studies have focused on English-speaking children, leaving limited research applicable to Vietnamese-speaking children, whose language exhibits distinct characteristics compared to English. This study aims to develop a system that utilizes eye-tracking technology to provide a visual representation of the eye movements in Vietnamese children with dyslexia, helping us understand their visual strategies during reading. We have designed a system capable of capturing eye movements of children through several tests that are suitable for Vietnamese kids. This allows us to analyze specific eye characteristics during reading, such as fixations and saccades, and visualize them using heatmap or scan path. By conducting tests on both children with dyslexia and children with typical development to initially compare their eye movement patterns, the findings suggest the potential use of this system in addressing subsequent issues, such as detection, intervention, and application development aimed at assisting Vietnamese children with dyslexia based on their visual reading strategies.
A Wideband Differentially Fed Dual-Polarized Antenna Array for 5G/6G mmWave Application

In this letter, a wideband millimeter-wave (mmWave) differentially fed (DF) dual-polarized (DP) magneto-electric (ME) dipole antenna is proposed for the fifth- and sixth-generation (5G/6G) wireless communications. Benefitting from the delicately designed cross-overlap differential feeding scheme deployed at the center of the perfectly symmetrical antenna, the ME-dipole can be effectively excited to achieve wideband operation for both orthogonal polarizations. Meanwhile, the feeding and radiation structures can be located at the same metallic layer to reduce the profile height while maintaining high port isolation. When the antenna element is excited by the ideal differential ports, a wide overlapped impedance bandwidth of about 58.3% (24.2–44.1 GHz), port isolation higher than 30 dB, a stable gain response with a peak gain of 7.5 dBi and symmetrical radiation patterns with low cross-polarization levels less than −40 dB can be achieved. For a proof-of-concept demonstration, a corresponding 1 × 4 phased array antenna is designed, fabricated and measured. A wide overlapped active impedance bandwidth of about 58% (24.7–44.8 GHz) and beam scanning characteristics of the array are experimentally verified. In virtue of wide bandwidth, simple and compact geometry, low profile, high integration, and ease of fabrication and miniaturization, the proposed antenna design is promising for diverse 5G/6G mmWave applications.
High-Transmission Biomimetics Structural Surfaces Produced via Ultrafast Laser Manufacturing

Inspired by periodically aligned micro/nanostructures on biological surfaces, researchers have been fabricating biomimetic structures with superior performance. As a promising and versatile tool, an ultrafast laser combined with other forms of processing technology has been utilized to manufacture functional structures, e.g., the biomimetic subwavelength structures to restrain the surface Fresnel reflectance. In this review paper, we interpret the biomimetic mechanism of antireflective subwavelength structures (ARSSs) for high-transmission windows. Recent advances in the fabrication of ARSSs with an ultrafast laser are summarized and introduced. The limitations and challenges of laser processing technology are discussed, and the future prospects for advancement are outlined, too.
The first records of two rare polyporoid fungi Picipes submelanopus and Picipes ulleungensis in Russia

Molecular genetic studies of the morphological genus Polyporus s. l. recently made it possible to detect the presence of several phylogenetic lineages among its representatives, to clarify the boundaries and scope of the taxon. Species with a black cuticle covering the stipe of the basidiomata have been separated in the genus Picipes. Most representatives of this genus are known from China. In Russia, out of 29 species of the genus, there are three widespread species of Picipes – P. badius, P. melanopus, P. tubaeformis, and one rare species – P. rhizophilus. Phylogenetic analysis of the nucleotide sequences of selected nrDNA loci obtained from the herbarium materials collected by us, originally assigned to Picipes melanopus, revealed the presence of two rare, morphologically similar species, P. submelanopus and P. ulleungensis, which turned out to be new to Russia. Picipes submelanopus is characterized by a terrestrial fruiting bodies and differentiated from P. melanopus, that grows on dead wood. All specimens of fruiting bodies of Picipes submelanopus collected by us in Western Siberia were found on the roots of woody plants, as in the typе locality in China. Picipes ulleungensis differs from P. melanopus by larger fruiting bodies, slightly larger pores. In order to differentiate Picipes submelanopus and P. ulleungensis from morphologically similar species, in addition to morphological characters and ecological preferences, it is desirable to use DNA barcoding methods.
A Best Practice Model of CDIO Implementation in IT Classrooms: Gamification Crowdsourcing Approach

The CDIO (Conceiving-Designing-Implementing-Operating) methodology is a recent educational theoretical framework that addresses IT/Engineering fundamental aspects of interactive learning inside classrooms. The CDIO approach is mainly associated with group projects and problem-based learning, in order to improve the technical and soft skills of university students, and to develop instructors' teaching and communication skills. The four steps mentioned earlier in the methodology imply crowdsourcing and gamification through which students need to show their understanding of the concept, designing a solution, implementing it and monitoring the progress and providing feedback. Despite its potential, the literature lacks the factors that impact the learner's attitude toward and behavior of this method, and how those factors are correlated in order to achieve a better understating about the CDIO implementation process.
SWiMM DEEPeR: A Simulated Underwater Environment for Tracking Marine Mammals Using Deep Reinforcement Learning and BlueROV2

This paper offers a feasibility study on using simulated environments for training autonomous underwater vehicles (AUVs). With the goal of monitoring marine megafauna, we propose a Unity-hosted simulation of a realistic open ocean environment, with a focus on simulating Blue Robotics’ BlueROV2. The result is SWiMM DEEPeR 1, coupling the former simulation with a reinforcement learning (RL) pipeline. Animated marine mammal models emulate the target objects of the real-world deployment scenario, offering a solution in a new application space (conservation) as well as a new problem space (visual active tracking). We provide experiments with respect to each stage of the proposed pipeline: i) image similarity experiments provide evidence for decisions around image rendering and data transfer, ii) autoencoder training demonstrates the feasibility of mapping raw images to low-dimensional feature representations, iii) agent training demonstrates successful self-learnt vehicle control.
Late Early Devonian brachiopods from Montys Hut Formation, central Victoria, Australia

Earp, C. , December 2015. Late Early Devonian brachiopods from Montys Hut Formation, central Victoria, Australia. Alcheringa 40, xxx–xxx. ISSN 0311-5518 A distinctive low-diversity fossil assemblage is reported from the Montys Hut Formation (Walhalla Group; Early Devonian), central Victoria, Australia. The fauna is dominated by two species of chonetoid brachiopods; two other brachiopods also occur in sufficient quantities to warrant description. Taungurungetes gen. nov. (? Devonochonetinae) is created to accommodate the nominate species of the assemblage, T. taggertyensis (Gill) comb. nov., and an additional species is described in open nomenclature from the underlying Norton Gully Sandstone. The other principal chonetoid is Parachonetes sp. cf. P. buchanensis (Gill). Capillate spiriferids from the assemblage were previously reported as Mauispirifer Allan. A redescription of M. hectori Allan shows the Victorian material is not congeneric and it is assigned to Tapongaspirifer melodiae gen. et sp. nov. (Filispiriferidae). The other minor constituent is Mesoleptostrophia belli sp. nov. Other (undescribed) fossils include ammonoids, a placoderm, dacryoconarids and vascular plants. A mid- to late Emsian age is indicated. It is concluded that the assemblage structure is consistent with the well-known high level of endemism in Emsian faunas. C. Earp [omaiosys@yahoo.com. au], 16B Ebony Place, Massey, Auckland 0614, New Zealand.
Hydrogen bonding in duplex DNA probed by DNP enhanced solid-state NMR N-H bond length measurements

Numerous biological processes and mechanisms depend on details of base pairing and hydrogen bonding in DNA. Hydrogen bonds are challenging to quantify by X-ray crystallography and cryo-EM due to difficulty of visualizing hydrogen atom locations but can be probed with site specificity by NMR spectroscopy in solution and the solid state with the latter particularly suited to large, slowly tumbling DNA complexes. Recently, we showed that low-temperature dynamic nuclear polarization (DNP) enhanced solid-state NMR is a valuable tool for distinguishing Hoogsteen base pairs (bps) from canonical Watson-Crick bps in various DNA systems under native-like conditions. Here, using a model 12-mer DNA duplex containing two central adenine-thymine (A-T) bps in either Watson-Crick or Hoogsteen confirmation, we demonstrate DNP solid-state NMR measurements of thymine N3-H3 bond lengths, which are sensitive to details of N-H···N hydrogen bonding and permit hydrogen bonds for the two bp conformers to be systematically compared within the same DNA sequence context. For this DNA duplex, effectively identical TN3-H3 bond lengths of 1.055 ± 0.011 Å and 1.060 ± 0.011 Å were found for Watson-Crick A-T and Hoogsteen A (syn)-T base pairs, respectively, relative to a reference amide bond length of 1.015 ± 0.010 Å determined for N-acetyl-valine under comparable experimental conditions. Considering that prior quantum chemical calculations which account for zero-point motions predict a somewhat longer effective peptide N-H bond length of 1.041 Å, in agreement with solution and solid-state NMR studies of peptides and proteins at ambient temperature, to facilitate direct comparisons with these earlier studies TN3-H3 bond lengths for the DNA samples can be readily scaled appropriately to yield 1.083 Å and 1.087 Å for Watson-Crick A-T and Hoogsteen A (syn)-T bps, respectively, relative to the 1.041 Å reference peptide N-H bond length. Remarkably, in the context of the model DNA duplex, these results indicate that there are no significant differences in N-H···N A-T hydrogen bonds between Watson-Crick and Hoogsteen bp conformers. More generally, high precision measurements of N-H bond lengths by low-temperature DNP solid-state NMR based methods are expected to facilitate detailed comparative analysis of hydrogen bonding for a range of DNA complexes and base pairing environments.
Automatic Step Recognition with Video and Kinematic Data for Intelligent Operating Room and Beyond

With the continuous development of intelligent operating room systems, the segmentation and automatic recognition of surgical workflow have become challenging research fields. In recent years, an increasing number of models have been proposed to address this challenge, with deep learning becoming the mainstream approach. In this paper, we propose a multi-stage network for surgical step recognition by using surgical video and kinematic data. Firstly, a convolutional neural network (ResNet34) is used to extract visual features from video frames. Next, since surgical videos are a form of sequential data, a Temporal Convolutional Network (TCN) is employed as a temporal extractor to process temporal information between video frames for classification. Finally, a multi-stage TCN network, consisting of Encoder-Decoded TCN and Dilated TCN architectures, is used to refine the result. The proposed network is compared against a LSTM network from our prior work and is evaluated on a surgical dataset named MISAW in two modes - video data with and without kinematic data. Experimental results indicate that kinematic data is crucial for robot motion control in the operating rooms of the future. The technology will also find application in robotic labs for the development and optimization of chemical manufacturing processes.
Packet Timeout Probability for Cognitive Cooperative Radio Network under Security Constraint

In this paper, we investigate the physical layer security of a cognitive relay network while considering joint constraints involving multiple primary users (PUs) and secondary users (SUs). Specifically, we address the scenario in which eavesdroppers attempt to exploit the confidential information of multiple PUs by monitoring multiple frequency bands. To make use of the licensed spectrum belonging to the PUs, SUs must adopt reasonable power allocation policies and frequency band selection strategies. These strategies serve not only to enhance their own performance but also to safeguard the PUs against eavesdropping. We introduce the concept of packet timeout and derive adaptive transmit power allocation policies for both the secondary transmitter (SU-Tx) and the secondary relay (SR). Additionally, we provide expressions for both the upper and lower bounds of the end-to-end packet timeout probability, which are used to assess the performance of the system under consideration. Finally, we present numerical results that explore the impact of various factors, such as the selected licensed frequency band, transmit power of the PUs, and channel mean powers, on the end-to-end packet timeout probability.
ConvTransNet: Merging Convolution with Transformer to Enhance Polyp Segmentation

Colonoscopy is widely acknowledged as the most efficient screening method for detecting colorectal cancer and its early stages, such as polyps. However, the procedure faces challenges with high miss rates due to the heterogeneity of polyps and the dependence on individual observers. Therefore, several deep learning systems have been proposed considering the criticality of polyp detection and segmentation in clinical practices. While existing approaches have shown advancements in their results, they still possess important limitations. Convolutional Neural Network - based methods have a restricted ability to leverage long-range semantic dependencies. On the other hand, transformer-based methods struggle to learn the local relationships among pixels. To address this issue, we introduce ConvTransNet, a novel deep neural network that combines the hierarchical representation of vision transformers with comprehensive features extracted from a convolutional backbone. In particular, we leverage the features extracted from two powerful backbones, ConvNeXt as CNN-based and Dual Attention Vision Transformer as transformer-based. By incorporating multi-stage features through residual blocks, ConvTransNet effectively captures both global and local relationships within the image. Through extensive experiments, ConvTransNet demonstrates impressive performance on the Kvasir-SEG dataset by achieving a Dice coefficient of 0.928 and an IOU score of 0.882. Additionally, when compared to previous methods on various datasets, ConvTransNet consistently achieves competitive results, showcasing its effectiveness and potential.
Split Hopkinson pressure bar tests on sandstone in coalmine under cyclic wetting and drying

Cyclic wetting and drying usually occurs in rock mass during groundwater water level variation caused by rainfalls and season changing.In order to investigate the influence of cyclic wetting and drying on dynamic mechanical properties of rock,a series of uniaxial dynamic compression tests on sandstone under cyclic wetting and drying are carried out by 50 mm variable cross-section split Hopkinson pressure bar(SHPB) apparatus.Sandstone specimens from Beifeng shaft-259 m of Hengyuan coalmine are processed into a cylindrical shape with a length to diameter ratio of 0.5. The corresponding dynamic stress-strain curves are obtained.It is found that as the Stefan effect of free water,wetting and drying 1 time gets a potentiation effect on sandstone;thus its dynamic uniaxial compressive strength is the highest.Then,with wetting and drying cycles increasing,dynamic uniaxial compressive strength reduces in a power relationship for physical weakening effect of water erosion;and the size of impact fragments becomes much smaller.The results show that when wetting and drying 12 times,dynamic uniaxial compressive strength of sandstone reduces about 24% compared with the result in wetting and drying 1 time,which shows a strong deterioration effect.
Multi-Branch Network for Imagery Emotion Prediction

For a long time, images have proved perfect at both storing and conveying rich semantics, especially human emotions. A lot of research has been conducted to provide machines with the ability to recognize emotions in photos of people. Previous methods mostly focus on facial expressions but fail to consider the scene context, meanwhile scene context plays an important role in predicting emotions, leading to more accurate results. In addition, Valence-Arousal-Dominance (VAD) values offer a more precise quantitative understanding of continuous emotions, yet there has been less emphasis on predicting them compared to discrete emotional categories. In this paper, we present a novel Multi-Branch Network (MBN), which utilizes various source information, including faces, bodies, and scene contexts to predict both discrete and continuous emotions in an image. Experimental results on EMOTIC dataset, which contains large-scale images of people in unconstrained situations labeled with 26 discrete categories of emotions and VAD values, show that our proposed method significantly outperforms state-of-the-art methods with 28.4% in mAP and 0.93 in MAE. The results highlight the importance of utilizing multiple contextual information in emotion prediction and illustrate the potential of our proposed method in a wide range of applications, such as effective computing, human-computer interaction, and social robotics.