Miracle-dz/UniFAR-FTUs huggingface dataset:
In Vivo Measurement of Ear Ossicle and Bony Wall Vibration by Sound Stimulation of Cartilage Conduction

The cartilage-conduction pathway was recently proposed as a third auditory pathway; however, middle-ear vibrations have not yet been investigated in vivo. We aimed to measure the ossicles and bone vibration upon cartilage-conduction stimulation with a non-contact laser Doppler vibrometer. We recruited adult patients with normal ear structures who underwent cochlear implant surgery at our hospital between April 2020 and December 2022. For sound input, a cartilage-conduction transducer, custom-made by RION Corporation (Tokyo, Japan), was fixed to the surface of the tragus and connected to an audiometer to regulate the output. A posterior tympanotomy was performed and a laser beam was directed through the cavity to measure the vibration of the ossicles, cochlear promontory, and posterior wall of the external auditory canal. Five participants (three men, mean age: 56.4 years) were included. The mean hearing loss on the operative side was 96.3 dB HL in one patient, and that of the other patients was off-scale. The vibrations were measured at a sound input of 1 kHz and 60 dB. We observed vibrations of all three structures, demonstrating the existence of cartilage-conduction pathways in vivo. These results may help uncover the mechanisms of the cartilage-conduction pathway in the future.
A study on light weight of radar-based human activity recognition model using self-attention mechanism

: Recently, radar-based human activity recognition (HAR) technology has been actively studied in the field of artificial intelligence by applying radar datasets to deep learning (DL) models to automatically learn and classification. This is one of the important applications in the field of activity recognition and can be used in various fields, such as exercise tracking, smart homes, self-driving cars, and health status monitoring, by recognizing human daily activity patterns. However, DL models are complex and have significant computational costs and numerous parameters to process and classify high-dimensional radar datasets. Therefore, their implementation on commercial mobile devices is limited by their computational complexity. Therefore, in this study, we propose a lightweight HAR DL model using Self-Attention technology to solve the complexity and computational costs of these DL models. Experimental results demonstrate that this model can maintain its performance while reducing the number of parameters required. In the future, these light-weight models will not only be usable on mobile devices but will also require lower computing power and memory capacity; therefore, they are expected to be used in various fields as time series-based DL models.
The Study of Galactic Disk Kinematics with SCUSS and SDSS Data

We derive chemical and kinematics properties of G and K dwarfs from the SCUSS and SDSS data. We aim to characterize and explore the properties of the Galactic disk in order to understand their origins and evolutions. A kinematics approach is used to separate Galactic stellar populations into the likely thin disk and thick disk sample. Then, we explore rotational velocity gradients with metallicity of the Galactic disks to provide constraints on the various formation models. We identify a negative gradient of the rotational velocity of the thin disk stars with [Fe/H], −18.2 ± 2.3 km s−1 dex−1. For the thick disk, we identify a positive gradient of the rotational velocity with [Fe/H], 41.7 ± 6.1 km s−1 dex−1. The eccentricity does not change with metallicity for the thin disk sample. Thick disk stars exhibit a trend of orbital eccentricity with metallicity (−0.13 dex−1). The thin disk shows a negative metallicity gradient with Galactocentric radial distance R, while the thick disk shows a flat radial metallicity gradient. Our results suggest that radial migration may play an important role in the formation and evolution of the thin disk.
Microfluidizing Technique Application for Algerian Cymbopogon citratus (DC.) Stapf Effects Enhanced Volatile Content, Antimicrobial, and Anti-Mycotoxigenic Properties

Medicinal plant extracts are a promising source of bioactive minor contents. The present study aimed to evaluate the distinguished volatile content of Algerian Cymbopogon citratus (DC.) Stapf before and after the microfluidization process and their related antimicrobial and anti-mycotoxigenic impacts and changes. The GC-MS apparatus was utilized for a comparative examination of Algerian lemongrass essential oil (LGEO) with its microfluidization nanoemulsion (MF-LGEO) volatile content. The MF-LGEO was characterized using Zetasizer and an electron microscope. Cytotoxicity, antibacterial, and antifungal activities were determined for the LGEO and MF-LGEO. The result reflected changes in the content of volatiles for the MF-LGEO. The microfluidizing process enhanced the presence of compounds known for their exceptional antifungal and antibacterial properties in MF-LGEO, namely, neral, geranial, and carvacrol. However, certain terpenes, such as camphor and citronellal, were absent, while decanal, not found in the raw LGEO, was detected. The droplet diameter was 20.76 ± 0.36 nm, and the polydispersity index (PDI) was 0.179 ± 0.03. In cytotoxicity studies, LGEO showed higher activity against the HepG2 cell line than MF-LGEO. Antibacterial LGEO activity against Gram-positive bacteria recorded an inhibitory zone from 41.82 ± 2.84 mm to 58.74 ± 2.64 mm, while the zone ranged from 12.71 ± 1.38 mm to 16.54 ± 1.42 mm for Gram-negative bacteria. Antibacterial activity was enhanced to be up to 71.43 ± 2.54 nm and 31.54 ± 1.01 nm for MF-LGEO impact against Gram-positive and Gram-negative pathogens. The antifungal effect was considerable, particularly against Fusarium fungi. It reached 17.56 ± 1.01 mm and 13.04 ± 1.37 mm for LGEO and MF-LGEO application of a well-diffusion assay, respectively. The MF-LGEO was more promising in reducing mycotoxin production in simulated fungal growth media due to the changes linked to essential compounds content. The reduction ratio was 54.3% and 74.57% for total aflatoxins (AFs) and ochratoxin A (OCA) contents, respectively. These results reflect the microfluidizing improvement impact regarding the LGEO antibacterial, antifungal and anti-mycotoxigenic properties.
Model validation with multivariate responses via factor analysis

Computational models have been widely applied to simulate complex physical phenomena because of rapid development of computers’ abilities and inexecutable conditions of the experiments. Validating the effectiveness of computational models is then essential and significant. Existing validation metrics focusing on a single response may cause confusing results when they are applied for multiple responses simultaneously. The target of this work is to validate computational models with multiple responses via the factor analysis method by considering both the uncertainty and correlation of the multiple responses. Factor analysis aims to explain the correlated multi-dimensional variables with fewer common factors and the latter then can describe the main information the former containing. Briefly, factor analysis has a favorable ascendency——dimensionality reduction, which makes multiple responses validation easy to implement. The proposed method is based on the factor analysis and the concept of “area metric” for validating a single response, which avoids comparing the joint distribution of the computational models and that of the experimental observations. It is applicable for validating multiple responses both at a single validation site and at multiple validation sites. Both numerical example and engineering example are employed to demonstrate the rationality and necessity of the proposed methodology.
Ray optics simulations of polarised microscopy textures in chiral nematic droplets

ABSTRACT We present a simple method for simulating optical polarised micrographs of director fields in optically birefringent structures. Jones matrix method is applied for simulating polarised micrographs with focusing optics that can sufficiently account for different focusing distances and numerical apertures (NAs) in the polarised microscopy, which are the typical experimental variables. Accuracy of the method is assessed by comparing experimental and numerical micrographs of various structures in cholesteric liquid crystal droplets. The effects of varied focusing distance and scale are tested. The performance of the developed method is further demonstrated by varying viewing direction, position of focusing plane and the size of the observed structure, which prove to be elementary and easily changed parameters of this approach. Graphical Abstract
Chemical Characterization and Ameliorating Effect of Centratherum anthelminticum Extract against Polycystic Ovary Syndrome in Wistar Rats

Polycystic ovary syndrome (PCOS) in females is an endocrine pathological condition of reproductive age which is usually caused by insulin resistance, hyperlipidemia, and oxidative stress. This research was aimed at evaluating the therapeutic effect of the Centratherum anthelminticum seed extract (CA) against PCOS in rodents as it is traditionally used to treat diabetes, inflammation, and gynecological problems. The CA was chemically characterized by high-performance liquid chromatography-diode array detection (HPLC-DAD). For the induction of PCOS, a high-fat diet (HFD) was given to all female Wistar rats for nine weeks except the normal control group, which was given a normal chow diet. Estradiol valerate was given to all rats except normal control. After the induction of PCOS, oral metformin (300 mg/kg) was given to the standard group, while CA was orally administered to diseased rats at 250, 500, and 750 mg/kg/day for 28 days. HPLC-DAD analysis revealed that kaempferol-3-pcoumaroylglucoside was present in the highest amount (146.8 ± 1.8 mg/g) of the extract followed by ferulic acid and malvidin-3-(6-caffeoyl)-glucoside. The in vivo results revealed a marked reduction in cholesterol and triglyceride levels in CA treatment groups. A significant rise was observed in progesterone and follicle stimulating hormone with a decrease in luteinizing hormone in the treatment groups as compared to disease control, which indicated normalization of the estrus cycle. The decrease in insulin resistance was characterized by low serum insulin levels in treatment groups. Treatment with CA also reduced inflammatory markers, such as IL-6 and NF-κB in PCOS rats. NrF2 and oxidative stress markers such as catalase, superoxide dismutase, malondialdehyde, and reduced glutathione were also improved by CA in the ovary of diseased rats. Histopathological examination showed the different developmental stages of normal follicles in CA-treated diseased rats which were indicative of a normal fertile estrous cycle. Overall, the results confirmed the efficacy of CA against PCOS in treating estradiol-HFD-induced PCOS due to its antidiabetic, anti-inflammatory, antihyperlipidemic, and antioxidant properties.
The relationships between precipitation amounts, number of rain days, and relative vorticity in the mid‐troposphere over Iran

Precipitation is one of the most studied atmospheric parameters, and its occurrence has a direct relationship with the atmospheric circulation pattern. This study investigates the relationship between relative vorticity in the mid‐troposphere (at 500 hPa), and precipitation amounts and the number of rain days over the period 1979–2013 in Iran. Relative vorticity was calculated using the u and v components of the wind data from the European Centre for Medium‐Range Weather Forecasts (ECMWF) interim reanalysis (ERA‐Interim) over Iran, with 0.125° spatial resolution. Gridded daily precipitation data from the Asfazari National Dataset with a spatial resolution of 15 × 15 km, covering the same period, were also used. Pearson's correlation coefficient was used to investigate, at the 90% confidence level, the relationship between relative vorticity, and monthly precipitation amount and number of rain days. The significance of the trend for relative vorticity for different months, at the 90% confidence level, was evaluated using the nonparametric modified Mann–Kendall test. The results showed a significant relationship between relative vorticity and the number of rain days and precipitation amounts over Iran. In temporal terms, the correlations between relative vorticity and the number of rain days and precipitation amounts are strongest during the months of high precipitation over Iran, especially in November and December. In spatial terms, eastern Iran exhibits the strongest relationship between precipitation and relative vorticity at the 500 hPa level. Examination of the time series data showed that the monthly precipitation amounts and numbers of rain days fluctuate in line with changes in relative vorticity during the period of study. Analysis of trends in the relative vorticity data also showed, at the 90% confidence level, that the maximum variations in relative vorticity occurred in autumn and winter, respectively. Trend analysis also showed a decreasing trend in relative vorticity in March and an increasing trend in November.
Curriculum-reinforcement learning on simulation platform of tendon-driven high-degree of freedom underactuated manipulator

A high degree of freedom (DOF) benefits manipulators by presenting various postures when reaching a target. Using a tendon-driven system with an underactuated structure can provide flexibility and weight reduction to such manipulators. The design and control of such a composite system are challenging owing to its complicated architecture and modeling difficulties. In our previous study, we developed a tendon-driven, high-DOF underactuated manipulator inspired from an ostrich neck referred to as the Robostrich arm. This study particularly focused on the control problems and simulation development of such a tendon-driven high-DOF underactuated manipulator. We proposed a curriculum-based reinforcement-learning approach. Inspired by human learning, progressing from simple to complex tasks, the Robostrich arm can obtain manipulation abilities by step-by-step reinforcement learning ranging from simple position control tasks to practical application tasks. In addition, an approach was developed to simulate tendon-driven manipulation with a complicated structure. The results show that the Robostrich arm can continuously reach various targets and simultaneously maintain its tip at the desired orientation while mounted on a mobile platform in the presence of perturbation. These results show that our system can achieve flexible manipulation ability even if vibrations are presented by locomotion.
Lightweight design of bus frames from multi-material topology optimization to cross-sectional size optimization

ABSTRACT A comprehensive solution for bus frame design is proposed to bridge multi-material topology optimization and cross-sectional size optimization. Three types of variables (material, topology and size) and two types of constraints (static stiffness and frequencies) are considered to promote this practical design. For multi-material topology optimization, an ordered solid isotropic material with penalization interpolation is used to transform the multi-material selection problem into a pure topology optimization problem, without introducing new design variables. Then, based on the previously optimal topology result, cross-sectional sizes of the bus frame are optimized to further seek the least mass. Sequential linear programming is preferred to solve the two structural optimization problems. Finally, an engineering example verifies the effectiveness of the presented method, which bridges the gap between topology optimization and size optimization, and achieves a more lightweight bus frame than traditional single-material topology optimization.
Delivering Resilience: Embedding a Resilience Building Module into First-Year Curriculum

Starting university is challenging. Students require resilience to face the inevitable challenges of university life, yet many may not be equipped with the strategies they need. In this research, we explored changes in resilience following the delivery of a resilience building module within a core first-year university course. Psychology students at the University of South Australia completed the adapted Resilience at Work Scale at two separate time points and undertook a resilience building module. Pre- and post-scores were obtained for students’ resilience (n = 205; n = 100 respectively); overall and components. On average, students had good levels of resilience at commencement, yet scores increased significantly across most components following completion of the module. Additionally, students who reported implementing resilience strategies experienced significantly higher score increases than their peers who did not. These findings hold important implications for staff across universities in relation to embedding resilience building programs into curriculum.
Memory-Based Augmentation Network for Video Captioning

Video captioning focuses on generating natural language descriptions according to the video content. Existing works mainly explore this multimodal learning with the paired source video and corresponding sentence, which have achieved competitive performances. Nonetheless, learning from video-description pair cannot capture implicit external knowledge, i.e., multiple visual context information and linguistic clues existing in the video-language dataset, which may limit the cognitive capability of the model to generate diverse descriptions. To this end, we propose a Memory-based Augmentation Network (MAN), in which a memory structure is designed to augment the current encoder-decoder framework by incorporating implicit external knowledge with a neural memory. Specifically, we first propose a visual memory for the encoder to store multiple visual contexts across videos in the dataset, which is utilized to obtain memory-augmented contextual features for the source video. In addition, a textual memory is introduced for the decoder to capture the external language clues across sentences in the dataset. It is adapted to capture memory-augmented language features in each time step. The proposed approach is able to capture comprehensive contextual understanding compared to the basic encoder-decoder framework, which is more compatible with the human cognitive process. Extensive experiments on three video captioning datasets including MSVD, MSR-VTT, and VATEX demonstrate the effectiveness of the proposed method.
Regulasi Emosi Sebagai Mediator Antara Insecure Attachment Dan Perilaku Agresif Pada Remaja

Aggressive behavior is often a problem that arises in adolescents. Aggressive behavior is related to the lack of adolescent skills in regulating emotions. Adolescents with insecure attachments will have poor emotional regulation. In addition, insecure attachment can be a predictor of the emergence of aggressive behavior in adolescents. This study aims to determine whether emotional regulation mediates the relationship between insecure attachment and aggressive behavior in adolescents. This research is a quantitative study involving 459 respondents who are still actively attending junior high school in the city of Semarang and aged 12-15 years, which were obtained by accidental sampling. Data were obtained using the Buss-Perry Aggression Questionnaire Short Form, The Experiences in Close Relationships — Revised General Short Form (ECR-R-GSF), and Emotion Regulation Questionnaire (ERQ), which were then analyzed using path analysis. This research gets the results that emotion regulation mediates the relationship between insecure attachment and aggressive behavior (p = 0,000 < 0,05). In addition aggressive behavior can be influenced by emotional regulation (β = -.207, p = .000) and emotional regulation and insecure attachment have an influence of 17.3% on aggressive behavior, the rest is contributed by other variables.
Comparison between the physical-optics approximation and exact methods solving the problem of light scattering by ice crystals of cirrus clouds

In the problem of light scattering by ice crystals of cirrus clouds, two exact methods (FDTD – finite difference time domain and DGTD – discontinuous Galerkin time domain) and the physical-optics approximation are used for numerical calculations of the Mueller matrix in the case of ice hexagonal plates and columns. It is shown that for the crystals larger than 10 μm at the wavelength of 0.532 μm the exact methods and physical-optics approximation closely agreed within three diffraction fringes about the centers of the diffraction patterns. As a result, in the case of random orientation of these crystals, the physical-optics approximation provides accuracy 95% for the averaged Mueller matrix.
Translating solitons in arbitrary codimension

We study the translating solitons of the mean curvature flow. Although many authors study translating solitons in codimension one, there are few references and examples for higher codimensional cases except for Lagrangian translating solitons. First we observe non-trivial examples of translating solitons in arbitrary codimension. We will see that they have the property called parallel principal normal (PPN). Inspired by this fact and the work of Smoczyk for self-shrinkers in 2005, we then characterize the complete translating solitons with PPN.
Acceleration of planes segmentation using normals from previous frame

One of the major problem in integration process of robots is to make them able to function in a human environment. In terms of computer vision, the major feature of human made rooms is the presence of planes [1, 2, 20, 21, 23]. In this article, we will present an algorithm dedicated to increase speed of a plane segmentation. The algorithm uses information about location of a plane and its normal vector to speed up the segmentation process in the next frame. In conjunction with it, we will address such aspects of ICP SLAM as performance and map representation.
Brain Injury Localization and Size Estimation Using Electromagnetic Symmetric Crossing Lines Method

Based on the hypothesis that healthy human brains are highly symmetric along the sagittal plane, a method to detect and localize brain injuries using the intersection of pairs of signals captured by symmetrical antennas surrounding the head is presented. The method localizes the target using information at the low-frequency band, whereas the shape of the target is estimated using information from the high-frequency band. Then, an intersection of two pairs of antennas enables identifying the position of the target. Finally, a heat map is used to visualize the injury. The results indicate that crossing pairs of signals from the hemisphere with injury exhibit significantly different amplitudes in the graph features compared to those not crossing the target ( $p < 0.003$ ). The experiments show that the proposed localization algorithm can achieve an accuracy of 0.85 ± 0.08 Dice similarity coefficient based on 150 experimental measurements on head phantoms.
Exponential Contractivity in the $L^p$-Wasserstein Distance for Diffusion Processes

By adopting the coupling by reflection and choosing an auxiliary function which is convex near infinity, we establish the exponential contractivity of diffusion semigroups (Pt)t≥0 with respect to the standard L p-Wasserstein distance for all p ∈ [1,∞). In particular, we show that for the Itô stochastic differential equation dXt = dBt + b(Xt) dt, if the drift term b satisfies that for any x, y ∈ Rd, 〈b(x)− b(y), x− y〉 ≤ { K1|x− y|2, |x− y| ≤ L; −K2|x− y|θ, |x− y| > L holds with some positive constants K1, K2, L > 0 and θ ≥ 2, then there is a constant λ > 0 such that for all p ∈ [1,∞), t > 0 and x, y ∈ Rd with |x− y| ≤ 1, Wp(δxPt, δyPt) ≤ C(p, θ)e|x− y|; for all p ∈ [1,∞), t > 0 and x, y ∈ Rd with |x− y| > 1, Wp(δxPt, δyPt) ≤ C(p, θ)e { |x− y|, θ = 2; |x− y| ∧ 1 t∧1 , θ > 2. This improves the main result in [12] where the exponential convergence is only proved for the L1-Wasserstein distance.