Miracle-dz/UniFAR-FTUs huggingface dataset:
In situ investigation on dynamic suspending of microdroplet on lotus leaf and gradient of wettable micro- and nanostructure from water condensation

Dynamic suspending behavior of microdroplet on fresh lotus leaf is in situ investigated at micro- and nanolevels, by water condensation via environmental scanning electronic microscopy. The observation and analysis reveal that a gradient of wettable micro- and nanostructure is formed along the exterior surface of papilla including nanohairs during water condensation. This gradient introduces a tendency of directional movement and enables the microdroplet move out of the valley of papillae until the microdroplet is suspended on the tops of papillae. This finding is significant to understand the mechanism of self-cleaning.
3-D Air-Embedded Millimeter-Wave Filtering Antenna and Its Interconnection with Package and Chip

In this paper, a three-dimensional (3-D) air-embedded filtering antenna, which works at millimeter-wave (MMW) frequency and can directly interconnect with package and chip, is proposed. The air cavities in the substrate integrated waveguides (SIW) resonators are realized by ball grid array (BGA) fences, which can also achieve 3-D vertical stacking for third-order filter and slot antenna seamlessly. And, by introducing the air cavities, the Q-factor of the resonators is enhanced, and then, the whole efficiency and selectivity of the filtering antenna are promoted, especially for the MMW application. What's more, the Antenna-in-Package (AiP) architecture based on the proposed filtering antenna is presented, and its interconnection structure within the package and chip is designed in detail. The realized gain of the antenna is 5.46 dB. The transmission structure has an insertion loss of less than 0.5 dB. And the proposed structure finally exhibits a passband around 35 GHz with a fractional bandwidth of 3.66%.
A Fast Detection Method of Turbulent Gases Based on Gated Recurrent Unit and Attention Mechanism

Unlike the stable gas mixtures often analyzed in lab settings, the gas mixtures in practice may change fast due to the turbulent conditions of the environment, making the detection of gas components challenging. There will be a great safety risk if no fast and accurate detection method. In this article, an attention-based gated recurrent unit (AGRU) is proposed to solve this problem. It was introduced in detail that the method based on the gated recurrent unit (GRU) and attention mechanism. The component and concentration of the gas mixture were analyzed simultaneously by the dual loss function. The individual gas concentration in the gas mixture was obtained by multilabel coding. It was used to evaluate the performance of the model by accuracy, root mean square error (RMSE), number of model parameters, and floating point of operations (FLOPs). The experiment result showed that the AGRU’s accuracy curve is fluctuating around 97%, and varying the length of response time between 3 and 30 s hardly affected the recognition accuracy of gas species. AGRU also has the smallest RMSE of each gas among models. At 3 s, AGRU’s FLOPs are smaller than Improved LeNet5, which lays the foundation for the deployment in the embedded. Therefore, our proposed algorithm has a higher detection performance, lower complexity, and excellent robustness to be applicable in various practical applications for fast detection.
Problematic Internet Use among Adults: A Cross-Cultural Study in 15 Countries

Background: The present study compared adult usage patterns of online activities, the frequency rate of problematic internet use (PIU), and risk factors (including the psychopathology associated with PIU, i.e., distress and impulsivity) among adults in 15 countries from Europe, America, and Asia. Methods: A total of 5130 adults from Belgium, Finland, Germany, Italy, Spain, France, Switzerland, Hungary, Poland, UK, Norway, Peru, Canada, US, and Indonesia completed an online survey assessing PIU and a number of psychological variables (i.e., depression, anxiety, stress, and impulsivity). The sample included more females, with a mean age of 24.71 years (SD = 8.70). Results: PIU was slightly lower in European countries (rates ranged from 1.1% in Finland to 10.1% in the UK, compared to 2.9% in Canada and 10.4% in the US). There were differences in specific PIU rates (e.g., problematic gaming ranged from 0.4% in Poland to 4.7% in Indonesia). Regression analyses showed that PIU was predicted by problematic social networking and gaming, lack of perseverance, positive urgency, and depression. Conclusions: The differences in PIU between countries were significant for those between continental regions (Europe versus non-European countries). One of the most interesting findings is that the specific PIU risks were generally low compared to contemporary literature. However, higher levels of PIU were present in countries outside of Europe, although intra-European differences existed.
Modeling and Simulation of Coupled PMSM

In this research a mathematical model of a coupled permanent magnet synchronous machines is realized in MATLAB/Simulink environment. In the model of the machines are included the aerodynamic force and the friction force as a resistance moment. For the simulation are used two different international driving cycle: WLTC class 1 and WLTC class3. The characteristics of the electric vehicles are provided by the manufacturer.
Highly Sensitive Electrochemical Endotoxin Sensor Based on Redox Cycling Using an Interdigitated Array Electrode Device

The Limulus amebocyte lysate (LAL) reaction-based assay, the most commonly used endotoxin detection method, requires a skilled technician. In this study, to develop an easy-to-use and highly sensitive endotoxin sensor, we created an electrochemical endotoxin sensor by using an interdigitated array electrode (IDAE) device with advantages of amplifiable signals via redox cycling and portability. We added Boc-Leu-Gly-Arg-p-aminophenol (LGR-pAP) as an electrochemical substrate for an LAL reaction and detected p-aminophenol (pAP) released from LGR-pAP as a product of an endotoxin-induced LAL reaction via an IDAE device. The IDAE device showed a great redox cycling efficiency of 79.8%, and a 4.79-fold signal amplification rate. Then, we confirmed that pAP was detectable in the presence of LGR-pAP through chronoamperometry with the potential of the anode stepped from −0.3 to 0.5 V vs. Ag/AgCl while the cathode was biased at −0.3 V vs. Ag/AgCl. Then, we performed an endotoxin assay by using the IDAE device. Our endotoxin sensor detected as low as 0.7 and 1.0 endotoxin unit/L after the LAL reaction for 1 h and 45 min, respectively, and these data were within the cut-off value for ultrapure dialysis fluid. Therefore, our highly sensitive endotoxin sensor is useful for ensuring medical safety.
Robust Variable Selection with Exponential Squared Loss for the Spatial Durbin Model

With the continuous application of spatial dependent data in various fields, spatial econometric models have attracted more and more attention. In this paper, a robust variable selection method based on exponential squared loss and adaptive lasso is proposed for the spatial Durbin model. Under mild conditions, we establish the asymptotic and “Oracle” properties of the proposed estimator. However, in model solving, nonconvex and nondifferentiable programming problems bring challenges to solving algorithms. To solve this problem effectively, we design a BCD algorithm and give a DC decomposition of the exponential squared loss. Numerical simulation results show that the method is more robust and accurate than existing variable selection methods when noise is present. In addition, we also apply the model to the 1978 housing price dataset in the Baltimore area.
Derivation of the perfect wave for optimising the strong-field driven electron recollision energy

In the article of L.E. Chipperfield et al. [Phys. Rev. Lett. 2009, 102, 063001], the ideal waveform was presented that maximised the recollision energy of a strong-field driven electron. In this paper we expound the derivation of this perfect wave, as well as a more general waveform for optimising electron trajectories for which the recollision occurs some distance from the place of origin. The ideal waveform acts as a guide for the synthesises of more practical waveforms that maximise the electron recollision energy, and so extend the high-order harmonic cut-off to higher frequencies.
Enhancement of Pathogen Toxicity by Feeding Reticulitermes chinensis Snyder Sonicated Bacteria Expressing Double-Stranded RNA That Interferes with Olfaction

Simple Summary Reticulitermes chinensis Snyder is an important pest that destroys trees and buildings and causes great damage. The present study investigated the role of RcOrco. A method for preparing large amounts of dsRNA using sonication of engineered bacteria was established. The dsRNA produced using this method was ingested by R. chinensis via feeding, which decreased the expression level of RcOrco and survival rate. The results of this study enhance our knowledge of orco function in social insects and propose new potential targets for termite control. Abstract Reticulitermes chinensis Snyder is a serious pest in China, and the odorant receptor co-receptor gene RcOrco plays a crucial role in olfaction. However, the function of RcOrco in the resistance of termites to entomopathogens has not been reported. We constructed dsRcOrco-HT115 engineered bacteria based on the RcOrco sequence from the full-length transcriptome data of R. chinensis. The engineered bacteria expressed dsRNA of RcOrco. Sonication was used to inactivate the dsRNA-HT115 strain and obtain a large amount of dsRcOrco. The dsRcOrco produced using this method overcame the problem that genetically engineered bacteria could not be applied directly and improved its effectiveness against termites. Bioassays using the dsRcOrco generated using this method showed that dsRcOrco significantly increased the toxicity of the bacterial and fungal pathogens to R. chinensis. The present study showed, for the first time, the function of Orco in termite resistance to pathogens, and the results provide a theoretical basis for the development and application of termite RNA biopesticides.
Welfare and Clinical Assessment on Physical Captures Followed by Anesthesia in Apennine Chamois (Rupicapra pyrenaica ornata)

Simple Summary Apennine chamois (Rupicapra pyrenaica ornata) is a vulnerable subspecies, and creation of new colonies is required for its conservation. Capturing mountain ungulates is not only logistically challenging, but also requires careful planning and clinical monitoring in order to ensure animal welfare and survival. This study reports collective physical capture followed by anesthesia of 21 Apennine chamois for translocation with conservation purposes. The chamois were captured with up-net® (Fondazione Universitaria “Centro Ricerche sulla Gestione della fauna selvatica”—CE.RI.GE.FA.S., Sampeyre—CN) or box-traps, then anesthetized with medetomidine–ketamine–acepromazine and monitored with advanced field techniques, including venous blood gas analysis, which was used for the first time on mountain ungulates in Europe. Despite the risk of metabolic acidosis and catching myopathy, 19 chamois survived and adapted to the new environment to found new colonies, which were monitored through GPS radiocollar data of all released chamois. Abstract The Apennine chamois (Rupicapra pyrenaica ornata) is one of the rarest subspecies in Italy, listed in Annexes II and IV of the Habitats Directive and currently included as a vulnerable subspecies in the International Union for Conservation of Nature (IUCN) Red List. The Maiella National Park population has recently been defined as a source population for reintroduction into other parks. Since collective captures allow for better selection of target animals for the establishment of new colonies, the aim of this study is to evaluate the physiological conditions and animal welfare in free-ranging Apennine chamois after collective physical capture followed by chemical immobilization with medetomidine 0.054 mg ± 0.007, ketamine 2.14 mg ± 0.28, and acepromazine 0.043 mg ± 0.006. Twenty-one Apennine chamois (18 females and 3 males) were captured and translocated for conservation purposes. The effects of capture and anesthesia were evaluated using clinical variables, hematology, serum biochemistry, and venous blood gas analysis, the latter being used in the field for the first time in chamois capture. A risk of metabolic acidosis and capture myopathy was identified, although it did not compromise the survival of 19 chamois, which adapted to novel environments and founded new colonies, as verified through GPS radiocollars. The protocol applied in this study represents an innovative approach to assessing animal physiology and welfare in collective mountain ungulate captures, useful for improving management activities for conservation purposes.
A Non-Reference Evaluation of Underwater Image Enhancement Methods Using a New Underwater Image Dataset

The rise of vision-based environmental, marine, and oceanic exploration research highlights the need for supporting underwater image enhancement techniques to help mitigate water effects on images such as blurriness, low color contrast, and poor quality. This paper presents an evaluation of common underwater image enhancement techniques using our new publicly-available Challenging Dataset for Underwater Image Enhancement (CDUIE). The collected dataset is comprised of 85 images of aquatic plants taken at a shallow depth of up to three meters from three different locations in the Great Lake Superior, USA, via a Remotely Operated Vehicle (ROV) equipped with a high-definition RGB camera. In particular, we use our dataset to benchmark nine state-of-the-art image enhancement models at three different depths using a set of common non-reference image quality evaluation metrics. Then we provide a comparative analysis of the performance of the selected models at different depths and highlight the most prevalent ones. The obtained results show that the selected image enhancement models are capable of producing considerably better-quality images with some models performing better than others at certain depths. The dataset is available at https://www.github. com/ashrafrepo/underwater-image-enhancement.
Mesoscale Variations of Tropospheric Aerosols

Abstract Tropospheric aerosols are calculated to cause global-scale changes in the earth's heat balance, but these forcings are space/time integrals over highly variable quantities. Accurate quantification of these forcings will require an unprecedented synergy among satellite, airborne, and surface-based observations, as well as models. This study considers one aspect of achieving this synergy—the need to treat aerosol variability in a consistent and realistic way. This need creates a requirement to rationalize the differences in spatiotemporal resolution and coverage among the various observational and modeling approaches. It is shown, based on aerosol optical data from diverse regions, that mesoscale variability (specifically, for horizontal scales of 40–400 km and temporal scales of 2–48 h) is a common and perhaps universal feature of lower-tropospheric aerosol light extinction. Such variation is below the traditional synoptic or “airmass” scale (where the aerosol is often assumed to be essentially ho.
Tumor Androgen Receptor Protein Level Is Positively Associated with a Better Overall Survival in Melanoma Patients

Androgen receptor (AR) is expressed in numerous tissues and serves important biologic functions in skin, prostate, immune, cardiovascular, and neural systems, alongside sexual development. Several studies have associated AR expression and patient survival in various cancers, yet there are limited studies examining the relationship between AR expression and cutaneous melanoma. This study used genomics and proteomics data from The Cancer Proteome Atlas (TCPA) and The Cancer Genome Atlas (TCGA), with 470 cutaneous melanoma patient data points. Cox regression analyses evaluated the association between AR protein level with overall survival and revealed that a higher level of AR protein was positively associated with a better overall survival (OS) (p = 0.003). When stratified by sex, the AR association with OS was only significant for both sexes. The multivariate Cox models with justifications of sex, age of diagnosis, stage of disease, and Breslow depth of the tumor confirmed the AR-OS association in all patients. However, the significance of AR was lost when ulceration was included in the model. When stratified by sex, the multivariate Cox models indicated significant role of AR in OS of female patients but not in males. AR-associated genes were identified and enrichment analysis revealed shared and distinct gene network in male and female patients. Furthermore, AR was found significantly associated with OS in RAS mutant subtypes of melanoma but not in BRAF, NF1, or triple-wild type subtypes of melanoma. Our study may provide insight into the well-known female survival advantage in melanoma patients.
Capture and Recognition of Bead Weaving Activities using Hand Skeletal Data and an LSTM Deep Neural Network

Several factors lead to the extinction of tangible cultural heritage, such as globalization, urbanization, intention and accidental neglect, modernization, mechanization, limited usage, migration, and the minimization of skilled practitioners/craft educators and owners. We, the Gesture and Form group, aim to preserve the bead weaving craft, which plays an essential role in culture. We aim to use Augmented reality (AR) and Machine Learning (ML) to preserve this craft. Preservation in this context means passing the technique from one generation to the other, even without a skilled craftsperson. To achieve this, we aim to use an LSTM deep neural network to classify micro activities in the Peyote stitch with the hand skeletal data from the Microsoft Hololens 2. In this paper, we present our preliminary work and a workflow of the ML process involved with a mini project we called "Thumbs-up gesture classification. " Using a single subject participant for the gesture classification, we achieve 100% accuracy on the training and test set, and new data from the device. Finally, we present a future direction for our research.
Mobility-Aware Proactive Edge Caching for Large Files in the Internet of Vehicles

By shifting the requested content to the edge in the Internet of Vehicles (IoV), edge caching is expected to be an effective solution to satisfy the low latency and high-reliability requirements of IoV users for multimedia services. However, the edge node’s coverage area and storage space are limited. Moreover, since vehicles have high mobility and in-vehicle multimedia applications require sequential delivery for contents, we need to address two main issues: 1) how to optimize the proactive content caching decision (i.e., the placement of cached content chunks) among edge nodes (ENs) to provide better Quality of Services (QoS) for IoV users and 2) how to ensure that vehicles can download the required contents sequentially to improve Quality of Experience (QoE). In this article, we propose a mobility-aware proactive edge caching scheme (MSTPS), where the spatial and temporal prediction of vehicles are taken into account for content deployment and scheduling. Specifically, we optimize the caching decision based on predicting the vehicle’s driving trajectory and travel preference. The scheme learns the vehicle’s travel preferences to cope with mobility uncertainty by combining users with similar travel patterns. Meanwhile, the proposed scheme can support the sequential downloading of content chunks. Furthermore, in order to deal with the dynamic characteristics and unpredictable challenges of the IoV, we design a system recovery strategy, which can avoid the degradation of the proposed scheme due to the failure of prediction. Finally, by using real mobility data sets and scenarios, we explore the impact of the number of ENs deployed in advance for each vehicle’s request when the cache needs to be updated on system performance. In addition, we evaluate the effectiveness of the proposed scheme. Our proposed scheme can achieve the best cache hit ratio and decrease caching costs compared to the existing mobility-aware in-order caching schemes.
FDSS-Based DFT-s-OFDM for 6G Wireless Sensing

Integrated sensing and communications (ISAC) is emerging as a key technology of 6G. Owing to the low peak-to-average power ratio (PAPR) property, discrete Fourier transform spread orthogonal frequency-division multiplexing (DFT-s-OFDM) is helpful to improve the sensing range and suitable for high-frequency transmission. However, compared to orthogonal frequency-division multiplexing (OFDM), the sensing accuracy of DFT-s-OFDM is relatively poor. In this paper, frequency-domain spectral shaping (FDSS) is adopted to enhance the performances of DFT-s-OFDM including sensing accuracy and PAPR by adjusting the correlation of signals. Specifically, we first establish a signal model for the ISAC system, followed by the description of performance indicators. Then, we analyze the influence of amplitude fluctuation of frequency domain signals on sensing performance, which shows the design idea of FDSS-enhanced DFT-s-OFDM. Further, a FDSS-enhanced DFT-s-OFDM framework is introduced for ISAC, where two types of FDSS filters including a pre-equalization filter and an isotropic orthogonal transform algorithm (IOTA) filter are designed. The simulation results show that the proposed scheme can obtain about 4 dB performance gain in terms of sensing accuracy over DFT-s-OFDM. In addition, FDSS-enhanced DFT-s-OFDM can significantly reduce PAPR and improve the power amplifier efficiency.
Scattering of infrared radiation by dust in NGC 7023 and NGC 2023

The contribution of scattered light to the total nebular emission is determined on the basis of linear polarization measurements at 1.25, 1.65, and 2.2 microns of the visual reflection nebulae NGC 7023 and NGC 2023. The percentage polarization of NGC 7023 slowly increases from 0.3 to 1 micron, with peak polarizations of up to 26 percent at 1.25 micron, then rapidly decreases, with values of 4-7 percent at 2.2 microns. This is interpreted as implying that scattered starlight contributes most to the SW emission, while unpolarized emission from small grains or large molecules dominates at longer wavelengths. IR polarization and surface brightness measurements are combined to derive the intensity of scattered light, which is then compared with scattering models. While the near-IR emission of both NGC 2023 and NGC 7023 is dominated by small-grain or large-molecule emission, IR scattered light plays a larger role in NGC 2023 than in NGC 7023.
A comparative study of 2.667 Gb/s OOK, DPSK, and PPM modulation formats for FSO applications

We have compared experimentally the transmission performance of on-off keying (OOK), differential phase-shift keying (DPSK), and pulse position modulation (PPM) optical waveforms at 2.5 Gb/s for free-space optical communication applications. We show that each technique is advantageous depending on the desired system complexity, cost, transmission data rate, optical aperture used (single mode vs. multimode), optical receiver used, availability of optical preamplifier, and ambient conditions. RZ format offers a 1- to 2-dB receiver sensitivity advantage over NRZ for both OOK and DPSK. With an optical preamplifier, an APD receiver offers no advantage over a PIN receiver. If the light can be collected efficiently in single-mode fiber without phase noise and an optical preamplifier is available, RZ-DPSK has definite performance advantages over other data formats. We measured an unoptimized balanced receiver sensitivity of 58 photons/bit for 10-9 BER for RZ-DPSK. For multimode received optical signals, RZ-OOK combined with an APD receiver is an optimum choice for 2.5 Gb/s.