Miracle-dz/UniFAR-FTUs huggingface dataset:
Densely connected deep random forest for hyperspectral imagery classification

ABSTRACT In very recent years, deep learning based methods have been widely introduced for the classification of hyperspectral images (HSI). However, these deep models need lots of training samples to tune abundant parameters which induce a heavy computation burden. Therefore, most of these algorithms need to be accelerated with high-performance graphics processing units (GPU). In this paper, a new deep model–densely connected deep random forest (DCDRF) is proposed to classify the hyperspectral images. This model is composed of multiple forward connected random forests. The DCDRF has following merits: 1) It obtains satisfactory classification accuracy with a small number of training samples, 2) It can be run efficiently on the central processing unit (CPU), 3) Only a few parameters are involved during the training. Experimental results based on three hyperspectral images demonstrate that the proposed method can achieve better classification performance than the conventional deep learning based methods.
DO3D: Self-supervised Learning of Decomposed Object-aware 3D Motion and Depth from Monocular Videos

Although considerable advancements have been attained in self-supervised depth estimation from monocular videos, most existing methods often treat all objects in a video as static entities, which however violates the dynamic nature of real-world scenes and fails to model the geometry and motion of moving objects. In this paper, we propose a self-supervised method to jointly learn 3D motion and depth from monocular videos. Our system contains a depth estimation module to predict depth, and a new decomposed object-wise 3D motion (DO3D) estimation module to predict ego-motion and 3D object motion. Depth and motion networks work collaboratively to faithfully model the geometry and dynamics of real-world scenes, which, in turn, benefits both depth and 3D motion estimation. Their predictions are further combined to synthesize a novel video frame for self-supervised training. As a core component of our framework, DO3D is a new motion disentanglement module that learns to predict camera ego-motion and instance-aware 3D object motion separately. To alleviate the difficulties in estimating non-rigid 3D object motions, they are decomposed to object-wise 6-DoF global transformations and a pixel-wise local 3D motion deformation field. Qualitative and quantitative experiments are conducted on three benchmark datasets, including KITTI, Cityscapes, and VKITTI2, where our model delivers superior performance in all evaluated settings. For the depth estimation task, our model outperforms all compared research works in the high-resolution setting, attaining an absolute relative depth error (abs rel) of 0.099 on the KITTI benchmark. Besides, our optical flow estimation results (an overall EPE of 7.09 on KITTI) also surpass state-of-the-art methods and largely improve the estimation of dynamic regions, demonstrating the effectiveness of our motion model. Our code will be available.
Soil Sealing: Quantifying Impacts on Soil Functions by a Geospatial Decision Support System

Soil sealing is considered among the most dangerous of land degradation processes on global, European and national scales. Despite important policy documents aiming to mitigate this soil threat, it currently shows no signs of abating, and current efforts often do not result in appropriate implementation of soil sealing mitigation in spatial planning, which represents the subject area governing soil sealing. In this paper, we show a spatial decision support system – based on a Geospatial Cyberinfrastructure – with the aim of applying it as an operational instrument aiming towards soil sealing mitigation. The system has the ambition to impact on those who take decision over soil sealing; typically, these are not agriculture experts but rather spatial planners.
Confidence-Aware RGB-D Face Recognition via Virtual Depth Synthesis

2D face recognition encounters challenges in unconstrained environments due to varying illumination, occlusion, and pose. Recent studies focus on RGB-D face recognition to improve robustness by incorporating depth information. However, collecting sufficient paired RGB-D training data is expensive and time-consuming, hindering wide deployment. In this work, we first construct a diverse depth dataset generated by 3D Morphable Models for depth model pre-training. Then, we propose a domain-independent pre-training framework that utilizes readily available pre-trained RGB and depth models to separately perform face recognition without needing additional paired data for retraining. To seamlessly integrate the two distinct networks and harness the complementary benefits of RGB and depth information for improved accuracy, we propose an innovative Adaptive Confidence Weighting (ACW). This mechanism is designed to learn confidence estimates for each modality to achieve modality fusion at the score level. Our method is simple and lightweight, only requiring ACW training beyond the backbone models. Experiments on multiple public RGB-D face recognition benchmarks demonstrate state-of-the-art performance surpassing previous methods based on depth estimation and feature fusion, validating the efficacy of our approach.
COMPARATIVE ANALYSIS OF NON-COOPERATIVE SPECTRUM SENSING TECHNIQUES IN COGNITIVE RADIO NETWORK

Cognitive radio (CR) is an integral system in telecommunications technology that gives unlicensed users access to licensed spectrums via dynamic spectrum access (DSA), to promote spectral efficiency. A significant operation in cognitive radio system is spectrum sensing. This paper evaluates and compares two of the major non-cooperative sensing techniques (energy and cyclostationary feature detector (CFD)) in order, to determine which gives better performance. Matlab Simulink was used as modeling and simulating tool for the evaluations. From the results, energy detector was simpler and faster but unlike CFD exhibited poor performance in corrupt channels.
Cystic Adenomyoma in Pregnancy: A Case Report

Abstract Cystic adenomyomas (CA) are rare. They primarily affect adolescents and young women in their fertile years. Therefore, fertility and pregnancy outcome are of pivotal relevance in this patient collective. Apart from the guidelines of the European Society of Human Reproduction and Embryology (ESHRE) on the management of endometriosis in general, there are no specific treatment recommendations for CA and, as far as our research shows, no data illustrating the behavior of a CA over the course of pregnancy. Thus, we report the case of a 32-year-old 1-gravida, 1-para, preconceptionally diagnosed with a CA by ultrasound. After thoroughly discussing further treatment options, the decision was made to opt for a more conservative approach and not perform surgery before attempting a next pregnancy. The patient conceived spontaneously and sonographic monitoring of the CA throughout pregnancy showed complete regression of the cystic component during the second trimester. A healthy baby was delivered at term by an uncomplicated elective cesarean section. Following a review of the literature and taking into account the course of our case, we propose the feasibility of a conservative, non-surgical approach in women with a CA and the desire to conceive.
THE ROLE OF INFORMATION SYSTEMS IN ADVANCING SMART VILLAGES: A RURAL TOURISM CASE STUDY

Recent studies highlight the need for a deeper understanding of the ways in which information systems, local government policy and community involvement affect the development of rural tourism. By using Structural Equation Modelling and Partial Least Squares (SEM-PLS), the current study aims to analyze the role of information systems, local government policy and local community engagement in rural tourism development. Using data from 69 participants in Watesjaya village, Bogor regency, the study analyzes multiple relationships among latent constructs. The data, encompassing variables such as system quality, information quality, local government policy, local community engagement, destination branding, and rural tourism development, undergoes meticulous reliability and validity assessments. Results from the SEM-PLS analysis unveil significant relationships and insights. Local community engagement emerges as a pivotal factor, positively influencing tourist satisfaction (0.499) and moderately affecting destination branding (0.239). However, local government policy exhibits a less pronounced positive impact on tourist satisfaction (0.069847) and a notable negative influence on destination branding (-0.300460), underscoring the need for policy realignment. Information quality paradoxically influences tourist satisfaction negatively (-0.185) and destination branding (-0.158), highlighting areas for strategic improvement. Meanwhile, information system quality positively affects tourist satisfaction (0.055) and significantly contributes to rural tourism development (0.783). This study provides a better understanding of stakeholders about rural tourism development by focusing on information system quality, information quality, local government policies, and local community engagement The study indicates that information system quality and local community engagement can be valuable indicators for boosting rural tourism development and improving tourist satisfaction.
Green Synthesis of Uncoated and Olive Leaf Extract-Coated Silver Nanoparticles: Sunlight Photocatalytic, Antiparasitic, and Antifungal Activities

The circular economy, which attempts to decrease agricultural waste while also improving sustainable development through the production of sustainable products from waste and by-products, is currently one of the main objectives of environmental research. Taking this view, this study used a green approach to synthesize two forms of silver nanoparticles: coated silver nanoparticles with olive leaf extract (Ag-olive) and uncoated pure silver nanoparticles (Ag-pure), which were produced by the calcination of Ag-olive at 550 °C. The extract and the fabricated nanoparticles were characterized by a variety of physicochemical techniques, including high-performance liquid chromatography (HPLC), thermal gravimetric analysis (TGA), X-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). Adult ticks (Hyalomma dromedarii) (Acari: Ixodidae) were used in this study to evaluate the antiparasitic activity of synthesized nanoparticles and extract. Furthermore, the antifungal activity was evaluated against Aspergillus aculeatus strain N (MW958085), Fuserium oxysporum (MT550034), and Alternaria tenuissiuma (MT550036). In both antiparasitic and antifungal tests, the as-synthesized Ag-olive showed higher inhibition activity than Ag-pure and olive leaf extract. The findings of this research suggest that Ag-olive may be a powerful and eco-friendly antiparasitic and antifungal agent. Ag-pure was also evaluated as a photocatalyst under sunlight for the detoxification of Eri-chrome-black T (EBT), methylene blue (MB), methyl orange (MO), and rhodamine B (RhB).
Gender Gap: Family Support, Perceived Work Productivity and Job Satisfaction on Working from Home

The purpose of this study is to test whether family support has a positive effect on job satisfaction. In addition, to find out whether there was a gender gap in perceived work productivity and job satisfaction between men and women both before and during the Covid-19 pandemic and whether perceived work productivity and job satisfaction did not experience any difference both before the COVID-19 pandemic and after the occurrence of the COVID-19 pandemic. A quantitative approach was used to distribute questionnaires using a purposive sampling technique to 62 employees working from home in West Sumatera in 2021. Simple regression MANOVA was conducted to analyze the data. The result of the study found that family support and job satisfaction have a positive and significant effect. Another finding is that there was no gender gap in perceived work productivity and job satisfaction between men and women before and during the Covid-19 pandemic. In addition, there was no difference between job satisfaction and perceived work productivity, both before the Covid-19 pandemic and during the Covid-19 pandemic. The research implied that it assists companies and managers in making decisions and considering the sustainability of working-from-home programs for their employees and workers. In addition, companies and agencies are also asked to create an effective working-from-home model for women and men. Furthermore, it gives trust to families to continue supporting each other to create a healthy psychological environment when facing the COVID-19 pandemic. This study tries to see whether there are gender differences between men and women in terms of perceived work productivity and job satisfaction when working from home. The results of the different tests show this is different. This is also the case with the difference between conditions before and during Covid-19. It shows that there is no difference in perceived work productivity and job satisfaction between men and women.
Positive effect of microvascular proliferation on functional recovery in experimental cervical spondylotic myelopathy

Background and purpose Cervical Spondylotic Myelopathy (CSM), the most common cause of spinal cord dysfunction globally, is a degenerative disease that results in non-violent, gradual, and long-lasting compression of the cervical spinal cord. The objective of this study was to investigate whether microvascular proliferation could positively affect neural function recovery in experimental cervical spondylotic myelopathy (CSM). Methods A total of 60 male adult Sprague–Dawley (SD) were randomly divided into four groups: Control (CON), Compression (COM), Angiostasis (AS), and Angiogenesis (A G),with 15 rats in each group. Rats in the AS group received SU5416 to inhibit angiogenesis, while rats in the AG group received Deferoxamine (DFO) to promote angiogenesis. Motor and sensory functions were assessed using the Basso Beattie Bresnahan (BBB) scale and somatosensory evoked potential (SEP) examination. Neuropathological degeneration was evaluated by the number of neurons, Nissl bodies (NB), and the de-myelination of white matter detected by Hematoxylin & Eosin(HE), Toluidine Blue (TB), and Luxol Fast Blue (LFB) staining. Immunohistochemical (IHC) staining was used to observe the Neurovascular Unit (NVU). Results Rats in the CON group exhibited normal locomotor function with full BBB score, normal SEP latency and amplitude. Among the other three groups, the AG group had the highest BBB score and the shortest SEP latency, while the AS group had the lowest BBB score and the most prolonged SEP latency. The SEP amplitude showed an opposite performance to the latency. Compared to the COM and AS groups, the AG group demonstrated significant neuronal restoration in gray matter and axonal remyelination in white matter. DFO promoted microvascular proliferation, especially in gray matter, and improved the survival of neuroglial cells. In contrast, SU-5416 inhibited the viability of neuroglial cells by reducing micro vessels. Conclusion The microvascular status was closely related to NVU remodeling an-d functional recovery. Therefore, proliferation of micro vessels contributed to function -al recovery in experimental CSM, which may be associated with NVU remodeling.
Valorization of Tannery Solid Waste Materials Using Microbial Techniques: Microbes in Tannery Solid Waste Management

This chapter describes how environmental pollution is the major problem associated with rapid industrialization, due to which the quantity of solid waste generated from the industries is increasing substantially. Solid wastes generated in leather industries are briefly classified into pre-tanned and post-tanned wastes. Although landfills, composting, anaerobic digestion and thermal incineration are available for disposal of these solid wastes, they do again pose severe environmental and financial burdens to the tanners. Microbe-mediated tannery solid waste management points to the recovery of value-added products from these wastes. Microbial valorization of tannery solid wastes for the production of saleable products would be a convincing, challenging and eco-friendly opening for its utilization when compared to that of chemical and thermal hydrolysis. Exploitation of traditional chemicals could be reduced and innovative products could be recovered, enabling sustainable solid waste management. This would ultimately alleviate the solid waste disposal problems and financial crisis faced by the tanners. Valorization of Tannery Solid Waste Materials Using Microbial Techniques: Microbes in Tannery Solid Waste Management
Characteristics of 2D Ultrasonic Vibration Incremental Forming of a 1060 Aluminum Alloy Sheet

Currently, 1060 aluminum alloy is widely applied in the electronics industry, construction, the aerospace field, traffic engineering, decorations, and the consumer goods market for its good chemical, physical, and mechanical properties. In general, excellent processing property is necessary and important for the manufacturing of complicated panels. In this paper, a special 2D ultrasonic vibration incremental forming method is designed to improve its plasticity and mechanical properties. Three kind of processing methods, including traditional single-point incremental forming, longitudinal ultrasonic vibration incremental forming, and 2D ultrasonic vibration incremental forming, are used for the flexible manufacturing of cones and cylindrical cups of 1060 aluminum alloy sheet. Then, micro-hardness tests, residual stress tests, and scanning electron microscopy tests are carried out to probe the changes in micro-structure and mechanical properties and to analyze the effects of different types of ultrasonic vibration on the plasticity and fracture characteristic of 1060 aluminum alloy. It is proven that 2D ultrasonic vibration facilitates the improvement of plasticity and surface qualities of 1060 aluminum alloy better than the other two processing methods. Therefore, the novel 2D ultrasonic vibration incremental forming process possesses substantial application value for the flexible and rapid manufacturing of complicated thin-walled component of aluminum alloy.
Investigation of the Thermal Structure in the Atmospheric Boundary Layer During Evening Transition and the Impact of Aerosols on Radiative Cooling

We have explored the evening transition using data from eighty days of observations across two fog seasons at the Kempegowda International Airport, Bengaluru (KIAB). Through field experiments and simulations integrating aerosol interaction in a radiation-conduction model, we elucidate the impact of aerosols on longwave cooling of the Atmospheric Boundary Layer (ABL). Field observations indicate that under calm and clear-sky conditions, the evening transition typically results in a distinct vertical thermal structure called the Lifted Temperature Minimum (LTM). We observe that the prevailing profile near the surface post-sunset is the LTM-profile. Additionally, the occurrence of LTM is observed to increase with decreases in downward and upward longwave flux, soil sensible heat flux, wind speed, and turbulent kinetic energy measured at two meters above ground level (AGL). In such scenarios, the intensity of LTM-profiles is primarily governed by aerosol-induced longwave heating rate (LHR) within the surface layer. Furthermore, the presence of clouds leads to increased downward flux, causing the disappearance of LTM, whereas shallow fog can enhance LTM intensity, as observed in both field observations and simulations. Usually, prevailing radiation models underestimate aerosol-induced longwave heating rate (LHR) by an order, compared to actual field observations. We attribute this difference to aerosol-induced radiation divergence. We show that impact of aerosol-induced LHR extends hundreds of meters into the inversion layer, affecting temperature profiles and potentially influencing processes such as fog formation. As the fog layer develops, LHR strengthens at its upper boundary, however, we highlight the difficulty in detecting this cooling using remote instruments such as microwave radiometer.
A Comparison of the Results from Artificial Intelligence-based and Human-based Transport-related Thematic Analysis

Artificial intelligence (AI) tools (in particular Large Language Models) have the potential to reduce the time needed to perform thematic analysis. To better understand their potential in the transportation field, we compare human-based to AI-based outcomes. Our findings indicate that AI tools, such as ChatGPT, could synthetize and summarize major topics present in our dataset regardless of previous user exposure to the subject or not. Nonetheless, caution is required as results might miss the nuance of less frequent themes. These tools could be used to accelerate the process under the supervision of researchers and practitioners given responder consent and the following of ethical practices.
MicroRNAs participate in the regulation of apoptosis and oxidative stress-related gene expression in rabbits infected with Lagovirus europaeus GI.1 and GI.2 genotypes

MicroRNAs (miRs) are a group of small, 17–25 nucleotide, non-coding RNA that regulate gene expression at the post-transcriptional level. To date, little is known about the molecular signatures of regulatory interactions between miRs and apoptosis and oxidative stress in viral diseases. Lagovirus europaeus is a virus that causes severe disease in rabbits (Oryctolagus cuniculus) called Rabbit Hemorrhagic Disease (RHD) and belongs to the Caliciviridae family, Lagovirus genus. Within Lagovirus europaeus associated with RHD, two genotypes (GI.1 and GI.2) have been distinguished, and the GI.1 genotype includes four variants (GI.1a, GI.1b, GI.1c, and GI.1d). The study aimed to assess the expression of miRs and their target genes involved in apoptosis and oxidative stress, as well as their potential impact on the pathways during Lagovirus europaeus—two genotypes (GI.1 and GI.2) infection of different virulences in four tissues (liver, lung, kidneys, and spleen). The expression of miRs and target genes related to apoptosis and oxidative stress was determined using quantitative real-time PCR (qPCR). In this study, we evaluated the expression of miR-21 (PTEN, PDCD4), miR-16b (Bcl-2, CXCL10), miR-34a (p53, SIRT1), and miRs—related to oxidative stress—miR-122 (Bach1) and miR-132 (Nfr-2). We also examined the biomarkers of both processes (Bax, Bax/Bcl-2 ratio, Caspase-3, PARP) and HO-I as biomarkers of oxidative stress. Our report is the first to present the regulatory effects of miRs on apoptosis and oxidative stress genes in rabbit infection with Lagovirus europaeus—two genotypes (GI.1 and GI.2) in four tissues (liver, lungs, kidneys, and spleen). The regulatory effect of miRs indicates that, on the one hand, miRs can intensify apoptosis (miR-16b, miR-34a) in the examined organs in response to a viral stimulus and, on the other hand, inhibit (miR-21), which in both cases may be a determinant of the pathogenesis of RHD and tissue damage. Biomarkers of the Bax and Bax/Bcl-2 ratio promote more intense apoptosis after infection with the Lagovirus europaeus GI.2 genotype. Our findings demonstrate that miR-122 and miR-132 regulate oxidative stress in the pathogenesis of RHD, which is associated with tissue damage. The HO-1 biomarker in the course of rabbit hemorrhagic disease indicates oxidative tissue damage. Our findings show that miR-21, miR-16b, and miR-34a regulate three apoptosis pathways. Meanwhile, miR-122 and miR-132 are involved in two oxidative stress pathways.