Miracle-dz/UniFAR-FTUs huggingface dataset:
RAANet: Range-Aware Attention Network for LiDAR-based 3D Object Detection with Auxiliary Density Level Estimation

3D object detection from LiDAR data for autonomous driving has been making remarkable strides in recent years. Among the state-of-the-art methodologies, encoding point clouds into a bird’s-eye view (BEV) has been demonstrated to be both effective and efﬁcient. Different from perspective views, BEV preserves rich spatial and distance information between objects; and while farther objects of the same type do not appear smaller in the BEV, they contain sparser point cloud features. This fact weakens BEV feature extraction using shared-weight convolutional neural networks. In order to address this challenge, we propose Range-Aware Attention Network (RAANet), which extracts more powerful BEV features and generates superior 3D object detections. The range-aware attention (RAA) convo-lutions signiﬁcantly improve feature extraction for near as well as far objects. Moreover, we propose a novel auxiliary loss for density estimation to further enhance the detection accuracy of RAANet for occluded objects. It is worth to note that our proposed RAA convolution is lightweight and compatible to be integrated into any CNN architecture used for the BEV detection. Extensive experiments on the nuScenes dataset demonstrate that our proposed approach outperforms the state-of-the-art methods for LiDAR-based 3D object detection, with real-time inference speed of 16 Hz for the full version and 22 Hz for the lite version. The code is publicly available at an anonymous Github
The Maternal and Child Health (MCH) Handbook and its Influence on Health Behaviors: A Literature Review

The Maternal and Handbook and its Influence on Health Objectives: The MCH handbook is a health record and home-based information tool that records and provides health information for women throughout their pregnancy, delivery, and postnatal period, and about the child from the years 0-5. A literature review was conducted using current evidence-based results to determine the effectiveness of the MCH handbook Methods: The Medline Ovid database was searched for “ Maternal and Child Health Handbook ” . Among the 50 results, 17 articles were found to be relevant and thus reviewed. Results: This literature review revealed that the MCH handbook is an effective tool that positively influences the behaviours of pregnant women in regard to immunizations, breastfeeding, nutrition, child development, and illnesses. Allowing for two-way communication ensures that the health of both pregnant women and their child(ren) are taken care of at an optimal level. Discussion: There is a need for greater collaboration between governments, the United Nations, donor agencies and NGOs. This will ensure that every mother, regardless of her culture and socioeconomic class, is educated and empowered well enough to positively impact both the health of her own, and her child(ren) ’ s.
The Role of Technology in Health Professions Education During the COVID-19 Pandemic

The COVID-19 pandemic has sparked radical shifts in the ways that both health care and health professions education are delivered. Before the pandemic, some degree programs were offered fully online or in a hybrid format, but in-person learning was considered essential to the education and training of health professionals. Similarly, even as the use of telehealth was slowly expanding, most health care visits were conducted in-person. The need to maintain a safe physical distance during the pandemic rapidly increased the online provision of health care and health professions education, accelerating technology adoption in both academic and professional health care settings. Many health care professionals, educators, and patients have had to adapt to new communication modalities, often with little or no preparation. Before the pandemic, the need for cost-effective, robust methodologies to enable teaching across distances electronically was recognized. During the pandemic, online learning and simulation became essential and were often the only means available for continuity of education and clinical training. This paper reviews the transition to online health professions education and delivery during the COVID-19 pandemic and provides recommendations for moving forward.
Millimeter-wave monolithic power amplifier for mobile broad-band systems

For personal communication systems, the highest possible integration into monolithic technology of all RF functions are desirable. A frequency band around 60 GHz is assigned for future mobile communication fourth-generation systems (i.e., mobile broad-band systems concept). In this paper, the design and test of two monolithic class-A power amplifiers with 0.15 /spl mu/m pseudomorphic heterojunction FET (PMHFET) technology is presented. One of the amplifiers is a three-stage cascade 50 /spl Omega/ amplifier and the second is a balanced amplifier based on the previous one, but matched for integration on a waveguide carrier. A study on the accuracy of the passive elements and discontinuities models at 60 GHz was performed. Models for the microstrip discontinuities were obtained from electromagnetic simulation. In order to choose the best FET bias, a nonlinear model for the PMHFETs devices, based on continuous DC and AC measurements, were derived. For comparison purposes, the FET simulation results with a nonlinear model based on pulsed measurements are also presented. To avoid stability problems, at the device level an RC feedback network was introduced. A 1-dB compression point of 18 dBm was measured on-wafer for both amplifiers at 62 GHz with V/sub DSbias/=3.5 V. The three-stage and balanced amplifiers chip sizes are 3 mm/spl times/1.5 mm and 3 mm/spl times/4 mm, respectively.
Bulk Gene Expression Deconvolution Reveals Infiltration of M2 Macrophages in Retinal Neovascularization

Purpose This study interrogated the transcriptional features and immune cellular landscape of the retinae of rats subjected to oxygen-induced retinopathy (OIR). Methods Bulk RNA sequencing was performed with retinal RNA isolated from control and OIR rats. Gene set enrichment analysis (GSEA) was undertaken to identify gene sets associated with immune responses in retinal neovascularization. Bulk gene expression deconvolution analysis by CIBERSORTx was performed to identify immune cell types involved in retinal neovascularization, followed by functional enrichment analysis of differentially expressed genes (DEGs). Protein–protein interaction analysis was performed to predict the hub genes relevant to identified immune cell types. CIBERSORTx was applied to profile immune cell types in the macula of patients with both proliferative diabetic retinopathy (PDR) and diabetic macular edema using a public RNA-seq dataset. Results Transcriptome analysis by GSEA revealed that the retina of OIR rats and patients with PDR is characterized by increased immunoregulatory interactions and complement cascade. Deconvolution analysis demonstrated that M2 macrophages infiltrate the retinae of OIR rats and patients with PDR. Functional enrichment analysis of DEGs in OIR rats showed that the dysregulated genes are related to leukocyte-mediated immunity and myeloid leukocyte activation. Downstream protein–protein interaction analysis revealed that several potential hub genes, including Ccl2, Itgam, and Tlr2, contribute to M2 macrophage infiltration in the ischemic retina. Conclusions This study highlights application of the gene expression deconvolution tool to identify immune cell types in inflammatory ocular diseases with transcriptomes, providing a new approach to assess changes in immune cell types in diseased ocular tissues.
Research on an Improved Self-Correcting Location Algorithm for Wireless Local Region

Node position technology is an internal demand of wireless sensor network, however, in most project account; it’s hard to obtain the nodes' exact position because of uncontrollability in the network deployment process. For this purpose, an improved self-correcting location algorithm which based on RSSI multilateral ranging was proposed in this paper. Other than the primary multilateral localization algorithm, a correcting node which adjacent to the blind node was imported into the pending location region. The main function is to reduce the influence caused by unilateral ranging error in the calculation of multilateral positioning and improves the positioning precision. Detailedly introduced the principle of self-correcting location algorithm, moreover, in order to check the improved algorithm’s location performance, a back testing was done via CC2430/CC2431 wireless nodes. Test results show that improved algorithm enhances the system’s accuracy and stability.
Smartphone-Based Colorimetric Detection of Chromium (VI) by Maleic Acid-Functionalized Gold Nanoparticles

Because of the significant environmental pollution produced by human activities, there is an ongoing need to develop transportable, simple, and reliable techniques for determining trace contaminants on the spot. This work reported a colorimetric detection method for aqueous Cr(VI) sensing by maleic acid-functionalized gold nanoparticles with high sensitivity and selectivity. The wine-red color of the probe solution can change to gray even in the presence of 1.0 µg L−1 of aqueous Cr(VI). Moreover, with the assistance of a smartphone installed with a commercially available color scan application software, its concentration of could be readily quantified on the spot without the help of UV-Vis spectrometer. The detection limit could reach as low as 0.1 µg L−1 with linear range from 0.2 to 2.0 µg L−1. Most importantly, the coefficient variation of the proposed smartphone-based method was equivalent to that of colorimetry, demonstrating the high accuracy of the proposed method for accurate detection of Cr(VI) in resource-constrained countries. Conclusively, with the help of the smartphone, this nanomaterials-based probe demonstrated the potential in the field of environment monitoring for on-site quantitative detection of any pollutants in resource-constrained countries.
Wavelet Analysis of Rainfall and Runoff Multidecadal Time Series on Large River Basins in Western North Africa

This work is dedicated to the study of the spatio-temporal variability of climate in Morocco by the analysis of rainfall (gridded and gauged data) and runoff. The wavelet analysis method has been used in this study to compare the rainfall and runoff series and to show the major discontinuities identified in 1970, 1980, and 2000. Several modes of variability have been detected; this approach has been applied to show annual (1 year) and inter-annual modes (2–4 years, 4–8 years, 8–12/8–16 years, and 16–30 years), and some modes are specific to some stations. This analysis will be complemented by the gridded data covering the period from 1940 to 1999, which will allow for a better understanding of the spatial variability of the highlighted signals set, which identified frequencies at 1 year and 8–16 years, distinguished different time periods at each basin and identified three main discontinuities in 1970, 1980, and 2000. The contribution of climatic indices is important as it is between 55% and 80%.
Design and simulation of the sliding mode controller for the vehicle blow-out process control

During vehicle driving process, the tyre security is very important, but the blow-out is inevitable sometimes, so it is very necessary to control the vehicle stability in order to avoid serious traffic accidents caused by the blowout. In this paper, with the tyre brush model and the seven degree of freedom vehicle model, the vehicle driving system model is modelled, and the front and rear tyres blow-out process was simulated and analysed. The results show that the vehicle will become unstable after the blow-out. In order to ensure the vehicle back to the stable range, the sliding mode controller is designed with the differential braking method, and the yaw rate is controlled by adjusting the braking torque at the opposite side of the blow-out tyre. With simulation, the sliding mode controller can guarantee the vehicle stability, shorten the braking distance and realise the safety brake during the tyre blow-out process.
Modeling of interconnect capacitance, delay, and crosstalk in VLSI

Increasing complexity in VLSI circuits makes metal interconnection a significant factor affecting circuit performance. In this paper, we first develop new closed-form capacitance formulas for two major structures in VLSI, namely: (1) parallel lines on a plane and (2) wires between two planes, by considering the electrical flux to adjacent wires and to ground separately. We then further derive closed-form solutions for the delay and crosstalk noise. The capacitance models agree well with numerical solutions of three-dimensional (3-D) Poisson equation as well as measurement data. The delay and crosstalk models agree well with SPICE simulations.
Investigating the Neoliberal Educational Agenda: The Effect of Reform Contexts on Teacher Agency

During the transition to democratic society a neoliberal educational agenda was introduced to guide the reform process in Estonia. Documentary analysis was conducted for this research and six periods emerged, which showed that expectations were placed on teachers that assumed the existence of teacher agency, while the reform context didn’t support its emergence. Evidence of change can be seen in the last periods, when also a significant dichotomy arises.
ERANN: An Algorithm to Extract Symbolic Rules from Trained Artificial Neural Networks

Abstract This paper presents an algorithm to extract symbolic rules from trained artificial neural networks (ANNs), called ERANN. In many applications, it is desirable to extract knowledge from ANNs for the users to gain a better understanding of how the networks solve the problems. Although ANN usually achieves high classification accuracy, the obtained results sometimes may be incomprehensible, because the knowledge embedded within them is distributed over the activation functions and the connection weights. This problem can be solved by extracting rules from trained ANNs. To do so, a rule extraction algorithm has been proposed in this paper to extract symbolic rules from trained ANNs. A standard three-layer feedforward ANN with four-phase training is the basis of the proposed algorithm. Extensive experimental studies on a set of benchmark classification problems, including breast cancer, iris, diabetes, wine, season, golfplaying, and lenses classification, demonstrates the applicability of the proposed method. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and the rules accuracy. The proposed method achieved accuracy values 96.28%, 98.67%, 76.56%, 91.01%, 100%, 100%, and 100% for the above problems, respectively. It has been seen that these results are one of the best results comparing with results obtained from related previous studies.
A two-channel feedback active noise control system with delayless subband architecture to reduce compressor noise of an enclosed heating, ventilation and air conditioning unit

This paper discusses the development of an active noise control (ANC) system to cancel compressor noise produced by a commercially available heating, ventilation and air conditioning unit enclosed within a closet. Feedback ANC architecture that requires no reference microphone is used for cost-effectiveness. A novel delayless subband adaptive filtering technique is used to reduce computational complexity of the algorithm and improve system performance. Finally, the system is extended to two-channel architecture in order to provide an additional zone of silence. Using an experimental setup, the noise from the compressor at two error microphone positions is recorded and all necessary secondary path measurements are taken. Noise attenuation levels of 11 dB and 21 dB are obtained at the two error microphones, resulting in an average attenuation of 18 dB.
Design of Intellectualized Monitoring Module Based on CAN Fieldbus for Air Pipeline of Marine

An intelligent module is design for monitoring air pipeline pressure on ship. The project is proposed adopting DSP as control core and employing redundant CAN bus to ensure the data transmission reliability. The key solution such as power supply, signal conditioning and communication are introduced in detail. The intelligent diagnosis and communication protocol are also discussed in the end.
Data Fusion Analysis Method for Assessment on Safety Monitoring Results of Deep Excavations

AbstractA safety monitoring system is usually applied in deep excavations in order to control the construction risk and to ensure the serviceability of adjacent facilities. Considering the mass data collected by different sensors, a reasonable assessment method on the monitoring results is necessary to evaluate the safety state of both the deep excavation itself and the surrounding environment. By introducing the conception of data fusion, a comprehensive assessment method is presented to find the anomaly in the safety monitoring results in this paper. Data fusion analyses on both a single monitoring item and the correlation of multiple monitoring items are proposed and studied. The one-class support vector machines (SVMs) are used to improve the data fusion analysis between a single monitoring item and different excavation parameters, and then developed to three-dimensional (3D) fusion analysis on a single item and multiple parameters of an excavation. The mechanical and geometric patterns between differ.
A Hybrid Approach for Cases Classification of Medical Data

Classification of cases has been widely applied in medicine, and it is helpful to disease diagnosis to a great extent. At present, the classification of medical cases is performed by physicians subjectively based on clinical theory and knowledge, which may hinder the diagnosis and treatment in some extent. In this paper, a hybrid classification approach (HCA) is proposed for medical data, it consists of two parts, including feature selection and classification. In feature selection, critical features are selected from the original features through linear correlation. Based on the selected features, cases are classified by C5.0 decision tree. And the proposed approach is evaluated through four medical datasets of diabetes, cardiac Single Proton Emission Computed Tomography (SPECT) images, lung cancer, and hepatitis survival for demonstration. On the four datasets, HCA shows a better construction for obviously higher classification accuracies, and it also outperforms some typical integrated classification methods.
Illuminance, difficulty, complexity and visual performance

Some recent results by Rowlands el al. have challenged the established relationship between illuminance, visual performance and task difficulty. A distinction can be drawn between task complexity, the number of operations needed to complete the task, and visual difficulty, the difficulty in seeing the detail required. It is then pqssible to show that the results of Rowlands et al. fit the established pattern and successfully to predict the results of a visual performance experiment using Landolt rings of the same visual difficulty but different task complexities.
The Correlation between Vitamin D and Clinical Implications for Obesity-Related Type 2 Diabetes Mellitus

Background: Obesity and type 2 diabetes have both rapidly raised during the last periods and are ongoing to increase at a disturbing rate universal. Several clinical and epidemiological researches demonstrated a reverse association between circulating vitamin D levels, central adiposity and the progress of insulin resistance and diabetes. Objective: The target of this work was to elucidate the complex role of vitamin D and the clinical implications of diabetes on metabolic defects related with obesity. Subjects and Methods: This study encompassed 90 diabetic patients (45 obese and 45 non obese) who were attending the National Diabetic Center/ Al-Mustansiriyah University during the period from June 2019 to January 2020; their age range was (35-60) years. All participant underwent clinical and biochemical examinations. Results: A substantial rise (p= 0.01) in waist/hip ratio, body mass index, fasting serum glucose, total cholesterol, triacylglycerol, and low density lipoprotein cholesterol in obese diabetic patients as paralleled to non-obese group. Moreover, there was an elevation in glycated hemoglobin, serum insulin, and homeostasis model assessment for insulin resistance in obese group, but it was not significant. A substantial decrease (p= 0.01) in serum high density lipoprotein cholesterol and vitamin D3 were detected in obese diabetic patients as paralleled to non-obese group. Also, obese diabetic patients had the higher percent (61%) of D3 deficiency as paralleled to non-obese patients. Conclusions: In the present study, it is found that there is significant increase in blood sugar in the individuals with decreased vitamin D levels, which was related with insulin resistance, decreased β-cell function, and obesity.
A Double-Deck Structure of Reduced Graphene Oxide Modified Porous Ti3C2Tx Electrode towards Ultrasensitive and Simultaneous Detection of Dopamine and Uric Acid

Considering the vital physiological functions of dopamine (DA) and uric acid (UA) and their coexistence in the biological matrix, the development of biosensing techniques for their simultaneous and sensitive detection is highly desirable for diagnostic and analytical applications. Therefore, Ti3C2Tx/rGO heterostructure with a double-deck layer was fabricated through electrochemical reduction. The rGO was modified on a porous Ti3C2Tx electrode as the biosensor for the detection of DA and UA simultaneously. Debye length was regulated by the alteration of rGO mass on the surface of the Ti3C2Tx electrode. Debye length decreased with respect to the rGO electrode modified with further rGO mass, indicating that fewer DA molecules were capable of surpassing the equilibrium double layer and reaching the surface of rGO to achieve the voltammetric response of DA. Thus, the proposed Ti3C2Tx/rGO sensor presented an excellent performance in detecting DA and UA with a wide linear range of 0.1–100 μM and 1–1000 μM and a low detection limit of 9.5 nM and 0.3 μM, respectively. Additionally, the proposed Ti3C2Tx/rGO electrode displayed good repeatability, selectivity, and proved to be available for real sample analysis.
A Dual-Frequency Transformer for Complex Impedances With Two Unequal Sections

In this letter, a small dual-frequency transformer with two unequal sections for complex impedances is proposed. To design this transformer, two different groups of nonlinear equations and the corresponding solutions processes are obtained. The results of numerical examples show that two complex impedances can be matched at two different frequencies simultaneously. This proposed transformer can be regarded as the extension of small dual-frequency transformer in two sections for two resistances.