Miracle-dz/UniFAR-FTUs huggingface dataset:
Equity Conjectures: A Methodological Tool for Centering Social Change in Learning and Design

Abstract This article offers methodological insights and tools to those engaged in design-based research (DBR) seeking to advance equity-oriented learning and outcomes through co-design. We respond to recent scholarship that points to the inseparability between the assumptions we hold about society and those we hold about learning, and consider how such insights can inform the methods we employ to facilitate learning in DBR. To do so, we examine the affordances of equity conjectures, statements about how learning remedies socially and historically constructed injustices, within conjecture mapping, a process frequently used in DBR efforts to make assumptions about learning visible to ground design, implementation, and iterative refinement. We share how we made participants’ equity conjectures visible in a research-practice partnership (RPP) between university researchers, elementary computer science (CS) curriculum designers, and elementary school teachers. We examine how making these equity conjectures visible during co-design of equity-focused CS lessons facilitated shifts in both the design process and the CS education practices of participating teachers. Our findings point to the utility of explicitly surfacing equity conjectures in collaborative design efforts aimed at equity and justice.
“Opioids are opioids” – A phenomenographic analyses of physicians’ understanding of what makes the initial prescription of opioids become long-term opioid therapy

Abstract Objectives To explore prescribers’ understanding of what makes initial prescription of opioids become long-term opioid therapy (opioids >90 days). Methods A qualitative research design, phenomenography, was used for this study. Fifteen attending physicians working within primary, secondary and tertiary care in Sweden in the fields of general practice, rehab medicine, orthopedic surgery, neurosurgery, or obstetrics and gynecology were purposively recruited consecutively until categorical saturation was reached. Semi-structured interviews were used for data collection. The transcripts were analyzed and categorized by two researchers. A third researcher checked for consistency between the data and the categories. An outcome space was constructed representing the logical relationship between the categories. Results The analysis identified six categories: The addictive opioid, The deserving patient, The ignorant prescriber, The lost patient, The compassionate prescriber, and The exposed prescriber. The differences in conceptions among the categories were clarified through three main contributors related to opioid therapy: prescriber’s characteristics, patient’s characteristics, and the healthcare organization. Conclusions Opioids were understood as being addictive with long-term use promoting a downward spiral of tolerance and withdrawal driving the pain, leading to continued prescription. Long-term opioid therapy could be justified for patients who improved in function, and who were perceived as trustworthy. Inadequate follow-up of patients, poor training in pain management and addiction medicine, personal attitudes and beliefs about opioids, a perceived professional obligation to treat patients with pain, and lack of collegial support, were factors understood to promote clinically unindicated long-term opioid therapy.
Sleep in an At Risk Adolescent Group: A Qualitative Exploration of the Perspectives, Experiences and Needs of Youth Who Have Been Excluded From Mainstream Education

The sleep needs, experiences and viewpoints were explored for UK adolescents who have been excluded from mainstream education. Qualitative data was gathered through interviews with 9 participants, aged 11–15 years, who also completed questionnaires. The participants had symptoms of inadequate sleep, poor sleep hygiene behaviours and were not getting the recommended amount of sleep on school nights. Participants described sleep patterns involving often staying up late and having different sleep timing on weekends than weekdays and having difficulties with their sleep. Use of technology and the relevance of family were identified as important and associated with facilitating and hindering factors for sleep. Participants communicated that they lack control over aspects of their sleep and their lives. The experiences and views of the participants can inform professionals’ understanding of how to collaborate with adolescents to improve their sleep and highlight that continued development of sleep education programmes is timely.
Review of Postoperative Delirium in Geriatric Patients After Hip Fracture Treatment

Introduction Postoperative delirium (POD) is a serious complication occurring in 4–53.3% of geriatric patients undergoing surgeries for hip fracture. Incidence of hip fractures is projected to grow 11.9% from 258,000 in 2010 to 289,000 in 2030 based on 1990 to 2010 data. As prevalence of hip fractures is projected to increase, POD is also anticipated to increase. Signficance Postoperative delirium remains the most common complication of emergency hip fracture surgery leading to high morbidity and mortality rates despite significant research conducted regarding this topic. This study reviews literature from 1990 to 2021 regarding POD in geriatric hip fracture management. Results Potentially modifiable and non-modifiable risk factors for developing POD include, but are not limited to, male gender, older age, multiple comorbidities, specific comorbidities (dementia, cognitive impairment, diabetes, vision impairment, and abnormal blood pressure), low BMI, preoperative malnutrition, low albumin, low hematocrit, blunted preoperative cytokines, emergency surgery, time to admission and surgery, preoperative medical treatment, polypharmacy, delirium-inducing medications, fever, anesthesia time, and sedation depth and type. Although the pathophysiology remains unclear, the leading theories suggest neurotransmitter imbalance, inflammation, and electrolyte or metabolic derangements as the underlying cause of POD. POD is associated with increased length of hospital stay, cost, morbidity, and mortality. Prevention and early recognition are key factors in managing POD. Methods to reduce POD include utilizing interdisciplinary teams, educational programs for healthcare professionals, reducing narcotic use, avoiding delirium-inducing medications, and multimodal pain control. Conclusion While POD is a known complication after hip fracture surgery, further exploration in prevention is needed. Early identification of risk factors is imperative to prevent POD in geriatric patients. Early prevention will enhance delivery of health care both pre- and post-operatively leading to the best possible surgical outcome and better quality of life after hip fracture treatment.
Chaotic Harris hawks optimization algorithm

Harris hawks optimization (HHO) is a population-based metaheuristic algorithm, inspired by the hunting strategy and cooperative behavior of Harris hawks. In this study, HHO is hybridized with 10 different chaotic maps to adjust its critical parameters. Hybridization is performed using four different methods. First, 15 test functions with unimodal and multimodal features are used for the analysis to determine the most successful chaotic map and the hybridization method. The results obtained reveal that chaotic maps increase the performance of HHO and show that the piecewise map method is the most effective one. Moreover, the proposed chaotic HHO is compared to four metaheuristic algorithms in the literature using the CEC2019 set. Next, the proposed chaotic HHO is applied to three mechanical design problems, including pressure vessel, tension/compression spring, and three-bar truss system as benchmarks. The performances and results are compared with other popular algorithms in the literature. They show that the proposed chaotic HHO algorithm can compete with HHO and other algorithms on solving the given engineering problems very successfully.
Ranking the DC Erosion Resistance of Silicone Rubber Composites with the Dry-Arc Resistance Test

This paper investigates the use of the dry-arc resistance test for ranking the DC erosion resistance of silicone rubber composites. The study utilizes the test as a controllable testing method for accelerating the erosion of silicone rubber surfaces by creating heat ablation with a stable scintillation. Alumina trihydrate is filled in silicone rubber at different levels and tested using the dry-arc resistance test and outcomes are correlated with the outcomes of the +DC inclined plane tracking-erosion test. Comparatively ranking the erosion depth and eroded volume outcomes for both tests preliminarily indicates a direct correlation in the ranking order observed for the composites under both tests. Outcomes of thermogravimetric and differential thermal analyses suggest the ranking is correlated with the amount of depolymerized silicone rubber leaving the composite in the gaseous phase. Ranking the thermal analyses outcomes on the basis of the depolymerized silicone rubber content correlates with the DC erosion resistance outcomes under the dry-arc resistance test and the inclined plane test. The outcomes collectively signify the validity of using the dry-arc resistance test for ranking the DC erosion resistance of silicone rubber composites.
2V-Gait: Gait Recognition using 3D LiDAR Robust to Changes in Walking Direction and Measurement Distance

Gait recognition, which is a biometric identifier for individual walking patterns, is utilized in many applications, such as criminal investigation and identification systems, because it can be applied at a long distance and requires no explicit cooperation of the subjects. In general, cameras are used for gait recognition, and several methods in previous studies have used depth information captured by RGB-D cameras. However, RGB-D cameras are limited in terms of their measurement distance and are difficult to access outdoors. In recent years, real-time multi-layer 3D LiDAR, which can obtain 3D range images of a target at ranges of over 100 m, has attracted significant attention for use in autonomous mobile robots, serving as eyes for obstacles detection and navigation. Compared with cameras, such 3D LiDAR has rarely been used for biometrics owing to its low spatial resolution. However, considering the unique characteristics of 3D LiDAR, such as the robustness of the illumination conditions, long measurement distances, and wide-angle scanning, the approach has the potential to be applied outdoors as a biometric identifier. The present paper describes a gait recognition system, called 2V-Gait, which is robust to variations in the walking direction of a subject and the distance measured from the 3D LiDAR. To improve the performance of gait recognition, we leverage the unique characteristics of 3D LiDAR, which are not included in regular cameras. Extensive experiments on our dataset show the effectiveness of the proposed approach.
Low-cost Multispectral Scene Analysis with Modality Distillation

Despite its robust performance under various illumination conditions, multispectral scene analysis has not been widely deployed due to two strong practical limitations: 1) thermal cameras, especially high-resolution ones are much more expensive than conventional visible cameras; 2) the most commonly adopted multispectral architectures, two-stream neural networks, nearly double the inference time of a regular mono-spectral model which makes them impractical in embedded environments. In this work, we aim to tackle these two limitations by proposing a novel knowledge distillation framework named Modality Distillation (MD). The proposed framework distils the knowledge from a high thermal resolution two-stream network with feature-level fusion to a low thermal resolution one-stream network with image-level fusion. We show on different multispectral scene analysis benchmarks that our method can effectively allow the use of low-resolution thermal sensors with more compact one-stream networks.
POCA: First Power-on Chip Authentication in Untrusted Foundry and Assembly

The increased complexity, extensive verification requirement, shortened time-to-market, and increased manufacturing and test costs have made fabless design houses adopt the horizontal business model where system-on-chips (SoCs) are shipped to outsourced semiconductor assembly and test facilities. However, such a model renders offshore facilities complete control over the manufacturing and test of integrated circuits (ICs), potentially enabling them to perform attacks like IC overproduction, intellectual property (IP) piracy, shipping defective chips into the supply chain, and stealing security assets (e.g., locking keys). In this paper, we propose a novel protocol called POCA, enabling the first power-on chip authentication during wafer sort to securely provision design assets inside the chip. Using POCA, the design house can authenticate the chips on the untrusted manufacturing/test floor and generate a shared secret key with the chip. This key is then utilized to encrypt the secret assets and securely provision them inside the chip after decryption. To the best of our knowledge, POCA is the first protocol that performs authentication at an untrusted foundry and ensures secure communication with the chip during the test. POCA has been implemented for ASIC and FPGA environments and is proven resistant to all possible attacks known to us as of today.
Effects of Insecticide, Weed-Free Period, and Row Spacing on Soybean (Glycine max) and Sicklepod (Cassia obtusifolia) Growth

Results from identical experiments conducted at Headland, AL, and Plains, GA, from 1980 through 1982 show insecticide treatment had little effect on soybean [Glycine max (L.) Merr. ‘Coker 237′] growth and morphology. Maximum insecticide applications increased soybean seed weight in two of five trials. Soybeans maintained free of sicklepod (Cassia obtusifolia L. ♯3 CASOB) for 4 weeks after emergence produced yields equal to those receiving season-long control in all trials, and 2-week control was equal to season-long maintenance in three trials. Length of weed interference-free maintenance did not affect soybean height. The number of pods per plant and seed weight were decreased when there was no control. Sicklepod shoot fresh weight and numbers decreased as the weed-free period increased from 0 weeks through the season. Row spacing had no effect on soybean height or seed size; however, the number of pods per plant was higher in 80- than in 40-cm rows. Row spacing influenced yield in only one trial where 20-cm rows outyielded 40-cm rows. A significant interaction occurred between the weed-free period and row spacing in two trials. Soybeans in 20-cm rows outyielded those in 40- and 80-cm rows when sicklepod was not controlled (i.e., 0 weeks interference-free maintenance).
An Efficient Approach for Evaluation of Multilayered Media Green's Functions

In this study, a novel approach is presented for efficient evaluation of Sommerfeld integrals arising in spatial-domain Green's functions in planar multilayered media. This approach allows us to tackle the difficulties encountered during the integration of the Sommerfeld integrals, which exhibit highly oscillatory and slowly decaying nature occurring especially at very high frequencies, e.g., at millimeter waves, that are finding increasing use in applications such as 5G and beyond. The oscillatory behavior of the integrand is modeled through an efficient interpolation and extrapolation scheme with a few samples needed to represent the integrand. Since the integrand is represented with a few exponentials, analytical integration can be used to speed up the process. The proposed approach is tested on different Green's functions and a good agreement is obtained.
Simultaneous underwater acoustic localization and communication: an experimental study

Currently in the field of autonomous underwater vehicles localization, it is difficult to do without a Doppler Velocity Log (DVL). Combined with distance measurements or not, this fairly expensive sensor is a must-have. In this paper we introduce our method by combining underwater acoustic communication and localization through Doppler shift estimation needed in the vehicle transmission modem for communication. This cost-effective technique provides an information on transmitter/receiver relative speed. We consider a fixed anchor with known position transmitting regularly to a receiver in a water pool of $3\text{m}^{2}$. Using an Extended Kalman filter, we compare standalone range measurements estimation with speed-only measurements and speed with range combined in the estimation filter. Experimental results demonstrate a consequent gain using speed computation associated with range measurement.
Speeding Dumbo: Pushing Asynchronous BFT Closer to Practice

—Asynchronous BFT consensus can implement ro- bust mission-critical decentralized services network without rely-ing on any form of timing assumption. Starting from the work of HoneyBadgerBFT (CCS 2016), several studies tried to push asynchronous BFT towards practice. In a recent work of Dumbo (CCS 2020), they redesigned the protocol backbone and used one multi-valued validated Byzantine agreement (MVBA) to replace n concurrent asynchronous binary agreement (ABA) protocols and dramatically improved the performance. Despite those efforts, asynchronous BFT protocols remain to be slow, and in particular, the latency is still quite large. There are two reasons contributing to the inferior performance: (1) the reliable broadcast (RBC) protocols still incur substantial costs; (2) the MVBA protocols are quite complicated and heavy, and all existing constructions need dozens of rounds and take the majority of the overall latency. We ﬁrst present a new construction of asynchronous BFT that replaces RBC instance with a cheaper broadcast component. It not only reduces the O ( n 3 ) message complexity incurred by n RBCs to O ( n 2 ) , but also saves up to 67% communications (in the presence of a fair network scheduler). Moreover, our technical core is a new MVBA protocol, Speeding MVBA, which is concretely more efﬁcient than all existing MVBAs. It requires only 6 rounds in the best case and expected 12 rounds in the worst case (by contrast, several dozens of rounds in the MVBA from Cachin et al. [12] and the recent Dumbo-MVBA [33], and around 20 rounds in the MVBA from Abraham et al. [4]). Our new technique of the construction might be of independent interests. We implemented Speeding Dumbo and did extensive tests among up to 150 EC2 t2.medium instances evenly allocated in 15 AWS regions across the globe. The experimental results show that Speeding Dumbo reduces the latency to about a half of Dumbo’s, and also doubles the throughput of Dumbo, through all system scales from 4 nodes to 150 nodes. We also did tests to benchmark individual components such as the broadcasts and the MVBA protocols, which may be of interests for future improvements.
Control Scheme for Negative-Sequence Voltage Compensation and Current Sharing in Inverter-Based Grid-Connected Microgrids

This article presents a control scheme that simultane-ously solves the problems of negative-sequence voltage compensation and negative-sequence current sharing in grid-connected microgrids using grid-feeding inverters. State-of-the-art schemes have previously solved these problems with low-performance control solutions or, alternatively, with high-performance solutions but paying the cost of high control-data traffic in the communication network. The proposed control scheme improves the performance of previous schemes for grid-feeding inverters with the following characteristics: 1) negative-sequence voltage compensation at any point of the microgrid, 2) accurate negative-sequence current sharing, and 3) low control-data traffic. In terms of implementation, two key points of the proposed control scheme are: the voltage compensation is based on a band-pass filter with complex coefficients and the current sharing is reached only with local current measurements. In the theoretical analysis, the system model is based on transfer functions with complex coefficients. This fact facilitates the control design due to 1) the system model is linear in this complex domain and 2) the multiple-input single-output model can be represented as a single-input single-output model for voltage compensation. The characteristics of the proposed control are validated by means of experimental results measured in a laboratory microgrid.
A Compact Broadband Circularly Polarized Spiral Antenna for Conformal Applications

This paper proposes a novel compact conformal broadband spiral antenna on a truncated cone. The radiating body of the antenna is composed of two-arm spiral metal strips, and the two arms with 180° differential excitation to generate unidirectional radiation and left-hand circular polarization in the axial direction of the spiral. Exclusive power divider and phase shifter are designed to form the feeding network. The presented antenna has the impedance bandwidth of 49.2 % (2.3-3.8 GHz) of ! S11! <-10 dB and the 3-dB axial ratio (AR) bandwidth of 57.1% (2.0-3.6 GHz). The miniaturized, compact and broadband characteristics of this designed antenna make it advantageous for drones and portable equipments.
Registration of Human Point Set using Automatic Key Point Detection and Region-aware Features

Non-rigid point set registration is challenging when point sets have large deformations and different numbers of points. Examples of such point sets include human point sets representing complex human poses captured by different types of depth cameras. In this work, we present a probabilistic, non-rigid registration method to deal with these issues. Two regularization terms are used: key point correspondences and local neighborhood preservation. Our method detects key points in the point sets based on geodesic distance. Correspondences are established using a new cluster-based, region-aware feature descriptor. This feature descriptor encodes the association of a cluster to the left-right (symmetry) or upper-lower regions of the point sets. We use the Stochastic Neighbor Embedding (SNE) constraint to preserve the local neighborhood of the point set. Experimental results on challenging 3D human poses demonstrate that our method outperforms the state-of-the-art methods. Our method achieved highly competitive performance with a slight increase of error by 3.9% in comparison with the method using manually specified key point correspondences.
Forgery Detection by Internal Positional Learning of Demosaicing Traces

We propose 4Point (Forensics with Positional Internal Training), an unsupervised neural network trained to assess the consistency of the image colour mosaic to find forgeries. Positional learning trains the model to learn the modulo-2 position of pixels, leveraging the translation-invariance of CNN to replicate the underlying mosaic and its potential inconsistencies. Internal learning on a single potentially forged image improves adaption and robustness to varied post-processing and counter-forensics measures. This solution beats existing mosaic detection methods, is more robust to various post-processing and counter-forensic artefacts such as JPEG compression, and can exploit traces to which state-of-the-art generic neural networks are blind. Check qbammey.github. io/4point for the code.