Miracle-dz/UniFAR-FTUs huggingface dataset:
LiDAR Odometry Methodologies for Autonomous Driving: A Survey

Vehicle odometry is an essential component of an automated driving system as it computes the vehicle's position and orientation. The odometry module has a higher demand and impact in urban areas where the global navigation satellite system (GNSS) signal is weak and noisy. Traditional visual odometry methods suffer from the diverse illumination status and get disparities during pose estimation, which results in significant errors as the error accumulates. Odometry using light detection and ranging (LiDAR) devices has attracted increasing research interest as LiDAR devices are robust to illumination variations. In this survey, we examine the existing LiDAR odometry methods and summarize the pipeline and delineate the several intermediate steps. Additionally, the existing LiDAR odometry methods are categorized by their correspondence type, and their advantages, disadvantages, and correlations are analyzed across-category and within-category in each step. Finally, we compare the accuracy and the running speed among these methodologies evaluated over the KITTI odometry dataset and outline promising future research directions.
A Review of Electronic Transport in Superconducting Sr2RuO4 Junctions

We review electronic transport in superconducting junctions with Sr2RuO4. Transport measurements provide evidence for chiral domain walls and, therefore, chiral superconductivity in superconducting Sr2RuO4, but so far, the symmetry of the underlying superconducting state remains inconclusive. Further studies involving density of states measurements and spin-polarised transport in local/non-local Sr2RuO4 junctions with magnetic materials could lead to fundamental discoveries and a better understanding of the superconducting state.
Genetic control and allele variation among soybean maturity groups 000 through IX

Soybean [Glycinemax (L.) Merr. ] maturity determines the growing region of a given soybean variety and is a primary factor in yield and other agronomic traits. The objectives of this research were to identify the quantitative trait loci (QTL) associated with maturity groups (MGs) and determine the genetic control of soybean maturity in each MG. Using data from 16,879 soybean accessions, genome‐wide association (GWA) analyses were conducted for each paired MG and across MGs 000 through IX. Genome‐wide association analyses were also performed using 184 genotypes (MGs V–IX) with days to flowering (DTF) and maturity (DTM) collected in the field. A total of 58 QTL were identified to be significantly associated with MGs in individual GWAs, which included 12 reported maturity loci and two stem termination genes. Genome‐wide associations across MGs 000–IX detected a total of 103 QTL and confirmed 54 QTL identified in the individual GWAs. Of significant loci identified, qMG‐5.2 had effects on the highest number (9) of MGs, followed by E2, E3, Dt2, qMG‐15.5, E1, qMG‐13.1, qMG‐7.1, and qMG‐16.1, which affected five to seven MGs. A high number of genetic loci (8–25) that affected MGs 0–V were observed. Stem termination genes Dt1 and Dt2 mainly had significant allele variation in MGs II–V. Genome‐wide associations for DTF, DTM, and reproductive period (RP) in the diversity panel confirmed 15 QTL, of which seven were observed in MGs V–IX. The results generated can help soybean breeders manipulate the maturity loci for genetic improvement of soybean yield.
Dysfunction of oligodendrocyte inwardly rectifying potassium channel in a rat model of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease caused by the death of motor neurons in the spinal cord and the brain. Although this disease is characterized by motoneuron degeneration, non‐neuronal cells such as oligodendrocytes play an important role in the disease onset and progression. The aim of our study was to examine functional properties of oligodendrocytes in the SOD1G93A rat model of ALS with a particular focus on the inwardly rectifying potassium channel Kir4.1 that is abundantly expressed in these glial cells and plays a role in the regulation of extracellular K+. First, we demonstrate that the expression of Kir4.1 is diminished in the spinal cord oligodendrocytes of the SOD1G93A rat. Moreover, our data show an elevated number of dysmorphic oligodendrocytes in the ALS spinal cord that is indicative of a degenerative phenotype. In order to assess physiological properties of oligodendrocytes, we prepared cell cultures from the rat spinal cord. Oligodendrocytes isolated from the SOD1G93A spinal cord display similar ramification of the processes as the control but express a lower level of Kir4.1. We further demonstrate an impairment of oligodendrocyte functional properties in ALS. Remarkably, whole‐cell patch‐clamp recordings revealed compromised membrane biophysical properties and diminished inward currents in the SOD1G93A oligodendrocytes. In addition, the Ba2+‐sensitive Kir currents were decreased in ALS oligodendrocytes. Altogether, our findings provide the evidence of impaired Kir4.1 expression and function in oligodendrocytes of the SOD1G93A spinal cord, suggesting oligodendrocyte Kir4.1 channel as a potential contributor to the ALS pathophysiology.
Micronuclei in Kif18a mutant mice form stable micronuclear envelopes and do not promote tumorigenesis

Kif18a mutant mice produce micronuclei following segregation of unaligned chromosomes but do not spontaneously form tumors. KIF18A KO cells form stable micronuclear envelopes around lagging chromosomes located near the spindle pole and outside the midzone. These data suggest stable micronuclei may not actively promote tumorigenesis.
Risk of Severe Acute Localized Reactions for Different Intraarticular Hyaluronic Acid Knee Injections in a Real-World Setting

Objective: Case reports of severe acute localized reactions (SALR) following intraarticular (IA) hyaluronic acid (HA) injections for knee osteoarthritis (OA) have been described. We compared surrogate SALR measures between patients using hylan G-F 20 and specific non-hylan G-F 20 HA products. Design: Knee OA patients were identified from the Optum Clinformatics dataset (January 2006 to June 2016), stratified into hylan G-F 20 and non-hylan G-F 20 HA users, matched by single or multiple injection products. Occurrences of surrogate SALR measures including inflammation/infection, intraarticular corticosteroid (CS) injections, arthrocentesis/aspiration, arthrotomy/incision and drainage, and arthroscopy were evaluated within 3 days post-HA. Results: Based on 694,404 HA injections, inflammation/infection rate was rare within 3 days of HA (up to 0.03%), with no statistical differences between hylan G-F 20 and non-hylan G-F 20 groups (matched by single or multiple injection products). The risk of knee arthrotomy/incision and drainage, arthroscopy, or arthrocentesis for hylan G-F 20 (2 mL) 3 weekly injection patients was lower than Hyalgan/Supartz and Orthovisc patients, but greater than Euflexxa patients. Overall, we found that Hylan G-F 20 (2 mL) 3 weekly injection had lower SALR rates compared to Hyalgan/Supartz and Orthovisc. However, Hylan G-F 20 (2 mL) 3 weekly injection had slightly higher rates of SALR when compared to Euflexxa. Among the single injection products, Hylan G-F 20 (6 mL) single injection had lower rates of SALR than Monovisc and Gel-One. Conclusions: This study shows no clear correlation between avian-derived or cross-linked products and SALR and provides evidence against avian-derived products or crosslinking as a source for these reactions.
A Right Invariant Extended Kalman Filter for Object based SLAM

With the recent advance of deep learning based object recognition and estimation, it is possible to consider object level SLAM where the pose of each object is estimated in the SLAM process. In this paper, based on a novel Lie group structure, a right invariant extended Kalman filter (RI-EKF) for object based SLAM is proposed. The observability analysis shows that the proposed algorithm automatically maintains the correct unobservable subspace, while standard EKF (Std-EKF) based SLAM algorithm does not. This results in a better consistency for the proposed algorithm comparing to Std-EKF. Finally, simulations and real world experiments validate not only the consistency and accuracy of the proposed algorithm, but also the practicability of the proposed RI-EKF for object based SLAM problem. The MATLAB code of the algorithm is made publicly available.
Multi-User Scheduling in Hybrid Millimeter Wave Massive MIMO Systems

While mmWave bands provide a large bandwidth for mobile broadband services, they suffer from severe path loss and shadowing. Multiple-antenna techniques such as beamforming (BF) can be applied to compensate the signal attenuation. We consider a special case of hybrid BF called per-stream hybrid BF (PSHBF) which is easier to implement than the general hybrid BF because it circumvents the need for joint analog-digital beamformer optimization. Employing BF at the base station enables the transmission of multiple data streams to several users in the same resource block. In this paper, we provide an offline study of proportional fair multi-user scheduling in a mmWave system with PSHBF to understand the impact of various system parameters on the performance. We formulate multi-user scheduling as an optimization problem. To tackle the non-convexity, we provide a feasible solution and show through numerical examples that the performance of the provided solution is very close to an upperbound. Using this framework, we provide extensive numerical investigations revealing several engineering insights.
Balanced Binocular Inputs Support Superior Stereopsis

Purpose Our visual system compares the inputs received from the two eyes to estimate the relative depths of features in the retinal image. We investigated how an imbalance in the strength of the input received from the two eyes affects stereopsis. We also explored the level of agreement between different measurements of sensory eye imbalance. Methods We measured the sensory eye imbalance and stereoacuity of 30 normally sighted participants. We made our measurements using a modified amblyoscope. The sensory eye imbalance was assessed through three methods: the difference between monocular contrast thresholds, the difference in dichoptic masking weight, and the contribution of each eye to a fused binocular percept. We referred them as the “threshold imbalance,” “masking imbalance,” and “fusion imbalance,” respectively. The stereoacuity threshold was measured by having subjects discriminate which of four circles were displaced in depth. All of our tests were performed using stimuli of the same spatial frequency (2.5 cycles/degree). Results We found a relationship between stereoacuity and sensory eye imbalance. However, this was only the case for fusion imbalance measurement (ρ = 0.52; P = 0.003). Neither the threshold imbalance nor the masking imbalance was significantly correlated with stereoacuity. We also found the threshold imbalance was correlated with both the fusion and masking imbalances (r = 0.46, P = 0.011 and r = 0.49, P = 0.005, respectively). However, a nonsignificant correlation was found between the fusion and masking imbalances. Conclusions Our findings suggest that there exist multiple types of sensory eye dominance that can be assessed by different tasks. We find only imbalances in dominance that result in biases to fused percepts are correlated with stereoacuity.
Dependability-Aware Routing and Scheduling for Time-Sensitive Networking

Time-Sensitive Networking (TSN) extends IEEE 802.1 Ethernet for safety-critical and real-time applications in several areas, e.g., automotive, aerospace or industrial automation. However, many of these systems also have stringent security requirements, and security attacks may impair safety. Given a TSN-based distributed architecture, a set of applications with tasks and messages, as well as a set of security and redundancy requirements, we are interested to synthesize a system configuration such that the real-time, safety and security requirements are upheld. We use the Timed Efficient Stream Loss-Tolerant Authentication (TESLA) low-resource multicast authentication protocol to guarantee the security requirements, and redundant disjunct message routes to tolerate link failures. We consider that tasks are dispatched using a static cyclic schedule table and that the messages use the time-sensitive traffic class in TSN, which relies on schedule tables (called Gate Control Lists, GCLs) in the network switches. A configuration consists of the schedule tables for tasks as well as the disjoint routes and GCLs for messages. We propose a Constraint Programming-based formulation which can be used to find an optimal solution with respect to our cost function. Additionally, we propose a Simulated Annealing based metaheuristic, which can find good solution for large test cases. We evaluate both approaches on several test cases.
Compact sets and the closure of their convex hulls in CAT(0) spaces

We study the closure of the convex hull of a compact set in a complete CAT(0) space. First we give characterization results in terms of compact sets and the closure of their convex hulls for locally compact CAT(0) spaces that are either regular or satisfy the geodesic extension property. Later inspired by a geometric interpretation of Carathéodory’s Theorem we introduce the operation of threading for a given set. We show that threading exhibits certain monotonicity properties with respect to intersection and union of sets. Moreover threading preserves compactness. Next from the commutativity of threading with any isometry mapping we prove that in a flat complete CAT(0) space the closure of the convex hull of a compact set is compact. We apply our theory to the computability of the Fréchet mean of a finite set of points and show that it is constructible in at most a finite number of steps, whenever the underlying space is of finite type.
Mechanistic analysis and significance of sphingomyelinase‐mediated decreases in transepithelial CFTR currents in nHBEs

Loss of function of the cystic fibrosis transmembrane conductance regulator (CFTR) causes cystic fibrosis (CF). In the lungs, this manifests as immune cell infiltration and bacterial infections, leading to tissue destruction. Previous work has determined that acute bacterial sphingomyelinase (SMase) decreases CFTR function in bronchial epithelial cells from individuals without CF (nHBEs) and with CF (cfHBEs, homozygous ΔF508‐CFTR mutation). This study focuses on exploring the mechanisms underlying this effect. SMase increased the abundance of dihydroceramides, a result mimicked by blockade of ceramidase enzyme using ceranib‐1, which also decreased CFTR function. The SMase‐mediated inhibitory mechanism did not involve the reduction of cellular CFTR abundance or removal of CFTR from the apical surface, nor did it involve the activation of 5′ adenosine monophosphate‐activated protein kinase. In order to determine the pathological relevance of these sphingolipid imbalances, we evaluated the sphingolipid profiles of cfHBEs and cfHNEs (nasal) as compared to non‐CF controls. Sphingomyelins, ceramides, and dihydroceramides were largely increased in CF cells. Correction of ΔF508‐CFTR trafficking with VX445 + VX661 decreased some sphingomyelins and all ceramides, but exacerbated increases in dihydroceramides. Additional treatment with the CFTR potentiator VX770 did not affect these changes, suggesting rescue of misfolded CFTR was sufficient. We furthermore determined that cfHBEs express more acid‐SMase protein than nHBEs. Lastly, we determined that airway‐like neutrophils, which are increased in the CF lung, secrete acid‐SMase. Identifying the mechanism of SMase‐mediated inhibition of CFTR will be important, given the imbalance of sphingolipids in CF cells and the secretion of acid‐SMase from cell types relevant to CF.
Asking Questions Like Educational Experts: Automatically Generating Question-Answer Pairs on Real-World Examination Data

Generating high quality question-answer pairs is a hard but meaningful task. Although previous works have achieved great results on answer-aware question generation, it is difficult to apply them into practical application in the education field. This paper for the first time addresses the question-answer pair generation task on the real-world examination data, and proposes a new unified framework on RACE. To capture the important information of the input passage we first automatically generate (rather than extracting) keyphrases, thus this task is reduced to keyphrase-question-answer triplet joint generation. Accordingly, we propose a multi-agent communication model to generate and optimize the question and keyphrases iteratively, and then apply the generated question and keyphrases to guide the generation of answers. To establish a solid benchmark, we build our model on the strong generative pre-training model. Experimental results show that our model makes great breakthroughs in the question-answer pair generation task. Moreover, we make a comprehensive analysis on our model, suggesting new directions for this challenging task.
Discovery of potential HER2 inhibitors from Mangifera indica for the treatment of HER2-Positive breast cancer: an integrated computational approach

Abstract Human epidermal growth factor receptor 2 (HER2) is a member of epidermal growth factor receptors with tyrosine kinase functionality. The dimerization of HER2 leads to the autophosphorylation of tyrosine residues within its cytoplasmic domain, resulting in hyperactivation of several downstream signal transduction pathways that play an important role in tumorigenesis, cancer aggressiveness and cell proliferation. Amplification or overexpression of HER2 has been found in approximately 15–30% of breast cancers. Hence, HER2 serve as a therapeutic biomarker in breast cancer. Herein, we applied structural bioinformatics techniques via molecular docking, molecular dynamics simulations, Molecular mechanics/generalized Born surface area (MM/GBSA) calculations and pharmacokinetic models to identify putative HER2 inhibitors. Application of stringent molecular docking results in the identification of bioactive compounds from Mangifera indica as selective, potent inhibitors of HER2. However, only the top three compounds with the highest negative docking score (< −9kcal/mol) was considered in reference to neratinib (−8.601 kcal/mol) for computational analysis. The molecular dynamics simulations and post-simulation analysis of docked HER2-ligand complexes unveil the substantial stability for M. indica ligands over the 100 ns simulation period. Additionally, MM/GBSA binding free energy calculation supports the inhibitory potential for the docked ligands, which exclusively revealed the highest binding energy for selected M. indica ligands than the reference compound (neratinib). The pharmacokinetic model showed that M. indica ligands are promising therapeutic agents. Conclusively, bioactive compounds from M. indica may serve as lead molecules that could be developed into potent and effective HER2 inhibitors for breast cancer treatment. Communicated by Ramaswamy H. Sarma
Dispersionless transport in washboard potentials revisited

We reassess the ‘dispersionless transport regime’ of Brownian particles in tilted periodic potentials. We show that the particles exhibit normal diffusive motion right after transitioning into the running state dragged by the constant bias force. No special transient dynamics appears, contrary to conjectures in the previous studies. The observed flat segment in the dispersion evolution curve is solely due to the broad spatial distribution of particles formed in the early superdiffusion stage. We quantitatively describe the whole evolution of the distribution function during superdiffusion and the transition to the normal diffusion that follows, in the framework of the two-well potential in the velocity space model. We show that the superdiffusion exponent is α = 3. The duration of the ostensible ‘dispersionless regime’ is derived analytically. It is shown to diverge exponentially as the temperature decreases to zero.
D-REX: Dialogue Relation Extraction with Explanations

Existing research studies on cross-sentence relation extraction in long-form multi-party conversations aim to improve relation extraction without considering the explainability of such methods. This work addresses that gap by focusing on extracting explanations that indicate that a relation exists while using only partially labeled explanations. We propose our model-agnostic framework, D-REX, a policy-guided semi-supervised algorithm that optimizes for explanation quality and relation extraction simultaneously. We frame relation extraction as a re-ranking task and include relation- and entity-specific explanations as an intermediate step of the inference process. We find that human annotators are 4.2 times more likely to prefer D-REX’s explanations over a joint relation extraction and explanation model. Finally, our evaluations show that D-REX is simple yet effective and improves relation extraction performance of strong baseline models by 1.2-4.7%.
DeepPyram: Enabling Pyramid View and Deformable Pyramid Reception for Semantic Segmentation in Cataract Surgery Videos

Semantic segmentation in cataract surgery has a wide range of applications contributing to surgical outcome enhancement and clinical risk reduction. However, the varying issues in segmenting the different relevant instances make the designation of a unique network quite challenging. This paper proposes a semantic segmentation network termed as DeepPyram that can achieve superior performance in segmenting relevant objects in cataract surgery videos with varying issues. This superiority mainly originates from three modules: (i) Pyramid View Fusion, which provides a varying-angle global view of the surrounding region centering at each pixel position in the input convolutional feature map; (ii) Deformable Pyramid Reception, which enables a wide deformable receptive field that can adapt to geometric transformations in the object of interest; and (iii) Pyramid Loss that adaptively supervises multi-scale semantic feature maps. These modules can effectively boost semantic segmentation performance, especially in the case of transparency, deformability, scalability, and blunt edges in objects. The proposed approach is evaluated using four datasets of cataract surgery for objects with different contextual features and compared with thirteen state-of-the-art segmentation networks. The experimental results confirm that DeepPyram outperforms the rival approaches without imposing additional trainable parameters. Our comprehensive ablation study further proves the effectiveness of the proposed modules.