Miracle-dz/UniFAR-FTUs huggingface dataset:
A Robust Gaussian Process-Based LiDAR Ground Segmentation Algorithm for Autonomous Driving

Robust and precise vehicle detection is the prerequisite for decision-making and motion planning in autonomous driving. Vehicle detection algorithms follow three steps: ground segmentation, obstacle clustering and bounding box fitting. The ground segmentation result directly affects the input of the subsequent obstacle clustering algorithms. Aiming at the problems of over-segmentation and under-segmentation in traditional ground segmentation algorithms, a ground segmentation algorithm based on Gaussian process is proposed in this paper. To ensure accurate search of real ground candidate points as training data for Gaussian process, the proposed algorithm introduces the height and slope criteria, which is more reasonable than the use of fixed height threshold for searching. After that, a sparse covariance function is introduced as the kernel function for calculation in Gaussian process. This function is more suitable for ground segmentation situation the radial basis function (RBF). The proposed algorithm is tested on our autonomous driving experimental platform and the public autonomous driving dataset KITTI, compared with the most used RANSAC algorithm and ray ground filter algorithm. Experiment results show that the proposed algorithm can avoid obvious over-segmentation and under-segmentation. In addition, compared with the RBF, the introduction of the sparse covariance function also reduces the computation time by 37.26%.
The Link Between Familial Care, the Covid Pandemic and Gender Linked Fate

ABSTRACT In this research note, we assess whether White and Black women who left the labor force to take care of family during the COVID-19 pandemic display higher levels of gender linked fate. The COVID pandemic compounded existing inequality in domestic labor as many women were forced to leave the workforce when schools moved to remote learning and many daycares closed. The gendered impact of the pandemic may have disproportionately fostered a sense of a common bond among women who altered their employment because of the pandemic. We test this hypothesis using a survey administered on a non-probability representative sample of American adults. We find that White and Black women who altered their employment to take care of family displayed higher levels of gender linked fate than others. Our findings suggest that changes in the social context along with personal experiences are tied to women’s perceptions of a common fate.
Recent Increase in the Occurrence of Snow Droughts Followed by Extreme Heatwaves in a Warmer World

The compound of late winter snow droughts and early spring heatwaves (compound snow drought and heatwave (CSDHW)) could dramatically affect ecosystems and water availability, but has not been systematically investigated. Here we present a comprehensive assessment of CSDHW events and possible driving mechanisms. We find that 7% of the snow‐covered area experiences significant (p < 0.05) CSDHW events, and an average of 35% of snow droughts are followed by heatwaves during 1981–2020. The spatial extent of CSDHW is asymmetrically enlarging, with a significant increase in Eurasia and a relatively high fluctuation in North America. Specifically, the warm‐type CSDHW (i.e., snow drought with normal or above‐average precipitation followed by heatwave) occurs more frequently, with spatial coverage increasing faster than the dry‐type CSDHW (i.e., snow drought with below‐average precipitation followed by heatwave). In comparison, dry snow drought is more likely to be followed by heatwave due to intensified soil drought and atmospheric aridity.
Identification of Genetic Variations in the NAD-Related Pathways for Patients with Major Depressive Disorder: A Case-Control Study in Taiwan

Abstract Background and Objectives: Nicotinamide adenine dinucleotide (NAD) is an important coenzyme in various physiological processes, including sirtuins (SIRTs) and kynurenine pathway (KP). Previous studies have shown that lower NAD levels can be indicative of increased risks of cancer and psychiatric disorders. However, there has been no prior study exploring the link between NAD homeostasis and psychiatric disorders from a genetic perspective. Therefore, we aimed to investigate the association of genetic polymorphism in the pathways of NAD biosynthesis with major depressive disorder (MDD). Methods: A total of 317 patients were included in the case group and were compared with sex-matched control group of 1268 participants (1:4 ratio) from Taiwan Biobank (TWB). All subjects in the control group were over 65 years old, which is well past the average age of onset of MDD. Genomic DNA extracted from patients’ blood buffy coat was analyzed using the Affymetrix TWB array. Full-model tests were conducted for the analysis of single nucleotide polymorphism (SNPs) in all candidate genes. We focused on genes within the NAD-related candidate pathways, including 15 in KP, 12 in nicotinate metabolism, 7 in SIRTs, and 19 in aldehyde dehydrogenases (ALDHs). A total of 508 SNPs were analyzed in this study. After significant SNPs were determined, 5000 genome-wide max(T) permutations were performed in Plink. Finally, we built a predictive model with logistic regression and assessed the interactions of SNPs with the haplotype association tests. Results: We found three SNPs that were significantly associated with MDD in our NAD-related candidate pathways, one within the KP (rs12622574 in ACMSD) and two within the nicotinate metabolism (rs28532698 in BST1 and rs3733593 in CD38). The observed association with MDD was significant in the dominant model of inheritance with marital status, education level, and body mass index (BMI) adjusted as covariates. Lastly, in haplotype analysis, the three associated SNPs consisted of one haploblock in ACMSD, four haploblocks in BST1, and two haploblocks in CD38. Conclusions: This study provides the first evidence that genetic variations involved in NAD homeostasis in the KP and nicotinate metabolism may be associated with the occurrence of MDD.
Determination of Lamb Wave Modes on Lithium-Ion Batteries Using Piezoelectric Transducers

This work presents a method to determine the type of Lamb mode (antisymmetric or symmetric) that propagates through a lithium-ion pouch cell. To determine the type of mode and the group velocity at a specific frequency, two- and three-transducer setups were created. For these setups, it is important that all transducers have the same polarization direction. Two transducers are affixed to the center of the cell at a distance of several centimeters from each other so that the group velocity can be determined. Using cross-correlation, the group velocity of the emerging mode can be calculated. The measurement setup and the processing method was first validated with experiments on acrylic glass and aluminum plates. The measurements were supported with FEM simulations and a numerically calculated model. The output voltages of the receiving piezo-elements obtained in the FEM simulation are in agreement with the underlying theories. The phase shift, which results from the output voltage of the piezo-elements mounted one above the other on different sides of the plate, shows the type of mode. The results of the experimental determination of the Lamb mode that propagates through a lithium-ion pouch cell were validated with a numerically calculated multi-layer model and therefore validate this novel experimental approach.
A Functional Connectome of Parkinson's Disease Patients Prior to Deep Brain Stimulation: A Tool for Disease-Specific Connectivity Analyses

Citation: Loh A, Boutet A, Germann J, Al-Fatly B, Elias GJB, Neudorfer C, Krotz J, Wong EHY, Parmar R, Gramer R, Paff M, Horn A, Chen JJ, Azevedo P, Fasano A, Munhoz RP, Hodaie M, Kalia SK, Kucharczyk W and Lozano AM (2022) A Functional Connectome of Parkinson’s Disease Patients Prior to Deep Brain Stimulation: A Tool for Disease-Specific Connectivity Analyses. Front. Neurosci. 16:804125. doi: 10.3389/fnins.2022. 804125 A Functional Connectome of Parkinson’s Disease Patients Prior to Deep Brain Stimulation: A Tool for Disease-Specific Connectivity Analyses
Usefulness of the Measurement of Serum Paraoxonase-1 Arylesterase Activity in the Diagnoses of COVID-19

The development of inexpensive, fast, and reliable screening tests for COVID-19 is, as yet, an unmet need. The present study was aimed at evaluating the usefulness of serum arylesterase activity of paraoxonase-1 (PON1) measurement as a screening test in patients with different severity levels of COVID-19 infection. We included 615 COVID-19-positive patients who were classified as asymptomatic, mildly symptomatic, severely symptomatic, or fatally symptomatic. Results were compared with 50 healthy volunteers, 330 patients with cancer, and 343 with morbid obesity. Results showed PON1 activity greatly decreased in COVID-19 compared to healthy volunteers; a receiver operating characteristics plot showed a high diagnostic accuracy. The degree of COVID-19 severity did not influence PON1 levels. Our results indicated that PON1 determination was efficient for disease diagnosis, but not for prognosis. Furthermore, patients with obesity or cancer presented alterations similar to those of COVID-19 patients. As such, elevated levels of PON1 indicate the absence of COVID-19, but low levels may be present in various other chronic diseases. The assay is fast and inexpensive. We suggest that PON1 measurement could be used as an initial, high cut-off point screening method, while lower values should be confirmed with the more expensive nucleic acid amplification test.
Water Justice as Socioenvironmental Justice

ABSTRACT Humanity will face water scarcity as this century progresses. Water use grew twice as fast as the global human population last century, and an increasing number of regions around the world are facing, or will face, freshwater scarcity. Four billion people face water scarcity at least one month out of the year. Scarcity makes water valuable for privatizers and commodifiers as an investment vehicle; it emboldens the currency of commodification. I will argue for water justice as socioenvironmental justice. The injustices that can and do attach to water are not reducible to merely distributional wrongs or injustices, they are moral and political harms as markers of a failing democracy; water injustice, then, is a structural harm. I build on the literature of power dynamics from Iris Marion Young and David Schlosberg and argue that water injustice is structural and involves mis- and mal-recognition and participation; moreover, I introduce the argument that water justice is participatory, a method of development that walks in lockstep with reflexive and discursive democracy.
An EGFET Based Common Source Amplifier as a Low-Frequency Instrumentation Amplifier for Sensitivity Measurement on RuO2 Lactic Acid Biosensor

In this study, a low-frequency instrumentation amplifier (LFIA) integrated with an extended-gate field-effect transistor (EGFET) is presented to realize the simplicity common source amplifier (CSA) structure. The proposed EGFET CSA was developed by the 0.18-μm CMOS process technology of Taiwan Semiconductor Manufacturing Company (TSMC). The EGFET CSA has low frequency and noise immunity function, and it can effectively output the response signal, with good stability and effectively improve the sensitivity, not susceptible to environmental factors, easy to replace, and low cost. Moreover, the simple circuit design of the EGFET CSA was used to analyze the sensing characteristics and to improve the stability of the ruthenium dioxide (RuO2) lactic acid (LA) biosensor. Therefore, the EGFET CSA is suitable for LA detection. The simple process of the EGFET CSA was used to analyze the sensing characteristics and to improve the stability of the ruthenium dioxide (RuO2) lactic acid (LA) biosensor. An arrayed potentiometric LA biosensor based on the RuO2 thin film was proposed and manufactured in this study. The experimental results indicated that the EGFET CSA as a low-frequency instrumentation amplifier has achieved a good sensitivity (53.41mV/mM) and satisfactory linearity (0.997) on the RuO2 LA biosensor as compared with the V-T measurement system.
Modeling Motorcyclists’ Aggressive Driving Behavior Using Computational and Statistical Analysis of Real-Time Driving Data to Improve Road Safety and Reduce Accidents

Driving behavior is considered one of the most important factors in all road crashes, accounting for 40% of all fatal and serious accidents. Moreover, aggressive driving is the leading cause of traffic accidents that jeopardize human life and property. By evaluating data collected by various collection devices, it is possible to detect dangerous and aggressive driving, which is a huge step toward altering the situation. The utilization of driving data, which has arisen as a new tool for assessing the style of driving, has lately moved the concentration of aggressive recognition research. The goal of this study is to detect dangerous and aggressive driving profiles utilizing data gathered from motorcyclists and smartphone APPs that run on the Android operating system. A two-stage method is used: first, determine driver profile thresholds (rules), then differentiate between non-aggressive and aggressive driving and show the harmful conduct for producing the needed outcome. The data were collected from motorcycles using -Speedometer GPS-, an application based on the Android system, supplemented with spatiotemporal information. After the completion of data collection, preprocessing of the raw data was conducted to make them ready for use. The next steps were extracting the relevant features and developing the classification model, which consists of the transformation of patterns into features that are considered a compressed representation. Lastly, this study discovered a collection of key characteristics which might be used to categorize driving behavior as aggressive, normal, or dangerous. The results also revealed major safety issues related to driving behavior while riding a motorcycle, providing valuable insight into improving road safety and reducing accidents.
Increasing Inhomogeneity of the Global Oceans

The ocean is inhomogeneous in hydrographic properties with diverse water masses. Yet, how this inhomogeneity has evolved in a rapidly changing climate has not been investigated. Using multiple observational and reanalysis datasets, we show that the spatial standard deviation (SSD) of the global ocean has increased by 1.4 ± 0.1% in temperature and 1.5 ± 0.1% in salinity since 1960. A newly defined thermohaline inhomogeneity index, a holistic measure of both temperature and salinity changes, has increased by 2.4 ± 0.1%. Climate model simulations suggest that the observed ocean inhomogeneity increase is dominated by anthropogenic forcing and projected to accelerate by 200%–300% during 2015–2100. Geographically, the rapid upper‐ocean warming at mid‐to‐low latitudes dominates the temperature inhomogeneity increase, while the increasing salinity inhomogeneity is mainly due to the amplified salinity contrast between the subtropical and subpolar latitudes.
Beyond talk and text: Visuality and critical discursive psychology

ABSTRACT Given the centrality of the visual to modern day life, this article introduces a visually informed approach to critical discursive psychology that facilitates the study of visual materials. We argue that the visual is a site where the social world is actively built and maintained, similar to what has been reasoned more generally about language use, and that critical discursive psychology can offer a rigorous approach to examining visual materials that can productively deepen our understanding of psychological concepts. As such, we integrate a consideration of visuality into critical discursive psychology theory, including a conceptualization of visual discourse and visual interpretative repertoires, provide tools for close readings of visual materials and guidance regarding how to employ these tools, and outline the process of identifying visual interpretative repertoires. We further connect these concepts to our previous experience carrying out this approach to inform future inquiries.
Clinical validation of superior vena cava respiratory variation in predicting fluid responsiveness using transthoracic echocardiography technique: a pilot study

Goal-directed fluid management constitutes an inseparable part of the perioperative routine practice of anesthesiologists. The patient’s de-hydration or overhydration status frequently contributes to severe se-quelae secondary to cardiopulmonary dysfunction and impairs enhanced recovery after surgery in the long term. Therefore, stringent fluid management tailored to the individualized volume status in those patients is mandatory. The application of inferior vena cava (IVC) respiratory variation in predicting fluid responsiveness has been a standard practice for patients undergoing major surgery in the tertiary hospital. However, the role of IVC-derived variables in fluid responsiveness evaluation in mechanically ventilated patients remains undetermined [1]. In addition, the acquisition of IVC images at the subxiphoid area is unavailable in patients undergoing open surgery with an abdominal midline incision. However, the superior vena cava (SVC) variation during the respiratory phase has better diagnostic value for volume status assessment, with high sensitivity and specificity [2, 3]. The subjects in those studies, however, unex-ceptionally received transesophageal echocardiographic (TEE) examina-tion. Besides
Effect of Process Parameters on the Performance of Drop-On-Demand 3D Inkjet Printing: Geometrical-Based Modeling and Experimental Validation

As additive manufacturing has evolved, 3D inkjet printing (IJP) has become a promising alternative manufacturing method able to manufacture functional multi-material parts in a single process. However, issues with part quality in terms of dimensional errors and lack of precision still restrict its industrial and commercial applications. This study aims at improving the dimensional accuracy of 3D IJP parts by developing an optimization-oriented simulation tool of droplet behavior during the drop-on-demand 3D IJP process. The simulation approach takes into consideration the effect of droplet volume, droplet center-to-center distance, coverage percentage of jetted droplets, the contact angle of the ink on the solid substrate and coalescence performance of overlapping droplets, in addition to the number of printed layers. Following the development of the simulation tool using MATLAB, its feasibility was experimentally validated and the results showed a good agreement with a maximum deviation of 2.25% for horizontal features. In addition, the simulated horizontal features are compared with the results of “Inkraster” software, which also illustrates droplet behavior, however, only in 2D. For vertical features, a dial gauge indicator is used to measure the sample height, and the validation results show that the simulation tool can predicate the height of the sample with an average error of 10.89% for a large droplet diameter and 8.09% for a small diameter. The simulation results were found to be in a good agreement with the dimensions of the printed parts. The developed tool was then used to elucidate the effect of resolution of processed TIFF image and droplet diameter on the dimensional accuracy of 3D IJP parts.
Bifurcation and vibration of a surface-coated elastic block under flexure

The behaviour of a surface-coated rectangular, non-linearly elastic block subject to (plane-strain) flexure is investigated in this thesis. We consider a rectangular block of incompressible, isotropic elastic material coated with a thin elastic film on part of its boundary. Initially, the bulk material undergoes a non-homogeneous deformation and the equilibrium of the coated body is examined on the basis of the elastic surface coating theory derived by Steigmann and Ogden (1997a). Incremental displacements are then superimposed on the finitely deformed configuration in order to study possible bifurcation of the deformed block. Numerical bifurcation results pertaining to two particular strain-energy functions (for the bulk material) and a general energy function (for the coating material) are subsequently obtained. These results allow the influence of the surface coating on the bifurcation behaviour of the block to be determined and assessed with reference to corresponding results for an uncoated block. Next, use is made of the dynamic equivalent of the static surface coating theory, developed by Ogden and Steigmann (1999), to establish incremental equations of motion for the coated block. Corresponding incremental governing equations for an uncoated, pre-flexed block then emerge as a special case. The resulting frequency equations are solved numerically, again on specialization of the form of strain-energy function. The numerical vibration results then provide evidence of the effect of surface coating on the dynamic behaviour of the considered coated block relative to the uncoated case. Finally, we turn our attention to the (non-linear) shear responses of bonded elastic bodies. We examine the plane-strain problem of a rectangular compressible isotropic elastic block bonded to two rigid parallel plates. The deformation behaviour of the block is described by applying minimum energy and maximum complementary energy principles to obtain upper and lower bounds on the shear stress-strain relationship. Although maximum and minimum principles are not generally justifiable in non-linear elasticity we show that under certain conditions they are applicable and, for a particular form of strain-energy function, derive explicit energy bounds which we illustrate graphically.
Channel Characterization for RIS-Aided Terahertz Communications: A Stochastic Approach

In this letter, we propose new channel characterizations for <xref rid="deqn1" ref-type="disp-formula">(1)</xref> stochastic Terahertz (THz) communications and <xref rid="deqn2" ref-type="disp-formula">(2)</xref> reconfigurable intelligent surface (RIS)-aided THz systems. Considering a spherical network with stochastic distances between nodes, we derive the exact closed-form expressions for the probability density function (PDF) and the cumulative distribution function (CDF) of the signal-to-noise ratio (SNR) over the direct link. Using the method of moments, the cascaded channels can be precisely characterized by <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> distribution. We show that by using a massive number of reflecting elements, <inline-formula> <tex-math notation="LaTeX">${M}$ </tex-math></inline-formula>, (e.g., <inline-formula> <tex-math notation="LaTeX">${M}~\geq $ </tex-math></inline-formula> 4096) the cascaded link actually outperforms the direct THz link in terms of outage probability (OP).
V-Band Dual-Polarized Filtering Transmitarray Antenna Enabled by a Planar Filtering Illumination Source

This article introduces a transmitarray antenna presenting excellent filtering and dual-polarization properties. Conventional transmitarrays resort to multilayered frequency-selective surfaces (FSSs) for filtering responses. In contrast, we propose a planar dual-polarized filtering antenna as an illumination source to enable a filtering transmitarray. The V-band dual-polarized filtering antenna is excited by a substrate integrated waveguide (SIW) feeding structure. By a novel tri-section feed and a well-design radiating element, up to four radiation nulls are produced, leading to an excellent filtering response validated with experimental results. Subsequently, the antenna is employed to illuminate a phase-shifting surface (PSS), achieving outstanding filtering response, stable dual-polarization characteristics, low profile, and ease of integration. The proposed antenna and transmitarray demonstrate significant potential in V-band millimeter-wave (mmW) applications.