Miracle-dz/UniFAR-FTUs huggingface dataset:
Reaching Students and Parents Through Weather Science and Safety Workshops for Teachers

Weeklong weather science and safety workshops were conducted with 66 teachers of kindergarten through eighth grade (K–8) in three Georgia counties using the American Red Cross (ARC) Masters of Disaster (MoD) curriculum. The workshop goals included building teacher interests in the MoD, increasing teacher knowledge about the MoD curriculum, increasing and evaluating its use by teachers, disseminating information about it to other teachers, evaluating students’ weather science and safety knowledge, and evaluating students’ and families’ weather safety behavior. Workshop participation produced significant increases in teachers’ knowledge about the MoD curriculum, their general knowledge of weather science and safety, and self-efficacy in teaching their students about severe weather. In the year following the workshops, at least 32 teachers from the workshops delivered 178 MoD lessons to 2,465 students in K–8. In a sample of 291 students whose teachers delivered an MoD lesson on lightning, tornadoes, hurricanes, or floods, students obtained a mean of 60% correct responses on a comprehensive postlesson follow-up test. In a follow-up study with a subsample of 94 parents whose children received instruction from the MoD curriculum, 71% of the families indicated that they had developed safety plans and took additional steps (e.g., assembled safety kits, identified evacuation routes, and/or gathered supplies) to prepare for severe weather. This project is thought to be the first of its kind to demonstrate systematically the effectiveness of weather science and safety education for teachers, their students, and the students’ parents.
Robot-assisted screw fixation in a cadaver utilizing magnetic resonance imaging–based synthetic computed tomography: toward radiation-free spine surgery. Illustrative case

BACKGROUND Synthetic computed tomography (sCT) can be created from magnetic resonance imaging (MRI) utilizing newer software. sCT is yet to be explored as a possible alternative to routine CT (rCT). In this study, rCT scans and MRI-derived sCT scans were obtained on a cadaver. Morphometric analysis was performed comparing the 2 scans. The ExcelsiusGPS robot was used to place lumbosacral screws with both rCT and sCT images. OBSERVATIONS In total, 14 screws were placed. All screws were grade A on the Gertzbein-Robbins scale. The mean surface distance difference between rCT and sCT on a reconstructed software model was –0.02 ± 0.05 mm, the mean absolute surface distance was 0.24 ± 0.05 mm, and the mean absolute error of radiodensity was 92.88 ± 10.53 HU. The overall mean tip distance for the sCT versus rCT was 1.74 ± 1.1 versus 2.36 ± 1.6 mm (p = 0.24); mean tail distance for the sCT versus rCT was 1.93 ± 0.88 versus 2.81 ± 1.03 mm (p = 0.07); and mean angular deviation for the sCT versus rCT was 3.2° ± 2.05° versus 4.04°± 2.71° (p = 0.53). LESSONS MRI-based sCT yielded results comparable to those of rCT in both morphometric analysis and robot-assisted lumbosacral screw placement in a cadaver study.
Alternative Constructions of Asymmetric Primitives from Obfuscation: Hierarchical IBE, Predicate Encryption, and More

We revisit constructions of asymmetric primitives from obfuscation and give simpler alternatives. We consider public-key encryption, (hierarchical) identity-based encryption ((H)IBE), and predicate encryption. Obfuscation has already been shown to imply PKE by Sahai and Waters (STOC’14) and full-ﬂedged functional encryption by Garg et al. (FOCS’13). We simplify all these constructions and reduce the necessary assumptions on the class of circuits that the obfuscator needs to support. Our PKE scheme relies on just a PRG and does not need any puncturing. Our IBE and bounded HIBE schemes convert natural key-delegation mechanisms from (recursive) applications of puncturable PRFs to IBE and HIBE schemes. Our most technical contribution is an unbounded HIBE, which uses (public-coin) diﬀering-inputs obfuscation for circuits and whose proof relies on a recent pebbling-based hybrid argument by Fuchsbauer et al. (ASIACRYPT’14). All our constructions are anonymous, support arbitrary inputs, and have compact keys and ciphertexts.
Bias and sources of error in discrete choice models: a critical reflection

Discrete choice models have attracted a lot of attention since decades as an alternative to traditional aggregate transport demand models. Since discrete choice models assume that the total utility of an alternative is not exactly known to analysists, researchers have commonly assumed that the utility consists of two components: deterministic utility and error term. The error term is assumed to be composed of different sources. This paper reviews studies on the effect of the different sources of uncertainty (Manski, 1973) such as measurement error, omitted relevant variables, and taste variation in discrete choice models. All this research is based on different assumptions about the source of uncertainty. In this study, we will compare the assumptions and discuss future research directions. In addition, we will discuss the possible effects of the different sources of uncertainty in a new type of discrete choice model: the random regret model.
Hadron Interactions: Graduate Student Series in Physics

P D B Collins and A D Martin 1984 Bristol: Adam Hilger x + 169 pp price £9.95 (IOP members' price £7.96) ISBN 0 85274 768 3 Collins and Martin give a good account of the present status of the interactions involved in elementary particle physics, which makes a very suitable introduction to the subject for graduate students or others. At the same time, it will repay study by more established practitioners.
Designing disturbance observer for non-linear systems – a Hirschorn inverse approach

Disturbance observers (DOBs) are increasingly being suggested as a necessary component in active anti-disturbance control. Although the structure and design pragmatics of DOBs for linear systems are well known, very few publications deal with DOB for non-linear systems. A new method for designing DOBs for non-linear systems has been proposed. Instead of the usual observer gain based approach, the proposed approach employs Lie derivative and Hirschorn inverse. The algorithm for the proposed DOB, its applicability, structure, along with its block diagram have been presented and discussed. Performance of the proposed DOB has been evaluated using highly non-linear chemical processes. Additionally, the performance is compared with that for a well-known DOB to demonstrate the superiority of the proposed DOB.
Voice pitch is negatively associated with sociosexual behavior in males but not in females

Acoustic cues play a major role in social interactions in many animal species. In addition to the semantic contents of human speech, voice attributes – e.g., voice pitch, formant position, formant dispersion, etc. – have been proposed to provide critical information for the assessment of potential rivals and mates. However, prior studies exploring the association of acoustic attributes with reproductive success, or some of its proxies, have produced mixed results. Here, we investigate whether the mean fundamental frequency (F0), formant position (Pf), and formant dispersion (Df) – dimorphic attributes of the human voice – are related to sociosexuality, as measured by the Revised Sociosexual Orientation Inventory (SOI-R) – a trait also known to exhibit sex differences – in a sample of native Spanish-speaking students (101 males, 147 females). Analyses showed a significant negative correlation between F0 and sociosexual behavior, and between Pf and sociosexual desire in males but not in females. These correlations remained significant after correcting for false discovery rate (FDR) and controlling for age, a potential confounding variable. Our results are consistent with a role of F0 and Pf serving as cues in the mating domain in males but not in females. Alternatively, the association of voice attributes and sociosexual orientation might stem from the parallel effect of male sex hormones both on the male brain and the anatomical structures involved in voice production.
Impacts of implementing a forensic treatment mall: A program evaluation

Psychiatric in-patients need programming and clinical interventions to support recovery and gradual re-integration into the community. Treatment malls are designed to meet these needs by offering psychosocial, person-centred rehabilitation groups in a centralized setting. Evidence suggests this treatment model increases patient engagement, broadens social networks, and improves functioning. Given this, our hospital implemented a treatment mall in our forensic services department in 2018. Because this was a new initiative at our hospital and the lack of outcome data on treatment malls in Canada, we conducted a program evaluation to explore the effects of the treatment mall and identify possible areas of improvement. Guided by a logic model, this evaluation used a retrospective chart review. Variables of interest included patient engagement, psychotropic pro re nata (PRN) administration, recovery scores, time spent off unit, elopement, use of restraints and seclusion, and patient activity levels. We assessed whether these changed post-implementation of the treatment mall. The results provide preliminary evidence of the positive effects of the treatment mall. Patient engagement and time spent off unit increased. Maintenance of changes and long-term outcomes remain to be seen; however, this evalua - tion provides support for the continued use and investigation of the treatment mall for our forensic services department.
Chilling stress drives organ-specific transcriptional cascades and dampens diurnal oscillation in tomato

Abstract Improving chilling tolerance in cold-sensitive crops, e.g. tomato, requires knowledge of the early molecular response to low temperature in these under-studied species. To elucidate early responding processes and regulators, we captured the transcriptional response at 30 minutes and 3 hours in the shoots and at 3 hours in the roots of tomato post-chilling from 24°C to 4°C. We used a pre-treatment control and a concurrent ambient temperature control to reveal that majority of the differential expression between cold and ambient conditions is due to severely compressed oscillation of a large set of diurnally regulated genes in both the shoots and roots. This compression happens within 30 minutes of chilling, lasts for the duration of cold treatment, and is relieved within 3 hours of return to ambient temperatures. Our study also shows that the canonical ICE1/CAMTA-to-CBF cold response pathway is active in the shoots, but not in the roots. Chilling stress induces synthesis of known cryoprotectants (trehalose and polyamines), in a CBF-independent manner, and induction of multiple genes encoding proteins of photosystems I and II. This study provides nuanced insights into the organ-specific response in a chilling sensitive plant, as well as the genes influenced by an interaction of chilling response and the circadian clock.
Poisson–exponential distribution: different methods of estimation

ABSTRACT In this study, we present different estimation procedures for the parameters of the Poisson–exponential distribution, such as the maximum likelihood, method of moments, modified moments, ordinary and weighted least-squares, percentile, maximum product of spacings, Cramer–von Mises and the Anderson–Darling maximum goodness-of-fit estimators and compare them using extensive numerical simulations. We showed that the Anderson–Darling estimator is the most efficient for estimating the parameters of the proposed distribution. Our proposed methodology was also illustrated in three real data sets related to the minimum, average and the maximum flows during October at São Carlos River in Brazil demonstrating that the PE distribution is a simple alternative to be used in hydrological applications.
PRICING VULNERABLE EUROPEAN OPTIONS WITH STOCHASTIC CORRELATION

In this paper, we present a new pricing model for vulnerable options, with time-varying variances for each asset described by Generalized Autoregressive Conditional Heteroscedasticity processes and correlated with the return of the asset. By connecting the underlying asset and the counterparty's assets through the market factor channel, the proposed model also captures stochastic correlation between the underlying asset return and the return of the counterparty's assets. The correlation depends on the levels of the variances of both assets and the market index as well. In the proposed framework, the closed-form solution for vulnerable options is derived and numerical results are presented to investigate the impact of counterparty default risk.
NFLUX Satellite-Based Surface Radiative Heat Fluxes. Part I: Swath-Level Products

AbstractThe Naval Research Laboratory (NRL) ocean surface flux (NFLUX) system originally provided operational near-real-time satellite-based surface state parameter and turbulent heat flux fields over the global ocean. This study extends the NFLUX system to include the production of swath-level shortwave and longwave radiative heat fluxes at the ocean surface. A companion paper presents the production of the satellite-based global gridded radiative heat flux analysis fields. The swath-level radiative heat fluxes are produced using the Rapid Radiative Transfer Model for Global Circulation Models (RRTMG), with the primary inputs of satellite-derived atmospheric temperature and moisture profiles and cloud information retrieved from the Microwave Integrated Retrieval System (MIRS). This study uses MIRS data provided for six polar-orbiting satellite platforms. Additional inputs to the RRTMG include sea surface temperature, aerosol optical depths, atmospheric gas concentrations, ocean surface albedo, and ocean .
Do we react differently toward bionic devices vs. cochlear implants and wheelchairs? Possible links with personality traits

The present study explored the attitudes toward individuals with bionic eyes and limbs, cochlear implants, and people with disabilities that imply using a wheelchair. Our sample consisted of 474 Romanian adults aged 18–61 (M = 27.56, SD = 11.80). Participants were randomly divided into five groups. They all filled scales related to personality characteristics, i.e., agreeableness, neuroticism, openness to experience, comprehension/intellectual efficiency, and previous contact with disability. Then, each group was presented with a vignette describing a character (wheelchair/bionic eye/bionic leg/cochlear implant/control group). Finally, they answered questions about their emotions, cognitions, and behaviors related to that context. Overall, our results suggested that higher agreeability, extraversion, openness to experience, intellectual complexity, and lower neuroticism were generally associated with more positive attitudes toward disability. When examining the differences in participants' emotions, cognitions, and behaviors depending on the target's characteristics, our results generally suggested that the most negative reactions were toward the character with a bionic eye. We discuss these findings considering their importance for shaping positive attitudes related to disability, especially related to the future technological advances in bionic devices.
Multi-Stage Classification of Retinal OCT Using Multi-Scale Ensemble Deep Architecture

Accurate noninvasive diagnosis of retinal disorders is required for appropriate treatment or precision medicine. This work proposes a multi-stage classification network built on a multi-scale (pyramidal) feature ensemble architecture for retinal image classification using optical coherence tomography (OCT) images. First, a scale-adaptive neural network is developed to produce multi-scale inputs for feature extraction and ensemble learning. The larger input sizes yield more global information, while the smaller input sizes focus on local details. Then, a feature-rich pyramidal architecture is designed to extract multi-scale features as inputs using DenseNet as the backbone. The advantage of the hierarchical structure is that it allows the system to extract multi-scale, information-rich features for the accurate classification of retinal disorders. Evaluation on two public OCT datasets containing normal and abnormal retinas (e.g., diabetic macular edema (DME), choroidal neovascularization (CNV), age-related macular degeneration (AMD), and Drusen) and comparison against recent networks demonstrates the advantages of the proposed architecture’s ability to produce feature-rich classification with average accuracy of 97.78%, 96.83%, and 94.26% for the first (binary) stage, second (three-class) stage, and all-at-once (four-class) classification, respectively, using cross-validation experiments using the first dataset. In the second dataset, our system showed an overall accuracy, sensitivity, and specificity of 99.69%, 99.71%, and 99.87%, respectively. Overall, the tangible advantages of the proposed network for enhanced feature learning might be used in various medical image classification tasks where scale-invariant features are crucial for precise diagnosis.
Green Synthesis of Silver Nanoparticles and Detection of Antimicrobial Activities of Exotic Weeds Like Parthenium hysterophorus: A Review

: Since ancient times, silver has been employed as a non-toxic, secure inorganic antibacterial and antifungal agent. In a variety of biological applications, silver exhibits a very high potential, especially when it is in the form of nanoparticles. The advantages of green synthesis processes include their reasonable budget and the accessibility of raw materials. This eco-sustainable feature has now emerged as a crucial social concern and plays a crucial role in preventing environmental pollution by lowering or removing hazardous materials. The current review is straightforward, economical
Accurate extrinsic calibration of solid-state light detection and ranging and camera system by coarse-to-fine grid-aligning

Abstract. A high-precision extrinsic calibration is the underlying premise of the accurate perception of light detection and ranging (LiDAR) and camera systems commonly used in the autonomous driving industry. We propose a coarse-to-fine strategy to get rigid-body transformation between solid-state LiDAR with non-repetitive scanning and a RGB camera system using a chessboard as the calibration target. This method exploits the reflectance intensity characteristics of the LiDAR point cloud, which exhibit the distinct distribution in white and black blocks of chessboard. In the coarse calibration step, a reflectance intensity Gaussian mixture model was used to extract the unicolor block point cloud from the chessboard point cloud. Therefore, the initial estimate of the extrinsic parameter was obtained by aligning the corners in the point cloud and calculating the centroid of the unicolor block point cloud and corners in the image. In the refinement step, we extracted points on the border of each block as LiDAR features and designed an iterative optimization algorithm to align the intensity of LiDAR features with grayscale features in the image. This method utilizes the intensity information and compensates for corner errors in the point cloud due to reflectance intensity binarization. The results of the comparative experiment revealed that the proposed method outperformed existing methods in terms of accuracy. Experiments based on simulations and real-world conditions revealed that the proposed algorithm demonstrated a high accuracy, robustness, and consistency.
Heteroscedasticity-robust estimation of autocorrelation

ABSTRACT This paper proposes estimators of the first-order autocorrelation that are based on suitably transformed ratios of successive observations. The new estimators are given by simple functions of the observations. Numerical optimization is not required. Simulations show that they are highly robust against extreme values and clusters of high volatility and are therefore particularly useful for the estimation of serial correlation in return series. Besides, the results of the simulation study also call into question the common practice of correcting the small-sample bias of conventional estimators.
Physics of the Earth (2nd edn)

Frank D Stacey Chichester: J Wiley 1977 pp ix + 414 price £13.40 The author aims in this book to bring fundamental problems in solid-earth geophysics to the attention of graduate and advanced undergraduate students of physics. It is a subject that has, of course, undergone several phases of extraordinary and fascinating development in recent years.
Progressive censoring tests based on weighted empirical distributions

AGAM NATH SINHA. Progressive Censoring Tests Based on Weighted Empirical Distributions. (Under the direction of PRANAB KUMAR SEN.) In sequential time studies where time to an event is of interest, such as in clinical trials and life testing problems, progressive censoring schemes (PCS) when adopted, usually lead to a shorter duration of experimentation with a combined reduction in cost and in sparing of lives of experimental units. In this dissertation time-sequential testing procedures based on empirical distribution functions, for testing simple and multiple regressions in problems where units enter into the experiment at the same point of times are developed. Asymptotic distribution theory of the proposed test statistics under the null hypothesis is studied and power properties of the tests against contiguous alternatives are examined. The two-sample and multi-sample problems are also discussed as special cases of the simple and multiple regression models. Simulated critical values of the tests are also presented for application purposes. An extension is made to the case of staggering entry situation when the units in the experiment enter at different points of time. PCS testing procedures are developed for simple and multiple regression in such situations. Asymptotic distribution theory of the proposed test statistics under the null hypothesis and relevant power properties are also discussed for the staggering entry situation. The treatments for the two-sample and multi-sample problems are similarly derived as special cases, of the simple and multiple regression models. The critical values of the proposed tests under the staggering entry are obtainE~d through simulation. Lastly some applications of the vari.ous proposed tests are presented and a comparison of the powers and mean stopping times of the proposed tests with some of the rival tests are studied.
Detection of Mycobacterial DNA in Human Bone Marrow

Bone marrow is a cell-rich tissue of the reticuloendothelial system essential in the homeostasis and accurate functioning of hematopoiesis and of the immune system; moreover, it is also rich in lipids because it contains marrow adipocytes. This work aimed to evaluate the detection of mycobacterial DNA in human bone marrow as a tool to understand the complex pathology caused by the main pathogen Mycobacterium tuberculosis (Mtb). Formalin-fixed paraffin-embedded human bone marrow samples were studied using both conventional PCR + hybridization and in situ PCR to figure out the cell distribution of the targeted DNA. Samples were retrospectively collected from HIV+ patients with microbiologically proved mycobacterial infection and from subjects without evidence of infection. Mycobacterium avium (Mav) as well as Mtb DNA was detected in both settings, including tissues with and without granulomas. We detected DNA from both mycobacterial species, using in situ PCR, inside bone marrow macrophages. Other cell types, including adipocytes, showed positive signals only for Mtb DNA. This result suggested, for the first time, that marrow adipocytes could constitute an ideal reservoir for the persistence of Mtb, allowing the bacilli to establish long-lasting latent infection within a suitable lipid environment. This fact might differentiate pathogenic behavior of non-specialized pathogens such as Mav from that of specialized pathogens such as Mtb.