Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Gloves and Occupational Tasks on Handgrip Strength in Structural Firefighters

Adequate handgrip strength (HGS) is important to safely perform fireground tasks. However, there is limited research describing the deleterious impact of glove use and fatigue from occupational tasks on HGS. Therefore, the aims of this investigation were to quantify the impact of glove use and occupational tasks on HGS, to explore the relationship between HGS versus the glove and task-induced decrement in HGS, and to evaluate the relationship between HGS and decrement in HGS versus occupational performance. Fourteen (Male: n = 13) career structural firefighters (Age: 35.5 ± 7.2 yr) performed a maximal isometric HGS assessment with and without gloves before and immediately following completion of a simulated fireground test (SFGT). General linear model with written contrast was used to identify significant differences in HGS between conditions. Pearson Correlations were used to describe bivariate relationships between the decrements in HGS and occupational task times. Significance was set at p < 0.05. There were significant main effects indicating that gloves, performing occupational tasks, and their combined effects decreased HGS (p < 0.001 for all). There were strong inverse relationships between baseline (barehanded) HGS versus the decrement in HGS from donning gloves (r = −0.82, p < 0.001) and from performing occupational tasks with gloves (r = −0.61, p = 0.021). Baseline HGS and the decrement in HGS due to wearing gloves and performing occupational tasks were not correlated to the timed completion of occupational tasks (p ≥ 0.27). These findings suggest that the use of regulation fire gloves and work-induced fatigue reduces HGS and these decrements are related to HGS. Practitioners are encouraged to utilize training strategies to optimize HGS among structural firefighters.
Auralization of a Car Pass-By Using Impulse Responses Computed with a Wave-Based Method

Auralization of traffic noise can be of great value for city planners and in the communication to citizens. In inner city environments, auralization of traffic noise based on predictions might require a wave-based method for the low frequencies. In this paper, a method to auralize a car pass-by using binaural impulse responses (BIRs) computed with the wave-based pseudospectral time-domain method (PSTD) in two dimensions is presented. A dry synthesized car signal is convolved with the BIRs for different locations in the street, and cross-fade windows are used in order to create a smooth transition between the source positions. Auralizations were performed for the simplified scenarios where buildings are absent, and for an environment where a long flat wall is located behind the car, opposite from the receiver. A same-different listening test was carried out in order to investigate whether increasing the angular spacing between the discrete source positions affects the perception of the car pass-by auralizations. Signal detection theory (SDT) was used for the design and analysis of the listening test. Results showed that differences exist, although they are difficult to notice. On average, 52.3% of the subjects found it almost impossible to spot any difference between auralizations with larger angular spacing (up to 10°) compared to the reference auralization (2° angular spacing).
The roles of an expanding wind field and inertial 1 stability in tropical cyclone secondary eyewall 2 formation 3 4 5

This is a preliminary PDF of the author-produced manuscript that has been peer-reviewed and accepted for publication. Since it is being posted so soon after acceptance, it has not yet been copyedited, formatted, or processed by AMS Publications. This preliminary version of the manuscript may be downloaded, distributed, and cited, but please be aware that there will be visual differences and possibly some content differences between this version and the final published version.
'But you didn't think what you were doing was risky': The Role of Risk in Mediating the Identities and Practices of Rock Climbers

This thesis examines the multiple meanings attached to risk by a small group of climbers based in the North of England. The study is anchored, empirically in sustained observational fieldwork, and in-depth interviews with adult subjects (9 females aged 22-77, 14 males aged 20-70). In completing this thesis, I believe I have made an original contribution to knowledge in three areas. In re-imagining risk in climbing, I argue that climbers do not participate in climbing because of a desire to take risks, rather, they make every effort to assess, manage and control risks when climbing. In reconceptualising risk in climbing, I present a conceptual model derived from the interviewees? accounts of risk. This model situates risk in climbing with risk in everyday life. The basis of my third original contribution to knowledge lies in the relationship between risk and identity. The interviewees differentiated between safe and unsafe climbers through reference to embodied climbing practices. The way a climber in this study assessed and managed risk marked them as a safe climber or conversely an unsafe climber. Furthermore, the data revealed both a gendered and an age-related dimension to the relationship between risk and identity. The desire to retain the identity of a climber over time was so strong that older climbers reported modifying their practices to sustain their status as a member of the insider group. In addition, the female interviewees described how perceived family responsibilities mediated membership of the insider group, and their identity as a safe and qualified climber. The female climbers in this study described how such responsibilities led them, like older climbers, to draw back from the edge. These findings have implications beyond the sport of rock climbing and its participants. This research has the potential to inform and enhance our appreciation of risk in other lifestyle sports and moreover, whilst there is a tendency to distinguish between lifestyle and traditional sports, there may be some application of the account of risk presented here to an exploration of risk in traditional sports. The arguments presented in this study also contribute to an understanding or risk more generally. A key conclusion from this study is that risk is best understood where the meanings attached to it are derived from individuals? everyday lived experience and relatedly where risk is situated within the broadest context of their lives. Finally, the data reported here suggests that risk activities and risk-taking should be explored in relation to an individual? s perceived identity and crucially, the significance of risk for the construction of that identity.
Spectral CT Reconstruction—ASSIST: Aided by Self-Similarity in Image-Spectral Tensors

Spectral computed tomography (CT) reconstructs multienergy images from data in different energy bins. However, these reconstructed images can be contaminated by noise due to the limited numbers of photons in the corresponding energy bins. In this paper, we propose a spectral CT reconstruction method aided by self-similarity in image-spectral tensors, which utilizes the self-similarity of patches in both spatial and spectral domains. Patches with similar structures identified by a joint spatial and spectral searching strategy form a basic tensor unit, and can be utilized to improve image quality. Specifically, each tensor is decomposed into a low-rank component and a sparse component, which respectively represent the stable structures and feature differences across different energy bins. The augmented Lagrange method is applied to optimize the proposed objective function. To validate the performance of the proposed method, several simulated clinical and real data experiments are performed. The qualitative and quantitative results demonstrate that the proposed method outperforms several representative state-of-the-art algorithms in terms of preserving image details and reducing artifacts.
In-Titanium Embedded Multiplexed Femtosecond Fiber Bragg Gratings under Intense Heat Flow - Comparison between Experimental and Numerical Heat and Strain Cartography

Optical fiber sensors received a large interest in the past decades thanks to key advantages such as high temperature resistance, insensitivity to electromagnetic perturbation, and a low intrusivity allowing an efficient integration into metallic parts [1]… In the aeronautical context, aircraft structures can be exposed to large temperature variation as well as high acceleration and vibration levels. Optical fiber sensors are good candidates to monitor under such environments.
Pharmacological and Nutritional Modulation of Metabolome and Metagenome in Cardiometabolic Disorders

Cardiometabolic disorders are major causes of morbidity and mortality worldwide. A growing body of research indicates that the gut microbiota, whether it interacts favorably or not, plays an important role in host metabolism. Elucidating metabolic pathways may be crucial in preventing and treating cardiometabolic diseases, and omics methods are key to studying the interaction between the fecal microbiota and host metabolism. This review summarizes available studies that combine metabolomic and metagenomic approaches to describe the effects of drugs, diet, nutrients, and specific foods on cardiometabolic health and to identify potential targets for future research.
Long-Range Prediction of Nonlinear Dynamics in Fibre Optics Using Transformer-Based Neural Network

Ultrafast nonlinear dynamics in fibre optics can be simulated using the nonlinear Schrödinger equation (NLSE). However, the process may be slow if we need to do many simulations, such as during the optimization of optical device. It has been shown that recurrent neural network (RNN), a branch of deep learning model, has promising result in predicting the nonlinear dynamics of a laser pulse [1], [2]. We propose the use of transformer-based [3] deep learning model, to achieve superior accuracy and speed by leveraging its long-term temporal dependency and parallel computation brought by the attention mechanism.
Dhanashakti : A high-iron pearl millet variety

Development of biofortified cultivars of staple crops can make significant contributions to reducing micronutrient malnutrition and several associated adverse health consequences. Pearl millet variety Dhanashakti, bred for high iron content, is an early maturing open-pollinated variety that has the highest level of iron content in any pearl millet cultivar produced so far. Dhanashakti also marks the first high-iron biofortified cultivar of any crop officially released and already adopted by farmers in the country.
Oatmeal and the Catechism: Scottish Gaelic Settlers in Quebec

This work records the oral history, folklore and folk-life of emigrants from the Outer Hebrides to Quebec in the 19th century. It opens with the historical background before telling oral history as remembered and experienced by the emigrants' descendants, telling of land clearing, "homesteading", farming, lumbering, bridge building and all the other tasks required to build a new community in the wilderness. Gaelic-speaking presbyterians, the group kept their language for the first three generations and still retain their religion to this day, as well as the tradition of the "taigh ceilidh". For more than a century people in the Outer Hebrides have been asking what happened to those who left. This work answers much of that question.
Early Diagnosis of Emphysema using Convolutional Neural Networks

This study’s goal was to create and assess a deep learning model for emphysema identification in chest Radiographs images using the NIH Chest Radiographs dataset. For the management and treatment of emphysema, a chronic lung illness that can cause severe morbidity and death, early identification and diagnosis are essential. Chest Radiographs are often used to diagnose emphysema and deep learning models have been successful in improving the accuracy and efficiency of this process. A study used a convolutional neural network (CNN) to categorize chest Radiographs images as either normal or indicative of emphysema. A portion of the dataset was utilized for training the model, while a different test set was used for assessment. The dataset underwent preprocessing to guarantee consistency and accuracy in the labelling of emphysema. The study’s findings showed that the CNN model, with an overall accuracy of 83%, was very accurate in identifying emphysema in chest Radiographs images. These findings demonstrate how deep learning models may enhance the precision and effectiveness of emphysema diagnosis.
PRESENCIA DEL GENERO PALEOCTODON (RODENTIA, OCTODONTIDAE) EN EL HUAYQUERIENSE (MIOCENO TARDIO) DE LA PROVINCIA DE LA PAMPA

Recently collected portions of the left and right mandibular rami of the extinct Palaeoctodon aff. P. simplicidens are analyzed. These remains are from the Huayquerian (late Miocene) Cerro Azul Formation, that outcrops in Bajo Giuliani, La Pampa Province, Argentina. We concluded that the following features, among others, indicate that Palaeoctodon represents the oldest Ctenornyine-like Octodonudae: the major axis of the masticatory plane directed antero-posteriorly, and a very reduced third molar.
Knowledge-based feature extraction and spectral image enhancement from remotely sensed images

Scene development plays the first step for synthetic image generation using DIRSIG (The Digital Imaging and Remote Sensing Image Generation Model). Traditionally the scenes are built manually; the procedure is very time consuming especially for complex urban scenes. The research focuses on contributing to the DIRSIG scene model development based on information retrieval from high-resolution multispectral images, such as WorldView-2 sensor imagery. The proposed approach takes advantage of a sequence of image processing routines to enhance the spectral images and extracts key geographical features for the man-made road network and naturally occurring water bodies. These routines take into account the spatial as well as spectral signatures in the multispectral images. They constitute a chained process, which includes several steps: pan-sharpening, image filtering, classification, segmentation, morphological processing, vectorization and final refinement. In the first step of the process, a novel and highly parallel nearestneighbor diffusion based pan-sharpening procedure (NNDiffuse) is designed to fuse a high spatial resolution panchromatic image with the spectral image. Image filtering using trilateral filters for multispectral images is devised to process the image, removing small variances in the image as well as preserving significant edges. Spectral features such as Spectral Angle Mapper (SAM) are used to locate natural resource coverage such as water bodies. Multispectral flood fill technique, a graph based connected component technique and a knowledge-based system is used to extract the road networks. Both the road network and the water bodies can be refined and exported as vectorized ArcGIS shapefile. The outcome of the research is a workflow to facilitate scene development from spectral images; it also contributes to the development in the field of cartographic feature extraction, photogrammetry and target detection.
Skyrmion vs. antiskyrmion Hall angles

We observe significant, 6.5% - 12%, differences between skyrmion and antiskyrmion Hall angles in existing experimental data. To account for them, the Thiele equation is generalized with the transverse velocity component in the collective coordinate of magnetization vector. The corresponding generalized Hall angle is formulated, and its consequences are compared to the data. A plausible physical origin is provided for explaining the Hall angle differences.
Surface reconstruction from photometric normals with reference height measurements

In the dome imaging system at UCL, sets of pixel-registered images can be captured, with a different direction of illumination for each image. A new method has been developed to estimate surface normals more accurately by solving the photometric normal equations as a regression over a set of illumination angles and intensities selected from the subset corresponding to the diffuse component of reflection from the object surface (the 'body colour'). The gradients are integrated to reconstruct a digital terrain map, using a Fourier transform to regularise (i.e. enforce integrability of) the gradients in the frequency domain. This yields a 3D surface that is continuous but distorted over the whole area with the height greatly amplified. The problem is that although the gradients give a good representation of the spatial frequencies in the surface, right up to the Nyquist frequency, they are not accurate for very low frequencies of a few cycles over the full object diameter. Such frequencies are represented in the Fourier plane by only a few sample points close to the (shifted) origin. Errors in these frequencies can result in 'curl' or 'heave' in the baseplane, even though the superimposed higher spatial frequencies may be accurate. The solution is to replace the inaccurate low frequencies of the photometric normals by the more accurate low frequencies of a surface constructed from a few known heights. This is conveniently achieved from the values measured by a digital height gauge by interpolating to produce a smooth ‘hump’ and then transforming into the frequency domain by an FFT.
Mid-IR Optical Frequency Comb Fourier Transform Spectroscopy Using an Antiresonant Hollow-Core Fiber

Optical frequency combs (OFCs) enable high resolution, sensitivity, and speed in spectroscopic measurements. An efficient way of generating an optical frequency comb in the mid-infrared (mid-IR) is the difference frequency generation (DFG) process, which involves the interaction of two input waves in a non-linear crystal, resulting in the generation of a third wave with a frequency that is the difference in frequency of the two input beams [1]. The classical way of extending the path of light-gas interaction in spectroscopic measurements, thus increasing the sensitivity, is to use multi-pass cells (MPC). However, MPCs have disadvantages related to the difficulty of aligning laser light into the cell or optical fringes. An alternative approach is to use the so-called antiresonant hollow-core fibres (ARHCF) [2]. ARHCFs are characterized by a wide low-loss transmission range in the mid-IR, high quality of the delivered beam, and their air core can be filled with the target gas sample, which makes them well suited for laser-based gas sensing.
Trump vs. the GOP: Political Determinants of COVID-19 Vaccine Hesitancy

This study examines the relationship between Trumpism and COVID-19 vaccination in the US. We ﬁnd that counties with greater Trump support show lower COVID-19 vaccination rates. However, this relationship is beyond the e ﬀ ects of Repub-lican partisanship. The distinctive e ﬀ ects of Trumpism are further validated through falsiﬁcation and placebo exercises. To address potential endogeneity, we suggest an instrumental variable (IV) strategy based on online search behavior before the rise of Trump. The IV estimates conﬁrm the negative link between Trump support and COVID-19 vaccination, which is conditional on the partisan divide or conservative orientation. As a mechanism, we provide evidence that distrust in science increased to a greater degree in counties that voted for Trump in 2016 more than they did for Romney in 2012. Moreover, we do not ﬁnd comparable results in places with an increase in Republican partisanship or conservatism. These results substantiate that the Trump e ﬀ ect on COVID-19 responses is not attributable to the general political climate.
On third-order rational difference equations, part 1

with nonnegative parameters a, b, g, d, A, B, C, D and with arbitrary nonnegative initial conditions x22, x21, x0 such that the denominator is always positive. Some extensions to higher order rational difference equations will also be presented. We are primarily interested in the boundedness nature of solutions, the global stability of the equilibrium points, the periodic character of the equation, and with convergence to periodic solutions including periodic trichotomies. For some related results see Refs. [1–63] and the references cited therein. Equation (1) contains 225 special cases of equations with positive parameters. See Refs. [8,52] for the numbering system which we use to designate the various special cases of rational difference equations. In Part 1 we give an up-to-date account on recent developments related to Equation (1) and we pose several thought provoking Open Problems and Conjectures whose investigation will play an important role in the development of the basic theory of nonlinear difference equations. In part 2 we present several new results concerning the existence of unbounded solutions in fourth-order rational difference equations. Of the 225 special cases of Equation (1), 39 special cases are trivial, linear, reducible to linear, Riccati equations, or reducible to Riccati equations. Another 28 special cases were the subject of investigation in the Kulenovic and Ladas book [44], which deals with the
Power Domain Aware DFT Implementation

Power awareness has become an important dimension for recent advances in VLSI. Multiple functional power domains (PD) are forcing Design-for-Test (DFT) designers to adjust DFT insertion and implementation to comply with IEEE 1801 correctness. Several challenges emerge for DFT tools and engineers, including but not restricted to a) additional low power cells inserted & crossings created due to DFT connections, b) power aware scan chain connection with optimal scan wirelength, and c) ensuring Unified Power Format (UPF) correctness post DFT insertion. This paper describes power domain aware DFT techniques for core wrapping, heterogenous fanouts and PD fencing aware scan chain stitching. A correct by construction approach results in fewer low power cells, improved scan wirelength & fewer IEEE 1801 rule violations. The EDA automation demonstrated in this paper reduces the manual overhead for chip designers to ensure power correctness of the design after DFT implementation.
Modal Gain and Cross-Saturation Effects on the Switching Capabilities of an Integrated Multi-Wavelength Laser

On-chip multi-wavelength lasers, i.e., lasers that emit at multiple and controllable wavelengths, have emerged as versatile devices that can be used as discretely tunable lasers and, due to their nonlinear dynamics behavior, have been proposed for signal processing and microwave generation applications [1]. When adding unfiltered phase-controlled optical feedback, efficient switching between two modes was observed with high extinction ratios by setting the two wavelengths in antiphase configuration after a round-trip in the external cavity [2]. However, the feedback-based control of the emission depends on the operation conditions and properties of the laser, such as injection current, modal gain, mode coupling, and even feedback strength. Thus, expanding this control mechanism to lasers with three or more modes requires an understanding of the role of these parameters in the switching. In this work, we experimentally show power switching between three modes with a high extinction ratio, enabled by the phase-controlled feedback, and we investigate numerically the impact of modal gain and mode coupling on the switching.