Miracle-dz/UniFAR-FTUs huggingface dataset:
Simplification of Shapes for Fabrication with V-Groove Milling Tools

We introduce here a pipeline for simplifying digital 3D shapes with the aim of fabricating them using 2D polygonal ﬂat parts. Our method generates shapes that, once unfolded, can be fabricated with CNC milling machines using special tools called V-Grooves. These tools make V-shaped furrows at given angles depending on the shape of the used tool. Milling the edges of each ﬂat facet simpliﬁes the manual assembly that consists only in folding the facets at the desired angle between the adjacent facets. Our method generates simpliﬁed shapes where every dihedral angle between adjacent facets belongs to a restricted set, thus making the assembly process quicker and more straightforward. Firstly, our method automatically computes a simpliﬁcation of the model, iterating local changes on a triangle mesh generated by applying the Marching Cubes algorithm on the original mesh. The user performs a second manual simpliﬁcation using a tool that removes spurious facets. Finally, we use a simple unfolding algorithm which ﬂattens the polygonal facets onto the 2D plane, so that a CNC milling machine can fabricate it with a sheet of rigid material
Utilizing Triage Data for Medical Imaging Studies in the Emergency Department

The use of radiological images is widespread in the emergency department (ED) as physicians commonly rely on them during initial evaluations to confirm diagnoses, contributing to prolonged waiting times. This study aimed to determine the relationship between commonly gathered triage data and the need for radiological imaging. Data were collected from electronic charts that contained routinely collected hospital data at the time of triage in the King Abdulaziz Medical City (KAMC) in Riyadh ED. The binary logistic regression results demonstrated a statistically significant relationship between age and radiological imaging ordered in the ED. Each one-unit increase in age corresponded to a 0.983-fold increase in the likelihood of ordering radiological imaging (odds ratio: 0.983, 95% confidence interval: 0.972-0.995, p = 0.004). In contrast, hypertension, diabetes, and heart failure were independent predictors of the need for radiological imaging in the ED (p >0.05). Patient data that are immediately available during ED triage can be used to predict the need for radiological imaging during ED visits. Such models can identify patients who may require radiological imaging during ED visits and expedite patient disposition.
Trust in numbers

Those who value quantitative and scientific evidence are faced with claims both of a reproducibility crisis in scientific publication and of a post‐truth society abounding in fake news and alternative facts. Both issues are of vital importance to statisticians, and both are deeply concerned with trust in expertise. By considering the ‘pipelines’ through which scientific and political evidence is propagated, I consider possible ways of improving both the trustworthiness of the statistical evidence being communicated, and the ability of audiences to assess the quality and reliability of what they are being told.
Public’s Legal Awareness on Child Marriage

This study aims to conduct a qualitative analysis of the legal awareness of ethnic Javanese people on the practice of child marriage in Bumirejo Hamlet, Tapak Siring Village, Sukau District. Data collection was conducted through interviews, observations and documentation from parents and perpetrators of child marriage, as well as community leaders. This study shows that the low legal awareness of the Javanese ethnic community on the practice of child marriage is motivated by low education, economy, community habits, and self-will. There has been no effort from local community leaders to minimize the occurrence of child marriage so that the practice of child marriage still occurs.
Comparison Between Shielding Effectiveness of Slotted Cavities in a Mode Stirred Chamber and Free Space

We conduct a comparative study using shielding effectiveness (SE) measurements from canonical test objects inside an anechoic chamber (AC) and a mode stirred chamber (MSC) and full wave electromagnetic (EM) simulations. SE is a critical parameter used to evaluate interference caused by external EM radiation and is defined as the ratio of the power received inside an enclosure to the power that would be received by the same antenna outside of the enclosure. Our test objects are high Q cylindrical cavities with 0, 1, and 8 slot apertures that show strong resonances at discrete frequencies between 1 and 2 GHz. Theory suggests that the SE measured in the AC and the SE measured in the MSC should be related by the peak directivity of the test object. For a test object with a small aperture, the results from the two chambers agree with theory, while the test object with a large aperture has significant discrepancies between the predicted relationship between the SE measured in the two chambers. This measured discrepancy implies there are geometries where the theory of SE in MSCs breaks down. This article presents a careful analysis of these results with the goal of understanding these discrepancies.
impact of Japan's trade agreements and safeguard renegotiation on U.S. access to Japan's beef market

Since 2018, Japan has ratified trade agreements that generate both challenges and opportunities for U.S. beef exporters. Using the Global Trade Analysis Project model, USDA, Economic Research Service researchers estimate that after 10 years Japan's imports of beef products will have increased by 26.6 percent, and Japan's production of beef products will have decreased by 17.2 percent. U.S. beef export values to Japan are estimated to increase $413.8 million.
Exploratory Analysis on Market Basket Data using Network Visualization

Market basket analysis is a powerful technique for understanding customer behavior and optimizing business strategies based on that understanding. Market-based analysis over time using visualization techniques can provide insights into market trends and relations, simplify complex data, and communicate insights effectively, which can help organizations make more informed decisions. This paper leverages a dataset focused on the users’ incomes and temporal aspects of market purchases. We modeled this dataset as three distinct temporal networks and performed an exploratory evaluation identifying patterns and anomalies in the data. More specifically, we identified groups of related products, indicating thematic purchases, and evaluated the impact of demographic factors, such as income, on customer spending.
On (in)tractability of connection and cut problems

This work addresses connection and cut problems from the viewpoint of graph classes and computational complexity, classic and parameterized. Regarding connection problems, we investigate the so-called TERMINAL CONNECTION problem (TCP), which can be seen as a generalisation of the classical STEINER TREE problem. We propose several complexity results for TCP, when restricted to specific graph classes, and some of its input parameters are fixed. As for cut problems, we analyse the complexity of the classical MAXCUT problem. We introduce the first complexity classification for the problem on interval graphs of bounded interval count. In addition, we prove the NP-completeness of MAXCUT on permutation graphs, settling a question posed by David S. Johnson in the Ongoing Guide to NP-completeness, which has been open since 1985. Finally, we consider the problem of computing the zig-zag number of a directed graph, which is a directed width measure defined over cuts of a graph.
WEAK CONVERGENCE TO STOCHASTIC INTEGRALS UNDER PRIMITIVE CONDITIONS IN NONLINEAR ECONOMETRIC MODELS

Limit theory with stochastic integrals plays a major role in time series econometrics. In earlier contributions on weak convergence to stochastic integrals, the literature commonly uses martingale and semi-martingale structures. Liang, Phillips, Wang, and Wang (2016) (see also Wang (2015), Chap. 4.5) currently extended weak convergence to stochastic integrals by allowing for a linear process or a α-mixing sequence in innovations. While these martingale, linear process and α-mixing structures have wide relevance, they are not sufficiently general to cover many econometric applications that have endogeneity and nonlinearity. This paper provides new conditions for weak convergence to stochastic integrals. Our frameworks allow for long memory processes, causal processes, and near-epoch dependence in innovations, which have applications in a wide range of econometric areas such as TAR, bilinear, and other nonlinear models.
The Evolutions of Microstructure, Texture and Hardness of A1050 Deformed by HPT at the Transition Area

High-pressure torsion (HPT) is an effective severe plastic deformation method to produce ultrafine-grained (UFG) and nanocrystalline (NC) materials. In the past, most studies have focused on the evolutions in the microstructure, texture and mechanical properties of HPT-deformed materials at peripheral regions. The corresponding evolutions at a special area were observed in this study to reveal the potential plastic deformation mechanism for face-centred cubic (FCC) material with high stacking fault energy. A decreasing trend was found in grain size, and the final grain size was less than 1 μm. However, close observation revealed that the general trend could be divided into different sub-stages, in which grain elongation and grain fragmentation were dominant, respectively. Additionally, microhardness demonstrated a non-linear increase with the development of plastic deformation. Finally, the microhardness reached a high level of ~64 HV. At the early stages of HPT, the C component was transformed into a cube component, suggesting the material flows around the shear plane normal (SPN) axis at these stages. However, finally they will be replaced by ideal simple shear orientations.
THE LIMITS OF TRANSLATABILITY EXEMPLIFIED BY METAPHOR TRANSLATION

Although in view of its importance and frequency in language use metaphor indubitably constitutes a pivotal issue in translation, it has hitherto received only random attention on the part of translation theorists. Presumably one of the main obstacles for a theory of translation to overcome is the intuitively subscribed and generally accepted "inadequacy of any single generalization about the translatability of metaphor. " If however we accept that there is such a thing as a theoretical constituent level on which translation phenomena can be dealt with, we must also accept that it is the proper task of translation theory to make generalizations about such phenomena. To admit the inadequacy of generalizations about the translatability of metaphor is to admit that translation theory as a whole is an absurd undertaking, since it then should be incapable of accounting for the translation of one of the most frequent phenomena in language use. Even if such generalizations must necessarily "fail to do justice to the great complexity of the factors determining the ontology of metaphors why certain metaphors are created and others not; why a metaphor that is strikingly effective in one language becomes peculiar or even unintelligible if transferred unchanged into another [. ]; in short, why languages are anisomorphic metaphorically" (Dagut, 1976: 32), it may content itself with the more modest task of laying bare some of the hidden mechanisms governing the translation of metaphors and their theoretic degree of translatability. In this paper it is my intention to make such specifications as seem necessary to provide a theoretical framework in which general statements about the translation of metaphors can be made.
Navigating the chaos of psychedelic neuroimaging: A multi-metric evaluation of acute psilocybin effects on brain entropy

Investigations into the acute effects of psychedelics on brain imaging have emphasised increased 'brain entropy' as a potential neural correlate. To date, 12 previous studies have reported brain entropy effects, each reporting a single and unique metric, none of which have been examined in an independent cohort. Here we evaluated acute psilocybin effects on these 12 brain entropy metrics in an independent cohort of 28 healthy participants. Following a single psilocybin dose, participants completed pre/post resting-state BOLD fMRI scans (28 pre-drug, 93 post-drug scans during the acute drug effects). Each scan was accompanied by a plasma sample to quantify plasma drug levels and estimate brain serotonin 2A receptor occupancy, as well as a rating of subjective drug intensity. We assessed relations between brain entropy and these measures with linear mixed-effects models. There was a significantly positive association for Shannon entropy of path-length and instantaneous correlation distributions and divergent associations of network-wise sample entropy at varying time-scales. We did not observe significant psilocybin effects for seven of 12 brain-entropy metrics. Whole-brain entropy metrics showed limited correlations between each other. Our observations suggest a nuanced acute effect of psychedelics on brain entropy, underscoring the need for reproducing effects. The variable effects and limited inter-metric correlation undermines the generalisability of 'brain entropy' as a singular construct. Future studies in clinical cohorts are crucial to elucidate the link between these metrics and therapeutic effects of psychedelics.
Oculomotor analysis to assess brain health: preliminary findings from a longitudinal study of multiple sclerosis using novel tablet-based eye-tracking software

A growing body of evidence supports the link between eye movement anomalies and brain health. Indeed, the oculomotor system is composed of a diverse network of cortical and subcortical structures and circuits that are susceptible to a variety of degenerative processes. Here we show preliminary findings from the baseline measurements of an ongoing longitudinal cohort study in MS participants, designed to determine if disease and cognitive status can be estimated and tracked with high accuracy based on eye movement parameters alone. Using a novel gaze-tracking technology that can reliably and accurately track eye movements with good precision without the need for infrared cameras, using only an iPad Pro embedded camera, we show that several eye movement parameters significantly correlated with clinical outcome measures of interest. Eye movement parameters were extracted from fixation, pro-saccade anti-saccade, and smooth pursuit visual tasks, whereas the clinical outcome measures were the scores of several disease assessment tools and standard cognitive tests such as the Expanded Disability Status Scale (EDSS), Brief International Cognitive Assessment for MS (BICAMS), the Multiple Sclerosis Functional Composite (MSFC) and the Symbol Digit Modalities Test (SDMT). Furthermore, multiple regression analyses show that a small set of oculomotor parameters can explain up to 74% of the variance of the clinical outcome measures. Taken together, these findings not only replicate previously known associations between eye movement parameters and clinical scores, this time using a novel mobile-based technology, but also the notion that interrogating the oculomotor system with a novel eye-tracking technology can inform us of disease severity and evolution, as well as the cognitive status of MS participants.
Creatine supplementation for optimisation of physical function in the patient at risk of functional disability: A systematic review and meta-analysis

Background The efficacy of creatine replacement through supplementation for the optimisation of physical function in the population at risk of functional disability is unclear. Methods We conducted a systematic literature search of MEDLINE, EMBASE, Cochrane Library and CINAHL until November 2022. Studies included were randomised controlled trials comparing the use of creatine supplementation with placebo in older adults and adults with chronic disease. The primary outcome was physical function measured by the sit-to-stand test after pooling data using random effects modelling. We also performed a Bayesian meta-analysis to describe the treatment effect in probability terms. Secondary outcomes included other measures of physical function, muscle function and body composition. The risk of bias was assessed using the Cochrane risk-of-bias tool. Results We identified 33 RCTs, comprising 1076 participants. From 6 trials reporting the primary outcome, the pooled standardised mean difference was 0.51 (95% CI 0.01 to 1.00; I2=62%; p=0.04); using weakly informative priors, the posterior probability that creatine supplementation improves physical function was 66.7%. Upper body muscle strength (SMD 0.25, 95% CI 0.06 to 0.44; I2=0%; p=0.01), handgrip strength (SMD 0.23, 95% CI 0.01 to 0.45; I2=0%; p=0.04) and lean tissue mass (MD 1.08kg; 95% CI 0.77 to 1.38; I2=26%; p<0.01) improved with creatine supplementation. The quality of evidence for all outcomes was low or very low due to a high risk of bias. Conclusion Creatine supplementation improves sit-to-stand performance, muscle function and lean tissue mass. It is crucial to conduct high-quality prospective RCTs to confirm these hypotheses (Prospero number, CRD42023354929).
The structural covariance of reading-related brain regions in adults and children with typical reading skills and developmental dyslexia

Structural covariance (SC) is a promising approach for investigating brain organization within the domain of literacy and developmental disorders as it thought to reflect both functional and structural information. This study presents a first-of-its-kind exploration of SC in reading- related brain regions across different ages and reading abilities. Whole-brain SC analyses were conducted for six key regions of the reading network, including an anterior and posterior subdivision of the visual word form area (VWFA). We compared SC matrices of typically reading adults (N=134) and children (N=110), and between typically reading children and children with dyslexia (N=68). Our results showed significant associations between reading-related brain regions in typically reading adults. We observed significant SC between the posterior VWFA and the left occipital cortex, and between the anterior VWFA and the left superior temporal gyrus and left inferior frontal gyrus. Typical-reading adults and children did not differ significantly in SC. However, typically reading children demonstrated significantly higher SC between the inferior parietal lobule (IPL) and other reading-related brain regions than children with dyslexia. Our findings provide support for a functional and structural division of the VWFA and underscore the crucial role of the IPL in fluent reading.
A non-standard optimal control problem using hyperbolic tangent

A current ideal control issue in the region of financial aspects has numerical properties that do not fall into the standard optimal control problem detailing. In our concern the state an incentive at the final time, y(T ) = z, is free and obscure, and furthermore the integrand is a piecewise consistent capacity of the obscure esteem y(T ). This is not a standard optimal control problem and cannot be settled utilizing Pontryagin’s Minimum Principle with the standard limit conditions at the final time. In the standard issue a free final state y(T ) yields an important limit condition p(T ) = 0, where p(t) is the costate. Since the integrand is a component of y(T ), the new fundamental condition is that y(T ) yield to be equivalent to a specific necessary that is a consistent capacity of z. We present a continuous estimation of the piecewise consistent integrand function through hyperbolic tangent approach and tackle a case utilizing a C++ shooting method with Newton emphasis for tackling the two point boundary value problem (TPBVP). The limiting free y(T ) value is computed in an external circle emphasis through the Golden Section method.
Performance Analysis and Evaluation of Post Quantum Secure Blockchain Federated Learning

Post-quantum security is critical in the quantum era. Quantum computers, along with quantum algorithms, make the standard cryptography based on RSA or ECDSA over FL or Blockchain vulnerable. The implementation of post-quantum cryptography (PQC) over such systems is poorly understood as PQC is still in its standardization phase. In this work, we propose a hybrid approach to employ PQC over blockchain-based FL (BFL), where we combine a stateless signature scheme like Dilithium (or Falcon) with a stateful hash-based signature scheme like the extended Merkle Signature Scheme (XMSS). We propose a linear-based formulaic approach to device role selection mechanisms based on multiple factors to address the performance aspect. Our holistic approach of utilizing a verifiable random function (VRF) to assist in the blockchain consensus mechanism shows the practicality of the proposed approaches. The proposed method and extensive experimental results contribute to enhancing the security and performance aspects of BFL systems.
Learning Robust, Agile, Natural Legged Locomotion Skills in the Wild

Recently, reinforcement learning has become a promising and polular solution for robot legged locomotion. Compared to model-based control, reinforcement learning based controllers can achieve better robustness against uncertainties of environments through sim-to-real learning. However, the corresponding learned gaits are in general overly conservative and unatural. In this paper, we propose a new framework for learning robust, agile and natural legged locomotion skills over challenging terrain. We incorporate an adversarial training branch based on real animal locomotion data upon a teacher-student training pipeline for robust sim-to-real transfer. Empirical results on both simulation and real world of a quadruped robot demonstrate that our proposed algorithm enables robustly traversing challenging terrains such as stairs, rocky ground and slippery floor with only proprioceptive perception. Meanwhile, the gaits are more agile, natural, and energy efficient compared to the baselines. Both qualitative and quantitative results are presented in this paper.
Transformer with Selective Shuffled Position Embedding and Key-Patch Exchange Strategy for Early Detection of Knee Osteoarthritis

Knee OsteoArthritis (KOA) is a widespread musculoskeletal disorder that can severely impact the mobility of older individuals. Insufficient medical data presents a significant obstacle for effectively training models due to the high cost associated with data labelling. Currently, deep learning-based models extensively utilize data augmentation techniques to improve their generalization ability and alleviate overfitting. However, conventional data augmentation techniques are primarily based on the original data and fail to introduce substantial diversity to the dataset. In this paper, we propose a novel approach based on the Vision Transformer (ViT) model with original Selective Shuffled Position Embedding (SSPE) and key-patch exchange strategies to obtain different input sequences as a method of data augmentation for early detection of KOA (KL-0 vs KL-2). More specifically, we fix and shuffle the position embedding of key and non-key patches, respectively. Then, for the target image, we randomly select other candidate images from the training set to exchange their key patches and thus obtain different input sequences. Finally, a hybrid loss function is developed by incorporating multiple loss functions for different types of the sequences. According to the experimental results, the generated data are considered valid as they lead to a notable improvement in the model's classification performance.