Miracle-dz/UniFAR-FTUs huggingface dataset:
Computing Discrete Logarithms

Let G be a multiplicatively-written finite cyclic group, let g ∈ G be a generator and let h ∈ G. The discrete logarithm problem (DLP) for (G, g, h) is the computational problem of determining an integer x such that h = gx. Note that the integer x is uniquely determined modulo the group order. Just as for the continuous logarithm function, one also writes x = logg h and refers to x as the discrete logarithm of h to the base g. The DLP has been central to public key cryptography ever since its inception by Diffie and Hellman in 1976 [15], and its study can be traced at least as far back as 1801, when discrete logarithms featured in Gauß’ Disquisitiones Arithmeticae, referred to there as indices with respect to a primitive root modulo a prime [23, art. 57– 60]. Indeed, the multiplicative group Fp of the field Fp of integers modulo a prime p is perhaps the most natural example of a group in which the DLP can be posed – which is presumably why Diffie and Hellman used this setting for their famous key agreement protocol – and it is still believed to be hard for well-chosen primes. In general, if the DLP is hard in a particular group then one can instantiate numerous important cryptographic protocols. So the issue at hand is: how hard is it to compute discrete logarithms in various groups? In this chapter we shall describe some cryptographically relevant DLPs and present some of the key ideas and constructions behind the most efficient algorithms known that solve them. Since the topic encompasses such a large volume of literature, for the finite field DLP we limit ourselves to a selection of results reflecting recent advances in fixed characteristic finite fields. We start by briefly recalling the so-called generic algorithms, which do not exploit any representational properties of group elements and may thus be applied to any finite cyclic group, and then recall the more sophisticated approach known as the index calculus method, which may be applied whenever the representation of elements of a group can be imbued with a suitable notion of smoothness. In §2 we introduce elliptic curves and pairings over finite fields and consider various discrete logarithm algorithms. Then in §3 we consider some groups in which the DLP is easier than for the strongest elliptic curves, including some families of weak curves. In §4 we focus on discrete logarithm algorithms for XTR and algebraic tori when defined over extension fields, and finally in §5 we present some of the key insights behind the breakthroughs between 2012 and 2014 that led to the downfall of finite fields of fixed characteristic in cryptography. First, we introduce some useful notation for describing the running time of discrete logarithm algorithms (or equivalently the complexity or hardness of the DLP),
Effects of water quality and soft-substrate on benthic macrofauna in the intertidal zone of Pochomil beach

A spatial and temporal study of the benthic macrofauna was carried out in the intertidal zone of Playa Pochomil, Nicaragua, in three sites called S.A (sandy site), SRR (rocky site with river) and S.R (rocky site), respectively. At the end of the study, a total of 596 individuals belonging to four Edges (Mollusca, Annelida, Arthropoda and Echinodermata) were counted. Benthic macrofauna diversity calculated using the ShannonWeaver index reflects very low diversity values during all sampling periods. Through the Jaccard and Morisita-Horn index, it was evidenced that there was low species similarity. In addition, it was found that the temporality had no significant direct effect on the abundance and distribution of the benthic macrofauna, but that it was mainly influenced by the physical characteristics of the sampling sites.
PhysioZoo ECG: Digital electrocardiography biomarkers to assess cardiac conduction

Introduction: The electrocardiogram (ECG) is a standard tool used in medical practice for identifying cardiac pathologies. Because the necessary expertise to interpret this tracing is not readily available in all medical institutions or at all in some large areas of developing countries, there is a need to create a data-driven approach that can automatically capture the information contained in this physiological time series. Yet, contrary to heart rate variability measures, a field which has seen the development of standards, advanced toolboxes and software, very little open tools exist for ECG morphological analysis. The primary objective of this work was to identify and implement clinically important digital ECG biomarkers for the purpose of creating a reference toolbox and software for ECG morphological analysis. Methods: The epltd algorithm was used for R-peak detection. We used a zero-phase filter with passband 0.67Hz - 100Hz to remove baseline wander and high frequency noise. We used a Notch filter at 50/60Hz to remove the power-line interference. ECG fiducial points were detected using the well-known open source wavedet algorithm. A total of 22 biomarkers were engineered including 14 extracted from intervals and segments duration and 8 from waves characteristics. Results and discussion: the result of this work consists of a Python toolbox termed “pebm” and its user interface termed “Physio'Zoo ECG” for data visualization and analysis. The software is available at physiozoo.com under a GNU GPL licence. The pebm toolbox may be used to provide new physiological information on cardiac conduction as well as used as a source of readily handcrafted features for training machine learning models.
Incorporating Clinical and Heartbeat Level Features with Multichannel ECG for Cardiac Abnormality Detection Using Parallel CNN and GAP Network

Background: Early and correct diagnosis of cardiac arrhythmias from Multichannel Electrocardiogram (MECG) is a challenging problem. We address this problem as part of the PhysioNet/Computing in Cardiology Challenge 2021 by classifying cardiac abnormalities from MECG. Method: The proposed method incorporates clinical features including patient age, gender and heartbeat features with MECG to detect cardiac abnormalities. Initially, MECG is cleaned from noise, followed by resampling and segmentation. Then R-peaks are extracted from Lead II signal using Pan Tompkins detector to obtain heartbeat level features such as heart rate, RR Intervals, Mean QRS Amplitude, Hermite polynomial coefﬁcients, statistical features, and Wave Amplitude based features. The feature vector consisting of clinical and heartbeat features is combined with MECG for classiﬁcation using a Parallel Convolution Neural Network with Global Average Pooling (PCNN-GAP) network. The model extracts local features using smaller convolution kernels and global patterns using larger kernels. Lastly, the last layer sigmoid activation function classiﬁes the rhythm into one or more cardiac abnormalities. Results: Our team, skylark, achieved a score of 0 . 466 , 0 . 426 , 0 . 5 , 0 . 491 , and 0 . 514 (ranked 131 th , 137 th , 116 th , 118 th , and 107 th out of 256 teams) for the 12-lead, 6-lead, 4-lead, 3-lead, and 2-lead versions of the hidden validation set with the Challenge evaluation metric.
REDUCING PLASTIC WASTE 1 Reducing plastic waste by visualizing marine consequences

Plastic pollution has become a major global conservation challenge. To reduce the generation of plastic waste, we designed and tested several behavioral interventions in a randomized control trial to reduce plastic waste in a high-rise office building. We randomly assigned eight floors in the building to four conditions: (1) simplified recycling signage, (2) signage with a marine animal trapped in plastic debris, (3) signage with a pledge that invited people to be plastic wise to protect ocean life, and (4) control. We found that the signage with the animal reduced plastic waste by 17%, the largest effect among the other conditions. After implementing the signage to the entire building, we found an overall reduction in plastic waste over six weeks. The current study demonstrates the effectiveness of visualizing marine consequences of plastic waste and provides a new behavioral solution connecting disposal actions and the downstream consequences for plastic waste reduction.
Adsorptions of Diatomic Gaseous Molecules (H2, N2 and CO) on the Surface of Li+@C16B8P8 Fullerene-Like Nanostructure: Computational Studies

Density functional theory (DFT) calculations have been performed to investigate the adsorption of hydrogen (H2), nitrogen (N2) and carbon monoxide (CO) diatomic gaseous molecules at the surface of Li+ contained C16B8P8 fullerene–like nanostructure (Li+@C16B8P8). The evaluated results from the optimized structures indicated that the adsorption processes could be taken placed for the interacting gas and fullerene systems. Moreover, the electronic properties indicated that the electrical conductivities of Nano Clusters systems are changed after the adsorption processes, in which it could be a signal for detection or sensing of the existence of the gas in the environment. These changes lead to declining the HOMO/LUMO gap of the Fullerene–Like Nano Cage to its original value. As a finding of this work, it could be mentioned that the Li+@C16B8P8 fullerene–like nano cage could be considered as a suitable adsorbent for the CO, N2 and H2 gaseous. It means that the utilized Li+@C16B8P8 Fullerene–Like Nano Cage can detect the existence of gas in the environment.
The geodiv r package: Tools for calculating gradient surface metrics

The geodiv r package calculates gradient surface metrics from imagery and other gridded datasets to provide continuous measures of landscape heterogeneity for landscape pattern analysis. geodiv is the first open‐source, command line toolbox for calculating many gradient surface metrics and easily integrates parallel computing for applications with large images or rasters (e.g. remotely sensed data). All functions may be applied either globally to derive a single metric for an entire image or locally to create a texture image over moving windows of a user‐defined extent. We present a comprehensive description of the functions available through geodiv. A supplemental vignette provides an example application of geodiv to the fields of landscape ecology and biogeography. geodiv allows users to easily retrieve estimates of spatial heterogeneity for a variety of purposes, enhancing our understanding of how environmental structure influences ecosystem processes. The package works with any continuous imagery and may be widely applied in many fields where estimates of surface complexity are useful.
Geometric Optimisation of a Coupled Vane Compressor

The coupled vane compressor (CVC) is a rotary compressor with two coupled vanes which slide diametrically through the rotor during operation. As compared to most other rotary vane compressors, this CVC works well with small rotor-to-stator diameter ratio, typically less than that for all existing rotary compressors (>0.7). Hence, CVC has probably the most compact design among all rotary compressors, thus saving materials and manufacturing cost. This compressor is intended for use in room air-conditioners and refrigerators. Currently, mathematical model and measurement have been carried out to determine the working characteristics of this compressor. In this paper, a genetic algorithm with constraints handling has been devised and linked with the verified mathematical model of the CVC to search for a set of geometrical parameters which produces highest COP when working in the refrigeration cycle. During this optimisation search process, the significant design variables such as rotor radius, cylinder radius, vane thickness and valve reed thickness are allowed to vary. In this paper, the details on the application of the optimization process, constraints handling and descriptions, objective function definitions as well as the details of optimization implementation will be presented and discussed. Results obtained will be shown and deliberated. The results show that this optimization study reconfirms the value of optimisation in compressor design.
Multi-Label Cardiac Abnormality Classification from Electrocardiogram Using Deep Convolutional Neural Networks

This paper proposes a deep neural network architecture to perform multi-label classification of 26 cardiac abnormalities from 12-lead and reduced lead ECG data. The model was created by team “NIMA” for the PhysioNet/Computing in Cardiology Challenge 2021. ECG signals of at most 20 seconds in length were used for training. The data are preprocessed by normalizing, resampling, and zero-padding to get a constant-sized array. The preprocessed ECG signals and Fast Fourier Transforms obtained from the preprocessed signals are each fed into two separate deep Convolutional Neural Networks. Spatial dropouts and average pooling are used between each convolutional layer to reduce overfitting and to reduce model complexity. Following the convolutional layers, the time and frequency domain network outputs are concatenated and passed through two dense layers that output an array of size 26. A threshold of 0.13 is used on the output array to determine the class while addressing data imbalance. The method achieved a score of 0.55, 0.51, 0.56, 0.55, and 0.56 ranking 2nd, 5th, 3rd, 3rd and 3rd out of 39 officially ranked teams on 12-lead, 6-lead, 4-lead, 3-lead, and 2-lead hidden test datasets, respectively, according to the challenge evaluation metric. Our model performs comparable to the 12 Lead ECG using smaller subsets of leads.
Electro-Mechanical Coupling in Human Atrial Cardiomyocytes: Model Development and Analysis of Inotropic Interventions

Human-based computational models are a powerful tool that complements the experimental approaches and can improve our understanding of individual components of the heart by integrating them into one system. This paper aims to couple and calibrate a human atrial electro-mechanical model to analyse the coupling effects and inotropic interventions on human atrial electrophysiology, calcium dynamics, and active isometric contraction on a cellular scale. A human atrial electrophysiology model was coupled with one of the recently developed biophysically detailed contraction models. A collection of human atrial experimental data has been presented to calibrate the coupled model. The calibrated electro-mechanical human atrial model yielded action potential, calcium transient and active tension that were validated against the experiments and conclusions were drawn to explain the mismatch between in-silico and in-vitro experiments on inotropic interventions. The coupled and calibrated human atrial electro-mechanical model and simulation framework developed in this study serves as a pathway for future investigations of the effect of contractile performance and inotropic interventions on the electrophysiology of the atria.
An analysis of the economic and social contribution of Brazilian agricultural cooperatives using the Statement of Value Added

Objective: Assess the creation of wealth by Brazilian agricultural cooperatives and its distribution to the economic agents that helped to create it, comparing the process with for-profit companies. Method:The analyses are based on secondary data from the database of the yearly “Best and Biggest”. The research design is classified as archival. The sample consists of 1,368 observations, distributed between 2010 and 2016, containing cooperatives and for-profit companies listed in the Ranking of the 400 largest in Brazilian agribusiness. To check the hypotheses, the statistical test Mann-Whitney was used. Results:The cooperatives contribute significantly to the creation of wealth in the Brazilian agricultural sector. Concerning the distribution of the created wealth, in both the cooperatives and the other companies, the collaborators are the main destination group of the valueadded. Against expectations, the tax load the cooperatives support is statistically similar to that of the other organizations. Finally, the cooperative members receive a percentage of the value added that is statistically higher than the value the company investors receive, consistently with the purpose of the cooperative. Contributions: The cooperatives contribute to the economy of the agricultural sector by creating and distributing wealth, mainly at times when the other organizations are stagnating.
MATH-SHU 236 Convex Relaxation of Maxcut and Mincut

Among many real applications, one immediate challenge is about the computational complexity. For example, remember in spectral clustering, the goal is actually to find the minimal ratio/normalized cut, which is proven to be NP-hard. To solve it, we employ the idea of relaxation. In fact, this idea is extremely powerful in other NP-hard problems as well. In particular, convex relaxation is an extremely useful technique in solving or providing an approximate solution of an other-wise NP-hard problem. We will see many examples later including Maxcut, compressive sensing, ratio/normalized cut, matrix completion, low-rank matrix recovery, group synchronization, community detection, and model selection (LASSO).
Trade Collapse During the COVID-19 Crisis and the Role of Demand Composition

We examine the role of demand composition in explaining the trade collapse and recovery during the ongoing covid-19 crisis. We apply an import-intensity-adjusted measure of demand to examineimport trends in 40 advanced and emerging economies over the period 1Q95 to 4Q20. We focus on the crisis periods related to covid-19 and the global financial crisis in 2008–2009. As during the global financial crisis, we find that import-intensity-adjusted demand is a key factor contributing to trade developments during the covid-19 crisis. The analysis also reveals substantial differences between the current crisis and the global financial crisis. Trade decline during the global financial crisis was heavily investment-led. In the current crisis, consumption and import demand from the service sector have had much larger roles. The recovery of trade has been notably faster during the covid-19 crisis and led by exports as opposed to the much more important role played by domestic demand during the global financial crisis.
The Aftermath of Debt Surges

Debt in emerging markets and developing economies is at its highest level in half a century. In about 9 in 10 emerging markets and developing economies, debt is higher now than it was in 2010, and in half of the emerging markets and developing economies, debt is more than 30 percentage points of GDP higher than in 2010. This article reviews a menu of options that in the past have helped lower debt burdens. It examines orthodox options (enhancing growth, fiscal consolidation, privatization, and wealth taxation) and heterodox options (inflation, financial repression, and debt default and restructuring). The mix of feasible options depends on country characteristics and the type of debt. However, none of these options comes without political, economic, and social costs. The challenges associated with debt reduction raise questions of global governance, including to what extent advanced economies can better support emerging market and developing economies in cushioning prospective shocks. Expected final online publication date for the Annual Review of Economics, Volume 14 is August 2022. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
Tongxinluo Exerts Inhibitory Effects on Pyroptosis and Amyloid-β Peptide Accumulation after Cerebral Ischemia/Reperfusion in Rats

Amyloid-β peptide (Aβ) accumulation is a detrimental factor in cerebral ischemia/reperfusion (I/R) injuries accounting for dementia induced by ischemic stroke. In addition to blood brain barrier (BBB), the glymphatic system mediated by aquaporin-4 (AQP-4) on astrocytic endfeet functions as an important pathway for the clearance of Aβ in the brain. Cerebral I/R induced astrocytic pyroptosis potentially causes the AQP-4 polarization loss and dysfunctional BBB-glymphatic system exacerbating the accumulation of Aβ. Furthermore, Aβ toxicity has been identified as a trigger of pyroptosis and BBB damage, suggesting an amplified effect of Aβ accumulation after cerebral I/R. Therefore, based on our previous work, this study was designed to explore the intervention effects of Tongxinluo (TXL) on astrocytic pyroptosis and Aβ accumulation after cerebral I/R in rats. The results showed that TXL intervention obviously alleviated the degree of pyroptosis by downregulating expression levels of cleaved caspase-11/1, N-terminal gasdermin D, nucleotide-binding oligomerization domain-like receptors pyrin domain containing 3 (NLRP3), interleukin-6 (IL-6), and cleaved IL-1β and abated astrocytic pyroptosis after cerebral I/R. Moreover, TXL intervention facilitated to restore AQP-4 polarization and accordingly relieve Aβ accumulation around astrocytes in ischemic cortex and hippocampus as well as the formation of toxic Aβ (Aβ1–42 oligomer). Our study indicated that TXL intervention could exert protective effects on ischemic brain tissues against pyroptotic cell death, inhibit astrocytic pyroptosis, and reduce toxic Aβ accumulation around astrocytes in cerebral I/R injuries. Furthermore, our study provides biological evidence for the potential possibility of preventing and treating poststroke dementia with TXL in clinical practice.
Understanding user communication around loneliness on online forums

Increasingly, individuals experiencing loneliness are seeking support on online forums—some of which focus specifically on discussions around loneliness (loneliness forums); loneliness may influence how these individuals communicate in other online forums not focused on loneliness (non-loneliness forums). In order to provide effective and appropriate online interventions around loneliness, it is important to understand how users who publish posts in a loneliness forum communicate in the loneliness forum and non-loneliness forums they belong to. In this paper, using language features, the following analyses are conducted: (1) Posts published on an online loneliness forum on Reddit, /r/Lonely are compared to posts (published by the same users and around the same time period) on two Reddit online forums i.e. an advice seeking forum, /r/AskReddit and a forum focused on discussions around depression (depression forum), /r/depression. (2) Interventions related to loneliness may vary depending on if an individual is lonely and depressed or lonely but not depressed; language use differences in posts published in /r/Lonely by the following set of users are identified: (a) users who post in both /r/Lonely and a depression forum and (b) users who post in /r/Lonely but not in the depression forum. The findings from this work gain new insights, for example: (i) /r/Lonely users tend to seek advice/ask questions related to relationships in the advice seeking forum, /r/AskReddit and (ii) users who are members of the loneliness forum but not the depression forum tend to publish posts (on the loneliness forum) on topic themes related to work/job, however, those who are members of the loneliness and depression forums tend to use more words associated with anger, negation, death, and post on topic themes related to affection relative to relationships in their loneliness forum posts. Some of the findings from this work also align with prior work e.g. users who express loneliness in online forums tend to make more reference to self. These findings aid in gaining insights into how users communicate on these forums and their support needs, thereby informing loneliness interventions.