Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulating Fatigue Crack Growth including Thermal Eﬀects Using the Phase Field Method

Putting a mechanical structure under repeated cyclic loading can lead to fatigue crack initiation and propagation in materials. In engineering processes, a fatigue crack evolution behavior can be very complicated when the structure is in a complex environment. It has been shown that internal friction is one of the most important factors for the fatigue behavior of materials. However, there is still a lack of studies on how to predict the inﬂuences of internal friction on fatigue crack evolution. In this work, we show that the phase ﬁeld model provides an elegant solution for structures under diﬀerent loading frequencies and temperatures. Although the phase ﬁeld fatigue model has been studied for years for mechanical loading situations, the question of how to include thermal fatigue eﬀect remains open. In this work, we add thermal stresses to the phase ﬁeld model as the second fatigue driving force. It is shown that the model is able to predict thermal fatigue behavior.
Role of Competitive Edge, Marketing Facilities, Financial Assistance, and Government Supports on SME Development in Bangladesh

The major driver of a country's ability to achieve social progress and a sustainable economy is industrialization. Considering that entrepreneurship is essential for launching new businesses that animate and revive the economy. Notably, in Bangladesh, the role of Bangladesh Small and Cottage Industry Corporation (BSCIC) is the main catalyst for developing sustainable entrepreneurship. However, there is criticism that the standpoints of small and medium-sized businesses of the BSCIC entrepreneurs are under the assistance of the Government. Therefore, it is essential to see the impacts of other factors on the performance of the BSCIC Entrepreneurs. Therefore, this study aims to explore the impacts of four factors, i.e., Competitive edge with large-scale industry, financial technical support, Marketing initiatives, and Government initiatives, on the performance of BSCIC Entrepreneurs. This study collected 65 sample data based on a questionnaire survey and the data was analyzed based on structural equation modeling. The result shows that marketing initiatives have a positive impact, but a competitive edge with large-scale industry as well as government support has negative impacts. Whereas the financial support does not show any impact on entrepreneurs’ performance. This study will help the entrepreneurs and policymakers improve the entrepreneurial development in Bangladesh.
Unlocking Comparative Plant Scoring with Siamese Neural Networks and Pairwise Pseudo Labelling

Phenotypic assessment of plants for herbicide discovery is a complex visual task and involves the comparison of a non-treated plant to those treated with herbicides to assign a phytotoxicity score. It is often subjective and difficult to quantify by human observers. Employing novel computer vision approaches using neural networks in order to be non-subjective and truly quantitative offers advantages for data quality, leading to improved decision making.In this paper we present a deep learning approach for comparative plant assessment using Siamese neural networks, an architecture that takes pairs of images as inputs, and we overcome the hurdles of data collection by proposing a novel pseudo-labelling approach for combining different pairs of input images. We demonstrate a high level of accuracy with this method, comparable to human scoring, and present a series of experiments grading Amaranthus retroflexus weeds using our trained model.
Signatures of Genetic Variation in Human microRNAs Point to Processes of Positive Selection and Population-speci�c Disease Risks

The occurrence of natural variation in human microRNAs has been the focus of numerous studies during the last twenty years. Most of them have been centered on the role of speci�c mutations in disease, while a minor proportion seek to analyse microRNA diversity in the genomes of human populations. We investigate the latest human microRNA annotations in the light of the most updated catalog of genetic variation provided by the 1000 Genomes Project. By means of the in silico analysis of microRNA variants we show that the level of evolutionary constraint of these sequences is governed by the interplay of different factors, like their evolutionary age or genomic location. The role of mutations in the shaping of microRNA-driven regulatory interactions is emphasized with the acknowledgement that, while the whole microRNA sequence is highly conserved, the seed region shows a pattern of higher genetic diversity that appears to be caused by the dramatic frequency shifts of a fraction of human microRNAs. We highlight the participation of these microRNAs in population-speci�c processes by identifying that not only the seed, but also the loop, are particularly differentiated regions among human populations. The quantitative computational comparison of signatures of population differentiation showed that candidate microRNAs with the largest differences are enriched in variants related to gene expression levels (eQTLs), selective sweeps and pathological processes. We explore the implication of these evolutionary-driven microRNAs and their single nucleotide variants in human diseases, such as different types of cancer, and discuss their role in population-speci�c disease risk.
Palaeogeographical reconstruction of the battle terrain in Ancient Thermopylae, Greece

The battle of Thermopylae (Malian Gulf, Central Greece) is one of the most famous ancient battles in European and world history. It took place on a narrow strip of land where it was possible for a few thousand Greeks to fight against the Persian army. The geomorphology of the battle terrain has changed significantly since ancient times due to the Sperchios River delta progradation. In this work an attempt is being made to undertake a palaeogeographical reconstruction of the pass and the battle terrain in Ancient Thermopylae in order to set out new information based on new geoarchaeological data. Geomorphological data in combination with geological, stratigraphical, paleontological data of an extensive drilling project supported by electrical resistivity tomography led to the determination of the palaeoenvironmental changes in the area of the Thermopylae Pass and for the palaeogeographical reconstruction of the battle terrain in ancient Thermopylae. The results of this research showed that in the “middle gate” of the Thermopylae Pass between the land and the sea there was a freshwater marsh supplied with large quantities of warm water coming from the thermal springs. The chronostratigraphical and sea level data confirmed its existence when the battle had taken place in 480 BC. This also confirms Herodotus' description that the road eastwards of Thermopylae was shut in by the sea and by marshes.
2023-06773 - Internship Deep learning techniques for radio identification (possibility of PhD afterwards)

With the popularisation of software defined radios (SDRs), an malevolent actor can deploy radio systems for interfering with legitimate communications, communicating on unlicensed bands and listening to private communications. In this proposed PhD work we target in a first moment spectrum sensing capabilities, that can be used to automatically locate and classify opponent transmissions, characterising it in terms of center frequency, occupied bandwidth, activity pattern, modulation and coding schemes, frame structure and more. Then we will study the identification problem, trying to uniquely single out individual transmitters among all transmitters. The proposed work will (i) create good datasets to train and test systems for spectrum sensing and (ii) develop deep learning (DL) systems for spectrum sensing/classification and identification.
BIS Working

The causal eﬀect of the European Central Bank’s corporate bond purchase program on bond spreads in the primary market is evaluated, making use of a novel regression discontinuity design. The results indicate that the program did not, on average, permanently alter the yield spreads of eligible bonds relative to those of noneligible. Combined with evidence from previous studies, this ﬁnding suggests the eﬀects of central bank asset purchase programs are in no way limited to the prices of the speciﬁc assets acquired.
Aseismic transient driving the swarm-like seismic sequence in the Pollino range, Southern Italy

Tectonic earthquake swarms challenge our understanding of earthquake processes since it is difficult to link observations to the underlying physical mechanisms and to assess the hazard they pose. Transient forcing is thought to initiate and drive the spatio-temporal release of energy during swarms. The nature of the transient forcing may vary across sequences and range from aseismic creeping or transient slip to diffusion of pore pressure pulses to fluid redistribution and migration within the seismogenic crust. Distinguishing between such forcing mechanisms may be critical to reduce epistemic uncertainties in the assessment of hazard due to seismic swarms, because it can provide information on the frequency-magnitude distribution of the earthquakes (often deviating from the assumed Gutenberg-Richter relation) and on the expected source parameters influencing the ground motion (for example the stress drop). Here we study the ongoing Pollino range (Southern Italy) seismic swarm, a long-lasting seismic sequence with more than five thousand events recorded and located since October 2010. The two largest shocks (magnitude M-w = 4.2 and M-w = 5.1) are among the largest earthquakes ever recorded in an area which represents a seismic gap in the Italian historical earthquake catalogue. We investigate the geometrical, mechanical and statistical characteristics of the largest earthquakes and of the entire swarm. We calculate the focal mechanisms of the M-l > 3 events in the sequence and the transfer of Coulomb stress on nearby known faults and analyse the statistics of the earthquake catalogue. We find that only 25 per cent of the earthquakes in the sequence can be explained as aftershocks, and the remaining 75 per cent may be attributed to a transient forcing. The b-values change in time throughout the sequence, with low b-values correlated with the period of highest rate of activity and with the occurrence of the largest shock. In the light of recent studies on the palaeoseismic and historical activity in the Pollino area, we identify two scenarios consistent with the observations and our analysis: This and past seismic swarms may have been 'passive' features, with small fault patches failing on largely locked faults, or may have been accompanied by an 'active', largely aseismic, release of a large portion of the accumulated tectonic strain. Those scenarios have very different implications for the seismic hazard of the area.
Extended Path Space Manifolds for Physically Based Differentiable Rendering

Physically based differentiable rendering has become an increasingly important topic in recent years. A common pipeline computes local color derivatives of light paths or pixels with respect to arbitrary scene parameters, and enables optimizing or recovering the scene parameters through iterative gradient descent by minimizing the difference between rendered and target images. However, existing approaches cannot robustly handle complex illumination effects including reflections, refractions, caustics, shadows, and highlights, especially when the initial and target locations of such illumination effects are not close to each other in the image space. To address this problem, we propose a novel data structure named extended path space manifolds. The manifolds are defined in the combined space of path vertices and scene parameters. By enforcing geometric constraints, the path vertices could be implicitly and uniquely determined by perturbed scene parameters. This enables the manifold to track specific illumination effects and the corresponding paths, i.e., specular paths will still be specular paths after scene parameters are perturbed. Besides, the path derivatives with respect to scene parameters could be computed by solving small linear systems. We further propose a physically based differentiable rendering method built upon the theoretical results of extended path space manifolds. By incorporating the path derivatives computed from the manifolds and an optimal transport based loss function, our method is demonstrated to be more effective and robust than state-of-the-art approaches in inverse rendering applications involving complex illumination effects.
Pristine nonmare rocks and the nature of the lunar crust

It is shown that the interdisciplinary study of the nonmare lunar rocks based on trace element, major element, and isotopic data plus petrographic evidence can succeed in amassing a large suite of demonstrably pristine rocks, and that the relative numbers of these rocks are not in accord with statistics amassed on soil fragments and glasses. The term 'pristine' is taken to mean rocks with primary compositions (albeit not necessarily textures) produced by lunar endogenous igneous processes. Melt rocks and crystalline matrix breccias produced by impact processes are excluded. A petrographic synonym for pristine would be 'unremelted, monomict'. It is found that anorthositic norites and noritic anorthosites were rare as primary nonmare rocks. Mechanical mixing appears to have been the dominant petrogenetic process on the highlands.
Monitoring Measurements from the Jason-1 Microwave Radiometer and Independent Validation with GPS

The Jason-1 Microwave Radiometer (JMR) provides measurements of the wet troposphere content to correct the altimetric range measurement for the associated path delay. Various techniques are used to monitor the JMR wet troposphere path delays, with measurements of zenith troposphere content from terrestrial GPS sites used as an independent verification technique. Results indicate that an unexpected offset of approximately +4.1 ± 1.2 mm (drier) emerged in the JMR measurements of wet path delay between cycles 28–32 of the Jason-1 mission, and that the measurements may be drifting at a rate of approximately −0.5 mm/year. These anomalies are shown to be caused by a −0.7 K offset in 23.8 GHz brightness temperatures between cycles 28–32, and a 0.16 ± 0.04 and −0.45 ± 0.08 K/year drift in the 18.7 and 34.0 GHz brightness temperatures, respectively. Intercomparison of the 3-Hz JMR brightness temperature measurements show that they have been drifting with respect to each other, and that a dependence on yaw-steering regime is present in these measurements. An offset of 0.5 m/s between cycles 28–32 and a drift of approximately 0.5 m/s/year in the JMR wind speed measurements is also associated with these anomalies in the 1-Hz brightness temperatures. These errors in JMR wind speeds presently have a negligible impact on the retrieved JMR path delays.
Classification of Brain Tumor Images Using CNN

A brain tumor is a serious malignant condition caused by unregulated as well as aberrant cell partitioning. Recent advances in deep learning have aided the healthcare business, particularly, diagnostic imaging for the diagnosis of numerous disorders. The most frequent and widely utilized machine learning model for image recognition is probably task CNN. Similarly, in our study, we categorize brain MRI scanning images using CNN and data augmentation and image processing techniques. We compared the performance of the scratch CNN model with that of pretrained VGG-16 models using transfer learning. Even though the investigation is carried out on a small dataset, the results indicate that our model's accuracy is quite successful and has extremely low complexity rates, achieving 100 percent accuracy compared to 96 percent accuracy for VGG-16. Compared to existing pretrained methods, our model uses much less processing resources and produces substantially greater accuracy.
The effect of viscous drag on damped simple harmonic motion

Dynamic viscosity is a quantity that describes the magnitude of a fluid’s internal friction or thickness. Traditionally, scientists measure this quantity by either calculating the terminal velocity of a falling sphere or the time a liquid takes to flow through a capillary tube. However, they have yet to conduct much research on finding this quantity through viscous damped simple harmonic motion. This phenomenon occurs when the movement of an oscillator experiencing Hooke’s law dissipates at a rate defined by the damping coefficient due to a fluid’s external drag force. The present study hypothesized that the relationship between the dynamic viscosity and the damping coefficient is positively correlated. To test this hypothesis, we computed the dynamic viscosities of glycerol-water mixtures of varying mass concentrations and filmed the oscillations of a vertical-spring mass system in each of these mixtures. We then determined the system’s damping coefficients through Vernier’s Logger Pro video analysis feature and implemented inferential statistics on a regression between these damping coefficients and the mixtures’ dynamic viscosities. The results through these methods demonstrated not only compelling evidence in favor of this hypothesis but also an alternative way to estimate a fluid’s dynamic viscosity through a least-squares regression line. With future experimentation, these results can help prepare shock absorbers for vehicle and structural engineering practices.
The in�uence of South East Asia Forest Fires on ambient Particulate Matter concentrations in Singapore: An Ecological Study using Random Forest and Vector Autoregressive Models

Background In recent decades, haze, due to biomass burning, has become a recurring problem in Southeast Asia (SEA). Haze degrades air quality, thus, causing detrimental effects on human health. Exposure to atmospheric particulate matter (PM) remains an important public health concern. Methods In this paper, we examined the long-term seasonality of PM 2.5 and PM 10 in Singapore. To study the association between forest �res in SEA and air quality in Singapore, we built two machine learning models, including the random forest (RF) model and the vector autoregressive (VAR) model, using a benchmark air quality dataset containing daily PM 2.5 and PM 10 from 2009 to 2018. Furthermore, we incorporated weather parameters as independent variables, to understand their effects on air quality. Results We observed two annual peaks, one in the middle of the year and one at the end of the year for both PM 2.5 and PM 10 . Singapore was more affected by �res from Kalimantan compared to �res from other SEA countries. In our experimental results, VAR models performed better than RF with Mean Absolute Percentage Error (MAPE) values being 0.8% and 6.1% lower for PM 2.5 and PM 10, respectively. Conclusions Our study �ndings suggest that air quality in Singapore can be reasonably anticipated with predictive models that incorporate information on forest �res and weather variations. The public communication of anticipated air quality at the national level bene�t who are at higher risk of experiencing poorer health due to poorer air quality.
Tropical Pacific control of intraseasonal oscillations off Chile by way of oceanic and atmospheric pathways

Sea level, current, satellite wind data and a simple model of wind‐forced, low frequency waves are used to study the origins of strong, observed intraseasonal variability in the ocean and atmosphere off Chile. There intraseasonal wind fluctuations are correlated to wind fluctuations in the equatorial Pacific, associated with the Madden‐Julian Oscillation. Results suggest intraseasonal teleconnections via two distinct atmospheric pathways. Very simple model simulations forced by satellite winds from the equator and the South American coast compare well with observed fluctuations of currents and sea level off central Chile. There most of this intraseasonal variability, particularly during summer and during El Niño events, arrives as free, oceanic, coastal trapped waves via oceanic, equatorial Kelvin waves, forced by tropical Pacific winds. South of 20°S, some oceanic intraseasonal variability is forced by local winds associated with the atmospheric teleconnections.
SOCIO-ECOLOGICAL CORRELATES OF EXERCISE AT CARDIAC 3 REHABILITATION COMPLETION

52 Objectives: To describe: (1) the amount of physical activity (PA) in cardiac rehabilitation (CR) 53 graduates by sex, and (2) the correlates of their PA. 54 Design: Secondary analysis of baseline data from a randomized trial was undertaken. Graduates 55 were recruited from 3 CR programs. Participants completed a questionnaire which assessed 56 constructs from the Socio-ecological model (i.e., individual-level, social and physical-57 environmental levels). PA was measured objectively using an ActiGraph GT3X accelerometer. 58 Multi-level modeling was performed. 59 Results: 255 patients consented, of which 200 (78.4%) completed the survey and provided valid 60 accelerometer data. Participants self-reported engaging in a mean of 184.51±129.10 (standard 61 deviation) minutes of moderate-to-vigorous-intensity PA (MVPA) per week (with men engaging 62 in more than women, p<.05). Accelerometer data revealed participants engaged in 63 169.65±136.49 minutes of MVPA/week, with 43 (25.1%) meeting recommendations. In the 64 mixed models, the socio-ecological correlate significantly related to greater self-reported MVPA 65 was self-regulation (p=.01; 95%CI=.07-.43); the correlate of accelerometer-derived MVPA was 66 neighborhood aesthetics (p=.02; 95%CI=.03-.39). 67 Conclusions: Approximately one-quarter of CR program completers are achieving MVPA 68 recommendations, although two-thirds perceive they are. CR programs should exploit 69 accelerometry, and promote self-regulation skills, namely self-monitoring, goal-setting, positive 70 reinforcement, time management and relapse prevention. Patients should be encouraged to 71 exercise in pleasing locations.
Fully Composable Homomorphic Encryption

A homomorphic encryption scheme is a cryptosystem that supports the evaluation of arbitrary functions or programs on encrypted data, without using the secret decryption key. More specifically, an encryption scheme is F-homomorphic (for some class of functions F) if for any f :Mw → M in F and message vector m ∈ Mw, given c = Enc(m), one can publicly compute a ciphertext c = Eval(f, c) that decrypts to Dec(c) = f(m). (See Figure 1 and Definition 5.) An encryption scheme is called fully homomorphic if it supports the computation of arbitrary programs, i.e., if F is the set of all possibly (efficiently computable) functions. This is the standard notion of fully homomorphic encryption (FHE), as used by Gentry’s first FHE candidate construction [Gen09b, Gen09a], as well as much subsequent work. (E.g., see recent surveys [Hal17, Bra19].) While this definition closely models the intended use of homomorphic encryption schemes in typical applications, it has some shortcomings. Stronger notions of security have also been considered (e.g., providing function privacy [Gen09b, BPMW16, OPP14, DD22, DS16]) but they are typically understood as “optional” features, and can often be obtained by extending a scheme satisfying the basic definition. In this paper we focus on a different issue: composability, i.e., the ability to concatenate (or, more generally, combine) different homomorphic computations together. The importance of composability, and the fact that it is not guaranteed by the standard definition of homomorphic correctness, was first pointed out by Gentry, Halevi and Vaikuntanathan [GHV10]. In fact, in a regular homomorphic encryption scheme, the evaluation function Evalf may in general use different types of input and output ciphertexts, so that the output of Evalf cannot even be used as input to another homomorphic evaluation