Miracle-dz/UniFAR-FTUs huggingface dataset:
Master Computer Science Investigating End-to-End Arrow-based operations in Apache Spark Name : Mariska IJpelaar Student

In the last few years humanity generated unimaginable amounts of data, and will only generate more. Coming up with efficient methods to process all this data is vital to keep up with production. While good progress was made in speeding up network and storage devices, CPU performance stayed behind. Thus, a lot of research focuses on improving data analytics efficiency. Apache Spark is a popular open-source analytics engine for large-scale data processing. It uses a row-wise format to represent its data. However, many analytical operations benefit more from a columnar format, such as Apache Arrow’s in-memory format. While previous work already tried to integrate Arrow into Spark, costly conversions from rowwise to columnar data could not be prevented. In this thesis, we investigate how one can best integrate Arrow’s format in Spark, without overhead from format-conversions. In this study, we analysed how previous work integrated Arrow’s format into Spark and what insights we can gather from it. From these insights, we created a Proof-of-Concept called Complete-Arrow-Spark (CAS). Within CAS we implemented a single end-to-end Arrow-based operator, to prove its feasibility. We solved many challenges to make Spark understand Arrow’s format. While we cannot process real-world applications yet, we produced promising results and found many areas of improvement.
The homotopy Lie algebra of symplectomorphism groups of 3-fold blow-ups of $(S^2 \times S^2, \sigma_{std} \oplus \sigma_{std}) $

We consider the 3-point blow-up of the manifold $ (S^2 \times S^2, \sigma \oplus \sigma)$ where $\sigma$ is the standard symplectic form which gives area 1 to the sphere $S^2$, and study its group of symplectomorphisms $\rm{Symp} ( S^2 \times S^2 \#\, 3\overline{\mathbb C\mathbb P}\,\! ^2, \omega)$. So far, the monotone case was studied by J. Evans and he proved that this group is contractible. Moreover, J. Li, T. J. Li and W. Wu showed that the group Symp$_{h}(S^2 \times S^2 \#\, 3\overline{ \mathbb C\mathbb P}\,\! ^2,\omega) $ of symplectomorphisms that act trivially on homology is always connected and recently they also computed its fundamental group. We describe, in full detail, the rational homotopy Lie algebra of this group. We show that some particular circle actions contained in the symplectomorphism group generate its full topology. More precisely, they give the generators of the homotopy graded Lie algebra of $\rm{Symp} (S^2 \times S^2 \#\, 3\overline{ \mathbb C\mathbb P}\,\! ^2, \omega)$. Our study depends on Karshon's classification of Hamiltonian circle actions and the inflation technique introduced by Lalonde-McDuff. As an application, we deduce the rank of the homotopy groups of $\rm{Symp}({\mathbb C\mathbb P}^2 \#\, 5\overline{\mathbb C\mathbb P}\,\! ^2, \tilde \omega)$, in the case of small blow-ups.
Sur l'existence des analyses multi-résolutions en théorie des ondelettes

On montre qu'une base d'ondelettes (? j,k) de L2(R) avec une fonction mere ? holderienne a support compact provient necessairement d'une analyse multi-resolution. La fonction-pere f a alors la meme regularite que la fonction ? et peut etre choisie a support compact.
A Study of Larynx Height in Speech Using the Thyro-Umbrometer

The thyro‐umbrometer consists of an array of seven rectangular photocells 14 in. × 1 14in. , placed on one side of the subject's neck (arranged so the long axis of the photocells is normal to the surface of the throat) with a point light source on the other side. The shadow of the subject's thyroid prominence is cast on the photocells. The output of each photocell is fed to a small computer, which locates the laryngeal prominence at the level of that photocell producing the least voltage. Preliminary results in tracking the larynx height and F0 reveal that (1) as has been widely reported in the literature, larynx height and F0 are positively correlated, but (2) larynx height is greatly affected by vowel and consonant articulation; specifically, (3) voiceless stops have consistently higher laryngeal position than phonetically similar utterances containing voiced stops. [Supported by the National Science Foundation. ]
Generalized Robin–Neumann explicit coupling schemes for incompressible fluid‐structure interaction: Stability analysis and numerics

We introduce a new class of explicit coupling schemes for the numerical solution of fluid‐structure interaction problems involving a viscous incompressible fluid and an elastic structure. These methods generalize the arguments reported in [Comput. Methods Appl. Mech. Engrg. , 267:566–593, 2013, Numer. Math., 123(1):21–65, 2013] to the case of the coupling with thick‐walled structures. The basic idea lies in the derivation of an intrinsic interface Robin consistency at the space semi‐discrete level, using a lumped‐mass approximation in the structure. The fluid–solid splitting is then performed through appropriate extrapolations of the solid velocity and stress on the interface. Based on these methods, a new, parameter‐free, Robin–Neumann iterative procedure is also proposed for the partitioned solution of implicit coupling. A priori energy estimates, guaranteeing the stability of the schemes and the convergence of the iterative procedure, are established within a representative linear setting. The accuracy and performance of the methods are illustrated in several numerical examples. Copyright © 2014 John Wiley & Sons, Ltd.
Mycobiome structure does not affect field litter decomposition in Eucalyptus and Acacia plantations

Mixed tree plantations have been studied because of their potential to improve biomass production, ecosystem diversity, and soil quality. One example is a mixture of Eucalyptus and Acacia trees, which is a promising strategy to improve microbial diversity and nutrient cycling in soil. We examined how a mixture of these species may influence the biochemical attributes and fungal community associated with leaf litter, and the effects on litter decomposition. We studied the litter from pure and mixed plantations, evaluating the effects of plant material and incubation site on the mycobiome and decomposition rate using litterbags incubated in situ. Our central hypothesis was litter fungal community would change according to incubation site, and it would interfere in litter decomposition rate. Both the plant material and the incubation locale significantly affected the litter decomposition. The origin of the litter was the main modulator of the mycobiome, with distinct communities from one plant species to another. The community changed with the incubation time but the incubation site did not influence the mycobiome community. Our data showed that litter and soil did not share the main elements of the community. Contrary to our hypothesis, the microbial community structure and diversity lacked any association with the decomposition rate. The differences in the decomposition pattern are explained basically as a function of the exchange of nitrogen compounds between the litter.
Meta-optimized Contrastive Learning for Sequential Recommendation

Contrastive Learning (CL) performances as a rising approach to address the challenge of sparse and noisy recommendation data. Although having achieved promising results, most existing CL methods only perform either hand-crafted data or model augmentation for generating contrastive pairs to find a proper augmentation operation for different datasets, which makes the model hard to generalize. Additionally, since insufficient input data may lead the encoder to learn collapsed embeddings, these CL methods expect a relatively large number of training data (e.g., large batch size or memory bank) to contrast. However, not all contrastive pairs are always informative and discriminative enough for the training processing. Therefore, a more general CL-based recommendation model called Meta-optimized Contrastive Learning for sequential Recommendation (MCLRec) is proposed in this work. By applying both data augmentation and learnable model augmentation operations, this work innovates the standard CL framework by contrasting data and model augmented views for adaptively capturing the informative features hidden in stochastic data augmentation. Moreover, MCLRec utilizes a meta-learning manner to guide the updating of the model augmenters, which helps to improve the quality of contrastive pairs without enlarging the amount of input data. Finally, a contrastive regularization term is considered to encourage the augmentation model to generate more informative augmented views and avoid too similar contrastive pairs within the meta updating. The experimental results on commonly used datasets validate the effectiveness of MCLRec.
Designing Localization Algorithms for Wireless Sensor Networks: A Geometric Approach

Localization is one of the most important issues in wireless sensor networks. Localization problems are more challenging when line-of-sight signals between anchors and sensors are not available. We approach geometrically towards localization of static sensors based on non-line-of-sight signals. Two range-based deterministic algorithms are proposed for localization using static anchors. The first algorithm assumes presence of line-of-sight and one-bound signals. Then we relax the assumption and propose another algorithm which localizes sensors based on receiving unknown-bound signals. Usually, large number of static anchors are required to localize all sensors in a network. Measurement errors are unavoidable in range-based localization algorithms. To overcome these problems, range-free localization algorithms using mobile anchors are proposed in literature, where a mobile anchor localizes all static sensors traveling through the sensor network. There are two different aspects of the existing algorithms. One aspect is to improve localization accuracy whereas the other tries to reduce path lengths of mobile anchors. The challenge is to design a movement strategy for mobile anchors which reduces path length while meeting the requirements of a range-free technique that yields better positioning accuracy. We propose a distributed range-free path planning algorithm for mobile anchors to localize sensors in arbitrary connected network. Another path planning algorithm for mobile anchors is proposed to localize sensors in a rectangular region with known boundary. The algorithms are designed in such a way that sensors can use an existing range-free algorithm for better positioning accuracy. Both these algorithms guarantee full localization. In mobile wireless sensor networks, mobile sensors are needed to localize frequently unlike the static sensors. Mobility of the sensors incur additional challenges for localization. We propose a localization algorithm for mobile sensors assuming sensors do not change direction during localization. An upper bound on localization error is ensured by this algorithm. Then we relax the assumption and propose another algorithm which localizes in presence of obstacles. Both algorithms are range-free, distributed and deterministic. Each of our proposed algorithms in this thesis are compared with recent works to show better performance. vii TH-1358_09612305
Unified Deep Learning

With the increase in depth and complexity, deep learning networks have made significant progress in various directions. However, the theoretical understanding of deep learning is still incomplete. Early research successfully proved the universal approximation theorem for linear networks, but these proofs were limited to linear networks. Subsequent studies attempted to prove the approximation properties of convolutions and Transformers, but the proof processes often relied on complex assumptions or were very intricate. This paper aims to propose a unified approach to demonstrate that multi-layer networks composed of convolutions and Transformers are specific realizations of the universal approximation theorem. This approach does not require any assumptions and proves that most networks composed of convolutions and Transformers can be mathematically written in the same form as the fully proven universal approximation theorem, thus establishing them as specific implementations of the universal approximation theorem. This bridges the gap between deep learning practice and theoretical understanding. The method of unifying them is to represent these network architectures (linear, convolutional, and Transformer) in matrix-vector form, hence this unified approach is called the matrix-vector method. This paper takes an important step towards unifying the entire field of deep learning. It deepens our theoretical understanding and reveals the fundamental principles behind the exceptional performance of these networks. It also paves the way for exploring new research directions and optimizing the learning process in various deep learning applications.
Valuation of Regulating Services of Ecosystems: Methodology and Applications

Part 1: Concepts 1. An introduction to the valuation of regulating services Pushpam Kumar and Michael D. Wood 2. Valuing Ecosystem Services: Benefits, values, space and time Brendan Fisher, Ian Bateman and R. Kerry Turner 3. Ecosystem services: managing trade-offs between provisioning and regulating services Thomas Elmqvist, Magnus Tuvendal, Jagdish Krishnaswamy and Kristoffer Hylander 4. The "Ecosystem Service Framework": A Critical Assessment R. David Simpson Part 2: Methodological applications 5. Evaluating the economic impacts of water harvesting in Burkina Faso Rodney B.W. Smith, Laura A. Hildreth and Kimsey Savadago 6. Accounting for regulating services Karl-Goran Maler, Sara Aniyar and Asa Jansson 7. Valuation of Ecosystem Services in Coastal Ecosystems: Asian and European perspectives Premachandra Wattage 8. Valuing the Storm Protection Services of the Mangroves: Methodological and Data challenges Saudamini Das 9. European Forests and Carbon Sequestration Services: An Economic Assessment of Climate Change Impacts Helen Ding, Paulo A.L. D. Nunes and Sonja Teelucksingh 10. Valuing the Services of Coral Reef Systems for Sustainable Coastal Management: A Case Study of the Gulf of Kachchh, India Arun M. Dixit, Lalit Kumar, Pushpam Kumar and Kinjal Pathak Part 3: Synthesis 11. Institutions and Ecosystem Functions: The Case of Keti Bunder, Pakistan John M. Gowdy and Aneel Salman 12. Valuation of Ecosystem Services: methods, opportunities and policy implications Nicolas Kosoy, Makiko Yashiro, Carlota Molinero and Anantha Duraiappah 13. Conclusions on the valuation of regulating services: current status and future perspectives Pushpam Kumar and Michael D. Wood
A Characterization of the Orientations of Ternary Matroids

A matroid or oriented matroid is dyadic if it has a rational representation with all nonzero subdeterminants in {±2k:k? Z}. Our main theorem is that an oriented matroid is dyadic if and only if the underlying matroid is ternary. A consequence of our theorem is the recent result of G. Whittle that a rational matroid is dyadic if and only if it is ternary. Along the way, we establish that each whirl has three inequivalent orientations. Furthermore, except for the rank-3 whirl, no pair of these are isomorphic.
Fast Global Kernel Density Mode Seeking: Applications to Localization and Tracking

Tracking objects in video using the mean shift (MS) technique has been the subject of considerable attention. In this work, we aim to remedy one of its shortcomings. MS, like other gradient ascent optimization methods, is designed to find local modes. In many situations, however, we seek the global mode of a density function. The standard MS tracker assumes that the initialization point falls within the basin of attraction of the desired mode. When tracking objects in video this assumption may not hold, particularly when the target's displacement between successive frames is large. In this case, the local and global modes do not correspond and the tracker is likely to fail. A novel multibandwidth MS procedure is proposed which converges to the global mode of the density function, regardless of the initialization point. We term the procedure annealed MS, as it shares similarities with the annealed importance sampling procedure. The bandwidth of the procedure plays the same role as the temperature in conventional annealing. We observe that an over-smoothed density function with a sufficiently large bandwidth is unimodal. Using a continuation principle, the influence of the global peak in the density function is introduced gradually. In this way, the global maximum is more reliably located. Since it is imperative that the computational complexity is minimal for real-time applications, such as visual tracking, we also propose an accelerated version of the algorithm. This significantly decreases the number of iterations required to achieve convergence. We show on various data sets that the proposed algorithm offers considerable promise in reliably and rapidly finding the true object location when initialized from a distant point
Mff‐Dependent Mitochondrial Fission Contributes to the Pathogenesis of Cardiac Microvasculature Ischemia/Reperfusion Injury via Induction of mROS‐Mediated Cardiolipin Oxidation and HK2/VDAC1 Disassociation‐Involved mPTP Opening

Background The cardiac microvascular system ischemia/reperfusion injury following percutaneous coronary intervention is a clinical thorny problem. This study explores the mechanisms by which ischemia/reperfusion injury induces cardiac microcirculation collapse. Methods and Results In wild‐type mice, mitochondrial fission factor (Mff) expression increased in response to acute microvascular ischemia/reperfusion injury. Compared with wild‐type mice, homozygous Mff‐deficient (Mffgt) mice exhibited a smaller infarcted area, restored cardiac function, improved blood flow, and reduced microcirculation perfusion defects. Histopathology analysis demonstrated that cardiac microcirculation endothelial cells (CMECs) in Mffgt mice had an intact endothelial barrier, recovered phospho‐endothelial nitric oxide synthase production, opened lumen, undivided mitochondrial structures, and less CMEC death. In vitro, Mff‐deficient CMECs (derived from Mffgt mice or Mff small interfering RNA–treated) demonstrated less mitochondrial fission and mitochondrial‐dependent apoptosis compared with cells derived from wild‐type mice. The loss of Mff inhibited mitochondrial permeability transition pore opening via blocking the oligomerization of voltage‐dependent anion channel 1 and subsequent hexokinase 2 separation from mitochondria. Moreover, Mff deficiency reduced the cyt‐c leakage into the cytoplasm by alleviating cardiolipin oxidation resulting from damage to the electron transport chain complexes and mitochondrial reactive oxygen species overproduction. Conclusions This evidence clearly illustrates that microcirculatory ischemia/reperfusion injury can be attributed to Mff‐dependent mitochondrial fission via voltage‐dependent anion channel 1/hexokinase 2–mediated mitochondrial permeability transition pore opening and mitochondrial reactive oxygen species/cardiolipin involved cyt‐c release.
Journal of Cerebral Blood Flow and Metabolism Substrate Utilization and Brain Development

Since the realization over a decade ago (Owen et aI., 1967) that the brain of the human adult can function, apparently normally, when up to two­ thirds of the substrates supplied are ketone bodies rather than glucose, consideration of substrate utili­ zation has to take into account which substrates are being used, as well as how much of each is being used. These questions have particular relevance throughout the period of brain development, both pre-and postnatally, since circumstances may arise under which an adequate supply of blood-borne glucose is compromised. Previous reviews on energy metabolism in the developing brain have emphasized the human baby and possible problems of adequate nutrition In the present review, the aim has been to detail quantita­ tive data for several animal species without neces­ sarily implying that all such data are directly rele­ vant to man. Fortunately, information available on young babies and children is sufficiently com­ prehensive to allow a direct comparison with other species. Arteriovenous differences provide the most con­ vincing evidence of net movements of substances between the blood and brain. Of their own they are informative, but they are most valuable when com­ bined with measurements of cerebral blood flow (CBF) so that rates of influx and efflux can be cal­ culated. The demonstration of net influx of a partic­ ular substrate leaves open the question of its meta­ bolic fate, which has to be studied in other ways (one way being the use of radioactive isotopes, which will be discussed below). Studies that include data on arteriovenous ex­ traction of substrates by the developing brain of sev­ eral species (man, baboon, dog, cow, sheep, and rat) are listed in Table 1. In many of the studies, subjects were anaesthetized and the type of anaesthetic used is indicated. Also indicated is whether or not CBF was determined. Humans The two earliest studies that demonstrated most clearly the ability of the brains of newborns and infants to use substrates other than glucose were those by Persson et ai. (1972) and Kraus et ai. (1974). Both studies showed that the ketone bodies, acetoacetate and D-3-hydroxybutyrate, were taken up by the brain in addition to glucose, even though the extent of ketonaemia was modest. For example, in newborns, after a fasting period of about 6 h av­ erage arterial concentrations for acetoacetate of 0.10 roM and of D-3-hydroxybutyrate of 0.16 roM were found with …
A taxonomy of anomalies in backbone network traffic

The potential threat of network anomalies on Internet has led to a constant effort by the research community to design reliable detection methods. Detection is not enough, however, because network administrators need additional information on the nature of events occurring in a network. Several works try to classify detected events or establish a taxonomy of known events. But, these works are non-overlapping in terms of anomaly type coverage. On the one hand, existing classification methods use a limited set of labels. On the other hand, taxonomies often target a single type of anomaly or, when they have wider scope, fail to present the full spectrum of what really happens in the wild. We thus present a new taxonomy of network anomalies with wide coverage of existing work. We also provide a set of signatures that assign taxonomy labels to events. We present a preliminary study applying this taxonomy with six years of real network traffic from the MAWI repository. We classify previously documented anomalous events and draw to main conclusions. First, the taxonomy-based analysis provides new insights regarding events previous classified by heuristic rule labeling. For example, some RST events are now classified as network scan response and the majority of ICMP events are split into network scans and network scan responses. Moreover, some previously unknown events now account for a substantial number of all UDP network scans, network scan responses and port scans. Second, the number of unknown events decreases from 20 to 10% of all events with the proposed taxonomy as compared to the heuristic approach.