Miracle-dz/UniFAR-FTUs huggingface dataset:
A Discussion about Explainable Inference on Sequential Data via Memory-Tracking

The recent explosion of deep learning techniques boosted the application of Artificial Intelligence in a variety of domains, thanks to their high performance. However, performance comes at the cost of interpretability: deep models contain hundreds of nested non-linear operations that make it impossible to keep track of the chain of steps that bring to a given answer. In our recently published paper [1], we propose a method to improve the interpretability of a class of deep models, namely Memory Augmented Neural Networks (MANNs), when dealing with sequential data. Exploiting the capability of MANNs to store and access data in external memory, tracking the process, and connecting this information to the input sequence, our method extracts the most relevant sub-sequences that explain the answer. We evaluate our approach both on a modified T-maze [2, 3] and on the Story Cloze Test [4], obtaining promising results.
Is Your Smartphone Really Safe? A Wake-up Call on Android Antivirus Software Effectiveness

A decade ago, researchers raised severe concerns about Android smartphones’ security by extensively assessing and recognising the limitations of Android antivirus software. Considering the significant increase in the economic role of smartphones in recent years, we would expect that security measures are significantly improved by now. To test this assumption, we conducted a relatively extensive study to evaluate the effectiveness of off-the-shelf antivirus software in detecting malicious applications injected into legitimate Android applications. We specifically repackaged seven widely used Android applications with 100 obfuscated malware instances. We submitted the 700 samples to the VirusTotal web portal, testing the effectiveness of the over 70 free and commercial antiviruses available in detecting them. For the obfuscation part, we intentionally employed publicly available tools that could be used by “just” a tech-savvy adversary. We used a combination of well-known and novel (but still simple) obfuscation techniques. Surprisingly (or perhaps unsurprisingly? ), our findings indicate that almost 76% of the samples went utterly undetected. Even when our samples were detected, this occurred for a handful (never more than 4) of Android antivirus software available on VirusTotal. This lack of awareness of the effectiveness of Android antivirus is critical because the false sense of security given by antivirus software could prompt users to install applications from untrusted sources, allowing attackers to install a persistent threat within another application easily.
The Solution for the Branching Factor of the Alpha-Beta Pruning Algorithm and its Optimality

This paper analyzes N n , d , the average number of terminal nodes examined by the 𝛼 – 𝛽 pruning algorithm in a uniform game tree of degree n and depth d for which the terminal values are drawn at random from a continuous distribution. It is shown that increasing the search depth by one extra step would increase N n , d by
Preliminary Results on a "Real" Iris Recognition System under Challenging Operational Conditions

Iris recognition algorithms have recently demonstrated excellent performance in the authentication task. In this paper, we present a technology transfer project for the development and testing of a biometric recognition system under challenging operational conditions. Due to the stringent operational requirements, the design and implementation of the system included a phase of selecting technologically advanced hardware. The lack of corresponding data sets implied a novel acquisition step. The evaluation phase is preliminary as the data set is being expanded for the acquisition of new samples capable of highlighting the system’s critical issues. Current samples were acquired in very different lighting conditions and in the presence of glasses, which was not yet done in the literature. In addition to the selected hardware, such data allowed us to simulate a realistic environmental context for the project’s final prototype.
A distributed EEMDN-SABiGRU model on Spark for passenger hotspot prediction

To address the imbalance problem between supply and demand for taxis and passengers, this paper proposes a distributed ensemble empirical mode decomposition with normalization of spatial attention mechanism based bi-directional gated recurrent unit (EEMDN-SABiGRU) model on Spark for accurate passenger hotspot prediction. It focuses on reducing blind cruising costs, improving carrying efficiency, and maximizing incomes. Specifically, the EEMDN method is put forward to process the passenger hotspot data in the grid to solve the problems of non-smooth sequences and the degradation of prediction accuracy caused by excessive numerical differences, while dealing with the eigenmodal EMD. Next, a spatial attention mechanism is constructed to capture the characteristics of passenger hotspots in each grid, taking passenger boarding and alighting hotspots as weights and emphasizing the spatial regularity of passengers in the grid. Furthermore, the bi-directional GRU algorithm is merged to deal with the problem that GRU can obtain only the forward information but ignores the backward information, to improve the accuracy of feature extraction. Finally, the accurate prediction of passenger hotspots is achieved based on the EEMDN-SABiGRU model using real-world taxi GPS trajectory data in the Spark parallel computing framework. The experimental results demonstrate that based on the four datasets in the 00-grid, compared with LSTM, EMD-LSTM, EEMD-LSTM, GRU, EMD-GRU, EEMD-GRU, EMDN-GRU, CNN, and BP, the mean absolute percentage error, mean absolute error, root mean square error, and maximum error values of EEMDN-SABiGRU decrease by at least 43.18%, 44.91%, 55.04%, and 39.33%, respectively.
Properties of Selected Soils in the Mataranka Area

The Department of Natural Resources, Environment The Arts and Sport (NRETAS) was requested by the Northern Territory Agricultural Association (NTAA) to participate in an improved irrigation and nutrient management project. NRETAS involvement was to describe, sample, test and report on three soil pits located at Portion 6280, Roper Highway Mataranka.
Exploring nonlinear spatiotemporal effects for personalized next point-of-interest recommendation

Next point-of-interest (POI) recommendation is an important personalized task in location-based social networks (LBSNs) and aims to recommend the next POI for users in a specific situation with historical check-in data. State-of-the-art studies linearly discretize the user’s spatiotemporal information and then use recurrent neural network (RNN) based models for modeling. However, these studies ignore the nonlinear effects of spatiotemporal information on user preferences and spatiotemporal correlations between user trajectories and candidate POIs. To address these limitations, a spatiotemporal trajectory (STT) model is proposed in this paper. We use the long short-term memory (LSTM) model with an attention mechanism as the basic framework and introduce the user’s spatiotemporal information into the model in encoding. In the process of encoding information, an exponential decay factor is applied to reflect the nonlinear drift of user interest over time and distance. In addition, we design a spatiotemporal matching module in the process of recalling the target to select the most relevant POI by measuring the relevance between the user’s current trajectory and the candidate set. We evaluate the performance of our STT model with four real-world datasets. Experimental results show that our model outperforms existing state-of-the-art methods.
Practical Tracking Via Adaptive Event-Triggered Feedback for Uncertain Nonlinear Systems

This paper addresses the event-triggered tracking for a class of uncertain nonlinear systems. Essentially different from the related works, the nonlinear systems allow serious (parametric) uncertainties, while no further a priori information, excepting some coarse information, is required on the reference signal to be tracked. This makes event-triggered control more challenging, partially because the sampling error cannot be precisely bounded any more. As main contributions of this paper, new adaptive event-triggered tracking schemes are proposed for the systems in two event-triggering architectures with different roles of the event-triggering mechanism on the information transmitting and control computing/updating. Much importantly, a dynamic gain is incorporated in either scheme not only to counteract the serious uncertainties, but also to overcome the bad influence of the sampling error. Based on the dynamic gain, two adaptive event-triggered controllers are designed with distinct event-triggering mechanisms, respectively. Particularly, to ensure application flexibility, one of the triggering mechanisms is rendered relatively independent of the controller signal. The designed event-triggered controllers are shown to achieve the practical tracking for the systems, that is, the prespecified arbitrary tracking accuracy can be guaranteed (a comparable objective to that via continuous-time control), while avoiding infinitely fast sampling/execution.
Exploiting Nonslip Wall Contacts to Position Two Particles Using the Same Control Input

Steered particles offer a method for targeted therapy, interventions, and drug delivery in regions inaccessible by large robots. For example, magnetic actuation of particles has the benefits of requiring no tethers, being able to operate from a distance, and in some cases allows imaging for feedback (e.g., MRI). This paper investigates position control of particles using uniform forces (the same force is applied everywhere in the workspace). Given a controllable field that can generate bidirectional forces in three orthogonal directions, steering one particle in three-dimensional (3-D) is trivial. Adding additional particles to steer makes the system underactuated because there are more states than control inputs. However, the walls of in vivo and artificial environments often have surface roughness such that the particles do not move unless actuation pulls them away from the wall. In the previous work, we showed that the individual two-dimensional (2-D) position of two particles is controllable using global inputs in a square workspace with nonslip wall contact [1]. Because in vivo environments are usually not square, this paper extends the previous work to all convex workspaces, and shows how this could be extended to 3-D positioning of neutrally buoyant particles. We investigate analytically an idealized variant of this problem with nonslip boundaries and control inputs that are applied uniformly to all particles in the workspace. This paper also implements the algorithms in 2-D using a hardware setup inspired by the gastrointestinal tract.
Chronic sustained inflammation links to left ventricular hypertrophy and aortic valve sclerosis: a new link between S100/RAGE and FGF23.

BACKGROUND Cardiovascular disease including left ventricular hypertrophy, diastolic dysfunction and ectopic valvular calcification are common in patients with chronic kidney disease (CKD). Both S100A12 and fibroblast growth factor 23 (FGF23) have been identified as biomarkers of cardiovascular morbidity and mortality in patients with CKD. We tested the hypothesis that human S100/calgranulin would accelerate cardiovascular disease in mice subjected to CKD. METHODS This review paper focuses on S100 proteins and their receptor for advanced glycation end products (RAGE) and summarizes recent findings obtained in novel developed transgenic hBAC-S100 mice that express S100A12 and S100A8/9 proteins. A bacterial artificial chromosome of the human S100/calgranulin gene cluster containing the genes and regulatory elements for S100A8, S100A9 and S100A12 was expressed in C57BL/6J mice (hBAC-S100). CKD was induced by ureteral ligation, and hBAC-S100 mice and WT mice were studied after 10 weeks of chronic uremia. RESULTS hBAC-S100 mice with CKD showed increased FGF23 in the heart, left ventricular hypertrophy (LVH), diastolic dysfunction, focal cartilaginous metaplasia and calcification of the mitral and aortic valve annulus together with aortic valve sclerosis. This phenotype was not observed in WT mice with CKD or in hBAC-S100 mice lacking RAGE with CKD, suggesting that the inflammatory milieu mediated by S100/RAGE promotes pathological cardiac hypertrophy in CKD. In vitro, inflammatory stimuli including IL-6, TNFα, LPS, or serum from hBAC-S100 mice up regulated FGF23 mRNA and protein in primary murine neonatal and adult cardiac fibroblasts. CONCLUSIONS Taken together, our study shows that myeloid-derived human S100/calgranulin is associated with the development of cardiac hypertrophy and ectopic cardiac calcification in a RAGE dependent manner in a mouse model of CKD. We speculate that FGF23 produced by cardiac fibroblasts in response to cytokines may act in a paracrine manner to accelerate LVH and diastolic dysfunction in hBAC-S100 mice with CKD. We suggest that S100/RAGE-mediated chronic sustained systemic inflammation is linked to pathological cardiac remodeling via direct up regulation of FGF23 in cardiac fibroblasts, thereby providing a new mechanistic understanding for the common association between CKD, diabetes, metabolic syndrome, or hypertension with left ventricular hypertrophy with diastolic dysfunction.
Fractional differential and integral operations via cumulative approach

In this study, a fractal operator model of cumulative processes is described. Accordingly, differential and integral operators of the fractional calculus are derived by the fractal operator model of a cumulative process. In order to exhibit the relation between our cumulative approach and fractional calculus, vertical motion of a body is handled within these frameworks. Thereby, regard to our assessments, the underlying physical mechanism of the success of the fractional differintegral operators in describing stochastic complex systems is uncovered to some extent.
Planar 2-D Scanning SIW Multibeam Array With Low Sidelobe Level for Millimeter-Wave Applications

A two-dimensionally (2-D) scanning multibeam array with planar structure and low sidelobe level (SLL) is realized in this paper. It is for the first time that the SLL of 2-D scanning multibeam array is properly addressed. To suppress the SLL, a <inline-formula> <tex-math notation="LaTeX">$4 \times 16$ </tex-math></inline-formula> beam-forming network (BFN) is proposed in this paper. Different from the existing schemes, such BFN can provide tapered illuminations in two orthogonal directions and thus can be applied to realize low-SLL 2-D scanning beams. The proposed <inline-formula> <tex-math notation="LaTeX">$4 \times 16$ </tex-math></inline-formula> BFN is formed by interconnecting two sets of sub-BFNs, each of which is stacked by several <inline-formula> <tex-math notation="LaTeX">$2 \times 4$ </tex-math></inline-formula> Butler matrices (BMs). Like other 2-D scanning schemes, the preliminary <inline-formula> <tex-math notation="LaTeX">$4 \times 16$ </tex-math></inline-formula> BFN is of 3-D topology so that it is challenging to be integrated into planar substrate integrated waveguide (SIW) structure. Facing this problem, some modifications of the proposed topology are conducted. Operation principle, simulation, and experiment of a planar, low-SLL 2-D scanning multibeam array operating at 28 GHz are illustrated, which can help to demonstrate its feasibility for millimeter-wave applications.
Broadband and filter radiometers at Ross Island, Antarctica: Detection of cloud ice phase versus liquid water influences on shortwave and longwave radiation

Surface radiometer data from Ross Island, Antarctica, collected during the austral summer 2015-16 by the US Department of Energy Atmospheric Radiation Measurement (ARM) program West Antarctic Radiation Experiment (AWARE), are used to evaluate how shortwave and longwave irradiance respond to changing cloud properties as governed by contrasting meteorological regimes. Shortwave atmospheric transmittance is derived from pyranometer measurements, 15 and cloud conservative-scattering optical depth is derived from filter radiometer measurements at 870 nm. With onshore flow associated with marine air masses, clouds contain mostly liquid water. With southerly flow over the Transantarctic Mountains, orographic forcing induces substantial cloud ice water content. These ice and mixed-phase clouds attenuate more surface shortwave irradiance than the maritime-influenced clouds, and also emit less longwave irradiance due to colder cloud base temperature. These detected irradiance changes are in a range that can mean onset or inhibition of surface melt over ice 20 shelves. This study demonstrates how basic and relatively low-cost broadband and filter radiometers can be used to detect subtle climatological influences of contrasting cloud microphysical properties at very remote locations.
Effective Matching of Patients to Clinical Trials using Entity Extraction and Neural Re-ranking

INTRODUCTION Clinical trials (CTs) often fail due to inadequate patient recruitment. Finding eligible patients involves comparing the patient's information with the CT eligibility criteria. Automated patient matching offers the promise of improving the process, yet the main difficulties of CT retrieval lie in the semantic complexity of matching unstructured patient descriptions with semi-structured, multi-field CT documents and in capturing the meaning of negation coming from the eligibility criteria. OBJECTIVES This paper tackles the challenges of CT retrieval by presenting an approach that addresses the patient-to-trials paradigm. Our approach involves two key components in a pipeline-based model: (i) a data enrichment technique for enhancing both queries and documents during the first retrieval stage, and (ii) a novel re-ranking schema that uses a Transformer network in a setup adapted to this task by leveraging the structure of the CT documents. METHODS We use named entity recognition and negation detection in both patient description and the eligibility section of CTs. We further classify patient descriptions and CT eligibility criteria into current, past, and family medical conditions. This extracted information is used to boost the importance of disease and drug mentions in both query and index for lexical retrieval. Furthermore, we propose a two-step training schema for the Transformer network used to re-rank the results from the lexical retrieval. The first step focuses on matching patient information with the descriptive sections of trials, while the second step aims to determine eligibility by matching patient information with the criteria section. RESULTS Our findings indicate that the inclusion criteria section of the CT has a great influence on the relevance score in lexical models, and that the enrichment techniques for queries and documents improve the retrieval of relevant trials. The re-ranking strategy, based on our training schema, consistently enhances CT retrieval and shows improved performance by 15% in terms of precision at retrieving eligible trials. CONCLUSION The results of our experiments suggest the benefit of making use of extracted entities. Moreover, our proposed re-ranking schema shows promising effectiveness compared to larger neural models, even with limited training data. These findings offer valuable insights for improving methods for retrieval of clinical documents.
Synkromisering af XPath Views

The increasing availability of XML-based data sources, e.g., for publishing data on the WWW, means that more and more applications (data consumers) rely on accessing and using XML data. Typically, the access is achieved by de(cid:2)ning views over the XML data, and accessing data through these views. However, the XML data sources are often independent of the data consumers and may change their schemas without noti(cid:2)cation, invalidating the XML views de(cid:2)ned by the data consumers. This requires the view de(cid:2)nitions to be updated to re(cid:3)ect the new structure of the data sources, a process termed view synchronization . XPath is the most commonly used language for retrieving parts of XML documents, and is thus an important cornerstone for XML view de(cid:2)nitions. This paper presents techniques for discovering schema changes in XML data sources and synchronizing XPath-based views to re(cid:3)ect these schema changes. In many cases, this allows the XML data consumers to continue their operation without interruption. Experiments show that the techniques work well even if both schema and data change at the same time. To our knowledge, this is the (cid:2)rst presented technique for synchronizing views over XML data.
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: The major histocompatibility complex class I and II molecules (MHC-I and MHC-II) plays a pivotal role in vertebrate immune response to antigenic peptides. In this paper we report the cloning and sequencing of the MHC class II b chain from sea bass (Dicentrarchus labrax L.). The six obtained cDNA sequences (designated as Dila-DAB) code for 250 amino acids, with a predicted 21 amino acid signal peptide and contain a 28 bp 5'-UTR and a 478 bp 3'-UTR. A multiple alignment of the predicted translation of the Dila-DAB sequences was assembled together with other fish and mammalian sequences and it showed the conservation of most amino acid residues characteristic of the MHC class II b chain structure. The highest basal Dila-DAB expression was found in gills, followed by gut and thymus, lower mRNA levels
De la communauté à la méta-communauté, décrypter les patrons de diversité

Les patrons de diversite caracterisent la structure de la diversite des communautes, c'est-a-dire sa valeur, sa distribution et son changement dans l'espace et le temps. Leur etude peut amener des informations importantes sur les processus ecologiques qui en sont a l'origine. Cependant de nombreuses hypotheses de travail sont faites lors de leur analyse. L'idee generale de cette these est qu'en remettant en cause ces hypotheses, un certain nombre de developpements lies aux indices de diversite et aux modeles nuls deviennent possibles et permettent de mieux comprendre les processus ecologiques a l'origine des patrons de diversite fonctionnelle ou phylogenetique. Le premier chapitre est consacre a l'etude des patrons de diversite fonctionnelle des communautes vegetales alpines a de multiples echelles spatiales et organisationnelles. Le second chapitre s'interesse aux perspectives methodologiques amenes par les nombres de Hill. Dans le dernier chapitre, on s'interesse aux enjeux methodologiques d'un nouveau type de donnees de communautes : l'ADN environnemental.
Physiological and microbiome adaptation of coral Turbinaria peltata in response to marine heatwaves

Abstract Against the backdrop of global warming, marine heatwaves are projected to become increasingly intense and frequent. This trend poses a potential threat to the survival of corals and the maintenance of entire coral reef ecosystems. Despite extensive evidence for the resilience of corals to heat stress, their ability to withstand repeated heatwave events has not been determined. In this study, we examined the responses and resilience of Turbinaria peltata to repeated exposure to marine heatwaves, with a focus on physiological parameters and symbiotic microorganisms. In the first heatwave, from a physiological perspective, T. peltata showed decreases in the Chl a content and endosymbiont density and significant increases in GST, caspase‐3, CAT, and SOD levels (p < .05), while the effects of repeated exposure on heatwaves were weaker than those of the initial exposure. In terms of bacteria, the abundance of Leptospira, with the potential for pathogenicity and intracellular parasitism, increased significantly during the initial exposure. Beneficial bacteria, such as Achromobacter arsenitoxydans and Halomonas desiderata increased significantly during re‐exposure to the heatwave. Overall, these results indicate that T. peltata might adapt to marine heatwaves through physiological regulation and microbial community alterations.