Miracle-dz/UniFAR-FTUs huggingface dataset:
This paper is included

Trigger-Action Platforms (TAPs) connect disparate online services and enable users to create automation rules in diverse domains such as smart homes and business productivity. Unfortunately, the current design of TAPs is ﬂawed from a privacy perspective, allowing unfettered access to sensitive user data. We point out that it suffers from two types of over-privilege: (1) attribute-level, where it has access to more data attributes than it needs for running user-created rules; and (2) token-level, where it has access to more APIs than it needs. To mitigate overprivilege and subsequent privacy concerns we design and implement minTAP, a practical approach to data access minimization in TAPs. Our key insight is that the semantics of a user-created automation rule implicitly speci-ﬁes the minimal amount of data it needs. This allows minTAP to leverage language-based data minimization to apply the principle of least-privilege by releasing only the necessary attributes of user data to TAPs and fending off unrelated API access. Using real user-created rules on the popular IFTTT TAP, we demonstrate that minTAP sanitizes a median of 4 sensitive data attributes per rule, with modest performance overhead and without modifying IFTTT.
Diffusion Models in Analysing Ernerging Technology Based Services

: In this article we discuss the problems of utilizing innovation diffusion (or, adoption) models in developing seenarios for mobile commerce services in three European countries: Finland, Germany, and Greece. We are not to test the various diffusion models as such, but rather to utilise the fundamental ideas of the models in determining the prerequisites for, the status of, and the pace of diffusion of mobile services in these different market areas. The estimates would serve as a starting point and as a validity check for scenario development. The early experience at the research design phase show that the 'mainstream' diffusion approach is vulnerable to three factors specific to the adoption of services that are subject to technical change and development: 'layered' adoption process in its social context, supply side, and continuous technical development.
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By combining a few modules, the CNS may learn new control policies quickly and efficiently. Support for a modular organization of the motor system has recently come from the observation of low dimensionality in the motor commands. However, stronger evidence would come from testing the predictions on the effect of an intervention on the mechanisms required to implement a modular controller. Thus, the authors propose to test the predictions of modularity on motor adaptation. They argue that unlike a nonmodular controller, a modular controller must adapt faster to a perturbation that is compatible with the modules (i.e., one that can be compensated by reusing the same modules), than to an incompatible perturbation (i.e., one that requires new modules).
Distributed Compressed Sensing

Compressed sensing is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for reconstruction. In this paper we introduce a new theory for distributed compressed sensing (DCS) that enables new distributed coding algorithms for multi-signal ensembles that exploit both intraand inter-signal correlation structures. The DCS theory rests on a new concept that we term the joint sparsity of a signal ensemble. We study in detail three simple models for jointly sparse signals, propose algorithms for joint recovery of multiple signals from incoherent projections, and characterize theoretically and empirically the number of measurements per sensor required for accurate reconstruction. We establish a parallel with the Slepian-Wolf theorem from information theory and establish upper and lower bounds on the measurement rates required for encoding jointly sparse signals. In two of our three models, the results are asymptotically best-possible, meaning that both the upper and lower bounds match the performance of our practical algorithms. Moreover, simulations indicate that the asymptotics take effect with just a moderate number of signals. In some sense DCS is a framework for distributed compression of sources with memory, which has remained a challenging problem for some time. DCS is immediately applicable to a range of problems in sensor networks and arrays.
in Computer

— Vehicular Adhoc Networks (VANET) are becoming more popular as the need for accessing and sharing data while on the move is increasing. Value-added applications such as online payment services, geographical location identification, etc. in VANET, improve driving safety, passenger comfort, offer great business opportunities, and attract more and more attention in our daily life. VANETs connect vehicles into a huge mobile adhoc network to share information on a larger scale. By enabling the vehicles to communicate with their neighbors and sharing their driving states, VANETs avoid accidents potentially caused by emergency braking, lane changing, etc. The characteristics of VANET pose both challenges and opportunities in achieving security goals. The various attacks in VANETs are the Sybil attack, DDOS attack, misbehaving and faulty nodes, sinkhole attack, spoofing, traffic analysis attack, position attack, and illusion attack. Providing security to VANET is important in terms of providing user anonymity, authentication, integrity, and privacy of data. In this paper, a comprehensive survey on the threats and vulnerabilities in VANETs are explored and analysed in detail. The compromised security goals are identified for each threat. The existing solutions for these threats are discussed in this paper.
A Neural Model of Memory Impairment in Di use Cerebral Atrophy

Background: Several previous computer-supported neural network models have been subjected to diiuse, progressive deletion of synapses/neurons. The goal in this past work has been to show that modeling cerebral neuropathological changes can provide a computational account for the pattern of memory degradation that occurs in diiuse degenerative processes such as Alzheimer's disease. Recently, however, it has been suggested that neural models cannot account for more detailed aspects of memory impairment, such as the relative sparing of remote versus recent memories observed experimentally in Alzheimer's disease Carrie, 1993]. Methods: The latter claim is examined from a computational perspective , in the framework of a neural associative memory model. Results: We describe a neural network model that not only demonstrates graceful, progressive memory deterioration as progressive, diiuse network damage occurs, but also clearly exhibits diierential sparing of remote versus recent memories. The model accounts for the experimentally observed temporal gradient of memory decline, the occurrence of false positive errors during retrieval, and testiies to the importance of modeling synaptic compensatory mechanisms. Conclusions: Our results show that neural models can account for a large variety of experimental phenomena characterizing memory degradation in Alzheimer patients. Speciic testable predictions are generated, concerning the relation between the neu-roanatomical degenerative ndings and the clinical manifestations of Alzheimer disease.
Navigated and individual α-peak-frequency–guided transcranial magnetic stimulation in male patients with treatment-refractory schizophrenia

Background: Previous electroencephalography (EEG) studies have indicated altered brain oscillatory α-band activity in schizophrenia, and treatment with repetitive transcranial magnetic stimulation (rTMS) using individualized α-frequency has shown therapeutic effects. Magnetic resonance imaging–based neuronavigation methods allow stimulation of a specific cortical region and improve targeting of rTMS; therefore, we sought to study the efficacy of navigated, individual α-peak-frequency–guided rTMS (αTMS) on treatment-refractory schizophrenia. Methods: We recruited medication-refractory male patients with schizophrenia or schizoaffective disorder in this doubleblind, sham-controlled study. We randomized patients to a 3-week course of either active αTMS or sham stimulation applied to the left dorsolateral prefrontal cortex (DLPFC). We assessed participants with the Positive and Negative Syndrome Scale (PANSS) and the Clinical Global Impression Scale (CGI) at baseline and after treatment. We conducted a follow-up assessment with the PANSS 3 months after intervention. Results: We included 44 patients. After treatment, we observed a significantly higher PANSS total score (p = 0.029), PANSS general psychopathology score (p = 0.027) and PANSS 5-factor model cognitive–disorganized factor score (p = 0.011) in the αTMS group than the sham group. In addition, the CGI–Improvement score was significantly higher among those who received αTMS compared with sham stimulation (p = 0.048). Limitations: The limited number of study participants included only male patients. Depression was not formally evaluated. Conclusion: Navigated αTMS to the left DLPFC reduced total, general psychopathological, and cognitive–disorganized symptoms of schizophrenia. These results provide evidence for the therapeutic efficacy of individual α-peak-frequency–guided rTMS in treatment-refractory schizophrenia. Clinical trial registration: NCT01941251; ClinicalTrials.gov
Determining the Wave Vector Direction of Equatorial Fast Magnetosonic Waves

We perform polarization analysis of the equatorial fast magnetosonic waves electric field over a 20‐min interval of Van Allen Probes A waveform receiver burst mode data. The wave power peaks at harmonics of the proton cyclotron frequency indicating that the spacecraft is near or in the source region. The wave vector is inferred from the direction of the major axis of the electric field polarization ellipsoid and the sign of the phase between the longitudinal electric and compressional magnetic field components. We show that wave vector is preferentially in the azimuthal direction as opposed to the radial direction. From Poynting flux analysis one would infer that the wave vector is primarily in the radial direction. We show that the error in the Poynting flux is large ~90°. These results strongly imply that the wave growth occurs during azimuthal propagation in the source region for this event.
PAPipe: A Pipeline for Comprehensive Population Genetic Analysis

Abstract Advancements in next-generation sequencing (NGS) technologies have led to a substantial increase in the availability of population genetic variant data, thus prompting the development of various population analysis tools to enhance our understanding of population structure and evolution. The tools that are currently used to analyze population genetic variant data generally require different environments, parameters, and formats of the input data, which can act as a barrier preventing the wide-spread usage of such tools by general researchers who may not be familiar with bioinformatics. To address this problem, we have developed an automated and comprehensive pipeline called PAPipe to perform nine widely used population genetic analyses using population NGS data. PAPipe seamlessly interconnects and serializes multiple steps, such as read trimming and mapping, genetic variant calling, data filtering, and format converting, along with nine population genetic analyses such as principal component analysis, phylogenetic analysis, population tree analysis, population structure analysis, linkage disequilibrium decay analysis, selective sweep analysis, population admixture analysis, sequentially Markovian coalescent analysis, and fixation index analysis. PAPipe also provides an easy-to-use web interface that allows for the parameters to be set and the analysis results to be browsed in intuitive manner. PAPipe can be used to generate extensive results that provide insights that can help enhance user convenience and data usability. PAPipe is freely available at https://github.com/jkimlab/PAPipe.
Characterizations of Centrifugal Electrospun Polyvinyl Alcohol/Sodium Alginate/Tamanu Oil/Silver Nanoparticles Wound Dressing

Known for its water solubility, flexibility, strong adhesion, and eco-friendly nature, polyvinyl alcohol (PVA) is widely used in various industries. In the medical field, it is used for applications such as creating bandages and orthopaedic devices. Incorporating sodium alginate (SA) into PVA membranes enhances their structural integrity, breathability, and permeability, thereby minimising the risk of cellular damage in the wound zone. Moreover, the addition of tamanu oil (C alophyllum inophyllum L.) and silver nanoparticles, both of which are known for their antibacterial properties and benefits in traditional wound healing, further enhances the membranes’ wound-healing effectiveness. Following production, the membranes undergo a series of tests designed to evaluate their physical properties as well as their antioxidant and antibacterial capabilities. Subsequently, in vitro testing is conducted using human skin cells; experiments on Wistar rats are then performed. Numerous experiments have consistently demonstrated that the performance of polyvinyl alcohol/sodium alginate/tamanu oil (PVA/SA/Oil) membrane is superior to that of polyvinyl alcohol/sodium alginate/tamanu oil/silver nanoparticles (PVA/SA/Oil/Ag NP) membrane. Specifically, the polyvinyl alcohol/sodium alginate (PVA/SA) combination exhibits an impressive wound-healing rate of 98.82% after 15 days, with cells maintaining a high viability of 92% in a nourishing environment. Moreover, these membranes exhibit exceptional resistance to the oxidation of free radicals, surpassing the 70% threshold, and they possess antibacterial activity against Staphylococcus aureus subsp. aureus in vitro. Based on the obtained results, the nanofiber membranes composed of polyvinyl alcohol/ alginate/ tamanu oil, with or without silver nanoparticles, have shown potential as wound dressings in the wound care discipline.
Digital Commons@Georgia Southern

Nasonia is a parasitoid wasp genus that serves as an emerging model for studying speciation due to an incompatibility between nuclear and mitochondrial genomes between sister taxa. Short generation times, easy rearing in a lab setting, producing large amounts of progeny, and whole genome sequencing make Nasonia is an excellent candidate for studying incomplete reproductive isolation. Nasonia have five chromosomes and exhibit haplo-diploid sex determination in which fertilized eggs develop into diploid females and unfertilized eggs develop into haploid males. Recessive phenotypes are hidden in diploid females but are laid bare in haploid males as there is no interaction between alleles. F2 male hybrids of Nasonia vitripennis and Nasonia giraulti experience high rates of mortality during development as compared to parent strains. Previous research has shown that 96% of F2 males with an incompatible allele on chromosome 5 combined with N. giraulti maternity die. F1 females experience low mortality in comparison to the high mortality that their sons, F2 males, experience. Large differences in mortality between F1 females and F2 males can be further investigated by studying F2 backcross females. I hypothesized that F1 females and F2 backcrossed heterozygous females experience similar levels of incompatibility to one another at the mortality locus as well as F2 backcrossed homozygous females and F2 males. I predicted that F2 backcross females would have intermediate mortality overall as compared to F1 females and F2 males. To test this, I conducted mortality experiments to determine differences in egg to adult survival between parent species, F2 males, and backcrossed F2 females. I found that F2 hybrids suffered greater mortality than both parent species. Egg to adult mortality was similar between F2 males
METTL3 as a novel diagnosis and treatment biomarker and its association with glycolysis, cuproptosis and ceRNA in oesophageal carcinoma

Abstract METTL3 has been shown to be involved in regulating a variety of biological processes. However, the relationship between METTL3 expression and glycolysis, cuproptosis‐related genes and the ceRNA network in oesophageal carcinoma (ESCA) remains unclear. ESCA expression profiles from databases were obtained, and target genes were identified using differential analysis and visualization. Immunohistochemistry (IHC) staining assessed METTL3 expression differences. Functional enrichment analysis using GO, KEGG and GSEA was conducted on the co‐expression profile of METTL3. Cell experiments were performed to assess the effect of METTL3 interference on tumour cells. Correlation and differential analyses were carried out to assess the relationship between METTL3 with glycolysis and cuproptosis. qRT‐PCR was used to validate the effects of METTL3 interference on glycolysis‐related genes. Online tools were utilized to screen and construct ceRNA networks based on the ceRNA theory. METTL3 expression was significantly higher in ESCA compared to the controls. The IHC results were consistent with the above results. Enrichment analysis revealed that METTL3 is involved in multiple pathways associated with tumour development. Significant correlations were observed between METTL3 and glycolysis‐related genes and cuproptosis‐related gene. Experiments confirmed that interfered with METTL3 significantly inhibited glucose uptake and lactate production in tumour cells, and affected the expression of glycolytic‐related genes. Finally, two potential ceRNA networks were successfully predicted and constructed. Our study establishes the association between METTL3 overexpression and ESCA progression. Additionally, we propose potential links between METTL3 and glycolysis, cuproptosis and ceRNA, presenting a novel targeted therapy strategy for ESCA.
Gestion du mauvais comportement des récepteurs dans les Protocoles de Contrôle de Congestion Multipoint

In multicast congestion control, receivers can misbehave by maliciously causing congestion to steal network bandwidth from well behaved flows. In source driven congestion control protocols (SDCC), receivers misbehave by sending a wrong feedback to the source. In receiverdriven congestion control protocols(RDCC), receivers misbehave by inflating their subscriptions. In this report, we present techniques to deal with these misbehaviours. Firstly, we show that when network tomography tools such as MINC are used in conjunction with SDCC protocols, they can aid in misbehavior detection. But in order to use MINC for misbehaviour detection, MINC itself must be made immune to misbehaviour. we analyze the effect of misbehavior within MINC and propose two techniques to detect and prevent misbehavior in MINC. For RDCC protocols, a misbehaviour prevention mechanism based on in-band distribution of keys was recently proposed for FLID-DL protocol. In this report, we show how we can design keys which can prevent misbehaviour in most RDCC protocols. Key-words: MINC, Network Tomography, Misbehavior, Multicast Congestion Control, secret sharing. Gestion du mauvais comportement des récepteurs dans les Protocoles de Contrôle de Congestion Multipoint Résumé : Les protocoles de contrôle de congestion actuels peuvent permettre à des récepteurs peu scrupuleux de mal se conduire en accaparant plus de bande passante qu’ils ne devraient. Avec les protocoles de contrôle de congestion contrôlés par la source (SDCC), il est possible à des récepteurs malveillants de falsifier les rapports de réception qu’ils envoeint à la source. En ce qui concerne les protocoles de contrôle de congestion contrôlés par les récepteurs (RDCC), certains récepteurs peuvent décider de s’abonner à toutes les couches de la source sans tenir compte des débits qui leur sont alloués. Dans ce rapport, nous présentons des techniques pour prévenir ces comportements indésirables. Nous montrons comment un outil de tomographie de réseau comme MINC peut être utilisé pour détecter ces comportements malveillants avec les protocoles SDCC. L’outil de tomographie doit dans un premier temps être rendu insensible à ces attaques. Nous analysons le comportement de MINC et proposons des mécanismes de détection et prévention contre ces comportements malicieux. Pour les protocoles RDCC, un mécanisme de prévention de comportement malicieux basé sur la distribution de clés a été proposé récemment pour le protocole FLID-DL. Nous proposons un nouveau mécanisme de génération de clés pour la plupart des protocoles RDCC. Mots-clés : Attaques, Contrôle de Congestion Multipoint, MINC, Outils de Tomographie du Réseau, partage de secrète. Dealing with Receiver Misbehavior in Multicast Congestion Control 3
EMG-based Multi-User Hand Gesture Classification via Unsupervised Transfer Learning Using Unknown Calibration Gestures

The poor generalization performance and heavy training burden of the gesture classification model contribute as two main barriers that hinder the commercialization of sEMG-based human-machine interaction (HMI) systems. To overcome these challenges, eight unsupervised transfer learning (TL) algorithms developed on the basis of convolutional neural networks (CNNs) were explored and compared on a dataset consisting of 10 gestures from 35 subjects. The highest classification accuracy obtained by CORrelation Alignment (CORAL) reaches more than 90%, which is 10% higher than the methods without using TL. In addition, the proposed model outperforms 4 common traditional classifiers (KNN, LDA, SVM, and Random Forest) using the minimal calibration data (two repeated trials for each gesture). The results also demonstrate the model has a great transfer robustness/flexibility for cross-gesture and cross-day scenarios, with an accuracy of 87.94% achieved using calibration gestures that are different with model training, and an accuracy of 84.26% achieved using calibration data collected on a different day, respectively. As the outcomes confirm, the proposed CNN TL method provides a practical solution for freeing new users from the complicated acquisition paradigm in the calibration process before using sEMG-based HMI systems.
ANISOTROPY OF THE ROUGH TURBULENT BOUNDARY LAYER SUBJECT TO A FAVORABLE PRESSURE GRADIENT

Laser-Doppler anemometry (LDA) measurements of the mean velocity and Reynolds stresses are carried out on a rough surface favorable pressure gradient (FPG) turbulent boundary layer. These data are compared with smooth FPG turbulent boundary layer data possessing the same strength of pressure gradient and with rough zero pressure gradient (ZPG) data. In order to properly capture the x -dependence of the single point statistics, consecutive measurements of 11 streamwise locations were performed. It is observed through the anisotropy coefficients that the isotropy of the flow is promoted by both the rough surface and the pressure gradient. The isotropization of the boundary layer close to the wall is increased by the roughness, while on the outer part of the boundary layer it is caused by the favorable pressure gradient imposed on the flow. It is also shown through the production terms that the roughness causes a greater production of the turbulence on the outer flow.