Miracle-dz/UniFAR-FTUs huggingface dataset:
Diffusing Your Mobile Apps: Extending In-Network Function Virtualization to Mobile Function Offloading

Motivated by the huge disparity between the limited battery capacity of user devices and the ever-growing energy demands of modern mobile apps, we propose INFv. It is the first offloading system able to cache, migrate and dynamically execute on demand functionality from mobile devices in ISP networks. It aims to bridge this gap by extending the promising NFV paradigm to mobile applications in order to exploit in-network resources. In this paper, we present the overall design, state-of-the-art technologies adopted, and various engineering details in the INFv system. We also carefully study the deployment configurations by investigating over 20K Google Play apps, as well as thorough evaluations with realistic settings. In addition to a significant improvement in battery life (up to 6.9x energy reduction) and execution time (up to 4x faster), INFv has two distinct advantages over previous systems: 1) a non-intrusive offloading mechanism transparent to existing apps; 2) an inherent framework support to effectively balance computation load and exploit the proximity of in-network resources. Both advantages together enable a scalable and incremental deployment of computation offloading framework in practical ISPs' networks.
No evidence for violation of the second law in extended black hole thermodynamics

Recently a number of papers have claimed that the horizon area - and thus the entropy - of near extremal black holes in anti-de Sitter spacetimes can be reduced by dropping particles into them. In this note we point out that this is a consequence of an underlying assumption that the energy of an infalling particle changes only the internal energy of the black hole, whereas a more physical assumption would be that it changes the enthalpy (mass). In fact, under the latter choice, the second law of extended black hole thermodynamics is no longer violated.
An integrated autoencoder-based filter for sparse big data

We propose a novel filter for sparse big data, called an integrated autoencoder (IAE), which utilizes auxiliary information to mitigate data sparsity. The proposed model achieves an appropriate balance between prediction accuracy, convergence speed, and complexity. We implement experiments on a GPS trajectory dataset, and the results demonstrate that the IAE is more accurate and robust than some state-of-the-art methods.
Towards a Federation of Smart City Services.

The emergence of the Internet of Things has accelerated the development of smart cities. Currently, an increasing number of smart city applications comprising various scenarios and use cases is being deployed and tested. However, to realize a smart city, it is necessary to have converging solutions as opposed to niche, detached solutions. Smart city platforms need to take into account existing services and infrastructures. Furthermore, in the context of a smart city it is important to account for various kinds of stakeholders with a variety of requirements with regard to data ownership, legal and organizational frameworks as well as commercial interests. We present the ALMANAC Smart City Platform as a solution which handles the described heterogeneity. Firstly, the platform allows the development of smart city applications by creating interoperability among devices and services. Secondly, the platform is deployed in a de-centralized, federated way that allows to map the organizational requirements to the deployed city systems. We introduce the concept of federation for smart cities and describe its implementation in the ALMANAC Platform through a case study which simulates a scenario in the waste management domain. This scenario models realworld requirements of a waste management company and the municipality of Turin. Keywords-internet of things; smart city; federation;
Cosmic time slip: Testing gravity on supergalactic scales with strong-lensing time delays

We devise a test of nonlinear departures from general relativity (GR) using time delays in strong gravitational lenses. We use a phenomenological model of gravitational screening as a step discontinuity in the measure of curvature per unit mass, at a radius $\Lambda$. The resulting slip between two scalar gravitational potentials leads to a shift in the apparent positions and time delays of lensed sources, relative to the GR predictions, of size $\gamma_{\rm PN}-1$. As a proof of principle, we use measurements of two lenses, RXJ1121-1231 and B1608+656, to constrain deviations from GR to be below $|\gamma_{\rm PN}-1| \leq 0.2 \times (\Lambda/100\, \rm kpc)$. These constraints are complementary to other current probes, and are the tightest in the range $\Lambda=10-200$ kpc, showing that future measurements of strong-lensing time delays have great promise to seek departures from general relativity on kpc-Mpc scales.
Getting the best out of data for small monograph presses: A case study of UCL press

Digital developments in scholarly publishing are giving rise to new data sources with the potential to provide insight into how OA monographs are being used and to support strategic decision-making by publishers. However, small OA monograph publishers face practical challenges in identifying relevant data, as well as in capturing, managing and interpreting it. This case study of UCL Press reports on a collaborative research project that sought to address some of these challenges. The project involved UCL Press, Knowledge Unlatched Research and the Centre for Culture and Technology at Curtin University in Australia (CCAT). Our goal was to identify the extent to which data that can be easily accessed by a small OA monograph press can be combined with low-cost tools for its analysis in order to provide useful insight into development and strategy; and to identify practical steps that can be taken by small OA monograph publishers to ensure that they are making the most of the data that they have access to.
A Holistic Survey of Wireless Multipath Video Streaming

Most of today's mobile devices are equipped with multiple network interfaces and one of the main bandwidth-hungry applications that would benefit from multipath communications is wireless video streaming. However, most of current transport protocols do not match the requirements of video streaming applications or are not designed to address relevant issues, such as delay constraints, networks heterogeneity, and head-of-line blocking issues. This article provides a holistic survey of multipath wireless video streaming, shedding light on the different alternatives from an end-to-end layered stack perspective, unveiling trade-offs of each approach and presenting a suitable taxonomy to classify the state-of-the-art. Finally, we discuss open issues and avenues for future work.
Optically and electrically excited intermediate electronic states in donor:acceptor based OLEDs

Thermally activated delayed fluorescence (TADF) emitters consisting of donor and acceptor molecules are potentially highly interesting for electroluminescence (EL) applications. Their strong fluorescence emission is considered to be due to reverse intersystem crossing (RISC), in which energetically close triplet and singlet charge transfer (CT) states, also called exciplex states, are involved. In order to distinguish between different mechanisms and excited states involved, temperature-dependent spin-sensitive measurements on organic light-emitting diodes (OLEDs) and thin films are essential. In our work we apply continuous wave (cw) and time-resolved (tr) photoluminescence (PL) spectroscopy as well as spin-sensitive EL and PL detected magnetic resonance to films and OLED devices made of three different donor:acceptor combinations. Our results clearly show that triplet exciplex states are formed and contribute to delayed fluorescence (DF) via RISC in both electrically driven OLEDs and optically excited films. In the same sample set we also found molecular triplet excitons, which occurred only in PL experiments under optical excitation and for some material systems only at low temperatures. We conclude that in all investigated molecular systems exciplex states formed at the donor:acceptor interface are responsible for TADF in OLEDs with distinct activation energies. Molecular (local) triplet exciton states are also detectable, but only under optical excitation, while they are not found in OLEDs when excited states are generated electrically. We believe that the weakly bound emissive exciplex states and the strongly bound non-emissive molecular triplet excited states coexist in the TADF emitters, and it is imperative to distinguish between optical and electrical generation paths as they may involve different intermediate excited states.
Improved procedure for mass inoculum production of Fusarium species in a short period of time

The induction of sporulation on artificial media is a critical factor for the production of inoculum in Fusarium species. An improved method of conidia production is described and compared to a conventional method growing Fusarium species on low-strength potato dextrose agar (LSPDA) under near-ultraviolet (NUV) light for 21 days. In the improved procedure, Fusarium spp. were grown in potato dextrose broth (PDB) for three days and subsequently spread as aliquots onto LSPDA; synthetic nutrient poor mineral agar (SNPMA) and water agar (WA) media. To remove excess water, the cultures were dried in a laminar flow cabinet for 20 to 30 min. Air-dried plates were incubated under NUV light at 25 oC for 3 days. To compare aggressiveness of conidia produced by either method, wheat ears were inoculated at the mid-flowering. Disease incidence (% infected kernels) and Fusarium head blight (FHB) severity as well as fungal biomass produced in the infected kernels were determined. The improved method effectively triggered sporulation of Fusarium spp. and gave high yields of conidia per unit of area within two days of incubation on solid media which is significantly higher compared to spore quantities produced with the conventional method. The average number of conidia produced by Fusarium spp. using the improved and conventional methods ranged from 56 to 156 and 0.8 to 38.6×10 6 (per plate), respectively. Spore production quantity was highly variable with the conventional method using different Fusarium species. However, morphology of conidia was similar in both assays. The aggressiveness of Fusarium inocula produced by both methods was not significantly different with respect to the ability to cause FHB and to colonize wheat kernels (P≤0.05). Microscopy examination showed the high conidiation rate from phialides on hypha. The method will facilitate studies of pathogens causing FHB requiring large quantities of conidia.
Spectrally-truncated kernel ridge regression and its free lunch

Kernel ridge regression (KRR) is a well-known and popular nonparametric regression approach with many desirable properties, including minimax rate-optimality in estimating functions that belong to common reproducing kernel Hilbert spaces (RKHS). The approach, however, is computationally intensive for large data sets, due to the need to operate on a dense $n \times n$ kernel matrix, where $n$ is the sample size. Recently, various approximation schemes for solving KRR have been considered, and some analyzed. Some approaches such as Nystrom approximation and sketching have been shown to preserve the rate optimality of KRR. In this paper, we consider the simplest approximation, namely, spectrally truncating the kernel matrix to its largest $r < n$ eigenvalues. We derive an exact expression for the maximum risk of this truncated KRR, over the unit ball of the RKHS. This result can be used to study the exact trade-off between the level of spectral truncation and the regularization parameter of the KRR. We show that, as long as the RKHS is infinite-dimensional, there is a threshold on $r$, above which, the spectrally-truncated KRR, surprisingly, outperforms the full KRR in terms of the minimax risk, where the minimum is taken over the regularization parameter. This strengthens the existing results on approximation schemes, by showing that not only one does not lose in terms of the rates, truncation can in fact improve the performance, for all finite samples (above the threshold). In other words, there is nothing to be gained by running the full KRR and one should always truncate. Our proof is elementary and distribution-free, only requiring the noise vector to be isotropic.
Recurrent Neural Processes

We extend Neural Processes (NPs) to sequential data through Recurrent NPs or RNPs, a family of conditional state space models. RNPs model the state space with Neural Processes. Given time series observed on fast real-world time scales but containing slow long-term variabilities, RNPs may derive appropriate slow latent time scales. They do so in an efficient manner by establishing conditional independence among subsequences of the time series. Our theoretically grounded framework for stochastic processes expands the applicability of NPs while retaining their benefits of flexibility, uncertainty estimation, and favorable runtime with respect to Gaussian Processes (GPs). We demonstrate that state spaces learned by RNPs benefit predictive performance on real-world time-series data and nonlinear system identification, even in the case of limited data availability.
Neural Response Generation with Meta-words

We present open domain dialogue generation with meta-words. A meta-word is a structured record that describes attributes of a response, and thus allows us to explicitly model the one-to-many relationship within open domain dialogues and perform response generation in an explainable and controllable manner. To incorporate meta-words into generation, we propose a novel goal-tracking memory network that formalizes meta-word expression as a goal in response generation and manages the generation process to achieve the goal with a state memory panel and a state controller. Experimental results from both automatic evaluation and human judgment on two large-scale data sets indicate that our model can significantly outperform state-of-the-art generation models in terms of response relevance, response diversity, and accuracy of meta-word expression.
Antimicrobial activity of the leaf extracts of Moringa oleifera and Jatropha curcas on pathogenic bacteria

This study evaluates the antimicrobial activity of the leaf extracts of Moringa oleifera and Jatropha curcas against Staphylococcus aureus and Escherichia coli . Different concentrations of the extracts were subjected to these organisms in which Moringa oleifera showed a higher zone of inhibition on Staphylococcus aureus (2.8 cm) while on E. coli (2.4 cm) while Jatropha curcas showed a higher zone of inhibition on E. coli (2.6 cm) while on S. aureus (1.80 cm). The minimum inhibitory concentration (MIC) of Moringa oleifera extract on E. coli and S. aureus were 0.250 mg/ml and 0.125 mg/ml respectively while MIC of Jatropha curcas extract on test organisms was 0.125 mg/ml. The quantitative phytochemical screening in g/kg revealed the presence of flavonoid 36 and 21, alkaloids 92 and 39, tannins 7.4 and 5.6, saponins 115.0 and 53.5, cyanogenic glycosides 8.4 and 14.5 for M. oleifera and J. curcas respectively. The observed antimicrobial properties could be due to the presence of these bioactive compounds and further substantiates the use of Moringa oleifera and Jatropha curcas leaf extracts in medicine. The extracts in correct doses can successfully be used in vivo to inhibit and eventually kill the test bacteria used in this study. © 2013 International Formulae Group. All rights reserved. Keywords: Moringa oleifera, Jatropha curcas , phytochemicals, bacteria, antimicrobial.
Asymptotic Structure for the Clique Density Theorem

The famous Erdős-Rademacher problem asks for the smallest number of $r$-cliques in a graph with the given number of vertices and edges. Despite decades of active attempts, the asymptotic value of this extremal function for all $r$ was determined only recently, by Reiher [Annals of Mathematics, 184 (2016) 683--707]. Here we describe the asymptotic structure of all almost extremal graphs. This task for $r=3$ was previously accomplished by Pikhurko and Razborov [Combinatorics, Probability and Computing, 26 (2017) 138--160].
Conceptor Debiasing of Word Representations Evaluated on WEAT

Bias in word representations, such as Word2Vec, has been widely reported and investigated, and efforts made to debias them. We apply the debiasing conceptor for post-processing both traditional and contextualized word embeddings. Our method can simultaneously remove racial and gender biases from word representations. Unlike standard debiasing methods, the debiasing conceptor can utilize heterogeneous lists of biased words without loss in performance. Finally, our empirical experiments show that the debiasing conceptor diminishes racial and gender bias of word representations as measured using the Word Embedding Association Test (WEAT) of Caliskan et al. (2017).
A Comparison Between the Effect of Three Types of Low-Calorie Diets on Controlling Blood Glucose and Lipids in People with Type 2 Diabetes

The blood glucose level of people with diabetes can be normalized through an appropriate diet, physical activity, the use of chemical drugs and medicinal plants. This study aims to investigate the effects of low-calorie diets (1200, 1500, and 1800 kcal) on glucose and serum lipids in poorly controlled type 2 diabetic patients. This clinical trial was conducted among 60 patients with type 2 diabetes mellitus. The criteria for entering the study were fasting blood glucose higher than 130 mg/dl, hemoglobin A 1 C higher than 7% and BMI higher than 25. Blood glucose, fasting blood glucose and lipid levels were measured before and after intervention two hours after each meal. Patients were trained by an expert. Then, the questionnaires were completed and analyzed. In this study, the mean fasting blood glucose level in patients who used 1500 and 1200 kcal diet decreased significantly after intervention (p<0.05). Glucose decreased significantly after two hours using a 1500 kcal diet (p<0.009). In addition, triglyceride and cholesterol levels were significantly reduced in patients who used the 1500 kcal diet (p<0.05). Although, there was no significant difference in blood glucose levels between 1200, 1500 and 1800 kcal diets based on gender, residencency and BMI. Regarding the fact that there was no significant difference in reducing blood glucose and serum lipids between 1200 and 1500 kcal diets. It is recommended to use a 1500 kcal diet instead of 1200 kcal diet, which imposes fewer limitations and is easier to tolerate.
A Comprehensive Model of Information Technology Value Creation in the Supply Chain

Investments in Information Technology (I.T.) continue to grow, yet there continue to be doubts regarding the economic benefits of I.T. This paper researches prior work into what constitutes I.T. value and how I.T. creates value. Two general approaches predominate the literature on researching I.T. value the micro economic production theory approach and the firm level process oriented approach. The micro economic production approach investigates the impact of multiple inputs (such as I.T. investment) on some output measure (such as productivity) using economic production theory techniques. This approach implicitly assumes usage of the I.T. investments. Because this approach fails to consider the usage of I.T. within the business, it lacks explanatory power in identifying how I.T. impacts firm level results. The firm level process oriented approach provides an explanation of how and why I.T. value is created because it considers I.T. usage in the business. This paper focuses on the process oriented approach and reviews prior work in this area. A comprehensive model of I.T. value building on prior work is presented.
Effectiveness of Distillation Attack and Countermeasure on Neural Network Watermarking

The rise of machine learning as a service and model sharing platforms has raised the need of traitor-tracing the models and proof of authorship. Watermarking technique is the main component of existing methods for protecting copyright of models. In this paper, we show that distillation, a widely used transformation technique, is a quite effective attack to remove watermark embedded by existing algorithms. The fragility is due to the fact that distillation does not retain the watermark embedded in the model that is redundant and independent to the main learning task. We design ingrain in response to the destructive distillation. It regularizes a neural network with an ingrainer model, which contains the watermark, and forces the model to also represent the knowledge of the ingrainer. Our extensive evaluations show that ingrain is more robust to distillation attack and its robustness against other widely used transformation techniques is comparable to existing methods.
Interface Dynamics for an Allen-Cahn-Type Equation Governing a Matrix-Valued Field

We consider the initial value problem for the generalized Allen-Cahn equation, \[\partial_t \Phi = \Delta \Phi-\varepsilon^{-2} \Phi (\Phi^t \Phi - I), \qquad x \in \Omega, \ t\geq 0,\] where $\Phi$ is an $n\times n$ real matrix-valued field, $\Omega$ is a two-dimensional square with periodic boundary conditions, and $\varepsilon > 0$. This equation is the gradient flow for the energy, $E(\Phi) := \int \frac{1}{2} \|\nabla \Phi \|^2_F+\frac{1}{4 \varepsilon^2} \| \Phi^t \Phi - I \|^2_F$, where $\| \cdot \|_F$ denotes the Frobenius norm. The primary contribution of this paper is to use asymptotic methods to describe the solution of this initial value problem. If the initial condition has single-signed determinant, at each point of the domain, at a fast $O(\varepsilon^{-2} t)$ time scale, the solution evolves towards the closest orthogonal matrix. Then, at the $O(t)$ time scale, the solution evolves according to the $O_n$ diffusion equation. Stationary solutions to the $O_n$ diffusion equation are analyzed for $n=2$. If the initial condition has regions where the determinant is positive and negative, a free interface develops. Away from the interface, in each region, the matrix-valued field behaves as in the single-signed determinant case. At the $O(t)$ time scale, the interface evolves in the normal direction by curvature. At a slow $O(\varepsilon t)$ time scale, the interface is driven by curvature and the surface diffusion of the matrix-valued field. For $n=2$, the interface is driven by curvature and the jump in the squared tangental derivative of the phase across the interface. In particular, we emphasize that the interface when $n\geq 2$ is driven by surface diffusion, while for $n=1$, the original Allen--Cahn equation, the interface is only driven by mean curvature. A variety of numerical experiments are performed to verify, support, and illustrate our analytical results.