Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypoxia Is Not a Main Stress When Mycobacterium tuberculosis Is in a Dormancy-Like Long-Chain Fatty Acid Environment

The capacity of Mycobacterium tuberculosis (Mtb) to sense, respond and adapt to a variable and hostile environment within the host makes it one of the most successful human pathogens. During different stages of infection, Mtb is surrounded by a plethora of lipid molecules and current evidence points out the relevance of fatty acids during the infectious process. In this study, we have compared the transcriptional response of Mtb to hypoxia in cultures supplemented with a mix of even long-chain fatty acids or dextrose as main carbon sources. Using RNA sequencing, we have identified differential expressed genes in early and late hypoxia, defined according to the in vitro Wayne and Hayes model, and compared the results with the exponential phase of growth in both carbon sources. We show that the number of genes over-expressed in the lipid medium was quite low in both, early and late hypoxia, relative to conditions including dextrose, with the exception of transcripts of stable and non-coding RNAs, which were more expressed in the fatty acid medium. We found that sigB and sigE were over-expressed in the early phase of hypoxia, confirming their pivotal role in early adaptation to low oxygen concentration independently of the carbon source. A drastic contrast was found with the transcriptional regulatory factors at early hypoxia. Only 2 transcriptional factors were over-expressed in early hypoxia in the lipid medium compared to 37 that were over-expressed in the dextrose medium. Instead of Rv0081, known to be the central regulator of hypoxia in dextrose, Rv2745c (ClgR), seems to play a main role in hypoxia in the fatty acid medium. The low level of genes associated to the stress-response during their adaptation to hypoxia in fatty acids, suggests that this lipid environment makes hypoxia a less stressful condition for the tubercle bacilli. Taken all together, these results indicate that the presence of lipid molecules shapes the metabolic response of Mtb to an adaptive state for different stresses within the host, including hypoxia. This fact could explain the success of Mtb to establish long-term survival during latent infection.
Dopamine and Serotonin Are Both Required for Mate-Copying in Drosophila melanogaster

Mate-copying is a form of social learning in which the mate-choice decision of an individual (often a female) is influenced by the mate-choice of conspecifics. Drosophila melanogaster females are known to perform such social learning, and in particular, to mate-copy after a single observation of one conspecific female mating with a male of one phenotype, while the other male phenotype is rejected. Here, we show that this form of social learning is dependent on serotonin and dopamine. Using a pharmacological approach, we reduced dopamine or serotonin synthesis in adult virgin females with 3-iodotyrosine (3-IY) and DL-para-chlorophenylalanine (PCPA), respectively, and then tested their mate-copying performance. We found that, while control females without drug treatment copied the choice of the demonstrator, drug-treated females with reduced dopamine or serotonin chose randomly. To ensure the specificity of the drugs, the direct precursors of the neurotransmitters, either the dopamine precursor L-3,4-dihydroxyphenylalanine (L-DOPA) or the serotonin precursor 5-L-hydroxytryptophan (5-HTP) were given together with the drug, (respectively 3-IY and PCPA) resulting in a full rescue of the mate-copying defects. This indicates that dopamine and serotonin are both required for mate-copying. These results give a first insight into the mechanistic pathway underlying this form of social learning in D. melanogaster.
Photoplethysmography for Quantitative Assessment of Sympathetic Nerve Activity (SNA) During Cold Stress

The differences in the degree of sympathetic nerve activity (SNA) over cutaneous blood vessels, although known to be more prominent in the periphery than the core vasculature, has not been thoroughly investigated quantitatively. Hence, two studies were carried out to investigate the differences in SNA between the periphery and the core during the cold pressor test (CPT) (right-hand immersion in ice water) and cold exposure (whole body exposed to cold air) using photoplethysmography (PPG). Two methods utilizing PPG, namely differential multi-site PTT measurements and low-frequency spectral analysis were explored for quantitative determination of SNA. Each study involved 12 healthy volunteers, and PPG signals were acquired from the right index finger (RIF), left index finger (LIF) (periphery) and the ear canal (core). During CPT, Pulse Transit Time (PTT) was measured to the respective locations and the mean percentage change in PTT during ice immersion at each location was used as an indicator for the extent of SNA. During cold exposure, the low-frequency spectral analysis was performed on the acquired raw PPGs to extract the power of the sympathetic [low-frequency (LF): 0.04–0.15 Hz] and parasympathetic components [high-frequency (HF): 0.15–0.4 Hz]. The ratio of LF/HF components was then used to quantify the differences in the influence of SNA on the peripheral and core circulation. PTT measured from the EC, and the LIF has dropped by 5 and 7%, respectively during ice immersion. The RIF PTT, on the other hand, has dropped significantly (P < 0.05) by 12%. During the cold exposure, the LF/HF power ratio at the finger has increased to 86.4 during the cold exposure from 19.2 at the baseline (statistically significant P = 0.002). While the ear canal LF/HF ratio has decreased to 1.38 during the cold exposure from 1.62 at baseline (P = 0.781). From these observations, it is evident that differential PTT measurements or low-frequency analysis can be used to quantify SNA. The results also demonstrate the effectiveness of the central auto-regulation during both short and long-term stress stimulus as compared to the periphery.
Reductions in Postprandial Plasma Allantoin Concentrations With Increasing Doses of Polyphenol Rich Curry Intake – A Randomized Crossover Trial

While dietary or supplementary antioxidants are thought to inhibit or delay oxidation of biological molecules, their utility in vivo has been marred by equivocal evidence. Consumption of polyphenol rich foods has been thought to alleviate postprandial oxidative stress and/or improve endothelial function. Although, previous studies suggested the utility of allantoin as a biomarker of oxidative stress, controlled dose response studies with dietary antioxidants to test this in humans have been limited. We therefore investigated the effects of 2 doses of polyphenol rich curry consumption on postprandial plasma concentrations of allantoin, allantoin to uric acid ratio, F2-isoprostanes using liquid chromatography-tandem mass spectrometry (LCMS-MS) and measured endothelial function using peripheral arterial tonometry (endoPAT). In a randomized controlled crossover trial in 17 non-smoking, healthy, Chinese men, aged 23.7 ± 2.4 years and BMI 23.1 ± 2.3 kg/m2, the volunteers consumed 3 test meals in a random order, consisting of either non-curry Dose 0 Control (D0C, 0 g spices), or Dose 1 Curry (D1C, 6 g spices) or Dose 2 Curry (D2C, 12 g spices), after overnight fast. There were significant reductions in postprandial allantoin concentrations (p < 0.001) and allantoin to uric acid ratio (p < 0.001) at 2 h and 3 h following test meal consumption, indicating improvements in postprandial redox balance with increasing curry doses, although there were no differences between treatments on F2-isoprostane concentrations or on RHI (measured at 2 h only). Allantoin may have a utility as a biomarker of redox balance, in an acute setting. The study was registered at www.clinicaltrials. gov (Identifier No. NCT02599272).
Two-Photon Uncaging of Glutamate

Two-photon microscopy produces the excited singlet state of a chromophore with wavelengths approximately double that used for normal excitation. Two photons are absorbed almost simultaneously, via a virtual state, and this makes the excitation technique inherently non-linear. It requires ultra-fast lasers to deliver the high flux density needed to access intrinsically very short lived intermediates, and in combination with lenses of high numerical aperture, this confines axial excitation highly. Since the two-photon excitation volume is similar to a large spine head, the technique has been widely used to study glutamatergic transmission in brain slices. Here I describe the principles of two-photon uncaging of glutamate and provide a practical guide to its application.
Preparation of Clathrin-Coated Vesicles From Arabidopsis thaliana Seedlings

Clathrin coated vesicles (CCVs) mediate endocytosis of plasma membrane proteins and deliver their content to the endosomes for either subsequent recycling to the plasma membrane or transport to the vacuole for degradation. CCVs assemble also at the trans-Golgi network (TGN) and is responsible for the transport of proteins to other membranes. Oligomerization of clathrin and recruitment of adaptor protein complexes promote the budding and the release of CCVs. However, many of the details during plant CCV formation are not completely elucidated. The analysis of isolated CCVs is therefore important to better understand the formation of plant CCVs, their cargos and the regulation of clathrin-mediated transport processes. In this article, we describe an optimized method to isolate CCVs from Arabidopsis thaliana seedlings.
Programming touch and full-body interaction with a remotely controlled robot in a secondary education STEM course

Contemporary research has introduced educational robotics in the classroom, but there are few studies about the effects of alternative embodied interaction modalities on computational thinking and science education. Twenty-six middle school students were asked to program interfaces for controlling the heading and speed of a robot using two types of embodied interaction modalities. We compared touch and full-body gestures to autonomous control, which does not require any embodied interaction. We assessed the development of their computational thinking skills by analyzing the projects they created during a problem-solving task and examined their understandings of science concepts related to kinematics. We found that novice students preferred full-body interfaces, while advanced students moved to more disembodied and abstract computational thinking. These findings might be applied to focus computing and science education activities to the right age and abilities groups of students.
Traffic forecasting in cellular networks using the LSTM RNN

In this work we design and implement a Neural Network that can identify recurrent patterns in various metrics which can be then used for cellular network traffic forecasting. Based on a custom architecture and memory, this Neural Network can handle prediction tasks faster and more accurately in real life scenarios. This approach offers a solution for service providers to enhance cellular network performance, by utilizing effectively the available resources. In order to provide a robust conclusion about the performance and precision of the proposed Neural Network, multiple predictions were made using the same data-set and the results were compared against other similar algorithms from the literature.
Context-, flow-, and field-sensitive data-flow analysis using synchronized Pushdown systems

Precise static analyses are context-, field- and flow-sensitive. Context- and field-sensitivity are both expressible as context-free language (CFL) reachability problems. Solving both CFL problems along the same data-flow path is undecidable, which is why most flow-sensitive data-flow analyses over-approximate field-sensitivity through k-limited access-path, or through access graphs. Unfortunately, as our experience and this paper show, both representations do not scale very well when used to analyze programs with recursive data structures. Any single CFL-reachability problem is efficiently solvable, by means of a pushdown system. This work thus introduces the concept of synchronized pushdown systems (SPDS). SPDS encode both procedure calls/returns and field stores/loads as separate but “synchronized” CFL reachability problems. An SPDS solves both individual problems precisely, and approximation occurs only in corner cases that are apparently rare in practice: at statements where both problems are satisfied but not along the same data-flow path. SPDS are also efficient: formal complexity analysis shows that SPDS shift the complexity from |F|3k under k-limiting to |S||F|2, where F is the set of fields and S the set of statements involved in a data-flow. Our evaluation using DaCapo shows this shift to pay off in practice: SPDS are almost as efficient as k-limiting with k=1 although their precision equals k=∞. For a typestate analysis SPDS accelerate the analysis up to 83× for data-flows of objects that involve many field accesses but span rather few methods. We conclude that SPDS can provide high precision and further improve scalability, in particularly when used in analyses that expose rather local data flows.
Secure and trust-aware routing in wireless sensor networks

Wireless Sensors Networks (WSNs) are susceptible to many security threats, and because of communication, computation and delay constraints of WSNs, traditional security mechanisms cannot be used. As a consequence, several secure routing methods have been proposed during the last decade, whereas trust management models and corresponding routing protocols have also been recently suggested as an even more effective security mechanism for WSNs. In this paper, we present a detailed survey on such routing protocols along with a proper classification according to their basic features. We first distinguish between secure multipath protocols and trust evaluation based protocols. The former are then distinguished to share and non share-based ones, whereas the latter are categorized according to their cluster-based structure or not. A comprehensive analysis is presented, accompanied by proper comparison and summarization tables for the most significant ones, as well as corresponding discussion and conclusions. Main emphasis is given to their novelty, basic methodology, pros and cons, kinds of faced attacks and complexity.
Gender identification through facebook data analysis using machine learning techniques

The purpose of this paper is to analyze Facebook users' profile aiming at identifying the gender of the profile's owner. To this end several machine learning models were adopted and applied on a representative set of features extracted from Facebook profiles describing users' preferences relative to their gender information. This study concludes that there is a plethora of features which can be mined from a Facebook profile and can be used in identifying the gender of a profile's owner. Moreover, the experiments reveal that this gender identification task can be accomplished effectively by using machine learning techniques with 97.30% accuracy, after considering a large amount of Facebook profile data.
Lock Contention Management in Multithreaded MPI

In this article, we investigate contention management in lock-based thread-safe MPI libraries. Specifically, we make two assumptions: (1) locks are the only form of synchronization when protecting communication paths; and (2) contention occurs, and thus serialization is unavoidable. Our work distinguishes between lock acquisitions with respect to work being performed inside a critical section; productive vs. unproductive. Waiting for message reception without doing anything else inside a critical section is an example of unproductive lock acquisition. We show that the high-throughput nature of modern scalable locking protocols translates into better communication progress for throughput-intensive MPI communication but negatively impacts latency-sensitive communication because of overzealous unproductive lock acquisition. To reduce unproductive lock acquisitions, we devised a method that promotes threads with productive work using a generic two-level priority locking protocol. Our results show that using a high-throughput protocol for productive work and a fair protocol for less productive code paths ensures the best tradeoff for fine-grained communication, whereas a fair protocol is sufficient for more coarse-grained communication. Although these efforts have been rewarding, scalability degradation remains significant. We discuss techniques that diverge from the pure locking model and offer the potential to further improve scalability.
Attack Synthesis for Strings using Meta-Heuristics

Information leaks are a significant problem in modern computer systems and string manipulation is prevalent in modern software. We present techniques for automated synthesis of side-channel attacks that recover secret string values based on timing observations on string manipulating code. Our attack synthesis techniques iteratively generate inputs which, when fed to code that accesses the secret, reveal partial information about the secret based on the timing observations, leading to recovery of the secret at the end of the attack sequence. We use symbolic execution to extract path constraints, automata-based model counting to estimate the probability of execution paths, and meta-heuristic methods to maximize information gain based on entropy for synthesizing adaptive attack steps.
A forensic investigation of Android mobile applications

This paper performs a forensic investigation to a set of Android mobile applications aiming at discovering sensitive information related to the owner of the mobile device. These applications were chosen based on the fact that: i) they are very popular on Google Play Store, ii) they handle sensitive personal information, iii) they have not been researched by previous works and iv) they are free to download and install. The three chosen applications belong to the following categories: bank, mobile network carrier and public transport. The evaluation of the security of the applications was performed using two techniques: code and disk analysis, as followed in the literature. Based on our findings we derive the conclusion that these applications despite their criticality have failed to incorporate security techniques to protect user's sensitive data and a forensic analysis can reveal crucial and significant information from a forensics point of view.
Bounded model checking of signal temporal logic properties using syntactic separation

Signal temporal logic (STL) is a temporal logic formalism for specifying properties of continuous signals. STL is widely used for analyzing programs in cyber-physical systems (CPS) that interact with physical entities. However, existing methods for analyzing STL properties are incomplete even for bounded signals, and thus cannot guarantee the correctness of CPS programs. This paper presents a new symbolic model checking algorithm for CPS programs that is refutationally complete for general STL properties of bounded signals. To address the difficulties of dealing with an infinite state space over a continuous time domain, we first propose a syntactic separation of STL, which decomposes an STL formula into an equivalent formula so that each subformula depends only on one of the disjoint segments of a signal. Using the syntactic separation, an STL model checking problem can be reduced to the satisfiability of a first-order logic formula, which is decidable for CPS programs with polynomial dynamics using satisfiability modulo theories (SMT). Unlike the previous methods, our method can verify the correctness of CPS programs for STL properties up to given bounds.
CloudNavi

The rapid development of mobile computing has prompted indoor navigation to be one of the most attractive and promising applications. Conventional designs of indoor navigation systems depend on either infrastructures or indoor floor maps. This article presents CloudNavi, a ubiquitous indoor navigation solution, which relies on the point clouds acquired by the 3D camera embedded in a mobile device. Particularly, CloudNavi first efficiently infers the walking trace of each user from captured point clouds and inertial data. Many shared walking traces and associated point clouds are combined to generate the point cloud traces, which are then used to generate a 3D path-map. Accordingly, CloudNavi can accurately estimate the location of a user by fusing point clouds and inertial data using a particle filter algorithm and then guiding the user to its destination from its current location. Extensive experiments are conducted on office building and shopping mall datasets. Experimental results indicate that CloudNavi exhibits outstanding navigation performance in both office buildings and shopping malls and obtains around 34% improvement compared with the state-of-the-art method.
Privacy leakages about political beliefs through analysis of Twitter followers

In this paper, we focus on privacy leakages about Twitter users and show that simply establishing follower and friend connections in the Twitter network might be enough to reveal sensitive information about the political beliefs of a user. More precisely, we create a Twitter dataset containing the twitter nodes of Greek news media and politicians, as well as their followers and present two approaches to predict the political beliefs of a Twitter user and the politicians the user will potentially follow. The intuition behind both approaches is the saying "Show me who your friends are, and I will tell you who you are". In the first approach, the politicians followed by the followers of the user are shown to be correlated to the politicians that the user follows. In the second one, the media that the user follows are used to predict the politicians that the user follows. The experimental results of both approaches confirm our claims and show that significant privacy leakages are possible.
Multi-RAT spectrum reallocation including carrier aggregation for 5G networks

Towards the 5G vision of massive access exploding the growth in data traffic, spectrum refarming and reallocation are considered key enabling technologies. Using spectrum reallocation (SR) with the spectrum originally assigned to a Radio Access Technology (RAT) and the the remaining to use spectrum reallocation in the context of multi-RATs (m-RAT). For example, GSM, HSPA and UMTS technologies to be underutilized due to the migration of subscribers to 4G networks are considered in the m-RAT application scenario. To this end, efforts are made in order to deploy m-RAT systems, where the spectrum assigned to m-RATs can be efficiently redistributed and utilized by the involved RATs. In this work, we assume a HSPA/LTE-A m-RAT that provide Carrier Aggregation (CA) too, and propose specific functionality in order to coordinate the operation of both RATs regarding the spectrum assignment and resource allocation. Results show that by assigning spectrum to cover a minimum performance requirement for HSPA, there is a significant performance improvement for LTE-A. Moreover, when spectrum assignment is performed jointly with resource allocation between the involved RATs, the throughput results are higher for both HSPA and LTE-A users.