Miracle-dz/UniFAR-FTUs huggingface dataset:
Time and Space in Android-Based Opportunistic Networks

Mobile devices like smartphones or other smart objects can create Opportunistic Networks with intermittent node contacts due to their wireless technology and their user's social behavior. In disaster, emergency and censorship situations, or if simply no internet connection is available, Opportunistic Networking can be used to connect devices to each other. We attempt to improve our Android-based network and take a look at time modification and buffer management issues. Syncing the time is a known problem due to the probable lack of a connection to the internet. Since the devices are user-controlled, changes in time have to be noticed and time differences between devices have to be exchanged. Also, we take a look at the special buffer which is not reserved entirely for the network but is shared with all applications on the device. For this paper, we developed functionality in form of multiple libraries to detect time changes and possible storage shortages on the devices, to synchronize time for our network, and to remove messages in a system in which there is not only one buffer but multiple virtual ones that belong to different applications. We conduct tests which detect when the Android system begins to notify about storage congestion and starts deleting buffer content. With these results, our libraries can improve the drop and queue policies that have to react before user data is deleted.
Hsp90 inhibitor AT‐533 blocks HSV‐1 nuclear egress and assembly

&NA; Heat shock protein 90 (Hsp90) has been identified as an essential host factor for the infection and replication of several viruses, including HSV‐1. Recent works have clearly shown that Hsp90 plays a role in the early stages of HSV‐1 infection, including nuclear import and DNA replication. However, the role of Hsp90 in the late stages of HSV‐1 infection remains unclear. In this study, we found that Hsp90 was up‐regulated during late viral infection. Treatment with the Hsp90 inhibitor AT‐533 significantly decreased the intracellular and extracellular virus titers, and strongly inhibited nucleocapsid egress from the nucleus. More detailed studies revealed that AT‐533 inhibited the nuclear egress of the viral nucleocapsid by suppressing the expression and translocation of nuclear‐associated proteins pUL31 and pUL34. In addition, we found that AT‐533 hindered the assembly of virus particles possibly though affecting the localization of glycoproteins in the endoplasmic reticulum and Golgi apparatus. These results thus invoke a new role for Hsp90 in the nucleocapsid egress and viral maturation of HSV‐1, and further promote the development of Hsp90 inhibitors as potential anti‐HSV‐1 drugs.
Unobtrusive Students' Engagement Analysis in Computer Science Laboratory Using Deep Learning Techniques

Nowadays, analysing the students' engagement using non-verbal cues is very popular and effective. There are several web camera based applications for predicting the students' engagement in an e-learning environment. But there are very limited works on analyzing the students' engagement using the video surveillance cameras in a teaching laboratory. In this paper, we propose a Convolutional Neural Networks based methodology for analysing the students' engagement using video surveillance cameras in a teaching laboratory. The proposed system is tested on five different courses of computer science and information technology with 243 students of NITK Surathkal, Mangalore, India. The experimental results demonstrate that there is a positive correlation between the students' engagement and learning, thus the proposed system outperforms the existing systems.
Temperature and Strain Discrimination in BOTDA Fiber Sensor by Utilizing Dispersion Compensating Fiber

Standard single mode fiber that normally used in Brillouin optical time domain analysis fiber sensors typically has only one Brilllouin gain peak (BGP), and its central frequency [i.e., Brillouin frequency shift (BFS)] can be affected by both temperature and strain, which gives rise to temperature and strain cross sensitivity. In this paper, we propose a new method to realize temperature and strain discrimination, for the first time to the best of our knowledge, by using commercial single mode dispersion compensating fiber (DCF) that has two BGPs located around 9.536 and 10.052 GHz, respectively. The two peaks have different temperature coefficients but nearly the same strain coefficients, which permits simultaneous temperature and strain sensing by combing the BFSs obtained from the two BGPs. The biggest advantage of the DCF is that the frequency space between its two BGPs is >100 MHz wider than some other fibers, ensuring much wider temperature and strain sensing range. In a proof of concept experiment, temperature and strain are fully discriminated with a temperature resolution of ~2.6 °C and a strain resolution of $\sim 64.6~\mu \varepsilon $ at the end of a 1-km sensing fiber with 2-m spatial resolution.
Fraus: Launching Cost-efficient and Scalable Mobile Click Fraud Has Never Been So Easy

Mobile click fraud is a type of attack where an adversary deceptively generates click events on mobile applications in pursuit of revenue. Conventionally, the attack is carried out by automating a massive number of physical devices. However, purchasing the devices incur substantial costs. A cheaper alternative to the physical devices is emulators. However, existing emulators are inefficient and vastly blocked due to their immense resource demand and defective device signatures. In this paper, we propose Fraus1, a cost-efficient and scalable approach to conduct largescale click fraud using device emulators. Fraus maintains a low resource profile by circumventing graphics emulation and applying lazy-loading techniques on system components. Besides, Fraus provides a seemingly authentic device signature and disguises itself as a legitimate device by fully emulating the missing hardware components including WiFi interfaces and cellular modems. To facilitate the management of numerous emulator instances, Fraus also offers a distributed management system, which is scalable and fault-tolerant. We evaluate the performance of Fraus by mocking attacks against the top 300 applications from the Google Play store. The results demonstrate that Fraus has high system stability and application compatibility. It also significantly reduces CPU usage and memory footprint up to 90% and 60% respectively compared with the existing emulators.1In Roman mythology, Fraus was the goddess or personification of treachery and fraud.
Crowd Simulation Incorporating Thermal Environments and Responsive Behaviors

Abstract Crowd simulation addresses algorithmic approaches to steering, navigation, perception, and behavioral models. Significant progress has been achieved in modeling interactions between agents and the environment to avoid collisions, exploit empirical local decision data, and plan efficient paths to goals. We address a relatively unexplored dimension of virtual human behavior: thermal perception, comfort, and appropriate behavioral responses. Thermal comfort is associated with the ambient environment, agent density factors, and interpersonal thermal feedback. A key feature of our approach is the temporal integration of both thermal exposure and occupant density to directly influence agent movements and behaviors (e.g., clothing changes) to increase thermal comfort. Empirical thermal comfort models are incorporated as a validation basis. Simple heat transfer models are used to model environment, agent, and interpersonal heat exchange. Our model’s generality makes it applicable to any existing crowd steering algorithm as it adds additional integrative terms to any cost function. Examples illustrate distinctive emergent behaviors such as balancing agent density with thermal comfort, hysteresis in responding to localized or brief thermal events, and discomfort and likely injury produced by extreme packing densities.
Filtration-induced production of conductive/robust Cu films on cellulose paper by low-temperature sintering in air

Cellulose paper is an attractive substrate for paper electronics because of its advantages of flexibility, biodegradability, easy incorporation into composites, low cost and eco-friendliness. However, the micrometre-sized pores of cellulose paper make robust/conductive films difficult to deposit onto its surface from metal-nanoparticle-based inks. We developed a Cu-based composite ink to deposit conductive Cu films onto cellulose paper via low-temperature sintering in air. The Cu-based inks consisted of a metallo-organic decomposition ink and formic-acid-treated Cu flakes. The composite ink was heated in air at 100°C for only 15 s to give a conductive Cu film (7 × 10−5 Ω cm) on the cellulose paper. Filtration of the Cu-based composite ink accumulated Cu flakes on the paper, which enabled formation of a sintered Cu film with few defects. A strategy was developed to enhance the bending stability of the sintered Cu films on paper substrates using polyvinylpyrrolidone-modified Cu flakes and amine-modified paper. The resistance of the Cu films increased only 1.3-fold and 1.1-fold after 1000 bending cycles at bending radii of 5 mm and 15 mm, respectively. The results of this study provide an approach to increasing the bending stability of Cu films on cellulose paper.
Image compression via multiple sampling-rate downsampling and super-resolution upconversion

Abstract. An image compression method utilizing multiple sampling-rate downsampling and super-resolution upconversion is proposed. The multiple sampling-rate downsampling modes and different quantization patterns are designed for each 32 × 32 macroblock at the encoder side. Meanwhile, the rate distortion optimization strategy is investigated to obtain the optimal downsampling and quantization mode. The chosen mode is used to downsample and code the original macroblocks. To obtain the full resolution block, the deep learning-based multiple models super-resolution upconversion is designed to reconstruct the decoded block at the decoder side. The experimental results demonstrate that our method can obtain the higher quality compressed image than JPEG and some state-of-the-art downsampling-based methods at almost all bit rates. At the same decoded image quality, our method can achieve 30% to 55% bit savings at low bit rates and 15% to 30% bit savings at medium to high bit rates. In addition, the proposed framework is applicable to other image compression standards.
LES and Wind Tunnel Test of Flow around Two Tall Buildings in Staggered Arrangement

Wind flow structures and their consequent wind loads on two high-rise buildings in staggered arrangement are investigated by Large Eddy Simulation (LES). Synchronized pressure and flow field measurements by particle image velocimetry (PIV) are conducted in a boundary layer wind tunnel to validate the numerical simulations. The instantaneous and time-averaged flow fields are analyzed and discussed in detail. The coherent flow structures in the building gap are clearly observed and the upstream building wake is found to oscillate sideways and meander down to the downstream building in a coherent manner. The disruptive effect on the downstream building wake induced by the upstream building is also observed. Furthermore, the connection between the upstream building wake and the wind loads on the downstream building is explored by the simultaneous data of wind pressures and wind flow fields.
Correlated Differential Privacy Protection for Big Data

Aiming at the privacy leakage problem of traditional differential privacy function in correlated datasets, a novel improved method based on machine learning and maximum information coefficient (MIC) was proposed, which improved the difference privacy of correlated datasets in big data. On this basis, the r-CBDP (r-Correlated Block Differential Privacy) protection model was proposed. Firstly r-CBDP used MIC and machine learning to determine the dependencies between correlated datasets, accurately calculated the correlated sensitivity of the query function, and then used clustering to divide big data into independent blocks, and implemented r-CBDP protection of data blocks to achieve the whole big data correlated differentiated privacy protection.
QAware: A Cross-Layer Approach to MPTCP Scheduling

Multipath TCP (MPTCP) allows applications to transparently use all available network interfaces by creating a TCP subflow per interface. One critical component of MPTCP is the scheduler that decides which subflow to use for each packet. Existing schedulers typically use estimates of end-to-end path properties, such as delay and bandwidth, for making the scheduling decisions. In this paper, we show that these scheduling decisions can be significantly improved by including readily available local information from the device driver queues to the decision-making process. We propose QAware, a novel cross-layer approach for MPTCP scheduling. QAware combines end-to-end delay estimates with local queue buffer occupancy information and allows for a better and faster adaptation to the network conditions. This results in more efficient use of the available resources and considerable gains in aggregate throughput. We present the design of QAware and evaluate its performance through simulations, and also through real experiments, comparing it to existing schedulers. Our results show that QAware performs significantly better than other available approaches for all use-cases and applications.
Modeling the Perceptual Quality of Immersive Images Rendered on Head Mounted Displays: Resolution and Compression

We develop a model that expresses the joint impact of spatial resolution <inline-formula> <tex-math notation="LaTeX">$s$ </tex-math></inline-formula> and JPEG compression quality factor <inline-formula> <tex-math notation="LaTeX">$q^{f}$ </tex-math></inline-formula> on immersive image quality. The model is expressed as the product of optimized exponential functions of these factors. The model is tested on a subjective database of immersive image contents rendered on a head mounted display. High Pearson correlation and Spearman correlation (>0.95) and small relative root mean squared error (<5.6%) are achieved between the model predictions and the subjective quality judgements. The immersive ground-truth images along with the rest of the database are made available for future research and comparisons.
Kernel multiblock partial least squares for a scalable and multicamera person reidentification system

Abstract. Person reidentification (Re-ID) aims at establishing global identities for individuals as they move across a camera network. It is a challenging task due to the drastic appearance changes that occur between cameras as a consequence of different pose and illumination conditions. Pairwise matching models yield state-of-the-art results in most of the person Re-ID datasets by capturing nuances that are robust and discriminative for a specific pair of cameras. Nonetheless, pairwise models are not scalable with the number of surveillance cameras. Therefore, elegant solutions combining scalability with high matching rates are crucial for the person Re-ID in real-world scenarios. We tackle this problem proposing a multicamera nonlinear regression model called kernel multiblock partial least squares (kernel MBPLS), a single subspace model for the entire camera network that uses all the labeled information. In this subspace, probe and gallery individual can be successfully matched. Experimental results in three multicamera person Re-ID datasets (WARD, RAiD, and SAIVT-SoftBIO) demonstrate that the kernel MBPLS presents favorable aspects, such as the scalability and robustness with respect to the number of cameras combined with the high matching rates.
FHIT, a Novel Modifier Gene in Pulmonary Arterial Hypertension

Rationale: Pulmonary arterial hypertension (PAH) is characterized by progressive narrowing of pulmonary arteries, resulting in right heart failure and death. BMPR2 (bone morphogenetic protein receptor type 2) mutations account for most familial PAH forms whereas reduced BMPR2 is present in many idiopathic PAH forms, suggesting dysfunctional BMPR2 signaling to be a key feature of PAH. Modulating BMPR2 signaling is therapeutically promising, yet how BMPR2 is downregulated in PAH is unclear. Objectives: We intended to identify and pharmaceutically target BMPR2 modifier genes to improve PAH. Methods: We combined siRNA high‐throughput screening of >20,000 genes with a multicohort analysis of publicly available PAH RNA expression data to identify clinically relevant BMPR2 modifiers. After confirming gene dysregulation in tissue from patients with PAH, we determined the functional roles of BMPR2 modifiers in vitro and tested the repurposed drug enzastaurin for its propensity to improve experimental pulmonary hypertension (PH). Measurements and Main Results: We discovered FHIT (fragile histidine triad) as a novel BMPR2 modifier. BMPR2 and FHIT expression were reduced in patients with PAH. FHIT reductions were associated with endothelial and smooth muscle cell dysfunction, rescued by enzastaurin through a dual mechanism: upregulation of FHIT as well as miR17‐5 repression. Fhit−/− mice had exaggerated hypoxic PH and failed to recover in normoxia. Enzastaurin reversed PH in the Sugen5416/hypoxia/normoxia rat model, by improving right ventricular systolic pressure, right ventricular hypertrophy, cardiac fibrosis, and vascular remodeling. Conclusions: This study highlights the importance of the novel BMPR2 modifier FHIT in PH and the clinical value of the repurposed drug enzastaurin as a potential novel therapeutic strategy to improve PAH.
Comparison of Induction Heating for Pans and Woks Using Planar Cooktops

In this paper, the heating performance of the pan-shaped and wok-shaped utensils on a same planar induction cooktop is analyzed and compared. Generally, the domestic induction cooker has a planar cooktop and adaptively heats pan-shaped utensils based on the magnetic induction mechanism. However, the shape of utensils are different in different cooking methods or cultures, specifically, the wok-shaped utensils are extremely popular in Asian countries. Therefore, the heating performance of the pan-shaped and wok-shaped utensils on a same planar induction cooktop should be considered and analyzed. This paper compares the thermal effect of the aforementioned utensils under the same planar cooktop theoretically and numerically. Abundant simulation results such as the magnetic flux density, eddy current distribution, Joule loss density and temperatures are given to validate the theoretical calculation. Finally, a possible solution is proposed to conquer the problem.
On the Road to Industry 4.0: A Fieldbus Architecture to Acquire Specific Smart Instrumentation Data in Existing Industrial Plant for Predictive Maintenance

In this paper we present our work which is part of the opportunity to implement Industry 4.0 roadmap in the context of AP-913 methodology. Advanced Process 913 is defined by World Association of Nuclear Operators. It is intended to increase Equipment Reliability and enhance the System Performance. In this context, Predictive Maintenance is part of the process and it requires accurate operating information gathered from various sources including particularly instrumentation health. To achieve this, the development of a fieldbus architecture for the acquisition of specific smart instrumentation data is presented. The challenge is to preserve the main 4-20mA current loop from any functional disruption and interruption of service as these valves are already deployed and connected to Programmable Logic Controller using standard 4-20mA current loop. To solve such a challenge, validation tests on a representative platform are presented to verify that there is no impact on the existing control flow.
High-Content Screening Campaign to Identify Compounds That Inhibit or Disrupt Androgen Receptor-Transcriptional Intermediary Factor 2 Protein-Protein Interactions for the Treatment of Prostate Cancer.

Twenty percent of prostate cancer (PCa) patients develop a noncurable drug-resistant form of the disease termed castration-resistant prostate cancer (CRPC). Overexpression of Androgen Receptor (AR) coactivators such as transcriptional intermediary factor 2 (TIF2) is associated with poor CRPC patient outcomes. We describe the implementation of the AR-TIF2 protein-protein interaction biosensor (PPIB) assay in a high-content screening (HCS) campaign of 143,535 compounds. The assay performed robustly and reproducibly and enabled us to identify compounds that inhibited dihydrotestosterone (DHT)-induced AR-TIF2 protein-protein interaction (PPI) formation or disrupted preexisting AR-TIF2 PPIs. We used multiparameter HCS data z-scores to identify and deprioritize cytotoxic or autofluorescent outliers and confirmed the resulting qualified actives in triplicate. None of the confirmed AR-TIF2 PPIB inhibitors/disruptors exhibited activity in a p53-hDM2 PPIB counter screen, indicating that they were unlikely to be either nonselective PPI inhibitors or to interfere with the biosensor assay format. However, eight confirmed AR-TIF2 PPIB actives also inhibited the glucocorticoid receptor (GR) nuclear translocation counter screen by >50%. These compounds were deprioritized because they either lacked AR specificity/selectivity, or they inhibited a shared component of the AR and GR signaling pathways. Twenty-nine confirmed AR-TIF2 PPIB actives also inhibited the AR nuclear localization counter screen, suggesting that they might indirectly inhibit the AR-TIF2 PPIB assay rather than directly blocking/disrupting PPIs. A total of 62.2% of the confirmed actives inhibited the DHT-induced AR-TIF2 PPI formation in a concentration-dependent manner with IC50s < 40 μM, and 59.4% also disrupted preexisting AR-TIF2 PPI complexes. Overall, the hit rate for the AR-TIF2 PPIB HCS campaign was 0.12%, and most hits inhibited AR-TIF2 PPI formation and disrupted preexisting AR-TIF2 complexes with similar AR-red fluorescent protein distribution phenotypes. Further secondary and tertiary hit characterization assays are underway to select AR-TIF2 PPI inhibitor/disruptor hits suitable for medicinal chemistry lead optimization and development into novel PCa/CRPC therapeutics.
Self-Organizing Neuroevolution for Solving Carpool Service Problem With Dynamic Capacity to Alternate Matches

Traffic congestion often incurs environmental problems. One of the most effective ways to mitigate this is carpooling transportation, which substantially reduces automobile demands. Due to the popularization of smartphones and mobile applications, a carpool service can be conveniently accessed via the intelligent carpool system. In this system, the service optimization required to intelligently and adaptively distribute the carpool participant resources is called the carpool service problem (CSP). Several previous studies have examined viable and preliminary solutions to the CSP by using exact and metaheuristic optimization approaches. For CSP-solving, evolutionary computation (e.g., metaheuristics) is a more promising option in comparison to exact-type approaches. However, all the previous state-of-the-art approaches use pure optimization to solve the CSP. In this paper, we employ the framework of neuroevolution to propose the self-organizing map-based neuroevolution (SOMNE) solver by which the SOM-like network represents the abstract CSP solution and is well-trained by using neural learning and evolutionary mechanism. The experimental section of this paper investigates the comparisons and analyses of two objective functions of the CSP and demonstrates that the proposed SOMNE solver achieves superior results when compared against those the other approaches produce, especially in regard to the optimization of the primary objective functions of the CSP. Finally, the visual results of the SOM are illustrated to show the effectiveness and efficiency of the evolutionary neural learning process.