Miracle-dz/UniFAR-FTUs huggingface dataset:
Radio Frequency Energy Harvesting for Underground Sensor Nodes: Possibilities and Challenges

Radio frequency energy harvesting (RFEH) is considered as one of the possible and environmentally friendly solution for energizing sensor devices and prolonging the lifetime of wireless sensor networks (WSNs). Despite being studied and experimented in several environments where WSNs are used, studies and experiments related to RFEH in underground wireless systems are limited to near-field wireless power transfer (WPT), measurement of received signal strength, and current conduction. The goal of this study is to examine the possibilities and challenges of actualizing RFEH in wireless underground sensor networks (WUSNs). A radio-frequency (RF) spectral survey was conducted, and a comparison was performed with similar surveys conducted worldwide to determine the generally available ambient RF energy. Using the aboveground to underground (AG2UG) RF communication model, the signal path loss was analyzed under varying conditions. By relating the ambient RF power and AG2UG signal path loss, it was found nearly impossible to harvest ambient RF energy with the harvesting antenna buried within the soil, as the best-case environment will require a rectenna with sensitivity of at least −62.75dBm. However ambient RF energy can be harvested when the harvesting antenna is in free space, while the other components are underground and will require a high sensitivity of at least −40 dBm. Another possibility for underground RFEH is the use of a dedicated WPT device located 1m above the ground, transmitting at 20 dBm with the RF energy harvester 30 cm below the soil surface with a sensitivity of at least -28.5 dBm.
Water Soluble Usnic Acid-Polyacrylamide Complexes with Enhanced Antimicrobial Activity against Staphylococcus epidermidis

Usnic acid, a potent antimicrobial and anticancer agent, poorly soluble in water, was complexed to novel antimicrobial polyacrylamides by establishment of strong acidic-base interactions. Thermal and spectroscopic analysis evidenced a molecular dispersion of the drug in the polymers and a complete drug/polymer miscibility for all the tested compositions. The polymer/drug complexes promptly dissolved in water and possessed a greater antimicrobial activity against Staphylococcus epidermidis than both the free drug and the polymer alone. The best results were obtained with the complex based on the lowest molecular weight polymer and containing a low drug content. Such a complex showed a larger inhibition zone of bacterial growth and a lower minimum inhibitory concentration (MIC) with respect to usnic acid alone. This improved killing effect is presumably due to the reduced size of the complexes that allows an efficient cellular uptake of the antimicrobial complexes. The killing effect extent seems to be not significantly dependent on usnic acid content in the samples.
Bifurcation into Functional Niches in Adaptation

One of the central questions in evolutionary biology concerns the dynamics of adaptation and diversification. This issue can be addressed experimentally if replicate populations adapting to identical environments can be investigated in detail. We have studied 501 such replicas using digital organisms adapting to at least two fundamentally different functional niches (survival strategies) present in the same environment: one in which fast replication is the way to live, and another where exploitation of the environment's complexity leads to complex organisms with longer life spans and smaller replication rates. While these two modes of survival are closely analogous to those expected to emerge in so-called r and K selection scenarios respectively, the bifurcation of evolutionary histories according to these functional niches occurs in identical environments, under identical selective pressures. We find that the branching occurs early, and leads to drastic phenotypic differences (in fitness, sequence length, and gestation time) that are permanent and irreversible. This study confirms an earlier experimental effort using microorganisms, in that diversification can be understood at least in part in terms of bifurcations on saddle points leading to peak shifts, as in the picture drawn by Sewall Wright.
Multi-view Multi-modal Feature Embedding for Endomicroscopy Mosaic Classification

Probe-based confocal laser endomicroscopy (pCLE) is an emerging tool for epithelial cancer diagnosis, which enables in vivo microscopic imaging during endoscopic procedures. As a new technique, definite clinical diagnosis is still referenced to the gold standard histology images. In this paper, we propose a Multi-View Multi-Modal Embedding framework (MVMME) to learn representative features for pCLE videos exploiting both pCLE mosaic and histology images. Each pCLE mosaic is represented by multiple feature representations including SIFT, Texton and HoG. A latent space is discovered by embedding the visual features from both mosaics and histology images in a supervised scheme. The features extracted from the latent spaces can make use of multi-modal imaging sources that are more discriminative than unimodal features from mosaics alone. The experiments based on real pCLE datasets demonstrate that our approach outperforms, with statistical significance, several single-view or single-modal methods. A binary classification accuracy of 96% has been achieved.
Poster abstract: Accurate monitoring of circardian rhythms using wearable Body Sensor Networks

Monitoring the impact of sleep deprivation on thermoregulation requires a careful measurement of skin temperature across the human body to have precise knowledge and understanding of the stability of circadian rhythms, the 24-hour cycles of biological activity. However, medical measurements and clinical trials are often carried out in controlled lab settings, which limits the realism and the duration of data collections, and increases significantly their costs. We aim to provide medical researchers studying the stability of the circadian rhythms with a tool for higher quality data collections. We design and develop a wireless unobtrusive monitoring system for accurate body temperature measurements to be worn by patients for several weeks while they live their normal life. Obtaining a long-lasting highly-accurate measurement system is challenging, as energy and computational resources are severely constrained in miniaturized wearable sensor nodes. We develop a prototype of an active temperature measurement system with 0.02°C accuracy, a lifetime of up to 3 weeks, and real-time feedback to a remote medic. Our preliminary experiments show that we can identify the circadian rhythms also in non-ambulatory environments, indicating that our tool could become a valuable asset for medical research.
Spatio-temporal image-based texture atlases for dynamic 3-D models

In this paper, we propose a method for creating a high-quality spatio-temporal texture atlas from a dynamic 3-D model and a set of calibrated video sequences. By adopting an actual spatio-temporal perspective, beyond independent frame-by-frame computations, we fully exploit the very high redundancy in the input video sequences. First, we drastically cut down on the amount of texture data, and thereby we greatly enhance the portability and the rendering efficiency of the model. Second, we gather the numerous different viewpoint/time appearances of the scene, so as to recover from low resolution, grazing views, highlights, shadows and occlusions which affect some regions of the spatio-temporal model. Altogether, our method allows the synthesis of novel views from a small quantity of texture data, with an optimal visual quality throughout the sequence, with minimally visible color discontinuities, and without flickering artifacts. These properties are demonstrated on real datasets.
The Impact of High-Intensity Interval Exercise Including Acceleration/Deceleration Patterns on Redox Status of Healthy Male Adults

High-intensity interval exercise (HIIE) is a type of structured physical training characterized by repeated bouts of high-intensity exercise interspersed with recovery periods. Although HIIE was found to improve physical performance in a relatively short period of time, there is emerging evidence suggesting that acute HIIE may induce oxidative stress. The purpose, therefore, of the present study was to examine the effect of intermittency and/or acceleration during HIIE on oxidative stress in male participants. Nine healthy males [(age: 21.0 ± 3.0 years; height: 180.0 ± 4.0 cm; body mass: 79.4 ± 7.9 kg; maximal oxygen uptake (V˙O2max) 52.0 ± 6.0 mL·kg−1·min−1)] were recruited to perform six distinct exercise protocols of various intermittency (high, medium, and low) and acceleration (high, medium, and low) while a control session was also included. Blood samples were obtained to determine oxidative stress indices (lipid hydroperoxides, superoxide dismutase, and total glutathione) at rest, 1 h, 2 h, and 24 h following exercise on a non-motorized treadmill. The intra-individual variability of participants was observed in lipid hydroperoxides at baseline, ranging from 1.80 to 20.69 μmol·L−1. No significant differences among the six different exercise protocols in any of the oxidative stress indices evaluated were observed (p > 0.05). These results suggest that the influence of various intermittency levels and acceleration patterns upon exercise-induced oxidative stress is negligible.
Frame Skip Is a Powerful Parameter for Learning to Play Atari

We show that setting a reasonable frame skip can be critical to the performance of agents learning to play Atari 2600 games. In all of the six games in our experiments, frame skip is a strong determinant of success. For two of these games, setting a large frame skip leads to state-of-the-art performance. The rate at which an agent interacts with its environment may be critical to its success. In the Arcade Learning Environment (ALE) (Bellemare et al. 2013) games run at sixty frames per second, and agents can submit an action at every frame. Frame skip is the number of frames an action is repeated before a new action is selected. Existing reinforcement learning (RL) approaches use static frame skip: HNEAT (Hausknecht et al. 2013) uses a frame skip of 0; DQN (Mnih et al. 2013) uses a frame skip of 2-3; SARSA and planning approaches (Bellemare et al. 2013) use a frame skip of 4. When action selection is computationally intensive, setting a higher frame skip can significantly decrease the time it takes to simulate an episode, at the cost of missing opportunities that only exist at a finer resolution. A large frame skip can also prevent degenerate super-human-reflex strategies, such as those described by Hausknecht et al. for Bowling, Kung Fu Master, Video Pinball and Beam Rider. We show that in addition to these advantages agents that act with high frame skip can actually learn faster with respect to the number of training episodes than those that skip no frames. We present results for six of the seven games covered by Mnih et al.: three (Beam Rider, Breakout and Pong) for which DQN was able to achieve near- or superhuman performance, and three (Q*Bert, Space Invaders and Seaquest) for which all RL approaches are far from human performance. These latter games were understood to be difficult because they require ‘strategy that extends over long time scales. ’ In our experiments, setting a large frame skip was critical to achieving state-of-the-art performance in two of these games: Space Invaders and Q*Bert. More generally, the frame skip parameter was a strong determinant of performance in all six games. Our learning framework is a variant of Enforced Subpopulations (ESP) (Gomez and Miikkulainen 1997), a neuroevolution approach that has been successfully imple
Preparing to analyse data

Journal of Pharmacology and Pharmacotherapeutics | January-June 2010 | Vol 1 | Issue 1 Understanding biostatistics is important for a biomedical researcher because modern day research methodology is based on the principles of statistics. Determination of sample size, sampling techniques, bias eliminating techniques such as randomization, summarizing data, interpretation of data and many other procedures followed in research use statistical methods so that the predictions or conclusions drawn at the end of a study are valid (validity) and can be applied to the population (generalization) from which the sample is drawn. Not only students but also many budding biomedical researchers develop a dislike for statistics which stems from blindly following the steps of statistical methods for data analysis without understanding the principles behind the statistical procedures. The application of statistical methods is considered by many a ritual at the end of the study rather than an important aspect that has a role in every step of research from planning till publication.
Correcting interperspective aliasing in autostereoscopic displays

An image presented on an autostereoscopic system should not contain discontinuities between adjacent views. A viewer should experience a continuous scene when moving from one view to the next. If corresponding points in two perspectives do not spatially abut, a viewer will experience jumps in the scene. This is known as interperspective aliasing. Interperspective aliasing is caused by object features far away from the stereoscopic screen being too small, which results in visual artifacts. By modeling a 3D point as a defocused image point, we can adapt Fourier analysis to devise a depth-dependent filter kernel that allows filtering of a stereoscopic 3D image. For synthetic 3D data, we use a simpler approach, which is to smear the data by a distance proportional to its depth
A photoactivated nanofiber graft material for augmented Achilles tendon repair

Suture repair of Achilles tendon rupture can cause infection, inflammation and scarring, while prolonged immobilization promotes adhesions to surrounding tissues and joint stiffness. Early mobilization can reduce complications provided the repair is strong enough to resist re‐rupture. We have developed a biocompatible, photoactivated tendon wrap from electrospun silk (ES) to provide additional strength to the repair that could permit early mobilization, and act as a barrier to adhesion formation.
Speeding-up Logic Programs by Combining EBG and FOIL

This paper presents an algorithm that combines traditional EBL techniques and recent developments in inductive logic programming to learn e ective clause selection rules for Prolog programs. When these control rules are incorporated into the original program, signi cant speed-up may be achieved. The algorithm produces not only EBL-like speed up of problem solvers, but is capable of automatically transforming some intractable algorithms into ones that run in polynomial time.
Sindice.com: a document-oriented lookup index for open linked data

Data discovery on the Semantic Web requires crawling and indexing of statements, in addition to the 'linked-data' approach of de-referencing resource URIs. Existing Semantic Web search engines are focused on database-like functionality, compromising on index size, query performance and live updates. We present Sindice, a lookup index over Semantic Web resources. Our index allows applications to automatically locate documents containing information about a given resource. In addition, we allow resource retrieval through inverse-functional properties, offer a full-text search and index SPARQL endpoints. Finally, we extend the sitemap protocol to efficiently index large datasets with minimal impact on data providers.
A Survey on Malware and Malware Detection Systems

Over the last decades, there were lots of studies made on malware and their countermeasures. The most recent reports emphasize that the invention of malicious software is rapidly increasing. Moreover, the intensive use of networks and Internet increases the ability of the spreading and the effectiveness of this kind of software. On the other hand, researchers and manufacturers making great efforts to produce anti-malware systems with effective detection methods for better protection on computers. In this paper, a detailed review has been conducted on the current situation of malware infection and the work done to improve anti-malware or malware detection systems. Thus, it provides an up-to-date comparative reference for developers of malware detection systems.
Stretching transactional memory

Transactional memory (TM) is an appealing abstraction for programming multi-core systems. Potential target applications for TM, such as business software and video games, are likely to involve complex data structures and large transactions, requiring specific software solutions (STM). So far, however, STMs have been mainly evaluated and optimized for smaller scale benchmarks. We revisit the main STM design choices from the perspective of complex workloads and propose a new STM, which we call SwissTM. In short, SwissTM is lock- and word-based and uses (1) optimistic (commit-time) conflict detection for read/write conflicts and pessimistic (encounter-time) conflict detection for write/write conflicts, as well as (2) a new two-phase contention manager that ensures the progress of long transactions while inducing no overhead on short ones. SwissTM outperforms state-of-the-art STM implementations, namely RSTM, TL2, and TinySTM, in our experiments on STMBench7, STAMP, Lee-TM and red-black tree benchmarks. Beyond SwissTM, we present the most complete evaluation to date of the individual impact of various STM design choices on the ability to support the mixed workloads of large applications.
The multicatalytic proteinase: a high-Mr endopeptidase.

Wilk & Orlowski (1980) were the first to describe a cation-sensitive neutral endopeptidase from bovine pituitary, and enzyme they later designated 'multicatalytic protease complex' (Wilk & Orlowski, 1983). Since then, similar or even identical enzymes have been isolated from a variety of tissues and cells, but have been assigned different names, e.g. high molecular weight peptide hydrolase (Edmunds & Pennington, 1982), high molecular weight enzyme (Hardy et al., 1983), high molecular weight cysteine proteinase II/III (Dahlmann et al., 1983), proteinase YscE (Achstetter et al., 1984), multicatalytic proteinase (Dahlmann et al., 1985), neutral endopeptidase (Ray & Harris, 1985), ingensin (Ishiura et al., 1985), alkaline protease (Rivett, 1985), multifunctional protease (Tanaka et al., 1986), macropain (McGuire & DeMartino, 1986), 20 S protease (Hough et al., 1987), endopeptidase-24.5 (Zolfaghari et al., 1987), alkaline serine proteinase (Mykles, 1987), large alkaline multifunctional protease or proteasome (Arrigo et al., 1988). Presently, this enzyme has been classified by the Enzyme Commission as a metalloprotease and assigned the number EC 3.4. 24.5, but, as pointed out elsewhere (Bond & Butler, 1987), the enzyme was erroneously catalogued. Members of most research groups who have published papers on this enzyme attended the 7th International Symposium on Intracellular Protein Catabolism (Shimoda, Japan, May 16-20, 1988) and they took the opportunity to discuss the properties of the enzyme isolated from various tissues. General consensus existed about the following properties of the enzyme: the molecular mass of the native enzyme is 650-670 kDa and it is composed of multiple subunits of 22-34 kDa. The enzyme cleaves peptide substrates with a basic, aromatic and acidic amino acid residue in the P1 position. The pH optima of these activities are within the neutral-alkaline range and the activities are differently affected by several proteinase inhibitors (e.g. leupeptin, antipain, chymostatin). No consensus could be reached as to the amino acid residues of the catalytic site(s) of the enzyme (serine-
A Novel Adaptive Proactive Secret Sharing without a Trusted Party

A (t + 1, n) proactive secret sharing is to protect a secret in long-lived system by distributing it to a group of n participants and refreshing their shares periodically in this fixed group, while any t+1 and more than t+1 shares can reconstruct the secret. In some environment, it needs to change not only the number of participants n but also the threshold value t. An adaptive proactive secret sharing is to refresh the shares as t and n change. In this paper, we propose a novel adaptive proactive secret sharing scheme without a trusted party. Our proposed scheme is uniformly efficient and tolerates t Byzantine faults in any single time interval, where the number of participants n ≥ 3t+1. The threshold value t and the number of participants n can be changed arbitrarily in two adjacent intervals. We also prove that our proposed scheme is secure under the discrete logarithm intractability assumption.
Assessment of reanalysis soil moisture products in the permafrost regions of the central of the Qinghai–Tibet Plateau

The long‐term and large‐scale soil moisture (SM) record is important for understanding land atmosphere interactions and their impacts on the weather, climate, and regional ecosystem. SM products are one of the parameters used in some Earth system models, but these records require evaluation before use. The water resources on the Qinghai–Tibet Plateau (QTP) are important to the water security of billions of people in Asia. Therefore, it is necessary to know the SM conditions on the QTP. In this study, the evaluation metrics of multilayer (0–10, 10–40, and 40–100 cm) SM in different reanalysis datasets of the European Centre for Medium‐Range Weather Forecasts interim reanalysis (ERA‐Interim [ERA]), National Centers for Environmental Prediction Climate Forecast System and the Climate Forecast System version 2 (CFSv2), and China Meteorological Administration Land Data Assimilation System (CLDAS) are compared with in situ observations at 5 observation sites, which represent alpine meadow, alpine swamp meadow, alpine grassy meadow, alpine desert steppe, and alpine steppe environments during the thawing season from January 1, 2011, to December 31, 2013, on the QTP. The ERA SM remains constant at approximately 0.2 m3⋅m−3 at all observation sites during the entire thawing season. The CLDAS and CFSv2 SM products show similar patterns with those of the in situ SM observations during the thawing season. The CLDAS SM product performs better than the CFSv2 and ERA for all vegetation types except the alpine swamp meadow. The results indicate that the soil texture and land cover types play a more important role than the precipitation to increase the biases of the CLDAS SM product on the QTP.