Miracle-dz/UniFAR-FTUs huggingface dataset:
Knowledge gain or system benefit in environmental decision making

The quality of environmental decisions are gauged according to the management objectives of a conservation project. Management objectives are generally about maximising some quantifiable measure of system benefit, for instance population growth rate. They can also be defined in terms of learning about the system in question, in such a case actions would be chosen that maximise knowledge gain, for instance in experimental management sites. Learning about a system can also take place when managing practically. The adaptive management framework (Walters 1986) formally acknowledges this fact by evaluating learning in terms of how it will improve management of the system and therefore future system benefit. This is taken into account when ranking actions using stochastic dynamic programming (SDP). However, the benefits of any management action lie on a spectrum from pure system benefit, when there is nothing to be learned about the system, to pure knowledge gain. The current adaptive management framework does not permit management objectives to evaluate actions over the full range of this spectrum. By evaluating knowledge gain in units distinct to future system benefit this whole spectrum of management objectives can be unlocked. This paper outlines six decision making policies that differ across the spectrum of pure system benefit through to pure learning. The extensions to adaptive management presented allow specification of the relative importance of learning compared to system benefit in management objectives. Such an extension means practitioners can be more specific in the construction of conservation project objectives and be able to create policies for experimental management sites in the same framework as practical management sites.
Dynamics of translation can determine the spatial organization of membrane-bound proteins and their mRNA

Significance Unlike their eukaryotic counterparts, bacterial cells are composed of a single compartment. This allows many rapidly diffusing macromolecules, such as proteins and mRNAs, to be evenly distributed in the cell. Important exceptions are proteins embedded in the cell membrane, which transport material and information across the membrane. Often these proteins attach to the membrane before their translation is complete, anchoring their mRNAs to the vicinity of the membrane. This coupling between translation and localization suggests that the dynamics of translation may shape the spatial organization. In this paper, we use a canonical model of nonequilibrium statistical physics to characterize this connection and show how tunable kinetic properties allow the cell to regulate the spatial organization of both mRNAs and proteins. Unlike most macromolecules that are homogeneously distributed in the bacterial cell, mRNAs that encode inner-membrane proteins can be concentrated near the inner membrane. Cotranslational insertion of the nascent peptide into the membrane brings the translating ribosome and the mRNA close to the membrane. This suggests that kinetic properties of translation can determine the spatial organization of these mRNAs and proteins, which can be modulated through posttranscriptional regulation. Here we use a simple stochastic model of translation to characterize the effect of mRNA properties on the dynamics and statistics of its spatial distribution. We show that a combination of the rate of translation initiation, the availability of secretory apparatuses, and the composition of the coding region determines the abundance of mRNAs near the membrane, as well as their residence time. We propose that the spatiotemporal dynamics of mRNAs can give rise to protein clusters on the membrane and determine their size distribution.
Related Work A large body of research on data reuse exploration methodologies for multimedia applications has led to numerous approaches for improving memory latency and reducing their energy footprint

Thread-level and data-level parallel architectures have become the design of choice in many of today’s energy-efficient computing systems. However, these architectures put substantially higher requirements on the memory subsystem than scalar architectures, making memory latency and bandwidth critical in their overall efficiency. Data reuse exploration aims at reducing the pressure on the memory subsystem by exploiting the temporal locality in data accesses. In this paper, we investigate the effects on performance and energy from a data reuse methodology combined with parallelization and vectorization in multiand many-core processors. As a test case, a full-search motion estimation kernel is evaluated on Intel R © CoreTM i7-4700K (Haswell) and i7-2600K (Sandy Bridge) multi-core processors, as well as on an Intel R © Xeon PhiTM many-core processor (Knights Landing) with Streaming Single Instruction Multiple Data (SIMD) Extensions (SSE) and Advanced Vector Extensions (AVX) instruction sets. Results using a single-threaded execution on the Haswell and Sandy Bridge systems show that performance and EDP (Energy Delay Product) can be improved through data reuse transformations on the scalar code by a factor of ≈3× and ≈6×, respectively. Compared to scalar code without data reuse optimization, the SSE/AVX2 version achieves ≈10×/17× better performance and ≈92×/307× better EDP, respectively. These results can be improved by 10% to 15% using data reuse techniques. Finally, the most optimized version using data reuse and AVX512 achieves a speedup of ≈35× and an EDP improvement of ≈1192× on the Xeon Phi system. While single-threaded execution serves as a common reference point for all architectures to analyze the effects of data reuse on both scalar and vector codes, scalability with thread count is also discussed in the paper.
Efficient skyline querying with variable user preferences on nominal attributes

Current skyline evaluation techniques assume a fixed ordering on the attributes. However, dynamic preferences on nominal attributes are more realistic in known applications. In order to generate online response for any such preference issued by a user, one obvious solution is to enumerate all possible preferences and materialize all results of these preferences. However, the pre-processing and storage requirements of a full materialization are typically prohibitive. Instead, we propose a semi-materialization method called the IPO-tree Search which stores partial useful results only. With these partial results, the result of each possible preference can be returned efficiently. We have also conducted experiments to show the efficiency of our proposed algorithm.
1 H NMR and Rheological Studies of the Calcium Induced Gelation Process in Aqueous Low Methoxyl Pectin Solutions

The H NMR relaxometry in combination with water proton spin–spin relaxation time measurements and rheometry have been applied to study the ionic gelation of 1% w/w aqueous low methoxyl pectin solution induced by divalent Ca cations from a calcium chloride solution. The model-free approach to the analysis of H NMR relaxometry data has been used to separate the information on the static (β) and dynamic (〈τc〉) behaviour of the systems tested. The H NMR results confirm that the average mobility of both water and the pectin molecules is largely dependent on the concentration of the cross-linking agent. The character of this dependency (β, 〈τc〉 and T2 vs. CaCl2 concentration) is consistent with the two-stage gelation process of low methoxyl pectin, in which the formation of strongly linked dimer associations (in the range of 0–2.5 mM CaCl2) is followed by the appearance of weak inter-dimer aggregations (for CaCl2 ≥ 3.5 mM). The presence of the weak gel structure for the sample with 3.5 mM CaCl2 has been confirmed by rheological measurements. Apart from that, the T1 and T2 relaxation times have been found to be highly sensitive to the syneresis phenomenon, which can be useful to monitor the low methoxyl pectin gel network stability.
Automatic Identification of Human Blastocyst Components via Texture

Choosing the most viable embryo during human in vitro fertilization (IVF) is a prime factor in maximizing pregnancy rate. Embryologists visually inspect morphological structures of blastocysts under microscopes to gauge their health. Such grading introduces subjectivity amongst embryologists and adds to the difficulty of quality control during IVF. In this paper, we introduce an algorithm for automatic segmentation of two main components of human blastocysts named: Trophectoderm (TE) and inner cell mass (ICM). We utilize texture information along with biological and physical characteristics of day-5 human embryos (blastocysts) to identify TE or ICM regions according to their intrinsic properties. Both these regions are highly textured and very similar in the quality of their texture, and they often look connected to each other when imaged. These attributes make their automatic identification and separation from each other a difficult task even for an expert embryologist. By automatically identifying TE and ICM regions, we offer the opportunity to perform more detailed assessment of blastocysts. This could help in analyzing, in a quantitative way, various visual/geometrical characteristics of these regions that when combined with the pregnancy outcome can determine the predictive values of such attributes. Our work aids future research in understanding why certain embryos have higher pregnancy success rates. This paper is tested on a set of 211 blastocyst images. We report an accuracy of 86.6% for identification of TE and 91.3% for ICM.
Fracture Toughness of Iron Boride Layers Obtained by Paste Boriding Process

The fracture toughness of the Fe2B phase was evaluated in this study. Formation of the Fe2B boride is carried out though paste boriding process applied on AISI 1045 steel surface. The treatment was carried out at temperatures of 1193, 1223 and 1273 K for 6 h using a 5 mm thick boron paste. A Vickers microhardness tester was used to generate microcracks at a load of 200g. The indentations were made across the thickness of the iron boride layer at four different distances from the substrate. The experimental results show that the critical stress intensity factor KIC for the Fe2B phase shows a potential law dependence on crack length; this contradicts the concepts of Linear Elastic Fracture Mechanics, which establish that the fracture toughness value is a constant of the material.
Fast SVM training using approximate extreme points

Applications of non-linear kernel support vector machines (SVMs) to large data sets is seriously hampered by its excessive training time. We propose a modification, called the approximate extreme points support vector machine (AESVM), that is aimed at overcoming this burden. Our approach relies on conducting the SVM optimization over a carefully selected subset, called the representative set, of the training data set. We present analytical results that indicate the similarity of AESVM and SVM solutions. A linear time algorithm based on convex hulls and extreme points is used to compute the representative set in kernel space. Extensive computational experiments on nine data sets compared AESVM to LIBSVM (Chang and Lin, 2011), CVM (Tsang et al., 2005), BVM (Tsang et al., 2007), LASVM (Bordes et al., 2005), SVMperf (Joachims and Yu, 2009), and the random features method (Rahimi and Recht, 2007). Our AESVM implementation was found to train much faster than the other methods, while its classification accuracy was similar to that of LIBSVM in all cases. In particular, for a seizure detection data set, AESVM training was almost 500 times faster than LIBSVM and LASVM and 20 times faster than CVM and BVM. Additionally, AESVM also gave competitively fast classification times.
Physical Mechanisms of Inactivation of Bacillus subtilis Spores Using Cold Atmospheric Plasmas

This paper presents a detailed study of the potential physical mechanisms of the microbial inactivation by cold atmospheric plasmas. With the Bacillus subtilis spores as a model microorganism and an atmospheric-plasma plume in helium flow, optical emission spectroscopy and inactivation kinetics are used to demonstrate the dominating role played by the reactive oxygen species (e.g., atomic oxygen and OH) as well as the minor contributions of the UV photons, heat, charged particles, and electric fields. To differentiate the concentrations of the reactive oxygen species, an atmospheric helium-oxygen plasma is also used for the spore inactivation. Results with the helium and the helium-oxygen plasmas are contrasted to highlight how the production of the spore-killing oxygen species may be enhanced
The effects of plantation practice on soil properties based on the comparison between natural and planted forests: a meta-analysis

Aim The effects of planted forests on soils are of great concern in the context of the increasing demands for timber production and atmospheric CO2 sequestration. However, the effects of plantations on soil properties have not well been quantified. We determined the effects of plantation practice on soil properties based on a comparison between natural forests and plantations. Locations All the continents except for Antarctica. Methods The meta-analysis approach was used to examine the differences in 14 soil variables in the mineral layer, including pH, bulk density, C, N, P, K, Ca, Mg, Na and Al concentrations, C/N ratio, cation exchangeable capacity, base saturation, and moisture between plantations and their adjacent natural forests from 73 published studies. Results Plantations did not differ from natural forests in soil pH or soil Na and Al concentrations. Soil bulk density below plantations increased by 12.5%, and soil C and N concentrations decreased by 36.0% and 26.5%, respectively, relative to natural forests. The other eight variables were 8.4–30.6% lower in plantations than in natural forests. The general patterns also held true for planted trees from the genus Pinus and for study regions in China. The patterns for soil bulk density and C and N concentrations were not different between the two groups in relation to various factors: stand age (< 25 years versus ≥ 25 years), leaf form (broadleaved versus coniferous) and leaf seasonality (deciduous versus evergreen), tree species origin (native versus exotic), land-use history (afforestation versus reforestation) and site preparation for plantations (burnt versus un-burnt treatment), and biogeographic zone (tropical versus temperate). Main conclusions Our results suggest that the level of soil fertility in plantations is unlikely to restore to the level in natural forests, implying that the replacement of natural forests by plantations may be a practice best avoided to maintain the ecosystem sustainability.
Quick, Practical Selection of Effective Seeds for Homology Search

It has been observed that in homology search gapped seeds have better sensitivity than ungapped ones for the same cost (weight). In this paper, we propose a probability leakage model (a dissipative Markov system) to elucidate the mechanism that confers power to spaced seeds. Based on this model, we identify desirable features of gapped search seeds and formulate an extremely efficient procedure for seed design: it samples from the set of spaced seed exhibiting those features, evaluates their sensitivity, and then selects the best. The sensitivity of the constructed seeds is negligibly less than that of the corresponding known optimal seeds. While the challenging mathematical question of characterizing optimal search seeds remains open, we believe that our eminently efficient and effective approach represents a satisfactory solution from a practitioner's viewpoint.
Jak‐inhibitors and UV‐B: Potential combined therapy for vitiligo

Vitiligo is an autoimmune condition caused by CD81 T lymphocyte mediated destruction of melanocytes (Damsky & King, 2017). While the condition is not dangerous, patients are greatly affected psychosocially by the condition, as they are left with patches of hypopigmentation which are cosmetically disfiguring. The goal of treatment is repigmentation of the patches; however, the current mainstays of treatment, such as light therapy, topical steroids, and topical tacrolimus have limited efficacy (Boniface, Seneschal, Picardo, & Taieb, 2017). Oral tofacitinib and topical ruxolitinib, Jak kinase inhibitors, were recently introduced as treatment modalities for vitiligo. An initial pilot study reported almost complete repigmentation, with <5% body surface area affected by hypopigmentation, over a 5month period in a patient treated with oral tofacitinib (Craiglow & King, 2015). With discontinuation of the medication, however, the patient’s vitiligo returned to their pre-treatment baseline (Craiglow & King, 2015). Topical ruxolitinib 1.5% cream was also studied revealing 76% (95% confidence interval, 53–99%; p5 .001) improvement in facial Vitiligo Area Scoring Index scores and 23% (95% confidence interval, 4–43%; p5 .02) improvement in overall Vitiligo Area Scoring Index scores over a 20-week period. Another study demonstrated two patients with vitiligo using Jak kinase inhibitors whose repigmentation was improved with sun exposure (Joshipura, Plotnikova, Goldminz, et al., 2017). Overall, studies are promising regarding the use of Jak-inhibitors in the treatment of vitiligo. Furthermore, this effect may be exaggerated when combined with ultraviolet (UV) radiation, specifically UV-B therapy (Joshipura, Plotnikova, Goldminz, et al., 2017). Theoretically, combined treatment with UV-B therapy may increase skin repigmentation since UV-B therapy has been shown to cause immunosuppression and melanocyte stimulation (Joshipura, Plotnikova, Goldminz, et al., 2017). Additional studies will be needed to determine whether Jak-inhibitors, combined with UV-B light therapy, is a safe and effective long term treatment for vitiligo.
Nanocrystalline diamond for medicine

The unique properties of thin amorphous diamond layers make them perspective candidates for producing advanced micro- electronic devices, coatings for cutting tools and optics. Moreover, due to the highest bicompatibility of carbon resulting from the presence of this element in human body, it appears to be a potential biomaterial. Until present the amorphous diamond has found industrial applications in some areas. One of the applications of the carbon layers are coatings for medical implants. The studies of carbon films as coatings for implants in surgery were aimed on the investigations of biological resistance of implants, histopathological investigations on laboratory animals, tests of corrosion resistance, measurements of mechanical properties and a breakdown test in Tyrod solution. The current state of published work in the subject is reviewed in the paper together with a discussion concerning classification of this material.
Betweenness Centrality-Based Consensus Protocol for Second-Order Multiagent Systems With Sampled-Data

This paper designs a new leader-following consensus protocol for second-order multiagent systems with time-varying sampling. For the first time in designing a leader-following protocol, the concept of betweenness centrality is adopted to analyze the information flow in the consensus problem for multiagent systems. By construction of a suitable Lyapunov–Krasovskii functional, some criteria for designing consensus protocols of such systems are established in terms of linear matrix inequalities which can be easily solved by various effective optimization algorithms. One numerical example is given to illustrate the validity of the proposed argument.
Smart Probabilistic Fingerprinting for Indoor Localization over Fog Computing Platforms

Indoor navigation and localization are becoming fundamental services nowadays. WiFi-based solutions such as FingerPrinting (FP) are the most widely adopted techniques for positioning and provide better results if compared to other approaches. They require to compare WiFi Received Signal Strength (RSS) with an pre-computed radio map called fingerprint. The recently proposed Smart Probabilistic FingerPrinting (P-FP) algorithm reduces the computational complexity of the traditional FP approach without any accuracy detriment. On the other hand, fog computing has emerged as a new promising paradigm in the recent years, which extends traditional mobile cloud computing capabilities towards the edge of the network and enables location-aware services. In this paper we propose to offload Smart P-FP computation over a fog platform exploiting a novel distributed algorithm. Performance evaluation validates the effectiveness of the proposed approach with the analysis of: i) the amount of power saved and ii) the efficiency of candidate selection process for offloading. Having 2 or more devices in the vicinity contributing to the computation makes offloading beneficial from a power standpoint. The offloading effectiveness increases with the number of devices willing to contribute and the amount of data to be transferred. Power savings can be as high as 80% if compared with local computation.
Surface Activation of NiTi Alloy by Using Electrochemical Process for Biomimetic Deposition of Hydroxyapatite Coating (TECHNICAL NOTE)

Electrochemical depositions of calcium phosphate (Ca-P) film on NiTi alloy in concentrated simulated body flood (SBF×5) were carried out by cathodic polarization. The Ca-P layer was successfully deposited on Ni-Ti alloy substrate under 10mA/cm2 current density for 2 hours at room temperature. Then, in order to investigate the bioactivity of the pre-calcified samples, they were immersed in SBF for 1 and 3 days. The microstructure, composition and bioactivity of the coatings were evaluated by using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR) techniques. Results showed that the activation of the surface of the NiTi alloy by electrochemical process can significantly enhance the biomimetic deposition during time. On the other hand, by increasing immersion time of pre-calcified samples in SBF from 1 to 3 days, the biomimetic coating uniformly covered the surface of the sample. The ratio of the Ca/P for the pre-calcified sample after immersion in SBF for 3 days was about 1.5 which is very close to the Ca/P ratio of stoichiometric hydroxyapatite.
A novel methodology for speeding up IC performance in 32nm FinFET

This paper presents a novel methodology for IC speed-up in 32nm FinFET. By taking advantage of independently controlling two gates of IG-FinFET, we develop the boosting structures that can improve the signal propagation on interconnect significantly. Furthermore, the circuit area and power dissipation issues are also taken into account. With the addition of boosting path, the full booster can reduce the delay of interconnect as much as 50% while consuming merely more than 18% of power. In the high-speed and low-power IC designs, the proposed boosting structure gives circuit designers several options in the trade-off between the power consumption and high performance which play an important role in application-specific integration circuits in the 22nm node and beyond.
End-to-End MAP Training of a Hybrid HMM-DNN Model

An hybrid of a hidden Markov model (HMM) and a deep neural network (DNN) is considered. End-to-end training using gradient descent is suggested, similarly to the training of connectionist temporal classification (CTC). We use a maximum a-posteriori (MAP) criterion with a simple language model in the training stage, and a standard HMM decoder without approximations. Recognition results are presented using speech databases. Our method compares favorably to CTC in terms of performance, robustness and quality of alignments.