Miracle-dz/UniFAR-FTUs huggingface dataset:
Stereo correspondence with slanted surfaces: critical implications of horizontal slant

We examine the stereo correspondence problem in the presence of slanted scene surfaces. In particular we highlight a previously overlooked geometric fact: a horizontally slanted surface (i.e. having depth variation in the direction of the separation of the two cameras) will appear horizontally stretched in one image as compared to the other image. Thus, while corresponding two images, N pixels on a scanline in one image may correspond to a different number of pixels M in the other image. This leads to three important modifications to existing stereo algorithms: (a) due to unequal sampling, intensity matching metrics such as the popular Birchfield-Tomasi procedure must be modified, (b) unequal numbers of pixels in the two images must be allowed to correspond to each other, and (c) the uniqueness constraint, which is often used for detecting occlusions, must be changed to a 3D uniqueness constraint. This paper discusses these new constraints and provides a simple scanline based matching algorithm for illustration. We experimentally demonstrate test cases where existing algorithms fail, and how the incorporation of these new constraints provides correct results. Experimental comparisons of the scanline based algorithm with standard data sets are also provided.
Sequence-selective intercalation of antitumour bis-naphthalimides into DNA. Evidence for an approach via the major groove.

LU 79553, a bis-naphthalimide drug highly active against human solid tumour xenografts, has been shown to bis-intercalate into DNA with a helix-unwinding angle of 37 degrees. Footprinting experiments with DNase I reveal that the drug is selective for mixed nucleotide sequences characterised by an alternating purine-pyrimidine motif, particularly those containing GpT (ApC) and TpG (CpA) steps. Derivatives bearing nitro or amino substituents on the naphthalimide chromophores bind at essentially identical sites. The footprinting profiles on tyrT DNA and on two fragments from pBS bear a remarkable resemblance to those determined for nogalamycin, an antibiotic which binds intercalatively leaving bulky carbohydrate substituents blocking both the major and minor grooves of the helix. Several lines of evidence indicate that the bis-naphthalimides recognise their preferred binding sites via the unusual expedient of intercalating from the major groove. Footprints on the complementary DNA strands sometimes appear staggered in the 5'direction. Repositioning the 2-amino group of G.C base pairs, which serves as a critical minor-groove marker, by substitution with inosine and/or 2,6-diaminopurine has little effect on the distribution of binding sites for LU 79553. The bis-naphthalimides affect the guanine-specific reaction with dimethyl sulfate (which reacts with the N7 position of the base located in the major groove) but not reactions with tetrachloropalladinate or methylene blue. Photoactivation of LU 79553-DNA complexes leads to a small amount of strand scission mainly at guanine residues. These observations make a strong case for binding via the major groove of the double helix, in contrast to nearly all common intercalating drugs, which could be important in explaining the unique biological selectivity of bis-naphthalimides.
Estimating Bat and Bird Mortality Occurring at Wind Energy Turbines from Covariates and Carcass Searches Using Mixture Models

Environmental impacts of wind energy facilities increasingly cause concern, a central issue being bats and birds killed by rotor blades. Two approaches have been employed to assess collision rates: carcass searches and surveys of animals prone to collisions. Carcass searches can provide an estimate for the actual number of animals being killed but they offer little information on the relation between collision rates and, for example, weather parameters due to the time of death not being precisely known. In contrast, a density index of animals exposed to collision is sufficient to analyse the parameters influencing the collision rate. However, quantification of the collision rate from animal density indices (e.g. acoustic bat activity or bird migration traffic rates) remains difficult. We combine carcass search data with animal density indices in a mixture model to investigate collision rates. In a simulation study we show that the collision rates estimated by our model were at least as precise as conventional estimates based solely on carcass search data. Furthermore, if certain conditions are met, the model can be used to predict the collision rate from density indices alone, without data from carcass searches. This can reduce the time and effort required to estimate collision rates. We applied the model to bat carcass search data obtained at 30 wind turbines in 15 wind facilities in Germany. We used acoustic bat activity and wind speed as predictors for the collision rate. The model estimates correlated well with conventional estimators. Our model can be used to predict the average collision rate. It enables an analysis of the effect of parameters such as rotor diameter or turbine type on the collision rate. The model can also be used in turbine-specific curtailment algorithms that predict the collision rate and reduce this rate with a minimal loss of energy production.
Acid-sensing cation channels

In both the CNS and peripheral nervous system (PNS), energy metabolism, neuronal activity, hypoxia, hypercapnia, and inflammation elicit pH fluctuations that may affect neuronal excitability and function. The acid-sensing ion channels (ASICs) are voltage-independent cation channels that are activated by acidic pH and are expressed in neurons throughout the body. ASICs belong to the degenerin/epithelial sodium (Na+) channel (DEG/ENaC) superfamily, which includes several amiloride-sensitive cation channels. ASICs are primarily permeable to Na+ and elicit cell depolarization, leading to secondary intracellular accumulation of calcium (Ca2+). ASICs in peripheral sensory neurons participate in nociception, mechanosensation, and taste transduction. In the CNS, ASICs are involved in synaptic plasticity, learning, fear conditioning, and maintenance of retinal integrity. Studies using ASIC channel blockers or transgenic mice indicate that ASICs may be involved in several neurologic disorders, including pain, cerebral ischemia, seizures, and neurodegeneration. ASICs may also have a role in anxiety and depression. Therefore, ASICs may represent novel targets for potential treatment of these disorders. The structure, function, modulation, and clinical implications of ASICs have been the subjects of several reviews.1–10
Adsorption of methylene blue onto activated carbon produced from tea (Camellia sinensis L.) seed shells: kinetics, equilibrium, and thermodynamics studies

Tea (Camellia sinensis L.) seed shells, the main byproduct of the manufacture of tea seed oil, were used as precursors for the preparation of tea activated carbon (TAC) in the present study. A high yield (44.1%) of TAC was obtained from tea seed shells via a one-step chemical method using ZnCl2 as an agent. The Brunauer-Emmett-Teller (BET) surface area and the total pore volumes of the obtained TAC were found to be 1 530.67 mg2/g and 0.782 6 cm3/g, respectively. The equilibrium adsorption results were complied with Langmuir isotherm model and its maximum monolayer adsorption capacity was 324.7 mg/g for methylene blue. Adsorption kinetics studies indicated that the pseudo-second-order model yielded the best fit for the kinetic data. An intraparticle diffusion model suggested that the intraparticle diffusion was not the only rate-controlling step. Thermodynamics studies revealed the spontaneous and exothermic nature of the sorption process. These results indicate that tea seed shells could be utilized as a renewable resource to develop activated carbon which is a potential adsorbent for methylene blue.
DropoutNet: Addressing Cold Start in Recommender Systems

Latent models have become the default choice for recommender systems due to their performance and scalability. However, research in this area has primarily focused on modeling user-item interactions, and few latent models have been developed for cold start. Deep learning has recently achieved remarkable success showing excellent results for diverse input types. Inspired by these results we propose a neural network based latent model called DropoutNet to address the cold start problem in recommender systems. Unlike existing approaches that incorporate additional content-based objective terms, we instead focus on the optimization and show that neural network models can be explicitly trained for cold start through dropout. Our model can be applied on top of any existing latent model effectively providing cold start capabilities, and full power of deep architectures. Empirically we demonstrate state-of-the-art accuracy on publicly available benchmarks. Code is available at https://github.com/layer6ai-labs/DropoutNet.
Countergradient heat flux observations during the evening transition period

Abstract. Gradient-based turbulence models generally assume that the buoyancy flux ceases to introduce heat into the surface layer of the atmospheric boundary layer in temporal consonance with the gradient of the local virtual potential temperature. Here, we hypothesize that during the evening transition a delay exists between the instant when the buoyancy flux goes to zero and the time when the local gradient of the virtual potential temperature indicates a sign change. This phenomenon is studied using a range of data collected over several intensive observational periods (IOPs) during the Boundary Layer Late Afternoon and Sunset Turbulence field campaign conducted in Lannemezan, France. The focus is mainly on the lower part of the surface layer using a tower instrumented with high-speed temperature and velocity sensors. The results from this work confirm and quantify a flux-gradient delay. Specifically, the observed values of the delay are ~ 30–80 min. The existence of the delay and its duration can be explained by considering the convective timescale and the competition of forces associated with the classical Rayleigh–Benard problem. This combined theory predicts that the last eddy formed while the sensible heat flux changes sign during the evening transition should produce a delay. It appears that this last eddy is decelerated through the action of turbulent momentum and thermal diffusivities, and that the delay is related to the convective turnover timescale. Observations indicate that as horizontal shear becomes more important, the delay time apparently increases to values greater than the convective turnover timescale.
The distribution function of dark matter in massive haloes

We study the distribution function (DF) of dark matter particles in haloes of mass range 10 14 -10 15 M ⊙ . In the numerical part of this work we measure the DF for a sample of relaxed haloes formed in the simulation of a standard A cold dark matter (ACDM) model. The DF is expressed as a function of energy E and the absolute value of the angular momentum L, a form suitable for comparison with theoretical models. By proper scaling we obtain the results that do not depend on the virial mass of the haloes. We demonstrate that the DF can be separated into energy and angular momentum components and propose a phenomenological model of the DF in the form f E (E)[1 + L2/(2L 2 0 )] -β ∞ +β 0L -2β 0. This formulation involves three parameters describing the anisotropy profile in terms of its asymptotic values (β 0 and β ∞ ) and the scale of transition between them (L 0 ). The energy part f E (E) is obtained via inversion of the integral for spatial density. We provide a straightforward numerical scheme for this procedure as well as a simple analytical approximation for a typical halo formed in the simulation. The DF model is extensively compared with the simulations: using the model parameters obtained from fitting the anisotropy profile, we recover the DF from the simulation as well as the profiles of the dispersion and kurtosis of radial and tangential velocities. Finally, we show that our DF model reproduces the power-law behaviour of phase-space density Q = ρ(r)σ 3 (r).
Implementation and control of the Velvet Fingers: A dexterous gripper with active surfaces

Since the introduction of the first prototypes of robotic end-effectors showing manipulation capabilities, much research focused on the design and control of robot hand and grippers. While many studies focus on enhancing the sensing capabilities and motion agility, a less explored topic is the engineering of the surfaces that enable the hand to contact the object. In this paper we present the prototype of the Velvet Fingers smart gripper, a novel concept of end-effector combining the simple mechanics and control of under-actuated devices together with high manipulation possibilities, usually offered only by dexterous robotic hands. This enhancement is obtained thanks to active surfaces, i.e. engineered contact surfaces able to emulate different levels of friction and to apply tangential thrusts to the contacted object. Through the paper particular attention is dedicated to the mechanical implementation, sense drive and control electronics of the device; some analysis on the control algorithms are reported. Finally, the capabilities of the prototype are showed through preliminary grasps and manipulation experiments.
In vitro culture of the eye and the retina of the mouse and rat.

Strange ways & Fell (1926) and Dorris (1938) showed that embryonic chick eyes could be cultivated successfully in vitro on plasma clots, and Harrison (1951) and Reinbold (1954) obtained satisfactory results with an agar-tyrode medium containing embryo extract. The retina in these eyes was undifferentiated and, though little or no increase in the size of the eyes occurred, the authors agreed that cytological differentiation proceeded at a more or less normal rate. Tansley (1933) reported the successful cultivation on plasma clots of whole eyes from rat embryos of 14–17 days and of isolated retina from rats up to 5 days old. Cytological differentiation proceeded at a normal rate, at least for the first few days in culture, but excessive growth of mesodermal elements tended to occur after 12 to 14 days. Rosette formation was a prominent feature in these cultures.
Value, Market Preferences and Trade of Beche-De-Mer from Pacific Island Sea Cucumbers

Market preferences of natural resources contribute to shape their exploitation and production. Beche-de-mer, the product after gutting, cooking, salting and drying sea cucumbers, is exported worldwide to Asian dried seafood markets. A better understanding of the trade, value and market preferences of Pacific island beche-de-mer could identify critical postharvest processing techniques and management strategies for fisheries and aquaculture. Data were collected on export prices and trade of beche-de-mer from Kiribati, Fiji, Tonga and New Caledonia, and the selling prices, respective sizes and organoleptic properties of the products in stores in China. Export prices varied considerably within and among the four countries and low-value species were the most exported by volume. Most of the beche-de-mer from the four Pacific islands is exported to Hong Kong, where quality products are sold and others are distributed to mainland China. Prices of the beche-de-mer in Chinese stores varied up to ten-fold and were mostly influenced by species, body size and, to a lesser extent, physical damage to the products. Market prices across species (averaging US$15–385 kg−1) appear to have mostly increased six- to twelve-fold over the past decade. The data allude that fisheries for Holothuria scabra, H. lessoni, H. fuscogilva, H. whitmaei and Thelenota ananas should be most carefully managed because they were the highest-value species and under greatest demand. The relationships between size of beche-de-mer and sale price were species specific and highly varied. This study also highlights the need for better regulations and/or enforcement of minimum size limits in sea cucumber fisheries, which can help to maximise economic benefits of wild stocks.
Effect of exercise-induced dehydration on time-trial exercise performance: a meta-analysis

Objective To use the meta-analytical procedures to determine the magnitude of the effect of exercise-induced dehydration (EID) upon time-trial (TT) exercise performance. Methods Studies were located via database searches and cross-referencing. TT performance outcomes were converted to mean percentage changes in power output. Random-effects model meta-regressions, analogue to the ANOVA and weighted mean effect summaries were used to delineate the effect of the EID-associated body weight (BW) loss on TT performance. Results Five research articles, all using cycling TTs, were included, producing 13 effect estimates and representing 39 subjects. The mean ambient temperature, relative humidity, exercise intensity and duration of the exercise trials were 26.0±6.7°C, 61±9%, 68±14% of VO2max and 86±34 min, respectively. The effect of EID (mean BW loss of 2.20±1.0%) during self-paced exercise conditions was to produce a non-significant increase in endurance performance of 0.06±2.72% (p=0.94), compared with the maintenance of euhydration (mean BW loss of 0.44±0.48%). Meta-regression analyses revealed a statistically significant relationship between the percentage changes in power output and exercise intensity and duration, but not with the EID-associated percentage changes in BW loss. Drinking according to the dictate of thirst was associated with an increase in TT performance compared with a rate of drinking below (+5.2±4.6%, p=0.01) or above (+2.4±5.0%, p=0.40) thirst. The probability that drinking to thirst confers a real and meaningful advantage on TT performances conducted under field conditions compared with a rate of drinking below and above thirst sensation is of the order of 98% and 62%, respectively. Conclusions (1) Compared with euhydration, EID (up to 4% BW loss) does not alter cycling performances during out-of-door exercise conditions; (2) exercise intensity and duration have a much greater impact on cycling TT performances than EID and; (3) relying on thirst sensation to gauge the need for fluid replacement maximises cycling TT performances.
The topological structure of asynchronous computability

We give necessary and sufficient combinatorial conditions characterizing the tasks that can be solved by asynchronous processes, of which all but one can fail, that communicate by reading and writing a shared memory. We introduce a new formalism for tasks, based on notions from classical algebraic and combinatorial topology, in which a task''s possible input and output values are each associated with high-dimensional geometric structures called simplicial complexes. We characterize computability in terms of the topological properties of these complexes. This characterization has a surprising geometric interpretation: a task is solvable if and only if the complex representing the task''s allowable inputs can be mapped to the complex representing the task''s allowable outputs by a function satisfying certain simple regularity properties. Our formalism thus replaces the ``operational'''' notion of a wait-free decision task, expressed in terms of interleaved computations unfolding in time, by a static ``combinatorial'''' description expressed in terms of relations among topological spaces, allowing us to exploit powerful theorems from the classic literature on algebraic and combinatorial topology. This approach yields the first impossibility results for several long-standing open problems in distributed computing, such as the ``renaming'''' problem of Attiya et al., and the ``$k$-set agreement'''' problem of Chaudhuri.
The Red Queen revisited: reevaluating the age selectivity of Phanerozoic marine genus extinctions

Abstract Extinction risk is inversely related to genus age (time since first appearance) in most intervals of the Phanerozoic marine fossil record, in apparent contradiction to the macroevolutionary Red Queen's Hypothesis, which posits that extinction risk is independent of taxon age. Age-dependent increases in the mean species richness and geographic range of genera have been invoked to reconcile this genus-level observation with the presumed prevalence of Red Queen dynamics at the species level. Here we test these explanations with data from the Paleobiology Database. Multiple logistic regression demonstrates that the association of extinction risk with genus age is not adequately explained by species richness or geographic range: there is a residual association between age and extinction risk even when range and richness effects are accounted for. Throughout most of the Phanerozoic the age selectivity gradient is highest among the youngest age cohorts, whereas there is no association between age and extinction risk among older age cohorts. Some of the apparent age selectivity of extinction in the global fauna is attributable to differences in extinction rate among taxonomic groups, but extinction risk declines with genus age even within most taxonomic orders. Notable exceptions to this pattern include the Cambrian–Ordovician, latest Permian, Triassic, and Paleocene intervals. The association of age with extinction risk could reflect sampling heterogeneity or taxonomic practice more than biological reality, but at present it is difficult to evaluate or correct for such biases. Alternatively, the pattern may reflect consistent extinction selectivity on some as-yet unidentified covariate of genus age. Although this latter explanation is not compatible with a Red Queen model if most genus extinctions have resulted from biological interactions, it may be applicable if most genus extinctions have instead been caused by recurrent physical disturbances that repeatedly impose similar selective pressures.
Daily Mood Assessment Based on Mobile Phone Sensing

With the increasing stress and unhealthy lifestyles in people's daily life, mental health problems are becoming a global concern. In particular, mood related mental health problems, such as mood disorders, depressions, and elation, are seriously impacting people's quality of life. However, due to the complexity and unstableness of personal mood, assessing and analyzing daily mood is both difficult and inconvenient, which is a major challenge in mental health care. In this paper, we propose a novel framework called Mood Miner for assessing and analyzing mood in daily life. Mood Miner uses mobile phone data - mobile phone sensor data and communication data (including acceleration, light, ambient sound, location, call log, etc.) - to extract human behavior pattern and assess daily mood. Our approach overcomes the problem of subjectivity and inconsistency of traditional mood assessment methods, and achieves a fairly good accuracy (around 50%) with minimal user intervention. We have built a system with clients on Android platform and an assessment model based on factor graph. We have also carried out experiments to evaluate our design in effectiveness and efficiency.
Empirical Studies on the Speed of Convergence of Neural Network Training Using Genetic Algorithms

This paper reports several experimental results on the speed of convergence of neural network training using genetic algorithms and back propagation. Recent excitement regarding genetic search lead some researchers to apply it to training neural networks. There are reports on both successful and faulty results, and, unfortunately, no systematic evaluation has been made. This paper reports results of systematic experiments designed to judge whether use of genetic algorithms provides any gain in neural network training over existing methods. Experimental results indicate that genetic search is, at best, equally efficient to faster variants of back propagation in very small scale networks, but far less efficient in larger networks.