Miracle-dz/UniFAR-FTUs huggingface dataset:
Seasonal Observation on Some Population Attributes of Aedes albopictus Females in Nagasaki, Japan, with Emphasis on the Relation between the Body Size and the Survival.

Humanbait collections of Aedes albopictus females were made 27 times from May to August, 1990 in Nagasaki, Japan. Seasonal variation was observed in the density, the body size as measured by the wing length and the parous rate of host-seeking females. Early in the observation period, generally the density was lower, the body size was larger and the parous rate was lower. However, when compared in each time period, clear positive correlation was recognized between the body size and the parous rate. It was also found that females with retained mature eggs or with heavily damaged wings had, on average, larger body size, suggesting the longer survival in larger females.
The ALMA Spectroscopic Survey in the HUDF: Constraining Cumulative CO Emission at 1 ≲ z ≲ 4 with Power Spectrum Analysis of ASPECS LP Data from 84 to 115 GHz

We present a power spectrum analysis of the ALMA Spectroscopic Survey Large Program (ASPECS LP) data from 84 to 115 GHz. These data predominantly probe small-scale fluctuations (k = 10–100 h Mpc−1) in the aggregate CO emission in galaxies at 1≲ z ≲ 4. We place an integral constraint on CO luminosity functions (LFs) in this redshift range via a direct measurement of their second moments in the three-dimensional (3D) autopower spectrum, finding a total CO shot-noise power μK2 (Mpc h−1)3. This upper limit (3σ) is consistent with the observed ASPECS CO LFs in Decarli et al. but rules out a large space in the range of inferred from these LFs, which we attribute primarily to large uncertainties in the normalization Φ* and knee L* of the Schechter-form CO LFs at z > 2. Also, through power spectrum analyses of ASPECS LP data with 415 positions from galaxies with available optical spectroscopic redshifts, we find that contributions to the observed mean CO intensity and shot-noise power of MUSE galaxies are largely accounted for by ASPECS blind detections. Finally, we sum the fluxes from individual blind CO detections to yield a lower limit on the mean CO surface brightness at 99 GHz of μK, which we estimate represents 68%–80% of the total CO surface brightness at this frequency.
Influence of the Grain Direction on the Low-temperature Pyrolysis of Large Wood Particles

Pyrolysis is the thermal decomposition of a solid fuel in an inert atmosphere. Biomass pyrolysis products are non-condensable gases, char, and tars. The amounts and compositions of the products depend on several operating parameters i.e. temperature, pressure, heating rate as well as the biomass properties. For large particles, the pyrolysis rate is affected by chemical kinetics, mass transfer and heat transfer. Owing to the anisotropy of the woody material, transport processes depend on the heating and flow direction relative to the wood grain, as well as on temperature, density, and moisture content. The present work investigates the effect of grain orientation on the wood pyrolysis. For this purpose, dried white pine wood cylinders of 1.9 cm diameter and 4 cm length were pyrolyzed using a flow of nitrogen heated to a temperature between 374 and 464 0C. The cylinders have two different grain orientations: parallel and perpendicular to the cylinder axis. The pyrolysis was performed in a turbulent nitrogen flow at atmospheric pressure for 30 min. Temperature profiles at three locations within the particle were measured using a sheathed K-type thermocouples with sheath diameter of 0.5 mm. The temporal evolution of several volatiles released during sample pyrolysis was measured using Fourier Transform Infrared (FTIR) and Non Dispersive Infrared (NDIR) analyzers. The data are compared in order to deduce the effects of sample grain orientation on the pyrolysis of woody biomass. It was noted that more gas and char were formed from the parallel gain orientation. This is due to the higher residence times of tars, such that there is a higher probability for their reacting to form secondary char and lighter gases prior to escaping from the particles.
Effect of nitrogen form, type of polyethylene film covering the tunnel and stage of fruit development on calcium content in sweet pepper fruits.

In this study we hypothesized that the effect of nitrogen form well as light in- tensity on Ca content in the sweet pepper fruit may depend on stage of fruit maturity. Thus the effect of nitrogen form (100% N-NO3 or 50% N-NO3 + 13% N-NH4 + 37% N-NH2), type of polyethylene film covering the tunnel (two types of film, Ginegar or Gemme 4S, characterized by various PAR transmissions) and stage of fruit maturity on Ca and dry matter content in sweet pepper fruits were determined. Sweet pepper plants were cultivated in rockwool slabs. The chemical analyses were performed on sweet pep- pers harvested in five stages of growth and ripening, beginning with fruits of 2-4 cm di- ameter. Plants supplied with nutrient solution containing nitrate N form accumulated more Ca. The influence of film type covering the tunnel was unsystematic. Irrespective of N form and film type the contents of Ca and dry matter varied depending on fruit growth and ripening stages. Systematic increase in Ca accumulation occurred until reaching the stage of mature-green sweet peppers, while during further ripening the level of Ca de- creased. The dynamics of dry matter accumulation were opposite to that of Ca. Additional determination of Ca was performed in mature green fruits, coming from nitrate N and Gemme 4S film (transmitted more light) treatment, both normal and with visible symp- toms of blossom-end rot (BER). The analysis was conducted separately in the upper and lower part of fruits. Higher amount of Ca was found in the upper part in normal and BER fruits. Since BER was developed in fruits with Ca content in the lower part equaled to 0.60 mg·g -1 d.m. , but in 2007 no symptoms of BER were noted in fruits contained only 0.38 mg·g -1 of Ca, other co-factors, not only low Ca level in fruit, should be considered in
The SAMI Galaxy Survey: The contribution of different kinematic classes to the stellar mass function of nearby galaxies

We use the complete Sydney-AAO Multi-object Integral field spectrograph (SAMI) Galaxy Survey to determine the contribution of slow rotators, as well as different types of fast rotators, to the stellar mass function of galaxies in the local Universe. We use stellar kinematics not only to discriminate between fast and slow rotators, but also to distinguish between dynamically cold systems (i.e., consistent with intrinsic axis ratios<0.3) and systems including a prominent dispersion-supported bulge. We show that fast rotators account for more than $80\%$ of the stellar mass budget of nearby galaxies, confirming that their number density overwhelms that of slow rotators at almost all masses from 109 to 1011.5M⊙. Most importantly, dynamically cold disks contribute to at least $25\%$ of the stellar mass budget of the local Universe, significantly higher than what is estimated from visual morphology alone. For stellar masses up to 1010.5M⊙, this class makes up $>=30\%$ of the galaxy population in each stellar mass bin. The fact that many galaxies that are visually classified as having two-components have stellar spin consistent with dynamically cold disks suggests that the inner component is either rotationally-dominated (e.g., bar, pseudo-bulge) or has little effect on the global stellar kinematics of galaxies.
Water Quality in Micro-watersheds Under Different Land Uses in the Municipality of Alegre, Espírito Santo

The present study aimed to evaluate water quality attributes in micro-watersheds under different soil uses. Therefore, four micro-watersheds under the following vegetation cover were selected: pasture, primary forest reforestation, forest, and coffee plantation. Surface and underground water sampling was performed bimonthly between February and December 2014, where thermotolerant coliforms, dissolved oxygen, total nitrogen, phosphorus, turbidity, temperature, pH, biochemical demand for oxygen and total solids were analyzed. Descriptive analyses of each variable were performed during dry and rainy periods, and the values were compared with the normative standards established by Brazilian legislation. Water Quality Indices (WQIs) were also calculated for each collection site. All sites presented some type of nonconformity with human consumption standards. The highest WQI values were found in the forest area micro-basin, followed by the coffee plantation and pasture area micro-basins, highlighting the importance of forested areas for water quality.
Seasonal variations in metal content of two Unio pictorum mancus (Mollusca, Unionidae) populations from two lakes of different trophic state

To assess the impact of lake trophy on trace element accumulation by Unio pictorum mancus, a population from the mesooligotrophic Lake Maggiore was compared with a population from the eutrophic Lake Candia. The element content in soft tissue and shell biomass, the seasonal variations of element concentrations in soft tissues and shell, and the relationship between element concentrations in the water and those in the tissues were estimated in pursuit of this objective. Thirteen mussel samplings were performed in Lake Maggiore between May 2003 and September 2004 and in Lake Candia between June 2003 and August 2004. Filtered water samples were collected seasonally. Water, shell and soft tissue samples were analysed by ICP-OES and ICP-MS for the measurement of following elements: Zn, Cu, Fe, Mn, Ni, As, Pb, Co, Cr, Mo, V, Cd, Be and Ca. The element concentrations in the mussel tissues and shell from Lake Maggiore were higher than those from Lake Candia. Due to the higher population density and higher element concentrations in the mussels of Lake Maggiore, the element content in the biomass per m2 in this lake far exceeded that in Lake Candia. The element concentrations in the mussel tissues, but not in their shells, of both lakes showed a seasonal pattern of variation; this was to be expected as a result of the slower turnover time of the elements in the shell than in the tissues. For all the elements, except Mo, Cr and Be, the "concentration factor" (C.F.) value was higher in Lake Maggiore than in Lake Candia mussels, ranging from 10 to 104 and 10 to 103 respectively. The higher concentrations in the mussel tissues from Lake Maggiore were justified not merely by the higher element concentrations in the lake water, but probably also because other causes, such as element concentrations in food and element abundance in available forms, combine to affect the concentrations of the elements in the tissues.
Interaction Graphs for Reliability Analysis of Power Grids: A Survey

Reliability analysis of power grids has been the focus of many researchers for years. However, the complex interactions among the large number of components in these systems and their contributions to the reliability of the system are not yet completely understood. Therefore, various techniques have been developed and used to model and analyze the underlying interactions among the components of the power grid with respect to reliability challenges, such as cascading failures. Such methods are important to reveal the essential information that may not be readily available from power system physical models and topologies. Based on these models, the influences and interactions among the components of the system may occur both locally and at distance due to the physics of electricity governing the power flow dynamics as well as other functional and cyber dependencies among the components of the system. These methods use data-driven approaches or techniques based on the physics of power and develop a graph to model the interactions among the components of the power grid. In this survey, we review various methods of developing interaction graphs as well as studies on reliability analysis of power grids using these graphs.
Valuation of Property Assets: An International Research Agenda

Abstract Over the past decade, there has been a significant growth in real estate research throughout the world. While many countries are characterised by differing histories of real estate education and research reflecting variations in political systems, land tenure, culture and economic development, the past ten years have witnessed a dramatic increase both in the volume of research and the opportunities for presentation and publication of findings. To date, there have been few reflective studies of the nature and scope of property research; consequently, we argue that it is useful to map the research terrain by analysing contributions to research conferences. We argue that, as not all contributions have been published, the conference provides a broader overview of the main areas of real estate research activity than would be possible from a similar study of contributions to academic journals. Similarly, the conference provides comprehensive coverage of research undertaken in the valuation specialism which is the specific focus of this paper. This paper presents initial findings from a comparative analysis of valuation papers presented at the RICS Cutting Edge (RICS CE), European Real Estate Society (ERES) and Pacific Rim Real Estate Society (PRRES) conferences over the period 1993 to 2001. The emerging themes and characteristics of a global valuation research agenda are discussed together with the implications for future research.
Poverty and Economic Growth in Swaziland: An Empirical Investigation

This paper examines the causal relationship between poverty reduction and economic growth in Swaziland during the period 1980–2011. Unlike some of the previous studies, the current study uses the newly developed ARDL-bounds testing approach to co-integration, and the ECM-based Granger causality method to examine this linkage. The study also incorporates financial development as a third variable affecting both poverty reduction and economic growth – thereby leading to a trivariate model. The results of this study show that economic growth does not Granger cause poverty reduction in Swaziland – either in the short run or in the long run. Instead, the study finds a causal flow from poverty reduction to economic growth in the short run. These findings, however, are not surprising, given the high level of income inequality in Swaziland. Studies have shown that when the level of income inequality is too high, economic growth alone may not necessarily lead to poverty reduction.
Thermal Efficiency of Quantum Memory Compression

Quantum coherence allows for reduced-memory simulators of classical processes. Using recent results in single-shot quantum thermodynamics, we derive a minimal work cost rate for quantum simulators that is quasistatically attainable in the limit of asymptotically infinite parallel simulation. Comparing this cost with the classical regime reveals that quantizing classical simulators not only results in memory compression but also in reduced dissipation. We explore this advantage across a suite of representative examples.
Progressive Compressed Records: Taking a Byte out of Deep Learning Data

Deep learning accelerators efficiently train over vast and growing amounts of data, placing a newfound burden on commodity networks and storage devices. A common approach to conserve bandwidth involves resizing or compressing data prior to training. We introduce Progressive Compressed Records (PCRs), a data format that uses compression to reduce the overhead of fetching and transporting data, effectively reducing the training time required to achieve a target accuracy. PCRs deviate from previous storage formats by combining progressive compression with an efficient storage layout to view a single dataset at multiple fidelities---all without adding to the total dataset size. We implement PCRs and evaluate them on a range of datasets, training tasks, and hardware architectures. Our work shows that: (i) the amount of compression a dataset can tolerate exceeds 50% of the original encoding for many DL training tasks; (ii) it is possible to automatically and efficiently select appropriate compression levels for a given task; and (iii) PCRs enable tasks to readily access compressed data at runtime--- utilizing as little as half the training bandwidth and thus potentially doubling training speed.
SAMM Long Videos: A Spontaneous Facial Micro- and Macro-Expressions Dataset

With the growth of popularity of facial micro-expressions in recent years, the demand for long videos with micro- and macro-expressions remains high. Extended from SAMM, a micro-expressions dataset released in 2016, this paper presents SAMM Long Videos dataset for spontaneous micro- and macro-expressions recognition and spotting. SAMM Long Videos dataset consists of 147 long videos with 343 macro-expressions and 159 micro-expressions. The dataset is FACS-coded with detailed Action Units (AUs). We compare our dataset with Chinese Academy of Sciences Macro-Expressions and Micro-Expressions (CAS(ME)2) dataset, which is the only available fully annotated dataset with micro- and macro-expressions. Furthermore, we preprocess the long videos using OpenFace, which includes face alignment and detection of facial AUs. We conduct facial expression spotting using this dataset and compare it with the baseline of MEGC III. Our spotting method outperformed the baseline result with F1-score of 0.3299.
Knowledge Dissemination, Capital Accumulation, Trade and Endogenous Growth

This paper preserves many of the primary features of the standard neoclassical framework while introducing some modifications that transform it into an open economy endogenous growth model with knowledge accumulation. The accumulation of knowledge is determined in part by the extent of knowledge spillovers from abroad, which in turn are affected by commercial policy that regulates the extent of trade between countries. The model predicts that trade liberalization (even if it is unilateral) will increase steady-state output growth in all countries while benefitting the liberalizing country the most in terms of relative income levels. Copyright 2000 by Oxford University Press.
Deep Hedging: Learning to Simulate Equity Option Markets

We construct realistic equity option market simulators based on generative adversarial networks (GANs). We consider recurrent and temporal convolutional architectures, and assess the impact of state compression. Option market simulators are highly relevant because they allow us to extend the limited real-world data sets available for the training and evaluation of option trading strategies. We show that network-based generators outperform classical methods on a range of benchmark metrics, and adversarial training achieves the best performance. Our work demonstrates for the first time that GANs can be successfully applied to the task of generating multivariate financial time series.
Ternary MobileNets via Per-Layer Hybrid Filter Banks

MobileNets family of computer vision neural networks have fueled tremendous progress in the design and organization of resource-efficient architectures in recent years. New applications with stringent real-time requirements on highly constrained devices require further compression of MobileNets-like compute-efficient networks. Model quantization is a widely used technique to compress and accelerate neural network inference and prior works have quantized MobileNets to 4 − 6 bits, albeit with a modest to significant drop in accuracy. While quantization to sub-byte values (i.e. precision ≤ 8 bits) has been valuable, even further quantization of MobileNets to binary or ternary values is necessary to realize significant energy savings and possibly runtime speedups on specialized hardware, such as ASICs and FPGAs. Under the key observation that convolutional filters at each layer of a deep neural network may respond differently to ternary quantization, we propose a novel quantization method that generates per-layer hybrid filter banks consisting of full-precision and ternary weight filters for MobileNets. Using this proposed quantization method, we quantize a substantial portion of weight filters of MobileNets to ternary values resulting in a 27.98% savings in energy, and a 51.07% reduction in the model size, while achieving comparable accuracy and no degradation in throughput on specialized hardware in comparison to the baseline full-precision MobileNets. Finally, we demonstrate the generalizability and effectiveness of hybrid filter banks to other neural network architectures.
Few-body bound states of two-dimensional bosons

We study clusters of the type A$_N$B$_M$ with $N\leq M\leq 3$ in a two-dimensional mixture of A and B bosons, with attractive AB and equally repulsive AA and BB interactions. In order to check universal aspects of the problem, we choose two very different models: dipolar bosons in a bilayer geometry and particles interacting via separable Gaussian potentials. We find that all the considered clusters are bound and that their energies are universal functions of the scattering lengths $a_{AB}$ and $a_{AA}=a_{BB}$, for sufficiently large attraction-to-repulsion ratios $a_{AB}/a_{BB}$. When $a_{AB}/a_{BB}$ decreases below $\approx 10$, the dimer-dimer interaction changes from attractive to repulsive and the population-balanced AABB and AAABBB clusters break into AB dimers. Calculating the AAABBB hexamer energy just below this threshold, we find an effective three-dimer repulsion which may have important implications for the many-body problem, particularly for observing liquid and supersolid states of dipolar dimers in the bilayer geometry. The population-imbalanced ABB trimer, ABBB tetramer, and AABBB pentamer remain bound beyond the dimer-dimer threshold. In the dipolar model, they break up at $a_{AB}\approx 2 a_{BB}$ where the atom-dimer interaction switches to repulsion.
Learning a Representation for Cover Song Identification Using Convolutional Neural Network

Cover song identification is a challenging task in the field of Music Information Retrieval (MIR) due to complex musical variations between query tracks and cover versions. Previous works typically utilize hand-crafted features and alignment algorithms for the task. More recently, further breakthroughs are achieved by employing neural network approaches. In this paper, we propose a novel Convolutional Neural Network (CNN) towards cover song identification. We train the network through classification criteria. Having been trained, the network is used to extract music representation for cover song identification. A training scheme is designed to train robust models against tempo changes. Experimental results show that our approach outperforms state-of-the-art methods on several public datasets with low time complexity.