Miracle-dz/UniFAR-FTUs huggingface dataset:
Chromosomal inversion polymorphism in Drosophila mediopunctata: seasonal, altitudinal, and latitudinal variation

The most polymorphic chromosome for inversions in Drosophila mediopunctata is the chromosome II, where 17 inversions have been found, eight of which occurring in the distal region and nine in the proximal region. We present an analysis of the chromosome II inversion polymorphism with respect to seasonal, altitudinal and latitudinal variation. In D. mediopunctata from the Parque Nacional do Itatiaia (southeastern Brazil), the frequencies of three of the distal inversions (namely DA, DS, and DP) vary seasonally. These inversions also show altitudinal clines in their frequencies. This microgeographic pattern was not observed on a macrogeographic scale. D. mediopunctata from Porto Alegre are less polymorphic for inversions than other populations, the most remarkable reduction occurring in the proximal region of chromosome II. There is a considerable difference between D. mediopunctata from Campinas and specimens from Serra do Japi, which are separated by only 50 km. In contrast, D. mediopunctata from Serra do Japi are much more similar to specimens from the Parque Nacional do Itatiaia, which is 200 km far.
The evolution of vacancy-type defects in silicon-on-insulator structures studied by positron annihilation spectroscopy

Variable-energy positron annihilation spectroscopy (VEPAS) has been applied to the study of the formation and evolution of vacancy-type defect structures in silicon (Si) and the 1.5 μm thick Si top layer of silicon-on-insulator (SOI) samples. The samples were implanted with 2 MeV Si ions at fluences between 1013 and 1015 cm−2, and probed in the as-implanted state and after annealing for 30 min at temperatures between 350 and 800 °C. In the case of SOI the ions were implanted such that their profile was predominantly in the insulating buried oxide layer, and thus their ability to combine with vacancies in the top Si layer, and that of other interstitials beyond the buried oxide, was effectively negated. No measurable differences in the positron response to the evolution of small clusters of n vacancies (Vn, n ∼ 3) in the top Si layer of the Si and SOI samples were observed after annealing up to 500 °C; at higher temperatures, however, this response persisted in the SOI samples as that in Si decreased towar.
Ice particle habit and surface roughness derived from PARASOL polarization measurements

Abstract. Ice clouds are an important element in the radiative balance of the earth's climate system, but their microphysical and optical properties still are not well constrained, especially ice particle habit and the degree of particle surface roughness. In situ observations have revealed common ice particle habits and evidence for surface roughness, but these observations are limited. An alternative is to infer the ice particle shape and surface roughness from satellite observations of polarized reflectivity since they are sensitive to both particle shape and degree of surface roughness. In this study an adding–doubling radiative transfer code is used to simulate polarized reflectivity for nine different ice habits and one habit mixture, along with 17 distinct levels of the surface roughness. A lookup table (LUT) is constructed from the simulation results and used to infer shape and surface roughness from PARASOL satellite polarized reflectivity data over the ocean. Globally, the retrievals yield a compact aggregate of columns as the most commonly retrieved ice habit. Analysis of PARASOL data from the tropics results in slightly more aggregates than in midlatitude or polar regions. Some level of surface roughness is inferred in nearly 70% of PARASOL data, with mean and median roughness near σ = 0.2 and 0.15, respectively. Tropical region analyses have 20% more pixels retrieved with particle surface roughness than in midlatitude or polar regions. The global asymmetry parameter inferred at a wavelength of 0.865 μm has a mean value of 0.77 and a median value of 0.75.
Lift enhancement by means of small-amplitude airfoil oscillations at low Reynolds numbers

Force and particle image velocimetry measurements were conducted on a NACA 0012 airfoil undergoing small-amplitude sinusoidal plunge oscillations at a poststall angle of attack and Reynolds number of 10,000. With increasing frequency of oscillation, lift increases and drag decreases due to the leading-edge vortices shed and convected over the suction surface of the airfoil. Within this regime, the lift coefficient increases approximately linearly with the normalized plunge velocity. Local maxima occur in the lift coefficient due to the resonance with the most unstable wake frequency, its subharmonic and first harmonic, producing the most efficient conditions for high-lift generation. At higher frequencies, a second mode of flowfield occurs. The leading-edge vortex remains nearer the leading edge of the airfoil and loses its coherency through impingement with the upward-moving airfoil. To capture this impingement process, high-fidelity computational simulations were performed that showed the highly transitional nature of the flow and a strong interaction between the upper and lower-surface vortices. A sudden loss of lift may also occur at high frequencies for larger amplitudes in this mode.
Study of Optimum Condition for Rapid Preparation of Thrombin using Russell’s Viper Venom Factor X Activator

The purpose of this study is to investigate a simple method with the optimum condition for rapid thrombin preparation from Cryoprecipitate-depleted Plasma (CDP) using RVV-X in the process. Thrombin preparation from human CDP was studied with the presence of different factors in batch condition including: 1) RVV-X; 2) volume of calcium chloride solution; 3) volume of sodium chloride solution for final extraction; and 4) incubation time. The properties of the prepared sample were analyzed for fibrin clot formation, total protein by Kjeldahl method, thrombin time, molecular weight and protein patterns by SDS-PAGE, and thrombin concentration by coagulation analyzer. The method and process of preparing thrombin and the study of optimum condition for rapidly preparing the highest yield of thrombin from starting CDP 100 ml were introduced. The best four conditions were concluded: 1) RVV-X 50 mcg should be present in the process; 2) volume of 0.25 M calcium chloride should be 3 ml; 3) volume of 0.85% sodium chloride for the final protein precipitate extraction should be 10 ml and; 4) no incubation time needed for prothrombin activation process. A solution prepared from the optimum condition showed an obvious band on SDS-PAGE at a molecular weight about 36,000 Da which is our target protein thrombin. The prepared solution had a total protein content of 0.065 g/dl and gave satisfactory results of thrombin time (9 seconds) and fibrin clot formation. The test results of thrombin concentration between the method with and without incubation time were 269.4 and 295.2 IU/ml, respectively. This result showed that the method with RVV-X but without incubation time for prothrombin activation (optimum condition) gave the highest yield of thrombin.
Variations of oxygen-18 in West Siberian precipitation during the last 50 years

Abstract. Global warming is associated with large increases in surface air temperature in Siberia. Here, we apply the isotope-enabled atmospheric general circulation model ECHAM5-wiso to explore the potential of water isotope measurements at a recently opened monitoring station in Kourovka (57.04° N, 59.55° E) in order to successfully trace climate change in western Siberia. Our model is constrained to atmospheric reanalysis fields for the period 1957–2013 to facilitate the comparison with observations of δD in total column water vapour from the GOSAT satellite, and with precipitation δ18O measurements from 15 Russian stations of the Global Network of Isotopes in Precipitation. The model captures the observed Russian climate within reasonable error margins, and displays the observed isotopic gradients associated with increasing continentality and decreasing meridional temperatures. The model also reproduces the observed seasonal cycle of δ18O, which parallels the seasonal cycle of temperature and ranges from −25 ‰ in winter to −5 ‰ in summer. Investigating West Siberian climate and precipitation δ18O variability during the last 50 years, we find long-term increasing trends in temperature and δ18O, while precipitation trends are uncertain. During the last 50 years, winter temperatures have increased by 1.7 °C. The simulated long-term increase of precipitation δ18O is at the detection limit (
Multivariable Iterative Learning Control Design Procedures: From Decentralized to Centralized, Illustrated on an Industrial Printer

Iterative learning control (ILC) enables high control performance through learning from the measured data, using only limited model knowledge in the form of a nominal parametric model to guarantee convergence. The aim of this brief is to develop a range of approaches for multivariable ILC, where specific attention is given to addressing interaction. The proposed methods either address the interaction in the nominal model or as uncertainty, i.e., through robust stability. The result is a range of techniques, including the use of the structured singular value (SSV) and Gershgorin bounds, which provide a different tradeoff between modeling requirements, i.e., modeling effort and cost and achievable performance. This allows an appropriate choice in view of modeling budget and performance requirements. The tradeoff is demonstrated in a case study on an industrial printer.
The Association between Obesity and Cancer

The prevalence of overweight and obesity has ascended from 15% in 1980 to 35% in 2005 and it will continue to increase in the future. Almost 22% of the whole cancer cases resulted from obesity and overweight according to the research done by Wolin et al. From multiple adequate evidences, it has been recorded about that obesity importantly causes a lot of types of cancer such as adenocarcinoma of esophagus, colorectal cancer, endometrial cancer (the lining of the uterus), post-menopausal breast cancer and renal cell cancer. Furthermore, obesity can lead to elevate other cancer risk the kind of gallbladder cancer, pancreatic cancer, hepatocellular cancer (subtype of liver cancer), thyroid cancer, cervical cancer (adenocarcinoma of the cervix), Non-Hodgkin Lymphoma (NHL), leukemia, multiple myeloma and malignant melanoma (a type of skin cancer). The attributable risks are 46% for endometrial cancer, 41% for gallbladder cancer between females, 40% for adenocarcinoma of esophagus between males, 37% for adenocarcinoma of esophagus between females, 27% for kidney cancer between females, 22% for kidney cancer between males, 22% for colon cancer between males, and 16% for breast cancer respectively in the 2008 metaanalysis. In addition, current investigations asserted that the attributable risks for all cancers are approximately 5% between males and 6% between females by associating with obesity and overweight in the UK. However, the mechanisms between cancer risk and obesity are uncertain and can be different according to the cancer types and also associated with the fat distribution in organism. Therefore, between some cancer types, waist hip ratio and waist circumference have been found to be more relevant than BMI because abdominal obesity can be diagnosed better with waist hip ratio and waist circumference. Generally, increased plasma insulin levels, elevated IGF-1 synthesis, reduced IGFBP-1 synthesis, and low plasma SHBG levels can be shown for mechanism of many of cancer types. In addition, adipokines can also be added in these mechanisms.
Deep Drone Racing: Learning Agile Flight in Dynamic Environments

Autonomous agile flight brings up fundamental challenges in robotics, such as coping with unreliable state estimation, reacting optimally to dynamically changing environments, and coupling perception and action in real time under severe resource constraints. In this paper, we consider these challenges in the context of autonomous, vision-based drone racing in dynamic environments. Our approach combines a convolutional neural network (CNN) with a state-of-the-art path-planning and control system. The CNN directly maps raw images into a robust representation in the form of a waypoint and desired speed. This information is then used by the planner to generate a short, minimum-jerk trajectory segment and corresponding motor commands to reach the desired goal. We demonstrate our method in autonomous agile flight scenarios, in which a vision-based quadrotor traverses drone-racing tracks with possibly moving gates. Our method does not require any explicit map of the environment and runs fully onboard. We extensively test the precision and robustness of the approach in simulation and in the physical world. We also evaluate our method against state-of-the-art navigation approaches and professional human drone pilots.
The Utilitarian View

Under the Hindu and Mahometan religions, the interests of the rest of the animal creation seem to have met with some attention. Why have they not, universally, with as much as those of human creatures, allowance made for the difference in point of sensibility? Because the laws that are have been the work of mutual fear; a sentiment which the less rational animals have not had the same means as man has of turning to account. Why ought they not? No reason can be given. If the being eaten were all, there is very good reason why we should be suffered to eat such of them as we like to eat: we are the better for it, and they are never the worse. They have none of those long-protracted anticipations of future misery which we have. The death they suffer in our hands commonly is, and always may be, a speedier, and by that means a less painful one, than that which would await them in the inevitable course of nature. If the being killed were all, there is very good reason why we should be suffered to kill such as molest us: we should be the worse for their living, and they are never the worse for being dead. But is there any reason why we should be suffered to torment them? Not any that I can see. Are there any why we should not be suffered to torment them? Yes, several. The day has been, I grieve to say in many places it is not yet past, in which the greater part of the species, under the denomination of slaves, have been treated by the law exactly upon the same footing as, in England for example, the inferior races of animals are still. The day may come, when the rest of the animal creation may acquire those rights which never could have been withholden from them but by the hand of tyranny. The French have already discovered that the blackness of the skin is no reason why a human being should be abandoned without redress to the caprice of a tormentor. It may come one day to be recognized, that the number of the legs, the villosity of the skin, or the termination of the os sacrum, are reasons equally insufficient for abandoning a sensitive being to the same fate. What else is it that should trace the insuperable line? Is it the faculty of reason, or, perhaps, the faculty of discourse? But a full-grown horse or dog is beyond comparison a more rational, as well as a more conversable animal, than an infant of a day, or a week, or even a month, old. But suppose the case were otherwise, what would it avail? the question is not, Can they reason? nor, Can they talk? but, Can they suffer?
Can C-band synthetic aperture radar be used to estimate soil organic carbon storage in tundra?

Abstract. A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR; ENVISAT Advanced SAR Global Monitoring mode) data. SOC values are directly determined from backscatter values instead of upscaling using land cover or soil classes. The multi-mode capability of SAR allows application across scales. It can be shown that measurements in C band under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. It is estimated that at least 29 Pg C is stored in the upper 30 cm of soils north of the tree line. This is approximately 25 % less than stocks derived from the soil-map-based Northern Circumpolar Soil Carbon Database (NCSCD). The total stored carbon is underestimated since the established empirical relationship is not valid for peatlands or strongly cryoturbated soils. The approach does, however, provide the first spatially consistent account of soil organic carbon across the Arctic. Furthermore, it could be shown that values obtained from 1 km resolution SAR correspond to accounts based on a high spatial resolution (2 m) land cover map over a study area of about 7 × 7 km in NE Siberia. The approach can be also potentially transferred to medium-resolution C-band SAR data such as ENVISAT ASAR Wide Swath with ∼ 120 m resolution but it is in general limited to regions without woody vegetation. Global Monitoring-mode-derived SOC increases with unfrozen period length. This indicates the importance of this parameter for modelling of the spatial distribution of soil organic carbon storage.
emission flux in rice soils under chronic nutrients constraints of phosphorus and potassiumLinking the soils lacking phosphorus & potassium for rice plant to the behaviors of methanogens and methanotrophs and methane emission

Nutrient status in soil is crucial for the growth and development of plants which indirectly/directly affect the ecophysiological functions of and resident soil microorganisms. Soil 50 methanogens and methanotrophs can be affected by soil nutrient availabilities and plant growth, which in turn modulate methane (CH4) emissions. Nutrient deficient has been shown to constrain plant growth,
Cognitive and Affective Perspective-Taking: Evidence for Shared and Dissociable Anatomical Substrates

Perspective-taking refers to the ability to recognize another person's point of view. Crucial to the development of interpersonal relationships and prosocial behavior, perspective-taking is closely linked to human empathy, and like empathy, perspective-taking is commonly subdivided into cognitive and affective components. While the two components of empathy have been frequently compared, the differences between cognitive and affective perspective-taking have been under-investigated in the cognitive neuroscience literature to date. Here, we define cognitive perspective-taking as the ability to infer an agent's thoughts or beliefs, and affective perspective-taking as the ability to infer an agent's feelings or emotions. In this paper, we review data from functional imaging studies in healthy adults as well as behavioral and structural imaging studies in patients with behavioral variant frontotemporal dementia in order to determine if there are distinct neural correlates for cognitive and affective perspective-taking. Data suggest that there are both shared and non-shared cognitive and anatomic substrates. For example, while both types of perspective-taking engage regions such as the temporoparietal junction, precuneus, and temporal poles, only affective perspective-taking engages regions within the limbic system and basal ganglia. Differences are also observed in prefrontal cortex: while affective perspective-taking engages ventromedial prefrontal cortex, cognitive perspective-taking engages dorsomedial prefrontal cortex and dorsolateral prefrontal cortex (DLPFC). To corroborate these findings, we also examine if cognitive and affective perspective-taking share the same relationship with executive functions. While it is clear that affective perspective-taking requires emotional substrates that are less prominent in cognitive perspective-taking, it remains unknown to what extent executive functions (including working memory, mental set switching, and inhibitory control) may contribute to each process. Overall results indicate that cognitive perspective-taking is dependent on executive functioning (particularly mental set switching), while affective perspective-taking is less so. We conclude with a critique of the current literature, with a focus on the different outcome measures used across studies and misconceptions due to imprecise terminology, as well as recommendations for future research.
Subgradient-Free Stochastic Optimization Algorithm for Non-smooth Convex Functions over Time-Varying Networks

In this paper we consider a distributed stochastic optimization problem without the gradient/subgradient information for the local objective functions, subject to local convex constraints. The objective functions may be non-smooth and observed with stochastic noises, and the network for the distributed design is time-varying. By adding the stochastic dithers into the local objective functions and constructing the randomized differences motivated by the Kiefer-Wolfowitz algorithm, we propose a distributed subgradient-free algorithm to find the global minimizer with local observations. Moreover, we prove that the consensus of estimates and global minimization can be achieved with probability one over the time-varying network, and then obtain the convergence rate of the mean average of estimates as well. Finally, we give a numerical example to illustrate the effectiveness of the proposed algorithm.
A Variational Prosody Model for the decomposition and synthesis of speech prosody

The quest for comprehensive generative models of intonation that link linguistic and paralinguistic functions to prosodic forms has been a longstanding challenge of speech communication research. More traditional intonation models have given way to the overwhelming performance of artificial intelligence (AI) techniques for training model-free, end-to-end mappings using millions of tunable parameters. The shift towards machine learning models has nonetheless posed the reverse problem – a compelling need to discover knowledge, to explain, visualise and interpret. Our work bridges between a comprehensive generative model of intonation and state-of-the-art AI techniques. We build upon the modelling paradigm of the Superposition of Functional Contours model and propose a Variational Prosody Model (VPM) that uses a network of deep variational contour generators to capture the context-sensitive variation of the constituent elementary prosodic cliches. We show that the VPM can give insight into the intrinsic variability of these prosodic prototypes through learning a meaningful prosodic latent space representation structure. We also show that the VPM brings improved modelling performance especially when such variability is prominent. In a speech synthesis scenario we believe the model can be used to generate a dynamic and natural prosody contour largely devoid of averaging effects.