Miracle-dz/UniFAR-FTUs huggingface dataset:
A METHOD FOR SCALING VEGETATION DYNAMICS: THE ECOSYSTEM DEMOGRAPHY MODEL (ED)

The problem of scale has been a critical impediment to incorporating important fine-scale processes into global ecosystem models. Our knowledge of fine-scale physiological and ecological processes comes from a variety of measurements, ranging from forest plot inventories to remote sensing, made at spatial resolutions considerably smaller than the large scale at which global ecosystem models are defined. In this paper, we describe a new individual-based, terrestrial biosphere model, which we label the ecosystem demography model (ED). We then introduce a general method for scaling stochastic individual-based models of ecosystem dynamics (gap models) such as ED to large scales. The method accounts for the fine-scale spatial heterogeneity within an ecosystem caused by stochastic disturbance events, operating at scales down to individual canopy-tree-sized gaps. By conditioning appropriately on the occurrence of these events, we derive a sizeand age-structured (SAS) approximation for the first moment of the stochastic ecosystem model. With this approximation, it is possible to make predictions about the large scales of interest from a description of the fine-scale physiological and population-dynamic processes without simulating the fate of every plant individually. We use the SAS approximation to implement our individual-based biosphere model over South America from 158 N to 158 S, showing that the SAS equations are accurate across a range of environmental conditions and resulting ecosystem types. We then compare the predictions of the biosphere model to regional data and to intensive data at specific sites. Analysis of the model at these sites illustrates the importance of fine-scale heterogeneity in governing large-scale ecosystem function, showing how population and community-level processes influence ecosystem composition and structure, patterns of aboveground carbon accumulation, and net ecosystem production.
biocontrol strategy of diaphania pulverulentalis targeting jheh gene through molecular cloning and insilico analysis

In insects, metamorphosis is controlled by interaction of endocrine agents mainly by Juvenile hormone and ecdysone. Juvenile Hormone Epoxide Hydrolase (JHEH), one of the major enzymes is involved in degradation of Juvenile hormone pathway and could be applied to control insects due to its irreversible reaction. The present work is focused on cloning of partial gene sequence and Insilico analysis of JHEH gene in Diaphania pulverulentalis (Dp) that is a serious insect pest on mulberry. A cDNA (800bps) encoding the partial JHEH was cloned from the mulberry leaf webber, Diaphania pulverulentalis. Partial DpJHEH sequence contains an open reading frame encoding 244 amino acids with high degree of similarity to the reported insect JHEHs at NCBI. This is the kind of its first study on molecular cloning and sequence information of JHEH in Diaphania pulverulentalis.
Music Retrieval: A Tutorial and Review

The increasing availability of music in digital format needs to be matched by the development of tools for music accessing, filtering, classification, and retrieval. The research area of Music Information Retrieval (MIR) covers many of these aspects. The aim of this paper is to present an overview of this vast and new field. A number of issues, which are peculiar to the music language, are described--including forms, formats, and dimensions of music--together with the typologies of users and their information needs. To fulfil these needs a number of approaches are discussed, from direct search to information filtering and clustering of music documents. An overview of the techniques for music processing, which are commonly exploited in many approaches, is also presented. Evaluation and comparisons of the approaches on a common benchmark are other important issues. To this end, a description of the initial efforts and evaluation campaigns for MIR is provided.
Mechanical property measurement of nano-scale metal films on the novel paddle cantilever beams using four step phase-shifting method

A test structure with nano-scale metal films, which is deposited on the novel paddle-like cantilever beam, was successfully fabricated and calibrated using standard C-MOS processes. Compared to the traditional cantilevered beam, the 40 mum thickness paddle-like structure provides the uniform stress distribution along the whole beam to decrease the measurement variation. The deflections of argentums, gold, and copper films (50-250 nm) driven by the electrostatic force were measured using four step phase-shifting method. The results present that the test structure and the optical (FSPS) method work properly. Furthermore, argentums presents that the deflection decreases after deposition to demonstrate that the tensile residual stress in the film. Oppositely, gold and copper films show compressive residual stress in them.
Exploring Biological Samples in 3 D Beyond Classic Electron Tomography

Imaging techniques of tridimensional reconstructions provide details of the interior of reconstructed objects otherwise inaccessible. Such methods allow the quantification of volumes and might give access to the information of the different elements constituting the object. They are used in many fields such as archeology, geophysics, material sciences, quality control and biology. In medicine, these methods represented by X-ray tomography [1], single photon emission computed tomography [2], magnetic resonance imaging [3] or positron emission tomography [4] are regularly used for exploration and diagnosis. In cell biology, volume reconstruction methods provide a more accurate vision of the relationships between cellular structures and organelles leading to a better understanding of life processes [5]. Thus, methods to obtain 3D information of objects are nowadays indispensable for large aspects of modern science. 3D reconstruction methods are usually based on the stacking of images obtained from sections of the studied object or on the combination of data from its projections. The electron microscopy techniques available nowadays which use the first approach are destructive to the specimen, since they are based on the progressive slicing by knives or by sample erosion by an ion beam. The second approach, used for electron tomography, is based on the analysis of the projections of a thick specimen (from 100 to 1000 nanometers), which is preserved and could be used for successive and complementary analyses. This is one reason that makes approaches based on reconstruction techniques from projections largely favored. These methods require image formation by the use of any kind of penetrating wave generated by a tomograph which also records the projected images [6]. To study samples at nanometric scale, the transmission electron microscope (TEM) is presently the most used tomograph although other alternatives are slowly being applied to life sciences, such as those based on synchrotron radiation [7]. Volume reconstructions methods based on the combination of TEM images acquired from a single specimen tilted at different angles are called transmission electron tomography (TET) [8]. The automation of image acquisition using TEMs started a quarter of century ago and was perfected more recently with the use of fast computers and sensitive and larger digital cameras sensors. This enabled TET as a routine in a reasonable number of well-equipped electron microscopy laboratories. In biology, TET has recently been combined with cryo-fixation methods [9,10] consisting in the freezing of samples at speed, pressure and temperature conditions to reach a quality of ice Exploring Biological Samples in 3D Beyond Classic Electron Tomography
Neuron Efficiency in Fluid Dynamics and Prediction of Groundwater Reservoirs'' Properties Using Pattern Recognition

Abstract—The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p1), fractured layer (p2), and the depth (h), while the dependent variable is the flow parameter (F= ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable gr (gravitational resistance) can be deduced from the elevation and apparent resistivity pa. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.
Speech-Evoked Brainstem Response

The auditory brainstem response (ABR) is a clinical tool to assess the neural functionality of the auditory brainstem. The use of verbal stimuli in ABR protocols has provided important information of how the speech stimuli are processed by the brainstem structure. The perception of speech sounds seems to begin in the brainstem, which has an important role in the reading process and the phonological acquisition speech ABR assessment allows the identification of fine-grained auditory processing deficits, which do not appear in click evoked ABR responses. The syllable /da/ is commonly used by speech ABR assessment due to it being considered a universal syllable and allows it to be applied in different countries with good clinical assertiveness. The speech ABR is a objective, fast procedure that can be applied to very young subjects. It be utilized in different languages and can provide differential diagnoses of diseases with similar symptoms, as an effective biomarker of auditory processing disorders present in various diseases, such as dyslexia, specific language impairment, hearing loss, auditory processing disorders, otitis media, and scholastic difficulties. Speech ABR protocols can assist in the detection, treatment, and monitoring of various types of hearing impairments.
PODRŠKA INTERESNIH SKUPINA RAZVOJU TURIZMA STAKEHOLDER SUPPORT FOR TOURISM DEVELOPMENT

SAŽETAK: Od ranih 1980-ih nositelji planiranja razvoja turizma zalagali su se za uključivanje interesnih skupina u planiranje iz najmanje tri razloga: prvo, interesne skupine koje podržavaju turistički razvoj sklonije su podržati investicije javnog sektora i projekte privatnog sektora; drugo, sklonije su tolerirati neke negativne učinke i, treće, više su gostoljubive prema turistima. Posljednji aspekt je važan s obzirom na to da istraživanja pokazuju da gostoljubivost i prijateljsko ponašanje lokalnog stanovništva pridonosi ukupnom zadovoljstvu turista. Tako stručnjaci koji se bave planiranjem turizma ističu potrebu praćenja stavova lokalnih interesnih skupina s ciljem ranog identifi ciranja mogućih problema i poduzimanja strategija kojima će se minimizirati eventualne konfl iktne situacije koje, ukoliko ostaju neotkrivene, potkopavaju potporu za razvoj destinacije i destinacijsku privlačnost za posjetitelje. Stoga je u okviru ovog istraživanja osmišljeno i provedeno kvalitativno i kvantitativno istraživanje kako bi se utvrdili stavovi zajednice o turizmu i njegovom budućem razvoju. Istraživanjem su obuhvaćene interesne skupine iz javnog sektora i turističkog sektora te stanovnici. Rezultati istraživanja otklonili su neke od ‘iluzija’ povezanih s ne(željenim) turističkim razvojem. Jednako važno, rad je unaprijedio istraživanja i metode u turističkom planiranju budući da postoji mali broj radova koji uzimaju u obzir stavove različitih interesnih skupina temeljene na reprezentativnim uzorcima.
A Review of Climate Signals as Predictors of Long-Term Hydro- Climatic Variability

In many parts of the world coupled oceans atmospheric phenomenon provide important predictive information about hydrologic variability. Therefore, studying the relationships of these large scale features of the atmosphere with hydroclimatic events is helpful in hydrolog‐ ical and meteorological long-lead forecasting, promoting awareness about climate variability, and water resources management. As the time scale over which the oceans respond are slower than atmosphere, efforts have been focused mostly on investigating the links of sea surface temperatures (SSTs) and sea level pressures (SLPs) of oceans with atmospheric changes for climate monitoring or use as potential hydro-climatic predictors.
Estimation of reliability in a multicomponent stress- strength model based on generalized linear failure rate distribution

In this paper, we consider the problem of estimation reliability in multicomponent stress-strength model, when the system consists of $k$-components have strength are given by independently and identically distributed random variables $X_{1},. ,X_{k}$ each component experiencing a random stress governed by a random variable $Y$. The reliability such system is obtained when strength and stress variables are given by a generalized linear failure rate distribution. The system is regarded as alive only if at least $s$ out of $k$ $(s<k)$ strength exceed the stress. The multicomponent reliability of the system is given by $R_{s,k}=P[$ at least $s$ of $X_{1},. ,X_{k}$ exceed $Y]$. The maximum likelihood estimator $(MLE)$ and Bayes estimator of $R_{s,k}$ are obtained. A simulation study is performed to compare the different estimators of $R_{s,k}$. Real data is used as a practical application of the proposed procedure.
Isoenzymatic characterization of Colletotrichum kahawae isolates with different levels of aggressiveness

The hemibiotrophic fungus Colletotrichum kahawae is the causal agent of Coffee Berry Disease - CBD, an economically devastating disease restricted to Arabica coffee production in Africa. Understanding pathogen variability is crucial for the implementation of disease control measures. In this study, six isoenzymatic systems (esterase, acid and alkaline phosphatase, malate dehydrogenase, peroxidase and superoxide dismutase) were used to assess the genetic variation among 12 C. kahawae isolates (from different geographic origins and with different levels of aggressiveness towards coffee) and one Colletotrichum gloeosporioides isolate (not pathogenic to green berries). Cluster analysis of the banding profiles obtained for the six enzymes enabled the differentiation of the two species and revealed the existence of intraspecific variability among C. kahawae isolates. Alkaline phosphatase was the most discriminative enzyme, allowing also the discrimination between the most and least aggressive isolates of C. kahawae.
Purification, characterization and structural determination of UDP-N-acetylglucosamine pyrophosphorylase produced by Moniliophthora perniciosa

The enzyme UDP-N-acetylglucosamine pyrophosphorylase (PyroMp) from Moniliophthora perniciosa (CCMB 0257), a pathogenic fungal strain and the causative agent of the witches' broom disease in Theobroma cacao, was partially purified by precipitation with ammonium sulfate and gel filtration on Sephacryl S-200. The buffer for enzyme extraction was sodium phosphate, 0.050 mol L-1, pH 7.0, containing 1.0 mol L-1 NaCl. Response surface methodology (RSM) was used to determine the optimum pH and temperature conditions. Four different isoenzymes (PyroMp I, PyroMp II, PyroMp III and PyroMp IV) were obtained with optimal pH ranging from 6.9-8.4 and optimum temperature ranging from 28 to 68 °C. The 3D structure of pyrophosphorylase of M. perniciosa was determined by comparative modeling. The model obtained showed a good quality, possessing 78.6% of amino acids in energetically allowed regions. The model was then submitted for DM simulation and showed a good geometric quality (91.1% Ramachandran plot). The active site of the enzyme was found to be extremely well conserved. This model will be useful for developing new inhibitors against witches' broom disease.
A Hierarchical Framework for Mitosis Detection in Time-Lapse Phase Contrast Microscopy Image Sequences of Stem Cell Populations

Measurement of the proliferative behaviors of cells in vitro is important to many biomedical applications ranging from basic biological research to advanced applications, such as drug discovery, stem cell manufacturing, and tissue engineering. Critical to such measurement is accurate identification and localization of mitosis, which is the process whereby a eukaryotic cell separates the chromosomes in its cell nucleus into two identical sets in two daughter nuclei. In the early years, it is possible to manually identify incidents of mitosis because mitotic cells in culture tend to retract, round up, and exhibit intensified surrounding halos under phase contrast illumination (Fig.1) for short-period, small-scale studies. Recently, many cell proliferation assays have been developed for high throughput cell imaging and analysis. Especially, phase contrast microscopy is a superior imaging modality because it enables continuous monitoring of live cells without requiring destructive methods of cell manipulation, such as cell lysis and staining. Consequently, the need for extended-time observation and the proliferation of high-throughput imaging have made automated image analysis mandatory.
Through-the-Lens Drone Filming

Aerial filming in action scenes using a drone is difficult for inexperienced flyers because manipulating a remote controller and meeting the desired image composition are two independent, while concurrent, tasks. Existing systems attempt to utilize wearable GPS-based or infrared-based sensors to track the human movement and to assist in capturing footage. However, these sensors work only in either indoor (infrared-based) or outdoor environments (GPS-based), but not both. In this paper, we introduce a novel drone filming system which integrates monocular 3D human pose estimation and localization into a drone platform to remove the constraints imposed by wearable-sensor-based solutions. Meanwhile, given the estimated position, we propose a novel drone control system, called “through-the-lens drone filming”, to allow a cameraman to conveniently control the drone by manipulating a 3D model in the preview, which closes the gap between the flight control and the viewpoint design. Our system includes two key enabling techniques: 1) subject localization based on visual-inertial fusion, and 2) through-the-lens camera planning. This is the first drone camera system which allows users to capture human actions by manipulating the camera in a virtual environment. From the drone hardware, we integrate a gimbal camera and two GPUs into the limited space of a drone and demonstrate the feasibility of running the entire system onboard with insignificant delays, which are sufficient for filming in our real-time application. Experimental results, in both simulation and real-world scenarios, demonstrate that our techniques can greatly ease camera control and capture better videos.
Study of Local Turbulence Profiles Relative to the Particle Surface in Particle-Laden Turbulent Flows

As particle-resolved simulations (PRSs) of turbulent flows laden with finite-size solid particles become feasible, methods are needed to analyze the simulated flows in order to convert the simulation data to a form useful for model development. In this paper, the focus is on turbulence statistics at the moving fluid‐solid interfaces. An averaged governing equation is developed to quantify the radial transport of turbulent kinetic energy when viewed in a frame moving with a solid particle. Using an interface-resolved flow field solved by the lattice Boltzmann method (LBM), we computed each term in the transport equation for a forced, particle-laden, homogeneous isotropic turbulence. The results illustrate the distributions and relative importance of volumetric source and sink terms, as well as pressure work, viscous stress work, and turbulence transport. In a decaying particle-laden flow, the dissipation rate and kinetic energy profiles are found to be self-siimilar. [DOI: 10.1115/1.4031692]
Noise-induced transitions in optomechanical synchronization

We study how quantum and thermal noise affects synchronization of two optomechanical limit-cycle oscillators. Classically, in the absence of noise, optomechanical systems tend to synchronize either in-phase or anti-phase. Taking into account the fundamental quantum noise, we find a regime where fluctuations drive transitions between these classical synchronization states. We investigate how this ‘mixed’ synchronization regime emerges from the noiseless system by studying the classical-to-quantum crossover and we show how the time scales of the transitions vary with the effective noise strength. In addition, we compare the effects of thermal noise to the effects of quantum noise.
Biodegradability of dissolved organic carbon in permafrost soils and aquatic systems : A meta-analysis

Abstract. As Arctic regions warm and frozen soils thaw, the large organic carbon pool stored in permafrost becomes increasingly vulnerable to decomposition or transport. The transfer of newly mobilized carbon to the atmosphere and its potential influence upon climate change will largely depend on the degradability of carbon delivered to aquatic ecosystems. Dissolved organic carbon (DOC) is a key regulator of aquatic metabolism, yet knowledge of the mechanistic controls on DOC biodegradability is currently poor due to a scarcity of long-term data sets, limited spatial coverage of available data, and methodological diversity. Here, we performed parallel biodegradable DOC (BDOC) experiments at six Arctic sites (16 experiments) using a standardized incubation protocol to examine the effect of methodological differences commonly used in the literature. We also synthesized results from 14 aquatic and soil leachate BDOC studies from across the circum-arctic permafrost region to examine pan-arctic trends in BDOC. An increasing extent of permafrost across the landscape resulted in higher DOC losses in both soil and aquatic systems. We hypothesize that the unique composition of (yedoma) permafrost-derived DOC combined with limited prior microbial processing due to low soil temperature and relatively short flow path lengths and transport times, contributed to a higher overall terrestrial and freshwater DOC loss. Additionally, we found that the fraction of BDOC decreased moving down the fluvial network in continuous permafrost regions, i.e. from streams to large rivers, suggesting that highly biodegradable DOC is lost in headwater streams. We also observed a seasonal (January–December) decrease in BDOC in large streams and rivers, but saw no apparent change in smaller streams or soil leachates. We attribute this seasonal change to a combination of factors including shifts in carbon source, changing DOC residence time related to increasing thaw-depth, increasing water temperatures later in the summer, as well as decreasing hydrologic connectivity between soils and surface water as the thaw season progresses. Our results suggest that future climate warming-induced shifts of continuous permafrost into discontinuous permafrost regions could affect the degradation potential of thaw-released DOC, the amount of BDOC, as well as its variability throughout the Arctic summer. We lastly recommend a standardized BDOC protocol to facilitate the comparison of future work and improve our knowledge of processing and transport of DOC in a changing Arctic.