Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-range time correlations in plasma edge turbulence

Analysis of the edge plasma fluctuation in several confinement devices reveals the self-similar character of the fluctuations through the presence of long-range time correlations. These results show that the tail of the autocorrelation function decays as a power law for time lags longer than the decorrelation time and as long as times on the order of the particle diffusion time. The algebraic decay of the longrange time correlations is consistent with plasma transport characterized by self-organized criticality. [S0031-9007(98)06077-3]
Decolorization of Acidic Dye by Charcoal from Coffee Grounds

From the viewpoints of decreasing environmental burdens and recycling of materials, the adsorption ability of charcoal from coffee grounds for acidic dye (acid orange 7) removal was investigated by the batch method. Differences in the removal ratio and removal rate of acid orange 7 could be explained by differences in the properties of charcoal such as specific surface area and pore volume. In the relationship between the amount of acid orange 7 adsorbed at each elapsed time and the square root of elapsed time, a good linearity was recognized. Since the good linearity between the acid orange 7 adsorption and the square root of elapsed time was recognized, the intraparticle diffusion of acid orange 7 onto pores of adsorbents was identified as the rate-limiting step in the adsorption process.
A Phenomenon Discovered While Imaging Dolphin Echolocation Sounds

Our overall goal is to analyze dolphin sounds to determine if dolphins utilize language or perhaps pictorial information in their complex whistles and clicks. We have recently discovered a novel phenomenon in images derived from digital recordings of the sounds of dolphins echolocating on submerged objects. Hydrophone recordings of dolphin echolocation sounds were input to a CymaScope, an analog instrument in which a water-filled, fusedquartz cell is acoustically excited in the vertical axis by a voice coil motor directly coupled to the cell. The resulting wave patterns were recorded with a digital video camera. We observed the formation of transient wave patterns in some of the digital video frames that clearly matched the shapes of the objects on which the dolphin echolocated, including a closed cell foam cube, a PVC cross, a plastic flowerpot, and a human subject. As further confirmation of this phenomenon the images were then converted into 3-dimensional computer models. The computer models were made such that the thickness at any given point was proportional to the brightness of a contrast-enhanced image with brighter areas thicker and darker areas thinner. These 3-dimensional virtual models were then printed in photopolymers utilizing a high definition 3D printer.
Final author response to anonymous referee #1

General comments: Comment 1 I. “The authors describe two WRF experiments to demonstrate the effects of northward shifts of boreal vegetation due to anticipated climate change. The experiments include the structural changes in high latitude ecosystems, which result in changes in soil moisture properties and heat fluxes. ” II. We greatly appreciate the referee taking time to read and comment our manuscript. We have revised the manuscript in accordance with the referee’s constructive comments and suggestions.
Stability and synchronization of delayed fractional-order projection neural network with piecewise constant argument of mixed type

Abstract Projection equations arise in several optimization problems and possess significant applications in many areas of science and engineering. In this paper, we propose a fractional-order projection neural network to solve quadratic programming problems. We study stability and synchronization for a class of delayed projection neural networks of mixed type via impulsive control. Using concepts of fractional calculus, we investigate the existence of solution and study its global asymptotic stability. Moreover, we propose an effective impulsive control scheme to achieve synchronization for the system. We demonstrate the validity and transient behaviour of the proposed neural network with the help of suitable examples.
SigSpec User's Manual

{\sc SigSpec} computes the spectral significance levels for the DFT amplitude spectrum of a time series at arbitrarily given sampling. It is based on the analytical solution for the Probability Density Function (PDF) of an amplitude level, including dependencies on frequency and phase and referring to white noise. Using a time series dataset as input, an iterative procedure including step-by-step prewhitening of the most significant signal components and MultiSine least-squares fitting is provided to determine a whole set of signal components, which makes the program a powerful tool for multi-frequency analysis. Instead of the step-by-step prewhitening of the most significant peaks, the program is also able to take into account several steps of the prewhitening sequence simultaneously and check for the combination associated to a minimum residual scatter. This option is designed to overcome the aliasing problem caused by periodic time gaps in the dataset. {\sc SigSpec} can detect non-sinusoidal periodicities in a dataset by simultaneously taking into account a fundamental frequency plus a set of harmonics. Time-resolved spectral significance analysis using a set of intervals of the time series is supported to investigate the development of eigenfrequencies over the observation time. Furthermore, an extension is available to perform the {\sc SigSpec} analysis for multiple time series input files at once. In this MultiFile mode, time series may be tagged as target and comparison data. Based on this selection, {\sc SigSpec} is capable of determining differential significance spectra for the target datasets with respect to coincidences in the comparison spectra. A built-in simulator to generate and superpose a variety of sinusoids and trends as well as different types of noise completes the software package at the present stage of development.
Productivity and the Performance of Agriculture in Latin America and the Caribbean: From the Lost Decade to the Commodity Boom

This study analyzes the performance of Latin America and the Caribbean's agriculture between 1980 and 2012 looking at the contribution of inputs, and total factor productivity (TFP) to growth in output per worker. A growth accounting approach that goes along the lines of neoclassical growth accounting combined with Data Envelopment Analysis, allows us to measure TFP growth using output and input indices and also to decompose this growth into contributions of technical change and changes in technical efficiency. Our findings show that between 1980 and 2012, regional agricultural output per worker and TFP increased 82 and 45 percent, respectively, reducing the difference between TFP in LAC and in OECD countries. This improved performance of agriculture was the result of fast growth in the use of fertilizer, increases in land productivity, and growth in the use of capital that expanded cultivated area per worker. Higher productivity of the animal stock, fast growth in the use of feed and in the number of animals per worker, have increased the share of livestock in total output and also contributed significantly to the improved performance of agriculture. Observed growth patterns at the country level suggest that countries that increased input per worker have increased TFP at a higher rate than countries with limited access to capital and land. As a result of these growth patterns, the improved performance in the region has amplified differences in labor productivity between countries. Growing differences in labor productivity and the fact that the favorable shock in commodity prices that benefited LAC's agriculture in recent years has apparently ran its course, raise concerns for the future.
Braun-Scharm, Hellmuth Psychogene Sehstörungen bei Kindern und Jugendlichen Praxis der Kinderpsychologie und Kinderpsychiatrie 37 (1988) 2, S. 38-43 urn:nbn:de:bsz-psydok-32570

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Competitive Biological Activities of Chitosan and Its Derivatives: Antimicrobial, Antioxidant, Anticancer, and Anti-Inflammatory Activities

Chitosan is obtained from alkaline deacetylation of chitin, and acetamide groups are transformed into primary amino groups during the deacetylation. The diverse biological activities of chitosan and its derivatives are extensively studied that allows to widening the application fields in various sectors especially in biomedical science. The biological properties of chitosan are strongly depending on the solubility in water and other solvents. Deacetylation degree (DDA) and molecular weight (MW) are the most decisive parameters on the bioactivities since the primary amino groups are the key functional groups of chitosan where permits to interact with other molecules. Higher DDA and lower MW of chitosan and chitosan derivatives demonstrated higher antimicrobial, antioxidant, and anticancer capacities. Therefore, the chitosan oligosaccharides (COS) with a low polymerization degree are receiving a great attention in medical and pharmaceutical applications as they have higher water solubility and lower viscosity than chitosan. In this review articles, the antimicrobial, antioxidant, anticancer, anti-inflammatory activities of chitosan and its derivatives are highlighted. The influences of physicochemical parameters of chitosan like DDA and MW on bioactivities are also described.
Amazon vegetation greenness as measured by satellite sensors over the last decade

During the last decade two major drought events, one in 2005 and another in 2010, occurred in the Amazon basin. Several studies have claimed the ability to detect the effect of these droughts on Amazon vegetation response, measured through satellite sensor vegetation indices (VIs). Such monitoring capability is important as it potentially links climate changes (increasing frequency and severity of drought), vegetation response as observed through vegetation greenness, and land‐atmosphere carbon fluxes which directly feedback into global climate change. However, we show conclusively that it is not possible to detect the response of vegetation to drought from space using VIs. We analysed 11 years of dry season (July–September) Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) and normalised difference vegetation index (NDVI) images. The VI standardised anomaly was analysed alongside the absolute value of EVI and NDVI, and the VI values for drought years were compared with those for non‐drought years. Through a series of analyses, the standardised anomalies and VI values for drought years were shown to be of similar magnitude to those for non‐drought years. Thus, while Amazon vegetation may respond to drought, this is not detectable through satellite‐observed changes in vegetation greenness. A significant long‐term decadal decline in VI values is reported, which is independent of the occurrence of drought. This trend may be caused by environmental or noise‐related factors which require further investigation.
3 DOF Upper Limb Rehabilitation Robot-Assisted Training System

Hemiplegia is the most common performance of stroke. In order to assist the recovery of upper limb hemiplegia patients, the author developed a 3-DOF upper limb rehabilitation robot system based on the technology of Virtual Reality. The system can help patients to complete the shoulder movements of abduction/adduction, flexion/ extension and the elbow movement of flexion/extension. The paper expounded the structure of the robot and conducted the kinematics analysis of the robot mechanism. A computer and a digital signal processor (DSP) constitute the control center of the system. Absolute encoders collect the information of robot motion and magnetic powder brakes complete the braking and loading processes. We have exploited Windows GDI and OpenGL to construct a virtual reality environment on the platform of Visual C++. Experiments show that the system can achieve both linear and compound motions easily, and reach the requirements of design. The introduction of the technology of Robot and Virtual Reality into the field of rehabilitation has provided a scientific and effective recovery mode for patients. Keywords-hemiplegia; rehabilitation; robot; VR; DSP;
Identification, verification and validation of process models in wastewater engineering: a critical review

This article presents a critical review of the existing methodologies for process mathematical modelling in the area of wastewater engineering. It is argued that model identifiability is not a major issue in mathematical modelling. Model verifiability is a very demanding criterion that can be replaced by a less stringent one: model observability. The issue of ‘complex models versus reduced-order models’ is to be resolved by introducing a new concept: optimal model complexity. The traditional procedures of model validation are not adequate and a mathematical framework for model quality evaluation is needed.
Embryo Morphokinetics Based on Time-Lapse Observation

Embryo incubation and evaluation are critical steps in assisted reproductive technology (ART). Conventionally, embryo assessment has been done by embryologists through removing embryos from a conventional incubator during the culture period. Over recent years, time-lapse systems (TLS) have been established which can take digital images of embryos at key points and time intervals. This technique allows embryologists to assess the embryo quality in the steady culture environment. According to TLS studies and prepared algorithm models, it seems that TLS alone or in combination with conventional morphology can be considered as a useful diagnostic tool to determine high-quality embryos and improve embryonic implantation and pregnancy rates. In addition, there were remarkable differences between embryo developmental time points and intervals regarding embryo gender, embryo fragmentation, and type of ovarian stimulation protocol. For confident conclusion, time-lapse imaging should be evaluated in further stud - ies, and the system should be evaluated for cost/benefit ratio effectiveness in individual laboratory.
Driving Performance Variability Among Elite Golfers

In recent years studies have been carried out on single subjects, for example by Kinugasa et al., 2004. It has been reported that it is unlikely any two golfers will have an identical swing, and even that an individual golfer is unlikely to produce two identical swings. The present study aimed to address performance variability among elite level golfers to ascertain whether single-subject (SS) analysis is merited for golf studies. Six elite golfers (0.1 ± 2.2 handicap, 22.1 ± 2.3 yrs) performed eight trials each using three randomly assigned drivers specifically constructed with matched physical properties for the current study. Testing was carried out on a purpose-built outdoor practice hole. A stereoscopic high-speed camera was used to record club head and ball launch conditions prior to and immediately after impact. Two laser range finders were positioned approximately 250 yards (229 m) from the tee providing measures of carry and accuracy. There existed significant differences in overall performance between subjects. Club head velocity, spin axis tilt, launch angle and dispersion all exhibited inter-subject differences (p<0.05). In addition, club head velocity exhibited significant intra-subject variability (p<0.01) among all subjects. However, whilst statistically significant variations in carry and dispersion were observed for shots performed with matched drivers, absolute variation was actually very small (<0.5 %). Results suggest that golf research merits SS analysis although intra-subject variability was also noted among even elite level golfers.
A Comparative Study of Failure Data for Software Reliability Estimation

Software reliability is one of the attributes of quality and its measurement is supported by Software Reliability Growth Models. Among many of the proposed SRGMs, some of the models have been widely used and few of them obsolete. The successful SRGMs are characterized by the accuracy of reliability estimation. In such models, the reliability estimation depends on the quality of failure data and its accuracy increases as the length of failure observation increases. In this paper, we have studied the role of failure data set in the reliability estimation by employing three different data sets on unified SRGM that has no distinction between failure observation and fault removal process. The selected SRGM is incorporated with two distribution functions one is exponential and another one is 2-staged erlang distribution. For easy implementation, we assume that the debugging process is perfect. That is the probability of error correction is one and no errors have been introduced during the debugging process. Three different cases of failure data are considered for our study such as database application software, web server, the interface of an operating system. The unknown parameters of each case are estimated by using SMERFS tool and the goodness-of-fit analysis is done in MATLAB environment.
Dynamic Chain Graph Models for Ordinal Time Series Data

This paper introduces sparse dynamic chain graph models for network inference in high dimensional non-Gaussian time series data. The proposed method parametrized by a precision matrix that encodes the intra time-slice conditional independence among variables at a fixed time point, and an autoregressive coefficient that contains dynamic conditional independences interactions among time series components across consecutive time steps. The proposed model is a Gaussian copula vector autoregressive model, which is used to model sparse interactions in a high-dimensional setting. Estimation is achieved via a penalized EM algorithm. In this paper, we use an efficient coordinate descent algorithm to optimize the penalized log-likelihood with the smoothly clipped absolute deviation penalty. We demonstrate our approach on simulated and genomic datasets. The method is implemented in an R package tsnetwork.
BSIM4 and BSIM Multi-Gate Progress

New technologies and alternate transistor structures are being developed to extend the CMOS scaling. Device models need to be developed and improved in parallel with the technology advancements to enable an efficient and quick adoption of the new technologies. Some of the recent advances in BSIM4 and BSIM Multi-gate models towards meeting this goal are presented in this paper. Improvements to the BSIM4 model include holistic stress-induced mobility enhancement model and a high-k dynamic behavior model. Preliminary results of the modeling of multi-gate architectures are also presented.
Influence of 660 and 830 Nm Laser Irradiation on Genetic Profile of Extracellular Matrix Proteins in Diabetic Wounded Human Skin Fibroblast Cells

The extracellular matrix (ECM) provides tissue structural integrity and its synthesis plays a crucial role in wound healing. Impaired wound healing ensues following the destruction of the ECM, or the inhibition of its synthesis. An imbalance in ECM synthesis and degradation is seen in patients with diabetes. This has led to the development of novel therapies that aim to decrease ECM destruction and increase its synthesis. Photobiomodulation (PBM) has been shown to speed up the healing of these slow-to-heal wounds, and numerous studies are being conducted to determine the underlying molecular cause. This study aimed to ascertain the effect of laser irradiation at a wavelength of 660 or 830 nm at a dose of 5 J/cm 2 on the genetic expression profile of genes involved in ECM proteins. cDNA was reverse transcribed from total isolated RNA and used in real-time qualitative polymerase chain reaction (qPCR). Genes concerned with the basement membrane, collagen and ECM structural constituents, and ECM protesases and inhibitors were evaluated. Results showed that a similar genetic profile (although not identical) was seen post irradiation. PBM was able to reduce the expression of ECM proteases and increase mRNA levels of ECM proteins. This study fortifies the notion that PBM stimulates cellular activity and can influence ECM matrix synthesis and degradation during wound healing. This study has also shown that PBM is able to stimulate cells at a genetic level.
Reduction in morphological plasticity in echinoid larvae: relationship of plasticity with maternal investment and food availability

Hypotheses: If phenotypic plasticity is costly or not beneficial to marine invertebrate larvae, then increased maternal investment into eggs should result in decreased plastic responses. If genetic assimilation is a mechanism for the evolutionary transition from planktotrophic to lecithotrophic larvae, then species with larger eggs will have reduced overall plasticity and growth trajectories similar to highly fed larvae from a species that exhibits plasticity. Organisms: Larvae reared from three subtropical echinoid species, Mellita tenuis, Clypeaster subdepressus, and Leodia sexiesperforata, collected from the Gulf coast of Florida that differ in degree of maternal investment into eggs. Methods: We reared larvae from each species at three food concentrations in laboratory cultures. We measured two larval structures (post-oral arm length and stomach size) on three occasions (1, 3, and 5 days after fertilization) and statistically compared these characters to determine: (1) within-species plastic responses to food environment and (2) between-species plastic responses to identical feeding treatments. Results: Larvae of M. tenuis and C. subdepressus, the two species with smaller eggs, both expressed plasticity of larval arms (elongated arms under low food conditions) and stomachs (smaller stomachs under low food conditions) early in development, whereas L. sexiesperforata larvae only showed significant changes in stomach size on the last day of measurement in the highest food treatment. Comparisons among species showed that larvae developing from smaller eggs had a significantly higher plastic response to exogenous food than larvae developing from large eggs.
Persistence in the Indian Stock Market Returns: An Application of Variance Ratio Test

This paper by Madhusoodanan applies the variance ratio tests under the null hypotheses of homoscedasticity as well as heteroscedasticity, to the Indian stock market. The tests are conducted at the aggregate level of market indices and disaggregate level of individual stocks. The results indicate that random walk hypothesis cannot be accepted in the Indian market. Both the market indices the author tested showed persistent behaviour, while most of the individual stocks also showed evidence on persistence. The variance ratios were significant under heteroscedasticity in most of the cases where it was significant under homoscedasticity assumption. This implies that heteroscedasticity does not play a major role in the Indian market.