Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Chinook Salmon Smolt Habitat Use in the lower Trinity River

This report summarizes data collections and analyses to assess variation in physical habitat characteristics selected by Chinook Salmon smolts in the Trinity River. Spatially, this study focuses on two mainstem Trinity River reaches located downstream of the confluence of the North Fork Trinity River, each several kilometers in length. This project was initiated to inform the extension of the Trinity River Stream Salmonid Simulator (S3) model from the confluence of the North Fork Trinity River to the confluence with the Klamath River. Several methods for observing and enumerating juvenile Chinook Salmon were explored, with the goal to compliment habitat models developed for Chinook Salmon fry and parr in the upper portion of the Trinity River mainstem. Methods applying various sonar camera technologies were deemed ineffective for the intended needs of the project. To complete the project, direct-observation snorkel counts we chosen as the data collection method. Time spent conducting field sampling methodology trials and elevated flows causing turbid waters too dark for effective sampling caused delays in implementation of the data collection. Eventually, assessments of habitat use were collected at the desired sites, but during a single week in August. The single week of sampling is generally thought to be too short to capture temporal variation in habitat use. Additionally, the August period of collection is rather late in the period of time when juvenile Chinook Salmon inhabit the Trinity River, and too few wild fish may have been present to accurately reflect the habitat selection of larger juveniles. The counts of Chinook Salmon juveniles from the survey reflect very low numbers, with nearly 80% of the counts recorded as zeros. A statistical Arcata Fisheries Data Series Report DS 2018-57 2 analysis of the counts suggests that juveniles in the lower river select habitat locations according to proximity to escape cover or river edge, but not according to the depth or velocity of the water flowing through the habitat area. These results are caveated with notes on the seasonally late and narrow window in which sampling occurred. However, the results are potentially relevant for actively migrating fish that might not be rearing in habitat areas, but rather using the mainstem river as a migration corridor to the Pacific Ocean.
Family Ties and Worker Displacement ∗

Young adults, aged 25 to 35, who live close to their parents experience stronger earnings recoveries after a job displacement than those who live farther away. This result is robust to a variety of controls and a reweighting exercise that account for potential differences between workers by location. The effect of parental proximity diminishes gradually with distance to one’s parents and is driven by post-displacement wages rather than labor supply. We find some evidence that parents’ job networks may help adult children to find local jobs. At older ages, living near one’s parents appears to have no impact. JEL codes: J61, J64, R23.
Mobile Devices as an Infrastructure : A Survey of Opportunistic Sensing Technology

Now that billions of people carry sensor-enabled mobile devices (e.g., smartphones), employing powerful capability of such commercial mobile products has become a promising approach for large-scale environmental and human-behavioral sensing. Such a new paradigm of scalable context monitoring is known as opportunistic sensing, and has been successfully applied to a broad range of applications. In this paper, we briefly introduce basic architecture and building blocks on which these emerging systems are based, and then provide a survey of recent progress in the opportunistic sensing technology.
SWAN-lake: opportunistic distributed sensing for Android smartphones

Today, smart devices like mobile phones and fitness trackers have many sensors. Formatting, combining and querying sensor data from such devices can be a challenging and cumbersome task. In this paper we introduce SWAN-Lake, a distributed mobile framework that provides structured access to sensor data. SWAN-Lake provides access to local sensors as well as access to sensors of nearby devices. Here, we take a distributed approach by using device-to-device communication for exchanging sensor data between smartphones. We evaluate the performance and resource utilization using different sensing scenarios for our SWAN-Lake Android implementation. As a result, we show that our framework is energy efficient and performs well under high load.
Application of GIS and logistic regression to fossil pollen data in modelling present and past spatial distribution of the Col

Citation for published version (APA): Flantua, S. G. A. , van Boxel, J. H. , Hooghiemstra, H. , & van Smaalen, J. (2007). Application of GIS and logistic regression to fossil pollen data in modelling present and past spatial distribution: A case study in the Columbian Savanna. In A. C. Wistanley (Ed.), GISRUK 2007: proceedings of the Geographical Information Science Research UK Conference: National Centre for Geocomputation, National University of Ireland Maynooth, 11th13th April 2007 (pp. 102-107). Maynooth: NUI.
Analysis of Magneto-Mechanical Jiles-Atherton-Sablik Model Regarding its Sensitivity to Non-linear Algorithm Parametrization

Sources of mechanical loadings emerge in nearly every production stages of electromagnetic machines, and can also be found during their utilization. From residual plastic strain to in use stress generation, this non-homogeneity in the mechanical state of soft magnetic materials affects their properties. In that sense, the present paper reviews the capacity of modeling such coupled effect using an unidirectional phenomenological model based on the Jiles-Atherton hysteresis theory: the Jiles-Atherton-Sablik model. The identification of the required parameters is realized through different non-linear algorithms, and the dependence of the model accuracy regarding its own parametrization is analyzed. On this particular point, results show that a careful attention has to be payed while using non-linear optimization, as some unphysical behavior could appear, leading to convergence troubles in the case of a FEM utilization of the models.
Mixing Enhancement of Electroosmotic Flow in Microchannels under DC and AC Electric Field

A novel micromixer is presented in this study and the effect of DC or AC electric field on mixing efficiency is investigated numerically. Four types of AC waveforms are considered to explore the flow characteristic and mixing efficiency. The velocity field, concentration field and the mixing efficiency are analyzed in details. The results demonstrated that a pair of vortices with opposite rotating directions is generated when DC or AC voltages is applied to the electrode plates planted within the walls. The generated vortices greatly enhance the mixing of incoming fluids with different concentrations. The mixing efficiency firstly rises with time and then reaches a relative stable periodic state under different potential waveforms. As the voltage applied on the plates increases, the mixing efficiency is improved obviously. The mixing efficiency under full-wave AC signal is the highest, and it is up to 95.44% when the applied potential is 3 V and frequency is 5 Hz.
Iterative Algorithm For Local Electricity Trading

Distribution networks are more active due to demand response programs which causes flexible behavior of end-users. This paper proposes an iterative algorithm to transact electricity based on interplay between aggregators and the Distribution Company (DisCo) considering the amount which the bottom-layer of a distribution system can provide from the aggregated end-users. The performance of the proposed trading algorithm was tested on a 33-bus test system for a distribution network. Similations for different scenarios were made to analyze the impact of different flexibility constraints on sustainability of the system and expected cost on distribution grid’s player.
Resolving the stratification discrepancy of turbulent natural convection in differentially heated air-filled cavities . Part II : end wall effects

This paper provides an explanation for the discrepancy in the central thermal stratification long observed between experimental and numerical studies of natural convection at high Rayleigh number in air-filled differentially heated cavities. The turbulent natural convection flow (RaH = 1.5 × 10 ) is investigated by means of large eddy simulations, which are first validated in comparison with the spectral simulations data presented in the first part of this paper (Sergent et al., 2010). Three sets of simulations are performed in configurations of increasing consideration of the experimental temperature distributions at the end walls. Results show that the complete set of experimental temperature distribution is needed to recover full agreement between numerical and experimental results. In particular, the thermal boundary conditions on the front and rear walls are found to be the key ingredient to obtain a good agreement. In the third part of this paper it is shown that this temperature distribution results from a complete 3D convection-conduction-radiation coupling at the cavity walls (Xin et al., 2010).
Role of calcium and AMP kinase in the regulation of mitochondrial biogenesis and GLUT 4 levels in muscle

Contractile activity induces mitochondrial biogenesis and increases glucose transport capacity in muscle. There has been much research on the mechanisms responsible for these adaptations. The present paper reviews the evidence, which indicates that the decrease in the levels of highenergy phosphates, leading to activation of AMP kinase (AMPK), and the increase in cytosolic Ca, which activates Ca/calmodulin-dependent protein kinase (CAMK), are signals that initiate these adaptative responses. Although the events downstream of AMPK and CAMK have not been well characterized, these events lead to activation of various transcription factors, including: nuclear respiratory factors (NRF) 1 and 2, which cause increased expression of proteins of the respiratory chain; PPAR-a, which up regulates the levels of enzymes of b oxidation; mitochondrial transcription factor A, which activates expression of the mitochondrial genome; myocyte-enhancing factor 2A, the transcription factor that regulates GLUT4 expression. The well-orchestrated expression of the multitude of proteins involved in these adaptations is mediated by the rapid activation of PPARg co-activator (PGC) 1, a protein that binds to various transcription factors to maximize transcriptional activity. Activating AMPK using 5-aminoimidizole-4-carboxamide-1-b-D-riboside (AICAR) and increasing cytoplasmic Ca using caffeine, W7 or ionomycin in L6 myotubes increases the concentration of mitochondrial enzymes and GLUT4 and enhances the binding of NRF-1 and NRF-2 to DNA. AICAR and Ca-releasing agents also increase the levels of PGC-1, mitochondrial transcription factor A and myocyte-enhancing factors 2A and 2D. These results are similar to the responses seen in muscle during the adaptation to endurance exercise and show that L6 myotubes are a suitable model for studying the mechanisms by which exercise causes the adaptive responses in muscle mitochondria and glucose transport.
Foliar Spray of Some Growth Regulators and Nutrient Elements for Improving Yield and Fruit Quality of Hayany Date Palm

The present investigation was carried out during the seasons of 2012 and 2013 seasons to study the effect of Naphthalen Acetic Acid (NAA), zinc chleate , boric acid and calcium chleate on fruit set, yield and fruit quality of Hayany date palm. Generally , the higher fruit set and fruit retention percentage, and fruit weight, volume, length and diameter were obtained by spraying Hayany date palm with Zn chleate at 0.2% in both experimental seasons. While the highest bunch weight and palm yield were recorded by spraying calcium chleate at 0.4 % ( 20.67 and 23.67 kg/bunch) and (219.10 and 250.90 kg/palm) in the 1 and 2 seasons, respectively , moreover, the highest total soluble solids and total acidity were cleared in fruits by spraying boric acid at 200 ppm (18.0 and 20.0 kg) in the 1 and 2 seasons, respectively and gave the highest reducing sugars and total sugar percent in both seasons. The lowest values of tannins content in fruit were obtained by spraying date palm with boric acid at 200 ppm (0.43 %) in 1 season and calcium chleate at 0.4 % (0.47 % ) in the 2 season. Kew words: Naphthalen acetic acid (NAA), zinc, boric acid , calcium , fruit set, yield , fruit quality , date palm .
Exploratory Text Segmentation through Joint Distribution Estimation

Résumé. We suggest a novel way for exploratory topic segmentation based on data grid models. In this context, a text can be represented as a data set of twodimensional points; each point is defined by two variables: a word (categorical value) and the placement of the word in the text (numerical value). Instantiating data grid models to the 2D-points turns the problem into coclustering. Simultaneously, the words are partitioned into clusters and the placement (or time) variable is discretized into intervals/segments, following a parameter-free Bayesian model selection approach. We also suggest several criteria for exploiting the resulting grid through agglomerative hierarchies, for interpreting the clusters of words and characterizing their components through insightful visualizations. Experiments on the Bible show the relevance of our approach.
Type-Separation as a Method for Eﬃcient Bytecode Veriﬁcation

Java Bytecode is applied on a large variety of diﬀerent architectures. Still, one problem arising is veriﬁcation of class ﬁles. This is especially true for constrained devices like cell phones and embedded systems. For larger programs the veriﬁcation algorithm is costly in either runtime or used memory. In this paper we present the basic principles of type-separated bytecode and show how its properties can be used to achieve a more eﬃcient veriﬁcation algorithm. Diﬀerent techniques which can signiﬁcantly decrease time and memory consumption during the ver-iﬁcation process without creating a substantial overhead in the program ﬁle are illustrated and compared.
Fuzzy System for Diagnosis and Treatment of Kidney Diseases

Medical diagnosis and treatment is very vague and complex decision task. A large number of symptoms contribute in the decision, making it complex. Also the decision factors are fuzzy in nature. A small mistake in the interpretation of the severity of the symptoms may lead to major mistake in the treatment decision resulting into serious complications. Fuzzy logic is a widely used theory to deal with this fuzziness [1]. This paper does focus on the design of fuzzy expert system for the diagnosis and treatment of kidney diseases. The paper is composed of four sections. Section I gives overview of kidney disease and some of the software’s available for its diagnosis. We describe the design of the developed fuzzy system FSDTKD in Section II. Section III does discuss the applications and advantages of the developed system. The paper concludes in Section IV with summarization and further directions to extend the work.
Prediction of Personalized Rating by Combining Bandwagon Effect and Social Group Opinion : using Hadoop-Spark Framework

The bandwagon effect is a psychological phenomenon that a person’s behaviors, attitudes, and beliefs are influenced by other people [1]. This phenomenon has been proved that it has an influence to user behaviors, even in online environment. However, a few studies have considered both of the bandwagon effect and social group opinion simultaneously for improving personalized rating prediction performance. In this paper, we propose a novel formulation for the users’ ratings that each rating is considered as a function of user preference rating and group-based social opinion which are adjusted by bandwagon effect. For to process real big data, we used Hadoop-Spark framework which can make high-speed operations. As a result, our method outperforms the existing model significantly in improving the prediction accuracy of users’ ratings on RMSE.
Finger Movement Identification Using EMG Signal on the Forearm

Finger movement identification is an important innovative interfacing method which has countless possible applications. It can be used to create a new age in human computer interfacing (HCI) devices. It can also be applied to medical applications, such as in the development of a more advanced prosthetic hand. The current research for this purpose includes methods such as computer vision and detecting finger motion through mechanical vibrations from skin surface. They have the limitation of being restrictive, in terms of the degree of movement that the hand is allowed from a certain optimum position, as well as being susceptible to environmental factors. In this study, the surface electromyography (sEMG) of the forearm from skin electrodes is developed and interfaced with computer. The response at the flexor carpi radialis muscle of the forearm is plotted for a group of subjects to observe the qualitative responsiveness of the sEMG to different types of finger movements. The results show that finger movement generates a corresponding response on the EMG electrodes. For the particular muscle being studied, the greatest individual digit amplitude response was observed for the ring finger (digitus annularis) across the subjects. In future studies, this research could be made more quantitative in nature by observing the frequency content of a variety of hand gestures across a sample of subjects
Data Driven Device Failure Prediction

Abstract : As society becomes more dependent upon computer systems to perform increasingly critical tasks, ensuring those systems do not fail also becomes more important. Many organizations depend heavily on desktop computers for day to day operations. Unfortunately, the software that runs on these computers is still written by humans and as such, is still subject to human error and consequent failure. A natural solution is to use statistical machine learning to predict failure. However, since failure is still a relatively rare event, obtaining labeled training data to train these models is not trivial. This work presents new simulated fault loads with an automated framework to predict failure in the Microsoft enterprise authentication service and Apache web server in an effort to increase up-time and improve mission effectiveness. These new fault loads were successful in creating realistic failure conditions that are accurately identified by statistical learning models.
Paper / Stochastic Hydrogeology : What Professionals Really Need ?

Quantitative hydrogeology celebrated its 150th anniversary in 2006. Geostatistics is younger but has had a very large impact in hydrogeology. Today, geostatistics is used routinely to interpolate deterministically most of the parameters that are required to analyze a problem or make a quantitative analysis. In a small number of cases, geostatistics is combined with deterministic approaches to forecast uncertainty. At a more academic level, geostatistics is used extensively to study physical processes in heterogeneous aquifers. Yet, there is an important gap between the academic use and the routine applications of geostatistics. The reasons for this gap are diverse. These include aspects related to the hydrogeology consulting market, technical reasons such as the lack of widely available software, but also a number of misconceptions. A change in this situation requires acting at different levels. First, regulators must be convinced of the benefit of using geostatistics. Second, the economic potential of the approach must be emphasized to customers. Third, the relevance of the theories needs to be increased. Last, but not least, software, data sets, and computing infrastructure such as grid computing need to be widely available.
Protective effect of Andrographis paniculata on hyperglycemic mediated oxidative damage in renal tissues of diabetic rats

The aim of this study is to evaluate the protective effect of ethanol extract of Andrographis paniculata (A. paniculata) on hyperglycemic mediated oxidative damage in the renal tissues of experimental diabetic rats and to determine the potential bioactive components of A. paniculata ethanol extract was scrutinized using GC-MS techniques. Diabetes was induced in rats by streptozotocin. Experimental period, the animal body weight, blood glucose, urea, serum proteins, cholesterol, antioxidant key enzymes and histological changes in kidneys were determined. The untreated diabetic and A. paniculata treated diabetic groups lost weight and consumed less quantity of food compared to the normal group. We noted decrease in blood glucose in the ethanol extract of A. paniculata treated diabetic group compared to normal and glibenclamide treated groups. The serum protein level was increase and cholesterol and urea levels were significantly (P<0.01) reduced in the A. paniculata extract treated group compared to the normal group. The levels of lipid peroxides in Plasma and kidney tissues were found to be elevated and kidney tissue enzymes of Superoxide dismutase, Catalase and Glutathione peroxidase were found to be decreased in streptozotocin induced diabetic rats when compared to normal. After treatment of A. paniculata, it brings back to significantly (P<0.01) near normal levels. Diabetes associated with marked histological changes in the kidney over a period of 32 days as revealed by tubular epithelial hypertrophy, glomerulosclerosis and glycogen accumulation. Treatment with A. paniculata extract afforded significant protection from renal damage whereas tubular damage was more pronounced in rats treated with glibenclamide. According to traditional indigenous medicinal systems of India this plant has got several medicinal effects without producing any severe side effects. This plant could be very well used as prevention of hyperglycemic complications and tissues damaging through the oxidation.
TROPICAL CYCLONE GENERATED ROGUE WAVES

This paper introduces a new deep sea dataset for the study of rogue and extreme rogue waves: the first is defined as a singular wave height greater than twice the significant wave height and the latter has the additional criteria of a wave height of 15 m or greater. This dataset is particularly unique due to the measurement of near field winds and waves from 4 major tropical cyclones and the swell from a 5 th . The introductory subsections include a primer on rogue waves, an overview of the field campaign, and a review of tropical cyclone (TC) generated sea states in the context of this study. The subsections under methods delve into detail about the mooring characteristics, buoy design, data analysis, and treatment of errors. The results section explains the timing of storm passages and attempts to objectively define periods in the data when the sea state is dominated by (and lacks) TC activity. Then, some simple analysis is presented of the two periods (TC and non-TC) for (1) number of rogue waves observed and (2) spectral characteristics related to unstable seas. The paper concludes with a discussion of the results and the potential of future work with this data.