Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular bacterial diversityofa forest soil under residue management regimes in subtropicalAustralia

A major operational change in exotic pine plantations of subtropical Australia has been the decision to retain postharvest residues on site. A long-term field experiment was established in February 1996 to examine the impacts of residue management regimes [i.e. the postharvest residues removed (G0R), natural amount of residues retained (G1R) and residue quantity doubled and retained (G2R)] on tree growth (F1 hybrid pine) and sustainable soil management. Twelve soil samples, which included the above three residue regimes with four replicates, were collected at plantation age 6.4 years. A 16S rRNA gene clone library was established following soil community DNA extraction, polymerase chain reaction amplification and cloning. A total of 324 clones, including 27 from each sample, were randomly selected and sequenced to represent the bacterial composition and diversity of the clone library and thus the soil bacterial community under the residue management regimes. Phylogenetic analyses indicated that Acidobacteria (37.6%) and Proteobacteria (35.6%) were the dominant components of the soil bacterial community, followed by Actinobacteria (14.7%), Chlamydiae/Verrucomicrobia (7.3%), Unclassified Bacteria (3.8%) and Gemmatimonadetes (1.0%). Analysis of molecular variance revealed that there was no significant difference in bacterial composition and diversity among the residue management regimes or their replicated samples.
Fraud Detection Using Random Forest Algorithm

The usage of internet, online shopping and home services are gaining importance among people. But, at the same time customers are also taking undesirable benefits by performing unusual activities. In case of online shopping, a certain limitation in purchasing number of products are specified by the e-commerce websites. When people are getting higher discounts, some people start taking advantage of it and conduct fraudulent activities. Therefore, analysis of fraud is required to detect them and prevent these unusual activities. In this paper, frauds are detected effectively by using Random Forest algorithm in R language. Keywords-Random Forest, caret, Data Mining, Machine Learning, Supervised Learning, Unsupervised Learning
Auto-Parallelizing Deep Learning for Multi-machine , Multi-GPU Environments

Being able to use a cluster of GPU resources is favorable especially for machine learning researchers, as training neural nets typically requires at least tens of GPUs in order to finish within feasible time. Neural networks can be made to be trainable on multiple devices, which are CPUs or GPUs in multi-machines, to speed up training and improve convergence. This is further facilitated by the introduction of deep learning systems such as TensorFlow [2], MXNet [4] and Caffe2 [1]; such frameworks allow users to easily utilize multi-machine, multi-GPU environments to train networks, to a certain degree. Unfortunately, extending single-machine, single-GPU neural net models to work in distributed environments is not a trivial job for common machine learning researchers. In most deep learning frameworks [1, 2, 4], a deep learning job is represented as a computation graph, and the computation graph needs to be changed for distributed environments, which requires partitioning model parameters across machines to balance out communication overheads, as well as replicating and assigning graph operators to devices so that hardware resources can cooperate to train a model. To this end, we introduce Parallax, an auto-parallelization module that helps machine learning researchers extend their single-model code to operate in data parallelism with multiGPU and multi-machine. Parallax receives a single-device graph, analyzes the graph, then transforms it into a multimachine, multi-GPU version of the computed settings. The automatically transformed graph can finally be run in distributed environments. Preliminary experiments show that with the help of Parallax, the ResNet-50 [9] model can be trained on a total of 12 GPUs across 3 machines with sublinear scale-out improvements in computation throughput. We also discuss several extensions on Parallax, including the application of model parallelism strategies to boost performance for models with relatively large parameters, as well as hybrid parallelism strategies that utilize both data parallelism and model parallelism.
Evidence on Structure Conduct Performance Hypothesis in Pakistani Commercial Banks

The purpose of this research is to examine the relationship between market structure and performance in thebanking sector using data from Pakistani commercial banks. Investigating the effect of changes in the marketstructure on profitability is based on the structure-conduct-performance (SCP) and efficient-structure (E-S)hypotheses. We have taken a sample of 20 scheduled commercial banks incorporated in Pakistan to examine theabove hypotheses, using the annual and pooled data for a period of 9 years from year 1996-2004. Threemeasures of bank’s performance are utilized: return on assets (ROA), return on capital (ROC) and return onequity (ROE). We have used concentration ratio (CR) to measure structure-conduct-performance (SCP)hypothesis and market share to measure efficient-structure (E-S) hypothesis. We have also used control variablesto capture market specific characteristics such as bank size, market size, risk to owners, liquidity measure,market risk, and market growth. Using regression analysis, we have found a positive relationship ofconcentration ratio (CR) with profitability. In light of these results, we conclude that there is a positiverelationship between profitability and concentration.The results of market share (MS) which is used for efficient structure (E-S) hypothesis explain a negativerelationship with profitability. The results of our analysis do not support the efficient structure (E-S) hypothesis.The empirical findings suggest that market concentration determines the profitability in Pakistani commercialbanks. Hence, we also conclude that there is a negative relationship between competition and profitability in thePakistani commercial banks. The leading banks are still enjoying the state of monopoly. But, the market trendshows that this state will not continue for a longer period as private commercial banks have started to competewith the existing top commercial banks.
Sensitivity of DBSCAN in identifying activity zones using online footprints

In mining spatial(-temporal) data for trajectory and activity analyses, a common task is to determine spatial clusters, which may represent activity zones. DBSCAN is a popular clustering algorithm. How the two parameters of DBSCAN that control the clustering algorithm may affect the results spatially has not been thoroughly investigated. This paper reported an incremental effort in conducting a sensitivity analysis by changing the parameter values. Preliminary results show that the two parameters work against each other to a certain degree. Increasing one parameter value (minpts) will break up larger clusters into smaller ones, while the other parameter (eps) controlled the spatial scale of clusters that can be detected.
A NEW MOSS GENUS OF FUNARIACEAE FROM TRANSBAIKALIA ( EAST SIBERIA , RUSSIA )

Afoninia dahurica from the Transbaikal region of the East Siberia in Russia is described as a new species accommodated in a new genus of Funariaceae, based on molecular phylogenetic evidence from nrITS, trnL-F and psbA-trnH, that highlights the combination of strongly reduced double peristome with a well developed annulus of inflated revoluble cells. The exostome teeth are tapered to the base and attached to basal membrane with a plate that is less than one third of the cell of the endostome to which it adheres. The plant is known from few nearby localities in a xeric area of Dahuria, growing on soil near cliffs.
Feasibility of agroforestry for sugarcane production and soil conservation in Brazil

*L.F. G. Pinto, M.S. Bernardes, and G.M.S. Camara, Crop Science Department – ESALQ / University of São Paulo, Brazil; G. Sparovek, Soil Sciences Department ESALQ / University of São Paulo, Brazil. *Corresponding author: lfgpinto@carpa.ciagri. usp.br, current address: R. Alexandre Fleming 875, Campinas, SP, Brazil 13092-340. ABSTRACT Brazil is the main world producer of sugarcane, growing it in a monocropping system with high input and technology. Its management plays an important role in conservation of soils and other natural resources and to the life quality of rural workers and urban communities. Due to law enforcement, the burning of cane before harvest has been eliminated and the harvest system has been mechanized. It has produced huge environmental and social impacts and the activity has become unviable for small producers and in areas with slopes higher than 12%. The features and potentials of this system are discussed, as well as the research needs and strategic priorities and actions to its adoption and success. Agroforestry systems with contour hedgerows are one of the most suitable options to make production and conservation possible in non-mechanized areas.
Creation of a longitudinally polarized subwavelength hotspot with an ultra-thin planar lens: vectorial Rayleigh–Sommerfeld method

This letter shows how a longitudinally polarized hotspot can be created by a planar ultra-thin lens that beats the diffraction limit. On the imaging plane, a subwavelength optical resolution 0. 39λ with almost purely longitudinal electric component has been demonstrated in air ambient. This novel paradigm addresses simultaneously both longitudinal polarization and deep sub-diffraction imaging, by a planar lens composed of ultra-thin opaque concentric annuli. The vectorial Rayleigh–Sommerfeld (VRS) approach, offering the advantage of significant reduction in computation, has been developed for a particular optimization of a flat lens with full control of polarization. Empowered by the robustness of VRS in dealing with polarization states, the proposed roadmap may be universally and efficiently integrated with other optimization algorithms to design super-resolution imaging with controlled polarization states at any wavelength without luminescence of the object. The lens, which is empowered by the proposed method, opens an avenue for the first time toward a highly integrated imaging system with advanced functionalities in far-field super-imaging, tailored polarization states and flat ultra-thin geometry simultaneously.
Measurement, Recognition, and Visualization of Piano Pedaling Gestures and Techniques

This paper presents a study of piano pedaling gestures and techniques on the sustain pedal from the perspective of measurement, recognition, and visualization. Pedaling gestures can be captured by a dedicated measurement system where the sensor data can be simultaneously recorded alongside the piano sound under normal playing conditions. Using the sensor data collected from the system, the recognition is comprised of two separate tasks: pedal onset/offset detection and classification by technique. The onset and offset times of each pedaling technique were computed using signal processing algorithms. Based on features extracted from every segment when the pedal is pressed, the task of classifying the segments by pedaling technique was undertaken using machine learning methods. We compared Support Vector Machines (SVM) and hidden Markov models (HMM) for this task. Our system achieves high accuracies, over 0.7 F1 score for all techniques and over 0.9 on average. The recognition results can be represented using novel pedaling notations and visualized in an audio-based score following application.
Delexicalized Supervised {German} Lexical Substitution

We address the German lexical substitution task, which requires retrieving a ranked list of meaning-preserving substitutes for a given target word within an utterance. With GermEval-2015: LexSub 1 , this challenge is posed for the ﬁrst time using German language data. In this work we build upon the existing state of the art for English lexical substitution, employing a delexicalized supervised system. In adapting the existing approach, we consider in particular the available lexical resources for German and evaluate their suitability to the task at hand. We report ﬁrst results on German lexical substitution and observe a similar performance as English systems evaluated on the SemEval dataset.
Anesthetic properties of Ocimum gratissimum essential oil for juvenile matrinxã

The matrinxa fish is suitable for Amazonian aquaculture, exhibiting positive characteristics such as good growth and feed conversion ratio. However, it is a very active fish and must be anesthetized for handling. The present study evaluated the use of Ocimum gratissimum essential oil (EO) as anesthetic for juvenile matrinxas. A first experiment assessed the induction time to anesthesia of 7 concentrations (20, 30, 40, 50, 60, 70 and 80 mg L-1 of O. gratissimum (EO). A second experiment investigated the physiological response to the anesthetic through analysis of tissue and blood parameters collected 0h (T0) and 24h after (T24) the experimental protocols that were applied to 4 groups: control, handling without O. gratissimum (EO) and handling with two EO levels. In the first experiment, fish were anesthetized within 10 min in the lowest EO concentration (20 mg L-1), and recovered within 2 min. As concentrations increased times to induction to anesthesia decreased from 10 min to 1 min (approximately). In the second experiment, plasma lactate, glucose and ammonia increased in the treatments involving handling and EO concentrations. After 24h, fish had recovered from the experimental procedures, and no mortality was observed in the next 30 days. Ocimum gratissimum was shown to be a suitable anesthetic for matrinxas, and causes minimum stress to fish in the concentrations and exposure time applied.
An Adaptive and Learning Approach to Sampling Optimization

This paper provides a methodology to rapidly and accurately explore the cost function of an optimization problem based on rejection sampling. Initial results show good precision and rapid convergence. This leads to numerous applications where a multi-minima problem must be optimized or solved, such as those seen in control problems, optimal orbit maneuvers, or constellation design. The approach will be shown to be adaptive and to cover mixed integer-real functions.
A Multi-Group Analysis of Innovation in Online Business Models

A sample of 295 firms in Canada across various sectors was used for testing the relationship between Net-enabled Business Innovation Cycle (NEBIC) and innovation in online business models. These firms were categorised as sectors with different levels of online selling adoption, online buying orientations and firms with different sizes. Quantitative analysis and SEM results revealed a reasonable fit between data collected and the model used: chi2 (4757.63), chi2 / DF (2.24), RMSEA (0.08), CFI (0.86), and TLI (0.86). The multi-group analysis showed statistically significant evidence that online seller’s differentiated firms with smaller sizes and firms with no prior online buying to demonstrate the relationship between Net-enablement capability and the choice to sell online. However, firms from different sectors with different online selling adoption rates showed statistically insignificant differences. Therefore, when considering the adoption of new technologies such as online selling, smaller firms with no prior online buying may produce better results in their business models regardless of their associated business sectors’ level of online selling adoption rates.
Effect of Cellulase and Lactic Acid Bacteria on Fermentation Quality and Chemical Composition of Wheat Straw Silage

The object of this study was to determine the effect of cellulase and lactic acid bacteria (LAB) on fermentation quality and chemical composition of wheat straw silage. Silages were prepared using a small-scale fermentation system and the moisture level was adjusted to 60% of fresh matter (FM) with deionized water. Treatments were designed as: control silage without additives, LAB inoculant Lactobacillus casei Z3-1 (1.0 × 106 cfu·g-1 of FM), commercial inoculant L. plantarum FG 1 (1.0 × 106 cfu·g-1 of FM), Z3-1 + cellulase and FG 1 + cellulase. The neutral detergent fiber (NDF), acid detergent fiber (ADF) and crude protein (CP) contents of the wheat straw prior to ensiling were 76.93%, 48.52% and 4.63% of dry matter (DM), respectively. After 30 days of fermentation, the silages treated with LAB and LAB + cellulase had a lower (P P P
Clustering Techniques on Pap-smear Images for the Detection of Cervical Cancer

A Pap smear test is the most efficient and prominent method for the detection of dysplasia in cervical cells. Pap smear is time-consuming and sometimes it is an erroneous method. Computer-assisted screening can be widely used for cervical cancer diagnosis and treatment. Most of the existing approaches do not give good performance on real images due to poor staining, dye, blood and inflammatory cells. In our proposed approach, we are extracting nucleus only from the Pap smear images. For segmentation Laplacian of Gaussian (LOG) filter and morphological operations has used for edge detection. In the classification phase, two clustering techniques K-means and Fuzzy c-means (FCM) has been used using Principle Component Analysis (PCA). The classification of Pap smear images is based on the Bethesda System. The approach has performed on a dataset obtained from pathologic lab containing 40 Pap smear images with 500 cells. Performance evaluation has done using Purity and Jaccard Index (JI). The purity of K-means is 0.815 and for FCM it's 0.875.
Comparison of capture and storage methods for aqueous macrobial eDNA using an optimized extraction protocol: advantage of enclosed filter

Aqueous environmental DNA (eDNA) is an emerging efficient non‐invasive tool for species inventory studies. To maximize performance of downstream quantitative PCR (qPCR) and next‐generation sequencing (NGS) applications, quality and quantity of the starting material is crucial, calling for optimized capture, storage and extraction techniques of eDNA. Previous comparative studies for eDNA capture/storage have tested precipitation and ‘open’ filters. However, practical ‘enclosed’ filters which reduce unnecessary handling have not been included. Here, we fill this gap by comparing a filter capsule (Sterivex‐GP polyethersulfone, pore size 0·22 μm, hereafter called SX) with commonly used methods. Our experimental set‐up, covering altogether 41 treatments combining capture by precipitation or filtration with different preservation techniques and storage times, sampled one single lake (and a fish‐free control pond). We selected documented capture methods that have successfully targeted a wide range of fauna. The eDNA was extracted using an optimized protocol modified from the DNeasy® Blood & Tissue kit (Qiagen). We measured total eDNA concentrations and Cq‐values (cycles used for DNA quantification by qPCR) to target specific mtDNA cytochrome b (cyt b) sequences in two local keystone fish species. SX yielded higher amounts of total eDNA along with lower Cq‐values than polycarbonate track‐etched filters (PCTE), glass fibre filters (GF) or ethanol precipitation (EP). SX also generated lower Cq‐values than cellulose nitrate filters (CN) for one of the target species. DNA integrity of SX samples did not decrease significantly after 2 weeks of storage in contrast to GF and PCTE. Adding preservative before storage improved SX results. In conclusion, we recommend SX filters (originally designed for filtering micro‐organisms) as an efficient capture method for sampling macrobial eDNA. Ethanol or Longmire's buffer preservation of SX immediately after filtration is recommended. Preserved SX capsules may be stored at room temperature for at least 2 weeks without significant degradation. Reduced handling and less exposure to outside stress compared with other filters may contribute to better eDNA results. SX capsules are easily transported and enable eDNA sampling in remote and harsh field conditions as samples can be filtered/preserved on site.
Towards a Broad-Scale Usability Evaluation of Hybrid BCIs

For the study, three graphical user interfaces (GUIs) were designed for their prospective use in controlling a brain-computer interface (BCI)-driven upper-limb neuroprosthesis. The action selection was divided into two stages: selection and confirmation that were controlled using event-related potentials (ERP) or motor imagery (MI). By evaluating usability on a broad-scale including behavioural, subjective and EEG data, the study provides valuable insights into the underlying dynamics that cause the differences in performance across the GUIs.
Long Wave Infrared Cavity Enhanced Sensors

The principal goal of Pacific Northwest National Laboratory's (PNNL's) long wave infrared (LWIR) cavity enhanced sensor (CES) task is to explore ultra-sensitive spectroscopic chemical sensing techniques and apply them to detecting proliferation of weapons of mass destruction (WMD). Our primary application is detecting signatures of WMD production, but LWIR CES techniques are also capable of detecting chemical weapons. The LWIR CES task is concerned exclusively with developing novel point sensors; stand-off detection is addressed by other PNNL tasks and projects. PNNL's LWIR CES research is distinguished from that done by others by the use quantum cascade lasers (QCLs) as the light source. QCLs are novel devices, and a significant fraction of our research has been devoted to developing the procedures and hardware required to implement them most effectively for chemical sensing. This report details the progress we have made on LWIR CES sensor development.
Correlates of Vigorous Physical Activity for Children in Grades 1 Through 12: Comparing Parent-Reported and Objectively Measured Physical Activity

Correlates of physical activity were examined in young people in grades 1 through 12, and analyses were conducted separately for eight age/grade and sex subgroups. Twenty-one explanatory variables were assessed by parental report. Physical activity was assessed in 781 young people via parent report, and 200 wore an accelerometer for seven days. Between 11% and 36% of parent-reported child vigorous physical activity was explained. The most consistent correlates were peer support and use of afternoon time for active rather than sedentary recreation. Peer support was the only significant correlate of objectively monitored activity in multiple subgroups.
Two-Dimensional l1-Norm Minimization in SAR Image Reconstriction

Abstract A nonconventional image algorithm, based on compressed sensing and l1-norm minimization in Synthetic Aperture Radar (SAR) application is discussed. A discrete model of the earth surface relief and mathematical modeling of SAR signal formation are analytically described. Sparse decomposition in Fourier basis to solve the SAR image reconstruction problem is discussed. In contrast to the classical one-dimensional definition of l1-norm minimization in SAR image reconstruction, applied to an image vector, the present work proposes a two-dimensional definition of l1-norm minimization to the image. To verify the correctness of the algorithm, results of numerical experiments are presented.