Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal fluctuation and reproduction of Thermocyclops decipiens (Copepoda, Cyclopoida) in an eutrophic lake of central Brazil.

Lake Paranoá is an eutrophic reservoir situated in the urban region of Brasília. This study was carried out in a fixed collection station located in the Riacho Fundo branch of the reservoir. Zooplankton samples were collected at intervals of 3-5 d at 9:00 a.m. during two months in the dry and rainy seasons for two years (dry-1996, rainy-1997, dry-1997 and rainy-1998), using a 64 microns-mesh plankton net. The most predominant species was Thermocyclops decipiens (about 50% of the total zooplankton community), which during the whole period had a high reproductive rate. The highest densities were found in the dry-1996 season (1700 ind/l for nauplii), and also fluctuated widely overtime. Nauplii stages dominated during the four periods, comprising 50-75% of the total population density. Ovigerous females peaked in the dry-1996 and rainy-1997 seasons, with 20-30% of the total females. The largest peak in egg production occurred during the dry-1996 season, and the total egg production was 2.0 x 10(3) eggs/l. Mesocyclops longisetus is a first record for Lake Paranoá. The ecological factors that determine the success of T. decipiens in eutrophic systems are related to omnivorous feeding habits and prey-predator interactions.
Simulation metamodeling in continuous time using dynamic Bayesian networks

The application of dynamic Bayesian networks (DBNs) is a recently introduced approach to simulation metamodeling where the probability distribution of simulation state is represented as a function of time. The DBN metamodels reveal the time evolution of simulation and enable alternative what-if analyses unlike previous metamodels that imitate the simulation model as an input-output mapping. In earlier studies, the analysis of DBNs is restricted to discrete time instants selected beforehand in the construction phase of the metamodel. This paper introduces an extension to the framework of DBN metamodeling that employs multivariate interpolation and allows the analysis in continuous time. In practice, an approximation for the probability distribution of the simulation state is calculated by interpolating between conditional probabilities given by the DBN. The utilization of multivariate interpolation in the context of DBN metamodeling is illustrated by examples dealing with Poisson arrival processes and air combat simulation.
Tabsol decision table preprocessor

This paper describes the Tabsol Decision Table Preprocessor, a program product of the B.F. Goodrich Company. The Tabsol (Tabular systems oriented language) Preprocessor, itself written in ANSI Cobol, is designed to translate horizontalrule, extended-entry decision tables into equivalent Cobol statements. Design objectives, language format and implementation results of the Tabsol Preprocessor are summarized in this paper. This preprocessor has been in full production use by the Information Systems Department of B.F. Goodrich Chemical Company since January 1971.
The Semantic Web and Policy ?

As Semantic Web technologies mature and become more accepted by researchers and developers alike, the widespread growth of the Semantic Web seems inevitable. However, this growth is currently hampered by the lack of well-defined security protocols and specifications. Though the Web does include fairly robust security mechanisms, they do not translate appropriately to the Semantic Web as they do not support autonomous machine access to data and resources and usually require some kind of human input [9]. Also, the ease of retrieval and aggregation of distributed information made possible by the Semantic Web raises privacy questions as it is not always possible to prevent misuse of sensitive information [12]. In order to realize it’s full potential as a powerful distributed model for publishing, utilizing, and extending information, it is important to develop security and privacy mechanisms for the Semantic Web. Policy frameworks built around machine-understandable policy languages, with their promise of flexibility, expressivity and automatable enforcement appear to be the obvious choice. The term policy is very broad and can mean different things in different contexts. We consider a policy to be a declarative set of rules that guide the behavior of entities within a system. Policies are a way to implement flexible security for dynamic and dis-
Using SharpeR

The SharpeR package provides basic functionality for testing significance of the Sharpe ratio of a series of returns, and of the Markowitz portfolio on a number of possibly correlated assets. [16] The goal of the package is to make it simple to estimate profitability (in terms of riskadjusted returns) of strategies or asset streams. 1 The Sharpe ratio and Optimal Sharpe ratio Sharpe defined the ‘reward to variability ratio’, now known as the ‘Sharpe ratio’, as the sample statistic
Low-Density Parity-Check Codes for Discretized Min-Sum Decoding

The performance of low-density parity-check (LDPC) codes transmitted over a memoryless binary-input continuous output additive white Gaussian noise (AWGN) channel and decoded with quantized min-sum decoding is strongly influenced by the decoder's quantization scheme. This paper presents an efficient algorithm that determines the best uniform scalar quantizer for a particular code. To maximize performance, it is necessary to determine degree distributions that best match the characteristics of the quantized min-sum decoder. Toward this end, an iterative optimization framework that jointly optimizes the degree distributions and the quantizer is presented
A study of intrusion detection system based on data mining

In this paper, classifications of intrusion detection and methods of data mining applied on them were introduced. Then, intrusion detection system design and implementation of based on data mining were presented. Such a system used APRIORI algorithm to analyse data association, which is the most influencing algorithm in mining Boolean association rules continuity item muster, with recurrence arithmetic based on idea of two period continuity item muster as core. Experiments showed that new type of attack can be detected effectively in the system, and knowledge base can be updated automatically, so the efficiency and accuracy of the intrusion detection were improved, and security of the network was enhanced.
Electron Microscopy Reconstruction of Brain Structure Using Sparse Representations Over Learned Dictionaries

A central problem in neuroscience is reconstructing neuronal circuits on the synapse level. Due to a wide range of scales in brain architecture such reconstruction requires imaging that is both high-resolution and high-throughput. Existing electron microscopy (EM) techniques possess required resolution in the lateral plane and either high-throughput or high depth resolution but not both. Here, we exploit recent advances in unsupervised learning and signal processing to obtain high depth-resolution EM images computationally without sacrificing throughput. First, we show that the brain tissue can be represented as a sparse linear combination of localized basis functions that are learned using high-resolution datasets. We then develop compressive sensing-inspired techniques that can reconstruct the brain tissue from very few (typically five) tomographic views of each section. This enables tracing of neuronal processes and, hence, high throughput reconstruction of neural circuits on the level of individual synapses.
Multilevel Display for Aggregated Document Networks

The challenge of finding documents relevant to a task is pervasive in today’s information rich society. Current methods for finding documents focus on keyword search using resources such as Internet search engines or digital libraries provided by professional organizations. Visual representations can augment the search for information, yet the vastness of sources must be dealt with in a way that makes these large bodies of documents comprehensible and individual documents identifiable. The current work describes a system that provides a means to organize documents through graph based clustering and allows the user to display and interact with an abstracted multilevel visual display of information. The clustering techniques used by the system to provide abstracted views exploit the organizational characteristics of document collections and web based sources to supply users a seamless representation useful for overview, document identification, and document retrieval.
Circle Orders , Ngon Orders and the Crossing Number of Partial Orders

Let F={P 1 ,. ,P m } be a family of sets. A partial order P(F, <) on F is naturally defined by the condition P i < P j iff P i is contained in P j. When the elements of F are disks (i.e. circles together with their interiors), P(F, <) is called a circle order; if the elements of F are n-polygons, P(F, <) is called an n-gon order. In this paper we study circle orders and n-gon orders. The crossing number of a partial order introduced in [5] is studied here. We show that for every n, there are partial orders with crossing number n. We prove next that the crossing number of circle orders is at most 2 and that the crossing number of n-gon orders is at most 2n. We then produce for every n≥4 partial orders of dimension n which are not circle orders. Also for every n≥3, we prove that there are partial orders of dimension 2n+2 which are not n-gon orders. Finally we prove that every partial order of dimension ≤ 2n is an n-gon order. (NSERC Canada) grant numbers A2507 and A0977. 1. Introduction. The study of simple geometric figures, such as points, circles and polygons has been the source of many interesting and important results since the beginnings of mathematics. The study of incidence relations in collections of points, lines and circles are found in books as far back as the famous Elements of Euclid. When dealing with families of simple geometric objects such as circles, polygons, and so on, a basic problem is that of determining the containment relations among the elements of the set. In this paper, we will study partial orders arising from containment problems of families of simple objects on the plane.
Using an On-line Educational Module to Increase Nurses' Conviction and Confidence in the Use of the Teach-Back Method for Discharge Instructions

Health literacy status can affect an individual’s ability to self-monitor and manage chronic conditions. It is not uncommon for patients to have difficulty comprehending key patient instructions. The role of the nurse in the hospital setting encompasses many facets which include patient teaching. Providing effective patient teaching is one role that many nurses do not feel confident in implementing. A sample of (N=18) nurses participated in on-line educational program to improve conviction and confidence in use of the teach-back method for delivery of discharge instructions. A pretest-posttest design was utilized and measured nurses’ conviction and confidence using the Conviction and Confidence Scale (CCS) survey. No statistically significant increase in conviction or confidence scores of participants was noted from pre-testing to post-testing. The survey also measured teach-back behaviors of participants. There was a notable increase of 72% in post-test intervention scores in the use of the teach-back behavior of asking the patient to explain what they were taught. This element is the foundation of the teachback method.
Rank Level Integration of Face Based Biometrics

This paper investigates the integration of two modalities: facial thermograms and ear, extracted from the same face, by using rank level fusion scheme. The first modality consists of the infrared thermal faces acquired using infrared camera whereas the second one constitutes point features on the ear imaged using ordinary digital camera. The acquired facial thermo grams and ear images are first normalized by locating ROI and then features are extracted using Haar wavelets and SHIFT (Scale Invariant Feature Transform) respectively. Integration of their associated ranks has been done by using the modified Borda count and logistic regression methods. The proposed authentication system is tested on 500 facial thermo grams and ear images and operates on 98% of genuine acceptance rates (GAR) at 0.1% of false acceptance rate (FAR). Although substantial work remains to be done, yet our results indicate that the rank level integration of facial thermo grams and ear images is poised to provide a promising direction to the face based multimodal biometric systems.
Rule inference for financial prediction using recurrent neural networks

The paper considers the prediction of noisy time series data, specifically, the prediction of foreign exchange rate data. A novel hybrid neural network algorithm for noisy time series prediction is presented which exhibits excellent performance on the problem. The method is motivated by consideration of how neural networks work, and by fundamental difficulties with random correlations when dealing with small sample sizes and high noise data. The method permits the inference and extraction of rules. One of the greatest complaints against neural networks is that it is hard to figure out exactly what they are doing-this work provides one answer for the internal workings of the network. Furthermore, these rules can be used to gain insight into both the real world system and the predictor. The paper focuses on noisy time series prediction and rule inference-use of the system in trading would typically involve the utilization of other financial indicators and domain knowledge.
Variational approaches to super-resolution with contrast enhancement and anisotropic diffusion

We present super-resolution methods that enhance im- age contrast and perform anisotropic diffusion simultaneously. Since we solve the super-resolution problem by encouraging Mach-band profiles while incorporating anisotropic diffusion, our technique not only reconstructs a high-resolution image from several overlapping noisy low-resolution images, but also enhances edges and image contrast while suppressing image noise during the restoration pro- cess. We apply this technique to a video stream, which can be aligned by 333 projective transformations. © 2003 SPIE and IS&T.
Design of a split P-shaped multiband microstrip patch antenna for modern communication system

A fictional design of a compact microstrip patch antenna for multiband frequency has been depicted in this paper. The proposed design presents a slit P-shaped antenna that operates at 3.5 GHz, 5.9 GHz, 9.2 GHz and 13.1 GHz. FR-4 (lossy) is used as substrate to design the recommended antenna which has a firm dimension of 18 × 20 mm2. This antenna operates at S, C, X and Ku band with moderate bandwidth because of its design and feedline. This P-shaped multiband antenna has directive gain of 3.3dBi, 4.9 dBi, 6.5 dBi and 7.1 dBi at resonating frequencies and is suitable for a modern communication system. Regarding this antenna, the results are obtained in terms of Return Loss, Voltage Standing Wave ratio, Gain and Radiation Pattern which have admissible values of return loss less than −10 dB, VSWR less than 2 at each resonant frequencies and Gain more than 3 dB.
A cooperative network measurement platform: Design and implementation

This paper describes the design and implementation of a new cooperative network measurement platform, which can be used for network management tasks such as distributed quality of service (QoS) measurement, cooperative network troubleshooting. The platform is based on a hybrid peer-to-peer (P2P) structure to realize node management and task coordination, in which the P2P communication protocol and message encoding are described, and other issues like incentive and security mechanisms are also discussed. Finally the typical application scenarios of the platform are presented.
Effect of yoga on positive–Negative affect and self-esteem on tribal male adolescents- A randomized control study

Aim: Effect of yoga on positive–negative affectivity and self-esteem in tribal adolescents. Material and Methods: This is a pilot randomized control study. Several chits were made in which the name of all the available students was written. The youngest boy from the group selected 30 chits for yoga group and the remaining students were included in the control group. The yoga group included 30 male adolescents between the age of 10 years and 18 years (M = 14.4, SD = 3.51). Control group included 25 male adolescents between the age of 10 years and 18 years (M = 13.3, SD = 1.90). PANAS-C and Rosenberg self-esteem scales were used to measure the positive–negative affectivity and self-esteem, respectively. Data was collected before and after interventions. Results: Study shows significant increase in positive affect (P = 0.008) and negative affect (P = 0.047) in experimental group as compared to control group's positive affect (P = 0.468) and negative affect (P = 0.156). Self-esteem in experimental group slightly reduced (P = 0.927). Similarly, self-esteem in control group reduced (P = 0.019). Conclusion: Study suggests that two weeks of yoga practice has a significant impact on positive-negative affect in tribal adolescents.
Fabrication of Micro-Needle Electrodes for Bio-Signal Recording by a Magnetization-Induced Self-Assembly Method

Micro-needle electrodes (MEs) have attracted more and more attention for monitoring physiological electrical signals, including electrode-skin interface impedance (EII), electromyography (EMG) and electrocardiography (ECG) recording. A magnetization-induced self-assembling method (MSM) was developed to fabricate a microneedle array (MA). A MA coated with Ti/Au film was assembled as a ME. The fracture and insertion properties of ME were tested by experiments. The bio-signal recording performance of the ME was measured and compared with a typical commercial wet electrode (Ag/AgCl electrode). The results show that the MA self-assembled from the magnetic droplet array under the sum of gravitational surface tension and magnetic potential energies. The ME had good toughness and could easily pierce rabbit skin without being broken or buckling. When the compression force applied on the ME was larger than 2 N, ME could stably record EII, which was a lower value than that measured by Ag/AgCl electrodes. EMG signals collected by ME varied along with the contraction of biceps brachii muscle. ME could record static ECG signals with a larger amplitude and dynamic ECG signals with more distinguishable features in comparison with a Ag/AgCl electrode, therefore, ME is an alternative electrode for bio-signal monitoring in some specific situations.
On the follower set graph of shifts of finite type

Constrained sequences have been used in many storage systems as well as in data transmission schemes. These sequences are usually described by a deterministic graph. The graph with the fewest vertices is obtained, in general, via a two-step procedure: The first step is to generate an initial graph, and the second one is to apply a vertex-minimization algorithm to identify classes of equivalent vertices. Applying the new concept of constraint set this work presents a new splitting algorithm to determine the vertices of the minimal presentation without determining an initial graph. Thus the transition function that connects the vertices is calculated over a smaller set, reducing the computation efforts for constructing this graph.
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and early maladaptive schemas: A single case study

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex illness, one that is devastating and life changing for many people. Early maladaptive schemas (EMS), as described by Young et al., (2003), have been observed in some patients with ME/CFS; seemingly adversely impacting on psychological and physical wellbeing. This study explores the experience of working at schema level with a woman with ME/CFS and endorsed EMS. It provides an overview of the therapeutic treatment, with the aim of adding to the limited research in this area.The instrumental single case study takes place within a clinical context. The client received 20 sessions of therapy. Standard cognitive behavioural therapy (CBT) was initially utilised to work with the client’s depression; once reduced, schema work commenced. Beck’s Depression Inventory (BDI-II) was used to measure mood, and Young’s Schema Questionnaire (YSQ-S3) was employed to measure schemas.By the end of therapy only two schemas from the nine schemas that the client had endorsed at the start of therapy remained at a level of ‘therapeutic significance’; three schemas diminished once the depression had been treated. The client reported that her quality of life had improved and that she had taken up part-time paid employment.The results appear to offer some support for working at schema level with people that have ME/CFS and also endorse EMS. However, treating existing depression first is recommended.
Accessing Replicated Data in a Large-Scale Distributed System

Replicating a data object improves the availability of the data, and can improve access latency by locating copies of the object near to their use. When accessing replicated objects across an internetwork, the time to access different replicas is non-uniform. Further, the probability that a particular replica is inaccessible is much higher in an internetwork than in a local-area network (LAN) because of partitions and the many intermediate hosts and networks that can fail. We report three replica-accessing algorithms which can be tuned to minimize either access latency or the number of messages sent. These algorithms assume only an unreliable datagram mechanism for communicating with replicas. Our work extends previous investigations into the performance of replication algorithms by assuming unreliable communication. We have investigated the performance of these algorithms by measuring the communication behavior of the Internet, and by building discrete-event simulations based on our measurements. We find that almost all message failues are either transient or due to long-term host failure, so that retrying messages a few times adds only a small amount to the overall message traffic while improving both access latency as long as the probability of message failure is small. Moreover, the algorithms which retry messages on failure provide significantly improved availability over those which do not.
Computer-aided definition, manipulation and depiction of objects composed of spheres

As previously demonstrated by Badler and O'Rourke, a variety of 3-D objects can be defined conveniently as collections of spheres-having various sizes and positions in 3-D space and possibly intersecting. This paper is an elaboration on the technique, describing methods of constructing and manipulating such objects and, most particularly, a method of achieving realism in rendering the picture-even though, for reasons of efficiency, computation is performed as if everything were 2-dimensional, with depth ordering.Pictorial realism results from three features of the overall method: roundedness of the basic picture plane images of individual spheres, pictorial merging of 3-dimensionally intersecting spheres (which are very likely intended as parts of the same object), and pictorial separation of spheres whose images overlap but which lie at significantly different depths in 3-space. Separation is achieved by a black line and resembles the lines traditionally found in cartoon cel animation; merging is accomplished by arranging, in effect, for every sphere image to be transparent to the brighter parts of images of other spheres of the same color.The system lends itself well to construction and manipulation of objects defined by geometry and mathematical transformations; it also serves well in construction and depiction of organic forms which arise and/or are modified by random growth and rules of contingency. Several examples of pictorial results are presented.