Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of prion protein in the cerebrospinal fluid of elk (Cervus canadensis nelsoni) with chronic wasting disease using protein misfolding cyclic amplification

Cerebrospinal fluid (CSF) has been examined as a possible source for preclinical diagnosis of prion diseases in hamsters and sheep. The present report describes the detection of chronic wasting disease (CWD) in the CSF of elk and evaluates its usefulness as an antemortem test for CWD. The CSF from 6 captive and 31 free-ranging adult elk was collected at necropsy and evaluated for the presence of the abnormal isoform of the prion protein that has been associated with CWD (PrPCWD) via protein misfolding cyclic amplification. Additionally, the obex from each animal was examined by immunohistochemistry (IHC). Four out of 6 captive animals were CWD-positive and euthanized due to signs of terminal CWD. The remaining 2 were CWD negative. None of the 31 free-range animals showed overt signs of CWD, but 12 out of 31 tested positive for CWD by IHC. Protein misfolding cyclic amplification detected PrPCWD from 3 of the 4 captive animals showing clinical signs of CWD and none of the nonclinical animals that were CWD positive by IHC. The data suggests that CWD prions can be detected in the CSF of elk, but only relatively late in the course of the disease.
Too Much Information? Information Provision and Search Costs

A seller often needs to determine the amount of product information to provide to consumers. We model costly consumer information search in the presence of limited information. We derive the consumer’s optimal stopping rule for the search process. We find that, in general, there is an intermediate amount of information that maximizes the likelihood of purchase. If too much information is provided, some of it is not as useful for the purchase decision, the average informativeness per search occasion is too low, and consumers end up choosing not to purchase the product. If too little information is provided, consumers may end up not having sufficient information to decide to purchase the product. The optimal amount of information increases with the consumer’s ex ante valuation of the product, because with greater ex ante valuation by the consumer, the firm wants to offer sufficient information for the consumer to be less likely to run out of information to check. One can also show that there is an intermediate amount of information that maximizes the consumer’s expected utility from the search problem (social welfare under some assumptions). Furthermore, this amount may be smaller than that which maximizes the probability of purchase; that is, the market outcome may lead to information overload with respect to the social welfare optimum. This paper can be seen as providing conditions under which too much information may hurt consumer decision making. Numerical analysis shows also that if consumers can choose to some extent which attributes to search through (but not perfectly), or if the firm can structure the information searched by consumers, the amount of information that maximizes the probability of purchase increases, but is close to the amount of information that maximizes the probability of purchase when the consumer cannot costlessly choose which attributes to search through.
Chromospheric Activity, Rotation, and Rotational Braking in M and L Dwarfs

We present results from a high-resolution spectroscopic survey of 45 L dwarfs, which includes both very low mass stars and brown dwarfs. Our spectra allow us to derive a significant number of new rotational velocities, and discover a slowly rotating (in projected velocity) L dwarf that allows more accurate measurement of spectroscopic rotations for these objects. We measure chromospheric activity (and often its variability) through the Hα emission line. Our primary new result is good evidence that magnetic braking dominates the angular momentum evolution of even brown dwarfs, although spindown times appear to increase as mass decreases. We confirm that activity decreases as effective temperature decreases, although a larger fraction of L dwarfs are active than has previously been reported. Essentially all active objects are also variable. We confirm the lack of a rotation-activity connection for L dwarfs. We find a minimum limit for rotational velocities that increases with later spectral types, rising from near zero in older mid-M stars to more than 20 km s−1 for mid-L objects. There is strong evidence that all L dwarfs are rapid rotators. We derive a braking law that can depend on either temperature or mass which can explain all the rotational results and provides an age dependence for the angular momentum evolution. It is clear that angular momentum loss mechanisms in smaller and cooler objects become more inefficient, starting at the fully convective boundary.
Maximizing Progress: High-Level Construals Promote Sensitivity To Goal Progress Asymmetries

ii Acknowledgments. iii Vita . iv List of Figures . vii Chapter 1: Introduction . 1 Construal Level Theory . 1 What Makes a Goal Primary? 6 Mixed Motive Social Dilemmas . 8 Chapter 2: The Present Studies . 10 Study 1. 11 Method . 11 Results and Discussion . 13 Study 2. 16 Method . 16 Results and Discussion . 17
A tactile sensing and feedback system for tumor localization

Haptic information such as pressure (tactile) distribution could improve the clinical outcomes significantly by helping to detect tumors within soft-tissue organs and indicating potential abnormalities. In open surgeries, fingers are used to obtain this information. However, current surgical tele-manipulators do not provide explicit haptic feedback during soft tissue palpation. This paper describes a tactile sensing and feedback system, consisting of a colored tactile information display and pneumatic multi-fingered haptic feedback. This tissue stiffness feedback system is validated by palpating two phantom organs to locate tissue tumors. The results proved that the stiffness distribution is acquirable, visible, and palpable using our method.
Decentralized Eigenvalue Algorithms for Distributed Signal Detection in Wireless Networks

In this paper, we derive and analyze two algorithms - referred to as decentralized power method (DPM) and decentralized Lanczos algorithm (DLA) - for distributed computation of one (the largest) or multiple eigenvalues of a sample covariance matrix over a wireless network. The proposed algorithms, based on sequential average consensus steps for computations of matrix-vector products and inner vector products, are first shown to be equivalent to their centralized counterparts in the case of exact distributed consensus. Then, closed-form expressions of the error introduced by nonideal consensus are derived for both algorithms. The error of the DPM is shown to vanish asymptotically under given conditions on the sequence of consensus errors. Finally, we consider applications to spectrum sensing in cognitive radio networks, and we show that virtually all eigenvalue-based tests proposed in the literature can be implemented in a distributed setting using either the DPM or the DLA. Simulation results are presented that validate the effectiveness of the proposed algorithms in conditions of practical interest (large-scale networks, small number of samples, and limited number of iterations).
An Empirical Risk Management Framework for Monitoring Network Security

Inherent vulnerabilities in software applications running in a computer network, bringing in personal devices to the network on an ad-hoc basis, a growing trend of network users accessing Web and utilise Cloud services remotely, and increasingly mature and stealthy techniques used by cyber-criminals have left the whole network vulnerable to cyber-attacks. This requires a network administrator to better understand the dynamic threat landscape and its associated risks so that appropriate security controls and policies could be applied as a countermeasure against existing and new cyber-attacks. However, measuring the risk of cyber attacks and identifying the most recent modus-operandi of cyber criminals on large computer networks can be difficult due to the wide range of services and applications running within the network, the multiple vulnerabilities associated with each application, the severity associated with each vulnerability, and the ever-changing attack vector of cyber criminals. In this paper we propose a framework to represent these features, enabling real-time network enumeration and traffic analysis to be carried out, in order to produce quantified measures of risk at specific points in time. We validate the approach using real-network data from a University network and show how the data can be used to understand the attack patterns and their trends.
Broad-Band Design Techniques for Transimpedance Amplifiers

In this paper, a novel bandwidth enhancement technique based on the combination of capacitive degeneration, broad-band matching network, and the regulated cascode (RGC) input stage is proposed and analyzed, which turns the transimpedance amplifier (TIA) design into a fifth-order low-pass filter with Butterworth response. This broad-band design methodology for TIAs is presented with an example implemented in CHRT 0.18-mum 1.8-V RF CMOS technology. Measurement data shows a -3-dB bandwidth of about 8 GHz with 0.25-pF photodiode capacitance. Comparing with the core RGC TIA without capacitive degeneration and broad-band matching network, this design achieves an overall bandwidth enhancement ratio of 3.6 with very small gain ripple. The transimpedance gain is 53 dBOmega with a group delay of 80plusmn20 ps. The chip consumes only 13.5-mW dc power and the measured average input-referred noise current spectral density is 18 pA/radicHz up to 10 GHz
Weather Research and Forecast ( WRF ) Model Port to Windows : Preliminary Report

The Weather Research and Forecast (WRF) project is a multi-year/multi-institution collaboration to develop a next generation regional forecast model and data assimilation system for operational numerical weather prediction (NWP) and atmospheric research. Under this project – a collaboration between The National Center for Atmospheric Research (NCAR), Microsoft Corporation, Advanced Micro Devices, Inc., and The Portland Group, Inc (PGI) – a prototype version of WRF has been developed and demonstrated running in parallel using MPI on an AMD OpteronTM dual-core processor based server running Windows Compute Cluster Server 2003, Microsoft Compute Cluster Pack,. This preliminary report describes progress and issues encountered in porting WRF to an HPC cluster running Windows, using Microsoft Subsystem for UNIX-based Applications (SUA) and the PGI Fortran compiler.
Differences in the Ways Sympathetic Neurons and Endocrine Cells Process, Store, and Secrete Exogenous Neuropeptides and Peptide-Processing Enzymes

Most neurons store peptides in large dense core vesicles (LDCVs) and release the neuropeptides in a regulated manner. Although LDCVs have been studied in endocrine cells, less is known about these storage organelles in neurons. In this study we use the endogenous peptide NPY (neuropeptide Y) and the endogenous peptide-processing enzyme PAM (peptidylglycine α-amidating monooxygenase) as tools to study the peptidergic system in cultured neurons from the superior cervical ganglion (SCG). Once mature, SCG neurons devote as much of their biosynthetic capabilities to neurotransmitter production as endocrine cells devote to hormone production. Unlike pituitary and atrium, SCG neurons cleave almost all of the bifunctional PAM protein they produce into soluble monofunctional enzymes. Very little PAM or NPY is secreted under basal conditions, and the addition of secretagogue dramatically stimulates the secretion of PAM and NPY to a similar extent. Although endocrine cells typically package “foreign” secretory products together with endogenous products, pro-opiomelanocortin- and PAM-derived products encoded by adenovirus in large part were excluded from the LDCVs of SCG neurons. When expressed in corticotrope tumor cells and primary anterior pituitary cultures, the same virally encoded products were metabolized normally. The differences that were observed could reflect differences in the properties of neuronal and endocrine peptidergic systems or differences in the ability of neurons and endocrine cells to express viral transcripts.
EVALUATING CROATIAN EQUITIES

In this paper we evaluate all three of the first quotation equities that are available in Croatia. First quotation equities are those that meet the highest accounting and reporting standards in Croatia. We find that two of the three compare favorably with stocks available on the world market. We also suggest the need for more and better data on Croatian equities.
Physical and Physiological Characteristics of Judo Athletes: An Update

Judo competition is characterized structurally by weight category, which raises the importance of physiological control training in judo. The aim of the present review was to examine scientific papers on the physiological profile of the judokas, maintenance or loss of weight, framing issues, such as anthropometric parameters (body fat percentage), heart rate responses to training and combat, maximal oxygen uptake, hematological, biological and hormones indicators. The values shown in this review should be used as a reference for the evaluation of physical fitness and the effectiveness of training programs. Hence, this information is expected to contribute to the development of optimal training interventions aiming to achieve maximum athletic performance and to maintain the health of judokas.
Joint Attention in Toddler Vocabulary Acquisition

The present study examined the child-caregiver dyad play environment and its relationship to child language development. The primary aim was to determine if joint attention was related to vocabulary acquisition. Dyads consisting of 19 toddlers and a caregiver were observed in a laboratory during free play. The child-caregiver dyad interactions were coded for object being held, gaze, pointing, noun usage, eye contact, engagement, and joint attention. Child language progression was assessed throughout the 6-month long study using the MacArthur-Bates Communicative Development Inventory. Findings suggest a relationship between joint attention and rate of MCDI percentile increase, and a connection between caregiver and child noun usage.
Marine boundary layer cloud regimes and POC formation in a CRM coupled to a bulk aerosol scheme

Abstract. A cloud-resolving model (CRM) coupled to a new intermediate-complexity bulk aerosol scheme is used to study aerosol–boundary-layer–cloud–precipitation interactions and the development of pockets of open cells (POCs) in subtropical stratocumulus cloud layers. The aerosol scheme prognoses mass and number concentration of a single lognormal accumulation mode with surface and entrainment sources, evolving subject to processing of activated aerosol and scavenging of dry aerosol by clouds and rain. The CRM with the aerosol scheme is applied to a range of steadily forced cases idealized from a well-observed POC. The long-term system evolution is explored with extended two-dimensional (2-D) simulations of up to 20 days, mostly with diurnally averaged insolation and 24 km wide domains, and one 10 day three-dimensional (3-D) simulation. Both 2-D and 3-D simulations support the Baker–Charlson hypothesis of two distinct aerosol–cloud "regimes" (deep/high-aerosol/non-drizzling and shallow/low-aerosol/drizzling) that persist for days; transitions between these regimes, driven by either precipitation scavenging or aerosol entrainment from the free-troposphere (FT), occur on a timescale of ten hours. The system is analyzed using a two-dimensional phase plane with inversion height and boundary layer average aerosol concentrations as state variables; depending on the specified subsidence rate and availability of FT aerosol, these regimes are either stable equilibria or distinct legs of a slow limit cycle. The same steadily forced modeling framework is applied to the coupled development and evolution of a POC and the surrounding overcast boundary layer in a larger 192 km wide domain. An initial 50% aerosol reduction is applied to half of the model domain. This has little effect until the stratocumulus thickens enough to drizzle, at which time the low-aerosol portion transitions into open-cell convection, forming a POC. Reduced entrainment in the POC induces a negative feedback between the areal fraction covered by the POC and boundary layer depth changes. This stabilizes the system by controlling liquid water path and precipitation sinks of aerosol number in the overcast region, while also preventing boundary layer collapse within the POC, allowing the POC and overcast to coexist indefinitely in a quasi-steady equilibrium.
Reduced kidney transplant rejection rate and pharmacoeconomic advantage of mycophenolate mofetil.

BACKGROUND Several multinational controlled clinical trials have shown that triple therapy immunosuppressive regimens which include mycophenolate mofetil (MMF), cyclosporin A (CSA) and steroids (S) are superior compared with conventional regimens which include azathioprine (AZA), CSA and S, mainly because MMF reduces the rate of acute rejection episodes in the first 6 months after kidney transplantation. Post-marketing studies are useful to evaluate the general applicability and costs of MMF-based immunosuppressive regimens. METHODS Based on the excellent results of the published controlled clinical trials, we have changed the standard triple therapy immunosuppressive protocol (AZA+CSA+S) to an MMF-based regimen (MMF+CSA+S) at our centre. To analyse the impact of this change in regimen, we have monitored 6-month patient and graft survival, rejection rate, serum creatinine and CSA levels, as well as the costs of the immunosuppressive and anti-rejection treatments, in 40 consecutive renal transplant recipients (MMF group) and have compared the data with 40 consecutive patients transplanted immediately prior to the change in regimen (AZA group). RESULTS Recipient and donor characteristics were similar in the AZA and MMF groups. Patient survival (37/40; 92.5% in the AZA group vs 38/40; 95% in the MMF group), graft survival (36/40 vs 36/40; both 90%) and serum creatinine (137+/-56 vs 139+/-44 micromol/l) after 6 months were not significantly different. However, the rate of acute rejection episodes (defined as a rise in creatinine without other obvious cause and treated at least with pulse steroids) was significantly reduced with MMF from 60 to 20% (P=0.0005). The resulting cost for rejection treatment was lowered 8-fold (from sFr. 2113 to 259 averaged per patient) and the number of transplant biopsies was lowered > 3-fold in the MMF group. The cost for the immunosuppressive therapy was increased 1.5-fold with MMF (from sFr. 5906 to 9231 per patient for the first 6 months). CONCLUSIONS The change from AZA to MMF resulted in a significant reduction in early rejection episodes, resulting in fewer diagnostic procedures and rehospitalizations. The optimal long-term regimen in terms of patient and pharmacoeconomic benefits remains to be defined.
Communication Complexity Method for Measuring Nondeterminism in Finite Automata

While deterministic finite automata seem to be well understood, surprisingly many important problems concerning nondeterministic finite automata (nfa's) remain open. One such problem area is the study of different measures of nondeterminism in finite automata and the estimation of the sizes of minimal nondeterministic finite automata. In this paper the concept of communication complexity is applied in order to achieve progress in this problem area. The main results are as follows:(1) Deterministic communication complexity provides lower bounds on the size of nfa's with bounded unambiguity. Applying this fact, the proofs of several results about nfa's with limited ambiguity can be simplified and presented in a uniform way. (2) There is a family of languages KONk2 with an exponential size gap between nfa's with polynomial leaf number/ambiguity and nfa's with ambiguity k. This partially provides an answer to the open problem posed by B. Ravikumar and O. Ibarra (1989, SIAM J. Comput. 18, 1263-1282) and H. Leung (1998, SIAM J. Comput. 27, 1073-1082).
Animal Models of Dry Eye Disease- A Review

A number of patient suffering from dry eye disease is increasing daily, subsequently increase the need of proper medication to treat the symptoms and eventually improve the patient’s condition. Thus the need arise for proper animal and non-human primate animal model of the disease, which would serve the purpose of understanding disease in the better physiological setting and medication for treating dry eye disease. This review article focus on some animal models disease like monkey, rabbit, rat, mice, dog and mouse which are generally used for carrying out studies on dry eye symptoms in research lab and industry worldwide. This paper also gives guidance toward the mechanistic and traditional model of dry eye disease and help researchers in deciding a particular relevant model for their own purpose.
FSS-OBOP: Feature subset selection guided by a bucket order consensus ranking

Several authors have ton the importance of aggregating the results of different feature selection methods in order to improve the solutions obtained. To the best of our knowledge, the consensus rankings obtained in all of these proposals do not allow that some variables are tied. This paper studies the advantages of allowing ties in the consensus ranking obtained from aggregating several features selection methods. This implies that the consensus ranking is modeled as the problem of obtaining the Optimal Bucket Order instead of solving the Rank Aggregation Problem. In this paper we propose a filter-wrapper algorithm, that we will call FSS-OBOP, which uses a filter-based consensus ranking with ties to guide the posterior wrapper phase. By using a benchmark with 12 high-dimensional datasets, we show that allowing ties in the consensus rankings leads to subsets that, when used to induce a classifier, obtain at least the same, when not better, accuracy. Furthermore, and what is actually more significant, they reduce the number of wrapper evaluations extraordinarily.
Collaborative Differentially Private Outlier Detection for Categorical Data

Collaborative analytics is crucial to extract value from data collected by different organizations and stored in separate silos. However, privacy and legal concerns often inhibit the integration and joint analysis of data. One of the most important data analytics tasks is that of outlier detection, which aims to find abnormal entities that are significantly different from the remaining data. In this paper, we define privacy in the context of collaborative outlier detection and develop a novel method to find outliers from horizontally partitioned categorical data in a privacy-preserving manner. Our method is based on a scalable outlier detection technique that uses attribute value frequencies. We provide an end-to-end privacy guarantee by using the differential privacy model and secure multiparty computation techniques. Experiments on real data show that our proposed technique is both effective and efficient.