Free ortho clinical diagnostics software for linux

Bandwidth Meter and Diagnostics is a Firefox extension that will automatically check whether Internet connection is working or not when a website can not be loaded, and a list of tools for network troubleshooting. Try to type a random domain name(e.g., qwqwqwq121212.com) to see what this means ...
This extension adds "Bandwidth Meter" to the Tools Menu. It performs the following tasks:
- Display your public IP address
- Display your public domain name
- Test download speed/bandwidth
- Test upload speed/bandwidth
This extension runs under any OS. If you use Windows, you could try our other Windows specific extension "Broadband Speed test and Diagnostics" that has extra features and can only run under Windows. We are creating this because we get many requests from non-windows users.

Veterans Health Information Systems and Technology Architecture is a healthcare information system (HIS). VistA is widely believed to be the largest integrated HIS in the world. WorldVistA project was originally developed and maintained by the U.S.
Department of Veterans Affairs (VA), based on the systems software architecture and implementation methodology developed by the U.S. Public Health Service jointly with the National Bureau of Standards.
It is designed to provide a high-quality medical care environment for the countrys military veterans. VistA has a proven track record of supporting a large variety of clinical settings and medical delivery systems.
Enhancements:
- This is the FOIAVistA SemiVivA 20060113 package with GT.M bundled.

• A Firewall with stateful packet inspection and application proxies guards Internet communications traffic in and out of the organization.
• A Virtual Private Network (VPN) gateway assures secure communications with remote offices, road warriors and telecommuters.
• Anti-Virus defends computers from both email and web-bourne viruses.
• Intrusion Protection detects and stops hostile probes and application-based attacks.
• Spam Filtering eliminates the productivity drain of opening and deleting unsolicited emails.
• Surf Protection (Content Filtering) and Spyware Protection improve productivity by blocking inappropriate web activities, provide full protection from user tracking threats and violation of privacy.

Major Features:

1. Protects all types of networks Windows, Linux, Unix and others.
2. Delivers comprehensive features at low cost maximizing your ROI (return on investment).
3. Highly effective. Has won numerous industry awards. Beat Cisco and Checkpoint in InfoWorld magazine product review, Beat IBM and Computer Associates in Linux World for Best Security Application.
4. Integrated management platform features an intuitive browser-based interface and one-step updates for rapid deployment and easy management.
5. Can be installed in under 15 minutes or purchased pre-installed on security appliances.
6. Can start with firewall, VPN and spam protection and add other security applications as needed, seamlessly.
7. Runs as a dedicated application server on top of a hardened operating system, which relieves operating system management headaches.
8. Runs on systems ranging from small devices up to large multi-processor systems utilizing gigabytes of memory.
9. Redundant systems can be configured to provide high availability and automatic failover in case of hardware or network failures.
10. Load balancing improves performance traffic shaping can set priorities by network, service and protocol.
11. Logging, automatic backup, and diagnostic tools support high reliability.
12. Free online evaluation workshop to get you started.

Enhancements:

• This Up2Date addresses a few issues that did not make the 7.4 GA version in time.
• This is a pure bugfix/stability release that strengthens the quality of your installation.

Gtk2::Ex::MindMapView::ArgUtils is a Perl module with argument handling utilites.

SYNOPSIS

use Gtk2::Ex::MindMapView::ArgUtils;

This is an internal set of argument handling utilities.

INTERFACE

args_required ($attributes_ref, @valid_keys)

Complains if a required argument to a module is missing.

args_store ($self, $attributes_ref)

Copies arguments from attributes hash to hash referenced by $self.

args_valid ($attributes_ref, @valid_keys)

Complains of an invalid or unexpected argument is given.

arg_default ($self, $key, $default)

Assigns a default value if one is needed.

DIAGNOSTICS

Missing required argument

The caller omitted an important required argument.

Invalid argument

An invalid or unexpected argument was found.

WWW::Facebook::API::REST::Client::Wall is a Perl module with Wall methods for Client.

SYNOPSIS

use WWW::Facebook::API::REST::Client;

Methods for accessing wall with WWW::Facebook::API::REST::Client

SUBROUTINES/METHODS

base

The WWW::Facebook::API::REST::Client::Base object to use to make calls to the REST server

get_count

The wall.getCount method of the Facebook API

DIAGNOSTICS

This module is used by WWW::Facebook::API::REST::Client and right now does not have any unique error messages.

CONFIGURATION AND ENVIRONMENT

WWW::Facebook::API::REST::Client::Wall requires no configuration files or environment variables.

JavaPK for Desktop (JPKD) is a Clinical Pharmacokinetic (CPK) Services (or Therapeutic Drug Monitoring, TDM).
It not only inherits all functionalities of JavaPK for Mobile Devices, but also has a built- in algorithm of users defined Bayesian model for individualized pharmacokinetic parameter estimation (UDBM) for batch input data.
Users can define their own pharmacokinetic prediction models with population PK parameters and then use the defined model to solve batch prediction data or applied the defined model to therapeutic drug monitoring (TDM).
JPKD is created for your own personal uses and testing purposes. JPKD shall be used as a guide or a decision support tool only. Medical decisions should NOT be solely based on the results of this program. Although this program has been tested thoroughly, the accuracy of the information cannot be guaranteed. Once you use JPKD, you have automatically agreed with this disclaimer.
Main features:
- Sawchuk-Zaske (aminoglycosides & vancomycin) and Bayesian method for PK parameter estimation
- 15 built-in drugs for TDM (see the below drug lists)
- functions for users defined Bayesian estimation drug models
- portable function for users defined models
- a built-in spread sheet for batch PK parameter estimation & input data manipulation
- application user-defined Bayesian model to TDM
- multiple desktop platforms (WinXP/NT, Mac OS X, Linux PC) supported
Built-in drug lists
- Amikacin
- Carbamazepine
- Cyclosporin
- Digoxin
- Enfuvirtide
- Everolimus
- Gentamicin
- Indinavir
- Lithium
- Phenytoin
- Ritonavir
- Tacrolimus
- Theophylline
- Tobramycin
- Vancomycin

PDL::LinearAlgebra Perl module contains linear algebra utils for PDL.

SYNOPSIS

use PDL::LinearAlgebra;

$a = random (100,100);
($U, $s, $V) = mdsvd($a);

This module provides a convenient interface to PDL::LinearAlgebra::Real and PDL::LinearAlgebra::Complex.

FUNCTIONS

setlaerror

Set action type when error is encountered, returns previous type. Available values are NO, WARN and BARF (predefined constants). If, for example, in computation of the inverse, singularity is detected, the routine can silently return values from computation (see manuals), warn about singularity or barf. BARF is the default value.

$a = sequence(5,5);
$err = setlaerror(NO);
($inv, $info)= minv($a);
if ($info){
# Change the diagonal (the inverse doesnt exist but its an example)
$a->diagonal(0,1)+=1e-8;
($inv, $info)= minv($a);
}
if ($info){
print "Cant compute the inversen";
}
else{
print "Inverse of $a is $inv";
}
setlaerror($err);

getlaerror

Get error type.

0 => NO,
1 => WARN,
2 => BARF
t
PDL = t(PDL, SCALAR(conj))
conj : Conjugate Transpose = 1 | Transpose = 0, default = 1;

Convenient function for transposing real or complex 2D array(s). For PDL::Complex, if conj is true returns conjugate transpose array(s) and doesnt support dataflow. Supports threading.

issym

PDL = issym(PDL, SCALAR|PDL(tol),SCALAR(hermitian))
tol : tolerance value, default: 1e-8 for double else 1e-5
hermitian : Hermitian = 1 | Symmetric = 0, default = 1;

Check symmetricity/Hermitianicity of matrix. Supports threading.

diag

Return i-th diagonal if matrix in entry or matrix with i-th diagonal with entry. I-th diagonal returned flows data back&forth. Can be used as lvalue subs if your perl supports it. Supports threading.

PDL = diag(PDL, SCALAR(i), SCALAR(vector)))
i : i-th diagonal, default = 0
vector : create diagonal matrices by threading over row vectors, default = 0
my $a = random(5,5);
my $diag = diag($a,2);
# If your perl support lvaluable subroutines.
$a->diag(-2) .= pdl(1,2,3);
# Construct a (5,5,5) PDL (5 matrices) with
# diagonals from row vectors of $a
$a->diag(0,1)

tritosym

Return symmetric or Hermitian matrix from lower or upper triangular matrix. Supports inplace and threading. Uses tricpy or ctricpy from Lapack.

PDL = tritosym(PDL, SCALAR(uplo), SCALAR(conj))
uplo : UPPER = 0 | LOWER = 1, default = 0
conj : Hermitian = 1 | Symmetric = 0, default = 1;
# Assume $a is symmetric triangular
my $a = random(10,10);
my $b = tritosym($a);

positivise

Return entry pdl with changed sign by row so that average of positive sign > 0. In other words thread among dimension 1 and row = -row if Sum(sign(row)) < 0. Works inplace.

my $a = random(10,10);
$a -= 0.5;
$a->xchg(0,1)->inplace->positivise;

mcrossprod

Compute the cross-product of two matrix: A x B. If only one matrix is given, take B to be the same as A. Supports threading. Uses crossprod or ccrossprod.

PDL = mcrossprod(PDL(A), (PDL(B))
my $a = random(10,10);
my $crossproduct = mcrossprod($a);

mrank

Compute the rank of a matrix, using a singular value decomposition. from Lapack.

SCALAR = mrank(PDL, SCALAR(TOL))
TOL: tolerance value, default : mnorm(dims(PDL),inf) * mnorm(PDL) * EPS
my $a = random(10,10);
my $b = mrank($a, 1e-5);

mnorm

Compute norm of real or complex matrix Supports threading.
PDL(norm) = mnorm(PDL, SCALAR(ord));

ord :
0|inf : Infinity norm
1|one : One norm
2|two : norm 2 (default)
3|fro : frobenius norm
my $a = random(10,10);
my $norm = mnrom($a);

mdet

Compute determinant of a general square matrix using LU factorization. Supports threading. Uses getrf or cgetrf from Lapack.

PDL(determinant) = mdet(PDL);
my $a = random(10,10);
my $det = mdet($a);

mposdet

Compute determinant of a symmetric or Hermitian positive definite square matrix using Cholesky factorization. Supports threading. Uses potrf or cpotrf from Lapack.

(PDL, PDL) = mposdet(PDL, SCALAR)
SCALAR : UPPER = 0 | LOWER = 1, default = 0
my $a = random(10,10);
my $det = mposdet($a);

mcond

Compute the condition number (two-norm) of a general matrix.
The condition number (two-norm) is defined:

norm (a) * norm (inv (a)).

Uses a singular value decomposition. Supports threading.

PDL = mcond(PDL)
my $a = random(10,10);
my $cond = mcond($a);

mrcond

Estimate the reciprocal condition number of a general square matrix using LU factorization in either the 1-norm or the infinity-norm.
The reciprocal condition number is defined:

1/(norm (a) * norm (inv (a)))

Supports threading.

PDL = mrcond(PDL, SCALAR(ord))
ord :
0 : Infinity norm (default)
1 : One norm
my $a = random(10,10);
my $rcond = mrcond($a,1);

morth

Return an orthonormal basis of the range space of matrix A.

PDL = morth(PDL(A), SCALAR(tol))
tol : tolerance for determining rank, default: 1e-8 for double else 1e-5
my $a = random(10,10);
my $ortho = morth($a, 1e-8);

mnull

Return an orthonormal basis of the null space of matrix A.

PDL = mnull(PDL(A), SCALAR(tol))
tol : tolerance for determining rank, default: 1e-8 for double else 1e-5
my $a = random(10,10);
my $null = mnull($a, 1e-8);

minv

Compute inverse of a general square matrix using LU factorization. Supports inplace and threading. Uses getrf and getri or cgetrf and cgetri from Lapack and return inverse, info in array context.

PDL(inv) = minv(PDL)
my $a = random(10,10);
my $inv = minv($a);

mtriinv

Compute inverse of a triangular matrix. Supports inplace and threading. Uses trtri or ctrtri from Lapack. Returns inverse, info in array context.

(PDL, PDL(info))) = mtriinv(PDL, SCALAR(uplo), SCALAR|PDL(diag))
uplo : UPPER = 0 | LOWER = 1, default = 0
diag : UNITARY DIAGONAL = 1, default = 0
# Assume $a is upper triangular
my $a = random(10,10);
my $inv = mtriinv($a);