QM for Windows provides mathematical analysis for Operations Management, Quantitative methods, or Management Science. It features calculation methods for PERT/CPM, Linear Programming, Decision Analysis, Transportation problem, Statistical functions, Game Theory, Goal Programming, etc.
This program can be helpful for students, who are following Management Science texts such as Introduction to Management Science by Taylor, Quantitative Analysis for Management by Render, as well as the the Operations Management textbooks.
We are pleased to include here brief descriptions of applications, development tools and interfaces available from ourselves and partner companies. Some of these are available free of charge, others are chargeable packages. Zumasys cannot guarantee the accuracy of the description text and does not specifically endorse any product.
QM (QP Modeler) is a freeware graphical modeling tool for designing andimplementing real-time embedded software based on the UML state machinesand the lightweight QP Real-Time Embedded Frameworks (RTEFs).QM is available for Windows 32/64-bit, Linux 64-bit, and MacOS.
The most recommended way of obtaining QM is by downloading theQP-bundle, which includesQM and also all QP frameworksand the QTools collection.The main advantage of obtaining QM bundled together like that is that youget all components, tools and examples ready to go.
NOTE: QP-bundle is themost recommended way of downloading and installing QM. However,if you are allergic to installers and GUIs or don't have administratorprivileges you can also download and install QM separatelyas described below.
NOTE: It is generally not recommended to install QM in such standardlocations as \"Program Files\" or \"Program Files (x86)\", because thesedirectories have access limitations and don't allow you to modify theQM Style Sheet (qm.qss) or the model templates.
If you wish, after the installation, you could create a desktop shortcutfor QM and you can also associate QM model files (*.qm and *.qmp)with the QM application (using the standard Windows Explorer and\"Open With\" popup menu).
After unzipping the archive, go to the qm/bin/ directory and make surethat the qm executable and the qm.sh shell script have executablepermissions. You can either do this with your desktop's file manageror at the command line, type:
Go to the QM releases anddownload the disk image for MacOS (qm_-macx64.dmg). Double clickon .dmg file. This will mount and open the disk image. To install theQM tool, you simply drag the qm.app image into the Applications folder(typically visible in the Dock). If you wish, you might also create thealias of the qm.app and place it on your Desktop.
The QM example models are included in the QP baseline distributions. Theconsole-type examples are available for Windows (MinGW and Visual C++),Linux, and macOS. GUI-based simulations are available for Windows with theraw Win32 API. Cross-platform GUI examples based on the Qt framework areavailable in QP/C++.
The QM graphical modeling tool is freeware. It is free to download andfree use, but is not open source. During the installation you will needto accept a basic End-User License Agreement (see -machine.com/qm/license.html ), which legally protectsQuantum Leaps from any warranty claims, prohibits removing any copyrightnotices from QM, selling it, and creating similar competitive products.The EULA also prohibits distributing QM from third-party websites. Theonly legitimate source of QM is the SourceForge.net/projects/qpc/ website.
NOTE: QM uses internally the Qt application toolkit under LGPLPlease refer to the LGPL Compliance Package for QM in the sub-directoryqt_lgpl or online at -machine.com/qm/qt_lgpl.html formore information how to obtain the source code for the Qt toolkit.
The code generated by QM is licensed under the same terms as theunderlying QP framework, for which the code has been generated. Pleaserefer to the QP licensing ( -machine.com/licensing/ )for more information.
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(B) Cartoon schematic showing head-fixed awake mouse with recording electrodes in red (L2/3) and blue (L5), with forepaw digit movement (green) monitored by the sensing arm (gray) that was also used for tactile stimulation.
(C) Biocytin reconstructions of L2/3 (red) and L5 (blue) neurons, with axons in lighter color, next to a histogram showing the depths of all recorded L2/3 and L5 neurons (n = 17 L2/3 neurons and n = 28 L5 neurons) based on micromanipulator reading and biocytin staining.
(A) Example whole-cell recordings from a L2/3 neuron (red) and L5 neuron (blue) with the digit movement (green) measured by the stimulator/sensing arm in contact with the glabrous skin of forepaw digit 3.
(H) The mean firing rate (Q and M periods) of L2/3 and L5 neurons plotted as a function of the distance between AP threshold and the mean value of the maximum 10% of the Vm (Max Vm). Filled circles show the mean value for one cell.
(I) Population Vm average of L2/3 (red) and L5 neurons (blue) centered on APs in L2/3 neurons during quiet (left, n = 8 pairs) and moving (right, n = 4 pairs) periods. Bottom, corresponding population L5 spike-time PSTHs.
(B) Plots of selected SDEs from seven dual whole-cell recordings. SDEs were aligned at threshold crossing at the onset (left) and offset (right) of the SDE in the L2/3 neuron and arranged by duration. Top boxes show L2/3 data, and bottom boxes show L5 with colors corresponding to the normalized Vm from minimum (blue) to maximum (red) values.
(C) Population distribution (top) and trial-by-trial measurements (bottom) of the subthreshold onset (left) and offset (right) times in L5 neurons relative to the onset and offset times in L2/3, respectively (n = 7 dual recordings). Onset and offset times were estimated by the 5% level of a sigmoidal fit to the Vm at onset and offset (see Supplemental Experimental Procedures for details).
(F) Population analysis of onset and offset times relative to the L2/3 SDE shows a significantly earlier onset in L5 but similar offset times. To calculate the onset/offset timing difference, we first measured the time of SDE onset/offset relative to the time of threshold crossing of the L2/3 SDE. Then, we subtracted the population mean L2/3 onset/offset time from all values. Filled circles with error bars show mean SEM, and lines show data from individual pairs.
(A) Population Vm average responses of L2/3 (red) and L5 (blue) neurons to onset of spontaneous digit movement (green shows the rectified first derivative of the digit movement (digitFD); n = 11 L2/3 cells and n = 19 L5 cells, from single and dual recording experiments). Movement onsets (dashed vertical line) were detected via thresholding of digitFD (see Experimental Procedures).
(B) Peak cross-correlation between the digitFD and the Vm shows no significant time lag between layers, indicating synchronous depolarization. Filled circles with error bars show mean SEM, and open circles show individual cells.
(E) L2/3 and L5 neurons show a decrease in tactile-evoked subthreshold response amplitude as mice go from quiet (Q) to movement (M). Filled circles with error bars show mean SEM. Lines show individual cells.
(F) Population analysis of background-subtracted AP firing rates to tactile stimulation of the forepaw shows no difference between Q (left) and M (right) periods in both layers. AP rate measured as the difference between the 100 ms before and 100 ms after stimulus onset.
(H) Absolute AP rate in the 100 ms after stimulus onset plotted as a function of the difference in Vm between AP threshold and the tactile stimulus-evoked response reversal potential. Filled circles show mean value of individual cells.
(J) Amplitude of L2/3 subthreshold tactile-evoked responses plotted against the amplitude of L5 subthreshold responses from the example pair in (A) shows highly correlated response amplitudes during Q (black) and M (orange) periods.
(K) Population data of cross-correlation of mean subthreshold tactile-evoked responses (combining Q and M responses) between L2/3 and L5 neurons. Filled circles with error bars show mean SEM, and open circles show individual cells.
(A) Mean Vm tactile-evoked responses with corresponding digit movement (green) and PSTHs from an L2/3 (red, top) and an L5 (blue, bottom) neuron in resting, quiet mice that showed no behavioral response (left, quiet-quiet [QQ]) or a short-latency digit movement following the stimulus (right, quiet-movement [QM]).
(D) The amplitude of the Vm response to tactile stimulation is significantly larger for QM trials than in QQ trials in both L2/3 and L5 neurons. Filled circles with error bars show mean SEM. Lines show individual cells.
We thank Janett König for technical help, Sven Blankenburg for help with coherence analysis, and Evgeny Bobrov, Jean-Sebastién Jouhanneau, and Birgit Voigt for comments on an earlier version of the manuscript. This work was funded by a European Research Council starting grant (ERC-2010-StG-260590, to J.F.A.P.), the Deutsche Forschungsgemeinschaft (DFG; Exc 257 NeuroCure, DFG-FOR-1341-BaCoFun and DFG-FOR-2143-Interneuron, to J.F.A.P.), the Fritz Thyssen Foundation, the European Union (3x3Dimaging 323945), and the Helmholtz Association. J.K. is funded by the Humboldt-Universität zu Berlin in the framework of the Excellence Initiative of the BMBF and DFG. 153554b96e