Abstract: The present disclosure relates generally to building surface products, for example, panels suitable for forming a building surface. The present disclosure relates more particularly to a building surface product including a gypsum panel with an upper edge that overlaps a lower edge of a neighboring gypsum panel.

Abstract: Methods and systems are disclosed wherein temperature in a device such as an ambulatory infusion pump is monitored during inductive charging of the device such that temperature-sensitive contents or components, such as, for example, insulin, particular circuitry and/or other components are not damaged. Temperature can be monitored in the device at one or more locations during inductive charging. If the temperature breaches one or more predetermined thresholds and/or is rising at a rate greater than one or more predetermined thresholds, charging can be suspended or provided at reduced power to prevent the temperature from further rising and damaging the contents and/or components of the device. One or more alerts associated with these events may also be triggered so that the user is aware of the situation and may take corrective action.

Abstract: A remote camera control for a cell phone camera is extendably attached to a cell phone case to retract into and be held in the cell phone case when not in use and to be extended from the cell phone case when in use to also serve as a handle for holding the cell phone case and cell phone therein a distance away from the user for taking “selfies” or other pictures.

Abstract: Embodiments model a series of partial trades on an investment portfolio to reduce the optimality discrepancy relative to a target optimal portfolio, and determine whether a partially rebalanced portfolio along the trading path is within a predefined threshold of statistical optimality relative to the target optimal portfolio. Certain embodiments maximize the impact of partial rebalancing of a portfolio by maximizing reduction of an optimality discrepancy while minimizing the trade cost function along the trading path from the initial portfolio toward the target optimal portfolio.

Abstract: Computer-implemented methods for constructing a risk-return optimal allocation to a set of assets, where a subset of the assets is at least partially insured or modified by the addition of derivative securities. The methods entail resampling a plurality of sets of returns consistent with a return distribution for each asset, with at least one asset modified by a derivative overlay, subject to terms of at least one contract requirement. A statistical mean of associated optimal portfolios is established, generating a resampled efficient frontier, on the basis of which a portfolio weight is selected for each asset according to a specified risk objective.

Abstract: Michaud rebalance probabilities are renormalized in the case of successive datasets, historical or simulated, where partial commonality of information is imputed to the two datasets. Two separate sets of optimization inputs correspond to a stochastic process and optimization subject to a set of constraints making the optimization analytically intractable. A subset of data drawn on the basis the first optimization input is recursively replaced with data sampled from the second optimization input, the extent of replacement governed by the extent of common information. A set of rebalance probabilities is calculated, and the Lth percentile is selected from the set of rebalance probabilities, where L is a specified confidence level. An adjusted critical value serves as a need-to-execute trigger for a single portfolio or a class of portfolios.

Abstract: A computer-implemented method and computer program product for selecting a portfolio weight (subject to specified constraints) for each of a plurality of assets of an optimal portfolio. A mean-variance efficient frontier is calculated based on expected return and standard deviation of return of each of the plurality of assets. Multiple sets of optimization inputs are drawn from a distribution of simulated optimization inputs consistent with the expected return and standard deviation of return of each of the assets and a specified level of forecast certainty, and then a simulated mean-variance efficient frontier is computed for each set of optimization inputs. A meta-resampled efficient frontier is determined as a statistical mean of associated portfolios, and a portfolio weight is selected for each asset according to a specified investment objective.

Abstract: A computer-implemented method and computer program product for selecting a portfolio weight (subject to specified constraints) for each of a plurality of assets of an optimal portfolio. A mean-variance efficient frontier is calculated based on input data characterizing the defined expected return and the defined standard deviation of return of each of the plurality of assets. Multiple sets of optimization inputs are drawn from a distribution of simulated optimization inputs consistent with the defined expected return, the defined standard deviation of return of each of the plurality of assets and then a simulated mean-variance efficient frontier is computed for each set of optimization inputs. A meta-resampled efficient frontier is determined as a statistical mean of associated portfolios among the simulated mean-variance efficient frontiers, and a portfolio weight is selected for each asset from the meta-resampled efficient frontier according to a specified investment objective.

Abstract: A computer-implemented method and computer program product for selecting a portfolio weight (subject to specified constraints) for each of a plurality of assets of an optimal portfolio. A mean-variance efficient frontier is calculated based on input data characterizing the defined expected return and the defined standard deviation of return of each of the plurality of assets. Multiple sets of optimization inputs are drawn from a distribution of simulated optimization inputs consistent with the defined expected return, the defined standard deviation of return of each of the plurality of assets and then a simulated mean-variance efficient frontier is computed for each set of optimization inputs. A meta-resampled efficient frontier is determined as a statistical mean of associated portfolios among the simulated mean-variance efficient frontiers, and a portfolio weight is selected for each asset from the meta-resampled efficient frontier according to a specified investment objective.

Abstract: A meteorological display system comprising at least one sensor mounted exteriorly of a building to sense at least one meteorological condition, a transmitter associated with the sensor, the transmitter having a circuit to transmit a signal representing the value measured by the sensor, a first display unit mounted interiorly of the building, the display unit having a circuit for receiving the signal and displaying an indicia reflecting the at least one meteorological condition, a repeater transmitter associated with the first display for sending a repeater signal to a second display unit. In one embodiment, the display unit is designed to sense and display and interior temperature, the interior temperature being modified to account for thermal loss due to location of the display unit.

Abstract: A computer-implemented method and computer program product for selecting a portfolio weight (subject to specified constraints) for each of a plurality of assets of an optimal portfolio. A mean-variance efficient frontier is calculated based on input data characterizing the defined expected return and the defined standard deviation of return of each of the plurality of assets. Multiple sets of optimization inputs are drawn from a distribution of simulated optimization inputs consistent with the defined expected return, the defined standard deviation of return of each of the plurality of assets and then a simulated mean-variance efficient frontier is computed for each set of optimization inputs. A meta-resampled efficient frontier is determined as a statistical mean of associated portfolios among the simulated mean-variance efficient frontiers, and a portfolio weight is selected for each asset from the meta-resampled efficient frontier according to a specified investment objective.

Abstract: A method for evaluating statistical congruence of an existing or putative portfolio with a target portfolio, both the current portfolio and the target portfolio having a plurality of assets. A mean-variance efficient portfolio is computed for a plurality of simulations of input data statistically consistent with an expected return and expected standard deviation of return, and each such portfolio is associated, by means of an index, with a specified portfolio on the mean variance efficient frontier. The number of simulations and the number of simulations periods is specified on the basis of a specified information correlation value. A statistical mean of the index-associated mean-variance efficient portfolios is used for evaluating a portfolio, in accordance with a specified balancing test, for statistical consistency with a specified risk objective and, additionally, for defining investment-relevant allocation ranges of portfolio weights.

Abstract: A method for evaluating statistical congruence of an existing or putative portfolio with a target portfolio, both the current portfolio and the target portfolio having a plurality of assets. A mean-variance efficient portfolio is computed for a plurality of simulations of input data statistically consistent with an expected return and expected standard deviation of return, and each such portfolio is associated, by means of an index, with a specified portfolio on the mean variance efficient frontier. The number of simulations and the number of simulations periods is specified on the basis of a specified information correlation value. A statistical mean of the index-associated mean-variance efficient portfolios is used for evaluating a portfolio, in accordance with a specified balancing test, for statistical consistency with a specified risk objective and, additionally, for defining investment-relevant allocation ranges of portfolio weights.

Abstract: A tool for reshaping corner bead, which is perforated right angle metal strip used in fabrication of corners in drywall building construction, spreads the legs of 90 degree angle corner bead outwardly to increase the included angle thereof. The bead is rolled between a pressure roller and a multiplicity of idler rollers. The apex of the bead runs in a circumferential groove of the vertically adjustable pressure roller which presses downwardly as the legs ride upon idler rollers which resist the downward force while allowing sideward motion of the legs. Preferably, the rollers are comprised of mated pairs of hemispheres and the bead is made to pass through the tool by driving the pressure roller with a screw gun. The frame of the tool has a detachable tang which enables the tool to be mounted from the side wall pocket of a common pickup truck box.

Abstract: A method for evaluating an existing or putative portfolio having a plurality of assets. A mean-variance efficient portfolio is computed for a plurality of simulations of input data statistically consistent with an expected return and expected standard deviation of return, and each such portfolio is associated, by means of an index, with a specified portfolio on the mean variance efficient frontier. A statistical mean of the index-associated mean-variance efficient portfolios is used for evaluating a portfolio for consistency with a specified risk objective.