Abstract: A stroller (201) is provided which includes a chassis (203, 205) having first (211) and second (213) opposing frame elements. The chassis is supported on a plurality of wheels (223, 224, 225, 226). A seat (231) is suspended from the chassis by way of a support element (241). The seat includes upper (233) and lower (235) portions and is adapted to accommodate a child such that the back of the child rests against the upper portion and such that the legs of the child rest against the lower portion. The support element has first and second ends which are rotatably attached to first (243) and second (245) pivots mounted, respectively, on the first and second frame elements. The first pivot rotates about a first axis, and the seat is disposed between the first axis and the plurality of wheels. A first motor (271) is provided which rotates the first pivot.

Abstract: Disclosed herein are systems, methods, and devices for implementing a referral processing engine. Methods may include identifying a candidate based on a plurality of search parameters, and identifying an employee based on social connection data identifying at least one social connection between the candidate and the employee. The methods may also include generating a first message configured to be sent to the employee, where the first message includes one or more data values characterizing features of the candidate and a job opportunity. The methods may also include receiving a first response from the employee, where the first response characterizes a referral decision of the employee. The methods may also include updating, based on the first response, at least one candidate profile data object stored in a data storage system.

Abstract: Systems, methods, and devices are disclosed herein for implementing a referral processor. Systems include a profile data aggregator configured to aggregate data from at least one data source and generate candidate profile data based, at least in part, on the aggregated data. Systems include a connectivity metric generator configured to identify at least one connection between at least one candidate and at least one employee based on the candidate profile data. The connectivity metric generator may be configured to generate at least one connectivity metric based on the identified at least one connection. Systems include a referral processing engine configured to return the at least one candidate and the at least one employee as a result. The referral processing engine may be further configured to generate messages based on the at least one connectivity metrics. The messages may be configured to automate a referral of the at least one candidate.

Abstract: Disclosed herein are systems, methods, and devices for generating connectivity metrics associated with a referral processor. Methods may include identifying a first plurality of candidates based on a plurality of search parameters, and identifying a plurality of social connections associated with the first plurality of candidates and a first plurality of employees. Methods may also include generating at least one connectivity metric associated with the first plurality of candidates based on the plurality of social connections, where the at least one connectivity metric characterizes a strength of at least one social connection between a candidate of the first plurality of candidates and an employee of the first plurality of employees. The methods may also include receiving a selection of at least one candidate and at least one employee, the selection being based, at least in part, on the at least one connectivity metric.

Abstract: Systems, methods, and devices are disclosed herein for implementing a referral search. Methods may include retrieving candidate profile data and social connection data from at least one data source, where the candidate profile data characterizes one or more features associated with a plurality of candidates, and where the social connection data characterizes social connections between the plurality of candidates and a plurality of other entities. The methods may also include generating a first plurality of candidate profile data objects based on the retrieved candidate profile data and social connection data, where each of the first plurality of candidate profile data objects is associated with at least one candidate. The methods may further include generating an index data object based on the first plurality of candidate profile data objects.

Abstract: A stroller (201) is provided which includes a chassis (203, 205) having first (211) and second (213) opposing frame elements. The chassis is supported on a plurality of wheels (223, 224, 225, 226). A seat (231) is suspended from the chassis by way of a support element (241). The seat includes upper (233) and lower (235) portions and is adapted to accommodate a child such that the back of the child rests against the upper portion and such that the legs of the child rest against the lower portion. The support element has first and second ends which are rotatably attached to first (243) and second (245) pivots mounted, respectively, on the first and second frame elements. The first pivot rotates about a first axis, and the seat is disposed between the first axis and the plurality of wheels. A first motor (271) is provided which rotates the first pivot.

Abstract: A stroller is provided which includes a chassis having first and second opposing frame elements; a seat suspended from said chassis by way of first and second support elements, wherein said seat includes upper and lower portions and is adapted to accommodate a child such that the back of the child rests against the upper portion and such that the legs of the child rest against the lower portion, wherein said first and second support elements are rotatably attached to said first and second frame elements, and wherein said first support element extends under said lower portion of said seat; and a motor which rotates said first support element.

Abstract: A method of presenting account payoff information to customers includes receiving electronic data relating to a plurality of customers and evaluating the data to determine a class to which each customer belongs. The method also includes preparing an account statement for each customer in a first class and for each customer in a second class. The account statement for each customer in the first class includes a standard message, and the account statement for each customer in the second class includes a detailed message. The method also includes transmitting an electronic file comprising the account statements for the plurality of customers to a statement generator. The standard message comprises a total time to pay off at least one hypothetical account balance at a hypothetical interest rate based on a first series of minimum payments. The detailed message comprises a total time to pay off an account balance of the customer at an interest rate of the customer based on a second series of minimum payments.

Abstract: A method of presenting account payoff information to customers includes receiving electronic data relating to a plurality of customers and evaluating the data to determine a class to which each customer belongs. The method also includes preparing an account statement for each customer in a first class and for each customer in a second class. The account statement for each customer in the first class includes a standard message, and the account statement for each customer in the second class includes a detailed message. The method also includes transmitting an electronic file comprising the account statements for the plurality of customers to a statement generator. The standard message comprises a total time to pay off at least one hypothetical account balance at a hypothetical interest rate based on a first series of minimum payments. The detailed message comprises a total time to pay off an account balance of the customer at an interest rate of the customer based on a second series of minimum payments.