Using html5 to use four diferent images depending on browser window size. Suitable for all modern browsers.

I want to share a fantastic little tool that I've only recently come across; Live.js, written by Martin Kool. This JavaScript file automatically checks for changes to your CSS and JavaScript files, and refreshes them. That means you can have your text editor in one half of the screen, and a web browser in the other. When you save changes in the editor, the updates are reflected immediately in your browser. It really helps to speed up your development time.

A small increase in customer retention can mean huge gains for your online store. Automate post-purchase emails to improve customer loyalty (and profits)!

The post 7 Ways to Engage Customers with Post-Purchase Email Automation appeared first on WooCommerce.

Recent advances in technology have helped both small and large companies to automate their business process to improve productivity. In fact, experts have also emphasized that productivity has stalled over the last couple of years. Numerous large-scale businesses also complained that their productivity was in decline despite implementing innovative workplace guidelines to improve the workflow. […] More

We’re delighted to launch the first ever website for this local irrigation company that has been around since 1989! Automated...continue reading

Access management can be a bit of a nightmare, especially when we realize that we rely on a number of different, independent services that power our organizations. Many businesses use Gmail for email, Google Docs for documents, Slack for communication, GitHub for their codebase, etc. Yet each of these services provides their own permissions screens, […]

The post Teamstack: Easy Automation of Identity Management (Sponsored) appeared first on David Walsh Blog.

If you compare the UX research methods we use today with the methods we used 16 years ago, something interesting emerges. We see that UX research is becoming increasingly remote and increasingly unmoderated. In other words, we're moving to a world where UX research is becoming automated. We can learn a lot from automated research. But it comes at the price of understanding our users.

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Let $1 le r < n$ be integers. We give a proof that the group $mathop{mathrm{Aut}}({X_{n}^{mathbb{N}}, sigma_{n}})$ of automorphisms of the one-sided shift on $n$ letters embeds naturally as a subgroup $mathcal{h}_{n}$ of the outer automorphism group $mathop{mathrm{Out}}(G_{n,r})$ of the Higman-Thompson group $G_{n,r}$. From this, we can represent the elements of $mathop{mathrm{Aut}}({X_{n}^{mathbb{N}}, sigma_{n}})$ by finite state non-initial transducers admitting a very strong synchronizing condition.

Let $H in mathcal{H}_{n}$ and write $|H|$ for the number of states of the minimal transducer representing $H$. We show that $H$ can be written as a product of at most $|H|$ torsion elements. This result strengthens a similar result of Boyle, Franks and Kitchens, where the decomposition involves more complex torsion elements and also does not support practical extit{a priori} estimates of the length of the resulting product.

We also give new proofs of some known results about $mathop{mathrm{Aut}}({X_{n}^{mathbb{N}}, sigma_{n}})$.

In this paper we first review the setting for the geometric Langlands functoriality and establish a result for the `backward' functoriality functor. We illustrate this by known examples of the geometric theta-lifting. We then apply the above result to obtain new Hecke eigen-sheaves. The most important application is a construction of the automorphic sheaf for G=GSp_4 attached to a G^L-local system on a curve X such that its standard representation is an irreducible local system of rank 4 on X.

Let $hat G$ be the finite simply connected version of an exceptional Chevalley group, and let $V$ be a nontrivial irreducible module, of minimal dimension, for $hat G$ over its field of definition. We explore the overgroup structure of $hat G$ in $mathrm{GL}(V)$, and the submodule structure of the exterior square (and sometimes the third Lie power) of $V$. When $hat G$ is defined over a field of odd prime order $p$, this allows us to construct the smallest (with respect to certain properties) $p$-groups $P$ such that the group induced by $mathrm{Aut}(P)$ on $P/Phi(P)$ is either $hat G$ or its normaliser in $mathrm{GL}(V)$.

Computer science class enrollments have rapidly risen in the past decade. With current class sizes, standard approaches to grading and providing personalized feedback are no longer possible and new techniques become both feasible and necessary. In this paper, we present the third version of Automata Tutor, a tool for helping teachers and students in large courses on automata and formal languages. The second version of Automata Tutor supported automatic grading and feedback for finite-automata constructions and has already been used by thousands of users in dozens of countries. This new version of Automata Tutor supports automated grading and feedback generation for a greatly extended variety of new problems, including problems that ask students to create regular expressions, context-free grammars, pushdown automata and Turing machines corresponding to a given description, and problems about converting between equivalent models - e.g., from regular expressions to nondeterministic finite automata. Moreover, for several problems, this new version also enables teachers and students to automatically generate new problem instances. We also present the results of a survey run on a class of 950 students, which shows very positive results about the usability and usefulness of the tool.

How to generate testing scenario libraries for connected and automated vehicles (CAVs) is a major challenge faced by the industry. In previous studies, to evaluate maneuver challenge of a scenario, surrogate models (SMs) are often used without explicit knowledge of the CAV under test. However, performance dissimilarities between the SM and the CAV under test usually exist, and it can lead to the generation of suboptimal scenario libraries. In this paper, an adaptive testing scenario library generation (ATSLG) method is proposed to solve this problem. A customized testing scenario library for a specific CAV model is generated through an adaptive process. To compensate the performance dissimilarities and leverage each test of the CAV, Bayesian optimization techniques are applied with classification-based Gaussian Process Regression and a new-designed acquisition function. Comparing with a pre-determined library, a CAV can be tested and evaluated in a more efficient manner with the customized library. To validate the proposed method, a cut-in case study was performed and the results demonstrate that the proposed method can further accelerate the evaluation process by a few orders of magnitude.

Our starting point are register automata for data words, in the style of Kaminski and Francez. We study the effects of the single-use restriction, which says that a register is emptied immediately after being used. We show that under the single-use restriction, the theory of automata for data words becomes much more robust. The main results are: (a) five different machine models are equivalent as language acceptors, including one-way and two-way single-use register automata; (b) one can recover some of the algebraic theory of languages over finite alphabets, including a version of the Krohn-Rhodes Theorem; (c) there is also a robust theory of transducers, with four equivalent models, including two-way single use transducers and a variant of streaming string transducers for data words. These results are in contrast with automata for data words without the single-use restriction, where essentially all models are pairwise non-equivalent.

Rescue vessels are the main actors in maritime safety and rescue operations. At the same time, aerial drones bring a significant advantage into this scenario. This paper presents the research directions of the AutoSOS project, where we work in the development of an autonomous multi-robot search and rescue assistance platform capable of sensor fusion and object detection in embedded devices using novel lightweight AI models. The platform is meant to perform reconnaissance missions for initial assessment of the environment using novel adaptive deep learning algorithms that efficiently use the available sensors and computational resources on drones and rescue vessel. When drones find potential objects, they will send their sensor data to the vessel to verity the findings with increased accuracy. The actual rescue and treatment operation are left as the responsibility of the rescue personnel. The drones will autonomously reconfigure their spatial distribution to enable multi-hop communication, when a direct connection between a drone transmitting information and the vessel is unavailable.

We present a LiDAR-based and real-time capable 3D perception system for automated driving in urban domains. The hierarchical system design is able to model stationary and movable parts of the environment simultaneously and under real-time conditions. Our approach extends the state of the art by innovative in-detail enhancements for perceiving road users and drivable corridors even in case of non-flat ground surfaces and overhanging or protruding elements. We describe a runtime-efficient pointcloud processing pipeline, consisting of adaptive ground surface estimation, 3D clustering and motion classification stages. Based on the pipeline's output, the stationary environment is represented in a multi-feature mapping and fusion approach. Movable elements are represented in an object tracking system capable of using multiple reference points to account for viewpoint changes. We further enhance the tracking system by explicit consideration of occlusion and ambiguity cases. Our system is evaluated using a subset of the TUBS Road User Dataset. We enhance common performance metrics by considering application-driven aspects of real-world traffic scenarios. The perception system shows impressive results and is able to cope with the addressed scenarios while still preserving real-time capability.

Web services often impose inter-parameter dependencies that restrict the way in which two or more input parameters can be combined to form valid calls to the service. Unfortunately, current specification languages for web services like the OpenAPI Specification (OAS) provide no support for the formal description of such dependencies, which makes it hardly possible to automatically discover and interact with services without human intervention. In this article, we present an approach for the specification and automated analysis of inter-parameter dependencies in web APIs. We first present a domain-specific language, called Inter-parameter Dependency Language (IDL), for the specification of dependencies among input parameters in web services. Then, we propose a mapping to translate an IDL document into a constraint satisfaction problem (CSP), enabling the automated analysis of IDL specifications using standard CSP-based reasoning operations. Specifically, we present a catalogue of nine analysis operations on IDL documents allowing to compute, for example, whether a given request satisfies all the dependencies of the service. Finally, we present a tool suite including an editor, a parser, an OAS extension, a constraint programming-aided library, and a test suite supporting IDL specifications and their analyses. Together, these contributions pave the way for a new range of specification-driven applications in areas such as code generation and testing.

Software development has been changing rapidly. This development process can be influenced through changing developer friendly approaches. We can save time consumption and accelerate the development process if we can automatically guide programmer during software development. There are some approaches that recommended relevant code snippets and APIitems to the developer. Some approaches apply general code, searching techniques and some approaches use an online based repository mining strategies. But it gets quite difficult to help programmers when they need particular type conversion problems. More specifically when they want to adapt existing interfaces according to their expectation. One of the familiar triumph to guide developers in such situation is adapting collections and arrays through automated adaptation of object ensembles. But how does it help to a novice developer in real time software development that is not explicitly specified? In this paper, we have developed a system that works as a plugin-tool integrated with a particular Data Mining Integrated environment (DMIE) to recommend relevant interface while they seek for a type conversion situation. We have a mined repository of respective adapter classes and related APIs from where developer, search their query and get their result using the relevant transformer classes. The system that recommends developers titled automated objective ensembles (AOE plugin).From the investigation as we have ever made, we can see that our approach much better than some of the existing approaches.

Assistive robots enable people with disabilities to conduct everyday tasks on their own. However, these tasks can be complex, containing both coarse reaching motions and fine-grained manipulation. For example, when eating, not only does one need to move to the correct food item, but they must also precisely manipulate the food in different ways (e.g., cutting, stabbing, scooping). Shared autonomy methods make robot teleoperation safer and more precise by arbitrating user inputs with robot controls. However, these works have focused mainly on the high-level task of reaching a goal from a discrete set, while largely ignoring manipulation of objects at that goal. Meanwhile, dimensionality reduction techniques for teleoperation map useful high-dimensional robot actions into an intuitive low-dimensional controller, but it is unclear if these methods can achieve the requisite precision for tasks like eating. Our insight is that---by combining intuitive embeddings from learned latent actions with robotic assistance from shared autonomy---we can enable precise assistive manipulation. In this work, we adopt learned latent actions for shared autonomy by proposing a new model structure that changes the meaning of the human's input based on the robot's confidence of the goal. We show convergence bounds on the robot's distance to the most likely goal, and develop a training procedure to learn a controller that is able to move between goals even in the presence of shared autonomy. We evaluate our method in simulations and an eating user study.

Convolutional neural networks (CNN) have shown promising results for end-to-end speech recognition, albeit still behind other state-of-the-art methods in performance. In this paper, we study how to bridge this gap and go beyond with a novel CNN-RNN-transducer architecture, which we call ContextNet. ContextNet features a fully convolutional encoder that incorporates global context information into convolution layers by adding squeeze-and-excitation modules. In addition, we propose a simple scaling method that scales the widths of ContextNet that achieves good trade-off between computation and accuracy. We demonstrate that on the widely used LibriSpeech benchmark, ContextNet achieves a word error rate (WER) of 2.1\%/4.6\% without external language model (LM), 1.9\%/4.1\% with LM and 2.9\%/7.0\% with only 10M parameters on the clean/noisy LibriSpeech test sets. This compares to the previous best published system of 2.0\%/4.6\% with LM and 3.9\%/11.3\% with 20M parameters. The superiority of the proposed ContextNet model is also verified on a much larger internal dataset.

Smart meters enable remote and automatic electricity, water and gas consumption reading and are being widely deployed in developed countries. Nonetheless, there is still a huge number of non-smart meters in operation. Image-based Automatic Meter Reading (AMR) focuses on dealing with this type of meter readings. We estimate that the Energy Company of Paran'a (Copel), in Brazil, performs more than 850,000 readings of dial meters per month. Those meters are the focus of this work. Our main contributions are: (i) a public real-world dial meter dataset (shared upon request) called UFPR-ADMR; (ii) a deep learning-based recognition baseline on the proposed dataset; and (iii) a detailed error analysis of the main issues present in AMR for dial meters. To the best of our knowledge, this is the first work to introduce deep learning approaches to multi-dial meter reading, and perform experiments on unconstrained images. We achieved a 100.0% F1-score on the dial detection stage with both Faster R-CNN and YOLO, while the recognition rates reached 93.6% for dials and 75.25% for meters using Faster R-CNN (ResNext-101).

In this paper, we continue our prior work on using imitation learning (IL) and model free reinforcement learning (RL) to learn driving policies for autonomous driving in urban scenarios, by introducing a model based RL method to drive the autonomous vehicle in the Carla urban driving simulator. Although IL and model free RL methods have been proved to be capable of solving lots of challenging tasks, including playing video games, robots, and, in our prior work, urban driving, the low sample efficiency of such methods greatly limits their applications on actual autonomous driving. In this work, we developed a model based RL algorithm of guided policy search (GPS) for urban driving tasks. The algorithm iteratively learns a parameterized dynamic model to approximate the complex and interactive driving task, and optimizes the driving policy under the nonlinear approximate dynamic model. As a model based RL approach, when applied in urban autonomous driving, the GPS has the advantages of higher sample efficiency, better interpretability, and greater stability. We provide extensive experiments validating the effectiveness of the proposed method to learn robust driving policy for urban driving in Carla. We also compare the proposed method with other policy search and model free RL baselines, showing 100x better sample efficiency of the GPS based RL method, and also that the GPS based method can learn policies for harder tasks that the baseline methods can hardly learn.

A computer implemented method for automatic chemical assay classification, the method comprising steps the computer is programmed to perform, the steps comprising: receiving a plurality of sets of parameters, each one of the received sets of parameters characterizing a respective assay of a chemical reaction, calculating a space enhancing proximity among points representative of assays of qualitatively identical chemical reactions, and representing each one of at least two of the received sets of parameters as a respective point in the calculated space, and dividing the points in the calculated space into a number of groups, according to proximity among the points in the calculated space, each group pertaining to a respective chemical reaction, thereby classifying the assays.

A method for computer-implemented unit-conversion method, the method comprising identifying a first numerical value in a first system of units displayed on a computing device, converting the first numerical value in the first system of units into a second numerical value, and displaying the second numerical value and the second system of units on the computing device.

In one exemplary embodiment, a computer-implemented method includes receiving, at a remote direct memory access (RDMA) device, a plurality of RDMA requests referencing a plurality of virtual pages. Data transfers are scheduled for the plurality of virtual pages, wherein the scheduling occurs at the RDMA device. The number of the virtual pages that are currently pinned is limited for the RDMA requests based on a predetermined pinned page limit.

A system and method for reconfiguring a computing environment comprising a consumption analysis server, a placement server, an infrastructure management client and a data warehouse in communication with a set of data collection agents and a database. The consumption analysis server operates on measured resource utilization data to yield a set of resource consumptions in regularized time blocks, collects host and virtual machine configurations from the computing environment and determines available capacity for a set of target hosts. The placement server assigns a set of target virtual machines to the target set of hosts in a new placement. In one mode of operation the new placement is nearly optimal. In another mode of operation, the new placement is “good enough” to achieve a threshold score based on an objective function of resource capacity headroom. The new placement is implemented in the computing environment.

A method is disclosed which may include analyzing communication requests in a business process between a client and a server offering a service application to be tested. The method may further include identifying a call to a web service in the analyzed communication. The method may also include determining a location of a Web Service Description Language (WSDL) file relating to the web service on a remote server and downloading the WSDL file from the determined location. A computer readable medium having stored thereon instructions for performing the method and a computer system are also disclosed.

The disclosure generally describes computer-implemented methods, software, and systems for creating and using two-tier mobile applications. A computer-implemented method includes identifying at least a portion of a database to be associated with a mobile application, retrieving a set of metadata associated with the at least a portion of the identified database, automatically generating a set of mobile application source code for directly accessing the at least a portion of the database based on the set of retrieved metadata, and compiling the set of mobile application source code into a distributable mobile application, the distributable mobile application configured to directly access the identified database associated with the mobile application. In some instances, the identifying, retrieving, generating, and compiling operations are performed at design time, while at runtime, the mobile application is executable by a mobile device and, during runtime execution, can request database-related information directly from the identified database.

A method of automating the deployment of a number of enterprise applications on one or more computer data processing systems. Each enterprise application or update is stored in a dynamic distribution directory and is provided with identifying indicia, such as stage information, target information, and settings information. When automated enterprise deployment is invoked, computer instructions in a computer readable medium provide for initializing deployment, performing deployment, and finalizing deployment of the enterprise applications or updates.

A method of adjusting a speed of a mobile machine is provided. Image data of a location is collected where currently generated sensor data and previously generated sensor data indicate a discontinuity in sensor data. The image data is analyzed to determine if a non-motion blur score for the image data is above a threshold value. Then, a speed of the mobile machine is adjusted based on a determination that the non-motion blur score is above the threshold value.

Traffic information readings corresponding to a vehicle are received, the readings including at least a location. The traffic information readings are compared to information already within a map database, and are used to derive additional map information augmenting or correcting that already within the database, the additional map information subsequently being stored in the database. Additional information that is derived includes the presence of stop signs and traffic lights at intersections, the legality of turns at certain times of day, and the connectedness or non-connectedness of road segments.

A system, method, and computer program product for automatically generating equivalent assertions in different forms for different verification tools, which may be analog or digital. A user submits a set of logic assertions that, if unclocked, are converted to clocked assertions by generating and skewing clocks to ensure simulator uniformity. A stimulus is generated, perhaps at random, or input. A test bench is either input or synthesized. For each verification tool, the test bench is simulated and simulation results are captured. An assertion status difference engine evaluates result differences between the verification tools, and identifies and outputs differences indicating a significant inconsistency. Errors in verification tool implementation and user assertion coding can be detected. The simulators used may include SPICE and Verilog, or any other simulators that differ in type, simulation algorithm, input format, or vendor implementation.

A method of creating a datasheet includes obtaining integrated circuit data from at least one data source, creating a data structure including the integrated circuit data obtained from the at least one data source, and creating a datasheet using data contained in the data structure. The datasheet is created in a human-readable format.

A method of detecting pre-determined phrases to determine compliance quality is provided. The method includes determining whether at least one of an event or a precursor event has occurred based on a comparison between pre-determined phrases and a communication between a sender and a recipient in a communications network, and rating the recipient based on the presence of the pre-determined phrases associated with the event or the presence of the pre-determined phrases associated with the precursor event in the communication.

An apparatus includes a plurality of applications and an integrator having a voice recognition module configured to identify at least one voice command from a user. The integrator is configured to integrate information from a remote source into at least one of the plurality of applications based on the identified voice command. A method includes analyzing speech from a first user of a first mobile device having a plurality of applications, identifying a voice command based on the analyzed speech using a voice recognition module, and incorporating information from the remote source into at least one of a plurality of applications based on the identified voice command.

A speech recognition system, method of recognizing speech and a computer program product therefor. A client device identified with a context for an associated user selectively streams audio to a provider computer, e.g., a cloud computer. Speech recognition receives streaming audio, maps utterances to specific textual candidates and determines a likelihood of a correct match for each mapped textual candidate. A context model selectively winnows candidate to resolve recognition ambiguity according to context whenever multiple textual candidates are recognized as potential matches for the same mapped utterance. Matches are used to update the context model, which may be used for multiple users in the same context.

A computer-implemented method of detecting automated identities, including. The method includes, using one or more computing devices, providing for display to a user a first representation of a first profile for a first identity and a second representation of a second profile for a second identity, providing for display to the user a choice indication mechanism for indicating a judgment about the first representation of the first profile for the first identity and the second representation of the second profile for the second identity, receiving an indication of the judgment from the user about the first representation of the first profile for the first identity and the second representation of the second profile for the second identity, and determining whether at least one of the first identity, the second identity, or the user is more or less likely to be automated, based at least in part on the received indication.

The disclosed device enables the recording of television broadcasts which are preprogrammed in a memory. The presence of data lines of the television signal in combination with the presence of a color television signal is checked. When the data lines stop, the video recorder is switched on in real time by a clock time signal.

An automatic programmed ventilation control system for operating a fan includes a fan drive circuit; a duty, cycle control circuit including means for selecting a duty cycle and means for setting the selected duty cycle; a timing circuit including means for selecting the time of day and means for setting the selected time of day; a fan speed control circuit including means for selecting a fan speed and means for setting the selected fan speed; and a manual override switch circuit for overriding the set duty cycle and fan speed for operating the fan at a predetermined speed for a preselected period of time.

A mechanism is provided in a storage device for performing a write operation. The mechanism configures a write buffer memory with a plurality of write buffer portions. Each write buffer portion is dedicated to a predetermined block size category within a plurality of block size categories. For each write operation from an initiator, the mechanism determines a block size category of the write operation. The mechanism performs each write operation by writing to a write buffer portion within the plurality of write buffer portions corresponding to the block size category of the write operation.

Systems and methods for processing magnetic resonance imaging (MRI) data are provided. A method includes receiving MRI data comprising a plurality of k-space points and deriving a plurality of image data sets based on the MRI data, each of the plurality of MRI image sets obtained by zeroing a different one of the plurality of k-space points. The method further includes computing image space metric values for each of the plurality of image data sets and adjusting a portion of the MRI data associated with ones of the image space metric values that fail to meet a threshold value to yield adjusted MRI data.

The disclosed embodiments relate to pulse oximetry. An exemplary pulse oximeter comprises a probe that is adapted to be attached to a body part of a patient to create a signal indicative of an oxygen saturation of blood of the patient, and a processor that is adapted to receive the signal produced by the probe, to calculate an SPO2 value based on the signal, to detect a plurality of pattern types of SPO2 indicative of pathophysiologic events, and to produce an output indicative of a detected one of the plurality of pattern types.

An asset health monitoring system (AHMS) can assign a confidence indicator to some or all the services of a computing service provider. In response to drops in the confidence indicators, the AHMS can automatically initiate testing of services and/or computing assets associated with the services in order to raise confidence that a particular service and its computing assets will perform correctly. Further, the AHMS can automatically initiate remediation procedures for the particular service and/or specific computing assets that fail the confidence testing. By automatically triggering testing and/or remediation procedures, the AHMS can increase reliability of the computing service provider by preemptively identifying problems.

An automated emergency power supply system (EPSS) and testing solution that records generator load values and engine exhaust temperature values to evaluate whether an EPSS test satisfies legislated test criteria. The EPSS test is carried out under software control, which initiates a test by instructing an automatic transfer switch (ATS) to change its status to a test status, causing the essential loads to be powered by a generator instead of a main utility power source. Power monitors record the ATS and generator status during the test as well as electrical parameter data from the ATS and generator and exhaust temperature data and other engine parameter data from the generator. When the test is concluded, the ATS is instructed to return the status to normal so that power delivery is resumed from the main power source. The electrical and engine parameter data is analyzed and compared against legislated test criteria to determine a pass/fail result of the EPSS test.

A blood processing centrifuge comprising: a rotor having an axis of rotation and being controllably spun around the axis, a mechanism for processing whole blood within the rotor while spinning, a computer controlling blood processing operations, the computer being mounted to the rotor and spinning therewith.

Systems and methods are provided for evaluating performance of forecasting models. A plurality of forecasting models may be generated using a set of in-sample data. Two or more forecasting models from the plurality of forecasting models may be selected for use in generating a combined forecast. An ex-ante combined forecast may be generated for an out-of-sample period using the selected two or more forecasting models. The ex-ante combined forecast may then be compared with a set of actual out-of-sample data to evaluate performance of the combined forecast.

An intracorporeal autonomous active medical device having a capsule body and a base. The capsule body includes a body portion and a lid portion, and the capsule body contains therein electronic circuitry containing the active elements of the autonomous medical device, and a power supply. The capsule body also includes a fastening system on an exterior surface of the capsule body that is configured to correspond with a fastening mechanism on the base configured to be anchored to a tissue wall. The fastening mechanism provides selective engagement between the capsule body and the base.

Methods and devices for determining optimal Atrial to Ventricular (AV) pacing intervals and Ventricular to Ventricular (VV) delay intervals in order to optimize cardiac output. Impedance, preferably sub-threshold impedance, is measured across the heart at selected cardiac cycle times as a measure of chamber expansion or contraction. One embodiment measures impedance over a long AV interval to obtain the minimum impedance, indicative of maximum ventricular expansion, in order to set the AV interval. Another embodiment measures impedance change over a cycle and varies the AV pace interval in a binary search to converge on the AV interval causing maximum impedance change indicative of maximum ventricular output. Another method varies the right ventricle to left ventricle (VV) interval to converge on an impedance maximum indicative of minimum cardiac volume at end systole. Another embodiment varies the VV interval to maximize impedance change.

A disposable electrode includes: an electrode pad; and a connector, connecting the electrode pad to a defibrillator, and including an information holder that can be provided with a transmissive opening or a light reflective member, the information holder holding information about at least an expiration date, depending on presence or absence of the transmissive opening or the light reflective member, the information holder allowing the information to be notified from the defibrillator when the connector is connected to the defibrillator.

In some embodiments, nerves surrounding arteries or leading to organs are targeted with energy sources to correct or modulate physiologic processes. In some embodiments, different types of energy sources are utilized singly or combined with one another. In some embodiments, bioactive agents or devices activated by the energy sources are delivered to the region of interest and the energy is enhanced by such agents.