​​Addressing a press conference, MHA Joint Secretary Punya Salila Srivastava said the government intends to give relaxations to people within the lockdown guidelines. These trains are part of this endeavour, she said.

Shramik special trains were run from May 1 on the request of different state governments. The railways has suspended passenger, mail and express trains to combat the spread of novel coronavirus (Covid-19) since March 24.

On February 21, ICITAP completed the Basic Criminal Investigation Training Course for 29 members of the Belize Police Department’s Criminal Investigation Branch.

OIP is now accepting registration for topic-specific FOIA training sessions to be offered online. 

Seventy-seven passengers and seven crew members were aboard when the train derailed and pulled 13 cars off the tracks.

Top trainer Mike de Kock has warned of a “grim reality” featuring “loss of jobs and euthanasia” of significant parts of the horse population if the South African racing shutdown continues. On Tuesday, the South African government blocked plans for a resumption when it refused to allow the sport to take place under Lockdown Level […]

The post Trainer Mike de Kock Warns Of Mass Job Loss, Euthanasias In South Africa If Racing Shutdown Continues appeared first on Horse Racing News | Paulick Report.

The NTSB is now recommending that commercial drivers be banned from using hands-free devices when operating their vehicle.

omg thats about right Hamish. I never trust work times on claimers especially.

oh here we go... seriously get a life tired of the racial BS.

Theres a new female trainer at Remington park, has pretty much zero stats/starts. So far her horses have qualified/won several stakes. . Pretty talented for zero trainer whos history shows zero starts. Qualified one last night again to futurity. And then Judd Kearls shill trainer padgett who won everything in NM has not hardly lit the board. Tres Abagados Stupidos do you anything about this girl?

Multiple graded stakes winner Call Paul, formerly trained by Jason Servis, had to be euthanized on Wednesday morning at Belmont Park. The Daily Racing Form reports that the colt suffered catastrophic injuries to his left hind leg during a workout over the training track. The 4-year-old Pennsylvania-bred son of Friesan Fire was breezing for the fourth […]

The post Former Jason Servis Trainee Call Paul Fatally Injured During Belmont Workout appeared first on Horse Racing News | Paulick Report.

Pandemic expected to magnify differences between healthy retailers and those with big financial troubles.

The Baltimore Orioles' Opening Day will be delayed by at least two weeks after Major League Baseball announced its response to the coronavirus outbreak Thursday.

https://www.nps.gov/grca/learn/news/national-park-service-announces-availability-of-environmental-assessment-for-train-operations-in-grand-canyon-national-park.htm

A Finding of No Significant Impact was signed on August 28, 2009, by Michael D. Snyder, Regional Director for the Intermountain Region of the National Park Service, for Train Operations at Grand Canyon National Park https://www.nps.gov/grca/learn/news/news_2009-08-31_trainea.htm

In spite of the rapid response time, park emergency responders were not able to revive 72-year old John Debelack of Saddlebrooke, Arizona. https://www.nps.gov/grca/learn/news/2011-06-29_death.htm

Horace P. Albright Training Center was officially listed to the National Register of Historic Places on September 30, 2013. The only National Park Service (NPS) training center in the West and located within the boundaries of Grand Canyon National Park, the Center is a state significant Historic District exemplifying simple, practical, modernist design of the Mission 66 Era. https://www.nps.gov/grca/learn/news/albright-training-center.htm

The trail between the El Tovar Hotel and the train depot will close for repairs July 1. https://www.nps.gov/grca/learn/news/el-tovar-walkway-detour.htm

Newcastle United goalkeeper Rob Elliot has opened up about team-mate Isaac Hayden and what makes him such an important player

DALLAS, April 3, 2020 — With the COVID-19 pandemic, more patients are having difficulty breathing and requiring ventilators to help them breathe. As hospital and intensive care unit (ICU) volumes increase with COVID-19 patients, health care ...

Recent studies of optimization methods and GNC of spacecraft near small bodies focusing on descent, landing, rendezvous, etc., with key safety constraints such as line-of-sight conic zones and soft landings have shown promising results; this paper considers descent missions to an asteroid surface with a constraint that consists of an onboard camera and asteroid surface markers while using a stochastic convex MPC law. An undermodeled asteroid gravity and spacecraft technology inspired measurement model is established to develop the constraint. Then a computationally light stochastic Linear Quadratic MPC strategy is presented to keep the spacecraft in satisfactory field of view of the surface markers while trajectory tracking, employing chance based constraints and up-to-date estimation uncertainty from navigation. The estimation uncertainty giving rise to the tightened constraints is particularly addressed. Results suggest robust tracking performance across a variety of trajectories.

In this work, we investigate multi-task learning as a way of pre-training models for classification tasks in digital pathology. It is motivated by the fact that many small and medium-size datasets have been released by the community over the years whereas there is no large scale dataset similar to ImageNet in the domain. We first assemble and transform many digital pathology datasets into a pool of 22 classification tasks and almost 900k images. Then, we propose a simple architecture and training scheme for creating a transferable model and a robust evaluation and selection protocol in order to evaluate our method. Depending on the target task, we show that our models used as feature extractors either improve significantly over ImageNet pre-trained models or provide comparable performance. Fine-tuning improves performance over feature extraction and is able to recover the lack of specificity of ImageNet features, as both pre-training sources yield comparable performance.

Many efforts of research are devoted to semantic role labeling (SRL) which is crucial for natural language understanding. Supervised approaches have achieved impressing performances when large-scale corpora are available for resource-rich languages such as English. While for the low-resource languages with no annotated SRL dataset, it is still challenging to obtain competitive performances. Cross-lingual SRL is one promising way to address the problem, which has achieved great advances with the help of model transferring and annotation projection. In this paper, we propose a novel alternative based on corpus translation, constructing high-quality training datasets for the target languages from the source gold-standard SRL annotations. Experimental results on Universal Proposition Bank show that the translation-based method is highly effective, and the automatic pseudo datasets can improve the target-language SRL performances significantly.

We propose a new method for realistic human motion transfer using a generative adversarial network (GAN), which generates a motion video of a target character imitating actions of a source character, while maintaining high authenticity of the generated results. We tackle the problem by decoupling and recombining the posture information and appearance information of both the source and target characters. The innovation of our approach lies in the use of the projection of a reconstructed 3D human model as the condition of GAN to better maintain the structural integrity of transfer results in different poses. We further introduce a detail enhancement net to enhance the details of transfer results by exploiting the details in real source frames. Extensive experiments show that our approach yields better results both qualitatively and quantitatively than the state-of-the-art methods.

Uncertain dynamic obstacles, such as pedestrians or vehicles, pose a major challenge for optimal robot navigation with safety guarantees. Previous work on motion planning has followed two main strategies to provide a safe bound on an obstacle's space: a polyhedron, such as a cuboid, or a nonlinear differentiable surface, such as an ellipsoid. The former approach relies on disjunctive programming, which has a relatively high computational cost that grows exponentially with the number of obstacles. The latter approach needs to be linearized locally to find a tractable evaluation of the chance constraints, which dramatically reduces the remaining free space and leads to over-conservative trajectories or even unfeasibility. In this work, we present a hybrid approach that eludes the pitfalls of both strategies while maintaining the original safety guarantees. The key idea consists in obtaining a safe differentiable approximation for the disjunctive chance constraints bounding the obstacles. The resulting nonlinear optimization problem is free of chance constraint linearization and disjunctive programming, and therefore, it can be efficiently solved to meet fast real-time requirements with multiple obstacles. We validate our approach through mathematical proof, simulation and real experiments with an aerial robot using nonlinear model predictive control to avoid pedestrians.

Restless multi-armed bandits are a class of discrete-time stochastic control problems which involve sequential decision making with a finite set of actions (set of arms). This paper studies a class of constrained restless multi-armed bandits (CRMAB). The constraints are in the form of time varying set of actions (set of available arms). This variation can be either stochastic or semi-deterministic. Given a set of arms, a fixed number of them can be chosen to be played in each decision interval. The play of each arm yields a state dependent reward. The current states of arms are partially observable through binary feedback signals from arms that are played. The current availability of arms is fully observable. The objective is to maximize long term cumulative reward. The uncertainty about future availability of arms along with partial state information makes this objective challenging. Applications for CRMAB abound in the domain of cyber-physical systems. This optimization problem is analyzed using Whittle's index policy. To this end, a constrained restless single-armed bandit is studied. It is shown to admit a threshold-type optimal policy, and is also indexable. An algorithm to compute Whittle's index is presented. Further, upper bounds on the value function are derived in order to estimate the degree of sub-optimality of various solutions. The simulation study compares the performance of Whittle's index, modified Whittle's index and myopic policies.

Neural machine translation (NMT) needs large parallel corpora for state-of-the-art translation quality. Low-resource NMT is typically addressed by transfer learning which leverages large monolingual or parallel corpora for pre-training. Monolingual pre-training approaches such as MASS (MAsked Sequence to Sequence) are extremely effective in boosting NMT quality for languages with small parallel corpora. However, they do not account for linguistic information obtained using syntactic analyzers which is known to be invaluable for several Natural Language Processing (NLP) tasks. To this end, we propose JASS, Japanese-specific Sequence to Sequence, as a novel pre-training alternative to MASS for NMT involving Japanese as the source or target language. JASS is joint BMASS (Bunsetsu MASS) and BRSS (Bunsetsu Reordering Sequence to Sequence) pre-training which focuses on Japanese linguistic units called bunsetsus. In our experiments on ASPEC Japanese--English and News Commentary Japanese--Russian translation we show that JASS can give results that are competitive with if not better than those given by MASS. Furthermore, we show for the first time that joint MASS and JASS pre-training gives results that significantly surpass the individual methods indicating their complementary nature. We will release our code, pre-trained models and bunsetsu annotated data as resources for researchers to use in their own NLP tasks.

Learning-based techniques are increasingly effective at controlling complex systems using data-driven models. However, most work done so far has focused on learning individual tasks or control laws. Hence, it is still a largely unaddressed research question how multiple tasks can be learned efficiently and simultaneously on the same system. In particular, no efficient state space exploration schemes have been designed for multi-task control settings. Using this research gap as our main motivation, we present an algorithm that approximates the smallest data set that needs to be collected in order to achieve high control performance for multiple learning-based control laws. We describe system uncertainty using a probabilistic Gaussian process model, which allows us to quantify the impact of potentially collected data on each learning-based controller. We then determine the optimal measurement locations by solving a stochastic optimization problem approximately. We show that, under reasonable assumptions, the approximate solution converges towards that of the exact problem. Additionally, we provide a numerical illustration of the proposed algorithm.

This paper considers a convex optimization problem with cost and constraints that evolve over time. The function to be minimized is strongly convex and possibly non-differentiable, and variables are coupled through linear constraints.In this setting, the paper proposes an online algorithm based on the alternating direction method of multipliers(ADMM), to track the optimal solution trajectory of the time-varying problem; in particular, the proposed algorithm consists of a primal proximal gradient descent step and an appropriately perturbed dual ascent step. The paper derives tracking results, asymptotic bounds, and linear convergence results. The proposed algorithm is then specialized to a multi-area power grid optimization problem, and our numerical results verify the desired properties.

We analyze the computational complexity of motion planning through local "input/output" gadgets with separate entrances and exits, and a subset of allowed traversals from entrances to exits, each of which changes the state of the gadget and thereby the allowed traversals. We study such gadgets in the 0-, 1-, and 2-player settings, in particular extending past motion-planning-through-gadgets work to 0-player games for the first time, by considering "branchless" connections between gadgets that route every gadget's exit to a unique gadget's entrance. Our complexity results include containment in L, NL, P, NP, and PSPACE; as well as hardness for NL, P, NP, and PSPACE. We apply these results to show PSPACE-completeness for certain mechanics in Factorio, [the Sequence], and a restricted version of Trainyard, improving prior results. This work strengthens prior results on switching graphs and reachability switching games.

The de Bruijn graph, its sequences, and their various generalizations, have found many applications in information theory, including many new ones in the last decade. In this paper, motivated by a coding problem for emerging memory technologies, a set of sequences which generalize sequences in the de Bruijn graph are defined. These sequences can be also defined and viewed as constrained sequences. Hence, they will be called constrained de Bruijn sequences and a set of such sequences will be called a constrained de Bruijn code. Several properties and alternative definitions for such codes are examined and they are analyzed as generalized sequences in the de Bruijn graph (and its generalization) and as constrained sequences. Various enumeration techniques are used to compute the total number of sequences for any given set of parameters. A construction method of such codes from the theory of shift-register sequences is proposed. Finally, we show how these constrained de Bruijn sequences and codes can be applied in constructions of codes for correcting synchronization errors in the $ell$-symbol read channel and in the racetrack memory channel. For this purpose, these codes are superior in their size on previously known codes.

Techniques for evaluation and/or retraining of a classification model built using labeled training data. In some aspects, a classification model having a first set of weights is retrained by using unlabeled input to reweight the labeled training data to have a second set of weights, and by retraining the classification model using the labeled training data weighted according to the second set of weights. In some aspects, a classification model is evaluated by building a similarity model that represents similarities between unlabeled input and the labeled training data and using the similarity model to evaluate the labeled training data to identify a subset of the plurality of items of labeled training data that is more similar to the unlabeled input than a remainder of the labeled training data.

A computer-implemented method is provided for statistical data learning under privacy constraints. The method includes: receiving, by a processor, a plurality of pieces of statistical information relating to a statistical object and aggregating, by the processor, the plurality of pieces of statistical information so as to provide an estimation of the statistical object. Each piece of statistical information includes an uncertainty variable, the uncertainty variable being a value determined from a function having a predetermined mean. The number of pieces of statistical information aggregated is proportional to the reliability of the estimation of the statistical object.

A method for designing a transformer in an integrated circuit includes receiving one or more desired characteristics of the transformer from user input and iteratively determining a design solution for the transformer through one or more simulations and modifications using a rule-set. The method combines the one or more desired characteristics with other preset characteristics of the transformer or the integrated circuit. A first model of the transformer is defined with typical load impedances and simulated having the combined characteristics to determine performance. Results of the simulation are processed to calculate performance with the load impedances specified by the user. The results are further processed to obtain a mathematical model that includes tuning capacitors. The first and subsequent models are modified by drawing on a rule-set of expert knowledge relating to general dependency of at least one design criterion, such as a physical, geometrical or performance characteristic, with another design criterion.

Techniques for sorting and filtering a list in a space-constrained viewing area are described. A filter widget and a list of items are displayed in a view of an electronic display screen. In response to user input selecting the filter widget, and without changing to a different view, a filter category overlay is displayed in the view to provide various selectable filter categories. In response to selection of a filter category, a visual depiction of the selected filter category is displayed in the view. The list of items is filtered according to the selected filter category and displayed in the view without changing to any other view. Subsequently added visual depictions are linearly stacked in the view. Further, a filter modification overlay, which provides selectable filtering attributes, is displayed upon selection of a visual depiction.

The present invention relates to a system and method for using the system. In particular, the present invention relates to an application, executable by a processing device to assess the organization of a non-nutritive suck (NNS) pattern of a patient and to entrain an organized NNS pattern in the patient. The software system receives data from an orofacial stimulation appliance to assess the patient's natural NNS pattern and generates a precise therapeutic pulse profile that is actuated as a tactile stimulus via the orofacial stimulation appliance to entrain an organized NNS pattern.

A vehicle powertrain has an engine, a driving shaft having a passage defined therein, a driven shaft, a pump, a hydraulic fluid reservoir, and a CVT. A driving pulley of the CVT includes a fixed sheave and a movable sheave disposed on the driving shaft for rotation therewith, a spring biasing a movable sheave away from the fixed sheave, and a CVT chamber fluidly communicating with the passage of the driving shaft. The pump supplies hydraulic fluid from the reservoir to the passage in the driving shaft. The hydraulic fluid flows from the passage to the CVT chamber to create a hydraulic pressure in the CVT chamber. The hydraulic pressure in the CVT chamber biases the movable sheave toward the fixed sheave.

A method of entraining a second fluid in a first fluid is provided. The method comprises supplying a first fluid to a processing passage (4) having an inlet (6) and an outlet (8), and supplying an entrainment fluid to a nozzle (10) which opens into the processing passage (4) intermediate the passage inlet (6) and the passage outlet (8). A second fluid which will undergo a change of phase and/or state when added to the first fluid is also provided, and supplied to a first port (22) opening into the processing passage (4) adjacent the nozzle (10). The entrainment fluid is injected from the nozzle (10) into the processing passage (4) so as to form a dispersed phase of the first and second fluids in a continuous vapor phase, and the vapor phase is condensed downstream of the nozzle (10). A device suitable for carrying out such a method is also provided.

To ensure easy and secure placement of a belt for KAATSU muscle training on a target compressed site near the proximal portion of a limb. A belt 100B has a longer first band-shaped member 110 and a shorter second band-shaped member 120 both of which have a band shape and are connected to a ring-shaped joint member 130 at their respective ends. In order to place the belt 100B on the target compressed site, the limb (right leg in this case) on which the belt 100B is expected to be placed is inserted into a loop of the first band-shaped member 110 formed by passing the end of the first band-shaped member 110 through an opening in the joint member 130, and the belt is moved up to the target compressed site. Then, the first band-shaped member 110 and the second band-shaped member 120 are pulled with both hands in the opposite directions. The belt 100B is placed on the target compressed site with the belt 100B being tensioned appropriately.

A device for damping vibrations in a drive train, in particular for plug screws in the pulp and paper industries. The device is principally characterized in that a cylindrical shaft, preferably designed as a hollow shaft, is provided, wherein the cylindrical shaft is arranged between the halves of a coupling and at least one ring having friction surfaces is arranged around the cylindrical shaft. Stick-slip vibrations that occur can thereby be favorably eliminated, and thus the gearbox and the motor of the drive train can be protected.

A rotational vibration damper includes a primary side (32) and a secondary side (46) which is rotatable with respect to the primary side (32) around an axis of rotation (A) against the action of a damper element arrangement (28). At least one damper element unit (42) of the first group (70) and at least one damper element unit (42') of the second group (70') are pre-loaded, and the primary side (32) and the secondary side (46) are pre-loaded in a basic relative rotation position with respect to one another. Proceeding from the basic relative rotation position of the primary side (32) with respect to the secondary side (46), a pre-loading path (V, V') of at least one pre-loaded damper element unit (42) is shorter than a maximum relative rotation path of the primary side (32) with respect to the secondary side (46).

A method for controlling a transmission of a powertrain system includes executing a single source shortest path search to identify a preferred shift path originating with an initial powertrain state and terminating at a target powertrain state, wherein the single source shortest path search employs transition-specific costs and situational costs to identify the preferred shift path. The preferred shift path is executed to achieve the target powertrain state.

A kinetic hybrid device and method for a vehicle may include a planetary gear system configured as a continuously variable transmission comprised of three or four ports. The kinetic hybrid device and method may include a flywheel connected to a first port of the system, a final drive connected to a second port of the system, and the variator for the flywheel connected to a third or fourth port of the system. The prime mover and/or other power sources may share a port with the flywheel, but do not share a port with the final drive.

A method of operating a drive-train of a vehicle that comprises a combustion engine whose torque for driving the vehicle can be transmitted to a drive output via a transmission, with a hydraulically actuated clutch when the clutch is engaged. An electric machine provides torque which can act upon the drive-train. The clutch is closed by filling the clutch with hydraulic fluid through a circuit by way of a pump which can be driven by the engine and the electric machine. The method is to engage the clutch when the combustion engine is initially off and/or when the electric machine is initially switched off, determining a driving dynamic based on the behavior of the driver and adjusting the speed of the electric machine based on the determined driving dynamic such that the greater the determined driving dynamic is, the more rapidly the clutch is filled by the pump.

A drive train apparatus (1) adapted for driving a pan and tilt head, which in use is intended to support a payload (for example a video camera), the apparatus includes respective successive drive elements (2, 3, 4) so coupled as to communicate a rotational movement applied at one end of the apparatus (1) from an output of a rotational input device (8) to a rotational output (16) disposed at the other end of the apparatus (1), in a manner whereby the rotational velocity of the rotational movement is reduced across the drive elements (2, 3, 4) thereby converting the torque applied to the input of each drive element (2, 3, 4) into an increased torque at the output of each drive element (2, 3, 4); a first stage one of the drive elements including a belt drive.

A rocking jaw gripper for restraining tubulars including an arm with a rocking jaw gripper rocker jaw, a rocking jaw gripper frame connected with the arm, a locking pin connecting the rocking jaw gripper frame to the chain cylinder, a hinge pin connecting the rocking jaw gripper frame to the arm and a plate jaw fastener retaining the rocker jaw body between the top plate and the bottom plate by engaging the tail hole of the rocker jaw body. When the rocking jaw gripper is engaged, it acts to restrain the movement of a tubular during make-up and break-out.

The invention relates to a universal wireless trainable transceiver unit with integrated bidirectional wireless interface functionality, and a method for same. Using a scan, push button or untrained channel mode, a user may enter into a wireless bidirectional interface mode of a trainable transceiver. The interface mode allows a user to select a sub-set of modes that include diagnostics, flash and vehicle interface. Each mode provides the trainable transceiver to communicate wirelessly in a bidirectional manner with another remote device.

A control switch incorporates a solid state transducer, a strain gauge. The transducer responds to a local environmental condition, such as fluid level, or pressure and exhibits a parameter change which can be detected as an electrical output. Control circuits coupled to the transducer can sense the parameter change and switch a source of electrical energy to a load in response thereto.