How fast animals move is critical to understanding their energetic requirements, locomotor capacity and foraging performance, yet current methods for measuring speed via animal-attached devices are not universally applicable. Here, we present and evaluate a new method that relates forward speed to the stochastic motion of biologging devices as tag jiggle, the amplitude of the tag vibrations as measured by high sample rate accelerometers, increases exponentially with increasing speed. We successfully tested this method in a flow tank using two types of biologging devices and in situ on wild cetaceans spanning ∼3 to >20 m in length using two types of suction cup-attached tag and two types of dart-attached tag. This technique provides some advantages over other approaches for determining speed as it is device-orientation independent and relies only on a pressure sensor and a high sample rate accelerometer, sensors that are nearly universal across biologging device types.
The forward speed of an organism is a fundamental link between physiology, energy expenditure and ecology across a wide range of spatial and temporal scales (Tucker, 1970), yet accurately and consistently measuring speed in natural environments has proven difficult. An accurate understanding of speed reflects an animal's locomotor performance (Domenici, 2001), energetic costs (Claireaux et al., 2006; Clark et al., 2010; Videler, 1993; Watanabe et al., 2011) and behavioral state (Aoki et al., 2012; Goldbogen et al., 2006), and also aids in 3D track reconstructions (Laplanche et al., 2015; Wilson and Wilson, 1988). In terrestrial environments, speed can be measured accurately using georeferencing techniques (e.g. von Hünerbein et al., 2000; Weimerskirch et al., 2002). However, global positioning systems (GPS) do not work underwater; thus, in aquatic environments, forward speed must be measured using multi-sensor, animal-borne tags (Aoki et al., 2012; Fletcher et al., 1996; Sato et al., 2003; Shepard et al., 2008; Wilson and Achleitner, 1985). While these devices have been successful in various contexts, all exhibit disadvantages including high-drag equipment (Kawatsu et al., 2009), orientation constraints (Chapple et al., 2015), a dependence on water clarity (Shepard et al., 2008), and unknown sensor responses within variable flow regimes (Wilson and Achleitner, 1985).
However, this metric can only be relied on when pitch is accurately determined and sufficiently steep, so these periods are commonly used to perform in situ calibrations for other speed metrics that can then be used to estimate speed for the duration of the device deployment (e.g. Blackwell et al., 1999; Goldbogen et al., 2006; Miller et al., 2016; Sato et al., 2003). One such method relies on the observation that the amplitude of flow noise recorded by a hydrophone increases exponentially with speed (Finger et al., 1979). In situ flow noise measurements are typically regressed against OCDR at high pitch, and then the calibration curve is applied to the entire time series (e.g. Fletcher et al., 1996; Goldbogen et al., 2006; Simon et al., 2009). This method is limited by errors at high and low speed (Goldbogen et al., 2006), errors associated with imperfect regression relationships, and relies on devices with higher battery and memory requirements than other onboard sensors.
Here, we describe an alternative speed estimation method that relies only on a pressure sensor and high sample rate accelerometers (>40 Hz) which are now commonplace in animal-attached tags. Accelerometers have been deployed on swimming animals from diverse taxa including birds (Noda et al., 2016), cartilaginous fish (Gleiss et al., 2011), bony fish (Wright et al., 2014), cnidarians (Fossette et al., 2015), pinnipeds (Ydesen et al., 2014), and both small (Wisniewska et al., 2016) and large cetaceans (Goldbogen et al., 2006). When moving through a dense medium like water at speeds above ∼1 m s−1, an accelerometer will record the continuous jiggling motion that results from passing through a turbulent flow (Movies 1 and 2). We demonstrate the jiggle method using data from three types of multi-sensor tags deployed on cetaceans and also test the method in a flow tank. Our data suggest that in addition to broader applicability, the jiggle method is robust to tag orientation differences and has smaller regression-associated error than the flow noise method.
The jiggle method can be implemented using Matlab v2013b or later (www.mathworks.com) code available at https://purl.stanford.edu/gd922zq9141. The method was developed from the observation that the amplitude of stochastic tag motion increases exponentially with increasing speed (Fig. 1), and this tag motion is measured continuously by the device's accelerometers. Accelerometers measure a combination of both specific (dynamic) and gravity-related (static) acceleration, but speed cannot be determined directly by integrating acceleration as small errors in calibration and tag orientation aggregate when integration of measured quantities is attempted, and because separating the two forms of acceleration is prone to error (Van Hees et al., 2013; Ware et al., 2016). Instead of estimating speed from acceleration, the jiggle method regresses the root-mean-square (RMS) amplitude of accelerometer motion along three axes against speed calculated using OCDR. We then use these regression equations to estimate speed for a given jiggle magnitude across the entire dataset.
Accelerometer jiggle during a blue whale (bw14_212a) feeding dive. (A) Jiggle amplitude regressed against periods of orientation-corrected depth rate (OCDR) when |pitch|>45 deg. (B) Sampling at 250 Hz: the accelerometer signal in all three axes increases in amplitude during descent and ascent and preceding each lunge feeding event. Accelerometer signals are deviations from a 0.4 s running mean of each axis. Speed was smoothed with a 1 s running mean filter. (C) A 250 point fast Fourier transform (FFT) with 25% overlap of the y-axis accelerometer signal, calculated and displayed using Triton (Wiggins, 2003).
The accelerometer jiggle amplitude along each axis is calculated using the function TagJiggle.m by bandpass filtering the magnitude of the high-frequency accelerometer signal using a 128 point symmetric finite impulse response (FIR) filter. A bandpass filter was used for consistency across deployments with up to an 800 Hz sampling rate. However, as most energy in the signal was in the lower frequencies, a high-pass filter could be used for most applications. The most robust filter was determined experimentally. For general use, a 10–90 Hz bandpass filter gives broadly consistent results but the upper limit should be less than the Nyquist frequency (half the sampling rate). The filtered vector is binned (default is ½ second) and centered on each sampling point, and the accelerometer jiggle RMS amplitude (J) of each bin is calculated on a dB scale relative to the accelerometer units.
Like any device that estimates speed based on water movement around an animal, different locations of the device on the animal and the size/shape of the animal itself will lead to different flow conditions and different water velocities at each tag location (Fiore et al., 2017; Schetz and Fuhs, 1999). Thus, calibration in a flow tank is not solely sufficient for speed estimation using any currently existing method, and an in situ calibration must be performed for every deployment. The function SpeedFromRMS.m (available at: https://purl.stanford.edu/gd922zq9141), which can also be used to calculate relationships for other speed metrics (e.g. flow noise), uses OCDR at high pitch angles (default |pitch|>45 deg) as the known speed values, and allows the user to graphically adjust the default parameters to provide greater thresholds for pitch and depth to increase the accuracy of OCDR. The function also allows the user to exclude periods of high roll rate which, for large animals like the baleen whales in this study with a body diameter of 3 m rolling at 40 deg s−1 (Segre et al., 2016), could potentially add to the overall speed experienced by the tag in a non-forward direction.
Biologging devices attached with suction cups are periodically subject to sliding on the animal's body surface, and in the process the tag may adopt a new orientation. To account for this, SpeedFromRMS.m calculates a separate curve for each user-defined period of tag orientation within a deployment. For each section, the script calculates a coefficient of determination (R2) and produces plots of jiggle RMS amplitude versus OCDR (Fig. 1A) as well as plots of time versus speed calculated from accelerometer jiggle, time versus speed from OCDR, and time versus depth.
(3)Finally, the regression equation is applied to J for all time points such that the resulting speed vector matches the length and sampling frequency of the original data (Figs 1–3).
Speed measurements from deployments of a CATS tag (bw140806-2) and a DTAG (bw14_218a) on a blue whale. (A) Both tag locations. (B) Video from CATS tag shows initial tag position near the pectoral flipper. (C) Five metrics of animal speed (JJ, jiggle; FN, flow noise; OCDR, orientation-corrected depth rate when |pitch|>45 deg) smoothed with a 1 s running mean filter showing comparable magnitudes and inflections. (D) The CATS tag slipped to the peduncle. The difference in amplitude of speed measured from the two tags reflects the increased peduncle motion during fluking; at the conclusion of fluking, the two metrics return to comparable values. OCDR during fluking is an unreliable metric of speed because of large oscillations when the travel direction does not coincide with animal pitch. The new position of the CATS tag is shown in E and the perspective from the tag video is shown in F.
Speed calculated from accelerometer motion and acoustic flow noise during the presence of other acoustic noise. Acceleration deviation is the z-axis deviation from a 0.4 s running mean of the accelerometer signal. JJ, jiggle; FN, flow noise. Spectrograms produced using Triton (Wiggins, 2003); dB values are self-referenced in the acoustic spectrograms. (A) A blue whale (bw14_262b) with stereotypical A and B calls (Thompson et al., 1996) recorded on the hydrophone and the accelerometer. Type A calls had most of their acoustic energy in the harmonics that overlapped with the filtered frequencies and showed dramatic increases in flow noise-derived speed. Accelerometer spectrogram is a 250 point FFT with 25% overlap. Acoustic data were downsampled to 8 kHz, and displayed using a 7000 point FFT with 25% overlap. (B) A humpback whale (mn151012-7) with 10 bioacoustic events. Events viii and ix were low-frequency vocalizations common to humpback whales in the NE Pacific (Fournet et al., 2015; Thompson et al., 1986). Event ix was apparent in both the accelerometer and hydrophone signal. Accelerometer spectrogram used a 200 point FFT with 50% overlap. Acoustic data were recorded at 22.05 kHz and are displayed using an 8192 point FFT with 25% overlap.
Utilizing suction cups designed for deployment on cetacean skin, we attached three types of CATS (Customized Animal Tracking Solutions) video tags (Cade et al., 2016; Goldbogen et al., 2017) with sampling rates of 40, 400 and 800 Hz and an Acousonde (Burgess, 2009) sampling at 400 Hz to the bottom of a recirculating flow tank (Movie 1) with an 18 cm×18 cm cross-sectional area. The devices were exposed to known incrementally increasing flow rates of 0.3 to 3.1 m s−1 for periods of 1 min at each speed (Fig. S1). Data were collected with the tags positioned in four orientations: (A) directly against the flow, (B) directly with the flow, (C) angled against the flow and (D) directly against the flow with only the front two suction cups attached (Fig. S2). The flow tank was controlled with a motor operating at known revolutions per minute (RPM) and the speed at each RPM setting was measured using a Höntzsch flowtherm NT flowmeter (www.hoentzsch.com/en/) at the location where the tag would be placed. The motor generated up to 0.12 m s−1 variation in flow speed at each RPM setting, so the median flow tank speed was regressed against the linearized mean of the corresponding RMS value of the accelerometer jiggle. As the flow tank itself vibrated during the trials (Fig. S1B), the tag was also attached to the outside of the tank and the accelerometer jiggle was calculated at each speed. The amplitudes of the tank vibrations were linearly subtracted from the values recorded in the flow before regressions were calculated (Fig. S2).
The correlations were run for J calculated from the accelerometer jiggle at various frequency ranges (Fig. S3) and this was used to determine both the range and axis that yielded the highest correlation coefficient.
The accelerometer jiggle method was tested using data from four tag types deployed on humpback whales (Megaptera novaeangliae Borowski 1781), fin whales [Balaenoptera physalus (Linnaeus, 1758)], blue whales [Balaenoptera musculus (Linnaeus, 1758)] and Risso's dolphins [Grampus griseus (G. Cuvier 1812)] off the coast of California. All tags were deployed from a 6 m rigid-hull inflatable boat using a 6 m pole under National Marine Fisheries Service permits 16111, 14534 or 14809 as well as institutional IACUC protocols. Suction cup tags were either CATS video tags or DTAGs (digital sound recording tags) (Johnson et al., 2009) and medium duration dart-attached tags (Szesciorka et al., 2016) were either Acousondes with a custom-modified base or modified TDR-10 tags (Wildlife Computers, Redmond, WA, USA) with an attached accelerometer and additional pressure sensor from CATS (www.cats.is). Accelerometer sampling rates ranged from 40 to 790 Hz. Animal pitch and roll were calculated for DTAG deployments using the DTAG tool kit (https://www.soundtags.org/dtags/dtag-toolbox/) and for CATS and Acousonde deployments using custom-written Matlab scripts (Cade et al., 2016). Accelerometers for DTAGs, Acousondes and CATS deployment mn161117-10 utilized a dynamic range of ±2 g, and remaining CATS deployments recorded at ±4 g.
Accelerometer jiggle amplitudes for 23 baleen whale deployments were calculated and regressed against OCDR at 13 frequency ranges to determine which filtering range consistently gave the best results (Fig. S3). Using the 10–90 Hz frequency range, forward speed was determined with both a univariate and a multivariate regression on OCDR for 27 total deployments on all species. The R2 from a single regression relationship for the whole deployment was compared with the weighted mean R2 (mR2) of each tag orientation section. Filtering at 10 Hz removed gravity-related acceleration signals associated with postural changes for our deployments (Sato et al., 2007), but higher frequency floors could also be employed without substantially reducing efficacy (Fig. S3, Movie 2). For deployments with hydroacoustic data (21 of the 27 overall deployments), speed was additionally calculated from the RMS amplitude of flow noise on the hydrophones (Goldbogen et al., 2006; Simon et al., 2009). The acoustic noise in the 66–94 Hz frequency band was calculated from 1 s bins around each data point, and the RMS amplitude was regressed against OCDR using SpeedFromRMS.m. For most varieties of biologging device, an anti-aliasing, pre-digitization high-pass filter is applied to both acoustic and accelerometer data – in the case of acoustics, specifically to reduce flow noise – so care must be taken to choose a frequency band that is not adversely affected by the filtering.
The amplitude of tag jiggle predictably increased with forward speeds greater than ∼1 m s−1 across all tag deployments and tag types. We confirmed the jiggle–speed relationship in laboratory experiments and we clarified the accelerometer axes and frequency ranges (10–90 Hz) that provided the most robust predictors of speed (Fig. S3, Eqn 2). The lower workable limit of the method was deployment and tag specific with a mean (±s.d.) minimum detected speed of 0.9±0.3 m s−1. At the upper limit, two deep-diving fin whales with dart-attached Acousondes regularly exceeded 7 m s−1 on steep descents to 300 m with no apparent limitations in the method. In comparison, a flow-noise method used previously in the same species was limited to less than 5 m s−1 because of clipping on the hydrophone (Goldbogen et al., 2006).
We observed a single case of accelerometer clipping that was not associated with the tag breaking the water–air interface (Movie 2). In this case, a humpback whale with a CATS video tag deployed near the animal's head, the dynamic range of the accelerometer was set to its minimum value. The tri-axial tag jiggle method filtered at 10–90 Hz as described above resulted in an upper detection limit of 6.2 m s−1, but if we used a lower-amplitude 70–90 Hz frequency band on only the y-axis signal (which was perpendicular to gravity for the high-speed event), it reduced the effect of clipping on speed determination (Movie 2). In the Risso's dolphins, clipping was more common, occurring in two of the four deployments with accelerometers set to ±2 g for a total of 12.9 s out of 20.1 h of tag data.
Among all tag deployments and tag types, the jiggle amplitude was correlated with OCDR regardless of whether our analysis included data from individual or multiple accelerometer axes. For most tags, the z-axis accelerometer data slightly improved results, but the z-axis performed poorly in dart-attached tags (Fig. S3). The highest correlations were found using a multi-variate exponential model that included data from all three accelerometer axes (Eqn 2). This method increased mR2 by 0.11±0.07 (n=27) over the use of the vector magnitude of the three axes. Contrary to the tags in the flow tanks, for which including frequencies above 50 Hz did not improve results, R2 values of the correlation for in situ deployments improved across tag types by including frequencies up to ∼90 Hz (Fig. S3). This result implies that while the method can be used with sample rates as low as 40 Hz, sampling at rates higher than 180 Hz will improve speed estimation.
In 16 of 21 deployments where speed was also calculated from flow noise, the jiggle amplitude had a stronger correlation with OCDR, resulting in smaller prediction intervals (95% prediction interval 0.20±0.28 m s−1 smaller), than flow noise. The average difference between mR2 values for the 21 deployments was 0.07±0.11. Across all 27 in situ deployments, mR2 for the jiggle method was 0.82±0.09, while mean mR2 for the flow noise method was 0.76±0.16. As a further test and comparison of these methods, we analyzed data from a CATS tag (sampling at 40 Hz) and a DTAG (250 Hz) deployed simultaneously on the same animal (Fig. 2). The four data streams were comparable in both amplitude and inflection for both high- and low-speed events. The CATS tag detached earlier than the DTAG, first sliding back near the flukes. The faster speeds traveled by the peduncle while oscillating were recorded on the CATS tag as a 1 m s−1 difference in speed between the two tags (Fig. 2).
The method for determining speed from accelerometer jiggle has several notable improvements over previous methods (i.e. flow noise), but some limitations that were common to previous techniques persist. Specifically, our analyses suggest that the jiggle–speed method is: (1) resilient to changes in tag orientation, (2) combines multiple metrics (three accelerometer axes) into a single model (Eqn 2), (3) is less affected by ambient noises than the flow noise method (Fig. 3), (4) has a high theoretical maximum detection limit, (5) is calculated only from low-power sensors that already exist on most devices, (6) is not subject to signal attenuation from pre-digitization high-pass filtering, and (7) exhibits higher model coefficients of determination (compared with flow noise) in all tag deployments sampled higher than 50 Hz. In addition to the ubiquity of accelerometers, the jiggle method has some advantages over propeller-based speed sensors that are commonly analyzed at 1 Hz resolution (Miller et al., 2016; Sato et al., 2003), can stall at both high and low speeds, must be properly oriented in the flow, and, for deployments on animals in highly productive waters or that dive near the sediment, are subject to clogging with particulates.
Because of the potentially high dynamic range of accelerometers, the jiggle method could potentially provide additional and direct validation of the highest swimming speeds in apex predators like sailfish (10 m s−1) (Marras et al., 2015), white sharks (11 m s−1) (Martin and Hammerschlag, 2012) and pilot whales (9 m s−1) (Aguilar Soto et al., 2008). Typical test deployments (e.g. Fig. 1) did not approach the maximum measurable speed. For this example, a jiggle amplitude of 2 g would have correlated with a speed of 9.1 m s−1 (17.7 kn), and a full range amplitude of 4 g would have correlated with a speed of 11.0 m s−1. These values are above the normal swim speeds of most marine mammals and fish (Block et al., 1992) and within the theoretical range of maximum speeds (10–15 m s−1) for cavitation-free swimming for lunate-tailed fish and mammals (Iosilevskii and Weihs, 2008; Svendsen et al., 2016). As clipping was more commonly observed in smaller animals, we recommend increasing accelerometer range to ±4 g for non-baleen whale deployments, though in some systems this may reduce the sensitivity.
The minimum detectable speed for the jiggle method of ∼0.9 m s−1 captures the mean swimming speed of 87% of the species reviewed by Sato et al. (2007). To detect slower swim speeds using the jiggle method, however, multiple accelerometers with different sensitivities could be used within the same tag. Alternatively, a dedicated device such as a semi-rigid antenna or dome that would vibrate or exhibit omnidirectional displacement in flow could be more sensitive to lower-speed flows. Currently, lower swim speeds are best measured by propeller-based systems (e.g. Sato et al., 2003).
Like any process that relies on models to make predictions outside of the observed data, the jiggle method has error associated with extrapolation from regression. Nevertheless, two tags on the same animal gave nearly identical speeds using the jiggle method (Fig. 2), with a mean difference between tags for data below 20 m of 0.16±0.14 m s−1. Additionally, substantial variance in the regression is likely due to inaccuracies in the OCDR metric, particularly during active stroking periods when pitch may deviate from the direction of forward travel (e.g. a 45 deg pitch with a 10 deg offset from the actual direction of travel would result in OCDR errors of 19%). When speed was measured in the flow tank, jiggle amplitude was more tightly correlated with speed (mean R2 values were 0.97±0.02 at the frequency range and axis with the highest correlation).
A final implication of the accelerometer–speed relationship is that biologically relevant signals may be obfuscated by high-frequency accelerometer sampling during high-speed events, and caution should be used when analyzing accelerometer signals [e.g. accelerometer jerk (Simon et al., 2012; Ydesen et al., 2014) and acoustic calls (Goldbogen et al., 2014)] that could occur simultaneously with high-speed events. Additionally, animals that do not themselves experience forces above a typical accelerometer sensitivity of ±2 g may nevertheless have datasets with clipped accelerometer readings due to tag jiggle at high speed, and these periods should be scrutinized to ensure that orientation estimation is not affected during these biologically important high-speed events. In conclusion, our analysis provides a greater ability to predict and understand these periods of high-amplitude accelerometer signals that have previously been treated as background noise (Saddler et al., 2017; Stimpert et al., 2015), and details a method for utilizing these signals to estimate animal speed over a considerable range of values.
DTAG deployments were conducted as part of the SoCal BRS project led by Brandon Southall and raw tag data were processed by Stacy DeRuiter, Alison Stimpert and Ann Allen. Thanks should also be extended to Elliott Hazen for his feedback on the multi-variate method, to Mark Johnson, Stacy DeRuiter and Alison Stimpert who wrote foundational code on which this method was built, and to two anonymous reviewers who provided helpful feedback.
Conceptualization: D.E.C., J.A.G.; Methodology: D.E.C.; Software: D.E.C.; Formal analysis: D.E.C.; Investigation: D.E.C., K.R.B., J.A.C., A.S.F.; Writing - original draft: D.E.C., J.A.G.; Writing - review & editing: D.E.C., K.R.B., J.A.C., A.S.F., J.A.G.; Project administration: J.A.G.; Funding acquisition: J.A.C., J.A.G.
DTAG deployments were funded under grants from the US Navy's Living Marine Resources Program and the Office of Naval Research Marine Mammal Program. Monterey Bay CATS tag deployments were funded by grants from the American Cetacean Society Monterey and San Francisco Bay chapters, and by the Meyers Trust. Support for D.E.C. was provided by Stanford University's Anne T. and Robert M. Bass Fellowship and for J.A.G. by the Office of Naval Research's Young Investigator Award (N00014-16-1-2477) and the National Science Foundation Integrative Organismal Systems award no. 1656691 and the Office of Polar Programs Antarctic Organisms and Ecosystems award no. 1644209.
An example data set as well as Matlab scripts for implementation of the method are available at: https://purl.stanford.edu/gd922zq9141.
(1992). Direct measurement of swimming speeds and depth of blue marlin. J. Exp. Biol. 166, 267-284.
(1999). Fundamentals of Fluid Mechanics. Hoboken, NJ, USA: John Wiley & Sons.
(1993). Fish Swimming. Dordrecht: Springer Science & Business Media.
(1988). Dead reckoning: a new technique for determining penguim movements at sea. Meeresforschung 32, 155-158.


It was only 10 months ago that the online boutique marketplace Farfetch raised $66 million to finance its international expansion and take its business into the real world with a click-and-collect service, but the startup has gone and done it again. On Wednesday morning, Farfetch announced that it's closed its fifth round of funding at $86 million.
Condé Nast International and Vitruvian Partners, already investors in the company, came back to participate in the round, which was led by DST Global. In case you were wondering, this investment puts Farfetch's total backing at nearly $200 million.
What's Farfetch doing with all that money? According to a release from the company, the same things as last time: international expansion and omnichannel initiatives like same-day delivery in new global markets. For the former, that will mean launching new local language sites in German, Korean and Spanish, entering new markets, and adding suppliers from Japan and Australia to its global roster of boutiques and brands.
With these operationally expensive maneuvers, Farfetch has been building a network that's both global and very local. Its click-and-collect service, which it launched in November just in time for the holiday rush, gave customers the option to order products from any boutique in Farfetch's universe and pick it up from another. Delivering on both levels is a big task for a company that's only been around since 2007, but hey, at least it's got the cash to make it happen.
Today, in its biggest e-commerce investment yet, Condé Nast International has announced a $20 million stake in Farfetch.com, a really cool e-commerce site through which you can shop the inventories of high-end boutiques all around the world, from Browns in London to, most recently, Fivestory in NYC.
The online trunk show startup is gearing up for big growth, including a revamped version of its site launching this spring.


text:
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package org.apache.camel.component.jpa;

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        case "scheduledexecutorservice":
        case "scheduledExecutorService": target.setScheduledExecutorService(property(camelContext, java.util.concurrent.ScheduledExecutorService.class, value)); return true;
        case "scheduler": target.setScheduler(property(camelContext, java.lang.Object.class, value)); return true;
        case "schedulerproperties":
        case "schedulerProperties": target.setSchedulerProperties(property(camelContext, java.util.Map.class, value)); return true;
        case "sendemptymessagewhenidle":
        case "sendEmptyMessageWhenIdle": target.setSendEmptyMessageWhenIdle(property(camelContext, boolean.class, value)); return true;
        case "sharedentitymanager":
        case "sharedEntityManager": target.setSharedEntityManager(property(camelContext, boolean.class, value)); return true;
        case "skiplockedentity":
        case "skipLockedEntity": target.setSkipLockedEntity(property(camelContext, boolean.class, value)); return true;
        case "startscheduler":
        case "startScheduler": target.setStartScheduler(property(camelContext, boolean.class, value)); return true;
        case "timeunit":
        case "timeUnit": target.setTimeUnit(property(camelContext, java.util.concurrent.TimeUnit.class, value)); return true;
        case "transacted": target.setTransacted(property(camelContext, boolean.class, value)); return true;
        case "useexecuteupdate":
        case "useExecuteUpdate": target.setUseExecuteUpdate(property(camelContext, java.lang.Boolean.class, value)); return true;
        case "usefixeddelay":
        case "useFixedDelay": target.setUseFixedDelay(property(camelContext, boolean.class, value)); return true;
        case "usepassedinentitymanager":
        case "usePassedInEntityManager": target.setUsePassedInEntityManager(property(camelContext, boolean.class, value)); return true;
        case "usepersist":
        case "usePersist": target.setUsePersist(property(camelContext, boolean.class, value)); return true;
        default: return false;
        }
    }

    @Override
    public Class<?> getOptionType(String name, boolean ignoreCase) {
        switch (ignoreCase ? name.toLowerCase() : name) {
        case "backofferrorthreshold":
        case "backoffErrorThreshold": return int.class;
        case "backoffidlethreshold":
        case "backoffIdleThreshold": return int.class;
        case "backoffmultiplier":
        case "backoffMultiplier": return int.class;
        case "bridgeerrorhandler":
        case "bridgeErrorHandler": return boolean.class;
        case "consumedelete":
        case "consumeDelete": return boolean.class;
        case "consumelockentity":
        case "consumeLockEntity": return boolean.class;
        case "delay": return long.class;
        case "deletehandler":
        case "deleteHandler": return org.apache.camel.component.jpa.DeleteHandler.class;
        case "entitymanagerproperties":
        case "entityManagerProperties": return java.util.Map.class;
        case "exceptionhandler":
        case "exceptionHandler": return org.apache.camel.spi.ExceptionHandler.class;
        case "exchangepattern":
        case "exchangePattern": return org.apache.camel.ExchangePattern.class;
        case "findentity":
        case "findEntity": return boolean.class;
        case "flushonsend":
        case "flushOnSend": return boolean.class;
        case "greedy": return boolean.class;
        case "initialdelay":
        case "initialDelay": return long.class;
        case "jointransaction":
        case "joinTransaction": return boolean.class;
        case "lazystartproducer":
        case "lazyStartProducer": return boolean.class;
        case "lockmodetype":
        case "lockModeType": return javax.persistence.LockModeType.class;
        case "maxmessagesperpoll":
        case "maxMessagesPerPoll": return int.class;
        case "maximumresults":
        case "maximumResults": return int.class;
        case "namedquery":
        case "namedQuery": return java.lang.String.class;
        case "nativequery":
        case "nativeQuery": return java.lang.String.class;
        case "parameters": return java.util.Map.class;
        case "persistenceunit":
        case "persistenceUnit": return java.lang.String.class;
        case "pollstrategy":
        case "pollStrategy": return org.apache.camel.spi.PollingConsumerPollStrategy.class;
        case "predeletehandler":
        case "preDeleteHandler": return org.apache.camel.component.jpa.DeleteHandler.class;
        case "query": return java.lang.String.class;
        case "remove": return boolean.class;
        case "repeatcount":
        case "repeatCount": return long.class;
        case "resultclass":
        case "resultClass": return java.lang.Class.class;
        case "runlogginglevel":
        case "runLoggingLevel": return org.apache.camel.LoggingLevel.class;
        case "scheduledexecutorservice":
        case "scheduledExecutorService": return java.util.concurrent.ScheduledExecutorService.class;
        case "scheduler": return java.lang.Object.class;
        case "schedulerproperties":
        case "schedulerProperties": return java.util.Map.class;
        case "sendemptymessagewhenidle":
        case "sendEmptyMessageWhenIdle": return boolean.class;
        case "sharedentitymanager":
        case "sharedEntityManager": return boolean.class;
        case "skiplockedentity":
        case "skipLockedEntity": return boolean.class;
        case "startscheduler":
        case "startScheduler": return boolean.class;
        case "timeunit":
        case "timeUnit": return java.util.concurrent.TimeUnit.class;
        case "transacted": return boolean.class;
        case "useexecuteupdate":
        case "useExecuteUpdate": return java.lang.Boolean.class;
        case "usefixeddelay":
        case "useFixedDelay": return boolean.class;
        case "usepassedinentitymanager":
        case "usePassedInEntityManager": return boolean.class;
        case "usepersist":
        case "usePersist": return boolean.class;
        default: return null;
        }
    }

    @Override
    public Object getOptionValue(Object obj, String name, boolean ignoreCase) {
        JpaEndpoint target = (JpaEndpoint) obj;
        switch (ignoreCase ? name.toLowerCase() : name) {
        case "backofferrorthreshold":
        case "backoffErrorThreshold": return target.getBackoffErrorThreshold();
        case "backoffidlethreshold":
        case "backoffIdleThreshold": return target.getBackoffIdleThreshold();
        case "backoffmultiplier":
        case "backoffMultiplier": return target.getBackoffMultiplier();
        case "bridgeerrorhandler":
        case "bridgeErrorHandler": return target.isBridgeErrorHandler();
        case "consumedelete":
        case "consumeDelete": return target.isConsumeDelete();
        case "consumelockentity":
        case "consumeLockEntity": return target.isConsumeLockEntity();
        case "delay": return target.getDelay();
        case "deletehandler":
        case "deleteHandler": return target.getDeleteHandler();
        case "entitymanagerproperties":
        case "entityManagerProperties": return target.getEntityManagerProperties();
        case "exceptionhandler":
        case "exceptionHandler": return target.getExceptionHandler();
        case "exchangepattern":
        case "exchangePattern": return target.getExchangePattern();
        case "findentity":
        case "findEntity": return target.isFindEntity();
        case "flushonsend":
        case "flushOnSend": return target.isFlushOnSend();
        case "greedy": return target.isGreedy();
        case "initialdelay":
        case "initialDelay": return target.getInitialDelay();
        case "jointransaction":
        case "joinTransaction": return target.isJoinTransaction();
        case "lazystartproducer":
        case "lazyStartProducer": return target.isLazyStartProducer();
        case "lockmodetype":
        case "lockModeType": return target.getLockModeType();
        case "maxmessagesperpoll":
        case "maxMessagesPerPoll": return target.getMaxMessagesPerPoll();
        case "maximumresults":
        case "maximumResults": return target.getMaximumResults();
        case "namedquery":
        case "namedQuery": return target.getNamedQuery();
        case "nativequery":
        case "nativeQuery": return target.getNativeQuery();
        case "parameters": return target.getParameters();
        case "persistenceunit":
        case "persistenceUnit": return target.getPersistenceUnit();
        case "pollstrategy":
        case "pollStrategy": return target.getPollStrategy();
        case "predeletehandler":
        case "preDeleteHandler": return target.getPreDeleteHandler();
        case "query": return target.getQuery();
        case "remove": return target.isRemove();
        case "repeatcount":
        case "repeatCount": return target.getRepeatCount();
        case "resultclass":
        case "resultClass": return target.getResultClass();
        case "runlogginglevel":
        case "runLoggingLevel": return target.getRunLoggingLevel();
        case "scheduledexecutorservice":
        case "scheduledExecutorService": return target.getScheduledExecutorService();
        case "scheduler": return target.getScheduler();
        case "schedulerproperties":
        case "schedulerProperties": return target.getSchedulerProperties();
        case "sendemptymessagewhenidle":
        case "sendEmptyMessageWhenIdle": return target.isSendEmptyMessageWhenIdle();
        case "sharedentitymanager":
        case "sharedEntityManager": return target.isSharedEntityManager();
        case "skiplockedentity":
        case "skipLockedEntity": return target.isSkipLockedEntity();
        case "startscheduler":
        case "startScheduler": return target.isStartScheduler();
        case "timeunit":
        case "timeUnit": return target.getTimeUnit();
        case "transacted": return target.isTransacted();
        case "useexecuteupdate":
        case "useExecuteUpdate": return target.getUseExecuteUpdate();
        case "usefixeddelay":
        case "useFixedDelay": return target.isUseFixedDelay();
        case "usepassedinentitymanager":
        case "usePassedInEntityManager": return target.isUsePassedInEntityManager();
        case "usepersist":
        case "usePersist": return target.isUsePersist();
        default: return null;
        }
    }

    @Override
    public Object getCollectionValueType(Object target, String name, boolean ignoreCase) {
        switch (ignoreCase ? name.toLowerCase() : name) {
        case "deletehandler":
        case "deleteHandler": return java.lang.Object.class;
        case "entitymanagerproperties":
        case "entityManagerProperties": return java.lang.Object.class;
        case "parameters": return java.lang.Object.class;
        case "predeletehandler":
        case "preDeleteHandler": return java.lang.Object.class;
        case "resultclass":
        case "resultClass": return java.lang.Object.class;
        case "schedulerproperties":
        case "schedulerProperties": return java.lang.Object.class;
        default: return null;
        }
    }
}

redpajama_set_name: RedPajamaGithub


text:
La croix de Créteuil de Chaudenay est une croix de chemin située sur le territoire de la commune de Chaudenay dans le département français de Saône-et-Loire et la région Bourgogne-Franche-Comté.

Historique

Elle fait l'objet d'une inscription au titre des monuments historiques depuis le .

Articles connexes
 Liste des monuments historiques de Saône-et-Loire

Références

Monument historique inscrit en 1927
Monument historique en Saône-et-Loire
Charnay

redpajama_set_name: RedPajamaWikipedia


text:
16-year-old faces magistrate for 2018 murder
September deadline for schools to ban sugary drinks
Laura Dowrich-Phillips Created : 13 May 2017 T&T News
Soft drinks, flavoured water and juices will be among the beverages missing from school cafeterias and canteens come September.
In a circular issued to schools on May 5, the Ministry of Education said Cabinet has taken a decision to restrict the sale or serving of sugar sweet beverages in Government and Government-assisted schools.
These include soft drinks, juice drinks, sports/energy drinks, flavoured water, tea, coffee and milk based drinks with added sugars and/or artificial sweeteners.
Only 100 percent fruit juices, low-fat milk, blended vegetables or fruit drinks with no added sugars and/or artificial sweeteners.
The Ministry advised that the changes should be done in a phased manner with all cafeterias/canteens in full compliance by September.
In January, Health Minister Terrence Deyalsingh said from April sugary drinks would be banned from schools.
He said the high prevalence of childhood obesity led to the early onset of non-communicable diseases (NCDS), in particular, hypertension.
He said the four key strategic objectives of the plan for NCDs included multi-sectoral policies and partnerships for NCD prevention and control, NCD risk factors and protective factors, health system response to NCDs and risk factors and NCD surveillance and research.
He said the ministry was also collaborating with the Education Ministry to implement these initiatives and called for children to be drinking more water.
What happens to your brain when you give up sugar
Children's Authority appeals to public to report abuse to Hotline
Sweet Sereni-tea serves the world of teas

redpajama_set_name: RedPajamaCommonCrawl


text:
Skip to main content Skip to footer links
Home Regional Program Corridor Program Local Program Project Explorer What's New Contact Us Get Notifications FAQ
We're hard at work to put mobility, safety and connectivity projects funded by the Austin Mobility Bonds on the ground. Here's where you'll find the latest news about Local, Corridor and Regional mobility improvements, including opportunities to get involved.
Technical Assistance Workshop
On November 3, 2021, the City of Austin sponsored a virtual Technical Assistance Workshop aimed to build capacity and offer insight in preparation for upcoming construction-related Corridor Mobility Bond projects. Three (3) local area industry service providers offered expertise and shared insights on understanding Financial Statements and securing Construction Bonds and Working Capital. To look at the presentation click on this link.
Click on the links below to read recent news releases regarding various projects and initiatives funded by the Austin Mobility Bonds.
Show the City Where You Want to See Walking and Biking Route Improvements with New Public Input Map (January 2022): Austin Public Works and Austin Transportation launched a Public Input Map that enables residents to show the City exactly where they'd like to see improvements to Austin's urban trails, bikeways, and street crossings. The map is open through March 6 and is part of ATX Walk Bike Roll, a project to update Austin's Urban Trails, Bikeways, and Sidewalk plans.
Bergstrom Spur Corridor Study Wins State-Level Achievement Award for Transportation Planning, Kicks-Off Design of Trail (December 2021): The City of Austin Public Works Urban Trails Program and Capital Area Metropolitan Planning Organization (CAMPO) are proud to announce that they have been awarded the Planning Achievement Award for Transportation Planning from the Texas Chapter of the American Planning Association for the Bergstrom Spur Corridor Study.
City of Austin Corridor Program Office Teams up with Austin PBS (November 2021): The City of Austin Corridor Program Office (CPO) is partnering with Austin PBS on an initiative to engage children and residents along Austin corridors, beginning with Airport Boulevard. The goals of this initiative are to understand how the community uses current mobility; to create a family destination at Austin PBS' new Airport Blvd. location; and to encourage the community to travel the corridor to Austin PBS and other destinations using mobility options improved through CPO's Corridor Construction Program.
Construction Will Soon Extend the Northern Walnut Creek Urban Trail (October 2021): The Northern Walnut Creek Trail will gain one mile in length by the end of 2022. In partnership with the Austin Parks and Recreation Department, Austin Public Works' Urban Trails Program will begin construction on Northern Walnut Creek Trail Section 2A later this month.
Provide Feedback on Austin's Sidewalks, Urban Trails, and Bikeways (August 2021): Austin Public Works and Austin Transportation invite the community to provide feedback that will help shape the future of Austin's streets, sidewalks, and urban trails. A survey is open now through September 26 for ATX Walk Bike Roll, a project to update plans that determine where and when to build the City's pedestrian and bicycle routes.
Longhorn Dam Bridge to close Saturday night (August 2021): Beginning Saturday, August 7, 2021, at 10 p.m., Austin Transportation Department will close South Pleasant Valley Road to vehicular traffic in both directions at Longhorn Dam Bridge for approximately eight hours as crews adjust the traffic control set up on the bridge. Pedestrian and bicycle access across the bridge will remain intact throughout the night.
Local Artists to Install Community-Centered Artwork Along Austin Corridors (August 2021): On Thursday, July 29, 2021, Austin City Council authorized the Economic Development Department (EDD) to execute contracts with four artists/artist teams. This selection will result in artwork installation along roadways included in the Corridor Construction Program. To-date, City Council has approved a total of six artists/artist teams, including the most recent four, to participate in this initiative.
New shared use path to open on east side of Longhorn Dam bridge (June 2021): As work continues on interim safety and mobility improvements to South Pleasant Valley Road over the Longhorn Dam bridge, the construction work zone will shift from the east side of the bridge to the west side on Sunday, June 27. Austin Transportation will establish a new temporary trail detour on Monday, June 28.
View our January 2022 e-Newsletter and get information on topics including:
Burnet Road Bid Alert
Anderson Mill Road Regional Mobility Project Complete
Pedestrian Hybrid Beacons on William Cannon Drive
I-35 Cap and Stitch Survey
View previous e-Newsletters by clicking on the links below:
Briefings to City Council, Boards & Commissions
City staff regularly provide briefings about the progress being made to implement the 2016 Mobility Bond and related programs and activities. These meetings are open to the public, and attendees have the opportunity to provide comments during citizen communication. The following is a list of upcoming briefings:
Check back later for more updates!
Home Contact Us Get Notifications Project Explorer
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© 2022 City of Austin


By now, you're used to seeing my weekly interviews with moms of all sorts from all over the country on my blog and in your inbox.
But recently, PsychCentral turned the tables and asked to interview ME! So, if you'd like to know more about why I do what I do, what I'm most passionate about, and what I want ALL moms to know, click through to check it out.


Pleasant Valley Community School District Celebrating 2017!
Thank you to the students, faculty, staff, parents, and community members who made 2016-17 such a great year! Enjoy the pictures below from the last few days of school!
Bridgeview students spent the last Friday before the end of the year celebrating a great year by visiting several stations with their school family groups.
Cody students celebrated the last day of school with a field day!
Hopewell students enjoyed the beautiful day, playing outside on the last day of school!
Pleasant View students spoke about what they liked best this year and what they expect to achieve next year, before getting a send-off from faculty and staff.
Riverdale Heights students watched the faculty versus 6th grade kickball game and took a school picture for Will Kohn.
Students spent the last day of school writing letters to future 7th graders and some got to play a game of kick ball!


text:
Additional matchday parking now available
Additional matchday parking has become available to Wolves supporters attending matches at Molineux during the 2019/20 season.
Wolves have entered an agreement with Wolverhampton Racecourse and Event Support Team Limited, which will see matchday parking become available at the Racecourse, within walking distance of Molineux.
Spaces are available to pre-order at wolverhamptonracecourseparking.co.uk for £5 per match, with parking still available to purchase for Saturday's Premier League clash with Watford at Molineux.
Entry to the Racecourse on Saturday will be open from midday, three hours before kick-off.
England under-21s to play three matches at Molineux
Inside The Museum | Unveiling the 'new' Molineux
Visit Molineux from your home
I love coming here every day, I love being part of this football club.


UPDATE: LINE, BBM on Board for In-Country Office Plans, The Jakarta Globe Indonesia's Communications and Information Minister Rudiantara said that during a recent visit to Silicon Valley, President Joko Widodo (or "Jokowi" for short) called on giant tech companies like Facebook, Twitter, and Netflix to open their branch offices in Indonesia. (Photo credit: GovInsider.Asia) The purpose, as … Continue reading Pay up or what, Indonesia?
Posted in IndonesiaTagged censorship, filtering, LGBT, RudiantaraLeave a Comment on Pay up or what, Indonesia?


This episode of InConversation features Lenny Abrahamson. His first feature Adam & Paul (2004) was launched at the Berlin International Film Festival, Telluride and Galway among many prestigious film festivals. Garage (2007) was awarded the CICAE Award upon its presentation at Cannes Directors' Fortnight. The film also won awards for Best Film, Best Director, Best Script and Best Actor at the 2008 Irish Film and Television Awards. In the same year Abrahamson also directed Prosperity, four one-hour TV films for RTÉ.
What Richard Did (2012), his third feature, premiered at the 2012 Toronto International Film Festival and was released to critical acclaim winning multiple awards in Ireland, best screenplay at the London Evening Standard awards, and best film at the Istanbul Film Festival.
Frank (2014) had its world premiere at the Sundance Film Festival. Abrahamson's next project is the adaptation of Emma Donoghue's hit novel Room.


Located in the Old Shoe Factory in downtown Brampton, Kaulika Yoga and Pilates offers a unique and eclectic space to explore your Yoga practice. The studio is warm and inviting, and acts as haven and resting stop before or after a long commute, day of work or busy day at home. Offering a wide range of classes in both heated and non-heated rooms, we have something for everyone.


This one has beautiful colors and an adorable layout, but it's geared toward little ones. I love that there's plenty of room in the cubes for more books because, believe me, there will be more! I also love the house-shaped bookshelf. If you start homeschooling young then your homeschooling room will gradually change from a playroom to a homeschooling room. Your kids will connect fun with learning because learning is supposed to be fun.
This one is set up in a kids' room with an entire wall devoted to homeschool learning. There are two computers, a desktop and a laptop, but an amazing lack of books. Let's hope there are more in the living room of the house. Limiting your children to online learning is just that, limiting. Books are more in depth and provide a deeper understanding of subjects. My last complaint–the chairs look really uncomfortable. If your kids aren't comfortable, they aren't going to want to sit for long and that makes learning not so fun.
This homeschooling room is set up for three kids, or at least three kids, with three laptops ready and raring to go, many cubes for books, and a nice big table for crafting, artwork, science, and whatever else comes along. Once again though, what's up with the really uncomfortable chairs and why aren't there any windows?
This is one of my favorite homeschooling rooms. There's a Twister mat on the floor for fun and tons of natural light which is really healthy for developing minds. You don't want them to feel like they're learning in a dark dimly lit dungeon. The chairs have chair pads and are sturdy and comfortable. The bookshelves are above and out of the way, leaving the kids plenty of space to work. I also have a fondness for globes, so I love that there's one right there on the counter next to the clock. Now take a look to the left. See the window seat? I love window seats for kids. They're awesome.
This is another one of my favorites, thanks to the many cubes for storing books and the window seat!! This one is makeshift from materials available, not a fancy store-bought or already installed window seat. You really can make your own window seat. Put tall bookshelves on either side of the window and place a bench between them. The green walls are also bright and cheery as is the natural light.
This is another favorite, maybe because I have artists in my family. There's an artboard (aka bulletin board) for placing completed artwork or art pieces in the process of drying, a chalkboard for inspiration and planning, and an easel with rolling paper for the artist at work. The giraffe made of papier mache is priceless. Lots of natural light and big windows. The only thing I didn't like about this room was the chairs. Sturdy, yes. Comfortable, no.
This room is beautiful. I'll tell you why. There are plenty of nooks for kids' mementos or cherished works of art and yet still enough room for books. There are three ergonomic chairs and room for laptops, books, and everything else a homeschooled kid needs. And look at the windows, big and beautiful with plenty of natural light and shades. Yep, shades. On the left wall you can see slots for bigger board games. Board games are a wonderful way to learn strategy and reasoning skills (like Clue).
This room makes good use of space and seems to have every subject covered. The problem is that there are no bookshelves. I'm hoping they are out of the picture somewhere lining the walls. The clutter on top of the cubby is also jarring. When kids make something special, it should have its own special spot, a showcase, until another special something is made to take its place. Shoving them all onto the top of a cubby is not so special. But I love the green paint on the cubby. The hanging light bulbs, not so much. It looks like a safety hazard.
This one has a little bit of everything–a table, a piano, bookshelves, a computer desk, an aquarium, and plants. The perfect learning environment. It's a little dark and, yes, I realize the window shade is closed, but still there should be more windows and natural light.
Okay, I'm not really giving out awards, but if I was, this is the room that would win. Homeschooling Room 7 which has everything a learning kid could need.


text:
Microsoft » Windows Vista : Security Vulnerabilities (CVSS score between 5 and 6.99)
1	 CVE-2018-7249 362 2018-02-26 2018-03-22
None Local Medium Not required Complete Complete Complete
An issue was discovered in secdrv.sys as shipped in Microsoft Windows Vista, Windows 7, Windows 8, and Windows 8.1 before KB3086255, and as shipped in Macrovision SafeDisc. Two carefully timed calls to IOCTL 0xCA002813 can cause a race condition that leads to a use-after-free. When exploited, an unprivileged attacker can run arbitrary code in the kernel.
2	 CVE-2017-0155 +Priv 2017-04-12 2019-10-03
The Graphics component in the kernel in Microsoft Windows Vista SP2; Windows Server 2008 SP2 and R2 SP1; and Windows 7 SP1 allows local users to gain privileges via a crafted application, aka "Windows Graphics Elevation of Privilege Vulnerability."
3	 CVE-2017-0101 119 Overflow +Priv 2017-03-17 2018-04-19
None Remote Medium Not required Partial Partial Partial
The kernel-mode drivers in Transaction Manager in Microsoft Windows Vista SP2; Windows Server 2008 SP2 and R2; Windows 7 SP1; Windows 8.1, Windows Server 2012 Gold and R2, Windows RT 8.1; Windows 10 Gold, 1511, and 1607; and Windows Server 2016 allow local users to gain privileges via a crafted application, aka "Windows Elevation of Privilege Vulnerability."
The Graphics Device Interface (GDI) in Microsoft Windows Vista SP2; Windows Server 2008 SP2 and R2 SP1; Windows 7 SP1; Windows 8.1; Windows Server 2012 Gold and R2; Windows RT 8.1; and Windows 10 Gold, 1511, and 1607 allows local users to gain privileges via a crafted application, aka "Windows GDI Elevation of Privilege Vulnerability." This vulnerability is different from those described in CVE-2017-0001, CVE-2017-0025, and CVE-2017-0047.
5	 CVE-2016-7237 284 DoS 2016-11-10 2018-10-12
None Remote Low ??? None None Complete
Local Security Authority Subsystem Service (LSASS) in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8.1, Windows Server 2012 Gold and R2, Windows RT 8.1, Windows 10 Gold, 1511, and 1607, and Windows Server 2016 allows remote authenticated users to cause a denial of service (system hang) via a crafted request, aka "Local Security Authority Subsystem Service Denial of Service Vulnerability."
6	 CVE-2016-3263 200 Bypass +Info 2016-10-14 2018-10-12
None Remote Low Not required Partial None None
Graphics Device Interface (aka GDI or GDI+) in Microsoft Windows Vista SP2; Windows Server 2008 SP2 and R2 SP1; Windows 7 SP1; Windows 8.1; Windows Server 2012 Gold and R2; Windows RT 8.1; Windows 10 Gold, 1511, and 1607; Office 2007 SP3; Office 2010 SP2; Word Viewer; Skype for Business 2016; Lync 2013 SP1; Lync 2010; Lync 2010 Attendee; and Live Meeting 2007 Console allows remote attackers to bypass the ASLR protection mechanism via unspecified vectors, aka "GDI+ Information Disclosure Vulnerability," a different vulnerability than CVE-2016-3262.
8	 CVE-2016-3237 264 Bypass 2016-08-09 2019-05-20
Kerberos in Microsoft Windows Vista SP2; Windows Server 2008 SP2 and R2 SP1; Windows 7 SP1; Windows 8.1; Windows Server 2012 Gold and R2; Windows RT 8.1; and Windows 10 Gold, 1511, and 1607 allows man-in-the-middle attackers to bypass authentication via vectors related to a fallback to NTLM authentication during a domain account password change, aka "Kerberos Security Feature Bypass Vulnerability."
9	 CVE-2016-3225 264 +Priv 2016-06-16 2018-10-12
The SMB server component in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8.1, Windows Server 2012 Gold and R2, Windows RT 8.1, and Windows 10 Gold and 1511 allows local users to gain privileges via a crafted application that forwards an authentication request to an unintended service, aka "Windows SMB Server Elevation of Privilege Vulnerability."
10	 CVE-2016-3221 264 +Priv 2016-06-16 2018-10-12
The kernel-mode drivers in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8.1, Windows Server 2012 Gold and R2, Windows RT 8.1, and Windows 10 Gold and 1511 allow local users to gain privileges via a crafted application, aka "Win32k Elevation of Privilege Vulnerability," a different vulnerability than CVE-2016-3218.
atmfd.dll in the Adobe Type Manager Font Driver in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8.1, Windows Server 2012 Gold and R2, Windows RT 8.1, and Windows 10 Gold and 1511 allows local users to gain privileges via a crafted application, aka "ATMFD.dll Elevation of Privilege Vulnerability."
13	 CVE-2016-3209 200 Bypass +Info 2016-10-14 2018-10-12
Graphics Device Interface (aka GDI or GDI+) in Microsoft Windows Vista SP2; Windows Server 2008 SP2 and R2 SP1; Windows 7 SP1; Windows 8.1; Windows Server 2012 Gold and R2; Windows RT 8.1; Windows 10 Gold, 1511, and 1607; Office 2007 SP3; Office 2010 SP2; Word Viewer; Skype for Business 2016; Lync 2013 SP1; Lync 2010; Lync 2010 Attendee; Live Meeting 2007 Console; .NET Framework 3.0 SP2, 3.5, 3.5.1, 4.5.2, and 4.6; and Silverlight 5 allows remote attackers to bypass the ASLR protection mechanism via unspecified vectors, aka "True Type Font Parsing Information Disclosure Vulnerability."
14	 CVE-2016-0128 254 2016-04-12 2019-09-27
None Remote Medium Not required Partial Partial None
The SAM and LSAD protocol implementations in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8.1, Windows Server 2012 Gold and R2, Windows RT 8.1, and Windows 10 Gold and 1511 do not properly establish an RPC channel, which allows man-in-the-middle attackers to perform protocol-downgrade attacks and impersonate users by modifying the client-server data stream, aka "Windows SAM and LSAD Downgrade Vulnerability" or "BADLOCK."
15	 CVE-2016-0091 20 Exec Code 2016-03-09 2018-10-12
OLE in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8.1, Windows Server 2012 Gold and R2, Windows RT 8.1, and Windows 10 Gold and 1511 allows remote attackers to execute arbitrary code via a crafted file, aka "Windows OLE Memory Remote Code Execution Vulnerability," a different vulnerability than CVE-2016-0092.
The sandbox implementation in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, Windows RT Gold and 8.1, and Windows 10 Gold and 1511 mishandles reparse points, which allows local users to gain privileges via a crafted application, aka "Windows Mount Point Elevation of Privilege Vulnerability," a different vulnerability than CVE-2016-0006.
18	 CVE-2015-6112 310 +Info 2015-11-11 2019-05-16
SChannel in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 lacks the required extended master-secret binding support to ensure that a server's X.509 certificate is the same during renegotiation as it was before renegotiation, which allows man-in-the-middle attackers to obtain sensitive information or modify TLS session data via a "triple handshake attack," aka "Schannel TLS Triple Handshake Vulnerability."
The kernel in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, Windows RT Gold and 8.1, and Windows 10 Gold and 1511 allows local users to gain privileges via a crafted application, aka "Windows Kernel Memory Elevation of Privilege Vulnerability," a different vulnerability than CVE-2015-6100.
21	 CVE-2015-2546 119 Overflow +Priv Mem. Corr. 2015-09-09 2019-05-14
The kernel-mode driver in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, Windows RT Gold and 8.1, and Windows 10 allows local users to gain privileges via a crafted application, aka "Win32k Memory Corruption Elevation of Privilege Vulnerability," a different vulnerability than CVE-2015-2511, CVE-2015-2517, and CVE-2015-2518.
22	 CVE-2015-2518 264 +Priv Mem. Corr. 2015-09-09 2019-05-14
25	 CVE-2015-2417 20 +Priv 2015-07-14 2019-05-08
None Remote Low Not required None Partial None
OLE in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 allows remote attackers to gain privileges via crafted input, as demonstrated by a transition from Low Integrity to Medium Integrity, aka "OLE Elevation of Privilege Vulnerability," a different vulnerability than CVE-2015-2416.
The Windows Installer service in Microsoft Windows Server 2003 SP2 and R2 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 allows local users to gain privileges via a custom action script associated with a .msi package, aka "Windows Installer EoP Vulnerability."
28	 CVE-2015-2369 Exec Code +Priv 2015-07-14 2018-10-12
Untrusted search path vulnerability in Windows Media Device Manager in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, and Windows 7 SP1 allows local users to gain privileges via a Trojan horse DLL in the current working directory, as demonstrated by a directory that contains a .rtf file, aka "DLL Planting Remote Code Execution Vulnerability."
29	 CVE-2015-1758 +Priv 2015-06-10 2018-10-12
Untrusted search path vulnerability in the LoadLibrary function in the kernel in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows Server 2012, and Windows RT allows local users to gain privileges via a Trojan horse DLL in an unspecified directory, aka "Windows LoadLibrary EoP Vulnerability."
Schannel in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 does not properly restrict Diffie-Hellman Ephemeral (DHE) key lengths, which makes it easier for remote attackers to defeat cryptographic protection mechanisms via unspecified vectors, aka "Schannel Information Disclosure Vulnerability."
The Service Control Manager (SCM) in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 does not properly constrain impersonation levels, which allows local users to gain privileges via a crafted application, aka "Service Control Manager Elevation of Privilege Vulnerability."
32	 CVE-2015-0095 476 DoS Bypass +Info 2015-03-11 2019-05-14
None Local Low Not required Partial None Complete
The kernel-mode drivers in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 allow local users to cause a denial of service (NULL pointer dereference and blue screen), or obtain sensitive information from kernel memory and possibly bypass the ASLR protection mechanism, via a crafted application, aka "Microsoft Windows Kernel Memory Disclosure Vulnerability."
Adobe Font Driver in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 allows remote attackers to obtain sensitive information from kernel memory, and possibly bypass the KASLR protection mechanism, via a crafted font, aka "Adobe Font Driver Information Disclosure Vulnerability," a different vulnerability than CVE-2015-0087.
35	 CVE-2015-0006 264 Bypass 2015-01-13 2018-10-12
None Local Network Low Not required None Complete None
The Network Location Awareness (NLA) service in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, and Windows Server 2012 Gold and R2 does not perform mutual authentication to determine a domain connection, which allows remote attackers to trigger an unintended permissive configuration by spoofing DNS and LDAP responses on a local network, aka "NLA Security Feature Bypass Vulnerability."
36	 CVE-2015-0003 476 DoS +Priv 2015-02-11 2019-05-14
win32k.sys in the kernel-mode drivers in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 allows local users to gain privileges or cause a denial of service (NULL pointer dereference) via a crafted application, aka "Win32k Elevation of Privilege Vulnerability."
The Graphics Component in Microsoft Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 does not properly process JPEG images, which makes it easier for remote attackers to bypass the ASLR protection mechanism via a crafted web site, aka "Graphics Component Information Disclosure Vulnerability."
DirectShow in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, and Windows Server 2012 Gold and R2 allows local users to gain privileges by leveraging control over a low-integrity process to execute a crafted application, aka "DirectShow Elevation of Privilege Vulnerability."
39	 CVE-2014-1811 399 DoS 2014-06-11 2019-05-16
None Remote Low Not required None None Partial
The TCP implementation in Microsoft Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 allows remote attackers to cause a denial of service (non-paged pool memory consumption and system hang) via malformed data in the Options field of a TCP header, aka "TCP Denial of Service Vulnerability."
40	 CVE-2014-0323 200 DoS +Info 2014-03-12 2019-05-13
None Local Low Not required Complete None Complete
win32k.sys in the kernel-mode drivers in Microsoft Windows XP SP2 and SP3, Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 allows local users to obtain sensitive information from kernel memory or cause a denial of service (system hang) via a crafted application, aka "Win32k Information Disclosure Vulnerability."
None Remote High Not required None Complete None
The Security Account Manager Remote (SAMR) protocol implementation in Microsoft Windows XP SP2 and SP3, Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, and Windows Server 2012 Gold and R2 does not properly determine the user-lockout state, which makes it easier for remote attackers to bypass the account lockout policy and obtain access via a brute-force attack, aka "SAMR Security Feature Bypass Vulnerability."
Untrusted search path vulnerability in Microsoft Windows XP SP2 and SP3, Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 allows local users to gain privileges via a Trojan horse cmd.exe file in the current working directory, as demonstrated by a directory that contains a .bat or .cmd file, aka "Windows File Handling Vulnerability."
43	 CVE-2013-5058 190 Overflow +Priv 2013-12-11 2019-05-13
Integer overflow in the kernel-mode drivers in Microsoft Windows XP SP2 and SP3, Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, and Windows Server 2012 Gold and R2 allows local users to gain privileges via a crafted application, aka "Win32k Integer Overflow Vulnerability."
44	 CVE-2013-3869 20 DoS 2013-11-13 2019-05-14
Microsoft Windows XP SP2 and SP3, Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, Windows 8.1, Windows Server 2012 Gold and R2, and Windows RT Gold and 8.1 allow remote attackers to cause a denial of service (daemon hang) via a web-service request containing a crafted X.509 certificate that is not properly handled during validation, aka "Digital Signatures Vulnerability."
Microsoft Active Directory Lightweight Directory Service (AD LDS) on Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, and Windows 8 and Active Directory Services on Windows Server 2008 SP2 and R2 SP1 and Server 2012 allow remote attackers to cause a denial of service (LDAP directory-service outage) via a crafted LDAP query, aka "Remote Anonymous DoS Vulnerability."
46	 CVE-2013-3660 119 1	 Overflow +Priv 2013-05-24 2018-10-12
The EPATHOBJ::pprFlattenRec function in win32k.sys in the kernel-mode drivers in Microsoft Windows XP SP2 and SP3, Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2 and R2 SP1, Windows 7 SP1, Windows 8, and Windows Server 2012 does not properly initialize a pointer for the next object in a certain list, which allows local users to obtain write access to the PATHRECORD chain, and consequently gain privileges, by triggering excessive consumption of paged memory and then making many FlattenPath function calls, aka "Win32k Read AV Vulnerability."
47	 CVE-2013-1293 DoS +Priv 2013-04-09 2020-09-28
The NTFS kernel-mode driver in Microsoft Windows Vista SP2, Windows Server 2008 SP2, R2, and R2 SP1, and Windows 7 Gold and SP1 allows local users to gain privileges or cause a denial of service (NULL pointer dereference and system crash) via a crafted application that leverages improper handling of objects in memory, aka "NTFS NULL Pointer Dereference Vulnerability."
Race condition in win32k.sys in the kernel-mode drivers in Microsoft Windows Vista SP2, Windows Server 2008 SP2, R2, and R2 SP1, Windows 7 Gold and SP1, Windows 8, Windows Server 2012, and Windows RT allows local users to gain privileges via a crafted application that leverages improper handling of objects in memory, aka "Win32k Race Condition Vulnerability."
Race condition in win32k.sys in the kernel-mode drivers in Microsoft Windows XP SP2 and SP3, Windows Server 2003 SP2, Windows Vista SP2, Windows Server 2008 SP2, R2, and R2 SP1, Windows 7 Gold and SP1, Windows 8, Windows Server 2012, and Windows RT allows local users to gain privileges via a crafted application that leverages improper handling of objects in memory, aka "Win32k Race Condition Vulnerability."
The SSL provider component in Microsoft Windows Vista SP2, Windows Server 2008 SP2, R2, and R2 SP1, Windows 7 Gold and SP1, Windows 8, Windows Server 2012, and Windows RT does not properly handle encrypted packets, which allows man-in-the-middle attackers to conduct SSLv2 downgrade attacks against (1) SSLv3 sessions or (2) TLS sessions by intercepting handshakes and injecting content, aka "Microsoft SSL Version 3 and TLS Protocol Security Feature Bypass Vulnerability."
Total number of vulnerabilities : 82 Page : 1 (This Page)2


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Tribunalele Poporului, compuse din Tribunalul Poporului din București și Tribunalul Poporului din Transilvania de Nord (cu sediul la Cluj), au fost două tribunale înființate după cel de-al doilea război mondial de guvernul României, împreună cu Comisia Aliată de Control pentru a ancheta prezumtivii criminali de război, conform art. 14 din Pactul de Armistițiu cu România.

Aproximativ 2.700 de cazuri au fost examinate de o comisie care a stabilit că existau dovezi suficiente pentru a trimite cca. jumătate din cazuri la parchet. 668 de inculpați au fost găsiți vinovați de crime de război, crime împotriva păcii și crime împotriva umanității.

Tribunalul din București a condamnat 187 de persoane.
Pe 14 februarie 1946 Tribunalul Poporului își reia activitatea prin judecarea procesului Centralei Evreilor, acuzată că ar fi executat ordinele Berlinului și Gestapoului în prigonirea evreilor. Președintele completului de judecată a fost Al. Voitinovici, iar acuzatori publici A. Schreiber și M. Mayo. Pe 18 februarie 1946 s-a pronunțat sentința în acest proces: V. Isanceanu (în contumacie) și Nandor Gingold - munca silnică și degradare civică - 10 ani, N. Grunberg-Wilmann - 20 de ani detenție grea; A Grossman-Grozea - 15 ani detenție grea, J. Leon -12 ani. Tuturor li se confiscă averea.

În procesul principal, din mai 1946, au fost judecați liderii fostei guvernări, în frunte cu Ion Antonescu (24 de inculpați). Curtea a pronunțat 13 sentințe de condamnare la moarte, dintre care 6 in absentia și neexecutate vreodată. Din restul de 7 condamnări, 3 au fost modificate în închisoare pe viață. Ion Antonescu, Mihai Antonescu, Constantin Vasiliu și Gheorghe Alexianu au fost executați la 1 iunie 1946 în închisoarea Jilava. Ceilalți au fost condamnați la închisoare pe viață sau la termene foarte lungi.

Tribunalul din Cluj și succesoarele sale au condamnat 481 de persoane: 370 unguri, 83 germani, 26 români și 2 evrei. Tribunalul din Cluj a decis 100 de condamnări la moarte, 163 de condamnări cu închisoare pe viață și alte sentințe.

Un mare număr dintre cei condamnați au fost judecați în contumacie și nu și-au ispășit niciodată pedeapsa (de exemplu, scriitorul maghiar Albert Wass). Unora dintre condamnații la pedeapsa capitală li s-a modificat sentința în condamnare la închisoare pe viață. Condamnații pentru crime de război care s-au purtat bine în închisoare au fost printre cei eliberați în baza unui decret din 1950. Restul au fost eliberați între 1962 și 1964 prin amnistiere.

Vezi și
 Pogromul de la Iași
 Ocupația sovietică a României
 România în al Doilea Război Mondial
 Masacrul de la Treznea
 Masacrul din Ip

Note
  Report of the International Commission on the Holocaust in Romania  (RICHR) submitted to President Ion Iliescu in Bucharest on November 11, 2004, and accepted by the Romanian government .
  Ch.12 - Trials of the war criminals  (PDF)
  Zoltan Tibori Szabo Evreimea transilvăneană din perioada de după al doilea război mondial, 1945-48 (Partea doua) "The People's Tribunals, Intra-Community Accusations and Inquiries" Radio Europa Liberă Detalii despre Tribunalul Poporului din Transilvania de Nord

Note

Justiția în România
Istoria Bucureștiului
Istoria Clujului


text:
Home / Cities / Rita and Me
At 6AM, my father demanded to get up for his regular morning TV regimen. However, there was a problem in that his TV was now surrounded by four large, snoring men who probably wouldn't take kindly to being rolled over by an old guy in a wheelchair. I tried explaining the situation to my father, but he insisted on going into the living room. Thankfully, we had an old black-and-white portable in the garage, which I retrieved and set up in the back bedroom...placating my father but making it impossible for my mother and me to get much more sleep.
Interestingly, I did hear a news report that explaining the shortage of workers in the area. Pretty much every store and restaurant had a help wanted sign out front. Although the reporter gave no source for his information, he said that the low-wage workers were on "vacation" drawing unemployment. "They'll be back when the unemployment runs out."
The movers arrived on-time around 8AM as the roofers were rising for the start of their workday. Suddenly the peace of our little home was shattered by the presence of nine burly men performing various acts of physical labor. As the roof was coming off, the furniture and boxes were going the door. The movers completed their task in around three hours and drove off into the sunrise.
Meanwhile, we discovered that our shingles were old and inadequately installed. Each shingle had only three nails instead of four and they appeared to be 20-year shingles rather than the more durable 30-year shingles. If we had gotten the roof replaced before the storm, perhaps the shingles wouldn't have blown off and they'd still be living there today. But there wasn't much we could do about that now.
Special mention should go to our old piano. In keeping with their habit of trying to do things on the cheap, in 1974 they purchased an old player piano (without the player mechanism) replaced the ivory and refinished the cabinet to give me an instrument to learn on. However, the age of the piano led to early development of a number of dead keys. Plus, it always sounded a bit like a player piano even when played by a human. I hated piano lessons and stopped playing after a couple of years (Despite my love for music, I always hated someone telling me how to make it). 30 years later, the piano's a wreck and it took all five grunting men to get it out of the old house and into the new one. Mommas...when in the market for a piano, I say go digital. They're cheaper, sound alot better, have better action (at least the good ones), never require tuning, take up less space, and when your kid loses interest, you can sell it quick and move it out with a small dolly.
Our old home was now quite empty and ready for the impending remedial demolition. My parents said goodbye to some old friends and we drove off into a new town and a new life.
Next: Wednesday, November 30, 2005