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We can view that file graphically as an SVG with:. which gives as a familiar call graph like other tools, but with the clunky unit of number of samples rather than seconds. See also: How to use google perf tools. I think this is the same underlying subsystem that perf uses, but you could of course attain even greater control by explicitly instrumenting your program at compile time with events of interest. This is likely too hardcore for most people, but it's kind of fun.

Minimal runnable example at: Quick way to count number of instructions executed in a C program. This seems to be closed source and xonly, but it is likely to be amazing from what I've heard. I'm not sure how free it is to use, but it seems to be free to download. TODO evaluate. Tested in Ubuntu Others: AMD Codeanalyst since replaced with AMD CodeXL , OProfile, 'perf' tools apt-get install linux-tools.

It is a sampling profiler, along the lines of the answer by Mike Dunlavey, which will gift wrap the results in a browsable call stack tree, annotated with the time or memory spent in each function, either cumulative or per-function.

I have used HPCToolkit and VTune and they are very effective at finding the long pole in the tent and do not need your code to be recompiled except that you have to use -g -O or RelWithDebInfo type build in CMake to get meaningful output.

I have heard TAU is similar in capabilities. IMHO identifying the piece that is causing bottleneck is the key here. I'd however try and answer the following questions first and choose tool based on that. valgrind with the combination of callgrind and kcachegrind should provide a decent estimation on the points above, and once it's established that there are issues with some section of code, I'd suggest to do a micro bench mark - google benchmark is a good place to start.

If you don't have a profiler, use the poor man's profiler. Hit pause while debugging your application. Most developer suites will break into assembly with commented line numbers.

You're statistically likely to land in a region that is eating most of your CPU cycles. For CPU, the reason for profiling in DEBUG mode is because if your tried profiling in RELEASE mode, the compiler is going to reduce math, vectorize loops, and inline functions which tends to glob your code into an un-mappable mess when it's assembled. An un-mappable mess means your profiler will not be able to clearly identify what is taking so long because the assembly may not correspond to the source code under optimization.

If you need the performance e. timing sensitive of RELEASE mode, disable debugger features as needed to keep a usable performance. It's cross-platform and allows you not to measure performance of your application also in real-time. You can even couple it with a live graph. Full disclaimer: I am the author. You can use a logging framework like loguru since it includes timestamps and total uptime which can be used nicely for profiling:.

At work we have a really nice tool that helps us monitoring what we want in terms of scheduling. This has been useful numerous times. Unfortunately I can't share code, just concepts. You use a "large" volatile buffer containing timestamps and event ID that you can dump post mortem or after stopping the logging system and dump this into a file for example.

hpp file. You customize the amount of events generated to focus solely on what you desire. It helped us a lot for scheduling issues while consuming the amount of CPU we wanted based on the amount of logged events per second. The probe function uses a few assembly lines to retrieve the clock timestamp ASAP and then sets an entry in the buffer. We also have an atomic increment to safely find an index where to store the log event.

Of course buffer is circular. just think you have a obstacle while you are in motion then it will decrease your speed. like that unwanted reallocation's looping,buffer overflows,searching,memory leakages etc operations consumes more execution power it will effect adversely over performance of the code, Be sure to add -pg to compilation before profiling:.

haven't tried it yet but I've heard good things about google-perftools. It will generate a file called gmon. out or callgrind. You can then use kcachegrind or debugger tool to read this file. It provides in-depth analysis and bottleneck pinpointing to the source line. Unlike most profilers, it's designed to be able to profile pthreads, OpenMP or MPI for parallel and threaded code.

Use -pg flag when compiling and linking the code and run the executable file. While this program is executed, profiling data is collected in the file a. There is two different type of profiling. out you got the following data - what percentage of the overall time was spent for the function, - how many seconds were spent in a function—including and excluding calls to sub-functions, - the number of calls, - the average time per call.

out to get the following data for each function which includes - In each section, one function is marked with an index number. Stack Overflow for Teams — Start collaborating and sharing organizational knowledge. Create a free Team Why Teams? Learn more about Collectives. Learn more about Teams.

Ask Question. Asked 14 years ago. Modified 5 months ago. Viewed k times. Improve this question. edited Jul 4 at Mateen Ulhaq asked Dec 17, at Gabriel Isenberg Gabriel Isenberg If you will provide more data about your development stack you might get better answers. There are profilers from Intel and Sun but you have to use their compilers. Is that an option? It is already answered on the following link: stackoverflow. Most of the answers are code profilers. However, priority inversion, cache aliasing, resource contention, etc.

can all be factors in optimizing and performance. I think that people read information into my slow code. FAQs are referencing this thread. Oh My! I used to use pstack randomly, most of the time will print out the most typical stack where the program is most of the time, hence pointing to the bottleneck. Show 2 more comments. Sorted by: Reset to default.

Highest score default Trending recent votes count more Date modified newest first Date created oldest first. If your goal is to use a profiler, use one of the suggested ones. Call graphs don't give you the same information, because They don't summarize at the instruction level, and They give confusing summaries in the presence of recursion. Improve this answer. edited May 30, at community wiki. This is basically a poor man's sampling profiler, which is great, but you run the risk of a too-small sample size which will possibly give you entirely spurious results.

Crash: I won't debate the "poor man" part :- It's true that statistical measurement precision requires many samples, but there are two conflicting goals - measurement and problem location. I'm focussing on the latter, for which you need precision of location, not precision of measure. Precise summaries of function times can be a clue, but every other stack sample will pinpoint the problem.

It is not. And the sad part is, for those that sample the call stack, the most useful information is right in front of them, but they throw it away, in the interests of "statistics". I don't mean to disagree with your technique.

Clearly I rely quite heavily on stack-walking sampling profilers. Use a real profiler so we don't have to come along behind you and fix the actual problems. Show 99 more comments. answered Apr 21, at Ajay Ajay 9, 7 7 gold badges 31 31 silver badges 34 34 bronze badges. valgrind is great, but be warned that it will make your program darn slow — neves. Check out also Gprof2Dot for an amazing alternative way to visualize the output.

py -f callgrind callgrind. x dot -Tsvg -o output. svg — Sebastian. neves Yes Valgrind is just not very helpful in terms of speed for profiling "gstreamer" and "opencv" applications real-time.

Sebastian: gprof2dot is now here: github. One thing to bear in mind is to compile WITH debug symbols included but WITH optimisation, to get something explorable yet with the speed characteristics similar to the actual "release" build. Be sure to add -pg to compilation before profiling: cc -o myprog myprog. c utils. c -g -pg I haven't tried it yet but I've heard good things about google-perftools. edited Aug 12, at try-catch-finally 7, 6 6 gold badges 43 43 silver badges 66 66 bronze badges.

answered Dec 17, at Nazgob Nazgob 8, 4 4 gold badges 39 39 silver badges 42 42 bronze badges. I agree that gprof is the current standard. Just a note, though, Valgrind is used to profile memory leaks and other memory-related aspects of your programs, not for speed optimization. Bill, In vaglrind suite you can find callgrind and massif. Both are pretty useful to profile apps — Salvatore Dario Minonne.

Bill-the-Lizard: Some comments on gprof : stackoverflow. gprof -pg is only an approximation of callstack profiling. It inserts mcount calls to track which functions are calling which other functions. It uses standard time based sampling for, uh, time.

It then apportions times sampled in a function foo back to the callers of foo , in proprtion to the numberr of calls. So it doesn't distinguish between calls of different costs.

Caveat: Have not done so myself. Show 1 more comment. answered Aug 17, at Will Will Great tool! I can't seem to figure that out perf report seems to give me the function names with the call parents so it's sort of an inverted butterfly view — kizzx2. Will, can perf show timechart of thread activity; with CPU number information added?

I want to see when and which thread was running on every CPU. kizzx2 - you can use gprof2dot and perf script. Very nice tool! Even newer kernels like 4. See brendangregg. html and brendangregg. html — Andrew Stern. This should be the accepted answer. Using a debugger introduces too much noise in the samples. Performance counters for linux works for multiple threads, multiple processes, user and kernel space, which is great. You can also retrieve many useful information such as branch and cache misses.

In the same website AndrewStern mentioned, there is a flamegraph which is very useful for this kind of analysis: flame graphs. It generates SVG files that can be opened with a web browser for interactive graphs!

So this is what I recommend. To see profiling results use: kcachegrind callgrind. edited Sep 5, at Peter Mortensen answered Jun 8, at Tõnu Samuel Tõnu Samuel 2, 2 2 gold badges 20 20 silver badges 30 30 bronze badges.

Now on some reason callgrind. My usual contexts are something like whole MySQL or PHP or some similar big thing. Often even do not know what I want to separate at first. Or in my case my program actually loads a bunch of data into an LRU cache, and I want not to profile that. It works, but loading that cache is slow and CPU intensive across code that I'm trying to profile in a different context, so callgrind produces badly polluted results.

TõnuSamuel, for me also callgrind. In my case, the program was getting crahsed while profiling. Once the reason for crash was resolved, I am able to see contents in callgrind. What is important to know is that Valgrind is basically a Virtual Machine: wikipedia Valgrind is in essence a virtual machine using just-in-time JIT compilation techniques, including dynamic recompilation. answered May 22, at anon anon.

Add a comment. I've been using Gprof the last couple of days and have already found three significant limitations, one of which I've not seen documented anywhere else yet : It doesn't work properly on multi-threaded code, unless you use a workaround The call graph gets confused by function pointers. edited Sep 15, at HugoTeixeira 4, 3 3 gold badges 22 22 silver badges 31 31 bronze badges.

answered Jun 30, at Yes, it does sampling, but not for number-of-calls figures. Interestingly, following your link ultimately led me to an updated version of the manual page I linked to in my post, new URL: sourceware.

Note: beware that the mcount counting function in glibc is not thread-safe. It is not clear to me if this explains my result in iii. I would ordinarily presume that "link with multi-threaded libraries" means actually using those libraries, and to a greater extent than this, but I could be wrong!

out main. c time. out For educational reasons, we will also do a run without optimizations enabled. out First, time tells us that the execution time with and without -pg were the same, which is great: no slowdown! sudo apt install graphviz python3 -m pip install --user gprof2dot gprof main. gprof dot -Tsvg -o output.

svg Here, the gprof tool reads the gmon. this image from a "real" software example taken from this ticket : Can you find the most critical call stack easily with all those tiny unsorted spaghetti lines going over one another? What we really need is a proper dedicated viewer for it, but I haven't found one yet: View gprof output in kcachegrind Which is the best replacement for KProf?

Alternatively, we can also observe the text output of the gprof built-in binutils tool which we previously saved at: cat main. gprof By default, this produces an extremely verbose output that explains what the output data means. Once you have understood the data output format, you can reduce verbosity to show just the data without the tutorial with the -b option: gprof -b main.

out In our example, outputs were for -O0 : Flat profile: Each sample counts as 0. I have also mentioned kcachegrind previously at: Tools to get a pictorial function call graph of code callgrind is the valgrind's tool to profile code and kcachegrind is a KDE program that can visualize cachegrind output. We view that file with: kcachegrind callgrind. perf from linux-tools perf seems to use exclusively Linux kernel sampling mechanisms. sudo apt install linux-tools time perf record -g.

out This added 0. out [. out [kernel] [k] 0xffffffff8ae7 0. out [kernel] [k] 0xffffffff8a 0. out [unknown] [k] 0x 0. out ld out [unknown] [.

out libc First install gperftools with: sudo apt install google-perftools Then, we can enable the gperftools CPU profiler in two ways: at runtime, or at build time. out See also: gperftools - profile file not dumped The nicest way to view this data I've found so far is to make pprof output the same format that kcachegrind takes as input yes, the Valgrind-project-viewer-tool and use kcachegrind to view that: google-pprof --callgrind main.

out prof. out kcachegrind callgrind. out After running with either of those methods, we get a prof. We can view that file graphically as an SVG with: google-pprof --web main. out which gives as a familiar call graph like other tools, but with the clunky unit of number of samples rather than seconds.

Alternatively, we can also get some textual data with: google-pprof --text main. out which gives: Using local file main. Using local file prof. Total: samples edited Jun 28 at answered Feb 17, at Ciro Santilli OurBigBook. com Ciro Santilli OurBigBook. com k 92 92 gold badges silver badges bronze badges. By default perf record uses the frame pointer register. Modern compilers don't record the frame address and instead use the register as a general purpose. The alternative is to compile with -fno-omit-frame-pointer flag or use a different alternative: record with --call-graph "dwarf" or --call-graph "lbr" depending on your scenario.

KDAB's hotspot ships with an AppImage these days, making it really easy to use. Read it using kcachegrind. Use gprof add -pg : cc -o myprog myprog. Intel VTune is the best free for educational purposes. edited Sep 6, at Tim Miller 5 5 silver badges 16 16 bronze badges.

answered Feb 23, at Ehsan Ehsan 1, 14 14 silver badges 13 13 bronze badges. answered Mar 17, at fwyzard fwyzard 2, 1 1 gold badge 19 19 silver badges 18 18 bronze badges.

As some Compose file elements can both be expressed as single strings or complex objects, merges MUST apply to the expanded form. Profiles allow to adjust the Compose application model for various usages and environments. A Compose implementation SHOULD allow the user to define a set of active profiles. The exact mechanism is implementation specific and MAY include command line flags, environment variables, etc. The Services top-level element supports a profiles attribute to define a list of named profiles.

Services without a profiles attribute set MUST always be enabled. A service MUST be ignored by the Compose implementation when none of the listed profiles match the active ones, unless the service is explicitly targeted by a command. In that case its profiles MUST be added to the set of active profiles. All other top-level elements are not affected by profiles and are always active.

References to other services by links , extends or shared resource syntax service:xxx MUST not automatically enable a component that would otherwise have been ignored by active profiles. Instead the Compose implementation MUST return an error. Top-level version property is defined by the specification for backward compatibility but is only informative. A Compose implementation SHOULD NOT use this version to select an exact schema to validate the Compose file, but prefer the most recent schema at the time it has been designed.

Compose implementations SHOULD validate whether they can fully parse the Compose file. If some fields are unknown, typically because the Compose file was written with fields defined by a newer version of the specification, Compose implementations SHOULD warn the user. Compose implementations MUST offer a way for user to override this name, and SHOULD define a mechanism to compute a default project name, to be used if the top-level name element is not set.

Services are backed by a set of containers, run by the platform according to replication requirements and placement constraints. Being backed by containers, Services are defined by a Docker image and set of runtime arguments.

All containers within a service are identically created with these arguments. A Compose file MUST declare a services root element as a map whose keys are string representations of service names, and whose values are service definitions.

A service definition contains the configuration that is applied to each container started for that service. Each service MAY also include a Build section, which defines how to create the Docker image for the service.

Compose implementations MAY support building docker images using this service definition. If not implemented the Build section SHOULD be ignored and the Compose file MUST still be considered valid. Build support is an OPTIONAL aspect of the Compose specification, and is described in detail in the Build support documentation. Each Service defines runtime constraints and requirements to run its containers.

Deploy support is an OPTIONAL aspect of the Compose specification, and is described in detail in the Deployment support documentation. If not implemented the Deploy section SHOULD be ignored and the Compose file MUST still be considered valid. build specifies the build configuration for creating container image from source, as defined in the Build support documentation. Each item in the list MUST have two keys:.

Modify the proportion of bandwidth allocated to this service relative to other services. Takes an integer value between 10 and , with being the default. Can be either an integer value using microseconds as unit or a duration. cpus define the number of potentially virtual CPUs to allocate to service containers. This is a fractional number.

cpuset defines the explicit CPUs in which to allow execution. Can be a range or a list 0,1. command overrides the default command declared by the container image i. The command can also be a list, in a manner similar to Dockerfile :. configs grant access to configs on a per-service basis using the per-service configs configuration. Two different syntax variants are supported.

There are two syntaxes defined for configs. To remain compliant to this specification, an implementation MUST support both syntaxes.

Implementations MUST allow use of both short and long syntaxes within the same document. The short syntax variant only specifies the config name.

The source name and destination mount point are both set to the config name. If the external config does not exist, the deployment MUST fail. Attempting to do so MUST result in an error. Compose implementations MAY also support additional protocols for custom use-cases. A registry value with the given name must be located in:. The following example loads the credential spec from a value named my-credential-spec in the registry:. When configuring a gMSA credential spec for a service, you only need to specify a credential spec with config , as shown in the following example:.

The short syntax variant only specifies service names of the dependencies. Service dependencies cause the following behaviors:.

Compose implementations MUST create services in dependency order. In the following example, db and redis are created before web. Compose implementations MUST remove services in dependency order. In the following example, web is removed before db and redis. Compose implementations MUST guarantee dependency services have been started before starting a dependent service. deploy specifies the configuration for the deployment and lifecycle of services, as defined here.

The format is the same format the Linux kernel specifies in the Control Groups Device Whitelist Controller. dns defines custom DNS servers to set on the container network interface configuration.

Can be a single value or a list. conf file on Linux. dns defines custom DNS search domains to set on container network interface configuration. domainname declares a custom domain name to use for the service container. MUST be a valid RFC hostname. entrypoint overrides the default entrypoint for the Docker image i. The entrypoint can also be a list, in a manner similar to Dockerfile :.

The files in the list MUST be processed from the top down. For the same variable specified in two env files, the value from the last file in the list MUST stand. Environment variables declared in the environment section MUST override these values — this holds true even if those values are empty or undefined.

Lines beginning with MUST be ignored. Blank lines MUST also be ignored. The value of VAL is used as a raw string and not modified at all. If the value is surrounded by quotes as is often the case for shell variables , the quotes MUST be included in the value passed to containers created by the Compose implementation. VAL MAY be omitted, in such cases the variable value is empty string. environment defines environment variables set in the container.

environment can use either an array or a map. Any boolean values; true, false, yes, no, SHOULD be enclosed in quotes to ensure they are not converted to True or False by the YAML parser.

Environment variables MAY be declared by a single key no value to equals sign. In such a case Compose implementations SHOULD rely on some user interaction to resolve the value. If they do not, the variable is unset and will be removed from the service container environment. expose defines the ports that Compose implementations MUST expose from container. These ports MUST be accessible to linked services and SHOULD NOT be published to the host machine.

Only the internal container ports can be specified. Extend another service, in the current file or another, optionally overriding configuration. You can use extends on any service together with other configuration keys. The extends value MUST be a mapping defined with a required service and an optional file key.

If supported Compose implementations MUST process extends in the following way:. Service denoted by service MUST be present in the identified referenced Compose file. Compose implementations MUST return an error if:. Two service definitions main one in the current Compose file and referenced one specified by extends MUST be merged in the following way:.

The following keys should be treated as mappings: build. args , build. labels , build. labels , deploy. limits , environment , healthcheck , labels , logging. One exception that applies to healthcheck is that main mapping cannot specify disable: true unless referenced mapping also specifies disable: true. Compose implementations MUST return an error in this case. Produces the following configuration for the cli service. The same output is produced if array syntax is used.

Note that mounted path now points to the new volume name and ro flag was applied. If referenced service definition contains extends mapping, the items under it are simply copied into the new merged definition. Merging process is then kicked off again until no extends keys are remaining. Here, cli services gets user key from common service, which in turn gets this key from base service.

constraints , deploy. preferences , deploy. Any duplicates resulting from the merge are removed so that the sequence only contains unique elements.

Unlike sequence fields mentioned above, duplicates resulting from the merge are not removed. An alias of the form SERVICE:ALIAS can be specified.

Values MUST set hostname and IP address for additional hosts in the form of HOSTNAME:IP. An example of where this is useful is when multiple containers running as different users need to all read or write the same file on a shared volume. test defines the command the Compose implementation will run to check container health.

It can be either a string or a list. Both forms below are equivalent:. NONE disable the healthcheck, and is mostly useful to disable Healthcheck set by image. Alternatively the healthcheck set by the image can be disabled by setting disable: true :. hostname declares a custom host name to use for the service container. image specifies the image to start the container from. Compose implementations with build support MAY offer alternative options for the end user to control precedence of pull over building the image from source, however pulling the image MUST be the default behavior.

image MAY be omitted from a Compose file as long as a build section is declared. Compose implementations without build support MUST fail when image is missing from the Compose file. init run an init process PID 1 inside the container that forwards signals and reaps processes. Set this option to true to enable this feature for the service.

ipc configures the IPC isolation mode set by service container. Available values are platform specific, but Compose specification defines specific values which MUST be implemented as described if supported:.

Supported values are platform-specific. labels add metadata to containers. You can use either an array or a map. The com. compose label prefix is reserved. Specifying labels with this prefix in the Compose file MUST result in a runtime error. links defines a network link to containers in another service.

Either specify both the service name and a link alias SERVICE:ALIAS , or just the service name. Containers for the linked service MUST be reachable at a hostname identical to the alias, or the service name if no alias was specified. If services do declare networks they are attached to, links SHOULD NOT override the network configuration and services not attached to a shared network SHOULD NOT be able to communicate.

Compose implementations MAY NOT warn the user about this configuration mismatch. logging defines the logging configuration for the service. The default and available values are platform specific. Driver specific options can be set with options as key-value pairs.

This is a modifier attribute that only has meaning if memory is also set. Using swap allows the container to write excess memory requirements to disk when the container has exhausted all the memory that is available to it. There is a performance penalty for applications that swap memory to disk often.

Available values are platform specific, but Compose specification define specific values which MUST be implemented as described if supported:. networks defines the networks that service containers are attached to, referencing entries under the top-level networks key. aliases declares alternative hostnames for this service on the network. Since aliases are network-scoped, the same service can have different aliases on different networks. Note : A network-wide alias can be shared by multiple containers, and even by multiple services.

If it is, then exactly which container the name resolves to is not guaranteed. In the example below, service frontend will be able to reach the backend service at the hostname backend or database on the back-tier network, and service monitoring will be able to reach same backend service at db or mysql on the admin network.

The corresponding network configuration in the top-level networks section MUST have an ipam block with subnet configurations covering each static address. Link-local IPs are special IPs which belong to a well known subnet and are purely managed by the operator, usually dependent on the architecture where they are deployed. Implementation is Platform specific. If unspecified, the default value is 0. Value MUST be within [,] range. pid sets the PID mode for container created by the Compose implementation.

Supported values are platform specific. Set to -1 for unlimited PIDs. Exposes container ports. The short syntax is a colon-separated string to set host IP, host port and container port in the form:.

Host IP, if not set, MUST bind to all network interfaces. Port can be either a single value or a range. Host and container MUST use equivalent ranges. Either specify both ports HOST:CONTAINER , or just the container port. In the latter case, the Compose implementation SHOULD automatically allocate any unassigned host port.

HOST:CONTAINER SHOULD always be specified as a quoted string, to avoid conflicts with yaml base float. Note : Host IP mapping MAY not be supported on the platform, in such case Compose implementations SHOULD reject the Compose file and MUST inform the user they will ignore the specified host IP.

privileged configures the service container to run with elevated privileges. Support and actual impacts are platform-specific. profiles defines a list of named profiles for the service to be enabled under. When not set, service is always enabled. Possible values are:. Compose implementations MAY override this behavior in the toolchain. restart defines the policy that the platform will apply on container termination. The value of runtime is specific to implementation. scale specifies the default number of containers to deploy for this service.

secrets grants access to sensitive data defined by secrets on a per-service basis. Two different syntax variants are supported: the short syntax and the long syntax. The short syntax variant only specifies the secret name. The source name and destination mountpoint are both set to the secret name. The following example uses the short syntax to grant the frontend service access to the server-certificate secret.

The value of server-certificate is set to the contents of the file. The following example sets the name of the server-certificate secret file to server. cert within the container, sets the mode to group-readable and sets the user and group to The value of server-certificate secret is provided by the platform through a lookup and the secret lifecycle is not directly managed by the Compose implementation.

Services MAY be granted access to multiple secrets. Long and short syntax for secrets MAY be used in the same Compose file. Defining a secret in the top-level secrets MUST NOT imply granting any service access to it. Such grant must be explicit within service specification as secrets service element.

Specified as a byte value. Specified as a duration. If unset containers are stopped by the Compose Implementation by sending SIGTERM. sysctls defines kernel parameters to set in the container. sysctls can use either an array or a map. You can only use sysctls that are namespaced in the kernel.

Docker does not support changing sysctls inside a container that also modify the host system. For an overview of supported sysctls, refer to configure namespaced kernel parameters sysctls at runtime. tmpfs mounts a temporary file system inside the container. tty configure service container to run with a TTY. ulimits overrides the default ulimits for a container.

user overrides the user used to run the container process. Default is that set by image i. Dockerfile USER , if not set, root.

Thank you for visiting nature. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer.

In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. As a clinical geneticist, Paul James is accustomed to discussing some of the most delicate issues with his patients.

But in early , he found himself having a particularly awkward conversation about sex. A year-old pregnant woman had visited his clinic at the Royal Melbourne Hospital in Australia to hear the results of an amniocentesis test to screen her baby's chromosomes for abnormalities. The baby was fine — but follow-up tests had revealed something astonishing about the mother.

Her body was built of cells from two individuals, probably from twin embryos that had merged in her own mother's womb. And there was more. One set of cells carried two X chromosomes, the complement that typically makes a person female; the other had an X and a Y. Halfway through her fifth decade and pregnant with her third child, the woman learned for the first time that a large part of her body was chromosomally male 1.

Sex can be much more complicated than it at first seems. According to the simple scenario, the presence or absence of a Y chromosome is what counts: with it, you are male, and without it, you are female. But doctors have long known that some people straddle the boundary — their sex chromosomes say one thing, but their gonads ovaries or testes or sexual anatomy say another.

Parents of children with these kinds of conditions — known as intersex conditions, or differences or disorders of sex development DSDs — often face difficult decisions about whether to bring up their child as a boy or a girl.

Some researchers now say that as many as 1 person in has some form of DSD 2. When genetics is taken into consideration, the boundary between the sexes becomes even blurrier. Scientists have identified many of the genes involved in the main forms of DSD, and have uncovered variations in these genes that have subtle effects on a person's anatomical or physiological sex.

What's more, new technologies in DNA sequencing and cell biology are revealing that almost everyone is, to varying degrees, a patchwork of genetically distinct cells, some with a sex that might not match that of the rest of their body.

Some studies even suggest that the sex of each cell drives its behaviour, through a complicated network of molecular interactions. These discoveries do not sit well in a world in which sex is still defined in binary terms. Few legal systems allow for any ambiguity in biological sex, and a person's legal rights and social status can be heavily influenced by whether their birth certificate says male or female.

That the two sexes are physically different is obvious, but at the start of life, it is not. Five weeks into development, a human embryo has the potential to form both male and female anatomy. Next to the developing kidneys, two bulges known as the gonadal ridges emerge alongside two pairs of ducts, one of which can form the uterus and Fallopian tubes, and the other the male internal genital plumbing: the epididymes, vas deferentia and seminal vesicles. At six weeks, the gonad switches on the developmental pathway to become an ovary or a testis.

If a testis develops, it secretes testosterone, which supports the development of the male ducts. It also makes other hormones that force the presumptive uterus and Fallopian tubes to shrink away. If the gonad becomes an ovary, it makes oestrogen, and the lack of testosterone causes the male plumbing to wither. The sex hormones also dictate the development of the external genitalia, and they come into play once more at puberty, triggering the development of secondary sexual characteristics such as breasts or facial hair.

Changes to any of these processes can have dramatic effects on an individual's sex. Gene mutations affecting gonad development can result in a person with XY chromosomes developing typically female characteristics, whereas alterations in hormone signalling can cause XX individuals to develop along male lines.

For many years, scientists believed that female development was the default programme, and that male development was actively switched on by the presence of a particular gene on the Y chromosome.

In , researchers made headlines when they uncovered the identity of this gene 3 , 4 , which they called SRY. Just by itself, this gene can switch the gonad from ovarian to testicular development.

For example, XX individuals who carry a fragment of the Y chromosome that contains SRY develop as males. By the turn of the millennium, however, the idea of femaleness being a passive default option had been toppled by the discovery of genes that actively promote ovarian development and suppress the testicular programme — such as one called WNT4. XY individuals with extra copies of this gene can develop atypical genitals and gonads, and a rudimentary uterus and Fallopian tubes 5.

In , researchers showed 6 that if another key ovarian gene, RSPO1 , is not working normally, it causes XX people to develop an ovotestis — a gonad with areas of both ovarian and testicular development.

These discoveries have pointed to a complex process of sex determination, in which the identity of the gonad emerges from a contest between two opposing networks of gene activity. Changes in the activity or amounts of molecules such as WNT4 in the networks can tip the balance towards or away from the sex seemingly spelled out by the chromosomes.

According to some scientists, that balance can shift long after development is over. Studies in mice suggest that the gonad teeters between being male and female throughout life, its identity requiring constant maintenance. In , researchers reported 7 deactivating an ovarian gene called Foxl2 in adult female mice; they found that the granulosa cells that support the development of eggs transformed into Sertoli cells, which support sperm development.

Two years later, a separate team showed 8 the opposite: that inactivating a gene called Dmrt1 could turn adult testicular cells into ovarian ones. The gonad is not the only source of diversity in sex. A number of DSDs are caused by changes in the machinery that responds to hormonal signals from the gonads and other glands.

Complete androgen insensitivity syndrome, or CAIS, for example, arises when a person's cells are deaf to male sex hormones, usually because the receptors that respond to the hormones are not working. People with CAIS have Y chromosomes and internal testes, but their external genitalia are female, and they develop as females at puberty. Conditions such as these meet the medical definition of DSDs, in which an individual's anatomical sex seems to be at odds with their chromosomal or gonadal sex.

But they are rare — affecting about 1 in 4, people 9. Some researchers now say that the definition should be widened to include subtle variations of anatomy such as mild hypospadias, in which a man's urethral opening is on the underside of his penis rather than at the tip. The most inclusive definitions point to the figure of 1 in people having some form of DSD, says Vilain see 'The sex spectrum'.

The sex spectrum. But beyond this, there could be even more variation. Since the s, researchers have identified more than 25 genes involved in DSDs, and next-generation DNA sequencing in the past few years has uncovered a wide range of variations in these genes that have mild effects on individuals, rather than causing DSDs. A DSD called congenital adrenal hyperplasia CAH , for example, causes the body to produce excessive amounts of male sex hormones; XX individuals with this condition are born with ambiguous genitalia an enlarged clitoris and fused labia that resemble a scrotum.

It is usually caused by a severe deficiency in an enzyme called hydroxylase. But women carrying mutations that result in a milder deficiency develop a 'non-classical' form of CAH, which affects about 1 in 1, individuals; they may have male-like facial and body hair, irregular periods or fertility problems — or they might have no obvious symptoms at all.

Another gene, NR5A1 , is currently fascinating researchers because variations in it cause a wide range of effects 10 , from underdeveloped gonads to mild hypospadias in men, and premature menopause in women. Many people never discover their condition unless they seek help for infertility, or discover it through some other brush with medicine. Last year, for example, surgeons reported that they had been operating on a hernia in a man, when they discovered that he had a womb The man was 70, and had fathered four children.

Studies of DSDs have shown that sex is no simple dichotomy. But things become even more complex when scientists zoom in to look at individual cells. The common assumption that every cell contains the same set of genes is untrue. Some people have mosaicism: they develop from a single fertilized egg but become a patchwork of cells with different genetic make-ups.

This can happen when sex chromosomes are doled out unevenly between dividing cells during early embryonic development. For example, an embryo that starts off as XY can lose a Y chromosome from a subset of its cells. If most cells end up as XY, the result is a physically typical male, but if most cells are X, the result is a female with a condition called Turner's syndrome, which tends to result in restricted height and underdeveloped ovaries.

This kind of mosaicism is rare, affecting about 1 in 15, people. The effects of sex-chromosome mosaicism range from the prosaic to the extraordinary. A few cases have been documented in which a mosaic XXY embryo became a mix of two cell types — some with two X chromosomes and some with two Xs and a Y — and then split early in development This results in 'identical' twins of different sexes. There is a second way in which a person can end up with cells of different chromosomal sexes.

James's patient was a chimaera: a person who develops from a mixture of two fertilized eggs, usually owing to a merger between embryonic twins in the womb. Another form of chimaerism, however, is now known to be widespread. Termed microchimaerism, it happens when stem cells from a fetus cross the placenta into the mother's body, and vice versa. It was first identified in the early s — but the big surprise came more than two decades later, when researchers discovered how long these crossover cells survive, even though they are foreign tissue that the body should, in theory, reject.

A study in recorded women with fetal cells in their blood as many as 27 years after giving birth 13 ; another found that maternal cells remain in children up to adulthood This type of work has further blurred the sex divide, because it means that men often carry cells from their mothers, and women who have been pregnant with a male fetus can carry a smattering of its discarded cells. Microchimaeric cells have been found in many tissues. In , for example, immunologist Lee Nelson and her team at the University of Washington in Seattle found XY cells in post-mortem samples of women's brains The oldest woman carrying male DNA was 94 years old.

Other studies have shown that these immigrant cells are not idle; they integrate into their new environment and acquire specialized functions, including in mice at least forming neurons in the brain But what is not known is how a peppering of male cells in a female, or vice versa, affects the health or characteristics of a tissue — for example, whether it makes the tissue more susceptible to diseases more common in the opposite sex.

Scientists are now finding that XX and XY cells behave in different ways, and that this can be independent of the action of sex hormones. He and his colleagues have shown 17 that the dose of X chromosomes in a mouse's body can affect its metabolism, and studies in a lab dish suggest 18 that XX and XY cells behave differently on a molecular level, for example with different metabolic responses to stress.

The next challenge, says Arnold, is to uncover the mechanisms. His team is studying the handful of X-chromosome genes now known to be more active in females than in males. Biologists may have been building a more nuanced view of sex, but society has yet to catch up.

True, more than half a century of activism from members of the lesbian, gay, bisexual and transgender community has softened social attitudes to sexual orientation and gender. Many societies are now comfortable with men and women crossing conventional societal boundaries in their choice of appearance, career and sexual partner.

But when it comes to sex, there is still intense social pressure to conform to the binary model. This pressure has meant that people born with clear DSDs often undergo surgery to 'normalize' their genitals.

Such surgery is controversial because it is usually performed on babies, who are too young to consent, and risks assigning a sex at odds with the child's ultimate gender identity — their sense of their own gender. Intersex advocacy groups have therefore argued that doctors and parents should at least wait until a child is old enough to communicate their gender identity, which typically manifests around the age of three, or old enough to decide whether they want surgery at all.

This issue was brought into focus by a lawsuit filed in South Carolina in May by the adoptive parents of a child known as MC, who was born with ovotesticular DSD, a condition that produces ambiguous genitalia and gonads with both ovarian and testicular tissue.

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