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XML Layouts. XML Resources. Published online Mar 9. Author information Article notes Copyright and License information Disclaimer. Email: moc. Published by Oxford University Press. Abstract Career choices affect not only our financial status but also our future well-being. Keywords: career choice, future simulation, multi-attribute decision-making, posteromedial cortex, precuneus.
Materials and Methods Participants All participants provided written informed consent before inclusion in the study, in accordance with the Declaration of Helsinki. Stimuli To select 80 jobs with minimal correlation between pay and interest, we conducted a preliminary experiment. Open in a separate window. Figure 1. Behavioral Data Analysis We set out to establish whether the willingness to obtain a job i. Figure 4. Results Behavioral Data The two-attribute-value model was better at predicting job value compared to the reduced-attribute-value models.
Neural Representation of Job and Attribute Values We identified the brain regions representing job value and the two attribute values. Table 1 Regions representing job and attribute values. Figure 2. Figure 3. Discussion The present study investigated the cortical representation of pay and interest, two key attributes of job value involved in career decisions. Limitations It is important to note that while we showed positive effects of pay and interest on job value, job value is unlikely to depend exclusively on these attributes.
References Akaike H. Information theory and an extension of the maximum likelihood principle. In: Selected papers of Hirotugu Akaike. New York, NY:Springer. The default network and self-generated thought: component processes, dynamic control, and clinical relevance. Ann N Y Acad Sci.
Evolutionary expansion of connectivity between multimodal association areas in the human brain compared with chimpanzees. Dopaminergic reward system: a short integrative review.
Int Arch Med. Consumption and saving: models of intertemporal allocation and their implications for public policy. J Econ Lit. Mixed-effects modeling with crossed random effects for subjects and items. J Mem Lang. Specifying the core network supporting episodic simulation and episodic memory by activation likelihood estimation.
Constructive consumer choice processes. J Consum Res. Career self-efficacy: exemplary recent research and emerging directions. J Career Assess. A meta-analytic examination of the relationship between job satisfaction and subjective well-being.
J Occup Organ Psychol. Evolutionary economics of mental time travel? Trends Cogn Sci. The brain and the braincase: a spatial analysis on the midsagittal profile in adult humans. J Anat. Evidence for expansion of the precuneus in human evolution.
Brain Struct Funct. Cognitive and neural bases of multi-attribute, multi-alternative, value-based decisions. Consumption growth parallels income growth: some new evidence.
In: National saving and economic performance. The precuneus: a review of its functional anatomy and behavioural correlates. Informatic parcellation of the network involved in the computation of subjective value.
Soc Cogn Affect Neurosci. Career choice and the risk premium in the labor market. Rev Econ Dyn. Beyond money: toward an economy of well-being.
Psychol Sci Public Interest. Whistle while you work: a review of the life satisfaction literature. J Manage. The relationship between job satisfaction and health: a meta-analysis. Occup Environ Med. Happiness at work.
Int J Manag Rev. Measuring nominal scale agreement among many raters. Psychol Bull. Future planning: default network activity couples with frontoparietal control network and reward-processing regions during process and outcome simulations.
Comparative analysis of the macroscale structural connectivity in the macaque and human brain. PLoS Comput Biol. Job preferences as revealed by employee-initiated job changes.
Int J Hum Resour Manag. Brain development after birth differs between Neanderthals and modern humans. Curr Biol. Mapping the structural core of human cerebral cortex. PLoS Biol. The long-term labor market consequences of graduating from college in a bad economy. Labour Econ. Segregated encoding of reward—identity and stimulus—reward associations in human orbitofrontal cortex. J Neurosci. Most neuroscience computational models usually have more than one input file from sources such as ModelDB [ 40 ].
To accommodate this requirement, we have added the capability for NSG users to upload input file in a zip format. For the NSG, we had to add and implement the functionality to uuencode the uploaded zip file and to uudecode the zip file on the computational resource during the staging of the input. In Figure 2 , the portal layer handles this functionality. To accommodate this, we created a mechanism to collect all such codes and compile them as a part of the job submission process.
Job scripts are automatically created and submitted. The compressed file is also made available for immediate download through the NSG portal. Figure 3 shows the event-driven interaction flow diagram for the NSG. Figure 3 shows the daemons responsible for submitting a job, monitoring job status, and retrieving the output. The daemons also help keep track of job and usage monitoring by updating the database.
The submit daemon is called when a task is created and submitted. While the job is processing on the HPC cluster, an intermediate results view option is available in the portal that gives a snapshot of the working directory that was created in the backend HPC cluster.
Advanced users can look at the intermediate results folder to see if their job has started or if any output file has been written. Another notable feature is the ability to clone a job on the portal. Users are able to clone their jobs, and this is helpful when they want to submit a job with the same input file but vary the parameters such as number of cores or the wall clock time. Ability to do parameter sweep studies will be provided in the future. During file staging from the portal to the remote cluster or while copying the results back, the task would fail either because there are too many open GridFTP connections on the remote cluster or the NFS home directory on the HPC cluster is slow because of multiple users using it.
Addressing this issue requires restarting autofs by system administrator of the HPC cluster. The output data, generated as a result of simulations using the NSG, are saved as a zip file and are made available on the portal. Email notification is sent to the users when a job completes. This is handled by a curl command in the job submission script, which notifies a servlet in the Web application when the job finishes. The check jobs and load results flowcharts are shown in Figure 3.
It should be noted that our goal was to provide a simple workflow as far as the users are concerned and hide all the complexities from them. The NSG user workflow consists of the following steps:. We also obtained community gateway account on both Trestles and Lonestar.
The initial allocation of , core hours was used up by early and, an additional , core hours was requested and approved by the XSEDE allocation committee.
This allocated time was also completely used up by the NSG users by mid-September Even when the allocated hours were almost fully spent, users requested to keep the NSG functional, and we were able to use an SDSC guest account that, among other things, allows users to use HPC resources under special circumstances.
Subsequent to this, an allocation request for 2. This estimate was based on usage during the third quarter of and from direct input from selected users. Although we do not have any usage data of what users did prior to the availability of the NSG, the usage demonstrates that there is certainly a need of such a science gateway for neuronal simulations on HPC resources.
This allocation proposal was favorably reviewed, and in December , we were awarded 1. Users of the community gateway account abide by the policies set by the NSG administrators. Currently, we allow core hours per user per year.
On the basis of the total amount of computer time acquired every year for the NSG and the total number of NSG users, we will decide what percentage of the total time can be allocated freely to each user and monitor their usage. Because not all the users consume the same amount of resource, we try to obtain an estimate from the users, and on the basis of their average usage and job size, the amount allocated to them will vary. The NSG also has the capability to allow users to run jobs with their own acquired allocation.
All user activities such as job submission statistics and usage are logged in the database. As a part of the user support environment, a ticketing system, monitored by NSG developers, is in place and is used to keep track of user questions and provide immediate assistance.
In this section, we discuss three topics that are part of most science gateways. The parallel performance of neuronal models is important in this regard as we expect our users to run parallel models using HPC resources.
The performance of parallel models is also important when we write XRAC allocation proposals justifying the total time we request for each year. Associated with this is the analysis of usage statistics of the allocated time by NSG users. As a part of the user activities, we also discuss some of the educational projects performed by undergraduate and high school students using the NSG.
The parallel scaling performance results for few of the publicly available neuronal models on HPC resources are discussed in this section. Parallel scaling is defined as the plot of speedup versus number of cores. Speedup on N cores is defined as the time taken to run on one core divided by the time taken to run the same case on N cores.
Parallel scaling will very much depend on the specific parallel neuronal models that will be developed as a part of research by the individual computational neuroscientists and run via the NSG on HPC resources. We decided to run two parallel neuronal models using the NEURON software because most of our users are currently using this software for their research.
The idea behind the scaling study is to show that depending on size of the parallel model, the NEURON code will scale to different number of cores [ 42 ].
It should be noted that the other neuronal tools, currently provided by the NSG, are also capable of running parallel models. It provides tools for conveniently building, managing, and using models that are numerically sound and computationally effIcient. It is particularly suitable for problems that involve cells with complex anatomical and biophysical properties. Figure 5 describes the scaling of biophysically realistic neural modeling of the MEG mu rhythm [ 43 ] system starting from four cores.
This model deals with variations in cortical oscillations and has been correlated with attention, working memory, and stimulus detection. Figure 6 describes the scaling of the large-scale model of the olfactory bulb [ 44 ] starting from 24 cores.
The olfactory bulb case models sparse distributed representation of odors in a large-scale olfactory bulb circuit. Typically, NSG users will run models starting on few cores and scale up, as the memory requirement may not make it feasible to run models on a single core. Figure 5 shows that the MEG mu rhythm model scales to about cores, and Figure 6 shows that the olfactory bulb model scales to about cores.
These results are expected as the MEG mu rhythm model is a smaller model, that is, having less number of neuronal cells, compared with the olfactory bulb model. It should be noted that the time taken to do these benchmark runs was at most around 20 h and so an insignifIcant part of the total allocation utilized by the users as reported in Section 3.
Resources for further information include:. This also means that these particular licenses are compatible. The Apache 2. Note that this sometimes depends on how the program is used or modified.
For example, the LGPL permits the covered software usually a library to be embedded in a larger work under many different licenses including proprietary licenses , subject to certain conditions. This need for legal analysis is one reason why creating new OSS licenses is strongly discouraged: It can be extremely difficult, costly, and time-consuming to analyze the interplay of many different licenses.
It is usually far better to stick to licenses that have already gone through legal review and are widely used in the commercial world. A copyright holder who releases creative works under one of the Creative Common licenses that permit commercial use and modifications would be using an OSS-like approach for such works.
Wikipedia maintains an encyclopedia using approaches similar to open source software approaches. Computer and electronic hardware that is designed in the same fashion as open source software OSS is sometimes termed open source hardware. The term has primarily been used to reflect the free release of information about the hardware design, such as schematics, bill of materials and PCB layout data, or its representation in a hardware description language HDL , often with the use of open source software to drive the hardware.
No, complying with OSS licenses is much easier than proprietary licenses if you only use the software in the same way that proprietary software is normally used. By definition, OSS software permits arbitrary use of the software, and allows users to re-distribute the software to others. The terms that apply to usage and redistribution tend to be trivially easy to meet e. Thus, complex license management processes to track every installation or use of the software, or who is permitted to use the software, is completely unnecessary.
Support for OSS is often sold separately for OSS; in such cases, you must comply with the support terms for those uses to receive support, but these are typically the same kinds of terms that apply to proprietary software and they tend to be simpler in practice. Since it is typically not legal to modify proprietary software at all, or it is legal only in very limited ways, it is trivial to determine when these additional terms may apply.
The real challenge is one of education - some developers incorrectly believe that just because something is free to download, it can be merged or changed without restriction. This has never been true, and explaining this takes little time.
Typically enforcement actions are based on copyright violations, and only copyright holders can raise a copyright claim in U. In the commercial world, the copyright holders are typically the individuals and organizations that originally developed the software. Under the current DoD contracting regime, the contractor usually retains the copyright for software developed with government funding, so in such cases the contractor not the government has the right to sue for copyright violation.
In some cases, the government obtains the copyright; in those cases, the government can sue for copyright violation. However, the government can release software as OSS when it has unlimited rights to that software.
The government is not the copyright holder in such cases, but the government can still enforce its rights. Although the government cannot directly sue for copyright violation, in such cases it can still sue for breach of license and, presumably, get injunctive relief to stop the breach and money damages to recover royalties obtained by breaching the license and perhaps other damages as well.
The doctrine of unclean hands , per law. In effect, the malicious developer could lose many or all rights over their license-violating result, even rights they would normally have had!
Since OSS licenses are quite generous, the only license-violating actions a developer is likely to try is to release software under a more stringent license… and those will have little effect if they cannot be enforced in court.
Many OSS licenses do not have a choice of venue clause, and thus cannot have an issue, although some do. If your contract has FAR clause However, the required FAR Clause This clause establishes that the choice of venue clause category 4 is superseded by the Contract Disputes Act category 2 , and thus the conflict is typically moot.
As always, if there are questions, consult your attorney to discuss your specific situation. This is in part because such a ban would prevent DoD groups from using the same analysis and network intrusion applications that hostile groups could use to stage cyberattacks. Indeed, vulnerability databases such as CVE make it clear that merely hiding source code does not counter attacks:.
Hiding source code does inhibit the ability of third parties to respond to vulnerabilities because changing software is more difficult without the source code , but this is obviously not a security advantage. There are valid business reasons, unrelated to security, that may lead a commercial company selling proprietary software to choose to hide source code e.
Some OSS is very secure, while others are not; some proprietary software is very secure, while others are not. Each product must be examined on its own merits.
The use of any commercially-available software, be it proprietary or OSS, creates the risk of executing malicious code embedded in the software. Even if a commercial program did not originally have vulnerabilities, both proprietary and OSS program binaries can be modified e. It may be illegal to modify proprietary software, but that will normally not slow an attacker.
Thankfully, there are ways to reduce the risk of executing malicious code when using commercial software both proprietary and OSS. It is impossible to completely eliminate all risks; instead, focus on reducing risks to acceptable levels. The use of software with a proprietary license provides absolutely no guarantee that the software is free of malicious code. Indeed, many people have released proprietary code that is malicious.
Such software does not normally undergo widespread public review, indeed, the source code is typically not provided to the public and there are often license clauses that attempt to inhibit review further e. Where it is important, examining the security posture of the supplier e. Similarly, OSS as well as proprietary software may indeed have malicious code embedded in it. In addition, since the source code is publicly released, anyone can review it, including for the possibility of malicious code.
The public release also makes it easy to have copies of versions in many places, and to compare those versions, making it easy for many people to review changes. This is not merely theoretical; in the Linux kernel development process resisted an attack. Whether or not this was intentional, it certainly had the same form as a malicious back door.
When the program was released as OSS, within 5 months this vulnerability was found and fixed. This shows that proprietary software can include functionality that could be described as malicious, yet remain unfixed - and that at least in some cases OSS is reviewed and fixed. Note that merely being released by a US firm is no guarantee that there is no malicious embedded code. Also, US citizens can attempt to embed malicious code into software, and many non-US citizens develop software without embedding malicious code.
In practice, commercial software OSS or not tends to be developed globally, especially when you consider their developers and supply chains. The good news is that, by definition, OSS provides its source code, enabling a more informed evaluation than is typically available for other kinds of COTS products.
Note also that merely being developed for the government is no guarantee that there is no malicious embedded code. Such developers need not be cleared, for example. Requiring that all developers be cleared first can reduce certain risks at substantial costs , where necessary, but even then there is no guarantee.
Note that most commercial software is not intended to be used where the impact of any error of any kind is extremely high e. Most commercial software including OSS is not designed for such purposes. The CBP ruling points out that 19 U.
Under the same reasoning, the CBP determined that building an object file from source code performed a substantial transformation into a new article. Yes, extensively. Intellipedia is implemented using MediaWiki, the open source software developed to implement Wikipedia.
Thus, even this FAQ was developed using open source software. Widely-used programs include the Apache web server, Firefox web browser, Linux kernel, and many other programs.
Commercial software including OSS that has widespread use often has lower risk, since there are often good reasons for its widespread use. Examples of OSS that are in widespread use include:. One approach is to use a general-purpose search engine such as Google and type in your key functional requirements. These include:. If you are looking for smaller pieces of code to reuse, search engines specifically for code may be helpful. Examples include:.
Look at the Numbers! It points to various studies related to market share, reliability, performance, scalability, security, and total cost of ownership. This is in addition to the advantages from OSS because it can be reviewed, modified, and redistributed with few restrictions inherent in the definition of OSS. That said, this does not mean that all OSS is superior to all proprietary software in all cases by all measures.
Each government program must determine its needs, and then evaluate its options for meeting those needs. The use of commercial products is generally encouraged, and when there are commercial products, the government expects that it will normally use whatever license is offered to the public. Depending on the contract and its interpretation, contractors may be required to get governmental permission to include commercial components in their deliverables; where this applies, this would be true for OSS components as well as proprietary components.
As with all commercial items, organizations must obey the terms of the commercial license, negotiate a different license if necessary, or not use the commercial item. An alternative is to not include the OSS component in the deliverable, but simply depend on it, as long as that is acceptable to the government. This is often done when the deliverable is a software application; instead of including commercially-available components such as the operating system or database system as part of the deliverable, the deliverable could simply state what it requires.
There are two versions of the GPL in widespread use: version 2 and version 3. The key issue with both versions of the GPL is that, unlike most other OSS licenses, the GPL licenses require that a recipient of a binary executable must be able to demand and receive the source code of that program, and the recipient must also be able to propogate the work under that license.
The Free Software Foundation FSF interprets linking a GPL program with another program as creating a derivative work, and thus imposing this license term in such cases.
In most cases, this GPL license term is not a problem. After all, most proprietary software licenses explicitly forbid modifying or even reverse-engineering the program, so the GPL actually provides additional rights not present in most proprietary software. So if the program is being used and not modified a very common case , this additional term has no impact.
Even for many modifications e. Software licensed under the GPL can be mixed with software released under other licenses, and mixed with classified or export-controlled software, but only under conditions that do not violate any license. Such mixing can sometimes only occur when certain kinds of separation are maintained - and thus this can become a design issue. Often such separation can occur by separating information into data and a program that uses it, or by defining distinct layers.
Note that enforcing such separation has many other advantages as well. However, this approach should not be taken lightly. This approach may inhibit later release of the combined result to other parties e. In some cases, export-controlled software may be licensed for export under the condition that the source code not be released; this would prevent release of software that had mixed GPL and export-controlled software.
When taking this approach, contractors hired to modify the software must not retain copyright or other rights to the result else the software would be conveyed outside the U. Where possible, it may be better to divide such components into smaller components in a way that avoids this issue. It can be argued that classified software can be arbitrarily combined with GPL code, beyond the approaches described above. While this argument may be valid, we know of no court decision or legal opinion confirming this.
Anyone who is considering this approach should obtain a determination from general counsel first and please let the FAQ authors know! If a legal method for using the GPL software for a particular application cannot be devised, and a different license cannot be negotiated, then the GPL-licensed component cannot be used for that particular purpose. If such software includes third-party components that were not produced in performace of that contract, the contractor is generally responsible for acquiring those components with acceptable licenses that premit the government to use that software.
This is not uncommon. Once the government has unlimited rights, it may release that software to the public under any terms it wishes - including by using the GPL. The program available to the public may improve over time, through contributions not paid for by the U. In that case, the U. Relevant government authorities make it clear that the Antideficiency Act ADA does not generally prohibit the use of OSS due to limitations on voluntary services.
Instead, the ADA prohibits government employees from accepting services that are not intended or agreed to be gratuitous, but were instead rendered in the hope that Congress will subsequently recognize a moral obligation to pay for the benefits conferred. Part of the ADA, Pub. Volume II of its third edition, section 6. Section 6. The red book section 6. It states that in , the Attorney General developed an opinion 30 Op. More recent decisions, such as the decision B by the U.
Instead, Government employees must ensure that they do not accept services rendered in the hope that Congress will subsequently recognize a moral obligation to pay for the benefits conferred. Services that are intended and agreed to be gratuitous do not conflict with this statute.
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