Software License Research Articles

Pattern of changes in morpho-densitometric parameters of magnocellular neurons of the hypothalamic paraventricular nucleus under restraint stress of different duration

The aim of the work was to define the nature of changes in morpho-densitometric parameters of magnocellular neurons of the hypothalamic paraventricular nucleus in rats at 6, 15 and 21 weeks of restricted living space. Materials and methods. A total of 55 male Wistar rats aged 6-10 months were used and divided into 4 groups (1 – intact control, 10 rats; 2, 3 and 4 – experimental groups of 15 rats each, which were in conditions of restricted environmental space for 6, 15 and 21 weeks, respectively). Morpho-densitometric analysis of 5-μm-thick rat brain sections was performed after preliminary standard histological processing and 48 hours of halocyanine-chrome staining by Einarson using an AxioImager-M2 microscope (Carl Zeiss, Germany). Images of magnocellular neurons of the hypothalamic paraventricular nuclei (PVN), which were topographically identified according to the stereotaxic atlas of the rat brain, were captured using a highly sensitive AxioCam-ERc 5s video camera (Carl Zeiss, Germany) and recorded as a computer file using AxioVision 40 V 4.8.2.0 software (license number 3005339). Quantitative data on the area of neurons, their nuclei and nucleoli, the content of heterogeneous DNA and RNA in the cell cytoplasm, nuclei and nucleoli were obtained in a semi-automatic mode using the open source software ImageJ (National Institutes of Health, USA). Results. Chronic stress condition modelled in rats for 6, 15, and 21 weeks (limited living space, inactivity, and complicated communications) resulted in a decrease in the area of cytoplasm and nuclei of magnocellular neurons of the hypothalamic PVN. The decrease was directly proportional to restrain stress duration: cytoplasm and nuclei by 18 % and 9 % at week 6 and by 40 % and 25 % at week 21, respectively, and only cytoplasm by 23 % at 15 weeks. On the contrary, the area of neuronal nuclei was increased by 31 % at 6 weeks of stress and 33 % at 15 weeks, and by 15 % at 21 weeks of stress compared to the control. The content of nucleic acids in the cytoplasm of magnocellular neurons of the hypothalamic PVN in the group of rats with 6-week restriction was 39 % less than in the control group, 34 % less than that in the group with 15-week restriction, and 42 % less than that in the group of 21-week restrain stress. In the nuclei of cells after 6 and 15 weeks of restriction, the content was decreased approximately equally by 37 % and 35 %, respectively, and long-term restriction (21 weeks) contributed to a 41 % decrease. In the neuron nucleoli, the content of nucleic acids was changed similarly: in the group of 6 weeks, a decrease of 40 % was characteristic, after 15 weeks – by 39 %, and after 21 weeks – by 43 %. Conclusions. Changes in the morphometric parameters of magnocellular neurons of the hypothalamic PVN in rats with long-term limitation of living space are characterized by time dependence and multidirectionality, which is related to the functional features of the neuron structural components (cytoplasm, nucleus and nucleoli). There is a progressive decrease in the cytoplasmic area of PVN neurons and their nuclei, while the nucleolar area increases with increasing length of living space limitation. The content of nucleic acids in the studied structures of the hypothalamic PVN magnocellular neurons after prolonged stress at each time point (6, 15, 21 weeks) becomes less than the control values by more than a third. Comparison of nucleic acid content in the neuron cytoplasm, nuclei, and nucleoli shows a narrow range of variations in the parameters of the experimental group rats between different periods.

Machine learning compliance-aware dynamic software allocation for energy, cost and resource-efficient cloud environment

With the growing number of cloud services protected by licenses, compliance management and assurance is becoming critical need to support the development of trustworthy cloud systems. In these systems, the multiplication of services and the inefficient resource utilization incurred energy consumption and costs increase despite the consolidation initiatives underway. Few works deal with resource allocation optimization at the SaaS level, which does not consider compliance aspects. Generally, the reported consolidation work does not address license management in the cloud environment as a whole, particularly from a resource management perspective, and the vast majority of consolidation work focuses on resource optimization at the infrastructure level. Thus, we propose a software license consolidation scheme based on multi-objective reinforcement learning that enables efficient use of resources and optimizes energy consumption, resource wastage, and costs while ensuring compliance with the processor-based licensing model. The experimental results show that our solution outperforms the baseline approaches in different scenarios with homogeneous and heterogeneous resources under different data center scales.

Importance and Various Types of Task Scheduling in Cloud Computing System

Cloud Computing has arisen as quite possibly the main new computing procedures in the undertaking. A blend of advances and cycles has prompted an insurgency in the manner that computing is created and conveyed to end client. Cloud Computing traces all the way back to 1950 for example the enormous scope centralized servers were made accessible to huge undertakings. Basically, the cloud architecture is built with the combined perspective of cloud provider, user, and the broker. Scheduling is the most important task in any working framework, and it is controlled by the CPU. This is due to the fact that resources are not stored in a particularly designated manner, but rather in a strictly handy manner in order to ensure maximum skills. Cloud computing is a relatively new technology that allows users to access computer infrastructure and other services on a demand basis. Various types of task schedulers have been developed to make use of the vast amount of cloud-based resources users can access while also improving the management of data centers. We can say that cloud computing has transformed IT by allowing users and consumers to access services via the Internet. These services range from hardware to software, saving money on both the expense of setting up physical resources and the cost of obtaining the appropriate software licenses. The task scheduling problem is one of the most important and prominent challenges facing the cloud computing system.

Tax Dispute in a Digital Economy: The Legal Implication in Nigeria

The study examines the tax disputes in a digital economy with a precise focused on the legal implications in Nigeria. The study explored some of the tax jurisdiction law in the digital economy. This digital economy encompasses various revenue streams and business models, such as e-commerce, digital services, online advertising, and software licensing. The study also identify transfer pricing issues arising from tax authorities in questioning the pricing of intra-group transactions involving intangible assets such as intellectual property rights or digital content. The significance of Permanent Establishment (PE) in determining a business's tax liabilities in a foreign jurisdiction were also discussed. The disputes that are commonly arise when taxpayers fail to fulfill their reporting obligations and the legal implications. However, the study highlighted the development of tax laws and regulations, leading to divergent views between taxpayers and tax authorities on the application and interpretation of tax laws in the digital context. Thus, the study employed a phenomenological research method, specifically a systematic review approach to examine the pertinent literature. Based on this study, it was concluded that tax authorities in Nigeria need to possess a deep understanding of the legal ramifications associated with tax disputes in the digital economy. To successfully navigate such disputes and contribute to an acquiescent and transparent digital economy, the study recommends that Nigerian tax collectors should closely collaborate with legal professionals, continuously update their knowledge of tax regulations, use technology solutions, and offer proactive advice to their clients. They should effectively handle tax disputes and play a vital role in ensuring a transparent and amenable digital economy. Keyword: Tax Disputes, Digital Economy, Legal Implication and Accountants

MLQD: A package for machine learning-based quantum dissipative dynamics

Machine learning has emerged as a promising paradigm to study the quantum dissipative dynamics of open quantum systems. To facilitate the use of our recently published ML-based approaches for quantum dissipative dynamics, here we present an open-source Python package MLQD (https://github.com/Arif-PhyChem/MLQD), which currently supports the three ML-based quantum dynamics approaches: (1) the recursive dynamics with kernel ridge regression (KRR) method, (2) the non-recursive artificial-intelligence-based quantum dynamics (AIQD) approach and (3) the blazingly fast one-shot trajectory learning (OSTL) approach, where both AIQD and OSTL use the convolutional neural networks (CNN). This paper describes the features of the MLQD package, the technical details, optimization of hyperparameters, visualization of results, and the demonstration of the MLQD's applicability for two widely studied systems, namely the spin-boson model and the Fenna–Matthews–Olson (FMO) complex. To make MLQD more user-friendly and accessible, we have made it available on the Python Package Index (PyPi) platform and it can be installed via ▪. In addition, it is also available on the XACS cloud computing platform (https://XACScloud.com) via the interface to the MLatom package (http://MLatom.com). Program summaryProgram Title: MLQDCPC Library link to program files:https://doi.org/10.17632/yxp37csy5x.1Developer's repository link:https://github.com/Arif-PhyChem/MLQDCode Ocean capsule:https://codeocean.com/capsule/5563143/treeLicensing provisions: Apache Software License 2.0Programming language: Python 3.0Supplementary material: Jupyter Notebook-based tutorialsExternal routines/libraries: Tensorflow, Scikit-learn, Hyperopt, Matplotlib, MLatomNature of problem: Fast propagation of quantum dissipative dynamics with machine learning approaches.Solution method: We have developed MLQD as a comprehensive framework that streamlines and supports the implementation of our recently published machine learning-based approaches for efficient propagation of quantum dissipative dynamics. This framework encompasses: (1) the recursive dynamics with kernel ridge regression (KRR) method, as well as the non-recursive approaches utilizing convolutional neural networks (CNN), namely (2) artificial intelligence-based quantum dynamics (AIQD), and (3) one-shot trajectory learning (OSTL).Additional comments including restrictions and unusual features:1.Users can train a machine learning (ML) model following one of the ML-based approaches: KRR, AIQD and OSTL.2.Users have the option to propagate dynamics with the existing trained ML models.3.MLQD also provides the transformation of trajectories into the training data.4.MLQD also supports hyperparameter optimization using MLATOM's grid search functionality for KRR and Bayesian methods with Tree-structured Parzen Estimator (TPE) for CNN models via the HYPEROPT package.5.MLQD also facilitates the visualization of results via auto-plotting.6.MLQD is designed to be user-friendly and easily accessible, with availability on the XACS cloud computing platform (https://XACScloud.com) via the interface to the MLATOM package (http://MLatom.com). In addition, it is also available as a pip package which makes it easy to install. Future outlook: MLQD will be extended to more realistic systems along with the incorporation of other machine learning-based approaches as well as the traditional quantum dynamics methods.

Open-Access Archaeological Predictive Modeling Using Zonal Statistics: A Case Study from Zanzibar, Tanzania

This paper presents a case study using zonal statistical analysis for archaeological predictive modeling with open-access software and free geospatial datasets. The method is applied to the rural landscapes of Zanzibar, Tanzania on the Swahili Coast. This study used QGIS (version 3.28) to perform zonal statistical analyses of environmental datasets weighted by settlement classes digitized from a 1907 historical map, to create predictive models for settlement across the island. These models were compared against the locations of major precolonial archaeological sites on the island and site data from a random stratified archaeological survey in an environmentally diverse region of northern Zanzibar. The results show strong correspondences between larger permanent site locations and areas of high likelihood for site detection in the predictive model. Additionally, there were correspondences between areas of lower likelihood for site detection and smaller, ephemeral sites related to agricultural production in swidden field plots. These results attest to Swahili rural complexity and enable an understanding of the specific environmental affordances that structured settlement and land use over the last millennium, in ways that shaped colonial contact in rural areas and altered the sociopolitical development of Zanzibar and the East African coast. The methods described here may be applicable for researchers and heritage managers in Africa and the Global South, where funding for large-scale field projects, expensive satellite imagery, or software licensing is limited.

Analysis of BLDC Electric Motor Shaft Treatment Model Using Numerical Method

This research studies the shaft strength of a BLDC electric motor. A Shaft is one of the components in a rotary engine and functions to transmit power. The design calculation is needed to determine the effect of the strength of the material being treated. The strength analysis of the shaft used FEM (Finite Element Method). The shaft is modeled on the manufacturing design and tested by numerical simulation with Ansys Mechanical 14.5-BRIN commercial license software. The static simulation used a structural statics module with static and dynamic load input. The research method comparing the results of FEM simulations with two different types of materials is determined. Based on the simulation parameters, the selected material types are JIS S45C tempered and AISI 1045 cold-drawn. The simulation results represent the maximum stress (von Mises) and total deformation. The deformation value of S45C tempered material is slightly higher than that of AISI 1045 cold drawn. However, both materials have the same maximum von Mises stress.

Algorithms for magnetic symmetry operation search and identification of magnetic space group from magnetic crystal structure.

A crystal symmetry search is crucial for computational crystallography and materials science. Although algorithms and implementations for the crystal symmetry search have been developed, their extension to magnetic space groups (MSGs) remains limited. In this paper, algorithms for determining magnetic symmetry operations of magnetic crystal structures, identifying magnetic space-group types of given MSGs, searching for transformations to a Belov-Neronova-Smirnova (BNS) setting, and symmetrizing the magnetic crystal structures using the MSGs are presented. The determination of magnetic symmetry operations is numerically stable and is implemented with minimal modifications from the existing crystal symmetry search. Magnetic space-group types and transformations to the BNS setting are identified by a two-step approach combining space-group-type identification and the use of affine normalizers. Point coordinates and magnetic moments of the magnetic crystal structures are symmetrized by projection operators for the MSGs. An implementation is distributed with a permissive free software license in spglib v2.0.2: https://github.com/spglib/spglib.

Use of Symmetrical Components in the Study of Electrical Disturbances in Distribution Systems with Charging Allocation for Electric Vehicles and Battery Banks

This paper presents a study of electric power distribution systems, which include battery banks and electric vehicle charging.Emphasis is placed to detect and distinguish voltage disturbances, conductor breaks, and other events that commonly occur in distribution systems. The research uses free license software ATPDraw™ to accurately model distribution systems and replicate voltage characteristics. The study investigates the ideal location of electric vehicle chargers, battery banks and electrical voltage meters in distribution systems. For this purpose, the General Algebraic Modeling System (GAMS) will be used, which provides high-level mathematical optimization capabilities to improve the observability of the system. Research will focus on possible mitigation to the problems these factors can cause in the power distribution system and explore strategies to minimize their negative effects. The discoveries will help improve the system performance, stability, and reliability of power distribution systems and support the integration of electric vehicles and energy storage.

Development of an educational low‐cost and ESP32‐based platform for fundamental physics

AbstractThis paper describes how to implement a new low‐cost modular and open‐source didactic platform using an ESP32 board. The latter is designed to be used in undergraduate fundamental physics in the context of preparatory classes for engineering training. Thus, we intend to create a platform that will serve both teachers and students as a concrete means of carrying out and exploiting certain experimental processes by themselves. In this context, Android devices are used together with electronics development boards to realize this platform with reduced material costs available as open‐source hardware and software licenses. Tests and results are presented and the goal is then attempted. The results of this work will provide a new insight into the work carried out in this theme.

Installation of gussets to reduce stress on the junction between the arm and bridge on the swing arm

The swing arm is one of the main components of a motorcycle that functions as a connection between the rear wheel and the frame. Under loading conditions, the joint area between the arm and the bridge experiences significant stress, leading to fractures in that region. This study aims to investigate the effectiveness of installing gussets to reduce the stress that occurs at the joint area between the arm and the bridge in the swing arm of ELGO electric motorcycles. The research was conducted using the static analysis simulation method with Solidworks 2021-2022 Research License software. The loading conditions were simulated based on the actual usage of the electric motorcycle. The simulation results revealed that without the installation of gussets, the joint area between the arm and the bridge in the swing arm experienced stress exceeding the yield strength of the material. This would inevitably lead to the breakage of the swing arm and potentially cause accidents for motorcycle riders. However, after the gussets were installed, the stress at the joint area between the arm and the bridge remained below the yield strength of the material. Based on these findings, it can be concluded that the installation of gussets successfully reduced the stress at the joint area between the arm and the bridge in the swing arm. This research outcome can serve as a reference for the design of swing arms for electric motorcycles.

How are websites used during development and what are the implications for the coding process?

Websites are frequently used to support the development process. This paper investigates how websites are used when writing code and programmers’ perceptions of the potential impact of this on their behaviour and the quality of the resulting software. We interviewed 18 programmers (13 students enrolled in undergraduate computer science courses, and 5 experienced professionals), and analysed the data thematically. The findings were used to develop a survey, which was distributed to 276 programmers (251 students, 25 experienced professionals). The results indicate that use of websites, especially Stack Overflow, is viewed as an essential part of programming by both students completing coursework and professionals developing code in industry.We also found that developers have experience of encountering a diverse set of problematic code snippets online, that copying code from websites without checking its quality or understanding how it worked is common, and that using online resources in this way had a potentially counter-productive effect on learning. Based on these findings, we make a number of recommendations, including better consideration of online code reuse in taught programmes, co-development and code-reuse practices in professional settings, and software licensing training for professional developers.Editor’s note: Open Science material was validated by the Journal of Systems and Software Open Science Board.

A Study of Hypervisor Based Virtualization and Related Major Security Issues in Cloud Computing Architecture

Abstract: With the use of cloud computing, a comprehensive web platform made up of many different services may be created and used as needed. Through the internet, cloud computing offers its services in an affordable, dependable, and productive manner. By offering services on a rental basis, cloud computing lowers the expenditure required to buy gear, software, and software licenses. It offers backups to maintain multiple copies of the data and lowers the cost of licensing. With the use of cloud computing, a comprehensive web platform made up of many different services may be created and used as needed. One of today's most fascinating technologies is cloud computing, which is scalable, versatile, and can lower the cost and complexity of applications. These advantages turned cloud computing from a far-fetched notion into one of the most rapidly expanding fields of technology today. Actually, virtualization technology is based on an older technique called virtualization, which contains security flaws that need to be fixed before they influence cloud computing. Additionally, limited security features of virtualization technology are needed to protect a wide-area system like the cloud. Therefore, modifications to the conventional virtualization design are needed to create an effective security solution. In order to safeguard the cloud environment, this article suggests novel security architecture in a virtualization technology based on hypervisors.

Revisiting Binary Code Similarity Analysis Using Interpretable Feature Engineering and Lessons Learned

Binary code similarity analysis (BCSA) is widely used for diverse security applications, including plagiarism detection, software license violation detection, and vulnerability discovery. Despite the surging research interest in BCSA, it is significantly challenging to perform new research in this field for several reasons. First, most existing approaches focus only on the end results, namely, increasing the success rate of BCSA, by adopting uninterpretable machine learning. Moreover, they utilize their own benchmark, sharing neither the source code nor the entire dataset. Finally, researchers often use different terminologies or even use the same technique without citing the previous literature properly, which makes it difficult to reproduce or extend previous work. To address these problems, we take a step back from the mainstream and contemplate fundamental research questions for BCSA. Why does a certain technique or a certain feature show better results than the others? Specifically, we conduct the first systematic study on the basic features used in BCSA by leveraging interpretable feature engineering on a large-scale benchmark. Our study reveals various useful insights on BCSA. For example, we show that a simple interpretable model with a few basic features can achieve a comparable result to that of recent deep learning-based approaches. Furthermore, we show that the way we compile binaries or the correctness of underlying binary analysis tools can significantly affect the performance of BCSA. Lastly, we make all our source code and benchmark public and suggest future directions in this field to help further research.

Eletric bass use as a teaching resource for the teaching of oscillations and soudwaves

Music has the potential to stimulate the brain to facilitate the memorization of information, with that there is the resourcefulness of seeking a teaching practice for teaching physics. This article proposes a didactic sequence for teaching Physics to 2nd year high school classes, using the practical context of sound waves, taking into account the difficulty of learning that is managed by abstract approaches. For the development of this project, an electric bass, audio interface and a free license software (Audacity) for audio capture were used, in addition, classes were approached to introduce the proposed content and later from the use of the electric instrument to the demonstration through the art of music with an interdisciplinary approach.

NFTs for Open-Source and Commercial Software Licensing and Royalties

Software licenses are legal agreements of sale and usage among software developers and clients. Such legal agreements are crucial to effectively manage ownership and protect the rights of involved parties. Today’s software licensing mechanisms are mostly centralized and do not address the ever-increasing issues and complexities of modern software that may include multiple licenses, open-source distribution, rewarding other contributors of external software libraries, and utilizing royalty payments for monetization. As a result, developers have lost confidence in the existing software licensing models, and many software projects are failing due to lack of funding and royalty payments. This paper addresses such issues and complexities by proposing a novel decentralized software licensing system based on Non-Fungible Tokens (NFTs) and blockchain. The proposed licensing system is applicable to both commercial and open-source software. We use NFTs as digital tokens that encapsulate software code and their artifacts by minting them as unique valuable assets that allow developers to store and manage them on a blockchain ledger. With NFTs, developers can register and license their code, monetize it on NFT marketplaces, and earn royalties from other software projects that use their code. We present system architecture, relevant sequence diagrams, and develop aggregation algorithms for Ethereum smart contracts with ERC-1155 NFTs. Furthermore, we perform functional validation of our system and analyze the cost of its adoption. We also analyze the security of the solution and show how its applicability can be generalized and extended. We have made our smart contract code and related testing scripts publicly available on GitHub.

Vivências de idosos com doença pulmonar crônica em uso de oxigenoterapia domiciliar prolongada no relacionamento amoroso e sexual

Abstract Objective To understand the meanings attributed by older adult with Chronic Obstructive Pulmonary Disease (COPD) using the Long-Term Home Oxygen Therapy (LTOT) regarding romantic relationships and sexual practice. Method Qualitative study in which seven semi-structured interviews were carried out with patients with a confirmed diagnosis of COPD and using LTOT, treated in an outpatient service. The content analysis technique was applied with the support of the WebQDA2.0 software license. COREQ criteria were used to report method and outcome. Results Two categories emerged: 1- Destabilization in the romantic relationship and in the sexual life of the LTOT user: : revealed that therapy causes relationship breakup, change of partner after prescription of the LTOT or even the idea of looking for an extramarital person; 2- Experience and meanings of COPD and oxygen therapy during sexual intercourse: suffering with physiological problems, how much the patient feels short of breath to have sexual intercourse and the impact of this on performance and frequency, reducing these moments with the partner. Conclusion The perception of elderly people with COPD using LTOT indicates that oxygen therapy had an impact on sexual practice and romantic relationships. Having good quality in relationships and sexual practice is a fundamental condition for health promotion.

The Future of Cloud Computing: Benefits and Challenges

The purpose of this paper is to provide a better knowledge of the cloud computing as well as to suggest relevant research paths in this growing field. Also, we will go through the future benefits of cloud computing and the upcoming possible challenges we will have. Intext Cloud, performance, cloud computing, architecture, scale-up, and big data are all terms used in this context. Cloud computing offers a wide range of architectural configurations, including the number of processors, memory, and nodes. Cloud computing has already changed the way we store, process, and access data, and it is expected to continue to have a significant impact on the future of information technology. Cloud computing enables organizations to scale their IT resources up or down quickly and easily, without the need for costly hardware upgrades. This can help organizations to respond more quickly to changing business needs and market conditions. By moving IT resources to the cloud, organizations can reduce their IT infrastructure costs and improve their operational efficiency. Cloud computing also allows organizations to pay only for the resources they use, rather than investing in expensive hardware and software licenses. Cloud providers invest heavily in security and compliance measures, which can help to protect organizations from cyber threats and ensure regulatory compliance. Cloud computing provides a scalable platform for AI and machine learning applications, enabling organizations to build and deploy these technologies more easily and cost-effectively. A task, an application, and its input can take up to 20 times longer or cost 10 times more than optimal. Cloud products’ ready adaptability has resulted in a paradigm change. Previously, an application was optimized for a specific cluster; however, in the cloud, the architectural configuration is tuned for the workload. The evolution of cloud computing from the era of mainframes and dumb terminals has been significant, but there are still many advancements to come. As we look towards the future, IT leaders and the companies they serve will face increasingly complex challenges in order to stay competitive in a constantly evolving cloud computing landscape. Additionally, it will be crucial to remain compliant with existing regulations as well as new regulations that may emerge in the future. It is safe to say that the next decade of cloud computing will be just as dramatic as the last where many internet services are becoming cloud-based, and huge enterprises will struggle to fund physical infrastructure. Cloud computing is significantly used in business innovation and because of its agility and adaptability, cloud technology enables new ways of working, operating, and running a business. The service enables users to access files and applications stored in the cloud from anywhere, removing the requirement for users to be always physically close to actual hardware. Cloud computing makes the connection available from anywhere because they are kept on a network of hosted computers that carry data over the internet. Cloud computing has shown to be advantageous to both consumers and corporations. To be more specific, the cloud has altered our way of life. Overall, cloud computing is likely to continue to play a significant role in the future of IT, enabling organizations to become more agile, efficient, and innovative in the face of rapid technological change. This is likely to drive further innovation in AI and machine learning in the coming years.

Implementing the HEVC standard in software

Implementation and use of an IT standard in software involves legal, technical and societal challenges. This paper addresses how an organisation can, and should, determine the conditions for implementation and use of the HEVC standard in software. The investigation considers the availability of the standard’s complete technical specification and the extent to which an organisation can access the information necessary to assess the licence conditions for standard essential patents impinging on the standard. Through an action case study approach the investigation analyses declarations in patent databases relevant to the standard and seeks to obtain patent licences from each declarant permitting implementation of the standard in software, where that software is to be provided under one (or several) of three specific open source software licences, and alternatively to be provided as an online service. Our analysis of legal and licensing conditions for use of the standard shows significant obstacles. We find that it is impossible to obtain licences from patent holders that would allow for implementation and use of the standard in open source software. The paper illuminates significant challenges related to conditions for use of the standard under (F)RAND terms and identifies that references to the standard in public procurement projects lead to anti-competitive effects.

Institutional Repositories in the Linked Open Data Cloud

We believe that the wealth of digital humanity research resources that is available in Institutional Repositories in Southern Africa is largely over-looked because it is not machine explorable as defined by Berners-Lee (2006). We argue that extracting research from Institutional Repositories, which Berners-Lee (2006) describes as One-Star Linked Data, and then enriching this research and storing it as tuples in a triple store (RDF data store) will expose the research to a greater audience; make it machine explorable; and integrate it with a broader network of Linked Data, known as the Linked Open Data Cloud (LODC). Our approach is to utilize software building blocks licensed under Free (Libre) Open Source Software (FLOSS) licences and to create a pipeline that can potentially transform any Institutional Repository into into a triple store, which can be published on the Internet as part of the LODC. Our transformation process embraces under-resourced institutions by utilizing FLOSS com- ponents and utilizing digital resources already published on the internet in order to promote the research from One-Star Linked data to Five-Star Linked Data in Berners-Lee (2006) taxonomy of linked data.