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In recent years, a lot of attention has been given to patterns in the Internet of Things (IoT). In essence, these patterns provide well-known ways to solve problems commonly encountered in the IoT paradigm. However, despite this recognition, conceptualising patterns in the IoT has proven to be difficult. This is mainly because IoT patterns come in many shapes, forms and sizes, and can be abstracted from many levels of the system architecture. In fact, many patterns in the IoT are system-independent and can be abstracted from other fundamental aspects that make up the IoT. This seemingly broad variations of patterns has led to some confusion regarding what constitute a pattern in the IoT. This has raised many unanswered questions in the IoT pattern community, such as (i) if patterns are not only about objects, and if they reach far beyond software architecture, then what is an IoT pattern?, and (ii) what are the solution categories in which the underlying IoT patterns can be abstracted? With these questions in mind, we set out to perform a deeper analysis of the meaning of the word pattern in the context of the IoT. We discovered that the IoT patterns give us a standardised vocabulary to talk about structures larger than objects, modules and procedures. That is, patterns are, in fact, a literature that is ingrained in problem solving and design thinking in the holistic IoT domain.

The Internet of Things (IoT) consists of several patterns that address a variety of problems encountered in the design and construction of reference architectures. Essentially, these patterns represent a set of conventional solutions and technologies that are used in the IoT paradigm to create ambient intelligence. However, in order for the IoT practitioners to use these patterns effectively, a catalogue that groups and classifies them in a systematic manner is required. Such a catalogue must facilitate easy and quick retrieval of the pattern, and clearly describe the intended purpose of each pattern. At the moment, no such catalogue exists, and the reviewed catalogues in the literature are either cumbersome or address these issues inadequately. This makes it difficult for users and the IoT practitioners to easily choose the relevant pattern for the given problem. Due to the large number of the IoT patterns, it is difficult to organise them in a manner that facilitate systematic classification. In this study, we propose a methodical, fivestep approach by which we can arrange these patterns for easy identification. The nature of this paper is theoretical, thus we focus on exploring some linguistic theories and algebraic structures that make up the core essence of this multifaceted process.

Patterns for the internet of things (IoT) which represent proven solutions used to solve design problems in the IoT are numerous. Similar to object-oriented design patterns, these IoT patterns contain multiple mutual heterogeneous relationships. However, these pattern relationships are hidden and virtually unidentified in most documents. In this paper, we use machine learning techniques to automatically mine knowledge graphs to map these relationships between several IoT patterns. The end result is a semantic knowledge graph database which outlines patterns as vertices and their relations as edges. We have identified four main relationships between the IoT patterns-a pattern is similar to another pattern if it addresses the same use case problem, a large-scale pattern uses a small- scale pattern in a lower level layer, a large pattern is composed of multiple smaller scale patterns underneath it, and patterns complement and combine with each other to resolve a given use case problem. Our results show some promising prospects towards the use of machine learning techniques to generate an automated repository to organise the IoT patterns, which are usually extracted at various levels of abstraction and granularity.

The Internet of Things patterns dictionary represents an aspect of a lexicon - it provides a set of definitions for the IoT patterns. This dictionary fulfills a function in language standardization for the IoT paradigm by providing patterns definitions that are based on a number of parameters. Definitions convey the meaning of a concept to the audience. In the field of linguistics, various types of definitions exist - each with a different purpose and focus. However, since a definition expresses the meaning of a word using other words, forming clear descriptive definitions can be a challenging venture. In the literature, definitions for patterns are often formed based on the author's knowledge and intuition without following any formal blueprint. In this paper, a systematic method for constructing lexical descriptive definitions for the IoT patterns is proposed. The aim is to evolve the theoretical framework presented here into a formal IoT patterns dictionary. Since it is common knowledge that each IoT pattern consists of a set of attributes, one can, in practice, derive a lexical definition for each pattern based on these attributes. In linguistics, the meaning of a lexical term is often derived from a combination of different components describing that particular object. Similarly, a definition of each IoT pattern is composed of at least one or more general and/or specific attributes that essentially, when juxstaposed, make up a unique definition of each pattern. Of course, our approach to definition formation is linguistics-based, and not rooted in software engineering. Thus, most of the content in this paper is dedicated to the discussion of several mechanisms for defining languages and showing that the attributes of a given pattern can be concatenated using an algebraic linguistics modus operandi to construct formal definitions.

Automatic Indexing of documents using paragraph vectors is a popular unsupervised method for learning distributed representations of texts. This method learns embedding of words with document vectors for document classification. In addition, this method can be leveraged for sentiment analysis. However, while the results presented in the original Doc2Vec study were promising, the overall proof of concept was rather narrow. In this study, we extend the Doc2Vec method, and enhance it to classify locality sensitive documents, i.e. domain-based documents which are largely similar with marginal differences. In particular, we use the enhanced Doc2Vec technique to classify similar documents describing the Internet of Things (IoT) patterns. We observed that our enhanced locality sensitive Doc2Vec technique performs significantly well to improve embedding quality. The model performance is in par with state-of-the-art results and can be qualified as a benchmark for similar vector space models.

Proper knowledge representation and conceptual analysis often require clear ontological support. This is particularly true for large domains in which explicit formal specifications of the terms is required for encoding knowledge, thus making it understandable to the end users. In the Internet of Things (IoT), there is a substantial development of solutions for a wide range of devices and IoT platforms. These solutions are based on existing known patterns which require interoperability for seamless connection and cross-platform resource sharing. However, to the best of our knowledge, pattern relationships for facilitating interoperability in the IoT are undocumented. The activity of developing a domain-specific ontology for the interoperability of the IoT patterns is therefore one of the fundamental steps in the organization of the IoT paradigm. It is clear, however, that this activity as well as other engineering activities, particularly with regard to the development of ontologies is often made complex by the use of confusing semantic terminologies and dense ontological structures. This often lead to ontological explicative horrors in which the essence of the ontology is hidden instead of highlighted. In this paper, we thus prefer to develop a lightweight ontology that clearly display relational dimensions between the IoT patterns. We use empirical analysis to identify core objects underneath the interoperability of the IoT technologies and patterns at a large-scale.

The paper presents a systematic literature review of the literature on the competencies that are essential to develop a globally competitive workforce in the field of data science. The systematic review covers a wide range of literature but focuses primarily, but not exclusively, on the computing, information systems, management, and organisation science literature. The paper uses a broad research search strategy covering four separate electronic databases. The search strategy led the researchers to scan 139 titles, abstracts and keywords. Sixty potentially relevant articles were identified, of which 42 met the quality criteria and contributed to the analysis. A critical appraisal checklist assessed the validity of each empirical study. The researchers grouped the findings under six broad competency themes: organisational, technical, analytical, ethical and regulatory, cognitive and social. Thematic analysis was used to develop a unified model of data science competency based on the evidence of the findings. This model will be applied to case studies and survey research in future studies. A unified data science competency model, supported by empirical evidence, is crucial in closing the skills gap, thereby improving the quality and competitiveness of the South Africa's data science workforce. Researchers are encouraged to contribute to the further conceptual development of data science competency.

The Internet of Things (IoT) is a paradigm with multitudes of design patterns. However, in order to use these patterns quickly and effectively, one must be able to make a differentiation between the existing patterns. At the moment, there is no known catalogue for the IoT patterns in which each pattern is described at a fine-grained level, i.e. in terms of its attributes. The need to discuss these patterns in terms of their attributes is important as it enables ease of understanding and allows us to group related patterns together for speedy retrieval. In this paper, we present an attributes extraction system which generates a list of attributes for a given IoT pattern. The attributes extraction system is based on identification and extraction of important sentences which describe the core properties of the given IoT pattern. The system uses multiple linguistics features to identify the most important sentences in a document with regard to describing the core essence of a given pattern. The system calculates an independent score for each sentence per feature. Through aggregation, the independent scores for each feature can then be combined to give a weighted mean score for each sentence. The evaluation results show that the attributes selected by the system are consistent with human ranking in the bulk of the examined documents.

Employers require software engineers to work in teams when developing software systems. It is therefore important for graduates to have experienced teamwork before they enter the job market. We describe an experiential learning exercise that we designed to teach the software engineering process in conjunction with teamwork skills. The underlying teaching strategy applied in the exercise maximises risks in order to provide maximal experiential learning opportunities. The students are expected to work in fairly large, yet short-lived, instructor-assigned teams to complete software engineering tasks. After undergoing the exercise our students form self-selected teams for their capstone projects. In this article, we determine and report on the influence the teaching exercise had on the formation of teams for the capstone project. By analysing data provided by the students through regular peer reviews we gain insight into the team dynamics as well as to what extent the members contributed to the team effort. We develop and present a graphical model of a capstone project team which highlights participation of individuals during the teaching exercise. The participatory history of the members is visualised using segmented concentric rings. We consider how this visualisation can aid the identification of capstone project teams that are at risk. In our experience the composition of the team and the behaviour of other members in the team may have a marked impact on the behaviour of each individual in the team. We established a team classification in order to model information about teams. We use a statistical clustering method to classify teams. For this we use team profiles that are based on the participatory levels of its members. The team types that emerge from the clustering are used to derive migration models. When we consider migration, we build spring models to visualise the teams through which individuals migrate. We colour code the teams to characterise them according to the team types that were identified during the cluster classification of the teams. Owing to the complexity of the resulting model, only migrations for capstone team members who have worked together during the exercise or for solitary capstone team members are modelled. These models support the identification of areas of interest that warrant further investigation. To conclude, we present our observations from the analysis of team compositions, team types, and team migrations and provide directions for future work and collaborations.

Most popular industry verticals such as smart health, smart mining, smart agriculture, etc. fail to map clearly the solution patterns used in the Internet of Things (IoT). This causes a disconnection in our understanding of the implementation approaches and solutions used in the IoT paradigm. Nonetheless, there is another way of subdividing this space – decoding the building blocks of the IoT architectures, with a focus on common components and patterns for interoperability. The IoT presents us with several design challenges at all architectural levels. This ranges from the overall architecture at the highest level to device connectivity at the lowest level. In this complex design, it is easy to get lost in the forest of the latest IoT offerings without understanding the underlying solution patterns. In this study, we have mapped several IoT architectural patterns, spanning several industry verticals, by analysing the literature that report on real-world IoT implementations to identify common, recurring solution patterns. In the spirit of the Gang-of-Four 1 and Christopher Alexander’s pattern language, as well as some recent advances in the IoT space, we have identified some systematic methods which are used to organise the IoT patterns.

The study of algorithms which solve the subgraph isomorphism problem is very important because it has many applications where data is modelled as graphs. Despite the subgraph isomorphism problem being NP-hard, research has been dedicated to proposing new algorithms which are designed to improve the shortcomings of the algorithms that have been previously proposed. However, some of the newly invented solutions do not improve on their predecessors and some are redundant because their algorithmic properties are not different from some existing algorithms. The problem arises because minimal effort has been made towards organising subgraph isomorphism algorithms in terms of their relationships and differences such that new solutions utilise knowledge extracted from the organisation of knowledge about these algorithms. The need to organise information has motivated the current study to show how Formal Concept Analysis can be used to build a conceptlattice based taxonomy of algorithms. There are many subgraph isomorphism algorithms and it is not feasible to list all of them. As a result, the implications between the attributes of the algorithms are used to build a representative taxonomy of the domain of subgraph isomorphism algorithms. The paper focuses on how the tools from Formal Concept Analysis can be used to build a taxonomy. This is illustrated using a small sample subset of algorithms.

Curriculum design has changed from the traditional centralised approach where a lecturer was provided with the curriculum and content they had to teach to an approach where lecturers are able to provide their own flavour to the curriculum based on their knowledge and expertise. With the change in society and democratic citizenship, the role of the student in curriculum design is coming to the fore. By enabling students to buy-in to the curriculum they are to be taught provides them with a sense of ownership and motivates them to learn the content presented.In this paper a module presented to fourth year students is used to show how when students are enabled to negotiate their curriculum, the content proposed during the negotiations deviates slightly over the years. From the results, the curricula presented after negotiation may look different in their approach, but all have common themes forming their foundation.

Curricula are not static, especially in Computer Science. Curricula specifications are updated and it is not always clear what the exact updates are nor the impact these updated may have on a curriculum which has been developed to comply with the specification. In this paper, the results of a comparison on the knowledge unit and topic-level between the ACM/IEEE Computer Science curriculum volumes of 2001, 2008 and 2013 is presented.

Humans will again set foot on the moon. The moon is covered by a layer of fine dust, which can pose a respiratory hazard. We investigated the pulmonary toxicity of lunar dust in rats exposed to 0, 2.1, 6.8, 20.8 and 60.6 mg/m(3) of respirable-size lunar dust for 4 weeks (6 h/day, 5 days/week); the aerosols in the nose-only exposure chambers were generated from a jet-mill ground preparation of a lunar soil collected during the Apollo 14 mission. After 4 weeks of exposure to air or lunar dust, groups of five rats were euthanized 1 day, 1 week, 4 weeks or 13 weeks after the last exposure for assessment of pulmonary toxicity. Biomarkers of toxicity assessed in bronchoalveolar fluids showed concentration-dependent changes; biomarkers that showed treatment effects were total cell and neutrophil counts, total protein concentrations and cellular enzymes (lactate dehydrogenase, glutamyl transferase and aspartate transaminase). No statistically significant differences in these biomarkers were detected between rats exposed to air and those exposed to the two low concentrations of lunar dust. Dose-dependent histopathology, including inflammation, septal thickening, fibrosis and granulomas, in the lung was observed at the two higher exposure concentrations. No lesions were detected in rats exposed to ≤6.8 mg/m(3). This 4-week exposure study in rats showed that 6.8 mg/m(3) was the highest no-observable-adverse-effect level (NOAEL). These results will be useful for assessing the health risk to humans of exposure to lunar dust, establishing human exposure limits and guiding the design of dust mitigation systems in lunar landers or habitats.

Many businesses see Big Data and Data Science as a catalyst for innovation. The problem is that many of these businesses are hesitant to embrace these new technologies mainly because of a shortage in skilled manpower. On a global level, higher education institutions are in the process of developing curricula for graduate degree programs relating to Big Data and Data Science. Developing such curriculum has its own challenges. For example: What level of knowledge is required from disciplines such as Computing and Statistics? What underlying foundations in Mathematics are required? This paper presents a framework for the design of an interdisciplinary Big Data and Data Science curriculum on the Master’s level.

Digraphs are used to model real world systems and therefore the need arises to be able to determine the similarity between two relatively large digraphs. This similarity is in terms of both the structure of the digraphs and the knowledge represented by their vertices and edges.Two algorithms are presented which derive their basic functionality from the Levenshtein distance algorithm. The Levenshtein algorithm is used in string comparisons to determine similarity. These two algorithms, not only calculate the edit distance between two digraphs, but preserve the operations used to convert one digraph into the other.The results of the two algorithms are discussed in terms their edit distance cost results and their execution speed. These results are contrasted with one another and with the Levenshtein distance algorithm adapted for representing digraphs. The results indicate that the two proposed algorithms are more accurate in terms of their edit distance calculations than the Levenshtein distance algorithm, but that the Levenshtein algorithm out performs them in terms of execution speed.

A pilot study was conducted to compare gauze with silicone foam that may be left in place for as long as seven days. Adult patients who were receiving treatment via peripherally inserted central catheters were recruited and alternately assigned to either the gauze or silicone foam group. Patient-reported itch and discomfort, nurse-reported ease of removal, and skin status were recorded for four weeks at each weekly dressing change. At a Glance • Peripherally inserted central catheters (PICCs) usually remain in place for the duration of chemotherapy treatment with dressings changed on a weekly basis. • A gauze cushioning barrier may be used to protect the skin against the PICC hub; however, guidelines recommend that gauze is changed every 24–48 hours. • Silicone foam may be superior to gauze as a cushioning barrier and is appropriate for weekly dressing maintenance. Refereed/Peer-reviewed

This article will describe how occupational therapists in Toronto, Canada, use the Safety Assessment of Function and the Environment for Rehabilitation (SAFER) tool and the SAFER tool manual to conduct home safety assessments and interventions. Interview, observation and task performance are used by therapists to complete the 97-item SAFER tool, which includes intervention strategies such as client and caregiver education. Further developments of the SAFER tool will be briefly described. Key words: occupational therapy, community, environmental safety, assessment, treatment, intervention

The Safety Assessment of Function and the Environment for Rehabilitation (SAFER Too)) was developed to assess people's abilities to manage functional activities safety within their homes. The results of a study to evaluate the instruments inter-rater and test-retest reliability and construct validity are reported. Reliability was evaluated using kappa for each dichotomous item. For inter-rater reliability, 59 of 66 items had acceptable reliability. For test-retest reliability, 63 of 70 items had acceptable kappa scores. For items where kappa could not be calculated because of limited variation between raters, percentage agreement was over 80%. For validity, higher SAFER Tool scores (that is, more safety problems) were hypothesised to be associated with less independence in activities of daily living (ADL) and instrumental activities of daily living (IADL) and more cognitive impairment. The correlation between SAFER Tool scores and cognitive impairment supported this hypothesis. The results of the correlations with ADL and IADL scores were less clear. This could be attributed to caregivers' assistance with activities which might have reduced risk, and generally limited variation in ADL scores. The reliability results from this study are positive. Further research to assure the SAFER Tools validity and predictive ability are needed.

Principal Linda Marshall discusses how we can support our teachers to carry out research and build a culture of evidence-based practice across our schools.

The Safety Assessment of Function and the Environment for Rehabilitation (SAFER Tool) was designed to evaluate seniors' abilities to manage safely within their home environments. This study evaluated the content validity, internal consistency and construct validity of the Tool. Content validity was established through the use of a review panel of seniors and clinical experts, and was supported by item analyses. Internal consistency was calculated and found to be high. Construct validity was evaluated by testing hypotheses about the SAFER Tool, which were not supported. These results provide support for the content validity and internal consistency of the instrument. Further psychometric testing of the SAFER Tool is needed.

The study investigated the methods used by small businesses to select people under the age of 20. While over 88 per cent of all businesses employ fewer than 25 people (about a third of the total workforce), very little is known about how they recruit and select their staff. A national sample of 498 small businesses, employing a total of 5612 people, were interviewed by a team of about 50 interviewers. A structured face-to-face interview was used to explore each organization's most recent selection of one or more young people. The recruitment and selection procedures they followed and techniques they used were probed in detail. Data were analysed in terms of general trends and differences relating to four main variables: size of business; geographical location; industry sector; and type of occupation. The results raise questions about ‘good’ and ‘fair’ practice and are discussed in terms of difference in selection practice between small and larger businesses. The selection and recruitment procedures used by small businesses, especially those employing 10 or fewer people, differ markedly from those of large organizations, being far more informal and unstructured. Among the major findings was a strong emphasis by employers on the importance of personality characteristics—such as honesty and integrity—and of interest in the job. All were rated as far more important than ability, aptitude or attainment.

We describe how we presented a year-long Software Engineering (SE) module. The first part of the module entailed a process we call rocking the boat. Our objective was to create an opportunity for our students to experience a complete software engineering project (from specification to delivery) within six weeks. During the second part students worked in self-selected teams on an industry-based SE project. Again they were required to undergo the complete SE lifecycle.We firstly describe the design of our module. We then describe how we gathered and analysed information on how the students behaved in their teams as well as about what they experienced while participating in the module. Finally, we discuss our observations. We conclude with remarks about the potential success and possible improvement of our teaching strategies and future research directions.

With the changes in the structure of the proposed volume for Computer Science of the ACM/IEEE curricula series for 2013 it is difficult to conceptualise what the extent of these changes are when reading the Strawman report. This paper is an attempt to quantify these changes. It discusses the core curricula as defined in the ACM/IEEE curricula volumes for Computer Science of 2001, 2008 Review and the 2013 Strawman report and shows how a real-world curriculum can be compared to the volumes.Both a visual comparison for the curricula volumes and an algorithmic comparison are presented. The visual comparison provides a quick indication that there are differences, while the algorithmic comparison provides a mechanism to quantify the differences and as a side effect the similarities. These comparisons are restricted to the core aspects of the curricula being evaluated and further to this subsections of the core curricula will be used for illustrative purposes in order to contain the complexity of curricula specifications.

We describe a process that we applied for teaching teamwork in a Software Engineering module. Our objective with this process was to create opportunities for our students to experience some of the problems of working in a group before they formed teams in which they had to work for the rest of the year. The process entails expecting students to work on well defined assignments for short periods in teams where risk factors were induced. Through experiencing these short bursts of intense team tribulation students are prepared to handle difficult events and situations in their teams.We describe the design and implementation of this process. We report on changes in the levels of participation of the students during the process. We offer our explanation of possible factors that may have caused the observed variations.

Many problems in the world exists where it is necessary to compare a given implementation with a specification and provide some quantification as to whether the implementation complies with the specification. An example of such a problem is determining whether a given curriculum complies with a specification as stipulated by a professional body such as the ACM/IEEE curriculum for Computing.In order to provide a mechanism for quantification, an algorithm is proposed that builds a new model. The new model is built in terms of the specification by making use of the contents of the implementation thereby ensuring that there is no loss of implementation data.Quantification with regards to the compliance of the implementation to the specification is provided by the proposed compliance measure. The measure comprises a suite of metrics with which the specification, implementation and the new model may be compared, resulting in a management tool for model improvement. A size-based metric of the compliance measure is proposed.

The SNF3 gene of Saccharomyces cerevisiae encodes a high-affinity glucose transporter that is homologous to mammalian glucose transporters. Point mutations affecting the function of the transporter were recovered from the genomes of four snf3 mutants and characterized. Two of the mutations introduced a charged amino acid into the first and second predicted membrane-spanning regions, respectively. The analogs of a bifunctional SNF3-lacZ fusion containing these two mutations were constructed, and the mutant fusion proteins were not localized to the plasma membrane, as judged by immunofluorescence microscopy. The third mutation produced a valine-to-isoleucine substitution in hydrophobic region 8, and the corresponding mutant fusion protein was correctly localized. The finding that this conservative change causes a transport defect is consistent with the possibility that this transmembrane region, which could exist as an amphipathic alpha-helix, forms part of the glucose channel through the membrane. The fourth snf3 allele harbored an ochre mutation midway through the coding sequence. We have also constructed mutations in the cloned SNF3 gene. A major difference between the yeast SNF3 protein and mammalian glucose transporters is the presence in the SNF3 protein of an additional 303 amino acids at the C terminus. Analysis of a series of C-terminal deletions and fusions to lacZ showed that this C-terminal region is important, but not essential, for transport function. We also report the genetic mapping of the SNF3 locus on the left arm of chromosome IV.

Biochemical and morphological studies were performed on Novikoff hepatoma ascites cell nucleolar matrix fractions prepared by deoxyribonuclease I digestion and high-molarity salt extractions essentially according to a published method [Berezney, R., & Buchholz, L. A. (1981) Exp. Cell Res. 20, 4995-5002]. The nucleolar matrix fraction was enriched in polypeptides of molecular mass of 28, 37.5, 40, 70, 72, 110 (protein C23), and 160 kDa, compared to the nuclear fraction in which polypeptides of molecular mass of 31, 33.5, 43.5, 46, 50, 56, and 59 kDa were predominant. About one-fourth of the protein, half of the RNA, and less than 4% of the DNA originally present in the nucleoli remained in the matrix fraction. Addition of single agents such as ethylenediaminetetraacetic acid, ribonuclease A, or mercaptoethanol during preparation had no significant effect on the polypeptide composition of the nucleolar matrix fraction. However, the combination of mercaptoethanol and ribonuclease A caused most of the RNA and protein to be removed, including protein C23 and the 160-kDa polypeptide, with polypeptides in the range of Mr 30 000-50 000 remaining. Electron microscopy of nucleolar matrix fractions revealed the presence of particles similar in size to the granular elements of nucleoli. However, when ribonuclease A and mercaptoethanol were included in the procedure, only amorphous material remained. Many proteins of nucleolar preribosomal RNP particles were also associated with the nucleolar matrix fraction. RNA from the nucleolar matrix fraction was enriched in sequences from 18S and 28S ribosomal RNA. These results indicate that preribosomal RNP particles are major constituents of a nucleolar matrix fraction prepared by the deoxyribonuclease I-high-molarity salt method.

In Vero cells incubated at 40 degrees C or treated with azetidine at 37 degrees C, synthesis of a polypeptide ('C') of apparent mol. wt. 66000 was stimulated. It was not phosphorylated and was found in the cytoplasmic fraction of cell lysates. In cells infected with herpes simplex virus type 1 (HSV-1) in the presence of azetidine, synthesis of cellular proteins, including polypeptide C, was suppressed and infected cell polypeptides ICP 4, 0, 22 and 27 (apparent mol. wt. 170000, 120000, 75000 and 60000, respectively) were made. All were phosphorylated and accumulated in the nucleus. Messenger RNA for the same four polypeptides was made in cells infected in the presence of cycloheximide. Thus, ICP 22 is distinct from cellular polypeptide C and is probably a virus-specific alpha polypeptide, although it differs from alpha ICP 4, 0 and 27 in that its rate of synthesis does not decline rapidly when later polypeptides are produced. It is modified after synthesis in at least two steps, the second of which may require a later virus-specific polypeptide. In cells infected with HSV-2 the synthesis of a polypeptide analogous to ICP 22 could not be detected.

The SNF3 gene is required for high-affinity glucose transport in the yeast Saccharomyces cerevisiae and has also been implicated in control of gene expression by glucose repression. We report here the nucleotide sequence of the cloned SNF3 gene. The predicted amino acid sequence shows that SNF3 encodes a 97-kilodalton protein that is homologous to mammalian glucose transporters and has 12 putative membrane-spanning regions. We also show that a functional SNF3-lacZ gene-fusion product cofractionates with membrane proteins and is localized to the cell surface, as judged by indirect immunofluorescence microscopy. Expression of the fusion protein is regulated by glucose repression.

In Model-Driven Engineering the primary artifact is a technology and architecture neutral model called a Platform Independent Model (PIM). The Use-Case, Responsibility Driven Analysis and Design (URDAD) is a service-oriented method which is used to construct a PIM commonly specified in the URDAD Domain- Specific Language (DSL). In this paper we show that model quality can be verified by specifying a set of quality constraints at metamodel level which are used to verify certain consistency, completeness, traceability and simplicity qualities of URDAD models. The set of constraints has been mapped onto the Object Constraint Language (OCL) and a tool used to verify these constraints has been developed. The set of constraints is also used by an URDAD model editor to verify aspects of model quality as it is being developed.