Old Colony Railroad, Massachusetts, 1873 (Raster Image)

This layer is a georeferenced raster image of the historic paper map entitled: Old Colony Railroad and connections, [by] E.N. Winslow, del. It was published in 1873. Covers southeastern Massachusetts, from Boston to Cape Cod. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Massachusetts State Plane Coordinate System, Mainland Zone (in Feet) (Fipszone 2001). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, or other information associated with the principal map. This map shows features such as roads, railroads, railroad stations, drainage, town boundaries and more. Includes two illustrations. This layer is part of a selection of digitally scanned and georeferenced historic maps of Massachusetts from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of regions, originators, ground condition dates (1755-1922), scales, and purposes. The digitized selection includes maps of: the state, Massachusetts counties, town surveys, coastal features, real property, parks, cemeteries, railroads, roads, public works projects, etc.

Choosing organics: A path analysis of factors underlying the selection of organic food among Australian consumers

Path analysis of attitudinal, motivational, demographic and behavioural factors influencing food choice among Australian consumers who had consumed at least some organic food in the preceding 12 months showed that concern with the naturalness of food and the sensory and emotional experience of eating were the major determinants of increasing levels of organic consumption. Increasing consumption was also related to other 'green consumption' behaviours such as recycling and to lower levels of concern with convenience in the purchase and preparation of food. Most of these factors were, in turn, strongly affected by gender and the level of responsibility taken by respondents for food provisioning within their households, a responsibility dominated by women. Education had a slightly negative effect on the levels of concern for sensory and emotional appeal due to lower levels of education among women. Income, age, political and ecological values and willingness to pay a premium for safe and environmentally friendly foods all had extremely minor effects. (C) 2004 Elsevier Ltd. All rights reserved.

Autologous hemopoietic stem cell transplantation in severe rheumatoid arthritis: A report from the EBMT and ABMTR

Objective. Since 1996, autologous hemopoietic stem cell transplantation (HSCT) has been used to treat severe rheumatoid arthritis (RA). To date, published reports have been individual cases or series containing small numbers. This study combined the worldwide experience in a single analysis. Methods. The Autoimmune Disease Databases of the European Group for Blood and Marrow Transplantation (EBMT) and the Autologous Blood and Marrow Transplant Registry (ABMTR) were used to identify patients with RA treated with autologous HSCT. Further information relating to patient and treatment-specific variables was obtained by questionnaire. Results. Seventy-six patients were registered from 15 centers. Seventy-three patients had received autologous HSCT, and in 3 patients hematopoietic stem cells (HSC) were mobilized but not transplanted. Transplanted patients (median age 42 yrs, 74% female, 86% rheumatoid factor positive) had been previously treated with a mean of 5 (range 2-9) disease modifying antirheumatic drugs (DMARD). Significant functional impairment was present, with a median Health Assessment Questionnaire (HAQ) score of 1.4 (range 1.1-2.0) and Steinbrocker score mean 2.39 (SD 0.58). The high dose treatment regimen was cyclophosphamide (CYC) alone in the majority of patients, mostly 200 mg/kg (n = 62). Seven patients received anti-thymocyte globulin (ATG) in addition to CYC, 2 patients busulfan and CYC (BuCYC), and one patient CYC with total body irradiation and ATG. One patient received fludarabine with ATG. Following treatment, one patient received bone marrow but the rest received chemotherapy and/or granulocyte colony-stimulating factor mobilized peripheral blood stem cells. The harvest was unmanipulated in 28 patients, the rest receiving some form of lymphocyte depletion, mostly through CD34+ selection. Median followup was 16 months (range 3-55). Responses were measured using the American College of Rheumatology (ACR) criteria. Forty-nine patients (67%) achieved at least ACR 50% response at some point following transplant. There was a significant reduction in the level of disability measured by the HAQ (p < 0.005). Most patients restarted DMARD within 6 months for persistent or recurrent disease activity, which provided disease control in about half the cases. Response was significantly related to seronegative RA (p = 0.02) but not to duration of disease, number of previous DMARD, presence of HLA-DR4, or removal of lymphocytes from the graft. There was no direct transplant related mortality, although one patient, treated with the BuCYC regimen, died 5 months post-transplant from infection and incidental non-small cell lung cancer. Conclusion. Autologous HSCT is a relatively safe form of salvage treatment in severe, resistant RA. In these open label studies significant responses were achieved in most patients, with over 50% achieving an ACR 50 or more response at 12 months. Although the procedure is not curative, recurrent or persistent disease activity may be subsequently controlled in some patients with DMARD. Clinical trials are necessary to develop this approach inpatients with aggressive disease who have failed conventional treatment including anti-tumor necrosis factor agents.

Innovation, productivity and growth in US business services:a firm-level analysis

This paper examines the impact of innovation on the performance of US business service firms. We distinguish between different levels of innovation (new-to-market and new-to-firm) in our analysis, and allow explicitly for sample selection issues. Reflecting the literature, which highlights the importance of external interaction in service innovation, we pay particular attention to the role of external innovation linkages and their effect on business performance. We find that the presence of service innovation and its extent has a consistently positive effect on growth, but no effect on productivity. There is evidence that the growth effect of innovation can be attributed, at least in part, to the external linkages maintained by innovators in the process of innovation. External linkages have an overwhelmingly positive effect on (innovator) firm performance, regardless of whether innovation is measured as a discrete or continuous variable, and regardless of the level of innovation considered.

The selection of biodiversity indicators for business landholdings

Businesses are seen as the next stage in delivering biodiversity improvements linked to local and UK Biodiversity Action Plans. Global discussion of biodiversity continues to grow, with the Millennium Ecosystem Assessment, updates to the Convention on Biological Diversity and The Economics of Ecosystems and Biodiversity being published during the time of this project. These publications and others detail the importance of biodiversity protection and also the lack of strategies to deliver this at an operational level. Pressure on UK landholding businesses is combined with significant business opportunities associated with biodiversity engagement. However, the measurement and reporting of biodiversity by business is currently limited by the complexity of the term and the lack of suitable procedures for the selection of metrics. Literature reviews identified confusion surrounding biodiversity as a term, limited academic literature regarding business and choice of biodiversity indicators. The aim of the project was to develop a methodology to enable companies to identify, quantify and monitor biodiversity. Research case studies interviews were undertaken with 10 collaborating organisations, selected to represent =best practice‘ examples and various situations. Information gained through case studies was combined with that from existing literature. This was used to develop a methodology for the selection of biodiversity indicators for company landholdings. The indicator selection methodology was discussed during a second stage of case study interviews with 4 collaborating companies. The information and opinions gained during this research was used to modify the methodology and provide the final biodiversity indicator selection methodology. The methodology was then tested through implementation at a mineral extraction site operated by a multi-national aggregates company. It was found that the methodology was a suitable process for implementation of global and national systems and conceptual frameworks at the practitioner scale. Further testing of robustness by independent parties is recommended to improve the system.

Knowledge-based system for casting process selection

Design of casting entails the knowledge of various interacting factors that are unique to casting process, and, quite often, product designers do not have the required foundry-specific knowledge. Casting designers normally have to liaise with casting experts in order to ensure the product designed is castable and the optimum casting method is selected. This two-way communication results in long design lead times, and lack of it can easily lead to incorrect casting design. A computer-based system at the discretion of a design engineer can, however, alleviate this problem and enhance the prospect of casting design for manufacture. This paper proposes a knowledge-based expert system approach to assist casting product designers in selecting the most suitable casting process for specified casting design requirements, during the design phase of product manufacture. A prototype expert system has been developed, based on production rules knowledge representation technique. The proposed system consists of a number of autonomous but interconnected levels, each dealing with a specific group of factors, namely, casting alloy, shape and complexity parameters, accuracy requirements and comparative costs, based on production quantity. The user interface has been so designed to allow the user to have a clear view of how casting design parameters affect the selection of various casting processes at each level; if necessary, the appropriate design changes can be made to facilitate the castability of the product being designed, or to suit the design to a preferred casting method.

A novel adaptive weight selection algorithm for multi-objective multi-agent reinforcement learning

To solve multi-objective problems, multiple reward signals are often scalarized into a single value and further processed using established single-objective problem solving techniques. While the field of multi-objective optimization has made many advances in applying scalarization techniques to obtain good solution trade-offs, the utility of applying these techniques in the multi-objective multi-agent learning domain has not yet been thoroughly investigated. Agents learn the value of their decisions by linearly scalarizing their reward signals at the local level, while acceptable system wide behaviour results. However, the non-linear relationship between weighting parameters of the scalarization function and the learned policy makes the discovery of system wide trade-offs time consuming. Our first contribution is a thorough analysis of well known scalarization schemes within the multi-objective multi-agent reinforcement learning setup. The analysed approaches intelligently explore the weight-space in order to find a wider range of system trade-offs. In our second contribution, we propose a novel adaptive weight algorithm which interacts with the underlying local multi-objective solvers and allows for a better coverage of the Pareto front. Our third contribution is the experimental validation of our approach by learning bi-objective policies in self-organising smart camera networks. We note that our algorithm (i) explores the objective space faster on many problem instances, (ii) obtained solutions that exhibit a larger hypervolume, while (iii) acquiring a greater spread in the objective space.

Dynamic decision-making based on NFR for managing software variability and configuration selection

Due to dynamic variability, identifying the specific conditions under which non-functional requirements (NFRs) are satisfied may be only possible at runtime. Therefore, it is necessary to consider the dynamic treatment of relevant information during the requirements specifications. The associated data can be gathered by monitoring the execution of the application and its underlying environment to support reasoning about how the current application configuration is fulfilling the established requirements. This paper presents a dynamic decision-making infrastructure to support both NFRs representation and monitoring, and to reason about the degree of satisfaction of NFRs during runtime. The infrastructure is composed of: (i) an extended feature model aligned with a domain-specific language for representing NFRs to be monitored at runtime; (ii) a monitoring infrastructure to continuously assess NFRs at runtime; and (iii) a exible decision-making process to select the best available configuration based on the satisfaction degree of the NRFs. The evaluation of the approach has shown that it is able to choose application configurations that well fit user NFRs based on runtime information. The evaluation also revealed that the proposed infrastructure provided consistent indicators regarding the best application configurations that fit user NFRs. Finally, a benefit of our approach is that it allows us to quantify the level of satisfaction with respect to NFRs specification.

Handling high level of censoring for endovascular aortic repair risk prediction

Feature selection is important in medical field for many reasons. However, selecting important variables is a difficult task with the presence of censoring that is a unique feature in survival data analysis. This paper proposed an approach to deal with the censoring problem in endovascular aortic repair survival data through Bayesian networks. It was merged and embedded with a hybrid feature selection process that combines cox's univariate analysis with machine learning approaches such as ensemble artificial neural networks to select the most relevant predictive variables. The proposed algorithm was compared with common survival variable selection approaches such as; least absolute shrinkage and selection operator LASSO, and Akaike information criterion AIC methods. The results showed that it was capable of dealing with high censoring in the datasets. Moreover, ensemble classifiers increased the area under the roc curves of the two datasets collected from two centers located in United Kingdom separately. Furthermore, ensembles constructed with center 1 enhanced the concordance index of center 2 prediction compared to the model built with a single network. Although the size of the final reduced model using the neural networks and its ensembles is greater than other methods, the model outperformed the others in both concordance index and sensitivity for center 2 prediction. This indicates the reduced model is more powerful for cross center prediction.

Client QoE-oriented segment selection for DASH

A segment selection method controlled by Quality of Experience (QoE) factors for Dynamic Adaptive Streaming over HTTP (DASH) is presented in this paper. Current rate adaption algorithms aim to eliminate buffer underrun events by significantly reducing the code rate when experiencing pauses in replay. In reality, however, viewers may choose to accept a level of buffer underrun in order to achieve an improved level of picture fidelity or to accept the degradation in picture fidelity in order to maintain the service continuity. The proposed rate adaption scheme in our work can maximize the user QoE in terms of both continuity and fidelity (picture quality) in DASH applications. It is shown that using this scheme a high level of quality for streaming services, especially at low packet loss rates, can be achieved. Our scheme can also maintain a best trade-off between continuity-based quality and fidelity-based quality, by determining proper threshold values for the level of quality intended by clients with different quality requirements. In addition, the integration of the rate adaptation mechanism with the scheduling process is investigated in the context of a mobile communication network and related performances are analyzed.

Modelling question selection behaviour in online communities

Value of online Question Answering (QandA) communities is driven by the question-answering behaviour of its members. Finding the questions that members are willing to answer is therefore vital to the effcient operation of such communities. In this paper, we aim to identify the parameters that cor- relate with such behaviours. We train different models and construct effective predictions using various user, question and thread feature sets. We show that answering behaviour can be predicted with a high level of success.

Firm-level productivity growth in Northern Ireland:the impact of exporting, innovation and public financial assistance

Motivated by the historically poor productivity performance of Northern Ireland firms and the longstanding productivity gap with the UK, the aim of this thesis is to examine, through the use of firm-level data, how exporting, innovation and public financial assistance impact on firm productivity growth. These particular activities are investigated due to the continued policy focus on their link to productivity growth and the theoretical claims of a direct positive relationship. In order to undertake these analyses a newly constructed dataset is used which links together cross-sectional and longitudinal data over the 1998-2008 period from the Annual Business Survey, the Manufacturing Sales and Export Survey; the Community Innovation Survey and Invest NI Selective Financial Assistance (SFA) payment data. Econometric methodologies are employed to estimate each of the relationships with regards to productivity growth, making use in particular of Heckman selection techniques and propensity score matching to take account of critical issues of endogeneity and selection bias. The results show that more productive firms self-select into exporting but there is no resulting productivity effect from starting to export; contesting the argument for learning-by-exporting. Product innovation is also found to have no impact on productivity growth over a four year period but there is evidence of a negative process innovation impact, likely to reflect temporary learning effects. Finally SFA assistance, including the amount of the payment, is found to have no short term impact on productivity growth suggesting substantial deadweight effects and/or targeting of inefficient firms. The results provide partial evidence as to why Northern Ireland has failed to narrow the productivity gap with the rest of the UK. The analyses further highlight the need for access to comprehensive firm-level data for research purposes, not least to underpin robust evidence-based policymaking.

Adaptív döntéshozatal a beszállítóválasztás példáján (Adaptive decision-making on example of the supplier selection)

Ez a tanulmány a projektvezetési szakirodalomban kialakult ismeretanyagot szem előtt tartva (noha tételesen nem hivatkozva arra) tárja fel azt a sajátos és tipikusnak nevezhető kontextust, amelyben a projektalapú szervezetek projektmarketing tevékenysége megnyilvánul. A tanulmány célja tehát nem magának a projektmarketingnek a kérdéskörére irányul, hanem elsősorban annak projektspecifikus kontextusára. Jellegét illetően a tanulmány spekulatív jellegű, vagyis lényegét tekintve nem empirikus kutatási eredményekből levont következtetésekre épül. _____ The author analyses the cognitive level of individual decisions by placing the adaptive decision-maker in the centre of interest. The main question is how do adaptive processes evolve and what factors determine the adaptive mechanism. The author builds on his own qualitative study conducted with the Grounded Theory Methodology in the SME sector. The supplier selection decision is chosen from the wide range of business decisions. From the research results the two elements of the adaptive mechanism – the metastructure and the attitude set –, the process of their evolution and the factors determining this process are presented. The findings here are a middle-range theory, which can be elaborated further, but they provide some interesting insights already.

Selection Of Students For Hotel Schools: A Comparative Study

In the discussion - Selection Of Students For Hotel Schools: A Comparative Study - by William Morgan, Professor, School of Hospitality Management at Florida International University, Morgan’s initial observation is: “Standards for the selection of students into schools of hospitality management around the world vary considerably when it comes to measuring attitudes toward the industry. The author discusses current standards and recommends some changes.” In addition to intellectual ability, Professor Morgan wants you to know that an intangible element such as attitude is an equally important consideration to students seeking curriculum and careers in the hospitality field. “…breaches in behavior or problems in the tourist employee encounter are often caused by attitudinal conditions which pre exist the training and which were not able to be totally corrected by the unfreezing, movement, and refreezing processes required in attitudinal change,” says Morgan. “…other than for some requirements for level or grade completed or marks obtained, 26 of the 54 countries sampled (48.1 percent) had no pre-selection process at all. Of those having some form of a selection process (in addition to grades), 14 schools in 12 countries (22.2 percent) had a formal admissions examination,” Professor Morgan empirically provides. “It was impossible, however, to determine the scope of this admissions examination as it might relate to attitude.” The attitude intangible is a difficult one to quantify. With an apparent sameness in hotels, restaurants, and their facilities the significant distinctions are to be found in their employees. This makes the selection process for both schools and employers a high priority. Moreover, can a student, or a prospective employee, overcome stereotypes and prejudices to provide a high degree of service in the hospitality industry? This query is an important element of this article. “If utilized in the hotel, technical, or trade school or in the hiring process at the individual facility, this [hiring] process would provide an opportunity to determine if the prospective student or worker is receptive to the training to be received,” advises Professor Morgan. “Such a student or worker is realistic in his aims and aspirations, ready in his ability to receive training, and responsive to the needs of the guest, often someone very different from himself in language, dress, or degree of creature comforts desired,” your author further counsels. Professor Morgan looks to transactional analysis, role playing, languages, and cross cultural education as playing significant roles in producing well intentioned and knowledgeable employees. He expands upon these concepts in the article. Professor Morgan holds The International Center of Glion, Switzerland in high regard and cites that program’s efforts to maintain relationships and provide graduates with ongoing attitudinal enlightenment programs.