Preliminary Case Study Research Articles

Integrated Production of Fuels, Energy and Chemicals from Jatropha Curcas: Multi-objective Optimisation of Sustainable Value Chains

In this work, a comprehensive optimisation model, based on mixed-integer linear programming, was developed that can support complex decision-making related to multi-product Jatropha value chains and can capture the trade-offs between water, energy and land utilisation. The model can identify promising Jatropha value chains for sustainable and efficient production of energy, fuels and chemicals. This paper presents the optimisation model and the key findings from a preliminary case study on biodiesel production for the Philippines.

Capturing the long-term interdependencies between building thermal energy supply and demand in urban planning strategies

Urban areas play a crucial role in fostering low carbon energy patterns and the decarbonization of buildings energy consumption is at the heart of this process. Energy system analyses have recently gained the attention of urban policy makers due to their comprehensive and long-term perspective on the activities of the entire supply/demand chain, traditionally treated independently when shaping building urban energy strategies.This paper presents a spatial and temporally resolved urban energy system optimization model with specific features in order to describe the interactions between energy efficiency in buildings and heat supply strategies. A preliminary case study is proposed for offering numerical evidence to results. The results show that a planned combination of fuel switching, energy efficiency and building retrofit may complementary lead to meet ambitious climate targets at a reasonable added cost.From the results emerge that urban energy system models might help researcher and decision makers in generating robust holistic scenarios and in providing quantitative elements to exclude actions that are not economically affordable, technologically feasible and environmentally sustainable. Nevertheless, to be fully adoptable for real applications, existing barriers need to be overcome with special attention to the definition of input data protocols and the stakeholder involvement since the beginning.

Framework for network-level pavement condition assessment using remote sensing data mining

Pavement condition monitoring is fundamental for the efficient allocation of resources in transportation asset management. However, data collection involves laborious and costly procedures. Our study intends to investigate the usage of remote sensing data for network-level pavement condition assessment that offers a more cost-effective alternative and a rapid infrastructure assessment tool that can be used in the aftermath of natural disasters. Based on an extensive literature review, a data mining framework was established to train models that predict the pavement condition of different road segments. The framework exploits the inherent information of multispectral images by generating spectral related attributes. To identify pavement sampling areas, an automated procedure using image segmentation replaces manual surface digitizing. Unlike previous research, different classification models were used to approximate the mapping function from spectral information to pavement conditions. A preliminary case study was conducted with data provided by the City of Dallas and multispectral images acquired from the Texas Natural Resources Information System. The mean-shift segmentation algorithm was used to locate noise introducing areas on the pavement surface. Four different classification models were trained using k-nearest neighbors, naive Bayes, support vector machines, and a multilayer perceptron. The developed models were employed to predict the road surface condition class of a test set not included in the training procedure. The multilayer perceptron presented the highest accuracy level of 71%, showing that the framework might have the potential for future implementation.

Evaluation of conformal radiotherapy treatment planning of breast cancer patients: Preliminary case study patients from Persahabatan Central Hospital

Persahabatan Central Hospital has served radiotherapy treatment for cancer patients using linac, Elekta Precise and XiO treatment planning system (TPS) since May 2017. This study collected 91 breast cancer patients treated from May 2017 until January 2019. Most patients were preceded by surgery either mammae radical mastectomy (MRM) (83.5%) or breast conservative surgery (BCS) (16.5%). Conformal treatment planning generally performed with 2 tangential fields and most included oblique fields for treating axillary lymph nodes. Percentage of patients with clinical tumor volumes >400 cm3 was 29%, in the range of 200-400 cm3 was 36%, and the rest was <200 cm3. The lung volume irradiated with dose ≥20 Gy was used as one of parameters for treatment optimization. The mrm patient number with lung volume irradiated >30% was 9 persons (11.8%), in the range of 20-30% was 65 persons (85.5%), and <20% was 2 persons (2.6%). For the bcs patients, the number followed these criteria with lung volume of 20-30% was 13 persons (86.7%), and <20% was 2 persons (13.3%). Most breast cancer patients treated with radiotherapy were advanced stage preceded by mrm, treatment planning was difficult for achieving lung volume <30% that irradiated with the dose ≥20 Gy.

Business Practices to Minimize Safety Risks: A Case Study of Two Adventure Tourism Businesses in Malaysia

Risk is inherent in adventure tourism. Without risk, adventure tourism will lose their excitement and uniqueness. Managing risk in commercial adventure tourism operation is essential for the safety of travelers. The improper risk management in this business may lead to some issues such as injury and accidents. Risks involved in adventure tourism are frequently highlighted by the media, usually after a reported accident of fatality. The increased in the number of reported accidents by media in the adventure tourism sector recently, may give significant effect and harmful impact on business as well as the whole tourism industry. Thus, it is important for the commercial adventure tourism businesses and company providers to have effective tools and model(s) in managing the risk effectively to avoid any circumstances that lead to accidents in order for the business to run smoothly with high reputation and confidence of customers. This study explores whether or not Malaysian adventure tourism businesses adhere to any risk management guidelines or models. Two preliminary case studies of adventure tourism businesses in Malaysia illustrated that these businesses have no specific guidelines and risk management models that adventure tourism businesses should adhere to. In addition, findings from this study also demonstrated that no specific regulations imposed by the government for adventure tourism businesses to comply to. This study advises on the application and implementation of the Event Management Body of Knowledge (EMBOK) model as part of Malaysian adventure tourism businesses risk management responsibilities.

Quantitative assessment of microbial quality and safety risk: A preliminary case study of strengthening raspberry supply system in Chile

National governments are moving to integrate risk analysis frameworks into food safety management systems at the country level. However, this process is less advanced in developing countries. In this context, the Chilean Livestock and Agriculture Service (SAG), Food Quality and Safety Agency (ACHIPIA) and the University of Nebraska-Lincoln (UNL) collaborated on a project to control generic Escherichia coli and Hepatitis A virus (HAV) contamination in both fresh and frozen raspberry products destined for export. The objectives of this study were to 1) identify along the raspberry supply chain the most influential factors of E. coli and HAV contamination in the final products; and 2) evaluate the efficacies of possible interventions to control these influential factors. To achieve these objectives, a unified quantitative model of microbial contamination in raspberries was developed to describe the impact of factors in a continuum from the farm to the destination of importation on E. coli/HAV contamination in fresh and frozen raspberry products. Multiple surveys were conducted to obtain country-specific data on current common practices of producing and processing raspberries in Chile for inputs into the simulation model. The model estimated mean bacterial loads of −1.64 and −5.46 logCFU/g for E. coli and mean viral loads of −6.45 and −6.51 logPDU/g for HAV in fresh and frozen raspberries, respectively. Sensitivity and scenario analyses indicated that reduction of E. coli contamination in the end products can be effectively achieved by improving the quality of water used for pesticide application, as well as by controlling the transport and storage time and temperature along raspberries supply chain. By contrast, to control HAV contamination in the end products, efforts should be focused on improving the hygiene practices of berry handlers on the farm and at the packing plant. This project provides straightforward recommendations for Chilean food safety authorities to effectively prioritize their financial and human resources to proactively prevent microbial contamination in raspberries. Moreover, this project provide a framework that can be extended to other countries to promote capability building for applying risk-based food safety management systems for public health protection.

Toward a heuristic for teaching the visual rhetoric of pitch decks

This study examined how three successful entrepreneurs/investors assessed the visual rhetoric of actual pitch decks from novice entrepreneurs. We compare their evaluations to the result of a heuristic for assessing visual rhetoric, Color CRAYONTIP. While the pitch deck is recognized as a key artifact in entrepreneurship, no studies have specifically addressed the visual design of the deck nor the key design skills novice entrepreneurs should implement to effectively persuade potential investors of the idea's promise. This preliminary and exploratory case study begins a dialogue on this topic by performing a visual analysis of seven novice decks which were deemed successful by experienced angel investors. The analysis revealed five key skills that appear to account for the success of these decks with the reviewers: rhetorical awareness, typography, color, photography, and contrast.

Wind Turbine Wake Effects on Wind Resource Assessments – a Case Study

This paper describes a case study of wind turbine wake loss effects on wind resource assessment in cold region. One year wind park SCADA data is used. Computational Fluid Dynamics (CFD) based numerical simulations are carried out for wind resource assessment and estimation of resultant Annual Energy Production (AEP). Numerical results are compared with the field SCADA data, where a good agreement is found. To better understand the wind flow physics and effects of wind turbine turbulence wake loss effects, three different wake loss models are used for the numerical simulations, where results with wake model is found in best agreement with the AEP estimation from field SCADA data. A detailed comparison of all wind turbines is also presented with the gross AEP. A preliminary case study about wind park layout optimization has also been carried out which shows that AEP can be improved by optimizing the wind park layout and CFD simulations can be used as a tool in this regards.

Towards inductive learning of surgical task knowledge: a preliminary case study of the peg transfer task

Abstract Autonomy in robotic surgery will significantly improve the quality of interventions in terms of safety and recovery time for the patient, and reduce fatigue of surgeons and hospital costs. A key requirement for such autonomy is the ability of the surgical system to encode and reason with commonsense task knowledge, and to adapt to variations introduced by the surgical scenarios and the individual patients. However, it is difficult to encode all the variability in surgical scenarios and in the anatomy of individual patients a priori, and new knowledge often needs to be acquired and merged with the existing knowledge. At the same time, it is not possible to provide a large number of labeled training examples in the robotic surgery. This paper presents a framework based on inductive logic programming and answer set semantics for incrementally learning domain knowledge from a limited number of executions of basic surgical tasks. As an illustrative example, we focus on the peg transfer task, and learn state constraints and the preconditions of actions starting from different levels of prior knowledge. We do so using a small dataset comprising human and robotic executions with the da Vinci surgical robot in a challenging simulated scenario.

Von der Metapher zur Methode

Summary From Metaphor to Method. Network Analysis as an Instrument for Research into Pre-Modern Societies The paper introduces an important and promising branch into the field of the rapidly evolving Digital Humanities, the Social Network Analysis (SNA). SNA can be defined as the application of the graph theory to the problem of modelling and analysing social structures. The network paradigm stresses the importance of relational aspects in history and it fits very well into pre-modern mentality and social practices. In a weakly institutionalised face-to-face society, social entanglements and interactions were absolutely crucial. Today, the development of modern computer technology and the ubiquity of the World Wide Web as well as social networks such as Facebook promote the application of this research paradigm. The article alludes to recent research contributions and discusses frequent methodological objections against the use of SNA in medieval and early modern history studies. In a second step, medieval network thinking and networking strategies which can be found for instance in genealogical sources and humanistic exchange of letters are discussed as possible objects of historical network research. Finally, a preliminary case study demonstrates how techniques of Text Mining and SNA can be applied to the investigation of late medieval Vatican registers, providing new insights into the money transfer (payment of annates) between Germany and Rome during the pontificate of Pope Sixtus IV. (1471 - 1484).

LawCrypt: Secret Sharing for Attorney-Client Data in a Multi-Provider Cloud Architecture

The accelerated employment of cloud computing among law firms is due to multiple benefits, including wide accessibility and inter-organizational information sharing. Nevertheless, the project’s preliminary case study revealed lawyers’ mass neglect of standard precautionary measures and, consequently, a high proportion of security breaches, putting confidential and important documents at risk. The goal of the multi-provider cloud secret sharing architecture was to ensure confidentiality, availability, and integrity of attorney documents while maintaining greater efficiency than traditional encryption algorithms. After an exhaustive development phase involving considerable testing and optimizations, software assessments of the architecture indicate the low computational overhead of adding the secret-sharing approach to a multi-provider law firm sharing environment. The efficient combination of constructions satisfies the engineering criteria as ChaCha20-Poly1305 warrants authenticity and privacy, and secret sharing ensures availability and perfect privacy. Compared with AES in CFB mode, widely used for encrypting data in the Cloud today, the secret sharing implementation boasts almost a 40% improvement over all file sizes. The only possible way of compromising this system is if multiple cloud providers collude, which is still unlikely given that the documents are additionally encrypted.

Implementing Quality to Assess the Performance of the Educational System: A Preliminary Case Study at the Libyan University Al Jabal Al Gharbi

This article proposes an overview of higher education systems that have adopted a performance-based evaluation model. Our theoretical approach offers some primary concepts related to the field of evaluation and performance. A particular emphasis is placed on the idea of quality that is realised through increased research into quality control and compliance with quality standards within higher education. We have based this on a qualitative survey carried out in Libya, where this evaluation model has been implemented in higher education and which is aiming for an improvement in the academic success of students and a better standing in international rankings.

A preliminary experimental feasibility case study of energy upgrade of pellets of lignite and plastic waste mixtures

AbstractThe calorific value enhancement of lignite by briquetting with novolac resin and plastic wastes is discussed in this work. Mixtures of several types of lignite with novolac as binder, with or without polypropylene, were manufactured in the form of pellets by curing. Pellets were pyrolyzed at 300°C and 500°C, and weight losses were determined. Chemical transformations during curing were studied by Fourier‐transform infrared spectroscopy, and the corresponding changes in the microstructure of the pellets were investigated by optical microscopy. Specimens of cured pellets were tested for their impact resistance index (IRI) and water resistance index (WRI). The incorporation of polypropylene in the pellets leads to an increase of IRI and a decrease of WRI. The calorific value was measured for both cured and pyrolyzed pellets. All pellets exhibit increased lower calorific value compared with raw lignite, indicating an upgrade of their energy content.

The impact of evacuating on short-term disaster recovery: A study of individuals affected by Hurricane Harvey living in Texas counties

It is commonly accepted that evacuating disaster areas prior to the impact of an event is in everyone's best interest. As such, many studies have investigated what factors influence both evacuation behavior and return migration. However, few studies have specifically looked at the direct influence that the decision to evacuate may have on individuals' disaster recovery. Through the analysis of a representative sample of individuals affected by Hurricane Harvey living in Texas, this preliminary case study observes that evacuation negatively affected the extent to which people were able to recover in the short-term. This observation was not respective of race/ethnicity nor level of poverty. Additionally, being Hispanic had a positive relationship with the extent to which an individual recovered in the short-term. Future research recommendations are made in an effort to better understand these observations that may have profound implications on whether or not people choose to evacuate in future disasters.

Synthesis of Combined Heat Exchange Network and Utility Supply Chain

This paper involves the development of an integrated supply chain superstructure that describes the holistic synthesis of the heat demand of multiple co-located process plants within a geographical area and their associated utility supply chains. The integrated superstructure comprises a set of feedstock supply nodes which connects a set of utility demand nodes through a set of feedstock/utility transportation modes. Different kinds of biomass and waste-based feedstocks, including seasonality associated with their availabilities, from which hot utilities can be generated, and different modes of transportation, are considered. The model also takes into consideration periodic variations in heat demand of the plants. The proposed integrated model is demonstrated on a preliminary hypothetical case study and the solution obtained shows that supply locations with relatively higher capacity were selected in the optimal supply chain network, despite having relatively higher unit cost and located furthest from the demand locations. In terms of transport mode, only road truck haulage was selected due to its relatively lower investment cost.

Signaling across the senses: a captive case study in pair-bonded red-bellied lemurs (Eulemur rubriventer) at the Duke Lemur Center, NC, USA.

We provide a preliminary case study in red-bellied lemurs (Eulemur rubriventer) to illustrate a multimodal approach to understanding communication strategies within a species with obligate pair-bonds. From June to August 2012, we observed and analyzed signaling behaviors across three established red-bellied lemur pairs at Duke Lemur Center (Durham, NC, USA). Our aim was to assess how individuals combine signal modalities to communicate with pair-mates, and to determine whether these strategies vary by time of day, sex, or pair. We analyzed rates of occurrence of touch (allogrooming, mutual grooming, physical contact, and huddling), scent (scent marking and allomarking), and sound (close-distance contact calls) using Wilcoxon rank sum and exact binomial tests. Time of day impacted rates of occurrence across signal modalities, with higher rates of combined signaling within each modality occurring earlier in the day (p < 0.03). Across time periods, all pairs used auditory signals most frequently, followed by olfactory signals, and finally tactile and tactile-olfactory signals (p < 0.01, all comparisons). In fact, auditory signals frequently overlapped the olfactory signaling modality, and travel rarely occurred without accompanying vocalizations. However, red-bellied lemurs spent the highest percentage of their observed time in tactile signaling bouts (on average, 19.5% of total observed time across pairs). Males and females participated equally in most signaling behaviors (p > 0.1), with the exception of scent marking, which males used more frequently (p < 0.01). The results of this study will aid in developing methods and hypotheses to determine how wild red-bellied lemurs communicate to form, maintain, and advertise their pair-bonds.

Innovating public engagement and patient involvement through strategic collaboration and practice

BackgroundPatient and public involvement and engagement is an important and expected component of health-related research activity in the UK. Specifically within the health research sphere, public engagement (usually defined as raising awareness of research) and patient involvement (usually defined as actively involving people in research) have traditionally been seen as separate but have much to gain from working together towards a common goal of better health outcomes for all.MethodsThis paper describes a unique approach taken by the Public Programmes Team: a small interdisciplinary team of public engagement specialists, with backgrounds in science, community development, public engagement and involvement, policy, ethics, communications, industry, museums and creative practice, embedded within translational research infrastructure and delivery in Manchester in the North West of England. We propose a new model of professional practice – a 'cycle' of engagement and involvement – innovating across the complementary fields of public engagement and patient involvement, and working inclusively and in partnership with people in health research. Further, our approach capitalises on strategic collaboration offering economies of scale and a joined up way of working. Our ambition is to boldly experiment, learn and reflect, responsibly and based on evidence and partnerships, using methods of engagement that address issues of social justice.ResultsHere, we report on preliminary case studies exemplifying the impact of our approach, and data relating to achievements and learning between April 2017 and March 2018. Informed by our findings, we propose that our approach has the potential to be replicated elsewhere.ConclusionsOur practice and the beginning of its evaluation lead us to believe that our way of working and model of professional practice – the ‘cycle’ of engagement and involvement – is effective in: addressing our vision of making health research relevant and inclusive for everyone; and embedding and joining up public involvement in a busy and fertile translational health research ecosystem.

Collaborative innovation in the sharing economy

Purpose With the emergence of the sharing economy paradigm, the process of innovation is no longer unidirectional, but cyclical. This paradigm shift requires a better understanding of social actors to fully leverage the promise of co-innovation in the sharing economy. To this end, the purpose of this paper is to develop a classification model to profile social actors based on their motivation to participate in different co-innovation activities. Design/methodology/approach A preliminary case study was first conducted to identify actors’ motivations to continuously participate in co-innovation activities. Next, a survey was administrated to validate the measurement model and then a discriminant analysis was run on a sample of 244 actors to classify actors based on their willingness to participate in three forms of co-innovation activities. Lastly, the resultant classifiers were cross-validated. Findings The results indicate that financial gains, entrepreneurship and learning are significant predictors of ideation (sharing new ideas). Enjoyment and learning are strong indicators of collaboration (sharing knowledge or experience), whereas networking, enjoyment, and altruism are most strongly related to socialization (sharing network and connections). These findings highlight three classes of social actors – ideators, collaborators and networkers – based on motivational differences. Originality/value Co-innovation among individual inventors is an understudied aspect of the sharing economy. This study provides a theoretically parsimonious classification model to profile social actors, predict the sharing activities in co-innovation networks, and highlight the importance of platform design to appeal to different classes of potential contributors in collaborative innovation.

Biostimulants for Plant Growth Promotion and Sustainable Management of Phytoparasitic Nematodes in Vegetable Crops

The parasitism of root-knot nematodes, Meloidogyne spp., can cause heavy yield losses to vegetable crops. Plant biostimulants are often reported for a side-suppressive effect on these pests and many commercial products are increasingly included in sustainable nematode control strategies. Source materials of most biostimulants derived from plant or seaweed raw materials were documented for a reliable suppression of root-knot nematode species, whereas the suppressiveness of microbial biostimulants was found largely variable, as related to the crop and to environmental factors. Chitosan-based biostimulants were also stated for a variable phytonematode suppression, though clearly demonstrated only by a few number of studies. In a preliminary experimental case study, four commercial biostimulants based on quillay extract (QE), sesame oil (SO), seaweeds (SE), or neem seed cake (NC) were comparatively investigated for their effects against the root-knot nematode M. incognita on potted tomato. Soil treatments with all the four biostimulants resulted in a significant reduction of nematode eggs and galls on tomato roots, though NC and SO were significantly more suppressive than QE or SE. In addition, almost all biostimulant treatments also resulted in a significant improvement of tomato growth compared to the non-treated control. These preliminary results seem to confirm the literature data and clearly indicate the potential role of biostimulants for a safe nematode management both in organic and integrated crop systems.

An early-stage analysis of climate-adaptive designs for multi-family buildings under future climate scenario: Case studies in Rome, Italy and Stockholm, Sweden

This paper presents a preliminary case study of climate-adaptive designs for urban multi-family buildings at early stage, to allow thermal comfort and minimum energy use from today to the last part of 21st century. The generated future climate data combined with comfort model assessment has been proposed as a new way including future climate scenarios in preliminary building design for two representative sites, in Rome, Italy and Stockholm, Sweden. The existing vulnerability to the expected climate conditions from psychometric analysis indicates that: (1) the climate trend in Rome would gradually lead to more failures in the majority of conventional adaptive design measures, as the cooling and dehumidification demands would rise from 5.3% to 23.6%, while the heating and humidification demands would decrease from 27% to 16%; (2) the climate trend in Stockholm would result in an increased comfort period by exploiting more adaptive design measures, since the heating and humidification demands would be reduced from 67% to 53%. However, the cooling and dehumidification demands would increase slightly from 0% to 1.5%. Accordingly, four main key risks are identified: 1) overheating would become a rising increasing public health threat for buildings in Rome that rely exclusively on natural ventilation; 2) open questions remain for the design team in the area of correct cooling load selection, additional space for the future installation and the effectiveness of current cooling device etc.; 3) occasional heat waves and gradual rising humidity levels are expected to be a vulnerable topic for conventional lightweight building in Stockholm; 4) buildings with a heavy heating load would tend to have greater cooling demand, especially those with poor ventilation resources or greater internal gains. In conclusion, it is suggested that envelope optimization, whichever climate type, is one of the most efficient and effective adaptation measures towards future climate conditions.