Risks, resources and reason: understanding smallholder decisions around farming system interventions in Eastern Indonesia

Adoption of new cattle management practices by Indonesian smallholders occurs less as a ‘technology transfer’ in the classical sense but rather as a series of conscious decisions by farming households weighing risks and resources as well as matching innovations to livelihood strategies. This paper uncovers the context of decisions and communication of innovations by way of social networks. The research looks at two geographically distinct cases where new cattle management practices have been introduced. We apply the lens of a common sense framework initially introduced by Clifford Geertz. Smallholder decisions are analysed within a socio-cultural context and a particular set of resources, risks and livelihood objectives. We show that the respective value placed on land, cattle and food security is central to adoption of new cattle management techniques. Far from accepting everything novel, smallholders are selective and willing to make changes to their farming system if they do not conflict with livelihood strategies. Innovations are communicated through a range of existing social networks and are either matched to existing livelihood strategies or perceived as stepping-stones out of agriculture.

Concepts and methods for efficient decentralized learning in federated settings

Deep Neural Networks (DNNs) have revolutionized a wide range of applications beyond traditional machine learning and artificial intelligence fields, e.g., computer vision, healthcare, natural language processing and others. At the same time, edge devices have become central in our society, generating an unprecedented amount of data which could be used to train data-hungry models such as DNNs. However, the potentially sensitive or confidential nature of gathered data poses privacy concerns when storing and processing them in centralized locations. To this purpose, decentralized learning decouples model training from the need of directly accessing raw data, by alternating on-device training and periodic communications. The ability of distilling knowledge from decentralized data, however, comes at the cost of facing more challenging learning settings, such as coping with heterogeneous hardware and network connectivity, statistical diversity of data, and ensuring verifiable privacy guarantees. This Thesis proposes an extensive overview of decentralized learning literature, including a novel taxonomy and a detailed description of the most relevant system-level contributions in the related literature for privacy, communication efficiency, data and system heterogeneity, and poisoning defense. Next, this Thesis presents the design of an original solution to tackle communication efficiency and system heterogeneity, and empirically evaluates it on federated settings. For communication efficiency, an original method, specifically designed for Convolutional Neural Networks, is also described and evaluated against the state-of-the-art. Furthermore, this Thesis provides an in-depth review of recently proposed methods to tackle the performance degradation introduced by data heterogeneity, followed by empirical evaluations on challenging data distributions, highlighting strengths and possible weaknesses of the considered solutions. Finally, this Thesis presents a novel perspective on the usage of Knowledge Distillation as a mean for optimizing decentralized learning systems in settings characterized by data heterogeneity or system heterogeneity. Our vision on relevant future research directions close the manuscript.

Modelling, simulations and monitoring for sustainable plant and animal production systems through precision technique

Protected crop production is a modern and innovative approach to cultivating plants in a controlled environment to optimize growth, yield, and quality. This method involves using structures such as greenhouses or tunnels to create a sheltered environment. These productive solutions are characterized by a careful regulation of variables like temperature, humidity, light, and ventilation, which collectively contribute to creating an optimal microclimate for plant growth. Heating, cooling, and ventilation systems are used to maintain optimal conditions for plant growth, regardless of external weather fluctuations. Protected crop production plays a crucial role in addressing challenges posed by climate variability, population growth, and food security. Similarly, animal husbandry involves providing adequate nutrition, housing, medical care and environmental conditions to ensure animal welfare. Then, sustainability is a critical consideration in all forms of agriculture, including protected crop and animal production. Sustainability in animal production refers to the practice of producing animal products in a way that minimizes negative impacts on the environment, promotes animal welfare, and ensures the long-term viability of the industry. Then, the research activities performed during the PhD can be inserted exactly in the field of Precision Agriculture and Livestock farming. Here the focus is on the computational fluid dynamic (CFD) approach and environmental assessment applied to improve yield, resource efficiency, environmental sustainability, and cost savings. It represents a significant shift from traditional farming methods to a more technology-driven, data-driven, and environmentally conscious approach to crop and animal production. On one side, CFD is powerful and precise techniques of computer modeling and simulation of airflows and thermo-hygrometric parameters, that has been applied to optimize the growth environment of crops and the efficiency of ventilation in pig barns. On the other side, the sustainability aspect has been investigated and researched in terms of Life Cycle Assessment analyses.

Network analysis and machine learning assist drug repurposing and safety assessment in neurological diseases

In recent decades, two prominent trends have influenced the data modeling field, namely network analysis and machine learning. This thesis explores the practical applications of these techniques within the domain of drug research, unveiling their multifaceted potential for advancing our comprehension of complex biological systems. The research undertaken during this PhD program is situated at the intersection of network theory, computational methods, and drug research. Across six projects presented herein, there is a gradual increase in model complexity. These projects traverse a diverse range of topics, with a specific emphasis on drug repurposing and safety in the context of neurological diseases. The aim of these projects is to leverage existing biomedical knowledge to develop innovative approaches that bolster drug research. The investigations have produced practical solutions, not only providing insights into the intricacies of biological systems, but also allowing the creation of valuable tools for their analysis. In short, the achievements are: • A novel computational algorithm to identify adverse events specific to fixed-dose drug combinations. • A web application that tracks the clinical drug research response to SARS-CoV-2. • A Python package for differential gene expression analysis and the identification of key regulatory "switch genes". • The identification of pivotal events causing drug-induced impulse control disorders linked to specific medications. • An automated pipeline for discovering potential drug repurposing opportunities. • The creation of a comprehensive knowledge graph and development of a graph machine learning model for predictions. Collectively, these projects illustrate diverse applications of data science and network-based methodologies, highlighting the profound impact they can have in supporting drug research activities.

The choice of the best among the shortest routes in transparent optical networks

This work introduces the problem of the best choice among M combinations of the shortest paths for dynamic provisioning of lightpaths in all-optical networks. To solve this problem in an optimized way (shortest path and load balance), a new fixed routing algorithm, named Best among the Shortest Routes (BSR), is proposed. The BSR`s performance is compared in terms of blocking probability and network utilization with Dijkstra`s shortest path algorithm and others algorithms proposed in the literature. The evaluated scenarios include several representative topologies for all-optical networking and different wavelength conversion architectures. For all studied scenarios, BSR achieved superior performance. (C) 2010 Elsevier B.V. All rights reserved.

Mutually connected phase-locked loop networks: dynamical models and design parameters

Distribution of timing signals is an essential factor for the development of digital systems for telecommunication networks, integrated circuits and manufacturing automation. Originally, this distribution was implemented by using the master-slave architecture with a precise master clock generator sending signals to phase-locked loops (PLL) working as slave oscillators. Nowadays, wireless networks with dynamical connectivity and the increase in size and operation frequency of the integrated circuits suggest that the distribution of clock signals could be more efficient if mutually connected architectures were used. Here, mutually connected PLL networks are studied and conditions for synchronous states existence are analytically derived, depending on individual node parameters and network connectivity, considering that the nodes are nonlinear oscillators with nonlinear coupling conditions. An expression for the network synchronisation frequency is obtained. The lock-in range and the transmission error bounds are analysed providing hints to the design of this kind of clock distribution system.

New simple and efficient heuristics for the uncapacitated single allocation hub location problem

Hub-and-spoke networks are widely studied in the area of location theory. They arise in several contexts, including passenger airlines, postal and parcel delivery, and computer and telecommunication networks. Hub location problems usually involve three simultaneous decisions to be made: the optimal number of hub nodes, their locations and the allocation of the non-hub nodes to the hubs. In the uncapacitated single allocation hub location problem (USAHLP) hub nodes have no capacity constraints and non-hub nodes must be assigned to only one hub. In this paper, we propose three variants of a simple and efficient multi-start tabu search heuristic as well as a two-stage integrated tabu search heuristic to solve this problem. With multi-start heuristics, several different initial solutions are constructed and then improved by tabu search, while in the two-stage integrated heuristic tabu search is applied to improve both the locational and allocational part of the problem. Computational experiments using typical benchmark problems (Civil Aeronautics Board (CAB) and Australian Post (AP) data sets) as well as new and modified instances show that our approaches consistently return the optimal or best-known results in very short CPU times, thus allowing the possibility of efficiently solving larger instances of the USAHLP than those found in the literature. We also report the integer optimal solutions for all 80 CAB data set instances and the 12 AP instances up to 100 nodes, as well as for the corresponding new generated AP instances with reduced fixed costs. Published by Elsevier Ltd.

Environmental, land-use and economic implications of Brazilian sugarcane expansion 1996-2006

Governments are promoting biofuels and the resulting changes in land use and crop reallocation to biofuels production have raised concerns about impacts on environment and food security. The promotion of biofuels has also been questioned based on suggested marginal contribution to greenhouse gas emissions reduction, partly due to induced land use change causing greenhouse gas emissions. This study reports how the expansion of sugarcane in Brazil during 1996-2006 affected indicators for environment, land use and economy. The results indicate that sugarcane expansion did not in general contribute to direct deforestation in the traditional agricultural region where most of the expansion took place. The amount of forests on farmland in this area is below the minimum stated in law and the situation did not change over the studied period. Sugarcane expansion resulted in a significant reduction of pastures and cattle heads and higher economic growth than in neighboring areas. It could not be established to what extent the discontinuation of cattle production induced expansion of pastures in other areas, possibly leading to indirect deforestation. However, the results indicate that a possible migration of the cattle production reached further than the neighboring of expansion regions. Occurring at much smaller rates, expansion of sugarcane in regions such as the Amazon and the Northeast region was related to direct deforestation and competition with food crops, and appear not to have induced economic growth. These regions are not expected to experience substantial increases of sugarcane in the near future, but mitigating measures are warranted.

Multiresolution spatial databases: Making web-based spatial applications faster

Spatial data has now been used extensively in the Web environment, providing online customized maps and supporting map-based applications. The full potential of Web-based spatial applications, however, has yet to be achieved due to performance issues related to the large sizes and high complexity of spatial data. In this paper, we introduce a multiresolution approach to spatial data management and query processing such that the database server can choose spatial data at the right resolution level for different Web applications. One highly desirable property of the proposed approach is that the server-side processing cost and network traffic can be reduced when the level of resolution required by applications are low. Another advantage is that our approach pushes complex multiresolution structures and algorithms into the spatial database engine. That is, the developer of spatial Web applications needs not to be concerned with such complexity. This paper explains the basic idea, technical feasibility and applications of multiresolution spatial databases.

Relationship between use of technology and employment rates for people with physical disabilities in Australia: Implications for education and training programmes

This study examined the impact of computer and assistive device use on the employment status and vocational modes of people with physical disabilities in Australia. A survey was distributed to people over 15 years in age with physical disabilities living in the Brisbane area. Responses were received from 82 people, including those with spinal cord injuries, cerebral palsy and muscular dystrophy. Of respondents 46 were employed, 22 were unemployed, and 12 were either students or undertaking voluntary work. Three-quarters of respondents used a computer in their occupations, while 15 used assistive devices. Using logistic regression analysis it was found that gender, education, level of computer skill and computer training were significant predictors of employment outcomes. Neither the age of respondent nor use of assistive software were significant predictors. From information obtained in this study guidelines for a training programme designed to maximize the employability of people with physical disabilities were developed.

MDA-based re-engineering with Object-Z

This paper describes a practical application of MDA and reverse engineering based on a domain-specific modelling language. A well defined metamodel of a domain-specific language is useful for verification and validation of associated tools. We apply this approach to SIFA, a security analysis tool. SIFA has evolved as requirements have changed, and it has no metamodel. Hence, testing SIFA’s correctness is difficult. We introduce a formal metamodelling approach to develop a well-defined metamodel of the domain. Initially, we develop a domain model in EMF by reverse engineering the SIFA implementation. Then we transform EMF to Object-Z using model transformation. Finally, we complete the Object-Z model by specifying system behavior. The outcome is a well-defined metamodel that precisely describes the domain and the security properties that it analyses. It also provides a reliable basis for testing the current SIFA implementation and forward engineering its successor.

The relationship between commercial agriculture and food availability to Kenyan farm families: A case study

This article examines the effects of agricultural commercialization and other factors on per capita food availability by means of a case study in the Nyeri district in Kenya. It was found that cash cropping has a negative influence on per capita food availability in the male-headed households. This negative influence is not apparent in the female-headed households and in fact, per capita food availability rises with increased agricultural commercialization. Households of married women seem to suffer more in terms of reduced food availability than households headed by females. Husbands have control over cash income and therefore influence food purchases. They are less likely than females to use the cash for food purchases and tend to spend the cash on themselves, thus reducing food availability to family members. This suggests that in some patriarchal societies, caution should be displayed in encouraging cash cropping especially in male-headed households. Cash cropping under such circumstances is unwise from both a food availability and food security point of view because it can result in reduced crop diversification hence increasing the risks of income food deficits for families. Other factors found to have an influence on per capita food availability are employment of the women outside households, educational level of the women and the quality of land.

Australia, the United States and a 'China growing strong': managing conflict avoidance

How to deal with a rising China constitutes one of the most seminal challenges facing the ANZUS alliance since its inception a half a century ago. Australia must reconcile its geography and economic interests in Asia with its post-war strategic and historic cultural orientation towards the United States. It must succeed in this policy task without alienating either Beijing or Washington in the process. The extent to which this is achieved will shape Australia's national security posture for decades to come. Three specific components of the 'Sino-American-Australian' triangle are assessed here: the future of Taiwan, the American development of a National Missile Defence (NMD), and the interplay between Sino-American power balancing and multilateral security politics. The policy stakes for Australia and for the continued viability of ANZUS are high in all three policy areas as a new US Administration takes office in early 2001. The article concludes that Australia's best interest is served by applying deliberate modes of decisionmaking in its own relations with both China and the US and by facilitating consistent and systematic dialogue and consultations with both of those great powers on key strategic issues.

The socio-religious beliefs and nature of the contemporary Vampire Subculture

The contemporary Vampire Subculture can be defined as a multi-faceted, socio-religious movement with its own distinct collective community and network of participants who share a similar belief system and customary lifestyle that reflect their concept of the vampire. The Vampire Subculture consists of individuals who profess to be 'real vampires', vampire communities of like-minded persons, 'blood-donors' who willingly allow vampires to partake of them, occult-based and mystical-orientated groups that appeal to their spirituality, the blood fetishists, and the live-action vampire role-players. In response, a Christian counter-movement of self-proclaimed 'vampire-slayers' has emerged that actively opposes the vampire subculture and its beliefs and practices. The socio-religious nature of the Vampire Subculture can be best described as a Segmented, Polycentric and Integrated Network of participants.