Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Layer Management in

Superpeer unstructured P2P systems have been found to be very effective by dividing the peers into two layers, superlayer and leaf-layer, in which message flooding is only conducted among superlayer and all leaf-peers are represented by corresponding superpeers. However, current superpeer systems do not employ any effective layer management schemes, so the transient and low- capacity peers are allowed to act as superpeers. Moreover, the lack of an appropriate size ratio maintenance mechanism on superlayer to leaf-layer makes the system's search performance far from being optimal. We present one workload model aimed at reducing the weighted overhead of a network. Using our proposed workload model, a network can determine an optimal layer size ratio between leaf-layer and superlayer. We then propose a Dynamic Layer Management algorithm, DLM, which can maintain an optimal layer size ratio and adaptively elect and adjust peers between superlayer and leaf-layer. DLM is completely distributed in the sense that each peer decides to be a superpeer or a leaf-peer independently without global knowledge. DLM could effectively help a superpeer P2P system maintain the optimal layer size ratio and designate peers with relatively long lifetime and large capacities as superpeers, and the peers with short lifetime and low capacities as leaf-peers under highly dynamic network situations. We demonstrate that the quality of a superpeer system is significantly improved under the DLM scheme by comprehensive simulations.
Decoding Cities to Model, Assess and Redesign them as Complex Urban Systems

The complexity of cities presents a key challenge in being able to ‘decode‘ and subsequently measure or describe them. Adding to these challenges is the transdisciplinary nature of city design which largely accords to disciplinary silos. This research argues that successful city design can benefit from understanding cities as complex sociotechnical systems – considering the interaction between humans, technology and the environment. This paper provides a precis of a programme of research which utilised the results of an international survey to ‘decode’ and construct a systems model of a main street to help understand and appropriately respond to city complexity. The research uses subject matter expert knowledge and insights from 70 survey participants, across 5 continents, to model an archetype main street. The project describes and models hundreds of physical objects, priority measures and main street functions with linkages between these components. The model allows for the exploration and measurement of a range of both technical characteristics such as engineering standards, as well as the influence and outcomes of necessary subjective measures like, user experience. It was able to provide an insight about which characteristics are critical to the city system, how they are delivered and why they are important - from a transdisciplinary perspective. This paper also highlights the work done to identify the relationships between the physical objects of a main street. Further details of the research programme are highlighted in the conclusions, including how the archetype model was used to explore the performance of a main street case study, identify missing components and locate them with consideration of their optimal proximity to other related features. We argue that this innovative approach may provide a more structured and process driven exploration of city design.
Decentralized Interruption-Tolerant using Secure Data Rescue for Armed Force Networks

– Mobile nodes in armed force (military) environments such as a battlefield or a hostile region are likely to suffer from intermittent network connectivity and frequent partitions. Disruption-tolerant network (DTN) technologies are becoming successful solutions that allow wireless devices carried by soldiers to communicate with each other and access the confidential information or command reliably by exploiting external storage nodes. Some of the most challenging issues in the scenario are enforcement of authorization policies and the policies update for secure data retrieval. Cipher text-policy attribute-based encryption (CP-ABE) is a promising cryptographic solution to the access control issues.A secure data retrieval scheme using CP-ABE for decentralized DTNs where multiple key authorities manage their attributes independently and describes how to apply the proposed mechanism to securely and efficiently manage the confidential data distributed in the disruption-tolerant military network.
(Re)Focussing on behavioural change: an examination of the utility of hidden Markov modelling

PurposeBehavioural change practice has focussed attention on understanding behaviour; failing to apply dynamic approaches that capture the underlying determinants of behavioural change. Following recommendations to direct analytical focus towards understanding both the causal factors of behaviour and behavioural change to enhance intervention practice, this paper aims to apply a hidden Markov model (HMM) approach to understand why people transition from one state to another (e.g. reporting changes from wasting food to not wasting food or vice versa). Design/methodology/approachData were drawn from a 2017 food waste programme that aimed to reduce waste of fruit and vegetables by increasing self-efficacy through a two-week pilot, featuring recipes and in-store cooking demonstrations. A repeated measure longitudinal research design was used. In total, 314 households completed a phone survey prior to the two-week pilot and 244 completed the survey in the weeks following the intervention (77% retention in the evaluation study). FindingsTwo behavioural states were identified, namely, fruit and vegetable (FV) wasters and non-FV wasters. Age was identified as a causal factor for FV food wasting prior to the campaign (45-54 years were most likely to waste FV). Following the intervention, a total of 43.8% transitioned away from FV wasters to non-wasters, and attitudes and self-efficacy were indicated as potential causal factors of this change in FV waste behaviour.Originality/valueThrough this application, it is demonstrated how HMM can identify behavioural states, rates of behaviour change and importantly how HMM can identify both causal determinants of behaviour and behavioural change. Implications, limitations and future research directions are outlined.
A new algorithm to measure relevance among Web pages

This paper proposes a new algorithm to measure relevance among Web pages (RWP) using a hybrid method of hyperlink analysis and content analysis. Here we used a new approach to Web searching where the input to the search process is not a set of query terms, rather the URL of a page, and the output is a set of related Web pages. A related Web page is one that addresses the same topic as the original page. Here, the proposed algorithm first uses only the connectivity information in the Web (i.e., the links between pages) and then the content of pages. To evaluate the performance, the algorithm is compared with existing algorithms. Experimental results show that RWP outperforms existing algorithms to find relevant Web pages. RWP increases the search efficiency effectively and enhances the application area of Web related research.
The Power of Humanitarian Narratives: A Domestic Coalition Theory of Justifications for Military Action

Conventional wisdom assumes the best way to mobilize public support for military action is through the lens of national security. Humanitarian justifications provide a helpful substitute when US interests are not at stake, but are less reliable. However, US presidents have provided humanitarian explanations for every military intervention of the post-Cold War period. What, if any, power do humanitarian justifications have in security-driven interventions? The article answers this question by developing a domestic coalition framework that evaluates justifications in terms of whose support matters most in the build-up to intervention. Survey experiments demonstrate that humanitarian narratives are necessary to build the largest possible coalition of support. However, presidents risk backlash if they stretch humanitarian claims too far. Data from thirteen waves of Chicago Council surveys and an original dataset of justifications for US interventions confirm that humanitarian justifications are a common and politically relevant tool. The findings challenge both the folk realist expectation that the public responds primarily to threats to its own security and the constructivist tendency to limit the power of humanitarian justifications to cases of humanitarian intervention. Instead, humanitarian justifications are equally, if not more, important than security explanations for mobilizing domestic support, even in security-driven interventions.
Caregivers of Mentally Ill Patients: A Cross-sectional Need-Based Assessment of Social Workers in Post-conflict Somalia

This study seeks to investigate the needs of family caregivers of people living with Mental illness in Somalia. Using an exploratory research design technique, a qualitative approach was employed for a one-on-one interview module to collect data from a total of 51 respondents identified as family caregivers of mentally ill persons undergoing rehabilitation in five (5) selected mental health facilities sampled for the study. In analyzing and interpreting qualitative data, a thematic content analysis was done which revealed that, in addition to medical care, family caregivers need not only social support in a form of affection to assist them in their various engagements, but also, adequate relaxation and leisure to regain lost energies and save them from stress and its harmful ramifications on their health. They also need decent accommodation to maintain their mentally ill relatives. The results further revealed that, caregivers needed financial support as well as emotional support from friends and society in order to psyche them up for their task. To understand the needs of patients’ treatment history and condition, caregivers need information. It is, therefore of necessity to social workers and other stakeholders that the needs of caregivers are adequately and sufficiently addressed.
Parallel Capsule Net for Ischemic Stroke Segmentation

Stroke is one of the leading causes of disability. Segmentation of ischemic stroke could help in planning an optimal treatment. Currently, radiologists use manual segmentation, which can often be time-consuming, laborious and error-prone. Automatic segmentation of ischemic stroke in MRI brain images is a challenging problem due to its small size, multiple occurrences and the need to use multiple image modalities. In this paper, we propose a new architecture for image segmentation, called Parallel Capsule Net, which uses max pooling in every parallel pathways along with dense connections between the parallel layers. We hypothesise that the spatial information lost due to max pooling in these layers can be retrieved by the use of such dense connections. In order to combine the information encoded by the parallel layers, outputs of the layers are concatenated before upsampling. We also propose the use of a modified loss function which consists of a regional term (Generalized Dice loss + Focal Loss) and a boundary term (Boundary loss) to address the problem of class imbalance which is prevalent in medical images. We achieved a competitive Dice score of 0.754, on ISLES SISS data set, compared to a score of 0.67 reported in earlier studies. We also obtained a Dice score of 0.902 with another popular data set, ATLAS. The proposed parallel capsule net can be extended to other similar medical image segmentation problems.
Comparative analysis of diagnostic platforms for measurement of differentially methylated insulin DNA

Circulating cell-free DNA (cfDNA) has been intensively investigated as a diagnostic and prognostic marker for various cancers. In recent years, presence of unmethylated insulin cfDNA in the circulation has been correlated with pancreatic β-cell death and risk of developing type 1 diabetes. Digital (d)PCR is an increasingly popular method of quantifying insulin cfDNA due to its ability to determine absolute copy numbers, and its increased sensitivity when compared to the more routinely used quantitative PCR. Multiple platforms have been developed to carry out dPCR. However, not all technologies perform comparably, thereby necessitating evaluation of each platform. Here, we compare two dPCR platforms: the QuantStudio 3D (QS3D, Applied Biosystems) and the QX200 (Bio-Rad), to measure copies of unmethylated/methylated insulin plasmids. The QS3D detected greater copy numbers of the plasmids than the QX200 (manual mode), whereas QX200 demonstrated minimal replicate variability, increased throughput, ease of use and the potential for automation. Overall, the performance of QX200, in our hands, was better suited to measure differentially methylated insulin cfDNA.
NEC's Simple Middlebox Configuration (SIMCO) Protocol Version 3.0

This document describes a protocol for controlling middleboxes such as firewalls and network address translators. It is a fully compliant implementation of the Middlebox Communications (MIDCOM) semantics described in RFC 3989. Compared to earlier experimental versions of the SIMCO protocol, this version (3.0) uses binary message encodings in order to reduce resource requirements.
ZONE-Based Multi-Access Edge Computing Scheme for User Device Mobility Management

Recently, new mobile applications and services have appeared thanks to the rapid development of mobile devices and mobile network technology. Cloud computing has played an important role over the past decades, providing powerful computing capabilities and high-capacity storage space to efficiently deliver these mobile services to mobile users. Nevertheless, existing cloud computing delegates computing to a cloud server located at a relatively long distance, resulting in significant delays due to additional time to return processing results from a cloud server. These unnecessary delays are inconvenient for mobile users because they are not suitable for applications that require a real-time service environment. To cope with these problems, a new computing concept called Multi-Access Edge Computing (MEC) has emerged. Instead of sending all requests to the central cloud to handle mobile users’ requests, the MEC brings computing power and storage resources to the edge of the mobile network. It enables the mobile user device to run the real-time applications that are sensitive to latency to meet the strict requirements. However, there is a lack of research on the efficient utilization of computing resources and mobility support when mobile users move in the MEC environment. In this paper, we propose the MEC-based mobility management scheme that arranges MEC server (MECS) as the concept of Zone so that mobile users can continue to receive content and use server resources efficiently even when they move. The results show that the proposed scheme reduce the average service delay compared to the existing MEC scheme. In addition, the proposed scheme outperforms the existing MEC scheme because mobile users can continuously receive services, even when they move frequently.
DSP based RBF neural modeling and control for active noise cancellation

This paper presents active control of acoustic noise using radial basis function (RBF) networks and a digital signal processor (DSP) real-time implementation. The neural control system consists of two stages: first, identification (modeling) of the secondary path of active noise control using RBF networks and its learning algorithm, and secondly neural control of the primary path based on the neural model obtained in the first stage. A tapped delay time is introduced in front of the neural controller, and another tapped delay line is inserted between controller neural networks and model neural networks. An algorithm referred to as FX-RBF is proposed to account for secondary path effects of the control system arising in active noise control. The resulting algorithm turns out to be the filtered-X version of the standard RBF learning algorithm. We address centralized and decentralized controller configurations and their DSP implementation is carried out. The effectiveness of the neural controller is demonstrated by applying the algorithm to active noise control within a 3-D enclosure to generate quiet zones around error microphones. Results of real-time experiments show 10-30 dB noise attenuation, better than those obtained by classical least mean-square techniques such as FX-LMS.
Establishment and management of leucaena in Latin America

Keynote paper presented at the International Leucaena Conference, 1‒3 November 2018, Brisbane, Queensland, Australia.Leucaena leucocephala (leucaena) is native to Mexico and Central America and is currently naturalized in the majority of Latin American countries. Over the last 2 decades, considerable research and promotion of leucaena have been carried out in Colombia, Mexico, Cuba, Brazil, Paraguay and Argentina. Research focused on the agronomic and management options for feeding beef, dairy or dual-purpose animals, with some studies on germplasm, weediness issues, toxicity, organic fertilizer application and environmental services.Over the past 10‒15 years, establishment and management of leucaena feeding systems in Latin America have varied according to country. For instance, intensive Silvopastoral Systems (iSPS) models are widely promoted and successfully adopted in Colombia, Mexico, Cuba, Venezuela and Northeast Brazil. In ISS, leucaena is planted at high density (>10,000 trees/ha), in combination with improved tropical grass and high-value timber species (200‒400 trees/ha), and intensively managed employing rotational grazing.In Paraguay and Argentina, leucaena is planted in single or double hedgerows with inter-row alleys of 6‒8 m, following the configuration used in Australia and mainly focused on beef production. In Mexico, leucaena is also cultivated with Tithonia diversifolia or lemon trees. Meanwhile, in other countries such as Cuba, leucaena has been established as protein banks using single/twin rows with inter-row spacing of 2‒4 m for feeding beef, dairy or dual-purpose animals. Overall, paddock sizes for protein banks and ISS range between 0.3 and 50 ha, while single and twin hedgerow systems are generally established over larger areas (20‒500 ha). Despite the significant benefits demonstrated by research on leucaena feeding systems over the past 2 decades, coupled with successful outcomes for farmers who have adopted these systems, total area sown remains low across Latin America. This review provides a comparison between Latin American and Australian leucaena pasture systems, and recommendations for future collaborative research between countries.
PDE Acceleration for Active Contours

Following the seminal work of Nesterov, accelerated optimization methods have been used to powerfully boost the performance of first-order, gradient-based parameter estimation in scenarios where second-order optimization strategies are either inapplicable or impractical. Accelerated gradient descent converges faster and performs a more robust local search of the parameter space by initially overshooting then oscillating back into minimizers which have a basis of attraction large enough to contain the overshoot. Recent work has demonstrated how a broad class of accelerated schemes can be cast in a variational framework leading to continuum limit ODE's. We extend their formulation to the PDE framework, specifically for the infinite dimensional manifold of continuous curves, to introduce acceleration, and its added robustness, into the broad range of PDE based active contours.
Acute exposure of glyphosate-based herbicide induced damages on common carp organs via heat shock proteins-related immune response and oxidative stress

Abstract A subacute toxicity test of 52.077 and 104.154 mg/L glyphosate-based herbicide (GBH) on common carp for 7 days was conducted. The results of qPCR reveled that GBH treatment generally promoted the HSP70, HSC70, and HSP90 levels in fish liver, kidney, spleen, and intestine, suggesting that the induction of HSPs might be associated with the toxicity of GBH. Further research revealed that GBH exposure remarkably promoted the expressions of IL-1β, IL-6, IL-8, IFN-γ, and TNF-α at mRNA level and altered the mRNA and protein levels of IL-10 and TGF-β, and generally inhibited T-AOC activity, but increased the MDA level, suggesting that GBH has immunotoxicity and causes oxidative stress on common carp.
In silico Analysis of Phytochemical Compound Found in Snake Fruit (Salacca zalacca) Peel as Anti-aging Agent

Skin aging is a complicated natural phenomenon characterized by progressive loss of structural integrity and physiological function of the skin. Snake fruit ( Salacca zalacca ) is an important fruit crop native from Indonesia. Its waste is a potential source bioactive phytochemical compound. Present study investigates possible anti-aging potency of phytochemical compound found in salak fruit peel based on its binding towards enzyme related in skin aging process. Molecular docking was performed towards enzyme subjected to degradation of dermal matrix (MMP1, NEP) and hyper-pigmentation (PPO3). Docked compound occupied the active site of each protein in which chlorogenic acid has the highest affinity among salak peel compound against MMP1, and Rutin against NEP and PPO3. Further intermolecular analysis revealed favourable interaction between chlorogenic acid, rutin towards respective protein. Taken together compound found in snake fruit, display possible inhibition towards protein related in skin aging and could be potentially used as anti-aging agent.
Evaluation of biochemical markers in type 2 diabetes mellitus with adjunct therapy of fenugreek seed aqueous extract

Background: Trigonella foenum-graecum seeds have been suggested to have potential anti-diabetic effects. Aim: To study effects of fenugreek seeds aqueous extract on glycemic status, insulin resistance, homeostatic model assessment, safety parameters and antioxidant superoxide dismutase in Type 2 Diabetes Mellitus (T2DM) subjects and its correlation. Methods: Randomized case-control study consisting of control (n=30), T2DM (n=30) and T2DM patients with adjunct therapy (n=30) of 1.32g fenugreek seeds aqueous extract for 3 months. Blood glucose, HbA1C, lipid profile, liver and kidney function tests were done using chemistry autoanalyzer. Insulin and C-peptide were done on chemiluminescence. Malondialdehyde and superoxide dismutase were analysed using spectrophotometer. Results: Glucose, HbA1C and malondialdehyde were significantly lowered after 3 months in group receiving adjunct therapy. Insulin resistance, anthropometric and antioxidant status were improved while haemoglobin, alanine transaminase and renal functions remained unaltered. Conclusion: Aqueous extract of fenugreek is effective and safe to control hyperglycemia in T2DM.