Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the roles of ICT in supporting sustainability practices

The concern about sustainability has arisen due to the overuse of natural resources and the increased use of energy consumption over the last decades. Information communication technologies (ICT) has the potential to address the three main aspects of sustainability (people, planet, profit) and therefore, several organizations have initiated a sustainable development by integrating ICT within their business activities. However, the roles of ICT in supporting sustainability initiatives have only been discussed in a limited number of studies and there is a lack of practical examples that demonstrate how the different roles of ICT are played out in an organization's environment. Therefore, this research aims to explore how ICT can be used by organizations to support sustainability initiatives. In particular, in this research-in-progress paper, we examine how a leading organization deploys Internet-of-Things as an example of an ICT application to support various sustainability initiatives. The study findings enhance the current understanding of how ICT can support sustainability practices of organizations.
Serum miR-300 as a diagnostic and prognostic biomarker in osteosarcoma

In order to determine whether microRNA (miR)-300 is a diagnostic and prognostic biomarker in osteosarcoma, the miR-300 levels in serum of 114 osteosarcoma patients and 114 healthy controls were compared, followed by serum analysis of the differences between the pre-operative and post-operative sera of these osteosarcoma patients. It was observed that the concentration levels of miR-300 in the serum of osteosarcoma patients was significantly higher than those in the serum of healthy controls (P<0.01). Furthermore, the concentration levels of miR-300 in the post-operative serum were significantly reduced when compared with the pre-operative serum levels (P<0.001). High miR-300 levels in serum correlated significantly with clinical stage, distant metastasis and poor survival of osteosarcoma patients. Notably, serum miR-300 was an independent prognostic marker for osteosarcoma. In conclusion, our results suggested that serum miR-300 may be a potential and useful noninvasive biomarker for the early detection of osteosarcoma.
Stochastic Single Period Inventory Decisions: Based on Full Quadratic Cost Functions

Abstract : This study addresses a general class of decision situations whose solutions are directly applicable to inventory acquisitions and or disposals. Although optimal solutions are well known when subsequent costs are linear to the amount of surplus or shortage, the perhaps more realistic case of non-linear costs has not been extensively studied. The results of this study suggest the optimal solutions i.e., acquisition quantity or supply for both conditions of risk and uncertainty about demand when the associated cost function is non- linear, i.e., quadratic. For conditions of risk optimal solutions are found which will yield minimum expected costs for the two-piece cost function where surplus and shortage costs are quadratic. This is done for both discrete and continuous demand variable. When future need for the item is unknown and only the maximum value can be estimated, optimal solutions are obtained for goals of minimaxing cost, minimaxing regret, and the Laplace criteria using a uniform probability distribution. It is shown that these different approaches to determining acquisition quantities under conditions of uncertainty lead, for this general class of decision problems, to the same optimal result. Hopefully, this information will aid in the decision process while making affordability assessments of new acquisitions. Affordability assessments, Single period inventory, Newsboy problem, Quadratic cost functions.
Environmental Water Requirements of Vallisneria nana in the Daly River , Northern Territory 1

The objective of the Commonwealth’s Environmental Flows Initiative (EFI) was to assist state and territory water resource agencies meet the COAG Water Reform requirements for making environmental water allocations. The NT received support due in part to the focus on water resource development shifting to Northern Australia and the concurrent lack of understanding about tropical water resources and their sustainable use. Intensive development of water resources is proceeding in the Daly Basin without an understanding of ecological requirements or environmental constraints.
A software-based methodology for the generation of peripheral test sets based on high-level descriptions

Nowadays, the use of Systems-on-Chip (SoCs) represents a very interesting solution, but also introduces some testing concerns. Up to now, researchers focused many efforts on the development of new software and hardware techniques for testing processors embedded in SoCs. However, the test of the surrounding peripherals has not been the subject of many research works, even if their importance within the entire system may be considerable. In this paper we focus on Software-based Self-Test techniques for testing peripheral components within a SoC and explore the possibility that test generation only relies on high-level metrics. We outline a possible test generation and application flow, and discuss the suitability of different RT-level metrics. By exploiting a sample case study, we quantitatively evaluate the effectiveness of the different metrics and the practical viability of the considered approach. As a major contribution, the paper shows that for peripheral components the relationship between high-level and gate-level metrics is higher than for the general case.
Flat Datacenter Storage

Flat Datacenter Storage (FDS) is a high-performance, fault-tolerant, large-scale, locality-oblivious blob store. Using a novel combination of full bisection bandwidth networks, data and metadata striping, and flow control, FDS multiplexes an application's large-scale I/O across the available throughput and latency budget of every disk in a cluster. FDS therefore makes many optimizations around data locality unnecessary. Disks also communicate with each other at their full bandwidth, making recovery from disk failures extremely fast. FDS is designed for datacenter scale, fully distributing metadata operations that might otherwise become a bottleneck. FDS applications achieve single-process read and write performance of more than 2GB/s. We measure recovery of 92GB data lost to disk failure in 6.2 s and recovery from a total machine failure with 655GB of data in 33.7 s. Application performance is also high: we describe our FDS-based sort application which set the 2012 world record for disk-to-disk sorting.
Tree-Based Parity Check for an Optimal Data Hiding Scheme

Reducing distortion between the cover object and the stego object is an important issue for steganography. The tree-based parity check method is very efficient for hiding a message on image data due to its simplicity. Based on this approach, we propose a majority vote strategy that results in least distortion for finding a stego object. The lower embedding efficiency of our method is better than that of previous works when the hidden message length is relatively large.
Path reduction in complex grid service provision

A complex grid service can be divided into several simple grid services. Performing these simple grid services in a specific sequence provides the results of the original complex one. These simple services can be provided using mobile agents or the Remote Procedure Call (RPC) method. The path reduction in the complex service provision will result a higher performance for the grid architecture. To reduce the mobile agent's path or the number of RPCs some services can be duplicated in other nodes. Duplication has several problems and difficulties such as ownership and copyright issues and financial problems. An interesting concept in the grid services, which have been presented recently, is the mobility of grid services. A mobile service can be migrated from one node to another one. In this paper, we integrate the mobility of agents with the mobility of services. In this model, the service provider sends a mobile agent to a defined sequence of nodes, and calls some grid services to migrate from other nodes to these nodes. This will reduce the provisioning path of complex services. Path reduction using migration of mobile services instead of copying services in several nodes may improve the performance and reduce the load of network and nodes.
Explaining the Reactions of Swiss Municipalities to The ‘Amalgamation Wave’: At the crossroad of institutional, economic and political pressures

Abstract Public sector organizations are simultaneously subject to three types of environmental pressure: institutional, economic and political. How do these pressures influence the strategic behaviour of public organizations when confronted with efficiency-oriented reforms? We focus on the strategic behaviour of Swiss municipalities facing the amalgamation wave: a reform characterized by a strong economic rationale. Results confirm that the success of reforms depends not only on its matching with economic underpinnings. It is also necessary to take the political leadership and the responsibility of reform implementation.
Far-Field Multicast Beamforming for Uniform Linear Antenna Arrays

The problem of transmit beamforming to multiple cochannel multicast groups is considered for the important special case when the channel vectors are Vandermonde. This arises when a uniform linear antenna antenna (ULA) array is used at the transmitter under far-field line-of-sight propagation conditions, as provisioned in 802.16e and related wireless backhaul scenarios. Two design approaches are pursued: (i) minimizing the total transmitted power subject to providing at least a prescribed received signal-to-interference-plus-noise-ratio (SINR) to each intended receiver; and (ii) maximizing the minimum received SINR under a total transmit power budget. Whereas these problems have been recently shown to be NP-hard, in general, it is proven here that for Vandermonde channel vectors, it is possible to recast the optimization in terms of the autocorrelation sequences of the sought beam vectors, yielding an equivalent convex reformulation. This affords efficient optimal solution using modern interior point methods. The optimal beam vectors can then be recovered using spectral factorization. Robust extensions for the case of partial channel state information, where the direction of each receiver is known to lie in an interval, are also developed. Interestingly, these also admit convex reformulation. The various optimal designs are illustrated and contrasted in a suite of pertinent numerical experiments.
Isolation and Expression Analysis of Novel Silicon Absorption Gene from Roots of Mangrove (Rhizophora apiculata) via Suppression Subtractive Hybridization

Silicon (Si) is the second most abundant element in soil after oxygen. It is not an essential element for plant growth and formation but plays an important role in increasing plant tolerance towards different kinds of abiotic and biotic stresses. The molecular mechanism of Si absorption and accumulation may differ between plants, such as monocotyledons and dicotyledons. Silicon absorption and accumulation in mangrove plants are affected indirectly by some proteins rich in serine and proline amino acids. The expression level of the genes responsible for Si absorption varies in different parts of plants. In this study, Si is mainly observed in the epidermal roots' cell walls of mangrove plants compared to other parts. The present work was carried out to discover further information on Si stress responsive genes in Rhizophora apiculata, using the suppression subtractive hybridization technique. To construct the cDNA library, two-month-old seedlings were exposed to 0.5, 1, and 1.5 mM SiO2 for 15 hrs and for 1 to 6 days resulting in a total of 360 high quality ESTs gained. Further examination by RT-PCR and real-time qRT-PCR showed the expression of a candidate gene of serine-rich protein.
Detection of Straight Lines Using a Spiking Neural Network Model

Receptive fields of neurons play various roles in biological neural networks. Based on a receptive field with the function of Hough transform, a spiking neural network model is proposed to detect straight lines in a visual image. Through the network, straight lines transform to corresponding neurons with high firing rates in the output neuron array. Simulation results show that straight lines can be detected by the network and firing rates of the corresponding neurons are referred to lengths of the lines. This model can be used to explain how a spiking neuron-based network can detect straight lines, and furthermore the model can be used in an artificial intelligent system.
Cplant/sup /spl trade// runtime system support for multi-processor and heterogeneous compute nodes

In this paper, we describe additions and modifications to the Computational Plant (Cplant/sup /spl trade//) system software to support multi-processor compute nodes and to support heterogeneous node types. We describe how these capabilities have been incorporated into our scalable runtime system and how these changes affect the interface seen by end users and application developers. We also discuss several important operating system and networking issues that can directly impact application performance. We present some initial performance metrics that indicate how our current implementation scales when multiple processes are running on a single node.
Multiple Loci Are Associated with Dilated Cardiomyopathy in Irish Wolfhounds

Dilated cardiomyopathy (DCM) is a highly prevalent and often lethal disease in Irish wolfhounds. Complex segregation analysis indicated different loci involved in pathogenesis. Linear fixed and mixed models were used for the genome-wide association study. Using 106 DCM cases and 84 controls we identified one SNP significantly associated with DCM on CFA37 and five SNPs suggestively associated with DCM on CFA1, 10, 15, 21 and 17. On CFA37 MOGAT1 and ACSL3 two enzymes of the lipid metabolism were located near the identified SNP.
Learning Extreme Multi-label Tree-classifier via Nearest Neighbor Graph Partitioning

Web scale classification problems, such as Web page tagging and E-commerce product recommendation, are typically regarded as multi-label classification with an extremely large number of labels. In this paper, we propose GPT, which is a novel tree-based approach for extreme multi-label learning. GPT recursively splits a feature space with a hyperplane at each internal node, considering approximate k-nearest neighbor graph on the label space. We learn the linear binary classifiers using a simple optimization procedure. We conducted evaluations on several large-scale real-world data sets and compared our proposed method with recent state-of-the-art methods. Experimental results demonstrate the effectiveness of our proposed method.
Developing a Research Community in Higher Education : from Student Feedback to Knowledge Construction

This paper describes a series of research and development projects into teaching and learning practices in Higher Education which have been undertaken at the University of Cambridge under the auspices of the Pedagogy Programme of the Cambridge-MIT Institute (CMI). These have involved a collaboration between groups of staff and students in participating departments and a team of education researchers based at the Centre for Applied Research in Educational Technologies (CARET). This collaboration has been marked by the evolution, over a period of about two years, of an organisation (CARET), of research processes, of educational practices and resources, and of roles and relationships within the research team. Most critically there has been a negotiation of norms and expectations on the part of participants and the legitimisation of discourses in a shared ‘problem space’. The research and development process can be conceptualised as one of ‘co-configuration’ with continual renegotiation of requirements and solutions. Roles and approaches have developed as researchers have gained better understanding of the priorities and ‘ways of thinking and practicing’ of other participants and those participants have in turn become familiar with the techniques and theoretical perspectives of education researchers. The importance of ‘boundary-crossing’ objects which provide points of focus for discourse and development is discussed, and what these might be in the context of education research and development projects. The paper concludes with a description of a new initiative informed by this view of research and development as co-configuration: the Teaching for Learning Network (TfLN).
Stereotype Threat and the Student‐Athlete

Achievement gaps may reflect the cognitive impairment thought to occur in evaluative settings (e.g., classrooms) where a stereotyped identity is salient (i.e., stereotype threat). This study presents an economic model of stereotype threat that reconciles prior evidence on how student effort and performance are influenced by this social-identity phenomenon. This study also presents empirical evidence from a laboratory experiment in which students at a selective college were randomly assigned to a treatment that primed their awareness of a stereotyped identity (i.e., student-athlete). This treatment reduced the test-score performance of athletes relative to non-athletes by 14 percent (effect size = -1.0).
Optimal object grasping using fuzzy logic

Robotic end effectors are commonly required to hold and manipulate various objects under a wide range of conditions. To achieve a satisfactory grip, optimal force control is required to avoid the risk of the object slipping out of the end effector and to avoid any possible damage to the object. In this paper, we investigate the use of fuzzy logic controllers to achieve optimal grasping. Starting with a set of manually-designed fuzzy rules from previous work, these were analysed and a shortcoming identified and corrected. Backpropagation learning was then employed to train a neurofuzzy controller with and without a priori knowledge. In the former case, the a priori knowledge which defined the start point for learning was obtained from the manually-designed rules. In the latter case, training started from different initial random weight settings. The learned solutions were very similar although training was faster with a priori knowledge. The learned neurofuzzy controller had better performance than the manually-designed fuzzy controller, particularly in respect of its faster control action.
Designing low-power circuits: practical recipes

The growing market of mobile, battery-powered electronic systems (e.g., cellular phones, personal digital assistants, etc.) demands the design of microelectronic circuits with low power dissipation. More generally, as density, size, and complexity of the chips continue to increase, the difficulty in providing adequate cooling might either add significant cost or limit the functionality of the computing systems which make use of those integrated circuits. In the past ten years, several techniques, methodologies and tools for designing low-power circuits have been presented in the scientific literature. However only a few of them have found their way in current design flows. The purpose of this paper is to summarize, mainly by way of examples, what in our experience are the most trustful approaches to low-power design. In other words, our contribution should not be intended as an exhaustive survey of the existing literature on low-power design; rather, we would like to provide insights a designer can rely upon when power consumption is a critical constraint. We will focus solely on digital circuits, and we will restrict our attention to CMOS devices, this technology being the most widely adopted in current VLSI systems.
Echocardiographic Parameters as Predictors of In-Hospital Mortality in Patients with Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention

Different ways have been used to stratify risk in acute coronary syndrome (ACS) patients. The aim of the study was to examine the usefulness of echocardiographic parameters as predictors of in-hospital outcome in patients with ACS after percutaneous coronary intervention (PCI). A data of 2030 patients with diagnosis of ACS hospitalized from December 2008 to December 2011 was used to develop a risk model based on echocardiographic parameters using the binary logistic regression. This model was independently evaluated in validation cohort prospectively (954 patients admitted during 2012). In-hospital mortality in derivation cohort was 7.73%, and 6.28% in validation cohort. Developed model has been designed with 4 independent echocardiographic predictors of in-hospital mortality: left ventricular ejection fraction (LVEF RR = 0.892; 95%CI = 0.854–0.932, P < 0.0005), aortic leaflet separation diameter (AOvs RR = 0.131; 95%CI = 0.027–0.627, P = 0.011), right ventricle diameter (RV RR = 2.675; 95%CI = 1.109–6.448, P = 0.028) and right ventricle systolic pressure (RVSP RR = 1.036; 95%CI = 1.000–1.074, P = 0.048). Model has good prognostic accuracy (AUROC = 0.84) and it retains good (AUROC = 0.78) when testing on the validation cohort. Risks for in-hospital mortality after PCI in ACS patients using echocardiographic measurements could be accurately predicted in contemporary practice. Incorporation of such developed model should facilitate research, clinical decisions, and optimizing treatment strategy in selected high risk ACS patients.
Enhanced real time facial detection and replacement using GPGPU

A method is presented for enhanced facial detection and replacement. This method builds on previous methods by addressing three key shortcomings: low performance, a tendency to misidentify walls as faces, and poor blending of the replacement face with the host body. General purpose graphics processing unit (GPGPU) technology is used to make this method feasible for use. Parameters for the algorithm are determined by experimentation. Measurements of the system show up to 3 times performance improvement from using the GPU. Blending of the host and replacement is smoother, though not seamless. Walls appear to no longer be misidentified as faces.
Prognostic Factors of Cholangiocarcinoma After Surgical Resection: A Retrospective Study of 293 Patients

Background Cholangiocarcinoma is one of the most common malignancies in China. Surgical resection is the only treatment option; however, diagnosis at advanced stage precludes surgery. Comprehensive knowledge of prognostic markers is missing. Hence, the aim of this study was to determine clinicopathological indexes that would be indicative of prognosis in post-operative cases of cholangiocarcinoma. Material/Methods A retrospective analysis of 293 cases of cholangiocarcinoma patients attending the 301 Military Hospital in Beijing, China between January 2004 and December 2010 were included in the study. The patients had follow-up history until August 2012. Cox proportional hazards model analysis was performed to identify indexes of prognosis. All indicators were analyzed by univariate and multivariate analysis. Results The median follow-up time was 55.90 months, with recurrence and metastasis in 162 cases (55.3%) and death in 223 cases (76.1%). The 1-year, 3-year, and 5-year survival rates were 71.7%, 38.2%, and 10.6%, respectively. The independent risk factors of overall survival were degree of tumor differentiation, TNM stage, surgical margin, intraoperative blood transfusion, tumor location, alkaline phosphatase levels in blood, and relapse. Conclusions Good prognosis in cholangiocarcinoma patients is indicated by highly differentiated tumor, early stages of TNM staging, no resection margin invaded, no intraoperative blood transfusion, intrahepatic tumor, normal alkaline phosphatase levels, and no relapse.