Miracle-dz/UniFAR-FTUs huggingface dataset:
Continental Shelf Sediments of Sarawak, Malaysian Borneo

Sediment distributions in deep sea influence the benthic community structure and thus play an important role in shaping the marine ecosystem. Several studies on sediment characteristics had been conducted in South China Sea (SCS), but only limited to coastal areas of regions within SCS territories. Therefore, this study was carried out to analyze the benthic sediment profile in an area beyond 12 nautical miles off the coast of Sarawak, southern SCS. Sediment samples were collected from 31 stations, comprising three depth ranges: (I) 20–50 m, (II) 50–100 m, and (III) 100–200 m. The total organic matter (TOM) contents were determined and subjected to dry and wet sieving methods for particle size analysis. TOM contents in the deep area (>50 m) were significantly higher (p = 0.05) and positively correlated (r = 0.73) with silt-clay fraction. About 55% and 82% of stations in strata II and III, respectively, were dominated by silt-clay fractions (<63 μm mean diameter), coherent with TOM data. In addition, sediments in the deep area (>50 m) tend to be poorly sorted, very fine skewed, and platykurtic. Unlike data obtained 20 years ago which reported high content of silt-clay (58%), this study recorded a lower content (35%); therefore, changes in sediment load had been observed in southern SCS.
Compiler-instrumented, Dynamic Secret-Redaction of Legacy Processes for Attacker Deception

An enhanced dynamic taint-tracking semantics is presented and implemented, facilitating fast and precise runtime secret redaction from legacy processes, such as those compiled from C/C++. The enhanced semantics reduce the annotation burden imposed upon developers seeking to add secret-redaction capabilities to legacy code, while curtailing over-tainting and label creep. An implementation for LLVM's DataFlow Sanitizer automatically instruments taint-tracking and secret-redaction support into annotated C/C++ programs at compile-time, yielding programs that can self-censor their address spaces in response to emerging cyber-attacks. The technology is applied to produce the first information flow-based honey-patching architecture for the Apache web server. Rather than merely blocking intrusions, the modified server deceptively diverts attacker connections to secret-sanitized process clones that monitor attacker activities and disinform adversaries with honey-data.
Design of a dual band and broadband microstrip monopole antenna

This paper presented a small dual band and broadband microstrip monopole antenna fed by CPW. The proposed monopole can generate two separate resonant modes and operate in two frequency bands that used for WLAN. The lower operating band covers from 2.27 GHz to 2.49 GHz and the upper operating band covers from 4.52 GHz to 6.61 GHz. The monopole only has a very small size, 15.4 mm times 10.2 mm times 0.762 mm and easy to integrate with other communication equipment. Simulation and experimental results show that the monopole can work at the two designed bands well.
Diversity of chromium‐resistant and ‐reducing bacteria in a chromium‐contaminated activated sludge

Aims: This study attempts to establish a relationship between the Cr(VI) resistance of the culturable microbial community and the Cr(VI) resistance and Cr(VI)‐reducing ability of representative strains of each population, in order to assess whether these are exclusive characteristics of one microbial group or abilities shared among many groups.
Compositional changes of major chemical compounds in Greek carob pods during development

Because of the strong association with health benefits of some chemical compounds contained in carob fruit the composition of chemical substances of two common type carob pods ( Ceratonia siliqua L.) and their changes during fruit developing in two periods of harvesting were reported. Samples were originated from a site near Rethymno, Crete Island, at an altitude of 100 m above the sea level. The moisture content determined through sample’s drying in 70 o C under vacuum, sugars by HPLC (high pressure liquid chromatography), total polyphenols by ultraviolet/visible (UV/Vis) and fatty acids by gas chromatography (GC) in the fleshy and wild types were determined at three stages of development. Principal sugars found were glucose, fructose and sucrose. The predominant fatty acid was linoleic acid (n-6) followed by oleic, palmitic and then linolenic (n-3) fatty acids. The total unsaturated fatty acids content was two times higher than the content of total saturated fatty acids in fully-developed carob pod. The ratio n-6/n-3 was under 5, showing a good equilibrium between the two essential fatty acids. The fully developed fruits of both varieties revealed lower contents of polyphenols, proteins and sugars compared with their previous growth stages. The fleshy carob pods exceed the wild variety in concentration of proteins, sugars and fatty acids, while the wild variety exceeds the fleshy in polyphenols concentration. KEY WORDS : Carob pods, Ceratonia siliqua L. , Fatty acids, Polyphenols, Sugars Bull. Chem. Soc. Ethiop. 2012 , 26(3), 343-351. DOI: http://dx.doi. org/10.4314/bcse.v26i3. 3
Multilevel Analysis of Uptake, Sessions, and Key Actors in a Socio-Technical Network

Learning in social settings is a complex phenomenon that involves multiple processes at individual and collective levels of agency. Thus, a richer understanding of learning in socio-technical networks will be furthered by analytic methods that can move between and coordinate analyses of individual, small group and network level phenomena. This paper outlines our implementation of an analytic framework intended to address these and other needs (e.g., integrating fragmented traces of activity into one analytic artifact), and gives an example using data from the Tapped In educator professional network. The methods build on empirical relationships between events to build a graph of uptake relations—how one event builds on another, which are then used to identify sessions in the space-time dimensions of a rich online environment, identify key actors within sessions using sociometrics, and find relationships between sessions that might be vectors for the transmission of ideas or practices.
Model checking a SystemC/TLM design of the AMBA AHB protocol

Transaction Level Modeling (TLM) is gaining more and more importance to quickly evaluate design alternatives in multimedia systems and other mixed HW/SW systems. However, the comprehensive and automated verification of TLM models is still a difficult challenge. In previous work, we presented an approach for model checking of SystemC/TLM designs based on a transformation into Uppaal timed automata. In this paper, we present an optimized version of our previously proposed transformation, and show its effectiveness with experimental results from an industrial case study. The key idea is to generate a Uppaal model that is especially tailored for being model checked. This significantly reduces the semantic state space and makes model checking considerably faster and less memory-consuming. We demonstrate this by comparing the verification times of both versions for our previously used case study, and by presenting results from a new and larger case study, namely a TLM implementation of the AMBA Advanced High-performance Bus (AHB). The AMBA bus is one of the most popular on-chip bus architectures in IP-based embedded SoCs, and it is used in many multimedia applications. The case study shows that with the proposed optimizations, our approach is applicable for industrial real world examples. The detection of a serious bug, namely a deadlock situation in a certain scenario, and also the verification of some important safety, liveness, and timing properties provide evidence for the usefulness of our approach.
CONSTRUCTING A COURSE PROFILE BY MEASURING COURSE OBJECTIVES

An ongoing goal in higher education is to provide quality education programs and to produce high quality graduates. While much of the attention to quality matters is focussed on outputs, there is little that addresses the preliminary or input side of the educational program. The purpose of this paper is to demonstrate that it is feasible to construct a course profile based on standard inputs in the form of the behavioral objectives that are stated for the subjects comprising the course. The application of the course profile will be found in supplementing the understanding of quality frameworks in the assessment of degree programs, thereby becoming a useful tool for benchmarking courses and comparing across department and institution boundaries.
A Pilot Study of an Automated Voice Response System and Nursing Intervention to Monitor Adherence to Oral Chemotherapy Agents

This study was designed to develop and test a system to monitor adherence with nonhormonal oral chemotherapeutic agents using an automated voice response (AVR) system plus nursing intervention. Participants were patients diagnosed with solid tumor cancers, primarily breast, colon, and lung cancers, who received the Symptom Management Toolkit and participated in an interview for symptom severity, satisfaction, and beliefs about oral agents. Patients received weekly AVR calls, which assessed adherence to oral agents and severity of 15 symptoms. Patients who reported adherence of below 100% of the prescribed oral agents or symptoms of 4 or greater (0-10 scale) for 3 consecutive weeks were called by a nurse for assistance with symptom management and adherence to oral chemotherapy medications. After the 8 weekly AVR calls, patients participated in a follow-up interview and medical record review. Participants were 30 oncology patients who were ambulatory and treated at 2 cancer centers in Midwest United States. The results indicate 23.3% nonadherence rate to oral chemotherapy medications due to symptoms and forgetting to take the medication. An association between symptom management and adherence was found. Symptom severity and beliefs about medications were not significantly different between adherent and nonadherent patients. This pilot study demonstrated the ability to accrue patients for a longitudinal trial and informed intervention design while providing guidance for future interventions and research studies.
A theoretical framework for the online consumer response process

Abstract This article describes the foundation and development of a theoretical framework for the online consumer response process. It is based on theoretical criteria for web-based commercial communication and the online consumer response process. Central to this article is the development of the concept of web-based commercial communication. This includes all advertising, marketing communication, public relations and promotional messages on the World Wide Web which are intended to move the consumer through certain response phases to the point of purchasing or proceeding to any other type of action; the identification of the marketing communication paradigm shift from offline to online; and the comparison between online and traditional mass media audience characteristics. A theoretical conceptualisation of the online consumer response process is undertaken and an analysis of consumer response models and the theory of the general consumer response process is performed. This article is a theoretical exploration of the phenomenon of ‘online consumer response’ and the proposed theoretical framework is intended to address the dearth of literature on the topic.
Trusted dissemation of data in Opportunistic Network

Recent advances in the field of computer network and wireless communication technologies, so called opportunistic networks is been materialized. Opportunistic network has many potential applications, from home security to the human preparedness. This paper considers a human aspects of trust , privacy and security on the performance of the opportunistic network, different research papers in the related fields are surveyed and proposed the solutions on this aspects. Keywords-opportunistic network; trust; privacy; security
Memory interfacing and instruction specification for reconfigurable processors

As custom computing machines evolve, it is clear that a major bottleneck is the slow interconnection architecture between the logic and memory. This paper describes the architecture of a custom computing machine that overcomes the interconnection bottleneck by closely integrating a fixed-logic processor, a reconfigurable logic array, and memory into a single chip, called OneChip-98. The OneChip-98 system has a seamless programming model that enables the programmer to easily specify instructions without additional complex instruction decoding hardware. As well, there is a simple scheme for mapping instructions to the corresponding programming bits. To allow the processor and the reconfigurable array to execute concurrently, the programming model utilizes a novel memory-consistency scheme implemented in the hardware. To evaluate the feasibility of the OneChip-98 architecture, a 32-bit MIPS-like processor and several performance enhancement applications were mapped to the Transmogrifier-2 field programmable system. For two typical applications, the 2-dimensional discrete cosine transform and the 64-tap FIR filter, we were capable of achieving a performance speedup of over 30 times that of a stand-alone state-of-the-art processor.
Design principle of gene expression used by human stem cells: implication for pluripotency

Human embryonic stem cells (ESC) are undifferentiated and are endowed with the capacities of self‐renewal and pluripotential differentiation. Adult stem cells renew their own tissue, but whether they can transdifferentiate to other tissues is still controversial. To understand the genetic program that underlies the pluripotency of stem cells, we compared the transcription profile of ESC with that of progenitor/stem cells of human hematopoietic and keratinocytic origins, along with their mature cells to be viewed as snapshots along tissue differentiation. ESC gene profiles show higher complexity with significantly more highly expressed genes than adult cells. We hypothesize that ESC use a strategy of expressing genes that represent various differentiation pathways and selection of only a few for continuous expression upon differentiation to a particular target. Such a strategy may be necessary for the pluripotency of ESC. The progenitors of either hematopoietic or keratinocytic cells also follow the same design principle. Using advanced clustering, we show that many of the ESC expressed genes are turned off in the progenitors/stem cells followed by a further down‐regulation in adult tissues. Concomitantly, genes specific to the target tissue are up‐regulated toward mature cells of skin or blood.
Theory-Based Determinants of Youth Smoking: A Multiple Influence Approach1

This study tested a broad array of determinants of smoking grounded in general social psychological theories, as well as personality and social development theories. Using data from 2,004 middle school students, all proximal and distal determinants significantly predicted smoking in the hypothesized direction. Further, hierarchical logistic regressions showed that intention to smoke, positive and negative attitudes toward smoking, impediments to smoking, self-efficacy to resist smoking, parent norms, and academic success most strongly predicted current smoking. Hierarchical linear regressions suggested that parental relatedness, maladaptive coping strategies, depression, and low academic aspirations most strongly predicted susceptibility to smoking for those who had not yet smoked a cigarette. Global expectancies were the strongest predictor of susceptibility in low socioeconomic status students. These findings may guide the development of future theorybased interventions that produce the greatest reductions in youth smoking.
A Bayesian hierarchical model with spatial variable selection: the effect of weather on insurance claims

Summary. Climate change will affect the insurance industry. We develop a Bayesian hierarchical statistical approach to explain and predict insurance losses due to weather events at a local geographic scale. The number of weather‐related insurance claims is modelled by combining generalized linear models with spatially smoothed variable selection. Using Gibbs sampling and reversible jump Markov chain Monte Carlo methods, this model is fitted on daily weather and insurance data from each of the 319 municipalities which constitute southern and central Norway for the period 1997–2006. Precise out‐of‐sample predictions validate the model. Our results show interesting regional patterns in the effect of different weather covariates. In addition to being useful for insurance pricing, our model can be used for short‐term predictions based on weather forecasts and for long‐term predictions based on downscaled climate models.
Errors in Language Learning and Use: Exploring Error Analysis

General editor's preface Author's preface Abbreviations 1. Definition and Delimitation Human error Successive paradigms Interlanguage and the veto on comparison Learners and native speakers The heyday of Error Analysis Mounting criticism of Error Analysis Data collection for Error Analysis 2. The Scope of Error Analysis Good English for the English Good English for the L2 learner The native speaker and the power dimension The Incompleteness hypothesis 3. Defining 'Error' Ignorance Measures of deviance Other Dimensions of Error: Error and Mistake Error: Mistake and Acquisition: Learning - An Equation? Lapsology 4. The Description of Errors Error detection Describing errors Error Classification Error Taxonomies Counting errors Profiling and Error Analysis Computerized Corpora of Errors: ICLE - COALA 5. Levels of Error Medium errors Text errors Lexical errors Classifying Lexical errors Grammar errors Discourse errors 6. Diagnosong Error Description and diagnosis Ignorance and avoidance Mother tongue influence: Interlingual errors Target language causes: Intralingual errors Learning-strategy based errors Communication strategy based errors Induced errors Compound and ambiguous errors 7. Error Gravity and Error Evaluation Evaluation Criteria for error gravity 8. Error Correction What is correction? Whether to correct: pros and cons How to do error correction: some options and principles Noticing error 9. A Case Study Elicitation and registration Error identification Categorizing the errors Status: error or mistake? Diagnosis Bibliography Index
Mondrian tree

With ubiquitous wireless connectivity and technological advances in mobile devices, we witness the growing demands and increasing market shares of mobile intelligent systems and technologies for real-time decision making and location-based knowledge discovery. Spatial alarms are considered as one of the fundamental capabilities for intelligent mobile location-based systems. Like time-based alarms that remind us the arrival of a future time point, spatial alarms remind us the arrival of a future spatial point. Existing approaches for scaling spatial alarm processing are focused on computing Alarm-Free Regions (Afr) and Alarm-Free Period (Afp) such that mobile objects traveling within an Afr can safely hibernate the alarm evaluation process for the computed Afp, to save battery power, until approaching the nearest alarm of interest. A key technical challenge in scaling spatial alarm processing is to efficiently compute Afr and Afp such that mobile objects traveling within an Afr can safely hibernate the alarm evaluation process during the computed Afp, while maintaining high accuracy. In this article we argue that on-demand computation of Afr is expensive and may not scale well for dense populations of mobile objects. Instead, we propose to maintain an index for both spatial alarms and empty regions (Afr) such that for a given mobile user's location, we can find relevant spatial alarms and whether it is in an alarm-free region more efficiently. We also show that conventional spatial indexing methods, such as R-tree family, k-d tree, Quadtree, and Grid, are by design not well suited to index empty regions. We present Mondrian Tree – a region partitioning tree for indexing both spatial alarms and alarm-free regions. We first introduce the Mondrian Tree indexing algorithms, including index construction, search, and maintenance. Then we describe a suite of Mondrian Tree optimizations to further enhance the performance of spatial alarm processing. Our experimental evaluation shows that the Mondrian Tree index, as an intelligent technology for mobile systems, outperforms traditional index methods, such as R-tree, Quadtree, and k-d tree, for spatial alarm processing.
Working memory and executive control : a festschrift for André Vandierendonck

Throughout his career, Andre Vandierendonck (PhD 1973, Ghent University) has been one of the most prominent scientific and institutional representatives of cognitive psychology in Belgium. Andre Vandierendonck became head of the Department of Experimental Psychology at Ghent University in 1995. At that time, the department consisted of two faculty members and a handful of scientific collaborators. Under the chairmanship of Andre Vandierendonck, it expanded exponentially after the introduction of a strong scientific research and publication tradition. Today, 15 years later, the same department counts nine faculty members and a scientific staff of nearly 60 people. Together, they produce a voluminous and high-quality body of scientific output addressing a wide range of topics in cognitive (neuro)psychology. Also at the European level, he has been active in the development and expansion of the field, as the president of European Society for Cognitive Psychology, as the editor of international journals and as one of the founders of the European Working Memory Symposia. This special issue is in celebration of Andre Vandierendonck’s contributions to cognitive psychology.
Parallel and Hierarchical Decision Making for Sparse Coding in Speech Recognition

Sparse coding exhibits promising performance in speech processing, mainly due to the large number of bases that can be used to represent speech signals. However, the high demand for computational power represents a major obstacle in the case of large datasets, as does the difficulty in utilising information scattered sparsely in high dimensional features. This paper reports the use of an online dictionary learning technique, proposed recently by the machine learning community, to learn large scale bases efficiently, and proposes a new parallel and hierarchical architecture to make use of the sparse information in high dimensional features. The approach uses multilayer perceptrons (MLPs) to model sparse feature subspaces and make local decisions accordingly; the latter are integrated by additional MLPs in a hierarchical way for making global decisions. Experiments on the WSJ database show that the proposed approach not only solves the problem of prohibitive computation with large-dimensional sparse features, but also provides better performance in a frame-level phone prediction task.