Miracle-dz/UniFAR-FTUs huggingface dataset:
Observations on intracellular pH during cleavage of eggs of Xenopus laevis

Direct measurements of intracellular pH was made with recessed-tip pH microelectrodes in fertilized eggs of the frog, Xenopus laevis, from approximately 1 h after fertilization to mid-blastula. The intracellular pH just before first cleavage was 7.65 +/- 0.04 (SD; n = 9). By stage 5 to the middle of stage 6, average intracellular pH was 7.70 +/- 0.06 (SD; n = 16). A statistically significant alkalization of 0.18 +/- 0.03 pH unit (SD; n = 5) was observed beginning in early blastula. A cycle of less than or equal to 0.05 pH unit was occasionally observed during the pre-blastula period, but its significance is unknown. By exposing the early cleavage embryo to saline buffered with sodium propionate, pH 4.7-5.0, it was possible to lower intracellular pH with some degree of control. Apparently, normal cleavage continued to occur when intracellular pH had been forced as much as 0.3 unit below normal. We conclude that this implies no specific involvement of intracellular pH in mitosis and cytokinesis. If intracellular pH was lowered further, cell division ceased at about pH 7.2, and furrow regression began at about pH 7.0. Once furrow regression occurred, subsequent development was usually arrested or abnormal when the embryo was transferred back to normal saline.
Macrophage Reverse Cholesterol Transport in Mice Expressing ApoA-I Milano

Objective—To compare the abilities of human wild-type apoA-I (WT apoA-I) and human apoA-IMilano (apoA-IM) to promote macrophage reverse cholesterol transport (RCT) in apoA-I–null mice infected with adeno-associated virus (AAV) expressing either WT apoA-I or apoA-IM. Methods and Results—WT apoA-I– or apoA-IM–expressing mice were intraperitoneally injected with [H3]cholesterol-labeled J774 mouse macrophages. After 48 hours, no significant difference was detected in the amount of cholesterol removed from the macrophages and deposited in the feces via the RCT pathway between the WT apoA-I and apoA-IM groups. Analysis of the individual components of the RCT pathway demonstrated that the apoA-IM–expressing mice promoted ATP-binding cassette transporter A1 (ABCA1)-mediated cholesterol efflux as efficiently as WT apoA-I but that apoA-IM had a reduced ability to promote cholesterol esterification via lecithin cholesterol-acyltransferase (LCAT). This resulted in reduced cholesteryl ester (CE) and increased free cholesterol (FC) levels in the plasma of mice expressing apoA-IM compared to WT apoA-I. These differences did not affect the rate of delivery of labeled cholesterol to the liver via SR-BI–mediated selective uptake or its subsequent excretion in the feces. Conclusion—Within the limits of the in vivo assay, WT apoA-I and apoA-IM are equally efficient at promoting macrophage RCT, suggesting that if apoA-IM is more atheroprotective than WT apoA-I it is not attributable to an enhancement of macrophage RCT.
Transferring Knowledge between Supervisors and Managerial Peer Groups: Falling at the trust hurdle

This abstract reports findings from an exploratory study that attempted to investigate the variables that impact on knowledge transfer between supervisors and managerial peer groups in organisations. Organisations rely on the dissemination of knowledge in order to drive their strategies, products and operations. This study suggests that cultural implications may impact on the transfer of knowledge in organisations. This study adopted a social constructionist approach to the transfer of knowledge by using the social process of sharing knowledge and its effect on respondents' perceived innovation in organisations. The sample consisted of 106 MBA students. The response rate was 100% of which 96 were useable. Both public and private sector organizations were represented across a wide variety of industries with over 50 respondents being directors or managers. A questionnaire comprising of 20 items consisting of open and closed questions was used; six were anchored to a 5 point Likert type scale, five were open, and two were closed requiring a yes or no answer. Seven items were included to collect demographic data. Quantitative data were analysed using descriptive statistics and qualitative data utilized category theme analysis. All respondents reported a low level of trust in peers (m=3.1) but a slightly higher level in supervisors (m=2.9). The Asian group reported less trust of their peers (m=3.3). Respondents reported that supervisors (64%) and peers (67%) withheld knowledge and reported satisfaction with the quantity (47%) and quality (43%) of knowledge disseminated by supervisors and quantity (45%) and quality (37%) of knowledge disseminated by peers. Sorting the data by country of origin into non-Asian and Asian groups revealed differences in reported levels of satisfaction with the quantity and quality of knowledge disseminated by supervisors and peers. The non-Asian group reported a 50% rate of satisfaction with the quality of knowledge from supervisors, whereas the Asian respondents reported a 35% rate of satisfaction. The Asian population reported a high level of withholding knowledge by peers (74%), while non-Asians reported a high level of withholding knowledge by supervisors (66%). Qualitative data was collected to show why supervisors and peers withheld knowledge and the respondent's emotional response. The category theme analysis revealed the following themes: anger, annoyance, alienation, frustration, lack of trust, and jealousy. The qualitative data showed that organisations promoted innovation (68%) through recognition, rewards and autonomy but that perceptions of innovation were culture specific. The combination of high levels of withholding knowledge, low levels of dissatisfaction …
Combining Instruction Prefetching with Partial Cache Locking to Improve WCET in Real-Time Systems

Caches play an important role in embedded systems to bridge the performance gap between fast processor and slow memory. And prefetching mechanisms are proposed to further improve the cache performance. While in real-time systems, the application of caches complicates the Worst-Case Execution Time (WCET) analysis due to its unpredictable behavior. Modern embedded processors often equip locking mechanism to improve timing predictability of the instruction cache. However, locking the whole cache may degrade the cache performance and increase the WCET of the real-time application. In this paper, we proposed an instruction-prefetching combined partial cache locking mechanism, which combines an instruction prefetching mechanism (termed as BBIP) with partial cache locking to improve the WCET estimates of real-time applications. BBIP is an instruction prefetching mechanism we have already proposed to improve the worst-case cache performance and in turn the worst-case execution time. The estimations on typical real-time applications show that the partial cache locking mechanism shows remarkable WCET improvement over static analysis and full cache locking.
Energy Optimization in Smart Homes Using Customer Preference and Dynamic Pricing

In this paper, we present an energy optimization technique to schedule three types of household appliances (user dependent, interactive schedulable and unschedulable) in response to the dynamic behaviours of customers, electricity prices and weather conditions. Our optimization technique schedules household appliances in real time to optimally control their energy consumption, such that the electricity bills of end users are reduced while not compromising on user comfort. More specifically, we use the binary multiple knapsack problem formulation technique to design an objective function, which is solved via the constraint optimization technique. Simulation results show that average aggregated energy savings with and without considering the human presence control system are 11.77% and 5.91%, respectively.
Adaptive Image Restoration: Perception Based Neural Nework Models and Algorithms.

This thesis describes research into the ﬁeld of image restoration. Restoration is a process by which an image suffering some form of distortion or degradation can be recovered to its original form. Two primary concepts within this ﬁeld have been investigated. The ﬁrst concept is the use of a Hopﬁeld neural network to implement the constrained least square error method of image restoration. In this thesis, the author reviews previous neural network restoration algorithms in the literature and builds on these algorithms to develop a new faster version of the Hopﬁeld neural network algorithm for image restoration. The versatility of the neural network approach is then extended by the author to deal with the cases of spatially variant distortion and adaptive regularisation. It is found that using the Hopﬁeld-based neural network approach, an image suffering spatially variant degradation can be accurately restored without a substantial penalty in restoration time. In addition, the adaptive regularisation restoration technique presented in this thesis is shown to produce superior results when compared to non-adaptive techniques and is particularly effective when applied to the difﬁcult, yet important, problem of semi-blind deconvolution. The second concept investigated in this thesis, is the difﬁcult problem of incorporating concepts involved in human visual perception into image restoration techniques. In this thesis, the author develops a novel image error measure which compares two images based on the differences between local regional statistics rather than pixel level differences. This measure more closely corresponds to the way humans perceive the differences between two images. Two restoration algorithms are developed by the author based on versions of the novel image error measure. It is shown that the algorithms which utilise this error measure have improved performance
Towards a Mobile Peer-to-Peer Service Platform

Peer-to-peer (P2P) technology is regarded as being disruptive for traditional fixed and mobile operators. However, it can also be considered as an opportunity for new ways of service provisioning. On the one hand, P2P concepts allow a more efficient usage of existing platform resources through relying on existing infrastructure including even the customer equipment and thus provide a cheap service platform. On the other hand, P2P technology brings new business opportunities through extending the service portfolio to user provided services and to ubiquitous environments. Along these lines, we outline in this paper the requirements and building blocks for a P2P based service platform for mobile environments. In addition to P2P lookup and information distribution, these building blocks include reliability, controllability, bootstrapping, reputation management, which address operator specific requirements in particular. Mobile networks pose severe challenges to a P2P service platform in terms of heterogeneous devices and access connections and frequent user joins and leaves. We present a hierarchical P2P system as a core component for a P2P service platform addressing those problems
Motion, Stereo and Color Analysis for Dynamic Virtual Environments

We develop a vision system for highly mobile autonomous agents that is capable of dynamic obstacle avoidance and active perception. We demonstrate the robust performance of the system in artificial animals with directable, foveated eyes, situated in physics-based virtual worlds. Through active perception, each agent controls its eyes and body by continuously analyzing photorealistic binocular retinal image streams. The vision system estimates optical flow, computes stereo disparity and segments looming targets in the low-resolution visual periphery while controlling eye movements to track an object fixated in the high-resolution fovea. It matches segmented targets against mental models of colored objects of interest in order to decide whether the segmented objects are harmless or represent dangerous obstacles. The latter are localized, enabling the artificial animal to exercise the sensorimotor control necessary to support complex behaviors, such as predation, and obstacle avoidance.
Rare event simulation

Discrete event simulation as a method for performance evaluation has become an indispensable tool in many fields, e.g., teletraffic engineering. New communication networks and services pose extreme requirements regarding the quality of service, e.g., cell loss probabilities in ATM1 networks in the order of 10 -9. Straightforward simulation for this type of rare event leads to simulation run times in the order of months and years, thus requiring new methods to be investigated and employed. In the following the state of the art in the field of Rare Event Simulation is described and examples are given for the RESTART2 /LRE3 method to demonstrate the type of results that can be achieved by using these methods. In recent years these methods have been applied to relevant quality of service parameters in ATM networks. Future applications will concern the investigation of the emerging quality of service concepts for Next Generation Internets.
Value-Based File Retention: File Attributes as File Value and Information Waste Indicators

Several file retention policy methods propose that a file retention policy should be based on file value. Though such a retention policy might increase the value of accessible files, the method to arrive at such a policy is underresearched. This article discusses how one can arrive at a method for developing file retention policies based on the use values of files. The method’s applicability is initially assessed through a case study at Capgemini, Netherlands. In the case study, we hypothesize that one can develop a file retention policy by testing causal relations between file attributes (as used by file retention methods) and the use value of files. Unfortunately, most file attributes used by file retention methods have a weak correlation with file value, resulting in the conclusion that these methods do not well select out high- and low-value files. This would imply the ineffectiveness of the used attributes in our study or errors in our conceptualization of file value. We continue with the last possibility and develop indicators for file utility (with low utility being waste). With this approach we were able to detect waste files, in a sample of files, with an accuracy of 80%. We therefore not only suggest further research in information waste detection as part of a file retention policy, but also to further explore other file attributes that could better predict file value and file utility.
Settings-Free Traveling-Wave-Based Earth Fault Location Using Unsynchronized Two-Terminal Data

This paper presents a two-terminal traveling-wave (TW)-based earth fault-location algorithm. It works using unsynchronized data and does not require information about the line parameters. Evaluated signals are decoupled into aerial and ground modes and, then, only the incident TWs of each mode are detected at the line ends. Earth fault case studies are carried out to attest the proposed algorithm feasibility, comparing its performance with those of one- and two-terminal approaches reported in the literature. Obtained results reveal that the proposed algorithm is straightforward and quite reliable.
The Malware Analysis Body of Knowledge (MABOK)

The ability to forensically analyse malicious software (malware) is becoming an increasingly important discipline in the field of Digital Forensics. This is because malware is becoming stealthier, targeted, profit driven, managed by criminal organizations, harder to detect and much harder to analyse. Malware analysis requires a considerable skill set to delve deep into malware internals when it is designed specifically to detect and hinder such attempts. This paper presents a foundation for a Malware Analysis Body of Knowledge (MABOK) that is required to successfully forensically analyse malware. This body of knowledge has been the result of several years of research into malware dissection.
Does More Corporate Governance Enhance Managerial Performance? CFO Perceptions And The Role Of Mindfulness

The results of studies into the effects of enhanced governance structures have been equivocal and there is virtually no literature on the performance effects of individual managers, such as the professional accountant in practice. This paper reports the results of an empirical study designed to assess the relationship of governance structures, specifically the conformance and performance dimensions defined by the International Federation of Accountants (2009), to mindfulness and managerial performance among CFOs in Canadian firms. Organizational theory describing high reliability organizations provides the theoretical framework for specifying and appraising capacity for mindfulness. As predicted, there is no significant direct relationship between governance and managerial performance for the conformance dimension; instead, this relationship is explained by the path through capacity for mindfulness and on to managerial performance, both of which are positively significant. Likewise, there is no significant relationship between governance and managerial performance for the conformance dimension; however, although there is a significant path between the performance dimension and capacity for mindfulness, the path from the latter to managerial performance is insignificant. Implicating the powerful role of the controllability principle in accounting may explain this unexpected finding.
Orthogonal signal decomposition coupled with Bayes and fuzzy discriminant classifiers for ultrasonic flaw detection

The performance of an ultrasonic flaw detection system is valued by its success in differentiating flaw echoes from those scattered by microstructures (e.g. grain scattering or clutter). In order to successfully detect and classify the target echoes from background noise, an effective feature extracting method and a robust decision process are required. In this study, we present a comparative evaluation of three orthogonal signal decomposition methods: constant B (bandwidth); constant E (energy); and constant Q (i.e., ratio of bandwidth to center frequency), spanning the entire frequency band of the signal. An efficient method of implementing orthogonal decomposition using the Haar filter is presented. Orthogonal decomposition of the signal offers feature vectors suitable for classification and signal evaluation. The differences observed in the probability density function of clutter and the flaw echoes resulting from orthogonal decomposition are utilized to design the Bayes and fuzzy discriminant classifiers for flaw detection. These classifiers show good sensitivities in detecting flaw echoes in the presence of strong clutter where the signal-to-noise ratio is about zero dB. In this paper we present a mathematical derivation for these techniques and experimental results to demonstrate their application in ultrasonic nondestructive testing.
Mining the usability of business process modeling tools: concept and case study

Business process models are key artifacts in business process management. The technical support of the process of process modeling is important for the quality and the applicability of the resulting models. The quality of that technical support plays an important role in the selection of corresponding software products and is a crucial characteristic of differentiation. Nevertheless, only little knowledge on the tool-specific line of actions and the corresponding challenges in the daily work of modelers is available, which makes it hard to improve a modeling tool against customer requirements. In order to address that conflict, we develop a method based on process mining, allowing the continuous analysis of modeling tools and the applied processes of process modeling with regard to software usability aspects. The resulting method containing the phases user monitoring, trace clustering, usage model derivation, usage model analysis, recommendation derivation and implementation primarily aims at a target-oriented design and further development of business process modeling tools and is evaluated with the ARIS Designer by performing a user study. The results allow promising estimations for an application of the method in a broader context.
Recovering Activity Diagrams from Object Oriented Code : an MDA-based Approach

The success of system modernization depends on the existence of technical frameworks for information integration and tool interoperation like the Model Driven Architecture (MDA). Reverse engineering techniques play a crucial role in system modernization. This paper describes how to reverse engineering activity diagrams from object oriented code in the MDA context focusing on transformations at model and metamodel levels. A framework to reverse engineering MDA models from object oriented code that distinguishes three different abstraction levels linked to models, metamodels and formal specifications, is described. At model level, transformations are based on static and dynamic analysis. At metamodel level, transformations are specified as OCL contracts between MOF (Meta Object Facility) metamodels which control the consistency of these transformations. The level of formal specification includes algebraic specifications of MOF metamodels and metamodelbased transformations. This paper analyzes a recovery process of activity diagrams from Java code by applying static and dynamic analysis and show a formalization of this process in terms of MOF metamodels.
A Novel Generalized Value Iteration Scheme For Partially-Unknown Continuous-Time Linear Systems

— In this paper, a novel generalized value iteration technique is presented for solving online the discounted linear quadratic (LQ) optimal control problems for continuous-time (CT) linear systems with an unknown system matrix A . In the proposed method, the discounted value function is considered, which is a general setting in reinforcement learning (RL) frameworks, but not fully considered in RL for CT dynamical systems. Moreover, stepwise-varying learning rate h i is introduced for the fast and safe convergence. For the stability and monotone convergence to the true optimal solution, it is mathematically proven that if stepwise-varying learning rate h i lies in some speciﬁed ranges, the proposed algorithm guarantees the so-called Hurwitz property concerning the stability of the closed loop system, and, in addition, converges to the discounted LQ optimal solution. These proofs also give the stability and monotone convergence conditions for the existing value iteration method as a special case since the proposed method is more general than the existing ones.