Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Small-Molecule AMP-Activated Protein Kinase Allosteric Activator with Beneficial Effects in db/db Mice

AMP-activated protein kinase (AMPK) is an energy sensor of metabolism that is an attractive therapeutic target for type 2 diabetes mellitus and metabolic syndrome. Using a homogeneous scintillation proximity assay (SPA), we identified a new small-molecule AMPK activator, ZLN024, which allosterically stimulated active AMPK heterotrimers and the inactive α1 subunit truncations α1 (1–394) and α1 (1–335) but not α1 (1–312). AMPK activation by ZLN024 requires the pre-phosphorylation of Thr-172 by at least one upstream kinase and protects AMPK Thr-172 against dephosphorylation by PP2Cα. ZLN024 activated AMPK in L6 myotubes and stimulated glucose uptake and fatty acid oxidation without increasing the ADP/ATP ratio. ZLN024 also activated AMPK in primary hepatocytes, decreased fatty acid synthesis and glucose output. Treatment of db/db mice with 15 mg/kg/day ZLN024 improved glucose tolerance; liver tissue weight, triacylglycerol and the total cholesterol content were decreased. The hepatic transcriptional level of G6Pase, FAS and mtGPAT were reduced. The transcription of genes involved in fatty acid oxidation and the mitochondrial biogenesis of muscle tissue were elevated. The ACC phosphorylation was increased in muscle and liver. This study provides a novel allosteric AMPK activator for functional study in vitro and in vivo and demonstrates that AMPK allosteric activators could be a promising therapeutic approach for type 2 diabetes mellitus and metabolic syndrome.
Universities as legal entities and community dispute resolution: An Australian case study

Abstract This article considers the exercise of statutory power by an Australian university, in the state of Victoria, when undertaking commercial activities that impact negatively on a local community. A single case study design is used to report on the process engaged in by the community and university to resolve this dispute. This includes consideration of the university’s characterisation of the activities it engaged in, the university bypassing local planning processes and the university’s identification of the community with which to conduct its consultation processes. All publicly available documents regarding the proposed development were scrutinised as well as records of public forums related to the dispute. The study findings advance public understanding of the complexity of the vexed question of the extent to which university legislation can be used for commercial purposes and key issues for consideration when undertaking university–community engagement that have wider application for universities globally. John Dewey’s philosophy of democracy and education provides valuable insights for developing democratic processes that facilitate deep understandings and good will that ultimately have the potential to enrich communities and prevent conflict.
Gratitude, insecure attachment, and positive outcomes among 12-step recovery program participants*

Abstract People in 12-step addiction recovery programs who have difficulty with social relationships and intimacy may be less likely to flourish given the highly social nature of 12-step programs. Gratitude is widely known among 12-step program members as a tool that facilitates well-being; in the field of positive psychology, gratitude is known for its prosocial qualities, including the development and maintenance of social relationships. However, there has been little research on gratitude in recovery, and no research that looks at people’s characteristic approach to closeness and intimacy (i.e. attachment style) and gratitude in recovery. In a sample of 184 members of 12-step addiction recovery programs (Alcoholics Anonymous and Narcotics Anonymous) we examined whether people who were more grateful reported higher positive indicators of recovery (i.e. 12-step program practices, AA promises), and better general life outcomes (i.e. more post-traumatic growth and social support; less stress and health symptoms). We also investigated whether gratitude was more important for people in recovery who have higher attachment anxiety or attachment avoidance. In line with our predictions, we found that higher levels of gratitude were positively associated with 12-step practices, AA promises, post-traumatic growth, and social support; and negatively associated with stress and health symptoms. Further, we discovered that when people with higher attachment avoidance (but not anxiety) were also grateful, they reported better outcomes. Findings suggest that gratitude is an important factor in this population that warrants further exploration. Future research might benefit from longitudinal or experimental methods that examine whether gratitude is an antecedent to or a result of 12-step practices, AA promises, post-traumatic growth, and social support.
Concept Extraction and Clustering for Topic Digital Library Construction

This paper is to introduce a new approach to build topic digital library using concept extraction and document clustering. Firstly, documents in a special domain are automatically produced by document classification approach. Then, the keywords of each document are extracted using the machine learning approach. The keywords are used to cluster the documents subset. The clustered result is the taxonomy of the subset. Lastly, the taxonomy is modified to the hierarchical structure for user navigation by manual adjustments. The topic digital library is constructed after combining the full-text retrieval and hierarchical navigation function.
Analyzing Popular Clustering Algorithms from Different Viewpoints

Clustering is widely studied in data mining community. It is used to partition data set into clusters so that intra-cluster data are similar and inter-cluster data are dissimilar. Different clustering methods use different similarity definition and techniques. Several popular clustering algorithms are analyzed from three different viewpoints: (1) clustering criteria, (2) cluster representation, and (3) algorithm framework. Furthermore, some new built algorithms, which mix or generalize some other algorithms, are introduced. Since the analysis is from several viewpoints, it can cover and distinguish most of the existing algorithms. It is the basis of the research of self-tuning algorithm and clustering benchmark.
Effect of Oxygen on Glucose Metabolism: Utilization of Lactate in Staphylococcus Aureus as Revealed by In Vivo NMR Studies

The ability to successfully adapt to changing host conditions is crucial for full virulence of bacterial pathogens. Staphylococcus aureus has to cope with fluctuating oxygen concentrations during the course of infection. Hence, we studied the effect of oxygen on glucose metabolism in non-growing S. aureus COL-S cells by in vivo 13C-NMR. Glucose catabolism was probed at different oxygen concentrations in suspensions of cells grown aerobically (direct effects on metabolism) or anaerobically (transcriptional adjustment to oxygen deprivation). In aerobically-grown cells, the rate of glucose consumption diminished progressively with decreasing oxygen concentrations. Additionally, oxygen deprivation resulted in biphasic glucose consumption, with the second phase presenting a higher rate. The fructose-1,6-bisphosphate pool peaked while glucose was still abundant, but the transient maximum varied with the oxygen concentration. As oxygen became limiting mannitol/mannitol-1-phosphate were detected as products of glucose catabolism. Under anoxic conditions, accumulation of mannitol-1-phosphate ceased with the switch to higher glucose consumption rates, which implies the activation of a more efficient means by which NAD+ can be regenerated. The distribution of end-products deriving from glucose catabolism was dramatically affected by oxygen: acetate increased and lactate decreased with the oxygen concentration; ethanol was formed only anaerobically. Moreover, oxygen promoted the energetically favourable conversion of lactate into acetate, which was particularly noticeable under fully oxygenated conditions. Interestingly, under aerobiosis growing S. aureus cells also converted lactate to acetate, used simultaneously glucose and lactate as substrates for growth, and grew considerably well on lactate-medium. We propose that the efficient lactate catabolism may endow S. aureus with a metabolic advantage in its ecological niche.
Active speech source localization by a dual coarse-to-fine search

Accurate and fast localization of multiple speech sound sources is a significant problem in videoconferencing systems. Based on the observation that the wavelengths of the sound from a speech source are comparable to the dimensions of the space being searched, and that the source is broadband, we develop an efficient search strategy that finds the source(s) in a given space. The search is made efficient by using coarse-to-fine strategies in both space and frequency. The algorithm is shown to be robust compared to typical delay-based estimators and fast enough for real-time implementation. Its performance can be further improved by using constraints from computer vision.
Negotiating contradictions in developing teacher identity during the EAL practicum in Australia

ABSTRACT This paper reports on how Maria (pseudonym), a non-native English speaker (NNES) and preservice teacher (PST) of English as an additional language (EAL), developed her professional identity during the practicum in an Australian secondary school. Drawing on activity theory, the study identified contradictions in Maria’s practicum activity and examined how Maria’s professional identity developed through her negotiation of the contradictions. Data included interviews with Maria before, during and after the practicum, her reflections, an interview with her school mentor (Ms Davies, pseudonym), and relevant documents. The findings reveal that Maria experienced contradictions between her multiple identities of NNES, student, becoming teacher, and classroom teacher, between her mentor’s teaching approach and that of her own, and between her practice and rules. The findings provide implications for researching teacher identity and supporting preservice EAL teachers in developing productive teacher identities during the practicum.
Using language complexity to measure cognitive load for adaptive interaction design

An adaptive interaction system, which is aware of the users' current cognitive load, can change its response, presentation and interaction flow to improve users' experience and their task performance. In this paper, we propose a novel speech content analysis approach for measuring users' cognitive load, based on their language and dialogue complexity. We have analysed the transcribed speech of operators working in computerized incident control rooms and involved in highly complex bushfire management tasks in Australia. The resulting patterns of language complexity show significant differences between the speech from cognitively low load and high load tasks. We also discuss the value of using this approach of cognitive load measurement for user interface evaluation and interaction design improvement.
Flexibility of KorA, a plasmid-encoded, global transcription regulator, in the presence and the absence of its operator

Abstract The IncP (Incompatibility group P) plasmids are important carriers in the spread of antibiotic resistance across Gram-negative bacteria. Gene expression in the IncP-1 plasmids is stringently controlled by a network of four global repressors, KorA, KorB, TrbA and KorC interacting cooperatively. Intriguingly, KorA and KorB can act as co-repressors at varying distances between their operators, even when they are moved to be on opposite sides of the DNA. KorA is a homodimer with the 101-amino acid subunits, folding into an N-terminal DNA-binding domain and a C-terminal dimerization domain. In this study, we have determined the structures of the free KorA repressor and two complexes each bound to a 20-bp palindromic DNA duplex containing its consensus operator sequence. Using a combination of X-ray crystallography, nuclear magnetic resonance spectroscopy, SAXS and molecular dynamics calculations, we show that the linker between the two domains is very flexible and the protein remains highly mobile in the presence of DNA. This flexibility allows the DNA-binding domains of the dimer to straddle the operator DNA on binding and is likely to be important in cooperative binding to KorB. Unexpectedly, the C-terminal domain of KorA is structurally similar to the dimerization domain of the tumour suppressor p53.
Special Interest Messaging: A Comparison of IGM Approaches

Hundreds of technical, special interest Internet weblogs are already generating thousands of niche articles worldwide, and many institutions are starting to create internal blogs for team collaboration. As this style of communication becomes more pervasive in the lives of employees and researchers, the difficulty of finding relevant information only grows with the number of authors and articles. To reduce the load, we propose using implicit group messaging (IGM) to automatically deliver relevant content to readers grouped by shared characteristics or interests. In this paper, we outline a context-aware application suited to special interest messaging and describe three alternative delivery models including our peer-to-peer (P2P) design called SPICE and a broker-based design. We investigate the advantages and disadvantages of each approach through detailed simulations driven by realistic data and actual national/global network topologies. We find that although a broker-based design is generally the most network efficient and lowest latency, a structured P2P system can offer exceptionally low and fair loading across peers and network links without relying on specialized broker nodes.
e-VeMAC: An enhanced vehicular MAC protocol to mitigate the exposed terminal problem

The VeMAC, a TDMA-based MAC protocol for Vehicular Ad-hoc NETworks (VANET), assigns disjoint sets of the time slots to vehicles moving in opposite directions and to road side units. So the VeMAC protocol reduces the access and merging collisions. Moreover, the VeMAC protocol employs slot release prevention condition which avoids unnecessarily releasing time slots when a node just enters the communication range of each other. Although VeMAC supports reliable and efficient transmission, it is still not full applicable for VANET in parallel transmission. In this paper, we propose an e-VeMAC protocol: an enhanced vehicular MAC protocol to mitigate the exposed terminal problem. The simulation results show that the e-VeMAC protocol supports more parallel transmissions than the VeMAC protocol.
Design and performance analysis of scheduling algorithms for WDM-PON under SUCCESS-HPON architecture

Results of the design and performance analysis of two new algorithms for efficient and fair scheduling of variable-length frames in a wavelength division multiplexing (WDM)-passive optical network (PON) under the Stanford University aCCESS-Hybrid PON (SUCCESS-HPON) architecture are reported. The WDM-PON under the SUCCESS-HPON architecture has unique features that have direct impacts on the design of scheduling algorithms. First, an optical line terminal (OLT) uses tunable transmitters and receivers that are shared by all the optical network units (ONUs) served by the OLT to reduce the number of expensive dense WDM (DWDM) transceivers. Second, also for cost reduction, ONUs have no local DWDM light sources but use optical modulators to modulate optical continuous wave (CW) bursts provided by the OLT for upstream transmissions. Therefore, the tunable transmitters at the OLT are used for both upstream and downstream transmissions. To provide efficient bidirectional communications between the OLT and the ONUs and guarantee fairness between upstream and downstream traffic, two scheduling algorithms have been designed: 1) batching earliest departure first (BEDF); and 2) sequential scheduling with schedule-time framing (S/sup 3/F). The BEDF is based on the batch scheduling mode where frames arriving at the OLT during a batch period are stored in virtual output queues (VOQs) and scheduled at the end of the batch period. It improves transmission efficiency by selecting the frame with the earliest departure time from a batch of multiple frames, which optimizes the usage of tunable transmitters in scheduling. Considering the high complexity of the optimization process in BEDF, the S/sup 3/F based on the sequential scheduling mode has also been designed as in the original sequential scheduling algorithm proposed earlier. In S/sup 3/F, the authors use VOQs to provide memory space protection among traffic flows and a granting scheme together with schedule-time framing for both upstream and downstream traffic to reduce framing and guard band overhead. Through extensive simulations under various configurations of the tunable transmitters and receivers, it has been demonstrated that both the BEDF and S/sup 3/F substantially improve the throughput and delay performances over the original sequential scheduling algorithm, while guaranteeing better fairness between upstream and downstream traffic.
Spoke-Darts for High-Dimensional Blue-Noise Sampling

Blue noise sampling has proved useful for many graphics applications, but remains underexplored in high-dimensional spaces due to the difficulty of generating distributions and proving properties about them. We present a blue noise sampling method with good quality and performance across different dimensions. The method, spoke-dart sampling, shoots rays from prior samples and selects samples from these rays. It combines the advantages of two major high-dimensional sampling methods: the locality of advancing front with the dimensionality-reduction of hyperplanes, specifically line sampling. We prove that the output sampling is saturated with high probability, with bounds on distances between pairs of samples and between any domain point and its nearest sample. We demonstrate spoke-dart applications for approximate Delaunay graph construction, global optimization, and robotic motion planning. Both the blue-noise quality of the output distribution and the adaptability of the intermediate processes of our method are useful in these applications.
Undesirable Effects of Goal Setting on Perceived Fairness, Commitment, and Unethical Behavior

Abstract. The positive effects of goal setting on motivation and performance are among the most established findings of industrial–organizational psychology. Accordingly, goal setting is a common management technique. Lately, however, potential negative effects of goal-setting, for example, on unethical behavior, are increasingly being discussed. This research replicates and extends a laboratory experiment conducted in the United States. In one of three goal conditions (do-your-best goals, consistently high goals, increasingly high goals), 101 participants worked on a search task in five rounds. Half of them (transparency yes/no) were informed at the outset about goal development. We did not find the expected effects on unethical behavior but medium-to-large effects on subjective variables: Perceived fairness of goals and goal commitment were least favorable in the increasing-goal condition, particularly in later goal rounds. Results indicate that when designing goal-setting interventions, organizations m.
The Rise of Big Data in Neurorehabilitation

Abstract In some fields, Big Data has been instrumental in analyzing, predicting, and influencing human behavior. However, Big Data approaches have so far been less central in speech-language pathology. This article introduces the concept of Big Data and provides examples of Big Data initiatives pertaining to adult neurorehabilitation. It also discusses the potential theoretical and clinical contributions that Big Data can make. The article also recognizes some impediments in building and using Big Data for scientific and clinical inquiry.
An Empirical Study of the 3-valued Kripke-kleene Semantics in Random Propositional Logic Programs Extended Abstract

We empirically studied the behavior of the 3-Valued Kripke-Kleene semantics in a parameterized distribution of random propositional logic programs. In our distribution, programs with m rules are generated from n propositional letters by repeating the following process m times: uniformly, randomly, and independently choose k letters (with replacement) from the set of n proposition letters and negate each of the last k ? 1 letters independently with probability p. The rst letter becomes the head of the rule and the remaining k ? 1 literals become the subgoals. The collection of m rules make up the logic program. We xed p = 0:5, k = 3 and varied n over a range of values investigating, for each, the relationship between m=n and the percentage of inconsistent models produced by the 3-Valued Kripke-Kleene semantics. In all of our experiments, the 3-Valued Kripke-Kleene semantics were computed with respect to a xed percentage of proposition letters (randomly chosen) initially assigned TRUE and a xed percentage (randomly chosen) initially assigned FALSE. We observed that there exist regions in the parameter space of our distribution in which the 3-Valued Kripke-Kleene semantics tends to produce a high percentage of inconsistent models, therefore, providing information useful to prune branches in a backtracking search for stable models. Also, we observed a region in which a very small percentage of inconsistent models are produced, therefore, providing very little information useful for pruning branches in a backtracking search.
Causality Interfaces and Compositional Causality Analysis 1

In this paper, we consider concurrent models of computation where ”actors” (components that are in charge of their own actions) communicate by exchanging messages. The interfaces of actors principally consist of “ports,” which mediate the exchange of messages. Actor-oriented architectures contrast with and complement object-oriented models by emphasizing the exchange of data between concurrent components rather than transfer of control. Examples of such models of computation include the classical actor model, synchronous languages, dataflow models, and discrete-event models. Many of these models of computation benefit considerably from having access to causality information about the components. This paper augments the interfaces of such components to include such causality information. It shows how this causality information can be algebraically composed so that compositions of components acquire causality interfaces that are inferred from their components and the interconnections. We illustrate the use of these causality interfaces to statically analyze discrete-event models for uniqueness of behaviors, synchronous models for causality loops, and dataflow models for schedulability.
Gas Sensing Mechanism of Gold Nanoparticles Decorated Single-Walled Carbon Nanotubes

Metal nanoparticles decorated single-walled carbon nanotubes (SWNTs) can lead to considerable enhancement in sensing performance towards different gas analytes, however the sensing mechanism was not clearly elucidated. The detailed sensing mechanism of hybrid gold-SWNT nanostructures toward hydrogen sulfide was investigated using field effect transistor (FET) transfer characteristics. At low H2S concentrations ( 100 ppbV), FET transfer characteristics show that the gold nanoparticles at the surface of SWNTs acted as nano-Schottky barriers to predominately modulate transconductance upon exposure to unfunctionalized SWNTs on gold electrodes which showed little or no response upon exposure. Although the sensitivity of Au/SWNT toward H2S was strongly dependent upon the size and number of gold nanoparticles, the sensing mechanism was independent of it.