Miracle-dz/UniFAR-FTUs huggingface dataset:
Am I missing something by not using story-telling? Why we should ask university students to use story-telling to evaluate their experiences of learning

ABSTRACT Evaluations of student’s learning experiences hold increasing currency in deciding how to improve teaching and learning. This article proposes that students who use story-telling for evaluation help to facilitate this. Adding to previous research that shows the benefit and challenges of gathering qualitative feedback, stories written by 47 Childhood Studies undergraduate students while at university in England explain their learning experiences. Analysis of the content of their stories identified what their learning journey had been like providing useful information to shape teaching and support their wellbeing; both important measures for universities because they are factors that influence retention and the number of applicants to their institution. The research concludes that stories written by students are useful because they enable the HE teacher to engage in new ways of listening and responding to personal accounts that communicate what the learning experience is like for students and what is important to them.
Proceedings of Symposia in Applied Mathematics Spacetime geometry from causal structure and a measurement

The causal structure of spacetime defines a partial order on the events of spacetime. In an earlier paper, using techniques from domain theory, we showed that for globally hyperbolic spacetimes one could reconstruct the topology from the causal structure. However, the causal structure determines the metric only up to a local rescaling (a conformal transformation); in a four dimensional spacetime, the metric tensor has ten components, and thus effectively only nine are determined by the causal structure. After establishing the relationship between measurement in domain theory, the concept of global time function and the Lorentz distance, we are able to domain theoretically recover the final tenth component of the metric tensor, thereby obtaining causal reconstruction of not only the topology of spacetime, but also its geometry.
Contention-Aware Metrics: Analysis of Distributed Algorithms

Contention-Aware Metrics: Analysis of Distributed Algorithms Resource contention is widely recognized as having a major impact on the performance of distributed algorithms. Nevertheless, the metrics that are commonly used to predict their performance take little or no account of contention. In this paper, we define two performance metrics for distributed algorithms that account for network contention as well as CPU contention. We then illustrate the use of these metrics by comparing four Atomic Broadcast algorithms, and show that our metrics allow for a deeper understanding of performance issues than conventional metrics.
Effects of Demand Managements on Sector Sizes and Okun's Law

This paper examines the effects of attempts at altering the magnitudes of macroeconomic output, GDP, by changing the pattern of demand shares of sectors which comprise the economy. We have earlier proved that larger shares of demands on a more productive subset of sectors results in a higher value of GDP. When demand patterns are changed before the model state reaches some neighborhood of an equilibrium, however, such pattern changes may reduce the magnitudes of GDP rather than increasing them. We explan this seemingly counter-intuitive behavior in this paper. We also examine the effects of endogenized shares of demands on the coefficients of the Okun’s law, and provide conditions under which higher GDP values produce larger coefficient values.
Domestic Capacities for Building Post-Conflict Peace

The existing democratization and peacebuilding literature often neglects the important role the domestic realm plays in post-conflict peacebuilding. To explain why some post-conflict peacebuilding operations have a greater likelihood of success than others, some scholars have examined the impact of factors such as international coordination, external donor interest, democratic sequencing, and hostility levels. This analysis focuses on domestic capacities for building peace in the aftermath of civil conflict in order to systematically explore the relationship between the domestic sphere and peacebuilding success. Using Sambanis and Doyle’s (2006) peacebuilding triangle model, new local capacities indexes will be created and tested. INDEX WORDS: Peacebuilding, Civil War, Democratization, Local capacities, Post-conflict reconstruction DOMESTIC CAPACITIES FOR BUILDING POST-CONFLICT PEACE
TLM protocol compliance checking at the Electronic System Level

Design and verification of embedded systems at the Electronic System Level (ESL) is common practice. In particular, Transaction Level Modeling (TLM) is the major reason for the success of ESL design. However, when detailed protocols are modeled at lower levels of TLM, the verification of the communication becomes a critical issue. In this paper, we present an approach for protocol compliance checking of new or detailed protocol implementations. They are checked against user-specified protocol sequences. We also analyze the protocol coverage achieved by the testbench and visualize the results on a protocol sequence graph. Experimental results for a SoC model demonstrate the advantages of our method.
Notice of RetractionMBA Education Teaching Evaluation Based on SPSS

In this paper, the current situation of MBA education teaching evaluation is analyzed, and the current articles related to MBA education teaching evaluation is discussed. The importance and necessity of MBA education teaching evaluation is explained too. Then a teaching evaluation form is designed, and MBA teachers of the specific university is evaluated; SPSS analytical software is applied; a scientific basis to grasp the current MBA education situation generally is provided. At last, scientific MBA education policies and management plans is established.
Overall and abdominal obesity indicators had different association with central arterial stiffness and hemodynamics independent of age, sex, blood pressure, glucose, and lipids in Chinese community-dwelling adults

Objective Limited large sample studies have specially compared overall and abdominal obesity in relation to central arterial stiffness and hemodynamics in community-dwelling adults, especially in the People’s Republic of China. This study aimed to compare the relationship between an overall obesity indicator (body mass index [BMI]), an abdominal obesity index (waist circumference [WC]), and central arterial stiffness and hemodynamics, independent of age, sex, blood pressure, glucose, and lipids, in Chinese community-dwelling adults. Methods For 2,624 adults in this study, anthropometric indices, such as BMI and WC, were measured. Central arterial stiffness was assessed by carotid-femoral pulse wave velocity (cfPWV). Central hemodynamics was represented by central pulse pressure (cPP). Results Both overall and abdominally obese adults were older, with significantly higher cfPWV, cPP, peripheral pulse pressure (pPP), fasting blood glucose (FBG), and low-density lipoprotein-cholesterol (LDL-C), and significantly lower high-density lipoprotein-cholesterol (HDL-C). After adjusting for age and sex, both the overall and abdominally obese individuals had independently higher pPP, FBG, and LDL-C levels, and lower HDL-C level. The overall obese individuals had independently higher cPP, but not cfPWV, after adjusting for age and sex, while the abdominally obese individuals had independently higher cfPWV, but not cPP. After adjusting for age, sex, pPP, FBG, LDL-C, and HDL-C, WC, but not BMI, was independently correlated with cfPWV, and BMI, but not WC, was independently associated with cPP. Age, sex, pPP, FBG, and HDL-C levels have independent association with cfPWV. Age, sex, pPP, but not FBG and HDL-C levels, have independent association with cPP. Conclusion The abdominal obesity index (WC), rather than the overall obesity indicator (BMI), was related to central arterial stiffness, independent of age, sex, blood pressure, glucose and lipids, while the overall obesity indicator (BMI), rather than the abdominal obesity indicator (WC), was independently correlated with central hemodynamics. Age, sex, and blood pressure were independently associated with central arterial stiffness and hemodynamics, but blood glucose and lipids were independently associated with central arterial stiffness, rather than hemodynamics.
Optimal parametric controller for perturbed balance and walking

We present full state feedback controllers for standing and walking balance of humanoid robot. The robot is simulated as a two-joint inverted pendulum for standing and a five-link model for walking, and is disturbed by a horizontal push with given size and location in the sagittal plane. We optimize the parametric controllers for different push sizes, locations, and directions. For standing balance, both impulsive and constant pushes are applied to simulate the hip strategy; for bipedal walking, instantaneous pushes are used as perturbations. The performance of optimized controllers are shown in handling different pushes for standing and walking balance.
Dual-Hormone Changes Are Related to Bargaining Performance

In the present research, we found that endogenous testosterone and cortisol changes were jointly related to bargaining outcomes. In a face-to-face competitive negotiation (Study 1) and a laboratory-based bargaining game (Study 2), testosterone rises were associated with high earnings and high relationship quality, but only if cortisol dropped. If cortisol rose, testosterone rises were associated with low earnings and poor relationship quality. Conflict between financial and social goals was related to the financially costly dual-hormone profile (testosterone increase and cortisol increase), whereas the absence of such conflict was related to the financially adaptive dual-hormone profile (testosterone increase and cortisol decrease). The findings suggest that when cortisol decreases, rising testosterone is implicated in adaptive bargaining behavior that maximizes earnings and relationship quality. But when cortisol increases, rising testosterone is related to conflict between social and financial motives, weak earnings, and poor relationship quality. These results imply that there are both bright and dark sides to rising testosterone in economic social interactions that depend on fluctuations in cortisol.
Hopf bifurcation and Chaos in Tabu Learning Neuron Models

In this paper, we consider the nonlinear dynamical behaviors of some tabu learning neuron models. We first consider a tabu learning single neuron model. By choosing the memory decay rate as a bifurcation parameter, we prove that Hopf bifurcation occurs in the neuron. The stability of the bifurcating periodic solutions and the direction of the Hopf bifurcation are determined by applying the normal form theory. We give a numerical example to verify the theoretical analysis. Then, we demonstrate the chaotic behavior in such a neuron with sinusoidal external input, via computer simulations. Finally, we study the chaotic behaviors in tabu learning two-neuron models, with linear and quadratic proximity functions respectively.
Supersonic turbulence in the cold massive core JCMT 18354−0649S★

An example of a cold massive core, JCMT 18354−0649S which is a possible high-mass analogue to a low-mass star-forming core, is studied. Line and continuum observations from James Clerk Maxwell Telescope, Mopra Telescope and Spitzer are presented and modelled in detail using a 3D molecular line radiative transfer code. In almost every way, JCMT 18354−0649S is a scaled-up version of a typical low-mass core with similar temperatures, chemical abundances and densities. The difference is that both the infall velocity and the turbulent width of the line profiles are an order of magnitude larger. While the higher infall velocity is expected due to the large mass of JCMT 18354−0649S, we suggest that the dissipation of this highly supersonic turbulence may lead to the creation of dense clumps of gas that surround the high-mass core.
Developing assessment instrument of qirāatul kutub at islamic boarding school

The purpose of this study was to develop and describe the quality and characteristics of an assessment instrument of by name of Qirāatul Kutub. This development research is based on Borg & Gall model. The steps of the development were (1) planning, (2) primary developing product, (3) preliminary field testing, (4) main field testing, and (5) final product revision. The subjects for preliminary field testing were 28 testees for performance test instrument and 96 testees for grammar mastery test derived from students of Darul Huda Islamic Boarding School, whereas the subjects for main field testing were 80 students for performance test instrument and 425 students for grammar mastery test. The research instruments were assessment instrument of Qirāatul Kutub which consisted of performance assessment instrument and grammar mastery essay test, observation and interview guide. The research data were analyzed based on Rasch Model. The results showed that: (1) the results of the development were 12 items of the performance test and 17 items of the grammar mastery test which were fit with the proposed model, (2) the item difficulty of the performance test ranged from -1.32 to 0.99, while for the grammar mastery test from -1.13 to 1.01; (3) the person reliability for the performance test was 0.86, item reliability was 0.97, and Cronbach’s alpha value was 0.97. The grammar mastery test has person reliability 0.97 and item reliability 0.99 with Cronbach’s alpha 0.90; (4) based on the test information function (TIF) and Standard Error of Measurement (SEM), the instruments were found to be good; the performance test and the grammar mastery test were suitable for learners with ability masteries between -4 and 4.
Personalized recommendation algorithm based on semantic clustering

The traditional clustering algorithm doesn't consider semantic in user session, so it cannot provide exact recommendation to users. In order to improve the recommendation quality, the thesis expresses user sessions as preferences of Web pages, then change it to semantic preferences based on domain ontology, computes semantic similarity between user sessions. Use this as a foundation, a personalized recommendation algorithm based on semantic clustering is improved, the algorithm initially clusters users with K-Nearest Neighbors of hierarchical agglomerative clustering algorithms, gets initial clustering center and the value of k, then adopts K-Means algorithm iterative refinement for clustering analysis. Experimental results show that: the improved algorithm can capture changes in user interests in time and the accuracy is better than traditional personalized recommendation algorithms.
Spectrum Sensing in multipath fading channels using Cosine Modulated Filter Bank for Cognitive Radio applications

In this paper, an elegant scheme for Spectrum Sensing (SS) in fading channels with Cosine Modulated Filter Banks (CMFBs) and energy detection method is proposed. Filter Bank Spectral estimators (FBSEs) are used as it allows sensing multiple subbands simultaneously. In fading channel conditions, the received signal also impaired with AWGN noise is equalized at the receiver and then sensed through Cosine modulated Spectral estimators. The energy detection is performed at the subband outputs of the CMFB. Spectral holes can be detected with high confidence due to spectral containment of cosine modulation in subband sensing. This method provides the flexibility to detect active signals in a fading environment. Simulations are done with Zero Forcing Equalizer (ZFE) and Minimum Mean Square Error (MMSE) equalizers and the results are compared.
Image retrieval based on spatial context with Relaxed Gabriel Graph pyramid

Imposing the coherence of the spatial context on local features is becoming a necessity for object retrieval and recognition. Motivated by the success of proximity graphs in topological decomposition, clustering, and gradient estimation, we introduce a variation on and a generalization of Delaunay Triangulation, called a Relaxed Gabriel Graph (RGG), as the apex of spatial neighborhood association and design a Centrality-Sensitive Pyramid (CSP) model for hierarchical spatial context modeling. RGG is parameterized, and so allows the tuning of various applications and datasets. CSP achieves better neighborhood association and is more robust as regards feature description error than other related work. Our method is evaluated on Flickr Logos 32, Holiday, and Oxford Buildings benchmarks. Experimental results and comparisons demonstrate the superiority of our method in an image retrieval scenario.
Culture Models for Studying Thyroid Biology and Disorders

The thyroid is composed of thyroid follicles supported by extracellular matrix, capillary network, and stromal cell types such as fibroblasts. The follicles consist of thyrocytes and C cells. In this microenvironment, thyrocytes are highly integrated in their specific structural and functional polarization, but monolayer and floating cultures cannot allow thyrocytes to organize the follicles with such polarity. In contrast, three-dimensional (3-D) collagen gel culture enables thyrocytes to form 3-D follicles with normal polarity. However, these systems never reconstruct the follicles consisting of both thyrocytes and C cells. Thyroid tissue-organotypic culture retains 3-D follicles with both thyrocytes and C cells. To create more appropriate experimental models, we here characterize four culture systems above and then introduce the models for studying thyroid biology and disorders. Finally, we propose a new approach to the cell type-specific culture systems on the basis of in vivo microenvironments of various cell types.
Strathprints Institutional Repository

The advance of remote sensing technology has been capable of providing abundant spatial and contextual information for object detection in optical satellite or aerial imagery, which facilitates subsequent automatic analysis and interpretation of the optical remotes sensing images (RSIs). Most existing object detection approaches suffer from two limitations. First, the feature representation used is insufficiently powerful to capture the spatial and structural patterns of objects and the background regions. Second, a large number of training data with manual annotation of object bounding boxes is required in the supervised learning techniques adopted while the annotation process is generally too expensive and sometimes even unreliable. To tackle these two limitations, a novel and effective geospatial object detection framework is proposed by combining the weakly supervised learning (WSL) and high-level feature learning. First, we employ an unsupervised feature learning approach via Deep Boltzmann Machine (DBM) to infer the spatial and structural information encoded in the low-level and middle-level features, which facilitates good semantic preserving ability for effective describing objects in optical RSIs. Then, we present a novel WSL approach to object detection in optical RSIs where the training sets require only binary labels indicating whether an image contains the target object or not. Based on the learnt high-level features, it jointly integrates saliency, intra-class compactness, and inter-class separability in a Bayesian framework to initialize a set of training examples from weakly labeled images and start iterative learning of the object detector. A novel evaluation criterion is also developed to detect model drift and cease the iterative learning. Comprehensive experiments on three optical RSI datasets with large variations in terms of spatial resolution, and types of objects have demonstrated the efficacy of the proposed approach in benchmarking with several state-of-the-art supervised learning based object detection approaches.
Role of Broca's area in encoding sequential human actions: a virtual lesion study

The exact contribution of Broca's area to motor cognition is still controversial. Here we used repetitive transcranial magnetic stimulation (5 Hz, five pulses) to interfere transiently with the function of left BA44 in 13 healthy individuals; the task consisted of reordering human actions or nonbiological events based on three pictures presented on a computer screen and extracted from a video showing the entire sequence beforehand. We found that a virtual lesion of left BA44 impairs individual performance only for biological actions, and more specifically for object-oriented syntactic actions. Our finding provides evidence that Broca's area plays a crucial role in encoding complex human movements, a process which may be crucial for understanding and/or programming actions.
Efficient metric indexing for similarity search

The goal in similarity search is to find objects similar to a specified query object given a certain similarity criterion. Although useful in many areas, such as multimedia retrieval, pattern recognition, and computational biology, to name but a few, similarity search is not yet supported well by commercial DBMS. This may be due to the complex data types involved and the needs for flexible similarity criteria seen in real applications. We propose an efficient disk-based metric access method, the Space-filling curve and Pivot-based B+-tree (SPB-tree), to support a wide range of data types and similarity metrics. The SPB-tree uses a small set of so-called pivots to reduce significantly the number of distance computations, uses a space-filling curve to cluster the data into compact regions, thus improving storage efficiency, and utilizes a B+-tree with minimum bounding box information as the underlying index. The SPB-tree also employs a separate random access file to efficiently manage a large and complex data. By design, it is easy to integrate the SPB-tree into an existing DBMS. We present efficient similarity search algorithms and corresponding cost models based on the SPB-tree. Extensive experiments using real and synthetic data show that the SPB-tree has much lower construction cost, smaller storage size, and can support more efficient similarity queries with high accuracy cost models than is the case for competing techniques. Moreover, the SPB-tree scales sublinearly with growing dataset size.
Adaptive bandwidth DLLs and PLLs using regulated supply CMOS buffers

A technique for designing DLLs and PLLs using CMOS buffers with a regulated supply is presented. By scaling the charge pump current and the output resistance of the regulating amplifier, the proposed loops achieve a wide bandwidth that tracks the operating frequency, a constant damping factor, large operating range and low noise sensitivity. Prototype loops designed in 0.35-/spl mu/m CMOS processes exhibit >10x operating range and less than 1% input tracking jitter.