Miracle-dz/UniFAR-FTUs huggingface dataset:
Geo-spatial analysis of activity spaces in a TOD environment – Tracking impacts of rail transport policy using kernel density estimation

Activity spaces are dynamic, 'people-based' accessibility measures that can be used to analyse spatial arrangements of travel. This paper reports on activity spaces in the context of transport policy aimed at changing travel behaviour by offering alternative transport options and new urban services within transit-oriented developments (TOD) environments. Specifically, we explore associations between TOD and activity spaces to derive visually easily comprehensible indicators, assisting practitioners and policy makers in determining decision-making effectiveness. We analyse results from household travel diaries collected within three unique TOD precincts in Perth, Western Australia situated alongside a 72 km new metro-rail link, pre- and post-opening, to identify impacts of the major transport intervention on travel. While activity spaces have increasingly been applied as metrics for assessing the extent of urban space used by households for satisfying their daily activity needs, their application to explore potential changes in built environment induced travel behaviour is a novel feature of this research. We employ herein kernel density estimation, which has great flexibility and superior visualisation capabilities in representing activity spaces, to longitudinally track travel behaviour changes. We also expand on previous investigation that considered discrete origin-destination trip data, by applying kernel density estimation to data including generated route information. Our findings suggest benefits of activity space analysis in investigating past transport infrastructure decisions and associated implications, promising a potential improvement for development of new policies and strategies in the transport sector.
The rules of the game : international money and exchange rates

Generalized financial volatility is capitalism's Achilles' heel. And nowhere is the problem of controlling such volatility more acute than in monetary and exchange-rate relationships across countries - the central theme of this book. The Rules of the Game brings together essays, written over the course of thirty years, by a major figure in the field that analyze and compare a wide variety of important international monetary regimes. These range from the establishment of the gold standard in the nineteenth century through Bretton Woods, the dollar standard, floating exchange rates, the European Monetary System, to current proposals for reforming world monetary arrangements. The essays are unique in that they specify precisely the rules of the game for each international monetary regime - past, present, and future. For ease of reference, the book offers boxed summaries of each set of rules and then discusses their advantages and disadvantages from the gold standard down to the author's proposal for a common monetary standard for the twenty-first century. Part I assesses each monetary regime's success in stabilizing prices and exchange rates, while fostering international trade. Part II addresses a central question each country faces: what are the benefits of giving up exchange-rate flexibility to join a common monetary standard? Part III focuses on overall monetary reform for limiting financial volatility and exchange-rate crises in the next century - including whether or not Western Europe should adopt a common currency. The last chapter synthesizes and updates the author's previous writings on rationalizing monetary arrangements among the major industrial countries of North America, Western Europe, and East Asia.
General Education and Special Education Teachers' Beliefs and Perceptions of Skills for Response to Intervention (RTI).

Changes in the No Child Left Behind (NCLB) law and the Individuals with Disabilities Education Act (IDEA) have opened a door to a new outlook on educational services in both general education and special education. Response to Intervention (RTI) is an answer to the changes prescribed in that legislation. RTI is a promising framework for education reform that focuses on tier instructions and prevention of academic failure. The reform will also affect, for example, the way Learning Disabilities are identified, teachers responsibilities and roles in instructional services for students in general education and the melding of special education and general education resources in the provision of instruction at the universal level. However, the decision to implement RTI, like other education reforms, often comes from the top. Teachers’ voices — their opinions — whether they want the reform or are ready for the changes — are rarely heard. This study aims to understand teachers’ own perceptions of their skills related to implementing RTI and their beliefs about the potential efficacy of the RTI framework. The finding suggested that training may be the leading factor to foster teachers’ belief in the RTI framework and their confidence to implement the change. Chapter
A Simple Model for A Generic Class of P2P Streaming Algorithms

P2P streaming tries to achieve scalability (like P2P file distribution) and at the same time meet real-time playback requirements. It is a challenging problem still not well understood. In this paper, we describe a simple stochastic model that can be used to compare different downloading strategies with random peer selection.Based on this model, we study the tradeoffs between supported peer population, buffer size and playback continuity. We first study two simple strategies: Rarest First and Greedy. The former is a well-known strategy for P2P file sharing that gives good scalability by trying to propagate the chunks of a file to as many peers as quickly as possible. The latter is an intuitively reasonable strategy to get urgent chunks first to maximize playback continuity from a peer’s local perspective. Yet in reality, both scalability and urgency should be taken care of. With this insight, we propose a Mixed strategy that achieves the best of both worlds. Furthermore, the Mixed Strategy comes with an adaptive algorithm that can adapt it buffer setting to dynamic peer population. We validate our analytical model with simulation. Finally, we also discuss the modeling assumptions and the model’s sensitivity to different parameters, and show that our model is robust.
Sentiment analysis at sentence level for heterogeneous datasets

Sentiment analysis is a process used to automatically extract useful information from a collection of unstructured documents, in the form of customer reviews, blog comments or online social network sites data respectively. This useful information plays a significant role for decision making to know people's sentiments regarding online product reviews, services, events, entities. In this paper, rules based supervised machine learning method is proposed for sentiment analysis at sentence level for heterogeneous datasets. The text document in heterogeneous datasets is divided into two classes i.e., subjective and objective. We determine the semantic orientation and strength of subjective sentences based on the semantic score of its sentiment bearing words through SentiWordnet. Our experiment results show that the proposed method improves the performance of existing work for sentiment analysis in term of accuracy.
A Domain Independent Explanation-Based Generalizer

A domain independent technique for generalizing a broad class of explanations is described. This method is compared and contrasted with other approaches to generalizing explanations, including an abstract version of the algorithm used in the STRIPS system and the EBG technique recently developed by Mitchell, Keller, and Kedar-Cabelli. We have tested this generalization technique on a number examples in different domains, and present detailed descriptions of several of these.
Bioavailability of all-trans and cis–Isomers of Lycopene

Lycopene, the predominant carotenoid in tomatoes, is among the major carotenoids in serum and tissues of Americans. Although about 90% of the lycopene in dietary sources is found in the linear, all-trans conformation, human tissues contain mainly cis-isomers. Several research groups have suggested that cis-lsomers of lycopene are better absorbed than the all-trans form because of the shorter length of the cis-isomer, the greater solubility of cis-isomers in mixed micelles, and/or as a result of the lower tendency of cis-isomers to aggregate. Work with ferrets, a species that absorbs carotenoids intact, has demonstrated that whereas a lycopene dose, stomach, and Intestinal contents contained 6–18% cis-lycopene, the mesenteric lymph secretions contained 77%-cis isomers. The ferret studies support the hypotheses that cis-isomers are substantially more bioavailable then all-trans lycopene. In vitro studies suggest that cis-isomers are more soluble in bile acid micelles and may be preferentially incorporated into chylomicrons. The implications of these findings are not yet clear. Rats appear to accumulate lycopene in tissues within the ranges reported for humans, suggesting that they can be used to study effects of lycopene isomers on disease processes. Investigations are underway to determine whether there are biological differences between all-trans and various cis-isomers of lycopene regarding its antioxidant properties or other biological functions.
Projecting semantic roles via Tai mappings

This work takes the paradigm of projecting annotations within labelled data into unlabelled data, via a mapping, and applies it to Semantic Role Labelling. The projections are amongst dependency trees and the mappings are the Tai-mappings that underlie the well known tree edit-distance algorithm. The system was evaluated in seven different languages. A number of variants are explored relating to the amount of information attended to in aligning nodes, whether the scoring is distance-based or similarity-based , and the relative ease with which nodes can be ignored. We find that all of these have statistically significant impacts on the outcomes, mostly in language independent ways, but sometimes language dependently.
An improved genetic algorithm for generation expansion planning

This paper presents a development of an improved genetic algorithm (IGA) and its application to a least-cost generation expansion planning (GEP) problem. Least-cost GEP problem is concerned with a highly constrained nonlinear dynamic optimization problem that can only be fully solved by complete enumeration, a process which is computationally impossible in a real-world GEP problem. In this paper, an improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. The main advantage of the IGA approach is that the "curse of dimensionality" and a local optimal trap inherent in mathematical programming methods can be simultaneously overcome. The IGA approach is applied to two test systems, one with 15 existing power plants, 5 types of candidate plants and a 14-year planning period, and the other, a practical long-term system with a 24-year planning period.
Hospital Variation in Missed Nursing Care

Quality of nursing care across hospitals is variable, and this variation can result in poor patient outcomes. One aspect of quality nursing care is the amount of necessary care that is omitted. This article reports on the extent and type of nursing care missed and the reasons for missed care. The MISSCARE Survey was administered to nursing staff (n = 4086) who provide direct patient care in 10 acute care hospitals. Missed nursing care patterns as well as reasons for missing care (labor resources, material resources, and communication) were common across all hospitals. Job title (ie, registered nurse vs nursing assistant), shift worked, absenteeism, perceived staffing adequacy, and patient work loads were significantly associated with missed care. The data from this study can inform quality improvement efforts to reduce missed nursing care and promote favorable patient outcomes.
Information Theory : New Challenges and New Interdisciplinary Tools Prepared

Information Theory (IT) is concerned with identifying, characterization and computation of basic limits of performance measures of communication systems. The classical question that it seeks to answer is what are the information rates in the multi-user setting that can be transmitted reliably over a given noisy channel. The transmission may involve various transmitter and various receivers. Rendering transmission over noisy channels reliable involves coding of the information to be transmitted. A given transmission rate vector C is said to be reliable if for any rate C ′ < C and every > 0 there exists a code that allows transmission at the rate C ′ with error rates smaller than . The set of reliable transmission rates C are called the capacity region. In this proposal we seek to create cooperation between specialists on classical information theory (IT) and other disciplines that are needed for the computations of new concepts of capacity that appear in the next generation networks in which the geometric aspects, mobility, power restriction play a key role on the capacity and connectivity. In view of the wealth of mathematical tools that are needed to study networks (and in particular SNs), we present a proposal for an inter-disciplinary research for networking dimensioning and design.
The association between childhood maltreatment, psychopathology, and adult sexual victimization in men and women: results from three independent samples

Background Childhood maltreatment (CM) has consistently been linked with adverse outcomes including substance use disorders and adult sexual revictimization. Adult sexual victimization itself has been linked with psychopathology but has predominately been studied in women. The current investigation examines the impact of CM and co-occurring psychopathology on adult sexual victimization in men and women, replicating findings in three distinct samples. Method We investigated the association between continuous CM factor scores and adult sexual victimization in the Childhood Trauma Study (CTS) sample (N = 2564). We also examined the unique relationship between childhood sexual abuse (CSA) and adult sexual victimization while adjusting for co-occurring substance dependence and psychopathology. We replicated these analyses in two additional samples: the Comorbidity and Trauma Study (CATS; N = 1981) and the Australian Twin-Family Study of Alcohol Use Disorders (OZ-ALC; N = 1537). Results Analyses revealed a significant association with CM factor scores and adult sexual victimization for both men and women across all three samples. The CSA factor score was strongly associated with adult sexual victimization after adjusting for substance dependence and psychopathology; higher odds ratios were observed in men (than women) consistently across the three samples. Conclusions A continuous measure of CSA is independently associated with adult sexual trauma risk across samples in models that included commonly associated substance dependence and psychopathology as covariates. The strength of the association between this CSA measure and adult sexual victimization is higher in magnitude for men than women, pointing to the need for further investigation of sexual victimization in male community samples.
Maltose-Binding Protein Enhances Secretion of Recombinant Human Granzyme B Accompanied by In Vivo Processing of a Precursor MBP Fusion Protein

Background The apoptosis-inducing serine protease granzyme B (GrB) is an important factor contributing to lysis of target cells by cytotoxic lymphocytes. Expression of enzymatically active GrB in recombinant form is a prerequisite for functional analysis and application of GrB for therapeutic purposes. Methods and Findings We investigated the influence of bacterial maltose-binding protein (MBP) fused to GrB via a synthetic furin recognition motif on the expression of the MBP fusion protein also containing an N-terminal α-factor signal peptide in the yeast Pichia pastoris. MBP markedly enhanced the amount of GrB secreted into culture supernatant, which was not the case when GrB was fused to GST. MBP-GrB fusion protein was cleaved during secretion by an endogenous furin-like proteolytic activity in vivo, liberating enzymatically active GrB without the need of subsequent in vitro processing. Similar results were obtained upon expression of a recombinant fragment of the ErbB2/HER2 receptor protein or GST as MBP fusions. Conclusions Our results demonstrate that combination of MBP as a solubility enhancer with specific in vivo cleavage augments secretion of processed and functionally active proteins from yeast. This strategy may be generally applicable to improve folding and increase yields of recombinant proteins.
Beyond the ballot: 57 democratic innovations from around the world

The aim of this study is to provide The Power Inquiry - an independent inquiry into Britain's democracy - with details and assessments of democratic innovations that might increase and deepen citizen participation in the political decision-making process. The study analyses fifty-seven different innovations – eleven of these are considered in more depth in case studies. The innovations are assessed according to the following criteria: selection mechanism, form of involvement, role in decision-making, scale and transferability, and resource implications. The innovations are categorised, described and assessed under the six headings:electoral innovations, consultation innovations, deliberation innovations, co-governance innovations, direct democracy innovations and e-governance innovations.
Depression and Fear among Muslim Families in Southern California A Post September 11 , 2001 Analysis

The authors of this article aim to raise cultural awareness and cultural sensitivity to marriage and family therapists by providing knowledge gained from a study of the impact of September 11, 2001, on Muslim families in Southern California. The authors will look at the depression and fear as related to such factors as culture, religion, ethnicity, and gender. Findings reflect the Muslim people experience varying levels of depression and fear when faced with traumatic events, such as the horrific events of September 11, 2001. The data in this study were collected and multiple regression statistical analysis were used to examine the significance or the extent to which factors contributed to imbalances in mental well being of Muslim families in Southern California. Findings may be helpful to marriage and family therapists when treating Muslim families. SIME journal MAJALLA.org
From wires to Partners: How the Internet has Fostered R&d Collaborations among Firms

This paper studies how IT investments shape the geography of firm innovation. We focus on the role of investments by US firms in basic internet technology on the organization of innovation. We combine establishment-level IT investment data with data on US patenting activity at the MSA level. Our difference-in-difference econometric estimation approach compares the citationweighted count of co-invented patents among two firm locations before basic Internet technology diffused (i.e., 1992) to the count of patents after its diffusion (i.e., 1998). Our results show that when two firm locations adopt Internet technology, the number of cross-location collaborative patents between them increases compared to an otherwise identical pair without Internet technology. We further find that the link between Internet adoption and cross-location patenting is greatest for firm pairs that have previously been successful innovators, have not collaborated before, and which have different research foci.
Binary coding of speech spectrograms using a deep auto-encoder

This paper reports our recent exploration of the layer-by-layer learning strategy for training a multi-layer generative model of patches of speech spectrograms. The top layer of the generative model learns binary codes that can be used for efficient compression of speech and could also be used for scalable speech recognition or rapid speech content retrieval. Each layer of the generative model is fully connected to the layer below and the weights on these connections are pretrained efficiently by using the contrastive divergence approximation to the log likelihood gradient. After layer-bylayer pre-training we “unroll” the generative model to form a deep auto-encoder, whose parameters are then fine-tuned using back-propagation. To reconstruct the full-length speech spectrogram, individual spectrogram segments predicted by their respective binary codes are combined using an overlapand-add method. Experimental results on speech spectrogram coding demonstrate that the binary codes produce a logspectral distortion that is approximately 2 dB lower than a subband vector quantization technique over the entire frequency range of wide-band speech. Index Terms: deep learning, speech feature extraction, neural networks, auto-encoder, binary codes, Boltzmann machine
The Impact of Upstream Catch and Global Warming on the Grey Mullet Fishery in Taiwan: A Non-cooperative Game Analysis

This paper examines the problem of non-cooperative fishing between Mainland China (MC) and Taiwan (TW) as well as the effects of rising sea surface temperature (SST) on the grey mullet fishery. The results show that Taiwan can expand its fleets to a greater extent when facing an imperfectly elastic demand for fish than when facing a perfectly elastic demand. In addition, when consumer welfare is included in the determination of the size of fleets, fleet size can expand more than when profit is considered alone. It is also shown that the expansion of the fleets in MC and the rising SST cause the rent obtained from the TW fishery to decline, and that Taiwan may partially offset such an adverse effect by adjusting the fleet size.
Effects of ω-3 fatty acids on toll-like receptor 4 and nuclear factor-κB p56 in lungs of rats with severe acute pancreatitis

AIM To determine the effects of ω-3 fatty acids (ω-3FA) on the toll-like receptor 4 (TLR4)/nuclear factor κB p56 (NF-κBp56) signal pathway in the lungs of rats with severe acute pancreatitis (SAP). METHODS A total of 56 Sprague-Dawley rats were randomly divided into 4 groups: control group, SAP-saline group, SAP-soybean oil group and SAP-ω-3FA group. SAP was induced by the retrograde infusion of sodium taurocholate into the pancreatic duct. The expression of TLR4 and NF-κBp56 in the lungs was evaluated by immunohistochemistry and Western blot analysis. The levels of inflammatory cytokines interleukin-6 and tumor necrosis factor-alpha in the lungs were measured by enzyme-linked immunosorbent assay. RESULTS The expression of TLR4 and NF-κBp56 in lungs and of inflammatory cytokines in serum significantly increased in the SAP group compared with the control group (P < 0.05), but was significantly decreased in the ω-3FA group compared with the soybean oil group at 12 and 24 h (P < 0.05). CONCLUSION During the initial stage of SAP, ω-3FA can efficiently lower the inflammatory response and reduce lung injury by triggering the TLR4/NF-κBp56 signal pathway.