Miracle-dz/UniFAR-FTUs huggingface dataset:
Eleven years of scholarly research in the Journal of Services Marketing

Purpose – The publication of papers in scholarly journals is an important channel for the dissemination of academic knowledge. Analyzing academic content provides useful insights into how services marketing evolves over a selected time frame. The purpose of this paper is to determine key trends published in the Journal of Services Marketing during the recent 11‐year period from 1998 to 2008.Design/methodology/approach – This paper presents a content analysis of the papers published in the Journal of Services Marketing during the period 1998‐2008. A total of 417 papers, excluding book reviews, were analyzed. Descriptive statistics provide an overview of the research contributions.Findings – The main finding is that most of the papers published in the Journal of Services Marketing during the recent 11‐year period are research‐based papers. Other findings include a trend towards co‐authorship, the use of surveys and empirical data, adults as research subjects, factor analysis, structural equation modeling, a.
Index structures for efficiently searching natural language text

Many existing indexes on text work at the document granularity and are not effective in answering the class of queries where the desired answer is only a term or a phrase. In this paper, we study some of the index structures that are capable of answering the class of queries referred to here as wild card queries and perform an analysis of their performance. Our experimental results on a large class of queries from different sources (including query logs and parse trees) and with various datasets reveal some of the performance barriers of these indexes. We then present Word Permuterm Index (WPI) which is an adaptation of the permuterm index for natural language text applications and show that this index supports a wide range of wild card queries, is quick to construct and is highly scalable. Our experimental resultS comparing WPI to alternative methods on a wide range oF wild card queries show a few orders of magnitude performancE improvements for WPI while the memory usage is kept the same for all compared systems.
Inducing Tree-Substitution Grammars

Inducing a grammar from text has proven to be a notoriously challenging learning task despite decades of research. The primary reason for its difficulty is that in order to induce plausible grammars, the underlying model must be capable of representing the intricacies of language while also ensuring that it can be readily learned from data. The majority of existing work on grammar induction has favoured model simplicity (and thus learnability) over representational capacity by using context free grammars and first order dependency grammars, which are not sufficiently expressive to model many common linguistic constructions. We propose a novel compromise by inferring a probabilistic tree substitution grammar, a formalism which allows for arbitrarily large tree fragments and thereby better represent complex linguistic structures. To limit the model's complexity we employ a Bayesian non-parametric prior which biases the model towards a sparse grammar with shallow productions. We demonstrate the model's efficacy on supervised phrase-structure parsing, where we induce a latent segmentation of the training treebank, and on unsupervised dependency grammar induction. In both cases the model uncovers interesting latent linguistic structures while producing competitive results.
Efficient provenance storage

As the world is increasingly networked and digitized, the data we store has more and more frequently been chopped, baked, diced and stewed. In consequence, there is an increasing need to store and manage provenance for each data item stored in a database, describing exactly where it came from, and what manipulations have been applied to it. Storage of the complete provenance of each data item can become prohibitively expensive. In this paper, we identify important properties of provenance that can be used to considerably reduce the amount of storage required. We identify three different techniques: a family of factorization processes and two methods based on inheritance, to decrease the amount of storage required for provenance. We have used the techniques described in this work to significantly reduce the provenance storage costs associated with constructing MiMI [22], a warehouse of data regarding protein interactions, as well as two provenance stores, Karma [31] and PReServ [20], produced through workflow execution. In these real provenance sets, we were able to reduce the size of the provenance by up to a factor of 20. Additionally, we show that this reduced store can be queried efficiently and further that incremental changes can be made inexpensively.
Selective Sampling with Drift

Recently there has been much work on selective sampling, an online active learning setting, in which algorithms work in rounds. On each round an algorithm receives an input and makes a prediction. Then, it can decide whether to query a label, and if so to update its model, otherwise the input is discarded. Most of this work is focused on the stationary case, where it is assumed that there is a fixed target model, and the performance of the algorithm is compared to a fixed model. However, in many real-world applications, such as spam prediction, the best target function may drift over time, or have shifts from time to time. We develop a novel selective sampling algorithm for the drifting setting, analyze it under no assumptions on the mechanism generating the sequence of instances, and derive new mistake bounds that depend on the amount of drift in the problem. Simulations on synthetic and real-world datasets demonstrate the superiority of our algorithms as a selective sampling algorithm in the drifting setting.
The Social Uses of Personal Photography : Methods for Projecting Future Imaging Applications

An important problem for technology design is predicting users and uses for emerging technologies—doing usercentered design for users and uses that don't yet exist. The primary contribution of this paper is in presenting a method for anticipating future uses of new technology by looking at users’ higher-order motives or activities for current and emerging technology. We identify three high-order motives or “social uses” for personal photos: constructing personal and group memory; creating and maintaining social relationships; and self-expression and self-presentation . We then articulate design implications for digital imaging technology with an emphasis on networked programmable mobile imaging devices, especially cameraphones.
Inferring MicroRNA Regulation of mRNA with Partially Ordered Samples of Paired Expression Data and Exogenous Prediction Algorithms

MicroRNAs (miRs) are known to play an important role in mRNA regulation, often by binding to complementary sequences in “target” mRNAs. Recently, several methods have been developed by which existing sequence-based target predictions can be combined with miR and mRNA expression data to infer true miR-mRNA targeting relationships. It has been shown that the combination of these two approaches gives more reliable results than either by itself. While a few such algorithms give excellent results, none fully addresses expression data sets with a natural ordering of the samples. If the samples in an experiment can be ordered or partially ordered by their expected similarity to one another, such as for time-series or studies of development processes, stages, or types, (e.g. cell type, disease, growth, aging), there are unique opportunities to infer miR-mRNA interactions that may be specific to the underlying processes, and existing methods do not exploit this. We propose an algorithm which specifically addresses [partially] ordered expression data and takes advantage of sample similarities based on the ordering structure. This is done within a Bayesian framework which specifies posterior distributions and therefore statistical significance for each model parameter and latent variable. We apply our model to a previously published expression data set of paired miR and mRNA arrays in five partially ordered conditions, with biological replicates, related to multiple myeloma, and we show how considering potential orderings can improve the inference of miR-mRNA interactions, as measured by existing knowledge about the involved transcripts.
Micro fl uidically Switched Frequency-Recon fi gurable Slot Antennas

This letter proposes a concept for frequency-reconfigurable slot antennas enabled by pressure-driven capacitive microfluidic switches. The switches are operated by pneumatically displacing a plug of eutectic gallium indium alloy (EGaIn) within an air-filledmicrochannel that traverses the slot orthogonally. Frequency reconfigurability is achieved by altering the displacement of conductive fluid within the channel, which reactively loads the slot. A transmission-line model is developed to capture the physical behavior of the fluid channel, and measurements are provided that show good agreement with the behavior of the model.
Coupling aware routing

In this paper, we develop methods to reduce interconnect delay and noise caused by coupling. First, we introduce two novel problems that deal with coupling-the Coupling-Free Routing (CFR) Problem and the Maximum Coupling-Free Layout (MAX-CFL) Problem. We argue that these problems are useful in both global and detailed routing. Then, we develop algorithms to efficiently solve the problems. Our experimental results show that the algorithms work effectively on real data.
What Is Where: Inferring Containment Relations from Videos

In this paper, we present a probabilistic approach to explicitly infer containment relations between objects in 3D scenes. Given an input RGB-D video, our algorithm quantizes the perceptual space of a 3D scene by reasoning about containment relations over time. At each frame, we represent the containment relations in space by a containment graph, where each vertex represents an object and each edge represents a containment relation. We assume that human actions are the only cause that leads to containment relation changes over time, and classify human actions into four types of events: move-in, move-out, no-change and paranormal-change. Here, paranomal-change refers to the events that are physically infeasible, and thus are ruled out through reasoning. A dynamic programming algorithm is adopted to finding both the optimal sequence of containment relations across the video, and the containment relation changes between adjacent frames. We evaluate the proposed method on our dataset with 1326 video clips taken in 9 indoor scenes, including some challenging cases, such as heavy occlusions and diverse changes of containment relations. The experimental results demonstrate good performance on the dataset.
Classification method into determinable and indeterminable areas using SVM and learning data selection

In this paper, a methodology that combines a classification algorithm with a combinatorial optimization problem is proposed. Using the proposed algorithm, classification problems of medical data such as breast cancer data can be performed more accurately. Using the conventional method, the breast cancer data is classified into malignant growth and benign tumor. However, the conventional classification seems insufficient, because there are erroneous cases sometimes, such as the data, having classified into benign, would be found out as malignant, later. To conquer the defect, the proposed method classify the breast cancer data into two groups; (1) the data which definitely belongs to malignant growth area, and (2) the data which has the possibility to belong to either malignant growth area or benign tumor area. Since the libraries of two value classification learning method, used in the conventional method, are highly evaluated in their performance and their easiness of use, the proposed method uses two value classification learning method as well, to achieve the goal. This problem is formulated as combinatorial optimization problem. In this formulation, the malignant growth area is maximized, because of the data which has the possibility to belong to either malignant or benign. The classification algorithm based on learning data selection is proposed, and the effectiveness of the proposed algorithm is discussed through the numerical experiments.
Fat Emulsion Intragastric Stability and Droplet Size Modulate Gastrointestinal Responses and Subsequent Food Intake in Young Adults1234

Background: Intragastric creaming and droplet size of fat emulsions may affect intragastric behavior and gastrointestinal and satiety responses. Objectives: We tested the hypotheses that gastrointestinal physiologic responses and satiety will be increased by an increase in intragastric stability and by a decrease in fat droplet size of a fat emulsion. Methods: This was a double-blind, randomized crossover study in 11 healthy persons [8 men and 3 women, aged 24 ± 1 y; body mass index (in kg/m2): 24.4 ± 0.9] who consumed meals containing 300-g 20% oil and water emulsion (2220 kJ) with 1) larger, 6-μm mean droplet size (Coarse treatment) expected to cream in the stomach; 2) larger, 6-μm mean droplet size with 0.5% locust bean gum (LBG; Coarse+LBG treatment) to prevent creaming; or 3) smaller, 0.4-μm mean droplet size with LBG (Fine+LBG treatment). The participants were imaged hourly by using MRI and food intake was assessed by using a meal that participants consumed ad libitum. Results: The Coarse+LBG treatment (preventing creaming in the stomach) slowed gastric emptying, resulting in 12% higher gastric volume over time (P < 0.001), increased small bowel water content (SBWC) by 11% (P < 0.01), slowed appearance of the 13C label in the breath by 17% (P < 0.01), and reduced food intake by 9% (P < 0.05) compared with the Coarse treatment. The Fine+LBG treatment (smaller droplet size) slowed gastric emptying, resulting in 18% higher gastric volume (P < 0.001), increased SBWC content by 15% (P < 0.01), and significantly reduced food intake by 11% (P < 0.05, equivalent to an average of 411 kJ less energy consumed) compared with the Coarse+LBG treatment. These high-fat meals stimulated substantial increases in SBWC, which increased to a peak at 4 h at 568 mL (range: 150–854 mL; P < 0.01) for the Fine+LBG treatment. Conclusion: Manipulating intragastric stability and fat emulsion droplet size can influence human gastrointestinal physiology and food intake.
Evaluation of Lossless Watermarking Techniques

One of the mechanisms to deter unauthorized copy and distribution of digital media is Digital Watermarking. Digital watermarking involves embedding of identifying information into the digital content which can be later recovered for verification and authentication. In conventional watermarking schemes certain amount of distortion to the recovered image is acceptable. This does not apply to all applications, particularly in military applications, space and medical imagery etc., loss of a single bit of information from the original image is not acceptable. Reversible watermarking is a novel category of watermarking schemes that can not only strengthen the ownership of the original media but also can completely recover the original media from the watermarked media. In reversible watermarking, the embedding process has an additional burden of embedding extra information in the payload that includes the recovery data that is used by the decoder to reconstruct the original image bit by bit. Thus the payload consists of the authentication information and recovery data. Reversible watermarking is especially suitable for the applications that require high quality images like for certain applications of digital media such as for legal evidence, digital commerce, security surveillance etc. any modification/tampering done to media has to be detected. Various lossless watermarking schemes are discussed in this paper. Keywords—Reversible Coding, PSNR, Histogram modification, Difference Expansion, DWT, Fragile Watermarking, Blind Watermarking
Mitochondrial Calcium Oscillations in C2C12 Myotubes*

Mitochondrial Ca2+concentration ([Ca2+] m ) was monitored in C2C12 skeletal muscle cells stably expressing the Ca2+-sensitive photoprotein aequorin targeted to mitochondria. In myotubes, KCl-induced depolarization caused a peak of 3.03 ± 0.14 μm [Ca2+] m followed by an oscillatory second phase (5.1 ± 0.1 per min). Chelation of extracellular Ca2+ or blockade of the voltage-operated Ca2+ channel attenuated both phases of the KCl response. The inhibitor of the sarcoplasmic reticulum Ca2+-ATPase, cyclopiazonic acid, reduced the amplitude of the KCl-induced [Ca2+] m peak and prevented the oscillations, suggesting that these were generated intracellularly. No such [Ca2+] m oscillations occurred with the nicotinic agonist carbachol, cyclopiazonic acid alone, or the purinergic agonist ATP. In contrast, caffeine produced an oscillatory behavior, indicating a role of ryanodine receptors as mediators of the oscillations. The [Ca2+] m response was desensitized when cells were exposed to two consecutive challenges with KCl separated by a 5-min wash, whereas a second pulse of carbachol potentiated [Ca2+] m , indicating differences in intracellular Ca2+ redistribution. Cross-desensitization between KCl and carbachol and cross-potentiation between carbachol and KCl were observed. These results suggest that close contacts between mitochondria and sarcoplasmic reticulum exist permitting Ca2+ exchanges during KCl depolarization. These newly demonstrated dynamic changes in [Ca2+] m in stimulated skeletal muscle cells might contribute to the understanding of physiological and pathological processes in muscular disorders.
A Novel Method for Assessing the Chaperone Activity of Proteins

Protein chaperones are molecular machines which function both during homeostasis and stress conditions in all living organisms. Depending on their specific function, molecular chaperones are involved in a plethora of cellular processes by playing key roles in nascent protein chain folding, transport and quality control. Among stress protein families–molecules expressed during adverse conditions, infection, and diseases–chaperones are highly abundant. Their molecular functions range from stabilizing stress-susceptible molecules and membranes to assisting the refolding of stress-damaged proteins, thereby acting as protective barriers against cellular damage. Here we propose a novel technique to test and measure the capability for protective activity of known and putative chaperones in a semi-high throughput manner on a plate reader. The current state of the art does not allow the in vitro measurements of chaperone activity in a highly parallel manner with high accuracy or high reproducibility, thus we believe that the method we report will be of significant benefit in this direction. The use of this method may lead to a considerable increase in the number of experimentally verified proteins with such functions, and may also allow the dissection of their molecular mechanism for a better understanding of their function.
On the nature of the fundamental activity of the nervous centres; together with an analysis of the conditioning of rhythmic activity in progression, and a theory of the evolution of function in the nervous system

I. Experiments in which the spinal cord is cut 24 II. Experiments in which the peripheral reflexes are tested during narcosis progression . 27 III. Movements of narcosis progression after de-afferentation of one hind limb . 32 IV. The general bearing of these experiments . 33 V. The fundamental conditions of rhythmic progression 34 VI. The nature and position of the reflex . 39 VII. Evolution of function in the nervous system. 43 Summary. 44
Examining Teacher's Comfort Level of Parental Involvement.

The connection between home and school is of utmost importance. Therefore, an important concern for those educating teachers is to help teachers recognize the need for and importance of establishing parental involvement and to help them create avenues in which communication can occur. Knowing that parental involvement is important and putting that knowledge into practice is often difficult for teachers. This study uncovered the present practices and attitudes of 131 urban teachers about parental involvement by asking them to complete an online survey. It was found that the teachers’ current practice and their schools’ policy did not align with their definitional understanding of parental involvement. In practice, parents were included in school sponsored back-to-school nights, parent-teacher conferences, chaperoning trips, fund raising activities, and implementing school and classroom agendas. There were few opportunities to include parents in policy making, curriculum decisions, or activities to determine and use home literacy events in the classroom. The importance of creating a connection between home and school cannot be underestimated. Therefore, an important concern for those educating teachers is to help teachers recognize the need for and importance of establishing parental involvement and to help them create avenues in which communication can occur. This study uncovers the present practices of teachers when establishing a connection between home and school. It looks at ways in which schools and teachers involve parents by asking elementary school teachers to complete a survey designed to determine their schools’ policies and practice. The purpose of the research is to determine levels of comfort of elementary school teachers when involving parents in their classrooms with a focus on ways in which they create partnerships with parents around literacy development. Need for Parent-School Connections Schools and families must work together to ensure student academic success. The need for home-school partnerships cannot be underestimated. In fact, the importance of parental involvement has been the focus of considerable research for quite some time (for example, Beck, 2002; Epstein, 1988; Shockley et al., 1995). In reviewing the literature on parental involvement, Henderson and Mapp (2002) found that students with involved parents were more likely to earn higher grades, enroll in higher level programs, be promoted, attend school regularly, have better social skills, and graduate. “When schools engage families in ways that are linked to improving learning, students make greater gains,” (p. 8). They also concluded that to be effective the form of involvement should be focused on improving achievement, helping parents develop specific knowledge and skills, inform parents what their children are learning, and how to help their children at home.
Semantic Generalization in a Graph-Based Data Model

This paper proposes the semantic generalization. This generalization makes it possible for a shape graph, which corresponds to a relation schema in the relational data model, to have elements by considering the semantics of the elements of the original shape graphs even if there is no common element in the original shape graphs. For this purpose, viewpoints and relationship trees are introduced. A viewpoint is a sub graph of a schema graph, and plays a role of a kind of hierarchy of concepts. A relationship tree is a hierarchy of relationships. The semantic generalization is informally and formally described. It is shown that the conventional generalization could be realized by using the semantic generalization.