nils-herrmann/clean_scirepeval huggingface dataset:
The Gaps Model of Service Quality and its Impact on Customer Satisfaction

The Service Quality or Gap model (SERVQUAL) has been recognised as an essential tool in identifying service quality and further than this the relationship between a company and its customers. This is vital for firms in sustaining existed advantage and ability to grow further. The purpose of this paper is to identify how applicable the model can be in the context of family owned restaurants and its implications. To this extent, research was conducted involving customers of two family owned restaurants in the Bournemouth area, South West of England. The dimensions of SERVQUAL fulfilled the purpose of research investigation, especially in the context of a narrowly defined sector as the family owned restaurants. The fact that customers were critical with certain aspects of the offered service indicates a higher degree of expectations in comparison with what they received. There were two major limitations in this study: a) the rather small number of completed questionnaires; and b) the somehow introductory to SERVQUAL process of data analysis. Both were dealt with by emphasising on gains of its applicability. The research pointed out that management of family owned restaurants should take into account a wide range of issues if they anticipate their business to survive in a world of financial recession. To this extent, attention to detail is necessary in order to satisfy contemporary customer service demands. As application of SERVQUAL has been so expanded, the real value of this study lies on its actual application. Its biggest asset lies upon identification of pockets of non-efficient service practices that could be of practical use.
Error-Tolerant Scribbles Based Interactive Image Segmentation

Scribbles in scribble-based interactive segmentation such as graph-cut are usually assumed to be perfectly accurate, i.e., foreground scribble pixels will never be segmented as background in the final segmentation. However, it can be hard to draw perfectly accurate scribbles, especially on fine structures of the image or on mobile touch-screen devices. In this paper, we propose a novel ratio energy function that tolerates errors in the user input while encouraging maximum use of the user input information. More specifically, the ratio energy aims to minimize the graph-cut energy while maximizing the user input respected in the segmentation. The ratio energy function can be exactly optimized using an efficient iterated graph cut algorithm. The robustness of the proposed method is validated on the GrabCut dataset using both synthetic scribbles and manual scribbles. The experimental results show that the proposed algorithm is robust to the errors in the user input and preserves the "anchoring" capability of the user input.
Calf circumference as a surrogate marker of muscle mass for diagnosing sarcopenia in Japanese men and women.

To examine the relationship between calf circumference and muscle mass, and to evaluate the suitability of calf circumference as a surrogate marker of muscle mass for the diagnosis of sarcopenia among middle-aged and older Japanese men and women.



A total of 526 adults aged 40-89 years participated in the present cross-sectional study. The maximum calf circumference was measured in a standing position. Appendicular skeletal muscle mass was measured using dual-energy X-ray absorptiometry, and the skeletal muscle index was calculated as appendicular skeletal muscle mass divided by the square of the height (kg/m(2)). The cut-off values for sarcopenia were defined as a skeletal muscle index of less than -2 standard deviations of the mean value for Japanese young adults, as defined previously.



Calf circumference was positively correlated with appendicular skeletal muscle (r = 0.81 in men, r = 0.73 in women) and skeletal muscle index (r = 0.80 in men, r = 0.69 in women). In receiver operating characteristic analysis, the optimal calf circumference cut-off values for predicting sarcopenia were 34 cm (sensitivity 88%, specificity 91%) in men and 33 cm (sensitivity 76%, specificity 73%) in women.



Calf circumference was positively correlated with appendicular skeletal muscle mass and skeletal muscle index, and could be used as a surrogate marker of muscle mass for diagnosing sarcopenia. The suggested cut-off values of calf circumference for predicting low muscle mass are <34 cm in men and <33 cm in women.
Analysis and Optimization of a Multistage Inventory-Queue System

An important issue in the management of supply chains and manufacturing systems is to control inventory costs at different locations throughout the system while satisfying an end-customer service-level requirement. The challenge involved is to solve a nonlinear constrained optimization problem that captures the key dynamics of a complex productioninventory system. In this paper, we first develop a multi-stage inventory-queue model and a job-queue decomposition approach, which evaluates the performance of serial manufacturing and supply systems with inventory control at every stage. We then present an efficient procedure to minimize the overall inventory in the system while meeting the required service level. Our technique is relatively simple and delivers accurate performance estimates. Furthermore, numerical studies generate certain managerial insights into related design and control issues.
Healthy aging diets other than the Mediterranean: A focus on the Okinawan diet

The traditional diet in Okinawa is anchored by root vegetables (principally sweet potatoes), green and yellow vegetables, soybean-based foods, and medicinal plants. Marine foods, lean meats, fruit, medicinal garnishes and spices, tea, alcohol are also moderately consumed. Many characteristics of the traditional Okinawan diet are shared with other healthy dietary patterns, including the traditional Mediterranean diet, DASH diet, and Portfolio diet. All these dietary patterns are associated with reduced risk for cardiovascular disease, among other age-associated diseases. Overall, the important shared features of these healthy dietary patterns include: high intake of unrefined carbohydrates, moderate protein intake with emphasis on vegetables/legumes, fish, and lean meats as sources, and a healthy fat profile (higher in mono/polyunsaturated fats, lower in saturated fat; rich in omega-3). The healthy fat intake is likely one mechanism for reducing inflammation, optimizing cholesterol, and other risk factors. Additionally, the lower caloric density of plant-rich diets results in lower caloric intake with concomitant high intake of phytonutrients and antioxidants. Other shared features include low glycemic load, less inflammation and oxidative stress, and potential modulation of aging-related biological pathways. This may reduce risk for chronic age-associated diseases and promote healthy aging and longevity.
Interactive Visualization of Gene Regulatory Networks with Associated Gene Expression Time Series Data

We present GENeVis, an application to visualize gene expression time series data in a gene regulatory network context. This is a network of regulator proteins that regulate the expression of their respective target genes. The networks are represented as graphs, in which the nodes represent genes, and the edges represent interactions between a gene and its targets. GENeVis adds features that are currently lacking in existing tools, such as mapping of expression value and corresponding p-value (or other statistic) to a single visual attribute, multiple time point visualization, and visual comparison of multiple time series in one view. Various interaction mechanisms, such as panning, zooming, regulator and target highlighting, data selection, and tooltips support data analysis and exploration. Subnetworks can be studied in detail in a separate view that shows the network context, expression data plots, and tables containing the raw expression data. We present a case study, in which gene expression time series data acquired in-house are analyzed by a biological expert using GENeVis. The case study shows that the application fills the gap between present biological interpretation of time series experiments, performed on a gene-by-gene basis, and analysis of global classes of genes whose expression is regulated by regulator proteins.
Variational Inference for Mahalanobis Distance Metrics in Gaussian Process Regression

We introduce a novel variational method that allows to approximately integrate out kernel hyperparameters, such as length-scales, in Gaussian process regression. This approach consists of a novel variant of the variational framework that has been recently developed for the Gaussian process latent variable model which additionally makes use of a standardised representation of the Gaussian process. We consider this technique for learning Mahalanobis distance metrics in a Gaussian process regression setting and provide experimental evaluations and comparisons with existing methods by considering datasets with high-dimensional inputs.
Face detection: Comparing Haar-like combined with cascade classifiers and Edge Orientation Matching

One of the major research areas attracting much interest is face recognition. This is due to the growing need of detection and recognition in the modern days' industrial applications. However, this need is conditioned with the high performance standards that these applications require in terms of speed and accuracy. In this work we present a comparison between two main techniques of face recognition in unconstraint scenes. The first one is Edge-Orientation Matching and the second technique is Haar-like feature selection combined cascade classifiers.
Hepatitis B and D viruses exploit sodium taurocholate co-transporting polypeptide for species-specific entry into hepatocytes.

Hepatitis B and D viruses (HBV and HDV) are human pathogens with restricted host ranges and high selectivity for hepatocytes; the HBV L-envelope protein interacts specifically with a receptor on these cells. We aimed to identify this receptor and analyze whether it is the recently described sodium-taurocholate co-transporter polypeptide (NTCP), encoded by the SLC10A1 gene.



To identify receptor candidates, we compared gene expression patterns between differentiated HepaRG cells, which express the receptor, and naïve cells, which do not. Receptor candidates were evaluated by small hairpin RNA silencing in HepaRG cells; the ability of receptor expression to confer binding and infection were tested in transduced hepatoma cell lines. We used interspecies domain swapping to identify motifs for receptor-mediated host discrimination of HBV and HDV binding and infection.



Bioinformatic analyses of comparative expression arrays confirmed that NTCP, which was previously identified through a biochemical approach is a bona fide receptor for HBV and HDV. NTCPs from rat, mouse, and human bound Myrcludex B, a peptide ligand derived from the HBV L-protein. Myrcludex B blocked NTCP transport of bile salts; small hairpin RNA-mediated knockdown of NTCP in HepaRG cells prevented their infection by HBV or HDV. Expression of human but not mouse NTCP in HepG2 and HuH7 cells conferred a limited cell-type-related and virus-dependent susceptibility to infection; these limitations were overcome when cells were cultured with dimethyl sulfoxide. We identified 2 short-sequence motifs in human NTCP that were required for species-specific binding and infection by HBV and HDV.



Human NTCP is a specific receptor for HBV and HDV. NTCP-expressing cell lines can be efficiently infected with these viruses, and might be used in basic research and high-throughput screening studies. Mapping of motifs in NTCPs have increased our understanding of the species specificities of HBV and HDV, and could lead to small animal models for studies of viral infection and replication.
A double-blind randomized trial of 5% ascorbic acid vs. 4% hydroquinone in melasma.

Melasma is an acquired treatment-resistant hyperpigmentation of the skin.



Sixteen women with idiopathic melasma were included in our trial. After randomization by another clinician, they were instructed to use, at night, 5% ascorbic acid cream on one side of the face and 4% hydroquinone cream on the other side, for 16 weeks. Sunscreen was applied daily throughout the period of observation. They were evaluated every month by colorimetry, digital photography, and regular color slides. Subjective evaluation by each patient was also taken into account.



The best subjective improvement was observed on the hydroquinone side with 93% good and excellent results, compared with 62.5% on the ascorbic acid side (P < 0.05); however, colorimetric measures showed no statistical differences. Side-effects were present in 68.7% (11/16) with hydroquinone vs. 6.2% (1/16) with ascorbic acid.



Although hydroquinone showed a better response, ascorbic acid may play a role in the therapy of melasma as it is almost devoid of side-effects; it could be used alone or in combination therapy.
Three decades of Kappaphycus alvarezii (Rhodophyta) introduction to non-endemic locations.

Given the increase in demand for sustainable livelihoods for coastal villagers in developing countries and for the commercial eucheumoid Kappaphycus alvarezii (Doty) Doty, for the carrageenan industry, there is a trend towards introducing K. alvarezii to more countries in the tropical world for the purpose of cultivation. However, there is also increasing concern over the impact exotic species have on endemic ecosystems and biodiversity. Quarantine and introduction procedures were tested in northern Madagascar and are proposed for all future introductions of commercial eucheumoids (K. alvarezii, K. striatum and Eucheuma denticulatum). In addition, the impact and extent of introduction of K. alvarezii was measured on an isolated lagoon in the southern Lau group of Fiji. It is suggested that, in areas with high human population density, the overwhelming benefits to coastal ecosystems by commercial eucheumoid cultivation far outweigh potential negative impacts. However, quarantine and introduction procedures should be followed. In addition, introduction should only take place if a thorough survey has been conducted and indicates the site is appropriate. Subsequently, the project requires that a well designed and funded cultivation development programme, with a management plan and an assured market, is in place in order to make certain cultivation, and subsequently the introduced algae, will not be abandoned at a later date.
Biotechnological Transformation of Lignocellulosic Biomass in to Industrial Products: An Overview

Lignocellulose—a major component of biomass available on earth is a renewable and abundantly available with great potential for bioconversion to value-added bio-products. The review aims at physio-chemical features of lignocellulosic biomass and composition of different lignocellulosic materials. This work is an overview about the conversion of lignocellulosic biomass into bio-energy products such as bio-ethanol, 1-butanol, bio-methane, bio-hydrogen, organic acids including citric acid, succinic acid and lactic acid, microbial polysaccharides, single cell protein and xylitol. The biotechnological aspect of bio-transformation of lignocelluloses research and its future prospects are also discussed.
Shattering and Compressing Networks for Betweenness Centrality

The betweenness metric has always been intriguing and used in many analyses. Yet, it is one of the most computationally expensive kernels in graph mining. For that reason, making betweenness centrality computations faster is an important and well-studied problem. In this work, we propose the framework, BADIOS, which compresses a network and shatters it into pieces so that the centrality computation can be handled independently for each piece. Although BADIOS is designed and tuned for betweenness centrality, it can easily be adapted for other centrality metrics. Experimental results show that the proposed techniques can be a great arsenal to reduce the centrality computation time for various types and sizes of networks. In particular, it reduces the computation time of a 4.6 million edges graph from more than 5 days to less than 16 hours.
Higher and derived stacks : a global overview

These are expended notes of my talk at the summer institute in algebraic geometry (Seattle, July-August 2005), whose main purpose is to present a global overview on the theory of higher and derived stacks. This text is far from being exhaustive but is intended to cover a rather large part of the subject, starting from the motivations and the foundational material, passing through some examples and basic notions, and ending with some more recent developments and open questions.
Learning to close loops from range data

This paper addresses the loop closure detection problem in slam, and presents a method for solving the problem using pairwise comparison of point clouds in both 2D and 3D. The point clouds are mathematically described using features that capture important geometric and statistical properties. The features are used as input to the machine learning algorithm AdaBoost, which is used to build a non-linear classifier capable of detecting loop closure from pairs of point clouds. Vantage point dependency in the detection process is eliminated by only using rotation invariant features, thus loop closure can be detected from arbitrary direction. The classifier is evaluated using publicly available data, and is shown to generalise well between environments. Detection rates of 66%, 63% and 53% for 0% false alarm rate are achieved for 2D outdoor data, 3D outdoor data and 3D indoor data, respectively. In both 2D and 3D, experiments are performed using publicly available data, showing that the proposed algorithm compares favourably to related work.
Stochastic Generative Hashing

Learning-based binary hashing has become a powerful paradigm for fast search and retrieval in massive databases. However, due to the requirement of discrete outputs for the hash functions, learning such functions is known to be very challenging. In addition, the objective functions adopted by existing hashing techniques are mostly chosen heuristically. In this paper, we propose a novel generative approach to learn hash functions through Minimum Description Length principle such that the learned hash codes maximally compress the dataset and can also be used to regenerate the inputs. We also develop an efficient learning algorithm based on the stochastic distributional gradient, which avoids the notorious difficulty caused by binary output constraints, to jointly optimize the parameters of the hash function and the associated generative model. Extensive experiments on a variety of large-scale datasets show that the proposed method achieves better retrieval results than the existing state-of-the-art methods.
Using simple agent-based modeling to inform and enhance neighborhood walkability

Pedestrian-friendly neighborhoods with proximal destinations and services encourage walking and decrease car dependence, thereby contributing to more active and healthier communities. Proximity to key destinations and services is an important aspect of the urban design decision making process, particularly in areas adopting a transit-oriented development (TOD) approach to urban planning, whereby densification occurs within walking distance of transit nodes. Modeling destination access within neighborhoods has been limited to circular catchment buffers or more sophisticated network-buffers generated using geoprocessing routines within geographical information systems (GIS). Both circular and network-buffer catchment methods are problematic. Circular catchment models do not account for street networks, thus do not allow exploratory 'what-if' scenario modeling; and network-buffering functionality typically exists within proprietary GIS software, which can be costly and requires a high level of expertise to operate.



This study sought to overcome these limitations by developing an open-source simple agent-based walkable catchment tool that can be used by researchers, urban designers, planners, and policy makers to test scenarios for improving neighborhood walkable catchments. A simplified version of an agent-based model was ported to a vector-based open source GIS web tool using data derived from the Australian Urban Research Infrastructure Network (AURIN). The tool was developed and tested with end-user stakeholder working group input.



The resulting model has proven to be effective and flexible, allowing stakeholders to assess and optimize the walkability of neighborhood catchments around actual or potential nodes of interest (e.g., schools, public transport stops). Users can derive a range of metrics to compare different scenarios modeled. These include: catchment area versus circular buffer ratios; mean number of streets crossed; and modeling of different walking speeds and wait time at intersections.



The tool has the capacity to influence planning and public health advocacy and practice, and by using open-access source software, it is available for use locally and internationally. There is also scope to extend this version of the tool from a simple to a complex model, which includes agents (i.e., simulated pedestrians) 'learning' and incorporating other environmental attributes that enhance walkability (e.g., residential density, mixed land use, traffic volume).
NNZ-2566: A Gly–Pro–Glu analogue with neuroprotective efficacy in a rat model of acute focal stroke

The N-terminal cleavage product of human insulin-like growth factor-1 (IGF-1) in the brain is the tripeptide molecule Glypromate (Gly-Pro-Glu). Glypromate has demonstrated neuroprotective effects in numerous in vitro and in vivo models of brain injury and is in clinical trials for the prevention of cognitive impairment following cardiac surgery. NNZ-2566 is a structural analogue of Glypromate, resulting from alpha-methylation of the proline moiety, which has improved the elimination half-life and oral bioavailability over the parent peptide. In vivo, NNZ-2566 reduces injury size in rats subjected to focal stroke. An intravenous infusion of NNZ-2566 of 4 h duration (3-10 mg/kg/h), initiated 3 h after endothelin-induced middle-cerebral artery constriction, significantly reduced infarct area as assessed on day 5. Neuroprotective efficacy in the MCAO model was also observed following oral administration of the drug (30-60 mg/kg), when formulated as a microemulsion. In vitro, NNZ-2566 significantly attenuates apoptotic cell death in primary striatal cultures, suggesting attenuation of apoptosis is one mechanism of action underlying its neuroprotective effects. NNZ-2566 is currently in clinical trials for the treatment of cognitive deficits following traumatic brain injury, and these data further support the development of the drug as a neuroprotective agent for acute brain injury.
Multi-microphone acoustic echo cancellation using multi-channel warped linear prediction of common acoustical poles

A computationally cheap extension from single-microphone acoustic echo cancellation (AEC) to multi-microphone AEC is presented for the case of a single loudspeaker. It employs the idea of common-acoustical-pole and zero modeling of room transfer functions (RTFs). The RTF models used for multi-microphone AEC share a fixed common denominator polynomial, which is calculated off-line by means of a multi-channel warped linear prediction. By using the common denominator polynomial as a prefilter, only the numerator polynomial has to be estimated recursively for each microphone, hence adapting to changes in the RTFs. This approach allows to decrease the number of numerator coefficients by one order of magnitude for each microphone compared with all-zero modeling. In a first configuration, the prefiltering is done on the adaptive filter signal, hence achieving a pole-zero model of the RTF in the AEC. In a second configuration, the (inverse) prefiltering is done on the loudspeaker signal, hence achieving a dereverberation effect, in addition to AEC, on the microphone signals.