nils-herrmann/clean_scirepeval huggingface dataset:
Efficacy Coefficients Determined Using Nail Permeability and Antifungal Activity in Keratin-Containing Media Are Useful for Predicting Clinical Efficacies of Topical Drugs for Onychomycosis

Onychomycosis is difficult to treat topically due to the deep location of the infection under the densely keratinized nail plate. In order to obtain an in vitro index that is relevant to the clinical efficacy of topical anti-onychomycosis drugs, we profiled five topical drugs: amorolfine, ciclopirox, efinaconazole, luliconazole, and terbinafine, for their nail permeabilities, keratin affinities, and anti-dermatophytic activities in the presence of keratin. Efinaconazole and ciclopirox permeated full-thickness human nails more deeply than luliconazole. Amorolfine and terbinafine did not show any detectable permeation. The free-drug concentration of efinaconazole in a 5% human nail keratin suspension was 24.9%, which was significantly higher than those of the other drugs (1.1-3.9%). Additionally, efinaconazole was released from human nail keratin at a greater proportion than the other drugs. The MICs of the five drugs for Trichophyton rubrum were determined at various concentrations of keratin (0-20%) in RPMI 1640 medium. The MICs of ciclopirox were not affected by keratin, whereas those of efinaconazole were slightly increased and those of luliconazole and terbinafine were markedly increased in the presence of 20% keratin. Efficacy coefficients were calculated using the nail permeation flux and MIC in media without or with keratin. Efinaconazole showed the highest efficacy coefficient, which was determined using MIC in media with keratin. The order of efficacy coefficients determined using MIC in keratin-containing media rather than keratin-free media was consistent with that of complete cure rates in previously reported clinical trials. The present study revealed that efficacy coefficients determined using MIC in keratin-containing media are useful for predicting the clinical efficacies of topical drugs. In order to be more effective, topical drugs have to possess higher efficacy coefficients.
- 1-Management Accounting Change in the Financial Services Sector : The Case of Activity-Based Costing in a Portuguese Bank

This paper aims to trace the development of management accounting systems (MAS) in a Portuguese bank, where an activity based costing system (ABC) is being trialled for implementation, as a means to improving the economy, efficiency and effectiveness of employee activity. The culture of banking in Portugal has changed significantly over the last 25 years, but at the same time there are older traditions which remain powerful. It will therefore be significant to study how an imported MAS like ABC is developed and disseminated within a Portuguese banking context. The research can be classified as a longitudinal study of organisational change using a single case study. It draws on Morgan and Sturdy’s (2000) critical framework for exploring change through three lenses – changing structures, changing discourses and the effect of both these processes on power and inequality. The study provides new insights into how management accounting practices, along with other organisational systems, play an important role questioning, visualising, analysing, and measuring implemented strategies. These practices have an important influence on strategic decision-making, and help legitimate action. As the language and practice of management have shifted towards strategy and marketing discourses, patterns of work, organisation and career are being restructured.
Panton–Valentine leukocidin-associated Staphylococcus aureus necrotizing pneumonia in infants: a report of four cases and review of the literature

Four children under 16 months of age presented within an 18-month period with severe, rapidly progressive Panton–Valentine leukocidin-associated ST93 Staphylococcus aureus necrotizing pneumonia. Two of the cases that required extracorporeal membranous oxygenation and proved fatal had poor prognostic features of leukopaenia, rash and pulmonary haemorrhage. All four cases had recent contact with S. aureus infection in a family member. Reported cases of S. aureus necrotizing pneumonia in infants are reviewed, and approach to management is discussed.
Synthesizing parallel graph programs via automated planning

We describe a system that uses automated planning to synthesize correct and efficient parallel graph programs from high-level algorithmic specifications. Automated planning allows us to use constraints to declaratively encode program transformations such as scheduling, implementation selection, and insertion of synchronization. Each plan emitted by the planner satisfies all constraints simultaneously, and corresponds to a composition of these transformations. In this way, we obtain an integrated compilation approach for a very challenging problem domain. We have used this system to synthesize parallel programs for four graph problems: triangle counting, maximal independent set computation, preflow-push maxflow, and connected components. Experiments on a variety of inputs show that the synthesized implementations perform competitively with hand-written, highly-tuned code.
Temporal Autoencoding Improves Generative Models of Time Series

Restricted Boltzmann Machines (RBMs) are generative models which can learn useful representations from samples of a dataset in an unsupervised fashion. They have been widely employed as an unsupervised pre-training method in machine learning. RBMs have been modified to model time series in two main ways: The Temporal RBM stacks a number of RBMs laterally and introduces temporal dependencies between the hidden layer units; The Conditional RBM, on the other hand, considers past samples of the dataset as a conditional bias and learns a representation which takes these into account. Here we propose a new training method for both the TRBM and the CRBM, which enforces the dynamic structure of temporal datasets. We do so by treating the temporal models as denoising autoencoders, considering past frames of the dataset as corrupted versions of the present frame and minimizing the reconstruction error of the present data by the model. We call this approach Temporal Autoencoding. This leads to a significant improvement in the performance of both models in a filling-in-frames task across a number of datasets. The error reduction for motion capture data is 56% for the CRBM and 80% for the TRBM. Taking the posterior mean prediction instead of single samples further improves the model’s estimates, decreasing the error by as much as 91% for the CRBM on motion capture data. We also trained the model to perform forecasting on a large number of datasets and have found TA pretraining to consistently improve the performance of the forecasts. Furthermore, by looking at the prediction error across time, we can see that this improvement reflects a better representation of the dynamics of the data as opposed to a bias towards reconstructing the observed data on a short time scale. We believe this novel approach of mixing contrastive divergence and autoencoder training yields better models of temporal data, bridging the way towards more robust generative models of time series.
Duplicate-skins for compatible mesh modelling

As compatible meshes play important roles in many computer-aided design applications, we present a new approach for modelling compatible meshes. Our compatible mesh modelling method is derived from the skin algorithm [Markosian et al. 1999] which conducts an active particle-based mesh surface to approximate the given models serving as skeletons. To construct compatible meshes, we developed a duplicate-skins algorithm to simultaneously grow two skins with identical connectivity over two skeleton models; therefore, the resultant skin meshes are compatible. Our duplicate-skins algorithm has less topological constraints on the input models: multiple polygonal models, models with ill-topology meshes, or even point clouds could all be employed as skeletons to model compatible meshes. Based on the results of our duplicate-skins algorithm, the modelling method of n-Ary compatible meshes is also developed in this paper.
Bottom-up and top-down attention are independent.

What is the relationship between top-down and bottom-up attention? Are both types of attention tightly interconnected, or are they independent? We investigated this by testing a large representative sample of the Dutch population on two attentional tasks: a visual search task gauging the efficiency of top-down attention and a singleton capture task gauging bottom-up attention. On both tasks we found typical performance--i.e., participants displayed a significant search slope on the search task and significant slowing caused by the unique, but irrelevant, object on the capture task. Moreover, the high levels of significance we observed indicate that the current set-up provided very high signal to noise ratios, and thus enough power to accurately unveil existing effects. Importantly, in this robust investigation we did not observe any correlation in performance between tasks. The use of Bayesian statistics strongly confirmed that performance on both tasks was uncorrelated. We argue that the current results suggest that there are two attentional systems that operate independently. We hypothesize that this may have implications beyond our understanding of attention. For instance, it may be that attention and consciousness are intertwined differently for top-down attention than for bottom-up attention.
Feedback-driven threading: power-efficient and high-performance execution of multi-threaded workloads on CMPs

Extracting high-performance from the emerging Chip Multiprocessors (CMPs) requires that the application be divided into multiple threads. Each thread executes on a separate core thereby increasing concurrency and improving performance. As the number of cores on a CMP continues to increase, the performance of some multi-threaded applications will benefit from the increased number of threads, whereas, the performance of other multi-threaded applications will become limited by data-synchronization and off-chip bandwidth. For applications that get limited by data-synchronization, increasing the number of threads significantly degrades performance and increases on-chip power. Similarly, for applications that get limited by off-chip bandwidth, increasing the number of threads increases on-chip power without providing any performance improvement. Furthermore, whether an application gets limited by data-synchronization, or bandwidth, or neither depends not only on the application but also on the input set and the machine configuration. Therefore, controlling the number of threads based on the run-time behavior of the application can significantly improve performance and reduce power.
 This paper proposes Feedback-Driven Threading (FDT), a framework to dynamically control the number of threads using run-time information. FDT can be used to implement Synchronization-Aware Threading (SAT), which predicts the optimal number of threads depending on the amount of data-synchronization. Our evaluation shows that SAT can reduce both execution time and power by up to 66% and 78% respectively. Similarly, FDT can be used to implement Bandwidth-Aware Threading (BAT), which predicts the minimum number of threads required to saturate the off-chip bus. Our evaluation shows that BAT reduces on-chip power by up to 78%. When SAT and BAT are combined, the average execution time reduces by 17% and power reduces by 59%. The proposed techniques leverage existing performance counters and require minimal support from the threading library.
Neurocognitive start-up tools for symbolic number representations

Attaching meaning to arbitrary symbols (i.e. words) is a complex and lengthy process. In the case of numbers, it was previously suggested that this process is grounded on two early pre-verbal systems for numerical quantification: the approximate number system (ANS or 'analogue magnitude'), and the object tracking system (OTS or 'parallel individuation'), which children are equipped with before symbolic learning. Each system is based on dedicated neural circuits, characterized by specific computational limits, and each undergoes a separate developmental trajectory. Here, I review the available cognitive and neuroscientific data and argue that the available evidence is more consistent with a crucial role for the ANS, rather than for the OTS, in the acquisition of abstract numerical concepts that are uniquely human.
Streaming submodular maximization: massive data summarization on the fly

How can one summarize a massive data set "on the fly", i.e., without even having seen it in its entirety? In this paper, we address the problem of extracting representative elements from a large stream of data. I.e., we would like to select a subset of say k data points from the stream that are most representative according to some objective function. Many natural notions of "representativeness" satisfy submodularity, an intuitive notion of diminishing returns. Thus, such problems can be reduced to maximizing a submodular set function subject to a cardinality constraint. Classical approaches to submodular maximization require full access to the data set. We develop the first efficient streaming algorithm with constant factor 1/2-ε approximation guarantee to the optimum solution, requiring only a single pass through the data, and memory independent of data size. In our experiments, we extensively evaluate the effectiveness of our approach on several applications, including training large-scale kernel methods and exemplar-based clustering, on millions of data points. We observe that our streaming method, while achieving practically the same utility value, runs about 100 times faster than previous work.
Copositive optimization - Recent developments and applications

Due to its versatility, copositive optimization receives increasing interest in the Operational Research community, and is a rapidly expanding and fertile field of research. It is a special case of conic optimization, which consists of minimizing a linear function over a cone subject to linear constraints. The diversity of copositive formulations in different domains of optimization is impressive, since problem classes both in the continuous and discrete world, as well as both deterministic and stochastic models are covered. Copositivity appears in local and global optimality conditions for quadratic optimization, but can also yield tighter bounds for NP-hard combinatorial optimization problems. Here some of the recent success stories are told, along with principles, algorithms and applications.
An algorithm to find relationships between web vulnerabilities

Over the past years, there has been a high increase in web sites using cloud computing. Like usual web site, those web applications can have most of the common web vulnerabilities, like SQL injection or cross-site scripting. Therefore, cloud computing has become more attractive to cyber criminals. Besides, in many cases it is necessary to comply with regulations like PCI DSS or standards like ISO/IEC 27001. To face those threats and requirements it is a common task to analyze web applications to detect and correct their vulnerabilities. The most used tools to analyze web applications are automatic scanners. But it is difficult to comparatively decide which scanner is best or at least is best suited to detect a particular vulnerability. To evaluate scanner capabilities some evaluation criteria have been defined. Often a web vulnerability classification is also used to evaluate scanners, but current web vulnerability classifications do not usually include all vulnerabilities. To face evaluation criteria which are not up-to-date and to have the fullest possible classification, in this paper a new method to map web vulnerability classifications is proposed. The result will be the vulnerabilities an automatic scanner has to detect. As classifications change over time, this new method could be executed when the existing classifications change or when new classifications are developed. The vulnerabilities described this way can also be seen as a web vulnerability classification that includes all vulnerabilities in the classifications taken into account.
Metrology Delay Time Reduction in Lithography with an Enhanced AMHS using Local FOUP Buffering

An enhanced automated material handling system (AMHS) that uses a local FOUP buffer at each tool is presented as a method of enabling lot size reduction and parallel metrology sampling in the photolithography (litho) bay. The local FOUP buffers can be integrated with current OHT AMHS systems in existing fabs with little or no change to the AMHS or process equipment. The local buffers enhance the effectiveness of the OHT by eliminating intermediate moves to stockers, increasing the move rate capacity by 15-20%, and decreasing the loadport exchange time to 30 seconds. These enhancements can enable the AMHS to achieve the high move rates compatible with lot size reduction down to 12-15 wafers per FOUP. The implementation of such a system in a photolithography bay could result in a 60-74% reduction in metrology delay time, which is the time between wafer exposure at a litho tool and collection of metrology and inspection data.
A Survey on Approaches of Motion Mode Recognition Using Sensors

Recognition of the mode of motion or mode of transit of the user or platform carrying a device is needed in portable navigation, as well as other technological domains. An extensive survey on motion mode recognition approaches is provided in this survey paper. The survey compares and describes motion mode recognition approaches from different viewpoints: usability and convenience, types of devices in terms of setup mounting and data acquisition, various types of sensors used, signal processing methods employed, features extracted, and classification techniques. This paper ends with a quantitative comparison of the performance of motion mode recognition modules developed by researchers in different domains.
Modeling collaboration formation with a game theory approach

While collaborative product development (CPD) is adopted by more and more firms as a business strategy, there is still lack of thorough research on the conditions under which the collaboration is formed. This paper proposes a mathematical model integrating trust, coordination, co-learning, and co-innovation dimensions of CPD. These dimensions, as well as additional parameters such as knowledge investment, absorption capability, efficacy, and complementarity enable the observation of the collaboration behavior under various scenarios. An analysis is conducted with Nash Bargaining approach to investigate the effect of various parameters on the collaboration formation as well as the revenue sharing. The analysis summary presents the optimum strategies for each scenario.
Correcting for contact geometry in Seebeck coefficient measurements of thin film devices

Driven by promising recent results, there has been a revived interest in the thermoelectric properties of organic (semi)conductors. Concomitantly, there is a need to probe the Seebeck coefficient S of modestly conducting materials in thin film geometry. Here we show that geometries that seem desirable from a signal-to-noise perspective may induce systematic errors in the measured value of S, Sm, by a factor 3 or more. The enhancement of Sm by the device geometry is related to competing conduction paths outside the region between the electrodes. We derive a universal scaling curve that allows correcting for this and show that structuring the semiconductor is not needed for the optimal electrode configuration, being a set of narrow, parallel strips.
Visualization of Brain Microstructure Through Spherical Harmonics Illumination of High Fidelity Spatio-Angular Fields

Diffusion kurtosis imaging (DKI) is gaining rapid adoption in the medical imaging community due to its ability to measure the non-Gaussian property of water diffusion in biological tissues. Compared to traditional diffusion tensor imaging (DTI), DKI can provide additional details about the underlying microstructural characteristics of the neural tissues. It has shown promising results in studies on changes in gray matter and mild traumatic brain injury where DTI is often found to be inadequate. The DKI dataset, which has high-fidelity spatio-angular fields, is difficult to visualize. Glyph-based visualization techniques are commonly used for visualization of DTI datasets; however, due to the rapid changes in orientation, lighting, and occlusion, visually analyzing the much more higher fidelity DKI data is a challenge. In this paper, we provide a systematic way to manage, analyze, and visualize high-fidelity spatio-angular fields from DKI datasets, by using spherical harmonics lighting functions to facilitate insights into the brain microstructure.
Challenges in the Delivery of E-Government through Kiosks

Kiosks are increasingly being heralded as a technology through which governments, government departments and local authorities or municipalities can engage with citizens. In particular, they have attractions in their potential to bridge the digital divide. There is some evidence to suggest that the citizen uptake of kiosks and indeed other channels for e-government, such as web sites, is slow, although studies on the use of kiosks for health information provision offer some interesting perspectives on user behaviour with kiosk technology. This article argues that the delivery of e-government through kiosks presents a number of strategic challenges, which will need to be negotiated over the next few years in order that kiosk applications are successful in enhancing accessibility to and engagement with egovernment. The article suggests that this involves consideration of: the applications to be delivered through a kiosk; one stop shop service and knowledge architectures; mechanisms for citizen identification; and, the integration of kiosks within the total interface between public bodies and their communities. The article concludes by outlining development and research agendas in each of these areas.
Bacteriology of surgical site and catheter related urinary tract infections among patients admitted in Mekelle Hospital, Mekelle, Tigray, Ethiopia.

Nosocomial infections are widespread and are important contributors to morbidity and mortality. Prevalence studies are useful in revealing the prevalence of hospital-acquired infections.



To determine the bacterial pathogens associated with hospital acquired surgical site infection (SSI) and urinary tract infection (UTI) and assess their susceptibility patterns in patients admitted in Mekelle Hospital in Ethiopia.



From November 2005 to April 2006 a prospective cross sectional study was conducted at Mekelle Hospital, Tigray region, North Ethiopia. The study population comprised of a total of 246 informed and consented adult patients hospitalized for surgical (n = 212) and Gynecology and Obstetrics cases (n = 34).



Of the 246 admitted patients, 68 (27.6%) developed nosocomial infections (SSI and/or nosocomial UTI) based on the clinical evaluations, and positive wound and urine culture results. Gram negative bacteria were predominantly isolated with a rate of 18/34 (53%) and 34/41 (83%) from SSI and UTI respectively. Most of the isolates from UTI have high rates of resistance (> 80%) to the commonly used antibiotics such as ampicillin, amoxicillin, chloramphenicol, gentamicin, streptomycin, and trimethoprim-sulphamethoxazole; and in isolates from SSI to amoxicillin and trimethoprim-sulphamethoxazole.



The results showed that the prevalence of HAIs (SSI and nosocomial UTI) in the Hospital is high when compared to previous Ethiopian and other studies despite the use of prophylactic antibiotics. The pathogens causing SSI and UT7 are often resistant to commonly used antimicrobials. The findings underscore the need for an infection control system and surveillance program in the hospital and to monitor antimicrobial resistance pattern for the use of prophylactic and therapeutic antibiotics.