nils-herrmann/clean_scirepeval huggingface dataset:
Comparison of Clinical Laboratory Standards Institute and European Committee on Antimicrobial Susceptibility Testing guidelines for the interpretation of antibiotic susceptibility at a University teaching hospital in Nairobi, Kenya: a cross sectional study
Venue: Annals of Clinical Microbiology and Antimicrobials

BackgroundThe Clinical Laboratory Standards Institute (CLSI) and the European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines are the most popular breakpoint guidelines used in antimicrobial susceptibility testing worldwide. The EUCAST guidelines are freely available to users while CLSI is available for non members as a package of three documents for US $500 annually. This is prohibitive for clinical microbiology laboratories in resource poor settings. We set out to compare antibiotic susceptibility determined by the two guidelines to determine whether adoption of EUCAST guidelines would significantly affect our susceptibility patterns.MethodsWe reviewed minimum inhibitory concentrations (MIC) of various antibiotics routinely reported for Escherichia coli (E. coli) Staphylococcus aureus (S. aureus) and Pseudomonas aeruginosa (P. aeruginosa) isolates from an automated microbiology identification system (VITEK 2) at the Aga Khan University Hospital Nairobi's Pathology department. These MICs were then analyzed using both CLSI 2015 and EUCAST 2015 guidelines and classified as resistant, intermediate or susceptible. We compared the susceptibility and agreement between the CLSI and EUCAST categorizations.ResultsSusceptibility data from a total of 5165 E. coli, 1103 S. aureus and 532 P. aeruginosa isolates were included. The concordance rates of the two guidelines for E. coli, S. aureus and P. aeruginosa ranged from 78.2 to 100 94.6 to 100 and 89.1 to 95.5 respectively. The kappa statistics for E. coli MICs revealed perfect agreement between CLSI and EUCAST for cefotaxime, ceftriaxone and trimethoprim sulfamethoxazole, almost perfect agreement for ampicillin, ciprofloxacin, cefuroxime, gentamicin and ceftazidime, substantial agreement for meropenem, moderate agreement for cefepime and amoxicillin clavulanate, fair agreement for nitrofurantoin and poor agreement for amikacin. For S. aureus the kappa statistics revealed perfect agreement for penicillin, trimethoprim sulfamethoxazole, levofloxacin, oxacillin, linezolid and vancomycin, almost perfect agreement for clindamycin, erythromycin and tetracycline and moderate agreement for gentamicin. For P. aeruginosa the kappa analysis revealed moderate to almost perfect agreement for all the anti pseudomonal antibiotics.ConclusionThe results show comparable antibiotic susceptibility patterns between CLSI and EUCAST breakpoints. Given that EUCAST guidelines are freely available, it makes it easier for laboratories in resource poor settings to have an updated and readily available reference for interpreting antibiotic susceptibilities.
Data profiling
Venue: 2016 IEEE 32nd International Conference on Data Engineering (ICDE)

One of the crucial requirements before consuming datasets for any application is to understand the dataset at hand and its metadata. The process of metadata discovery is known as data profiling. Profiling activities range from ad hoc approaches, such as eye balling random subsets of the data or formulating aggregation queries, to systematic inference of structural information and statistics of a dataset using dedicated profiling tools. In this tutorial, we highlight the importance of data profiling as part of any data related use case, and discuss the area of data profiling by classifying data profiling tasks and reviewing the state of the art data profiling systems and techniques. In particular, we discuss hard problems in data profiling, such as algorithms for dependency discovery and profiling algorithms for dynamic data and streams. We conclude with directions for future research in the area of data profiling. This tutorial is based on our survey on profiling relational data
Solar Radiation Fundamentals and PV System Components

Solar PV technology has emerged as one of the most matured and fast evolving renewable energy technologies and it is expected that it will play a major role in the future global electricity generation mix. Keeping the rapid development of the PV technology into consideration, this chapter systematically documents the evolution of solar PV material as well as the PV applications and PV markets. It also provides insight into the trend in batteries and inverters used for solar PV applications. Furthermore, a comparative analysis of different PV technologies and its development is summarized. The rest of the chapter aims at providing a comprehensive analysis of solar radiation measurement and modelling techniques to assess the availability of solar radiation at different locations. The chapter presents comprehensive information for solar energy engineers, architects and other practitioners.
Topology for cascaded multilevel inverter

This study presents a topology for cascaded multilevel inverter (MLI) Each module is made up of H and half bridges, two isolated equal dc sources and a bidirectional auxiliary circuit. One leg of the H bridge and the half bridge are cut and the corresponding terminals are connected to the both ends of an equal split dc source. The free ends of the half bridge are connected together to form a common output node of the inverter. The auxiliary circuit is inserted between the midpoint of the split dc sources and this very output node. The output point of the uncut leg of the H bridge forms the remaining output node. With this circuit arrangement, proper control of the switches in the bridges and the auxiliary circuit, in each cascaded cell, can produce nine output voltage levels. A comparison is made between the proposed inverter, classical CHB and some of the recent developed MLI topologies with respect to specified figure of merits, as well as the per unit power losses. For two cascaded modules, simulation and experimental verifications are carried out on the proposed inverter topology for an R L load; adequate results are presented.
Topology Aware Fully Convolutional Networks for Histology Gland Segmentation
Venue: MICCAI

The recent success of deep learning techniques in classification and object detection tasks has been leveraged for segmentation tasks. However, a weakness of these deep segmentation models is their limited ability to encode high level shape priors, such as smoothness and preservation of complex interactions between object regions, which can result in implausible segmentations. In this work, by formulating and optimizing a new loss, we introduce the first deep network trained to encode geometric and topological priors of containment and detachment. Our results on the segmentation of histology glands from a dataset of 165 images demonstrate the advantage of our novel loss terms and show how our topology aware architecture outperforms competing methods by up to 10 in both pixel level accuracy and object level
Development and Testing of Naturally Buckling Steel Braces

Steel concentrically braced frames inherently provide great strength and stiffness, and are widely used for seismic resisting systems in buildings. These include conventional buckling braced frames and buckling restrained braced frames. Although the latter can prevent brace buckling and provide ductile behavior, both types of braces provide no hysteretic damping at small drift levels and offer very limited post yielding stiffness. This study proposes a new type of steel brace with a novel mechanism the naturally buckling brace (NBB) The design combines high strength and low yield steels arranged in parallel with a specified initial eccentricity along the brace length, providing ductile seismic behavior. Six tests of various NBB models subjected to cyclic loading were conducted to examine the seismic performance of the proposed NBB. Two specimens out of the six achieved the characteristics intended for NBB. The test results showed that the NBB specimens with appropriate design parameters could achieve early yielding, or hysteretic damping, from around 0.11% story drift and prevent local buckling as well as deformation concentration up to a very large story drift (greater than 3% A single NBB would provide an asymmetric hysteretic behavior, a large post yielding stiffness in tension, and a ductile performance with stable energy dissipation. Further systematic studies of NBBs are needed to comprehensively evaluate the capacities and limitations of the NBBs, including the reliability of performance with repeated tests.
Sampling optimization for networked underwater gliders
Venue: OCEANS 2016 Shanghai

This paper focuses on coverage sampling over a given region by a fleet of underwater gliders. The coverage performance is evaluated by the observing uncertainty performed by Objective Analysis (OA) Deployed gliders are commonly restricted to move through transects along which the data collected are convenient for data assimilation. We optimize the initial location and the initial heading of each glider that are deployed into an interested region by using Generic Algorithm (GA) Two cases of environmental sampling tasks are used for verifying the proposed approach.
Constrained differential evolution optimization for underwater glider path planning in sub mesoscale eddy sampling
Venue: Appl. Soft Comput.

Graphical abstractDisplay Omitted HighlightsAn approach for tackling constrained underwater glider sub mesoscale path planning.The feasible path area is defined as a corridor around the border of an ocean eddy.A new configuration of constrained differential evolution algorithm and mechanisms.A new benchmark set with 28 different specialized scenarios defines the challenge.Per scenario and aggregated performance analyses of different mechanism's new configurations. This paper presents an approach for tackling constrained underwater glider path planning (UGPP) where the feasible path area is defined as a corridor around the border of an ocean eddy. The objective of the glider here is to sample the oceanographic variables more efficiently while keeping a bounded trajectory. Therefore, we propose a solution based on differential evolution (DE) algorithm mechanisms, including in its configuration self adaptation of control parameters, population size reduction, constraint handling with adjustment, and mutation based on elitistic best vector. Different aspects of this DE configuration are studied for the constrained UGPP challenge, on a prepared benchmark set comprised of 28 different specialized scenarios. The DE configurations were tested over a benchmark set over 51 independent runs for each DE configuration aspect. Comparison and suitability for the combination of these mechanisms is reported, through the per scenario and aggregated statistical performance differences, including different constraint handling definition strategies, different DE mutation strategies' configurations, and population sizing parameterizations. Our proposed solution outranked all other compared algorithms, keeping a trajectory within the limits with 100% success rate in all physically feasible scenarios; on average, it improved the randomly initialized trajectories fitness by roughly 50% even reaching perfect fitness (all around, 360 degree eddy corridor sampling) in some scenarios.
Stress Management and Job Performance in the Industries Sector of Mali

Work has severaldefinitions. However it is defined as an activity that is to perform a specifictask in a given environment social, organizational and production in a given time and for compensation. The first component of work is the physical environment in which it takes place. In this set are distinguished on one hand the atmosphere and the other hand factors of production. To qualitatively assess work, it's determined by its performance. The stress is positive because of the finished product, marketing, margins and earnings. This means that the leaders of the industry manage well the micro and macroeconomics; shareholders ensure financial and strategic activity that bankers give the best loans and credits (heritage, Finance, strategy) that references to grant the delivery inputs of guarantee (economics, Finance, strategy) conditions take account of sociability, liquidity, sector risk, strength of the business, its future and the competence of its leaders. The stress is negative in an industry if it has increased internal and international competition; the emergence of substitute products; the loss of an important client or his bankruptcy; the bankruptcy of a bank with which the industry had preferred financial relations; the emergence of new regulations concerning safety and the protection of the environment in which the industry did not; the decline continues to the listing on the stock exchange; the rotation of stocks and different clients of the industry standard; the financing of investments by operation of repeated losses of operating resources; the impossibility of renewal of credit stress is a reaction to physical or psychological constraints. It can highlight different sources of occupational stress investments sources at work (working conditions, urgency of the time etc. Ambiguities and overload conflicts of roles of responsibilities (several suicide in French companies) career too or no promotion, lack of job security, ambition thwarted, difficult professional relationship with supervisor, colleagues, subordinates, difficulties of delegation of authority, organizational climate: no or limited participation in the process of decisions, restrictions on the power of decisions (budget) family and personal life can also be a source of stress.
The Most Ancient Greek Manuscripts of the Ladder of John Climacus

The Byzantine hand written tradition of the Ladder of Divine Ascent has poorly been studied. The first step in this direction should be the systematic description of all surviving Greek manuscripts of this book. According to the counting of the author, not less than 511 Greek manuscripts from the eighth to the nineteenth century with text of the Ladder were kept. This article is dedicated to the 35 most ancient books, dated from 8th to 10th century. The most ancient Greek manuscripts of the Ladder are available in the libraries of not less than 8 countries (Italy, Greece, Egypt, Russia, England, Germany, France and Israel (Jerusalem)
Engagement, Flow, Self Efficacy, and Eustress of University Students: A Cross National Comparison Between the Philippines and Argentina
Venue: The Journal of psychology

This study examined how self efficacy, eustress, and flow interact with academic engagement. First, it aimed to test a theoretical model that proposes that self efficacy and eustress promote both flow and engagement and that, in turn, the state of flow promotes academic engagement in undergraduate student. We hypothesized that the theoretical model would be invariant for two countries: the Philippines and Argentina. Secondly, this research aimed to compare the levels of self efficacy, eustress, study flow and academic engagement experiences in students from both countries. One hundred seventy six Filipinos and 171 Argentinean students participated in the study by completing inventories using the Utrecht Student Engagement Scale (Schaufeli, Martinez, et al. 2002) Optimal Experience Survey (Mesurado, 2008) Self efficacy Scale (O'Sullivan, 2011) and Eustress Scale (O'Sullivan, 2011) Results show that the theoretical model fits the data well in both countries and is invariant across the Philippines and Argentina. Self efficacy has a positive effect on flow and engagement, whereas eustress has a significant positive relationship with flow but is not directly associated with engagement. However, eustress has an indirect effect, through flow, on student engagement. On the other hand, there are different levels of engagement, flow, self efficacy, and eustress. Argentinean students scored higher on absorption, dedication, self efficacy, and flow. Filipino students, meanwhile, scored higher on eustress.
Subfield profitability analysis reveals an economic case for cropland diversification

Public agencies and private enterprises increasingly desire to achieve ecosystem service outcomes in agricultural systems, but are limited by perceived conflicts between economic and ecosystem service goals and a lack of tools enabling effective operational management. Here we use Iowa an agriculturally homogeneous state representative of the Maize Belt to demonstrate an economic rationale for cropland diversification at the subfield scale. We used a novel computational framework that integrates disparate but publicly available data to map ~3.3 million unique potential management polygons (9.3 Mha) and reveal subfield opportunities to increase overall field profitability. We analyzed subfield profitability for maize/soybean fields during 2010 2013 four of the most profitable years in recent history and projected results for 2015. While cropland operating at a loss of US$ 250 ha 1 or more was negligible between 2010 and 2013 at 18 000 190 000 ha <2% of row crop land) the extent of highly unprofitable land increased to 2.5 Mha, or 27% of row crop land, in the 2015 projection. Aggregation of these areas to the township level revealed 'hotspots' for potential management change in Western, Central, and Northeast Iowa. In these least profitable areas, incorporating conservation management that breaks even (e.g. planting low input perennials) into low yielding portions of fields could increase overall cropland profitability by 80% This approach is applicable to the broader region and differs substantially from the status quo of 'top down' land management for conservation by harnessing private interest to align profitability with the production of ecosystem services.
A hybrid multi criteria decision model for supporting customer focused profitability analysis
Venue: Ind. Manag. Data Syst.

Strategic analysis of customer profitability for assessing market segmentation and reconfiguring customer relationship management (CRM) activities remains the key factor for achieving high return on CRM investment. The purpose of this paper is to map the profit based ranking of corporate customers into the current market segments, with a view of determining the relative profitability of each market segment. This study develops a novel model that combines activity based costing (ABC) CRM, fuzzy analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) methods to evaluate strategically customer profitability and prioritizing corporate accounts. This case study airline company has invested heavily in CRM over the past seven years on integrating multi functional departments that touch customers. The airline operations management and marketing functions provide key inputs. Results of the hybrid model validate feasibility of the proposed model. The airline management makes use of the ranking results to optimize customer profitability by reconfiguring marketing programs, integrated schedule design, fleet assignment, maintenance routing, crew scheduling, and real time optimization of schedule recovery in the aftermath of disruptions or irregularities. The proposed model also directs the marketing function to customize service offerings and introduce appropriate service levels to engage customers of different segments for the purpose of maximizing corporate profitability. Significant amount of investment is necessary to design and implement the extensive CRM database and systems to assure customer data quality and availability so as to bear fruits in the proposed hybrid model. These data requirements can especially be a critical barrier for small to medium sized companies. This hybrid model is able to capitalize on the benefits of the ABC, CRM, fuzzy AHP, and TOPSIS methods and offset their deficiencies. Most importantly, it can be applied to various industries without complex modification. This study represents the first move to adopt the fuzzy AHP and TOPSIS methods to analyze the ABC and CRM data inputs of an airline company. In mapping the profit based ranking of corporate customers into the current market segments, the relative profitability of each market segment can be determined.
Dark Territory: The Secret History of Cyber War

A book that grips, informs, and alarms, finely researched and lucidly related. John le Carr As cyber attacks dominate front page news, as hackers join terrorists on the list of global threats, and as top generals warn of a coming cyber war, few books are more timely and enlightening than Dark Territory: The Secret History of Cyber War, by Slate columnist and Pulitzer Prizewinning journalist Fred Kaplan. Kaplan probes the inner corridors of the National Security Agency, the beyond top secret cyber units in the Pentagon, the "information warfare" squads of the military services, and the national security debates in the White House, to tell this never before told story of the officers, policymakers, scientists, and spies who devised this new form of warfare and who have been planningand (more often than people know) fightingthese wars for decades. From the 1991 Gulf War to conflicts in Haiti, Serbia, Syria, the former Soviet republics, Iraq, and Iran, where cyber warfare played a significant role, Dark Territory chronicles, in fascinating detail, a little known past that shines an unsettling light on our future.
Classification of cyber attacks in South Africa
Venue: 2016 IST Africa Week Conference

This paper introduces a classification scheme for the visual classification of cyber attacks. Through the use of the scheme, the impact of various cyber attacks throughout the history of South Africa are investigated and classified. The goal of this paper is to introduce a classification scheme that arranges attacks into different classes and sub classes, which is presented visually. To enhance the visual description, each class has a maximum of three sub classes, which can overlap. This classification scheme helps to show the diverse impacts of cyber attacks in South Africa. This method of classification can be used for the assessment of any cyber attack and to find similarities between attacks.
Oil palm expansion drives avifaunal decline in the Pucallpa region of Peruvian Amazonia

Oil palm is one of the world's most rapidly expanding crops, replacing humid forests across tropical regions. Studies examining the effect of this land conversion on biodiversity have tended to focus predominantly on Southeast Asia, where the majority of the world's oil palm is produced. Because the Amazon possesses the greatest area of suitable land for oil palm expansion, oil palm is considered an emerging threat to Amazonian biodiversity. This is the first study to examine how oil palm agriculture affects avian diversity within the context of Western Amazonia. We used mist nets to conduct avifaunal surveys of forest and oil palm habitat in the Pucallpa region of Peruvian Amazonia. Bird species richness, species evenness, and overall abundance were all significantly higher in the forest than in oil palm habitat. Strikingly, less than 5% of all captured species were common to both forest and oil palm habitat. The species absent from the oil palm plantations were disproportionately habitat specialists, forest interior birds, birds with high sensitivity to disturbance, and insectivores and frugivores. The results suggest that oil palm is particularly poor habitat for Amazonian birds, and that the species that are persist on them are of lower conservation value. Given the apparent lack of diversity on oil palm plantations, preventing further conversion of forests to oil palm should be prioritized.