nils-herrmann/clean_scirepeval huggingface dataset:
Aegle marmelos Mediated Green Synthesis of Different Nanostructured Metal Hexacyanoferrates: Activity against Photodegradation of Harmful Organic Dyes
Venue: Scientifica

Prussian blue analogue potassium metal hexacyanoferrate (KMHCF) nanoparticles Fe4[Fe(CN)6]3 (FeHCF) K2Cu3[Fe(CN)6]2 (KCuHCF) K2Ni[Fe(CN)6]*3H2O (KNiHCF) and K2Co[Fe(CN)6] (KCoHCF) have been synthesized using plant based biosurfactant Aegle marmelos (Bael) and water as a green solvent. It must be emphasized here that no harmful reagent or solvent was used throughout the study. Plant extracts are easily biodegradable and therefore do not cause any harm to the environment. Hence, the proposed method of synthesis of various KMHCF nanoparticles followed a green path. The synthesized nanoparticles were characterized by powder X ray diffraction (PXRD) Field Emission Scanning Electron Microscopy (FE SEM) Transmission Electron Microscopy (TEM) and Fourier Transform Infrared Spectroscopy (FT IR) MHCF nanoparticles were used for the photocatalytic degradation of toxic dyes like Malachite Green (MG) Eriochrome Black T (EBT) Methyl Orange (MO) and Methylene Blue (MB) Under optimized reaction conditions, maximum photocatalytic degradation was achieved in case of KCuHCF nanoparticles mediated degradation process (MG: 96.06% EBT: 83.03% MB: 94.72% and MO: 63.71% followed by KNiHCF (MG: 95% EBT: 80.32% MB: 91.35% and MO: 59.42% KCoHCF (MG: 91.45% EBT: 78.84% MB: 89.28% and MO: 58.20%
Magnetic thin film deposition with pulsed magnetron sputtering: deposition rate and film thickness distribution

The goal of conducted study was an experimental determining the relations between technological parameters of magnetron sputtering process on deposition rate (R) and thickness uniformity of magnetic thin films. Planar Ni79Fei6Mo5 target with a diameter of 100 mm was sputtered in argon (Ar) atmosphere. Deposition rate was measured in a function of gas pressure, target power and target substrate distance. The highest value of R280 nmmin 1. The obtained results in deposition rate of magnetic film were compared to deposition rate of cooper (Cu) aluminum (Al) titanium (Ti) and titanium oxide (TiOx) and the deposition rate of Ni Fe alloy were higher that Al and Ti. The film thickness distribution was measured for radial distance from the target centre ranging up to 60 mm and target substrate distance ranging form 70 to 115 mm. Among others it was stated that for the larger value of target substrate distance the larger uniform of film thickness are obtained.
Patrons, clients, designers and developers: the Jewish contribution to secular: building in England

Mumford, the American architectural critic, once remarked that the influence exercised by Jews, as by Huguenots, was out of all proportion to their numbers.1 He was of course repeating a truth noted by many. Although the Jewish minority in the United Kingdom amounts to a mere half per cent of the population, we have seen Jewish MPs in excess of 5 per cent returned to postwar parliaments. The Daily Telegraph, Reuter's despatches, belisha beacons, the Shell logo and the regimental march of the Royal Marines are now deemed thoroughly British, their Jewish origins forgotten. While the contributions of English Jews in the fields of public life, phi? lanthropy, medicine, science, philosophy, literature, scholarship, industry, banking and commerce are well documented, their influence on the built environment of English towns and on individual buildings (and some of their contents) is perhaps not so well known. Such influence may be exer? cised in several ways: as designer, patron, client, promoter, developer or financier of buildings or groups of buildings. In this paper I exclude the specifically Jewish built heritage dealt with in my previous publications since 1954.2
Work engagement, job satisfaction, and turnover intentions: A comparison between supervisors and line level employees

This study aims to investigate the influence of employee positions (supervisor vs line level employee) on work related variables (e.g. work engagement, job satisfaction and turnover intentions)  Data were collected from line level employees and supervisors of 29 mid to up scale hotels. A series of one way ANCOVA were performed to test the position differences in work engagement, job satisfaction and turnover intentions. Hierarchical regression analyses were conducted to examine the moderating role of employees' positions on the relationships between those variables.  Supervisors have significantly higher work engagement and lower turnover intentions than line level employees, whereas job satisfaction does not differ across positions. Employee positions significantly moderate the relationship between absorption and job satisfaction, and the relationship between dedication and turnover intentions.  This study provides an in depth analysis for hotel managers to capture work related factors (i.e. work engagement, job satisfaction and turnover intentions) across employee positions. Dedication is the primary barometer that significantly leads to job satisfaction and reduced turnover intentions compared to vigor and absorption. Although job satisfaction may be boosted by improving employee work engagement (i.e. vigor, dedication and absorption) increasing absorption is not an effective solution to increase supervisors' job satisfaction. Hotel managers need to carefully monitor supervisors' levels of dedication, given its focal impact on turnover intentions.  This study is one of the first attempts to examine the differences between line level employees' and supervisors' work engagement (i.e. vigor, dedication and absorption) and its consequences (i.e. job satisfaction and turnover intentions) Findings highlight the unique influence of the individual dimension of work engagement on job satisfaction and turnover intentions. This study reveals the moderating effect of employee positions on the links between engagement dimensions and consequences.
The impact of knowledge management on job satisfaction
Venue: J. Knowl. Manag.

This paper aims to propose that knowledge management (KM) could be a way to nurture job satisfaction and examine how KM can increase individual employees' job satisfaction.  A theoretical model concerning the connections between five facets of KM (knowledge acquisition, knowledge sharing, knowledge creation, knowledge codification and knowledge retention) and job satisfaction is proposed. It is then empirically tested with a structural equation modelling partial least squares analysis of a survey data set of 824 observations, collected from the members of a Finnish municipal organisation.  Existence of KM processes in one's working environment is significantly linked with high job satisfaction. Especially intra organisational knowledge sharing seems to be a key KM process, promoting satisfaction with one's job in most employee groups. Interestingly, significant knowledge based promoters of job satisfaction differ as a function of job characteristics. Practical implications KM has a strong impact on employee job satisfaction, and therefore, managers are advised to implement KM activities in their organisations, not only for the sake of improving knowledge worker performance but also for improving their well being at work.  This paper produces knowledge on a type of consequence of KM that has been largely unexplored in previous research, individual job satisfaction. Also, it promotes moving the KM literature to the next stage where the impact of KM practices is not explored as a "one size fits all" type of a phenomenon, but rather as a contingent and contextual issue.
The role of supervisory behavior, job satisfaction and organizational commitment on employee turnover

Few studies have presented structural turnover models including both job satisfaction and organizational commitment measures. Recent research suggests that perceived supervisor leadership may contribute to employee well being, job satisfaction and organizational commitment. This study proposes a structural turnover intention model including supervisory behavior (person oriented and task oriented dimensions) job satisfaction and organizational commitment. Furthermore, the study proposes to test whether this model fits in both small and medium sized enterprises and in large enterprises. The sample included 763 employees from different types of organizations who have completed a measure of their perception of their supervisoraEUR(tm)s behavior and self administrated measures of job satisfaction, organizational commitment and turnover intention. Results show that person oriented leadership behavior affects turnover intentions through job satisfaction and organizational commitment more than task oriented leadership behavior. Only organizational commitment had a direct effect in explaining turnover intention. Finally, results indicate that the model is applicable both in small and medium sized enterprises and large enterprises.
How can core self evaluations influence job burnout? The key roles of organizational commitment and job satisfaction
Venue: Journal of health psychology

This study aimed to explore how core self evaluations influenced job burnout and mainly focused on the confirmation of the mediator roles of organizational commitment and job satisfaction. A total of 583 female nurses accomplished the Core Self Evaluation Scale, Organizational Commitment Scale, Minnesota Satisfaction Questionnaire, and Maslach Burnout Inventory General Survey. The results revealed that core self evaluations, organizational commitment, job satisfaction, and job burnout were significantly correlated with each other. Structural equation modeling indicated that core self evaluations can significantly influence job burnout and are completely mediated by organizational commitment and job satisfaction.
Transformational leadership, empowerment, and job satisfaction: the mediating role of employee empowerment
Venue: Human Resources for Health

BackgroundRecent studies have revealed that nursing staff turnover remains a major problem in emerging economies. In particular, nursing staff turnover in Malaysia remains high due to a lack of job satisfaction. Despite a shortage of healthcare staff, the Malaysian government plans to create 181 000 new healthcare jobs by 2020 through the Economic Transformation Programme (ETP) This study investigated the causal relationships among perceived transformational leadership, empowerment, and job satisfaction among nurses and medical assistants in two selected large private and public hospitals in Malaysia. This study also explored the mediating effect of empowerment between transformational leadership and job satisfaction.MethodsThis study used a survey to collect data from 200 nursing staff, i.e. nurses and medical assistants, employed by a large private hospital and a public hospital in Malaysia. Respondents were asked to answer 5 point Likert scale questions regarding transformational leadership, employee empowerment, and job satisfaction. Partial least squares structural equation modeling (PLS SEM) was used to analyze the measurement models and to estimate parameters in a path model. Statistical analysis was performed to examine whether empowerment mediated the relationship between transformational leadership and job satisfaction.ResultsThis analysis showed that empowerment mediated the effect of transformational leadership on the job satisfaction in nursing staff. Employee empowerment not only is indispensable for enhancing job satisfaction but also mediates the relationship between transformational leadership and job satisfaction among nursing staff.ConclusionsThe results of this research contribute to the literature on job satisfaction in healthcare industries by enhancing the understanding of the influences of empowerment and transformational leadership on job satisfaction among nursing staff. This study offers important policy insight for healthcare managers who seek to increase job satisfaction among their nursing staff.
Renewable and sustainable bioenergy production from microalgal co cultivation with palm oil mill effluent (POME) A review

Sustainable and cost effective ways to produce renewable energy from biomass have generated considerable interest. Palm oil industries generates huge amount of waste. From one tonne of processed fresh fruit bunches (FFB) different types of wastes are generated which includes empty fruit bunch (EFB) (23% mesocarp fiber (12% shell (5% and palm oil mill effluent (POME) (60% POME has a high chemical and biochemical oxygen demand and mineral content such as nitrogen and phosphorous which can cause severe pollution to the environment. This can be a great nutrient for algal cultivation whilst remediating effluent and generating biomethane through anaerobic digestion. Algae capable of producing lipids and hydrocarbons with their photosynthetic abilities are among potential candidates for bioenergy generation. The harvested microalgal biomass can be used to produce bioethanol through fermentation. An integrated wastewater treatment and renewable bioenergy production would be an added benefit to the oil palm industry.
Effectiveness of Roundtable on Sustainable Palm Oil (RSPO) for reducing fires on oil palm concessions in Indonesia from 2012 to 2015

Fire is a common tool for land conversion and management associated with oil palm production. Fires can cause biodiversity and carbon losses, emit pollutants that deteriorate air quality and harm human health, and damage property. The Roundtable on Sustainable Palm Oil (RSPO) prohibits the use of fire on certified concessions. However, efforts to suppress fires are more difficult during El Nino conditions and on peatlands. In this paper, we address the following questions for oil palm concessions developed prior to 2012 in Sumatra and Kalimantan, the leading producers of oil palm both within Indonesia and globally: (1) for the period 2012 2015, did RSPO certified concessions have a lower density of fire detections, fire ignitions, or 'escaped' fires compared with those concessions that are not certified? and (2) did this pattern change with increasing likelihood of fires in concessions located on peatland and in dry years? These questions are particularly critical in fuel rich peatlands, of which approximately 46% of the area was designated as oil palm concession as of 2010. We conducted propensity scoring to balance covariate distributions between certified and non certified concessions, and we compare the density of fires in certified and non certified concessions using Kolmogorov Smirnov tests based on moderate resolution imaging spectroradiometer Active Fire Detections from 2012 2015 clustered into unique fire events. We find that fire activity is significantly lower on RSPO certified concessions than non RSPO certified concessions when the likelihood of fire is low (i.e. on non peatlands in wetter years) but not when the likelihood of fire is high (i.e. on non peatlands in dry years or on peatlands) Our results provide evidence that RSPO has the potential to reduce fires, though it is currently only effective when fire likelihood is relatively low. These results imply that, in order for this mechanism to reduce fire, additional strategies will be needed to control fires in oil palm plantations in dry years and on peatlands.
Assessing the potential additionality of certification by the Round table on Responsible Soybeans and the Roundtable on Sustainable Palm Oil

Commodity crop expansion has increased with the globalization of production systems and consumer demand, linking distant socio ecological systems. Oil palm plantations are expanding in the tropics to satisfy growing oilseed and biofuel markets, and much of this expansion has caused extensive deforestation, especially in Asia. In Latin America, palm oil output has doubled since 2001, and the majority of expansion seems to be occurring on non forested lands. We used MODIS satellite imagery (250 m resolution) to map current oil palm plantations in Latin America and determined prior land use and land cover (LULC) using high resolution images in Google Earth. In addition, we compiled trade data to determine where Latin American palm oil flows, in order to better understand the underlying drivers of expansion in the region. Based on a sample of 342 032 ha of oil palm plantations across Latin America, we found that 79% replaced previously intervened lands (e.g. pastures, croplands, bananas) primarily cattle pastures (56% The remaining 21% came from areas that were classified as woody vegetation (e.g. forests) most notably in the Amazon and the Peten region in northern Guatemala. Latin America is a net exporter of palm oil but the majority of palm oil exports (70% stayed within the region, with Mexico importing about half. Growth of the oil palm sector may be driven by global factors, but environmental and economic outcomes vary between regions (i.e. Asia and Latin America) within regions (i.e. Colombia and Peru) and within single countries (i.e. Guatemala) suggesting that local conditions are influential. The present trend of oil palm expanding onto previously cleared lands, guided by roundtable certifications programs, provides an opportunity for more sustainable development of the oil palm sector in Latin America.
Which Regular Expression Patterns Are Hard to Match?
Venue: 2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS)

Regular expressions constitute a fundamental notion in formal language theory and are frequently used in computer science to define search patterns. In particular, regular expression matching and membership testing are widely used computational primitives, employed in many programming languages and text processing utilities. A classic algorithm for these problems constructs and simulates a non deterministic finite automaton corresponding to the expression, resulting in an O(m n) running time (where m is the length of the pattern and n is the length of the text) This running time can be improved slightly (by a polylogarithmic factor) but no significantly faster solutions are known. At the same time, much faster algorithms exist for various special cases of regular expressions, including dictionary matching, wildcard matching, subset matching, word break problem etc. In this paper, we show that the complexity of regular expression matching can be characterized based on its depth (when interpreted as a formula) Our results hold for expressions involving concatenation, OR, Kleene star and Kleene plus. For regular expressions of depth two (involving any combination of the above operators) we show the following dichotomy: matching and membership testing can be solved in near linear time, except for "concatenations of stars" which cannot be solved in strongly sub quadratic time assuming the Strong Exponential Time Hypothesis (SETH) For regular expressions of depth three the picture is more complex. Nevertheless, we show that all problems can either be solved in strongly sub quadratic time, or cannot be solved in strongly sub quadratic time assuming SETH. An intriguing special case of membership testing involves regular expressions of the form "a star of an OR of concatenations" e.g.  This corresponds to the so called word break problem, for which a dynamic programming algorithm with a runtime of (roughly) O(n m) is known. We show that the latter bound is not tight and improve the runtime to O(n m0.44.
A Survey on Regular Expression Matching for Deep Packet Inspection: Applications, Algorithms, and Hardware Platforms
Venue: IEEE Communications Surveys Tutorials

Deep packet inspection (DPI) is widely used in content aware network applications such as network intrusion detection systems, traffic billing, load balancing, and government surveillance. Pattern matching is a core and critical step in DPI, which checks the payload of each packet for known signatures (patterns) in order to identify packets with certain characteristics (e.g. malicious packets that carry viruses or worms) Regular expression is the major tool for signature description due to its powerful and flexible expressive ability. However, this flexibility also brings great challenges for efficient implementation in practice. Despite of hundreds to thousands of empirical proposals, wire speed matching for large scale regular expressions still remains a big challenge. The gap between the matching throughput and the link speed is widening with the ever increasing network link speed and pattern scale. This survey begins with a full scale application background of DPI and technical background of regular expression matching in order to provide a global view and essential knowledge for readers. We then analyze the challenges in regular expression matching originated from the state explosion of finite state automaton used for regular expression matching. The nature of state explosion is analyzed in details, and the state of the art solutions are grouped into categories of methods to relieve state expansion and methods to avoid state explosion, suggestions are also provided for building compact and efficient automata in different scenarios. Furthermore, proposals employing parallel platforms, including field programmable gate array, GPU, general multi processors, and ternary content addressable memory, to accelerate the matching process are introduced and thoroughly discussed. We also provide guidelines for efficient deployment for each of these platforms.
Exploring regular expression usage and context in Python
Venue: ISSTA

Due to the popularity and pervasive use of regular expressions, researchers have created tools to support their creation, validation, and use. However, little is known about the context in which regular expressions are used, the features that are most common, and how behaviorally similar regular expressions are to one another. In this paper, we explore the context in which regular expressions are used through a combination of developer surveys and repository analysis. We survey 18 professional developers about their regular expression usage and pain points. Then, we analyze nearly 4,000 open source Python projects from GitHub and extract nearly 14,000 unique regular expression patterns. We map the most common features used in regular expressions to those features supported by four major regex research efforts from industry and academia: brics, Hampi, RE2, and Rex. Using similarity analysis of regular expressions across projects, we identify six common behavioral clusters that describe how regular expressions are often used in practice. This is the first rigorous examination of regex usage and it provides empirical evidence to support design decisions by regex tool builders. It also points to areas of needed future work, such as refactoring regular expressions to increase regex understandability and context specific tool support for common regex usages.
SIMD accelerated regular expression matching
Venue: DaMoN '16

String processing tasks are common in analytical queries powering business intelligence. Besides substring matching, provided in SQL by the like operator, popular DBMSs also support regular expressions as selective filters. Substring matching can be optimized by using specialized SIMD instructions on mainstream CPUs, reaching the performance of numeric column scans. However, generic regular expressions are harder to evaluate, being dependent on both the DFA size and the irregularity of the input. Here, we optimize matching string columns against regular expressions using SIMD vectorized code. Our approach avoids accessing the strings in lockstep without branching, to exploit cases when some strings are accepted or rejected early by looking at the first few characters. On common string lengths, our implementation is up to 2X faster than scalar code on a mainstream CPU and up to 5X faster on the Xeon Phi co processor, improving regular expression support in DBMSs.