bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measuring the maturity of Indian small and medium enterprises for unofficial readiness for capability maturity model integration‐based software process improvement
Authors: Singh Ashima , Gill Sukhpal Singh 
Published: April 2020

AbstractEstablishing the maturity levels of ‐ Small and Medium Enterprises (SMEs) without Capability Maturity Model Integration (CMMI) certification has always been regarded as an extremely challenging task. Software process improvement (SPI) has targeted to monitor and improve software processes, thereby improving the software business. Although there is scientific interest in SPI, little attention has been specifically given to the exploration of maturity levels for non‐CMMI SMEs. The goal is to explore the effect of time on process maturity and maturity levels achieved informally or unofficially by SMEs that are not otherwise CMMI certified. To find out the maturity levels achieved informally, a CMMI‐DEV v1.3 based survey questionnaire is administered to Indian software SMEs. Time of establishment of SMEs and follow‐up of CMMI‐based processes and practices unofficially are used as two important parameters to decide upon process maturity and achievement of specific CMMI level informally. This paper has been successful in ascertaining the effect of time of establishment of SMEs and follow‐up of CMMI‐based processes on process maturity using proposed RuleML that advocates adoption of more than 70% of CMMI‐DEV v1.3 process area‐specific practices for an SME to be unofficially ready for CMMI‐based SPI initiatives. The findings manifest multidimensional aspects of unofficial readiness of SMEs for CMMI‐based SPI that can be used by relevant authorities to select SMEs for funding for SPI initiatives. Finally, the proposed work has been validated statistically using t‐test for CMMI Level II and Level III.
Solar desalination: Cases, synthesis, and challenges
Authors: Delgado William R. , Beach Timothy , Luzzadder‐Beach Sheryl 
Published: April 2020

AbstractDesalination will become an increasingly important water resource to supply a growing world population that will face greater water scarcity in the coming decades. Desalination processes are energy‐intensive and currently rely on fossil fuels that contribute to global warming and exacerbate the planet's water woes. Solar power, as a low‐carbon energy resource, can reduce desalination's environmental footprint. However, there are many logistical considerations to take into account when planning solar desalination projects. This paper examines six of these issues, which include: (a) the spatial distribution of solar energy and saline water, (b) modeling tools to measure the financial feasibility of solar powered desalination plants, (c) community approval, (d) interconnection policies for solar desalination plants connected to the regional grid, (e) combining solar energy with other renewable energy sources, and (f) potential carbon savings from switching to solar energy. The paper will conduct its analysis through four key case studies in El Paso, Texas, Abilene, Texas, Abu Dhabi, United Arab Emirates, and Denmark, Australia. The paper concludes with a discussion on how improved solar technology will further the economic prospects of solar desalination and an analysis of brine disposal options that include siting seawater desalination operations in waters with high circulation and explaining how brine harvesting could lead to useful economic mineral products such as sodium, chlorine, potassium, and magnesium.This article is categorized under:
Engineering Water > Sustainable Engineering of Water
Development and validation of forensically useful growth models for Central European population of Creophilus maxillosus L. (Coleoptera: Staphylinidae)
Authors: Frątczak-Łagiewska Katarzyna , Grzywacz Andrzej , Matuszewski Szymon 
Published: April 2020

AbstractThe hairy rove beetle, Creophilus maxillosus (Linnaeus) (Staphylinidae), is recognized for its use in forensic entomology. However, insufficient developmental data exist for the Central European population of this species. Accordingly, we studied the development of C. maxillosus at ten constant temperatures (10–32.5 °C). Based on these results, linear and nonlinear developmental models were created and validated. We also studied the effect of different homogenous diets (third-instar larvae or puparia of Calliphora sp. Robineau-Desvoidy or Lucilia sp. Robineau-Desvoidy (Diptera: Calliphoridae) or mix of first- and second-instar larvae of Necrodes littoralis (Linnaeus) (Coleoptera: Silphidae)) on the development and mortality of C. maxillosus. Average total development times ranged between 122.21 days at 15 °C and 22.18 days at 30 °C. Beetles reached the adult stage in seven out of ten temperatures (15–30 °C). No beetles reached the adult stage when fed with larvae of N. littoralis; their development times at first and second larval stage were also significantly longer than in other food conditions. When C. maxillosus larvae were fed with blowfly larvae, the highest mortality was observed at the pupal stage, as compared when they were fed with blowfly puparia—at the first larval stage. While validating thermal summation models, the highest age estimation errors were found for beetles bred at 10 and 12.5 °C (between 21 and 43% for all developmental events). Age estimation errors were on average higher for pupation and eclosion than hatching and first and second ecdyses. While validating the models with specimens fed with different diets, the highest errors were recorded for beetles fed with N. littoralis larvae (22% for the first ecdysis and 33% for the second ecdysis) and Lucilia sp. puparia (32% for pupation and 22% for eclosion). Implications for C. maxillosus use in forensic entomology are discussed.

Key Points• Development of the Central European population of C. maxillosus was studied at ten constant temperatures and using different homogenous diets.• Thermal summation models were validated with insects reared at different temperatures and fed with different diets.• Total development times ranged between 122 days at 15 °C and 22 days at 30 °C. Beetles reached the adult stage in seven temperatures (15–30 °C).• The highest age estimation errors were found for beetles bred at 10 and 12.5 °C (21–43%) and for beetles fed with Necrodes littoralis larvae (22–33%).• The lowest mortality was observed for beetles fed with Calliphora sp. and Lucilia sp. larvae. Estimation errors were generally low for beetles fed with blowfly larvae or Calliphora sp. puparia.
Associations of whole blood polyunsaturated fatty acids and insulin resistance among European children and adolescents
Authors: Marth Sarah , Börnhorst Claudia , Mehlig Kirsten , Russo Paola , Moreno Luis A. , De Henauw Stefaan , Veidebaum Toomas , Molnár Dénes , Tornaritis Michael , Risé Patrizia , Wolters Maike ,   on behalf of the IDEFICS and I.Family consortia
Published: April 2020

AbstractThis study aims to examine the association of whole blood n-3 and n-6 polyunsaturated fatty acids (PUFA) with insulin resistance (IR) in children. Whole blood fatty acids were measured in 705 children aged 2–9 years of the European IDEFICS/I.Family cohort using gas chromatography in units of weight percentage of all detected fatty acids (%wt/wt). IR was determined by the Homeostasis Model Assessment for IR (HOMA). Mixed effect models were used to assess the associations between selected baseline PUFA and HOMA z-scores at baseline and after 2- and 6-year follow-ups using models with basic and additional confounder adjustment as well as stratified by sex and weight status. In the basic model, α-linolenic (β = 1.46 SD/%wt/wt, p = 0.006) and eicosapentaenoic acid (β = 1.17 SD/%wt/wt, p = 0.001) were positively associated with baseline HOMA z-score. In the stratified analyses, α-linolenic acid was positively associated with HOMA z-score in girls only (β = 1.98 SD/%wt/wt, p = 0.006) and arachidonic acid was inversely associated with baseline HOMA in thin/normal-weight children (β = − 0.13 SD/%wt/wt, p = 0.0063). In the fully adjusted model, no statistically significant associations were seen.Conclusions: Our overall results do not indicate a protective role of higher blood n-3 PUFA or an adverse role of higher blood arachidonic acid proportion on the risk of IR.

What is Known:•Intervention studies reported a beneficial effect of n-3 PUFA supplementation on insulin resistance compared with placebo while observational studies in cildren are inconclusive.•Studies have shown a positive association of n-6 arachidonic acid and insulin resistance indicating an adverse role of arachidonic acid.

What is New:•Cross-sectional and longitudinal analyses based on circulating blood fatty acid concentrations in a large cohort of European children and adolescents.•Overall results do not support a protective role of n-3 PUFA or an adverse role of arachidonic acid in insulin resistance.
Preparation and properties of fly ash-based geopolymer concrete with alkaline waste water obtained from foundry sand regeneration process
Authors: Moni S M Fuad Kabir , Ikeora O. , Pritzel C. , Görtz B. , Trettin R. 
Published: April 2020

AbstractThe aim of the research was to investigate the influences of high alkaline content foundry sand regeneration wastes incorporated with fly ash in the production of geopolymer concrete. The fly ash-based geopolymer concrete was activated using alkaline solutions of sodium silicate and sodium hydroxide. The geopolymeric products were characterized using X-ray diffraction, scanning electron microscopy, Fourier-transform infrared spectroscopy and simultaneous thermal analysis. A higher compressive strength was observed in mechanical strengths test in the geopolymer and its respective foam concrete made of waste water in comparing to reference water (tap water). Furthermore, a packed arrangement and lower pore size distribution for both geopolymer and foam concrete were observed using nitrogen gas adsorption and mercury intrusion porosimetry, in contrast, to waste water and reference water.
Multi-generational genetic consequences of reinforcement in a bird metapopulation
Authors: Ranke Peter S. , Skjelseth Sigrun , Hagen Ingerid Julie , Billing Anna Maria , Pedersen Åsa Alexandra Borg , Pärn Henrik , Ringsby Thor Harald , Sæther Bernt-Erik , Jensen Henrik 
Published: April 2020

AbstractTranslocation of conspecific individuals to reduce extinction risk of small, isolated populations and prevent genetic depletion is a powerful tool in conservation biology. An important question is how the translocated individuals influence the long-term genetic composition of the recipient population. Here, we experimentally reinforced a house sparrow (Passer domesticus) population, and examined the impact of this translocation on allele frequencies, levels of heterozygosity and genetic differentiation over six cohorts. We found no permanent increase in the mean number of alleles across loci or levels of observed heterozygosity, but a few alleles private to the translocated individuals remained in the population and we found a short-term increase in heterozygosity. Consequently, genetic differentiation of the recipient population compared to the genetic composition prior to reinforcement was small. The limited genetic impact was due to combined effects of a small probability of establishment and low mating success for the translocated individuals, together with increased genetic drift in the recipient population. Our findings emphasize the importance of selection and genetic drift as forces that may decrease the genetic contribution of reinforcement, especially in small populations. Conservation managers should aim to improve habitat quality in the recipient population to reduce genetic drift following translocation and thereby avoid the need for continued reinforcement. Furthermore, by facilitating establishment success and selecting individuals expected to have high mating success, possibly indicated by sexually selected traits, genetic contribution of released individuals is increased which in turn will decrease reproductive skew and genetic drift.
Interpretation Bias in Online and Offline Social Environments and Associations with Social Anxiety, Peer Victimization, and Avoidance Behavior
Authors: Miers Anne C. , Sumter Sindy R. , Clark David M. , Leigh Eleanor 
Published: April 2020

Abstract
Background
In face-to-face (offline) social situations a tendency, or bias, to negatively interpret ambiguous situations is consistently related to social anxiety. Although social interactions increasingly occur over the Internet (online), our understanding of cognitive processes in online social situations and how they relate to social anxiety, social experiences, and behavior, is limited.

Methods
In a sample of 324 young people (18–25 years), the current study addressed this gap in two ways: by simultaneously investigating online and offline interpretation bias in relation to social anxiety; and examining the extent to which online interpretation bias predicts peer victimization and avoidance.

Results
In line with hypotheses, online and offline interpretation bias each correlated positively with social anxiety; the offline interpretation bias-social anxiety association was stronger. Regression analyses revealed unique associations between online interpretation bias and online peer victimization and avoidance, after controlling for social anxiety and offline interpretation bias.

Discussion
Findings suggest that cognitive behavioral interventions for social anxiety could be optimized through eliciting and testing negative social beliefs related to online social settings.

Conclusions
The current study’s results indicate the importance of studying online interpretation bias to further understand social anxiety in online social environments.
Bifurcation analysis for non-local design of a hybrid observer for the impulsive Goodwin’s oscillator
Authors: Yamalova Diana , Medvedev Alexander , Zhusubalyiev Zhanybai T. 
Published: April 2020

AbstractThe impulsive Goodwin’s oscillator is a mathematical model capturing the dynamics arising in a closed-loop system, where a third-order linear time-invariant plant is subject to an intrinsic pulse-modulated feedback. Originally, the model was motivated by pulsatile regulation in endocrine systems but also has other potential applications. The asymptotic estimation of the hybrid state of the impulsive Goodwin’s oscillator is considered in this paper. A hybrid observer makes use of the continuous plant output to correct the estimates of the state vector through two output error feedbacks: a continuous and a discrete one. When the hybrid state estimation error is zero, the observer is in a synchronous mode characterized by the firings of the impulses in the observer feedback and those of the plant occurring simultaneously. The synchronous mode thus corresponds to an equilibrium point of the hybrid state error dynamics. To guarantee asymptotic convergence of the observer to the synchronous mode, the basin of attraction of the equilibrium has to include all feasible initial deviations of the state estimates. To guarantee the above properties, a numerical observer design approach based on bifurcation analysis of a discrete map capturing the observer state transitions from one impulse firing to another is proposed and its efficacy is demonstrated in simulation.
Dust-to-Gas and Refractory-to-Ice Mass Ratios of Comet 67P/Churyumov-Gerasimenko from Rosetta Observations
Authors: Choukroun Mathieu , Altwegg Kathrin , Kührt Ekkehard , Biver Nicolas , Bockelée-Morvan Dominique , Drążkowska Joanna , Hérique Alain , Hilchenbach Martin , Marschall Raphael , Pätzold Martin , Taylor Matthew G. G. T. , Thomas Nicolas 
Published: April 2020

AbstractThis chapter reviews the estimates of the dust-to-gas and refractory-to-ice mass ratios derived fromRosettameasurements in the lost materials and the nucleus of 67P/Churyumov-Gerasimenko, respectively. First, the measurements byRosettainstruments are described, as well as relevant characteristics of 67P. The complex picture of the activity of 67P, with its extreme North-South seasonal asymmetry, is presented. Individual estimates of the dust-to-gas and refractory-to-ice mass ratios are then presented and compared, showing wide ranges of plausible values.Rosetta’s wealth of information suggests that estimates of the dust-to-gas mass ratio made in cometary comae at a single point in time may not be fully representative of the refractory-to-ice mass ratio within the cometary nuclei being observed.
Multi-source knowledge fusion: a survey
Authors: Zhao Xiaojuan , Jia Yan , Li Aiping , Jiang Rong , Song Yichen 
Published: April 2020

AbstractMulti-source knowledge fusion is one of the important research topics in the fields of artificial intelligence, natural language processing, and so on. The research results of multi-source knowledge fusion can help computer to better understand human intelligence, human language and human thinking, effectively promote the Big Search in Cyberspace, effectively promote the construction of domain knowledge graphs (KGs), and bring enormous social and economic benefits. Due to the uncertainty of knowledge acquisition, the reliability and confidence of KG based on entity recognition and relationship extraction technology need to be evaluated. On the one hand, the process of multi-source knowledge reasoning can detect conflicts and provide help for knowledge evaluation and verification; on the other hand, the new knowledge acquired by knowledge reasoning is also uncertain and needs to be evaluated and verified. Collaborative reasoning of multi-source knowledge includes not only inferring new knowledge from multi-source knowledge, but also conflict detection, i.e. identifying erroneous knowledge or conflicts between knowledges. Starting from several related concepts of multi-source knowledge fusion, this paper comprehensively introduces the latest research progress of open-source knowledge fusion, multi-knowledge graphs fusion, information fusion within KGs, multi-modal knowledge fusion and multi-source knowledge collaborative reasoning. On this basis, the challenges and future research directions of multi-source knowledge fusion in a large-scale knowledge base environment are discussed.
Is Non-Steroidal Anti-Inflammatory Therapy Non-Inferior to Antibiotic Therapy in Uncomplicated Urinary Tract Infections: a Systematic Review
Authors: Carey Matthew R. , Vaughn Valerie M. , Mann Jason , Townsend Whitney , Chopra Vineet , Patel Payal K. 
Published: April 2020

Abstract
Background
Amid growing antimicrobial resistance, there is an increasing focus on antibiotic stewardship efforts to reduce inappropriate antibiotic prescribing. In this context, novel approaches for treating infections without antibiotics are being explored. One such strategy is the use of non-steroidal anti-inflammatory drugs (NSAIDs) for uncomplicated urinary tract infections (UTIs). Therefore, we conducted a systematic review of randomized controlled trials to evaluate the rates of symptom resolution and infectious complications in adult women with uncomplicated UTIs treated with antibiotics versus NSAIDs.

Methods
We systematically searched PubMed, CINHAL, Scopus, Web of Science Core Collection, EMBASE, and ClinicalTrials.gov from inception until January 13, 2020, for randomized controlled trials comparing NSAIDs with antibiotics for treatment of uncomplicated UTIs in adult women. Studies comparing symptom resolution between groups were eligible. Two authors screened all studies independently and in duplicate; data were abstracted using a standardized template. Risk of bias was assessed using the Cochrane Collaboration tool.

Results
Five randomized trials that included 1309 women with uncomplicated UTI met inclusion criteria. Three studies (1130 patients) favored antibiotic therapy in terms of symptom resolution. Two studies (179 patients) found no difference between NSAIDs and antibiotics in terms of symptom resolution. Three studies reported rates of pyelonephritis, two of which found higher rates in patients treated with NSAIDs versus antibiotics. Between two studies that reported this outcome (747 patients), patients randomized to NSAIDs received fewer antibiotic prescriptions compared with those in the antibiotics group. Three studies were at low risk of bias, one had an unclear risk of bias, and one was at high risk of bias.

Discussion
For the outcomes of symptom resolution and complications in adult women with UTI, evidence favors antibiotics over NSAIDs.

Prospero
CRD42018114133
Microfluidic approaches for the analysis of protein–protein interactions in solution
Authors: Arter William E. , Levin Aviad , Krainer Georg , Knowles Tuomas P. J. 
Published: April 2020

AbstractExploration and characterisation of the human proteome is a key objective enabling a heightened understanding of biological function, malfunction and pharmaceutical design. Since proteins typically exhibit their behaviour by binding to other proteins, the challenge of probing protein-protein interactions has been the focus of new and improved experimental approaches. Here, we review recently developed microfluidic techniques for the study and quantification of protein–protein interactions. We focus on methodologies that utilise the inherent strength of microfluidics for the control of mass transport on the micron scale, to facilitate surface and membrane-free interrogation and quantification of interacting proteins. Thus, the microfluidic tools described here provide the capability to yield insights on protein–protein interactions under physiological conditions. We first discuss the defining principles of microfluidics, and methods for the analysis of protein–protein interactions that utilise the diffusion-controlled mixing characteristic of fluids at the microscale. We then describe techniques that employ electrophoretic forces to manipulate and fractionate interacting protein systems for their biophysical characterisation, before discussing strategies that use microdroplet compartmentalisation for the analysis of protein interactions. We conclude by highlighting future directions for the field, such as the integration of microfluidic experiments into high-throughput workflows for the investigation of protein interaction networks.
Machine Learning in Business Process Monitoring: A Comparison of Deep Learning and Classical Approaches Used for Outcome Prediction
Authors: Kratsch Wolfgang , Manderscheid Jonas , Röglinger Maximilian , Seyfried Johannes 
Published: April 2020

AbstractPredictive process monitoring aims at forecasting the behavior, performance, and outcomes of business processes at runtime. It helps identify problems before they occur and re-allocate resources before they are wasted. Although deep learning (DL) has yielded breakthroughs, most existing approaches build on classical machine learning (ML) techniques, particularly when it comes to outcome-oriented predictive process monitoring. This circumstance reflects a lack of understanding about which event log properties facilitate the use of DL techniques. To address this gap, the authors compared the performance of DL (i.e., simple feedforward deep neural networks and long short term memory networks) and ML techniques (i.e., random forests and support vector machines) based on five publicly available event logs. It could be observed that DL generally outperforms classical ML techniques. Moreover, three specific propositions could be inferred from further observations: First, the outperformance of DL techniques is particularly strong for logs with a high variant-to-instance ratio (i.e., many non-standard cases). Second, DL techniques perform more stably in case of imbalanced target variables, especially for logs with a high event-to-activity ratio (i.e., many loops in the control flow). Third, logs with a high activity-to-instance payload ratio (i.e., input data is predominantly generated at runtime) call for the application of long short term memory networks. Due to the purposive sampling of event logs and techniques, these findings also hold for logs outside this study.