bluuebunny/crossref_metadata_2025_split huggingface dataset:
Energy‐efficient task allocation for service provisioning in machine‐to‐machine systems
Authors: Skocir Pavle , Kusek Mario , Jezic Gordan 
Published: August 2017

SummaryMachine‐to‐Machine (M2M) communication systems enable autonomous communication between heterogeneous devices. In many applications, those devices are used to obtain measurements from sensors connected to them. By integrating M2M with the Internet of things paradigm, sensors and the data they obtain can be easily accessed via Internet infrastructure. This novelty, along with the advancement of processing power on small devices and the possibility to connect more sensors to one sensing device, poses new challenges and opens new opportunities in the area. This paper presents an algorithm and a protocol devised for task allocation to nodes of the M2M architecture where M2M devices are battery powered. The presented mechanism tackles some of the identified challenges within the area. First challenge is to determine the right node for performing data analysis. Certain data analysis tasks can be performed on device, instead of only on servers, which is a traditional approach. Another challenge is to relate the process of obtaining measurements with user needs, i.e. to collect data only when users have interest in it. The last identified challenge is to extend lifetime of services with higher priority, instead of prolonging lifetime of all devices within the network. Adoption of the proposed mechanism is justified on specific services in a smart home environment. Copyright © 2017 John Wiley & Sons, Ltd.
Preschool children's response to behavioural parent training and parental predictors of outcome in routine clinical care
Authors: van der Veen‐Mulders Lianne , Hoekstra Pieter J. , Nauta Maaike H. , van den Hoofdakker Barbara J. 
Published: August 2017

ObjectiveTo investigate the effectiveness of behavioral parent training (BPT) for preschool children with disruptive behaviours and to explore parental predictors of response.MethodsParents of 68 preschool children, aged between 2.7 and 5.9 years, participated in BPT. We evaluated the changes in children's behaviour after BPT with a one group pretest–posttest design, using a waiting period for a double pretest. Outcome was based on parents' reports of the intensity and number of behaviour problems on the Eyberg Child Behavior Inventory. Predictor variables included parents' attention‐deficit/hyperactivity disorder symptoms, antisocial behaviours, and alcohol use, and maternal parenting self‐efficacy and disciplining.ResultsMother‐reported child behaviour problems did not change in the waiting period but improved significantly after BPT (d = 0.63). High levels of alcohol use by fathers and low levels of maternal ineffective disciplining were each associated with somewhat worse outcome.ConclusionsBPT under routine care conditions clearly improves disruptive behaviours in preschool children. Mothers who consider themselves as inadequate in disciplining and mothers whose partners do not consume high levels of alcohol report the largest improvements.
Different aspects of emotional intelligence of borderline personality disorder
Authors: Peter Mathell , Arntz Arnoud R. , Klimstra Theo , Vingerhoets Ad J.J.M. 
Published: August 2017

ObjectivesThe present study investigated deficiencies in different components of emotional intelligence in borderline personality disorder (BPD).MethodThe Mayer–Salovey–Caruso Emotional Intelligence Test (MSCEIT) and the Emotional Quotient Inventory (EQ‐i) were used to assess EI dimensions. BPD patients (N = 85; 69 women; M = 33.6 years) were compared with Cluster C personality disorder (PD) patients (N = 39; 23 women; M = 36.6 years) and nonpatients (N = 69; 44 women; M = 35.6 years).ResultsCompared to the Cluster C PD patients and the nonpatient group, BPD patients displayed only deficits in their ability to understand emotions as measured with the Mayer–Salovey–Caruso Emotional Intelligence Test. The Emotional Quotient Inventory only revealed deficits in stress management in BPD patients compared to Cluster C PD patients.ConclusionsOur findings suggest that BPD patients have the ability to regulate emotions effectively, but they subjectively experience deficits in emotion regulation and therefore may not use this ability when they need it.
Comparing the acceptability of a positive psychology intervention versus a cognitive behavioural therapy for clinical depression
Authors: Lopez‐Gomez Irene , Chaves Covadonga , Hervas Gonzalo , Vazquez Carmelo 
Published: August 2017

There is growing evidence on the efficacy of positive psychology interventions (PPI) to treat clinical disorders. However, very few studies have addressed their acceptability. The present study aimed to analyse 2 key components of acceptability (i.e., client satisfaction and adherence to treatment) of a new PPI programme, the Integrative Positive Psychological Intervention for Depression (IPPI‐D), in comparison to a standard cognitive behavioural therapy (CBT) programme in the treatment of clinical depression. One hundred twenty‐eight women with a DSM‐IV diagnosis of major depression or dysthymia were allocated to a 10‐session IPPI‐D or CBT group intervention condition. Results showed that both interventions were highly acceptable for participants. Attendance rates were high, and there were no significant differences between conditions. However, the IPPI‐D condition showed significantly higher client satisfaction than the CBT condition. Moreover, acceptability did not differ based on participants' severity of symptoms, regardless of condition. These findings encourage further investigations of the applicability of PPI in clinical settings in order to broaden the range of acceptable and suitable therapies for depressed patients.Key Practitioner Message

This study sheds light on the client satisfaction and adherence to a positive intervention.
For participants, positive psychology interventions (PPI) may be more satisfactory than CBT as PPI are framed within a positive mental health model and, consequently, may reduce the risk of stigmatization
Because acceptability of treatments and preferences may affect the efficacy of treatments, this study provides an excellent opportunity to offer professionals more therapeutic options to tailor treatments to clients' needs and expectations
Fabrication of Lead‐Free (CH3NH3)3Bi2I9 Perovskite Photovoltaics in Ethanol Solvent
Authors: Li Haijin , Wu Congcong , Yan Yongke , Chi Bo , Pu Jian , Li Jian , Priya Shashank 
Published: August 2017

AbstractThe toxicity of lead present in organohalide perovskites and the hazardous solvent systems used for their synthesis hinder the deployment of perovskite solar cells (PSCs). Herein, an environmentally friendly route toward bismuth‐based, lead‐free (CH3NH3)3Bi2I9 perovskites that utilize ethanol as the solvent is described. Using this method, dense and homogeneous microstructures were obtained, compared to the porous, rough microstructures obtained using dimethylformamide. Photovoltaic performances were enhanced, with an open‐circuit voltage of 0.84 V measured.
Variable kernel‐based computing algorithms for estimating sparse multipath channels
Authors: Yang Jie , Zhao Ruijie , Song Rongfang , Xiong Jian , Liang Yan , Luo Wang , Xu Li , Gui Guan 
Published: August 2017

SummaryAccurate channel estimation algorithms are required to mitigate the frequency‐selective fading in the broadband wireless communication systems. Many physical experiments revealed that finite impulsive responses are distributed as sparse in delayed time domain. Hence, the inherent sparse information can be exploited by state‐of‐the‐art computing algorithms, in order to improve channel accuracy. Existing computing algorithms, zero‐attracting recursive least square (ZA‐RLS) and reweighted ZA‐RLS (RZA‐RLS), have been developed to exploit channel sparsity. However, optimization theory implies that accuracy of the computing algorithms can be further improved to exploit more sparsity information. To further improve the estimation performance, this paper proposes a correntropy induced metric (CIM)‐penalized RLS (CIM‐RLS) based sparse channel estimation algorithm. Here, sparse constraint is performed by CIM function, while error constraint term is computed by RLS. In particular, Gaussian kernel is adopted for computing the CIM, and its variable kernel width (VKW) is computed for adaptively exploiting the channel sparsity. Monte Carlo simulation results are conducted to verify the proposed algorithm in different scenarios.
An agent‐based workflow scheduling mechanism with deadline constraint on hybrid cloud environment
Authors: Chang Yue‐Shan , Fan Chih‐Tien , Sheu Ruey‐Kai , Jhu Syuan‐Ru , Yuan Shyan‐Ming 
Published: August 2017

SummaryWith the advances of cloud computing, business and scientific‐oriented jobs with certain workflows are increasingly migrated to and run on a variety of cloud environments. These jobs are often with the property of deadline constraint and have to be completed within limited time. Therefore, to schedule a job with workflow (short for workflow) with deadline constraint is increasingly becoming a crucial research issue. In this paper, we, based on previous work, propose an agent‐based workflow scheduling mechanism to schedule workflows that are with deadline constraint into federated cloud environment.Design and MethodsWe add a workflow agent into the original framework to schedule the deadline‐constraint workflow. The workflow agent can smoothly schedule workflows to the cloud system according to their required resource and automatically monitor their execution. In order to accurately predict the execution time of each task to meet deadline constraint on certain VM with given resource, we inherit the use of rough set theory to estimate execution time of task in our previous work.Result and DiscussionA heuristic algorithm that is embedded into the workflow agent is also proposed because the problem had been shown to be NP‐complete. The mechanism also adopts dynamic job dispatching method to reduce the usage of VM and to improve the resource utilization. We also conducted experiments to evaluate the efficiency and effectiveness.ConclusionThe experimental results show that the prediction time is very close to the real execution time and can efficiently schedule multiple scientific workflows to meet the deadline constraints simultaneously.
Mitigating tail latency in IEEE 802.11–based networks
Authors: Kim Dohyung , Yeom Ikjun , Lee Tae‐Jin 
Published: August 2017

SummaryDelay sensitive applications are being actively introduced with the advent of 5G and vehicular communications, and such applications are very sensitive to tail latency. However, tail latency has not been seriously considered so far, especially in IEEE 802.11–based networks. Channel access is scheduled by random Contention Window (CW) values in IEEE 802.11–based networks, and the node with the larger CW waits longer, and it may even observe multiple transmissions from a single contending node, which results in a long latency tail. In this paper, we propose a new decentralized MAC called SynchMAC to mitigate this latency tail. In SynchMAC, every competing node transmits exactly one packet within a virtual time slot without a centralized controller. Using the proposed approach, the maximum channel access latency is bounded by T×2N, where T is the time required for transmitting a single packet (including Inter‐Frame Space and CW) and N is the number of competing nodes. To maximize the system throughput, the proposed scheme optimizes the value of T by considering the probability of successful transmission. Our simulation study shows that SynchMAC reduces the maximum access latency by up to 94% and 53% compared with the conventional IEEE 802.11 MAC and the comparative scheme, respectively, without degrading throughput performance. We also show that SynchMAC is easily extended to support weighted access.
Identification of specific markers for amphetamine synthesised from the pre‐precursor APAAN following the Leuckart route and retrospective search for APAAN markers in profiling databases from Germany and the Netherlands
Authors: Hauser Frank M. , Rößler Thorsten , Hulshof Janneke W. , Weigel Diana , Zimmermann Ralf , Pütz Michael 
Published: August 2017

Abstractα‐Phenylacetoacetonitrile (APAAN) is one of the most important pre‐precursors for amphetamine production in recent years. This assumption is based on seizure data but there is little analytical data available showing how much amphetamine really originated from APAAN. In this study, several syntheses of amphetamine following the Leuckart route were performed starting from different organic compounds including APAAN. The organic phases were analysed using gas chromatography–mass spectrometry (GC–MS) to search for signals caused by possible APAAN markers. Three compounds were discovered, isolated, and based on the performed syntheses it was found that they are highly specific for the use of APAAN. Using mass spectra, high resolution MS and nuclear magnetic resonance (NMR) data the compounds were characterised and identified as 2‐phenyl‐2‐butenenitrile, 3‐amino‐2‐phenyl‐2‐butenenitrile, and 4‐amino‐6‐methyl‐5‐phenylpyrimidine. To investigate their significance, they were searched in data from seized amphetamine samples to determine to what extent they were present in illicitly produced amphetamine. Data of more than 580 cases from amphetamine profiling databases in Germany and the Netherlands were used for this purpose. These databases allowed analysis of the yearly occurrence of the markers going back to 2009. The markers revealed a trend that was in agreement with seizure reports and reflected an increasing use of APAAN from 2010 on. This paper presents experimental proof that APAAN is indeed the most important pre‐precursor of amphetamine in recent years. It also illustrates how important it is to look for new ways to identify current trends in drug production since such trends can change within a few years.
Gender differences in disordered eating behaviors and body dissatisfaction among adolescents with type 1 diabetes: Results from diabetes MILES youth—Australia
Authors: Araia Emanuala , Hendrieckx Christel , Skinner Timothy , Pouwer Frans , Speight Jane , King Ross M. 
Published: August 2017

AbstractObjectiveTo examine gender differences in disordered eating behaviors (DEB) and body dissatisfaction in adolescents with type 1 diabetes. While evidence shows that female youth with type 1 diabetes are more prone to DEB compared to their peers without diabetes, little is known about male adolescents.MethodIn a national online survey, adolescents (13–19 years) with type 1 diabetes for ≥1 year completed the Diabetes Eating Problem Survey‐Revised (DEPS‐R), and the Body Mass Index Silhouette Matching Test (BMI‐SMT) and items on binge eating and insulin omission.ResultsAbout 477 adolescents (mean age 16 years; 62% females) completed the DEPS‐R and 431 the BMI‐SMT. The DEPS‐R total score was higher for females than males, with scores for females increasing with age. BMI, HbA1c, insulin omission, and binge‐eating frequency were associated moderately with DEPS‐R for both genders. On the BMI‐SMT, 88% of females wanted to be thinner. Of the males, 76% reported body dissatisfaction; however, only 43% expressed a desire for thinness with the remainder desiring a larger body size. DEPS‐R was positively associated with the discrepancy between perceived actual and ideal body size for both genders.DiscussionA large proportion of adolescents with type 1 diabetes, particularly females reported engaging in DEB. Similarly, high rates of body dissatisfaction were reported, though ideal body shape preferences differed by gender. Given the high levels of self‐reported DEB and gender‐based patterns of body dissatisfaction, future research needs to examine the effectiveness of routine screening of DEB and consider implementation of stepped care approaches.
Recovery of plant communities after ecological restoration of forestry‐drained peatlands
Authors: Haapalehto Tuomas , Juutinen Riikka , Kareksela Santtu , Kuitunen Markku , Tahvanainen Teemu , Vuori Hilja , Kotiaho Janne S. 
Published: August 2017

AbstractEcological restoration is expected to reverse the loss of biodiversity and ecosystem services. Due to the low number of well‐replicated field studies, the extent to which restoration recovers plant communities, and the factors underlying possible shortcomings, are not well understood even in medium term. We compared the plant community composition of 38 sites comprising pristine, forestry‐drained, and 5 or 10 years ago restored peatlands in southern Finland, with special interest in understanding spatial variation within studied sites, as well as the development of the numbers and the abundances of target species. Our results indicated a recovery of community composition 5–10 years after restoration, but there was significant heterogeneity in recovery. Plant communities farthest away from ditches were very similar to their pristine reference already 10 years after restoration. In contrast, communities in the ditches were as far from the target as the drained communities. The recovery appears to be characterized by a decline in the number and abundance of species typical to degraded conditions, and increase in the abundance of characteristic peatland species. However, we found no increase above the drained state in the number of characteristic peatland species. Our results suggest that there is a risk of drawing premature conclusions on the efficiency of ecological restoration with the current practice of short‐term monitoring. Our results also illustrate fine‐scale within‐site spatial variability in the degradation and recovery of the plant communities that should be considered when evaluating the success of restoration. Overall, we find the heterogeneous outcome of restoration observed here promising. However, low recovery in the number of characteristic species demonstrates the importance of prioritizing restoration sites, and addressing the uncertainty of recovery when setting restoration targets. It appears that it is easier to eradicate unwanted species than regain characteristic species by restoration.
A pantropical analysis of the impacts of forest degradation and conversion on local temperature
Authors: Senior Rebecca A. , Hill Jane K. , González del Pliego Pamela , Goode Laurel K. , Edwards David P. 
Published: August 2017

AbstractTemperature is a core component of a species' fundamental niche. At the fine scale over which most organisms experience climate (mm to ha), temperature depends upon the amount of radiation reaching the Earth's surface, which is principally governed by vegetation. Tropical regions have undergone widespread and extreme changes to vegetation, particularly through the degradation and conversion of rainforests. As most terrestrial biodiversity is in the tropics, and many of these species possess narrow thermal limits, it is important to identify local thermal impacts of rainforest degradation and conversion. We collected pantropical, site‐level (<1 ha) temperature data from the literature to quantify impacts of land‐use change on local temperatures, and to examine whether this relationship differed aboveground relative to belowground and between wet and dry seasons. We found that local temperature in our sample sites was higher than primary forest in all human‐impacted land‐use types (N = 113,894 daytime temperature measurements from 25 studies). Warming was pronounced following conversion of forest to agricultural land (minimum +1.6°C, maximum +13.6°C), but minimal and nonsignificant when compared to forest degradation (e.g., by selective logging; minimum +1°C, maximum +1.1°C). The effect was buffered belowground (minimum buffering 0°C, maximum buffering 11.4°C), whereas seasonality had minimal impact (maximum buffering 1.9°C). We conclude that forest‐dependent species that persist following conversion of rainforest have experienced substantial local warming. Deforestation pushes these species closer to their thermal limits, making it more likely that compounding effects of future perturbations, such as severe droughts and global warming, will exceed species' tolerances. By contrast, degraded forests and belowground habitats may provide important refugia for thermally restricted species in landscapes dominated by agricultural land.
RADseq dataset with 90% missing data fully resolves recent radiation of Petalidium (Acanthaceae) in the ultra‐arid deserts of Namibia
Authors: Tripp Erin A. , Tsai Yi‐Hsin Erica , Zhuang Yongbin , Dexter Kyle G. 
Published: August 2017

AbstractDeserts, even those at tropical latitudes, often have strikingly low levels of plant diversity, particularly within genera. One remarkable exception to this pattern is the genus Petalidium (Acanthaceae), in which 37 of 40 named species occupy one of the driest environments on Earth, the Namib Desert of Namibia and neighboring Angola. To contribute to understanding this enigmatic diversity, we generated RADseq data for 47 accessions of Petalidium representing 22 species. We explored the impacts of 18 different combinations of assembly parameters in de novo assembly of the data across nine levels of missing data plus a best practice assembly using a reference Acanthaceae genome for a total of 171 sequence datasets assembled. RADseq data assembled at several thresholds of missing data, including 90% missing data, yielded phylogenetic hypotheses of Petalidium that were confidently and nearly fully resolved, which is notable given that divergence time analyses suggest a crown age for African species of 3.6–1.4 Ma. De novo assembly of our data yielded the most strongly supported and well‐resolved topologies; in contrast, reference‐based assembly performed poorly, perhaps due in part to moderate phylogenetic divergence between the reference genome, Ruellia speciosa, and the ingroup. Overall, we found that Petalidium, despite the harshness of the environment in which species occur, shows a net diversification rate (0.8–2.1 species per my) on par with those of diverse genera in tropical, Mediterranean, and alpine environments.
Recent advances in capillary electrophoresis separation of monosaccharides, oligosaccharides, and polysaccharides
Authors: Mantovani Veronica , Galeotti Fabio , Maccari Francesca , Volpi Nicola 
Published: August 2017

AbstractThis article illustrates the basis and applications of methodologies for the analysis of simple and complex carbohydrates by means of CE. After a description of the most common and novel approaches useful for the analysis and characterization of carbohydrates, this review covers the recent advances in CE separation of monosaccharides, oligosaccharides, and polysaccharides. Various CE techniques are also illustrated for the study of carbohydrates derived from complex glyco‐derivatives such as glycoproteins and glycolipids, essential for biopharmaceutical and glycoproteomics applications as well as for biomarker detection. Most glycans have no significant UV absorption, and derivatization with fluorophore groups prior to separation usually results in higher sensitivity and an improved electrophoretic profile. We also discuss the recent applications and separations by CE of derivatized simple and more complex carbohydrates with different chromophoric active tags. Overall, this review aims to give an overview of the most recent state‐of‐the‐art techniques used in carbohydrate analysis by CE.