bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unusual Case of Suicide With a Modified Trap Gun
Authors: Vadysinghe Amal , Dassanayake Prasanna , Wickramasinghe Medhani 
Published: March 2017

Introduction
Trap gun is an illegal, locally manufactured gun with a basic trip system used to hunt wild animals.

Case Report
The body of a 28-year-old man was found in the jungle in supine position with both legs apart. A trap gun was between the legs pointing toward the cranial side of the body. It had 2 free wires that were not connected together. There was no evidence of foul play.
The body had a single-entry wound (2.5-cm diameter) in the anterior chest, with blackening, burning, and tattooing. Six metal particles and nylon clothing material were embedded into soft tissue. No exit wound was found. Toxicology analysis reported an alcohol level of 72 mg/dL. The cause of death was multiple shrapnel injury to the chest at close to intermediate range by a single discharge from a trap gun. Circumstance was concluded as suicide.
Ballistic and firearm experts opined that an illegal, manually operated, battery-powered ignition device was used to ignite the gun powder.

Conclusion
We report the first case of suicide by a modified trap gun in literature.
Finding analytic stationary solutions to the chemical master equation by gluing state spaces at one or two states recursively
Authors: Meng X. Flora , Baetica Ania-Ariadna , Singhad Vipul , Murray Richard M. 
Published: March 2017

AbstractNoise is often indispensable to key cellular activities, such as gene expression, necessitating the use of stochastic models to capture its dynamics. The chemical master equation (CME) is a commonly used stochastic model that describes how the probability distribution of a chemically reacting system varies with time. Knowing analytic solutions to the CME can have benefits, such as expediting simulations of multiscale biochemical reaction networks and aiding the design of distributional responses. However, analytic solutions are rarely known. A recent method of computing analytic stationary solutions relies on gluing simple state spaces together recursively at one or two states. We explore the capabilities of this method and introduce algorithms to derive analytic stationary solutions to the CME. We first formally characterise state spaces that can be constructed by performing single-state gluing of paths, cycles or both sequentially. We then study stochastic biochemical reaction networks that consist of reversible, elementary reactions with two-dimensional state spaces. We also discuss extending the method to infinite state spaces and designing stationary distributions that satisfy user-specified constraints. Finally, we illustrate the aforementioned ideas using examples that include two interconnected transcriptional components and chemical reactions with two-dimensional state spaces.Subject AreasSystems biology, synthetic biology, biomathematics, bioengineering
Aperiodic neural activity is a better predictor of schizophrenia than neural oscillations
Authors: Peterson Erik J. , Rosen Burke Q. , Belger Aysenil , Voytek Bradley , Campbell Alana M. 
Published: March 2017

AbstractDiagnosis and symptom severity in schizophrenia are associated with irregularities across neural oscillatory frequency bands, including theta, alpha, beta, and gamma. However, electroencephalographic signals consist of both periodic and aperiodic activity characterized by the (1/fX) shape in the power spectrum. In this paper we investigated oscillatory and aperiodic activity differences between patients with schizophrenia and healthy controls during a target detection task. Separation into periodic and aperiodic components revealed that the steepness of the power spectrum better predicted group status than traditional band-limited oscillatory power in a classification analysis. Aperiodic activity also outperformed the predictions made using participants’ behavioral responses. Additionally, the differences in aperiodic activity were highly consistent across all electrodes. In sum, compared to oscillations the aperiodic activity appears to be a more accurate and more robust way to differentiate patients with schizophrenia from healthy controls.Significance statementUnderstanding the neurobiological origins of schizophrenia and identifying reliable and consistent biomarkers are of critical importance to improving treatment of that disease. Numerous studies have reported disruptions to neural oscillations in patients with schizophrenia. This has, in part, led to schizophrenia being characterized as a disease of disrupted neural coordination, reflected by changes in frequency band power. We report however that changes in the aperiodic signal can also predict clinical status. Unlike band-limited power though, aperiodic activity predicts status better than participants’ own behavioral performance and acts as a consistent predictor across all electrodes. Alterations in the aperiodic signal are consistent with well-established inhibitory neuron dysfunctions associated with schizophrenia, allowing for a direct link between noninvasive EEG and chronic, widespread, neurobiological deficits.
SV2: Accurate Structural Variation Genotyping andDe NovoMutation Detection from Whole Genomes
Authors: Antaki Danny , Brandler William M , Sebat Jonathan 
Published: March 2017

AbstractMotivationStructural Variation (SV) detection from short-read whole genome sequencing is error prone, presenting significant challenges for population or family-based studies of disease.ResultsHere we describe SV2, a machine-learning algorithm for genotyping deletions and duplications from paired-end sequencing data. SV2can rapidly integrate variant calls from multiple structural variant discovery algorithms into a unified call set with high genotyping accuracy and capability to detect de novo mutations.Availability and ImplementationSV2is freely available on GitHub (https://github.com/dantaki/SV2)
A semantic web services discovery approach based on a mobile agent using metadata
Authors: Ben Seghir Nadia , Kazar Okba , Rezeg Khaled , Bourekkache Samir 
Published: March 2017

Purpose
The success of web services involved the adoption of this technology by different service providers through the web, which increased the number of web services, as a result making their discovery a tedious task. The UDDI standard has been proposed for web service publication and discovery. However, it lacks sufficient semantic description in the content of web services, which makes it difficult to find and compose suitable web services during the analysis, search, and matching processes. In addition, few works on semantic web services discovery take into account the user’s profile. The purpose of this paper is to optimize the web services discovery by reducing the search space and increasing the number of relevant services.

Design/methodology/approach
The authors propose a new approach for the semantic web services discovery based on the mobile agent, user profile and metadata catalog. In the approach, each user can be described by a profile which is represented in two dimensions: personal dimension and preferences dimension. The description of web service is based on two levels: metadata catalog and WSDL.

Findings
First, the semantic web services discovery reduces the number of relevant services through the application of matching algorithm “semantic match”. The result of this first matching restricts the search space at the level of UDDI registry, which allows the users to have good results for the “functional match”. Second, the use of mobile agents as a communication entity reduces the traffic on the network and the quantity of exchanged information. Finally, the integration of user profile in the service discovery process facilitates the expression of the user needs and makes intelligible the selected service.

Originality/value
To the best knowledge of the authors, this is the first attempt at implementing the mobile agent technology with the semantic web service technology.
Distributed emitter parameter refinement based on maximum likelihood
Authors: Xu Xin 
Published: March 2017

Purpose
Emitter parameter estimation via signal sorting is crucial for communication, electronic reconnaissance and radar intelligence analysis. However, due to problems of transmitter circuit, environmental noises and certain unknown interference sources, the estimated emitter parameter measurements are still inaccurate and biased. As a result, it is indispensable to further refine the parameter values. Though the benchmark clustering algorithms are assumed to be capable of inferring the true parameter values by discovering cluster centers, the high computational and communication cost makes them difficult to adapt for distributed learning on massive measurement data. The paper aims to discuss these issues.

Design/methodology/approach
In this work, the author brings forward a distributed emitter parameter refinement method based on maximum likelihood. The author’s method is able to infer the underlying true parameter values from the huge measurement data efficiently in a distributed working mode.

Findings
Experimental results on a series of synthetic data indicate the effectiveness and efficiency of the author’s method when compared against the benchmark clustering methods.

Originality/value
With the refined parameter values, the complex stochastic parameter patterns could be discovered and the emitters could be identified by merging observations of consistent parameter values together. Actually, the author is in the process of applying her distributed parameter refinement method for PRI parameter pattern discovery and emitter identification. The superior performance ensures its wide application in both civil and military fields.
Analysing customer behaviour in mobile app usage
Authors: Chen Qianling , Zhang Min , Zhao Xiande 
Published: March 2017

Purpose
Big data produced by mobile apps contains valuable knowledge about customers and markets and have been viewed as productive resources. The purpose of this paper is to propose a multiple methods approach to elicit intelligence and value from big data by analysing the customer behaviour in mobile app usage.

Design/methodology/approach
The big data analytical approach is developed using three data mining techniques: RFM(recency, frequency, monetary) analysis, link analysis, and association rule learning. The authors then conduct a case study to apply this approach to analyse the transaction data extracted from a mobile app.

Findings
This approach can identify high value and mass customers, and understand their patterns and preferences in using the functions of the mobile app. Such knowledge enables the developer to capture the behaviour of large pools of customers and to improve products and services by mixing and matching the functions and offering personalised promotions and marketing information.

Originality/value
The approach used in this study balances complexity with usability, thus facilitating corporate use of big data in making product improvement and customisation decisions. The approach allows developers to gain insights into customer behaviour and function usage preferences by analysing big data. The identified associations between functions can also help developers improve existing, and design new, products and services to satisfy customers’ unfulfilled requirements.
A little help from my friends: how purchasing gains influence in complex business-to-business services: the case of legal
Authors: Tate Wendy L. , Ellram Lisa M. , Schmelzle Ulrich 
Published: March 2017

PurposeThe purpose of this research is to develop an understanding of how purchasing can become meaningfully involved in complex business-to-business service purchases.Design/methodology/approachA single in-depth case study method of an exemplar organization was applied to better understand the purchasing function’s role in adding to the value proposition in complex, non-traditional business-to-business service purchases.FindingsPowerful allies or advocates can mediate purchasing involvement in service procurement. However, once the involvement is initiated, purchasing must make a positive contribution with respect to the specific needs and expectations of the budget owner to retain its influence.Research limitations/implicationsThis research extends institutional theory to show how powerful allies or advocates can mediate purchasing involvement in the complex services spend.Practical implicationsThis study describes the potential impact of purchasing’s involvement in complex services spend and highlights the opportunities for purchasing managers to improve supplier management and drive out additional costs.Originality/valueFor the business practitioner, this research provides evidence regarding how individual functions can gain influence in the organization. A conceptual model describes the meaningful involvement of purchasing in complex business-to-business service purchases.
Selecting the reliable supplier by using the advisor agents
Authors: Majd Elham , Balakrishnan Vimala , Godazgar Vahid 
Published: March 2017

Purpose
This paper aims to enhance the successful interaction between buyers and suppliers who use intelligent agents by presenting a computational model to detect the most reliable supplier agent according to advice of an advisor agent.

Design/methodology/approach
In this case, the authors study the most representative models in agent environments. According to these analysis criteria, a computational model was presented to compute the reliability of supplier agents and then select the most reliable one. To evaluate the proposed method, the experimentation was carried out in two stages. First, the average accuracy of model in computing the reliability was evaluated by comparing a random selection method. Second, the performance of the model in detecting the most reliable supplier was evaluated in an agent environment by applying trust network game as a simulator.

Findings
The experimental results revealed that the proposed method can detect the most reliable supplier accurately in both consistent and oscillating agent environments.

Originality/value
The authors believe that the proposed model will be beneficial to enhance the fulfillment of purchasing between buyers and suppliers.
A new model for measuring salesperson lifetime value
Authors: Farías Pablo , Torres Eduardo , Mora Cortez Roberto 
Published: March 2017

PurposeThe purpose of this paper is to propose a new salesperson valuation model. This paper presents a calculation method for estimating both the individual lifetime value of a salesperson and the sales force equity.Design/methodology/approachThis is a conceptual paper supported by a case study.FindingsThe authors contribute to the literature by operationalizing the salesperson lifetime value concept and introducing new important aspects in comparison with previous discussions, including peer effect, recruitment/hiring cost and termination costs.Originality/valueThis manuscript theoretically and practically contributes to personnel value management in the organization and sales force financial control. The authors introduce peer effects, hiring/recruitment costs and termination costs, which are missing as a set in previous research. In addition, this paper offers a simple but robust model to practitioners’ use.
Healthcare leaders’ views on successful quality improvement initiatives and context
Authors: Barson Stuart , Doolan-Noble Fiona , Gray Jonathon , Gauld Robin 
Published: March 2017

PurposeThe purpose of this paper is to investigate the contextual factors contributing to the sustainability of healthcare quality improvement (QI) initiatives.Design/methodology/approachThemes from semi-structured interviews with international healthcare leaders are compared with Kaplan and Provostet al.’s (2012) model for understanding success in quality (MUSIQ). Critical success factors within these themes are shown in detail.FindingsThe interviews provide a rich source of information on critical success factors. The themes largely correspond with MUSIQ, reinforcing its robustness. An important factor emerging from the interviews was the importance of engagement with patients and families in QI, and this needs consideration in seeking to understand context in QI.Research limitations/implicationsInterview participants represent a limited set of western countries and health systems. Their experiences may not hold true in other settings.Practical implicationsThe detail on critical success factors provides QI practitioners with guidance on designing and implementing sustainable initiatives.Originality/valueIncluding consideration of contextual factors for engagement with patients and families in frameworks for context in QI appears to be an original idea that will add value to such frameworks. Researchers in patient engagement are starting to address contextual factors and connections should be made with this work.
FRAX and mandibular sparse trabeculation as fracture predictors: a longitudinal study from 1980 to 2002
Authors: Sundh Valter , Hange Dominique , Ahlqwist Margareta , Hakeberg Magnus , Lissner Lauren , Jonasson Grethe 
Published: March 2017

The fracture assessment tool (FRAX) is widely used for predicting fractures, but better methods are needed. The aim of this study was to determine whether visual assessments of mandibular trabecular bone could improve FRAX predictions. Three age‐cohorts of women were examined twice – 499 women in 1980/1981 and 412 women in 1992/1993; 397 participated in both examinations. Information on 10‐yr fracture events was available, and bone trabeculation was assessed in radiographs as ‘dense’, ‘mixed’, or ‘sparse’. Fracture assessment tool values, without bone mineral density (BMD), were calculated twice. Both sparse trabeculation and FRAX >15% were associated with a twofold higher risk for future fracture in the younger group and with a three‐ to fourfold higher risk for future fracture in the older group. For those with both FRAX >15% and sparse trabeculation, the relative risk (RR) for a fracture in the next 10 yr was 5.9 (95% CI: 3.5–9.8) in the younger group and 22.7 (95% CI: 5.6–92) in the older group. If either FRAX >15% or sparse trabeculation was present, the RR was 2.6 (95% CI: 1.7–4.1) in the younger group and 15.7 (95% CI: 3.9–6.4) in the older group. We concluded that FRAX >15%, without BMD measurements, was an effective fracture predictor, and mandibular sparse trabeculation had a substantial additive effect. Together, FRAX plus mandibular sparse trabeculation predicts major osteoporotic fractures to approximately the same extent as does FRAX with BMD measurements.
Numerical simulation of prestrain history effect on ductile crack growth in mismatched welded joints
Authors: Song W. , Liu X. , Berto F. , Xu J. , Fang H. 
Published: March 2017

AbstractPipe reeling may lead to plastic pre‐deformation (prestrain) around existing cracks in components; therefore, investigating whether this process accelerates or counteracts ductile crack growth, especially for strength mismatched welded joints, is warranted. This study focused on the effect of prestrain history on ductile crack growth in mismatched welded joints. A single‐edge‐notched tension specimen was selected for numerical study, and the crack was assumed to have existed before a prestrain history was applied. Crack growth resistance curves for plane strain and mode I crack growth under large‐scale yielding conditions have been computed using the complete Gurson model. Meanwhile, symmetrical and non‐symmetrical prestrain cycle modes with different loading levels were applied to the overmatched specimens. The outcome demonstrated that the mismatch ratio (the ratio between the yield stress of the weld metal and base metal) showed a significant effect on fracture resistance regardless of the stage at which the prestrain cycle loading was located. By contrast, the processing of the crack growth was weakened by the increase of prestrain values, and the symmetrical prestrain cycle resulted in greater plastic damage than the non‐symmetrical prestrain cycle did. However, the initial crack length had a non‐significant effect on the ductile fracture considering the prestrain and mismatch effects.
Diabetes mellitus not an unfavorable factor on the prognosis of hepatitis C virus‐related hepatocellular carcinoma
Authors: Yoshida Naoki , Midorikawa Yutaka , Higaki Tokio , Nakayama Hisashi , Tsuji Shingo , Matsuoka Shunichi , Ishihara Hisamitsu , Moriyama Mitsuhiko , Takayama Tadatoshi 
Published: March 2017

AimDiabetes mellitus (DM) is a potential risk factor for hepatocarcinogenesis, especially in patients with hepatitis C virus (HCV) infection. We aimed to elucidate whether DM influences the surgical outcomes of patients with hepatocellular carcinoma (HCC).MethodsOur patients were routinely controlled to keep urinary glucose excretion to less than 3.0 g/day before surgery, and the serum glucose level under 200 mg/dL after surgery. The surgical outcomes and postoperative complications of 112 patients with HCV‐related HCC with DM (DM group) were compared to those of 112 propensity‐matched patients without DM (non‐DM group).ResultsAfter a median follow‐up of 3.2 years (range, 0.2–11.3 years), the median overall (5.2 years; 95% confidence interval, 3.8–6.5 years) and recurrence‐free survival (2.2 years; 1.7–2.9 years) in the DM group were not significantly different from those (6.3 years; 5.4–7.1 years, P = 0.337; and 2.2 years; 1.7–3.6 years, P = 0.613) in the non‐DM group. The independent factors related to overall survival were the background liver (hazard ratio, 2.06; 95% confidence interval, 1.27–3.39, P = 0.014) and tumor differentiation grade (2.07; 1.14–4.05, P = 0.015). Thirty‐two patients (28.5%) in the DM group and 32 patients (28.5%) in the non‐DM group had morbidities after operation, with no significant difference between the groups (P = 1.000). Furthermore, postoperative control status of DM did not affect the prognostic outcome.ConclusionDiabetes mellitus does not affect the surgical outcomes of patients with HCV‐related HCC, and it is not an unfavorable factor when selecting candidates for liver resection of HCC.