bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic liability to posttraumatic stress disorder and its association with postpartum depression
Authors: Bang Madsen Kathrine , Liu Xiaoqin , Albiñana Clara , Jóhann Vilhjálmsson Bjarni , Agerbo Esben , Mortensen Preben Bo , Hougaard David Michael , Nordentoft Merete , Werge Thomas , Mors Ole , Børglum Anders D. , Munk-Olsen Trine 
Published: July 2022

AbstractBackgroundChildbirth may be a traumatic experience and vulnerability to posttraumatic stress disorder (PTSD) may increase the risk of postpartum depression (PPD). We investigated whether genetic vulnerability to PTSD as measured by polygenic score (PGS) increases the risk of PPD and whether a predisposition to PTSD in PPD cases exceeds that of major depressive disorder (MDD) outside the postpartum period.MethodsThis case-control study included participants from the iPSYCH2015, a case-cohort of all singletons born in Denmark between 1981 and 2008. Restricting to women born between 1981 and 1997 and excluding women with a first diagnosis other than depression (N = 22 613), 333 were identified with PPD. For each PPD case, 999 representing the background population and 993 with MDD outside the postpartum were matched by calendar year at birth, cohort selection, and age. PTSD PGS was calculated from summary statistics from the Psychiatric Genomics Consortium with LDpred2-auto. Odds ratios (ORs) were estimated using conditional logistic regression adjusted for parental psychiatric history and country of origin, PGS for MDD and age at first birth, and the first 10 principal components.ResultsThe PTSD PGS was significantly associated with PPD (OR 1.42, 95% CI 1.20–1.68 per standard deviation increase in PTSD PGS) compared to healthy female controls. Genetic PTSD vulnerability in PPD cases did not exceed that of matched female depression cases outside the postpartum period (OR 1.10, 95% CI 0.94–1.30 per standard deviation increase).ConclusionsGenetic vulnerability to PTSD increased the risk of PPD but did not differ between PPD cases and women with depression at other times.
Spatial autocorrelation analysis and the social organisation of crop and herd management at Çatalhöyük
Authors: Hodder Ian , Bogaard Amy , Engel Claudia , Pearson Jessica , Wolfhagen Jesse 
Published: July 2022

AbstractThis article uses spatial autocorrelation analysis in order to explore the social organisation of crop and herd management at the Neolithic site of Çatalhöyük in south-central Turkey. Evidence for spatial clustering across the settlement is sought at different scales (house, neighbourhood, radial wedge, sector, sub-mound) in the different periods of occupation from Early to Late. The data used are sheep carbon and nitrogen isotopes, densities of weed species in archaeobotanical assemblages and the densities of weed species in sheep dung. The results are interpreted in relation to existing work both on crop and herd management and consumption at Çatalhöyük and on the social organisation of the settlement. Complex nested and cross-cutting social groupings shared many aspects of production and consumption activities across the site resulting in limited spatial clustering of values. The impacts of taphonomic factors on these results are considered. Especially by the Late period of occupation at Çatalhöyük, there is some evidence of distinct labour and consumption organisation linked to houses and house groupings.
Feasibility of intraprocedural augmented reality visualisation of 3D rotational angiography in congenital cardiac catheterisation
Authors: Salavitabar Arash , Whiteside Wendy , Zampi Jeffrey D. 
Published: July 2022

AbstractThree-dimensional rotational angiography has become a mainstay of congenital cardiac catheterisation. Augmented reality is an exciting and emerging technology that allows for interactive visualisation of 3D holographic images in the user’s environment. This case series reports on the feasibility of intraprocedural augmented reality visualisation of 3D rotational angiography in five patients with CHD.
Named-entity recognition in Turkish legal texts
Authors: Çetindağ Can , Yazıcıoğlu Berkay , Koç Aykut 
Published: July 2022

AbstractNatural language processing (NLP) technologies and applications in legal text processing are gaining momentum. Being one of the most prominent tasks in NLP, named-entity recognition (NER) can substantiate a great convenience for NLP in law due to the variety of named entities in the legal domain and their accentuated importance in legal documents. However, domain-specific NER models in the legal domain are not well studied. We present a NER model for Turkish legal texts with a custom-made corpus as well as several NER architectures based on conditional random fields and bidirectional long-short-term memories (BiLSTMs) to address the task. We also study several combinations of different word embeddings consisting of GloVe, Morph2Vec, and neural network-based character feature extraction techniques either with BiLSTM or convolutional neural networks. We report 92.27% F1 score with a hybrid word representation of GloVe and Morph2Vec with character-level features extracted with BiLSTM. Being an agglutinative language, the morphological structure of Turkish is also considered. To the best of our knowledge, our work is the first legal domain-specific NER study in Turkish and also the first study for an agglutinative language in the legal domain. Thus, our work can also have implications beyond the Turkish language.
STEM Education Pilot a Resounding Success: Project Lets Young People Experience World-Class Scientific Equipment and Training
Authors: Hughes Louise 
Published: July 2022

Abstract:
As part of the Hitachi High-Tech America Inspire STEM Education Outreach Programme in the UK, a successful STEM (Science, Technology, Engineering and Math) education pilot has seen over 5000 students from 80 schools given the opportunity to use scanning electron microscopes (SEMs) for their own experiments. The collaborative project allowed students to design, propose, and execute experiments to give them hands-on experience with scientific research. Feedback from the project has been resoundingly positive, with many students gaining new skills and an interest in STEM, and it looks set to grow further to allow more students access to high-level scientific equipment.
AXON Dose: A Solution for Measuring and Managing Electron Dose in the TEM
Authors: Damiano John , Walden Stamp , Franks Alan , Marusak Kate , Larson Ben , Coy Mike , Nackashi David 
Published: July 2022

Abstract:
The interaction of the electron beam with materials during TEM/STEM imaging often leads to radiation damage. While a variety of low-dose techniques can help mitigate beam damage, true dose management starts with knowing the precise total accumulated dose and dose rate that a sample has seen throughout an experiment. AXON Dose allows users to calibrate their instruments, track electron dose/dose rate across a sample as a function of time and location, and quantify the impact of dose on individual samples.
Bee discovery suggests the importance of urban gardens in a changing world
Authors: Egerer Monika 
Published: July 2022

AbstractThe diversity and distribution of wild bees are dramatically changing due to habitat fragmentation, agricultural intensification and climate change. In cities, urban gardens are proposed ‘island’ habitats for bees offering floral and nesting resources. Yet, it is largely unclear how gardens play a role in changes in species diversity and distribution. This paper reports on the discovery of a bee species to our knowledge previously undocumented in the region of Berlin, Germany. We discovered Lasioglossum limbellum in a community garden created on concrete slabs of annual and perennial vegetation. As a cavity nester in soft rock cliffs—a natural habitat functionally not existent in urban areas—the life history of this species makes this discovery particularly interesting, and an opportunity to explore the role of urban gardens in biodiversity change. This report aims to spur future research, reporting and discussion on the changes in diversity and distribution of wild bees specifically in urban areas.
Who benefits from individual placement and support? A meta-analysis
Authors: de Winter Lars , Couwenbergh Chrisje , van Weeghel Jaap , Sanches Sarita , Michon Harry , Bond Gary R. 
Published: July 2022

Abstract

Aims
Individual placement and support (IPS) is an evidence-based service model to support people with mental disorders in obtaining and sustaining competitive employment. IPS is increasingly offered to a broad variety of service users. In this meta-analysis we analysed the relative effectiveness of IPS for different subgroups of service users both based on the diagnosis and defined by a range of clinical, functional and personal characteristics.

Methods
We included randomised controlled trials that evaluated IPS for service users diagnosed with any mental disorder. We examined effect sizes for the between-group differences at follow-up for three outcome measures (employment rate, job duration and wages), controlling for methodological confounders (type of control group, follow-up duration and geographic region). Using sensitivity analyses of subgroup differences, we analysed moderating effects of the following diagnostic, clinical, functional and personal characteristics: severe mental illness (SMI), common mental disorders (CMD), schizophrenia spectrum disorders, mood disorders, duration of illness, the severity of symptoms, level of functioning, age, comorbid alcohol and substance use, education level and employment history.

Results
IPS is effective in improving employment outcomes compared to the control group in all subgroups, regardless of any methodological confounder. However, IPS was relatively more effective for service users with SMIs, schizophrenia spectrum disorders and a low symptom severity. Although IPS was still effective for people with CMD and with major depressive disorder, it was relatively less effective for these subgroups. IPS was equally effective after both a short and a long follow-up period. However, we found small, but clinically not meaningful, differences in effectiveness of IPS between active and passive control groups. Finally, IPS was relatively less effective in European studies compared to non-European studies, which could be explained by a potential benefits trap in high welfare countries.

Conclusions
IPS is effective for all different subgroups, regardless of diagnostic, clinical, functional and personal characteristics. However, there might be a risk of false-positive subgroup outcomes and results should be handled with caution. Future research should focus on whether, and if so, how the IPS model should be adapted to better meet the vocational needs of people with CMD and higher symptom severity.
Bringing Multilateral Environmental Agreements into Development Finance: An Analysis of the Asian Infrastructure Investment Bank's Environmental and Social Framework
Authors: Lin Wei-Chung 
Published: July 2022

AbstractMultilateral development banks (MDBs) are crucial in promoting economic growth through their project finance activities. Meanwhile, to address negative effects arising from their development projects, MDBs increasingly have focused their attention on the environmental and social impacts of their supported projects in recent decades. This article analyzes the relationship between the Environmental and Social Framework (ESF) adopted by the Asian Infrastructure Investment Bank (AIIB) and multilateral environmental agreements (MEAs). It argues that better compliance with MEAs by the AIIB and its borrowers in implementing AIIB-supported development projects will be achieved only if its independent accountability mechanism (IAM) can actively examine project compliance with the ESF in the light of MEAs. The AIIB has an opportunity to provide leadership in promoting the fulfilment of MEA obligations in development finance. However, this is contingent on ensuring effective oversight by its newly established IAM moving forward.
Evaluation of amino acid–inhibiting herbicide mixtures for hair fescue (Festuca filiformis) management in lowbush blueberry
Authors: White Scott N. 
Published: July 2022

AbstractHair fescue is a perennial grass weed in lowbush blueberry fields that forms dense sods and reduces yield. As a result of natural tolerance or resistance of this grass to other currently registered herbicides growers rely on preemergence (PRE) applications of pronamide and postemergence (POST) applications of the Group 2 herbicides foramsulfuron and nicosulfuron + rimsulfuron for hair fescue management. This causes repeated application of Group 2 herbicides, which is compounded by the recent registration of flazasulfuron for POST suppression of hair fescue in lowbush blueberry. Mixtures of Group 2 herbicides with the amino acid–inhibiting herbicides glyphosate (Group 9) and glufosinate (Group 10), however, can improve weed control and may delay herbicide resistance development. This research used a factorial arrangement of Group 2 herbicides (none, foramsulfuron [35 g ai ha−1], nicosulfuron + rimsulfuron [13 + 13 g ai ha−1], flazasulfuron [50 g ai ha−1]) and mixtures (none, with glyphosate [902 g ae ha−1], and with glufosinate [750 g ai ha−1]) to identify possible mixtures that improve weed control and delay resistance development. Herbicides were applied in spring nonbearing year, fall bearing year, and fall nonbearing year, with each application timing conducted as a separate experiment. Foramsulfuron and nicosulfuron + rimsulfuron were not effective as fall applications, and spring applications of these herbicides with glyphosate or glufosinate improved hair fescue suppression. Glyphosate and glufosinate were more effective as fall rather than spring applications. Flazasulfuron was effective across all application timings, although its mixture with glufosinate generally improved hair fescue suppression. Flazasulfuron + glufosinate is tentatively recommended as an effective mixture for management of spring nonbearing-year and fall bearing-year hair fescue in lowbush blueberry.
Correlation Coefficient‐Based Information Criterion for Quantification of Dependence Characteristics in Hydrological Time Series
Authors: Xie Ping , Huo Jingqun , Sang Yan‐Fang , Li Yaqing , Chen Jie , Wu Ziyi , Singh Vijay P. 
Published: July 2022

AbstractQuantification of the dependence characteristics in hydrological time series is essential for understanding hydrological variability and for managing water resources. However, how determining a suitable model for describing the dependent components is still a challenge. In this article, we proposed a correlation coefficient‐based information criterion (CCIC) to determine the optimal model order of regression‐based models for quantifying the dependence characteristics in hydrological time series. CCIC was developed by combining the index of correlation coefficient and the information entropy index. The former was used to reflect the fitting error of the model and the latter was used as a penalty term to reflect the model uncertainty. They have similar roles as the two terms of the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) used commonly in hydrology. Results of Monte‐Carlo experiments verified higher and more stable accuracy of determining the true model order by CCIC than by AIC and BIC. Moreover, results indicated that the mean value of a time series had a big impact on the accuracy of CCIC. If the mean value of a time series was far from its initial value, the estimation of CCIC would have a big bias, causing low accuracy in the determination of suitable model order. The application of CCIC to annual precipitation from 520 stations in China further confirmed its advantages over AIC and BIC and indicated the significant short‐term dependence characteristics of annual precipitation in the Yangtze River basin. The proposed CCIC approach has potential for wider use in hydrometeorology.
Hydraulic Issues Concerning Injection of Harvested Rainwater to the Subsurface Through Drywells: Insight From Numerical Simulations of Flow in a Realistic Combined Vadose Zone‐Groundwater Flow System
Authors: Russo D. , Kurtzman D. , Nachshon U. 
Published: July 2022

AbstractThis study focuses on the analyses of field‐scale water flow originating from a drywell, using the 3‐D Richards equation for the local description of the flow in a spatially heterogeneous, combined vadose zone‐groundwater flow system. Realistic features of the flow system, that is, height of the groundwater table, records of the time‐dependent rainfall data, spatial heterogeneity of soil hydraulic properties and flow‐controlled attributes, as well as man‐controlled characteristics of the drywell, were considered in the analyses. The effect of (a) the depth‐dependency of the soil type, (b) the vertical position of the drywell's screen, and (c) the mode of water injection to the drywell (constant or time‐dependent), on the performance of the drywell, were examined. Results, and in particular those related to the importance of the soil type depth‐dependency with regard to the drywell performance, can be explained by the physics of flow in unsaturated soils of differing soil texture. Of specific significance is the transition zone between the two different soil types in the case in which the spatially‐heterogeneous coarse‐textured soil overlies the spatially heterogeneous fine‐textured soil. In this case, when most of the drywell screen is located within this transition zone and when the flow is transient and non‐monotonous, the downward flow from the drywell is maximized. Although this study is site‐specific, we believe that its results are novel and relevant for sandy to sandy‐clay soils associated with managed aquifer recharge technology based on a device whose vertical axis is perpendicular to the soil layering.
Time‐of‐Arrival of Coronal Mass Ejections: A Two‐Phase Kinematics Approach Based on Heliospheric Imaging Observations
Authors: Paouris Evangelos , Vourlidas Angelos 
Published: July 2022

AbstractThe forecasting of the Time‐of‐Arrival (ToA) of coronal mass ejections (CMEs) to Earth does not yet meet most Space Weather users' requirements. The main physical reason is our incomplete understanding of CME propagation in the inner heliosphere. Therefore, many ToA forecasting algorithms rely on simple empirical relations to represent the interplanetary propagation phase using, mostly, kinematic information from coronagraphic observations below 30 solar radii (Rs) and a couple rather simplifying assumptions of constant direction and speed for the transient. We replace the assumption of constant speed in the inner heliosphere with a two‐phase behavior consisting of a decelerating (or accelerating) phase from 20 Rs to some distance, followed by a coasting phase to Earth. In a nod toward a forecasting scheme, we consider Earth‐directed CMEs, use kinematic measurements only from the Heliospheric Imagers aboard both STEREO spacecraft, treat each spacecraft separately to increase the event statistics, analyze the measurements in a data‐assimilative fashion, and intercompare them against three localization schemes for single viewpoint observations (fixed‐φ, harmonic mean and self‐similar expansion). For the 21 cases, we obtain the best mean absolute error (MAE) of 6.4 ± 1.9 hr. In fact, the difference between calculated and observed ToA is <52 min for 42% of the cases that return plausible ToA estimates. We find that some CMEs continue to decelerate beyond even 0.7 AU but reasonable forecasts should be possible with 31 hr lead time. This work is a proof‐of‐concept and an analysis of a larger event sample is required to fully validate this technique.
High‐Dimensional Groundwater Flow Inverse Modeling by Upscaled Effective Model on Principal Components
Authors: Zhao Yue , Guo Quan , Lu Chunhui , Luo Jian 
Published: July 2022

AbstractThe main computational costs of gradient‐based inverse methods for high‐resolution groundwater flow inverse problems include costly forward model simulations and the large number of such simulations required to determine the Jacobian matrix. We develop an upscaling‐based inverse approach, named upscaled principal component inverse approach (UPCIA), which achieves dimensionality reduction and reduces computational cost of forward model simulations by evaluating the Jacobian through upscaled effective models on a coarse‐resolution grid constructed from upscaled principal components. UPCIA integrates downscaling into the inverse problem by estimating principal component coefficients based on the coarse‐resolution forward model, which are then used to generate high‐resolution parameter fields. Various numerical experiments demonstrate the effectiveness and efficiency of UPCIA, including 2‐D/3‐D high‐dimensional steady‐state and transient hydraulic tomography with known storativity to estimate multi‐Gaussian transmissivity or hydraulic conductivity fields. Results show that the hydraulic head is insensitive to small‐scale variability of conductivity, and UPCIA provides high‐quality inversion results similar to inverse methods with high‐resolution forward model simulations and significantly reduces computation time by orders of magnitude. In addition to supporting the characterization of heterogeneity in sufficient detail, UPCIA can also be used to examine whether finer resolution is necessary and possibly to determine an optimal inverse resolution.
Country experiences on the path to exclusive use of validated automated blood pressure measuring devices within the HEARTS in the Americas Initiative
Authors: Lombardi Cintia , Picone Dean S. , Sharman James E. , Campbell Norm R. C. , Farias Rafael , Guerre Stephanie , Gittens Anselm , Paccot Melanie , Villacres Nilda , Valdes Yamile , Ordunez Pedro 
Published: July 2022

AbstractThe aim of the HEARTS in the Americas initiative is to promote the adoption of global best practices in the prevention and control of cardiovascular diseases, and improve the control of hypertension. HEARTS is being implemented in 21 countries and a diverse set of actions and measures are in progress to improve exclusive access in primary health care facilities to automated blood pressure measuring devices that have been validated for accuracy. The purpose of this manuscript is to illustrate these efforts, mainly in the regulatory and public procurement arena, and to present information on common challenges and solutions identified. Examples from six countries confirm the need for not only a robust regulatory framework to increase availability of validated automated blood pressure measuring devices but also a comprehensive strategic approach that involves relevant stakeholders, includes a multi-pronged approach and is associated with a national program to prevent and control non communicable diseases.