bluuebunny/crossref_metadata_2025_split huggingface dataset:
Initial experience on abdominal photon-counting computed tomography in clinical routine: general image quality and dose exposure
Authors: Becker Benjamin V. , Kaatsch Hanns Leonhard , Nestler Kai , Overhoff Daniel , Schneider Julian , Dillinger Daniel , Piechotka Joel , Brockmann Marc A. , Ullmann Reinhard , Port Matthias , Scherthan Harry , Waldeck Stephan 
Published: December 2022

Abstract
Objectives
Photon-counting computed tomography has lately found its way into clinical routine. The new technique could offer substantial improvements regarding general image quality, image noise, and radiation dose reduction. This study evaluated the first abdominal examinations in clinical routine and compared the results to conventional computed tomography.

Methods
In this single-center retrospective study, 66 patients underwent photon-counting and conventional abdominal CT. Four radiologists assessed general image quality, image noise, and image artifacts. Signal-to-noise ratio and dose properties of both techniques within the clinical application were compared. An ex vivo phantom study revealed the radiobiological impact by means of DNA double-strand break foci in peripheral blood cells by enumerating γ-H2AX+53BP1 foci.

Results
General image quality in accordance with the Likert scale was found superior for photon-counting CT (4.74 ± 0.46 vs. 4.25 ± 0.54; p < 0.001). Signal-to-noise ratio (p < 0.001) and also dose exposure were higher for photon-counting CT (DLP: 419.2 ± 162.2 vs. 372.3 ± 236.6 mGy*cm; p = 0.0435). CT exposure resulted in significantly increased DNA damage in comparison to sham control (p < 0.001). Investigation of the average foci per cell and radiation-induced foci numbers revealed significantly elevated numbers (p = 0.004 and p < 0.0001, respectively) after photon-counting CT.

Conclusion
Photon-counting CT in abdominal examinations showed superior results regarding general image quality and signal-to-noise ratio in clinical routine. However, this seems to be traded for a significantly higher dose exposure and corresponding double-strand break frequency. Optimization of standard protocols in further clinical applications is required to find a compromise regarding picture quality and dose exposure.

Key Points
• Photon-counting computed tomography promises to enhance the diagnostic potential of medical imaging in clinical routine.
• Retrospective single-center study showed superior general image quality accompanied by higher dose exposure in initial abdominal PCCT protocols compared to state-of-the-art conventional CT.
• A simultaneous ex vivo phantom study revealed correspondingly increased frequencies of DNA double-strand breaks after PCCT.
Delayed primary anastomosis for repair of long-gap esophageal atresia: technique revisited
Authors: Friedmacher Florian 
Published: December 2022

AbstractThe operative management of patients born with long-gap esophageal atresia (LGEA) remains a major challenge for most pediatric surgeons, due to the rarity and complex nature of this malformation. In LGEA, the distance between the proximal and distal esophageal end is too wide, making a primary anastomosis often impossible. Still, every effort should be made to preserve the native esophagus as no other conduit can replace its function in transporting food from the oral cavity to the stomach satisfactorily. In 1981, Puri et al. observed that in newborns with LGEA spontaneous growth and hypertrophy of the two segments occur at a rate faster than overall somatic growth in the absence of any form of mechanical stretching, traction or bouginage. They further noted that maximal natural growth arises in the first 8–12 weeks of life, stimulated by the swallowing reflex and reflux of gastric contents into the lower esophageal pouch. Since then, creation of an initial gastrostomy and continuous suction of the upper esophageal pouch followed by delayed primary anastomosis at approximately 3 months of age has been widely accepted as the preferred treatment option in most LGEA cases, generally providing good functional results. The current article offers a comprehensive update on the various aspects and challenges of this technique including initial preoperative management and subsequent gap assessment, while also discussing potential postoperative complications and long-term outcome.
Effects of psychological treatments on functioning in people with Schizophrenia: a systematic review and meta-analysis of randomized controlled trials
Authors: Bighelli Irene , Wallis Sofia , Reitmeir Cornelia , Schwermann Felicitas , Salahuddin Nurul Husna , Leucht Stefan 
Published: December 2022

AbstractFunctioning is recognized as a key treatment goal in alleviating the burden of schizophrenia. Psychological interventions can play an important role in improving functioning in this population, but the evidence on their efficacy is limited. We therefore aimed to evaluate the effect of psychological interventions in functioning for patients with schizophrenia. To conduct this systematic review and meta-analysis, we searched for published and unpublished randomized controlled trials (RCTs) in EMBASE, MEDLINE, PsycINFO, BIOSIS, Cochrane Library, WHO International Clinical Trials Registry Platform (ICTRP), ClinicalTrials.gov and the Study register of the Cochrane Schizophrenia Group. The outcome functioning was measured with validated scales. We performed random-effects pairwise meta-analysis to calculate standardized mean differences (SMDs) with 95% confidence intervals (CIs). We included 58 RCTs (5048 participants). Psychological interventions analyzed together (SMD =  – 0.37, 95% CI  – 0.49 to  – 0.25), cognitive behavioral therapy (30 RCTs, SMD =  – 0.26, 95% CI  – 0.39 to  – 0.12), and third wave cognitive-behavioral therapies (15 RCTs, SMD =  – 0.60, 95% CI  – 0.83 to  – 0.37) were superior to control in improving functioning, while creative therapies (8 RCTs, SMD = 0.01, 95% CI  – 0.38 to 0.39), integrated therapies (4 RCTs, SMD =  – 0.21, 95% CI  – 1.20 to 0.78) and other therapies (4 RCTs, SMD =  – 0.74, 95% CI  – 1.52 to 0.04) did not show a benefit. Psychological interventions, in particular cognitive behavioral therapy and third wave cognitive behavioral therapies, have shown a therapeutic effect on functioning. The confidence in the estimate was evaluated as very low due to risk of bias, heterogeneity and possible publication bias.
Plasma GDF15 levels associated with circulating immune cells predict the efficacy of PD-1/PD-L1 inhibitor treatment and prognosis in patients with advanced non-small cell lung cancer
Authors: Hong Green , Sun Pureum , Chung Chaeuk , Park Dongil , Lee Song-I , Kim Nayoung , Lee Seong Eun , Lee Jeong Eun , Kang Yea Eun , Kang Da Hyun 
Published: December 2022

Abstract
Purpose
Although increased plasma growth differentiation factor-15 (GDF15) levels have been reported in patients with various cancers, the predictive role of PD-1/PD-L1 inhibitors in advanced cancers remains unknown. This study aimed to investigate GDF15 levels as a predictive marker in advanced non-small cell lung cancer (NSCLC) treated with PD-1/PD-L1 inhibitors and analyze their association with immune cell populations.

Methods
This study included 87 patients with advanced NSCLC receiving anti-PD-1/PD-L1 inhibitors between March 2018 and May 2020. Blood samples were obtained immediately before and months after PD-1/PD-L1 inhibitor administration.

Results
The objective response rate (ORR) was significantly higher in the low GDF15 than in the high GDF15 group (39.2% vs. 15.3%, P = 0.013). The median progression-free survival (PFS) was significantly longer in the low GDF15 than in the high GDF15 group (13.2 [95% CI 7.6–18.9] vs. 7.2 [95% CI 4.8–9.6] months, P = 0.048). Moreover, plasma GDF15 levels negatively correlated with PD-1+/CD8+ T cells (r = − 0.399, P = 0.003) and positively with PD-1+/Treg cells (r = 0.507, P < 0.001) and PD-1+Treg/CD4+ T cells (r = 0.439, P < 0.001). The ORR was significantly higher in the group with decreased GDF15 from baseline than in the increased GDF15 group (37.2% vs. 10.0%, P = 0.026). The median PFS was significantly longer in the decreased GDF15 group (14.8 [95% CI 10.4–19.2] vs. 5.9 [95% CI 2.8–9.0] months, P = 0.002). Plasma GDF15 levels were associated with PD-1+CD8+ T cells and PD-1+ Treg cells.

Conclusion
Plasma GDF15 could be a potential biomarker for predicting the efficacy and survival benefit of immunotherapy in advanced NSCLC.
Both climate sensitivity and growth trend of European beech decrease in the North German Lowlands, while Scots pine still thrives, despite growing sensitivity
Authors: Diers Marco , Weigel Robert , Leuschner Christoph 
Published: December 2022

AbstractKey messageBeech and pine respond differently to climate change. June precipitation is of particular influence for beech, and February/March temperature for pine.AbstractClimate warming exposes forests to increasing abiotic stress, demanding for difficult silvicultural decisions about the right choice of future timber species. Scots pine (Pinus sylvestris) and European beech (Fagus sylvatica) are major timber species in the North German Lowlands, which have suffered from recent hot droughts, thus raising concern about their suitability for future production forests in the region. We investigated the climate sensitivity of tree growth and long-term growth trends of ten paired beech and pine forests along a precipitation gradient in the North German Lowlands with the aim to compare the species’ climate sensitivity and to search for species-specific climatic thresholds. In the majority of beech stands, basal area increment (BAI) has lost its positive trend since the 1980s or growth declined since then, while the BAI of pine has continually increased. Long-term change in June precipitation is in the study region a more important determinant of beech growth trends than the amount of MAP, while pine growth is largely dependent on the warmth of February/March. Yet, pine growth is also sensitive to dry mid summers, with sensitivity increasing toward low MAP. Climate sensitivity of growth has significantly declined since the 1980s in beech, while the dominant drought signal of June persisted in pine. We conclude that recent climate change is affecting radial growth of beech and pine differently with both species revealing signs of vulnerability to hot droughts, suggesting for the drier part of the study region the preference of more drought-tolerant hardwood timber species over beech and pine.
Adding the neuro to cognition: from food storing to nest building
Authors: Healy Susan D. 
Published: December 2022

AbstractTypically, investigations of animal cognition couple careful experimental manipulations with examination of the animal’s behavioural responses. Sometimes those questions have included attempts to describe the neural underpinnings of the behavioural outputs. Over the past 25 years, behaviours that involve spatial learning and memory (such as navigation and food storing) has been one context in which such dual or correlated investigations have been both accessible and productive. Here I review some of that work and where it has led. Because of the wealth of data and insights gained from that work and song learning before it, it seems that it might also be useful to try to add some neurobiology to other systems in animal cognition. I finish then, with a description of recent work on the cognition and neurobiology of avian nest building. It is still relatively early days but asking questions about the cognition of nest building has already shown both neural correlates of nest building and that learning and memory play a much greater role in this behaviour than previously considered. While it is not yet clear how putting these components together will be synergistic, the examples of song learning and food storing provide encouragement. Perhaps this might be true for other behaviours too?
Data-driven innovation development: an empirical analysis of the antecedents using PLS-SEM and fsQCA
Authors: Hossain Mohamamd Alamgir , Quaddus Mohammed , Hossain Md Moazzem , Gopakumar Gopika 
Published: December 2022

AbstractData-driven innovation (DDI) is a primary source of competitive advantage for firms and is a contemporary research priority. However, what facilitates the development of DDI has largely been understudied in literature. Through a systematic literature review, this study finds technological, organizational, and environmental variables under the TOE framework, which would drive effective DDI development. We thus develop a research model, which is tested using survey data from 264 Australian firms engaged in DDI development. The data have been analysed using both symmetric (partial least squares based structural equation modelling (PLS-SEM)) and asymmetric (fuzzy-set qualitative comparative analysis (fsQCA)) methods. The mixed method enhances the confidence in our empirical analyses of the antecedent variables of DDI development. PLS-SEM has revealed that technological readiness (i.e., data quality and metadata quality), and organizational absorptive capacity and readiness (i.e., technology-oriented leadership and availability of IT skilled professionals) affect DDI development. Our fsQCA results complement and extend the findings of PSL-SEM analysis. It reveals that quality of data and metadata, technology-oriented leadership, and exploitation capacity individually are necessary—but are not sufficient—conditions for high DDI development. Further, it identifies three different solutions each for small, medium, and large firms by combining the TOE factors. Additionally, this study suggests that the TOE framework is more applicable to small firms, on DDI context. Findings of our study have been related with theoretical and practical implications.
Is blockchain a cure for peer-to-peer lending?
Authors: Yan Wangcheng , Zhou Wenjun 
Published: December 2022

AbstractThe blockchain, a decentralized ledger system, has been considered a revolutionary technology to transform businesses, including the financial markets. As peer-to-peer (P2P) lending is also known for decentralization in the sense that individuals borrow from and lend to each other directly, bypassing traditional banks, we explore the possibility and benefits of blockchains in P2P lending. We first provide an economic analysis of existing P2P lending problems, including herding and platform-borrower collusion, with and without the blockchain mechanism. We note that, compared with the existing markets, blockchain-backed P2P lending is highly effective in privacy preservation and borrower quality distinction. Since the role of intermediaries is eliminated in the blockchain world, the chance of platform-borrower collusion is also minimized. Moreover, we show that borrowers and lenders can expect additional surplus when the origination fee in traditional P2P lending is replaced with a smaller tokenization cost and when borrowers present a more accurate financial incentive in a smart contract. With the smart contract, borrowers are allowed to propose optimal interest rates based on their creditworthiness and capacity of repayment while detailed personal information is not required. Additionally, we demonstrate that small investors’ surplus can be further enhanced due to the elimination of herding.
Sedimentary, littoral and planktic diatoms show different diversity patterns and assembly mechanisms in mountain lakes of the northern European Alps
Authors: Ossyssek Stefan , Hofmann Andrea Maria , Geist Juergen , Raeder Uta 
Published: December 2022

AbstractThis study analysed diversity patterns of sedimentary, littoral and planktic diatoms in 43 mountain lakes in the northern European Alps and identified processes that contribute to these patterns. Linear regression models showed a significant increase of sedimentaryα-diversity with lake area and conductivity and a negative trend with increasing elevation, whilst the littoral diatomα-diversity increased significantly with conductivity and lake water temperature. Planktic diatomα-diversity significantly decreased with lake area and depth. August water temperature, total phosphorus, conductivity and lake depth explained a significant part of the variation and were significantly correlated with pairwiseβ-diversities in the data sets, but spatial and shared effects of space and environment were more important for planktic and littoral diatoms. A null model approach based on assemblages’ dissimilarities revealed that the structure of littoral and planktic assemblages was predominantly stochastic. In contrast, sedimentary diatoms were formed by both deterministic and stochastic processes. Abundant and widespread species contributed a large part to the assemblageβ-diversity. The results point to a stronger role of niche assembly in sedimentary than for littoral and planktic diatoms. Dispersal limitation, in turn, is likely to contribute to the spatial patterns and stochastic assembly processes observed for littoral and planktic diatoms.
Influence of a 265 °C heat treatment on the residual stress state of a PBF-LB/M AlSi10Mg alloy
Authors: Roveda Ilaria , Serrano-Munoz Itziar , Mishurova Tatiana , Madia Mauro , Pirling Thilo , Evans Alexander , Klaus Manuela , Haubrich Jan , Requena Guillermo , Bruno Giovanni 
Published: December 2022

AbstractLaser Powder Bed Fusion (PBF-LB/M) additive manufacturing (AM) induces high magnitude residual stress (RS) in structures due to the extremely heterogeneous cooling and heating rates. As the RS can be deleterious to the fatigue resistance of engineering components, great efforts are focused on understanding their generation and evolution after post-process heat treatments. In this study, one of the few of its kind, the RS relaxation induced in an as-built PBF-LB/M AlSi10Mg material by a low-temperature heat treatment (265 °C for 1 h) is studied by means of X-ray and neutron diffraction. Since the specimens are manufactured using a baseplate heated up to 200 °C, low RS are found in the as-built condition. After heat treatment a redistribution of the RS is observed, while their magnitude remains constant. It is proposed that the redistribution is induced by a repartition of stresses between the α-aluminium matrix and the silicon phase, as the morphology of the silicon phase is affected by the heat treatment. A considerable scatter is observed in the neutron diffraction RS profiles, which is principally correlated to the presence (or absence) ofpocketsof porosity developed at the borders of the chessboard pattern.
The Effect of COVID-19 Restrictions on Routine Activities and Online Crime
Authors: Johnson Shane D. , Nikolovska Manja 
Published: December 2022

Abstract
Objectives
Routine activity theory suggests that levels of crime are affected by peoples’ activity patterns. Here, we examine if, through their impact on people’s on- and off-line activities, COVID-19 restriction affected fraud committed on- and off-line during the pandemic. Our expectation was that levels of online offending would closely follow changes to mobility and online activity—with crime increasing as restrictions were imposed (and online activity increased) and declining as they were relaxed. For doorstep fraud, which has a different opportunity structure, our expectation was that the reverse would be true.

Method
COVID-19 restrictions systematically disrupted people’s activity patterns, creating quasi-experimental conditions well-suited to testing the effects of “interventions” on crime. We exploit those conditions using ARIMA time series models and UK data for online shopping fraud, hacking, doorstep fraud, online sales, and mobility to test hypotheses. Doorstep fraud is modelled as a non-equivalent dependent variable, allowing us to test whether findings were selective and in line with theoretical expectations.

Results
After controlling for other factors, levels of crime committed online were positively associated with monthly variation in online activities and negatively associated with monthly variation in mobility. In contrast, and as expected, monthly variation in doorstep fraud was positively associated with changes in mobility.

Conclusions
We find evidence consistent with routine activity theory, suggesting that disruptions to people’s daily activity patterns affect levels of crime committed both on- and off-line. The theoretical implications of the findings, and the need to develop a better evidence base about what works to reduce online crime, are discussed.
Joint replenishment meets scheduling
Authors: Györgyi Péter , Kis Tamás , Tamási Tímea , Békési József 
Published: December 2022

AbstractIn this paper, we consider a combination of the joint replenishment problem (JRP) and single-machine scheduling with release dates. There is a single machine and one or more item types. Each job has a release date, a positive processing time, and it requires a subset of items. A job can be started at time t only if all the required item types were replenished between the release date of the job and time point t. The ordering of item types for distinct jobs can be combined. The objective is to minimize the total ordering cost plus a scheduling criterion, such as total weighted completion time or maximum flow time, where the cost of ordering a subset of items simultaneously is the sum of a joint ordering cost, and an additional item ordering cost for each item type in the subset. We provide several complexity results for the offline problem, and competitive analysis for online variants with min–sum and min–max criteria, respectively.
MAP inference algorithms without approximation for collective graphical models on path graphs via discrete difference of convex algorithm
Authors: Akagi Yasunori , Marumo Naoki , Kim Hideaki , Kurashima Takeshi , Toda Hiroyuki 
Published: December 2022

AbstractCollective graphical model (CGM) is a probabilistic model that provides a framework for analyzing aggregated count data. Maximum a posteriori (MAP) inference of unobserved variables under given observations is one of the essential operations in CGM. Because the MAP inference problem is known to be NP-hard in general, the current mainstream approach is to solve an alternative problem obtained by approximating the objective function and applying continuous relaxation. However, this approach has two significant drawbacks. First, the quality of the solution deteriorates when the values in the count data are negligible due to the inaccuracy of Stirling’s approximation. Second, the application of continuous relaxation causes the violation of integrality constraints. This paper proposes novel algorithms for MAP inference in CGMs on path graphs to overcome these problems. Our method is based on the discrete difference of convex algorithm (DCA); DCA is a general framework to minimize the sum of a convex function and a concave function by repeatedly minimizing surrogate functions. Utilizing the particular structure of path graphs, we efficiently solve the surrogate function minimization by minimum convex cost flow algorithms. Furthermore, our approach also leads to a new method of solving another important task; MAP inference of the sample size in CGM on path graphs. Our method is naturally applicable to this task, allowing us to design very efficient algorithms. Experimental results on synthetic and real-world datasets show the effectiveness of the proposed algorithms.