bluuebunny/crossref_metadata_2025_split huggingface dataset:
Origins, motives, and challenges in Western–Chinese research collaborations amid recent geopolitical tensions: findings from Swedish–Chinese research collaborations
Authors: Shih Tommy , Forsberg Erik 
Published: April 2022

AbstractUntil recently, modern science had been dominated by a handful of Western countries. However, since the turn of the millennium, the global science landscape has undergone dramatic changes. The number of nations where a significant proportion of research done is of high international standard has now increased considerably. China particularly stands out and is today one of the leading science nations in the world. Overall, Chinese research collaborations with countries in the Western world exemplify the general trend towards increasing complexity in the global research landscape. It has gradually become obvious that differences between institutional settings need to be managed more systematically to promote cross-border research cooperation for shared benefits, from individual to institutional levels. An informed discussion of managing complex conditions necessitates an understanding of the relationship-level dynamics of research collaborations. In order to identify what aspects of international research collaborations are the most pertinent to systematically manage at individual and institutional levels, this paper investigates projects in a bilateral Swedish–Chinese funding program. The paper finds that the majority of collaborations funded had yielded positive impact in terms of publications, strengthened research capacity in research groups, and resource accumulation. The challenges found in the collaborations are related to needs such as improving transparency, ethical concerns, and imbalances in reciprocity.
Impact of JAK Inhibitors in Pediatric Patients with STAT1 Gain of Function (GOF) Mutations—10 Children and Review of the Literature
Authors: Deyà-Martínez Angela , Rivière Jaques G. , Roxo-Junior Pérsio , Ramakers Jan , Bloomfield Markéta , Guisado Hernandez Paloma , Blanco Lobo Pilar , Abu Jamra Soraya Regina , Esteve-Sole Ana , Kanderova Veronika , García-García Ana , Lopez-Corbeto Mireia , Martinez Pomar Natalia , Martín-Nalda Andrea , Alsina Laia , Neth Olaf , Olbrich Peter 
Published: April 2022

Abstract
Introduction
Since the first description of gain of function (GOF) mutations in signal transducer and activator of transcription (STAT) 1, more than 300 patients have been described with a broad clinical phenotype including infections and severe immune dysregulation. Whilst Jak inhibitors (JAKinibs) have demonstrated benefits in several reported cases, their indications, dosing, and monitoring remain to be established.

Methods
A retrospective, multicenter study recruiting pediatric patients with STAT1 GOF under JAKinib treatment was performed and, when applicable, compared with the available reports from the literature.

Results
Ten children (median age 8.5 years (3–18), receiving JAKinibs (ruxolitinib (n = 9) and baricitinib (n = 1)) with a median follow-up of 18 months (2–42) from 6 inborn errors of immunity (IEI) reference centers were included. Clinical profile and JAKinib indications in our series were similar to the previously published 14 pediatric patients. 9/10 (our cohort) and 14/14 patients (previous reports) showed partial or complete responses. The median immune deficiency and dysregulation activity scores were 15.99 (5.2–40) pre and 7.55 (3–14.1) under therapy (p = 0.0078). Infection, considered a likely adverse event of JAKinib therapy, was observed in 1/10 patients; JAKinibs were stopped in 3/10 children, due to hepatotoxicity, pre-HSCT, and absence of response.

Conclusions
Our study supports the potentially beneficial use of JAKinibs in patients with STAT1 GOF, in line with previously published data. However, consensus regarding their indications and timing, dosing, treatment duration, and monitoring, as well as defining biomarkers to monitor clinical and immunological responses, remains to be determined, in form of international prospective multicenter studies using established IEI registries.
Genetic Testing in Egyptian Patients with Inborn Errors of Immunity: a Single-Center Experience
Authors: EL Hawary Rabab E. , Meshaal Safa S. , Abd Elaziz Dalia S. , Alkady Radwa , Lotfy Sohilla , Eldash Alia , Erfan Aya , Chohayeb Engy A. , Saad Mai M. , Darwish Rania K. , Boutros Jeannette A. , Galal Nermeen M. , Elmarsafy Aisha M. 
Published: April 2022

Abstract
Background
Inborn errors of immunity (IEI) are a group of heterogeneous disorders with geographic and ethnic diversities. Although IEI are common in Egypt, genetic diagnosis is limited due to financial restrictions. This study aims to characterize the genetic spectrum of IEI patients in Egypt and highlights the adaptation of the molecular diagnostic methods to a resource-limited setting.

Methods
Genetic material from 504 patients was studied, and proper diagnosis was achieved in 282 patients from 246 families. Mutational analysis was done by Sanger sequencing, next-generation sequencing (NGS) targeting customized genes panels, and whole-exome sequencing (WES) according to the patients’ phenotypes and availability of genetic testing.

Results
A total of 194 variants involving 72 different genes were detected with RAG1/2 genes being the most encountered followed by DOCK8, CYBA, LRBA, NCF1, and JAK3. Autosomal recessive (AR) inheritance was detected in 233/282 patients (82.6%), X-linked (XL) recessive inheritance in 32/282 patients (11.3%), and autosomal dominant (AD) inheritance in 18/282 patients (6.4%), reflecting the impact of consanguineous marriages on the prevalence of different modes of inheritance and the distribution of the various IEI disorders.

Conclusion
The study showed that a combination of Sanger sequencing in selected patients associated with targeted NGS or WES in other patients is an effective diagnostic strategy for IEI diagnosis in countries with limited diagnostic resources. Molecular testing can be used to validate other nonexpensive laboratory techniques that help to reach definitive diagnosis and help in genetic counseling and taking proper therapeutic decisions including stem cell transplantation or gene therapy.
Local Weather Conditions Affect Forager Size and Visitation Rate on Bramble Flowers (Rubus fruticosus) in Bumble Bees (Bombus spp)
Authors: Uthoff Cassandra , Ruxton Graeme 
Published: April 2022

AbstractBumble bees (Bombus; Hymenoptera) are crucial pollinators for many agricultural crops, but their numbers have declined - with climate change as a possible driver. Different aspects of local weather conditions can have substantial effects on bumble bees’ ability to forage. Here we made 501 observations of bumblebee workers on bramble flowers (Rubus fruticosus) to explore how the characteristic sizes of foragers active and their individual rate of movement between flowers were correlated with aspects of weather. Firstly, we found that increased ambient temperature is correlated to reduced activity in larger workers. Moreover, while higher humidity was linked to an increase in smaller workers, an increase in cloud cover led their numbers to decrease. Visitation rate and temperature showed a significant negative relationship whereas no other weather aspect affected visitation rate significantly. Our results suggest that predicted rises in ambient temperatures will adversely affect bumble bee foraging, and particularly so for larger-bodied workers. We anticipate that this study can be used as a foundation for longer-term and more detailed studies on bumble bee foraging and colony performance. Such work is vital to identify management measures to mitigate pollinator declines and preserve food security.
Characterising a Single-Photon Detector for ALPS II
Authors: Shah Rikhav , Isleif Katharina-Sophie , Januschek Friederike , Lindner Axel , Schott Matthias 
Published: April 2022

AbstractTransition Edge Sensors (TESs) have found widespread application in fundamental studies due to their low background rate, high efficiency, and excellent energy resolution. This makes them suitable candidates for ALPS II, which investigates the existence of new particles (axions and axion-like-particles) which couple very weakly to photons. ALPS II anticipates an extremely low signal rate $$<10^{-5}$$

<

10

-
5

cps (amounting to $$\sim $$
∼
1–2 photons a day). The detection of these low energy ($$\sim $$
∼
1 eV, 1064 nm) photons with a high energy resolution is necessary for ALPS II. We show that with our TES setup, we can analyze the TES pulses with different methods such as pulse fitting and Principal Component Analysis (PCA). These achieve (using the standard deviation) an energy resolution ($$\Delta E/E$$

Δ
E
/
E

) down to $$\sim 8\%$$

∼
8
%

. The pulse analysis, with a chosen fitting approach, assists also in achieving a very low dark count rate $$\mathcal {O}\left( 10^{-6} \right) $$

O

10

-
6

cps for 1064 nm photon signal searches in the TES.
A polynomial variant of diophantine triples in linear recurrences
Authors: Fuchs Clemens , Heintze Sebastian 
Published: April 2022

AbstractLet $$ (G_n)_{n=0}^{\infty } $$

(

G
n

)

n
=
0

∞

be a polynomial power sum, i.e. a simple linear recurrence sequence of complex polynomials with power sum representation $$ G_n = f_1\alpha _1^n + \cdots + f_k\alpha _k^n $$

G
n

=

f
1

α
1
n

+
⋯
+

f
k

α
k
n

and polynomial characteristic roots $$ \alpha _1,\ldots ,\alpha _k $$

α
1

,
…
,

α
k

. For a fixed polynomial p, we consider sets $$ \left\{ a,b,c \right\} $$

a
,
b
,
c

consisting of three non-zero polynomials such that $$ ab+p, ac+p, bc+p $$

a
b
+
p
,
a
c
+
p
,
b
c
+
p

are elements of $$ (G_n)_{n=0}^{\infty } $$

(

G
n

)

n
=
0

∞

. We will prove that under a suitable dominant root condition there are only finitely many such sets if neither $$ f_1 $$

f
1

nor $$ f_1 \alpha _1 $$

f
1

α
1

is a perfect square.
Development and validation of the Remote Working Benefits & Disadvantages scale
Authors: Ingusci Emanuela , Signore Fulvio , Cortese Claudio Giovanni , Molino Monica , Pasca Paola , Ciavolino Enrico 
Published: April 2022

AbstractThe changes that are constantly occurring in the labour sector have led organisations and companies to move towards digital transformation. This process was accelerated by the COVID-19 pandemic and conducted to a massive recourse to the practice of remote working, which in this study is understood as the term for the way of performing work outside the usual workplace and with the support of ICT. Currently, there are no flexible scales in the literature that allow measuring the benefits and disadvantages of remote working with a single instrument. Thus, the distinction between the positive and negative consequences of working remotely, substantiated by a solid literature, provides a framework for a systematical understanding of the issue. The aim of the present study is to develop and validate a scale on remote working benefits and disadvantages (RW-B&D scale). For this end, a preliminary Exploratory Factor Analysis (EFA) with 304 participants, a tailored EFA with a sample of 301 workers and a Confirmatory Factor Analysis (CFA) with 677 workers were conducted. Participants were all Italian employees who worked remotely during the period of the COVID-19 health emergency. Data were collected between October 2020 and April 2021. The psychometric robustness of the model was assessed through bootstrap validation (5000 resamples), fit indices testing and measurement of factorial invariance. The statistical analyses demonstrated the bifactorial nature of the scale, supporting the research hypothesis. The model showed good fit indices, bootstrap validation reported statistically significant saturations, good reliability indices, and convergent and discriminant validity. Measurement invariance was tested for gender and organisational sector. The results suggested that the novel scale facilitates the quantitative measurement of the benefits and disadvantages associated with remote working in empirical terms. For this reason, it could be a streamlined and psychometrically valid instrument to identify the potential difficulties arising from remote working and, at the same time, the positive aspects that can be implemented to improve organisational well-being.
The effects of U.S. county and state income inequality on self-reported happiness and health are equivalent to zero
Authors: Sommet Nicolas , Elliot Andrew J. 
Published: April 2022

Abstract
Purpose
A popular idea in the social sciences is that contexts with high income inequality undermine people’s well-being and health. However, existing studies documenting this phenomenon typically compare a small number of higher-level units (countries/regions). Here, we use local income inequality indicators and temporal designs to provide the most highly powered test to date of the associations between income inequality and self-reported happiness and health in the US﻿A

Method
We combined county-level income inequality data (county-level Gini coefficients) with the responses from the General Social Survey (GSS) Cross-sectional dataset (13,000 + participants from ≈1000 county-waves) and Panels (3 × 3000 + participants from 3 × ≈500 county-waves); we used the GSS happiness (“not too happy,” “pretty happy,” or “very happy”) and health (“poor,” “fair,” “good,” or “excellent”) variables.

Results
Multilevel-ordered logistic models and equivalence tests revealed that the within-county effects of income inequality on self-reported happiness and health were systematically equivalent to zero. Additional analyses revealed that the within-state effects were identical, that using alternative measures of state income inequality led to the same conclusions, and that lagged effects (between + 1 and + 12 years) were never significant and always equivalent to zero.

Conclusion
The present work suggests that—at least in the USA—income inequality is likely neither associated with self-reported happiness nor with self-reported health.
Pharmacosimulation of delays and interruptions during administration of tirofiban: a systematic comparison between EU and US dosage regimens
Authors: Heramvand Nadia , Masyuk Maryna , Muessig Johanna M. , Nia Amir M. , Karathanos Athanasios , Polzin Amin , Valgimigli Marco , Gurbel Paul A. , Tantry Udaya S. , Kelm Malte , Jung Christian 
Published: April 2022

AbstractTirofiban is a glycoproteine (GP) IIb/IIIa receptor antagonist, which inhibits platelet-platelet aggregation and is a potential adjunctive antithrombotic treatment in patients with acute coronary syndromes (ACS) or high-risk percutaneous coronary interventions (PCI). It is administered intravenously as a bolus followed by continuous infusion. However, the dosage recommendations in the United States (US) and European Union (EU) differ considerably. Furthermore, in routine clinical practice, deviations from the recommendations may occur. The objective of the present study was to investigate the impact of different alterations on tirofiban plasma concentrations in US and EU administration regimens and to give suggestions for delay management in clinical practice. We therefore mathematically simulated the effects of different bolus-infusion delays and infusion interruptions in different scenarios according to the renal function. Here, we provide a systematic assessment of concentration patterns of tirofiban in the US versus EU dosage regimens. We show that differences between the two regimens have important effects on plasma drug levels. Furthermore, we demonstrate that deviations from the proper administration mode affect the concentration of tirofiban. Additionally, we calculated the optimal dosage of a second bolus to rapidly restore the initial concentration without causing overdosage. In conclusion, differences in tirofiban dosing regimens between the U.S and EU and potential infusion interruptions have important effects on drug levels that may impact on degrees of platelet inhibition and thus antithrombotic effects. Thus, the findings of our modelling studies may help to explain differences in clinical outcomes observed in previous clinical trials on tirofiban.
Optimal Exposure Time in Gamma-Ray Attenuation Experiments for Monitoring Time-Dependent Densities
Authors: Gonzalez-Nicolas Ana , Bilgic Deborah , Kröker Ilja , Mayar Assem , Trevisan Luca , Steeb Holger , Wieprecht Silke , Nowak Wolfgang 
Published: April 2022

AbstractSeveral environmental phenomena require monitoring time-dependent densities in porous media, e.g., clogging of river sediments, mineral dissolution/precipitation, or variably-saturated multiphase flow. Gamma-ray attenuation (GRA) can monitor time-dependent densities without being destructive or invasive under laboratory conditions. GRA sends gamma rays through a material, where they are attenuated by photoelectric absorption and then recorded by a photon detector. The attenuated intensity of the emerging beam relates to the density of the traversed material via Beer–Lambert’s law. An important parameter for designing time-variable GRA is the exposure time, the time the detector takes to gather and count photons before converting the recorded intensity to a density. Large exposure times capture the time evolution poorly (temporal raster error, inaccurate temporal discretization), while small exposure times yield imprecise intensity values (noise-related error, i.e. small signal-to-noise ratio). Together, these two make up the total error of observing time-dependent densities by GRA. Our goal is to provide an optimization framework for time-dependent GRA experiments with respect to exposure time and other key parameters, thus facilitating neater experimental data for improved process understanding. Experimentalists set, or iterate over, several experimental input parameters (e.g., Beer–Lambert parameters) and expectations on the yet unknown dynamics (e.g., mean and amplitude of density and characteristic time of density changes). We model the yet unknown dynamics as a random Gaussian Process to derive expressions for expected errors prior to the experiment as a function of key experimental parameters. Based on this, we provide an optimization framework that allows finding the optimal (minimal-total-error) setup and demonstrate its application on synthetic experiments.
Super-Resolved Segmentation of X-ray Images of Carbonate Rocks Using Deep Learning
Authors: Alqahtani Naif J. , Niu Yufu , Wang Ying Da , Chung Traiwit , Lanetc Zakhar , Zhuravljov Aleksandr , Armstrong Ryan T. , Mostaghimi Peyman 
Published: April 2022

AbstractReliable quantitative analysis of digital rock images requires precise segmentation and identification of the macroporosity, sub-resolution porosity, and solid\mineral phases. This is highly emphasized in heterogeneous rocks with complex pore size distributions such as carbonates. Multi-label segmentation of carbonates using classic segmentation methods such as multi-thresholding is highly sensitive to user bias and often fails in identifying low-contrast sub-resolution porosity. In recent years, deep learning has introduced efficient and automated algorithms that are capable of handling hard tasks with precision comparable to human performance, with application to digital rocks super-resolution and segmentation emerging. Here, we present a framework for using convolutional neural networks (CNNs) to produce super-resolved segmentations of carbonates rock images for the objective of identifying sub-resolution porosity. The volumes used for training and testing are based on two different carbonates rocks imaged in-house at low and high resolutions. We experiment with various implementations of CNNs architectures where super-resolved segmentation is obtained in an end-to-end scheme and using two networks (super-resolution and segmentation) separately. We show the capability of the trained model of producing accurate segmentation by comparing multiple voxel-wise segmentation accuracy metrics, topological features, and measuring effective properties. The results underline the value of integrating deep learning frameworks in digital rock analysis.
Influence-Aware Successive Point-of-Interest Recommendation
Authors: Cheng Xinghe , Li Ning , Rysbayeva Gulsim , Yang Qing , Zhang Jingwei 
Published: April 2022

AbstractIn recent years, with the rapid development of mobile applications, user check-in histories have been increasing. Successive point-of-interest (POI) recommendation has gained growing attention. Existing successive point-of-interest recommendation methods learn long- and short-term user preferences through historical check-in sequences to provide more personalized services. However, due to sparse data and complicated temporal patterns, the application of such technique is still limited by two challenges: 1) difficulty meeting user travel needs in time; 2) difficulty capturing users complicated behavior patterns. To address this problem, we propose a new Influence-Aware successive POI recommendation Model (InfAM), which can learn the influence of POIs in a short-term sequence fragment for next point-of-interest recommendation. To capture periodic patterns of user movements, InfAM takes a user’s check-in data within a day as an input sequence to address the current travel needs of the user. In addition, based on multihead attention mechanism and user embedding, InfAM focuses on the influence of POIs in short-term sequences and general user preferences in these sequences. Therefore, InfAM integrates three specific dependencies, which can fully learn the dynamic interaction between short-term preferences: the influence of POIs in short-term sequence fragments (POI-poi), user preferences (POI-user), and the periodicity of check-ins (POI-time). Evaluation results on real-world datasets show that InfAM achieves state-of-the-art recommendation performance.
Socioeconomic factors do not predict sleep apnea in a population sample from Mecklenburg-Western Pomerania, Germany
Authors: Krüger Markus , Obst Anne , Bernhardt Olaf , Ewert Ralf , Penzel Thomas , Stubbe Beate , Fietze Ingo , Ivanovska Tatyana , Biffar Reiner , Daboul Amro 
Published: April 2022

Abstract
Purpose
Socioeconomic factors are known to modulate health. Concerning sleep apnea, influences of income, education, work, and living in a partnership are established. However, results differ between national and ethnic groups. Results also differ between various clinical studies and population-based approaches. The goal of our study was to determine if such factors can be verified in the population of Pomerania, Germany.

Methods
A subgroup from the participants of the population-based Study of Health in Pomerania volunteered for an overnight polysomnography. Their data were subjected to an ordinal regressions analysis with age, sex, body mass index (BMI), income, education, work, and life partner as predictors for the apnea–hypopnea index.

Results
Among the subgroup (N = 1209) from the population-based study (N = 4420), significant effects were found for age, sex, and BMI. There were no significant effects for any of the socioeconomic factors.

Conclusion
Significant effects for well-established factors as age, sex, and BMI show that our study design has sufficient power to verify meaningful associations with sleep apnea. The lack of significant effects for the socioeconomic factors suggests their clinical irrelevance in the tested population.