bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alternative Weltordnungen. Stärkt Russlands Ukraine-Krieg internationale Antagonismen?
Authors: Schirm Stefan A. 
Published: December 2022

ZusammenfassungRusslands Überfall auf die Ukraine schärft die Konturen internationaler Antagonismen. Die unterschiedlichen Lager bestanden allerdings seit längerem und formierten sich in den letzten zwei Dekaden bereits deutlich. Dem politischen Westen mit seinen postulierten Werten der Demokratie, Marktwirtschaft, Menschenrechte und friedlichen Konfliktbeilegung steht zunehmend ein politischer Süden gegenüber, der nationale Autonomie, Nicht-Einmischung in interne Angelegenheiten und staatlich gesteuerte wirtschaftliche Entwicklung priorisiert. Der politische Süden verweigert sich der westlichen Militärhilfe für die Ukraine sowie den Sanktionen gegen Russland, pflegt nach wie vor enge Beziehungen zu Moskau und kritisiert westliche Weltordnungsansprüche als Bevormundung. Zentrale Akteure sind hierbei die Schwellenländer der BRICS, die in der letzten Dekade die Schaffung neuer internationaler Organisationen als Alternativen zu den westlich dominierten Institutionen der Liberal International Order (LIO) vorantrieben. Allerdings haben die Staaten des Südens die Institutionen der LIO nicht verlassen und führen meist ihre intensiven Wirtschaftsbeziehungen mit dem Westen weiter.
Fundamentalism and modernity: the case of Theravada
Authors: Frasch Tilman 
Published: December 2022

AbstractThe article investigates the possibility of the Theravada fraternity at the Mahavihara monastery of Sri Lanka became a ‘fundamentalist’ movement especially in its quarrel with king Mahasena in the 4th century CE. Beginning with defining the crucial constituents of fundamentalism, the article explores the major organisational and religious conflict lines between the three monastic traditions and highlights the use of Pali as a specific language to encode the canon. Though not all of the aspects of the definition are met, the Mahavihara showed clear signs of an inward-looking, exclusivist and scripturalist movement; features that it shares with ‘fundamentalist’ movements. The article thus questions the relatively fixed connection between fundamentalism and modernity, which is a common feature of current research on fundamentalism.
The action of enhancing weak light capture via phototropic growth and chloroplast movement in plants
Authors: Xin Guang-yuan , Li Lu-ping , Wang Peng-tao , Li Xin-yue , Han Yuan-ji , Zhao Xiang 
Published: December 2022

AbstractTo cope with fluctuating light conditions, terrestrial plants have evolved precise regulation mechanisms to help optimize light capture and increase photosynthetic efficiency. Upon blue light-triggered autophosphorylation, activated phototropin (PHOT1 and PHOT2) photoreceptors function solely or redundantly to regulate diverse responses, including phototropism, chloroplast movement, stomatal opening, and leaf positioning and flattening in plants. These responses enhance light capture under low-light conditions and avoid photodamage under high-light conditions. NON-PHOTOTROPIC HYPOCOTYL 3 (NPH3) and ROOT PHOTOTROPISM 2 (RPT2) are signal transducers that function in the PHOT1- and PHOT2-mediated response. NPH3 is required for phototropism, leaf expansion and positioning. RPT2 regulates chloroplast accumulation as well as NPH3-mediated responses. NRL PROTEIN FOR CHLOROPLAST MOVEMENT 1 (NCH1) was recently identified as a PHOT1-interacting protein that functions redundantly with RPT2 to mediate chloroplast accumulation. The PHYTOCHROME KINASE SUBSTRATE (PKS) proteins (PKS1, PKS2, and PKS4) interact with PHOT1 and NPH3 and mediate hypocotyl phototropic bending. This review summarizes advances in phototropic growth and chloroplast movement induced by light. We also focus on how crosstalk in signaling between phototropism and chloroplast movement enhances weak light capture, providing a basis for future studies aiming to delineate the mechanism of light-trapping plants to improve light-use efficiency.
Modeling the growth of H2S-producing bacteria in tropical brackish water shrimp under fluctuating temperature regimes
Authors: Dabadé D. Sylvain , Zannou Oscar , Azokpota Paulin , Hounhouigan D. Joseph 
Published: December 2022

AbstractH2S-producing bacteria are known to be an important group of spoilage organisms associated with tropical brackish water shrimp (Penaeus notialis). This study aimed at developing a mathematical model predicting the growth of H2S-producing bacteria in P. notialis as a function of temperature for a better shrimp quality management. Shrimp samples were stored at various temperatures from 0 to 28 °C. At appropriate time intervals, samples were taken out for the enumeration of H2S-producing bacteria. Two primary models (the Baranyi model and the reparameterized Gompertz model) and two secondary models (the Ratkowsky equation and the Arrhenius equation) were used for comparison purpose. The developed model was validated under fluctuating storage temperatures simulating temperature fluctuation in the shrimp supply chain. The results showed that the initial concentration of H2S-producing bacteria was 3.6 ± 0.1 log (CFU/g). The maximum concentration reached at the end of storage was temperature dependent. As expected, storage temperature had a significant effect (P < 0.05) on growth rates of H2S-producing bacteria during shrimp storage. The reparameterized Gompertz model and the Arrhenius equation performed better (lower root mean square error of the residuals) and were selected as primary and secondary models, respectively in this study. The validation of the developed model showed that it can be used to predict satisfactorily the growth of H2S-producing bacteria, thus to predict the shelf-life of tropical brackish water shrimp.
Quantum remote sensing with atom-light entangled interface
Authors: Shi Minwei , Ming Sheng , Wu Shuhe , Zhang Dong , Du Wei , Yang Peiyu , Bao Guzhi , Guo Jinxian , Zhang Weiping 
Published: December 2022

AbstractQuantum remote sensing utilizes quantum entanglement between the probe and the receiver to enhance the capability to sense a remote target. Quantum illumination is considered as a promising protocol to realize such a quantum technology in an environment of high loss and intense noise. However, the protocol requires an additional on-demand quantum memory, the imperfect performance of which diminishes the quantum advantage and limits the enhancement of sensing. In this paper, we propose a new protocol for quantum remote sensing based on quantum illumination with atom-light entangled interface. Compared to conventional light-only quantum illumination, the proposed protocol utilizes Raman coupling to create a long-lived atomic spin wave entangled with a Stokes light. The atomic spin wave, automatically built-in memory via the Raman coupling, acts as a local reference. The entangled Stokes light is used as a probe to irradiate a remote target. Meanwhile, the returned probe light from target is detected through coupling again to the atomic spin wave. A joint measurement on the returned probe light and spin wave is performed to discriminate the target. A 4 dB quantum enhancement over classical illumination is estimated. The atom-light entangled interface naturally integrates the quantum source, quantum memory, and quantum receiver in a single unit which exhibits great potential to develop highly compact and portable devices for quantum-enhanced remote sensing.
Addressing misalignments to improve the US health care system by integrating patient-centred care, patient-centred real-world data, and knowledge-sharing: a review and approaches to system alignment
Authors: Levine Douglas S. , Drossman Douglas A. 
Published: December 2022

Abstract
Background
The ills of the United States health care system have been debated for decades. Imbalance in the system’s strengths and performance shortfalls stem from misalignments among system participants.

Methods
We examine the conflicts that health care system participants provoke in essential features of health care—information, products, services, and access—using a two-part model. The first part comprises patient-provider relationships that give rise to patient-centred care. The second part includes stakeholders that influence patient-provider relationships but do not provide direct patient care. Misalignments between these parts interfere with the system’s quadruple aim: to improve population health, enhance both patient and provider care experiences, and reduce per-capita costs.

Results
Knowledge-sharing and documented practices and tools to implement patient-centred care and use real-world data can help to align the health care system. Patients, providers, and stakeholders should meet patient-centred care objectives because the patient should be the centre of all health care system operations. Alignment is driven by patient-centred real-world data generated by patient-provider relationships and used by stakeholders. Patient-centred real-world data reveal informative portrayals of patient preferences, health outcomes, resource utilization, and costs across subpopulations. These data enable stakeholders to produce patient-centred information, products, services, and access. These stakeholder outputs meet patients’ individual needs, support providers’ personalized care, and improve system-wide care quality, satisfaction, outcomes, and cost-effectiveness.

Conclusions
Patient-centred real-world data are valuable commodities and an aligning force. The United States health care system must remove barriers to providers’ patient-centred care practices, use patient-centred real-world data generated from ideal patient-provider relationships, and prioritize patient-centred care among all participants.
Machine Learning for Lung Cancer Diagnosis, Treatment, and Prognosis
Authors: Li Yawei , Wu Xin , Yang Ping , Jiang Guoqian , Luo Yuan 
Published: December 2022

Abstract
The recent development of imaging and sequencing technologies enables systematic advances in the clinical study of lung cancer. Meanwhile, the human mind is limited in effectively handling and fully utilizing the accumulation of such enormous amounts of data. Machine learning-based approaches play a critical role in integrating and analyzing these large and complex datasets, which have extensively characterized lung cancer through the use of different perspectives from these accrued data. In this review, we provide an overview of machine learning-based approaches that strengthen the varying aspects of lung cancer diagnosis and therapy, including early detection, auxiliary diagnosis, prognosis prediction, and immunotherapy practice. Moreover, we highlight the challenges and opportunities for future applications of machine learning in lung cancer.
A fuzzy model to predict the mechanical characteristics of friction stir welded joints of aluminum alloy AA2014-T6
Authors: Ashok S.K. , Ponni alias sathya S. 
Published: December 2022

AbstractFriction stir welding is a prominent technique for making defect-free joints of aluminum alloys. The aluminum alloy AA2014-T6 finds wide applications in aerospace, naval and automotive applications. This paper attempts to predict the tensile strength and hardness characteristics of friction stir welded aluminum alloy AA2014-T6 by a fuzzy logic model. Friction stir welding was carried out by varying tool rotational speed (700, 1,000 and 1,400rpm), welding speed (20, 35, 50mm/min) and axial force (10, 12, 14kN) at three levels. The tensile strength and hardness characteristics of the welded specimens were obtained from the experiments conducted as per Taguchi’s L27 orthogonal array. A Mamdani-type fuzzy logic model was developed to predict the tensile strength and nugget hardness characteristics of the FSW joints. The fuzzy model was evaluated by comparing the results of confirmation experiments with that of the results predicted by the model. The confirmation experiments were conducted with a new set of parameters other than the ones used for building the model. The fuzzy model exhibits marginal variations of 2.53% for tensile strength and 2.42% for weld nugget hardness compared to the results of the conformation experiments.
Thrombolysis in Stroke Mimics: Comprehensive Stroke Centers vs Telestroke Sites
Authors: Nair Radhika , Khan Khurshid , Stang Jillian M. , Halabi Mary-Lou , Youngson Erik , Alrohimi Anas , Shuaib Ashfaq 
Published: December 2022

ABSTRACT:Background:Hyperacute treatment of acute stroke may lead to thrombolysis in stroke mimics (SM). Our aim was to determine the frequency of thrombolysis in SM in primary stroke centers (PSC) dependent on telestroke versus comprehensive stroke centers (CSC).Method:Retrospective review of prospectively collected data from the Quality improvement and Clinical Research (QuICR) registry, the Discharge Abstract Database (DAD), and The National Ambulatory Care Reporting System (NACRS) of consecutive patients treated with intravenous thrombolysis for acute ischemic stroke in Alberta (Canada) from April 2016 to March 2021.Result:A total of 2471 patients who received thrombolysis were included. Linking the QuICR registry to DAD 169 (6.83%) patients were identified as SM; however, on our review of the records, only 112 (4.53%) were actual SM. SMs were younger with a mean age of 61.66 (±16.15) vs 71.08 (±14.55) in stroke. National Institute of Health Stroke Scale was higher in stroke with a median (IQR) of 10 (5–17) vs 7 (5–10) in SM. Only one patient (0.89 %) in SM groups had a small parenchymal hemorrhage versus 155 (6.57%) stroke patients had a parenchymal hemorrhage. There was no death among patients of thrombolysed SM during hospitalization versus 276 (11.69%) in stroke. There was no significant difference in the rate of SM among thrombolysed patients between PSC 27 (5.36%) versus CSC 85 (4.3%) (P = 0.312). The most responsible diagnosis of SM was migraine/migraine equivalent, functional disorder, seizure, and delirium.Conclusion:The diagnosis of SM may not always be correct when the information is extracted from databases. The rate of thrombolysis in SM via telestroke is similar to treatment in person at CSC.
A comparison of methods for microbiologic environmental sampling
Authors: Thompson Sharon C. , Rutala William A. , Sickbert-Bennett Emily E. , DiBiase Lauren M. , Anderson Deverick J. , Weber David J. ,   for the Centers of Disease Control and Prevention Epicenters Program
Published: December 2022

AbstractWe compared the effectiveness of 4 sampling methods to recover Staphylococcus aureus, Klebsiella pneumoniae and Clostridioides difficile from contaminated environmental surfaces: cotton swabs, RODAC culture plates, sponge sticks with manual agitation, and sponge sticks with a stomacher. Organism type was the most important factor in bacterial recovery.
Lack of correlation between standardized antimicrobial administration ratios (SAARs) and healthcare-facility–onset Clostridioides difficile infection rates in Veterans Affairs medical facilities
Authors: Evans Martin E. , Jones Makoto M. , Davis Kelly W. , Lane Matthew T. , Simbartl Loretta A. , McCauley Brian P. , Gauldin Natalie , Roselle Gary A. 
Published: December 2022

AbstractWe detected no correlation between standardized antimicrobial administration ratios (SAARs) and healthcare facility-onset Clostridioides difficile infection (HO-CDI) rates in 102 acute-care Veterans Affairs medical centers over 16 months. SAARs may be useful for investigating trends in local antimicrobial use, but no ratio threshold demarcated HO-CDI risk.
Assessing the Credibility of Constitutional Experts
Authors: Braman Eileen 
Published: December 2022

AbstractThis study investigates how citizens assess the credibility of constitutional experts on matters of government authority. Analyses of data from two similarly designed experiments, conducted with national samples, reveal that partisanship, race, and level of education are significant predictors of survey respondents’ willingness to extend credibility to constitutional experts. The compatibility of the views expressed by experts with respondents’ own policy views on issues that are the subject of proposed government action is also important. Evidence shows that this consistency is more important in the decision that experts are credible than in decisions that they are not credible, suggesting that esteem motives are relevant in the decision to credit experts who express views congenial to our own that are distinct from social-identity motives scholars have theorized to be important in partisan resistance to expertise. The implications of findings for holding government officials accountable to constitutional limits on government authority are considered.
COMPLETE LOGICS FOR ELEMENTARY TEAM PROPERTIES
Authors: KONTINEN JUHA , YANG FAN 
Published: December 2022

AbstractIn this paper, we introduce a logic based on team semantics, called
$\mathbf {FOT} $
, whose expressive power is elementary, i.e., coincides with first-order logic both on the level of sentences and (possibly open) formulas, and we also show that a sublogic of
$\mathbf {FOT} $
, called
$\mathbf {FOT}^{\downarrow } $
, captures exactly downward closed elementary (or first-order) team properties. We axiomatize completely the logic
$\mathbf {FOT} $
, and also extend the known partial axiomatization of dependence logic to dependence logic enriched with the logical constants in
$\mathbf {FOT}^{\downarrow } $
.
Statutory interpretation after Brexit: implications from a case study of VAT
Authors: Zu Yige 
Published: December 2022

AbstractAs the UK left the European Union, a new body of UK law, labelled ‘retained EU law’, was introduced to save and convert certain parts of EU law into UK statutes. This paper explores the impact of Brexit on statutory interpretation in the UK in the context of VAT. In particular, it looks at whether, and the manner in which, UK courts and the Court of Justice of the European Union (CJEU) will move in different directions when interpreting what is essentially the same law. The paper predicts the post-Brexit evolution of statutory interpretation in UK courts based on an empirical study of cases concerning VAT referred by UK courts to the CJEU between 1973 and 2020, augmented by a doctrinal analysis of selected cases. The methodology is built on the premise that past case decisions may provide an indication of the nature of possible future divergence. A case study of VAT may offer wider implications as to departure from the CJEU jurisprudence in other legal areas in the coming years.
Common index divisor of the number fields defined by
Authors: Jakhar Anuj , Kaur Sumandeep , Kumar Surender 
Published: December 2022

AbstractLet $K={\mathbf {Q}}(\theta )$ be an algebraic number field with $\theta$ a root of an irreducible polynomial $x^5+ax+b\in {\mathbf {Z}}[x]$. In this paper, for every rational prime $p$, we provide necessary and sufficient conditions on $a,\,~b$ so that $p$ is a common index divisor of $K$. In particular, we give sufficient conditions on $a,\,~b$ for which $K$ is non-monogenic. We illustrate our results through examples.
Green fodder cultivation improves technical efficiency of dairy farmers in semi-arid tropics of central India: a micro-analysis
Authors: Choudhary Bishwa Bhaskar , Sharma Purushottam , Singh Priyanka , Kumar Sunil , Gupta Gaurendra , Kantwa S. R. , Upadhyay Deepak , Wasnik Vinod Kumar , Prasad Mahendra , Sharma R. K. 
Published: December 2022

AbstractThis study assessed the impact of improved green fodder production activities on technical efficiency (TE) of dairy farmers in climate vulnerable landscapes of central India. We estimated stochastic production frontiers, considering potential self-selection bias stemming from both observable and unobservable factors in adoption of fodder interventions at farm level. The empirical results show that TE for treated group ranges from 0.55 to 0.59 and that for control ranges from 0.41 to 0.48, depending on how biases are controlled. Additionally, the efficiency levels of both adopters and non-adopters would be underestimated if the selectivity bias is not appropriately accounted. As the average TE is consistently higher for adopter farmers than the control group, promoting improved fodder cultivation would increase input use efficiency, especially in resource-deprived small holder dairy farmers in the semi-arid tropics.
Deep problems with neural network models of human vision
Authors: Bowers Jeffrey S. , Malhotra Gaurav , Dujmović Marin , Llera Montero Milton , Tsvetkov Christian , Biscione Valerio , Puebla Guillermo , Adolfi Federico , Hummel John E. , Heaton Rachel F. , Evans Benjamin D. , Mitchell Jeffrey , Blything Ryan 
Published: December 2022

Abstract
Deep neural networks (DNNs) have had extraordinary successes in classifying photographic images of objects and are often described as the best models of biological vision. This conclusion is largely based on three sets of findings: (1) DNNs are more accurate than any other model in classifying images taken from various datasets, (2) DNNs do the best job in predicting the pattern of human errors in classifying objects taken from various behavioral datasets, and (3) DNNs do the best job in predicting brain signals in response to images taken from various brain datasets (e.g., single cell responses or fMRI data). However, these behavioral and brain datasets do not test hypotheses regarding what features are contributing to good predictions and we show that the predictions may be mediated by DNNs that share little overlap with biological vision. More problematically, we show that DNNs account for almost no results from psychological research. This contradicts the common claim that DNNs are good, let alone the best, models of human object recognition. We argue that theorists interested in developing biologically plausible models of human vision need to direct their attention to explaining psychological findings. More generally, theorists need to build models that explain the results of experiments that manipulate independent variables designed to test hypotheses rather than compete on making the best predictions. We conclude by briefly summarizing various promising modeling approaches that focus on psychological data.
Constant rank factorisations of smooth maps, with applications to sonar
Authors: Robinson Michael 
Published: December 2022

AbstractSonar systems are frequently used to classify objects at a distance by using the structure of the echoes of acoustic waves as a proxy for the object’s shape and composition. Traditional synthetic aperture processing is highly effective in solving classification problems when the conditions are favourable but relies on accurate knowledge of the sensor’s trajectory relative to the object being measured. This article provides several new theoretical tools that decouple object classification performance from trajectory estimation in synthetic aperture sonar processing. The key insight is that decoupling the trajectory from classification-relevant information involves factoring a function into the composition of two functions. The article presents several new general topological invariants for smooth functions based on their factorisations over function composition. These invariants specialise to the case when a sonar platform trajectory is deformed by a non-small perturbation. The mathematical results exhibited in this article apply well beyond sonar classification problems. This article is written in a way that supports full mathematical generality.