bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accelerating digital business growth in a green economy and environmental sustainability
Authors: Natorina A , Bavyko O , Bondarchuk M , Brahina O , Puchkova S 
Published: January 2023

Abstract
It is supposed to consider that the main focus of digital businesses in a green economy and environmental sustainability is the implementation of a relevant and capable strategy of accelerating growth that provides the management system flexibility, which obviously contributes to rapid adaptation to the external environment and guarantee effective realization of the business potential. It is created and visualized the constructive basis for determining the strategy of accelerating digital business growth in a green economy and environmental sustainability. It is conceptualized the model of the determination of the strategy of accelerating digital business growth in a green economy and environmental sustainability as well as interpreted its mechanism. It is developed the matrix of the strategies of accelerating digital business growth in a green economy and environmental sustainability. The approbation of methodological tools allowed retailers to strengthen their competitive advantages due to the ability to quickly respond to any entropic phenomena and, in turn, contributed to the increase of rapid progressive development of their digital business.
Poland’s energy security during the transformation process in comparison with the EU countries
Authors: Bluszcz A , Manowska A , Tobór-Osadnik K , Wyganowska M 
Published: January 2023

Abstract
This article concerns the assessment of the level of energy independence of European Union countries, including Poland, based on selected indicators, such as: the level of final energy consumption in a household per capita, GDP per capita, GDP energy consumption, net import dependency ratio (NID). The article shows that the energy sector, mostly based on the great extent of hard coal and lignite (77%) in Poland is because of the rich amount of these resources in the country which in result makes it more self-sufficient than most EU countries. The mining sector in Poland is a strategic branch of the national economy and determines the country’s energy security, but its continuous transformation is still necessary mostly due to the variable conditions of said industry and how closely related they are to the ecological aspects. The article also refers to the economic situation of the studied mining regions in Poland, which in recent years have shown a significant downward trend in economic dynamics.
Analysis and modification of the ventilation network of an underground tourist mining facility in order to make new workings accessible
Authors: Słota K 
Published: January 2023

Abstract
The attractiveness of tourist facilities is based, among other things, on the continuous expansion of their offer. In the case of the underground mining facility, this will involve making new workings available for tours. To this end, analyses were carried out on the existing ventilation network, a model of the network was made and adapted to the future situation. In order to ventilate the new excavations, a new fan station, and a large diameter borehole were designed. Phases Ia, Ib, II and III of the changes to the ventilation network with a view to opening up a new chamber are presented.
Safety document for excavations used for tourism and recreation in the aspect of the new geological and mining law - theory and practice
Authors: Słota Zbigniew 
Published: January 2023

Abstract
Underground tourist routes are an important element of natural or cultural heritage. The primary document applicable to mining is the Law of June 9, 2011. Geological and Mining Law. The article presents the concept of a “safety document” in the aspect of the pending amendments to the Geological and Mining Law. Through these actions, Entities using or planning to use mine workings for tourism and recreation purposes were given guidelines and instructions on the correct construction, taking into account all the necessary elements, for the development of a comprehensive safety document for underground workings used for tourism and recreation purposes.
Learning curves for the multi-class teacher–student perceptron
Authors: Cornacchia Elisabetta , Mignacco Francesca , Veiga Rodrigo , Gerbelot Cédric , Loureiro Bruno , Zdeborová Lenka 
Published: January 2023

Abstract
One of the most classical results in high-dimensional learning theory provides a closed-form expression for the generalisation error of binary classification with a single-layer teacher–student perceptron on i.i.d. Gaussian inputs. Both Bayes-optimal (BO) estimation and empirical risk minimisation (ERM) were extensively analysed in this setting. At the same time, a considerable part of modern machine learning practice concerns multi-class classification. Yet, an analogous analysis for the multi-class teacher–student perceptron was missing. In this manuscript we fill this gap by deriving and evaluating asymptotic expressions for the BO and ERM generalisation errors in the high-dimensional regime. For Gaussian teacher, we investigate the performance of ERM with both cross-entropy and square losses, and explore the role of ridge regularisation in approaching Bayes-optimality. In particular, we observe that regularised cross-entropy minimisation yields close-to-optimal accuracy. Instead, for Rademacher teacher we show that a first-order phase transition arises in the BO performance.
Categorical representation learning and RG flow operators for algorithmic classifiers
Authors: Sheshmani Artan , You Yi-Zhuang , Fu Wenbo , Azizi Ahmadreza 
Published: January 2023

Abstract
Following the earlier formalism of the categorical representation learning, we discuss the construction of the ‘RG-flow-based categorifier’. Borrowing ideas from the theory of renormalization group (RG) flows in quantum field theory, holographic duality, and hyperbolic geometry and combining them with neural ordinary differential equation techniques, we construct a new algorithmic natural language processing architecture, called the RG-flow categorifier or for short the RG categorifier, which is capable of data classification and generation in all layers. We apply our algorithmic platform to biomedical data sets and show its performance in the field of sequence-to-function mapping. In particular, we apply the RG categorifier to particular genomic sequences of flu viruses and show how our technology is capable of extracting the information from given genomic sequences, finding their hidden symmetries and dominant features, classifying them, and using the trained data to make a stochastic prediction of new plausible generated sequences associated with a new set of viruses which could avoid the human immune system.
When Hay Was King
Authors: Ron Ariel 
Published: January 2023

Abstract
Hay was a linchpin of the early industrial energy regime. It was the primary fodder for working horses, who became more rather than less important over the 1800s. Though largely ignored by historians, hay was of comparable value to cotton and wheat in the nineteenth-century United States. The crop’s historiographical invisibility is partly due to its relatively informal and decidedly subglobal production and exchange patterns. Whereas cotton and wheat exports passed through customhouses and institutionalized exchanges that carefully recorded trade volumes, hay was almost never exported and often underwent no market transaction at all, instead being used as an intermediate good on farms. Only when the US federal government added a detailed agricultural census in 1850 did the magnitude and importance of hay production become publicly legible. At that point, hay was drafted into a wide-ranging debate about economic development between Northern antislavery nationalists and Southern proslavery free traders, with “King Hay” emerging as a foil for “King Cotton.” King Hay thus urges historians to pay more attention to the trade patterns, developmental policies, and economic ideologies that generated distinctly national, as opposed to global, economic spaces within nineteenth-century capitalism.
HelixGAN a deep-learning methodology for conditional de novo design of α-helix structures
Authors: Xie Xuezhi , Valiente Pedro A , Kim Philip M 
Published: January 2023

Abstract

Motivation
Protein and peptide engineering has become an essential field in biomedicine with therapeutics, diagnostics and synthetic biology applications. Helices are both abundant structural feature in proteins and comprise a major portion of bioactive peptides. Precise design of helices for binding or biological activity is still a challenging problem.

Results
Here, we present HelixGAN, the first generative adversarial network method to generate de novo left-handed and right-handed alpha-helix structures from scratch at an atomic level. We developed a gradient-based search approach in latent space to optimize the generation of novel α-helical structures by matching the exact conformations of selected hotspot residues. The designed α-helical structures can bind specific targets or activate cellular receptors. There is a significant agreement between the helix structures generated with HelixGAN and PEP-FOLD, a well-known de novo approach for predicting peptide structures from amino acid sequences. HelixGAN outperformed RosettaDesign, and our previously developed structural similarity method to generate D-peptides matching a set of given hotspots in a known L-peptide. As proof of concept, we designed a novel D-GLP1_1 analog that matches the conformations of critical hotspots for the GLP1 function. MD simulations revealed a stable binding mode of the D-GLP1_1 analog coupled to the GLP1 receptor. This novel D-peptide analog is more stable than our previous D-GLP1 design along the MD simulations. We envision HelixGAN as a critical tool for designing novel bioactive peptides with specific properties in the early stages of drug discovery.

Availability and implementation
https://github.com/xxiexuezhi/helix_gan.

Supplementary information
Supplementary data are available at Bioinformatics online.
The impact of atrial fibrillation on prognosis in aortic stenosis
Authors: Laenens Dorien , Stassen Jan , Galloo Xavier , Ewe See Hooi , Singh Gurpreet K , Ammanullah Mohammed R , Hirasawa Kensuke , Sia Ching-Hui , Butcher Steele C , Chew Nicholas W S , Kong William K F , Poh Kian Keong , Ding Zee P , Ajmone Marsan Nina , Bax Jeroen J 
Published: January 2023

Abstract

Background
Atrial fibrillation (AF) and aortic stenosis (AS) are both highly prevalent and often coexist. Various studies have focused on the prognostic value of AF in patients with AS, but rarely considered left ventricular (LV) diastolic function as a prognostic factor.

Objective
To evaluate the prognostic impact of AF in patients with AS while correcting for LV diastolic function.

Methods
Patients with first diagnosis of significant AS were selected and stratified according to history of AF. The endpoint was all-cause mortality.

Results
In total, 2849 patients with significant AS (mean age 72 ± 12 years, 54.8% men) were evaluated, and 686 (24.1%) had a history of AF. During a median follow-up of 60 (30–97) months, 1182 (41.5%) patients died. Ten-year mortality rate in patients with AF was 46.8% compared to 36.8% in patients with sinus rhythm (SR) (log-rank P &lt; 0.001). On univariable (HR: 1.42; 95% CI: 1.25–1.62; P &lt; 0.001) and multivariable Cox regression analysis (HR: 1.19; 95% CI: 1.02–1.38; P = 0.026), AF was independently associated with mortality. However, when correcting for indexed left atrial volume, E/e’ or both, AF was no longer independently associated with all-cause mortality.

Conclusion
Patients with significant AS and AF have a reduced survival as compared to patients with SR. Nonetheless, when correcting for markers of LV diastolic function, AF was not independently associated with outcomes in patients with significant AS.
Other markers of medullary thyroid cancer, not only calcitonin
Authors: Censi Simona , Manso Jacopo , Mian Caterina 
Published: January 2023

Abstract

Background
Medullary thyroid cancer (MTC) is a rare neuroendocrine tumor originating from parafollicular C-cells. It represents 2% of all thyroid malignancies and 0.4-1.4% of all thyroid nodules. MTC has a variable clinical course, with complete remission often difficult to achieve. An early diagnosis is still crucial in MTC management, enabling a radical surgical treatment, the only chance for curing the patient. Calcitonin (Ct) is a very sensitive MTC tumor marker in patients with thyroid nodules, although Ct-negative MTCs have been described, but not all clinical guidelines recommend the Ct routine measurement in thyroid nodules because of the absolute low prevalence of MTC in the general population and the consequent scarce positive predictive value of Ct. Moreover, the specificity of moderately high Ct levels is not high. Thus, the scientific community has been investigating the possible role of other tumor markers for MTC diagnosis and prognosis.

Aim of the review
The present review is an attempt to summarize the knowledge available today on the role of other serum markers for MTC alternative to Ct.

Conclusions
At present, literature data does not seem solid enough yet to establish effective flowcharts in evaluating a thyroid nodule for MTC, involving alternative serum markers, particularly in cases of moderately high CT levels. MTC is a rare diagnosis in thyroid nodules, and this makes the evaluation of any tumor serum marker accuracy problematic. More extensive and prospective studies are needed to shed more light on this intriguing challenge.
Hygiene may attenuate selection for antibiotic resistance by changing microbial community structure
Authors: Aspenberg Magnus , Maad Sasane Sara , Nilsson Fredrik , Brown Sam P , Wollein Waldetoft Kristofer 
Published: January 2023

Abstract
Good hygiene, in both health care and the community, is central to containing the rise of antibiotic resistance, as well as to infection control more generally. But despite the well-known importance, the ecological mechanisms by which hygiene (or other transmission control measures) affect the evolution of resistance remain to be elucidated. Using metacommunity ecology theory, we here propose that hygiene attenuates the effect of antibiotic selection pressure. Specifically, we predict that hygiene limits the scope for antibiotics to induce competitive release of resistant bacteria within treated hosts, and that this is due to an effect of hygiene on the distribution of resistant and sensitive strains in the host population. We show this in a mathematical model of bacterial metacommunity dynamics, and test the results against data on antibiotic resistance, antibiotic treatment, and the use of alcohol-based hand rub in long-term care facilities. The data are consistent with hand rub use attenuating the resistance promoting effect of antibiotic treatment. Our results underscore the importance of hygiene, and point to a concrete way to weaken the link between antibiotic use and increasing resistance.
Combining European and U.S. risk prediction models with polygenic risk scores to refine cardiovascular prevention: the CoLaus|PsyCoLaus Study
Authors: de La Harpe Roxane , Thorball Christian W , Redin Claire , Fournier Stephane , Müller Olivier , Strambo Davide , Michel Patrik , Vollenweider Peter , Marques-Vidal Pedro , Fellay Jacques , Vaucher Julien 
Published: January 2023

Abstract

Aims
A polygenic risk score (PRS) has the potential to improve individual atherosclerotic cardiovascular disease (ASCVD) risk assessment. To determine whether a PRS combined with two clinical risk scores, the Systematic COronary Risk Evaluation 2 (SCORE2) and the Pooled Cohort Equation (PCE) improves the prediction of ASCVD.

Methods and results
Using a population-based European prospective cohort, with 6733 participants at the baseline (2003–2006), the PRS presenting the best predictive accuracy was combined with SCORE2 and PCE to assess their joint performances for predicting ASCVD Discrimination, calibration, Cox proportional hazard regression, and net reclassification index were assessed. : 4218 subjects (53% women; median age, 53.4 years), with 363 prevalent and incident ASCVD, were used to compare four PRSs. The metaGRS_CAD PRS presented the best predictive capacity (AUROC = 0.77) and was used in the following analyses. 3383 subjects (median follow-up of 14.4 years), with 190 first-incident ASCVD, were employed to test ASCVD risk prediction. The changes in C statistic between SCORE2 and PCE models and those combining metaGRS_CAD with SCORE2 and PCE were 0.008 (95% CI, −0.00008–0.02, P = 0.05) and 0.007 (95% CI, 0.005–0.01, P = 0.03), respectively. Reclassification was improved for people at clinically determined intermediate-risk for both clinical scores [NRI of 9.6% (95% CI, 0.3–18.8) and 12.0% (95% CI, 1.5–22.6) for SCORE2 and PCE, respectively].

Conclusion
Combining a PRS with clinical risk scores significantly improved the reclassification of risk for incident ASCVD for subjects in the clinically determined intermediate-risk category. Introducing PRSs in clinical practice may refine cardiovascular prevention for subgroups of patients in whom prevention strategies are uncertain.
Domains of Sedentary Behavior and Cognitive Function: The Health, Aging, and Body Composition Study, 1999/2000 to 2006/2007
Authors: Major Laura , Simonsick Eleanor M , Napolitano Melissa A , DiPietro Loretta 
Published: January 2023

Abstract

Background
This study examines the relationship between various domains of sedentary behavior and subsequent cognitive function to evaluate whether different sedentary activities have specific associations with future cognitive performance.

Methods
Data were from 1 261 older adults participating in the Health, Aging, and Body Composition (Health ABC) Study between 1999/2000 and 2006/2007. Total sitting time (hours/day), reading time (hours/week), and TV time (≤27/≥28 h/wk) were self-reported at baseline and 3 years later. At follow-up, cognitive function was evaluated using the Teng Mini-Mental State Examination (3MS) and the Digit Symbol Substitution Test (DSST). Multivariable linear regression modeling examined the independent associations of baseline sedentary behaviors and 3-year change in those behaviors with cognitive function scores at follow-up, adjusting for important covariables.

Results
Baseline total sitting time was positively associated with 3MS (β = 0.14 ± 0.07; p &lt; .05) and DSST (β = 0.20 ± 0.10; p &lt; .05) scores at follow-up, as was reading time (β = 0.09 ± 0.03; p &lt; .05 for 3MS score and β = 0.14 ± 0.04; p &lt; 0.01 for DSST score). Participants who increased their TV watching time over 3 years had a significantly lower 3MS score (β = −1.45 ± 0.71; p &lt; .05) at follow-up, compared with those who maintained a low level of TV time (referent). These findings were independent of age, sex, race, education level, health status, depressive symptoms, and physical activity.

Conclusion
Some types of sedentary behavior may have benefits for cognitive function in older age, thus highlighting the importance of measuring different domains of sitting time.
Open and reusable annotated mass spectrometry dataset of a chemodiverse collection of 1,600 plant extracts
Authors: Allard Pierre-Marie , Gaudry Arnaud , Quirós-Guerrero Luis-Manuel , Rutz Adriano , Dounoue-Kubo Miwa , Walker Tom W N , Defossez Emmanuel , Long Christophe , Grondin Antonio , David Bruno , Wolfender Jean-Luc 
Published: January 2023

Abstract
As privileged structures, natural products often display potent biological activities. However, the discovery of novel bioactive scaffolds is often hampered by the chemical complexity of the biological matrices they are found in. Large natural extract collections are thus extremely valuable for their chemical novelty potential but also complicated to exploit in the frame of drug-discovery projects. In the end, it is the pure chemical substances that are desired for structural determination purposes and bioactivity evaluation. Researchers interested in the exploration of large and chemodiverse extract collections should thus establish strategies aiming to efficiently tackle such chemical complexity and access these structures. Establishing carefully crafted digital layers documenting the spectral and chemical complexity as well as bioactivity results of natural extracts collections can help prioritize time-consuming but mandatory isolation efforts. In this note, we report the results of our initial exploration of a collection of 1,600 plant extracts in the frame of a drug-discovery effort. After describing the taxonomic coverage of this collection, we present the results of its liquid chromatography high-resolution mass spectrometric profiling and the exploitation of these profiles using computational solutions. The resulting annotated mass spectral dataset and associated chemical and taxonomic metadata are made available to the community, and data reuse cases are proposed. We are currently continuing our exploration of this plant extract collection for drug-discovery purposes (notably looking for novel antitrypanosomatids, anti-infective and prometabolic compounds) and ecometabolomics insights. We believe that such a dataset can be exploited and reused by researchers interested in computational natural products exploration.
The temporal value of local scientific expertise
Authors: Feldman Maryann P , Dibiaggio Ludovic , Tran Tan 
Published: January 2023

Abstract
Inventors located in a vibrant scientific community enjoy faster access to relevant publications. The key role of the local scientific community is to provide access to global knowledge and not necessarily to feed the colocated inventors with direct inputs. We develop the logic for these effects and provide empirical tests using dyads of publication and patent data. We develop a model that links scientific knowledge, codified through publication, to industry’s inventive activity. Our analysis includes three key steps. First, we characterize the knowledge profile of local expertise for French NUTS3 jurisdictions. Second, we match scientific publications to industrial patents to consider the specific scientific knowledge useful to industrial invention. Finally, we examine the extent to which the presence of a local related scientific knowledge base provides utility for local inventions. Specifically, we consider the ability of local inventions to more rapidly avail themselves of scientific knowledge when located in a munificent location. We find that location reduces the timing to access to relevant worldwide publications by almost 1 year. Thus, colocation with scientific experts provides inventors a timing advantage by allowing earlier exploitation of recent global scientific discoveries.