bluuebunny/crossref_metadata_2025_split huggingface dataset:
Signatures of 1.5 MeV leptons in nuclear reactions
Authors: Kovacs Andras , Zatelepin Valery , Baranov Dmitry 
Published: May 2023

Abstract
While experimental physics progressed tremendously since the 1970s, the neutron model has remained essentially unchanged. Motivated by developments in both experiments and theory, which we briefly review in section 1, we propose that the initial neutron decay step is not the emission of an 80 GeV mass boson particle, but the emission of a much lighter lepton particle. On the basis of well-known neutron data, in section 2 we estimate that this new lepton’s mass is 1.5 MeV.
Historically, investigations of deuteron photo-dissociation led nuclear scientists to assume that no electron-like particle is associated with neutron decay. We therefore re-examine these experiments in section 3. We demonstrate that deuteron photo-dissociation leads to 2p
+ + e
− products at high photon energies. Our calculations show why a deuteron always breaks up into p + n particles at <3 MeV photon energy.
Sections 4 - 7 discuss the properties and interactions of the 1.5 MeV lepton particle. Numerous investigations, including our own experiments, demonstrate the presence of negative elementary charges within atomic nuclei. The emission or absorption of negative nuclear charges involves the emission or absorption of a new lepton particle, which always decays into an electron. Various mass measurement methods converge to the same result: the emitted or absorbed lepton is approximately three times heavier than an ordinary electron. Specifically, we measure its mass to be 1553.5 keV.
Our work demonstrates that, despite being a single particle, the neutron comprises a positive and a negative elementary charge. To make sense of the neutron structure, it is necessary to firstly understand the proton’s and the newly discovered 1.5 MeV lepton’s internal structures. In section 9, we apply our results to better understand the neutron’s properties.
Towards testing a dark matter candidate that emerges from the scalar ether theory
Authors: Arminjon Mayeul 
Published: May 2023

Abstract
According to a scalar theory of gravity with a preferred frame, electromagnetism in the presence of a gravitational field implies that there is an additional energy tensor, which might contribute to dark matter. The expression of this tensor is determined by a mere scalar p, that depends on the EM field and (for a weak field) on the Newtonian gravitational field. We briefly recall why this tensor arises and how the EM field in a galaxy can be calculated. The data fields that enter the PDE for the scalar field p oscillate very quickly in space and time, as does the EM field. This prevents integration of that PDE at the relevant galactic scale. Therefore, a homogenization of that PDE has to be operated. We discuss in some detail three possible ways of applying the homogenization theory to that PDE: time, space, or spacetime homogenization. The second and third ways may lead to feasible, albeit heavy calculations.
Weyl and Majorana for Neutral Particles
Authors: Dvoeglazov Valeriy V. 
Published: May 2023

Abstract
We compare various formalisms for neutral particles. It is found that they contain unexplained contradictions. Next, we investigate the spin-1/2 and spin-1 cases in different bases. Next, we look for relations with the Majorana-like field operator. We show explicitly incompatibility of the Majorana anzatzen with the Dirac-like field operators in both the original Majorana theory and its generalizations. Several explicit examples are presented for higher spins too. It seems that the calculations in the helicity basis only give mathematically and physically reasonable results.
Group contraction in physics: History and potential
Authors: Knap Jaroslav 
Published: May 2023

Abstract
This article serves as a review of the mathematical tool of group contraction with an emphasis on physical applications. It was implicitly understood that some theories contain others as a special case (e.g., the relation between special relativity and Newtonian mechanics), but until the 1950s there was no firm mathematical grounding for such relations. We discuss the historical development of these concepts, their application to symmetry groups of space and time, and their relevance to the phenomenon of spontaneous symmetry breaking. Finally, we close by proposing a speculative chronology of space-time symmetries in the early universe.
The measurement in classical and quantum theory
Authors: Kryukov Alexey A. 
Published: May 2023

Abstract
The Bohigas-Giannoni-Schmit (BGS) conjecture states that the Hamiltonian of a microscopic analogue of a classical chaotic system can be modeled by a random matrix from a Gaussian ensemble. Here, this conjecture is considered in the context of a recently discovered geometric relationship between classical and quantum mechanics. Motivated by BGS, we conjecture that the Hamiltonian of a system whose classical counterpart performs a random walk can be modeled by a family of independent random matrices from the Gaussian unitary ensemble. By accepting this conjecture, we find a relationship between the process of observation in classical and quantum physics, derive irreversibility of observation and describe the boundary between the micro and macro worlds.
New technique of ion identification in Accelerator Mass Spectrometry using low-pressure TPC with GEM readout
Authors: Bondar A. , Buzulutskov A. , Parkhomchuk V. , Petrozhitsky A. , Shakirova T. , Sokolov A. 
Published: May 2023

Abstract
We have developed and successfully tested a low-pressure Time Projection Chamber (TPC) with Gas Electron Multiplier (GEM) readout for Accelerator Mass Spectrometry (AMS).

AMS facility in Novosibirsk has a problem of separating isobar ions of different chemical elements that have the same atomic mass. The typical example is radioactive isotopes 10Be and 10B that are used to date geological objects at a time scale of ten million years. To solve this problem, a new ion identification technique, namely that based on measuring both ion track ranges and ion energies in low-pressure TPCs with GEM readout, has been developed. This technique is proposed to be applied in AMS for dating geological objects, namely for geochronology of Cenozoic era.

In this work, we developed a new larger version of the TPC with a dedicated thin silicon nitride window for an efficient passage of ions. The TPC characteristics were studied in isobutane at low pressures using alpha particle sources. In addition, the use of GEM instead of THGEM has been shown to substantially improve the energy resolution at a nominal pressure (50 torr). Using these results and SRIM code simulations, it is shown that isobaric boron and beryllium ions can be effectively separated at AMS, providing efficient dating on a scale of ten million years. This technique will be applied in the AMS facility in Novosibirsk in the near future.
High efficiency, low cost, RF sources for accelerators and colliders
Authors: Ives R.L. , Read M. , Bui T. , Marsden D. , Collins G. , Freund H. , Ho R. , Higgins L. , Walker C. , Conant J. , Chase B. , Reid J. , Kroc T. , Yakovlev V. , Thangaraj J.C.T. , Dhuley R.C. , Potter J. , Jensen A. , Weatherford B. , Nanni E.A. , Tantawi S. 
Published: May 2023

Abstract
Accelerators for High Energy Physics (HEP) are large users
of energy, much of it in the form of radiofrequency (RF) power to
accelerate particles to very high energies. Proposed HEP projects
will require even larger amounts of RF energy. Increasing concerns
of the cost and availability of energy will require the HEP
community to use energy as efficeintly as possible. Successful
transfer of HEP technology to the public and private sectors will be
most effective if it is highly efficient.

Historically, the HEP community has utilized available RF power
sources, mainly in the form of vacuum tube technology, much of which
was developed during the cold war or is otherwized used in the
private sector. The private sector is moving to solid-state RF
sources which do not exibit the electrical efficiency that is needed
for future HEP projects.

Here, we summarize the state of the development of a number of RF
sources that promise efficeincies of 80% and above. We also outline
future efforts that are needed to fully realize the potential of
these sources.
Gauge theory for mixed p-spin glasses
Authors: Itoi C , Sakamoto Y 
Published: May 2023

Abstract
Physical quantities in the mixed p-spin glasses are evaluated with Nishimori’s gauge theory and several variance inequalities. The

Z

2

-symmetry breaking and the replica-symmetry breaking (RSB) are studied in finite and infinite dimensions. Obtained bounds on the expectation of the square of the magnetization and spontaneous magnetization enable us to clarify properties of paramagnetic and spin glass phases. It is proven that variances of ferromagnetic and spin glass order parameters vanish on the Nishimori line in the infinite volume limit. These results imply the self-averaging of these order parameters on the Nishimori line. The self-averaging of the spin glass order parameter rigorously justifies already argued absence of RSB on the Nishimori line.
Oxygen requirement analysis in the wastewater treatment plant using machine learning
Authors: Măcinic M E , Robescu L D , Boncescu C , Robescu D 
Published: May 2023

Abstract
The research presented in this article refers to the optimization of oxygen requirement in biological wastewater treatment using machine learning (ML) techniques with the highest efficiency of the process. The treatment technology of wastewater treatment plant consists of sequential biological reactor with nutrient removal. The analysis is based on the daily data over a period of 2 years, influent, respectively effluent wastewater characteristics, wastewater flow rate and concentration of oxygen in biological reactor. Octave software was used to build the model and it was obtained an accuracy of 85%.
Thermal bridge assessment at industrial buildings
Authors: Iancu I E , Moga L M 
Published: May 2023

Abstract
It is well known that the thermal performance of a building is influenced by the solutions that define the building’s envelope. In the case of industrial buildings, due to the use of different envelope solutions (e.g. sandwich panels, prefabricated concrete panels etc.), the types of thermal bridge details are often different in comparison to those currently found in residential, office and administrative buildings. Thus, several numerical simulations were performed by analysing details of envelope elements identified at industrial buildings, especially the areas prone to intensified heat flow (joint areas, intersections, glazed surfaces, and others.). Therefore, the paper will present the assessment of thermal bridge details for four industrial buildings having various destinations. The effects of two-dimensional heat transfer in envelope elements, such as windows, walls, foundations, roofs and doors, will be evaluated. The impact of the thermal bridges will be measured by verifying to what extent the level of thermal performance of each envelope component meets the thermal resistance requirements, as well as the building envelope ensures the global heat transfer coefficient for each of the studied cases. A series of conclusions and recommendations will be provided for specialists and designers in the building energetics field.
Antibacterial activity of green synthesized ZnO nano-flower using pineapple peel extract
Authors: Rini A S , Linda T M , Hamzah Y , Umar L , Sari M , Rati Y 
Published: May 2023

Abstract
Plant-based nanoparticles provide significant advantages over conventional physico-chemical techniques in medicine and biology. This paper reports the green route to synthesise ZnO particles using pineapple peel extract at various zinc precursor concentrations and evaluate their antibacterial activity. Morphological, structural, and optical properties of ZnO were characterised using SEM, XRD, FTIR, and UV–vis. The antibacterial potential of ZnO particles was evaluated against two clinical strains of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) using the paper disc diffusion method. SEM images exhibit flower-like ZnO with diameters in the range of 331–538 nm. The hexagonal wurtzite crystal phase of ZnO has been confirmed by XRD analysis with a crystal size of 14–17 nm. The FTIR spectrum has also validated the Zn-O bonding and the presence of additional functional groups in the samples. Antibacterial activity of the nanoflower ZnO towards E. coli and S. aureus displays inhibitory zone widths of 17.23 ± 3.03 mm and 30.14 ± 1.86 mm, respectively. These findings reveal that nanoflower ZnO produced using the pineapple peel extract exhibited a large bacterial inhibition zone, indicating that it is potentially used as food packaging or antibiotics.
Investigation of parameters and morphology of coated WC tool while machining X-750 using NSGA-II
Authors: Bohat Manjeet , Sharma Neeraj 
Published: May 2023

Abstract
Nickel-based superalloys have numerous applications in automobile, aerospace, turbine blades, nuclear, oil refinery etc, due to their excellent properties like strength, wear resistance, corrosion resistance and higher creep strength. Because of these properties, modern manufacturing industries need help with the machining of nickel-based superalloys, i.e. hard-to-machine materials. In the present research, Ni-based X-750 alloy is machined with turning operation by a conventional lathe machine using a TiAlN PVD coated tungsten carbide tool at different rotational speed (TRS), depth of cut (DoC) and feed (F) values as input parameters whereas material removal rate (MRR) and tool wear (TW) are the responses of the study. The design of experiments (DoE) is prepared by response surface methodology-based Box-Behnken Design. Analysis of variance (ANOVA) was applied to investigate the percentage contribution of each machining parameter on responses. Non-dominated Sorting Genetic Algorithm-II (NSGA-II) simultaneously optimizes the developed empirical models of MRR and TW. The predicted solutions suggested by NSGA-II are the best solution, and confirmation experiments are conducted on randomly selected parametric settings from these solutions. The optimized set presented by NSGA-II is TRS: 900RPM; DoC: 0.06 mm; F: 0.1 mm rev−1, and the maximum relative error in the case of MRR and TW is in the permissible limit. Scanning electron microscopy (SEM) and Energy dispersive spectroscopy (EDS) are used to investigate the morphology of tool insert before and after machining at optimized value TRS: 900 RPM; DoC: 0.1 mm; F: 0.06 mm rev−1, and it shows the wear marks on the tool, and the Energy dispersive spectroscopy confirms the presence of coating and WC. SEM is used to investigate the morphology of chips formed at different optimized parametric settings.
Robust trajectory tracking controller for an octocopter UAV
Authors: Dixit Abhishek , Agrawal Pooja , Misra Ajay 
Published: May 2023

Abstract
This work proposes an Input-Output linearization (IOL) trajectory tracking controller for an actuated octocopter unmanned aerial vehicle (UAV). The underactuated octocopter dynamics is converted into actuated one using the differential flat outputs. The proposed controller for actuated octocopter UAV is robustified using α Uncertainty and Disturbance Estimator (αUDE). The Lyapunov theory is used to ascertain closed-loop stability in achieving the desired trajectory. A comparative study is carried out to show the better performance of the proposed controller. Results show the efficacy of the proposed controller in handling the effects of slow as well as fast varying disturbances, parametric uncertainties, and measurement noise. The quantitative analysis based on performance indices and root mean square error validated the results.
Attention-based cross domain graph neural network for prediction of drug–drug interactions
Authors: Yu Hui , Li KangKang , Dong WenMin , Song ShuangHong , Gao Chen , Shi JianYu 
Published: May 2023

Abstract
Drug–drug interactions (DDI) may lead to adverse reactions in human body and accurate prediction of DDI can mitigate the medical risk. Currently, most of computer-aided DDI prediction methods construct models based on drug-associated features or DDI network, ignoring the potential information contained in drug-related biological entities such as targets and genes. Besides, existing DDI network-based models could not make effective predictions for drugs without any known DDI records. To address the above limitations, we propose an attention-based cross domain graph neural network (ACDGNN) for DDI prediction, which considers the drug-related different entities and propagate information through cross domain operation. Different from the existing methods, ACDGNN not only considers rich information contained in drug-related biomedical entities in biological heterogeneous network, but also adopts cross-domain transformation to eliminate heterogeneity between different types of entities. ACDGNN can be used in the prediction of DDIs in both transductive and inductive setting. By conducting experiments on real-world dataset, we compare the performance of ACDGNN with several state-of-the-art methods. The experimental results show that ACDGNN can effectively predict DDIs and outperform the comparison models.
CMGN: a conditional molecular generation net to design target-specific molecules with desired properties
Authors: Yang Minjian , Sun Hanyu , Liu Xue , Xue Xi , Deng Yafeng , Wang Xiaojian 
Published: May 2023

Abstract
The rational design of chemical entities with desired properties for a specific target is a long-standing challenge in drug design. Generative neural networks have emerged as a powerful approach to sample novel molecules with specific properties, termed as inverse drug design. However, generating molecules with biological activity against certain targets and predefined drug properties still remains challenging. Here, we propose a conditional molecular generation net (CMGN), the backbone of which is a bidirectional and autoregressive transformer. CMGN applies large-scale pretraining for molecular understanding and navigates the chemical space for specified targets by fine-tuning with corresponding datasets. Additionally, fragments and properties were trained to recover molecules to learn the structure–properties relationships. Our model crisscrosses the chemical space for specific targets and properties that control fragment-growth processes. Case studies demonstrated the advantages and utility of our model in fragment-to-lead processes and multi-objective lead optimization. The results presented in this paper illustrate that CMGN has the potential to accelerate the drug discovery process.
ODNA: identification of organellar DNA by machine learning
Authors: Martin Roman , Nguyen Minh Kien , Lowack Nick , Heider Dominik 
Published: May 2023

Abstract

Motivation
Identifying organellar DNA, such as mitochondrial or plastid sequences, inside a whole genome assembly, remains challenging and requires biological background knowledge. To address this, we developed ODNA based on genome annotation and machine learning to fulfill.

Results
ODNA is a software that classifies organellar DNA sequences within a genome assembly by machine learning based on a predefined genome annotation workflow. We trained our model with 829 769 DNA sequences from 405 genome assemblies and achieved high predictive performance (e.g. matthew's correlation coefficient of 0.61 for mitochondria and 0.73 for chloroplasts) on independent validation data, thus outperforming existing approaches significantly.

Availability and implementation
Our software ODNA is freely accessible as a web service at https://odna.mathematik.uni-marburg.de and can also be run in a docker container. The source code can be found at https://gitlab.com/mosga/odna and the processed data at Zenodo (DOI: 10.5281/zenodo.7506483).
Epidemiology and association with outcomes of polypharmacy in patients undergoing surgery: retrospective, population-based cohort study
Authors: Jónsdóttir Freyja , Blöndal Anna B , Guðmundsson Aðalsteinn , Bates Ian , Stevenson Jennifer M , Sigurðsson Martin I 
Published: May 2023

Abstract

Background
The aim of this study was to determine the prevalence of preoperative polypharmacy and the incidence of postoperative polypharmacy/hyper-polypharmacy in surgical patients and their association with adverse outcomes.

Methods
This was a retrospective, population-based cohort study among patients older than or equal to 18 years undergoing surgery at a university hospital between 2005 and 2018. Patients were categorized based on the number of medications: non-polypharmacy (fewer than 5); polypharmacy (5–9); and hyper-polypharmacy (greater than or equal to 10). The 30-day mortality, prolonged hospitalization (greater than or equal to 10 days), and incidence of readmission were compared between medication-use categories.

Results
Among 55 997 patients, the prevalence of preoperative polypharmacy was 32.3 per cent (95 per cent c.i. 33.5 to 34.3) and the prevalence of hyper-polypharmacy was 25.5 per cent (95 per cent c.i. 25.2 to 25.9). Thirty-day mortality was higher for patients exposed to preoperative hyper-polypharmacy (2.3 per cent) and preoperative polypharmacy (0.8 per cent) compared with those exposed to non-polypharmacy (0.6 per cent) (P &lt; 0.001). The hazards ratio (HR) of long-term mortality was higher for patients exposed to hyper-polypharmacy (HR 1.32 (95 per cent c.i. 1.25 to 1.40)) and polypharmacy (HR 1.07 (95 per cent c.i. 1.01 to 1.14)) after adjustment for patient and procedural variables. The incidence of longer hospitalization (greater than or equal to 10 days) was higher for hyper-polypharmacy (11.3 per cent) and polypharmacy (6.3 per cent) compared with non-polypharmacy (4.1 per cent) (P &lt; 0.001). The 30-day incidence of readmission was higher for patients exposed to hyper-polypharmacy (10.2 per cent) compared with polypharmacy (6.1 per cent) and non-polypharmacy (4.8 per cent) (P &lt; 0.001). Among patients not exposed to polypharmacy, the incidence of new postoperative polypharmacy/hyper-polypharmacy was 33.4 per cent (95 per cent c.i. 32.8 to 34.1), and, for patients exposed to preoperative polypharmacy, the incidence of postoperative hyper-polypharmacy was 16.3 per cent (95 per cent c.i. 16.0 to 16.7).

Conclusion
Preoperative polypharmacy and new postoperative polypharmacy/hyper-polypharmacy are common and associated with adverse outcomes. This highlights the need for increased emphasis on optimizing medication usage throughout the perioperative interval.

Registration number
NCT04805151 (http://clinicaltrials.gov).
Retracted and Replaced: Altered microstructure of the contralesional ventral premotor cortex and motor output after stroke
Authors: Wróbel Paweł P , Guder Stephanie , Feldheim Jan F , Graterol Pérez José A , Frey Benedikt M , Choe Chi-un , Bönstrup Marlene , Cheng Bastian , Rathi Yogesh , Pasternak Ofer , Thomalla Götz , Gerloff Christian , Shenton Martha E , Schulz Robert 
Published: May 2023

AbstractThis article has been retracted and replaced. Please see https://doi.org/10.1093/braincomms/fcae149 for details. The replacement article can be found at https://doi.org/10.1093/braincomms/fcae115