bluuebunny/crossref_metadata_2025_split huggingface dataset:
A study on the impacts of antibiotic pollution and its remediation
Authors: Talukder Pratik , Chanda Sounak , Mishra Meghna , Sinha Baishakhi , Dutta Anushka , Adhikary Ayan , Mukherjee Arundhuti , Datta Suravi 
Published: November 2023

AbstractAntibiotics' ability to treat bacterial infections has long been seen as a pillar of modern medicine. Antibiotic abuse and widespread overuse, however, have resulted in unexpected consequences that call for significant adjustments in policy to be mitigated. High levels of antibiotic emissions from manufacturing facilities may help to develop new types of resistant bacteria. Such pollution is acknowledged by many scientists, business leaders, decision‐makers, and other interested parties as an unneeded and intolerable risk to public health worldwide. Antibiotics are frequently produced by soil microorganisms. The bacteria and fungi are microorganisms that produce antibiotics that are helpful in preventing or treating disease. With the invention of Penicillin, antibiotics gained widespread recognition. Since then, they have fundamentally changed how bacterial infections in animals and humans are treated. Since a significant portion of antibiotics are released from human and animal bodies without being degraded, this means that various environmental components, including soils and river water, are contaminated with antibiotics. In this case, it is anticipated that the structure and productivity of the microbiota inhabiting such environments may be impacted by the varied concentration of this type of microbial inhibitor present in different ecosystems. This effect can take place at various levels, including modifications to the population's overall structure, the selection of resistant species, or changes to bacterial physiology.
Setting the Course for Net Zero
Authors: Beckmann Markus , Zöttl Gregor , Grimm Veronika , Becker Thomas , Schober Markus , Zipse Oliver 
Published: November 2023

AbstractThe Road to Net Zero starts from the Paris Agreement, which sets a global goal to limit global warming to well below 2 °C above pre-industrial levels, and an ambition to limit warming to 1.5 °C. The Agreement represents a turning point in the approach to tackling climate change, moving from a mitigation logic focused on reducing carbon emissions to an exit logic focused on full decarbonisation. The challenge is to translate the ambitious goals of the Paris Agreement into practical and achievable action plans that can be implemented at national and local levels. This will require a coordinated and joint effort by governments, businesses, and civil society to mobilise resources, build capacity, and put in place the necessary policies and regulations to support the transition to a low-carbon future. After discussing basic climate science foundations in Sect. 2.2 and the global climate policy ‘Road to Paris’, as well as the implications of the Paris Agreement in Sect. 2.3, national policy frameworks and governance mechanisms that can be implemented at the national level to meet the Nationally Determined Contributions (NDCs) are reviewed in Sect. 2.4. While the expert discussion between Prof. Grimm, Dr Becker, and Oliver Zipse in Sect. 2.5 is dedicated to the balancing act between technology openness and energy policy control mechanisms, Sect. 2.6 gives an outlook on how the goals of the Paris Agreement can be broken down to the company level. In this context, future research questions for the evaluation of legitimised measurement and target-setting frameworks for the private sector are discussed.
Transforming Value Chains for Sustainability
Authors: Voigt Kai-Ingo , Czaja Lothar , Zipse Oliver 
Published: November 2023

AbstractAchieving the Paris goal of limiting global warming to well below 2 °C requires radical decarbonization of our economy, including a shift to renewable energy. In the automotive sector, electromobility offers a promising option for making this transition. However, while electric vehicles (EVs) have lower emissions during their use phase, a significant part of the carbon footprint is shifted upstream in the value chain to raw material extraction and battery production. Against this background, this chapter provides an in-depth look at how the automotive industry’s transition to electromobility leads to far-reaching implications for the EV battery value chain. The chapter begins with a brief review of resource scarcity as a relevant strategic background for the circular economy. It continues with the different steps of the linear EV battery value chain. The chapter then uses a circularity perspective to discuss the technology and value chain steps for closing the loop in the EV battery life cycle. It concludes with an outlook on the challenges of circular EV battery value chains.
Intervertebral Disk Degeneration and Bone Mineral Density: A Bidirectional Mendelian Randomization Study
Authors: Zhao Jie , Wang Jingyu , Xu Haixu , Hu Wei , Shi Fangyuan , Fan Zhengrui , Zhou Chunlei , Mu Hong 
Published: November 2023

AbstractThis study aimed to investigate the causal relationship between bone mineral density (BMD) and intervertebral disk degeneration (IVDD) using a two-sample bidirectional Mendelian randomization analysis. Summary-level data from the Genome-Wide Association Study (GWAS) were used. Instrumental variables (IVs) for IVDD were selected from the large-scale Genome-Wide Association Study (GWAS) (20,001 cases and 164,682 controls). Bone mineral density (BMD) at five different sites (heel (n = 426,824), total body (TB) (n = 56,284), forearm (FA) (n = 8143), femoral neck (FN) (n = 32,735), and lumbar spine (LS) (n = 28,498)) was used as a phenotype for OP. Bidirectional causality between IVDD and BMD was assessed using inverse variance weighting (IVW) and other methods. Related sensitivity analyses were performed. Myopia was also analyzed as a negative control result to ensure the validity of IVs. Heel bone mineral density (heel BMD), total body bone mineral density (TB-BMD), femoral neck bone mineral density (FN-BMD), and lumbar spine bone mineral density (LS-BMD) have a direct causal relationship on intervertebral disk degeneration (IVDD) [heel BMD-related analysis: beta = 0.06, p = 0.03; TB-BMD-related analysis: beta = 0.18, p = 8.72E-08; FN-BMD-related analysis: beta = 0.15, p = 4.89E-03; LS-BMD-related analysis: beta = 0.16, p = 1.43E-04]. There was no evidence of a significant causal effect of IVDD on BMD. In conclusion, our study found a significant positive causal effect of lower BMD on IVDD, and we identified significant causal effects of heel, TB-, FN-, and LS-BMD on IVDD, but there was no evidence of a significant causal effect of IVDD on BMD.
Fungal Diseases Caused by Serious Contamination of Pharmaceuticals and Medical Devices, and Rapid Fungal Detection Using Nano-Diagnostic Tools: A Critical Review
Authors: Ahmed Mohamed Abd El-Gawad El-Sayed , Abbas Heba S. , Kotakonda Muddukrishnaiah 
Published: November 2023

AbstractFungal-contaminated compounded pharmaceuticals and medical devices pose a public health problem. This review aimed to provide an organized overview of the literature on that critical issue. Firstly, it was found that compounding pharmacies can produce drugs that are contaminated with fungi, leading to outbreaks of severe fungal diseases. Secondly, inadequate sterile compounding techniques or storage conditions, or exceeding the limit of a fungal count, can result in fungal contamination. Lastly, nanotools can be used to rapidly detect fungi, thus improving fungal diagnostic procedures. To achieve this goal, we have reviewed the published data on PubMed, the CDC, and FDA Web sites, and a literature search was undertaken to identify severe fungal infections associated with compounding pharmacies outside of hospitals, limited by the dates 2003 to 2021. The “Preferred Reporting Items for Critical Reviews” were followed in searching, including, and excluding papers. Fungal outbreaks have been documented due to contaminated pharmaceuticals and medical devices. In 2013, 55 people died from fungal meningitis caused by contaminated steroid injections containing methylprednisolone acetate. Additionally, in 2021, Aspergillus penicillioides contamination was reported in ChloraPrep drugs, which was attributed to the storage conditions that were conducive to the growth of this fungus. These incidents have resulted in severe infectious diseases, such as invasive mycoses, cornea infections, Endophthalmitis, and intestinal and gastric mycosis. By implementing preventive measures and policies, it is possible to avoid these outbreaks. Creating Nano-diagnostics presents a major challenge, where promptly diagnosing fungal infections is required to determine the proper corrective and preventive measures.
SMP-DL: a novel stock market prediction approach based on deep learning for effective trend forecasting
Authors: Shaban Warda M. , Ashraf Eman , Slama Ahmed Elsaid 
Published: November 2023

AbstractAs the economy has grown rapidly in recent years, more and more people have begun putting their money into the stock market. Thus, predicting trends in the stock market is regarded as a crucial endeavor, and one that has proven to be more fruitful than others. Profitable investments will result in rising stock prices. Investors face significant difficulties making stock market-related predictions due to the lack of movement and noise in the data. In this paper, a new system for predicting stock market prices is introduced, namely stock market prediction based on deep leaning (SMP-DL). SMP-DL splits into two stages, which are (i) data preprocessing (DP) and (ii) stock price’s prediction (SP2). In the first stage, data are preprocessed to obtain cleaned ones through several stages which are detect and reject missing value, feature selection, and data normalization. Then, in the second stage (e.g., SP2), the cleaned data will pass through the used predicted model. In SP2, long short-term memory (LSTM) combined with bidirectional gated recurrent unit (BiGRU) to predict the closing price of stock market. The obtained results showed that the proposed system perform well when compared to other existing methods. As RMSE, MSE, MAE, andR2values are 0.2883, 0.0831, 0.2099, and 0.9948. Moreover, the proposed method was applied using different datasets and it performs well.
A càdlàg rough path foundation for robust finance
Authors: Allan Andrew L. , Liu Chong , Prömel David J. 
Published: November 2023

AbstractUsing rough path theory, we provide a pathwise foundation for stochastic Itô integration which covers most commonly applied trading strategies and mathematical models of financial markets, including those under Knightian uncertainty. To this end, we introduce the so-called property (RIE) for càdlàg paths, which is shown to imply the existence of a càdlàg rough path and of quadratic variation in the sense of Föllmer. We prove that the corresponding rough integrals exist as limits of left-point Riemann sums along a suitable sequence of partitions. This allows one to treat integrands of non-gradient type and gives access to the powerful stability estimates of rough path theory. Additionally, we verify that (path-dependent) functionally generated trading strategies and Cover’s universal portfolio are admissible integrands, and that property (RIE) is satisfied by both (Young) semimartingales and typical price paths.
Rapid discrimination of Panax ginseng powder adulterated with various root plants by FT-IR spectroscopy coupled with multivariate analysis
Authors: Choi Ji-Young , Kim Minhyun , Park Sanghyeok , Cho Jeong-Seok , Lim Jeong Ho , Moon Kwang-Deog 
Published: November 2023

AbstractPanax ginseng powder adulterated with other root plants (arrowroot, bellflower, and lance asiabell) was discriminated using Fourier transform infrared (FT-IR) spectroscopy, combined with multivariate analysis. Principal component analysis visually diagnosed the adulteration by showing two distinct clusters based on presence of adulteration. Wavenumber regions (1000 cm−1 and 3300 cm−1) selected from the loading plot associated with the vibration of OH and CH bond in ginsenoside and aromatic compounds. A quantitative model for the content of ginsenosides and specific aromatic compounds as indicators of pure ginseng powder, was developed based on partial least square regression analysis. The performance of the prediction model preprocessed with the Savizky–Golay 1st derivative was improved to R2 of 0.9650, 0.9635, and 0.9591 for Rb1, Rc, and β-Panasinsene, respectively. Therefore, FT-IR technology makes it possible to rapidly authenticate pure ginseng product based on the ginsenoside contents and aroma compound.
Localized in-situ deposition: a new dimension to control in fabricating surface micro/nano structures via ultrafast laser ablation
Authors: Fan Peixun , Jiang Guochen , Hu Xinyu , Wang Lizhong , Zhang Hongjun , Zhong Minlin 
Published: November 2023

AbstractControllable fabrication of surface micro/nano structures is the key to realizing surface functionalization for various applications. As a versatile approach, ultrafast laser ablation has been widely studied for surface micro/nano structuring. Increasing research efforts in this field have been devoted to gaining more control over the fabrication processes to meet the increasing need for creation of complex structures. In this paper, we focus on the in-situ deposition process following the plasma formation under ultrafast laser ablation. From an overview perspective, we firstly summarize the different roles that plasma plumes, from pulsed laser ablation of solids, play in different laser processing approaches. Then, the distinctive in-situ deposition process within surface micro/nano structuring is highlighted. Our experimental work demonstrated that the in-situ deposition during ultrafast laser surface structuring can be controlled as a localized micro-additive process to pile up secondary ordered structures, through which a unique kind of hierarchical structure with fort-like bodies sitting on top of micro cone arrays were fabricated as a showcase. The revealed laser-matter interaction mechanism can be inspiring for the development of new ultrafast laser fabrication approaches, adding a new dimension and more flexibility in controlling the fabrication of functional surface micro/nano structures.
Graphical Abstract
Causal structure of spacetime and Scott topology
Authors: Mazibuko Langelihle , Baboolal Dharmanand , Goswami Rituparno 
Published: November 2023

AbstractIn this paper we establish the spacetime manifold as a partially ordered set via the casual structure. We show that these partially ordered sets are naturally continuous as a suitable way below relation can be established via the chronological order. We further consider those classes of spacetimes on which a lattice structure can be endowed by physically defining the joins and meets. By considering the physical properties of null geodesics on the spacetime manifold we show that these lattices are necessarily distributive. These lattices are then continuous as a result of the equivalence between the way below relation and chronology. This enables us to define the Scott topology on the spacetime manifold and describe it on an equal footing as any other continuous lattice. We further show that the Scott topology is a proper subset of Alexandroff topology, which must be the manifold topology for the strongly causal spacetimes, (and hence a coarser topology than Alexandroff). In the process we find some interesting results on the sobriety of these manifolds. We prove that they are necessarily not sober under the Scott topology but regain their sobriety under Alexandroff topology. We also define a dual Scott topology on these manifolds by endowing them with bicontinuous poset structure and show that the join of the Scott topology with the dual is the Alexandroff topology. We also discuss the previous works done in this topic and how the present work generalises those results to some extent.
Neurologic Manifestations of Tick-Borne Diseases Transmitted by Deer Ticks (Ixodes scapularis) in the USA
Authors: Lum Michael , Syritsyna Olga , Spitzer Eric D. , Marcos Luis A. 
Published: November 2023

Abstract
Purpose of Review
This article aims to review the relevant updates in pathogenesis, diagnostics, clinical manifestations, and treatments of tick-borne diseases involving the nervous system, with special emphasis on emerging viral and bacterial infections transmitted by deer ticks (Ixodes scapularis).

Recent Findings
Neuroborreliosis includes a wide array of peripheral and/or central nervous system syndromes, of which diagnosis depends on a combination of clinical gestalt, serum serologic testing, and CSF cellular and serologic analysis. Powassan virus may cause life-threatening neuroinvasive disease and diagnosis that is based on CSF serology with treatment being largely supportive. Neurologic manifestations of anaplasmosis and babesiosis are rare but have been documented in case reports. Diagnosis is dependent on serum molecular and microscopic and serologic testing, and the pathophysiologic mechanisms of these neurologic syndromes are not fully understood. Borrelia miyamotoi is an emerging pathogen and, in immunocompromised patients, can cause severe meningoencephalitis.

Summary
Ixodes scapularis-borne infections such as Lyme disease, anaplasmosis, babesiosis, Powassan virus, and Borrelia miyamotoi disease can have significant neurologic manifestations. Due to the potential for poor outcomes, physicians must have a working knowledge of these pathogens, and a high index of suspicion is required to screen for these diseases in patients with the correct risk factors. Future research will help realize the full range of neurologic manifestations of these pathogens and also clarify their underlying pathophysiologic mechanisms, which will aid in developing new methods of diagnosis and treatment.
Nitrogen-Doped Magnetic-Dielectric-Carbon Aerogel for High-Efficiency Electromagnetic Wave Absorption
Authors: Wang Shijie , Zhang Xue , Hao Shuyan , Qiao Jing , Wang Zhou , Wu Lili , Liu Jiurong , Wang Fenglong 
Published: November 2023

AbstractCarbon-based aerogels derived from biomass chitosan are encountering a flourishing moment in electromagnetic protection on account of lightweight, controllable fabrication and versatility. Nevertheless, developing a facile construction method of component design with carbon-based aerogels for high-efficiency electromagnetic wave absorption (EWA) materials with a broad effective absorption bandwidth (EAB) and strong absorption yet hits some snags. Herein, the nitrogen-doped magnetic-dielectric-carbon aerogel was obtained via ice template method followed by carbonization treatment, homogeneous and abundant nickel (Ni) and manganese oxide (MnO) particles in situ grew on the carbon aerogels. Thanks to the optimization of impedance matching of dielectric/magnetic components to carbon aerogels, the nitrogen-doped magnetic-dielectric-carbon aerogel (Ni/MnO-CA) suggests a praiseworthy EWA performance, with an ultra-wide EAB of 7.36 GHz and a minimum reflection loss (RLmin) of − 64.09 dB, while achieving a specific reflection loss of − 253.32 dB mm−1. Furthermore, the aerogel reveals excellent radar stealth, infrared stealth, and thermal management capabilities. Hence, the high-performance, easy fabricated and multifunctional nickel/manganese oxide/carbon aerogels have broad application aspects for electromagnetic protection, electronic devices and aerospace.
Analysis of the EFARC non-pillar mining stope: roof failure and overlying pressure in inclined coal seams
Authors: Zhen Enze , Dong Shizhuo , Huang Jian , Wang Yajun , Wang Mengxiang , Zhang Xinyue , Tao Yizhe 
Published: November 2023

AbstractDuring the process of coal mining, there is a violent appearance of mining stress when the initial weighting occurs. To guarantee the safety of the gob-side entry formed automatically by roof-cutting (EFARC) in an inclined coal seam, a study was conducted on the initial weighting mechanism and appearance characteristics through field monitoring and theoretical analysis. The findings reveal that, upon the initial breaking of the main roof in the non-pillar mining stope of an inclined coal seam, the deflection of the thin plate structure exhibits asymmetric distribution, with the maximum position situated in the middle-upper part of the thin plate. As the main roof thin plate reaches its limit interval, the tensile fracture first occurs in the middle-upper part of the coal wall in front and back of the stope. Once broken, the thin plate changes to a simply supported state. The analysis of field data reveals that the mine pressure in the non-pillar stope of EFARC shows an asymmetric weighting phenomenon. The periodic weighting interval at the ends of the working face increases, and the weighting intensity decreases. These results can serve as theoretical support for controlling mine pressure in non-pillar mining through EFARC in inclined coal seams and can serve as a basis for further investigations in this area.
GNN for Deep Full Event Interpretation and Hierarchical Reconstruction of Heavy-Hadron Decays in Proton–Proton Collisions
Authors: García Pardiñas Julián , Calvi Marta , Eschle Jonas , Mauri Andrea , Meloni Simone , Mozzanica Martina , Serra Nicola 
Published: November 2023

AbstractThe LHCb experiment at the Large Hadron Collider (LHC) is designed to perform high-precision measurements of heavy-hadron decays, which requires the collection of large data samples and a good understanding and suppression of multiple background sources. Both factors are challenged by a fivefold increase in the average number of proton–proton collisions per bunch crossing, corresponding to a change in the detector operation conditions for the LHCb Upgrade I phase, recently started. A further tenfold increase is expected in the Upgrade II phase, planned for the next decade. The limits in the storage capacity of the trigger will bring an inverse relationship between the number of particles selected to be stored per event and the number of events that can be recorded. In addition the background levels will rise due to the enlarged combinatorics. To tackle both challenges, we propose a novel approach, never attempted before in a hadronic collider: a Deep-learning based Full Event Interpretation (DFEI), to perform the simultaneous identification, isolation and hierarchical reconstruction of all the heavy-hadron decay chains per event. This strategy radically contrasts with the standard selection procedure used in LHCb to identify heavy-hadron decays, that looks individually at subsets of particles compatible with being products of specific decay types, disregarding the contextual information from the rest of the event. Following the DFEI approach, once the relevant particles in each event are identified, the rest can be safely removed to optimise the storage space and maximise the trigger efficiency. We present the first prototype for the DFEI algorithm, that leverages the power of Graph Neural Networks (GNN). This paper describes the design and development of the algorithm, and its performance in Upgrade I simulated conditions.