bluuebunny/crossref_metadata_2025_split huggingface dataset:
An intent recognition pipeline for conversational AI
Authors: Chandrakala C. B. , Bhardwaj Rohit , Pujari Chetana 
Published: December 2023

AbstractNatural Language Processing (NLP) is one of the Artificial Intelligence applications that is entitled to allow computers to process and understand human language. These models are utilized to analyze large volumes of text and also support aspects like text summarization, language translation, context modeling, and sentiment analysis. Natural language, a subset of Natural Language Understanding (NLU), turns natural language into structured data. NLU accomplishes intent classification and entity extraction. The paper focuses on a pipeline to maximize the coverage of a conversational AI (chatbot) by extracting maximum meaningful intents from a data corpus. A conversational AI can best answer queries with respect to the dataset if it is trained on the maximum number of intents that can be gathered from the dataset which is what we focus on getting in this paper. The higher the intent we gather from the dataset, the more of the dataset we cover in training the conversational AI. The pipeline is modularized into three broad categories - Gathering the intents from the corpus, finding misspellings and synonyms of the intents, and finally deciding the order of intents to be picked up for training any classifier ML model. Several heuristic and machine-learning approaches have been considered for optimum results. For finding misspellings and synonyms, they are extracted through text vector neural network-based algorithms. Then the system concludes with a suggestive priority list of intents that should be fed to a classification model. In the end, an example of three intents from the corpus is picked, and their order is suggested for the optimum functioning of the pipeline. This paper attempts to pick intents in descending order of their coverage in the corpus in the most optimal way possible.
The Brazilian Pharmaceutical Industry: Actors, Institutions, and Policies
Authors: Paranhos Julia , Hasenclever Lia , Perin Fernanda S. 
Published: December 2023

AbstractThis paper aims to characterize the main actors in the Brazilian pharmaceutical industry — national companies, foreign companies and public laboratories — and analyze how they were affected and how they reacted to changes over the last 30 years in the institutional framework. The results show that national companies have been gaining prominence in the Brazilian pharmaceutical market with their internationalization movement and their strengthening of innovation strategies.
Pharmaceutical Innovation in Latin America and the Caribbean
Authors: Vargas Verónica , Darrow Jonathan 
Published: December 2023

AbstractThis study assesses Latin America and Caribbean countries’ capacity to innovate new pharmaceuticals, defined as developing new drugs and vaccines, repurposing existing drugs, and inventing around patents to produce new drug variations. Vaccine innovation includes reengineering existing vaccines, developing new manufacturing methods, and the clinical development of unapproved vaccine candidates initiated elsewhere.
Modulation of Equatorial Currents and Tropical Instability Waves During the 2021 Atlantic Niño
Authors: Tuchen Franz Philip , Perez Renellys C. , Foltz Gregory R. , Brandt Peter , Subramaniam Ajit , Lee Sang‐Ki , Lumpkin Rick , Hummels Rebecca 
Published: December 2023

AbstractIn the boreal summer of 2021, the equatorial Atlantic experienced the strongest warm event, that is, Atlantic Niño, since the beginning of satellite observations in the 1970s. Such events have far‐reaching impacts on large‐scale wind patterns and rainfall over the surrounding continents. Yet, developing a paradigm of how Atlantic Niño interacts with the upper‐ocean currents and intraseasonal waves remains elusive. Here we show that the equatorial Kelvin wave associated with the onset of the 2021 Atlantic Niño modulated both the background flow and the eddy flux of the equatorial upper‐ocean circulation, causing an extremely weak and delayed tropical instability wave (TIW) season. TIW‐induced variations of sea surface temperature (SST), sea surface salinity, sea surface height, and eddy temperature advection were exceptionally weak during May to July, the climatological peak of TIW activity, but rebounded in August when higher than normal variability was observed. Moored velocity data at 23°W show that during the peak of the 2021 Atlantic Niño from June to August, the Equatorial Undercurrent was deeper and stronger than usual. An anomalously weak eddy momentum flux strongly suppressed barotropic energy conversion north of the equator from May to July, likely contributing to low TIW activity. Reduced baroclinic energy conversion also might have played a role, as the meridional gradient of SST was sharply reduced during the Atlantic Niño. Despite extremely weak TIW velocities, modest intraseasonal variability of chlorophyll‐a (Chl‐a) was observed during the Atlantic Niño, due to pronounced meridional Chl‐a gradients that partly compensated for the weak TIWs.
Understanding the Effects of Aerosols on Electrification and Lightning Polarity in an Idealized Supercell Thunderstorm via Model Emulation
Authors: Sun Mengyu , Li Zhanqing , Wang Tao , Mansell Edward R. , Qie Xiushu , Shan Siyu , Liu Dongxia , Cribb Maureen 
Published: December 2023

AbstractAerosol effects on the lightning intensity and polarity of a continental supercell storm were investigated using a three‐dimensional lightning scheme within the Weather Research and Forecasting model. We find that both intra‐cloud (IC) and cloud‐to‐ground (CG) flashes are enhanced by the increasing number of cloud condensation nuclei (CCN), especially the percentage of positive CG (+CG) strokes peaking at 42%. Electrical characteristics of the storm varied in different aerosol scenarios through microphysical processes. Added aerosols increase the number of cloud droplets and ice‐phase hydrometeors. The greater ice‐crystal concentration and larger graupel size ensure sufficient charge separation, leading to higher charge density and more lightning discharges. In addition, an inverted polarity charge structure with a strong positive‐charge region in the mid‐levels was formed mainly due to the positively charged graupel in the presence of higher supercooled cloud water content. Positive lightning channels originating from this positive‐charge region propagated to the ground, producing more +CG strokes. When the aerosol concentration was low, the charge density in the upper positive‐charge region was much lower due to smaller ice‐particle content. Consequently, there were barely any +CG strokes. Most of the negative CG flashes deposited positive charge in the lower negative‐charge region.
Upward Lightning at Wind Turbines: Risk Assessment From Larger‐Scale Meteorology
Authors: Stucke Isabell , Morgenstern Deborah , Diendorfer Gerhard , Mayr Georg J. , Pichler Hannes , Schulz Wolfgang , Simon Thorsten , Zeileis Achim 
Published: December 2023

AbstractUpward lightning (UL) has become a major threat to the growing number of wind turbines producing renewable electricity. It can be much more destructive than downward lightning due to the large charge transfer involved in the discharge process. Ground‐truth lightning current measurements indicate that less than 50% of UL could be detected by lightning location systems (LLS). UL is expected to be the dominant lightning type during the cold season. However, current standards for assessing the risk of lightning at wind turbines mainly consider summer lightning, which is derived from LLS. This study assesses the risk of LLS‐detectable and LLS‐undetectable UL at wind turbines using direct UL measurements at instrumented towers. These are linked to meteorological data using random forests. The meteorological drivers for the absence/occurrence of UL are found from these models. In a second step, the results of the tower‐trained models are extended to a larger study area (central and northern Germany). The tower‐trained models for LLS‐detectable lightning are independently verified at wind turbine sites in this area and found to reliably diagnose this type of UL. Risk maps based on cold season case study events show that high probabilities in the study area coincide with actual UL flashes. This lends credibility to the application of the model to all UL types, increasing both risk and affected areas.
Incorporating an Interactive Fire Plume‐Rise Model in the DOE's Energy Exascale Earth System Model Version 1 (E3SMv1) and Examining Aerosol Radiative Effect
Authors: Lu Zheng , Liu Xiaohong , Ke Ziming , Zhang Kai , Ma Po‐Lun , Fan Jiwen 
Published: December 2023

AbstractThe vertical distribution of biomass burning aerosol (BBA) is important in regulating their impacts on weather and climate. The plume‐rise process affects the injection height of BBA and interacts with the air parcel lifting and cloud processes. However, these processes are not represented in most global climate models. In this study, we replaced the fixed vertical profiles of monthly BBA emissions in the Department of Energy's Energy Exascale Earth System Model version 1 (E3SMv1) with an interactive fire plume‐rise model. The vertical distribution of BBA emissions was calculated as a function of ambient thermodynamic conditions from the host E3SMv1, with distributions of fire sizes and sensible heat fluxes derived from the observations. The maximum fire radiative power (FRP) technique was used to determine the fire size. Scaling‐FRP technique is used to calculate the wildfire heat release. Daily BBA emission, superimposed with a fire diurnal cycle retrieved from the satellite observation, was included in model simulations. The model shows improved agreement with satellite retrievals and in situ measurement during the National Oceanic and Atmospheric Administration Wildfire Experiment for Cloud chemistry, Aerosol absorption, and Nitrogen campaign. The model‐observation comparison demonstrates the importance of the plume‐rise model and fire diurnal cycle assumption in determining the BBA fields. We also find that E3SMv1 with new features produces a larger carbonaceous aerosol burden, leading to 0.13 W m−2 warming at the top of atmosphere compared to the default E3SMv1. This highlights the importance of accurately representing the BBA injection height and indicates a no‐linear nature in the BBA‐induced radiative effect.
Neuro‐Adaptive Finite Time Composite Fault Tolerant Control for Attitude Control Systems of Satellites
Authors: Wang Yingdong , Liang Tiantian , Yang Jianxiong , Liu Jian 
Published: December 2023

AbstractAn adaptive finite time composite fault tolerant control strategy based on an optimized neural network for Attitude control systems (ACSs) of satellites is proposed considering the state time‐varying delays, concurrent actuator and sensor faults, system uncertainties, modelable external disturbance and operating noise. An uncertain time‐varying state space model for ACSs of satellites is established, and sensor faults are equivalent to actuator‐like faults. A disturbance observer is designed for estimating the modelable external disturbance, and an improved dwarf mongoose optimization (DMO) algorithm based on the Levy flight distribution is utilized to optimize the basis function of hyperbasis function neural networks to better estimate the augmented actuator faults that include the actuator fault and the actuator‐like fault. Furthermore, an adaptive finite time composite fault‐tolerant controller is proposed, which includes the delay‐dependent feedback control law, disturbance estimation based‐disturbance compensation law and the adaptive fault compensation law based on the augmented fault estimation using the improved DMO‐hyper basis function neural network. The finite time boundness of the close‐loop dynamics to the uncertainties, operating noise, and augmented actuator faults and the robustness of the measurement to the uncertainties, operating noise and augmented actuator faults are analyzed, and the observer and controller design is formulated as the linear matrix inequalities. Simulation examples for ACSs in different working conditions are considered to exhibit the proposed method's effectiveness.
The Impact of Flocculation on In Situ and Ex Situ Particle Size Measurements by Laser Diffraction
Authors: de Lange S. I. , Sehgal D. , Martínez‐Carreras N. , Waldschläger K. , Bense V. , Hissler C. , Hoitink A. J. F. 
Published: December 2023

AbstractAccurate particle size distribution (PSD) measurements of suspended particulate matter (SPM) composed of flocs and aggregates are important to improve understanding of ecological and geomorphological processes, and for environmental engineering applications. PSDs can be measured in situ (in the field) using a submersible sensor, or ex situ (in the laboratory) using samples. The methodological choice is often guided by logistical factors, and the differences in PSDs acquired by in situ and ex situ measurements is of concern. In this study, a laser‐diffraction instrument (the LISST‐200X) was used to compare in situ and ex situ PSD measurements. Samples measured ex situ were stored for three consecutive weeks and measured each week in a laboratory using different stirrer speeds. We observed that ex situ measurements display a higher D50 (median particle size) than in situ measurements of the same sample (up to 613% larger, 112% on average). Our experiments show that the difference between in situ and ex situ measurements can be explained by flocculation of the riverine sediments during the first week of storage. During the subsequent ex situ measurements, the stirring results in a significantly lower D50. Ex situ measurements are therefore unsuitable for flocculated SPM. This study provides recommendations for optimizing PSD measurements by calculating the measurement times required to obtain robust PSD measurements (exceeding 3 min per sample), which are larger for field samples with coarser particles and wider PSDs.
Multigroup analysis of compositions of microbiomes with covariate adjustments and repeated measures
Authors: Lin Huang , Peddada Shyamal Das 
Published: December 2023

AbstractMicrobiome differential abundance analysis methods for two groups are well-established in the literature. However, many microbiome studies involve more than two groups, sometimes even ordered groups such as stages of a disease, and require different types of comparison. Standard pairwise comparisons are inefficient in terms of power and false discovery rates. In this Article, we propose a general framework, ANCOM-BC2, for performing a wide range of multigroup analyses with covariate adjustments and repeated measures. We illustrate our methodology through two real datasets. The first example explores the effects of aridity on the soil microbiome, and the second example investigates the effects of surgical interventions on the microbiome of patients with inflammatory bowel disease.
A Tutorial on Skeletal Muscle Metabolism and the Role of Blood Lactate: Implications for Speech Production
Authors: Morton-Jones Mariah E. , Gladden L. Bruce , Kavazis Andreas N. , Sandage Mary J. 
Published: December 2023

Purpose:
The purpose of this tutorial is threefold: (a) present relevant exercise science literature on skeletal muscle metabolism and synthesize the limited available research on metabolism of the adult human speech musculature in an effort to elucidate the role of metabolism in speech production; (b) introduce a well-studied metabolic serum biomarker in exercise science, lactate, and the potential usefulness of investigating this metabolite, through a well-established exercise science methodology, to better understand metabolism of the musculature involved in voice production; and (c) discuss exercise physiology considerations for future voice science research that seeks to investigate blood lactate and metabolism in voice physiology in an ecologically valid manner.

Method:
This tutorial begins with relevant exercise science literature on the basic cellular processes of muscle contraction that require energy and the metabolic mechanisms that regenerate the energy required for task execution. The tutorial next synthesizes the available research investigating metabolism of the adult human speech musculature. This is followed by the authors proposing a hypothesis of speech metabolism based on the voice science literature and the application of well-studied exercise science principles of muscle physiology. The tutorial concludes with a discussion and the potential usefulness of lactate in investigations to better understand the metabolism of the musculature involved in vocal demand tasks.

Conclusion:
The role of metabolism during speech (respiratory, laryngeal, and articulatory) is an understudied yet critical aspect of speech physiology that warrants further study to better understand the metabolic systems that are used to meet vocal demands.
An adaptive image compression algorithm based on joint clustering algorithm and deep learning
Authors: Liang Yanxia , Zhao Meng , Liu Xin , Jiang Jing , Lu Guangyue , Jia Tong 
Published: December 2023

AbstractIn recent years, deep artificial neural networks have attracted much attention and have been applied in various fields because they surpass the parameter fitting effect of traditional methods under the condition of data convergence. On the other hand, limited transmission bandwidth and storage capacity make image compression necessary in communication. Here, a compression algorithm that combines the K‐means clustering algorithm with the neural network algorithm is proposed. First, the pixel points of the image are clustered by K‐means algorithm in order to reduce the amount of data input to the neural network algorithm. Secondly, neural network is used to extract image features which realizes further compression. The experiment results show that the peak signal‐to‐noise ratio (PSNR) is 33.48 dB at most with compression ratio at 32:1. The ablation experiment shows that the run time speeds up 9.5% compared to the algorithm without K‐means clustering. Comprehensive comparison experiment shows that the average PSNR is 30.09 dB, which is larger than other baseline approaches. The proposed algorithm is an efficient solution for image compression.
A wideband dual‐band bandstop filter with flexible control of stopband rejection, bandwidth and centre frequency ratio
Authors: Xu Chang , Wang Xiaolong , Zhu Lei , Sun Wenzhong , Li Kun , Milinevsky Gennadi , Lu Geyu 
Published: December 2023

AbstractA novel wideband dual‐band bandstop filter with multi‐transmission zeros and multi‐reflection zeros is presented. It consists of two pairs of symmetric open‐ended coupled lines at two sides and (2N − 1) pairs of coupled‐line sections with an open‐circuited stub in the middle. Through even‐ and odd‐mode analyses, general simultaneous equations for characteristic impedances are derived with the proposed algorithm. By suitably selecting all the design parameters, the proposed topology could not only provide a controllable equal‐ripple response in the passband but also control the stopband rejection, bandwidth (BW), and centre frequency ratio in the stopband flexibly. For verification, one prototype circuit is finally fabricated and measured in the experiment. Good agreement between the measured and simulated results is attained so as to successfully validate the correctness of the proposed design method.
A distributed peer‐to‐peer energy trading model in integrated electric–thermal system
Authors: Huang Ting , Sun Yi , Hao Jianhong , Sun Chong , Liu Chuang 
Published: December 2023

AbstractTo promote the energy accommodation of both electrical and heating power while considering the source–load uncertainties, a peer‐to‐peer (P2P) energy trading model among prosumers in the integrated electric–thermal system is proposed here, considering the energy trading agent (ETA) with self‐build energy system. The solar heat‐pump hybrid thermal water system (SPTS) and the transferring loss of heating power is considered and modelled based on the principle of steady‐state thermal transfer. Since the variations of load and PV cannot be described by any single common distribution, the chance‐constraints programming based on the Gaussian mixture model (GMM) is proposed to handle the uncertainty of the net load. As the proposed power trading problem is a non‐convex problem with binary variables, an improved alternating direction method of multiplier (ADMM) based on the predictor‐corrector and two‐stage cycle iterations is proposed to enhance the convergence performance of standard ADMM. Finally, an example simulation verifies the effectiveness; this results show that the proposed model can decrease the total cost by 26.7% and enhance local energy balance by 61.8% compared to other cases.
Condition assessment criteria evaluation of asymmetric aged and fully aged silicone rubber insulators based on leakage current harmonics
Authors: Esmaieli Mehdi , Khodsuz Masume , Nouri Hassan 
Published: December 2023

AbstractThe leakage current characteristic monitoring of transmission line insulators is considered a worthy technique for insulator state prediction. In this paper, the harmonic analysis of leakage current signals has been performed to analyze the composite insulator condition. Experimental studies of asymmetrically aged, fully aged, and virgin insulators have been conducted. The effects of different aging types, pollution, and humidity on leakage current components, such as harmonics and the phase differences with the applied voltage, have been investigated. The analysis of the results shows that the effect of asymmetric aging on leakage current components is non‐linear, and this non‐linearity increases with the degree of pollution. Also, the type of insulator aging can be determined by the ratio of the third‐ and fifth‐order leakage current harmonics. For instance, the classification of insulators into virgin, asymmetrically aged, and fully aged can be determined by examining the corresponding value ranges of 0–0.5, 0.5–0.9, and > 0.9, respectively. Similarly, the phase difference values of < 15% and those > 15% indicate the clean and polluted operating conditions individually.
A Comprehensive Review of Pyogenic Spondylitis Management for Neurosurgeons
Authors: Yunoki Masatoshi 
Published: December 2023

AbstractOlder populations have been increasing recently, resulting in an increase in cases of pyogenic spondylitis. Neurosurgeons who frequently treat the elderly are at a higher risk of encountering this condition. Therefore, this article provides a summary of the literature and our experience to help neurosurgeons effectively manage pyogenic osteomyelitis. It is important not to rule out pyogenic spondylosis when examining a patient with back pain, even in the absence of a fever. This is because the chronic type is common, easily overlooked, and early diagnosis and treatment are crucial. Empirical antibiotics should be avoided in cases where blood culture and biopsy are negative, to prevent microbial resistance and an increase in difficult-to-treat cases. Biopsies, such as computed tomography-guided percutaneous biopsy and full endoscopic debridement and drainage, should be attempted. Currently, 6 weeks of parenteral antibiotic therapy is the main treatment for pyogenic spondylitis. Surgical treatment is recommended if this method is ineffective. However, in the early stages, full endoscopic debridement and drainage and percutaneous pedicle screw fixation are optional.