bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Two-dimensional P-type ZnO Powder Illuminated By Visible Light for the Inhibition of Gram-positive and Gram-negative Bacteria in Water
Authors: Díaz-Gómez C. , Carrillo-Morales M. , Zagal-Padilla C. K. , Masegosa-Méndez H. , Gamboa S. A.
Published: December 2023

Bacteria affect food quality in developing countries by spreading through contaminated soils and water. Antibiotics are used indiscriminately to eliminate Gram-positive and Gram-negative bacteria, with varying degrees of success. The use of nanomaterials with bactericidal properties can minimize the overuse of antibiotics. In this study, a two-dimensional p-type ZnO powder was successfully synthesized and its bactericidal properties were demonstrated. The XRD and Raman spectroscopy results indicated the presence of wurtzite-phase ZnO with Oi as the predominant native defect, resulting in p-type conductivity. SEM analysis confirmed the two-dimensional morphology, and optoelectronic characterization revealed a bandgap of 3.17 eV. Despite this high bandgap value, a plasmonic effect was generated on the surface of two-dimensional ZnO, which enhanced its bactericidal properties when the powders were in contact with bacteria. From an initial colony level of 5.5 × 105 CFU/mL, a significant decrease in the number of Gram-positive bacteria to 1.15 × 105 CFU/mL was observed, whereas the number of Gram-negative bacteria slightly increased to 1.45 × 106 CFU/mL. The observed inhibition rates were higher than those achieved with the broad-spectrum antibiotic, as validated in this study. The use of two-dimensional ZnO may provide a sustainable solution for the eradication of waterborne pathogens using visible light alone.
A taxonomy of critical factors towards sustainable operations and supply chain management 4.0 in developing countries
Authors: Caiado Rodrigo Goyannes Gusmão , Scavarda Luiz Felipe , Vidal Guilherme , de Mattos Nascimento Daniel Luiz , Garza-Reyes Jose Arturo
Published: December 2023

Supply chain disruptions, intensified by black swan events such as the COVID-19 pandemic and the Russia-Ukraine war, have increased the interest in resilient supply chains, which can be achieved by adopting sustainable Industry 4.0 (I4.0) practices. However, the critical success factors (CSFs) for sustainable I4.0 in operations and supply chain management (S-OSCM4.0) are unclear, and there is a lack of a holistic and empirically validated taxonomy of CSFs from multiple stakeholders' perspectives to guide organizations in this transition. Moreover, developing countries face specific challenges that require prioritizing the proper set of CSFs for sustainable digitalization. Therefore, this paper aims to develop a CSFs-based taxonomy for S-OSCM4.0 to help organizations stay current in I4.0 adoption and integrate sustainability in OSCM. We first conducted a systematic literature review (SLR) of 131 papers using bibliometric and content analyses and synthesized the theoretical findings into an alpha taxonomy of CSFs following an inductive approach. Then, we employed a Delphi survey technique combining fuzzy logic to solicit experts' perceptions from a developing country to analyze and validate the taxonomy and determine the most pertinent CSFs, resulting in a beta taxonomy of CSFs for S-OSCM4.0. The developed taxonomy represents a pioneering managerial artefact that can guide sustainable development through an inclusive digital transformation with less environmental impact, contributing to decision-making in S-OSCM4.0, especially for operations in developing countries.
Some Inequalities for the Fourier Transform and Their Limiting Behaviour
Authors: Garofalo Nicola
Published: December 2023

We identify a one-parameter family of inequalities for the Fourier transform whose limiting case is the restriction conjecture for the sphere. Using Stein’s method of complex interpolation, we prove the conjectured inequalities when the target space is $$L^2$$

L
2

, and show that this recovers in the limit the celebrated Tomas-Stein theorem.
A taxonomic revision of the genus Weberbauerella Ulbr. (Leguminosae: Papilionoideae) in Peru and Chile
Authors: Orellana-Garcia A. , Hechenleitner P. , Whaley O. Q. , Capcha-Ramos J. , Moat J. , Lewis G. P.
Published: December 2023

The little-known and infrequently collected papilionoid legume genus Weberbauerella, is only known from outlying regions of the Atacama Desert. Presently it comprises three species, one in Chile and two in Peru. These small, woody, perennial species, enigmatic in both occurrence and form, are found growing in isolated populations in climatically extreme conditions. They are characterised by the presence of pustular glands throughout. Here we revise the genus, providing a key to the species, descriptions, distribution maps, illustrations, assessments of conservation status and notes on a northern variant population.
Upper-GI highlights from ASCO and ASCO-GI 2023 meetings: changing paradigm in treatment sequence
Authors: Ilhan-Mutlu Aysegül , Bergen Elisabeth Sophie
Published: December 2023

The annual meeting of the American Society of Medical Oncology (ASCO) was held as usual in Chicago, while the meeting focused on gastrointestinal tumors, ASCO-GI, was held in San Francisco. In particular, ASCO-GI included many phase III trials, the data of which have the potential to change the practice in the near future for tumors of the upper gastrointestinal tract (upper-GI), including tumors of the esophagus, gastroesophageal junction, stomach, and pancreas. Interestingly, ASCO and also the European Society for Medical Oncology (ESMO) offer the virtual plenary sessions under the motto “Today’s Science Can Wait.” As more physicians and scientists become comfortable with online tools in the post-pandemic era, presenting potential practice-changing data outside of annual meetings appears feasible. Here we present a summary of upper-GI tumor abstracts from two major ASCO meetings including virtual plenary series.
Does Cultural Robotics Need Culture? Conceptual Fragmentation and the Problems of Merging Culture with Robot Design
Authors: Mansouri Masoumeh , Taylor Henry
Published: December 2023

Increasingly, roboticists have to pay attention to cultural norms and expectations. But roboticists have generally worked with a relatively narrow understanding of culture, based on nationality. This contrasts with the rich and diverse understandings of culture from disciplines as diverse as sociology, philosophy, and anthropology. Here we draw on the philosophy of science literature on scientific terminology to argue that culture is aconceptually fragmentedconcept: the concept has no unified definition, and alternative definitions of culture are useful for different areas within robotics. We argue that this has important implications for robotics. We consider two possible reactions to this situation. One claims that, despite the lack of a unified definition, the concept of culture still fulfils useful roles within robotics, and ought to be preserved. The other argues that the problems with the concept are so great that the concept ought to be eliminated from discussions in robotics. We argue in favour of the former option.
How can population models contribute to contemporary pest management practices?
Authors: Yamanaka Takehiko
Published: December 2023

Population models provide a logical knowledge base before conducting laborious and expensive field experiments. Historically, two types of population models have been developed: highly realistic simulations and simple analytical models. Highly realistic simulations comprise a complicated systems model, whereas simple analytical models comprise various analytical models that focus only on the fundamental structure of the target pest population. Although both approaches have contributed to pest management science, each has limitations, poor predictability, and lacks substantial connections to reality. Assimilation by state-space modeling, in which observation and process models are jointly incorporated, is a good compromise between a simple model and reality in nature. In the big data era, artificial intelligence (AI), specifically aimed at high predictability, has recently become popular. If vital physical and biological records are automatically censored in the field with high precision, AI will produce the most plausible predictions, providing the best practical solution given our current knowledge. AI can be a powerful tool in the contemporary world; however, deductive modeling approaches are still important when considering the behavior of AIs and may also provide important insights to detect deficient information in the data.
Digitalisierung und Regulierung am Arbeitsmarkt
Authors: Weber Enzo
Published: December 2023

Industrie 4.0 und künstliche Intelligenz stehen in der Agenda der Debatte um die Zukunft des Arbeitsmarkts seit Jahren an erster Stelle. Die Corona-Krise hat der Digitalisierung im Arbeitsleben nochmals einen plötzlichen Schub gegeben. Die Transformation der Wirtschaft und die Weiterentwicklung von Sozialstaat und Arbeitsgesellschaft stellen die entscheidenden Herausforderungen dar. Dieser Artikel diskutiert einige Kernfragen und politische Gestaltungmöglichkeiten: Grundeinkommen, Weiterbildungspolitik, Robotersteuern und soziale Sicherung.
An intent recognition pipeline for conversational AI
Authors: Chandrakala C. B. , Bhardwaj Rohit , Pujari Chetana
Published: December 2023

Natural 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

This 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

This 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

In 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

Aerosol 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

Upward 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

The 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

An 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

Accurate 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

Microbiome 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.
New model for aspartic acid species in aqueous calcium carbonate growth environments: challenges and perspectives
Authors: Schuitemaker Alicia , Koziara Katarzyna B. , Raiteri Paolo , Gale Julian D. , Demichelis Raffaella
Published: December 2023

A new classical model for aspartate anions relevant to biomineralization was developed. Their dynamics was explored in water, providing solvation structure and free energies, conformational free energy profiles and pairing free energies.
The effect of cation size on structure and properties of Ba-based tetragonal tungsten bronzes Ba4M2Nb10O30 (M = Na, K or Rb) and Ba4M2Nb8Ti2O30 (M = Ca or Sr)
Authors: Løndal Nora Statle , Williamson Benjamin Albert Dobson , Walker Julian , Einarsrud Mari-Ann , Grande Tor
Published: December 2023

We investigate the effect of the size of the M cation, including cation disorder, on the crystal structure and dielectric properties in a series of Ba-based tetragonal tungsten bronzes.
Porous carbonaceous materials simultaneously dispersing N, Fe and Co as bifunctional catalysts for the ORR and OER: electrochemical performance in a prototype of a Zn–air battery
Authors: Jaramillo Daniela , Alvarez German , Díaz Cristian , Pérez Sebastián , Muñoz Saldaña Juan , Sierra Ligia , López Betty Lucy , Moreno-Zuria Alonso , Mohamedi Mohamed , Palacio Ruben
Published: December 2023

Infiltration of mesopores in SBA-15 hard template with phenanthroline complexes of Fe3+ and Co2+ allowed the dispersion of nitrogen, iron and cobalt species on the surface of the CMK-3 replica, as heterogeneous catalyst for the ORR and OER reactions.
Half-sandwich ruthenium complexes with acylhydrazone ligands: synthesis and catalytic activity in the N-alkylation of hydrazides
Authors: Li Heng , Wang Ke , Yang Lin , Luo Yu-Zhou , Yao Zi-Jian
Published: December 2023

Half-sandwich ruthenium complexes exhibit excellent catalytic efficiency in the N-alkylation of acyl hydrazides using alcohols as coupling partners.
Anthracene derivatives with strong spin–orbit coupling and efficient high-lying reverse intersystem crossing beyond the El-Sayed rule
Authors: Kim Ki Ju , Kim Jaesung , Lim Jong Tae , Heo Jinyeong , Park Bum Jun , Nam Hyewon , Choi Hyeonwoo , Yoon Seung Soo , Kim Woojae , Kang Sunwoo , Kim Taekyung
Published: December 2023

The anthracene derivative, 2MIQ-NPA, exhibits a high-lying reverse intersystem crossing process, diverging from El-Sayed rule. In the blue OLED utilizing 2MIQ-NPA, the exciton utilization efficiency reaches 64.3%, surpassing the theoretical limit.
Fe-doped carbon dot liposome enhanced radiosensitivity of tumor cells by inducing ferroptosis
Authors: Ge Guili , Tu Hanyu , Wang Dan , Chen Mingjian , Zeng Zhaoyang , Guo Can , Wu Xu , Xiong Wei
Published: December 2023

Fe-CDs-PEG, a new kind of nanometer carbon dots material can catalyze H2O2 to produce ROS and effectively inhibit the proliferation of lung cancer cells through ROS, induce lung cancer cells ferroptosis, and enhance radiotherapy sensitivity.
Electrode-free flexible batteries enabled by electro-deposition of both Zn and MnO2 from electrolytes
Authors: Luo Shiqiang , Liu Shiwei , Yang Guoshen , Liu Chuanlong , Wu Jiazhen , Hiralal Pritesh , Nie Zanxiang , Amaratunga Gehan A. J. , Zhou Hang
Published: December 2023

Flexible thin-film and cable batteries are fabricated with the pre-coating steps of anode and cathode materials replaced by one-step charging.
Functional magnetic nanoparticles for protein delivery applications: understanding protein–nanoparticle interactions
Authors: Sharma Rajat , Ungar Daniel , Dyson Edward , Rimmer Stephen , Chechik Victor
Published: December 2023

Magnetic iron oxide nanoparticles coated with PNIPMAM polymer can encapsulate protein guests and release them upon (magnetic) heating above 45 °C in the presence of competitor proteins.
Advanced inorganic nanomaterials for high-performance electrochromic applications
Authors: Huang Zekun , Feng Liping , Xia Xianjie , Zhao Jing , Qi Penglu , Wang Yiting , Zhou Junhua , Shen Laifa , Zhang Shengliang , Zhang Xiaogang
Published: December 2023

Advanced electrochromic nanomaterials with excellent optical performance have shown numerous potential applications including smart windows, multicolor displays, atuto-diming mirrors, camouflage and adaptive thermal management.
Electrochemistry-enabled residue-specific modification of peptides and proteins
Authors: Bandyopadhyay Ayan , Biswas Pranay , Kundu Sudipta K. , Sarkar Rajib
Published: December 2023

This review focuses on up-to-date developments of electrochemistry-promoted residue-specific modification of peptides and proteins. Specific modification protocols for five redox-active amino acid residues, namely cysteine, tyrosine, tryptophan, histidine and methionine, were explained in detail.
Rapid synthesis of benzofulvenes from α-bromodiarylethylenes based on a 1,4-palladium shift strategy
Authors: Rahim Abdur , Zhan Shuming , Hong Biqiong , Duan Longhui , Gu Zhenhua
Published: December 2023

The synthesis of benzofulvenes from α-halo diarylethylenes through 1,4-palladium migration has been reported. The reaction accepts a variety of functional groups and affords a wide range of functionalized benzofulvenes up to 93% yields.
Single-molecule electrochemical imaging resolves the midpoint potentials of individual fluorophores on nanoporous antimony-doped tin oxide
Authors: Lu Jin , Lew Matthew D.
Published: December 2023

We report reversible switching of oxazine, cyanine, and rhodamine dyes by a nanoporous antimony-doped tin oxide electrode that enables single-molecule (SM) imaging of electrochemical activity.
Enzymatic-related network of catalysis, polyamine, and tumors for acetylpolyamine oxidase: from calculation to experiment
Authors: Fang Dong , Zhang Zhiyang , Zhai Jihang , Guo Baolin , Li Pengfei , Liu Xiaoyuan , Song Jinshuai , Xie Songqiang , Wu Ruibo , Zhao Yuan , Wang Chaojie
Published: December 2023

Enzymatic-related network of catalysis, polyamine, and tumors for acetylpolyamine oxidase: from calculation to experiment.
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.
VdaBSC: A Novel Vulnerability Detection Approach for Blockchain Smart Contract by Dynamic Analysis
Authors: Sosu Rexford Nii Ayitey , Chen Jinfu , Boahen Edward Kwadwo , Zhang Zikang
Published: December 2023

Smart contracts have gained immense popularity in recent years as self‐executing programs that operate on a blockchain. However, they are not immune to security flaws, which can result in significant financial losses. These flaws can be detected using dynamic analysis methods that extract various aspects from smart contract bytecode. Methods currently used for identifying vulnerabilities in smart contracts mostly rely on static analysis methods that search for predefined vulnerability patterns. However, these patterns often fail to capture complex vulnerabilities, leading to a high rate of false negatives. To overcome this limitation, researchers have explored machine learning‐based methods. However, the accurate interpretation of complex logic and structural information in smart contract code remains a challenge. In this study, we present a technique that combines real‐time runtime batch normalization and data augmentation for data preprocessing, along with n‐grams and one‐hot encoding for feature extraction of opcode sequence information from the bytecode. We then combined bidirectional long short‐term memory (BiLSTM), convolutional neural network, and the attention mechanism for vulnerability detection and classification. Additionally, our model includes a gated recurrent units memory module that enhances efficiency using historical execution data from the contract. Our results demonstrate that our proposed model effectively identifies smart contract vulnerabilities.
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

In 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

A 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

To 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

The 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

Older 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.
Truth and its political forms: an explorative cartography
Authors: Posselt Gerald , Seitz Sergej
Published: December 2023

For some years now, the significance of truth for politics has been intensely debated under the buzzword “post-truth.” However, this cannot hide the fact that political theory and philosophy have systematically neglected the relationship between truth and politics throughout their history. This article intends to remedy this desideratum by differentiating the various modes in which truth is referred to and invoked in the political field. To this end, the main strands of the post-truth debate are reconstructed and their shortcomings are pointed out. Second, based on a contrasting reading of Habermas and Foucault, possible starting points for systematizing the relationship between truth and politics are discussed. Third, and as a prolegomenon to such a systematization, the article proposes a cartography of political truth forms and relations along five fault lines: truth as foundation and de-foundation, truth as coercion and freedom, truth as virtue and scandal, truth as secret and transparency, and truth as knowledge and practice.
High-pressure structure and reactivity of crystalline bibenzyl: Insights and prospects for the synthesis of functional double-core carbon nanothreads
Authors: Agati Milo , Romi Sebastiano , Fanetti Samuele , Bini Roberto
Published: December 2023

The high-pressure synthesis of double-core nanothreads derived from pseudo-stilbene crystals represents a captivating approach to isolate within the thread chromophores or functional groups without altering its mechanical properties. These entities can be effectively utilized to finely tune optical properties or as preferential sites for functionalization. Bibenzyl, being isostructural with other members of this class, represents the ideal system for building co-crystals from which we can synthesize double-core nanothreads wherein bridging chromophores, such as the azo or ethylene moieties, are embedded in the desired concentration within a fully saturated environment. To achieve this, a critical step is the preliminary characterization of the high-pressure behavior of crystalline bibenzyl. We report here an accurate investigation performed through state-of-the-art spectroscopic techniques, Raman and Fourier transform infrared spectroscopy, and x-ray diffraction up to 40 GPa. Our findings reveal a strongly anisotropic compression of the crystal, which determines, at pressures between 1 and 2 GPa, consistent modifications of the vibrational spectrum, possibly related to a torsional distortion of the molecules. A phase transition is detected between 9 and 10 GPa, leading to a high pressure phase where, above 24 GPa, the nanothread formation is observed. However, the observed reaction was limited in extent and required significantly higher pressures in comparison to other members of the pseudo-stilbene family. This comprehensive study is imperative in laying the foundation for future endeavors, aiming to synthesize double-core nanothreads from pseudo-stilbene crystals, and provides crucial insights into the high-pressure behavior and phase transitions of crystalline bibenzyl.
Progressive augmentation of turbulence models for flow separation by multi-case computational fluid dynamics driven surrogate optimization
Authors: Amarloo Ali , Rincón Mario Javier , Reclari Martino , Abkar Mahdi
Published: December 2023

In the field of data-driven turbulence modeling, the consistency of the a posteriori results and generalizability are the most critical aspects of new models. In this study, we combine a multi-case surrogate optimization technique with a progressive augmentation approach to enhance the performance of the popular k−ω shear stress transport (SST) turbulence model in the prediction of flow separation. We introduce a separation factor into the transport equation of a turbulent specific dissipation rate (ω) to correct the underestimation of the turbulent viscosity by the k−ω SST model in the case of flow separation for two-dimensional cases. The new model is optimized based on their performance on the training cases including periodic hills and curved backward-facing step flow. Simulation of the channel flow is likewise included in the optimization process to guarantee that the original performance of k−ω SST is preserved in the absence of separation. The new model is verified on multiple unseen cases with different Reynolds numbers and geometries. Results show a significant improvement in the prediction of the recirculation zone, velocity components, and distribution of the friction coefficient in both training and testing cases, where flow separation is expected. The performance of the new models on the test case with no separation shows that they preserve the successful performance of k−ω SST when flow separation is not expected.
Laminar-type gratings overcoated with carbon-based materials to enhance analytical sensitivity of flat-field emission spectrograph in the VUV region
Authors: Murano T. , Koshiya S. , Koike M. , Hatano T. , Pirozhkov A. S. , Kakio T. , Hayashi N. , Oue Y. , Konishi K. , Nagano T. , Kondo K. , Terauchi M.
Published: December 2023

Laminar-type spherical diffraction gratings overcoated with carbon-based materials were designed, fabricated, and evaluated for the purpose of enhancing the analytical sensitivity of the flat-field spectrograph in a vacuum ultraviolet region of 35–110 eV. As the design benchmark for numerical calculations, diffraction efficiency (DE) and spectral flux, which are defined by the product of the DE and numerical aperture and correlate with the analytical sensitivity of the spectrograph, were used. To simplify the feasibility study on the overcoating effects, we assumed a laminar-type grating having a grating constant of 1/1000 mm and coated with a Au layer of 30.0 nm thickness and an incidence angle of 84.0°. The optimized groove depth and duty ratio were 30.0 nm and 0.3, respectively. In addition, the optimum thicknesses of the overcoating layer were 44, 46, 24, and 30 nm for B4C, C, diamond-like-carbon, and SiC, respectively. Based on these results, we have fabricated a varied-line-spacing holographic grating overcoated with B4C with a thickness of 47 nm. For the experimental evaluation, we used the light source of Mg-L and Al-L emissions excited by the electron beam generated from an electron microscope, an objective flat-field spectrograph, and a CCD imaging detector. The experimental results showed that the spectrograph employing a new grating overcoated with the B4C layer indicated almost the same spectral resolution and 2.9–4.2 times higher analytical sensitivity compared with those obtained with a previously designed Au-coated grating having a grating constant of 1/1200 mm and used at an incidence of 86.0°.