bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chemo‐enzymatic Synthesis of Pseudo‐trisaccharide Aminoglycoside Antibiotics with Enhanced Nonsense Read‐through Inducer Activity
Authors: Lee Na Joon , Kang Woongshin , Kwon Younghae , Oh Jae Wook , Jung Hogwuan , Seo Minsuk , Seol Yurin , Wi Jae Bok , Ban Yeon Hee , Yoon Yeo Joon , Park Je Won 
Published: October 2022

AbstractAminoglycosides (AGs) are broad‐spectrum antibiotics used to treat bacterial infections. Over the last two decades, studies have reported the potential of AGs in the treatment of genetic disorders caused by nonsense mutations, owing to their ability to induce the ribosomes to read through these mutations and produce a full‐length protein. However, the principal limitation in the clinical application of AGs arises from their high toxicity, including nephrotoxicity and ototoxicity. In this study, five novel pseudo‐trisaccharide analogs were synthesized by chemo‐enzymatic synthesis by acid hydrolysis of commercially available AGs, followed by an enzymatic reaction using recombinant substrate‐flexible KanM2 glycosyltransferase. The relationships between their structures and biological activities, including the antibacterial, nephrotoxic, and nonsense readthrough inducer (NRI) activities, were investigated. The absence of 1‐N‐acylation, 3′,4′‐dideoxygenation, and post‐glycosyl transfer modifications on the third sugar moiety of AGs diminishes their antibacterial activities. The 3′,4′‐dihydroxy and 6′‐hydroxy moieties regulate the in vitro nephrotoxicity of AGs in mammalian cell lines. The 3′,4′‐dihydroxy and 6′‐methyl scaffolds are indispensable for the ex vivo NRI activity of AGs. Based on the alleviated in vitro antibacterial properties and nephrotoxicity, and the highest ex vivo NRI activity among the five compounds, a kanamycin analog (6′‐methyl‐3′′‐deamino‐3′′‐hydroxykanamycin C) was selected as a novel AG hit for further studies on human genetic disorders caused by premature transcriptional termination.
An IoT enabled smart healthcare system using deep reinforcement learning
Authors: Jagannath Duraiswamy Jothinath , Dolly Raveena Judie , Let Gunamony Shine , Peter James Dinesh 
Published: October 2022

AbstractSmart healthcare systems do exist with a variety of architectures. However, the hunt for better smart healthcare systems is more predominant. The cutting‐edge field of IoT (internet of things) and technological developments provide better solutions for smart healthcare systems using Sensor–Body Area Networks. Thus, the patient's sensor data can be collected, stored, analyzed, and suitable treatments can be offered, over the inter‐network, anytime, anywhere. The most complex part in such systems is the physician analysis of the huge volume of patient's data, to handle and prepare suitable diagnose and treatment for humanity. This article reveals a methodology of Deep Reinforcement Learning for smart healthcare decisions in an IoT interfaced Smart Healthcare–intelligent monitoring system. The system incorporates four layers, patient data collection, Edge computing, patient data transmission and Cloud computing. IoT is employed for automatic collection of Patient's data and for transmission of data, to data centers. Artificial intelligence techniques are used to analyze these data to provide suitable decisions, diagnosis, and treatment for those patients and humanity. Deep Reinforcement Learning provides the platform for smart decisions, diagnosis, and treatment. The investigation was experimented with synthetic simulated data of various BAN sensors. We developed a data set of size 286, which contains 21 different health parameters. After pre‐processing, these data were stored in the Amazon web services (AWS) cloud server using (message queue telemetry and transport) MQTT–IoT protocol. Initially, the Deep Q‐Network (DQN) was imposed to the training algorithm. The methodology was examined in PyTorch using a single GTX 1080 Ti X GPU with the training data sizes from 27 to 1536. The training time was about 10,000 to 90,000 s for training 500 epochs. In the high dimensional action space environment, the algorithm responded slowly to analyze, explore, and determine effective healthcare strategies. The systems convergence response of estimated hidden health state (g') and the actual health state (g) for the 21 different health parameters were estimated, whose values range from 0 to 1. The system responded with smart decisive interventions, which were good and close to that of a Physician's decision. The proposed methodology is definitely a promising solution for a smart and economic telemedicine.
RETRACTED: Response of intercropping coffee (Coffea arabica L.) with banana (Musa spp.) on yield, yield components, and quality of coffee
Authors: Tehulie Nuru Seid , Nigatie Taminaw Zewdie 
Published: October 2022

AbstractThe coffee plant (Coffea arabica L.) is thought to have begun as an understory tree species in Ethiopia's northeastern high rain forests. Bananas (Musa spp.) are commonly intercropped with coffee to provide shade as well as food and money. However, the effect of this practice on coffee production is little known, hence the present study was initiated with the objective of evaluating the effect of intercropping coffee with banana on the yield and quality of both crops. The experiment was carried out using mature coffee intercropped with banana (var. Butezua) in different ratios in Kalu district, northeastern Ethiopia between the 2018 and 2020 cropping seasons. It was conducted in a randomized complete block design with three replications of four intercropping ratios (4C:1B, 3C:1B, 2C:1B, and 1C:1B) and two sole cropped plots (sole coffee, C; and sole banana, B). Over years, analysis of variance showed that intercropping of coffee and banana highly significantly (p < .01) influenced yield and growth parameters, such as clean coffee (a coffee free of taints and defects) yield, total plant height, number of main stem nodes, main stem internode length, number and percent of bearing primary branches, number of fruiting nodes per branch, canopy diameter, leaf length, leaf width, and leaf area of coffee trees. Similarly, coffee bean length, bean width, bean thickness, height up to the first primary branch, and number of primary branches were significantly (p < .05) affected by the treatments. In general, the results revealed that among the intercropped treatments, the staggered planting pattern (4C:1B) gave the maximum clean coffee yield (1,357.3 kg ha−1) and fresh banana fruit yield (20,482 kg ha−1) followed by the 3C:1B treatment, which gave (1,346.5 and 21,321 kg ha−1) clean coffee and green banana yields, respectively. In addition, higher mean land equivalent ratios (LER) of 1.78 and 1.61 and maximum net benefits of 316,265.50 and 302,484.00 Ethiopian birr (ETB) ha−1 were obtained from 4C:1B and 3C:1B, respectively. Therefore, it can be concluded that farmers in the Kalu area and similar agro‐ecologies can use these two ratios when practicing coffee–banana intercropping. Further intercropping studies may be required to validate the present results over locations.
Honeycomb‐Type TiO2 Films Toward a High Tolerance to Optical Paths for Perovskite Solar Cells
Authors: Bao Yaqi , Wang Dourong , Hui Wei , Gu Lei , Chao Lingfeng , Song Lin 
Published: October 2022

AbstractGiven the advantages of high power conversion efficiencies (PCEs), antisolvent‐step free production, and suitability for device production in ambient conditions, perovskite solar cells (PSCs) based on ionic‐liquid solvents have attained particular research interest. To further improve device performance, light management could be optimized to increase light harvesting in the perovskite layer. Here, ordered honeycomb‐like TiO2 (Hc‐TiO2) structures with a periodicity of around 450 nm were fabricated through a sacrificial template method. With this photonic crystal structure, the control to light flow and the confinement effect for perovskite growth were achieved simultaneously in the Hc‐TiO2, leading to improved light absorption as well as preferred crystal orientation. Furthermore, a reduced trap‐state density and a well‐aligned energy level induced by the perovskite/pore interlayer facilitated the charge‐carrier extraction from the perovskite layer to electron transport layer. As a result, the structured devices performed better than the planar cells. And the angular dependent J–V sweeps show that the structured device reserved 76 % of its initial short circuit current density (Jsc), whereas the planar cell showed more than a half loss under the incident light of 40°, demonstrating a reduced downward trend in Jsc with the presence of photonic crystal structures. This occurrence also suggests that the structured PSCs in this work have a high tolerance to optical path changes.
Detection of 18‐methyl steroids: Case report on a forensic urine sample and corresponding dietary supplements
Authors: Thieme Detlef , Anielski Patricia , Rzeppa Sebastian , Wolf Clemens A. , Wolber Gerhard , Keiler Annekathrin M. 
Published: October 2022

AbstractThe detection of a putative 18‐methyl‐19‐nortestosterone metabolite in a forensic bodybuilder's urine sample collected as part of a criminal proceeding has triggered a follow‐up investigation. Four different dietary supplements in the possession of the suspect were examined with regard to possible precursor steroids. This led to the detection of the declared ingredient methoxydienone, which was confirmed by both, GC–MSMS and LC‐HRMSMS. As neither 18‐methyl‐testosterone, nor 18‐methyl‐19‐nortestosterone were detectable in the supplements, the possibility that the metabolite originates from methoxydienone was investigated. For this purpose, the metabolic fate of methoxydienone was studied in vitro using human HepG2 cells and in vivo by a single oral administration. While the 18‐methyl‐19‐nortestosterone metabolite was not generated by HepG2 cells incubated with methoxydienone, it was observed in the urine samples collected at 2, 6, 10 and 24 h after methoxydienone administration. Moreover, the potential binding of methoxydienone as ligand to the human androgen receptor was modelled in silico in comparison with 18‐methylnandrolone, for which androgen receptor activation had been shown in an in vitro approach before. In conclusion, we could ascribe the presence of the 18‐methyl‐19‐nortestosterone metabolite in a forensic urine sample to originate from methoxydienone present in dietary supplements. Methoxydienone was observed to slowly degrade by demethylation of the methoxy substituent in liquid solutions. While no compound‐specific intermediates were identified that allowed differentiation from other 18‐methyl steroids, the 18‐methyl‐19‐nortestosterone metabolite proved to be a suitable marker for reliable detection in doping analysis.
BeeDNA: Microfluidic environmental DNA metabarcoding as a tool for connecting plant and pollinator communities
Authors: Harper Lynsey R. , Niemiller Matthew L. , Benito Joseph B. , Paddock Lauren E. , Knittle E. , Molano‐Flores Brenda , Davis Mark A. 
Published: October 2022

AbstractPollinators are declining globally, and this loss can reduce plant reproduction, erode critical ecosystem services and resilience, and drive economic losses. Monitoring pollinator biodiversity trends is essential for adaptive conservation and management, but conventional surveys are often costly, time‐consuming, and requires considerable taxonomic expertise. Environmental DNA (eDNA) metabarcoding surveys are booming due to their rapidity, nondestructiveness, and cost efficiency. Microfluidic technology allows multiple primer sets from different markers to be used in eDNA metabarcoding for more comprehensive inventories, minimizing associated primer bias. We evaluated microfluidic eDNA metabarcoding for pollinator community monitoring in both controlled greenhouse and natural field settings. Using a variety of sampling, preservation, and extraction methods, we assessed pollinator communities with a number of markers using microfluidic metabarcoding. In greenhouse experiments, microfluidic eDNA metabarcoding detected the target bumblebee in two of four focal flower species as well as greenhouse insects in all focal flower species. In the field, numerous common regional arthropods, including some directly observed, were detected. Pollinator detection was maximized using whole flower heads preserved in ATL buffer and extracted with a modified Qiagen® DNeasy protocol for amplification with COI primers. eDNA surveillance could enhance pollinator assessment by detecting protected and endangered species and being more applicable to remote, inaccessible locations, whilst reducing survey time, effort, and expense. Microfluidic eDNA metabarcoding requires optimization to address remaining efficacy concerns, but this approach shows potential in revealing complex networks underpinning critical ecosystem functions and services, enabling more accurate assessments of ecosystem resilience.
Development of a hands‐free electrolarynx for obtaining a human‐like voice using the LPC residual wave
Authors: Takeuchi Masaki , Soejima Yutaro , Ahn Jaesol , Lee Kunhak , Takaki Ken , Ifukube Tohru , Yabu Ken‐Ichiro , Takamichi Shinnosuke , Sekino Masaki 
Published: October 2022

AbstractThe conventional electrolarynx (EL) restores the voice of people who have lost their voice, however, its voice sounds like a robot and it occupies user's one hand. Therefore, we developed a hands‐free wearable electrolarynx that improves the voice quality with the LPC residual wave as the vibration sound. Our device was able to reproduce sounds below 500 Hz, which is close to the fundamental frequency, but from 1700 Hz to 4000 Hz, the conventional EL continuously showed a frequency response closer to the spectrum of the user's vocal sound than our device. Thus, the periodic sound of the fundamental frequency band was found to be closer to human speech than individuality or sound quality.
Electrocatalytic Generation of Acyl Radicals and Their Applications
Authors: Zhang Haonan , Liang Sen , Wei Dengchao , Xu Kun , Zeng Chengchu 
Published: October 2022

AbstractIn this review, we highlighted the main achievements in the field of electrocatalytic generation of acyl radicals and their applications. These electrochemical strategies were introduced with an emphasis on the substrate scope, reaction limitation and underlying mechanism. The related reactions were categorized according to the pathways of acyl radical generation, including outer‐sphere electron transfer (ET), inner‐sphere ET, and hydrogen atom transfer (HAT) processes.
Nickel‐Catalyzed Cascade Cyclization‐Negishi Coupling of Redox Active Esters for the Synthesis of Pyrrolidines
Authors: Nieto‐Carmona Juan Carlos , San Román Raúl , Buñuel Elena , Cárdenas Diego J. 
Published: October 2022

AbstractWe have developed a Ni‐catalyzed cascade cyclization/Negishi‐coupling reaction for the formation of pyrrolidines and pyrrolidinones starting from N‐protected allylamines and acrylamides which contain a redox active ester group. The reaction provides two C−C bonds in a single operation and takes place with both alkylzinc and arylzinc bromides as nucleophiles. Activation of RAE by low valent Ni complexes involving a radical pathway followed by a fast cyclization of intermediate carbon radicals is proposed.
Copper(I)‐Catalyzed Regioselective Tandem Cyanoalkylative Cyclization of 1,5‐Dienes with Cyclobutanone Oxime Esters
Authors: Wang Panpan , Leng Yuting , Wu Yangjie 
Published: October 2022

AbstractAn effective strategy for construction of 1,5‐dihydro‐2H‐pyrrol‐2‐one scaffolds by a cascade of 1,5‐dienes with cyclobutanone oxime esters was developed. The reaction proceeded through radical addition, 5‐endo cyclization, and subsequent deprotonation, in which two new C−C bonds were formed. This protocol features excellent regioselectivity and a low‐cost catalyst, as well as broad substrate scope, which are expected to promote its potential applications in pharmacy and synthetic chemistry.
Application of Hilbert instantaneous spectrum on improved bolt anchoring quality detection
Authors: Li Chen , Gao Guozhong , Wang Yunsheng 
Published: October 2022

AbstractThe nondestructive testing technology for bolt anchoring quality based on the acoustic reflection method is developing rapidly. Hilbert transform instantaneous spectrum is frequently used. However, due to the existence of the folding phenomenon in the instantaneous phase, the accurate identification of reflected signal and the effective calculation of the anchorage compactness remain a challenge. The instantaneous frequency curve of the bolt signal is used to overcome the phase folding problem. The instantaneous frequency curve of the signal can help accurately identify the reflected signal from the bolt bottom and the position of the defect, thus accurately calculate the length of the bolt and the position of the defect. According to the analysis of the instantaneous amplitude curve of the signal, the formula for computing the bolt anchorage compactness is derived based on the correlation between the attenuation amplitude ratio of the reflected signal and the bolt anchoring quality. Research results show that difficult problems such as bolt reflection signal identification and anchorage compactness calculation are both effectively solved. The model simulation analyzes and field application examples verify the effectiveness and practicability of the methodology, which provides a robust way for the nondestructive testing of the bolt anchoring quality.
Channel synchronization based on deep learning
Authors: Wei Peng , Lu Ruimin , Ye Ganhua , Xie Shijun , Wang Ruidong 
Published: October 2022

AbstractAiming at the difficulty of the deep neural network (DNN) adapting to channel changes in communication systems, a channel synchronization deep neural network (CSDNN) based on deep learning (DL) is designed for realizing carrier synchronization, bit timing synchronization, and automatic gain control (AGC). By introducing a frequency‐domain cyclic convolution (FDCC) layer, the network transformed the time‐domain triangle activation into frequency domain linear activation taking FFT and IFFT matrixes as the activation function, solved the reverse gradient transmission‐blocking problems in training the time‐domain carrier synchronization neural network, effectively overcome the FFT inherent “fence” effect, and accurately compensated carrier frequency offset; By introducing a time‐domain cyclic convolution (TDCC) layer and the special frame structure design containing repetitive training sequence, the network training was completed to realize bit timing synchronization under the condition of the uncertain corresponding relationship between training data and labels. Combining phase inverse rotation dense (PIRD) layer, the network can be trained with very little training data to complete fast carrier synchronization and timing synchronization, at the same time adjust the received signal gain and suppress the jamming, which makes it is possible to train the channel synchronization deep neural network online under jamming environment, and provide a feasible way of realizing the intelligent communication system.
Education disrupted: Students beginning college during the COVID‐19 pandemic
Authors: Kinzie Jillian , Cole James 
Published: October 2022

AbstractIn the second year of the COVID‐19 pandemic, students entering college in fall 2021 had an unprecedented culmination to high school and transition to college. This chapter explores the experience of entering college students following these unprecedented circumstances, examining high school disruptions, including changes in the learning environment and its relationship to instructional mode preferences in college, and documenting students’ sense of optimism for college, their mental and emotional health, and perceptions of academic difficulty. Results show that the educational impact of the pandemic was not uniform across student groups and will remain an important factor in these students’ educational journey.
Methods to study adult hippocampal neurogenesis in humans and across the phylogeny
Authors: Terreros‐Roncal Julia , Flor‐García Miguel , Moreno‐Jiménez Elena P. , Rodríguez‐Moreno Carla B. , Márquez‐Valadez Berenice , Gallardo‐Caballero Marta , Rábano Alberto , Llorens‐Martín María 
Published: October 2022

AbstractThe hippocampus hosts the continuous addition of new neurons throughout life—a phenomenon named adult hippocampal neurogenesis (AHN). Here we revisit the occurrence of AHN in more than 110 mammalian species, including humans, and discuss the further validation of these data by single‐cell RNAseq and other alternative techniques. In this regard, our recent studies have addressed the long‐standing controversy in the field, namely whether cells positive for AHN markers are present in the adult human dentate gyrus (DG). Here we review how we developed a tightly controlled methodology, based on the use of high‐quality brain samples (characterized by short postmortem delays and ≤24 h of fixation in freshly prepared 4% paraformaldehyde), to address human AHN. We review that the detection of AHN markers in samples fixed for 24 h required mild antigen retrieval and chemical elimination of autofluorescence. However, these steps were not necessary for samples subjected to shorter fixation periods. Moreover, the detection of labile epitopes (such as Nestin) in the human hippocampus required the use of mild detergents. The application of this strictly controlled methodology allowed reconstruction of the entire AHN process, thus revealing the presence of neural stem cells, proliferative progenitors, neuroblasts, and immature neurons at distinct stages of differentiation in the human DG. The data reviewed here demonstrate that methodology is of utmost importance when studying AHN by means of distinct techniques across the phylogenetic scale. In this regard, we summarize the major findings made by our group that emphasize that overlooking fundamental technical principles might have consequences for any given research field.
Relative sensitivity value (RSV): A metric for measuring input parameter influence in life cycle assessment modeling
Authors: Bhatt Akul , Abbassi Bassim 
Published: October 2022

Abstract
Life cycle assessment (LCA) is a commonly used tool to quantify life cycle environmental footprints of products. Uncertainty in LCA modeling, particularly from uncertainty in production practices (represented through input parameter arguments), can lead to incorrect conclusions and hamper decision-making. Characterization of uncertainty through stochastic means and sensitivity analysis is utilized in a small fraction of LCA case studies, and the majority of studies default to scenario analysis due to its lower barrier to implementation and its results are easier to interpret. In this article, we introduce a sensitivity metric, relative sensitivity value (RSV), which allows LCA practitioners to gauge the relative influence of production practices on life cycle impacts in multiple phases and impact categories. Relative sensitivity value bridges the gap between scenario analysis and global sensitivity analysis, and it allows an LCA practitioner to provide an easy-to-interpret metric for quantifying the degree to which incremental changes in production practices influences the life cycle environmental footprint. We present the methodology used to calculate RSV and provide programming code, which can be readily used by an LCA practitioner to calculate RSV for their LCA model. We demonstrate the usage of RSV through a livestock husbandry LCA case study, in which we show how RSV results may be presented and interpreted, and how conclusions regarding production practices may be drawn. Integr Environ Assess Manag 2023;19:547–555. © 2022 SETAC