Susceptibility of European Agrilus beetle species to the biocontrol agents of Emerald Ash Borer in the laboratory by Katy Reed, Freya Cole, Neil Audsley, Anastasia Uglow, Rachel Down, Kerry Barnard, Daegan Inward

“…To allow a rapid response when the beetle is detected, slow its spread and protect trees as part of a wider integrated pest management programme, pre-emptive biological control strategies that are suitable for Great Britain and the rest of Europe must urgently be developed. Three classical hymenopteran biological control agents have been mass-reared and released within North America to control EAB: the egg parasitoid Oobius agrili Zhang and Huang (Hymenoptera: Encyrtidae), and the larval parasitoids Tetrastichus planipennisi and Spathius galinae Belokobylskij & Strazanac (Hymenoptera: Braconidae). …”
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Spectral multiplier theorems for abstract harmonic oscillators on UMD lattices by van Neerven, Jan, Portal, Pierre, Sharma, Himani

“…We prove functional calculus results for these abstract harmonic oscillators that match classical Hörmander spectral multiplier estimates for the harmonic oscillator $-\frac{1}{2}\Delta + \frac{1}{2}|x|^{2}$ on $L^{p}(\mathbb{R}^{d})$. …”
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Urdu Handwritten Characters Data Visualization and Recognition Using Distributed Stochastic Neighborhood Embedding and Deep Network by Mujtaba Husnain, Malik Muhammad Saad Missen, Shahzad Mumtaz, Dost Muhammad Khan, Mickäel Coustaty, Muhammad Muzzamil Luqman, Jean-Marc Ogier, Hizbullah Khattak, Sikandar Ali, Ali Samad

“…We performed three tasks in a disciplined order; namely, (i) we generated a state-of-the-art dataset of both the Urdu handwritten characters and numerals by inviting a number of native Urdu participants from different social and academic groups, since there is no publicly available dataset of such type till date, then (ii) applied classical approaches of dimensionality reduction and data visualization like Principal Component Analysis (PCA), Autoencoders (AE) in comparison with t-Stochastic Neighborhood Embedding (t-SNE), and (iii) used the reduced dimensions obtained through PCA, AE, and t-SNE for recognition of Urdu handwritten characters and numerals using a deep network like Convolution Neural Network (CNN). …”
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Telecommand Rejection Probability in CCSDS-Compliant LDPC-Coded Space Transmissions With Tail Sequence by Rebecca Giuliani, Massimo Battaglioni, Marco Baldi, Franco Chiaraluce, Nicola Maturo

“…A low-complexity approach classically used to detect CLTU termination is to choose a non-correctable string as the tail sequence, and then exploit the decoder failure on that sequence as termination detection. …”
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Functional Involvement of Melatonin and Its Receptors in Reproductive Regulation of the Marine Teleost, Large Yellow Croaker (<i>Larimichthys crocea</i>) by Xudong Liang, Jixiu Wang, Baoyi Huang, Haojie Yuan, Yucheng Ren, Chenqian Wu, Tianming Wang, Jingwen Yang

“…Enzyme- linked immunosorbent assay (ELISA) results further demonstrated that in vitro melatonin incubation in the brain of <i>L. crocea</i> influenced gonadotropin-releasing hormone (GnRH) and testosterone secretion in a dose-dependent manner, suggesting actions beyond the classical hypothalamic–pituitary–gonadal (HPG) axis. …”
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SensorDBSCAN: Semi-Supervised Active Learning Powered Method for Anomaly Detection and Diagnosis by Petr Ivanov, Maria Shtark, Alexander Kozhevnikov, Maksim Golyadkin, Dmitry Botov, Ilya Makarov

“…The proposed approach combines a transformer-based encoder trained with a triplet-based contrastive learning objective and the classical density-based clustering algorithm DBSCAN, enabling strong feature extraction, efficient and interpretable feature space organization and simple clustering algorithm. …”
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Determination of the degree of sulfonation in cross-linked and non-cross-linked Poly(ether ether ketone) using different analytical techniques by Abdul G. Al Lafi, Mohammed S. Rihawy, Abdul W. Allaf, Ali Alzier, Reem Hasan

“…Both non-cross-linked and cross-linked SPEEK were examined to assess the advantages and limitations of these methods. Classical approaches, such as titration and back titration are suitable for all sulfonated samples; however, they are limited by challenges like the extended time required for neutralization reaction due to hydrogen bonding between sulfonic acid groups. …”
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Mesenchymal stem cells-derived exosomes attenuate mouse non-heart-beating liver transplantation through Mir-17-5p-regulated Kupffer cell pyroptosis by Yang Tian, Ming Jin, Nanwei Ye, Zhenzhen Gao, Yuancong Jiang, Sheng Yan

“…This action inhibited NLRP3-mediated pyroptosis of Kupffer cells through the classical Caspase1-dependent pathway, alleviating DCD liver graft injury. …”
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Intravenous esketamine in pediatric Rett syndrome: An open-label, early phase 1 pilot study by Huiping Li, Shu Liu, Caimei Lin, Yuchao Wu, Xiuping Wu, Yukun Huang, Yajun Wu, Xiubin Tong, Xiu Xu

“…This was a prospective, single-arm, single-site, open-label, early phase 1 pilot study. Three girls with classic RTT aged 5–10 years were enrolled. Esketamine was intravenously administrated once per week for 5 weeks. …”
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Complete Genome Sequence of the Plant Growth-Promoting Bacterium Hartmannibacter diazotrophicus Strain E19T by Christian Suarez, Stefan Ratering, Torsten Hain, Moritz Fritzenwanker, Alexander Goesmann, Jochen Blom, Trinad Chakraborty, Boyke Bunk, Cathrin Spröer, Jörg Overmann, Sylvia Schnell

“…Interestingly, no genes classically reported to encode for ACC deaminase activity are present. …”
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<i>Rosa damascena</i> Mill. Essential Oil: Analysis of In Vitro and In Vivo Genotoxic and Cytotoxic Potentials by Employing Three Cytogenetic Endpoints by Tsvetelina Gerasimova, Svetla Gateva, Gabriele Jovtchev, Tsveta Angelova, Margarita Topashka-Ancheva, Ana Dobreva, Milka Mileva

“…That predetermined the object of this study—to evaluate, through classical cytogenetic methods, the possible cytotoxic/genotoxic activities of <i>R. damascena</i> Mill. …”
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Approximate Solutions of Combinatorial Problems via Quantum Relaxations by Bryce Fuller, Charles Hadfield, Jennifer R. Glick, Takashi Imamichi, Toshinari Itoko, J. Richard Thompson, Yang Jiao, M. Marna Kagele, W. Blom-Schieber Adriana, Rudy Raymond, Antonio Mezzacapo

“…It produces average cuts that approximate the optimal one by a factor of least 0.555 or 0.625, depending on the relaxation chosen, if given access to a quantum state with energy between the optimal classical cut and the maximal relaxed energy. The second rounding protocol is deterministic and is based on the estimation of Pauli observables. …”
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A Multistage Detection Framework Based on TFA and Multiframe Correlation for HFSWR by Zongtai Li, Gangsheng Li, Ling Zhang, Lanjun Liu, Q. M. Jonathan Wu

“…Comparative analysis against classical target detection algorithms demonstrates the superior detection performance of the proposed framework within clutter regions. …”
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Self‐Boosting Programmable Release of Multiple Therapeutic Agents by Activatable Heterodimeric Prodrug‐Enzyme Assembly for Antitumor Therapy by Shanshan Jiang, Bhaskar Gurram, Junfei Zhu, Shan Lei, Yifan Zhang, Ting He, Oya Tagit, Hui Fang, Peng Huang, Jing Lin

“…However, reactive oxygen species (ROS) as classical endogenous stimuli in the tumor microenvironment (TME) are not enough to achieve the expected drug release. …”
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3-Epi-betulinic acid 3-O-β-D-glucopyranoside (eBAG) induces autophagy by activation of AMP-activated protein kinase in hepatocellular carcinoma by Mengjie Liu, Xuqiang Liu, Kaiyue He, Yongping Jian, Yujia Li, Jinrong Guo, Jingyu Yang, Zhixiang Xu, Wenyi Kang

“…The eBAG-induced cell death was inhibited by knock-down of autophagy related gene (ATG) 5 and ATG7, by administration of 3-methyladenine, a selective autophagy inhibitor that suppresses phosphoinositide 3-kinase (PI3K), and by chloroquine, a classic autophagy f lux inhibitor. We demonstrated that eBAG induced an autophagy-mediated cell death. …”
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Evaluating machine learning models for supernova gravitational wave signal classification by Y Sultan Abylkairov, Matthew C Edwards, Daniil Orel, Ayan Mitra, Bekdaulet Shukirgaliyev, Ernazar Abdikamalov

“…We test convolutional and recurrent neural networks, as well as six classical algorithms: random forest, support vector machines, naïve Bayes(NB), logistic regression, k -nearest neighbors, and eXtreme gradient boosting. …”
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RECQL4 requires PARP1 for recruitment to DNA damage, and PARG dePARylation facilitates its associated role in end joining by Mansoor Hussain, Prabhat Khadka, Komal Pekhale, Tomasz Kulikowicz, Samuel Gray, Alfred May, Deborah L. Croteau, Vilhelm A. Bohr

“…Furthermore, depletion of PARP1 or RECQL4 substantially impacted classical-NHEJ- and alternative-NHEJ-mediated DSB repair. …”
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Triplet Electron Exchange in Carbon Nanodots‐assisted Long‐persistent near‐infrared Chemiluminescence for Oncology Synergistic Imaging and Therapy by Run‐Wei Song, Tian‐Ci Jiang, Xue‐Yang Zhang, Cheng‐Long Shen, Qing Lou, Chong‐Xin Shan

“…Abstract In classical photodynamic therapy, tumor cells are killed by the cytotoxic species via type‐I/II photochemical reactions, seriously limited by the external photoexcitation and hypoxia. …”
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Modeling and robust control of a parallel robotic mechanism driven by linear actuators based on shape memory alloys by Alejandro Guarneros-Sandoval, Mariana Ballesteros, Rita Q. Fuentes-Aguilar, Isaac Chairez

“…The results show the versatility of the single SMA-based actuator in developing a parallel structure using a hybrid model that can obtain better results than a classical PD controller. The structure control shows the possible use of the linear SMA actuator for more complex parallel mechanisms.…”
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Determinants of physical activity among female students based on the transtheoretical model by Maryam Abdoli, Leili Tapak, Payam Amini, Azam Geravandi, Babak Moeini, Omid Hamidi, Maryam Afshari

“…This study was conducted on 745 individuals between the ages of 12 and 16 years and was analyzed using a generalized linear model (GLM) approach with appropriate link functions using both classical and Bayesian frameworks. The results show that in model 1, the probit link function is a more appropriate approach to determine the risk factors for physical activity. …”
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