Lightweight Transformer traffic scene semantic segmentation algorithm integrating multi-scale depth convolution by Gang XIE, Quanyi WANG, Xinlin XIE, Jian’an WANG

“…Aiming at the problems of discontinuous segmentation of thin strip objects that were easy to blend into the surrounding background and a large number of model parameters in the semantic segmentation algorithm of traffic scenes, a lightweight Transformer traffic scene semantic segmentation algorithm integrating multi-scale depth convolution was proposed.First, a multi-scale strip feature extraction module (MSEM) was constructed based on deep convolution to enhance the representation ability of thin strip target features at different scales.Secondly, a spatial detail auxiliary module (SDAM) was designed using the convolutional inductive bias feature in the shallow network to compensate for the loss of deep spatial detail information to optimize object edge segmentation.Finally, an asymmetric encoding-decoding network based on the Transformer-CNN framework (TC-AEDNet) was proposed.The encoder combined Transformer and CNN to alleviate the loss of detail information and reduce the amount of model parameters; while the decoder adopted a lightweight multi-level feature fusion design to further model the global context.The proposed algorithm achieves the mean intersection over union (mIoU) of 78.63% and 81.06% respectively on the Cityscapes and CamVid traffic scene public datasets.It can achieve a trade-off between segmentation accuracy and model size in traffic scene semantic segmentation and has a good application prospect.…”
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Exploration of Potent Human α-Glucosidase Inhibitors Using In Silico Approaches: Molecular Docking, DFT, Molecular Dynamics Simulations, and MMPBSA by Jyoti Bashyal, Bimal Kumar Raut, Siddha Raj Upadhyaya, Kabita Sharma, Niranjan Parajuli

“…Furthermore, drug-like behavior and favorable ADMET profiles affirmed scolopianate A and ponasterone A as robust α-glucosidase inhibitors. …”
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Harnessing the power of seaweed: unveiling the potential of marine algae in drug discovery by Leonel Pereira, Ana Valado

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Sirkusdirektør Arnardos manesjespråk by Lars Anders Kulbrandstad, Anne Golden

“…Dette holder vi opp mot det som karakteriserer varieteten rent lingvistisk slik vi finner den dokumentert blant annet i videoopptak av sirkusforestillinger. …”
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APLICACIÓN DEL ANÁLISIS FACTORIAL PARA DISCRIMINAR ESPACIALMENTE VARIABLES GEOGRAFICAS by Arnobio Germán Poblete, Juan Leonidas Minetti, María José Vera

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High-Throughput Screening and Molecular Dynamics Simulation of Natural Products for the Identification of Anticancer Agents against MCM7 Protein by Xin Zhang, Hui Chen, Hui Lin, Ronglan Wen, Fan Yang

“…As a consequence of using specific pharmacological, physiological, and ADMET criteria, four new prevailing compounds, NPA000018, NPA000111, NPA00305, and NPA014826, were successfully selected. …”
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Insilico targeting of virus entry facilitator NRP1 to block SARS-CoV2 entry. by Nousheen Bibi, Maleeha Shah, Shahzad Khan, Muhammad Shahzad Chohan, Mohammad Amjad Kamal

“…Following virtual screening, docking studies, and evaluation of binding affinity and ADMET properties, 10 compounds were shortlisted. …”
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Structure-guided identification of mitogen-activated protein kinase-1 inhibitors towards anticancer therapeutics. by Md Nayab Sulaimani, Shazia Ahmed, Farah Anjum, Taj Mohammad, Anas Shamsi, Ravins Dohare, Md Imtaiyaz Hassan

“…Subsequently, the selected hits underwent rigorous screening that included the identification of potential pan-assay interference compounds (PAINS), ADMET evaluation, and prediction of pharmacological activities using PASS analysis. …”
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Molecular docking of phytosterols in Stenochlaena palustris as anti-breast cancer by Dona Marisa, Lisda Hayatie, Siti Juliati, Eko Suhartono, Noer Komari

“…Molecular docking parameters included Gibb's free energy and interactions between ligand and protein. ADMET properties were analyzed using pkCSM and SwissADME. …”
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Synthesis, characterization, and in silico studies of substituted 2,3-dihydro-1,3,4-thiadiazole derivatives by Yasser H. Zaki, Sobhi M. Gomha, Basant Farag, Magdi E.A. Zaki, Ahmed M. Hussein

“…Notably, parameters such as heat of formation, net charges, and dipole moments were computed, revealing good agreement between the experimental and theoretical results. …”
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Therapeutic molecules for multiple human diseases identified from pigeon pea (Cajanus cajan L. Millsp.) through GCâMS and molecular docking by Deepu Mathew, Lidiya John P., Manila T.M., Divyasree P., Sandhya Rajan V.T.K.

“…The molecules identified through docking were further subjected to ADMET analysis and promising drug candidates were identified for each disease. …”
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Chemical Constituents from Uapaca guineensis (Phyllanthaceae), and the Computational Validation of Their Antileishmanial and Anti-inflammatory Potencies by Gervais Mouthé Happi, Mireille Towa Yimtchui, Sikiru Akinyeye Ahmed, Shina Salau, Liliane Clotilde Dzouemo, Klev Gaïtan Sikam, Jean Duplex Wansi

“…Since the plant is widely used for the treatment of skin diseases, leishmaniasis and inflammatory diseases, the antileishmanial and anti-inflammatory potencies of all the isolated compounds have been computationally validated through their ability to inhibit the receptors 1QCC and 2XOX (for the antileishmanial studies) and 6Y3C and 1CX2 (for the anti-inflammatory studies). Furthermore, the ADMET studies of compounds have been done to evaluate their drug-likeness. …”
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Selective mPGES-1 Inhibitor Ameliorated Adjuvant-Induced Arthritis in the Rat Model by Min Ji Kim, Hwi-Ho Lee, Choi Kim, Ja Yeon Lee, Kyung-Sook Chung, Kyung-Tae Lee, Jae Yeol Lee

“…MPO-0144 also exhibited favorable ADMET profiles. However, MPO-0144 did not show any inhibitory effects on human mPGES-1 enzyme at a high concentration. …”
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In Silico Study of Coumarins: Wedelolactone as a Potential Inhibitor of the Spike Protein of the SARS-CoV-2 Variants by Saurav Katuwal, Siddha Raj Upadhyaya, Rishab Marahatha, Asmita Shrestha, Bishnu P. Regmi, Karan Khadayat, Saroj Basnet, Ram Chandra Basnyat, Niranjan Parajuli

“…Physicochemical, QSAR, and pharmacokinetics analyses of the coumarins revealed wedelolactone as the best inhibitor of the spike protein with ideal Lipinski’s drug-likeness and optimal ADMET properties. Furthermore, coarse-grained molecular dynamics (MD) simulation studies of spike protein-wedelolactone complexes validated the stable binding of wedelolactone in the respective binding pockets. …”
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Effect of simulated gastrointestinal digestion on antioxidant, and anti-inflammatory activities of bioactive peptides generated in sausages fermented with Staphylococcus simulans Q... by Hongying Li, Hongbing Fan, Zihan Wang, Qiujin Zhu, Jianping Wu

“…PeptideRanker, BIOPEP-UWM and admetSAR were used to further predict the functional properties and intestinal absorption of the identified peptide sequences from GI digestion. …”
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Discovery of Anti-inflammatory Peptides from Channa argus Using Virtual Screening, Molecular Docking, and Cell Model by XIANG Huan, LU Meiming, CHEN Shengjun, HUANG Hui, HU Xiao, ZHAO Yongqiang, WEI Ya

“…The results showed that 109 bioactive peptides obtained with papain were not toxic, from which 34 highly water-soluble peptides were selected for analysis of adsorption, distribution, metabolism, excretion and toxicity (ADMET) properties. Peptides KF, PR, NC, YR, WEL, QWWR and DEECWF exhibited high-affinity binding to TRL2 and TRL4 mainly through hydrogen bonding. …”
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Infrared illumination for difficult peripheral venous catheterisation in critically ill adult patients: the prospective, randomised, multicentre ICARE trial by Étienne Audureau, Sophie Demeret, Nicolas Mongardon, Damien Contou, Matthieu Schmidt, Muriel Fartoukh, Armand Mekontso Dessap, Daniel Da Silva, Frédérique Schortgen, Rachida Ouedraogo, Aline Alves, Amélie Bruant, Oumar Sy, Cécilia Tabra Osorio, Amélie Chenal, Laurence Krzyzaniak, Marianne Le Joncour, Latifa Ait Benaissa, Meriem Bouguerra, Stéphanie Tanguy Dubois, Eric Starczala, Chirine Petyt, Séverine Dezellus, Jean Francois Georger, Ann-Cécile Pallud, Damien Carras, Fabien Boussely

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Dense Nursery Stock Detecting and Counting Based on UAV Aerial Images and Improved LSC-CNN by PENG Xiaodan, CHEN Fengjun, ZHU Xueyan, CAI Jiawei, GU Mengmeng

“…The ablation experiment proved that the improved LSC-CNN model could effectively resolve the issues of missed detections and false positives in the LSC-CNN model, which were caused by the density and large-scale variations present in the nursery stock dataset. IntegrateNet, PSGCNet, CANet, CSRNet, CLTR and LSC-CNN models were chosen as comparative models. …”
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Large-scale Cosmic-ray Anisotropies with 19 yr of Data from the Pierre Auger Observatory by A. Abdul Halim, P. Abreu, M. Aglietta, I. Allekotte, K. Almeida Cheminant, A. Almela, R. Aloisio, J. Alvarez-Muñiz, A. Ambrosone, J. Ammerman Yebra, G. A. Anastasi, L. Anchordoqui, B. Andrada, L. Andrade Dourado, S. Andringa, L. Apollonio, C. Aramo, P. R. Araújo Ferreira, E. Arnone, J. C. Arteaga Velázquez, P. Assis, G. Avila, E. Avocone, A. Bakalova, F. Barbato, A. Bartz Mocellin, J. A. Bellido, C. Berat, M. E. Bertaina, G. Bhatta, M. Bianciotto, P. L. Biermann, V. Binet, K. Bismark, T. Bister, J. Biteau, J. Blazek, C. Bleve, J. Blümer, M. Boháčová, D. Boncioli, C. Bonifazi, L. Bonneau Arbeletche, N. Borodai, J. Brack, P. G. Brichetto Orchera, F. L. Briechle, A. Bueno, S. Buitink, M. Buscemi, M. Büsken, A. Bwembya, K. S. Caballero-Mora, S. Cabana-Freire, L. Caccianiga, F. Campuzano, R. Caruso, A. Castellina, F. Catalani, G. Cataldi, L. Cazon, M. Cerda, B. Čermáková, A. Cermenati, J. A. Chinellato, J. Chudoba, L. Chytka, R. W. Clay, A. C. Cobos Cerutti, R. Colalillo, R. Conceição, A. Condorelli, G. Consolati, M. Conte, F. Convenga, D. Correia dos Santos, P. J. Costa, C. E. Covault, M. Cristinziani, C. S. Cruz Sanchez, S. Dasso, K. Daumiller, B. R. Dawson, R. M. de Almeida, B. de Errico, J. de Jesús, S. J. de Jong, J. R. T. de Mello Neto, I. De Mitri, J. de Oliveira, D. de Oliveira Franco, F. de Palma, V. de Souza, E. De Vito, A. Del Popolo, O. Deligny, N. Denner, L. Deval, A. di Matteo, C. Dobrigkeit, J. C. D’Olivo, L. M. Domingues Mendes, Q. Dorosti, J. C. dos Anjos, R. C. dos Anjos, J. Ebr, F. Ellwanger, M. Emam, R. Engel, I. Epicoco, M. Erdmann, A. Etchegoyen, C. Evoli, H. Falcke, G. Farrar, A. C. Fauth, T. Fehler, F. Feldbusch, A. Fernandes, B. Fick, J. M. Figueira, P. Filip, A. Filipčič, T. Fitoussi, B. Flaggs, T. Fodran, M. Freitas, T. Fujii, A. Fuster, C. Galea, B. García, C. Gaudu, P. L. Ghia, U. Giaccari, F. Gobbi, F. Gollan, G. Golup, M. Gómez Berisso, P. F. Gómez Vitale, J. P. Gongora, J. M. González, N. González, D. Góra, A. Gorgi, M. Gottowik, F. Guarino, G. P. Guedes, E. Guido, L. Gülzow, S. Hahn, P. Hamal, M. R. Hampel, P. Hansen, V. M. Harvey, A. Haungs, T. Hebbeker, C. Hojvat, J. R. Hörandel, P. Horvath, M. Hrabovský, T. Huege, A. Insolia, P. G. Isar, P. Janecek, V. Jilek, J. Jurysek, K.-H. Kampert, B. Keilhauer, A. Khakurdikar, V. V. Kizakke Covilakam, H. O. Klages, M. Kleifges, F. Knapp, J. Köhler, F. Krieger, M. Kubatova, N. Kunka, B. L. Lago, N. Langner, M. A. Leigui de Oliveira, Y. Lema-Capeans, A. Letessier-Selvon, I. Lhenry-Yvon, L. Lopes, J. P. Lundquist, A. Machado Payeras, D. Mandat, B. C. Manning, P. Mantsch, F. M. Mariani, A. G. Mariazzi, I. C. Mariş, G. Marsella, D. Martello, S. Martinelli, O. Martínez Bravo, M. A. Martins, H.-J. Mathes, J. Matthews, G. Matthiae, E. Mayotte, S. Mayotte, P. O. Mazur, G. Medina-Tanco, J. Meinert, D. Melo, A. Menshikov, C. Merx, S. Michal, M. I. Micheletti, L. Miramonti, S. Mollerach, F. Montanet, L. Morejon, K. Mulrey, R. Mussa, W. M. Namasaka, S. Negi, L. Nellen, K. Nguyen, G. Nicora, M. Niechciol, D. Nitz, D. Nosek, V. Novotny, L. Nožka, A. Nucita, L. A. Núñez, C. Oliveira, M. Palatka, J. Pallotta, S. Panja, G. Parente, T. Paulsen, J. Pawlowsky, M. Pech, J. Pȩkala, R. Pelayo, V. Pelgrims, L. A. S. Pereira, E. E. Pereira Martins, C. Pérez Bertolli, L. Perrone, S. Petrera, C. Petrucci, T. Pierog, M. Pimenta, M. Platino, B. Pont, M. Pothast, M. Pourmohammad Shahvar, P. Privitera, M. Prouza, S. Querchfeld, J. Rautenberg, D. Ravignani, J. V. Reginatto Akim, A. Reuzki, J. Ridky, F. Riehn, M. Risse, V. Rizi, E. Rodriguez, J. Rodriguez Rojo, M. J. Roncoroni, S. Rossoni, M. Roth, E. Roulet, A. C. Rovero, A. Saftoiu, M. Saharan, F. Salamida, H. Salazar, G. Salina, P. Sampathkumar, J. D. Sanabria Gomez, F. Sánchez, E. M. Santos, E. Santos, F. Sarazin, R. Sarmento, R. Sato, C. M. Schäfer, V. Scherini, H. Schieler, M. Schimassek, M. Schimp, D. Schmidt, O. Scholten, H. Schoorlemmer, P. Schovánek, F. G. Schröder, J. Schulte, T. Schulz, S. J. Sciutto, M. Scornavacche, A. Sedoski, A. Segreto, S. Sehgal, S. U. Shivashankara, G. Sigl, K. Simkova, F. Simon, R. Šmída, P. Sommers, R. Squartini, M. Stadelmaier, S. Stanič, J. Stasielak, P. Stassi, S. Strähnz, M. Straub, T. Suomijärvi, A. D. Supanitsky, Z. Svozilikova, Z. Szadkowski, F. Tairli, A. Tapia, C. Taricco, C. Timmermans, O. Tkachenko, P. Tobiska, C. J. Todero Peixoto, B. Tomé, Z. Torrès, A. Travaini, P. Travnicek, M. Tueros, M. Unger, R. Uzeiroska, L. Vaclavek, M. Vacula, J. F. Valdés Galicia, L. Valore, E. Varela, V. Vašíčková, A. Vásquez-Ramírez, D. Veberič, I. D. Vergara Quispe, V. Verzi, J. Vicha, J. Vink, S. Vorobiov, C. Watanabe, A. A. Watson, A. Weindl, M. Weitz, L. Wiencke, H. Wilczyński, D. Wittkowski, B. Wundheiler, B. Yue, A. Yushkov, O. Zapparrata, E. Zas, D. Zavrtanik, M. Zavrtanik, The Pierre Auger Collaboration

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Exploring target selectivity in designing and identifying PI3Kα inhibitors for triple negative breast cancer with fragment-based and bioisosteric replacement approach by Debojyoti Halder, Shreya Mukherjee, R. S. Jeyaprakash

“…The top two bioisosteres of Djh1 – Compound 10, Compound 06 represented excellent efficacy and selectivity towards PI3Kα in the treatment of TNBC after analysis of ADMET analysis. Further, in vitro and in vivo analysis might prove the effectiveness of the hit compounds.…”
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