Optical next generation reservoir computing by Hao Wang, Jianqi Hu, YoonSeok Baek, Kohei Tsuchiyama, Malo Joly, Qiang Liu, Sylvain Gigan

“…Optical NGRC shows superiority in shorter training length and fewer hyperparameters compared to conventional optical RC based on scattering media, while achieving better forecasting performance. …”
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Mathematical model for prediction of Tuberculosis in Nigeria using hybrid fractional differential equations and artificial neural network methods by Samson Linus Manu, Shikaa Samuel, Taparki Richard, Eshi Priebe Dovi

“…The data used for the analysis were obtained from the TB report by the World Health Organisation (WHO) TB Data Base, Nigeria Dash Board, from the years 2010–-2020. …”
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Construction of a predictive model for cervical lymph node metastasis in papillary thyroid carcinoma by YanHong Hao, Yuan Su, Yanan Li, Qiaohong Pan, Liping Liu

“…Comprehensive clinical information, serological indices, and ultrasonography features were obtained for every participant. LASSO (Least Absolute Shrinkage and Selection Operator) and BSR (Best Subset Regression) to select features for model construction. …”
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MEN: leveraging explainable multimodal encoding network for precision prediction of CYP450 inhibitors by Abena Achiaa Atwereboannah, Wei-Ping Wu, Mugahed A. Al-antari, Sophyani B. Yussif, Chukwuebuka J. Ejiyi, Edwin K. Tenagyei, Grace-Mercure B. Kissanga, Gyarteng S. A. Emmanuel, Yeong Hyeon Gu, Emmanuel Ahene

“…Specifically, the Fingerprint Encoder Network (FEN) processes molecular fingerprints, the Graph Encoder Network (GEN) extracts structural features from graph-based representations, and the Protein Encoder Network (PEN) captures sequential patterns from protein sequences. …”
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Guest Editorial-SOLUTIONS OF CHILDHOOD OBESITY-AND-MALNUTRITION by Syed Arif Kamal

“…This becomes much more important for the sport academies, who like to train and to groom national and international athletes. …”
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Accelerating high-concentration monoclonal antibody development with large-scale viscosity data and ensemble deep learning by Lateefat A. Kalejaye, Jia-Min Chu, I-En Wu, Bismark Amofah, Amber Lee, Mark Hutchinson, Chacko Chakiath, Andrew Dippel, Gilad Kaplan, Melissa Damschroder, Valentin Stanev, Maryam Pouryahya, Mehdi Boroumand, Jenna Caldwell, Alison Hinton, Madison Kreitz, Mitali Shah, Austin Gallegos, Neil Mody, Pin-Kuang Lai

“…We developed DeepViscosity, consisting of 102 ensemble artificial neural network models to classify low-viscosity (≤20 cP) and high-viscosity (>20 cP) mAbs at 150 mg/mL, using 30 features from a sequence-based DeepSP model. Two independent test sets, comprising 16 and 38 mAbs with known experimental viscosity, were used to assess DeepViscosity’s generalizability. …”
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BroilerTrack: Automatic multi-camera multi-broiler tracking by Thinh Phan, Hoang Kim Tran, Andrew Lockett, Isaac Phillips, Hao Vo, Duy Le, Michael T. Kidd, James Mason, Santiago Avendano, Ngan Le

“…Unlike traditional approaches that rely heavily on appearance features, BroilerTrack employs a position-based tracking strategy in a unified coordinate system (unified plane), thereby circumventing identity ambiguity caused by the homogeneous appearance of broilers. …”
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THE IMPACT OF THE AZERBAIJANI LANGUAGE VOCALISM ON BAKU RESIDENTS RUSSIAN PRONUNCIATION: THE BILINGUAL ASPECT by Sanay H. Huseynli

“…The influence of the vowels ə, ö, ü, which are not specific for Russian phonemes, comes through the pronunciation of Azerbaijani words included in the vocabulary of Baku residents (names, household items, geographical names, etc.) in the “Azerbaijani” way, that is, with the preservation phonetic features of these words. 3. Vowel sounds are added based on the law of harmony, which is specific for all Turkic languages (and not only!). …”
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Encouraging Safety 4.0 to enhance industrial culture: An extensive study of its technologies, roles, and challenges by Abid Haleem, Mohd Javaid, Ravi Pratap Singh

“…Managing data-driven safety measures and training employees to use these technologies efficiently can be challenging. …”
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The Optimal Design of an Inclined Porous Plate Wave Absorber Using an Artificial Neural Network Model by Senthil Kumar Natarajan, Seokkyu Cho, Il-Hyoung Cho

“…These features have been optimized to minimize the averaged reflection coefficient and the installation space (spatial footprint) with the application of a trained ANN model. …”
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ZAS-F: A Zero-Shot Abstract Sub-Goal Framework Empowers Robots for Long Horizontal Inventory Tasks by Yongshuai Wu, Jian Zhang, Shaoen Wu, Shiwen Mao, Ying Wang

“…The learned policy extracts abstract features from multimodal and extensive temporal observations and subsequently uses these features to predict task-agnostic sub-goals by reasoning about their latent relations. …”
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Online Education in the Republic of Karelia in the New Realities of Society Development by O. V. Potasheva, A. N. Bykova

“…A study of the results of an online survey of teachers in the Republic of Karelia revealed a number of features and difficulties in the introduction of distance learning technologies for schoolchildren in the new realities of an isolated educational process: the level of proficiency in distance learning technologies at the beginning of the Covid-2019 pandemic among teachers in Karelia was quite high - 68.3%, 72.8% of them had the experience of independent study of forms and technologies of distance learning, 27.9% of the interviewed teachers completed advanced training courses. …”
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Effect of testosterone treatment during puberty in boys with Klinefelter syndrome (The TIPY Study): protocol for a nationwide randomised, double-blinded, placebo-controlled study by Gary Butler, Anders Juul, Judith L Ross, Jørgen Holm Petersen, Kurt Kristensen, Ann-Margrethe Rønholt Christensen, Ida Dyhr Caspersen, Andrés Felipe Østergaard Fritzbøger, Niels Birkebæk, Anders Jørgen Schou, Shanlee Davis, Sophie van Rijn, Lise Aksglaede

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Performance of an AI prediction tool for new-onset atrial fibrillation after coronary artery bypass graftingResearch in context by Hualong Ma, Dalong Chen, Weitao Lv, Qiuying Liao, Jingyi Li, Qinai Zhu, Ying Zhang, Lizhen Deng, Xiaoge Liu, Qinyang Wu, Xianliang Liu, Qiaohong Yang

“…We aimed to develop and validate a novel AI-based bedside tool that accurately predicts predict NOAF after CABG. …”
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Automatic melanoma and non-melanoma skin cancer diagnosis using advanced adaptive fine-tuned convolution neural networks by Muhammad Amir Khan, Tehseen Mazhar, Muhammad Danish Ali, Umar Farooq Khattak, Tariq Shahzad, Mamoon M. Saeed, Habib Hamam

“…To capture high-level, global features specific to skin cancer, we replace the fully connected (FC) layers, responsible for encoding such features, with a new FC layer based on principal component analysis (PCA). …”
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Attention Mechanism and Weighted Trend Loss for Wind Speed Correction by Liu Xu, Yang Hao, Liang Xiaoyun, Chen Jing, Li Qiaoping, Li Ruqing, Chen Min

“…A new weighted trend-based mean squared error loss function is developed to optimize the correction process. …”
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Exploratory development of human–machine interaction strategies for post-stroke upper-limb rehabilitation by Kang Xia, Xue-Dong Chang, Chong-Shuai Liu, Yu-Hang Yan, Han Sun, Yi-Min Wang, Xin-Wei Wang

“…Method An Up-limb Rehabilitation Device and Utility System (UarDus) is proposed along with 3 HMI strategies namely robot-in-charge, therapist-in-charge and patient-in-charge. Based on physiological structure of human upper-limb and scapulohumeral rhythm (SHR) of shoulder, a base exoskeleton with 14 degrees of freedoms (DoFs) is designed as foundation of the 3 strategies. …”
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Machine learning model for predicting tertiary lymphoid structures and treatment response in triple-negative breast cancer by Yidan Lin, Yushuai Yu, Qing Wang, Kaiyan Huang, Shukai Guo, Jie Zhang, Yihui He, Xin Yu, Jiwen Zhang, Fan Meng, Shicong Tang, Junhui Yuan, Chuangui Song

“…This multicenter study retrospectively included 697 patients, including the training cohort (n = 137), the TLS validation cohort (n = 63) and the NAT response validation cohorts (n = 560). …”
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Using deep learning for ultrasound images to diagnose chronic lateral ankle instability with high accuracy by Masamune Kamachi, Kohei Kamada, Noriyuki Kanzaki, Tetsuya Yamamoto, Yuichi Hoshino, Atsuyuki Inui, Yuta Nakanishi, Kyohei Nishida, Kanto Nagai, Takehiko Matsushita, Ryosuke Kuroda

“…Transfer learning was performed using 3 pretraining DL models, and the accuracy, precision, recall (sensitivity), specificity, F-measure, and the area under the receiver operating characteristic curve (AUC) were calculated based on the confusion matrix. The important features were visualized using occlusion sensitivity, a method for visualizing areas that are important for model prediction. …”
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A Comprehensive Review of Remote Sensing Technology for Mass-Flowering Crops Extraction by Qingji Meng, Shuying Zang, Bingxue Zhu, Kaishan Song, Miao Li, Li Sun

“…In the extraction of mass-flowering crops and the observation of their flowering periods, commonly used remote sensing data sources include optical data (Sentinel-2, Landsat 8, Landsat 5, MODIS, etc.) and radar data (Sentinel-1, TerraSAR-X, etc.), and the fusion of multisource data is an effective means to improve the research accuracy in this field. Features such as vegetation indices (notably normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI)), band features, polarization features, and phenological features are essential for analyzing mass-flowering crops. …”
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