Flood Forecasting for Small Reservoirs Based on Neural Networks by PENG Wei, XIONG Jiayi, JIANG Xianqun, GAO Yueming

“…In flood forecasting,empirical prediction methods report low accuracy,and traditional hydrological models face the problems of large workloads and difficult promotion when they are applied to small reservoirs.Hence,an artificial neural network (ANN) method is introduced,which is equipped with powerful feature-learning capability.It is combined with the genetic algorithm (GA) to find the optimal parameters for flood forecasting of small reservoirs as GA can realize automatic optimization of the time step and hidden-layer neuron nodes in ANN.In this way,parameter search can be targeted,and personalized flood forecasting models can be constructed for each small reservoir.In addition,the flood forecasting models based on the back propagation (BP),long short-term memory (LSTM),and gated recurrent unit (GRU) neural networks are built,and comparisons between simulations and measured data are conducted for the flood process.The results show that the LSTM model has high prediction accuracy and good stability and can learn and simulate the water-level change pattern of the actual flood process,demonstrating better prediction performance than BP and GRU models.…”
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Emergency Nursing Didactics – Opinions, Resource, and Skill Exchange (E.N.D.O.R.S.E) – A collaborative academic initiative in the Emergency Department by Mohammad Anzal Rehman, Elrasheed Salih, Honey Mathew, Ramna Abdulrahman, Ahmad Chahla, Rishi Prasad

“…Post-session questionnaires revealed that 92.3% of participants found the sessions provided them with new information, with approximately 88% of them ‘Very confident' (5/5) in using the skills taught thereafter. 77% of participants rated the quality of the sessions as ‘Excellent' (5/5), and 88% indicated they would like for the topics to be repeated in future sessions. …”
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OSTEOARTICULAR INJURY IN PSORIATIC PATIENTS ACCORDING TO THE DATA OF PEST (PSORIASIS EPIDEMIOLOGY SCREENING TOOL) QUESTIONNAIRE AND RHEUMATOLOGICAL CLINICOINSTRUMENTAL EXAMINATION by M. N. Chamurlieva, E. Yu. Loginova, T. V. Korotaeva, E. A. Batkaev

“…Answers to 6 questions about nail psoriasis in the PEST questionnaire were rated; each positive answer corresponded to 1; PEST ≥3 or <3 is indicative of the presence or absence of psoriasis, respectively. …”
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Duration of the hypotensive effect of modified transscleral cyclophotocoagulation in patients with diabetic neovascular glaucoma by O. V. Guzun, O. S. Zadorozhnyy, I. O. Nasinnyk, Wael Chargui, A. R. Korol

“…The independent variables with the largest impact on the need for repeat TSCPC in diabetic patients with NVG were the baseline pain numeric rating scale score ≥ 8 (odds ratio (OR), 4.0; 95% confidence interval (CI), 1.84-8.91), presence of ocular complications (OR, 3.02; 95% CI, 1.84-8.91), diabetes duration ≥7 years (OR, 2.03; 95% CI, 1.46-2.28) and IOP ≥35 mmHg (OR, 1.16; 95% CI, 1.4-3.3).…”
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Re-composing Physical Form with Energy-Based Resilience Approach to Improve Thermal Comfort (Case Study: Sadra New Town) by Sahar Akbari, Mahsa Sholeh, Sahand Lotfi

“…In the first step, energy resilience criteria based on global energy resilience rating systems and theoretical research conducted, including smart location, resources and energy, transportation and use, neighborhood form and development pattern, and placemaking, were identified as five layers. …”
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Brain Effective Connectivity Analysis Facilitates the Treatment Outcome Expectation of Sound Therapy in Patients With Tinnitus by Han Lv, Jinduo Liu, Qian Chen, Zuozhen Zhang, Zhaodi Wang, Shusheng Gong, Junzhong Ji, Zhenchang Wang

“…We hypothesized that the pattern of directional functional connectivity can provide key information on treatment outcomes. …”
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Time-Series Forecasting Method Based on Hierarchical Spatio-Temporal Attention Mechanism by Zhiguo Xiao, Junli Liu, Xinyao Cao, Ke Wang, Dongni Li, Qian Liu

“…Breaking through traditional structural designs, the model employs a Squeeze-and-Excitation Network (SENet) to reconstruct the convolutional layers of the Temporal Convolutional Network (TCN), strengthening the feature expression of key time steps through dynamic channel weight allocation to address the redundancy issue of traditional causal convolutions in local pattern capture. A Bidirectional Gated Recurrent Unit (BiGRU) variant based on a global attention mechanism is designed, leveraging the collaboration between gating units and attention weights to mine cross-period long-distance dependencies and effectively alleviate the gradient disappearance problem of Recurrent Neural Network (RNN-like) models in multi-scale time-series analysis. …”
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Spectrogram-Based Arrhythmia Classification Using Three-Channel Deep Learning Model with Feature Fusion by Alaa Eleyan, Fatih Bayram, Gülden Eleyan

“…To enhance performance, the extracted features are concatenated before feeding them into a gated recurrent unit (GRU) model. The proposed approach is extensively evaluated on two ECG datasets (MIT-BIH + BIDMC and MIT-BIH) with three and five classes, respectively. …”
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Pain in women with and without bipolar spectrum disorder by Amanda L. Stuart, Michael Berk, Michael Berk, Michael Berk, Michael Berk, Julie A. Pasco, Julie A. Pasco, Julie A. Pasco, Julie A. Pasco, Mohammadreza Mohebbi, Shae E. Quirk, Lana J. Williams, Lana J. Williams

“…Pain during the past week was determined by numeric rating scale (0–10, 10 = pain as severe as I can imagine) and deemed present if ≥5. …”
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Long-term effects of orthognathic surgery on masticatory function in individuals with cleft lip and palate: A prospective study by Patricia Martins Bueno, Paulo Alceu Kiemle Trindade, Laís Hollara Medeiros, Leide Vilma Fidélis da Silva, Ivy Kiemle Trindade-Suedam

“…Three variables were evaluated: 1) Bite Force (BF) (measured in Newtons – N) presented as the average of the bite force from the right and left molars (x‾ RM + LM), using a gnathodynamometer (IDDK Kratos), 2) Masticatory Efficiency (ME) (ranging from 0 to 1, with values closer to 1 indicating poorer efficiency), assessed through a dual-color masticatory gum test analyzed visually and optoelectronically (ViewGum©), and 3) Masticatory Capacity (MC): patient-reported ability to chew, rated on a two-point scale (P/R = poor to reasonable, G/O = good to optimal). …”
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Two‐Terminal MoS2‐Based Retinomorphic Devices with Enhanced Synaptic Plasticity by Younghoon Lim, Taehun Kim, Jaesik Eom, Onsik Harm, Junsung Byeon, Jungmoon Lim, Juwon Lee, Sangyeon Pak, SeungNam Cha

“…Herein, the two‐terminal retinomorphic devices are reported featuring a tailored gating voltage range near zero and enhanced synaptic plasticity by providing another recombination route to suppress the PPC effect. …”
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Spintronic Memtransistor Leaky Integrate and Fire Neuron for Spiking Neural Networks by Aijaz H. Lone, Meng Tang, Daniel N. Rahimi, Xuecui Zou, Dongxing Zheng, Hossein Fariborzi, Xixiang Zhang, Gianluca Setti

“…Based on the ferromagnetic multilayer spintronic devices, a magnetic field‐gated and current‐controlled spintronic Leaky Integrate‐and‐Fire (LIF) neuron with memtransistor properties is showcased. …”
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Ion Channels in Hematopoietic and Mesenchymal Stem Cells by Serena Pillozzi, Andrea Becchetti

“…These channels can also regulate leukemia cell interaction with MSCs, which also involves integrin receptors and affects the MSC-mediated protection from chemotherapy. Ligand-gated channels are also implicated in these processes. …”
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Landau–Kleffner Syndrome Can Herald the Diagnosis of GRIN2A Gene Mutation by Ayman Khalil Ebrahim, Jaafar Jawad Makhlooq, Maryam Yusuf Busehail

“…N-methyl-D-aspartate receptors (NMDARs) are glutamate-gated channels that are essential for synaptic transmission and plasticity in the central nervous system. …”
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Dynamic interplay of hierarchical rank and social contexts in shaping perceived fairness by Yaner Su, Ying Zeng, Andre Aleman, Sander Martens, Pengfei Xu, Yue-jia Luo, Katharina S. Goerlich

“…Experiment 1 showed that participants accepted more offers from superior than inferior proposers and rated them as fairer. Reaction times were longer for sub-fair offers, and for fair offers made by inferior players. …”
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Association of white matter hyperintensity burden and infarct volume in the anterior choroidal artery territory with early neurological progression: a dual-center retrospective stu... by Weiwei Gao, Weiwei Gao, Lixue Wang, Junyi Huang, Yitao Yu, Jingjing She, Jingjing She, Jingjing She, Mingyang Wang, Lijuan Cai, Lijuan Cai, Taishan Kang, Xingyu Chen, Xingyu Chen, Jianzhong Lin, Renjing Zhu, Renjing Zhu, Renjing Zhu

“…WMH burden and infarct volume were assessed using the Fazekas visual rating scale and an automated volumetric quantification method based on lesion prediction algorithm, respectively. …”
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Versatile optoelectronic memristor based on wide-bandgap Ga2O3 for artificial synapses and neuromorphic computing by Dongsheng Cui, Mengjiao Pei, Zhenhua Lin, Hong Zhang, Mengyang Kang, Yifei Wang, Xiangxiang Gao, Jie Su, Jinshui Miao, Yun Li, Jincheng Zhang, Yue Hao, Jingjing Chang

“…The “AND” and “OR” logic gates in memristor-aided logic (MAGIC) are implemented by utilizing voltage polarity and UV light as input signals. …”
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Semantic Patent Classification Using Stack Generalization of Deep Models by Shahla Nemati

“…To solve this issue, we have introduced a deep ensemble model for semantic paragraph-level pattern classification based on the semantic content of patents. …”
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Conv1D-LSTM: Autonomous Breast Cancer Detection Using a One-Dimensional Convolutional Neural Network With Long Short-Term Memory by Mitanshi Rastogi, Meenu Vijarania, Neha Goel, Akshat Agrawal, Cresantus N. Biamba, Celestine Iwendi

“…The developed hybrid model outperforms various other state-of-the-art techniques like ANN, CNN, CNN-Bi-LSTM-GRU-AM (Convolutional Neural Network-Bidirectional Long Short-Term Memory-Gated Recurrent Unit-Attention Mechanism), and CNN-GRU (Convolutional Neural Network- Gated Recurrent Unit) in terms of accuracy, feature extraction and computational time. …”
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A novel deep learning-based 1D-CNN-optimized GRU approach for heart disease prediction by Jini Mol G., Ajith Bosco Raj T.

“…To identify the irregularities in the cardiac data pattern, a gated recurrent unit (GRU) classifier and a one-dimensional convolutional neural network (1D-CNN) are introduced. …”
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