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Filename: drivers/Session_files_driver.php
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File: /var/www/html/index.php
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Function: require_once
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Filename: Session/Session.php
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File: /var/www/html/index.php
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Function: require_once
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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler
File: /var/www/html/index.php
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Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
Line: 249
Function: _error_handler
File: /var/www/html/index.php
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Message: Trying to access array offset on value of type null
Filename: controllers/Detail.php
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Function: _error_handler
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Filename: controllers/Detail.php
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Function: _error_handler
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Function: require_once
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Filename: models/Detail_model.php
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File: /var/www/html/application/models/Detail_model.php
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Function: strpos
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Function: insertAPISummary
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Filename: helpers/my_audit_helper.php
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Function: str_replace
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Function: formatAIDetailSummary
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Filename: controllers/Detail.php
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We monitored regional cerebral activity with BOLD fMRI while subjects were presented written sentences differing in their grammatical structure (subject-relative or object-relative center-embedded clauses) and their short-term memory demands (short or long antecedent-gap linkages). A core region of left posterior superior temporal cortex was recruited during all sentence conditions in comparison to a pseudofont baseline, suggesting that this area plays a central role in sustaining comprehension that is common to all sentences. Right posterior superior temporal cortex was recruited during sentences with long compared to short antecedent-gap linkages regardless of grammatical structure, suggesting that this brain region supports passive short-term memory during sentence comprehension. Recruitment of left inferior frontal cortex was most clearly associated with sentences that featured both an object-relative clause and a long antecedent-gap linkage, suggesting that this region supports the cognitive resources required to maintain long-distance syntactic dependencies during the comprehension of grammatically complex sentences.
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http://dx.doi.org/10.1002/hbm.10006 | DOI Listing |
Prosthet Orthot Int
December 2024
School of Intelligent Rehabilitation Engineering, Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China.
Background: Prosthetic socket is a key component of the prosthesis for clinical application; its performance directly affects the adaptation of the residual limb to the prosthetic socket. There are long-term and short-term volume fluctuation of the residual limb. The volume fluctuation of the residual limb will lead to the pressure mismatch at the interface of the residual limb and the prosthetic socket, which will cause a series of skin and fit problems.
View Article and Find Full Text PDFWater Res X
January 2025
Shanghai Institute of Pollution Control and Ecological Security, Shanghai, 200092, China.
Sudden shocking load events featuring significant increases in inflow quantities or concentrations of wastewater treatment plants (WWTPs), are a major threat to the attainment of treated effluents to discharge quality standards. To aid in real-time decision-making for stable WWTP operations, this study developed a probabilistic deep learning model that comprises encoder-decoder long short-term memory (LSTM) networks with added capacity of producing probability predictions, to enhance the robustness of real-time WWTP effluent quality prediction under such events. The developed probabilistic encoder-decoder LSTM (P-ED-LSTM) model was tested in an actual WWTP, where bihourly effluent quality prediction of total nitrogen was performed and compared with classical deep learning models, including LSTM, gated recurrent unit (GRU) and Transformer.
View Article and Find Full Text PDFHeliyon
December 2024
Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Selangor, Malaysia.
The agriculture sector is confronted with numerous challenges in the quest for accurate crop yield estimation, which is essential for efficient resource management and mitigating food scarcity in a rapidly growing global population. This research paper delves into the application of advanced Artificial Intelligence (AI) techniques to enhance crop yield estimation in the context of diverse agricultural challenges. Through a systematic literature review and analysis of relevant studies, this paper explores the role of AI methods, such as Machine Learning (ML) and Deep Learning (DL), in addressing the complexities posed by geographical variations, crop diversity, and cultivation areas.
View Article and Find Full Text PDFBMC Psychol
December 2024
Beijing Infinite Brain Technology Co., Ltd, Beijing, 100022, PR China.
Background: Traditional cognitive assessments, often reliant on paper-and-pencil tests and professional evaluators, suffer from subjectivity and limited result discrimination. This study introduces the Baguan Online Cognitive Assessment System (BOCAS), a tablet-based system that evaluates both general cognitive ability (GCA) and domain-specific functions across six domains: sensory-motor skills, processing speed, sustained attention, working memory, cognitive flexibility, and spatial ability.
Methods: BOCAS was validated with 151 healthy Chinese adults aged 18-40.
Sci Rep
December 2024
Advanced Manufacturing Institute, King Saud University, Riyadh, 11421, Saudi Arabia.
Recently, social demands for a good quality of life have increased among the elderly and disabled people. So, biomedical engineers and robotic researchers aimed to fuse these techniques in a novel rehabilitation system. Moreover, these models utilized the biomedical signals acquired from the human body's particular organ, cells, or tissues.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!