Research on a New Intelligent and Rapid Screening Method for Depression Risk in Young People Based on Eye Tracking Technology.

Depression is a prevalent mental disorder, with young people being particularly vulnerable to it. Therefore, we propose a new intelligent and rapid screening method for depression risk in young people based on eye tracking technology. We hypothesized that the "emotional perception of eye movement" could characterize defects in emotional perception, recognition, processing, and regulation in young people at high risk for depression. Based on this hypothesis, we designed the "eye movement emotional perception evaluation paradigm" and extracted digital biomarkers that could objectively and accurately evaluate "facial feature perception" and "facial emotional perception" characteristics of young people at high risk of depression. Using stepwise regression analysis, we identified seven digital biomarkers that could characterize emotional perception, recognition, processing, and regulation deficiencies in young people at high risk for depression. The combined effectiveness of an early warning can reach 0.974. Our proposed technique for rapid screening has significant advantages, including high speed, high early warning efficiency, low cost, and high intelligence. This new method provides a new approach to help effectively screen high-risk individuals for depression.

A new early warning method for mild cognitive impairment due to Alzheimer's disease based on dynamic evaluation of the "spatial executive process".

Objective: Mild cognitive impairment (MCI) due to Alzheimer's disease (AD), as an early stage of AD, is an important point for early warning of AD. Neuropathological studies have shown that AD pathology in pre-dementia patients involves the hippocampus and caudate nucleus, which are responsible for controlling cognitive mechanisms such as the spatial executive process (SEP). The aim of this study is to design a new method for early warning of MCI due to AD by dynamically evaluating SEP. Methods: We designed fingertip interaction handwriting digital evaluation paradigms and analyzed the dynamic trajectory of fingertip interaction and image data during "clock drawing" and "repetitive writing" tasks. Extracted fingertip interaction digital biomarkers were used to assess participants' SEP disorders, ultimately enabling intelligent diagnosis of MCI due to AD. A cross-sectional study demonstrated the predictive performance of this new method. Results: We enrolled 30 normal cognitive (NC) elderly and 30 MCI due to AD patients, and clinical research results showed that there may be neurobehavioral differences between the two groups in digital biomarkers captured during SEP. The early warning performance for MCI due to AD of this new method (areas under the curve (AUC) = 0.880) is better than that of the Minimum Mental State Examination (MMSE) neuropsychological scale (AUC = 0.856) assessed by physicians. Conclusion: Patients with MCI due to AD may have SEP disorders, and this new method based on dynamic evaluation of SEP will provide a novel human-computer interaction and intelligent early warning method for home and community screening of MCI due to AD.

A New Smart 2-Min Mobile Alerting Method for Mild Cognitive Impairment Due to Alzheimer's Disease in the Community.

The early identification of mild cognitive impairment (MCI) due to Alzheimer's disease (AD), in an early stage of AD can expand the AD warning window. We propose a new capability index evaluating the spatial execution process (SEP), which can dynamically evaluate the execution process in the space navigation task. The hypothesis is proposed that there are neurobehavioral differences between normal cognitive (NC) elderly and AD patients with MCI reflected in digital biomarkers captured during SEP. According to this, we designed a new smart 2-min mobile alerting method for MCI due to AD, for community screening. Two digital biomarkers, total mission execution distance (METRtotal) and execution distance above the transverse obstacle (EDabove), were selected by step-up regression analysis. For the participants with more than 9 years of education, the alerting efficiency of the combination of the two digital biomarkers for MCI due to AD could reach 0.83. This method has the advantages of fast speed, high alerting efficiency, low cost and high intelligence and thus has a high application value for community screening in developing countries. It also provides a new intelligent alerting approach based on the human-computer interaction (HCI) paradigm for MCI due to AD in community screening.

Exploratory Research on Key Technology of Human-Computer Interactive 2.5-Minute Fast Digital Early Warning for Mild Cognitive Impairment.

Objective: As the preclinical stage of Alzheimer's disease (AD), Mild Cognitive Impairment (MCI) is characterized by hidden onset, which is difficult to detect early. Traditional neuropsychological scales are main tools used for assessing MCI. However, due to its strong subjectivity and the influence of many factors such as subjects' educational background, language and hearing ability, and time cost, its accuracy as the standard of early screening is low. Therefore, the purpose of this paper is to propose a new key technology of fast digital early warning for MCI based on eye movement objective data analysis. Methodology. Firstly, four exploratory indexes (test durations, correlation degree, lengths of gaze trajectory, and drift rate) of MCI early warning are determined based on the relevant literature research and semistructured expert interview; secondly, the eye movement state is captured based on the eye tracker to realize the data extraction of four exploratory indexes. On this basis, the human-computer interactive 2.5-minute fast digital early warning paradigm for MCI is designed; thirdly, the rationality of the four early warning indexes proposed in this paper and their early warning effectiveness on MCI are verified. Results: Through the small sample test of human-computer interactive 2.5 fast digital early warning paradigm for MCI conducted by 32 elderly people aged 70-90 in a medical institution in Hangzhou, the two indexes of "correlation degree" and "drift rate" with statistical differences are selected. The experiment results show that AUC of this MCI early warning paradigm is 0.824. Conclusion: The key technology of human-computer interactive 2.5 fast digital early warning for MCI proposed in this paper overcomes the limitations of the existing MCI early warning tools, such as low objectification level, high dependence on professional doctors, long test time, requiring high educational level, and so on. The experiment results show that the early warning technology, as a new generation of objective and effective digital early warning tool, can realize 2.5-minute fast and high-precision preliminary screening and early warning for MCI in the elderly.

Immobilization persistence of Cu, Cr, Pb, Zn ions by the addition of steel slag in acidic contaminated mine soil.

Adding steel slag to the acidic contaminated mine soil can immobilize heavy metal ions, but immobilization persistence of the metal ions needs to be determined. In this study, dynamic column simulation experiments were set up to compare the immobilization persistence of Cu, Cr, Pb and Zn ions in original soil and with the addition of slag, lime or fly ash to the soil during a simulated 36-month of acid rain leaching. After adding slag and lime, the pH, organic matter content and cation exchange capacity of soil were significantly increased. Compared with the original soil, additions of slag and lime to the soil were able to persistently immobilize the metal ions, whereas fly ash additions had little effect. During simulation, the metal ion concentrations in the slag group leaching solution were essentially consistent with Standard IV for groundwater. The metal ions were immobilized to form instable hydroxides and stable fractions following adding slag to soil. The hydroxide could rerelease metal ions by acid rain leaching, part of which were re-immobilized into stable fractions by entering slag lattice and complexing with soil organic matter. Therefore, adding slag to soil can persistently immobilize metal ions for heavy metal-contaminated acidic mine soil.

Influence of ferrous-metal production on mercury contamination and fractionation in farmland soil around five typical iron and steel enterprises of Tangshan, China.

Iron and steel production is one of the main anthropogenic sources of mercury (Hg) emission and release. Oxidized and particulate Hg discharged from iron and steel enterprises deposit into the surrounding soil, which accumulate and introduce environmental risks. Therefore, it is important to assess Hg pollution in the soil surrounding iron and steel enterprises. In this study, the Hg pollution, Hg distribution from steel plants and Hg fractionation in farmland soil around five typical steel plants were analysed in Tangshan of China. The Hg pollution indexes (Pi) of more than 90% soil samples were greater than 3 by the single factor pollution index method, which showed that most soil samples around the five steel plants were strongly contaminated by Hg. The Hg contents in soil increased first and then decreased, and the maximum content presented at 250-300 m away from the boundary of the steel plants. The order of Hg fraction proportion in the soil samples was extractable (35%-43%) > volatile (24%-36%) > residual (10%-26%) > reducible (0-15%) > oxidizable (0-12%). The distribution of Hg fraction in farmland soil had no regular trend with the distance from the steel plants. The volatile Hg and extractable Hg were dominant in farmland soil, and their combined proportion was greater than 60%. These two fractions of Hg are at risk of re-volatilization into the atmosphere or potential absorption by plants.