MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis

According to the World Health Organization, the number of mental disorder patients, especially depression patients, has grown rapidly and become a leading contributor to the global burden of disease. However, the present common practice of depression diagnosis is based on interviews and clinical scales carried out by doctors, which is not only labor-consuming but also time-consuming. One important reason is due to the lack of physiological indicators for mental disorders. With the rising of tools such as data mining and artificial intelligence, using physiological data to explore new possible physiological indicators of mental disorder and creating new applications for mental disorder diagnosis has become a new research hot topic. However, good quality physiological data for mental disorder patients are hard to acquire. We present a multi-modal open dataset for mental-disorder analysis. The dataset includes EEG and audio data from clinically depressed patients and matching normal controls. All our patients were carefully diagnosed and selected by professional psychiatrists in hospitals. The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications. The 128-electrodes EEG signals of 53 subjects were recorded as both in resting state and under stimulation; the 3-electrode EEG signals of 55 subjects were recorded in resting state; the audio data of 52 subjects were recorded during interviewing, reading, and picture description. We encourage other researchers in the field to use it for testing their methods of mental-disorder analysis

Comparative Investigation of the Undercooling Capacity and Single-Crystal Castability of Some Ni-Based Superalloys

The undercooling capacity of a superalloy is an essential physical property to determine its single-crystal (SC) castability, because stray grains (SGs) will be formed if the geometrical undercooling established at the platform extremities exceeds the undercooling capacity of the applied alloy. In the present work, both the undercooling capacity of eight Ni-based superalloys and their SC castability were experimentally investigated. The liquidus temperature, the critical temperature for grain nucleation, and hence the undercooling capacities of the investigated alloys were evaluated based on the temperature evolution during the heating and cooling processes. The current experimental study revealed a significant difference in undercooling capacity for the superalloys. In the production of SC blade castings, the tendency to form SG defects was found to be highly related to the alloy’s undercooling capacity. The alloys having a low undercooling capacity of around 10 K were very prone to the formation of SGs. In comparison, the alloys with a moderate undercooling capacity from 20 K to 30 K could be easily cast into SC blades without SGs, exhibiting the best SC castability. Other factors influencing the SG formation were also analyzed. As a result, a criterion for the formation of geometry-related SG defects was proposed, in which the influence of the alloy undercooling capacity, casting geometry, and solidification condition are involved

Integrated Aerodynamic/Electrochemical Microsystem for Collection and Detection of Nanogram-level Airborne Bioaccessible Metals

The soluble fraction of aerosol particulate matter containing trace metals has the potential to engender toxicity and exacerbate the adverse health effects of particulate matter. In this study, an inertial-impaction-based fluidic chip integrated with electrochemical detection was developed to achieve high collection efficiency and measurements of the bioaccessible metal fraction at the nanogram level. The average collection efficiency for ultrafine and fine particles larger than 50 nm, obtained at a flow rate of 2.5 L/min, was above 70%. The detection ranges of aerosol soluble copper depended on the collection duration and airflow rate. At a working flow rate of 3.1 L/min and collection efficiency of 70%, the microsystem was capable of detecting Cu concentrations above 53 ng/m3, 32 ng/m3 and 8 ng/m3 with 3 h, 5 h and 20 h collection periods, respectively, which were in the range of reported atmospheric concentrations. The detection ratio of real-world samples (i.e. PM10-like aerosol) was 100 ± 14%, indicating excellent aerodynamic collection and reliable electrochemical detection. The collection and sensing performance of the microsystem demonstrates a new step towards an online, mobile, low-cost, and miniaturized routine monitoring system for bioaccessible metals and possibly other soluble components in the aerosols

Self-supporting smart air filters based on PZT/PVDF electrospun nanofiber composite membrane

Smart air filters are beneficial to provide highly efficient particle removal, treat multiple contaminants simultaneously and conserve energy during air filtration processes. Herein, a type of self-supporting smart air filter (SSSAF) was fabricated by sandwiching the VOC-responsive PZT/PVDF electrospun membrane with two metal mesh electrodes. Besides the high filtration efficiency for sub-micron particles, the SSSAF showed good responses to pressure drop in the range of 0 to 500 Pa via the electroactivity of PZT/PVDF membrane. In addition, the SSSAF achieved VOC sensing function via the swelling properties of PZT/PVDF membrane in organic vapors, demonstrated by its signal to 50 to 200 ppm ethanol vapors. The SSSAF was employed to harvest wind energy, which was further applied to inhibit bacterial growth without the need of additional power input. Our SSSAF was designed to take advantage of the energy carried by the filtration air flow, which is necessary in any filtration system thus brings a stable and innate energy source. The results provide new insight into development of all-in-one smart air filters.ISSN:0300-9467ISSN:1385-8947ISSN:1873-3212ISSN:0923-046

Integrated aerodynamic/electrochemical microsystem for collection and detection of nanogram-level airborne bioaccessible metals

The soluble fraction of aerosol particulate matter containing trace metals has the potential to engender toxicity and exacerbate the adverse health effects of particulate matter. In this study, an inertial-impaction-based fluidic chip integrated with electrochemical detection was developed to achieve high collection efficiency and measurements of the bioaccessible metal fraction at the nanogram level. The average collection efficiency for ultrafine and fine particles larger than 50 nm, obtained at a flow rate of 2.5 L/min, was above 70%. The detection ranges of aerosol soluble copper depended on the collection duration and airflow rate. At a working flow rate of 3.1 L/min and collection efficiency of 70%, the microsystem was capable of detecting Cu concentrations above 53 ng/m3, 32 ng/m3 and 8 ng/m3 with 3 h, 5 h and 20 h collection periods, respectively, which were in the range of reported atmospheric concentrations. The detection ratio of real-world samples (i.e. PM10-like aerosol) was 100 ± 14%, indicating excellent aerodynamic collection and reliable electrochemical detection. The collection and sensing performance of the microsystem demonstrates a new step towards an online, mobile, low-cost, and miniaturized routine monitoring system for bioaccessible metals and possibly other soluble components in the aerosols.ISSN:0925-400

Aerosol-into-liquid capture and detection of atmospheric soluble metals across the gas–liquid interface using Janus-membrane electrodes

The soluble fraction of atmospheric transition metals is particularly associated with health effects such as reactive oxygen species compared to total metals. However, direct measurements of the soluble fraction are restricted to sampling and detection units in sequence burdened with a compromise between time resolution and system bulkiness. Here, we propose the concept of aerosol-into-liquid capture and detection, which allowed one-step particle capture and detection via the Janus-membrane electrode at the gas–liquid interface, enabling active enrichment and enhanced mass transport of metal ions. The integrated aerodynamic/electrochemical system was capable of capturing airborne particles with a cutoff size down to 50 nm and detecting Pb(II) with a limit of detection of 95.7 ng. The proposed concept can pave the way for cost-effective and miniaturized systems, for the capture and detection of airborne soluble metals in air quality monitoring, especially for abrupt air pollution events with high airborne metal concentrations (e.g., wildfires and fireworks).ISSN:0027-8424ISSN:1091-649

Any Long-term Effect of the Beirut Port Explosion on the Airborne Particulate Matter?

The Beirut port explosion in 2020 released a huge amount of chemicals including ammonium nitrate, however, the long-term effects of the explosion on air quality and public health remain unclear. In this study, particulate matter (PM10) samples were collected in Beirut, Lebanon 1 month and 3 months after the explosion. The average concentrations of main anions measured in 2020 (one and three months after the explosion) were compared with those in 2009-2015 by calculating the percentage of difference, and the average concentrations of cations and anions in September (one month after the explosion) and November (three months after the explosion) 2020 were also compared to identify any abnormal values, indicating insignificant effects on the post-explosion PM in terms of component concentrations. That is, PM and gases directly induced by the explosion might be subject to rapid atmospheric transport and deposition. Hence, the results imply that investigations of the chemical contaminations in soil and water are urgently needed. Long-term monitoring is necessary to avoid subsequent air pollution caused by possible particle resuspension. The continuous demolition and reconstruction after the explosion are possibly the main long-term effect of the Beirut port explosion, causing an elevated concentration of PM2.5 at ground level 400% higher than the recommended concentrations (15 mu g m-3 for 24-hour mean). Protective measures must be taken to reduce the exposure risks by controlling the PM release from demolition and construction, traffic, and diesel generators. The cancer risk in Beirut based on PAHs measurements in 2021 was also estimated and discussed.ISSN:1680-8584ISSN:2071-140