Magnetite particles accelerate methanogenic degradation of highly concentrated acetic acid in anaerobic digestion process.

The anaerobic digestion (AD) process has become significant for its capability to convert organic wastewater into biogas, a valuable energy source. Excessive acetic acid accumulation in the anaerobic digester can inhibit methanogens, ultimately leading to the deterioration of process performance. Herein, the effect of magnetite particles (MP) as an enhancer on the methanogenic degradation of highly-concentrated acetate (6 g COD/L) was examined through long-term sequential AD batch tests. Bioreactors with (AM) and without (AO) MP were compared. AO experienced inhibition and its methane production rate (qm) converged to 0.45 L CH4/g VSS/d after 10 sequential batches (AO10, the 10th batch in a series of the sequential batch tests conducted using bioreactors without MP addition). In contrast, AM achieved 3-425% higher qm through the sequential batches, indicating that MP could counteract the inhibition caused by the highly-concentrated acetate. MP addition to inhibited bioreactors (AO10) successfully restored them, achieving qm of 1.53 L CH4/g VSS/d, 3.4 times increase from AO10 after 8 days lag time, validating its potential as a recovery strategy for inhibited digesters with acetate accumulation. AM exhibited higher microbial populations (1.8-3.8 times) and intracellular activity (9.3 times) compared to AO. MP enriched Methanosaeta, Peptoclostridium, Paraclostridium, OPB41, and genes related to direct interspecies electron transfer and acetate oxidation, potentially driving the improvement of qm through MP-mediated methanogenesis. These findings demonstrated the potential of MP supplementation as an effective strategy to accelerate acetate-utilizing methanogenesis and restore an inhibited anaerobic digester with high acetate accumulation.

Near-Field Communication in Biomedical Applications.

Near-field communication (NFC) is a low-power wireless communication technology used in contemporary daily life. This technology contributes not only to user identification and payment methods, but also to various biomedical fields such as healthcare and disease monitoring. This paper focuses on biomedical applications among the diverse applications of NFC. It addresses the benefits of combining traditional and new sensors (temperature, pressure, electrophysiology, blood flow, sweat, etc.) with NFC technology. Specifically, this report describes how NFC technology, which is simply applied in everyday life, can be combined with sensors to present vision and opportunities to modern people.

Validating attentive locomotion training using interactive treadmill: an fNIRS study.

BACKGROUND: Existing treadmill-based locomotion training, which has been used for gait function recovery, still has limitations, such as less attentive training. Interactive treadmills (ITMs) were developed to overcome these limitations, but it has not yet been verified that ITMs can make the user pay closer attention to walk training. METHODS: An experimental comparison between ITMs and conventional treadmills was conducted by measuring the level of the user's attention using functional near-infrared spectroscopy (fNIRS). To consider the effect of task complexity on the subject's attention, we provided two (slow and fast) speed conditions for walking on both treadmills. RESULTS: Both the cortical activity images and oxygenated hemoglobin (oxyHb) changes showed that the level of attention to walking induced by the ITM was significantly higher than that induced by the conventional treadmill. We found that the walking speed on the ITM also affected the level of attention. CONCLUSION: ITM-based locomotion training would be a promising solution to the limitations of existing treadmill-based locomotion training currently used to improve gait function recovery. TRIAL REGISTRATION: DGIST-HR-150309-03-02 . Registered 01 March 2015.

Iron particle-integrated anammox granules in baffled reactor: Enhanced settling property and nitrogen removal performance.

This study evaluates iron particle-integrated anammox granules (IP-IAGs) to enhance wastewater treatment efficiency. The IP-IAGs resulted in notable improvements in settleability and nitrogen removal. The settling velocity of IP-IAGs increased by 17.91 % to 2.92 ± 0.20 cm/s, and the total nitrogen removal efficiency in batch mode improved by 6.82 %. These changes indicate enhanced biological activity for effective treatment. In continuous operation, the IP-IAGs reactor showed no accumulation of nitrite until 40 d, reaching a peak nitrogen removal rate (NRR) of 1.54 kg-N/m3·d and a nitrogen removal efficiency of 82.61 %. Furthermore, a partial nitritation-anammox reactor that treated anaerobic digestion effluent achieved a NRR of 1.41 ± 0.09 kg-N/m3·d, proving the applicability of IP-IAGs in real wastewater conditions. These results underscore the potential of IP-IAGs to enhance the efficiency and stability of anammox-based processes, marking a significant advancement in environmental engineering for wastewater treatment.

Thickness of hydrogel for nitrifying biomass entrapment determines the free ammonia susceptibility differently in batch and continuous modes.

Hydrogels immobilizing nitrifying bacteria with different thicknesses of 0.55 and 1.13 cm (HG-0.55 and HG-1.13, respectively) were produced. It was recognized that the thickness of media is a crucial parameter that affects both the stability and efficiency of wastewater treatment. Batch mode experiments were conducted to quantify specific oxygen uptake rate (SOUR) values at various total ammonium nitrogen (TAN) concentrations and pH levels. In the batch test, HG-0.55 exhibited 2.4 times higher nitrifying activity than HG-1.13, with corresponding SOUR values of 0.00768 and 0.00317 mg-O2/L mL-PVA min, respectively. However, HG-0.55 was more susceptible to free ammonia (FA) toxicity than HG-1.13, resulting in a reduction of 80% and 50% in SOUR values for HG-0.55 and -1.13, respectively, upon increasing the FA concentration from 15.73 to 118.12 mg-FA/L. Continuous mode experiments were conducted to assess the partial nitritation (PN) efficiency in practical applications, where continuous wastewater inflow maintains low FA toxicity through high ammonia-oxidizing rates. With step-wise TAN concentration increases, HG-0.55 experienced a gentler increase in FA concentration compared to HG-1.13. At a nitrogen loading rate of 0.78-0.95 kg-N/m3 day, the FA increase rate for HG-0.55 was 0.0179 kg-FA/m3 day, while that of HG-1.13 was 0.0516 kg-FA/m3 day. In the batch mode, where wastewater is introduced all at once, the high accumulation of FA posed a disadvantage for the FA-susceptible HG-0.55, which made it unsuitable for application. However, in the continuous mode, the thinner HG-0.55, with its larger surface area and high ammonia oxidation activity, proved to be suitable and demonstrated its effectiveness. This study provides valuable insights and a framework for the utilization strategy of immobilized gels in addressing the toxic effects of FA in practical processes.

Application of poly (vinyl alcohol)-cryogels to immobilizing nitrifiers: Enhanced tolerance to shear stress-induced destruction and viability control.

The hardness of poly (vinyl alcohol)-cryogels (PVA-CGs) was improved under three parameter conditions: 7.5 %-12.5 % PVA, 1-5 freezing-thawing cycles (FTCs), and the addition of 0 %-10 % glycerol as a cryoprotectant. This study investigated the effects of shear stress-induced destruction (SSID) on mechanical strength by inducing rapid erosion with a high frictional force. Tolerance to SSID (Tol-SSID) exhibited different sensitivities and trends depending on the above three fabrication parameters. The measured Tol-SSID exhibited consistent and inconsistent trends with tensile strength and swelling, respectively. Tol-SSID evaluation provides new insights into the practically meaningful mechanical strength of PVA-CGs against strong friction, which simulates extreme shear stress in a bioreactor. A PVA-CG with a PVA concentration of 10 % and in two FTCs resulted in Tol-SSID and tensile strength of 88.3 % and 0.59 kPa, respectively. Here, 5 % glycerol was added to maintain the bacterial respiration activity of immobilized nitrifiers of 0.097 mg-O2/g-VSS·min and survival of 88.6 %. The continuous mode of nitrification using the optimized PVA-CG for 10 days resulted in an ammonia removal rate of 0.2173 kg-N/m3·d, which is an improvement over cases without glycerol addition: 0.1426 and 0.1472 kg-N/m3·d for PVA-CGs in two and three FTCs, respectively.

Antibiofilm mechanism of peppermint essential oil to avert biofilm developed by foodborne and food spoilage pathogens on food contact surfaces.

Establishing efficient methods to combat bacterial biofilms is a major concern. Natural compounds, such as essential oils derived from plants, are among the favored and recommended strategies for combatting bacteria and their biofilm. Therefore, we evaluated the antibiofilm properties of peppermint oil as well as the activities by which it kills bacteria generally and particularly their biofilms. Peppermint oil antagonistic activities were investigated against Vibrio parahaemolyticus, Listeria monocytogenes, Pseudomonas aeruginosa, Escherichia coli O157:H7, and Salmonella Typhimurium on four food contact surfaces (stainless steel, rubber, high-density polyethylene, and polyethylene terephthalate). Biofilm formation on each studied surface, hydrophobicity, autoaggregation, metabolic activity, and adenosine triphosphate quantification were evaluated for each bacterium in the presence and absence (control) of peppermint oil. Real-time polymerase chain reaction, confocal laser scanning microscopy, and field-emission scanning electron microscopy were utilized to analyze the effects of peppermint oil treatment on the bacteria and their biofilm. Results showed that peppermint oil (1/2× minimum inhibitory concentration [MIC], MIC, and 2× MIC) substantially lessened biofilm formation, with high bactericidal properties. A minimum of 2.5-log to a maximum of around 5-log reduction was attained, with the highest sensitivity shown by V. parahaemolyticus. Morphological experiments revealed degradation of the biofilm structure, followed by some dead cells with broken membranes. Thus, this study established the possibility of using peppermint oil to combat key foodborne and food spoilage pathogens in the food processing environment.

An EEG-based asynchronous MI-BCI system to reduce false positives with a small number of channels for neurorehabilitation: A pilot study.

Many studies have used motor imagery-based brain-computer interface (MI-BCI) systems for stroke rehabilitation to induce brain plasticity. However, they mainly focused on detecting motor imagery but did not consider the effect of false positive (FP) detection. The FP could be a threat to patients with stroke as it can induce wrong-directed brain plasticity that would result in adverse effects. In this study, we proposed a rehabilitative MI-BCI system that focuses on rejecting the FP. To this end, we first identified numerous electroencephalogram (EEG) signals as the causes of the FP, and based on the characteristics of the signals, we designed a novel two-phase classifier using a small number of EEG channels, including the source of the FP. Through experiments with eight healthy participants and nine patients with stroke, our proposed MI-BCI system showed 71.76% selectivity and 13.70% FP rate by using only four EEG channels in the patient group with stroke. Moreover, our system can compensate for day-to-day variations for prolonged session intervals by recalibration. The results suggest that our proposed system, a practical approach for the clinical setting, could improve the therapeutic effect of MI-BCI by reducing the adverse effect of the FP.

Combined machine learning and biomolecular analysis for stability assessment of anaerobic ammonium oxidation under salt stress.

In this study, the stability of the total nitrogen removal efficiency (TNRE) was modeled using an artificial neural network (ANN)-based binary classification model for the anaerobic ammonium oxidation (AMX) process under saline conditions. The TNRE was stabilized to 80.2 ± 11.4% at the final phase under the salinity of 1.0 ± 0.02%. The results of terminal restriction fragment length polymorphism (T-RFLP) analysis showed the predominance of Candidatus Jettenia genus. Real-time quantitative PCR analysis revealed the average abundance of Ca. Jettenia and Kuenenia spp. increased in 3.2 ± 5.4 × 108 and 2.0 ± 2.2 × 105 copies/mL, respectively. The prediction accuracy using operational parameters with data augmentation was 88.2%. However, integration with T-RFLP and real-time qPCR signals improved the prediction accuracy by 97.1%. This study revealed the feasible application of machine learning and biomolecular signals to the stability prediction of the AMX process under increased salinity.

A Paradigm to Enhance Motor Imagery Using Rubber Hand Illusion Induced by Visuo-Tactile Stimulus.

Enhancing motor imagery (MI) results in amplified event-related desynchronization (ERD) and is important for MI-based rehabilitation and brain-computer interface (BCI) applications. Many attempts to enhance the MI by providing a visual guidance have been reported. We believe that the rubber hand illusion (RHI), which induces body ownership over an external object, can provide better guidance to enhance MI; thus, an RHI-based paradigm with motorized moving rubber hand was proposed. To validate the proposed MI enhancing paradigm, we conducted an experimental comparison among paradigms with 20 healthy subjects. The peak amplitude and arrival times of ERD were compared at contralateral and ipsilateral electroencephalogram channels. We found significantly amplified ERD caused by the proposed paradigm, which is similar to the ERD caused by motor execution. In addition, the arrival time suggests that the proposed paradigm is applicable for BCI. In conclusion, the proposed paradigm can significantly enhance the MI with better characteristics for use with BCI.

Toward Comparison of Cortical Activation with Different Motor Learning Methods Using Event-Related Design: EEG-fNIRS Study.

Recently, motor imagery brain-computer interface (MI-BCI) has been studied as a motor learning method and evaluated by comparing with conventional passive and active training. Most functional near-infrared spectroscopy (fNIRS) studies adopted block design for comparing those motor learning methods, including MI-BCI. Compared to the block design, event-related design would be more appropriate for estimating cortical activation in MI-BCI which provides feedback for each trial. This paper is a preliminary study to check the feasibility whether event-related design can be applicable for MI-BCI. To this end, three different motor learning methods involving MI-BCI were compared. In hemodynamic response, MI-BCI showed significantly stronger cortical activation than passive training (PT), and weaker than active training (AT), which conforms most existing studies. The results demonstrate that event-related design could be applied to investigate cortical effects of MI-BCI and comparing hemodynamic responses of different motor learning methods.

Wireless, Skin-Mountable EMG Sensor for Human-Machine Interface Application.

The development of advanced technologies for wireless data collection and the analysis of quantitative data, with application to a human-machine interface (HMI), is of growing interest. In particular, various wearable devices related to HMIs are being developed. These devices require a customization process that considers the physical characteristics of each individual, such as mounting positions of electrodes, muscle masses, and so forth. Here, the authors report device and calculation concepts for flexible platforms that can measure electrical signals changed through electromyography (EMG). This soft, flexible, and lightweight EMG sensor can be attached to curved surfaces such as the forearm, biceps, back, legs, etc., and optimized biosignals can be obtained continuously through post-processing. In addition to the measurement of EMG signals, the application of the HMI has stable performance and high accuracy of more than 95%, as confirmed by 50 trials per case. The result of this study shows the possibility of application to various fields such as entertainment, the military, robotics, and healthcare in the future.

An Ambulatory Gait Monitoring System with Activity Classification and Gait Parameter Calculation Based on a Single Foot Inertial Sensor.

GOAL: For healthcare and clinical use, ambulatory gait monitoring systems using inertial sensors have been developed to estimate the user gait parameters, such as walking speed, stride time, and stride length. However, to adapt the systems effectively to daily-life activities, they need to be able to classify the gait activities of daily-life to obtain the parameters for each activity. In this study, we propose a simple classification algorithm based on a single inertial sensor for ease of use, which classifies three major gait activities: leveled walk, ramp walk, and stair walk. METHOD: The classification can be performed with gait parameter estimation simultaneously. The developed system that includes classification and parameter estimation algorithms was evaluated with eight healthy subjects within a gait lab and on an outdoor daily-life walking course. RESULTS: The results showed that the estimated gait parameters were comparable to existing studies (range of walking speed root mean square error: 0.059-0.129 m/s), and the classification accuracy was sufficiently high for all three gait activities: 98.5% for the indoor gait lab experiment and 95.5% for the outdoor complex daily-life walking course experiment. CONCLUSION: The proposed system is simple and effective for daily-life gait analysis, including gait activity classification and gait parameter estimation for each activity.