Missing Value Imputation of Wireless Sensor Data for Environmental Monitoring.

Over the past few years, the scale of sensor networks has greatly expanded. This generates extended spatiotemporal datasets, which form a crucial information resource in numerous fields, ranging from sports and healthcare to environmental science and surveillance. Unfortunately, these datasets often contain missing values due to systematic or inadvertent sensor misoperation. This incompleteness hampers the subsequent data analysis, yet addressing these missing observations forms a challenging problem. This is especially the case when both the temporal correlation of timestamps within a single sensor and the spatial correlation between sensors are important. Here, we apply and evaluate 12 imputation methods to complete the missing values in a dataset originating from large-scale environmental monitoring. As part of a large citizen science project, IoT-based microclimate sensors were deployed for six months in 4400 gardens across the region of Flanders, generating 15-min recordings of temperature and soil moisture. Methods based on spatial recovery as well as time-based imputation were evaluated, including Spline Interpolation, MissForest, MICE, MCMC, M-RNN, BRITS, and others. The performance of these imputation methods was evaluated for different proportions of missing data (ranging from 10% to 50%), as well as a realistic missing value scenario. Techniques leveraging the spatial features of the data tend to outperform the time-based methods, with matrix completion techniques providing the best performance. Our results therefore provide a tool to maximize the benefit from costly, large-scale environmental monitoring efforts.

Classification of Targets and Distractors in an Audiovisual Attention Task Based on Electroencephalography.

Within the broader context of improving interactions between artificial intelligence and humans, the question has arisen regarding whether auditory and rhythmic support could increase attention for visual stimuli that do not stand out clearly from an information stream. To this end, we designed an experiment inspired by pip-and-pop but more appropriate for eliciting attention and P3a-event-related potentials (ERPs). In this study, the aim was to distinguish between targets and distractors based on the subject's electroencephalography (EEG) data. We achieved this objective by employing different machine learning (ML) methods for both individual-subject (IS) and cross-subject (CS) models. Finally, we investigated which EEG channels and time points were used by the model to make its predictions using saliency maps. We were able to successfully perform the aforementioned classification task for both the IS and CS scenarios, reaching classification accuracies up to 76%. In accordance with the literature, the model primarily used the parietal-occipital electrodes between 200 ms and 300 ms after the stimulus to make its prediction. The findings from this research contribute to the development of more effective P300-based brain-computer interfaces. Furthermore, they validate the EEG data collected in our experiment.

Design and Construction of an Experimental Setup to Enhance Mineral Weathering through the Activity of Soil Organisms.

Enhanced weathering (EW) is an emerging carbon dioxide (CO2) removal technology that can contribute to climate change mitigation. This technology relies on accelerating the natural process of mineral weathering in soils by manipulating the abiotic variables that govern this process, in particular mineral grain size and exposure to acids dissolved in water. EW mainly aims at reducing atmospheric CO2 concentrations by enhancing inorganic carbon sequestration. Until now, knowledge of EW has been mainly gained through experiments that focused on the abiotic variables known for stimulating mineral weathering, thereby neglecting the potential influence of biotic components. While bacteria, fungi, and earthworms are known to increase mineral weathering rates, the use of soil organisms in the context of EW remains underexplored. This protocol describes the design and construction of an experimental setup developed to enhance mineral weathering rates through soil organisms while concurrently controlling abiotic conditions. The setup is designed to maximize weathering rates while maintaining soil organisms' activity. It consists of a large number of columns filled with rock powder and organic material, located in a climate chamber and with water applied via a downflow irrigation system. Columns are placed above a fridge containing jerrycans to collect the leachate. Representative results demonstrate that this setup is suitable to ensure the activity of soil organisms and quantify their effect on inorganic carbon sequestration. Challenges remain in minimizing leachate losses, ensuring homogeneous ventilation through the climate chamber, and avoiding flooding of the columns. With this setup, an innovative and promising approach is proposed to enhance mineral weathering rates through the activity of soil biota and disentangle the effect of biotic and abiotic factors as drivers of EW.

Are syngeneic mouse tumor models still valuable experimental models in the field of anti-cancer drug discovery?

To establish the pharmacological profile of a molecule with anti-cancer potential, it seems essential to add an in vivo approach to the first pharmacological experiments carried out in vitro. The present study aims to characterize the degree of sensitivity of seven syngeneic models (two leukemias and five solid tumors) to eleven molecules which have proven to be clinically reliable. We also used some of these models to investigate whether the molecular effects on the extent of growth in a subcutaneously grafted experimental model correlate with the effects of the same drug on the survival of the animals so grafted. Our data show that all the molecules demonstrated significant anti-tumor activities in two mouse leukemia models (with some discrepancies between the two). Two lymphoma models displayed weaker chemosensitivity profiles than the two leukemia models from which they were developed. Two other models, namely the MXT-HS mammary carcinoma and the B16 melanoma, appeared to be rather chemoresistant. However, a direct relationship was evident between the drug-induced decrease in the tumor growth rate and the increase observed in the survival periods of the MXT tumor-bearing mice. This relationship was also observed in the L1210_LYM lymphoma, though to a lesser extent, and was completely absent from the B16 melanoma model. Finally, our data indicated that we had developed a pair of metastasizing, as opposed to non-metastasizing, lymphoma and mammary carcinoma models. In conclusion, the present study shows that syngeneic mouse tumor models can be used as valuable in vivo experimental models for the screening of potential anti-cancer agents.

Evaluation of the Pharmacokinetics and Renal Excretion of Simeprevir in Subjects with Renal Impairment.

BACKGROUND: Simeprevir is a N3/4 protease inhibitor approved for the treatment of hepatitis C virus (HCV) infection. HCV prevalence is higher in patients with chronic kidney disease compared with the general population; safe and efficacious therapies in renal impairment are needed. OBJECTIVES: To evaluate simeprevir renal excretion in healthy subjects and to compare the simeprevir steady-state pharmacokinetics between subjects with severe renal impairment and healthy subjects. METHODS: In the mass balance study, healthy adults received a single 200-mg dose of (14)C-simeprevir; radioactivity in the urine and feces was quantified until concentrations were <2% of the administered dose and seven or more stools were produced. In the pharmacokinetic study, non-HCV-infected adults with severe renal impairment (estimated glomerular filtration rate ≤29 mL/min/1.73 m(2)) and matched healthy subjects (estimated glomerular filtration rate ≥80 mL/min/1.73 m(2)) received 150 mg simeprevir for 7 days. Pharmacokinetic analysis was performed post-dose on Day 7. RESULTS: (14)C-simeprevir recovery from the urine was low (0.009-0.138% of total dose). The minimum plasma concentration, maximum plasma concentration, and area under the plasma concentration-time curve at 24 h were 71, 34, and 62% higher, respectively, in subjects with severe renal impairment compared with healthy subjects. The mean fraction of simeprevir unbound to protein was <0.0001 (all subjects). Most adverse events were grade I or II; one subject with renal impairment who was receiving fenofibrate presented with grade 3 rhabdomyolysis. CONCLUSIONS: Simeprevir plasma concentrations were mildly elevated in subjects with severe renal impairment. The results suggest that simeprevir may be administered without dose adjustment in patients with renal impairment.