Irradiance Sensing through PV Devices: A Sensitivity Analysis.

In this work, a sensitivity analysis for the closed-form approach of irradiance sensing through photovoltaic devices is proposed. A lean expression to calculate irradiance on a photovoltaic device, given its operating point, temperature and equivalent circuit model, is proposed. On this expression, the sensitivity towards errors in the measurement of the photovoltaic device operating point and temperature is analyzed, determining optimal conditions to minimize sensitivity. The approach is studied for two scenarios, a stand-alone sensor and irradiance sensing on an operating power-producing photovoltaic device. A low-cost realization of a virtual sensor employing the closed form for monitoring performance of photovoltaic module is also presented, showing the advantage of this kind of simple solution. The proposed solution can be used to create a wireless sensor network for remote monitoring of a photovoltaic plant, assessing both electrical and environmental conditions of the devices in real time.

Development and Validation of a Method for the Detection and Quantification of Antidepressants and Antipsychotics in Bone Samples by GC-MS.

Bone marrow is the tissue contained inside the bones and can be considered one of the potential alternative tissues in forensic toxicology. This matrix could be particularly useful in those cases where the routine sample is not available due to an advanced state of decomposition or skeletonization of the corpse. The aim of this study was to develop, validate and apply an analytical method of extraction and analysis of different antidepressants and antipsychotics, commonly used in therapy, from spiked pig ribs. Pig ribs, each of 5 g and 5 cm long, were spiked at three concentration levels (100, 200 and 500 ng/g). For each concentration, 10 pig ribs were prepared. The method involves the leaching by ethanol at different pHs of nine drugs from the inside of ribs, in particular from the bone marrow, without the fragmentation of bone tissue. Following a liquid-liquid purification and extraction, analysis was performed by gas chromatography coupled with mass spectrometry in selected ion monitoring mode. For method validation was assessed linearity, sensitivity, precision and accuracy, matrix interferences and, finally, carryover. Analytical method performance was acceptable respect to acceptance criteria for validation. No matrix interferences were detected; for this reason, it is possible to affirm that this method has a good selectivity. Moreover, the method was not affected by carryover. Considering that the study conducted on pig ribs has given encouraging results, it can be assumed that this method can be used in forensic toxicological protocols (human autopsy cases) as alternative to classic procedures.

Toxicological investigations in a fatal and non-fatal accident due to hydrogen sulphide (H2S) poisoning.

Hydrogen sulphide (H2S) is one of the most toxic natural gas and represents a not rare cause of fatal events in workplaces. We report here a serious accidental poisoning by hydrogen sulphide inhalation involving six sailors. Three of them died while the other three survived and were transported to the emergency room. No greenish discolouration of the body, that could be a feature of these type of deaths, was observed at autopsy. Given that blood and/or urine H2S detection does not allow to discriminate if it is related to inhalation or to putrefactive processes, the determination of thiosulphate, H2S main metabolite, is decisive. The succession of fatal events reported here can be rebuilt by toxicological data interpretation: the subject 1 died after a longer interval of time as demonstrated by the highest blood and urine thiosulfate concentrations; the subject 2 died after a short interval of time as showed by a lower blood and urine thiosulfate concentrations than subject 1; the subject 3 died almost immediately after H2S inhalation since he showed the lowest blood thiosulfate concentration, and no trace of sulphide and thiosulfate was found in the urine.

On Training Efficiency and Computational Costs of a Feed Forward Neural Network: A Review.

A comprehensive review on the problem of choosing a suitable activation function for the hidden layer of a feed forward neural network has been widely investigated. Since the nonlinear component of a neural network is the main contributor to the network mapping capabilities, the different choices that may lead to enhanced performances, in terms of training, generalization, or computational costs, are analyzed, both in general-purpose and in embedded computing environments. Finally, a strategy to convert a network configuration between different activation functions without altering the network mapping capabilities will be presented.

Seismicity pattern changes before the M = 4.8 Aeolian Archipelago (Italy) earthquake of August 16, 2010.

We investigated the seismicity patterns associated with an M = 4.8 earthquake recorded in the Aeolian Archipelago on 16, August, 2010, by means of the region-time-length (RTL) algorithm. This earthquake triggered landslides at Lipari; a rock fall on the flanks of the Vulcano, Lipari, and Salina islands, and some damages to the village of Lipari. The RTL algorithm is widely used for investigating precursory seismicity changes before large and moderate earthquakes. We examined both the spatial and temporal characteristics of seismicity changes in the Aeolian Archipelago region before the M = 4.8 earthquake. The results obtained reveal 6-7 months of seismic quiescence which started about 15 months before the earthquake. The spatial distribution shows an extensive area characterized by seismic quiescence that suggests a relationship between quiescence and the Aeolian Archipelago regional tectonics.

SVM versus MAP on accelerometer data to distinguish among locomotor activities executed at different speeds.

Two approaches to the classification of different locomotor activities performed at various speeds are here presented and evaluated: a maximum a posteriori (MAP) Bayes' classification scheme and a Support Vector Machine (SVM) are applied on a 2D projection of 16 features extracted from accelerometer data. The locomotor activities (level walking, stair climbing, and stair descending) were recorded by an inertial sensor placed on the shank (preferred leg), performed in a natural indoor-outdoor scenario by 10 healthy young adults (age 25-35 yrs.). From each segmented activity epoch, sixteen features were chosen in the frequency and time domain. Dimension reduction was then performed through 2D Sammon's mapping. An Artificial Neural Network (ANN) was trained to mimic Sammon's mapping on the whole dataset. In the Bayes' approach, the two features were then fed to a Bayes' classifier that incorporates an update rule, while, in the SVM scheme, the ANN was considered as the kernel function of the classifier. Bayes' approach performed slightly better than SVM on both the training set (91.4% versus 90.7%) and the testing set (84.2% versus 76.0%), favoring the proposed Bayes' scheme as more suitable than the proposed SVM in distinguishing among the different monitored activities.