[1] Various methods have been proposed in the literature to predict the rainfall conditions that are likely to trigger landslides in a given area. Most of these methods, however, only consider the rainfall events that resulted in landslides and provide deterministic thresholds with a single possible output (landslide or no-landslide) for a given input (rainfall conditions). Such a deterministic view is not always suited to landslides. Slope stability, in fact, is not ruled by rainfall alone and failure conditions are commonly achieved with a combination of numerous relevant factors. When different outputs (landslide or no-landslide) can be obtained for the same input a probabilistic approach is preferable. In this work we propose a new method for evaluating rainfall thresholds based on Bayesian probability. The method is simple, statistically rigorous, and returns a value of landslide probability (from 0 to 1) for each combination of the selected rainfall variables. The proposed approach was applied to the Emilia-Romagna Region of Italy taking advantage of the historical landslide archive, which includes more than 4000 events for which the date of occurrence is known with daily accuracy. The results show that landsliding in the study area is strongly related to rainfall event parameters (duration, intensity, total rainfall) while antecedent rainfall seems to be less important. The distribution of landslide probability in the rainfall duration-intensity shows an abrupt increase at certain duration-intensity values which indicates a radical change of state of the system and suggests the existence of a real physical threshold.

Dopamine D(3) antagonism combined with serotonin 5-HT(1A) and 5-HT(2A) receptor occupancy may represent a novel paradigm for developing innovative antipsychotics. The unique pharmacological features of 5i are a high affinity for dopamine D(3), serotonin 5-HT(1A) and 5-HT(2A) receptors, together with a low affinity for dopamine D(2) receptors (to minimize extrapyramidal side effects), serotonin 5-HT(2C) receptors (to reduce the risk of obesity under chronic treatment), and for hERG channels (to reduce incidence of torsade des pointes). Pharmacological and biochemical data, including specific c-fos expression in mesocorticolimbic areas, confirmed an atypical antipsychotic profile of 5i in vivo, characterized by the absence of catalepsy at antipsychotic dose.

We present a new method for the automatic classification of Persistent Scatters Interferometry (PSI) time series based on a conditional sequence of statistical tests. Time series are classified into distinctive predefined target trends, such as uncorrelated, linear, quadratic, bilinear and discontinuous, that describe different styles of ground deformation. Our automatic analysis overcomes limits related to the visual classification of PSI time series, which cannot be carried out systematically for large datasets. The method has been tested with reference to landslides using PSI datasets covering the northern Apennines of Italy. The clear distinction between the relative frequency of uncorrelated, linear and non-linear time series with respect to mean velocity distribution suggests that different target trends are related to different physical processes that are likely to control slope movements. The spatial distribution of classified time series is also consistent with respect the known distribution of flat areas, slopes and landslides in the tests area. Classified time series enhances the radar interpretation of slope movements at the site scale, pointing out significant advantages in comparison with the conventional analysis based solely on the mean velocity. The test application also warns against potentially misleading classification outputs in case of datasets affected by systematic errors. Although the method was developed and tested to investigate landslides, it should be also useful for the analysis of other ground deformation processes such as subsidence, swelling/shrinkage of soils, or uplifts due to deep injections in reservoirs

Combination of dopamine D3 antagonism, serotonin 5-HT1A partial agonism, and antagonism at 5-HT2A leads to a novel approach to potent atypical antipsychotics. Exploitation of the original structure-activity relationships resulted in the identification of safe and effective antipsychotics devoid of extrapyramidal symptoms liability, sedation, and catalepsy. The potential atypical antipsychotic 5bb was selected for further pharmacological investigation. The distribution of c-fos positive cells in the ventral striatum confirmed the atypical antipsychotic profile of 5bb in agreement with behavioral rodent studies. 5bb administered orally demonstrated a biphasic effect on the MK801-induced hyperactivity at dose levels not able to induce sedation, catalepsy, or learning impairment in passive avoidance. In microdialysis studies, 5bb increased the dopamine efflux in the medial prefrontal cortex. Thus, 5bb represents a valuable lead for the development of atypical antipsychotics endowed with a unique pharmacological profile for addressing negative symptoms and cognitive deficits in schizophrenia.

As a continuation of our efforts to develop innovative ligands for D(3), 5-HT(1A), and 5-HT(2A) receptors with low propensity to block hERG channels, we propose a series bishetero(homo)arylpiperazines 5a-m as novel and potent multifunctional ligands characterized by low occupancy at D(2) and 5-HT(2C) receptors.