Solute Trapping of Group III, IV, and V Elements in Silicon by an Aperiodic Stepwise Growth Mechanism

With rapid solidification following pulsed laser melting, we have measured the dependence on interface orientation of the amount of solute trapping of several group III, IV, and V elements (As, Ga, Ge, In, Sb, Sn) in Si. The aperiodic stepwise growth model of Goldman and Aziz accurately fits both the velocity and orientation dependence of solute trapping of all of these solutes except Ge. The success of the model implies a ledge structure for the crystal/melt interface and a step-flow mechanism for growth from the melt. In addition, we have observed an empirical inverse correlation between the two free parameters (-“diffusive speeds”) in this model and the equilibrium solute partition coefficient of a system. This correlation may be used to estimate values of these free parameters for other systems in which solute trapping has not or cannot be measured. The possible microscopic origin of such a correlation is discussed.Engineering and Applied Science

Learning curve for laparoscopic cholecystectomy has not been defined: A systematic review

Background: Laparoscopic cholecystectomy is one of the most performed surgeries worldwide but its learning curve is still unclear. Methods: A systematic review was conducted according to the 2009 Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Two independent reviewers searched the literature in a systematic manner through online databases, including Medline, Scopus, Embase, and Google Scholar. Human studies investigating the learning curve of laparoscopic cholecystectomy were included. The Newcastle–Ottawa scale for cohort studies and the GRADE scale were used for the quality assessment of the selected articles. Results: Nine cohort studies published between 1991 and 2020 were included. All studies showed a great heterogeneity among the considered variables. Seven articles (77.7%) assessed intraoperative variables only, without considering patient's characteristics, operator's experience, and grade of gallbladder inflammation. Only five articles (55%) provided a precise cut-off value to see proficiency in the learning curve, ranging from 13 to 200 laparoscopic cholecystectomies. Conclusions: The lack of clear guidelines when evaluating the learning curve in surgery, probably contributed to the divergent data and heterogeneous results among the studies. The development of guidelines for the investigation and reporting of a surgical learning curve would be helpful to obtain more objective and reliable data especially for common operation such as laparoscopic cholecystectomy

Volcano monitoring and early warning on Mt Etna, Italy, using volcanic tremor – Methods and technical aspects

Recent activity on Mt Etna was characterized by 25 lava fountains occurred on Mt Etna in 2011 and the first semester of 2012. In summer 2012 volcanic activity in a milder form was noticed within the Bocca Nuova crater, before it came to an essential halt in August 2012. Together with previous unrests (e. g., in 2007-08) these events offer rich material for testing automatic data processing and alert issue in the context of volcano monitoring. Our presentation focuses on the seismic background radiation – volcanic tremor – which has a key role in the surveillance of Mt Etna. From 2006 on a multi-station alert system exploiting STA/LTA ratios, has been established in the INGV operative centre of Catania. Besides, also the frequency content has been found to change correspondingly to the type of volcanic activity, and can thus be exploited for warning purposes. We apply Self Organizing Maps and Fuzzy Clustering which offer an efficient way to visualize signal characteristics and its development with time. These techniques allow to identify early stages of eruptive events and automatically flag a critical status before this becomes evident in conventional monitoring techniques. Changes of tremor characteristics are related to the position of the source of the signal. Given the dense seismic network we can base the location of the sources on distribution of the amplitudes across the network. The locations proved to be extremely useful for warning throughout both a flank eruption in 2008 as well as the 2011 lava fountains. During all these episodes a clear migration of tremor sources towards the eruptive centres was revealed in advance. The location of the sources completes the picture of an imminent volcanic unrest and corroborates early warnings flagged by the changes of signal characteristics. Automatic real time data processing poses high demands on computational efficiency, robustness of the methods and stability of data acquisition. The amplitude based multi-station approach is not sensitive to the failure of single stations and therefore offers a good stability. On the other hand, the single station approach, exploiting unsupervised classification techniques, limits logistic efforts, as only one or few key stations are necessary. A common characteristics of both strategies is their robustness to disturbances (undesired transients like earthquakes, noise, short gaps in the continuous data flow). False alarms were not encountered so far. A critical issue it the reliability of data storage and access. Therefore, a specific hardware cluster architecture has been proposed for failover protection, including a Storage Area Network system. We present concepts of the software architectures which allow easy data access following predefined user policies. We also envisage the integration of seismic data and those originating from other scientific fields (e. g., volcano imagery, geochemistry, deformation, gravity, magneto-telluric). This will facilitate cross-checking of evidences encountered from the single data streams, in particular allow their immediate verification with respect to ground truth

The July 2006 eruption of Mount Etna (Italy) monitored through continuous soil radon measurements

Radon (222Rn) is a short-lived decay product derived from 238U, with a half-life of only 3.8 days. This gas ascends towards the earth’s surface mainly through cracks or faults. In recent decades radon has been used as a tool for predicting earthquakes and volcanic eruptions, because anomalous variations of its activity have often been reported before the occurrence of such geodynamic events. The recent eruptive activity of Mount Etna in Sicily (Italy) has been documented by multidisciplinary visual, geochemical, and instrumental observations. Here we describe the results obtained during the 10-day July 2006 Strombolian-effusive eruption of Mount Etna by using a radon probe installed near Torre del Filosofo (˜2950 m above sea level). This site is located ˜1 km south of the Southeast Crater, the youngest and most active of the four summit craters of the volcano, and the site of the July 2006 eruption. In order to better interpret the soil radon data we have compared them with simultaneously acquired volcanic tremor signals and a relative measurement of the thermal radiance emitted from the eruption area, derived from thermal camera measurements. During the month prior to the onset of the 2006 eruption, soil radon activity remained at low levels (˜1 x 103 Bq/m3); similar values persisted even when effusive activity started late on 14 July 2006. Only at ˜02:50 on the 15th July, radon activity showed a sharp increase (up to ˜50 x 103 Bq/m3) in a 20 minute interval, and a further increase to ˜20 x 106 Bq/m3 during the following hours. Explosive activity started at 04:30, 100 minutes after the initial rise in soil radon activity. High values in radon activity with numerous peaks persisted through the following four days, and were then followed by a marked decline until early on 20th July, when an extremely sharp rise brought the levels of radon activity to unprecedented values of nearly 1.7 x 108 Bq/m3, and remained very high for the next ˜24 hours. The episode of lava fountaining of 20th July occurred during this interval, starting 10 hours after the maximum in radon activity. From then on through the end of the eruptive phase, the levels of radon activity fluctuated with values rarely exceeding 106 Bq/m3 and then gradually declined starting from around noon on 22nd July. At the end of the eruption, radon levels remained higher (10-100 x 103 Bq/m3) than those recorded before the eruption. In conclusion, the onset of the Strombolian activity (15 July) and the lava fountaining (20 July) were related to significant changes in the magma pressure within the conduit. These two events were preceded by some hours with increases in radon soil emission by 4-5 orders of magnitude. For this reason we can imagine in the future the use of this signal as a potential precursor of this type of volcanic activity. Minor changes in eruptive behaviour did not produce significant variations in the monitored parameters. We interpret peaks in radon activity as due primarily to microfracturing of uranium-bearing rock. These observations suggest that radon measurements in the summit area of Etna are strongly controlled by the state of stress within the volcano and demonstrate the usefulness of radon data acquisition before and during eruptions

Monitoring System of Eastern Sicily (Italy) devised by a specialist team (UFSO) at the INGV- Catania Section, Italy.

Eastern Sicily in Italy is well-known as a high seismic and volcanic risk area. From a monitoring point of view, a team/unit of people has been created (UFSO) with the task of managing all the activities connected to the faultless operation of the Working Room that is the strategic centre during periods of routine operations or in the case of emergency. Among the primary activities of monitoring and surveillance, the management of the video camera network located on the main Sicilian active volcanoes represents a major goal. This task is achieved by means of permanent, visible and infrared cameras together with similar mobile systems, in order to observe each phenomenon related to the volcanic activity. The expert staff can therefore make decisions, in real time, from useful information in order to understand the phenomena in action. With the aim of maximizing the results and performance of all the networks, the UFSO is attentive to the planning and realization of hardware and software systems that are always available in the mobile van unit. In this context, the staff actively participates in national and European research projects dealing with the development and use of new systems with high technological content. Another aspect of the work, moreover, is represented by the development of supervisory control software, namely software providing automatic control of the working systems. Such algorithms allow to immediately and remotely signal to the duty-personnel states of alert of several modules, indicating, when possible, the probable failure causes

Data mining in the context of monitoring Mt Etna, Italy

The persistent volcanic activity of Mt Etna makes the continuous monitoring of multidisciplinary data a first-class issue. Indeed, the monitoring systems rapidly accumulate huge quantity of data, arising specific problems of an- dling and interpretation. In order to respond to these problems, the INGV staff has developed a number of software tools for data mining. These tools have the scope of identifying structures in the data that can be related to volcanic activity, furnishing criteria for the identification of precursory scenarios. In particular, we use methods of clustering and classification in which data are divided into groups according to a- priori-defined measures of similarity or distance. Data groups may assume various shapes, such as convex clouds or complex concave bodies.The “KKAnalysis” software package is a basket of clustering methods. Currently, it is one of the key techniques of the tremor-based automatic alarm systems of INGV Osservatorio Etneo. It exploits both Self-Organizing Maps and Fuzzy Clustering. Beside seismic data, the software has been applied to the geo- chemical composition of eruptive products as well as a combined analysis of gas-emission (radon) and seismic data. The “DBSCAN” package exploits a concept based on density-based clustering. This method allows discovering clusters with arbitrary shape. Clusters are defined as dense regions of objects in the data space separated by re- gions of low density. In DBSCAN a cluster grows as long as the density within a group of objects exceeds some threshold. In the context of volcano monitoring, the method is particularly promising in the recognition of ash par- ticles as they have a rather irregular shape. The “MOTIF” software allows us to identify typical waveforms in time series, outperforming methods like cross-correlation that entail a high computational effort. MOTIF can recognize the non-imilarity of two patterns on a small number of data points without going through the whole length of data vectors. All the developments aforementioned come along with modules for feature extraction and post-processing. Spe- cific attention is devoted to the obustness of the feature extraction to avoid misinterpretations due to the presence of disturbances from environmental noise or other undesired signals originating from the source, which are not relevant for the purpose of volcano surveillance

Food literacy as a resilience factor in response to health-related uncertainty

Purpose: During the Covid-19 pandemic, people were deprived of their freedom, unable to engage in physical and social activities, and worried about their health. Uncertainty, insecurity, and confinement are all factors that may induce stress, uneasiness, fear, and depression. In this context, this study aims to identify possible relationships of emotions caused by health risks and restrictions to outdoor activities with well-informed decisions about food consumption. Design/methodology/approach: The theoretical framework of this research draws on the stimulus-organism-response paradigm yielding six research hypotheses. An online survey was designated to test these hypotheses. A total of 1,298 responses were gathered from Italy, Greece, and the United Kingdom. Data analyses include demographic group comparisons, moderation, and multiple regression tests. Findings: The results showed that when people miss their usual activities (including freedom of movement, social contact, travelling, personal care services, leisure activities, and eating at restaurants) and worry about their health and the health of their families, they turn to safer food choices of higher quality, dedicating more of their time and resources to cooking and eating. Research limitations/implications: The findings showcase how risk-based thinking is critical for management and marketing strategies. Academics and practitioners may rely on these findings to include extreme conditions within their scope, understanding food literacy as a resilience factor to cope with health risks and stimulated emotions. Originality/value: This study identified food behavioural patterns under risk-laden conditions. A health risk acted as an opportunity to look at food consumption as a means of resilience

Data Mining in the Context of Monitoring Mt Etna, Italy

The persistent volcanic activity of Mt Etna makes the continuous monitoring of multidisciplinary data a first-class issue. Indeed, the monitoring systems rapidly accumulate huge quantity of data, arising specific problems of andling and interpretation. In order to respond to these problems, the INGV staff has developed a number of software tools for data mining. These tools have the scope of identifying structures in the data that can be related to volcanic activity, furnishing criteria for the identification of precursory scenarios. In particular, we use methods of clustering and classification in which data are divided into groups according to apriori- defined measures of similarity or distance. Data groups may assume various shapes, such as convex clouds or complex concave bodies.The “KKAnalysis” software package is a basket of clustering methods. Currently, it is one of the key techniques of the tremor-based automatic alarm systems of INGV Osservatorio Etneo. It exploits both Self-Organizing Maps and Fuzzy Clustering. Beside seismic data, the software has been applied to the geochemical composition of eruptive products as well as a combined analysis of gas-emission (radon) and seismic data. The “DBSCAN” package exploits a concept based on density-based clustering. This method allows discovering clusters with arbitrary shape. Clusters are defined as dense regions of objects in the data space separated by regions of low density. In DBSCAN a cluster grows as long as the density within a group of objects exceeds some threshold. In the context of volcano monitoring, the method is particularly promising in the recognition of ash particles as they have a rather irregular shape. The “MOTIF” software allows us to identify typical waveforms in time series, outperforming methods like cross-correlation that entail a high computational effort. MOTIF can recognize the non-imilarity of two patterns on a small number of data points without going through the whole length of data vectors. All the developments aforementioned come along with modules for feature extraction and post-processing. Specific attention is devoted to the obustness of the feature extraction to avoid misinterpretations due to the presence of disturbances from environmental noise or other undesired signals originating from the source, which are not relevant for the purpose of volcano surveillance