A new proxy of the average volatility of a basket of returns: A Monte Carlo study

The volatility of returns plays a pivotal role in modern finance and an accurate evaluation of this parameter is crucial in portfolio and risk management decisions. Until quite recent it was common practice in the literature to use the squared return as proxy of volatility. However, as pointed out by several authors, this measure of volatility includes a large noisy component. In this paper we propose a procedure, based on a generalized dynamic factors model methodology, to obtain a more accurate estimate of volatility of a basket of returns.

The evolution of the ISOLDE control system

The ISOLDE on-line mass separator facility is operating on a Personal Computer based control system since spring 1992. Front End Computers accessing the hardware are controlled from consoles running Microsoft WindowsTM through a Novell NetWare4TM local area network. The control system is transparently integrated in the CERN wide office network and makes heavy use of the CERN standard office application programs to control and to document the running of the ISOLDE isotope separators. This paper recalls the architecture of the control system, shows its recent developments and gives some examples of its graphical user interface

Decision support system for integrated management of mycotoxins in feed and food supply chains

Mycotoxins present a global food safety threat of our feed and food. Mycotoxins are toxic metabolites of certain fungi in agricultural products that are harmful to animal and human health. The presence of mycotoxins in these products depends on a variety of management and environmental factors in the field, during storage and/or processing of feed and food commodities. To date, information on mycotoxin management is available, but is not easy to access by supply chain actors. This study aimed to design, build and test a Decision Support System (DSS) that can help decision making on mycotoxin management by various actors along the feed and food supply chains. As part of this, available knowledge and data on mycotoxin prevention and control were collected and synthesised into easy to understand guidelines and tools for various groups of end-users. The DSS consists of four different modules: (a) static information module and (b) scenario analysis module, (c) dynamic module for forecasting mycotoxins, and (d) dynamic module for real-time monitoring of moulds/mycotoxins in grain silos. Intended end-users are all end-user groups for modules (a) and (b); growers and collectors for module (c) and; post-harvest storage managers for module (d). The DSS is user-friendly and accessible through PCs, tablets and smartphones (see https://mytoolbox-platform.com/). In various phases of the DSS development, the tool has been demonstrated to groups of end-users, and their suggestions have been taken into account, whenever possible. Also, a near final version has been tested with individual farmers on the easiness to use the system. In this way we aimed to maximise the DSS uptake by actors along the chain. Ultimately, this DSS will improve decision making on mycotoxin management; it will assist in reducing mycotoxin contamination in the key crops of Europe, thereby reducing economic losses and improving animal and human health

The impact of management practices to prevent and control mycotoxins in the European food supply chain: My ToolBox project results

The presence of mycotoxins in cereals has led to large economic losses in Europe. In the course of the European project MyToolBox, prevention and control measures to reduce mycotoxin contamination in cereals were developed. This study aimed to estimate the impact of these prevention and control measures on both the reduction in crop losses and the increased volume of crops suitable for food and/or feed. It focused on the following measures: the use of fungicides during wheat cultivation, the use of resistant maize cultivars and/or biocontrol during maize cultivation, the use of real time sensors in storage silos, the use of innovative milling strategies during the pasta making process, and the employment of degrading enzymes during the process of bioethanol and Dried Distillers Grains with Solubles (DDGS) production. The impact assessment was based on the annual volume of cereals produced, the annual levels of mycotoxin contamination, and experimental data on the prevention and control measures collected in the course of the MyToolBox project. Results are expressed in terms of reduced volumes of cereals lost, or as additional volumes of cereals available for food meeting the current European legal limits. Results showed that a reduction in crop losses as well as an increase in the volume of crops suitable as food and/or feed is feasible with each proposed prevention or control measure along the supply chain. The impact was the largest in areas and in years with the highest mycotoxin contamination levels but would have less impact in years with low mycotoxin levels. In further research, the impact assessment may be validated using future data from more years and European sites. Decision makers in the food and feed supply chain can use this impact assessment to decide on the relevant prevention and control strategies to apply

Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning

Mycotoxin contamination of corn is a pervasive problem that negatively impacts human and animal health and causes economic losses to the agricultural industry worldwide. Historical aflatoxin (AFL) and fumonisin (FUM) mycotoxin contamination data of corn, daily weather data, satellite data, dynamic geospatial soil properties, and land usage parameters were modeled to identify factors significantly contributing to the outbreaks of mycotoxin contamination of corn grown in Illinois (IL), AFL >20 ppb, and FUM >5 ppm. Two methods were used: a gradient boosting machine (GBM) and a neural network (NN). Both the GBM and NN models were dynamic at a state-county geospatial level because they used GPS coordinates of the counties linked to soil properties. GBM identified temperature and precipitation prior to sowing as significant influential factors contributing to high AFL and FUM contamination. AFL-GBM showed that a higher aflatoxin risk index (ARI) in January, March, July, and November led to higher AFL contamination in the southern regions of IL. Higher values of corn-specific normalized difference vegetation index (NDVI) in July led to lower AFL contamination in Central and Southern IL, while higher wheat-specific NDVI values in February led to higher AFL. FUM-GBM showed that temperature in July and October, precipitation in February, and NDVI values in March are positively correlated with high contamination throughout IL. Furthermore, the dynamic geospatial models showed that soil characteristics were correlated with AFL and FUM contamination. Greater calcium carbonate content in soil was negatively correlated with AFL contamination, which was noticeable in Southern IL. Greater soil moisture and available water-holding capacity throughout Southern IL were positively correlated with high FUM contamination. The higher clay percentage in the northeastern areas of IL negatively correlated with FUM contamination. NN models showed high class-specific performance for 1-year predictive validation for AFL (73%) and FUM (85%), highlighting their accuracy for annual mycotoxin prediction. Our models revealed that soil, NDVI, year-specific weekly average precipitation, and temperature were the most important factors that correlated with mycotoxin contamination. These findings serve as reliable guidelines for future modeling efforts to identify novel data inputs for the prediction of AFL and FUM outbreaks and potential farm-level management practices

Emotional Cues during Simultaneous Face and Voice Processing: Electrophysiological Insights

Both facial expression and tone of voice represent key signals of emotional communication but their brain processing correlates remain unclear. Accordingly, we constructed a novel implicit emotion recognition task consisting of simultaneously presented human faces and voices with neutral, happy, and angry valence, within the context of recognizing monkey faces and voices task. To investigate the temporal unfolding of the processing of affective information from human face-voice pairings, we recorded event-related potentials (ERPs) to these audiovisual test stimuli in 18 normal healthy subjects; N100, P200, N250, P300 components were observed at electrodes in the frontal-central region, while P100, N170, P270 were observed at electrodes in the parietal-occipital region. Results indicated a significant audiovisual stimulus effect on the amplitudes and latencies of components in frontal-central (P200, P300, and N250) but not the parietal occipital region (P100, N170 and P270). Specifically, P200 and P300 amplitudes were more positive for emotional relative to neutral audiovisual stimuli, irrespective of valence, whereas N250 amplitude was more negative for neutral relative to emotional stimuli. No differentiation was observed between angry and happy conditions. The results suggest that the general effect of emotion on audiovisual processing can emerge as early as 200 msec (P200 peak latency) post stimulus onset, in spite of implicit affective processing task demands, and that such effect is mainly distributed in the frontal-central region

Exploration of Shared Genetic Architecture Between Subcortical Brain Volumes and Anorexia Nervosa

In MRI scans of patients with anorexia nervosa (AN), reductions in brain volume are often apparent. However, it is unknown whether such brain abnormalities are influenced by genetic determinants that partially overlap with those underlying AN. Here, we used a battery of methods (LD score regression, genetic risk scores, sign test, SNP effect concordance analysis, and Mendelian randomization) to investigate the genetic covariation between subcortical brain volumes and risk for AN based on summary measures retrieved from genome-wide association studies of regional brain volumes (ENIGMA consortium, n = 13,170) and genetic risk for AN (PGC-ED consortium, n = 14,477). Genetic correlations ranged from − 0.10 to 0.23 (all p > 0.05). There were some signs of an inverse concordance between greater thalamus volume and risk for AN (permuted p = 0.009, 95% CI: [0.005, 0.017]). A genetic variant in the vicinity of ZW10, a gene involved in cell division, and neurotransmitter and immune system relevant genes, in particular DRD2, was significantly associated with AN only after conditioning on its association with caudate volume (pFDR = 0.025). Another genetic variant linked to LRRC4C, important in axonal and synaptic development, reached significance after conditioning on hippocampal volume (pFDR = 0.021). In this comprehensive set of analyses and based on the largest available sample sizes to date, there was weak evidence for associations between risk for AN and risk for abnormal subcortical brain volumes at a global level (that is, common variant genetic architecture), but suggestive evidence for effects of single genetic markers. Highly powered multimodal brain- and disorder-related genome-wide studies are needed to further dissect the shared genetic influences on brain structure and risk for AN