Nowcasting industrial production using linear and non-linear models of electricity demand

This article proposes different modelling approaches which exploit electricity market data to nowcast industrial production. Our models include linear, mixed-data sampling (MIDAS), Markov-Switching (MS) and MS-MIDAS regressions. Comparisons against autoregressive approaches and other commonly used macroeconomic predictors show that electricity market data combined with an MS model significantly improve nowcasting performance, especially during turbulent economic states, such as those generated by the recent COVID-19 pandemic. The most promising results are provided by an MS model which identifies two volatility regimes. These results confirm that electricity market data provide timely and easy-to-access information for nowcasting macroeconomic variables, especially when it is most valuable, i.e. during times of crisis and uncertainty

Forecasting energy commodity prices: a large global dataset sparse approach

This paper focuses on forecasting quarterly energy prices of commodities, such as oil, gas and coal, using the Global VAR dataset proposed by Mohaddes and Raissi (2018). This dataset includes a number of potentially informative quarterly macroeconomic variables for the 33 largest economies, overall accounting for more than 80% of the global GDP. To deal with the information on this large database, we apply a dynamic factor model based on a penalized maximum likelihood approach that allows to shrink parameters to zero and to estimate sparse factor loadings. The estimated latent factors show considerable sparsity and heterogeneity in the selected loadings across variables. When the model is extended to predict energy commodity prices up to four periods ahead, results indicate larger predictability relative to the benchmark random walk model for 1-quarter ahead for all energy commodities. In our application, the largest improvement in terms of prediction accuracy is observed when predicting gas prices from 1 to 4 quarters ahead

Brief communication: The curious case of the large wood-laden flow event in the Pocuro stream (Chile)

Large wood transported during extreme flood events can represent a relevant additional source of hazards that should be taken into account in mountain environments. However, direct observations and monitoring of large-wood transport during floods are difficult and scarce. Here we present a video of a flood characterised by multiple phases of large-wood transport, including an initial phase of wood-laden flow rarely described in the literature. Estimations of flow velocity and transported wood volume provide a good opportunity to develop models of large-wood-congested transport

mRNA-Sequencing Analysis Reveals Transcriptional Changes in Root of Maize Seedlings Treated with Two Increasing Concentrations of a New Biostimulant

Biostimulants are a wide range of natural or synthetic products containing substances and/or microorganisms that can stimulate plant processes to improve nutrient uptake, nutrient efficiency, tolerance to abiotic stress, and crop quality ( http://www.biostimulants.eu/ , accessed September 27, 2017). The use of biostimulants is proposed as an advanced solution to face the demand for sustainable agriculture by ensuring optimal crop performances and better resilience to environment changes. The proposed approach is to predict and characterize the function of natural compounds as biostimulants. In this research, plant growth assessments and transcriptomic approaches are combined to investigate and understand the specific mode(s) of action of APR, a new product provided by the ILSA group (Arzignano, Vicenza). Maize seedlings (B73) were kept in a climatic chamber and grown in a solid medium to test the effects of two different combinations of the protein hydrolysate APR (A1 and A1/2). Data on root growth evidenced a significant enhancement of the dry weight of both roots and root/shoot ratio in response to APR. Transcriptomic profiles of lateral roots of maize seedlings treated with two increasing concentrations of APR were studied by mRNA-sequencing analysis (RNA-seq). Pairwise comparisons of the RNA-seq data identified a total of 1006 differentially expressed genes between treated and control plants. The two APR concentrations were demonstrated to affect the expression of genes involved in both common and specific pathways. On the basis of the putative function of the isolated differentially expressed genes, APR has been proposed to enhance plant response to adverse environmental conditions

Tracking log displacement during floods in the Tagliamento River using RFID and GPS tracker devices

Large pieces of in-channel wood can exert an important role on the ecological and morphological properties of gravel-bed rivers. On the other side, when transported during flood events, large wood can become a source of risk for sensitive structures such as bridges. However, wood displacement and velocity in river systems are still poorly understood, especially in large gravel-bed rivers. This study focuses on log transport in a valley reach of Tagliamento River (Italy). Log displacement during flood events of different magnitudes recorded from June 2010 to October 2011 has been analysed thanks to the installation of 113 radio frequency identification (RFID) tags and 42 GPS tracker devices in logs of different dimensions. Recovery rates of logs equipped with RFID and GPS trackers were about 43% and 42%, respectively. The GPS devices allowed us to analyse in details the log displacement and transport overtime, indicating a higher log entrainment during rising limb of hydrographs. The threshold for the entrainment of logs from low bars is around 40% of bankfull water stage. No clear relationship was found between the peak of flood and log displacement length and velocity. However, log displacement length and velocity appear significantly correlated to the ratio between the peak of flow and the water stage exceeding the flow duration curve for 25% of time (i.e. the ratio hmax/h25 ratio). Log deposition was observed to occur at the peak flow, and logs transported during ordinary events are preferably deposited on low bars. This study reveals the potentials of GPS tracker devices to monitor the entrainment and movements of logs in large gravel-bed rivers during floods. These observations could be useful for better planning of river management practices and strategies involving the use of large wood pieces and could help for calibrating wood budgets at the reach scale

Characterization of wood-laden flows in rivers

Inorganic sediment is not the only solid‐fraction component of river flows; flows may also carry significant amounts of large organic material (i.e., large wood), but the characteristics of these wood‐laden flows (WLF) are not well understood yet. With the aim to shed light on these relatively unexamined phenomena, we collected home videos showing natural flows with wood as the main solid component. Analyses of these videos as well as the watersheds and streams where the videos were recorded allowed us to define for the first time WLF, describe the main characteristics of these flows and broaden the definition of wood transport regimes (adding a new regime called here hypercongested wood transport). According to our results, WLF may occur repeatedly, in a large range of catchment sizes, generally in steep, highly confined single thread channels in mountain areas. WLF are typically highly unsteady and the log motion is non‐uniform, as described for other inorganic sediment‐laden flows (e.g., debris flows). The conceptual integration of wood into our understanding of flow phenomena is illustrated by a novel classification defining the transition from clear water to hypercongested, wood and sediment‐laden flows, according to the composition of the mixture (sediment, wood, and water). We define the relevant metrics for the quantification and modelling of WLF, including an exhaustive discussion of different modelling approaches (i.e., Voellmy, Bingham and Manning) and provide a first attempt to simulate WLF. We draw attention to WLF phenomena to encourage further field, theoretical, and experimental investigations that may contribute to a better understanding of flows river basins, leading to more accurate predictions, and better hazard mitigation and management strategies

Localization of a gene for nonsyndromic renal hypodysplasia to chromosome 1p32-33.

Nonsyndromic defects in the urinary tract are the most common cause of end-stage renal failure in children and account for a significant proportion of adult nephropathy. The genetic basis of these disorders is not fully understood. We studied seven multiplex kindreds ascertained via an index case with a nonsyndromic solitary kidney or renal hypodysplasia. Systematic ultrasonographic screening revealed that many family members harbor malformations, such as solitary kidneys, hypodysplasia, or ureteric abnormalities (in a total of 29 affected individuals). A genomewide scan identified significant linkage to a 6.9-Mb segment on chromosome 1p32-33 under an autosomal dominant model with reduced penetrance (peak LOD score 3.5 at D1S2652 in the largest kindred). Altogether, three of the seven families showed positive LOD scores at this interval, demonstrating heterogeneity of the trait (peak HLOD 3.9, with 45% of families linked). The chromosome 1p32-33 interval contains 52 transcription units, and at least 23 of these are expressed at stage E12.5 in the murine ureteric bud and/or metanephric mesenchyme. These data show that autosomal dominant nonsyndromic renal hypodysplasia and associated urinary tract malformations are genetically heterogeneous and identify a locus for this common cause of human kidney failure