Safe Concurrency Introduction through Slicing

Traditional refactoring is about modifying the structure of existing code without changing its behaviour, but with the aim of making code easier to understand, modify, or reuse. In this paper, we introduce three novel refactorings for retrofitting concurrency to Erlang applications, and demonstrate how the use of program slicing makes the automation of these refactorings possible

Semantic and inferencing abilities in children with communication disorders

Background: Semantic and inferencing abilities have not been fully examined in children with communication difficulties. Aims: To investigate the inferential and semantic abilities of children with communication difficulties using newly designed tasks. Methods & Procedures: Children with different types of communication disorder were compared with each other and with three groups of typically developing children: those of the same chronological age and two groups of younger children. In total, 25 children aged 11 years with specific language impairment and 22 children, also 11 years of age, with primary pragmatic difficulties were recruited. Typically developing groups aged 11 (n = 35; age‐match), and those aged 9 (n = 40) and 7 (n = 37; language similar) also participated as comparisons. Outcomes & Results: For Semantic Choices, children with specific language impairment performed significantly more poorly than 9‐ and 11‐year‐olds, whilst the pragmatic difficulties group scored significantly lower than all the typically developing groups. Borderline differences between specific language impairment and pragmatic difficulties groups were found. For inferencing, children with communication impairments performed significantly below the 11‐year‐old peers, but not poorer than 9‐ and 7‐year‐olds, suggesting that this skill is in line with language ability. Six children in the pragmatic difficulties group who met diagnosis for autism performed more poorly than the other two clinical groups on both tasks, but not statistically significantly so. Conclusions: Both tasks were more difficult for those with communication impairments compared with peers. Semantic but not inferencing abilities showed a non‐significant trend for differences between the two clinical groups and children with pragmatic difficulties performed more poorly than all typically developing groups. The tasks may relate to each other in varying ways according to type of communication difficulty

e-EVN monitoring of M87

M87 is a privileged laboratory for a detailed study of the properties of jets, owing to its proximity (D=16.7 Mpc, 1 mas = 0.080 pc), its massive black hole (~6.0 x 10^9M) and its conspicuous emission at radio wavelengths and above. We started on November 2009 a monitoring program with the e-EVN at 5 GHz, in correspondence of the season of Very High Energy (VHE) observations. Indeed, two episodes of VHE activity have been reported in February and April 2010. We present here the main results of these multi-epoch observations: the inner jet and HST-1 are both detected and resolved in our datasets. We study the apparent velocity of HST-1, which seems to be increasing since 2005, and the flux density variability in the inner jet. All in all, the radio counterpart to this year’s VHE event seems to be different from the ones in 2005 and 2008, opening new scenario for the radio-high energy connection

Health disorders and their association with production and functional traits in Holstein Friesian cows

Logistic regression models were used for studying the relationships between milk yield, body condition score (BCS), somatic cell score and some disorders of periparturient cows (mammary edema and retained placenta) with the occur- rence of ovarian cysts, clinical mastitis and lameness. Data from milk recording (milk yield and somatic cell content) col- lected at nearly monthly intervals (time period: 35 ± 3 d) were merged with BCS recorded on the same dates of milk recording on periparturient heifers, lactating and dry cows, and with health disorders data (retained placenta, severe mammary edema, ovarian cysts and clinical mastitis and lameness) collected during regular herd activities over nearly 3.5 years. Data were from one commercial herd consisting of over 200 lactating dairy cows and exhibiting an average 305-d milk yield of nearly 10,000 kg. A total of 5,315 records from 728 lactations and 429 cows were used in the analy- ses. The time period incidence rate was 11.9%, 6.6% and 4.6% for ovarian cysts, lameness and mastitis, respectively, and the lactational incidence rate was 44.1%, 33.4% and 28.1% for ovarian cysts, lameness and mastitis, respectively. Occurrence of both ovarian cysts and mastitis was more common in the early lactation than afterwards, whereas lame- ness tended to occurr erratically during lactation. The risk of occurrence of mastitis and lameness was lower in primi- parous when compared to multiparous cows. The increase of milk yield increased the risk of occurrence of ovarian cysts (odds ratio: 1.32, P < 0.01) and of mastitis (odds ratio: 1.12, P < 0.10), whereas no significant relationship was found between milk yield and lameness. An increase of somatic cell score was found to be a risk factor for mastitis (odds ratio: 1.36, P<0.01) and for the occurrence of lameness (odds ratio: 1.06, P<0.05). The occurrence of relative risk of disor- ders was not related to BCS at calving, and monthly variation of BCS was related to the onset of mastitis only. Retained placenta did not appear to present a risk factor for the occurrence of diseases of concern, whereas the presence of severe mammary edema at calving increased the risk of mastitis occurrence by nearly 50%. Regular recording of herd health data seems advisable for a better understanding of the relationships between production and functional traits and the occurrence of health disorders

Exposure modelling of transmission towers using street-level imagery and a deep learning object detection model

Exposure modelling is a vital component of disaster risk assessments, providing geospatial information of assets at risk and their characteristics. Detailed information about exposure bring benefits to the spatial representation of a rapidly changing environment and allows decision makers to establish better policies aimed at reducing disaster risk. This work proposes and demonstrates a methodology aimed at linking together volunteered geographic information from OpenStreetMap (OSM), street-level imagery from Google Street View (GSV) and deep learning object detection models into the automated creation of exposure datasets of power grid transmission towers, an asset particularly vulnerable to strong wind among other perils. The methodology is implemented through a start-to-end pipeline that starting from the locations of transmission towers derived from the power grid layer of OSMs world infrastructure, can assign relevant features of the tower based on the identification and classification returned from an object detection model over street-level imagery of the tower, obtained from GSV. The initial outcomes yielded promising results towards the establishment of the exposure dataset. For the identification task, the YOLOv5 model returned a mean average precision (mAP) of 83.57% at intersection over union (IoU) of 50%. For the classification problem, although predictive performance varies significantly among tower types, we show that high values of mAP can be achieved when there is a sufficiently high number of good quality images with which to train the model. (c) 2022, National Technical University of Athens. All rights reserved

Combining phospholipases and a liquid lipase for one-step biodiesel production using crude oils

Background Enzymatic biodiesel is becoming an increasingly popular topic in bioenergy literature because of its potential to overcome the problems posed by chemical processes. However, the high cost of the enzymatic process still remains the main drawback for its industrial application, mostly because of the high price of refined oils. Unfortunately, low cost substrates, such as crude soybean oil, often release a product that hardly accomplishes the final required biodiesel specifications and need an additional pretreatment for gums removal. In order to reduce costs and to make the enzymatic process more efficient, we developed an innovative system for enzymatic biodiesel production involving a combination of a lipase and two phospholipases. This allows performing the enzymatic degumming and transesterification in a single step, using crude soybean oil as feedstock, and converting part of the phospholipids into biodiesel. Since the two processes have never been studied together, an accurate analysis of the different reaction components and conditions was carried out. Results Crude soybean oil, used as low cost feedstock, is characterized by a high content of phospholipids (900 ppm of phosphorus). However, after the combined activity of different phospholipases and liquid lipase Callera Trans L, a complete transformation into fatty acid methyl esters (FAMEs >95%) and a good reduction of phosphorus (P <5 ppm) was achieved. The combination of enzymes allowed avoidance of the acid treatment required for gums removal, the consequent caustic neutralization, and the high temperature commonly used in degumming systems, making the overall process more eco-friendly and with higher yield. Once the conditions were established, the process was also tested with different vegetable oils with variable phosphorus contents. Conclusions Use of liquid lipase Callera Trans L in biodiesel production can provide numerous and sustainable benefits. Besides reducing the costs derived from enzyme immobilization, the lipase can be used in combination with other enzymes such as phospholipases for gums removal, thus allowing the use of much cheaper, non-refined oils. The possibility to perform degumming and transesterification in a single tank involves a great efficiency increase in the new era of enzymatic biodiesel production at industrial scale

Endothelial cells, endoplasmic reticulum stress and oxysterols

Oxysterols are bioactive lipids that act as regulators of lipid metabolism, inflammation, cell viability and are involved in several diseases, including atherosclerosis. Mounting evidence linked the atherosclerosis to endothelium dysfunction; in fact, the endothelium regulates the vascular system with roles in processes such as hemostasis, cell cholesterol, hormone trafficking, signal transduction and inflammation. Several papers shed light the ability of oxysterols to induce apoptosis in different cell lines including endothelial cells. Apoptotic endothelial cell and endothelial denudation may constitute a critical step in the transition to plaque erosion and vessel thrombosis, so preventing the endothelial damaged has garnered considerable attention as a novel means of treating atherosclerosis. Endoplasmic reticulum (ER) is the site where the proteins are synthetized and folded and is necessary for most cellular activity; perturbations of ER homeostasis leads to a condition known as endoplasmic reticulum stress. This condition evokes the unfolded protein response (UPR) an adaptive pathway that aims to restore ER homeostasis. Mounting evidence suggests that chronic activation of UPR leads to cell dysfunction and death and recently has been implicated in pathogenesis of endothelial dysfunction. Autophagy is an essential catabolic mechanism that delivers misfolded proteins and damaged organelles to the lysosome for degradation, maintaining basal levels of autophagic activity it is critical for cell survival. Several evidence suggests that persistent ER stress often results in stimulation of autophagic activities, likely as a compensatory mechanism to relieve ER stress and consequently cell death. In this review, we summarize evidence for the effect of oxysterols on endothelial cells, especially focusing on oxysterols-mediated induction of endoplasmic reticulum stress

Beam-based characterization of plasma density in a capillary-discharge waveguide

Next-generation plasma-based accelerators can push electron bunches to gigaelectronvolt energies within centimeter distances. In these devices, the accelerating force is provided by a driver pulse, either a laser pulse or a particle bunch, that loses its energy into the plasma generating huge electric fields up to tens of GV/m. The stability of such fields strongly depends on plasma density, whose exact value should be precisely known and controlled. However, currently available methods based on spectroscopic or interferometric techniques find it very difficult to measure plasma density lower than 1015–16 cm−3 in capillary-discharge waveguides. Here, we present a novel diagnostic tool that allows us to estimate the average density of a plasma capillary by probing it with an ultra-relativistic electron beam. The plasma density and the generated accelerating field are inferred by analyzing the beam longitudinal phase space after its interaction with the plasma. The results are validated by simulations showing excellent agreement