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Security and Quality of Service (QoS) in communication networks are critical factors supporting end-to-end dataflows in data centers. On the other hand, it is essential to provide mechanisms that enable different treatments for applications requiring sensitive data transfer. Both applications’ requirements can vary according to their particular needs. To achieve their goals, it is necessary to provide services so that each application can request both the quality of service and security services dynamically and on demand. This article presents QoSS, an API web service to provide both Quality of Service and Security for applications through software-defined networks. We developed a prototype to conduct a case study to provide QoS and security. QoSS finds the optimal end-to-end path according to four optimization rules: bandwidth-aware, delay-aware, security-aware, and application requirements (considering the bandwidth, delay, packet loss, jitter, and security level of network nodes). Simulation results showed that our proposal improved end-to-end application data transfer by an average of 45%. Besides, it supports the dynamic end-to-end path configuration according to the application requirements. QoSS also logs each application’s data transfer events to enable further analysis.

Software-defined networking (SDN) is the fastest growing and most widely deployed network infrastructure due to its adaptability to new networking technologies and intelligent applications. SDN simplifies network management and control by separating the control plane from the data plane. The SDN controller performs the routing process using the traditional shortest path approach to obtain end-to-end paths. This process usually does not consider the nodes’ capacity and may cause network congestion and delays, affecting flow performance. Therefore, we evaluate the most conventional routing criteria in the SDN scenario based on Dijkstra’s algorithm and compare the found paths with our proposal based on a cellular genetic algorithm for multi-objective optimization (MOCell). We compare our proposal with another multi-objective evolutionary algorithm based on decomposition (MOEA/D) for benchmark purposes. We evaluate various network parameters such as bandwidth, delay, and packet loss to find the optimal end-to-end path. We consider a large-scale inter-domain SDN scenario. The simulation results show that our proposed method can improve the performance of data streams with TCP traffic by up to 54% over the traditional routing method of the shortest path and by 33% for the highest bandwidth path. When transmitting a constant data stream using the UDP protocol, the throughput of the MOCell method is more than 1.65% and 9.77% for the respective paths.

In cattle, proper rumen functioning and digestion are intimately linked to chewing behavior. Yet, high grain feeding impairs chewing activity, increasing the risk of subacute ruminal acidosis and dysfermentation. This study aimed to screen 9 different phytogenic compounds for their potential to modulate chewing activity, meal size, rumino-reticular short-chain fatty acids (SCFA), and pH during consumption in a first daily meal and shortly thereafter in cattle fed a grain-rich diet. Treatments were control (total mixed ration without phytogenic) or addition of a phytogenic compound at a low or high dose. Phytogenic compounds and doses (all in mg/kg) were angelica root (6.6 and 66), capsaicin (10 and 100), gentian root (6.6 and 66), garlic oil (0.3 and 3), ginger extract (40 and 400), L-menthol (6.7 and 67), mint oil (15.3 and 153), thyme oil (9.4 and 94), and thymol (5 and 50), for the low and high groups, respectively. Before the start of the screening experiment, cows were fed to reach subacute ruminal acidosis conditions, confirmed with the time of ruminal pH5.8 being 655 ± 148.2 min/d. During the screening experiment, the treatments were offered in a controlled meal (2.5 kg of DM for 4 h) as part of the daily diet with 65% concentrate. Each treatment was tested in 4 of the 9 cannulated Holstein cows using an incomplete Latin square design. Ruminal and reticular fluids were sampled before and after each treatment, and data collected before the meal were used as covariates. Chewing and ruminal pH were monitored during the treatment, followed by 2 h of complete feed restriction, and then 4 h of ad libitum feed intake without phytogenic. Data showed that supplementation of angelica root tended to linearly increase rumination time immediately after the first meal when feed was restricted (27.3, 41.9, and 42.6 ± 5.99 min for control, low and high groups, respectively). Capsaicin increased eating time (43.6, 49.4, and 66.4 ± 4.93 min) during consumption but did not affect ruminal total SCFA or mean ruminal pH. Garlic oil reduced the concentration of reticular total SCFA (75.7, 71.3, and 60.1 mM) and tended to decrease ruminal acetate-to-propionate ratio (2.50, 1.78, and 1.87 ± 0.177) with no effect on ruminal pH. The L-menthol affected reticular total SCFA quadratically (76.1, 64.9, and 81.0 ± 4.22%), and ruminal pH responded quadratically when feed was reintroduced ad libitum (6.0, 6.3, and 6.1 ± 0.07). Mint oil did not affect chewing or total SCFA during consumption, but the low dose increased ruminal pH (6.5, 6.7, and 6.5 ± 0.08). Thyme oil tended to lower the severity of ruminal acidosis. Overall, phytogenic compounds demonstrated distinct dose-dependent effects to beneficially influence chewing behavior, modulate fermentation, and mitigate ruminal acidosis in dairy cows under a high-grain challenge diet.

Phytogenic compounds may influence salivation or salivary properties. However, their effects on the bovine salivary proteome have not been evaluated. We investigated changes in the bovine salivary proteome due to transition from forage to high-concentrate diet, with and without supplementation with a phytogenic feed additive. Eight non-lactating cows were fed forage, then transitioned to a 65% concentrate diet (DM basis) over a week. Cows were control (n = 4, CON) or supplemented with a phytogenic feed additive (n = 4, PHY). Proteomic analysis was conducted using liquid chromatography coupled with mass spectrometry. We identified 1233 proteins; 878 were bovine proteins, 189 corresponded to bacteria, and 166 were plant proteins. Between forage and high-concentrate, 139 proteins were differentially abundant (P 0.05), with 48 proteins having a log2FC difference |2|. The salivary proteome reflected shifts in processes involving nutrient utilization, body tissue accretion, and immune response. Between PHY and CON, 195 proteins were differently abundant (P 0.05), with 37 having a log2FC difference |2|; 86 proteins were increased by PHY, including proteins involved in smell recognition. Many differentially abundant proteins correlated (r |0.70|) with salivary bicarbonate, total mucins or pH. Results provide novel insights into the bovine salivary proteome using a non-invasive approach, and the association of specific proteins with major salivary properties influencing rumen homeostasis. SIGNIFICANCE: Phytogenic compounds may stimulate salivation due to their olfactory properties, but their effects on the salivary proteome have not been investigated. We investigated the effect of high-concentrate diets and supplementation with a phytogenic additive on the salivary proteome of cows. We show that analysis of cows' saliva can be a non-invasive approach to detect effects occurring not only in the gut, but also systemically including indications for gut health and immune response. Thus, results provide unique insights into the bovine salivary proteome, and will have a crucial contribution to further understand animal response in terms of nutrient utilization and immune activity due to the change from forage to a high-energy diet. Additionally, our findings reveal changes due to supplementation with a phytogenic feed additive with regard to health and olfactory stimulation. Furthermore, findings suggest an association between salivary proteins and other components like bicarbonate content.

Switching diets from forage to a high-grain (HG) diet increases the risk of rumen fermentation disorders in cattle. However, the effects of the duration of the HG feeding, after the diet switch, on animal behavior and health have received considerably less attention. This experiment primarily aimed to assess the effects of the duration of an HG diet on the chewing, eating, and lying behavior and salivation dynamics in a control group (CON) and a group of cows receiving a phytogenic feed supplement (TRT) at 0.04% (DM basis), which included L-menthol, thymol, eugenol, mint oil, and cloves powder. The experiment was a crossover design with nine non-lactating cows, and two experimental periods with an intermediate washout of four weeks. In each period, the cows were first fed a forage diet for a week to collect baseline measurements representing week 0; then, the diet was switched over a week to HG (65% concentrate), which was fed for four continuous weeks (week 1, week 2, week 3, and week 4 on an HG diet, respectively). The cows were divided in two groups of four and five animals and were randomly allocated to CON or TRT. The data analysis revealed that at the start of the HG feeding, the dry matter intake and the cows’ number of lying bouts increased, but the eating time, rumination time, and meal frequency decreased, resulting in a greater eating rate. We also found that an advanced duration on an HG diet further decreased the rumination time, total chewing time, chewing index, and sorting in favor of short feed particles, with the lowest values in week 4. The feed bolus size increased but feed the ensalivation decreased in week 4 compared to week 0. The dietary switch increased salivary lysozyme activity, and the advanced duration on the HG diet increased salivary pH, but salivary phosphate decreased in weeks 1 and 2 on the HG diet. Supplementation with TRT increased sorting in favor of physically effective NDF (peNDF) in week 2 and increased salivary pH in week 4 on an HG diet. Overall, the negative effects of the HG diet in cattle are more pronounced during the initial stage of the HG feeding. However, several detrimental effects were exacerbated with the cows’ advanced duration on feed, with host adaptive changes still observed after 3 and 4 weeks following the diet switch. The TRT mitigated some of the negative effects through the temporal improvement of the salivary properties and the intake of peNDF, which are known to modulate rumen fermentation.

Scientific applications requires to process, analyze and transfer large volumes of data in the shortest possible time from distributed data sources. In order to improve their performance, it is necessary to provide them with specific QoS parameters. On the other hand, SDN is presented as a new paradigm of communications networks that facilitates the management of the communications infrastructure and consequently allows to dynamically incorporate QoS parameters to the applications running in this type of network. With both these paradigms in mind, we conducted this research to answer the following questions: Do scientific applications that are running in an SDN-Enabled distributed data centers improve their performance? Do they consider network QoS parameters for job scheduling? The methodology used was to consult articles in specialized databases containing the keywords SDN and for scientific applications: HPC and Big Data. Then, we analyzed the articles where these keywords intersect with some of the parameters related to QoS in communications networks. Also, we reviewed QoS proposals in SDN to identify the advances in this research area. The results of this paper are: i) QoS is an open issue to incorporate in scientific applications that are running in an SDN ii) we identified the challenges to join both these paradigms, and iii) we present a strategy to provide QoS to scientific applications that are being executed among SDN-Enabled distributed data centers.

Internet-of-Things (IoT) environment has a dynamic nature with high risks of confidentiality, integrity, and availability violations. The loss of information, denial of access, information leakage, collusion, technical failures, and data security breaches are difficult to predict and anticipate in advance. These types of nonstationarity are one of the main issues in the design of the reliable IoT infrastructure capable of mitigating their consequences. It is not sufficient to propose solutions for a given scenario, but mechanisms to adapt the current solution to changes in the environment. In this article, we present a multicloud storage architecture called WA-MRC-RRNS that combines the weighted access scheme, threshold secret sharing, and redundant residue number system with multiple failure detection/recovery mechanisms and homomorphic ciphers. We provide a theoretical analysis of the probability of information loss, data redundancy, speed of encoding/decoding, and show how to dynamically configure parameters to cope with different objective preferences, workloads, and cloud properties. We propose a multiobjective optimization mechanism to adjust redundancy, encryption–decryption speed, and data loss probability. Comprehensive experimental analysis with real data shows that our approach provides a secure way to mitigate the uncertainty of the use of untrusted and not reliable IoT infrastructure.

Microbial composition and activity in the gastrointestinal tract (GIT) of cattle has important implications for animal health and welfare, driving the focus of research toward ways to modify their function and abundance. However, our understanding of microbial adaption to nutritional changes remains limited. The aim of this study was to examine the progressive mechanisms of adaptation in the rumen and hindgut of cattle receiving increasing amounts of starch with or without dietary supplementation of a blended phytogenic feed additive (PFA; containing menthol, thymol and eugenol). We used 16S rRNA gene amplicon sequencing to assess the microbial composition and predicted metabolic pathways in ruminal solid and liquid digesta, and feces. Furthermore, we employed targeted liquid chromatography-mass spectrometry methods to evaluate rumen fluid metabolites. Results indicated a rapid microbial adaptation to diet change, starting on the second day of starch feeding for the particle associated rumen liquid (PARL) microbes. Solid rumen digesta- and feces-associated microbes started changing from the following day. The PARL niche was the most responsive to dietary changes, with the highest number of taxa and predicted pathways affected by the increase in starch intake, as well as by the phytogenic supplementation. Despite the differences in the microbial composition and metabolic potential of the different GIT niches, all showed similar changes toward carbohydrate metabolism. Metabolite measurement confirmed the high prevalence of glucose and volatile fatty acids (VFAs) in the rumen due to the increased substrate availability and metabolic activity of the microbiota. Families Prevotellaceae, Ruminococcaceae and Lachnospiraceae were found to be positively correlated with carbohydrate metabolism, with the latter two showing wide-ranging predicted metabolic capabilities. Phytogenic supplementation affected low abundant taxa and demonstrated the potential to prevent unwanted implications of feeding high-concentrate diet, such as reduction of microbial diversity. The inclusion of 50% concentrate in the diet caused a major shift in microbial composition and activity in the GIT of cattle. This study demonstrated the ability of microorganisms in various GIT niches to adjust differentially, yet rapidly, to changing dietary conditions, and revealed the potential beneficial effects of supplementation with a PFA during dietary adaptation.

People with opioid use disorder (OUD) experience lower quality of life (QoL) than the general population, but buprenorphine treatment for OUD could help improve QoL of individuals with OUD. Thus, we conducted a systematic review and meta-analysis of the impact of buprenorphine on QoL among people with OUD.Seven databases were searched through August 2020. We included English-language studies with pre- and post- QoL assessments internationally. Standardized mean differences were calculated for five domains of QoL measures using a random effects model for correlated effect sizes with robust variance estimation. Meta-regression was used to assess variation in effect sizes based on QoL domain, treatment, and patient factors.Twenty-one peer-reviewed studies from twelve countries were included. Only three studies included a no-treatment control group and five studies assigned groups using randomization. Improvements between baseline and follow-up were observed across all five domains of QoL measures (overall, physical, psychological, social, and environmental). The certainty of evidence was low for all domains of QoL, and very low for environmental QoL. We did not observe differences in the effect of buprenorphine on QoL by QoL domain, duration, dose, participant characteristics, or adjunctive counseling services.Buprenorphine treatment likely improves overall, physical, psychological, and social QoL, and may improve environmental QoL, for individuals with OUD. Findings are limited by study quality, including lack of control groups and incomplete reporting. Future studies with more rigorous methods and comprehensive reporting are needed.

This study evaluated the effects of duration of high-concentrate feeding on ruminal and fecal fermentation profile, as well as selected systemic health biomarkers in nonlactating cows supplemented with or without a phytogenic feed additive (PHY). In addition, ruminal degradation kinetics and total-tract nutrient digestibility were evaluated when feeding either only forage or a high-concentrate diet. Nine nonlactating, cannulated Holstein cows were used in a crossover design. Each period included 1 wk of forage feeding (wk 0), diet transition, and 4 wk on the high-concentrate diet (1, 2, 3 and wk 4; 65% dry matter basis). Cows received PHY or not (control). Compared with wk 0, from wk 1 onward, cows on high concentrate showed greater reticular, ruminal, and fecal total volatile fatty acids (VFA), with a greater level of VFA in the rumen than in the hindgut. However, ruminal fermentation was modulated differently by PHY, which showed increased total VFA in wk 1 and increased butyrate in wk 2 in the particle-associated fluid of rumen. In the hindgut, PHY increased propionate in wk 3. Cows fed a high-concentrate diet from wk 1 and onward also showed greater ruminal lactate, as well as lower ruminal and fecal pH, independent of PHY. In addition, compared with cows in wk 1 on a high-concentrate diet, cows in wk 4 had a greater total VFA in free fluid of the rumen and lower fecal pH. Compared with cows at wk 0, cows at wk 1 on high concentrate onward showed greater serum amyloid A and greater activity of glutamate dehydrogenase. In contrast, the high-concentrate diet decreased in situ ruminal degradability of grass silage but increased degradability of corn grain as well as total-tract nutrient digestibility, with total-tract neutral detergent fiber digestibility being greater for cows on the PHY treatment. Overall, from the start of high-concentrate feeding, gut fermentation increased, but differently according to location or PHY, with a stronger build-up of VFA in the rumen compared with the hindgut. In addition, a longer duration on high concentrate exacerbated gut acidification. The enhancing effects of PHY on total VFA and butyrate in particle-associated fluid of the rumen suggest beneficial effects of PHY on particle-associated bacteria, likely contributing to the increased neutral detergent fiber digestibility. The greater production of ruminal butyrate with PHY may be beneficial for the host, given the health benefits of this acid, but more research is needed to elucidate the effects on gut microbiota and the effects of increased butyrate in nonlactating dairy cows.

The aim was to evaluate the effect of changing from forage to a high grain diet on chewing, feed sorting and lying behavior of cows supplemented with or without a phytogenic feed additive. Nine cows were blocked in two groups and used in a change-over design. Each experimental run consisted of one week of forage feeding, one week of diet transition, and four weeks of high grain feeding (65% concentrate). During the washout period of 10 weeks between the two runs, cows grazed on pasture. Cows were fed either a control diet (CON) or a diet with a phytogenic additive (PHY) based on menthol, thymol and eugenol. Data on chewing, feed sorting and lying behavior were analyzed using SAS with week of feeding and supplementation as fixed effects, and cow as random effect. Data across weeks from the same cow were processed using a first order variance-covariance structure matrix taking into account that the covariance decays with time. We found a reduction (P < 0.01) in rumination time by 53% with diet change. Within the high grain feeding, rumination reached lowest value in the second week (160 min/d). The high grain diet increased (P < 0.01) selection for long size particles by 20%. Although lying time was not affected immediately after diet change, it increased (P < 0.01) by 8% from the second week of high grain consumption. In the fourth week of grain feeding, there was a tendency for PHY to increase rumination (P = 0.07) and total chewing time (P = 0.10), but with no effect on sorting for fiber or lying time. The high grain diet decreased chewing and standing time, and increased sorting for fibrous ingredients especially after one week of feeding. The phytogenic feed additive may contribute to stimulate chewing in long term supplementation.

Modern algorithms for symmetric and asymmetric encryptions are not suitable to provide security of data that needs data processing. They cannot perform calculations over encrypted data without first decrypting it when risks are high. Residue Number System (RNS) as a homomorphic encryption allows ensuring the confidentiality of the stored information and performing calculations over encrypted data without preliminary decoding but with unacceptable time and resource consumption. An important operation for encrypted data processing is a number comparison. In RNS, it consists of two steps: the computation of the positional characteristic of the number in RNS representation and comparison of its positional characteristics in the positional number system. In this paper, we propose a new efficient method to compute the positional characteristic based on the approximate method. The approximate method as a tool to compare numbers does not require resource-consuming non-modular operations that are replaced by fast bit right shift operations and taking the least significant bits. We prove that in case when the dynamic range of RNS is an odd number, the size of the operands is reduced by the size of the module. If one of the RNS moduli is a power of two, then the size of the operands is less than the dynamic range. We simulate proposed method in the ISE Design Suite environment on the FPGA Xilinx Spartan-6 SP605 and show that it gains 31% in time and 37% in the area on average with respect to the known approximate method. It makes our method efficient for hardware implementation of cryptographic primitives constructed over a prime finite field.

Saliva facilitates feed ingestion, nutrient circulation, and represents an important pH buffer for ruminants, especially for cattle fed high-concentrate diets that promote rumen acidification. This experiment evaluated the short-term effects of nine phytogenic compounds on salivation, saliva physico-chemical composition as well as ingested feed boli characteristics in cattle. A total of nine ruminally cannulated Holstein cows were used. Each compound was tested in four of these cows as part of a high-concentrate meal (2.5 kg of total mixed ration in dry matter basis for 4 h) in low or high dose, and was compared to a control meal without compound. Saliva was sampled orally (unstimulated saliva) for physico-chemical composition analysis. Composition of the ingested saliva (stimulated saliva), salivation and feed boli characteristics were assessed from ingesta collected at the cardia during the first 30 min of the meal. Analysis of unstimulated saliva showed that supplementation with capsaicin and thyme oil increased buffer capacity, while supplementation with thymol, L-menthol and gentian root decreased saliva pH. In addition, supplementing angelica root decreased saliva osmolality. Regression analysis on unstimulated saliva showed negative associations between mucins and bicarbonate as well as with phosphate when garlic oil, thyme oil or angelica root was supplemented. Analysis of stimulated saliva demonstrated that supplementation with garlic oil increased phosphate concentration, thyme oil tended to increase osmolality, capsaicin and thymol increased buffer capacity, and ginger increased phosphate content. Furthermore, salivation rate increased with ginger and thymol, and tended to increase with garlic oil, capsaicin, L-menthol and mint oil. Feed ensalivation increased with capsaicin. A positive association was found between feed bolus size and salivation rate when any of the phytogenic compounds was supplemented. Overall, our results demonstrate positive short-term effects of several phytogenic compounds on unstimulated and stimulated saliva physico-chemical properties, salivation or feed boli characteristics. Thus, the phytogenic compounds enhancing salivary physico-chemical composition have the potential to contribute to maintain or improve ruminal health in cattle fed concentrate-rich rations.

A Digital Twin (DT) is a set of computational models representing real-time physical objects and processes in a digital world. The increasing adoption of this paradigm by the major industrial equipment vendors to simulate real-time working conditions and perform smart decision-making, established the Smart Factory Digital Twins architectures, where a set of DTs published as microservices interact with each other exchanging information by streaming technology. In this sense, a fundamental problem consists of selecting adequate computational resources to simulate the physical objects. In an Infrastructure as a Service (IaaS) cloud for DTs, the allocation focuses on distributing the jobs of the set into the virtual machine instances in a way that computational resources demand is satisfied and the cost is minimized. In this paper, we propose a set of algorithms based on heuristics, metaheuristics, and Mixed Integer Programming to find low-cost solutions. The performance of algorithms is evaluated using Amazon EC2 instances and DT jobs with randomly generated bandwidth, memory, and processor requirements. The experimental results show that the proposed approaches based on bin packing, genetic algorithms, partition, filtering, set coverage, and branch and bound strategies present a competitive performance in the workload allocation of the computational set of jobs of a DT into an IaaS cloud environment. Our allocation heuristic-based techniques allow considerable cost savings in medium and large periods concerning standard approaches such as local search.

Physical effective fiber in the diet promotes chewing, contributing to the regulation of ruminal pH through saliva production, which leads to rumen health. However, lower dietary fiber content in high-grain diets may reduce rumination time and compromise ruminal pH regulation. The objective of this experiment was to evaluate rumination behavior and rumino-reticular pH variations during an 8-day adaptation to a 65% concentrate diet. For this study nine ruminally cannulated non-lactating Holstein cows were used. Prior to the initiation of the adaptation, cows were transitioned from a forage-only grass silage diet to a 65% DM concentrate diet over eight days. Rumination was monitored using RumiWatch halters (RumiWacthSystem ITIN+HOCH). Rumino-reticular pH was measured using eCow indwelling pH systems in five of nine cows recording data every 15 minutes. Data were analysed with SAS, the statistical model included day as fixed effect and cow was considered as random effect. Adaptation days had an effect (P < 0.01) on rumination time, number of rumination chews per minute, and mean daily (rumino-reticular) pH. Especially, rumination time decreased from 439 to 327±62.8 minutes per day from day 1 to 8, respectively. Concomitantly, rumination chews per minute decreased from 68.8 to 65.6±2.06, and mean daily pH decreased from 6.54 and 6.26±0.07, respectively. Nevertheless, daily dry matter intake (P = 0.23) and eating time (P = 0.37) were not affected during the adaptation period. In conclusion, adaptation to a high-grain diet and the associated decrease in physically effective fiber gradually reduced chewing activity and ruminal/reticular pH. However, compared to the forage-only diet, significant reduction in rumination time was only noted at the 65% concentrate level.

Intensive dairy production systems encourage feeding of high-concentrate diets to increase milk production efficiency. However, there is limited information regarding the effect of a SARA challenge diet on chewing behavior and rumino-reticular short chain fatty acid (SCFA) concentration. The objective of this study was to evaluate chewing activity and SCFA production in the rumen and reticulum, using nine ruminally cannulated non-lactating Holstein cows. Preceding the trial, cows were transitioned from 100% forage to 65% DM concentrate over eight days. Trial day 1 began once cows reached 65% DM concentrate and monitoring during 23 days. RumiWatch halters were used to monitor chewing activity. SCFA analysis was conducted on rumen and reticulum fluid collected 4 hours after feeding using gas chromatography. Data were analyzed with SAS, with the fixed effect of days and cow as random effect. There was an increase in DM intake during the first four hours after feeding: 1.97 and 2.25 ± 0.12 kg for day 1 and 23, respectively (P < 0.05). There was no difference in rumination time (P = 0.16) with 29 ± 8.5 minutes during the first four hours of feeding. However, chewing index (P = 0.08) tended to decrease from 36.7 to 29.4 ± 4.4 minutes of chewing/kg of DM for day 1 and 23, respectively. Moreover, on day 1, propionate increased from 19.9 ± 1.02 to 20.1 ± 1.02% and from 24.04 ± 0.93 to 25.4 ± 1.02% compared to day 23 for rumen and reticulum, respectively (P < 0.05). In addition, from day 1 to day 23, the rumen and reticulum acetate/propionate ratio declined from 3.2 ± 0.15 and 3.1 ± 0.1, to 2.5 ± 0.15, respectively, and reticulum SCFA decreased from 87 to 67 µmol/g, respectively. Overall, there was no effect of the 23-day SARA challenge diet on chewing activity. However, there was a reduction of SCFA concentration in reticulum, which may be due to enhanced SCFA absorption or increased feed bolus neutralizing capacity.

Salivary secretions are essential for the regulation of digestive processes, as well as rumen and cow health. This research evaluated the effects of the duration of high-grain feeding, and of the time relative to a meal, on salivation, saliva properties, feed bolus characteristics, chewing activity, ruminal and reticular volatile fatty acids, as well as salivary and ruminal pH. Nine nonlactating cannulated Holstein cows were sampled at 1 and 23 d after transition to a 65% grain diet (short term and long term, respectively). Both before and after a controlled meal (2.5 kg of dry matter, offered over 4 h), unstimulated saliva was taken orally for composition analysis. Stimulated salivation and feed boli characteristics were evaluated by collection of ingesta from cardia during 30 min. Chewing and ruminal pH were measured during the controlled meal and for a total of 6 h thereafter. Results from unstimulated saliva showed no effect of the duration of high-grain feeding on bicarbonate, phosphate, total proteins, mucins, lysozyme, and buffer capacity, but increased osmolality at the long term. Lysozyme activity did not differ with high-grain feeding duration, but tended to be lower after the meal. In contrast to short-term-fed cows, the long-term-fed cows increased both meal consumption and feed bolus size, but decreased chewing and feed ensalivation (5.2 vs. 4.6 ± 0.50 g of saliva/g of dry matter), and had lower pH of the stimulated saliva (7.00 vs. 6.67 ± 0.076). These cows also had decreased chewing index (66.5 vs. 45.4 min/kg of neutral detergent fiber), and despite the increase in stimulated saliva buffer capacity (0.027 vs. 0.039 ± 0.006), mean ruminal pH decreased (6.31 vs. 6.11 ± 0.065) during ad libitum feeding. Both in the rumen and reticulum, the concentration of total volatile fatty acids was lower and propionate proportion was higher at the long term. Linear regression analyses revealed a positive influence of the flow rates of salivary bicarbonate and phosphate on ruminal pH during the short term. For every 1-mol increment in the flow of bicarbonate or phosphate, ruminal pH increased by 0.062 or 0.439 units, respectively. Overall, salivary buffers are key determinants of ruminal pH regulation, especially during short-term grain feeding. However, in the long term, ruminal pH drop during ad libitum feeding was stronger, and this effect seems to be exacerbated by increased feed bolus size, accompanied by reductions in feed ensalivation, stimulated saliva pH, and chewing index.

Multi-unmanned aerial vehicle (multi-UAV) systems have become popular in applications such as precision agriculture, remote sensing, and pollution monitoring. Commonly, multi-UAV systems require to reach and maintain a specific flight formation during mission execution. This can be achieved by using a distributed UAV formation control strategy in which each UAV has a flight controller whose function is to calculate the control actions for the UAV actuators such that the UAV formation is maintained. To perform this task, the control strategy requires the reliable and timely exchange of information within the UAV formation. The information that is needed by the controller is commonly referred to as state information (SI). It has been assumed that SI can be properly disseminated by means of multi-hop communications, i.e., by deploying a flying ad-hoc network (FANET). In this sense, multi-hop broadcast protocols (MBPs) that were previously proposed for mobile and vehicular ad-hoc networks seem to be suited for this task. However, previous work dealing with distributed UAV formation control has made communication and networking assumptions that would be hard to fulfill in actual FANET deployments. Moreover, the efficiency of the MBPs to disseminate SI within a FANET remains unexplored. The goal of this paper is to analyze how the network performance offered by different MBPs impacts the effectiveness of distributed UAV formation control to maintain UAV formation. An evaluation framework to perform this task is proposed in this paper. The simulation results demonstrate the relevance of MBP performance in SI message dissemination and thus in the ability of the controller to maintain a formation.

Nowadays, industrial robot applications are required to customize the manufacturing of diverse products to reduce both downtime and standoff variability. The two methods for robot programming are regularly implemented to carry out that goal. The first one, online programming, requires a specialized operator to guide the robot through desired poses, and the quality of the result is directly limited by his skill level. On the other side, off-line programming uses software packaging to simulate robot applications before their implementation. It reduces downtime with respect to online programming but requires additional calibration steps. In this paper, a novel procedure is presented to obtain accurate surface approximations by combining linear interpolations generated during online programming with a triangulated surface reconstruction of a workpiece surface representation. The method uses a point cloud instead of a predefined mesh to reduce the standoff variability between the robotic tool center point and the surface. Additionally, a technique based on a penalized least squares method was implemented to smooth the trajectory, including position and orientation. The proposed methodology was validated with three well-known case studies involving real trajectories, with simulations in MATLAB and RobotStudio, as well as by experimentation with an industrial ABB robot. The quality of the results demonstrates a great efficiency of this method for path generation based on surface reconstruction.

Feeding with high-concentrate diets increases the risk of subacute ruminal acidosis (SARA). This experiment was conducted to evaluate whether supplementing a phytogenic feed additive based on L-menthol, thymol, eugenol, mint oil (Mentha arvensis) and cloves powder (Syzygium aromaticum) (PHY) can amend the ruminal fermentation profile, modulate the risk of SARA and reduce inflammation in cattle. The experiment was designed as a crossover design with nine non-lactating Holstein cows, and was conducted in two experimental runs. In each run, cows were fed a 100% forage diet one week (wk 0), and were then transitioned stepwise over one week (0 to 65% concentrate, wk adapt.) to a high concentrate diet that was fed for 4 weeks. Animals were fed diets either with PHY or without (CON). The PHY group had an increased ruminal pH compared to CON, reduced time to pH < 5.8 in wk 3, which tended to decrease further in wk 4, reduced the ruminal concentration of D-lactate, and tended to decrease total lactate (wk 3). In wk 2, PHY increased acetate, butyrate, isobutyrate, isovalerate, and the acetate to propionate ratio compared to CON. Phytogenic supplementation reduced inflammation compared to CON in wk 3. Overall, PHY had beneficial effects on ruminal fermentation, reduced inflammation, and modulated the risk of SARA starting from wk 3 of supplementation.

The rumen epithelium has a pivotal role in nutrient uptake and host health. This study aimed to explore the role of microRNAs (miRNAs) in the epithelial transcriptome during diet transition from forage to high-grain feeding and the modulation through supplementation with a phytogenic feed additive. Rumen biopsies were collected from 9 ruminally-cannulated non-lactating Holstein cows fed a baseline forage diet (FD) and then transitioned to high-grain feeding (HG; 65% concentrate on a dry matter basis). Cows were randomly allocated into a control group (CON, n = 5) and a group supplemented with a phytogenic feed additive (PHY, n = 4). MiRNA and mRNA sequencing was performed in parallel and transcripts were analyzed for differential expression, pathway enrichment analysis, and miRNA-mRNA interaction networks. We identified 527 miRNAs shared by all samples of the rumen epithelium, from which, bta-miR-21-5p, bta-miR-143 and bta-miR-24-3p were the most expressed. Six miRNAs were differentially expressed between CON and PHY and 8 miRNAs between FD and HG feeding, which were mainly associated with fat metabolism. Transcriptome analysis identified 9481 differentially expressed genes (DEGs) between FD and HG, whereas PHY supplementation resulted in 5 DEGs. DEGs were mainly involved in epithelium development and morphogenesis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with tricarboxylic acid and short chain fatty acid (SCFA) metabolism were enriched in DEGs between diets. MiRNA target prediction and anti-correlation analysis was used to construct networks and identify DEGs targeted by DE miRNAs responsive to diet or PHY. This study allowed the identification of potential miRNA regulation mechanisms of gene expression during transition from FD to HG feeding and phytogenic supplementation, evidencing a direct role of miRNAs in host responses to nutrition.

Modern dairy production systems require larger inputs of energy in diets to increase milk yield. Therefore, dairy cows are at risk of experiencing subacute ruminal acidosis (SARA). The objective of this study was to evaluate grains and forage rumen degradability in cows fed different diets supplemented with a phytogenic (PHY) feed additive. The experiment was conducted with nine rumen-cannulated non-lactating Holstein cows blocked in two groups of four and five animals, and were part of a cross-over design. This study consisted in 2 runs separated by a 12-week washout period, in which cows grazed on pasture. Each experimental run had one week of forage (F) feeding, one week of transition to a high grain (HG) diet, and four weeks of HG (65:35 concentrate to forage ratio in dry matter basis). Cows were supplemented with PHY (a blend of menthol and thymol) or a control carrier (CON) from week F. Corn and wheat grain were ground through a 4 mm screen, while grass silage was ground through a 6 mm screen. Sampling for in situ degradability was performed in F and in week four of HG diet. Data were analyzed with SAS with week of feeding and supplementation as fixed effects and cow as random effect. Corn and wheat 24-h dry matter (DM) and organic matter (OM) degradability increased during HG diet compared with F (P < 0.05), grass silage DM and OM 48-h degradability was reduced by HG diet compared to F (P < 0.01). Additionally, wheat grain 24-h OM degradability was higher for PHY compared to CON under F and HG diet conditions (P = 0.05). Overall, diet composition and SARA conditions can influence grains and fiber degradability in the rumen.

This article proposes a framework to design and implement e- Health interventions in a comprehensive manner. We draw on complexity science to study the interplay of the ecosystem, the behavior and interactions among its agents. We provide a platform to estimate the Quality of Experience (QoE) to assess the relationship between technology and human factors involved in e-Health projects. Our aim is to estimate QoE in e-Health ecosystems from the perspective of complexity by adopting a methodology that uses fuzzy logic to study the behavior of the ecosystem’s agents. We apply the proposed framework to a remote diagnosis case by means of an ultrasound probe through a satellite link. Despite the ambiguities for determining QoE, the experiment demonstrates the applicability of the framework and allows to stressing the importance of human factors in the implementation of e-Health projects. En este artículo se propone un marco de referencia para diseñar e implementar intervenciones de e-Salud de una manera integral. Recurrimos a la ciencia de la complejidad para estudiar la interacción de los agentes del ecosistema. Para ello, proporcionamos una plataforma para estimar la Calidad de Experiencia (o QoE, por sus siglas en inglés) para evaluar la relación entre la tecnología y los factores humanos que intervienen en los proyectos de e-Salud. Nuestro objetivo es estimar la QoE en los ecosistemas de e-Salud desde la perspectiva de la complejidad mediante la adopción de una metodología que utiliza la lógica difusa para estudiar el comportamiento de los agentes del ecosistema. Aplicamos el marco propuesto a un caso de diagnóstico remoto por medio de una sonda de ultrasonido a través de un enlace por satélite. A pesar de las ambigüedades involucradas en la determinación de calidad de la experiencia, el experimento demuestra la aplicabilidad del marco de referencia propuesto y permite subrayar la importancia de los factores humanos en la implementación de proyectos de e-Salud.

Phytogenic compounds, e.g. secondary plant compounds and essential oils, are often used as supplements in ruminant nutrition to modulate microbial fermentation under ruminal dysbiosis associated with high grain feeding. The aim of this study was to evaluate the short-term effects of phytogenic compounds on volatile fatty acids (VFA) production and composition in cows affected by subacute ruminal acidosis (SARA). Nine substances were tested at low and high dosage (1x and 10x respectively) using nine non-lactating ruminally cannulated Holstein cows, adapted to a 65% concentrate and 35% silage (grass and corn) ration (DM basis). Feeding was restricted for nine hours before providing the substance mixed with five kg of TMR. Each substance and dosage was tested individually on four cows (n = 4/compound/dose) over a period of four hours. Rumen and reticulum fluid were collected before the treatment, and four hours after feeding. VFA were measured with gas chromatography. Ruminal pH was continuously recorded (eCow indwelling pH systems). Data were analyzed with the Proc Mixed procedure of SAS. Seven out of nine compounds showed an effect or a trend on VFA measured, both in rumen and reticulum. Acetic acid in rumen fluid decreased with garlic oil, while low dose mint oil increased its concentration (P = 0.06 and P = 0.01, respectively). Low dose mint oil (P < 0.01) and L-menthol (P = 0.03) both increased the A:P ratio, whereas garlic oil tended towards a decrease in the A:P ratio. Garlic oil and ginger showed negative correlations between total VFA and mean ruminal pH (P = 0.03 and P < 0.01, respectively). Our results suggest that phytogenic compounds can modulate microbial activity within four hours of feeding. The use of phytogenic compounds may have beneficial effects on microbial fermentation under low pH conditions associated with high grain feeding.

Cloud storage is one of the most popular models of cloud computing. It benefits from a shared set of configurable resources without limitations of local data storage infrastructures. However, it brings several cybersecurity issues. In this work, we address the methods of mitigating risks of confidentiality, integrity, availability, information leakage associated with the information loss/change, technical failures, and denial of access. We rely on a configurable secret sharing scheme and error correction codes based on the Redundant Residue Number System (RRNS). To dynamically configure RRNS parameters to cope with different objective preferences, workloads, and cloud properties, we take into account several conflicting objectives: probability of information loss/change, extraction time, and data redundancy. We propose an approach based on a genetic algorithm that is effective for multi-objective optimization. We implement NSGA-II, SPEA2, and MOCell, using the JMetal 5.6 framework. We provide their experimental analysis using eleven real data cloud storage providers. We show that MOCell algorithm demonstrates best results obtaining a better Pareto optimal front approximation and quality indicators such as inverted generational distance, additive epsilon indicator, and hypervolume. We conclude that multi-objective genetic algorithms could be efficiently used for storage optimization and adaptation in a non-stationary multi-cloud environment.

Recurrence of papillary thyroid carcinoma after initial treatment is challenging. Surgical reintervention is recommended, but cure after surgery in uncertain and surgical morbidity may be high. This study evaluates the effect of compartment-oriented lymph node dissection (LND) on clinical and biochemical cure rate as well as the related complications. All patients who underwent LND for recurrent papillary thyroid carcinoma between 2000 and 2015 were included. Demography, the extent of the initial surgery, usage of 131I, the pattern of recurrence, diagnosis, details of the surgical reintervention, histological findings, surgical morbidity, and clinical and biochemical outcomes were analyzed. There were 11 (12.7%) males and 75 (87.2%) females with a mean age of 42.8 ± 14.6 years. Seventy-seven patients had undergone total thyroidectomy and in 67 (77.9%) some type of LN resection. In 76 (88.3%), 131I was administered after the initial surgery. We localized suspicious lymph nodes by US in all patients, and metastases were documented before surgery by FNA in 63. Seven (8.13%) patients underwent central LND, 63 (73.2%) lateral LND and 16 (18.6%) both, central and lateral LND. Major complications occurred in 6 patients (6.9%). Sixty-two (72.0%) patients received 131I after surgery. A second surgical re-exploration was performed in 30 (34.8%) patients, and 7 patients required 3 or more additional LND. In a mean follow-up of 59.4 ± 39 months, 51 (59.3%) patients are clinically, radiologically and biochemically free of disease. In this series, compartment-oriented lymph node resection of recurrent papillary thyroid carcinoma leads to a final clinical and biochemical disease-free status of 59.3% with 6.9% of major complications.

Cloud storages delivered as services are made available to the general public. As cloud storage provider prices become low, they have moved into the mainstream of storage technology. However, there are various factors that cause many potential users do not use it intensively. There exist high risks for confidentiality, integrity, and availability violation associated with the loss of information, denial of access, technical failures, etc. In this article, we propose a two-level secret sharing scheme (TL-SSS) based on a residue number system (RNS) for a configurable, reliable, and secure distributed data storage. RNS moduli of a special type increase the reliability of the data storage system and reduce the computational complexity of the data encoding and decoding from linear-logarithmic to linear. TL-SSS is the weighted data access structure. It creates and distributes data shares according to the characteristics of the cloud storages under various scenarios. We provide a solution that improves system reliability without reduction of the security level. In contrast to classical solutions, it can restore the data with less available shares than the state-of-the-art approaches.

Despite all the benefits a cloud data storages offer to customers, there is a high risk of breach of confidentiality, integrity, and availability related with the uncertainty of errors and falsifications, loss of information, denial of access for a long time, information leakage, conspiracy, and technical failures. In this article, we propose a configurable, reliable, and secure distributed data storage scheme with improved data redundancy, reliability, and encoding/decoding speed. Our system utilizes a Polynomial Residue Number System (PRNS) with a new method of error correction codes and secret sharing schemes. We introduce the concept of an approximate value of a rank (AR) of a polynomial. It reduces the computational complexity of the encoding/decoding and PRNS coefficients size. Based on the properties of the approximate value and PRNS, we introduce the AR-PRNS method for error detection, correction, and controlling computational results with capabilities of scalable parallel computing. We provide a theoretical basis to configure and optimize the redundancy of stored data and encoding/decoding speed to cope with different objective preferences, workloads, and storage properties. Theoretical analysis shows that, by appropriate selection of AR-PRNS parameters, the proposed scheme increases the safety, reliability, and reduces the overhead of data storage.

BackgroundThe COVID-19 pandemic has exposed the vulnerability of healthcare services worldwide, especially in underdeveloped countries. There is a clear need to develop novel computer-assisted diagnosis tools to provide rapid and cost-effective screening in places where massive traditional testing is not feasible. Lung ultrasound is a portable, easy to disinfect, low cost and non-invasive tool that can be used to identify lung diseases. Computer-assisted analysis of lung ultrasound imagery is a relatively recent approach that has shown great potential for diagnosing pulmonary conditions, being a viable alternative for screening and diagnosing COVID-19.ObjectiveTo evaluate and compare the performance of deep-learning techniques for detecting COVID-19 infections from lung ultrasound imagery.MethodsWe adapted different pre-trained deep learning architectures, including VGG19, InceptionV3, Xception, and ResNet50. We used the publicly available POCUS dataset comprising 3326 lung ultrasound frames of healthy, COVID-19, and pneumonia patients for training and fine-tuning. We conducted two experiments considering three classes (COVID-19, pneumonia, and healthy) and two classes (COVID-19 versus pneumonia and COVID-19 versus non-COVID-19) of predictive models. The obtained results were also compared with the POCOVID-net model. For performance evaluation, we calculated per-class classification metrics (Precision, Recall, and F1-score) and overall metrics (Accuracy, Balanced Accuracy, and Area Under the Receiver Operating Characteristic Curve). Lastly, we performed a statistical analysis of performance results using ANOVA and Friedman tests followed by post-hoc analysis using the Wilcoxon signed-rank test with the Holm’s step-down correction.ResultsInceptionV3 network achieved the best average accuracy (89.1%), balanced accuracy (89.3%), and area under the receiver operating curve (97.1%) for COVID-19 detection from bacterial pneumonia and healthy lung ultrasound data. The ANOVA and Friedman tests found statistically significant performance differences between models for accuracy, balanced accuracy and area under the receiver operating curve. Post-hoc analysis showed statistically significant differences between the performance obtained with the InceptionV3-based model and POCOVID-net, VGG19-, and ResNet50-based models. No statistically significant differences were found in the performance obtained with InceptionV3- and Xception-based models.ConclusionsDeep learning techniques for computer-assisted analysis of lung ultrasound imagery provide a promising avenue for COVID-19 screening and diagnosis. Particularly, we found that the InceptionV3 network provides the most promising predictive results from all AI-based techniques evaluated in this work. InceptionV3- and Xception-based models can be used to further develop a viable computer-assisted screening tool for COVID-19 based on ultrasound imagery.

The classification of services in 5G/B5G (Beyond 5G) networks has become important for telecommunications service providers, who face the challenge of simultaneously offering a better Quality of Service (QoS) in their networks and a better Quality of Experience (QoE) to users. Service classification allows 5G service providers to accurately select the network slices for each service, thereby improving the QoS of the network and the QoE perceived by users, and ensuring compliance with the Service Level Agreement (SLA). Some projects have developed systems for classifying these services based on the Key Performance Indicators (KPIs) that characterize the different services. However, Key Quality Indicators (KQIs) are also significant in 5G networks, although these are generally not considered. We propose a service classifier that uses a Machine Learning (ML) approach based on Supervised Learning (SL) to improve classification and to support a better distribution of resources and traffic over 5G/B5G based networks. We carry out simulations of our proposed scheme using different SL algorithms, first with KPIs alone and then incorporating KQIs and show that the latter achieves better prediction, with an accuracy of 97% and a Matthews correlation coefficient of 96.6% with a Random Forest classifier.

When Internet of Things (IoT) big data analytics (BDA) require to transfer data streams among software defined network (SDN)-based distributed data centers, the data flow forwarding in the communication network is typically done by an SDN controller using a traditional shortest path algorithm or just considering bandwidth requirements by the applications. In BDA, this scheme could affect their performance resulting in a longer job completion time because additional metrics were not considered, such as end-to-end delay, jitter, and packet loss rate in the data transfer path. These metrics are quality of service (QoS) parameters in the communication network. This research proposes a solution called QoSComm, an SDN strategy to allocate QoS-based data flows for BDA running across distributed data centers to minimize their job completion time. QoSComm operates in two phases: (i) based on the current communication network conditions, it calculates the feasible paths for each data center using a multi-objective optimization method, (ii) it distributes the resultant paths among data centers configuring their openflow Switches (OFS) dynamically. Simulation results show that QoSComm can improve BDA job completion time by an average of 18%.

Silvopasture is a type of agroforestry that could deliver ecosystem services and support local livelihoods by integrating trees into pasture-based livestock systems. This study modeled the financial returns from silvopastures, planted forests, and conventional cattle-pasture systems in Amazonas, Peru using capital budgeting techniques. Forests had a lower land expectation value (USD 845 per hectare) than conventional cattle systems (USD 1275 per hectare) at a 4% discount rate. &ldquo, Typical&rdquo, model silvopastures, based on prior landowner surveys in the Amazonas region, were most competitive at low discount rates. The four actual silvopastoral systems we visited and examined had higher returns (4%: USD 1588 to USD 9524 per hectare) than either alternative pure crop or tree system, more than likely through strategies for generating value-added such as on-site retail stands. Silvopasture also offers animal health and environmental benefits, and could receive governmental or market payments to encourage these practices.

We address concepts and principles of the development, training, and use of applications in heterogeneous environments that integrate different computational infrastructures including HPC-clusters, grids, and clouds. Existing differences in the Grid and cloud computing models significantly complicate problem-solving processes in such environments for end-users. In this regards, we propose the toolkit named Orlando Tools for creating scalable applications for solving large-scale scientific and applied problems. It provides mechanisms for the subject domain specification, problem formulation, problem-solving time prediction, problem-solving scheme execution, monitoring, etc. The toolkit supports hands-on training skills for end-users. To demonstrate the practicability and benefits of Orlando Tools, we present an example of the development and use of the scalable application for solving practical problems of warehouse logistics.

This paper concerns with the development of two new testbeds, the associated datasets, and the analysis of the results obtained by applying different heuristic optimization algorithms that participated in the 2018 panel and competition on”Emerging heuristic optimization algorithms for operational planning of sustainable electrical power systems”. This activity was organized by the IEEE PES Working Group on Modern Heuristic Optimization (WGMHO), under the IEEE PES Analytic Methods in Power Systems (AMPS) Committee. This competition builds upon other previous competitions focused on the application of optimal power flow (OPF) to tackle schedulling problems of electrical power systems. Unlike the previous competitions, the new test beds consider more factors reflecting the stochasticity associated to renewable power generation, controllable loads, and electric vehicles. Developers of different emerging algorithms were challenged to perform algorithmic improvements and tuning within a limited computing budget. To this aim, the organizers of the competition developed and provided a set of encrypted codes for problem evaluation (i.e. calculation of objective function and constraints and saving of results). The results obtained by the best performing algorithms point out the relevance of modern heuristic optimization to tackle the complexity of stochastic OPF, without resorting to problem simplifications, and within a restricted computing budget.

In recent years, traditional data centers have been used to host high-performance computing infrastructure, such as HPC clusters, addressing specific requirements for different research and scientific projects. Computes, storage, network, and security infrastructure is usually from heterogenous manufacturers and has multiple management interfaces.

Atrial fibrillation (AF) is a common type of cardiac arrhythmia. AF is associated with increased rates of death and hospitalizations. It is also related to a degraded quality of life and reduced exercise capacity. Ageing increases the risk of developing AF, as well as hypertension and obesity. Continuous ECG monitoring is required in patients with previously diagnosed AF. Studies have also demonstrated that daily ECG monitoring increases the successful detection of silent AF among older adults. In this sense facilitating AF monitoring using portable devices such as Smartphones will increase patients life quality and could help to an early diagnosis. With this in mind in this work we present a proposal to detect AF using pulsatile photoplethysmogram (PPG) signal from a fingertip using the built-in camera lens in a smartphone. We developed an algorithm intended to sense paroxysmal AF considering resource utilization capabilities in order to be used in mobile devices with constrained.

The past decade, virtual machines emerged to solve many infrastructure problems and practical use of computing resources. The limitations of this type of technology, are in the sense of resource overload because each virtual machine has a complete copy of an operating system plus different libraries needed to run an application. Containers technology reduces this load by eliminating the hypervisor and the virtual machine for its operation, where each application is executed with the most elementary of a server, plus a shared instance of the operating system that hosts it. Container technology is already an essential part of the IT industry, as it is a simpler and more efficient way to virtualize Micro-Services with workflow’s creations support in development and operations (DevOps). Unlike the use of virtual machines, this solution generates much less overhead in the kernel host and the application, improving performance. In the high-performance computing (HPC) there is a willingness to implement this solution for scientific computing purposes. The most important and standard technology in the industry is Docker, however is not a trivial and direct adoption of this standard for the requirements of scientific computing in a HPC environment. In the present study, a review of research works focused on the use of containers for the HPC will be carried out with the objective of familiarizing the user and system administrator of HPC in the use of this technology, and how scientific research projects can get benefit from this type of technology in terms of mobility of compute and reproducibility of workflows.

Clays present a cost effective and sustainable method for removing uranium and heavy metals from drinking water because of their cation exchange capabilities. However, managing muddy suspensions is problematic; therefore, clay pellets as presented in this paper are a promising alternative. Three standard clays and two regional clays were evaluated for sorption, both in powder form and in pellet structure for comparison. The objective was to evaluate individual sorption processes and assess the effect on uranium sorption due to the process of altering the clay powder to produce pellets. The sorption capacity of the pellets is sufficiently large to not only sorb the intrinsic non-bonded uranium but to continue to sorb uranium from contaminated water. Furthermore, the uranyl cation was also removed preferentially in the presence of Pb(2+) and Cd(2+) heavy metal cations, hydronium ions, and more importantly the naturally occurring cations, Na(1+), Ca(2+), and Mg(2+) that occur in abundant concentrations. Clay pellets as well as powders reduced uranium concentrations, and in extreme cases from 450 ppb, 15 times the Environmental Protection Agency maximum contaminant level to non-detectable limits. Clay pellets are excellent candidates for the safe and manageable removal of uranium and heavy metals to produce potable water

Background Although mortality rates related with Chikungunya (CHIK) outbreaks into Latin America’s endemic-dengue rural and new urban regions are low, dealing with symptoms and sequelae can produce both a significant burden of disease and diminish quality of life — from many months to years — after the acute phase of infection, with a significant impact on public and individual health. Objectives The aim of this work was to establish a PANLAR-ACCAR consensus on diagnosis and treatment of CHIK-related inflammatory arthropathies transmitted by Ae. Aegypti and Ae. Albopictus in Latin America (LA). Methods Based on the Consensus Development Conference format, a panel of ACCAR rheumatologists (n=10) took part in this PANLAR initiative. Experts voted recommendations from a previous content analysis of the medical literature on CHIK, four subsequent topic’s Conferences and a workshop. Consensus represents the majority agreement (≥80%) achieved for each recommendation. Results The panel reach four overarching principles: 1) CHIK virus (CHIKV) is a re-emergent virus transmitted by two species of mosquitoes: Ae. Aegypti and Ae. Albopictus; 2) CHIKV caused massive outbreaks in LA; 3) Chronic CHIKV infection produces an inflammatory joint disease that in some cases can last several months to years, and 4) Currently, there are no vaccines or antivirals available for CHIKV infections. Conclusions PANLAR-ACCAR achieve 13 recommendations on CHIK categorised in three groups: 1) epidemiology and clinical manifestations; 2) diagnosis, and 3) treatment, representing the consensus agreement from the panel’s members. References [1] Pineda C, Munoz-Louis R, Caballero-Uribe CV, Viasus D. Chikungunya in the region of the Americas. A challenge for rheumatologists and health care systems. Clin Rheumatol2016;35(10):2381–5. [2] Fernandez-Salas I, Danis-Lozano R, Casas-Martinez M, Ulloa A, Bond JG, Marina CF, et al. Historical inability to control Aedes aegypti as a main contributor of fast dispersal of chikungunya outbreaks in Latin America. Antiviral Res2015;124:30–42. [3] Khoury VJ, Camilo PR. Chikungunya virus (CHIKV): what can be expected after the acute phase?Reumatol Clin2016;12(1):1–3. [4] JC Rueda, J-I Angarita, AM Santos, E-L Saldarriaga, I Pelaez-Ballestas, MJ Soares-Santeugini, J Londono. SAT0576 [5] Improved clinical scenario for chikungunya diagnosis Annals of the Rheumatic Diseases2017Jun;76(Suppl 2):994. Disclosure of Interest None declared

Vehicular ad-hoc networks (VANETs) have been identified as a key technology to enable intelligent transport systems (ITS), which in turn have the potential to radically enhance the safety and comfort of vehicles on the road as well as the potential to reduce their environmental impact. Nevertheless, several issues still must be addressed in order to fully exploit the potential of VANETs in favor of ITSs. Particularly, one key open issue in VANETs is the multi-hop broadcast message dissemination (MBMD) for safety and infotainment applications. In this context, fuzzy rule-based systems (FRBSs) have been proved to be useful when designing MBMD protocols for VANETs. However, a methodological tuning of the FRBS for such MBMD protocols to improve their performance in terms of metrics like packet delivery ratio still remains open. This paper deals with the problem of determining the best position and overlap between fuzzy states (FSs) of the MFs for FRBS-based MBMD protocols in order to enhance its performance. Specifically, a component-based methodology using genetic algorithm (GA) for the MFs tuning problem is proposed. The proposed methodology is validated by tuning two relevant FRBS-based MBMD protocols found in the literature. The tuned MBMD protocols have been evaluated over a range of realistic scenarios. Obtained results from the evaluations show that the tuned MBMD protocols provide better performance than the heuristically defined FRBSs in terms of important metrics like packet delivery ratio.

A group of well-defined equations (1) are implemented on a simulation algorithm by using a 2-DFDTD method. The method allows find behaviors in the eye diagrams not encountered by simple physical measuring (2) (3).

The USA300 North American epidemic (USA300-NAE) clone of methicillin-resistant Staphylococcus aureus has caused a wave of severe skin and soft tissue infections in the United States since it emerged in the early 2000s, but its geographic origin is obscure. Here we use the population genomic signatures expected from the serial founder effects of a geographic range expansion to infer the origin of USA300-NAE and identify polymorphisms associated with its spread. Genome sequences from 357 isolates from 22 U.S. states and territories and seven other countries are compared. We observe two significant signatures of range expansion, including decreases in genetic diversity and increases in derived allele frequency with geographic distance from the Pennsylvania region. These signatures account for approximately half of the core nucleotide variation of this clone, occur genome wide, and are robust to heterogeneity in temporal sampling of isolates, human population density, and recombination detection methods. The potential for positive selection of a gyrA fluoroquinolone resistance allele and several intergenic regions, along with a 2.4 times higher recombination rate in a resistant subclade, is noted. These results are the first to show a pattern of genetic variation that is consistent with a range expansion of an epidemic bacterial clone, and they highlight a rarely considered but potentially common mechanism by which genetic drift may profoundly influence bacterial genetic variation., IMPORTANCE The process of geographic spread of an origin population by a series of smaller populations can result in distinctive patterns of genetic variation. We detect these patterns for the first time with an epidemic bacterial clone and use them to uncover the clone’s geographic origin and variants associated with its spread. We study the USA300 clone of methicillin-resistant Staphylococcus aureus, which was first noticed in the early 2000s and subsequently became the leading cause of skin and soft tissue infections in the United States. The eastern United States is the most likely origin of epidemic USA300. Relatively few variants, which include an antibiotic resistance mutation, have persisted during this clone’s spread. Our study suggests that an early chapter in the genetic history of this epidemic bacterial clone was greatly influenced by random subsampling of isolates during the clone’s geographic spread.

Background: The yeasts species determination is fundamental not only for an accurate diagnosis but also for establishing a suitable patient treatment. We performed a concordance study of five methodologies for the species identification of oral isolates of Candida in Colombia. Methods: Sixty-seven Candida isolates were tested by; API® 20C-AUX,Vitek®2 Compact, Vitek®MS, Microflex® and a molecular test (panfungal PCR and sequencing). The commercial cost and processing time of the samples was done by graphical analysis. Results: Panfungal PCR differentiated 12 species of Candida, Vitek®MS and Microflex® methods identified 9 species, and API® 20C-AUX and Vitek®2 Compact methods identified 8 species each. Weighted Kappa (wK) showed a high agreement between Panfungal PCR, Vitek®MS, Microflex® and API® 20C-AUX (wK 0.62-0.93). The wK that involved the Vitek®2 Compact method presented moderate or good concordances compared with the other methods (wK 0.56-0.73). Methodologies based on MALDI TOF MS required 4 minutes to generate results and the Microflex® method had the lowest selling price. Conclusion: The methods evaluated showed high concordance in their results, being higher for the molecular methods and the methodologies based on MALDI TOF. The latter are faster and cheaper, presenting as promising alternatives for the routine identification of yeast species of the genus Candida. RESUMEN: Introducción: La clasificación a nivel de especies de las levaduras del género Candida de origen clínico es fundamental para el diagnóstico y la instauración de un adecuado tratamiento para el paciente. Se realizó un estudio de concordancia de cinco metodologías usadas para la identificación de aislamientos orales de Candida spp en Colombia. Métodos: Sesenta y siete aislamientos de Candida spp fueron identificados a nivel de especie utilizando; API® 20 C AUX‚ Vitek® 2 Compact, MALDI TOF (Vitek® MS y Microflex®) y una prueba molecular, PCR Panfungal y secuenciación. Un análisis del costo comercial y tiempo de procesamiento de las muestras por cada método fue realizado mediante el análisis gráfico de ambas variables. Resultados: La PCR Panfungal y secuenciación diferenció 12 especies de Candida‚ los métodos Vitek® MS y Microflex® identificaron 9 especies y los métodos API® 20 C AUX y Vitek® 2 Compact identificaron 8 especies. El análisis de Kappa ponderado (wK) demostró una concordancia alta entre los métodos PCR Panfungal y secuenciación‚ Vitek® MS‚ Microflex® y API® 20 C AUX‚ concordancias agrupadas en las categorías buena y muy buena (wK 0.62-0.93); los Kp que involucraron el método Vitek® 2 Compact presentaron concordancias moderadas o buenas frente a los otros métodos (wK 0.56-0.73). Las metodologías basadas en MALDI TOF MS requirieron 4 minutos para generar un resultado y el método Microflex® fue el método que en nuestro medio presentó el menor precio de venta del servicio. Conclusión: Los métodos evaluados presentaron una alta concordancia en sus resultados‚ siendo más alta para los métodos moleculares y las metodologías basadas en MALDI TOF MS; estas últimas son metodologías más rápidas, económicas y precisas, las cuales se presentan como alternativas prometedoras para la identificación rutinaria de especies de levaduras del género Candida. COL0013709

Este artículo describe un sistema móvil de teleasistencia médica para apoyar la atención de casos de emergencia, utilizando servicios de transmisión de signos vitales y videoconferencia en tiempo real. Así, en forma remota, los médicos especialistas pueden dar instrucciones precisas y oportunas a los paramédicos, con el propósito de mejorar la atención médica que recibe el paciente. Se analizan los aspectos técnicos de conectividad y factibilidad para la puesta en operación del sistema desde el punto de vista de cobertura inalámbrica, normatividad y tecnología actualmente disponibles en México, en donde los resultados obtenidos indican que la elección del servicio de comunicación inalámbrica es importante para soportar este servicio. Finalmente, se presentan resultados de la evaluación con diferentes tecnologías de comunicación inalámbrica y los retos e implicaciones en la adopción tecnológica por parte de los actores en la sala de emergencia y la unidad médica móvil, para que el sistema propuesto sea utilizado de manera efi ciente en el entorno hospitalario.