Optimal day-ahead scheduling of integrated urban energy systems

An optimal day-ahead scheduling method (ODSM) for the integrated urban energy system (IUES) is introduced, which considers the reconfigurable capability of an electric distribution network. The hourly topology of a distribution network, a natural gas network, the energy centers including the combined heat and power (CHP) units, different energy conversion devices and demand responsive loads (DRLs), are optimized to minimize the day-ahead operation cost of the IUES. The hourly reconfigurable capability of the electric distribution network utilizing remotely controlled switches (RCSs) is explored and discussed. The operational constraints from the unbalanced three-phase electric distribution network, the natural gas network, and the energy centers are considered. The interactions between the electric distribution network and the natural gas network take place through conversion of energy among different energy vectors in the energy centers. An energy conversion analysis model for the energy center was developed based on the energy hub model. A hybrid optimization method based on genetic algorithm (GA) and a nonlinear interior point method (IPM) is utilized to solve the ODSM model. Numerical studies demonstrate that the proposed ODSM is able to provide the IUES with an effective and economical day-ahead scheduling scheme and reduce the operational cost of the IUES.

Mania Triggered by Sleep Loss: Implications for Postpartum Psychosis

Background and Aims To examine whether a history of mood episodes triggered by sleep loss is associated with (1) postpartum psychosis (PP) and (2) more broadly-defined postpartum mood episodes that included postnatal depression (PND), in women with bipolar disorder (BD). Methods Participants were 622 parous women with a diagnosis of bipolar-I disorder recruited in the UK to the Bipolar Disorder Research Network. Diagnosis and perinatal episodes were assessed via interview and case note data. Women were also asked during the interview whether episodes of mania and/or depression were triggered by sleep loss. We compared the rates of PP and PND within women who did and did not endorse sleep loss as a trigger of mood episodes. Results Women who reported that their episodes of mania were usually triggered by sleep loss were twice as likely to have experienced an episode of PP (OR = 2.00, 95% CI = 1.20–3.36) than women who did not report this. This effect remained significant when controlling for clinical and demographic factors. We found no significant associations between depression triggered by sleep loss and PP. Analyses in which we defined postpartum episodes at a broader level to include both PP and PND were not significant. Conclusions In pregnant women with BD, a history of mania following sleep loss could be a potential marker of vulnerability to severe postpartum episodes. Further study in prospective samples is required in order to confirm these findings, which may have important implications for understanding the aetiology of PP and of mood disorders more generally.

Threat analysis of IoT networks using artificial neural network intrusion detection system

The Internet of things (IoT) is still in its infancy and has attracted much interest in many industrial sectors including medical fields, logistics tracking, smart cities and automobiles. However, as a paradigm, it is susceptible to a range of significant intrusion threats. This paper presents a threat analysis of the IoT and uses an Artificial Neural Network (ANN) to combat these threats. A multi-level perceptron, a type of supervised ANN, is trained using internet packet traces, then is assessed on its ability to thwart Distributed Denial of Service (DDoS/DoS) attacks. This paper focuses on the classification of normal and threat patterns on an IoT Network. The ANN procedure is validated against a simulated IoT network. The experimental results demonstrate 99.4% accuracy and can successfully detect various DDoS/DoS attacks.

68Ga somatostatin analog radiolabelling: The radiopharmacist's point of view

International audience

Wireless Sensor Network Deployment

Wireless Sensor Networks (WSNs) are widely used for various civilian and military applications, and thus have attracted significant interest in recent years. This work investigates the important problem of optimal deployment of WSNs in terms of coverage and energy consumption. Five deployment algorithms are developed for maximal sensing range and minimal energy consumption in order to provide optimal sensing coverage and maximum lifetime. Also, all developed algorithms include self-healing capabilities in order to restore the operation of WSNs after a number of nodes have become inoperative. Two centralized optimization algorithms are developed, one based on Genetic Algorithms (GAs) and one based on Particle Swarm Optimization (PSO). Both optimization algorithms use powerful central nodes to calculate and obtain the global optimum outcomes. The GA is used to determine the optimal tradeoff between network coverage and overall distance travelled by fixed range sensors. The PSO algorithm is used to ensure 100% network coverage and minimize the energy consumed by mobile and range-adjustable sensors. Up to 30% - 90% energy savings can be provided in different scenarios by using the developed optimization algorithms thereby extending the lifetime of the sensor by 1.4 to 10 times. Three distributed optimization algorithms are also developed to relocate the sensors and optimize the coverage of networks with more stringent design and cost constraints. Each algorithm is cooperatively executed by all sensors to achieve better coverage. Two of our algorithms use the relative positions between sensors to optimize the coverage and energy savings. They provide 20% to 25% more energy savings than existing solutions. Our third algorithm is developed for networks without self-localization capabilities and supports the optimal deployment of such networks without requiring the use of expensive geolocation hardware or energy consuming localization algorithms. This is important for indoor monitoring applications since current localization algorithms cannot provide good accuracy for sensor relocation algorithms in such indoor environments. Also, no sensor redeployment algorithms, which can operate without self-localization systems, developed before our work.

Progesterone attenuates microglial-driven retinal degeneration and stimulates protective Fractalkine-CX3CR1 signaling

Retinitis pigmentosa (RP) is a degenerative disease leading to photoreceptor cell loss. Mouse models of RP, such as the rd10 mouse (B6.CXBl-Pde6brd10/J), have enhanced our understanding of the disease, allowing for development of potential therapeutics. In 2011, our group first demonstrated that the synthetic progesterone analogue ‘Norgestrel’ is neuroprotective in two mouse models of retinal degeneration, including the rd10 mouse. We have since elucidated several mechanisms by which Norgestrel protects stressed photoreceptors, such as upregulating growth factors. This study consequently aimed to further characterize Norgestrel’s neuroprotective effects. Specifically, we sought to investigate the role that microglia might play; for microglial-derived inflammation has been shown to potentiate neurodegeneration. Dams of post-natal day (P) 10 rd10 pups were given a Norgestrel-supplemented diet (80mg/kg). Upon weaning, pups remained on Norgestrel. Tissue was harvested from P15-P50 rd10 mice on control or Norgestrel-supplemented diet. Norgestrel-diet administration provided significant retinal protection out to P40 in rd10 mice. Alterations in microglial activity coincided with significant protection, implicating microglial changes in Norgestrel-induced neuroprotection. Utilizing primary cultures of retinal microglia and 661W photoreceptor-like cells, we show that rd10 microglia drive neuronal cell death. We reveal a novel role of Norgestrel, acting directly on microglia to reduce pro-inflammatory activation and prevent neuronal cell death. Norgestrel effectively suppresses cytokine, chemokine and danger-associated molecular pattern molecule (DAMP) expression in the rd10 retina. Remarkably, Norgestrel upregulates fractalkine-CX3CR1 signaling 1 000-fold at the RNA level, in the rd10 mouse. Fractalkine-CX3CR1 signaling has been shown to protect neurons by regulating retinal microglial activation and migration. Ultimately, these results present Norgestrel as a promising treatment for RP, with dual actions as a neuroprotective and anti-inflammatory agent in the retina.

Induction of Hebbian associative plasticity through paired non-invasive brain stimulation of premotor-motor areas to elucidate the network's functional role

The ventral premotor cortex (PMv) is believed to play a pivotal role in a multitude of visuomotor behaviors, such as sensory-guided goal-directed visuomotor transformations, arbitrary visuomotor mapping, and hyper-learnt visuomotor associations underlying automatic imitative tendencies. All these functions are likely carried out through the copious projections connecting PMv to the primary motor cortex (M1). Yet, causal evidence investigating the functional relevance of the PMv-M1 network remains elusive and scarce. In the studies reported in this thesis we addressed this issue using a transcranial magnetic stimulation (TMS) protocol called cortico-cortical paired associative stimulation (ccPAS), which relies on multisite stimulation to induce Hebbian spike-timing dependent plasticity (STDP) by repeatedly stimulating the pathway connecting two target areas to manipulate their connectivity. Firstly, we show that ccPAS protocols informed by both short- and long-latency PMv-M1 interactions effectively modulate connectivity between the two nodes. Then, by pre-activating the network to apply ccPAS in a state-dependent manner, we were able to selectively target specific functional visuo-motor pathways, demonstrating the relevance of PMv-M1 connectivity to arbitrary visuomotor mapping. Subsequently, we addressed the PMv-to-M1 role in automatic imitation, and demonstrated that its connectivity manipulation has a corresponding impact on automatic imitative tendencies. Finally, by combining dual-coil TMS connectivity assessments and ccPAS in young and elderly individuals, we traced effective connectivity of premotor-motor networks and tested their plasticity and relevance to manual dexterity and force in healthy ageing. Our findings provide unprecedent causal evidence of the functional role of the PMv-to-M1 network in young and elderly individuals. The studies presented in this thesis suggest that ccPAS can effectively modulate the strength of connectivity between targeted areas, and coherently manipulate a networks’ behavioral output. Results open new research prospects into the causal role of cortico-cortical connectivity, and provide necessary information to the development of clinical interventions based on connectivity manipulation.

Tree regularized neural networks for key point analysis

This thesis contributes to the ArgMining 2021 shared task on Key Point Analysis. Key Point Analysis entails extracting and calculating the prevalence of a concise list of the most prominent talking points, from an input corpus. These talking points are usually referred to as key points. Key point analysis is divided into two subtasks: Key Point Matching, which involves assigning a matching score to each key point/argument pair, and Key Point Generation, which consists of the generation of key points. The task of Key Point Matching was approached using different models: a pretrained Sentence Transformers model and a tree-constrained Graph Neural Network were tested. The best model was the fine-tuned Sentence Transformers, which achieved a mean Average Precision score of 0.75, ranking 12 compared to other participating teams. The model was then used for the subtask of Key Point Generation using the extractive method in the selection of key point candidates and the model developed for the previous subtask to evaluate them.

Clustering Of Water Bodies In Unpolluted And Polluted Environments Based On Escherichia Coli Phylogroup Abundance Using A Simple Interaction Database.

Different types of water bodies, including lakes, streams, and coastal marine waters, are often susceptible to fecal contamination from a range of point and nonpoint sources, and have been evaluated using fecal indicator microorganisms. The most commonly used fecal indicator is Escherichia coli, but traditional cultivation methods do not allow discrimination of the source of pollution. The use of triplex PCR offers an approach that is fast and inexpensive, and here enabled the identification of phylogroups. The phylogenetic distribution of E. coli subgroups isolated from water samples revealed higher frequencies of subgroups A1 and B23 in rivers impacted by human pollution sources, while subgroups D1 and D2 were associated with pristine sites, and subgroup B1 with domesticated animal sources, suggesting their use as a first screening for pollution source identification. A simple classification is also proposed based on phylogenetic subgroup distribution using the w-clique metric, enabling differentiation of polluted and unpolluted sites.

Adding value to the meat of spent laying hens manufacturing sausages with a healthy appeal

The aim of this study was to evaluate the viability of the use of spent laying hens' meat in the manufacturing of mortadella-type sausages with healthy appeal by using vegetable oil instead of animal fat. 120 Hy-line® layer hens were distributed in a completely randomized design into two treatments of six replicates with ten birds each. The treatments were birds from light Hy-line® W36 and semi-heavy Hy-line® Brown lines. Cold carcass, wing, breast and leg fillets yields were determined. Dry matter, protein, and lipid contents were determined in breast and leg fillets. The breast and legg fillets of three replicates per treatment were used to manufacture mortadella. After processing, sausages were evaluated for proximal composition, objective color, microbiological parameters, fatty acid profile and sensory acceptance. The meat of light and semi-heavy spent hens presented good yield and composition, allowing it to be used as raw material for the manufacture of processed products. Mortadellas were safe from microbiological point of view, and those made with semi-heavy hens fillets were redder and better accepted by consumers. Values for all sensory attributes were evaluated over score 5 (neither liked nor disliked). Both products presented high polyunsaturated fatty acid contents and good polyunsaturated to saturated fatty acid ratio. The excellent potential for the use of meat from spent layer hens of both varieties in the manufacturing of healthier mortadella-type sausage was demonstrated.

Trichomycterus dali: a new highly troglomorphic catfish (Silurifomes: Trichomycteridae) from Serra da Bodoquena, Mato Grosso do Sul State, Central Brazil

Trichomycterus dali, new species, is described from flooded limestone caves in Serra da Bodoquena karst area, State of Mato Grosso do Sul, Central Brazil. The new species is diagnosed by a unique character in the genus, the presence of conspicuous, ridge-like adipose folds lining dorsally throughout the body. Trichomycterus dali can be further distinguished readily from epigean congeners by the reduction of eyes and skin pigmentation (except for T. gorgona), and from remaining congeners (i.e., all hypogean plus T. gorgona) by the total loss of eyes, not visible externally (except for T. sandovali and T. spelaeus). Other diagnostic features includes very long barbels, especially the nasal (99.3-143.5% HL) and the maxillary (97.0-131.3% HL), pectoral-fin ray count reaching I,9 and a unique cranial fontanel with a conspicuous constriction on the meeting point of supraoccipital and the two frontal bones. The troglobitic status of the species is suggested by the presence of troglomorphisms on an advanced degree, especially the reduction of skin pigmentation, the total loss of eyes and the enlarged barbels. In addition, the presence of a well developed adipose fold in adults may indicate a distinctive adaptation acquired by neoteny to withstand the food scarce conditions of its hypogean habitat.

Dynamical models for computer viruses propagation

Nowadays, digital computer systems and networks are the main engineering tools, being used in planning, design, operation, and control of all sizes of building, transportation, machinery, business, and life maintaining devices. Consequently, computer viruses became one of the most important sources of uncertainty, contributing to decrease the reliability of vital activities. A lot of antivirus programs have been developed, but they are limited to detecting and removing infections, based on previous knowledge of the virus code. In spite of having good adaptation capability, these programs work just as vaccines against diseases and are not able to prevent new infections based on the network state. Here, a trial on modeling computer viruses propagation dynamics relates it to other notable events occurring in the network permitting to establish preventive policies in the network management. Data from three different viruses are collected in the Internet and two different identification techniques, autoregressive and Fourier analyses, are applied showing that it is possible to forecast the dynamics of a new virus propagation by using the data collected from other viruses that formerly infected the network. Copyright (c) 2008 J. R. C. Piqueira and F. B. Cesar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Border figure detection using a phase oscillator network with dynamical coupling

Oscillator networks have been developed in order to perform specific tasks related to image processing. Here we analytically investigate the existence of synchronism in a pair of phase oscillators that are short-range dynamically coupled. Then, we use these analytical results to design a network able of detecting border of black-and-white figures. Each unit composing this network is a pair of such phase oscillators and is assigned to a pixel in the image. The couplings among the units forming the network are also dynamical. Border detection emerges from the network activity.

Comparison of the Effects of Electrical Field Stimulation and Low-Level Laser Therapy on Bone Loss in Spinal Cord-Injured Rats

Objective: This study investigated the effects of low-level laser therapy (LLLT) and electrical stimulation (ES) on bone loss in spinal cord-injured rats. Materials and Methods: Thirty-seven male Wistar rats were divided into four groups: standard control group (CG); spinal cord-injured control (SC); spinal cord-injured treated with laser (SCL; GaAlAs, 830 nm, CW, 30mW/cm, 250 J/cm(2)); and spinal cord-injured treated with electrical field stimulation (SCE; 1.5 MHz, 1: 4 duty cycles, 30 mW, 20 min). Biomechanical, densitometric, and morphometric analyses were performed. Results: SC rats showed a significant decrease in bone mass, biomechanical properties, and morphometric parameters (versus CG). SCE rats showed significantly higher values of inner diameter and internal and external areas of tibia diaphyses; and the SCL group showed a trend toward the same result (versus SC). No increase was found in either mechanical or densitometric parameters. Conclusion: We conclude that the mentioned treatments were able to initiate a positive bone-tissue response, maybe through stimulation of osteoblasts, which was able to determine the observed morphometric modifications. However, the evoked tissue response could not determine either biomechanical or densitometric modifications.

Mutational analysis of genes p14ARF, p15INK4b, p16INK4a, and PTEN in human nervous system tumors

The cancer is one of the most common and severe problems in clinical medicine, and nervous system tumors represent about 2% of the types of cancer. The central role of the nervous system in the maintenance of vital activities and the functional consequences of the loss of neurons can explain how severe brain cancers are. The cell cycle is a highly complex process, with a wide number of regulatory proteins involved, and such proteins can suffer alterations that transform normal cells into malignant ones. The INK4 family members (CDK inhibitors) are the cell cycle regulators that block the progression of the cycle through the R point, causing an arrest in G1 stage. The p14ARF (alternative reading frame) gene is a tumor suppressor that inhibits p53 degradation during the progression of the cell cycle. The PTEN gene is related to the induction of growth suppression through cell cycle arrest, to apoptosis and to the inhibition of cell adhesion and migration. The purpose of the present study was to assess the mutational state of the genes p14ARF, p15INK4b, p16INK4a, and PTEN in 64 human nervous system tumor samples. Homozygous deletions were found in exon 2 of the p15INK4b gene and exon 3 of the p16INK4a gene in two schwannomas. Three samples showed a guanine deletion (63 codon) which led to a loss of heterozygosity in the p15 gene, and no alterations could be seen in the PTEN gene. Although the group of patients was heterogeneous, our results are in accordance with other different studies that indicate that homozygous deletion and loss of heterozygosity in the INK4 family members are frequently observed in nervous system tumors.