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This paper aims to develop distributed algorithms for nonconvex optimization problems with complicated constraints associated with a network. The network can be a physical one, such as an electric power network, where the constraints are nonlinear power flow equations, or an abstract one that represents constraint couplings between decision variables of different agents. Despite the recent development of distributed algorithms for nonconvex programs, highly complicated constraints still pose a significant challenge in theory and practice. We first identify some difficulties with the existing algorithms based on the alternating direction method of multipliers (ADMM) for dealing with such problems. We then propose a reformulation that enables us to design a two-level algorithm, which embeds a specially structured three-block ADMM at the inner level in an augmented Lagrangian method framework. Furthermore, we prove the global and local convergence as well as iteration complexity of this new scheme for general nonconvex constrained programs, and show that our analysis can be extended to handle more complicated multi-block inner-level problems. Finally, we demonstrate with computation that the new scheme provides convergent and parallelizable algorithms for various nonconvex applications, and is able to complement the performance of the state-of-the-art distributed algorithms in practice by achieving either faster convergence in optimality gap or in feasibility or both. [ABSTRACT FROM AUTHOR]

Building knowledge on how child welfare services (CWS) should tailor services for unaccompanied refugee minors (URMs) is important. URMs and youth in foster care are high-risk groups taken care of by the CWS in Norway. Little is known on whether knowledge gained from youth in foster care can inform services for URMs, and if these groups are comparable in terms of experiences of potential traumatic events (PTEs) and post-traumatic stress disorder (PTSD) symptom load. Eighty-one URMs reported PTEs and PTSD-symptoms using an adapted version of the Child and Adolescent Trauma Screen (CATS). Responses were described and compared with a sample of 303 youth in foster care in linear regression models. We present relative risks (RR) and standardized mean differences (SMD) for the PTEs and the PTSD subscale and total score between the groups in forest plots. URMs had experienced a mean (standard deviation) of 6.4 (3.4) PTEs and 43.9% reported to have PTSD-symptoms at or above the clinical cut off. Compared to the foster youth, URMs reported more exposures of interpersonal violence outside of the family (RRs ranging from 66.4 [95%CI 18.1; 243.5) to 1.3 (1.0, 1.5)], and more PTSD-symptoms in the re-experiencing subscale [SMD = 0.3 (95% CI 0.1, 0.6)]. The frequency and types of PTEs and the PTSD-symptom load and profile among URMs and youth in foster care differed. Findings underscore the importance of qualified and targeted care for URMs, and that this care should differ to that of other high-risk groups in the CWS. [ABSTRACT FROM AUTHOR]

This study reconstructs Middle and Late Neolithic dietary practices in the area of the today Czech Republic and Lower Austria with a help of complementary evidence of stable isotope and dental microwear analysis. From a total of 171 humans, carbon and nitrogen isotopic values were measured in bone collagen of 146 individuals (accompanied by 64 animals) while 113 individuals were included into buccal dental microwear analysis. The samples were divided into two newly established chronological phases: Neolithic B (4900–4000 BC) and Neolithic C (3800–3400 BC) based on radiocarbon data modelling. Isotopic results show that the Neolithic diet was of terrestrial origin with a dominant plant component. A small but statistically significant shift in human carbon isotopic values to a higher δ13C was observed during the Neolithic C, probably reflecting an underlying change in plant growing conditions. Dental microwear results suggest a shift in adult diet and/or food preparation techniques between the Neolithic B and C, which, however, was not reflected in either the carbon or nitrogen isotopic values. The positive correlations between nitrogen isotopic values and the dental microwear variables (NV, XV, XT and NV/NT) observed in the adult sample suggest that meat rather than milk was the dominant source of animal protein, or that food enriched in 15N was processed specifically. Also, as both methods offer a snapshot of different periods of an individual’s life, the presence of a significant correlation may imply highly repetitive dietary behaviour during their lifetime. [ABSTRACT FROM AUTHOR]

The level P-glycoprotein (Pgp) in organs of pregnant rabbits and its content and activity in the placental barrier at different stages of pregnancy were studied. An increase in Pgp content in the jejunum on days 7, 14, 21, and 28 of pregnancy in comparison with this parameter non-pregnant females was revealed by ELISA; in the liver, Pgp content was higher on day 7 and tended to increase on day 14; in the kidney and cerebral cortex, Pgp content was higher on day 28 of pregnancy in parallel with an increase in serum progesterone concentration. We also observed a decrease in Pgp content in the placenta on days 21 and 28 of pregnancy in comparison with day 14 and a decrease in Pgp activity in the placental barrier, which was confirmed by enhanced penetration of fexofenadine (Pgp substrate) through the barrier. [ABSTRACT FROM AUTHOR]

Previous work with Atomic Force Microscope (AFM) nanoindentation, on longitudinal and cross-sections of the human hair fibre, allowed for the derivation of a model for the mechanical behaviour of human hair, called the Anisotropic Index. Expanding that research further, and by applying this model, the nanomechanical behaviour of hairs from patients with the disease Trichothiodystrophy (TTD) has been examined and structural insights, gained from combining the AFM results with Differential Scanning Calorimetry (DSC) experiments and tensile measurements, suggests that TTD-affected hairs have a relatively increased amount of Keratin Intermediate Filaments, contained in compartments of differing crosslinking extent. The associated calculations of axial and transverse Young's Moduli deliver values in good agreement with the measured fibre mechanics. Furthermore, comparing these findings with the results previously obtained from the study of hairs from patients with the disease Monilethrix, it is shown that the Anisotropic Index correlates well with the known deficiencies in both hair types obtained from such patients and allows for discerning between the Control hair and from those affected by the two diseases. AFM nanoindentation along and across the fibre axis and the Anisotropic Index thus appear to reveal structural details of hair not otherwise acquirable, whilst DSC may offer a quick and simple method for distinguishing between different severities of TTD. [ABSTRACT FROM AUTHOR]

Integrin expression forms focal adhesions, but how this process is physiologically regulated is unclear. Ihog proteins are evolutionarily conserved, playing roles in Hedgehog signaling and serving as trans-homophilic adhesion molecules to mediate cell-cell interactions. Whether these proteins are also engaged in other cell adhesion processes remains unknown. Here, we report that Drosophila Ihog proteins function in the integrin-mediated adhesions. Removal of Ihog proteins causes blister and spheroidal muscle in wings and embryos, respectively. We demonstrate that Ihog proteins interact with integrin via the extracellular portion and that their removal perturbs integrin distribution. Finally, we show that Boc, a mammalian Ihog protein, rescues the embryonic defects caused by removing its Drosophila homologs. We thus propose that Ihog proteins contribute to integrin-mediated focal adhesions. [ABSTRACT FROM AUTHOR]

The aim was to investigate the association between plasma levels of cellular adhesion molecules (CAMs) and risk factors, subtypes, severity and short-term mortality of acute ischemic stroke (IS), and to identify a panel of biomarkers to predict short-term mortality after IS. The prospective study evaluated 132 IS patients within 24 h of their hospital admission. The baseline IS severity was assessed using the National Institutes Health Stroke Scale (NIHSS) and categorized as mild (NIHSS < 5), moderate (NIHSS 5–14) and severe (NIHSS ≥ 15). After three-month follow-up, the disability was assessed using the modified Rankin Scale (mRS); moreover, the patients were classified as survivors and non-survivors. Baseline inflammatory and anti-inflammatory cytokines and soluble CAMs were evaluated. Twenty-nine (21.9%) IS patients were non-survivors and showed higher NIHSS and soluble vascular cellular adhesion molecule 1 (sVCAM-1) than the survivors. The sVCAM-1 levels positively correlated with age, homocysteine, severity, and disability. The model #3 combining sVCAM-1 and NIHSS showed better results to predict short-term mortality with an area under the curve receiving operating characteristics (AUC/ROC) of 0.8841 [95% confidence interval (CI): 0.795–0.941] than the models with sVCAM-1 and NIHSS alone, with positive predictive value of 68.0%, negative predictive value of 91.3%, and accuracy of 86.5%. In conclusion, the combined model with baseline severity of IS and sVCAM-1 levels can early predict the prognosis of IS patients who may benefit with therapeutic measures of personalized therapy that taken into account these biomarkers. Moreover, this result suggests that VCAM-1 might be a potential target for the therapeutic strategies in IS. [ABSTRACT FROM AUTHOR]

In his Confessions, Augustine says that he achieved great intellectual insight from what he cryptically calls the "books of the Platonists." Prior to reading these books, he was a corporealist and was unable to conceive of incorporeal beings. Because of the insurmountable philosophical problems corporealism caused for the Christian belief he was seeking, Augustine claims that this was the greatest intellectual barrier he faced in converting to Christianity. As such, the specific contents and effects of these Platonist books are of great biographical and philosophical interest. Heretofore, the explanation of the contents and effects of these books has not been forthcoming. This essay aims to supply it. I argue that Augustine learned the mereological distinction between pertensive and entensive presence in the books of the Platonists. This distinction is required for properly conceiving of incorporeal beings. In support of this thesis, I show that Augustine himself says that he learned this very distinction, that the distinction is present in Platonist texts that scholars agree were among "the books of the Platonists," that the distinction is present in one of Augustine's earliest works, and that this distinction is uniquely capable of resolving the philosophical difficulties he faced as a corporealist. [ABSTRACT FROM AUTHOR]

Multidimensional data visualization is one of the most active research topics in information visualization since various information in our daily life forms multidimensional datasets. Scatterplot selection is an effective approach to represent essential portions of multidimensional data in a limited display space. Various metrics for evaluating scatterplots, such as scagnostics, have been applied to scatterplot selection. One of the open problems of this research topic is that various scatterplots cannot be selected if we simply apply one of the metrics. In other words, we may want to apply multiple metrics simultaneously in a balanced manner when we want to select a variety of scatterplots. This paper presents a new scatterplot selection technique that solves this problem. First, the technique calculates the scores of scatterplots with multiple metrics and then constructs a graph by connecting pairs of scatterplots that have similar scores. Next, it uses a graph coloring algorithm to assign different colors to scatterplots that have similar scores. We can extract a set of various scatterplots by selecting them that the specific same color is assigned. This paper introduces two case studies: the former study is with a retail transaction dataset while the latter study is with a design optimization dataset. [ABSTRACT FROM AUTHOR]

Light alkenes are among the main petrochemical intermediate products, the consumption of which is steadily growing. Using ethylene as an example, the possibilities of using polyfunctional heterogeneous catalysts for carrying out practically important reactions of its oligomerization, alkylation, and metathesis were considered. Particular attention was paid to catalysts for the conversion of ethylene to propylene. [ABSTRACT FROM AUTHOR]

In migraine, the trigeminal nerve is intimately involved in the pathophysiology of the disease. We hypothesized that alterations in the sensory trigeminal activation in migraine would be reflected by EEG-derived event-related potentials (ERP). We aimed to investigate differences in the temporal and spatial processing of trigeminal stimuli between interictal migraine patients and healthy subjects. ERP to trigeminal stimuli were recorded at 128-channels to allow localization of their cortical sources with high temporal resolution. Seventeen patients with episodic migraine without aura, 17 subjects with episodic migraine with aura, and 17 healthy subjects participated in the study. The first branch of the trigeminal nerve was stimulated using intranasal chemical (CO2), cutaneous electrical, and cutaneous mechanical (air puff) stimuli. Analyses were performed with regard to micro-state segmentation, ERP source localization, and correlation with the patients' clinical characteristics. Topographical assessments of EEG configurations were associated with the pathological condition. The source analysis revealed altered trigeminal-sensory response patterns in the precuneus, temporal pole, and cerebellum for both migraine groups during the interictal phase. The estimated current source density was positively correlated with migraine disease duration, indicating brain functional and structural changes as a consequence of the disease. Hyperactivity of the cerebellar posterior lobe was observed as a specific trigeminal response of migraine patients with aura. In conclusion, our results suggest the presence of brain changes accompanying the advancement of migraine as an expression of dysfunctional central pain processing. Hence, we identified EEG patterns in response to mechano-/chemosensory stimuli that can serve as biomarkers of migraine. [ABSTRACT FROM AUTHOR]

Pollution with emerging microscopic contaminants such as microplastics (MPs) and nanoplastics (NPs) including polystyrene (PS) in aquatic and terrestrial environments is increasingly recognized. PS is largely used in packaging materials and is dumped directly into the ecosystem. PS micro-nano-plastics (MNPs) can be potentially bioaccumulated in the food chain and can cause human health concerns through food consumption. Earlier MP research has focused on the aquatic environments, but recent researches show significant MP and NP contamination in the terrestrial environments especially agricultural fields. Though PS is the hotspot of MPs research, however, to our knowledge, this systematic review represents the first of its kind that specifically focused on PS contamination in agricultural soils, covering sources, effects, and ways of PS mitigation. The paper also provides updated information on the effects of PS on soil organisms, its uptake by plants, and effects on higher animals as well as human beings. Directions for future research are also proposed to increase our understanding of the environmental contamination of PS in terrestrial environments. [ABSTRACT FROM AUTHOR]

In order to improve the tribological performance of perfluoroethylene- propylene copolymer (FEP), two modifiers, melt-processable polytetrafluoroethylene (M-PTFE) with a low friction coefficient and graphene oxide (GO) with wear resistance, were added into FEP in the fixed M-PTFE/FEP weight ratio of 1/4 to prepare composites. The formed GO/M-PTFE/FEP composites were evaluated in terms of friction coefficient and volume wear rate. The results indicated that the highest tensile strength have appeared at GO addition of 0.15 wt%, while the elongation at break emerged at 0.20 wt% GO. The friction coefficient and wear rate of composites decreased initially and then increased with increasing GO addition. During friction, free radicals were generated by the scission of the fluorinated molecular chain under imposed shear force and thermal striking, and subsequently reacted with oxyl to form peroxy radicals. In this manner, iron carbides were eventually formed on the counterpart surface. In addition to direct transfer and deposition on the friction tracks of the counterpart, GO embedded in the perfluorinated matrix could be transferred to the surface of the steel ring during friction. [ABSTRACT FROM AUTHOR]

The requirement for energy and its management is growing in today's world. The energy sector is an area of interest for many countries around the world. To address the current fossil fuel issue, the scientific community is developing novel energy-saving experiments. Thermal energy storage is a mode of conserving energy. Thermal energy storage not only reduces energy consumption inconsistencies but also improves energy efficiency and reliability, which is an important part of energy conservation. In the realm of thermal energy storage, phase change materials (PCMs) are growing popularity and gaining awareness. By expanding, the area of heat transfer and reducing the seepage of melting materials, microcapsules improve the mechanical and thermal performance of PCMs used in the storage of thermal energy. PCM encapsulation is required to avoid PCM leakage, increase heat transmission, and control and reduce PCM reactivity with the environment. A vast number of researches on PCM microcapsules have been reported recently to explain their utility in energy systems. A complete evaluation of PCM microcapsules for thermal energy storage is presented in this paper. This review covers five topics: PCM classification, shell materials of encapsulation, microencapsulation methods, characterization of PCM microcapsules, and thermal applications. This review intends to aid researchers from diverse domains to gain a better understanding of PCM microcapsules and provide crucial guidance for future thermal energy storage using this technology. [ABSTRACT FROM AUTHOR]

Automated analysis and recognition of human emotion play an important role in the development of a human–computer interface. High temporal resolution of EEG signals enables us to noninvasively study the emotional brain activities. However, one major obstacle in this procedure is extracting the essential information in presence of the low spatial resolution of EEG recordings. The pattern of each emotion is clearly defined by mapping from scalp sensors to brain sources using the standardized low-resolution electromagnetic tomography (sLORETA) method. A graph neural network (GNN) is then used for EEG-based emotion recognition in which sLORETA sources are considered as the nodes of the underlying graph. In the proposed method, the inter-source relations in EEG source signals are encoded in the adjacency matrix of GNN. Finally, the labels of the unseen emotions are recognized using a GNN classifier. The experiments on the recorded EEG dataset by inducing excitement through music (recorded in brain-computer interface research lab, University of Tabriz) indicate that the brain source activity modeling by ESB-G3N significantly improves the accuracy of emotion recognition. Experimental results show classification accuracy of 98.35% for two-class classification of positive and negative emotions. In this paper, we concentrate on extracting active emotional cortical sources using EEG source imaging (ESI) techniques. Auditory stimuli are used to rapidly and efficiently induce emotions in participants (visual stimuli in terms of video/image are either slow or inefficient in inducing emotions). We propose the use of active EEG sources as graph nodes by EEG source-based GNN node (ESB-G3N) algorithm. The results show an absolute improvement of 1–2% over subject-dependent and subject-independent scenarions compared to the existing approaches. [ABSTRACT FROM AUTHOR]

Microorganisms in hot deserts face heat and other environmental conditions, such as desiccation, UV radiation, or low nutrient availability. Therefore, this hostile environment harbour microorganisms with acquired characteristics related to survival in their habitat, which can be exploited in biotechnology. In this work, the genome of Paenibacillus sp. MDMC362 isolated from the Merzouga desert in Morocco was sequenced to understand its survival strategy's genetic basis; and to evaluate the thermostability of a catalase extracted from genomic annotation files using molecular dynamics. Paenibacillus sp. MDMC362 genome was rich in genetic elements involved in the fight against different stresses, notably temperature stress, UV radiations, osmotic stress, carbon starvation, and oxidative stress. Indeed, we could identify genes of the operons groES-groEL and hrcA-grpE-dnaK and those involved in the different stages of sporulation, which can help the bacteria to survive the high temperatures imposed by a desertic environment. We also observed the genetic components of the UvrABC system and additional mechanisms involved in DNA repair, which help overcome UV radiation damage. Other genes have been identified in the genome, like those coding for ectoine and proline, that aids fight osmotic stress and desiccation. Catalase thermostability investigation using molecular dynamics showed that the protein reached stability and conserved its compactness at temperatures up to 373.15 K. These results suggest a potential thermostability of the enzyme. Since the studied protein is a core protein, thermostability could be conserved among Paenibacillus sp. MDMC362 closely related strains; however, bacteria from harsh environments may have a slight advantage regarding protein stability. [ABSTRACT FROM AUTHOR]

Objectives: We examined the association between diabetes mellitus (DM) and longitudinal MRI biomarkers for thigh muscle degeneration in patients with knee osteoarthritis (KOA) and their mediatory role in worsening KOA-related symptoms. Methods: The Osteoarthritis Initiative (OAI) participants with radiographic KOA (Kellgren-Lawrence grade ≥ 2) were included. Thighs and corresponding knees of KOA patients with versus without self-reported DM were matched for potential confounders using propensity score (PS) matching. We developed and used a validated deep learning method for longitudinal thigh segmentation. We assessed the association of DM with 4-year longitudinal muscle degeneration in biomarkers of muscle cross-sectional area (CSA) and contractile percentage (non-fat CSA/total CSA). We further investigated whether DM is associated with 9-year risk of KOA radiographic progression, knee replacement (KR), and symptoms worsening. Finally, we evaluated whether the DM–KOA worsening association is mediated through preceding muscle degeneration. Results: After PS matching, 698 thighs/knees were included (185:513 with:without DM; average ± SD age:64 ± 8-years; female/male:1.4). Baseline DM was associated with a decreased contractile percent of total thigh muscles and quadriceps (mean difference, 95%CI −0.16%/year, −0.25 to −0.07, and −0.21%/year, −0.33 to −0.08). DM was also associated with an increased risk of worsening KOA-related symptoms (hazard ratio, 95%CI 1.70, 1.18–2.46) but not radiographic progression or KR. The decrease in quadriceps contractile percent partially mediated the increased risk of symptoms worsening in patients with DM. Conclusions: Baseline DM is associated with thigh muscle degeneration and KOA-related symptoms worsening. As a potentially modifiable risk factor, DM-associated longitudinal thigh muscle degeneration may partially mediate the symptoms worsening in patients with DM and coexisting KOA. Key Points: • Diabetes mellitus (DM) is associated with worsening knee osteoarthritis (KOA)-related symptoms. • As a potentially modifiable factor, DM-associated thigh muscle (quadriceps) degeneration partially mediates the worsening of KOA-related symptoms. [ABSTRACT FROM AUTHOR]

In the current internet of things era, various devices can provide more services by connecting to the Internet. However, the explosive growth of connected devices will cause cloud core overload and significant network delays. To overcome these overload and delay problems, the mobile edge computing (MEC) network is proposed to provide most of the computing and storage near the radio access network to reduce the traffic of the core cloud network and provide lower latency for the terminal. Mobile edge computing can work with third parties to develop multiple services, such as mobile big data analysis and context-aware services. However, while using the service, it may also encounter a large amount of popular data being accessed in a short period of time. Without proper handling of replica generation and deployment, even in low-latency environments, it can still kill the benefits of MEC due to increased access time. Although many scholars have proposed related issues for copy replication, there are still.parts that can be improved. To avoid the situation of insufficient availability of replicas, replica replication is performed, but infinite replicas may lead to a significant increase in traffic and waste of resources. And when deploying replicas, it is necessary to avoid placing them on congested nodes and consider how to achieve better load balancing. To improve the above problems, we synthesize the advantages of previous algorithms, make up for the shortcomings, and propose an adaptive replica configuration mechanism to predict the popularity of files and replicate replicas to low-blocking nodes. This method spreads the subsequent access workload by copying the popular file in advance to improve the system's overall performance. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) magnetic materials promise unconventional properties and quantum phases as well as advances in ultra-compact spintronics. Miniaturization of 2D magnets often reaches a single monolayer but in general can go beyond this limit, as demonstrated by 2D magnetism of submonolayer Eu superstructures coupled with Si. The question is whether the submonolayer magnetism constitutes a general phenomenon. Herein, we demonstrate that regular Eu lattices form a class of 2D magnets displaying various structures, stoichiometries, and chemical bonding. We synthesized and studied a set of Eu superstructures on Ge(001). Their magnetic properties are consistent with the emergence of a magnetic order such as ferro- or ferrimagnetism. In particular, control over the magnetic transition temperature by weak magnetic fields indicates the 2D nature of the magnetism. Taken together, Eu/Ge and Eu/Si superstructures seed a nucleus of the research area addressing the emergence of magnetism in submonolayer chemical species. [ABSTRACT FROM AUTHOR]

This work addresses optimal control problems governed by a linear time-dependent partial differential equation (PDE) as well as integer constraints on the control. Moreover, partial observations are assumed in the objective function. The resulting problem poses several numerical challenges due to the mixture of combinatorial aspects, induced by integer variables, and large scale linear algebra issues, arising from the PDE discretization. Since classical solution approaches such as the branch-and-bound framework are typically overwhelmed by such large-scale problems, this work extends an improved penalty algorithm proposed by the authors, to the time-dependent setting. The main contribution is a novel combination of an interior point method, preconditioning, and model order reduction yielding a tailored local optimization solver at the heart of the overall solution procedure. A thorough numerical investigation is carried out both for the heat equation as well as a convection-diffusion problem demonstrating the versatility of the approach. [ABSTRACT FROM AUTHOR]

Cell fate transition is a fascinating process involving complex dynamics of three-dimensional (3D) chromatin organization and phase separation, which play an essential role in cell fate decision by regulating gene expression. Phase separation is increasingly being considered a driving force of chromatin folding. In this review, we have summarized the dynamic features of 3D chromatin and phase separation during physiological and pathological cell fate transitions and systematically analyzed recent evidence of phase separation facilitating the chromatin structure. In addition, we discuss current advances in understanding how phase separation contributes to physical and functional enhancer-promoter contacts. We highlight the functional roles of 3D chromatin organization and phase separation in cell fate transitions, and more explorations are required to study the regulatory relationship between 3D chromatin organization and phase separation. 3D chromatin organization (shown by Hi-C contact map) and phase separation are highly dynamic and play functional roles during early embryonic development, cell differentiation, somatic reprogramming, cell transdifferentiation and pathogenetic process. Phase separation can regulate 3D chromatin organization directly, but whether 3D chromatin organization regulates phase separation remains unclear. [ABSTRACT FROM AUTHOR]

The increasing demand for agricultural products can be met by maximizing production potential and reducing crop losses caused by common plant-parasitic nematodes. Chemical-based nematode management is a successful technique for mitigating damage and yield losses caused by nematode pests; however, inappropriate and irresponsible application of synthetic pesticides has negative impacts on fauna, bioflora, and natural enemies such as predators and parasites. The use of biocontrol agents is the most appreciated method for nematode control among farmers because it's safe and reduces environmental pollution. There is increasing focus on the biological control of plant-parasitic nematodes using plant growth-promoting rhizobacteria (PGPR) as a biopesticide. Moreover, PGPR strains can promote plant growth by producing various secondary metabolites of these PGPRs. This review focuses on the direct (Nitrogen fixation, phytohormone formation, phosphate solubilization, Potassium solubilization, siderophores and ammonia production) and indirect mechanisms (Hyperparasitism, antibiosis, lytic enzyme production, induced systemic resistance) of action of PGPR in plant-parasitic nematodes management, and the future prospects of PGPR-based plant-parasitic nematodes biocontrol agents. [ABSTRACT FROM AUTHOR]

There is widespread agreement that student teachers need to construct an integrated knowledge base across multiple domains. This study examined the contributions of intraindividual factors of self-regulated learning to explaining student teachers' (a) integration of knowledge across topics and domains (i.e., integrative learning) and (b) disjointed processing of potentially domain-specific learning content (i.e., separative learning). The factors considered were study approaches; cognitive, metacognitive, and resource-related learning strategy use; epistemological and pedagogical beliefs; and career choice motivation. The study applied a cross-sectional survey design and examined separative and integrative learning in N = 103 student teachers by way of multiple regression analyses with backward eliminations. A key finding is that deep and strategic study approaches and certain cognitive learning strategies contributed significantly to explaining integrative learning in student teachers. Epistemological and pedagogical beliefs were not able to predict integrative learning. Regarding separative learning, the study identified the surface study approach, specific epistemological and pedagogical beliefs, and the "usefulness" motive for career choice as positive predictors and critical thinking as a negative predictor. The study demonstrates differences in how integrative and separative learning are shaped by distinct intraindividual factors. Implications are discussed with regard to student teachers' self-regulated learning and pre-service teacher education. [ABSTRACT FROM AUTHOR]

In this paper, we demonstrate that digital technologies can be successfully applied to image analysis and prediction of the properties of functional materials using the example of a new method for rapidly identifying crystallographic orientation parameters of multicrystalline silicon. The proposed method is based on machine learning. The analysis of textured multicrystalline silicon wafers is carried out using the original single-crystal grain clustering algorithm, and the crystallographic orientation parameters are identified using a neural network model. The identification is based on the correlation of the contrast of the macrostructure display associated with the reflective features of the grains and their orientation parameters. Neural network architecture—multilayer perceptron—is chosen taking into account the restrictions on the amount of input data. However, in conjunction with the algorithm, the optimal amount of training data satisfies the requirements of the neural network training process and ensures high efficiency in identifying orientation parameters on scanned images of textured multicrystalline silicon wafers. Together with the algorithm, the optimal amount of training data satisfies the requirements of the neural network training process and ensures high efficiency in identifying orientation parameters on scanned images of textured multicrystalline silicon wafers. [ABSTRACT FROM AUTHOR]

Currently, few approaches are available for mixed-integer nonlinear robust optimization. Those that do exist typically either require restrictive assumptions on the problem structure or do not guarantee robust protection. In this work, we develop an algorithm for convex mixed-integer nonlinear robust optimization problems where a key feature is that the method does not rely on a specific structure of the inner worst-case (adversarial) problem and allows the latter to be non-convex. A major challenge of such a general nonlinear setting is ensuring robust protection, as this calls for a global solution of the non-convex adversarial problem. Our method is able to achieve this up to a tolerance, by requiring worst-case evaluations only up to a certain precision. For example, the necessary assumptions can be met by approximating a non-convex adversarial via piecewise relaxations and solving the resulting problem up to any requested error as a mixed-integer linear problem. In our approach, we model a robust optimization problem as a nonsmooth mixed-integer nonlinear problem and tackle it by an outer approximation method that requires only inexact function values and subgradients. To deal with the arising nonlinear subproblems, we render an adaptive bundle method applicable to this setting and extend it to generate cutting planes, which are valid up to a known precision. Relying on its convergence to approximate critical points, we prove, as a consequence, finite convergence of the outer approximation algorithm. As an application, we study the gas transport problem under uncertainties in demand and physical parameters on realistic instances and provide computational results demonstrating the efficiency of our method. [ABSTRACT FROM AUTHOR]

This paper examines the impact of using heavy water (D2O, D = deuterium) in cementitious materials as an alternative to conventional water (light water) for improvement in neutron radiography (NR) of cementitious materials. Cement pastes with two different water-to-cement ratios were made using heavy and light water. The macroscopic cross sections of heavy water, light water and ordinary portland cement were measured. Isothermal calorimetry, porosity, and non-evaporable water content were measured. NR measurements were also performed. The measured macroscopic cross section of the cement paste samples compared well with predictions made using a composite model based on Beer's law. [ABSTRACT FROM AUTHOR]

The phenomenon of intercellular mitochondrial transfer has attracted great attention in various fields of research, including stem cell biology. Elucidating the mechanism of mitochondrial transfer from healthy stem cells to cells with mitochondrial dysfunction may lead to the development of novel stem cell therapies to treat mitochondrial diseases, among other advances. To visually evaluate and analyze the mitochondrial transfer process, dual fluorescent labeling systems are often used to distinguish the mitochondria of donor and recipient cells. Although enhanced green fluorescent protein (EGFP) has been well-characterized for labeling mitochondria, other colors of fluorescent protein have been less extensively evaluated in the context of mitochondrial transfer. Here, we generated different lentiviral vectors with mitochondria-targeted red fluorescent proteins (RFPs), including DsRed, mCherry (both from Discosoma sp.) Kusabira orange (mKOκ, from Verrillofungia concinna), and TurboRFP (from Entacmaea quadricolor). Among these proteins, mitochondria-targeted DsRed and its variant mCherry often generated bright aggregates in the lysosome while other proteins did not. We further validated that TurboRFP-labeled mitochondria were successfully transferred from amniotic epithelial cells, one of the candidates for donor stem cells, to mitochondria-damaged recipient cells without losing the membrane potential. Our study provides new insight into the genetic labeling of mitochondria with red fluorescent proteins, which may be utilized to analyze the mechanism of intercellular mitochondrial transfer. [ABSTRACT FROM AUTHOR]

LiOH–LiBr binary system is thoroughly investigated by means of DSC and XRD experimental analysis. Observed discrepancies compared to previous existing studies relate to temperature values of phase equilibria as well as stoichiometric compounds present in the system. From our experimental results, a modified LiOH–LiBr phase diagram is proposed which gives satisfactory explanation to all observations carried out. It includes stoichiometric compounds Li2(OH)Br (peritectoid plateau at 250 °C, x ≤ 0.666), Li3(OH)2Br (stable between 230 and 280 °C, melting peritectically for x ≥ 0.5) and Li4(OH)3Br (peritectic plateau at 289 °C, x ≥ 0.5). It also displays a eutectic transition at 254 °C approx., which extends over the composition range x > 0 to x = 0.66–0.67, with eutectic point at x = 0.40. The disagreements with previous studies also concern the enthalpies of transition. Whatever the transition is considered, the enthalpies measured in this work are much lower than those predicted before. However, the peritectic compound Li4(OH)3Br is still an attractive candidate for TES applications around 300 °C such as Direct Steam Generation CSP technology. In particular, when compared to NaNO3, which the reference material at that temperature, the advantages of using Li4(OH)3Br as heat storage material lie in the higher volumetric latent heat storage capacity (+ 54%) and lower volume changes during phase transitions (3% vs. 11%). This would result in smaller storage tanks, lower size heat exchangers, contributing to decrease the cost of the storage system. [ABSTRACT FROM AUTHOR]

We show that deciding the feasibility of a booking (FB) in the European entry-exit gas market is coNP-hard if a nonlinear potential-based flow model is used. The feasibility of a booking can be characterized by polynomially many load flow scenarios with maximum potential-difference, which are computed by solving nonlinear potential-based flow models. We use this existing characterization of the literature to prove that FB is coNP-hard by reducing Partition to the infeasibility of a booking. We further prove that computing a potential-difference maximizing load flow scenario is NP -hard even if we can determine the flow direction a priori. From the literature, it is known that FB can be decided in polynomial time on trees and a single cycle. Thus, our hardness result draws the first line that separates the easy from the hard variants of FB and finally answers that FB is hard in general. [ABSTRACT FROM AUTHOR]

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The prevalence of adult obesity has risen markedly in recent decades. The endocrine system precisely regulates energy balance, fat abundance and fat deposition. Interestingly, white adipose tissue is an endocrine gland producing adipokines, which regulate whole-body physiology, including energy balance and reproduction. Endocrine disruptor chemicals (EDCs) include natural substances or chemicals that affect the endocrine system by multiple mechanisms and increase the risk of adverse health outcomes. Numerous studies have associated exposure to EDCs with obesity, classifying them as obesogens by their ability to activate different mechanisms, including the differentiation of adipocytes, increasing the storage of triglycerides, or elevating the number of adipocytes. Moreover, in recent years, not only industrial deception and obesity have intensified but also the problem of human infertility. Reproductive functions depend on hormone interactions, the balance of which may be disrupted by various EDCs or obesity. This review gives a brief summary of common EDCs linked with obesity, the mechanisms of their action, and the effect on adipokine levels, reproduction and connected disorders, such as polycystic ovarian syndrome, decrease in sperm motility, preeclampsia, intrauterine growth restriction in females and decrease of sperm motility in males. [ABSTRACT FROM AUTHOR]

Available therapeutic strategies for cancers have developed side effects, resistance, and recurrence that cause lower survival rates. Utilizing targeted drug delivery techniques has opened up new hopes for increasing the efficacy of cancer treatment. The current study aimed to investigate the appropriate condition of primming human amniotic epithelial cells (hAECs) with paclitaxel as a dual therapeutic approach consisting of inherent anticancer features of hAECs and loaded paclitaxel. The effects of paclitaxel on the viability of hAECs were evaluated to find an appropriate loading period. The possible mechanism of hAECs paclitaxel resistance was assessed using verapamil. Afterward, the loading and releasing efficacy of primed hAECs were evaluated by HPLC. The anti-neoplastic effects and apoptosis as possible mechanism of conditioned media of paclitaxel-loaded hAECs were assessed on breast and cervical cancer cell lines. hAECs are highly resistant to cytotoxic effects of paclitaxel in 24 h. Evaluating the role of P-glycoproteins in hAECs resistance showed that they do not participate in hAECs resistance. The HPLC demonstrated that hAECs uptake/release paclitaxel with optimum efficacy in 8000 ng/ml treatment. Assessing the anti-proliferative effect of primed hAECs condition media on cancer cells showed that the secretome induced 3.3- and 4.8-times more potent effects on MCF-7 and HeLa, respectively, and enhanced the apoptosis process. These results suggest that hAECs could possibly be used as a drug delivery system for cancer treatment. Besides, inherent anticancer effects of hAECs were preserved during the modification process. Synergistic anticancer effects of paclitaxel and hAECs can be translated into clinical practice, which would be evaluated in the future studies. [ABSTRACT FROM AUTHOR]

Correctly delimiting species and populations is a prerequisite for studies of connectivity, adaptation and conservation. Genomic data are particularly useful to test species differentiation for organisms with few informative morphological characters or low discrimination of cytoplasmic markers, as in Scleractinians. Here we applied Restriction site Associated DNA sequencing (RAD-sequencing) to the study of species differentiation and genetic structure in populations of Pocillopora spp. from Oman and French Polynesia, with the objectives to test species hypotheses, and to study the genetic structure among sampling sites within species. We focused here on coral colonies morphologically similar to P. acuta (damicornis type β). We tested the impact of different filtering strategies on the stability of the results. The main genetic differentiation was observed between samples from Oman and French Polynesia. These samples corresponded to different previously defined primary species hypotheses (PSH), i.e., PSHs 12 and 13 in Oman, and PSH 5 in French Polynesia. In Oman, we did not observe any clear differentiation between the two putative species PSH 12 and 13, nor between sampling sites. In French Polynesia, where a single species hypothesis was studied, there was no differentiation between sites. Our analyses allowed the identification of clonal lineages in Oman and French Polynesia. The impact of clonality on genetic diversity is discussed in light of individual-based simulations. [ABSTRACT FROM AUTHOR]

Major global change factors, including carbon dioxide (CO2) fertilization, warming, change in precipitation, nitrogen deposition, and land-use change have the potential to significantly affect future stocks of soil organic carbon (SOC). These factors, individually or by interacting with each other, can also trigger positive or negative feedback to the processes affecting the rate of SOC formation or loss. Despite rapid progress in the understanding of carbon (C) cycling processes in the last few decades, much uncertainty remains in our ability to precisely forecast potential changes in SOC stocks in the rapidly changing future world. Stable C isotopes have been extensively used in natural observational studies as well as in laboratory and field experiments that manipulate CO2 concentration, temperature, moisture, nitrogen fertilization, and vegetation type to understand the complex interactions and feedbacks that result from changing climate, plants and their herbivores, as well as soil microorganisms. Newly developed tools such as compound-specific isotope analysis, nano-SIMS (secondary ion mass spectroscopy), and stable isotope probing (SIP) permit isotope tracing in a specific ecosystem pool into specific C compounds and processes, thus providing in-depth insights into many processes affecting C biogeochemistry. The recent availability of affordable and reliable field-deployable optical isotope monitoring devices has provided researchers with a new set of tools for continuously tracking the 13C-CO2 fluxes at the ecosystem level, enabling deeper insights into C biogeochemistry under changing environmental conditions. Despite these great strides, there is a scarcity of review studies that have comprehensively examined the use of C isotopes in studying SOC responses under global change factors. This review highlights recent progress in understanding the effect of major global change factors on SOC fluxes and stocks using selected examples covering scales from plant rhizospheres to geographic regions. Moreover, we discuss the strengths and limitations of current approaches and recent scientific advancements to highlight the new prospects evolving from the exceptional temporal and spatial resolution of stable isotope analysis in studying how global change affects SOC. Finally, we suggest that studies using stable C isotopes are well-poised to focus on identifying how dominant SOC cycling processes respond to environment-specific limiting factors and any thresholds and tipping points that define those relationships. [ABSTRACT FROM AUTHOR]

Fruits and vegetables are very important agricultural products in daily life. Evaluating the quality attributes of fresh fruits and vegetables by nondestructive sensing techniques has been an intensive research topic over the past two decades. The research progress on the detection of internal and external quality attributes of fresh fruits and vegetables using various nondestructive spectroscopic and imaging techniques, including visible/near-infrared spectroscopy, time-resolved and space-resolved spectroscopy, machine vision, hyperspectral and multispectral imaging, fluorescence techniques, X-ray imaging, computed tomography scanning, magnetic resonance imaging, and Raman techniques, is presented and discussed in this review. Each kind of fruit or vegetable shows great variability in physical characteristics (including size, shape, color, and temperature) and biological characteristics (including cultivar, season, maturity level, and geographical origin). This physical and biological variability complicates the quality evaluation of fresh fruits and vegetables. To eliminate the influence of variability and improve the inspection accuracy, a lot of attempts, including pre-processing, light intensity transformation, global model, band math, model transfer, etc., have been made in image correction and spectral compensation methods. This review provides a detailed summary of the various methods for solving the problem of physical and biological variability, as well as their advantages and disadvantages. Additionally, the current problems to be solved in spectroscopic and imaging technologies and the research trends of nondestructive measurement of the quality of fresh fruits and vegetables in the future are also revealed. [ABSTRACT FROM AUTHOR]

Hereditary peripheral neuropathies called Charcot-Marie-Tooth (CMT) disease affect the sensory nerves as well as motor neurons. CMT diseases are composed of a heterogeneous group of diseases. They are characterized by symptoms such as muscle weakness and wasting. Type 2 CMT (CMT2) disease is a neuropathy with blunted or disrupted neuronal morphological differentiation phenotypes including process formation of peripheral neuronal axons. In the early stages of CMT2, demyelination that occurs in Schwann cells (glial cells) is rarely observed. CMT2W is an autosomal-dominant disease and is responsible for the gene encoding histidyl-tRNA synthetase 1 (HARS1), which is a family molecule of cytoplasmic aminoacyl-tRNA synthetases and functions by ligating histidine to its cognate tRNA. Despite increasing knowledge of the relationship of mutations on responsible genes with diseases, it still remains unclear how each mutation affects neuronal differentiation. Here we show that in neuronal N1E-115 cells, a severe Asp364-to-Tyr (D364Y) mutation of HARS1 leads to formation of small aggregates of HARS1 proteins; in contrast, wild type proteins are distributed throughout cell bodies. Expression of D364Y mutant proteins inhibited process formation whereas expression of wild type proteins possessed the normal differentiation ability to grow processes. Pretreatment with the antiepileptic valproic acid recovered inhibition of process formation by D364Y mutant proteins through the c-Jun N-terminal kinase signaling pathway. Taken together, these results indicate that the D364Y mutation of HARS1 causes HARS1 proteins to form small aggregates, inhibiting process growth, and that these effects are recovered by valproic acid. This could be a potential therapeutic drug for CMT2W at the cellular levels. [ABSTRACT FROM AUTHOR]

Despite extensive research on the biomechanics of insect wings over the past years, direct mechanical measurements on sensitive wing specimens remain very challenging. This is especially true for examining delicate museum specimens. This has made the finite element method popular in studies of wing biomechanics. Considering the complexities of insect wings, developing a wing model is usually error-prone and time-consuming. Hence, numerical studies in this area have often accompanied oversimplified models. Here we address this challenge by developing a new tool for fast, precise modelling of insect wings. This application, called WingGram, uses computer vision to detect the boundaries of wings and wing cells from a 2D image. The app can be used to develop wing models that include complex venations, corrugations and camber. WingGram can extract geometric features of the wings, including dimensions of the wing domain and subdomains and the location of vein junctions. Allowing researchers to simply model wings with a variety of forms, shapes and sizes, our application can facilitate studies of insect wing morphology and biomechanics. Being an open-access resource, WingGram has a unique application to expand how scientists, educators, and industry professionals analyse insect wings and similar shell structures in other fields, such as aerospace. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of forecasting multivariate aggregated human mobility while preserving the privacy of the individuals concerned. Differential privacy, a state-of-the-art formal notion, has been used as the privacy guarantee in two different and independent steps when training deep learning models. On one hand, we considered gradient perturbation, which uses the differentially private stochastic gradient descent algorithm to guarantee the privacy of each time series sample in the learning stage. On the other hand, we considered input perturbation, which adds differential privacy guarantees in each sample of the series before applying any learning. We compared four state-of-the-art recurrent neural networks: Long Short-Term Memory, Gated Recurrent Unit, and their Bidirectional architectures, i.e., Bidirectional-LSTM and Bidirectional-GRU. Extensive experiments were conducted with a real-world multivariate mobility dataset, which we published openly along with this paper. As shown in the results, differentially private deep learning models trained under gradient or input perturbation achieve nearly the same performance as non-private deep learning models, with loss in performance varying between 0.57 and 2.8 % . The contribution of this paper is significant for those involved in urban planning and decision-making, providing a solution to the human mobility multivariate forecast problem through differentially private deep learning models. [ABSTRACT FROM AUTHOR]

As a highly secure and reliable system, aviation faces challenges including digital transformation, high production operation costs, low maintenance efficiency, and intensive technology. One of the most beneficial technologies is the digital twin (DT), which can solve the above issues. This paper investigates aviation industry DT from government authorities, industry, and academia. Firstly, it surveys the development of the definition of DT and compares its concepts with the Internet of Things, cyber-physical systems, and digital thread etc. Next, it shows the research timeline of aviation DT in the past 10 years by authorities such as Air Force Research Laboratory and National Aeronautics and Space Administration. Then, this paper reviews the state-of-the-art research status of DT in the whole lifecycle of the aviation system and concludes that aviation DT is the most widely used in manufacturing and maintenance, and should pay attention to the application of UAV DT. Finally, it summarizes that data fusion, high-fidelity modeling, integration with New IT, and human–machine interaction are the key technologies of aviation DT. The future possible research directions could be digital process twin risk control, interactive DT, and DT data learning. [ABSTRACT FROM AUTHOR]

Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial phase, it may lead to death. Despite many significant efforts and promising outcomes in this domain, accurate segmentation and classification remain a challenging task. A major challenge for brain tumor detection arises from the variations in tumor location, shape, and size. The objective of this survey is to deliver a comprehensive literature on brain tumor detection through magnetic resonance imaging to help the researchers. This survey covered the anatomy of brain tumors, publicly available datasets, enhancement techniques, segmentation, feature extraction, classification, and deep learning, transfer learning and quantum machine learning for brain tumors analysis. Finally, this survey provides all important literature for the detection of brain tumors with their advantages, limitations, developments, and future trends. [ABSTRACT FROM AUTHOR]

Purpose: An investigation of arthroscopic surgery combined with coverage of the microfractured wound surface with platelet-rich plasma (PRP) and fibrin gels (FG) to treat knee cartilage defects.Methods: Between February 2017 and February 2020, 145 patients with knee cartilage defects were treated. Only isolated full-thickness cartilage defects were included, and 28 patients (12 men and 16 women) were included in this study. They were all treated with arthroscopic surgery on subchondral bones, filled with PRP and thrombin, and sealed with FG. The knee pain visual analogue scale (VAS) scores were measured after the patients climbed ten stairs up and down, and the Western Ontario and McMaster Universities osteoarthritis index and the area of cartilage defects were measured through the pre-operative and post-operative follow-up. The complication incidences were also observed.Results: All patients were followed up for ten to 15 months (median 12 months). The knee pain VAS scores decreased from 6.57 ± 1.07 pre-operatively to 2.09 ± 1.35 at the last follow-up. The WOMAC osteoarthritis index decreased from 44.32 ± 3.95 (mean ± sd) pre-operatively to 16.57 ± 2.20 by the last follow-up. The cartilage defect decreased from 2.93 ± 0.65 cm2 pre-operatively to 1.09 ± 0.69 cm2 at the last follow-up. All scores showed statistically significant improvements after surgery (p < 0.05). No complications were observed.Conclusion: The combination therapy of arthroscopic surgery and covering the microfractured wound surface with PRP and FG can repair knee cartilage defects, relieve pain, and improve function, and is a safe and effective treatment. [ABSTRACT FROM AUTHOR]

The representation of land surface processes in hydrological and climatic models critically depends on the soil water characteristics curve (SWCC) that defines the plant availability and water storage in the vadose zone. Despite the availability of SWCC datasets in the literature, significant efforts are required to harmonize reported data before SWCC parameters can be determined and implemented in modeling applications. In this work, a total of 15,259 SWCCs from 2,702 sites were assembled from published literature, harmonized, and quality-checked. The assembled SWCC data provide a global soil hydraulic properties (GSHP) database. Parameters of the van Genuchten (vG) SWCC model were estimated from the data using the R package 'soilhypfit'. In many cases, information on the wet- or dry-end of the SWCC measurements were missing, and we used pedotransfer functions (PTFs) to estimate saturated and residual water contents. The new database quantifies the differences of SWCCs across climatic regions and can be used to create global maps of soil hydraulic properties. Measurement(s) Soil water content at their given matric potential Technology Type(s) pressure plate • sandbox apparatus • pressure chamber [ABSTRACT FROM AUTHOR]

Previous studies on resting-state electroencephalographic responses in patients with depressive disorders have identified electroencephalogram (EEG) parameters as potential biomarkers for the early detection and diagnosis of depressive disorders. However, these studies did not investigate the relationship between resting-state EEG microstates and the early detection of depressive symptoms in preclinical individuals. To explore the possible association between resting-state EEG microstate temporal dynamics and depressive symptoms among college students, EEG microstate analysis was performed on eyes-closed resting-state EEG data for approximately 5 min from 34 undergraduates with high intensity of depressive symptoms and 34 age- and sex-matched controls with low intensity of depressive symptoms. Five microstate classes (A-E) were identified to best explain the datasets of both groups. Compared to controls, the mean duration, occurrence, and coverage of microstate class B increased significantly, whereas the occurrence and coverage of microstate classes D and E decreased significantly in individuals with high intensity of depressive symptoms. Additionally, the presence of microstate class B was positively correlated with participants' Beck Depression Inventory-II (BDI-II) scores, and the presence of microstate classes D and E were negatively correlated with their BDI-II scores. Further, individuals with high intensity of depressive symptoms had higher transition probabilities of A→B, B→A, B→C, B→D, and C→B, with lower transition probabilities of A→D, A→E, D→A, D→E, E→A, E→C, and E→D than controls. These results highlight resting-state EEG microstate temporal dynamics as potential biomarkers for the early detection and timely treatment of depression in college students. [ABSTRACT FROM AUTHOR]

Movement is manifested through a series of patterns at multiple spatial and temporal scales. Movement data today are becoming available at increasingly fine-grained temporal granularity. These observations often represent multiple behavioral modes and complex patterns along the movement path. However, the relationships between the observation scale of movement data and the analysis scales at which movement patterns are captured remain understudied. This article aims at investigating the role of temporal scale in movement data analytics. It takes up an important question of "how do decisions surrounding the scale of movement data and analyses impact our inferences about movement patterns?" Through a set of computational experiments in the context of human movement, we take a systematic look at the impact of varying temporal scales on common movement analytics techniques including trajectory analytics to calculate movement parameters (e.g., speed, path tortuosity), estimation of individual space usage, and interactions analysis to detect potential contacts between multiple mobile individuals. [ABSTRACT FROM AUTHOR]

Humans are social animals and the interpersonal bonds formed between them are crucial for their development and well being in a society. These relationships are usually structured into several layers (Dunbar's layers of friendship) depending on their significance in an individual's life with closest friends and family being the most important ones taking major part of their time and communication effort. However, we have little idea how the initiation and termination of these relationships occurs across the lifespan. Mobile phones, in particular, have been used extensively to shed light on the different types of social interactions between individuals and to explore this, we analyse a national cellphone database to determine how and when changes in close relationships occur in the two genders. In general, membership of this inner circle of intimate relationships is extremely stable, at least over a three-year period. However, around 1–4% of alters change every year, with the rate of change being higher among 17-21 year olds than older adults. Young adult females terminate more of their opposite-gender relationships, while older males are more persistent in trying to maintain relationships in decline. These results emphasise the variability in relationship dynamics across age and gender, and remind us that individual differences play an important role in the structure of social networks. Overall, our study provides a holistic understanding of the dynamic nature of close relationships during different stages of human life. [ABSTRACT FROM AUTHOR]

Rapid transport by deep convection is an important mechanism for delivering surface emissions of reactive halocarbons and other trace species to the tropical tropopause layer (TTL), a key region of transport to the stratosphere. Recent model studies have indicated that increased delivery of short-lived halocarbons to the TTL could delay stratospheric ozone recovery. We report here measurements in the TTL over the western Pacific Ocean of short-lived halocarbons and other trace gases that were transported eastward after convective lofting over Asia. Back-trajectories indicate the sampled air primarily originated from the Indian subcontinent. While short-lived organic bromine species show no measurable change over background mixing ratios, short-lived chlorinated organic species were elevated above background mixing ratios (dichloromethane (Δ48.2 ppt), 1,2-dichloroethane (Δ4.21 ppt), and chloroform (Δ4.85 ppt)), as well as longer-lived halogenated species, methyl chloride (Δ82.0 ppt) and methyl bromide (Δ1.91 ppt). This transported air mass thus contributed an excess equivalent effective chlorine burden of 316 ppt, with 119 ppt from short lived chlorinated species, to the TTL. Non-methane hydrocarbons (NMHC) were elevated 60 - 400% above background mixing ratios. The NMHC measurements were used to characterize the potential source regions, which are consistent with the convective influence analysis. The measurements indicate a chemical composition heavily impacted by biofuel/biomass burning and industrial emissions. This work shows that convection can loft Asian emissions, including short-lived chlorocarbons, and transport them to the remote TTL. [ABSTRACT FROM AUTHOR]

Research has shown assistance can provide many benefits to novices lacking the mental models needed for problem solving in a new domain. However, varying approaches to assistance, such as subgoals and next-step hints, have been implemented with mixed results. Next-Step hints are common in data-driven tutors due to their straightforward generation from historical student data, as well as research showing positive impacts on student learning. However, there is a lack of research exploring the possibility of extending data-driven methods to provide higher-level assistance. Therefore, we modified our data-driven Next-Step hint generator to provide Waypoints, hints that are a few steps ahead, representing problem-solving subgoals. We hypothesized that Waypoints would benefit students with high prior knowledge, and that Next-Step hints would most benefit students with lower prior knowledge. In this study, we investigated the influence of data-driven hint type, Waypoints versus Next-Step hints, on student learning in a logic proof tutoring system, Deep Thought, in a discrete mathematics course. We found that Next-Step hints were more beneficial for the majority of students in terms of time, efficiency, and accuracy on the posttest. However, higher totals of successfully used Waypoints were correlated with improvements in efficiency and time in the posttest. These results suggest that Waypoint hints could be beneficial, but more scaffolding may be needed to help students follow them. [ABSTRACT FROM AUTHOR]

We are concerned with the simulation and optimization of large-scale gas pipeline systems in an error-controlled environment. The gas flow dynamics is locally approximated by sufficiently accurate physical models taken from a hierarchy of decreasing complexity and varying over time. Feasible work regions of compressor stations consisting of several turbo compressors are included by semiconvex approximations of aggregated characteristic fields. A discrete adjoint approach within a first-discretize-then-optimize strategy is proposed and a sequential quadratic programming with an active set strategy is applied to solve the nonlinear constrained optimization problems resulting from a validation of nominations. The method proposed here accelerates the computation of near-term forecasts of sudden changes in the gas management and allows for an economic control of intra-day gas flow schedules in large networks. Case studies for real gas pipeline systems show the remarkable performance of the new method. [ABSTRACT FROM AUTHOR]