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Abstract Frogs are an ecologically diverse and phylogenetically ancient group of anuran amphibians that include important vertebrate cell and developmental model systems, notably the genus Xenopus. Here we report a high-quality reference genome sequence for the western clawed frog, Xenopus tropicalis, along with draft chromosome-scale sequences of three distantly related emerging model frog species, Eleutherodactylus coqui, Engystomops pustulosus, and Hymenochirus boettgeri. Frog chromosomes have remained remarkably stable since the Mesozoic Era, with limited Robertsonian (i.e., arm-preserving) translocations and end-to-end fusions found among the smaller chromosomes. Conservation of synteny includes conservation of centromere locations, marked by centromeric tandem repeats associated with Cenp-a binding surrounded by pericentromeric LINE/L1 elements. This work explores the structure of chromosomes across frogs, using a dense meiotic linkage map for X. tropicalis and chromatin conformation capture (Hi-C) data for all species. Abundant satellite repeats occupy the unusually long (~20 megabase) terminal regions of each chromosome that coincide with high rates of recombination. Both embryonic and differentiated cells show reproducible associations of centromeric chromatin and of telomeres, reflecting a Rabl-like configuration. Our comparative analyses reveal 13 conserved ancestral anuran chromosomes from which contemporary frog genomes were constructed.

Recently, Code Quality (CQ) has become critical in a wide range of organizations and in many areas from academia to industry. CQ, in terms of readability, security, and testability, is a major goal throughout the software development process because it affects overall Software Quality (SQ) in terms of subsequent releases, maintenance, and updates. It is particularly important for the development of safety critical systems. Existing studies on CQ have several shortcomings in that they are based on incomplete information about the source code, and tend to focus on only one feature, which is likely to determine the performance of the model. Moreover, these considerations often limit obtaining high accuracy because there is no strong relationship between the input data and the output data. Thus, it is necessary to design an effective and efficient SQ measurement system for measuring multiple quality factors. To that end, we propose a deep learning framework that employed a Latent Dirichlet Allocation (LDA) with Convolutional Neural Networks (CNN), called CNN-LDA, to classify input data into topics that are related to CQ features and to identify hidden patterns and correlations in programming data. Three SQ metrics (i.e., readability, security, and testability) and machine learning techniques (e.g., random forest (RF) and support vector machine (SVM)) are taken into account to validate the proposed model. The proposed CNN-LDA outperformed its peers across the vast majority of datasets examined. The average overall F-measure for readability, security, and testability are 94%,94% and 93%. The average overall accuracy for readability, security, and testability are 93%,93% and 92%. The superiority of LDA-CNN over the other classifiers was very clear based on a Wilcoxon’s non-parametric statistical test (α=0.05).

Abstract Systemic lupus erythematosus (SLE) is a devastating autoimmune disorder characterized by failure of self-tolerance with resultant production of autoreactive antibodies. The etiology of this syndrome is complex, involving perturbations in immune cell signaling and development. The NZBWF1 mouse spontaneously develops a lupus-like syndrome and has been widely used as a model of SLE for over 60 years. The NZBWF1 model represents the F1 generation of a cross between New Zealand Black (NZB) and New Zealand White (NZW) mice. In order to better understand the factors that contribute to the development of autoimmunity, single cell RNA sequencing was conducted using the bone marrow from female NZBWF1 mice prior to the development of overt disease. The results were contrasted with single cell RNA sequencing results from the two parental strains. The expected findings of B cell abundance and upregulation, and evidence of interferon signaling were validated in this model. In addition, several novel areas of inquiry were identified. Most notably, the data showed a marked upregulation of the ferritin light chain across all cell types in the NZBWF1 mice compared to parental controls. This data can serve as a gene expression atlas of all hematopoietic cells in the NZBWF1 bone marrow prior to the development of autoimmunity.

Abstract Preeclampsia (PE) is associated with adverse cerebrovascular effects during and following parturition including stroke, small vessel disease, and vascular dementia. A potential contributing factor to the cerebrovascular dysfunction is the loss of cerebral blood flow (CBF) autoregulation. Autoregulation is the maintenance of CBF to meet local demands with changes in perfusion pressure. When perfusion pressure rises, vasoconstriction of cerebral arteries and arterioles maintains flow and prevents the transfer of higher systemic pressure to downstream microvasculature. In the face of concurrent hypertension, loss of autoregulatory control exposes small delicate microvessels to injury from elevated systemic blood pressure. While placental ischemia is considered the initiating event in the preeclamptic cascade, the factor(s) mediating cerebrovascular dysfunction are poorly understood. Elevated plasma proinflammatory cytokines, such as tumor necrosis factor α (TNF‐α) and interleukin‐17 (IL‐17), are potential mediators of autoregulatory loss. Impaired CBF responses to increases in systemic pressure are attributed to the impaired pressure‐induced (myogenic) constriction of small cerebral arteries and arterioles in PE. Myogenic vasoconstriction is initiated by pressure‐induced vascular smooth muscle cell (VSMC) stretch. Recent studies from our laboratory group indicate that proinflammatory cytokines impair the myogenic mechanism of CBF autoregulation via inhibition of vascular degenerin proteins, putative mediators of myogenic constriction in VSMCs. This brief review links studies showing the effect of proinflammatory cytokines on degenerin expression and CBF autoregulation to the pathological cerebral consequences of preeclampsia.

Abstract A new articulated postcranial specimen of an indeterminate ankylosaurid dinosaur from the Upper Cretaceous (middle-upper Campanian) Baruungoyot Formation from Hermiin Tsav, southern Gobi Desert, Mongolia includes twelve dorsal vertebrae, ribs, pectoral girdles, forelimbs, pelvic girdles, hind limbs, and free osteoderms. The new specimen shows that Asian ankylosaurids evolved rigid bodies with a decreased number of pedal phalanges. It also implies that there were at least two forms of flank armor within Ankylosauridae, one with spine-like osteoderms and the other with keeled rhomboidal osteoderms. Unique anatomical features related to digging are present in Ankylosauridae, such as dorsoventrally flattened and fusiform body shapes, extensively fused series of vertebrae, anteroposteriorly broadened dorsal ribs, a robust humerus with a well-developed deltopectoral crest, a short robust ulna with a well-developed olecranon process, a trowel-like manus, and decreased numbers of pedal phalanges. Although not fossorial, ankylosaurids were likely able to dig the substrate, taking advantage of it for self-defence and survival.

Resource constrained project scheduling problems (RCPSPs) are complex optimization problems that aim to minimize project completion time after considering limited resources and precedence-related activities with known durations. However, due to the dynamic nature of real-world applications, activity durations are vulnerable to change. In addition, resource demands along with resource availability at any stage of a project can also vary due to disruptions, which compel practitioners to re-think existing scheduling methodologies. Consequently, to mitigate the conjoint effect of those uncertainties and/or disruptions, this paper proposes a real-time reactive scheduling approach. To deal with uncertain activity durations, a chance constrained based approach is followed, which is later solved by an advanced meta-heuristic based approaches called IGFBIS and IGFBID. After solving an exhaustive list of stochastic RCPSP instances, this paper proves the efficacy of the proposed approaches, which is proven to be more useful to mitigate uncertainty or disruption while executing real-life projects.

Multilevel converters (MLCs) are extensively used in medium- and high-power applications. Currently, MLCs are also used in grid integration of renewable sources of energy. In this paper a three-phase 11-level MLC topology is investigated which requires a smaller number of active switches compared to similar existing topologies for the same number of levels. In order to eliminate lower order harmonics, selective harmonic elimination (SHE) pulse width modulation technique is used. A projectile target search (PTS) algorithm is used to solve nonlinear SHE equations to determine the optimum values of switching angles to eliminate 5th, 7th, 11th and 13th harmonics from the converter output voltage. The PTS algorithm finds the best value of switching angles for different modulation indices (M) and these values are used in simulating the converter for eliminating lower order harmonics. Total harmonic distortion (THD) analysis is conducted for PTS optimization techniques at different modulation index. Simulation results are verified by hardware-in-the-loop test of the proposed three-phase converter using a Typhoon HIL-402 emulator.

The Resource-Constrained Project-Scheduling Problem (RCPSP) is an NP-hard problem which can be found in many research domains. The optimal solution of the RCPSP problems requires a balance between exploration/exploitation and diversification/intensification. With this in mind, quantum-inspired evolutionary algorithms' ability to improve the population and quality of solutions, this work investigates the performance of a quantum-inspired genetic algorithm (QIGA), which has been adapted to work with RCPSPs. The proposed QIGA possesses the same structure as classical genetic algorithms, but the initial and updated populations are implemented using quantum gates and quantum superposition, bearing in mind the adaptation of such operators to fit with discrete problems. This work aims to solve RCPSPs using the QIGA to investigate the influence of the various quantum parameters in the proposed algorithm, such as the quantum population size, different options for the quantum gates and re-combination to use in the QIGA. The well-known PSPLIB benchmark instances of J30, J60 and J120 activities are used to test the effectiveness and performance of the proposed QIGA. It is apparent from the results that quantum mutation, quantum crossover and representation of quantum superposition using quantum gates enhances population diversity. The QIGA is also found to outperform many other evolutionary algorithms.

The net present value (NPV)-based resource constrained project scheduling problem (RCPSP) is a well-known scheduling problem in many industries, such as construction, software development, and manufacturing. Over the last five decades, although different approaches have been proposed to solve the problem, no single approach has been shown to achieve satisfactory performances with quality solutions for a wide range of problems. This study presents a hybrid immune genetic algorithm (IGA) to solve NPV-based RCPSPs. Hybridizing a genetic algorithm (GA) with an immune algorithm (IA) enhances the overall performance of their standalone components (i.e., only GA or IA). Performance of the proposed IGA is further improved by applying a variable insertion based local search (VINS) and forward-backward improvement (FBI). A restart mechanism is presented to the algorithm which induces diversity and helps to avoid becoming trapped in local optima. Moreover, an activity move rule (AMR) is implemented to shift the negative cash flow associated activities to further improve the NPV. Taguchi Design of Experiment (DOE) is conducted to investigate the impact of various parameters and to determine the appropriate set of parameters for the proposed IGA. The performances of the proposed algorithms are tested on 17,280 standard benchmark instances ranging from 25 to 100 activities. Comparison with the state-of-art algorithms through extensive numerical experiments reveal the effectiveness of the proposed algorithms. Overall, the proposed algorithm outperforms existing algorithms, particularly the projects with 0% and 100% negative cash flow associated activities, the 75-activity instances, and the projects with two resources usage in terms of a lower value of average percentage deviation.

This article presents a high-gain DC-to-DC converter with a single switch, called the cubic converter, which provides very high voltage gain compared to the existing topologies such as the quadratic converter and conventional boost converter. The operation of the proposed converter at a lower duty ratio ensures lesser conduction losses. Various mathematical approaches are employed to confirm the higher voltage gain and improved efficiency of the converter. The proposed cubic boost converter (CBC) is compared with the quadratic boost converter (QBC) and other converters discussed in the literature. A generalized nth-order boost converter is also derived. To test the effectiveness of the QBC and CBC circuits, the Hardware-In-the-Loop (HIL) validation is performed using Typhoon HIL 402 real-time emulator machine. Moreover, the proposed topology is tested and compared with other topologies for maximum power point tracking (MPPT) of a solar photovoltaic (PV) array to show its effectiveness in a real-world scenario. A detailed comparison between conventional boost, QBC and CBC is presented for dynamic partial shading conditions in real-time mode using Typhoon HIL 402 real-time emulator machine.

When subjected to partial shading (PS), photovoltaic (PV) arrays suffer from the significantly reduced output. Although the incorporation of bypass diodes at the output alleviates the effect of PS, such modification results in multiple peaks of output power. Conventional algorithms—such as perturb and observe (P&O) and hill-climbing (HC)—are not suitable to be employed to track the optimal peak due to their convergence to local maxima. To address this issue, various artificial intelligence (AI) based algorithms—such as an artificial neural network (ANN) and fuzzy logic control (FLC)—have been employed to track the maximum power point (MPP). Although these algorithms provide satisfactory results under PS conditions, a very large amount of data is required for their training process, thereby imposing an excessive burden on processor memory. Consequently, this paper proposes a novel optimization algorithm based on stochastic search (random exploration of search space), known as the adaptive jaya (Ajaya) algorithm in which two adaptive coefficients are incorporated for maximum power point tracking (MPPT) with a rapid convergence rate, fewer power fluctuations and high stability. The algorithm successfully eliminates the issues associated with existing conventional and AI-based algorithms. Moreover, the proposed algorithm outperforms other state-of-the-art stochastic search-based techniques in terms of fewer fluctuations, robustness, simplicity, and faster convergence to the optima. Extensive analysis of results obtained from MATLAB® is done to prove the above performance parameters under static insolation conditions (using a three, four and a five-module series-connected PV system), under dynamically varying insolation (using a four-module series connected system), by changing the PV module rating (using a four-module series connected system) and using an IEC standard.

Robots that can move autonomously and can make intelligent decisions by perceiving their environments and surrounding objects are known as autonomous mobile robots. Such robots have rapidly moved from laboratories to automated industries to fill a variety of roles in our lives, homes, offices, hospitals, industries, and even on the streets. The interest in mobile robots is growing rapidly, prompting an enormous amount of research over the last 30 years, on critical factors of mobile robots such as locomotion, perception, localization, mapping, ego-motion tracking, and dynamic navigation. This article surveys these essential factors of autonomous mobile robots in terms of mathematical modeling, control issues, and challenging factors. Brief discussions are provided on the fundamentals of these technologies, popular algorithms in comprehensive mode, future challenges, and promising directions to guide the construction of an autonomous mobile robot with high accuracy and effectiveness. Since it is difficult to find complete coverage of those topics in a single location, this article provides a guideline for researchers entering the field or for innovators in the mobile robotics sector. The paper also examines open challenges in indoor mobile robots and identifies potential futures for autonomous mobile robots.

High voltage conversion dc/dc converters have perceived in various power electronics applications in recent times. In particular, the multi-port converter structures are the key solution in DC microgrid and electric vehicle applications. This paper focuses on a modified structure of non-isolated four-port (two input and two output ports) power electronic interfaces that can be utilized in electric vehicle (EV) applications. The main feature of this converter is its ability to accommodate energy resources with different voltage and current characteristics. The suggested topology can provide a buck and boost output simultaneously during its course of operation. The proposed four-port converter (FPC) is realized with reduced component count and simplified control strategy which makes the converter more reliable and cost-effective. Besides, this converter exhibits bidirectional power flow functionality making it suitable for charging the battery during regenerative braking of an electric vehicle. The steady-state and dynamic behavior of the converter are analyzed and a control scheme is presented to regulate the power flow between the diversified energy supplies. A small-signal model is extracted to design the proposed converter. The validity of the converter design and its performance behavior is verified using MATLAB simulation and experimental results under various operating states.

This article presents an 11-level operation of the WE (Wee)-Type inverter. The topology employs a single DC-source, has a reduced number of components, and exhibits a boosting capability. A voltage balancing algorithm is proposed where the inverter’s redundant states are employed to maintain the auxiliary DC-link voltage. It is shown that with the control algorithm, the link voltage is preserved at half the primary DC-link voltage, and the 11-level operation is possible for any load. The presented 11-level WE-type structure is also compared with recent 11-level structures and has a lowest cost factor. Two modulation strategies verify the 11-level operation of the inverter: first, a modified nearest level control (MNLC) with the usage of both zero states is developed; and, second, selective harmonic elimination (SHE) is employed, where the angles are generated using a differential evolution (DE) technique. The maximum efficiency of the inverter is 97.55 %. The performance of the inverter is validated in MATLAB/Simulink and on the hardware-in-the-loop platform.

In this work, the evaluation of the design and optimization of proposed offgrid hybrid microgrid systems for different load dispatch strategies is presented by assessing the component sizes, system responses and different cost analyses of the proposed system. This study optimizes the sizing of the Barishal and Chattogram (two popular divisions in Bangladesh) hybrid microgrid systems consisting of wind turbine, storage unit, solar PV, diesel generator and a load profile of 27.31 kW for five dispatch techniques: (i) generator order, (ii) cycle charging, (iii) load following, (iv) HOMER predictive dispatch and (v) combined dispatch strategy. The considered microgrids are optimized for the least CO2 gas emission, Net Present Cost, and Levelized Cost of Energy. The two microgrids are analyzed for the five dispatch techniques using HOMER software, and subsequently, the power system performance and feasibility study of the microgrids are performed in MATLAB Simulink. The results in this research provide a guideline to estimate different component sizes and probable costing for the optimal operation of the proposed microgrids under various load dispatch conditions. The simulation results suggest that ‘Load Following’ is the best dispatch strategy for the proposed microgrids having a stable power system response with the lowest net present cost, levelized cost of energy, operating cost, and CO2 emission rate. Additionally, the combined dispatch strategy is determined to be the worst dispatch technique for the proposed off-grid hybrid microgrid design having the maximum levelized cost of energy, net present cost, operating cost and CO2 emission.

Battery ensures power solutions for many necessary portable devices such as electric vehicles, mobiles, and laptops. Owing to the rapid growth of Li-ion battery users, unwanted incidents involving Li-ion batteries have also increased to some extent. In particular, the sudden breakdown of industrial and lightweight machinery due to battery failure causes a substantial economic loss for the industry. Consequently, battery state estimation, management system, and estimation of the remaining useful life (RUL) have become a topic of interest for researchers. Considering this, appropriate battery data acquisition and proper information on available battery data sets may require. This review paper is mainly focused on three parts. The first one is battery data acquisitions with commercially and freely available Li-ion battery data set information. The second is the estimation of the states of battery with the battery management system. And third is battery RUL estimation. Various RUL prognostic methods applied for Li-ion batteries are classified, discussed, and reviewed based on their essential performance parameters. Information on commercially and publicly available data sets of many battery models under various conditions is also reviewed. Various battery states are reviewed considering advanced battery management systems. To that end, a comparative study of Li-ion battery RUL prediction is provided together with the investigation of various RUL prediction algorithms and mathematical modelling.

This paper presents new and efficient modulation techniques applied on the recently introduced compact nine-level switched-capacitor inverter (C9LSCI). The paper also discusses the performance of the inverter under selective harmonic elimination (SHE) and mitigation (SHM) based on the heuristic Bat-Algorithm (BA) technique. Two new modulation techniques employing CD-type carrier waves and M-type carrier waves are proposed, showing a rise in efficiency, an increase in RMS voltage, reduction in capacitor voltage ripple, and a reduction in harmonic distortion (THD). Four recently introduced modulating signals, namely the third harmonic injection, thirty-degree bus clamped PWM (THTDBCPWM), third harmonic injection sixty-degree bus clamped PWM (THSDBCPWM), one pole clamped PWM (OPCPWM). Loss balancing two-pole clamped PWM (LBTPCPWM) are applied to the inverter with the proposed carriers, and a comparative analysis is carried out on different performance parameters. The proposed carriers’ efficacy in Alternate Phase Opposition Disposition (APOD), Phase Opposition Disposition (POD), and Phase Disposition (PD) is validated. Further, Bat algorithm (BA) is applied as a heuristic approach to determine the optimum angles for the application of SHE and SHM. The efficacy of all the above techniques on the C9LSCI is verified in MATLAB/Simulink environment and further validated on an experimental setup.

This review provides a comprehensive overview of the state-of-the-art methods of graph-based networks from a deep learning perspective. Graph networks provide a generalized form to exploit non-euclidean space data. A graph can be visualized as an aggregation of nodes and edges without having any order. Data-driven architecture tends to follow a fixed neural network trying to find the pattern in feature space. These strategies have successfully been applied to many applications for euclidean space data. Since graph data in a non-euclidean space does not follow any kind of order, these solutions can be applied to exploit the node relationships. Graph Neural Networks (GNNs) solve this problem by exploiting the relationships among graph data. Recent developments in computational hardware and optimization allow graph networks possible to learn the complex graph relationships. Graph networks are therefore being actively used to solve many problems including protein interface, classification, and learning representations of fingerprints. To encapsulate the importance of graph models, in this paper, we formulate a systematic categorization of GNN models according to their applications from theory to real-life problems and provide a direction of the future scope for the applications of graph models as well as highlight the limitations of existing graph networks.

This work introduces a 49-level Asymmetrical Inverter (AMLI) with boosted output based on the cascaded operation of two 7-Level Modified Packed U-Cell inverters (MPUC-7). The converter is capable of operation with a boosted voltage of up to 1.714 times the maximum DC voltage employed. It requires only 12 active switches and 4 voltage sources. With the sources set in the ratio of 14:7:2:1, the 7-level output of the two converters is so utilized that the 72 = 49-level output voltage is generated across the load. A detailed explanation of level formation is discussed. This converter is operated using an Artificial Neural Network (ANN) which is trained for the harmonic elimination in the output voltage waveform. For the calculation of optimum angles, a meta-heuristic based Genetic Algorithm (GA) technique is employed. The generation of 49-level output requires 24 transitions in one quarter of a cycle. All these angles are generated for various desired output voltages, and the ANN is trained offline for the same. The converter and its control are simulated in MATLAB/Simulink® environment, and the results are verified on the experimental setup. The multilevel output thus obtained is nearly sinusoidal and the Total Harmonic Distortion (THD) thus produced is under the specified limit of IEEE.

Although several multi-operator and multi-method approaches for solving optimization problems have been proposed, their performances are not consistent for a wide range of optimization problems. Also, the task of ensuring the appropriate selection of algorithms and operators may be inefficient since their designs are undertaken mainly through trial and error. This research proposes an improved optimization framework that uses the benefits of multiple algorithms, namely, a multi-operator differential evolution algorithm and a co-variance matrix adaptation evolution strategy. In the former, reinforcement learning is used to automatically choose the best differential evolution operator. To judge the performance of the proposed framework, three benchmark sets of bound-constrained optimization problems (73 problems) with 10, 30 and 50 dimensions are solved. Further, the proposed algorithm has been tested by solving optimization problems with 100 dimensions taken from CEC2014 and CEC2017 benchmark problems. A real-world application data set has also been solved. Several experiments are designed to analyze the effects of different components of the proposed framework, with the best variant compared with a number of state-of-the-art algorithms. The experimental results show that the proposed algorithm is able to outperform all the others considered.

The study of deoxyribonucleic acid (DNA) is crucial in many fields, including medicine, biology, zoology, agriculture, and forensics. Since reading a DNA sequence is onerous because of its massive length, it is common in many DNA analysis applications to divide DNA strands into small segments or fragments which, after analysis, must be reassembled. Since this reassembly takes a non-specific polynomial time to solve, the DNA fragment assembly problem (DFAP) is NP-hard. This paper proposes a new assembler for tackling the DFAP based on the overlap-layout-consensus (OLC) approach. The proposed assembler adapts a discrete whale optimization algorithm (DWOA) using standard operators adopted from evolutionary algorithms to simulate the strategy adopted by humpback whales when searching for prey. For the first time, we formulate the behaviors of whales to be applied directly to any discrete optimization problem based on three primary operations: a swap-based best-position operator, an ordered crossover operator, and selection of a random whale operation to perform the exploitation and exploration phases of the algorithm. These operations were carefully designed to preserve the methodology of the original whale algorithm. DFAP is a multi-objective problem that seeks to reach the optimal order of segments that maximizes the overlap score and minimizes the number of contigs (set of overlapping DNA segments) to compose a one-contig DNA strand. Existing local search methods, such as problem aware local search (PALS) many non-conflicting movements (PALS2-many), suffer from being trapped in local optima. Hence, the integration of DWOA with PALS2-many improves the search capability for finding the optimal order of fragments. In addition, we propose a new variation of PALS2-many that achieves simultaneously the two objectives of DFAP. Our proposed DWOA was compared with a number of the most recent robust assemblers: a hybrid crow search algorithm for solving the DFAP (CSA-P2M*Fit), P2M*Fit, and a hybrid genetic algorithm (GA-P2M*Fit). The experimental results and statistical analyses of the proposed DWOA on thirty benchmark instances show that DWOA significantly outperforms those algorithms in reaching fewer contigs, in addition to being competitive with CSA-P2M*Fit and superior to P2M*Fit and GA-P2M*Fit for the overlap score.

Abstract Background Placental ischemia and hypertension, characteristic features of preeclampsia, are associated with impaired cerebral blood flow (CBF) autoregulation and cerebral edema. However, the factors that contribute to these cerebral abnormalities are not clear. Several lines of evidence suggest that angiotensin II can impact cerebrovascular function; however, the role of the renin angiotensin system in cerebrovascular function during placental ischemia has not been examined. We tested whether the angiotensin type 1 (AT1) receptor contributes to impaired CBF autoregulation in pregnant rats with placental ischemia caused by surgically reducing uterine perfusion pressure. Methods Placental ischemic or sham operated rats were treated with vehicle or losartan from gestational day (GD) 14 to 19 in the drinking water. On GD 19, we assessed CBF autoregulation in anesthetized rats using laser Doppler flowmetry. Results Placental ischemic rats had impaired CBF autoregulation that was attenuated by treatment with losartan. In addition, we examined whether an agonistic autoantibody to the AT1 receptor (AT1-AA), reported to be present in preeclamptic women, contributes to impaired CBF autoregulation. Purified rat AT1-AA or vehicle was infused into pregnant rats from GD 12 to 19 via mini-osmotic pumps after which CBF autoregulation was assessed. AT1-AA infusion impaired CBF autoregulation but did not affect brain water content. Conclusions These results suggest that the impaired CBF autoregulation associated with placental ischemia is due, at least in part, to activation of the AT1 receptor and that the RAS may interact with other placental factors to promote cerebrovascular changes common to preeclampsia.

Goniopholididae is a group of basal neosuchian crocodyliforms closely related to Paralligatoridae and Eusuchia that lived during the Jurassic and Early Cretaceous. Goniopholidids have the long, flat snout and secondary palate of modern crocodylians, the acquisition of which is regarded as a key feature in the early evolution of crocodylian body plan and their aquatic adaptation. Here, we report a new species, Amphicotylus milesi, with the description from the best-preserved specimen to date of Goniopholididae from Wyoming, USA. Its posterior extension of the nasopharyngeal passage (pterygoid secondary palate) and the shortening and dorsal deflection of the ceratobranchial suggest that basal neosuchians could raise their gular valve to separate oral and pharyngeal cavities as in modern crocodylians. The anatomy of Amphicotylus milesi sheds light on the acquisition of this new respiratory system in the crocodyliform evolution and their early aquatic adaptation, leading to modern crocodylians.

Sexual reproduction is nearly ubiquitous in the vertebrate world, yet its evolution and maintenance remain a conundrum due to the cost of males. Conversely, asexually reproducing species should enjoy a twofold population increase and thus replace sexual species all else being equal, but the prevalence of asexual species is rare. However, stable coexistence between asexuals and sexuals does occur and can shed light on the mechanisms asexuals may use in order to persist in this sex-dominated world. The asexual Amazon molly (Poecilia formosa) is required to live in sympatry with one of its sexual sperm hosts –sailfin molly (Poecilia latipinna) and Atlantic molly (Poecilia mexicana)—and are ecological equivalents to their host species in nearly every way except for reproductive method. Here, we compare the visual lateralization between Amazon mollies and sailfin mollies from San Marcos, Texas. Neither Amazon mollies nor sailfin mollies exhibited a significant eye bias. Additionally, Amazon mollies exhibited similar levels of variation in visual lateralization compared to the sailfin molly. Further investigation into the source of this variation –clonal lineages or plasticity—is needed to better understand the coexistence of this asexual-sexual system.

Elasmosaurid plesiosaurian remains have been documented from non-marine to paralic (fluvial to estuarine) sediments of the upper Campanian Dinosaur Park Formation (DPF) of southern Alberta since 1898. Despite this long collection history, this material has received relatively little research attention, largely due to the highly fragmentary nature of most recovered specimens. However, this assemblage is significant, as it constitutes a rare occurrence of plesiosaurian remains in a non-marine depositional environment. This study reports on a recently collected and prepared specimen, which represents the most complete elasmosaurid yet collected from the DPF. This specimen preserves the trunk region, the base of the neck and tail, a partial fore and hind limb, and tooth, and is sufficiently complete to be assigned as the holotype of a new genus and species. This new taxon is diagnosed by a distinctive character state combination including a boomerang-shaped clavicular arch with acute anterior process, convex anterolateral margin, deeply embayed posterior margin, and pronounced ventral keel, together with the presence of 22 dorsal vertebrae, and the anterior dorsal centra bearing a ventral notch. The DPF plesiosaurian fossils were recovered from both estuarine/bay and fluvial palaeochannel sediments. The holotype skeleton represents an osteologically mature individual with an estimated body length of around 5 m, although the largest referred DPF elasmosaurid might have been closer to 7 m, which is considerably larger than other plesiosaurians reported from non-marine deposits. This suggests small-body lengths relative to typical elasmosaurids from marine settings, but is consistent with other plesiosaurians recovered from non-marine sediments. The identification of a distinct elasmosaurid taxon in the DPF might be evidence of niche-partitioning among the predominantly oceanic members of the ubiquitous plesiosaurian clade.

Abstract Autoimmune diseases such as psoriasis, rheumatoid arthritis, and systemic lupus erythematosus (SLE) have high rates of hypertension and cardiovascular disease. Systemic lupus erythematosus is a prototypic autoimmune disorder that primarily affects women of childbearing age and is associated with a loss of self‐tolerance, autoreactive B and T lymphocytes, and the production of autoantibodies, especially to nuclear components. In this study, we hypothesized that the pristane‐inducible model of SLE would develop hypertension and vascular dysfunction as the disease progressed. To test this hypothesis, female C57BL/6 mice were administered PBS or pristane. Seven months after pristane administration, mice developed various autoantibodies, including anti‐dsDNA IgG, anti‐ssDNA IgG, and anti‐nRNP IgG, as well as hypergammaglobulinemia. Several other immunological changes, including increased circulating neutrophils and increased CD4−CD8− (double negative) thymocytes were also detected. Mean arterial pressure (MAP) was elevated in pristane‐treated mice when compared to PBS‐treated mice. In addition, second‐order mesenteric arteries from pristine‐treated mice had impaired relaxation to the endothelium‐dependent vasodilator acetylcholine compared to PBS‐treated mice. These data suggest that the immune system dysfunction present in the pristane model of lupus contributes to the development of hypertension and vascular dysfunction.

Over the last few decades, there has been a resurgent interest in New World martial art traditions. The bulk of the attention has focused on African and African diasporic traditions. Many well-researched books and articles have resulted from this focus. Yet, there is much less interest regarding other combative modalities brought to the shores of the New World. For centuries immigrant communities have brought with them sophisticated combative systems that persist to this day. As part of a broader hoplological project, this article seeks to identify and document the diverse armed combative systems still extant and practiced in South America and the Caribbean that have not transformed into solely institutionalized sports or recreational pastimes. With few exceptions these arts continue to be taught, practiced, and used in a variety of informal situations to ensure one’s property or public reputation or as part of an economic strategy in the informal economy. At times paralleling and overlapping these more pragmatic goals, these arts also persist as a way of preserving older cultural moralities, ethics, and forms of masculinity.

Reliable and efficient risk assessments are essential to deal effectively with potential risks in international construction projects. However, most conventional risk modeling methods are based on the hypothesis that risk factors are independent, which does not account adequately for the causal relationships among risk factors. In this study, a risk assessment model for international construction projects was developed to improve the efficacy of risk management by integrating fault tree analysis and fuzzy set theory with a Bayesian belief network. The risk rating of each risk factor, expressed as the product of risk occurrence probability and impact, was incorporated into the risk assessment model to evaluate degrees of risk. Therefore, risk factors were categorized into different risk levels taking into account their inherent causal relationships, which allowed the identification of critical risk factors. The applicability of the fuzzy Bayesian belief network-based risk assessment model was verified using a case study through a comparative analysis with the results from a fuzzy synthetic evaluation method. The comparison shows that the proposed risk assessment model is able to provide guidelines for an effective risk management process and ultimately to increase project performance in a complex environment such as international construction projects.

Abstract Systemic lupus erythematosus (SLE) is an autoimmune disorder with prevalent hypertension and renal disease. To avoid side effects of immunosuppressive drugs, alternative therapies are needed. Curcumin has been used in Eastern medicine for its anti‐inflammatory and antioxidant properties. This study tested whether oral curcumin administration attenuates autoimmunity and renal injury during SLE. Female NZBWF1 (model of SLE) and NZW/LacJ (control) mice were administered curcumin (500 mg kg‐1 day‐1, oral gavage) for 14 days in two separate groups beginning at either 26 or 32 weeks of age. Body weight and composition were monitored throughout the study. Immune activity was assessed by spleen weight, circulating dsDNA autoantibodies, and B lymphocytes. Renal injury (albumin excretion, glomerulosclerosis, blood urea nitrogen (BUN)) was measured as a hemodynamic function (glomerular filtration rate (GFR), mean arterial pressure (MAP)) in conscious mice. Body weight and composition were maintained in curcumin‐treated SLE mice, but decreased in vehicle‐treated SLE mice. Curcumin‐treated SLE mice had lower spleen weight and renal injury (glomerulosclerosis) compared to vehicle‐treated SLE mice when treatment started at 26 weeks of age. When curcumin treatment started at 32 weeks of age, renal injury (glomerulosclerosis, BUN) was reduced in SLE mice compared to vehicle‐treated SLE mice. GFR was reduced, and MAP was increased in vehicle‐treated SLE mice compared to controls; however, these were not improved with curcumin. No significant changes were observed in curcumin‐treated control mice. These data suggest that curcumin modulates autoimmune activity and may lessen renal injury in female mice with SLE.

Ceratopsids are among the most ubiquitous dinosaur taxa from the Late Cretaceous terrestrial formations of the Western Interior of North America, comprising two subfamilies, Chasmosaurinae and Centrosaurinae. The Two Medicine Formation of northwestern Montana has produced numerous remains of centrosaurine dinosaurs, which represent three taxa previously considered valid: Rubeosaurus ovatus, Einiosaurus procurvicornis and Achelousaurus horneri. Here, we reassess the previous referral of specimens to Rubeousaurus ovatus and demonstrate that this taxon is represented solely by its holotype specimen, which was first diagnosed as Styracosaurus ovatus. One of the specimens previously referred to ‘Rubeosaurus’ ovatus instead represents a new eucentrosauran centrosaurine taxon diagnosed here, Stellasaurus ancellae gen. et sp. nov. Stellasaurus expresses a unique combination of eucentrosauran centrosaurine characters, including an elongate nasal horncore, diminutive supraorbital horncores, and a parietal bearing straight, elongate P3 processes, semi-elongate P4 processes and non-elongate P5, P6 and P7 processes. Within the stratigraphic succession of Eucentrosaura, Stellasaurus occurs intermediate to Styracosaurus albertensis and Einiosaurus, and likewise reflects intermediate morphology. Assessed within the stratigraphic, geographical, taphonomic, ontogenetic and phylogenetic framework of Unified Frames of Reference, we fail to reject the hypothesis that Stellasaurus ancellae represents a transitional taxon within an anagenetic lineage of eucentrosauran centrosaurines.

Visual cues are often a vital part of animal communication and courtship. While a plethora of studies have focused on the role that hormones play in acoustic communication of anurans, relatively few have explored hormonal modulation of vision in these animals. Much of what we do know comes from behavioral studies, which show that a frog’s hormonal state can significantly affect both its visual behavior and mating decisions. However, to fully understand how frogs use visual cues to make these mating decisions, we must first understand how their visual system processes these cues, and how hormones affect these processes. To do this, we performed electroretinograms (ERGs) to measure retinal sensitivity of túngara frogs (Physalaemus pustulosus), a neotropical species whose mating behavior includes previously described visual cues. To determine the effect of hormonal state on visual sensitivity, ERGs were recorded under scotopic and photopic conditions in frogs that were either non-reproductive or hormone-treated with human chorionic gonadotropin (hCG) prior to testing. Additionally, measurements of optical anatomy determined how túngara frog eye and retina morphology related to physiological sensitivity. As expected, we found that both sexes display higher visual sensitivity under scotopic conditions compared to photopic conditions. However, hormone injections significantly increased retinal sensitivity of females under scotopic conditions. These results support the hypothesis that hormonal modulation of neural mechanisms, such as those mediating visually guided reproductive behavior in this species, include modulation of the receptor organ: the retina. Thus, our data serve as a starting point for elucidating the mechanism of hormonal modulation of visual sensitivity.

Animal sexual signals should be conspicuous to mates but not to enemies. Here, the authors show that call site properties can set limits on the attractiveness of male frogs' advertisement call, but that males may balance sexual success over predation risk by digging deeper puddles.

Near infrared (NIR) remote sensing has applications in vegetation analysis as well as geological investigations. For extra-terrestrial applications, this is particularly relevant to Moon, Mars and asteroid exploration, where minerals exhibiting spectral phenomenology between 600 and 800 nm have been identified. Recent progress in the availability of processors and sensors has created the possibility of development of low-cost instruments able to return useful scientific results. In this work, two Raspberry Pi camera types and a panchromatic astronomy camera were trialed within a pushbroom sensor to determine their utility in measuring and processing the spectrum in reflectance. Algorithmic classification of all 15 test materials exhibiting spectral phenomenology between 600 and 800 nm was easily performed. Calibration against a spectrometer considers the effects of the sensor, inherent image processing pipeline and compression. It was found that even the color Raspberry Pi cameras that are popular with STEM applications were able to record and distinguish between most minerals and, contrary to expectations, exploited the infra-red secondary transmissions in the Bayer filter to gain a wider spectral range. Such a camera without a Bayer filter can markedly improve spectral sensitivity but may not be necessary.

Ornithomimid material from the Belly River Group (Campanian) of Alberta, Canada is described as sharing characters with Qiupalong henanensis from the Qiupa Formation of Henan Province, China. Derived characters and character combinations of the pubis and astragalocalcaneum were previously used to diagnose Q. henanensis and support the referral of this material to Qiupalong sp., representing the first known occurrences of Qiupalong outside of China. Qiupalong is the sixth ornithomimid taxon to be reported from the Dinosaur Park Formation and the first ornithomimid genus with a transcontinental distribution. The Alberta material represents the oldest known occurrences of Qiupalong, and a reconsideration of character evidence suggests that this genus is phylogenetically nested within other North American ornithomimids. A North American origin for Qiupalong and subsequent dispersal to Asia is proposed.

The Dinosaur Park Formation (DPF) has a diverse assemblage of chasmosaurines currently represented by Chasmosaurus belli, C. russelli, Vagaceratops irvinensis, and Mercuriceratops gemini, and may also include remains possibly referable to Spiclypeus shipporum. Two skulls, YPM 2016 and AMNH 5402, previously referred to C. belli, both have a straight posterior parietal bar with five epiparietals present (YPM 2016) or inferred (AMNH 5402) on each side – the combination of which is unique to V. irvinensis. Based on our new morphological observations and interpretations of these two skulls, we recover V. irvinensis as a species of Chasmosaurus (C. irvinensis), although the interrelationships between C. irvinensis, C. belli, and C. russelli remain unclear. We refrain from formerly assigning YPM 2016 and AMNH 5402 to C. irvinensis, however, as their parietal fenestrae are significantly larger and their epiparietals are significantly shorter than those of C. irvinensis; instead, we reassign these two skulls to Chasmosaurus sp. Given the low stratigraphic position of YPM 2016 (unknown in AMNH 5402) relative to C. irvinensis, we believe this specimen to represent a basal member of the lineage leading to C. irvinensis. If our assessment is correct, this would indicate that the C. irvinensis lineage has a large degree of stratigraphic overlap with that of C. belli and C. russelli. The close phylogenetic relationship and supposed stratigraphic separation for these three taxa reported in previous studies were used to suggest that they may represent an anagenetic lineage, whereby C. russelli evolved into C. belli, and C. belli evolved into, and was entirely replaced by, the latter. However, the lack of stratigraphic separation between these three taxa indicates that they instead arose via cladogenesis.

Ontogenetic sequences are relatively rare among dinosaurs, with Ceratopsia being one of the better represented clades, and especially among geologically earlier forms, such as Psittacosaurus. Psittacosaurus is a small, bipedal basal ceratopsian abundant in the Lower Cretaceous deposits of Asia, whose cranial and endocranial morphology has been well studied, but only cursory details have been published on the bones surrounding the brain. Using reconstructions created from micro-computed tomography scans of well-preserved skulls from the Barremian–Aptian Yixian Formation, China, we document morphological changes in the braincase of Psittacosaurus lujiatunensis through three growth stages, hatchling, juvenile, and adult, thus providing the first detailed study of ceratopsian braincase morphology through ontogeny. Notable ontogenetic changes in the braincase of P. lujiatunensis include a dramatic relative reduction in size of the supraoccipital, an increase in the lateral expansion of the paroccipital processes and a decrease in the angle between the lateral semicircular canal and the palatal plane. These ontogenetic morphological changes in the braincase relate to expansion of the cranium and brain through growth, as well as reflecting the switch from quadrupedal juveniles to bipedal adults as documented in the changing orientation of the horizontal semicircular canal through ontogeny. Recognition of these patterns in a basal ceratopsian has implications for understanding key events in later ceratopsian evolution, such as the development of the parieto-squamosal frill in derived neoceratopsians.

Abstract Cardiovascular disease is the major cause of mortality among patients with the autoimmune disorder systemic lupus erythematosus (SLE). Our laboratory previously reported that immunosuppression with mycophenolate mofetil, a common therapy in patients with SLE, attenuates the development of hypertension in an experimental model of SLE. Cyclophosphamide (CYC) is another common therapy for patients with SLE that has contributed to improved disease management; however, its impact on the development of hypertension associated with SLE is not clear. We tested whether treatment with CYC (25 mg/kg, once/week, IP injection) for 4 weeks would attenuate hypertension in an established female mouse model of SLE with hypertension (30‐week‐old NZBWF1 females). Plasma anti‐dsDNA IgG levels, pathogenic for the disease, were lower in CYC‐treated SLE mice compared to vehicle‐treated SLE mice, suggesting efficacy of the therapy to suppress aberrant immune system function. Mean arterial pressure (MAP) was assessed by carotid artery catheters in conscious mice. Treatment did not attenuate the development of hypertension when compared to vehicle‐treated SLE mice; however, urinary albumin excretion was lower in CYC‐treated animals. Corresponding with the reduction in autoantibodies, data suggest that CYC treatment lowered circulating CD45R+ B cells. Paradoxically, circulating CD11b+Ly6G+ neutrophils were increased in CYC‐treated SLE mice compared to vehicle treated. Estrus cycling data also suggest that CYC treatment had an impact on ovarian function that may be consistent with reduced circulating estrogen levels. Taken together, these data suggest that CYC treatment attenuates autoantibody production and renal disease during SLE, but that the potential to affect MAP may be blunted by the increase in circulating neutrophils and CYC's impact on ovarian function.

The optimization of photovoltaic (PV) systems relies on the development of an accurate model of the parameter values for the solar/PV generating units. This work proposes a modified artificial jellyfish search optimizer (MJSO) with a novel premature convergence strategy (PCS) to define effectively the unknown parameters of PV systems. The PCS works on preserving the diversity among the members of the population while accelerating the convergence toward the best solution based on two motions: (i) moving the current solution between two particles selected randomly from the population, and (ii) searching for better solutions between the best-so-far one and a random one from the population. To confirm its efficacy, the proposed method is validated on three different PV technologies and is being compared with some of the latest competitive computational frameworks. The numerical simulations and results confirm the dominance of the proposed algorithm in terms of the accuracy of the final results and convergence rate. In addition, to assess the performance of the proposed approach under different operation conditions for the solar cells, two additional PV modules (multi-crystalline and thin-film) are investigated, and the demonstrated scenarios highlight the utility of the proposed MJSO-based methodology.

In this research, a new approach for tackling the permutation flow shop scheduling problem (PFSSP) is proposed. This algorithm is based on the steps of the elitism continuous genetic algorithm improved by two strategies and used the largest rank value (LRV) rule to transform the continuous values into discrete ones for enabling of solving the combinatorial PFSSP. The first strategy is combining the arithmetic crossover with the uniform crossover to give the algorithm a high capability on exploitation in addition to reducing stuck into local minima. The second one is re-initializing an individual selected randomly from the population to increase the exploration for avoiding stuck into local minima. Afterward, those two strategies are combined with the proposed algorithm to produce an improved one known as the improved efficient genetic algorithm (IEGA). To increase the exploitation capability of the IEGA, it is hybridized a local search strategy in a version abbreviated as HIEGA. HIEGA and IEGA are validated on three common benchmarks and compared with a number of well-known robust evolutionary and meta-heuristic algorithms to check their efficacy. The experimental results show that HIEGA and IEGA are competitive with others for the datasets incorporated in the comparison, such as Carlier, Reeves, and Heller.