Maintaining and restoring ecological connectivity is considered a global imperative to help reverse the decline of biodiversity. To be successful, practitioners need to be guided by connectivity modeling research that is rigorous and reliable for the task at hand. However, the methods and workflows within this rapidly growing field are diverse and few have been rigorously scrutinized. We propose three procedural steps that should be consistently undertaken and reported on in connectivity modeling studies in order to improve rigour and utility: (1) describe the type of connectivity being modeled, (2) assess the uncertainty and sensitivity of model parameters, and (3) validate the model outputs, ideally with independent data. We reviewed the literature to determine the extent to which studies included these three steps. We focused on studies that generated novel landscape connectivity outputs using circuit theory. Among 181 studies meeting our search criteria, 39% communicated the type of connectivity being modeled and 18% conducted some form of sensitivity or uncertainty analysis (or both). Only 19% of studies attempted to validate their connectivity model outputs and only 7% used fully independent data. Our findings highlight a clear need and opportunity to improve the rigour, reliability, and utility of connectivity modeling research. At a minimum, researchers should be transparent about which, if any, of these three steps were undertaken. This will help practitioners make more informed decisions and ensure limited resources for connectivity conservation and restoration are allocated appropriately.

The present study presents an alternative analytical workflow that combines mid-infrared (MIR) microscopic imaging and deep learning to diagnose human lymphoma and differentiate between small and large cell lymphoma. We could show that using a deep learning approach to analyze MIR hyperspectral data obtained from benign and malignant lymph node pathology results in high accuracy for correct classification, learning the distinct region of 3900 cm-1 to 850 cm-1. The accuracy is above 95% for every pair of malignant lymphoid tissue and still above 90% for the distinction between benign and malignant lymphoid tissue for binary classification. These results demonstrate that a preliminary diagnosis and subtyping of human lymphoma could be streamlined by applying a deep learning approach to analyze MIR spectroscopic data.

A document by David Slotwiner. Click on the document to view its contents.

Rapid urbanization and global climate change are likely to exacerbate urban flooding intensity, frequency, and uncertainty. Thus, it is fundamental and crucial to investigate the dominant influencing factors for the mitigation of urban flooding. However, the influence of building patterns on urban flooding remains limited. Taking Beijing, a typical megacity, as a case study area, we quantified the importance of building patterns and their interaction effect at the subwatershed scale using the boosted regression tree (BRT) and geographical detector model (GeoD). The results indicated that (1) the landscape shape index, slope, green space ratio and waterbody ratio were the most important influencing factors determining urban flooding, with a total relative contribution of 67.23%, (2) building metrics had a certain impact on urban flooding, and the sum of the relative contribution can reach 21.03%, (3) with urban flooding density, the landscape shape index, slope, and green space ratio exhibited a combination of negative and positive correlation, and (4) an enhancement effect existed between building metrics, especially the building congestion degree and building density. These findings provide quantitative insights that rational urban morphology planning can improve stormwater management and promote urban sustainability in megacities.

Plants can detect neighbouring plants through a reduction in the ratio between red and far-red light (R:FR). This provides a signal of plant-plant competition and induces rapid plant growth while inhibiting defence against biotic stress, two interlinked responses designated as the shade avoidance syndrome (SAS). Consequently, the SAS can influence plant-herbivore interactions that could cascade to higher trophic levels. However, little is known on how the expression of the SAS can influence tritrophic interactions. We investigated whether changes in R:FR affect the emission of herbivore-induced plant volatiles (HIPVs), and whether these changes influence the attraction of the zoophytophagous predator Macrolophus pygmaeus. We also studied how the expression of the SAS and subsequent inhibition of plant defences affects the reproduction of M. pygmaeus in both the presence and absence of the greenhouse whitefly ( Trialeurodes vaporariorum) as arthropod prey. The results show that changes in R:FR have little effect on HIPV emissions and predator attraction. However, a reduction in R:FR leads to increased reproduction of both the predator and the whiteflies. We conclude that shade avoidance responses can increase the population development of M. pygmaeus directly by reducing plant defences, and indirectly by supporting higher herbivore densities.

We aimed to report the case of a Pakistani female who presented with MMD and hyperthyroidism, and the worldwide literature review of the case reports on MMD associated with hyperthyroidism. Methods: The study was carried out using PRISMA’s recommendations. An electronic search on PubMed, Cochrane Library, and Google Scholar was carried out. Articles explaining the association between Moyamoya disease and thyroid-related diseases were included. Results: A total of 31 studies were included in the review, with the preponderance of Japanese females. The review has systematically compiled in detail all the aspects of moyamoya syndrome and thyroid disorders- from detailed histories of the included patients to the treatment interventions used and their outcomes. Conclusion: The authors are with the suggestion that more cases of MMD and its association with other major factors should be presented in Pakistan as well as in all parts of the world.

This paper aims to understand the binding strategies of a nanobody-protein pair by studying known complexes. Rigid body protein-ligand docking programs produce several complexes, called decoys, which are good candidates with high scores of shape complementarity, electrostatic interactions, desolvation, buried surface area, and Lennard-Jones potentials. It is not known which decoy represents the true structure. We studied thirty-seven nanobody-protein complexes from the Single Domain Antibody Database, sd-Ab DB, [http://www.sdab-db.ca/](http://www.sdab-db.ca/). For each structure, a large number of decoys are generated using the Fast Fourier Transform algorithm of the software ZDOCK. The decoys were ranked according to their target protein-nanobody interaction energies, calculated by using the Dreiding Force Field, with rank 1 having the lowest interaction energy. Out of thirty-six PDB structures, twenty-five true structures were predicted as rank 1. Eleven of the remaining structures required Ångstrom size rigid body translations of the nanobody relative to the protein to match the given PDB structure. After the translation the Dreiding interaction (DI) energies of all complexes decreased and became rank 1. In one case, rigid body rotations as well as translations of the nanobody were required for matching the crystal structure. We used a Monte Carlo algorithm that randomly translates and rotates the nanobody of a decoy and calculates the DI energy. Results show that rigid body translations and the DI energy are sufficient for determining the correct binding location and pose of ZDOCK created decoys. A survey of the sd-Ab DB showed that each nanobody makes at least one salt bridge with its partner protein, indicating that salt bridge formation is an essential strategy in nanobody-protein recognition. Based on the analysis of the thirty-six crystal structures and evidence from existing literature, we propose a set of principles that could be used in the design of nanobodies.

The purple tomato variety ‘Indigo Rose’(InR) is favored due to its bright appearance and abundant anthocyanins. SlHY5 is associated with anthocyanin biosynthesis in ‘Indigo Rose’ plants. However, residual anthocyanins still present in Slhy5 seedlings and fruit peel indicated there was an anthocyanin induction pathway that is independent of HY5 in plants. The molecular mechanism of color formation in ‘Indigo Rose’ and Slhy5 mutants is unclear. In this study, we performed omics analysis to clarify the regulatory network underlying coloration in seedling and fruit peel of ‘Indigo Rose’ and Slhy5 mutant. Results showed that the total amount of anthocyanins in both seedling and fruit of InR were significantly higher than those in Slhy5 mutant and most genes associated with anthocyanin biosynthesis exhibited higher expression levels in InR, suggesting that SlHY5 play pivotal roles in flavonoid biosynthesis both in tomato seedlings and fruit. Yeast two-hybrid (Y2H) results revealed that SlBBX24 physically interacts with SlAN2-like and SlAN2, while SlWRKY44 could interact with SlAN11 protein. Unexpectedly, both SlPIF1 and SlPIF3 were found to interact with SlBBX24, SlAN1 and SlJAF13 by yeast two-hybrid assay. Suppression of SlBBX24 by virus-induced gene silencing (VIGS) retarded the purple coloration of the fruit peel, indicating an important role of SlBBX24 in the regulation of anthocyanin accumulation. These results deepen the understanding of purple color formation in tomato seedling and fruits in an HY5-dependent or independent manner via excavating the genes involved in anthocyanin biosynthesis based on omics analysis.

Title: Sweet syndrome masquerading as a disseminated and pulmonary fungal disease in a child with acute myeloid leukemia: case report and review of the literature

In a case of dilated cardiomyopathy complicated by pulseless ventricular tachycardia, a shock was deemed unnecessary after the first analysis of the automated external defibrillator (AED). Continued high-quality chest compressions and strong pressure of the AED pad against the chest wall led to successful defibrillation after the second analysis.

Here we present a diagnostically challenging Bing-Neel Syndrome (BNS) case successfully treated with systemic chemoimmunotherapy and ibrutinib, with remarkable clinical response. BNS is an extremely rare direct central nervous system infiltration by malignant lymphoplasmocytic lymphoma cells in patients with Waldenstroms macroglobulinaemia.

Beluga Whale Optimization (BWO) is a recently developed meta-heuristics search algorithm to provide good balance between the exploration phase and the exploitation phase in solving benchmark optimization problems. However, the local search of the basic BWO algorithm has slow convergence rate due to its poor exploitation capability. We proposed a hybrid algorithm using a chaotic variant of the present optimization algorithm in order to enhance its exploitation ability and abbreviated as CBWO. To appraise the performance of CBWO, it is first verified on 23 standard benchmark functions. A comparative study has been done that shows the advantage of the proposed algorithm and associated with a number of existing algorithms. Simulation results were carried out on eleven classical engineering problems. Pseudo code of CBWO algorithm is presented in paper. Results come to know that CBWO could be more effective in optimization with quicker and advanced convergence rate and accuracy.

This letter reports a 28-GHz multi-port magneto-electric (ME) dipole array for 5G applications. The proposed antenna array enlarges the system polarization diversity with the capability of being utilized as a balanced antenna, a dual-polarized antenna and a circularly polarized antenna. Co-planar waveguide (CPW) lines are used to connect ME dipole radiators to achieve a high gain with simple feeding structure. The proposed antenna array exhibits a -10dB impedance bandwidth of 12.8% and a maximal peak realized gain of 13.52 dBi as a balanced antenna, and exhibits a -10dB impedance bandwidth of 28.57%, a 3-dB axial ratio bandwidth of 16% and a maximal peak realized gain of 12.15 dBi as a circularly polarized antenna.

A document by Baolei Jia. Click on the document to view its contents.

Connectivity maintains the spatial dynamics of metapopulations by promoting dispersal between habitat patches, potentially buffering populations and communities against continued global change. However, this function is threatened by habitats becoming increasingly fragmented, and habitat matrices becoming increasingly inhospitable, potentially reducing the resilience and persistence of populations. Yet, we lack a clear understanding of how reduced connectivity interacts with rates of environmental change to destabilise populations. Using laboratory microcosms containing metapopulations of the Collembola Folsomia candida, we investigate the impact of habitat connectivity on metapopulation persistence under a range of simulated droughts, a key stressor for this species. We manipulated both drought severity and the number of patches affected by drought across landscapes connected by either good or poor-quality corridors. We measured the time of population extinction, the maximum rate of population decline, and the variability of abundance among patches as criteria to evaluate the persistence ability of metapopulations. We show that whilst drought severity and number of drought-affected patches negatively influenced population persistence, these results were mitigated by increased habitat connectivity, which increased population persistence time and decreased both how fast populations declined and the variability in abundance among patches. Our results suggest that enhancing spatial connectivity can increase the persistence of metapopulations, increasing the time available for conservation actions to take effect, and/or for species to adapt or move in the face of continued stress. Given that fragmentation increases the isolation of habitats, improving habitat connectivity by using good quality corridors may provide a useful strategy to enhance the resistance of spatially structured populations.

Background Malignant brain tumors are among the most threatening diseases of the central nervous system, and despite increasingly updated treatments, the prognosis has not been improved. Tumor treating fields (TTFields) are an emerging approach in cancer treatment using intermediate-frequency and low-intensity electric field, and can lead to development of novel therapeutic options. Recent findings A series of biological processes induced by TTFields to exert anti-cancer effects have been identified, and applications of TTFields in oncology have been increasingly reported. This review addresses the mechanisms of TTFields and recent advances in the application of TTFields therapy in malignant brain tumors, especially in glioblastoma (GBM). Conclusions As a novel therapeutic strategies, TTFields have shown promising results in many clinical trials, especially in GBM, and continue to evolve. A growing number of patients with malignant brain tumors are being enrolled in ongoing clinical studies demonstrating that TTFields-based combination therapies can improve treatment outcomes.

Nowadays, power systems operate near the voltage stability margin because of high load demand. Therefore, the system operator must be aware of the operating system condition in order to use preventive and corrective control actions to avoid the voltage collapse that might occur. In this regard, having a suitable algorithm to determine the time that operator needs to use either preventive or corrective control is essential. Also, it is necessary to obtain suitable models for implementing these control actions. In this paper, based on the load prediction curve of each bus, a new method is proposed to estimate the remaining time that voltage instability will occur. Also, a new algorithm is suggested to select the best control action (preventive or corrective) according to the remaining time until voltage instability and the operating state of the power system. In addition, two models based on voltage stability constrained optimal power flow (VSC-OPF) considering the constraints related to voltage stability index and the remaining time until voltage instability have been proposed for both kinds of control. The effectiveness of the proposed algorithm and models has been tested on IEEE 14-bus and IEEE 57-bus power systems.

Direct visualization of polymer crystalline structure remains challenging due to the lack of contrast across different microphases of polymers. Here we address this conundrum using an aggregation-induced emission luminogen (AIEgen) with confinement fluorescence effect, which could be used as a “built-in” sensor to label different crystalline phases. Computational simulations reveal that the confined space induces the AIEgens to take a more planar conformation, resulting in a red-shifted emission spectrum. With this property, the information of various polymer crystalline forms is converted into different fluorescence colors, which is attributed to the different spatial dimensions of the polymer amorphous layer between lamellar crystals where the AIEgens are located. Finally, polymer crystalline phases distinction, quantitative crystallinity determination, and stereocomplex crystals visualization are achieved, providing a relationship between crystalline microstructure and fluorescence signals. This work demonstrates the potential of AIE fluorescence technology in polymer science, providing a theoretical and experimental guideline for the materials processing and optimization of mechanical performance.

The COVID-19 pandemic highlighted existing disparities in healthcare and public policies in the United States. Although measures such as social distancing and hygiene behaviors have been advocated for, many were impossible to do for certain populations, leaving them at greater risk of contracting and spreading the virus. Conditions in immigration detention facilities have long been criticized, but deficiencies in sanitation and safety exponentiated the spread of COVID-19 in these facilities. The current studies assess the primary factors that underlie support of policies designed to mitigate the spread of COVID-19 in immigration detention centers. We hypothesized that fear of COVID may overtake attitudes towards immigrants in predictive strength of policy support. Data gathered in Summer of 2020 (n=141) and Spring of 2021 (n=137) were analyzed using regression analyses to identify attitudes and variables most predictive of policy support. Contrary to our hypothesis, perceived risk of COVID-19 did not predict attitudes in either study. Rather, results indicate that attitudes towards immigrants proved to be the most significant predictor of support for these policies. The results indicate that negative attitudes towards immigrants remain the most impactful factors in support of policies aimed at reducing illness and death, even during a worldwide pandemic.

Microchannel reactor designs suffer from a fundamental limitation resulting from the flow configuration in which a reacting stream flows parallel to a heat transfer surface through which the majority of heat is transferred perpendicular to the direction of fluid flow. The present study aims to provide a unique microchannel fluid processing system for performing chemical reactions with temperature control. The present study relates to a unique method for performing reversible endothermic, exothermic reactions, and competing reactions. The method comprises flowing reactants through a reaction channel in thermal contact with a heat exchange channel, and conducting heat in support of the reaction between the reactants and fluid flowing through the heat exchange channel to substantially raise or lower the temperature of the reactants as they travel through the reaction channel.  Particular emphasis is placed upon how to provide improved conversion and selectivity in chemical reactions, provide chemical reactor systems that are compact, and provide thermally efficient chemical reactor systems. The distribution characteristics of temperature and species in micro-structured heat-exchanger reactors are investigated and the reactor performance is evaluated by performing numerical simulations using computational fluid dynamics. The results indicate that microchannel technology is capable of high heat and mass transfer coefficients between a bulk reaction fluid and the catalytic heat exchange surface. Carbon monoxide output from the fuel processor is controlled over the operating range of the processor. When the reaction in the reaction chamber is a reversible exothermic reaction, heat is generated in the reaction chamber and transferred to the heat exchange fluid. Microchannel reactors offer less resistance to heat and mass transfer thus creating the opportunity for dramatic reductions in process hardware volume. While a steam reforming catalyst in the form of a powder or pellets is appropriate in larger devices, diminished performance may result in the form of a powder or pellets in miniature devices and reactors. The steam reforming catalyst contains a suitable amount of at least one metal oxide and cerium to contribute to high methanol conversion properties. The shift reaction increases hydrogen yield while reducing carbon monoxide. Microchannel reactors offer the advantage of exceptional heat exchange integration and can be utilized for approaching optimum temperature trajectories for exothermic, reversible reactions. Keywords: Distribution characteristics; Chemical kinetics; Temperature trajectories; Fluid streams; Thermal gradients; Reaction selectivity

Polypropylene fumarate (PPF) is an unsaturated polyester that can be copolymerized with a vinyl monomer to give a biocompatible and biodegradable thermoset. The PPF has been successfully cured with vinyl phosphonic acid (VPA) and vinyl phosphonic acid di-ethyl ester (VPES) to improve various properties of PPF polymers as bone tissue scaffolds. However, the cell-material interactions of VPA and VPES cured PPF scaffolds have not been reported before. Therefore, the essential novelty of this research is the demonstration of the in vitro biocompatibility and bone formation capacity of VPA and VPES cured PPF scaffolds for bone tissue regeneration. In this study, the PPF polymer was synthesized via polycondensation of fumaric acid and excess propylene glycol, then thermally cured with VPA and VPES in the presence of benzoyl peroxide initiator via radical polymerization at changing co-monomer and initiator weight ratios. The biocompatibility of the materials was analyzed by MTS assay, indicated that PPF/VPA 70/30 copolymers supported human osteoblast cell (HOb) attachment and proliferation better than other copolymers. Scanning electron microscope analyses showed all samples supported HObs attachment and growth. The von Kossa, alkaline phosphatase, and osteocalcin activities were evaluated in order to observe the osteoblast activity of HObs seeded onto thermally cured PPF copolymers. Both PPF/VPA (80/20) 2% BP and PPF/VPA (70/30) 3% BP were found superior to all other samples. Conclusively, thermally cured PPF/VPA scaffolds represent a novel and promising strategy for the in vitro induction of osteogenesis.

Recombinant adeno-associated viruses are a promising gene therapy, with several therapeutics on the market in the United States. As we continue to industrialize manufacturing of these viral vectors, we strive to improve productivity and yield. To this end, we investigated a novel transfection reagent to improve the genomic titer of adeno-associated virus 8. Using a miniaturized automated 250 mL scale bioreactor system, we generated models of genomic and capsid titer from two multivariate design of experiments; one centered around bioprocess conditions, and another based on the transfection conditions. Using the optimized setpoints returned from these models, we improved our viral genome titer out of the bioreactor to beyond 1 × 10 12 vg/mL; to our knowledge the highest genomic titer reported from an upstream process utilizing HEK293 cells. When we applied these setpoints to six serotypes carrying a unique viral payload, five of the six returned higher genomic titers than the control condition, but were all below the titer of the vector used in our optimization studies. These data suggest that the choice of transfection reagent is a major factor in viral titer and percent full capsids, and that transfection conditions are serotype and payload specific.

Technological advancement makes the world a global village. The immense use of software systems has modernized human society in every aspect. Thus, the security parameter is an important element that needs to be considered while developing software systems. Considering the significance of software security, it is important to consider the security practices from the early phase of the software development life cycle (SDLC), i.e., requirements engineering (RE). Hence, this study aims to identify and categorize RE practices important to apply for secure software development (SSD) in a geographically distributed development environment. To study the RE practices concerning SSD, we conducted a questionnaire survey with industrial experts in the global software development (GSD) context. Furthermore, the interpretive structure modeling (ISM) approach was applied to evaluate the relationship between the RE security practice core categories. This paper identifies 70 practices and classifies them into 11 fundamental dimensions (categories) to assist GSD organizations in specifying the requirements for SSD. The ISM results show the “Awareness of Secure Requirement Engineering (SRE)” category has the most decisive influence on the other ten core categories of the identified RE security practices. With the help of empirical evidence and the ISM approach, this work attempts to identify potential security practices and to give a set of secure RE practices that can be used to improve the security of the software development process.

Drought stress can severely affect seed characteristics and seed metabolism during development, resulting in a grain yield reduction. Here, we examined the effect of drought on seed characteristics and central metabolism of seven different plant species, i.e., tomato, pepper, and eggplant from the Solanaceae family; melon and watermelon from the Cucurbitaceae family; maize from the Poaceae family; and sunflowers from the Asteraceae family. Synchronized changes of seed weight and seed size in response to drought were observed, showing smaller seed size and lower 1000 seeds weight for tomato and melon while larger seed size and higher 1000 seeds weight for pepper, eggplant, maize, and sunflower. Except for watermelon, number of seeds per plant declined in drought condition for all the species. Principal component analysis and hierarchical clustering highlighted differences of seed relative metabolite content due to phylogenetic differences and different regimes of water deficit. Correlation network analysis revealed interspecies differences in the metabolites associated with seed traits and stress-specific metabolite coordinated behavior in each species. The results suggest that the maintenance of seed dimensions in droughty environments may depend on the rewiring of amino acids and sugar metabolic network. The detected metabolic interactions that are conserved across species shed light on phylogenetic relationships. This comparative study expands our understanding of the interspecific diversity of seed metabolism in response to drought and may assist us for future breeding programs in light of climate change.