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The rise of Fe magnetic moment, changes in Al electronic structure and a variation of Al magnetic polarization in thin films of transition metal aluminide Fe _60 Al _40 have been probed through the order-disorder phase transition by soft x-ray absorption spectroscopy and x-ray resonant magnetic reflectivity in the extreme ultraviolet regime. In a course of the transition induced by 20 keV Ne ^+ irradiation with low fluences (∼10 ^14 ions cm ^−2 ), x-ray magnetic circular dichroism spectra taken at the Fe L $_{2,3}$ absorption edges at room and low temperatures revealed a pronounced increase of Fe $3\textit{d}$ states spin-polarization. X-ray resonant magnetic reflectivity applied to the Al L $_{2,3}$ and Fe M $_{2,3}$ edges allowed to detect the magnetic polarization of Al atoms in the films. The changes in Al electronic structure have been seen by alteration of Al K edge x-ray absorption near edge structure. A difference in anisotropy fields for films before and after irradiation has been observed by element-specific hysteresis loops recorded at low temperatures in absorption and reflection geometries at the Fe L $_{2,3}$ and M $_{2,3}$ edges, respectively. An attempt to reduce the top oxide layer by an inductively coupled hydrogen plasma has shown a possibility to recover the chemically ordered phase.

IntroductionNeutralizing antibodies (Abs) are one of the immune components required to protect against viral infections. However, developing vaccines capable of eliciting neutralizing Abs effective against a broad array of HIV-1 isolates has been an arduous challenge.ObjectiveThis study sought to test vaccines aimed to induce Abs against neutralizing epitopes at the V1V2 apex of HIV-1 envelope (Env).MethodsFour groups of rabbits received a DNA vaccine expressing the V1V2 domain of the CRF01_AE A244 strain on a trimeric 2J9C scaffold (V1V2-2J9C) along with a protein vaccine consisting of an uncleaved prefusion-optimized A244 Env trimer with V3 truncation (UFO-BG.ΔV3) or a V1V2-2J9C protein and their respective immune complexes (ICs). These IC vaccines were made using 2158, a V1V2-specific monoclonal Ab (mAb), which binds the V2i epitope in the underbelly region of V1V2 while allosterically promoting the binding of broadly neutralizing mAb PG9 to its V2 apex epitope in vitro.ResultsRabbit groups immunized with the DNA vaccine and uncomplexed or complexed UFO-BG.ΔV3 proteins (DNA/UFO-UC or IC) displayed similar profiles of Env- and V1V2-binding Abs but differed from the rabbits receiving the DNA vaccine and uncomplexed or complexed V1V2-2J9C proteins (DNA/V1V2-UC or IC), which generated more cross-reactive V1V2 Abs without detectable binding to gp120 or gp140 Env. Notably, the DNA/UFO-UC vaccine elicited neutralizing Abs against some heterologous tier 1 and tier 2 viruses from different clades, albeit at low titers and only in a fraction of animals, whereas the DNA/V1V2-UC or IC vaccines did not. In comparison with the DNA/UFO-UC group, the DNA/UFO-IC group showed a trend of higher neutralization against TH023.6 and a greater potency of V1V2-specific Ab-dependent cellular phagocytosis (ADCP) but failed to neutralize heterologous viruses.ConclusionThese data demonstrate the capacity of V1V2-2J9C-encoding DNA vaccine in combination with UFO-BG.ΔV3, but not V1V2-2J9C, protein vaccines, to elicit homologous and heterologous neutralizing activities in rabbits. The elicitation of neutralizing and ADCP activities was modulated by delivery of UFO-BG.ΔV3 complexed with V2i mAb 2158.

Resonant elastic soft X-ray magnetic scattering (XRMS) is a powerful tool to explore long-periodic spin textures in single crystals. However, due to the limited momentum transfer range imposed by long wavelengths of photons in the soft x-ray region, Bragg diffraction is restricted to crystals with the large lattice parameters. Alternatively, small-angle X-ray scattering has been involved in the soft energy X-ray range which, however, brings in difficulties with the sample preparation that involves focused ion beam milling to thin down the crystal to below a few hundred nm thickness. We show how to circumvent these restrictions using XRMS in specular reflection from a sub-nanometer smooth crystal surface. The method allows observing diffraction peaks from the helical and conical spin modulations at the surface of a Cu[Formula: see text]OSeO[Formula: see text] single crystal and probing their corresponding chirality as contributions to the dichroic scattered intensity. The results suggest a promising way to carry out XRMS studies on a plethora of noncentrosymmetric systems hitherto unexplored with soft X-rays due to the absence of the commensurate Bragg peaks in the available momentum transfer range.

Natural disasters caused by heavy rainfall often cause huge loss of life and property. Hence, the task of precipitation nowcasting is of great importance. To solve this problem, several deep learning methods have been proposed to forecast future radar echo images, and then the predicted maps are converted to the distribution of rainfall. The prevailing spatiotemporal sequence prediction methods apply a ConvRNN structure, which combines the convolution and recurrent neural network. Although ConvRNN methods achieve remarkable success, they do not capture both local and global spatial features simultaneously, which degrades the nowcasting in regions of heavy rainfall. To address this issue, we propose a Region Attention Block (RAB) and embed it into ConvRNN to enhance forecasting in the areas with heavy rainfall. Besides, the ConvRNN models find it hard to memorize longer historical representations with limited parameters. To this end, we propose a Recall Attention Mechanism (RAM) to improve the prediction. By preserving longer temporal information, RAM contributes to the forecasting, especially in the moderate rainfall intensity. The experiments show that the proposed model, Region Attention Predictive Network (RAP-Net), significantly outperforms state-of-the-art methods.

The authors introduce photonic force optical coherence elastography that uses a light-sheet for parallelised and localised mechanical loading. They demonstrate the combination of 3D imaging of extracellular matrix mechanics with cellular-scale resolution and dynamic monitoring of cell-mediated changes.

Precipitation nowcasting plays a vital role in preventing meteorological disasters, and Doppler radar data act as an important input for nowcasting models. When using the traditional extrapolation method it is difficult to model highly nonlinear echo movements. The key challenge of the nowcasting mission lies in achieving high-precision radar echo extrapolation. In recent years, machine learning has made great progress in the extrapolation of weather radar echoes. However, most of models neglect the multi-modal characteristics of radar echo data, resulting in blurred and unrealistic prediction images. This paper aims to solve this problem by utilizing the features of a generative adversarial network (GAN), which can enhance multi-modal distribution modeling, and design the radar echo extrapolation model GAN–argcPredNet v1.0. The model is composed of an argcPredNet generator and a convolutional neural network discriminator. In the generator, a gate controlling the memory and output is designed in the rgcLSTM component, thereby reducing the loss of spatiotemporal information. In the discriminator, the model uses a dual-channel input method, which enables it to strictly score according to the true echo distribution, and it thus has a more powerful discrimination ability. Through experiments on a radar dataset from Shenzhen, China, the results show that the radar echo hit rate (probability of detection; POD) and critical success index (CSI) have an average increase of 21.4 % and 19 %, respectively, compared with rgcPredNet under different intensity rainfall thresholds, and the false alarm rate (FAR) has decreased by an average of 17.9 %. We also found a problem during the comparison of the result graph and the evaluation index. The recursive prediction method will produce the phenomenon that the prediction result will gradually deviate from the true value over time. In addition, the accuracy of high-intensity echo extrapolation is relatively low. This is a question worthy of further investigation. In the future, we will continue to conduct research from these two directions.

Here the authors show that an HIV vaccine in non-human primates that focuses antibodies on the V1V2 region of gp120 is superior to infection or immunization with whole envelope vaccines for inducing V1V2 antibodies with anti-viral functions that correlate with protection.

The second genus and species of recently established planthopper family Inoderbidae, Ingensala xiai gen. et sp. nov., is described based on a well-preserved specimen from mid-Cretaceous Kachin (Burmese) amber, and it can be definitely attributed to Inoderbidae mainly based on its head structure, pronotum, and mesonotum without median and lateral carinae and tegmen venation. Ingensala gen. nov. is superficially similar to Eofulgoridium regarding its venation pattern, rather than to the Inoderbidae type genus Inoderbe, and further confirmed that Inoderbidae might descend from the Jurassic planthopper family Fulgoridiidae. The early fork of CuA and the stem CuA bearing many branches also can be found in Jurassic Qiyangiricaniidae and Eocene Weiwoboidae. Ingensala gen. nov. also superficially resembles some Tropiduchidae: Tropiduchinae. The new genus differs from the type genus Inoderbe to a large extent according to its wide head, frons without fastigium, antennae not so elongate, the tectiform condition of wings' position in repose, large, broad and translucent tegmen, triangular basal cell, single CuA1, legs covered with short setae, and the lack of filamentous wax on body. Therefore, two new subfamilies (Inoderbinae stat. nov. and Ingensalinae subfam. nov.) are established for these two genera respectively. The diversification in planthoppers could be the result of pressure of environmental changes during the mid-Cretaceous, and Inoderbidae provides more information for us to understand the Cretaceous stage of Fulgoroidea evolution and diversification.

Mapping of the HIV Env surface epitopes targeted by broadly neutralizing antibodies (bNAbs) is of great interest for HIV-1 vaccine design. Here, the authors present the 3.2 Å cryo-EM structure of the bNAb M4008_N1 in complex with BG505 DS-SOSIP, an engineered native-like Env trimer and observe that the bNAb epitope is centered at the V3 crown and that M4008_N1 uses its CDR H3 to form an extended β-sheet with the β-hairpin of the V3 crown in a conformation stabilized in the prefusion trimer.

Developing a safe and effective malaria vaccine is critical to reducing the spread and resurgence of this deadly disease, especially in children. In recent years, vaccine technology has seen expanded development of subunit protein, peptide, and nucleic acid vaccines. This is due to their inherent safety, the ability to tailor their immune response, simple storage requirements, easier production, and lower expense compared to using attenuated and inactivated organism-based approaches. However, these new vaccine technologies generally have low efficacy. Subunit vaccines, due to their weak immunogenicity, often necessitate advanced delivery vectors and/or the use of adjuvants. A new area of vaccine development involves design of synthetic micro- and nano-particles and adjuvants that can stimulate immune cells directly through their physical and chemical properties. Further, the unique and complex life cycle of the Plasmodium organism, with multiple stages and varying epitopes/antigens presented by the parasite, is another challenge for malaria vaccine development. Targeting multistage antigens simultaneously is therefore critical for an effective malaria vaccine. Here, we rationally design a layer-by-layer (LbL) antigen delivery platform (we called LbL NP) specifically engineered for malaria vaccines. A biocompatible modified chitosan nanoparticle (trimethyl chitosan, TMC) was synthesized and utilized for LbL loading and release of multiple malaria antigens from pre-erythrocytic and erythrocytic stages. LbL NP served as antigen/protein delivery vehicles and were demonstrated to induce the highest Plasmodium falciparum Circumsporozoite Protein (PfCSP) specific T-cell responses in mice studies as compared to multiple controls. From immunogenicity studies, it was concluded that two doses of intramuscular injection with a longer interval (4 weeks) than traditional malaria vaccine candidate dosing would be the vaccination potential for LbL NP vaccine candidates. Furthermore, in PfCSP/Py parasite challenge studies we demonstrated protective efficacy using LbL NP. These LbL NP provided a significant adjuvant effect since they may induce innate immune response that led to a potent adaptive immunity to mediate non-specific anti-malarial effect. Most importantly, the delivery of CSP full-length protein stimulated long-lasting protective immune responses even after the booster immunization 4 weeks later in mice.

An outstanding challenge in the clinical care of cancer is moving from a one-size-fits-all approach that relies on population-level statistics towards personalized therapeutic design. Mathematical modeling is a powerful tool in treatment personalization, as it allows for the incorporation of patient-specific data so that treatment can be tailor-designed to the individual. Herein, we work with a mathematical model of murine cancer immunotherapy that has been previously-validated against the average of an experimental dataset. We ask the question: what happens if we try to use this same model to perform personalized fits, and therefore make individualized treatment recommendations? Typically, this would be done by choosing a single fitting methodology, and a single cost function, identifying the individualized best-fit parameters, and extrapolating from there to make personalized treatment recommendations. Our analyses show the potentially problematic nature of this approach, as predicted personalized treatment response proved to be sensitive to the fitting methodology utilized. We also demonstrate how a small amount of the right additional experimental measurements could go a long way to improve consistency in personalized fits. Finally, we show how quantifying the robustness of the average response could also help improve confidence in personalized treatment recommendations.

The objective of this paper is to present the development of 3D digital manufacturing through synchronous 5-axes printing for greatly enhancing the strength of the printed parts. In traditional fused deposition manufacturing (FDM), which is one of the digital manufacturing technologies, the melted material is required to be extruded from the nozzle on the workspace platform with a fixed direction. The strength is restricted in the direction of perpendicular to the layers since the printing way is layer by layer. The poor adhesion between the layers becomes a weakness to resist external force, especially when the force exerted from different directions. In this paper, algorithms for synchronous five axes printing based on the surface printing trajectory has been proposed to overcome the lack of strength issue. A five axes synchronous 3D printing machine developed in our NTU Intelligent Robotics and Automation Lab enhances the strength of the printed parts by adding additional materials to the surface of the parts. Five axes printing can achieve the goal of printing in different orientations so that the strength of the printed parts is greatly enhanced in comparison with the printing in a fixed direction only. The five axes synchronous 3D printing has been successfully demonstrated in physical printing. The strength analysis of printed parts is also performed under the three-point bending test and the tensile test. It shows that the strength of the five axes printed sample is increased by nearly three times in the bending test and nearly two times stronger in the tensile test.

Introduction: Digital technologies, including text messaging and mobile phone apps, can be leveraged to increase people's physical activity and manage health. Chatbots, powered by artificial intelligence, can automatically interact with individuals through natural conversation. They may be more engaging than one-way messaging interventions. To our knowledge, physical activity chatbots have not been developed with low-income participants, nor in Spanish—the second most dominant language in the U.S. We recommend best practices for physical activity chatbots in English and Spanish for low-income women.Methods: We designed a prototype physical activity text-message based conversational agent based on various psychotherapeutic techniques. We recruited participants through SNAP-Ed (Supplemental Nutrition Assistance Program Education) in California (Alameda County) and Tennessee (Shelby County). We conducted qualitative interviews with participants during testing of our prototype chatbot, held a Wizard of Oz study, and facilitated a co-design workshop in Spanish with a subset of our participants.Results: We included 10 Spanish- and 8 English-speaking women between 27 and 41 years old. The majority was Hispanic/Latina (n = 14), 2 were White and 2 were Black/African American. More than half were monolingual Spanish speakers, and the majority was born outside the US (>50% in Mexico). Most participants were unfamiliar with chatbots and were initially skeptical. After testing our prototype, most users felt positively about health chatbots. They desired a personalized chatbot that addresses their concerns about privacy, and stressed the need for a comprehensive system to also aid with nutrition, health information, stress, and involve family members. Differences between English and monolingual Spanish speakers were found mostly in exercise app use, digital literacy, and the wish for family inclusion.Conclusion: Low-income Spanish- and English-speaking women are interested in using chatbots to improve their physical activity and other health related aspects. Researchers developing health chatbots for this population should focus on issues of digital literacy, app familiarity, linguistic and cultural issues, privacy concerns, and personalization. Designing and testing this intervention for and with this group using co-creation techniques and involving community partners will increase the probability that it will ultimately be effective.

The harmonic operation in a terahertz gyrotron traveling-wave amplifier (gyro-TWA) permits a reduced magnetic field, whereas a harmonic multiplying gyro-TWA enables magnetic field reduction and frequency multiplication. This study comparatively analyzes the 400-GHz fourth-harmonic gyro-TWAs and fourth-harmonic multiplying gyro-TWAs with axis-encircling electron beams. This property of the gyro-TWAs with axis-encircling electron beams enables us avoid the appearance of the majority of the competing modes. According to the simulation results obtained using multi-mode codes, the attenuating severs suppress the remaining competing modes. In the case of a harmonic gyro-TWA containing a sever section, the copper-section start-oscillation length is significantly influenced by a decrease in the sever-section radius when compared with an increase in the sever-section length. Furthermore, a stable fourth-harmonic TE41-mode gyro-TWA containing sever sections is proposed. We propose fourth-harmonic TE41-mode multiplying gyro-TWAs, where the drive stages operate in the fundamental-harmonic TE11 mode to reduce the frequency of the drive wave. We subsequently develop a stable fourth-harmonic multiplying gyro-TWA with sever sections in the drive and amplified stages to avoid the competing modes and enhance the output power. The stable high-gain fourth-harmonic gyro-TWA can yield a peak output power of 2.7 kW at 400.6 GHz with a saturated gain of 75 dB and a bandwidth of 0.7 GHz for a 75-kV and 2-A electron beam with an axial velocity spread of 3%. Furthermore, a peak output power of 1.7 kW can be obtained by the fourth-harmonic multiplying gyro-TWA at 400.4 GHz with a saturated gain of 57 dB and a bandwidth of 0.4 GHz. Subsequently, we calculate the power and gain scaling for the harmonic gyro-TWA and harmonic multiplying gyro-TWA.

Triple-negative breast cancer is highly heterogeneous and aggressive. Here, the authors utilise single-cell RNA sequencing to investigate this heterogeneity, and discover a subpopulation of cells associated with metastasis and treatment resistance signatures, and linked to long term survival outcomes.

Lack of understanding of the effects of warming and winter grazing on soil fungal contribution to the nitrous oxide (N2O) production process has limited our ability to predict N2O fluxes under changes in climate and land use management, because soil fungi play an important role in driving terrestrial N cycling. A controlled warming and winter grazing experiment that included control (C), winter grazing (G), warming (W) and warming with winter grazing (WG) was conducted to investigate the effects of warming and winter grazing on soil N2O production potential in an alpine meadow on the Tibetan Plateau. Our results showed that soil bacteria and fungi contributed 46 ± 2 % and 54 ± 2 % to nitrification, and 37 ± 3 % and 63 ± 3 % to denitrification in the control treatment, respectively. We conclude that soil fungi could be the main source of N2O production potential for the Tibetan alpine grasslands. In our results, neither warming nor winter grazing affected the activity of enzymes responsible for overall nitrification and denitrification. However, warming significantly increased the enzyme activity of bacterial nitrification and potential of N2O production from denitrification to 53 ± 2 % and 55 ± 3 %, respectively, but decreased them to 47 ± 2 % and 45 ± 3 %, respectively. Winter grazing had no such effects. Warming and winter grazing may not affect the soil N2O production potential, but climate warming can alter biotic pathways responsible for N2O production process. These findings confirm the importance of soil fungi in the soil N2O production process and how they respond to environmental and land use changes in alpine meadow ecosystems. Therefore, our results provide some new insights into ecological controls on the N2O production process and contribute to the development of an ecosystem nitrogen cycle model.

The data and services analysis are indispensable for the refined development of SDI. This paper, taking Chinese NSDI as a study case, analyzed the data and services advantages and shortcomings of Chinese NSDI and developed a recommendable data and services framework which could improve the Chinese NSDI better services for public and private sectors from known, attainable and usable aspects by using Backx model. And the recommendation framework can also be referenced by other national and local SDI for its better services and applications.

The introduction of service robots in the public domain has introduced a paradigm shift in how robots are interacting with people, where robots must learn to autonomously interact with the untrained public instead of being directed by trained personnel. As an example, a hospital service robot is told to deliver medicine to Patient Two in Ward Three. Without awareness of what “Patient Two” or “Ward Three” is, a service robot must systematically explore the environment to perform this task, which requires a long time. The implementation of a Semantic Map allows for robots to perceive the environment similar to people by associating semantic information with spatial information found in geometric maps. Currently, many semantic mapping works provide insufficient or incorrect semantic-metric information to allow a service robot to function dynamically in human-centric environments. This paper proposes a semantic map with a hierarchical semantic organization structure based on a hybrid metric-topological map leveraging convolutional neural networks and spatial room segmentation methods. Our results are validated using multiple simulated and real environments on our lab's custom developed mobile service robot and demonstrate an application of semantic maps by providing only vocal commands. We show that this proposed method provides better capabilities in terms of semantic map labeling and retain multiple levels of semantic information.