Inverse Ising effect and Ising magnetoresistance

Ising (Zeeman-type) spin-orbit coupling (SOC) generated by in-plane inverse asymmetry has attracted considerable attention, especially in Ising superconductors and spin-valley coupling physics. However, many unconventional observations and emerging physical phenomena remain to be elucidated. Here, we theoretically study the spin texture of {\sigma}_z (spin angular momentum projection along z) induced by Ising SOC in 1Td WTe2, and propose an unconventional spin-to-charge conversion named inverse Ising effect, in which the directions of the spin current, spin polarization and charge current are not orthogonal. In particular, we predict the Ising magnetoresistance, whose resistance depends on the out-of-plane magnetic momentum in WTe2/ferromagnetic heterostructure. The Ising magnetoresistance is believed to be an interesting counterpart to the well studied spin Hall magnetoresistance. Our predictions provide promising way to spin-momentum locking and spin-charge conversion based on emerging Ising SOC

Hemogenic Endothelial Cells Can Transition to Hematopoietic Stem Cells through a B-1 Lymphocyte-Biased State during Maturation in the Mouse Embryo

Precursors of hematopoietic stem cells (pre-HSCs) have been identified as intermediate precursors during the maturation process from hemogenic endothelial cells to HSCs in the aorta-gonad-mesonephros (AGM) region of the mouse embryo at embryonic day 10.5. Although pre-HSCs acquire an efficient adult-repopulating ability after ex vivo co-culture, their native hematopoietic capacity remains unknown. Here, we employed direct transplantation assays of CD45-VE-cadherin(VC)+KIT+(V+K+) cells (containing pre-HSCs) into immunodeficient neonatal mice that permit engraftment of embryonic hematopoietic precursors. We found that freshly isolated V+K+ cells exhibited significantly greater B-1 lymphocyte-biased repopulating capacity than multilineage repopulating capacity. Additionally, B cell colony-forming assays demonstrated the predominant B-1 progenitor colony-forming ability of these cells; however, increased B-2 progenitor colony-forming ability emerged after co-culture with Akt-expressing AGM endothelial cells, conditions that support pre-HSC maturation into HSCs. Our studies revealed an unexpected B-1 lymphocyte bias of the V+K+ population and acquisition of B-2 potential during commitment to the HSC fate

Whole exome sequencing of insulinoma reveals recurrent T372R mutations in YY1

Functional pancreatic neuroendocrine tumours (PNETs) are mainly represented by insulinoma, which secrete insulin independent of glucose and cause hypoglycaemia. The major genetic alterations in sporadic insulinomas are still unknown. Here we identify recurrent somatic T372R mutations in YY1 by whole exome sequencing of 10 sporadic insulinomas. Further screening in 103 additional insulinomas reveals this hotspot mutation in 30% (34/113) of all tumours. T372R mutation alters the expression of YY1 target genes in insulinomas. Clinically, the T372R mutation is associated with the later onset of tumours. Genotyping of YY1, a target of mTOR inhibitors, may contribute to medical treatment of insulinomas. Our findings highlight the importance of YY1 in pancreatic β-cells and may provide therapeutic targets for PNETs

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Gait Phase Classification of Lower Limb Exoskeleton Based on a Compound Network Model

The classification of lower limb gait phase is very important for the control of exoskeleton robots. In order to enable the exoskeleton to determine gait phase and provide appropriate assistance to the wearer, we propose a compound network based on CNN-BiLSTM. The method uses data from inertial measurement units placed on the leg and pressure sensor arrays placed on the sole as inputs to the model. The convolutional neural network (CNN) is used to obtain the local key features of gait data, and then the bidirectional long short-term memory (BiLSTM) network is used to extract the serialized gait phase information from the local key features to obtain the high-level feature expression. Finally, the seven phases of both feet were obtained through the classification of the softmax layer. We designed a gait acquisition system and collected the gait data from seven subjects at varying walking speeds. In the test set, the highest gait phase classification accuracy can reach 95.09%. We compared the proposed model with the long short-term memory (LSTM) network and gated recurrent unit (GRU) network. The experimental results show that the average accuracy of CNN-BiLSTM network from seven subjects is 0.417% higher than that of the LSTM network and 0.596% higher than that of the GRU network. Therefore, the ability of the CNN-BiLSTM network to classify gait phases can be applied in designing exoskeleton controllers that can better assist for different gait phases correctly to assist the wearer to walk

Anaesthesia Management of a Crash Caesarean Section for Placental Abruption, Incorporating a Rotational Thromboelastometry-guided Management of Massive Haemorrhage - A Case Report

World Congress of AnaesthesiologistsSingapor

Optimization of Torque-Control Model for Quasi-Direct-Drive Knee Exoskeleton Robots Based on Regression Forecasting

The choice of torque curve in lower-limb enhanced exoskeleton robots is a key problem in the control of lower-limb exoskeleton robots. As a human–machine coupled system, mapping from sensor data to joint torque is complex and non-linear, making it difficult to accurately model using mathematical tools. In this research study, the knee torque data of an exoskeleton robot climbing up stairs were obtained using an optical motion-capture system and three-dimensional force-measuring tables, and the inertial measurement unit (IMU) data of the lower limbs of the exoskeleton robot were simultaneously collected. Nonlinear approximations can be learned using machine learning methods. In this research study, a multivariate network model combining CNN and LSTM was used for nonlinear regression forecasting, and a knee joint torque-control model was obtained. Due to delays in mechanical transmission, communication, and the bottom controller, the actual torque curve will lag behind the theoretical curve. In order to compensate for these delays, different time shifts of the torque curve were carried out in the model-training stage to produce different control models. The above model was applied to a lightweight knee exoskeleton robot. The performance of the exoskeleton robot was evaluated using surface electromyography (sEMG) experiments, and the effects of different time-shifting parameters on the performance were compared. During testing, the sEMG activity of the rectus femoris (RF) decreased by 20.87%, while the sEMG activity of the vastus medialis (VM) increased by 17.45%. The experimental results verify the effectiveness of this control model in assisting knee joints in climbing up stairs

Optimization of deacidification for concentrated grape juice

Excessive organic acids in grape juice will not only result in poor taste but will also cause turbidity and sedimentation. Tartaric acid exerts the most significant acidity among all organic acids in grape juice. In this study, we used tartaric acid as the main target and anion‐exchange resin to remove tartaric acid from concentrated grape juice. Factors influencing the removal process were optimized by liquid chromatography with ultraviolet detection and statistical analysis for optimal deacidification of concentrated grape juice. Use of the anion‐exchange resin 335 treat the concentrated grape juice at a ratio of 1:6 (2:11.98) at 15.57°C for 4.35 hr. The tartaric acid removal rate reached 69.01%; the anion‐exchange resin 335 demonstrated the best removal effect

Are the planning targets of liquid biofuel development achievable in China under climate change?

Liquid biofuels from non-grain energy crops on marginal land could become an important substitute of gasoline in the transport sector, and offer the possibility to reduce competition with food crops for land resources. However, the cultivation of energy crops is facing profound challenges due to changing temperature and precipitation in the future. To assess the impact of climate change on the potential of liquid biofuels on marginal land in China, this study used a geographic information system-based approach combined with multiple factor analysis to identify the spatial distribution of marginal land suitable for nine major energy crops in China. Climate scenarios were generated based on bias-corrected results of five different climate models under two representative concentration pathways (RCP2.6 and 8.5). Results show that climate change is projected to have a substantial impact on the land availability for biofuel production in the 2050s under both RCPs. The total amount of marginal land suitable for energy crops was 170.2 million hectares for the period of 2010–2019, and would increase in the 2050s under both RCPs. The changing pattern of area are similar under both RCP 2.6 and 8.5, only the magnitude is different. All the species are projected to have a northward spread in China. The amount of marginal land suitable for all the energy crops is projected to increase in the 2050s, except for Miscanthus floridulus, and Miscanthus lutarioriparius under RCP 8.5. However, the potential productivity of the energy crops is projected to have a substantial decrease in the 2050s. The average yields of the energy crops are only about one fourth of their yields in the 2010s due to climate change. Combined with high costs of producing biofuels and numerous ecological tradeoffs, it is likely that liquid biofuels development using 1.5 and 2-generation energy crops does not have an optimistic perspective in China

Pressure-induced zigzag phosphorus chain and superconductivity in boron monophosphide

We report on the prediction of the zinc-blende structure BP into a novel C2/m phase from 113 to 208 GPa which possesses zigzag phosphorus chain structure, followed by another P4(2)/mnm structure above 208 GPa above using the particle-swarm search method. Strong electron-phonon coupling lambda in compressed BP is found, in particular for C2/m phase with the zigzag phosphorus chain, which has the highest lambda (0.56-0.61) value among them, leading to its high superconducting critical temperature T-c (9.4 K-11.5 K), which is comparable with the 4.5 Kto 13 Kvalue of black phosphorus phase I (orthorhombic, Cmca). This is the first system in the boron phosphides which shows superconductivity from the present theoretical calculations. Our results show that pressure-induced zigzag phosphorus chain in BP exhibit higher superconducting temperature T-C, opening a new route to search and design new superconductor materials with zigzag phosphorus chains