Evolution of the SPX gene family and its role in the response mechanism to low phosphorus stress in self-rooted apple stock.

BACKGROUND: Phosphorus plays a key role in plant adaptation to adversity and plays a positive role in the yield and quality formation of apples. Genes of the SPX domain-containing family are widely involved in the regulation of phosphorus signalling networks. However, the mechanisms controlling phosphorus deficiency are not completely understood in self-rooted apple stock. RESULTS: In this study, 26 members of the apple SPX gene family were identified by genome-wide analysis, and further divided into four subfamilies (SPX, SPX-MFS, SPX-EXS, and SPX-RING) based on their structural features. The chromosome distribution and gene duplications of MdSPXs were also examined. The promoter regions of MdSPXs were enriched for multiple biotic/abiotic stresses, hormone responses and typical P1BS-related elements. Analysis of the expression levels of 26 MdSPXs showed that some members were remarkably induced when subjected to low phosphate (Pi) stress, and in particular MdSPX2, MdSPX3, and MdPHO1.5 exhibited an intense response to low Pi stress. MdSPX2 and MdSPX3 showed significantly divergent expression levels in low Pi sensitive and insensitive apple species. Protein interaction networks were predicted for 26 MdSPX proteins. The interaction of MdPHR1 with MdSPX2, MdSPX3, MdSPX4, and MdSPX6 was demonstrated by yeast two-hybrid assay, suggesting that these proteins might be involved in the Pi-signaling pathway by interacting with MdPHR1. CONCLUSION: This research improved the understanding of the apple SPX gene family and contribute to future biological studies of MdSPX genes in self-rooted apple stock.

Integrated modelling of flow-sediment transport and power generation in the Three Gorges Reservoir.

Reservoirs play a crucial role in regulating runoff and generating energy. However, they also lead to significant sedimentation in the reservoir area. In this study, we propose an integrated model that combines a 1-D hydro- and sediment dynamic module with a power generation module. The model considers both suspended and bed load transports. This model is applied to the Three Gorges Reservoir (TGR) and evaluate its performance against corresponding measurements. The results demonstrate that:① the proposed model accurately reproduces the processes of flow and sediment transport, bed deformation, and power generation during the hydrological years of 2019 and 2020. The relative errors for average discharge and bed deformation volume are <6 % and 10 %, respectively. Moreover, the calculated total power (982 × 108-1115 × 108 kW·h) closely agree with the measured values (969 × 108-1118 × 108 kW·h); ② the inflows of small tributaries have a noticeable impact on the calculated water discharge in the TGR. This impact will lead to a 16 % increase in average discharge and alter the magnitudes and occurrence times of flood peaks; ③ the flocculation of fine sediment particles significantly affects sediment transport, particularly in the sub-reach close to the dam. This flocculation will result in a 37 %-57 % reduction in average suspended sediment discharge and a 63 %-93 % reduction in peak sediment discharge. This research provides a comprehensive tool for simulating flow and sediment transport as well as power generation, which can support the optimal regulation of the TGR.

Rethinking Delayed Hemodynamic Responses for fNIRS Classification.

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging technology for monitoring cerebral hemodynamic responses. Enhancing fNIRS classification can improve the performance of brain-computer interfaces (BCIs). Currently, deep neural networks (DNNs) do not consider the inherent delayed hemodynamic responses of fNIRS signals, which causes many optimization and application problems. Considering the kernel size and receptive field of convolutions, delayed hemodynamic responses as domain knowledge are introduced into fNIRS classification, and a concise and efficient model named fNIRSNet is proposed. We empirically summarize three design guidelines for fNIRSNet. In subject-specific and subject-independent experiments, fNIRSNet outperforms other DNNs on open-access datasets. Specifically, fNIRSNet with only 498 parameters is 6.58% higher than convolutional neural network (CNN) with millions of parameters on mental arithmetic tasks and the floating-point operations (FLOPs) of fNIRSNet are much lower than CNN. Therefore, fNIRSNet is friendly to practical applications and reduces the hardware cost of BCI systems. It may inspire more research on knowledge-driven models for fNIRS BCIs. Code is available at https://github.com/wzhlearning/fNIRSNet.

Multichromosomal mitochondrial genome of Punica granatum: comparative evolutionary analysis and gene transformation from chloroplast genomes.

BACKGROUND: Punica granatum is a fundamentally important fruit tree that has important economic, medicinal and ornamental properties. At present, there are few reports on the mitochondrial genome of pomegranate. Hence, in this study the P. granatum mitogenome was sequenced and assembled to further understanding of organization, variation, and evolution of mitogenomes of this tree species. RESULTS: The genome structure was multi-chromosomes with seven circular contigs, measuring 382,774 bp in length with a 45.91% GC content. It contained 74 genes, including 46 protein-coding genes, 25 tRNA genes, and three rRNA genes. There were 188 pairs of dispersed repeats with lengths of 30 or greater, primarily consisting of reverse complementary repeats. The mitogenome analysis identified 114SSRs and 466 RNA editing sites. Analyses of codon usage, nucleotide diversity and gene migration from chloroplast to mitochondrial were also conducted. The collinear and comparative analysis of mitochondrial structures between P. granatum and its proximal species indicated that P. granatum 'Taishanhong' was closely related to P. granatum 'Qingpitian' and Lagerstroemia indica. Phylogenetic examination based on the mitogenome also confirmed the evolutionary relationship. CONCLUSION: The results offered crucial information on the evolutionary biology of pomegranate and highlighted ways to promote the utilization of the species' germplasm.

Tuning and exploiting interlayer coupling in two-dimensional van der Waals heterostructures.

Two-dimensional (2D) layered materials can stack into new material systems, with van der Waals (vdW) interaction between the adjacent constituent layers. This stacking process of 2D atomic layers creates a new degree of freedom-interlayer interface between two adjacent layers-that can be independently studied and tuned from the intralayer degree of freedom. In such heterostructures (HSs), the physical properties are largely determined by the vdW interaction between the individual layers,i.e.interlayer coupling, which can be effectively tuned by a number of means. In this review, we summarize and discuss a number of such approaches, including stacking order, electric field, intercalation, and pressure, with both their experimental demonstrations and theoretical predictions. A comprehensive overview of the modulation on structural, optical, electrical, and magnetic properties by these four approaches are also presented. We conclude this review by discussing several prospective research directions in 2D HSs field, including fundamental physics study, property tuning techniques, and future applications.

Identification of LsLAZY1 gene in Leymus secalinus and validation of its function in Arabidopsis thaliana.

Root systems anchor plants to the substrate in addition to transporting water and nutrients, playing a fundamental role in plant survival. The LAZY1 gene mediates gravity signal transduction and participates in root and shoot development and auxin flow in many plants. In this study, a regulator, LsLAZY1, was identified from Leymus secalinus based on previous transcriptome data. The conserved domain and evolutionary relationship were further analyzed comprehensively. The role of LsLAZY1 in root development was investigated by genetic transformation and associated gravity response and phototropism assay. Subcellular localization showed that LsLAZY1 was localized in the nucleus. LsLAZY1 overexpression in Arabidopsis thaliana (Col-0) increased the length of the primary roots (PRs) and the number of lateral roots (LRs) compared to Col-0. Furthermore, 35S:LsLAZY1 transgenic seedlings affected auxin transport and showed a stronger gravitational and phototropic responses. It also promoted auxin accumulation at the root tips. These results indicated that LsLAZY1 affects root development and auxin transport. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-023-01326-4.

PgMYB1 Positively Regulates Anthocyanin Accumulation by Activating PgGSTF6 in Pomegranate.

The peel color of pomegranates is an important exterior quality that determines market value. Anthocyanins are biosynthesized in the cytosol and then transported to the vacuole for storage. However, the molecular mechanism that determines the color variation between red and white pomegranates remains unclear. In this study, we identified an R2R3-MYB protein (PgMYB1) that interacts with the PgGSTF6 promoter and regulates its transcriptional expression, thus promoting the accumulation of anthocyanins in pomegranate. The expression of PgMYB1 and PgGSTF6 was positively correlated with the anthocyanin content in red and white pomegranates. Further investigation showed that the knockdown of PgMYB1 in red pomegranate 'Taishanhong' (TSH), by the virus-induced gene-silencing system, inhibited anthocyanin accumulation. Together, our results indicate that PgMYB1 controls the transport of anthocyanin via PgGSTF6 and thus promotes anthocyanin accumulation in red pomegranates. Our results have a certain reference value for further clarifying the regulation of anthocyanin synthesis and transport in pomegranate fruits.

A New Grey Wolf Optimizer Tuned Extended Generalized Predictive Control for Distillation Process.

The distillation process plays an essential role in the petrochemical industry. However, the high-purity distillation column has complicated dynamic characteristics such as strong coupling and large time delay. To control the distillation column accurately, we proposed an extended generalized predictive control (EGPC) method inspired by the principles of extended state observer and proportional-integral-type generalized predictive control method; the proposed EGPC can adaptively compensate the system for the effects of coupling and model mismatch online and performs well in controlling time-delay systems. The strong coupling of the distillation column needs fast control, and the large time delay requires soft control. To balance the requirement for fast and soft control at the same time, a grey wolf optimizer with reverse learning and adaptive leaders number strategies (RAGWO) was proposed to tune the parameters of EGPC, and these strategies enable RAGWO to have a better initial population and improve its exploitation and exploration ability. The benchmark test results indicate that the RAGWO outperforms the existing optimizers for most of the selected benchmark functions. Extensive simulations show that the proposed method in terms of fluctuation and response time is superior to other methods for controlling the distillation process.

The relationship between patient-family caregiver congruence/incongruence in acceptance of illness and family caregivers' anticipatory grief.

OBJECTIVE: Cancer is a family affair that negatively impacts the lives of patients and their family caregivers. This study takes a dyadic perspective to investigate the effect of patient-family caregiver illness acceptance congruence/incongruence on family caregivers' anticipatory grief (AG) and examine whether caregivers' resilience moderates the abovementioned relationship. METHODS: For the study, 304 dyads of advanced lung cancer patients and their family caregivers from three tertiary hospitals in Jinan, Shandong Province, China were recruited. The data were analyzed using polynomial regressions and response surface analyses. RESULTS: Family caregivers' AG was lower when patient-family caregiver illness acceptance was congruent rather than incongruent. Lower patient-caregiver illness acceptance congruence was associated with higher AG in family caregivers compared with higher illness acceptance congruence. Family caregivers reported significantly higher AG only if their illness acceptance was lower than that of their patients. In addition, caregivers' resilience moderated the effects of patient-caregiver illness acceptance congruence/incongruence on family caregivers' AG. CONCLUSIONS: Patient-family caregiver illness acceptance congruence was beneficial to family caregivers' AG; resilience can be a protective factor for buffering the impact of illness acceptance incongruence on family caregivers' AG.

High-sensitivity and high extinction ratio fiber strain sensor with temperature insensitivity by cascaded MZI and FPI.

Low extinction ratio (ER) and high temperature cross-sensitivity are serious but common problems for most strain sensors based on Vernier effect. In this study, a hybrid cascade strain sensor of a Mach-Zehnder interferometer (MZI) and a Fabry-Perot interferometer (FPI) with high sensitivity and high ER based on Vernier effect is proposed. The two interferometers are separated by a long single-mode fiber (SMF). The MZI is used as the reference arm, which can be flexibly embedded in the SMF. The FPI is used as the sensing arm and the hollow-core fiber (HCF) as the FP cavity to reduce optical loss. Simulation and experiments have proven that this method can significantly increase ER. At the same time, the second reflective face of the FP cavity is indirectly spliced to increase the active length to improve the strain sensitivity. Through the amplification of Vernier effect, the maximum strain sensitivity is -649.18p m/µ ε, and the temperature sensitivity is only 5.76pm/∘C. The magnetic field was measured by combining the sensor with a Terfenol-D (magneto-strictive material) slab to verify the strain performance, and the magnetic field sensitivity is -7.53nm/mT. The sensor has many advantages and has potential applications in the field of strain sensing.

Identifying, Resolving, and Quantifying Anisotropy in ReS2 Nanomechanical Resonators.

As an emerging two-dimensional semiconductor, rhenium disulfide (ReS2 ) is renowned for its strong in-plane anisotropy in electrical, optical, and thermal properties. In contrast to the electrical, optical, optoelectrical, and thermal anisotropies that are extensively studied in ReS2 , experimental characterization of mechanical properties has largely remained elusive. Here, it is demonstrated that the dynamic response in ReS2 nanomechanical resonators can be leveraged to unambiguously resolve such disputes. Using anisotropic modal analysis, the parameter space for ReS2 resonators in which mechanical anisotropy is best manifested in resonant responses is determined. By measuring their dynamic response in both spectral and spatial domains using resonant nanomechanical spectromicroscopy, it is clearly shown that ReS2 crystal is mechanically anisotropic. Through fitting numerical models to experimental results, it is quantitatively determined that the in-plane Young's moduli are 127 and 201 GPa along the two orthogonal mechanical axes. In combination with polarized reflectance measurements, it is shown that the mechanical soft axis aligns with the Re-Re chain in the ReS2 crystal. These results demonstrate that dynamic responses in nanomechanical devices can offer important insights into intrinsic properties in 2D crystals and provide design guidelines for future nanodevices with anisotropic resonant responses.

Comprehensive analysis of cucumber RAV family genes and functional characterization of CsRAV1 in salt and ABA tolerance in cucumber.

The RAV (related to ABI3 and VP1) transcription factors are specific and exist in plants, which contain a B3 DNA binding domain and/or an APETALA2 (AP2) DNA binding domain. RAVs have been extensively studied in plants, and more and more evidences show that RAVs are involved in various aspects of plant growth and development, stress resistance and hormone signal transduction. However, the systematic analysis of RAV family in cucumber is rarely reported. In this study, eight CsRAV genes were identified in cucumber genome and we further comprehensively analyzed their protein physicochemical properties, conserved domains, gene structure and phylogenetic relationships. The synteny analysis and gene duplications of CsRAV genes were also analysed. Cis-element analysis revealed that the CsRAVs promoter contained several elements related to plant hormones and abiotic stress. Expression analysis showed that NaCl and ABA could significantly induce CsRAV genes expression. Subcellular localization revealed that all CsRAVs were localized in the nucleus. In addition, 35S:CsRAV1 transgenic Arabidopsis and cucumber seedlings enhanced NaCl and ABA tolerance, revealing CsRAV1 may be an important regulator of abiotic stress response. In conclusion, comprehensive analysis of CsRAVs would provide certain reference for understanding the evolution and function of the CsRAV genes.

Orientation-polarization dependence of pressure-induced Raman anomalies in anisotropic 2D ReS2.

We report an in situ high-pressure (0-30.24 GPa) optical study of the 2D ReS2 crystal under four specific configurations of sample orientation and laser polarization. Unlike the horizontal measurement configuration that has been widely used, under the vertical sample configuration we observe the anomalous disappearance behavior of Raman modes. Through analyzing the peak evolution under different configurations with tensor calculations, we identify the effect of pressure on different components in the full 3 × 3 Raman tensor of the anisotropic ReS2 crystal. These results provide new evidence on the remarkable tunability of pressure engineering on the crystal structure, and our methods offer an additional degree of freedom for studying pressure engineering on 2D anisotropic materials.

Ni/NiO Exsolved Perovskite La0.2Sr0.7Ti0.9Ni0.1O3-δ for Semiconductor-Ionic Fuel Cells: Roles of Electrocatalytic Activity and Physical Junctions.

A semiconductor-ionic fuel cell (SIFC) is recognized as a promising technology and an alternative approach to reduce the operating temperature of solid oxide fuel cells. The development of alternative semiconductors substituting easily reduced transition metal oxide is a great challenge as high activity and durability should be satisfied simultaneously. In this study, the B-site Ni-doped La0.2Sr0.7Ti0.9Ni0.1O3-δ (LSTN) perovskite is synthesized and used as a potential semiconductor for SIFC. The in situ exsolution and A-site deficiency strategy enable the homogeneous decoration of Ni/NiO nanoparticles as reactive sites to improve the electrode reaction kinetics. It also supports the formation of basic ingredient of the Schottky junction to improve the charge separation efficiency. Furthermore, additional symmetric Ni0.8Co0.15Al0.05LiO2-δ (NCAL) electrocatalytic electrode layers significantly enhance the electrode reaction activity and cells' charge separation efficiency, as confirmed by the superior open circuit voltage of 1.13 V (close to Nernst's theoretical value) and peak power density of 650 mW cm-2 at 550 °C, where the latter is one order of magnitude higher than NCAL electrode-free SIFC. Additionally, a bulk heterojunction effect is proposed to illustrate the electron-blocking and ion-promoting processes of the semiconductor-ionic composite electrolyte in SIFCs, based on the energy band values of the applied materials. Overall, we found that the energy conversion efficiency of novel SIFC can be remarkably improved through in situ exsolution and intentional introduction of the catalytic functionality.

Electrically Tunable MXene Nanomechanical Resonators Vibrating at Very High Frequencies.

As an emerging class of two-dimensional (2D) layered nanomaterial, MXene exhibits a number of intriguing properties, such as good electrical conductivity and high elastic modulus, and has witnessed continued growth in related device research. However, nanoscale MXene devices which leverage both the intrinsic electrical and mechanical properties of these 2D crystals have not been experimentally studied. Here we demonstrate nanoelectromechanical resonators based on 2D MXene crystals, where Ti3C2Tx drumheads with a wide range of thickness, from more than 50 layers all the way down to a monolayer, exhibit robust nanomechanical vibrations with fundamental-mode frequency f0 up to >70 MHz in the very high frequency (VHF) band, a displacement noise density down to 52 fm/Hz1/2, and a fundamental-mode frequency-quality factor product up to f0 × Q ≈ 6.85 × 109 Hz. By combining experimental results with theoretical calculations, we independently derive the Young's modulus of 2D Ti3C2Tx crystals to be 270-360 GPa, in excellent agreement with nanoindentation measurements, based on which we elucidate frequency scaling pathways toward microwave frequencies. We further demonstrate electrical tuning of resonance frequency in MXene resonators and frequency-shift-based MXene vacuum gauges with responsivity of 736%/Torr and detection range down to 10-4 Torr. Our study can lead to the design and creation of nanoscale vibratory devices that exploit the intrinsic electrical and mechanical properties in 2D MXene crystals.

Incremental PID Controller-Based Learning Rate Scheduler for Stochastic Gradient Descent.

As we all know, the learning rate plays a vital role in deep neural network (DNN) training. This study introduces an incremental proportional-integral-derivative (PID) controller widely used in automatic control as a learning rate scheduler for stochastic gradient descent (SGD). To automatically calculate the current learning rate, we utilize feedback control to determine the relationship between training losses and learning rates, named incremental PID learning rates, which include PID-Base and PID-Warmup. The new schedulers reduce the dependence on the initial learning rate and achieve higher accuracy. Compared with multistep learning rates (MSLR), cyclical learning rates (CLR), and SGD with warm restarts (SGDR), incremental PID learning rates based on feedback control obtain higher accuracy on CIFAR-10, CIFAR-100, and Tiny-ImageNet-200. We believe that our methods can improve the performance of SGD.

Physical and mental health problems of Chinese front-line healthcare workers before, during and after the COVID-19 rescue mission: a qualitative study.

OBJECTIVE: To explore the physical and mental health problems of front-line healthcare workers fighting COVID-19 across the three phases of the epidemic rescue mission (before, during and after) in China. DESIGN: A qualitative study was adopted using face to face, in-depth semistructured interviews. Phenomenological research methods and Colaizzi's seven-step analysis method were used in the study. SETTING: The setting of the study was the offices of healthcare workers in 12 tertiary hospitals. PARTICIPANTS: Thirty-one front-line healthcare workers from 16 provinces in China, who carried out rescue missions in Hubei Province, were interviewed from October to November 2020. RESULTS: Physical and mental health problems existed before, during and after the COVID-19 rescue mission. Eleven themes emerged during the three phases. Two themes appeared before rescue mission: basic diseases, anxiety before rescue mission. Five themes appeared during rescue mission: basic physical function disorder, physical exhaustion, negative cognition, negative emotions and negative behaviour. Four themes appeared after rescue mission: physical dysfunction, negative emotions, stigmatisation and hypochondriasis. CONCLUSION: Both physical and mental health problems occurred throughout the three phases. The study results pointed that a comprehensive prevention and control system that addresses both physical and mental health problems of front-line healthcare workers throughout the three phases of epidemic rescue mission (before, during and after), and that involves themselves, their families, hospitals, the government and social organisations is needed.

Conservative dynamics in a novel class of 3D generalized thermostatted systems.

This paper reports a method to derive a novel class of 3D generalized thermostatted oscillators from a simple damped harmonic oscillator. Its detailed procedure is obtained through a mathematical derivation. Then, we propose an example system to show the effectiveness of the method. Furthermore, the numerical analysis is performed to investigate its rich conservative dynamics, including chaotic sea, hierarchical invariant tori, and the coexistence of chaotic seas and invariant tori with islands-around-islands hierarchy, even if there are three dissipative terms in the example system. To verify the existence of conservative chaos at the physical level, an analog circuit is presented to observe the existing conservative chaotic flows in National Instruments multisim. We finally provide two systems, which can produce conservative chaotic flows with more complicated topologies, and draw our conclusions.

Nanomechanical Resonators: Toward Atomic Scale.

The quest for realizing and manipulating ever smaller man-made movable structures and dynamical machines has spurred tremendous endeavors, led to important discoveries, and inspired researchers to venture to previously unexplored grounds. Scientific feats and technological milestones of miniaturization of mechanical structures have been widely accomplished by advances in machining and sculpturing ever shrinking features out of bulk materials such as silicon. With the flourishing multidisciplinary field of low-dimensional nanomaterials, including one-dimensional (1D) nanowires/nanotubes and two-dimensional (2D) atomic layers such as graphene/phosphorene, growing interests and sustained effort have been devoted to creating mechanical devices toward the ultimate limit of miniaturization─genuinely down to the molecular or even atomic scale. These ultrasmall movable structures, particularly nanomechanical resonators that exploit the vibratory motion in these 1D and 2D nano-to-atomic-scale structures, offer exceptional device-level attributes, such as ultralow mass, ultrawide frequency tuning range, broad dynamic range, and ultralow power consumption, thus holding strong promises for both fundamental studies and engineering applications. In this Review, we offer a comprehensive overview and summary of this vibrant field, present the state-of-the-art devices and evaluate their specifications and performance, outline important achievements, and postulate future directions for studying these miniscule yet intriguing molecular-scale machines.