INPP5K controls the dynamic structure and signaling of wild-type and mutated, leukemia-associated IL-7 receptors.

The downstream signaling of the interleukin-7 (IL-7) receptor (IL-7R) plays important physiological and pathological roles, including the differentiation of lymphoid cells and proliferation of acute lymphoblastic leukemia cells. Gain-of-function mutations in the IL-7Rα chain, the specific component of the receptor for IL-7, result in constitutive, IL-7-independent signaling and trigger acute lymphoblastic leukemia. Here, we show that the loss of the phosphoinositide 5-phosphatase INPP5K is associated with increased levels of the INPP5K substrate phosphatidylinositol 4,5-bisphosphate (PtdIns[4,5]P2) and causes an altered dynamic structure of the IL-7 receptor. We discovered that the IL-7Rα chain contains a very conserved positively charged polybasic amino acid sequence in its cytoplasmic juxtamembrane region; this region establish stronger ionic interactions with negatively charged PtdIns(4,5)P2 in the absence of INPP5K, freezing the IL-7Rα chain structure. This dynamic structural alteration causes defects in IL-7R signaling, culminating in decreased expressions of EBF1 and PAX5 transcription factors, in microdomain formation, cytoskeletal reorganization, and bone marrow B-cell differentiation. Similar alterations after the reduced INPP5K expression also affected mutated, constitutively activated IL-7Rα chains that trigger leukemia development, leading to reduced cell proliferation. Altogether, our results indicate that the lipid 5-phosphatase INPP5K hydrolyzes PtdIns(4,5)P2, allowing the requisite conformational changes of the IL-7Rα chain for optimal signaling.

3D Off-Grid Localization for Adjacent Cavitation Noise Sources Using Bayesian Inference.

The propeller tip vortex cavitation (TVC) localization problem involves the separation of noise sources in proximity. This work describes a sparse localization method for off-grid cavitations to estimates their precise locations while keeping reasonable computational efficiency. It adopts two different grid (pairwise off-grid) sets with a moderate grid interval and provides redundant representations for adjacent noise sources. To estimate the position of the off-grid cavitations, a block-sparse Bayesian learning-based method is adopted for the pairwise off-grid scheme (pairwise off-grid BSBL), which iteratively updates the grid points using Bayesian inference. Subsequently, simulation and experimental results demonstrate that the proposed method achieves the separation of adjacent off-grid cavitations with reduced computational cost, while the other scheme suffers from a heavy computational burden; for the separation of adjacent off-grid cavitations, the pairwise off-grid BSBL took significantly less time (29 s) compared with the time taken by the conventional off-grid BSBL (2923 s).

Multi-Sonar Distributed Fusion for Target Detection and Tracking in Marine Environment.

The multi-sonar distributed fusion system has been pervasively deployed to jointly detect and track marine targets. In the realistic scenario, the origin of locally transmitted tracks is uncertain due to clutter disturbance and the presence of multi-target. Moreover, attributed to the different sonar internal processing times and diverse communication delays between sonar and the fusion center, tracks unavoidably arrive in the fusion center with temporal out-of-sequence (OOS), both problems pose significant challenges to the fusion system. Under the distributed fusion framework with memory, this paper proposes a novel multiple forward prediction-integrated equivalent measurement fusion (MFP-IEMF) method, it fuses the multi-lag OOST with track origin uncertainty in an optimal manner and is capable to be implemented in both the synchronous and asynchronous multi-sonar tracks fusion system. Furthermore, a random central track initialization technique is also proposed to detect the randomly born marine target in time via quickly initiating and confirming true tracks. The numerical results show that the proposed algorithm achieves the same optimality as the existing OOS reprocessing method, and delivers substantially improved detection and tracking performance in terms of both ANCTT and estimation accuracy compared to the existing OOST discarding fusion method and the ANF-IFPFD method.

Improvement in the Tracking Performance of a Maneuvering Target in the Presence of Clutter.

The proposed work uses fixed lag smoothing on the interactive multiple model-integrated probabilistic data association algorithm (IMM-IPDA) to enhance its performance. This approach makes use of the advantages of the fixed lag smoothing algorithm to track the motion of a maneuvering target while it is surrounded by clutter. The suggested method provides a new mathematical foundation in terms of smoothing for mode probabilities in addition to the target trajectory state and target existence state by including the smoothing advantages. The suggested fixed lag smoothing IMM-IPDA (FLs IMM-IPDA) method's root mean square error (RMSE), true track rate (TTR), and mode probabilities are compared to those of other recent algorithms in the literature in this study. The results clearly show that the proposed algorithm outperformed the already-known methods in the literature in terms of these above parameters of interest.

A Machine-Learning-Based Robust Classification Method for PV Panel Faults.

Renewable energy resources have gained considerable attention in recent years due to their efficiency and economic benefits. Their proportion of total energy use continues to grow over time. Photovoltaic (PV) cell and wind energy generation are the least-expensive new energy sources in most countries. Renewable energy technologies significantly contribute to climate mitigation and provide economic benefits. Apart from these advantages, renewable energy sources, particularly solar energy, have drawbacks, for instance restricted energy supply, reliance on weather conditions, and being affected by several kinds of faults, which cause a high power loss. Usually, the local PV plants are small in size, and it is easy to trace any fault and defect; however, there are many PV cells in the grid-connected PV system where it is difficult to find a fault. Keeping in view the aforedescribed facts, this paper presents an intelligent model to detect faults in the PV panels. The proposed model utilizes the Convolutional Neural Network (CNN), which is trained on historic data. The dataset was preprocessed before being fed to the CNN. The dataset contained different parameters, such as current, voltage, temperature, and irradiance, for five different classes. The simulation results showed that the proposed CNN model achieved a training accuracy of 97.64% and a testing accuracy of 95.20%, which are much better than the previous research performed on this dataset.

Modified Smoothing Algorithm for Tracking Multiple Maneuvering Targets in Clutter.

This research work extends the fixed interval smoothing based on the joint integrated track splitting (FIsJITS) filter in the multi-maneuvering-targets (MMT) tracking environment. We contribute to tackling unknown dynamics of the multi-maneuvering-targets (MMT) using the standard kinematic model. This work is referred to as smoothing MMT using the JITS (MMT-sJITS). The existing FIsJITS algorithm is computationally more complex to solve for the MMT situation because it enumerates a substantial number of measurement-to-track assignments and calculates their posteriori probabilities globally. The MMT-sJITS updates a current target track by assuming the joint (common) measurements detected by neighbor tracks are modified clutters (or pretended spurious measurements). Thus, target measurement concealed by a joint measurement is optimally estimated based on measurement density of the modified clutter. This reduces computational complexity and provides improved tracking performance. The MMT-sJITS generates forward tracks and backward tracks using the measurements collected by a sensor such as a radar. The forward and backward multi-tracks state predictions are fused to obtain priori smoothing multi-track state prediction, as well as their component existence probabilities. This calculates the smoothing estimate required to compute the forward JITS state estimate, which reinforces the MMT tracking efficiently. Monte Carlo simulation is used to verify best false-track discrimination (FTD) analysis in comparison with existing multi-targets tracking algorithms.

A Modified Bayesian Framework for Multi-Sensor Target Tracking with Out-of-Sequence-Measurements.

Target detection and tracking is important in military as well as in civilian applications. In order to detect and track high-speed incoming threats, modern surveillance systems are equipped with multiple sensors to overcome the limitations of single-sensor based tracking systems. This research proposes the use of information from RADAR and Infrared sensors (IR) for tracking and estimating target state dynamics. A new technique is developed for information fusion of the two sensors in a way that enhances performance of the data association algorithm. The measurement acquisition and processing time of these sensors is not the same; consequently the fusion center measurements arrive out of sequence. To ensure the practicality of system, proposed algorithm compensates the Out of Sequence Measurements (OOSMs) in cluttered environment. This is achieved by a novel algorithm which incorporates a retrodiction based approach to compensate the effects of OOSMs in a modified Bayesian technique. The proposed modification includes a new gating strategy to fuse and select measurements from two sensors which originate from the same target. The state estimation performance is evaluated in terms of Root Mean Squared Error (RMSE) for both position and velocity, whereas, track retention statistics are evaluated to gauge the performance of the proposed tracking algorithm. The results clearly show that the proposed technique improves track retention and and false track discrimination (FTD).

Tracking and Estimation of Multiple Cross-Over Targets in Clutter.

Tracking problems, including unknown number of targets, target trajectories behaviour and uncertain motion of targets in the surveillance region, are challenging issues. It is also difficult to estimate cross-over targets in heavy clutter density environment. In addition, tracking algorithms including smoothers which use measurements from upcoming scans to estimate the targets are often unsuccessful in tracking due to low detection probabilities. For efficient and better tracking performance, the smoother must rely on backward tracking to fetch measurement from future scans to estimate forward track in the current time. This novel idea is utilized in the joint integrated track splitting (JITS) filter to develop a new fixed-interval smoothing JITS (FIsJITS) algorithm for tracking multiple cross-over targets. The FIsJITS initializes tracks employing JITS in two-way directions: Forward-time moving JITS (fJITS) and backward-time moving JITS (bJITS). The fJITS acquires the bJITS predictions when they arrive from future scans to the current scan for smoothing. As a result, the smoothing multi-target data association probabilities are obtained for computing the fJITS and smoothing output estimates. This significantly improves estimation accuracy for multiple cross-over targets in heavy clutter. To verify this, numerical assessments of the FIsJITS are tested and compared with existing algorithms using simulations.

Multisensor-Based Target-Tracking Algorithm with Out-of-Sequence-Measurements in Cluttered Environments.

A localization and tracking algorithm for an early-warning tracking system based on the information fusion of Infrared (IR) sensor and Laser Detection and Ranging (LADAR) is proposed. The proposed Kalman filter scheme incorporates Out-of-Sequence Measurements (OOSMs) to address long-range, high-speed incoming targets to be tracked by networked Remote Observation Sites (ROS) in cluttered environments. The Rauch⁻Tung⁻Striebel (RTS) fixed lag smoothing algorithm is employed in the proposed technique to further improve tracking accuracy, which, in turn, is used for target profiling and efficient filter initialization at the targeted platform. This efficient initialization increases the probability of target engagement by increasing the distance at which it can be effectively engaged. The increased target engagement range also reduces risk of any damage from debris of the engaged target. Performance of the proposed target localization algorithm with OOSM and RTS smoothing is evaluated in terms of root mean square error (RMSE) for both position and velocity, which accurately depicts the improved performance of the proposed algorithm in comparison with existing retrodiction-based OOSM filtering algorithms. The effects of assisted target state initialization at the targeted platform are also evaluated in terms of Time to Impact (TTI) and true track retention, which also depict the advantage of the proposed strategy.

V4C3 MXene: a Type-II Nodal Line Semimetal with Potential as High-Performing Anode Material for Mg-Ion Battery.

We have used density functional theory simulations to explore the topological characteristics of a new MXene-like material, V4C3, and its oxide counterpart, assessing their potential as anode materials for Mg-ion batteries. Our research reveals that V4C3 monolayer is a topological type-II nodal line semimetal, protected by time reversal and spatial inversion symmetries. This type-II nodal line is marked by unique drumhead-like edge states that appear either inside or outside the loop circle, contingent upon the edge ending. Intriguingly, even with an increase in metallicity due to oxygen functionalization, the topological features of V4C3 remain intact. Consequently, the monolayer V4C3 has a topologically enhanced electrical conductivity that amplifies further upon oxygen functionalization. During the charging phase, a remarkable storage concentration led to a peak specific capacity of 894.73 mAh g-1 for V4C3, which only decreases to 789.33 mAh g-1 for V4C3O2. When compared to V2C, V4C3 displays a significantly lower specific capacity loss due to functionalization, demonstrating its superior electrochemical properties. Additionally, V4C3 and V4C3O2 exhibit moderate average open-circuit voltages (0.54 V for V4C3 and 0.58 V for V4C3O2) and energy barriers for intercalation migration (ranging between 0.29-0.63 eV), which are desirable for anode materials. Thus, our simulation results support V4C3 potential as an efficient anode material for Mg-ion batteries.

Dual-band independently tunable 8-element MIMO antenna for 5G smartphones.

In this paper, a multi-input multi-output (MIMO) antenna for future mobile phone applications operating in sub-6 GHza using a novel combination of an E-shaped slot placed on the ground plane and an F-shaped probe is used to achieve a dual-band independently tunable antenna. The proposed antenna is not only self-isolated but it has also effectively achieved high isolation of greater than 17 dB in both 3.5 GHz (3.4 - 3.6 GHz) and 4.7 GHz (4.6 - 4.87 GHz) frequency bands for 8-element MIMO antenna configuration for 5G smartphones. The simple yet compact size of (0.035 λ0Image 1 0.23 λ0), of the slot antenna produces a balanced slot mode which not only reduces the ground effects but also improves the isolation between two adjacent input ports. The novelty of the proposed dual-band MIMO antenna is its independent control of each band across a wide frequency band and results demonstrate higher efficiency (64% - 71%) and diversity gain performance in both frequency bands. Furthermore, the antenna is designed by the meticulous configurations of 8-antenna elements without employing any external decoupling structure to attain the desired polarization diversity. The prototype of this 8-element MIMO antenna is also fabricated and measured to validate its simulated performance. The simple structure of the proposed design and high efficiency makes it a promising candidate for 5G smartphones.

Topological Nodal Surface and Quadratic Dirac Semimetal States and van Hove Singularities in ScH3 and LuH3 Superconductors.

The coexistence of non-trivial topology and superconductivity in a material may induce a novel physical phenomenon known as topological superconductivity. Topological superconductors have been the subject of intense research, yet there are severe limitations in their application due to a lack of suitable materials. Topological nodal surface semimetals with nearly flat nodal surfaces near the Fermi level can be promising materials to achieve topological superconductivity. Here, we use first-principles calculations to examine the topological electronic characteristics of two new superconductors, ScH3 and LuH3, at both ambient and high pressures. Our studies show that both ScH3 and LuH3 have van Hove singularities, which confirms their superconductivity. Interestingly, both materials host topological nodal surface states under the protection of time reversal and spatial inversion symmetries in the absence of spin-orbit coupling (SOC). These nodal surfaces are distinguished by a pair of unique drum-head-like surface states not previously observed in nodal surface semimetals. Moreover, the nodal surfaces transform into essential spin-orbit quadratic Dirac points when SOC is included. Our findings demonstrate that ScH3 and LuH3 are good candidates to investigate the exotic properties of both nodal surface semimetals (NSSMs) and quadratic Dirac semimetal states and also provide a platform to explore the coexistence of topology and superconductivity in NSSMs with promising applications in high-speed electronics and topological quantum computing.

Robust Tunable Large-Gap Quantum Spin Hall States in Monolayer Cu2S on Insulating Substrates.

Quantum spin Hall (QSH) insulators with large band gaps and dissipationless edge states are of both technological and scientific interest. Although numerous two-dimensional (2D) systems have been predicted to host the QSH phase, very few of them harbor large band gaps and retain their nontrivial band topology when they are deposited on substrates. Here, based on a first-principles analysis with hybrid functional calculations, we investigated the electronic and topological properties of inversion-asymmetric monolayer copper sulfide (Cu2S). Interestingly, we found that monolayer Cu2S possesses an intrinsic QSH phase, Rashba spin splitting, and a large band gap of 220 meV that is suitable for room-temperature applications. Most importantly, we constructed heterostructures of a Cu2S film on PtTe2, h-BN, and Cu(111) substrates and found that the topological properties remain preserved upon an interface with these substrates. Our findings suggest Cu2S as a possible platform to realize inversion-asymmetric QSH insulators with potential applications in low-dissipation electronic devices.

Does farmers' agricultural investment is impacted by green finance policies and financial constraint? From the perspective of farmers' heterogeneity in Northwest China.

Green finance is a situation in which finance and environmental conservation are combined. Green credit management is a crucial green financial mechanism for achieving a win-win situation with economic development and environmental conservation through prudent credit resource allocation. Similarly, the continued involvement of farmers in green finance policies as micro-actors is critical to policy execution in rural regions. In current research, we utilized 2520 micro-surveys to measure the effects of green finance policies on agricultural investment of farmers in a difference-in-differences framework and developed a mediation effect model based on the degree of coupling coordination between financial development and environmental sustainability. It investigates the effects of heterogeneity in farmers' management on the mediating effect of financial restrictions. The study results show that, in comparison to the favorable effects of green finance policies on agricultural investment of farmers, the inclusion of a financial constraint variable reduces that benefit. Furthermore, farmers that engage in non-agricultural management practices are more likely to benefit from green finance policies and are impacted by the intermediate mechanism's financial restrictions. The construction of a rural green financial system should accomplish differentiated positioning and rapid development.

Questions about chemokine and chemokine receptor antagonism in renal inflammation.

Chemokines remain attractive therapeutic targets for modulating inflammatory diseases in all areas of medicine including acute and chronic kidney disease. Industry has launched huge programs for the development of chemokine antagonists, and clinical trials with chemokine and chemokine receptor antagonists are ongoing. However, chemokine biology remains an area of unexpected discoveries. Here we discuss a number of questions which need to be addressed to further explore the potential of chemokine antagonism in renal inflammation: Why does renal expression of chemokines and chemokine receptors not always correlate with their functional significance? Why does chemokine antagonism only partially reduce renal leukocyte counts? Will antagonist combinations be more effective in reducing renal inflammation? What are the functional roles of homeostatic chemokines and atypical, nonsignaling chemokine receptors in renal inflammation? And finally, what classes of chemokine antagonists are available to address these questions experimentally?

Metered Dose Inhaler Technique: A Priority Catch for Physicians.

BACKGROUND: Asthma is a non-curable but preventable disease that can be controlled by a proper approach. Inhalational route is considered to be one of the fastest, non-invasive course for the management of asthma. Despite its importance, compliance towards proper inhalational technique remains quite low. Thus, United Kingdom guidelines and Global Strategy for Asthma Management and Prevention (GINA) recommend regular assessment of inhaler techniques in all asthma patients. OBJECTIVE: To evaluate the inhalational technique of asthma patients visiting out-patient departments of public sector tertiary care hospitals of Rawalpindi and correlate with various demographic factors. METHODS: A cross-sectional study was conducted on a total of 209 respondents visiting the outpatient department of public sector hospitals in Rawalpindi. Asthmatic patients were included via a non-probability consecutive sampling technique and were assessed for inhaler techniques via a structured checklist. Statistical data were analyzed using IBM Statistical Package for Social Sciences (SPSS®), version 25.0 (IBM Corp., Armonk, NY, USA). RESULTS: Two hundred and nine asthma patients were included. Only 10% of patients demonstrated the correct inhaler technique. Continuing inhaling till lungs are full, holding breath for five to 10 seconds, and breathing out slowly after using the inhaler were most poorly followed. CONCLUSION: Most asthma patients are using poor inhalation technique, risking sub-optimal drug delivery and inadequate effects. Hence, it is the need of the hour to focus on patient training and education.

Ultrasonically controlled growth of monodispersed octahedral BiVO4 microcrystals for improved photoelectrochemical water oxidation.

The synthesis of facet-controlled structures with precise morphology and exposed reactive surface is one of the key research challenges. We effectively endeavoured to obtain the monodisperse octahedral bismuth vanadate microcrystals with exposed {101},{200},{312} and {021} dominant facets through an optimized sonochemical assisted hydrothermal process. A pulse sonication (5-s ON and 2-s OFF cycle, 21 W ultrasonic power and 20 kHz ultrasonic frequency) for 30 mins followed by 1 h hydrothermal treatment was found to yield the preferred octahedral morphology. The microscopic and X-ray analysis suggested a potent role of ultrasonic waves for the initial seed growth and its evolution into a well-defined monodisperse microcrystals. The density functional theory (DFT) calculations revealed strongly localized bandgap states with a bandgap of ~2.47 eV. The PEC measurements for water oxidation demonstrated the efficacy of these microcrystals as photoanode. Notably, the optimized octahedral BiVO4 microstructure exhibited a superior performance as evident from photocurrent density ~0.9 mAcm-2 at 1.23 V vs. RHE and %IPCE value of ~22% compared to analogous photoanodes under visible light irradiation.

Altered chondrocyte differentiation, matrix mineralization and MEK-Erk1/2 signaling in an INPPL1 catalytic knock-out mouse model of opsismodysplasia.

Opsismodysplasia (OPS) is a rare but severe autosomal recessive skeletal chondrodysplasia caused by inactivating mutations in the Inppl1/Ship2 gene. The molecular mechanism leading from Ship2 gene inactivation to OPS is currently unknown. Here, we used our Ship2Δ/Δ mouse expressing reduced amount of a catalytically-inactive SHIP2 protein and a previously reported SHIP2 inhibitor to investigate growth plate development and mineralization in vivo, ex vivo and in vitro. First, as observed in OPS patients, catalytic inactivation of SHIP2 in mouse leads to reduced body length, shortening of long bones, craniofacial dysmorphism, reduced height of the hyperthrophic chondrocyte zone and to defects in growth plate mineralization. Second, intrinsic Ship2Δ/Δ bone defects were sufficient to induce the characteristic OPS alterations in bone growth, histology and mineralization ex vivo. Third, expression of osteocalcin was significantly increased in SHIP2-inactivated chondrocyte cultures whereas production of mineralized nodules was markedly decreased. Targeting osteocalcin mRNA with a specific shRNA increased the production of mineralized nodules. Fourth, levels of p-MEK and p-Erk1/2 were significantly increased in SHIP2-inactivated chondrocytes in response to serum and IGF-1, but not to FGF2, as compared to control chondrocytes. Treatment of chondrocytes and bones in culture with a MEK inhibitor partially rescued the production of mineralized nodules, the size of the hypertrophic chondrocyte zone and bone growth, raising the possibility of a treatment that could partially reduce the phenotype of this severe condition. Altogether, our results indicate that Ship2Δ/Δ mice represent a relevant model for human OPS. They also highlight the important role of SHIP2 in chondrocytes during endochondral ossification and its different differentiation steps. Finally, we identified a role of osteocalcin in mineralized nodules production and for the MEK-Erk1/2 signaling pathway in the OPS phenotype.