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Due to various technical issues, existing numerical weather prediction (NWP) models often perform poorly at forecasting rainfall in the first several hours. To correct the bias of an NWP model and improve the accuracy of short-range precipitation forecasting, we propose a deep learning-based approach called UNetMask, which combines NWP forecasts with the output of a convolutional neural network called UNet. The UNetMask involves training the UNet on historical data from the NWP model and gridded rainfall observations for 6-hour precipitation forecasting. The overlap of the UNet output and the NWP forecasts at the same rainfall threshold yields a mask. The UNetMask blends the UNet output and the NWP forecasts by taking the maximum between them and passing through the mask, which provides the corrected 6-hour rainfall forecasts. We evaluated UNetMask on a test set and in real-time verification. The results showed that UNetMask outperforms the NWP model in 6-hour precipitation prediction by reducing the FAR and improving CSI scores. Sensitivity tests also showed that different small rainfall thresholds applied to the UNet and the NWP model have different effects on UNetMask’s forecast performance. This study shows that UNetMask is a promising approach for improving rainfall forecasting of NWP models.

Finding special items in data streams, like heavy hitters, top-k items, and persistent items, has always been a hot topic in the field of network measurement. While data streams nowadays are usually high-dimensional, most prior works optimize data structures to accurately find special items according to a certain primary dimension and yield little insight into the correlations between dimensions, where the dimension can be a single data dimension or a combination of multiple data dimensions. Therefore, we propose to find special quadratic elements in data streams to reveal the close correlations between the primary and secondary dimensions. Here, both the primary and secondary dimensions are selected according to specific application purposes. Based on the special items mentioned above, we extend our problem to three applications related to heavy hitters, top-k, and persistent items, and design a generic framework DUET to process them. We analyze the error bound of our algorithm theoretically and conduct extensive experiments on four publicly available data sets. Our experimental results show that DUET can achieve 3.5 times higher throughput and three orders of magnitude lower average relative error than cutting-edge algorithms. Moreover, we propose an optimized framework based on DUET, namely O-DUET, to further improve the estimation accuracy. We also discuss a hardware-version DUET and deploy it on Tofino.

The quality of the video stream is the key to neural network-based video analytics. However, low-quality video is inevitably collected by existing surveillance systems because of poor-quality cameras or over-compressed/pruned video streaming protocols, e.g., as a result of upstream bandwidth limit. To address this issue, existing studies use quality enhancers (e.g., neural super-resolution) to improve the quality of videos (e.g., resolution) and eventually ensure inference accuracy. Nevertheless, directly applying quality enhancers does not work in practice because it will introduce unacceptable latency. In this paper, we present AccDecoder, a novel accelerated decoder for real-time and neural-enhanced video analytics, selects a few frames adaptively via Deep Reinforcement Learning (DRL) to enhance the quality and inference then reuse on the unselected ones. Next, we extend AccDecoder to AccDecoder+ by formulating the resolution-involved Markov decision process (MDP) to achieve resolution adaptation; it aims to trade accuracy and latency corresponding under various video resolutions. Proved by experiments, AccDecoder provides efficient inference capability via filtering important frames using DRL for DNN-based inference and reusing the results for the other frames via extracting the reference relationship among frames and blocks, which contributes 6-21% accuracy improvement and a latency reduction of 20-80% than baselines. Compared with AccDecoder, AccDecoder+ achieves an additional 2-7% accuracy improvement.

Multipath TCP (MPTCP) is a burgeoning transport protocol which enables the server to transmit the traffic across multiple network interfaces in parallel. Classic MPTCPs have good friendliness and practicality such as relatively low overhead, but are hard to achieve consistent high-throughput and adaptability, especially for the ability to flexibly balance the congestion among different subpaths. In contrast, learning-based MPTCPs can essentially achieve consistent high-throughput and adaptability, but have poor friendliness and practicality. In this paper, we proposed MPLibra, a combined multipath congestion control framework that can complement the advantages of classic MPTCPs and learning-based MPTCPs together. MPLibra periodically leverages both classic MPTCPs and learning-based MPTCPs to make decisions and select the better one based on real-time network feedbacks. Extensive simulations on NS3 show that MPLibra can achieve good performance and outperform state-of-the-art MPTCPs under different network conditions. MPLibra improves the throughput by 40.5% and reduces the file download time by 29.94% compared with LIA, achieves good friendliness and balances congestion timely. What’s more, on the basis of MPLibra, we propose MPLibra+ which adds a safety module and an optimized packet scheduler and is the upgrade version of MPLibra. MPLibra+ has better ability to cope with untrained network environment and achieve better performance on heterogeneous scenarios compared with MPLibra.

Fiber has been considered as an ideal material for virus insulation due to the readily available electrostatic adsorption. However, restricted by the electrostatic attenuation and filtration performance decline, their long-lasting applications are unable to satisfy the requirements of medical protective equipment for major medical and health emergencies such as global epidemics, which results in both a waste of resources and environmental pollution. We overcame these issues by constructing a fiber-in-tube structure, achieving the robust reusability of fibrous membranes. Core fibers within the hollow could form generators with tube walls of shell fibers to provide persistent, renewable static electricity via piezoelectricity and triboelectricity. The PM0.3insulation efficiency achieved 98% even after 72 h of humidity and heat aging, through beating and acoustic waves, which is greatly improved compared with that of traditional nonwoven fabric (∼10% insulation). A mask spun with our fiber also has a low breathing resistance (differential pressure <24.4 Pa/cm2). We offer an approach to enrich multifunctional fiber for developing electrifiable filters, which make the fiber-in-tube filtration membrane able to durably maintain a higher level of protective performance to reduce the replacement and provide a new train of thought for the preparation of other high-performance protective products.

Aims:Targeted temperature management is recommended for at least 24 h in comatose survivors of in-hospital cardiac arrest (IHCA) after the return of spontaneous circulation; however, whether an extension for 72 h leads to better neurological outcomes is uncertain. Methods:We included data from the Qilu Hospital of Shandong University between July 20, 2019, and June 30, 2022. Unconscious patients who had return of spontaneous circulation lasting >20 consecutive min and received endovascular cooling (72 h) or normothermia treatment were compared in terms of survival-to-discharge and favorable neurological survival. Propensity score matching was used to formulate balanced 1:3 matched patients. Results:In total, 2,084 patients were included. Sixteen patients received extended endovascular cooling and 48 matched controls received normothermia therapy. Compared with the normothermia group, patients who received prolonged endovascular cooling had a higher survival-to-discharge rate. However, good neurological outcomes did not differ significantly. Before matching, Cox regression analysis, using mortality as the event, showed that extended endovascular cooling independently affected the survival of IHCA patients. Conclusions:Among comatose patients who had been resuscitated from IHCA, the use of endovascular cooling for 72 h might confer a benefit on survival-to-discharge.

Data centers heavily rely on scale-out architectures like fat-tree, BCube and VL2 to accommodate a large number of commodity servers. Since the traditional electrical network is demand-oblivious and cannot perfectly respond to the bursty traffic generated by big data applications, a growing trend is to design demand-aware topologies via introducing the converters with adjustable optical links, instead of adding more wiring links. However, little is known today about how to fully exploit the potential of the flexibility from the converters: the joint optimization on adjusting the optical links inside the converters and the routing in the whole network remains algorithmically challenging. In this paper, we design a set of customized converters for Diamond, VL2 and BCube topologies and initiate the optimization study in hybrid switching data center networks. As a case study, we introduce demand-aware load balancing problem (DLBP), i.e., a joint optimization on the physical layer (how the optical links interconnect inside the converter) and the network layer (how to determine the route especially for elephant flows in the whole network). We prove that DLBP is not only NP-hard, but also $\rho $ -inapproximation. Accordingly, we design two algorithms: the first one is an intuitive greedy algorithm and the second one uses reinforcement learning to improve upon the solution of the first one. Trace-driven evaluations show that our algorithms can reduce the traffic congestion by 12% on average.

Counterfeit items are growing worldwide, affecting the global economy and human health. Anticounterfeiting tags based on a physical microstructure or chemical materials have enjoyed long-term commercial success due to their visualization and inexpensive production. However, conventional anticounterfeiting tags can be readily imitated. Herein, we have overcome this limitation by assembling colloidal nanospheres and two luminescent micromaterials into a composited photonic crystal (PhC) and achieved massive scale-up fabrication of multilevel anticounterfeiting PhC films in just several minutes of thermal rolling. The fabricated PhC film exhibits three optical states, including angle-dependent structural color (reflectivity = 66%) under white light, emits green light under 980 nm light, and emits red light under ultraviolet light. Multilevel anticounterfeiting colorful images were obtained by further use of masking templates, which integrate colors from both physically colored microstructures and chemical luminescent materials. Besides, the thermal-rolling process also shows excellent feasibility for assembling microunits with different sizes into high-quality functional PhC films.

Charger placement is an important problem in improving the quality of service in wireless rechargeable sensor networks. This paper studies the problem of Wireless ChArger PlacemeNt with Multiple (Directional) Antennas (WANDA). The problem is described as follows: given a set of wireless chargers equipped with multiple directional antennas and a set of wireless rechargeable sensors, determine the chargers’ positions and orientations to maximize the overall charging utility. According to the relative positional relationship between the antennas, the problem is classified into Relative Orientation Fixed (WANDA-ROF) and Relative Orientation Unfixed (WANDA-ROU) situations. To address WANDA, we present a piecewise constant function to approximate the nonlinearity of charging power and propose an area discretization technique to reduce the infinite solution space to a limited one without performance loss. Then, we prove the monotonic submodularity of WANDA, and present a $\frac{1}{2}-\epsilon$12-ε approximation algorithm for the ROF situation and a $\frac{1}{6}-\epsilon$16-ε approximation algorithm for the ROU situation, all run in polynomial time. Finally, we conduct extensive simulation and experiments to show that our algorithms outperform comparison algorithms by at least 16% for ROF situation and 12% for ROU situation.

Banana (Musa nana L.) is a typical tropical and climacteric fruit. Post-harvest ripening is an important process involving changes in banana quality. The key physicochemical indicators associated with the quality of bananas were analysed during storage at 12 ℃. The gas compounds released during the storage of banana fruits were measured in situ using solid-phase microextraction tandem gas chromatography–mass spectrometry (SPME–GC–MS). The results showed that the L* value, weight loss, and solid/acid ratio significantly increased during post-ripening, while the a* value, firmness, titratable acidity (TA), and total phenol content showed a marked decrease. Among the released volatiles, esters were the most abundant gases, accounting for approximately 90% of the total gas amount. After analysing the correlation between volatiles and physicochemical parameters, the total volatile and ester contents were found to have a significant positive correlation with the a* value and solid/acid ratio, as well as an obvious negative correlation with the firmness. This study provides a reference for monitoring the ripening state of banana fruit by non-destructive measurement of its released gases in situ.

Virtualized network functions (VNFs) enable software applications to replace traditional middleboxes, which are more flexible and scalable in the network service provision. This paper focuses on ensuring Service Availability via Failure Elimination (SAFE) using VNF scaling, that is, given the resource requirements of VNF instances, finding an optimal and robust instance consolidation strategy, which can recover from one instance failure quickly. To address the above problem, we present a framework based on rounding and dynamic programming. First, we discretize the range of resource requirements into several sub-ranges, and thus the number of instance types becomes a constant. Second, we further reduce the number of instance types by gathering several small instances into a bigger one. Third, we propose an algorithm built on dynamic programming to solve the instance consolidation problem with a limited number of instance types. Finally, we set up a testbed to profile the functional relationship between the resource and the throughput for different types of VNFs, and conduct simulations to validate our theoretical results according to profiling results. The simulation results show that our algorithm outperforms the standby deployment model by 27.33% on average in terms of the number of servers required. Furthermore, SAFE has marginal overheads, around 7.22%, compared to the instance consolidation strategy without VNF backup consideration.

The effectiveness of time- and temperature-sensitive medical products (TTSMPs) (vaccines, medicines, and biological agents) is generally evaluated by sporadically checking the storage conditions recorded in electronic thermometers. However, electronic thermometers do not achieve all-time and all-regional record, resulting in the wrong evaluation of a single TTSMP and seriously endangering public health. Herein, we report a photonic crystal sensor for evaluating the effectiveness of a single TTSMP processing storage environment. The photonic crystal sensor assembled by colloidal microspheres (WO3–xnanospheres were added into the microsphere gap) generates a fascinating composite color of angle-dependent structural color (maximum reflectivity = 45%) and durative color (WO3–xcoloration). Effectiveness evaluation principle reveals that the pattern on the sensor, which was printed by the composite color, fades sensitively to time and temperature, thus having different visible periods (0–21 days affected by temperature). The visible periods of the patterns can be used to evaluate a single TTSMP’s effectiveness stored under different temperatures. Furthermore, the photonic crystal sensor shows outstanding flexibility and slight adhesion, offering a promising application toward the effectiveness evaluation of TTSMPs throughout storage, transportation, and sales processes.

A controller needs to solve the multi-commodity flow problem and globally update the network under tight time constraints to maintain optimal network configurations. This centralized optimization in data centers involves many variables and constraints, which has a slow convergence speed and little scalability. In this paper, we propose MiFi, which aims to Minimize Flow cost or intuitively average transmission delay (delay or latency of flows), under reconfiguration budget constraints in data centers. Thus, we formulate this optimization problem as a constrained Markov Decision Process and propose a set of algorithms to solve it in a scalable manner. We first develop a propagation algorithm to identify the flows mostly affected in terms of latency and configuration in the next update. Then, we set a limitation range (the subset of switches requiring network updates) for updating them to improve adaptability and scalability by updating a less number of flows each time to achieve fast operations. Further, based on the Drift-Plus-Penalty method in Lyapunov theory, we propose a heuristic policy without prior information of flow demand and a renewal policy with a performance guarantee to minimize the additive optimality gap. To the best of our knowledge, MiFi is the first paper that studies the range and frequency of flow reconfigurations, which has both theoretical and practical significance in the area. Emulations and numerical simulations, which are much better than the estimated theoretical bound, show that MiFi outperforms the state of the art algorithms in terms of latency by over 45% while making improvements in adaptability and scalability.

Aiming at the problems of low fault location accuracy and large diagnosis error of traditional link fault diagnosis methods, this paper designs a new fault diagnosis method for substation relay protection link operation based on characteristic parameters. Firstly, the equivalent circuit fault characteristic parameters of the link are extracted through the degradation model, and the characteristic parameters such as link rated delay drift, link sampling value and frame loss are determined. Then, the correlation of characteristic parameters is determined according to the clustering core parameters, and the irrelevant characteristic parameters are removed through the error function. Finally, the fault characteristic sequence is determined according to different characteristic parameters in the node, and the fault point location is determined by Min distance to achieve fault diagnosis. The experimental results show that the proposed method can improve the accuracy of link fault location, and the diagnosis effect is good.

Photonic crystal (PhC) light emitter (PC-LE) devices attract extensive attention in anticounterfeiting for their manipulated light emission and iridescent structural color, but their large-scale three-dimensional fabrication is still limited by poor mechanical strength and microstructural defects. Herein, colloidal nanospheres incorporated with photoluminescent dye were assembled to three-dimensional PC-LE devices through a large-scale compressing-induced strategy, which realized dual iridescent and reversible photochromic colors. Periodically distributed refractive indices between molten molecular chains and cross-linked nanospheres generated the iridescent structural color. Subsequently, the device surface reflected another different structural color after partially removing the surface molecular chains by etching. The light emission intensity of the dye was sufficient to obtain the reversible photochromic colors. Simultaneously, the manipulation toward light emission of the photonic band gap achieved the shape of the photoluminescent intenstiy spectra that varied in accordance with the reflective peak. Furthermore, by use of screen-printing tools and transparent masking glue, the etching process became an inkless color printing process, generating a colorful bar code (2 cm × 2 cm) on the device surface. The code was reversibly displayed and encrypted through control of the reflection and emission of light. Significantly, the PC-LE devices opened up a new route for advanced display, color printing, and anticounterfeiting stickers.

The rapid development of underwater vehicles has posed the pressing and urgent requirement for smart underwater skin. Developing the multi-function underwater skin for sound detection and absorption is of significance for environment investigation and stable operation of underwater vehicles. Herein, a novel underwater acoustic skin with dual functions of sensitive sound detection and effective sound absorption under high hydrostatic pressure was reported. With addition of piezoelectric multiple yolk–shell particles and carbon nanotube network, the smart skin exhibited excellent sound absorption performance and enhanced mechanical property, which retained a high sound coefficient under pressure of 3 MPa compared to the resin skin. The enhanced skin with piezoelectric particles also exhibited sensitive sound detection capability with admirable directivity. The results proved the broad application prospect of the acoustic skin based on piezoelectric multiple yolk–shell particles and conductive network in the underwater extreme environment.

The demand for flexible, efficient, and self-powered cochlear implants applied to remedy sensorineural hearing loss caused by dysfunctional hair cells remains urgent. Herein, we report an acoustic core–shell resonance harvester for the application of artificial cochleae based on the piezo-triboelectric effect. Integrating dispersed BaTiO3particles as cores and porous PVDF-TrFE as shells, the acoustic harvest devices with ingenious core–shell structures exhibit outstanding piezo-triboelectric properties (Voc= 15.24 V, DAsc= 9.22 mA/m2). The acoustic harvest principle reveals that BaTiO3nanocores resonate with sound waves and bounce against porous PVDF-TrFE microshells, thereby generating piezo-triboelectric signals. By experimental measurement and numerical modeling, the vibration process and resonance regulation of acoustic harvest devices were intensively investigated to regulate the influential parameters. Furthermore, the acoustic harvesters exhibit admirable feasibility and sensitivity for sound recording and show potential application for artificial cochlea.

Restricted by the inherent property of low power density, acoustic energy can hardly be effectively captured by conventional piezo- or triboelectric nanogenerators for powering miniature electronics. Herein, a novel piezo–tribo hybrid nanogenerator employing nanoporous polyvinylidene fluoride (PVDF) hollow fiber and polydimethylsiloxane (PDMS) valve, which can mimic the eardrum, has been advocated for efficient acoustic harvesting. The nanoporous, hollow, and valve structure design, together with the effective combination of piezo- and triboelectricity, make the nanoporous PVDF hollow fiber and PDMS valve based acoustic harvester (PHVAH) a promising candidate for acoustic–electric conversion. With an optimal output of 105.5 V and 16.7 μA and a power density of 0.92 W m–2under the sound stimulation of 117.6 dB and 150 Hz, it can not only recognize audio signals but also convert the sound into electrical energy to light up seven LED bulbs in series. Exhibiting excellent durability and stability, the disruptive innovation proposed here is an effective method for hunting the ubiquitous sound energy in the environment, which provides great potential and impetus for using acoustic–electric conversion to power various low-power-consumption sensors.

The black-water regulating valve is very easy to be damaged due to the erosion of the key components, such as valve spool and valve seat. This work presents the failure analysis of the spool and seat of regulating valve in the black-water treatment system. Scanning electron microscopy and X-ray energy-dispersive spectrometer were used to detect the morphology and chemical compositions of failure valve samples. The computational fluid dynamics method was also adopted to simulate the medium flow characteristics in black-water regulating valve. The results show that most erosion areas of the valve occur at the spool-seat throttle zone. The erosion profile is mainly manifested in plastic deformation pits, cutting abrasions, furrows, pinhole pits and impact pits. The particles and cavitation bubbles move toward the throttle zone driven by black-water medium, causing particles impact and bubbles collapse. The particle flow velocity in the throttle zone of the valve is between 50 and 175 m/s, while the maximum velocity can reach 175 m/s. The valve suffered severe particle erosion and cavitation erosion under the particle impact and bubble collapse, finally resulting in its failure.

With the intensification of industrial and agricultural wastewater pollution, biotoxin heavy metals remain in the natural hydrosphere, posing a great threat to the ecological environment. In the ten methods for heavy metal removal in aqueous environments discussed in this paper, the adsorption method demonstrates greater flexibility and superior cost and environmental benefits. Phytate, with its abundant phosphate groups and good conductivity, is widely used in the modification process of various adsorbents. The report in this study shows that phytate-modified adsorbents generally improve the adsorption of heavy metals, such as the adsorption rate of cadmium and copper on nanofiltration membranes reaching nearly 100%, the adsorption capacity of magnetic particles increasing by 11.480 times, and even up to 17.233 times for biochar. In addition, a large number of adsorbents modified with phytate can maintain good adsorption performance after 2–5 cycles and are easy to regenerate. In this paper, we compare a wide range of remediation techniques for heavy metal pollution and the advantages and disadvantages of adsorbents, and analyze the structure and adsorption mechanism of phytate. The synthetic process and adsorption capability of the composite products regarding the application of phytate modification are highlighted. This paper focuses on several effective adsorbents for phytate modification, reflecting the benefits and potentials of phytate as a modifier, with the goal of enhancing the adsorption performance of raw materials and remediating heavy metal pollution in water environments.

It is hard for traditional current protection to solve problems of distribution networks with highly penetrative DGs. The fault information required by the most protection methods cannot be provided by the poor infrastructure of distribution networks. In this paper, a sufficient criterion based on the maximal current differences between adjacent transmission lines is proposed to promote selective configuration of protection scheme. The principle of the criterion and its advantages on current protection application are analyzed. The suppress influence of DG on the current of downstream transmission line current can be processed without high demand for communication in distribution network with DGs. Through the simulation in Matlab/Simulink, the effectiveness of the proposed criterion is validated.

Traditional self-assembly methods for photonic crystals (PCs) limited by poor mechanical performance and microstructure defects make it hard to be directly applied to optical devices, whose performance strongly rely on mechanical performance and microstructure of PCs. Here, a thermoforming-etching strategy combining both traditional processing and nanofabrication is reported to develop cross-linked polystyrene microsphere-based PC bulks with outstanding mechanical performance. It illustrates scientific principles, where surface molecular chains of PS microspheres were activated and entangled with each other under thermoforming conditions (200 °C; 220 MPa), resulting in applicable mechanical strength (hardness and modulus reach 0.12 and 4.12 GPa, respectively). The optimum optical reflectivity of the PS microsphere-based (180 nm) PC bulk is 49.4% at 381 nm. Furthermore, these PC bulks have been successfully written in anti-counterfeiting and realized colorful pattern printing. The innovative method opens a new route for the rapid and simple fabrication of the nanoparticle structure which can be used as various functional devices and directly promotes the industrialization of bulk PC devices, such as optical and display devices, and so forth.

Infrared light (IR) detection principles limited by poor photoresponsivity and sparse photogenerated carrier make them impossible to directly applied in flexible IR sensing field attributed to low π–π conjugation effect, thick P–N junction, and harsh band gap, of which IR self-powered electronic skin (e-skin) strongly relies on the essential property of exotic photosensitive-exciting materials, hardly any flexible organic polymer or nanocomposites. Here, an innovative IR self-powered principle is reported that outstanding piezoelectric effect of poly(vinylidene fluoride) nanofibers (PVDF NFs) is driven by microcrystals’ volume expansion caused by the solid–solid phase transition of PVDF/multiwalled carbon nanotubes (MWCNTs)/highly elastic phase change polymer (HEPCP) (PMH) nanocomposites due to MWCNT’s excellent IR photoabsorption and thermal conversion capabilities. A flexible IR-sensitive nanocomposite is successfully developed employing PVDF/HEPCP NFs as the framework of a three-dimensional network structure wrapped by the MWCNT/HEPCP nanocomposite. The 33, 50, and 60 wt % PMH nanocomposites are demonstrated cyclic, IR-regulated on/off piezoelectric sensitivity of 889.7, 977.6, and 493.8 mV/(mW·mm–2) at IR powers of 5.3 mW/mm2, respectively. Furthermore, IR self-powered e-skin has been developed successfully and realized an accurate IR stimulus-sensing location due to the sensitivity, which depends on the size of the sensing area. This innovative strategy provides a new route to the fundamental science and applications of flexible IR self-powered devices, such as e-skin, artificial vision, soft robots, active surveillance sensors, etc.

Flexible piezoelectric nanogenerators with high power output and superior mechanical stability that can respond to tiny human movements are essential for the development of portable power sources and smart sensors. Herein, a poly(vinylidene fluoride) (PVDF) nanofiber aerogel with a bionic cytoplasmic matrix structure and controllable super-elasticity is constructed by wet electrospinning for self-powered sensing. The PVDF-based aerogel exhibits remarkable elastic resilience with a high compressive stress of 2 MPa at 50% strain. The three-dimensional porous structure and high specific surface area endow the aerogel excellent electrical properties. The corresponding PVPU-NG device has an optimum output of 156 V and 34.9 μA with a power density of 5.5 W m−2, which can illuminate 50 light-emitting diodes. In addition, this PVPU-NG can respond to tiny human movements and convert mechanical energy into electrical energy to power miniature electronics. Specifically, the PVPU-NG can generate peak-to-peak voltages of approximately 1.8 V and 31 V during elbow bending and walking, respectively. As a result, the PVDF-based nanofiber aerogel, which exhibits high compressive strength and improved pressure sensitivity, demonstrates broad application prospects in wearable electronics and portable power sources.

The speed of one-time power flow calculation is hard to be further improved with satisfied accuracy and stability after decades of researches. However, the improvement on many-times calculation speed may be possible and is important for practical application. This paper proposes a novel method which can dramatically improve the many-times calculation speed of power flow without sacrifice of accuracy, convergence and stability in DC power systems. To achieve the purpose, this paper adopts a novel basic technique to separate the computation loads of grid topology analysis and bus types analysis from power flow equations. The technique is based on the analysis of linear relationships-based nonlinear problems and strict mathematical derivations. Combined with the basic technique, a correctness method is also proposed to deal with the specific nonlinear factors in power flow calculation. Thus, a complete novel power flow calculation method is proposed and the detailed mathematical derivation is presented. With the novel ant lion optimizer, the proper DC test systems are constructed. Compared with classical Newton–Raphson method, the proposed method is more stable and the initial values requirement is lower. At last, the numerical verification validates that the speed of the proposed method can be more than 10 times faster than Newton–Raphson method without the sacrifice of other performance.

Out-of-hospital cardiac arrest (OHCA) is a time-critical and fatal medical emergency that has been linked to non-optimal temperatures. However, the future burden of OHCA due to non-optimal temperatures, heatwaves, and cold spells under climate change has not been well evaluated.

The present research was conducted to investigate the effects of dietary supplementation of Lactobacillus plantarumand its fermentation products on growth performance, specific immune function, intestinal pH, and cecal microorganisms in yellow-feather broilers. A total of 1,200 yellow-feather broilers of similar weight and good health condition at 1 d of age were selected and randomly divided into 5 groups. The CK group was fed the basal diet, and the experimental group (I, II, III, IV) were supplemented with 0.1, 0.15% L. plantarumand 3, 4% L. plantarumfermentation products. The results showed that each treatment could improve the growth performance (P< 0.05) and feed conversion rate of yellow-feather broilers. Besides, the pH value of the gastrointestinal tract of yellow-feather broilers (P< 0.05) was significantly reduced through the use of L. plantarumand its fermentation products as additives, which also facilitated the animals to regulate the balance of cecal microorganisms. The immune function assay showed that the bursal index (P< 0.05), spleen index (P< 0.05), and the content of serum immunoglobulins IgA and IgG (P< 0.05) were significantly increased in yellow-finned broilers aged 1 to 21 d by supplementing the diet with L. plantarum. In conclusion, adding L. plantarumor its fermentation products to the diet can improve the growth performance of yellow-feather broilers, and the direct addition of L. plantarumis better than adding fermentation products.

ABSTRACTNK group 2, member D (NKG2D) is one of the most critical activating receptors expressed by natural killer (NK) cells. There is growing evidence that acute myeloid leukemia (AML) cells may evade NK cell-mediated cell lysis by expressing low or no ligands for NKG2D (NKG2D-Ls). We hypothesized that CCAAT/enhancer-binding protein α (C/EBPα), one of the most studied lineage-specific transcription factors in hematopoiesis, might influence the expression of NKG2D-Ls. To test this hypothesis, we first examined the endogenous expression of wild-type C/EBPα (C/EBPα-p42) in human AML cell lines and demonstrated that its expression level was highly relevant to the sensitivity of AML cells to NK cell cytotoxicity. Induction of C/EBPα-p42 in the low endogenous CEBPA-expressing AML cell line increased the sensitivity to NK-induced lysis. Moreover, decreased expression of C/EBPα-p42 by RNA interference in AML cells abrogated NK-mediated cytotoxicity. We further showed that the increase in NK susceptibility caused by C/EBPα-p42 occurred through up-regulation of the NKG2D-Ls ULBP2/5/6 in AML cells. More importantly, chromatin immunoprecipitation (ChIP) coupled with high-throughput sequencing captured C/EBPα motif signatures at the enhancer regions of the ULBP 2/5/6genes. Whilst, the AML-associated C/EBPα C-terminal mutant and N-terminal truncated mutant (C/EBPα-p30) diminished ULBP2/5/6transcription. Finally, we identified that histone demethylase lysine-specific demethylase 1 (LSD1) inhibition can restore the expression of ULBPs via induction of CEBPAexpression in AML cells, which may represent a novel therapeutic strategy for CEBPA-mutated AML.Abbreviations:C/EBPα: CCAAT/enhancer-binding protein α; TF: Transcription factor; AML: Acute myeloid leukemia; TAD: Transactivation domain; FS: Frameshift; NK: Natural killer; NKG2D: NK group 2, member D; NKG2D-Ls: Ligands for NKG2D; MHC: Major histocompatibility complex; MICA: MHC class I-related chain A; ULBP: UL16-binding protein; STAT3: Signal transducer and activator of transcription 3; LSD1: Lysine-specific demethylase 1; Ab: Antibody; PBMC: Peripheral blood mononuclear cell; PBS: Phosphate-buffered saline; CFSE: Carboxyfluorescein diacetate succinimidyl ester; PI: Propidium iodide; shRNA: Short hairpin RNA; ChIP: Chromatin immunoprecipitation; BM: Binding motif; HCNE: Highly conserved noncoding element; TSS: Transcription start site; HMA: Hypomethylating agent; AZA: Azacitidine/5-azacytidine; DAC: Decitabine/5-aza-29-deoxycytidine; 2-PCPA: Tranylcypromine; RBP: RNA-binding protein; MSI2: MUSASHI-2; HDACi: Inhibitor of histone deacetylases; VPA: Valproate; DNMTi: DNA methyl transferase inhibitor; SCLC: Small cell lung cancer