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Since determining the weight of pigs during large-scale breeding and production is challenging, using non-contact estimation methods is vital. This study proposed a novel pig weight prediction method based on a modified mask region-convolutional neural network (mask R-CNN). The modified approach used ResNeSt as the backbone feature extraction network to enhance the image feature extraction ability. The feature pyramid network (FPN) was added to the backbone feature extraction network for multi-scale feature fusion. The channel attention mechanism (CAM) and spatial attention mechanism (SAM) were introduced in the region proposal network (RPN) for the adaptive integration of local features and their global dependencies to capture global information, ultimately improving image segmentation accuracy. The modified network obtained a precision rate (P), recall rate (R), and mean average precision (MAP) of 90.33%, 89.85%, and 95.21%, respectively, effectively segmenting the pig regions in the images. Five image features, namely the back area, body length, body width, average depth, and eccentricity, were investigated. The pig depth images were used to build five regression algorithms (ordinary least squares (OLS), AdaBoost, CatBoost, XGBoost, and random forest (RF)) for weight value prediction. AdaBoost achieved the best prediction result with a coefficient of determination (R2) of 0.987, a mean absolute error (MAE) of 2.96 kg, a mean square error (MSE) of 12.87 kg2, and a mean absolute percentage error (MAPE) of 8.45%. The results demonstrated that the machine learning models effectively predicted the weight values of the pigs, providing technical support for intelligent pig farm management.

Abstract Background The incidence of hyperlipidemic acute pancreatitis (HLAP) has been increasing annually. However, population-based morbidity assessments need to be updated. Early, rapid, and effective lipid-lowering may minimize pancreatic injury and improve clinical prognosis. It is essential to choose the proper treatment. However, treatment options for HLAP are controversial, and there is no uniform treatment protocol. Methods In this retrospective study, 127 patients with hyperlipidemic severe acute pancreatitis (HL-SAP) were registered from January 2018 to December 2022 at the General Hospital of Ningxia Medical University. Medical and radiological records of hospitalized patients were collected to determine clinical features, severity, complications, mortality, recurrence rate, and treatment. Risk factors for HL-SAP were analyzed using multifactorial logistic regression. A propensity score matching method was used to compare the clinical outcomes of standard and plasma exchange therapies. Results In this research, the prevalence of HLAP increased about 1.6 times, and the prevalence of HL-SAP was 50.60%. HL-SAP occurs most often in people between the ages of 30 and 39. Amylase exceeded 110 U/L in 84.3% of patients and 330 U/L in only 47.2%. 83.5% of HL-SAP patients had fatty livers and high body mass index (BMI). A total of 48.0% of patients experienced organ failure, ICU treatment (55.1%), recurrence (33.1%), and death (21.3%). Between the hyperlipidemic group and the biliary group in terms of age, gender, BMI, fatty liver, pleural effusion, abdominal constriction syndrome (ACS), multiple organ dysfunction syndrome (MODS), length of hospital, medical costs, morbidity and mortality, triglyceride, cholesterol, creatinine, blood glucose, D-dimer, amylase, albumin, lactate dehydrogenase, serum phosphorus, serum calcium, oxygenation index, and recurrence rate were statistically significant (P

Polycystic ovary syndrome (PCOS) is the most common and multifactorial endocrine disease among women of reproductive age. Aberrant folliculogenesis is a common pathological characteristic of PCOS, but the underlying molecular mechanism remains unclear. Emerging evidence indicated that aberrant expression of long noncoding RNAs (lncRNAs) may contribute to the pathogenesis of PCOS. In this study, we found that lncRNA PKD1P6 expression was remarkably down-regulated in ovarian granulosa cells (GCs) of hyperandrogenic PCOS (HA-PCOS) patients and negatively correlated with serum testosterone (T) levels. We further showed that overexpression of PKD1P6 markedly reduced cell viability, attenuated DNA synthesis capacity, arrested the cell cycle at G0/G1 phase and promoted apoptosis of KGN cells. Exosomes derived from PKD1P6 overexpression cells exerted similar effects to PKD1P6 overexpression on the function of KGN cells. Mechanistically, PKD1P6 could act as a competing endogenous RNA (ceRNA) by directly binding with miR-135b-5p. Overexpression of PKD1P6 significantly suppressed ERK1/2 activation, whereas up-regulation of miR-135b-5p exerted an opposing effect. Additionally, excessive androgen was showed to diminish PKD1P6 expression while promote miR-135b-5p expression of PCOS models in vitro and vivo. Collectively, our findings delineate the clinical significance of PKD1P6 in HA-PCOS and the new regulatory mechanisms involved in abnormal folliculogenesis, providing a promising therapeutic target for HA-PCOS.

As a new type of semiconductor laser, photonic crystal surface-emitting lasers (PCSELs) feature large-area single-mode surface emission with high power and high beam quality. The unique features of single-mode lasing over a large area active region are implemented by the in-plane optical feedback from two-dimensional (2D) photonic crystal cavities. In larger PCSEL cavities, the lasing gain threshold becomes similar for the fundamental and high-order modes, which degrades single-mode operation. Here, we investigate the impact of carrier injection on PCSEL modes by controlling the injection area and the gain mode interaction. Optical and electrical simulations are carried out to calculate the gain mode overlapping factor for different p electrode designs. We fabricated 250 × 250 µm2 photonic crystal cavities with different p electrode sizes for injection area control. The PCSEL device characterization results show that devices with an electrode size to cavity side length ratio of 0.6 have the maximum slope efficiency and a lower lasing threshold with a single lobe beam profile. Such selective carrier injection can also provide gain-guided resonance in the PCSEL cavities and enhance optical gain in the fundamental mode while suppressing gain in the high-order modes.

Automatic seizure detection plays a crucial role in epilepsy diagnosis and treatment. Traditional machine learning based automatic seizure detection requires additional feature engineering and finding the optimal hand-crafted features is a challenging issue. Therefore, a novel end-to-end deep learning model that combines attention mechanism, temporal convolutional network(TCN), and bidirectional gated recurrent unit (BiGRU) is proposed for seizure detection in this work. Our model only requires filtering of the raw electroencephalogram(EEG) signals to remove artifacts, without the need for time-consuming feature extraction. Post-processing procedures including moving-average filtering, thresholding, and the collar technique are then applied to enhance the model’s performance. Experiments were conducted on the CHB-MIT dataset and the SH-SDU dataset. In patient-specific experiments, our model achieved average accuracies of 98.77% on the CHB-MIT dataset and 93.61% on the SH-SDU dataset. In cross-patient experiments, average accuracies of 93.78% and 91.37% were obtained, respectively. The total time required for the model to process 1-hour EEG signals is only 5.33s. These outstanding results indicate that our model achieves high accuracy and real-time performance in seizure detection tasks and could provide reference for clinical seizure diagnosis.

Abstract Adenosine N1 methylation (m1A) of RNA, a type of post-transcriptional modification, has been shown to play a significant role in the progression of cancer. The objective of the current research was to analyze the genetic alteration and prognostic significance of m1A regulators in kidney renal clear cell carcinoma (KIRC). Genomic and clinicopathological characteristics were obtained from 558 KIRC patients in the Cancer Genome Atlas (TCGA) and Gene Omnibus Expression (GEO) databases. Alterations in the gene expression of ten m1A-regulators were analyzed and survival analysis was performed using the Cox regression method. We also identified three clusters of patients based on their distinct m1A alteration patterns, using integrated analysis of the ten m1A-related regulators, which were significantly related to overall survival (OS), disease-free survival (DFS) and tumor microenvironment (TME) immune cell infiltration cells in KIRC. Our findings showed that m1A alteration patterns have critical roles in determining TME complexity and its immune cell composition. Furthermore, different m1A expression patterns were significantly associated with DFS and OS rates in KIRC patients. In conclusion, the identified m1A RNA modification patterns offer a potentially effective way to classify KIRC patients based on their TME immune cell infiltration, enabling the development of more personalized and successful treatment strategies for these patients.

Abstract Background This study aimed to compare the clinical outcomes of non-transecting urethroplasty and lingual mucosal urethroplasty in the treatment of iatrogenic bulbar urethral stricture. Results A total of 25 patients with iatrogenic bulbar urethral stricture were enrolled, 12 of whom underwent lingual mucosal urethroplasty, 13 patients who underwent non-transecting urethroplasty. All patients were followed-up and evaluated at 3 postoperative months. Evaluations included urethrography, maximum urine flow rate (Qmax), nocturnal erectile function testing, International Index of Erectile Function (IIEF-5) assessment, and Anxiety Related Scale (SAS) assessment. In terms of operation time, there was a significant difference between non-transecting urethroplasty and lingual mucosal urethroplasty. However, there was no significant intergroup difference in intraoperative blood loss. Both techniques were associated with significantly improved Qmax relative to preoperative rates, but there was no significant difference between the groups in this regard over 3 months of postoperative follow-up. Nocturnal penile tumescence and rigidity results showed that there was no significant change in tip hardness after surgery in the non-transecting urethroplasty group. Moreover, IIEF-5 scores indicated that there was no significant intergroup difference in terms of subjective postoperative erectile function. According to the preliminary psychological evaluations during postoperative follow-up, the anxiety scores of patients undergoing non-transecting urethroplasty significantly improved, but there was no significant change in the mean SAS score among patients who underwent lingual mucosal urethroplasty. Conclusion Both surgical methods can achieve the clinical goal of treating iatrogenic bulbar urethral stricture. Non-transecting urethroplasty has the characteristics of short operation time, relative technical simplicity, and retention of the original erectile function of most patients, and the surgical outcomes of non-transecting urethroplasty are not inferior to those of lingual mucosal urethroplasty, and it is a promising technique for widespread use to treat bulbar urethral strictures.

In this study, a phenol–formaldehyde resin–montmorillonite intercalation composite solution was used as a modifier to treat Chinese fir via impregnation and compression. The basic characteristics and wettability of the PF (phenol–formaldehyde)–montmorillonite impregnation solution were analyzed. The effects of the solid content of PF, the quantity of montmorillonite, and the impregnation time on the impregnation weight gain of Chinese fir were studied through orthogonal experiments. The results showed that when the amount of montmorillonite was 1%, the wettability of the PF–montmorillonite impregnation solution performed the best, the curing time was short, and the curing strength was high. The optimal impregnation process consists of a PF solid content of 25%, an impregnation time of 120 min, and a montmorillonite ratio of 1%. Under these conditions, the modified Chinese fir was prepared via hot pressing. The effects of the addition of montmorillonite and different levels of compressibility on the physical and mechanical properties of modified wood were studied. The physical and mechanical properties were found to be better when the compression ratio was 33%: the density increased from 0.33 g/cm3 to 0.58 g/cm3; the surface hardness increased from 33.6 HD to 70.9 HD; the static bending strength increased from 60.4 MPa to 98.7 MPa; and the elastic modulus increased from 6 390 MPa to 11 498 MPa. After 30 days of release, the compression rebound rate was 3.97%. Meanwhile, the micromorphology and heat resistance of the impregnated compressed Chinese fir showed that the PF–montmorillonite impregnation solution entered into the cell cavity and intercellular space of the Chinese fir and formed a good composite, thus improving the water resistance, heat resistance, and physical and mechanical properties.

In this study, layered double hydroxide (LDH) and molybdenum disulfide (MoS2) were used as additives to prepare lubricants. The morphology and particle distribution of the LDH and MoS2 were characterized using a scanning electron microscope and a laser particle size analyzer, respectively. Thermogravimetric analysis was used to compare the performance of the lubricants at high temperature. The extreme pressure and wear resistance performance of the lubricants were tested using a four-ball machine and a fretting-wear machine. Then, the lubricants were applied in a bolt fastener. The loosening torque and surface wear condition at high temperature were compared. By adding LDH and MoS2 to the lubricants, the extreme pressure and wear resistance performance and anti-seize performance at high temperature were improved significantly. The LDH showed better anti-seize performance than the MoS2 because of its strong and stable structure at high temperature. The MoS2 showed better anti-wear performance under a high load because of its soft layered structure. The MoS2 with a larger particle size showed better extreme pressure performance under a high load. The LDH and MoS2 played a synergistic effect under the conditions of high temperature and high load.

Solid-state lithium batteries are promising candidates for improving battery safety and boosting energy density. However, the application of both typical solid-state electrolytes, inorganic ceramic/glass and organic polymer electrolytes, are facing their respective inherent challenges, including large interfacial resistance and unwanted interfacial reactions of inorganic electrolytes, and narrow electrochemical stability windows of polymer electrolytes. The design of multi-layer solid-state electrolytes, such as inorganic/inorganic, inorganic/polymer and polymer/polymer structures, provides a viable solution to these issues by effectively improving the interfacial stability and widening the electrochemical window, which exhibits unparallel advantages in solid-state batteries with the help of non-diffusible characteristic of solid-state electrolytes. Given the extensive research and progress reported, this paper reviews the latest advancements in multi-layer solid-state electrolytes and categorizes them into inorganic-based, polymer-based and composite-based systems. Each is discussed separately, focusing on their design rationales, functional mechanisms, electrochemical performances, and residual challenges. In addition, to meet the requirements of practical applications, the potential strategies for further development of multi-layer solid-state electrolytes are also briefly presented.

Abstract Background Spinal infection caused by Coxiella burnetii is rare and difficult to diagnose. Here we reported a case of spinal infection from Coxiella burnetii detected by the metagenomic next-generation sequencing (mNGS). Case presentation A 66-year-old male farmer with no medical history reported severe sharp low back pain, numbness and lower limb weakness for three years. Magnetic resonance imaging (MRI) revealed bone destruction and spinal cord compression within L1 and L2. mNGS testing showed that the inspected specimen collected from spinal lesion was detected positively for Coxiella burnetii. After receiving the combined treatment of antibiotic therapy and surgical intervention, the patient recovered well, and the sagittal MRI showed that vertebral edema signals disappeared and the graft of bone fused 16 months after surgery. Conclusion The mNGS may be benefit for early diagnosis and intervention of non-specific spinal infection, and future studies should validate its effectiveness for clinical use in spinal infections. Additionally, antibiotic therapy combined with surgical intervention plays an important role on the treatment of spinal infection caused by Coxiella burnetii.

Particle Impact Drilling (PID) is a new technology to effectively improve the rate of penetration (ROP) for oil and gas drilling in hard and strongly abrasive formations. In this paper, numerical simulation method is used to analyse the motion characteristics and the modulation method of particle swarm in high-pressure tank for the particle injection system based on differential pressure ejection in PID. The numerical simulation results show that: when there is no modulation elements, the motion of particle swarm in the high-pressure tank follows an asymmetric funnel flow with pulsating state, which could be divided into vertical flow domain, fast flow domain, slow flow domain and stagnation domain. The unstable dynamic arching effect of the funnel flow, the viscous effect of the liquid bridge force and the collapsing effect of the particle swarm could probably lead to the blockage of the discharge port of the high-pressure tank. When the semiapex angles of the high-pressure tank decreases, the volume flow rate of particles increases and the stagnation domain becomes smaller, but it becomes easier to form arching and blockage. The modelling results indicate that the pulsation of the funnel flow is minimum when the semiapex angle is 45° without the mutilation element, which means the funnel flow of the particle swarm is relatively stable. By introducing a conical modulating element above the discharge port, the unstable funnel flow of the particle swarm could be transformed to an overall uniform flow. The modelling results indicate that the installation height of the modulation element has the greatest influence on the pulsation degree. The optimized parameters for the conical modulation element based on numerical modelling tests are 70° for the vertex angle, 35 mm for the length of the flank and 70 mm for the installation heigh.

Silicon carbide particle-reinforced aluminum matrix composites (SiCp/Al) find diverse applications in engineering. Nevertheless, SiCp/Al exhibit limited machinability due to their special structure. A pulsed laser ultrasonic vibration assisted cutting (PLUVAC) method was proposed to enhance the machining characteristics of SiCp/Al and decrease surface defects. The finite element model was constructed, considering both the thermal effect of the pulsed laser and the location distribution of SiC particles. The model has been developed to analyze the damage forms of SiC particles and the formation mechanisms for the surface morphology. The influence of pulsed laser power on average cutting forces has also been analyzed. Research results indicate that PLUVAC accelerates the transition from the brittleness to the plastic of SiC particles, which helps to reduce surface scratching caused by fragmented SiC particles. Furthermore, the enhancement of surface quality is attributed to the decrease in surface cracks and the beneficial coating effect of the Al matrix. The accuracy of the simulation is verified by experiments, and the feasibility of PLUVAC method to enhance the surface quality of SiCp/Al is confirmed.

Adaptive sampling of the marine environment may improve the accuracy of marine numerical prediction models. This study considered adaptive sampling path optimization for a three-dimensional (3D) marine observation platform, leading to a path-planning strategy based on evolutionary deep reinforcement learning. The low sampling efficiency of the reinforcement learning algorithm is improved by evolutionary learning. The combination of these two components as a new algorithm has become a current research trend. We first combined the evolutionary algorithm with different reinforcement learning algorithms to verify the effectiveness of the combination of algorithms with different strategies. Experimental results indicate that the fusion of the two algorithms based on a maximum-entropy strategy is more effective for adaptive sampling using a 3D marine observation platform. Data assimilation experiments indicate that adaptive sampling data from a 3D mobile observation platform based on evolutionary deep reinforcement learning improves the accuracy of marine environment numerical prediction systems.

Epilepsy is a chronic neurological disease associated with abnormal neuronal activity in the brain. Seizure detection algorithms are essential in reducing the workload of medical staff reviewing electroencephalogram (EEG) records. In this work, we propose a novel automatic epileptic EEG detection method based on Stockwell transform and Transformer. First, the S-transform is applied to the original EEG segments, acquiring accurate time-frequency representations. Subsequently, the obtained time-frequency matrices are grouped into different EEG rhythm blocks and compressed as vectors in these EEG sub-bands. After that, these feature vectors are fed into the Transformer network for feature selection and classification. Moreover, a series of post-processing methods were introduced to enhance the efficiency of the system. When evaluating the public CHB-MIT database, the proposed algorithm achieved an accuracy of 96.15%, a sensitivity of 96.11%, a specificity of 96.38%, a precision of 96.33%, and an area under the curve (AUC) of 0.98 in segment-based experiments, along with a sensitivity of 96.57%, a false detection rate of 0.38/h, and a delay of 20.62 s in event-based experiments. These outstanding results demonstrate the feasibility of implementing this seizure detection method in future clinical applications.

Based on the hourly observation data of 79 automatic weather stations in Shanghai from 2010 to 2020 and the rainstorm warning signal data issued by the Shanghai Meteorological Center and District Meteorological Centers from 2016 to 2020, the spatial and temporal distribution characteristics of the rainstorm in Shanghai are analyzed using statistical metrics such as trend analysis and cumulative frequency. On the basis of statistical analysis of the frequency and timeliness of rainstorm warning signals at different levels, the difference of the timeliness of rainstorm warning signals under different synoptic conditions was studied. The results show that the rainstorm meeting the 6-h rainfall standard presents a significantly increasing trend, particularly for the rainstorm with the "Blue " warning. The rainstorm meeting the 6-h rainfall standard is the minimum in July, while the rainstorm meeting the 1-h rainfall standard is mroe in July than in June, which indicates that the frequency of short-time rainstorm in Shanghai is higher in July due to the control of subtropical high. The rainstorm in Shanghai usually lasts relatively short in the afternoon, while the longer rainstorm usually occurs in the morning. The frequency of heavy rainstorm is the highest in the urban area and Pudong near the Huangpu River, which may be related to the urban heat island effect. The release time of early warning signal in Shanghai presents a feature of bimodal distribution. The first peak appears at 12:00, and the release of early warning signals from 12:00 to 17:00 is relatively concentrated. The second peak appears at 6:00 in the morning.The average duration of early warning signals of all levels is 5.9 hours. The average hit rate of rainstorm early warning in Shanghai is 82.4%, and the average rainstorm warning time is 1.3 hours. The severe convective rainstorm at the edge of the subtropical high has the shortest warning timeliness, and the rainstorm near the typhoon body or the peripheral spiral rain belt is easy to be missed, which requires special attention in future.

Abstract High nickel content layered cathodes, represented by NCM (LiNixCoyMnzO2, x + y + z = 1), are now widely employed in the market of electric vehicles, owing to their high energy density. With the gradual increase of nickel content and capacity, the issues on cycling life and safety become more serious. In this review, various strategies for improving the performance of high nickel NCM are summarized on the aspects of surface coating, ionic doping, and single‐crystal NCM. The coating strategy was separately described according to the physical property of coating species, including inert material coating, Li+‐conductor coating, electronic conductor coating, and mixed conductor coating. These coating species help to suppress the interfacial oxidation of electrolytes by NCM, improving the cycling life and safety. The elemental doping in the crystal lattice of NCM is then presented in the aspects of cation, anion, and mixed‐ion doping, which are beneficial to stabilize the layered structure during charge–discharge and so promote the electrochemical performance. In quite recent years, the strategy of single‐crystal NCM was demonstrated to be a promising pathway, owing to the dramatically reduced surface area and grain boundary. Finally, the remaining unsolved challenges and future strategies for further development of NCM cathode materials are outlined.

The corpus cavernosum is the most important structure for penile erection, and its dysfunction causes physiological and psychological problems. Here the authors perform single-cell RNA-sequencing on corpus cavernosum samples from males with normal erection and erectile dysfunction patients, providing insights into this pathology.

Motor imagery brain-computer interface (MI-BCI) is a promising tool for neuro-rehabilitation. The real-time MI-BCI enables people with motor dysfunction disease to interact with the outside world. This work develops a Matlab-based real-time MI-BCI (MartMi-BCI) software, which involves two main modules, a real-time EEG analysis platform (RTEEGAP) and a model training platform (MTP). The RTEEGAP can realize real-time EEG analysis in time, frequency, and spatial domains and perform MI experiments with real-time feedback based on the OpenBCI device. Simultaneously, the MTP can train the CSP-based MI classification model and visualize the time–frequency reaction map. We hope the MartMi-BCI software can promote the development of EEG-based MI paradigm design and EEG classification algorithms.

Abstract Na+ superionic conductor (NASICON)‐structured Na4VMn(PO4)3 (NVMP) possesses stable cycling performance at 2.5–3.8 V by replacing V with lower cost Mn but suffers rapid capacity decay when further widening the voltage to 2.5–4.2 V, owing to a less stable V4+/V5+ redox couple. Herein, to stabilize the V4+/V5+ couple and improve the reversibility, a series of carbon‐coated NVMP (NVMP@C) with different V/Mn ratios are compared, among which, Na3.25V1.75Mn0.25(PO4)3@C delivers an additional reversible V4+/V5+ capacity of 7 mAh g−1 at the voltage of 3.9–4.2 V. Based on this, to further activate the capacity of V4+/V5+, Al‐doped Na3.25V1.75−yMn0.25Aly(PO4)3 structures are synthesized. When 0.5 Al is doped, 15 mAh g−1 capacity corresponding to V4+/V5+ can be released. In addition, it is found that the activation of V4+/V5+ is not conducive to electrochemical reversibility and C‐rate performance, owing to the shrinkage of the whole framework structure with the oxidization of V4+ to V5+.

Dark-field microscopy offers several advantages, including high image contrast, minimal cell damage, and the absence of photobleaching of nanoprobes, which make it highly advantageous for cell imaging. The NIR-II window has emerged as a prominent research focus in optical imaging in recent years, with its low autofluorescence background in biological samples and high imaging SBR. In this study, we initially compared dark-field imaging results of colorectal cancer cells in both visible and NIR-II wavelengths, confirming the superior performance of NIR-II imaging. Subsequently, we synthesized gold nanorods with localized surface plasmon resonance (LSPR) absorption peaks in the NIR-II window. After bio-compatible modification, we non-specifically labeled colorectal cancer cells for NIR-II dark-field scattering imaging. The imaging results revealed a sixfold increase in SBR, especially in the 1425–1475 nm wavelength range. Finally, we applied this imaging system to perform dark-field imaging of cell nuclei in the NIR-II region and used GNRs for specific nuclear labeling in colorectal cancer cells. The resulting images exhibited higher SBR than non-specifically-labeled cell imaging, and the probe’s labeling was precise, confirming the potential application of this system in photothermal therapy and drug delivery for cancer cells.

Visual inspection of long-term electroencephalography (EEG) is a tedious task for physicians in neurology. Based on bidirectional gated recurrent unit (Bi-GRU) neural network, an automatic seizure detection method is proposed in this paper to facilitate the diagnosis and treatment of epilepsy. Firstly, wavelet transforms are applied to EEG recordings for filtering pre-processing. Then the relative energies of signals in several particular frequency bands are calculated and inputted into Bi-GRU network. Afterwards, the outputs of Bi-GRU network are further processed by moving average filtering, threshold comparison and seizure merging to generate the discriminant results that the tested EEG belong to seizure or not. Evaluated on CHB-MIT scalp EEG database, the proposed seizure detection method obtained an average sensitivity of 93.89% and an average specificity of 98.49%. 124 out of 128 seizures were correctly detected and the achieved average false detection rate was 0.31 per hour on 867.14 h testing data. The results show the superiority of Bi-GRU network in seizure detection and the proposed detection method has a promising potential in the monitoring of long-term EEG.

Automatic seizure detection system can serve as a meaningful clinical tool for the treatment and analysis of epilepsy using electroencephalogram (EEG) and has obtained rapid development. An automatic detection of epileptic seizure method based on kernel-based robust probabilistic collaborative representation (ProCRC) combined with graph-regularized non-negative matrix factorization (GNMF) is proposed in this work. The raw EEG signals are pre-processed through the wavelet transform to obtain time-frequency distribution of EEG signals as preliminary feature information and GNMF is further employed for dimension reduction, retaining and enhancing the productive feature information of EEG signals. Then, the test sample is represented using robust ProCRC that can decide whether the testing sample belongs to each class (seizure or non-seizure) by jointly maximizing the likelihood. In addition, the kernel trick is applied to improve the separability of non-linear high dimensional EEG signals in robust ProCRC. Finally, post-processing techniques are introduced to generate more accurate and reliable results. The average epoch-based sensitivity of 96.48%, event-based sensitivity of 93.65% and specificity of 98.55% are acquired in this method, which is evaluated on the public Freiburg EEG database.

Due to the material properties of single-crystal silicon, it is difficult to achieve high-efficiency processing in conventional turning. Fast tool servo (FTS) turning has emerged as a favorable technology for processing brittle materials. This paper investigates the tool radius, feed speed, and cutting depth effects on the maximum undeformed chip thickness (MUCT). A high-frequency low-coupling FTS system is designed for processing experiments. Effects of the tool rake angle, tool radius, cutting speed, and vibration frequency on the critical undeformed chip thickness (CUCT) are explored in this paper. Experimental results indicate FTS technology can increase the CUCT from 80 nm to 580 nm. Surface and subsurface morphology tests of conventional and FTS single-crystal silicon cutting verify that FTS technology can obtain an optical surface roughness of 5 nm and lower subsurface damage. Moreover, FTS turning can reduce tool wear. Lastly, through Raman spectroscopy analysis, the amorphous phase remaining on the machined surface is lower when FTS turning is employed.

Abstract Background Although multiple studies have demonstrated a role for exosomes during virus infections, our understanding of the mechanisms by which exosome exchange regulates immune response during viral infections and affects viral pathogenesis is still in its infancy. In particular, very little is known for cytoplasmic single-stranded RNA viruses such as SARS-CoV-2 and Rift Valley fever virus (RVFV). We have used RVFV infection as a model for cytoplasmic single-stranded RNA viruses to address this gap in knowledge. RVFV is a highly pathogenic agent that causes RVF, a zoonotic disease for which no effective therapeutic or approved human vaccine exist. Results We show here that exosomes released from cells infected with RVFV (designated as EXi-RVFV) serve a protective role for the host and provide a mechanistic model for these effects. Our results show that treatment of both naïve immune cells (U937 monocytes) and naïve non-immune cells (HSAECs) with EXi-RVFV induces a strong RIG-I dependent activation of IFN-B. We also demonstrate that this strong anti-viral response leads to activation of autophagy in treated cells and correlates with resistance to subsequent viral infection. Since we have shown that viral RNA genome is associated with EXi-RVFV, RIG-I activation might be mediated by the presence of packaged viral RNA sequences. Conclusions Using RVFV infection as a model for cytoplasmic single-stranded RNA viruses, our results show a novel mechanism of host protection by exosomes released from infected cells (EXi) whereby the EXi activate RIG-I to induce IFN-dependent activation of autophagy in naïve recipient cells including monocytes. Because monocytes serve as reservoirs for RVFV replication, this EXi-RVFV-induced activation of autophagy in monocytes may work to slow down or halt viral dissemination in the infected organism. These findings offer novel mechanistic insights that may aid in future development of effective vaccines or therapeutics, and that may be applicable for a better molecular understanding of how exosome release regulates innate immune response to other cytoplasmic single-stranded RNA viruses.

A suitable jump Markov system (JMS) filtering approach provides an efficient technique for tracking surface targets. In complex surface target tracking situations, due to the joint influences of lost measurements with an unknown probability and heavy-tailed measurement noise (HTMN), the estimation accuracy of conventional interacting multiple model (IMM) methods may be seriously degraded. Aiming to address the filtering issues in JMSs with HTMNs and random measurement losses, this paper presents an IMM filtering approach with the adaptive estimation of unknown measurement loss probability. In this study, we assumed that the measurement noises obey student’s t-distributions and then proposed Bernoulli random variables (BRVs) to characterize the random measurement loss. Notably, by converting the two likelihood functions from the weighted sum form to exponential multiplication, we established hierarchical Gaussian state space models to directly utilize the variational inference method. The system state vectors, unknown distribution parameters, BRVs, and unknown measurement loss probabilities were estimated simultaneously according to the variational Bayesian inference in the IMM framework. The results of maneuvering target tracking simulations verified that the presented filtering approach demonstrated superior estimation accuracy compared to existing IMM filters.

In this work, MgAl-layered double hydroxides (LDH) were synthesized by co-precipitation method using a colloid mill and characterized by XRD and SEM. It was found that the environmentally friendly LDHs had greater performance than the traditional antioxidant. By adding LDHs into large electric shovel grease (GRK-A) in open-pit coal mine, the service lifetime of grease was extended by 20%. With the increase in LDH addition, the grease sample attains greater activation energy, and the thermal oxidation and decomposition resistance become stronger. Comparing the energy storage modulus and flow transition index at different temperatures, adding the right amount of LDHs needs close attention for the system oxidation resistance and viscoelasticity. For the electric shovel grease, the best oxidation resistance and rheological properties can be achieved by adding 2% of LDHs. The rheological viscosity–temperature curves show that the grease samples with different ratios of solid LDHs have better low-temperature properties than the mine grease. This work outlines a simple method for creating an environmentally sustainable lubricant additive with the use of LDH. LDH serves as a novel inorganic antioxidant additive that is optimal for open gear lubrication and sliding friction.

Traditional methods for detecting foodstuff hazards are time-consuming, inefficient, and destructive. Spectral imaging techniques have been proven to overcome these disadvantages in detecting foodstuff hazards. Compared with traditional methods, spectral imaging could also increase the throughput and frequency of detection. This study reviewed the techniques used to detect biological, chemical, and physical hazards in foodstuffs including ultraviolet, visible and near-infrared (UV-Vis-NIR) spectroscopy, terahertz (THz) spectroscopy, hyperspectral imaging, and Raman spectroscopy. The advantages and disadvantages of these techniques were discussed and compared. The latest studies regarding machine learning algorithms for detecting foodstuff hazards were also summarized. It can be found that spectral imaging techniques are useful in the detection of foodstuff hazards. Thus, this review provides updated information regarding the spectral imaging techniques that can be used by food industries and as a foundation for further studies.

Abstract Background Many pathogens, including Yersinia pestis, cannot be consistently and reliably cultured from blood. New approaches are needed to facilitate the detection of proteins, nucleic acid and microorganisms in whole blood samples to improve downstream assay performance. Detection of biomarkers in whole blood is difficult due to the presence of host proteins that obscure standard detection mechanisms. Nanotrap® particles are micron-sized hydrogel structures containing a dye molecule as the affinity bait and used to detect host biomarkers, viral nucleic acids and proteins as well as some bacterial markers. Nanotraps have been shown to bind and enrich a wide variety of biomarkers and viruses in clinically relevant matrices such as urine and plasma. Our objective was to characterize the binding ability of Nanotrap particle type CN3080 to Y. pestis bacteria, bacterial proteins and nucleic acids from whole human blood in order to potentially improve detection and diagnosis. Results CN3080 Nanotraps bind tightly to Yersinia bacteria, even after washing, and we were able to visualize the co-localized Nanotraps and bacteria by electron microscopy. These magnetic hydrogel Nanotraps were able to bind Yersinia DNA, supporting the utility of Nanotraps for enhancing nucleic acid-based detection methods. Nanotraps were capable of increasing Y. pestis nucleic acid yield by fourfold from whole human blood compared to standard nucleic acid extraction. Interestingly, we found CN3080 Nanotraps to have a high affinity for multiple components of the Yersinia type III secretion system (T3SS), including chaperone proteins, Yop effector proteins and virulence factor protein LcrV (V). Using Nanotraps as a rapid upstream sample-prep tool, we were able to detect LcrV in human blood by western blotting with minimal blood interference in contrast to direct western blotting of blood samples in which LcrV was obscured. We were able to computationally model the interaction of LcrV with the CN3080 Nanotrap dye and found that it had a low delta-G, suggesting high affinity. Importantly, Nanotraps were also able to enhance detection of secreted Yersinia proteins by mass spectrometry. Conclusion Upstream use of magnetic CN3080 Nanotrap particles may improve the downstream workflow though binding and enrichment of biomarkers and speed of processing. Utilization of Nanotrap particles can improve detection of Yersinia pestis proteins and nucleic acid from whole human blood and contribute to downstream assays and diagnostics including molecular methods such as sequencing and PCR and protein-based methods. Graphic Abstract

ObjectivesTo investigate the pharmacokinetics (PK) and pharmacodynamics (PD) of Y-shape branched PEGylated recombinant human growth hormone (YPEG-rhGH) and evaluate its short-term efficacy and safety in children with growth hormone deficiency (GHD).MethodsA total of 43 children with GHD from 12 sites in China were enrolled in this randomized, multicenter, active-controlled, double-blind (YPEG-rhGH doses) trial. Patients were randomized 1:1:1:1 to 100, 120, and 140 μg/kg/week of YPEG-rhGH groups and daily rhGH 35 μg/kg/day groups. The treatment lasted 12 weeks. The primary outcome was the area under the curve of the change of insulin-like growth factor-1 (IGF-1). The secondary outcome was the height velocity (HV) increment at week 12.ResultsA dose-dependent response of maximum plasma concentration (Cmax) and area under the concentration-time curves from 0 to 168 hours (AUC0-168h) were observed for YPEG-rhGH. The ratio of Cmax and the ratio of AUC0-168h from the first to the last dosing were 1.09~1.11 and 1.22~1.26 respectively. A YPEG-rhGH dose-dependent increase in area under effect curve (AUEC) of IGF-1 fold change was observed. Model-derived mean IGF-1 SDS was in the normal range for all three YPEG-rhGH doses. At week 12, HV was 7.07, 10.39, 12.27 cm/year, and 11.58 cm/year for YPEG-rhGH 100, 120, and 140 μg/kg/week and daily rhGH respectively. Adherence and safety were consistent with the profile of daily rhGH. No related serious adverse events were reported.ConclusionThe PK/PD suggests that YPEG-rhGH is suitable for the once-weekly treatment of pediatric GHD. YPEG-rhGH 120 ~ 140 μg/kg/week provides the closest HV increment with similar safety and tolerability compared to daily rhGH 35 μg/kg/day in children with GHD.Clinical Trial RegistrationClinicalTrials.gov, identifier [NCT04513171].

Abstract We characterized the in vivo interstitial fluid (IF) content of extracellular vesicles (EVs) using the GFP‐4T1 syngeneic murine cancer model to study EVs in‐transit to the draining lymph node. GFP labelling confirmed the IF EV tumour cell origin. Molecular analysis revealed an abundance of IF EV‐associated proteins specifically involved in mitophagy and secretory autophagy. A set of proteins required for sequential steps of fission‐induced mitophagy preferentially populated the CD81+/PD‐L1+ IF EVs; PINK1, TOM20, and ARIH1 E3 ubiquitin ligase (required for Parkin‐independent mitophagy), DRP1 and FIS1 (mitochondrial peripheral fission), VDAC‐1 (ubiquitination state triggers mitophagy away from apoptosis), VPS35, SEC22b, and Rab33b (vacuolar sorting). Comparing in vivo IF EVs to in vitro EVs revealed 40% concordance, with an elevation of mitophagy proteins in the CD81+ EVs for both murine and human cell lines subjected to metabolic stress. The export of cellular mitochondria proteins to CD81+ EVs was confirmed by density gradient isolation from the bulk EV isolate followed by anti‐CD81 immunoprecipitation, molecular sieve chromatography, and MitoTracker export into CD81+ EVs. We propose the 4T1 in vivo model as a versatile tool to functionally characterize IF EVs. IF EV export of fission mitophagy proteins has broad implications for mitochondrial function and cellular immunology.

A proper filtering method for jump Markov system (JMS) is an effective approach for tracking a maneuvering target. Since the coexisting of heavy-tailed measurement noises (HTMNs) and one-step random measurement delay (OSRMD) in the complex scenarios of the surface maneuvering target tracking, the effectiveness of typical interacting multiple model (IMM) techniques may decline severely. To solve the state estimation problem in JMSs with HTMN and OSRMD simultaneously, this article designs a novel robust IMM filter utilizing the variational Bayesian (VB) inference framework. This algorithm models the HTMNs as student’s t-distribuitons, and presents a random Bernoulli variable to describe the OSRMD in JMSs. By transforming measurement likelihood function form from weighted summation to exponential product, this paper constructs hierarchical Gaussian state space models. Then, the state vectors, random Bernoulli vairable, and model probability are inferred jointly according to VB inference. The surface maneuvering target tracking simulation example result indicates that the presented IMM filter achieves superior target state estimation accuracy among existing IMM filters.

The dispersion of nanomaterials in lubricating oil plays an important role in the lubrication and wear-resistance properties. In this work, supramolecular layered double hydroxides (LDHs) were prepared and added to lubricating oil with different dispersants. The content of key elements in the samples was measured by an oil element analyzer, and the dispersion properties of different samples were studied. The friction coefficient of the samples was measured by high-frequency linear vibration (SRV), and the morphology and composition were characterized by SEM to study the antiwear performance and action mechanism of LDH. The oxidation induction time of the samples was measured by RBOT to study the antioxygenic properties of LDH in lubricating oil. The results show that LDH can be well-dispersed in lubricating oil with the action of specific dispersants. After adding LDH, the antiwear performance of lubricating oil was improved, as a uniform and dense protective film was formed on the friction surface.

Abstract Background The Human T-cell Lymphotropic Virus Type-1 (HTLV-1) is a blood-borne pathogen and etiological agent of Adult T-cell Leukemia/Lymphoma (ATLL) and HTLV-1 Associated Myelopathy/Tropical Spastic Paraparesis (HAM/TSP). HTLV-1 has currently infected up to 10 million globally with highly endemic areas in Japan, Africa, the Caribbean and South America. We have previously shown that Extracellular Vesicles (EVs) enhance HTLV-1 transmission by promoting cell–cell contact. Results Here, we separated EVs into subpopulations using differential ultracentrifugation (DUC) at speeds of 2 k (2000×g), 10 k (10,000×g), and 100 k (100,000×g) from infected cell supernatants. Proteomic analysis revealed that EVs contain the highest viral/host protein abundance in the 2 k subpopulation (2 k > 10 k > 100 k). The 2 k and 10 k populations contained viral proteins (i.e., p19 and Tax), and autophagy proteins (i.e., LC3 and p62) suggesting presence of autophagosomes as well as core histones. Interestingly, the use of 2 k EVs in an angiogenesis assay (mesenchymal stem cells + endothelial cells) caused deterioration of vascular-like-tubules. Cells commonly associated with the neurovascular unit (i.e., astrocytes, neurons, and macrophages) in the blood–brain barrier (BBB) showed that HTLV-1 EVs may induce expression of cytokines involved in migration (i.e., IL-8; 100 k > 2 k > 10 k) from astrocytes and monocyte-derived macrophages (i.e., IL-8; 2 k > 10 k). Finally, we found that EVs were able to promote cell–cell contact and viral transmission in monocytic cell-derived dendritic cell. The EVs from both 2 k and 10 k increased HTLV-1 spread in a humanized mouse model, as evidenced by an increase in proviral DNA and RNA in the Blood, Lymph Node, and Spleen. Conclusions Altogether, these data suggest that various EV subpopulations induce cytokine expression, tissue damage, and viral spread.

Considering the compensation of thermo-optic coefficients (TOC) between GaN-based cavity and TiO2 photonic crystal (PhC) layer, we have theoretically designed a photonic crystal surface emitting laser (PCSEL) with temperature-insensitive wavelength. The structure includes a freestanding GaN membrane with embedded multiple InGaN/GaN quantum well (QW) layer and the top TiO2 PhC layer. The high refractive index (RI) of PhC and the freestanding membrane cavity structure cooperate to enable a stronger field-coupling in PhC, thus fulfill the athermal coupling condition. Interestingly, the wavelength temperature dependence is only 0.0015 nm/°C for such PCSEL with a 82% PhC confinement factor, and its athermal property is proportional to the field confinement factor in TiO2 PhC layer. To illustrate, a general formula has been developed after the investigations of thermo-optic effect and thermal expansion effect.

Abstract Background The lack of specificity and high degree of false positive and false negative rates when using mammographic screening for detecting early-stage breast cancer is a critical issue. Blood-based molecular assays that could be used in adjunct with mammography for increased specificity and sensitivity could have profound clinical impact. Our objective was to discover and independently verify a panel of candidate blood-based biomarkers that could identify the earliest stages of breast cancer and complement current mammographic screening approaches. Methods We used affinity hydrogel nanoparticles coupled with LC-MS/MS analysis to enrich and analyze low-abundance proteins in serum samples from 20 patients with invasive ductal carcinoma (IDC) breast cancer and 20 female control individuals with positive mammograms and benign pathology at biopsy. We compared these results to those obtained from five cohorts of individuals diagnosed with cancer in organs other than breast (ovarian, lung, prostate, and colon cancer, as well as melanoma) to establish IDC-specific protein signatures. Twenty-four IDC candidate biomarkers were then verified by multiple reaction monitoring (LC-MRM) in an independent validation cohort of 60 serum samples specifically including earliest-stage breast cancer and benign controls (19 early-stage (T1a) IDC and 41 controls). Results In our discovery set, 56 proteins were increased in the serum samples from IDC patients, and 32 of these proteins were specific to IDC. Verification of a subset of these proteins in an independent cohort of early-stage T1a breast cancer yielded a panel of 4 proteins, ITGA2B (integrin subunit alpha IIb), FLNA (Filamin A), RAP1A (Ras-associated protein-1A), and TLN-1 (Talin-1), which classified breast cancer patients with 100% sensitivity and 85% specificity (AUC of 0.93). Conclusions Using a nanoparticle-based protein enrichment technology, we identified and verified a highly specific and sensitive protein signature indicative of early-stage breast cancer with no false positives when assessing benign and inflammatory controls. These markers have been previously reported in cell-ECM interaction and tumor microenvironment biology. Further studies with larger cohorts are needed to evaluate whether this biomarker panel improves the positive predictive value of mammography for breast cancer detection.

ABSTRACT Purpose: To evaluate the protective effect of Cuscuta chinensis Lam. polysaccharides (PCCL) on 5-fluorouracil-(5-FU)-induced intestinal mucositis (IM) in mice. Methods: PCCL was orally administered at a dose of 20 mg·kg–1 for 7 days and its protective effect on 5-FU-induced IM (5-FU, 50 mg·kg–1 for 5 days) was evaluated by monitoring changes in body weight, degree of diarrhea, levels of tissue inflammatory factors (tumor necrosis factor α, interleukin 6, and interleukin 1β levels), apoptosis rates, and the expression levels of caspase-3, Bax and Bcl-2. Results: The severity of mucosal injury (as reflected by body weight changes, degree of diarrhea, height of villi, and damage to crypts) was significantly attenuated by PCCL administration. PCCL also reduced the levels of tissue inflammatory factors, the apoptosis rate, and the expression of caspase-3 and Bax, and increased Bcl-2 expression. Conclusions: PCCL administration may be significantly protective against 5-FU-induced IM by inhibiting apoptosis and regulating the abnormal inflammation associated with it.

Abstract The distribution of the received signals in many array processing applications is noncircular. Although optimal widely linear beamformer (WLB) can provide the best performance for noncircular received signals, its performance degrades severely under model mismatches in practical applications. As a remedy, we propose a robust WLB by using precise reconstruction of extended interference-plus-noise covariance matrix (EINCM) and low-complexity estimation of extended desired signal steering vector (EDSSV). We propose to first determine the steering vectors, powers, and noncircularity coefficients of all signals and the noise power. In contrast to the previous reconstruction methods using the integration over a wide angular sector, we reconstruct the interference-plus-noise covariance matrix (INCM) and the pseudo INCM accurately according to their definitions. By using INCM and pseudo INCM, we can precisely reconstruct the EINCM. We propose to estimate the EDSSV by intersecting two extended subspaces, which are respectively formed by eigendecomposing the extended sample covariance matrix and the extended desired signal covariance matrix. Unlike the convex optimization methods, the proposed EDSSV estimation does not require any optimization programming and yields a solution with closed expression in low computational complexity. Simulation results show that the proposed robust WLB provides near optimal performance under several model mismatch cases.

Abstract Background Albumin-globulin ratio (AGR), a variable based on serum albumin and non-albumin proteins, has been demonstrated as a predictor of mortality in patients with malignant neoplasm. The aim of this study was to evaluate the prognostic value of AGR on peritoneal dialysis (PD) patients. Methods We retrospectively analyzed 602 incident PD patients from January 1st, 2008, to December 31st, 2017, at our center and followed them until December 31st, 2018. Kaplan-Meier curves and multivariate Cox regression models were applied to analyze the association between AGR and all-cause of mortality and cardiovascular mortality. Results The median follow-up time was 32.17 (interquartile range = 32.80) months. During follow-up, 131 (21.8%) patients died, including 57 patients (43.5%) who died due to cardiovascular diseases. Kaplan-Meier curves showed that patients with AGR > 1.26 had better rates of survival than those with AGR ≤ 1.25 (p

Censored measurements frequently occur in network systems involving censored sensors or saturated sensors. In addition, unreliable network characteristics can produce random measurement delays during signal transmission. In this paper, we investigate the state estimation problem for network systems with the simultaneous appearance of the aforementioned two measurement uncertainties. The occurrences of two random measurement phenomena are described by two Bernoulli random variables in which the censored variable is dependent on the delay variable. The probability of the process signal being uncensored is calculated by the local approximations using a priori and a posteriori of the state estimation. Then, a novel measurement model that incorporates both the censoring random matrix and the signal delay is established. Based on this model, an optimal recursive estimation method is proposed for systems with specified two uncertainties by making use of an innovation analysis approach and a weighted conditional expectation formula. The superior performance of our proposed method is verified through a typical oscillator simulation example.

Abiotic stress is the focus of research on passion fruit characters because of its damage to the industry. Basic helix-loop-helix (bHLH) is one of the Transcription factors (TFs) which can act in an anti-abiotic stress role through diverse biological processes. However, no systemic analysis of the passion fruit bHLH (PebHLH) family was reported. In this study, 117 PebHLH members were identified from the genome of passion fruit, related to plant stress resistance and development by prediction of protein interaction. Furthermore, the transcriptome sequencing results showed that the PebHLHs responded to different abiotic stresses. At different ripening stages of passion fruit, the expression level of most PebHLHs in the immature stage (T1) was higher than that in the mature stage (T2 and T3). Eight PebHLHs with differentially expressed under different stress treatments and different ripening stages were selected and verified by qRT-PCR. In this research, the expression of one member, PebHLH56, was induced under cold stress. Further, the promoter of PebHLH56 was fused to β-Galactosidase (GUS) to generate the expression vector that was transformed into Arabidopsis. It showed that PebHLH56 could significantly respond to cold stress. This study provided new insights into the regulatory functions of PebHLH genes during fruit maturity stages and abiotic stress, thereby improving the understanding of the characteristics and evolution of the PebHLH gene family.

Abstract Over the past years, wind energy has been considered as a promising solution for clean and sustainable energy development, but wind curtailment remains a challenge to wind power development. On this basis, utilization of non‐grid‐connected wind power becomes crucial and necessary as it can mitigate wind curtailment and improve energy efficiency. This paper proposes the collaboration strategy and optimization model of wind farm‐hybrid energy storage system (WF‐HESS) for non‐grid‐connected wind power based on battery and superconducting magnetic energy storage (SMES) whose combination can effectively cope with fluctuation and intermittence of wind input. The optimization problem is simultaneously investigated by the minimization of total cost, wind curtailment magnitude, and loss of power supply probability (LPSP). The multi‐objective particle swarm optimization (MOPSO) is introduced to find available solutions, and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is applied to determine the optimal one. Results are obtained for a case study, and the effectiveness and the feasibility of proposed model are verified by a comparative analysis and a sensitivity analysis. Results analysis and discussion show that the WF‐HESS model and the application of HESS have important influence on promoting utilization of non‐grid‐connected wind power and mitigating wind curtailment.

To reduce the amount of computation in traditional model predictive current control, to improve the flexibility in choosing the direction and amplitude in the voltage vector synthesis of a dual three-phase motor by two degrees of freedom, and to reduce the output torque ripple and current ripple, this paper proposes a dual second-order model predictive control algorithm based on current loop operation optimization. Compared with the conventional speed loop using the PI control algorithm and the traditional MPC control algorithm, the proposed algorithm adopts the second-order MPC control mode in the speed loop, which decreases the speed regulation time and increases motor immunity. Meanwhile, the second-order MPC control mode is adopted in the current loop, and the traditional iterative calculation method is improved to calculate the direction and amplitude of the output voltage vector through the analytic function, which increases the flexibility of the output voltage vector. Additionally, a four-vector SVPWM is employed to modulate the voltage vector to reduce the current amplitude in the harmonic subspace. The simulation results indicate that the algorithm proposed in this paper can significantly reduce the torque ripple and the current ripple as well as increase the transient performance of the motor.

Here we describe a case of multidrug-resistant tuberculous meningitis associated with injury inflicted during spinal surgery. A 54-year-old man was diagnosed with multidrug-resistant spinal tuberculosis (TB). Anterior debridement and fusion with posterior fusion and instrumentation were conducted to remove damaged bone and TB-associated granulomatous tissue. After surgical decompression, a lancet wound (about 5 mm in length) was discovered in the cerebral dura mater at the L3 position of the vertebral body. At four weeks post-surgery, the patient experienced fever, hemiparesis, and aphasia. Cerebrospinal fluid (CSF) findings were consistent with TB meningitis, while in vitro susceptibility test results confirmed that the patient had multidrug-resistant TB. Our data highlight a possible TBM infection associated with a surgical lesion in a spinal TB patient. Rapid molecular diagnostics are urgently needed to formulate efficacious regimens for treating these patients.

In target tracking, the tracking process needs to constantly update the data information. However, during data acquisition and transmission of sensors, outliers may occur frequently, and the model is disturbed by non-Gaussian noise, that affects the performance of system state estimation. In this paper, a new filtering algorithm is proposed based on QR decomposition and singular value decomposition (SVD) method, namely adaptive robust unscented Kalman filter (QS-ARUKF) to suppress the interference of outliers, nonGaussian noise as well as a model error to achieve high accuracy state estimation. An adaptive filtering algorithm based on strong tracking idea is used in modifying the state equation of unscented Kalman filter (UKF), so that the algorithm can effectively improve the tracking ability of the state model. By using the robust filtering method to construct a new cost function used to modify the measurement covariance formula of the Kalman filter, the error of measurement model can be effectively suppressed. The QR decomposition is introduced to the time update and measurement update to avoid the covariance non-positive definite. We propose the SVD method to address the problem of numerical sensitivity in the filtering process. The purpose of this method is to replace the calculation of the inverse of the filter gain matrix and further improve the robustness of the algorithm. The simulation results showed that the proposed algorithm has higher accuracy and better robustness than the traditional filtering method.

In target tracking, the tracking process needs to constantly update the data information. For maneuvering target, model mismatch and loss of high-order moment information disrupt the accuracy of the state estimation. In this paper, an adaptive high-order unscented Kalman filter (AHUKF) algorithm is proposed for the case of errors occurring in the capturing of model dynamic behavior using the classical unscented Kalman filter (UKF) algorithm. By introducing the free parameter, the analytical solution of the high-order unscented transformation (UT) was obtained, the basis for choosing free parameters was analyzed, and the stability of the algorithm was discussed. A method for obtaining the optimal adaptive factor based on the prediction residual estimation covariance matrix was proposed, which reduces the influence of the dynamic model error and was applied to the target tracking model. In this paper, the proposed AHUKF is applied to a target tracking problem with state mutation, different sampling intervals, and different turn rates, respectively. Simulation results for target tracking illustrate that the proposed algorithm is more accurate and robust than the UKF, high-order unscented Kalman filter (HUKF) and adaptive unscented Kalman filter (AUKF).

A cubature Kalman filter is considered to be one of the most useful methods for nonlinear systems. However, when the statistical characteristics of noise are unknown, the estimation accuracy is degraded. Therefore, an adaptive square-root cubature Kalman filter (ASCKF) is designed to handle the unknown noise. The maximum likelihood criterion and expectation-maximization algorithm are employed to adaptively estimate the parameters of unknown noise, thus restraining the disturbance resulting from unknown noise and improving the estimation accuracy. The stability of the proposed algorithm is theoretically analyzed. Finally, simulations are carried out to illustrate that the performance of the ASCKF algorithm is much more reliable than that of a standard square-root cubature Kalman filter.

To limit the high-frequency chattering originating from the conventional sliding mode observer in a PMSM sensorless control system of vacuum pumps and reduce the steady-state error caused by the phase lag of the coordinate system on the estimated speed, a speed estimation algorithm was proposed based on the super-twisting sliding mode observer. Then, the proposed algorithm was applied to observe an electromotive force. To this end, the Lyapunov function was established to analyze the stability of the current dynamic error equation. In this regard, the estimated phase lag of the rotating coordinate system was considered to study the influence of the speed estimation error. Moreover, a speed estimation algorithm considering the d-axis estimation of back electromotive force is proposed. The performed analyses show that the speed estimation algorithm based on a super-twisting sliding mode observer has promising estimation accuracy. It is concluded that the proposed algorithm can be effectively applied to suppress high-frequency chattering in the system, reduce the influence of phase lag in the estimation coordinate system on the speed estimation error, remove the low-pass filter and phase compensation module, and improve the accuracy of speed estimation.

This paper studies modifications made to the Bosanquet equation in order to fit the experimental observations of the liquid filling process in circular tubes that occurs by capillary force. It is reported that there is a significant difference between experimental observations and the results predicted by the Bosanquet equation; hence, it is reasonable to investigate these differences intensively. Here, we modified the Bosanquet equation such that it could consider more factors that contribute to the filling process. First, we introduced the air flowing out of the tube as the liquid inflow. Next, we considered the increase in hydraulic resistance due to the surface roughness of the inner tube. Finally, we further considered the advancing contact angle, which varies during the filling process. When these three factors were included, the modified Bosanquet equation was well correlated with the experimental results, and the R square—which indicates the fitting quality between the simulation and the experiment—significantly increased to above 0.99.