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Although spermatogenic dysfunction is widely found in patients with human immunodeficiency virus (HIV), the underlying reasons remain unclear. Thus far, potential hypotheses involving viral reservoirs, testicular inflammation, hormone imbalance, and cachexia show inconsistent correlation with spermatogenic dysfunction. Here, northern pig-tailed macaques (NPMs) exhibited marked spermatogenic dysfunction after long-term infection with simian immunodeficiency virus (SIVmac239), with significant decreases in Johnsen scores, differentiated spermatogonial stem cells, and testicular proliferating cells. The above hypotheses were also evaluated. Results showed no differences between SIV− and SIV+ NPMs, except for an increase in follicle stimulating hormone (FSH) during SIV infection, which had no direct effect on the testes. However, long-term SIVmac239 infection undermined pancreatic islet β cell function, partly represented by significant reductions in cellular counts and autophagy levels. Pancreatic islet β cell dysfunction led to glucose metabolism disorder at the whole-body level, which inhibited lactate production by Sertoli cells in testicular tissue. As lactate is the main energy substrate for developing germ cells, its decrease was strongly correlated with spermatogenic dysfunction. Therefore, glucose metabolism disorder appears to be a primary cause of spermatogenic dysfunction in NPMs with long-term SIVmac239 infection.

Abstract Background Controllable and multiple DNA release is critical in modern gene-based therapies. Current approaches require complex assistant molecules for combined release. To overcome the restrictions on the materials and environment, a novel and versatile DNA release method using a nano-electromechanical (NEMS) hypersonic resonator of gigahertz (GHz) frequency is developed. Results The micro-vortexes excited by ultra-high frequency acoustic wave can generate tunable shear stress at solid–liquid interface, thereby disrupting molecular interactions in immobilized multilayered polyelectrolyte thin films and releasing embedded DNA strands in a controlled fashion. Both finite element model analysis and experiment results verify the feasibility of this method. The release rate and released amount are confirmed to be well tuned. Owing to the different forces generated at different depth of the films, release of two types of DNA molecules with different velocities is achieved, which further explores its application in combined gene therapy. Conclusions Our research confirmed that this novel platform based on a nano-electromechanical hypersonic resonator works well for controllable single and multi-DNA release. In addition, the unique features of this resonator such as miniaturization and batch manufacturing open its possibility to be developed into a high-throughput, implantable and site targeting DNA release and delivery system.

Even as gigahertz (GHz) acoustic streaming has developed into a multi-functional platform technology for biochemical applications, including ultrafast microfluidic mixing, microparticle operations, and cellar or vesicle surgery, its theoretical principles have yet to be established. This is because few studies have been conducted on the use of such high frequency acoustics in microscale fluids. Another difficulty is the lack of velocimetry methods for microscale and nanoscale fluidic streaming. In this work, we focus on the basic aspects of GHz acoustic streaming, including its micro-vortex generation principles, theoretical model, and experimental characterization technologies. We present details of a weak-coupled finite simulation that represents our current understanding of the GHz-acoustic-streaming phenomenon. Both our simulation and experimental results show that the GHz-acoustic-induced interfacial body force plays a determinative role in vortex generation. We carefully studied changes in the formation of GHz acoustic streaming at different acoustic powers and flow rates. In particular, we developed a microfluidic-particle-image velocimetry method that enables the quantification of streaming at the microscale and even nanoscale. This work provides a full map of GHz acoustofluidics and highlights the way to further theoretical study of this topic. Keywords: Acoustic streaming, Gigahertz, Body force, Microfluidic PIV

The most common issues for many clustering algorithms include the slow convergence, requirement for pre-specification of a number of parameters, and the lack of robustness when dealing with anomalies. Recently, the density peak clustering (DPC) algorithm was proposed to discover the centers of clusters by finding the density peaks in a dataset based on their local densities. The DPC needs neither an iterative process nor a large number of parameters, and it supports a heuristic approach, known as the decision graph, to manually select cluster centroids. However, the selection of the key parameters of the DPC was not systematically investigated. In this paper, we propose the feasible residual error-based density peak clustering algorithm with the fragment merging strategy, where the local density within the neighborhood region is measured through the residual error computation and the resulting residual errors are then used to generate residual fragments for cluster formation. The model parameters are then able to be calculated from the equations with statistical theoretical justification. We also develop a semi-automatic cluster identification method to eliminate the iterative process of manual centroid selection. The robustness and effectiveness of the proposed algorithm compared to the DPC and other clustering algorithms are demonstrated through experiments on standard benchmark datasets. The proposed method named feasible residual error-based density peak clustering (FREDPC) algorithm with the fragment merging strategy only needs to perform in one single step without any iteration and thus it is fast and has a great potential to be applied on a wide range of applications.

For the design of printed circuit board (PCB) winding, it is necessary to take into account the requirements of electromagnetic and manufacture technology of PCB winding, which directly affect the output power of the machine. In this paper, for axial flux permanent magnet generator (AFPMG) of a small wind power system, the unequal-width (UEW) winding is proposed for the aim of improving the output power of the generator. The design ideas and methods of unequal-width (UEW) winding are proposed in combination with manufacture technology of the PCB. The finite element analysis (FEA) model of machine is built. The analytical formulas of electromotive force (EMF) and winding loss are derived. Though the comparisons between reactance and impedance of PCB winding, the analytical formula of output power is simplified. These characteristics of the generator with traditional equal-width(EW) winding and proposed UEW winding are analyzed and compared in detail by FEA and analytical calculation. The result shows that the output power of the generator with UEW winding is improved largely. Finally, the validity of the FEA model and analysis method is verified by experiment of prototype machine, which provides the reference for the design of AFPMG with PCB winding.

The health effects of suspended particulate matter (PM) in the air are well documented; however, there is a lack of convenient tools to recognize and quantify PM onsite. Here, we design and fabricate a portable PM analysis system to realize onsite aerosol particle analysis. The system contains a micromachined virtual impactor (VI), a thermophoretic deposition chip, and a smartphone-based portable imaging device. The silicon dioxide (SiO2) particles and polystyrene sphere (PLS) particles are used to verify the micro-sized VI with an accurate cut-off diameter of $2~\mu \text{m}$ (PM2). After separation, the fine particles are thermally deposited on a replaceable film. Then, a smartphone connected with a hand-held optical microscope is applied to directly image and analyze the deposited particles with the assistance of a self-developed Android application; thus, the size and distribution of the particles can be acquired immediately. The PM analysis device is successfully applied to analyze the particle content from a smoking cigarette as a real complex sample demonstration. Considering the compact integration of the particle separation, collection, detection, and analysis components, the reported PM analysis device is promising for point-of-need outdoor and indoor air quality monitoring.

Injecting drug users (IDUs) are the major risk group for HIV-1 infection in the China-Myanmar border area. There are a large number of Burmese IDUs living in Yunnan (Yunnan-mIDUs) who might be associated with the cross-border transmission of HIV-1. From 2010 to 2013, 617 Yunnan-mIDUs were recruited from three counties of Yunnan, 19.0% of whom were detected to be HIV-1 positive by serological testing. Partial HIV-1 p17, pol, vif-env, and env genes were amplified from the positive samples and were sequenced. Phylogenetic and HIV-1 subtyping analyses revealed that HIV-1 recombinant forms (RFs), including RF_BC (36.4%), RF_01BC (26.1%), RF_01C (9.1%) and RF_01B (1.1%), were predominant among this cohort. Of the identified HIV-1 strains, 14.8%, 9.1% and 3.4% belonged to subtype C, CRF01_AE and subtype B, respectively. Transmission cluster analysis showed that sequences from the Yunnan-mIDUs formed transmission clusters not only with those from Burmese IDUs but also with those from Chinese IDUs, indicating that Yunnan-mIDUs might acquire HIV-1 infection from or spread HIV-1 to both Burmese and Chinese IDUs. Phylogeographic analyses revealed three cross-border transmission patterns associated with Yunnan-mIDUs, in which Yunnan-mIDUs served as the crucial nodes linking the Burmese and Chinese IDUs. These results suggest that Yunnan-mIDUs are a potential viral reservoir for the diffusion of HIV-1 in Yunnan and play a pivotal role in the bidirectional cross-border transmission of HIV-1 in the China-Myanmar border region. More intervention efforts that focus on Yunnan-mIDUs are recommended in Yunnan’s campaign against HIV/AIDS.

Ambient suspended particulate matter (PM) (primarily with particle diameter 2.5 µm or less, i.e., PM2.5) can adversely affect ecosystems and human health. Currently, optical particle sensors based on light scattering dominate the portable PM sensing market. However, the light scattering method has poor adaptability to different-sized PM and adverse environmental conditions. Here, we design and develop a portable PM sensing microsystem that consists of a micromachined virtual impactor (VI) for particle separation, a thermophoretic deposition chip for particle collection, and an extended-gate field-effect transistor (FET) for particle analysis. This system can realize on-site separation, collection, and analysis of aerosol particles without being influenced by environmental factors. In this study, the design of the VI is thoroughly analyzed by numerical simulation, and mixtures of different-sized silicon dioxide (SiO2) particles are used in an experimental verification of the performance of the VI and FET. Considering the low cost and compact design of the whole system, the proposed PM analysis microsystem has potential for PM detection under a wide range of conditions, such as heavily polluted industrial environments and for point-of-need outdoor and indoor air quality monitoring.

Abstract Hydrodynamic force loading platforms for controllable cell mechanical deformation play an essential role in modern cell technologies. Current systems require assistance from specific microstructures thus limiting the controllability and flexibility in cell shape modulation, and studies on real‐time 3D cell morphology analysis are still absent. This article presents a novel platform based on acoustic streaming generated from a gigahertz device for cell shape control and real‐time cell deformation analysis. Details in cell deformation and the restoration process are thoroughly studied on the platform, and cell behavior control at the microscale is successfully achieved by tuning the treating time, intensity, and wave form of the streaming. The application of this platform in cell membrane permeability modulation and analysis is also exploited. Based on the membrane reorganization during cell deformation, the effects of deformation extent and deformation patterns on membrane permeability to micro‐ and macromolecules are revealed. This technology has shown its unique superiorities in cell mechanical manipulation such as high flexibility, high accuracy, and pure fluid force operation, indicating its promising prospect as a reliable tool for cell property study and drug therapy development.

Pulmonary microbial invasion frequently occurs during AIDS progression in HIV patients. Inflammatory cytokines and other immunoregulatory factors play important roles in this process. We previously established an AIDS model of SIVmac239 infection in northern pig-tailed macaques (NPMs), which were divided into rapid progressor (RP) and slow progressor (SP) groups according to their AIDS progression rates. In this study, we performed 16S rDNA and transcriptome sequencing of the lungs to reveal the molecular mechanism underlying the difference in progression rate between the RPs and SPs. We found that microbial invasion in the RP group was distinct from that in the SP group, showing marker flora of the Family XI, Enterococcus and Ezakiella, and more Lactobacilli. Through pulmonary transcriptome analysis, we found that the transcription factor ZNF683 had higher expression in the SP group than in the RP group. In subsequent functional experiments, we found that ZNF683 increased the proliferation and IFNγ secretion ability of CD8+ T cells, thus decreasing SIV or HIV replication, which may be related to AIDS progression in SIVmac239-infected NPMs. This study helps elucidate the various complexities of disease progression in HIV-1-infected individuals.

Disturbed blood flow has been recognized to promote platelet aggregation and thrombosis via increasing accumulation of von Willebrand factor (VWF) at the arterial post-stenotic sites. The mechanism underlying the disturbed-flow regulated endothelial VWF production remains elusive. Here we described a mouse model, in which the left external carotid artery (LECA) is ligated to generate disturbed flow in the common carotid artery. Ligation of LECA increased VWF accumulation in the plasma. Carotid arterial thrombosis was induced by ferric chloride (FeCl3) application and the time to occlusion in the ligated vessels was reduced in comparison with the unligated vessels. In vitro, endothelial cells were subjected to oscillatory shear (OS, 0.5 ± 4 dynes/cm2) or pulsatile shear (PS, 12 ± 4 dynes/cm2). OS promoted VWF secretion as well as the cell conditioned media-induced platelet aggregation by regulating the intracellular localization of vesicle-associated membrane protein 3 (VAMP3) and synaptosomal-associated protein 23 (SNAP23). Disruption of vimentin intermediate filaments abolished the OS-induced translocation of SNAP23 to the cell membrane. Knockdown of VAMP3 and SNAP23 reduced the endothelial secretion of VWF. Systemic inhibition of VAMP3 and SNAP23 by treatment of mice with rapamycin significantly ameliorated the FeCl3-induced thrombogenesis, whereas intraluminal overexpression of VAMP3 and SNAP23 aggravated it. Our findings demonstrate VAMP3 and SNAP23 as potential targets for preventing the disturbed flow-accelerated thrombus formation.

The activity of blind thrust faults drives fold deformation of overlying strata, leading the folds to be geometrically related to the underlying blind thrust faults. However, it is often challenging to select an appropriate kinematic model for a thrust fault-related fold. To construct the model of the Guman fold in front of the Western Kunlun Mountains in western China, we interpret deformed terrace profiles and a high-resolution seismic reflection profile that crosses the fold. Combining deformation characteristics of the terrace profiles and subsurface structures interpreted from the seismic reflection data, the Guman fold is best explained as a fault-bend fold with lower flat-ramp-upper flat geometry that grows by kink-band migration. Previous studies and the seismic reflection profile show that the blind fault ramp dips 20 ± 4° to the south. Using the fault bend fold model with Monte Carlo probability distributions, the uplifted and dated T1c terrace surface (250 ± 35 ka) and fault geometry indicate a slip rate of 2.6+1.3/−0.4 mm/yr along the underlying fault ramp. The uplift of the pre-growth strata across the underlying fault ramp combined with the fold initiation in the early Pleistocene (2.14–1.8 Ma) indicate a long-term slip rate of 1.7+0.6/−0.2 mm/yr along the underlying fault ramp. For a lower flat-ramp-upper flat fault-bend fold with fault dip of 20°, 13% of the slip along the underlying fault ramp would be absorbed by the fold above the fault ramp, whereas 87% of the slip will be transferred forward along the upper fault flat. Therefore, the shortening accommodated by the Guman anticline is 0.34+0.18/−0.06 mm/yr while the slip rate along the upper fault flat is 2.3+1.1/−0.4 mm/yr since the T1c terrace abandonment. This result explains why the shortening of the Guman Anticline is largely hidden from the relative movement of Global Positioning Stations sites to the north and south of the fold. These findings support the view that most of the crustal shortening of the Western Kunlun Mountain is transferred basinward along the shallow detachment and is likely ultimately absorbed by the Mazatagh Thrust located 200 km away in the hinterland of the Tarim Basin.

Atherosclerotic plaque preferentially develops in arterial curvatures and branching regions, where endothelial cells constantly experience disturbed blood flow. By contrast, the straight arteries are generally protected from plaque formation due to exposure of endothelial cells to vaso-protective laminar blood flow. However, the role of flow patterns on endothelial barrier function remains largely unclear. This study aimed to investigate new mechanisms underlying the blood flow pattern-regulated endothelial integrity. Exposure of human endothelial cells to pulsatile shear (PS, mimicking the laminar flow) compared to oscillatory shear (OS, mimicking the disturbed flow) increased the expressions of long non-coding RNA MALAT1 and tight junction proteins ZO1 and Occludin. This increase was abolished by knocking down MALAT1 or Nesprin1 and 2. PS promoted the association between Nesprin1 and SUN2 at the nuclear envelopes, and induced a nuclear translocation of β-catenin, likely through enhancing the interaction between β-catenin and Nesprin1. In the in vivo study, mice were treated via intraperitoneal injection with β-catenin agonist SKL2001 or its inhibitor XAV939, and they were then subjected to Evans blue injection to assess aortic endothelial permeability. The aortas exhibited a reduced wall permeability to Evans blue in SKL2001-treated mice whereas an enhanced permeability in XAV939-treated mice. We concluded that laminar flow promotes nuclear localization of Nesprins, which facilitates the nuclear access of β-catenin to stimulate MALAT1 transcription, resulting in increased expressions of ZO1 and Occludin to protect endothelial barrier function.

Incomplete observation of hourly air-pollutants concentration data is a common issue existing in urban air quality monitoring networks. This research proposes a spatial interpolation method to impute missing values presented in air pollutants data sets based on low rank matrix completion (LRMC). It considers air pollutants data of high correlation and consistency in its spatial distribution. We evaluate the performance of the proposed method when imputing various air pollutants concentration time series (NOx,O3,SO2,PM2.5,PM10) in terms of root mean square error (RMSE), index of agreement (D2), and goodness of fit (R2). It systematically compared with existing established imputation techniques, including nearest neighboring, mean substitution, regression-based method, spline interpolation, spectral method, and regularized expectation maximization algorithm (EM). As a spatial imputation method, LRMC outperforms these methods used in this research under the condition of larger missing ratio (such as 30% removal) on the central air pollutants monitoring station. For all monitoring stations, comprehensive experimental results show that LRMC always generates robust results to replace missing data with reasonable substitutions, and it is not sensitive to the length of missing gaps. The promising imputation performance in terms of the indicator R2 obtained by the proposed LRMC demonstrates that it can effectively impute missing values of air pollutants time series based on their inherent patterns.

Numerous human actions such as “Phoning,” “PlayingGuitar,” and “RidingHorse” can be inferred by static cue-based approaches even if their motions in video are available considering one single still image may already sufficiently explain a particular action. In this research, we investigate human action recognition in still images and utilize deep ensemble learning to automatically decompose the body pose and perceive its background information. Firstly, we construct an end-to-end NCNN-based model by attaching the nonsequential convolutional neural network (NCNN) module to the top of the pretrained model. The nonsequential network topology of NCNN can separately learn the spatial- and channel-wise features with parallel branches, which helps improve the model performance. Subsequently, in order to further exploit the advantage of the nonsequential topology, we propose an end-to-end deep ensemble learning based on the weight optimization (DELWO) model. It contributes to fusing the deep information derived from multiple models automatically from the data. Finally, we design the deep ensemble learning based on voting strategy (DELVS) model to pool together multiple deep models with weighted coefficients to obtain a better prediction. More importantly, the model complexity can be reduced by lessening the number of trainable parameters, thereby effectively mitigating overfitting issues of the model in small datasets to some extent. We conduct experiments in Li’s action dataset, uncropped and 1.5x cropped Willow action datasets, and the results have validated the effectiveness and robustness of our proposed models in terms of mitigating overfitting issues in small datasets. Finally, we open source our code for the model in GitHub (https://github.com/yxchspring/deep_ensemble_learning) in order to share our model with the community.

Infrared spectroscopy (IR) quantitative analysis technology has shown excellent development potential in the field of oil and gas logging. However, due to the high overlap of the IR absorption peaks of alkane molecules and the offset of the absorption peaks in complex environments, the quantitative analysis of IR spectroscopy applied in the field puts forward higher requirements for modelling speed and accuracy. In this paper, a new type of fast IR spectroscopy quantitative analysis method based on adaptive step-sliding partial least squares (ASS-PLS) is designed. A sliding step control function is designed to change the position of the local PLS analysis model in the full spectrum band adaptively based on the relative change of the current root mean square error and the global minimum root-mean-square error for rapid modelling. The study in this paper reveals the influence of the position and width of the local modelling window on the performance, and how to quickly determine the optimal modelling window in an uncertain sample environment. The performance of the proposed algorithm has been compared with three typical quantitative analysis methods by experiments on an IR spectrum dataset of 400 alkane samples. The results show that this method has a fast quantitative modelling speed with high analysis accuracy and stability. It has important practical value for promoting IR spectroscopy gas-logging technology.

Swarm intelligence algorithms (SIAs) have demonstrated excellent performance when solving optimization problems including many real-world problems. However, because of their expensive computational cost for some complex problems, SIAs need to be accelerated effectively for better performance. This paper presents a high-performance general framework to accelerate SIAs (FASI). Different from the previous work which accelerates SIAs through enhancing the parallelization only, FASI considers both the memory architectures of hardware platforms and the dataflow of SIAs, and it reschedules the framework of SIAs as a converged dataflow to improve the memory access efficiency. FASI achieves higher acceleration ability by matching the algorithm framework to the hardware architectures. We also design deep optimized structures of the parallelization and convergence of FASI based on the characteristics of specific hardware platforms. We take the quantum behaved particle swarm optimization algorithm as a case to evaluate FASI. The results show that FASI improves the throughput of SIAs and provides better performance through optimizing the hardware implementations. In our experiments, FASI achieves a maximum of 290.7 Mb/s throughput which is higher than several existing systems, and FASI on FPGAs achieves a better speedup than that on GPUs and multi-core CPUs. FASI is up to 123 times and not less than 1.45 times faster in terms of optimization time on Xilinx Kintex Ultrascale xcku040 when compares to Intel Core i7-6700 CPU/NVIDIA GTX1080 GPU. Finally, we compare the differences of deploying FASI on hardware platforms and provide some guidelines for promoting the acceleration performance according to the hardware architectures.

Fireworks algorithm (FWA) is a novel swarm intelligence algorithm recently proposed for solving complex optimization problems. Because of its powerful global optimization ability to solve classification problems, we first present an optimization classification model in this paper. In this model, a linear equation set is constructed according to classification problems. This optimization classification model can be solved by most evolutionary computation techniques. In this paper, a self-adaptive FWA (SaFWA) is developed so that the optimization classification model can be solved efficiently. In SaFWA, four candidate solution generation strategies (CSGSs) are employed to increase the diversity of solutions. In addition, a self-adaptive search mechanism has also been introduced to use the four CSGSs simultaneously. To extensively assess the performance of SaFWA on solving classification problems, eight datasets have been used in the experiments. The experimental results show that it is feasible to solve classification problems through the optimization classification model and SaFWA. Furthermore, SaFWA performs better than FWA, FWA variants with only one CSGS, particle swarm optimization, and differential evolution on most of the training sets and test sets.

Support vector clustering (SVC) is a boundary-based algorithm, which has several advantages over other clustering methods, including identifying clusters of arbitrary shapes and numbers. Leveraged by the high generalization ability of the large margin distribution machine (LDM) and the optimal margin distribution clustering (ODMC), we propose a new clustering method: minimum distribution for support vector clustering (MDSVC), for improving the robustness of boundary point recognition, which characterizes the optimal hypersphere by the first-order and second-order statistics and tries to minimize the mean and variance simultaneously. In addition, we further prove, theoretically, that our algorithm can obtain better generalization performance. Some instructive insights for adjusting the number of support vector points are gained. For the optimization problem of MDSVC, we propose a double coordinate descent algorithm for small and medium samples. The experimental results on both artificial and real datasets indicate that our MDSVC has a significant improvement in generalization performance compared to SVC.

A microfluidic film bulk acoustic wave resonator gas sensor (mFBAR) adapted specifically as an in-line detector in gas chromatography was described. This miniaturized vapor sensor was a non-destructive detector with very low dead volume (0.02 μL). It was prepared by enclosing the resonator in a microfluidic channel on a chip with dimensions of only 15 mm × 15 mm × 1 mm. The device with polymer coating showed satisfactory performance in the detection of organophosphorus compound, demonstrating a very low detection limit (a dozen parts per billion) with relatively short response time (about fifteen seconds) toward the simulant of chemical warfare agent, dimethyl methylphosphonate. The in-line detection of the mFBAR sensor with FID was constructed and employed to directly measure the concentration profile on the solid surface by the mFBAR with the controlled concentration profile in the mobile phase at the same time. The difference of peak-maximum position between mobile phase and solid phase could be a convenient indicator to measure mass transfer rate. With the response of the mFBAR and FID obtained in one injection, an injection mass-independent parameter can be calculated and used to identify the analyte of interest.

Abstract Deep brain stimulation in thalamic regions has been proposed as a treatment for epilepsy. The electrical current excites thalamocortical activity which is controlled by γ-aminobutyric acid (GABA)ergic interneurons in the reticular thalamic nucleus (nRT). Previous studies showed that enhancing GABAergic inhibitory strength in the nRT reduces the duration and power of seizures, indicating that the thalamus plays an important role in modulating cortical seizures. The aim of the present study was to apply optogenetics to study the role of the nRT in modulating cortical seizures. We used PV-ChR2-EYFP transgenic mice from Jackson Laboratories, in which only Channelrhodopsin-2 (ChR2) is expressed in parvalbumin-expressing interneurons. Cortical seizure-like activity was induced by electrical stimulation of the corpus callosum after applying 4-aminopyridine. ChR2 expression was abundant in the nRT and cerebellum in PV-ChR2-EYFP transgenic mice. Light stimulation in the nRT caused burst firing in regions of the thalamus and nRT in vitro. Multi-unit activity increased during high-frequency (100 and 50 Hz) light stimulation in the S1 region and thalamus in vivo. Corpus callosum stimulation-induced seizure-like activity was effectively suppressed by high-frequency (100 Hz) and long-duration (10 s) light stimulation. The suppressive effects were reversed by applying a GABAB receptor antagonist but not a GABAA receptor antagonist in the cortex. The results indicated that light stimulation affected thalamocortical relay neurons by activating ChR2-expression neurons in the nRT. High-frequency and long-duration light stimulation was more effective in suppressing cortical seizure-like activity. GABAB receptors may participate in suppressing seizure-like activity.

Abstract The elderly population infected with HIV-1 is often characterized by the rapid AIDS progression and poor treatment outcome, possibly because of immunosenescence resulting from both HIV infection and aging. However, this hypothesis remains to be fully tested. Here, we studied 6 young and 12 old Chinese rhesus macaques (ChRM) over the course of three months after simian immunodeficiency virus (SIV) SIVmac239 infection. Old ChRM showed a higher risk of accelerated AIDS development than did young macaques, owing to rapidly elevated plasma viral loads and decreased levels of CD4+ T cells. The low frequency of naïve CD4+ T cells before infection was strongly predictive of an increased disease progression, whereas the severe depletion of CD4+ T cells and the rapid proliferation of naïve lymphocytes accelerated the exhaustion of naïve lymphocytes in old ChRM. Moreover, in old ChRM, a robust innate host response with defective regulation was associated with a compensation for naïve T cell depletion and a high level of immune activation. Therefore, we suggest that immunosenescence plays an important role in the accelerated AIDS progression in elderly individuals and that SIV-infected old ChRM may be a favorable model for studying AIDS pathogenesis and researching therapies for elderly AIDS patients.

This paper reported a wireless controlled micro-actuator system for rapid heating and mixing of multiple droplets using integrated arrays of micro-fabricated 2.5 GHz solid-mounted thin-film piezoelectric resonators (SMRs) and a millimeter-scale omnidirectional antenna. An equivalent circuit is proposed to analyze the mechanism of the heating, mixing of the SMR, and the wireless communication system. The heating and mixing rate can be tuned by adjusting the input power as well as the transmission distance between the transmitting antenna and the receiving antennas. A heating rate up to 3.7 °C per second and ultra-fast mixing of the droplet was demonstrated with the wireless microsystem. In addition, two types of circuits, H-shaped and rake-shaped, were designed and fabricated for parallel operating actuator array and controlling the power distribution with the array. Both uniform and gradient heating of the multiple droplets are achieved, which can be potentially applied for developing high-throughput wireless micro-reactor system.

Objective: Dysbiosis of gastric microbiota such as Helicobacter pylori plays a significant role in pathogenesis and progression of gastric cancer. Our aim was to evaluate the composition and functional effects of gastric microbiota in superficial gastritis (SG) and advanced gastric adenocarcinoma (GC).Methods: We carried out shotgun metagenomic sequencing on gastric wash samples from 6 patients with GC and 5 patients with SG. The taxonomic composition was profiled using MetaPhlAn2 and functional gene pathway was profiled using HUMAnN2. Differences in microbial composition and pathways between the two patient groups were assessed via LEfSe.Results: The gastric microbiota in GC patients was characterized by reduced species richness, enrichment of 13 bacterial taxa and depletion of 31 taxa (q < 0.05). The most representative taxa which were abundant in GC corresponded to the commensals or opportunistic pathogens that usually colonize the oral cavity, including genera Neisseria, Alloprevotella, and Aggregatibacter, species Streptococcus_mitis_oralis_pneumoniae and strain Porphyromonas_endodontalis.t_GCF_000174815. Each of the three GC-associated genera could separate GC from SG completely. In particular, Sphingobium yanoikuyae, a bacterium capable of degrading carcinogenic compounds, was depleted in GC. Functionally, pathways associated with the biosynthesis of lipopolysaccharide (LPS) and L-arginine were enriched in GC, whereas pathways involved in the fermentation of short chain fatty acids (SCFAs) and branched amino acid metabolism were more abundant in SG.Conclusions: Our results present new alterations in the gastric microbiome in patients with GC from a whole-genome perspective, suggesting that microbiome composition and function can be used for prognosis and diagnosis of GC.

The solar selective absorber coating (SSAC) are at the core of the efficient solar-thermal system. In this paper, for the first time, the Chromium-iron oxidation mixture cermet was successfully prepared on the surface of ultra-pure ferritic stainless steel by chemical coloring as SSAC. The coating surface has an optical trap structure, and the chromium-iron oxidation mixture cermet is used as an absorption layer to realize solar-thermal conversion. The solar absorptance (AM1.5) of the coating reached 93.66, and the thermal emittance was less than 13. After thermal shock tests at 25/300 °C done 32 times (accumulated 812.8 h), the Performance Criterion (PC) of the coating was 0.01375 < 0.05, showing outstanding thermal stability.

The northern pig-tailed macaques (NPMs) lack TRIM5α, an antiviral restriction factor, and instead have TRIM5-CypA. In our previous study, we demonstrated that HIV-1NL4−3 successfully infected NPMs and formed a long-term viral reservoir in vivo. However, the HIV-1-infected NPMs showed relatively high viremia in the first 6 weeks of infection, which declined thereafter suggesting that HIV-1 NL4−3 infection in these animals was only partly permissive. To optimize HIV-1 infection in NPMs therefore, we generated HIV-1NL4−R3A and stHIV-1sv, and infected NPMs with these viruses. HIV-1NL4−R3A and stHIV-1sv can replicate persistently in NPMs during 41 weeks of acute infection stage. Compared to the HIV-1NL4−R3A, stHIV-1sv showed a notably higher level of replication, and the NPMs infected with the latter induced a more robust neutralizing antibody but a weaker cellular immune response. In addition, IFN-I signaling was significantly up-regulated with the viral replication, and was higher in the stHIV-1sv infected macaques. Consequently, the sequences of pro-viral env showed fewer G-A hyper-mutations in stHIV-1sv, suggesting that vif gene of SIV could antagonize the antiviral effects of APOBEC3 proteins in NPMs. Taken together, NPMs infected with HIV-1NL4−R3A and stHIV-1sv show distinct virological and immunological features. Furthermore, interferon-related gene expression might play a role in controlling primary HIV-1NL4−R3A and stHIV-1sv replication in NPMs. This result suggests NPM is a potential HIV/AIDS animal model.

The performance of density based clustering algorithms may be greatly influenced by the chosen parameter values, and achieving optimal or near optimal results very much depends on empirical knowledge obtained from previous experiments. To address this limitation, we propose a novel density based clustering algorithm called the Density Propagation based Adaptive Multi-density clustering (DPAM) algorithm. DPAM can adaptively cluster spatial data. In order to avoid manual intervention when choosing parameters of density clustering and still achieve high performance, DPAM performs clustering in three stages: (1) generate the micro-clusters graph, (2) density propagation with redefinition of between-class margin and intra-class cohesion, and (3) calculate regional density. Experimental results demonstrated that DPAM could achieve better performance than several state-of-the-art density clustering algorithms in most of the tested cases, the ability of no parameters needing to be adjusted enables the proposed algorithm to achieve promising performance.

We investigate a novel way of robust face image feature extraction by adopting the methods based on Unsupervised Linear Subspace Learning to extract a small number of good features. Firstly, the face image is divided into blocks with the specified size, and then we propose and extract pooled Histogram of Oriented Gradient (pHOG) over each block. Secondly, an improved Earth Mover’s Distance (EMD) metric is adopted to measure the dissimilarity between blocks of one face image and the corresponding blocks from the rest of face images. Thirdly, considering the limitations of the original Locality Preserving Projections (LPP), we proposed the Block Structure LPP (BSLPP), which effectively preserves the structural information of face images. Finally, an adjacency graph is constructed and a small number of good features of a face image are obtained by methods based on Unsupervised Linear Subspace Learning. A series of experiments have been conducted on several well-known face databases to evaluate the effectiveness of the proposed algorithm. In addition, we construct the noise, geometric distortion, slight translation, slight rotation AR, and Extended Yale B face databases, and we verify the robustness of the proposed algorithm when faced with a certain degree of these disturbances.

Bulk acoustic wave (BAW) resonators are widely applied in filters and gravimetric sensors for physical or biochemical sensing. In this work, a new architecture of BAW resonator is demonstrated, which introduces a pair of reflection layers onto the top of a thin film bulk acoustic resonator (FBAR) device. The new device can be transformed between type I and type II dispersions by varying the thicknesses of the reflection layers. A computational modeling is developed to fully investigate the acoustic waves and the dispersion types of the device theoretically. The novel structure makes it feasible to fabricate both type resonators in one filter, which offers an effective alternative to improve the pass band flatness in the filter. Additionally, this new device exhibits a high quality factor (Q) in the liquid, which opens a possibility for real time measurement in solutions with a superior limitation of detection (LOD) in sensor applications.

A quantitative description of the dynamics of droplet motion has been a long-standing concern in electrowetting research. Although many static and dynamic models focusing on droplet motion induced by electrowetting-on-dielectric (EWOD) already exist, some dynamic features do not fit these models well, especially the dynamic saturation phenomenon. In this paper, a dynamic saturation model of droplet motion on the single-plate EWOD device is presented. The phenomenon that droplet velocity is limited by a dynamic saturation effect is precisely predicted. Based on this model, the relationship between droplet motion and device physics is extensively discussed. The static saturation phenomenon is treated with a double-layer capacitance electric model, and it is demonstrated as one critical factor determining the dynamics of droplet motion. This work presents the relationship between dynamics of electrowetting induced droplet motion and device physics including device structure, surface material and interface electronics, which helps to better understand electrowetting induced droplet motions and physics of digital microfluidics systems.

This paper reports on the implementation of an ultraminiature 140 MHz narrowband filter based on aluminum nitride Lamb wave resonators. Monolithically integrated with a pair of on-chip capacitors and cascaded with a pair of inductors, the filter is well matched to 50 ohm, showing a remarkably high performance. A low pass-band insertion loss of 2.78 dB and steep filter skirts are achieved. The form factor of the monolithic microelectromechanical systems filter is more than ten times smaller than its surface acoustic wave counterpart in the intermediate frequency band and it involves much simpler matching circuits.

Ribosome inactivating proteins (RIPs) inhibit protein synthesis by depurinating the large ribosomal RNA and some are found to possess anti-human immunodeficiency virus (HIV) activity. Maize ribosome inactivating protein (RIP) has an internal inactivation loop which is proteolytically removed for full catalytic activity. Here, we showed that the recombinant active maize RIP protected chimeric simian-human immunodeficiency virus (SHIV) 89.6-infected macaque peripheral blood mononuclear cells from lysis ex vivo and transiently reduced plasma viral load in SHIV89.6-infected rhesus macaque model. No evidence of immune dysregulation and other obvious side-effects was found in the treated macaques. Our work demonstrates the potential development of maize RIP as an anti-HIV agent without impeding systemic immune functions.

The carbon–neutral target presents a significant challenge for the sewage sludge treatment and disposal (SSTD) industry, necessitating strategic planning for a low-carbon transition. However, flexible and comprehensive carbon emission analysis tools to support this goal remain lacking. This study presents a carbon emission analysis tool to evaluate the carbon emission characteristics and future mitigation potentials of SSTD. The tool integrates life cycle inventory (LCI) modeling-based analysis, sensitivity analysis, regression analysis, and scenario analysis. Carbon emissions are dynamically calculated based on sludge properties, technological level, and industry external parameters, providing a foundation for adaptable evaluation tailored to local conditions. The framework considers the potential effects of multi-parameter and multi-aspect changes in scene design, both within and outside the industry, to achieve dynamic and comprehensive simulations. A case study conducted in Wuhan, China, demonstrated the usability and application processes of the framework. The results indicated that carbon emissions from SSTD are projected to more than double from 2021 to 2060 without interventions. Among the mitigation measures, energy and chemical savings would yield the largest reduction potential, followed by the technical layout adjustment and the promotion of energy efficiency. Operational optimization in the sludge industry and outside the industry would contribute the least. With all mitigation measures applied, emissions could decrease to –82.91 kt CO2-eq in 2060, equivalent to 13.03% compensation for emissions from the sewage treatment line. Among all the processes, incineration routes are recommended due to their current and future low carbon emissions. The cooperative resource route of anaerobic digestion and land use also shows promise as it progressively demonstrates superior performance with increasing organic matter and nutrient content of sludge. Critical factors, sub-processes, and emission types for different routes were identified and can be optimized accordingly. The developed method demonstrates sufficient flexibility to be applied to other cities and larger-scale regions, thereby offering technical and strategic support for SSTD towards carbon–neutral operation.

‘Big data’ is an area of growing research interest within sociology and numerous other disciplines. The rapid development of social media platforms and other web resources offer a vast and readily accessible repository of data associated with participants’ activities, attitudes and personal information on a scale and depth that would have previously been difficult to access without substantial resources. However, as well as offering opportunities to social researchers, this medium also presents a significant range of challenges. Ethical issues are one much debated area where social scientists are having to reassess their longstanding modus operandi, given questions regarding access to personal data and ambiguities regarding its status and legitimate usage. In addition, the scale of data accessible and the possible skills required to collect and analyse it is also a critical issue, and is an area that, arguably, has received lesser attention. In its infancy, online research could be fairly rudimentary, employing simple techniques to gather information from weblogs, forums and so on. However, the possibilities now presented by large-scale social media platforms has created the potential for more sophisticated research that often requires specialist technical expertise, involving collaborative work by computer and social scientists working together. This is a scenario that raises its own concerns, not least in terms of forging areas of shared understanding between these disparate disciplines sufficient to facilitate such projects. This article addresses such issues, providing a reflection on the theoretical and practical experience of engaging in online research, from fledgling involvement to embarking on a current collaborative interdisciplinary project. The aim is to provide some insights to other social scientists with respect to some of the potential advantages and pitfalls of web research, while a flavour of the current project, exploring Scottish Referendum and UK General Election related Twitter data, is also presented.

A 3D three-phase segmentally variable density perforation optimization model for horizontal wells is built by coupling reservoir fluid filtration, near wellbore inflow and wellbore conduit flow based on reservoir numerical simulation. The effects of 8 factors (filtration difference between heel/toe and middle intervals, imperforated interval, permeability heterogeneity, oil layer thickness heterogeneity, porosity heterogeneity, wellbore pressure drawdown, maximum perforation density, and perforation optimization principles) on perforation density and inflow profile, and that of fluid viscosity, casing diameter and pipe wall coarseness on well bore pressure drawdown, are analyzed for segmentally variable density perforation of horizontal wells. Results show that filtration difference between heel/toe and middle intervals, imperforated interval, permeability heterogeneity and oil layer thickness heterogeneity have significant effects on segmentally variable density perforation. In particular, different perforation density optimizations may occur when filtration difference between heel/toe and middle interval is not considered; imperforated interval may affect inflow profile; well bore pressure drawdown can be ruled out for segmentally variable density perforation of most horizontal wells onshore in China. The contrast between predicted and actual production of Well AT9-7H in the Tahe Oilfield indicates that the model is highly accurate. Key words: horizontal well, segmentally variable density perforation, reservoir numerical simulation, imperforated interval, inflow profile, heterogeneity

Solitons are self-trapped modes existing in various nonlinear systems. Creating stable solitons in two- and three-dimensional settings is a challenging goal in various branches of physics. Several methods have been developed theoretically and experimentally to achieve this, but few of them can support stable multi-dimensional solitons in free space. Recently, a new scheme using spin-orbit-coupling (SOC) has been proposed to create stable 2D solitons in Bose–Einstein condensates (BECs). This paper reviews recent theoretical progress on creating stable 2D solitons in spinor dipolar BEC with SOC, combined with long-range dipole-dipole interaction (DDI), Zeeman splitting (ZS) and contact nonlinearity, in free space. The continuous family of stable symmetric vortex solitons (SVS), asymmetric vortex solitons (AVS), as well as gap solitons (GS) is found via different settings. Their existence and stability conditions are summarized and discussed in detail. The mobility properties of these types of solitons are also addressed. For SVS, a potential method to manipulate its shape and mobility is investigated. These results are supposed to enrich our understanding of 2D solitons and help create multi-dimensional solitons in experiments.

In this paper, we develop a novel dual-mode gas sensor system which comprises a silicon nanoribbon field effect transistor (Si-NR FET) and a film bulk acoustic resonator (FBAR). We investigate their sensing characteristics using polar and nonpolar organic compounds, and demonstrate that polarity has a significant effect on the response of the Si-NR FET sensor, and only a minor effect on the FBAR sensor. In this dual-mode system, qualitative discrimination can be achieved by analyzing polarity with the Si-NR FET and quantitative concentration information can be obtained using a polymer-coated FBAR with a detection limit at the ppm level. The complementary performance of the sensing elements provides higher analytical efficiency. Additionally, a dual mixture of two types of freons (CFC-113 and HCFC-141b) is further analyzed with the dual-mode gas sensor. Owing to the small size and complementary metal-oxide semiconductor (CMOS)-compatibility of the system, the dual-mode gas sensor shows potential as a portable integrated sensing system for the analysis of gas mixtures in the future.

Camptothecin (CPT), a traditional anti-tumor drug, has been shown to possess anti-HIV-1 activity. To increase the antiviral potency, the anti-HIV activities of two CPT derivatives, 10-hydroxy-CPT and 7-hydroxymethyl-CPT, were evaluated in vitro. The therapy index (TI) of CPT, 10-hydroxy-CPT and 7-hydroxymethyl-CPT against HIV-1IIIB in C8166 were 24.2, 4.2 and 198.1, and against clinical isolated strain HIV-1KM018 in PBMC were 10.3, 3.5 and 66.0, respectively. While the TI of CPT, 10-hydroxy-CPT and 7-hydroxymethyl-CPT against HIV-2CBL-20 were 34.5, 10.7 and 317.0, respectively, and the TI of the three compounds against HIV-2ROD showed the similar values. However, when the antiviral mechanisms were considered, we found there was no inhibition of 7-hydroxymethyl-CPT on viral cell-to-cell transmission, and was no inhibition on reverse transcriptase, protease or integrase in cell-free systems. 7-Hydroxymethyl-CPT showed no selective killing of chronically infected cells after 3 days of incubation. In conclusion, 7-hydroxymethyl-CPT showed more potent anti-HIV activity, while 10-hydroxy-CPT had less efficient activity, compared with the parent CPT. Though the antiviral mechanisms remain to be further elucidated; the modification of -OH residues at C-7 of CPT could enhance the antiviral activity, while of -OH residues at C-10 of CPT had decreased the antiviral activity, which provides the preliminary modification strategy for anti-viral activities enhancement of this compound.

Data with categorical attributes are ubiquitous in the real world. However, existing partitional clustering algorithms for categorical data are prone to fall into local optima. To address this issue, in this paper we propose a novel clustering algorithm, ABC-K-Modes (Artificial Bee Colony clustering based on K-Modes), based on the traditional k-modes clustering algorithm and the artificial bee colony approach. In our approach, we first introduce a one-step k-modes procedure, and then integrate this procedure with the artificial bee colony approach to deal with categorical data. In the search process performed by scout bees, we adopt the multi-source search inspired by the idea of batch processing to accelerate the convergence of ABC-K-Modes. The performance of ABC-K-Modes is evaluated by a series of experiments in comparison with that of the other popular algorithms for categorical data.

Immune activation plays a significant role in the disease progression of HIV. Microbial products, especially bacterial lipopolysaccharide (LPS), contribute to immune activation. Increasing evidence indicates that T lymphocyte homeostasis disruptions are associated with immune activation. However, the mechanism by which LPS affects disruption of immune response is still not fully understood. Chronically SHIVB’WHU-infected Chinese rhesus macaques received 50 μg/kg body weight LPS in this study. LPS administration affected the virus/host equilibrium by elevating the levels of viral replication and activating T lymphocytes. LPS induced upregulation of CD8+ naïve T cells and downregulated the number of CD4+ and CD8+ T effector memory cells. The downregulated effector memory cells are associated with a lower frequency of monofunctional and polyfunctional cells, and an upregulated programmed cell death-1 (PD-1) expression on CD4+ and CD8+ T cells was observed in monkeys after LPS stimulation. Our data provide new insights into the function of LPS in the immune activation in SHIV/HIV infection.

The very small vibration of a solidly-mounted resonator (SMR) in fluid may trigger a relatively large motion of the covering fluid, which was implied by our protein-related experimental results. Therefore, a series of experimental methods for characterizing the mechanical longitudinal vibration of the SMR and the corresponding out-of-plane dynamic response of the fluid above the SMR surface is described in this paper. A SMR device with theoretical resonance frequency of 2.5 GHz was driven by an amplitude-modulated (AM) signal, in which the amplitude is modulated by a signal of the second resonance frequency of the atomic force microscope (AFM) cantilever. A lock-in amplifier is used to demodulate the vibration response of the AFM cantilever, which is proportional to the amplitude of the sample vibration in contact mode and tapping mode. The amplitude-frequency curve of the SMR surface is obtained in contact mode with a relatively stronger interaction force between the AFM tip and the SMR surface. The amplitude-frequency curve of the motion of the liquid above the SMR device and the peak amplitude of the fluid at different distances above the SMR surface are measured in tapping mode with a relatively weak interaction force between the AFM tip and the fluid sample.

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This paper demonstrates a novel micro-size (120 μm × 200 μm) piezoelectric gas sensor based on a piezotransduced single-crystal silicon bulk acoustic resonator (PSBAR). The PSBARs operate at 102 MHz and possess high Q values (about 2000), ensuring the stability of the measurement. A corresponding gas sensor array is fabricated by integrating three different self-assembled monolayers (SAMs) modified PSBARs. The limit of detection (LOD) for ethanol vapor is demonstrated to be as low as 25 ppm with a sensitivity of about 1.5 Hz/ppm. Two sets of identification code bars based on the sensitivities and the adsorption energy constants are utilized to successfully discriminate isopropanol (IPA), ethanol, hexane and heptane vapors at low and high gas partial pressures, respectively. The proposed sensor array shows the potential to form a portable electronic nose system for volatile organic compound (VOC) differentiation.

We developed a highly sensitive humidity sensor based on the combination of ultrahigh-frequency film bulk acoustic resonator (FBAR) and nano-assembled polyelectrolyte (PET) thin films. The water molecule absorption efficiency was optimized by forming loosely-packed PET nanostructures. Then, the humidity sensing characteristics were analyzed in terms of sensitivity, linearity, reversibility, stability and detection limit. As a result, PET-coated FBAR exhibits excellent humidity sensitivity of 2202.20 Hz/ppm, which is five orders of magnitude higher than quartz crystal microbalance (QCM). Additionally, temperature dependence was investigated with the result that PET-coated FBAR possessed a higher sensitivity at low temperature. Furthermore, we realized the selective detection of water vapor from volatile organic compounds (VOCs) with respect to the polarity property. Owing to the high sensitivity, miniaturized size and ultrahigh operating frequency, PET-coated FBAR is uniquely favorable as a wireless humidity sensor node to integrate into wireless sensor networks (WSNs).