Objective The study aimed to evaluate the impact of Botulinum toxin A (BoNT/A) on neuropsychiatric symptoms in Parkinson’s disease (PD) patients. Methods A total of 125 PD patients and an equal number of age- and gender-matched healthy controls were involved. Mental health status was assessed using the Cornell Medical Index (CMI) self-assessment questionnaire. Sixty-four PD patients exhibiting neuropsychiatric symptoms were selected for the controlled study and randomly grouped into treatment and control groups. The treatment group received BoNT/A injections, while the control group received a placebo. The primary outcome measures included depression scores from the CMI and the proportion of patients displaying improvement in neuropsychiatric symptoms at 8 weeks post-treatment. The secondary outcome was other CMI scores at 4, 8, and 12 weeks post-treatment. Results The outcomes revealed that PD patients had significantly higher scores in various neuropsychiatric factors compared to healthy controls. At 4 weeks post-treatment, the treatment group displayed improvements in depression and tension. At 8 weeks post-treatment, they exhibited significant reductions in depression, anxiety, sensitivity, and tension compared to the control group. Moreover, a notably higher percentage of patients in the treatment group showed improvement in neuropsychiatric symptoms compared to the control group. At 12 weeks post-treatment, the treatment group exhibited significant improvements in somatization, depression, sensitivity, and tension. Conclusion PD patients commonly experience multiple neuropsychiatric symptoms, and BoNT/A has demonstrated efficacy in alleviating these symptoms. Specifically, BoNT/A was found to effectively alleviate somatization, tension, anxiety, depression, and sensitivity in PD patients.

Immersive techniques, such as virtual reality, augmented reality, and mixed reality, take immersive displays as carriers to provide immersive experience. A large number of approaches focus on the visualization of scientific data in immersive environments while just a few methods concentrate on interactive information visualization (InfoVis) in an immersive environment, although InfoVis has been extended to the 3-D space for a long time. In the era of data explosion, the traditional 2-D space is unable to convey large amounts of abstract information in an intuitive way. Meanwhile, desktop-based 3-D InfoVis generally leads to visual conflict and confusion owing to limited display size and field of vision. In this survey, we search for the interactive techniques in immersive InfoVis and summarize their commonalities and discuss their differences and potential trends. The data types of abstract information in InfoVis can be categorized into graph/network data, high-dimensional and multivariate data, time-varying data, and text and document data. Besides, the visual presentation of information in immersive environments is also summarized, especially for charts, plots, and diagrams, which are some basic components of InfoVis techniques. We also described the immersive applications of InfoVis techniques, including the tools or frameworks on immersive analytics and infographics. The discussion about the traditional nonimmersive and the immersive methods in data visualizations show that the latter one has the potential to become an alternative to explore massive information in the future.

Investing in energy efficiency is considered to be an effective way to reduce the carbon emissions. However, the resulting CO2 savings may be partially or totally offset by the rebound effect (RE). This paper goes beyond the traditional energy RE to investigate the rebound effect as related to CO2 emissions, aims to explore the direct CO2 rebound effect (CRE) in urban households at the provincial level. To achieve the objective, this study uses IPCC carbon emissions accounting method, then proposes an elasticity approach and constructs an individual fixed-effect variable coefficient panel data model. The results show that the total CO2 emissions from household energy consumption were rising in most provinces during 2002–2017. The purchased electricity and heat CO2 emissions are growing faster than combustion CO2 emissions. Regarding the magnitude of the CRE, there are three types of direct CRE among urban households in China: the backfire effect, partial rebound effect and super conservation effect. Overall, the average direct CRE in urban households is 59.90%; specifically, the western region has the highest direct CRE (90.92%), compared with the eastern region (52.84%) and central region (24.88%). The government should take into account the CRE of households, in order to avoid overestimating the carbon reduction. Attention should also be paid to the differences between provinces when formulating energy policies. The analysis above helps local governments to formulate effective energy policies to promote households’ carbon emission reduction.

In this paper, a modulated signal recognition method based on feature fusion and ResCNN (FF-ResCNN) under generalized fractal noise background is proposed. Firstly, in the feature extraction and fusion part, considering the robustness, anti-noise and interpretability of the features, the fusion feature vectors of generalized fractal spectrum, instantaneous feature and high-order cumulant feature are constructed. Secondly, in order to suppress the possible gradient and degradation problems, the ResCNN model is used to train and classify the fusion features when the CNN model is used to further collect the deep-level abstract features. Finally, feature extraction, feature fusion and classification experiments are carried out for nine modulated signals under two noise types (GWN and fractal noise). Experimental results show that in the case of generalized fractal noise, when SNR=0dB, the recognition accuracy of signal modulation type reaches 95.42%, which verifies the superiority of the proposed method. At the same time, the simulation analysis is carried out for different feature fusion schemes, which provides a valuable reference for feature combination optimization under different noise environment.

MOTIVATION:Narrative visualization for scientific data explorations can help users better understand the domain knowledge, because narrative visualizations often present a sequence of facts and observations linked together by a unifying theme or argument. Narrative visualization in immersive environments can provide users with an intuitive experience to interactively explore the scientific data, because immersive environments provide a brand new strategy for interactive scientific data visualization and exploration. However, it is challenging to develop narrative scientific visualization in immersive environments. In this paper, we propose an immersive narrative visualization tool to create and customize scientific data explorations for ordinary users with little knowledge about programming on scientific visualization, They are allowed to define POIs (point of interests) conveniently by the handler of an immersive device. RESULTS:Automatic exploration animations with narrative annotations can be generated by the gradual transitions between consecutive POI pairs. Besides, interactive slicing can be also controlled by device handler. Evaluations including user study and case study are designed and conducted to show the usability and effectiveness of the proposed tool. AVAILABILITY:Related information can be accessed at: https://dabigtou.github.io/richenliu/.

Recent researches showed that nucleotide-binding domain and leucine-rich repeat protein 3 (NLRP3) inflammasome inhibition exerted dopaminergic neuroprotection in cellular or animal models of Parkinson’s disease (PD). NLRP3 inflammasome has been proposed as a drug target for treatment of PD. However, the interplay between chronic NLRP3 inflammasome and progressive α-synuclein pathology keeps poorly understood. Moreover, the potential mechanism keeps unknown. In the present study, we investigate whether NLRP3 inflammasome inhibition prevents α-synuclein pathology by relieving autophagy dysfunction in the chronic 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP) mouse model of PD. NLRP3 knockout mice and their wild-type counterparts were treated with continuous MPTP administration via osmotic mini-pumps. Dopaminergic neuronal degeneration was assessed by western blotting and immunohistochemistry (IHC). The levels of dopamine and its metabolites were determined using high-performance liquid chromatography. NLRP3 inflammasome activation and autophagy biomarkers were assessed by western blot. The expressions of pro-inflammatory cytokines were measured by ELISA. The glial reaction and α-synuclein pathology were assessed by IHC and immunofluorescence. Our results show that NLRP3 inflammasome inhibition via NLRP3 knockout not only protects against nigral dopaminergic degeneration and striatal dopamine deletion but also prevents nigral pathological α-synuclein formation in PD mice. Furthermore, it significantly suppresses MPTP-induced glial reaction accompanied by the secretion of pro-inflammatory cytokines in the midbrain of mice. Most importantly, it relieves autophagy dysfunction in the midbrain of PD mice. Collectively, we demonstrate for the first time that improving autophagy function is involved in the preventive effect of NLRP3 inflammasome inhibition on α-synuclein pathology in PD.

Diffusion Tensor Imaging (DTI) reveals subtle abnormalities associated with stroke, multiple sclerosis, schizophrenia and dyslexia, which has a broad application prospect in the medical field. The densely sampled 3-D DTI fiber tracts in biological specimens have high geometric, spatial and anatomical complexity. To provide users with more immersive and convenient interactions in exploring DTI fibers, we design specific interactions based on the APIs of Leap Motion. Leap Motion is a somatosensory interaction device focusing on hand tracking. We design four different interaction modes for users to analyze the data in different interaction stages and scenarios, in order to better explore the DTI fibers which users are interested in by Leap Motion gestures. They are Normal Mode, Box Basic Interaction Mode, Box Logic Operation Mode, and Cluster Exploration Mode. Users can conduct tradition manipulations over the whole DTI fiber data in Normal Mode. Boxes are employed to filter out uninteresting tracts in Box Basic Interaction Mode, and expression-based queries are further designed to get logic set operations based on multiple boxes in Box Logic Operation Mode, e.g., the intersection, union and complement of boxes. Complex logic combination queries are allowed to perform to reduce visual clutter and help users explore DTI fibers more precisely. In Cluster Exploration Mode, DTI fibers can be classified by clustering them into spatially and anatomically related tracts and then different clusters can be explored individually by designed gestures. Compared with the explorations through traditional input devices, the evaluation tests show that the proposed approach is more intuitive and efficient in 3-D explorations and provides an immersive experience for users to explore the DTI fiber data.

Obstacle avoidance algorithm is often used in data visualization to connect lines between data items or perform route planning in 3D volume visualization. The traditional obstacle avoidance algorithm is often designed to find a shortest path between two data items. It is not suitable to be used in visualization, because it needs to achieve a more artistic and smooth effect. Well-designed visualization often provides user-friendly, effective, and efficient manipulations and interactions. In this paper, we use an obstacle avoidance algorithm to connect lines between data items, which can be used to visualize set information present in category data (or set data). Specifically, we use A-star algorithm to conduct obstacle avoidance between data items, then we make the lines more artistic and smooth by introducing a series pivot points. Finally, we visualize the data items by connecting the lines to show the category information and sub-category information or other information. Experiments show that the proposed approach is capable of revealing the set information present in category data.

Volume visualization has wide application in science, engineering, biomedicine and other domains to help understand complex observational or simulative data. Transfer function is a traditional volume visualization approach, which is designed to assign different schemes of color and transparency for each voxel in volume data. In this paper, we design a histogram-based nonlinear transfer function editor. The design of nonlinear histogram and non-uniform grids in the background provides visual cues for users to edit transfer function more efficiently. The larger the histogram bin sizes are, the wider the bin widths will be drawn in the background. Then, a wavelet-like short transfer function (we call it TF-let) is designed, which can be serialized and reloaded fast in the subsequent explorations. Furthermore, we design a TF-let fusion approach to fuse multiple TF-lets by simply clicking the corresponding TF-let nodes. Compared with the traditional linear method, two evaluation tests show that the proposed approach is less sensitive and more efficient to edit the control points of the transfer function. Finally, use cases show the proposed approach is capable of achieving some hard-to-find tiny structures and visualizing them much more clearly.

Abstract. Seismic data visualization and analysis can help the domain experts, e.g., geologists and oil or gas exploration experts, to explore the distribution of petroleum or gas. It assists them to get a better understanding of stratigraphic structures and the distribution of the geological materials, e.g., underground flow path (UFP) and the contexts of UFPs (river delta, floodplain, slump fan, oil well, etc.). UFPs are one of the significant stratigraphic structures according to the domain experts, because they are closely related to the distribution and the migration of oil or gas. We design a quadratic-surface distance query scheme to explore UFPs and their contexts within a local region. First, it just needs to share parameters of quadratic surfaces to the rendering modules instead of all volume data or all subvolume data to conduct distance queries, and it is flexible to perform multiple complex logic operations through the quadratic surface-based queries. Second, it enables one to perform domain-specific interactions after distance queries such as the flexible switching of multiple display modes. Third, it enables one to perform local transfer function on different subvolumes different query results or their arbitrary combinations. We have evaluated the approach by comparing them with existing methods by performance evaluation and result evaluation. Results show that the proposed approach is capable of performing complex distance queries and fulfilling the domain-specific interactions getting better results and timing performance.

BACKGROUND Endothelial dysfunction plays a central part in the pathogenesis of coronary atherosclerosis. The adipokine resistin is one of the key players in endothelial cell dysfunction. In addition, the role of epicardial fat in coronary artery endothelial dysfunction is also emphasized. We investigated whether vasodilator-stimulated phosphoprotein (VASP) is involved in resistin-related endothelial dysfunction and the phenotype conversion of epicardial adipocytes. MATERIAL AND METHODS Cell proliferation and migration were evaluated by MTT and Transwell chamber assay, respectively. Next, we took epicardial fat samples from patients with valvular heart disease and non- coronary artery disease. Gene expression was determined by reverse transcription- quantitative polymerase chain reaction and relative abundance of the protein by Western blotting. RESULTS Resistin induced endothelial proliferation and migration in a dose-dependent manner. Both resistin-induced cell proliferation and migration were effectively blocked by ablation of VASP. The brown adipose tissue-specific genes for uncoupling protein 1 (UCP-1) and PR-domain-missing16 (PRDM16) decreased, but the white adipose tissue-specific genes for resistin and RIP140 increased in VASP-deficient adipocytes compared with the LV-sicntr group. However, disruption of the Ras homolog gene family member A (RhoA) /Rho-associated kinase (ROCK) in VASP-deficient adipocytes with specific inhibitors inverted the adipocyte phenotype existing in VASP-deficient adipocytes. Furthermore, the expressions of proinflammatory cytokines interleukin-6 (IL-6), interleukin-8 (IL-8), and monocyte chemoattractantprotein-1 (MCP-1) in VASP-deficient adipocytes were markedly upregulated compared with the LV-sicntr group. CONCLUSIONS These results suggest a physiological role for VASP in coronary atherosclerosis through regulating adipokine resistin and phenotype conversion of epicardial adipose tissue.

A series of para‐toluene sulfonamide ligands [TsNHPr‐i(HL1), TsNHBu‐t(HL2), TsNHPh(HL3), TsNHPhMe‐p(HL4), TsNHPhOMe‐p(HL5)] were synthesized by amidation using para‐toluene sulfonyl chloride reacting with different primary amines. A series of homoleptic lanthanide complexes (Ln L3, 1–10) (Ln = La, L = L1 (1), Ln = Gd, L = L2 (2), Ln = La, L = L2 (3), Ln = Gd, L = L2(4), Ln = La, L = L3 (5), Ln = Gd, L = L3 (6), Ln = La, L = L4 (7), Ln = Gd, L = L4(8), Ln = La, L = L5 (9), Ln = Gd, L = L5 (10)) were prepared by amine elimination reactions of the ligands with Ln[N(SiMe3)2]3 (Ln = La, Gd). Complexes 1, 3, 5, 7 and 9 were all characterized by NMR spectra, and the structures of complex 3 was determined by single‐crystal X‐ray diffraction. Complex 3 crystallizes a binuclear cluster, consisting of two La3+ and six (TsNBu‐t)− anions. Three (TsNBu‐t)− anions are chelating to each La3+ as bidentate model with O and N forming three‐membered chelate rings; one of three anions is bridging to another La3+ via oxygen. All complexes were characterized using elemental analysis and infrared spectra. The catalytic properties of complexes 1–10 for the ring‐opening polymerization of ε‐caprolactone were studied and the results showed that all complexes are efficient initiators for this ring‐opening polymerization reaction.

Considering the social properties of mobile sinks, we propose a biased trajectory dissemination of uncontrolled mobile sinks for event collection in wireless sensor networks. In biased trajectory dissemination of uncontrolled mobile sink, we first divide the whole network into clusters which can be managed by cluster heads that are elected in turn for intra-cluster event collection and inter-cluster communication. Second, for a mobile sink, we further divide the clusters it visits into biased clusters and non-biased clusters according to its staying probability. The mobile sink will send its mobility message which shows its location as it moves into a new cluster. We then construct a biased loop which is composed of all biased clusters and some non-biased clusters to disseminate a mobile sink’s mobility message only to clusters on it when the mobile sink moves into a biased cluster. We also construct query path that connects any cluster head that is not on the biased loop to a cluster head on it. An event could be transmitted to the biased loop along the query path for further forwarding to the mobile sink. Numerous simulations show the superior performance of biased trajectory dissemination of uncontrolled mobile sink compared to the representative schemes in terms of average path length, delay, and network energy consumption.

The study aimed to investigate the correlation between Parkinson’s disease (PD) and serum levels of uric acid (UA), albumin and their interaction. A cross-sectional study was conducted to evaluate the relationship of serum UA, albumin with PD. A total of 96 PD patients and 108 healthy controls were recruited at Huai’an First People’s Hospital, Nanjing Medical University. Baseline data included age, gender, body mass index (BMI), disease duration, Hoehn and Yahr scale (H&Y) stage, serum UA and albumin levels. The levels of serum UA and albumin were significantly lower in PD patients than those in controls (P = 0.001; P = 0.000). Serum albumin levels were strikingly different in H&Y group (P = 0.004). Multivariable logistic regression showed that the levels of serum UA (P = 0.001, adjusted OR 0.993, 95% CI 0.988–0.997) and albumin (P = 0.000, adjusted OR 0.513, 95% CI 0.425–0.620) were independent risk factors in PD. The receiver operating characteristic (ROC) curve analyses showed that the area under curve (AUC) for serum UA and albumin was 0.669 (95% CI 0.594–0.744) and 0.883 (95% CI 0.835–0.931), respectively. The combination of serum albumin and UA improved the AUC to 0.898 (95% CI 0.854–0.942). Serum UA and albumin levels significantly decreased in PD patients and were independent risk factors for PD. More studies are needed to confirm our findings.

Two novel asymmetrical carbazole-based diamines 9-(2-(1,1'-binaphthyl-4-yl) benzyl)-9H-carbazole-3,6-diamine (BNBCD) and 9-((4'-(9H-carbazol-9-yl)biphenyl-2-yl)methyl-9H-carbazole-3,6-diamine (CBMCD) were synthesized. A series of novel soluble aromatic polyimides were prepared from these diamines by poly-condensation with Pyromelitic dianhydride (PMDA) and 2,2',3,3'-biphenyl tetracarboxylic dianhydride (BPDA) via a two-step procedure. The resulting polymers were fully characterized, they exhibited excellent organosolubility and high thermal stability with the temperature of 5% weight loss under nitrogen atmosphere over 400 degrees C. Resistive switching devices with the configuration of Al/polymer/ITO were constructed from these polyimides by using conventional solution coating process. The memory devices based on PI-a, PI-b and PI-c exhibited a flash type memory capability, whereas the PI-d presented a write once read many times (WORM) memory capability. (C) 2016 Elsevier Ltd. All rights reserved.

A four-channel automotive night vision system is designed and developed .It is consist of the four active near-infrared cameras and an Mulit-channel image processing display unit,cameras were placed in the automobile front, left, right and rear of the system .The system uses near-infrared laser light source，the laser light beam is collimated, the light source contains a thermoelectric cooler (TEC),It can be synchronized with the camera focusing, also has an automatic light intensity adjustment, and thus can ensure the image quality. The principle of composition of the system is description in detail,on this basis, beam collimation,the LD driving and LD temperature control of near-infrared laser light source,four-channel image processing display are discussed.The system can be used in driver assistance, car BLIS, car parking assist system and car alarm system in day and night.

An integrated GPS/INS system provides more accurate estimates of position and attitude compared to individual systems. Availability of inertial sensors and GPS cores has opened up new opportunities for low cost INS/GPS systems which find wide spread application. Different integration techniques of GPS/INS integration have been implemented to obtain accurate position in navigation systems. A loosely coupled GPS/INS integration has been adopted in this paper. Real-time system discussed here is more suitable for navigation systems. In this paper, the modeling on GPS/INS integrated navigation system is design and simulated.

Recent advancement in digital signal processing and analog-to-digital conversion techniques has driven the use of software radio in radio frequency signal receiving. This paper applies the concept of software radio to GPS signal acquisition and tracking. GPS signal receiver consists of RF front-end, buffer memory, and a digital signal processor. In comparison with traditional approaches, the software radio structure has many advantages such as programmability and flexibility. In this paper, GPS acquisition and tracking algorithms are designed and developed. The simulation results show that this technique can improve the whole performance of GPS receivers and can provide the experiment platform with the design and development of kinds of the new algorithms and ideas for enhancing GPS receiver performance.

GPS can provide both military and private users with accurate information about user position and velocity. However its data rate is low as well as 1~10Hz, and it will not provide a continuous and reliable information among mountains, dense forests and high building. Inertial Navigation System (INS) is an autonomous, all-weather navigation system that can provide continuous information of position, velocity and attitude regardless of the surrounding. But the performance of INS deteriorates with time due to inertial sensor performance. GPS and INS have complementary properties, whose integration is an efficient way of improving the whole performance of navigation system. In this paper, the models of GPS and INS, respectively, are built and analyzed, and then a tightly coupled GPS/INS system based on the information of GPS position and velocity is modeled and simulated, which is compared with integrated system using only GPS position data. The simulation and analysis results demonstrate that integrated system can greatly enhance the robustness and reliability of autonomous navigation system.