Navigation in a small world with local information

It is commonly known that there exist short paths between vertices in a network showing the small-world effect. Yet vertices, for example, the individuals living in society, usually are not able to find the shortest paths, due to the very serious limit of information. To theoretically study this issue, here the navigation process of launching messages toward designated targets is investigated on a variant of the one-dimensional small-world network (SWN). In the network structure considered, the probability of a shortcut falling between a pair of nodes is proportional to $r^{-\alpha}$, where $r$ is the lattice distance between the nodes. When $\alpha =0$, it reduces to the SWN model with random shortcuts. The system shows the dynamic small-world (SW) effect, which is different from the well-studied static SW effect. We study the effective network diameter, the path length as a function of the lattice distance, and the dynamics. They are controlled by multiple parameters, and we use data collapse to show that the parameters are correlated. The central finding is that, in the one-dimensional network studied, the dynamic SW effect exists for $0\leq \alpha \leq 2$. For each given value of $\alpha$ in this region, the point that the dynamic SW effect arises is $ML^{\prime}\sim 1$, where $M$ is the number of useful shortcuts and $L^{\prime}$ is the average reduced (effective) length of them.Comment: 10 pages, 5 figures, accepted for publication in Physical Review

A Proposed Technique to Acquire Cavity Pressure Using a Surface Strain Sensor During Injection- Compression Molding

A new technique was proposed and experimentally verified for the cavity pressure acquisition in the injection-compression molding (ICM). The surface strain of the fixed mold half and the cavity pressure were monitored simultaneously during ICM. In the compression stage, a directly proportional relationship between the cavity pressure and mold surface strain was found and determined via the regression analysis. By taking the advantage of this relationship, the cavity pressure profile with high accuracy was indirectly obtained from the nondestructive measurement of the mold surface strain. Moreover, the mold surface strain profile could indicate the part weight or thickness and the critical time when the part surface lost contact with the cavity surface in a large area. The monitoring of the mold surface strain could serve as an interesting alternative to the direct monitoring of the cavity pressure with respect to process and part quality control for ICM

NUMERICAL PREDICTION AND EXPERIMENTAL VALIDATION OF TRANSIENT TEMPERATURE PROFILES DURING REHEATING PREFORM IN STRETCH BLOW MOLDING

ABSTRACT Reheating of the preform represents an important stage in the two-stage stretch blow molding (SBM) process. This work aimed at developing a temperature acquisition system with an emphasis on the design of both thermocouples and brush mechanism, which leads the acquisition system to be used to measure in real time the transient temperature profiles within the wall of the reheated preform as it rotates. The measured temperature distributions both through the thickness of the preform and along its length were then compared with numerical results predicted by solving a thermal model for the preform reheating in the SBM. Both the radiative and convective heat transfers were considered in the simulation. After being verified by experimental dada, the thermal model was used to predict the transient temperature profiles within reheated preform under different conditions, such as preform thickness, air convection coefficient, and reheating time. This work helps to better deepen the understanding of the preform reheating in the two-stage SBM process

SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar

The 4D Millimeter wave (mmWave) radar is a promising technology for vehicle sensing due to its cost-effectiveness and operability in adverse weather conditions. However, the adoption of this technology has been hindered by sparsity and noise issues in radar point cloud data. This paper introduces spatial multi-representation fusion (SMURF), a novel approach to 3D object detection using a single 4D imaging radar. SMURF leverages multiple representations of radar detection points, including pillarization and density features of a multi-dimensional Gaussian mixture distribution through kernel density estimation (KDE). KDE effectively mitigates measurement inaccuracy caused by limited angular resolution and multi-path propagation of radar signals. Additionally, KDE helps alleviate point cloud sparsity by capturing density features. Experimental evaluations on View-of-Delft (VoD) and TJ4DRadSet datasets demonstrate the effectiveness and generalization ability of SMURF, outperforming recently proposed 4D imaging radar-based single-representation models. Moreover, while using 4D imaging radar only, SMURF still achieves comparable performance to the state-of-the-art 4D imaging radar and camera fusion-based method, with an increase of 1.22% in the mean average precision on bird's-eye view of TJ4DRadSet dataset and 1.32% in the 3D mean average precision on the entire annotated area of VoD dataset. Our proposed method demonstrates impressive inference time and addresses the challenges of real-time detection, with the inference time no more than 0.05 seconds for most scans on both datasets. This research highlights the benefits of 4D mmWave radar and is a strong benchmark for subsequent works regarding 3D object detection with 4D imaging radar

LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion

As an emerging technology and a relatively affordable device, the 4D imaging radar has already been confirmed effective in performing 3D object detection in autonomous driving. Nevertheless, the sparsity and noisiness of 4D radar point clouds hinder further performance improvement, and in-depth studies about its fusion with other modalities are lacking. On the other hand, most of the camera-based perception methods transform the extracted image perspective view features into the bird's-eye view geometrically via "depth-based splatting" proposed in Lift-Splat-Shoot (LSS), and some researchers exploit other modals such as LiDARs or ordinary automotive radars for enhancement. Recently, a few works have applied the "sampling" strategy for image view transformation, showing that it outperforms "splatting" even without image depth prediction. However, the potential of "sampling" is not fully unleashed. In this paper, we investigate the "sampling" view transformation strategy on the camera and 4D imaging radar fusion-based 3D object detection. In the proposed model, LXL, predicted image depth distribution maps and radar 3D occupancy grids are utilized to aid image view transformation, called "radar occupancy-assisted depth-based sampling". Experiments on VoD and TJ4DRadSet datasets show that the proposed method outperforms existing 3D object detection methods by a significant margin without bells and whistles. Ablation studies demonstrate that our method performs the best among different enhancement settings

RICD: A rice indica cDNA database resource for rice functional genomics

<p>Abstract</p> <p>Background</p> <p>The <it>Oryza sativa </it>L. <it>indica </it>subspecies is the most widely cultivated rice. During the last few years, we have collected over 20,000 putative full-length cDNAs and over 40,000 ESTs isolated from various cDNA libraries of two <it>indica </it>varieties Guangluai 4 and Minghui 63. A database of the rice <it>indica </it>cDNAs was therefore built to provide a comprehensive web data source for searching and retrieving the <it>indica </it>cDNA clones.</p> <p>Results</p> <p>Rice <it>Indica </it>cDNA Database (RICD) is an online MySQL-PHP driven database with a user-friendly web interface. It allows investigators to query the cDNA clones by keyword, genome position, nucleotide or protein sequence, and putative function. It also provides a series of information, including sequences, protein domain annotations, similarity search results, SNPs and InDels information, and hyperlinks to gene annotation in both The Rice Annotation Project Database (RAP-DB) and The TIGR Rice Genome Annotation Resource, expression atlas in RiceGE and variation report in Gramene of each cDNA.</p> <p>Conclusion</p> <p>The online rice <it>indica </it>cDNA database provides cDNA resource with comprehensive information to researchers for functional analysis of <it>indica </it>subspecies and for comparative genomics. The RICD database is available through our website <url>http://www.ncgr.ac.cn/ricd</url>.</p

Ethyl 2-{[(1Z)-(3-methyl-5-oxo-1-phenyl-4,5-dihydro-1H-pyrazol-4-yl­idene)(p-tol­yl)meth­yl]amino}-3-phenyl­propanoate

The asymmetric unit of the title compound, C29H29N3O3, contains two mol­ecules, which exist in their enamine–keto form, being stabilized by strong intra­molecular N—H⋯O hydrogen bonds, which generate S(6) loops. In the crystal, inter­molecular C–H⋯O hydrogen bonds link the mol­ecules into chains, which are further linked by weak C—H⋯π inter­actions, forming a two-dimensional network

Ecofriendly electrospun membranes loaded with visible-light-responding nanoparticles for multifunctional usages : highly efficient air filtration, dye scavenging, and bactericidal activity

Ambient particulate matter pollution has posed serious threats to global environment and public health. However, highly efficient filtration of submicron particles, the so-named "secondary pollution" caused by, e.g., bacterial growth in filters and the use of nondegradable filter materials, remains a serious challenge. In this study, poly(vinyl alcohol) (PVA) and konjac glucomannan (KGM)-based nanofiber membranes, loaded with ZnO nanoparticles, were prepared through green electrospinning and ecofriendly thermal cross-linking. Thus obtained fibrous membranes not only show highly efficient air-filtration performance but also show superior photocatalytic activity and antibacterial activity. The filtration efficiency of the ZnO@PVA/KGM membranes for ultrafine-particles (300 nm) was higher than 99.99%, being superior to that of commercial HEPA filters. By virtue of the high photocatalytic activity, methyl orange was efficiently decolorized with a removal efficiency of more than 98% at an initial concentration of 20 mg under 120 min of solar irradiation. A multifunctional membrane with high removal efficiency, low flow resistance, superior photocatalytic activity, and superior antibacterial activity was successfully achieved. It is conceivable that the combination of a biodegradable polymer and an active metal particle would form an unprecedented photocatalytic system, which will be quite promising for environmental remediation such as air filtration and water treatment

Foodborne Pathogens of Enterobacteriaceae, Their Detection and Control

Foodborne pathogens of Enterobacteriaceae including Escherichia coli, Salmonella, Shigella, Yersinia, etc., causes a great number of diseases and has a significant impact on human health. Here, we reviewed the prevalence, virulence, and antimicrobial susceptibility of Enterobacteriaceae belonging to 4 genera: E. coli, Salmonella, Shigella, and Yersinia. The routes of the pathogens’ transmission in the food chain; the antimicrobial resistance, genetic diversity, and molecular epidemiology of the Enterobacteriaceae strains; novel technologies for detection of the bacterial communities (such as the molecular marker-based methods, Immunoaffinity based detection, etc.); and the controlling of the foodborne pathogens using chemical/natural compounds or physical methods (such as UV-C and pulsed-light treatment, etc.), is also summarized