A multi-channel integrated auditory function test system.

The auditory brainstem response (ABR) remains the gold standard for evaluating hearing function in both animal models and humans. Features of ABR, including threshold, wave I amplitude and latency are critical for diagnosing and investigating the mechanisms of hearing loss. Critically, the rapid proliferation of genetically engineered mouse models in hearing research has created an imperative demand for high-throughput ABR testing capabilities.

An Integrated System for Comprehensive Mouse Peripheral Vestibular Function Evaluation Based on Vestibulo-ocular Reflex.

Purpose: In the fields of both vestibular and auditory research, reliable vestibular function tests are essential. However, unlike the auditory function tests, which use standard Auditory Brainstem Response (ABR) equipment, there is no equivalent widely adopted apparatus for vestibular tests. Vestibulo-ocular reflexes (VORs) are the compensatory ocular reflexes that ensure stable vision during head motion.

Co-occurrence of microbial source tracking markers and antibiotic resistance genes in Chishui River, China.

Fecal contamination is an important source for the emergence of antibiotic resistance genes (ARGs) worldwide. Identifying the host sources of ARG contamination and distinguishing whether the increased abundance of ARGs in the environment is due to on-site selection or the result of fecal contamination can effectively protect water quality and predict human health risks. In this study, the occurrence of 5 ARGs (, , , , and ), 1 mobile element 1 and 7 microbial source tracker (MST) markers (CPQ_064, BacHum, Rum-2-Bac, BacCow, P.

Semicircular Canals Input Can Modify the Fast-Phase Nystagmus in Off-Vertical Axis Rotation of Mice.

Vestibular research is essential for understanding and treating disorders such as vertigo and Meniere's disease. The vestibulo-ocular reflex (VOR) is a key method for assessing vestibular function and an essential tool for diagnosing vertigo. Traditionally, the VOR comprises angular VOR (aVOR) and translational VOR (tVOR), which originate from the vestibular semicircular canals (SCCs) and otolith organs, respectively.

A loop-mediated isothermal amplification assay for the rapid and quantitative tracking of fecal contamination sources in water.

Fecal contamination in water poses a serious threat to public health and the ecological environment. Numerous qPCR-based methods have been used to identify the source of fecal contamination, but this method relies on expensive equipment, well-established laboratory conditions, and experienced personnel, significantly reducing the timeliness of identifying contamination sources. Here, we developed a loop-mediated isothermal amplification (LAMP) assay for tracking the sources of fecal contamination to rapid identifying and quantifying humans, ruminants, pigs, and poultry fecal contamination.

Effects of Curing Conditions on Pore Structure of Ultra-High-Strength Shotcrete (UHSSC) Based on X-ray Computed Tomography.

Shotcrete is widely used in mine and civil engineering as supporting structure. A new type of ultra-high-strength shotcrete (UHSSC) with viscosity-enhancing agent was taken as the research object in this paper. A microstructure model of UHSSC under different curing conditions (standard curing, natural curing and film curing) was reconstructed using X-ray computed tomography (X-CT).

Research on Microwave Pyrolysis Recovery and Reuse Performance of Carbon Fiber Composites.

Carbon fiber-reinforced resin matrix composites find extensive applications across various industries. However, their widespread use also generates significant waste, leading to resource depletion and environmental concerns. Studying the production of composite materials using recovered carbon fiber is imperative to mitigate the environmental impact associated with waste from carbon fiber-reinforced resin matrix composites and optimize resource utilization.

Bacterial community succession and the enrichment of antibiotic resistance genes on microplastics in an oyster farm.

Microplastics can be colonized by microorganisms and form plastisphere. However, knowledge of bacterial community succession and the enrichment of antibiotic resistance genes (ARGs) and pathogens on microplastics in aquaculture environments is limited. Here, we conducted a 30-day continuous exposure experiment at an oyster farm.

Distribution and correlation between antibiotic resistance genes and host-associated markers before and after swine fever in the longjiang watershed.

Antibiotic resistance genes (ARGs) are abundantly shed in feces. Thus, it is crucial to identify their host sources so that ARG pollution can be effectively mitigated and aquatic ecosystems can be properly conserved. Here, spatiotemporal variations and sources of ARGs in the Longjiang watershed of South China were investigated by linking them with microbial source tracker (MST) indicators.

Pulsed infrared stimulation evoked electrical potential in mouse vestibular system.

To improve accuracy of VsEP and avoid the inherent limitation of mechanical vibration, we designed an infrared optical stimulation approach to stimulate mouse vestibular system and measured the evoked potential. IR pulses (1871 nm, 30 pps and 100 μs pulse width) were delivered to mice with different vestibular dysfunction levels and the evoked potential was recorded. The result suggests that the amplitude and latency of the IR-evoked potential (IR-VsEP) were significantly associated with vestibular function integrity.

Structured AutoEncoders for Subspace Clustering.

Existing subspace clustering methods typically employ shallow models to estimate underlying subspaces of unlabeled data points and cluster them into corresponding groups. However, due to the limited representative capacity of the employed shallow models, those methods may fail in handling realistic data without the linear subspace structure. To address this issue, we propose a novel subspace clustering approach by introducing a new deep model-Structured AutoEncoder (StructAE).

Robust Kernel Low-Rank Representation.

Recently, low-rank representation (LRR) has shown promising performance in many real-world applications such as face clustering. However, LRR may not achieve satisfactory results when dealing with the data from nonlinear subspaces, since it is originally designed to handle the data from linear subspaces in the input space. Meanwhile, the kernel-based methods deal with the nonlinear data by mapping it from the original input space to a new feature space through a kernel-induced mapping.

A Unified Framework for Representation-Based Subspace Clustering of Out-of-Sample and Large-Scale Data.

Under the framework of spectral clustering, the key of subspace clustering is building a similarity graph, which describes the neighborhood relations among data points. Some recent works build the graph using sparse, low-rank, and l -norm-based representation, and have achieved the state-of-the-art performance. However, these methods have suffered from the following two limitations.

Automatic face naming by learning discriminative affinity matrices from weakly labeled images.

Given a collection of images, where each image contains several faces and is associated with a few names in the corresponding caption, the goal of face naming is to infer the correct name for each face. In this paper, we propose two new methods to effectively solve this problem by learning two discriminative affinity matrices from these weakly labeled images. We first propose a new method called regularized low-rank representation by effectively utilizing weakly supervised information to learn a low-rank reconstruction coefficient matrix while exploring multiple subspace structures of the data.