Persistent Test-time Adaptation in Episodic Testing Scenarios

Current test-time adaptation (TTA) approaches aim to adapt to environments that change continuously. Yet, when the environments not only change but also recur in a correlated manner over time, such as in the case of day-night surveillance cameras, it is unclear whether the adaptability of these methods is sustained after a long run. This study aims to examine the error accumulation of TTA models when they are repeatedly exposed to previous testing environments, proposing a novel testing setting called episodic TTA. To study this phenomenon, we design a simulation of TTA process on a simple yet representative $\epsilon$-perturbed Gaussian Mixture Model Classifier and derive the theoretical findings revealing the dataset- and algorithm-dependent factors that contribute to the gradual degeneration of TTA methods through time. Our investigation has led us to propose a method, named persistent TTA (PeTTA). PeTTA senses the model divergence towards a collapsing and adjusts the adaptation strategy of TTA, striking a balance between two primary objectives: adaptation and preventing model collapse. The stability of PeTTA in the face of episodic TTA scenarios has been demonstrated through a set of comprehensive experiments on various benchmarks

Trichinellosis in Vietnam

Trichinellosis is a zoonotic parasitic disease with a worldwide distribution. The aim of this work was to describe the epidemiological and clinical data of five outbreaks of trichinellosis, which affected ethnic minorities living in remote mountainous areas of northwestern Vietnam from 1970 to 2012. Trichinellosis was diagnosed in 126 patients, of which 11 (8.7%) were hospitalized and 8 (6.3%) died. All infected people had consumed raw pork from backyard and roaming pigs or wild boar at wedding, funeral, or New Year parties. The short incubation period (average of 9.5 days), the severity of the symptoms, which were characterized by diarrhea, abdominal pain, fever, myalgia, edema, weight loss, itch, and lisping, and the high mortality, suggest that patients had ingested a high number of larvae. The larval burden in pigs examined in one of the outbreaks ranged from 70 to 879 larvae/g. These larvae and those collected from a muscle biopsy taken from a patient from the 2012 outbreak were identified as Trichinella spiralis. Data presented in this work show that the northern regions of Vietnam are endemic areas for Trichinella infections in domestic pigs and humans

MaskDiff: Modeling Mask Distribution with Diffusion Probabilistic Model for Few-Shot Instance Segmentation

Few-shot instance segmentation extends the few-shot learning paradigm to the instance segmentation task, which tries to segment instance objects from a query image with a few annotated examples of novel categories. Conventional approaches have attempted to address the task via prototype learning, known as point estimation. However, this mechanism depends on prototypes (\eg mean of $K-$shot) for prediction, leading to performance instability. To overcome the disadvantage of the point estimation mechanism, we propose a novel approach, dubbed MaskDiff, which models the underlying conditional distribution of a binary mask, which is conditioned on an object region and $K-$shot information. Inspired by augmentation approaches that perturb data with Gaussian noise for populating low data density regions, we model the mask distribution with a diffusion probabilistic model. We also propose to utilize classifier-free guided mask sampling to integrate category information into the binary mask generation process. Without bells and whistles, our proposed method consistently outperforms state-of-the-art methods on both base and novel classes of the COCO dataset while simultaneously being more stable than existing methods. The source code is available at: https://github.com/minhquanlecs/MaskDiff.Comment: Accepted at AAAI 2024 (oral presentation

An identification of the tolerable time-interleaved analog-to-digital converter timing mismatch level in high-speed orthogonal frequency division multiplexing systems

High-speed Terahertz communication systems has recently employed orthogonal frequency division multiplexing approach as it provides high spectral efficiency and avoids inter-symbol interference caused by dispersive channels. Such high-speed systems require extremely high-sampling time-interleaved analog-to-digital converters at the receiver. However, timing mismatch of time-interleaved analog-to-digital converters significantly causes system performance degradation. In this paper, to avoid such performance degradation induced by timing mismatch, we theoretically determine maximum tolerable mismatch levels for orthogonal frequency division multiplexing communication systems. To obtain these levels, we first propose an analytical method to derive the bit error rate formula for quadrature and pulse amplitude modulations in Rayleigh fading channels, assuming binary reflected gray code (BRGC) mapping. Further, from the derived bit error rate (BER) expressions, we reveal a threshold of timing mismatch level for which error floors produced by the mismatch will be smaller than a given BER. Simulation results demonstrate that if we preserve mismatch level smaller than 25% of this obtained threshold, the BER performance degradation is smaller than 0.5 dB as compared to the case without timing mismatch

Status of the shore area from Tiengiang to Camau: causes of accumulation and erosion

The paper presents some results of the research programs which had been performed during 1996-1999 (“Studying of river-sea interaction in the mouth of Tien river” and KHCN.06.08). Based on these results the morphological schemes of the shore areas from Tiengiang to Camau were compiled; causes and mechanics of accumulation and erosion were also determined. These results may be used as scientific basis for forecasting the development of the shoreline, it will contribute to the management, protection and reasonable exploitation the shore areas

The Photocatalytic Activity of the Bi2O3-B2O3-ZnO-TiO2 Glass Coating

Due to the low melting temperature, the glazes based on the Bi2O3-B2O3-ZnO system are used as coatings on the surface of industrial glass substrates. Moreover, the composition of these coatings does not contain PbO, meeting the optical and environmental properties requirements. In this study, TiO2 was used in the Bi2O3-B2O3-ZnO glaze system to improve its photocatalytic ability. This can be considered a four – component glass system Bi2O3-B2O3-ZnO-TiO2. The heating microscopy results show that the melting temperature of the glaze system is 606 °C. The Fourier transform infrared spectroscopy results show that the TiO2 polyhedra are located independently in the structure without participating in forming a glass network. Thanks to that, the photocatalytic properties of TiO2 are maintained. The X-ray diffraction patterns results show that the formed TiO2 nanocrystals are rutile and anatase crystals. The results of determining the band gap energy using UV-Vis show that the band gap energy of the base glaze system increases with the addition of TiO2. The methylene blue decomposition results also showed that the ability to decompose organic increased when TiO2 was added to the glaze coating. The characteristics such as melting temperature, microstructure, and photocatalytic capacity of Bi2O3-B2O3-ZnO-TiO2 white glazes (5 and 10 % weight of TiO2) also were indicated in this paper

Cloning and expression of pigC gene in Escherichia coli

Prodigiosin (Pg), which is particularly of interest because of anticancer and antimicrobial activities, can be produced through the PigC-catalyzed condensation reaction of 4-methoxy-2, 2’-bipyrrole-5-carboxyaldehyde (MBC) and 2-methyl-3-amylpyrrole (MAP). Therefore, the PigC protein plays an important role in prodigiosin biosynthetic pathway. However, studies related to PigC protein have not been carried out in Vietnam yet. In this work, the pigC gene was cloned and expressed in Escherichia coli DH10B and BL21 (DE3), respectively. Using PCR and universal primers, we amplified a fragment of 3 kb covering entire coding region of the pigC gene from Serratia sp. strain M5. The pigC gene was inserted into pJET1.2 vector, and then transformed into E. coli DH10B. The sequence of a recombinant vector pJET1.2/pigC was evaluated by using whole colony PCR amplification. Sequence alignment results revealed that the obtained pigC gene possesses 71.5% and 75.4% of nucleotide identity in comparison with two strains, Serratia 39006 and Serratia sp. AS9 published in GenBank with their respective accession numbers of AJ833001 and CP002773. The recombinant vector pJET1.2/pigC was used to reamplify pigC, and the acquired amplicon was inserted into pET22b vector at the site of HindIII and XhoI. The clone E. coli BL21 (DE3) containing recombinant vector pET22b/pigC was expressed in the auto-induced medium. The presence of PigC protein in the lysate was identified as a 100 kDa band through Western Blot analysis using anti his-tag antibody. Afterward, the PigC protein was purified by Ni-NTA column, and its expression level was quantified through SDS-PAGE analysis. The results of our study provide a potential material for producing prodigiosin from recombinant protein in Vietnam

Chaotic Compressed Sensing and Its Application to Magnetic Resonance Imaging

Fast image acquisition in magnetic resonance imaging (MRI) is important, due to the need to find ways that help relieve patient’s stress during MRI scans. Methods for fast MRI have been proposed, most notably among them are pMRI (parallel MRI), SWIFT (SWeep Imaging with Fourier Transformation), and compressed sensing (CS) based MRI. Although it promises to significantly reduce acquisition time, applying CS to MRI leads to difficulties with hardware design because of the randomness nature of the measurement matrix used by the conventional CS methods. In this paper, we propose a novel method that combines the above-mentioned three approaches for fast MRI by designing a compound measurement matrix from a series of single measurement matrices corresponding to pMRI, SWIFT, and CS. In our method, the CS measurement matrix is designed to be deterministic via chaotic systems. This chaotic compressed sensing (CCS) measurement matrix, while retaining most features of the random CS matrix, is simpler to realize in hardware. Several compound measurement matrices have been constructed and examined in this work, including CCS-MRI, CCS-pMRI, CCS-SWIFT, and CCS-pSWIFT. Simulation results showed that the proposed method allows an increase in the speed of the MRI acquisition process while not compromising the quality of the acquired MR images