More Context, Less Distraction: Visual Classification by Inferring and Conditioning on Contextual Attributes

CLIP, as a foundational vision language model, is widely used in zero-shot image classification due to its ability to understand various visual concepts and natural language descriptions. However, how to fully leverage CLIP's unprecedented human-like understanding capabilities to achieve better zero-shot classification is still an open question. This paper draws inspiration from the human visual perception process: a modern neuroscience view suggests that in classifying an object, humans first infer its class-independent attributes (e.g., background and orientation) which help separate the foreground object from the background, and then make decisions based on this information. Inspired by this, we observe that providing CLIP with contextual attributes improves zero-shot classification and mitigates reliance on spurious features. We also observe that CLIP itself can reasonably infer the attributes from an image. With these observations, we propose a training-free, two-step zero-shot classification method named PerceptionCLIP. Given an image, it first infers contextual attributes (e.g., background) and then performs object classification conditioning on them. Our experiments show that PerceptionCLIP achieves better generalization, group robustness, and better interpretability. For example, PerceptionCLIP with ViT-L/14 improves the worst group accuracy by 16.5% on the Waterbirds dataset and by 3.5% on CelebA

On the Possibilities of AI-Generated Text Detection

Our work focuses on the challenge of detecting outputs generated by Large Language Models (LLMs) from those generated by humans. The ability to distinguish between the two is of utmost importance in numerous applications. However, the possibility and impossibility of such discernment have been subjects of debate within the community. Therefore, a central question is whether we can detect AI-generated text and, if so, when. In this work, we provide evidence that it should almost always be possible to detect the AI-generated text unless the distributions of human and machine generated texts are exactly the same over the entire support. This observation follows from the standard results in information theory and relies on the fact that if the machine text is becoming more like a human, we need more samples to detect it. We derive a precise sample complexity bound of AI-generated text detection, which tells how many samples are needed to detect. This gives rise to additional challenges of designing more complicated detectors that take in n samples to detect than just one, which is the scope of future research on this topic. Our empirical evaluations support our claim about the existence of better detectors demonstrating that AI-Generated text detection should be achievable in the majority of scenarios. Our results emphasize the importance of continued research in this are

Metabolic Interaction of the Active Constituents of Coptis chinensis

Coptis chinensis is commonly used in traditional Chinese medicine. The study investigated metabolic interaction of the active constituents (berberine, coptisine, palmatine, and jatrorrhizine) of Coptis chinensis in human liver microsomes. After incubation of the four constituents of Coptis chinensis in HLMs, the metabolism of the four constituents was observed by HPLC. The in vitro inhibition experiment between the active constituents was conducted, and IC50 value was estimated. Coptisine exhibited inhibitions against the formation of the two metabolites of berberine with IC50 values of 6.5 and 8.3 μM, respectively. Palmatine and jatrorrhizine showed the weaker inhibitory effect on the formation of the metabolites of berberine. Berberine showed a weak inhibitory effect on the production of coptisine metabolite with an IC50 value of 115 μM, and palmatine and jatrorrhizine had little inhibitory effect on the formation of coptisine metabolite. Berberine, coptisine, and jatrorrhizine showed no inhibitory effect on the generation of palmatine metabolite (IC50 > 200 μM). The findings suggested that there are different degrees of metabolic interaction between the four components. Coptisine showed the strongest inhibition toward berberine metabolism

Specific, simple and rapid detection of porcine circovirus type 2 using the loop-mediated isothermal amplification method

<p>Abstract</p> <p>Background</p> <p>Porcine circovirus type 2 (PCV2) is the causative agent of postweaning multisystemic wasting syndrome (PMWS), and porcine dermatitis and nephropathy syndrome (PDNS). It has caused heavy losses in global agriculture in recent decades. Rapid detection of PCV2 is very important for the effective prophylaxis and treatment of PMWS.</p> <p>Results</p> <p>A loop-mediated isothermal amplification (LAMP) assay was used to detect PCV2 in this study. Three pairs of primers were specially designed for recognizing eight distinct sequences of the ORF2 gene. This gene lies in the PCV2 virus genome sequence, and encodes the Rep protein that is involved in virus replication. Time and temperature conditions for amplification of PCV2 genes were optimized to be 55 min at 59°C. The analysis of clinical samples indicated that the LAMP method was highly sensitive. The detection limit for PCV2 by the LAMP assay was 10 copies, whereas the limit by conventional PCR was 1000 copies. The assay did not cross-react with PCV1, porcine reproductive and respiratory syndrome virus, porcine epidemic diarrhea virus, transmissible gastroenteritis of pigs virus or rotavirus. When 110 samples were tested using the established LAMP system, 95 were detected as positive.</p> <p>Conclusion</p> <p>The newly developed LAMP detection method for PCV2 was more specific, sensitive, rapid and simple than before. It complements and extends previous methods for PCV2 detection and provides an alternative approach for detection of PCV2.</p

Efficient wide-bandgap perovskite solar cells with open-circuit voltage deficit below 0.4 V via hole-selective interface engineering

Wide-bandgap mixed-halide perovskite solar cells (WBG-PSCs) are promising top cells for efficient tandem photovoltaics to achieve high power conversion efficiency (PCE) at low cost. However, the open-circuit voltage (VOC) of WBG-PSCs is still unsatisfactory as the VOC-deficit is generally larger than 0.45 V. Herein, we report a buried interface engineering strategy that substantially improves the VOC of WBG-PSCs by inserting amphophilic molecular hole-selective materials featuring with a cyanovinyl phosphonic acid (CPA) anchoring group between the perovskite and substrate. The assembly and redistribution of CPA-based amphiphilic molecules at the perovskite-substrate buried interface not only promotes the growth of a low-defect crystalline perovskite thin film, but also suppresses the photo-induced halide phase separation. The energy level alignment between wide-bandgap perovskite and the hole-selective layer is further improved by modulating the substituents on the triphenylamine donor moiety (methoxyls for MPA-CPA, methyls for MePA-CPA, and bare TPA-CPA). Using a 1.68 eV bandgap perovskite, the MePA-CPA-based devices achieved an unprecedentedly high VOC of 1.29 V and PCE of 22.3% under standard AM 1.5 sunlight. The VOC-deficit (&lt;0.40 V) is the lowest value reported for WBG-PSCs. This work not only provides an effective approach to decreasing the VOC-deficit of WBG-PSCs, but also confirms the importance of energy level alignment at the charge-selective layers in PSCs.</p

Disrupted asymmetry of inter- and intra-hemispheric functional connectivity in patients with drug-naive, first-episode schizophrenia and their unaffected siblings

BACKGROUND: Lack of normal asymmetry in the brain has been reported in patients with schizophrenia. However, it remains unclear whether disrupted asymmetry originates from inter-hemispheric functional connectivity (FC) and/or intra-hemispheric FC in this patient population. METHODS: Forty-four patients with drug-naive, first-episode schizophrenia, 42 unaffected siblings, and 44 healthy controls underwent resting-state functional magnetic resonance imaging (fMRI) scan. The parameter of asymmetry (PAS) and support vector machine (SVM) were used to analyze the data. Patients were treated with olanzapine for 8 weeks. FINDINGS: Compared with healthy controls, patients showed lower PAS scores in the left middle temporal gyrus (MTG)/inferior temporal gyrus (ITG), left posterior cingulate cortex (PCC)/precuneus and left angular gyrus, and higher PAS scores in the left precentral gyrus/postcentral gyrus. Unaffected siblings also showed lower PAS scores in the left MTG/ITG and left PCC/precuneus relative to healthy controls. Further, SVM analysis showed that a combination of the PAS scores in these two clusters in patients at baseline was able to predict clinical response after 8weeks of olanzapine treatment with 77.27% sensitivity, 72.73% specificity, and 75.00% accuracy. INTERPRETATION: The present study suggests disrupted asymmetry of inter- and intra-hemispheric FC in drug-naive, first-episode schizophrenia; in addition, a reduced asymmetry of inter-hemispheric FC in the left MTG/ITG and left PCC/precuneus may serve as an endophenotype for schizophrenia, and may have clinical utility to predict response to olanzapine treatment. FUND: The National Key RandD Program of China and the National Natural Science Foundation of China