Conditional Support Alignment for Domain Adaptation with Label Shift

Unsupervised domain adaptation (UDA) refers to a domain adaptation framework in which a learning model is trained based on the labeled samples on the source domain and unlabelled ones in the target domain. The dominant existing methods in the field that rely on the classical covariate shift assumption to learn domain-invariant feature representation have yielded suboptimal performance under the label distribution shift between source and target domains. In this paper, we propose a novel conditional adversarial support alignment (CASA) whose aim is to minimize the conditional symmetric support divergence between the source's and target domain's feature representation distributions, aiming at a more helpful representation for the classification task. We also introduce a novel theoretical target risk bound, which justifies the merits of aligning the supports of conditional feature distributions compared to the existing marginal support alignment approach in the UDA settings. We then provide a complete training process for learning in which the objective optimization functions are precisely based on the proposed target risk bound. Our empirical results demonstrate that CASA outperforms other state-of-the-art methods on different UDA benchmark tasks under label shift conditions

A Turn-On Fluorescence-Based Fibre Optic Sensor for the Detection of Mercury

The design, development, and evaluation of an optical fibre sensor for the detection of Hg2+ in aqueous media are discussed in detail in this paper. A novel fluorescent polymeric material for Hg2+ detection, based on a coumarin derivative (acting as the fluorophore) and an azathia crown ether moiety (acting as the mercury ion receptor), has been synthesized. The fluorophore was covalently immobilized onto the fibre surface by polymerisation using the ion imprinting technique and exhibited a significant increase in fluorescence intensity in response to Hg2+ via a photoinduced electron transfer (PET) mechanism. The sensor provided a response over a concentration range of 0–28 µM with an acceptable response rate of around 11 min and a recovery rate of around 30 min in a Tris-EDTA buffer solution. A detection limit of 0.15 µM was obtained with a possibility of improvement by changing the thickness of the polymer layer and using a more sensitive detector. High-quality performance is seen through a high selectivity for Hg2+ over other metal ions, excellent photo-stability and reversibility which was also demonstrated, making this type of sensor potentially well suited for in-situ monitoring of mercury in the environment

The effect of deuteration on organic magnetoresistance

NOTICE: this is the author’s version of a work that was accepted for publication in Synthetic Metals. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in SYNTHETIC METALS, 161, 7-8, (2011) DOI 10.1016/j.synthmet.2010.11.04

Solitude profiles and psychological adjustment in Chinese late adolescence: a person-centered research

Objectives: From the perspective of person-centered research, the present study aimed to identify the potential profiles of solitude among late adolescents based on their solitary behavior, motivation, attitude, and time alone. In addition, to echo the paradox of solitude, we further explored the links between solitude profiles and adjustment outcomes.Methods: The participants of the study were 355 late adolescents (56.34% female, M age = 19.71 years old) at three universities in Shanghai, China. Measures of solitary behavior, autonomous motivation for solitude, attitude toward being alone, and time spent alone were collected using adolescents' self-report assessments. The UCLA Loneliness Scale, the Beck Depression Inventory, and the Basic Psychological Needs Scales were measured as indices of adjustment.Results: Latent profile analysis revealed four distinct groups: absence of the aloneness group (21.13%), the positive motivational solitude group (29.01%), the negative motivational solitude group (38.03%), and the activity-oriented solitude group (11.83%). Differences emerged among these four groups in terms of loneliness, depressive symptoms, and basic needs satisfaction, with adolescents in the negative motivational solitude group facing the most risk of psychological maladjustment.Conclusion: Findings revealed the possible heterogeneous nature of solitude among Chinese late adolescents and provided a theoretical basis for further understanding of adolescents' solitary state

On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation

Constructing a robust model that can effectively generalize to test samples under distribution shifts remains a significant challenge in the field of medical imaging. The foundational models for vision and language, pre-trained on extensive sets of natural image and text data, have emerged as a promising approach. It showcases impressive learning abilities across different tasks with the need for only a limited amount of annotated samples. While numerous techniques have focused on developing better fine-tuning strategies to adapt these models for specific domains, we instead examine their robustness to domain shifts in the medical image segmentation task. To this end, we compare the generalization performance to unseen domains of various pre-trained models after being fine-tuned on the same in-distribution dataset and show that foundation-based models enjoy better robustness than other architectures. From here, we further developed a new Bayesian uncertainty estimation for frozen models and used them as an indicator to characterize the model's performance on out-of-distribution (OOD) data, proving particularly beneficial for real-world applications. Our experiments not only reveal the limitations of current indicators like accuracy on the line or agreement on the line commonly used in natural image applications but also emphasize the promise of the introduced Bayesian uncertainty. Specifically, lower uncertainty predictions usually tend to higher out-of-distribution (OOD) performance.Comment: Advances in Neural Information Processing Systems (NeurIPS) 2023, Workshop on robustness of zero/few-shot learning in foundation model

RNA polymerase II stalling promotes nucleosome occlusion and pTEFb recruitment to drive immortalization by Epstein-Barr virus

Epstein-Barr virus (EBV) immortalizes resting B-cells and is a key etiologic agent in the development of numerous cancers. The essential EBV-encoded protein EBNA 2 activates the viral C promoter (Cp) producing a message of ~120 kb that is differentially spliced to encode all EBNAs required for immortalization. We have previously shown that EBNA 2-activated transcription is dependent on the activity of the RNA polymerase II (pol II) C-terminal domain (CTD) kinase pTEFb (CDK9/cyclin T1). We now demonstrate that Cp, in contrast to two shorter EBNA 2-activated viral genes (LMP 1 and 2A), displays high levels of promoter-proximally stalled pol II despite being constitutively active. Consistent with pol II stalling, we detect considerable pausing complex (NELF/DSIF) association with Cp. Significantly, we observe substantial Cp-specific pTEFb recruitment that stimulates high-level pol II CTD serine 2 phosphorylation at distal regions (up to +75 kb), promoting elongation. We reveal that Cp-specific pol II accumulation is directed by DNA sequences unfavourable for nucleosome assembly that increase TBP access and pol II recruitment. Stalled pol II then maintains Cp nucleosome depletion. Our data indicate that pTEFb is recruited to Cp by the bromodomain protein Brd4, with polymerase stalling facilitating stable association of pTEFb. The Brd4 inhibitor JQ1 and the pTEFb inhibitors DRB and Flavopiridol significantly reduce Cp, but not LMP1 transcript production indicating that Brd4 and pTEFb are required for Cp transcription. Taken together our data indicate that pol II stalling at Cp promotes transcription of essential immortalizing genes during EBV infection by (i) preventing promoter-proximal nucleosome assembly and ii) necessitating the recruitment of pTEFb thereby maintaining serine 2 CTD phosphorylation at distal regions

Optical Fiber-Based Heavy Metal Detection Using the Localized Surface Plasmon Resonance Technique

An innovative, reflection-based localized surface plasmon resonance (LSPR) fiber-optic sensor has been developed and demonstrated to detect the concentration of several heavy metal lead ions in an aqueous solution. By using a self-assembling technique, gold nanoparticles (Au NPs) have been immobilized on an optical fiber surface and functionalized with 1,1-Mercaptoundecanoic acid (MUA; HS(CH2)10CO2H) in order to make the fiber selective to each the important heavy metal ion, Pb2+ or Cd2+. The concentration of the heavy metal then can be determined from the link between binding rate and the shift of the LSPR resonance wavelength. The Pb2+ ion sensitivity of the sensor thus created has been determined to be 0.28 nm/mM, with a typical response time of 30 seconds. Importantly, the probe has been shown to be reversible through a simple process involving the use of Ethylenedinitrilotetraacetic acid (EDTA;(HO2CCH2)2NCH2 CH2N(CH2CO2H)2) chelator to remove the bound heavy metal ion

Optical fibre thermometry using ratiometric green emission of an upconverting nanoparticle- polydimethylsiloxane composite

The thermally coupled green band emission from excited Er 3+ ions has been used in the past to create optical thermometers, by doping the material in various types of media, particularly glasses. Glasses are known to be excellent hosts for Er 3+ ions: however, high temperatures (>900 K) are usually required for doping these ions into glasses and a non-linear temperature response is often produced. In this work, the frequently encountered drawbacks of glass-based temperature sensors have been addressed by developing a temperature sensor created at a lower temperature (543 K), by dip-coating chemically synthesized upconverting nanoparticles (UCNP-NaYF4:(18%) Yb 3+ , (2%) Er 3+) embedded in polydimethylsiloxane (PDMS) onto the tip of a 1000 μm optical fibre, to create the actual fibre probe. The sensor shows an excellent linear response (R 2 = 0.991) over a very useful temperature range of 295 K-473 K, with a sensitivity of 2.9 ×10-3 K-1 , a temperature resolution of ± 2.7 K and response time of ~ 5 seconds. Additionally, a probe was investigated 2 where a pure upconverting nanoparticle powder was coated on the tip of optical fibre and its spectral and temperature response was obtained (and cross compared with that of UCNP-PDMS composite). The results obtained from the probe development work show that the UCNP-PDMS-coated optical fibre temperature sensor developed offers a better alternative to more conventional Er 3+ doped glass-based temperature sensors, in terms of the thermal budget, the synthesis process and the ease of coating, creating as a result, a very linear device response