Spectral Line De-confusion in an Intensity Mapping Survey

Spectral line intensity mapping has been proposed as a promising tool to efficiently probe the cosmic reionization and the large-scale structure. Without detecting individual sources, line intensity mapping makes use of all available photons and measures the integrated light in the source confusion limit, to efficiently map the three-dimensional matter distribution on large scales as traced by a given emission line. One particular challenge is the separation of desired signals from astrophysical continuum foregrounds and line interlopers. Here we present a technique to extract large-scale structure information traced by emission lines from different redshifts, embedded in a three-dimensional intensity mapping data cube. The line redshifts are distinguished by the anisotropic shape of the power spectra when projected onto a common coordinate frame. We consider the case where high-redshift [CII] lines are confused with multiple low-redshift CO rotational lines. We present a semi-analytic model for [CII] and CO line estimates based on the cosmic infrared background measurements, and show that with a modest instrumental noise level and survey geometry, the large-scale [CII] and CO power spectrum amplitudes can be successfully extracted from a confusion-limited data set, without external information. We discuss the implications and limits of this technique for possible line intensity mapping experiments.Comment: 13 pages, 14 figures, accepted by Ap

Understanding factors relevant to poor sleep and coping methods in people with schizophrenia

Background Sleep disruption is pervasive in people with schizophrenia, but few studies have explored their sleep experiences. This study aims to identify factors relevant to sleep problems and explore coping methods used by community-dwelling people with schizophrenia. Methods Eighteen participants with schizophrenia were recruited from three mental health centers in Taiwan. They completed a semi-structured interview and the Pittsburgh Sleep Quality Index (PSQI) assessment. The Person-Environment-Occupation model offered a framework to assess factors related to sleep. Thematic analysis was used for the qualitative data analysis. Results Factors related to sleep were classified under person, environment, and occupation domains. The person domain included three subthemes: psychiatric symptoms, unpleasant emotions, and frustration about sleep. The environment domain included three subthemes: sensory intrusions from the environment, quality of bedding, and roommates. The occupation domain included sleep interruption and sleep preparation. There were notable discrepancies in sleep quality between the participants’ narratives and their PSQI global scores. Regarding coping methods for poor sleep, sleep medication was the primary strategy while some participants also used other strategies, such as modifying the environment, adjusting routines, or engaging in activities that improve sleep quality. Conclusions Psychiatric symptoms and nightmares were identified as unique sleep disruptions in people with schizophrenia, and poor economic status was also found to impact their sleep. The sleep quality of people with schizophrenia tends to be poor, as identified by the PSQI, even though they may have positive perceptions of their sleep quality. Our participants appeared to prefer to take hypnotics to address their sleep problems, which may be due to limited knowledge about alternatives. Mental health professionals are encouraged to receive training in the application of non-pharmacological approaches to support their clients’ issues related to sleep

Is the Radio Source Dipole from NVSS Consistent with the CMB and Λ\LambdaCDM?

The dipole moment in the angular distribution of the cosmic microwave background (CMB) is thought to originate from the Doppler Effect and our motion relative to the CMB frame. Observations of large-scale structure (LSS) should show a related "kinematic dipole" and help test the kinematic origin of the CMB dipole. Intriguingly, many previous LSS dipole studies suggest discrepancies with the expectations from the CMB. Here we reassess the apparent inconsistency between the CMB measurements and dipole estimates from the NVSS catalog of radio sources. We find that it is important to account for the shot-noise and clustering of the NVSS sources, as well as kinematic contributions, in determining the expected dipole signal. We use the clustering redshift method and a cross-matching technique to refine estimates of the clustering term. We then derive a probability distribution for the expected NVSS dipole in a standard $\Lambda$CDM cosmological model including all (i.e., kinematic, shot-noise and clustering) dipole components. Our model agrees with most of the previous NVSS dipole measurements in the literature at better than $\lesssim 2\sigma$. We conclude that the NVSS dipole is consistent with a kinematic origin for the CMB dipole within $\Lambda$CDM.Comment: 24 pages, 9 figures, submitted to Ap

Out-Of-Band Management on UEFI System Firmware

The modern Redfish is a specification that utilize RESTful interface semantics to access data defined in model format to perform out-of-band (OOB) management through specific OOB software or hardware (such as Baseboard Management Controller, BMC). The OOB management allow users to configure system remotely when the system is in either power-off or power-on state. Industry can expect there are more and more pre-boot firmware drivers (like UEFI drivers) and system peripherals (such as PCI devices, PCI add-on-card and so on) support Redfish Schema/Configuration data model in the near future. This article describes the method to abstract the data communication/synchronization between UEFI drivers and OOB management on UEFI firmware environment. Furthermore, this article is not only restricted to single OOB management on system, the abstracts method described in this article is flexible and extensible to support multiple OOB management instances on one system simultaneously. Not only Redfish OOB management data model is supported, this article fulfills the requirements of any other data model of OOB managements such as OData XML/JSON data model, CIM-XML data model, 3rd party data model and etc

KL-Divergence Guided Temperature Sampling

Temperature sampling is a conventional approach to diversify large language model predictions. As temperature increases, the prediction becomes diverse but also vulnerable to hallucinations -- generating tokens that are sensible but not factual. One common approach to mitigate hallucinations is to provide source/grounding documents and the model is trained to produce predictions that bind to and are attributable to the provided source. It appears that there is a trade-off between diversity and attribution. To mitigate any such trade-off, we propose to relax the constraint of having a fixed temperature over decoding steps, and a mechanism to guide the dynamic temperature according to its relevance to the source through KL-divergence. Our experiments justifies the trade-off, and shows that our sampling algorithm outperforms the conventional top-k and top-p algorithms in conversational question-answering and summarization tasks

Translation-Enhanced Multilingual Text-to-Image Generation

Research on text-to-image generation (TTI) still predominantly focuses on the English language due to the lack of annotated image-caption data in other languages; in the long run, this might widen inequitable access to TTI technology. In this work, we thus investigate multilingual TTI (termed mTTI) and the current potential of neural machine translation (NMT) to bootstrap mTTI systems. We provide two key contributions. 1) Relying on a multilingual multi-modal encoder, we provide a systematic empirical study of standard methods used in cross-lingual NLP when applied to mTTI: Translate Train, Translate Test, and Zero-Shot Transfer. 2) We propose Ensemble Adapter (EnsAd), a novel parameter-efficient approach that learns to weigh and consolidate the multilingual text knowledge within the mTTI framework, mitigating the language gap and thus improving mTTI performance. Our evaluations on standard mTTI datasets COCO-CN, Multi30K Task2, and LAION-5B demonstrate the potential of translation-enhanced mTTI systems and also validate the benefits of the proposed EnsAd which derives consistent gains across all datasets. Further investigations on model variants, ablation studies, and qualitative analyses provide additional insights on the inner workings of the proposed mTTI approaches.Comment: ACL 2023 (Main

Privacy-aware reversible watermarking in cloud computing environments

As an interdisciplinary research between watermarking and cryptography, privacy-aware reversible watermarking permits a party to entrust the task of embedding watermarks to a cloud service provider without compromising information privacy. The early development of schemes were primarily based upon traditional symmetric-key cryptosystems, which involve an extra implementation cost of key exchange. Although recent research attentions were drawn to schemes compatible with asymmetric-key cryptosystems, there were notable limitations in the practical aspects. In particular, the host signal must either be enciphered in a redundant way or be pre-processed prior to encryption, which would largely limit the storage efficiency and scheme universality. To relax the restrictions, we propose a novel research paradigm and devise different schemes compatible with different homomorphic cryptosystems. In the proposed schemes, the encoding function is recognised as an operation of adding noise, whereas the decoding function is perceived as a corresponding denoising process. Both online and offline contentadaptive predictors are developed to assist watermark decoding for various operational requirements. A three-way trade-off between the capacity, fidelity and reversibility is analysed mathematically and empirically. It is shown that the proposed schemes achieve the state-the-art performance