Effects of Hydrogen Plasma on the Electrical Properties of F-Doped ZnO Thin Films and p-i-n -Si:H Thin Film Solar Cells

1.5 wt% zinc fluoride (ZnF2) was mixed with zinc oxide powder to form the F-doped ZnO (FZO) composition. At first, the FZO thin films were deposited at room temperature and 5×10-3 Torr in pure Ar under different deposition power. Hall measurements of the as-deposited FZO thin films were investigated, and then the electrical properties were used to find the deposition power causing the FZO thin films with minimum resistance. The FZO thin films with minimum resistance were further treated by H2 plasma and then found their variations in the electrical properties by Hall measurements. Hydrochloric (HCl) acid solutions with different concentrations (0.1%, 0.2%, and 0.5%) were used to etch the surfaces of the FZO thin films. Finally, the as-deposited, HCl-etched as-deposited, and HCl-etched H2-plasma-treated FZO thin films were used as transparent electrodes to fabricate the p-i-n α-Si:H thin film solar cells and their characteristics were compared in this study. We would show that using H2-plasma-treated and HCl-etched FZO thin films as transparent electrodes would improve the efficiency of the fabricated thin film solar cells

Large, valley-exclusive Bloch-Siegert shift in monolayer WS2

Coherent interaction with off-resonance light can be used to shift the energy levels of atoms, molecules, and solids. The dominant effect is the optical Stark shift, but there is an additional contribution from the so-called Bloch-Siegert shift that has eluded direct and exclusive observation in solids. We observed an exceptionally large Bloch-Siegert shift in monolayer tungsten disulfide (WS[subscript 2]) under infrared optical driving. By controlling the light helicity, we could confine the Bloch-Siegert shift to occur only at one valley, and the optical Stark shift at the other valley, because the two effects obey opposite selection rules at different valleys. Such a large and valley-exclusive Bloch-Siegert shift allows for enhanced control over the valleytronic properties of two-dimensional materials.United States. Department of EnergyUnited States. Dept. of Energy. Division of Materials Sciences and EngineeringGordon and Betty Moore Foundation (EPiQS Initiative Grant GBMF4540)Harvard University. Center for Integrated Quantum Materials (Grant DMR-1231319

Body Mass Index–Mortality Relationship in Severe Hypoglycemic Patients With Type 2 Diabetes

AbstractBackgroundHypoglycemia is associated with a higher risk of death. This study analyzed various body mass index (BMI) categories and mortalities of severe hypoglycemic patients with type 2 diabetes mellitus (DM) in a hospital emergency department.MethodsThe study included 566 adults with type 2 diabetes who were admitted to 1 medical center in Taiwan between 2008 and 2009 with a diagnosis of severe hypoglycemia. Mortality data, demographics, clinical characteristics and the Charlson’s Comorbidity Index were obtained from the electronic medical records. Patients were stratified into 4 study groups as determined by the National institute of Health (NiH) and World Health organization classification for BMi, and the demographics were compared using the analysis of variance and χ2 test. Kaplan-Meier’s analysis and the Cox proportional-hazards regression model were used for mortality, and adjusted hazard ratios were adjusted for each BMi category among participants.ResultsAfter controlling for other possible confounding variables, BMI <18.5 kg/m2 was independently associated with low survival rates in the Cox regression analysis of the entire cohort of type 2 DM patients who encountered a hypoglycemic event. Compared to patients with normal BMI, the mortality risk was higher (adjusted hazard ratios = 4.9; 95% confidence interval [CI] = 2.4-9.9) in underweight patients. Infection-related causes of death were observed in 101 cases (69.2%) and were the leading cause of death.ConclusionsAn independent association was observed between BMI less than 18.5 kg/m2 and mortality among type 2 DM patient with severe hypoglycemic episode. Deaths were predominantly infection related

Konsep Demokrasi Politik Dalam Islam

Coexistence of chronic rhinosinusitis (CRS) with asthma appears to impair asthma control. Type-2 innate lymphoid cells (ILC2s) respond to the cytokines of thymic stromal lymphopoietin (TSLP), interleukin (IL)-25 and IL-33, thus contributing to airway diseases such as CRS and asthma. We investigate whether the augmented Th2-cytokines in CRS might be related to sinonasal tract ILC2s corresponding to enhanced IL-25, IL-33 and TSLP release in severe asthmatics, and be involved in asthma control. Twenty-eight asthmatics (12 non-severe and 16 severe) with CRS receiving nasal surgery were enrolled. The predicted FEV1 inversely associated with CRS severity of CT or endoscopy scores. Higher expression of Th2-driven cytokines (IL-4, IL-5, IL-9, and IL-13), TSLP, IL-25 and IL-33 in nasal tissues was observed in severe asthma. Severe asthmatics had higher ILC2 cell counts in their nasal tissues. ILC2 counts were positively correlated with Th2-cytokines. Nasal surgery significantly improved asthma control and lung function decline in severe asthma and CRS. The higher expression of IL-33/ILC2 axis-directed type 2 immune responses in nasal tissue of CRS brought the greater decline of lung function in severe asthma. ILC2-induced the upregulated activity of Th2-related cytokines in asthmatics with CRS may contribute to a recalcitrant status of asthma control

AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks

Transformer-based pre-trained models with millions of parameters require large storage. Recent approaches tackle this shortcoming by training adapters, but these approaches still require a relatively large number of parameters. In this study, AdapterBias, a surprisingly simple yet effective adapter architecture, is proposed. AdapterBias adds a token-dependent shift to the hidden output of transformer layers to adapt to downstream tasks with only a vector and a linear layer. Extensive experiments are conducted to demonstrate the effectiveness of AdapterBias. The experiments show that our proposed method can dramatically reduce the trainable parameters compared to the previous works with a minimal decrease in task performances compared with fine-tuned pre-trained models. We further find that AdapterBias automatically learns to assign more significant representation shifts to the tokens related to the task in consideration.Comment: The first two authors contributed equally. This paper was published in Findings of NAACL 202

Investigating the Effects of Large-Scale Pseudo-Stereo Data and Different Speech Foundation Model on Dialogue Generative Spoken Language Model

Recent efforts in Spoken Dialogue Modeling aim to synthesize spoken dialogue without the need for direct transcription, thereby preserving the wealth of non-textual information inherent in speech. However, this approach faces a challenge when speakers talk simultaneously, requiring stereo dialogue data with speakers recorded on separate channels, a notably scarce resource. To address this, we have developed an innovative pipeline capable of transforming single-channel dialogue data into pseudo-stereo data. This expanded our training dataset from a mere 2,000 to an impressive 17,600 hours, significantly enriching the diversity and quality of the training examples available. The inclusion of this pseudo-stereo data has proven to be effective in improving the performance of spoken dialogue language models. Additionally, we explored the use of discrete units of different speech foundation models for spoken dialogue generation.Comment: submitted to interspeech 202

Dimensionality of Carbon Nanomaterials Determines the Binding and Dynamics of Amyloidogenic Peptides: Multiscale Theoretical Simulations

Experimental studies have demonstrated that nanoparticles can affect the rate of protein self-assembly, possibly interfering with the development of protein misfolding diseases such as Alzheimer's, Parkinson's and prion disease caused by aggregation and fibril formation of amyloid-prone proteins. We employ classical molecular dynamics simulations and large-scale density functional theory calculations to investigate the effects of nanomaterials on the structure, dynamics and binding of an amyloidogenic peptide apoC-II(60-70). We show that the binding affinity of this peptide to carbonaceous nanomaterials such as C60, nanotubes and graphene decreases with increasing nanoparticle curvature. Strong binding is facilitated by the large contact area available for π-stacking between the aromatic residues of the peptide and the extended surfaces of graphene and the nanotube. The highly curved fullerene surface exhibits reduced efficiency for π-stacking but promotes increased peptide dynamics. We postulate that the increase in conformational dynamics of the amyloid peptide can be unfavorable for the formation of fibril competent structures. In contrast, extended fibril forming peptide conformations are promoted by the nanotube and graphene surfaces which can provide a template for fibril-growth

Use of the Hospital Anxiety and Depression Scale and the Taiwanese Depression Questionnaire for screening depression in head and neck cancer patients in Taiwan

OBJECTIVE: The purposes of this study are 1) to estimate the prevalence of common mental disorders including depressive disorder in patients with head and neck cancer (HNC) at baseline and at the 6-month follow-up and 2) to test the validity of two self-reported questionnaires, the Hospital Anxiety and Depression Scale (HADS) and the Taiwanese Depression Questionnaire (TDQ), for screening depression in patients with HNC. METHODS: Participants were recruited from the outpatient collaborative care clinic for HNC of a tertiary hospital in Taiwan between January 2010 and January 2011. Ninety-three patients with HNC were enrolled and assessed using the HADS, TDQ, and Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, fourth edition, Patient edition, at baseline and at the 6-month follow-up. Conventional validity indices of the HADS and TDQ were examined. RESULTS: Our results showed that the validity of the TDQ was satisfactory and comparable to that of both the HADS depression subscale and the HADS total scale. The cutoff scores of the HADS and TDQ for screening possible depressive disorders were 8 and 15, respectively. The areas under the receiver operating characteristic curve of the HADS and TDQ were mean 0.975±0.015 and 0.966±0.019, respectively. Thirteen participants (14%) were diagnosed with depressive disorders at the 6-month follow-up, compared with 8.5% at baseline. CONCLUSION: Our results indicate that both the HADS and TDQ are valid instruments for screening depression in patients with HNC

M-SpeechCLIP: Leveraging Large-Scale, Pre-Trained Models for Multilingual Speech to Image Retrieval

This work investigates the use of large-scale, pre-trained models (CLIP and HuBERT) for multilingual speech-image retrieval. For non-English speech-image retrieval, we outperform the current state-of-the-art performance by a wide margin when training separate models for each language, and show that a single model which processes speech in all three languages still achieves retrieval scores comparable with the prior state-of-the-art. We identify key differences in model behavior and performance between English and non-English settings, presumably attributable to the English-only pre-training of CLIP and HuBERT. Finally, we show that our models can be used for mono- and cross-lingual speech-text retrieval and cross-lingual speech-speech retrieval, despite never having seen any parallel speech-text or speech-speech data during training.Comment: Submitted to ICASSP 202