Miracle-dz/UniFAR-FTUs huggingface dataset:
VDIP-TGV: Blind Image Deconvolution via Variational Deep Image Prior Empowered by Total Generalized Variation

Recovering clear images from blurry ones with an unknown blur kernel is a challenging problem. Deep image prior (DIP) proposes to use the deep network as a regularizer for a single image rather than as a supervised model, which achieves encouraging results in the nonblind deblurring problem. However, since the relationship between images and the network architectures is unclear, it is hard to find a suitable architecture to provide sufficient constraints on the estimated blur kernels and clean images. Also, DIP uses the sparse maximum a posteriori (MAP), which is insufficient to enforce the selection of the recovery image. Recently, variational deep image prior (VDIP) was proposed to impose constraints on both blur kernels and recovery images and take the standard deviation of the image into account during the optimization process by the variational principle. However, we empirically find that VDIP struggles with processing image details and tends to generate suboptimal results when the blur kernel is large. Therefore, we combine total generalized variational (TGV) regularization with VDIP in this paper to overcome these shortcomings of VDIP. TGV is a flexible regularization that utilizes the characteristics of partial derivatives of varying orders to regularize images at different scales, reducing oil painting artifacts while maintaining sharp edges. The proposed VDIP-TGV effectively recovers image edges and details by supplementing extra gradient information through TGV. Additionally, this model is solved by the alternating direction method of multipliers (ADMM), which effectively combines traditional algorithms and deep learning methods. Experiments show that our proposed VDIP-TGV surpasses various state-of-the-art models quantitatively and qualitatively.
Improving Input-label Mapping with Demonstration Replay for In-context Learning

In-context learning (ICL) is an emerging capability of large autoregressive language models where a few input-label demonstrations are appended to the input to enhance the model's understanding of downstream NLP tasks, without directly adjusting the model parameters. The effectiveness of ICL can be attributed to the strong language modeling capabilities of large language models (LLMs), which enable them to learn the mapping between input and labels based on in-context demonstrations. Despite achieving promising results, the causal nature of language modeling in ICL restricts the attention to be backward only, i.e., a token only attends to its previous tokens, failing to capture the full input-label information and limiting the model's performance. In this paper, we propose a novel ICL method called Repeated Demonstration with Sliding Causal Attention, (RdSca). Specifically, we duplicate later demonstrations and concatenate them to the front, allowing the model to `observe' the later information even under the causal restriction. Besides, we introduce sliding causal attention, which customizes causal attention to avoid information leakage. Experimental results show that our method significantly improves the input-label mapping in ICL demonstrations. We also conduct an in-depth analysis of how to customize the causal attention without training, which has been an unexplored area in previous research.
Comparison of the 10-, 14- and 20-Item CES-D Scores as Predictors of Cognitive Decline

The association between depressive symptomatology and cognitive decline has been examined using the Centre for Epidemiologic Studies-Depression Scale (CES-D); however, concerns have been raised about this self-report measure. Here, we examined how the CES-D total score from the 14- and 10-item versions compared to the 20-item version in predicting progression to cognitive decline from a cognitively unimpaired baseline. Data from 1054 participants were analysed using ordinal logistic regression, alongside moderator and receiver-operating characteristics curve analyses. All baseline total scores significantly predicted progression to cognitive decline. The 14-item version was better than the 20-item version in predicting consensus diagnosis, as shown by their AICs, while also showing the highest accuracy when discriminating between participants by diagnosis at last visit. We did not find sex to moderate the relationship between CES-D score and cognitive decline. Current findings suggest the 10- and 14-item versions of the CES-D are comparable to the 20-item version, and that the 14-item version may be better at predicting longitudinal consensus diagnosis compared to the 20-item version.
Long-Time Water Quality Variations in the Yangtze River from Landsat-8 and Sentinel-2 Images Based on Neural Networks

Total phosphorus (TP) and total nitrogen (TN) represent the primary water quality parameters indicative of the eutrophication status in the mainstream of the Yangtze River. Nowadays, satellite remote sensing offers an economical and efficient method for monitoring the water environment with a broad geographical scope, while single satellite and traditional methods are still limited. In this paper, inversion models of TN and TP are constructed and evaluated based on the neural networks (NNs) algorithm and random forest (RF) algorithm in the upper, middle, and lower reaches of the Yangtze River, respectively. Subsequently, the monthly variations of TN and TP concentrations are estimated and analyzed in the mainstream of the Yangtze River using Landsat-8 and Sentinel-2 satellites images from January 2016 to December 2022. The results show that the NNs model exhibits better estimation performance than the RF model within the study area. The accuracy of the TN model varies across different sections, with R2 values of 0.70 in the upstream, 0.67 in the midstream, and 0.74 in the downstream, accompanied by respective RMSE values of 0.21 mg/L, 0.21 mg/L, and 0.23 mg/L. Similarly, the TP model exhibits varying accuracy in different sections, with R2 values of 0.71 in the upstream, 0.69 in the midstream, and 0.78 in the downstream, along with corresponding RMSE values of 0.008 mg/L, 0.012 mg/L, and 0.008 mg/L. From 2016 to 2022, the concentrations of TN and TP in the mainstream of the Yangtze River exhibited an overall downward trend, with TN decreasing by 13.7% and TP decreasing by 46.2%. Furthermore, this study also gives the possible causes of water quality changes in the mainstream of the Yangtze River with a specific focus on hydrometeorological factors.
Carbon-isotope signatures of Albian to Cenomanian (Cretaceous) shelf carbonates of the Natih Formation, Sultanate of Oman

The δ13C values of Albian to Cenomanian shallow-marine carbonate sequences of the Natih Formation have been collected from subsurface cores of a key location in Oman. The 450-m-thick stack of shelf carbonates is without significant gaps in deposition. The δ13C data range between 1‰ and 6‰, more-or-less tracking the evolution over time of δ13C in seawater established elsewhere in time-equivalent pelagic carbonate sequences. Anchored by biostratigraphy the isotope profile suggests several additional time correlations. It thus provides significantly enhanced stratigraphic resolution and a key section for regional correlations. In particular, the onset of Natih deposition (Natih F and G members) coincides with the Albian/Cenomanian boundary event, thus placing the base Natih into the Albian. The Natih C and D members were deposited mainly during the Mid-Cenomanian oceanic anoxic event, while the carbon-isotopes signature of the Natih A Member, which is at this locality incomplete due to erosion, documents the onset of the Cenomanian/Turonian boundary event (OAE2). This indicates a latest Cenomanian, possibly Early Turonian age for the top Natih at this subsurface location and suggests an Early Turonian age for the more complete Natih section exposed in the nearby Oman Mountains sections. Both organic-rich intervals of the Natih Formation (Natih E4b and B2) do not correlate with global Oceanic Anoxic Events indicating a rather local setting for source-rock deposition. This is further supported by an isotopic anomaly associated with the organic-rich Natih B. The anomaly is likely related to near-seabed diagenesis or a temporary limited water exchange of the intra-shelf basin with the open ocean and the incorporation of recycled carbon from oxidized organic matter into the water column and the inorganic carbon pool. The subsurface carbon-isotope profile correlates well with those from nearby outcrop and other subsurface sections adding further confidence that primary signatures are preserved and can be used for correlations. As in other Early Cretaceous shelf sequences of the Arabian Plate oxygen isotopes are lighter than expected for calcite deposited in equilibrium with Cretaceous seawater indicating most likely whole-scale recrystallization and stabilization during shallow burial at slightly elevated temperatures.
PERCENT FAT MASS AND BODY MASS INDEX AS CARDIORESPIRATORY FITNESS PREDICTORS IN YOUNG ADULTS (Persentase lemak dan indeks massa tubuh sebagai prediktor kebugaran kardiorespiratorik pada dewasa muda)

The present study aimed to analyze the association between body fatness measures, i.e. body mass index (BMI) and percent fat mass (% FM) with cardiorespiratory fitness (CRF) in young adults. Seventy five undergraduate students aged 19-21 years were included in this cross sectional study. Body composition was assessed by tetra polar Bioelectrical Impedance Analysis method, and CRF was determined as VO 2 max level by conducting Balke test and flexibility by sit-and-reach test. Regression tests were performed to assess the associations between the body fatness measures and CRF. The mean (SD) % FM and BMI were 25.6 (8.3) % and 22.4 (4.2) kg/m 2 , respectively. Both BMI and % FM were inversely associated with VO 2 max and flexibility. The associations of % FM with each CRF measure were stronger (% FM-VO 2 max: R 2 =0.45, p<0.0001; % FM-flexibility: R 2 =0.16, p<0.0001) than those of BMI (BMI-VO 2 max: R 2 = 0.12, p=0.002; BMI-flexibility: R 2 =0.07, p<0.0001). Including gender as a variable predictor greatly improved almost all associations. We suggest that %FM is a better predictor for VO 2 max than BMI. Further studies are needed to elucidate the relationships of body fatness measures adjusted for potential confounding factors with CRF measures other than VO 2 max.
Discussion of "Resistance Changes during Compression of Carbon Fiber Cement Composites"

The subject paper provides experimental results on the change in electrical resistance of carbon fiber cement upon compression. Results are given for curing ages of 7 days and 140 days. The results are compared with those in the paper by Chen and Chung 1996. The results of Chen and Chung 1996 are for a curing age of 7 days only. In other publications on this subject Fu and Chung 1996, 1997; Fu et al. 1997, 1998; Bontea et al. 2000; Wen and Chung 2000, 2001a,b, 2003; Chung 2002, the curing age is 28 days. Comparison of the results of the subject paper for a curing age of 140 days should not be made with those of Chen and Chung 1996 for a curing age of 7 days. Rather, comparison should be made with the results of the other previously listed papers for a curing age of 28 days. How the resistance changes in response to strain is very different between curing ages of 7 and 28 days, as reported by Fu and Chung 1997. The results in Figs. 7, 9, and 10 of the subject paper for a curing age of 140 days are consistent with prior work for a curing age of 28 days.
( 587 j ) Photocatalytic Reforming of Biomass for Hydrogen Production Poster

Combustion of fossil fuels is one of the main causes of the climate change, due to the production of harmful CO2. As a consequence, significant scientific efforts aim at developing cleaner and more sustainable fuel resources. Hydrogen is a promising alternative, as hydrogen has a high energy density and no harmful products are formed during its combustion. Hydrogen is currently produced from natural gas or coal by gasification, liquefaction or steam reforming [1]. However, these methods are highly energy demanding and they still require natural resources that are not renewable. In contrast, PhotoCatalytic Reforming (PhCR) only uses solar energy to convert aqueous phase biomass waste streams into H2 and CO2. [2]
CHIEF EXECUTIVE OFFICER (CEO) ATTRIBUTES AND TAX AVOIDANCE INSIGHT FROM LISTED NON-FINANCIAL FIRMS IN NIGERIA

The study mainly examined the effect of chief executive officers’ attribute on tax avoidance of listed non-financial firms in Nigeria. To achieve this objective, this study specifically tests the hypothesis that chief executive officers’ attributes in the context of chief executive officers’ tenure, chief executive officers’ ownership, chief executive officers’ gender and chief executive officers’ nationality significantly affects tax avoidance over a 10year time frame (2012 – 2021) for non-financial listed firms in Nigeria. This study is anchored on the Upper Echelon Theory noting that the key concept of the upper echelon theory is that the company reflects its chief executive officer. Robust regression analysis technique was employed to test the formulated hypotheses after fulfilling the necessary conditions for obtaining non-spurious regression estimates. Specifically, the result reveals mixed evidence suggesting that the effect of chief executive officers’ attribute on tax avoidance depends on the observed or unobserved traits. Particularly, the result suggests that higher ownership rights owned by the chief executive officer reduces the level of tax avoidance of listed non-finance firms in Nigeria. Therefore, this study recommends among others that to optimize the non-debt tax saving strategy, management must develop a culture within the organization that values responsible tax planning and encourages chief executive officers’ to actively consider the non-debt tax shield as a strategic tool. Further, management team should promote transparency and open communication about tax strategies, ensuring that tax planning is integrated into overall business decision-making processes. Keywords: Chief Executive Officer Attribute, Tax Avoidance, Robust Regression, Upper Echelon Theory.
Scalar mixing and entrainment in an axisymmetric jet subjected to external turbulence

The effect of zero-mean-flow external turbulence on the topology of the scalar turbulent/turbulent interface (TTI) has been recently studied in axisymmetric jets (Kohan&Gaskin, J. Fluid Mech., vol. 950, 2022, A32). The present study aims to understand the process of turbulent entrainment into a jet, as affected by background turbulence, using scalar statistics. Planar-laser-induced fluorescence was employed to capture the orthogonal cross sections of the jet at a fixed downstream station with varying background turbulence intensities and length scales. The conditional scalar profiles revealed that the thickness of the scalar TTI is greater than that of the traditional turbulent/non-turbulent interface (TNTI), and the interfacial thickness is an increasing function of the background turbulence intensity. Although nibbling remains the primary entrainment mechanism in the far field, increased occurrence of concentration 'holes' within the interfacial layer in the presence of ambient turbulence suggests a more significant role of large-scale engulfment in the turbulent/turbulent entrainment process. Enhanced contribution of the area of detached jet patches (i.e. 'islands') to that of the main jet is hypothesized to be evidence of intense detrainment events in the background turbulence. This can potentially explain the reduced net entrainment into the jet, which manifests as less negative values of scalar skewness within the jet core.
The Use Of Social Media And Its Relationship With Vocational School Learning Outcomes

This study aims to determine whether there is a relationship between the use of social media and student learning outcomes at SMK Negeri 1 Tondano. This type of research uses a quantitative approach with a correlational design. This research is correlational because this research seeks to investigate the correlation between two variables. Quantitative research is a study that uses numbers to collect data and provide an interpretation of the research results. The results of the research are based on descriptive analysis that has been carried out using social media. Students of SMK Negeri 1 Tondano from 45 samples, there is a maximum value of 85 with a mean of 50.81. This means that most students use social media. In this study, it was obtained that the student learning outcomes of SMK Negeri 1 Tondano averaged 77.38 which indicated that the score was above the minimum passing criteria. Thus the Relationship between Social Media Use and Student Learning Outcomes Based on simple linear regression analysis, there is a significant negative relationship between social media use and Student Learning Outcomes.
Modelling high-latitude ionosphere for time-varying plasma convection

The paper discusses how variations in the pattern of convective plasma flows should be included in self-consistent time-dependent models of the coupled ionosphere-thermosphere system. The author shows how these variations depend upon the mechanism by which the solar wind flow excites the convection. The modelling of these effects is not just of relevance to the polar ionosphere. This is because the influence of convection is not confined to high latitudes: the resultant heating and composition changes in the thermosphere are communicated to lower latitudes by the winds which are also greatly modified by the plasma convection. These thermospheric changes alter the global distribution of plasma by modulating the rates of the chemical reactions which are responsible for the loss of plasma. Hence the modelling of these high-latitude processes is of relevance to the design and operation of HF communication, radar and navigation systems worldwide.
A sustainable storage solution for the Science Museum Group

Museums in recent years have sought ways to reduce the environmental impact of their operations. One approach has been to look at ways to cut back on the energy required to stabilise storage conditions, particularly relative humidity, through passive moisture control rather than mechanical systems of heating and air conditioning. To this end the Science Museum Group employed hemp in the form of hemp-lime concrete, to construct a new storage facility for its collections, drawing on research into the buffering ability of hygroscopic natural building materials. The objective was to reduce energy use, to decrease reliance on mechanical systems and to produce very stable levels of relative humidity, in order to ensure the preservation of significant heritage collections. Although a prototype, to date, this building has performed as anticipated despite some initial construction snags and mechanical system malfunctions. The results encourage further investigation into hygroscopic construction materials to design even more energy-saving ways of providing stable storage conditions for museums.
Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming

Sketching algorithms have recently proven to be a powerful approach both for designing low-space streaming algorithms as well as fast polynomial time approximation schemes (PTAS). In this work, we develop new techniques to extend the applicability of sketching-based approaches to the sparse dictionary learning and the Euclidean $k$-means clustering problems. In particular, we initiate the study of the challenging setting where the dictionary/clustering assignment for each of the $n$ input points must be output, which has surprisingly received little attention in prior work. On the fast algorithms front, we obtain a new approach for designing PTAS's for the $k$-means clustering problem, which generalizes to the first PTAS for the sparse dictionary learning problem. On the streaming algorithms front, we obtain new upper bounds and lower bounds for dictionary learning and $k$-means clustering. In particular, given a design matrix $\mathbf A\in\mathbb R^{n\times d}$ in a turnstile stream, we show an $\tilde O(nr/\epsilon^2 + dk/\epsilon)$ space upper bound for $r$-sparse dictionary learning of size $k$, an $\tilde O(n/\epsilon^2 + dk/\epsilon)$ space upper bound for $k$-means clustering, as well as an $\tilde O(n)$ space upper bound for $k$-means clustering on random order row insertion streams with a natural"bounded sensitivity"assumption. On the lower bounds side, we obtain a general $\tilde\Omega(n/\epsilon + dk/\epsilon)$ lower bound for $k$-means clustering, as well as an $\tilde\Omega(n/\epsilon^2)$ lower bound for algorithms which can estimate the cost of a single fixed set of candidate centers.
Etiological Profile, Targeted Levothyroxine Dosing and Impact of Partial Newborn Screening in Congenital Hypothyroidism—A Single Centre Experience

Background: Congenital hypothyroidism (CH) is the most common cause of preventable intellectual disability. Newborn screening (NBS) for CH has been in vogue in many parts of the world since 1970, but despite its well-known benefits, many developing countries including India have not been able to establish universal NBS for CH till date. Objective: The aim of this study was to review the clinical aspects of congenital hypothyroidism in a tertiary care university referral teaching hospital, focusing on aetiology of CH, predictors of permanence, optimal targeted dose strategies based on aetiology and the effect of newborn screening on the time to diagnosis. Material and Methods: The electronic medical records of 233 children with CH referred to our centre between January 2009 and December 2019 were analysed. A partial NBS was established in the state in 2012. Results: Dyshormonogenesis (57.5%) was the most common aetiology of CH. The incidence of transient CH in children with a gland in situ (GIS) was 35%. Levothyroxine (LT-4) dose of >2.75 μg/kg/day (sensitivity 76.5, specificity 72), >2.15 μg/kg/day (sensitivity 82.4, specificity 61.9) and >1.85 μg/kg/day (sensitivity 76.5, specificity 61.9) at years 1, 2 and 3, respectively, were predictors of permanent CH. An initial LT-4 dose ≥8 μg/kg was sufficient and very seldom led to undertreatment in children with dyshormonogenesis. On the contrary, even doses ≥13 mcg/kg/day led to frequent undertreatment in children with thyroid dysgenesis. After the introduction of newborn screening, the median age at diagnosis came down from 45 days (IQR 14–180 days) to ten days (IQR 3–12 days). Conclusion: Targeted dosing based on aetiology of CH may be more appropriate to optimise outcomes. The time to diagnosis of CH reduced significantly after the adoption of even a partial NBS program highlighting the urgent need for implementation of the same in resource poor settings.
Beach rating : A methodological approach

A beach rating scheme was devised and implemented between 1989-1991 to rank the major public recreation beaches along the U.S. open marine coasts based on 50 criteria. For the past five years America's best beaches have been determined and reported to the media. The top ten beaches are always found in Hawaii and Florida because the survey was in general developed for swimming beaches, but other categories (e.g., scenic, walking, wild, sports) of beaches have also been arrayed, which results in top rankings for beaches from Maine to Washington. Beaches are always changing because of storm impact, beach nourishment, pollution problems, etc. so the rankings vary year to year.