Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Ketoconazole on the Clinical Recovery in Central Serous Chorioretinopathy

Purpose Patients with hypercortisolism have been associated with a higher prevalence of the pachychoroid spectrum including central serous chorioretinopathy (CSCR), which may explain the inconsistency of therapeutic responses of the mineralocorticoid receptor antagonist because hyperaldosteronism has rarely been detected in patients with CSCR. Therefore, this study aimed to evaluate the effects of ketoconazole, the first-line cortisol inhibitor, on the resolution of subretinal fluid (SRF) in CSCR and to analyze correlations between choroidal thickness and steroid hormones. Patients and Methods This retrospective cohort study included 41 naïve CSCR eyes of 41 patients categorized into control (20 eyes) and treatment (21 eyes) groups. Patients in the treatment group were administered oral ketoconazole at a daily dose of 400 or 600 mg for 3–6 weeks. At week 12, rescue laser therapy was applied to patients exhibiting persistent SRF. Thus, a survival analysis was performed to determine the time interval from presentation to clinical resolution of SRF. Secondary outcomes consisted of eyes with persistent SRF and factors affecting the therapeutic response. Results The mean 24-hour urinary free cortisol (UFC) levels were elevated at 181 ± 70 and 150 ± 68 µg/day (range: 20–150) in the treatment and control groups, respectively (p = 0.21). After controlling for age and gender, baseline UFC levels were significantly associated with choroidal thickness in both eyes (p < 0.05). Ketoconazole significantly increased the CSCR resolution with the median time to resolution of 7 vs 16 weeks (p < 0.01) and decreased the proportion of eyes receiving rescue therapy at 12 weeks (23.8% vs 50%; p = 0.01). Prolonged CSCR durations were likely found in elderly patients with thick choroids in fellow eyes. Conclusion Patients with CSCR showed elevated glucocorticoids, which further correlated with their choroidal thickness. Using cortisol blockers may shorten the duration of existing SRF.
Evaluation of the Relationship Between the Changes in the Corneal Biomechanical Properties and Changes in the Anterior Segment OCT Parameters Following Customized Corneal Cross-Linking

Purpose This study aimed to investigate the relationship between changes in corneal biomechanical properties and changes in anterior segment optical coherence tomography (AS-OCT) parameters preoperatively and following customized corneal cross-linking (C-CXL) in eyes with progressive keratoconus. Patients and Methods This study included 44 eyes of 44 patients (33 men, 11 women; average age 22.8 ± 6.4 years) who underwent C-CXL for progressive keratoconus. Scheimpflug-based tonometer (SBT) and AS-OCT findings were evaluated preoperatively and 3 months following CXL. Parameters related to changes in SBT parameters were examined by multiple regression analysis using the stepwise method. Results Regarding SBT parameters, significant changes were observed in the integrated area under the curve of the inverse concave radius (pre, 12.19 ± 1.95/mm; post, 11.26 ± 1.89/mm; p < 0.0001), maximum inverse radius (pre, 0.24 ± 0.04/mm; post, 0.23 ± 0.04/mm; p = 0.0053), deformation amplitude ratio max 2 mm (pre, 5.53 ± 0.81; post, 5.29 ± 0.71; p = 0.0048), and stress–strain index (pre, 0.74 ± 0.16; post, 0.84 ± 0.20; p < 0.0001), pre and post C-CXL. Regarding AS-OCT parameters, significant changes were observed in average keratometry (pre, 47.87 ± 3.61 D; post, 47.56 ± 3.29 D, p = 0.0104), steep keratometry (pre, 49.61 ± 4.01 D; post, 49.25 ± 3.59 D; p = 0.0115), maximum keratometry (pre, 55.44 ± 6.22 D; post, 54.68 ± 5.56 D; p = 0.0061), and thinnest corneal thickness (pre, 450.43 ± 41.74 μm; post, 444.00 ± 39.35 μm; p < 0.0001), pre and post C-CXL. Multiple regression analysis demonstrated that when the change in the deformation amplitude (DA) ratio max (2 mm) was the dependent variable, age, change in average keratometry, and change in the thinnest corneal thickness were selected as explanatory variables. When changes in the stiffness parameter at applanation 1 and stress–strain index were the dependent variables, change in the intraocular pressure (IOP) was selected as the explanatory variable. Conclusion Change in the SBT parameters following C-CXL could be related to the age, change in the IOP value, change in average keratometry, and thinnest corneal thickness.
Spectrum of collective transverse excitations in liquid cesium near the melting point (in English)

The spectrum of generalized transverse excitations of liquid cesium at 308 K is calculated within the approach of generalized collective modes. The transverse \current{current" time correlation function is obtained in the form which satis es the rst frequency moments up to the sixth order. The crossover from the usual hydrodynamic behavior to the regime, where well{de ned shear waves are supported by the liquid, is studied. We found the wavenumber k h = 0:092 A 1 at which the shear propagating modes disappear and transform into two relaxing modes, where one of them is the usual hydrodynamic one. The generalized static shear viscosity is calculated in a wide range of wave numbers k. In hydrodynamic limit we found good agreement of the calculated generalized shear viscosity with experimental data.
Pre-B Lymphoid Cell Line

Interleukin-7 (IL-7) is a potent stimulator of pre-B-lymphocyte proliferation. Pre-B cells transformed by a variety of oncogenes including those of the ABL protein tyrosine kinase family were screened for endogenous IL-7 mRNA expression by polymerase chain reaction and a sensitive bioassay for secreted IL-7. Some v-abl but none of the BCR/ABL, v-src, v-fms, v-myc, v-ras, or v-raf transformants analyzed contained elevated IL-7 transcripts. None of the cell lines secreted detectable bioactivity. We overexpressed IL-7 via a retroviral vector in an IL-7-dependent pre-B cell line to assess the potential for autocrine growth stimulation and malignant transformation. We achieved dramatic deregulation of IL-7 translational suppression by removing portions of the 5' flanking region. Levels of IL-7 expression much greater than those needed to establish factorindependent growth did not induce colony formation in agar by IL-7-expressing pre-B cell lines, and the majority of these lines were nontumorigenic in syngeneic mice. The same pre-B cell line transformed by v-abl displayed a highly malignant phenotype while containing dramatically lower IL-7 transcript levels. We conclude that endogenous IL-7 expression is not a necessary event in transformation of pre-B cells, nor is it sufficient to explain the malignant phenotype in v-abl-transformed cells. Up regulation of endogenous IL-7 expression in some transformed pre-B cells may be one of several synergistic events which can lead to malignant conversion.
A Fast and Power-Efficient Hardware Architecture for Non-Maximum Suppression

Non-maximum suppression (NMS) is an indispensable post-processing step in face detection. The vast majority of face detection methods need NMS to merge the candidate detected face boxes that belong to the same face. However, the standard NMS is a greedy and local optimization technique which suffers from several shortcomings, such as high complexity (<inline-formula> <tex-math notation="LaTeX">${O}$ </tex-math></inline-formula>(<inline-formula> <tex-math notation="LaTeX">${N} ^{\boldsymbol {2}}$ </tex-math></inline-formula>)), high latency, and large power consumption. This brief alleviates these problems and presents an efficient hardware architecture for NMS, meanwhile, carries out the optimization for the calculation unit to achieve the reduction of area accordingly. Based on the multi-thread computing, this brief utilizes sliding window to obtain parallelism and uses position-based bit table technique for the enhancement of data accessing and data reusing, which greatly decreases the cost of memory access and power consumption. The proposed hardware architecture is implemented in TSMC 28-nm technology. Experiments show that the power consumption is 6.142 mW and the latency is 12.79 <inline-formula> <tex-math notation="LaTeX">$ {\mu }\text{s}$ </tex-math></inline-formula> to cluster 1000 candidate boxes, whose energy efficiency is higher than those state-of-the-art methods by <inline-formula> <tex-math notation="LaTeX">$3798 {\times }$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$358 {\times }$ </tex-math></inline-formula>, respectively.
Landiolol for refractory tachyarrhythmias in the intensive care unit: case reports

Abstract Tachyarrhythmias are common complications of critically ill patients treated on intensive care units. Landiolol is an ultra-short acting beta-blocker with a very high beta1-selectivity. Therefore, landiolol effectively reduces heart rate with only minimal negative effects on blood pressure and inotropy. This article describes two cases of successful treatment of supraventricular and ventricular tachycardias with landiolol in critically ill patients.
Quasi-Periodic Energy Variation in a Zonal Flow-Baroclinic Wave Interaction Model

Non-linear interaction between mean zonal flow and a baroclinic wave is investigated numerically by using a two-layer quasi-geostrophic *-channel model with inclusion of friction and diabatic heating. In a series of experiments, meridional gradient of the heating is varied to elucidate the seasonal variation of the characteristics of non-linear baroclinic waves. Results obtained by these experiments are summarized as follows: (1) As a result of non-linear interaction, thereexists an energy variation with a period of 2-3 weeks as well as 3-4 days. (2) For small meridional gradient of the diabatic heating, energy variation of 2-3 week period is maintained by the fluctuation of horizontal eddy momentum flux. Namely, the dominant energy process of this frequency range is the barotropic conversion. (3) The baroclinic energy transfer becomes prominent withincreasing the meridional gradient of the heating. The energy cycle is mainly accompanied bythe fluctuation of eddy heat flux. It is suggested that the zonal flow-braoclinic wave interaction isone possible mechanism to explain the quasi-periodic variation in the real atmosphere with time scales of two to three weeks, which is known as the "index cycle" or "tropospheric vacillation" (Webster and Keller, 1975; McGuirk and Reiter, 1976).
A numerical investigation on hydro-mechanical behaviour of a high centreline tailings dam

PROF DR ALI AKHTARPOUR* holds a BSc in Civil Engineering and an MSc and PhD in Geotechnical Engineering from Amirkabir University of Technology in Iran. He is an assistant Professor at Ferdowsi University of Mashhad in Iran. His research interests include geotechnical earthquake engineering and numerical investigations into geotechnical problems with regard to infrastructure such as dams, foundations and excavations.
CIA_A_251067 673..681

1Student Research Committee, School of Nursing and Midwifery, Qazvin University of Medical Sciences, Qazvin, Iran; 2Social Determinants of Health Research Center, Research Institute for Prevention of NonCommunicable Diseases, Qazvin University of Medical Sciences, Qazvin, Iran; 3Faculty of Education, Monash University, Clayton, Australia; 4Department of Biostatistics and Medical Informatics, Faculty of Medicine, Ahi Evran University, Kirsehir, Turkey Background: Flourishing is related to positive outcomes for physical and mental health, as
Dietary effect of energy levels on growth performance and carcass characteristics of White Pekin duck over 21 days

Abstract This experiment was conducted to determine the maximum dietary energy levels on growth performance and carcass characteristics of White Pekin duck. the Six dietary treatments were formulated based on their apparent metabolizable energy (AME) concentrations from 2,700 to 3,200 kcal/kg with a 100 kcal/kg gap to evaluate the accurate dietary AME requirement to address current knowledge and further issues for fulfilling the genetic potential of meat-type white Pekin ducklings. A total of 432 one-day-old male White Pekin ducklings were randomly allocated into one of six dietary treatments with six replicates (12 birds per pen). The diets were formulated as corn-soybean meal-based diets to meet or exceed the Nutrient Requirement of Poultry specification for meat-type ducks. Growth performance indices (i.e. average daily gain [ADG], average daily feed intake, feed conversion ratio) were measured weekly. Medium body weight (BW) ducklings from each pen were sacrificed to analyze the carcass traits and abdominal fat content on day 21. Obtained data were analyzed to estimate significant effect using the one-way ANOVA of IBM SPSS Statistics (Version, 25). If the p-value of the results were significant, differences in means among treatments were separated by Tukey’s post hoc test. Significant differences were then analyzed with a linear and quadratic broken model to estimate the accurate concentration of AME. Ducklings fed higher dietary AME diets increased (p < 0.05) BW, ADG. Ducklings fed higher AME than 2,900 kcal/kg diets increased abdominal fat accumulation and leg meat portion. The estimated requirement by linear plateau method showed from 3,000.00 kcal/kg to 3,173.03 kcal/kg whereas the requirement by quadratic plateau method indicated from 3,100.00 kcal/kg to 3,306.26 kcal/kg. Collectively, estimated dietary requirements exhibit diverse results based on the measured traits and analysis methods. All the estimated requirements in this experiment present higher than previous research, the maximum requirement for the next diet formulation should be selected by the purpose of the diet.
Risk Management Committee and Real Earnings Management Through Sales: Evidence from Nigeria

Article history: Received 3 July 2018 Received in revised form 23 July 2018 Accepted 26 July 2018 Available online 1 August 2018 This study examines the impact of risk management committee on real earnings management through sales manipulation of listed companies in Nigeria. The analysis is based on a sample of 80 listed non-financial firms for the period of five years (20122016), making up 400 firm-year observation. The data was extracted from the annual report of the sample firms and Thompson Reuters database. Panel corrected standard error regression (PCSE) was employed. The results show that risk management committee (RMC) and independence directors reduce the management desire to manipulate the reported earnings. The study informs the regulators on the needs for firms to set up an independent RMC to restrain management from manipulating the real earnings activities through sales.
Usability Testing and Feedback Collection in a School Context: Case Poetry Machine

Evaluation methods emphasizing children’s natural interaction help in getting feedback from children for product development. This paper presents a case study with 9- to 10-year-old children in a school context. The evaluated system was an artificial intelligence–based poetry writing system, and the methods used were peer tutoring with paired interviews and group testing with a new Feedback Game. The evaluation criteria included the number of usability problems, usefulness, and fun. The applicability of the methods is discussed along with the resources required. Peer tutoring revealed numerous problems, whereas group testing and the Feedback Game were quick to conduct and analyze.
Vision Transformers with Hierarchical Attention

This paper tackles the high computational/space complexity associated with Multi-Head Self-Attention (MHSA) in vanilla vision transformers. To this end, we propose Hierarchical MHSA (H-MHSA), a novel approach that computes self-attention in a hierarchical fashion. Specifically, we first divide the input image into patches as commonly done, and each patch is viewed as a token. Then, the proposed H-MHSA learns token relationships within local patches, serving as local relationship modeling. Then, the small patches are merged into larger ones, and H-MHSA models the global dependencies for the small number of the merged tokens. At last, the local and global attentive features are aggregated to obtain features with powerful representation capacity. Since we only calculate attention for a limited number of tokens at each step, the computational load is reduced dramatically. Hence, H-MHSA can efficiently model global relationships among tokens without sacrificing fine-grained information. With the H-MHSA module incorporated, we build a family of Hierarchical-Attention-based Transformer Networks, namely HAT-Net. To demonstrate the superiority of HAT-Net in scene understanding, we conduct extensive experiments on fundamental vision tasks, including image classification, semantic segmentation, object detection, and instance segmentation. Therefore, HAT-Net provides a new perspective for vision transformers. Code and pretrained models are available at https://github.com/yun-liu/HAT-Net.
Robust SAR ATR on MSTAR with Deep Learning Models trained on Full Synthetic MOCEM data

the promising potential of Deep Learning for Automatic Target Recognition (ATR) on Synthetic Aperture Radar (SAR) images vanishes when considering the complexity of collecting training datasets measurements. Simulation can overcome this issue by producing synthetic training datasets. However, because of the limited representativeness of simulation, models trained in a classical way with synthetic images have limited generalization abilities when dealing with real measurement at test time. Previous works identified a set of equally promising deep-learning algorithms to tackle this issue. However, these approaches have been evaluated in a very favorable scenario with a synthetic training dataset that overfits the ground truth of the measured test data. In this work, we study the ATR problem outside of this ideal condition, which is unlikely to occur in real operational contexts. Our contribution is threefold. (1) Using the MOCEM simulator (developed by SCALIAN DS for the French MoD/DGA), we produce a synthetic MSTAR training dataset that differs significantly from the real measurements. (2) We experimentally demonstrate the limits of the state-of-the-art. (3) We show that domain randomization techniques and adversarial training can be combined to overcome this issue. We demonstrate that this approach is more robust than the state-of-the-art, with an accuracy of 75 %, while having a limited impact on computing performance during training. Keywords— SAR, radar, ATR, MSTAR, SAMPLE, deep learning, classification, simulation, synthetic dataset, MOCEM.
Proximal Splitting Adversarial Attack for Semantic Segmentation

Classification has been the focal point of research on adversarial attacks, but only a few works investigate methods suited to denser prediction tasks, such as semantic segmentation. The methods proposed in these works do not accurately solve the adversarial segmentation problem and, therefore, overestimate the size of the perturbations required to fool models. Here, we propose a white-box attack for these models based on a proximal splitting to produce adversarial perturbations with much smaller $\ell_{\infty}$ norms. Our attack can handle large numbers of constraints within a nonconvex minimization framework via an Augmented Lagrangian approach, coupled with adaptive constraint scaling and masking strategies. We demonstrate that our attack significantly outperforms previously proposed ones, as well as classification attacks that we adapted for segmentation, providing a first comprehensive benchmark for this dense task.
Dark dimension, the swampland, and the dark matter fraction composed of primordial black holes

Very recently, it was suggested that combining the Swampland program with the smallness of the dark energy and confronting these ideas to experiment lead to the prediction of the existence of a single extra-dimension (dubbed the dark dimension) with characteristic length-scale in the micron range. We show that the rate of Hawking radiation slows down for black holes perceiving the dark dimension and discuss the impact of our findings in assessing the dark matter fraction that could be composed of primordial black holes. We demonstrate that for a species scale of ${\cal O}(10^{10}~{\rm GeV})$, an all-dark-matter interpretation in terms of primordial black holes should be feasible for masses in the range $10^{14} \leq M_{BH}/{\rm g}\leq 10^{21}$. This range is extended compared to that in the 4D theory by 3 orders of magnitude in the low mass region. We also show that PBHs with $M_{\rm BH} \sim 10^{12}~{\rm g}$ could potentially explain the well-known Galactic 511 keV gamma-ray line if they make up a tiny fraction of the total dark matter density.
Learn to Adapt: Robust Drift Detection in Security Domain

Deploying robust machine learning models has to account for concept drifts arising due to the dynamically changing and non-stationary nature of data. Addressing drifts is particularly imperative in the security domain due to the ever-evolving threat landscape and lack of sufficiently labeled training data at the deployment time leading to performance degradation. Recently proposed concept drift detection methods in literature tackle this problem by identifying the changes in feature/data distributions and periodically retraining the models to learn new concepts. While these types of strategies should absolutely be conducted when possible, they are not robust towards attacker-induced drifts and suffer from a delay in detecting new attacks. We aim to address these shortcomings in this work. we propose a robust drift detector that not only identifies drifted samples but also discovers new classes as they arrive in an on-line fashion. We evaluate the proposed method with two security-relevant data sets -- network intrusion data set released in 2018 and APT Command and Control dataset combined with web categorization data. Our evaluation shows that our drifting detection method is not only highly accurate but also robust towards adversarial drifts and discovers new classes from drifted samples.
SN 2016dsg: A Thermonuclear Explosion Involving a Thick Helium Shell

A thermonuclear explosion triggered by a He-shell detonation on a carbon–oxygen white-dwarf core has been predicted to have strong UV line blanketing at early times due to the iron-group elements produced during He-shell burning. We present the photometric and spectroscopic observations of SN 2016dsg, a subluminous peculiar Type I supernova consistent with a thermonuclear explosion involving a thick He shell. With a redshift of 0.04, the i-band peak absolute magnitude is derived to be around −17.5. The object is located far away from its host, an early-type galaxy, suggesting it originated from an old stellar population. The spectra collected after the peak are unusually red, show strong UV line blanketing and weak O i λ7773 absorption lines, and do not evolve significantly over 30 days. An absorption line around 9700–10500 Å is detected in the near-infrared spectrum and is likely from the unburnt He in the ejecta. The spectroscopic evolution is consistent with the thermonuclear explosion models for a sub-Chandrasekhar-mass white dwarf with a thick He shell, while the photometric evolution is not well described by existing models.