Miracle-dz/UniFAR-FTUs huggingface dataset:
Perception of an Ambiguous Figure: Subconscious Social Group Bias or Anchor Effect?

Older participants who are briefly presented with the ‘my wife and my mother-in-law’ ambiguous figure estimate its age to be higher than young participants do. This finding is thought to be the result of a subconscious social group bias that influences participants’ perception of the figure. Because people are better able to recognize similarly aged individuals, young participants are expected to perceive the ambiguous figure as a young woman, while older participants are more likely to recognize an older lady. We replicate the difference in age estimates, but find no relationship between participants’ age and their perception of the ambiguous figure. This leads us to conclude that the positive relationship between participants’ age and their age estimates of the ambiguous ‘my wife and my mother-in-law’ figure is better explained by the own-age anchor effect, which holds that people use their own age as a yard stick to determine the age of the figure, regardless of whether the young woman or the older lady is perceived. Assimilation of others’ characteristics to one’s own is particularly likely to occur in uncertain circumstances that provide little information to base judgments on, such as estimating the age of a briefly presented ambiguous figure.
Transjugular intrahepatic portosystemic shunt: a meta-analysis of 8 mm versus 10 mm stents

Introduction Transjugular intrahepatic portosystemic shunt (TIPS) is an approach that is used to alleviate portal hypertension-related symptoms. The optimal stent diameter for TIPS remains controversial. Aim To assess outcomes in patients who underwent TIPS using 8 mm and 10 mm stents. Material and methods The PubMed, Embase, and Cochrane Library databases were queried for all pertinent studies. The meta-analysis was conducted using RevMan v5.3. This meta-analysis was registered at the PROSPERO website (Number: CRD42020212392). Results Eighty-two potentially relevant articles were initially detected, with seven of these ultimately being included in this meta-analysis. Patients in the 10 mm stent group exhibited a significantly higher Δportosystemic pressure gradient (ΔPPG) relative to the 8 mm group (p = 0.04), whereas no differences between groups were observed with respect to postoperative hepatic encephalopathy (HE, p = 0.25), re-bleeding (p = 0.82), liver transplantation (p = 0.45), or mortality (p = 0.43) rates. The TIPS dysfunction rate was significant lower in the 10 mm group (p = 0.01). In Asian studies, the postoperative HE rate was found to be significantly lower in the 8 mm group relative to the 10 mm group (p = 0.02), whereas all other endpoints were comparable between these groups. In Western studies, ΔPPG values were significantly greater in the 10 mm group (p < 0.0001), whereas all other endpoint data were comparable between these groups. Conclusions TIPS with 10 mm stents provides a lower TIPS dysfunction rate. However, 8 mm stents may be recommended for Asian patients, as they can decrease the risk of postoperative HE.
Fabrication of Transparent ZnO Thick Film with Unusual Orientation by the Chemical Bath Deposition

We report a fabrication of transparent ZnO thick films by a chemical bath deposition using zinc acetate ethanolic–aqueous solutions with cetyltrimethylammonium chloride (CTAC). In this system, CTAC plays a particular role in nucleation and crystal growth of ZnO, and the micrometer-thick ZnO films formed on ZnO-buffered glass substrates. The resultant ZnO thick films show a high transmittance of around 80% in the visible region. An orientation of ZnO nuclei formed on the substrates in the early stage is different from a c-axis orientation of the ZnO-buffer layer, and the resultant ZnO thick films also show the unusual orientation. The detailed information on the orientation of these ZnO films was analyzed based on X-ray diffraction (XRD) 2θ/θ scan measurements at angles between in-plane and out-of-plane geometries. According to the results, the c-axis of ZnO is tilted at around 40–50° with respect to the film normal, and the micrometer-thick ZnO films exhibit the (112)-plane orientation by adjusting the CT.
A Cautionary Tale About Detecting Malware Using Hardware Performance Counters and Machine Learning

Editor’s note: This article revisits the literature around the use of hardware performance counters for malware detection, highlighting discrepancies, and providing a retrospection of challenges for future research. —Rosario Cammarota, Intel Labs —Francesco Regazzoni, University of Amsterdam and Università della Svizzera Italiana.
ADMM Check Node Penalized Decoders for LDPC Codes

Alternating direction method of multipliers (ADMM) is an efficient implementation of linear programming (LP) decoding for low-density parity-check (LDPC) codes. By adding penalty terms to the objective function of the LP decoding model, ADMM variable node (VN) penalized decoding can suppress the non-integral solutions and improve the frame error rate (FER) performance in the low signal-to-noise ratio (SNR) region. In this paper, we propose a novel ADMM check node (CN) penalized decoding algorithm. Codeword solutions which satisfy all parity-check equations will have smaller penalty values than non-codeword solutions, including the non-integral solutions. We discuss the required properties of CN-penalty functions, propose a few functions that satisfy those properties, and study their performance/complexity trade-offs. We also investigate the convergence properties of the proposed algorithm and prove that its performance is independent of the transmitted codeword. Using Monte Carlo simulations and instanton analysis, we then demonstrate that the proposed CN-penalized decoder outperforms ADMM VN penalized decoders in both waterfall and error floor regions. This comes at the expense of some increase in the decoding complexity.
Effect of N-fixing Bacteria on Nitrogen Fertilizer Requirements for some Sugar Beet Varieties

Two field trials were carried out at Tamiya Agricultural Research Station, (latitude of 29.58 ° N and longitude of 30.96 ° E), Fayoum Governorate,Egypt, during 2018/2019 and 2019/2020 seasons to study the relative importance of nitrogen-fixing bacteria i.e. Bacillus polymyxa (BC)and Azospirillum brasilense (AZS) as a soil drench under mineral nitrogen fertilizer levels and their effects on some sugar beet varieties. A split-plot design was used. Four treatments of nitrogen fertilization (80 kg N/fed ”control”, 60 kg N/fed + soil drench with BC, 60 kg N/fed + soil drench with AZS and 60 kg N/fed + soil drench with a mixture of BC and AZS) were occupied the main plots, whereas, six varieties (Beta303, Sirona, Panther,Des9003, Athospoly and Maximus) were distributed randomly in the sub-plots. Adding 60 kg N/fed + soil drench with a mixture of AZS and BC was adequate to produce the economical values of extractable sugar%, root and sugar yields/fed. Varieties Sirona and Maximus had the highest values of root and sugar yields/fed. Significant interactions effects among nitrogen treatments and varieties on the studied traits were discussed. Root and sugar yields/fed were significantly and positively correlated with leaf area index and crop growth rate, root diameter and its fresh weight/plant, in both seasons. Under the environmental conditions of this study, it was found that sowing Sirona and/or Maximus varieties under fertilization of 60 kg N/fed in combination with a mixture of BC and AZS at 5L/fed twice as a soil drench could be recommended to achieve the economical root and sugar yields/fed.
Understanding the viscosity of supercooled liquids and the glass transition through molecular simulations

Abstract We discuss a potential energy landscape (PEL) approach to calculate the characteristically sluggish viscous behaviour of supercooled liquids. This phenomenon is central to the theoretical understanding of the liquid-to-glass transition, a long-standing challenge in non-equilibrium statistical mechanics of amorphous states of matter. Experimentally, the shear viscosity of supercooled glass-forming liquids shows strong variations with the quench temperature. In particular, two types of behaviour are observed, Arrhenius and highly super-Arrhenius. Conceptually, the molecular description of the structural and dynamical processes underpinning the viscosity behaviour has become a topic of interest because of general implications for the kinetics of slow relaxation in the glassy state. We regard the supercooled liquid as an assembly of interacting particles undergoing thermal fluctuations such that the system evolves in space and time by crossing a series of potential energy barriers. To find these barriers and their corresponding atomic configurations, we apply an energy landscape sampling algorithm that maps out the evolution trajectories in the form of alternating sequences of local energy minima and saddle points. The energy sequences and the atomic coordinates constitute a body of atomic-scale data which we then process using two distinct methods. One is based on an effective activation barrier extracted from the transition-state pathway data, and the other is based on the linear response theory of statistical mechanics. The former is heuristic by being more physically transparent, while the latter is theoretically more rigorous. Through these two complementary calculations, an understanding of the temperature variations of shear viscosities of supercooled liquids, as well as the nature of fragile and strong behaviour of the glass transition, emerges. Our calculation provides a molecular-level account of the viscosities of supercooled liquids in a unified and consistent manner without invoking ad hoc assumptions. Relative to the nature of the glass transition, the usefulness of the PEL perspective is demonstrated, along with the concept of crossover between strong and fragile behaviour. In terms of advancing atomistic simulation capability, we believe the time-scale limitations of traditional molecular dynamics may be significantly extended through the use of metadynamics algorithms for sampling transition-state pathways.
Detection of Cardiac Structural Abnormalities in Fetal Ultrasound Videos Using Deep Learning

Artificial Intelligence (AI) technologies have recently been applied to medical imaging for diagnostic support. With respect to fetal ultrasound screening of congenital heart disease (CHD), it is still challenging to achieve consistently accurate diagnoses owing to its manual operation and the technical differences among examiners. Hence, we proposed an architecture of Supervised Object detection with Normal data Only (SONO), based on a convolutional neural network (CNN), to detect cardiac substructures and structural abnormalities in fetal ultrasound videos. We used a barcode-like timeline to visualize the probability of detection and calculated an abnormality score of each video. Performance evaluations of detecting cardiac structural abnormalities utilized videos of sequential cross-sections around a four-chamber view (Heart) and three-vessel trachea view (Vessels). The mean value of abnormality scores in CHD cases was significantly higher than normal cases (p < 0.001). The areas under the receiver operating characteristic curve in Heart and Vessels produced by SONO were 0.787 and 0.891, respectively, higher than the other conventional algorithms. SONO achieves an automatic detection of each cardiac substructure in fetal ultrasound videos, and shows an applicability to detect cardiac structural abnormalities. The barcode-like timeline is informative for examiners to capture the clinical characteristic of each case, and it is also expected to acquire one of the important features in the field of medical AI: the development of “explainable AI. ”
Conforto térmico e desempenho de bezerras Girolando alojadas em abrigos individuais com diferentes coberturas

This research was developed with the aim to characterize the effects of thermal ambience on physiological responses, comfort indexes and Holstein/Gir calves performance, housed in individual hutches covered with different materials. The experimental period was from January to March of 2012, lasting for 56 days, conducted by 24 crossbred calves with genetic of 7/8 Holstein-Gir. The treatments consisted of three types of covering materials, palm straw, recycled polymer tile and fiber cement tile. A completely randomized design was adopted and in order to compare means the Tukey test (p < 0.05) was used. The enthalpy and the radiant thermal load differed statistically in all treatments, being the lowest values presented by the recycled- tile-covered housings, 59.3 kJ kg-1 dry air and 444.8 W m-2, respectively. As for the physiological variables, there was no significant difference in any of the studied variables, however, the respiratory frequency in all treatments was high, and more emphasized on animals under fiber cement covered hutches (57.2 mov min-1) indicating that the animals were under heat stress.
Investor Sentiment and Volatility Prediction of Currencies and Commodities During the COVID-19 Pandemic

In this note, we examine whether the volatility predictive power of investor sentiment for currencies and commodities is sensitive to the COVID-19 pandemic. The Credit Suisse Fear Barometer (CSFB) and the VIX are used to measure investor sentiment. The volatility of seven major currencies, gold, and oil is investigated. Using daily data from 2005 to 2020, we show that VIX is a better predictor than CSFB. However, they have no predictive power during the COVID-19 pandemic period. This may be attributed to the different nature of fear sentiment during the crisis.
Mini-cutting of Plathymenia reticulata benth. with ministumps conducted in suspended seedbed and tubes

Background: Despite the importance of Plathymenia reticulata for forestry and ecological purposes, a protocol for the vegetative propagation of the species remains unclear mainly due to the low adventitious rooting of the propagules of the species. In this sense, this work aimed to evaluate the rooting of minicuttings of juvenile materials of P. reticulata and our hypothesis: (1) maintaining propagules under mist chamber for different periods affects the rooting process; (2) the mini-stump management system due to the restriction of the root system affects the production of mini-cuttings and the quality of clonal seedlings. Results: It was not necessary for more than 30 days in a mist chamber to induce rooting. The highest percentage of rooting was obtained 50 days after staking. Mini-gardens set up in suspended seedbed and tubes (280 cm 3 ) had the average mini-cuttings productivity of 4.32 and 2.06, respectively, over 270 days of exploration (monthly collections). At 120 days after staking, there was no difference in the survival and in the final quality of clonal seedlings produced. However, clonal seedlings from minigarden in tubes had higher height, leaf area, and number of first-order roots. Regardless of the minigarden management, the clonal seedling production index was 50%. Conclusion: We can conclude that P. reticulata seedling production via mini-cutting technique is possible.
Operating Temperature Range of Phosphorous-Doped Optical Fiber Dosimeters Exploiting Infrared Radiation-Induced Attenuation

Point or distributed optical fiber (OF)-based dosimeters can exploit the observed linear dependence of the radiation-induced attenuation (RIA) at 1550 nm in phosphosilicate OFs to monitor the total ionizing dose (TID). The temperature dependence of the radiation sensitivity coefficients at 1550 nm (expressed in dB km<inline-formula> <tex-math notation="LaTeX">$^{-1}$ </tex-math></inline-formula> Gy<inline-formula> <tex-math notation="LaTeX">$^{-1}$ </tex-math></inline-formula>) of three phosphorus-doped single-mode OFs has been investigated between −80 °C and 300 °C for TID ranging from 1 Gy to 1 kGy(SiO<sub>2</sub>). Our measurements reveal the same temperature dependence of the calibration factor for the three fibers at the higher temperatures (>120 °C) where the P1 defects, at the origin of the IR-RIA, are metastable. However, the uncertainties on the TID measurements through the fiber-based dosimeter remain within the 15% for temperatures ranging from −80 °C to 120 °C for the three tested fibers. The independence of the RIA and then of the dose measurements from the dose rate is also maintained in this temperature range.
FINITE ELEMENT METHOD BASED DESIGN AND ANALYSIS OF A LOW TORQUE RIPPLE DOUBLE-STATOR SWITCHED RELUCTANCE MOTOR

Double-stator switched reluctance motors (DSSRMs) acquire attention because of their high torque/power generating capability compared to conventional and segmented rotor switched reluctance motors. One of the main limiting performance indices of such motors for industrial applications is its high torque ripple. This paper proposes a 12/10/12 pole DSSRM with an angular shift of half of the stroke angle between inner and outer stators. The respective phase windings of the inner and outer stators are parallelly excited with the same phase angle shift to reduce the torque ripple. Each rotor segment is constructed with a pair of half rotor segments that are isolated from each other through the insertion of a non-magnetic isolator between them. Firstly, the design hypothesis for a low torque ripple DSSRM has been presented; thereafter, some geometric modifications have been suggested and investigated to obtain a nearby response in the proposed DSSRM. The calculation of the width of the non-magnetic isolator, modification in the pole height of outer stator and modification in the arc angles of rotor segments/stator poles are discussed in detail. The effectiveness of the proposed motor is investigated through a 2D finite-element modelling and simulation in ANSYS/MAXWELL software. Simulation results show that the torque ripple is significantly reduced by 74.9% in the proposed DSSRM compared to the baseline DSSRM.
Market performance and corporate governance in banking sector Indonesia stock exchange

--This research aimed to determine the effect of market performance and corporate governance on the banking sector listed on the Indonesia Stock Exchange (IDX). The sample used as many as 20 companies during the 2015-2019 period using a purposive sampling technique. The data analysis technique used is linear regression analysis. The results obtained from the research are that Earnings per Share and Price Earnings Ratio influences stock returns in the banking sector and Good Corporate Governance can moderate Earnings per Share and Price Earnings Ratio on stock returns. Keywords---earnings per share, good corporate, good governance, price-earnings ratio, stock return.
Use of coal fly ash for simultaneous co-adsorptive removal of phenol and cyanide from simulated coke wastewater

The present study deals with the process parameter optimization and modeling of simultaneous adsorption of phenol and cyanide from simulated coke wastewater onto acid treated coal fly ash. At a temperature of 30 °C , pH of 9 and adsorbent dose of 40 g L -1 , optimum removal of phenol and cyanide was found to be 67 and 82%, respectively for initial concentration of 200 mg L -1 phenol and 20 mg L -1 cyanide. Both single-component and multi-component isotherms were applied to the experimental data in the range of initial concentration of 100-1000 mg L -1 of phenol and 10-100 mg L -1 of cyanide. Extended Langmuir and extended Freundlich isotherms were found to be best fitted model for phenol and cyanide, respectively. The monolayer capacity of fly ash as calculated by extended Langmuir isotherm was 248 mg phenol g -1 of fly ash and 1.2 mg cyanide g -1 of fly ash. Kinetic studies revealed chemisorptions to be the mechanism of adsorption of both phenol and cyanide. Thermodynamic parameters viz, ∆G 0 , ∆H 0 and ∆S 0 were calculated as -1.7, -7.3 kJ mol -1 , -0.05 kJ mol -1 K -1 for phenol and -3.8, 24 kJ mol -1 and 0.09 kJ mol -1 K -1 for cyanide adsorption, respectively indicating process of phenol adsorption onto fly ash as exothermic and spontaneous while that of cyanide as endothermic in nature.
Dual-Features Student-t Distribution Mixture Model Based Remote Sensing Image Registration

In the work, we present a novel multiviewpoint and multitemporal remote sensing image registration method based on a dual-features Student-<inline-formula> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula> distribution mixture model (DSMM) under a variational Bayesian (VB) framework. The main contributions of the work are: 1) guided image filter (GIF) is adopted to smooth edges and strengthen ridges of images for heightening characteristics of feature point; 2) a Student-<inline-formula> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula> distribution mixture model (SMM) based DSMM designs a global and local descriptor to estimate correspondences from local to global scale; and 3) local structure constraints are designed to preserve relationships of neighbors of points and the scale of neighborhood structure of points to constrain transformation. The experimental results demonstrate the better performance of our DSMM against five state-of-the-art methods.
SNACS Annotation of Case Markers and Adpositions in Hindi

We present in-progress annotation of semantic relations expressed through adpositions and case markers in a Hindi corpus. We used the multilingual SNACS annotation scheme, which has been applied to a variety of typologically diverse languages. Annotation problems in Hindi are examined and used to suggest changes to SNACS. We look towards finalizing the corpus and using it for future work in typology and semantic role-dependent tasks.
Optimal nonparametric change point analysis

: We study change point detection and localization for univariate data in fully nonparametric settings, in which at each time point, we acquire an independent and identically distributed sample from an unknown distribution that is piecewise constant. The magnitude of the distributional changes at the change points is quantiﬁed using the Kolmogorov–Smirnov distance. Our framework allows all the relevant parameters, namely the minimal spacing between two consecutive change points, the minimal magnitude of the changes in the Kolmogorov–Smirnov distance, and the number of sample points collected at each time point, to change with the length of the time series. We propose a novel change point detection algorithm based on the Kolmogorov–Smirnov statistic and show that it is nearly minimax rate optimal. Our theory demonstrates a phase transition in the space of model parameters. The phase transition separates parameter combinations for which consistent localization is possible from the ones for which this task is statistically infeasible. We provide extensive numerical experiments to support our theory.