Miracle-dz/UniFAR-FTUs huggingface dataset:
Reproducibility as Side Effect

The ability to keep records and reproduce experiments is a critical element of the scientific method for any discipline. However, the recording and publishing of research artifacts that allow to reproduce and directly compare against existing research continue to be a challenge. In this paper, we propose an experiment précis framework that helps the experiment repeatability. Guided by the framework, we implement a prototype tool called ReGen which generates repeatable experiment scripts that can be used or shared along with a detailed experiment description automatically. Evaluation shows that ReGen is effective in reducing the researcher’s efforts of creating a repeatable experiment in a real setting.
Risk-Sharing and Information: Theory and Measurement in Village Economies

RISK-SHARING A N D INFORMATION: THEORY A N D M E A S U R E M E N T VILLAGE ECONOMIES IN ETHAN LIGON A B S T R A C T . A r r a n g e m e n t s for a c h i e v i n g efficient r i s k - s h a r i n g v a r y d e p e n d i n g o n the i n f o r m a t i o n a v a i l a b l e t o agents i n the e c o n o m y . T h e u s u a l E u l e r e q u a t i o n r e s t r i c t s efficient a l l o c a t i o n s i n a n e c o n o m y w h i c h o b e y s the p e r m a n e n t i n c o m e h y p o t h e s i s , w h i l e efficient a l l o c a t i o n s i n a n e c o n o m y w i t h p r i v a t e i n f o r m a t i o n a n d l o n g - t e r m c o n t r a c t s satisfy a n e a r l y s y m m e t r i c r e s t r i c t i o n , b u t not the E u l e r e q u a t i o n . F u l l i n s u r a n c e a r r a n g e m e n t s are u n i q u e i n t h a t t h e y satisfy b o t h r e s t r i c t i o n s . W e l o o k at a n e n v i r o n m e n t i n w h i c h i t seems l i k e l y t h a t l o n g - t e r m c o n t r a c t s p l a y a role i n m i t i g a t i n g the effects o f p r i v a t e i n f o r m a t i o n : t h r e e v i l l a g e e c o n o m i e s i n S o u t h I n d i a . T h e e v i d e n c e t h a t c o n s u m p t i o n a l l o c a t i o n s satisfy the p r i v a t e i n f o r m a t i o n r e s t r i c t i o n is q u i t e s t r o n g i n t w o o f the t h r e e v i l l a g e s ; the e v i d e n c e for the t h i r d v i l l a g e is m i x e d . INTRODUCTION T h i s paper attempts to characterize and test the behavior of consumption in a class of private information models. Interest in this class of models is motivated by the failure of 'permanent income' models and complete markets models, two workhorses of economic theory, to adequately account for the role which i n d i v i d u a l income plays in determining consumption, particularly in the village economies of developing countries. A l t h o u g h many other researchers have appealed to private information in order to explain the shortcomings of existing models, this research may be the first to actually test tightly specified ver­ sions of the complete markets and permanent income models against an explicit private information alternative. 1.1. T h r e e economic regimes. E c o n o m i s t s ' models can often be classified according to what markets are present in t h e m . In this taxonomy, there is a locus of models near F r i e d m a n ' s work on the permanent income hypothesis; models which have a full set of spot and credit markets, and which we will assign to the permanent income regime. T h i s regime includes i m p o r t a n t contribu­ tions by M u t h (1960), Bewley (1977) and H a l l (1978). F o r the purposes of this research, this last contribution is of particular interest because of H a l l ' s seminal role in proposing to test the i m p l i ­ cations (derived from the Euler equations) of the permanent income model. C o n s u m p t i o n in these permanent income models depends on the nature of the individual income processes of agents. Date: O c t o b e r 1996.
Machine Learning and Steel

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Tricritical Behavior in Charge-Order System

Tricritical point in charge-order systems and its criticality are studied for a microscopic model by using the mean-field approximation and exchange Monte Carlo method in the classical limit as well as by using the Hartree–Fock approximation for the quantum model. We study the extended Hubbard model and show that the tricritical point emerges as an endpoint of the first-order transition line between the disordered phase and the charge-ordered phase at finite temperatures. Strong divergences of several fluctuations at zero wavenumber are found and analyzed around the tricritical point. Especially, the charge susceptibility χ c and the susceptibility of the next-nearest-neighbor correlation χ R are shown to diverge and their critical exponents are derived to be the same as the criticality of the susceptibility of the double occupancy χ D ( 0 ) . The singularity of conductivity at the tricritical point is clarified. We show that the singularity of the conductivity σ is governed by that of the carrier density.
Mexican origin First-generation College Students Activating Funds of Knowledge to Navigate Basic Needs Insecurity

The present study examines the presence of Basic Needs Insecurity (BNI) among Mexican origin first-generation college students. Specifically, this transformative mixed methods study explores BNI in access to healthcare, housing, employment, and transportation among study participants. Most importantly, this research illuminates students’ Funds of Knowledge (FK) as assets and strategies that Mexican origin first-generation college students activate to navigate BNI. Findings reveal higher levels of BNI present among first-generation compared to continuing-generation college students and highlight familial, community, and institutional supports as sources of FK for Mexican origin first-generation college students to address BNI. Implications for research and practice are provided.
Assessment on durability of lightweight concrete using alkali modified fly ash based atrificial coarse aggregate (FACA)

ABSTRACT Thermal power plant is the backbone of India’s energy generation comprising of more than 50%. Since Indian coal is of low grade with ash content of the order of 30–55% in comparison with imported coal which has low ash content of the order of 3–15%, huge piles of fly ash is left over which poses environmental degradation. In order to reduce its harmful effects on environment, we have to reuse/recycle this industrial by-product. As concrete contains 80% coarse aggregate, huge quantity of fly ash waste can be utilized if we reuse it as artificial coarse aggregate. This work compiles the results of a pilot scale study on durability properties of concrete made from fly ash-based artificial coarse aggregate (FACA). The molarity of NaOH, NaOH-to-Na2SiO3 ratio and alkaline-solution-to-fly-ash ratio used in this research are 8 M, 0.5 and 0.4 respectively. The coarse aggregate is produced by crushing the geopolymer mass in a crusher. The fundamental durability properties of the concrete (FACACRETE) prepared from FACA is compared with the conventional concrete (using crushed granite stone) at M20, M25 and M30 grades of concrete. It is observed that on increasing the grade of concrete, the ultrasonic pulse velocity test gives better result for both conventional concrete and FACACRETE.
Untargeted Metabolomics by Using UHPLC–ESI–MS/MS of an Extract Obtained with Ethyl Lactate Green Solvent from Salvia rosmarinus

Salvia rosmarinus (Lamiaceae), previously known as Rosmarinus officinalis, is a plant cultivated worldwide, native to the Mediterranean region. Its leaves are traditionally used for cooking. This species possesses numerous biological activities, including antioxidant, antimicrobial, anticancer, anti-inflammatory, and hepatoprotective properties. These biological properties are due to the presence of phenolic compounds, including rosmarinic acid and phenolic diterpenoids, such as carnosic acid and carnosol. In this study, we investigated the chemical composition of a green extract obtained by maceration with ethyl lactate for the first time. Seventy-five compounds were tentatively identified by UHPLC–ESI–MS/MS, including six organic acids, six cinnamic acid derivatives, five fatty acids, eighteen flavonoids, and thirty-eight terpenoids. Thus, abietane-type diterpenoids from the ethyl lactate extract were the predominant diterpenoids in the Chilean S. rosmarinus species, in contrast to the Chinese species, in which labdane and isopimarane-type diterpenoids were found for the first time. Finally, our study confirms that the extraction of S. rosmarinus with green ethyl lactate as a solvent is efficient and sustainable for the identification of flavonoids, phenols, and terpenoids from leaves.
Boosting eWOM through Social Media Brand Page Engagement: The Mediating Role of Self-Brand Connection

The present study’s objective is to investigate the influence of active and passive social media brand page engagement on eWOM, via self-brand connection. To accomplish this objective, an online survey was conducted among a sample of Facebook users from Romania, Facebook being the most popular social network worldwide, and Romania being an adequate representation of a European developing country. To assess the proposed research model, we used partial least squares structural equation modeling (PLS-SEM). Our results show that social media brand page engagement, either passive or active, has a positive impact eWOM, both directly and indirectly, via self-brand connection. Additionally, our research reveals that the two types of social media brand page engagement generate eWOM distinctly: although passive engagement has a considerably stronger direct influence on self-brand connection, active engagement is equally influential for both self-brand connection and eWOM. However, due to the mediating role of self-brand connection, the total effect on eWOM is relatively equal for both passive and active engagement. The research provides practical implications for social media marketers, emphasizing the importance of increasing consumers’ engagement with social media brand pages for generating eWOM and, consequently, to attract new customers and to reinforce brand loyalty for existing ones.
A Novel PSMA-Targeted Probe for NIRF-Guided Surgery and Photodynamic Therapy: Synthesis and Preclinical Validation

A total of 20% to 50% of prostate cancer (PCa) patients leave the surgery room with positive tumour margins. The intraoperative combination of fluorescence guided surgery (FGS) and photodynamic therapy (PDT) may be very helpful for improving tumour margin delineation and cancer therapy. PSMA is a transmembrane protein overexpressed in 90–100% of PCa cells. The goal of this work is the development of a PSMA-targeted Near InfraRed Fluorescent probe to offer the surgeon a valuable intraoperative tool for allowing a complete tumour removal, implemented with the possibility of using PDT to kill the eventual not resected cancer cells. PSMA-617 binding motif was conjugated to IRDye700DX-NHS and the conjugation did not affect the photophysical characteristics of the fluorophore. The affinity of IRDye700DX-PSMA-617 towards PCa cells followed the order of their PSMA expression, i.e., PC3-PIP > LNCaP > PC3, PC3-FLU. NIRF imaging showed a significant PC3-PIP tumour uptake after the injection of 1 or 5 nmol with a maximum tumour-to-muscle ratio (ca. 60) observed for both doses 24 h post-injection. Importantly, urine, healthy prostate, and the bladder were not fluorescent at 24 h post-injection. Flow cytometry and confocal images highlighted a co-localization of PSMA+ cells with IRDye700DX-PSMA uptake. Very interestingly, ex vivo analysis on a tumour specimen highlighted a significant PSMA expression by tumour-associated macrophages, likely attributable to extracellular vesicles secreted by the PSMA(+) tumour cells. FGS proved that IRDye700DX-PSMA was able to easily delineate tumour margins. PDT experiments showed a concentration-dependent decrease in cell viability (from 75% at 10 nM to 12% at 500 nM), whereas controls did not show any cytotoxicity. PC3-PIP tumour-bearing mice subjected to photodynamic therapy showed a delayed tumour growth. In conclusion, a novel PSMA-targeted NIRF dye with dual imaging-PDT capabilities was synthesized and displayed superior specificity compared to other small PSMA targeted molecules.
Forecasting Energy Demand Using Conditional Random Field and Convolution Neural Network

Electric load forecasting has been identified as an effective strategy to increase output and revenues in electrical manufacturing and distribution organizations. Several strategies for forecasting power consumption have been suggested; however, they all fail to account for small variations in power demand throughout the prediction. Therefore, the aim of this study was to develop a CRF-based power consumption prediction technique (CRF-PCP) to meet the difficulty of estimating energy consumption (EC). The EC of regions in the area is forecasted using convolution neural networks (CNNs) and conditional random fields (CRFs). Then, using the cloud, the predicted results are delivered to the electricity distribution system. To our knowledge, this is the first attempt to forecast electricity demand using CNN and CRF algorithms. In comparison to state-of-the-art algorithms, this proposed technique achieves 98.9 % accuracy. This recommended work also obtained minimum values of root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and mean bias error (MBE) by using 10-fold cross-validation (CV) and a hold-out (CV) methodology.
Opacity calculations for stellar astrophysics

Opacity is a key ingredient of stellar structure and evolution. In the present work, we recall the role of opacity in asteroseismology, focusing mainly on two kinds of astrophysical objects: $\beta$ Cephei-type stars, and the Sun. The detailed opacity code SCO-RCG for local-thermodynamic-equilibrium plasmas is described and interpretation of laser and Z-pinch experiments are presented and discussed. The possible role of multi-photon processes on radiative accelerations is outlined, and the main aspects of opacity modeling which should be improved are mentioned.
Welding Training Simulation using Virtual Reality with Multiple Marker Tracking Method

This paper presents the use of a vision-based marker with a Virtual Reality (VR) system in welding training simulation to gain psychomotor skills for various welding positions. This paper addresses the lack of conceptual design and design management framework which leverage the combination of the VR world and tracking technique. The research explores the area of VR in welding training and how multiple markers tracking methods can be utilized to overcome the tracking problems in VR for welding training simulation. A prototype system is designed and developed. The combined VR and multiple tracking method features are useful and effective for physical-based VR learning such as in welding training simulation.
Activation of Piezo1 Increases Na,K-ATPase-Mediated Ion Transport in Mouse Lens

Lens ion homeostasis depends on Na,K-ATPase and NKCC1. TRPV4 and TRPV1 channels, which are mechanosensitive, play important roles in mechanisms that regulate the activity of these transporters. Here, we examined another mechanosensitive channel, piezo1, which is also expressed in the lens. The purpose of the study was to examine piezo1 function. Recognizing that activation of TRPV4 and TRPV1 causes changes in lens ion transport mechanisms, we carried out studies to determine whether piezo1 activation changes either Na,K-ATPase-mediated or NKCC1-mediated ion transport. We also examined channel function of piezo1 by measuring calcium entry. Rb uptake was measured as an index of inwardly directed potassium transport by intact mouse lenses. Intracellular calcium concentration was measured in Fura-2 loaded cells by a ratiometric imaging technique. Piezo1 immunolocalization was most evident in the lens epithelium. Potassium (Rb) uptake was increased in intact lenses as well as in cultured lens epithelium exposed to Yoda1, a piezo1 agonist. The majority of Rb uptake is Na,K-ATPase-dependent, although there also is a significant NKCC-dependent component. In the presence of ouabain, an Na,K-ATPase inhibitor, Yoda1 did not increase Rb uptake. In contrast, Yoda1 increased Rb uptake to a similar degree in the presence or absence of 1 µM bumetanide, an NKCC inhibitor. The Rb uptake response to Yoda1 was inhibited by the selective piezo1 antagonist GsMTx4, and also by the nonselective antagonists ruthenium red and gadolinium. In parallel studies, Yoda1 was observed to increase cytoplasmic calcium concentration in cells loaded with Fura-2. The calcium response to Yoda1 was abolished by gadolinium or ruthenium red. The calcium and Rb uptake responses to Yoda1 were absent in calcium-free bathing solution, consistent with calcium entry when piezo1 is activated. Taken together, these findings point to stimulation of Na,K-ATPase, but not NKCC, when piezo1 is activated. Na,K-ATPase is the principal mechanism responsible for ion and water homeostasis in the lens. The functional role of lens piezo1 is a topic for further study.
Charge-Hall effect driven by spin force: reciprocal of the spin-Hall effect

A new kind of charge-Hall effect is shown. Unlike in the usual Hall effect, the driving force in the longitudinal direction is a spin force, which may originate from the gradient of a Zeeman field or a spin-dependent chemical potential. The transverse force is provided by a Berry curvature in a mixed position-momentum space. We can establish an Onsager relation between this effect and the spin-Hall effect provided the spin current in the latter is modified by a torque dipole contribution. This remarkable relation leads to new ways for experimental detection of spin accumulation predicted by the spin Hall effect.
Two‐dimensional beam steering array using planar eight‐element composite right/left‐handed leaky‐wave antennas

A two‐dimensional beam steering array composed of an eight‐element antenna array using composite right/left‐handed leaky‐wave antennas fed by an 8 × 8 Butler matrix network is designed at X‐band. An eight‐way beam switching in one direction by input port switching and a continuous beam steering in the other direction by frequency sweep are achieved. A wide range beam steering operation covering from −55 to +53 degrees by port switching and from −37 to +27 degrees by frequency sweep is demonstrated with the maximum gain of 9.2 dBi.
Near-Infrared Imaging of the Host Galaxies of Three Radio-loud Quasars at z ∼ 1.5

We present high spatial resolution near-infrared H-band (1.65 μm) images, taken with ISAAC on UT1 of the ESO Very Large Telescope, of three radio-loud quasars at z ~ 1.5, as a pilot study for imaging of a larger sample of radio-loud and radio-quiet quasars in the redshift range 1 < z < 2. We are able to clearly detect the host galaxy in two quasars (PKS 0000-177 and PKS 0348-120) and marginally in the third (PKS 0402-362). The host galaxies appear compact (average bulge scale length R(e) ~ 4 kpc) and luminous [average MH = -27.6 ± 0.1 ]. They are ~2.5 mag more luminous than the typical galaxy luminosity [M = -25.0 ± 0.2], and are comparable to the hosts of low-redshift radio-loud quasars [MH ~ -26], taking into account passive stellar evolution. Their luminosities are also similar to those of high-redshift radio galaxies. All three quasars have at least one close companion galaxy at a projected distance less than 50 kpc from the quasar, assuming they are at the same redshift.
Integral field observations of damped Lyman‐α galaxies

We report preliminary results from a targeted investigation on quasars containing damped Lyman-α absorption (DLA) lines as well strong metal absorption lines, carried out with the Potsdam Multi Aperture Spectrophotometer (PMAS). We search for line-emitting objects at the same redshift as the absorption lines and close to the line of sight of the QSOs. We have observed and detected the already confirmed absorbing galaxies in Q2233+131 (zabs = 3.15) and Q0151+045 (zabs=0.168), while failing to find spectral signatures for the z = 0.091 absorber in Q0738+313. From the Q2233+131 DLA galaxy, we have detected extended Lyα emission from an area of 3″ ×5″. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Experimental Study of a Tubular Solar Distillation System with Heat Exchanger Using a Parabolic Trough Collector

One way to overcome the scarcity of clean water through sustainable approach is by utilizing a solar distillation system. This easy-to-use technology is adopting tubular solar distillation. The three main components, which are the most essential for producing the amount of permeate, are the solar collector, tubular and heat exchanger (HE). This study aims to determine the performance of a tubular solar distillation device equipped with HE using a parabolic trough collector (PTC). The PTC has an area of 5.1 m2 covered with a solar reflective chrome film. Aluminum tubular acts as the feedwater heater. The HE is placed inside the tubular, which acts as a coolant to convert the steam phase into freshwater/permeate and as a feedwater heater to flow into the tubular. In the present study, several parameters were tested: comprise temperature, solar radiation, pressure, humidity, mass flow rate, permeate productivity and efficiency. This study demonstrated the production of a sufficient amount of permeate, which was 5.32 L for 6 h. The efficiency of this device yielded a peak of 48.2% during solar radiation of 813 W/m2 in an average ambient temperature of 32 °C, with an overall average of 44.59%.
A Spectral Algorithm for Learning Hidden Markov Models

Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computationally hard (under cryptographic assumptions), and practitioners typically resort to search heuristics which suffer from the usual local optima issues. We prove that under a natural separation condition (bounds on the smallest singular value of the HMM parameters), there is an efficient and provably correct algorithm for learning HMMs. The sample complexity of the algorithm does not explicitly depend on the number of distinct (discrete) observations— it implicitly depends on this quantity through spectral properties of the underlying HMM. This makes the algorithm particularly applicable to settings with a large number of observations, such as those in natural language processing where the space of observation is sometimes the words in a language. The algorithm is also simple: it employs only a singular value decomposition and matrix multiplications.