Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic programming for hydrological applications: to model or to forecast that is the question

Genetic programming (GP) is a widely used machine learning (ML) algorithm that has been applied in water resources science and engineering since its conception in the early 1990s. However, similar to other ML applications, the GP algorithm is often used as a data fitting tool rather than as a model building instrument. We find this a gross underutilization of the GP capabilities. The most unique and distinct feature of GP that makes it distinctly different from the rest of ML techniques is its capability to produce explicit mathematical relationships between input and output variables. In the context of theory-guided data science (TGDS) which recently emerged as a new paradigm in ML with the main goal of blending the existing body of knowledge with ML techniques to induce physically sound models. Hence, TGDS has evolved into a popular data science paradigm, especially in scientific disciplines including water resources. Following these ideas, in our prior work, we developed two hydrologically informed rainfall-runoff model induction toolkits for lumped modelling and distributed modelling based on GP. In the current work, the two toolkits are applied using a different hydrological model building library. Here, the model building blocks are derived from the Sugawara TANK model template which represents the elements of hydrological knowledge. Results are compared against the traditional GP approach and suggest that GP as a rainfall-runoff model induction toolkit preserves the prediction power of the traditional GP short-term forecasting approach while benefiting to better understand the catchment runoff dynamics through the readily interpretable induced models.
Construct validity and measurement invariance of the Asian Family Characteristics Scale in the Thai population

PurposeThe purpose of this paper was to establish the psychometric properties of the Asian Family Characteristics Scale (AFCS) in the Thai population.Design/methodology/approachThe 30-item AFCS originally developed in the Malay language was translated into Thai. Thai (n = 384) and Malay (n = 500) participants in Study 1 responded to the AFCS in their respective languages. The data were subjected to a confirmatory factor analysis with a measurement invariance test. In Study 2, Thai participants (n = 495) filled out the AFCS and Chulalongkorn Family Index, International Personality Item Pool-NEO, Self-Compassion Scale, Depression, Anxiety, and Stress Scale (DASS-21) and Satisfaction with Life Scale.FindingsStudy 1 showed that the measurement model of the Thai AFCS fit the data from the Thai population. The measurement invariance test confirmed that the structure and meaning of the AFCS are equivalent across the Thai and Malay samples. Study 2 demonstrated the AFCS's convergent validity by showing that the AFCS score had a positive correlation with the Chulalongkorn Family Inventory, self-compassion, agreeableness, conscientiousness, satisfaction with life and a negative correlation with neuroticism, depression, anxiety and stress. The AFCS's discriminant validity was supported by nonsignificant correlations with extraversion and openness to experience.Originality/valueThis paper is an attempt to develop a family characteristic measure specifically for the Asian population. The results provide empirical evidence for measurement invariance and validity of the scale in another Asian language, enhancing its cross-cultural generalizability.
An Advanced Artificial Intelligence System for Investigating Tropical Cyclone Rapid Intensification with the SHIPS Database

Currently, most tropical cyclone (TC) rapid intensification (RI) prediction studies are conducted based on a subset of the SHIPS database using a relatively simple model structure. However, variables (features) in the SHIPS database are built upon human expertise in TC intensity studies based on hard and subjective thresholds, and they should be explored thoroughly to make full use of the expertise. Based on the complete SHIPS data, this study constructs a complicated artificial intelligence (AI) system that handles feature engineering and selection, imbalance, prediction, and hyper parameter-tuning, simultaneously. The complicated AI system is used to further improve the performance of the current studies in RI prediction, and to identify other essential SHIPS variables that are ignored by previous studies with variable importance scores. The results outperform most of the earlier studies by approximately 21–50% on POD (Probability Of Detection) with reduced FAR (False Alarm Rate). This study built a baseline for future work on new predictor identification with more complicated AI techniques.
Shield Design of the First Protective Collimator in the METU-Defocusing Beamline (DBL) Project

Abstract The Middle East Technical University Defocusing Beamline (METU-DBL) is being constructed in order to perform single event effects tests for the electronic components in accordance with the European Space Agency (ESA) European Space Components Coordination (ESCC) No. 25100 standard. The aim of this beamline is to provide a suitable test area at the end of the beamline using the beam elements, such as collimators and magnets. Shielding is a crucial precaution for the safety of the radiation workers and the protection of the electronic components from the detrimental effects of radiation. In the METU-DBL, shielding studies have started with the first protective collimator because the proton beam hits the collimator, resulting in secondary particle production that increases the dose level in the research and development (R&D) room. The shielding studies of the first protective collimator used in the pretest setup of the METU-DBL are presented in this study. The whole beamline was defined in the FLUKA simulation program to calculate the absorbed radiation dose and make shielding designs. Various shielding designs were studied in FLUKA and the 15th one was selected as a suitable shielding design for the first protective collimator. This shield was manufactured and mounted on the first protective collimator and used in 20 irradiations during the pretests. At the end of 20 irradiations, it was observed that the shield is effective at decreasing the dose level in the R&D room.
Effect of Residue Type on Extractable Organic and Microbial Biomass Carbon Fractions Under Long-Term Soil Fertilization

The labile organic carbon (C) pool plays a vital role in soil biogeochemical transformation and can be used as a sensitive indicator of the response of soil quality to agricultural practice. However, little is known about how residue type and soil fertilization affect the incorporation of residue C into labile organic C pools. A 360-day laboratory incubation was conducted with the addition of 13C-labeled maize residues (root, stem and leaf) to unfertilized and organic-fertilized soils. A greater contribution of residue C to extractable organic C (EOC, 7.2%) was observed in the unfertilized soil than that in the organic-fertilized soil (6.0%). The contribution of residue C to microbial biomass C (MBC) was 20%-50% in the organic-fertilized soil, but only 10%-30% in the unfertilized soil. This suggests that, in organic-fertilized soil, there is accelerated transformation of residue C into microbial biomass and a higher capacity for residue C stabilization through greater, or more efficient anabolism. Moreover, the distribution of leaf C into MBC was higher than that from root and stem in the unfertilized soil, whereas more root C entered to EOC and MBC than from stem and leaf in the organic-fertilized soil. This shows that maize root can also be involved in microbial assimilation, but it depends on the initial soil nutrition. Overall, these findings deepen our understanding of the mechanisms of microbe-mediated C transformation processes, and provide relevant insights into the capture and incorporation of plant residue C into labile organic C pools driven by residue type and soil fertilization.
Evaluation of factors increasing the risk of silent brain infarction using multidetector computed tomography in patients undergoing carotid artery stenting

Objectives: This study aims to identify the factors increasing the risk of silent brain infarction using multidetector computer tomography (MDCT) in patients undergoing carotid artery stenting (CAS). Patients and methods: Medical data of a total of 24 patients (12 males, 12 females; mean age: 65.4±74 years; range, 50 to 76 years) who underwent CAS between December 2017 and July 2019 were retrospectively analyzed. The plaque characteristics of carotid arteries and the aortic arch structures were determined using MDCT before the procedure. The patients were divided into two groups based on the diffusion-weighted images after the procedure. Those with and without silent brain infarction were in Group 1 (n=10) and Group 2 (n=14), respectively. Both groups were compared in terms of aortic arch structures and the plaque characteristics. Results: There was a significant difference between the groups in terms of plaque in the aortic arch (n=8 vs. n=5, respectively, p=0.047). The number of irregular plaque surfaces, plaque length, and plaque volume were significantly higher in Group 1 than Group 2 (8 vs. 5, respectively; p=0.047; 21.8 vs. 17.6, respectively; p=0.045, and 991.1 vs. 740.3, respectively; p=0.015). The percentages of lipid components in total plaque volume were significantly higher in Group 1 (p=0.026). The receiver operating characteristic analysis revealed that 17.8% of lipid components in total volume had 64.3% sensitivity and 90% specificity in the differentiation of the groups. Conclusion: Evaluation of aortic arch structures and the plaque characteristics in carotid arteries using MDCT may be useful for predicting the risk of silent brain infarction after CAS.
Hedging and Competition

We study how risk management through hedging impacts firms and competition among firms in the life insurance industry - an industry with over 7 Trillion in assets and over 1,000 private and public firms. We show that firms that are likely to face costly external finance increase hedging after staggered state-level financial reform that reduces the costs of hedging. After hedging, these firms have lower risk and fewer negative income shocks. Post market reform, product market competition is also impacted. Firms that are previously more likely to face costly external finance, lower price, increase policy sales and market share relative to unaffected companies. The results are consistent with hedging allowing firms that face potential costly financial distress to decrease risk and become more competitive.
Failures of Gricean reasoning and the role of stereotypes in the production of gender marking in French

We partly replicate von der Malsburg et al. (2020)’s recent experiments investigating the relationship between speaker expectations, gender stereotypes and language use in English on a grammatical gender language: French. The results of our experiment show how the linguistic particularities of the English and French gender marking systems interact with speaker expectations and stereotypes to create different patterns of gender marking production. They also raise a puzzle for current theoretical and computational frameworks that formalize Gricean pragmatics, particularly those in which informativity (Gricean Quantity) is assumed to play a driving role in linguistic production. CÉLINE POZNIAK
Developing A Novel Coumarone-Phenyl Amide Functionalized [Gd(III)-Pt(IV)] Complex as High T1, T2 Relaxive M-MRI Contrast Agent for Cancer Diagnosis

Pt(IV) cored Gd(III) metal complex as a multimodal MRI contrast agent for cancer diagnosis is reported. The hetero nuclear complex [Pr-(DO3-Ch-Ph-Am-Gd(III))2Pt(II)] is highly soluble in water and stable at room temperature. The complex shows high longitudinal (r1p = 24.43 mM-1 s-1) and transversal (r2p = 38.61 mM-1 s-1) relaxivity values in neat aqueous solution at pH =7 and at 27 oC. The relaxivity value of the complex is greater than the low molecular weight, FDA approved MRI contrast agents. The presence of two water molecules in the first coordination sphere and a replaceable hydrogen atom in the linker enhances the proton relaxation rate and gives a huge relaxivity value. The r2p/r1P ratio of 1.58 confirms that the complex is a T1-weighted contrast agent. The presence of high polar coumarone pendant arm and high rigid acridone moieties in the complex make the complex as better anticancer agent for ovarian cancer. The high polar nature of the coumarone, phenyl amide, acridone moiety will show better binding efficiency with ovarian cancer creating CA125 glycoprotein.
A miniaturized three‐dimensional log periodic Koch‐dipole array antenna using T‐shaped top loading

A log periodic dipole array antenna (LPDA) is miniaturized by using top loading. The Koch dipole further helps to shrink the antenna size. Different from the traditional LPDA that features a planar structure, the proposed log periodic Koch‐dipole array (LPKDA) adopts two identical pairs of top‐loaded Koch‐dipoles that deploy orthogonally along the feed line. This results in a tree‐like three‐dimensional antenna geometry, which introduces one extra dimension of freedom for antenna designers. The influence of the top‐loading on antenna's impedance bandwidth is studied under the Wheeler and Chu's limit. The characteristic of the Koch‐dipole is analyzed. Taking the advantage of 3D printing technology to fabricate complex models, the proposed LPKDA is printed by selective laser melting using aluminum alloy. The simulated −10‐dB bandwidth is 117.4% (0.91‐3.54 GHz) The LPKDA has the average gain of 5.3 dBi over the 1 to 3.5 GHz impedance bandwidth in measurement. Radiation patterns agree well in simulation and measurement. Compared with conventional LPDA of the same impedance bandwidth, the proposed LPKDA features 42%‐dimensional reduction. This letter proves the feasibility of antenna optimization by using both innovative design method and advanced fabrication process.
In Vivo Self‐Powered Wireless Transmission Using Biocompatible Flexible Energy Harvesters

Additional surgeries for implantable biomedical devices are inevitable to replace discharged batteries, but repeated surgeries can be a risk to patients, causing bleeding, inflammation, and infection. Therefore, developing self‐powered implantable devices is essential to reduce the patient's physical/psychological pain and financial burden. Although wireless communication plays a critical role in implantable biomedical devices that contain the function of data transmitting, it has never been integrated with in vivo piezoelectric self‐powered system due to its high‐level power consumption (microwatt‐scale). Here, wireless communication, which is essential for a ubiquitous healthcare system, is successfully driven with in vivo energy harvesting enabled by high‐performance single‐crystalline (1 − x)Pb(Mg1/3Nb2/3)O3−(x)Pb(Zr,Ti)O3 (PMN‐PZT). The PMN‐PZT energy harvester generates an open‐circuit voltage of 17.8 V and a short‐circuit current of 1.74 µA from porcine heartbeats, which are greater by a factor of 4.45 and 17.5 than those of previously reported in vivo piezoelectric energy harvesting. The energy harvester exhibits excellent biocompatibility, which implies the possibility for applying the device to biomedical applications.
Enhanced computational imaging with encoding masks optimized by deep neural networks

This research investigates the usage of deep neural networks (DNNs) to optimize encoding masks that, when combined with digital imaging systems, can recover high spatial frequency content that would otherwise be filtered out by the OTF. It has been shown that Fourier ptychographic photography (FPP) can recover high resolution imagery by imaging scenes that have been illuminated by a controlled light source. Instead of a controlled light source, this research utilizes light encoding masks that are optimized by a DNN to allow for decreased blur and increased resolution of recovered imagery. A masks generator is optimized in a generative adversarial network (GAN) where generated masks are used to recover imagery through a FPP phase recovery algorithm. The masks and recovery algorithm are optimized according to a loss function comparing the recovered imagery to the pristine, undegraded imagery as dictated by a Wasserstein critic, a DNN model. This method creates masks optimal for recovering high frequency spatial information of specific imaged object types based on the training dataset used.
EXPERIMENTAL STUDY TO DETERMINE THE LOCAL CONDENSATION HEAT TRANSFER COEFFICIENTE FOR R134A FLOWING THROUGH A 4.8 MM INTERNAL DIAMETER SMOOTH HORIZONTAL TUBE

Refrigerant fluid R134a is commonly one of the most utilised in vapour compression cycles wordlide, wheter in dommestic HVAC or automotive regrigeration systems. This paper’s goal is to experimetnally determine the fluid local condensation Heat Transfer Coefficient (HTC), in several flor regimes. In this work, the mass flux was equal to 200, 250 and 300 kg/(m2s) and the fluid flowed through a smooth, horizontal 4.8 mm internal diameter aluminium pipe, during which its vapour quality varied along the entire quality range. A purpose built test rig was developed, in which fluid conditions were constantly monitored and controlled. Through measurements in temperature and pressure, an energy balance was used to calculate experimentally the local heat transfer coeeficient. Average results for the unit quality range equalled to 3781 , 3459 and 3944 W/m2K for saturation temperature equal to 30 C and the aforementioned mass velocities. Likewise, at 35C the averages HTC found were 2903, 3141 and 3898 W/m2K at the same mass flux rates. Later on, the experimental results were compared to ten commonly used HTC correlation found in relevant references, with Chato’s correlation returning the best fitting.
a-SiCxNy:H thin films for applications in solar cells as passivation and antireflective coatings

Amorphous a-SiCxNy:H thin films may be an alternative to a-Si:N:H coatings which are commonly used in silicon solar cells. This material was obtained by PECVD (13.56 MHz) method. The reaction gases used: silane, methane, nitrogen and ammonia. The structure of the layers were investigated by scanning electron microscopy (SEM) and infrared spectroscopy (FTIR). IR absorption spectra of a-SiCxNy:H layers confirmed the presence of various hydrogen bonds – it is important for passivation of Si structural defects. The ellipsometric measurements were implemented to determine the thickness of layers d, refractive index n, extinction coefficient k and energy gap Eg. The values of the energy gap of a-SiCxNy:H layers are in the range from 1.89 to 4.34 eV. The correlation between energy gap of materials and refractive index was found. Generally the introduction of N and/or C into the amorphous silicon network rapidly increases the Eg values.
Cross-cutting and Like-minded Discussion on Social Media: The Moderating Role of Issue Importance in the (De)mobilizing Effect of Political Discussion on Political Participation

ABSTRACT Using a student survey with multistage probability sampling in Taiwan, we revisited the deliberation-participation paradox by examining the relationship between cross-cutting/like-minded discussion and online political participation, emphasizing the moderating role of issue importance and focusing particularly on the social media context and two political issues in Taiwan. We found that political ambivalence, which has been proposed as the underlying mechanism between cross-cutting exposure and participation, plays a significant mediating role. Cross-cutting discussion demobilizes participation indirectly through increasing political ambivalence, while like-minded discussion mobilizes participation indirectly through decreasing political ambivalence. More importantly, the two indirect effects are conditioned upon the level of issue importance in that the demobilizing effect of cross-cutting discussion was weakened while the mobilizing effect of like-minded discussion was strengthened when the level of issue importance increased.
Analyzing and Ranking Prevalent News over Social Media

Since the growth of social media, news outrage over mass through social media has become evident and its control over all information sources has increased significantly. Social media services such as twitter collects enormous amounts of information and allows media companies to publish news related information as tweets. Every other big news company has its twitter account to public news in form of tweets. Beside news social media platforms has enormous amount of news attached to them as well. To make correct and better information reach to users we have to filter noise and segregate the content based on similarity and content’s respective value. Even after filtering noise, information payload exists in data so to prioritize information must be ranked in order of considered factors. In our proposed work, news are filtered and ranked based on three factors. First, media focus (MF) which tells the temporal prevalence of a particular topic in news media. Second, user attention (UA) which tells how mass is responding to the topic. Last, is the user interaction which tells how users are forming view over the topic. Our proposed work introduces an unsupervised machine learning framework which identifies news topics prevalent in both social media and the news media, and then ranks them ordering them using their degrees of MF, UA, and UI.
Biotic Resistance Against Invasive Macroalgae: The Role of Omnivorous Sparid Fishes in the Herbivory on Caulerpa Cylindracea

Herbivory has long been considered an important component of biotic resistance against macroalgae invasions in marine habitats. However, most of the studies on herbivory of invasive algae refer only to consumption by strictly herbivorous organisms, whereas consumption by omnivorous organisms has been largely ignored and rarely quantified. In this study, we assess whether the commonest omnivorous sparid species in the Mediterranean Sea are consuming the highly invasive alga, Caulerpa cylindracea, and determine its importance in their diet and their electivity towards it as a source of food. Our results confirm that three of the four fish species we studied do, in fact, consume C. cylindracea, but in most cases, the importance of C. cylindracea in the diet was low. Indeed, the low electivity values confirm that all four fish species avoid feeding on the invasive alga and that it is probably consumed accidentally. However, despite animals and detritus being the main food for these sea bream species, several individual specimens were found to have consumed high amounts of C. cylindracea. This suggests a potential role that these fish species may play in controlling, to some extent, the abundance of the invader. We suggest that herbivory by omnivorous fish might complement the higher impact exerted by the strict herbivores, and together, they might contribute to the overall biotic resistance against the invader.