Miracle-dz/UniFAR-FTUs huggingface dataset:
The Institute of International Finance: From Poacher to Gamekeeper?

Abstract The Institute of International Finance (IIF) is a key actor in global finance, mixing private-interest representation and market governance roles. Analyzing the historical development of the IIF offers important insights into the interaction between state and business and the resulting patterns of public and private governance. Based on archive sources and a unique set of interviews with elite policymakers spanning three decades, I argue that market structures, interest groups, and public policymaking processes stand in a recursive relationship. Secondly, I argue that interest groups take on private governance roles with the aim to remain the focal point of public policymakers vis-à-vis competing interest groups. This has important implications for the study of interest groups and global financial governance. The analysis of interest groups should be extended to the way they shape markets through private governance mechanisms and how that recursively feeds back into interest group advocacy and public policymaking processes to fully grasp lobbying dynamics. The study of global governance should include analysis of interest group competition within the opportunities and constraints emanating from public policymaking processes so as to understand the emergence of private patterns of governance and their interaction with public governance mechanisms.
Comparative Performances of Microalgal-Bacterial Co-Cultivation to Bioremediate Synthetic and Municipal Wastewaters Whilst Producing Biodiesel Sustainably

The potentiality of a microalgal-bacterial culture system was explored in bioremediating wastewater while generating biomass for biodiesel production. A pre-determined optimal activated sludge and microalgal ratio was adopted and cultivation performance was evaluated in both synthetic and municipal wastewater media for nitrogen removal along with biomass and lipid generation for biodiesel production. The microalgal-bacterial consortium grown in the municipal wastewater medium produced higher biomass and lipid yields than those in the synthetic wastewater medium. The presence of trace elements in the municipal wastewater medium, e.g., iron and copper, contributed to the upsurge of biomass, thereby leading to higher lipid productivity. Both the microbial cultures in the synthetic and municipal wastewater media demonstrated similar total nitrogen removal efficiencies above 97%. However, the nitrification and assimilation rates were relatively higher for the microbial culture in the municipal wastewater medium, corresponding to the higher microbial biomass growth. Accordingly, the feasibility of the microalgal-bacterial consortium for bioremediating real municipal wastewaters was attested in this study by virtue of higher biomass and lipid production. The assessment of fatty acid methyl esters (FAME) composition showed the mixed microbial biomasses comprised 80–93% C16 to C18 FAME species, signifying efficient fuel combustion properties for quality biodiesel requirements.
Directed Self‐Assembly of Gold Nanoparticles on Graphene‐Ionic Liquid Hybrid for Enhancing Electrocatalytic Activity

The effects of introducing gold (Au) nanoparticles (NP) on the electrochemical properties of graphene functionalized with ionic liquid were investigated by cyclic voltammetry, amperometry, and AC impedance analysis. The introduction of Au NPs onto graphene-ionic liquid sheets led to enhanced electron transfer rate, low charge transfer resistance, and large electrocatalytic area. An electrochemical biosensor device based on the hybrid of Au NPs and functionalized graphenes was fabricated and found to have superior electrochemical performance in the detection of glucose, with a sensitivity of 0.16 m Am M � 1 , a detection limit of 0.13 mM, and a response time of 5 s.
Big Data Analytics in Healthcare using Machine Learning Algorithms: A Comparative Study

In recent years vast quantities of data have been managed in various ways of medical applications and multiple organizations worldwide have developed this type of data and, together, these heterogeneous data are called big data. Data with other characteristics, quantity, speed and variety are the word big data. The healthcare sector has faced the need to handle the large data from different sources, renowned for generating large amounts of heterogeneous data. We can use the Big Data analysis to make proper decision in the health system by tweaking some of the current machine learning algorithms. If we have a large amount of knowledge that we want to predict or identify patterns, master learning would be the way forward. In this article, a brief overview of the Big Data, functionality and ways of Big data analytics are presented, which play an important role and affect healthcare information technology significantly. Within this paper we have presented a comparative study of algorithms for machine learning. We need to make effective use of all the current machine learning algorithms to anticipate accurate outcomes in the world of nursing.
Ensemble Model Development for the Prediction of a Disaster Index in Water Treatment Systems

The quantitative analysis of the disaster effect on water supply systems can provide useful information for water supply system management. In this study, a total disaster index (TDI) was developed using open-source public data in 419 water treatment plants in Korea with 23 input variables. The TDI quantifies the possible effects or damage caused by three major disasters (typhoons, heavy rain, and earthquakes) on water supply systems. The four components (regional factor, risk factor, urgency factor, and response and recovery factor) were calculated using input variables to determine the disaster index (DI) of each disaster. The weight of the input variables was determined using principal component analysis (PCA), and the weights of the DI of three natural disasters and four components used to calculate the TDI were determined by the analytical hierarchy process (AHP). Specifically, two ensemble machine learning models, random forest (RF) and XGBoost (XGB), were used to develop models to predict the TDI. Both models predicted the TDI with the coefficient of determination and root-mean-square error-observations standard deviation ratio of 0.8435 and 0.3957 for the RF model and 0.8629 and 0.3703 for the XGB model, respectively. The relative importance analysis suggests that the number of input variables can be minimized, which improves the models’ practical applicability.
Latent classes of childhood maltreatment in children and adolescents in foster care: associations with ICD-11 PTSD and complex PTSD

ABSTRACT Background: Children and adolescents in foster care often experience many co-occurring subtypes of maltreatment. However, little is known about different combinations of maltreatment subtypes, referred to as maltreatment classes. Furthermore, the association between those maltreatment classes and ICD-11 posttraumatic stress disorder (PTSD) and complex PTSD (CPTSD) has not been investigated in children and adolescents. In previous studies, classes characterized by cumulative maltreatment were associated with severe psychopathological symptoms. So far, no study investigated ICD-11 PTSD and CPTSD. Objective: The first aim of this study was the detection of distinct maltreatment classes by examining frequently co-occurring maltreatment subtypes. The second aim was the examination of the association between those maltreatment classes and ICD-11 PTSD and CPTSD. Method: Participants were 147 children and adolescents currently living in foster care institutions in Lower Austria. Maltreatment history, ICD-11 PTSD and CPTSD were assessed using standardized self-report questionnaires. Latent class analysis was applied to examine maltreatment subtypes. χ2 difference testing was used to examine class associations with PTSD and CPTSD. Results: Three latent classes that comprised different subtypes of maltreatment were identified (limited maltreatment, n = 49; high neglect, n = 53; cumulative maltreatment, n = 45). Cumulative maltreatment was associated with higher symptom severity of PTSD and CPTSD than the limited maltreatment and the high neglect class, with effect sizes ranging from 0.62 to 0.93. Conclusions: The association of the cumulative maltreatment class with the highest symptom severity of PTSD and CPTSD highlights the detrimental effect of cumulative maltreatment. The detection of a high neglect class identifies children and adolescents, who are at high-risk of experiencing future maltreatment because of their previous experiences of neglect and the associated lack of protection. The examination of the association of distinct maltreatment classes with ICD-11 PTSD and CPTSD might provide implications for targeted prevention, assessment and treatment. HIGHLIGHTS • Three classes of childhood maltreatment were detected (limited maltreatment, high neglect, cumulative maltreatment). • Class membership was associated with ICD-11 PTSD and CPTSD. • Based on the findings, tailored prevention and intervention is possible for high-risk individuals.
Climate change and freshwater ecology: Hydrological and ecological methods of comparable complexity are needed to predict risk

Many freshwater ecosystems are in decline because of anthropogenic disturbance including climate change, yet our understanding of ecological vulnerability to future conditions including climatic variation is limited. Understanding climate risks to freshwater ecosystems requires combining hydrological and ecological knowledge. While there have been significant advances in ecohydrological approaches when applied within the large array of methods available for undertaking impact assessments, the ecological and hydrological elements are often not well‐integrated. This results in a mismatch in their ability to accommodate the inherent uncertainty in both impacts and responses. We examine published literature that assesses climate change impacts on freshwater ecosystems using both hydrological and ecological models to better understand method choices. We identify four fundamentally distinct modeling approaches used to assess climate change risk. We discuss which approaches are less useful for predicting ecological impacts under climate change, and highlight approaches of comparable complexity that can maximize the utility of dynamic, process‐based modeling while capturing the effects of climate uncertainty and variability. Using an illustrative case study of riparian vegetation health under climate change, we show how the four alternate modeling approaches feature different degrees of information in their outcomes and inferences about future risk. Most current studies that examine climate change risks to freshwater ecosystems use simplified methods or inadequately combine key elements. However, unless the interactions between changing hydrologic variability and ecological responses are explicitly captured in scale‐sensitive modeling methods, the risks of climate change to freshwater ecosystems will likely be substantially misrepresented, with negative consequences for effective management responses. Capturing these interactions requires combining ecological and hydrological methods of comparable complexity.
The effects of morphology, mobility size, and secondary organic aerosol (SOA) material coating on the ice nucleation activity of black carbon in the cirrus regime

Abstract. There is evidence that black carbon (BC) particles may affect cirrus formation and, hence, global climate by acting as potential ice nucleating particles (INPs) in the troposphere. Nevertheless, the ice nucleation (IN) ability of bare BC and BC coated with secondary organic aerosol (SOA) material remains uncertain. We have systematically examined the IN ability of 100–400 nm size-selected BC particles with different morphologies and different SOA coatings representative of anthropogenic (toluene and n -dodecane) and biogenic ( β -caryophyllene) sources in the cirrus regime ( −46 to −38 ∘ C). Several BC proxies were selected to represent different particle morphologies and oxidation levels. Atmospheric aging was further replicated with the exposure of SOA-coated BC to OH. The results demonstrate that the 400 nm hydrophobic BC types nucleate ice only at or near the homogeneous freezing threshold. Ice formation at cirrus temperatures below homogeneous freezing thresholds, as opposed to purely homogeneous freezing, was observed to occur for some BC types between 100 and 200 nm within the investigated temperature range. More fractal BC particles did not consistently act as superior INPs over more spherical ones. SOA coating generated by oxidizing β -caryophyllene with O 3 did not seem to affect BC IN ability, probably due to an SOA-phase state transition. However, SOA coatings generated from OH oxidation of various organic species did exhibit higher IN-onset supersaturation ratio with respect to ice (SS i ), compared with bare BC particles, with the toluene-SOA coating showing an increase in SS i of 0.1–0.15 while still below the homogeneous freezing threshold. Slightly oxidized toluene SOA coating seemed to have a stronger deactivation effect on BC IN ability than highly oxidized toluene SOA, which might be caused by oligomer formation and the phase state transition of toluene SOA under different oxidation levels. n -dodecane and β -caryophyllene-derived SOA-coated BC only froze in the homogeneous regime. We attribute the inhibition of IN ability to the filling of the pores on the BC surface by the SOA material coating. OH exposure levels of n -dodecane and β -caryophyllene SOA coating experiments, from an equivalent atmospheric exposure time from 10 to 90 d, did not render significant differences in the IN potential. Our study of selected BC types and sizes suggests that increases in diameter, compactness, and/or surface oxidation of BC particles lead to more efficient IN via the pore condensation freezing (PCF) pathway, and that coatings of common SOA materials can inhibit the formation of ice.
Boulder Fall Activity in the Jezero Crater, Mars

Jezero crater is the landing site for the Mars 2020 Perseverance rover. We report 63 boulder fall tracks within the crater using High‐Resolution Imaging Science Experiment (HiRISE) images. The boulder tracks have both fresh and faded morphologies similar to those reported elsewhere on Mars, but reported for the first time in Jezero crater. We combine observations from 16 boulder‐tracks on the western delta deposit with 47 in the surrounding regions to infer possible process(es) of boulder destabilization, which can be tested with rover observations. This newly found hazard should be taken into account for rover operations. Boulders associated with tracks are geologically “recent falls,” so it is possible that the surfaces of these boulders may provide an opportunity to sample material less exposed to radiation than other rocks at the martian surface and could be ideal targets to analyze for organics.
The Instructional Design of a 4C/ID-Inspired Learning Environment for Upper Secondary School Students’ Research Skills

In today’s complex world, the acquisition of research skills is considered an important goal in education. Consequently, there is a growing body of literature that recognizes the value of well-designed learning environments for effectively supporting the development of this complex set of skills. However, a clear consensus on how these research skills can be facilitated is currently lacking, and the design processes underlying the learning environments aiming to foster students’ research skills are not always clearly outlined. Furthermore, interventions aiming to foster these skills are often implemented in the domains of physics, biology, and chemistry, while other domains (such as behavioral and social sciences domains) remain understudied. In addition, current approaches to foster research skills often refer to only a few epistemic activities (Fischer et al., 2014) related to research skills. Inspired by a design-based research approach, this design effort case seeks to clearly explain the design considerations for, and the development of an online learning environment aiming to foster upper secondary school students’ research skills in a behavioral sciences context. The online learning environment (RISSC or Research In Social SCiences) consists of a lesson series designed based on a systematic approach to four-component instructional design (van Merriënboer & Kirschner, 2018), and was piloted with two different cohorts in upper secondary education and in first year of university. Louise Maddens is currently pursuing her PhD in Instructional Psychology and Technology at KU Leuven and is also affiliated with itec, imec research group at KU Leuven. Her research interests include instructional design, complex learning and research skills education.
Influence of tropical pastures on grazing behavior parameters of young lambs

Tropical sward characteristics can alter lamb ingestive behavior. Our study evaluated the ingestive behavior of young lambs in different tropical pastures to identify which variables interfere in their grazing activity. Two years of study were carried out with 54 weaned lambs distributed in three different swards: 1) monoculture of a upright grass, guinea grass (Panicum maximum; GG); 2) monoculture of a shrubby legume pigeon pea (Cajanus cajan; PP) and 3) contiguous areas with half the paddock with GG and half with PP (GP). The experiment was set out in a randomized complete block design. Lamb ingestive behavior was observed from sunrise to sunset with records every 5 minutes. To identify the main variables that affected with the lamb grazing activity, a multivariate analysis of the Decision Tree was performed. Our results showed that there was no difference in the ingestive behavior parameters of young lambs in different swards (P > 0.05). There was interaction among the swards and the experimental periods for the variables idleness time and biting rate (P ≤ 0.05). Grazing time of the animals increased 40% with experimental period progression. The Decision Tree identified leaf:stem ratio as the variable that most influenced lamb grazing time in GG and GP swards while in the PP sward grazing time was directly related to the pasture height. The behavior of young lambs on tropical pasture is variable as there is a change in the behavioral response over time. In addition, the grazing time of these animals can be estimated by means of variables related to pasture structural characteristics (leaf:stem ratio and height) together with chemical variables.
A narrative review of the challenges and countermeasures in hepatoblastoma management during COVID-19 epidemic

An infectious disease named “coronavirus disease 2019” (COVID-19) currently has brought a threat to global health security and trends to be more and more severe in many countries. It also has introduced great challenges to the diagnosis and management of children with hepatoblastoma (HB). During the COVID-19 pandemic, pediatric surgeons should not only develop personalized treatment plans for HB therapy, but also emphasize the diagnosis, prevention, and treatment of this virus. Children with both HB and COVID-19 are recommended to undertake multidisciplinary assessment. Anti-SARS-CoV-2 therapy may be a preferred treatment for the infected without presenting a surgical emergency. However, emergent operation may be necessary for HB children with concurrent COVID-19 who developed a life-threatening surgical emergency condition. Otherwise, for children with negative virus examination results, treatment advice should be based on the impact of the epidemic and regional economic considerations. A “wait and see” strategy is recommended for children with resectable tumors after new adjuvant chemotherapy treatment (NACT). Assessment of liver transplantation is recommended for children with HB whose tumors cannot be resected after NACT. Children with HB with pulmonary metastasis may have abnormal findings on chest imaging due to COVID-19. Besides, the detailed therapeutic regimens may vary for children with HB with or without an emergency presentation. Based on previous consensus, current research, and the experiences of our hospital, we aim to offer available management plans for the above-mentioned concerns.
Comparison of internal target volumes defined by three-dimensional, four-dimensional, and cone-beam computed tomography images of a motion phantom

Background To explore the variations of the gross tumor volume (GTV) from different three-dimensional computed tomography (3DCT) scan modes and the consistency of internal target volume (ITV) between different 3DCT, cone-beam computed tomography (CBCT) and four-dimensional computed tomography (4DCT) scan, a study using a motion phantom simulating sinusoidal movement was conducted. Methods For three 3DCT scan modes: the GTV was contoured, and ITVI was generated on the basis of GTV with a 10-mm margin while ITVII and ITVIII with a 0-mm margin on the motion direction. ITVCBCT and ITVMIP were contoured on the images of CBCT and maximum-intensity projection (MIP) reconstructed 4DCT images. The centroid position shifts of ITVs were analyzed. The volume consistency between ITVI, ITVII, ITVIII and ITVMIP were evaluated by calculating the Dice similarity coefficient (Dsc) and the value of Δ Volume (ΔV). Furthermore, the 3DCT and CBCT images from 12 NSCLC patients were retrospectively collected, then the Dsc and ΔV were calculated. Results The mean ± standard deviation of centroid position of ITVI, ITVII and ITVIII were 2.3±4.7, 2.6±4.0, and 1.0±1.4 mm, respectively. The mean ± standard deviation of Dsc between ITVI, ITVII, ITVIII and ITVMIP were 0.78±0.77, 0.86±0.1, and 0.94±0.05, respectively. The ΔV of ITVI, ITVII, ITVIII were 29.67%, 17.22%, and 6.46%, respectively. The ITV from CBCT showed a deduction rate of 3.1–9.3% compared to 4DCT. For the patients, the mean Dsc andΔV between ITVI and ITVCBCT were 0.50 and 60.76%. Conclusions The GTV acquired from 3DCT scan mode I possessed great deviation of centroid position and target volume. ITV on the basis of this GTV was significantly larger than ITVMIP. A good similarity was showed between ITVIII and ITVMIP, 4DCT is still a golden standard for the ITV delineation, but in the absence of 4DCT, image from 3DCT scan mode III and KV-CBCT may be considered for ITV delineation with caution.
Stochastic computing in convolutional neural network implementation: a review

Stochastic computing (SC) is an alternative computing domain for ubiquitous deterministic computing whereby a single logic gate can perform the arithmetic operation by exploiting the nature of probability math. SC was proposed in the 1960s when binary computing was expensive. However, presently, SC started to regain interest after the widespread of deep learning application, specifically the convolutional neural network (CNN) algorithm due to its practicality in hardware implementation. Although not all computing functions can translate to the SC domain, several useful function blocks related to the CNN algorithm had been proposed and tested by researchers. An evolution of CNN, namely, binarised neural network, had also gained attention in the edge computing due to its compactness and computing efficiency. This study reviews various SC CNN hardware implementation methodologies. Firstly, we review the fundamental concepts of SC and the circuit structure and then compare the advantages and disadvantages amongst different SC methods. Finally, we conclude the overview of SC in CNN and make suggestions for widespread implementation.