Miracle-dz/UniFAR-FTUs huggingface dataset:
Sovereign Cocos, WP/22/78, April 2022

: We study a model of equilibrium sovereign default in which the government issues cocos (contingent convertible bonds) that stipulate a suspension of debt payments when the government faces liquidity shocks in the form of an increase of the bondholders' risk aversion. We find that in spite of reducing the frequency of defaults triggered by liquidity shocks, introducing cocos increases the overall default frequency. By mitigating concerns about liquidity, cocos make indebtedness and default risk more attractive for the government. In contrast, cocos that stipulate debt forgiveness when the government faces the shock, achieve larger welfare gains by reducing default risk.
Robust High-Dimensional Classification From Few Positive Examples

We tackle an extreme form of imbalanced classification, with up to 105 features but as few as 5 samples from the minority class. This problem occurs in predicting predicting tumor types and fraud detection, among others. Standard imbalanced classification methods are not designed for such severe data scarcity. Sampling-based methods need too many samples due to the high-dimensionality, while cost-based methods must place too high a weight on the limited minority samples. Our proposed method, called DIRECT, bypasses sample generation by training the classifier over a robust smoothed distribution of the minority class. DIRECT is fast, simple, robust, parameter-free, and easy to interpret. We validate DIRECT on several real-world datasets spanning document, image, and medical classification. DIRECT is up to 5x − 7x better than SMOTE-like methods, 30−200% better than ensemble methods, 3x − 7x better than cost-sensitive methods. The greatest gains are for settings with the fewest samples in the minority class, where DIRECT’s robustness is most helpful.
Development and performance evaluation of the electric-hydraulic concave clearance control system based on maize feed rate monitoring

: Complex field environments, diverse crop conditions, and varying feed rate fluctuations commonly result in a decline in the threshing performance and the clogging of the threshing cylinder for maize harvesters. In order to overcome these problems, an electric-hydraulic concave clearance automatic control system for the threshing unit was developed based on the maize feed rate monitoring, which can automatically realize the best match between the concave clearance and diverse feed rates during harvesting. The threshing performance of the electric-hydraulic control system was evaluated for varying and uneven maize feed rate fluctuations, such as the feed rate increased (6-8-10 kg/s), the feed rate decreased after an increase (6-10-8 kg/s, 8-10-6 kg/s), the feed rate increased after a decrease (8-6-10 kg/s, 10-6-8 kg/s), and the feed rate decreased (10-8-6 kg/s). In particular, the threshing rotor shaft peak torque, the range of threshing rotor shaft torque, the rate of broken grains (BGR), and the rate of unthreshed grains (UGR) with and without the electric-hydraulic control system were tested. Treatments with the electric-hydraulic control system were adjustable concave clearance with the value of 45 mm, 50 mm, and 55 mm. Treatments without the electric-hydraulic control system were constant concave clearance (50 mm). Results demonstrate that the threshing unit with the electric-hydraulic control system outperformed the one without the electric-hydraulic control system, with threshing rotor peak torque, the range of threshing rotor axis torque, the BGR, and the UGR decreasing by 18.38%, 38.27%, 2.08%, and 0.10%, respectively. Moreover, the rate of broken grains was lower than 5.00%, better than the national standard. Thus, the feed rate fluctuations and timely adjustment of the concave clearance were able to avoid blocking the rotor and improve the threshing performance compared to the constant concave clearance. 156–164.
Performance analysis of operating multi-stage flash distillation unit coupled with nuclear power plant

Multi-stage flash (MSF) process is the most widely used technology in large scale desalination plants which utilizes low quality steam produced in nuclear power plant. The objective of this study is to analyze the performance of brine heater used in 4,500 m 3 /d capacity MSF desalination plant at Nuclear Desalination Demonstration Plant (NDDP), Kalpakkam commissioned in 2008. The effi ciency of brine heater, after 12 y of service, was investigated by analyzing the influence of volu - metric flow rate and scale thickness on heat transfer rate. The tube side pressure drop increases steeply as a function of volumetric flow rate of cold fluid. A maximum pressure drop of 17.1 kPa was developed at an optimized flow rate of 1,500 m 3 /h. The overall heat transfer coefficient increases gradually as scale thickness decreases and reached an ultimate of 4,395.3 W/m 2 K at a scale thickness of 0.00005 m. For small scale thickness, the percentage reduction in overall heat trans fer coefficient increased steeply and attained a saturation limit at 0.00025 m scale thickness. The overall heat transfer coefficient increased from 623.4 to 646.3 W/m 2 K as the volumetric flow rate increased from 750 to 1,500 m 3 /h. This study shows that the thermal efficiency of brine heater has not declined significantly after prolonged years of service under different operating conditions.
Registered Report: D AT AFL OW Towards a Data-Flow-Guided Fuzzer

—Coverage-guided greybox fuzzers rely on feedback derived from control-ﬂow coverage to explore a target program and uncover bugs. This is despite control-ﬂow feedback offering only a coarse-grained approximation of program behavior. Data ﬂow intuitively more-accurately characterizes program behavior. Despite this advantage, fuzzers driven by data-ﬂow coverage have received comparatively little attention, appearing mainly when heavyweight program analyses (e
Automatic and Manual Detection of Generated News: Case Study, Limitations and Challenges

In this paper, we study the exploitation of language generation models for disinformation purposes from two viewpoints. Quantitatively, we argue that language models hardly deal with domain adaptation (i.e., the ability to generate text on topics that are not part of a training database, as typically required for news). For this purpose, we show that both simple machine learning models and manual detection can spot machine-generated news in this practically-relevant context. Qualitatively, we put forward the differences between these automatic and manual detection processes, and their potential for a constructive interaction in order to limit the impact of automatic disinformation campaigns. We also discuss the consequences of these findings for the constructive use of natural language generation to produce news items.
Prevalence of multidrug resistant Escherichia coli recovered from patients suffering from urinary tract infections

Urinary tract infections are common human bacterial infections caused by Escherichia coli , which is one of the most frequent uropathogens. Treatment of such infections has become challenging due to the elevated levels of antimicrobial resistance. The aims of this work were to study the resistance pattern of E. coli pathogens recovered from patients with urinary tract infections attending to Minia University Hospital, Minia Governorate, Egypt, and to detect the co-existence of different extended spectrum β-lactamases (ESBLs) and metallo β-lactamases (MBLs) genes. The in vitro antibiotic sensitivity was tested using the disc diffusion assay. The production of ESBLs and MBLs was investigated through the combined disk and EDTA-combined disk synergy assays, while the molecular studies were carried out using the conventional polymerase chain reaction (PCR). High prevalence of ESBLs producers (61.6 %) was detected, whereas ESBLs and MBLs production was significantly associated with high multiple antimicrobial resistance index (MARI). The bla- TEM was the most prevalent genotype (94.6 %), while the prevalence of bla- NDM and bla- IMP was 45.9 % and 40.5 %, respectively. Imipenem and amikacin were the most effective antibacterial antibiotics. The current results showed statistically significant association of the tested genes, as 89 % of the E. coli isolates harbored more than one gene. This study highlighted a public health concern; as the elevated antibiotic resistance narrowed the therapeutic options and led to the failure of treatment of such bacterial infections.
New Trends that Define the 21st-Century Library

Abstract This chapter addresses the dramatic changes that are taking place in public library design and how these changes affect the ways the public library is managed and used. The public library is becoming the cultural center of the community and the place to go for digital information. While maintaining areas for quiet individual study, the public library now provides spaces for collaborative work as well. And, because of automation, the staff can now work more closely with patrons than in the past. With the current emphasis on green buildings, many new and transformed libraries have been designed as examples of sustainable practice for their communities. All these changes can help create a new perception of the public library, resulting in raised visibility, more use, and increased membership.
Active invasion of Porphyromonas gingivalis and infection-induced complement activation in ApoE-/- mice brains

Active invasion Porphyromonas gingivalis and infection-induced complement activation in ApoE -/- mice brains. Abstract Periodontal disease is a polymicrobial inflammatory disease that leads to chronic systemic inflammation and direct infiltration of bacteria/bacterial components, which may contribute to the development of Alzheimer’s disease. ApoE -/- mice were orally infected (N = 12) with Porphyromonas gingivalis, Treponema denticola , Tannerella forsythia and Fusobacterium nucleatum as mono- and polymicrobial infections. ApoE -/- mice were sacrificed following 12 and 24 weeks of chronic infection. Bacterial genomic DNA was isolated from all brain tissues except for the F. nucleatum mono-infected group. Polymerase chain reaction was performed using universal 16s rDNA primers and species- specific primer sets for each organism to determine whether the infecting pathogens accessed the brain. Sequencing amplification products confirmed the invasion of bacteria into the brain during infection. The innate immune responses were detected using antibodies against complement activation products of C3 convertase stage and the membrane attack complex. Molecular methods demonstrated that 6 out of 12 ApoE -/- mice brains contained P. gingivalis genomic DNA at 12 weeks (P = 0.006), and 9 out of 12 at 24 weeks of infection (P = 0.0001). Microglia in both infected and control groups demonstrated strong intracellular labeling with C3 and C9, due to on-going biosynthesis. Tthe pyramidal neurons of the hippocampus in 4 out of 12 infected mice brains demonstrated characteristic opsonization with C3 activation fragments (P = 0.032). These results show that the oral pathogen P. gingivalis was able to access the ApoE -/- mice brain and thereby contributed to complement activation with bystander neuronal injury.
Islaris: verification of machine code against authoritative ISA semantics

Recent years have seen great advances towards verifying large-scale systems code. However, these verifications are usually based on hand-written assembly or machine-code semantics for the underlying architecture that only cover a small part of the instruction set architecture (ISA). In contrast, other recent work has used Sail to establish formal models for large real-world architectures, including Armv8-A and RISC-V, that are comprehensive (complete enough to boot an operating system or hypervisor) and authoritative (automatically derived from the Arm internal model and validated against the Arm validation suite, and adopted as the official formal specification by RISC-V International, respectively). But the scale and complexity of these models makes them challenging to use as a basis for verification. In this paper, we propose Islaris, the first system to support verification of machine code above these complete and authoritative real-world ISA specifications. Islaris uses a novel combination of SMT-solver-based symbolic execution (the Isla symbolic executor) and automated reasoning in a foundational program logic (a new separation logic we derive using Iris in Coq). We show that this approach can handle Armv8-A and RISC-V machine code exercising a wide range of systems features, including installing and calling exception vectors, code parametric on a relocation address offset (from the production pKVM hypervisor); unaligned access faults; memory-mapped IO; and compiled C code using inline assembly and function pointers.
THE EFFECT OF MULTIMEDIA INSTRUCTIONAL PACKAGES ON STUDENTS' ACADEMIC ACHIEVEMENT IN

This study examined the effects of computer-based multimedia instructional packages on the academic achievement of students offering Biology in Senior Secondary Schools in Ibadan, Oyo State, Nigeria. Two multimedia instructional packages were designed for the study. The study adopted the pretest-posttest, control group, experimental research design. The population of the study consists of 80 randomly selected students from three secondary schools in Ibadan, Oyo State, Nigeria. The samples were randomly assigned to three groups (one control and two experimental groups). The moderating effects of gender and learning styles were also tested. The results showed that there was a significant main effect of treatment on students' achievement in Biology (F (2, 58) = 27.18; P < 0.05; partial eta square = 0.48). Also, gender had no significant main effect on students' performance (F (1, 58) = 3.97; P > 0.05; Partial eta square = 0.06). It was therefore concluded that multimedia instructional packages significantly enhanced students learning of Biology concepts than the conventional strategy, regardless of gender and the preferred learning style of students. Therefore, it was recommended that more multimedia instructional packages be designed and used in secondary schools for effective and efficient teaching and learning of Biology.
THE EFFICACY OF AN EDUCATIONAL INTERVENTION ON LATINAS’ CERVICAL CANCER SCREENING KNOWLEDGE

The (Under Latinas’ lack of knowledge regarding cervical cancer screening (CCS) guidelines has a significant impact on CCS adherence and ultimately impacts their health outcomes related to cervical cancer. Studies have demonstrated that small media, culturally relevant educational interventions are highly effective in improving Latinas’ knowledge of CCS (Moran et al., 2016; Thompson et al., 2019; Warner et al., 2018). The purpose of this scholarly project was to implement and evaluate the efficacy of a small media educational intervention on Latinas’ knowledge of CCS and human papillomavirus (HPV) and evaluate the participants’ satisfaction with the intervention. A convenience sample of 50 Hispanic female patients between the ages of 21-65 was obtained from a community health center in the Southeast region of the United States. The fotonovela utilized in the Thompson et al. (2019) study was the intervention used for this project; it was offered in Spanish and English and included information on CCS and HPV. A pre- and post-test questionnaire assessing the participants’ CCS and HPV knowledge was administered. In addition, the post-questionnaire included questions that evaluated the participants’ satisfaction with the fotonovela. Following implementation of the fotonovela, participants significantly increased their average post-test CCS and HPV knowledge scores (Pre: 50.6; Post: 83.6, p <.000). All 50 participants (100%) reported overall satisfaction with the fotonovela. The findings of this project were both statistically and clinically significant indicating that the fotonovela is an effective and favorable educational intervention, thus its implementation is warranted in healthcare settings that provide care to Latinas.
4. Collective Agency Freedom as the Engine of a Common Good Dynamic: A Conceptual Proposal for Measurement

The first part of this book proposes a practical notion of the common good that is dynamic and grounded in people’s actions. It sees development as the result of collective processes and collective actions in which people’s interactions shape their common destiny. In this sense, agency is posited as the engine of a common good approach to development that is truly human. In this chapter, I focus on this key driver of common good dynamics. My aim here is to reflect on what agency freedom could entail for such an approach by justifying its constitutive role for development and its collective nature, to then identify potential dimensions to measure it. I identify at least two caveats in how agency is discussed in the literature: first, the notion is primarily discussed at the individual level, and second, existing indicators aiming at capturing this concept generally reflect this bias by over-emphasising the ability of individuals to make choices. Instead, I will argue that it is the collective aspect of agency that provides a more appropriate appraisal of agency for a common good approach, which I present broadly as the opportunity for a given population to identify, organise, and act together as a collective unit to achieve common goals. Three dimensions for its measurement
Modeling the regular/irregular dissociation in non-fluent aphasia in a recurrent neural network

In the debate between single-route and dual-route models of verb inflection, the dissociation between regular and irregular verbs in the non-fluent variety of aphasia has been a key sticking point for the proponents of the single-route model. This paper adopts a state-of-the-art neural model which has previously been used to learn inflectional morphology, and shows that it can also be used to model data from non-fluent aphasia. This challenges the assumption that a dual-route model is necessary to capture apparent dissociations in aphasia data and encourages a reanalysis of the deficits involved in non-fluent aphasia.
SURVEYING PARENTAL MEDIATION AND DIGITAL LITERACY. WERE PARENTS READY DURING COVID-19?

The pandemic initiated an extensive and sudden digital transformation in the society. It forced parents and children to take a digital surge in their lives. The aim of our survey is to explore to what extend children's online behavior has changed during the pandemic, to study whether demographic factors and digital literacy of parents, are associated with the changes observed, and lastly to explore to what extend parents are familiar with age and content classification systems online, which will allow them to make informed decisions about media content consumed by their children. The study reveals that a significant percentage of parents (29.8%) report changes in the online habits of their children. Furthermore, our research affirms that digital literacy of parents is the key to overcome potential online risks of children, especially during the pandemic. Notably, the age group 9-12 is the age group, which shows the biggest percentage of parents noticing changes in their child's online habits. Finally, it is revealed that parents were unprepared to follow this fast transformation pace, and only a low percentages of them appears to be familiar with age (49.8%) and content classification systems (27.9%) online. © 2022 IADIS Press. All rights reserved.
A Review of Strength Performance of Empty Fruit Bunch as Replacement Material in Building Structures

Recently, eco-friendly construction has become a hot topic. One of the concepts’ alternatives is the use of green natural resources. The oil palm Empty Fruit Bunch (EFB) is a byproduct of the oil plantation, and its improper disposal can have a detrimental influence on the environment. Agricultural waste can be used as a replacement material in concrete, which is known as modified concrete. The material performance of modified concrete with partial waste material replacement must be comparable to that of ordinary concrete. As a result, the use of raw resources will be reduced indirectly, and the material will become a more sustainable construction material. This study presents the utilization of EFB natural fibre as an alternative building material. It demonstrates that research into employing EFB as alternative replacement material in concrete has yet to be discovered. EFB was primarily used to manufacture cement board, roof insulation, and cement bricks, among other things. As a result, future research should focus on expanding the use of these by-products in the building industry. Further research into the process of generating cost-effective adoption applications will be examined to build a sustainable environment by lowering negative environmental impact.
Sparse Identification of Variable Star Dynamics

Variable stars play a crucial role as standard candles and provide valuable insights into stellar physics. They can be modeled either through fully fledged hydrodynamical simulations or analytically as systems of coupled differential equations describing the evolution of relevant physical quantities. Typically, such equations are arrived at by simplified physical assumptions concerning the conservation laws governing stellar interiors. Here we apply a data-driven technique—sparse identification of nonlinear dynamics (SINDy)—to automatically learn governing equations from observed light curves. We apply SINDy to 3100 light curves of three different variable types from the Catalina Sky Survey. The success rate depends systematically on variable type, with possible implications for variable star classification; however, it does not obviously depend on amplitude or period. Successful models can be reduced to the generalized Lienard equation ẍ+(a+bx+cẋ)ẋ+x=0 . Members of the Lienard class of ordinary differential equations, such as the well-studied van der Pol oscillator, already saw some application to variable star modeling. For a, b = 0 the equation can be solved exactly, and it admits both periodic and nonperiodic solutions. We find a condition on the coefficients of the general equation for the presence of a limit cycle, which is also observed numerically in several instances.
Inner Sequential Single Solid Method for Layout Optimization of Multi-Materials

In multiple materials layout optimization, the optimal solution is difficult to achieve due to the number of design variables being too large and the material interpolation scheme becoming complicated when using density-like method. To bypass this problem, an inner sequential single solid optimization (ISSSO) method is presented in this study. There are two types of iterations in the optimization process of this method: the inner and outer iterations. In the inner iteration, the original layout optimization of many materials is replaced with a series of single solid sub-optimizations. In each sub-optimization, only one solid is chosen to update and the rest keeps unchanged. The inner iteration stops when all the solids are updated consequently. The next loop of inner iteration starts when the current solution does not meet the requirement of convergence. The outer iteration starts only if the current inner iteration comes to an end. In the outer iteration, the new inner iterations for update of all the solid materials are carried out. The effectiveness of ISSSO method is verified by comparing the calculation results with other methods.