Miracle-dz/UniFAR-FTUs huggingface dataset:
Managing Tree Seed in an Uncertain Climate: Conference Summary

Canadian forests will experience greater increases in temperature than those growing further south. One set of projections for Ontario indicates that by the end of the century, average summer temperature will increase from 3 to 7oC (southern and northern Ontario, respectively) and that winter temperatures will increase from up to 4oC in the south to 10oC in the north (Colombo et al. 2007). Predictions of precipitation with climate change vary, but future precipitation may be insufficient to prevent large areas of Ontario forests from experiencing more frequent and intense drought (Wotton et al. 2003, Colombo et al. 2007). Such temperature and soil moisture changes would alter the ecological conditions in forests enough to affect how well trees are adapted to local climates.
Micro-tomographic characterization of dissolution-induced local porosity changes including fines migration in carbonate rock

The microstructure of carbonate rocks experiences substantial changes under reactive processes, in particular chemical dissolution and deposition, including dissolution-released-fines migration occurring during acidizing. A better understanding of such changes at the pore scale and their influences on rock properties is of great value for the effective design and implementation of reactive processes in carbonate reservoirs. In this work, we demonstrate the use of X-ray micro-computed tomography (micro-CT) to quantitatively investigate the local porosity changes in a meso-/ microporous carbonate core sample during chemical dissolution. A reactive flooding experiment in a core sample by a nonacidic solution is designed such that changes in pore space from before to after the reactant injection could be imaged in exactly the same locations with micro-CT at a resolution of less than 5 lm. A methodology with three-phase segmentation and 2D histograms of image intensity is used to quantify distributions of the evolution of each image voxel. This technique allows the incorporation of microporosity into the calculation of the evolution regions, including the migration of fines, to accurately quantify the evolution scenarios. The micro-CT images reveal a quasiuniform dissolution pattern and allow characterizing the accompanying migration of fines within the core sample. The 3D pore networks are derived from the image data, which quantify changes in network structure and the pore geometry. The 2D histograms of image intensity derived from the preand post-dissolution images show quantitatively how macroand micropores are enlarged by dissolution close to the inlet, whereas the deposition of fines mainly occurs in pores far from the inlet boundary. These results can explain why permeability of the sample initially decreases and then increases when injection time increases. Pore-surface area between each region is computed on the basis of the spatially resolved voxel evolution scenarios. This allows calculation of local distribution of reactive surface area, which, in turn, will assist in the prediction of local reaction rates in reactive flow simulators.
A Generative and Mutational Approach for Synthesizing Bug-Exposing Test Cases to Guide Compiler Fuzzing

Random test case generation, or fuzzing, is a viable means for uncovering compiler bugs. Unfortunately, compiler fuzzing can be time-consuming and inefficient with purely randomly generated test cases due to the complexity of modern compilers. We present COMFUZZ, a focused compiler fuzzing framework. COMFUZZ aims to improve compiler fuzzing efficiency by focusing on testing components and language features that are likely to trigger compiler bugs. Our key insight is human developers tend to make common and repeat errors across compiler implementations; hence, we can leverage the previously reported buggy-exposing test cases of a programming language to test a new compiler implementation. To this end, COMFUZZ employs deep learning to learn a test program generator from open-source projects hosted on GitHub. With the machine-generated test programs in place, COMFUZZ then leverages a set of carefully designed mutation rules to improve the coverage and bug-exposing capabilities of the test cases. We evaluate COMFUZZ on 11 compilers for JS and Java programming languages. Within 260 hours of automated testing runs, we discovered 33 unique bugs across nine compilers, of which 29 have been confirmed and 22, including an API documentation defect, have already been fixed by the developers. We also compared COMFUZZ to eight prior fuzzers on four evaluation metrics. In a 24-hour comparative test, COMFUZZ uncovers at least 1.5× more bugs than the state-of-the-art baselines.
Thesis Master’s Level The Effects of Mergers and Acquisitions on Firms’ Performance

: Mergers and acquisitions are one of the most researched topics in the financial literature and many research has been done. This thesis aims to analyse the impact of mergers and acquisitions on firms’ performance for the acquired firms and uses the difference-in-differences (DID) estimation method with variation in treatment timing to achieve the objective. The data used in this thesis are collected from database of Institute for Mergers, Acquisitions and Alliances (IMAA) for 25 companies that merged between 2005 and 2019 and from the database of Indonesia Stock Exchange for 25 firms that did not undertake the mergers and acquisitions in the same period. The findings of this study indicate that there are statistically not significant effects on Return on Assets (ROA) and Return on Equity (ROE). This suggests that the mergers and acquisitions do not affect the company's financial performance in terms of profitability.
Chronic infection: as an ecological model for emergence of the chronic obstructive pulmonary disease

Chronic infections; emerging as complications of some primary diseases, can hardly be considered as classical infectious processes. Such infections may be caused by the non-traditional pathogenic bacteria; as in the cases of cystic fibrosis; chronic obstructive pulmonary disease (COPD), inflammatory bowel diseases, etc. Emergence of these complications is caused by several disorders in the ecosystem; constituting the human body and its microbiota. It is reasonable to extrapolate some ecological principles of the bacterial community's assembly in the humans; as there is a wide variety of factors affecting this, which can be considered as ecological ones. The human microbiota is formed during changes of the different bacterial succession types; under the influence of stochastic and deterministic ecological processes, in addition to different types of the selection pressure. During certain diseases, such as COPD, the normal course of the bacterial community's formation is disrupted. It is associated with anatomical and physiological defects, which cause changes in the properties of the ecological niche; occupied by the communities ( i.e ., airways in the case of COPD). Altered niches can be occupied by the virulent microorganisms, which get resource advantage and form new stable community. The severity of such chronic infections is correlated with biological diversity in the communities, which tends to decrease in the more severe cases and in the exacerbations. The aim of this study was to create an ecological model of the chronic infections; through synthesizing the ecological and medical knowledge. This model, such as the COPD; may establish new approach to the chronic infections etiopathogenesis, which enables to get better understanding of the clinical course in these diseases and to propose more effective therapies in the future.
Cognitive-Behavioral Treatment of Perfectionism: An Overview of the State of Research and Practical Therapeutical Procedures

Background: Perfectionism represents an important transdiagnostic predisposing and maintaining factor in a number of psychological disorders. Moreover, perfectionism can complicate the treatment of psychological disorders and contribute to treatment resistance. In the present article, cognitive behavioral therapy (CBT) interventions to reduce perfectionistic patterns are explained. In addition, specifics of the therapeutic relationship with perfectionists as well as the etiology and possible functionalities of perfectionistic patterns are discussed. Summary: The effectiveness of classical CBT interventions for reducing perfectionism has been demonstrated in a number of studies. Recent research furthermore points to the (potential) benefit of interventions that fall into the third wave of CBT (such as mindfulness-based, schema therapeutic or self-compassion-based approaches) – however, there is still a lack of studies with sufficient methodological quality. Key Messages: While a number of different CBT approaches are available for the treatment of perfectionism, future studies should increasingly examine which interventions are particularly indicated for which patient characteristics.
Measurements of HCFC‐142b and HCFC‐141b in the Cape Grim air Archive: 1978–1993

Stored air samples collected at Cape Grim, Tasmania since 1978, have been analyzed by GC-MS to investigate the change in the tropospheric concentration of HCFC-142b and HCFC-141b over the past 15 years. Between April 1978 and September 1993 the concentration of HCFC-142b rose from 0.20±0.02 pptv to 3.0±0.3 pptv, with the majority of this increase occurring from 1989 onwards. By mid-1993 the rate of increase had reached 0.9±0.1 pptv/yr. From 1982 to 1991 the average concentration of HCFC-141b was 0.08±0.01 pptv. A very sharp increase in concentration began in 1992 however, such that it reached 0.46±0.05 pptv by September 1993. Using a 2-D model of atmospheric chemistry, constrained by these observations, global emissions of these two compounds have been calculated and found to differ from other estimates. This is partly due to the background concentration levels which existed prior to the start of the other estimated emissions.
The Ethicality of Point-of-Sale Marketing Campaigns: Normative The Ethicality of Point-of-Sale Marketing Campaigns: Normative Ethics Applied to Cause-Related Checkout Charities Ethics Applied to Cause-Related Checkout Charities

“Would you like to contribute to XYZ charity by adding a dollar to your bill today? ” Point-of-sale campaigns for fundraising are common to grocery stores, pharmacies, restaurants and warehouse clubs. Commonly referred to as ‘checkout charity,’ these fundraisers have generated over $4.1 billion in contributions for nonprofits over the past three decades. Yet little research has focused on the ethicality of this type of campaign. To address this need, we analyze the issue using behavioral ethics
Effects of Missing Data on Estimates of Monthly Mean General Circulation Statistics.

Abstract To assess the impact of missing data on general circulation statistics, an analysis has been carried out on the effect of systematically decreasing the amount of available data. Thus the accuracy of monthly mean analyses of a variety of parameters including means, variances, and covariances is determined from ECMWF data as a function of the number of twice-daily analyses included in the monthly mean. Because the standard error of a monthly mean depends on the standard deviation of the daily values and the effective number of independent observations during each month, results have been expressed as the ratio of the root-mean-square error (RMSE) in the monthly mean to the daily standard deviation, thus allowing fairly universal relationships to be developed for application to many parameters, and to different season latitudes and longitudes. Results are indeed dependent upon the numbers of observations and the autocorrelation within each series, but could be modeled sufficiently well, for this pur.
Dynamic Versus Static Presentation Formats, Do They Impact Performance Differently?

According to the Cognitive Theory of Multimedia Learning (Mayer, 2009) learning with multimedia requires the integration of verbal and visual information (e.g., printed text and static images, narrated animation). Studies exploring the effects of dynamic versus static presentations yield mixed re-sults. Few studies explore comparing dynamic versus static presentations to teach mathematics. Most experimental studies occur in a controlled lab setting. The present study aimed to assess the impact of multimedia learning formats beyond the experimental lab to an authentic setting (i.e., classrooms) to teach mathematics. In Spring 2017, we compared weekly outcomes for students who accessed online interactive video modules (DYNAMIC) demonstrating calculus level 1 topics to students who accessed the same content presented in printed text and static image format (STATIC). Students in two sections of undergraduate course Calculus 1 (011) and (001) alternated each week the online pre-work material presented in either interactive video module or text-image document. They were assessed with problem-solving and conceptual questions at the beginning and end of each week. The results demonstrated no statistically significant differences on presentation formats for the assessments provided at the beginning and end of each week. Participants also answered the same survey question at the end of each online topical lesson related to the perceived effectiveness of the instructional material to help students master the topic. Survey results indi-50
Emotional Intelligence and Turnover Intentions among Teaching Staff in Kenya's Private Universities

The objective of this study was to establish the relationship between emotional intelligence and turnover intentions among the teaching staff in Kenya's Private Universities. The study was anchored on the mixed theory of emotional intelligence. It focused on all 36 private universities in Kenya as listed by the Commission for university education as at June 2021. The research was guided by positivism philosophy and used cross-sectional survey design. A sample size of 364 teaching staff from Kenyan Private Universities was obtained through stratified proportionate random sampling. The researcher used a structured questionnaire to collect primary data for the study from 364 respondents. Quantitative data analysis was conducted using statistical package for the social sciences (SPSS) software and involved diagnostic tests, descriptive and inferential statistical analysis. The results revealed a weak positive and significant relationship between emotional intelligence and turnover intentions. The research recommends the leadership of private universities in Kenya to assess a candidate’s emotional intelligence ability to build strong relationships among employees when employing the teaching staff. The study further recommends that employees in these institutions be trained on emotional intelligence aspects of Self-awareness, Self-regulation, Social-awareness and social management or social skills at institutional and personal level. This training should include all leaders at various levels such as vice chancellors, deputy vice chancellors’ deans and non-academic leaders.
Combined Genomic and Imaging Techniques Show Intense Arsenic Enrichment Caused by Detoxification in a Microbial Mat of the Dead Sea Shore

Microbial mats and microbialites are essential tools for reconstructing early life and its environments. To better understand microbial trace element cycling, a microbial mat was collected from the sinkhole systems of the western shores of the Dead Sea, a dynamic environment exhibiting diverse extreme environments. Intense arsenic enrichment was measured (up to 6.5 million times higher than current concentrations in water, and 400 times the bulk concentration in the mat). Arsenic was found predominantly as As(V) in organic molecules, as shown by XANES spectra and high‐resolution elemental mapping. Arsenic cycling genes obtained from metagenomic analysis were associated with arsenic detoxification, supporting an active mechanism of As(V) uptake, As(III) efflux and organoarsenic accumulation in the extracellular polymeric substances (EPS) of the mat. Thus, we propose that such localized As enrichment can be attributed to a transient increase in As(V) concentrations in the circulating subsurface water of the Dead Sea shore and its subsequent incorporation into organoarsenic molecules through microbial detoxification processes. Our data set supports the possibility of metalloid enrichment recorded in very localized facies due to rapid geogenic fluctuations in the chemistry of the water flowing over a biofilm. In this context, this example calls for caution in interpreting metal(loid) enrichment in organic matter‐rich layers and microbialites of Paleoproterozoic origin. Arsenic signatures in Precambrian organic matter and carbonate rocks may host biosignatures, including evidence for extracellular polymeric substances, As‐binding and detoxification processes, without supporting arsenotrophy. However, they provide clues to better assess the paleoenvironmental conditions at the time of microbial mat formation.
Durham E-Theses Rank Lower Bounds in Propositional Proof Systems Based on Integer Linear Programming Methods

The work of this thesis is in the area of proof complexity, an area which looks to uncover the limitations of proof systems. In this thesis we investigate the rank complexity of tautologies for several of the most important proof systems based on integer linear programming methods. The three main contributions of this thesis are as follows: Firstly we develop the first rank lower bounds for the proof system based on the Sherali-Adams operator and show that both the Pigeonhole and Least Number Principles require linear rank in this system. We also demonstrate a link between the complexity measures of Sherali-Adams rank and Resolution width. Secondly we present a novel method for deriving rank lower bounds in the wellstudied Cutting Planes proof system. We use this technique to show that the Cutting Plane rank of the Pigeonhole Principle is logarithmic. Finally we separate the complexity measures of Resolution width and SheraliAdams rank from the complexity measures of Lovász and Schrijver rank and Cutting Planes rank.
Computing marine-ice thickness at an ice-shelf base

Abstract The freezing of sea water to the base of an ice shelf can give rise to large patches of accumulated ice, a phenomenon known as marine ice. In this study a numerical method is presented for calculating the thickness of the marine-ice layer using an ice- shelf-ocean model. The present-day modeling paradigm of ice-shelf–ocean interaction usually involves the fixed specification of the ice-shelf geometry while the ocean circulation in the cavity beneath the ice shelf evolves freely. This approach relies on several assumptions, such as steady-state ice-shelf thickness and ice-shelf flow fields, in order to make reasonable quantitative estimates of the thermodynamic exchange processes occurring at the ice-shelf base. This paper discusses the impact of these and other assumptions on the estimation of the thickness of the marine-ice layer. Model simulation results are presented for an idealized ice-shelf–ocean configuration as a demonstration of the feasibility of the numerical method. A sensitivity analysis is given so as to quantify the relative uncertainty in the marine-ice thickness that arises from uncertainties in the model input parameters, these being principally the ice-shelf flow field, the basal accumulation rate and the ice-shelf thickness field.
Genetic basis of hypertrophic cardiomyopathy

Objectives: The purpose of this study was to explore a novel disease gene for hypertrophic cardiomyopathy (HCM) and evaluate functional alteration(s) caused by mutations. Background: Mutations in genes encoding myofilaments or Z-disc proteins of the cardiac sarcomere cause HCM, but the disease-causing mutations can be found in half of the patients, indicating that novel HCM-susceptibility genes await discovery. We studied a candidate gene ANKRD1 encoding for cardiac ankyrin repeat protein (CARP) that is a Z-disc component interacting with N2A domain of titin/connectin and N-terminal domain of myopalladin. Methods: We analyzed 384 HCM patients for mutations in ANKRD1 and in the N2A domain of titin/connectin gene (TTN). Interaction of CARP with titin/connectin or myopalladin was investigated using co-immunoprecipitation assay to demonstrate the functional alteration caused by ANKRD1 or TTN mutations. Functional abnormalities caused by the ANKRD1 mutations were also examined at the cellular level in neonatal rat cardiomyocytes. Results: Three ANKRD1 missense mutations, Pro52Ala, Thr123Met and Ile280Val, were found in 3 patients. All mutations increased binding of CARP to both titin/connectin and myopalladin. In addition, TTN mutations, Arg8500His and Arg8604Gln, in the N2A domain were found in 2 patients and these mutations increased binding of titin/connectin to CARP. Myc-tagged CARP showed that the mutations resulted in abnormal localization of CARP in cardiomyocytes. Conclusion: CARP abnormalities may be involved in the pathogenesis of HCM.
Improving Local Search for Resource-Constrained Planning

A ubiquitous feature of planning problems — problems involving the automatic generation of action sequences for attaining a given goal — is the need to economize limited resources such as fuel or money. While heuristic search, mostly based on standard algorithms such as A*, is currently the superior method for most varieties of planning, its ability to solve critically resource-constrained problems is limited: current planning heuristics are bad at dealing with this kind of structure. To address this, one can try to devise better heuristics. An alternative approach is to change the nature of the search instead. Local search has received some attention in planning, but not with a specific focus on how to deal with limited resources. We herein begin to fill this gap. We highlight the limitations of previous methods, and we devise a new improvement (smart restarts) to the local search method of a previously proposed planner (Arvand). Systematic experiments show how performance depends on problem structure and search parameters. In particular, we show that our new method can outperform previous planners by a large margin.
GUILHERME DE JONG GENOMIC PREDICTION AND GENOME-WIDE ASSOCIATION STUDY: AN APPLICATION OF QUANTITATIVE GENETICS IN PLANT BREEDING PROGRAMS

The development of new tools and advances in high throughput genomic technologies have facilitated genomic selection the identification of sources of variation, especially of complex traits. Therefore, the availability of abundant and cheap markers made it possible to exploit the marker information in breeding programs. The most common tools used in breeding programs that exploit the dense marker coverage are genomic prediction and genome-wide association studies. In the genomic prediction, marker parameters are estimated from a training dataset with genotyped and phenotyped individuals. Subsequently, the trained model is used to predict performance for individuals that are only genotyped. On the other hand, genome-wide association studies test marker-trait associations that may be responsible for the causal variation of interest. We investigated the performance of different genomic prediction models to select parents in the early stage of a hybrid breeding program using estimated general combining ability and their impact on selection accuracy and long-term genetic gain. We evaluated the performance of five genomic prediction models under different SNP marker densities or QTL genotypes using stochastic simulations of an entire hybrid breeding program. We also investigated the ability of univariate and multivariate GWAS identifying markers linked to loci that contribute to resistance to Diplodia ear rot or Fusarium ear rot or both diseases in maize inbred lines. We evaluated the univariate and multivariate approaches using a maize diverse panel evaluated for three different traits.