Miracle-dz/UniFAR-FTUs huggingface dataset:
Preface of the 7th International Workshop on Quantitative Approaches to Software Quality (QuASoQ 2019)

Well-chosen variable names play significant roles in program comprehension and high-quality software development and maintenance. However, even though all variables have easyto-understand names, attention needs to be paid to the similarity among those names as well because a highly similar pair of variables may decrease the readability of code and might cause a fault. In order to analyze the relationship of variable similarity with the risk of introducing faults, this paper collects variable data from ten Java open source development projects and conducts an empirical study on the following three research questions: (1) Does the distribution of similarity differ among software development projects? , (2) What is the appropriate threshold of similarity? , and (3) How can the threshold of similarity contribute to the fault-prone method prediction? Then, the empirical results show the following findings: (1) The distribution of similarity is nearly identical regardless of the project; (2) Programmers should avoid giving similar names to different variables to prevent a fault introduction, and the threshold of Levenshtein similarity is 0.35; (3) By classifying Java methods with the above threshold, the risk of overlooking fault-introducing events in the fault-prone prediction model is effectively reduced; The recall of the prediction model improves by 12.8% on average.
Predicting Visual Futures with Image Captioning and Pre-Trained Language Models

The task of visual forecasting deals with pre-001 dicting future events from a sequence of in-002 put images. Purely pixel-based approaches 003 ﬁnd this challenging due to the presence of ab-004 stract concepts and temporal events at differ-005 ent timescales. In this paper, we present an ap-006 proach that combines image captioning with 007 pre-trained language models to predict visual 008 futures. By leveraging language as an inter-009 mediate medium, our model is able to perform 010 more effective temporal reasoning on two dif-011 ferent tasks – visual story cloze and action 012 forecasting. Despite making the ﬁnal predic-013 tions using only the generated captions, our 014 approach outperforms state-of-the-art systems 015 by 4% and 6% respectively on the two tasks. 016 We ﬁnd that our model consistently picks im-017 ages/actions that are semantically relevant to 018 the given image sequence instead of simply re-019 lying on visual similarity. 1 020
Grammatical Domains and Syntax-guided Grammar Induction

Grammatical domains are sets of related grammars. Such domains appear naturally whenever a common datatype like a date, a phone number or an address has multiple textual representations. While the grammar induction problem may be intractable in general, when specialized to such grammatical domains it is often not only feasible but efficient. In this paper, we introduce the concept of grammatical domains and propose to learn grammars within such domains using Syntax-guided Grammar Induction (SGI), a refinement of the traditional grammar induction problem that includes a syntactic specification of the grammars to search through. To support the definition of grammatical domains, we design Saggitarius, the first user-facing meta-language for specifying grammatical domains. The Saggitarius system comes equipped with an algorithm for solving SGI problems based on encoding them as MaxSMT instances. We also define a benchmark suite for SGI and evaluate the effectiveness of the algorithm on our benchmark suite, showing it typically returns a satisfying grammar within a few seconds. We describe a case study in which we use Saggitarius to detect classes of XML documents and find that Saggitarius metagrammars can be used to tame a highly ambiguous search space. Finally, we perform a second case study in which we use Saggitarius to detect CSV dialects. Our general purpose tool infers grammars for 84% of the files in the case study within the specified timeout. On these grammars, it has comparable accuracy to custom-built dialect detection tools.
Impact of Personal ProtectionHabits on the Spread of Pandemics: Insights from an Agent-Based Model

Background. After several waves of spread of the COVID-19 pandemic, countries around the world are struggling to regain their economies by slowly lifting mobility restrictions and social distance measures applied during the crisis. Meanwhile, recent studies provide compelling evidence on how contact distancing, the use of face masks, and handwashing habits can reduce the risk of SARS-CoV-2 transmission. In this context, we investigated the effect that these personal protection habits can have in preventing new waves of contagion. Methods. We extended an agent-based COVID-19 epidemic model in a simulated community to incorporate the mechanisms of these aforementioned personal care habits and measure their incidence in person-to-person transmission. A full factorial experiment design was performed to illustrate the extent to which the interplay between these personal habits is effective in mitigating the spread of disease. A global sensitivity analysis was performed on the parameters that control these habits to further validate the results. Results. We found that observing physical distance is the dominant habit in reducing disease transmission, although adopting either or both of the other two habits is necessary to some extent to suppress a new outbreak entirely. When physical distance is not observed, adherence to the use of masks or handwashing has a significant decrease in infections and mortality, but the epidemic still unfolds. We also found that in all scenarios, the combined effect of adhering to the three habits is more powerful than adopting them separately. Conclusions. Our findings suggest that a broad adherence of the population to voluntary self-care habits would help contain unfold of new outbreaks.e purpose of our model is illustrative and contributes to ratify the importance of urging citizens to adopt the amalgam of personal care habits as a primary collective protection measure to prevent communities from returning to confinements, while immunisation is carried out in late stages of the pandemic.
COMPARATIVE STUDY OF CONVENTIONAL AND RECIPROCAL RECOMMENDATION SYSTEM

: Recommendation systems provide an intelligent way to navigate through an ocean of options available at users’ disposal and present information that they perceive to be useful and worth trying out. Recommender Systems (RS) are assistance in the form of software, tools or algorithms that may guide a target user in making decision by proposing him recommendations based on his interests. In conventional recommendation system we have active elements on one side (Person) and passive elements in others side (Products). Success is determined by only one side (user–side) who is seeking recommendation, but the other way is not possible. Reciprocal recommendation is a special case of recommendation system where both sides we have active participants (people) and their mutual agreement is mandatory for a successful relation. Many social websites’ core task is to recommend people to people. The objective of this article is to do a comparative study of conventional and reciprocal recommendation system and study the domain of applications and the approaches used for the implementation in the recommendation system.
HiRID-ICU-Benchmark - A Comprehensive Machine Learning Benchmark on High-resolution ICU Data

The recent success of machine learning methods applied to time series collected from Intensive Care Units (ICU) exposes the lack of standardized machine learning benchmarks for developing and comparing such methods. While raw datasets, such as MIMIC-IV or eICU, can be freely accessed on Physionet, the choice of tasks and pre-processing is often chosen ad-hoc for each publication, limiting comparability across publications. In this work, we aim to improve this situation by providing a benchmark covering a large spectrum of ICU-related tasks. Using the HiRID dataset, we define multiple clinically relevant tasks in collaboration with clinicians. In addition, we provide a reproducible end-to-end pipeline to construct both data and labels. Finally, we provide an in-depth analysis of current state-of-the-art sequence modeling methods, highlighting some limitations of deep learning approaches for this type of data. With this benchmark, we hope to give the research community the possibility of a fair comparison of their work.
Semantic Similarity of Concepts for a Human-Centered Idea Recommendation Feature in the Clustering Application Orchard

Orchard is a creative clustering application developed in the Idea2Market project. The task of bringing many ideas into spacial-relation, called clustering, is part of a more extensive ideation process and is considered highly creative and beneficial to humans in developing ideas. Hence, taking away this task with an automated cluster generation might harm the ideation process. Still, manually going through a stack of hundreds of ideas can be mundane. This thesis implements a recommendation feature that supports users in clustering many ideas to synthesize and evolve them into more advanced and promising ideas. The creative task of clustering remains in the user’s hand. However, through interaction they can control which ideas are explored next when building their representation of ideas by clustering them. This is done by repetitively specifying a target for which the recommendation feature provides similar ideas. For the similarity measurements, to recommend similar ideas, the recommendation feature applies the information of knowledge graphs (KGs) that describe resources and encode relations and facts of concepts. This work includes experiments on the performance of five variants of concept similarity methods and one idea similarity method using the Wikidata KG to ensure the accuracy of the used similarity measures. The similarity method path uses the path-length between concepts of the KG, the methods res, lin, jcn differently apply a graph-based Information Content measurement and wpath combines the two. The evaluation points out the potential of Wikidata as a knowledge source for semantic similarity. The semantic similarity approach proved its suitability by a high correlation to human perceptions of word similarity for five well-studied datasets, namely R&G, M&C, WS353, WS353-Sim, and SimLex. wpath performed best in three out of five datasets and thus was applied in the recommendation feature. The idea similarity method is a variant of the Word Mover’s Distance and proved its accuracy in further experiments. A Think-Aloud user study with five participants conducted for this thesis shows that the recommendation feature achieves a targeted and more efficient iteration through the ideas for the clustering tool Orchard. With the novel feature, the participants reported they were able to explore the ideas for clusters of their current interest, which enabled an in-depth iteration on various topics. These observations could indicate an improvement in the idea synthesis, which could be looked at in further research.
A Translation-Aborting Small Open Reading Frame in the Intergenic Region Promotes Translation of a Mg<sup>2+</sup> Transporter in <italic toggle='yes'>Salmonella</italic> Typhimurium

Bacterial mRNAs often harbor upstream open reading frames (uORFs) in the 59 untranslated regions (UTRs). Translation of the uORF usually affects downstream gene expression at the levels of transcription and/or translation initiation. Unlike other uORFs mostly located in the 59UTR, we discovered an 8-amino-acid ORF, designated mgtQ, in the intergenic region between the mgtC virulence gene and the mgtB Mg21 transporter gene in the Salmonella mgtCBRU operon. Translation of mgtQ promotes downstream mgtB Mg21 transporter expression at the level of translation by releasing the ribosome-binding sequence of the mgtB gene that is sequestered in a translation-inhibitory stem-loop structure. Interestingly, mgtQ Asp2 and Glu5 codons that induce ribosome destabilization are required for mgtQ-mediated mgtB translation. Moreover, the mgtQ Asp and Glu codons-mediated mgtB translation is counteracted by the ribosomal subunit L31 that stabilizes ribosome. Substitution of the Asp2 and Glu5 codons in mgtQ decreases MgtB Mg21 transporter production and thus attenuates Salmonella virulence in mice, likely by limiting Mg21 acquisition during infection. IMPORTANCE Translation initiation regions in mRNAs that include the ribosome-binding site (RBS) and the start codon are often sequestered within a secondary structure. Therefore, to initiate protein synthesis, the mRNA secondary structure must be unfolded to allow the RBS to be accessible to the ribosome. Such unfolding can be achieved by various mechanisms that include translation of a small upstream open reading frame (uORF). In the intracellular pathogen Salmonella enterica serovar Typhimurium, translation of the Mg21 transporter mgtB gene is enhanced by an 8amino-acid upstream ORF, namely, mgtQ, that harbors Asp and Glu codons, which are likely to destabilize ribosome during translation. Translation of the mgtQ ORF promotes the formation of a stem-loop mRNA structure sequestering anti-RBS and thus releases the mgtB RBS. Because mgtQ-mediated MgtB Mg21 transporter production is required for Salmonella virulence, this pathogen seems to control the virulence determinant production exquisitely via this uORF during infection.
Detoxification Esterase StrH Initiates Strobilurin Fungicide Degradation in <italic toggle='yes'>Hyphomicrobium</italic> sp. Strain DY-1

Strobilurin fungicides are widely used in agricultural production due to their broad-spectrum and fungal mitochondrial inhibitory activities. However, their massive application has restrained the growth of eukaryotic algae and increased collateral damage in freshwater systems, notably harmful cyanobacterial blooms (HCBs). In this study, a strobilurin fungicide-degrading strain, Hyphomicrobium sp. strain DY-1, was isolated and characterized successfully. Moreover, a novel esterase gene, strH, responsible for the de-esterification of strobilurin fungicides, was cloned, and the enzymatic properties of StrH were studied. For trifloxystrobin, StrH displayed maximum activity at 50°C and pH 7.0. The catalytic efficiencies (kcat/Km) of StrH for different strobilurin fungicides were 196.326 2.30mM21 · s21 (trifloxystrobin), 4.646 0.05mM21 · s21 (picoxystrobin), 2.946 0.02mM21 · s21 (pyraclostrobin), and (2.416 0.19) 1022mM21 · s21 (azoxystrobin). StrH catalyzed the de-esterification of a variety of strobilurin fungicides, generating the corresponding parent acid to achieve the detoxification of strobilurin fungicides and relieve strobilurin fungicide growth inhibition of Chlorella. This research will provide insight into the microbial remediation of strobilurin fungicide-contaminated environments. IMPORTANCE Strobilurin fungicides have been widely acknowledged as an essential group of pesticides worldwide. So far, their residues and toxic effects on aquatic organisms have been reported in different parts of the world. Microbial degradation can eliminate xenobiotics from the environment. Therefore, the degradation of strobilurin fungicides by microorganisms has also been reported. However, little is known about the involvement of enzymes or genes in strobilurin fungicide degradation. In this study, a novel esterase gene responsible for the detoxification of strobilurin fungicides, strH, was cloned in the newly isolated strain Hyphomicrobium sp. DY-1. This degradation process detoxifies the strobilurin fungicides and relieves their growth inhibition of Chlorella.
Compartmentalization of Melanin Biosynthetic Enzymes Contributes to Self-Defense against Intermediate Compound Scytalone in <italic toggle='yes'>Botrytis cinerea</italic>

In filamentous fungi, 1,8-dihydroxynaphthalene (DHN) melanin is a major component of the extracellular matrix, endowing fungi with environmental tolerance and some pathogenic species with pathogenicity. However, the subcellular location of the melanin biosynthesis pathway components remains obscure. Using the gray mold pathogen Botrytis cinerea, the DHN melanin intermediate scytalone was characterized via phenotypic and chemical analysis of mutants, and the key enzymes participating in melanin synthesis were fused with fluorescent proteins to observe their subcellular localizations. The Dbcscd1 mutant accumulated scytalone in the culture filtrate rather than in mycelium. Excessive scytalone appears to be self-inhibitory to the fungus, leading to repressed sclerotial germination and sporulation in the Dbcscd1 mutant. The BcBRN1/2 enzymes responsible for synthesizing scytalone were localized in endosomes and found to be trafficked to the cell surface, accompanied by the accumulation of BcSCD1 proteins in the cell wall. In contrast, the early-stage melanin synthesis enzymes BcPKS12/13 and BcYGH1 were localized in peroxisomes. Taken together, the results of this study revealed the subcellular distribution of melanin biosynthetic enzymes in B. cinerea, indicating that the encapsulation and externalization of the melanin synthetic enzymes need to be delicately orchestrated to ensure enzymatic efficiency and protect itself from the adverse effect of the toxic intermediate metabolite. IMPORTANCE The devastating gray mold pathogen Botrytis cinerea propagates via melanized conidia and sclerotia. This study reveals that the sclerotial germination of B. cinerea is differentially affected by different enzymes in the melanin synthesis pathway. Using gene knockout mutants and chemical analysis, we found that excessive accumulation of the melanin intermediate scytalone is inhibitory to B. cinerea. Subcellular localization analysis of the melanin synthesis enzymes of B. cinerea suggested twostage partitioning of the melanogenesis pathway: the intracellular stage involves the steps until the intermediate scytalone was translocated to the cell surface, whereas the extracellular stage comprises all the steps occurring in the wall from scytalone to final melanin formation. These strategies make the fungus avert self-poisoning during melanin production. This study opens avenues for better understanding the mechanisms of secondary metabolite production in filamentous fungi.
Kernel-Based Hamilton-Jacobi Equations for Data-Driven Optimal Control: The General Case

SUMMARY Recently, control theory using machine learning, which is usefulforthecontrolofunknownsystems,hasattractedsigniﬁcantattention. Thisstudyfocusesonsuchatopicwithoptimalcontrolproblemsforun-knownnonlinearsystems.Becauseoptimalcontrollersaredesignedbasedonmathematicalmodelsofthesystems,itischallengingtoobtainmodelswithinsuﬃcientknowledgeofthesystems. Kernelfunctionsarepromisingfordevelopingdata-drivenmodelswithlimitedknowledge.However,thecomplexformsofsuchkernel-basedmodelsmakeitdiﬃculttodesignthe optimal controllers. The design corresponds to solving Hamilton-Jacobi (HJ) equations because their solutions provide optimal controllers. There-fore, the aim of this study is to derive certain kernel-based models for which the HJ equations are solved in an exact sense, which is an extended version of the authors’ former work. The HJ equations are decomposed into tractable algebraic matrix equations and nonlinear functions. Solving the matrix equations enables us to obtain the optimal controllers of the model. A numerical simulation demonstrates that kernel-based models and controllers are successfully developed.
CPD_CONTENT 2020

Background: Breast cancer is one of the leading cancers in women in the Western world. Cancer treatment, especially chemotherapy, is often associated with physical and psychosocial side effects. Objective: To improve the quality of life and manage side effects, a new integrative mind-body-medicine group concept for breast cancer patients receiving chemotherapy was developed and pilot tested. Methods: Breast cancer patients participated in a 66 hours mind-body-medicine group program tailored to the needs of cancer patients during chemotherapy. The program was integrated into standard care encompassing mindfulness training, yoga, moderate exercise, nutrition, complementary self-help strategies, cognitive restructuring, and acupuncture. Quality of life (EORTC QLQ-C30), depression and anxiety (HADS), stress (PSS-10), and fatigue (BFI) were assessed before and after the program, as well as satisfaction and safety. Analyses were carried out on exploratory basis with paired samples t-tests. Results: Fifty-seven female patients, aged 51.3±10.5 years, with breast cancer diagnoses were enrolled. After completing the program, global EORTC quality of life was improved (D=9.5; 95%-CI=[2.9|16.1]; p=.005), although the EORTC-symptom scales assessing fatigue (D=9.9; 95%-CI=[1|18.8]; p=.030), nausea (D=7.1; 95%CI=[0.6|13.6]; p=.031), and dyspnea (D=12.5; 95%-CI=[2.9|22.1]; p=.011) were found to be increased. Stress (D=-3.5; 95%-CI=[-5|-2.1]; p=.000), anxiety (D=-3.8; 95%-CI=[-4.9|-2.7]; p=.000) and depression (D=-3.9; 95%-CI=[-4.9|-2.8]; p=.000) were also found to be significantly reduced. Regarding the severity of (D=0.2; 95%CI=[-0.8|0.5]; p=.644) and the impairment due to fatigue (D=0.1; 95%-CI=[-0.8|0.6]; p=.696), no significant worsening was observed. Patients were satisfied with the program. No serious adverse events were reported. Conclusion: Breast cancer patients benefit from an integrative mind-body-medicine group program during chemotherapy regarding the quality of life and psychological symptoms. Randomized controlled trials are warranted. A R T I C L E H I S T O R Y Received: June 16, 2020 Accepted: October 31, 2020 DOI: 10.2174/1381612826666201211111122
ScholarWorks @ Georgia State University ScholarWorks @ Georgia State University Aristotle on the Role of Practical Intellect in Determining the Ends Aristotle on the Role of Practical Intellect in Determining the Ends

In this thesis, I argue that an Aristotelian virtuous person not only reasons about the means of her action but also the ends of her action. A person who has been well habituated but never reflects on her ends is not yet virtuous. To be virtuous, the person needs to apprehend and may revise her apprehension of the ends that have been given to her in her habituation, such as apprehending what it is to be generous. I argue that to arrive at what it is to be generous, practical induction and reflective equilibrium are needed. Both practical induction and reflective equilibrium are exercises of practical intellect. Once the person apprehends what it is to be generous, she would be in a good position to determine a generous action as the appropriate end for a situation and justify why a particular action is generous.
The AI Doctor Is In: A Survey of Task-Oriented Dialogue Systems for Healthcare Applications

Task-oriented dialogue systems are increasingly prevalent in healthcare settings, and have been characterized by a diverse range of architectures and objectives. Although these systems have been surveyed in the medical community from a non-technical perspective, a systematic review from a rigorous computational perspective has to date remained noticeably absent. As a result, many important implementation details of healthcare-oriented dialogue systems remain limited or underspecified, slowing the pace of innovation in this area. To fill this gap, we investigated an initial pool of 4070 papers from well-known computer science, natural language processing, and artificial intelligence venues, identifying 70 papers discussing the system-level implementation of task-oriented dialogue systems for healthcare applications. We conducted a comprehensive technical review of these papers, and present our key findings including identified gaps and corresponding recommendations.