Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing the learnability of process interactions using grammatical spaces

A challenge in learning phonological grammars is learning how phonological processes interact. It has been argued that some process interactions are easier to learn than others. One basis for this argument is asymmetries observed in experimental settings: artificial languages generated from certain process interactions are more likely to be successfully reproduced by participants than others. In this paper, we argue that asymme- tries in production do not necessarily provide direct support that some phonological interactions are easier to learn. Rather, we show that these asymmetries can instead emerge due to differences in the number of consistent or nearly-consistent gram- mars each pattern has. We present a noisy channel model of morpho-phonological learning and apply it to a recent behav- ioral study examining the learnability of phonological process interactions. We find that, due to the relative difference in the number of grammars that can exactly match or nearly match the observed data, the model achieves the same qualitative re- sults as those observed in experimental settings.
Improving source-code representations to enhance search-based software repair

Automatically improving and repairing software using search-based methods is an active research topic. Many current systems use existing source code as the ingredients of repairs, either through evolutionary computation derived random mutation or other heuristic operators. However, these code transformation operators are not always well-matched to the granularity of the source code on which they operate. This paper proposes a static source-to-source preprocessing step to produce code with more uniform granularity that exposes relevant program components to the repair process. This approach, called Program Repair Enhancement via Preprocessing (PREP), has been applied to three different repair tools, each of which uses different code transformation operators and search algorithms. In every case, applying PREP before the search allows the tool to repair software defects that were previously unattainable by that tool. PREP finds 88 unique previously-unreported correct repairs across these tools. This result is significant because it is applicable to most search-based software improvement methods, and it addresses the fundamental issue of how to match the granularity of the representation to the granularity of operators.
PUBLIC HEALTH APPLICATIONS OF TWITTER DURING THE CURRENT COVID-19 PANDEMIC

Health education and promotion tools continue to evolve as new interventions and programs are designed to take advantage of current technology. The widespread use of social media sites across all types of populations make them ideal to serve as accessible platforms for public health campaigns. Understanding the interactions between social determinants of health and various networking sites may also prove crucial to developing strategies that reduce health disparities among vulnerable populations. Equally important is the use of misinformation and spam links to spread false reports and increase public anxieties. Overcoming this barrier is essential during public health crises, such as infectious disease outbreaks, in order to reduce disease transmission and unnecessary panic, which can lead to negative health behaviors. As one of the largest networking sites, Twitter has proven its utility in the public health field in prior research by providing emotional support and acting as a communication and public surveillance system, as well as serving as a tremendous source for data. By analyzing how Twitter has impacted COVID-19 responses for prevention and treatment, and how the site can be effectively used to disseminate information throughout the pandemic to educate and inform the public, improvements on communication strategies and response efforts can be employed during future epidemics or pandemics. Despite the small data sample, this research project can act as a framework for larger investigations focused on social media use and COVID-19 and how Twitter can be used by NGO and governmental agencies during public health crises.
Characterisation of the performance of p-type Si detectors for hard X-ray spectroscopy

High-density compound semiconductors with sufficiently-high photon attenuations, such as CdZnTe, are required for the detection of the high-energy X-rays (>20 keV), typical to applications of the HEXITEC ASIC. However, in low-energy applications (2–20 keV), the lower electron-hole-pair generation energy of Si offers the potential of improved spectroscopic resolution. Si-based pixelated X-ray sensors are typically based on n-type material where holes are the carrier that form the signal measured on the pixels. However, the incorporation of p-type dopants into the material enables these sensors to be operated effectively in electron readout. This is similar to CdZnTe sensors, where electrons are measured by the pixels. Critically, this allows a single electron-sensitive chip to be utilised for low- and high-energy measurements. Presented in this paper are the results of the spectroscopic characterisation of four p-type-Si sensors (two 300 μm and two 500 μm thick), manufactured by Micron Semiconductors Ltd., and flip-chip bonded to the HEXITEC ASIC. At 13.94 keV all tested devices displayed average FWHM of <540 eV and the average ASIC-limited FWHM of 489 ± 75 eV measured for a single 300 μm module represents the highest resolution measured with the HEXITEC ASIC. Results also show very low pixel-to-pixel variations in the measured FWHM demonstrating the excellent spatial uniformity of these devices, and a study into the temporal stability of a single detector over a ∼30 h period demonstrated negligible changes in spectroscopic performance.
The fully-kinetic investigations on the ion acceleration mechanisms in an electron-driven magnetic nozzle

A fully kinetic particle-in-cell study is conducted to investigate the ion acceleration mechanisms in an electron-driven magnetic nozzle. All five powers contributing to the axial kinetic energy of ions are derived and evaluated under different magnetic field strength and inlet density profiles. Among them, the electrothermal and electromagnetic acceleration contributes over 98% of the total accelerating power. The dominating acceleration mechanism is found to be the electrothermal acceleration, covering two thirds of the axial accelerating power in the electron-driven magnetic nozzle. The electromagnetic mechanism is found to originate from four sources, among which the major accelerating and decelerating one are the diamagnetic acceleration driven by radial gradient of electron pressure and the E × B mechanism due to the inward ion detachment. The power induced by the viscous-stress of electrons contributes 14%–23% of the decelerating power, indicating the non-negligible influence of finite electron Larmor radius effect on the ion acceleration. Results indicates that the net effect of electromagnetic mechanism can even be decelerating when the magnetic field is too high with a uniform inlet. Finally, the conversion efficiency from the inlet thermal energy to the ion axial kinetic energy is derived and evaluated, which can reach as high as 65.0% under 0.25 T with a Gaussian-profile inlet. Raising the magnetic field to 0.75 T or a uniform inlet will decrease the conversion efficiency.
Demo: Recovering Autonomous Robotic Vehicles from Physical Attacks

—Robotic Vehicles (RV) rely extensively on sensor inputs to operate autonomously. Physical attacks such as sensor tampering and spoofing feed erroneous sensor measurements to deviate RVs from their course and result in mission failures. We present PID-Piper , a novel framework for automatically recovering RVs from physical attacks. We use machine learning (ML) to design an attack resilient FeedForward Controller (FFC), which runs in tandem with the RV’s primary controller and monitors it. Under attacks, the FFC takes over from the RV’s primary controller to recover the RV, and allows the RV to complete its mission successfully. Our evaluation on 6 RV systems including 3 real RVs shows that PID-Piper allows RVs to complete their missions successfully despite attacks in 83% of the cases.
Auction-theoretic aspects of cross-border auctions

1. Abstract Cross-border renewable energy auctions are a topic of growing interest for policymakers, but remain under-analysed. In cross-border auctions, projects located outside of the auction-conducting country can participate and compete for support. There are numerous options for designing cross-border auctions for renewable energy support. This paper examines how opening auctions to projects in other countries inﬂuences both the allocative efﬁciency (i.e., projects with the lowest generation costs are awarded) and the resulting award prices. A conceptual categorization is developed with three distinct types of cross-border auctions, each with different degrees of openness and implications for auction outcomes. The types are: Joint Auctions, where two countries implement a common auction scheme, open to projects from both countries, mutually opened auctions ("Mutual Auctions"), a scenario in which both countries open their auction schemes, and unilaterally opened auctions ("Unilateral Auctions"), where both countries conduct auctions but only one country opens its support scheme to foreign projects. Furthermore, we evaluate the outcomes of Separate Auctions, in which two countries conduct their auctions independently, while only domestic projects are allowed to participate. Auction-theoretic modelling shows that Joint Auctions can achieve both allocative efﬁciency and moderate award prices. However, a complex implementation process and necessary bi-lateral coordination might make this option difﬁcult to realise. Sequential Mutual Auctions, i.e., when the open auctions are conducted one after another and with enough time in between the auctions and not within a very short time frame, lead to similar outcomes, but with less administrative effort, since both participating countries can choose their own auction design. The remaining design choices all show a low probability of allocative efﬁciency and might lead to higher awarded prices. More generally, the analysis shows that parallel auctions (where project developers must choose in which auction they want to participate and cannot participate in both) tend to decrease the efﬁciency of a support scheme.
Feature Extraction from JavaScript

: Source code analyzation is generally a challenging task and it is especially true for loosely typed languages like JavaScript. Traditionally analyzation is done by hand with the help of static analyzation tools which has many disadvantages - one of which is the lack of robustness. The recent advances in machine learning are promising to increase the robustness of source code analysis, however for ML models to work a meaningful and compatible representation is needed. We propose a speciﬁc way of extracting features of JavaScript source code based on it’s underlying structure (AST) then we embed these features to a ﬁxed length vector using Doc2Vec. Applying this method on a dataset of 150 000 Java Script source ﬁles we found this representation to be meaningful as the semantically similar AST nodes are grouped together after the embedding.
Demo: Hijacking Connected Vehicle Alexa Skills

—Current voice assistant platforms allow users to interact with their cars through voice commands. However, this convenience comes with substantial cyber-risk to voice-controlled vehicles. In this demo, we show a “malicious” skill with unwanted control actions on the Alexa system could hijack voice commands that are supposed to be sent to a benign third-party connected vehicle skill.
The recent concept in the management of anterior Skull base tumor: A review of the literature

Introduction Tumor of the skull base are classified based on their tissue of origin. Tumor originates from epithelium, mesenchyme, and neuroectoderm. Management of tumors depends on location, histologic characteristics, and their behaviors. A sinus endoscopy, Computerized tomography scan, and Magnetic Resonance Imaging should be performed to know the type and extent of the tumor. Treatment includes surgical excision either endoscopic vs open, chemotherapy and immunotherapy. We are highlighting the management option of each tumor according to their type of tissue origin and its location. Methods: A PubMed search was conducted for relevant publications using the terms “anterior skull base malignancies” and “anterior skull base malignancies treatment and “open vs endoscopic anterior skull base malignancies. ” The publication language should be English. Results: Articles published after 2000 that cover the most recent paradigm shift in the treatment of anterior skull base tumors were included. There have been 35 articles found, despite 20 of them are being rejected due to the lack of full text, abstract, and non-english. Three of the fifteen articles have been downloaded twice, thus they have been excluded. Conclusion: Skull base tumors are treated based on findings of diagnostic nasal endoscopy and imaging results. CT scans and MRIs are becoming more significant in the diagnosis of diseases. Endoscopic techniques to the skull base were beneficial in treating the malignancy. Chemotherapy can be used as a gold standard first-line treatment with radiation and surgery for significant types of head and neck tumors. immunotherapy-like checkpoint inhibitors targeting PD1 are the second-line treatments of advanced HNSCC. Prospective research and trials will be required in the future.
Model Aware LiDAR Odometry and Mapping (MA-LOAM): Improving Simultaneous Localization and Mapping accuracy by robustly leveraging a Building Information Model

The ability to accurately determine the position of an agent in an unknown environment is of crucial importance for the Simultaneous Localization And Mapping (SLAM) problem. Better localization and odometry estimates lead to improved map generation. This map forms the basis of most robot navigation stacks and is essential for driving without human interference. With the increase in automation along with the use of robotics, there is an increased need to refine the SLAM related methodologies. While indoor navigation usually lacks access to reliable Global Positioning System (GPS) data, it has the advantage of having a known building model in most cases. This extra level of information can be exploited to boost the quality of both the localization and mapping modules. As the real environment usually differs significantly from the theoretical model, a methodology that is resilient to outliers and scan model differences is proposed. This approach is added on top of Lidar Odometry And Mapping (LOAM) and also made open source to the public.
Empathic Design for Community Resilience

1. Empathy: Definition and Characteristics Empathy in psychology was considered as a research topic of experimental research in the early 20th century, and since then, it has been explored in several major fields of cognitive, developmental, social, and clinical psychology . The new research on empathy as a major part of emotional intelligence in the late 20th century, however, made it a central concept in some significant psychological and psychotherapist research studies. Recently an increasing number of studies have been conducted on the role of empathy in engineering education and practice .
GiLE Journal of Skills Development Are young graduates ready for the job market of the future? The study of the Italian case

The current paper presents the Italian results of the Project Erasmus + “ 21 st Century Skills: Changing the Approach to Teaching in Higher Education ” funded by the European Commission. The paper is aimed at presenting the work of Smarthink Ltd, as project partner, providing definitions, current research, and the best practices for teaching the ‘ so-called ’ soft skills among university students and fresh graduates in Italy, and to understand the employers’ perception of the owned and desired competencies among young employees. The study design was twofold. Firstly, desk research where major documents, national and international, were collected on the topic in Italy, and secondly, market research where a sample of entrepreneurs was interviewed in order to gather additional information on the level of development of these skills among young graduates and employees. Findings revealed that in Italy 21st Century Skills developed by young graduates are still few and that there are only a few examples of best practices to develop these competencies at the university level. In addition, employers testified that, while young graduates are usually well prepared in terms of the level of knowledge acquired during their studies, on the other side, they regularly lack practical skills and soft skills required by the marketplace. In conclusion, there is a broad and general need in Italy to improve these skills in order to make young people more employable, giving priority to skills such as critical thinking, collaboration, and self-direction. For this reason, the role of institutions like universities becomes crucial in order to reach this goal.
Meta-learning from Learning Curves Challenge 2022 Fact sheet template

1 Team details • Team name *: AIpert • Team leader name *: Giorgia Franchini • Team affiliation *: UNIMORE University of Modena and Reggio Emilia • Team leader address *: Via Campi, 213/B 41125 Modena (MO) • Team leader phone number *: 059 205 5243 • Team leader email *: giorgia.franchini@unimore.it • Name of other team members (if any) Elena Govi, Davide Sapienza, Carmelo Scribano • Team website URL (if any):
Carbide: A Safe Persistent Memory Multilingual Programming Framework

Persistent memory (PM) technology has brought the opportunity of accessing persistent data directly by using load and store instructions, improved memory system capacity, and a unified programming model for persistent and volatile programs. Many PM libraries [1–6] have been introduced to operate on PM devices safely. Although they provide safe interfaces to interact with PM, not all of them verifiably address novel PM programming challenges. Of a particular class of PM libraries, some of them provide strong guarantees to prevent PM-related bugs. Corundum [4] is the state-of-the-art in this category, but it applies several restrictive rules that thwart performance optimizations. The diversity in the offerings and limitations of the current PM programming frameworks motivates us to look for a hybrid PM programming model that can be both flexible and verifiably safe.
The Centrality of Team Leaders in Knowledge-Sharing Activities: Their Dual Role as Knowledge Processors

This chapter focuses on the extraction of accurate knowledge embedded in various Internet repositories, liable to frequent updates of content, and the effective sharing within organizational teams; an area that has not been extensively researched. We will address this issue by exploring the central and dual role of team leaders in their capacity as knowledge processors, functioning both as “sources” and “recipients” of net-based knowledge. The case of action teams that have to deal with unpredictable situations and thus, need to obtain and make instant use of accurate knowledge, is also considered. Further suggestions are made regarding team leaders’ active participation in particular knowledge-sharing channels, the multifaceted nature of the knowledge exchange, the essentiality of time boundaries, as well as knowledgesearch and knowledge-sharing costs. Besides making concrete suggestions, and far from exhausting the various issues in the literature of knowledge sharing, this study offers a potentially new scope for the team leader’s role in the knowledge society on the Internet.
Damage identification of a long-span arch bridge based on support vector machine

As a new machine learning algorithm,the method of support vector machine (SVM) shows its superiority of the ability of regression in the fields of damage identification.Considering variation ratio of curvature mode as the feature parameters of damage identification,the method of the damage identification of a long-span arch bridge based on SVM was presented.At first,the variation ratio of curvature mode was used to carry on damage location identification.Then,the training samples were reconstructed,the method of least square support vector machine was used to identify the long-span arch bridge damage level,and the identification results were very close to the target values under the condition of small samples.Compared with the results from the RBF neural network,the precision of the proposed method was verified.
Accelerated Aging Mediates the Associations of Unhealthy Lifestyles with Cardiovascular Disease, Cancer, and Mortality: Two Large Prospective Cohort Studies

With a wellvalidated aging measure - Phenotypic Age Acceleration (PhenoAgeAccel), this study examined whether and to what extent aging mediates the associations of unhealthy lifestyles with adverse health outcomes. Data were from 405,944 adults (40-69 years) from UK Biobank (UKB) and 9,972 adults (20-84 years) from US National Health and Nutrition Examination Surveys (NHANES). The mediation proportion of PhenoAgeAccel in associations of unhealthy lifestyles with incident cardiovascular disease, incident cancer, and all-cause mortality were 20.0%, 17.8%, and 26.6% (P values <0.001) in UKB, respectively. The mediation proportion of PhenoAgeAccel in associations of lifestyles with cancer mortality, and all-cause mortality were 25.7%, and 35.2% (P values <0.05) in NHANES, respectively. This study demonstrated that accelerated aging partially mediated the associations of lifestyles with adverse health outcomes in UK and US populations. The findings reveal a novel pathway and the potential of geroprotective programs in mitigating health inequality in late-life beyond lifestyle interventions.
Analisis Servicescape, Interaction Quality, Service Convenience Terhadap Service Quality Pada Beberapa Minimarket Di Kota Manado

Kualitas layanan dan kenyamanan sangat ditentukan oleh orang, dan lingkungan pelayanan. Tujuan penelitian untuk membuktikan pengaruh servicescape , interaction quality , dan service convenience terhadap service quality . Responden penelitian adalah para pelanggan pada beberapa minimarket di Kota Manado dengan jumlah sampel sebanyak 121 orang. Teknik analisis menggunakan Analisis Jalur dengan menggunakan SPSS 18. Hasil penelitian menunjukan servicescape berpengaruh tidak signifikan terhadap service convenience dan service quality . Sementara interaction quality berpengaruh signifikan terhadap service convenience dan service quality. Service convenience memediasi pengaruh servicescape dan service convenience terhadap service quality. Sebaiknya pihak manajemen minimarket mempertahankan dan meningkatkan kualitas pelayanan karyawan. Interaksi antar karyawan dengan karyawan, maupun karyawan dengan pelanggan akan lebih baik bila, pihak manajemen juga memperhatikan kenyamanan tempat berbelanja, dan merekrut tenaga kerja dari masyarakat sekitar tempat usaha. Kata kunci : servicescape, interaction quality, service convenience, kualitas jasa