Miracle-dz/UniFAR-FTUs huggingface dataset:
Converbs in heritage Turkish: A contrastive approach

Abstract Turkish expresses adverbial subordination predominantly by means of converb clauses. These are headed by nonfinite verbs, i.e. converbs, which have a converb suffix attached to the stem. The different converbs express different aspectual relations between the subordinate and the superordinate clause, and they can be modifying or non-modifying. We analyse data from speakers of Turkish as a heritage language in Germany and the U.S. as well as monolingual speakers of Turkish in Turkey. The data come from two age groups: adults and adolescents. We show that unlike in canonical Turkish, converbs in heritage Turkish can be multifunctional, meaning that they can express both simultaneity and causality, for example. Furthermore, we show that converbs in heritage Turkish can be both modifying and non-modifying. As possible factors which might be responsible for such variation, we discuss language contact, sociolinguistic differences between the speaker communities (Germany vs. the U.S.) and age of the speakers.
An Exploratory Study on Dead Methods in Open-source Java Desktop Applications

Background. Dead code is a code smell. It can refer to code blocks, fields, methods, etc. that are unused and/or unreachable. Empirical evidence shows that dead code harms source code comprehensibility and maintainability in software applications. Researchers have gathered little empirical evidence on the spread of dead code in software applications. Moreover, we know little about the role of this code smell during software evolution. Aims. Our goal is to gather preliminary empirical evidence on the spread and evolution of dead methods in open-source Java desktop applications. Given the exploratory nature of our investigation, we believe that its results can justify more resource- and time-demanding research on dead methods. Method. We quantitatively analyzed the commit histories of 13 open-source Java desktop applications, whose software projects were hosted on GitHub, for a total of 1,044 commits. We focused on dead methods detected at a commit level to investigate the spread and evolution of dead methods in the studied applications. The perspective of our explorative study is that of both practitioners and researchers. Results. The most important take-away results can be summarized as follows: (i) dead methods seems to affect open-source Java desktop applications; (ii) dead methods generally survive for a long time, in terms of commits, before being "buried" or "revived;" (iii) dead methods are rarely revived; and (iv) most dead methods are dead since the creation of the corresponding methods. Conclusions. We conclude that developers should carefully handle dead methods in open-source Java desktop applications since this code smell is harmful, widespread, rarely revived, and survives for a long time in software applications. Our results also justify future research on dead methods.
Fast and Consistent Remote Direct Access to Non-volatile Memory

For performance benefits, recent trends of modern data centers tend to use NVM (Non-volatile Memory) as storage and utilize one-sided primitives of RDMA (Remote Direct Memory Access) to directly access NVM for I/O requests. However, one-sided RDMA doesn’t have durability semantics currently, and data may partially exist in the NVM when crashes happen, thus causing unexpected data inconsistency. Existing solutions sacrifice either read or write performance in exchange for consistency guarantees. In this paper, we introduce a multi-version log-structuring design, named eFactory, which delivers high performance for both read and write, yet also provides data consistency. In eFactory, a multi-version list is built for each object to solve the problem of crash consistency, especially when multiple clients update the same object concurrently. To transfer data directly with RDMA write as well as reduce CRC overhead on the read critical path, a single background thread is assigned to conduct integrity verification and data persisting. Furthermore, eFactory proposes a hybrid read scheme to gain high performance for reads without losing consistency guarantee. With a durability flag embedded in the object, the client can detect the durability status of data and re-read it if necessary. Evaluations show that eFactory outperforms IMM and SAW (solutions that sacrifice write performance) by 0.42x-2.79x and 0.66x-2.85x for write respectively, while maintains comparable read performance with them. In addition, the read throughput of eFactory is 1.3x-1.96x and 1.24x-1.67x of Erda and Forca (solutions that guarantee consistency at the cost of reading performance) respectively.
Sentry-NoC: A Statically-Scheduled NoC for Secure SoCs

SoC security has become essential with devices now pervasive in critical infrastructure in homes and businesses. Today’s embedded SoCs are becoming increasingly high-performance and complex, comprising multiple cores, accelerators, and IP blocks interconnected with a Network-on-Chip (NoC). As these IPs can originate from diverse sources, they cannot be trusted to form the root of trust in SoCs. However, the NoC itself, being the communication backbone linking all IPs, is naturally positioned to be the basis for a secure SoC. Therefore, there is a need for an efficient solution that both meets the stringent requirements of modern embedded SoC designs, while maintaining a high level of security.In this paper, we demonstrate how statically-scheduled NoCs inherently enforce traffic isolation and non-interference of communication. The time-division multiplexing (TDM) of NoC links across applications provably ensures that security properties are fulfilled. However, conventional TDM NoCs are still vulnerable to side-channel attacks. We thus propose temporal and data obfuscation schemes that can be embedded within static TDM NoCs, randomizing source-destination communication patterns and switching activity over the links. Our proposed statically-scheduled Sentry-NoC links up untrusted IP blocks to form a secure SoC. Sentry-NoC targets key security properties to effectively mitigate side-channel attacks with an extremely low overhead, reducing average temporal correlation by 81% and average data correlation by 91%.
Are we speaking the industry language? The practice and literature of modernizing legacy systems with microservices

Microservice architecture has gained much attention in the last few years in both industry and academia. Microservice is an architectural style that enables developing systems as a suite of small loosely coupled, and autonomous (micro)services that encapsulate business capabilities and communicate with each other using language-agnostic APIs. Despite the microservice adoption for modernizing legacy systems, few studies investigate how microservices are used in practice. Furthermore, the literature still scarce on presenting studies on why and how the modernization is conducted in practice in comparison to existing literature on the subject. Thus, our goal is to investigate if industry and academy are speaking the same language concerning the modernization of legacy systems with microservices, by means of a rigorous study on the use of microservices in the industry. For doing so, we design a survey to understand the state of practice from the perspective of a modernization process roadmap derived from the literature. In this paper, we report the results of a survey with 56 software companies, from which 35 (63.6%) adopt the microservice architecture in their legacy systems. Results pointed out the most expected benefits that drive the migration to microservices are easier software maintenance, better scalability, ease of deployment, and technology flexibility. Besides, we verified, based on a set of activities defined in the modernization process, that the practitioners are performing their migration process according to the best literature practices.
A Web-based Dental Caries Detection System Using Image Recognition and Deep Learning with SUS and UTAUT Analysis

The vital processes of a clinic system are the diagnostic process as well as storing patient dental records, forms, reports and other medical notes. This study created a web-based application that has an automatic dental caries detection and assessment tool, along with an online storage for patient dental records. The dental caries detection tool enabled the user to upload dental images, and output the severity class level, based on the ICDAS II criteria. This tool incorporated deep learning algorithms and uses the ImageAI Python library. Moreover, the web app works as an online dental diagnostic service and is able to store the patient's dental records and information in a database. Furthermore, SUS and UTAUT questionnaires were used to assess the usability. The SUS resulted with an average standard deviation of 0.7765, that interpreted the respondents’ answers to be consistent and a mean score of 76.25 which shows that most of the users found the system usable. The Unified Theory of Acceptance and Use of Technology (UTAUT) raw scores revealed high marks towards the questions under attitude toward using technology, social influence, and behavioral intention.
The Existence and Co-Modifications of Code Clones within or across Microservices

In recent years, microservice architecture has been widely applied in software design. In addition, more and more monolithic software systems have been migrated into a microservice architecture. The core idea is to decompose the concerns of software projects into small and loosely-coupled services. Each service is supposed to be developed and even managed independently, which in turn improving the efficiency of development and maintenance. Code clone is common during software implementations, and many prior studies have revealed that code clones could cause maintenance difficulties. However, there is little work exploring the impacts of code clones on microservice projects. To bridge this gap, we focus on exploring the existence and co-modifications of within-service and cross-service code clones. With our evaluation of eight microservice projects, we have presented that there still exist code clones within services or across services. In addition, both within-service and cross-service code clones have been involved in co-modifications, meaning that these clones have caused maintenance difficulties. Finally, we have explored the characteristics of co-modifications in terms of changed LOC for both within-service and cross-service code clones.
Characterizing and Predicting Good First Issues

Background. Where to start contributing to a project is a critical challenge for newcomers of open source projects. To support newcomers, GitHub utilizes the Good First Issue (GFI) label, with which project members can manually tag issues in an open source project that are suitable for the newcomers. However, manually labeling GFIs is time- and effort-consuming given the large number of candidate issues. In addition, project members need to have a close understanding of the project to label GFIs accurately. Aims. This paper aims at providing a thorough understanding of the characteristics of GFIs and an automatic approach in GFIs prediction, to reduce the burden of project members and help newcomers easily onboard. Method. We first define 79 features to characterize the GFIs and further analyze the correlation between each feature and GFIs. We then build machine learning models to predict GFIs with the proposed features. Results. Experiments are conducted with 74,780 issues from 10 open source projects from GitHub. Results show that features related to the semantics, readability, and text richness of issues can be used to effectively characterize GFIs. Our prediction model achieves a median AUC of 0.88. Results from our user study further prove its potential practical value. Conclusions. This paper provides new insights and practical guidelines to facilitate the understanding of GFIs and the automation of GFIs labeling.
Why Do Organizations Adopt Agile Scaling Frameworks?: A Survey of Practitioners

Background: The benefits of agile methods in small, co-located projects have inspired their adoption in large firms and projects. Scaling frameworks, such as Large-Scale Scrum (LeSS) and the Scaled Agile Framework (SAFe), have been proposed by practitioners to scale agile to larger contexts, and become rather widely adopted in the industry. Despite the popularity of the frameworks, the knowledge on the reasons, expected benefits, and satisfaction of organizations adopting them is still limited. Aims: This paper presents a study of practitioners who have adopted an agile scaling framework in their organization and investigates the reasons for, expected benefits of, and the satisfaction level with the adoption of the selected framework. Method: We conducted a survey of software practitioners. We received data from 204 respondents representing ten frameworks adopted in 26 countries and located in six continents. Results: The results show that SAFe is the most widely adopted framework among our respondents. The two most commonly mentioned reasons for adopting agile scaling frameworks are to scale to more people and to remain competitive in the market. The most common expected benefits are improving the collaboration and dependency management between teams. We also found some unique reasons and expected benefits for the framework adoption, such as inculcating an agile mindset, addressing the needs of regulated environments, dissolving silos, and technical excellence. Our findings indicated statistically significant differences for reasons, expected benefits, and satisfaction between different frameworks. Most of our respondents report that the selected framework met their expectations. Conclusions: This paper offers the first quantitative assessment of reasons, expected benefits, and satisfaction of firms for adopting agile scaling frameworks. Future studies comparing scaling frameworks could help firms in selecting the most suitable framework fitting their needs.
Crash-Consistency-Aware Encryption for Non-Volatile Memories

Data security is a very important issue in non-volatile memory (NVM) systems. Due to high security and low decryption latency, counter mode encryption (CME) is often used, which unfortunately suffers from extra efforts to guarantee the crash consistency of counters. Existing schemes fail to efficiently guarantee the crash consistency of counters and data, thus resulting in inefficient recovery and high costs. In this paper, we propose a Crash-Consistency-Aware Encryption scheme (CCAE) for NVM systems. CCAE is inspired by two key observations. First, we observe that all used log entries in a transaction have the same number of encryption times before being recycled due to the write appending feature. This motivates our shared counter optimization for log encryption. Second, we observe that the counters related to uncommitted data blocks only need to be restored to the latest or newer value before the crash to avoid OTP reuse. This motivates our delayed counter persistency scheme for data encryption. Evaluation results show that compared with the state-of-the-art design, CCAE reduces NVM write traffic caused by counters by 67%, improves system performance by 14%, and decreases NVM energy consumption by 35%.
Mechanistic Model of Telomere Length Homeostasis in Yeast

Cells maintain homeostatic telomere length, and this homeostatic disruption leads to various types of diseases. Presently, it is not clear how telomeres achieve homeostasis. One of the prevailing hypotheses is a protein-counting model with a built-in sensor mechanism that counts proteins that directly regulate the telomeric length. However, it does not explain telomere length regulation at the mechanistic level. Here, we present a mathematical model based on the underlying molecular mechanisms of length regulation needed to establish telomere length homeostasis in yeast. We perform both deterministic and stochastic simulations to validate the models with the experimental data of Teixeira et al., rate-balance plot, and phase plane analysis to understand the nature of dynamics exhibited by the models. For global analysis, we constructed bifurcation diagrams. The model explains the role of negative and positive feedback loops and a delay between telomerase and telomere-bound proteins, leading to oscillations in telomere length. We map these in-silico results to Teixeira’s proposition of telomeres making a transition between extendible and non-extendible states.
Ataxin-2 Disordered Region Promotes Huntingtin Protein Aggregation And Neurodegeneration In Drosophila Models Of Huntington’s Disease

The Ataxin-2 (Atx2) protein contributes to the progression of neurodegenerative phenotypes in animal models of amyotrophic lateral sclerosis (ALS), type 2 spinocerebellar ataxia (SCA-2), Parkinson’s Disease (PD) and Huntington’s Disease (HD). However, because the Atx2 protein contains multiple separable activities, deeper understanding requires experiments to address the exact mechanisms by which Atx2 modulates neurodegeneration (ND) progression. Recent work on two ALS models, C9ORF72 and FUS, in Drosophila has shown that a C-terminal intrinsically disordered region (cIDR) of Atx2 protein, required for assembly of ribonucleoprotein (RNP) granules, is essential for the progression of neurodegenerative phenotypes as well as for accumulation of protein inclusions associated with these ALS models. Here we show that the Atx2-cIDR also similarly contributes to the progression of degenerative phenotypes and accumulation of Huntingtin protein aggregates in Drosophila models of HD. Because Huntingtin is not an established component of RNP granules, these observations support a recently hypothesised, unexpected protein-handling function for RNP granules, which could contribute to the progression of Huntington’s disease and, potentially, other proteinopathies.
Th2 single-cell heterogeneity and clonal interorgan distribution in helminth-infected mice

Th2 cells provide effector functions in type 2 immune responses to helminths and allergens. Despite knowledge about molecular mechanisms of Th2 cell differentiation, there is little information on Th2 cell heterogeneity and clonal distribution between organs. To address this, we performed combined single-cell transcriptome and TCR clonotype analysis on murine Th2 cells in mesenteric lymph nodes (MLN) and lung after infection with Nippostrongylus brasiliensis (Nb) as a human hookworm infection model. We find organ-specific expression profiles, but also populations with conserved migration or effector/resident memory signatures that unexpectedly cluster with potentially regulatory Il10posFoxp3neg cells. A substantial MLN subpopulation with an interferon response signature suggests a role for interferon-signaling in Th2 differentiation or diversification. Further RNA-inferred developmental directions indicate proliferation as a hub for differentiation decisions. We also link long noted Cxcr3 expression in the Th2 compartment to a population of Il4pos NKT cells. Although the TCR repertoire is highly heterogeneous, we identified expanded clones and CDR3 motifs. Clonal relatedness between distant organs confirmed effective exchange of Th2 effector cells, although locally expanded clones dominated the response. These results provide new insights in Th2 cell subset diversity and clonal relatedness in distant organs.
Direct brain recordings reveal continuous encoding of structure in random stimuli

The brain excels at processing sensory input, even in rich or chaotic environments. Mounting evidence attributes this to the creation of sophisticated internal models of the environment that draw on statistical structures in the unfolding sensory input. Understanding how and where this modeling takes place is a core question in statistical learning and predictive processing. In this context, we address the role of transitional probabilities as an implicit structure supporting the encoding of a random auditory stream. Leveraging information-theoretical principles and the high spatiotemporal resolution of intracranial electroencephalography, we analyzed the trial-by-trial high-frequency activity representation of transitional probabilities. This unique approach enabled us to demonstrate how the brain continuously encodes structure in random stimuli and revealed the involvement of a network outside of the auditory system, including hippocampal, frontal, and temporal regions. Linking the frame-works of statistical learning and predictive processing, our work illuminates an implicit process that can be crucial for the swift detection of patterns and unexpected events in the environment.
Effect of Acetylene Black Content to Half Cells Li-ion Battery Performance Based on Li4Ti5O12 using Li2CO3 as Lithium Ion Source with Hydrothermal Mechanochemical Process

Lithium titanate (Li4Ti5O12)/LTO is a promising candidate to be used as anode electrode in Li-ion battery, to replace graphite in Li-ion battery application. Crystal structure of lithium titanate/LTO is more stable or undergoes less strain than graphite during intercalation and de-intercalation process Li+ ions. However, although lithium titanate has good stability, the material has low electrical conductivity and lithium ion diffusion. The purpose of this research is to synthesis the spinel LTO using combinated hydrothermal and mechanochemical processes from xerogel TiO2. Then, to increase the conductivity, in the half-cell battery assembly process it was added acetylene black conductive (AB) additive with various from 10%, to 15% in wt. The LTO obtained were characterized using scanning electron microscope (SEM), X-Ray Diffraction (XRD) and Brunauer–Emmett–Teller (BET). The XRD showed a rutile as minor phase, while SEM showed homogeneous distribution of particle with an average particle size of 0.35 μm. The BET showed that the surface area of LTO formed is 2.26 m2/g. The assembled coin half cells used this Li4Ti5O12 as a cathode and lithium metal foil as the anode were tested using electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and charge discharge (CD). The conductivity value obtained from EIS corresponds to the contents of AB. Meanwhile, the CV and CD testing showed that higher percentage of AB causing the decrease of battery specific capacity. The highest specific capacity at the rate of 10C is obtained at the mixture of 10wt% AB with the value of 40.91 mAh/g.
µ-Theraphotoxin Pn3a inhibition of CaV3.3 channels reveals a novel isoform-selective drug binding site

Low voltage-activated calcium currents are mediated by T-type calcium channels CaV3.1, CaV3.2, and CaV3.3, which modulate a variety of physiological processes including sleep, cardiac pace-making, pain, and epilepsy. CaV3 isoforms’ biophysical properties, overlapping expression and lack of subtype-selective pharmacology hinder the determination of their specific physiological roles in health and disease. Notably, CaV3.3’s contribution to normal and pathophysiological function has remained largely unexplored. We have identified Pn3a as the first subtype-selective spider venom peptide inhibitor of CaV3.3, with >100-fold lower potency against the other T-type isoforms. Pn3a modifies CaV3.3 gating through a depolarizing shift in the voltage dependence of activation thus decreasing CaV3.3-mediated currents in the normal range of activation potentials. Paddle chimeras of KV1.7 channels bearing voltage sensor sequences from all four CaV3.3 domains revealed preferential binding of Pn3a to the S3-S4 region of domain II (CaV3.3DII). This novel T-type channel pharmacological site was explored through computational docking simulations of Pn3a into all T-type channel isoforms highlighting it as subtype-specific pharmacophore with therapeutic potential. This research expands our understanding of T-type calcium channel pharmacology and supports the suitability of Pn3a as a molecular tool in the study of the physiological roles of CaV3.3 channels.