Miracle-dz/UniFAR-FTUs huggingface dataset:
Centralizing Place as Past(s), Present(s), Future(s): Hybridities of Literate Identities and Place in the Life of a Black Immigrant Scholar

Abstract:In this brief essay, the theory of place is used in conjunction with a Sankofan approach to highlight the ways in which place functioned as both material and experiential and influenced my situatedness as a literacy and language scholar, mother, and individual. Through this interconnection drawn from my time in community as a 2018 Literacy Research Association STAR Fellow, I demonstrate how the "hybridities of identities and places" influenced my decisions to navigate positivistic as well as interpretivist, critical, and pluralist epistemologies while I straddled qualitative and quantitative worlds. My resulting scholarship demonstrates how critical literacy theory came to undergird the challenges posed to monoglossic language ideology as I have advocated for heteroglossic norms and explored a raciolinguistic perspective in the racialized Englishes and literacies of Black (Caribbean) immigrant populations. Addressing perceptions that accompany the use of these Englishes across geographical, symbolic, and social borders through qualitative research, I illustrate why I also use quantitative methods to advocate for literacy instruction and assessment that acknowledges the intersecting influences of 'dialect', race, and culture in the literacies of Black immigrant multilingual youth. By engaging in this process, I demonstrate how my literacy research is largely intertwined with how I have engaged with the past and present to influence the future, thereby reflecting hybridities of literate identities and place. Implications for those who work with Black immigrants are provided.
PrimPol variant V102A with altered primase and polymerase activities

PrimPol is a human DNA primase-polymerase which restarts DNA synthesis beyond DNA lesions and non-B DNA structures blocking replication. Disfunction of PrimPol in cells leads to slowing of DNA replication rates in mitochondria and nucleus, accumulation of chromosome aberrations, cell cycle delay, elevated sensitivity to DNA-damaging agents. PrimPol has been suggested to be associated with the development of ophthalmic diseases, elevated mitochondrial toxicity of antiviral drugs and increased cell resistance to chemotherapy. Here, we describe a rare missense PrimPol variant V102A with altered biochemical properties identified in patients suffering from ovarian and cervical cancer. The Val102Ala substitution dramatically reduced both the primase and DNA polymerase activities of PrimPol as well as specifically decreased its ability to incorporate ribonucleotides. We suggest that substitutions in this region would likely distort the active site and affect the catalytic activity of PrimPol.
Body-Wave Extraction and Tomography at Long Beach, CA, with Ambient-Noise Interferometry

We retrieve diving P waves by applying seismic interferometry to ambient noise records observed at Long Beach, California, and invert travel times of these waves to estimate 3D P-wave velocity structure. The ambient noise is recorded by a dense and large network, which has about 2500 receivers with 100-m spacing. In contrast from the surface-wave extraction, bodywave extraction is much harder because body-wave energy is less than surface waves in this scale. For travel-time tomography, we need to extract body waves at each pair of receivers separately. Therefore, we employ two post-correlation filters to reject noisy signals (which are unusable for body-wave tomography). The first filter rejects traces base on low P-wave correlation with the stack of all traces at that distance. The second filter measures coherent energy between all retained traces and suppresses incoherent noise in each trace. With these filters, we can reconstruct clear body waves from each virtual source. Then we estimate 3D P-wave velocities from these waves with travel-time tomography. The velocities show high resolution structure.
A pgr5 suppressor screen uncovers a distinct mechanism safeguarding the cytochrome b6f complex from damage through PGR5

PROTON GRADIENT REGULATION5 (PGR5) is thought to promote cyclic electron flow (CEF) and its deficiency causes increased photosensitivity of photosystem I (PSI), leading to lethality under fluctuating light (FL). By screening for suppressor mutations that rescue FL lethality of pgr5 plants, we identified a portfolio of mutations affecting 12 photosynthesis-related proteins. Six are required for proper PSII function, one (CcdA) promotes cytochrome (cyt) b6f assembly, and another (PAA1) provides plastocyanin with its copper cofactor. Two other mutations are associated with the chloroplast FBPase cFBP1. This, together with targeted knockout of other genes in the pgr5 background, suggests three pathways to restore FL viability: (i) reduced electron flow to PSI due to defects in PSII, cyt b6f or plastocyanin but not PSI, (ii) increased electron flow from PSI due to inactivation of ACHT2, a regulator of cFBP1 activity, and (iii) hyperactivity of the NDH-dependent CEF due to inactivation of cFBP1. The remaining two suppressor mutations affected the cyt b6f complex. PFSC1 controls cyt b6f accumulation at early developmental stages. DEIP1/NTA1, previously suggested to be essential for cyt b6f assembly, appears to protect cyt b6f from deleterious effects of PGR5, since plants lacking both DEIP1/NTA1 and PGR5 are viable and accumulate cyt b6f.
“Is Taking a Bubble Bath Going to Make My Life Easier Tomorrow? Maybe Not!”

The author considers the context of COVID-19 as a catalyst for (re)thinking about how teacher educators might better teach preservice and early-career teachers’ need to attend to holistic wellness as part of their preparation and induction work. Using narrative inquiry, interviews with three early-career teachers were conducted and analyzed, and mental health and self-care were salient topics. This piece draws heavily from participants’ comments because their responses relate to work-life balance and stress management. Finally, there is a discussion about the need for teacher educators to explicitly address self-care as part of teacher preparation, as well as recommendations for how teacher educators might go about this work.
Scoring-Tool zu Identifizierung von Patienten mit erhöhtem Risiko für Arzneimittel-bezogene Probleme- Bericht einer Punkt-Prävalenzuntersuchung bei Aufnahme im Krankenhaus

Zusammenfassung Einleitung Die Arzneimitteltherapie wird als Hochrisiko-Prozess bezeichnet und bedarf besonderer Aufmerksamkeit, insbesondere an den Sektorengrenzen. Pharmazeutische Dienstleistungen wie zum Beispiel eine Medikationsanalyse sind geeignete Maßnahmen zur Verbesserung der Arzneimitteltherapiesicherheit. Sie sind wirksam bei der Erkennung und Behebung von Arzneimittel-bezogenen Problemen. Risiko-Scoring-Tools sind in der Literatur als hilfreiches Instrument zur priorisierten Medikationsanalyse von Patient:innen mit Risiko für Arzneimittel-bezogene Probleme beschrieben. Methodik In einer Punkt-Prävalenzuntersuchung wurde unter Anwendung eines Medikationsrisiko-Tools der Anteil der Patient:innen mit einem erhöhten Risiko für Arzneimittel-bezogene Probleme bei Aufnahme ins Krankenhaus multizentrisch erfasst. Darüber hinaus wurde das Angebot pharmazeutischer Dienstleistungen durch die Krankenhausapotheken ermittelt. Ergebnisse Insgesamt haben sich 11 (58%; 11/19) Krankenhausapotheken in Sachsen an der Punkt-Prävalenzuntersuchung beteiligt. Es wurden 875 Patient:innen eingeschlossen. Bei 32% (279/875) der Patient:innen wurde ein erhöhtes Risiko für Arzneimittel-bezogene Probleme mittels Scoring-Tool (Meris-Score >12-Gruppe) ermittelt. Dabei betrug die Anzahl der Arzneistoffe in der Meris-Score >12-Gruppe 10,6 (Mittelwert; Standardabweichung 3,5; n=279), in der Meris-Score ≤12-Gruppe waren es nur fünf Arzneimittel pro Patient:in (Mittelwert 4,6; Standardabweichung 2,8; n=596). Das Alter der Patient:innen in der Meris-Score >12-Gruppe betrug im Mittel 75,9 ± 11 Jahre, während das Alter der Patient:innen in der Meris-Score ≤12-Gruppe im Mittel 60,6 ± 17,9 Jahre betrug. Diskussion Die Priorisierung mit Hilfe eines Scoring-Tools erschient bei den derzeit noch nicht regelhaft etablierten pharmazeutischen Dienstleistungen in sächsischen Krankenhäusern besonders wichtig, um Patient:innen mit einem erhöhten Risiko für Arzneimittel-bezogene Probleme frühzeitig zu identifizieren.
Adversarial Doodles: Interpretable and Human-drawable Attacks Provide Describable Insights

DNN-based image classification models are susceptible to adversarial attacks. Most previous adversarial attacks do not focus on the interpretability of the generated adversarial examples, and we cannot gain insights into the mechanism of the target classifier from the attacks. Therefore, we propose Adversarial Doodles, which have interpretable shapes. We optimize black b\'ezier curves to fool the target classifier by overlaying them onto the input image. By introducing random perspective transformation and regularizing the doodled area, we obtain compact attacks that cause misclassification even when humans replicate them by hand. Adversarial doodles provide describable and intriguing insights into the relationship between our attacks and the classifier's output. We utilize adversarial doodles and discover the bias inherent in the target classifier, such as"We add two strokes on its head, a triangle onto its body, and two lines inside the triangle on a bird image. Then, the classifier misclassifies the image as a butterfly. "
An Eye-Tracking Study on Viewer Compliance with the Gestalt Closure Principle: Analyzing the Impact of Gap Size and the Golden Ratio

Abstract The Gestalt principle of closure refers to brain activity filling in missing information to perceive objects as complete, even when partially hidden. Designers leverage this principle to imply shapes without explicitly showing them. However, evaluating viewer responses poses challenges. The author conducted a comprehensive eye-tracking experiment to determine when viewers mentally completed a gap in a circle and explored the potential influence of the golden ratio on the closure principle. The golden ratio, approximately 1.618, is associated with visual harmony and is used in art and design to create pleasing proportions. Findings showed that viewers tend to mentally close gaps up to 135° but avoid closure beyond 150°. This suggests the golden ratio’s relevance in applying the closure principle to design.
Optimized automatic pickers: application to the ANCORP data set

SUMMARY It has become increasingly important to develop fast and accurate automatic procedures to process and fully exploit increasing large seismic data sets. Traditionally these data sets are processed manually, which requires significant amounts of both manpower and time with sometimes-variable results. We have developed a cost minimization approach to train three automatic pickers: an Sta/Lta, Tpd and the PAI-K picker at each station within a dense temporary network located in northern Chile and southern Bolivia. The optimum picking parameters for each station show regional variability and need to be adjusted individually to achieve the best performance. We developed a weighting scheme that uses four independent predictors of weight calibrated using a handpicked data subset, which mimics the picking by an expert seismologist. We use the fact that each of the three pickers highlights different properties of the observed seismic trace to combine two pickers that work in tandem. The first makes an initial pick before the second picker refines and improves the accuracy of the automatic pick. We find the tandem pickers improve the accuracy of the automatic picks when compared to the single automatic pickers. We demonstrate that following the cost minimization procedure described here the automatic picks have sufficient accuracy that they would be suitable for high-precision earthquake location, focal mechanism determination or high-resolution seismic tomography.
Colorful Electrotactile Feedback on the Wrist

Providing rich feedback on small devices, like smartwatches, can be difficult. We propose colorful electrotactile feedback on the back of a smartwatch. Colorful electrotactile feedback provides private notifications, is energy efficient, and can express various sensations in different qualities. In a first study, 13 participants explored 49 different combinations of frequency and pulse width regarding the perceived “colorfulness” of electrotactile feedback. We investigated what sensations can be expressed with electrotactile feedback and which qualities of these sensations are conveyed. To describe the sensations, participants chose the best fitting terms from a list of 21 terms. The three most frequently selected terms were prickling (177), vibrating (163), and irritating (112). The three least frequently selected ones were twitching (31), tickling (29), and itching (28). In a second study with 17 participants we evaluated a reduced set of 9 sensations that we selected and refined based on the results of study 1. We evaluated these sensations regarding recognition rates and achieved recognition rates of up to 84% without prior learning. Furthermore, we investigated the acceptance of colorful electrotactile feedback and present a method for an easier and faster calibration of electrotactile feedback.
Dynamic Weighted Adversarial Learning for Semi-Supervised Classification under Intersectional Class Mismatch

Nowadays, class-mismatch problem has drawn intensive attention in Semi-Supervised Learning (SSL), where the classes of labeled data are assumed to be only a subset of the classes of unlabeled data. However, in a more realistic scenario, the labeled data and unlabeled data often share some common classes while they also have their individual classes, which leads to an “intersectional class-mismatch” problem. As a result, existing SSL methods are often confused by these individual classes and suffer from performance degradation. To address this problem, we propose a novel Dynamic Weighted Adversarial Learning (DWAL) framework to properly utilize unlabeled data for boosting the SSL performance. Specifically, to handle the influence of the individual classes in unlabeled data (i.e., Out-Of-Distribution classes), we propose an enhanced adversarial domain adaptation to dynamically assign weight for each unlabeled example from the perspectives of domain adaptation and a class-wise weighting mechanism, which consists of transferability score and prediction confidence value. Besides, to handle the influence of the individual classes in labeled data (i.e., private classes), we propose a dissimilarity maximization strategy to suppress the inaccurate correlations caused by the examples of individual classes within labeled data. Therefore, our DWAL can properly make use of unlabeled data to acquire an accurate SSL classifier under intersectional class-mismatch setting, and extensive experimental results on five public datasets demonstrate the effectiveness of the proposed model over other state-of-the-art SSL methods.
The Dynamics of Web-Based Community Safety Groups: Lessons Learned from the Nation of Neighbors [Social Sciences]

Online social networks targeted toward national priorities such as disaster planning, crime watch, or food safety are increasingly described in research studies. A central research challenge is to understand the determinants of the successful growth of such communities. The use of a visual analytics tool would guide the community managers to understand their dynamics. To study this, we used data from the Nation of Neighbors (NON) [11], which is a platform for online neighborhood crime watch communities of residents and law enforcement officers to interact over the shared goals of preventing crime and strengthening communities. The members and law enforcement jurisdiction can add their community to NON; report crime or other incidents in their communities; participate in community discussion; share news, photos, or documents; and manage upcoming events. The system sends real-time e-mail or text message alerts to the community members.
SourcererJBF: A Java Build Framework For Large-Scale Compilation

Researchers and tool developers working on dynamic analysis, software testing, automated program repair, verification, and validation, need large compiled, compilable, and executable code corpora to test their ideas. The publicly available corpora are relatively small, and/or non-compilable, and/or non-executable. Developing a compiled code corpus is a laborious activity demanding significant manual effort and human intervention. To facilitate large-scale program analysis research, we develop SourcererJBF, a Java Build Framework that can automatically build a large Java code corpus without project-specific instructions and human intervention. To generate a compiled code corpus, SourcererJBF creates an offline knowledge base by collecting external dependencies from the project directories and existing build scripts (if available). It constructs indices of those collected external dependencies that enable a fast search for resolving dependencies during the project compilation. As the output of the large-scale compilation, it produces JAigantic, a compilable Java corpus containing compiled projects, their bytecode, dependencies, normalized build script, and build command. We evaluated SourcererJBF’s effectiveness, correctness, performance, and scalability in a large collection of Java projects. Our experimental results demonstrate that SourcererJBF is significantly effective and scalable in building large Java code corpus. Besides, it substantiates reasonable performance and correctness similar to projects’ existing build systems.
A Comparative Analysis of Preferred Communication Options of Passengers in Networked Shared Automated Vehicles

The introduction of automated mobility will lead to new forms of interaction with vehicles. Exactly how this interaction will occur, particularly in coordinating connected vehicles, is largely unexplored. We investigated whether a built-in system that directly combines a messenger function with the route change function is better for destination coordination among multiple vehicles than traditional messenger apps on the smartphone. We conducted a user study with N = 17 participants who experienced a simulated ride in a low-fidelity prototype of a shared automated vehicle (SAV). Each participant tested both interaction options with imaginary passengers in a connected SAV. Results showed a high usability for both solutions. However, the qualitative interview data showed participants preferred communication via the built-in messenger system. The simple and clear operation of the holistic concept was particularly emphasized, while concerns were expressed about privacy and hygiene.
Content Moderation Folk Theories And Perceptions of Platform Spirit Among Marginalized Social Media Users

Social media users create folk theories to help explain how elements of social media operate. Marginalized social media users face disproportionate content moderation and removal on social media platforms. We conducted a qualitative interview study (n = 24) to understand how marginalized social media users may create folk theories in response to content moderation and their perceptions of platforms’ spirit, and how these theories may relate to their marginalized identities. We found that marginalized social media users develop folk theories informed by their perceptions of platforms’ spirit to explain instances where their content was moderated in ways that violate their perceptions of how content moderation should work in practice. These folk theories typically address content being removed despite not violating community guidelines, along with bias against marginalized users embedded in guidelines. We provide implications for platforms, such as using marginalized users’ folk theories as tools to identify elements of platform moderation systems that function incorrectly and disproportionately impact marginalized users.
Training examples : inputs + outputs algorithm model New inputs New outputs Training Running

Model evaluation plays a special role in interactive machine learning (IML) systems in which users rely on their assessment of a model’s performance in order to determine how to improve it. A better understanding of what model criteria are important to users can therefore inform the design of user interfaces for model evaluation as well as the choice and design of learning algorithms. We present work studying the evaluation practices of end users interactively building supervised learning systems for real-world gesture analysis problems. We examine users’ model evaluation criteria, which span conventionally relevant criteria such as accuracy and cost, as well as novel criteria such as unexpectedness. We observed that users employed evaluation techniques— including cross-validation and direct, real-time evaluation— not only to make relevant judgments of algorithms’ performance and interactively improve the trained models, but also to learn to provide more effective training data. Furthermore, we observed that evaluation taught users about what types of models were easy or possible to build, and users sometimes used this information to modify the learning problem definition or their plans for using the trained models in practice. We discuss the implications of these findings with regard to the role of generalization accuracy in IML, the design of new algorithms and interfaces, and the scope of potential benefits of incorporating human interaction in the design of supervised learning systems.
A First Look at the Language of Kundal Shahi in Azad Kashmir

This paper presents some preliminary notes on the previously undescribed Indo-Aryan language of Kundal Shahi, a village in Pakistani-administered Kashmir. We present data from which it appears that the Kundal Shahi language must have descended from an archaic form of Shina, while showing more recent influences from Kashmiri and Hindko in particular. It is not mutually intelligible with any of these languages. Like many other languages in the northwestern corner of the South-Asian subcontinent, Kundal Shahi has contrastive tone. With less than 500 active speakers, most of whom are over 40 years of age, the language is definitely endangered.
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This paper describes CDSOLT, a protocol which optimizes LT code to increase the throughput of flooding in ad hoc wireless network. We propose to apply on each hop and locally XOR operation over encoded packets in decoding process, so that more native packets could be discovered and avoid hence a break in the decoding process. Encoding also can be applied with both received singletons (native packets) and non-singletons, and generated candidates can be used in optimization criteria or in LT coding as random encoded packet from selected number of native packets. The efficiency of network coding is further enhanced by applying source independent backbones. As shown in our simulation, CDSOLT reduces number of transmissions by making use of more computations at nodes. Intermediate nodes may either forward packets without changes over few disjoint routes, or could also apply same algorithm to produce novel encoded packets and assist destination.