Surface-level Features Research Articles

There Is no Universal Standard of Beauty.

This article discusses the various factors that contribute to facial beauty and the different contexts in which they are significant. The authors examine the roles of the golden ratio, ideal proportions, symmetry, and specific facial features in what constitutes an attractive face. They also investigate the influence of cultural and evolutionary perspectives on facial beauty and the impact of social media on our perception of beauty. The article provides a comprehensive overview of the topic and emphasises the significance of facial beauty and its impact on our lives. The authors acknowledge that the concept of beauty is difficult to define with absolute precision, and that the objective-subjective argument regarding facial beauty remains unsolved. However, they argue that physical attributes undoubtedly influence perceptions of attractiveness, but beauty extends beyond surface-level features. They also suggest that embracing diversity in beauty standards fosters a more inclusive society that celebrates the unique qualities of every person.Level of Evidence V This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Cultural Tailoring and Targeting of Messages: A Systematic Literature Review

ABSTRACT Cultural targeting and tailoring are different, yet they remain intertwined in the literature inhibiting theory development and limiting the possibility of determining their effects. This preregistered systematic literature review describes these constructs and provides a framework for cultural tailoring with evidence from a review of 63 studies, published from 2010 to 2020, to characterize the processes, elements, and theories used in the existing literature. The results show that 86% of studies self-defined as cultural tailoring, but coding revealed relatively few tailoring studies (25%) with 31% including both tailoring and targeting elements. Most studies used outreach and consultation as processes for tailoring or targeting with participatory approaches used in a fifth of the studies. Surface-level features of message content were commonly used to tailor or target with deep-cultural-values found in only a quarter of the studies. We argue from theories of communication accommodation and persuasion that cultural tailoring or targeting may provide gains in attention, recall, or source evaluation.

Examining the role of assignment design and peer review on student responses and revisions to an organic chemistry writing-to-learn assignment

Research on student learning in organic chemistry indicates that students tend to focus on surface level features of molecules with less consideration of implicit properties when engaging in mechanistic reasoning. Writing-to-learn (WTL) is one approach for supporting students’ mechanistic reasoning. A variation of WTL incorporates peer review and revision to provide opportunities for students to interact with and learn from their peers, as well as revisit and reflect on their own knowledge and reasoning. However, research indicates that the rhetorical features included in WTL assignments may influence the language students use in their responses. This study utilizes machine learning to characterize the mechanistic features present in second-semester undergraduate organic chemistry students’ responses to two versions of a WTL assignment with different rhetorical features. Furthermore, we examine the role of peer review on the mechanistic reasoning captured in students’ revised drafts. Our analysis indicates that students include both surface level and implicit features of mechanistic reasoning in their drafts and in the feedback to their peers, with slight differences depending on the rhetorical features present in the assignment. However, students’ revisions appeared to be primarily connected to the peer review process via the presence of surface features in the drafts students read (as opposed to the feedback received). These findings indicate that further scaffolding focused on how to utilize information gained from the peer review process (i.e., both feedback received and drafts read) and emphasizing implicit properties could help support the utility of WTL for developing students’ mechanistic reasoning in organic chemistry.

Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Text

Evaluation practices in natural language generation (NLG) have many known flaws, but improved evaluation approaches are rarely widely adopted. This issue has become more urgent, since neural generation models have improved to the point where their outputs can often no longer be distinguished based on the surface-level features that older metrics rely on. This paper surveys the issues with human and automatic model evaluations and with commonly used datasets in NLG that have been pointed out over the past 20 years. We summarize, categorize, and discuss how researchers have been addressing these issues and what their findings mean for the current state of model evaluations. Building on those insights, we lay out a long-term vision for evaluation research and propose concrete steps for researchers to improve their evaluation processes. Finally, we analyze 66 generation papers from recent NLP conferences in how well they already follow these suggestions and identify which areas require more drastic changes to the status quo.

Ab initio prediction and characterization of membrane binding of HIV-1 broadly neutralizing antibodies by multi-scale simulations.

Rare but potent broadly neutralizing antibodies (bnAbs) engage the HIV virion membrane and the membrane proximal exposed region (MPER) peptide during neutralization. A preliminary lipid mediated binding step is suggested to increase antigen avidity but it remains unclear how initial membrane association occurs and thus what features are essential to mature bnAbs against a lipid-antigen epitope. In this study, we derived computational methods to investigate biophysical features of MPER bnAbs driving membrane association. We performed microsecond atomistic simulations of Fabs docked in a lipid bilayer. Phospholipid binding in CDR loops is predicted in all 4 replicates of PGZL1, 4E10 and 10E8 where a phospholipid headgroup position closely matches the phosphate position in lipid-soaked x-ray crystallography structures (mean RMSD 0.6, 0.7, 2.7 Å respectively). Interaction profiles also highlight how framework regions FRH3 (PGZL1 and 4E10) or FRL3 (10E8) significantly associate with lipids. We then conducted fixed velocity pulling simulations for 4E10 and mutants with reduced affinity for lipid vesicles in vitro. Max force calculates differences in energy required to dissociate Fabs, establishing a bona fide tool to approximate membrane affinities. We expanded this platform to track evolution of binding affinity with inferred germline, intermediate, and mature PGZL1 variants that show increasing binding strengths. To reduce bias from pre-docked membrane conformations, we generated coarse grained models with a Fab initiated above a bilayer. Spontaneous membrane binding events (>1 µs) are detected in over half of the 18 independent 14 µs bnAb trajectories but only in 2 of 18 replicates for negative control BSA. Altogether we present a computational toolkit to biophysically evaluate residue-specific and surface level features of membrane binding antibodies and differentiate membrane affinities, facilitating future studies of complete MPER or other auto-reactive bnAb maturation pathways.

A Queer Way of Counting: Bibliography and Computational Approaches to the Queer Novel

The relationship of queer studies to literary text mining has been vexed by the latter's formative interest in large scales, clear categories and general trends, all at odds with queer investment in particulars, details, and persons and objects who resist normative patterns and labels. The history of queer bibliography, especially as embodied by early work such as Jeanette Foster's Sex Variant Women in Literature (1956) and Roger Austen's Playing the Game: the Homosexual Novel in America (1977), however, presents a compelling model for a kind of queer enumeration which is community-oriented rather than externally imposed, centered first and foremost on the task of guiding readers to new queer texts, and which is affectively invested in the task of counting itself: a kind of literary engagement that shows the queer potential of the question "how many?" Using a small corpus of queer novels derived from modern lists of book recommendations—a contemporary form of queer bibliography—I show that, while many kinds of textual queerness elude currently existing computational methods, these methods are nonetheless capable of identifying a variety of queer textual traces, both in queer fiction identified as such, and in presumptively straight novels. While future work in this area will ultimately require more sophisticated methods, these already extant tools offer scholars of queer literature an intriguing focus on surface-level features such as explicit terms of sexual identity—and the work of bibliographers such as Foster and Austen offers the theoretical foundations that new methods must be based upon.

Identification of defective weld and quality monitoring in manual metal arc welding process using surface level image features

The current research work is the demonstration of the development of a monitoring methodology for the identification of defective weld using surface-level features. A novel grey level-based indicator has been proposed in this research work that has the potential to identify defective welds. The proposed methodology has been validated with a well-established 2D wavelet transform framework to prove the capacity of the proposed methodology. In comparison to the wavelet transform the proposed methodology has been found to be more successful and computationally efficient with less a priori knowledge and limited pre-processing steps making it more effective. In this framework extracted image features along with the process parameters are used as the input to the support vector machine-based regression model for the prediction of the ultimate tensile strength of the welds. It is observed that the model yields an average absolute percentage error of 2.83% compared to the model developed only with process parameters that yield an error of 5.09%. The improvement in the prediction capability of the model leads to the impression that the proposed methodology is effective. The methodology can be used in human free automation system for monitoring of manual metal arc welding process.

Feature based Entailment Recognition for Malayalam Language Texts

Textual entailment is a relationship between two text fragments, namely, text/premise and hypothesis. It has applications in question answering systems, multi-document sum-marization, information retrieval systems, and social network analysis. In the era of the digital world, recognizing semantic variability is important in understanding inferences in texts. The texts are either in the form of sentences, posts, tweets, or user experiences. Hence understanding inferences from customer experiences helps companies in customer segmentation. The availability of digital information is ever-growing with textual data in almost all languages, including low resource languages. This work deals with various machine learning approaches applied to textual entailment recognition or natural language inference for Malayalam, a South Indian low resource language. A performance-based analysis using machine learning classification techniques such as Logistic Regression, Decision Tree, Support Vector Machine, Random Forest, AdaBoost, and Naive Bayes is done for the MaNLI (Malayalam Natural Language Inference) dataset. Different lexical and surface-level features are used for this binary and multiclass classification. With the increasing size of the dataset, there is a drop in the performance of feature-based classification. A comparison of feature-based models with deep learning approaches highlights this inference. The main focus here is the feature-based analysis with 14 different features and its comparison, essential to any NLP classification problem.

Arabic Diacritic Recovery Using a Feature-rich biLSTM Model

Diacritics (short vowels) are typically omitted when writing Arabic text, and readers have to reintroduce them to correctly pronounce words. There are two types of Arabic diacritics: The first are core-word diacritics (CW), which specify the lexical selection, and the second are case endings (CE), which typically appear at the end of word stems and generally specify their syntactic roles. Recovering CEs is relatively harder than recovering core-word diacritics due to inter-word dependencies, which are often distant. In this article, we use feature-rich recurrent neural network model that use a variety of linguistic and surface-level features to recover both core word diacritics and case endings. Our model surpasses all previous state-of-the-art systems with a CW error rate (CWER) of 2.9% and a CE error rate (CEER) of 3.7% for Modern Standard Arabic (MSA) and CWER of 2.2% and CEER of 2.5% for Classical Arabic (CA). When combining diacritized word cores with case endings, the resultant word error rates are 6.0% and 4.3% for MSA and CA, respectively. This highlights the effectiveness of feature engineering for such deep neural models.

Complete Binary Representation for 3-D Palmprint Recognition

3-D palmprint recognition has attracted a wide range of attentions due to its potential for civilian applications. Designing an effective representation is a key problem for the 3-D palmprint recognition. In this paper, we propose a complete binary representation (CBR) for the 3-D palmprint multiple-dimensional feature representation and recognition. First, we propose a multiple orientation binary representation (MOBR) to extract 2-D gray-level features of 3-D palmprint. Then, we propose a novel and effective compact surface type (CST) to characterize 3-D palmprint surface feature, and design a CST binary representation (CSTBR) to capture the surface consistency within a local patch. Finally, we develop a CBR method by integrating the MOBR and CSTBR, which can effectively represent both 2-D orientation-level and 3-D surface-level features of 3-D palmprint images. We conduct extensive intercomparison experiments to demonstrate the effectiveness of the proposed CBR method on a benchmark 3-D palmprint database. Also, we carry out multiple intracomparisons to validate the superiority of the MOBR- and CST-based representations.

The ETCBC Database of the Hebrew Bible

We provide a brief introduction to the history, methodology, and tools of the Eep Talstra Centre for Bible and Computer (ETCBC). The ETCBC maintains a searchable database of morphology, syntax, and text-level features for the Hebrew Bible, Hebrew inscriptions, Dead Sea Scrolls, the Peshitta, and one of the Targumim. The ETCBC follows a form-to-function approach, in which surface-level features are registered first and functional labels second. Linguists and exegetes can use the database’s freely accessible query tools for pattern searches and analysis of the text’s structure to address their research questions

Readability Analysis of Bengali Literary Texts

ABSTRACTIn this paper we propose a set of novel regression models for readability scoring in Bengali language, which can also be used for Hindi, making use of several lexical, surface-level, syntactic and semantic features. We perform 5-fold and leave-one-out cross-validation on a human-annotated gold standard dataset of 30 passages, written by 4 eminent Bengali litterateurs. On this dataset, our best model achieves a mean squared error (MSE) of 57%, which is better than state-of-the-art results (73% MSE). We further perform feature analysis to identify potentially useful features in learning a regression model for Bengali readability. Ablation studies indicate the importance of compound characters (Juktakkhors) in readability assessment.

When 2 × 4 is meaningful: the N400 and P300 reveal operand format effects in multiplication verification.

Arithmetic problems share many surface-level features with typical sentences. They assert information about the world, and readers can evaluate this information for sensibility by consulting their memories as the statement unfolds. When people encounter the solution to the problem 3 × 4, the brain elicits a robust ERP effect as a function of answer expectancy (12 being the expected completion; 15 being unexpected). Initially, this was labeled an N400 effect, implying that semantic memory had been accessed. Subsequent work suggested instead that the effect was driven by a target P300 to the correct solutions. The current study manipulates operand format to differentially promote access to language-based semantic representations of arithmetic. Operands were presented either as spoken number words or as sequential Arabic numerals. The critical solution was always an Arabic numeral. In Experiment 1, the correctness of solutions preceded by spoken operands modulated N400 amplitude, whereas solutions preceded by Arabic numerals elicited a P300 for correct problems. In Experiment 2, using only spoken operands, the delay between the second operand and the Arabic numeral solution was manipulated to determine if additional processing time would result in a P300. With a longer delay, an earlier N400 and no distinct P300 were observed. In brief, highly familiar digit operands promoted target detection, whereas spoken numbers promoted semantic level processing-even when solution format itself was held constant. This provides evidence that the brain can process arithmetic fact information at different levels of representational meaningfulness as a function of symbolic format.

Orienting to see what's important: Learn to ignore the irrelevant.

The current study used a triad judgment task to assess whether blocking by comparison type in a triad judgment task could lead people to pay less attention to surface-level (irrelevant) features and pay more attention to deep (structural) features of information. A sample of 313 participants recruited through Mechanical Turk participated in this study. On each triad, participants were asked to evaluate which of two source scenarios went best with the target scenario. Three types of triads were constructed with materials related to the ability to perceive ethical issues within the practice of psychology. One type of triad contrasted a scenario that was similar to the target in terms of surface-level features and a scenario that was similar in terms of deep features (similar surface-similar deep, SS/SD). A second triad type contrasted a scenario that was similar in terms of deep features with an unrelated scenario (similar deep-unrelated, SD/U). The third contrasted a scenario that was similar in terms of surface features with an unrelated scenario (similar surface-unrelated, SS/U). There were 10 triads of each type. We found that with all the blocking orders except two, participants reliably chose the SS scenario over the SD scenario for the SS/SD triads. However, participants who started out with the SD/U triads did not. The results provide evidence that people often have the ability to perceive the deep, but they are distracted by the surface-level features. The results also show that people can be oriented away from being distracted by the surface-level features so that they can see the deep.

Infant differential behavioral responding to discrete emotions.

Emotional communication regulates the behaviors of social partners. Research on individuals' responding to others' emotions typically compares responses to a single negative emotion compared with responses to a neutral or positive emotion. Furthermore, coding of such responses routinely measure surface level features of the behavior (e.g., approach vs. avoidance) rather than its underlying function (e.g., the goal of the approach or avoidant behavior). This investigation examined infants' responding to others' emotional displays across 5 discrete emotions: joy, sadness, fear, anger, and disgust. Specifically, 16-, 19-, and 24-month-old infants observed an adult communicate a discrete emotion toward a stimulus during a naturalistic interaction. Infants' responses were coded to capture the function of their behaviors (e.g., exploration, prosocial behavior, and security seeking). The results revealed a number of instances indicating that infants use different functional behaviors in response to discrete emotions. Differences in behaviors across emotions were clearest in the 24-month-old infants, though younger infants also demonstrated some differential use of behaviors in response to discrete emotions. This is the first comprehensive study to identify differences in how infants respond with goal-directed behaviors to discrete emotions. Additionally, the inclusion of a function-based coding scheme and interpersonal paradigms may be informative for future emotion research with children and adults. Possible developmental accounts for the observed behaviors and the benefits of coding techniques emphasizing the function of social behavior over their form are discussed. (PsycINFO Database Record

Moving Beyond Pseudoargumentation: Teachers’ Enactments of an Educative Science Curriculum Focused on Argumentation

ABSTRACTArgumentation, a key epistemic practice in science, engages students in socially constructing knowledge claims using evidence. However, teachers need support in integrating argumentation into classroom instruction. We examined teachers’ enactments of an educative science curriculum and their curricular decision making for argumentation. Ten middle school teachers enacted lessons that focused on both the structure of an argument and argumentation as a dialogic process. For each teacher, we analyzed videotapes of two lessons and follow‐up interviews. Across the teachers, we observed a wide range in teachers’ enactments. In some instances, teachers’ instructional practices aligned with the underlying epistemic goals, while in other cases the structural aspects were oversimplified and discourse norms followed more traditional teacher‐led patterns. To support classroom instruction to move beyond pseudoargumentation, we found three main influences on teachers’ curricular decision making in classes with higher quality argumentation: (1) teachers’ understanding of argumentation as an epistemic practice (rather than surface level features), (2) teachers as critically reflective curriculum users, and (3) teachers problematizing their prior teaching experiences. As a field, we need to think critically about how to design teacher education experiences to discourage the relabeling of teaching with reform‐oriented terms, such as argumentation, and instead support instructional transformation.

Query-oriented evidence extraction to support evidence-based medicine practice

BackgroundEvidence-based medicine practice requires medical practitioners to rely on the best available evidence, in addition to their expertise, when making clinical decisions. The medical domain boasts a large amount of published medical research data, indexed in various medical databases such as MEDLINE. As the size of this data grows, practitioners increasingly face the problem of information overload, and past research has established the time-associated obstacles faced by evidence-based medicine practitioners. In this paper, we focus on the problem of automatic text summarisation to help practitioners quickly find query-focused information from relevant documents. MethodsWe utilise an annotated corpus that is specialised for the task of evidence-based summarisation of text. In contrast to past summarisation approaches, which mostly rely on surface level features to identify salient pieces of texts that form the summaries, our approach focuses on the use of corpus-based statistics, and domain-specific lexical knowledge for the identification of summary contents. We also apply a target-sentence-specific summarisation technique that reduces the problem of underfitting that persists in generic summarisation models. ResultsIn automatic evaluations run over a large number of annotated summaries, our extractive summarisation technique statistically outperforms various baseline and benchmark summarisation models with a percentile rank of 96.8%. A manual evaluation shows that our extractive summarisation approach is capable of selecting content with high recall and precision, and may thus be used to generate bottom-line answers to practitioners’ queries. ConclusionsOur research shows that the incorporation of specialised data and domain-specific knowledge can significantly improve text summarisation performance in the medical domain. Due to the vast amounts of medical text available, and the high growth of this form of data, we suspect that such summarisation techniques will address the time-related obstacles associated with evidence-based medicine.

Assessing Student Writing on Tablets

There is increasing expectation that schools should be able to use tablets for a range of instructional and assessment purposes. This article considers the comparability of student writing on tablets and laptops to ensure that writing assessment is conducted in a way that is fair to all students. Data were collected from a sample of 826 students from Virginia and South Dakota at 2 grade levels. Each student was provided with a laptop, a tablet, or a tablet with an external keyboard and asked to respond to a grade-level-appropriate essay prompt. Results indicated no difference in the essay score or surface-level essay features across study conditions. However, the relatively short length of essays written, the fact that reference materials were not required to respond to the essay prompts, and the general motivational level of student participants were likely contributing factors to the observed outcomes.

Pedagogical content knowledge of argumentation: Using classroom contexts to assess high‐quality PCK rather than pseudoargumentation

AbstractDespite the recent emphasis on science practices, little work has focused on teachers' knowledge of these key learning goals. The development of high quality assessments for teachers' pedagogical content knowledge (PCK) of science practices, such as argumentation, is important to better assess the needs of teachers and to develop supportive teacher education experiences. In this paper, we present lessons learned from a development process to conceptualize, design, and pilot a measure of teachers' PCK of argumentation. We use the results from our pilot test with 103 middle school science teachers, cognitive interviews with 24 middle school science teachers, and feedback from 10 advisors to present these lessons learned. Specifically, this work resulted in the refinement of our conceptualization of PCK of argumentation in two areas: (1) Moving beyond pseudoargumentation of surface level features to target the quality of structural components and students' dialogic interactions as well as the use of instructional strategies that align with student needs and (2) Focusing on dialogic argumentation in terms of the quality of student interactions in which they build off of and critique each others' claims, rather than goals such as persuasion that are difficult to observe. In addition, the iterative design process suggested that PCK of argumentation assessments should use classroom contexts (such as vignettes, student writing, and video) to activate teachers' knowledge in use by connecting to their prior experiences; however, the student argumentation examples need to highlight one specific strength or challenge and provide sufficient detail around the example to focus the assessment item. © 2015 Wiley Periodicals, Inc. J Res Sci Teach 53: 261–290, 2016.

Sperm Nuclear Vacuoles Do Not Influence Cellular Architecture

Recent literature has demonstrated that high-power evaluation of sperm vacuoles may aid in the identification of embryos capable of developing into blastocysts with ICSI (1). However, there is evidence that sperm vacuole assessment has little diagnostic and prognostic value when assessing the infertile couple (2). We sought to investigate whether vacuoles are optical artifacts, surface irregularities or true intracellular defects and to evaluate the correlation between the appearance of sperm vacuoles on high magnification light microscopy with ultra-structural alterations that may cause their appearance. Sperm cell assessment for morphological analysis was carried out on motile sperm under upright microscopy at 1000X or following magnification at 6000X under inverted microscopy. Aliquots of semen samples were fixed using standard electron microscopy solutions and were processed for scanning electron microscopy (SEM) as well as transmission electron microscopy (TEM). One hundred spermatozoa were imaged using each technique at 25-30,000X. Spermatozoa were subsequently analyzed using focused ion beam scanning electron microscopy (FIB-SEM). Structures consistent with described vacuoles were noted under both upright and inverted microscopy. SEM was unable to locate vacuoles; there were no discrete concave or convex surface features although numerous linear surface irregularities such as trenches and ridges were noted. TEM frequently identified non-membrane-bound regions that were enveloped by the nucleus and contained within the nuclear DNA. FIB-SEM was able to characterize the three-dimensional relationship between these structures, the surrounding nuclear DNA, and surface irregularities. Surface-level features such as ridges/trenches are ubiquitous; their appearance is affected by the imaging modality and the spatial orientation of the sperm at the time of the analysis. Multidimensional ultrastructural analysis was able to identify non-membrane-bound regions within the nucleus. While these areas may resemble space-occupying lesions, the sperm surfaces surrounding these structures do not appear to be affected; there is no evidence of alterations in organellar organization, cellular architecture or acrosomal conformation. As such, it is plausible that vacuoles are neither pathologic nor pathognomonic and instead are a physiologic byproduct of sperm maturation.