Blind Guess Research Articles

Annotation-free prediction of microbial dioxygen utilization.

Aerobes require dioxygen (O2) to grow; anaerobes do not. However, nearly all microbes-aerobes, anaerobes, and facultative organisms alike-express enzymes whose substrates include O2, if only for detoxification. This presents a challenge when trying to assess which organisms are aerobic from genomic data alone. This challenge can be overcome by noting that O2 utilization has wide-ranging effects on microbes: aerobes typically have larger genomes encoding distinctive O2-utilizing enzymes, for example. These effects permit high-quality prediction of O2 utilization from annotated genome sequences, with several models displaying ≈80% accuracy on a ternary classification task for which blind guessing is only 33% accurate. Since genome annotation is compute-intensive and relies on many assumptions, we asked if annotation-free methods also perform well. We discovered that simple and efficient models based entirely on genomic sequence content-e.g., triplets of amino acids-perform as well as intensive annotation-based classifiers, enabling rapid processing of genomes. We further show that amino acid trimers are useful because they encode information about protein composition and phylogeny. To showcase the utility of rapid prediction, we estimated the prevalence of aerobes and anaerobes in diverse natural environments cataloged in the Earth Microbiome Project. Focusing on a well-studied O2 gradient in the Black Sea, we found quantitative correspondence between local chemistry (O2:sulfide concentration ratio) and the composition of microbial communities. We, therefore, suggest that statistical methods like ours might be used to estimate, or "sense," pivotal features of the chemical environment using DNA sequencing data.IMPORTANCEWe now have access to sequence data from a wide variety of natural environments. These data document a bewildering diversity of microbes, many known only from their genomes. Physiology-an organism's capacity to engage metabolically with its environment-may provide a more useful lens than taxonomy for understanding microbial communities. As an example of this broader principle, we developed algorithms that accurately predict microbial dioxygen utilization directly from genome sequences without annotating genes, e.g., by considering only the amino acids in protein sequences. Annotation-free algorithms enable rapid characterization of natural samples, highlighting quantitative correspondence between sequences and local O2 levels in a data set from the Black Sea. This example suggests that DNA sequencing might be repurposed as a multi-pronged chemical sensor, estimating concentrations of O2 and other key facets of complex natural settings.

International Multi-Specialty Expert Physician Preoperative Identification of Extranodal Extension n Oropharyngeal Cancer Patients using Computed Tomography: Prospective Blinded Human Inter-Observer Performance Evaluation.

Extranodal extension (pENE) is a critical prognostic factor in oropharyngeal cancer (OPC) that drives therapeutic disposition. Determination of pENE from radiological imaging has been associated with high inter-observer variability. However, the impact of clinician specialty on human observer performance of imaging-detected extranodal extension (iENE) remains poorly understood. To characterize the impact of clinician specialty on the accuracy of pre-operative iENE in human papillomavirus-positive (HPV+) OPC using computed tomography (CT) images. This prospective observational human performance study analyzed pre-therapy CT images from 24 HPV+ OPC patients, with duplication of 6 scans (n=30) of which 21 were pathologically confirmed pENE. Thirty-four expert observers, including 11 radiologists, 12 surgeons, and 11 radiation oncologists, independently assessed these scans for iENE and reported human-detected radiologic criteria and observer confidence. The primary outcomes included accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and Brier score for each physician, compared to ground-truth pENE. The significance of radiographic signs for prediction of pENE were determined through logistic regression analysis. Fleiss' kappa measured interobserver agreement, and Hanley-MacNeil AUC discrimination testing. Median accuracy across all specialties was 0.57 (95%CI 0.39 to 0.73), with no specialty showing discriminate performance greater than random estimation (median AUC 0.64, 95%CI 0.44 to 0.83). Significant differences between radiologists and surgeons in Brier scores (0.33 vs. 0.26, p < 0.01), radiation oncologists and surgeons in sensitivity (0.48 vs. 0.69, p > 0.1), and radiation oncologists and radiologists/surgeons in specificity (0.89 vs. 0.56, p > 0.1). Indistinct capsular contour and nodal necrosis were significant predictors of correct pENE status among all specialties. Interobserver agreement was weak for all the radiographic criteria, regardless of specialty (κ<0.6). Multiobserver testing shows physician discrimination of HPV+OPC pENE on pre-operative CT remains non-different than blind guessing, with high interrater variability and low diagnostic accuracy, regardless of clinician specialty. While minor differences in diagnostic performance among specialties are noted, they do not significantly affect the overall poor agreement and discrimination rates observed. The findings underscore the need for further research into automated detection systems or enhanced imaging techniques to improve the accuracy and reliability of iENE assessments in clinical practice.

Can an extended-matching second-language vocabulary test format bridge the gap between meaning-recognition and meaning-recall?

Meaning-recognition and meaning-recall vocabulary tests are commonly used to assess knowledge of the form-meaning link as it relates to the receptive skills. Although meaning-recognition is generally more convenient, think-aloud protocols have revealed that in comparison to meaning-recall, meaning-recognition is more susceptible to blind guessing and the use of construct-irrelevant test strategies. Perhaps because of this, meaning-recall tends to be a stronger predictor of reading ability. Following Budescu (1988), this article reports on three studies that investigated an extended-matching test (EMT) format that was designed to address these limitations of meaning-recognition while retaining its convenience. An EMT with 90 target words was developed. It contained three clusters, each with a 30:130 ratio of target words to Vietnamese L2 response options. In comparison to meaning-recall criterion measures, the EMT did not meaningfully differ in terms of internal reliability, mean scores, and, importantly, the strength of the correlation with reading comprehension scores. The consistency of correct/incorrect response classifications ranged from 83 % to 86 %. These initial findings suggest that the EMT format may be used interchangeably with meaning-recall for many research purposes.

Measuring depth of academic vocabulary knowledge

In second language (L2) vocabulary studies there is continuing interest in tests of depth of vocabulary knowledge, measuring various aspects of word knowledge other than just the form–meaning link that is the focus of breadth (or size) tests. This study aimed to explore new formats that could be used as diagnostic tools for assessing depth of academic vocabulary knowledge. The participants were 222 first-year students taking a programme of English for academic purposes (EAP) at a university in Vietnam. The depth measure was a newly developed test of a sample of words from Gardner and Davies’ Academic Vocabulary List, including sub-tests on receptive knowledge of synonyms, collocations and word parts. The participants also took the Updated Vocabulary Levels Test as a breadth measure, as well as a translation test. Results showed that most of the students had a relatively limited knowledge of general English vocabulary. There was a moderate correlation between the breadth and depth tests. The students had the best knowledge of synonyms, followed by word parts and then collocations. The collocation and word parts sub-tests included a Not Sure option to discourage blind guessing, and analyses of responses to this option offered useful insights into the students’ test-taking behaviour.

Evaluating knowledge-based security questions for fallback authentication.

Failed user authentication is a common event. Forgotten passwords and fingerprint non-recognition are the most common causes. Therefore, there is a need for efficient backup authentication methods, known as fallback authentication. However, fallback authentication methods suffer from different security and usability issues. This study aims to improve the security and usability of knowledge-based fallback authentication in the form of static security questions. The approach proposed in this study was designed considering different factors, such as question features, authentication mechanisms, and the use of tools to aid in composing memorable and secure answers. This study used a two-part experiment with 23 participants to evaluate the proposed approach based on security model testing. The results show that the proposed approach offered improved resistance to blind guess, focused guess, and observation guess attacks. While usability was clearly improved with questions that were based on recognition mechanisms, our results indicate that fallback authentication systems need a flexible level of security and avoidance of complexity in composing answers. In addition, our results indicate the effectiveness of using user behavioral details in the choice of topics for questions, where behavioral questions must have both high recall levels and resistance against guessing attacks. This work theoretically extends the knowledge of fallback authentication research by evaluating new security questions for fallback authentication considering replace of classical topics of security questions by introducing new topics of security questions based on user behavior and personal preferences. Also, this study applies methods of managing answers to security questions by encouraging users to compose answers based on free strict rules that inspire them to create strong and memorable answers based on their own rules. In addition, the findings of this study could support the deployment of knowledge-based authentication in fallback systems as a practical contribution to the user authentication field.

Robustness of building energy optimization with uncertainties using deterministic and stochastic methods: Analysis of two forms

Building performance optimization is effective in searching for optimal design solutions, but its result may be unrobust with uncertainties in input parameters, especially for form design. Stochastic optimization is a promising approach to handle this problem, but its effectiveness in improving robustness is unclear. In this study, stochastic optimization is compared to the traditional deterministic method under holistic uncertainties in 13 input parameters. Energy optimizations of two office building forms, a shoe-box and an irregular quadrilateral, were inspected. The results indicate that robustness problems exist in both deterministic and stochastic optimization with uncertainties, but utilizing optimization results is still a good strategy, as the average chance of the optimized form outperforming random designs exceeds 0.7 for all cases involved. Using stochastic optimization helps obtain more robust results, but the expected increase in the average chance is only 3.2 % and 1.2 % for the two forms, and thus its effect should not be overstressed. We suggest that it be used only in major decision-making events considering its hefty demands in time and computation power. Reducing the uncertainty in input parameters is a more effective strategy. By reducing the variance in input parameters by 44 % compared with the “blind guess” scenario, the average chance is expected to increase by 7.2 % and 1.4 %, respectively. Making the assumed distribution closer to the real distribution of uncertain parameters is also helpful, with expected increases of 2.2 % and 0.7 %, respectively, if the variance difference between the two distributions is reduced by 44 % relative to a “blind guess.”

THE FIRST STEPS TOWARDS THE FIRST-ORDER POLITENESS RESEARCH IN UDMURT

The research is the continuation of my dissertation written at the Department of the Finno-Ugrian Philology of the University of Szeged. However, in this research I do not analyse politeness on my own like I did in my dissertation, as I include answers of native speakers of the language. They express their own ideas about the different answers I got during my PhD research. This study is based on interviews conducted with 10 native speakers of the Udmurt language. These speakers not only represent different age groups but they have different backgrounds as well: I included speakers of the southern and the northern dialects of the language, there are students and teachers of the Udmurt State University and there are two speakers who had been living abroad for at least two years at the time of recording. There were three main exercises to complete during the interview: in the first one they had to express their opinions about answers that I had acquired earlier in different politeness situations, in the second one they had to group answers based on which ones can belong to the same speaker and in the last one I showed them the correct groups of answers and they had to identify the age, the gender, the dialect and the place of origin of the speaker. Their answers can be really helpful to support my previous results or to open a new perspective in the research because, as native speakers, they are able to understand small differences that could be easily skimmed over by non-native speakers. This research has two main parts. In the first part the native speakers express their ideas about answers in given situations and in the second part they try to identify the age, the gender, the dialect and the place of origin of the speakers based on their answers. In the first part the answers usually matched with each other but the interpretation of the Udmurt second past in this situation led to the biggest contradiction in this research. Some of the speakers (as I expected) said that it makes the sentence more polite, but there were some speakers who felt exactly the opposite way about it because in their interpretation it means that the speaker used this tense to avoid responsibility. From the second part it draws out clearly, that there is no age, gender, dialectal or geographical group of speakers who could be easily identified by the given answers and the speakers mainly, but not exclusively, used stereotypes for identification. The result of this is that the answers were about as accurate as taking a blind guess.

Reconsidering the Assessment Policy: Practical Use of Liberal Multiple-choice Tests (SAC Method)

Examinees’ performances are assessed using a wide variety of different techniques. Multiple-choice (MC) tests are among the most frequently used ones. Nearly, all standardized achievement tests make use of MC test items and there is a variety of ways to score these tests. The study compares number right and liberal scoring (SAC) methods. Mixed methods sequential explanatory research design was used which consists of both quantitative and qualitative analysis of the data. A test with ten questions was conducted to 73 prospective English teachers who were selected purposively and they were asked why they had chosen more than one option in the second part of the test. Priority was on the quantitative data obtained from the test results. Qualitative data were collected using participants’ explanations for their answers. The analysis of the qualitative findings was used to explain the findings of the quantitative results. The results reveal that liberal scoring method rewards partial knowledge and penalizes blind guessing. It is superior to the conventional scoring methods as it eliminates their disadvantages. Though it eliminates the disadvantages of other scoring methods, liberal scoring method is difficult to be used practically in the classroom. Without a technological help, teachers may find liberal scoring method really difficult. The study also provides teachers with a Microsoft Excel document for practical use of liberal MC tests. With the help of this document, teachers can easily conduct liberal MC tests in their exams. Suggestions to the test designers and policymakers at both national and international levels about the use of liberal scoring method were provided at the end of the study.

Cheryl's Birthday

We present four logic puzzles and after that their solutions. Joseph Yeo designed 'Cheryl's Birthday'. Mike Hartley came up with a novel solution for 'One Hundred Prisoners and a Light Bulb'. Jonathan Welton designed 'A Blind Guess' and 'Abby's Birthday'. Hans van Ditmarsch and Barteld Kooi authored the puzzlebook 'One Hundred Prisoners and a Light Bulb' that contains other knowledge puzzles, and that can also be found on the webpage http://personal.us.es/hvd/lightbulb.html dedicated to the book.

Exponential Parameterization and ϵ-Uniformly Sampled Reduced Data

We study the quality of piecewise-Lagrange interpolation for non-parametric data based on e-uniform samplings and different forms of exponential parameterization. Surprisingly, it turns out that there is a sharp discontinuity in the quality of interpolation: exponential parameterization performs no better than a blind uniform guess, except for the case of scaled cumulative chord, which matches parametric interpolation.

Detecting wave function collapse without prior knowledge

We are concerned with the problem of detecting with high probability whether a wave function has collapsed or not, in the following framework: A quantum system with a d-dimensional Hilbert space is initially in state ψ; with probability 0 &amp;lt; p &amp;lt; 1, the state collapses relative to the orthonormal basis b1, …, bd. That is, the final state ψ′ is random, it is ψ with probability 1 − p and bk (up to a phase) with p times Born’s probability bk|ψ2. Now an experiment on the system in state ψ′ is desired that provides information about whether or not a collapse has occurred. Elsewhere [C. W. Cowan and R. Tumulka, J. Phys. A: Math. Theor. 47, 195303 (2014)], we identify and discuss the optimal experiment in case that ψ is either known or random with a known probability distribution. Here, we present results about the case that no a priori information about ψ is available, while we regard p and b1, …, bd as known. For certain values of p, we show that the set of ψs for which any experiment E is more reliable than blind guessing is at most half the unit sphere; thus, in this regime, any experiment is of questionable use, if any at all. Remarkably, however, there are other values of p and experiments E such that the set of ψs for which E is more reliable than blind guessing has measure greater than half the sphere, though with a conjectured maximum of 64% of the sphere.

Can one detect whether a wave function has collapsed?

Consider a quantum system prepared in state ψ, a unit vector in a d-dimensional Hilbert space. Let b1, …, bd be an orthonormal basis and suppose that, with some probability 0 < p < 1, ψ ‘collapses’, i.e., gets replaced by bk (possibly times a phase factor) with Born’s probability |〈bk|ψ〉|2. The question we investigate is: how well can any quantum experiment on the system determine afterwards whether a collapse has occurred? The answer depends on how much is known about the initial vector ψ. We provide a number of different results addressing several variants of the question. In each case, no experiment can provide more than rather limited probabilistic information. In case ψ is drawn randomly with uniform distribution over the unit sphere in Hilbert space, no experiment performs better than a blind guess without measurement; that is, no experiment provides any useful information.

Revision of Guilford Formula to Correct Item Difficulty for Guessing in Multiple Choice Test Items

The original Guilford formula for estimation of multiple choice item difficulty was based on a penalty for guessing. This penalty was originally based on completely random or blind guessing, which means that it is purely based on mathematical estimation and on significantly violated assumptions. While authentic and fair estimation is expected to be based on mixed scoring formula which adds another correction factor to integrate measurement theory with decision theory based on partial knowledge and risk- taking behavior. A new formula with two correction factors related to guessing, partial knowledge and risk-taking is presented in this paper. Further studies are suggested for reviewing the validation of the main assumptions of item theory models.

Revision of Guilford Formula to Correct Item Difficulty for Guessing in Multiple Choice Test Items

The original Guilford formula for estimation of multiple choice item difficulty was based on a penalty for guessing. This penalty was originally based on completely random or blind guessing, which means that it is purely based on mathematical estimation and on significantly violated assumptions. While authentic and fair estimation is expected to be based on mixed scoring formula which adds another correction factor to integrate measurement theory with decision theory based on partial knowledge and risk- taking behavior. A new formula with two correction factors related to guessing, partial knowledge and risk-taking is presented in this paper. Further studies are suggested for reviewing the validation of the main assumptions of item theory models.

Issues in user authentication using security questions

Security questions are a human-authentication method leveraging unique private knowledge that only the valid user has and provide a reliable means for supplementary authentication. Security questions offer a low-cost alternative for password-resets and provide an additional layer of security beyond the traditional username-and-password protection method. In this survey paper, we review current literature on security questions, examine the issues on their use and identify the areas that need further research. The results of our review indicate that the current literature has acknowledged and discussed how security questions are susceptible to predominantly three types of attacks: blind guess, focused guess and observation. We found gaps in the literature in areas of using automated systems to provide real-time evaluation of responses and providing feedback to users to improve security. Finally, we outline potential directions for future research in using security questions more effectively.

Development of a Regional Soil Productivity Index Using an Artificial Neural Network Approach

Soil productivity indices represent ratings of the potential plant biomass production of soils. Inductive approaches determine productivity based on inferred effects of soil properties on yield. Conversely, deductive approaches use yield information to estimate productivity. Our objective was to compare the performance of both types of productivity indices for assessing regional soil productivity for wheat (Triticum aestivum L.) yield in the Pampas. Soil data from soil surveys and interpolated climate information were utilized. Wheat yield data from a 40‐yr period and representing ?45 Mha were used. Inductive productivity indices showed a low correlation with observed yield (R2 &lt; 0.45, P = 0.05). The best performance of deductive empirical methods was attained using a blind guess option, but soils could only be rated when yield data were available. Yield models based on the neural network approach had good performance (R2 = 0.614, root mean square error [RMSE] = 548 kg ha–1) and was used for regional productivity index development. This index could be extrapolated to soils for which yield data are not available, and its validation with yield averages was optimal (R2 = 0.728, P = 0.05). Regional high productivity was achieved for combinations of medium to high levels of soil organic C and soil available water storage capacity variables, which showed a positive interaction. This methodology for assessing soil productivity based on an empirical yield‐based model may be applied in other regions of the world and for different crops.

Piecewise-quadratics and exponential parameterization for reduced data

In this paper we discuss the problem of interpolating the so-called reduced dataQm={qi}i=0m to estimate the unknown curve γ satisfying γ(ti)=qi. The corresponding interpolation knots {ti}i=0m for the reduced data are assumed to be unknown. The main issue for such non-parametric data fitting (given selected interpolation scheme) is to complement {ti}i=0m with somehow guessed {tˆi}i=0m, so that the respective trajectory estimation is achieved with possibly fast orders. This work discusses the so-called exponential parameterizations used in computer graphics for curve modeling, which is combined here with piecewise-quadraticsγˆ2. Such family of guessed knots {tˆiλ}i=0m (with 0⩽λ⩽1) comprises well-known cases. Indeed, for λ=0a blind uniform guess follows. When λ=1/2 the so-called centripetal parameterization occurs. On the other hand, if λ=1cumulative chords are invoked. As already established for γˆ2, cumulative chords for all admissible samplings match a cubic convergence order α(1)=3 holding also for the corresponding non-reduced data({ti}i=0m,Qm) used with piecewise-quadratics γ̃2 (i.e. a special case of the so-called parametric interpolation). Our main result reads that, for exponential parameterization and curves sampled more-or-less uniformly (forming a wide subclass of admissible samplings) the resulting convergence rates α(λ) for λ∈[0,1) do not accelerate continuously from α(0)=1 to α(1)=3. In fact, they all coincide and satisfy sharp condition α(λ)=α(0)=1. The sharpness of the asymptotic estimates between curve γ and its interpolant γˆ2 derived herein is confirmed by theoretical argument and independently verified by experimental testing. In addition, we also demonstrate that, a natural candidate for re-parameterization of γˆ2 to synchronize both domains of γ and γˆ2 (necessary to derive the asymptotics in question) may fail to form a genuine re-parameterization.

Delayed Perceptual Awareness in Rapid Perceptual Decisions

The flourishing of studies on the neural correlates of decision-making calls for an appraisal of the relation between perceptual decisions and conscious perception. By exploiting the long integration time of noisy motion stimuli, and by forcing human observers to make difficult speeded decisions – sometimes a blind guess – about stimulus direction, we traced the temporal buildup of motion discrimination capability and perceptual awareness, as assessed trial by trial through direct rating. We found that both increased gradually with motion coherence and viewing time, but discrimination was systematically leading awareness, reaching a plateau much earlier. Sensitivity and criterion changes contributed jointly to the slow buildup of perceptual awareness. It made no difference whether motion discrimination was accomplished by saccades or verbal responses. These findings suggest that perceptual awareness emerges on the top of a developing or even mature perceptual decision. We argue that the middle temporal (MT) cortical region does not confer us the full phenomenic depth of motion perception, although it may represent a precursor stage in building our subjective sense of visual motion.

Predicting average regional yield and production of wheat in the Argentine Pampas by an artificial neural network approach

A regional analysis of the effects of soil and climate factors on wheat yield was performed in the Argentine Pampas in order to obtain models suitable for yield estimation and regional grain production prediction. Soil data from soil surveys and climate data from meteorological records were employed. Grain production information from statistics at county level was integrated at a geomorphological level. The Pampas was divided into 10 geographical units and data from 10 growing season were used (1995–2004). Surface regression and artificial neural networks (ANN) methodologies were tested for analyzing the data. Wheat yield was correlated to soil available water holding capacity (SAWHC) in the upper 100 cm of the profiles ( r 2 = 0.39) and soil organic carbon (SOC) content ( r 2 = 0.26). The climate factor with stronger effect on yield was the rainfall/crop potential evapotranspiration ratio (R/CPET) during the fallow and vegetative crop growing cycle periods summed ( r 2 = 0.31). The phototermal quotient (PQ) during the pre-anthesis period had also a significant effect on yield ( r 2 = 0.05). A surface regression response model was developed that account for 64% of spatial and interannual yield variance, but this model could not perform a better yield prediction than the blind guess technique. An ANN was fitted to the data that accounted for 76% of yield variability. Comparing predicted versus observed yield a lower RMSE ( P = 0.05) was obtained using the ANN than using the regression or the blind guess methods. Regional production estimations performed by the ANN showed a good agreement with observed data with a RMSE equivalent to 7% of the whole surveyed area production. As variables used for the ANN development may be available around 40–60 days before wheat harvest, the methodology may be used for wheat production forecasting in the Pampas.

Multiple choice and true/false tests: reliability measures and some implications of negative marking

The standard error of measurement usefully provides confidence limits for scores in a given test, but is it possible to quantify the reliability of a test with just a single number that allows comparison of tests of different format? Reliability coefficients do not do this, being dependent on the spread of examinee attainment. Better in this regard is a measure produced by dividing the standard error of measurement by the test's ‘reliability length’, the latter defined as the maximum possible score minus the most probable score obtainable by blind guessing alone. This, however, can be unsatisfactory with negative marking (formula scoring), as shown by data on 13 negatively marked true/false tests. In these the examinees displayed considerable misinformation, which correlated negatively with correct knowledge. Negative marking can improve test reliability by penalizing such misinformation as well as by discouraging guessing. Reliability measures can be based on idealized theoretical models instead of on test data. These do not reflect the qualities of the test items, but can be focused on specific test objectives (e.g. in relation to cut‐off scores) and can be expressed as easily communicated statements even before tests are written.