Miracle-dz/UniFAR-FTUs huggingface dataset:
Question Difficulty Prediction for READING Problems in Standard Tests

Standard tests aim to evaluate the performance of examinees using different tests with consistent difficulties. Thus, a critical demand is to predict the difficulty of each test question before the test is conducted. Existing studies are usually based on the judgments of education experts (e.g., teachers), which may be subjective and labor intensive. In this paper, we propose a novel Test-aware Attention-based Convolutional Neural Network (TACNN) framework to automatically solve this Question Difficulty Prediction (QDP) task for READING problems (a typical problem style in English tests) in standard tests. Specifically, given the abundant historical test logs and text materials of questions, we first design a CNN-based architecture to extract sentence representations for the questions. Then, we utilize an attention strategy to qualify the difficulty contribution of each sentence to questions. Considering the incomparability of question difficulties in different tests, we propose a test-dependent pairwise strategy for training TACNN and generating the difficulty prediction value. Extensive experiments on a real-world dataset not only show the effectiveness of TACNN, but also give interpretable insights to track the attention information for questions.
Predicting Intentions to Use Condoms Using Gender, Sexual Experience, and the Theory of Planned Behavior

Abstract This study examined condom use intentions among a large diverse group of African American adolescents and provides useful information to assist in the development of effective HIV prevention interventions. Using the Theory of Planned Behavior (TPB), we explored which constructs are important in shaping intentions to use condoms for younger versus older, female versus male, and sexually experienced versus sexually inexperienced African American youth (n=832). Youth were recruited from inner city schools (n=666) and church youth groups (n=166). Findings indicate that improving subjective norms will be effective with all groups, whereas interventions to improve perceived behavioral control are likely to have an impact on all except sexually experienced girls. Attitudes toward condom use were associated with condom intentions, but only among sexually experienced youth. Prevention programs could greatly increase their efficacy by creating modules that focus on the needs of specific groups when identification of important characteristics (e.g., sexual experience) is possible. Our results indicate that sexually experienced girls may require the most specialized approaches.
HISTORICAL DEMOGRAPHY, SELECTION, AND COALESCENCE OF MITOCHONDRIAL AND NUCLEAR GENES IN PROCHILODUS SPECIES OF NORTHERN SOUTH AMERICA

Abstract Fishes of the genus Prochilodus are ecologically and commercially important, ubiquitous constituents of large river biota in South America. Recent ecologic and demographic studies indicate that these fishes exist in large, stable populations with adult census numbers exceeding one million individuals. Abundance data present a stark contrast to very low levels of genetic diversity (Θ) and small effective population sizes (Ne) observed in a mitochondrial (mt) DNA dataset obtained for two species, Prochilodus mariae, and its putative sister taxon, Prochilodus rubrotaeniatus. Both species occupy major river drainages (Orinoco, Essequibo, and Negro) of northeastern South America. Disparity between expectations based on current abundance and life history information and observed genetic data in these lineages could result from historical demographic bottlenecks, or alternatively, natural selection (i.e., a mtDNA selective sweep). To ascertain underlying processes that affect mtDNA diversity in these species we compared Θ and Ne estimates obtained from two, unlinked nuclear loci (calmodulin intron-4 and elongation factor-1α intron-6) using an approach based on coalescent theory. Genetic diversity and Ne estimated from mtDNA and nuclear sequences were uniformly low in P. rubrotaeniatus from the Rio Negro, suggesting that this population has encountered a historical bottleneck. For all P. mariae populations, Θ and Ne based on nuclear sequences were comparable to expectations based on current adult census numbers and were significantly greater than mtDNA estimates, suggesting that a selective mtDNA sweep has occurred in this species. Comparative genetic analysis indicates that a suite of evolutionary processes involving historical demography and natural selection have influenced patterns of genetic variation and speciation in this important Neotropical fish group.
An Emotional Call to Action: Integrating Affective Neuroscience in Models of Motor Control

Intimate relationships between emotion and action have long been acknowledged, yet contemporary theories and experimental research within affective and movement neuroscience have not been linked into a coherent framework bridging these two fields. Accumulating psychological and neuroimaging evidence has, however, brought new insights regarding how emotions affect the preparation, execution, and control of voluntary movement. Here we review main approaches and findings on such emotion–action interactions. To assimilate key emotion concepts of action tendencies and motive states with fundamental constructs of the motor system, we underscore the need for integrating an information-processing approach of motor control into affective neuroscience. This should provide a rich foundation to bridge the two fields, allowing further refinement and empirical testing of emotion theories and better understanding of affective influences in movement disorders.
Optimization of truck tyres selection

This thesis, which consists of an introduction and five appended papers, concerns the optimal selection of tyres for a variety of vehicle configurations as well as operating environments. The selection problem stems from a project cooperation between Chalmers University of Technology and Volvo Group Trucks Technology. We analyze the selection problem from a mathematical optimization point of view. The overall purpose is to reduce the tractive energy required to run the vehicle. We develop a computationally efficient vehicle dynamics model of the vehicle, the tyres, and the operating environment. The tyres are represented by a surrogate model of the rolling resistance coefficient, which measures the energy losses caused by the tyres. The properties of the surrogate model called for a methodology for connecting expert knowledge about a general simulation-based function with its radial basis function interpolation. An algorithm for the solution of a large set of instances of a simulation-based optimization problem with continuous variables has been developed and tested on a set of problem instances. This algorithm enables an efficient computation of approximately optimal tyre designs (represented by continuous variables) for each vehicle configuration and operating environment specification. A splitting algorithm for simulation-based optimization problems with categorical variables has been developed and evaluated on a set of test problems. This algorithm outperforms all algorithms applicable to this class of optimization problems, and finds an approximately optimal tyres configuration. Since each execution of this algorithm requires many computationally expensive evaluations of the simulation-based objective function, it cannot be used to solve the full tyres selection problem. The two latter algorithms are then combined to enable the efficient solution of many instances of a simulation-based optimization problem with categorical variables. The resulting algorithm is applied to a couple of instances of the tyres selection problem. Our experiments show that the optimization methodology developed enables a computationally efficient solution of the truck tyres selection problem, in the combinatorial domain of possible vehicle configurations and operating environment specifications. Putting our methodology into practice will involve many challenges besides the problems studied in this thesis; however we have shown that our methodology can be utilized in the sales tool at Volvo.
Scavenger receptor A mediates H2O2 production and suppression of IL‐12 release in murine macrophages

Although class A type I/II scavenger receptor (SR‐A) is involved in numerous macrophage functions, its signaling ability remains uncertain. We used monoclonal antibodies (mAb) to specifically stimulate receptors on mouse alveolar (AMs) and peritoneal macrophages (PMs). Immobilized anti‐SR‐A (2F8) and anti‐FcγR II/III (2.4G2) mAb stimulated hydrogen peroxide (H2O2) production in normal C3H/HeJ AMs (by 55% and 98%, respectively) and resident PMs (66% and 128%). The 2F8 mAb‐stimulated H2O2 production resulted from specific stimulation of SR‐A, since this response was absent in AMs from SR‐A‐deficient or C57BL/6 mice—the latter strain expressing an allelic form of SR‐A, unrecognizable by 2F8 mAb. H2O2 production stimulated by anti‐SR‐A but not by anti‐FcγRII/III mAb was preserved in FcγRI/III‐deficient mice, ruling out involvement of FcγRs in the 2F8 mAb effect. In comparison with the FcγR‐stimulated respiratory burst, the response to anti‐SR‐A mAb was delayed and, unlike the former, inhibited by pertussis toxin. Ligation of SR‐A also inhibited lipopolysaccharide plus interferon‐γ‐stimulated interleukin‐12 (IL‐12) release, by 25% in AMs and by 68% in thioglycollate‐elicited PMs, consistent with different levels of SR‐A expression. Neither nitrite nor IL‐6 accumulation was affected by anti‐SR‐A mAb. SR‐A‐stimulated H2O2 does not seem to mediate the inhibition of IL‐12 release, since the inhibition was neither reversed by scavenging of H2O2 nor mimicked by exogenous H2O2. Our results indicate that SR‐A not only mediates endocytosis but can also generate signals such as H2O2, which may affect microbicidal or proinflammatory functions.
Regularisation, interpolation and visualisation of diffusion tensor images using non-Euclidean statistics

Practical statistical analysis of diffusion tensor images is considered, and we focus primarily on methods that use metrics based on Euclidean distances between powers of diffusion tensors. First, we describe a family of anisotropy measures based on a scale invariant power-Euclidean metric, which are useful for visualisation. Some properties of the measures are derived and practical considerations are discussed, with some examples. Second, we discuss weighted Procrustes methods for diffusion tensor imaging interpolation and smoothing, and we compare methods based on different metrics on a set of examples as well as analytically. We establish a key relationship between the principal-square-root-Euclidean metric and the size-and-shape Procrustes metric on the space of symmetric positive semi-definite tensors. We explain, both analytically and by experiments, why the size-and-shape Procrustes metric may be preferred in practical tasks of interpolation, extrapolation and smoothing, especially when observed tensors are degenerate or when a moderate degree of tensor swelling is desirable. Third, we introduce regularisation methodology, which is demonstrated to be useful for highlighting features of prior interest and potentially for segmentation. Finally, we compare several metrics in a data set of human brain diffusion-weighted magnetic resonance imaging, and point out similarities between several of the non-Euclidean metrics but important differences with the commonly used Euclidean metric.
Acute Pain Management in Emergency Department, Low Dose Ketamine Versus Morphine, A Randomized Clinical Trial

Background Ketamine, as an opium alternative, has been proposed for pain relief in the emergency department (ED). Objectives This study was carried out to compare low dose ketamine (LDK) with morphine for pain relief in trauma patients. Methods In this randomized double-blinded clinical trial, 300 trauma patients from the ED of 2 teaching hospitals in Tehran, Iran were enrolled and randomly divided into 2 equal groups. The 1st group received 0.2 mg/kg of ketamine while the 2nd group received 0.1 mg/kg of intravenous morphine. The pain intensity and complications were measured and compared every 15 minutes to 1 hour. Results Fifteen minutes after drug injection in both groups, a significant reduction was found in average pain intensity compared to the initial pain (P = 0.01). At 15 minutes, no significant difference was found in both groups in regards to average pain intensity (P = 0.23). The average pain intensity at 30, 45, and 60 minutes in the group receiving morphine was lower than the ketamine group (P = 0.01, P < 0.001, P < 0.001 respectively). Two complications (drop in O2 saturation below 90% and flushing) were significantly greater in the morphine group. Conclusions The results of this study suggest that LDK, at a dose of 0.2 mg/kg, in the earlier minutes leads to significant reduction of pain when compared to that of intravenous morphine. It also created fewer complications than morphine.
A framework for the experimental comparison of solar and skydome illumination

The illumination and appearance of the solar/skydome is critical for many applications in computer graphics, computer vision, and daylighting studies. Unfortunately, physically accurate measurements of this rapidly changing illumination source are difficult to achieve, but necessary for the development of accurate physically-based sky illumination models and comparison studies of existing simulation models. To obtain baseline data of this time-dependent anisotropic light source, we design a novel acquisition setup to simultaneously measure the comprehensive illumination properties. Our hardware design simultaneously acquires its spectral, spatial, and temporal information of the skydome. To achieve this goal, we use a custom built spectral radiance measurement scanner to measure the directional spectral radiance, a pyranometer to measure the irradiance of the entire hemisphere, and a camera to capture high-dynamic range imagery of the sky. The combination of these computer-controlled measurement devices provides a fast way to acquire accurate physical measurements of the solar/skydome. We use the results of our measurements to evaluate many of the strengths and weaknesses of several sun-sky simulation models. We also provide a measurement dataset of sky illumination data for various clear sky conditions and an interactive visualization tool for model comparison analysis available at http://www.graphics. cornell.edu/resources/clearsky/.
Alkaline phosphatase flare with hyperostosis of bone metastases in lung adenocarcinoma treated with gefitinib

Alkaline phosphatase (ALP) flare has been reported to occur during cancer treatment as a favorable event, particularly in the presence of bone metastasis. There have been only a few reports in lung cancer and associated radiographic findings have seldom been described. The authors observed ALP flare in a female patient with lung adenocarcinoma soon after the initiation of gefitinib. Moreover, on computed tomography, metastatic lesions of the rib and thoracic spine showed marked hyperostosis, with sizes larger than the original bone structure, suggesting efficacy of gefitinib. The significance of such hyperostosis should be elucidated.
Efficient Green Emission from Wurtzite AlxIn1–xP Nanowires

Direct band gap III–V semiconductors, emitting efficiently in the amber–green region of the visible spectrum, are still missing, causing loss in efficiency in light emitting diodes operating in this region, a phenomenon known as the “green gap”. Novel geometries and crystal symmetries however show strong promise in overcoming this limit. Here we develop a novel material system, consisting of wurtzite AlxIn1–xP nanowires, which is predicted to have a direct band gap in the green region. The nanowires are grown with selective area metalorganic vapor phase epitaxy and show wurtzite crystal purity from transmission electron microscopy. We show strong light emission at room temperature between the near-infrared 875 nm (1.42 eV) and the “pure green” 555 nm (2.23 eV). We investigate the band structure of wurtzite AlxIn1–xP using time-resolved and temperature-dependent photoluminescence measurements and compare the experimental results with density functional theory simulations, obtaining excellent agreement. Our work paves the way for high-efficiency green light emitting diodes based on wurtzite III-phosphide nanowires.
A learning-based automatic spinal MRI segmentation

Image segmentation plays an important role in medical image analysis and visualization since it greatly enhances the clinical diagnosis. Although many algorithms have been proposed, it is still challenging to achieve an automatic clinical segmentation which requires speed and robustness. Automatically segmenting the vertebral column in Magnetic Resonance Imaging (MRI) image is extremely challenging as variations in soft tissue contrast and radio-frequency (RF) in-homogeneities cause image intensity variations. Moveover, little work has been done in this area. We proposed a generic slice-independent, learning-based method to automatically segment the vertebrae in spinal MRI images. A main feature of our contributions is that the proposed method is able to segment multiple images of different slices simultaneously. Our proposed method also has the potential to be imaging modality independent as it is not specific to a particular imaging modality. The proposed method consists of two stages: candidate generation and verification. The candidate generation stage is aimed at obtaining the segmentation through the energy minimization. In this stage, images are first partitioned into a number of image regions. Then, Support Vector Machines (SVM) is applied on those pre-partitioned image regions to obtain the class conditional distributions, which are then fed into an energy function and optimized with the graph-cut algorithm. The verification stage applies domain knowledge to verify the segmented candidates and reject unsuitable ones. Experimental results show that the proposed method is very efficient and robust with respect to image slices.
Urban vulnerability and the contribution of socio-environmental fragmentation

As ongoing parallel processes, urbanization and climate change call for overarching context-specific responses that tackle the complex challenges involved and include a comprehensive data base to identify the most pressing action needs. We argue that urban vulnerabilities must take centre stage in this regard. What comes to the fore in the context of urban vulnerability to climate-related hazards is the interaction of human systems with the environment. Understanding the impact of changes in temperature and precipitation on socio-ecological systems is therefore not enough. Insights into the complexity of urban development, social inequalities, economics and politics are needed. To address this complexity, the article focuses on the challenges associated with socio-environmental fragmentation patterns and residential vulnerability, since the interlinkages between them contribute substantially to furthering insights into the specifics of ‘urban’ vulnerabilities to climate-related hazards. An approach that combines socio-environmental fragmentation and residential vulnerability is presented. This approach explores socio-environmental urban developments as well as individual perceptions and capacities.
Investigations of Water Structure at the Solid/Liquid Interface in the Presence of Supported Lipid Bilayers by Vibrational Sum Frequency Spectroscopy

The structure of water was investigated at the quartz/water interface in the presence of supported lipid bilayers (SLBs) by the use of infrared−visible sum frequency spectroscopy. By varying the pH of the bulk solution and the charge on the SLB, changes in both ice-like and water-like peaks were observed in the OH stretch region with respect to the plain quartz/water interface. The oscillator strengths were most affected by applying charged SLBs, rather than bilayers that did not contain a net charge. Time-dependent studies of the ice-like peak intensity at pH 5.6 during the fusion of lipid vesicles to the bare quartz surfaces revealed that the formation rate of a negatively charged SLB was much slower than that of positively charged and neutral SLBs.
Sensitivity to genuine versus posed emotion specified in facial displays

Two experiments were performed to investigate whether social perceivers were sensitive to the veracity of sad and fear facial displays as well as happiness. In Experiment 1, participants were asked to consider in blocks whether targets were happy or not, sad or not, fearful or not. Triads of photographs (neutral, posed, genuine) were displayed and results showed participants were sensitive to whether each emotion was present and distinguished posed from genuine displays. This sensitivity was emotion specific. In Experiment 2, participants completed a priming task to eliminate instructions to judge target displays. Neutral, posed and genuine displays from a single target were used as primes in a word valance identification task. The results revealed faster responding to positive words following genuine than posed happiness and faster responding to negative words following genuine than posed fear. Together the two experiments demonstrated perceiver sensitivity to negative emotion in an explicit and implicit context.
In situ Biofilm Quantification in Bioelectrochemical Systems by using Optical Coherence Tomography

Abstract Detailed studies of microbial growth in bioelectrochemical systems (BESs) are required for their suitable design and operation. Here, we report the use of optical coherence tomography (OCT) as a tool for in situ and noninvasive quantification of biofilm growth on electrodes (bioanodes). An experimental platform is designed and described in which transparent electrodes are used to allow real‐time, 3D biofilm imaging. The accuracy and precision of the developed method is assessed by relating the OCT results to well‐established standards for biofilm quantification (chemical oxygen demand (COD) and total N content) and show high correspondence to these standards. Biofilm thickness observed by OCT ranged between 3 and 90 μm for experimental durations ranging from 1 to 24 days. This translated to growth yields between 38 and 42 mgCODbiomass gCODacetate −1 at an anode potential of −0.35 V versus Ag/AgCl. Time‐lapse observations of an experimental run performed in duplicate show high reproducibility in obtained microbial growth yield by the developed method. As such, we identify OCT as a powerful tool for conducting in‐depth characterizations of microbial growth dynamics in BESs. Additionally, the presented platform allows concomitant application of this method with various optical and electrochemical techniques.