Miracle-dz/UniFAR-FTUs huggingface dataset:
What the Students for Fair Admissions Cases Reveal about Racial Preferences

Using detailed admissions data made public in the SFFA [Students for Fair Admissions] v. Harvard and SFFA v. UNC [University of North Carolina] cases, we examine how racial preferences for underrepresented minorities affect their admissions to Harvard and UNC–Chapel Hill. At Harvard, the admit rates for typical African American applicants are, on average, over four times higher than if they had been treated as white. For typical Hispanic applicants the increase is 2.4 times. At UNC, in-state African Americans’ admit rate is over 70% higher. For out-of-state applicants, the increase is more than tenfold. At both universities, racial preferences are larger for those from more advantaged backgrounds.
DIRECT AND INDIRECT CORRECTIVE FEEDBACK ON EFL STUDENTS’ WRITING PERFORMANCE

Most studies have shown that students’ writing performance improves in accuracy over time after receiving written feedback from teachers, but there is little research adequately examining how different types of written feedback help the writing of students with different proficiency levels in general, and in relation to specific aspects of the content and form of writing, nor investigating students’ preferences when receiving feedback. Therefore, to fill this gap, a study was conducted to achieve two research purposes: (1) to assess students’ writing performance after doing revisions based on written feedback, and (2) to understand the preference of students with different proficiency levels toward feedback strategies. The study involve d 60 college students ; 40 from NCYU and 20 from UT . The students were divided into four groups to receive two types of written feedback—direct corrective feedback in endnotes and indirect corrective feedback in endnotes. Student essays and responses to feedback preference questionnaire were analyzed to answer the problems. The results indicated that significantly, the low proficiency writers who received direct corrective feedback performed better than the low proficiency writers who received indirect corrective feedback. While, no matter whether direct or indirect corrective feedback was received by the high proficiency writers, they performed equally well. Moreover, all students had a positive attitude towards the teacher’s feedback. Also, they preferred receiving direct corrective feedback to indirect corrective feedback focused on content and form .
Effects of Wall Thickness and Crush Initiators Position under Experimental Drop Test on Square Tubes

Crush initiators are the weakest points to reduce initial peak load force with significant energy absorption ability. The objective of this paper is to study the effects of square tube thickness and crush initiators position for impact energy absorber (IEA) performance on thin-walled square tubes. Two square tubes having thickness about 0.6 mm (specimen code A) and 1 mm (specimen Code C) were tested under dynamic load. The crushing initiator is designed around the shape of the tube wall and has eight holes with a fixed diameter of 6.5 mm. In the experiment, the crushing initiator was determined at 5 different locations on the specimen wall. These locations are 10 mm, 20 mm. 30 mm, 40 mm, and 50 mm measured from the initial collision position of the specimen tested. The impact load mass was about 80 kg and had a drop height of about 1.5 m. Using the simulation program of the LabVIEW Professional Development System 2011 and National Instrument (NI) 9234 software equipped with data acquisition hardware NI cDAQ-9174 the signal from the load cell was sent to a computer. By controlling the thickness of the thin-walled square tube, the peak loading force can be decreased by approximately 56.75% and energy absorption ability of IEA can be increased approximately to 11.83%. By using different thin-walled square tube can produce different best crush initiators position with the lowest peak load force.
Communicate and Vote: Collective Truth-tracking in Networks

From diﬀerent angles of science, there has been a growing interest in the abilities of groups to track the truth. The Condorcet Jury Theorem (1785) states that without communication, inﬁnitely big groups will reach a correct majority opinion with certainty. Coughlan (2000), meanwhile formulated a model in which all agents communicate with each other, showing that majorities are only just as good as fully-communicating individuals. In reality, communication is usually between these two extremes: some agents communicate with some of the others, but not with all others. We refer to this as partial communication . This thesis provides a Bayesian framework to study the inﬂuence of partial communication on individual as well as group accuracy, thereby generalising Condorcet’s as well as Coughlan’s setting. We obtain results for individual and group accuracy in three type of networks. Firstly, we study the extreme case where there is either no communication or everyone communicates with everyone. Secondly, we determine accuracy for regular networks, in which all agents communicate with equally many other agents. Thirdly, we derive a formula to express the expected accuracy in random networks, in which agents can communicate with various numbers of other agents. The formula enables us to determine the eﬀect of various parameters on the individual and group accuracy in a random network with partial communication. Finally, we show that in random networks, despite correlation between agents, we can still obtain accurate majorities under some constraints.
Morphometric analysis of lumbar vertebrae using CT scans in Nepalese population

Introduction: Understanding anatomy of the lumbar vertebrae is necessary to achieve clinical success during surgery, for the development of the spinal implants and instruments and to understand changes in elderly and in male and female patients. Methods: A cross-sectional study was done in 50 patients in Nepal to study the lumbar morphometric analysis of the vertebral body, intervertebral disc and spinal canal. Patients who underwent CT IVU for nephrolithiasis at our center were included for analysis of the lumbar morphometry. All the traumatic cases and pathological lesions, such as infection, tumor were excluded from the study. Patients having low backache due to probable intervertebral disc pathology were also excluded from the study. Data analysis was done from Microsoft excel and the mean, standard deviation and range were calculated. Results: The anterior-posterior diameter of the vertebral body, varied from 25.97 mm at L1 to 29.39 mm at L5. The transverse diameter of the body ranged from 31.55 mm at L 1 to 44.13mm at L5. There were changes in height of body. First from L1 - L3 there was increase in height and from L4-L5 there was decrease in height with least height at L5 (22.71mm). According to our study the L1 vertebra has narrowest transverse diameter of spinal canal(21.25mm) whereas L4 has narrowest antero-posterior diameter of spinal canal(12.37mm). Conclusion: In the lumbar area, detailed anatomical knowledge is critical for performing a safe operation. These findings give guidance to the surgeons during various approach while performing operative procedure like pedicle screws, vertebral body screws, cages and laminar hooks.
Study of Piezoelectric Vibration Energy Harvester with non-linear conditioning circuit using an integrated model

ABSTRACT Piezoelectric vibration energy harvester (PVEH) consists of a cantilever bimorph with piezoelectric layers pasted on its top and bottom, which can harvest power from vibrations and feed to low power wireless sensor nodes through some power conditioning circuit. In this paper, a non-linear conditioning circuit, consisting of a full-bridge rectifier followed by a buck–boost converter, is employed to investigate the issues of electrical side of the energy harvesting system. An integrated mathematical model of complete electromechanical system has been developed. Previously, researchers have studied PVEH with sophisticated piezo-beam models but employed simplistic linear circuits, such as resistor, as electrical load. In contrast, other researchers have worked on more complex non-linear circuits but with over-simplified piezo-beam models. Such models neglect different aspects of the system which result from complex interactions of its electrical and mechanical subsystems. In this work, authors have integrated the distributed parameter-based model of piezo-beam presented in literature with a real world non-linear electrical load. Then, the developed integrated model is employed to analyse the stability of complete energy harvesting system. This work provides a more realistic and useful electromechanical model having realistic non-linear electrical load unlike the simplistic linear circuit elements employed by many researchers.
The health effects of 14 weeks of physical activity in a real-life setting for adults with intellectual disabilities

Background: Individuals with intellectual disabilities (ID) have a reduced physical health compared to the general population, and one of the main contributors is inactivity. Aim: To investigate how 14 weeks of physical activity (PA) in a real-life setting affects cardiovascular fitness, body composition and bone health of adults with ID. Methods: Adults with ID were recruited into a PA-group or a control group (CON). The PA-group participated in 14 weeks of PA. Body composition, cardiovascular fitness and bone health were assessed before and after the intervention. Outcomes & results: Cardiovascular fitness and body composition improved from pre to post within the PA-group: Heart rates (HR) during the last 30 seconds of two increments of a treadmill test, were reduced (3.2 km/h: -4.4 bpm, p<0.05; 4.8 km/h: -7.5 bpm, p<0.001) and fat mass was reduced (-1.02 kg, p<0.05). Between-group differences in favour of the PA-group, were observed in whole body bone mineral density (BMD) (0.024 g/cm2, p<0.05) and in BMD of the left femur neck (0.043 g/cm2, p<0.05). Conclusions & Implications: Fourteen weeks of PA increase cardiovascular fitness, reduced fat mass and improved BMD in the weight-bearing skeleton in the PA-group. Increased and regular PA seems to be a promising tool to promote physical health in adults with ID.
Land Quality 1

: We develop a new measure of land quality by estimating weights in a Poisson regression of population in grid cells on a vector of geographic characteristics and country fixed effects. Aggregating to the level of countries, we construct average land quality (ALQ) and quality-adjusted population density (QAPD). We establish several novel facts. First, current income per capita is positively correlated with ALQ. Second, while income today is unrelated to conventional population density, it is strongly negatively related to QAPD. Third, this negative relationship was not present in 1820 and emerged because today’s lower income countries have experienced faster population growth since then. Fourth, countries with higher average land quality began sustained modern economic growth earlier, and this earlier takeoff largely explains the ALQ -modern income relationship. We posit a framework in which higher land quality led to denser populations in Malthusian equilibrium and, via agglomeration effects, an earlier takeoff from that equilibrium. Less dense countries that took off later experienced larger multiplications of their populations over the course of the demographic transition due to the import of health technologies from countries that took off first. __________________________________ Abstract We develop a new measure of land quality by estimating weights in a Poisson regression of population in grid cells on a vector of geographic characteristics and country fixed effects. Aggregating to the level of countries, we construct average land quality ( ALQ ) and quality-adjusted population density ( QAPD ). We establish several novel facts. First, current income per capita is positively correlated with ALQ . Second, while income today is unrelated to conventional population density, it is strongly negatively related to QAPD . Third, this negative relationship was not present in 1820 and emerged because today’s lower income countries have experienced faster population growth since then. Fourth, countries with higher average land quality began sustained modern economic growth earlier, and this earlier takeoff largely explains the ALQ -modern income relationship. We posit a framework in which higher land quality led to denser populations in Malthusian equilibrium and, via agglomeration effects, an earlier takeoff from that equilibrium. Less dense countries that took off later experienced larger multiplications of their populations over the course of the demographic transition due to the import of health technologies from countries that took off first.
Q UASISTATIC F RACTURE USING N ONLINEAR -N ONLOCAL E LASTOSTATICS WITH E XPLICIT T ANGENT S TIFFNESS M ATRIX A

We apply a nonlinear-nonlocal ﬁeld theory for numerical calculation of quasistatic fracture. The model is given by a regularized nonlinear pairwise (RNP) potential in a peridynamic formulation. The potential function is given by an explicit formula with an explicit ﬁrst and second derivatives. This fact allows us to write the entries of the tangent stiffness matrix explicitly thereby saving computational costs during the assembly of the tangent stiffness matrix. We validate our approach against classical continuum mechanics for the linear elastic material behavior. In addition, we compare our approach to a state-based peridynamic model that uses standard numerical derivations to assemble the tangent stiffness matrix. The numerical experiments show that for elastic material behavior our approach agrees with both classical continuum mechanics and the state-based model. The fracture model is applied to produce a fracture simulation for a ASTM E8 like tension test. We conclude with an example of crack growth in a pre-cracked square plate. For the pre-cracked plate, we investigated load in force (soft loading) and load in displacement ( hard loading). Our approach is novel in that only bond softening is used as opposed to bond breaking. For the fracture simulation we have shown that our approach works with and without initial damage for two common test problems.
On the structure of finitely presented Bestvina-Brady groups

Right-angled Artin groups and their subgroups are of great interest because of their geometric, combinatorial and algorithmic properties. It is convenient to define these groups using finite simplicial graphs. The isomorphism type of the group is uniquely determined by the graph. Moreover, many structural properties of right-angled Artin groups can be expressed in terms of their defining graph. In this paper, we address the question of understanding the structure of a class of subgroups of right-angled Artin groups in terms of the graph. Bestvina and Brady, in their seminal work, studied these subgroups (now called Bestvina–Brady groups or Artin kernels) from a finiteness conditions viewpoint. Unlike the right-angled Artin groups the isomorphism type of Bestvina–Brady groups is not uniquely determined by the defining graph. We prove that certain finitely presented Bestvina–Brady groups can be expressed as an iterated amalgamated product. Moreover, we show that this amalgamated product can be read off from the graph defining the ambient right-angled Artin group.
Entailment Tree Explanations via Iterative Retrieval-Generation Reasoner

Large language models have achieved high performance on various question answering (QA) benchmarks, but the explainability of their output remains elusive. Structured explanations, called entailment trees, were recently suggested as a way to explain and inspect a QA system's answer. In order to better generate such entailment trees, we propose an architecture called Iterative Retrieval-Generation Reasoner (IRGR). Our model is able to explain a given hypothesis by systematically generating a step-by-step explanation from textual premises. The IRGR model iteratively searches for suitable premises, constructing a single entailment step at a time. Contrary to previous approaches, our method combines generation steps and retrieval of premises, allowing the model to leverage intermediate conclusions, and mitigating the input size limit of baseline encoder-decoder models. We conduct experiments using the EntailmentBank dataset, where we outperform existing benchmarks on premise retrieval and entailment tree generation, with around 300% gain in overall correctness.
Disks in Nearby Young Stellar Associations Found Via Virtual Reality

The Disk Detective citizen science project recently released a new catalog of disk candidates found by visual inspection of images from NASA’s Wide-field Infrared Survey Explorer mission and other surveys. We applied this new catalog of well-vetted disk candidates to search for new members of nearby young stellar associations (YSAs) using a novel technique based on Gaia data and virtual reality (VR). We examined AB Doradus, Argus, β Pictoris, Carina, Columba, Octans-Near, Tucana–Horologium, and TW Hya by displaying them in VR together with other nearby stars, color coded to show infrared excesses found via Disk Detective. Using this method allows us to find new association members in mass regimes where isochrones are degenerate. We propose 10 new YSA members with infrared excesses: three of AB Doradus (HD 44775, HD 40540 and HD 44510), one of β Pictoris (HD 198472), two of Octans-Near (HD 157165 and BD+35 2953), and four disk-hosting members of a combined population of Carina, Columba, and Tucana–Horologium: CPD-57 937, HD 274311, HD 41992, and WISEA J092521.90-673224.8. This last object (J0925) appears to be an extreme debris disk with a fractional infrared luminosity of 3.7 × 10−2. We also propose two new members of AB Doradus that do not show infrared excesses: TYC 6518-1857-1 and CPD-25 1292. We find HD 15115 appears to be a member of Tucana–Horologium rather than β Pictoris. We advocate for membership in Columba–Carina of HD 30447, CPD-35 525, and HD 35841. Finally, we propose that three M dwarfs, previously considered members of Tucana–Horologium are better considered a separate association, tentatively called “Smethells 165”.
Diverse Weight Averaging for Out-of-Distribution Generalization

Standard neural networks struggle to generalize under distribution shifts in computer vision. Fortunately, combining multiple networks can consistently improve out-of-distribution generalization. In particular, weight averaging (WA) strategies were shown to perform best on the competitive DomainBed benchmark; they directly average the weights of multiple networks despite their nonlinearities. In this paper, we propose Diverse Weight Averaging (DiWA), a new WA strategy whose main motivation is to increase the functional diversity across averaged models. To this end, DiWA averages weights obtained from several independent training runs: indeed, models obtained from different runs are more diverse than those collected along a single run thanks to differences in hyperparameters and training procedures. We motivate the need for diversity by a new bias-variance-covariance-locality decomposition of the expected error, exploiting similarities between WA and standard functional ensembling. Moreover, this decomposition highlights that WA succeeds when the variance term dominates, which we show occurs when the marginal distribution changes at test time. Experimentally, DiWA consistently improves the state of the art on DomainBed without inference overhead.
ERNIE-Search: Bridging Cross-Encoder with Dual-Encoder via Self On-the-fly Distillation for Dense Passage Retrieval

Neural retrievers based on pre-trained language models (PLMs), such as dual-encoders, have achieved promising performance on the task of open-domain question answering (QA). Their effectiveness can further reach new state-of-the-arts by incorporating cross-architecture knowledge distillation. However, most of the existing studies just directly apply conventional distillation methods. They fail to consider the particular situation where the teacher and student have different structures. In this paper, we propose a novel distillation method that significantly advances cross-architecture distillation for dual-encoders. Our method 1) introduces a self on-the-fly distillation method that can effectively distill late interaction (i.e., ColBERT) to vanilla dual-encoder, and 2) incorporates a cascade distillation process to further improve the performance with a cross-encoder teacher. Extensive experiments are conducted to validate that our proposed solution outperforms strong baselines and establish a new state-of-the-art on open-domain QA benchmarks.
MetaV: A Meta-Verifier Approach to Task-Agnostic Model Fingerprinting

Protecting the intellectual property (IP) of deep neural networks (DNN) becomes an urgent concern for IT corporations. For model piracy forensics, previous model fingerprinting schemes are commonly based on adversarial examples constructed for the owner's model as the fingerprint, and verify whether a suspect model is indeed pirated from the original model by matching the behavioral pattern on the fingerprint examples between one another. However, these methods heavily rely on the characteristics of classification tasks which inhibits their application to more general scenarios. To address this issue, we present MetaV, the first task-agnostic model fingerprinting framework which enables fingerprinting on a much wider range of DNNs independent from the downstream learning task, and exhibits strong robustness against a variety of ownership obfuscation techniques. Specifically, we generalize previous schemes into two critical design components in MetaV: the adaptive fingerprint and the meta-verifier, which are jointly optimized such that the meta-verifier learns to determine whether a suspect model is stolen based on the concatenated outputs of the suspect model on the adaptive fingerprint. As a key of being task-agnostic, the full process makes no assumption on the model internals in the ensemble only if they have the same input and output dimensions. Spanning classification, regression and generative modeling, extensive experimental results validate the substantially improved performance of MetaV over the state-of-the-art fingerprinting schemes and demonstrate the enhanced generality of MetaV for providing task-agnostic fingerprinting. For example, on fingerprinting ResNet-18 trained for skin cancer diagnosis, MetaV achieves simultaneously 100% true positives and 100% true negatives on a diverse test set of 70 suspect models, achieving an about 220% relative improvement in ARUC over the optimal baseline.
Mitigating Neural Network Overconfidence with Logit Normalization

Detecting out-of-distribution inputs is critical for safe deployment of machine learning models in the real world. However, neural networks are known to suffer from the overconfidence issue, where they produce abnormally high confidence for both in- and out-of-distribution inputs. In this work, we show that this issue can be mitigated through Logit Normalization (LogitNorm) -- a simple fix to the cross-entropy loss -- by enforcing a constant vector norm on the logits in training. Our method is motivated by the analysis that the norm of the logit keeps increasing during training, leading to overconfident output. Our key idea behind LogitNorm is thus to decouple the influence of output's norm during network optimization. Trained with LogitNorm, neural networks produce highly distinguishable confidence scores between in- and out-of-distribution data. Extensive experiments demonstrate the superiority of LogitNorm, reducing the average FPR95 by up to 42.30% on common benchmarks.