Miracle-dz/UniFAR-FTUs huggingface dataset:
Red Teaming Deep Neural Networks with Feature Synthesis Tools

Interpretable AI tools are often motivated by the goal of understanding model behavior in out-of-distribution (OOD) contexts. Despite the attention this area of study receives, there are comparatively few cases where these tools have identified previously unknown bugs in models. We argue that this is due, in part, to a common feature of many interpretability methods: they analyze model behavior by using a particular dataset. This only allows for the study of the model in the context of features that the user can sample in advance. To address this, a growing body of research involves interpreting models using \emph{feature synthesis} methods that do not depend on a dataset. In this paper, we benchmark the usefulness of interpretability tools on debugging tasks. Our key insight is that we can implant human-interpretable trojans into models and then evaluate these tools based on whether they can help humans discover them. This is analogous to finding OOD bugs, except the ground truth is known, allowing us to know when an interpretation is correct. We make four contributions. (1) We propose trojan discovery as an evaluation task for interpretability tools and introduce a benchmark with 12 trojans of 3 different types. (2) We demonstrate the difficulty of this benchmark with a preliminary evaluation of 16 state-of-the-art feature attribution/saliency tools. Even under ideal conditions, given direct access to data with the trojan trigger, these methods still often fail to identify bugs. (3) We evaluate 7 feature-synthesis methods on our benchmark. (4) We introduce and evaluate 2 new variants of the best-performing method from the previous evaluation. A website for this paper and its code is at https://benchmarking-interpretability.csail. mit.edu/
High-Throughput Secure Multiparty Computation with an Honest Majority in Various Network Settings

In this work, we present novel protocols over rings for semi-honest secure three-party computation (3-PC) and malicious four-party computation (4-PC) with one corruption. Compared to state-of-the-art protocols in the same setting, our protocols require fewer low-latency and high-bandwidth links between the parties to achieve high throughput. Our protocols also reduce the computational complexity by requiring up to 50 percent fewer basic instructions per gate. Further, our protocols achieve the currently best-known communication complexity (3, resp. 5 elements per multiplication gate) with an optional preprocessing phase to reduce the communication complexity of the online phase to 2 (resp. 3) elements per multiplication gate. In homogeneous network settings, i.e. all links between the parties share similar network bandwidth and latency, our protocols achieve up to two times higher throughput than state-of-the-art protocols. In heterogeneous network settings, i.e. all links between the parties share different network bandwidth and latency, our protocols achieve even larger performance improvements. We implemented our protocols and multiple other state-of-the-art protocols (Replicated 3-PC, Astra, Fantastic Four, Tetrad) in a novel open-source C++ framework optimized for achieving high throughput. Five out of six implemented 3-PC and 4-PC protocols achieve more than one billion 32-bit multiplication or more than 32 billion AND gates per second using our implementation in a 25 Gbit/s LAN environment. This is the highest throughput achieved in 3-PC and 4-PC so far and between two and three orders of magnitude higher than the throughput MP-SPDZ achieves in the same settings.
Impact of freeze-in on dark matter isocurvature

Dark matter freeze-in is a compelling cosmological production mechanism in which all or some of the observed abundance of dark matter is generated through feeble interactions it has with the Standard Model. In this work we present the first analysis of freeze-in dark matter fluctuations and consider two benchmark models: freeze-in through the direct decay of a heavy vector boson and freeze-in through pair annihilation of Standard Model particles in the thermal bath. We provide a theoretical framework for determining the impact of freeze-in on curvature and dark matter isocurvature perturbations. We determine freeze-in dark matter fluid properties from first principles, tracking its evolution from its relativistic production to its final cold state, and calculate the evolution of the dark matter isocurvature perturbation. We find that in the absence of initial isocurvature, the freeze-in production of dark matter does not source isocurvature. However, for an initial isocurvature perturbation seeded by inflation, the nonthermal freeze-in process may allow for a fraction of the isocurvature to persist, in contrast to the exponential suppression it receives in the case of thermal dark matter. In either case, the evolution of the curvature mode is unaffected by the freeze-in process. We show sensitivity projections of future cosmic microwave background experiments to the amplitude of uncorrelated, totally anticorrelated, and totally correlated dark matter isocurvature perturbations. From these projections, we infer the sensitivity to the abundance of freeze-in dark matter that sustains some fraction of the primordial isocurvature.
Scalable Video Object Segmentation with Identification Mechanism

This paper delves into the challenges of achieving scalable and effective multi-object modeling for semi-supervised Video Object Segmentation (VOS). Previous VOS methods decode features with a single positive object, limiting the learning of multi-object representation as they must match and segment each target separately under multi-object scenarios. Additionally, earlier techniques catered to specific application objectives and lacked the flexibility to fulfill different speed-accuracy requirements. To address these problems, we present two innovative approaches, Associating Objects with Transformers (AOT) and Associating Objects with Scalable Transformers (AOST). In pursuing effective multi-object modeling, AOT introduces the IDentification (ID) mechanism to allocate each object a unique identity. This approach enables the network to model the associations among all objects simultaneously, thus facilitating the tracking and segmentation of objects in a single network pass. To address the challenge of inflexible deployment, AOST further integrates scalable long short-term transformers that incorporate scalable supervision and layer-wise ID-based attention. This enables online architecture scalability in VOS for the first time and overcomes ID embeddings' representation limitations. Given the absence of a benchmark for VOS involving densely multi-object annotations, we propose a challenging Video Object Segmentation in the Wild (VOSW) benchmark to validate our approaches. We evaluated various AOT and AOST variants using extensive experiments across VOSW and five commonly used VOS benchmarks, including YouTube-VOS 2018&2019 Val, DAVIS-2017 Val&Test, and DAVIS-2016. Our approaches surpass the state-of-the-art competitors and display exceptional efficiency and scalability consistently across all six benchmarks. Project page: https://github.com/yoxu515/aot-benchmark.
Distributed Reconfigurable Intelligent Surfaces Assisted Wireless Communication: Asymptotic Analysis under Imperfect CSI

This work studies the net sum-rate performance of a distributed reconfigurable intelligent surfaces (RISs)-assisted multi-user multiple-input-single-output (MISO) downlink communication system under imperfect instantaneous-channel state information (I-CSI) to implement precoding at the base station (BS) and statistical-CSI (S-CSI) to design the RISs phase-shifts. Two channel estimation (CE) protocols are considered for I-CSI acquisition: (i) a full CE protocol that estimates all direct and RISs-assisted channels over multiple training sub-phases, and (ii) a low-overhead direct estimation (DE) protocol that estimates the end-to-end channel in a single sub-phase. We derive the deterministic equivalents of signal-to-interference-plus-noise ratio (SINR) and ergodic net sum-rate under Rayleigh and Rician fading and both CE protocols, for given RISs phase-shifts, which are then optimized based on S-CSI. Simulation results reveal that the low-complexity DE protocol yields better net sum-rate than the full CE protocol when used to obtain CSI for precoding. A benchmark full I-CSI based RISs design is also outlined and shown to yield higher SINR but lower net sum-rate than the S-CSI based RISs design due to the large overhead associated with full I-CSI acquisition. Therefore the proposed DE-S-CSI based design for precoding and reflect beamforming achieves high net sum-rate with low complexity, overhead and power consumption.
Can We Trust AI-Generated Educational Content? Comparative Analysis of Human and AI-Generated Learning Resources

As an increasing number of students move to online learning platforms that deliver personalized learning experiences, there is a great need for the production of high-quality educational content. Large language models (LLMs) appear to offer a promising solution to the rapid creation of learning materials at scale, reducing the burden on instructors. In this study, we investigated the potential for LLMs to produce learning resources in an introductory programming context, by comparing the quality of the resources generated by an LLM with those created by students as part of a learnersourcing activity. Using a blind evaluation, students rated the correctness and helpfulness of resources generated by AI and their peers, after both were initially provided with identical exemplars. Our results show that the quality of AI-generated resources, as perceived by students, is equivalent to the quality of resources generated by their peers. This suggests that AI-generated resources may serve as viable supplementary material in certain contexts. Resources generated by LLMs tend to closely mirror the given exemplars, whereas student-generated resources exhibit greater variety in terms of content length and specific syntax features used. The study highlights the need for further research exploring different types of learning resources and a broader range of subject areas, and understanding the long-term impact of AI-generated resources on learning outcomes.
Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective

This work studies the problem of learning unbiased algorithms from biased feedback for recommendation. We address this problem from a novel distribution shift perspective. Recent works in unbiased recommendation have advanced the state-of-the-art with various techniques such as re-weighting, multi-task learning, and meta-learning. Despite their empirical successes, most of them lack theoretical guarantees, forming non-negligible gaps between theories and recent algorithms. In this paper, we propose a theoretical understanding of why existing unbiased learning objectives work for unbiased recommendation. We establish a close connection between unbiased recommendation and distribution shift, which shows that existing unbiased learning objectives implicitly align biased training and unbiased test distributions. Built upon this connection, we develop two generalization bounds for existing unbiased learning methods and analyze their learning behavior. Besides, as a result of the distribution shift, we further propose a principled framework, Adversarial Self-Training (AST), for unbiased recommendation. Extensive experiments on real-world and semi-synthetic datasets demonstrate the effectiveness of AST.
When the neighborhood matters: contextual selection on seedling traits in native and non-native California grasses.

Plants interact extensively with their neighbors, but the evolutionary consequences of variation in neighbor identity are not well understood. Seedling traits are likely to experience selection that depends on the identity of neighbors because they influence competitive outcomes. To explore this, we evaluated selection on seed mass and emergence time in two California grasses, the native perennial Stipa pulchra and the non-native annual Bromus diandrus, in the field with six other native and non-native neighbor grasses in single and mixed species treatments. We also quantified characteristics of each neighbor treatment to further investigate factors influencing their effects on fitness and phenotypic selection. Selection favored larger seeds in both focal species and this was largely independent of neighbor identity. Selection generally favored earlier emergence in both focal species, but neighbor identity influenced the strength and direction of selection on emergence time in S. pulchra but not B. diandrus. Greater light interception, higher soil moisture, and greater productivity of neighbors was associated with more intense selection for earlier emergence and larger seeds. Our findings suggest that changes in plant community composition can alter patterns of selection in seedling traits, and that these effects can be associated with measurable characteristics of the community.
SWMF Global Magnetosphere Simulations of January 2005: Geomagnetic Indices and Cross‐Polar Cap Potential

We simulated the entire month of January 2005 using the Space Weather Modeling Framework (SWMF) with observed solar wind data as input. We conducted this simulation with and without an inner magnetosphere model and tested two different grid resolutions. We evaluated the model's accuracy in predicting Kp, SYM‐H, AL, and cross‐polar cap potential (CPCP). We find that the model does an excellent job of predicting the SYM‐H index, with a root‐mean‐square error (RMSE) of 17–18 nT. Kp is predicted well during storm time conditions but overpredicted during quiet times by a margin of 1 to 1.7 Kp units. AL is predicted reasonably well on average, with an RMSE of 230–270 nT. However, the model reaches the largest negative AL values significantly less often than the observations. The model tended to overpredict CPCP, with RMSE values on the order of 46–48 kV. We found the results to be insensitive to grid resolution, with the exception of the rate of occurrence for strongly negative AL values. The use of the inner magnetosphere component, however, affected results significantly, with all quantities except CPCP improved notably when the inner magnetosphere model was on.
Lateral hinge fracture in medial opening wedge high tibial osteotomy: a narrative review

Lateral hinge fractures (LHF) are one of the most common complications of medial opening wedge high tibial osteotomy (MOWHTO), and are the leading cause of construct instability displacement, non-union, and varus recurrence after this procedure. To date, Takeuchi’s classification is the most popular classification to describe this complication, and it can help surgeons to make intra and postoperative decisions. Opening medial gap width is the most recognized factor related to LHF occurrence. Recognizing the implications of LHF in patients’ clinical and radiographic results has led many authors to propose surgical tips and the use of osteosynthesis materials such as K-wires and screws for its prevention, which should be considered when identifying risk factors for LHF during preoperative planning. The evidence for determining the optimal management of LHF is scarce and mostly supported by experts’ opinions and recommendations; therefore, studies are still needed to identify the most appropriate behavior when dealing with such a complication.
Reduced Total Airway Count and Airway Wall Tapering after Three-Years in Ex-Smokers

Abstract Computed tomography (CT) total-airway-count (TAC) and airway wall-thickness differ across chronic obstructive pulmonary disease (COPD) severities, but longitudinal insights are lacking. The aim of this study was to evaluate longitudinal CT airway measurements over three-years in ex-smokers. In this prospective convenience sample study, ex-smokers with (n = 50; 13 female; age = 70 ± 9 years; pack-years = 43 ± 26) and without (n = 40; 17 female; age = 69 ± 10 years; pack-years = 31 ± 17) COPD completed CT, 3He magnetic resonance imaging (MRI), and pulmonary function tests at baseline and three-year follow-up. CT TAC, airway wall-area (WA), lumen-area (LA), and wall-area percent (WA%) were generated. Emphysema was quantified as the relative-area-of-the-lung with attenuation < –950 Hounsfield-units (RA950). MRI ventilation-defect-percent (VDP) was also quantified. Differences over time were evaluated using paired-samples t tests. Multivariable prediction models using the backwards approach were generated. After three-years, forced-expiratory-volume in 1-second (FEV1) was not different in ex-smokers with (p = 0.4) and without (p = 0.5) COPD, whereas RA950 was (p < 0.001, p = 0.02, respectively). In ex-smokers without COPD, there was no change in TAC (p = 0.2); however, LA (p = 0.009) and WA% (p = 0.01) were significantly different. In ex-smokers with COPD, TAC (p < 0.001), WA (p = 0.04), LA (p < 0.001), and WA% (p < 0.001) were significantly different. In all ex-smokers, TAC was related to VDP (baseline: ρ = –0.30, p = 0.005; follow-up: ρ = –0.33, p = 0.002). In significant multivariable models, baseline airway wall-thickness was predictive of TAC worsening. After three-years, in the absence of FEV1 worsening, TAC diminished only in ex-smokers with COPD and airway walls were thinner in all ex-smokers. These longitudinal findings suggest that the evaluation of CT airway remodeling may be a useful clinical tool for predicting disease progression and managing COPD. Clinical trial registration: www.clinicaltrials. gov NCT02279329
Comparative analysis of craniofacial asymmetry in subjects with and without symptoms of temporomandibular joint disorders: a cross-sectional study

Objectives The aim of the study was to quantify and compare craniofacial asymmetry in subjects with and without symptoms of temporomandibular joint disorders (TMDs). Materials and Methods A total of 126 adult subjects were categorized into two groups (63 with a TMDs and 63 without a TMDs), based on detection of symptoms using the Temporomandibular Joint Disorder-Diagnostic Index (TMD-DI) questionnaire. Posteroanterior cephalograms of each subject were traced manually and 17 linear and angular measurements were analyzed. Craniofacial asymmetry was quantified by calculating the asymmetry index (AI) of bilateral parameters for both groups. Results Intra- and intergroup comparisons were analyzed using independent t-test and Mann–Whitney U test, respectively, with a P<0.05 considered statistically significant. An AI for each linear and angular bilateral parameter was calculated; higher asymmetry was found in TMD-positive patients compared with TMD-negative patients. An intergroup comparison of AIs found highly significant differences for the parameters of antegonial notch to horizontal plane distance, jugular point to horizontal plane distance, antegonial notch to menton distance, antegonial notch to vertical plane distance, condylion to vertical plane distance, and angle formed by vertical plane, O point and antegonial notch. Significant deviation of the menton distance from the facial midline was also evident. Conclusion Greater facial asymmetry was seen in the TMD-positive group compared with the TMD-negative group. The mandibular region was characterized by asymmetries of greater magnitude compared with the maxilla. Patients with facial asymmetry often require management of temporomandibular joint (TMJ) pathology to achieve a stable, functional, and esthetic result. Ignoring the TMJ during treatment or failing to provide proper management of the TMJ and performing only orthognathic surgery may result in worsening of TMJ-associated symptoms (jaw dysfunction and pain) and re-occurrence of asymmetry and malocclusion. Assessments of facial asymmetry should take into account TMJ disorders to improve diagnostic accuracy and treatment outcomes.
On Maximal Homogeneous 3-Geometries and Their Visualization

The motivation for this talk and paper is related to the classification of the homogeneous simply connected maximal 3-geometries (the so-called Thurston geometries: E 3 , S 3 , H 3 , S 2 × R , H 2 × R , S L 2 R ˜ , Nil , and Sol ) and their applications in crystallography. The first author found in (Molnar 1997) (see also the more popular (Molnar et al. 2010; 2015) with co-author colleagues, together with more details) a unified projective interpretation for them in the sense of Felix Klein’s Erlangen Program: namely, each S of the above space geometries and its isometry group Isom ( S ) can be considered as a subspace of the projective 3-sphere: S ⊂ P S 3 , where a special maximal group G = Isom ( S ) ⊆ Coll ( P S 3 ) of collineations acts, leaving the above subspace S invariant. Vice-versa, we can start with the projective geometry, namely with the classification of Coll ( P S 3 ) through linear transforms of dual pairs of real 4-vector spaces ( V 4 , V 4 , R , ∼ ) = P S 3 (up to positive real multiplicative equivalence ∼) via Jordan normal forms. Then, we look for projective groups with 3 parameters, and with appropriate properties for convenient geometries described above and in this paper.
Frailty and Outcomes Following Cardiopulmonary Resuscitation for Perioperative Cardiac Arrest

Key Points Question Is there an association between frailty and outcomes following cardiopulmonary resuscitation for perioperative cardiac arrest? Findings In this cohort study of 3058 patients with perioperative cardiac arrests, frailty was associated with increased mortality and nonhome discharge. Among patients with severe frailty, increased Risk Analysis Index was associated with steadily increasing risk of mortality and nonhome discharge, and the association with mortality was most pronounced in the context of nonemergency surgery. Meaning Identifying patients undergoing surgery with frailty may inform primary prevention strategies, guide shared decision-making regarding perioperative cardiopulmonary resuscitation, and promote goal-concordant surgical care.
PENGARUH CAR, NPL, BOPO, DAN LDR TERHADAP ROA PADA BUSN DEVISA

ABSTRACT Developments in the banking world very rapidly have a high level complexity and the effect on the performance of a bank. This research is meant to test the influence of CAR, NPL, BOPO, and LDR to the return on asset (ROA) which is listed at Indonesia Stock Exchange. The population is 20 foreign exchange national private commercial banks. The data is the secondary data which has been obtained from the banking annual financial statements which have been published at indonesia stock exchange in 2010-2015 periods. The sample collection technique has been carried out by using purposive sampling with 3 criteria and the samples are 5 banks. The analysis method has been done by using multiple linear regressions analysis. The hypothesis test which has been done by using t test shows that CAR variable has negative and insignificant influence to the ROA, and NPL has negative and significant influence to the ROA, and BOPO has negative and significant influence to the ROA, and LDR has negative and significant influence to the ROA. NPL shows its dominant influence upon all independent variable i.e. CAR, BOPO, and LDR. Keywords: CAR, NPL, BOPO, LDR, ROA