Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the cloud of feature interaction scores in a Rashomon set

Interactions among features are central to understanding the behavior of machine learning models. Recent research has made significant strides in detecting and quantifying feature interactions in single predictive models. However, we argue that the feature interactions extracted from a single pre-specified model may not be trustworthy since: a well-trained predictive model may not preserve the true feature interactions and there exist multiple well-performing predictive models that differ in feature interaction strengths. Thus, we recommend exploring feature interaction strengths in a model class of approximately equally accurate predictive models. In this work, we introduce the feature interaction score (FIS) in the context of a Rashomon set, representing a collection of models that achieve similar accuracy on a given task. We propose a general and practical algorithm to calculate the FIS in the model class. We demonstrate the properties of the FIS via synthetic data and draw connections to other areas of statistics. Additionally, we introduce a Halo plot for visualizing the feature interaction variance in high-dimensional space and a swarm plot for analyzing FIS in a Rashomon set. Experiments with recidivism prediction and image classification illustrate how feature interactions can vary dramatically in importance for similarly accurate predictive models. Our results suggest that the proposed FIS can provide valuable insights into the nature of feature interactions in machine learning models.
TextSLAM: Visual SLAM With Semantic Planar Text Features

We propose a novel visual SLAM method that integrates text objects tightly by treating them as semantic features via fully exploring their geometric and semantic prior. The text object is modeled as a texture-rich planar patch whose semantic meaning is extracted and updated on the fly for better data association. With the full exploration of locally planar characteristics and semantic meaning of text objects, the SLAM system becomes more accurate and robust even under challenging conditions such as image blurring, large viewpoint changes, and significant illumination variations (day and night). We tested our method in various scenes with the ground truth data. The results show that integrating texture features leads to a more superior SLAM system that can match images across day and night. The reconstructed semantic 3D text map could be useful for navigation and scene understanding in robotic and mixed reality applications.
Optimal Seat Arrangement: What Are the Hard and Easy Cases?

We study four NP-hard optimal seat arrangement problems which each have as input a set of n agents, where each agent has cardinal preferences over other agents, and an n-vertex undirected graph (called the seat graph). The task is to assign each agent to a distinct vertex in the seat graph such that either the sum of utilities or the minimum utility is maximized, or it is envy-free or exchange-stable. Aiming at identifying hard and easy cases, we extensively study the algorithmic complexity of the four problems by looking into natural graph classes for the seat graph (e.g., paths, cycles, stars, or matchings), problem-specific parameters (e.g., the number of non-isolated vertices in the seat graph or the maximum number of agents towards whom an agent has non-zero preferences), and preference structures (e.g., non-negative or symmetric preferences). For strict preferences and seat graphs with disjoint edges and isolated vertices, we correct an error in the literature and show that finding an envy-free arrangement remains NP-hard in this case.
Analysis of Visual Question Answering Algorithms with attention model

Visual question answering (VQA) usesimage processing algorithms to process the image and natural language processing methods to understand and answer the question. VQA is helpful to a visually impaired person, can be used for the security surveillance system and online chatbots that learn from the web. It uses NLP methods to learn the semantic of the question and to derive the textual features. Computer vision techniques are used for generating image representation in such a way that they can identify the objects about which question is asked. The Attention model tries to mimic the human behavior of giving attention to a different region of an image according to our understanding of its context. This paper critically examines and reviews methods of VQA algorithm such as generation of semantics of text, identification of objects and answer classification techniques that use the co-attention approach.
Variable-length Neural Interlingua Representations for Zero-shot Neural Machine Translation

The language-independency of encoded representations within multilingual neural machine translation (MNMT) models is crucial for their generalization ability on zero-shot translation. Neural interlingua representations have been shown as an effective method for achieving this. However, fixed-length neural interlingua representations introduced in previous work can limit its flexibility and representation ability. In this study, we introduce a novel method to enhance neural interlingua representations by making their length variable, thereby overcoming the constraint of fixed-length neural interlingua representations. Our empirical results on zero-shot translation on OPUS, IWSLT, and Europarl datasets demonstrate stable model convergence and superior zero-shot translation results compared to fixed-length neural interlingua representations. However, our analysis reveals the suboptimal efficacy of our approach in translating from certain source languages, wherein we pinpoint the defective model component in our proposed method.
Count-Based Research in Management

We review 11 years (2001-2011) of management research using count-based dependent variables in 10 leading management journals. We find that approximately one out of four papers use the most basic Poisson regression model in their studies. However, due to potential concerns of overdispersion, alternative regression models may have been more appropriate. Furthermore, in many of these papers the overdispersion may have been caused by excess zeros in the data, suggesting that an alternative zero-inflated model may have been a better fit for the data. To illustrate the potential differences among the model specifications, we provide a comparison of the different models using previously published data. Additionally, we simulate data using different parameters. Finally, we offer a simplified decision tree guideline to improve future count-based research.
Cross-domain Iterative Network for Simultaneous Denoising, Limited-angle Reconstruction, and Attenuation Correction of Low-dose Cardiac SPECT

Single-Photon Emission Computed Tomography (SPECT) is widely applied for the diagnosis of ischemic heart diseases. Low-dose (LD) SPECT aims to minimize radiation exposure but leads to increased image noise. Limited-angle (LA) SPECT enables faster scanning and reduced hardware costs but results in lower reconstruction accuracy. Additionally, computed tomography (CT)-derived attenuation maps ($\mu$-maps) are commonly used for SPECT attenuation correction (AC), but it will cause extra radiation exposure and SPECT-CT misalignments. In addition, the majority of SPECT scanners in the market are not hybrid SPECT/CT scanners. Although various deep learning methods have been introduced to separately address these limitations, the solution for simultaneously addressing these challenges still remains highly under-explored and challenging. To this end, we propose a Cross-domain Iterative Network (CDI-Net) for simultaneous denoising, LA reconstruction, and CT-free AC in cardiac SPECT. In CDI-Net, paired projection- and image-domain networks are end-to-end connected to fuse the emission and anatomical information across domains and iterations. Adaptive Weight Recalibrators (AWR) adjust the multi-channel input features to enhance prediction accuracy. Our experiments using clinical data showed that CDI-Net produced more accurate $\mu$-maps, projections, and reconstructions compared to existing approaches that addressed each task separately. Ablation studies demonstrated the significance of cross-domain and cross-iteration connections, as well as AWR, in improving the reconstruction performance.
Dynamical structure factor and a new method to measure the pairing gap in two-dimensional attractive Fermi-Hubbard model

By calculating the dynamical structure factor along the high symmetry directions in the Brillouin zone, the dynamical excitations in two-dimensional attractive Fermi-Hubbard model are studied based on the random-phase approximation. At the small transfer momentum, the sound speed can be obtained and is suppressed by the interaction strength. In particular, at the transfer momentum ${\bf q}=\left[\pi,\pi\right]$, the dynamical structure factor consists of a sharp bosonic molecular excitation peak in the low-energy region and a broad atomic excitation band in the higher energy region. Furthermore, as the hopping strength increases (the interaction strength decreases), the weight of the molecular excitation peak decreases monotonically while the weight of the atomic excitations increases quickly. The area of the molecular excitation peak scales with the square of the pairing gap, which also applies to the spin-orbit coupling case. These theoretical results show that the pairing gap in optical lattice can be obtained experimentally by measuring the dynamical structure factor at ${\bf q}=\left[\pi,\pi\right]$.
The C10orf76–PI4KB axis orchestrates CERT-mediated ceramide trafficking to the distal Golgi

Mizuike et al. show that C10orf76, a PI4KB-binding protein, is pivotal for the ceramide transport protein CERT to act at the membrane contact sites between the endoplasmic reticulum and distal Golgi regions. This finding gives a mechanical insight into the metabolic channeling for ceramide-to-sphingomyelin conversion.
Transcriptomic and immunophenotypic characterization of two cases of adamantinoma‐like Ewing sarcoma of the thyroid gland

Adamantinoma‐like Ewing sarcoma (ALES) is a rare aggressive malignancy occasionally diagnosed in the thyroid gland. ALES shows basaloid cytomorphology, expresses keratins, p63, p40, frequently CD99, and harbours the t(11;22) EWSR1::FLI1 translocation. There is debate on whether ALES resembles more sarcoma or carcinoma.
Examining regulatory focus in the acceleration and deceleration of engagement and exhaustion cycles among nurses

Background Given that emotional exhaustion and nurse engagement have significant implications for nurse well-being and organizational performance, determining how to increase nurse engagement while reducing nurse exhaustion is of value. Purpose Resource loss and gain cycles, as theorized in conservation of resources theory, are examined using the experience of emotional exhaustion to evaluate loss cycles and work engagement to evaluate gain cycles. Furthermore, we integrate conservation of resources theory with regulatory focus theory to examine how the ways in which individuals approach work goals serves as a facilitator to the acceleration and deceleration of both of these cycles. Methodology/Approach Using data from nurses working in a hospital in the Midwest United States at six time points spanning over 2 years, we demonstrate the accumulation effects of the cycles over time using latent change score modeling. Results We found that prevention focus was associated with the accelerated accumulation effects of emotional exhaustion and that promotion focus was associated with the accelerated accumulation effects of work engagement. Furthermore, prevention focus attenuated the acceleration of engagement, but promotion did not influence the acceleration of exhaustion. Conclusion Our findings suggest that individual factors such as regulatory focus are key to helping nurses to better control their resource gain and loss cycles. Practice Implications We provide implications for nurse managers and health care administrators to help encourage promotion focus and suppress prevention focus in the workplace.
The impact of recurrence timing and tumor burden score on overall survival among patients undergoing repeat hepatectomy for colorectal liver metastases

Approximately 15% of patients experience a resectable intrahepatic recurrence after an index curative‐intent hepatectomy for colorectal liver metastases (CRLM). We sought to investigate the impact of recurrence timing and tumor burden score (TBS) at the time of recurrence on overall survival among patients undergoing repeat hepatectomy.
Suicide literacy and attitudes toward psychological help-seeking: a cross-sectional study of students

Objective Higher education students express high levels of suicidal ideation. However, data on students’ knowledge of suicide and attitudes toward seeking professional psychological help are lacking. Therefore, a cross-sectional study was conducted to evaluate students’ suicidal ideation, suicide literacy and attitudes toward seeking professional psychological help, and to assess whether these variables were interrelated. Methods Higher education students completed an online survey that consisted of 12 questions on suicide literacy (based on the Literacy of Suicide Scale), the Attitudes Toward Seeking Professional Psychological Help Scale and the Suicidal Ideation Attributes Scale. Results A total of 2004 students completed the survey. Female students and biomedical students showed the highest suicide literacy and most positive help-seeking attitudes. Higher study year was associated with more positive help-seeking attitudes. Art students expressed the highest levels of suicidal ideation. Suicide literacy had a weak positive correlation with help-seeking attitudes (Spearman’s rho = 0.186). Conclusions Suicidal ideation, suicide literacy and help-seeking attitudes may differ according to student’s gender, study year and study field. Better suicide literacy may promote psychological help-seeking behavior.
Shifted Excitation Raman Difference Spectroscopy Combined with Wide Area Illumination and Sample Rotation for Wood Species Classification

Raman spectroscopy has found its way into a wide range of applications and is successfully applied for qualitative and quantitative studies. Despite significant technical progress over the last few decades, there are still some challenges that limit its more widespread usage. This paper presents a holistic approach to addressing simultaneously the problems of fluorescence interference, sample heterogeneity, and laser-induced sample heating. Long wavelength shifted excitation Raman difference spectroscopy (SERDS) at 830 nm excitation combined with wide-area illumination and sample rotation is presented as a suitable approach for the investigation of selected wood species. Wood as a natural specimen represents a well-suited model system for our study as it is fluorescent, heterogeneous, and susceptible to laser-induced modifications. Two different subacquisition times (50 and 100 ms) and two sample rotation speeds (12 and 60 r/min) were exemplarily assessed. Results demonstrate that SERDS can effectively separate the Raman spectroscopic fingerprints of the wood species balsa, beech, birch, hickory, and pine from intense fluorescence interference. Sample rotation in conjunction with 1 mm-diameter wide-area illumination was suitable to obtain representative SERDS spectra of the wood species within 4.6 s. Using partial least squares discriminant analysis, a classification accuracy of 99.4% for the five investigated wood species was realized. This study highlights the large potential of SERDS combined with wide-area illumination and sample rotation for the effective analysis of fluorescent, heterogeneous, and thermally sensitive specimens in a wide range of application areas. Graphical Abstract This is a visual representation of the abstract.
Localisation accuracy with iodine‐125 seed versus wire guidance for breast cancer surgery

Impalpable breast lesions generally require image‐guided localisation for breast‐conserving surgery. A standard technique is to place a hook wire (HW) within the lesion. Radioguided occult lesion localisation using iodine seeds (ROLLIS) involves inserting a 4.5 mm iodine‐125 seed (seed) into the lesion. We hypothesised that a seed could be more precisely positioned in relation to the lesion than a HW and that this may be associated with a lower re‐excision rate.
The psychometrics of the Persian version of the perfectionistic self‐presentation scale–junior form

The perfectionistic self‐presentation scale (PSPS)–junior form is a self‐report questionnaire used to measure perfectionistic self‐presentation in children and adolescents. It consists of 18 items and 3 subscales, including perfectionistic self‐promotion, non‐display of imperfection, and nondisclosure of imperfection.
Correlation between grading methods of the cochlear endolymphatic hydrops and hearing loss in meniere’s disease using three-dimensional real inversion recovery sequences

Abstract Background The grading of intracochlear endolymphatic hydrops (EH) in Meniere’s disease (MD) varies and lacks uniformity. Aims To compare the grading consistency and correlation between different grade methods of intracochlear EH and hearing loss. Materials and methods Thirty-one patients diagnosed with MD underwent gadolinium-enhanced magnetic resonance imaging. Two radiologists graded the cochlea EH according to M1, M2, M3, or M4. We analysed the grading consistency and correlation between the EH degrees and hearing loss. Results The weighted kappa coefficients for inter-observer and intra-observer agreements for grading using M1 were good, whereas those for M2, M3, and M4 are excellent (all p < 0.001). The cochlear EH degree based on M2 was correlated with the low-to-mid frequencies, high frequencies, full frequencies, and MD clinical stage (all p < 0.05). The degrees based on M1, M3, M4 were only relevant to some of the 4 items. Conclusions The grading consistency of M2, M3, M4 is relatively higher than that of M1, and M2 shows the strongest correlation with hearing loss. Significance Our results provide a more accurate method for assessing the clinical severity of MD.
An Analysis of ADCP Wave Directional Distributions with Comparison to Triplet Measurement Techniques Using ADCP and Triplet Data

Introduction The ability to accurately resolve wave directional distributions in nature is of crucial importance to such applications as port and harbor monitoring, wave climate modeling, and sediment transport. The ADCP Directional Wave Gauge has the theoretical potential for exceptional directional resolution and accuracy. Wave data from many independent deployments seems to substantiate this potential. The goal of this paper is to characterize the ADCP directional resolution, and place it in perspective with other common methods of measuring directional waves. To that end we have: a) Theoretically modeled the ADCP's array. b) Compared the performance of traditional triplet processing, to array processing using a number of simulated directional distributions.
CsbD, a Novel Group B Streptococcal Stress Response Factor That Contributes to Bacterial Resistance against Environmental Bile Salts

GBS, a conditional pathogenetic colonizer of the human intestinal flora, can cause severe infectious diseases in immunocompromised patients. Therefore, it is critical to understand the factors that contribute to the resistance to bile salts, which are abundant in the intestine but harmful to bacteria. ABSTRACT Group B Streptococcus (GBS) can cause many serious infections and result in severe symptoms depending on the infected organs. To survive and initiate infection from the gastrointestinal tract, GBS must resist physiochemical factors, such as bile salts, a potent antibacterial compound in the intestine. We found that GBS isolated from diverse sources all possess the capability to defend bile salts and permit survival. By constructing the GBS A909 transposon mutant library (A909Tn), we identified several candidate genes that might participate in the bile salt resistance of GBS. The rodA and csbD genes were validated as relevant to bile salt resistance. The rodA gene was anticipated to be related to peptidoglycan synthesis and influence the bile salt resistance of GBS by cell wall construction. Notably, we found that the csbD gene worked as a bile salt resistance response factor and influenced several ABC transporter genes, specifically at the later growth period of GBS under bile salt stress. We further detected the marked intracellular bile salt accumulation in ΔcsbD by hydrophilic interaction chromatography-liquid chromatography/mass spectrometry (HILIC-LC/MS). Collectively, we showed a novel GBS stress response factor, csbD, contributes to bacterial survival in bile salts by sensing bile salt stress and subsequently induces transcription of transporter genes to excrete bile salts. IMPORTANCE GBS, a conditional pathogenetic colonizer of the human intestinal flora, can cause severe infectious diseases in immunocompromised patients. Therefore, it is critical to understand the factors that contribute to the resistance to bile salts, which are abundant in the intestine but harmful to bacteria. We identified rodA and csbD genes involved in bile salt resistance using a transposon insertion site sequencing (TIS-seq) based screen. The rodA gene products might be involved in peptidoglycan synthesis as important contributors to stress resistance including bile salts. However, the csbD gene conferred bile salt resistance by promoting transporter genes transcription at the later growth period of GBS in response to bile salts. These findings developed a better understanding of the stress response factor csbD on the bile salt resistance of GBS.
The association of hyperuricemia and maternal and fetal outcomes among pregnant women: a meta-analysis

Abstract Objective This meta-analysis aimed to investigate the relationship between hyperuricemia and maternal and neonatal complications in pregnant women. Methods We searched PubMed, Embase, Web of Science, and the Cochrane Library from the databases’ inception to August 12, 2022. We included studies that reported results on the association between hyperuricemia and maternal and fetal outcomes among pregnant women. Using the random-effects model, the pooled odds ratio (OR) with 95% confidence intervals (CIs) was calculated for each outcome analysis. Results A total of 7 studies, including 8104 participants, were included. The pooled OR for pregnancy-induced hypertension (PIH) was 2.61 [0.26, 26.56] (z = 0.81, p = .4165; I 2 = 96.3%). The pooled OR for preterm birth was 2.52 [1.92, 3.30] (z = 6.64, p < .0001; I 2 = 0%). The pooled OR for low birth weight (LBW) was 3.44 [2.52, 4.70] (z = 7.77, p < .0001; I 2 = 0%). The pooled OR for small gestational age (SGA) was 1.81 [0.60, 5.46] (z = 1.06, p = .2912; I 2 = 88.6%). Conclusion Results of this meta-analysis indicate a positive relationship between hyperuricemia and PIH, preterm birth, LBW, and SGA in pregnant women.