Miracle-dz/UniFAR-FTUs huggingface dataset:
FULLY AUTOMATIC IMAGE-BASED REGISTRATION OF UNORGANIZED TLS DATA

The estimation of the transformation parameters between different point clouds is still a crucial task as it is usually followed by scene reconstruction, object detection or object recognition. Therefore, the estimates should be as accurate as possible. Recent developments show that it is feasible to utilize both the measured range information and the reflectance information sampled as image, as 2D imagery provides additional information. In this paper, an image-based registration approach for TLS data is presented which consists of two major steps. In the first step, the order of the scans is calculated by checking the similarity of the respective reflectance images via the total number of SIFT correspondences between them. Subsequently, in the second step, for each SIFT correspondence the respective SIFT features are filtered with respect to their reliability concerning the range information and projected to 3D space. Combining the 3D points with 2D observations on a virtual plane yields 3D-to-2D correspondences from which the coarse transformation parameters can be estimated via a RANSAC-based registration scheme including the EPnP algorithm. After this coarse registration, the 3D points are again checked for consistency by using constraints based on the 3D distance, and, finally, the remaining 3D points are used for an ICP-based fine registration. Thus, the proposed methodology provides a fast, reliable, accurate and fully automatic image-based approach for the registration of unorganized point clouds without the need of a priori information about the order of the scans, the presence of regular surfaces or human interaction.
Gradient based Feature Attribution in Explainable AI: A Technical Review

The surge in black-box AI models has prompted the need to explain the internal mechanism and justify their reliability, especially in high-stakes applications, such as healthcare and autonomous driving. Due to the lack of a rigorous definition of explainable AI (XAI), a plethora of research related to explainability, interpretability, and transparency has been developed to explain and analyze the model from various perspectives. Consequently, with an exhaustive list of papers, it becomes challenging to have a comprehensive overview of XAI research from all aspects. Considering the popularity of neural networks in AI research, we narrow our focus to a specific area of XAI research: gradient based explanations, which can be directly adopted for neural network models. In this review, we systematically explore gradient based explanation methods to date and introduce a novel taxonomy to categorize them into four distinct classes. Then, we present the essence of technique details in chronological order and underscore the evolution of algorithms. Next, we introduce both human and quantitative evaluations to measure algorithm performance. More importantly, we demonstrate the general challenges in XAI and specific challenges in gradient based explanations. We hope that this survey can help researchers understand state-of-the-art progress and their corresponding disadvantages, which could spark their interest in addressing these issues in future work.
A Short Survey on Importance Weighting for Machine Learning

Importance weighting is a fundamental procedure in statistics and machine learning that weights the objective function or probability distribution based on the importance of the instance in some sense. The simplicity and usefulness of the idea has led to many applications of importance weighting. For example, it is known that supervised learning under an assumption about the difference between the training and test distributions, called distribution shift, can guarantee statistically desirable properties through importance weighting by their density ratio. This survey summarizes the broad applications of importance weighting in machine learning and related research.
Human adaptations to climatic change in Liguria across the Middle–Upper Paleolithic transition

There has been much focus on the disruptive effects of dramatic climatic shifts on Paleolithic population dynamics, but the topic of cultural continuity across such events has been less intensely investigated, despite its importance to the way archeologists think about the ways humans have interacted with their environment in the past. This paper presents data from western Liguria (Italy) and especially the site of Riparo Bombrini, to investigate the nature of the apparent resilience of the Proto‐Aurignacian technocomplex in the face of the Phlegrean Fields super‐eruption ca. 40 000 cal a BP and the general climatic instability during Marine Isotope Stage 3. While the Proto‐Aurignacian shows some internal variability that could reflect an adaptation to changing environmental conditions, overall it remains very stable in terms of its techno‐typology and social geography across these events. Additionally, the radiocarbon chronology for the site clearly shows that the Proto‐Aurignacian outlasts both the super‐eruption and Heinrich Event 4 as a whole, by as much as 2000 years. Comparisons with the regional Mousterian record indicate that the Proto‐Aurignacian marks the advent of a new way for humans to respond to climatic change, which opens up new avenues to reflect on the disappearance of the Mousterian.
The Employee Clientele of Corporate Leverage: Evidence from Family Labor Income Diversification

Using employee job-level data, we empirically test the equilibrium matching between a firm’s debt usage and its employee job risk aversion (“clientele effect”), as predicted by the existing theories. We measure job risk aversion for a firm’s employees using their labor income concentration in the firm, calculated as the fraction of the employees’ total personal labor income or total household labor income that is accounted for by their income from this particular firm. Using a sample of about 1,400 U.S. public firms from 1990-2008, we find a robust negative relation between leverage and employee job risk aversion, which is consistent with the clientele effect. Specifically, when a firm’s existing employees have higher labor income concentration in it, the firm tends to have lower contemporaneous and future leverage. Moreover, in terms of new hires, firms with lower leverage are more likely to recruit employees with less alternative labor income. Our results continue to hold after we control for firm fixed effects, other employee characteristics such as wages, gender, age, race, and education, and managerial risk attitudes. Further, the matching between a firm’s leverage and its workers’ labor income concentration in it is more pronounced for firms with higher labor intensity and those in financial distress.
miR‐708/LSD1 axis regulates the proliferation and invasion of breast cancer cells

Breast cancer is one of the most common malignant tumors in women worldwide. The microRNAs (miRNAs) are small, noncoding RNAs that regulate various biological processes, including breast cancer. miR‐708 played an important role in a variety of cancers. However, its involvement in breast cancer remains largely unclear. In this study, we found that forced the expression of miR‐708 in breast cancer cell lines decreased cell proliferation and invasion, whereas inhibition of miR‐708 increased cell growth and invasion. miR‐708 could directly target the LSD1 3′UTR to downregulate the expression. Further studies suggested that inhibition of LSD1 could phenocopied function of the miR‐708 overexpression in MDA‐MB‐231 cells . Overexpression of LSD1 could counteract the effects of miR‐708 on the proliferation and invasion. Taken together, the results indicate that miR‐708 may function as a tumor suppressor gene in breast cancer development, and miR‐708/LSD1 axis may be a therapeutic intervention in breast cancer in the future.
Participation of Reactive Oxygen Species in the Lysophosphatidic Acid-stimulated Mitogen-activated Protein Kinase Kinase Activation Pathway (*)

Recent evidence suggests that reactive oxygen species (ROS) may function as second messengers in intracellular signal transduction pathways. We explored the possibility that ROS were involved in lysophosphatidic acid (LPA)-induced mitogen-activated protein (MAP) kinase signaling pathway in HeLa cells. Antioxidant N-acetylcysteine inhibited the LPA-stimulated MAP kinase kinase activity. Direct exposure of HeLa cells to hydrogen peroxide resulted in a concentration- and time-dependent activation of MAP kinase kinase. Inhibition of catalase with aminotriazole enhanced the effect of LPA on induction of MAP kinase kinase. Further, LPA stimulated ROS production in HeLa cells. These findings suggest that ROS participate in the LPA-elicited MAP kinase signaling pathway.
Optimal Block-Level Draft Verification for Accelerating Speculative Decoding

Speculative decoding has shown to be an effective method for lossless acceleration of large language models (LLMs) during inference. In each iteration, the algorithm first uses a smaller model to draft a block of tokens. The tokens are then verified by the large model in parallel and only a subset of tokens will be kept to guarantee that the final output follows the distribution of the large model. In all of the prior speculative decoding works, the draft verification is performed token-by-token independently. In this work, we propose a better draft verification algorithm that provides additional wall-clock speedup without incurring additional computation cost and draft tokens. We first formulate the draft verification step as a block-level optimal transport problem. The block-level formulation allows us to consider a wider range of draft verification algorithms and obtain a higher number of accepted tokens in expectation in one draft block. We propose a verification algorithm that achieves the optimal accepted length for the block-level transport problem. We empirically evaluate our proposed block-level verification algorithm in a wide range of tasks and datasets, and observe consistent improvements in wall-clock speedup when compared to token-level verification algorithm. To the best of our knowledge, our work is the first to establish improvement over speculative decoding through a better draft verification algorithm.
Predicting the Scaling Relations between the Dark Matter Halo Mass and Observables from Generalised Profiles II: Intracluster Gas Emission

We investigate the connection between a cluster’s structural configuration and observable measures of its gas emission that can be obtained in X-ray and Sunyaev-Zeldovich (SZ) surveys. We present an analytic model for the intracluster gas density profile: parameterised by the dark matter halo’s inner logarithmic density slope, α, the concentration, c, the gas profile’s inner logarithmic density slope, ε, the dilution, d, and the gas fraction, η, normalised to cosmological content. We predict four probes of the gas emission: the emission-weighted, TX, and mean gas mass-weighted, Tmg, temperatures, and the spherically, Ysph, and cylindrically, Ycyl, integrated Compton parameters. Over a parameter space of clusters, we constrain the X-ray temperature scaling relations, M200 – TX and M500 – TX, within 57.3% and 41.6%, and M200 – Tmg and M500 – Tmg, within 25.7% and 7.0%, all respectively. When excising the cluster’s core, the M200 – TX and M500 – TX relations are further constrained, to within 31.3% and 17.1%, respectively. Similarly, we constrain the SZ scaling relations, M200 – Ysph and M500 – Ysph, within 31.1% and 17.7%, and M200 – Ycyl and M500 – Ycyl, within 25.2% and 22.0%, all respectively. The temperature observable Tmg places the strongest constraint on the halo mass, whilst TX is more sensitive to the parameter space. The SZ constraints are sensitive to the gas fraction, whilst insensitive to the form of the gas profile itself. In all cases, the halo mass is recovered with an uncertainty that suggests the cluster’s structural profiles only contribute a minor uncertainty in its scaling relations.
Exploration of Location-Based Services Adoption

As mobile technologies become more ubiquitous in the general population, it is reasonable to assume that individuals will consume services and software to enhance their aspirations and entertainment desires. This paper discusses a controlled experiment to explore aspects of user perceptions of their use of location-based services. This study examines a location-based service prototype experiment and analysis based on the UTAUT model. The results show significant indicators that suggest behavior patterns of early adopters of location-based services are being observed. We discuss these influences and attempt to explain their significance. Moreover, more curiously we discuss why some of our model was unsupported and postulate why.
A Role for the RNA Chaperone Hfq in Controlling Adherent-Invasive Escherichia coli Colonization and Virulence

Adherent-invasive Escherichia coli (AIEC) has been linked with the onset and perpetuation of inflammatory bowel diseases. The AIEC strain LF82 was originally isolated from an ileal biopsy from a patient with Crohn's disease. The pathogenesis of LF82 results from its abnormal adherence to and subsequent invasion of the intestinal epithelium coupled with its ability to survive phagocytosis by macrophages once it has crossed the intestinal barrier. To gain further insight into AIEC pathogenesis we employed the nematode Caenorhabditis elegans as an in vivo infection model. We demonstrate that AIEC strain LF82 forms a persistent infection in C. elegans, thereby reducing the host lifespan significantly. This host killing phenotype was associated with massive bacterial colonization of the nematode intestine and damage to the intestinal epithelial surface. C. elegans killing was independent of known LF82 virulence determinants but was abolished by deletion of the LF82 hfq gene, which encodes an RNA chaperone involved in mediating posttranscriptional gene regulation by small non-coding RNAs. This finding reveals that important aspects of LF82 pathogenesis are controlled at the posttranscriptional level by riboregulation. The role of Hfq in LF82 virulence was independent of its function in regulating RpoS and RpoE activity. Further, LF82Δhfq mutants were non-motile, impaired in cell invasion and highly sensitive to various chemical stress conditions, reinforcing the multifaceted function of Hfq in mediating bacterial adaptation. This study highlights the usefulness of simple non-mammalian infection systems for the identification and analysis of bacterial virulence factors.
Genetic algorithm based optimization and post optimality analysis of multi-pass face milling

This paper presents an optimization technique for the multi-pass face milling process. Genetic algorithm (GA) is used to obtain the optimum cutting parameters by minimizing the unit production cost for a given amount of material removal. Cutting speed, feed and depth of cut for the finish and rough passes are the cutting parameters. An equal depth of cut for roughing passes has been considered. A lookup table containing the feasible combinations of depth of cut in finish and rough passes is generated so as to reduce the number of variables by one. The resulting mixed integer nonlinear optimization problem is solved in a single step using GA. The entire technique is demonstrated in a case study. Post optimality analysis of the example problem is done to develop a strategy for optimizing without running GA again for different values of total depth of cut.
An exact algorithm for kinodynamic planning in the plane

Planning time-optimal motions has been a major focus of research in robotics. In this paper we consider the following problem: given an object in two-dimensional physical space, an initial point, and a final point, plan a time-optimal obstacle-avoiding motion for this object subject to bounds on the velocity and acceleration of the object. We give the first algorithm which solves the problem exactly in the case where the velocity and acceleration bounds are given in theL∞ norm. We further prove the following important results: a tracking lemma and a loop-elimination theorem, both of which are applicable to the case of arbitrary norms. The latter result implies that, with or without obstacles, a path which intersects itself can be replaced by one which does not do so and which takes time less than or equal to that taken by the original path.
Effects of Green Tea Tannin on Cisplatin‐induced Nephropathy in LLC‐PK1 Cells and Rats

A study was conducted to clarify whether green tea tannin ameliorated cisplatin‐induced renal injury in terms of lactate dehydrogenase and malondialdehyde leakage from a renal epithelial cell line, swine‐derived LLC‐PK1 cells in culture. Green tea tannin was shown to suppress the cytotoxicity of cisplatin, the suppressive effect increasing with the dose of green tea tannin. The effect of cisplatin was then investigated in rats given green tea tannin for 40 days before cisplatin administration and in control rats given no green tea tannin.
ADHD and behavioral disorders: Assessment, management, and an update from DSM-5

Behavioral disorders in pediatric patients—primarily attention deficit hyperactivity disorder (ADHD)—pose a clinical challenge for health care providers to accurately assess, diagnose, and treat. In 2013, updated diagnostic criteria for behavioral disorders were published, including ADHD and a new diagnostic entity: disruptive mood dysregulation disorder. Revised criteria for ADHD includes oldest age for occurrence of symptoms, need for symptoms to be present in more than one setting, and requirement for number of symptoms in those aged 17 and older. Assessment of ADHD relies primarily on the clinical interview, including the medical and social history, along with the aid of objective measures. The clinical course of ADHD is chronic with symptom onset occurring well before adolescence. Most patients have symptoms that continue into adolescence, and some into adulthood. Many patients with ADHD have comorbid disorders such as depression, disruptive behavior disorders, or substance abuse, which need to be addressed first in the treatment plan. Treatment of ADHD relies on a combination of psychopharmacologic, academic, and behavioral interventions, which produce response rates up to 80%.
Metabolic Syndrome : Differences for Asian Americans is in Their Body Fat Percentages

Asian Americans are not frequently thought of as being obese or overweight yet some of the Asian American subgroups have a disproportionate risk for cardiovascular disease and type 2 diabetes mellitus. Although the standardized body mass index (BMI) assessment is an adequate tool for reporting secular prevalence trends for overweight/obesity across populations, it falls short in accuracy when assessing Asian Americans. In recent years more has been written about the re-evaluation of BMI cut points for normal weight, overweight, or obese Asian Americans. Additionally, the waist circumference norm was modified to indicate a smaller waist size is a risk for metabolic syndrome. The purpose of this paper is to provide an overview of the research literature on BMI and percentage of body fat as it relates to health risk for metabolic syndrome for Asian American subgroups. Three databases were used to identify articles for this review: Google Scholar, CINHAL, and PubMed. Seven hundred twenty-six articles were initially identified as meeting the criteria; 690 articles were eliminated after a review of the article titles revealed the content did not meet the focus of this review. Of the remaining articles, 19 were eliminated after a review of the abstracts indicated they were meta-analyses, review articles, or case studies. The remaining 18 articles were included in this review. Three common themes emerged. (1) The differences in BMI and body fat percentage are evident between Asian Americans and other ethnic groups. (2) Differences in the percentage of body fat exist between Asian American subgroups, and between Asian Americans and Asian immigrants. (3) There are differences in disease development end points when comparing Asian American subgroups and Asian immigrant subgroups. There are differences in body fat distribution and body fat percentages as well as BMI compared to other ethnic groups for metabolic syndrome. There are also differences between Asian immigrant/Asian American subgroups whereby some are more susceptible to diabetes and cardiovascular disease. Research is necessary to determine if these differences have an underlying genetic predisposition. Additionally, researchers need to oversample Asian immigrant/Asian American participants in comparison studies and need to identify each subgroup in their research rather than aggregating Asian immigrants/Asian Americans by geographical origin or as one common group designated as a generic group of “Asians. ”
Morphological and distribution variability of preferential flow in plantation soils on the purple sandstone hillslopes using image analysis

Preferential flow is more rapid water and solutes transport in soils, and it can control the flood process in watershed. The extent of preferential flow in different age Chinese fir (Cunninghamia lanceolata) plantation soils on purple sandstone hillslopes was investigated in ponded infiltration tests using brilliant blue dye. Veridical and horizontal infiltration patterns were photographed to assess morphological and distribution properties. Conductivity of preferential flow was 2.347#x2013;2.68 times as much as that of soil matrix flow, and thus increased the penetrability of plantation soils. Parameters ‘dye coverage’ (DC) and ‘distance to nearest point’ (DNP), obtained from computer image analysis, indicate that significant discrepancies on morphology of preferential flow exist in different age Chinese fir soils and the distribution of preferential flow is aggregative. ‘Pathway factor’, ‘root factor’ and ‘soil physical factor’ can explain 92% of the morphological variation by factor analysis. Plant growth and soil properties influence the formation mechanisms of preferential flow.
Whole-Genome Analysis of Candidate genes Associated with Seed Size and Weight in Sorghum bicolor Reveals Signatures of Artificial Selection and Insights into Parallel Domestication in Cereal Crops

Seed size and seed weight are major quality attributes and important determinants of yield that have been strongly selected for during crop domestication. Limited information is available about the genetic control and genes associated with seed size and weight in sorghum. This study identified sorghum orthologs of genes with proven effects on seed size and weight in other plant species and searched for evidence of selection during domestication by utilizing resequencing data from a diversity panel. In total, 114 seed size candidate genes were identified in sorghum, 63 of which exhibited signals of purifying selection during domestication. A significant number of these genes also had domestication signatures in maize and rice, consistent with the parallel domestication of seed size in cereals. Seed size candidate genes that exhibited differentially high expression levels in seed were also found more likely to be under selection during domestication, supporting the hypothesis that modification to seed size during domestication preferentially targeted genes for intrinsic seed size rather than genes associated with physiological factors involved in the carbohydrate supply and transport. Our results provide improved understanding of the complex genetic control of seed size and weight and the impact of domestication on these genes.