Miracle-dz/UniFAR-FTUs huggingface dataset:
RL4RS: A Real-World Benchmark for Reinforcement Learning based Recommender System

Reinforcement learning based recommender systems (RL-based RS) aims at learning a good policy from a batch of collected data, by casting sequential recommendation to multi-step decision-making tasks. However, current RL-based RS benchmarks commonly have a large reality gap, because they involve artiﬁcial RL datasets or semi-simulated RS datasets, and the trained policy is directly evaluated in the simulation environment. In real-world situations, not all recommendation problems are suitable to be transformed into reinforcement learning problems. Unlike previous academic RL research, RL-based RS suﬀers from extrapolation error and the diﬃculties of being well-validated before deployment. In this paper, we introduce the RL4RS (Reinforcement Learning for Recommender Systems) benchmark - a new resource fully collected from industrial applications to train and evaluate RL algorithms with special concerns on the above issues. It contains two datasets, tuned simulation environments, related advanced RL baselines, data understanding tools, and counterfactual policy evaluation algorithms. The RL4RS suit can be found at https://github.com/fuxiAIlab/RL4RS. In addition to the RL-based recommender systems, we expect the resource to contribute to research in reinforcement learning and neural combinatorial optimization.
Probabilistic orbits and dynamical masses of emission-line binaries

The observed orbits of emission-line stars may be affected by systematics owing to their broad emission lines being formed in complex and extended environments. This is problematic when orbital parameter probability distributions are estimated assuming radial-velocity data are solely comprised of Keplerian motion plus Gaussian white noise, leading to overconfident and inaccurate orbital solutions, with implications for the inferred dynamical masses and hence evolutionary models. We present a framework in which these systems can be meaningfully analysed. We synthesise benchmark datasets, each with a different and challenging noise formulation, for testing the performance of different algorithms. We make these datasets freely available with the aim of making model validation an easy and standardised practice in this field. Next, we develop an application of Gaussian processes to model the radial-velocity systematics of emission-line binaries, named marginalised $\mathcal {GP}$. We benchmark this algorithm, along with current standardised algorithms, on the synthetic datasets and find our marginalised $\mathcal {GP}$ algorithm performs significantly better than the standard algorithms for data contaminated by systematics. Finally, we apply the marginalised $\mathcal {GP}$ algorithm to four prototypical emission-line binaries: Eta Carinae, GG Carinae, WR 140, and WR 133. We find systematics to be present in several of these case studies; and consequently, the predicted orbital parameter distributions, and dynamical masses, are modified from those previously determined.
2020 State of the Octoverse: Securing the World's Software

Open source is the connective tissue for much of the information economy. You would be hard-pressed to find a scenario where your data does not pass through at least one open source component. Many of the services and technology we all rely on, from banking to healthcare, also rely on open source software. The artifacts of open source code serve as critical i infrastructure for much of the global economy, making the security of open source software mission-critical to the world.
Quantum field theories, Markov random fields and machine learning

The transition to Euclidean space and the discretization of quantum field theories on spatial or space-time lattices opens up the opportunity to investigate probabilistic machine learning within quantum field theory. Here, we will discuss how discretized Euclidean field theories, such as the ϕ 4 lattice field theory on a square lattice, are mathematically equivalent to Markov fields, a notable class of probabilistic graphical models with applications in a variety of research areas, including machine learning. The results are established based on the Hammersley-Clifford theorem. We will then derive neural networks from quantum field theories and discuss applications pertinent to the minimization of the Kullback-Leibler divergence for the probability distribution of the ϕ 4 machine learning algorithms and other probability distributions.
Detection of Driver Drowsiness by Calculating the Speed of Eye Blinking

Many road accidents are caused by drowsiness of the driver. While there are methods to detect closed eyes, it is a non-trivial task to detect the gradual process of a driver becoming drowsy. We consider a simple real-time detection system for drowsiness merely based on the eye blinking rate derived from the eye aspect ratio. For the eye detection we use HOG and a linear SVM. If the speed of the eye blinking drops below some empirically determined threshold, the system triggers an alarm, hence preventing the driver from falling into microsleep. In this paper, we extensively evaluate the minimal requirements for the proposed system. We find that this system works well if the face is directed to the camera, but it becomes less reliable once the head is tilted significantly. The results of our evaluations provide the foundation for further developments of our drowsiness detection system.
Human-Centered Explainable AI (XAI): From Algorithms to User Experiences

In recent years, the field of explainable AI (XAI) has produced a vast collection of algorithms, providing a useful toolbox for researchers and practitioners to build XAI applications. With the rich application opportunities, explainability is believed to have moved beyond a demand by data scientists or researchers to comprehend the models they develop, to an essential requirement for people to trust and adopt AI deployed in numerous domains. However, explainability is an inherently human-centric property and the field is starting to embrace human-centered approaches. Human-computer interaction (HCI) research and user experience (UX) design in this area are becoming increasingly important. In this chapter, we begin with a high-level overview of the technical landscape of XAI algorithms, then selectively survey our own and other recent HCI works that take human-centered approaches to design, evaluate, and provide conceptual and methodological tools for XAI. We ask the question"what are human-centered approaches doing for XAI"and highlight three roles that they play in shaping XAI technologies by helping navigate, assess and expand the XAI toolbox: to drive technical choices by users' explainability needs, to uncover pitfalls of existing XAI methods and inform new methods, and to provide conceptual frameworks for human-compatible XAI.
SLURP: Side Learning Uncertainty for Regression Problems

It has become critical for deep learning algorithms to quantify their output uncertainties to satisfy reliability constraints and provide accurate results. Uncertainty estimation for regression has received less attention than classification due to the more straightforward standardized output of the latter class of tasks and their high importance. However, regression problems are encountered in a wide range of applications in computer vision. We propose SLURP, a generic approach for regression uncertainty estimation via a side learner that exploits the output and the intermediate representations generated by the main task model. We test SLURP on two critical regression tasks in computer vision: monocular depth and optical flow estimation. In addition, we conduct exhaustive benchmarks comprising transfer to different datasets and the addition of aleatoric noise. The results show that our proposal is generic and readily applicable to various regression problems and has a low computational cost with respect to existing solutions.
What averages do not tell: predicting real life processes with sequential deep learning

Process Mining concerns discovering insights on business processes from their execution data that are logged by supporting information systems. The logged data (event log) is formed of event sequences (traces) that correspond to executions of a process. Many Deep Learning techniques have been successfully adapted for predictive Process Mining that aims to predict outcomes of processes, remaining time of the process execution, the next event, or even the entire suffix of running traces. Traces are multimodal sequences and very differently structured than the natural language sentences or images often used in Deep Learning. This may require a different approach to processing. Relevant challenges may be the skewness of trace-length distribution and of the activity distribution in real-life logs. So far, there has been little focus on these differences. For suffix prediction, the performance of Deep Learning models was evaluated only on average measures and for a small number of real-life logs with different pre-processing and evaluation strategies, which makes a comparison difficult. We provide an unified end-to-end framework and compare the performance of seven state-of-the-art sequential architectures in common settings. Results show that sequence modeling still has a lot of room for improvement for the majority of the more complex datasets. Further research is required to get consistent performance not just in average measures but over all the prefixes.
How to Fairly Allocate Easy and Difficult Chores

A major open question in fair allocation of indivisible items is whether there always exists an allocation of chores that is Pareto optimal (PO) and envy-free up to one item (EF1). We answer this question affirmatively for the natural class of bivalued utilities, where each agent partitions the chores into easy and difficult ones, and has cost 𝑝 > 1 for chores that are difficult for her and cost 1 for chores that are easy for her. Such an allocation can be found in polynomial time using an algorithm based on the Fisher market. We also show that for a slightly broader class of utilities, where each agent 𝑖 can have a potentially different integer 𝑝 𝑖 , an allocation that is maximin share fair (MMS) always exists and can be computed in polynomial time, provided that each 𝑝 𝑖 is an integer. Our MMS arguments also hold when allocating goods instead of chores, and extend to another natural class of utilities, namely weakly lexicographic utilities.
Accuracy of 3 Soft Tissue Prediction Methods After Double-Jaw Orthognathic Surgery in Class III Patients

Purpose We aimed to evaluate the accuracy and validity of conventional manual prediction method (CM) and 2-dimensional and 3-dimensional (3D) soft tissue prediction methods for Class III bimaxillary orthognathic surgery patients. Methods Twenty skeletal Class III patients were included in this study. Soft tissue prediction was achieved with a traditional manual technique, 2-dimensional software (Dolphin Imaging, version 11.5), and 3-dimensional software (SimPlant Master, version 16.0) on preoperative lateral cephalometric radiographs and cone beam computurized tomography (CBCT) images and then compared with postoperative lateral cephalometric radiographs obtained at least 6 months after surgery (mean, 11.5 ± 6.77 months). Forty-eight measurements were done to determine the reliability of the methods. Results All prediction methods have limited postsurgery prediction accuracy for the subnasal upper lip area. Most of the differences were not more than 3 mm for all study groups, except the 3D software, which predicted the upper lip area to be, on average, 3.08 ± 1.38 mm further back (P < 0.001). Although the conventional method predicted 20 of 48 measurements similar to the final results, the poorest predictions were found at the nasal and labiomental areas (P < 0.001). Two-dimensional software predicted 23 of 48 measurements very close to the final results but made significantly different predictions for the nasolabial and labiomental angles, labrale superius point, and the chin area. Conclusions The 3D method predicted, especially the upper lip area, to be significantly and clinically incorrect, and its soft tissue prediction was insufficient compared with the other 2 methods. The 3D software needs to be updated, especially in evaluating soft tissue A point and upper lip changes after surgery.
Differential Effect of Atpenin A5 on ROS Production from Wild- Type Mitochondrial Complex II in Human Cancer Cells and Normal Cells

Human mitochondrial complex II is an intriguing enzyme, which has been the focus of medical research during the past few decades since it contributes to pathogenesis of mitochondrial diseases as well as a target for chemotherapy. Reactive oxygen species (ROS) pro- duced by this enzyme has been implicated in both these conditions. While ROS produced from mutated mitochondrial complex II has been implicated in pathogenesis of mitochon- drial diseases, ROS produced from pharmacologically inhibited mitochondrial complex II has been implicated in cancer cell death. In this chapter, we show that inhibition of mito- chondrial complex II in human cancer cells with atpenin A5 produces detectable levels of ROS while normal cells do not. Thus, this enzyme may be used as a potential target for developing new anticancer drugs to trigger ROS-mediated selective death of cancer cells. isolation buffer without sodium resuspended in the same buffer, and stored on ice until analysis. Integrity of the mitochondria was analyzed by citrate synthase activity in the presence and absence of 0.05% sucrose monolaurate (SML) in the assay mixture. the difference in ROS production observed in this study is attributed to the difference in posttranslational modifications of mitochondrial complex II between normal cells and cancer cells, may under and microenvironments.
The Modified 11-Item Frailty Index and Postoperative Outcomes in Patients Undergoing Lateral Lumbar Interbody Fusion

An modified 11-item frailty index score was found to be independently associated with urologic complications in patients who underwent lateral lumbar interbody fusion (LLIF). Patients in all frailty categories experienced significant improvements in back pain, leg pain, and the Oswestry Disability Index at 1 year postoperatively. LLIF surgery may be useful for patients with high frailty index. Study Design. Retrospective cohort study. Objective. The aim of this study was to analyze postoperative complications and recovery patterns in different modified 11-item frailty index (mFI-11) groups after lateral lumbar interbody fusion (LLIF) surgery. Summary of Background Data. The relationship between the mFI-11 score and LLIF surgery has not been previously reported. Methods. A single-center, consecutive series of patients who underwent LLIF with at least two years of follow-up were retrospectively reviewed. Complications after LLIF surgery were recorded. Clinical outcomes, including the visual analog scale (VAS) for back/leg pain and the Oswestry Disability Index (ODI), were evaluated preoperatively and at 1 and 2 years postoperatively. The proportions of patients who achieved substantial clinical benefit (SCB) for the VAS-B, VAS-L, and ODI were also analyzed. Results. One hundred fifty-two patients included in the present study were grouped according to their mFI-11 score: 0 (n = 39), 0.09 (n = 69), 0.18 (n = 31), and ≥0.27 (n = 13). An mFI-11 score ≥0.27 was a significant predictor of urinary complications (adjusted odds ratio: 3.829, P = 0.013). At 2 years postoperatively, patients in all frailty categories experienced improvements in the VAS for back pain, VAS for leg pain, and ODI, without significant differences between the four groups (p = 0.182, 0.121, and 0.804, respectively). There were also no significant differences in the proportions of patients achieving SCB for back/leg pain and the ODI between the four groups (P = 0.843, 0.957, and 0.915, respectively). Conclusion. An mFI-11 score was found to be independently associated with urologic complications in patients who underwent LLIF. Patients in all frailty categories experienced significant improvements in back pain, leg pain, and the ODI at 1 year and 2 years postoperatively. LLIF surgery may be useful for patients with high frailty index. Level of Evidence: 4
Feasibility and outcome of the Rotapro system in treating severely calcified coronary lesions: The Rotapro study

Background The Rotapro study was conducted to evaluate the safety and feasibility of the new Rotapro rotational atherectomy system (RAS) for lesion preparation in calcified coronary artery stenosis. Methods Between 2015 and 2019 consecutive patients undergoing rotational atherectomy (RA) with the new Rotapro system and the conventional rotablator (Rotablator) were included from the Bad Krozingen Rotablation Registry. The primary endpoint was the incidence of in-hospital major adverse cardiovascular and cerebral event (MACCE) rate. Results Rotablation was performed in 3.6% of all patients (n = 597) treated by percutaneous coronary intervention. Procedural outcomes were compared according to the applied RAS (n = 246 Rotapro vs. n = 351 Rotablator). Overall technical success was achieved in 98.3% of patients. The primary endpoint of in-hospital MACCE was comparable between the Rotapro- and the Rotablator-group (3.7% vs. 5.7%, respectively, p = 0.254). The Rotapro group was associated with significant reductions of fluoroscopy time (30 vs. 38 min, p < 0.0001), procedural time (82.5 vs. 96 min, p = 0.0003), applied contrast volume (210 vs. 290 mL, p < 0.0001) and radiation dose (6129 vs. 9827 cGy*cm2, p < 0.0001) compared to the Rotablator group. Conclusions The present study demonstrates the safety and efficacy of the new Rotapro system. Inhospital MACCE rates were comparable between both RAS, whereas Rotapro was associated with less fluoroscopy time, radiation dose as well as contrast use.
Spore Germination Apparatus in Clostridium botulinum Group I and II

Spore germination is a significant step in the transformation of dormant spores into exponentially dividing vegetative cells, and in the case of Clostridium botulinum in the formation of the deadly botulinum neurotoxin. The ability of nutrient and non-nutrient germinants to induce germination of strains Af84 (C. botulinum Group I) and Eklund 17B (C. botulinum Group II) was established by measuring the change in optical density and by microscopic observation. Germination of strains Af84 and Eklund 17B was initiated by the nutrient germinants L-alanine and L-cysteine and the non-nutrient germinants dodecylamine (DDA) and lysozyme, but not by calcium dipicolinic acid (CaDPA). Heating spores of strain Af84 for 4 hours at 95°C delivered a 3-log reduction in viability. Heat damaged spores of strain Af84 could not be recovered using lysozyme, L-alanine or DDA. Thermal death of spores of strain Eklund 17B occurred within 2 minutes of heating at 85°C, and resulted in a 5-log reduction in viability. The presence of lysozyme (10μg/ml) increased the recovery of heat damaged spores of strain Eklund 17B, however, the presence of L-alanine and DDA had no effect. The timing of DPA release in relation to cortex hydrolysis is still unknown in C. botulinum, however this study found that DPA is released within 18 hours of germinant addition in strain Af84 and within 50 minutes for strain Eklund 17B. In addition, the average DPA concentration per spore of strains Af84 and Eklund 17B was shown to be 1.9pg and 2.1pg, respectively. Results obtained indicate that part of the germination apparatus in Group II strain Eklund 17B is damaged by heating, rather than the spore DNA. Understanding the mechanisms involved in spore germination can improve the control of botulinum neurotoxin forming clostridia, prevent foodborne botulism, and thereby contribute to the microbiological safety of foods.
Parental acculturation and oral health of children among immigrants.

OBJECTIVES This cross-sectional study aimed to examine the associations between parental acculturation level and strategies and children's caries experience and oral health (OH) behaviors. METHODS Participants were immigrant parents of children aged 2-12 years. Data were collected by validated questionnaires gathering information on socio-demographics, child's OH behaviors, and parents'; acculturation and dental examinations determining child's caries experience using DMFT/dmft index. Univariate and multivariate regression analyses were used. RESULTS Three hundred and thirty-six parent/child dyads completed the study. Length of residency (B = 0.103; 95% CI: 0.064, 0.141) parents' education (B = 1.691; 95% CI: 1.228, 2.155), and household income (B = -0.959; 95% CI: -1.566, -0.352) significantly predicted acculturation level. Parents with high Canadian cultural knowledge reported higher frequency of children's toothbrushing (p-value = 0.015). Parents of children who consumed sugar >1/day had higher mean scores of acculturation to Canadian culture (p-value = 0.016), English language proficiency (p-value = 0.024), and Canadian food adoption (p-value = 0.046). Parents of children who visited the dentist within last 12 months had significantly higher assimilation and lower separation mean scores. Parents of children who visited dentist because of dental problems had higher marginalization mean score than those who went for check-ups (p-value = 0.046). Parental acculturation was not significantly correlated with their children's dmft/DMFT level. CONCLUSIONS Children of highly acculturated parents reported higher toothbrushing frequency and were more likely to consume sugar than children of less acculturated parents. Assimilated parents reported more and marginalized parents reported less favorable OH behaviors than other categories. Parental acculturation level or strategy was not associated with children's caries experience.
Poly-gamma-glutamic acid-vitamin complex and use thereof

Provided are a poly-gamma-glutamic acid-vitamin complex and use thereof. The poly-gamma-glutamic acid(PGA)-vitamin complex increases stability and absorption of vitamin, and enhances sustained release of vitamin. The PGA-vitamin complex also has excellent skin-compatibility, water-retention and absorption. The poly-gamma-glutamic acid-vitamin complex is provided, wherein a hydroxy group of water-soluble vitamin C, fat-soluble vitamin D or derivatives thereof is bound to a carboxyl group of poly-gamma-glutamic acid through a ester bond; the poly-gamma-glutamic acid-water-soluble vitamin C complex is represented by formula (I); the poly-gamma-glutamic acid-fat-soluble vitamin D complex is represented by formula (II); the derivative of water-soluble vitamin C is ethylascorbyl ether, magnesium ascorbyl phosphate, ascorbic acid 2-glucoside or allantoin ascorbate; the derivative of fat-soluble vitamin D is ergocalciferol or cholescalciferol; and the poly-gamma-glutamic acid is produced by Bacillus subtilis.