Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Partially Observable Non-Deterministic Action Models

Recently, interests in learning action models have been increasing. Although non-deterministic planning has been developed for several decades, most previous studies in the field of action model learning still focus on classical and deterministic action models. This paper presents an algorithm for identifying non-deterministic actions, including effects and preconditions, in partially observable domains. It can be applied when people know nothing about a transferring system and only the action-observation sequences are given. Such scenarios are common in real-world applications. This work focuses on problems in which actions are composed of simple logical structures and features are observed under some frequency. The learning process is divided into three steps: First, compute the probability of each proposition which holds in a state. Second, extract effect schema from propositions and then extract preconditions. Third, cluster effect schema to remove redundancy. Experimental results on benchmark domains show that action model learning is still useful in
Humility as a necessary virtue in common-law decision making

ABSTRACT Humility holds a modest but important place among the judicial virtues. But in spite of its growing popularity, it does not yet have a place on the ‘central judicial virtues’ lists. This paper provides an argument that judicial humility, especially institutional judicial humility, should be considered a necessary judicial virtue at least in common-law jurisdictions. This is because it is a necessary ingredient in precedent-based decisions that are fully justified from the point of view of the law and of political morality. Further, while it is sufficient that individual judges make decisions that a humble judge would have made, the judicial community must in fact be humble in order to produce fully justified common-law decisions – humility is therefore necessary as a community-virtue.
Instance Segmentation and Number Counting of Grape Berry Images Based on Deep Learning

In order to achieve accurate segmentation of each grape image per berry, we construct a dataset composed of red globe grape samples and use a two-stage “localization–segmentation” framework-based mask region convolutional neural network (Mask R-CNN) and one-stage “pixel classification without localization” framework-based You Only Look At CoefficienTs (YOLACT) and segmenting objects by locations (SOLO) models in the grape segmentation experiments. The optimal performance of the model Mask R-CNN was applied for further study. To address the problem of overlapping and occlusion causing inaccurate fruit detection in this model, the postprocessing algorithm of the Mask R-CNN model was improved by using the linear weighting method, and the experimental results were significantly improved. The model average precision (AP)0.50, AP0.75, the mean average precision (mAP), and the mean intersection of union (mIoU) improved by 1.98%, 2.72%, 4.30%, and 3.55%, respectively. The correlation coefficient was improved from 93.59% to 96.13% by using the improved Mask R-CNN to count the number of red globe grape berries, which also further illustrates that the fruit detection problem was well solved. Using the generalized method on untrained images of different grape varieties in different scenes also achieved good segmentation results. In this study, we provide a method for segmenting and counting grape berries that is useful for automating the grape industry.
Asymmetric Sulfoxidation by a Tyrosinase Biomimetic Dicopper Complex with a Benzimidazolyl Derivative of L-Phenylalanine

A challenge in mimicking tyrosinase activity using model compounds is to reproduce its enantioselectivity. Good enantioselection requires rigidity and a chiral center close to the active site. In this study, the synthesis of a new chiral copper complex, [Cu2(mXPhI)]4+/2+, based on an m-xylyl-bis(imidazole)-bis(benzimidazole) ligand containing a stereocenter with a benzyl residue directly bound on the copper chelating ring, is reported. Binding experiments show that the cooperation between the two metal centers is weak, probably due to steric hindrance given by the benzyl group. The dicopper(II) complex [Cu2(mXPhI)]4+ has catalytic activity in the oxidations of enantiomeric couples of chiral catechols, with an excellent discrimination capability for Dopa-OMe enantiomers and a different substrate dependence, hyperbolic or with substrate inhibition, for the L- or D- enantiomers, respectively. [Cu2(mXPhI)]4+ is active in a tyrosinase-like sulfoxidation of organic sulfides. The monooxygenase reaction requires a reducing co-substrate (NH2OH) and yields sulfoxide with significant enantiomeric excess (e.e.). Experiments with 18O2 and thioanisole yielded sulfoxide with 77% incorporation of 18O, indicating a reaction occurring mostly through direct oxygen transfer from the copper active intermediate to the sulfide. This mechanism and the presence of the chiral center of the ligand in the immediate copper coordination sphere are responsible for the good enantioselectivity observed.
XRecon: An Explainbale IoT Reconnaissance Attack Detection System Based on Ensemble Learning

IoT devices have grown in popularity in recent years. Statistics show that the number of online IoT devices exceeded 35 billion in 2022. This rapid growth in adoption made these devices an obvious target for malicious actors. Attacks such as botnets and malware injection usually start with a phase of reconnaissance to gather information about the target IoT device before exploitation. In this paper, we introduce a machine-learning-based detection system for reconnaissance attacks based on an explainable ensemble model. Our proposed system aims to detect scanning and reconnaissance activity of IoT devices and counter these attacks at an early stage of the attack campaign. The proposed system is designed to be efficient and lightweight to operate in severely resource-constrained environments. When tested, the implementation of the proposed system delivered an accuracy of 99%. Furthermore, the proposed system showed low false positive and false negative rates at 0.6% and 0.05%, respectively, while maintaining high efficiency and low resource consumption.
A Novel Aggregation-Induced Emission Fluorescent Probe for Detection of β-Amyloid Based on Pyridinyltriphenylamine and Quinoline–Malononitrile

β-amyloid is an important pathological feature of Alzheimer’s disease. Its abnormal production and aggregation in the patient’s brain is an important basis for the early diagnosis and confirmation of Alzheimer’s disease. In this study, a novel aggregation-induced emission fluorescent probe, PTPA-QM, was designed and synthesized based on pyridinyltriphenylamine and quinoline–malononitrile. These molecules exhibit a donor–donor–π–acceptor structure with a distorted intramolecular charge transfer feature. PTPA-QM displayed the advantages of good selectivity toward viscosity. The fluorescence intensity of PTPA-QM in 99% glycerol solution was 22-fold higher than that in pure DMSO. PTPA-QM has been confirmed to have excellent membrane permeability and low toxicity. More importantly, PTPA-QM exhibits a high affinity towards β-amyloid in brain sections of 5XFAD mice and classical inflammatory cognitive impairment mice. In conclusion, our work provides a promising tool for the detection of β-amyloid.
A Crustal Deformation Pattern on the Northeastern Margin of the Tibetan Plateau Derived from GPS Observations

The northeastern margin is a natural experimental field for studying crustal extrusion and expansion mechanisms. The accurate crustal deformation pattern is a key point in the analysis of regional deformation mechanisms and seismic hazard research and judgment. In this paper, the present-day GPS velocity field on the northeastern margin of the Tibetan Plateau was obtained from encrypted GPS observations around the Haiyuan–Liupanshan fault zone, combined with GPS observations on the northeastern margin of the Tibetan Plateau from 2010 to 2020. Firstly, we divided the study area into three relatively independent blocks: the ORDOS block, Alxa block, and Lanzhou block; secondly, the accurate fault distribution of the Haiyuan–Liupanshan fault zone was taken into account to obtain the optimal inversion model; finally, using the block and fault back-slip dislocation model, the inversion obtained the slip rate distribution, locking depth, and slip deficit rate of each fault. The results indicate that the Laohushan Fault and Haiyuan Fault are dominated by the left-lateral strike-slip, while the Liupanshan Fault is dominated by the thrust dip-slip, and the Guguan–Baoji Fault has both left-lateral strike-slip and thrust dip-slip components. The maximum locking depths of the Laohushan Fault, Haiyuan Fault, Liupanshan Fault, and Guguan–Baoji Fault are 5 km, 13 km, 15 km, and 10 km, respectively, and the locking of the Haiyuan Fault is strong in the middle section and weak in the eastern and western section. The Haiyuan Fault is still in the post-earthquake stress adjustment stage. The slip deficit rate decays from 3.6 mm/yr to 1.8 mm/yr from west to east along the fault zone. Combined with geological and historical seismic data, the results suggest that the mid-long-term seismic risk in the Liupanshan Fault is high.
Establishing Sex-Dependent Reference Intervals for KL-6 in Danish Adults

Krebs von den Lungen-6 (KL-6) is a promising biomarker for the diagnosis and prognosis of interstitial lung disease. However, reference intervals in Northern Europeans remain to be established using a latex-particle-enhanced turbidimetric immunoassay. The participants were Danish blood donors subjected to strict health requirements. Analyses were performed using the Nanopia KL-6 reagent on the cobas 8000 module c502. Sex-partitioned reference intervals were determined using a parametric quantile approach according to the Clinical and Laboratory Standards Institute guideline EP28-A3c. The study included 240 participants—121 females and 119 males. The common reference interval was 59.4–398.5 U/mL (95% confidence intervals (CI) for the lower and upper limits were 47.3–71.9 and 369.5–430.1, respectively). For females, the reference interval was 56.8–324.0 U/mL (95% CIs for the lower and upper limits were 36.1–77.6 and 303.3–344.7, respectively). For males, the reference interval was 51.5–448.7 U/mL (95% CIs for the lower and upper limits were 32.8–71.2 and 397.3–508.1, respectively). These results emphasize the importance of sex partitioning when evaluating KL-6 reference intervals. The reference intervals increase the clinical applicability of the KL-6 biomarker and provide a basis for future scientific studies of its utility in patient management.
Involvement of the Restoration of Cerebral Blood Flow and Maintenance of eNOS Expression in the Prophylactic Protective Effect of the Novel Ferulic Acid Derivative FAD012 against Ischemia/Reperfusion Injuries in Rats

Tissue plasminogen activator, aiming to restore cerebral blood flow (CBF), has been used for acute ischemic strokes in clinics; however, its narrow therapeutic time window remains a serious concern. To develop novel prophylactic drugs to alleviate cerebral ischemia/reperfusion injuries, ferulic acid derivative 012 (FAD012) was synthesized and showed comparable antioxidant properties to ferulic acid (FA) and probably possesses the potent ability to cross the blood–brain barrier. A more potent cytoprotective effect of FAD012 against H2O2-induced cytotoxicity in PC12 cells was also observed. In vivo toxicity was not observed in rats given a long-term oral administration of FAD012, indicating its good tolerability. A one-week-course oral administration of FAD012 significantly alleviated middle cerebral artery occlusion (MCAO)-induced cerebral ischemia/reperfusion injuries in rats, accompanied by the restoration of CBF and endothelial nitrogen oxide synthetase (eNOS) expression. Treatment with FAD012 significantly restored the cell viability and eNOS expression damaged by H2O2, used to mimic MCAO-triggered oxidative stress, in rat brain microvascular endothelial cells. Our findings suggested that FAD012 protected the viability of vascular endothelium and maintained eNOS expression, ultimately contributing to the restoration of CBF, and may provide a rationale for the development of FAD012 into an effective prophylactic drug for patients at high risk of stroke.
Surgical Treatment of Solitary Metachronous Adrenal Metastasis from Urothelial Carcinoma of the Urinary Bladder

Urothelial cancer is a common neoplasm and metastatic disease correlates with a poor prognosis. Isolated adrenal gland metastases of urothelial carcinoma are quite rare, and management options can decide a patient’s prognosis. Herein we report the case of a 76-year-old man with a metachronous solitary adrenal metastasis from a bladder carcinoma, who underwent adrenalectomy as part of his treatment. Furthermore, we discuss the cases of solitary adrenal metastases of urothelial carcinoma available in the literature, to identify key features to direct appropriate treatment of this rare metastatic site of urothelial cancer and improve prognosis and survival. Still, further prospective studies are needed to design effective therapeutic strategies.
Equivalent measure changes for subordinate diffusions

Abstract A subordinate diffusion is a Markovian jump-diffusion or pure jump process obtained by time changing a diffusion process with an independent Lévy or additive subordinator. This class of processes has found many applications in financial modeling. In this paper, we develop sufficient conditions and necessary conditions for the distributions of two subordinate diffusions to be equivalent, which are important for derivatives pricing and calibration. We obtain asymptotics for the jump intensity of a large class of subordinate diffusions near zero, which allow us to reduce these conditions to explicit restrictions on the model parameters that can be directly checked in applications. These asymptotics are also useful in detecting finiteness of the jump variation for these processes.
GraphSAGE-Based Dynamic Spatial–Temporal Graph Convolutional Network for Traffic Prediction

Traffic networks exhibit complex spatial-temporal dependencies, and accurately capturing such dependencies is critical to improving prediction accuracy. Recently, many deep learning models have been proposed for spatial-temporal dependency modeling. While numerous deep learning models have been developed for spatial-temporal dependency modeling, most rely on different types of convolutions to extract spatial and temporal correlations separately. To address this limitation, we propose a novel deep learning framework for traffic prediction called GraphSAGE-based Dynamic Spatial-Temporal Graph Convolutional Network (DST-GraphSAGE), which can capture dynamic spatial and temporal dependencies simultaneously. Our model utilizes a spatial-temporal GraphSAGE module to extract localized spatial-temporal correlations from past observations of a node’s spatial neighbors. Meanwhile, the attention mechanism is incorporated to dynamically learn weights between traffic nodes based on graph features. Additionally, to capture long-term trends in traffic data, we employ dilated causal convolution as the temporal convolution layer. A series of numerical experiments are conducted on five real-world datasets, which demonstrates the effectiveness of our model for spatial-temporal dependency modeling.
Residual Reinforcement Learning for Motion Control of a Bionic Exploration Robot—RoboDact

This article aims to investigate the motion control method of a bionic underwater exploration robot (RoboDact). The robot is equipped with a double-joint tail fin and two undulating pectoral fins to obtain good mobility and stability. The hybrid propulsion mode helps perform stable and effective underwater exploration and measurement. To coordinate these two kinds of bionic propulsion fins and address the challenge of measurement noises and external disturbances during underwater exploration, a novel residual reinforcement learning method with parameter randomization (PR-RRL) is proposed. The control strategy is a weighted superposition of a feedback controller and a residual controller. The observation feedback controller based on active disturbance rejection control (ADRC) is adapted to improve stability and convergence. And the residual controller based on the soft actor–critic (SAC) algorithm is adapted to improve adaptability to uncertainties and disturbances. Moreover, the parameter randomization training strategy is proposed for adapting natural complicated scenarios by randomizing the partial dynamics of the underwater exploration robot during the training phase. Finally, the feasibility and efficacy of the presented motion control method are validated by comprehensive simulation tests and RoboDact prototype physical experiments.
Permutation polynomial based interleavers for turbo codes over integer rings: theory and applications

Turbo codes are a class of high performance error correcting codes (ECC) and an interleaver is a critical component for the channel coding performance of turbo codes. Algebraic constructions of interleavers are of particular interest because they admit analytical designs and simple, practical hardware implementation. Sun and Takeshita [33] have shown that the class of quadratic permutation polynomials over integer rings provides excellent performance for turbo codes. Recently, quadratic permutation polynomial (QPP) based interleavers have been proposed into 3rd Generation Partnership Project Long Term Evolution (3GPP LTE) draft [55] for their excellent error performance, simple implementation and algebraic properties which admit parallel processing and regularity. In some applications, such as deep space communications, a simple implementation of deinterleaver is also of importance. In this dissertation, a necessary and sufficient condition is proven for the existence of a quadratic inverse polynomial (deinterleaver) for a quadratic permutation polynomial over an integer ring. Further, a simple construction is given for the quadratic inverse. We also consider the inverses of QPPs which do not admit quadratic inverses. It is shown that most 3GPP LTE interleavers admit quadratic inverses. However, it is shown that even when the 3GPP LTE interleavers do not admit quadratic inverses,
Effect of Supllementary Safflower Oil (Carthamus tinctorius)On Some Blood Paramerers of Common Carp (Cyprinus carpio L)

The experiment carried out in fishes labrotary in the college of agriculture /university of Baghdad for 75 days ,of common carp Cyprinus carpio distributed randomly with average weight 33.02gm fish on 15glass tan with dimensions of (60x40x40cm) and on five treatments experience in three replicates (7 fishes for glass),were fed on manufactured in labrotary with protein content between 23.62and 26.50 % and energy about 3021.45 and 3073.75 calorie/ kgm. The Results of the statistical analysis of of cholesterol showed no significant differences between treatment T3 (139.5) and T1, T2 and T4, which reached 146.2, 144.6 and 131.75 mg / dl respectively . The result cholesterol level checking decrease of triglycerides with increase the level of safflower oil in diet , it was the highest value for the T1 (210.15) mg/dl and the lowest value for T5it was 100.85 mg/dl. and no significant difference (p<0.01)for high density lipoproteins but the highest value was for T5 (49.10 mg/dl), and the result of low density lipoprotein show increase with increase of safflower oil it was the lowest value forT5(30.85, 31.10 mg/dl) We inference from this study the possibility of adding safflower oil, helping them control the cholesterol levels and lipoproteins in the blood of common carp.
Cosmetic and Pharmaceutic Products with Selected Natural and Synthetic Substances for Melasma Treatment and Methods of Their Analysis

Melasma is a fairly common condition that is the result of hyperpigmentation caused by increased melanin secretion. In the course of melasma, certain areas of the skin become darker than the rest of the epidermis. Although the pathogenesis remains incompletely clarified, several contributing factors have been identified, namely exposure to ultraviolet and visible light, family predisposition, pregnancy, and the use of exogenous hormones. Since current beauty standards associate healthy skin with its flawless and uniform color, people strive to eliminate any unaesthetic discoloration. Cosmetic and pharmaceutical products containing active substances with a whitening effect then become helpful. The most commonly used for this purpose are hydroquinone, arbutin, retinoids, organic acids (e.g., kojic, azelaic, and ellagic), and vitamins (B3, C, and E). However, the undesirable side effects they cause and the drive to replace synthetic chemicals with their natural counterparts have resulted in numerous reports on extracts of natural origin that exhibit skin-whitening effects. The purpose of this paper is to review the most recent scientific literature, which presents active substances of natural and synthetic origin with potential for the treatment of melasma. In addition, analytical techniques that can be used for qualitative and quantitative analysis of these substances present in cosmetic and pharmaceutical products will also be presented.
Rogue Waves: A Unifying Model of Human Seizure Propagation

Multiple Sources of Fast Traveling Waves During Human Seizures: Resolving a Controversy Schlafly ED, Marshall FA, Merricks EM, Eden UT, Cash SS, Schevon CA, Kramer MA. J Neurosci. 2022;42(36):6966-6982. doi:10.1523/JNEUROSCI.0338-22.2022 During human seizures organized waves of voltage activity rapidly sweep across the cortex. Two contradictory theories describe the source of these fast traveling waves: either a slowly advancing narrow region of multiunit activity (an ictal wavefront) or a fixed cortical location. Limited observations and different analyses prevent resolution of these incompatible theories. Here we address this disagreement by combining the methods and microelectrode array recordings (N = 11 patients, 2 females, N = 31 seizures) from previous human studies to analyze the traveling wave source. We find—inconsistent with both existing theories—a transient relationship between the ictal wavefront and traveling waves, and multiple stable directions of traveling waves in many seizures. Using a computational model that combines elements of both existing theories, we show that interactions between an ictal wavefront and fixed source reproduce the traveling wave dynamics observed in vivo. We conclude that combining both existing theories can generate the diversity of ictal traveling waves. Significance Statement: The source of voltage discharges that propagate across cortex during human seizures remains unknown. Two candidate theories exist, each proposing a different discharge source. Support for each theory consists of observations from a small number of human subject recordings, analyzed with separately developed methods. How the different, limited data and different analysis methods impact the evidence for each theory is unclear. To resolve these differences, we combine the unique, human microelectrode array recordings collected separately for each theory and analyze these combined data with a unified approach. We show that neither existing theory adequately describes the data. We then propose a new theory that unifies existing proposals and successfully reproduces the voltage discharge dynamics observed in vivo.