Miracle-dz/UniFAR-FTUs huggingface dataset:
Autogenerated manipulation primitives

The central theme in robotic manipulation is that of the robot interacting with the world through physical contact. We tend to describe that physical contact using specific words that capture the nature of the contact and the action, such as grasp, roll, pivot, push, pull, tilt, close, open etc. We refer to these situation-specific actions as manipulation primitives. Due to the nonlinear and nonsmooth nature of physical interaction, roboticists have devoted significant efforts towards studying individual manipulation primitives. However, studying individual primitives one by one is an inherently limited process, due engineering costs, overfitting to specific tasks, and lack of robustness to unforeseen variations. These limitations motivate the main contribution of this paper: a complete and general framework to autogenerate manipulation primitives. To do so, we develop the theory and computation of contact modes as a means to classify and enumerate manipulation primitives. The contact modes form a graph, specifically a lattice. Our algorithm to autogenerate manipulation primitives (AMP) performs graph-based optimization on the contact mode lattice and solves a linear program to generate each primitive. We designed several experiments to validate our approach. We benchmarked a wide range of contact scenarios and our pipeline’s runtime was consistently in the 10 s of milliseconds. In simulation, we planned manipulation sequences using AMP. In the real-world, we showcased the robustness of our approach to real-world modeling errors. We hope that our contributions will lead to more general and robust approaches for robotic manipulation.
AN ADAPTIVE NONMONOTONIC TRUST REGION METHOD WITH CURVILINEAR SEARCHES

在这篇论文，为采用两种信任区域技术和曲线的搜索的非强迫的优化的一个算法被建议。 在每次重复，我们解决其半径适应地被产生仅仅一次的信任区域潜水艇问题。 当潜水艇问题的答案是不能接受的时，非单调的回溯的曲线的搜索被执行。 全球集中和建议算法的快本地集中率在一些合理条件下面被建立。 数字实验的结果被报导显示出建议算法的有效性。
An Interpretable Gray Box Model for Ship Fuel Consumption Prediction Based on the SHAP Framework

Shipping companies and maritime organizations want to improve the energy efficiency of ships and reduce fuel costs through optimization measures; however, the accurate fuel consumption prediction of fuel consumption is a prerequisite for conducting optimization measures. In this study, the white box models (WBMs), black box models (BBMs), and gray box models (GBMs) are developed based on sensor data. GBMs have great potential for the prediction of ship fuel consumption, but the lack of interpretability makes it difficult to determine the degree of influence of different influencing factors on ship fuel consumption, making it limited in practical engineering applications. To overcome this difficulty, this study obtains the importance of GBM input characteristics for ship fuel consumption by introducing the SHAP (SHAPley Additive exPlanations) framework. The experimental results show that the prediction performance of the WBM is much lower than that of the BBM and GBM, while the GBM has better prediction performance by applying the a priori knowledge of WBMs to BBMs. Combining with SHAP, a reliable importance analysis of the influencing factors is obtained, which provides a reference for the optimization of ship energy efficiency, and the best input features for fuel consumption prediction are obtained with the help of importance ranking results.
A COMPARATIVE ANALYSIS OF TEXT CLASSIFICATION ALGORITHMS FOR POS AMBIGUITY USING WEKA

This paper presents an experimental study of supervised algorithms for text classification. Naive Bayes, Support Vector Machines, Random Forests, Decision Trees, KNNs, Neural Networks, and Logistic Regression have been compared. These algorithms are tested and compared on the Weka tool. For this experiment, a dataset of two thousand sentences with parts of speech ambiguity has been collected. The collected data are organized and pre-processed by removing stop words and feature extraction. The results of the comparison are based on the F-score, recall, and precision values returned by each algorithm. Results show that out of these seven classifiers, Decision Tree is computationally efficient and shows a higher accuracy percentage. To enhance the accuracy of the classified document, we have proposed a hybrid model. In this model, we have integrated the SVM, Decision Tree, and Naive Bayes’ algorithm to get a more accurate result as compared to Decision Tree. This classification approach is coined “AmbiF”. The accuracy of all analyzed algorithms ranges between sixty-six to eighty-four percent while for AmbiF model it is reported as eighty-five percent.
Incorporation of α-Tocopherol into Pea Protein Edible Film Using pH-Shifting and Nanoemulsion Treatments: Enhancing Its Antioxidant Activity without Negative Impacts on Mechanical Properties

The aim of this study is to develop an antioxidant film based on pea protein isolate (PPI) without sacrificing the packaging properties. To achieve this, α-tocopherol was incorporated to impart antioxidant activity to the film. We investigated the effects on film properties resulting from the addition of α-tocopherol in a nanoemulsion form and pH-shifting treatment of PPI. The results revealed that direct addition of α-tocopherol into un-treated PPI film disrupted film structure and formed a discontinuous film with rough surface, and thereby significantly decreasing the tensile strength and elongation at break. However, pH-shifting treatment in combination with the α-tocopherol nanoemulsion, formed a smooth and compact film, which greatly improved the mechanical properties. It also significantly changed the color and opacity of PPI film, but had little effects on film solubility, moisture content, and water vapor permeability. After the addition of α-tocopherol, the DPPH scavenging ability of PPI film was greatly improved and the release of α-tocopherol was mainly within the first 6 h. Additionally, pH-shifting and nanoemulsion did not affect the film’s antioxidant activity nor the release rate. In conclusion, pH-shifting combined with nanoemulsion is an effective method to incorporate hydrophobic compounds such as α-tocopherol into protein-based edible films without negative impacts on film mechanical properties.
Alteration of Blood Oxidative Stress Status in Patients with Thoracic Aortic Dissection: A Pilot Study

Background: Thoracic aortic dissection (TAD) is a life-threatening condition which usually occurs on an aneurysmal aortic wall. Although increasing data have shown that inflammation and oxidative stress play an important role in the patho-physiology of dissection, systemic oxidative stress status (OSS) has not been clearly determined in patients suffering from TAD. Methods: A cohort of 115 patients presenting type A or B TAD were admitted to our center from 2013 to 2017. Out of this cohort, 46 patients were included in a study on dissected aorta (LIege study on DIssected Aorta: LIDIA). In 18 out of the 46 patients, systemic OSS parameters were evaluated after TAD diagnosis by determination of eight different antioxidants, four trace elements, two markers of oxidative lipid damage and two inflammatory markers. Results: The 18 TAD patients included 10 men and 8 women (median age: 62 years; interquartile range: 55–68) diagnosed with type A (N = 8) or B (N = 10) TAD. Low plasma levels of vitamin C, β-carotene, γ-tocopherol, thiol proteins, paraoxonase and selenium were observed in these 18 patients. By contrast, the concentration of copper and total hydroperoxides, copper/zinc ratio, as well as inflammatory markers, were higher than the reference intervals. No difference was observed in oxidative stress biomarker concentrations between type A and B TAD patients. Conclusions: This pilot study, limited to 18 TAD patients, revealed a heightened systemic OSS, determined at 15.5 days (median) after the initial diagnosis, in those TAD patients without complications (malperfusion syndrome and aneurysm formation). Larger studies on biological fluids are needed to better characterize the oxidative stress and interpret its consequence in TAD disease.
Effect of Chicken Manure Fermentation Extract as an Alternative to Chemical Fertilizer on Cucumber Growth and Soil Microbiome Environment

ABSTRACT In recent years, the destruction of the soil environment caused by excessive application of chemical fertilizers has attracted attention to using organic fertilizers to replace chemical fertilizers. Previous studies have shown that chicken manure fermentation extract (CMFE) as an organic fertilizer may also directly influence soil nutrient availability from the soil native pool and fertilizer application. However, it is unclear whether application CMFE can partially replacing chemical fertilizer to reduce the amount of chemical fertilizer without reducing cucumber yield. Therefore, an experiment was conducted in Yantai Agricultural Science Academy of Shandong Province in 2018 and 2019. In 2018, five fertilization combinations were set up, namely CK (900 kg·ha−1 chemical fertilizer), T1 (750 kg·ha−1 chemical fertilizer +150 L·ha−1 CMFE), T2 (675 kg·ha−1 chemical fertilizer +225 L·ha−1 CMFE), T3 (600 kg·ha−1 chemical fertilizer +300 L·ha−1 CMFE) and T4 (525 kg·ha−1 chemical fertilizer +375 L·ha−1 CMFE). Selected the optimal combination T3 for testing in 2019. The yield, quality, photosynthesis and growth indicators of cucumber, as well as soil nutrients and microbial content were determined. The results showed that the fertilization combination of 600 kg·ha−1 chemical fertilizer +300 L·ha−1 CMFE (T3) can minimize the amount of chemical fertilizer used without reducing yield. Compared with conventional fertilizer application, CMFE partially replacing chemical fertilizer did not reduce cucumber yield, but significantly increased cucumber vitamin C and protein content. CMFE partially replacing chemical fertilizer increased the root to shoot ratio as well as the fresh and dry weight of vegetative organs in cucumber, optimizing the growth and development of cucumber. Compared with conventional fertilizer application, CMFE partially replacing chemical fertilizer increased the content of soil organic matter, improved the composition structure of soil microbial community, increased the relative abundance of Actinomycete and Acinetobacter, and reduced the relative abundance of Bacteroides, Ascomycota, and Basidiomycetes. Overall, CMFE partially replacing chemical fertilizer optimized the growth and development of cucumbers, increased the root to shoot ratio, increased soil organic matter content, increased microbial abundance and diversity, and improved the composition structure of soil microbial communities. Therefore, in order to reduce the use of fertilizers, it is recommended to partially replacing chemical fertilizers with CMFE, with the optimal combination of 600 kg·ha−1 chemical fertilizer +300 L·ha−1 CMFE (T3).
Evaluation of the agreement and reliability of Transpalpebral Tonometers compared with Goldmann Applanation Tonometer – A systematic Review and Meta-Analysis Protocol

In 2020, the global prevalence of glaucoma was estimated to be 76 million and it was projected to increase to 111.8 million by 2040. Accurate intraocular pressure (IOP) measurement is imperative in glaucoma management since it is the only modifiable risk factor. Numerous studies have compared the reliability of IOP measured using transpalpebral tonometers and Goldmann applanation tonometry (GAT). This systematic review and meta-analysis aims to update the existing literature with a reliability and agreement comparison of transpalpebral tonometers against the gold standard GAT for IOP measurement among individuals presenting for ophthalmic examinations. The data collection will be performed using a predefined search strategy through electronic databases. Prospective methods-comparison studies published between January 2000 and September 2022 will be included. Studies will be deemed eligible if they report empirical findings on the agreement between transpalpebral tonometry and Goldmann applanation tonometry. The standard deviation and limits of agreement between each study and their pooled estimate along with weights and percentage of error will be reported using a forest plot. Cochrane's Q test and the I2 statistic will be used to assess heterogeneity, and the publication bias will be investigated using a funnel plot, Begg's and Egger's tests. The review results will provide additional evidence on the reliability of transpalpebral tonometers that, in turn, could possibly assist practitioners to make informed decision about using it as a screening or diagnostic device for clinical practice, outreach camps, or home-based screening. Institutional Ethics Committee registration number: RET202200390. PROSPERO Registration Number: CRD42022321693.
Collaborative museum heist with reinforcement learning

Non‐playable characters (NPCs) play a crucial role in enhancing immersion in video games. However, traditional NPC behaviors are often hard‐coded using methods such as Finite State Machines, Decision and Behavior trees. This has a few limitations; namely, it is quite difficult to implement complex cooperative behaviors and secondly this makes it easy for human players to identify and exploit patterns in behavior. To overcome these challenges, Reinforcement learning (RL) can be used to generate dynamic and real‐time NPC responses to human player actions. In this paper, we report on first results of applying RL techniques to a Non‐Zero Sum, adversarial asymmetric game, using a multi‐agent team. The game environment simulates a museum heist, where the objective of the successfully trained team of robbers with different skills (Locksmith, Technician) is to steal valuable items from the museum without being detected by the scripted security guards and cameras. Both agents were trained concurrently with separate policies and received both individual and group reward signals. Through this training process, the agents learned to cooperate effectively and use their skills to maximize both individual and team benefits. These results demonstrate the feasibility of realizing the full game where both robbers and security guards are trained at the same time to achieve their adversarial goals.
Five-level cascaded H-bridge inverter for renewable energy applications

This paper presents a five-level inverter based on the phase-disposition pulse width modulation (PD-PWM) technique for renewable energy applications. The conventional cascaded H-bridge (CHB) five-level inverter structure is reproduced, and an LC filter is designed to get optimum results from the inverter output. Two batteries are used as renewable energy sources to investigate the performance of the designed inverter. The system can provide 220 volts and 50 Hz AC supply with a 6.9 kW power supply to the load/grid. The designed output is compared with filter and without filter circuit. It provides sinusoidal voltage and current output with a very low total harmonic distortion (THD) of 2.75% which is compliant with IEEE 519 standards. MATLAB/Simulink software tool is used for the entire design. The inverter’s output is graphically represented, and discussed various parameters like switching frequency, THD, modulation index, and rated voltage.
Pulse-Based ISAC: Data Recovery and Ranging Estimation for Multi-Path Fading Channels

Pulse-based integrated sensing and communication (ISAC) systems have the advantages of high ranging resolution and strong resistance to self-interference, compared with continuous wave (CW) based systems. However, for pulse-based ISAC systems, multi-path channels pose various challenges to data recovery and ranging by providing diversity gain for data recovery but incurring the interference to the identification of the first path in ranging. In this paper, we design a pulse-based ISAC receiver for multi-path channels. The designed receiver can obtain the diversity gain by correlating the received signal with the estimated template signal. Meanwhile, it can detect the arrival of the first path by using a threshold detection method based on a constant false alarm rate (CFAR). Furthermore, we extend the pulse-based ISAC design to a low-resolution analog-to-digital converter (ADC) scenario. A low-cost receiver design is provided for the pulse-based ISAC system that can recover data and estimate range simultaneously considering the non-linear effect caused by the low-resolution ADC. Simulation results show that compared with the generalized maximum likelihood (GML) based receiver, the proposed full-resolution pulse-based ISAC receiver has 1dB signal-to-noise ratio (SNR) loss in bit error rate (BER) and almost the same mean squared error (MSE) performance with the significantly reduced computational complexity. Also, compared with the full-resolution ISAC receiver, the ISAC receiver with 3-level quantization incurs only 0.8dB SNR loss in BER and 1dB SNR loss in MSE.
Ideal class groups, Hilbert's irreducibility theorem, and integral points of bounded degree on curves

R´´ Nousla construction et le comptage, pour tout couple d'entiers m,n > 1, des corps de nombres de degre n dont le groupe des classes possede un "grand" m-rang. Notre technique repose essentiellement sur le theoreme d'irreductibilite de Hilbert et sur des resultats concernant les points entiers de degre borne sur des courbes. Abstract. We study the problem of constructing and enumer- ating, for any integers m,n > 1, number fields of degree n whose ideal class groups have "large" m-rank. Our technique relies fun- damentally on Hilbert's irreducibility theorem and results on in- tegral points of bounded degree on curves.
Site Agnostic Approach to Early Detection of Cyberbullying on Social Media Networks

The rise in the use of social media networks has increased the prevalence of cyberbullying, and time is paramount to reduce the negative effects that derive from those behaviours on any social media platform. This paper aims to study the early detection problem from a general perspective by carrying out experiments over two independent datasets (Instagram and Vine), exclusively using users’ comments. We used textual information from comments over baseline early detection models (fixed, threshold, and dual models) to apply three different methods of improving early detection. First, we evaluated the performance of Doc2Vec features. Finally, we also presented multiple instance learning (MIL) on early detection models and we assessed its performance. We applied timeawareprecision (TaP) as an early detection metric to asses the performance of the presented methods. We conclude that the inclusion of Doc2Vec features improves the performance of baseline early detection models by up to 79.6%. Moreover, multiple instance learning shows an important positive effect for the Vine dataset, where smaller post sizes and less use of the English language are present, with a further improvement of up to 13%, but no significant enhancement is shown for the Instagram dataset.
Impact of ethical leadership, HRM practices and ethical climate on organizational citizenship behaviors in Nigerian local governments

PurposeThe increasing number of ethical scandals reported in many public organizations all over the world, highlighted the need for more in-depth studies on the influence of ethical leadership and management practices in the public sector organizations. This study examines the link (direct and indirect) between ethical leadership, HRM practices, ethical climate and organizational citizenship behaviors (OCBs) within the context of Nigerian local governments.Design/methodology/approachA cross-sectional design was adopted and data for the study was collected quantitatively by administering questionnaires to supervisors/leaders and their respective employees/subordinates. A total of 270 participants comprising 135 leaders/supervisors who are head of departments and another 135 employee/subordinates participated in the study. Partial Least Square Structural Equation Modeling (PLS-SEM) was used in testing the hypotheses.FindingsThe findings show that ethical leadership, HRM practices and ethical climate significantly affect OCBs. Also, the study shows that ethical climate mediated both the relationships between ethical leadership and OCBs, and HRM practices and OCBs respectively. Thus, the study concluded that both ethical leadership and HRM practices can influence OCBs directly and also indirectly through ethical climate.Practical implicationsThe study empirically delineates the importance of ethical leadership, HRM practices and ethical climate in promoting more OCBs within the context of Nigerian local governments. Therefore, managers/administrators should encourage ethical leadership style, and implement good HRM practices and promote ethical climate within their organization so as to boost their employees' OCBs.Originality/valueThe findings of this study will contribute to the understanding of the relationships between ethical leadership, HRM practices, ethical climate and OCBs in the public sector organizations within Nigeria. The findings will also provide additional support that ethical climate is an important mechanism on the relationship between ethical leadership and HRM practices on OCBs.
A monolithic approach for interaction of incompressible viscous fluid and an elastic body based on fluid pressure Poisson equation

This paper describes a new monolithic approach based on the fluid pressure Poisson equation (PPE) to solve an interaction problem of incompressible viscous fluid and an elastic body. The PPE is derived so as to be consistent with the coupled equation system for the fluid‐structure interaction (FSI). Based on this approach, we develop two kinds of efficient monolithic methods. In both methods, the fluid pressure is derived implicitly so as to satisfy the incompressibility constraint, and all other unknown variables are derived fully explicitly or partially explicitly. The coefficient matrix of the PPE for the FSI becomes symmetric and positive definite and its condition is insensitive to inhomogeneity of material properties. The arbitrary Lagrangian–Eulerian (ALE) method is employed for the fluid part in order to take into account the deformable fluid‐structure interface. To demonstrate fundamental performances of the proposed approach, the developed two monolithic methods are applied to evaluate the added mass and the added damping of a circular cylinder as well as to simulate the vibration of a rectangular cylinder induced by vortex shedding. Copyright © 2005 John Wiley & Sons, Ltd.
Recent Progress in Gels for Neuropathic Pain

Neuropathic pain is a complex and debilitating condition that affects millions of people worldwide. While several treatment options are available, they often have limited efficacy and are associated with adverse effects. In recent years, gels have emerged as a promising option for the treatment of neuropathic pain. Inclusion of various nanocarriers, such as cubosomes and niosomes, into gels results in pharmaceutical forms with higher drug stability and increased drug penetration into tissues compared to products currently marketed for the treatment of neuropathic pain. Furthermore, these compounds usually provide sustained drug release and are biocompatible and biodegradable, which makes them a safe option for drug delivery. The purpose of this narrative review was to provide a comprehensive analysis of the current state of the field and identify potential directions for future research in the development of effective and safe gels for the treatment of neuropathic pain, ultimately improving the quality of life for patients suffering from neuropathic pain.
A contour fluctuation data processing method for fire flame detection using a color camera

In fire detection using image processing, it is required that the system has enough robustness and elimination of the influence of disturbance. The authors have developed a method for fire flame detection, by calculating space-time fluctuation data on a contour of the flame colored area. In the paper, the fire flame detection algorithm using a color CCD camera is explained and the results of the experiment, performed to verify the effectiveness of our method, are demonstrated.