nils-herrmann/clean_scirepeval huggingface dataset:
Introduction to Tensor Decompositions and their Applications in Machine Learning
Venue: ArXiv
Year: 2017

Tensors are multidimensional arrays of numerical values and therefore generalize matrices to multiple dimensions. While tensors first emerged in the psychometrics community in the $20^\text{th} century, they have since then spread to numerous other disciplines, including machine learning. Tensors and their decompositions are especially beneficial in unsupervised learning settings, but are gaining popularity in other sub disciplines like temporal and multi relational data analysis, too. The scope of this paper is to give a broad overview of tensors, their decompositions, and how they are used in machine learning. As part of this, we are going to introduce basic tensor concepts, discuss why tensors can be considered more rigid than matrices with respect to the uniqueness of their decomposition, explain the most important factorization algorithms and their properties, provide concrete examples of tensor decomposition applications in machine learning, conduct a case study on tensor based estimation of mixture models, talk about the current state of research, and provide references to available software libraries.
Non local L_0 L 0 Gradient Minimization Filter and Its Applications for Depth Image Upsampling
Venue: ICIG
Year: 2017

In this work, we propose a non local (L_{0} gradient minimization filter. The nonlocal idea is to restore an unknown pixel using other similar pixels, and the nonlocal gradient model has been verified for feature and structure preserving. We introduce the nonlocal idea into a (L_{0} gradient minimization approach, which is effective for preserving major edges while eliminating the low amplitude structures. An optimization framework is designed for achieving this effort. Many optimized based filters do not have the property of joint filtering, so they can not be used in many problems, such as joint denoising, joint upsampling, while the proposed filter not only inherits the advantages of the (L_{0} gradient minimization filter, but also has the property of the joint filtering. So our filter can be applied to joint super resolution. With the guidance of the high resolution image, we propose upsampling the low resolution depth image with the proposed filter. Experimental results demonstrate the effectiveness of our method both qualitatively and quantitatively compared with the state of the art methods.
Family Struggles and Substance use among First Generation College Students
Year: 2015

Data for the current study was collected from a large southeastern research university. A total of 902 college students completed an online questionnaire and received class credit or extra credit for their participation. The majority of participants were female (n 647, 71.7% and identified as white (n 613, 68% The age of participants ranged from 18 to 59 (M 21.58) Two hundred and two participants (22.4% indicated that they were first generation students.
An Insider Threat Detection Method Based on User Behavior Analysis
Venue: Intelligent Information Processing
Year: 2018

Insider threat has always been an important hidden danger of information system security, and the detection of insider threat is the main concern of information system organizers. Before the anomaly detection, the process of feature extraction often causes a part of information loss, and the detection of insider threats in a single time point often causes false positives. Therefore, this paper proposes a user behavior analysis model, by aggregating user behavior in a period of time, comprehensively characterizing user attributes, and then detecting internal attacks. Firstly, the user behavior characteristics are extracted from the multi domain features extracted from the audit log, and then the XGBoost algorithm is used to train. The experimental results on a user behavior dataset show that the XGBoost algorithm can be used to identify the insider threats. The value of F measure is up to 99.96% which is better than SVM and random forest algorithm.
Release optimization of fermentable sugars from defatted rice bran for bioethanol production
Year: 2018

The aim of this study was to optimize the enzymatic hydrolysis of defatted rice bran (DRB) for release fermentable sugars with subsequent bioethanol production. Optimization of enzymatic hydrolysis was achieved using a sequential experimental design, performing a fractional factorial design (FFD) followed by two Central Composite Rotatable Designs (CCRDs) The optimization was achieved under the conditions of 200 g L 1 of DRB concentration, 30 mL of a amylase g 1 of DRB and 40 mL g 1 of amyloglucosidase (AMG) at action times of two and three hours, respectively. In bioethanol production, it was evaluated the effect of adding of 15 mL g 1 of protease prior to the action of amylases. Fermentation was conducted at 29degC, with 4.0% Saccharomyces cerevisiae and initial pH of 5.0. The hydrolysis with protease yielded 3.55% ethanol, an increase of 115.15% in relation to the medium without protease addition, and the conversion had a yield of 101.5% in 24h of alcoholic fermentation. This study demonstrates the possibility to obtain bioethanol from DRB.
Performance of vehicle speed estimation using wireless sensor networks: a region based approach
Venue: The Journal of Supercomputing
Year: 2014

In this paper, a novel region based approach for estimating the speed of a vehicle using wireless sensor networks is presented. Compared with a point based approach, which is used to determine the vehicle arrival and departure points separately in each node, the proposed region based approach is used to determine the speed of a vehicle at the server using the similarities among the sensor data received from two sensor nodes. In the proposed approach, a moving average filter is applied to reduce noise in the sensor reading. Next, N samples of data around a feature point with a first order derivative larger than the chosen threshold are recorded. Delta coding is then applied to compress the data and minimize the power consumption required for communication from the sensor nodes to the server. Finally, the similarity of the data received from the two sensor nodes is measured to estimate the speed of the vehicle. More specifically, a similarity measure, a modified version of a cross correlation function, is proposed. In addition, an evolutionary programming technique is adopted to find the optimal parameters for the threshold value of the first order derivative and the number of samples that need to be sent to the server. Experimental results are provided to show the effectiveness of the proposed region based vehicle speed estimation approach.
Spectroscopic Investigations, DFT Calculations, and Molecular Docking Studies of the Anticonvulsant (2E) 2 [3 (1H Imidazol 1 yl) 1 phenylpropylidene] N (4 methylphenyl)hydrazinecarboxamide
Year: 2016

Drug discovery for the management of neurological disorders is a challenging arena in medicinal chemistry. Vibrational spectral studies of (2E) 2 [3 (1H imidazol 1 yl) 1 phenylpropylidene] N (4 methylphenyl)hydrazinecarboxamide (2E) IPPMP) have been recorded and analyzed to identify the functional groups and intermolecular/intramolecular interactions of the title molecule. The blue shift of the C H stretching wavenumber reveals the presence of improper C HO hydrogen bonding. The equilibrium geometry, harmonic vibrational wavenumbers, Frontier orbital energy, and natural bond orbital analyses have been carried out using density functional theory with a B3LYP/6 311
An ingeniously assembled metal organic framework on the surface of FeMn co doped Ni(OH)2 as a high efficiency electrocatalyst for the oxygen evolution reaction.
Venue: Dalton transactions
Year: 2021

To overcome the problem of the sluggish kinetics of the oxygen evolution reaction (OER) it is of great significance to develop an efficient and stable non noble metal based OER catalyst for electrocatalytic energy conversion and storage. Herein, a complex of a metal organic framework and hydroxide is synthesized by performing a ligand etching strategy on FeMn co doped Ni(OH)2 nanosheets in situ grown on nickel foam (FeMn Ni(OH)2@MOF/NF) Benefiting from the unique sheet on sheet hierarchical structure, multi metal active nodes and two active materials grown in situ, the resulting FeMn Ni(OH)2@MOF/NF demonstrated brilliant OER activity with an overpotential of 199 mV to achieve a current density of 10 mA cm 2 and long term stability. This research will provide a new strategy for the design of high performance OER electrocatalysts.
TransNFCM: Translation Based Neural Fashion Compatibility Modeling
Venue: AAAI
Year: 2019

Identifying mix and match relationships between fashion items is an urgent task in a fashion e commerce recommender system. It will significantly enhance user experience and satisfaction. However, due to the challenges of inferring the rich yet complicated set of compatibility patterns in a large e commerce corpus of fashion items, this task is still underexplored. Inspired by the recent advances in multirelational knowledge representation learning and deep neural networks, this paper proposes a novel Translation based Neural Fashion Compatibility Modeling (TransNFCM) framework, which jointly optimizes fashion item embeddings and category specific complementary relations in a unified space via an end to end learning manner. TransNFCM places items in a unified embedding space where a category specific relation (category comp category) is modeled as a vector translation operating on the embeddings of compatible items from the corresponding categories. By this way, we not only capture the specific notion of compatibility conditioned on a specific pair of complementary categories, but also preserve the global notion of compatibility. We also design a deep fashion item encoder which exploits the complementary characteristic of visual and textual features to represent the fashion products. To the best of our knowledge, this is the first work that uses category specific complementary relations to model the category aware compatibility between items in a translation based embedding space. Extensive experiments demonstrate the effectiveness of TransNFCM over the state of the arts on two real world datasets.
Evaluation of an inflammation based prognostic score in patients with inoperable gastro oesophageal cancer
Venue: British Journal of Cancer
Year: 2006

There is increasing evidence that the presence of an ongoing systemic inflammatory response is associated with poor outcome in patients with advanced cancer. The aim of the present study was to examine whether an inflammation based prognostic score (Glasgow Prognostic score, GPS) was associated with survival, in patients with inoperable gastro oesophageal cancer. Patients diagnosed with inoperable gastro oesophageal carcinoma and who had measurement of albumin and C reactive protein concentrations, at the time of diagnosis, were studied (n=258) Clinical information was obtained from a gastro oesophageal cancer database and analysis of the case notes. Patients with both an elevated C reactive protein >10 mg l 1) and hypoalbuminaemia <35 g l 1) were allocated a GPS score of 2. Patients in whom only one of these biochemical abnormalities was present were allocated a GPS score of 1, and patients with a normal C reactive protein and albumin were allocated a score of 0. On multivariate survival analysis, age (hazard ratio (HR) 1.22, 95% CI 1.02 1.46, P<0.05) stage (HR 1.55, 95% CI 1.30 1.83, P<0.001) the GPS (HR 1.51, 95% CI 1.22 1.86, P<0.001) and treatment (HR 2.53, 95% CI 1.80 3.56, P<0.001) were significant independent predictors of cancer survival. A 12 month cancer specific survival in patients with stage I/II disease receiving active treatment was 67 and 60% for a GPS of 0 and 1, respectively. For stage III/IV disease, 12 months cancer specific survival was 57, 25 and 12% for a GPS of 0, 1 and 2, respectively. In the present study, the GPS predicted cancer specific survival, independent of stage and treatment received, in patients with inoperable gastro oesophageal cancer. Moreover, the GPS may be used in combination with conventional staging techniques to improve the prediction of survival in patients with inoperable gastro oesophageal cancer.
Darwinolide, a New Diterpene Scaffold That Inhibits Methicillin Resistant Staphylococcus aureus Biofilm from the Antarctic Sponge Dendrilla membranosa
Venue: Organic letters
Year: 2016

A new rearranged spongian diterpene, darwinolide, has been isolated from the Antarctic Dendroceratid sponge Dendrilla membranosa. Characterized on the basis of spectroscopic and crystallographic analysis, the central seven membered ring is hypothesized to originate from a ring expansion of a spongian precursor. Darwinolide displays 4 fold selectivity against the biofilm phase of methicillin resistant Staphylococcus aureus compared to the planktonic phase and may provide a scaffold for the development of therapeutics for this difficult to treat infection.
Overview of Botulinum Toxins for Aesthetic Uses.
Venue: Clinics in plastic surgery
Year: 2016

Botulinum toxin type A (BTA) can be used for facial aesthetics. The 3 currently available BTA types include onabotulinumtoxinA (Botox; Botox Cosmetic, Allergan, Irvine, CA) abobotulinumtoxinA (Dysport; Ipsen, Ltd, Berkshire, UK) and incobotulinumtoxinA (Xeomin; Merz Pharmaceuticals, Frankfurt, Germany) The mechanism of action and clinical uses for treatment of dynamic lines of the forehead, brow, glabella, lateral orbit, nose, and lips are presented, as well as treatment of masseter hypertrophy, platysmal bands, and improvements of the perioral region. Specific BTA injection sites and suggested doses are presented.
Maximizing Social Media Application for Students in Learning English
Year: 2020

In this modern society, social media is widely used especially for millennials. Besides entertainment and communication, social media can be used for education. This article aims to investigate the role of a social media application in learning English. This work focus on how social media can be used for learning English in students' daily activity. The online survey is used in distributing several students. In this part, 127 students responded to this survey and they answered the questionnaire distributed. From their answers, it can be concluded that social media take a part in learning English. They communicate through social media in English and many articles, video, news, and others. in English. They are pushed to be able to understand it. Furthermore, they sometimes get additional material and information from lecturer and classmates through social media such as WhatApps or Line. They said they improve their English skills such as speaking and listening (in term of vocabulary and structure) It is recommended for us to be able to speak English because now the development of technology uses English as the default language. That is why having social media for students is a good way to learn English. Lecturers can take this chance to teach English through social media.
THE INFLUENCE OF VEHICLE AXLE CONFIGURATION AGAINST BACK AND MAXIMUM DEFLECTION DUE TO EXCESSIVE LOAD WITH BENKELMAN BEAM TOOLS
Year: 2018

he cause of early damage to road sections in Indonesia is still a matter of debate among expert and road expert. But it was pointed out that many parties that these early damages were likely caused by the age of the road plan that had been passed, the puddle of water on the road surface that could not flow due to poor drainage, excessive overloaded traffic loads which caused more road life short of planning. The research was carried out on the local road which was assumed to represent the condition of the thickness of the flexible pavement layer, with one hope that it could be known the reverse deflection and maximum deflection on the road section. The research was conducted by looking at the back deflection and the maximum deflection that occurred due to variations in loading and variations in commercial vehicle axle configuration. Vehicle axle configurations used in this research is Single Axle Dual Wheel (SADW) Single Axle Single Wheel (SASW) and Dual Axle Tandem Wheel (TADW) SADW and SASW are represented by Truck 1.2 H, TADW is represented by Truk 1.22. The results of the research, data analysis and calculation process obtained the maximum deflection magnitude right on the vehicle axle (mc) can be determined by making a deflection ratio, Dm30 Dmc so that it is obtained Dmc Dm30 Drc because of the Dr30 Drc Dr30 magnitude (m30 p x r30) and magnitude (rc q x r30) then the magnitude Dmc (p Dr30 (q Dr30 p q Dr30. For reverse deflection value, SADW with vehicle load 14.24 tons and rc Dr30 1,05mm, and TADW with vehicle load 16.73 tons and rc 0,48mm for maximum deflection value SADW 14.24 tons mc 1,18 mm, TADW 16,73 ton mc 0,58 mm and maximum deflection for PSADW Single Axle Single Wheel sasw (SASW) PSADW 14,24 ton PSASW 4,62 ton D D P 0,27 mm.
Multi sensor marginalized particle filter based on average weight optimization in correlated noise
Year: 2016

Particle filter is a kind of powerful and effective simulation based method to perform optimal state estimation in nonlinear non Gaussian state space models. However, its main drawback is with large computational complexity and not suitable for noise correlation condition, which limits its application in the multi sensor measurement system. Aiming at the above problem, a novel multi sensor marginalized particle filter based on average weight optimization in correlated noise is proposed. First, marginalized particle filter is used as the basic framework of new algorithm realization by marginalizing the states appearing linearly in the dynamical system, and the objective is to reduce the calculated amount. Second, considering the rational utilization of multi sensor measurement, the average weight optimization strategy is used to improve the adverse influence caused by random measurement noise in measuring process of particles weight. Third, combining with the model reconstruction technology, a new decoupling approach of correlated noise is designed in multi sensor measurement. Finally, the theoretical analysis and experimental results show the feasibility and efficiency of the proposed algorithm.
An advanced adaptive backstepping control method for STATCOM
Venue: The 26th Chinese Control and Decision Conference (2014 CCDC)
Year: 2014

An innovative approach to high robustness and anti interference performance for static synchronous compensator (STATCOM) control systems is proposed to address the problems including parameter uncertainties and external disturbances which often deteriorate system performance significantly. Improvement is made in three aspects. Firstly, the adaptive backstepping control has been adopted to design the state feedback control law and improve the transient stability of the STATCOM recursively. Secondly, In order to reduce high degree of coupling between the states and the estimation error, the adaptive law and the state feedback control law are designed separately by using the immersion and invariance adaptive (I&I adaptive) control. Thirdly, the dissipation inequality is constructed between energy storage function and an energy supply function in each step. This can get a certificate theoretically that the energy is dissipated and the robustness of the control system. Moreover, the compared simulations show that more rapid speed response and stronger robustness can be obtained by the proposed approach than other advanced algorithms under the same conditions.
Clinical characteristics of non alcoholic fatty liver disease in Chinese adult hypopituitary patients
Venue: World journal of gastroenterology
Year: 2019

Patients with hypothalamic pituitary disease have the feature of central obesity, insulin resistance, and dyslipidemia, and there is increased prevalence of liver dysfunction consistent with non alcoholic fatty liver disease (NAFLD) in this population. The causes of hypopituitarism in the reported studies varied and combined pituitary hormone deficiency including central diabetes insipidus is much common in this population. This retrospective cross sectional study was performed to analyze the clinical characteristics and related factors with NAFLD and cirrhosis in Chinese adult hypopituitary/panhypopituitary patients.  To analyze the clinical characteristics of and related risk factors for NAFLD in Chinese adult hypopituitary patients.  Adult Chinese patients with hypopituitarism and/or panhypopituitarism were enrolled at the Pituitary Center of Peking Union Medical College Hospital between August 2012 and April 2018. According to abdominal ultrasonography, these patients were divided into an NAFLD group and an NAFLD group, and the latter was further divided into an NAFLD group and a cirrhotic group. The data, such as patient characteristics, diagnosis, and treatment, were extracted from medical records, and statistical analysis was performed.  A total of 36 male and 14 female adult Chinese patients with hypopituitarism were included in this retrospective study; 43 (87.0% of these patients exhibited growth hormone (GH) deficiency, and 39 (78.3% had diabetes insipidus. A total of 27 (54.0% patients were diagnosed with NAFLD, while seven patients were cirrhotic. No significant differences were noted in serum GH or insulin like growth factor 1 among patients with cirrhosis, subjects with NAFLD, and those without NAFLD. However, plasma osmolality and serum sodium concentration of the cirrhotic patients were 314.9 mOsm/kgH2O and 151.0 mmol/L, respectively, which were significantly higher than those of the NAFLD patients (P 0.036 and 0.042, respectively) Overweight/obesity and insulin resistance were common metabolic disorders in this population. The body mass index (BMI) and homeostasis model assessment of insulin resistance parameters of the cirrhotic patients were 27.7 kg/m2 and 9.57, respectively, which were significantly higher than those of the patients without NAFLD (P 0.011 and 0.044, respectively) A correlation analysis was performed, and fasting insulin concentration was positively associated with plasma osmolality in patients with NAFLD, after adjusting for gender, age, and BMI (r 0.540, P 0.046) but no correlation was noted in patients without NAFLD.  NAFLD is common in patients with hypopituitarism. Plasma osmolality and serum sodium levels of hypopituitary patients with cirrhosis are higher than those of subjects with NAFLD, and fasting insulin concentration is positively associated with plasma osmolality in patients with NAFLD, which suggests that hyperosmolality might be a contributor to the worsening of NAFLD in hypopituitary patients.