nils-herrmann/clean_scirepeval huggingface dataset:
Comparative characterization of all cellulosomal cellulases from Clostridium thermocellum reveals high diversity in endoglucanase product formation essential for complex activity
Venue: Biotechnology for Biofuels
Year: 2017

BackgroundClostridium thermocellum is a paradigm for efficient cellulose degradation and a promising organism for the production of second generation biofuels. It owes its high degradation rate on cellulosic substrates to the presence of supra molecular cellulase complexes, cellulosomes, which comprise over 70 different single enzymes assembled on protein backbone molecules of the scaffold protein CipA.ResultsAlthough all 24 single cellulosomal cellulases were described previously, we present the first comparative catalogue of all these enzymes together with a comprehensive analysis under identical experimental conditions, including enzyme activity, binding characteristics, substrate specificity, and product analysis. In the course of our study, we encountered four types of distinct enzymatic hydrolysis modes denoted by substrate specificity and hydrolysis product formation: (i) exo mode cellobiohydrolases (CBH) (ii) endo mode cellulases with no specific hydrolysis pattern, endoglucanases (EG) (iii) processive endoglucanases with cellotetraose as intermediate product (pEG4) and (iv) processive endoglucanases with cellobiose as the main product (pEG2) These modes are shown on amorphous cellulose and on model cello oligosaccharides (with degree of polymerization DP 3 to 6) Artificial mini cellulosomes carrying combinations of cellulases showed their highest activity when all four endoglucanase groups were incorporated into a single complex. Such a modeled nonavalent complex (n 9 enzymes bound to the recombinant scaffolding protein CipA) reached half of the activity of the native cellulosome. Comparative analysis of the protein architecture and structure revealed characteristics that play a role in product formation and enzyme processivity.ConclusionsThe identification of a new endoglucanase type expands the list of known cellulase functions present in the cellulosome. Our study shows that the variety of processivities in the enzyme complex is a key enabler of its high cellulolytic efficiency. The observed synergistic effect may pave the way for a better understanding of the enzymatic interactions and the design of more active lignocellulose degrading cellulase cocktails in the future.
Study on the influence of urban green space on the physical and mental welfare of residents
Year: 2020

Green spaces in cities provide an urban landscape where human beings can live close to nature. The inclusion of green space is an important part of improving the living environment of residents and an effective way to improve their physical and mental health. Taking the main urban area of Hangzhou as the research subject, a remote sensing image of urban green space was interpreted by GIS technology to obtain the green space layout of the main urban area of the city. At the same time, the population density was used as the resistance factor, the number and area of green space within 500m network distance of traffic network as classification standard. Secondly, perceptual data from 665 residents were obtained through questionnaire surveys of 45 high, medium, and low residential areas with different grades. Finally, a structural equation model was used to evaluate the inter group analysis based on the number of green spaces and playtime, and distinguish the differences between various groups and the causes of these differences. The model was also used to assess the number of green spaces and the area they covered, residents' cognition, motivation, and green space attraction, plus the relationship between health benefits and satisfaction. The results show that the number of urban green spaces and the number of times the residents use the spaces have a significant positive relationship with the residents' well being.
Pengaruh Gel Kulit Nanas Madu Terhadap Penyembuhan Luka Terbakar Derajat Dua Pada Tikus Putih (Rattus Novergicus)
Venue: SRIWIJAYA JOURNAL OF MEDICINE
Year: 2019

Kulit nanas (Ananas comosus. L) merupakan limbah dari olahan buah nanas yang populer dikonsumsi oleh masyarakat. Kulit nanas mengandung senyawa flavonoid yang mampu mempercepat rposes penyembuhan luka bakar derajat 2. Tujuan dari penelitian ini adalah untuk mengetahui efek penyembuhan luka bakar dari gel kulit nanas pada tikus yang telah diberikan luka bakar derajat 2. Penelitian ini merupakan penelitian eksperimental dengan desain post test only control group. Ekstrak kulit nanas dibuat dengan menggunakan metode ekstraksi maserasi. Metode yang digunakan dalam uji efektifitas penyembuhan luka bakar derajat 2 ini menggunakan tikus putih (Rattus novergicus) Sampel terdiri dari 5 kelompok perlakuan yaitu gel kulit nanas dengan konsentrasi 10% 20% dan 30% dan kelompok kontrol bioplacenton disertai kontrol negatif. Analisis data menggunakan One Way ANOVA. Hasil penelitian ini adalah efektivitas gel kulit nanas dengan konsentrasi optimal 20% dengan efek penyembuhan mampu meyamai obat komersil bioplasenton.
A combination theorem for convex hyperbolic manifolds, with applications to surfaces in 3 manifolds
Year: 2008

We prove the convex combination theorem for hyperbolic n manifolds. Applications are given both in high dimensions and in three dimensions. One consequence is that given two geometrically finite subgroups of a discrete group of isometries of hyperbolic n space, satisfying a natural condition on their parabolic subgroups and intersection with a separable subgroup, there are finite index subgroups which generate a subgroup that is an amalgamated free product. Constructions of infinite volume hyperbolic n manifolds are described by gluing lower H dimensional manifolds. It is shown that every slope on a cusp of a hyperbolic 3 manifold is a multiple immersed boundary slope. If the fundamental group of a hyperbolic 3 manifold contains a maximal surface group not carried by an embedded surface, then it contains a freely indecomposable group with second Betti number at least 2.
Ultraviolet polarisation sensitivity in the stomatopod crustacean Odontodactylus scyllarus
Venue: Journal of Comparative Physiology A
Year: 2009

The ommatidia of crustacean eyes typically contain two classes of photoreceptors with orthogonally oriented microvilli. These receptors provide the basis for two channel polarisation vision in the blue green spectrum. The retinae of gonodactyloid stomatopod crustaceans possess a great variety of structural specialisations for elaborate polarisation vision. One type of specialisation is found in the small, distally placed R8 cells within the two most ventral rows of the mid band. These ultraviolet sensitive photoreceptors produce parallel microvilli, a feature suggestive for polarisation sensitive photoreceptors. Here, we show by means of intracellular recordings combined with dye injections that in the gonodactyloid species Odontodactylus scyllarus, the R8 cells of mid band rows 5 and 6 are sensitive to linear polarised ultraviolet light. We show that mid band row 5 R8 cells respond maximally to light with an e vector oriented parallel to the mid band, whereas mid band row 6 R8 cells respond maximally to light with an e vector oriented perpendicular to the mid band. This orthogonal arrangement of ultraviolet sensitive receptor cells could support ultraviolet polarisation vision. R8 cells of rows 5 and 6 are known to act as quarter wave retarders around 500 nm and thus are the first photoreceptor type described with a potential dual role in polarisation vision.
Forecasting the load of electrical power systems in mid and long term horizons A review
Year: 2016

Load forecasting has always been an important part in the planning and operation of electric utilities, i.e. both transmission and distribution companies. With technological advancement, change in economic condition and many other factors (to be discussed in this work) load forecasting is becoming more important. The forecast affects as well as gets affected because of the load impacting factors and actions taken in different time horizons. However, due to its stochastic and uncertainty characteristics, it has been one challenging problem for electrical utilities to accurately forecast future load demand. This study aims at reviewing the different load forecasting techniques developed for the mid and long term horizons of electrical power systems. Since there has never been an explicit literature study of the various forecasting techniques for mid and long term horizons, this study reviews techniques for each of the forecasting horizons, citing various methodologies developed so far supported by published literature. This study is concluded with discussion on future research directions.
Verified Uncertainty Calibration
Venue: NeurIPS
Year: 2019

Applications such as weather forecasting and personalized medicine demand models that output calibrated probability estimates those representative of the true likelihood of a prediction. Most models are not calibrated out of the box but are recalibrated by post processing model outputs. We find in this work that popular recalibration methods like Platt scaling and temperature scaling are (i) less calibrated than reported, and (ii) current techniques cannot estimate how miscalibrated they are. An alternative method, histogram binning, has measurable calibration error but is sample inefficient it requires $O(B/\epsilon^2) samples, compared to $O(1/\epsilon^2) for scaling methods, where $B$ is the number of distinct probabilities the model can output. To get the best of both worlds, we introduce the scaling binning calibrator, which first fits a parametric function to reduce variance and then bins the function values to actually ensure calibration. This requires only $O(1/\epsilon^2 B) samples. Next, we show that we can estimate a model's calibration error more accurately using an estimator from the meteorological community or equivalently measure its calibration error with fewer samples $O(\sqrt{B} instead of $O(B) We validate our approach with multiclass calibration experiments on CIFAR 10 and ImageNet, where we obtain a 35% lower calibration error than histogram binning and, unlike scaling methods, guarantees on true calibration. In these experiments, we also estimate the calibration error and ECE more accurately than the commonly used plugin estimators. We implement all these methods in a Python library: this https URL
Pengaruh Saham Syari'ah, Sukuk, Dan Reksadana Syari'ah Terhadap Pertumbuhan Ekonomi Nasional
Year: 2018

Penelitian ini dilatarbelakangi bahwa industri keuangan syari'ah khususnya instrumen pasar modal syari'ah yaitu saham syari'ah, sukuk, dan reksadana syari'ah berkembang cukup pesat sehingga memiliki peranan dalam perkembangan sector riil maupun aktivitas produksi barang dan jasa suatu negara. Dalam hal ini peneliti menghubungkan pengaruh saham syari'ah, sukuk dan reksadana syari'ah terhadap pertumbuhan ekonomi nasional. Adapun yang menjadi tujuan penelitian ini adalah untuk menjelaskan pengaruh saham syari'ah, sukuk dan reksadana syari'ah terhadap pertumbuhan ekonomi nasional dan seberapa signifikan pengaruh tersebut. Jenis penelitian ini menggunakan pendekatan kuantitatif dengan tehnik pengumpulan data berupa observasi dan dokumentasi. Metode analisis data yang digunakan adalah metode asosiatif, yaitu metode yang bertujuan untuk mengetahui hubungan antara dua variabel atau lebih sehingga akan dapat dibangun suatu teori yang berfungsi untuk menjelaskan dan mengontrol suatu gejala. Hasil analisis menunjukkan bahwa saham syari'ah berpengaruh positif tidak signifikan terhadap pertumbuhan ekonomi nasional tetapi sukuk/obligasi syari'ah dan reksadana syari'ah berpengaruh positif dan signifikan terhadap pertumbuhan ekonomi nasional. Namun pengujian secara simultan, menunjukkan bahwa saham syari'ah, sukuk, dan reksadana syari'ah berpengaruh positif dan signifikan terhadap pertumbuhan ekonomi nasional.
Computer Technology Promotes Enterprise Digital Transformation Taking Z Company FSSC Construction as an Example
Venue: 2020 International Conference on Computer Science and Management Technology (ICCSMT)
Year: 2020

COVID 19 has amplified the urgency of digital transformation of enterprises. The development and application of computer technologies such as 5G, blockchain, and big data provide favorable conditions for the digital transformation of enterprises. Financial digital transformation is at the forefront of the digital age. So, this article takes the construction of Z company's Financial Shared Service Center (FSSC) as an example, through the analysis of the construction process, function positioning, application effects and problems in the construction of the Z company's FSSC, it is concluded that enterprises should pay attention to several key points in the construction of the FSSC, the first step of the company in digital transformation. Such as accurate positioning, laying a good foundation for standardization, staff enhancement, scientific management and control process design, and top leaders' attention. And finally combined with the development of computer technology to make a prospect for the application of FSSC in public institutions and governments across the country.
Drum Beats and Where To Find Them: Sampling Drum Patterns from a Latent Space
Venue: ICCC
Year: 2020

This paper presents a large dataset of drum patterns and compares two different architectures of artificial neural networks that produce latent explorable spaces with some recognizable genre areas. Adversarially constrained autoencoder interpolations (ACAI) show better results in comparison with a standard variational autoencoder. To our knowledge, this is the first application of ACAI to drum pattern generation.
Vertical farming systems bring new considerations for pest and disease management
Year: 2020

Vertical farming is an emerging area of food production that aims to provide sustainable intensification of agriculture by maximising the obtainable yield per unit area of land. This approach commonly utilises stacked horizontal levels of crop growth in glasshouse or controlled environment (CE) facilities. Vertical farming has, however, received relatively little scientific investigation to date. Consequently, important factors such as economic feasibility, system design and optimisation of production methods are still being evaluated. Vertical farming methods bring additional considerations for the effective management of pests and diseases compared with conventional protected horticulture, such as movement of both pest and beneficial insects between growth levels. This article aims to provide a perspective on the positive and negative issues facing pest and disease control in Vertical farming systems. We highlight important considerations for system optimisation and areas for future investigation.
Analysis of Key Technology Application of Computer Multimedia Technology
Venue: 2019 11th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)
Year: 2019

With the development of our society and economy, the Internet has been popularized in our country. Our country has successfully transformed into the Internet and digital era, and entered the era of global economic integration. As a comprehensive and advanced technology, computer multimedia technology has been widely used and popularized in all walks of life in the country and society. In the sustained development of society, the requirements for computer multimedia technology will become higher and higher, and the use of computer multimedia technology will become more and more frequent. Therefore, continuous optimization and upgrading of key technologies of computer multimedia technology is the inevitable requirement of development. This paper mainly summarizes computer multimedia technology and key technology, and deeply analyses the application of key technology in computer multimedia technology for reference.
Perceiving the Problem of Poverty and Schooling: Deconstructing the Class Stereotypes that Mis Shape Education Practice and Policy
Year: 2012

A rich history of scholarship has demonstrated the ways in which popular stereotypes of disenfranchised communities, including people living in poverty, affect individual biases and preconceptions. Less attention has been paid to the ways in which such stereotypes help frame policy and practice responses regarding social problems, such as the economic "achievement gap." The purpose of this essay is to examine the nature of poverty based stereotyping in the context of popular discourses regarding the education of poor and low income students. In doing so, I analyze stereotypes commonly used to locate the problem of the economic "achievement gap" as existing within, rather than as pressing upon, poor and low income families. I then discuss how these stereotypes have fed deficit ideology and, as a result, misdirected policy and practice responses to gross class inequities in U.S. schools.
Comparison of the clinical performance of airway management with the i gel(r) and laryngeal mask airway SupremeTM in geriatric patients: a prospective and randomized study
Venue: Korean journal of anesthesiology
Year: 2019

Geriatric patients are susceptible to respiratory and hemodynamic adverse events during endotracheal intubation and extubation due to anatomic and physiological changes with aging. Supraglottic airway devices (SADs) provide reduced airway morbidity and increased hemodynamic stability in adults. However, studies that have compared the clinical performance of SADs in geriatric patients are limited. Therefore, we evaluated the clinical performance of airway management with i gel(r) and laryngeal mask airway Supreme (LMA SupremeTM) in geriatric patients.  The subjects were American Society of Anesthesiologists physical status classification I III geriatric (65 85 years) patients who underwent elective surgery with general anesthesia and were randomly allocated into the i gel(r) group and the LMA SupremeTM group. We compared the time for successful insertion on a first attempt as a primary outcome, and the secondary outcomes were success rate, ease of insertion, maneuver for successful ventilation, oropharyngeal leak pressure, gastric insufflation, fiberoptic view grades, ventilator problems, and adverse events.  Insertion time was significantly shorter for the i gel(r) than the LMA SupremeTM (21.4 6.8 vs. 29.3 9.9 s; P 0.011) The i gel(r) was also easier to insert than the LMA SupremeTM (P 0.014) Gastric insufflation was less frequent with the i gel(r) than the LMA SupremeTM (0% vs. 31.3% P 0.013) Other measurements were comparable between groups.  Both devices can be safely applied to geriatric patients with similar success rates and oropharyngeal leak pressures. However, inserting the i gel(r) was faster and easier compared to the LMA SupremeTM in geriatric patients.
An Autonomous Path Planning Model for Unmanned Ships Based on Deep Reinforcement Learning
Venue: Sensors
Year: 2020

Deep reinforcement learning (DRL) has excellent performance in continuous control problems and it is widely used in path planning and other fields. An autonomous path planning model based on DRL is proposed to realize the intelligent path planning of unmanned ships in the unknown environment. The model utilizes the deep deterministic policy gradient (DDPG) algorithm, through the continuous interaction with the environment and the use of historical experience data; the agent learns the optimal action strategy in a simulation environment. The navigation rules and the ship's encounter situation are transformed into a navigation restricted area, so as to achieve the purpose of planned path safety in order to ensure the validity and accuracy of the model. Ship data provided by ship automatic identification system (AIS) are used to train this path planning model. Subsequently, the improved DRL is obtained by combining DDPG with the artificial potential field. Finally, the path planning model is integrated into the electronic chart platform for experiments. Through the establishment of comparative experiments, the results show that the improved model can achieve autonomous path planning, and it has good convergence speed and stability.
Exploiting Structural and Temporal Influence for Dynamic Social Aware Recommendation
Venue: Journal of Computer Science and Technology
Year: 2020

Recent years have witnessed the rapid development of online social platforms, which effectively support the business intelligence and provide services for massive users. Along this line, large efforts have been made on the social aware recommendation task, i.e. leveraging social contextual information to improve recommendation performance. Most existing methods have treated social relations in a static way, but the dynamic influence of social contextual information on users' consumption choices has been largely unexploited. To that end, in this paper, we conduct a comprehensive study to reveal the dynamic social influence on users' preferences, and then we propose a deep model called Dynamic Social Aware Recommender System (DSRS) to integrate the users' structural and temporal social contexts to address the dynamic social aware recommendation task. DSRS consists of two main components, i.e. the social influence learning (SIL) and dynamic preference learning (DPL) Specifically, in the SIL module, we arrange social graphs in a sequential order and borrow the power of graph convolution networks (GCNs) to learn social context. Moreover, we design a structural temporal attention mechanism to discriminatively model the structural social influence and the temporal social influence. Then, in the DPL part, users' individual preferences are learned dynamically by recurrent neural networks (RNNs) Finally, with a prediction layer, we combine the users' social context and dynamic preferences to generate recommendations. We conduct extensive experiments on two real world datasets, and the experimental results demonstrate the superiority and effectiveness of our proposed model compared with the state of the art methods.
Joint Optimization of Computation and Communication Power in Multi User Massive MIMO Systems
Venue: IEEE Transactions on Wireless Communications
Year: 2018

With the growing interest in the deployment of massive multiple input multiple output (MIMO) systems and millimeter wave technology for fifth generation wireless systems, the computation power to the total power consumption ratio is expected to increase rapidly due to high data traffic processing at the baseband unit. Therefore in this paper, a joint optimization problem of computation and communication power is formulated for multi user massive MIMO systems with partially connected structures of radio frequency (RF) transmission systems. When the computation power is considered for massive MIMO systems, the results of this paper reveal that the energy efficiency of massive MIMO systems decreases with increasing the number of antennas and RF chains, which is contrary with the conventional energy efficiency analysis results of massive MIMO systems, i.e. only communication power is considered. To optimize the energy efficiency of multi user massive MIMO systems, an upper bound on energy efficiency is derived. Considering the constraints on partially connected structures, a suboptimal solution consisting of the baseband and RF precoding matrices is proposed to approach the upper bound on energy efficiency of multi user massive MIMO systems. Furthermore, an optimized hybrid precoding with computation and communication power algorithm is developed to realize the joint optimization of computation and communication power. Simulation results indicate that the proposed algorithm improves energy and cost efficiencies and the maximum power saving is achieved by 76.59% for multi user massive MIMO systems with partially connected structures.