nils-herrmann/clean_scirepeval huggingface dataset:
Evaluation of historic building conversion options in the context of sustainable development
Year: 2014

Sustainable development is a method of resource management, the effect of which not only meet the needs of the present but also of future generations. Historical monuments as part of national heritage are a resource, which is protected not only in the sense of its cultural value but also has a potential for the creation of socio economic values. The process of extending the life cycle of a historic building is associated primarily with the analysis of the options for its conversion in the light of various criteria, many of which have a fuzzy character. The aim of the paper regards the proper selection and also description of the criteria for assessing conversion options for historic buildings in the context of sustainable development.
X ray computed tomography observations of water flow through anisotropic methane hydrate bearing sand
Year: 2009

We used X ray computed tomography (CT) to image and quantify the effect of a heterogeneous sand grain size distribution on the formation and dissociation of methane hydrate, as well as the effect on water flow through the heterogeneous hydrate bearing sand. A 28 cm long sand column was packed with several segments having vertical and horizontal layers with sands of different grain size distributions. During the hydrate formation, water redistribution occurred. Observations of water flow through the hydrate bearing sands showed that water was imbibed more readily into the fine sand, and that higher hydrate saturation increased water imbibition in the coarse sand due to increased capillary strength. Hydrate dissociation induced by depressurization resulted in different flow patterns with the different grain sizes and hydrate saturations, but the relationships between dissociation rates and the grain sizes could not be identified using the CT images. The formation, presence, and dissociation of hydrate in the pore space dramatically impact water saturation and flow in the system.
Foundation of Deep Machine Learning in Neural Networks
Year: 2019

This chapter introduces several basic neural network models, which are used as the foundation for the further development of deep machine learning in neural networks. The deep machine learning is a very different approach in terms of feature extraction compared with the traditional feature extraction methods. This conventional feature extraction method has been widely used in the pattern recognition approach. The deep machine learning in neural networks is to automatically "learn" the feature extractors, instead of using human knowledge to design and build feature extractors in the pattern recognition approach. We will describe some typical neural network models that have been successfully used in image and video analysis. One type of the neural networks introduced here is called supervised learning such as the feed forward multi layer neural networks, and the other type is called unsupervised learning such as the Kohonen model (also called self organizing map (SOM) Both types are widely used in visual recognition before the nurture of the deep machine learning in the convolutional neural networks (CNN) Specifically, the following models will be introduced: (1) the basic neuron model and perceptron, (2) the traditional feed forward multi layer neural networks using the backpropagation, (3) the Hopfield neural networks, (4) Boltzmann machines, (5) Restricted Boltzmann machines and Deep Belief Networks, (6) Self organizing Maps, and (7) the Cognitron and Neocognitron. Both Cognitron and Neocognitron are deep neural networks that can perform the self organizing without any supervision. These models are the foundation for discussing texture classification by using deep neural networks models.
Isothermal reduction kinetics and mineral phase of chromium bearing vanadium titanium sinter reduced with CO gas at 873 1273 K
Venue: International Journal of Minerals, Metallurgy, and Materials
Year: 2018

Reduction of chromium bearing vanadium titanium sinter (CVTS) was studied under simulated conditions of a blast furnace, and thermodynamics and kinetics were theoretically analyzed. Reduction kinetics of CVTS at different temperatures was evaluated using a shrinking unreacted core model. The microstructure, mineral phase, and variation of the sinter during reduction were observed by X ray diffraction, scanning electron microscopy, and metallographic microscopy. Results indicate that porosity of CVTS increased with temperature. Meanwhile, the reduction degree of the sinter improved with the reduction rate. Reduction of the sinter was controlled by a chemical reaction at the initial stage and inner diffusion at the final stage. Activation energies measured 29.22 99.69 kJ/mol. Phase transformations in CVTS reduction are as follows: Fe2O3 Fe3O4 FeO Fe; Fe2TiO5 Fe2TiO4 FeTiO3; FeO*V2O3 V2O3; FeO*Cr2O3 Cr2O3.
Analisis Kinerja Protokol Routing AODV, DSR, dan OLSR pada Mobile Ad hoc Network Berdasarkan Parameter Quality of Service
Year: 2018

MANET is autonomous, self configured, and applicable to emergency locations such as forest fires, earthquakes, floods, and health monitoring. However, challenges and difficulties faced by the mobile ad hoc network (MANET) is a dynamically built network system, without the support of infrastructure in communicating between one node and other nodes, and limited energy sources. To overcome MANET problems and to obtain optimal network quality, the selections of routing protocols and quality of service (QoS) are significant in MANET design. This study aims to analyze the performance of routing protocols: dynamic source routing (DSR) ad hoc on demand distance vector (AODV) and optimized link state routing (OLSR) based on QoS. The analyzed QoS parameters include packet delivery ratio (PDR) packet loss, throughput, and delay. Simulation results using network simulator version based on the number of node densities indicate that OLSR has better performance compared to AODV and DSR regarding PDR, packet loss, throughput, and delay.
Applying Social Network Analysis to Identify the Social Support Needs of Adolescent and Young Adult Cancer Patients and Survivors.
Venue: Journal of adolescent and young adult oncology
Year: 2018

This article examines how theoretical and clinical applications of social network analysis (SNA) can inform opportunities for innovation and advancement of social support programming for adolescent and young adult (AYA) cancer patients and survivors. APPLICATIONS SNA can help address potential barriers and challenges to initiating and sustaining AYA peer support by helping to identify the diverse psychosocial needs among individuals in the AYA age range; find strategic ways to support and connect AYAs at different phases of the cancer trajectory with resources and services; and increase awareness of psychosocial resources and referrals from healthcare providers. Network perspectives on homophily, proximity, and evolution provide a foundational basis to explore the utility of SNA in AYA clinical care and research initiatives. The uniqueness of the AYA oncology community can also provide insight into extending and developing current SNA theories.  Using SNA in AYA psychosocial cancer research has the potential to create new ideas and pathways for supporting AYAs across the continuum of care, while also extending theories of SNA. SNA may also prove to be a useful tool for examining social support resources for AYAs with various chronic health conditions and other like groups.
Timing Problems: When Care and Violence Converge in Stephen King's Horror Novel Christine
Year: 2017

Judith Butler, Joan Tronto, and Stephen King all hinge human experience on shared ontological vulnerability, but whereas Butler and Tronto use vulnerability to build ethical commitments, King exploits aging, disability, and death to frighten us. King's horror genre is provocative for the imaginative landscape of feminist theory precisely because he uses vulnerability to magnify the anxieties of mass culture. In Christine, the characters' shared susceptibility to psychic and physical injury blurs the boundary between care and violence. Like Butler, King depicts our social worlds encrusted with normative violence: the mundane ways that norms police gender, race, class, and disability identities. And like Butler, King makes undecidability a key feature of human identity: the idea that needs and identities are uncertain. Normative violence and undecidability trouble the starting point of Tronto's care theory attentiveness to needs because both concepts invest interdependency with ambiguity and conflict. But like Tronto, King recognizes that care actors must act, even amid ambiguity and even when their actions make care and aggression converge. Christine's supernatural plot details the psychic possession of an American teenager, but the novel's more terrifying story is about interdependency and how normative violence is not the antithesis of care, but its dark underbelly.
Structure of a biologically active binuclear palladium complex in the compound bis(bis[(m2 2 chloroethylammonium) (1,10 phenanthroline) palladium(I) octanitrates dihydrates
Year: 2009

The structure of a biologically active binuclear palladium complex, namely, (1,10 phenanthroline) Pd(m2 2 chloroethylammonium)24+ 4NO3 H2O, has been determined using X ray diffraction analysis. The compound crystallizes in the monoclinic system, space group of symmetry Cc, with the unit cell parameters a 24.527(3) A, b 13.097(1) A, c 22.651(3) A, b 104.23(1)deg, V 7052(2) A3, Z 8, and r 1.88 g/cm3. The final discrepancy factor is R1 0.0316 for 15581 symmetrically nonequivalent reflections with I 2s(I) wR2 0.0513, and GooF 1.047. The palladium atoms reside in the oxidation state of 1+ which is rarely encountered in organometallic compounds. The asymmetric part of the unit cell contains two chemically equivalent but crystallographically independent positively charged binuclear palladium complexes, eight NO3 anions, and two water molecules. The p p stacking interaction between the nearest 1,10 phenanthroline rings of the neighboring layers takes place. Moreover, the interlayer and intralayer interactions occur through electrostatic interaction forces and a complex three dimensional system of hydrogen bonds, which are formed by water molecules and N3+ groups.
Stochastic dynamics of division of labor games in finite populations
Venue: Knowl. Based Syst.
Year: 2018

A theoretical investigation on the strategy evolution in the self organized division of labor dilemma is performed by means of evolutionary game theory. The often used Fermi function is employed for driving the strategy updating, based on which the fixation probability of the involved strategy (performing which task) is calculated. Results about the evolution dynamics of the division of labor for two player games are: (1) the fixation probabilityfor any selection intensity is derived; (2) the fixation probability and fixation time under weak selection are gained and a comparison with neutral selection is performed. In this case, the conditions to facilitate cooperation in division of labor are found. Then we extend the model to a multi player one to describe the self organized task allocation when multiple players are involved in one game. Relevant results for weak selection to favor the coexistence state of the two strategies for the multi player games are gained. These results help understand and design effective mechanism where self organized collective dynamics occurs in the form of maximizing the benefit of the multi agent system.
Fixed weight Hopfield Neural Network based on optical implementation of all optical MZI XNOR logic gate
Venue: Photonics Europe
Year: 2010

Many researches are conducted to improve Hopfield Neural Network (HNN) performance especially for speed and memory capacity in different approaches. However, there is still a significant scope of developing HNN using Optical Logic Gates. We propose here a new model of HNN based on all optical XNOR logic gates for real time color image recognition. Firstly, we improved HNN toward optimum learning and converging operations. We considered each unipolar image as a set of small blocks of 3 pixels as vectors for HNN. This enables to save large number of images in the net with best reaching into global minima, and because there are only eight fixed states of weights so that only single iteration performed to construct a vector with stable state at minimum energy. HNN is useless in dealing with data not in bipolar representation. Therefore, HNN failed to work with color images. In RGB bands each represents different values of brightness, for d bit RGB image it is simply consists of d layers of unipolar. Each layer is as a single unipolar image for HNN. In addition, the weight matrices with stability of unity at the diagonal perform clear converging in comparison with no self connecting architecture. Synchronously, each matrix matrix multiplication operation would run optically in the second part, since we propose an array of all optical XOR gates, which uses Mach Zehnder Interferometer (MZI) for neurons setup and a controlling system to distribute timely signals with inverting to achieve XNOR function. The primary operation and simulation of the proposal HNN is demonstrated.
Overcoming Multidrug Resistant MRSA Using Conventional Aminoglycoside Antibiotics
Venue: Advanced science
Year: 2020

Global multidrug resistant (MDR) bacteria are spreading rapidly and causing a great threat to human health due to the abuse of antibiotics. Determining how to resensitize MDR bacteria to conventional inefficient antibiotics is of extreme urgency. Here, a low temperature photothermal treatment (PTT, 45 degC) is utilized with red phosphorus nanoparticles to resensitize methicillin resistant Staphylococcus aureus (MRSA) to conventional aminoglycoside antibiotics. The antibacterial mechanism is studied by the proteomic technique and molecular dynamics (MD) simulation, which proves that the aminoglycoside antibiotics against MRSA can be selectively potentiated by low temperature PTT. The catalytic activity of 2 aminoglycoside phosphotransferase (APH (2' a modifying enzyme is demonstrated to be obviously inhibited via detecting the consumption of adenosine triphosphate (ATP) in the catalytic reaction. It is also found that the active site of aspartic acid (ASP) residues in APH (2' is thermally unstable from the results of molecular dynamics simulation. Its catalytic ability is inhibited by preventing the deprotonating procedure for the target OH of gentamycin. The combined therapy also exhibits great biocompatibility and successfully treats MRSA infections in vivo. This low temperature PTT strategy has the potential to be an exogenous modifying enzyme inhibitor for the treatment of MDR bacterial infection.
What is the evidence for a role for diet and nutrition in osteoarthritis?
Venue: Rheumatology
Year: 2018

As current treatment options in OA are very limited, OA patients would benefit greatly from some ability to self manage their condition. Since diet may potentially affect OA, we reviewed the literature on the relationship between nutrition and OA risk or progression, aiming to provide guidance for clinicians. For overweight/obese patients, weight reduction, ideally incorporating exercise, is paramount. The association between metabolic syndrome, type 2 diabetes and OA risk or progression may partly explain the apparent benefit of dietary lipid modification resulting from increased consumption of long chain omega 3 fatty acids from oily fish/fish oil supplements. A strong association between OA and raised serum cholesterol together with clinical effects in statin users suggests a potential benefit of reduction of cholesterol by dietary means. Patients should ensure that they meet the recommended intakes for micronutrients such as vitamin K, which has a role in bone/cartilage mineralization. Evidence for a role of vitamin D supplementation in OA is unconvincing.
CMS Changes in Reimbursement for HAIs: Setting A Research Agenda
Venue: Medical care
Year: 2010

The Centers for Medicare and Medicaid Services (CMS) promulgated regulations commencing October 1, 2008, which deny payment for selected conditions occurring during the hospital stay and are not present on admission. Three of the 10 hospital acquired conditions covered by the new CMS policy involve healthcare associated infections, which are a common, expensive, and often preventable cause of inpatient morbidity and mortality. To outline a research agenda on the impact of CMS's payment policy on the healthcare system and the prevention of healthcare associated infections. An invitational daylong conference was convened in April 2009. Including the planning committee and speakers there were 41 conference participants who were national experts and senior researchers. Building upon a behavioral model and organizational theory and management research a conceptual framework was applied to organize the wide range of issues that arose. A broad array of research topics was identified. Thirty two research agenda items were organized in the areas of incentives, environmental factors, organizational factors, clinical outcomes, staff outcomes, and financial outcomes. Methodological challenges are also discussed. This policy is a first significant step to move output based inpatient funding to outcome based funding, and this agenda is applicable to all hospital acquired conditions. Studies beginning soon will have the best hope of capturing data for the years preceding the policy change, a key element in nonexperimental research. The CMS payment policy offers an excellent opportunity to understand and influence the use of financial incentives for improving patient safety.
Coding Exon Structure Aware Realigner (CESAR) Utilizing Genome Alignments for Comparative Gene Annotation.
Venue: Methods in molecular biology
Year: 2019

Alignment based gene identification methods utilize sequence conservation between orthologous protein coding genes to annotate genes in newly sequenced genomes. CESAR is an approach that makes use of existing genome alignments to transfer genes from one genome to other aligned genomes, and thus generates comparative gene annotations. To accurately detect conserved exons that exhibit an intact reading frame and consensus splice sites, CESAR produces a new alignment between orthologous exons, taking information about the exon's reading frame and splice site positions into account. Furthermore, CESAR is able to detect most evolutionary splice site shifts, which helps to annotate exon boundaries at high precision. Here, we describe how to apply CESAR to generate comparative gene annotations for one or many species, and discuss the strengths and limitations of this approach. CESAR is available at https:/github.com/hillerlab/CESAR2.0
Does economic freedom enhance the impact of foreign direct investment on economic growth in north African countries? A panel data analysis
Year: 2016

type="main" xml:lang="en" This article investigates the causal interactions between foreign direct investment (FDI) economic freedom and economic growth on a panel of four North African countries (Tunisia, Morocco, Algeria and Egypt) over a 5 year period from 1980 to 2013. Using the System Generalized Method of Moments (GMM) in a panel data analysis, we found strong evidence of a positive link between FDI and economic growth. We also found that economic freedom appears to be working as a complement to FDI and that the effect of FDI is more pronounced in the presence of the economic freedom variable. This means that the countries which promote greater freedom of economic activities benefit more from the presence of multinational corporations (MNCs)
Conformational Analysis of 5 Methyl 1,3 oxathiane
Venue: Russian Journal of Organic Chemistry
Year: 2018

Computer simulation of conformational transformations of 5 methyl 1,3 oxathiane at the DFT PBE/3z, RI MP2/l2, and HF/6 31++G(d,p) levels of theory has shown that the interconversion between the equatorial (global minimum) and axial chair conformers occurs along several independent pathways through five flexible forms. Nine transition states corresponding to different half chair forms, as well as symmetrical and unsymmetrical boat conformers, have been localized on the potential energy surface. The free conformational energy of the methyl group has been estimated at 0.9 1.0 kcal/mol by comparison of the calculated and experimental vicinal coupling constants in the 1H NMR spectra.
Distributed transmission power control for communication congestion control and awareness enhancement in VANETs
Venue: PloS one
Year: 2018

The vehicular ad hoc network (VANET) has been identified as one of the most promising technologies for managing future intelligent transportation systems. This paper proposes a distributed transmission power adjustment algorithm for communication congestion control and awareness enhancement to address communication congestion problems that can arise in VANETs. The objective of the proposed algorithm is to provide maximum awareness of surrounding vehicles' status while maintaining a communications channel load below the allowed threshold. The proposed algorithm accomplishes this by adjusting the transmission range of each vehicle in the network progressively and gradually, while monitoring the communications channel load of each vehicle. By changing the transmission range of a vehicle little by little according to the communications channel load of its neighboring vehicles, the algorithm finds the optimal transmission range that provides maximum awareness without resulting in communications congestion. In addition, the proposed algorithm appropriately controls the channel load in a fair manner without sacrificing awareness of specific vehicles in the congested situation. This allows nearby vehicles to obtain more peripheral information to help them stay away from potential hazards and maintain safety. The proposed algorithm was implemented in a simulation environment, and its performance was validated in various traffic scenarios. The simulation results show that the proposed algorithm can deal with communication congestion by controlling the transmission power fairly to a target threshold in various traffic situations.
Algorithmic content moderation: Technical and political challenges in the automation of platform governance
Year: 2020

As government pressure on major technology companies builds, both firms and legislators are searching for technical solutions to difficult platform governance puzzles such as hate speech and misinformation. Automated hash matching and predictive machine learning tools what we define here as algorithmic moderation systems are increasingly being deployed to conduct content moderation at scale by major platforms for user generated content such as Facebook, YouTube and Twitter. This article provides an accessible technical primer on how algorithmic moderation works; examines some of the existing automated tools used by major platforms to handle copyright infringement, terrorism and toxic speech; and identifies key political and ethical issues for these systems as the reliance on them grows. Recent events suggest that algorithmic moderation has become necessary to manage growing public expectations for increased platform responsibility, safety and security on the global stage; however, as we demonstrate, these systems remain opaque, unaccountable and poorly understood. Despite the potential promise of algorithms or 'AI' we show that even 'well optimized' moderation systems could exacerbate, rather than relieve, many existing problems with content policy as enacted by platforms for three main reasons: automated moderation threatens to (a) further increase opacity, making a famously non transparent set of practices even more difficult to understand or audit, (b) further complicate outstanding issues of fairness and justice in large scale sociotechnical systems and (c) re obscure the fundamentally political nature of speech decisions being executed at scale.