nils-herrmann/clean_scirepeval huggingface dataset:
Early osseointegration driven by the surface chemistry and wettability of dental implants

The objective of this study was to investigate the impact of two different commercially available dental implants on osseointegration. The surfaces were sandblasting and acid etching (Group 1) and sandblasting and acid etching, then maintained in an isotonic solution of 0.9% sodium chloride (Group 2).



X-ray photoelectron spectroscopy (XPS) was employed for surface chemistry analysis. Surface morphology and topography was investigated by scanning electron microscopy (SEM) and confocal microscopy (CM), respectively. Contact angle analysis (CAA) was employed for wetting evaluation. Bone-implant-contact (BIC) and bone area fraction occupied (BAFO) analysis were performed on thin sections (30 μm) 14 and 28 days after the installation of 10 implants from each group (n=20) in rabbits' tibias. Statistical analysis was performed by ANOVA at the 95% level of significance considering implantation time and implant surface as independent variables.



Group 2 showed 3-fold less carbon on the surface and a markedly enhanced hydrophilicity compared to Group 1 but a similar surface roughness (p>0.05). BIC and BAFO levels in Group 2 at 14 days were similar to those in Group 1 at 28 days. After 28 days of installation, BIC and BAFO measurements of Group 2 were approximately 1.5-fold greater than in Group 1 (p<0.05).



The surface chemistry and wettability implants of Group 2 accelerate osseointegration and increase the area of the bone-to-implant interface when compared to those of Group 1.
Predicting interruptibility for manual data collection: a cluster-based user model

Previous work suggests that Quantified-Self applications can retain long-term usage with motivational methods. These methods often require intermittent attention requests with manual data input. This may cause unnecessary burden to the user, leading to annoyance, frustration and possible application abandonment. We designed a novel method that uses on-screen alert dialogs to transform recurrent smartphone usage sessions into moments of data contributions and evaluate how accurately machine learning can reduce unintended interruptions. We collected sensor data from 48 participants during a 4-week long deployment and analysed how personal device usage can be considered in scheduling data inputs. We show that up to 81.7% of user interactions with the alert dialogs can be accurately predicted using user clusters, and up to 75.5% of unintended interruptions can be prevented and rescheduled. Our approach can be leveraged by applications that require self-reports on a frequent basis and may provide a better longitudinal QS experience.
Real-time liquid biopsy in cancer patients: fact or fiction?

Distant metastases harbor unique genomic characteristics not detectable in the corresponding primary tumor of the same patient and metastases located at different sites show a considerable intrapatient heterogeneity. Thus, the mere analysis of the resected primary tumor alone (current standard practice in oncology) or, if possible, even reevaluation of tumor characteristics based on the biopsy of the most accessible metastasis may not reveal sufficient information for treatment decisions. Here, we propose that this dilemma can be solved by a new diagnostic concept: liquid biopsy, that is, analysis of therapeutic targets and drug resistance-conferring gene mutations on circulating tumor cells (CTC) and cell-free circulating tumor DNA (ctDNA) released into the peripheral blood from metastatic deposits. We discuss the current challenges and future perspectives of CTCs and ctDNA as biomarkers in clinical oncology. Both CTCs and ctDNA are interesting complementary technologies that can be used in parallel in future trials assessing new drugs or drug combinations. We postulate that the liquid biopsy concept will contribute to a better understanding and clinical management of drug resistance in patients with cancer.
Repetitive High-Voltage All-solid-state Marx Generator for Excimer DBD UV Sources

In order to develop an efficient and reliable pulsed power supply for excimer dielectric barrier discharge (DBD) ultraviolet (UV) sources, a pulse generator using Marx topology is adopted. MOSFETs are used as switches. The 12-stage pulse generator operates with a voltage amplitude in the range of 0-5.5 kV. The repetition rate and pulsewidth can be adjusted from 0.1 to 50 kHz and 2 to 20 μs, respectively. It is used to excite KrCl* excilamp, a typical DBD UV source. In order to evaluate the performance of the pulse generator, a sinusoidal voltage power supply dedicated for DBD lamp is also used to excite the KrCl* excilamp. It shows that the lamp excited by the pulse generator has better performance with regard to radiant power and system efficiency. The influence of voltage amplitude, repetition rate, pulsewidth, and rise and fall times on radiant power and system efficiency is investigated using the pulse generator. An inductor is inserted between the pulse generator and the KrCl* excilamp to reduce electromagnetic interference and enhance system reliability.
Corporate Financial Evaluation and Bankruptcy Prediction Implementing Artificial Intelligence Methods

Corporate accounting statements provide financial markets, and tax services with valuable data on the economic health of companies, although financial indices are only focused on a very limited part of the activity within the company. Useful tools in the field of processing extended financial and accounting data are the methods of Artificial Intelligence, aiming the efficient delivery of financial information to tax services, investors, and financial markets where lucrative portfolios can be created.
OntoWiki: A Tool for Social, Semantic Collaboration

We present OntoWiki, a tool providing support for agile, distributed knowledge engineering scenarios. OntoWiki facilitates the visual presentation of a knowledge base as an information map, with different views on instance data. It enables intuitive authoring of semantic content, with an inline editing mode for editing RDF content, similar to WYSIWYG for text documents. It fosters social collaboration aspects by keeping track of changes, allowing comments and discussion on every single part of a knowledge base, enabling to rate and measure the popularity of content and honoring the activity of users. OntoWiki enhances the browsing and retrieval by offering semantic enhanced search strategies. All these techniques are applied with the ultimate goal of decreasing the entrance barrier for projects and domain experts to collaborate using semantic technologies. In the spirit of the Web 2.0 OntoWiki implements an ”architecture of participation” that allows users to add value to the application as they use it. It is available as open-source software and a demonstration platform can be accessed at http://3ba.se.
A simple model for calculating residential 60-Hz magnetic fields.

A model is presented that permits the calculation of densities of 60-Hz magnetic fields throughout a residence from only a few measurements. We assume that residential magnetic fields are produced by sources external to the house and by the residential grounding circuit. The field from external sources is measured with a single probe. The field produced by the grounding circuit is calculated from the current flowing in the circuit and its geometry. The two fields are combined to give a prediction of the total field at any point in the house. A data-acquisition system was built to record the magnitude and phase of the grounding current and the field from external sources. The model's predictions were compared with measurements of the total magnetic field at a single location in 23 houses; a correlation coefficient of .87 was obtained, indicating that the model has good predictive capability. A more detailed study that was carried out in one house permitted comparisons of measurements with the model's predictions at locations throughout the house. Again, quite reasonable agreement was found. We also investigated the temporal variability of field readings in this house. Daily magnetic field averages were found to be considerably more stable than hourly averages. Finally, we demonstrate the use of the model in creating a profile of the magnetic fields in a home.
Designing With Data : Moving Beyond The Design Space Catalog

Design space catalogs, which present a collection of different options for selection by human designers, have become commonplace in architecture. Increasingly, these catalogs are rapidly generated using parametric models and informed by simulations that describe energy usage, structural efficiency, daylight availability, views, acoustic properties, and other aspects of building performance. However, by conceiving of computational methods as a means for fostering interactive, collaborative, guided, expert-dependent design processes, many opportunities remain to improve upon the originally static archetype of the design space catalog. This paper presents developments in the areas of interaction, automation, simplification, and visualization that seek to improve on the current catalog model while also describing a vision for effective computer-aided, performance-based design processes in the future.
Network Analysis in the Legal Domain: A complex model for European Union legal sources

Legislators, designers of legal information systems, as well as citizens face often problems due to the interdependence of the laws and the growing number of references needed to interpret them. In this paper, we introduce the ”Legislation Network” as a novel approach to address several quite challenging issues for identifying and quantifying the complexity inside the Legal Domain. We have collected an extensive data set of a more than 60-year old legislation corpus, as published in the Official Journal of the European Union, and we further analysed it as a complex network, thus gaining insight into its topological structure. Among other issues, we have performed a temporal analysis of the evolution of the Legislation Network, as well as a robust resilience test to assess its vulnerability under specific cases that may lead to possible breakdowns. Results are quite promising, showing that our approach can lead towards an enhanced explanation in respect to the structure and evolution of legislation properties.
Pycnodysostosis, a lysosomal disease caused by cathepsin K deficiency.

Pycnodysostosis, an autosomal recessive osteochondrodysplasia characterized by osteosclerosis and short stature, maps to chromosome 1q21. Cathepsin K, a cysteine protease gene that is highly expressed in osteoclasts, localized to the pycnodysostosis region. Nonsense, missense, and stop codon mutations in the gene encoding cathepsin K were identified in patients. Transient expression of complementary DNA containing the stop codon mutation resulted in messenger RNA but no immunologically detectable protein. Thus, pycnodysostosis results from gene defects in a lysosomal protease with highest expression in osteoclasts. These findings suggest that cathepsin K is a major protease in bone resorption, providing a possible rationale for the treatment of disorders such as osteoporosis and certain forms of arthritis.
Cytotoxicity of the beta-carboline alkaloids harmine and harmaline in human cell assays in vitro.

beta-Carboline alkaloids are natural products widely distributed in plants and also found in alcoholic beverages, well-cooked foods and tobacco smoke. Various authors have reported genotoxic activities of several carboline in prokaryotic and eukaryotic cells that have been attributed to their abilities to intercalate into DNA. But studies on the genotoxic and on the cytotoxic potencies in human cells in vitro are not found in the literature. In the present study the toxicities of one full aromatic beta-carboline alkaloid (harmine) and one dihydro-beta-carboline alkaloid (harmaline) were evaluated by means of two in vitro human cell assays: the cytochalasin-B blocked micronucleus (CBMN) assay and the viability/colony formation assay with four different human cultured non-transformed (CCD18Lu) and transformed (HeLa, C33A and SW480) cells. Neither alkaloid was able to induce micronuclei levels above that of control levels in a wide range of doses tested; although, harmine at the highest concentrations assayed induced apoptotic as well as necrotic cells. Harmine produced a good viability of all cell lines assayed (control and tumor) while harmaline significantly reduced the viability of transformed and non-transformed cell lines in a dose-dependent manner. Harmine displayed a dose-dependent inhibitory effect on cell proliferation against all human carcinoma cells, but the SW480 transformed cell line showed a higher sensitivity. These results suggested that harmine was identified as a useful inhibitor of tumor development.
Leaf Morphology, Photosynthetic Performance, Chlorophyll Fluorescence, Stomatal Development of Lettuce (Lactuca sativa L.) Exposed to Different Ratios of Red Light to Blue Light

Red and blue light are both vital factors for plant growth and development. We examined how different ratios of red light to blue light (R/B) provided by light-emitting diodes affected photosynthetic performance by investigating parameters related to photosynthesis, including leaf morphology, photosynthetic rate, chlorophyll fluorescence, stomatal development, light response curve, and nitrogen content. In this study, lettuce plants (Lactuca sativa L.) were exposed to 200 μmol⋅m(-2)⋅s(-1) irradiance for a 16 h⋅d(-1) photoperiod under the following six treatments: monochromatic red light (R), monochromatic blue light (B) and the mixture of R and B with different R/B ratios of 12, 8, 4, and 1. Leaf photosynthetic capacity (A max) and photosynthetic rate (P n) increased with decreasing R/B ratio until 1, associated with increased stomatal conductance, along with significant increase in stomatal density and slight decrease in stomatal size. P n and A max under B treatment had 7.6 and 11.8% reduction in comparison with those under R/B = 1 treatment, respectively. The effective quantum yield of PSII and the efficiency of excitation captured by open PSII center were also significantly lower under B treatment than those under the other treatments. However, shoot dry weight increased with increasing R/B ratio with the greatest value under R/B = 12 treatment. The increase of shoot dry weight was mainly caused by increasing leaf area and leaf number, but no significant difference was observed between R and R/B = 12 treatments. Based on the above results, we conclude that quantitative B could promote photosynthetic performance or growth by stimulating morphological and physiological responses, yet there was no positive correlation between P n and shoot dry weight accumulation.
RNA-guided human genome engineering via Cas9.

Bacteria and archaea have evolved adaptive immune defenses, termed clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) systems, that use short RNA to direct degradation of foreign nucleic acids. Here, we engineer the type II bacterial CRISPR system to function with custom guide RNA (gRNA) in human cells. For the endogenous AAVS1 locus, we obtained targeting rates of 10 to 25% in 293T cells, 13 to 8% in K562 cells, and 2 to 4% in induced pluripotent stem cells. We show that this process relies on CRISPR components; is sequence-specific; and, upon simultaneous introduction of multiple gRNAs, can effect multiplex editing of target loci. We also compute a genome-wide resource of ~190 K unique gRNAs targeting ~40.5% of human exons. Our results establish an RNA-guided editing tool for facile, robust, and multiplexable human genome engineering.
DecaWave : Exploring State of the Art Commercial Localization

In developing technology for indoor localization, we have recently begun exploring commercially available state of the art localization technologies. The DecaWave DW1000 is a new ultra-wideband transceiver that advertises high-precision indoor pairwise ranging between modules with errors as low as 10 cm. We are currently exploring this technology to automate obtaining anchor ground-truth locations for other indoor localization systems. Anchor positioning is a constrained version of indoor localization, with minimal time constraints and static devices. However, as we intend to include the DW1000 hardware on our own localization system, this provides an opportunity for gathering performance data for a commerciallyenabled localization system deployed by a third-party for comparison purposes. We do not claim the ranging hardware as our original work, but we do provide a hardware implementation, an infrastructure for converting pairwise measurements to locations, and the front-end for viewing the results.
The Nature of Love

Love is a wondrous state, deep, tender, and rewarding. Because of its intimate and personal nature it is regarded by some as an improper topic for experimental research. But, whatever our personal feelings may be, our assigned mission as psychologists is to analyze all facets of human and animal behavior into their component variables. So far as love or affection is concerned, psychologists have failed in this mission. The little we know about love does not transcend simple observation, and the little we write about it has been written better by poets and novelists. But of greater concern is the fact that psychologists tend to give progressively less attention to a motive which pervades our entire lives. Psychologists, at least psychologists who write textbooks, not only show no interest in the origin and development of love or affection, but they seem to be unaware of its very existence.
General SPICE Models for Memristor and Application to Circuit Simulation of Memristor-Based Synapses and Memory Cells

Memristor had been ̄rst theorized nearly 40 years ago by Prof. Chua, as the fourth fundamental circuit element beside the three existing elements (Resistor, Capacitor and Inductor) but because no one has succeeded in building a memristor, it has long remained a theoretical element. Some months ago, Hewlett-Packard (hp) announced it created a memristor using a TiO2=TiO2 X structure. In this paper, the characteristics, structures and relations for the invented hp's memristor are brie°y reviewed and then two general SPICE models for the charge-controlled and °ux-controlled memristors are introduced for the ̄rst time. By adjusting the model parameters to the hp's memristor characteristics some circuit properties of the device are studied and then two important memristor applications as the memory cell in a nonvolatileRAM structure and as the synapse in an arti ̄cial neural network are studied. By utilizing the introduced models and designing the appropriate circuits for two most important applications; a nonvolatile memory structure and a programmable logic gate, circuit simulations are done and the results are presented.
Around-body interaction: sensing & interaction techniques for proprioception-enhanced input with mobile devices

The space around the body provides a large interaction volume that can allow for big interactions on small mobile devices. However, interaction techniques making use of this opportunity are underexplored, primarily focusing on distributing information in the space around the body. We demonstrate three types of around-body interaction including canvas, modal and context-aware interactions in six demonstration applications. We also present a sensing solution using standard smartphone hardware: a phone's front camera, accelerometer and inertia measurement units. Our solution allows a person to interact with a mobile device by holding and positioning it between a normal field of view and its vicinity around the body. By leveraging a user's proprioceptive sense, around-body Interaction opens a new input channel that enhances conventional interaction on a mobile device without requiring additional hardware.
A review of machine learning methods to predict the solubility of overexpressed recombinant proteins in Escherichia coli

Over the last 20 years in biotechnology, the production of recombinant proteins has been a crucial bioprocess in both biopharmaceutical and research arena in terms of human health, scientific impact and economic volume. Although logical strategies of genetic engineering have been established, protein overexpression is still an art. In particular, heterologous expression is often hindered by low level of production and frequent fail due to opaque reasons. The problem is accentuated because there is no generic solution available to enhance heterologous overexpression. For a given protein, the extent of its solubility can indicate the quality of its function. Over 30% of synthesized proteins are not soluble. In certain experimental circumstances, including temperature, expression host, etc., protein solubility is a feature eventually defined by its sequence. Until now, numerous methods based on machine learning are proposed to predict the solubility of protein merely from its amino acid sequence. In spite of the 20 years of research on the matter, no comprehensive review is available on the published methods. This paper presents an extensive review of the existing models to predict protein solubility in Escherichia coli recombinant protein overexpression system. The models are investigated and compared regarding the datasets used, features, feature selection methods, machine learning techniques and accuracy of prediction. A discussion on the models is provided at the end. This study aims to investigate extensively the machine learning based methods to predict recombinant protein solubility, so as to offer a general as well as a detailed understanding for researches in the field. Some of the models present acceptable prediction performances and convenient user interfaces. These models can be considered as valuable tools to predict recombinant protein overexpression results before performing real laboratory experiments, thus saving labour, time and cost.
A dynamic decoupling control algorithm for Halbach array permanent magnet spherical motor based on computed torque method

A Halbach array permanent magnet spherical motor (HPMSM) can provide 3 degrees-of-freedom motion in a single joint, simplify the mechanical structure greatly, improve the positioning precision and response speed. However, a HPMSM is a multivariable, nonlinear and strong coupling system with serious inter-axis nonlinear coupling. The dynamic model of a HPMSM is described in this paper, and a control algorithm based on computed torque method is proposed to realize the dynamic decoupling control of the HPMSM. Simulations results indicate that this algorithm can make the system track continues trajectory ideally and eliminate the influences of inter-axis nonlinear coupling effectively to achieve a good control performance.
' s personal copy Influencing behaviour : The mindspace way

The ability to influence behaviour is central to many of the key policy challenges in areas such as health, finance and climate change. The usual route to behaviour change in economics and psychology has been to attempt to ‘change minds’ by influencing the way people think through information and incentives. There is, however, increasing evidence to suggest that ‘changing contexts’ by influencing the environments within which people act (in largely automatic ways) can have important effects on behaviour. We present a mnemonic, MINDSPACE, which gathers up the nine most robust effects that influence our behaviour in mostly automatic (rather than deliberate) ways. This framework is being used by policymakers as an accessible summary of the academic literature. To motivate further research and academic scrutiny, we provide some evidence of the effects in action and highlight some of the significant gaps in our knowledge.  (2012) 264–277