nils-herrmann/clean_scirepeval huggingface dataset:
Organizational Determinants of Interprofessional Collaboration in Integrative Health Care: Systematic Review of Qualitative Studies

Inteprofessional collaboration (IPC) between biomedically trained doctors (BMD) and traditional, complementary and alternative medicine practitioners (TCAMP) is an essential element in the development of successful integrative healthcare (IHC) services. This systematic review aims to identify organizational strategies that would facilitate this process.



We searched 4 international databases for qualitative studies on the theme of BMD-TCAMP IPC, supplemented with a purposive search of 31 health services and TCAM journals. Methodological quality of included studies was assessed using published checklist. Results of each included study were synthesized using a framework approach, with reference to the Structuration Model of Collaboration.



Thirty-seven studies of acceptable quality were included. The main driver for developing integrative healthcare was the demand for holistic care from patients. Integration can best be led by those trained in both paradigms. Bridge-building activities, positive promotion of partnership and co-location of practices are also beneficial for creating bonding between team members. In order to empower the participation of TCAMP, the perceived power differentials need to be reduced. Also, resources should be committed to supporting team building, collaborative initiatives and greater patient access. Leadership and funding from central authorities are needed to promote the use of condition-specific referral protocols and shared electronic health records. More mature IHC programs usually formalize their evaluation process around outcomes that are recognized both by BMD and TCAMP.



The major themes emerging from our review suggest that successful collaborative relationships between BMD and TCAMP are similar to those between other health professionals, and interventions which improve the effectiveness of joint working in other healthcare teams with may well be transferable to promote better partnership between the paradigms. However, striking a balance between the different practices and preserving the epistemological stance of TCAM will remain the greatest challenge in successful integration.
Discrete exterior calculus discretization of incompressible Navier-Stokes equations over surface simplicial meshes

A conservative discretization of incompressible Navier-Stokes equations is developed based on discrete exterior calculus (DEC). A distinguishing feature of our method is the use of an algebraic discretization of the interior product operator and a combinatorial discretization of the wedge product. The governing equations are first rewritten using the exterior calculus notation, replacing vector calculus differential operators by the exterior derivative, Hodge star and wedge product operators. The discretization is then carried out by substituting with the corresponding discrete operators based on the DEC framework. Numerical experiments for flows over surfaces reveal a second order accuracy for the developed scheme when using structured-triangular meshes, and first order accuracy for otherwise unstructured meshes. By con∗Corresponding author Email addresses: mamdouh.mohamed@kaust.edu.sa (Mamdouh S. Mohamed), hirani@illinois.edu (Anil N. Hirani), ravi.samtaney@kaust.edu.sa (Ravi Samtaney) On leave, Department of Mechanical Design and Production, Faculty of Engineering, Cairo University, Giza, Egypt.  2016 struction, the method is conservative in that both mass and vorticity are conserved up to machine precision. The relative error in kinetic energy for inviscid flow test cases converges in a second order fashion with both the mesh size and the time step.
Velocity/Position Integration Formula Part I: Application to In-Flight Coarse Alignment

The in-flight alignment is a critical stage for airborne inertial navigation system/Global Positioning System (INS/GPS) applications. The alignment task is usually carried out by the Kalman filtering technique that necessitates a good initial attitude to obtain a satisfying performance. Due to the airborne dynamics, the in-flight alignment is much more difficult than the alignment on the ground. An optimization-based coarse alignment approach that uses GPS position/velocity as input, founded on the newly-derived velocity/position integration formulae is proposed. Simulation and flight test results show that, with the GPS lever arm well handled, it is potentially able to yield the initial heading up to 1 deg accuracy in 10 s. It can serve as a nice coarse in-flight alignment without any prior attitude information for the subsequent fine Kalman alignment. The approach can also be applied to other applications that require aligning the INS on the run.
Thesaurus-based named entity recognition system for detecting spatio-temporal crime events in Spanish language from Twitter

Social networks offer an invaluable amount of data from which useful information can be obtained on the major issues in society, among which crime stands out. Research about information extraction of criminal events in Social Networks has been done primarily in English language, while in Spanish, the problem has not been addressed. This paper propose a system for extracting spatio-temporally tagged tweets about crime events in Spanish language. In order to do so, it uses a thesaurus of criminality terms and a NER (named entity recognition) system to process the tweets and extract the relevant information. The NER system is based on the implementation OSU Twitter NLP Tools, which has been enhanced for Spanish language. Our results indicate an improved performance in relation to the most relevant tools such as Standford NER and OSU Twitter NLP Tools, achieving 80.95% precision, 59.65% recall and 68.69% F-measure. The end result shows the crime information broken down by place, date and crime committed through a webservice.
Realtime Two-Way Coupling of Meshless Fluids and Nonlinear FEM

In this paper, we present a novel method to couple Smoothed Particle Hydrodynamics (SPH) and nonlinear FEM to animate the interaction of fluids and deformable solids in real time. To accurately model the coupling, we generate proxy particles over the boundary of deformable solids to facilitate the interaction with fluid particles, and develop an efficient method to distribute the coupling forces of proxy particles to FEM nodal points. Specifically, we employ the Total Lagrangian Explicit Dynamics (TLED) finite element algorithm for nonlinear FEM because of many of its attractive properties such as supporting massive parallelism, avoiding dynamic update of stiffness matrix computation, and efficient solver. Based on a predictor-corrector scheme for both velocity and position, different normal and tangential conditions can be realized even for shell-like thin solids. Our coupling method is entirely implemented on modern GPUs using CUDA. We demonstrate the advantage of our two-way coupling method in computer animation via various virtual scenarios.
A GNSS anti-spoofing technology based on Doppler shift in vehicle networking

Modern vehicles incorporate dozens of sensors to provide vital sensor data to the system, where GNSS (global satellite navigation system) gives the localization, navigation, and time synchronization that can improve the safety factor of the vehicles. However, the GNSS signal is very vulnerable to jamming especially spoofing attacks that have great influence on safety and financially critical applications. It is important to protect GNSS from all kinds of jamming, which can guarantee the stability. So many anti-spoofing schemes are proposed which mainly on spoofing detection. But they have large-complexity that cannot be used in real-time scenario. In this paper, a GNSS anti-spoofing technology based on Doppler shift in vehicle networking is proposed. In the case where one spoofing source is present that contains several spoofing signals, it can conduct the spoofing detection using two methods given in this paper with a low cost. The technology is very effective and validated through simulation results.
1.3 V 20 ps time-to-digital converter for frequency synthesis in 90-nm CMOS

We propose and demonstrate a 20-ps time-to-digital converter (TDC) realized in 90-nm digital CMOS. It is used as a phase/frequency detector and charge pump replacement in an all-digital phase-locked loop for a fully-compliant Global System for Mobile Communications (GSM) transceiver. The TDC core is based on a pseudodifferential digital architecture that makes it insensitive to nMOS and pMOS transistor mismatches. The time conversion resolution is equal to an inverter propagation delay, which is the finest logic-level regenerative timing in CMOS. The TDC is self calibrating with the estimation accuracy better than 1%. It additionally serves as a CMOS process strength estimator for analog circuits in this large system-on-chip. Measured integral nonlinearity is 0.7 least significant bits. The TDC consumes 5.3 mA raw and 1.3 mA with power management from a 1.3-V supply.
Generative Model for Material Experiments Based on Prior Knowledge and Attention Mechanism

Material irradiation experiment is dangerous and complex, thus it requires those with a vast advanced expertise to process the images and data manually. In this paper, we propose a generative adversarial model based on prior knowledge and attention mechanism to achieve the generation of irradiated material images (datato-image model), and a prediction model for corresponding industrial performance (image-to-data model). With the proposed models, researchers can skip the dangerous and complex irradiation experiments and obtain the irradiation images and industrial performance parameters directly by inputing some experimental parameters only. We also introduce a new dataset ISMD which contains 22000 irradiated images with 22,143 sets of corresponding parameters. Our model achieved high quality results by compared with several baseline models. The evaluation and detailed analysis are also performed.
A Heuristics Approach for Fast Detecting Suspicious Money Laundering Cases in an Investment Bank

Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most international financial institutions have been implementing anti-money laundering solutions (AML) to fight investment fraud. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project for the purpose of developing a new solution for the AML Units in an international investment bank, we proposed a data mining-based solution for AML. In this paper, we present a heuristics approach to improve the performance for this solution. We also show some preliminary results associated with this method on analysing transaction datasets. data mining, anti money laundering, clustering, heuristics.
Preclinical dose number and its application in understanding drug absorption risk and formulation design for preclinical species.

In the drug discovery setting, the ability to rapidly identify drug absorption risk in preclinical species at high doses from easily measured physical properties is desired. This is due to the large number of molecules being evaluated and their high attrition rate, which make resource-intensive in vitro and in silico evaluation unattractive. High-dose in vivo data from rat, dog, and monkey are analyzed here, using a preclinical dose number (PDo) concept based on the dose number described by Amidon and other authors ( 1993, 10, 264-270). PDo, as described in this article, is simply calculated as dose (mg/kg) divided by compound solubility in FaSSIF (mg/mL) and approximates the volume of biorelevant media per kilogram of animal that would be needed to fully dissolve the dose. High PDo values were found to be predictive of difficulty in achieving drug exposure (AUC)-dose proportionality in in vivo studies, as could be expected; however, this work analyzes a large data set (>900 data points) and provides quantitative guidance to identify drug absorption risk in preclinical species based on a single solubility measurement commonly carried out in drug discovery. Above the PDo values defined, >50% of all in vivo studies exhibited poor AUC-dose proportionality in rat, dog, and monkey, and these values can be utilized as general guidelines in discovery and early development to rapidly assess risk of solubility-limited absorption for a given compound. A preclinical dose number generated by biorelevant dilutions of formulated compounds (formulated PDo) was also evaluated and defines solubility targets predictive of suitable AUC-dose proportionality in formulation development efforts. Application of these guidelines can serve to efficiently identify compounds in discovery that are likely to present extreme challenges with respect to solubility-limited absorption in preclinical species as well as reduce the testing of poor formulations in vivo, which is a key ethical and resource matter.
A 910MHz/2.4GHz easily tunable dual-band antenna for power harvesting and sensor networking applications

This work presents a 910MHz/2.4GHz dual-band dipole antenna for Power Harvesting and/or Sensor Network applications whose main advantage lies on its easily tunable bands. Tunability is achieved via the low and high frequency dipole separation Wgap. This separation is used to increase or decrease the S11 magnitude of the required bands. Such tunability can be used to harvest energy in environments where the electric field strength of one carrier band is dominant over the other one, or in the case when both carriers have similar electric field strength. If the environment is crowed by 820MHz-1.02GHz carries Wgap is adjusted to 1mm in order to harvest/sense only the selected band; if the environment is full of 2.24GHz - 2.52 GHz carriers Wgap is set to 7mm. When Wgap is selected to 4mm both bands can be harvested/sensed. The proposed antenna works for UHF-RFID, GSM-840MHz, 3G-UMTS, Wi-Fi and Bluetooth standards. Simulations are carried out in Advanced Design System (ADS) Momentum using commercial FR4 printed circuit board specification.
A simple and effective method for online signature verification

This paper presents a simple and efficient method for online signature verification. The technique is based on a feature set comprising of several histograms that can be computed efficiently given a raw data sequence of an online signature. The features which are represented by a fixed-length vector can not be used to reconstruct the original signature, thereby providing privacy to the user's biometric trait in case the stored template is compromised. To test the verification performance of the proposed technique, several experiments were conducted on the well known MCYT-100 and SUSIG datasets including both skilled forgeries and random forgeries. Experimental results demonstrate that the performance of the proposed technique is comparable to state-of-art algorithms despite its simplicity and efficiency.
Structure and stereochemistry of the active metabolite of clopidogrel.

Clopidogrel (SR25990C, PLAVIX) is a potent antiplatelet drug, which has been recently launched and is indicated for the prevention of vascular thrombotic events in patients at risk. Clopidogrel is inactive in vitro, and a hepatic biotransformation is necessary to express the full antiaggregating activity of the drug. Moreover, 2-oxo-clopidogrel has been previously suggested to be the essential key intermediate metabolite from which the active metabolite is formed. In the present paper, we give the evidence of the occurrence of an in vitro active metabolite after incubation of 2-oxo-clopidogrel with human liver microsomes. This metabolite was purified by liquid chromatography, and its structure was studied by a combination of mass spectometry (MS) and NMR experiments. MS results suggested that the active metabolite belongs to a family of eight stereoisomers with the following primary chemical structure: 2-[1-[1-(2-chlorophenyl)-2-methoxy-2-oxoethyl]-4-sulfanyl-3-piperidinylidene]acetic acid. Chiral supercritical fluid chromatography resolved these isomers. However, only one of the eight metabolites retained the biological activity, thus underlining the critical importance of associated absolute configuration. Because of its highly labile character, probably due to a very reactive thiol function, structural elucidation of the active metabolite was performed on the stabilized acrylonitrile derivative. Conjunction of all our results suggested that the active metabolite is of S configuration at C 7 and Z configuration at C 3-C 16 double bound.
Why and how developers fork what from whom in GitHub

Forking is the creation of a new software repository by copying another repository. Though forking is controversial in traditional open source software (OSS) community, it is encouraged and is a built-in feature in GitHub. Developers freely fork repositories, use codes as their own and make changes. A deep understanding of repository forking can provide important insights for OSS community and GitHub. In this paper, we explore why and how developers fork what from whom in GitHub. We collect a dataset containing 236,344 developers and 1,841,324 forks. We make surveys, and analyze programming languages and owners of forked repositories. Our main observations are: (1) Developers fork repositories to submit pull requests, fix bugs, add new features and keep copies etc. Developers find repositories to fork from various sources: search engines, external sites (e.g., Twitter, Reddit), social relationships, etc. More than 42 % of developers that we have surveyed agree that an automated recommendation tool is useful to help them pick repositories to fork, while more than 44.4 % of developers do not value a recommendation tool. Developers care about repository owners when they fork repositories. (2) A repository written in a developer’s preferred programming language is more likely to be forked. (3) Developers mostly fork repositories from creators. In comparison with unattractive repository owners, attractive repository owners have higher percentage of organizations, more followers and earlier registration in GitHub. Our results show that forking is mainly used for making contributions of original repositories, and it is beneficial for OSS community. Moreover, our results show the value of recommendation and provide important insights for GitHub to recommend repositories.
Hybrid bonding technology with Cu-Cu/adhesives for high density 2.5D/3D integration

We have developed Cu-Cu/adhesives hybrid bonding technique by using collective cutting of Cu bumps and adhesives in order to achieve high density 2.5D/3D integration. It is considered that progression of high density interconnection leads to lower height of bonding electrodes, resulting in narrow gap between ICs. Therefore, it is difficult to fill in adhesive to such a narrow gap ICs after bonding. Thus, we consider that hybrid bonding of pre-applied adhesives and Cu-Cu thermocompression bonding must be advantageous, in terms of void less bonding and minimizing bonding stress by adhesives and also low electricity by Cu-Cu solid diffusion bonding. In the present study, we adapted the following process; at first adhesives were spin coated on the wafer with Cu post and then pre-baked. After that, pre-applied adhesives and Cu bumps were simultaneously cut by single crystal diamond bite. We found that both adhesives and Cu post surfaces after cutting have highly smooth surface less than 10nm, and dishing phenomena, which might be occurred in typical CMP process, could not be seen on the cut Cu post/ adhesives surfaces.
Indoor Localization and Tracking using Wi-Fi Access Points

Location finding by using wireless technology is one of the emerging and important technologies of wireless sensor networks. GPS can be utilized for outdoor areas only it cannot be used for tracking the user inside the building. The main motivation of this paper is to implement the system which can locate and track the user inside the building. Indoor locations include buildings like an airport, huge malls, supermarkets, universities and large infrastructures. The significant problem that this system solves is of tracking the user inside the building. The accurate indoor location can be found out by using the Received Signal Strength Indication (RSSI). The additional hardware is not required for RSSI, and moreover, it is easy to understand. The RSS (Received Signal Strength) values are calculated with the help of WiFi Access points and the mobile device. The system should provide the exact location of the user and also track the user. This paper presents a system that helps in finding out the exact location and tracking of the mobile device in the indoor environment. It can also be used to navigate the user to a required destination using the navigation function.
Mosaic block detection based on HOG with SVM classifier and template matching

Digital video signal is widely used in modern society. There is increasing demand for it to be more secure and highly reliable. Focusing on this, we propose a method of detecting mosaic blocks. Our proposed method combines two algorithms: HOG with SVM classifier and template matching. We also consider characteristics of mosaic blocks other than shape. Experimental results show that our proposed method has high detection performance of mosaic blocks.
Aggregating Inter-Sentence Information to Enhance Relation Extraction

Previous work for relation extraction from free text is mainly based on intra-sentence information. As relations might be mentioned across sentences, inter-sentence information can be leveraged to improve distantly supervised relation extraction. To effectively exploit inter-sentence information , we propose a ranking-based approach, which first learns a scoring function based on a listwise learning-to-rank model and then uses it for multi-label relation extraction. Experimental results verify the effectiveness of our method for aggregating information across sentences. Additionally, to further improve the ranking of high-quality extractions, we propose an effective method to rank relations from different entity pairs. This method can be easily integrated into our overall relation extraction framework, and boosts the precision significantly.
Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz

The variational quantumeigensolver (VQE) algorithmcombines the ability of quantumcomputers to efficiently compute expectation valueswith a classical optimization routine inorder to approximate ground state energies of quantumsystems. In this paper,we study the applicationofVQE to the simulation ofmolecular energies using theunitary coupled cluster (UCC) ansatz.We introducenew strategies to reduce the circuit depth for the implementationofUCCand improve theoptimizationof thewavefunction basedonefficient classical approximationsof the cluster amplitudes.Additionally,wepropose an analytical method to compute the energy gradient that reduces the sampling cost for gradient estimationby several orders ofmagnitude compared tonumerical gradients.We illustrate ourmethodologywithnumerical simulations for a systemof fourhydrogen atoms that exhibit strong correlation and show that the circuit depthofVQEusing aUCCansatz canbe reducedwithout introducing significant loss of accuracy in the finalwavefunctions and energies.