nils-herrmann/clean_scirepeval huggingface dataset:
Towards Personalized Medicine: Leveraging Patient Similarity and Drug Similarity Analytics

The rapid adoption of electronic health records (EHR) provides a comprehensive source for exploratory and predictive analytic to support clinical decision-making. In this paper, we investigate how to utilize EHR to tailor treatments to individual patients based on their likelihood to respond to a therapy. We construct a heterogeneous graph which includes two domains (patients and drugs) and encodes three relationships (patient similarity, drug similarity, and patient-drug prior associations). We describe a novel approach for performing a label propagation procedure to spread the label information representing the effectiveness of different drugs for different patients over this heterogeneous graph. The proposed method has been applied on a real-world EHR dataset to help identify personalized treatments for hypercholesterolemia. The experimental results demonstrate the effectiveness of the approach and suggest that the combination of appropriate patient similarity and drug similarity analytics could lead to actionable insights for personalized medicine. Particularly, by leveraging drug similarity in combination with patient similarity, our method could perform well even on new or rarely used drugs for which there are few records of known past performance.
Bullous Scabies.

Scabies is a common contagious cutaneous disease and usually affects the young, characterized by polymorphous lesions that may present as burrows, pruritic papules, and inflammatory nodules. Bullous scabies (BS) is its rather rare subtype, mimicking bullous pemphigoid. We report a 15-year-old Chinese boy presenting with 1-month history of pruritic bullae on his penile skin, showing poor response to both topical steroids and systemic antihistamines, but cured by sulfur ointment alone. No recurrence occurred in the 5 years of follow-up. We also reviewed the published cases. Up to date, 44 cases, including the present, have been reported. Of them, 30 were male and 14 were female. The age range was from 1 to 89 years old, with a median age of 70.6 years. The bullous lesions may involve the arms, legs, trunk, genitals, feet, buttocks, thighs, neck, inguinal folds, and may even be generalized. Trunk and extremities are the most common involved locations. Facial or mucosa involvement had never been reported. The histological findings present as a subepidermal split with variable inflammatory infiltrate predominantly neutrophils, and eosinophilic spongiosis, or both. Eighteen of 32 patients showed positive deposition of linear-granular IgG or complement 3 alone or in various combinations, and five of 24 patients revealed circulating IgG. All the 40 cases with therapeutic details were cured by antiscabietic remedy. BS always involves the trunk and extremities. It has a predilection for elderlies and males. The treatments for BS are similar to those of classical scabies.
Underwater Object Tracking Using Sonar and USBL Measurements

In the scenario where an underwater vehicle tracks an underwater target, reliable estimation of the target position is required.While USBL measurements provide target position measurements at low but regular update rate, multibeam sonar imagery gives high precision measurements but in a limited field of view. This paper describes the development of the tracking filter that fuses USBL and processed sonar image measurements for tracking underwater targets for the purpose of obtaining reliable tracking estimates at steady rate, even in cases when either sonar or USBL measurements are not available or are faulty. The proposed algorithms significantly increase safety in scenarios where underwater vehicle has to maneuver in close vicinity to human diver who emits air bubbles that can deteriorate tracking performance. In addition to the tracking filter development, special attention is devoted to adaptation of the region of interest within the sonar image by using tracking filter covariance transformation for the purpose of improving detection and avoiding false sonar measurements. Developed algorithms are tested on real experimental data obtained in field conditions. Statistical analysis shows superior performance of the proposed filter compared to conventional tracking using pure USBL or sonar measurements.
Energy Efficient Mobile Cloud Computing Powered by Wireless Energy Transfer

Achieving long battery lives or even self sustainability has been a long standing challenge for designing mobile devices. This paper presents a novel solution that seamlessly integrates two technologies, mobile cloud computing and microwave power transfer (MPT), to enable computation in passive low-complexity devices such as sensors and wearable computing devices. Specifically, considering a single-user system, a base station (BS) either transfers power to or offloads computation from a mobile to the cloud; the mobile uses harvested energy to compute given data either locally or by offloading. A framework for energy efficient computing is proposed that comprises a set of policies for controlling CPU cycles for the mode of local computing, time division between MPT and offloading for the other mode of offloading, and mode selection. Given the CPU-cycle statistics information and channel state information (CSI), the policies aim at maximizing the probability of successfully computing given data, called computing probability, under the energy harvesting and deadline constraints. The policy optimization is translated into the equivalent problems of minimizing the mobile energy consumption for local computing and maximizing the mobile energy savings for offloading which are solved using convex optimization theory. The structures of the resultant policies are characterized in closed form. Furthermore, given non-causal CSI, the said analytical framework is further developed to support computation load allocation over multiple channel realizations, which further increases the computing probability. Last, simulation demonstrates the feasibility of wirelessly powered mobile cloud computing and the gain of its optimal control.
Auricular acupuncture in the treatment of cocaine/crack abuse: a review of the efficacy, the use of the National Acupuncture Detoxification Association protocol, and the selection of sham points.

The United Kingdom has had a significant increase in addiction to and use of cocaine among 16-29-year olds from 6% in 1998 to 10% in 2000. In 2000, the United Kingdom had the highest recorded consumption of "recent use" cocaine in Europe, with 3.3% of young adults. Acupuncture is quick, inexpensive, and relatively safe, and may establish itself as an important addiction service in the future.



To select investigations that meet the inclusion criteria and critically appraise them in order to answer the question: "Is acupuncture effective in the treatment of cocaine addiction?" The focus shall then be directed toward the use of the National Acupuncture Detoxification Association (NADA) protocol as the intervention and the selection of sham points for the control group.



The ARRC database was accessed from Trina Ward (M. Phil. student) at Thames Valley University. AMED, MEDLINE and Embase were also accessed along with "hand" searching methods at the British Library.



People addicted to either cocaine or crack cocaine as their main addiction, needle-acupuncture, single-double-blinded process, randomized subjects, a reference group incorporating a form of sham points.



use of moxibustion, laser acupuncture, transcutaneous electrical nerve stimulation (TENS) electroacupuncture or conditions that did not meet the inclusion criteria.



The criteria set by ter Riet, Kleijnen and Knipschild (in 1990); Hammerschlag and Morris (in 1990); Koes, Bouter and van der Heijden (in 1995), were modified into one set of criteria consisting of 27 different values.



Six randomized controlled trials (RCTs) met the inclusion criteria and were included in this review. All studies scored over 60 points indicating a relatively adequate methodology quality. The mean was 75 and the standard deviation was 6.80. A linear regression analysis did not yield a statistically significant association (n = 6, p = 0.11).



This review could not confirm that acupuncture was an effective treatment for cocaine abuse. The NADA protocol of five treatment points still offers the acupuncturist the best possible combination of acupuncture points based upon Traditional Chinese Medicine. Throughout all the clinical trials reviewed, no side-effects of acupuncture were noted. This paper calls for the full set of 5 treatment points as laid out by the NADA to be included as the treatment intervention. Points on the helix, other than the liver yang points, should be selected as sham points for the control group.
mini-Tn7 insertion in bacteria with single attTn7 sites: example Pseudomonas aeruginosa

Broad host-range mini-Tn7 vectors facilitate integration of single-copy genes into bacterial chromosomes at a neutral, naturally evolved site. Here we present a protocol for employing the mini-Tn7 system in bacteria with single attTn7 sites, using the example Pseudomonas aeruginosa. The procedure involves, first, cloning of the genes of interest into an appropriate mini-Tn7 vector; second, co-transfer of the recombinant mini-Tn7 vector and a helper plasmid encoding the Tn7 site-specific transposition pathway into P. aeruginosa by either transformation or conjugation, followed by selection of insertion-containing strains; third, PCR verification of mini-Tn7 insertions; and last, optional Flp-mediated excision of the antibiotic-resistance selection marker present on the chromosomally integrated mini-Tn7 element. From start to verification of the insertion events, the procedure takes as little as 4 d and is very efficient, yielding several thousand transformants per microgram of input DNA or conjugation mixture. In contrast to existing chromosome integration systems, which are mostly based on species-specific phage or more-or-less randomly integrating transposons, the mini-Tn7 system is characterized by its ready adaptability to various bacterial hosts, its site specificity and its efficiency. Vectors have been developed for gene complementation, construction of gene fusions, regulated gene expression and reporter gene tagging.
Spline-Based Image Registration

The problem of image registration subsumes a number of problems and techniques in multiframe image analysis, including the computation of optic flow (general pixel-based motion), stereo correspondence, structure from motion, and feature tracking. We present a new registration algorithm based on spline representations of the displacement field which can be specialized to solve all of the above mentioned problems. In particular, we show how to compute local flow, global (parametric) flow, rigid flow resulting from camera egomotion, and multiframe versions of the above problems. Using a spline-based description of the flow removes the need for overlapping correlation windows, and produces an explicit measure of the correlation between adjacent flow estimates. We demonstrate our algorithm on multiframe image registration and the recovery of 3D projective scene geometry. We also provide results on a number of standard motion sequences.
Discovering User Interest on Twitter with a Modified Author-Topic Model

This paper focuses on the problem of discovering users' topics of interest on Twitter. While previous efforts in modeling users' topics of interest on Twitter have focused on building a "bag-of-words" profile for each user based on his tweets, they overlooked the fact that Twitter users usually publish noisy posts about their lives or create conversation with their friends, which do not relate to their topics of interest. In this paper, we propose a novel framework to address this problem by introducing a modified author-topic model named twitter-user model. For each single tweet, our model uses a latent variable to indicate whether it is related to its author's interest. Experiments on a large dataset we crawled using Twitter API demonstrate that our model outperforms traditional methods in discovering user interest on Twitter.
An Approximate, Efficient Solver for LP Rounding

The vertex cover problem Find a set of vertices that cover the graph LP rounding is a 4 step scheme to approximate combinatorial problems with theoretical guarantees on solution quality. Several problems in machine learning, computer vision and data analysis can be formulated using NP-­‐hard combinatorial optimization problems. In many of these applications, approximate solutions for these NP-­‐hard problems are 'good enough'.
Finger design automation for industrial robot grippers: A review

Designing robust end-effector plays a crucial role in performance of a robot workcell. Design automation of industrial grippers’ fingers/jaws is therefore of the highest interest in the robot industry. This paper systematically reviews the enormous studies performed in relevant research areas for finger design automation. Key processes for successfully achieving automatic finger design are identified and research contributions in each key process are critically reviewed. The proposed approaches in each key process are analyzed, verified and benchmarked. The most promising methods to accomplish finger design automation are highlighted and presented.
Challenges faced by Small and Medium Enterprise Suppliers when bidding for tenders . A case of Thika District

The Public procurement market in Kenya like other countries worldwide deal with a wide range of supplies. Though these contracts vary mainly in size, some are clearly within the capabilities of Small and Medium size Enterprises (SMEs). However, SMEs are sidelined from participating in public procurement despite their qualifications, sizes and level of production and despite this preferential treatment of SMEs, comparative tallies of public contracts secured by SMEs in Thika District against those secured by large enterprises are still very small. The study examined the challenges that the SMEs in Thika District face when bidding for tenders and it seeks to determine why they risk losing tenders. The research design used was descriptive and exploratory. The study established that there is a clear Legal/Regulatory framework established in the country to knob public procurement though these guidelines are not open to public scrutiny. The conditions for tendering are not the same for each tenderer and there are ethical malpractices sighted during the process. SMEs encounter financial challenges which include financial regulations and shortage of own financial resources. Information on public procurement and tendering to the SMEs is not adequately available as most respondents were not aware of its existence. The research concluded that the existence of the legal framework makes it difficult for upcoming SMEs to compete with the established players thus discouraging their participation. Ethical aspect hinders the SMEs from participating in tendering due to in-transparency in the process. Financial requirement is a hindrance. Information on public procurement and tendering is not adequately available to the SMEs thus poor access to the little information availed to them.
Voronoi-Based Segmentation of Cells on Image Manifolds

We present a method for finding the boundaries between adjacent regions in an image, where “seed” areas have already been identified in the individual regions to be segmented. This method was motivated by the problem of finding the borders of cells in microscopy images, given a labelling of the nuclei in the images. The method finds the Voronoi region of each seed on a manifold with a metric controlled by local image properties. We discuss similarities to other methods based on image-controlled metrics, such as Geodesic Active Contours, and give a fast algorithm for computing the Voronoi regions. We validate our method against hand-traced boundaries for cell images.
Web Page Recommendation Based on Bitwise Frequent Pattern Mining

In many applications, web surfers would like to get recommendation on which collections of web pages that would be interested to them or that they should follow. In order to discover this information and make recommendation, data mining in general—or frequent pattern mining in specific—can be applicable. Since its introduction, frequent pattern mining has drawn attention from many researchers. Consequently, many frequent pattern mining algorithms have been proposed, which include levelwise Apriori-based algorithms, tree-based algorithms, hyperlinked array structure based algorithms, as well as vertical mining algorithms. While these algorithms are popular, they also suffer from some drawbacks. To avoid these drawbacks, we propose an alternative frequent pattern mining algorithm called BW-mine in this paper. Evaluation results show that our proposed algorithm is both space-and time-efficient. Furthermore, to show the practicality of BW-mine in real-life applications, we apply BW-mine to discover popular pages on the web, which in turn gives the web surfers recommendation of web pages that might be interested to them.
Study & Analysis of Web Content Mining Tools to Improve Techniques of Web Data Mining

 Web content mining in normal parlance is to download information available on the websites. Such a process involves tremendous stress and time-taking. To augment such a process the software related to web content mining can be used so that a computer can use this software or tools to download the essential information that one would require. It collects the appropriate and perfectly fitting information from websites that one requires. In this paper several tools for web content mining are discussed and their relative merits and demerits are mentioned.
Tracing the lineage of view data in a warehousing environment

We consider the view data lineageproblem in a warehousing environment: For a given data item in a materialized warehouse view, we want to identify the set of source data items that produced the view item. We formally define the lineage problem, develop lineage tracing algorithms for relational views with aggregation, and propose mechanisms for performing consistent lineage tracing in a multisource data warehousing environment. Our result can form the basis of a tool that allows analysts to browse warehouse data, select view tuples of interest, and then “drill-through” to examine the exact source tuples that produced the view tuples of interest.
An Efficient Cryptographic Hash Algorithm (BSA)

Recent cryptanalytic attacks have exposed the vulnerabilities of some widely used cryptographic hash functions like MD5 and SHA-1. Attacks in the line of differential attacks have been used to expose the weaknesses of several other hash functions like RIPEMD, HAVAL. In this paper we propose a new efficient hash algorithm that provides a near random hash output and overcomes some of the earlier weaknesses. Extensive simulations and comparisons with some existing hash functions have been done to prove the effectiveness of the BSA, which is an acronym for the name of the 3 authors.
Database of normal human cerebral blood flow measured by SPECT: I. Comparison between I-123-IMP, Tc-99m-HMPAO, and Tc-99m-ECD as referred with O-15 labeled water PET and voxel-based morphometry.

Three accumulative tracers, iodine-123-labeled N-isopropyl-p-iodoamphetamine (I-123-IMP), technetium-99m-labeled hexamethylpropyleneamineoxime (Tc-99m-HMPAO), and technetium-99m-labeled ethyl cysteinate dimer (Tc-99m-ECD) are widely used to measure cerebral blood flow (CBF) in single-photon emission computed tomography (SPECT). In the present study, normal regional distribution of CBF measured with three different SPECT tracers was entered into a database and compared with regional distribution of CBF measured by positron emission tomography (PET) with H2(15)O. The regional distribution of tissue fractions of gray matter determined by voxel-based morphometry was also compared with SPECT and PET CBF distributions.



SPECT studies with I-123-IMP, Tc-99m-HMPAO, and Tc-99m-ECD were performed on 11, 20, and 17 healthy subjects, respectively. PET studies were performed on 11 healthy subjects. Magnetic resonance (MR) imaging studies for voxel-based morphometry were performed on 43 of the 48 subjects who underwent SPECT study. All SPECT, PET, and MR images were transformed into the standard brain format with the SPM2 system. The voxel values of each SPECT and PET image were globally normalized to 50 ml/100 ml/min. Gray matter, white matter, and cerebrospinal fluid images were segmented and extracted from all transformed MR images by applying voxel-based morphometry methods with the SPM2 system.



Regional distribution of all three SPECT tracers differed from that of H2150 in the pons, midbrain, thalamus, putamen, parahippocampal gyrus, posterior cingulate gyrus, temporal cortex, and occipital cortex. No significant correlations were observed between the tissue fraction of gray matter and CBF with any tracer.



Differences in regional distribution of SPECT tracers were considered to be caused mainly by differences in the mechanism of retention of tracers in the brain. Regional distribution of CBF was independent of regional distribution of gray matter fractions, and consequently the blood flow per gray matter volume differed for each brain region.
A Direct Torque Controlled Induction Motor with Variable Hysteresis Band

An improved direct torque controlled induction motor drive is reported in this paper. It is established that the conventional direct torque controlled drive has more torque and flux ripples in steady state, which result in poor torque response, acoustic noise and incorrect speed estimations. Hysteresis controllers also make the switching frequency of voltage source inverter a variable quantity. A strategy of variable duty ratio control scheme is proposed to increase switching frequency, and adjust the width of hysteresis bands according to the switching frequency. This technique minimizes torque and current ripples, improves torque response, and reduces switching losses in spite of its simplicity. Simulation results establish the improved performance of the proposed direct torque control method compared to conventional methods.
AMBER: Automatic Supervision for Multi-Attribute Extraction

The extraction of multi-attribute objects from the deep web is the bridge between the unstructured web and structured data. Existing approaches either induce wrappers from a set of human-annotated pages or leverage repeated structures on the page without supervision. What the former lack in automation, the latter lack in accuracy. Thus accurate, automatic multi-attribute object extraction has remained an open challenge. AMBER overcomes both limitations through mutual supervision between the repeated structure and automatically produced annotations. Previous approaches based on automatic annotations have suffered from low quality due to the inherent noise in the annotations and have attempted to compensate by exploring multiple candidate wrappers. In contrast, AMBER compensates for this noise by integrating repeated structure analysis with annotation-based induction: The repeated structure limits the search space for wrapper induction, and conversely, annotations allow the repeated structure analysis to distinguish noise from relevant data. Both, low recall and low precision in the annotations are mitigated to achieve almost human quality (> 98%) multiattribute object extraction. To achieve this accuracy, AMBER needs to be trained once for an entire domain. AMBER bootstraps its training from a small, possibly noisy set of attribute instances and a few unannotated sites of the domain.