nils-herrmann/clean_scirepeval huggingface dataset:
ALOHOMORA: a tool for linkage analysis using 10K SNP array data

ALOHOMORA is a software tool designed to facilitate genome-wide linkage studies performed with high-density single nucleotide polymorphism (SNP) marker panels such as the Affymetrix GeneChip(R) Human Mapping 10K Array. Genotype data are converted into appropriate formats for a number of common linkage programs and subjected to standard quality control routines before linkage runs are started. ALOHOMORA is written in Perl and may be used to perform state-of-the-art linkage scans in small and large families with any genetic model. Options for using different genetic maps or ethnicity-specific allele frequencies are implemented. Graphic outputs of whole-genome multipoint LOD score values are provided for the entire dataset as well as for individual families.


AVAILABILITY
ALOHOMORA is available free of charge for non-commercial research institutions. For more details, see http://gmc.mdc-berlin.de/alohomora/
Long-term culture-initiating cells (LTC-IC) produced from CD34+ cord blood cells with limiting dilution method.

Even though much progress has been made in defining primitive hematologic cell phenotypes by using flow cytometry and clonogenic methods, the direct method for study of marrow repopulating cells still remains to be elusive. Long Term Culture-Initiating Cells (LTC-IC) are known as the most primitive human hematopoietic cells detectable by in vitro functional assays.



In this study, LTC-IC with limiting dilution assay was used to evaluate repopulating potential of cord blood stem cells.



CD34 selections from cord blood were completed succesfully with magnetic beads (73,64%±9,12). The average incidence of week 5 LTC-IC was 1: 1966 CD34+ cells (range 1261-2906).



We found that number of LTC-IC obtained from CD34+ cord blood cells were relatively low in numbers when compared to previously reported bone marrow CD34+ cells. This may be due to the lack of some transcription and growth factors along with some cytokines and chemokines released by accessory cells which are necessary for proliferation of cord blood progenitor/stem cells and it presents an area of interest for further studies.
Auto-Scaling Model for Cloud Computing System

Recently, Cloud Computing introduces some new concepts that entirely change the way applications are built and deployed. Usually, Cloud systems rely on virtualization techniques to allocate computing resources on demand. Thus, scalability is a critical issue to the success of enterprises involved in doing business on the cloud. In this paper, we will describe the novel virtual cluster architecture for dynamic scaling of cloud applications in a virtualized Cloud Computing environment. An auto-scaling algorithm for automated provisioning and balancing of virtual machine resources based on active application sessions will be introduced. Also, the energy cost is considered in the proposed algorithm. Our work has demonstrated the proposed algorithm is capable of handling sudden load requirements, maintaining higher resource utilization and reducing energy cost.
Resonant synchronous rectification for high frequency DC/DC converter

Resonant synchronous rectification for high frequency low voltage high current DC/DC converter is proposed in this paper. It features soft-switching and no body-diode conduction, which is very promising for high switching frequency operation. A family of isolated soft-switching DC/DC converters and two non-isolated soft-switching DC/DC converters implementing the resonant synchronous rectification are proposed in this paper. A prototype of 1 MHz 48 V-to-1.2 V/28 A 1/16 brick DC-DC converter demonstrates the 84% overall efficiency.
The Impact of Layout-Dependent STI Stress and Effective Width on Low-Frequency Noise and High-Frequency Performance in Nanoscale nMOSFETs

The impact of channel width scaling on low-frequency noise (LFN) and high-frequency performance in multifinger MOSFETs is reported in this paper. The compressive stress from shallow trench isolation (STI) cannot explain the lower LFN in extremely narrow devices. STI top corner rounding (TCR)-induced Δ<i>W</i> is identified as an important factor that is responsible for the increase in transconductance <i>Gm</i> and the reduction in LFN with width scaling to nanoscale regime. A semi-empirical model was derived to simulate the effective mobility (μ<sub>eff</sub>) degradation from STI stress and the increase in effective width (<i>W</i><sub>eff</sub>) from Δ<i>W</i> due to STI TCR. The proposed model can accurately predict width scaling effect on <i>Gm</i> based on a tradeoff between μ<sub>eff</sub> and <i>W</i><sub>eff</sub>. The enhanced STI stress may lead to an increase in interface traps density (<i>N</i><sub>it</sub>), but the influence is relatively minor and can be compensated by the <i>W</i><sub>eff</sub> effect. Unfortunately, the extremely narrow devices suffer <i>fT</i> degradation due to an increase in <i>C</i><sub>gg</sub>. The investigation of impact from width scaling on μ<sub>eff</sub>, <i>Gm</i>, and LFN, as well as the tradeoff between LFN and high-frequency performance, provides an important layout guideline for analog and RF circuit design.
Fast and robust face recognition via coding residual map learning based adaptive masking

Robust face recognition (FR) is an active topic in computer vision and biometrics, while face occlusion is one of the most challenging problems for robust FR. Recently, the representation (or coding) based FR schemes with sparse coding coefficients and coding residual have demonstrated good robustness to face occlusion; however, the high complexity of l1-minimization makes them less useful in practical applications. In this paper we propose a novel coding residual map learning scheme for fast and robust FR based on the fact that occluded pixels usually have higher coding residuals when representing an occluded face image over the non-occluded training samples. A dictionary is learned to code the training samples, and the distribution of coding residuals is computed. Consequently, a residual map is learned to detect the occlusions by adaptive thresholding. Finally the face image is identified by masking the detected occlusion pixels from face representation. Experiments on benchmark databases show that the proposed scheme has much lower time complexity but comparable FR accuracy with other popular approaches.
Significance of Forrest Classification , Rockall ’ S and Blatchford ’ S Risk Scoring System in Prediction of Rebleeding in Peptic Ulcer Disease

Prediction of the risk in patients with upper gastrointestinal bleeding has been the subject of different studies for several decades. This study showed the significance of Forrest classification, used in initial endoscopic investigation for evaluation of bleeding lesion, for the prediction of rebleeding. Rockall and Blatchford risk score systems evaluate certain clinical, biochemical and endoscopic variables significant for the prediction of rebleeding as well as the final outcome of disease. The percentage of rebleeding in the group of studied patients in accordance with Forrest classification showed that the largest number of patients belonged to the FIIb group. The predictive evaluation of initial and definitive Rockall score was significantly associated with percentage of rebleeding, while Blatchfor score had boundary significance. Acta Medica Medianae 2007;46(4):38-43.
The Design of a Visual History Tool to help Users Refind Information within a

On the WWW users frequently revisit information they have previously seen, but " keeping found things found " is difficult when the information has not been visited frequently or recently, even if a user knows which website contained the information. This paper describes the design of a tool to help users refind information within a given website. The tool encodes data about a user's interest in webpages (measured by dwell time), the frequency and recency of visits, and navigational associations between pages, and presents navigation histories in list-and graph-based forms. A design evaluation, conducted using examples of refinding failures from a previous user study, shows that list-based presentation helps when users have only visited a small number of pages on a website (this accounted 50+ % of refinding failures). With the tool's filtering capabilities, graph-based presentation is likely to greatly increase success during revisiting when a website has often been used.
Memory-guided exploration in reinforcement learning

The life-long learning architecture attempts to create an adaptive agent through the incorporation of prior knowledge over the lifetime of a learning agent. Our paper focuses on task transfer in reinforcement learning and specifically in Q-learning. There are three main model free methods for performing task transfer in Qlearning: direct transfer, soft transfer and memoryguided exploration. In direct transfer Q-values from a previous task are used to initialize the Q-values of the next task. Soft transfer initializes the Q-values of the new task with a weighted average of the standard initialization value and the Q-values of the previous task. In memory-guided exploration the Q-values of previous tasks are used as a guide in the initial exploration of the agent. The weight that the agent gives to its past experience decreases over time. We explore stability issues related to the off-policy nature of memory-guided exploration and compare memory-guided exploration to soft transfer and direct transfer in three different envi-
Sciatica of nondisc origin and piriformis syndrome: diagnosis by magnetic resonance neurography and interventional magnetic resonance imaging with outcome study of resulting treatment.

Because lumbar magnetic resonance (MR) imaging fails to identify a treatable cause of chronic sciatica in nearly 1 million patients annually, the authors conducted MR neurography and interventional MR imaging in 239 consecutive patients with sciatica in whom standard diagnosis and treatment failed to effect improvement.



After performing MR neurography and interventional MR imaging, the final rediagnoses included the following: piriformis syndrome (67.8%), distal foraminal nerve root entrapment (6%), ischial tunnel syndrome (4.7%), discogenic pain with referred leg pain (3.4%), pudendal nerve entrapment with referred pain (3%), distal sciatic entrapment (2.1%), sciatic tumor (1.7%), lumbosacral plexus entrapment (1.3%), unappreciated lateral disc herniation (1.3%), nerve root injury due to spinal surgery (1.3%), inadequate spinal nerve root decompression (0.8%), lumbar stenosis (0.8%), sacroiliac joint inflammation (0.8%), lumbosacral plexus tumor (0.4%), sacral fracture (0.4%), and no diagnosis (4.2%). Open MR-guided Marcaine injection into the piriformis muscle produced the following results: no response (15.7%), relief of greater than 8 months (14.9%), relief lasting 2 to 4 months with continuing relief after second injection (7.5%), relief for 2 to 4 months with subsequent recurrence (36.6%), and relief for 1 to 14 days with full recurrence (25.4%). Piriformis surgery (62 operations; 3-cm incision, transgluteal approach, 55% outpatient; 40% with local or epidural anesthesia) resulted in excellent outcome in 58.5%, good outcome in 22.6%, limited benefit in 13.2%, no benefit in 3.8%, and worsened symptoms in 1.9%.



This Class A quality evaluation of MR neurography's diagnostic efficacy revealed that piriformis muscle asymmetry and sciatic nerve hyperintensity at the sciatic notch exhibited a 93% specificity and 64% sensitivity in distinguishing patients with piriformis syndrome from those without who had similar symptoms (p < 0.01). Evaluation of the nerve beyond the proximal foramen provided eight additional diagnostic categories affecting 96% of these patients. More than 80% of the population good or excellent functional outcome was achieved.
Depth accuracy of the RealSense F200: Low-cost 4D facial imaging

The RealSense F200 represents a new generation of economically viable 4-dimensional imaging (4D) systems for home use. However, its 3D geometric (depth) accuracy has not been clinically tested. Therefore, this study determined the depth accuracy of the RealSense, in a cohort of patients with a unilateral facial palsy (n = 34), by using the clinically validated 3dMD system as a gold standard. The patients were simultaneously recorded with both systems, capturing six Sunnybrook poses. This study has shown that the RealSense depth accuracy was not affected by a facial palsy (1.48 ± 0.28 mm), compared to a healthy face (1.46 ± 0.26 mm). Furthermore, the Sunnybrook poses did not influence the RealSense depth accuracy (p = 0.76). However, the distance of the patients to the RealSense was shown to affect the accuracy of the system, where the highest depth accuracy of 1.07 mm was measured at a distance of 35 cm. Overall, this study has shown that the RealSense can provide reliable and accurate depth data when recording a range of facial movements. Therefore, when the portability, low-costs, and availability of the RealSense are taken into consideration, the camera is a viable option for 4D close range imaging in telehealth.
Indian concepts on sexuality

India is a vast country depicting wide social, cultural and sexual variations. Indian concept of sexuality has evolved over time and has been immensely influenced by various rulers and religions. Indian sexuality is manifested in our attire, behavior, recreation, literature, sculptures, scriptures, religion and sports. It has influenced the way we perceive our health, disease and device remedies for the same. In modern era, with rapid globalization the unique Indian sexuality is getting diffused. The time has come to rediscover ourselves in terms of sexuality to attain individual freedom and to reinvest our energy to social issues related to sexuality.
A Survey on Expert Recommendation in Community Question Answering

Community question answering (CQA) represents the type of Web applications where people can exchange knowledge via asking and answering questions. One significant challenge of most real-world CQA systems is the lack of effective matching between questions and the potential good answerers, which adversely affects the efficient knowledge acquisition and circulation. On the one hand, a requester might experience many low-quality answers without receiving a quality response in a brief time; on the other hand, an answerer might face numerous new questions without being able to identify the questions of interest quickly. Under this situation, expert recommendation emerges as a promising technique to address the above issues. Instead of passively waiting for users to browse and find their questions of interest, an expert recommendation method raises the attention of users to the appropriate questions actively and promptly. The past few years have witnessed considerable efforts that address the expert recommendation problem from different perspectives. These methods all have their issues that need to be resolved before the advantages of expert recommendation can be fully embraced. In this survey, we first present an overview of the research efforts and state-of-the-art techniques for the expert recommendation in CQA. We next summarize and compare the existing methods concerning their advantages and shortcomings, followed by discussing the open issues and future research directions.
Semantic-Based Image Retrieval in Remote Sensing Archive: An Ontology Approach

In recent years, remote sensing image data have increased significantly due to the improvement of remote sensing technique. On the other hand, data acquisition rate will also be accelerated by increasing satellite sensors. Hence, it is a large challenge to make full use of so considerable data by conventional retrieval approach. The lack of semantic based retrieval capability has impeded application of remote sensing data. To address the issue, we propose a framework based on domain-dependent ontology to perform semantic retrieval in image archives. Firstly, primitive features expressed by color and texture are extracted to gain homogeneous region by means of our unsupervised algorithm. The homogeneous regions are described by high-level concepts depicted and organized by domain specific ontology. Interactive learning technique is employed to associate regions and high-level concepts. These associations are used to perform querying task. Additionally, a reasoning mechanism over ontology integrating an inference engine is discussed. It enables the capability of semantic query in archives by mining the interrelationships among domain concepts and their properties to satisfy users’ requirements. In our framework, ontology is used to provide a sharable and reusable concept set as infrastructure for high level extension such as reasoning. Finally, preliminary results are present and future work is also discussed. KeywordsImage retrieval; Ontology; Semantic reasoning;
Design of Folded Cascode OTA in Different Regions of Operation through gm / ID Methodology

This paper presents an optimized methodology to folded cascode operational transconductance amplifier (OTA) design. The design is done in different regions of operation, weak inversion, strong inversion and moderate inversion using the gm/ID methodology in order to optimize MOS transistor sizing. Using 0.35μm CMOS process, the designed folded cascode OTA achieves a DC gain of 77.5dB and a unity-gain frequency of 430MHz in strong inversion mode. In moderate inversion mode, it has a 92dB DC gain and provides a gain bandwidth product of around 69MHz. The OTA circuit has a DC gain of 75.5dB and unity-gain frequency limited to 19.14MHZ in weak inversion region. CMOS IC design, Folded Cascode OTA, gm/ID methodology, optimization.
Size-Dependent Heating of Magnetic Iron Oxide Nanoparticles.

The ability to generate heat under an alternating magnetic field (AMF) makes magnetic iron oxide nanoparticles (MIONs) an ideal heat source for biomedical applications including cancer thermoablative therapy, tissue preservation, and remote control of cell function. However, there is a lack of quantitative understanding of the mechanisms governing heat generation of MIONs, and the optimal nanoparticle size for magnetic fluid heating (MFH) applications. Here, we show that MIONs with large sizes (>20 nm) have a specific absorption rate (SAR) significantly higher than that predicted by the widely used linear theory of MFH. The heating efficiency of MIONs in both the superparamagnetic and ferromagnetic regimes increased with size, which can be accurately characterized with a modified dynamic hysteresis model. In particular, the 40 nm ferromagnetic nanoparticles have an SAR value approaching the theoretical limit under a clinically relevant AMF. An in vivo study further demonstrated that the 40 nm MIONs could effectively heat tumor tissues at a minimal dose. Our experimental results and theoretical analysis on nanoparticle heating offer important insight into the rationale design of MION-based MFH for therapeutic applications.
Pairing Wi-Fi and Bluetooth MAC addresses through passive packet capture

The majority of smart devices used nowadays (e.g., smartphones, laptops, tablets) is capable of both Wi-Fi and Bluetooth wireless communications. Both network interfaces are identified by a unique 48-bits MAC address, assigned during the manufacturing process and unique worldwide. Such addresses, fundamental for link-layer communications and contained in every frame transmitted by the device, can be easily collected through packet sniffing and later used to perform higher level analysis tasks (user tracking, crowd density estimation, etc.). In this work we propose a system to pair the Wi-Fi and Bluetooth MAC addresses belonging to a physical unique device, starting from packets captured through a network of wireless sniffers. We propose several algorithms to perform such a pairing and we evaluate their performance through experiments in a controlled scenario. We show that the proposed algorithms can pair the MAC addresses with good accuracy. The findings of this paper may be useful to improve the precision of indoor localization and crowd density estimation systems and open some questions on the privacy issues of Wi-Fi and Bluetooth enabled devices.
Identifying Temporal Orientation of Word Senses

The ability to capture time information is essential to many natural language processing and information retrieval applications. Therefore, a lexical resource associating word senses to their temporal orientation might be crucial for the computational tasks aiming at the interpretation of language of time in texts. In this paper, we propose a semi-supervised minimum cuts strategy that makes use of WordNet glosses and semantic relations to supplement WordNet entries with temporal information. Intrinsic and extrinsic evaluations show that our approach outperforms prior semi-supervised non-graph classifiers.
The concept and evolution of involved site radiation therapy for lymphoma

We describe the development of radiation therapy for lymphoma from extended field radiotherapy of the past to modern conformal treatment with involved site radiation therapy based on advanced imaging, three-dimensional treatment planning and advanced treatment delivery techniques. Today, radiation therapy is part of the multimodality treatment of lymphoma, and the irradiated tissue volume is much smaller than before, leading to highly significant reductions in the risks of long-term complications.
Human tracking using floor sensors based on the Markov chain Monte Carlo method

The aim of this paper is to develop a human tracking system that is resistant to environmental changes and covers wide area. Simply structured floor sensors are low-cost and can track people in a wide area. However, the sensor reading is discrete and missing; therefore, footsteps do not represent the precise location of a person. A Markov chain Monte Carlo method (MCMC) is a promising tracking algorithm for these kinds of signals. We applied two prediction models to the MCMC: a linear Gaussian model and a highly nonlinear bipedal model. The Gaussian model was efficient in terms of computational cost while the bipedal model discriminated people more accurate than the Gaussian model. The Gaussian model can be used to track a number of people, and the bipedal model can be used in situations where more accurate tracking is required.
The tear trough ligament: anatomical basis for the tear trough deformity.

The exact anatomical cause of the tear trough remains undefined. This study was performed to identify the anatomical basis for the tear trough deformity.



Forty-eight cadaveric hemifaces were dissected. With the skin over the midcheek intact, the tear trough area was approached through the preseptal space above and prezygomatic space below. The origins of the palpebral and orbital parts of the orbicularis oculi (which sandwich the ligament) were released meticulously from the maxilla, and the tear trough ligament was isolated intact and in continuity with the orbicularis retaining ligament. The ligaments were submitted for histologic analysis.



A true osteocutaneous ligament called the tear trough ligament was consistently found on the maxilla, between the palpebral and orbital parts of the orbicularis oculi, cephalad and caudal to the ligament, respectively. It commences medially, at the level of the insertion of the medial canthal tendon, just inferior to the anterior lacrimal crest, to approximately the medial-pupil line, where it continues laterally as the bilayered orbicularis retaining ligament. Histologic evaluation confirmed the ligamentous nature of the tear trough ligament, with features identical to those of the zygomatic ligament.



This study clearly demonstrated that the prominence of the tear trough has its anatomical origin in the tear trough ligament. This ligament has not been isolated previously using standard dissection, but using the approach described, the tear trough ligament is clearly seen. The description of this ligament sheds new light on considerations when designing procedures to address the tear trough and the midcheek.