nils-herrmann/clean_scirepeval huggingface dataset:
Mitochondrial DNA deletions are abundant and cause functional impairment in aged human substantia nigra neurons

Using a novel single-molecule PCR approach to quantify the total burden of mitochondrial DNA (mtDNA) molecules with deletions, we show that a high proportion of individual pigmented neurons in the aged human substantia nigra contain very high levels of mtDNA deletions. Molecules with deletions are largely clonal within each neuron; that is, they originate from a single deleted mtDNA molecule that has expanded clonally. The fraction of mtDNA deletions is significantly higher in cytochrome c oxidase (COX)-deficient neurons than in COX-positive neurons, suggesting that mtDNA deletions may be directly responsible for impaired cellular respiration.
Outlier Detection in Test and Questionnaire Data

Classical methods for detecting outliers deal with continuous variables. These methods are not readily applicable to categorical data, such as incorrect/correct scores (0/1) and ordered rating scale scores (e.g., 0, . . . , 4) typical of multi-item tests and questionnaires. This study proposes two definitions of outlier scores suited for categorical data. One definition combines information on outliers from scores on all the items in the test, and the other definition combines information from all pairs of item scores. For a particular item-score vector, an outlier score expresses the degree in which the item-score vector is unusual. For ten real-data sets, the distribution of each of the two outlier scores is inspected by means of Tukey’s fences and the extreme studentized deviate procedure. It is investigated whether the outliers that are identified are influential with respect to the statistical analysis performed on these data. Recommendations are given for outlier identification and accommodation in test and questionnaire data.
Smith-Lemli-Opitz Syndrome and the DHCR 7 Gene

Smith-Lemli-Opitz syndrome, a severe developmental disorder associated with multiple congenital anomalies, is caused by a defect of cholesterol biosynthesis. Low cholesterol and high concentrations of its direct precursor, 7-dehydrocholesterol, in plasma and tissues are the diagnostic biochemical hallmarks of the syndrome. The plasma sterol concentrations correlate with severity and disease outcome. Mutations in the DHCR7 gene lead to deficient activity of 7-dehydrocholesterol reductase (DHCR7), the final enzyme of the cholesterol biosynthetic pathway. The human DHCR7 gene is localised on chromosome 11q13 and its structure has been characterized. Ninetyone different mutations in the DHCR7 gene have been published to date. This paper is a review of the clinical, biochemical and molecular genetic aspects.
Yolk sac nutrient composition and fat uptake in late-term embryos in eggs from young and old broiler breeder hens.

In the present study, we examined the composition, amount, and uptake of yolk nutrients [fat, protein, water, and carbohydrates (COH)] during incubation of eggs from 30- and 50-wk-old broiler breeder hens. Eggs were sampled at embryonic d 0 (fresh eggs), 13, 15, 17, 19, and 21 (hatch). Egg, embryo, yolk content, and yolk sac membrane were weighed, and the yolk sac (YS; i.e., yolk content + yolk sac membrane) composition was analyzed. From 30 to 50 wk of age, the albumen weight increased by 13.3%, whereas the yolk increased by more than 40%. The proportion of fat in the fresh yolk of the 30-wk-old group was 23.8% compared with 27.4% in the 50-wk-old group, whereas the proportion of protein was 17.9% compared with 15.6%, respectively. During incubation, results indicated that water and protein infiltrated from other egg compartments to the YS. Accordingly, the calculated change in the content of water and protein between fresh yolk and sampled YS does not represent the true uptake of these components from the YS to the embryo, and only fat uptake from the YS can be accurately estimated. By embryonic d 15, fat uptake relative to embryo weight was lower in the 30-wk-old group than in the 50-wk-old group. However, by embryonic d 21, embryos of both groups reached similar relative fat uptake, suggesting that to hatch, embryos must attain a certain amount of fat as a source of energy for the hatching process. The amount of COH in the YS increased similarly during incubation in eggs from hens of both ages, reaching a peak at embryonic d 19, suggesting COH synthesis in the YS. At hatch, the amount of protein, water, and COH in the residual YS, relative to the weight of the yolk-free chick, was similar in eggs from young and old hens. However, chicks from the younger hens had less fat in the YS for their immediate posthatch nutrition compared with those from the older hens.
On the Design of Provably Secure Lightweight Remote User Authentication Scheme for Mobile Cloud Computing Services

Secure and efficient lightweight user authentication protocol for mobile cloud computing becomes a paramount concern due to the data sharing using Internet among the end users and mobile devices. Mutual authentication of a mobile user and cloud service provider is necessary for accessing of any cloud services. However, resource constraint nature of mobile devices makes this task more challenging. In this paper, we propose a new secure and lightweight mobile user authentication scheme for mobile cloud computing, based on cryptographic hash, bitwise XOR, and fuzzy extractor functions. Through informal security analysis and rigorous formal security analysis using random oracle model, it has been demonstrated that the proposed scheme is secure against possible well-known passive and active attacks and also provides user anonymity. Moreover, we provide formal security verification through ProVerif 1.93 simulation for the proposed scheme. Also, we have done authentication proof of our proposed scheme using the Burrows-Abadi-Needham logic. Since the proposed scheme does not exploit any resource constrained cryptosystem, it has the lowest computation cost in compare to existing related schemes. Furthermore, the proposed scheme does not involve registration center in the authentication process, for which it is having lowest communication cost compared with existing related schemes.
Sampling and Recovery of Pulse Streams

Compressive sensing (CS) is a new technique for the efficient acquisition of signals, images and other data that have a sparse representation in some basis, frame, or dictionary. By sparse we mean that the N-dimensional basis representation has just K <;<; N significant coefficients; in this case, the CS theory maintains that just M = O( K log N) random linear signal measurements will both preserve all of the signal information and enable robust signal reconstruction in polynomial time. In this paper, we extend the CS theory to pulse stream data, which correspond to S -sparse signals/images that are convolved with an unknown F-sparse pulse shape. Ignoring their convolutional structure, a pulse stream signal is K = SF sparse. Such signals figure prominently in a number of applications, from neuroscience to astronomy. Our specific contributions are threefold. First, we propose a pulse stream signal model and show that it is equivalent to an infinite union of subspaces. Second, we derive a lower bound on the number of measurements M required to preserve the essential information present in pulse streams. The bound is linear in the total number of degrees of freedom S + F, which is significantly smaller than the naïve bound based on the total signal sparsity K = SF. Third, we develop an efficient signal recovery algorithm that infers both the shape of the impulse response as well as the locations and amplitudes of the pulses. The algorithm alternatively estimates the pulse locations and the pulse shape in a manner reminiscent of classical deconvolution algorithms. Numerical experiments on synthetic and real data demonstrate the advantages of our approach over standard CS.
A STUDY OF CONTINUOUS BLOOD GLUCOSE MONITORING USING NON INVASIVE TECHNIQUE

The advent of a pain free non-invasive technology would improve the patient’s compliance for regular blood glucose monitoring. Subsequently the diabetic patient’s life will improve considerably. Glucose monitoring is an integral part of diabetes management, and the maintenance of physiological blood glucose concentration is the only way for a diabetic to avoid life-threatening diabetic complications. Many reviews have already been published on this topic, but the great amount of information available and the fast development of technologies require a continuous update in the research status. This manuscript aims to review the various NGM techniques and devices.  Blood Glucose Monitoring; Diabetes Management; Non – Invasive Technique ______________________________________________________________________________________________________________
Static Free Space Detection with Laser Scanner using Occupancy Grid Maps

Drivable free space information is vital for autonomous vehicles that have to plan evasive maneu vers in realtime. In this paper, we present a new efficient met hod for environmental free space detection with laser scann er based on 2D occupancy grid maps (OGM) to be used for Advance d Driving Assistance Systems (ADAS) and Collision Avo idance Systems (CAS). Firstly, we introduce an enhanced in verse sensor model tailored for high-resolution laser scanners f or building OGM. It compensates the unreflected beams and deals with the ray casting to grid cells accuracy and computationa l effort problems. Secondly, we introduce the ‘vehicle on a circle for grid maps’ map alignment algorithm that allows building more accurate local maps by avoiding the computationally expensive inaccurate operations of image sub-pixel shifting a nd rotation. The resulted grid map is more convenient for ADAS f eatures than existing methods, as it allows using less memo ry sizes, and hence, results into a better real-time performance. Thirdly, we present an algorithm to detect what we call the ‘in-sight edges’. These edges guarantee modeling the free space area with a single polygon of a fixed number of vertices regardless th e driving situation and map complexity. The results from real world experiments show the effectiveness of our approach.  Occupancy Grid Map; Static Free Space Detection; Advanced Driving Assistance Systems; las er canner; autonomous driving
An Overview of Biomolecular Event Extraction from Scientific Documents

This paper presents a review of state-of-the-art approaches to automatic extraction of biomolecular events from scientific texts. Events involving biomolecules such as genes, transcription factors, or enzymes, for example, have a central role in biological processes and functions and provide valuable information for describing physiological and pathogenesis mechanisms. Event extraction from biomedical literature has a broad range of applications, including support for information retrieval, knowledge summarization, and information extraction and discovery. However, automatic event extraction is a challenging task due to the ambiguity and diversity of natural language and higher-level linguistic phenomena, such as speculations and negations, which occur in biological texts and can lead to misunderstanding or incorrect interpretation. Many strategies have been proposed in the last decade, originating from different research areas such as natural language processing, machine learning, and statistics. This review summarizes the most representative approaches in biomolecular event extraction and presents an analysis of the current state of the art and of commonly used methods, features, and tools. Finally, current research trends and future perspectives are also discussed.
The gut microbiota of larvae of Rhynchophorus ferrugineus Oliver (Coleoptera: Curculionidae)

The red palm weevil (RPW) Rhynchophorus ferrugineus Olivier (Coleoptera: Curculionidae) is one of the major pests of palms. The larvae bore into the palm trunk and feed on the palm tender tissues and sap, leading the host tree to death. The gut microbiota of insects plays a remarkable role in the host life and understanding the relationship dynamics between insects and their microbiota may improve the biological control of insect pests. The purpose of this study was to analyse the diversity of the gut microbiota of field-caught RPW larvae sampled in Sicily (Italy). The 16S rRNA gene-based Temporal Thermal Gradient Gel Electrophoresis (TTGE) of the gut microbiota of RPW field-trapped larvae revealed low bacterial diversity and stability of the community over seasons and among pools of larvae from different host trees. Pyrosequencing of the 16S rRNA gene V3 region confirmed low complexity and assigned 98% of the 75,564 reads to only three phyla: Proteobacteria (64.7%) Bacteroidetes (23.6%) and Firmicutes (9.6%) and three main families [Enterobacteriaceae (61.5%), Porphyromonadaceae (22.1%) and Streptococcaceae (8.9%)]. More than half of the reads could be classified at the genus level and eight bacterial genera were detected in the larval RPW gut at an abundance ≥1%: Dysgonomonas (21.8%), Lactococcus (8.9%), Salmonella (6.8%), Enterobacter (3.8%), Budvicia (2.8%), Entomoplasma (1.4%), Bacteroides (1.3%) and Comamonas (1%). High abundance of Enterobacteriaceae was also detected by culturing under aerobic conditions. Unexpectedly, acetic acid bacteria (AAB), that are known to establish symbiotic associations with insects relying on sugar-based diets, were not detected. The RPW gut microbiota is composed mainly of facultative and obligate anaerobic bacteria with a fermentative metabolism. These bacteria are supposedly responsible for palm tissue fermentation in the tunnels where RPW larvae thrive and might have a key role in the insect nutrition, and other functions that need to be investigated.
The design and implementation of AspectC++

Aspect-Oriented Programming (AOP) is a programming paradigm that supports the modular implementation of crosscutting concerns. Thereby, AOP improves the maintainability, reusability, and configurability of software in general. Although already popular in the Java domain, AOP is still not commonly used in conjunction with C/C++. For a broad adoption of AOP by the software industry, it is crucial to provide solid language and tool support. However, research and tool development for C++ is known to be an extremely hard and tedious task, as the language is overwhelmed with interacting features and hard to analyze. Getting AOP into the C++ domain is not just technical challenge. It is also the question of integrating AOP concepts with the philosophy of the C++ language, which is very different from Java. This paper describes the design and development of the AspectC++ language and weaver, which brings fully-fledged AOP support into the C++ domain.
External beam radiotherapy ± chemotherapy in the treatment of anal canal cancer: a single-institute long-term experience on 100 patients.

One-hundred patients treated with curative radiotherapy (RT) ± chemotherapy (CT) for an anal canal carcinoma (T1-4N0-3M0) were retrospectively analyzed. Five- and 10-year local control (LC) rates were 73% and 67%, respectively. Acute and late G3-G4 toxicity rates were 32% and 12%, respectively. Two patients underwent a colostomy for a G4 anal toxicity. This study confirms the outcomes of RT ± CT in the treatment of anal canal cancer. Concomitant CT and LC statistically influenced Overall Survival and Colostomy-Free Survival. CT also statistically reduced the risk of nodal relapse. High rates of acute skin toxicity impose tailored volumes and techniques of irradiation.
High-Efficiency ClassE Power Amplifier for Wireless Power Transfer System

This paper presents a single-ended Class-E power amplifier for wireless power transfer systems. The power amplifier is designed with a low-cost power MOSFET and high-Q inductor. It adopts a second harmonic filter in the output matching network. The proposed Class-E power amplifier has low second harmonic level by the second harmonic filter. Also, we designed an input driver with a single supply voltage for driving the Class-E power amplifier. The implemented Class-E power amplifier delivers an output power of 40.8 dBm and a high-efficiency of 90.3% for the 6.78 MHz input signal. Index Terms — Class-E power amplifier, High efficiency amplifier, wireless power transfer, harmonic filter
Impact of therapeutic strategies on the prognosis of candidemia in the ICU.

To determine the epidemiology of Candida bloodstream infections, variables influencing mortality, and antifungal resistance rates in ICUs in Spain.



Prospective, observational, multicenter population-based study.



Medical and surgical ICUs in 29 hospitals distributed throughout five metropolitan areas of Spain.



Adult patients (≥ 18 yr) with an episode of Candida bloodstream infection during admission to any surveillance area ICU from May 2010 to April 2011.



Candida isolates were sent to a reference laboratory for species identification by DNA sequencing and susceptibility testing using the methods and breakpoint criteria promulgated by the European Committee on Antimicrobial Susceptibility Testing. Prognostic factors associated with early (0-7 d) and late (8-30 d) mortality were analyzed using logistic regression modeling.



We detected 773 cases of candidemia, 752 of which were included in the overall cohort. Among these, 168 (22.3%) occurred in adult ICU patients. The rank order of Candida isolates was as follows: Candida albicans (52%), Candida parapsilosis (23.7%), Candida glabrata (12.7%), Candida tropicalis (5.8%), Candida krusei (4%), and others (1.8%). Overall susceptibility to fluconazole was 79.2%. Cumulative mortality at 7 and 30 days after the first episode of candidemia was 16.5% and 47%, respectively. Multivariate analysis showed that early appropriate antifungal treatment and catheter removal (odds ratio, 0.27; 95% CI, 0.08-0.91), Acute Physiology and Chronic Health Evaluation II score (odds ratio, 1.11; 95% CI, 1.04-1.19), and abdominal source (odds ratio, 8.15; 95% CI, 1.75-37.93) were independently associated with early mortality. Determinants of late mortality were age (odds ratio, 1.04; 95% CI, 1.01-1.07), intubation (odds ratio, 7.24; 95% CI, 2.24-23.40), renal replacement therapy (odds ratio, 6.12; 95% CI, 2.24-16.73), and primary source (odds ratio, 2.51; 95% CI, 1.06-5.95).



Candidemia in ICU patients is caused by non-albicans species in 48% of cases, C. parapsilosis being the most common among these. Overall mortality remains high and mainly related with host factors. Prompt adequate antifungal treatment and catheter removal could be critical to decrease early mortality.
Advanced imaging of the scapholunate ligamentous complex

The scapholunate joint is one of the most involved in wrist injuries. Its stability depends on primary and secondary stabilisers forming together the scapholunate complex. This ligamentous complex is often evaluated by wrist arthroscopy. To avoid surgery as diagnostic procedure, optimization of MR imaging parameters as use of three-dimensional (3D) sequences with very thin slices and high spatial resolution, is needed to detect lesions of the intrinsic and extrinsic ligaments of the scapholunate complex. The paper reviews the literature on imaging of radial-sided carpal ligaments with advanced computed tomographic arthrography (CTA) and magnetic resonance arthrography (MRA) to evaluate the scapholunate complex. Anatomy and pathology of the ligamentous complex are described and illustrated with CTA, MRA and corresponding arthroscopy. Sprains, mid-substance tears, avulsions and fibrous infiltrations of carpal ligaments could be identified on CTA and MRA images using 3D fat-saturated PD and 3D DESS (dual echo with steady-state precession) sequences with 0.5-mm-thick slices. Imaging signs of scapholunate complex pathology include: discontinuity, nonvisualization, changes in signal intensity, contrast extravasation (MRA), contour irregularity and waviness and periligamentous infiltration by edema, granulation tissue or fibrosis. Based on this preliminary experience, we believe that 3 T MRA using 3D sequences with 0.5-mm-thick slices and multiplanar reconstructions is capable to evaluate the scapholunate complex and could help to reduce the number of diagnostic arthroscopies.
FirmUp: Precise Static Detection of Common Vulnerabilities in Firmware

We present a static, precise, and scalable technique for finding CVEs (Common Vulnerabilities and Exposures) in stripped firmware images. Our technique is able to efficiently find vulnerabilities in real-world firmware with high accuracy. Given a vulnerable procedure in an executable binary and a firmware image containing multiple stripped binaries, our goal is to detect possible occurrences of the vulnerable procedure in the firmware image. Due to the variety of architectures and unique tool chains used by vendors, as well as the highly customized nature of firmware, identifying procedures in stripped firmware is extremely challenging. Vulnerability detection requires not only pairwise similarity between procedures but also information about the relationships between procedures in the surrounding executable. This observation serves as the foundation for a novel technique that establishes a partial correspondence between procedures in the two binaries. We implemented our technique in a tool called FirmUp and performed an extensive evaluation over 40 million procedures, over 4 different prevalent architectures, crawled from public vendor firmware images. We discovered 373 vulnerabilities affecting publicly available firmware, 147 of them in the latest available firmware version for the device. A thorough comparison of FirmUp to previous methods shows that it accurately and effectively finds vulnerabilities in firmware, while outperforming the detection rate of the state of the art by 45% on average.
Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification

Recently, substantial research effort has focused on how to apply CNNs or RNNs to better capture temporal patterns in videos, so as to improve the accuracy of video classification. In this paper, however, we show that temporal information, especially longer-term patterns, may not be necessary to achieve competitive results on common trimmed video classification datasets. We investigate the potential of a purely attention based local feature integration. Accounting for the characteristics of such features in video classification, we propose a local feature integration framework based on attention clusters, and introduce a shifting operation to capture more diverse signals. We carefully analyze and compare the effect of different attention mechanisms, cluster sizes, and the use of the shifting operation, and also investigate the combination of attention clusters for multimodal integration. We demonstrate the effectiveness of our framework on three real-world video classification datasets. Our model achieves competitive results across all of these. In particular, on the large-scale Kinetics dataset, our framework obtains an excellent single model accuracy of 79.4% in terms of the top-1 and 94.0% in terms of the top-5 accuracy on the validation set.