nils-herrmann/clean_scirepeval huggingface dataset:
A Probabilistic Discriminative Model for Android Malware Detection with Decompiled Source Code

Mobile devices are an important part of our everyday lives, and the Android platform has become a market leader. In recent years a number of approaches for Android malware detection have been proposed, using permissions, source code analysis, or dynamic analysis. In this paper, we propose to use a probabilistic discriminative model based on regularized logistic regression for Android malware detection. Through extensive experimental evaluation, we demonstrate that it can generate probabilistic outputs with highly accurate classification results. In particular, we propose to use Android API calls as features extracted from decompiled source code, and analyze and explore issues in feature granularity, feature representation, feature selection, and regularization. We show that the probabilistic discriminative model also works well with permissions, and substantially outperforms the state-of-the-art methods for Android malware detection with application permissions. Furthermore, the discriminative learning model achieves the best detection results by combining both decompiled source code and application permissions. To the best of our knowledge, this is the first research that proposes probabilistic discriminative model for Android malware detection with a thorough study of desired representation of decompiled source code and is the first research work for Android malware detection task that combines both analysis of decompiled source code and application permissions.
Biopesticides: an ecofriendly approach for pest control.

An ecofriendly alternative to chemical pesticides is biopesticides, which encompasses a broad array of microbial pesticides, biochemicals derived from micro-organisms and other natural sources, and processes involving the genetic incorporation of DNA into agricultural commodities that confer protection against pest damage. Biopesticides fall into three major classes. The potential benefits to agriculture and public health programmes through the use of biopesticides are considerable. The interest in biopesticides is based on the disadvantages associated with chemical pesticides are discussed. The total world production of biopesticides is over 3,000 tons/yr, which is increasing at a rapid rate. India has a vast potential for biopesticides. However, its adoption by farmers in India needs education for maximizing gains. The market share of biopesticides is only 2.5% of the total pesticide market. The stress on organic farming and on residue free commodities would certainly warrant increased adoption of biopesticides by the farmers. Biopesticides being target pest specific are presumed to be relatively safe to non-target organism including humans. However, in India, the registration committee requires the data on chemistry, bioefficacy, toxicity and packaging and labeling, for registration. Pesticide Registration Committee has so far not approved any guidelines for the registration of GM biopesticides. In India, some of the biopesticides like Bt, NPV, neem based pesticides, etc. have already been registered and are being practiced.
Pectoral nerve block (Pecs block) with sedation for breast conserving surgery without general anesthesia

Most regional anesthesia in breast surgeries is performed as postoperative pain management under general anesthesia, and not as the primary anesthesia. Regional anesthesia has very few cardiovascular or pulmonary side-effects, as compared with general anesthesia. Pectoral nerve block is a relatively new technique, with fewer complications than other regional anesthesia. We performed Pecs I and Pec II block simultaneously as primary anesthesia under moderate sedation with dexmedetomidine for breast conserving surgery in a 49-year-old female patient with invasive ductal carcinoma. Block was uneventful and showed no complications. Thus, Pecs block with sedation could be an alternative to general anesthesia for breast surgeries.
Learning to Evaluate Image Captioning

Evaluation metrics for image captioning face two challenges. Firstly, commonly used metrics such as CIDEr, METEOR, ROUGE and BLEU often do not correlate well with human judgments. Secondly, each metric has well known blind spots to pathological caption constructions, and rule-based metrics lack provisions to repair such blind spots once identified. For example, the newly proposed SPICE correlates well with human judgments, but fails to capture the syntactic structure of a sentence. To address these two challenges, we propose a novel learning based discriminative evaluation metric that is directly trained to distinguish between human and machine-generated captions. In addition, we further propose a data augmentation scheme to explicitly incorporate pathological transformations as negative examples during training. The proposed metric is evaluated with three kinds of robustness tests and its correlation with human judgments. Extensive experiments show that the proposed data augmentation scheme not only makes our metric more robust toward several pathological transformations, but also improves its correlation with human judgments. Our metric outperforms other metrics on both caption level human correlation in Flickr 8k and system level human correlation in COCO. The proposed approach could be served as a learning based evaluation metric that is complementary to existing rule-based metrics.
The edentulous ridge expansion technique: a five-year study.

This study presents the clinical results of a surgical technique that expands a narrow ridge when its orofacial width precludes the placement of dental implants. In 170 people, 329 implants were placed in sites needing ridge enlargement using the endentulous ridge expansion procedure. This technique involves a partial-thickness flap, crestal and vertical intraosseous incisions into the ridge, and buccal displacement of the buccal cortical plate, including a portion of the underiying spongiosa. Implants were placed in the expanded ridge and allowed to heal for 4 to 5 months. When indicated, the implants were exposed during a second-stage surgery to allow visualization of the implant site. Occlusal loading was applied during the following 3 to 5 months by provisional prostheses. The final phase was the placement of the permanent prostheses. The results yielded a success rate of 98.8%.
DB&A: An Open Source Web Service for Meter Data Management

With the increasing number of initiatives dealing with storing meter data, systems that perform Meter Data Management (MDM) constitute a critical component for realising the potential benefits of the smart grid. However, most of the MDM systems designed today are generalised to such an extent that they do not consider the relational structure of electrical system. Furthermore, these systems do often not restrict themselves to specific data latency requirements. To address this issue, this paper presents the Database & Analytics (DB&A), an open reference implementation for a MDM system that is instantiated as a web service. Its design is based on a set of design goals, an explicitly addressed data latency scope and five real-world scenarios. We present an abstract model of the metering hierarchy that allows MDM systems to be used as compositional services, forming a service tree. Moreover, we provide implementation details about analytic functions to support the service tree. The DB&A is evaluated on a cloud and embedded platform using a subset of data constructed from a case study that includes 8 months of real data. The results show that the DB&A complies with the boundaries of the defined data latency scope for the cloud and embedded platform.
Model Guided Deep Learning Approach Towards Prediction of Physical System Behavior

Cyber-physical control systems involve a discrete computational algorithm to control continuous physical systems. Often the control algorithm uses predictive models of the physical system in its decision making process. However, physical system models suffer from several inaccuracies when employed in practice. Mitigating such inaccuracies is often difficult and have to be repeated for different instances of the physical system. In this paper, we propose a model guided deep learning method for extraction of accurate prediction models of physical systems, in presence of artifacts observed in real life deployments. Given an initial potentially suboptimal mathematical prediction model, our model guided deep learning method iteratively improves the model through a data driven training approach. We apply the proposed approach on the closed loop blood glucose control system. Using this proposed approach, we achieve an improvement over predictive Bergman Minimal Model by a factor of around 100.
Cell segmentation in 3D confocal images using supervoxel merge-forests with CNN-based hypothesis selection

Automated segmentation approaches are crucial to quantitatively analyze large-scale 3D microscopy images. Particularly in deep tissue regions, automatic methods still fail to provide error-free segmentations. To improve the segmentation quality throughout imaged samples, we present a new supervoxel-based 3D segmentation approach that outperforms current methods and reduces the manual correction effort. The algorithm consists of gentle preprocessing and a conservative super-voxel generation method followed by supervoxel agglomeration based on local signal properties and a postprocessing step to fix under-segmentation errors using a Convolutional Neural Network. We validate the functionality of the algorithm on manually labeled 3D confocal images of the plant Arabidopsis thaliana and compare the results to a state-of-the-art meristem segmentation algorithm.
DNA methylation and cancer.

DNA methylation is one of the most intensely studied epigenetic modifications in mammals. In normal cells, it assures the proper regulation of gene expression and stable gene silencing. DNA methylation is associated with histone modifications and the interplay of these epigenetic modifications is crucial to regulate the functioning of the genome by changing chromatin architecture. The covalent addition of a methyl group occurs generally in cytosine within CpG dinucleotides which are concentrated in large clusters called CpG islands. DNA methyltransferases are responsible for establishing and maintenance of methylation pattern. It is commonly known that inactivation of certain tumor-suppressor genes occurs as a consequence of hypermethylation within the promoter regions and a numerous studies have demonstrated a broad range of genes silenced by DNA methylation in different cancer types. On the other hand, global hypomethylation, inducing genomic instability, also contributes to cell transformation. Apart from DNA methylation alterations in promoter regions and repetitive DNA sequences, this phenomenon is associated also with regulation of expression of noncoding RNAs such as microRNAs that may play role in tumor suppression. DNA methylation seems to be promising in putative translational use in patients and hypermethylated promoters may serve as biomarkers. Moreover, unlike genetic alterations, DNA methylation is reversible what makes it extremely interesting for therapy approaches. The importance of DNA methylation alterations in tumorigenesis encourages us to decode the human epigenome. Different DNA methylome mapping techniques are indispensable to realize this project in the future.
Scale invariance and noise in natural images

Natural images are known to have scale invariant statistics. While some eariler studies have reported the kurtosis of marginal bandpass filter response distributions to be constant throughout scales, other studies have reported that the kurtosis values are lower for high frequency filters than for lower frequency ones. In this work we propose a resolution for this discrepancy and suggest that this change in kurtosis values is due to noise present in the image. We suggest that this effect is consistent with a clean, natural image corrupted by white noise. We propose a model for this effect, and use it to estimate noise standard deviation in corrupted natural images. In particular, our results suggest that classical benchmark images used in low-level vision are actually noisy and can be cleaned up. Our results on noise estimation on two sets of 50 and a 100 natural images are significantly better than the state-of-the-art.
Use of CT scans in selection of patients for pectus excavatum surgery: a preliminary report.

A pectus index can be derived from dividing the transverse diameter of the chest by the anterior-posterior diameter on a simple CT scan. In a preliminary report, all patients who required operative correction for pectus excavatum had a pectus index greater than 3.25 while matched normal controls were all less than 3.25. A simple CT scan may be a useful adjunct in objective evaluation of children and teenagers for surgery of pectus excavatum.
Design of Wideband Circularly Polarized Antenna Using Coupled Rotated Vertical Metallic Plates

A simple structure composed of four rotated metallic plates is proposed to enhance the bandwidth of circularly polarized (CP) crossed-dipole antenna. The metallic plates are vertically added on the ground plane in a sequential rotation way, surrounding the primary radiator of the crossed-dipole antenna. Owing to the coupling with the radiator, orthogonal currents can be induced on the metallic plates. Additional impedance and axial ratio passbands can, therefore, be generated beside the original operating band, enhancing its bandwidth substantially. As the metallic plates are mounted on the ground plane, no extra footprint is needed, making the area of the wideband antenna very compact. Simulation and measured results show that by using this simple structure, the operating bandwidth of CP crossed-dipole antenna can be enhanced significantly from ~30% to 106.1%. The structure is also applicable to the intrinsically narrowband patch antennas.
The Errors of Erik Erikson a Critique of Young Man Luther "youth: Fidelity and Diversity," in the Challenge of Youth Childhood and Society Identity and the Life Cycle the Life Cycle Completed Erikson's Doctrine of Man

Building on the fraudulent foundation established by atheist Sigmund Freud, psychoanalyst Erik Erikson has proposed a series of eight "life cycles," each with an accompanying "life crisis," to explain both human behavior and man's religious tendencies. Erikson's extensive application of his theories to the life of Martin Luther reveals his contempt for the living God who has revealed Himself in Scripture. This paper will consider Erikson's view of man, sin, redemption, and religion, along with an analysis of his eight "life cycles." Finally, we will critique his attempted psychoanalysis of Martin Luther.
Differential diagnosis of pearly penile papules and penile condyloma acuminatum by dermoscopy.

abnormality. Asymmetrical limb defects are characteristic and affect about 84% of patients. Hypoplastic or absent distal phalanges have been the most commonly reported limb anomalies, but some patients lack hands or lower legs [6]. At the other end of the spectrum, there may be hypoplastic nails. The lower limbs are generally more severely affected than the upper limbs. Congenital heart disease is another characteristic component of this syndrome, affecting about 8% of cases. Other clinical features seen in Adams Oliver syndrome include short stature, kidney (renal) malformations, cleft palate, small eyes (micropthalmia), spinal bifida occulta, accessory nipples, undescended testis, skin lesions and neurological abnormalities. Mental retardation is present in a few cases [7]. Though Adams Oliver syndrome does not usually alter the life span, various neurological complications can develop. To date our patient has manifested clinically with delayed milestones and epileptic fits. This patient requires a long term follow up for neurological manifestations like neuroectodermal tumours, hydrocephalus and various congenital anomalies which are likely to manifest at a later stage in life. ■ Acknowledgements. Conflict of interest: none. Financial support: none.
A review of communication-oriented optical wireless systems

This article presents an overview of optical wireless (OW) communication systems that operate both in the short(personal and indoor systems) and the long-range (outdoor and hybrid) regimes. Each of these areas is discussed in terms of (a) key requirements, (b) their application framework, (c) major impairments and applicable mitigation techniques, and (d) current and/or future trends. Personal communication systems are discussed within the context of point-to-point ultra-high speed data transfer. The most relevant application framework and related standards are presented, including the next generation Giga-IR standard that extends personal communication speeds to over 1 Gb/s. As far as indoor systems are concerned, emphasis is given on modeling the dispersive nature of indoor OW channels, on the limitations that dispersion imposes on user mobility and dispersion mitigation techniques. Visible light communication systems, which provide both illumination and communication over visible or hybrid visible/ infrared LEDs, are presented as the most important representative of future indoor OW systems. The discussion on outdoor systems focuses on the impact of atmospheric effects on the optical channel and associated mitigation techniques that extend the realizable link lengths and transfer rates. Currently, outdoor OW is commercially available at 10 Gb/s Ethernet speeds for Metro networks and Local-Area-Network interconnections and speeds are expected to increase as faster and more reliable optical components become available. This article concludes with hybrid optical wireless/radio-frequency (OW/RF) systems that employ an additional RF link to improve the overall system reliability. Emphasis is given on cooperation techniques between the reliable RF subsystem and the broadband OW system.
DNA damage, aging, and cancer.

2009;361:1475-85.  DNA damage has emerged as a major culprit in cancer and many diseases related to aging. The stability of the genome is supported by an intricate machinery of repair, damage tolerance, and checkpoint pathways that counteracts DNA damage. In addition, DNA damage and other stresses can trigger a highly conserved, anticancer, antiaging survival response that suppresses metabolism and growth and boosts defenses that maintain the integrity of the cell. Induction of the survival response may allow interventions that improve health and extend the life span. Recently, the first candidate for such interventions, rapamycin (also known as sirolimus), has been identified.1 Compromised repair systems in tumors also offer opportunities for intervention, making it possible to attack malignant cells in which maintenance of the genome has been weakened. Time-dependent accumulation of damage in cells and organs is associated with gradual functional decline and aging.2 The molecular basis of this phenomenon is unclear,3-5 whereas in cancer, DNA alterations are the major culprit. In this review, I present evidence that cancer and diseases of aging are two sides of the DNAdamage problem. An examination of the importance of DNA damage and the systems of genome maintenance in relation to aging is followed by an account of the derailment of genome guardian mechanisms in cancer and of how this cancerspecific phenomenon can be exploited for treatment.
Facial arterial depth and relationship with the facial musculature layer.

Previous studies have revealed a variation in the origin and distribution patterns of the facial artery. However, the relationship between the facial artery and the facial muscles has not been well described. The purpose of this study was to determine the facial artery depth and relationship with the facial musculature layer, which represents critical information for dermal filler injection and oral and maxillofacial surgery.



Fifty-four embalmed adult faces from Korean cadavers (36 male and 18 female cadavers; mean age, 73.3 years) were used in this study. A detailed dissection was performed, with great care being taken to avoid damaging the facial artery underlying the facial skin and muscle.



The facial artery was first categorized according to the patterns of its final arterial branches. The branching pattern was classified simply into three types: type I, nasolabial pattern (51.8 percent); type II, nasolabial pattern with an infraorbital trunk (29.6 percent); and type III, forehead pattern (18.6 percent). Each type was further subdivided according to the facial artery depth and relationship with the facial musculature layer as types Ia (37.0 percent), Ib (14.8 percent), IIa (16.7 percent), IIb (12.9 percent), IIIa (16.7 percent), and IIIb (1.9 percent).



This study provides new anatomical insight into the relationships between the facial artery branches and the facial muscles, including providing useful information for clinical applications in the fields of oral and maxillofacial surgery.
Protecting Location Privacy in Spatial Crowdsourcing using Encrypted Data

In spatial crowdsourcing, spatial tasks are outsourced to a set of workers in proximity of the task locations for efficient assignment. It usually requires workers to disclose their locations, which inevitably raises security concerns about the privacy of the workers’ locations. In this paper, we propose a secure SC framework based on encryption, which ensures that workers’ location information is never released to any party, yet the system can still assign tasks to workers situated in proximity of each task’s location. We solve the challenge of assigning tasks based on encrypted data using homomorphic encryption. Moreover, to overcome the efficiency issue, we propose a novel secure indexing technique with a newly devised SKD-tree to index encrypted worker locations. Experiments on real-world data evaluate various aspects of the performance of the proposed SC platform.
Engineering Deep Representations for Modeling Aesthetic Perception

Many aesthetic models in multimedia and computer vision suffer from two shortcomings: 1) the low descriptiveness and interpretability<xref rid="fn1" ref-type="fn"><sup>1</sup></xref> of the hand-crafted aesthetic criteria (i.e., fail to indicate region-level aesthetics) and 2) the difficulty of engineering aesthetic features adaptively and automatically toward different image sets. To remedy these problems, we develop a deep architecture to learn aesthetically relevant visual attributes from Flickr,<xref rid="fn2" ref-type="fn"><sup>2</sup></xref> which are localized by multiple textual attributes in a weakly supervised setting. More specifically, using a bag-of-words representation of the frequent Flickr image tags, a sparsity-constrained subspace algorithm discovers a compact set of textual attributes (i.e., each textual attribute is a sparse and linear representation of those frequent image tags) for each Flickr image. Then, a weakly supervised learning algorithm projects the textual attributes at image-level to the highly-responsive image patches. These patches indicate where humans look at appealing regions with respect to each textual attribute, which are employed to learn the visual attributes. Psychological and anatomical studies have demonstrated that humans perceive visual concepts in a hierarchical way. Therefore, we normalize these patches and further feed them into a five-layer convolutional neural network to mimic the hierarchy of human perceiving the visual attributes. We apply the learned deep features onto applications like image retargeting, aesthetics ranking, and retrieval. Both subjective and objective experimental results thoroughly demonstrate the superiority of our approach.<fn id="fn1"><label><sup>1</sup></label><p>In this paper, “describing” and “interpretability” means the ability of seeking region-level representation of each mined textual attribute, i.e., a sparse and linear representation of those frequent image tags.</p></fn><fn id="fn2"><label><sup>2</sup></label><p><uri>https://www.flickr.com/</uri></p></fn>