nils-herrmann/clean_scirepeval huggingface dataset:
Recurrent Slice Networks for 3D Segmentation of Point Clouds

Point clouds are an efficient data format for 3D data. However, existing 3D segmentation methods for point clouds either do not model local dependencies [21] or require added computations [14, 23]. This work presents a novel 3D segmentation framework, RSNet1, to efficiently model local structures in point clouds. The key component of the RSNet is a lightweight local dependency module. It is a combination of a novel slice pooling layer, Recurrent Neural Network (RNN) layers, and a slice unpooling layer. The slice pooling layer is designed to project features of unordered points onto an ordered sequence of feature vectors so that traditional end-to-end learning algorithms (RNNs) can be applied. The performance of RSNet is validated by comprehensive experiments on the S3DIS[1], ScanNet[3], and ShapeNet  datasets. In its simplest form, RSNets surpass all previous state-of-the-art methods on these benchmarks. And comparisons against previous state-of-the-art methods  demonstrate the efficiency of RSNets.
Optimal design and electromagnetic analysis of yokeless and segmented armature machine based on finite-element method and genetic algorithm

In view of the complex and special structure of the yokeless and segmented armature machine (YASA), this paper presents optimal design of a 22kW YASA to increase the torque density and reduce the cogging torque. The initial design dimensions are proposed by sizing equation and the 3D finite- element analysis (FEA). Then, the parameters such as the outer diameter, ratio of inner and outer diameter, permanent magnet height, air-gap length are optimized by genetic algorithm (GA). By means of the 3D FEA, the electromagnetic performances of YASA are investigated. Finally, a prototype is manufactured and tested. The results confirm that the design and optimization are reliable.
7 Review of Nanocomposite Thin Films and Coatings Deposited by PVD and CVD Technology

Commonly it is assumed that the nanocrystalline materials are composed of elements like grains, crystallites, layers, e.g., of a size of ca. 100 nm. (more typically less than 50 nm; often less than 10 nm – in the case of superhard nanocomposite, materials for optoelectronic applications, etc.) at least in one direction. The definition give above limits the size of the structure elements, however it has to be seen only as a theoretical value and doesn’t have any physical importance. Thin films and coatings are applied to structural bulk materials in order to improve the desired properties of the surface, such as corrosion resistance, wear resistance, hardness, friction or required colour, e.g., golden, black or a polished brass-like. The research issues concerning the production of coatings are one of the more important directions of surface engineering development, ensuring the obtainment of coatings of high utility properties in the scope of mechanical characteristics and wear resistance. Giving new utility characteristics to commonly known materials is frequently obtained by laying simple monolayer, multilayer or gradient coatings using PVD methods (Dobrzanski et al., 2005; Lukaszkowicz & Dobrzanski, 2008). While selecting the coating material, we encounter a barrier caused by the fact that numerous properties expected from an ideal coating are impossible to be obtained simultaneously. The application of the nanostructure coatings is seen as the solution of this issue. Nanostructure and particularly nanocomposite coatings deposited by physical vapour deposition or chemical vapour deposition, have gained considerable attention due to their unique physical and chemical properties, e.g. extremely high indentation hardness (40-80 GPa) (Veprek et al., 2006, 2000; Zou et al., 2010), corrosion resistance (Audronis et al., 2008; Lukaszkowicz et al., 2010), excellent high temperature oxidization resistance (Vaz et al., 2000; Voevodin & Zabinski, 2005), as well high abrasion and erosion resistance (Cheng et al., 2010; Polychronopoulou et al., 2009; Veprek & Veprek-Heijman, 2008). In the present work, the emphasis is put on current practices and future trends for nanocomposite thin films and coatings deposited by physical vapour deposition (PVD) and chemical vapour deposition (CVD) techniques. This review will not be so exhaustive as to cover all aspects of such coatings, but the main objective is to give a general sense of what has so far been accomplished and where the field is going.
Awake vs. asleep placement of spinal cord stimulators: a cohort analysis of complications associated with placement.

Patients will typically undergo awake surgery for permanent implantation of spinal cord stimulation (SCS) in an attempt to optimize electrode placement using patient feedback about the distribution of stimulation-induced paresthesia. The present study compared efficacy of first-time electrode placement under awake conditions with that of neurophysiologically guided placement under general anesthesia.



A retrospective review was performed of 387 SCS surgeries among 259 patients which included 167 new stimulator implantation to determine whether first time awake surgery for placement of spinal cord stimulators is preferable to non-awake placement.



The incidence of device failure for patients implanted using neurophysiologically guided placement under general anesthesia was one-half that for patients implanted awake (14.94% vs. 29.7%).



Non-awake surgery is associated with fewer failure rates and therefore fewer re-operations, making it a viable alternative. Any benefits of awake implantation should carefully be considered in the future.
Measuring and evaluating the compactness of superpixels

Superpixel segmentation has become a popular preprocessing step in computer vision with a great variety of existing algorithms. Almost all algorithms claim to compute compact superpixels, but no one showed how to measure compactness and no one investigated the implications. In this paper, we propose a novel metric to measure superpixel compactness. With this metric, we show that there is a trade-off between compactness and boundary recall. In addition, we propose an algorithm that allows to precisely control this trade-off and that outperforms the current state-of-the-art. As a demonstration, we show the importance of considering compactness with the help of an example application.
Energy aware communication between smart IoT monitoring devices

One of the most important issue that must be addressed in designing communication protocols for wireless sensor networks (WSN) is how to save sensor node energy while meeting the needs of applications. Recent researches have led to new protocols specifically designed for sensor networks where energy awareness is an essential consideration. Internet of Things (IoT) is an innovative ICT paradigm where a number of intelligent devices connected to Internet are involved in sharing information and making collaborative decision. Integration of sensing and actuation systems, connected to the Internet, means integration of all forms of energy consuming devices such as power outlets, bulbs, air conditioner, etc. Sometimes the system can communicate with the utility supply company and this led to achieve a balance between power generation and energy usage or in general is likely to optimize energy consumption as a whole. In this paper some emerging trends and challenges are identified to enable energy-efficient communications in Internet of Things architectures and between smart devices. The way devices communicate is analyzed in order to reduce energy consumption and prolong system lifetime. Devices equipped with WiFi and RF interfaces are analyzed under different scenarios by setting different communication parameters, such as data size, in order to evaluate the best device configuration and the longest lifetime of devices.
RC 24953 ( W 1003-002 )

Universal background models (UBM) in speaker recognition systems are typically Gaussian mixture models (GMM) traine d from a large amount of data using the maximum likelihood criterion. This paper investigates three alternative crit eria for training the UBM. In the first, we cluster an existing automat ic speech recognition (ASR) acoustic model to generate the UBM . In each of the other two, we use statistics based on the speake r labels of the development data to regularize the maximum lik elihood objective function in training the UBM. We present an iterative algorithm similar to the expectation maximization (EM) algorithm to train the UBM for each of these regularized maximum likelihood criteria. We present several experiments t hat show how combining only two systems outperforms the best published results on the English telephone tasks of the NIST 2008 speaker recognition evaluation.
Morphological and Abstract Case

This article examines the relationship between abstract and morphological case, arguing that morphological case realizes abstract Case features in a postsyntactic morphology, according to the Elsewhere Condition. A class of prima facie ergative-absolutive languages is identified wherein intransitive subjects receive abstract nominative Case and transitive objects receive abstract accusative Case; these are realized through a morphological default, which is often mislabeled as absolutive. Further support comes from split ergativity based on a nominal hierarchy, which is shown to have a morphological source. Proposals that case and agreement are purely morphological phenomena are critiqued.
Detection of Norovirus genogroup I and II by multiplex real-time RT- PCR using a 3'-minor groove binder-DNA probe

Due to an increasing number of norovirus infections in the last years rapid, specific, and sensitive diagnostic tools are needed. Reverse transcriptase-polymerase chain reactions (RT-PCR) have become the methods of choice. To minimize the working time and the risk of carryover contamination during the multi-step procedure of PCR the multiplex real-time RT-PCR for the simultaneous detection of genogroup I (GI) and II (GII) offers advantages for the handling of large amounts of clinical specimens.



We have developed and evaluated a multiplex one-tube RT-PCR using a combination of optimized GI and GII specific primers located in the junction between ORF1 and ORF2 of the norovirus genome. For the detection of GI samples, a 3'-minor groove binder-DNA probe (GI-MGB-probe) were designed and used for the multiplex real-time PCR.



Comparable results to those of our in-house nested PCR and monoplex real-time-PCR were only obtained using the GI specific MGB-probe. The MGB-probe forms extremely stable duplexes with single-stranded DNA targets, which enabled us to design a shorter probe (length 15 nucleotides) hybridizing to a more conserved part of the GI sequences. 97% of 100 previously norovirus positive specimens (tested by nested PCR and/or monoplex real-time PCR) were detected by the multiplex real-time PCR. A broad dynamic range from 2 x 10(1) to 2 x 10(7) genomic equivalents per assay using plasmid DNA standards for GI and GII were obtained and viral loads between 2.5 x 10(2) and 2 x 10(12) copies per ml stool suspension were detected.



The one-tube multiplex RT real-time PCR using a minor groove binder-DNA probe for GI is a fast, specific, sensitive and cost-effective tool for the detection of norovirus infections in both mass outbreaks and sporadic cases and may have also applications in food and environmental testing.
Efficient implementation of adaptive P1-FEM in Matlab

We provide a Matlab package p1afem for an adaptive P1-finite element method (AFEM). This includes functions for the assembly of the data, different error estimators, and an indicator-based adaptive mesh-refining algorithm. Throughout, the focus is on an efficient realization by use of Matlab built-in functions and vectorization. Numerical experiments underline the efficiency of the code which is observed to be of almost linear complexity with respect to the runtime. Although the scope of this paper is on AFEM, the general ideas can be understood as a guideline for writing efficient Matlab code.
Ultrasonic Detection of Middle Ear Effusion

Of the 74 ears tested, 45 (61%) had effusion on direct inspection. The effusion was purulent in 8 ears (18%), serous in 9 ears (20%), and mucoid in 28 ears (62%). Ultrasound identified the presence or absence of effusion in 71 cases (96%) (P=.04). Ultrasound distinguished between serous and mucoid effusion with 100% accuracy (P=.04). The probe did not distinguish between mucoid and purulent effusion.
Efficiency of WhatsApp as a Means of Disseminating Educational Information

This study aims to investigate the level of usage of this social networking application (WhatsApp messenger) and identify the impact of WhatsApp messenger on the quality of education through improving the interaction of instructor-student communication, and student-student communication in which they can create, share and/or exchange information and ideas in an e-learning environment. The researchers conducted this pilot study focusing on exploring the following scopes : The effectiveness of WhatsApp on academic performance among students in UAE, Exploring the common activities that the students undertake when using WhatsApp messenger, The extent to which students use WhatsApp in academic environments, whether this technological platform has affected the social behavior and interactions of students inside the classroom and the overall impact of WhatsApp on educational levels and quality compared to the common educational standards. Applied.data is collected through a questionnaire administered on a random sample of 100 UAE university students. Respondents were students enrolled in the Canadian University and Al Dar University during the academic year 2015-2016 and studying an array of specializations. Results show strong positive indicators that there are distinct differences between the face to face formal teaching method and the e-learning method applied via WhatsApp. Indicators show that the learning environment being influenced by multiple variables, therefore there is a growing need for more innovative teaching methods that make the experience more engaging.
Annona muricata (Annonaceae): A Review of Its Traditional Uses, Isolated Acetogenins and Biological Activities

Annona muricata is a member of the Annonaceae family and is a fruit tree with a long history of traditional use. A. muricata, also known as soursop, graviola and guanabana, is an evergreen plant that is mostly distributed in tropical and subtropical regions of the world. The fruits of A. muricata are extensively used to prepare syrups, candies, beverages, ice creams and shakes. A wide array of ethnomedicinal activities is contributed to different parts of A. muricata, and indigenous communities in Africa and South America extensively use this plant in their folk medicine. Numerous investigations have substantiated these activities, including anticancer, anticonvulsant, anti-arthritic, antiparasitic, antimalarial, hepatoprotective and antidiabetic activities. Phytochemical studies reveal that annonaceous acetogenins are the major constituents of A. muricata. More than 100 annonaceous acetogenins have been isolated from leaves, barks, seeds, roots and fruits of A. muricata. In view of the immense studies on A. muricata, this review strives to unite available information regarding its phytochemistry, traditional uses and biological activities.
Learning from the Web: Extracting General World Knowledge from Noisy Text

The quality and nature of knowledge that can be found by an automated knowledge-extraction system depends on its inputs. For systems that learn by reading text, the Web offers a breadth of topics and currency, but it also presents the problems of dealing with casual, unedited writing, non-textual inputs, and the mingling of languages. The results of extraction using the KNEXT system on two Web corpora – Wikipedia and a collection of weblog entries – indicate that, with automatic filtering of the output, even ungrammatical writing on arbitrary topics can yield an extensive knowledge base, which human judges find to be of good quality, with propositions receiving an average score across both corpora of 2.34 (where the range is 1 to 5 and lower is better) versus 3.00 for unfiltered output from the same sources.
Effect of a hypocaloric diet, increased protein intake and resistance training on lean mass gains and fat mass loss in overweight police officers.

We compare the effects of a moderate hypocaloric, high-protein diet and resistance training, using two different protein supplements, versus hypocaloric diet alone on body compositional changes in overweight police officers. A randomized, prospective 12-week study was performed comparing the changes in body composition produced by three different treatment modalities in three study groups. One group (n = 10) was placed on a nonlipogenic, hypocaloric diet alone (80% of predicted needs). A second group (n = 14) was placed on the hypocaloric diet plus resistance exercise plus a high-protein intake (1.5 g/kg/day) using a casein protein hydrolysate. In the third group (n = 14) treatment was identical to the second, except for the use of a whey protein hydrolysate. We found that weight loss was approximately 2.5 kg in all three groups. Mean percent body fat with diet alone decreased from a baseline of 27 +/- 1.8 to 25 +/- 1.3% at 12 weeks. With diet, exercise and casein the decrease was from 26 +/- 1.7 to 18 +/- 1.1% and with diet, exercise and whey protein the decrease was from 27 +/- 1.6 to 23 +/- 1.3%. The mean fat loss was 2. 5 +/- 0.6, 7.0 +/- 2.1 and 4.2 +/- 0.9 kg in the three groups, respectively. Lean mass gains in the three groups did not change for diet alone, versus gains of 4 +/- 1.4 and 2 +/- 0.7 kg in the casein and whey groups, respectively. Mean increase in strength for chest, shoulder and legs was 59 +/- 9% for casein and 29 +/- 9% for whey, a significant group difference. This significant difference in body composition and strength is likely due to improved nitrogen retention and overall anticatabolic effects caused by the peptide components of the casein hydrolysate.
Defense Against Adversarial Attacks Using High-Level Representation Guided Denoiser

Neural networks are vulnerable to adversarial examples, which poses a threat to their application in security sensitive systems. We propose high-level representation guided denoiser (HGD) as a defense for image classification. Standard denoiser suffers from the error amplification effect, in which small residual adversarial noise is progressively amplified and leads to wrong classifications. HGD overcomes this problem by using a loss function defined as the difference between the target model's outputs activated by the clean image and denoised image. Compared with ensemble adversarial training which is the state-of-the-art defending method on large images, HGD has three advantages. First, with HGD as a defense, the target model is more robust to either white-box or black-box adversarial attacks. Second, HGD can be trained on a small subset of the images and generalizes well to other images and unseen classes. Third, HGD can be transferred to defend models other than the one guiding it. In NIPS competition on defense against adversarial attacks, our HGD solution won the first place and outperformed other models by a large margin.1
Caching Techniques for Streaming Multimedia over the Internet

Existing solutions for streaming multimedia in the Internet do not scale in terms of object size and number of supported streams. Using separate unicast streams, for example, will overload both network and servers. While caching is the standard technique for improving scalability, existing caching schemes do not support streaming media well. In this paper, we propose a complete solution for caching multimedia streams in the Internet by extending existing techniques and proposing new techniques to support streaming media. These include segmentation of streaming objects, dynamic caching, and self-organizing cooperative caching. We consider these techniques in an integrated fashion. We implemented a complete caching architecture called SOCCER using the network simulator ns-2 and evaluate the effectiveness of each proposed technique and compare them to alternative caching solutions. Streaming Media, Caching, Proxy.
The crying baby: what approach?

Cry-fuss problems are among the most common clinical presentations in the first few months of life and are associated with adverse outcomes for some mothers and babies. Cry-fuss behaviour emerges out of a complex interplay of cultural, psychosocial, environmental and biologic factors, with organic disturbance implicated in only 5% of cases. A simplistic approach can have unintended consequences. This article reviews recent evidence in order to update clinical management.



New research is considered in the domains of organic disturbance, feed management, maternal health, sleep management, and sensorimotor integration. This transdisciplinary approach takes into account the variable neurodevelopmental needs of healthy infants, the effects of feeding management on the highly plastic neonatal brain, and the bi-directional brain-gut-enteric microbiota axis. An individually tailored, mother-centred and family-centred approach is recommended.



The family of the crying baby requires early intervention to assess for and manage potentially treatable problems. Cross-disciplinary collaboration is often necessary if outcomes are to be optimized.
Phenotypic and molecular characterisation of the Aarskog–Scott syndrome: a survey of the clinical variability in light of FGD1 mutation analysis in 46 patients

Faciogenital dysplasia or Aarskog–Scott syndrome (AAS) is a genetically heterogeneous developmental disorder. The X-linked form of AAS has been ascribed to mutations in the FGD1 gene. However, although AAS may be considered as a relatively frequent clinical diagnosis, mutations have been established in few patients. Genetic heterogeneity and the clinical overlap with a number of other syndromes might explain this discrepancy. In this study, we have conducted a single-strand conformation polymorphism (SSCP) analysis of the entire coding region of FGD1 in 46 AAS patients and identified eight novel mutations, including one insertion, four deletions and three missense mutations (19.56% detection rate). One mutation (528insC) was found in two independent families. The mutations are scattered all along the coding sequence. Phenotypically, all affected males present with the characteristic AAS phenotype. FGD1 mutations were not associated with severe mental retardation. However, neuropsychiatric disorders, mainly behavioural and learning problems in childhood, were observed in five out of 12 mutated individuals. The current study provides further evidence that mutations of FGD1 may cause AAS and expands the spectrum of disease-causing mutations. The importance of considering the neuropsychological phenotype of AAS patients is discussed.
National Healthcare Safety Network (NHSN) Report, data summary for 2010, device-associated module.

This report is a summary of Device-associated (DA) Module data collected by hospitals participating in the National Healthcare Safety Network (NHSN) for events occurring from January through December 2010 and re­ ported to the Centers for Disease Control and Prevention (CDC) by July 7, 2011. This report updates previously published DA Module data from the NHSN and provides contemporary comparative rates. This report comple­ ments other NHSN reports, including national and state-specific reports of standardized infection ratios for select health care-associated infections (HAIs). The NHSN was established in 2005 to integrate and supersede 3 legacy surveillance systems at the CDC: the National Nosocomial Infections Surveillance system, the Dialysis Surveillance Network, and the National Sur­ veillance System for Healthcare Workers. NHSN data col­ lection, reporting, and analysis are organized into 3 components—Patient Safety, Healthcare Personnel