nils-herrmann/clean_scirepeval huggingface dataset:
Absolute phase recovery in structured light illumination systems: Sinusoidal vs. intensity discrete patterns

Structured light illumination is a well established technology for noncontact 3D surface measurements. A common challenge in those systems is to obtain the absolute surface information using few measurement frames. This work discusses techniques based on the projection of multiple sinusoidal fringe patterns with different fringe period, as well as the projection of intensity discrete Gray Code and grey level coded patterns. The use of sinusoidal multi frequency techniques has been since years an on going area of research, where various algorithms have been developed based on beats, look up tables, or number theoretical approaches. This work shows that a related technique, the so called algebraic reconstruction technique that is borrowed from the area of multi wavelength interferometry can be used for this purpose. This approach provides a robust analytical solution to the phase unwrapping problem. However, this work argues that despite these advances, the acquisition of additional phase maps obtained with different fringe periods requires too many measurement frames, and hence is inefficient. Motivated by that, this work proposes a new grey level coding scheme that uses only few measurement frames, overcomes typical defocus errors, and has an error detecting feature. The latter feature makes the need of separate error detecting algorithms obsolete. This so called closed loop space filling curve can be implemented with an arbitrary number of N grey levels enabling to code up to 2N code words. The performance of this so called closed loop space filling curve is demonstrated using experimental data.
Prognostic and predictive biomarkers in metastatic colorectal cancer anti EGFR therapy.
Venue: World journal of gastroenterology

To reviewing genetic and epigenetic make up of metastatic colorectal cancers (mCRCs) addicted to epidermal growth factor receptor (EGFR) signalling.  The present study summarizes the potential value of prognostic and predictive biomarkers in selecting mCRC patients treated with anti EGFR therapy. A meta analysis was performed using a systematic search of PubMed, Medline and Web of Science to identify eligible papers until March 21(st) 2016 using these following terms: 'colorectal cancer' "predictive biomarkers' "anti EGFR therapy" "KRAS" "NRAS' "PIK3CA" "TP53" "PTEN" 'EGFR" "MET" "HER2" "epiregulin" "amphiregulin" "prognostic biomarkers" "BRAF" "miRNA" and "antibody dependent cell mediated cytotoxicity (ADCC) activity" Two investigators independently evaluated and extracted data from each identified studies based on selected criteria of inclusion and exclusion.  The introduction of agents targeting EGFR such as cetuximab and panitumumab increased overall survival of mCRCs. Nevertheless, it has firstly became evident that response rates to cetuximab regimens in unselected patient populations were typically lower than 30% Clinical data confirmed the predictive value of RAS mutations for resistance to cetuximab and panitumumab leading to the license of these monoclonal antibodies exclusively for the management of patients with RAS wild type colorectal cancers. So far the identification of predictive biomarkers have generated interesting, though preliminary and, at times, conflicting data on the importance of tumour mRNA levels of EGFR ligands, of activating mutations in other genes such as NRAS and PIK3CA. The prognostic value of selected microRNAs level and ADCC activity is under investigation, while the prognostic impact of BRAF status remains controversial.  This review focuses on the personalized treatment of mCRC and discusses the potential of new prognostic and predictive biomarkers in selecting patients treated with anti EGFR therapy.
Word Spotting Using Radial Descriptor Graph
Venue: 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)

In this paper we present, the Radial Descriptor Graph, a novel approach to compare pictorial representation of handwritten text, which is based on the radial descriptor. To build a radial descriptor graph, we compute the radial descriptor and generate feature points. These points are the nodes of the graph, and each adjacent points are connected to its adjacent node to form a planar graph. Then we iteratively reduce the edges of the graph, by merging adjacent nodes, to form a multilevel hierarchical representation of the graph. To compare two pictorial representations, we measure the distance between their correspondence planar graphs, after calculating the dominant signal for each node. The graph matching is based on optimizing the function that takes into account the distance between the feature points and the structure of the graphs. The distance between two radial descriptors is computed by measuring the difference between their corresponding dominant signals. We have tested our approach on three different datasets and obtained encouraging results.
Electrophysiological evaluation of attention in drivers and passengers: Toward an understanding of drivers' attentional state in autonomous vehicles

In order to safely use autonomous vehicle technologies, it is important to understand the state of drivers' attention as they ride in Level 3 self driving vehicles, because they might be required to take manual control of the vehicle in certain situations. We assumed that the attentional state of a driver who has perfect confidence in a self driving system, and as a result, who is unready to take control of the vehicle is similar to that of a passenger riding in a vehicle driven by another person. Therefore, we compared electrophysiological signals from drivers and passengers that were riding a vehicle in real road environments. Results indicated the following differences: (1) The number of small saccadic eye movements was greater in drivers than in passengers, whereas the number of large saccadic eye movements was greater in passengers than in drivers, indicating that passengers tended to look at information irrelevant to safe driving. (2) The amplitude of the P1 component of eye fixation related brain potentials time locked to the offset of large saccadic eye movements was greater in drivers than in passengers, indicating that visual information processing load was lower in passengers. (3) The duration of eye blinks was longer in passengers than in drivers, indicating that the arousal level of passengers was relatively low. These findings suggest that these electrophysiological indices can be useful measures for evaluating the attention of drivers while riding in Level 3 autonomous vehicles. Possible differences in the attentional state between drivers and passengers are discussed.
China&Apos;S Lost Generation: Changes in Beliefs and Their Intergenerational Transmission

Beliefs about whether effort pays off govern some of the most fundamental choices individuals make. This paper uses China's Cultural Revolution to understand how these beliefs can be affected, how they impact behavior, and how they are transmitted across generations. During the Cultural Revolution, China's college admission system based on entrance exams was suspended for a decade until 1976, effectively depriving an entire generation of young people of the opportunity to access higher education (the "lost generation" Using data from a nationally representative survey, we compare cohorts who graduated from high school just before and after the college entrance exam was resumed. We find that members of the "lost generation" who missed out on college because they were born just a year or two too early believe that effort pays off to a much lesser degree, even 40 years into their adulthood. However, they invested more in their children's education, and transmitted less of their changed beliefs to the next generation, suggesting attempts to safeguard their children from sharing their misfortunes.
China's new lost generation: the casualty of China's economic transformation

China's surge into global middle income status over the space of three decades has been spectacular. However, a potentially large and burdensome cost has been imposed on a generation of adolescents and young adults who abandoned the countryside, and with it access to basic education, in order to seek the anticipated advantages of jobs in the country's burgeoning urban industrial sector. This large swath of off farm migrants transformed China. It propelled China to the status of the 'world's factory' and created the scale and accumulated learning by doing enabling China's transition to a 'knowledge economy' that no longer depends on the labor of China's new 'Lost Generation. As the Lost Generation and its left behind children, who suffer from a chronic lack of schooling, thicken the lower tail of China's income distribution, it may be the rising, prosperous urban middle class that ultimately incurs the social, economic, and political challenges associated with China's generation of off farm migrant households once essential for launching China's economic ascent.
The Lost Generation. "Barefoot Doctors" in Post reform China

In the 1960s and 1970s, China's barefoot doctor system was acclaimed worldwide for providing inexpensive and equally accessible medical care for rural populations. In the 1980s, with the advent of market reform, the barefoot doctor system came to an end. Many barefoot doctors either became private doctors or gave up medical practice. More than three decades have passed since this dramatic change, and barefoot doctors seem to have been forgotten. However, the legacy of the barefoot doctor system is still felt in the hardship of aging former barefoot doctors who now find themselves pensionless. Based on ethnographic research in a county in Sichuan Province from 2011 to 2012, this article explores the experience of a group of former barefoot doctors to observe their transition in post reform China, and their struggle for payment, pension, and status in recent years. It records the change these doctors experienced from barefoot doctors working under very difficult conditions in the collective era, to individual doctors in the market era who struggle with qualification requirements, market competition, and selfsupport, to the newly ambiguous status of village doctors, who constitute an important part of the primary health care network but are still marginalised in the health care system.
The gut microbiome as a virtual endocrine organ with implications for farm and domestic animal endocrinology.
Venue: Domestic animal endocrinology

The gut microbiome exerts a marked influence on host physiology, and manipulation of its composition has repeatedly been shown to influence host metabolism and body composition. This virtual endocrine organ also has a role in the regulation of the plasma concentrations of tryptophan, an essential amino acid and precursor to serotonin, a key neurotransmitter within both the enteric and central nervous systems. Control over the hypothalamic pituitary adrenal axis also appears to be under the influence of the gut microbiota. This is clear from studies in microbiota deficient germ free animals with exaggerated responses to psychological stress that can be normalized by monocolonization with certain bacterial species including Bifidobacterium infantis. Therapeutic targeting of the gut microbiota may thus be useful in treating or preventing stress related microbiome gut brain axis disorders and metabolic diseases, much the same way as redirections of metabolopathies can be achieved through more traditional endocrine hormone based interventions. Moreover, the implications of these findings need to be considered in the context of farm and domestic animal physiology, behavior, and food safety.
The benefits and limitations of animal models for translational research in cartilage repair
Venue: Journal of Experimental Orthopaedics

Much research is currently ongoing into new therapies for cartilage defect repair with new biomaterials frequently appearing which purport to have significant regenerative capacity. These biomaterials may be classified as medical devices, and as such must undergo rigorous testing before they are implanted in humans. A large part of this testing involves in vitro trials and biomechanical testing. However, in order to bridge the gap between the lab and the clinic, in vivo preclinical trials are required, and usually demanded by regulatory approval bodies. This review examines the in vivo models in current use for cartilage defect repair testing and the relevance of each in the context of generated results and applicability to bringing the device to clinical practice. Some of the preclinical models currently used include murine, leporine, ovine, caprine, porcine, canine, and equine models. Each of these has advantages and disadvantages in terms of animal husbandry, cartilage thickness, joint biomechanics and ethical and licencing issues. This review will examine the strengths and weaknesses of the various animal models currently in use in preclinical studies of cartilage repair.
Treatment of full thickness focal cartilage lesions with a metallic resurfacing implant in a sheep animal model, 1 year evaluation.
Venue: Osteoarthritis and cartilage

Full depth focal cartilage lesions do not heal spontaneously and while some of these lesions are asymptomatic they might progress to osteoarthritis. Treatment for these lesions is warranted and the gold standard treatment at younger age remains biological healing by cell stimulation. In the middle age patient the success rate of biologic treatment varies, hence the surge of non biological alternatives. Our objective was to evaluate the efficacy and safety of a metallic implant for treatment of these lesions with respect to the long term panarticular cartilage homeostasis.  The medial femoral condyle of 16 sheep was operated unilaterally. A metallic implant was inserted in the weight bearing surface at an aimed height of 0.5 mm recessed. Euthanasia was performed at 6 or 12 months. Implant height and tilt was analyzed using a laser scanning device. Damage to cartilage surfaces was evaluated macroscopically and microscopically according to the Osteoarthritis Research Society International (OARSI) recommendations.  Thirteen sheep were available for evaluation and showed a varying degree of cartilage damage linearly increasing with age. Cartilage damage of the medial tibial plateau opposing the implant was increased compared to the non operated knee by 1.77 units (p 0.041; 95% CI: 0.08, 3.45) on a 0 27 unit scale. Remaining joint compartments were unaffected. Implant position averaged 0.54 recessed (95% CI: 0.41, 0.67) CONCLUSIONS Our results showed a consistent and accurate placement of these implants at a defined zone. At this position cartilage wear of opposing and surrounding joint cartilage is limited. Thus expanded animal and human studies are motivated.
Halosulfuron: Crop Tolerance, Weed Control and Species Sensitivity in Dry Beans

University of Guelph, 2016 Dr. Peter Sikkema and Dr. Rene Van Acker Twelve field experiments were conducted over a two year period (2013, 2014) to evaluate the tolerance of white bean to halosulfuron and spectrum of weeds controlled with halosulfuron applied alone and in combination with trifluralin, pendimethalin, EPTC, dimethenamid P or S metolachlor applied preplant incorporated (PPI) and pendimethalin, dimethenamid P or S metolachlor applied preemergence (PRE) At 1 and 4 weeks after emergence (WAE) halosulfuron applied PPI or PRE, applied alone or in combination with trifluralin, pendimethalin, EPTC, dimethenamid P or S metolachlor caused 3% At 4 and 8 WAE, halosulfuron applied PPI or PRE provided 90% control of common lambsquarters, wild mustard, redroot pigweed and common ragweed and 60% control of green foxtail. Weed biomass and density data reflected the weed control ratings. White bean yield with halosulfuron applied in combination with trifluralin, pendimethalin, EPTC, dimethenamid P or S metolachlor was equivalent to the weed free control. Halosulfuron absorption, translocation and metabolism were studied in white and adzuki bean. Halosulfuron was absorbed more rapidly in adzuki bean than white bean. Adzuki bean reached 90% absorption (t90) 26.2 hours after treatment (HAT) while white bean required 40.1 HAT to reach t90. The maximum halosulfuron absorption (Amax) was higher in adzuki bean (75.7% than in white bean (65.3% More C halosulfuron was translocated to the apex, 1 trifoliate, stem above the treated leaf and roots in aduzki bean than in white bean. The maxiumum radioactivity translocated out of treated leaf (Tmax) was higher in adzuki bean (17.7% than in white bean (12.1% Halosulfuron was broken down to the same metabolites in white and adzuki bean. The half life of halosulfuron in adzuki bean and white bean was 16 HAT and 6 HAT, respectively. Differential tolerance of white and adzuki bean to halosulfuron can be attributed to greater absorption, greater translocation and decreased metabolism in adzuki bean.
Caffeine: Towards uniformed representation and acceleration for deep convolutional neural networks
Venue: 2016 IEEE/ACM International Conference on Computer Aided Design (ICCAD)

With the recent advancement of multilayer convolutional neural networks (CNN) deep learning has achieved amazing success in many areas, especially in visual content understanding and classification. To improve the performance and energy efficiency of the computation demanding CNN, the FPGA based acceleration emerges as one of the most attractive alternatives. In this paper we design and implement Caffeine, a hardware/software co designed library to efficiently accelerate the entire CNN on FPGAs. First, we propose a uniformed convolutional matrix multiplication representation for both computation intensive convolutional layers and communication intensive fully connected (FCN) layers. Second, we design Caffeine with the goal to maximize the underlying FPGA computing and bandwidth resource utilization, with a key focus on the bandwidth optimization by the memory access reorganization not studied in prior work. Moreover, we implement Caffeine in the portable high level synthesis and provide various hardware/software definable parameters for user configurations. Finally, we also integrate Caffeine into the industry standard software deep learning framework Caffe. We evaluate Caffeine and its integration with Caffe by implementing VGG16 and AlexNet network on multiple FPGA platforms. Caffeine achieves a peak performance of 365 GOPS on Xilinx KU060 FPGA and 636 GOPS on Virtex7 690t FPGA. This is the best published result to our best knowledge. We achieve more than 100x speedup on FCN layers over previous FPGA accelerators. An end to end evaluation with Caffe integration shows up to 7.3x and 43.5x performance and energy gains over Caffe on a 12 core Xeon server, and 1.5x better energy efficiency over the GPU implementation on a medium sized FPGA (KU060) Performance projections to a system with a high end FPGA (Virtex7 690t) shows even higher gains.
Exemplar inspired strategies for low resource spoken keyword search in Swahili
Venue: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

We present exemplar inspired low resource spoken keyword search strategies for acoustic modeling, keyword verification, and system combination. This state of the art system was developed by the SINGA team in the context of the 2015 NIST Open Keyword Search Evaluation (OpenKWS15) using conversational Swahili provided by the IARPA Babel program. In this work, we elaborate on the following: (1) exploiting exemplar training samples to construct a non parametric acoustic model using kernel density estimation at test time; (2) rescoring hypothesized keyword detections through quantifying their acoustic similarity with exemplar training samples; (3 extending our previously proposed system combination approach to incorporate prosody features of exemplar keyword samples.
Deriving a strategy for synthesizing lengthening disfluencies based on spontaneous conversational speech data

Our overarching research project explores the usability of disfluencies in incremental spoken dialogue systems. This endeavor requires basic phonetic research on disfluencies in spontaneous speech corpora as to define strategies for synthesizing disfluencies in a meaningful way. In this paper, our current research focus lies in an investigation of disfluency related lengthening as a promising time buying strategy in synthesized dialogue [1][2] We base our analyses on the results of a search tool aiming to automatically detect lengthening in spontaneous speech corpora occurring without adjacency to phrase boundaries or other disfluencies, i.e. standalone lengthening phenomena. We analyzed disfluency related lengthening in the "monomodal" half of the GECO corpus  with regard to their context, word class, syllable position and phone type. We then postulate a disfluency insertion strategy for synthetic speech that prioritizes lengthening phenomena based on the results obtained in our study.
Visual Aesthetic Analysis for Handwritten Document Images
Venue: 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)

We present an approach for analyzing the visual aesthetic property of a handwritten document page which matches with human perception. We formulate the problem at two independent levels: (i) coarse level which deals with the overall layout, space usages between lines, words and margins, and (ii) fine level, which analyses the construction of each word and deals with the aesthetic properties of writing styles. We present our observations on multiple local and global features which can extract the aesthetic cues present in the handwritten documents.
Matching Handwritten Document Images
Venue: ECCV

We address the problem of predicting similarity between a pair of handwritten document images written by potentially different individuals. This has applications related to matching and mining in image collections containing handwritten content. A similarity score is computed by detecting patterns of text re usages between document images irrespective of the minor variations in word morphology, word ordering, layout and paraphrasing of the content. Our method does not depend on an accurate segmentation of words and lines. We formulate the document matching problem as a structured comparison of the word distributions across two document images. To match two word images, we propose a convolutional neural network (cnn) based feature descriptor. Performance of this representation surpasses the state of the art on handwritten word spotting. Finally, we demonstrate the applicability of our method on a practical problem of matching handwritten assignments.