nils-herrmann/clean_scirepeval huggingface dataset:
An External Capacitorless Low-Dropout Regulator With High PSR at All Frequencies From 10 kHz to 1 GHz Using an Adaptive Supply-Ripple Cancellation Technique

Herein is presented an external capacitorless low-dropout regulator (LDO) that provides high-power-supply rejection (PSR) at all low-to-high frequencies. The LDO is designed to have the dominant pole at the gate of the pass transistor to secure stability without the use of an external capacitor, even when the load current increases significantly. Using the proposed adaptive supply-ripple cancellation (ASRC) technique, in which the ripples copied from the supply are injected adaptively to the body gate, the PSR hump that appears in conventional gate-pole-dominant LDOs can be suppressed significantly. Since the ASRC circuit continues to adjust the magnitude of the injecting ripples to an optimal value, the LDO presented here can maintain high PSRs, irrespective of the magnitude of the load current <inline-formula> <tex-math notation="LaTeX">$I_{L}$ </tex-math></inline-formula>, or the dropout voltage <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm {DO}}$ </tex-math></inline-formula>. The proposed LDO was fabricated in a 65-nm CMOS process, and it had an input voltage of 1.2 V. With a 240-pF load capacitor, the measured PSRs were less than −36 dB at all frequencies from 10 kHz to 1 GHz, despite changes of <inline-formula> <tex-math notation="LaTeX">$I_{L}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm {DO}}$ </tex-math></inline-formula> as well as process, voltage, temperature (PVT) variations.
Neoantigens in cancer immunotherapy

The clinical relevance of T cells in the control of a diverse set of human cancers is now beyond doubt. However, the nature of the antigens that allow the immune system to distinguish cancer cells from noncancer cells has long remained obscure. Recent technological innovations have made it possible to dissect the immune response to patient-specific neoantigens that arise as a consequence of tumor-specific mutations, and emerging data suggest that recognition of such neoantigens is a major factor in the activity of clinical immunotherapies. These observations indicate that neoantigen load may form a biomarker in cancer immunotherapy and provide an incentive for the development of novel therapeutic approaches that selectively enhance T cell reactivity against this class of antigens.
The 4S Web-Marketing Mix model

This paper reviews the criticism on the 4Ps Marketing Mix framework, the most popular tool of traditional marketing management, and categorizes the main objections of using the model as the foundation of physical marketing. It argues that applying the traditional approach, based on the 4Ps paradigm, is also a poor choice in the case of virtual marketing and identifies two main limitations of the framework in online environments: the drastically diminished role of the Ps and the lack of any strategic elements in the model. Next to identifying the critical factors of the Web marketing, the paper argues that the basis for successful E-Commerce is the full integration of the virtual activities into the company’s physical strategy, marketing plan and organisational processes. The four S elements of the Web-Marketing Mix framework present a sound and functional conceptual basis for designing, developing and commercialising Business-to-Consumer online projects. The model was originally developed for educational purposes and has been tested and refined by means of field projects; two of them are presented as case studies in the paper.
Complex Event Detection at Wire Speed with FPGAs

Complex event detection is an advanced form of data stream processing where the stream(s) are scrutinized to identify given event patterns. The challenge for many complex event processing (CEP) systems is to be able to evaluate event patterns on high-volume data streams while adhering to realtime constraints. To solve this problem, in this paper we present a hardware based complex event detection system implemented on field-programmable gate arrays (FPGAs). By inserting the FPGA directly into the data path between the network interface and the CPU, our solution can detect complex events at gigabit wire speed with constant and fully predictable latency, independently of network load, packet size or data distribution. This is a significant improvement over CPU based systems and an architectural approach that opens up interesting opportunities for hybrid stream engines that combine the flexibility of the CPU with the parallelism and processing power of FPGAs.
A deep learning pipeline for product recognition on store shelves

Recognition of grocery products in store shelves poses peculiar challenges. Firstly, the task mandates the recognition of an extremely high number of different items, in the order of several thousands for medium-small shops, with many of them featuring small inter and intra class variability. Then, available product databases usually include just one or a few studio-quality images per product (referred to herein as reference images), whilst at test time recognition is performed on pictures displaying a portion of a shelf containing several products and taken in the store by cheap cameras (referred to as query images). Moreover, as the items on sale in a store as well as their appearance change frequently over time, a practical recognition system should handle seamlessly new products/packages. Inspired by recent advances in object detection and image retrieval, we propose to leverage on state of the art object detectors based on deep learning to obtain an initial productagnostic item detection. Then, we pursue product recognition through a similarity search between global descriptors computed on reference and cropped query images. To maximize performance, we learn an ad-hoc global descriptor by a CNN trained on reference images based on an image embedding loss. Our system is computationally expensive at training time but can perform recognition rapidly and accurately at test time.
Comparison of in-person and digital photograph assessment of stage III and IV pressure ulcers among veterans with spinal cord injuries.

Digital photographs are often used in treatment monitoring for home care of less advanced pressure ulcers. We investigated assessment agreement when stage III and IV pressure ulcers in individuals with spinal cord injury were evaluated in person and with the use of digital photographs. Two wound-care nurses assessed 31 wounds among 15 participants. One nurse assessed all wounds in person, while the other used digital photographs. Twenty-four wound description categories were applied in the nurses' assessments. Kappa statistics were calculated to investigate agreement beyond chance (p < or = 0.05). For 10 randomly selected "double-rated wounds," both nurses applied both assessment methods. Fewer categories were evaluated for the double-rated wounds, because some categories were chosen infrequently and agreement could not be measured. Interrater agreement with the two methods was observed for 12 of the 24 categories (50.0%). However, of the 12 categories with agreement beyond chance, agreement was only "slight" (kappa = 0-0.20) or "fair" (kappa = 0.21-0.40) for 6 categories. The highest agreement was found for the presence of undermining (kappa = 0.853, p < 0.001). Interrater agreement was similar to intramethod agreement (41.2% of the categories demonstrated agreement beyond chance) for the nurses' in-person assessment of the double-rated wounds. The moderate agreement observed may be attributed to variation in subjective perception of qualitative wound characteristics.
CNN features are also great at unsupervised classification

This paper aims at providing insight on the transferability of deep CNN features to unsupervised problems. We study the impact of different pretrained CNN feature extractors on the problem of image set clustering for object classification as well as fine-grained classification. We propose a rather straightforward pipeline combining deep-feature extraction using a CNN pretrained on ImageNet and a classic clustering algorithm to classify sets of images. This approach is compared to state-of-the-art algorithms in image-clustering and provides better results. These results strengthen the belief that supervised training of deep CNN on large datasets, with a large variability of classes, extracts better features than most carefully designed engineering approaches, even for unsupervised tasks. We also validate our approach on a robotic application, consisting in sorting and storing objects smartly based on clustering.
Exercise training in patients with advanced chronic heart failure (NYHA IIIb) promotes restoration of peripheral vasomotor function, induction of endogenous regeneration, and improvement of left ventricular function.

Attenuated peripheral perfusion in patients with advanced chronic heart failure (CHF) is partially the result of endothelial dysfunction. This has been causally linked to an impaired endogenous regenerative capacity of circulating progenitor cells (CPC). The aim of this study was to elucidate whether exercise training (ET) affects exercise intolerance and left ventricular (LV) performance in patients with advanced CHF (New York Heart Association class IIIb) and whether this is associated with correction of peripheral vasomotion and induction of endogenous regeneration.



Thirty-seven patients with CHF (LV ejection fraction 24+/-2%) were randomly assigned to 12 weeks of ET or sedentary lifestyle (control). At the beginning of the study and after 12 weeks, maximal oxygen consumption (Vo(2)max) and LV ejection fraction were determined; the number of CD34(+)/KDR(+) CPCs was quantified by flow cytometry and CPC functional capacity was determined by migration assay. Flow-mediated dilation was assessed by ultrasound. Capillary density was measured in skeletal muscle tissue samples. In advanced CHF, ET improved Vo(2)max by +2.7+/-2.2 versus -0.8+/-3.1 mL/min/kg in control (P=0.009) and LV ejection fraction by +9.4+/-6.1 versus -0.8+/-5.2% in control (P<0.001). Flow-mediated dilation improved by +7.43+/-2.28 versus +0.09+/-2.18% in control (P<0.001). ET increased the number of CPC by +83+/-60 versus -6+/-109 cells/mL in control (P=0.014) and their migratory capacity by +224+/-263 versus -12+/-159 CPC/1000 plated CPC in control (P=0.03). Skeletal muscle capillary density increased by +0.22+/-0.10 versus -0.02+/-0.16 capillaries per fiber in control (P<0.001).



Twelve weeks of ET in patients with advanced CHF is associated with augmented regenerative capacity of CPCs, enhanced flow-mediated dilation suggestive of improvement in endothelial function, skeletal muscle neovascularization, and improved LV function.
Lithium batteries and cathode materials.

In the previous paper Ralph Brodd and Martin Winter described the different kinds of batteries and fuel cells. In this paper I will describe lithium batteries in more detail, building an overall foundation for the papers that follow which describe specific components in some depth and usually with an emphasis on the materials behavior. The lithium battery industry is undergoing rapid expansion, now representing the largest segment of the portable battery industry and dominating the computer, cell phone, and camera power source industry. However, the present secondary batteries use expensive components, which are not in sufficient supply to allow the industry to grow at the same rate in the next decade. Moreover, the safety of the system is questionable for the large-scale batteries needed for hybrid electric vehicles (HEV). Another battery need is for a high-power system that can be used for power tools, where only the environmentally hazardous Ni/ Cd battery presently meets the requirements. A battery is a transducer that converts chemical energy into electrical energy and vice versa. It contains an anode, a cathode, and an electrolyte. The anode, in the case of a lithium battery, is the source of lithium ions. The cathode is the sink for the lithium ions and is chosen to optimize a number of parameters, discussed below. The electrolyte provides for the separation of ionic transport and electronic transport, and in a perfect battery the lithium ion transport number will be unity in the electrolyte. The cell potential is determined by the difference between the chemical potential of the lithium in the anode and cathode, ∆G ) -EF. As noted above, the lithium ions flow through the electrolyte whereas the electrons generated from the reaction, Li ) Li+ + e-, go through the external circuit to do work. Thus, the electrode system must allow for the flow of both lithium ions and electrons. That is, it must be both a good ionic conductor and an electronic conductor. As discussed below, many electrochemically active materials are not good electronic conductors, so it is necessary to add an electronically conductive material such as carbon * To whom correspondence should be addressed. Phone and fax: (607) 777-4623.   2004, 104,
Tree-Structured Reinforcement Learning for Sequential Object Localization

Existing object proposal algorithms usually search for possible object regions over multiple locations and scales separately, which ignore the interdependency among different objects and deviate from the human perception procedure. To incorporate global interdependency between objects into object localization, we propose an effective Tree-structured Reinforcement Learning (Tree-RL) approach to sequentially search for objects by fully exploiting both the current observation and historical search paths. The Tree-RL approach learns multiple searching policies through maximizing the long-term reward that reflects localization accuracies over all the objects. Starting with taking the entire image as a proposal, the Tree-RL approach allows the agent to sequentially discover multiple objects via a tree-structured traversing scheme. Allowing multiple near-optimal policies, Tree-RL offers more diversity in search paths and is able to find multiple objects with a single feedforward pass. Therefore, Tree-RL can better cover different objects with various scales which is quite appealing in the context of object proposal. Experiments on PASCAL VOC 2007 and 2012 validate the effectiveness of the Tree-RL, which can achieve comparable recalls with current object proposal algorithms via much fewer candidate windows.
To Graft or Not to Graft? Evidence-Based Guide to Decision Making in Oral Bone Graft Surgery

Rehabilitation of the incomplete dentition by means of osseointegrated implants represents a highly predictable and widespread therapy. Advantages of oral implant treatment over conventional non-surgical prosthetic rehabilitation involve avoidance of removable dentures and tooth structure conservation of the remaining dentition. Implant placement necessitates sufficient bone quantity as well as bone quality, that may be compromised following tooth loss or trauma. Sufficient alveolar bone to host implants of 10 mm in length and 3-4 mm in diameter has been traditionally regarded as minimum requirements to allow bone-demanded implant placement. Three-dimensional bone morphology, however, may not permit favourable implant positioning. In the age of prosthetic-driven implant treatment, bone grafting procedures may be indicated not exclusively due to lack of bone volume, but to ensure favourable biomechanics and long-term esthetic outcome. A vast variety of treatment modalities have been suggested to increase alveolar bone volume and thus overcome the intrinsic limitations of oral implantology. Although success rates of various bone graft techniques are high, inherent disadvantages of augmentation procedures include prolonged treatment times, raised treatment costs and increased surgical invasion associated with patient morbidity and potential complications. Therefore, treatment tactics to obviate bone graft surgery are naturally preferred by both patients and surgeons. Nongrafting options, such as implants reduced in length and diameter or the use of computerguided implant surgery, may on the other hand carry the risk of lower predictability and reduced long-term success. To graft or not to graft? – that is the question clinicians are facing day-to-day in oral implant rehabilitation.
Analysis of all-in-focus image processing in image restoration

We discuss a new deblurring problems in this paper. Focus measurements play a fundamental role in image processing techniques. Most traditional methods neglect spatial information in the frequency domain. Therefore, this study analyzed image data in the frequency domain to determine the value of spatial information. but instead misleading noise reduction results . We found that the local feature is not always a guide for noise reduction. This finding leads to a new method to measure the image edges in focus deblurring. We employed an all-in-focus measure in the frequency domain, based on the energy level of frequency components. We also used a multi-circle enhancement model to analyze this spatial information to provide a more accurate method for measuring images. We compared our results with those using other methods in similar studies. Findings demonstrate the effectiveness of our new method.
Cannabidiol (CBD) and its analogs: a review of their effects on inflammation.

First isolated from Cannabis in 1940 by Roger Adams, the structure of CBD was not completely elucidated until 1963. Subsequent studies resulted in the pronouncement that THC was the 'active' principle of Cannabis and research then focused primarily on it to the virtual exclusion of CBD. This was no doubt due to the belief that activity meant psychoactivity that was shown by THC and not by CBD. In retrospect this must be seen as unfortunate since a number of actions of CBD with potential therapeutic benefit were downplayed for many years. In this review, attention will be focused on the effects of CBD in the broad area of inflammation where such benefits seem likely to be developed. Topics covered in this review are; the medicinal chemistry of CBD, CBD receptor binding involved in controlling Inflammation, signaling events generated by CBD, downstream events affected by CBD (gene expression and transcription), functional effects reported for CBD and combined THC plus CBD treatment.
The Vertical Farm : A Review of Developments and Implications for the Vertical City

This paper discusses the emerging need for vertical farms by examining issues related to food security, urban population growth, farmland shortages, “food miles”, and associated greenhouse gas (GHG) emissions. Urban planners and agricultural leaders have argued that cities will need to produce food internally to respond to demand by increasing population and to avoid paralyzing congestion, harmful pollution, and unaffordable food prices. The paper examines urban agriculture as a solution to these problems by merging food production and consumption in one place, with the vertical farm being suitable for urban areas where available land is limited and expensive. Luckily, recent advances in greenhouse technologies such as hydroponics, aeroponics, and aquaponics have provided a promising future to the vertical farm concept. These high-tech systems represent a paradigm shift in farming and food production and offer suitable and efficient methods for city farming by minimizing maintenance and maximizing yield. Upon reviewing these technologies and examining project prototypes, we find that these efforts may plant the seeds for the realization of the vertical farm. The paper, however, closes by speculating about the consequences, advantages, and disadvantages of the vertical farm’s implementation. Economic feasibility, codes, regulations, and a lack of expertise remain major obstacles in the path to implementing the vertical farm.
2 . 2 um BSI CMOS image sensor with two layer photodetector

Back Side Illumination (BSI) CMOS image sensors with two-layer photo detectors (2LPDs) have been fabricated and evaluated. The test pixel array has green pixels (2.2um x 2.2um) and a magenta pixel (2.2um x 4.4um). The green pixel has a single-layer photo detector (1LPD). The magenta pixel has a 2LPD and a vertical charge transfer (VCT) path to contact a back side photo detector. The 2LPD and the VCT were implemented by high-energy ion implantation from the circuit side. Measured spectral response curves from the 2LPDs fitted well with those estimated based on lightabsorption theory for Silicon detectors. Our measurement results show that the keys to realize the 2LPD in BSI are; (1) the reduction of crosstalk to the VCT from adjacent pixels and (2) controlling the backside photo detector thickness variance to reduce color signal variations.
Does gamification increase engagement with online programs? A systematic review

Engagement in online programs is difficult to maintain. Gamification is the recent trend that offers to increase engagement through the inclusion of game-like features like points and badges, in non-game contexts. This review will answer the following question, 'Are gamification strategies effective in increasing engagement in online programs?'



Eight databases (Web of Science, PsycINFO, Medline, INSPEC, ERIC, Cochrane Library, Business Source Complete and ACM Digital Library) were searched from 2010 to the 28th of October 2015 using a comprehensive search strategy. population" included adults, "intervention" involved an online program or smart phone application that included at least one gamification feature. "Comparator" was a control group, "outcomes" included engagement and "downstream" outcomes which occurred as a result of engagement; and "study design" included experimental studies from peer-reviewed sources. Effect sizes (Cohens d and 95% confidence intervals) were also calculated.



1017 studies were identified from database searches following the removal of duplicates, of which 15 met the inclusion criteria. The studies involved a total of 10,499 participants, and were commonly undertaken in tertiary education contexts. Engagement metrics included time spent (n = 5), volume of contributions (n = 11) and occasions visited to the software (n = 4); as well as downstream behaviours such as performance (n = 4) and healthy behaviours (n = 1). Effect sizes typically ranged from medium to large in direct engagement and downstream behaviours, with 12 out of 15 studies finding positive significant effects in favour of gamification.



Gamification is effective in increasing engagement in online programs. Key recommendations for future research into gamification are provided. In particular, rigorous study designs are required to fully examine gamification's effects and determine how to best achieve sustained engagement.
Deep Sparse Rectifier Neural Networks

Rectifying neurons are more biologically plausible than logistic sigmoid neurons, which are themselves more biologically plausible than hyperbolic tangent neurons. However, the latter work better for training multi-layer neural networks than logistic sigmoid neurons. This paper shows that networks of rectifying neurons yield equal or better performance than hyperbolic tangent networks in spite of the hard non-linearity and non-differentiability at zero and create sparse representations with true zeros which are remarkably suitable for naturally sparse data. Even though they can take advantage of semi-supervised setups with extraunlabeled data, deep rectifier networks can reach their best performance without requiring any unsupervised pre-training on purely supervised tasks with large labeled datasets. Hence, these results can be seen as a new milestone in the attempts at understanding the difficulty in training deep but purely supervised neural networks, and closing the performance gap between neural networks learnt with and without unsupervised pre-training.