nils-herrmann/clean_scirepeval huggingface dataset:
Detecting activities of daily living in first-person camera views

We present a novel dataset and novel algorithms for the problem of detecting activities of daily living (ADL) in firstperson camera views. We have collected a dataset of 1 million frames of dozens of people performing unscripted, everyday activities. The dataset is annotated with activities, object tracks, hand positions, and interaction events. ADLs differ from typical actions in that they can involve long-scale temporal structure (making tea can take a few minutes) and complex object interactions (a fridge looks different when its door is open). We develop novel representations including (1) temporal pyramids, which generalize the well-known spatial pyramid to approximate temporal correspondence when scoring a model and (2) composite object models that exploit the fact that objects look different when being interacted with. We perform an extensive empirical evaluation and demonstrate that our novel representations produce a two-fold improvement over traditional approaches. Our analysis suggests that real-world ADL recognition is “all about the objects,” and in particular, “all about the objects being interacted with.”
Review of Trust and Machine Ethics Research: Towards A Bio-Inspired Computational Model of Ethical Trust (CMET)

Recent advances in the fields of robotics, cyborg development, moral psychology, trust, multi agent-based systems and socionics have raised the need for a better understanding of ethics, moral reasoning, judgment and decision-making within the system of man and machines. Here we seek to understand key research questions concerning the interplay of ethical trust at the individual level and the social moral norms at the collective end. We review salient works in the fields of trust and machine ethics research, underscore the importance and the need for a deeper understanding of ethical trust at the individual level and the development of collective social moral norms. Drawing upon the recent findings from neural sciences on mirror-neuron system (MNS) and social cognition, we present a bio-inspired Computational Model of Ethical Trust (CMET) to allow investigations of the interplay of ethical trust and social moral norms.
Drug Hypersensitivity Reactions: Classification and relationship to T cell activation

The clinical characteristics of drug hypersensitivity reactions are very heterogeneous as drugs can actually elicit all types of immune reactions. The majority of allergic reactions involve either drug-specific IgE or T cells. Their stimulation leads to quite distinct immune responses, which are classified according to Gell and Coombs. Here, an extension of this subclassification, which considers the distinct T-cell functions and immunopathologies, is presented. These subclassifications are clinically useful, as they require different treatment and diagnostic steps.
Conventional Linear versus Purse-string Skin Closure after Loop Ileostomy Reversal: Comparison of Wound Infection Rates and Operative Outcomes

Wound infection after an ileostomy reversal is a common problem. To reduce wound-related complications, purse-string skin closure was introduced as an alternative to conventional linear skin closure. This study is designed to compare wound infection rates and operative outcomes between linear and purse-string skin closure after a loop ileostomy reversal.



Between December 2002 and October 2010, a total of 48 consecutive patients undergoing a loop ileostomy reversal were enrolled. Outcomes were compared between linear skin closure (group L, n = 30) and purse string closure (group P, n = 18). The operative technique for linear skin closure consisted of an elliptical incision around the stoma, with mobilization, and anastomosis of the ileum. The rectus fascia was repaired with interrupted sutures. Skin closure was performed with vertical mattress interrupted sutures. Purse-string skin closure consisted of a circumstomal incision around the ileostomy using the same procedures as used for the ileum. Fascial closure was identical to linear closure, but the circumstomal skin incision was approximated using a purse-string subcuticular suture (2-0 Polysorb).



Between group L and P, there were no differences of age, gender, body mass index, and American Society of Anesthesiologists (ASA) scores. Original indication for ileostomy was 23 cases of malignancy (76.7%) in group L, and 13 cases of malignancy (77.2%) in group P. The median time duration from ileostomy to reversal was 4.0 months (range, 0.6 to 55.7 months) in group L and 4.1 months (range, 2.2 to 43.9 months) in group P. The median operative time was 103 minutes (range, 45 to 260 minutes) in group L and 100 minutes (range, 30 to 185 minutes) in group P. The median hospital stay was 11 days (range, 5 to 4 days) in group L and 7 days (range, 4 to 14 days) in group P (P < 0.001). Wound infection was found in 5 cases (16.7%) in group L and in one case (5.6%) in group L (P = 0.26).



Based on this study, purse-string skin closure after a loop ileostomy reversal showed comparable outcomes, in terms of wound infection rates, to those of linear skin closure. Thus, purse-string skin closure could be a good alternative to the conventional linear closure.
Breast cancer detection using automated whole breast ultrasound and mammography in radiographically dense breasts

Mammography, the standard method of breast cancer screening, misses many cancers, especially in dense-breasted women. We compared the performance and diagnostic yield of mammography alone versus an automated whole breast ultrasound (AWBU) plus mammography in women with dense breasts and/or at elevated risk of breast cancer. AWBU screening was tested in 4,419 women having routine mammography ( Cancers occurring during the study and subsequent 1-year follow-up were evaluated. Sensitivity, specificity and positive predictive value (PPV) of biopsy recommendation for mammography alone, AWBU and mammography with AWBU were calculated. Breast cancer detection doubled from 23 to 46 in 6,425 studies using AWBU with mammography, resulting in an increase in diagnostic yield from 3.6 per 1,000 with mammography alone to 7.2 per 1,000 by adding AWBU. PPV for biopsy based on mammography findings was 39.0% and for AWBU 38.4%. The number of detected invasive cancers 10 mm or less in size tripled from 7 to 21 when AWBU findings were added to mammography. AWBU resulted in significant cancer detection improvement compared with mammography alone. Additional detection and the smaller size of invasive cancers may justify this technology’s expense for women with dense breasts and/or at high risk for breast cancer.
A new index to discriminate between iron deficiency anemia and thalassemia trait

The most common microcytic and hypochromic anemias are iron deficiency anemia and thalassemia trait. Several indices to discriminate iron deficiency anemia from thalassemia trait have been proposed as simple diagnostic tools. However, some of the best discriminative indices use parameters in the formulas that are only measured in modern counters and are not always available in small laboratories. The development of an index with good diagnostic accuracy based only on parameters derived from the blood cell count obtained using simple counters would be useful in the clinical routine. Thus, the aim of this study was to develop and validate a discriminative index to differentiate iron deficiency anemia from thalassemia trait.



To develop and to validate the new formula, blood count data from 106 (thalassemia trait: 23 and iron deficiency: 83) and 185 patients (thalassemia trait: 30 and iron deficiency: 155) were used, respectively. Iron deficiency, β-thalassemia trait and α-thalassemia trait were confirmed by gold standard tests (low serum ferritin for iron deficiency anemia, HbA2>3.5% for β-thalassemia trait and using molecular biology for the α-thalassemia trait).



The sensitivity, specificity, efficiency, Youden's Index, area under receiver operating characteristic curve and Kappa coefficient of the new formula, called the Matos & Carvalho Index were 99.3%, 76.7%, 95.7%, 76.0, 0.95 and 0.83, respectively.



The performance of this index was excellent with the advantage of being solely dependent on the mean corpuscular hemoglobin concentration and red blood cell count obtained from simple automatic counters and thus may be of great value in underdeveloped and developing countries.
Integrated Pest Management

Worldwide, integrated pest management (IPM) is the policy decision for pest management. It has been five decades since the development of threshold theory and harmonious control strategies were the domain of pest management research in the USA, Canada, and some parts of Europe. In the 1970s the work on development and validation of IPM technologies started in developing countries. The implementation of IPM and pesticide reduction programs has been in place in the developed and developing countries for the last three to four decades. There are plausible questions raised about the objectives of IPM, adoption of IPM practices, and pesticide use. Questions are also being raised on the use of robust indicators to measure the impact of IPM research and extension. Pesticide use by volume, pesticide use by treatment frequency index, reduction in use of more toxic pesticides, and environmental impact quotient have been used as IPM impact evaluation indicators. Low volume pesticides and transgenic crops both decreased and stabilized pesticide use in the 1990s and early 2000s. Since then, the pesticide sales regained an upward trajectory, and pesticide use in agriculture has increased. Transgenetic crops were thus not proven to be a perfect technique in IPM. We propose that the reduction in pesticide use frequency and the environmental impact quotient be the primary indicators to evaluate the success of IPM programs in the future. We have moved full circle from IPM to integrated pest and pesticide management. This chapter analyzes the development and implementation of IPM programs in the developed and developing countries and their impact on pesticide use.
Integrated coverage and connectivity configuration in wireless sensor networks

An effective approach for energy conservation in wireless sensor networks is scheduling sleep intervals for extraneous nodes, while the remaining nodes stay active to provide continuous service. For the sensor network to operate successfully, the active nodes must maintain both sensing coverage and network connectivity. Furthermore, the network must be able to configure itself to any feasible degrees of coverage and connectivity in order to support different applications and environments with diverse requirements. This paper presents the design and analysis of novel protocols that can dynamically configure a network to achieve guaranteed degrees of coverage and connectivity. This work differs from existing connectivity or coverage maintenance protocols in several key ways: 1) We present a Coverage Configuration Protocol (CCP) that can provide different degrees of coverage requested by applications. This flexibility allows the network to self-configure for a wide range of applications and (possibly dynamic) environments. 2) We provide a geometric analysis of the relationship between coverage and connectivity. This analysis yields key insights for treating coverage and connectivity in a unified framework: this is in sharp contrast to several existing approaches that address the two problems in isolation. 3) Finally, we integrate CCP with SPAN to provide both coverage and connectivity guarantees. We demonstrate the capability of our protocols to provide guaranteed coverage and connectivity configurations, through both geometric analysis and extensive simulations.
Compact Watershed and Preemptive SLIC: On Improving Trade-offs of Superpixel Segmentation Algorithms

A major insight from our previous work on extensive comparison of super pixel segmentation algorithms is the existence of several trade-offs for such algorithms. The most intuitive is the trade-off between segmentation quality and runtime. However, there exist many more between these two and a multitude of other performance measures. In this work, we present two new super pixel segmentation algorithms, based on existing algorithms, that provide better balanced trade-offs. Better balanced means, that we increase one performance measure by a large amount at the cost of slightly decreasing another. The proposed new algorithms are expected to be more appropriate for many real time computer vision tasks. The first proposed algorithm, Preemptive SLIC, is a faster version of SLIC, running at frame-rate (30 Hz for image size 481x321) on a standard desktop CPU. The speed-up comes at the cost of slightly worse segmentation quality. The second proposed algorithm is Compact Watershed. It is based on Seeded Watershed segmentation, but creates uniformly shaped super pixels similar to SLIC in about 10 ms per image. We extensively evaluate the influence of the proposed algorithmic changes on the trade-offs between various performance measures.
Fit-breaks: incorporating physical activity breaks in introductory CS lectures

University can be a difficult, stressful time for students. This stress causes problems ranging from academic difficulties and poor performance, to serious mental and physical health issues. Studies have shown that physical activity can help reduce stress, improve academic performance and contribute to a healthier campus atmosphere physically, mentally, and emotionally. Computer science is often considered among the most difficult and stressful programs offered at academic institutions. Yet the current stereotype of computer scientists includes unhealthy lifestyle choices and de-emphasizes physical activity. 
 This paper analyzes the effects of introducing short periods of physical activity into an introductory CS course, during the normal lecture break. Contrary to the stereotype of CS students, participation was high, and the students enjoyed these Fit-Breaks more than alternative break activities. This small injection of physical activity also had a measurable impact on the students' overall satisfaction with life, and may have had positive impacts on stress, retention, and academic performance as well as improved student perception, especially in areas that are traditionally problematic for female computer science students. 
 Fit-Breaks are low-cost, easy to replicate, and enjoyable exercises. Instead of sitting quietly for ten minutes staring at a phone; stretching, moving, and getting a short burst of physical activity has a positive benefit for students. And the good news is: they actually enjoy it.
Natural Language Processing and Hindi Language

Natural Language Processing (NLP) is the most important field of computer science which deals with human language and computers. In India, most of the people live in the rural areas, so they have the problem of understanding English language. To address this issue, we discussed here, about various factors which affect Hindi natural language processing. In this paper, a framework for information retrieval in Hindi is also proposed by authors. This framework is based on automatically inducing word sense using graph based method for all open class words present in the intended query. Till now researchers have worked for noun sense only, but here we expanded the framework for all open class words i.e. noun, verb, adverb and adjective.
A lane-departure identification based on LBPE, Hough transform, and linear regression

This paper presents a lane-departure identification (LDI) system of a traveling vehicle on a structured road with lane marks. As is the case with modified version of the previous EDFbased LDI approach [J.W. Lee, A machine vision system for lane-departure detection, CVIU 86 (2002) 52–78], the new system increases the number of lane-related parameters and introduces departure ratios to determine the instant of lane departure and a linear regression (LR) to minimize wrong decisions due to noise effects. To enhance the robustness of LDI, we conceive of a lane boundary pixel extractor (LBPE) capable of extracting pixels expected to be on lane boundaries. Then, the Hough transform utilizes the pixels from the LBPE to provide the lane-related parameters such as an orientation and a location parameter. The fundamental idea of the proposed LDI is based on an observation that the ratios of orientations and location parameters of leftand right-lane boundaries are equal to one as far as the optical axis of a camera mounted on a vehicle is coincident with the center of lane. The ratios enable the lanerelated parameters and the symmetrical property of both lane boundaries to be connected. In addition, the LR of the lane-related parameters of a series of successive images plays the role of determining the trend of a vehicle s traveling direction and the error of the LR is used to avoid a wrong LDI. We show the efficiency of the proposed LDI system with some real images.  Corresponding author.
On the Extraction, Ordering, and Usage of Landmarks in Planning

Many known planning tasks have inherent constraints concerning the best order in which to achieve the goals. A number of research efforts have been made to detect such constraints and use them for guiding search, in the hope to speed up the planning process. We go beyond the previous approaches by defining ordering constraints not only over the (top level) goals, but also over the sub-goals that will arise during planning. Landmarks are facts that must be true at some point in every valid solution plan. We show how such landmarks can be found, how their inherent ordering constraints can be approximated, and how this information can be used to decompose a given planning task into several smaller sub-tasks. Our methodology is completely domainand planner-independent. The implementation demonstrates that the approach can yield significant performance improvements in both heuristic forward search and GRAPHPLAN-style planning.
Novel therapies for immune-mediated inflammatory diseases: What can we learn from their use in rheumatoid arthritis, spondyloarthritis, systemic lupus erythematosus, psoriasis, Crohn's disease and ulcerative colitis?

The past three decades have witnessed remarkable advances in our ability to target specific elements of the immune and inflammatory response, fuelled by advances in both biotechnology and disease knowledge. As well as providing superior treatments for immune-mediated inflammatory diseases (IMIDs), such therapies also offer unrivalled opportunities to study the underlying immunopathological basis of these conditions.In this review, we explore recent approaches to the treatment of IMIDs and the insights to pathobiology that they provide. We review novel biologic agents targeting the T-helper 17 axis, including therapies directed towards interleukin (IL)-17 (secukinumab, ixekizumab, bimekizumab), IL-17R (brodalumab), IL-12/23p40 (ustekinumab, briakinumab) and IL-23p19 (guselkumab, tildrakizumab, brazikumab, risankizumab, mirikizumab). We also present an overview of biologics active against type I and II interferons, including sifalumumab, rontalizumab, anifrolumab and fontolizumab. Emerging strategies to interfere with cellular adhesion processes involved in lymphocyte recruitment are discussed, including both integrin blockade (natalizumab, vedolizumab, etrolizumab) and sphingosine-1-phosphate receptor inhibition (fingolimod, ozanimod). We summarise the development and recent application of Janus kinase (JAK) inhibitors in the treatment of IMIDs, including first-generation pan-JAK inhibitors (tofacitinib, baricitinib, ruxolitinib, peficitinib) and second-generation selective JAK inhibitors (decernotinib, filgotinib, upadacitinib). New biologics targeting B-cells (including ocrelizumab, veltuzumab, tabalumab and atacicept) and the development of novel strategies for regulatory T-cell modulation (including low-dose IL-2 therapy and Tregitopes) are also discussed. Finally, we explore recent biotechnological advances such as the development of bispecific antibodies (ABT-122, COVA322), and their application to the treatment of IMIDs.
Deep Self-Organizing Map for visual classification

We proposed a Deep Self-Organizing Map (DSOM) algorithm which is completely different from the existing multi-layers SOM algorithms, such as SOINN. It consists of layers of alternating self-organizing map and sampling operator. The self-organizing layer is made up of certain numbers of SOMs, with each map only looking at a local region block on its input. The winning neuron's index value from every SOM in self-organizing layer is then organized in the sampling layer to generate another 2D map, which could then be fed to a second self-organizing layer. In this way, local information is gathered together, forming more global information in higher layers. The construction method of the DSOM is unique and will be introduced in this paper. Experiments were carried out to discuss how the DSOM architecture parameters affect the performance. We evaluate our proposed DSOM on MNIST and CASIA-HWDB1.1 dataset. Experimental results show that DSOM outperforms the original supervised SOM by 7:17% on MNIST and 7:25% on CASIA-HWDB1.1.
Efficient Filtering of XML Documents for Selective Dissemination of Information

Information Dissemination applications are gaining increasing popularity due to dramatic improvements in communications bandwidth and ubiquity. The sheer volume of data available necessitates the use of selective approaches to dissemination in order to avoid overwhelming users with unnecessaryinformation. Existing mechanisms for selective dissemination typically rely on simple keyword matching or “bag of words” information retrieval techniques. The advent of XML as a standard for information exchangeand the development of query languages for XML data enables the development of more sophisticated filtering mechanisms that take structure information into account. We have developed several index organizations and search algorithms for performing efficient filtering of XML documents for large-scale information dissemination systems. In this paper we describe these techniques and examine their performance across a range of document, workload, and scale scenarios.
Importance of Computer Assisted Teaching & Learning Methods for Chemistry

Understanding the basic concepts of chemistry is very important for the students of secondary school level and university level. The Computer Assisted Teaching and Learning (CATL) methods are marked by the usage of computers in teaching and learning processes. Usage of WORD, EXCEL, POWERPOINT, ACCESS, PHOTOSHOP etc., as well as the use of specialized packages such as CHEMDRAW, SCIFINDER etc., can be worth mentioning. The role of internet in feeding the thirst of students is comparably far better than the classroom teaching. By the use of CATL methods, students can acquire high quality of mental models.