nils-herrmann/clean_scirepeval huggingface dataset:
Oscillatory dynamics in a bacterial cross protection mutualism
Venue: Proceedings of the National Academy of Sciences

Enzymatic deactivation of antibiotics is a cooperative behavior that can allow resistant cells to protect sensitive cells from antibiotics. The prevalence of this mechanism of antibiotic resistance in clinical isolates and in soil bacteria makes it important both clinically and ecologically. Here, we demonstrate experimentally that two populations of resistant bacteria can form a cross protection mutualism in a two drug environment, allowing the coculture to survive high antibiotic concentrations at which neither of the two strains can survive alone. Moreover, we find that daily growth dilution cycles result in large oscillations in the relative abundances of the two strains, thus demonstrating that mutualisms can display striking dynamical behavior. Cooperation between microbes can enable microbial communities to survive in harsh environments. Enzymatic deactivation of antibiotics, a common mechanism of antibiotic resistance in bacteria, is a cooperative behavior that can allow resistant cells to protect sensitive cells from antibiotics. Understanding how bacterial populations survive antibiotic exposure is important both clinically and ecologically, yet the implications of cooperative antibiotic deactivation on the population and evolutionary dynamics remain poorly understood, particularly in the presence of more than one antibiotic. Here, we show that two Escherichia coli strains can form an effective cross protection mutualism, protecting each other in the presence of two antibiotics (ampicillin and chloramphenicol) so that the coculture can survive in antibiotic concentrations that inhibit growth of either strain alone. Moreover, we find that daily dilutions of the coculture lead to large oscillations in the relative abundance of the two strains, with the ratio of abundances varying by nearly four orders of magnitude over the course of the 3 day period of the oscillation. At modest antibiotic concentrations, the mutualistic behavior enables long term survival of the oscillating populations; however, at higher antibiotic concentrations, the oscillations destabilize the population, eventually leading to collapse. The two strains form a successful cross protection mutualism without a period of coevolution, suggesting that similar mutualisms may arise during antibiotic treatment and in natural environments such as the soil.
Richter syndrome: pathogenesis and management.
Venue: Seminars in oncology

Richter syndrome (RS) is the development of an aggressive lymphoma in patients with a previous or concomitant diagnosis of chronic lymphocytic leukemia (CLL) The incidence rate RS is ~0.5% per year of observation. Two biomarkers (NOTCH1 mutations and subset 8 configuration of the B cell receptor) may help identifying CLL patients at risk of RS to be considered for close monitoring and a careful biopsy policy. In the presence of clinical features suspicious of RS, diagnosis of transformation and choice of the site of biopsy may take advantage of fluorine 18 fluorodeoxyglucose (18)FDG) positron emission tomography (PET)/computed tomography (CT) Molecular lesions of regulators of tumor suppression (TP53) cell cycle (CDKN2A) and cell proliferation (NOTCH1, MYC) overall account for ~90% of RS and may be responsible for the aggressive clinical phenotype observed in this disease because of the combined effect of chemoresistance and rapid disease kinetics. The prognosis of RS is generally highly unfavorable. However, the pattern of survival is not homogeneous and the most important prognostic factor is the clonal relationship between the CLL and the aggressive lymphoma clones. Rituximab containing polychemotherapy represents the backbone for induction treatment in RS. Younger patients who respond to induction therapy should be offered stem cell transplant (SCT) to prolong survival.
HMF: Heatmap and WiFi Fingerprint Based Indoor Localization with Building Layout Consideration
Venue: 2016 IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS)

In recent years, WiFi fingerprint based localization has received much attention due to its deployment practicability. Although existing works show WiFi fingerprinting can achieve good localization accuracy, the experiments were conducted under their own testbeds within a small area and a short period. In this work, we investigate the impact of different indoor environmental factors, such as temporal and spatial similarity, on the performance of WiFi fingerprinting. We find that, WiFi fingerprinting is highly environment sensitive. In an open space, it is quite challenging to find spatially varying but temporally stable signatures for adjacent reference locations. To address this issue, we propose a heatmap based WiFi fingerprinting (called HMF) by utilizing layout construction as an additional input to improve WiFi fingerprint localization in open space environment. Our experimental results show, HMF can improve existing WiFi fingerprinting schemes like Radar and Horus by 28% and 80% in moderately open space, e.g. a wide corridor.
Application of Image Analysis Techniques to Develop a Quality Control Tool for Automated Optimum Binder Content Determination of Open Graded Friction Course Mixtures

In some transportation agencies, including the Florida Department of Transportation (DOT) open graded friction course (OGFC) mixtures are designed by estimating the optimum binder content (OBC) The estimation is based on visual inspection of the asphalt binder draindown (ABD) configuration of three OGFC samples placed on pie plates with predetermined trial asphalt binder contents (ACs) The inspection of the ABD configuration is performed by trained and experienced technicians who determine the OBC with perceptive interpolation or extrapolation based on the known AC values of the above samples. To eliminate the human subjectivity involved in this method, the authors first developed an automated image processing based method for prediction of the OBC by using digital images of the pie plate specimens (PPSs) In the extended research effort reported in this paper, a quality control tool (QCT) was developed for the aforementioned automated method to enhance its reliability when implemented by other agencies and contractors. The QCT was developed with three quality control imaging parameters (QCIPs) orientation, spatial distribution, and segregation of ABD configuration of PPS images. Then, the above QCIPs were evaluated from PPS images of a variety of mixture designs produced with the Florida DOT visual method. The statistical and computer generated results indicated that the selected QCIPs are adequate for the formulation of quality control criteria for PPS production. The authors believe that the developed QCT will enhance the reliability and accuracy of the automated OBC estimation image processing based method.
Clinical instrumentation and applications of Raman spectroscopy.
Venue: Chemical Society reviews

Clinical diagnostic devices provide new sources of information that give insight about the state of health which can then be used to manage patient care. These tools can be as simple as an otoscope to better visualize the ear canal or as complex as a wireless capsule endoscope to monitor the gastrointestinal tract. It is with tools such as these that medical practitioners can determine when a patient is healthy and to make an appropriate diagnosis when he/she is not. The goal of diagnostic medicine then is to efficiently determine the presence and cause of disease in order to provide the most appropriate intervention. The earliest form of medical diagnostics relied on the eye direct visual observation of the interaction of light with the sample. This technique was espoused by Hippocrates in his 5th century BCE work Epidemics, in which the pallor of a patient's skin and the coloring of the bodily fluids could be indicative of health. In the last hundred years, medical diagnosis has moved from relying on visual inspection to relying on numerous technological tools that are based on various types of interaction of the sample with different types of energy light, ultrasound, radio waves, X rays etc. Modern advances in science and technology have depended on enhancing technologies for the detection of these interactions for improved visualization of human health. Optical methods have been focused on providing this information in the micron to millimeter scale while ultrasound, X ray, and radio waves have been key in aiding in the millimeter to centimeter scale. While a few optical technologies have achieved the status of medical instruments, many remain in the research and development phase despite persistent efforts by many researchers in the translation of these methods for clinical care. Of these, Raman spectroscopy has been described as a sensitive method that can provide biochemical information about tissue state while maintaining the capability of delivering this information in real time, non invasively, and in an automated manner. This review presents the various instrumentation considerations relevant to the clinical implementation of Raman spectroscopy and reviews a subset of interesting applications that have successfully demonstrated the efficacy of this technique for clinical diagnostics and monitoring in large (n 50) in vivo human studies.
Aspect Level Sentiment Classification with Deep Memory Network
Venue: EMNLP

We introduce a deep memory network for aspect level sentiment classification. Unlike feature based SVM and sequential neural models such as LSTM, this approach explicitly captures the importance of each context word when inferring the sentiment polarity of an aspect. Such importance degree and text representation are calculated with multiple computational layers, each of which is a neural attention model over an external memory. Experiments on laptop and restaurant datasets demonstrate that our approach performs comparable to state of art feature based SVM system, and substantially better than LSTM and attention based LSTM architectures. On both datasets we show that multiple computational layers could improve the performance. Moreover, our approach is also fast. The deep memory network with 9 layers is 15 times faster than LSTM with a CPU implementation.
Neuromodulated Spike Timing Dependent Plasticity, and Theory of Three Factor Learning Rules
Venue: Front. Neural Circuits

Classical Hebbian learning puts the emphasis on joint pre and postsynaptic activity, but neglects the potential role of neuromodulators. Since neuromodulators convey information about novelty or reward, the influence of neuromodulators on synaptic plasticity is useful not just for action learning in classical conditioning, but also to decide "when" to create new memories in response to a flow of sensory stimuli. In this review, we focus on timing requirements for pre and postsynaptic activity in conjunction with one or several phasic neuromodulatory signals. While the emphasis of the text is on conceptual models and mathematical theories, we also discuss some experimental evidence for neuromodulation of Spike Timing Dependent Plasticity. We highlight the importance of synaptic mechanisms in bridging the temporal gap between sensory stimulation and neuromodulatory signals, and develop a framework for a class of neo Hebbian three factor learning rules that depend on presynaptic activity, postsynaptic variables as well as the influence of neuromodulators.
Full Range Soft Switching Isolated Buck Boost Converters With Integrated Interleaved Boost Converter and Phase Shifted Control
Venue: IEEE Transactions on Power Electronics

A new method for deriving isolated buck boost (IBB) converter with single stage power conversion is proposed in this paper and novel IBB converters based on high frequency bridgeless interleaved boost rectifiers are presented. The semiconductors, conduction losses, and switching losses are reduced significantly by integrating the interleaved boost converters into the full bridge diode rectifier. Various high frequency bridgeless boost rectifiers are harvested based on different types of interleaved boost converters, including the conventional boost converter and high step up boost converters with voltage multiplier and coupled inductor. The full bridge IBB converter with voltage multiplier is analyzed in detail. The voltage multiplier helps to enhance the voltage gain and reduce the voltage stresses of the semiconductors in the rectification circuit. Hence, a transformer with reduced turns ratio and parasitic parameters, and low voltage rated MOSFETs and diodes with better switching and conduction performances can be applied to improve the efficiency. Moreover, optimized phase shift modulation strategy is applied to the full bridge IBB converter to achieve isolated buck and boost conversion. What's more, soft switching performance of all of the active switches and diodes within the whole operating range is achieved. A 380 V output prototype is fabricated to verify the effectiveness of the proposed IBB converters and its control strategies.
A soft switching interleaved boost DC/DC converter
Venue: 2016 19th International Conference on Electrical Machines and Systems (ICEMS)

A novel soft switching interleaved boost dc/dc converter is proposed in this paper. The proposed converter combines the conventional pulse width modulation technique, soft commutation technique to promote the circuit performance. The proposed converter uses two boost dc/dc converters with interleaved operation to increase the output power and reduce the input ripple current and output ripple voltage. Comparison with conventional interleaved boost dc/dc converter, the proposed converter has not additional voltage stress on main switches. A soft switching auxiliary circuit is configured in the presented dc/dc converter to provide the soft switching function on main switches and auxiliary switches and improve the problem of switching losses and EMI. A prototype has been implemented in laboratory to verify circuit theory.
The Cost of Sharing: The Effect of Sharing Inclination on Information Overload
Venue: ECIS

Current research on social media emphasizes that sharing information comes with great benefits to the individual who shares. In this paper, we adopt a different perspective by arguing that individuals with a high inclination to share information through social media also incur substantial cognitive costs. In particular, we hypothesize that during two phases of the sharing process, information appraisal and asynchronous interactivity, the sharer is confronted with information processing requirements that considerably draw on his or her limited cognitive capacity and thus increase the likelihood of experiencing information overload. We furthermore argue that this effect is more pronounced for individuals with a high compared to low need for cognition because they feel particularly motivated to process information. Our hypotheses are supported by a large survey generated dataset (n=30,392) from six countries. We additionally find a positive direct effect of need for cognition on information overload. We discuss contributions to conversations on information sharing, information overload, and need for cognition research in the context of social media and we highlight managerial implications of our findings.
Report from the Information Overload and Underload Workgroup

The duality of information overload and underload is a defining issue of our age. Scholarly information is abundant but not universally accessible to all scholars and learners, thereby hindering or prohibiting equitable engagement in ongoing scholarly conversations. Access is a core aspect of the issue of overload and underload both access to research materials and access to venues where one can contribute to the scholarly corpus but it is not the only aspect. Our group agreed that the problem of overload is preferable to that of underload; however, the dual nature of the issue makes that conclusion more nuanced, dynamic, and situational. In this report we explore the many factors and causes of information overload and underload and also develop ideas for solutions. A summary of the issues is provided. OSI2016 Workgroup Question Information underload occurs when we don't have access to the information we need (for a variety of reasons, including cost) researchers based at smaller institutions and in the global periphery, policymakers, and the general public, particularly with regard to medical research. Overload occurs when we can access everything but are simply overwhelmed by the torrent of information available (not all of which is equally valuable) Are these issues two sides of the same coin? In both cases, how can we work together to figure out how to get people the information they need? Can we? How widespread are these issues? What are the economic and research consequences of information underload and overload?
Information Overload and Underload

Information underload occurs when we donAC/a!aC/t have access to the information we need (for a variety of reasons, including cost) AC/a!aresearchers based at smaller institutions and in the global periphery, policymakers, and the general public, particularly with regard to medical research. Overload occurs when we can access everything but are simply overwhelmed by the torrent of information available (not all of which is equally valuable) Are these issues two sides of the same coin? In both cases, how can we work together to figure out how to get people the information they need? Can we? How widespread are these issues? What are the economic and research consequences of information underload and overload?
Big five personality trait and internet addiction: A meta analytic review
Venue: Comput. Hum. Behav.

Internet use has been increasing exponentially day by day depending on technological developments. In connection with this, excessive internet use leads to unhealthy internet use named as internet addiction. Recently, it is remarkable that internet addiction and big five personality traits are closely related. In this framework, the aim of this research is to investigate relations between internet addiction and big five personality traits. For this purpose, meta analysis method was used in this research. In line with the aim of the research, 12 studies were included in the meta analysis and 13 effect sizes were calculated from these researches. As a result of meta analysis, it was found that all big five personality traits had a meaningful relation with internet addiction. In this context, it was determined that neuroticism was positively related with internet addiction whereas openness to new experiences, conscientiousness, extraversion and agreeableness were negatively related with it. In consequence, it is considered that big five personality traits are an important factor in terms of internet addiction. Openness negatively associated with internet addiction.Conscientiousness negatively associated with internet addiction.Extraversion negatively associated with internet addiction.Agreeableness negatively associated with internet addiction.Neuroticism positively associated with internet addiction.
Hot flushes and night sweats symptom profiles over a 17 year period in mid aged women: The role of hysterectomy with ovarian conservation.
Venue: Maturitas

There is limited research on hot flushes and night sweats in women with a hysterectomy with ovarian conservation. We aimed to describe the patterns of these symptoms in a cohort of Australian women and to investigate the relationship between distinct symptom patterns and hysterectomy status.  Repeated measures latent class analysis (LCA) was used to identify hot flushes and night sweats symptom patterns across seven surveys (over 17 years) in the mid cohort of the Australian Longitudinal Study on Women's Health. Multinomial logistic regression was used to assess the associations of the symptom patterns in women with a hysterectomy with ovarian conservation (n=1129) versus women without a hysterectomy (n=4977)  A higher proportion of women with a hysterectomy than of those without experienced a constant pattern of hot flushes (15% versus 30% and night sweats (9% versus 19% Women with a hysterectomy had higher odds of constant hot flushes versus minimal hot flushes (OR=1.97, 95% CI: 1.64, 2.35) and constant versus minimal night sweats (OR=2.09, 95% CI: 1.70, 2.55) Smoking, a 'lower level of education to non professional occupation' pathway and body mass index (BMI) patterns of 'always obese' and 'increasingly obese' were also associated with a higher risk of constant symptoms.  Women who have a hysterectomy (with ovarian conservation) have a higher risk of hot flushes and night sweats that persist over an extended period.
Energy Efficiency and Spectrum Efficiency of Multihop Device to Device Communications Underlaying Cellular Networks
Venue: IEEE Transactions on Vehicular Technology

Device to device (D2D) communications are usually considered to be two user equipment units (UEs) communicating directly without going through the central base station (BS) In fact, they can be further broadened to multihop D2D communications in which a UE may help other UEs communicate with each other or assist other UEs to communicate with the BS. In this paper, we investigate a scenario of multihop D2D communications where one UE may help other two UEs to exchange information with a two time slot physical layer network coding scheme. We analyze the average energy efficiency and spectral efficiency of multihop D2D communications under Rayleigh fading channels and get close analytical approximations based on Taylor series expansion. Comparisons with direct D2D communications and traditional cellular communications through BS are provided. The optimal UE transmission powers of these three different modes to maximize the energy efficiency are also derived.