nils-herrmann/clean_scirepeval huggingface dataset:
Drive current boosting of n-type tunnel FET with strained SiGe layer at source

Though silicon tunnel field effect transistor (TFET) has attracted attention for sub-60mV/decade subthreshold swing and very small OFF current (IOFF), its practical application is questionable due to low ON current (ION) and complicated fabrication process steps. In this paper, a new n-type classical-MOSFET-alike tunnel FET architecture is proposed, which offers sub-60mV/decade subthreshold swing along with a significant improvement in ION. The enhancement in ION is achieved by introducing a thin strained SiGe layer on top of the silicon source. Through 2D simulations it is observed that the device is nearly free from short channel effect (SCE) and its immunity towards drain induced barrier lowering (DIBL) increases with increasing germanium mole fraction. It is also found that the body bias does not change the drive current but after body current gets affected. An ION of 0:58mA=mm and a minimum average subthreshold swing of 13mV/decade is achieved for 100 nm channel length device with 1.2V supply voltage and 0.7 Ge mole fraction, while maintaining the IOFF in fA range.
Minimum Interference Channel Assignment in Multiradio Wireless Mesh Networks

In this paper, we consider multihop wireless mesh networks, where each router node is equipped with multiple radio interfaces, and multiple channels are available for communication. We address the problem of assigning channels to communication links in the network with the objective of minimizing the overall network interference. Since the number of radios on any node can be less than the number of available channels, the channel assignment must obey the constraint that the number of different channels assigned to the links incident on any node is at most the number of radio interfaces on that node. The above optimization problem is known to be NP-hard. We design centralized and distributed algorithms for the above channel assignment problem. To evaluate the quality of the solutions obtained by our algorithms, we develop a semidefinite program and a linear program formulation of our optimization problem to obtain lower bounds on overall network interference. Empirical evaluations on randomly generated network graphs show that our algorithms perform close to the above established lower bounds, with the difference diminishing rapidly with increase in number of radios. Also, ns-2 simulations, as well as experimental studies on testbed, demonstrate the performance potential of our channel assignment algorithms in 802.11-based multiradio mesh networks.
Revisiting the role of language in spatial cognition: Categorical perception of spatial relations in English and Korean speakers.

The spatial relation of support has been regarded as universally privileged in nonlinguistic cognition and immune to the influence of language. English, but not Korean, obligatorily distinguishes support from nonsupport via basic spatial terms. Despite this linguistic difference, previous research suggests that English and Korean speakers show comparable nonlinguistic sensitivity to the support/nonsupport distinction. Here, using a paradigm previously found to elicit cross-language differences in color discrimination, we provide evidence for a difference in sensitivity to support/nonsupport between native English speakers and native Korean speakers who were late English learners and tested in a context that privileged Korean. Whereas the former group showed categorical perception (CP) when discriminating spatial scenes capturing the support/nonsupport distinction, the latter did not. An additional group of native Korean speakers-relatively early English learners tested in an English-salient context-patterned with the native English speakers in showing CP for support/nonsupport. These findings suggest that obligatory marking of support/nonsupport in one's native language can affect nonlinguistic sensitivity to this distinction, contra earlier findings, but that such sensitivity may also depend on aspects of language background and the immediate linguistic context.
A new formula for normal tissue complication probability (NTCP) as a function of equivalent uniform dose (EUD).

To facilitate the use of biological outcome modeling for treatment planning, an exponential function is introduced as a simpler equivalent to the Lyman formula for calculating normal tissue complication probability (NTCP). The single parameter of the exponential function is chosen to reproduce the Lyman calculation to within approximately 0.3%, and thus enable easy conversion of data contained in empirical fits of Lyman parameters for organs at risk (OARs). Organ parameters for the new formula are given in terms of Lyman model m and TD(50), and conversely m and TD(50) are expressed in terms of the parameters of the new equation. The role of the Lyman volume-effect parameter n is unchanged from its role in the Lyman model. For a non-homogeneously irradiated OAR, an equation relates d(ref), n, v(eff) and the Niemierko equivalent uniform dose (EUD), where d(ref) and v(eff) are the reference dose and effective fractional volume of the Kutcher-Burman reduction algorithm (i.e. the LKB model). It follows in the LKB model that uniform EUD irradiation of an OAR results in the same NTCP as the original non-homogeneous distribution. The NTCP equation is therefore represented as a function of EUD. The inverse equation expresses EUD as a function of NTCP and is used to generate a table of EUD versus normal tissue complication probability for the Emami-Burman parameter fits as well as for OAR parameter sets from more recent data.
Systematic Abstraction of Abstract Machines

We describe a derivational approach to abstract interpretation that yields novel and transparently sound static analyses when applied to well-established abstract machines for higherorder and imperative programming languages. To demonstrate the technique and support our claim, we transform the CEK machine of Felleisen and Friedman (Proc. of the 14th ACM SIGACT-SIGPLAN Symp. Prin. Program.  1987, pp. 314–325), a lazy variant of Krivine’s machine (Higher-Order Symb.  2007, , and the stackinspecting CM machine of Clements and Felleisen ( 2004, pp. 1029–1052) into abstract interpretations of themselves. The resulting analyses bound temporal ordering of program events; predict return-flow and stack-inspection behavior; and approximate the flow and evaluation of by-need parameters. For all of these machines, we find that a series of well-known concrete machine refactorings, plus a technique of store-allocated continuations, leads to machines that abstract into static analyses simply by bounding their stores. These machines are parameterized by allocation functions that tune performance and precision and substantially expand the space of analyses that this framework can represent. We demonstrate that the technique scales up uniformly to allow static analysis of realistic language features, including tail calls, conditionals, mutation, exceptions, first-class continuations, and even garbage collection. In order to close the gap between formalism and implementation, we provide translations of the mathematics as running Haskell code for the initial development of our method.
Holistic Indexing in Main-memory Column-stores

Great database systems performance relies heavily on index tuning, i.e., creating and utilizing the best indices depending on the workload. However, the complexity of the index tuning process has dramatically increased in recent years due to ad-hoc workloads and shortage of time and system resources to invest in tuning.
 This paper introduces holistic indexing, a new approach to automated index tuning in dynamic environments. Holistic indexing requires zero set-up and tuning effort, relying on adaptive index creation as a side-effect of query processing. Indices are created incrementally and partially;they are continuously refined as we process more and more queries. Holistic indexing takes the state-of-the-art adaptive indexing ideas a big step further by introducing the notion of a system which never stops refining the index space, taking educated decisions about which index we should incrementally refine next based on continuous knowledge acquisition about the running workload and resource utilization. When the system detects idle CPU cycles, it utilizes those extra cycles by refining the adaptive indices which are most likely to bring a benefit for future queries. Such idle CPU cycles occur when the system cannot exploit all available cores up to 100%, i.e., either because the workload is not enough to saturate the CPUs or because the current tasks performed for query processing are not easy to parallelize to the point where all available CPU power is exploited.
 In this paper, we present the design of holistic indexing for column-oriented database architectures and we discuss a detailed analysis against parallel versions of state-of-the-art indexing and adaptive indexing approaches. Holistic indexing is implemented in an open-source column-store DBMS. Our detailed experiments on both synthetic and standard benchmarks (TPC-H) and workloads (SkyServer) demonstrate that holistic indexing brings significant performance gains by being able to continuously refine the physical design in parallel to query processing, exploiting any idle CPU resources.
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data

We describe a Bayesian approach for learning Bayesian networks from a combination of prior knowledge and statistical data. First and foremost, we develop a methodology for assessing informative priors needed for learning. Our approach is derived from a set of assumptions made previously as well as the assumption of likelihood equivalence, which says that data should not help to discriminate network structures that represent the same assertions of conditional independence. We show that likelihood equivalence when combined with previously made assumptions implies that the user's priors for network parameters can be encoded in a single Bayesian network for the next case to be seen—a prior network—and a single measure of confidence for that network. Second, using these priors, we show how to compute the relative posterior probabilities of network structures given data. Third, we describe search methods for identifying network structures with high posterior probabilities. We describe polynomial algorithms for finding the highest-scoring network structures in the special case where every node has at most k = 1 parent. For the general case (k > 1), which is NP-hard, we review heuristic search algorithms including local search, iterative local search, and simulated annealing. Finally, we describe a methodology for evaluating Bayesian-network learning algorithms, and apply this approach to a comparison of various approaches.
Forecasting Fine-Grained Air Quality Based on Big Data

In this paper, we forecast the reading of an air quality monitoring station over the next 48 hours, using a data-driven method that considers current meteorological data, weather forecasts, and air quality data of the station and that of other stations within a few hundred kilometers. Our predictive model is comprised of four major components: 1) a linear regression-based temporal predictor to model the local factors of air quality, 2) a neural network-based spatial predictor to model global factors, 3) a dynamic aggregator combining the predictions of the spatial and temporal predictors according to meteorological data, and 4) an inflection predictor to capture sudden changes in air quality. We evaluate our model with data from 43 cities in China, surpassing the results of multiple baseline methods. We have deployed a system with the Chinese Ministry of Environmental Protection, providing 48-hour fine-grained air quality forecasts for four major Chinese cities every hour. The forecast function is also enabled on Microsoft Bing Map and MS cloud platform Azure. Our technology is general and can be applied globally for other cities.
Chronic pain and the emotional brain: specific brain activity associated with spontaneous fluctuations of intensity of chronic back pain.

Living with unrelenting pain (chronic pain) is maladaptive and is thought to be associated with physiological and psychological modifications, yet there is a lack of knowledge regarding brain elements involved in such conditions. Here, we identify brain regions involved in spontaneous pain of chronic back pain (CBP) in two separate groups of patients (n = 13 and n = 11), and contrast brain activity between spontaneous pain and thermal pain (CBP and healthy subjects, n = 11 each). Continuous ratings of fluctuations of spontaneous pain during functional magnetic resonance imaging were separated into two components: high sustained pain and increasing pain. Sustained high pain of CBP resulted in increased activity in the medial prefrontal cortex (mPFC; including rostral anterior cingulate). This mPFC activity was strongly related to intensity of CBP, and the region is known to be involved in negative emotions, response conflict, and detection of unfavorable outcomes, especially in relation to the self. In contrast, the increasing phase of CBP transiently activated brain regions commonly observed for acute pain, best exemplified by the insula, which tightly reflected duration of CBP. When spontaneous pain of CBP was contrasted to thermal stimulation, we observe a double-dissociation between mPFC and insula with the former correlating only to intensity of spontaneous pain and the latter correlating only to pain intensity for thermal stimulation. These findings suggest that subjective spontaneous pain of CBP involves specific spatiotemporal neuronal mechanisms, distinct from those observed for acute experimental pain, implicating a salient role for emotional brain concerning the self.
Internet Addiction: Metasynthesis of 1996-2006 Quantitative Research

This study reports the results of a meta-analysis of empirical studies on Internet addiction published in academic journals for the period 1996-2006. The analysis showed that previous studies have utilized inconsistent criteria to define Internet addicts, applied recruiting methods that may cause serious sampling bias, and examined data using primarily exploratory rather than confirmatory data analysis techniques to investigate the degree of association rather than causal relationships among variables. Recommendations are provided on how researchers can strengthen this growing field of research.
Learning and Enjoyment in Serious Gaming - Contradiction or Complement?

Research has mainly neglected to examine if the possible antagonism of play/games and seriousness affects the educational potential of serious gaming. This article follows a microsociological approach and treats play and seriousness as different social frames, with each being indicated by significant symbols and containing unique social rules, adequate behavior and typical consequences of action. It is assumed that due to the specific qualities of these frames, serious frames are perceived as more credible but less entertaining than playful frames – regardless of subject matter. Two empirical studies were conducted to test these hypotheses. Results partially confirm expectations, but effects are not as strong as assumed and sometimes seem to be moderated by further variables, such as gender and attitudes. Overall, this article demonstrates that the educational potential of serious gaming depends not only on media design, but also on social context and personal variables.
A Hybrid Heuristic for the Minimum Weight Vertex Cover Problem

Given an undirected graph with weights associated with its vertices, the minimum weight vertex cover problem seeks a subset of vertices with minimum sum of weights such that each edge of the graph has at least one endpoint belonging to the subset. In this paper, we propose a hybrid approach, combining a steady-state genetic algorithm and a greedy heuristic, for the minimum weight vertex cover problem. The genetic algorithm generates vertex cover, which is then reduced to minimal weight vertex cover by the heuristic. We have evaluated the performance of our algorithm on several test problems of varying sizes. Computational results show the effectiveness of our approach in solving the minimum weight vertex cover problem.
The Effect of Commiphora molmol (Myrrh) in Treatment of Trichomoniasis vaginalis infection

Trichomoniasis vaginalis is now an important worldwide health problem. Metronidazole has so far been used in treatment, but the metronidazole-resistant strains and unpleasant adverse effects have been de-veloped. Myrrh is one of the oldest known medicinal plants used by the ancient Egyptians for medical purposes and for mummification. Commiphora molmol (Myrrh) proved safe for male reproductive organ which is the main habitat of T. vaginalis and this study aims to evaluate the efficacy of the herbal against T. vaginalis in females.



In the present study, 33 metronidazole-resistant T. vaginalis females were treated with a combined course of metronidazole and tinidazole. Those still resistant to the combined treatment were given C. molmol. Also, natural plant extract purified from pomegranate (Punica granatum, Roman) was in-vitro investigated for its efficacy against T. vaginalis on Diamond media.



The anti-T. vaginalis activity of both P. granatum (in-vitro) and C. molmol (in-vivo) extracts gave promis-ing results.



The anti-T. vaginalis activity of P. granatum and C. molmol showed promising results indicating to sources of new anti-Ttrichomonas agents.
9.8 Receiver with integrated magnetic-free N-path-filter-based non-reciprocal circulator and baseband self-interference cancellation for full-duplex wireless

Full-duplex (FD) is an emergent wireless communication paradigm where the transmitter (TX) and the receiver (RX) operate at the same time and at the same frequency. The fundamental challenge with FD is the tremendous amount of TX self-interference (SI) at the RX. Low-power applications relax FD system requirements , but an FD system with -6dBm transmit power, 10MHz signal bandwidth and 12dB NF budget still requires 86dB of SI suppression to reach the -92dBm noise floor. Recent research has focused on techniques for integrated self-interference cancellation (SIC) in FD receivers [1-3]. Open challenges include achieving the challenging levels of SIC through multi-domain cancellation, and low-loss shared-antenna (ANT) interfaces with high TX-to-RX isolation. Sharedantenna interfaces enable compact form factor, translate easily to MIMO, and ease system design through channel reciprocity.
Obesity stigma: important considerations for public health.

Stigma and discrimination toward obese persons are pervasive and pose numerous consequences for their psychological and physical health. Despite decades of science documenting weight stigma, its public health implications are widely ignored. Instead, obese persons are blamed for their weight, with common perceptions that weight stigmatization is justifiable and may motivate individuals to adopt healthier behaviors. We examine evidence to address these assumptions and discuss their public health implications. On the basis of current findings, we propose that weight stigma is not a beneficial public health tool for reducing obesity. Rather, stigmatization of obese individuals threatens health, generates health disparities, and interferes with effective obesity intervention efforts. These findings highlight weight stigma as both a social justice issue and a priority for public health.
Clinical parameters in male genital lichen sclerosus: a case series of 329 patients.

The dermatological aspects of male genital lichen sclerosus (MGLSc) have not received much prominence in the literature. Sexual morbidity appears under-appreciated, the role of histology is unclear, the relative places of topical medical treatment and circumcision are not established, the prognosis for sexual function, urinary function and penis cancer is uncertain and the pathogenesis has not been specifically studied although autoimmunity (as in women) and HPV infection have been mooted.


To illuminate the above by analysing the clinical parameters of a large series of patients with MGLSc.


A total of 329 patients with a clinical diagnosis of MGLSc were identified retrospectively from a dermatology-centred multidisciplinary setting. Their clinical and histopathological features and outcomes have been abstracted from the records and analysed by simple descriptive statistics.


The collation and analysis of clinical data derived from the largest series of men with MGLSc ever studied from a dermatological perspective has been achieved. These data allow the conclusions below to be drawn.



  MGLSc is unequivocally a disease of the uncircumcised male; the adult peak is late in the fourth decade; dyspareunia is a common presenting complaint; non-specific histology requires careful interpretation; most men are either cured by topical treatment with ultrapotent steroid (50-60%) or by circumcision (>75%); effective and definitive management appears to abrogate the risk of developing penile squamous cell carcinoma; urinary contact is implicated in the pathogenesis of MGLSc; HPV infection and autoimmunity seem unimportant.
The Preventable Causes of Death in the United States: Comparative Risk Assessment of Dietary, Lifestyle, and Metabolic Risk Factors

Knowledge of the number of deaths caused by risk factors is needed for health policy and priority setting. Our aim was to estimate the mortality effects of the following 12 modifiable dietary, lifestyle, and metabolic risk factors in the United States (US) using consistent and comparable methods: high blood glucose, low-density lipoprotein (LDL) cholesterol, and blood pressure; overweight-obesity; high dietary trans fatty acids and salt; low dietary polyunsaturated fatty acids, omega-3 fatty acids (seafood), and fruits and vegetables; physical inactivity; alcohol use; and tobacco smoking.



We used data on risk factor exposures in the US population from nationally representative health surveys and disease-specific mortality statistics from the National Center for Health Statistics. We obtained the etiological effects of risk factors on disease-specific mortality, by age, from systematic reviews and meta-analyses of epidemiological studies that had adjusted (i) for major potential confounders, and (ii) where possible for regression dilution bias. We estimated the number of disease-specific deaths attributable to all non-optimal levels of each risk factor exposure, by age and sex. In 2005, tobacco smoking and high blood pressure were responsible for an estimated 467,000 (95% confidence interval [CI] 436,000-500,000) and 395,000 (372,000-414,000) deaths, accounting for about one in five or six deaths in US adults. Overweight-obesity (216,000; 188,000-237,000) and physical inactivity (191,000; 164,000-222,000) were each responsible for nearly 1 in 10 deaths. High dietary salt (102,000; 97,000-107,000), low dietary omega-3 fatty acids (84,000; 72,000-96,000), and high dietary trans fatty acids (82,000; 63,000-97,000) were the dietary risks with the largest mortality effects. Although 26,000 (23,000-40,000) deaths from ischemic heart disease, ischemic stroke, and diabetes were averted by current alcohol use, they were outweighed by 90,000 (88,000-94,000) deaths from other cardiovascular diseases, cancers, liver cirrhosis, pancreatitis, alcohol use disorders, road traffic and other injuries, and violence.



Smoking and high blood pressure, which both have effective interventions, are responsible for the largest number of deaths in the US. Other dietary, lifestyle, and metabolic risk factors for chronic diseases also cause a substantial number of deaths in the US.