nils-herrmann/clean_scirepeval huggingface dataset:
Connection-Oriented DNS to Improve Privacy and Security

The Domain Name System (DNS) seems ideal for connectionless UDP, yet this choice results in challenges of eavesdropping that compromises privacy, source-address spoofing that simplifies denial-of-service (DoS) attacks on the server and third parties, injection attacks that exploit fragmentation, and reply-size limits that constrain key sizes and policy choices. We propose T-DNS to address these problems. It uses TCP to smoothly support large payloads and to mitigate spoofing and amplification for DoS. T-DNS uses transport-layer security (TLS) to provide privacy from users to their DNS resolvers and optionally to authoritative servers. TCP and TLS are hardly novel, and expectations about DNS suggest connections will balloon client latency and overwhelm server with state. Our contribution is to show that T-DNS significantly improves security and privacy: TCP prevents denial-of-service (DoS) amplification against others, reduces the effects of DoS on the server, and simplifies policy choices about key size. TLS protects against eavesdroppers to the recursive resolver. Our second contribution is to show that with careful implementation choices, these benefits come at only modest cost: end-to-end latency from TLS to the recursive resolver is only about 9% slower when UDP is used to the authoritative server, and 22% slower with TCP to the authoritative. With diverse traces we show that connection reuse can be frequent (60 -- 95% for stub and recursive resolvers, although half that for authoritative servers), and after connection establishment, experiments show that TCP and TLS latency is equivalent to UDP. With conservative timeouts (20 s at authoritative servers and 60 s elsewhere) and estimated per-connection memory, we show that server memory requirements match current hardware: a large recursive resolver may have 24k active connections requiring about 3.6 GB additional RAM. Good performance requires key design and implementation decisions we identify: query pipelining, out-of-order responses, TCP fast-open and TLS connection resumption, and plausible timeouts.
Symbolic and Parametric Model Checking of Discrete-Time Markov Chains

We present a language-theoretic approach to symbolic model checking of PCTL over discrete-time Markov chains. The probability with which a path formula is satisfied is represented by a regular expression. A recursive evaluation of the regular expression yields an exact rational value when transition probabilities are rational, and rational functions when some probabilities are left unspecified as parameters of the system. This allows for parametric model checking by evaluating the regular expression for different parameter values, for instance, to study the influence of a lossy channel in the overall reliability of a randomized protocol.
Debrief in Emergency Departments to Improve Compassion Fatigue and Promote Resiliency.

The purpose of this case study was to describe compassion fatigue using one nurse's experience as an example and to present the process of Personal Reflective Debrief as an intervention to prevent compassion fatigue in emergency department (ED) nurses. Debriefing after adverse outcomes using a structured model has been used in health care as a nonthreatening and relatively low-cost way to discuss unanticipated outcomes, identify opportunities for improvement, and heal as a group. There are many methods of debrief tailored to specific timing around events, specific populations of health care workers, and amount of time for debriefing. Debrief with personal and group reflection will help develop insights that nurses may need to understand their own emotions and experiences, as well as to develop knowledge that can be used in subsequent situations. Regular engagement in a proactive scheduled Personal Reflective Debrief has been identified as a method of promoting resiliency in an environment where the realities of emergency nursing make compassion fatigue an imminent concern. Nurses working in the ED normally experience some level of stress because of high acuity patients and high patient volume; yet, repeated exposure puts them at risk for developing compassion fatigue. The Personal Reflective Debrief is one way emergency nurses can alleviate some of this caring-related stress and thereby become more resilient. Increasing nurses' resilience to workplace stress can counter compassion fatigue. The key is to provide planned, proactive resources to positively improve resiliency.
Network Science and Cybersecurity

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SERIES ( Statistics # 2005-05 ) Evaluating String Comparator Performance for Record Linkage

We compare variations of string comparators based on the Jaro-Winkler comparator and edit distance comparator. We apply the comparators to Census data to see which are better classifiers for matches and nonmatches, first by comparing their classification abilities using a ROC curve based analysis, then by considering a direct comparison between two candidate comparators in record linkage results.
DWARF14 is a non-canonical hormone receptor for strigolactone

Classical hormone receptors reversibly and non-covalently bind active hormone molecules, which are generated by biosynthetic enzymes, to trigger signal transduction. The α/β hydrolase DWARF14 (D14), which hydrolyses the plant branching hormone strigolactone and interacts with the F-box protein D3/MAX2, is probably involved in strigolactone detection. However, the active form of strigolactone has yet to be identified and it is unclear which protein directly binds the active form of strigolactone, and in which manner, to act as the genuine strigolactone receptor. Here we report the crystal structure of the strigolactone-induced AtD14–D3–ASK1 complex, reveal that Arabidopsis thaliana (At)D14 undergoes an open-to-closed state transition to trigger strigolactone signalling, and demonstrate that strigolactone is hydrolysed into a covalently linked intermediate molecule (CLIM) to initiate a conformational change of AtD14 to facilitate interaction with D3. Notably, analyses of a highly branched Arabidopsis mutant d14-5 show that the AtD14(G158E) mutant maintains enzyme activity to hydrolyse strigolactone, but fails to efficiently interact with D3/MAX2 and loses the ability to act as a receptor that triggers strigolactone signalling in planta. These findings uncover a mechanism underlying the allosteric activation of AtD14 by strigolactone hydrolysis into CLIM, and define AtD14 as a non-canonical hormone receptor with dual functions to generate and sense the active form of strigolactone.
Applying Sensor-Based Technology to Improve Construction Safety Management

Construction sites are dynamic and complicated systems. The movement and interaction of people, goods and energy make construction safety management extremely difficult. Due to the ever-increasing amount of information, traditional construction safety management has operated under difficult circumstances. As an effective way to collect, identify and process information, sensor-based technology is deemed to provide new generation of methods for advancing construction safety management. It makes the real-time construction safety management with high efficiency and accuracy a reality and provides a solid foundation for facilitating its modernization, and informatization. Nowadays, various sensor-based technologies have been adopted for construction safety management, including locating sensor-based technology, vision-based sensing and wireless sensor networks. This paper provides a systematic and comprehensive review of previous studies in this field to acknowledge useful findings, identify the research gaps and point out future research directions.
Asthmon: empowering asthmatic children's self-management with a virtual pet

Asthma is a common chronic childhood disease. Children spend a majority of their time in schools, and barriers to on-site asthma management have been reported. Previous forms of clinical intervention have regarded patients as passive subjects. However, self-management plays a significant role in caring for asthmatics. We consider asthmatic children and their parents, primary caregivers, as active participants in their treatment and care. To achieve this, we created Asthmon, a portable virtual pet that measures the lung capacity, and instructs appropriate actions to take.
A Randomized, Controlled Trial of Cavity Shave Margins in Breast Cancer.

Routine resection of cavity shave margins (additional tissue circumferentially around the cavity left by partial mastectomy) may reduce the rates of positive margins (margins positive for tumor) and reexcision among patients undergoing partial mastectomy for breast cancer.



In this randomized, controlled trial, we assigned, in a 1:1 ratio, 235 patients with breast cancer of stage 0 to III who were undergoing partial mastectomy, with or without resection of selective margins, to have further cavity shave margins resected (shave group) or not to have further cavity shave margins resected (no-shave group). Randomization occurred intraoperatively after surgeons had completed standard partial mastectomy. Positive margins were defined as tumor touching the edge of the specimen that was removed in the case of invasive cancer and tumor that was within 1 mm of the edge of the specimen removed in the case of ductal carcinoma in situ. The rate of positive margins was the primary outcome measure; secondary outcome measures included cosmesis and the volume of tissue resected.



The median age of the patients was 61 years (range, 33 to 94). On final pathological testing, 54 patients (23%) had invasive cancer, 45 (19%) had ductal carcinoma in situ, and 125 (53%) had both; 11 patients had no further disease. The median size of the tumor in the greatest diameter was 1.1 cm (range, 0 to 6.5) in patients with invasive carcinoma and 1.0 cm (range, 0 to 9.3) in patients with ductal carcinoma in situ. Groups were well matched at baseline with respect to demographic and clinicopathological characteristics. The rate of positive margins after partial mastectomy (before randomization) was similar in the shave group and the no-shave group (36% and 34%, respectively; P=0.69). After randomization, patients in the shave group had a significantly lower rate of positive margins than did those in the no-shave group (19% vs. 34%, P=0.01), as well as a lower rate of second surgery for margin clearance (10% vs. 21%, P=0.02). There was no significant difference in complications between the two groups.



Cavity shaving halved the rates of positive margins and reexcision among patients with partial mastectomy. (Funded by the Yale Cancer Center; ClinicalTrials.gov number, NCT01452399.).
Communication chains and multitasking

There is a growing literature on managing multitasking and interruptions in the workplace. In an ethnographic study, we investigated the phenomenon of communication chains, the occurrence of interactions in quick succession. Focusing on chains enable us to better understand the role of communication in multitasking. Our results reveal that chains are prevalent in information workers, and that attributes such as the number of links, and the rate of media and organizational switching can be predicted from the first catalyzing link of the chain. When chains are triggered by external interruptions, they have more links, a trend for more media switches and more organizational switches. We also found that more switching of organizational contexts in communication is associated with higher levels of stress. We describe the role of communication chains as performing alignment in multitasking and discuss the implications of our results.
Models and Algorithms for Interactive audio Rendering

Realistic modeling of reverberant sound in 3D virtual worlds provides users with important cues for localizing sound sources and understanding spatial properties of the environment. Unfortunately, current geometric acoustic modeling systems do not accurately simulate reverberant sound. Instead, they model only direct transmission and specular reflection, while diffraction is either ignored or modeled through statistical approximation. However, diffraction is important for correct interpretation of acoustic environments, especially when the direct path between sound source and receiver is occluded. The Uniform Theory of Diffraction (UTD) extends geometrical acoustics with diffraction phenomena: illuminated edges become secondary sources of diffracted rays that in turn may propagate through the environment. In this paper, we propose an efficient way for computing the acoustical effect of diffraction paths using the UTD for deriving secondary diffracted rays and associated diffraction coefficients. Our main contributions are: 1) a beam tracing method for enumerating sequences of diffracting edges efficiently and without aliasing in densely occluded polyhedral environments; 2) a practical approximation to the simulated sound field in which diffraction is considered only in shadow regions; and 3) a real-time auralization system demonstrating that diffraction dramatically improves the quality of spatialized sound in virtual environments.
An adherent raindrop detection method using MSER

Image processing algorithms used in surveillance systems are designed to work under good weather conditions. For example, in a rainy day, raindrops are adhered to camera lenses and windshields, resulting in partial occlusions in acquired images, and making performance of image processing algorithms significantly degraded. To improve performance of surveillance systems in a rainy day, raindrops have to be automatically detected and removed from images. Addressing this problem, this paper proposes an adherent raindrop detection method from a single image which does not need training data and special devices. The proposed method employs image segmentation using Maximally Stable Extremal Regions (MSER) and qualitative metrics to detect adherent raindrops from the result of MSER-based image segmentation. Through a set of experiments, we demonstrate that the proposed method exhibits efficient performance of adherent raindrop detection compared with conventional methods.
Combination of Sharing Matrix and Image Encryption for Lossless $(k,n)$ -Secret Image Sharing

This paper first introduces a <inline-formula> <tex-math notation="LaTeX">$(k,n)$ </tex-math></inline-formula>-sharing matrix <inline-formula> <tex-math notation="LaTeX">$S^{(k, n)}$ </tex-math></inline-formula> and its generation algorithm. Mathematical analysis is provided to show its potential for secret image sharing. Combining sharing matrix with image encryption, we further propose a lossless <inline-formula> <tex-math notation="LaTeX">$(k,n)$ </tex-math></inline-formula>-secret image sharing scheme (SMIE-SIS). Only with no less than <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> shares, all the ciphertext information and security key can be reconstructed, which results in a lossless recovery of original information. This can be proved by the correctness and security analysis. Performance evaluation and security analysis demonstrate that the proposed SMIE-SIS with arbitrary settings of <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> has at least five advantages: 1) it is able to fully recover the original image without any distortion; 2) it has much lower pixel expansion than many existing methods; 3) its computation cost is much lower than the polynomial-based secret image sharing methods; 4) it is able to verify and detect a fake share; and 5) even using the same original image with the same initial settings of parameters, every execution of SMIE-SIS is able to generate completely different secret shares that are unpredictable and non-repetitive. This property offers SMIE-SIS a high level of security to withstand many different attacks.
Solving Interleaved and Blended Sequential Decision-Making Problems through Modular Neuroevolution

Many challenging sequential decision-making problems require agents to master multiple tasks, such as defense and offense in many games. Learning algorithms thus benefit from having separate policies for these tasks, and from knowing when each one is appropriate. How well the methods work depends on the nature of the tasks: Interleaved tasks are disjoint and have different semantics, whereas blended tasks have regions where semantics from different tasks overlap. While many methods work well in interleaved tasks, blended tasks are difficult for methods with strict, human-specified task divisions, such as Multitask Learning. In such problems, task divisions should be discovered automatically. To demonstrate the power of this approach, the MM-NEAT neuroevolution framework is applied in this paper to two variants of the challenging video game of Ms. Pac-Man. In the simplified interleaved version of the game, the results demonstrate when and why such machine-discovered task divisions are useful. In the standard blended version of the game, a surprising, highly effective machine-discovered task division surpasses human-specified divisions, achieving the best scores to date in this game. Modular neuroevolution is thus a promising technique for discovering multimodal behavior for challenging real-world tasks.
Compact and Low-Profile Textile EBG-Based Antenna for Wearable Medical Applications

A compact wearable antenna with a novel miniaturized electromagnetic bandgap (EBG) structure at 2.4 GHz for medical application is presented in this letter. The design demonstrates a robust, compact, and low-profile solution to meet the requirements of wearable applications. The EBG structure reduces the back radiation and the impact of frequency detuning due to the high losses of human body. In addition, the structure improves the front-to-back ratio (FBR) by 15.5 dB. The proposed compact antenna with dimensions of  ${\text{46}}\,\times \,{\text{46}}\,\times \,{\text{2.4 mm}}^{3}$ yields an impedance bandwidth of 27% (2.17–2.83 GHz), with a gain enhancement of 7.8 dBi and more than 95% reduction in the specific absorption rate. Therefore, the antenna is a promising candidate for integration into wearable devices applied in various domains, specifically biomedical technology.
An Architecture for Embodied Conversational Characters

In this paper we describe the computational and architectural requirements for systems which support real-time multimodal interaction with an embodied conversational character. We argue that the three primary design drivers are real-time multithreaded entrainment, processing of both interactional and propositional information, and an approach based on a functional understanding of human face-to-face conversation. We then present an architecture which meets these requirements and an initial conversational character that we have developed who is capable of increasingly sophisticated multimodal input and output in a limited
A simple proof of the Littlewood-Richardson rule and applications

We present a simple proof of the Littlewood-Richardson rule using a sign-reversing involution, and show that a similar involution provides a com-binatorial proof of the SXP algorithm of Chen, Garsia, and Remmel 2] which computes the Schur function expansion of the plethysm of a Schur function and a power sum symmetric function. The methods of this paper have also been applied to prove combinatorial formulas for the characters of coordinate rings of nilpotent conjugacy classes of matrices 14].
A Syntactically Constrained Bidirectional-Asynchronous Approach for Emotional Conversation Generation

Traditional neural language models tend to generate generic replies with poor logic and no emotion. In this paper, a syntactically constrained bidirectional-asynchronous approach for emotional conversation generation (ESCBA) is proposed to address this issue. In our model, pre-generated emotion keywords and topic keywords are asynchronously introduced into the process of decoding. It is much different from most existing methods which generate replies from the first word to the last. Through experiments, the results indicate that our approach not only improves the diversity of replies, but gains a boost on both logic and emotion compared with baselines.
Perinatal risks of untreated depression during pregnancy.

To review the literature on the perinatal risks involved in untreated depression during pregnancy.



We searched Medline and medical texts for all studies pertaining to this area up to the end of April 2003. Key phrases entered were depression and pregnancy, depression and pregnancy outcome, and depression and untreated pregnancy. We did not include bipolar depression.



While there is wide variability in reported effects, untreated depression during pregnancy appears to carry substantial perinatal risks. These may be direct risks to the fetus and infant or risks secondary to unhealthy maternal behaviours arising from the depression. Recent human data suggest that untreated postpartum depression, not treatment with antidepressants in pregnancy, results in adverse perinatal outcome.



The biological dysregulation caused by gestational depression has not received appropriate attention: most studies focus on the potential but unproven risks of psychotropic medication. No in-depth discussion of the role of psychotherapy is available. Because they are not aware of the potentially catastrophic outcome of untreated maternal depression, this imbalance may lead women suffering from depression to fear teratogenic effects and refuse treatment.
Information coding in the olfactory system: Evidence for a stereotyped and highly organized epitope map in the olfactory bulb

In the mammalian olfactory system, information from approximately 1000 different odorant receptor types is organized in the nose into four spatial zones. Each zone is a mosaic of randomly distributed neurons expressing different receptor types. In these studies, we have obtained evidence that information highly distributed in the nose is transformed in the olfactory bulb of the brain into a highly organized spatial map. We find that specific odorant receptor gene probes hybridize in situ to small, and distinct, subsets of olfactory bulb glomeruli. The spatial and numerical characteristics of the patterns of hybridization that we observe with different receptor probes indicate that, in the olfactory bulb, olfactory information undergoes a remarkable organization into a fine, and perhaps stereotyped, spatial map. In our view, this map is in essence an epitope map, whose approximately 1000 distinct components are used in a multitude of different combinations to discriminate a vast array of different odors.