nils-herrmann/clean_scirepeval huggingface dataset:
HAZUS-MH Flood Loss Estimation Methodology . II . Damage and Loss Assessment

Part I of this two-part paper provided an overview of the HAZUS-MH Flood Model and a discussion of its capabilities for characterizing riverine and coastal flooding. Included was a discussion of the Flood Information Tool, which permits rapid analysis of a wide variety of stream discharge data and topographic mapping to determine flood-frequencies over entire floodplains. This paper reports on the damage and loss estimation capability of the Flood Model, which includes a library of more than 900 damage curves for use in estimating damage to various types of buildings and infrastructure. Based on estimated property damage, the model estimates shelter needs and direct and indirect economic losses arising from floods. Analyses for the effects of flood warning, the benefits of levees, structural elevation, and flood mapping restudies are also facilitated with the Flood Model.  2006 7:2 72 CE Database subject headings: Floods; Damage; Estimation; Models; Mapping.
Adynamic bone disease: from bone to vessels in chronic kidney disease.

Adynamic bone disease (ABD) is a well-recognized clinical entity in the complex chronic kidney disease (CKD)-mineral and bone disorder. Although the combination of low intact parathyroid hormone (PTH) and low bone alkaline phosphatase levels may be suggestive of ABD, the gold standard for precise diagnosis is histomorphometric analysis of tetracycline double-labeled bone biopsies. ABD essentially is characterized by low bone turnover, low bone volume, normal mineralization, and markedly decreased cellularity with minimal or no fibrosis. ABD is increasing in prevalence relative to other forms of renal osteodystrophy, and is becoming the most frequent type of bone lesion in some series. ABD develops in situations with reduced osteoanabolic stimulation caused by oversuppression of PTH, multifactorial skeletal resistance to PTH actions in uremia, and/or dysregulation of Wnt signaling. All may contribute not only to bone disease but also to the early vascular calcification processes observed in CKD. Various risk factors have been linked to ABD, including calcium loading, ageing, diabetes, hypogonadism, parathyroidectomy, peritoneal dialysis, and antiresorptive therapies, among others. The relationship between low PTH level, ABD, increased risk fracture, and vascular calcifications may at least partially explain the association of ABD with increased mortality rates. To achieve optimal bone and cardiovascular health, attention should be focused not only on classic control of secondary hyperparathyroidism but also on prevention of ABD, especially in the steadily growing proportions of diabetic, white, and elderly patients. Overcoming the insufficient osteoanabolic stimulation in ABD is the ultimate treatment goal.
Barrier/liner stacks for scaling the Cu interconnect metallization

Self-forming barriers and advanced liner materials are studied extensively for their Cu gapfill performance and interconnect scaling. In this paper, 22nm1/2 pitch Cu low-k interconnects with barrier (Mn-based, TaN) /liner (Co, Ru) combinations are compared and benchmarked for their resistivity, resistance scaling, and electromigration (EM) performance. Extendibility to 16nm copper width was explored experimentally and a projection towards 12nm width is performed. It is found that the Ru-liner based systems show a higher overall Cu-resistivity. We show that this increase can be compensated by combining Ru with a thinner Mn-based barrier, which increases the effective Cu-area at a particular trench width. The EM performance reveals that the Ru-liner systems have a better EM lifetime compared to the Co-liner based systems. More interestingly, in a comparison of the maximum current density Jmax a significant improvement is found for the scaled Mn-based/Ru system, making it therefore a serious candidate to extend the Cu metallization.
A Survey of Statistical Machine Translation

Statistical machine translation (SMT) treats the translation of natural language as a machine learning problem. By examining many samples of human-produced translation, SMT algorithms automatically learn how to translate. SMT has made tremendous strides in less than two decades, and many popular techniques have only emerged within the last few years. This survey presents a tutorial overview of state-of-the-art SMT at the beginning of 2007. We begin with the context of the current research, and then move to a formal problem description and an overview of the four main subproblems: translational equivalence modeling, mathematical modeling, parameter estimation, and decoding. Along the way, we present a taxonomy of some different approaches within these areas. We conclude with an overview of evaluation and notes on future directions. This is a revised draft of a paper currently under review. The contents may change in later drafts. Please send any comments, questions, or corrections to alopez@cs.umd.edu. Feel free to cite as University of Maryland technical report UMIACS-TR-2006-47. The support of this research by the GALE program of the Defense Advanced Research Projects Agency, Contract No. HR0011-06-2-0001, ONR MURI Contract FCPO.810548265, and Department of Defense contract RD-02-5700 is acknowledged.
A WIDEBAND SLOTTED WAVEGUIDE ANTENNA ARRAY FOR SAR SYSTEMS

Possibilities for the extension of the operational frequency band of slotted waveguide antennas are studied. It is shown that by using both conventional longitudinal slots and subarraying techniques it is possible to reach the relative bandwidth of about 15%. This result is illustrated by the development of a novel slotted waveguide antenna for high-resolution SAR applications. The antenna operates in the X-band and forms the beam of 4◦ × 6◦ with the gain of about 30 dB.
Privacy-preserving blockchain-based electric vehicle charging with dynamic tariff decisions

Electric vehicles are gaining widespread adoption and are a key component in the establishment of the smart grid. Beside the increasing number of electric vehicles, a dense and widespread charging infrastructure will be required. This offers the opportunity for a broad range of different energy providers and charging station operators, both of which can offer energy at different prices depending on demand and supply. While customers benefit from a liberalized market and a wide selection of tariff options, such dynamic pricing use cases are subject to privacy issues and allow to detect the customer’s position and to track vehicles for, e.g., targeted advertisements. In this paper we present a reliable, automated and privacy-preserving selection of charging stations based on pricing and the distance to the electric vehicle. The protocol builds on a blockchain where electric vehicles signal their demand and charging stations send bids similar to an auction. The electric vehicle owner then decides on a particular charging station based on the supply-side offers it receives. This paper shows that the use of blockchains increases the reliability and the transparency of this approach while preserving the privacy of the electric vehicle owners.
Development and Implementation of the Balanced Scorecard for a Higher Educational Institution using Business Intelligence Tools

The objective of designing a strategy for an institution is to create more value and achieve its vision, with clear and coherent strategies, identifying the conditions in which they are currently, the sector in which they work and the different types of competences that generate, as well as the market in general where they perform, to create this type of conditions requires the availability of strategic information to verify the current conditions, to define the strategic line to follow according to internal and external factors, and in this way decide which methods to use to implement the development of a strategy in the organization. This research project was developed in an institution of higher education where the strategic processes were analyzed from different perspectives i.e. financial, customers, internal processes, and training and learning using business intelligence tools, such as Excel Power BI, Power Pivot, Power Query and a relational database for data repository; which helped having agile and effective information for the creation of the balanced scorecard, involving all levels of the organization and academic units; operating key performance indicators (KPI’s), for operational and strategic decisions. The results were obtained in form of boards of indicators designed to be visualized in the final view of the software constructed with previously described software tools. Business intelligence; balanced scorecard; key performance indicators; BI Tools
The role of excitatory amino acids and NMDA receptors in traumatic brain injury.

Brain injury induced by fluid percussion in rats caused a marked elevation in extracellular glutamate and aspartate adjacent to the trauma site. This increase in excitatory amino acids was related to the severity of the injury and was associated with a reduction in cellular bioenergetic state and intracellular free magnesium. Treatment with the noncompetitive N-methyl-D-aspartate (NMDA) antagonist dextrophan or the competitive antagonist 3-(2-carboxypiperazin-4-yl)propyl-1-phosphonic acid limited the resultant neurological dysfunction; dextrorphan treatment also improved the bioenergetic state after trauma and increased the intracellular free magnesium. Thus, excitatory amino acids contribute to delayed tissue damage after brain trauma; NMDA antagonists may be of benefit in treating acute head injury.
Games with Procedurally Rational Players

We study interactive situations in which players are boundedly rational. Each player, rather than optimizing given a belief about the other players' behavior, as in the theory of Nash equilibrium, uses the following choice procedure. She rst associates one consequence with each of her actions by sampling (literally or virtually) each of her actions once. Then she chooses the action that has the best consequence. We deene a notion of equilibrium for such situations and study its properties.  Economists' interest in game theory was prompted by dissatisfaction with the assumption underlying the notion of competitive equilibrium that each economic agent ignores other agents' actions when making choices. Game theory analyzes the interaction of agents who \think strategically", making their decisions rationally after forming beliefs about their opponents' moves, beliefs that are based on an analysis of the opponents' interests.
New Sepsis Definition (Sepsis-3) and Community-acquired Pneumonia Mortality. A Validation and Clinical Decision-Making Study.

The Sepsis-3 Task Force updated the clinical criteria for sepsis, excluding the need for systemic inflammatory response syndrome (SIRS) criteria. The clinical implications of the proposed flowchart including the quick Sequential (Sepsis-related) Organ Failure Assessment (qSOFA) and SOFA scores are unknown.



To perform a clinical decision-making analysis of Sepsis-3 in patients with community-acquired pneumonia.



This was a cohort study including adult patients with community-acquired pneumonia from two Spanish university hospitals. SIRS, qSOFA, the Confusion, Respiratory Rate and Blood Pressure (CRB) score, modified SOFA (mSOFA), the Confusion, Urea, Respiratory Rate, Blood Pressure and Age (CURB-65) score, and Pneumonia Severity Index (PSI) were calculated with data from the emergency department. We used decision-curve analysis to evaluate the clinical usefulness of each score and the primary outcome was in-hospital mortality.



Of 6,874 patients, 442 (6.4%) died in-hospital. SIRS presented the worst discrimination, followed by qSOFA, CRB, mSOFA, CURB-65, and PSI. Overall, overestimation of in-hospital mortality and miscalibration was more evident for qSOFA and mSOFA. SIRS had lower net benefit than qSOFA and CRB, significantly increasing the risk of over-treatment and being comparable with the "treat-all" strategy. PSI had higher net benefit than mSOFA and CURB-65 for mortality, whereas mSOFA seemed more applicable when considering mortality/intensive care unit admission. Sepsis-3 flowchart resulted in better identification of patients at high risk of mortality.



qSOFA and CRB outperformed SIRS and presented better clinical usefulness as prompt tools for patients with community-acquired pneumonia in the emergency department. Among the tools for a comprehensive patient assessment, PSI had the best decision-aid tool profile.
Multi-Region Ensemble Convolutional Neural Network for High Accuracy Age Estimation

In real life, when telling a person’s age from his/her face, we tend to look at his/her whole face first and then focus on certain important regions like eyes. After that we will focus on each particular facial feature individually like the nose or the mouth so that we can decide the age of the person. Similarly, in this paper, we propose a new framework for age estimation, which is based on human face sub-regions. Each sub-network in our framework takes the input of two images each from human facial region. One of them is the global face, and the other is a vital sub-region. Then, we combine the predictions from different sub-regions based on a majority voting method. We call our framework Multi-Region Network Prediction Ensemble (MRNPE) and evaluate our approach using two popular public datasets: MORPH Album II and Cross Age Celebrity Dataset (CACD). Experiments show that our method outperforms the existing state-of-the-art age estimation methods by a significant margin. The Mean Absolute Errors (MAE) of age estimation are dropped from 3.03 to 2.73 years on the MORPH Album II and 4.79 to 4.40 years on the CACD.
Dealing with Uncertainties? Combining System Dynamics with Multiple Criteria Decision Analysis or with Exploratory Modelling

System Dynamics is often used to explore issues that are characterised by uncertainties. This paper discusses first of all different types of uncertainties that system dynamicists need to deal with and the tools they already use to deal with these uncertainties. From this discussion it is concluded that stand-alone System Dynamics is often not sufficient to deal with uncertainties. Then, two venues for improving the capacity of System Dynamics to deal with uncertainties are discussed, in both cases, by matching System Dynamics with other method(ologie)s: first with Multi-Attribute Multiple Criteria Decision Analysis, and finally with Exploratory Modelling.
Can dietary methionine restriction increase the effectiveness of chemotherapy in treatment of advanced cancer?

Most metastatic tumors, such as those originating in the prostate, lung, and gastrointestinal tract, respond poorly to conventional chemotherapy. Novel treatment strategies for advanced cancer are therefore desperately needed. Dietary restriction of the essential amino acid methionine offers promise as such a strategy, either alone or in combination with chemotherapy or other treatments. Numerous in vitro and animal studies demonstrate the effectiveness of dietary methionine restriction in inhibiting growth and eventually causing death of cancer cells. In contrast, normal host tissues are relatively resistant to methionine restriction. These preclinical observations led to a phase I clinical trial of dietary methionine restriction for adults with advanced cancer. Preliminary findings from this trial indicate that dietary methionine restriction is safe and feasible for the treatment of patients with advanced cancer. In addition, the trial has yielded some preliminary evidence of antitumor activity. One patient with hormone-independent prostate cancer experienced a 25% reduction in serum prostate-specific antigen (PSA) after 12 weeks on the diet, and a second patient with renal cell cancer experienced an objective radiographic response. The possibility that methionine restriction may act synergistically with other cancer treatments such as chemotherapy is being explored. Findings to date support further investigation of dietary methionine restriction as a novel treatment strategy for advanced cancer.
GEOMETRICAL ASPECTS OF AIRBORNE LASER SCANNING AND TERRESTRIAL LASER SCANNING

This paper reviews the current state of laser scanning from airborne and terrestrial platforms for geometric reconstruction of object shape and size. The current performance figures of sensor systems are presented in an overview. Next, their calibration and the orientation of the acquired point clouds is discussed. For airborne deployment this is usually one step, whereas in the terrestrial case laboratory calibration and registration of point clouds are (still) two distinct, independent steps. As laser scanning is an active measurement technology, the interaction of the emitted energy with the object surface has influences on the range measurement. This has to be considered in order to explain geometric phenomena in the data. While the problems, e.g. multiple scattering, are understood well, there is currently a lack of remedies. Then, in analogy to the processing chain, segmentation approaches for laser scanning data are reviewed. Segmentation is a task relevant for almost all applications. Likewise, DTM (digital terrain model) reconstruction is relevant for many applications of airborne laser scanning, and is therefore discussed, too. This paper reviews the main processing steps necessary for many applications of laser scanning.
Multi-layer four-way out-of-phase power divider for substrate integrated waveguide applications

In this paper, a novel multi-layer four-way out-of-phase power divider based on substrate integrated waveguide (SIW) is proposed. The four-way power division is realized by 3-D mode coupling; vertical partitioning of a SIW followed by lateral coupling to two half-mode SIW. The measurement results show the excellent insertion loss (S<inf>21</inf>, S<inf>31</inf>, S<inf>41</inf>, S<inf>51</inf>: −7.0 ± 0.5 dB) and input return loss (S<inf>11</inf>: −10 dB) in X-band (7.63 GHz ∼ 11.12 GHz). We expect that the proposed power divider play an important role for the integration of compact multi-way SIW circuits.
Challenges and Opportunities in Game Artificial Intelligence Education Using Angry Birds

Games have been an important tool for motivating undergraduate students majoring in computer science and engineering. However, it is difficult to build an entire game for education from scratch, because the task requires high-level programming skills and expertise to understand the graphics and physics. Recently, there have been many different game artificial intelligence (AI) competitions, ranging from board games to the state-of-the-art video games (car racing, mobile games, first-person shooting games, real-time strategy games, and so on). The competitions have been designed such that participants develop their own AI module on top of public/commercial games. Because the materials are open to the public, it is quite useful to adopt them for an undergraduate course project. In this paper, we report our experiences using the Angry Birds AI Competition for such a project-based course. In the course, teams of students consider computer vision, strategic decision-making, resource management, and bug-free coding for their outcome. To promote understanding of game contents generation and extensive testing on the generalization abilities of the student's AI program, we developed software to help them create user-created levels. Students actively participated in the project and the final outcome was comparable with that of successful entries in the 2013 International Angry Birds AI Competition. Furthermore, it leads to the development of a new parallelized Angry Birds AI Competition platform with undergraduate students aiming to use advanced optimization algorithms for their controllers.
Psyllium is superior to docusate sodium for treatment of chronic constipation.

Stool softening is a physician's first step in the management of chronic constipation.



To compare stool softening (stool water content) and laxative efficacy of psyllium hydrophilic mucilloid vs. docusate sodium.



The multi-site, randomized, double-blind, parallel-design study of 170 subjects with chronic idiopathic constipation involved a 2-week baseline (placebo) phase followed by 2 weeks of treatment. The treatment phase compared psyllium (5.1 g b.d.) plus docusate placebo to docusate sodium (100 mg b.d.) plus psyllium placebo. Stools were collected and assessed.



Compared to baseline, psyllium increased stool water content vs. docusate (psyllium 2.33% vs. docusate 0.01%, P = 0.007). Psyllium also increased stool water weight (psyllium 84.0 g/BM; docusate 71.4 g/BM; P = 0.04), total stool output (psyllium 359.9 g/week: docusate 271.9 g/week; P = 0.005), and O'Brien rank-type score combining objective measures of constipation (psyllium 475.1; docusate 403.9; P = 0.002). Bowel movement (BM) frequency was significantly greater for psyllium (3.5 BM/week) vs. docusate (2.9 BM/week) in treatment week 2 (P = 0.02), with no significant difference (P > 0.05) between treatment groups in treatment week 1 (3.3 vs. 3.1 BM/week).



Psyllium is superior to docusate sodium for softening stools by increasing stool water content, and has greater overall laxative efficacy in subjects with chronic idiopathic constipation.
Confining solitons in the Higgs phase of C P N − 1 model : Self-consistent exact solutions in large-N limit

The quantum CP model is in the confining (or unbroken) phase with a full mass gap in an infinite space, while it is in the Higgs (broken or deconfinement) phase accompanied with Nambu-Goldstone modes in a finite space such as a ring or finite interval smaller than a certain critical size. We find a new self-consistent exact solution describing a soliton in the Higgs phase of the CP model in the large-N limit on a ring. We call it a confining soliton. We show that all eigenmodes have real and positive energy and thus it is stable.
Bored in the USA: Experience sampling and boredom in everyday life.

We report new evidence on the emotional, demographic, and situational correlates of boredom from a rich experience sample capturing 1.1 million emotional and time-use reports from 3,867 U.S. adults. Subjects report boredom in 2.8% of the 30-min sampling periods, and 63% of participants report experiencing boredom at least once across the 10-day sampling period. We find that boredom is more likely to co-occur with negative, rather than positive, emotions, and is particularly predictive of loneliness, anger, sadness, and worry. Boredom is more prevalent among men, youths, the unmarried, and those of lower income. We find that differences in how such demographic groups spend their time account for up to one third of the observed differences in overall boredom. The importance of situations in predicting boredom is additionally underscored by the high prevalence of boredom in specific situations involving monotonous or difficult tasks (e.g., working, studying) or contexts where one's autonomy might be constrained (e.g., time with coworkers, afternoons, at school). Overall, our findings are consistent with cognitive accounts that cast boredom as emerging from situations in which engagement is difficult, and are less consistent with accounts that exclusively associate boredom with low arousal or with situations lacking in meaning.