nils-herrmann/clean_scirepeval huggingface dataset:
Evaluation of ultraviolet disinfection of microalgae by growth modeling: application to ballast water treatment

Ultraviolet disinfection is a frequent option for eliminating viable organisms in ballast water to fulfill international and national regulations. The objective of this work is to evaluate the reduction of microalgae able to reproduce after UV irradiation, based on their growth features. A monoculture of microalgae Tisochrysis lutea was irradiated with different ultraviolet doses (UV-C 254 nm) by a flow-through reactor. A replicate of each treated sample was held in the dark for 5 days simulating a treatment during the ballasting; another replicate was incubated directly under the light, corresponding to the treatment application during de-ballasting. Periodic measurements of cell density were taken in order to obtain the corresponding growth curves. Irradiated samples depicted a regrowth following a logistic curve in concordance with the applied UV dose. By modeling these curves, it is possible to obtain the initial concentration of organisms able to reproduce for each applied UV dose, thus obtaining the dose-survival profiles, needed to determine the disinfection kinetics. These dose-survival profiles enable detection of a synergic effect between the ultraviolet irradiation and a subsequent dark period; in this sense, the UV dose applied during the ballasting operation and subsequent dark storage exerts a strong influence on microalgae survival. The proposed methodology, based on growth modeling, established a framework for comparing the UV disinfection by different devices and technologies on target organisms. This procedure may also assist the understanding of the evolution of treated organisms in more complex assemblages such as those that exist in natural ballast water.
Interior permanent-magnet motor for ship propulsion, design and testing

The main design features and the results of tests carried out on a prototype of a 750 kW interior permanent-magnet (IPM) motor for ship propulsion are presented. The principal reasons for choosing an IPM motor design over other available types of permanent-magnet (PM) motors for ship propulsion have been discussed in detail. The test results indicate that the motor parameters and its performance confirm the predictions made in the design stage.
Superpixel regions extraction for target detection

In this paper, an algorithm of target region detection is proposed based on superpixel segmentation in the field of computer vision which is imported to high-resolution remote sensing images for superpixel-level rather than pixel-level target detection. For the problem of massive data, redundant information and time-consuming targets searching of high-resolution remote sensing images with complex scene and large size, the region of interest (ROI) extraction strategy based on a visual saliency map detection is adopted. Second, the multidimensional description vector of local feature is constructed via superpixels obtained from simple linear iterative clustering (SLIC). Third, combine with the prior information of the target to determine the threshold of feature, from which we select the candidate superpixels belong to target. Experimental results show that the proposed algorithm is more effective in high-resolution remote sensing images, overcoming the situation of complex background interference and robust to the target rotation. In addition, the proposed algorithm performs favorably against the traditional sliding windows search algorithm. On one hand, significantly reduces the computing complexity of the search space, and achieves the data dimensionality reduction. On the other hand, it brings lower false probability and improves the detection accuracy.
Dijkstra monads for free

Dijkstra monads enable a dependent type theory to be enhanced with support for specifying and verifying effectful code via weakest preconditions. Together with their closely related counterparts, Hoare monads, they provide the basis on which verification tools like F*, Hoare Type Theory (HTT), and Ynot are built. We show that Dijkstra monads can be derived âfor freeâ by applying a continuation-passing style (CPS) translation to the standard monadic definitions of the underlying computational effects. Automatically deriving Dijkstra monads in this way provides a correct-by-construction and efficient way of reasoning about user-defined effects in dependent type theories. We demonstrate these ideas in EMF*, a new dependently typed calculus, validating it via both formal proof and a prototype implementation within F*. Besides equipping F* with a more uniform and extensible effect system, EMF* enables a novel mixture of intrinsic and extrinsic proofs within F*.
Shifting the Baseline: Single Modality Performance on Visual Navigation & QA

We demonstrate the surprising strength of unimodal baselines in multimodal domains, and make concrete recommendations for best practices in future research. Where existing work often compares against random or majority class baselines, we argue that unimodal approaches better capture and reflect dataset biases and therefore provide an important comparison when assessing the performance of multimodal techniques. We present unimodal ablations on three recent datasets in visual navigation and QA, seeing an up to 29% absolute gain in performance over published baselines.
Self-Guiding Multimodal LSTM - when we do not have a perfect training dataset for image captioning

In this paper, a self-guiding multimodal LSTM (sg-LSTM) image captioning model is proposed to handle uncontrolled imbalanced real-world image-sentence dataset. We collect FlickrNYC dataset from Flickr as our testbed with 306, 165 images and the original text descriptions uploaded by the users are utilized as the ground truth for training. Descriptions in FlickrNYC dataset vary dramatically ranging from short term-descriptions to long paragraph-descriptions and can describe any visual aspects, or even refer to objects that are not depicted. To deal with the imbalanced and noisy situation and to fully explore the dataset itself, we propose a novel guiding textual feature extracted utilizing a multimodal LSTM (m-LSTM) model. Training of m-LSTM is based on the portion of data in which the image content and the corresponding descriptions are strongly bonded. Afterwards, during the training of sg-LSTM on the rest training data, this guiding information serves as additional input to the network along with the image representations and the ground-truth descriptions. By integrating these input components into a multimodal block, we aim to form a training scheme with the textual information tightly coupled with the image content. The experimental results demonstrate that the proposed sg-LSTM model outperforms the traditional state-of-the-art multimodal RNN captioning framework in successfully describing the key components of the input images.
The relationship among computer work, environmental design, and musculoskeletal and visual discomfort: examining the moderating role of supervisory relations and co-worker support.

The prevalence of work-related upper extremity musculoskeletal disorders and visual symptoms reported in the USA has increased dramatically during the past two decades. This study examined the factors of computer use, workspace design, psychosocial factors, and organizational ergonomics resources on musculoskeletal and visual discomfort and their impact on the safety and health of computer work employees.



A large-scale, cross-sectional survey was administered to a US manufacturing company to investigate these relationships (n = 1259). Associations between these study variables were tested along with moderating effects framed within a conceptual model.



Significant relationships were found between computer use and psychosocial factors of co-worker support and supervisory relations with visual and musculoskeletal discomfort. Co-worker support was found to be significantly related to reports of eyestrain, headaches, and musculoskeletal discomfort. Supervisor relations partially moderated the relationship between workspace design satisfaction and visual and musculoskeletal discomfort.



This study provides guidance for developing systematic, preventive measures and recommendations in designing office ergonomics interventions with the goal of reducing musculoskeletal and visual discomfort while enhancing office and computer workers' performance and safety.
Cache-Aided Heterogeneous Networks: Coverage and Delay Analysis

This paper characterizes the performance of a generic $K$-tier cache-aided heterogeneous network (CHN), in which the base stations (BSs) across tiers differ in terms of their spatial densities, transmission powers, pathloss exponents, activity probabilities conditioned on the serving link and placement caching strategies. We consider that each user connects to the BS which maximizes its average received power and at the same time caches its file of interest. Modeling the locations of the BSs across different tiers as independent homogeneous Poisson Point processes (HPPPs), we derive closed-form expressions for the coverage probability and local delay experienced by a typical user in receiving each requested file. We show that our results for coverage probability and delay are consistent with those previously obtained in the literature for a single tier system.
Block design as a measure of everyday spatial ability: a study of ecological validity.

This study investigated the effectiveness of the WAIS-R Block Design subtest to predict everyday spatial ability for 65 university undergraduates (15 men, 50 women) who were administered Block Design, the Standardized Road Map Test of Direction Sense, and the Everyday Spatial Activities Test. In addition, the verbally loaded National Adult Reading Test was administered to assess whether the more visuospatial Block Design subtest was a better predictor of spatial ability. Moderate support was found. When age and sex were accounted for, Block Design accounted for 36% of the variance in performance (r = -.62) on the Road Map Test and 19% of the variance on the performance of the Everyday Spatial Activities Test (r = .42). In contrast, the scores on the National Adult Reading Test did not predict performance on the Road Map Test or Everyday Spatial Abilities Test. This suggests that, with appropriate caution, Block Design could be used as a measure of everyday spatial abilities.
Characteristics, complications, and gaps in evidence-based interventions in rheumatic heart disease: the Global Rheumatic Heart Disease Registry (the REMEDY study).

Rheumatic heart disease (RHD) accounts for over a million premature deaths annually; however, there is little contemporary information on presentation, complications, and treatment.



This prospective registry enrolled 3343 patients (median age 28 years, 66.2% female) presenting with RHD at 25 hospitals in 12 African countries, India, and Yemen between January 2010 and November 2012. The majority (63.9%) had moderate-to-severe multivalvular disease complicated by congestive heart failure (33.4%), pulmonary hypertension (28.8%), atrial fibrillation (AF) (21.8%), stroke (7.1%), infective endocarditis (4%), and major bleeding (2.7%). One-quarter of adults and 5.3% of children had decreased left ventricular (LV) systolic function; 23% of adults and 14.1% of children had dilated LVs. Fifty-five percent (n = 1761) of patients were on secondary antibiotic prophylaxis. Oral anti-coagulants were prescribed in 69.5% (n = 946) of patients with mechanical valves (n = 501), AF (n = 397), and high-risk mitral stenosis in sinus rhythm (n = 48). However, only 28.3% (n = 269) had a therapeutic international normalized ratio. Among 1825 women of childbearing age (12-51 years), only 3.6% (n = 65) were on contraception. The utilization of valvuloplasty and valve surgery was higher in upper-middle compared with lower-income countries.



Rheumatic heart disease patients were young, predominantly female, and had high prevalence of major cardiovascular complications. There is suboptimal utilization of secondary antibiotic prophylaxis, oral anti-coagulation, and contraception, and variations in the use of percutaneous and surgical interventions by country income level.
The Energy Efficiency Of Iram Architectures

Portable systems demand energy efficiency in order to maximize battery life. IRAM architectures, which combine DRAM and a processor on the same chip in a DRAM process, are more energy efficient than conventional systems. The high density of DRAM permits a much larger amount of memory on-chip than a traditional SRAM cache design in a logic process. This allows most or all IRAM memory accesses to be satisfied on-chip. Thus there is much less need to drive high-capacitance off-chip buses, which contribute significantly to the energy consumption of a system. To quantify this advantage we apply models of energy consumption in DRAM and SRAM memories to results from cache simulations of applications reflective of personal productivity tasks on low power systems. We find that IRAM memory hierarchies consume as little as 22% of the energy consumed by a conventional memory hierarchy for memory-intensive applications, while delivering comparable performance. Furthermore, the energy consumed by a system consisting of an IRAM memory hierarchy combined with an energy efficient CPU core is as little as 40% of that of the same CPU core with a traditional memory hierarchy.
Multimodal People Tracking and Trajectory Prediction based on Learned Generalized Motion Patterns

A sensor-based model of a service robot's environment is a prerequisite for interaction. Such a model should contain the positions of the robot's interaction partners. Additionally to the actual positions of the partners it is important for the service robot to predict their possible future positions. This knowledge could for example be used to realize efficient path planning for delivery tasks. In this paper we propose an extensible framework for systems that combine different sensor modalities in a general tracking system. Exemplarily, a tracking system is implemented that fuses tracking algorithms in laser range scans as well as in camera images by a particle filter. We point out the real-time capabilities of our tracking algorithms implementation. Practical experiments show that multimodality increases the system's robustness to incorrect measurements of single sensors. Furthermore, the observed trajectories are generalized to trajectory patterns by a novel method which uses self organizing maps. Those patterns are used to predict trajectories of the currently observed persons. It is also demonstrated that a self organizing map is suitable for learning and generalizing trajectories. Convenient predictions of future trajectories are presented which are deduced from these generalizations
A Companion Cell–Dominant and Developmentally Regulated H3K4 Demethylase Controls Flowering Time in Arabidopsis via the Repression of FLC Expression

Flowering time relies on the integration of intrinsic developmental cues and environmental signals. FLC and its downstream target FT are key players in the floral transition in Arabidopsis. Here, we characterized the expression pattern and function of JMJ18, a novel JmjC domain-containing histone H3K4 demethylase gene in Arabidopsis. JMJ18 was dominantly expressed in companion cells; its temporal expression pattern was negatively and positively correlated with that of FLC and FT, respectively, during vegetative development. Mutations in JMJ18 resulted in a weak late-flowering phenotype, while JMJ18 overexpressors exhibited an obvious early-flowering phenotype. JMJ18 displayed demethylase activity toward H3K4me3 and H3K4me2, and bound FLC chromatin directly. The levels of H3K4me3 and H3K4me2 in chromatins of FLC clade genes and the expression of FLC clade genes were reduced, whereas FT expression was induced and the protein expression of FT increased in JMJ18 overexpressor lines. The early-flowering phenotype caused by the overexpression of JMJ18 was mainly dependent on the functional FT. Our findings suggest that the companion cell-dominant and developmentally regulated JMJ18 binds directly to the FLC locus, reducing the level of H3K4 methylation in FLC chromatin and repressing the expression of FLC, thereby promoting the expression of FT in companion cells to stimulate flowering.
Health-Seeking Influence Reflected by Online Health-Related Messages Received on Social Media: Cross-Sectional Survey

Major social networking platforms, such as Facebook, WhatsApp, and Twitter, have become popular means through which people share health-related information, irrespective of whether messages disseminated through these channels are authentic.



This study aims to describe the demographic characteristics of patients that may demonstrate their attitudes toward medical information shared on social media networks. Second, we address how information found through social media affects the way people deal with their health. Third, we examine whether patients initiate or alter/discontinue their medications based on information derived from social media.



We conducted a cross-sectional survey between April and June 2015 on patients attending outpatient clinics at King Abdulaziz University, Jeddah, Saudi Arabia. Patients who used social media (Facebook, WhatsApp, and Twitter) were included. We designed a questionnaire with closed-ended and multiple-choice questions to assess the type of social media platforms patients used and whether information received on these platforms influenced their health care decisions. We used chi-square test to establish the relationship between categorical variables.



Of the 442 patients who filled in the questionnaires, 401 used Facebook, WhatsApp, or Twitter. The majority of respondents (89.8%, 397/442) used WhatsApp, followed by Facebook (58.6%, 259/442) and Twitter (42.3%, 187/442). In most cases, respondents received health-related messages from WhatsApp and approximately 42.6% (171/401) reported ever stopping treatment as advised on a social media platform. A significantly higher proportion of patients without heart disease (P=.001) and obese persons (P=.01) checked the authenticity of information received on social media. Social media messages influenced decision making among patients without heart disease (P=.04). Respondents without heart disease (P=.001) and obese persons (P=.01) were more likely to discuss health-related information received on social media channels with a health care professional. A significant proportion of WhatsApp users reported that health-related information received on this platform influenced decisions regarding their family's health care (P=.001). Respondents' decisions regarding family health care were more likely to be influenced when they used two or all three types of platforms (P=.003).



Health education in the digital era needs to be accurate, evidence-based, and regulated. As technologies continue to evolve, we must be equipped to face the challenges it brings with it.
Advanced Numerical and Experimental Techniques for Analysis of Dynamic Responses and Solder Joint Reliability During Drop Impact

Board level solder joint reliability performance during drop test is a critical concern to semiconductor and electronic product manufacturers. A new JEDEC standard for board level drop test of handheld electronic products was just released to specify the drop test procedure and conditions. However, there is no detailed information stated on dynamic responses of printed circuit board (PCB) and solder joints which are closely related to stress and strain of solder joints that affect the solder joint reliability, nor there is any simulation technique which provides good correlation with experimental measurements of dynamic responses of PCB and the resulting solder joint reliability during the entire drop impact process. In this paper, comprehensive dynamic responses of PCB and solder joints, e.g., acceleration, strains, and resistance, are measured and analyzed with a multichannel real-time electrical monitoring system, and simulated with a novel input acceleration (Input-G) method. The solder joint failure process, i.e., crack initiation, propagation, and opening, is well understood from the behavior of dynamic resistance. It is found experimentally and numerically that the mechanical shock causes multiple PCB bending or vibration which induces the solder joint fatigue failure. It is proven that the peeling stress of the critical solder joint is the dominant failure indicator by simulation, which correlates well with the observations and assumptions by experiment. Coincidence of cyclic change among dynamic resistance of solder joints, dynamic strains of PCB, and the peeling stress of the critical solder joints indicates that the solder joint crack opens and closes when the PCB bends down and up, and the critical solder joint failure is induced by cyclic peeling stress. The failure mode and location of critical solder balls predicted by modeling correlate well with experimental observation by cross section and dye penetration tests
Enhancing spark's contract checking facilities using symbolic execution

Spark, a subset of Ada for engineering safety and security-critical systems, is one of the best commercially available frameworks for formal-methods-supported development of critical software. Spark is designed for verification and includes a software contract language for specifying functional properties of procedures. Even though Spark and its static analysis components are beneficial and easy to use, its contract language is rarely used for stating properties beyond simple constraints on scalar values due to the burdens the associated tool support imposes on developers. Symbolic execution (SymExe) techniques have made significant strides in automating reasoning about deep semantic properties of source code. However, most work on SymExe has focused on bug-finding and test case generation as opposed to tasks that are more verification-oriented such as contract checking. In previous work we have presented: (a) SymExe techniques for checking software contracts in embedded critical systems, and (b) Bakar Kiasan, a tool that implements these techniques in an integrated development environment for Spark. In this paper, we give a detailed walk-through of Bakar Kiasan as it is applied to an industrial code base for an embedded security device. We illustrate how Bakar Kiasan provides significant increases in automation, usability, and functionality over existing Spark contract checking tools, and we present results from performance evaluations of its application to industrial examples.
Evidence Combination From an Evolutionary Game Theory Perspective

Shafer evidence theory is a primary methodology for multisource information fusion because it is good at dealing with uncertain information. This theory provides a Dempster's rule of combination to synthesize multiple evidences from various information sources. However, in some cases, counter-intuitive results may be obtained based on that combination rule. Numerous new or improved methods have been proposed to suppress these counter-intuitive results based on perspectives, such as minimizing the information loss or deviation. Inspired by evolutionary game theory, this paper considers a biological and evolutionary perspective to study the combination of evidences. An evolutionary combination rule (ECR) is proposed to help find the most biologically supported proposition in a multievidence system. Within the proposed ECR, we develop a Jaccard matrix game to formalize the interaction between propositions in evidences, and utilize the replicator dynamics to mimick the evolution of propositions. Experimental results show that the proposed ECR can effectively suppress the counter-intuitive behaviors appeared in typical paradoxes of evidence theory, compared with many existing methods. Properties of the ECR, such as solution's stability and convergence, have been mathematically proved as well.