nils-herrmann/clean_scirepeval huggingface dataset:
Economic burden of malaria on businesses in Ghana: a case for private sector investment in malaria control

Despite the significant gains made globally in reducing the burden of malaria, the disease remains a major public health challenge, especially in sub-Saharan Africa (SSA) including Ghana. There is a significant gap in financing malaria control globally. The private sector could become a significant source of financing malaria control. To get the private sector to appreciate the need to invest in malaria control, it is important to provide evidence of the economic burden of malaria on businesses. The objective of this study, therefore, was to estimate the economic burden on malaria on businesses in Ghana, so as to stimulate the sector’s investment in malaria control. Data covering 2012–2014 were collected from 62 businesses sampled from Greater Accra, Ashanti and Western Regions of Ghana, which have the highest concentration of businesses in the country. Data on the cost of businesses’ spending on treatment and prevention of malaria in staff and their dependants as well as staff absenteeism due to malaria and expenditure on other health-related activities were collected. Views of business leaders on the effect of malaria on their businesses were also compiled. The analysis was extrapolated to cover 5828 businesses across the country. The results show that businesses in Ghana lost about US$6.58 million to malaria in 2014, 90 % of which were direct costs. A total of 3913 workdays were lost due to malaria in firms in the study sample during the period 2012–2014. Businesses in the study sample spent an average of 0.5 % of the annual corporate returns on treatment of malaria in employees and their dependants, 0.3 % on malaria prevention, and 0.5 % on other health-related corporate social responsibilities. Again business leaders affirmed that malaria affects their businesses’ efficiency, employee attendance and productivity and expenses. Finally, about 93 % of business leaders expressed the need private sector investment in malaria control. The economic burden of malaria on businesses in Ghana cannot be underestimated. This, together with business leaders’ acknowledgement that it is important for private sector investment in malaria control, provides motivation for engagement of the private sector in financing malaria control activities.
Energy Efficient Battery Management

A challenging aspect of mobile communications consists in exploring ways in which the available run time of the terminals can be maximized. In this paper we investigate battery management techniques that can dramatically improve the energy efficiency of radio communication devices. We consider an array of electrochemical cells connected in parallel. Through simple scheduling algorithms the discharge from each cell is properly shaped to optimize the charge recovery mechanism, without introducing any additional delay in supplying the required power. Then, a traffic management scheme, that exploits the knowledge of the cells state of charge, is implemented to achieve a further improvement in the battery performances. In this case, the discharge demand may be delayed. Results indicate that the proposed battery management techniques improve system performance no matter which parameters values are chosen to characterize the cells behavior.  As the popularity of radio communications equipments increases, the reliability and energy capacity of batteries becomes a critical issue. Indeed, a greater battery capacity means a longer run time of the terminals, and therefore it is a determinating factor in the success of a product. Due to the disparity in the rate of technological advance in batteries and in portable communications equipments markets, software/hardware solutions have to be found to improve the battery performance. As shown by experimental tests , ,  and analytical results , , a greater battery capacity can be obtained by using a pulsed current discharge instead of a constant current discharge. In fact, under a pulsed discharge profile the charge recovery mechanism inherent to many secondary storage batteries can be exploited. During the interruptions of the drained current, so calledrest time periods , the battery is able to recover charge thanks to the diffusion process[4]. Longer rest times translate into a greater capacity delivered by the battery [6]. An application of the pulsed discharge technique and its benefits can be observed in GSM and other TDMA based systems, where a high current is needed from the battery just during the packet transmission time (e.g., 557 s in GSM), otherwise a value of current about 10 times lower is drained [7]. For a summary of the behavior of real batteries, please refer to . In this paper, we explore ways in which the energy efficiency of mobile wireless communications can be enhanced through the use of improved energy-efficient battery management techSupported by NSF under grant CCR 9714651. Carla F. Chiasserini is on leave at the University of California, San Diego. caacity delivered
Diagnostic Value of Serum Angiogenesis Markers in Ovarian Cancer Using Multiplex Immunoassay

As cancer development involves pathological vessel formation, 16 angiogenesis markers were evaluated as potential ovarian cancer (OC) biomarkers. Blood samples collected from 172 patients were divided based on histopathological result: OC (n = 38), borderline ovarian tumours (n = 6), non-malignant ovarian tumours (n = 62), healthy controls (n = 50) and 16 patients were excluded. Sixteen angiogenesis markers were measured using BioPlex Pro Human Cancer Biomarker Panel 1 immunoassay. Additionally, concentrations of cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) were measured in patients with adnexal masses using electrochemiluminescence immunoassay. In the comparison between OC vs. non-OC, osteopontin achieved the highest area under the curve (AUC) of 0.79 (sensitivity 69%, specificity 78%). Multimarker models based on four to six markers (basic fibroblast growth factor-FGF-basic, follistatin, hepatocyte growth factor-HGF, osteopontin, platelet-derived growth factor AB/BB-PDGF-AB/BB, leptin) demonstrated higher discriminatory ability (AUC 0.80-0.81) than a single marker (AUC 0.79). When comparing OC with benign ovarian tumours, six markers had statistically different expression (osteopontin, leptin, follistatin, PDGF-AB/BB, HGF, FGF-basic). Osteopontin was the best single angiogenesis marker (AUC 0.825, sensitivity 72%, specificity 82%). A three-marker panel consisting of osteopontin, CA125 and HE4 better discriminated the groups (AUC 0.958) than HE4 or CA125 alone (AUC 0.941 and 0.932, respectively). Osteopontin should be further investigated as a potential biomarker in OC screening and differential diagnosis of ovarian tumours. Adding osteopontin to a panel of already used biomarkers (CA125 and HE4) significantly improves differential diagnosis between malignant and benign ovarian tumours.
Social Sustainability and Its Indicators through a Disability Studies and an Ability Studies Lens

The present journal recently stated in the call for a special issue on social sustainability, ―[t]hough sustainable development is said to rest on  ̳three pillars‘, one of these—social sustainability—has received significantly less attention than its bio-physical environmental and economic counterparts‖. The current issue promises to engage the concepts of ―development sustainability‖, ―bridge sustainability‖ and ―maintenance sustainability‖ and the tensions between these different aspects of social sustainability. The aim of the present study is to identify the visibility of disabled people in the academic social sustainability literature, to ascertain the impact and promises of social sustainability indicators put forward in the same literature and to engage especially with the concepts of ―development sustainability‖, ―bridge sustainability‖ and ―maintenance sustainability‖ through disability studies and ability studies lenses. We report that disabled people are barely covered in the academic social sustainability literature; of the 5165 academic articles investigated only 26 had content related to disabled people and social sustainability. We also conclude that social sustainability indicators evident in the 1909 academic articles with the phrase ―social sustainability‖ in the abstract mostly focused on products and did not reflect yet the goals outlined in the ―development sustainability‖ aspect of social sustainability proposed by Vallance such as basic needs, building social capital, justice and so on. We posit that if the focus within the social sustainability discourse shifts more toward the social that an active presence of disabled people in this OPEN ACCESS Sustainability 2013, 5 4890 discourse is essential to disabled people. We showcase the utility of an ability studies lens to further the development and application of the ―development sustainability‖, ―bridge sustainability‖ and ―maintenance sustainability‖ concepts. We outline how different ability expectations intrinsic to certain schools of thought of how to deal with human-nature relationships (for example anthropocentric versus bio/ecocentric) impact this relationship and ―bridge sustainability‖. As to ―maintenance development‖, we posit that no engagement has happened yet with the ability expectation conflicts between able-bodied and disabled people, or for that matter with the ability expectation differences between different able-bodied groups within social sustainability discourses; an analysis essential for the maintenance of development. In general, we argue that there is a need to generate ability expectation conflict maps and ability expectations conflict resolution mechanisms for all sustainable development discourses individually and for ability conflicts between sustainable development discourses.
ESD-WP-2003-01 . 27-ESD Internal Symposium SUPPLY CHAIN MANAGEMENT UNDER THE THREAT OF INTERNATIONAL TERRORISM

On the morning of September 11, 2001, the United States and the Western world entered into a new era – one in which large scale terrorist acts are to be expected. The impacts of the new era will challenge supply chain managers to adjust relations with suppliers and customers, contend with transportation difficulties and amend inventory management strategies. This paper looks at the twin corporate challenges of (i) preparing to deal with the aftermath of terrorist attacks and (ii) operating under heightened security. The first challenge involves setting certain operational redundancies. The second means less reliable lead times and less certain demand scenarios. In addition, the paper looks at how companies should organize to meet those challenges efficiently and suggests a new public-private partnership. While the paper is focused on the US, it has worldwide implications.
Vehicle routing with soft time windows and stochastic travel times: A column generation and branch-and-price solution approach

We study a vehicle routing problem with soft time windows and stochastic travel times. In this problem, we consider stochastic travel times to obtain routes which are both efficient and reliable. In our problem setting, soft time windows allow early and late servicing at customers by incurring some penalty costs. The objective is to minimize the sum of transportation costs and service costs. Transportation costs result from three elements which are the total distance traveled, the number of vehicles used and the total expected overtime of the drivers. Service costs are incurred for early and late arrivals; these correspond to time-window violations at the customers. We apply a column generation procedure to solve this problem. The master problem can be modeled as a classical set partitioning problem. The pricing subproblem, for each vehicle, corresponds to an elementary shortest path problem with resource constraints. To generate an integer solution, we embed our column generation procedure within a branch-and-price method. Computational results obtained by experimenting with well-known problem instances are reported.
A Digital Clock and Data Recovery Architecture for Multi-Gigabit/s Binary Links

In this tutorial paper, we present a general architecture for digital clock and data recovery (CDR) for high-speed binary links. The architecture is based on replacing the analog loop filter and voltage-controlled oscillator (VCO) in a typical analog phase-locked loop (PLL)-based CDR with digital components. We provide a linearized analysis of the bang-bang phase detector and CDR loop including the effects of decimation and self-noise. Additionally, we provide measured results from an implementation of the digital CDR system which are directly comparable to the linearized analysis, plus measurements of the limit cycle behavior which arises in these loops when incoming jitter is small. Finally, the relative advantages of analog and digital implementations of the CDR for high-speed binary links is considered
Energy- and endurance-aware design of phase change memory caches

Phase change memory (PCM) is one of the most promising technology among emerging non-volatile random access memory technologies. Implementing a cache memory using PCM provides many benefits such as high density, non-volatility, low leakage power, and high immunity to soft error. However, its disadvantages such as high write latency, high write energy, and limited write endurance prevent it from being used as a drop-in replacement of an SRAM cache. In this paper, we study a set of techniques to design an energy- and endurance-aware PCM cache. We also modeled the timing, energy, endurance, and area of PCM caches and integrated them into a PCM cache simulator to evaluate the techniques. Experiments show that our PCM cache design can achieve 8% of energy saving and 3.8 years of lifetime compared with a baseline PCM cache having less than a hour of lifetime.
Study on the feasibility of LoRaWAN for smart city applications

Recent research on Low Power Wide Area Network (LPWAN) technologies which provide the capability of serving massive low power devices simultaneously has been very attractive. The LoRaWAN standard is one of the most successful developments. Commercial pilots are seen in many countries around the world. However, the feasibility of large scale deployments, for example, for smart city applications need to be further investigated. This paper provides a comprehensive case study of LoRaWAN to show the feasibility, scalability, and reliability of LoRaWAN in realistic simulated scenarios, from both technical and economic perspectives. We develop a Matlab based LoRaWAN simulator to offer a software approach of performance evaluation. A practical LoRaWAN network covering Greater London area is implemented. Its performance is evaluated based on two typical city monitoring applications. We further present an economic analysis and develop business models for such networks, in order to provide a guideline for commercial network operators, IoT vendors, and city planners to investigate future deployments of LoRaWAN for smart city applications.
Learning to Draw Samples with Amortized Stein Variational Gradient Descent

We propose a simple algorithm to train stochastic neural networks to draw samples from given target distributions for probabilistic inference. Our method is based on iteratively adjusting the neural network parameters so that the output changes along a Stein variational gradient direction (Liu & Wang, 2016) that maximally decreases the KL divergence with the target distribution. Our method works for any target distribution specified by their unnormalized density function, and can train any black-box architectures that are differentiable in terms of the parameters we want to adapt. We demonstrate our method with a number of applications, including variational autoencoder (VAE) with expressive encoders to model complex latent space structures, and hyper-parameter learning of MCMC samplers that allows Bayesian inference to adaptively improve itself when seeing more data.
Quantification of five neuropsychological approaches to defining mild cognitive impairment.

Operational definitions of cognitive impairment have varied widely in diagnosing mild cognitive impairment (MCI). Identifying clinical subtypes of MCI has further challenged diagnostic approaches because varying the components of the objective cognitive assessment can significantly impact diagnosis. Therefore, the authors investigated the applicability of diagnostic criteria for clinical subtypes of MCI in a naturalistic research sample of community elders and quantified the variability in diagnostic outcomes that results from modifying the neuropsychological definition of objective cognitive impairment.



Cross-sectional and longitudinal study.



San Diego, CA, Veterans Administration Hospital.



Ninety nondemented, neurologically normal, community-dwelling older adults were initially assessed and 73 were seen for follow-up approximately 17 months later.



Participants were classified via consensus diagnosis as either normally aging or having MCI via each of the five diagnostic strategies, which varied the cutoff for objective impairment and the number of neuropsychological tests considered in the diagnostic process.



A range of differences in the percentages identified as MCI versus cognitively normal were demonstrated, ranging from 10-74%, depending on the classification criteria used. A substantial minority of individuals demonstrated diagnostic instability over time and across diagnostic approaches. The single domain nonamnestic subtype diagnosis was particularly unstable (e.g., prone to reclassification as normal at follow up).



Our findings provide empirical support for a neuropsychologically derived operational definition of clinical subtypes of MCI and point to the importance of using comprehensive neuropsychological assessments. Diagnoses, particularly involving nonamnestic MCI, were variable over time. The applicability and utility of this particular MCI subtype warrants further investigation.
Overview of the ImageCLEF 2018 Caption Prediction Tasks

The caption prediction task is in 2018 in its second edition after the task was first run in the same format in 2017. For 2018 the database was more focused on clinical images to limit diversity. As automatic methods with limited manual control were used to select images, there is still an important diversity remaining in the image data set. Participation was relatively stable compared to 2017. Usage of external data was restricted in 2018 to limit critical remarks regarding the use of external resources by some groups in 2017. Results show that this is a difficult task but that large amounts of training data can make it possible to detect the general topics of an image from the biomedical literature. For an even better comparison it seems important to filter the concepts for the images that are made available. Very general concepts (such as “medical image”) need to be removed, as they are not specific for the images shown, and also extremely rare concepts with only one or two examples can not really be learned. Providing more coherent training data or larger quantities can also help to learn such complex models.
Student engagement and its relationship with early high school dropout.

Although the concept of school engagement figures prominently in most school dropout theories, there has been little empirical research conducted on its nature and course and, more importantly, the association with dropout. Information on the natural development of school engagement would greatly benefit those interested in preventing student alienation during adolescence. Using a longitudinal sample of 11,827 French-Canadian high school students, we tested behavioral, affective, cognitive indices of engagement both separately and as a global construct. We then assessed their contribution as prospective predictors of school dropout using factor analysis and structural equation modeling. Global engagement reliably predicted school dropout. Among its three specific dimensions, only behavioral engagement made a significant contribution in the prediction equation. Our findings confirm the robustness of the overall multidimensional construct of school engagement, which reflects both cognitive and psychosocial characteristics, and underscore the importance attributed to basic participation and compliance issues in reliably estimating risk of not completing basic schooling during adolescence.
Large-Scale Study of Curiosity-Driven Learning

Reinforcement learning algorithms rely on carefully engineering environment rewards that are extrinsic to the agent. However, annotating each environment with hand-designed, dense rewards is not scalable, motivating the need for developing reward functions that are intrinsic to the agent. Curiosity is a type of intrinsic reward function which uses prediction error as reward signal. In this paper: (a) We perform the first large-scale study of purely curiosity-driven learning, i.e. without any extrinsic rewards, across 54 standard benchmark environments, including the Atari game suite. Our results show surprisingly good performance, and a high degree of alignment between the intrinsic curiosity objective and the handdesigned extrinsic rewards of many game environments. (b) We investigate the effect of using different feature spaces for computing prediction error and show that random features are sufficient for many popular RL game benchmarks, but learned features appear to generalize better (e.g. to novel game levels in Super Mario Bros.). (c) We demonstrate limitations of the prediction-based rewards in stochastic setups. Game-play videos and code are at https://pathak22.github. io/large-scale-curiosity/.
Biotechnological production of flavours and fragrances

The biotechnological generation of natural aroma compounds is rapidly expanding. Aroma chemicals, such as vanillin, benzaldehyde (bitter almond, cherry) and 4-(R)-decanolide (fruity–fatty) are marketed on a scale of several thousand tons per year. Their possible production by single-step biotransformations, bioconversions and de novo synthesis using microorganisms, plant cells or isolated enzymes is shown. The perspectives of bioprocesses for the oxifunctionalisation of lower terpenes by genetically modified organisms and economic aspects are discussed.
Sequence to Logic with Copy and Cache

Generating logical form equivalents of human language is a fresh way to employ neural architectures where long shortterm memory effectively captures dependencies in both encoder and decoder units. The logical form of the sequence usually preserves information from the natural language side in the form of similar tokens, and recently a copying mechanism has been proposed which increases the probability of outputting tokens from the source input through decoding. In this paper we propose a caching mechanism as a more general form of the copying mechanism which also weighs all the words from the source vocabulary according to their relation to the current decoding context. Our results confirm that the proposed method achieves improvements in sequence/token-level accuracy on sequence to logical form tasks. Further experiments on cross-domain adversarial attacks show substantial improvements when using the most influential examples of other domains for training.