nils-herrmann/clean_scirepeval huggingface dataset:
Development of Standard Operational Procedures for Bacterial Management in Marine Fish Hatcheries

of a thesis at the University of Miami. Thesis supervised by Professor Larry Brand. No. of pages in text. (43) Live feeds are utilized in marine fish hatcheries to feed and promote the health of finfish larvae due to their nutritional advantages. The presence of detrimental bacteria in rotifer culture can cause disease outbreaks in larval rearing. Nevertheless, the use of UV application to disinfect seawater is not very effective to eliminate and inactivate all pathogenic agents presented in the raw surface water. To investigate new methods of disinfection, two experiments were conducted at the University of Miami Experimental Hatchery (UMEH) to quantify and test for antibiotic susceptibility for Vibrio spp. and the total coliforms by using plate counting method and treating with two water-soluble antibiotics, Tobramycin and Minocycline, at concentrations of 30 μg/mL, 100 μg/mL and 200 μg/mL. In the first experiment, water samples from Virginia Key Bear Cut, Florida were collected from five locations beginning from surface water, settling tank, sand filter, after a 120 watts UV instrument and after a 80 watts UV instrument respectively. No fecal coliform colonies were observed by plate counting method after UV disinfections, implying a complete inactivation by UV irradiation, but V. vulnificus, V. parahaemolyticus and
Towards a Multi-cluster Analytical Engine for Transportation Data

In the new digital age, the pace and volume of growing transportation related data is exceeding our ability to manage and analyze it. In this position paper, we present a data engine, Godzilla, to ingest real-time traffic data and support analytic and data mining over traffic data. Godzilla is a multi-cluster approach to handle large volumes of growing data, changing workloads and varying number of users. The data originates at multiple sources, and consists of multiple types. Meanwhile, the workloads belong to three camps, namely batch processing, interactive queries and graph analysis. Godzilla support multiple language abstractions from scripting to SQL-like language.
Chronic Bacterial Sialadenitis-A Case Report

Sialadenitis is an acute infection of the salivary glands. The parotid gland is most commonly affected by inflammation. Staphylococcus aureus is the most common pathogen associated with acute parotitis. Inflammatory changes in the ducts are known as sialodochitis. Inflammatory diseases of the salivary glands (Sialadenitis). Here we report a case of recurrent bacterial sialadenitis in a 45year-old female patient on the left lower third of her face.
Suspicion of money laundering reporting obligations : Auditor compliance , or sceptical failure to engage ?

Money laundering has become of increasing concern to law makers in recent years, principally because of its associations with terrorism. Recent legislative changes in the United Kingdom mean that auditors risk becoming state law enforcement agents in the private sector. We examine this legislation from the perspective of the changing nature of the relationship between auditors and the state, and the surveillant assemblage within which this is located. Auditors are statutorily obliged to file Suspicious Activity Reports (SARs) into an online database, ELMER, but without much guidance regarding how suspicion is determined. Criminal rather than civil or regulatory sanctions apply to auditors’ instances of non-compliance. This paper evaluates the surveillance implications of the legislation for auditors through lenses developed in the accounting and sociological literature by Brivot andGendron, Neu andHeincke, Deleuze and Guattari, and Haggerty and Ericson. It finds that auditors are generating information flows which are subsequently reassembled into discrete and virtual ‘data doubles’ to be captured and utilised by authorised third parties for unknown purposes. The paper proposes that the surveillant assemblage has extended into the space of the auditor-client relationship, but this extension remains inhibited as a result of auditors’ relatively weak level of engagement in providing SARs, thereby pointing to a degree of resistance in professional service firms regarding the deployment of regulation that compromises the foundations of this
The structure of DNA in the nucleosome core

The 1.9-Å-resolution crystal structure of the nucleosome core particle containing 147 DNA base pairs reveals the conformation of nucleosomal DNA with unprecedented accuracy. The DNA structure is remarkably different from that in oligonucleotides and non-histone protein–DNA complexes. The DNA base-pair-step geometry has, overall, twice the curvature necessary to accommodate the DNA superhelical path in the nucleosome. DNA segments bent into the minor groove are either kinked or alternately shifted. The unusual DNA conformational parameters induced by the binding of histone protein have implications for sequence-dependent protein recognition and nucleosome positioning and mobility. Comparison of the 147-base-pair structure with two 146-base-pair structures reveals alterations in DNA twist that are evidently common in bulk chromatin, and which are of probable importance for chromatin fibre formation and chromatin remodelling.
Computer Security Incident Response Team Effectiveness: A Needs Assessment

Computer security incident response teams (CSIRTs) respond to a computer security incident when the need arises. Failure of these teams can have far-reaching effects for the economy and national security. CSIRTs often have to work on an ad hoc basis, in close cooperation with other teams, and in time constrained environments. It could be argued that under these working conditions CSIRTs would be likely to encounter problems. A needs assessment was done to see to which extent this argument holds true. We constructed an incident response needs model to assist in identifying areas that require improvement. We envisioned a model consisting of four assessment categories: Organization, Team, Individual and Instrumental. Central to this is the idea that both problems and needs can have an organizational, team, individual, or technical origin or a combination of these levels. To gather data we conducted a literature review. This resulted in a comprehensive list of challenges and needs that could hinder or improve, respectively, the performance of CSIRTs. Then, semi-structured in depth interviews were held with team coordinators and team members of five public and private sector Dutch CSIRTs to ground these findings in practice and to identify gaps between current and desired incident handling practices. This paper presents the findings of our needs assessment and ends with a discussion of potential solutions to problems with performance in incident response.
A privacy-preserving framework for outsourcing location-based services to the cloud

Thanks to the popularity of mobile devices a large number of location-based services (LBS) have emerged. While a large number of privacy-preserving solutions for LBS have been proposed, most of these solutions do not consider the fact that LBS are typically cloud-based nowadays. Outsourcing data and computation to the cloud raises a number of significant challenges related to data confidentiality, user identity and query privacy, fine-grain access control, and query expressiveness. In this work, to the best of our knowledge, we propose the first privacy-preserving outsourced LBS system supporting continuous access control, multi-location queries, and per-query privacy limit. The proposed framework also supports search by location attributes in addition to locations themselves. We provide a security analysis to show that the proposed scheme preserves privacy in the presence of different threats. We also show the viability of our proposed solution and scalability with the number of locations through an experimental evaluation, using a real-life OpenStreetMap dataset.
HEART RATE VALUES AND LEVELS OF ATTENTION AND RELAXATION IN EXPERT ARCHERS DURING SHOOTING

The main purpose of this paper was to present single channel EEG records and heart rate (HR) changes during shooting routine of 8 experienced archers. Possible differences between recurve and compound shooters in named values were investigated in accordance to arrow score. Additional contribution of this study was systematical review of psychophysiological studies done in archery. Descriptive statistics revealed that compound shooters achieved higher arrow score values, had higher heart rate values pre, during and post shooting, had higher attention values pre, during and post shooting and very similar meditation values pre, during and post shooting according to recurve shooters. ANOVA showed significant differences (p<0,01) between compound shooters and recurve shooters in variables of arrow score, all heart rate and attention level variables, except ones concerning meditation levels. Overall, the obtained results were interesting and can serve as a starting ground for future experiments in order to reach valid and concrete biofeedback data that will support archery excellence.
3D bioprinting for engineering complex tissues.

Bioprinting is a 3D fabrication technology used to precisely dispense cell-laden biomaterials for the construction of complex 3D functional living tissues or artificial organs. While still in its early stages, bioprinting strategies have demonstrated their potential use in regenerative medicine to generate a variety of transplantable tissues, including skin, cartilage, and bone. However, current bioprinting approaches still have technical challenges in terms of high-resolution cell deposition, controlled cell distributions, vascularization, and innervation within complex 3D tissues. While no one-size-fits-all approach to bioprinting has emerged, it remains an on-demand, versatile fabrication technique that may address the growing organ shortage as well as provide a high-throughput method for cell patterning at the micrometer scale for broad biomedical engineering applications. In this review, we introduce the basic principles, materials, integration strategies and applications of bioprinting. We also discuss the recent developments, current challenges and future prospects of 3D bioprinting for engineering complex tissues. Combined with recent advances in human pluripotent stem cell technologies, 3D-bioprinted tissue models could serve as an enabling platform for high-throughput predictive drug screening and more effective regenerative therapies.
Open Set Domain Adaptation by Backpropagation

Numerous algorithms have been proposed for transferring knowledge from a label-rich domain (source) to a label-scarce domain (target). Most of them are proposed for closed-set scenario, where the source and the target domain completely share the class of their samples. However, in practice, a target domain can contain samples of classes that are not shared by the source domain. We call such classes the “unknown class” and algorithms that work well in the open set situation are very practical. However, most existing distribution matching methods for domain adaptation do not work well in this setting because unknown target samples should not be aligned with the source. In this paper, we propose a method for an open set domain adaptation scenario, which utilizes adversarial training. This approach allows to extract features that separate unknown target from known target samples. During training, we assign two options to the feature generator: aligning target samples with source known ones or rejecting them as unknown target ones. Our method was extensively evaluated and outperformed other methods with a large margin in most settings.
Finding a biosignature for melancholic depression.

Melancholia is typified by features of psychomotor slowing, anxiety, appetite loss and sleep changes. It is usually observed in 20-30% of individuals meeting diagnostic criteria for major depressive disorder (MDD). There is currently no agreement on whether melancholic MDD represents a distinct entity defined by neurobiological as well as clinical features or, rather, a specifier for MDD. This situation is reflected in the revisions to DSM, including in the DSM-5 due for release in 2013. With this context in mind, the authors review the origins of the construct of melancholia in MDD, its theoretical grounding and the defining characteristics that arose from this research. The authors then outline the state of knowledge on the neurobiology of melancholia. This second aspect is illustrative of the National Institutes of Mental Health's research domain criteria initiative, which offers a framework for redefining constructs along neurobiological dimensions. The authors also consider the outlook for identifying a useful biosignature of melancholia.
Dynamic Video Stitching via Shakiness Removing

Stitching videos captured by hand-held mobile cameras can essentially enhance entertainment experience of ordinary users. However, such videos usually contain heavy shakiness and large parallax, which are challenging to stitch. In this paper, we propose a novel approach of video stitching and stabilization for videos captured by mobile devices. The main component of our method is a unified video stitching and stabilization optimization that computes stitching and stabilization simultaneously rather than does each one individually. In this way, we can obtain the best stitching and stabilization results relative to each other without any bias to one of them. To make the optimization robust, we propose a method to identify background of input videos, and also common background of them. This allows us to apply our optimization on background regions only, which is the key to handle large parallax problem. Since stitching relies on feature matches between input videos, and there inevitably exist false matches, we thus propose a method to distinguish between right and false matches, and encapsulate the false match elimination scheme and our optimization into a loop, to prevent the optimization from being affected by bad feature matches. We test the proposed approach on videos that are causally captured by smartphones when walking along busy streets, and use stitching and stability scores to evaluate the produced panoramic videos quantitatively. Experiments on a diverse of examples show that our results are much better than (challenging cases) or at least on par with (simple cases) the results of previous approaches.
A Technology Review of Smart Sensors With Wireless Networks for Applications in Hazardous Work Environments

Workers in hazardous environments such as mining are constantly exposed to the health and safety hazards of dynamic and unpredictable conditions. One approach to enable them to manage these hazards is to provide them with situational awareness: real-time data (environmental, physiological, and physical location data) obtained from wireless, wearable, smart sensor technologies deployed at the work area. The scope of this approach is limited to managing the hazards of the immediate work area for prevention purposes; it does not include technologies needed after a disaster. Three critical technologies emerge and converge to support this technical approach: smart-wearable sensors, wireless sensor networks, and low-power embedded computing. The major focus of this report is on smart sensors and wireless sensor networks. Wireless networks form the infrastructure to support the realization of situational awareness; therefore, there is a significant focus on wireless networks. Lastly, the “Future Research” section pulls together the three critical technologies by proposing applications that are relevant to mining. The applications are injured miner (person-down) detection; a wireless, wearable remote viewer; and an ultrawide band smart environment that enables localization and tracking of humans and resources. The smart environment could provide location data, physiological data, and communications (video, photos, graphical images, audio, and text messages). Electrical engineer, Pittsburgh Research Laboratory, National Institute for Occupational Safety and Health, Pittsburgh, PA. President, The Designer-III Co., Franklin, PA. General engineer, Pittsburgh Research Laboratory (now with the National Personal Protective Technology Laboratory), National Institute for Occupational Safety and Health, Pittsburgh, PA. Supervisory general engineer, Pittsburgh Research Laboratory, National Institute for Occupational Safety and Health, Pittsburgh, PA.
Assembly process and reliability assessment of TSV/RDL/IPD interposer with multi-chip-stacking for 3D IC integration SiP

In this study, a 3D IC integration system-in-package (SiP) with TSV/RDL/IPD interposer is designed and developed. Emphasis is placed on the Cu revealing, embedded stress sensors, non-destructive inspection, thermal modeling and measurement, and final assembly and reliability assessments.
A vision-based system for automatic hand washing quality assessment

Hand washing is a critical activity in preventing the spread of infection in health-care environments and food preparation areas. Several guidelines recommended a hand washing protocol consisting of six steps that ensure that all areas of the hands are thoroughly cleaned. In this paper, we describe a novel approach that uses a computer vision system to measure the user’s hands motions to ensure that the hand washing guidelines are followed. A hand washing quality assessment system needs to know if the hands are joined or separated and it has to be robust to different lighting conditions, occlusions, reflections and changes in the color of the sink surface. This work presents three main contributions: a description of a system which delivers robust hands segmentation using a combination of color and motion analysis, a single multi-modal particle filter (PF) in combination with a k-means-based clustering technique to track both hands/arms, and the implementation of a multi-class classification of hand gestures using a support vector machine ensemble. PF performance is discussed and compared with a standard Kalman filter estimator. Finally, the global performance of the system is analyzed and compared with human performance, showing an accuracy close to that of human experts.
Autonomous vehicle navigation using evolutionary reinforcement learning

Reinforcement learning schemes perform direct on-line search in control space. This makes them appropriate for modifying control rules to obtain improvements in the performance of a system. The effectiveness of a reinforcement learning strategy is studied here through the training of a learning classz$er system (LCS) that controls the movement of an autonomous vehicle in simulated paths including left and right turns. The LCS comprises a set of conditionaction rules (classifiers) that compete to control the system and evolve by means of a genetic algorithm (GA). Evolution and operation of classifiers depend upon an appropriate credit assignment mechanism based on reinforcement learning. Different design options and the role of various parameters have been investigated experimentally. The performance of vehicle movement under the proposed evolutionary approach is superior compared with that of other (neural) approaches based on reinforcement learning that have been applied previously to the same benchmark problem.
An Interleaved Full Nyquist High-Speed DAC Technique

A 9 bit 11 GS/s DAC is presented that achieves an SFDR of more than 50 dB across Nyquist and IM3 below -50 dBc across Nyquist. The DAC uses a two-times interleaved architecture to suppress spurs that typically limit DAC performance. Despite requiring two current-steering DACs for the interleaved architecture, the relative low demands on performance of these sub-DACs imply that they can be implemented in an area and power efficient way. Together with a quad-switching architecture to decrease demands on the power supply and bias generation and employing the multiplexer switches in triode, the total core area is only 0.04 mm 2 while consuming 110 mW from a single 1.0 V supply.
An Empirical Study of Investigating Mobile Applications Development Challenges

mobile application development is rapidly evolving with substantial economic and scientific interest. One of the primary reasons for mobile application development failure is the increasing number of mobile platforms; some organizations endorse mobile application development before understanding the associated development challenges of each target platform.  the objective of this paper is to identify the challenges of native, web, and hybrid mobile applications, which can undermine the successful development of such applications.  we adopted a two-phase research approach: at first, the challenges were identified via a systematic literature review (SLR); and then, the identified challenges were validated through conducting interviews with practitioners.  through both research approaches, we identified nine challenges vital to the success of mobile application development and four additional challenges from interviews not reported in the literature. A comparison of the challenges (native, web, and hybrid) identified in SLR indicates that there are slightly more differences than similarities between the challenges. On the other hand, the challenges (native, web, and hybrid) identified in interviews indicates that there are more similarities than differences between the challenges. Our results show a weak negative correlation between the ranks obtained from the SLR and the interviews (<inline-formula> <tex-math notation="LaTeX">$[rs(9) = -.034]$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$p = 0.932$ </tex-math></inline-formula>). The results obtained from our t-test (i.e., <inline-formula> <tex-math notation="LaTeX">$t = 0.868, p = 0.402 > 0.05$ </tex-math></inline-formula>) depicts that there is no significant difference between the findings of SLR and interviews.  mobile application development organizations should try to address the identified challenges when developing mobile applications (native, web, or hybrid) to increase the probability of mobile application success.
A Stretchable Multimodal Sensor for Soft Robotic Applications

This paper presents the design, fabrication, and characterization of a multimodal sensor with integrated stretchable meandered interconnects for uniaxial strain, pressure, and uniaxial shear stress measurements. It is designed based on a capacitive sensing principle for embedded deformable sensing applications. A photolithographic process is used along with laser machining and sheet metal forming technique to pattern sensor elements together with stretchable grid-based interconnects on a thin sheet of copper polyimide laminate as a base material in a single process. The structure is embedded in a soft stretchable Ecoflex and PDMS silicon rubber encapsulation. The strain, pressure, and shear stress sensors are characterized up to 9%, 25 kPa, and ±11 kPa of maximum loading, respectively. The strain sensor exhibits an almost linear response to stretching with an average sensitivity of −28.9 fF%−1. The pressure sensor, however, shows a nonlinear and significant hysteresis characteristic due to nonlinear and viscoelastic property of the silicon rubber encapsulation. An average best-fit straight line sensitivity of 30.9 fFkPa−1 was recorded. The sensitivity of shear stress sensor is found to be 8.1 fFkPa−1. The three sensing elements also demonstrate a good cross-sensitivity performance of 3.1% on average. This paper proves that a common flexible printed circuit board (PCB) base material could be transformed into stretchable circuits with integrated multimodal sensor using established PCB fabrication technique, laser machining, and sheet metal forming method.