nils-herrmann/clean_scirepeval huggingface dataset:
TRAUMATIC STRESS AND QUALITY OF ATTACHMENT: REALITY AND INTERNALIZATION IN DISORDERS OF INFANT MENTAL HEALTH

This article describes the interface between the fields of attachment and child trauma, their respective contributions to an understanding of infant mental health disturbances, and the clinical applications of an integration between attachment theory and trauma-informed treatment and research. The organizing theme is that a dual attachment and trauma lens must be used in the assessment and treatment of infants and toddlers with mental health and relationship problems. The quality of attachment is an important factor in children’s capacity to process and resolve traumatic experiences. At the same time, traumatic events often have a damaging effect on the quality of existing attachments by introducing unmanageable stress in the infant–parent relationship. It is argued that trauma in the first years of life needs to be assessed and treated in the context of the child’s primary attachments. Reciprocally, the etiology of attachment disturbances should include an assessment of possible exposure to trauma in the child and in the parents. Current conceptualizations of attachment and trauma are reviewed from this perspective, and a clinical illustration is presented to highlight how a traumatic stressor can trigger behaviors reminiscent of disorganized attachment.  Este artı ́culo describe la relacio ́n antre los campos de la afectividad y el trauma infantil, sus respectivas contribuciones a la comprensio ́ de los trastornos de salud mental infantil, y las aplicaciones clı́nicas de una integracio ́n entre la teorı ́a de la afectividad y el tratamiento de informacio ́n del trauma, y la investigacio ́n. El tema central es que un lente doble de afectividad y trauma debe usarse en la evaluacio ́n y tratamiento de infantes y bebe ́s que presentan problemas en cuanto a su salud mental y sus relaciones afectivas. La calidad de la afectividad es un factor importante en la capacidad de los nin ̃os para procesar y resolver experiencias trauma ́ticas. Al mismo tiempo, los hechos trauma ́ticos a menudo le causan dan ̃o a la calidad de las existentes relaciones afectivas, ya que introducen tensiones difı ́cil e sobrellevar en la relación entre el infante y su madre o padre. Se sostiene que el trauma en los primeros an ̃os de vida necesita ser evaluado y tratado dentro del contexto de las relaciones afectivas primarias del nin ̃o. Recı ́procamente, la etiologı ́a de los trastornos de la afectividad debe incluir una evaluacio ́n del haber estado posiblemente expuesto al trauma, tanto en el caso del nin ̃o como de sus padres. Las conceptualizaciones actuales de la afectividad y el trauma se revisan desde esta perspectiva, y se presenta una ilustracio ́n clı́nica para subrayar co ́mo una situacio ́n traumática de estre ́s puede dar origen a conductas que son reminiscentes de relaciones afectivas desorganizadas. Direct correspondence to: Alicia F. Lieberman, San Francisco General Hospital, Building 20, Suite 2100, 1001 Potrero Avenue, San Francisco, CA 94110; . Traumatic Stress and Attachment Quality ● 337 IMHJ (Wiley) RIGHT
An Empirical Study on Mutation, Statement and Branch Coverage Fault Revelation That Avoids the Unreliable Clean Program Assumption

Many studies suggest using coverage concepts, such as branch coverage, as the starting point of testing, while others as the most prominent test quality indicator. Yet the relationship between coverage and fault-revelation remains unknown, yielding uncertainty and controversy. Most previous studies rely on the Clean Program Assumption, that a test suite will obtain similar coverage for both faulty and fixed ('clean') program versions. This assumption may appear intuitive, especially for bugs that denote small semantic deviations. However, we present evidence that the Clean Program Assumption does not always hold, thereby raising a critical threat to the validity of previous results. We then conducted a study using a robust experimental methodology that avoids this threat to validity, from which our primary finding is that strong mutation testing has the highest fault revelation of four widely-used criteria. Our findings also revealed that fault revelation starts to increase significantly only once relatively high levels of coverage are attained.
Comparative Stability Analysis of Droop Control Approaches in Voltage-Source-Converter-Based DC Microgrids

Droop control has been widely applied in dc microgrids (MGs) due to its inherent modularity and ease of implementation. Among the different droop control methods that can be adopted in dc MGs, two options have been considered in this paper: I-V and V-I droop. I-V droop controls the dc current depending on the dc voltage while V-I droop regulates the dc voltage based on the output current. The paper proposes a comparative study of V-I/I-V droop control approaches in dc MGs focusing on steady-state power-sharing performance and stability. The paper presents the control scheme for current-mode (I-V droop) and voltage-mode ( V-I droop) systems, derives the corresponding output impedance of the source subsystem, including converters dynamics, and analyzes the stability of the power system when supplying constant power loads. The paper first investigates the impact on stability of the key parameters including droop gains, local control loop dynamics, and number of sources and then performs a comparison between current-mode and voltage-mode systems in terms of stability. In addition, a generalized analytical impedance model of a multisource, multiload power system is presented to investigate stability in a more realistic scenario. For this purpose, the paper proposes the concept of “global droop gain” as an important factor to determine the stability behaviour of a parallel sources based dc system. The theoretical analysis has been validated with experimental results from a laboratory-scale dc MG.
All-To-All Broadcast in Hexagonal Torus Networks On-Chip

Hexagonal torus networks are special family of Eisenstein-Jacobi (EJ) networks which have gained popularity as good candidates network On-Chip (NoC) for interconnecting Multiprocessor System-on-Chips (MPSoCs). They showed better topological properties compared to the 2D torus networks with the same number of nodes. All-to-all broadcast is a collective communication algorithm used frequently in some parallel applications. Recently, an off-chip all-to-all broadcast algorithm has been proposed for hexagonal torus networks assuming half-duplex links and all-ports communication. The proposed all-to-all broadcast algorithm does not achieve the minimum transmission time and requires 24 kextra buffers, where kis the network diameter. We first extend this work by proposing an efficient all-to-all broadcast on hexagonal torus networks under full-duplex links and all-ports communications assumptions which achieves the minimum transmission delay but requires 36 k extra buffers per router. In a second stage, we develop a new all-to-all broadcast more suitable for hexagonal torus network on-chip that achieves optimal transmission delay time without requiring any extra buffers per router. By reducing the amount of buffer space, the new all-to-all broadcast reduces the routers cost which is an important issue in NoCs architectures.
A Statistical Approach to Detect Jamming Attacks in Wireless Sensor Networks

Wireless Sensor Networks (WSNs), in recent times, have become one of the most promising network solutions with a wide variety of applications in the areas of agriculture, environment, healthcare and the military. Notwithstanding these promising applications, sensor nodes in WSNs are vulnerable to different security attacks due to their deployment in hostile and unattended areas and their resource constraints. One of such attacks is the DoS jamming attack that interferes and disrupts the normal functions of sensor nodes in a WSN by emitting radio frequency signals to jam legitimate signals to cause a denial of service. In this work we propose a step-wise approach using a statistical process control technique to detect these attacks. We deploy an exponentially weighted moving average (EWMA) to detect anomalous changes in the intensity of a jamming attack event by using the packet inter-arrival feature of the received packets from the sensor nodes. Results obtained from a trace-driven simulation show that the proposed solution can efficiently and accurately detect jamming attacks in WSNs with little or no overhead.
Exploring Demographic Language Variations to Improve Multilingual Sentiment Analysis in Social Media

Different demographics, e.g., gender or age, can demonstrate substantial variation in their language use, particularly in informal contexts such as social media. In this paper we focus on learning gender differences in the use of subjective language in English, Spanish, and Russian Twitter data, and explore cross-cultural differences in emoticon and hashtag use for male and female users. We show that gender differences in subjective language can effectively be used to improve sentiment analysis, and in particular, polarity classification for Spanish and Russian. Our results show statistically significant relative F-measure improvement over the gender-independent baseline 1.5% and 1% for Russian, 2% and 0.5% for Spanish, and 2.5% and 5% for English for polarity and subjectivity classification.
Hypopigmented mycosis fungoides versus mycosis fungoides with concomitant hypopigmented lesions: same disease or different variants of mycosis fungoides?

Hypopigmented mycosis fungoides (HMF) is a rare subtype of mycosis fungoides (MF). We compared patients with exclusive hypopigmented lesions with a group of MF patients with concomitant different lesions.



20 patients with HMF only and 14 patients with hypopigmented lesions concomitant with other types of lesions (mixed MF, MMF) were selected. Clinical-epidemiological analysis as well as histological and immunohistochemical studies were performed.



HMF and MMF preserve some similarities, like predilection for dark-skinned persons and slow progression, but they also present differences: the exclusive variant is associated with early onset and a clear CD8+ immunophenotype, whereas MMF patients tend to present a predominance of CD4+ cell infiltrates. Histological analysis revealed similar findings; relapsing courses were common.



Whether patients are suffering from exclusive HMF or MMF, the presence of hypopigmented lesions can be considered a marker of good prognosis in MF, since both groups presented similar data, such as staging and disease duration.
Towards Verifiably Ethical Robot Behaviour

Ensuring that autonomous systems work ethically is both complex and difficult. However, the idea of having an additional ‘governor’ that assesses options the system has, and prunes them to select the most ethical choices is well understood. Recent work has produced such a governor consisting of a ‘consequence engine’ that assesses the likely future outcomes of actions then applies a Safety/Ethical logic to select actions. Although this is appealing, it is impossible to be certain that the most ethical options are actually taken. In this paper we extend and apply a well-known agent verification approach to our consequence engine, allowing us to verify the correctness of its ethical decision-making.
Story scripting for automating cinematics and cut-scenes in video games

Storytelling can play a very important role in the success of modern video games. Unfortunately, it can be quite difficult for writers to directly create and integrate story content into games on their own, and they must instead rely upon programmers and others on the development team to implement their stories. This needlessly complicates the game development process, leading to increased costs, more strain on developer time, and loss of creative control and, potentially, story quality as a result. Consequently, tools and supports are necessary to enable writers to generate story content for games directly, with minimal programming or programmer assistance required, if any.
 This paper examines the use of specialized story scripting elements to automate the production of cinematics and cut-scenes for video games. These elements allow writers to specify their stories in a well-defined, structured format that can be acted out automatically by software. This paper discusses these story scripting elements in depth, along with a prototype software engine capable of using these elements for cinematic and cut-scene automation. This paper also presents experiences with using this engine to recreate cinematics and cut-scenes from existing commercial video games.
Vertex reconstruction of neutrino interactions using deep learning

Deep learning offers new tools to improve our understanding of many important scientific problems. Neutrinos are the most abundant particles in existence and are hypothesized to explain the matter-antimatter asymmetry that dominates our universe. Definitive tests of this conjecture require a detailed understanding of neutrino interactions with a variety of nuclei. Many measurements of interest depend on vertex reconstruction — finding the origin of a neutrino interaction using data from the detector, which can be represented as images. Traditionally, this has been accomplished by utilizing methods that identify the tracks coming from the interaction. However, these methods are not ideal for interactions where an abundance of tracks and cascades occlude the vertex region. Manual algorithm engineering to handle these challenges is complicated and error prone. Deep learning extracts rich, semantic features directly from raw data, making it a promising solution to this problem. In this work, deep learning models are presented that classify the vertex location in regions meaningful to the domain scientists improving their ability to explore more complex interactions.
Natural Language Explanations in Human-Collaborative Systems

As autonomous systems and people collaborate more, it is evident that there is an increasing need for systems that are transparent and explicable. Especially in critical decisionmaking applications such as those employed in autonomous vehicles or in-home robotic eldercare, it is important for robots to be coherent and articulate what decisions they are making as well as why they arrived at such decisions. While research has suggested the need for explanations for years [7], there is an increasing interest in explaining machine learning and autonomous behavior. There have been contributions in making classification systems more intelligible (e.g., [6, 10]). In robotics, there has been work in enabling agents to explain task failures [3], to generate task plans that are optimized for explanation [13], and to explain why no plan can be found to begin with . Additionally, there have been contributions towards enabling robots to summarize their experiences and generate natural language descriptions of them [11, 9]. These approaches place emphasis on allowing users to specify their preferences with respect to the level of detail they desire. We also argue that natural language communication is an appealing medium for articulating decision-making for several reasons. First, as robots are increasingly being used by non-expert average users rather than computer science experts, we should aim for interaction modalities that they are most comfortable with including language. Second, natural language affords us the ability to provide rich descriptions and explanations of often-complex robot behavior. However, the richness of natural language also means it can be challenging to generate “good” explanations. We are interested in developing approaches to generating and evaluating natural language explanations of robot behavior in order to improve human-robot collaboration.
Bacteriological Examination of Computer Keyboards and Mouse Devices and their Susceptibility Patterns to Disinfectants

Computers are ubiquitous and have been shown to be contaminated with potentially pathogenic bacteria in some communities. There is no economical way to test all the keyboards and mouse out there, but there are common-sense ways to prevent bacterial contamination or eliminate it if it exists. In this study, swabs specimens were collected from surfaces of 250 computer keyboards and mouse and plated on different bacteriological media. Organisms growing on the media were purified and identified using microbiological standards. It was found that all the tested computer keyboards and mouse devices, were positive for microbial contamination. The percentages of isolated bacteria (Staphylococcus spp., Escherichia spp., Pseudomonas spp. and Bacillus spp.) were 43.3, 40.9, 30.7, 34.1, 18.3, 18.2, 7.7 and 6.8% for computer keyboards and mouse respectively. The isolated bacteria were tested against the 6 different disinfectants (Dettol, Isol, Izal, JIK, Purit and Septol ® ). Antibacterial effects of the disinfectants were also concentration dependent. The agar well diffusion technique for determining Minimum Inhibitory Concentration (MIC) was employed. The Killing rate (K) and Decimal Reduction Time (DRT) of the disinfectants on the organism were also determined. The overall result of this study showed that Dettol ® , followed by JIK ® was highly effective against all the bacterial isolates tested while Septol and Izal ® were least effective. Isol and Purit ® showed moderate antibacterial effects. Keyboards and mouse should be disinfected daily. However, it is recommended that heightened surveillance of the microbial examination of computer keyboards should be undertaken at predetermined intervals.
Intravitreal ranibizumab (Lucentis) for branch retinal vein occlusion-induced macular edema: nine-month results of a prospective study.

The purpose of this study was to evaluate the effect of individualized repeated intravitreal injections of ranibizumab (Lucentis, Genentech, South San Francisco, CA) on visual acuity and central foveal thickness (CFT) for branch retinal vein occlusion-induced macular edema.



This study was a prospective interventional case series. Twenty-eight eyes of 28 consecutive patients diagnosed with branch retinal vein occlusion-related macular edema treated with repeated intravitreal injections of ranibizumab (when CFT was >225 microm) were evaluated. Optical coherence tomography and fluorescein angiography were performed monthly.



The mean best-corrected distance visual acuity improved from 62.67 Early Treatment of Diabetic Retinopathy Study letters (logarithm of the minimum angle of resolution = 0.74 +/- 0.28 [mean +/- standard deviation]) at baseline to 76.8 Early Treatment of Diabetic Retinopathy Study letters (logarithm of the minimum angle of resolution = 0.49 +/- 0.3; statistically significant, P < 0.001) at the end of the follow-up (9 months). The mean letter gain (including the patients with stable and worse visual acuities) was 14.3 letters (2.9 lines). During the same period, 22 of the 28 eyes (78.6%) showed improved visual acuity, 4 (14.2%) had stable visual acuity, and 2 (7.14%) had worse visual acuity compared with baseline. The mean CFT improved from 349 +/- 112 microm at baseline to 229 +/- 44 microm (significant, P < 0.001) at the end of follow-up. A mean of six injections was performed during the follow-up period. Our subgroup analysis indicated that patients with worse visual acuity at presentation (<or=50 letters in our series) showed greater visual benefit from treatment. "Rebound" macular edema was observed in 5 patients (17.85%) at the 3-month follow-up visit and in none at the 6- and 9-month follow-ups. In 18 of the 28 patients (53.6%), the CFT was <225 microm at the last follow-up visit, and therefore, further treatment was not instituted. No ocular or systemic side effects were noted.



Individualized repeated intravitreal injections of ranibizumab showed promising short-term results in visual acuity improvement and decrease in CFT in patients with macular edema associated with branch retinal vein occlusion. Further studies are needed to prove the long-term effect of ranibizumab treatment on patients with branch retinal vein occlusion.
An empirical validation of a unified model of electronic government adoption (UMEGA)

a Emerging Markets Research Centre (EMaRC), School of Management, Swansea University Bay Campus, Fabian Way, Swansea SA1 8EN, Wales, UK b Section of Information & Communication Technology, Faculty of Technology, Policy, and Management, Delft University of Technology, The Netherlands c Nottingham Business School, Nottingham Trent University, UK d School of Management, Swansea University Bay Campus, Fabian Way, Swansea SA1 8EN, Wales, UK e School of Management, Swansea University Bay Campus, Fabian Way, Crymlyn Burrows, Swansea, SA1 8EN, Wales, UK
Introducing The Neuroscience Gateway

Last few decades have seen the emergence of computational neuroscience as a mature field where researchers are interested in modeling complex and large neuronal systems and require access to high performance computing machines and associated cyberinfrastructure to manage computational workflow and data. The neuronal simulation tools, used in this research field, are also implemented for parallel computers and suitable for high performance computing machines. But using these tools on complex high performance computing machines remain a challenge due to issues with acquiring computer time on these machines located at national supercomputer centers, dealing with complex user interface of these machines, dealing with data management and retrieval. The Neuroscience Gateway is being developed to alleviate all of these barriers to entry for computational neuroscientist. It hides or eliminates, from the point of view of the users, all the administrative and technical barriers and makes parallel neuronal simulation tools easily available and accessible on complex high performance computing machines and handles the running of jobs and data management and retrieval. This paper describes the architecture it is based on, how it is implemented, and how users can use this for computational neuroscience research using high performance computing at the back end. computational neuroscience, science gateway, high performance computing
Asymmetric PI(3,4,5)P3 and Akt signaling mediates chemotaxis of axonal growth cones.

The action of many extracellular guidance cues on axon pathfinding requires Ca2+ influx at the growth cone (Hong et al., 2000; Nishiyama et al., 2003; Henley and Poo, 2004), but how activation of guidance cue receptors leads to opening of plasmalemmal ion channels remains largely unknown. Analogous to the chemotaxis of amoeboid cells (Parent et al., 1998; Servant et al., 2000), we found that a gradient of chemoattractant triggered rapid asymmetric PI(3,4,5)P3 accumulation at the growth cone's leading edge, as detected by the translocation of a GFP-tagged binding domain of Akt in Xenopus laevis spinal neurons. Growth cone chemoattraction required PI(3,4,5)P3 production and Akt activation, and genetic perturbation of polarized Akt activity disrupted axon pathfinding in vitro and in vivo. Furthermore, patch-clamp recording from growth cones revealed that exogenous PI(3,4,5)P3 rapidly activated TRP (transient receptor potential) channels, and asymmetrically applied PI(3,4,5)P3 was sufficient to induce chemoattractive growth cone turning in a manner that required downstream Ca2+ signaling. Thus, asymmetric PI(3,4,5)P3 elevation and Akt activation are early events in growth cone chemotaxis that link receptor activation to TRP channel opening and Ca2+ signaling. Altogether, our findings reveal that PI(3,4,5)P3 elevation polarizes to the growth cone's leading edge and can serve as an early regulator during chemotactic guidance.