nils-herrmann/clean_scirepeval huggingface dataset:
Memory encoding in Alzheimer's disease: an fMRI study of explicit and implicit memory.

Alzheimer's disease is the most common cause of dementia in older adults. Although the cognitive deficits and pathologic hallmarks of Alzheimer's disease have been well characterized, few functional imaging studies have examined the functional competency of specific brain regions and their relationship to specific behavioural memory deficits in Alzheimer's disease. We used functional MRI (fMRI) to examine seven early stage Alzheimer's disease patients and seven healthy age-matched neurologically normal control subjects during intentional encoding of scenes. Subjects viewed blocks of novel scenes, repeated scenes or baseline. Data were analysed using whole-brain statistical parametric mapping and region of interest approaches. The Alzheimer's disease group demonstrated impaired explicit recognition memory, but intact implicit memory (repetition priming), for the scenes. Alzheimer's disease patients demonstrated a graded deficit in activation for novel versus repeated scenes along the ventral visual stream, with most impaired activation changes in the mesial temporal lobe (MTL) and fusiform regions, most preserved activations in primary visual cortex and variably affected activations in secondary visual areas. Group-level correlations with behavioural measures of explicit memory were found in MTL, lingual and fusiform areas, whereas correlations with priming were found in lateral occipital, parietal and frontal areas. Together, these fMRI findings indicate a dissociation in Alzheimer's disease between impaired explicit memory encoding in MTL and fusiform regions and intact implicit encoding in earlier-stage occipital cortex.
Relevance feedback in image retrieval: A comprehensive review

We analyze the nature of the relevance feedback problem in a continuous representation space in the context of content-based image retrieval. Emphasis is put on exploring the uniqueness of the problem and comparing the assumptions, implementations, and merits of various solutions in the literature. An attempt is made to compile a list of critical issues to consider when designing a relevance feedback algorithm. With a comprehensive review as the main portion, this paper also offers some novel solutions and perspectives throughout the discussion.
Condensation methodologies for two-dimensional non-uniform constellations

Two-dimensional non-uniform constellations (2D-NUC) have been adopted for the most recent terrestrial broadcasting system called ATSC 3.0. They are known for being more efficient than one-dimensional non uniform constellations (1D-NUC) and uniform constellations (UC). They can be used in any communication system with the bit-interleaved coded modulation (BICM) structure. However, one of the main challenges of such constellations is their design for optimal behaviour in a wide range of cases and the design of a demapper that exploits their advantages. This paper presents two different condensation methodologies to design efficient 2D-NUCs simple in design and with limited demapping complexity. The proposal provides a complexity reduction of the design and demapping processes in the range from 13% to 94%. The demapping stage provides performance losses less than 0.1 dB if compared with standard 2D-NUC demapping.
Maternal Control of Child Feeding During the Weaning Period: Differences Between Mothers Following a Baby-led or Standard Weaning Approach

A controlling maternal feeding style has been shown to have a negative impact on child eating style and weight in children over the age of 12 months. The current study explores maternal feeding style during the period of 6–12 months when infants are introduced to complementary foods. Specifically it examines differences between mothers who choose to follow a traditional weaning approach using spoon feeding and pureés to mothers following a baby-led approach where infants are allowed to self feed foods in their solid form. Seven hundred and two mothers with an infant aged 6–12 months provided information regarding weaning approach alongside completing the Child Feeding Questionnaire. Information regarding infant weight and perceived size was also collected. Mothers following a baby-led feeding style reported significantly lower levels of restriction, pressure to eat, monitoring and concern over child weight compared to mothers following a standard weaning response. No association was seen between weaning style and infant weight or perceived size. A baby-led weaning style was associated with a maternal feeding style which is low in control. This could potentially have a positive impact upon later child weight and eating style. However due to the cross sectional nature of the study it cannot be ascertained whether baby-led weaning encourages a feeding style which is low in control to develop or whether mothers who are low in control choose to follow a baby-led weaning style.
Training neural nets with the reactive tabu search

In this paper the task of training subsymbolic systems is considered as a combinatorial optimization problem and solved with the heuristic scheme of the reactive tabu search (RTS). An iterative optimization process based on a "modified local search" component is complemented with a meta-strategy to realize a discrete dynamical system that discourages limit cycles and the confinement of the search trajectory in a limited portion of the search space. The possible cycles are discouraged by prohibiting (i.e., making tabu) the execution of moves that reverse the ones applied in the most recent part of the search. The prohibition period is adapted in an automated way. The confinement is avoided and a proper exploration is obtained by activating a diversification strategy when too many configurations are repeated excessively often. The RTS method is applicable to nondifferentiable functions, is robust with respect to the random initialization, and effective in continuing the search after local minima. Three tests of the technique on feedforward and feedback systems are presented.
Scaling agile methods to regulated environments: An industry case study

Agile development methods are growing in popularity with a recent survey reporting that more than 80% of organizations now following an agile approach. Agile methods were seen initially as best suited to small, co-located teams developing non-critical systems. The first two constraining characteristics (small and co-located teams) have been addressed as research has emerged describing successful agile adoption involving large teams and distributed contexts. However, the applicability of agile methods for developing safety-critical systems in regulated environments has not yet been demonstrated unequivocally, and very little rigorous research exists in this area. Some of the essential characteristics of agile approaches appear to be incompatible with the constraints imposed by regulated environments. In this study we identify these tension points and illustrate through a detailed case study how an agile approach was implemented successfully in a regulated environment. Among the interesting concepts to emerge from the research are the notions of continuous compliance and living traceability.
An analysis and comparison of database cracking kernels

Database indexes are a core technique to speed up data retrieval in any kind of data processing system. However, in the presence of schemas with many attributes it becomes infeasible to create indexes for all columns, as maintenance costs and space requirements are simply too high. In these situations, a much more promising approach is to adaptively index the data, i.e. the database gradually partitions (or cracks) those columns that are frequently used in selections. In doing so, the "indexedness" of a table adapts to the requirements of the workload. A large body of work has investigated database cracking, which is a subset of adaptive indexing.
 Irrespective of their algorithmic behavior, essentially all these works have in common, that the proposed methods use a simple two-sided in-place cracking kernel at the core, which performs a partitioning step. As this partitioning makes a large portion of the total indexing effort, the choice of the kernel can make a factor of two difference in the running time for a method sitting on top.
 To approach the topic, we first perform an experimental evaluation of existing state-of-the-art kernels and study their respective downsides in detail. Based on the gained insights, we propose both an advanced version of the best existing kernel as well as a new and unconventional approach, which utilizes features of the operating system as well as data parallelism. In our final evaluation of all kernels, we vary entry size, index layout, selectivity, and number of threads, and provide a decision tree to select the best cracking kernel for the respective situation.
An Efficient Finger-Knuckle-Print Based Recognition System Fusing SIFT and SURF Matching Scores

This paper presents a novel combination of local-local information for an efficient finger-knuckle-print (FKP) based recognition system which is robust to scale and rotation. The non-uniform brightness of the FKP due to relatively curvature surface is corrected and texture is enhanced. The local features of the enhanced FKP are extracted using the scale invariant feature transform (SIFT) and the speeded up robust features (SURF). Corresponding features of the enrolled and the query FKPs are matched using nearest-neighbour-ratio method and then the derived SIFT and SURF matching scores are fused using weighted sum rule. The proposed system is evaluated using PolyU FKP database of 7920 images for both identification mode and verification mode. It is observed that the system performs with CRR of 100% and EER of 0.215%. Further, it is evaluated against various scales and rotations of the query image and is found to be robust for query images downscaled upto 60% and for any orientation of query image.
Enhanced brain connectivity in long-term meditation practitioners

Very little is currently known about the cerebral characteristics that underlie the complex processes of meditation as only a limited number of studies have addressed this topic. Research exploring structural connectivity in meditation practitioners is particularly rare. We thus acquired diffusion tensor imaging (DTI) data of high angular and spatial resolution and used atlas-based tract mapping methods to investigate white matter fiber characteristics in a well-matched sample of long-term meditators and controls (n=54). A broad field mapping approach estimated the fractional anisotropy (FA) for twenty different fiber tracts (i.e., nine tracts in each hemisphere and two inter-hemispheric tracts) that were subsequently used as dependent measures. Results showed pronounced structural connectivity in meditators compared to controls throughout the entire brain within major projection pathways, commissural pathways, and association pathways. The largest group differences were observed within the corticospinal tract, the temporal component of the superior longitudinal fasciculus, and the uncinate fasciculus. While cross-sectional studies represent a good starting point for elucidating possible links between meditation and white matter fiber characteristics, longitudinal studies will be necessary to determine the relative contribution of nature and nurture to enhanced structural connectivity in long-term meditators.
IO Performance Interference among Consolidated n-Tier Applications: Sharing Is Better Than Isolation for Disks

The performance unpredictability associated with migrating applications into cloud computing infrastructures has impeded this migration. For example, CPU contention between co-located applications has been shown to exhibit counter-intuitive behavior. In this paper, we investigate IO performance interference through the experimental study of consolidated n-tier applications leveraging the same disk. Surprisingly, we found that specifying a specific disk allocation, e.g., limiting the number of Input/Output Operations Per Second (IOPs) per VM, results in significantly lower performance than fully sharing disk across VMs. Moreover, we observe severe performance interference among VMs can not be totally eliminated even with a sharing strategy (e.g., response times for constant workloads still increase over 1,100%). By using a micro-benchmark (Filebench) and an n-tier application benchmark systems (RUBBoS), we demonstrate the existence of disk contention in consolidated environments, and how performance loss occurs when co-located database systems in order to maintain database consistency flush their logs from memory to disk. Potential solutions to these isolation issues are (1) to increase the log buffer size to amortize the disk IO cost (2) to decrease the number of write threads to alleviate disk contention. We validate these methods experimentally and find a 64% and 57% reduction in response time (or more generally, a reduction in performance interference) for constant and increasing workloads respectively.
The BRICS component model: a model-based development paradigm for complex robotics software systems

Because robotic systems get more complex all the time, developers around the world have, during the last decade, created component-based software frameworks (Orocos, Open-RTM, ROS, OPRoS, SmartSoft) to support the development and reuse of "large grained" pieces of robotics software. This paper introduces the BRICS Component Model (BCM) to provide robotics developers with a set of guidelines, metamodels and tools for structuring as much as possible the development of, both, individual components and component-based architectures, using one or more of the aforementioned software frameworks at the same time, without introducing any framework- or application-specific details. The BCM is built upon two complementary paradigms: the "5Cs" (separation of concerns between the development aspects of Computation, Communication, Coordination, Configuration and Composition) and the meta-modeling approach from Model-Driven Engineering.
An empirical study of dormant bugs

Over the past decade, several research efforts have studied the quality of software systems by looking at post-release bugs. However, these studies do not account for bugs that remain dormant (i.e., introduced in a version of the software system, but are not found until much later) for years and across many versions. Such dormant bugs skew our under- standing of the software quality. In this paper we study dormant bugs against non-dormant bugs using data from 20 different open-source Apache foundation software systems. We find that 33% of the bugs introduced in a version are not reported till much later (i.e., they are reported in future versions as dormant bugs). Moreover, we find that 18.9% of the reported bugs in a version are not even introduced in that version (i.e., they are dormant bugs from prior versions). In short, the use of reported bugs to judge the quality of a specific version might be misleading. Exploring the fix process for dormant bugs, we find that they are fixed faster (median fix time of 5 days) than non- dormant bugs (median fix time of 8 days), and are fixed by more experienced developers (median commit counts of developers who fix dormant bug is 169% higher). Our results highlight that dormant bugs are different from non-dormant bugs in many perspectives and that future research in software quality should carefully study and consider dormant bugs.
Active Learning for Real Time Detection of Polyps in Videocolonoscopy

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Active Learning For Real Time Detection Of Polyps In Videocolonoscopy Quentin Angermann, Aymeric Histace, Olivier Romain
An adaptive FEC algorithm using hidden Markov chains

Anumber of performance issues must be addressed in order to transmit continuous media stream over the Internet with acceptable quality [9, 6] . These include reducing jitter and recovering from packet losses mainly due to congestion in the routers . Several methods can be used to deal with the loss of a packet such as : retransmission schemes, error concealment, error resilience, interleaving, and FEC (forward error correction) . Each has its advantages/disadvantages depending on the network scenario and conditions (RTT, propagation delay, topology, channel error rate, congestion in the sender/receiver path, etc.) . In this work we focus on FEC techniques. FEC works by adding redundant information to the stream being transmitted in order to reconstruct the original stream at the receiver when packet losses occur. Among its advantages are the small delays introduced to recover information compared to retransmission, for instance, and simplicity of implementation . A clear disadvantage is the increase in the transmission rate due to the redundancy added. One of the simplest approaches among FEC techniques that have been proposed in the literature [11] is to add a packet to each group of N 1 packets with a payload equal to the result of an XOR operation performed in the group. Clearly, if one packet out of the N is lost, the stream is completely recovered . This is accomplished at the expense ofextra bandwidth, in this example an increase of 1/(N 1) . In  a clever FEC scheme was proposed in which each packet carries a sample of the previous transmitted packet but compression is used to reduce the overhead . In  another technique was developed aimed at maintaining a good compromise between recovery efficiency and bandwidth usage. Since packet losses are mostly due to congestion, increasing the amount of protection using FEC may be unfair to flow controlled streams and also may even have an adverse effect on the results  . Therefore, the FEC algorithm should be carefully chosen according to the error characteristics ofthe path between the sender and receiver. Another issue is to develop accurate models ofthe loss process . Many studies exist to characterize the loss process [2, 14, 8] . Simple models such as the Bernoulli process, the Gilbert model and sophisticated Markov models have been proposed. Using either the Bernoulli or the Gilbert process, the work of[3] propose an adaptive algorithm based on the FECscheme of[4] . Recently, the work of Salamatian and Vaton [13] has shown that Hidden
Judgment under emotional certainty and uncertainty: the effects of specific emotions on information processing.

The authors argued that emotions characterized by certainty appraisals promote heuristic processing, whereas emotions characterized by uncertainty appraisals result in systematic processing. The 1st experiment demonstrated that the certainty associated with an emotion affects the certainty experienced in subsequent situations. The next 3 experiments investigated effects on processing of emotions associated with certainty and uncertainty. Compared with emotions associated with uncertainty, emotions associated with certainty resulted in greater reliance on the expertise of a source of a persuasive message in Experiment 2, more stereotyping in Experiment 3, and less attention to argument quality in Experiment 4. In contrast to previous theories linking valence and processing, these findings suggest that the certainty appraisal content of emotions is also important in determining whether people engage in systematic or heuristic processing.
Shape, Illumination, and Reflectance from Shading

A fundamental problem in computer vision is that of inferring the intrinsic, 3D structure of the world from flat, 2D images of that world. Traditional methods for recovering scene properties such as shape, reflectance, or illumination rely on multiple observations of the same scene to overconstrain the problem. Recovering these same properties from a single image seems almost impossible in comparison-there are an infinite number of shapes, paint, and lights that exactly reproduce a single image. However, certain explanations are more likely than others: surfaces tend to be smooth, paint tends to be uniform, and illumination tends to be natural. We therefore pose this problem as one of statistical inference, and define an optimization problem that searches for the most likely explanation of a single image. Our technique can be viewed as a superset of several classic computer vision problems (shape-from-shading, intrinsic images, color constancy, illumination estimation, etc) and outperforms all previous solutions to those constituent problems.
Through mold vias for stacking of mold embedded packages

The constant drive towards further miniaturization and heterogeneous system integration leads to a need for new packaging technologies which also allow large area processing and 3D integration with potential for low cost applications. Large area mold embedding technologies and embedding of active components into printed circuit boards (Chip-in-Polymer) are two major packaging trends in this area. This paper describes the use of a novel S2iP (Stacked System in Package) interconnect technique using advanced molding process for multi chip embedding in combination with large area and low cost redistribution technology derived from printed circuit board manufacturing with a focus on integration of through mold vias for package stacking. The use of compression molding equipment with liquid or granular epoxy molding compounds for the targeted integration process flow is a new technology that has been especially developed to allow large area embedding of single chips but also of multiple chips or heterogeneous systems on wafer scale, typically 8” to 12”. Future developments will deal with panel sizes up to 470 × 370 mm². The wiring of the embedded components in this novel type of SiP is done using PCB manufacturing technologies, i.e. a resin coated copper (RCC) film is laminated over the embedded components — whichever no matter which shape they are: a compression molded wafer or a larger rectangular area of a Molded Array Package (MAP). Interconnects are formed by laser drilling to die pads and electroplating — all of them making use of standard PCB processes. Thus, through vias which are standard features in PCB manufacturing and can be also integrated in the proposed process flow for mold embedding in combination with RCC based redistribution. Vias were drilled by laser or mechanically after RCC lamination and were metalized together with the vias for chip interconnection. Within this study different liquid and granular molding compounds have been intensively evaluated on their processability. Via drilling process by laser and mechanical drilling is systematically developed and analyzed with focus on via diameter, pitch, mold thickness and molding compound composition and here especially on filler particle sizes and distribution. The feasibility of the entire process chain is demonstrated by fabrication of a Ball Grid Array (BGA) type of system package with two embedded dies and through mold vias allowing the stacking of these BGA packages. Finally, a technology demonstrator is described consisting of two BGAs stacked on each other and mounted on a base substrate enabling the electrical test of a daisy chain structure through the stacked module, allowing the evaluation of the technology and the applied processes.