nils-herrmann/clean_scirepeval huggingface dataset:
GluN2A and GluN2B subunit-containing NMDA receptors in hippocampal plasticity

N-Methyl-d-aspartate receptor (NMDAR)-dependent synaptic plasticity is a strong candidate to mediate learning and memory processes that require the hippocampus. This plasticity is bidirectional, and how the same receptor can mediate opposite changes in synaptic weights remains a conundrum. It has been suggested that the NMDAR subunit composition could be involved. Specifically, one subunit composition of NMDARs would be responsible for the induction of long-term potentiation (LTP), whereas NMDARs with a different subunit composition would be engaged in the induction of long-term depression (LTD). Unfortunately, the results from studies that have investigated this hypothesis are contradictory, particularly in relation to LTD. Nevertheless, current evidence does suggest that the GluN2B subunit might be particularly important for plasticity and may make a synapse bidirectionally malleable. In particular, we conclude that the presence of GluN2B subunit-containing NMDARs at the postsynaptic density might be a necessary, though not a sufficient, condition for the strengthening of individual synapses. This is owing to the interaction of GluN2B with calcium/calmodulin-dependent protein kinase II (CaMKII) and is distinct from its contribution as an ion channel.
FOLLOWING RED BLOOD CELLS IN A PULMONARY CAPILLARY

The red blood cells or erythrocytes are biconcave shaped cells and consist mostly in a membrane delimiting a cytosol with a high concentration in hemoglobin. This membrane is highly deformable and allows the cells to go through narrow passages like the capillaries which diameters can be much smaller than red blood cells one. They carry oxygen thanks to hemoglobin, a complex molecule that have very high affinity for oxygen. The capacity of erythrocytes to load and unload oxygen is thus a determinant factor in their efficacy. In this paper, we will focus on the pulmonary capillary where red blood cells capture oxygen. In order to numerically study the behavior of red blood cells along a whole capillary, we propose a camera method that consists in working in a reference frame that follows the red blood cells. More precisely, the domain of study is reduced to a neighborhood of the red blood cells and moves along at erythrocytes mean velocity. This method avoids too large mesh deformation. Our goal is to understand how erythrocytes geometrical changes along the capillary can affect its capacity to capture oxygen. The first part of this document presents the model chosen for the red blood cells along with the numerical method used to determine and follow their shapes along the capillary. The membrane of the red blood cell is complex and has been modelled by an hyper-elastic approach coming from [16]. This camera method is then validated and confronted with a standard Arbitrary Lagrangian Eulerian (ALE) method in which the displacements of the red blood cells are correlated with the deformation of an initial mesh of the whole capillary with red blood cells at start positions. Some geometrical properties of the red blood cells observed in our simulations are then studied and discussed. The second part of this paper deals with the modeling of oxygen and hemoglobin chemistry in the geometries obtained in the first part. We have implemented a full complex hemoglobin behavior with allosteric states inspired from [4]. 1 Laboratoire MSC, Université Paris 7 / CNRS, 10 rue Alice Domon et Léonie Duquet, F-75205 Paris cedex 13 c © EDP Sciences, SMAI 2008
MARS SMART LANDER SIMULATIONS FOR ENTRY , DESCENT , AND LANDING

Two primary simulations have been developed and are being updated for the Mars Smart Lander Entry, Descent, and Landing (EDL). The high fidelity engineering end-to-end EDL simulation that is based on NASA Langley’s Program to Optimize Simulated Trajectories (POST) and the end-to-end real-time, hardware-in-the-loop simulation test bed, which is based on NASA JPL’s Dynamics Simulator for Entry, Descent and Surface landing (DSENDS). This paper presents the status of these Mars Smart Lander EDL end-to-end simulations at this time. Various models, capabilities, as well as validation and verification for these simulations are discussed.
Pseudo Double Bubble: Jejunal Duplication Mimicking Duodenal Atresia on Prenatal Ultrasound 

Prenatal ultrasound showing a double bubble is considered to be pathognomonic of duodenal atresia. We recently encountered an infant with prenatal findings suggestive of duodenal atresia with a normal karyotype who actually had a jejunal duplication cyst on exploration. A finding of an antenatal double bubble should lead to a thorough evaluation of the gastrointestinal tract and appropriate prenatal/neonatal testing and management as many cystic lesions within the abdomen can present with this prenatal finding.
GPU-Accelerated Sparse LU Factorization for Circuit Simulation with Performance Modeling

The sparse matrix solver by LU factorization is a serious bottleneck in Simulation Program with Integrated Circuit Emphasis (SPICE)-based circuit simulators. The state-of-the-art Graphics Processing Units (GPU) have numerous cores sharing the same memory, provide attractive memory bandwidth and compute capability, and support massive thread-level parallelism, so GPUs can potentially accelerate the sparse solver in circuit simulators. In this paper, an efficient GPU-based sparse solver for circuit problems is proposed. We develop a hybrid parallel LU factorization approach combining task-level and data-level parallelism on GPUs. Work partitioning, number of active thread groups, and memory access patterns are optimized based on the GPU architecture. Experiments show that the proposed LU factorization approach on NVIDIA GTX580 attains an average speedup of 7.02× (geometric mean) compared with sequential PARDISO, and 1.55× compared with 16-threaded PARDISO. We also investigate bottlenecks of the proposed approach by a parametric performance model. The performance of the sparse LU factorization on GPUs is constrained by the global memory bandwidth, so the performance can be further improved by future GPUs with larger memory bandwidth.
Mutual Inductance Calculation of Movable Planar Coils on Parallel Surfaces

Recent developments of the wireless battery charging platform have prompted requirements to investigate the mutual inductance between a movable planar coil and the fixed planar coil on the charging platform. The wireless battery charging platform must allow the load to be placed anywhere on the charging surface. Therefore, the relative position between the movable energy-receiving coil and the energy-transmitting coils on the charging platform must be flexible. In this paper, an extended formula is proposed for the mutual inductance calculation for two coaxial or noncoaxial planar spiral windings sandwiched between two double-layer substrates. It can quickly determine the mutual coupling of two planar windings that can have different relative positions and distance between them. This new calculation method provides a new and useful tool for determining the mutual inductance of a movable planar coil and the fixed planar coil on the wireless battery charging platform. The theory has been favorably tested and compared with practical measurements and also with finite-element analysis.
The Social Media Ecology: User Perceptions, Strategies and Challenges

Many existing studies of social media focus on only one platform, but the reality of users' lived experiences is that most users incorporate multiple platforms into their communication practices in order to access the people and networks they desire to influence. In order to better understand how people make sharing decisions across multiple sites, we asked our participants (N=29) to categorize all modes of communication they used, with the goal of surfacing their mental models about managing sharing across platforms. Our interview data suggest that people simultaneously consider "audience" and "content" when sharing and these needs sometimes compete with one another; that they have the strong desire to both maintain boundaries between platforms as well as allowing content and audience to permeate across these boundaries; and that they strive to stabilize their own communication ecosystem yet need to respond to changes necessitated by the emergence of new tools, practices, and contacts. We unpack the implications of these tensions and suggest future design possibilities.
A Bipedal Walking Robot with Efficient and Human-Like Gait

Here we present the design of a passive-dynamics based, fully autonomous, 3-D, bipedal walking robot that uses simple control, consumes little energy, and has human-like morphology and gait. Design aspects covered here include the freely rotating hip joint with angle bisecting mechanism; freely rotating knee joints with latches; direct actuation of the ankles with a spring, release mechanism, and reset motor; wide feet that are shaped to aid lateral stability; and the simple control algorithm. The biomechanics context of this robot is discussed in more detail in , and movies of the robot walking are available at Science Online and http://www.tam.cornell.edu/~ruina/powerwalk.html. This robot adds evidence to the idea that passive-dynamic approaches might help design walking robots that are simpler, more efficient and easier to control.
Functional Gradient Boosting based on Residual Network Perception

Residual Networks (ResNets) have become stateof-the-art models in deep learning and several theoretical studies have been devoted to understanding why ResNet works so well. One attractive viewpoint on ResNet is that it is optimizing the risk in a functional space by combining an ensemble of effective features. In this paper, we adopt this viewpoint to construct a new gradient boosting method, which is known to be very powerful in data analysis. To do so, we formalize the gradient boosting perspective of ResNet mathematically using the notion of functional gradients and propose a new method called ResFGB for classification tasks by leveraging ResNet perception. Two types of generalization guarantees are provided from the optimization perspective: one is the margin bound and the other is the expected risk bound by the sample-splitting technique. Experimental results show superior performance of the proposed method over state-of-the-art methods such as LightGBM.
Near-field 3-D synthetic aperture radar imaging via compressed sensing

This paper successfully implements compressed sensing (CS) to a near-field wideband 3-D synthetic aperture radar (SAR) imaging system. SAR data are measured at a low percentage of random-selected positions on a uniform grid of planar aperture in the stripmap mode. The near-field 3-D range migration algorithm (RMA) is used in combination with the CS principle to reconstruct the 3-D image via l1 regularized least-square approach. Experiments were performed with Q-band stepped-frequency monostatic stripmap SAR imaging system on a blue foam embedded with eight rubber pads and one copper square chip. The results of the experiments show near-field 3-D image of the specimen under test (SUT) can be reconstructed efficiently from low percentage of the full measurement positions, which largely lessens the data collection load. The reconstructed image was better focused and denoised.
A 7 DOF exoskeleton arm: Shoulder, elbow, wrist and hand mechanism for assistance to upper limb disabled individuals

This paper illustrates the mechanical structure's spherical motion, kinematic matrices and achievable workspace of an exoskeleton upper limb device. The purpose of this paper is to assist individuals that have lost their upper limb motor functions by creating an exoskeleton device that does not require an external support; but still provides a large workspace. This allows for movement according to the Activities of Daily Living (ADL).
The MBTI and social information processing: an incremental validity study.

The ability of the Myers-Briggs Type Indicator (MBTI;  1985) to predict performance on social cognitive tasks tapping information processing effort was assessed. Judgment and intuition interacted to predict amount of attributional adjustment on a dispositional attribution task. The MBTI scales predicted processing above and beyond measures of the five factors, rational-experiential preferences, and causal uncertainty. The relevance of these results for interpretation of the MBTI indexes is discussed.
Platform-as-a-Service Architecture for Performance Isolated Multi-tenant Applications

Software-as-a-Service (SaaS) often shares one single application instance among different tenants to reduce costs. However, sharing potentially leads to undesired influence from one tenant onto the performance observed by the others. This is a significant problem as performance is one of the major obstacles for cloud customers. The application does intentionally not manage hardware resources, and the operating system is not aware of application level entities like tenants which makes the performance control a challenge. In case the SaaS is hosted on a Platform-as-a-Service (PaaS), the SaaS developer usually wants to control performance-related issues according to individual needs, and available information is even more limited. Thus, it is difficult to control the performance of different tenants to keep them isolated. Existing work focuses on concrete methods to provide performance isolation in systems where the whole stack is under control. In this paper we present a concrete PaaS enhancement which enables application developers to realize isolation methods for their hosted SaaS application. In a case study we evaluated the applicability and effectiveness of the enhancement in different environments.
Agents and Devices: A Relative Definition of Agency

According to Dennett, the same system may be described using a ‘physical’ (mechanical) explanatory stance, or using an ‘intentional’ (beliefand goalbased) explanatory stance. Humans tend to find the physical stance more helpful for certain systems, such as planets orbiting a star, and the intentional stance for others, such as living animals. We define a formal counterpart of physical and intentional stances within computational theory: a description of a system as either a device, or an agent, with the key difference being that ‘devices’ are directly described in terms of an input-output mapping, while ‘agents’ are described in terms of the function they optimise. Bayes’ rule can then be applied to calculate the subjective probability of a system being a device or an agent, based only on its behaviour. We illustrate this using the trajectories of an object in a toy grid-world domain.
Summoning Demons: The Pursuit of Exploitable Bugs in Machine Learning

Governments and businesses increasingly rely on data analytics and machine learning (ML) for improving their competitive edge in areas such as consumer satisfaction, threat intelligence, decision making, and product efficiency. However, by cleverly corrupting a subset of data used as input to a target’s ML algorithms, an adversary can perturb outcomes and compromise the effectiveness of ML technology. While prior work in the field of adversarial machine learning has studied the impact of input manipulation on correct ML algorithms, we consider the exploitation of bugs in ML implementations. In this paper, we characterize the attack surface of ML programs, and we show that malicious inputs exploiting implementation bugs enable strictly more powerful attacks than the classic adversarial machine learning techniques. We propose a semi-automated technique, called steered fuzzing, for exploring this attack surface and for discovering exploitable bugs in machine learning programs, in order to demonstrate the magnitude of this threat. As a result of our work, we responsibly disclosed five vulnerabilities, established three new CVE-IDs, and illuminated a common insecure practice across many machine learning systems. Finally, we outline several research directions for further understanding and mitigating this threat.
Acetylated Hyaluronic Acid: Enhanced Bioavailability and Biological Studies

Hyaluronic acid (HA), a macropolysaccharidic component of the extracellular matrix, is common to most species and it is found in many sites of the human body, including skin and soft tissue. Not only does HA play a variety of roles in physiologic and in pathologic events, but it also has been extensively employed in cosmetic and skin-care products as drug delivery agent or for several biomedical applications. The most important limitations of HA are due to its short half-life and quick degradation in vivo and its consequently poor bioavailability. In the aim to overcome these difficulties, HA is generally subjected to several chemical changes. In this paper we obtained an acetylated form of HA with increased bioavailability with respect to the HA free form. Furthermore, an improved radical scavenging and anti-inflammatory activity has been evidenced, respectively, on ABTS radical cation and murine monocyte/macrophage cell lines (J774.A1).
Vision Based Object Counting Using Speeded Up Robust Features for Inventory Control

In this paper, an approach for industrial machine vision system is introduced for effective maintenance of inventory in order to minimize the production cost in supply chain network. The objective is to propose an efficient technique for object identification, localization, and report generation to monitor the inventory level in real time video stream based on the object appearance model. The appearance model is considered as visual signature by which individual object can be detected anywhere via camera feed. Herein, Speeded Up Robust Features (SURF) are used to identify the object. Firstly, SURF features are extracted from prototype image which refers to predefined template of individual objects, and then extracted from the camera feed of inventory i.e. scene image. Density based clustering on SURF points of prototype is done, followed by feature mapping of each cluster to SURF points in scene image. Homographic transforms are then used to obtain the location and mark the presence of objects in the scene image. Further, for better invariance to occlusion and faster computation, a novel method for tuning the hyper parameters of clustering is also proposed. The proposed methodology is found to be reliable and is able to give robust real time count of objects in inventory with invariance to scale, rotation and upto 70% of occlusion.
The paradoxical psychological effects of lysergic acid diethylamide (LSD).

Lysergic acid diethylamide (LSD) is a potent serotonergic hallucinogen or psychedelic that modulates consciousness in a marked and novel way. This study sought to examine the acute and mid-term psychological effects of LSD in a controlled study.



A total of 20 healthy volunteers participated in this within-subjects study. Participants received LSD (75 µg, intravenously) on one occasion and placebo (saline, intravenously) on another, in a balanced order, with at least 2 weeks separating sessions. Acute subjective effects were measured using the Altered States of Consciousness questionnaire and the Psychotomimetic States Inventory (PSI). A measure of optimism (the Revised Life Orientation Test), the Revised NEO Personality Inventory, and the Peter's Delusions Inventory were issued at baseline and 2 weeks after each session.



LSD produced robust psychological effects; including heightened mood but also high scores on the PSI, an index of psychosis-like symptoms. Increased optimism and trait openness were observed 2 weeks after LSD (and not placebo) and there were no changes in delusional thinking.



The present findings reinforce the view that psychedelics elicit psychosis-like symptoms acutely yet improve psychological wellbeing in the mid to long term. It is proposed that acute alterations in mood are secondary to a more fundamental modulation in the quality of cognition, and that increased cognitive flexibility subsequent to serotonin 2A receptor (5-HT2AR) stimulation promotes emotional lability during intoxication and leaves a residue of 'loosened cognition' in the mid to long term that is conducive to improved psychological wellbeing.
Fecundity, growth, and survival of the angelfish Pterophyllum scalare (Perciformes: Cichlidae) under laboratory conditions.

The freshwater angelfishes (Pterophyllum) are South American cichlids that have become very popular among aquarists, yet scarce information on their culture and aquarium husbandry exists. We studied Pterophyllum scalare to analyze dietary effects on fecundity, growth, and survival of eggs and larvae during 135 days. Three diets were used: A) decapsulated cysts of Artemia, B) commercial dry fish food, and C) a mix diet of the rotifer Brachionus plicatilis and the cladoceran Daphnia magna. The initial larval density was 100 organisms in each 40 L aquarium. With diet A, larvae reached a maximum weight of 3.80 g, a total length of 6.3 cm, and a height of 5.8 cm; with diet B: 2.80 g, 4.81 cm, and 4.79 cm, and with diet C: 3.00 g, 5.15 cm, and 5.10 cm, respectively. Significant differences were observed between diet A, and diet B and C, but no significantly differences were observed between diets B and C. Fecundity varied from 234 to 1,082 eggs in 20 and 50 g females, respectively. Egg survival ranged from 87.4% up to 100%, and larvae survival (80 larvae/40 L aquarium) from 50% to 66.3% using diet B and A, respectively. Live food was better for growing fish than the commercial balanced food diet. Fecundity and survival are important factors in planning a good production of angelfish.
An Improved Faster R-CNN for Same Object Retrieval

An improved faster region-based convolutional neural network (R-CNN) [same object retrieval (SOR) faster R-CNN] is proposed to retrieve the same object in different scenes with few training samples. By concatenating the feature maps of shallow and deep convolutional layers, the ability of Regions of Interest (RoI) pooling to extract more detailed features is improved. In the training process, a pretrained CNN model is fine-tuned using a query image data set, so that the confidence score can identify an object proposal to the object level rather than the classification level. In the query process, we first select the ten images for which the object proposals have the closest confidence scores to the query object proposal. Then, the image for which the detected object proposal has the minimum cosine distance to the query object proposal is considered as the query result. The proposed SOR faster R-CNN is applied to our Coke cans data set and three public image data sets, i.e., Oxford Buildings 5k, Paris Buildings 6k, and INS 13. The experimental results confirm that SOR faster R-CNN has better identification performance than fine-tuned faster R-CNN. Moreover, SOR faster R-CNN achieves much higher accuracy for detecting low-resolution images than the fine-tuned faster R-CNN on the Coke cans (0.094 mAP higher), Oxford Buildings (0.043 mAP higher), Paris Buildings (0.078 mAP higher), and INS 13 (0.013 mAP higher) data sets.