nils-herrmann/clean_scirepeval huggingface dataset:
Outline for a theory of intelligence

Intelligence is defined as that which produces successful behavior. Intelligence is assumed to result from natural selection. A model is proposed that integrates knowledge from research in both natural and artificial systems. The model consists of a hierarchical system architecture wherein: 1) control bandwidth decreases about an order of magnitude at each higher level, 2) perceptual resolution of spatial and temporal patterns contracts about an order-of-magnitude at each higher level, 3) goals expand in scope and planning horizons expand in space and time about an order-of-magnitude at each higher level, and 4) models of the world and memories of events expand their range in space and time by about an order-of-magnitude at each higher level. At each level, functional modules perform behavior generation (task decomposition planning and execution), world modeling, sensory processing, and value judgment. Sensory feedback control loops are closed at every level.
Maximizing Sum Rates in Cognitive Radio Networks: Convex Relaxation and Global Optimization Algorithms

A key challenge in wireless cognitive radio networks is to maximize the total throughput also known as the sum rates of all the users while avoiding the interference of unlicensed band secondary users from overwhelming the licensed band primary users. We study the weighted sum rate maximization problem with both power budget and interference temperature constraints in a cognitive radio network. This problem is nonconvex and generally hard to solve. We propose a reformulation-relaxation technique that leverages nonnegative matrix theory to first obtain a relaxed problem with nonnegative matrix spectral radius constraints. A useful upper bound on the sum rates is then obtained by solving a convex optimization problem over a closed bounded convex set. It also enables the sum-rate optimality to be quantified analytically through the spectrum of specially-crafted nonnegative matrices. Furthermore, we obtain polynomial-time verifiable sufficient conditions that can identify polynomial-time solvable problem instances, which can be solved by a fixed-point algorithm. As a by-product, an interesting optimality equivalence between the nonconvex sum rate problem and the convex max-min rate problem is established. In the general case, we propose a global optimization algorithm by utilizing our convex relaxation and branch-and-bound to compute an ε-optimal solution. Our technique exploits the nonnegativity of the physical quantities, e.g., channel parameters, powers and rates, that enables key tools in nonnegative matrix theory such as the (linear and nonlinear) Perron-Frobenius theorem, quasi-invertibility, Friedland-Karlin inequalities to be employed naturally. Numerical results are presented to show that our proposed algorithms are theoretically sound and have relatively fast convergence time even for large-scale problems
Cloud-Assisted Multiparty Computation from Fully Homomorphic Encryption

We construct protocols for secure multiparty computation with the help of a computationally powerful party, namely the “cloud”. Our protocols are simultaneously efficient in a number of metrics: •  our protocols run in 4 rounds in the semi-honest setting, and 5 rounds in the malicious setting. • Communication: the number of bits exchanged in an execution of the protocol is independent of the complexity of function f being computed, and depends only on the length of the inputs and outputs. • Computation: the computational complexity of all parties is independent of the complexity of the function f , whereas that of the cloud is linear in the size of the circuit computing f . In the semi-honest case, our protocol relies on the “ring learning with errors” (RLWE) assumption, whereas in the malicious case, security is shown under the Ring LWE assumption as well as the existence of simulation-extractable NIZK proof systems and succinct non-interactive arguments. In the malicious setting, we also relax the communication and computation requirements above, and only require that they be “small” – polylogarithmic in the computation size and linear in the size of the joint size of the inputs. Our constructions leverage the key homomorphic property of the recent fully homomorphic encryption scheme of Brakerski and Vaikuntanathan (CRYPTO 2011, FOCS 2011). Namely, these schemes allow combining encryptions of messages under different keys to produce an encryption (of the sum of the messages) under the sum of the keys. We also design an efficient, non-interactive threshold decryption protocol for these fully homomorphic encryption schemes. ∗This work was partially supported by the Check Point Institute for Information Security and by the Israeli Centers of Research Excellence (I-CORE) program (center No. 4/11). †This work was partially supported by an NSERC Discovery Grant, by DARPA under Agreement number FA875011-2-0225. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the author and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of DARPA or the U.S. Government.
Scale coding bag of deep features for human attribute and action recognition

Most approaches to human attribute and action recognition in still images are based on image representation in which multi-scale local features are pooled across scale into a single, scale-invariant encoding. Both in bag-of-words and the recently popular representations based on convolutional neural networks, local features are computed at multiple scales. However, these multi-scale convolutional features are pooled into a single scale-invariant representation. We argue that entirely scale-invariant image representations are sub-optimal and investigate approaches to scale coding within a bag of deep features framework. Our approach encodes multi-scale information explicitly during the image encoding stage. We propose two strategies to encode multi-scale information explicitly in the final image representation. We validate our two scale coding techniques on five datasets: Willow, PASCAL VOC 2010, PASCAL VOC 2012, Stanford-40 and Human Attributes (HAT-27). On all datasets, the proposed scale coding approaches outperform both the scale-invariant method and the standard deep features of the same network. Further, combining our scale coding approaches with standard deep features leads to consistent improvement over the state of the art.
Mullerian duct anomalies: MR imaging

Mullerian duct anomalies (MDAs) are rare, affecting approximately 1% of all women and about 3% of women with poor reproductive outcomes. These congenital anomalies usually result from one of the following categories of abnormalities of the mullerian ducts: failure of formation (no development or underdevelopment) or failure of fusion of the mullerian ducts. The American Fertility Society (AFS) classification of uterine anomalies is widely accepted and includes seven distinct categories. MR imaging has consolidated its role as the imaging modality of choice in the evaluation of MDA. MRI is capable of demonstrating the anatomy of the female genital tract remarkably well and is able to provide detailed images of the intra-uterine zonal anatomy, delineate the external fundal contour of the uterus, and comprehensively image the entire female pelvis in multiple imaging planes in a single examination. The purpose of this pictorial essay is to show the value of MRI in the diagnosis of MDA and to review the key imaging features of anomalies of formation and fusion, emphasizing the relevance of accurate diagnosis before therapeutic intervention.
Approximation in mechanism design

This talk surveys three challenge areas for mechanism design and describes the role approximation plays in resolving them. Challenge 1: optimal mechanisms are parameterized by knowledge of the distribution of agent's private types. Challenge 2: optimal mechanisms require precise distributional information. Challenge 3: in multi-dimensional settings economic analysis has failed to characterize optimal mechanisms. The theory of approximation is well suited to address these challenges. While the optimal mechanism may be parameterized by the distribution of agent's private types, there may be a single mechanism that approximates the optimal mechanism for any distribution. While the optimal mechanism may require precise distributional assumptions, there may be approximately optimal mechanism that depends only on natural characteristics of the distribution. While the multi-dimensional optimal mechanism may resist precise economic characterization, there may be simple description of approximately optimal mechanisms. Finally, these approximately optimal mechanisms, because of their simplicity and tractability, may be much more likely to arise in practice, thus making the theory of approximately optimal mechanism more descriptive than that of (precisely) optimal mechanisms. The talk will cover positive resolutions to these challenges with emphasis on basic techniques, relevance to practice, and future research directions.
UHF RFID PIFA array tag antenna for human body applications

This paper reports a four-element array tag antenna close to a human body for UHF Radio frequency identification (RFID) applications. The four-element array is based on PIFA grounded by vias, which can enhance the directive gain. The array antenna is fed by a four-port microstrip-line power divider. The input impedance of the power divider is designed to match with that of a Monza® 4 microchip. The parametric analysis of conjugate matching was performed and prototypes were fabricated to verify the simulated results. Experimental tests show that the maximum reading range achieved by an RFID tag equipped with the array antenna achieves about 3.9 m when the tag was mounted on a human body.
Decreased serotonergic receptor binding in rhombic lip-derived regions of the medulla oblongata in the sudden infant death syndrome.

The sudden infant death syndrome (SIDS) is postulated to result from a failure of homeostatic responses to life-threatening challenges (e.g. asphyxia, hypercapnia) during sleep. The ventral medulla participates in sleep-related homeostatic responses, including chemoreception, arousal, airway reflex control, thermoregulation, respiratory drive, and blood pressure regulation, in part via serotonin and its receptors. The ventral medulla in humans contains the arcuate nucleus, in which we have shown isolated defects in muscarinic and kainate receptor binding in SIDS victims. We also have demonstrated that the arcuate nucleus is anatomically linked to the nucleus raphé obscurus, a medullary region with serotonergic neurons. We tested the hypothesis that serotonergic receptor binding is decreased in both the arcuate nucleus and nucleus raphé obscurus in SIDS victims. Using quantitative autoradiography, 3H-lysergic acid diethylamide (3H-LSD binding) to serotonergic receptors (5-HT1A-D and 5-HT2 subtypes) was measured blinded in 19 brainstem nuclei. Cases were classified as SIDS (n = 52), acute controls (infants who died suddenly and in whom a complete autopsy established a cause of death) (n = 15), or chronic cases with oxygenation disorders (n = 17). Serotonergic binding was significantly lowered in the SIDS victims compared with controls in the arcuate nucleus (SIDS, 6 +/- 1 fmol/mg tissue; acutes, 19 +/- 1; and chronics, 16 +/- 1; p = 0.0001) and n. raphé obscurus (SIDS, 28 +/- 3 fmol/mg tissue; acutes, 66 +/- 6; and chronics, 59 +/- 1; p = 0.0001). Binding, however, was also significantly lower (p < 0.05) in 4 other regions that are integral parts of the medullary raphé/serotonergic system, and/or are derived, like the arcuate nucleus and nucleus raphé obscurus, from the same embryonic anlage (rhombic lip). These data suggest that a larger neuronal network than the arcuate nucleus alone is involved in the pathogenesis of SIDS, that is, a network composed of inter-related serotonergic nuclei of the ventral medulla that are involved in homeostatic mechanisms, and/or are derived from a common embryonic anlage.
Happily (n)ever after: Aging in the context of oxidative stress, proteostasis loss and cellular senescence

Aging is a complex phenomenon and its impact is becoming more relevant due to the rising life expectancy and because aging itself is the basis for the development of age-related diseases such as cancer, neurodegenerative diseases and type 2 diabetes. Recent years of scientific research have brought up different theories that attempt to explain the aging process. So far, there is no single theory that fully explains all facets of aging. The damage accumulation theory is one of the most accepted theories due to the large body of evidence found over the years. Damage accumulation is thought to be driven, among others, by oxidative stress. This condition results in an excess attack of oxidants on biomolecules, which lead to damage accumulation over time and contribute to the functional involution of cells, tissues and organisms. If oxidative stress persists, cellular senescence is a likely outcome and an important hallmark of aging. Therefore, it becomes crucial to understand how senescent cells function and how they contribute to the aging process. This review will cover cellular senescence features related to the protein pool such as morphological and molecular hallmarks, how oxidative stress promotes protein modifications, how senescent cells cope with them by proteostasis mechanisms, including antioxidant enzymes and proteolytic systems. We will also highlight the nutritional status of senescent cells and aged organisms (including human clinical studies) by exploring trace elements and micronutrients and on their importance to develop strategies that might increase both, life and health span and postpone aging onset.
The Trouble with Autopilots: Assisted and Autonomous Driving on the Social Road

As self-driving cars have grown in sophistication and ability, they have been deployed on the road in both localised tests and as regular private vehicles. In this paper we draw upon publicly available videos of autonomous and assisted driving (specifically the Tesla autopilot and Google self-driving car) to explore how their drivers and the drivers of other cars interact with, and make sense of, the actions of these cars. Our findings provide an early perspective on human interaction with new forms of driving involving assisted-car drivers, autonomous vehicles and other road users. The focus is on social interaction on the road, and how drivers communicate through, and interpret, the movement of cars. We provide suggestions toward increasing the transparency of autopilots' actions for both their driver and other drivers.
An application of Naive Bayes classification for credit scoring in e-lending platform

P2P lending is a new form of lending where in the lenders and borrowers can meet at a common platform like Prosper and ZOPA and strike a best deal. While the borrower looks for a lender who offers the fund at a cheaper interest rate, the lender looks for a borrower whose probability of default is nil or minimal. The peer to peer lending sites can help the lenders judge the borrower by allowing the analysis of the social structures like friendship networks and group affiliations. A particular user can be judged based on his profile and on the information extracted from his social network like borrower's friend's profile and activities (like lending, borrowing and bidding activities). We are using classification algorithm to classify good and bad borrowers, where the input attributes consists of both core credit and social network information. Most of these algorithms only take a single table as input, whereas in the real world most data are stored in multiple tables and managed by relational database systems. Transferring data from multiple tables into a single table, especially merging the social network data causes problems like high redundancy. A simple classifier performs well on real single table data but when applied in a multi-relational (Multi table) setting; its accuracy suffers from the altered statistical information of individual attributes during “join”. Therefore we are using a multi relational Bayesian classification method to predict the default probabilities of borrowers.
Ketamine use, cognition and psychological wellbeing: a comparison of frequent, infrequent and ex-users with polydrug and non-using controls.

Preliminary research has indicated that recreational ketamine use may be associated with marked cognitive impairments and elevated psychopathological symptoms, although no study to date has determined how these are affected by differing frequencies of use or whether they are reversible on cessation of use. In this study we aimed to determine how variations in ketamine use and abstention from prior use affect neurocognitive function and psychological wellbeing.



We assessed a total of 150 individuals: 30 frequent ketamine users, 30 infrequent ketamine users, 30 ex-ketamine users, 30 polydrug users and 30 controls who did not use illicit drugs. Cognitive tasks included spatial working memory, pattern recognition memory, the Stockings of Cambridge (a variant of the Tower of London task), simple vigilance and verbal and category fluency. Standardized questionnaires were used to assess psychological wellbeing. Hair analysis was used to verify group membership.



Frequent ketamine users were impaired on spatial working memory, pattern recognition memory, Stockings of Cambridge and category fluency but exhibited preserved verbal fluency and prose recall. There were no differences in the performance of the infrequent ketamine users or ex-users compared to the other groups. Frequent users showed increased delusional, dissociative and schizotypal symptoms which were also evident to a lesser extent in infrequent and ex-users. Delusional symptoms correlated positively with the amount of ketamine used currently by the frequent users.



Frequent ketamine use is associated with impairments in working memory, episodic memory and aspects of executive function as well as reduced psychological wellbeing. 'Recreational' ketamine use does not appear to be associated with distinct cognitive impairments although increased levels of delusional and dissociative symptoms were observed. As no performance decrements were observed in the ex-ketamine users, it is possible that the cognitive impairments observed in the frequent ketamine group are reversible upon cessation of ketamine use, although delusional symptoms persist.
Effect of cigarette smoking on intraocular pressure.

postoperative corneal sensitivity; however, no signifi­ cant changes were detected in the intergroup compar­ isons. (4) Group B had an 8.2% reduction in ECC, significantly higher than in the rest of the groups (Group A1: 4.8%; Group A2: 5.0%). (5) Endothelial cell loss showed linear correlation with CDE (Group B: r Z 0.47; Group A2: r Z 0.81; both P ! .01) . (6) Group A2 patients had significantly worse scores on the subjective discomfort index. The clinical significance of our study is that in energy-demanding cataracts, the combination of dispersive and cohesive OVDs seems to protect the endothelial cells more efficiently than the cohesiveonly OVD (Visthesia). That is, for the same CDE, more endothelial cells were lost in the cohesive-only OVD patients. Moreover, the endothelial loss pattern in these patients was more random than the in the dispersive–cohesive OVD (Duovisc) patients. How­ ever, although statistically significant, the increased endothelial loss in the cohesive-only OVD patients did not interfere with postoperative visual acuity or corneal thickness. On the other hand, the subjective discomfort feeling was significantly more pronounced in the dispersive–cohesive OVD patients; therefore additional intracameral anesthesia is considered to be necessary. The intracameral anesthesia we used in our study provided anesthesia comparable to that of the cohesive-only OVD, with no evident impact on endothelial cells. In summary, we consider that Visthesia and Duovisc offer comparable surgical outcomes in stage 3 cataract extraction surgery using torsional intelligent phaco technology. Despite the fact that the international liter­ ature provides conflicting comparative outcomes regarding the efficacy of the several commercially available OVDs, our results suggest that Duovisc provides an additional significant protective effect on endothelial cells that should be taken into consider­ ation, especially in cases with a low preoperative ECC.
Pilot-Based Compensation of Frequency-Selective I/Q Imbalances in Direct-Conversion OFDM Transmitters

This paper presents a pilot-based compensation algorithm for mitigation of frequency-selective I/Q imbalances in direct-conversion OFDM transmitters. By deploying a feedback loop from RF to baseband, together with a properly-designed pilot signal structure, the I/Q imbalance properties of the transmitter are efficiently estimated in a subcarrier-wise manner. Based on the obtained I/Q imbalance knowledge, the imbalance effects on the actual transmit waveform are then mitigated by baseband pre-distortion acting on the mirror-subcarrier signals. The compensation performance of the proposed structure is analyzed using extensive computer simulations, indicating that very high image rejection ratios can be achieved in practical system set-ups with reasonable pilot signal lengths.
A statistical model for angle of arrival in indoor multipath propagation

Multiple antenna systems are a useful way of overcoming the effects of multipath interference, and can allow more efficient use of spectrum. In order to test the effectiveness of various algorithms such as diversity combining, phased array processing, and adaptive array processing in an indoor environment, a channel model is needed which models both the time and angle of arrival in indoor environments. Some data has been collected indoors and some temporal models have been proposed, but no existing model accounts for both time and angle of arrival. This paper discusses existing models for the time of arrival, experimental data that were collected indoors, and a proposed extension of the Saleh-Valenzuela model , which accounts for the angle of arrival. Model parameters measured in two different buildings are compared with the parameters presented in the paper by Saleh and Valenzuela, and some statistical validation of the model is presented.
The effects of technostress within the context of employee use of ICT

The main purpose of the present study is to help managers cope with the negative effects of technostress on employee use of ICT. Drawing on transaction theory of stress (Cooper, Dewe, & O’Driscoll, 2001) and information systems (IS) continuance theory (Bhattacherjee, 2001) we investigate the effects of technostress on employee intentions to extend the use of ICT at work. Our results show that factors that create and inhibit technostress affect both employee satisfaction with the use of ICT and employee intentions to extend the use of ICT. Our findings have important implications for the management of technostress with regard to both individual stress levels and organizational performance. A key implication of our research is that managers should implement strategies for coping with technostress through the theoretical concept of technostress inhibitors.