nils-herrmann/clean_scirepeval huggingface dataset:
Longitudinal studies of cognition and functional outcome in schizophrenia: implications for MATRICS

It is generally accepted that cognitive deficits in schizophrenia are related to functional outcome. However, support for longitudinal relationships between cognition and functional outcome has not been as well documented. The current paper presents a review of 18 recently published longitudinal studies (minimum 6-month follow up) of the relationships between cognition and community outcome in schizophrenia. Results from these studies reveal considerable support for longitudinal associations between cognition and community outcome in schizophrenia. These studies demonstrate that cognitive assessment predict later functional outcome and provide a rationale for psychopharmacological interventions for cognitive deficits in schizophrenia. Although the relationships between cognition and community outcome are well-supported, it is clear that community functioning is also affected by a host of factors apart from cognition that are usually not considered in clinical trial studies (e.g., psychosocial rehabilitation and educational/vocational opportunities). In the second part of the paper, we consider intervening steps between cognitive performance measures and community outcome. These steps are apt to have important implications for clinical trials of cognition-enhancing agents in schizophrenia.
Simple topologies of PWM AC-AC converters

This letter proposes a new family of simple topologies of PWM AC-AC converters with minimal switches. With extension from the basic DC-DC converters, a series of AC-AC converters such as buck, boost, buck-boost, Cuk, and isolated converters are obtained. By PWM duty ratio control, they become a "solid-state transformer" with a continuously variable turns ratio. All the proposed AC-AC converters in this paper employ only two switches. Compared to the existing circuits that use six switches or more, they can reduce cost and improve reliability. The operating principle and control method of the proposed topologies are presented. Analysis and simulation results are given using the Cuk AC-AC converter as an example. The analysis can be easily extended to other converters of the proposed family.
Greedy Strikes Back: Improved Facility Location Algorithms

A fundamental facility location problem is to choose the location of facilities, such as industrial plants and warehouses, to minimize the cost of satisfying the demand for some commodity. There are associated costs for locating the facilities, as well as transportation costs for distributing the commodities. Thii problem is commonly referred to as the uncapacitated facility location problem. Applications to bank account location and clustering, as well as many related pieces of work, are discussed by Cornuejols, Nemhauser, and Wolsey . Recently, the first constant factor approximation algorithm for this problem was obtained by Shmoys, Tardos and Aardal . We show that a simple greedy heuristic combined with the Shmoys, Tardos and Aardal algorithm , can be used to derive a better approximation guarantee. We discuss a few variants of the problem, demonstrating better approximation factors for restricted versions of the problem. We also show that the problem is Max SNP-hard. However, the inapproximability constants derived from the Max SNP hardness are very close to one. By relating this problem to Set Cover, we can prove a better lower bound on the best possible approximation ratio.
Neonatal Facial Pain Detection Using NNSOA and LSVM

We report classification experiments using the pilot Infant COPE database of neonatal facial expressions. Two sets of DCT coeffiecents were used to train a neural network simultaneous algorithm (NNSOA) and a linear support vector machine (LSVM) to classify neonatal expressions into the two categories of pain and nonpain. In the first set (VAR) only 80 of the coefficients with the highest variance were included. In the second set (SFFS), 15 DCT coefficients were selected by applying Sequential Forward Floating Selection (SFFS) . We found that NNSOA+VAR produced the best classification score of 95.38% accuracy, but with no statistical difference compared with the DCT sets. However, NNSOA using the DCT coefficients outperformed with statistical significance previous experiments reported in  that used PCA components. It is surmised that NNSOA, an algorithm that eliminates unnecessary weights, is more stable than LSVM and may be better than SFFS at identifying relevant features.
Enterprise Microblogging: Procrastination or productive use?

There are growing fears amongst corporate managers that the introduction of Social Media and related technologies such as microblogging platforms will lead to large-scale time-wasting with negative impacts on corporate productivity. Our research analyses the communication practices of a corporate team that has embraced an Enterprise Microblogging platform and embedded its use into their day-to-day activities. We conduct a genre analysis of the team’s microblogs and compare our results with a recent study of public microblogging on the Twitter platform. By analyzing genre repertoires we have shown that enterprise microblogging can be significantly different to the public equivalent, and that in the corporate context, microblogging platforms can be used in productive ways.
An efficient algorithm for the "optimal" stable marriage

In an instance of size n of the stable marriage problem, each of n men and n women ranks the members of the opposite sex in order of preference. A stable matching is a complete matching of men and women such that no man and woman who are not partners both prefer each other to their actual partners under the matching. It is well known  that at least one stable matching exists for every stable marriage instance. However, the classical Gale-Shapley algorithm produces a marriage that greatly favors the men at the expense of the women, or vice versa. The problem arises of finding a stable matching that is optimal under some more equitable or egalitarian criterion of optimality. This problem was posed by Knuth [6] and has remained unsolved for some time. Here, the objective of maximizing the average (or, equivalently, the total) “satisfaction” of all people is used. This objective is achieved when a person's satisfaction is measured by the position of his/her partner in his/her preference list. By exploiting the structure of the set of all stable matchings, and using graph-theoretic methods, an O(n4) algorithm for this problem is derived.
Maximum Likelihood Reconstruction for Emission Tomography

Previous models for emission tomography (ET) do not distinguish the physics of ET from that of transmission tomography. We give a more accurate general mathematical model for ET where an unknown emission density ¿ = ¿(x, y, z) generates, and is to be reconstructed from, the number of counts n*(d) in each of D detector units d. Within the model, we give an algorithm for determining an estimate ¿ of ¿ which maximizes the probability p(n*|¿) of observing the actual detector count data n* over all possible densities ¿. Let independent Poisson variables n(b) with unknown means ¿(b), b = 1, ···, B represent the number of unobserved emissions in each of B boxes (pixels) partitioning an object containing an emitter. Suppose each emission in box b is detected in detector unit d with probability p(b, d), d = 1, ···, D with p(b, d) a one-step transition matrix, assumed known. We observe the total number n* = n*(d) of emissions in each detector unit d and want to estimate the unknown ¿ = ¿(b), b = 1, ···, B. For each ¿, the observed data n* has probability or likelihood p(n*|¿). The EM algorithm of mathematical statistics starts with an initial estimate ¿0 and gives the following simple iterative procedure for obtaining a new estimate ¿new, from an old estimate ¿old, to obtain ¿k, k = 1, 2, ···, ¿new(b)= ¿old(b) ¿Dd=1 n*(d)p(b,d)/¿¿old(b¿)p(b¿,d),b=1,···B.
Bleomycin sclerotherapy for lymphatic malformation after unsuccessful surgical excision: case report.

Lymphatic malformations (LMs) are benign cystic masses resulting from the abnormal development of lymphatic channels. Lymphatic malformations occur primarily in the head and neck region. Surgical excision of lymphatic malformation is followed by high rate of recurrence and a high risk of complications. Bleomycin is an established antineoplastic drug. It can be used as a sclerosing agent in vascular anomalies. We present a child who was unsuccessfully treated with four surgical resections, with peripheral palsy of facial nerve as complication. The lymphatic malformation was successfully treated in our institution with intralesional administration of bleomycin.
Systems Competition and Network Effects

Many products have little or no value in isolation, but generate value when combined with others. Examples include: nuts and bolts, which together provide fastening services; home audio or video components and programming, which together provide entertainment services; automobiles, repair parts and service, which together provide transportation services; facsimile machines and their associated communications protocols, which together provide fax services; automatic teller machines and ATM cards, which together provide transaction services; camera bodies and lenses, which together provide photographic services. These are all examples of products that are strongly complementary, although they need not be consumed in fixed proportions. We describe them as forming systems, which refers to collections of two or more components together with an interface that allows the components to work together. This paper and the others in this symposium explore the economics of such systems. Market competition between systems, as opposed to market competition between individual products, highlights at least three important issues: expectations, coordination, and compatibility. A recent wave of research has focused on the behavior and performance of the variety of private and public institutions that arise in systems markets to influence expectations, facilitate coordination, and achieve compatibility. In many cases, the components purchased for a single system are spread over time, which means that rational buyers must form expectations about
Roles and Responsibilities of Cyber Intelligence for Cyber Operations in Cyberspace

In this paper, we proposed roles and responsibilities of cyber intelligence in cyber operations. In particular, we focused on the roles and responsibilities of cyber intelligence on each phase of cyber operations. Cyber operations are activities related to defense, assurance, and attack to achieve objectives in or through cyberspace. While cyber operation is conducting, cyber intelligence must properly support cyber commander and units for ensuring cyberspace intelligence superiority. Cyber intelligence is a cyber-discipline that exploits a number of information collection and analysis approaches to provide direction and decision to cyber commander and cyber operation units. This is a key role in both cyberattack and cyber defense. We know that the branch of information and communications conducts cyber operations in cyberspace. But we don’t know well that the cyber intelligence is more in charge of the policy, strategic, and tactics in cyber operations. It is collected information requested from cyber command and units, and is disseminated information to department related to cyber operations. The cyber intelligence is a key factor in cyber operation cycle.
Car monitoring, alerting and tracking model: Enhancement with mobility and database facilities

Statistics show that the number of cars is increasing rapidly and so is the number of car theft attempts, locally and internationally. Although there are a lot of car security systems that had been produced lately, but the result is still disappointing as the number of car theft cases still increases. The thieves are inventing cleverer and stronger stealing techniques that need more powerful security systems. This project “Car Monitoring and Tracking System” is being proposed to solve the issue. It introduces the integration between monitoring and tracking system. Both elements are very crucial in order to have a powerful security system. The system can send SMS and MMS to the owner to have fast response especially if the car is nearby. This paper focuses on using MMS and database technology, the picture of the intruder will be sent via local GSM/GPRS service provider to user (and/or) police. The Database offers the required information about car and owner, which will help the police or security authorities in their job. Moreover, in the event of theft local police and user can easily track the car using GPS system that can be link to Google Earth and other mapping software. The implementation and testing results show the success of prototype in sending MMS to owner within 40 seconds and receiving acknowledgment to the database (police or security unit) within 4 minutes. The timing and results are suitable to owner and police to take suitable action against intruder.
Fine-grained Concept Linking using Neural Networks in Healthcare

To unlock the wealth of the healthcare data, we often need to link the real-world text snippets to the referred medical concepts described by the canonical descriptions. However, existing healthcare concept linking methods, such as dictionary-based and simple machine learning methods, are not effective due to the word discrepancy between the text snippet and the canonical concept description, and the overlapping concept meaning among the fine-grained concepts. To address these challenges, we propose a Neural Concept Linking (NCL) approach for accurate concept linking using systematically integrated neural networks. We call the novel neural network architecture as the COMposite AttentIonal encode-Decode neural network (COM-AID). COM-AID performs an encode-decode process that encodes a concept into a vector and decodes the vector into a text snippet with the help of two devised contexts. On the one hand, it injects the textual context into the neural network through the attention mechanism, so that the word discrepancy can be overcome from the semantic perspective. On the other hand, it incorporates the structural context into the neural network through the attention mechanism, so that minor concept meaning differences can be enlarged and effectively differentiated. Empirical studies on two real-world datasets confirm that the NCL produces accurate concept linking results and significantly outperforms state-of-the-art techniques.
Deep Learning for Biomedical Information Retrieval: Learning Textual Relevance from Click Logs

We describe a Deep Learning approach to modeling the relevance of a document’s text to a query, applied to biomedical literature. Instead of mapping each document and query to a common semantic space, we compute a variable-length difference vector between the query and document which is then passed through a deep convolution stage followed by a deep regression network to produce the estimated probability of the document’s relevance to the query. Despite the small amount of training data, this approach produces a more robust predictor than computing similarities between semantic vector representations of the query and document, and also results in significant improvements over traditional IR text factors. In the future, we plan to explore its application in improving PubMed search.
Tactical Language and Culture Training Systems: Using Artificial Intelligence to Teach Foreign Languages and Cultures

The Tactical Language and Culture Training System (TLCTS) helps people quickly acquire communicative skills in foreign languages and cultures. More than 20,00 0 learners worldwide have used TLCTS courses. TLCTS utili zes artificial intelligence technologies in multiple wa ys: during the authoring process, and at run time to process l arner speech, interpret learner actions, control the resp on e of non-player characters, and evaluate and assess lear ner performance and proficiency. This paper describes the architecture of TLCTS and the artificial intelligence techn ologies that it employs, and presents results from multiple evaluation studies that demonstrate the benefits of learn ing foreign language and culture using this approach.
A smart pill for drug delivery with sensing capabilities

In this paper a novel system for local drug delivery is described. The actuation principle of the micropump used for drug delivery relies on the electrolysis of a water-based solution, which is separated from a drug reservoir by an elastic membrane. The electrolytically produced gases pressurize the electrolytic solution reservoir, causing the deflection of the elastic membrane. Such deflection, in turn, forces the drug out of its reservoir through a nozzle. The proposed system is integrated in a swallowable capsule, equipped with an impedance sensor useful to acquire information on the physiological conditions of the tissue. Such information can be used to control pump activation.
A Real Time Speech to Text Conversion Technique for Bengali Language

This paper presents a model to convert natural Bengali language to text. The proposed model requires the usage of the open sourced framework Sphinx 4 which is written in Java and provides the required procedural coding tools to develop an acoustic model for a custom language like Bengali. Our main objective was to ensure that the system was adequately trained on a word by word basis from various speakers so that it could recognize new speakers fluently. We used a free digital audio workstation (DAW) called Audacity to manipulate the collected recording data via continuous frequency profiling techniques to reduce the Signal-to-Noise-Ratio (SNR), vocal leveling, normalization and syllable splitting as well as merging which ensure an error free 1:1-word mapping of each utterance with its mirror transcription file text. To evaluate the performance of proposed model, we utilize an audio dataset of recorded speech data from 10 individual speakers consisting of both males and females using custom transcript files that we wrote. Experimental results demonstrate that the proposed model exhibits average 71.7% accuracy for our tested dataset.
A Compact Ultrawideband Antenna With 3.4/5.5 GHz Dual Band-Notched Characteristics

We propose a compact planar ultrawideband (UWB) antenna with 3.4/5.5 GHz dual band-notched characteristics. The antenna consists of a beveled rectangular metal patch and a 50 Omega coplanar waveguide (CPW) transmission line. By etching two nested C-shaped slots in the patch, band-rejected filtering properties in the WiMAX/WLAN bands are achieved. The proposed antenna is successfully simulated, designed, and measured showing broadband matched impedance, stable radiation patterns and constant gain. An equivalent circuit model of the proposed antenna is presented to discuss the mechanism of the dual band-notched UWB antenna. A UWB antenna and a single band-notched one are also provided for references.
Inference and Design in Kuba and Zillij Art with Shape Grammars

We present a simple method for structural inference in African Kuba cloth, and Moorish zillij mosaics. Our work is based on Stiny and Gips’ formulation of “Shape Grammars”. It provides art scholars and geometers with a simple yet powerful medium to perform analysis of existing art and draw inspiration for new designs. The analysis involves studying an artwork and capturing its structure as simple shape grammar rules. We then show how interesting families of artworks could be generated using simple variations in their corresponding grammars.
Estimation of collective maneuvers through cooperative multi-agent planning

In order to determine a cooperative driving strategy, it is beneficial for an autonomous vehicle to incorporate the intended motion of surrounding vehicles within its own motion planning. However, as intentions cannot be measured directly and the motion of multiple vehicles often are highly interdependent, this incorporation has proven challenging. In this paper, the problem of maneuver estimation is addressed, focusing on situations with close interaction between traffic participants. Therefore, we define collective maneuvers based on trajectory homotopy, describing the relative motion of multiple vehicles in a scene. Representing maneuvers by sample trajectories, maneuver-dependent prediction models of the vehicle states can be defined. This allows for a Bayesian estimation of maneuver probabilities given observations of the real motion. The approach is evaluated by simulation in overtaking scenarios with oncoming traffic and merging scenarios at an intersection.
Functional neuroanatomy of face and object processing. A positron emission tomography study.

Studies of brain-damaged patients have revealed the existence of a selective impairment of face processing, prosopagnosia, resulting from lesions at different loci in the occipital and temporal lobes. The results of such studies have led to the identification of several cortical areas underlying the processing of faces, but it remains unclear what functional aspects of face processing are served by these areas and whether they are uniquely devoted to the processing of faces. The present study addresses these questions in a positron emission tomography (PET) study of regional cerebral blood flow in normal adults, using the 15 oxygen water bolus technique. The subjects participated in six tasks (with gratings, faces and objects), and the resulting level of cerebral activation was mapped on images of the subjects' cerebral structures obtained through magnetic resonance and was compared between tasks using the subtraction method. Compared with a fixation condition, regional cerebral blood flow (rCBF) changes were found in the striate and extrastriate cortex when subjects had to decide on the orientation of sine-wave gratings. A face-gender categorization resulted in activation changes in the right extrastriate cortex, and a face-identity condition produced additional activation of the fusiform gyrus and anterior temporal cortex of both hemispheres, and of the right parahippocampal gyrus and adjacent areas. Cerebral activation during an object-recognition task occurred essentially in the left occipito-temporal cortex and did not involve the right hemisphere regions specifically activated during the face-identity task. The results provide the first empirical evidence from normal subjects regarding the crucial role of the ventro-medial region of the right hemisphere in face recognition, and they offer new information about the dissociation between face and object processing.