Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy and Clinical Determinants of Antipsychotic Polypharmacy in Psychotic Patients Experiencing an Acute Relapse and Admitted to Hospital Stay: Results from a Cross-Sectional and a Subsequent Longitudinal Pilot Study

Background. Antipsychotic polypharmacy is used in several psychiatric disorders, despite poor evidence existing to support this practice. Aim. We evaluated whether psychotic patients in acute relapse exposed to antipsychotic polypharmacy (AP + AP) showed different demographic, clinical, or psychopathological features compared to those exposed to one antipsychotic (AP) and whether AP + AP patients showed significantly higher improvement compared to AP patients after a 4-week treatment. Methods. Inpatients were subdivided into AP + AP and AP ones. In the cross-sectional step, patients were compared according to demographics, clinical variables, and scores on rating scales. In the longitudinal step, patients remained for 4 weeks under admission medications and were compared for clinical improvement. Results. AP + AP patients were more frequently diagnosed with schizophrenia and mental retardation as a comorbid illness. AP + AP patients were more frequently under first-generation antipsychotics and had worse clinical presentation. After 4 weeks of treatment, both AP + AP and AP patients improved compared to the baseline. However, AP patients scored significantly less than AP + AP patients at the Clinical Global Impression Scale at the 4-week time point but not at the baseline, indicating a treatment-specific improvement. Conclusions. Antipsychotic polypharmacy may be offered to specific types of psychotic patients. However, efficacy of this strategy is limited at best.
Adoption and Utilisation , Skill Constraints and Firm-Level Performance : Evidence from UK Benchmarking Surveys

In the context of the skill-biased technological revolution associated with Information and Communication Technologies (ICTs), firms with relatively high (low) proportions of skilled workers can be expected to have a comparative advantage (disadvantage) in minimising the costs both of ICT adoption and of learning how to make best use of ICTs. In this paper we make use of benchmarking survey data for UK enterprises between 1997-99, combined with post-survey financial data for the same enterprises, in order to assess the impact of ICT skill constraints on financial performance at firm level. The results provide clear evidence that ICT skill constraints have an indirect negative impact on firm performance as a result of the restrictions that such skill deficiencies place on ICT adoption and on the intensity of use of ICTs (once they have been installed). However, there is only weak evidence of skill constraints impinging directly on firm performance at given levels of ICT adoption and utilisation.
The impact of content knowledge, specialized content knowledge, peer analysis and self-analysis on pre-service physical education teachers' error detection abilities

This study investigated the change in specialized content knowledge (SCK), specifically error detection skills, and sought to answer the following questions: (a) Does attending a common content knowledge (CCK) and SCK workshop and assessing videotaped performances of a volleyball skill (forearm pass) result in increased ability to identify performance errors in that skill? , and (b) Does attending a CCK and SCK workshop and then assessing one’s own performance have a greater impact on error detection skill development as compared to assessing the performance of a peer? Participants were 20 undergraduate physical education teacher education (PETE) students (12 male and 8 female) enrolled in PETE courses. A pre-test, post-test experimental design was used to determine the effectiveness of increasing undergraduate students’ SCK through a CCK and SCK workshop and video analysis. Pre-test procedures included participants viewing a middle school male and female performing a volleyball forearm pass and evaluating the performance by indicating if they observed or did not observe the critical elements. The CCK and SCK workshop included instruction of the critical elements of the pass and common errors typically demonstrated by beginners. Video analysis included participants evaluating a peer or themselves performing 10 volleyball passes. The study concluded with a post-test evaluating the same male and female middle school student. A two-way repeated measures ANOVA was used to compare the preand posttest means. Results indicated post-test means for the peer analysis and self-analysis groups were significantly higher than pre-test mean scores. No significant difference was found between groups. Results revealed a trend of participants scoring the lowest on the pre-test evaluation showing the largest change in error detection ability from pre-test to post-test. This study demonstrated a short workshop and video analysis increased error detection ability for the volleyball forearm pass in undergraduate PETE majors. Physical education teacher education programs may want to consider implementing short instructional episodes to improve error detection skills. Future research should consider investigating the role of feedback on participants as they practice detecting errors and investigating if the number of errors performed by the model during video analysis effects error detection abilities. THE IMPACT OF CONTENT KNOWLEDGE, SPECIALIZED CONTENT KNOWLEDGE, PEER ANALYSIS AND SELF-ANALYSIS ON PRE-SERVICE PHYSICAL EDUCATION TEACHERS’ ERROR DETECTION ABILITIES An Abstract of a Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree Doctor of Education
EFFICIENT HEURISTICS FOR SIMULATING POPULATION OVERFLOW IN FEED-FORWARD NETWORKS

In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overflow in feed-forward networks. This heuristic attempts to approximate the “optimal” state-dependent change of measure without the need for difficult analysis or costly optimization involved in other recently proposed adaptive importance sampling algorithms. Preliminary simulation experiments with a 4-node feed-forward network yield asymptotically efficient estimates, with relative error increasing at most linearly in the overflow level, where state-independent importance sampling is demonstrably ineffective.
Compressive wireless arrays for bearing estimation

Joint processing of sensor array outputs improves the performance of parameter estimation and hypothesis testing problems beyond the sum of the individual sensor processing results. When the sensors have high data sampling rates, arrays are tethered, creating a disadvantage for their deployment and also limiting their aperture size. In this paper, we develop the signal processing algorithms for randomly deployable wireless sensor arrays that are severely constrained in communication bandwidth. We focus on the acoustic bearing estimation problem and show that when the target bearings are modeled as a sparse vector in the angle space, low dimensional random projections of the microphone signals can be used to determine multiple source bearings by solving an l 1-norm minimization problem. Field data results are shown where only 10 bits of information is passed from each microphone to estimate multiple target bearings.
MIMO channel statistics and signal processing in mode-division multiplexing systems

We review channel models for mode-division multiplexing (MDM) systems, the statistics derived from them, and their implications for system performance and complexity. We present the fundamentals of architectures and algorithms for multi-input multi-output (MIMO) equalization. With careful physical link design and judicious choice of signal processing architectures, the challenges of MIMO signal processing can be overcome in MDM systems.
Modular Multilevel Converter AC Motor Drives With Constant Torque From Zero to Nominal Speed

Modular multilevel converters are shown to have a great potential in the area of medium-voltage drives. Low-distortion output quantities combined with low average switching frequencies for the semiconductor devices create an ideal combination for very high-efficiency drives. However, the large number of devices and capacitors that have to conduct the fundamental-frequency current require more complex converter control techniques than its two-level counterpart. Special care needs to be taken for starting and operation at low speeds, where the low-frequency current may cause significant unbalance between the submodule capacitor voltages and disturb the output waveforms. In this paper, principles for converter operation with high torque in the whole speed range are investigated. Experimental results from a down-scaled 12-kVA prototype converter running a loaded motor at various speeds between standstill and the rated speed are also provided.
A Novel Semantic Annotation Algorithm for Models Based on Associated Scene

An automatic 3D semantic annotation algorithm is proposed based on the associated scene between models. This algorithm uses the semantic context of 3D models to annotate the non-annotated nodes in terms of the annotated nodes. Firstly, this algorithm abstracts the extensible 3D (X3D) scene into the X3D conventional scene tree, transforming the conventional scene tree into an in-line node scene tree. Additionally, the algorithm uses the X3D ontology for semantic reasoning between the scene and the models. Lastly, the algorithm annotates the model files automatically. This study analyses the time and space complexity of the algorithm. Experimental results confirm that this algorithm improves not only the annotation validity but also the retrieval performance.
Geocast in vehicular environments: caching and transmission range control for improved efficiency

Geocast in vehicular ad hoc networks allows to realize applications like virtual warning signs for improved road safety, which address a geographical area rather than an individual vehicle. In this paper we propose to include caching in the geocast forwarding scheme and improved neighborhood selection to address in particular the high velocities of vehicles. High velocities of vehicular networks are a major difference to usual mobile ad hoc networks which assume only moderate node movement. We show that a cache for presently unforwardable messages caused by network partitioning or unfavorable neighbors can significantly improve the geocast delivery success ratio. The improved neighborhood selection taking frequent neighborhood changes into account significantly decreases network load and decreased end-to-end delivery delay.
A SEARCH FOR DISTANT SOLAR SYSTEM BODIES IN THE REGION OF SEDNA

We present the results of a wide-field survey for distant Sedna-like bodies in the outer solar system using the 1.2 m Samuel Oschin Telescope at Palomar Observatory. We searched ∼12,000 deg2 down to a mean limiting magnitude of 21.3 in R. A total number of 53 Kuiper Belt objects and Centaurs have been detected, 25 of which were discovered in this survey. No additional Sedna-like bodies with perihelia beyond 70 AU were found despite a sensitivity to motions out to ∼1000 AU. We place constraints on the size and distribution of objects on Sedna orbits.
Optimal tightening forces for multi-fingered robust manipulation

We address the problem of choosing adequate contact forces to ensure the stability of a multi-fingered grasp in face of external disturbances of unknown intensity. The contact forces we look for are tightening, pre-strain forces rather than active, direction-related blocking forces. We compute such tightening forces, together with blocking forces and a lower-bound approximation of an existing grasp quality measure, in only one linear programming problem. The tightening forces ensure robustness to the largest-minimum resisted disturbance wrench, but a variety of optimal contact forces may be further computed from the desired robustness by solving a quadratic programming problem.
Active Percolation Analysis of Pyramidal Neurons of Somatosensory Cortex

This article describes the investigation of morphological variations among two sets of neuronal cells, namely a control group of wild type mouse cells and a group of cells of a transgenic line. Special attention is given to singular points in the neuronal structure, namely the branching points and extremities of the dendritic processes. The characterization of the spatial distribution of such points is obtained by using a recently reported morphological technique based on forced percolation and window-size compensation, which is particularly suited to the analysis of scattered points, presenting several coexisting densities. Different dispersions were identified in our statistical analysis, suggesting that the transgenic line of neurons is characterized by a more pronounced morphological variation. A classification scheme based on a canonical discriminant function was also considered in order to identify the morphological differences.
TD(0) Converges Provably Faster than the Residual Gradient Algorithm

In Reinforcement Learning (RL) there has been some experimental evidence that the residual gradient algorithm converges slower than the TD(0) algorithm. In this paper, we use the concept of asymptotic convergence rate to prove that under certain conditions the synchronous off-policy TD(0) algorithm converges faster than the synchronous off-policy residual gradient algorithm if the value function is represented in tabular form. This is the first theoretical result comparing the convergence behaviour of two RL algorithms. We also show that as soon as linear function approximation is involved no general statement concerning the superiority of one of the algorithms can be made.
Abstract—clustering Algorithms Are Attractive for the Task Of

class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases. The well-known clustering algorithms offer no solution to the combination of these requirements. In this paper, a density based clustering algorithm (DCBRD) is presented, relying on a knowledge acquired from the data by dividing the data space into overlapped regions. The proposed algorithm discovers arbitrary shaped clusters, requires no input parameters and uses the same definitions of DBSCAN algorithm. We performed an experimental evaluation of the effectiveness and efficiency of it, and compared this results with that of DBSCAN. The results of our experiments demonstrate that the proposed algorithm is significantly efficient in discovering clusters of arbitrary shape and size.
Multi-channel Active Noise Control for All Uncertain Primary and Secondary Paths

Fully adaptive feedforward control algorithm is proposed for general multi-channel active noise control (ANC) when all the noise transmission channels are uncertain. To reduce the actual canceling error, two kinds of virtual errors are introduced and are forced into zero by adjusting three adaptive FIR filter matrices in an on-line manner, which can result in the canceling at the objective points. Unlike other conventional approaches, the proposed algorithm does not need exact identification of the secondary paths, and so requires neither any dither signals nor the PE property of the source noises, which is a great advantage of the proposed adaptive approach.
Omega-6 Fatty Acids and Risk for Cardiovascular Disease: A Science Advisory From the American Heart Association Nutrition Subcommittee of the Council on Nutrition, Physical Activity, and Metabolism; Council on Cardiovascular Nursing; and Council on Epidemiology and Prevention

A large body of literature suggests that higher intakes of omega-6 (or n-6) polyunsaturated fatty acids (PUFAs) reduce risk for coronary heart disease (CHD). However, for the reasons outlined below, some individuals and groups have recommended substantial reductions in omega-6 PUFA intake.1–4 The purpose of this advisory is to review evidence on the relationship between omega-6 PUFAs and the risk of CHD and cardiovascular disease. Omega-6 PUFAs are characterized by the presence of at least 2 carbon-carbon double bonds, with the first bond at the sixth carbon from the methyl terminus. Linoleic acid (LA), an 18-carbon fatty acid with 2 double bonds (18:2 omega-6), is the primary dietary omega-6 PUFA. LA cannot be synthesized by humans, and although firm minimum requirements have not been established for healthy adults, estimates derived from studies in infants and hospitalized patients receiving total parenteral nutrition suggest that an LA intake of ≈0.5% to 2% of energy is likely to suffice. After consumption, LA can be desaturated and elongated to form other omega-6 PUFAs such as γ-linolenic and dihomo-γ-linolenic acids. The latter is converted to the metabolically important omega-6 PUFA arachidonic acid (AA; 20:4 omega-6), the substrate for a wide array of reactive oxygenated metabolites. Because LA accounts for 85% to 90% of the dietary omega-6 PUFA, this advisory focuses primarily on this fatty acid, recognizing that dietary AA, which can affect tissue AA levels,5 may have physiological sequelae.6–8 LA comes primarily from vegetable oils (eg, corn, sunflower, safflower, soy). The average US intake of LA, according to National Health and Nutrition Examination Survey 2001 to 2002 data for adults ≥19 years of age, is 14.8 g/d.9 On the basis of an average intake of 2000 kcal/d, LA intake is 6.7% of energy. AA (≈0.15 g/d) is consumed preformed in meat, …
The Effect of Recurrent Mutation on the Linkage Disequilibrium under a Selective Sweep

A selective sweep describes the reduction of diversity due to strong positive selection. If the mutation rate to a selectively beneficial allele is sufficiently high, Pennings and Hermisson (2006a) have shown, that it becomes likely, that a selective sweep is caused by several individuals. Such an event is called a soft sweep and the complementary event of a single origin of the beneficial allele, the classical case, a hard sweep. We give analytical expressions for the linkage disequilibrium (LD) between two neutral loci linked to the selected locus, depending on the recurrent mutation to the beneficial allele, measured by $D$ and $\hat{\sigma_D^2}$, a quantity introduced by Ohta and Kimura (1969), and conclude that the LD-pattern of a soft sweep differs substantially from that of a hard sweep due to haplotype structure. We compare our results with simulations.
ArchView - Analyzing Evolutionary Aspects of Complex Software Systems

Large and complex software systems are confronted with continuous changes during all stages in their life comprising development, maintenance, migration, and retirement. On the one side these changes are mandatory to guarantee the success of a software system but on the other side changes affect the architecture and design of a software system. Therefore, a continuous observation and analysis of the architecture and the design is needed to early identify shortcomings and resolve them. In this dissertation we propose the ArchView approach that focuses on the analysis and evaluation of software modules regarding their structural and evolutionary characteristics. Software modules are architectural elements that are implemented in source files, classes, or aggregations of them. The primary objective of our approach is to extract higher-level views of software modules and their dependency relationships that allow the spectator to identify structural and evolutionary shortcomings. For the analysis of the structural and evolutionary characteristics of software modules ArchView uses software metrics and coupling relationships. Software metrics quantify the size, complexity, coupling degree, modification and problem frequency of software modules. Coupling relationships show change as well as implemented dependency relationships between modules. Both, metrics and coupling relationships are computed for a number of subsequent source code releases giving insights into the evolution of modules. For the identification of structural and evolutionary shortcomings ArchView introduces a graph representation technique that is based on the principle of measurement mapping. Metric values are mapped to graphical attributes highlighting in particular modules and dependency relationships with noticeable structural and evolutionary characteristics. To handle the various characteristics we present a number of different view configurations that we implemented in a prototype tool. They can be extended and used by engineers in everyday analysis tasks. The evaluation and validation of the ArchView approach and its different view configurations is done with the large open source project Mozilla. We focus on the analysis of the content and layout modules with different higher-level views. Resulting views clearly show the usefulness of ArchView to visualize structural and evolutionary characteristics of Mozilla modules and point out a number of shortcomings in their design.
Chaining Convolution and Correlation in Practice: A Case Study in Visual Tracking

Two dimensional convolution and cross-correlation operations are used in many image processing and computer vision applications, with algorithms commonly using a number of these operations. It is well known that these operations can be performed quickly by using a FFT to reduce computational complexity. In this paper we investigate the extent that the structure of algorithms with multiple convolution and cross-correlation operations can be exploited to further reduce computational complexity. Using the CACTuS visual tracking algorithm as a case study, we demonstrate how successive convolution and correlation operations may be chained together in the Fourier domain by taking into account the growth and shift of the output. We experimentally demonstrate that our chaining technique can result in run-time reductions of up to 55% when compared to the individual FFT approach.
Harmony and dissonance: organizing the people's voices on political controversies

The wikileaks documents about the death of Osama Bin Laden and the debates about the economic crisis in Greece and other European countries are some of the controversial topics being played on the news everyday. Each of these topics has many different aspects, and there is no absolute, simple truth in answering questions such as: should the EU guarantee the financial stability of each member country, or should the countries themselves be solely responsible? To understand the landscape of opinions, it would be helpful to know which politician or other stakeholder takes which position - support or opposition - on these aspects of controversial topics.