Dual Content Semantics, privative adjectives and dynamic compositionality

This paper defends the view that common nouns have a dual semantic structure that includes extension-determining and non-extension-determining components. I argue that the non-extension-determining components are part of linguistic meaning because they play a key compositional role in certain constructions, especially in privative noun phrases such as "fake gun" and "counterfeit document". Furthermore, I show that if we modify the compositional interpretation rules in certain simple ways, this dual content account of noun phrase modification can be implemented in a type-driven formal semantic framework. In addition, I also argue against traditional accounts of privative noun phrases which can be paired with the assumption that nouns do not have a dual semantic structure. At the most general level, this paper presents a proposal for how we can begin to integrate a psychologically realistic account of lexical semantics with a linguistically plausible compositional semantic framework

The Structure of Semantic Competence: Compositionality as an Innate Constraint of The Faculty of Language

This paper defends the view that the Faculty of Language is compositional, i.e., that it computes the meaning of complex expressions from the meanings of their immediate constituents and their structure. I fargue that compositionality and other competing constraints on the way in which the Faculty of Language computes the meanings of complex expressions should be understood as hypotheses about innate constraints of the Faculty of Language. I then argue that, unlike compositionality, most of the currently available non-compositional constraints predict incorrect patterns of early linguistic development. This supports the view that the Faculty of Language is com- positional. More generally, this paper presents a way of framing the compositionality debate (by focusing on its implications for language acquisition) that can lead to its even- tual resolution, so it will hopefully also interest theorists who disagree with its main conclusion

THE EFFECTS OF ACUTE PSYCHOLOGICAL STRESS ON ENZYMES REGULATING THE KYNURENINE PATHWAY

INTRODUCTION An emerging body of literature recognizes the relationship between stress and inflammation. The kynurenine pathway is particularly relevant because it accounts for the majority of tryptophan’s metabolism [1]. Activation of the kynurenine pathway depletes the tryptophan pool for serotonin, and has been associated with the emergence of depressive-like symptoms and “sickness behaviour” (anhedonia, anxiety, and sleep disturbances) in animals [1]. The first and rate limiting step of the kynurenine pathway converts tryptophan to kynurenine and can be catalyzed by tryptophan 2,3-dioxygenase (TDO), which operates under basal conditions, or by indoleamine 2,3-dioxygenase 1 (IDO1), which predominates under inflammatory states [2]. Indeed, previous research has shown that IDO1 can be induced by cytokines, such as tumor necrosis factor alpha (TNFα) [1,2]. Recent data from our lab indicates that TNFα protein is increased in the amygdala 4 h after exposure to an acute stressor. Hence, this investigation attempted to determine the effects of acute stress on mRNA levels of enzymes regulating the kynurenine pathway. METHODS Adult, male, Sprague Dawley rats (N=48) were subjected to 120 minutes of restraint stress and rapidly decapitated 1 h, 2 h, 4 h, 6 h, or 24 h later. Trunk blood was collected and analyzed for circulating corticosterone and TNFα levels. Brains were extracted and excised into amygdalae, hypothalami, prefrontal cortices, and hippocampi. RNA was isolated, followed by cDNA synthesis, and quantitative PCR (qPCR) to quantify mRNA levels of IDO1, TDO, kynurenine aminotransferase 1 (KAT1), kynurenine 3-monooxygenase (KYNM), kynureninase (KYNU), and 3-hydroxyanthranilate 3,4-dioxygenase. RESULTS Results indicated that plasma corticosterone levels were elevated 2 h after the acute stressor, while circulating levels of TNFα were increased at the 1 h and the 2 h post stress time points. Analysis of amygdalar qPCR data indicated an upregulation of IDO1 mRNA at the 1 h time point, and increased KYNM and KYNU mRNA at the 4 h time point. There were no amygdalar mRNA changes in the other genes. Regarding hypothalamic data, there was an increase in TDO mRNA at the 4 h time point and KYNU mRNA at the 1 h time point. DISCUSSION AND CONCLUSIONS Increases in expression of kynurenine pathway enzymes in the amygdala occurred in a time dependent manner. Taken together, the data is concordant with previous reports, which indicate that IDO1 and TDO can be induced by TNFα and corticosterone, respectively [1,2]. The result of increased amygdalar KYNM and KYNU mRNA following acute stress represents a novel finding and suggests that stress shifts the kynurenine pathway towards neurotoxic metabolites, such as 3-hyroxykynurenine and quinolinic acid, which may aggravate the symptoms of inflammation-induced depression. Follow up work on this study would investigate mRNA changes in other brain regions, such as the prefrontal cortex and the hippocampus. In addition, plasma and brain concentrations of tryptophan, kynurenine, kynurenic acid, and quinolinic acid would be determined to see if they are in accordance with the mRNA data. Ultimately, the present study highlights the kynurenine pathway as a potential therapeutic target for inflammation-induced depression

The Promises and Perils of Radio as a Medium of Faith in a Q’eqchi’-Maya Catholic Community

Because their parish is large, dispersed, and overwhelmingly rural, FM radio is one of the few reliable means through which the Q’eqchi’-Maya Catholics of San Felipe in Alta Verapaz, Guatemala, can communicate with each other en masse. Yet, because it is a one-way medium, it is also impossible to gauge how its intended audience is responding, or if is even there to receive broadcasted messages. Drawing on ethnographic material collected in 2005 (on the use of radio broadcasting to call together ritual participants) and 2016 (on an ultimately failed attempt to launch a radio station to serve rural parishioners), this paper examines how parish lay leaders attempt to negotiate this dilemma as they work to create a unique sense of Q’eqchi’-Maya Catholic community

Multi Look-Up Table Digital Predistortion for RF Power Amplifier Linearization

Premi extraordinari doctorat curs 2007-2008, àmbit d’Enginyeria de les TICAquesta Tesi Doctoral se centra en el disseny d'un nou linealitzador de Predistorsió Digital (Digital Predistortion - DPD) capaç de compensar la dinàmica i els efectes no lineals introduïts pels Amplificadors de Potència (Power Amplifiers - PAs). Un dels trets més rellevants d'aquest nou predistorsionador digital i adaptatiu consisteix en ser deduïble a partir d'un model de PA anomenat Nonlinear Auto-Regressive Moving Average (NARMA). A més, la seva arquitectura multi-LUT (multi-Taula) permet la implementació en un dispositiu Field Programmable Gate Array (FPGA).La funció de predistorsió es realitza en banda base, per tant, és independent de la banda freqüencial on es durà a terme l'amplificació del senyal de RF, el que pot resultar útil si tenim en compte escenaris multibanda o reconfigurables. D'altra banda, el fet que aquest DPD tingui en compte els efectes de memòria introduïts pel PA, representa una clara millora de les prestacions aconseguides per un simple DPD sense memòria. En comparació amb d'altres DPDs basats en models més computacionalment complexos, com és el cas de les xarxes neuronals amb memòria (Time-Delayed Neural Networks - TDNN), la estructura recursiva del DPD proposat permet reduir el nombre de LUTs necessàries per compensar els efectes de memòria del PA. A més, la seva estructura multi-LUT permet l'escalabilitat, és a dir, activar or desactivar les LUTs que formen el DPD en funció de la dinàmica que presenti el PA.En una primera aproximació al disseny del DPD, és necessari identificar el model NARMA del PA. Un dels majors avantatges que presenta el model NARMA és la seva capacitat per trobar un compromís entre la fidelitat en l'estimació del PA i la complexitat computacional introduïda. Per reforçar aquest compromís, l' ús d'algoritmes heurístics de cerca, com són el Simulated Annealing o els Genetic Algorithms, s'utilitzen per trobar els retards que millor caracteritzen la memòria del PA i per tant, permeten la reducció del nombre de coeficients necessaris per caracteritzar-la. Tot i així, la naturalesa recursiva del model NARMA comporta que, de cara a garantir l'estabilitat final del DPD, cal dur a terme un estudi previ sobre l'estabilitat del model.Una vegada s'ha obtingut el model NARMA del PA i s'ha verificat l'estabilitat d'aquest, es procedeix a l'obtenció de la funció de predistorsió a través del mètode d'identificació predictiu. Aquest mètode es basa en la continua identificació del model NARMA del PA i posteriorment, a partir del model obtingut, es força al PA perquè es comporti de manera lineal. Per poder implementar la funció de predistorsió en la FPGA, cal primer expressar-la en forma de combinacions en paral·lel i cascada de les anomenades Cel·les Bàsiques de Predistorsió (BPCs), que són les unitats fonamentals que composen el DPD. Una BPC està formada per un multiplicador complex, un port RAM dual que actua com a LUT (taula de registres) i un calculador d'adreces. Les LUTs s'omplen tenint en compte una distribució uniforme dels continguts i l'indexat d'aquestes es duu a terme mitjançant el mòdul de l'envoltant del senyal. Finalment, l'adaptació del DPD consisteix en monitoritzar els senyals d'entrada i sortida del PA i anar duent a terme actualitzacions periòdiques del contingut de les LUTs que formen les BPCs. El procés d'adaptació del contingut de les LUTs es pot dur a terme en la mateixa FPGA encarregada de fer la funció de predistorsió, o de manera alternativa, pot ser duta a terme per un dispositiu extern (com per exemple un DSP - Digital Signal Processor) en una escala de temps més relaxada. Per validar l'exposició teòrica i provar el bon funcionalment del DPD proposat en aquesta Tesi, es proporcionen resultats tant de simulació com experimentals que reflecteixen els objectius assolits en la linealització del PA. A més, certes qüestions derivades de la implementació pràctica, tals com el consum de potència o la eficiència del PA, són també tractades amb detall.This Ph.D. thesis addresses the design of a new Digital Predistortion (DPD) linearizer capable to compensate the unwanted nonlinear and dynamic behavior of power amplifiers (PAs). The distinctive characteristic of this new adaptive DPD is its deduction from a Nonlinear Auto Regressive Moving Average (NARMA) PA behavioral model and its particular multi look-up table (LUT) architecture that allows its implementation in a Field Programmable Gate Array (FPGA) device.The DPD linearizer presented in this thesis operates at baseband, thus becoming independent on the final RF frequency band and making it suitable for multiband or reconfigurable scenarios. Moreover, the proposed DPD takes into account PA memory effects compensation which representsan step forward in overcoming classical limitations of memoryless predistorters. Compared to more computational complex DPDs with dynamic compensation, such Time-Delayed Neural Networks (TDNN), this new DPD takes advantage of the recursive nature of the NARMA structure to relax the number of LUTs required to compensate memory effects in PAs. Furthermore, its parallel multi-LUT architecture is scalable, that is, permits enabling or disabling the contribution of specific LUTs depending on the dynamics presented by a particular PA.In a first approach, it is necessary to identify a NARMA PA behavioral model. The extraction of PA behavioral models for DPD linearization purposes is carried out by means of input and output complex envelope signal observations. One of the major advantages of the NARMA structure regards its capacity to deal with the existing trade-off between computational complexity and accuracy in PA behavioral modeling. To reinforce this compromise, heuristic search algorithms such the Simulated Annealing or Genetic Algorithms are utilized to find the best sparse delays that permit accurately reproducing the PA nonlinear dynamic behavior. However, due to the recursive nature of the NARMA model, an stability test becomes a previous requisite before advancing towards DPD linearization.Once the PA model is identified and its stability verified, the DPD function is extracted applying a predictive predistortion method. This identification method relies just on the PA NARMA model and consists in adaptively forcing the PA to behave as a linear device. Focusing in the DPD implementation, it is possible to map the predistortion function in a FPGA, but to fulfill this objective it is first necessary to express the predistortion function as a combined set of LUTs.In order to store the DPD function into a FPGA, it has to be stated in terms of parallel and cascade Basic Predistortion Cells (BPCs), which are the fundamental building blocks of the NARMA based DPD. A BPC is formed by a complex multiplier, a dual port RAM memory block acting as LUT and an address calculator. The LUT contents are filled following an uniform spacing procedure and its indexing is performed with the amplitude (modulus) of the signal's envelope.Finally, the DPD adaptation consists in monitoring the input-output data and performing frequent updates of the LUT contents that conform the BPCs. This adaptation process can be carried out in the same FPGA in charge of performing the DPD function, or alternatively can be performed by an external device (i.e. a DSP device) in a different time-scale than real-time operation.To support all the theoretical design and to prove the linearization performance achieved by this new DPD, simulation and experimental results are provided. Moreover, some issues derived from practical experimentation, such as power consumption and efficiency, are also reported and discussed within this thesis.Award-winningPostprint (published version

Dynamic selection and estimation of the digital predistorter parameters for power amplifier linearization

© © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a new technique that dynamically estimates and updates the coefficients of a digital predistorter (DPD) for power amplifier (PA) linearization. The proposed technique is dynamic in the sense of estimating, at every iteration of the coefficient's update, only the minimum necessary parameters according to a criterion based on the residual estimation error. At the first step, the original basis functions defining the DPD in the forward path are orthonormalized for DPD adaptation in the feedback path by means of a precalculated principal component analysis (PCA) transformation. The robustness and reliability of the precalculated PCA transformation (i.e., PCA transformation matrix obtained off line and only once) is tested and verified. Then, at the second step, a properly modified partial least squares (PLS) method, named dynamic partial least squares (DPLS), is applied to obtain the minimum and most relevant transformed components required for updating the coefficients of the DPD linearizer. The combination of the PCA transformation with the DPLS extraction of components is equivalent to a canonical correlation analysis (CCA) updating solution, which is optimum in the sense of generating components with maximum correlation (instead of maximum covariance as in the case of the DPLS extraction alone). The proposed dynamic extraction technique is evaluated and compared in terms of computational cost and performance with the commonly used QR decomposition approach for solving the least squares (LS) problem. Experimental results show that the proposed method (i.e., combining PCA with DPLS) drastically reduces the amount of DPD coefficients to be estimated while maintaining the same linearization performance.Peer ReviewedPostprint (author's final draft

"Reporting of Two or More Races in the 1999 American Community Survey"

This paper investigates the causes of western Germany's remarkably poor performance since 1992. The paper challenges the view that the poor record of the nineties, particularly the marked deterioration in public finances since unification, might be largely attributable to unification. Instead, the analysis highlights the role of ill-timed and overly ambitious fiscal consolidation in conjunction with tight monetary policies of an exceptional length and degree. The issue of fiscal sustainability and Germany's fiscal and monetary policies are assessed both in the light of economic theory and in comparison to the best practices of other more successful countries. The analysis concludes that Germany's dismal record of the nineties must not be seen as a direct and apparently inevitable result of unification. Rather, the record arose as a perfectly unnecessary consequence of unsound macro demand policies conducted under the Bundesbank's dictate in response to it, policies that caused the severe and protracted de-stabilization of western Germany in the first place.

Workshops at IMS2023

Lists future events that should be of interest to practitioners and researchers.Peer ReviewedPostprint (published version

Reporting of Two or More Races In the 1999 American Community Survey

This study presents data on race, collected at selected sites throughout the country for the 1999 American Community Survey (ACS). In particular, the distribution of the population by race and Hispanic or Latino origin is examined, as are the reporting of multiple races, number of races, and major race combinations and the extent to which the race and Hispanic/Latino questions were not answered. Although the ACS sites were not intended to be a nationally representative sample, the study's results provide important insights into what might be learned from Census 2000.