Kielellinen erityisvaikeus : oirekuva ja familiaalisuus potilasasiakirjojen perusteella

Goals. Specific language impairment (SLI) has a negative impact on child s speech and language development and interaction. Disorder may be associated with a wide range of comorbid problems. In clinical speech therapy it is important to see the child as a whole so that the rehabilitation can be targeted properly. The aim of this study was to describe the linguistic-cognitive and comorbid symptoms of children with SLI at the age of five, as well as to provide an overwiew of the developmental disorders in the families. The study is part of a larger research project, which will examine paths of development and quality of life of children with SLI as young adults. Methods. The data consisted of patient documents of 100 5-year old children, who were examined in Lastenlinna mainly at 1998. Majority of the subjects were boys, and children s primary diagnosis was either F80.1 or F80.2, which was most common, or both. The diagnosis and the information about the linguistic-cognitive status and comorbid symptoms were collected from reports of medical doctors and experts of other fields, as well as mentions related to familiality. Linguistic-cognitive symptoms were divided into subclasses of speech motor functions, prosessing of language, comprehension of language and use of language. Comorbid symptoms were divided into subclasses of interaction, activity and attention, emotional and behavior problems and neurologic problems. Statistical analyses were based mainly on Pearson s Chi Square test. Results and conclusions. Problems in language processing and speech motor functions were most common of the linguistic-cognitive symptoms. Most of the children had symptoms from two or three symptom classes, and it seemed that girls had more symptoms than boys. Usually children did not have any comorbid symptoms, or had them from one or three symptom classes. Of the comorbid symptoms the most prevalent ones were problems in activity and attention and neurological symptoms, which consisted mostly of motoric and visuomotoric symptoms. The most common of the comorbid diagnoses was F82, specific developmental disorder of motor function. According to literature children with SLI may have problems in mental health, but the results of this study did not confirm that. Children with diagnosis F80.2 had more linguistic-cognitive and comorbid symptoms than children with diagnosis F80.1. The cluster analyses based on all the symtoms revealed four subgroups of the subjects. Of the subjects 85 percent had a positive family history of developmental disorders, and the most prevalent problem in the families was delayed speech development. This study outlined the symptom profile of children with SLI and laid a foundation for the future longitudinal study. The results suggested that there are differences between linguistic-cognitive symptoms of boys and girls, which is important to notice especially when assessing and diagnosing children with SLI.

Dietary habits and obesity: the role of emotional and cognitive factors

In post-industrialised societies, food is more plentiful, accessible and palatable than ever before and technological development has reduced the need for physical activity. Consequently, the prevalence of obesity is increasing, which is problematic as obesity is related to a number of diseases. Various psychological and social factors have an important influence on dietary habits and the development of obesity in the current food-rich and sedentary environments. The present study concentrates on the associations of emotional and cognitive factors with dietary intake and obesity as well as on the role these factors play in socioeconomic disparities in diet. Many people cognitively restrict their food intake to prevent weight gain or to lose weight, but research on whether restrained eating is a useful weight control strategy has produced conflicting findings. With respect to emotional factors, the evidence is accumulating that depressive symptoms are related to less healthy dietary intake and obesity, but the mechanisms explaining these associations remain unclear. Furthermore, it is not fully understood why socioeconomically disadvantaged individuals tend to have unhealthier dietary habits and the motives underlying food choices (e.g., price and health) could be relevant in this respect. The specific aims of the study were to examine 1) whether obesity status and dieting history moderate the associations of restrained eating with overeating tendencies, self-control and obesity indicators; 2) whether the associations of depressive symptoms with unhealthier dietary intake and obesity are attributable to a tendency for emotional eating and a low level of physical activity self-efficacy; and 3) whether the absolute or relative importance of food choice motives (health, pleasure, convenience, price, familiarity and ethicality) contribute to the socioeconomic disparities in dietary habits. The study was based on a large population-based sample of Finnish adults: the participants were men (N=2325) and women (N=2699) aged 25-74 who took part in the DILGOM (Dietary, Lifestyle and Genetic Determinants of Obesity and Metabolic Syndrome) sub-study of the National FINRISK Study 2007. The participants weight, height, waist circumference and body fat percentage were measured in a health examination. Psychological eating styles (the Three-Factor Eating Questionnaire-R18), food choice motives (a shortened version of the Food Choice Questionnaire), depressive symptoms (the Center for Epidemiological Studies Depression Scale) and self-control (the Brief Self-Control Scale) were measured with pre-existing questionnaires. A validated food frequency questionnaire was used to assess the average consumption of sweet and non-sweet energy-dense foods and vegetables/fruit. Self-reported total years of education and gross household income were used as indicators of socioeconomic position. The results indicated that 1) restrained eating was related to a lower body mass index, waist circumference, emotional eating and uncontrolled eating, and to a higher self-control in obese participants and current/past dieters. In contrast, the associations were the opposite in normal weight individuals and those who had never dieted. Thus, restrained eating may be related to better weight control among obese individuals and those with dieting experiences, while among others it may function as an indicator of problems with eating and an attempt to solve them. 2) Emotional eating and depressive symptoms were both related to less healthy dietary intake, and the greater consumption of energy-dense sweet foods among participants with elevated depressive symptoms was attributable to the susceptibility for emotional eating. In addition, emotional eating and physical activity self-efficacy were both important in explaining the positive association between depressive symptoms and obesity. 3) The lower vegetable/fruit intake and higher energy-dense food intake among individuals with a low socioeconomic position were partly explained by the higher priority they placed on price and familiarity and the lower priority they gave to health motives in their daily food choices. In conclusion, although policy interventions to change the obesogenic nature of the current environment are definitely needed, knowledge of the factors that hinder or facilitate people s ability to cope with the food-rich environment is also necessary. This study implies that more emphasis should be placed on various psychological and social factors in weight control programmes and interventions.

Ribavirin-Induced Anemia in Hepatitis C Virus Patients Undergoing Combination Therapy

The current standard of care for hepatitis C virus (HCV) infection - combination therapy with pegylated interferon and ribavirin - elicits sustained responses in only similar to 50% of the patients treated. No alternatives exist for patients who do not respond to combination therapy. Addition of ribavirin substantially improves response rates to interferon and lowers relapse rates following the cessation of therapy, suggesting that increasing ribavirin exposure may further improve treatment response. A key limitation, however, is the toxic side-effect of ribavirin, hemolytic anemia, which often necessitates a reduction of ribavirin dosage and compromises treatment response. Maximizing treatment response thus requires striking a balance between the antiviral and hemolytic activities of ribavirin. Current models of viral kinetics describe the enhancement of treatment response due to ribavirin. Ribavirin-induced anemia, however, remains poorly understood and precludes rational optimization of combination therapy. Here, we develop a new mathematical model of the population dynamics of erythrocytes that quantitatively describes ribavirin-induced anemia in HCV patients. Based on the assumption that ribavirin accumulation decreases erythrocyte lifespan in a dose-dependent manner, model predictions capture several independent experimental observations of the accumulation of ribavirin in erythrocytes and the resulting decline of hemoglobin in HCV patients undergoing combination therapy, estimate the reduced erythrocyte lifespan during therapy, and describe inter-patient variations in the severity of ribavirin-induced anemia. Further, model predictions estimate the threshold ribavirin exposure beyond which anemia becomes intolerable and suggest guidelines for the usage of growth hormones, such as erythropoietin, that stimulate erythrocyte production and avert the reduction of ribavirin dosage, thereby improving treatment response. Our model thus facilitates, in conjunction with models of viral kinetics, the rational identification of treatment protocols that maximize treatment response while curtailing side effects.

Bayesian Decentralized Spectrum Sensing in Cognitive Radio Networks

This paper considers the problem of spectrum sensing, i.e., the detection of whether or not a primary user is transmitting data by a cognitive radio. The Bayesian framework is adopted, with the performance measure being the probability of detection error. A decentralized setup, where N sensors use M observations each to arrive at individual decisions that are combined at a fusion center to form the overall decision is considered. The unknown fading channel between the primary sensor and the cognitive radios makes the individual decision rule computationally complex, hence, a generalized likelihood ratio test (GLRT)-based approach is adopted. Analysis of the probabilities of false alarm and miss detection of the proposed method reveals that the error exponent with respect to M is zero. Also, the fusion of N individual decisions offers a diversity advantage, similar to diversity reception in communication systems, and a tight bound on the error exponent is presented. Through an analysis in the low power regime, the number of observations needed as a function of received power, to achieve a given probability of error is determined. Monte-Carlo simulations confirm the accuracy of the analysis.

Spectral Sensing of Adaptive Frequency Hopping Signal for Cognitive Radio

The issue of dynamic spectrum scene analysis in any cognitive radio network becomes extremely complex when low probability of intercept, spread spectrum systems are present in environment. The detection and estimation become more complex if frequency hopping spread spectrum is adaptive in nature. In this paper, we propose two phase approach for detection and estimation of frequency hoping signals. Polyphase filter bank has been proposed as the architecture of choice for detection phase to efficiently detect the presence of frequency hopping signal. Based on the modeling of frequency hopping signal it can be shown that parametric methods of line spectral analysis are well suited for estimation of frequency hopping signals if the issues of order estimation and time localization are resolved. An algorithm using line spectra parameter estimation and wavelet based transient detection has been proposed which resolves above issues in computationally efficient manner suitable for implementation in cognitive radio. The simulations show promising results proving that adaptive frequency hopping signals can be detected and demodulated in a non cooperative context, even at a very low signal to noise ratio in real time.

Cyclic Prefix Based Cooperative Sequential Spectrum Sensing Algorithms for OFDM

This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user is using Orthogonal Frequency Division Multiplexing (OFDM). For this we develop cooperative sequential detection algorithms that use the autocorrelation property of cyclic prefix (CP) used in OFDM systems. We study the effect of timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power. We also modify the detector to mitigate the effects of these impairments. The performance of the proposed algorithms is studied via simulations. We show that sequential detection can significantly improve the performance over a fixed sample size detector.

Error exponent analysis of energy-based bayesian spectrum sensing under fading channels

This paper analyzes the error exponents in Bayesian decentralized spectrum sensing, i.e., the detection of occupancy of the primary spectrum by a cognitive radio, with probability of error as the performance metric. At the individual sensors, the error exponents of a Central Limit Theorem (CLT) based detection scheme are analyzed. At the fusion center, a K-out-of-N rule is employed to arrive at the overall decision. It is shown that, in the presence of fading, for a fixed number of sensors, the error exponents with respect to the number of observations at both the individual sensors as well as at the fusion center are zero. This motivates the development of the error exponent with a certain probability as a novel metric that can be used to compare different detection schemes in the presence of fading. The metric is useful, for example, in answering the question of whether to sense for a pilot tone in a narrow band (and suffer Rayleigh fading) or to sense the entire wide-band signal (and suffer log-normal shadowing), in terms of the error exponent performance. The error exponents with a certain probability at both the individual sensors and at the fusion center are derived, with both Rayleigh as well as log-normal shadow fading. Numerical results are used to illustrate and provide a visual feel for the theoretical expressions obtained.

Antenna Selection in Interference-Constrained Underlay Cognitive Radios: SEP-Optimal Rule and Performance Benchmarking

In the underlay mode of cognitive radio, secondary users are allowed to transmit when the primary is transmitting, but under tight interference constraints that protect the primary. However, these constraints limit the secondary system performance. Antenna selection (AS)-based multiple antenna techniques, which exploit spatial diversity with less hardware, help improve secondary system performance. We develop a novel and optimal transmit AS rule that minimizes the symbol error probability (SEP) of an average interference-constrained multiple-input-single-output secondary system that operates in the underlay mode. We show that the optimal rule is a non-linear function of the power gain of the channel from the secondary transmit antenna to the primary receiver and from the secondary transmit antenna to the secondary receive antenna. We also propose a simpler, tractable variant of the optimal rule that performs as well as the optimal rule. We then analyze its SEP with L transmit antennas, and extensively benchmark it with several heuristic selection rules proposed in the literature. We also enhance these rules in order to provide a fair comparison, and derive new expressions for their SEPs. The results bring out new inter-relationships between the various rules, and show that the optimal rule can significantly reduce the SEP.

Cognitive radio implementation for a frequency hopping primary signal

Frequency hopping communications, used in the military present significant opportunities for spectrum reuse via the cognitive radio technology. We propose a MAC which incorporates hop instant identification, and supports network discovery and formation, QOS Scheduling and secondary communications. The spectrum sensing algorithm is optimized to deal with the problem of spectral leakage. The algorithms are implemented in a SDR platform based test bed and measurement results are presented.

Metal based photosensitizers of tetradentate Schiff base: Promising role in anti-tumor activity through singlet oxygen generation mechanism

In the present investigation, a Schiff base N'(1),N'(3)-bis(Z)-(2-hydroxynapthyl)methylidene]benzene-1,3-dicarbod ihydrazide (L-1) and its Co(II), Ni(II) and Cu(II) complexes have been synthesized and characterized as novel photosensitizing agents for photodynamic therapy (PDT). The interaction of these complexes with calf thymus DNA (CT DNA) has been explored using absorption, thermal denaturation and viscometric studies. The experimental results revealed that Co(II) and Ni(II) complexes on binding to CT DNA imply a covalent mode, most possibly involving guanine N7 nitrogen of DNA, with an intrinsic binding constant K-b of 4.5 x 10(4) M-1 and 4.2 x 10(4) M-1, respectively. However, interestingly, the Cu(II) complex is involved in the surface binding to minor groove via phosphate backbone of DNA double helix with an intrinsic binding constant K-b of 5.7 x 10(4) M-1. The Co(II), Ni(II) and Cu(II) complexes are active in cleaving supercoiled (SC) pUC19 DNA on photoexposure to UV-visible light of 365 nm, through O-1(2) generation with quantum yields of 0.28, 0.25 and 0.30, respectively. Further, these complexes are cytotoxic in A549 lung cancer cells, showing an enhancement of cytotoxicity upon light irradiation. (C) 2013 Elsevier B.V. All rights reserved.

Subject independent human action recognition using spatio-depth information and meta-cognitive RBF network

In this paper, we present a machine learning approach for subject independent human action recognition using depth camera, emphasizing the importance of depth in recognition of actions. The proposed approach uses the flow information of all 3 dimensions to classify an action. In our approach, we have obtained the 2-D optical flow and used it along with the depth image to obtain the depth flow (Z motion vectors). The obtained flow captures the dynamics of the actions in space time. Feature vectors are obtained by averaging the 3-D motion over a grid laid over the silhouette in a hierarchical fashion. These hierarchical fine to coarse windows capture the motion dynamics of the object at various scales. The extracted features are used to train a Meta-cognitive Radial Basis Function Network (McRBFN) that uses a Projection Based Learning (PBL) algorithm, referred to as PBL-McRBFN, henceforth. PBL-McRBFN begins with zero hidden neurons and builds the network based on the best human learning strategy, namely, self-regulated learning in a meta-cognitive environment. When a sample is used for learning, PBLMcRBFN uses the sample overlapping conditions, and a projection based learning algorithm to estimate the parameters of the network. The performance of PBL-McRBFN is compared to that of a Support Vector Machine (SVM) and Extreme Learning Machine (ELM) classifiers with representation of every person and action in the training and testing datasets. Performance study shows that PBL-McRBFN outperforms these classifiers in recognizing actions in 3-D. Further, a subject-independent study is conducted by leave-one-subject-out strategy and its generalization performance is tested. It is observed from the subject-independent study that McRBFN is capable of generalizing actions accurately. The performance of the proposed approach is benchmarked with Video Analytics Lab (VAL) dataset and Berkeley Multimodal Human Action Database (MHAD). (C) 2013 Elsevier Ltd. All rights reserved.

SEP-optimal antenna selection for average interference constrained underlay cognitive radios

In the underlay mode of cognitive radio, secondary users can transmit when the primary is transmitting, but under tight interference constraints, which limit the secondary system performance. Antenna selection (AS)-based multiple antenna techniques, which require less hardware and yet exploit spatial diversity, help improve the secondary system performance. In this paper, we develop the optimal transmit AS rule that minimizes the symbol error probability (SEP) of an average interference-constrained secondary system that operates in the underlay mode. We show that the optimal rule is a non-linear function of the power gains of the channels from secondary transmit antenna to primary receiver and secondary transmit antenna to secondary receive antenna. The optimal rule is different from the several ad hoc rules that have been proposed in the literature. We also propose a closed-form, tractable variant of the optimal rule and analyze its SEP. Several results are presented to compare the performance of the closed-form rule with the ad hoc rules, and interesting inter-relationships among them are brought out.

Cross-Linked, Biodegradable, Cytocompatible Salicylic Acid Based Polyesters for Localized, Sustained Delivery of Salicylic Acid: An In Vitro Study

In order to suppress chronic inflammation while supporting cell proliferation, there has been a continuous surge toward development of polymers with the intention of delivering anti-inflammatory molecules in a sustained manner. In the above backdrop, we report the synthesis of a novel, stable, cross-linked polyester with salicylic acid (SA) incorporated in the polymeric backbone and propose a simple synthesis route by melt condensation. The as-synthesized polymer was hydrophobic with a glass transition temperature of 1 degrees C, which increases to 17 degrees C upon curing. The combination of NMR and FT-IR spectral techniques established the ester linkages in the as-synthesized SA-based polyester. The pH-dependent degradation rate and the rate of release of salicylic acid from the as-synthesized SA-based polymer were studied at physiological conditions in vitro. The polyester underwent surface erosion and exhibited linear degradation kinetics in which a change in degradation rate is observed after 4-10 days and 24% mass loss was recorded after 4 months at 37 degrees C and pH 7.4. The delivery of salicylic acid also showed a similar change in slopes, with a sustained release rate of 3.5% in 4 months. The cytocompatibility studies of these polyesters were carried out with C2C12 murine myoblast cells using techniques like MTT assay and flow cytometry. Our results strongly suggest that SA-based polyester supports cell proliferation for 3 days in culture and do not cause cell death (<7%), as quantified by propidium iodide (PI) stained cells. Hence, these polyesters can be used as implant materials for localized, sustained delivery of salicylic acid and have applications in adjuvant cancer therapy, chronic wound healing, and as an alternative to commercially available polymers like poly(lactic acid) and poly(glycolic acid) or their copolymers.

Antenna Selection with Power Adaptation in Interference-Constrained Cognitive Radios

The performance of an underlay cognitive radio (CR) system, which can transmit when the primary is on, is curtailed by tight constraints on the interference it can cause to the primary receiver. Transmit antenna selection (AS) improves the performance of underlay CR by exploiting spatial diversity but with less hardware. However, the selected antenna and its transmit power now both depend on the channel gains to the secondary and primary receivers. We develop a novel Chernoffbound based optimal AS and power adaptation (CBBOASPA) policy that minimizes an upper bound on the symbol error probability (SEP) at the secondary receiver, subject to constraints on the average transmit power and the average interference to the primary. The optimal antenna and its power are presented in an insightful closed form in terms of the channel gains. We then analyze the SEP of CBBOASPA. Extensive benchmarking shows that the SEP of CBBOASPA for both MPSK and MQAM is one to two orders of magnitude lower than several ad hoc AS policies and even optimal AS with on-off power control.

Multimodal therapy for complete regression of malignant melanoma using constrained nonlinear optimal dynamic inversion

Using a realistic nonlinear mathematical model for melanoma dynamics and the technique of optimal dynamic inversion (exact feedback linearization with static optimization), a multimodal automatic drug dosage strategy is proposed in this paper for complete regression of melanoma cancer in humans. The proposed strategy computes different drug dosages and gives a nonlinear state feedback solution for driving the number of cancer cells to zero. However, it is observed that when tumor is regressed to certain value, then there is no need of external drug dosages as immune system and other therapeutic states are able to regress tumor at a sufficiently fast rate which is more than exponential rate. As model has three different drug dosages, after applying dynamic inversion philosophy, drug dosages can be selected in optimized manner without crossing their toxicity limits. The combination of drug dosages is decided by appropriately selecting the control design parameter values based on physical constraints. The process is automated for all possible combinations of the chemotherapy and immunotherapy drug dosages with preferential emphasis of having maximum possible variety of drug inputs at any given point of time. Simulation study with a standard patient model shows that tumor cells are regressed from 2 x 107 to order of 105 cells because of external drug dosages in 36.93 days. After this no external drug dosages are required as immune system and other therapeutic states are able to regress tumor at greater than exponential rate and hence, tumor goes to zero (less than 0.01) in 48.77 days and healthy immune system of the patient is restored. Study with different chemotherapy drug resistance value is also carried out. (C) 2014 Elsevier Ltd. All rights reserved.