957 resultados para specific needs


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Metadata is data that fully describes the data and the areas they represent, allowing the user to decide on their use as best as possible. Allow reporting on the existence of a set of data linked to specific needs. The use of metadata has the purpose of documenting and organizing a structured organizational data in order to minimize duplication of efforts to locate them and to facilitate maintenance. It also provides the administration of large amounts of data, discovery, retrieval and editing features. The global use of metadata is regulated by a technical group or task force composed of several segments such as industries, universities and research firms. Agriculture in particular is a good example for the development of typical applications using metadata is the integration of systems and equipment, allowing the implementation of techniques used in precision agriculture, the integration of different computer systems via webservices or other type of solution requires the integration of structured data. The purpose of this paper is to present an overview of the standards of metadata areas consolidated as agricultural.

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The wide use of e-technologies represents a great opportunity for underserved segments of the population, especially with the aim of reintegrating excluded individuals back into society through education. This is particularly true for people with different types of disabilities who may have difficulties while attending traditional on-site learning programs that are typically based on printed learning resources. The creation and provision of accessible e-learning contents may therefore become a key factor in enabling people with different access needs to enjoy quality learning experiences and services. Another e-learning challenge is represented by m-learning (which stands for mobile learning), which is emerging as a consequence of mobile terminals diffusion and provides the opportunity to browse didactical materials everywhere, outside places that are traditionally devoted to education. Both such situations share the need to access materials in limited conditions and collide with the growing use of rich media in didactical contents, which are designed to be enjoyed without any restriction. Nowadays, Web-based teaching makes great use of multimedia technologies, ranging from Flash animations to prerecorded video-lectures. Rich media in e-learning can offer significant potential in enhancing the learning environment, through helping to increase access to education, enhance the learning experience and support multiple learning styles. Moreover, they can often be used to improve the structure of Web-based courses. These highly variegated and structured contents may significantly improve the quality and the effectiveness of educational activities for learners. For example, rich media contents allow us to describe complex concepts and process flows. Audio and video elements may be utilized to add a “human touch” to distance-learning courses. Finally, real lectures may be recorded and distributed to integrate or enrich on line materials. A confirmation of the advantages of these approaches can be seen in the exponential growth of video-lecture availability on the net, due to the ease of recording and delivering activities which take place in a traditional classroom. Furthermore, the wide use of assistive technologies for learners with disabilities injects new life into e-learning systems. E-learning allows distance and flexible educational activities, thus helping disabled learners to access resources which would otherwise present significant barriers for them. For instance, students with visual impairments have difficulties in reading traditional visual materials, deaf learners have trouble in following traditional (spoken) lectures, people with motion disabilities have problems in attending on-site programs. As already mentioned, the use of wireless technologies and pervasive computing may really enhance the educational learner experience by offering mobile e-learning services that can be accessed by handheld devices. This new paradigm of educational content distribution maximizes the benefits for learners since it enables users to overcome constraints imposed by the surrounding environment. While certainly helpful for users without disabilities, we believe that the use of newmobile technologies may also become a fundamental tool for impaired learners, since it frees them from sitting in front of a PC. In this way, educational activities can be enjoyed by all the users, without hindrance, thus increasing the social inclusion of non-typical learners. While the provision of fully accessible and portable video-lectures may be extremely useful for students, it is widely recognized that structuring and managing rich media contents for mobile learning services are complex and expensive tasks. Indeed, major difficulties originate from the basic need to provide a textual equivalent for each media resource composing a rich media Learning Object (LO). Moreover, tests need to be carried out to establish whether a given LO is fully accessible to all kinds of learners. Unfortunately, both these tasks are truly time-consuming processes, depending on the type of contents the teacher is writing and on the authoring tool he/she is using. Due to these difficulties, online LOs are often distributed as partially accessible or totally inaccessible content. Bearing this in mind, this thesis aims to discuss the key issues of a system we have developed to deliver accessible, customized or nomadic learning experiences to learners with different access needs and skills. To reduce the risk of excluding users with particular access capabilities, our system exploits Learning Objects (LOs) which are dynamically adapted and transcoded based on the specific needs of non-typical users and on the barriers that they can encounter in the environment. The basic idea is to dynamically adapt contents, by selecting them from a set of media resources packaged in SCORM-compliant LOs and stored in a self-adapting format. The system schedules and orchestrates a set of transcoding processes based on specific learner needs, so as to produce a customized LO that can be fully enjoyed by any (impaired or mobile) student.

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The dynamicity and heterogeneity that characterize pervasive environments raise new challenges in the design of mobile middleware. Pervasive environments are characterized by a significant degree of heterogeneity, variability, and dynamicity that conventional middleware solutions are not able to adequately manage. Originally designed for use in a relatively static context, such middleware systems tend to hide low-level details to provide applications with a transparent view on the underlying execution platform. In mobile environments, however, the context is extremely dynamic and cannot be managed by a priori assumptions. Novel middleware should therefore support mobile computing applications in the task of adapting their behavior to frequent changes in the execution context, that is, it should become context-aware. In particular, this thesis has identified the following key requirements for novel context-aware middleware that existing solutions do not fulfil yet. (i) Middleware solutions should support interoperability between possibly unknown entities by providing expressive representation models that allow to describe interacting entities, their operating conditions and the surrounding world, i.e., their context, according to an unambiguous semantics. (ii) Middleware solutions should support distributed applications in the task of reconfiguring and adapting their behavior/results to ongoing context changes. (iii) Context-aware middleware support should be deployed on heterogeneous devices under variable operating conditions, such as different user needs, application requirements, available connectivity and device computational capabilities, as well as changing environmental conditions. Our main claim is that the adoption of semantic metadata to represent context information and context-dependent adaptation strategies allows to build context-aware middleware suitable for all dynamically available portable devices. Semantic metadata provide powerful knowledge representation means to model even complex context information, and allow to perform automated reasoning to infer additional and/or more complex knowledge from available context data. In addition, we suggest that, by adopting proper configuration and deployment strategies, semantic support features can be provided to differentiated users and devices according to their specific needs and current context. This thesis has investigated novel design guidelines and implementation options for semantic-based context-aware middleware solutions targeted to pervasive environments. These guidelines have been applied to different application areas within pervasive computing that would particularly benefit from the exploitation of context. Common to all applications is the key role of context in enabling mobile users to personalize applications based on their needs and current situation. The main contributions of this thesis are (i) the definition of a metadata model to represent and reason about context, (ii) the definition of a model for the design and development of context-aware middleware based on semantic metadata, (iii) the design of three novel middleware architectures and the development of a prototypal implementation for each of these architectures, and (iv) the proposal of a viable approach to portability issues raised by the adoption of semantic support services in pervasive applications.

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The use of scaffolds for Tissue Engineering (TE) is increasing due to their efficacy in helping the body rebuild damaged or diseased tissue. Hydroxyapatite (HA) is the most suitable bioactive ceramic to be used in orthopaedic reconstruction since it replicates the mineral component of the hard tissues, and it has therefore excellent biocompatibility properties. The temporal and spatial control of the tissue regeneration process is the limit to be overcome in order to treat large bone and osteochondral defects. In this thesis we describe the realization of a magnetic scaffolds able to attract and take up growth factors or other bio-agents in vivo via a driving magnetic force. This concept involves the use of magnetic nanoparticles (MNP) functionalized with selected growth factors or stem cells. These functionalized MNP act as shuttles transporting the bio-agents towards and inside the scaffold under the effect of the magnetic field, enhancing the control of tissue regeneration processes. This scaffold can be imagined as a fixed “station” that provides a unique possibility to adjust the scaffold activity to the specific needs of the healing tissue. Synthetic bone graft substitutes, made of collagen or biomineralized collagen (i.e. biomimetic Hydroxyapatite/collagen composites) were used as starting materials for the fabrication of magnetic scaffolds. These materials are routinely used clinically to replace damaged or diseased cartilaginous or bone tissue. Our magnetization technique is based on a dip-coating process consisting in the infilling of biologically inspired porous scaffolds with aqueous biocompatible ferrofluids’ suspensions. In this technique, the specific interconnected porosity of the scaffolds allows the ferrofluids to be drawn inside the structure by capillarity. A subsequent freeze-drying process allows the solvent elimination while keeping very nearly the original shape and porosity of the scaffolds. The remaining magnetic nanoparticles, which are trapped in the structure, lead to the magnetization of the HA/Collagen scaffold. We demonstrate here the possibility to magnetize commercially available scaffolds up to magnetization values that are used in drug delivery processes. The preliminary biocompatibility test showed that the investigated scaffolds provide a suitable micro-environment for cells. The biocompatibility of scaffold facilitates the growth and proliferation of osteogenic cells.

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Recently in most of the industrial automation process an ever increasing degree of automation has been observed. This increasing is motivated by the higher requirement of systems with great performance in terms of quality of products/services generated, productivity, efficiency and low costs in the design, realization and maintenance. This trend in the growth of complex automation systems is rapidly spreading over automated manufacturing systems (AMS), where the integration of the mechanical and electronic technology, typical of the Mechatronics, is merging with other technologies such as Informatics and the communication networks. An AMS is a very complex system that can be thought constituted by a set of flexible working stations, one or more transportation systems. To understand how this machine are important in our society let considerate that every day most of us use bottles of water or soda, buy product in box like food or cigarets and so on. Another important consideration from its complexity derive from the fact that the the consortium of machine producers has estimated around 350 types of manufacturing machine. A large number of manufacturing machine industry are presented in Italy and notably packaging machine industry,in particular a great concentration of this kind of industry is located in Bologna area; for this reason the Bologna area is called “packaging valley”. Usually, the various parts of the AMS interact among them in a concurrent and asynchronous way, and coordinate the parts of the machine to obtain a desiderated overall behaviour is an hard task. Often, this is the case in large scale systems, organized in a modular and distributed manner. Even if the success of a modern AMS from a functional and behavioural point of view is still to attribute to the design choices operated in the definition of the mechanical structure and electrical electronic architecture, the system that governs the control of the plant is becoming crucial, because of the large number of duties associated to it. Apart from the activity inherent to the automation of themachine cycles, the supervisory system is called to perform other main functions such as: emulating the behaviour of traditional mechanical members thus allowing a drastic constructive simplification of the machine and a crucial functional flexibility; dynamically adapting the control strategies according to the different productive needs and to the different operational scenarios; obtaining a high quality of the final product through the verification of the correctness of the processing; addressing the operator devoted to themachine to promptly and carefully take the actions devoted to establish or restore the optimal operating conditions; managing in real time information on diagnostics, as a support of the maintenance operations of the machine. The kind of facilities that designers can directly find on themarket, in terms of software component libraries provides in fact an adequate support as regard the implementation of either top-level or bottom-level functionalities, typically pertaining to the domains of user-friendly HMIs, closed-loop regulation and motion control, fieldbus-based interconnection of remote smart devices. What is still lacking is a reference framework comprising a comprehensive set of highly reusable logic control components that, focussing on the cross-cutting functionalities characterizing the automation domain, may help the designers in the process of modelling and structuring their applications according to the specific needs. Historically, the design and verification process for complex automated industrial systems is performed in empirical way, without a clear distinction between functional and technological-implementation concepts and without a systematic method to organically deal with the complete system. Traditionally, in the field of analog and digital control design and verification through formal and simulation tools have been adopted since a long time ago, at least for multivariable and/or nonlinear controllers for complex time-driven dynamics as in the fields of vehicles, aircrafts, robots, electric drives and complex power electronics equipments. Moving to the field of logic control, typical for industrial manufacturing automation, the design and verification process is approached in a completely different way, usually very “unstructured”. No clear distinction between functions and implementations, between functional architectures and technological architectures and platforms is considered. Probably this difference is due to the different “dynamical framework”of logic control with respect to analog/digital control. As a matter of facts, in logic control discrete-events dynamics replace time-driven dynamics; hence most of the formal and mathematical tools of analog/digital control cannot be directly migrated to logic control to enlighten the distinction between functions and implementations. In addition, in the common view of application technicians, logic control design is strictly connected to the adopted implementation technology (relays in the past, software nowadays), leading again to a deep confusion among functional view and technological view. In Industrial automation software engineering, concepts as modularity, encapsulation, composability and reusability are strongly emphasized and profitably realized in the so-calledobject-oriented methodologies. Industrial automation is receiving lately this approach, as testified by some IEC standards IEC 611313, IEC 61499 which have been considered in commercial products only recently. On the other hand, in the scientific and technical literature many contributions have been already proposed to establish a suitable modelling framework for industrial automation. During last years it was possible to note a considerable growth in the exploitation of innovative concepts and technologies from ICT world in industrial automation systems. For what concerns the logic control design, Model Based Design (MBD) is being imported in industrial automation from software engineering field. Another key-point in industrial automated systems is the growth of requirements in terms of availability, reliability and safety for technological systems. In other words, the control system should not only deal with the nominal behaviour, but should also deal with other important duties, such as diagnosis and faults isolations, recovery and safety management. Indeed, together with high performance, in complex systems fault occurrences increase. This is a consequence of the fact that, as it typically occurs in reliable mechatronic systems, in complex systems such as AMS, together with reliable mechanical elements, an increasing number of electronic devices are also present, that are more vulnerable by their own nature. The diagnosis problem and the faults isolation in a generic dynamical system consists in the design of an elaboration unit that, appropriately processing the inputs and outputs of the dynamical system, is also capable of detecting incipient faults on the plant devices, reconfiguring the control system so as to guarantee satisfactory performance. The designer should be able to formally verify the product, certifying that, in its final implementation, it will perform itsrequired function guarantying the desired level of reliability and safety; the next step is that of preventing faults and eventually reconfiguring the control system so that faults are tolerated. On this topic an important improvement to formal verification of logic control, fault diagnosis and fault tolerant control results derive from Discrete Event Systems theory. The aimof this work is to define a design pattern and a control architecture to help the designer of control logic in industrial automated systems. The work starts with a brief discussion on main characteristics and description of industrial automated systems on Chapter 1. In Chapter 2 a survey on the state of the software engineering paradigm applied to industrial automation is discussed. Chapter 3 presentes a architecture for industrial automated systems based on the new concept of Generalized Actuator showing its benefits, while in Chapter 4 this architecture is refined using a novel entity, the Generalized Device in order to have a better reusability and modularity of the control logic. In Chapter 5 a new approach will be present based on Discrete Event Systems for the problemof software formal verification and an active fault tolerant control architecture using online diagnostic. Finally conclusive remarks and some ideas on new directions to explore are given. In Appendix A are briefly reported some concepts and results about Discrete Event Systems which should help the reader in understanding some crucial points in chapter 5; while in Appendix B an overview on the experimental testbed of the Laboratory of Automation of University of Bologna, is reported to validated the approach presented in chapter 3, chapter 4 and chapter 5. In Appendix C some components model used in chapter 5 for formal verification are reported.

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Drug abuse is a major global problem which has a strong impact not only on the single individual but also on the entire society. Among the different strategies that can be used to address this issue an important role is played by identification of abusers and proper medical treatment. This kind of therapy should be carefully monitored in order to discourage improper use of the medication and to tailor the dose according to the specific needs of the patient. Hence, reliable analytical methods are needed to reveal drug intake and to support physicians in the pharmacological management of drug dependence. In the present Ph.D. thesis original analytical methods for the determination of drugs with a potential for abuse and of substances used in the pharmacological treatment of drug addiction are presented. In particular, the work has been focused on the analysis of ketamine, naloxone and long-acting opioids (buprenorphine and methadone), oxycodone, disulfiram and bupropion in human plasma and in dried blood spots. The developed methods are based on the use of high performance liquid chromatography (HPLC) coupled to various kinds of detectors (mass spectrometer, coulometric detector, diode array detector). For biological sample pre-treatment different techniques have been exploited, namely solid phase extraction and microextraction by packed sorbent. All the presented methods have been validated according to official guidelines with good results and some of these have been successfully applied to the therapeutic drug monitoring of patients under treatment for drug abuse.

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This thesis work aims to develop original analytical methods for the determination of drugs with a potential for abuse, for the analysis of substances used in the pharmacological treatment of drug addiction in biological samples and for the monitoring of potentially toxic compounds added to street drugs. In fact reliable analytical techniques can play an important role in this setting. They can be employed to reveal drug intake, allowing the identification of drug users and to assess drug blood levels, assisting physicians in the management of the treatment. Pharmacological therapy needs to be carefully monitored indeed in order to optimize the dose scheduling according to the specific needs of the patient and to discourage improper use of the medication. In particular, different methods have been developed for the detection of gamma-hydroxybutiric acid (GHB), prescribed for the treatment of alcohol addiction, of glucocorticoids, one of the most abused pharmaceutical class to enhance sport performance and of adulterants, pharmacologically active compounds added to illicit drugs for recreational purposes. All the presented methods are based on capillary electrophoresis (CE) and high performance liquid chromatography (HPLC) coupled to various detectors (diode array detector, mass spectrometer). Biological samples pre-treatment was carried out using different extraction techniques, liquid-liquid extraction (LLE) and solid phase extraction (SPE). Different matrices have been considered: human plasma, dried blood spots, human urine, simulated street drugs. These developed analytical methods are individually described and discussed in this thesis work.

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Objective: Significant others are central to patients' experience and management of their cancer illness. Building on our validation of the Distress Thermometer (DT) for family members, this investigation examines individual and collective distress in a sample of cancer patients and their matched partners, accounting for the aspects of gender and role. Method: Questionnaires including the DT were completed by a heterogeneous sample of 224 couples taking part in a multisite study. Results: Our investigation showed that male patients (34.2%), female patients (31.9%), and male partners (29.1%) exhibited very similar levels of distress, while female partners (50.5%) exhibited much higher levels of distress according to the DT. At the dyad level just over half the total sample contained at least one individual reporting significant levels of distress. Among dyads with at least one distressed person, the proportion of dyads where both individuals reported distress was greatest (23.6%). Gender and role analyses revealed that males and females were not equally distributed among the four categories of dyads (i.e. dyads with no distress; dyads where solely the patient or dyads where solely the partner is distressed; dyads where both are distressed). Conclusion: A remarkable number of dyads reported distress in one or both partners. Diverse patterns of distress within dyads suggest varying risks of psychosocial strain. Screening patients' partners in addition to patients themselves may enable earlier identification of risk settings. The support offered to either member of such dyads should account for their role- and gender-specific needs. Copyright © 2010 John Wiley ; Sons, Ltd.

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A major unresolved question in developmental neurobiology is how the nervous system is adapted to the specific needs of the organism at different life stages. In the holometabolous insect Drosophila melanogaster, the larval ventral nervous system (VNS) is comprised of similar repeating segments, as opposed to the adult VNS, which varies greatly from segment to segment both in number and types of neurons. The adult-specific neurons of each segment are generated by 25 distinct types of neuronal progenitor cells called neuroblasts (NBs) that appear in a stereotyped array (Truman et al., 2004). Each NB divides repeatedly to produce a distinct set of daughter cells termed a lineage, which is bilaterally symmetric but present to varying degrees in each segment. These daughter cells can be distinguished by their position within the nervous system as well as by their axonal projections. Each of the 25 NBs produces neurons; if both daughter cells are present in a lineage then both sibling populations survived, whereas if only one projection is seen cell death occurred, leaving a hemilineage (half lineage). In some lineages, the same sibling type survives in all segments in which the lineage appears, but in others, the surviving sibling type varies across segments, resulting in a different morphology for the same lineage in different segments. How are these differences in survival and morphology controlled? The Hox genes provide positional information for developing structures along the anterior-posterior (AP) axis of animals. They encode transcription factors, thereby controlling the activity of genes down stream. In the postembryonic VNS, each NB lineage features its own characteristic expression pattern of Hox genes Antp and Ubx, which can vary from segment-to-segment, and can thereby cause variation in the number of neural cells and axonal projections that survive. This study defines the wild-type expression pattern of Antp and elucidates the role of Antp in gain of function studies. These studies are possible due to the MARCM (Mosaic Analysis with a Repressible Cell Marker) method, which allows the genetically manipulated cells to be specifically labeled in an otherwise normal, unlabeled organism. The results indicate that Antp is expressed in a segment-, lineage-, and hemilineage-specific manner. Antp is sufficient for both anterior and posterior transformations of particular lineages, including promotion of cell death and/or survival as well as axon guidance.

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The United States¿ Federal and State laws differentiate between acceptable (or, legal) and unacceptable (illegal) behavior by prescribing restrictive punishment to citizens and/or groups that violate these established rules. These regulations are written to treat every person equally and to fairly serve justice; furthermore, the sanctions placed on offenders seek to reform illegal behavior through limitations on freedoms and rehabilitative programs. Despite the effort to treat all offenders fairly regardless of social identity categories (e.g., sex, race, ethnicity, socioeconomic status, age, ability, and gender and sexual orientation) and to humanely eliminate illegal behavior, the American penal system perpetuates de facto discrimination against a multitude of peoples. Furthermore, soaring recidivism rates caused by unsuccessful re-entry of incarcerated offenders puts economic stress on Federal and State budgets. For these reasons, offenders, policy-makers, and law-abiding citizens should all have a vested interest in reforming the prison system. This thesis focuses on the failure of the United States corrections system to adequately address the gender-specific needs of non-violent female offenders. Several factors contribute to the gender-specific discrimination that women experience in the criminal justice system: 1) Trends in female criminality that skew women¿s crime towards drug-related crimes, prostitution, and property offenses; 2) Mandatory minimum sentences for drug crimes that are disproportionate to the crime committed; 3) So-called ¿gender-neutral¿ educational, vocational, substance abuse, and mental health programming that intends to equally rehabilitate men and women, but in fact favors men; and 4) The isolating nature of prison structures that inhibits smooth re-entry into society. I argue that a shift in the placement and treatment of non-violent female offenders is necessary for effective rehabilitation and for reducing recidivism rates. The first component of this shift is the design and implementation of gender- responsive treatment (GRT) rather than gender-neutral approaches in rehabilitative programming. The second shift is the utilization of alternatives to incarceration, which provide both more humane treatment of offenders and smoother reintegration to society. Drawing on recent scholarship, information from prison advocacy organizations, and research with men in an alternative program, I provide a critical analysis of current policies and alternative programs, and suggest several proposals for future gender- responsive programs in prisons and in place of incarceration. I argue that the expansion of gender-responsive programming and alternatives to incarceration respond to the marginalization of female offenders, address concerns about the financial sustainability of the United States criminal justice system, and tackle high recidivism rates.

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Cognitive Remediation approaches have proven to be effective in enhancing cognitive functions and psychosocial outcomes in multi-episode schizophrenia patients. However, there is a paucity of studies evaluating Cognitive Remediation in first-episode psychosis patients and in those symptomatically at-risk for psychosis. This is despite the growing evidence that impairments in neuro- and social-cognitive functions are already present in early psychosis and even in at-risk mental states and are important predictors of poor outcome, including transition to psychosis. Moreover, Cognitive Remediation applied at younger ages and at earlier stages of schizophrenia yielded greater cognitive and functional gains. Therefore, Cognitive Remediation may be especially appropriate for early intervention. Against this background, we will review and discuss the efficacy of current Cognitive Remediation approaches in early psychosis and in at-risk mental states. Furthermore, we will present novel interventions that are tailored to the specific needs and developmental tasks of patients at-risk for psychosis and aim at improving social and self-referential cognitions as well as interpersonal skills

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Prevention of psychoses has been intensively investigated within the past two decades, and particularly, prediction has been much advanced. Depending on the applied risk indicators, current criteria are associated with average, yet significantly heterogeneous transition rates of ≥30 % within 3 years, further increasing with longer follow-up periods. Risk stratification offers a promising approach to advance current prediction as it can help to reduce heterogeneity of transition rates and to identify subgroups with specific needs and response patterns, enabling a targeted intervention. It may also be suitable to improve risk enrichment. Current results suggest the future implementation of multi-step risk algorithms combining sensitive risk detection by cognitive basic symptoms (COGDIS) and ultra-high-risk (UHR) criteria with additional individual risk estimation by a prognostic index that relies on further predictors such as additional clinical indicators, functional impairment, neurocognitive deficits, and EEG and structural MRI abnormalities, but also considers resilience factors. Simply combining COGDIS and UHR criteria in a second step of risk stratification produced already a 4-year hazard rate of 0.66. With regard to prevention, two recent meta-analyses demonstrated that preventive measures enable a reduction in 12-month transition rates by 54-56 % with most favorable numbers needed to treat of 9-10. Unfortunately, psychosocial functioning, another important target of preventive efforts, did not improve. However, these results are based on a relatively small number of trials; and more methodologically sound studies and a stronger consideration of individual profiles of clinical needs by modular intervention programs are required

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PURPOSE: Patients with chronic depression (CD) by definition respond less well to standard forms of psychotherapy and are more likely to be high utilizers of psychiatric resources. Therefore, the aim of this guidance paper is to provide a comprehensive overview of current psychotherapy for CD. The evidence of efficacy is critically reviewed and recommendations for clinical applications and research are given. METHODS: We performed a systematic literature search to identify studies on psychotherapy in CD, evaluated the retrieved documents and developed evidence tables and recommendations through a consensus process among experts and stakeholders. RESULTS: We developed 5 recommendations which may help providers to select psychotherapeutic treatment options for this patient group. The EPA considers both psychotherapy and pharmacotherapy to be effective in CD and recommends both approaches. The best effect is achieved by combined treatment with psychotherapy and pharmacotherapy, which should therefore be the treatment of choice. The EPA recommends psychotherapy with an interpersonal focus (e.g. the Cognitive Behavioural Analysis System of Psychotherapy [CBASP]) for the treatment of CD and a personalized approach based on the patient's preferences. DISCUSSION: The DSM-5 nomenclature of persistent depressive disorder (PDD), which includes CD subtypes, has been an important step towards a more differentiated treatment and understanding of these complex affective disorders. Apart from dysthymia, ICD-10 still does not provide a separate entity for a chronic course of depression. The differences between patients with acute episodic depression and those with CD need to be considered in the planning of treatment. Specific psychotherapeutic treatment options are recommended for patients with CD. CONCLUSION: Patients with chronic forms of depression should be offered tailored psychotherapeutic treatments that address their specific needs and deficits. Combination treatment with psychotherapy and pharmacotherapy is the first-line treatment recommended for CD. More research is needed to develop more effective treatments for CD, especially in the longer term, and to identify which patients benefit from which treatment algorithm.

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A wide variety of spatial data collection efforts are ongoing throughout local, state and federal agencies, private firms and non-profit organizations. Each effort is established for a different purpose but organizations and individuals often collect and maintain the same or similar information. The United States federal government has undertaken many initiatives such as the National Spatial Data Infrastructure, the National Map and Geospatial One-Stop to reduce duplicative spatial data collection and promote the coordinated use, sharing, and dissemination of spatial data nationwide. A key premise in most of these initiatives is that no national government will be able to gather and maintain more than a small percentage of the geographic data that users want and desire. Thus, national initiatives depend typically on the cooperation of those already gathering spatial data and those using GIs to meet specific needs to help construct and maintain these spatial data infrastructures and geo-libraries for their nations (Onsrud 2001). Some of the impediments to widespread spatial data sharing are well known from directly asking GIs data producers why they are not currently involved in creating datasets that are of common or compatible formats, documenting their datasets in a standardized metadata format or making their datasets more readily available to others through Data Clearinghouses or geo-libraries. The research described in this thesis addresses the impediments to wide-scale spatial data sharing faced by GIs data producers and explores a new conceptual data-sharing approach, the Public Commons for Geospatial Data, that supports user-friendly metadata creation, open access licenses, archival services and documentation of parent lineage of the contributors and value- adders of digital spatial data sets.

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Very few studies have described MUP-1 concentrations and measured prevalence of Laboratory Animal Allergy (LAA) at such a diverse institution as the private medical school (MS) that is the focus of this study. Air sampling was performed in three dissimilar animal research facilities at MS and quantitated using a commercially available ELISA. Descriptive data was obtained from an anonymous laboratory animal allergy survey given to both animal facility employees and the researchers who utilize these facilities alike. Logistic regression analysis was then implemented to investigate specific factors that may be predictive of developing LAA as well as factors influencing the reporting of LAA symptoms to the occupational health program. Concentrations of MUP-1 detected ranged from below detectable levels (BDL) to a peak of 22.64 ng/m3 . Overall, 68 employees with symptoms claimed they improved while away from work and only 25 employees reported their symptoms to occupational health. Being Vietnamese, a smoker, not wearing a mask, and working in any facility longer than one year were all significant predictors of having LAA symptoms. This study suggests a LAA monitoring system that relies on self-reporting can be inadequate in estimating LAA problems. In addition, efforts need to be made to target training and educational materials for non-native English speaking employees to overcome language and cultural barriers and address their specific needs. ^