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Shoulder Impingement : Short-term effects of a thoracic spine manipulation and a systematic review of physical therapy strategies
(Universidade Federal de São Carlos, 2015-11-18) Haik, Melina Nevoeiro; Camargo, Paula Rezende; https://lattes.cnpq.br/7602596349127054; https://lattes.cnpq.br/8240155487619947
Background: Shoulder impingement syndrome (SIS) is a common cause of shoulder pain complains and numerous treatment strategies are available in the clinic. Questions remain regarding the effects of Thoracic Spinal Manipulation (TSM) on SIS and concerning the efficacy of available techniques on the treatment of this population. Objectives: In a clinical trial, the objective was to evaluate short-term effects of a TSM on pain, function, scapular kinematics and scapular muscle activity in individuals with SIS. In a systematic review, the objective was to summarize current evidence regarding effectiveness of physical therapy to improve pain, function and range of motion in this population. Methods: In the clinical trial, participants were randomly allocated to TSM group (n=30) or sham-TSM group (n=31) and attended 2 intervention sessions over a 1-week period. Shoulder pain, shoulder function (DASH and WORC questionnaires), scapular kinematics and scapular muscle activity were measured. A blinded assessor evaluated the outcomes at day 1, day 2-pre, day 2-post and day 3. In the review, Pubmed, Web of Science, CINAHL Cochrane, Embase, Lilacs, Ibecs and Scielo databases were searched up to April 2015. Randomized controlled trials investigating different modalities of physical therapy in the treatment of patients with SIS on pain, function/disability or range of motion were included. Results: In the clinical trial, TSM group improved pain (1.1 points) and tended to improve function (5.0 points on WORC) over the sham-TSM group after 2 intervention sessions. Scapular upward rotation increased 4.0°, 5.3° and 3.3° at day 2-pre, day 2-post and day 3, respectively, in the TSM group during lowering of the arm. Changes in scapular internal rotation and tilt were not different between groups. Upper and lower trapezius activity decreased in the TSM group and both groups, respectively, during elevation and lowering of the arm. Serratus anterior activity increased in the sham-TSM group. In the review, sixty-two RCTs were included. The majority had a low to moderate risk of bias. Exercise therapy provided high evidence of improvements to the treatment in the short, mid or long-term. Dynamic humeral centering, proprioceptive exercises and manual therapy associated with conventional exercises enhance the improvements in the short-term. Low-level laser, ultrasound, pulsed electromagnetic field and kinesio taping provided moderate and high evidence level towards no benefits to the treatment of SIS. Microwave diathermy, transcutaneous electrical nerve stimulation and isolated manual therapy or acupuncture provided limited evidence of benefits. Conclusion: TSM may be worthy to achieve short-term reduction of shoulder pain, increase of scapular upward rotation and decrease of upper trapezius activity facilitating the application of other movement-based interventions in individuals with SIS. Exercise therapy should be used as the first choice to improve pain, function and range of motion, and the association of manual therapy should be the best choice to accelerate symptoms decrease and progress exercise therapy quickly. Low-level laser therapy, ultrasound, pulsed electromagnetic field and kinesio taping do not provide significant effects to the therapy and therefore could be avoided. More studies are necessary to improve evidence concerning effects of diacutaneous fibrolysis, microwave diathermy, transcutaneous electrical stimulation, acupuncture and isolated manual therapy techniques in the treatment of SIS.
Máquinas de classificação para detectar polaridade de mensagens de texto em redes sociais
(Universidade Federal de São Carlos, 2015-11-18) Von Lochter, Johannes; Almeida, Tiago Agostinho de; https://lattes.cnpq.br/5368680512020633; https://lattes.cnpq.br/8704682239077456
The popularity of social networks have attracted attention of companies. The growing amount of connected users and messages posted per day make these environments fruitful to detect needs, tendencies, opinions, and other interesting information that can feed marketing and sales departments. However, the most social networks impose size limit to messages, which lead users to compact them by using abbreviations, slangs, and symbols. Recent works in literature have reported advances in minimizing the impact created by noisy messages in text categorization tasks by means of semantic dictionaries and ontology models. They are used to normalize and expand short and messy text messages before using them with a machine learning approach. In this way, we have proposed an ensemble of machine learning methods and natural language processing techniques to find the best way to combine text processing approaches with classification methods to automatically detect opinion in short english text messages. Our experiments were diligently designed to ensure statistically sound results, which indicate that the proposed system has achieved a performance higher than the individual established classifiers.