From acute to chronic pain: tapentadol in the progressive stages of this disease entity

OBJECTIVE: Chronic pain is now recognized as a neural disease, which results from a maladaptive functional and structural transformation process occurring over time. In its chronic phase, pain is not just a symptom but also a disease entity. Therefore, pain must be properly addressed, as many patients still report unsatisfactory pain control despite on-going treatment. The selection of the therapy - taking into account the pathophysiological mechanisms of pain - and the right timing can result in a successful analgesic outcome. This review will present the functional and structural modifications leading to chronification of pain, focusing on the role of tapentadol in this setting. MATERIALS AND METHODS: For inclusion in this review, research studies were retrieved via a keyword-based query of multiple databases (MEDLINE, Embase, Cochrane). The search was last updated in November 2016; no limitations were applied. RESULTS: Functional and structural abnormalities of the nervous system associated with pain chronification have been reported in several conditions, including osteoarthritis, chronic back pain, chronic pelvic pain and fibromyalgia. Correct identification and treatment of pain in recurrent/progressive stage is crucial to prevent chronification and related changes in neural structures. Among analgesic drugs, tapentadol, with its dual mechanism of action (opioid agonist and noradrenaline reuptake blocker), has recently resulted active in pain control at both central and spinal level. CONCLUSIONS: Tapentadol represents a suitable candidate for patients at early progressive stage of pain who have developed neuroplasticity with modification of pain pathways. The availability of different doses of tapentadol may help clinicians to tailor treatment based on the individual need of each patient, with the aim to enhance therapeutic appropriateness in the treatment of musculoskeletal and neuropathic pain

A Benchmarking of DCM Based Architectures for Position and Velocity Controlled Walking of Humanoid Robots

This paper contributes towards the development and comparison of Divergent-Component-of-Motion (DCM) based control architectures for humanoid robot locomotion. More precisely, we present and compare several DCM based implementations of a three layer control architecture. From top to bottom, these three layers are here called: trajectory optimization, simplified model control, and whole-body QP control. All layers use the DCM concept to generate references for the layer below. For the simplified model control layer, we present and compare both instantaneous and Receding Horizon Control controllers. For the whole-body QP control layer, we present and compare controllers for position and velocity control robots. Experimental results are carried out on the one-meter tall iCub humanoid robot. We show which implementation of the above control architecture allows the robot to achieve a walking velocity of 0.41 meters per second.Comment: Submitted to Humanoids201

GenColors: Annotation and comparative genomics made easy

GenColors is a web-based software/database system initially aimed at an improved and accelerated annotation of prokaryotic genomes making extensive use of genome comparison (Romualdi et al., _Bioinformatics_ 2005; Romualdi et al., _Methods Mol. Biol._ 2007). It offers a seamless integration of data from ongoing sequencing projects and annotated genomic sequences obtained from GenBank. With GenColors dedicated genome browsers containing a group of related genomes can be easily set up and maintained. The tool has been efficiently used for sequenceing and annotating the Borrelia garinii genome and is currently applied to a number of other ongoing genome projects on _Legionella_, _Pseudomonas_ and _E. coli_ genomes. Examples for freely accessible GenColors-based dedicated genome browsers are the Spirochetes Genome Browser SGB ("sgb.fli-leibniz.de":http://sgb.fli-leibniz.de), the Photogenome Browser CGB ("cgb.fli-leibniz.de":http://cgb.fli-leibniz.de) and the Enterobacter Genome Browser ENGENE ("engene.fli-leibniz.de":http://engene.fli-leibniz.de). The system has now been adapted to handle also eukaryotic genomes. A first application of this feature is the annotation and analysis of two fungal species (unpublished). Another GenColors-based tool is the Jena Prokaryotic Genome Viewer - JPGV ("jpgv.fli-leibniz.de":http://jpgv.fli-leibniz.de). Contrary to the dedicated browsers it offers information on almost all finished bacterial genomes. Currently, it includes 1140 genomic elements of 293 species

The State of the Canadian Appointment Process After Liberal Reforms

In 2016, the newly elected Liberal government introduced reforms to the appointments system following well established partisan selections by previous governments. The government claimed that the new policy would provide Canadians with a more honourable, merit-based appointment process that would be free from political interference. This paper assesses the extent to which the objectives of the new policy came to fruition. The research examines the process of citizen participation by evaluating 1,168 Governor-in-Council (GIC) appointments made by the Liberal government to 204 federal institutions over the first four years of the program. The paper compares this group to 1,428 GIC appointments made by the former Conservative government during its final term in office. The research explores whether the reforms have changed the type and quality of appointments to federal organizations since the new system came into effect. The analysis uses the publicly available demographic information of geographic location, educational background, occupation, and gender for each appointee. This paper provides critical insight into current and future processes of citizen participation and discusses its implications for democratic politics in Canada. The research shows that the Liberal reforms did not improve the quality of appointments to federal organizations. The relevant demographic information for the Liberal appointees was similar to that of the Harper government, which meant the new changes tended to focus on representation rather than qualifications

Malattia trombotica: condizioni cliniche ad aumentato rischio e terapia anticoagulante

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Machine Learning S-Wave Scattering Phase Shifts Bypassing the Radial Schr\"odinger Equation

We present a machine learning model resting on convolutional neural network (CNN) capable to yield accurate scattering phase shifts in s-wave caused by different three-dimensional spherically symmetric potentials at fixed collision energy thereby bypassing the radial Schr\"odinger equation. We obtain good performance even in the presence of potential instances supporting bound states

PENGARUH KETELADANAN GURU DALAM IMPLEMENTASI PENDIDIKAN KARAKTER: TINJAUAN PERSPEKTIF PESERTA DIDIK

Abstrak: Penelitian ini bertujuan untuk memperoleh informasi tentang pengaruh keteladanan guru terhadap upaya implementasi penanaman pendidikan karakter ditinjau dari perspektif peserta didik. Metode penelitian yang peneliti gunakan adalah studi literatur dan penelitian deskriptif. Teknik pengumpulan data dilakukan dengan mengumpulkan dan mengolah sumber bacaan seperti buku dan refrensi lain yang terkait dengan topik penelitian. Selain itu, peneliti juga melakukan wawancara dengan empat peserta didik dari gender, sekolah, dan daerah yang berbeda. Setelah melakukan penelitian, peneliti menemukan bahwa keteladanan yang diperlihatkan oleh guru memberi persepsi dan pengaruh terhadap cara berpikir dan perilaku peserta didik. Penanaman pendidikan karakter tidak cukup jika hanya sebatas retorika dari guru karena peserta didik juga mengharapkan adanya sinkronisasi antara perkataan dan tindakan guru itu sendiri untuk memberi inspirasi keteladanan. Empat narasumber juga mengaku bahwa ada cara berpikir dan perilaku dalam dirinya yang terpengaruh dari keteladanan guru.Abstract:  This study aims to obtain information about the influence of teacher model on efforts to implement character education in the perspective of students. A literature review and descriptive research are the research methods used by the researcher. Collecting and analyzing reading sources such as books and other references relating to the research topic are used as data gathering approaches. In addition, the researcher conducted interviews with four students of various genders, schools, and geographical locations. After performing the investigation, the researcher discovered that the teacher's model had an impact on the students' way of thinking and behavior. Character education is insufficient if it is restricted to rhetoric from the teacher, because students need the teacher's words and deeds to be in sync in order to encourage exemplary behavior. Four interviewees also admitted that there are ways of thinking and behavior in them that are influenced by the teacher's model

Telaah Potensi Reunifikasi Tiongkok Terhadap Taiwan: Tinjauan Teori Attitudinal Factor

This study attempts to examine the potential of China's reunification of Taiwan, which has been fought for up until the time of Xi Jinping. The Chinese side has made various efforts to achieve unification, one of which is proposing the "one country, two systems" model that would make Taiwan part of a Chinese province with the high autonomy. However, Taiwan still refused the invitation to reunify China. Using an approach from integrative factor theory, specifically Michael Haas's attitudinal factor, the researchers found that the potential for reunification will be difficult to materialize in the near future due to differences in ideology, Taiwan's distrust of China's involvement, Taiwan's strengthening of identity, and US intervention. China must change its approach if it is to achieve reunification by avoiding methods of military intimidation and strongly committed to respecting the autonomy of the reunified regions to gain complete trust all of Taiwan.Penelitian ini mencoba untuk mengkaji potensi reunifikasi Tiongkok terhadap Taiwan yang terus diperjuangkan hingga era pemerintahan Xi Jinping. Pihak Tiongkok telah melakukan berbagai upaya untuk mewujudkan reunifikasi, salah satunya dengan menawarkan model “Satu Negara Dua Sistem" yang akan menjadikan Taiwan sebagai bagian provinsi Tiongkok yang mempunyai status otonomi tinggi. Namun, Taiwan masih menolak ajakan reunifikasi dari Tiongkok. Menggunakan pendekatan teori faktor integrasi, yakni Attitudinal Factor dari Michael Haas, peneliti menemukan bahwa potensi reunifikasi akan sulit terwujud dalam waktu dekat dikarenakan perbedaan ideologi, kecurigaan Taiwan terhadap komitmen Tiongkok, menguatnya identitas Taiwan, dan adanya campur tangan Amerika Serikat. Tiongkok perlu mengubah pendekatan jika ingin merealisasikan reunifikasi dengan menghindari metode ancaman militer dan berkomitmen tinggi menghormati otonomi daerah-daerah reunifikasi sehingga mendapatkan kepercayaan penuh dari Taiwan

Diagnosis and classification of pediatric acute appendicitis by artificial intelligence methods: An investigator-independent approach

Acute appendicitis is one of the major causes for emergency surgery in childhood and adolescence. Appendectomy is still the therapy of choice, but conservative strategies are increasingly being studied for uncomplicated inflammation. Diagnosis of acute appendicitis remains challenging, especially due to the frequently unspecific clinical picture. Inflammatory blood markers and imaging methods like ultrasound are limited as they have to be interpreted by experts and still do not offer sufficient diagnostic certainty. This study presents a method for automatic diagnosis of appendicitis as well as the differentiation between complicated and uncomplicated inflammation using values/parameters which are routinely and unbiasedly obtained for each patient with suspected appendicitis. We analyzed full blood counts, c-reactive protein (CRP) and appendiceal diameters in ultrasound investigations corresponding to children and adolescents aged 0–17 years from a hospital based population in Berlin, Germany. A total of 590 patients (473 patients with appendicitis in histopathology and 117 with negative histopathological findings) were analyzed retrospectively with modern algorithms from machine learning (ML) and artificial intelligence (AI). The discovery of informative parameters (biomarker signatures) and training of the classification model were done with a maximum of 35% of the patients. The remaining minimum 65% of patients were used for validation. At clinical relevant cut-off points the accuracy of the biomarker signature for diagnosis of appendicitis was 90% (93% sensitivity, 67% specificity), while the accuracy to correctly identify complicated inflammation was 51% (95% sensitivity, 33% specificity) on validation data. Such a test would be capable to prevent two out of three patients without appendicitis from useless surgery as well as one out of three patients with uncomplicated appendicitis. The presented method has the potential to change today’s therapeutic approach for appendicitis and demonstrates the capability of algorithms from AI and ML to significantly improve diagnostics even based on routine diagnostic parameters