The Role of Historian Physicians in the Development of the Islamic and Spanish Civilization

زمینه و هدف: نقش و جایگاه پزشکان تاریخ‌نگار یا مورخان پزشک یکی از مؤلفه‌های مهم در توسعه علمی و تمدنی اسپانیای اسلامی است که قابل بررسی و جستجوی بیشتر است. در فرایند توسعه تمدن اسلامی اقشار مختلف اعم از ادیبان، پزشکان، حکیمان، مورخان و... نقش ایفا کرده‌اند. با وجود تحقیقات و بررسی‌هایی که تاکنون درباره پزشکان اندلسی صورت گرفته، لیکن درباره پزشکانی که علاوه بر امر طبابت، تاریخ‌نگار هم بوده‌اند، کم‌تر اطلاعاتی در دست است. پژوهش حاضر با هدف معرفی و تبیین کارکرد اطبای تاریخ‌نگار، می‌کوشد میزان اثرگذاری آن‌ها در توسعه علمی و پیشبرد فرهنگی تمدن اندلس در دوره اسلامی را مشخص و بررسی نماید. مواد و روش‌ها: این پژوهش بر پایه روش مطالعات مروری و با اتکا به منابع نوشتاری و داده‌های کتابخانه‌ای انجام گرفته است که پس از گردآوری و مطالعه منابع موثق، از جمله الاحاطه فی تاریخ الغرناطه، العبر، مفاتیح العلوم، عیون الانباء فی طبقات الاطباء و... مطالب بر اساس اهمیت و اعتبار آن‌ها تنظیم و تدوین شده‌اند. یافته‌ها: نتیجه تحقیق بیانگر آن است که پزشکان وقایع‌نگار، با ثبت گزارش‌های موثق و دقیق از نوآوری‌ها و پویش‌های دانشوران و کوشندگان عرصه علم و فرهنگ در تمدن اندلس، نقش ویژه‌ای در روند توسعه هم‌زمان دانش طب و تاریخ و امکان‌سنجی مقایسه مطالعات میان‌رشته‌ای ایفا کرده‌اند. همچنین آموزش دانش پزشکی به سایر کشورها از جمله فرانسه، پرتغال و... راه پیدا کرد، به گونه‌ای که دانشجویان و علاقمندان علم پزشکی از دانشگاه‌های مونپلیه و پاریس برای فراگیری طبابت نزد استادان مسلمان در شهر قرطبه پایتخت اندلس جمع می‌شدند. نتیجه‌گیری: بیشتر پزشکان مسلمان در اسپانیای تحت حاکمیت اسلام، ضمن پرداختن به امر طبابت، دستی در نگارش تاریخ داشته‌اند و با دقت بیشتری نسبت به دیگر مورخان، به ثبت و ضبط تحولات علمی و فرهنگی در تمدن اندلس مبادرت کرده‌اند. وجاهت علمی و بینش عالمانه این پزشکان، نگارش تاریخ‌نگارانه آن‌ها را متمایز ساخته و سبب شده تا سیمای راستین تمدن اندلس و شکوفایی فرهنگی آن، به خوبی در متون این اطبای مورخ بازنمود داشته باشد.Background and Aim: The role and position of physicians Historian or medical historian is one of the most important components in the scientific and civilization development of Islamic Spain which can be further explored. In the process of the development of Islamic civilization, different classes including literary, physicians, sages, historians and others have played a role. There is little information available on Andalusian physicians, but there is little information on physicians who have been historians in addition to medical practice. The purpose of this study is to introduce and explain the function of the historian's lecturer, to determine their impact on the scientific development and cultural advancement of Andalusian civilization in the Islamic era. Materials and Methods: This study is based on a literature review method, referring to written sources and library data. After gathering and studying reliable sources, the contents are adjusted based on their importance and validity. Findings: The results of this study indicate that chiropractors, by recording credible and accurate reports of Andalusian cultural developments, have a special role in the process of simultaneous development of knowledge of medicine and history and the feasibility of comparing interdisciplinary studies. Conclusion: Most Muslim practitioners in Islamic-dominated Spain, while practicing medicine, have been instrumental in writing history and have recorded and recorded more scientific and cultural developments in Andalusian civilization than other historians. The scholarly prestige and wisdom of these practitioners have distinguished them from their historical writing and made it well-represented in the texts of this historian's monastery and its flourishing cultural landscape.   Please cite this article as: Vaziry SA, Ashrafi A, Salim MN. The Role of Historian Physicians in the Development of the Islamic and Spanish Civilization. Med Hist J 2018; 10(36): 43-51

Application of the anatomical fiducials framework to a clinical dataset of patients with Parkinson’s disease

Establishing spatial correspondence between subject and template images is necessary in neuroimaging research and clinical applications such as brain mapping and stereotactic neurosurgery. Our anatomical fiducial (AFID) framework has recently been validated to serve as a quantitative measure of image registration based on salient anatomical features. In this study, we sought to apply the AFIDs protocol to the clinic, focusing on structural magnetic resonance images obtained from patients with Parkinson’s disease (PD). We confirmed AFIDs could be placed to millimetric accuracy in the PD dataset with results comparable to those in normal control subjects. We evaluated subject-to-template registration using this framework by aligning the clinical scans to standard template space using a robust open preprocessing workflow. We found that registration errors measured using AFIDs were higher than previously reported, suggesting the need for optimization of image processing pipelines for clinical grade datasets. Finally, we examined the utility of using point-to-point distances between AFIDs as a morphometric biomarker of PD, finding evidence of reduced distances between AFIDs that circumscribe regions known to be affected in PD including the substantia nigra. Overall, we provide evidence that AFIDs can be successfully applied in a clinical setting and utilized to provide localized and quantitative measures of registration error. AFIDs provide clinicians and researchers with a common, open framework for quality control and validation of spatial correspondence and the location of anatomical structures, facilitating aggregation of imaging datasets and comparisons between various neurological conditions

From global choreographies to verifiable efficient distributed implementations

International audienc

Cytoarchitecture of the Anterior Cingulate Cortex in Patients with Schizophrenia, Bipolar Disorder and Major Depression

There is evidence for impaired neuron migration during development in patients with schizophrenia and bipolar disorder, and we hypothesized to find evidence for this in post-mortem cortical tissue. We used layer-specific markers and novel automated cell counting methods to investigate large areas of the anterior cingulate cortex in patients with major depression, bipolar disorder and schizophrenia. We did not find profound differences, suggesting that any cytoarchitectural abnormalities are subtle. Almost no differences were seen in major depression, except for a smaller cell size in one region. Bipolar patients had increased densities and smaller cells in lower layers, and decreased densities in upper layers. This may support our hypothesis, or it could be explained by increased cell death in upper layers or decreased neuropil in lower layers. Patients with schizophrenia had non-consistent changes, which did not support our hypothesis. Thus, schizophrenia is potentially a particularly heterogeneous disease with multiple pathophysiological abnormalities.M.Sc

Wireless Communication Attack Using SDR and Low-Cost Devices

International audienceWhile Wireless communication (WLC) enhances the user mobility and extends the connection and services to extreme isolated points, is the only way to establish a connection over long distance (mainly earth and space), it has many weak points: Interference, Spectrum limitations, bandwidth cost, various regulations, etc. But the major drawback is the security and risk vulnerabilities. To clarify this idea and highlight several security issues, we are working on the weak points of our wireless networks and communication protocols. In this manuscript, we develop several scenarios of Wireless attacks using simple and low-price equipment. Indeed using Software Defined Radio (SDR), a potential hacker can now access a wide range of wireless-based communication like Keyless entry, GPS and RFID system. It can also interfer and jam several other WLC services and networks

In-Network Data Aggregation for Ad Hoc Clustered Cognitive Radio Wireless Sensor Network

International audienceIn cognitive radio wireless sensor networks (CRSN), the nodes act as secondary users. Therefore, they can access a channel whenever its primary user (PU) is absent. Thus, the nodes are assumed to be equipped with a spectrum sensing (SS) module to monitor the PU activity. In this manuscript, we focus on a clustered CRSN, where the cluster head (CH) performs SS, gathers the data, and sends it toward a central base station by adopting an ad hoc topology with in-network data aggregation (IDA) capability. In such networks, when the number of clusters increases, the consumed energy by the data transmission decreases, while the total consumed energy of SS increases, since more CHs need to perform SS before transmitting. The effect of IDA on CRSN performance is investigated in this manuscript. To select the best number of clusters, a study is derived aiming to extend the network lifespan, taking the SS requirements, the IDA effect, and the energy consumed by both SS and transmission into consideration. Furthermore, the collision rate between primary and secondary transmissions and the network latency are theoretically derived. Numerical results corroborate the efficiency of IDA to extend the network lifespan and minimize both the collision rate and the network latency

Spectrum Sensing for Full-Duplex Cognitive Radio Systems

International audienceFull-Duplex (FD) transceiver has been proposed to be used in Cognitive Radio (CR) in order to enhance the Secondary User (SU) Data-Rate.In FD CR systems, in order to diagnose the Primary User activity, SU can perform the Spectrum Sensing while operating. Making an accurate decision about the PU state is related to the minimization of the Residual Self Interference (RSI). RSI represents the error of the Self Interference Cancellation (SIC) and the receiver impairments mitigation such as the Non-Linear Distortion (NLD) of the receiver Low-Noise Amplifier (LNA). In this manuscript, we deal with the RSI problem by deriving, at the first stage, the relation between the ROC curves under FD and Half-Duplex (HD) (when SU stops the transmission while sensing the channel). Such relation shows the RSI suppression to be achieved in FD in order to establishan efficient Spectrum Sensing relatively to HD. In the second stage, we deal with the receiver impairments by proposing a new technique to mitigatethe NLD of LNA. Our results show the efficiency of this method that can help the Spectrum Sensing to achieve a closed performance under FD to that under HD

Comparative Study of Spectrum Sensing methods

International audienceCognitive Radio (CR) was introduced by Mitola in [1], in order to improve the distribution of the frequencyspectrum to satisfy the growing evolution in wireless applications. Therefore, the major goal of CR is toidentify the non-presence of Primary User (PU) which has the legal right of transmission [1] [2]. In case ofabsence of PU, the CR can allocate the unused band to a Secondary User (SU). The SU should stop histransmission if PU starts to be active, in order to avoid any interference. In fact, many techniques have beenintroduced in order to estimate the opportunity of free bandwidth; those techniques could be classified as:Blind and Cooperative. The cooperative techniques need a priori information about the PU to do the sensingof the channel, while the blind techniques do not

A Deep Neural Network Model for Hybrid Spectrum Sensing in Cognitive Radio

International audienceSpectrum sensing (SS) is an essential task of the secondary user (SU) in a cognitive radio system. SS monitors the primary user (PU) activity in order to avoid any collision with SU, as the latter should be silent when PU is active on a given channel. Hybrid SS (HSS) is one of the powerful methods used to monitor PU activity. It consists of using different detectors together to make a final decision on the PU status. In this manuscript, artificial neural networks (ANN) are used to perform HSS. Since our data is composed from the test statistics (TSs) of several detectors, thus it can be modeled as tabular. Fully connected neural networks become the most suitable ANN model. We applied cutting-edge techniques in the field of deep learning in order to get the best possible accurate neural network model in our application. These techniques boil down to: embedding, regularization, batch normalization and smart learning rate selection. With the help TSs related to several detectors, ANN is trained to distinguish between two hypotheses, H-0: PU is absent and H-1: PU is active. Numerical results show the effectiveness of our proposed ANN-based HSS, as it outperforms the classical ANN-based energy detector and proves its capability to detect PU signal at very low SNR