In Search of Free Spaces to Breathe: Turkey's United June Movement,Social Uprising,and Spatial Maintainability

This study examines the socio-spatial practices of the United June Movement (UJM), a grassroots movement that drew inspiration from the neighbourhood forums of the Gezi Park protests. We argue that the counter-sites of politicisation and symbolic places engraved on the social movements’ memory formed the socio-spatial base of solidarity networks and the long-term political organising of UJM. Secondly, we suggest that in an authoritarian context, activist organisations nourishing from full-scale protests such as UJM need to form, reshape, and sustain free spaces where they feel protected. For testing these arguments, we designed fieldwork around UJM with an ethnographic approach. We concluded that the desire for social change has the potential of generating alternative visions in a spatiotemporal context, but in the medium term, it can turn into a feeling of self-enclosure or being besieged. Even so, such attempts leave a perpetual legacy, tagged to certain spaces and geographies.     

Modeling Net Ecosystem Carbon Dioxide Exchange Using Temporal Neural Networks after Wavelet Denoising

Eddy covariance (EC) time‐series data obtained from flux towers are noisy due to both stochastic atmospheric turbulence and deterministic processes, and no standard data‐denoising protocols exist for them. The potential of six temporal artificial neural networks (ANNs) augmented with and without three orthogonal wavelet functions was tested for predicting net ecosystem exchange of carbon dioxide (CO₂) based on a long‐term EC data set for a temperate peatland. Multiple comparisons were made of (1) temporal ANNs with and without discrete wavelet transform (DWT) denoising; (2) denoising with the orthogonal wavelet families of Daubechies, Coiflet, and Symmlet; (3) different decomposition levels; (4) time‐delay neural network, time‐lag recurrent network, and recurrent neural network; (5) online learning versus batch learning algorithms; and (6) diel, diurnal, and nocturnal periods. The coefficient of determination, root mean square error, and mean absolute error performance metrics were used for multiple comparisons based on training, cross‐validation, and independent validation of the temporal ANNs as a function of 24 explanatory variables contained in an EC data set. Integration of the temporal ANNs and DWT denoising provided more accurate and precise estimates of net ecosystem CO₂ exchange. Los datos de series de tiempo de covarianza tipo Eddy (EC) obtenidos de torres de flujo (flux‐towers) contienen ruido debido tanto a la turbulencia atmosférica estocástica como a los procesos determinísticos modelados. A pesar de esto, no existen protocolos estandarizados para la eliminación de ruido en este tipo de datos. El estudio presente pone a prueba el potencial de seis redes neuronales artificiales temporales (ANN) a las que se les añade con (y remueve) tres funciones de transformada de ondícula (wavelets) ortogonales con el fin de predecir el intercambio neto ecosistémico (NEE) de dióxido de carbono (CO2) usando un conjunto de datos EC de largo plazo correspondientes a una turbera ubicada en zona templada. Se realizaron múltiples comparaciones de (1) las ANN temporales con y sin transformación wavelet discreta (DWT) para la remoción del ruido; (2) la eliminación de ruido usando las familias de wavelets ortogonales de tipo Daubechies, Coiflet y Symmlet; (3) diferentes niveles de descomposición; (4) redes neuronales con retraso temporal (time‐delay) (TDNN ), con retardo (lag) de red recurrente (TLRN), y la red neuronal recurrente (RNN); (5) con aprendizaje en línea versus algoritmos de aprendizaje en lote (batch); y, (6) para ciclos circadianos, diurnos, y nocturnos. Para comparar los rendimientos de cada método se calcularon el coeficiente de determinación, el error cuadrático medio (RMSE), y la media de error absoluto (MAE), provenientes de los datos de validación cruzada, calibración y validación independiente de los ANN temporales y en función de 24 variables explicativas de los datos EC. Los autores concluyen que la integración de los ANN temporales con la remoción de ruido tipo wavelet proporciona estimaciones más exactas y precisas del intercambio neto ecosistémico de CO2. 受随机大气湍流和确定性过程扰动的影响,利用涡度相关法从通量塔中测定的时间序列数据是高噪音的,目前仍缺乏标准的数据去噪方案。本文基于一个温带泥炭地长期观测的EC数据集,测试了六个潜在的时态人工神经网络(ANNs),以及其在包含或者不包含三个正交的小波函数增强的条件下对二氧化碳（CO2）的净生态系统交换（NEE）的预测能力。比较试验分为以下几组：(1)使用或不使用离散小波变换（DWT）去噪的时态ANNs;(2)采用Daubechies, Coiflet和 Symmlet正交小波族去噪;(3)不同的小波分解层级;(4)时间延滞神经网络（TDNN）、时间滞后递归网络（TLRN）和递归神经网络(RNN);(5)在线学习与批量学习算法;(6)昼夜、白天和夜间三种周期。将时态ANNs作为EC数据集中24个解释变量的函数,运用决定系数、均方根误差(RMSE)和平均绝对误差(MAE)指标对其训练、交叉验证和独立验证过程进行多重比较测试。结果显示,集成时态ANNs和DWT去噪可以提供更为准确的净生态系统CO2交换量的估计。     

Restorationist Counter‐Enlightenment: Thomas M'Crie on the Concept of Civil Liberty

Enlightenment notions for Counter‐Enlightenment purposes have not to date been used to provide a comprehensive context for Scottish religious history‐writing in the age of Counter‐Revolution and Restoration. The Evangelical historian and divine Thomas M'Crie's studies on Scottish Reformation history, Life of John Knox and Life of Andrew Melville, published in 1811 and 1819 respectively, exhibit an abundance of historiographical material for research. M'Crie was among the most renowned writers of his own time, but his historical works have been briefly passed over in recent secondary sources. The main purpose of this study is to rescue M'Crie's historical works on the Scottish Reformation past from near oblivion. This article argues that M'Crie produced an apology for the Scottish Reformation, adopting an aggressive style that attacked Scottish Enlightenment historians and thinkers such as William Robertson and David Hume, especially in the matter of their treatment of John Knox and Andrew Melville. M'Crie tried to restore his chosen past in order to influence the religious and political affairs of Scotland. In M'Crie's Counter‐Enlightenment historiography, the concept of civil liberty and Presbyterianism become interchangeable in a Restorationist religio‐political discourse. That is why M'Crie's enthusiasm for the Scottish Reformation constitutes the most representative example of the Presbyterian interpretation, which held its own against Enlightenment influence.     

More than a Disease: The History of General Paralysis of the Insane in Turkey

This article explores the history of general paralysis of the insane (GPI) and its treatment in Turkey. GPI was considered as “a disease of civilization” at the end of the nineteenth century. From the early years of the twentieth century, Turkish psychiatrists discussed and interpreted the causes of GPI and followed the European diagnostic and treatment methods of the disease. Austrian psychiatrist Julius Wagner-Jauregg (1857–1940) introduced and developed “malaria fever therapy” for general paralysis in 1917. Malaria fever therapy spread to other countries and, during the 1920s, the treatment was also used in Turkey. This article not only aims to illuminate an unnoticed aspect of the history of psychiatry in Turkey but also uses GPI as a model to illustrate how psychiatry in Turkey was influenced by the developments in Europe.