Miracle-dz/UniFAR-FTUs huggingface dataset:
All-optical radio-frequency modulation of Anderson-localized modes

All-optical modulation of light relies on exploiting intrinsic material nonlinearities. However, this optical control is rather challenging due to the weak dependence of the refractive index and absorption coefficients on the concentration of free carriers in standard semiconductors. To overcome this limitation, resonant structures with high spatial and spectral confinement are carefully designed to enhance the stored electromagnetic energy, thereby requiring lower excitation power to achieve significant nonlinear effects. Small mode-volume and high quality (Q)-factor cavities also offer an efficient coherent control of the light field and the targeted optical properties. Here, we report on optical resonances reaching Q - 10^5 induced by disorder on novel photonic/phononic crystal waveguides. At relatively low excitation powers (below 1 mW), these cavities exhibit nonlinear effects leading to periodic (up to - 35 MHz) oscillations of their resonant wavelength. Our system represents a test-bed to study the interplay between structural complexity and material nonlinearities and their impact on localization phenomena and introduces a novel functionality to the toolset of disordered photonics.
Topological chaos in inviscid and viscous mixers

Topological chaos may be used to generate highly effective laminar mixing in a simple batch stirring device. Boyland, Aref & Stremler (2000) have computed a material stretch rate that holds in a chaotic flow, provided it has appropriate topological properties, irrespective of the details of the flow. Their theoretical approach, while widely applicable, cannot predict the size of the region in which this stretch rate is achieved. Here, we present numerical simulations to support the observation of Boyland et al. that the region of high stretch is comparable with that through which the stirring elements move during operation of the device. We describe a fast technique for computing the velocity field for either inviscid, irrotational or highly viscous flow, which enables accurate numerical simulation of dye advection. We calculate material stretch rates, and find close agreement with those of Boyland et al., irrespective of whether the fluid is modelled as inviscid or viscous, even though there are significant differences between the flow fields generated in the two cases.
The coin tossing view of finance and the appearance of Brownian motion

In the past decades, advanced probabilistic methods have had significant impact on the field of finance, both in academia and in the financial industry. Conversely, financial questions have stimulated new research directions in probability. In this survey paper, we review some of these developments and point to some areas that might deserve further investigation. We start by reviewing the basics of arbitrage pricing theory, with special emphasis on incomplete markets and on the different roles played by the “real-world” probability measure and its equivalent martingale measures. We then focus on the issue of model ambiguity, also called Knightian uncertainty. We present two case studies in which it is possible to deal with Knightian uncertainty in mathematical terms. The first case study concerns the hedging of derivatives, such as variance swaps, in a strictly pathwise sense. The second one deals with capital requirements and preferences specified by convex and coherent risk measures. In the final two sections we discuss mathematical issues arising from the dramatic increase of algorithmic trading in modern financial markets.
Modeling of Soil Cation Exchange Capacity Based on Fuzzy Table Look-up Scheme and Artificial Neural Network Approach

In this study, a new approach is proposed as a modification to a standard fuzzy modeling method based on the table look-up scheme. 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. Then, neural network model (feed-forward back propagation network) and fuzzy table look-up scheme were employed to develop a pedotransfer function for predicting soil CEC using easily measurable characteristics of clay and organic carbon. In order to evaluate the models, root mean square error (RMSE) and R 2 were used. The value of RMSE and R 2 derived by ANN model for CEC were 0.47 and 0.94 respectively, while these parameters for fuzzy table look-up scheme were 0.33 and 0.98 respectively. Results showed that fuzzy table look-up scheme had better performance in predicting and modeling of soil cation exchange capacity than artificial neural network.
The size-luminosity relation at z=7 in CANDELS and its implication on reionization

Context. The exploration of the relation between galaxy sizes and other physical parameters (luminosity, mass, star formation rate) has provided important clues for understanding galaxy formation, but such exploration has until recently been limited to intermediate redshift objects. Aims. We use the currently available CANDELS Deep+Wide surveys in the GOODS-South, UDS and EGS fields, complemented by data from the HUDF09 program, to address the relation between size and luminosity at z � 7. Methods. The six different fields used for this study are characterized by a wide combination of depth and areal coverage, well suited for reducing the biases the observed size-magnitude plane. From these fields, we select 153 z-band dropout galaxies. Detailed simulations have been carried out for each of these six fields, inserting simulated galaxies at different magnitudes and half light radius in the two dimensional images for all the HST bands available and recovering them as carried out for the real galaxies. These simulations allow us to derive precisely the completeness as a function of size and magnitude and to quantify measurements errors/biases, under the assumption that the 2-D profile of z=7 galaxies is well represented by an exponential disk function. Results. We find in a rather robust way that the half light radius distribution function of z � 7 galaxies fainter than J = 26.6 is peaked at � 0.1 arcsec (or equivalently 0.5 kpc proper), while at brighter magnitudes high-z galaxies are typically larger than �0.15 arcsec. We also find a well defined size-luminosity relation, Rh / L 1/2 . We compute the Luminosity Function in the HUDF and P12HUDF fields, finding large spatial variation on the number density of faint galaxies. Adopting the size distribution and the size-luminosity relation found for faint galaxies at z=7, we derive a mean slope of 1.7 ± 0.1 for the luminosity function of LBGs at this redshift. Conclusions. Using this LF, we find that the number of ionizing photons emitted from galaxies at z � 7 cannot keep the Universe re-ionized if the IGM is clumpy (CHII � 3) and the Lyman continuum escape fraction of high-z LBGs is relatively low (fesc � 0.3). If these results are confirmed and strengthened by future CANDELS data, in particular by the forthcoming deep observations in GOODS-South and North and the wide field COSMOS, we can put severe limits to the role of galaxies in the reionization of the Universe.
Histopathological Alterations in Muscle, Liver and Gill Tissues of Zebra Fish Danio Rerio due to Environmentally Relevant Concentrations of Organochlorine Pesticides (OCPs) and Heavy Metals

The study monitored the toxicity of environmentally relevant concentration of pesticides and metals in zebra fish Danio rerio. Zebra fish were exposed to environmentally relevant concentration of pesticides and metals for a period of 14 days. The individual and the combined toxicity of pesticides and metals were evaluated. The pesticides and metals treated groups showed histopathological alterations in the muscle, liver and gill tissues. Significant alterations were seen in liver and gill compared to muscle tissue. Among groups, the changes in group III (pesticides treated) were severe followed by group II (metals treated) and then the group IV (metals and pesticides treated, combined toxicity). Splitting of muscle fibers and necrosis was observed in muscle tissue. In the liver tissues severe damages such as dilation and congestion of blood sinusoids, cytoplasmic vacuolation and necrosis were observed. Pronounced hyperplasia and well defined necrosis was observed in gill. In conclusion the evidence of pathological alterations in gills and livers of zebra fish Danio rerio appeared to be a useful bio-marker to assess the impact of combined toxicity of pesticides and metals.
Slow strategies for student (and staff) engagement.

The past two years have seen an explosion of interest in the Slow Movement as a response to stress and overwork in universities. Many staff are working less and giving themselves appropriate breaks from academic life. Yet the theoretical and practical tactics and ideas for slowing down have not been shared with students, even as students suffer from overwork and employability concerns. At the same time, many universities have sought to engage students through new research-led approaches to teaching. We suggest that student engagement can be defined as the extent to which a student feels they belong to a department and that a department cares about them. We offer two methods of increasing this type of engagement. First, introduce students to the slow movement and second, take seriously the issue of staff engagement. We evaluate our own efforts to foster slow student and staff engagement through a ‘Shut Up and Write’ sessions adopted by the Geography Department at UCL.
A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud‐base mass flux, given a large‐scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud‐base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud‐base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge‐discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud‐base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.
Evaluation and Management of Heart Failure

Despite advances in the prevention, diagnosis, and management of cardiovascular disease, heart failure (HF) continues to be a major burden on morbidity, mortality, and cost to our community (1). Systolic HF is a complex syndrome of structural, functional, and biologic alterations characterized by abnormalities in cardiac function that cause inadequate blood supply to tissues. The issues of poor perfusion or lack of “forward flow” are complicated by “backward flow” which produce congestion in the lungs, liver dysfunction, and renal venous hypertension (cardiorenal syndrome) (2). No matter the etiology, damage to the heart muscle starts a cascade of events that lead to neurohormonal abnormalities such as the sympathetic nervous system, the renin–angiotensin–aldosterone system (RAAS), and vasopressin activation (3). The end result is a symptomatic patient with decrease exercise tolerance with an underlying systemic neurohormonal activation associated with poor prognosis (4). HF is now a serious public health concern. It is estimated that 6 million Americans have HF, with an associated 3 million hospital discharges per year. Half of these discharges are related to diastolic HF or impaired relaxation of the heart (5). Although patients with diastolic HF have better prognosis, they have the same number of hospitalization as those with systolic HF (6). Despite evidence-based medicine, mortality at 5 years is 50% for HF with 30-day mortality after hospital discharge at 10% to 12%. (1) In-hospital mortality if admitted with a systolic blood pressure less than 100 mmHg and a serum creatinine 2.0 mg/dL is estimated to be approximately 16% (7). Additionally, 30-day readmission rates continue to be problematic, presently 30% of all HF patients will be readmitted to a hospital within that time frame. As our medical community struggles to keep HF patients out of the hospital, estimated costs related to HF issues have risen to 29 billion dollars a year (1). The purpose of this chapter is to review the pathophysiology, diagnosis, treatment options, and controversies in HF as it pertains to the critical care patient.
Smart Techniques Employed for Monitoring of Agricultural Parameters

Agriculture is one of the primary occupations of man since early civilizations. Even today, manual intervention is inevitable. Around sixty to seventy per cent of the population depend on the resources from the agricultural sector. Asian nations rank second in terms of the farm field output. The agricultural sector is not fully automated with one of the main reasons being the cost. Controlled climatic conditions are very important for plant growth and hence for optimum produce. Farmers suffer large financial losses because of wrong predictions of weather and incorrect irrigation methods. In this context, with the evolution of miniaturized sensor devices coupled with wireless technologies, it is possible to remotely monitor parameters such as moisture, temperature, humidity and detect the leaf diseases. The project’s objective is to design and develop an embedded system that can acquire the farm field parameters and efficiently process them so that it can be wirelessly transmitted to a remote place. According to the parameters that are received continuously by the end user, decision based on monitoring can be done. This improves the quality of plant growth and takes care of each of the nutrient parameters required for its growth. A part of the paper also deals with Greenhouse which plays an important part of the agriculture and horticulture sectors in our country as they can be used to grow plants under controlled climatic conditions for optimum produce. The proposed system is an embedded system which constantly monitors the digitized parameters of the various sensors and verifies them with the predefined threshold values and checks if any corrective action is to be taken by controlling the parameters inside the greenhouse by actuating a cooler, foggier, dripper and light respectively in accordance with the necessary conditions for the
Revolutionary Pressures and the Survival of Political Leaders 1

Leaders face multiple threats to their political survival. In additional to surviving the threats to tenure from within the existing political systems, which is modeled using Bueno de Mesquita et al’s (2003) selectorate theory, leaders risk being deposed through revolutions are coups. To ameliorate the threat of revolution, leaders can either increase public goods provisions to buy off potential revolutionaries or contract the provision of those public goods, such as freedom of assembly, transparency and free press, which enable revolutionaries to coordinate. Which response a leader chooses depends upon existing institutions and the structure of government finances. These factors also affect the likelihood and direction of institutional change. Tests of leader survival indicate that revolutionary threats increase the likelihood of deposition for nondemocratic leaders. Leaders with access to resource such as foreign aid, or natural resource rents are best equipped to survive these threats and avoid the occurrence of these threats in the first place.
Impact of airborne Doppler wind lidar profiles on numerical simulations of a tropical cyclone

During the THORPEX Pacific Asian Regional Campaign (TPARC) field experiment in 2008, an airborne Doppler wind lidar (DWL) was onboard the U.S. Naval Research Laboratory's P‐3 research flight. It was the first time the DWL was used for a tropical cyclone mission. This paper presents the first results demonstrating the impact of airborne DWL measurements on the numerical simulation of Typhoon Nuri (2008) in its formation phase. With an advanced research version of the weather research and forecasting (WRF) model and its data assimilation systems, numerical results show the DWL data have a positive impact on numerical simulations of Typhoon Nuri in terms of its formation, track and intensity. Dropsondes released in the areas where the DWL was operating show good agreement for measured winds. Compared with the three‐dimensional variational method, a four‐dimensional variational data assimilation system is deemed to be more promising for assimilating the DWL data.
Individual Patient Data Meta-Analysis of Time-to-Event Outcomes: An Application of a Poisson-Gamma-Frailty Model

The goal of meta-analysis is to combine outcomes of several independent studies all addressing the same or a closely related research question. Traditionally, meta-analysis models combine summary estimates of a single quantitative endpoint, taken from di↵erent studies, to produce a single pooled result. Univariate fixed or random e↵ect models are then employed to analyse the data. In the presence of multiple outcomes (like overall and disease-free survival), multiple time points (e.g. in longitudinal studies) or multiple treatment groups, multiple pooled results are required. In such situations, a pooled result for each endpoint is usually obtained by applying a separate univariate meta-analysis to each endpoint independently. This approach is rather simple and ignores the potential correlation between endpoints. A multivariate meta-analysis model is required to improve e ciency over separate univariate analysis and allow the association between endpoints to be modelled. A particular situation with multiple endpoints arises when each trial contributing to the meta-analysis provides survival proportions at a series of time-points. Such values are clearly correlated and a multivariate model is required to synthesize them jointly. A Poisson correlated gamma-frailty model can be employed to account for within-study correlation and heterogeneity between studies. This model was applied before on aggregate survival data extracted from published trial reports. The aim of this thesis is to extend the use of this model to time-toevent meta-analysis at individual patient data (IPD) level. An IPD approach is considered the gold standard in meta-analysis as it can improve the quality of the analysis and therefore the reliability of the conclusions based on the statistical analysis. The data used in the thesis is provided by the Dutch Children Oncology Group (DCOG) and comes from a retrospective worldwide study. Children su↵ering from acute myeloid leukemia (AML) were followed since diagnosis of the disease. All analysis has been implemented in R software. The codes and functions are written generic and can be applied to other datasets of similar structure. ACKNOWLEDGEMENTS I would like to express my deepest gratitude to my thesis advisor Dr. Marta Fiocco for her generous support and enthusiastic encouragement during the writing of this dissertation. This work would have never been possible without her guidance. Special thanks should be given to all my professors from the master track of ”statistical science for the life and behavioural sciences” for giving me valuable assistance during my study. I wish to thank my family and friends for their support and encouragement throughout my study. The Dutch Children Oncology Group (DCOG) is gratefully acknowledged for providing the dataset. CONTENTS
Biological disinfestation of soil-borne bacterial wilt pathogen using a large population of virulent bacteriophages supported via the lytic cycle of non-phytopathogenic host bacteria introduced into soil

Field-grown tomato plants frequently suffer from infection by Ralstonia solanacearum, a bacterial wilt pathogen. We have not succeeded in producing bacterial wilt-resistant tomato cultivars via conventional breeding techniques. This work established an alternative biological method to disinfest bacterial pathogens in soil; i.e. the lysis of bacterial cells by the infection of virulent bacteriophages (phages) introduced into soil. For this purpose, we collected strains of R. solanacearum (tester strains) to screen various virulent phages. Soil samples were collected from 1210 fields (including paddy fields) located in several districts of Japan to obtain phages with different host ranges. The isolated phages were inoculated into 48 tester strains separately and eventually classified into 56 types based on their distinct host ranges. Lytic infection was confirmed using the standard plaque formation assay. Our procedure consists of several steps: 1) monitoring bacterial pathogens living in the fields used for tomato cultivation; 2) selecting phages that infect all of the bacterial isolates obtained from the test field; 3) multiplying the selected phages on a large scale using a 100-L jar fermentor to prepare a bacterial lysate containing 10 to 10 phage particles/ml; 4) diluting the lysate with 10 volumes of a fresh suspension of a non-phytopathogenic, phage-susceptible isolate of R. solanacearum to ensure subsequent multiplication of the phages in the soil; 5) soaking the soil with the diluted lysate and subsequently tilling the soil to promote encounters between the phages and target bacterial pathogens in the soil; and 6) confirming the successful elimination of the soil-borne pathogen from a field. The bacteria in soil were detected by suspending soil samples in sterilised water, centrifuging the suspension at low speed, and then spreading the supernatant on solid Tz-PCG medium selective for R. solanacearum. After a 2-day incubation, the resulting pinkish-red pathogen-specific colonies were counted to determine the number of bacteria in the soil samples. The practicability of the system was examined using an experimental 5 × 5-m block (depth 60 cm) in a paddy field to be switched to tomato cultivation. Soil samples were collected at points throughout the block. In all samples, specific bacterial colonies with different growth speeds or colony shapes appeared on the selective medium. These isolated bacteria were shake-cultured in liquid broth until the solution became turbid, and the turbid culture was divided for inoculation with different phage
Welfare state expenditure and inequalities in voluntary association participation

There are large gaps in associational involvement along education, income and gender lines and across different organizations. This paper examines the extent to which these gaps vary across countries. We argue that, next to the discussion about crowding out effects that is often found in the literature, it is important to look at conditioning effects of welfare states. Through welfare state policies, resources are redistributed in society. In turn, these resources enable participation in voluntary associations and organizations. Our analyses — based on multi-level models and data of the European Social Survey — indicate that extensive welfare state expenditures reduce participatory inequalities, with some variation according to the kind of organization under study. Our findings suggest that conditioning effects of welfare states deserve greater attention in research and that participatory inequalities may be reduced by social policy.