Miracle-dz/UniFAR-FTUs huggingface dataset:
Endotoxin in the urban and rural environment: ambient concentration and biomarkers of pulmonary exposure

Three main projects are included in this dissertation. Though seemingly broad in scope, this research afforded a unique opportunity for comprehensive study of urban and rural environmental inhalation exposures to endotoxin (lipopolysaccharide – LPS) and the associated immune response. In the LA PM10 Endotoxin Study, ambient concentration of LPS in PM (particulate matter) was quantified through analysis of air samples collected in Southern California. Endotoxin concentrations measured were lower than recognized thresholds for adverse health effects in occupational exposures, but in the same range as for indoor effects. This study provides the first extensive characterization of endotoxin concentration across a large metropolitan area in relation to PM10 and other pollutant monitoring, and supports the need for studies of the role of endotoxin in childhood asthma in urban settings. The Mouse Whole Blood Assay (WBA) Study replicated LPS-induced airway inflammation in a laboratory model. Presently, there is a need for less invasive options for evaluating pulmonary responses to occupational exposures. The whole blood assay (WBA), which measures cytokine production of leukocytes after ex vivo stimulation with LPS, may be one such option. This study used an endotoxin-tolerance model to demonstrate the efficacy of the WBA as a biomarker of inhalation exposure to swine concentrated animal feeding operation (CAFO) dust and showed the utility of the WBA for assessing susceptibility to organic dust-induced lung inflammation. Finally, The Human WBA Study applied the WBA outside the controlled environment of the laboratory. This study utilized pulmonary function testing (PFT), symptom questionnaires and the WBA to evaluate inflammatory responses following an inhalation exposure to purified LPS in CAFO workers and controls. Subjects were stratified into response groups for analysis of WBA results based on PFT response. All
Hepatic neutrophil migration, kinetics and long-term outcome in severe alcoholic hepatitis

Alcohol-related liver disease (ARLD) refers to the spectrum of hepatic pathology arising from excessive alcohol consumption. In contrast to most of continental Europe, where the incidence is falling, ARLD is a growing clinical problem in the UK and currently accounts for ten percent of all deaths occurring between 40 - 49 years of age. Severe alcoholic hepatitis (AH) is arguably the most florid manifestation of ARLD, presenting with jaundice and features of hepatic decompensation, often in those without an existing diagnosis of liver disease. Despite abstinence short-term mortality approaches 40%, which may be improved by early diagnosis and timely medical therapy. Among current controversies in the management of severe AH are the necessity for liver biopsy to confirm the diagnosis, and hence there is a recognised need for non-invasive diagnostic aids. Corticosteroids have remained the mainstay of therapy for over 30 years, although a significant minority fail to respond and are particularly susceptible to infections as a consequence of treatment. A means of prospectively and non-invasively identifying these individuals would be a significant advancement.
Recognition of Natural Hand Gestures Using Bidirectional Long Short-Term Memory Model

Recent studies have been trying to use voices and body gestures similar to human communication methods to control intelligent devices such as robots instead of giving commands using a keyboard or a mouse. Human being obtains about 80% of information using vision, and about 55% of all meaning of communication is related to vision. In addition, hand gestures are most frequently used in non-verbal communication. Therefore, there have been many researches to give commands to a robot. Existing studies were limited to recognition of ﬁxed hand gestures and shapes, requiring users to be educated on motions that can be used to communicate with robots. To solve this problem, we use fuzzy inference to select meaningful gesture in continuous gesture at ﬁrst. Hand position is interpolated using the Lagrangian method. Also, we use the Kalman ﬁlter for object-occlusion or self-occlusion. After generating a sequence of continuously received hand positions using a chain code, the fuzzy theory is used to select meaningful motions among various hand gestures. Eventually, we perform a method of recognizing meaningful hand gestures using a recurrent neural network with bidirectional long short-term memory (LSTM) architecture. Even though selecting the meaningful motion was hard, if it was selected correctly, the ratio of hand gesture recognition was very high in experiment results.
Association of Occupation and Breast Cancer Mortality in the State of Vermont, 1989-1993

Vermont’s breast cancer death rate is among the highest in the U.S. This study analyzed the association between breast cancer mortality and occupation in Vermont women. Given that Vermont is a rural state, one initial hypothesis was that occupational exposure to pesticides might partly explain the high death rate. Death certificate data from 1989-1993 were analyzed to determine relative risk of breast cancer death according to occupation. Case-control analysis demonstrated increased relative risk of breast cancer death for women in two broad occupational groups: 1) Executive, Administrator and Managers and 2) Professionals. Decreased relative risk of breast cancer death was seen for the occupational group of Homemaker. Data indicated that women in the occupational group of Farming, Forestry, and Fishing were not at increased risk of dying from breast cancer. The associations of occupation and breast cancer mortality in Vermont women do not differ significantly from those seen in larger U.S. studies.
Estimating hourly global solar irradiance using artificial neural networks – A case study of Hong Kong

Solar energy is the most popular resource for power generation among the various available renewable energy alternatives. Solar radiation data are important for solar photovoltaic (PV) systems and passive energy-efficient building designs. Due to the unavailability of measurement in rural locations, solar radiation prediction models are required. In recent years, the Artificial Neural Networks (ANN) were successfully used for predicting solar radiation. However, previous works indicated that the ANN techniques were mainly focusing on prediction of monthly average or daily solar radiation, a few of them were modelled for predicting solar irradiance in hourly basis. In this study, prediction models of global solar irradiance on a horizontal surface will be developed based on neural-network techniques. Hourly meteorological variables between 2012 and 2015 acquired from the measurements made by local meteorological station were used for the study. To consider the effectiveness of individual predictors, different combinations of input variables were analysed using the Levenberg-Marquardt (LM) algorithm. Finally, equations were modelled by regression based on the important predictors. The developed models were used to estimate the global irradiance and assessed against measurement results.
Systematic Comparison of Power Corridor Classification Methods from ALS Point Clouds

Power corridor classification using LiDAR (light detection and ranging) point clouds is an important means for power line inspection. Many supervised classification methods have been used for classifying power corridor scenes, such as using random forest (RF) and JointBoost. However, these studies did not systematically analyze all the relevant factors that affect the classification, including the class distribution, feature selection, classifier type and neighborhood radius for classification feature extraction. In this study, we examine these factors using point clouds collected by an airborne laser scanning system (ALS). Random forest shows strong robustness to various pylon types. When classifying complex scenes, the gradient boosting decision tree (GBDT) shows good generalization. Synthetically, considering performance and efficiency, RF is very suitable for power corridor classification. This study shows that balanced learning leads to poor classification performance in the current scene. Data resampling for the original unbalanced dataset may not be necessary. The sensitivity analysis shows that the optimal neighborhood radius for feature extraction of different objects may be different. Scale invariance and automatic scale selection methods should be further studied. Finally, it is suggested that RF, original unbalanced class distribution, and complete feature set should be considered for power corridor classification in most cases.
Adaptive cache policy scheduling for big data applications on distributed tiered storage system

Multitiered storage systems, which are made up of heterogeneous devices, are widely used in distributed environments to accelerate the I/O performance of upper big data applications. It raises new challenges in efficient data migration through smart caching mechanisms among heterogeneous storage levels, such as MEM‐SSD‐HDD. To optimize the cache policy scheduling mechanism on the distributed tiered storage architecture, we proposed a general framework with five layers, including a tiered storage system layer, a cache migration policy layer, a cache policy adaptive scheduling layer, a data access pattern layer, and a big data application layer. The framework prototype has been designed and implemented on the widely used distributed hybrid storage system named Alluxio. To meet the demands of the big data application layer, on the one hand, we designed a couple of cache eviction policies and promotion policies covering various access patterns on the cache migration policy layer (several proposed eviction policies have been adopted by the Alluxio open‐source community). On the other hand, two adaptive cache policy scheduling algorithms for selecting appropriate policies in various scenarios are designed and implemented on the cache policy adaptive scheduling layer. The scheduling algorithms are designed based on the hit ratio statistics and data access pattern model prediction, respectively. Experimental results show that the proposed cache policies are very effective for various big data applications, such as Spark SQL. The proposed cache policy scheduling algorithms with various eviction policies can improve around 20% hit ratio than that with a single eviction policy.
Topographic Control of Southern Ocean Gyres and the Antarctic Circumpolar Current: A Barotropic Perspective

In the Southern Ocean the Antarctic Circumpolar Current is significantly steered by large topographic features, and subpolar gyres form in their lee. The geometry of topographic features in the Southern Ocean is highly variable, but the influence of this variation on the large-scale flow is poorly understood. Using idealized barotropic simulations of a zonal channel with a meridional ridge, it is found that the ridge geometry is important for determining the net zonal volume transport. A relationship is observed between ridge width and volume transport that is determined by the form stress generated by the ridge. Gyre formation is also highly reliant on the ridge geometry. A steep ridge allows gyres to form within regions of unblocked geostrophic (f/H) contours, with an increase in gyre strength as the ridge width is reduced. These relationships among ridge width, gyre strength, and net zonal volume transport emerge to simultaneously satisfy the conservation of momentum and vorticity.
Airflow characteristics under planar opposed ventilation jets in a controlled indoor environment

Healthy, comfortable and intelligent indoor environment is a key objective in comprehensive well-being. This is also a main target of advanced HVAC-technology. In indoor environments, air distribution plays a major role while providing clean air to occupants. Therefore, investigating ventilation jets is an essential matter. In this study, the main objective was to improve knowledge on numerical modeling and airflow characteristics. In addition, the reliability of modeling methods were investigated. The experiments were carried out in a test room by using omnidirectional anemometers. The planar air jets were supplied below the ceiling from the opposite long-side walls. The exhaust openings were correspondingly near the floor. Isothermal and incompressible viscous airflow was simulated by using RANS, URANS, DES (SST-k-ω - LES) and SBES (SST-k-ω - LES) methods. The results show that modeling method has considerable effects on the predicted airflow field. However, the study indicates that correctly implemented numerical modeling may predict well the averaged airflow characteristics. Furthermore, the unsteady simulation allows airflows to fluctuate reasonably. In addition, SBES and DES methods were more sensitive in generating the airflow fluctuations than URANS. A recommendation is to carefully test and choose a modeling method for indoor airflows.
Peningkatan Potensi Ibu Rumah Tangga dalam Mengolah Sampah Organik Rumah Tangga Menggunakan Metode Takakura di Desa Cibiru Wetan, Kabupaten Bandung

INCREASING OF HOUSEWIVES POTENTIAL IN PROCESSING DOMESTIC ORGANIC WASTE BY USING TAKAKURA METHOD IN CIBIRU WETAN VILLAGE, BANDUNG REGENCY. Domestic waste (DW) is a major environmental challenge for many urban local bodies in Indonesia both in the village and in the city, where urbanization, industrialization and economic growth have resulted in increased waste generation per person. One way to solve this waste is to turn organic domestic into compost. Composting, the recycling of organic waste such as vegetation and food waste reduces the amount of waste going to landfill and is, therefore, a rapidly growing sector. Desa Cibiru Wetan, Kab. Bandung, West Java is one of the villages that has learned about how to process organic waste into compost and become a pilot project but because of the distance between raw materials and management with compost incubator so that compost production is disturbed. Therefore, the purpose of the project activity was to produce compost from domestic organic waste by the Takakura method. In this method, a small incubator was used and placed at the home of the community. Although on a small scale but with many multipliers, it able to produce an abundant compost and can be an alternative for the existing compost incubator method. The stage included counseling and socialization, training in making incubator Takakura, training in production compos,t and monitoring and evaluation. The results showed a good understanding of both groups for both the socialization and counseling stages as well as for the practice of production of compost. In conclusion, the activity on the production of compost by using Takakura method able was to solved for domestic organic waste and remind set the interest of the community in producing compost.
Animal model for colorectal cancer.

: The development of a satisfactory rodent model for cancer of the large intestine began with the discovery by Laqueur and associates in 1962 that the plant product, cycasin (methylazoxymethanol glycoside), is a potent carcinogen for rodents. Soon after that, DMH, AOM, and MAM were found to be even more efficient intestinal carcinogens in rats. These three compounds, plus two direct acting carcinogens (MNNG, MNU) are used almost exclusively in current animal investigations. Although all these chemicals have some degree of activity in all rodents, they are most effective in rats. Various rat strains differ somewhat in susceptibility, Sprague-Dawley being the most sensitive to these carcinogens. Cancers of the large intestine in the animal model resemble adenocarcinomas in humans, and they spread in a similar manner except that metastases to the liver and lung are very uncommon in animals. Animal studies support epidemiological and human experimental observations of dietary factors involved in colorectal cancer formation. Most physicians believe that the majority of colorectal cancers develop from preexisting adenomas. Morson has shown that large adenomas and villous adenomas have a greater risk of developing cancer than small adenomas. Hill has theorized that there are different factors responsible for the formation of small adenomas from normal mucosa, for the growth of small to large adenomas, and for the development of cancer from large adenomas. Animal studies provide some support for this concept. Weak intestinal carcinogens tend to induce more benign adenomas than carcinomas. Very small doses of strong carcinogens also induce some adenomas and a few early polypoid intestinal cancers after a long latent period. Moderate to large amounts of DHM, for example, induce only malignant lesions even when these lesions are as small as 1 mm. These observations suggest a relationship between adenomas and carcinomas. There is also biochemical evidence to support the staged progression of carcinogenesis. An example is the graded increases in ODC activity that occur in tissues undergoing tumorigenesis.
PickCells: A Physically Reconfigurable Cell-composed Touchscreen

Touchscreens are the predominant medium for interactions with digital services; however, their current fixed form factor narrows the scope for rich physical interactions by limiting interaction possibilities to a single, planar surface. In this paper we introduce the concept of PickCells, a fully re-configurable device concept composed of cells, that breaks the mould of rigid screens and explores a modular system that affords rich sets of tangible interactions and novel across-device relationships. Through a series of co-design activities -- involving HCI experts and potential end-users of such systems -- we synthesised a design space aimed at inspiring future research, giving researchers and designers a framework in which to explore modular screen interactions. The design space we propose unifies existing works on modular touch surfaces under a general framework and broadens horizons by opening up unexplored spaces providing new interaction possibilities. In this paper, we present the PickCells concept, a design space of modular touch surfaces, and propose a toolkit for quick scenario prototyping.
Harmful Fouling Communities on Fish Farms in the SW Mediterranean Sea: Composition, Growth and Reproductive Periods

Biological fouling organisms on fish cages represent a major issue and costly factor in marine finfish aquaculture. Cnidarians have been identified as one of the most problematical groups, contributing significantly to the occlusion and structural stress of the cage nets, but also dramatically affecting farmed species health in aquaculture facilities worldwide. Recently, significant relationships were established in different Spanish aquaculture facilities between hydrozoans and juvenile fish affected by gill injuries and mortality episodes. Community composition, growth rate and reproductive potential of biofouling were monitored on fish cages over two seasonal periods of fry cages farming, located in southern Spain (SW Alboran Sea), with a special focus on cnidarians. Biomass and community composition of biofouling changed with time and between studied periods, with a marked seasonality in colonization periods and taxonomic composition, particularly for the colonial hydrozoans. The hydroids Ectopleura larynx and Pennaria disticha were found at the highest densities. P. disticha was responsible for major biomass contribution to total hydroid biomass with the fastest growth rates. In addition, actinulae larvae of E. larynx were identified in zooplankton samples at high densities especially during periods of fry introduction in sea cages (when fish are highly vulnerable). These results corroborate evidence of the detrimental influence of fouling cnidarians in Mediterranean finfish aquaculture due to a direct harmful impact on fish health. Investigations on population dynamics, reproductive biology and envenomation potential of fouling hydrozoans should be regarded as key component of best monitoring practices to ensure good farmed fish welfare, maximization of aquaculture production and overall marine spatial planning.
Intercomparison of sediment transport formulas in current and combined wave-current conditions

The 2D horizontal morphodynamic modeling system MORSYS2D simulates bottom topography evolution in coastal zones. Sand fluxes are computed with different practical formulas, either for current dominated (e.g, Ackers & White, van Rijn) or combined wave-current flows (e.g., Soulsby van Rijn). Although sensitivity analyses of bottom topography changes in terms of the transport formulas used have already been done, a comparison of the sediment fluxes computed with the different formulations, considering the same flow conditions and using the parameterizations considered in the model (e.g, bottom roughness, bottom stress) is lacking. With that purpose, we have conceptualized a suitable range of wave and current conditions above a sand bed composed of uniform sediment that is characteristic of the conditions encountered in estuaries, tidal inlets and continental shelves, and applied the several flux formulations. To assess the differences obtained, the average value and the standard deviation were computed for each flow condition. This exercise enabled us to identify, for different parameter ranges, the transport formulations which are consistent with one another and those that deviate the most from the mean. This information is useful in practical applications by defining conditions for optimal formula performance.
Unified collision avoidance behaviour for autonomously steering characters

Amongst the domains that utilise artificial agents, the interactive multimedia requires the greatest variety of agent motion. Digital characters must be able to wander, pursue, flee, follow and flock according to the requirements of their virtual environment. This is a well-studied problem for which many satisfactory solutions exist. However, solutions to the complementary problem of collision avoidance are less effective. Such solutions are specialised according to the type of obstacle to be avoided, which may require them to be used simultaneously. In consequence, they can compete for control over character motion. Although a number of arbitration strategies have been developed to address this problem, each requires substantial calibration and can cause unrealistic and erratic motion. As motion is a characteristic that can be immediately judged by observers, such flaws can pervasively undermine the perceived quality of multimedia systems. This thesis proposes an alternative collision avoidance technique that is intended to be complementary to the other forms of motion that characters may perform. It involves the application of repulsive – ‘push away’ – and tangential – ‘push around’ – forces to characters, each moderated by the character’s distance from the obstacle it is attempting to avoid. The resultant force vectors are a product of the arrangement of obstacles in the virtual environment, represented using a procedurally generated field. The technique can be applied to a variety of motion scenarios involving characters with disparate kinematic properties. It is effective in many pathological failure cases identified in steering literature and, within a small number of constraints, the limitations of the system according to its configuration can be precisely known.