Miracle-dz/UniFAR-FTUs huggingface dataset:
Applying Deep Learning in Street View Imagery for Environmental Health Research

approved: ______________________________________________________ Dr. Lizhong Chen Urban green space is associated with multiple physical and mental health outcomes. Several benefits of green space, such as stress reduction and attention restoration, are dependent on visual perception of green space exposures. However, traditional green space exposure measures do not capture street-level exposures. In this project, we apply deep learning models to measure green space in street view imagery. We train Faster R-CNN model on PasadenaUrbanTree dataset and equip it with the ability to detect trees, which is then used to count the number of trees in the test images. We also employ a PSPNet model that pretrained on ade20k dataset to do semantic segmentation on street view images and compute the portion of green space. Combining the outcomes from object detection and semantic segmentation, the green space in street view imagery can be measured quantitatively.
Dynamic Graph Cuts in Parallel

This paper aims at bridging the two important trends in efficient graph cuts in the literature, the one is to decompose a graph into several smaller subgraphs to take the advantage of parallel computation, the other is to reuse the solution of the max-flow problem on a residual graph to boost the efficiency on another similar graph. Our proposed parallel dynamic graph cuts algorithm takes the advantages of both, and is extremely efficient for certain dynamically changing MRF models in computer vision. The performance of our proposed algorithm is validated on two typical dynamic graph cuts problems: the foreground-background segmentation in video, where similar graph cuts problems need to be solved in sequential and GrabCut, where graph cuts are used iteratively.
Survival of Patients with Primary Brain Tumors: Comparison of Two Statistical Approaches

Purpose We reviewed the survival time for patients with primary brain tumors undergoing treatment with stereotactic radiation methods at the Masaryk Memorial Cancer Institute Brno. We also identified risk factors and characteristics, and described their influence on survival time. Methods In summarizing survival data, there are two functions of principal interest, namely, the survival function and the hazard function. In practice, both of them can depend on some characteristics. We focused on nonparametric methods, propose a method based on kernel smoothing, and compared our estimates with the results of the Cox regression model. The hazard function is conditional to age and gross tumor volume and visualized as a color-coded surface. A multivariate Cox model was also designed. Results There were 88 patients with primary brain cancer, treated with stereotactic radiation. The median survival of our patient cohort was 47.8 months. The estimate of the hazard function has two peaks (about 10 months and about 40 months). The survival time of patients was significantly different for various diagnoses (p≪0.001), KI (p = 0.047) and stereotactic methods (p = 0.033). Patients with a greater GTV had higher risk of death. The suitable threshold for GTV is 20 cm3. Younger patients with a survival time of about 50 months had a higher risk of death. In the multivariate Cox regression model, the selected variables were age, GTV, sex, diagnosis, KI, location, and some of their interactions. Conclusion Kernel methods give us the possibility to evaluate continuous risk variables and based on the results offer risk-prone patients a different treatment, and can be useful for verifying assumptions of the Cox model or for finding thresholds of continuous variables.
The weakest failure detector for solving consensus

We determine what information about failures is necessary and sufficient to solve Consensus in asynchronous distributed systems subject to crash failures. In Chandra and Toueg [1996], it is shown that W, a failure detector that provides surprisingly little information about which processes have crashed, is sufficient to solve Consensus in asynchronous systems with a majority of correct processes. In this paper, we prove that to solve Consensus, any failure detector has to provide at least as much information as W. Thus, W is indeed the weakest failure detector for solving Consensus in asynchronous systems with a majority of correct processes.
Measurement and Quality in Object-Oriented Design

In order to support the maintenance of object-oriented software systems, the quality of their design must be evaluated using adequate quantification means. In spite of the current extensive use of metrics, if used in isolation, metrics are oftentimes too fine grained to quantify comprehensively an investigated aspect of the design. To help the software engineer detect and localize design problems, the novel detection strategy mechanism is defined so that deviations from good-design principles and heuristics are quantised inform of metrics-based rules. Using detection strategies an engineer can directly localize classes or methods affected by a particular design flaw (e.g. God Class), rather than having to infer the real design problem from a large set of abnormal metric values. In order to reach the ultimate goal of bridging the gap between qualitative and quantitative statements about design, the dissertation proposes a novel type of quality model, called factor-strategy. In contrast to traditional quality models that express the goodness of design in terms of a set of metrics, this novel model relates explicitly the quality of a design to its conformance with a set of essential principles, rules and heuristics, which are quantified using detection strategies.
Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning

Many state-of-the-art approaches for Multi Kernel Learning (MKL) struggle at finding a compromise between performance, sparsity of the solution and speed of the optimization process. In this paper we look at the MKL problem at the same time from a learning and optimization point of view. So, instead of designing a regularizer and then struggling to find an efficient method to minimize it, we design the regularizer while keeping the optimization algorithm in mind. Hence, we introduce a novel MKL formulation, which mixes elements of p-norm and elastic-net kind of regularization. We also propose a fast stochastic gradient descent method that solves the novel MKL formulation. We show theoretically and empirically that our method has 1) state-of-the-art performance on many classification tasks; 2) exact sparse solutions with a tunable level of sparsity; 3) a convergence rate bound that depends only logarithmically on the number of kernels used, and is independent of the sparsity required; 4) independence on the particular convex loss function used.
Carbon Dioxide and Methane Dynamics in a Small Boreal Lake During Winter and Spring Melt Events

In seasonally ice‐covered lakes, carbon dioxide (CO2) and methane (CH4) emission at ice‐off can account for a significant fraction of the annual budget. Yet knowledge of the mechanisms controlling below lake‐ice carbon (C) dynamics and subsequent CO2 and CH4 emissions at ice‐off is limited. To understand the control of below ice C dynamics, and C emissions in spring, we measured spatial variation in CO2, CH4, and dissolved inorganic and organic carbon from ice‐on to ice‐off, in a small boreal lake during a winter with sporadic melting events. Winter melt events were associated with decreased surface water DOC in the forest‐dominated basin and increased surface water CH4 in the mire‐dominated basin. At the whole‐lake scale, CH4 accumulated below ice throughout the winter, whereas CO2 accumulation was greatest in early winter. Mass‐balance estimates suggest that, in addition to the CO2 and CH4 accumulated during winter, external inputs of CO2 and CH4 and internal processing during ice‐melt could represent significant sources of C gas emissions during ice‐off. Moreover, internal processing of CO2 and CH4 worked in opposition, with production of CO2 and oxidation of CH4 dominating at ice‐off. These findings have important implications for how small boreal lakes will respond to warmer winters in the future; increased winter melt events will likely increase external inputs below ice and thus alter the extent and timing of CO2 and CH4 emissions to the atmosphere at ice‐off.
Non‐Oriented MLS Gradient Fields

We introduce a new approach for defining continuous non‐oriented gradient fields from discrete inputs, a fundamental stage for a variety of computer graphics applications such as surface or curve reconstruction, and image stylization. Our approach builds on a moving least square formalism that computes higher‐order local approximations of non‐oriented input gradients. In particular, we show that our novel isotropic linear approximation outperforms its lower‐order alternative: surface or image structures are much better preserved, and instabilities are significantly reduced. Thanks to its ease of implementation (on both CPU and GPU) and small performance overhead, we believe our approach will find a widespread use in graphics applications, as demonstrated by the variety of our results.
Recognition of Meteor Showers From the Heights of Ionization Trails

Meteoroids constantly enter the Earth's atmosphere, collide with atmospheric molecules, and heat and ablate in the sufficiently dense atmospheric layers at heights between 70 and 110 km. It is still a problem to recognize properties of the meteor streams among the sporadic background. The meteor radar observations at Sodankylä Geophysical Observatory (67°22′N, 26°38′E, Finland) during 2008–2017 show that meteoroids of some showers produce ionization trails at altitudes noticeably exceeding those of sporadic meteors. Using the median height of meteor trails and corresponding upper and lower quartiles as a metric, we unambiguously distinguish all northern hemisphere meteor showers with a zenithal hourly rate larger than 12, namely, the Quadrantids, Lyrids, Eta Aquariids, Arietids (or/and Daytime Zeta Perseids), Perseids, Orionids, Leonids, and Geminids. Additionally, signatures of a possible meteor stream during 26–30 January were detected, although identification of this stream is still under question. This new analysis indicates that the origin of the shower meteor trails at higher altitudes is likely due to higher speed and probably lighter or less dense meteoroids belonging to the showers.
Static code analysis

Programmers usually employ static checkers, it checks our programs for errors without executing them, in a process called static code analysis. In this way, it works with a program that has an initial indication of correctness (because it compiles) and try to avoid well-known traps and pitfalls before measuring it against its specifications (when it's tested). We use FindBugs, a popular open source static code checker for Java. Static code checkers in Java come in two flavors: those that work directly on the program source code and those that work on the compiled bytecode. Although each code checker works in its own way, most share some basic traits. They read the program and construct some model of it, a kind of abstract representation that they can use for matching the error patterns they recognize. They also perform some kind of data-flow analysis, trying to infer the possible values that variables might have at certain points in the program. Data-flow analysis is especially important for vulnerability checking, an increasingly important area for code checkers
Photometric scaling relations for bulges of galaxies

We describe the photometric parameters of the bulges of galaxies of different Hubble types including ellipticals, lenticulars, early and late type spirals and early type dwarf galaxies. Analyzing the distributions of various photometric parameters and two- and three-dimensional correlations between them, we find that there is a difference in the correlations exhibited by bright ($M_{\rm K} < -22$) and faint bulges, irrespective of their Hubble type. Importantly, the bright bulges, which include typically E/S0 galaxies and bulges of early type spirals, are tightly distributed around a common photometric plane (PP), while their fainter counterparts, mainly bulges of late type spirals and dwarf galaxies show significant deviation from the planar distribution. We show that the specific entropy, determined from the bulge structural parameters, systematically increases as we move from late to early Hubble types. We interpret this as evidence for hierarchical merging and passive evolution scenarios for bright and faint bulges respectively.
Toe joints that enhance bipedal and fullbody motion of humanoid robots

Addresses the extension of a humanoid's action capability by attaching toe joints. The effectiveness of toe joints is discussed in three aspects. One is utilizing it to speed up the walking, another is using it to enable a humanoid to go up higher steps, and the other is using it to whole-body action in which knees are contacting the ground. Feet with toe joints are developed for humanoid 'H6'. An experiment of the wholebody action in which knees are contacting the ground is carried out to show the usefulness of toe joints for such actions. Then the walking pattern generation system is extended to use toe joints. Using this extended system maximum speed of knee joints can be reduced at the same walking speed, and 80% faster walking speed is achieved on humanoid 'H6'.
The clinical assessment of the patient with early dementia

Dementia is a clinical state characterised by a loss of function in at least two cognitive domains. When making a diagnosis of dementia, features to look for include memory impairment and at least one of the following: aphasia, apraxia, agnosia and/or disturbances in executive functioning. To be significant the impairments should be severe enough to cause problems with social and occupational functioning and the decline must have occurred from a previously higher level. It is important to exclude delirium when considering such a diagnosis. When approaching the patient with a possible dementia, taking a careful history is paramount. Clues to the nature and aetiology of the disorder are often found following careful consultation with the patient and carer. A focused cognitive and physical examination is useful and the presence of specific features may aid in diagnosis. Certain investigations are mandatory and additional tests are recommended if the history and examination indicate particular aetiologies. It is useful when assessing a patient with cognitive impairment in the clinic to consider the following straightforward questions: An understanding of cognitive function and its anatomical correlates is necessary in order to ascertain which brain areas are affected. This, in turn, aids diagnosis. A discussion of the localisation of all cognitive processes is beyond the scope of this review. It is, however, particularly important to have an understanding of memory and its subdivisions, which is necessary to aid in differential diagnosis. We shall then illustrate how the history and examination, including bedside cognitive testing, are used in diagnosis. When considering any memory disorder it is important to have an understanding …
Regression with n→1 by Expert Knowledge Elicitation

We consider regression under the "extremely small n large p" condition, where the number of samples n is so small compared to the dimensionality p that predictors cannot be estimated without prior knowledge. This setup occurs in personalized medicine, for instance, when predicting treatment outcomes for an individual patient based on noisy high-dimensional genomics data. A remaining source of information is expert knowledge, which has received relatively little attention in recent years. We formulate the inference problem of asking expert feedback on features on a budget, propose an elicitation strategy for a simple "small n" setting, and derive conditions under which the elicitation strategy is optimal. Experiments on simulated experts, both on synthetic and genomics data, demonstrate that the proposed strategy can drastically improve prediction accuracy.
Experimental study on perfomance of wind catcher in tropical climate

Today, the knowledge of using natural ventilation in buildings with consideration of traditional architecture of different areas, has become an important factor to consider in the buildings. The focus is on increasing the quality of space regarding to climate and environmental parameters. Iran is a country with vast and different types of climate and each one has come with it's own harmonic way and response in architecture. In these study conventional traditional buildings exposed to the hot and humid weather in the northern coast of Persian Gulf and Oman Sea is considered. The wind catcher is widely applied in these areas to enhance the natural ventilation in buildings. Studying the regional measures of the local expert architects can contribute to a suitable building design for such a climate. This paper aims to study how the wind catcher works by the wind-tunnel testing and CFD simulations. The main objective of this research is to discover how a wind catcher works by considering climate situations of a tropical region. The results show that increasing the height optimizes a wind catcher's performance by taking other appropriate variables. Furthermore, this study shows that the proposed system, even at relatively low speed outdoor wind, is able to create ventilation in a residential unit. According to the results of the wind-tunnel test and CFD simulations, the wind catcher can be used in hot and humid tropical areas to help create thermal comfort in green buildings by increasing the natural ventilation.
Decadal changes in summer precipitation over arid northwest China and associated atmospheric circulations

The precipitation over arid regions may be low, but its environmental impacts can be very dramatic. The decadal variability in precipitation can also effectively disturb climatic environmental regimes. To advance the understanding of precipitation variability over arid regions, this paper focuses on decadal variability in summer precipitation over arid northwest China and its associated atmospheric circulations, using observation‐based data and atmospheric reanalysis during the period 1961–2016. The results show that climatologically, precipitation over this region has a strong seasonality and that 60.2% falls in summer. The summer precipitation increased 15.5 mm, accounting for 52.4% of the total annual increase in this part of China from 1961 to 2016. Decadal changes in summer precipitation occurred in approximately 1991 with a north–south difference structure modulated by large‐scale circulation anomalies over the Indian Ocean and central Asia as well as a shift in water vapour transport. In a positive phase, anticyclonic circulation anomalies occupy the Indian Ocean with cyclonic anomalies over central Asia, favouring stronger northwards moisture transport towards northwest China, and vice versa. Moreover, the significantly enhanced northwards water vapour transport from low‐latitude seas is also critical to the decadal changes approximately in 1991 summer precipitation in arid northwest China. These findings contribute to the understanding of decadal precipitation variability over arid regions, especially the increasing influence of low‐latitude circulations and moisture transport processes.
Arhgef15 Promotes Retinal Angiogenesis by Mediating VEGF-Induced Cdc42 Activation and Potentiating RhoJ Inactivation in Endothelial Cells

Background Drugs inhibiting vascular endothelial growth factor (VEGF) signaling are globally administered to suppress deregulated angiogenesis in a variety of eye diseases. However, anti-VEGF therapy potentially affects the normal functions of retinal neurons and glias which constitutively express VEGF receptor 2. Thus, it is desirable to identify novel drug targets which are exclusively expressed in endothelial cells (ECs). Here we attempted to identify an EC-specific Rho guanine nucleotide exchange factor (GEF) and evaluate its role in retinal angiogenesis. Methodology/Principal Findings By exploiting fluorescence-activated cell sorting and microarray analyses in conjunction with in silico bioinformatics analyses, we comprehensively identified endothelial genes in angiogenic retinal vessels of postnatal mice. Of 9 RhoGEFs which were highly expressed in retinal ECs, we show that Arhgef15 acted as an EC-specific GEF to mediate VEGF-induced Cdc42 activation and potentiated RhoJ inactivation, thereby promoting actin polymerization and cell motility. Disruption of the Arhgef15 gene led to delayed extension of vascular networks and subsequent reduction of total vessel areas in postnatal mouse retinas. Conclusions/Significance Our study provides information useful to the development of new means of selectively manipulating angiogenesis without affecting homeostasis in un-targeted tissues; not only in eyes but also in various disease settings such as cancer.
Satisfying Resource Constraints in Space Missions byOn-line Task Reconfiguration

This paper addresses the problem of robust plan execution in the context of exploration mission plans carried on by planetary rovers. In order to deal with limited computational resources, and with limited rover’s autonomy (the rover is not allowed to change its plan), the paper proposes a novel methodology to cope with contingencies rising at execution time. The approach aims at reconfiguring on the fly the plan by changing the parameter configuration of the actions still to be executed. By exploiting an enriched action representation based on the notion of execution modalities, the ReCon system is able to (i) early detect the violation of mission resource constraints, (ii) find (if any) a new assignment of modalities to preserve the mission plan constraints. ReCon uses constraint satisfaction techniques both for plan consistency and plan reconfiguration. Finally, the paper reports a preliminary set of experimental results which in practice confirms the feasibility and the advantages of the approach.
The effect of toe trimming on behavior, mobility, toe length and other indicators of welfare in tom turkeys.

Society is increasingly concerned about the welfare of animals kept for food production, for this reason, invasive procedures such as toe trimming in turkeys must be studied to assess the corresponding welfare implications and to ensure such procedures are acceptable for continued use. To this end, research was conducted to evaluate the welfare effects of toe trimming on toms raised to 140 d. The study used 306 Hybrid Converter toms, half of which were toe trimmed using a Microwave Claw Processor (MCP) which group are denoted T, and half of which were sham treated but not trimmed, which group are denoted NT. Turkey behavior was observed on d 1, 3, 5, and 133. Toe cross sections were taken every second day for 14 d after treatment and were used to histologically examine the healing process. Toe length, gait score, and bird stance were assessed on d 55, 84, 119, and 139. For the first 5 d after treatment, T birds demonstrated less active behaviors such as feeding, standing, walking and running (P ≤ 0.05), indicative of pain with the effect diminishing with age. At d 133, T turkeys stood more and walked less than NT birds (P ≤ 0.05). Gait score and bird stance were not affected by treatment. Trimmed toes were on average 91.9% of the length of NT toes and toe length was more variable (P ≤ 0.05) as a result of the trimming process. Histological examination indicated T toes had complete epithelium closure over the healthy tissue by d 8 and were fully healed by d 14. Although bird mobility and stance were unaffected by treatment, turkey behavior both early and late in the production cycle were suggestive of pain and balance effects; both indicators of reduced welfare as a result of toe trimming.