Miracle-dz/UniFAR-FTUs huggingface dataset:
Free-Form Image Inpainting with Gated Convolution (Supplementary)

In this supplementary material, we first provide details of our free-form mask generation algorithm in Section 1 and sketch generation algorithm in Section 2. We then study the effects of sketch input in Section 3 with an example where the input image uses the same mask but different sketches. Next we provide visualization and interpretation of learned gating values in Section 4. We show additional ablation study of our proposed SN-PatchGAN in Section 5. We show more comparison results of Global&Local [1], ContextAttention [4], PartialConv [2] (both our implementation within same framework and official model via online demo1) and our GatedConv in Section 6. We finally show more inpainting results of our system with support of free-form masks and user guidance on both natural scenes and faces in Section 7. Moreover, a recorded realtime video demo is available at: https://youtu.be/ uZkEi9Y2dj4.
Screening for Osteoporosis – Making an Informed Choice of DXA or Calcaneal QUS

Osteoporosis is characterized by a reduction in bone mass or bone mineral density and an increase in fracture risk. As it runs a silent course before presenting with a fracture, the importance of screening especially of risk groups for timely diagnosis and treatment, cannot be overemphasized. Often in developing countries, where access to labs and devices like DXA may be limited, onsite high-volume screening can contribute significantly in diagnosing Osteoporosis cases and contribute towards reduction in morbidity and economic burden due to development of fractures. Though DXA is the gold standard for Osteoporosis diagnosis, recently calcaneal quantitative ultrasound is emerging as a convenient, portable, low cost and radiation free device for in-clinic or onsite screening. Therefore, the differences in parameter interpretation and evaluation, along with relative advantages and disadvantages of using calcaneal QUS over DXA should be well understood before making an informed choice.
A Statistical Framework for the Prediction of Fault-Proneness

Accurate prediction of fault-prone modules in software development process enables effective discovery and identification of the defects. Such prediction models are especially valuable for the large-scale systems, where verification experts need to focus their attention and resources to problem areas in the system under development. This chapter presents a methodology for predicting fault-prone modules using a modified random forests algorithm. Random forests improve classification accuracy by growing an ensemble of trees and letting them vote on the classification decision. We applied the methodology to five NASA public domain defect datasets. These datasets vary in size, but all typically contain a small number of defect samples. If overall accuracy maximization is the goal, then learning from such data usually results in a biased classifier. To obtain better prediction of fault-proneness, two strategies are investigated: proper sampling technique in constructing the tree classifiers, and threshold adjustment in determining the “winning” class. Both are found to be effective in accurate prediction of fault-prone modules. In addition, the chapter presents a IGI PUBLISHING This paper appears in the publication, Advances in Machine Learning Applications in Software Engineering edited by Du Zhang & Jeffrey J.P. Tsa © 2007, IGI Global 701 E. Chocolate Avenue, Suite 200, Hershey PA 17033-1240, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.igi-pub.com ITB14916
Interleukin-6 - exercise factor and modulator of metabolic function? : review article

Recent evidence supports multifaceted functions of interleukin- 6 (IL-6). While this cytokine was originally known for its pro-inflammatory function in diseases such as rheumatoid arthritis, today it is recognised for its important antagonistic, anti-inflammatory role in regulating immune processes. Released from skeletal muscle, abdominal adipose and hypothalamic tissue during exercise, it also has 'endocrine-like' metabolic regulatory action that has been linked to energy expenditure, glycogenolysis, and fat oxidation during acute exercise exposure. The quantity and timing of exercise-induced IL- 6 production is dependent on exercise duration, intensity and mode. Eccentric exercise that results in damage to contractile muscle tissue and/or the muscle cytoskeleton, is associated with an increase that peaks approximately 2 hours after cessation of exercise. In contrast, concentric exercise, which is not accompanied by an inflammatory response, induces an increment in IL-6 during exercise. During concentric exercise intramuscular IL-6 production is stimulated by complex signalling cascades which are initiated by elevated intramuscular calcium concentrations. With prolongation of the exercise IL-6 has been shown to act as a 'sensor' regulating blood glucose homeostasis and lipolysis in white adipose tissue. Activation of the IL-6 gene in skeletal muscle is substrate-regulated and greatest when muscle glycogen stores are low. The therapeutic potential of IL-6 in treating obesity has been established in both rodents and humans. While a deficiency of IL-6 has been associated with greater fat mass and lower metabolic rate during exercise, elevated circulating IL-6 concentrations have been shown to inhibit the production of tumour necrosis factor-alpha. This may provide a mechanism to explain how exercise attenuates metabolic disorders associated with low-grade inflammation such as type-2 diabetes, artherosclerosis and possibly autoimmune diseases.
NFS Nordic Fertility Society Clinical guideline

Each clinical situation, including the condition of the patient and other information, must be assessed individually by the fertility clinic staff, who should then act based on his or her experience, knowledge, and evaluation. Clinical science is constantly developing. New examination and treatment options may therefore arise. Some of these may be internationally recognised, but not yet assessed in relation to the existing guidelines.
Comportamiento hemodinámico de la anestesia total intravenosa con propofol en cirugía de tumores intracraneales

Introduction: Within the neurosurgical conditions, brain tumors conform a very peculiar group and constitute a challenge for the anesthesiologist. Objectives: To specify the anesthetic conduct in patients with supratentorial intracranial tumors and the perioperative behavior of hemodynamic variables, perioperative complications as well as to correlate the complications appeared with the age of patients. Method: A descriptive study was carried out, with 39 patients underwent surgery of supratentorial intracranial tumors, in “Capitán Roberto Rodriguez Fernandez” Hospital, Morón, between January 2009 and December 2010. Total intravenous anesthesia with Propofol was applied to them. All of them greater than 18 years, with physical state ASA II, III and Glasgow scale superior to 8 points. The induction and maintenance were made with propofol, fentanyl and vecuronium, oxygen and compressed air. The bio-parameter behavior was monitoring in four times. Results: It was found stability in the monitorized parameters. The most frequent complication was the respiratory alkalosis. Complications related to propofol were not identified, nor correlation between complications appeared and the age of the patients.
Dynamic Points Agglomeration for Hierarchical Point Sets Learning

Many previous works on point sets learning achieve excellent performance with hierarchical architecture. Their strategies towards points agglomeration, however, only perform points sampling and grouping in original Euclidean space in a fixed way. These heuristic and task-irrelevant strategies severely limit their ability to adapt to more varied scenarios. To this end, we develop a novel hierarchical point sets learning architecture, with dynamic points agglomeration. By exploiting the relation of points in semantic space, a module based on graph convolution network is designed to learn a soft points cluster agglomeration. We construct a hierarchical architecture that gradually agglomerates points by stacking this learnable and lightweight module. In contrast to fixed points agglomeration strategy, our method can handle more diverse situations robustly and efficiently. Moreover, we propose a parameter sharing scheme for reducing memory usage and computational burden induced by the agglomeration module. Extensive experimental results on several point cloud analytic tasks, including classification and segmentation, well demonstrate the superior performance of our dynamic hierarchical learning framework over current state-of-the-art methods.
GENERATORS AND RELATIONS FOR SOERGEL BIMODULES

The monoidal category of Soergel bimodules is an incarnation of the Hecke category and plays a fundamental role in Kazhdan-Lusztig theory. We present this category by generators and relations, using the language of planar diagrammatics. We show that Libedinsky’s light leaves give a basis for morphism spaces and use this result to provide a new proof of Soergel’s classification of the indecomposable Soergel bimodules. PRELIMINARY VERSION. DO NOT DISTRIBUTE
PointAE: Point Auto-Encoder for 3D Statistical Shape and Texture Modelling

The outcome of standard statistical shape modelling is a vector space representation of objects. Any convex combination of vectors of a set of object class examples generates a real and valid example. In this paper, we propose a Point Auto-Encoder (PointAE) with skip-connection, attention blocks for 3D statistical shape modelling directly on 3D points. The proposed PointAE is able to refine the correspondence with a correspondence refinement block. The data with refined correspondence can be fed to the PointAE again and bootstrap the constructed statistical models. Instead of two seperate models, PointAE can simultaneously model the shape and texture variation. The extensive evaluation in three open-sourced datasets demonstrates that the proposed method achieves better performance in representation ability of the shape variations.
OTT_A_217935 7129..7137

Yanjun Shen* Huige Wang* Xiangmei Chen Wendong Li Jinglong Chen 1 1Department of Oncology, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, People’s Republic of China; 2Department of Gynecology, Wangjing Hospital of Chinese Academy of Chinese Medical, Beijing 100102, People’s Republic of China; 3Department of Pathology, Beijing Ditan Hospital, Capital Medical Uiversity, Beijing 100015, People’s Republic of China
A 5kW Three-Phase Buck+Boost Telecommunications Power Supply Module Input Stage Maintaining Unity Power Factor Under Failure of a Mains Phase

In this paper the reliable operation of a threephase three-switch buck-type PWM unity power factor rectifier with integrated boost output stage is investigated experimentally under heavily unbalanced mains, i.e. mains voltage unbalance, loss of one phase, short circuit of two phases or earth fault of one phase. The control scheme which allows to control the system for any mains condition without change-over of the control structure is described in detail. Furthermore, experimental results which confirm the proposed control concept for different mains failure conditions and for the transition from balanced mains to a failure condition and vice versa are shown and the behavior of the output voltage in case of a mains failure is investigated. Moreover, efficiency, power factor and total harmonic distortion of the rectifier system under a mains failure are analyzed. The experimental results are derived from a 5 kW prototype of the rectifier system (input voltage range (208 . . . 480) Vrms lineto-line, output voltage 400 V), where the control is realized by a 32-bit digital signal processor.
Machine learning methods for classification of the green infrastructure in city areas

Reducing green urban infrastructure pose a huge threat to cities sustainability. It is important to monitor and track the health of vegetation. For efficient planning of urban development and maintenance of green urban infrastructure, the key is to have up to date maps. Using satellite imagery is the easiest way to cover large city areas. In order to map vegetation, there are many possible solutions; however, the most effective way is using machine learning methods. Machine learning is divided into supervised and unsupervised classification and each can be divided into several different methods. Many authors have considered different methods and they use them to access accuracy on satellite image information extraction. They have used different satellite images and naturally higher resolution imagery results in better classification. However, there is still lack of comprehensive analysis of more supervised machine learning methods in similar cities. This paper aims to provide analysis of four different machine learning methods: support vector machine, artificial neural network, naïve Bayes and random forest. The objective of the support vector machine algorithm is to find a hyperplane in an N-dimensional space that distinctly classifies the data points where hyperplanes are decision boundaries that help to classify the data points and support vectors data points that are closer to the hyperplane and influence the position and orientation of the hyperplane. Artificial neural networks are brain-inspired systems which are intended to replicate the way that humans learn. Neural networks consist of input and output layers, and hidden layers. They are excellent tools for finding patterns which are far too complex or numerous for a human programmer to extract and teach the machine to recognize. A Naive Bayes classifier is a probabilistic machine learning model that is used for classification task and the crux of the classifier is based on the Bayes theorem. Random Forest creates a forest and makes it random and is an ensemble of Decision Trees, most of the time trained with the bagging method which general idea is that a combination of learning models increases the overall result. All of the mentioned methods will be tested on Sentinel-2A imagery. Sentinel-2A multispectral imager has thirteen sensors which is useful in vegetation extraction. Methods will be compared using error matrix and kappa statistics.
LncRNA AW112010 Promotes Mitochondrial Biogenesis and Hair Cell Survival: Implications for Age-Related Hearing Loss

Long noncoding RNA (lncRNA) disorder has been found in many kinds of age-associated diseases. However, the role of lncRNA in the development of age-related hearing loss (AHL) is still largely unknown. This study sought to uncover AHL-associated lncRNAs and the function. RNA-sequencing was conducted to profile lncRNA expression in the cochlea of an early-onset AHL mouse model. RT-qPCR assay was used to validate the expression pattern of lncRNAs. ATP assay, JC-1 assay, mitochondrial probe staining, CCK-8 assay, Western blot, and immunocytochemistry were performed to detect the effects of lncRNA AW112010 in HEI-OC1 cells and the mouse cochlea. We identified 88 significantly upregulated lncRNAs and 46 significantly downregulated lncRNAs in the cochlea of aged C57BL/6 mice. We focused on the significantly upregulated AW112010. Silencing of AW112010 decreased the ATP level, mitochondrial membrane potential, and cell viability and increased mitochondrial ROS generation under oxidative stress in HEI-OC1 cells. AW112010 overexpression promoted cell survival in HEI-OC1 cells. AW112010 knockdown reduced mitochondrial mass and impaired mitochondrial biogenesis in HEI-OC1 cells. Activation of mitochondrial biogenesis by resveratrol and STR1720 promoted cell survival. The mitochondrial biogenesis process was activated in the cochlea of aged mice. Moreover, AW112010 regulated AMPK signaling in HEI-OC1 cells. Transcription factor Arid5b elevated in the aged cochlea and induced AW112010 expression and mitochondrial biogenesis in HEI-OC1 cells. Taken together, lncRNAs are dysregulated with aging in the cochlea of C57BL/6 mice. The Arid5b/AW112010 signaling was induced in the aged mouse cochlea and positively modulated the mitochondrial biogenesis to maintain mitochondrial function.
Students’ Potential Abilities as Correlates of Self-Employment Start-Up Intentions: Evidence from Private Sector-Led Technical and Vocational Education Institutions in Nigeria

The current study examines the correlation between TVET students’ potential abilities and self-employment start-up intentions. The participants of the survey were 209 students of Nigerian TVET Institutions. Using a Bivariate Pearson Correlation Matrix and Simple Linear Regression tests of relationships, the results revealed a significant relationship between TVET students’ potential abilities and self-employment start-up intentions. More specifically, the results revealed significant correlations among communication and collaboration skills, critical thinking and problem solving skills, managerial and leadership skills, flexibility and adaptability skills, lifelong learning and self-direction skills and the intentions of TVET students to engage in self-employed business. Contrarily, the results show that there is no correlations between creative and innovative skills, ICT literacy and numeracy skills, social and cross-cultural skills, desirability and feasibility skills and the intentions of TVET students to engage in self-employed business upon graduation. Implications, limitations and logical conclusions were spotted out in the study. https://doi.org/10.26803/ijlter.18. 9.8
Modulation of the immune response to mycobacteria: implications on protection and pathology

Effective control of Mycobacterium tuberculosis infection requires the induction of inflammatory T helper (Th) 1 responses and avoidance of tissue damage. However, little is known about the mechanisms that rule the fine balance between protection and pathology in this infection. The anti-inflammatory cytokine IL-10 is important for the regulation of the immune response to several pathogens. However, despite the fact that elevated levels of IL-10 have been detected in tuberculosis patients, the role of IL-10 during M. tuberculosis infection is not clearly understood. In this study, we evaluated the impact of a transient over-expression of IL-10, during either the innate or the adaptive phases of the immune response, in the outcome of infection. For this, we used a novel animal model, the PMT-10 mice, which over-express IL-10 under the control of a zinc-inducible promoter. These transgenic animals were infected with M. tuberculosis, either via the intranasal or intravenous route and the expression of IL-10 was induced at different stages of the infection. Over-expression of IL-10 early after infection did not influence the capacity of PMT-10 mice to control bacterial growth, regardless the route of inoculation. In contrast, over-expression of IL10 during the chronic phase of infection caused significant effects in the progression of M. tuberculosis infection. Interestingly, whereas in intravenous infection, late IL-10 induction resulted in a transient increase in susceptibility of PMT-10 mice to M. tuberculosis, in intranasal infection, induction of IL-10 led to an increased resistance of PMT-10 mice that was maintained until the end of the experiment. However, no major differences were observed between induced and noninduced PMT-10 mice concerning the dynamic of cells or cytokine expression during infection that could explain the different outcomes observed. Although the cellular and molecular mechanisms underlying the differences observed remain unknown, altogether our data suggest that the impact of IL-10 expression during an infection with M. tuberculosis is variable. Indeed, we show for the first time that the timing of IL10 expression as well as the route of inoculation can determine the outcome of M. tuberculosis infection. Further understanding of our observations might be useful in the context of immunomodulatory strategies based on IL-10 expression or suppression.
Adopting a resilience lens to analyse adaptation to climate change on summer mountain pastures

Summer mountain pastures represent a key forage resource for many agropastoral farming systems, whose herds graze on these areas during summer. The extensive pastoral management of these areas enables to preserve both the forage value and the biodiversity of the vegetation. However, climate change threatens the fragile equilibrium of these complex socio-ecosystems, and existing analytical frameworks appear inadequate in this new context. In this paper we mobilise the concept of social ecological resilience in order to bring new keys to accompany adaptation to climate change on summer mountain pastures. Through this concept, we analyse the way diversity of vegetation is mobilized for adaptation at different management levels.
A pilot study to test the effectiveness of Education Queensland's

The study described in this article, uncovered the realities and expectations of computer use by Languages Other Than English (LOTE) teachers in language classrooms in state high and primary schools in metropolitan Brisbane. The expectations of LOTE teachers concerning computer use by teachers are listed as part of the Education Queensland initiative called 'Schooling 2001', implemented in 1997. This bold, generously funded three year project had, as one of its major goals, the improvement of computer technology skills and professional development in the teaching workforce. It had, as part of its blueprint, the stipulation that all teachers across the state of Queensland must have attained and applied the 'Minimum Standards' in technological competence by the end of the year 2001. This research was prompted by indications that the project's goals were not on target: that just one year before the project's deadline (2001), many teachers were still not using computers in the classrooms to achieve and extend curriculum goals. Consequently, it examined the attitudes of LOTE teachers in Brisbane towards language learning and computer technology to try to uncover the reasons why Computer Assisted Language Learning (CALL) was not being used in their language classrooms. The study revealed that, although the stipulations inherent in the 'Schooling 2001' project are straight forward and well articulated, there are many other complex factors which impact on and often impede a smooth transition to computer implementation by teachers. Studies such as this have much to offer researchers in dealing with understanding the many complex aspects surrounding computer use by teachers. Large amounts of financial resources given by government institutions as part of an education project, although necessary, are not adequate to ensure a successful adoption of computers by teachers in their classrooms, if proper mechanisms are not used continuously to monitor and support the successful implementation of such a project.