Miracle-dz/UniFAR-FTUs huggingface dataset:
Parameter Optimization and Learning

The visual system of human beings can easily interpret 2D line drawings and perceive their 3D models . In order to emulate this visual ability by a computer, many algorithms have been proposed in the literature. The optimization-based algorithms are the most successful and popular methods in this field . These algorithms derive a 3D configuration from its 2D line drawing by minimizing an objective function , whose input variables are the missing depths of the vertices in the line drawing. The objective function is formulated as a weighted sum of several image regularities , each of which describes a rule that the optimal 3D configuration should satisfy as much as possible. In this way, the algorithms seek a reconstruction that best satisfies the regularities. Although the state of the art optimization-based 3D reconstruction algorithms can reconstruct a wide range of 3D objects, there is a serous problem with these algorithms , in which a large number of free parameters are set without optimization, causing distorted 3D objects often. In this thesis, we propose two approaches to solve the parameter setting and tuning problems. Firstly, the values of different image regularities span in very different ranges and their varying patterns during the optimization procedure are not well correlated, thus the traditional fixed regularity weights in the objective function would cause the problem that only the large value regularities dominate the optimization direction . We propose an adaptive parameter-setting strategy to handle this different regularity range problem. This adaptive strategy can be understood as a proper normalization method for the image regularities
Conducting Linear Growth Curve Analysis with the SA ! ! System

In longitudinal studies, the change in the response variable over time is often of interest. Linear growth curve analysis allows you to estimate the mean slope as a function of time. Analysis becomes more difficult when there is individual variation about the mean slope and repeated observations are not independent. The MIXED procedure in the SAS/STA-r soltware can model random effects which allows for individual variation. This procedure allows various models for the random effects component as well as for the error component. The method of generalized estimating equations (GEE) provides a robust covariance matrix even when the correlation structure of repeated observations is misspecrried. A SAS macro is available that applies GEE to longitudinal data analysis. The macro does not explicnly model random effects, but provides valid results when data actually contain random effects. This paper discusses how you can use either the MIXED procedure or the GEE macro to perform linear growth curve analysis. Various models were fit to simulated data to validate the correct model and examine effects of model misspecrrication.
Automatic Verification of Laparoscopic 3D Reconstructions with Stereo Cross-Validation

A n important task in computer-assisted laparosurgery is to automatically and densely reconstruct the surgical environment in 3D. The most successful approaches are Simultaneous Localization and Mapping (SLAM) and Structure-from-Motion (SfM). Nevertheless SLAM and SfM can both fail for several reasons. The ability to automatically and quickly detect reconstruction failures is therefore a crucial component in a robust system. We present stereoscopic cross-validation as the first solution for this task. This is designed for SfM reconstruction, works with calibrated stereo laparoscopes, and requires no additional sensors or interventional imaging.
Running title: A refined rat primary neonatal microglial culture method

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Differential Hepatic Gene Expression and Antioxidant Activity in Male and Female Rats Induced by Subchronic Aflatoxicosis B1

Aflatoxin B1 (AFB1) is the most toxic mycotoxin that was proven to be deleterious to human and several animal species. Current work aimed at evaluating the sex-based differential hepatic genotoxic effect and the antioxidant activity as implications of subchronic aﬂatoxicosis B1. Albino rats were used that comprised two equal AFB1treated groups with AFB1 contaminated olive oil (50µg/kg) and a control group for each gender that received the vehicle only. Parts of animals’ livers were homogenized for gene expression assessment using quantitative RT-PCR and antioxidant activity analyses. Caspase-3 immunohistopathological examination was concomitantly undertaken. Results showed that AFB1 induced signiﬁcant overexpression in cell cycle proliferation (ODC1), apoptosis (Aen), and antioxidant heme oxygenase (Hmox) genes in males alongside Bax (Bcl2- associated protein) under-expression. Meanwhile, female rats showed significant overexpression for (Hmox) and under-expression of Bax and Tnf (Tumor necrosis factor). Concomitant total hepatic antioxidant activity of liver homogenates showed a reduction in males, contrasting females. Degenerate vacuolated hepatocytes, polymorphic nuclei, cellular infiltration with concomitant Caspase-3 positive cells were profound findings in male rats. Hence, AFB1 is deferentially genotoxic at the given dose especially to male rats towards carcinogenicity, oxidative stress and apoptosis compared to a brief but compensated oxidative stress in females.
Establishing the reliability of test procedures in order to investigate the effect of penetrating trunk trauma and prolonged mechanical ventilation on the recovery of adult survivors

Gunshot wounds and/or stab wounds to the trunk are injuries commonly seen in South African hospitals. Such injuries often necessitate exploratory surgical intervention to identify and treat injuries to the internal organs. These patients are managed in the intensive care unit and often undergo prolonged mechanical ventilation with immobilization that often results in some degree of muscle dysfunction. In order to monitor the recovery of adult sur vivors over a 6-month period after hospital discharge, validation of the six-minute walk test and hand-held dynamometry between data collectors was necessary. Methods: Data was collected for the six-minute walk test and hand-held dynamometry by three data collectors. Subsequently a correlation coefficient (Pearson product moment correlate) was calculated and one-way analysis of variance (ANOVA) performed to assess the degree of association between the data. Results and Discussion: A strong positive correlation existed for data collected on the 6-minute walk test between data collectors 1, 2 and 3 with r ranging from 0.71 to 1 (p < 0.025 to p < 0.0005). The intra-class correlation (ICC) scores between data collectors ranged from 0.69 to 0.90 confirming this finding. A weak to fair correlation existed between data collectors for dynamometry measurements of the triceps and quadriceps muscles. Intra-class correlation scores ranged from 0.11 to 0.71. Conclusion: A strongly positive inter-observer correlation existed for data sets for the six-minute walk test. A weak intra-observer correlation existed for data sets collected by data collectors for dynamometry however this improved with intervention. The degree of association between data sets for dynamometry should be assessed again during the main study.
Progress Towards Bioelectrochemical Remediation of Hexavalent Chromium

Chromium is one of the most frequently used metal contaminants. Its hexavalent form Cr(VI), which is exploited in many industrial activities, is highly toxic, is water-soluble in the full pH range, and is a major threat to groundwater resources. Alongside traditional approaches to Cr(VI) treatment based on physical-chemical methods, technologies exploiting the ability of several microorganisms to reduce toxic and mobile Cr(VI) to the less toxic and stable Cr(III) form have been developed to improve the cost-effectiveness and sustainability of remediating hexavalent chromium-contaminated groundwater. Bioelectrochemical systems (BESs), principally investigated for wastewater treatment, may represent an innovative option for groundwater remediation. By using electrodes as virtually inexhaustible electron donors and acceptors to promote microbial oxidation-reduction reactions, in in situ remediation, BESs may offer the advantage of limited energy and chemicals requirements in comparison to other bioremediation technologies, which rely on external supplies of limiting inorganic nutrients and electron acceptors or donors to ensure proper conditions for microbial activity. Electron transfer is continuously promoted/controlled in terms of current or voltage application between the electrodes, close to which electrochemically active microorganisms are located. Therefore, this enhances the options of process real-time monitoring and control, which are often limited in in situ treatment schemes. This paper reviews research with BESs for treating chromium-contaminated wastewater, by focusing on the perspectives for Cr(VI) bioelectrochemical remediation and open research issues.
A Multisensory, Green, and Energy Efficient Housing Neuromarketing Method

Green products, clean energy, energy union, green buildings, eco-innovations, environment-related, and similar initiatives and policies have become very popular and widely applied all over the world. A pleasant built environment (parks, flowerbeds, beautiful buildings) and a repulsive environment (noise, polluted surroundings) influence a buyer’s outlook on an advertisement differently. An aesthetic, comfortable, and clean built environment evokes positive emotional states, not only at the time of housing selection and purchase but during the building’s life cycle as well. Potential housing buyers always feel comfortable in certain built environments, and they are inclined to spend more time there. The issues needing answers are how to measure the segmentation/physiological indicators (crowd composition by gender and age groups), as well as the emotional (happy, sad, angry, valence) and physiological (heart rate) states of potential homebuyers realistically, to produce an integrated evaluation of such data and offer buyers rational, green, and energy efficient housing alternatives. To achieve this purpose, the Multisensory, green and energy efficient housing neuromarketing method was developed to generate the necessary conditions. Here, around 200 million multisensory data recordings (emotional and physiological states) were accumulated, and the environmental air pollution (CO, NO2, PM10, volatile organic compounds) and noise pollution were investigated. Specific green and energy efficient building case studies appear in this article to demonstrate the developed method clearly. The obtained research results are in line with those from previous and current studies, which state that the interrelation of environmental responsiveness and age forms an inverse U and that an interest in green and energy efficient housing depends on age.
High Intensity Interval Training: Cardiorespiratory Adaptations, Metabolic and Performance

High Intensity Interval Training (IT) involves repeating maximum and/or supramaximal sprints for short and/or long periods (≥ 90 – 120% of the maximum oxygen consumption speed [vVO2max]; ≥ the Maximal Lactate Steady State [MLSS]) separated by recovery periods, which may be passive or by performing exercises in moderate intensity (passive and active pausing, respectively). However, such cardiorespiratory, metabolic, morphological, and performance adaptations depend on manipulating acute variables which guide the continuous training process, including volume, intensity, different times and types of recovery between series, and weekly training schedule. With this in mind, the study aimed to review and discuss various results investigating the effects of TI in cardiorespiratory, metabolic, and performance parameters in athletes and physically active individuals. The most relevant original scientific studies as of September, 2015, were analyzed, using the following databases: Science Citation, Index, Scopus, Sport Discus, The Scielo, and National Library of Medicine, combining the following keywords: endurance training, running training, recovery, repeated sprint, high intensity, speed endurance, interval training, anaerobic, and rest interval. It has been concluded literature has not clearly demonstrated the best combination of training variables, which allow for better efficiency in increasing cardiorespiratory, metabolic, and performance parameters. Most studies have showing effort intensity, when close to maximum cardiorespiratory capacity, results in increased stress and, therefore, greater cardiorespiratory and metabolic adaptations.
EVALUATION OF ANTI-ULCER EFFECTS OF ETHANOLIC EXTRACT OF DELONIX REGIA FLOWER

Ulcer is one of the most common disorder in the world. The available antiulcer drug in the market have different side effect. So the people move to herbal drug for a better result and lesser side effect. Delonix regia is a plant from the family leguminosae is extensively available in the word. The earlier researcher found that the plant contain the chemical constitutent like tannin, saponin, flavonoid, so it have a good antioxident property. So, this study is planned recurred the antiulcer activity by ethanolic extract of the different doses (100mg/kg, 200mg,kg & 400mg/kg) of the flower of Delonix regia (EEDRF) on ethanol induced ulcer model in experimental rat whereas lansoprazole (8mg/kg) was taken as an standard drug. It has been found that the extract shows significant antiulcer activity in a dose dependent manner. The protection of ulcer may due to the presence of antioxidant principles present in the plant.
Национален универзитет Гјеонгсанг, Кореја MEASURING SELF-ESTEEM OF DEAF/HARD OF HEARING COLLEGE STUDENTS

Ова истражување ги проучува имплицитното и експлицитното самопочитување кај глувите и наглувите студенти, со триест и шест субјекти на возраст од 18 до 21 година (возраст ± СД, 19.4±0.9). Во продложение се дадени резултатите од ова истражување: исто како и студентите што слушаат, глувите/наглувите студенти имаат значаен ефект на имплицитното самопочитување; ниту една од набљудуваните корелации со експлицитното почитување не е значајна ниту за атрибутивниот тест за имплицитни асоцијации (IAT Implicit Association Test) ниту за афективниот IAT; имплицитното самопочитување е повисоко кај испитаниците од машки пол отколку кај испитаниците од женски пол; не постојат значајни корелации помеѓу имплицитното самопочитување и нивото на депресија. Социјалните споредби, негативните оценки и однесувањето на другите секогаш се со тенденција да му наштетат на експлицитното самопочитување кај глувите/наглувите студенти. Сепак, сѐ уште постои позитивно карактеризирање на однесувањето кон себе во нивната претстава за себе. This study examines Deaf/hard of hearing college students' implicit and explicit selfesteem, with thirty-six 18 to 21 year old (Age ± SD, 19.4±0.9) subjects. Following are the results of this study: Just as hearing students, Deaf/hard of hearing students also have significant implicit self-esteem effect; none of the observed correlations with explicit esteem is significant for either attributive IAT or the affective IAT; Implicit self-esteem of males is higher than that of females; No significant correlation exists between implicit self-esteem and the level of depression. Social comparisons and negative evaluations and attitudes of others always tend to damage explicit self-esteem of Deaf/hard of hearing students. However, positive self-attitude characterizations still exist in their self-schema.
Parity and metabolic syndrome in middle-aged Iranian women: a cross-sectional study

Introduction: The hormonal changes that happen during pregnancy may have effects on weight, blood pressure, dyslipidaemia, and possibly metabolic syndrome. The aim of this study was to determine the association between parity and metabolic syndrome in middle-aged women in Babol, Iran. Methods: A total number of 800 women, with the age range of 30 to 50, were selected through a systematic random sampling method and sampling propionate to size from Babol. The metabolic syndrome was diagnosed based on the criteria set by the National Cholesterol Education Program (NCEP) III. The individuals' socio-demographic characteristics, the number of live births, pregnancies, lifestyles, current physical activity, and dietary factors were assessed. Logistic regression was used to determine the independent association between parity and the prevalence of metabolic syndrome. Results: The data were obtained from 633 participants (79.1%). The women, who reported a history of gravidity or parity, had a mean score of 2.4 ± 1.0. One hundred and ten (110, 17.4%) women had less than two parities and 523(82.6%) had two or more parties. Women who developed metabolic syndrome were more likely to have a higher parity at the time of interview (p= 0.001). Women with ≥ 2 parity had significantly higher odds of metabolic syndrome (OR= 1.91, 95% CI= 1.08-3.37). In addition, logistic regression analyses were then performed to assess the association of parity with each component of the metabolic syndrome. The women with ≥ 2 parity were significantly more likely to have abdominal obesity (p= 0.010). Conclusion: Higher parity or gravidity was associated with higher prevalence of metabolic syndrome in middle-aged women. Health policy makers should work with health providers to reduce the risk of metabolic syndrome in middle-aged multipar women.
Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding

Intelligence Quotient (IQ) Test is a set of standardized questions designed to evaluate human intelligence. Verbal comprehension questions appear very frequently in IQ tests, which measure human's verbal ability including the understanding of the words with multiple senses, the synonyms and antonyms, and the analogies among words. In this work, we explore whether such tests can be solved automatically by artificial intelligence technologies, especially the deep learning technologies that are recently developed and successfully applied in a number of fields. However, we found that the task was quite challenging, and simply applying existing technologies (e.g., word embedding) could not achieve a good performance, mainly due to the multiple senses of words and the complex relations among words. To tackle these challenges, we propose a novel framework consisting of three components. First, we build a classifier to recognize the specific type of a verbal question (e.g., analogy, classification, synonym, or antonym). Second, we obtain distributed representations of words and relations by leveraging a novel word embedding method that considers the multi-sense nature of words and the relational knowledge among words (or their senses) contained in dictionaries. Third, for each type of questions, we propose a specific solver based on the obtained distributed word representations and relation representations. Experimental results have shown that the proposed framework can not only outperform existing methods for solving verbal comprehension questions but also exceed the average performance of the Amazon Mechanical Turk workers involved in the study. The results indicate that with appropriate uses of the deep learning technologies we might be a further step closer to the human intelligence.
PRESERVATION OF RAW COW MILK USING NON THERMAL TREATMENTS

This study was undertaken to evaluate the feasibility of using non thermal treatments for the preservation of raw cow milk. Samples of cow milk were incubated at 4oC as a control (C), heat treated at 80 oC for 10min (HT), activated LP-system (LPs), added soluble chitosan (CH, 0.1%), β-glucan (BG, 30mg/L) or glucomannan (GM, 30mg/L). All treated samples were incubated at 25oC, 37oC or 45oC. Ttitratable acidity (T.A%), milk stability, rennet coagulation time, starter activity, total aerobic mesophilic bacterial count (TBC), spore forming bacterial count (SC), coliform (CC) and mould & yeast (M.Y) in all samples were determined during incubation. A significant slowing down in the rate of increase in T.A% was found in all samples. Shelf-life of raw milk was of 19, 13, 12, 11, and 10 hr, during incubation at 25 oC for samples treated with HT, CH, LP, BG, and GM, respectively, with the same acidity (0.195%) in all samples. The clot on boiling and alchol stability tests of all samples are o0f the same trend of titratable acidity. The starter activity decreased significantly by adding CH, BG, GM and LPs. However HT as well as control treatments had a significant higher starter activity than other treatments. On the other side, all treatments reduced significantly rennet coagulation time, except LPs and HT treatments, which delayed coagulation time. Results showed no significant differences between all samples for TBC at the different incubation temperatures. Spore count in HT and CH treatments was significantly less than other treatments. Moreover, HT treatments had the lowest count for coliform, and M&Y. Coliform count was significantly lower by adding BG than other treatments.
Regularising Deep Networks with Deep Generative Models

We develop a new method for regularising neural networks. We learn a probability distribution over the activations of all layers of the model and then insert imputed values into the network during training. We obtain a posterior for an arbitrary subset of activations conditioned on the remainder. This is a generalisation of data augmentation to the hidden layers of a network, and a form of data-aware dropout. We demonstrate that our training method leads to higher test accuracy and lower test-set cross-entropy for neural networks trained on CIFAR-10 and SVHN compared to standard regularisation baselines: our approach leads to networks with better calibrated uncertainty over the class posteriors all the while delivering greater test-set accuracy.