Miracle-dz/UniFAR-FTUs huggingface dataset:
Deposition of Boron Nitride Films from BB''B

The chemical vapor deposition of boron nitride from BB'B''-trichloroborazine was investigated in a microbalance equipment with a hot wall reactor. It was possible to monitor the evaporating and depositing masses simultaneously, so that the kinetics of the CVD-process could be measured in detail. The evaporation rate was studied in the temperature range between 285 and 330 K. The activation energy of the evaporation was determined to be 65 ± 2 kJ/mole. The deposition process was investigated at temperatures between 973 and 1233 K in an argon atmosphere at total pressures between 250 and 2000 Pa. The deposition of boron nitride on silicon could be described by a Langmuir reaction type. A gas phase decomposition of BB'B''-trichloroborazine was observed, so that the concentration at the substrate was dependent on the residence time of the precursor in the hot zone of the reactor. The deposited layers were colorless and amorphous and had the correct 1/1 stoichiometry between boron and nitrogen (WDX-Analysis). The layers contained less than 1 % of chlorine. SiC-Tyranno-fiber fabrics were coated homogeneously with BN-layers of 200-300 nm thickness. A tensile strength decrease of approximately 15 % was observed for the coated fibers. Oxidation experiments showed that the layers were oxidized at temperatures above 873 K in an Ar/O 2 -atmosphere leading to a brittle behavior of the fibers.
Energetics of particle collisions near dirty rotating extremal black holes: Banados-Silk-West effect versus Penrose process

If two particles collide near the horizon of a rotating extremal black hole, under certain conditions the energy E_{c.m. } in the center-of-mass frame can grow without limit (the so-called Banados-Silk-West effect). We consider collisions that produce two other particles. We show that for a generic dirty (surrounded by matter) black hole, there exist upper bounds on the energy and mass of product particles which can be detected at infinity. As a result, the positive energy gain is possible but is quite modest. It mainly depends on two numbers in which near-horizon behavior of the metric is encoded. The obtained results suggest astrophysical limits on the possibility of observation of the products of the collisional Banados-Silk-West effect. These results are consistent with recent calculations for the Kerr metric, extending them to generic dirty black holes. It is shown that for dirty black holes there are types of scenarios of energy extraction impossible in the Kerr case.
Digital WPI Major Qualifying Projects ( All Years ) Major Qualifying Projects April 2017 Control of a Bipedal Robot

In this project, we developed and modified the Anthropomorphic Robotic Movement System (ARMS) to allow for the simulation and implementation of low-energy walking, standing, and control. The robot underwent an in-depth analysis of its mechanical designs, including a retrofit of the cabling system, upgrades to the series elastics, and an implementation of a mechanical gravity compensation system using springs and variable radius pulleys. Additionally, the electrical system was completely overhauled with new microcontrollers and sensors to allow for better control of the robot. Finally, a new control schema with gravity compensation was implemented to allow for control of the robot. The combination of the mechanical, electrical, and control changes were evaluated via standing, leaning, and walking simulations and tests.
Housing and household wealth inequality: Evidence from the People's Republic of China

We examine the issue of the widening wealth inequality in the People’s Republic of China (PRC) from the perspective of housing. Using China Household Finance Survey (CHFS) data from 2011, we find that the PRC’s wealth inequality including housing is much larger than income inequality. Housing value appreciation, in particular, contributes to wealth inequality by allowing households to enjoy equity market premium through investing more in equity markets and taking a higher position in risky assets. JEL Classification: E44, O11, O15 ADBI Working Paper 671 Li, Li, and Ouyang
Scaffold Techniques and Designs in Tissue Engineering Functions and Purposes: A Review

In this review paper, the definition of the tissue engineering (TE) was comprehensively explored towards scaffold fabrication techniques and applications. Scaffold properties and features in TE, biological aspects, scaffold material composition, scaffold structural requirements, and old and current manufacturing technologies were reported and discussed. In almost all the reviewed reports, the TE definition denotes renewal, development, and repairs of damaged tissues caused by various factors such as disease, injury, or congenital disabilities. TE is multidisciplinary that combines biology, biochemistry, clinical medicine, and materials science whose application in cellular systems such as organ transplantation serves as a delivery vehicle for cells and drug. According to the previous literature and this review, the scaffold fabrication techniques can be classified into two main categories: conventional and modern techniques. These TE fabrication techniques are applied in the scaffold building which later on are used in tissue and organ structure. The benefits and drawbacks of each of the fabrication techniques have been described in conjunction with current areas of research devoted to deal with some of the challenges. To figure out, the highlighted aspects aimed to define the advancements and challenges that should be addressed in the scaffold design for tissue engineering. Additionally, this study provides an excellent review of original numerical approaches focused on mechanical characteristics that can be helpful in the scaffold design assessment in the analysis of scaffold parameters in tissue engineering.
Investigating the Structural Stability of the Phillips Curve Relationship

The reduced-form correlation between inflation and measures of real activity has changed substantially for the main developed economies over the post-WWII period. In this paper we attempt to describe the observed inflation dynamics in the United Kingdom, the United States and the euro area with a sequence of New Keynesian Phillips Curve (NKPC) equations that are log-linearised around different, non-zero, steady-state inflation levels. In doing this, we follow a two-step estimation strategy. First, we model the time variation in the relationship between inflation and a real cost-based measure of activity through a Markov-switching vector autoregressive model. We then impose the cross-equation restrictions of a Calvo pricing-based NKPC under non-zero steady-state inflation and estimate the structural parameters by minimising for each inflation state the distance between the restricted and unrestricted vector autoregressive parameters. The structural estimation results indicate that for all the economies there is evidence for a structurally invariant NKPC, albeit with a significant backward-looking component.
Ecology and morphological variability of Aulacoseira granulata (Bacillariophyceae) in Spanish reservoirs

The ecology of Aulacoseira (formerly Melosira) granulata and its different forms in ~30 reservoirs scattered throughout Spain has been analysed. Nutrient concentration explained a significant proportion of the variation in cell characteristics. In general, there is a tendency to find large cells with less densely areolated valves in nutrient-rich waters. Ecological differences between the type and its variety angustissima mainly concern calcium concentrations Aulacoseira granulata showed a unimodal response to the concentration of calcium, and preferred lower concentrations of calcium than the variety angustissima. The ecological differences between the a and -y forms (statuses) of A.granulata were also the object of our investigation. The y status occurred in all the reservoirs studied in summer, but in only 3 of 28 reservoirs studies in the overturn period. Light and turbulence explained the ecological differences observed between the two forms. The y status showed a certain preference for less turbulent waters compared with the a status, which is a more cosmopolitan form in its requirements.
A Comparison of Adult Children of Alcoholic Families with Adult Children From Non-Alcoholic Families on Depression, Self-Esteem, and Anxiety

The problem of this study was to test the differences between adult children from alcoholic families with adult children from non-alcoholic families on levels of depression, self-esteem, and anxiety. The sample consisted of 203 volunteers, all from the Counselor Education Department, 150 females and 53 males, ages 19 and older. Volunteers who were noted as being adult children of alcoholic families numbered 60. Measures used were the Children of Alcoholics Screening Test (CAST), the Beck Depression Inventory (BDI), the State-Trait Anxiety Inventory (STAI), and the Coopersmith Adult Self-Esteem Inventory (SEI). Multivariate Analysis of Variance was used to test for differences between groups. In addition, a secondary analysis using a one-way MANOVA was used to test for differences between dysfunctional and functional family of origin status on the dependent variables of depression, self-esteem, and anxiety.
SDF-MAN: SEMI-SUPERVISED DISPARITY FUSION

Refining raw disparity maps from different algorithms to exploit their complementary advantages is still challenging. Uncertainty estimation and complex disparity relationships among pixels limit the accuracy and robustness of existing methods and there is no standard method for fusion of different kinds of depth data. In this paper, we introduce a new method to fuse disparity maps from different sources, while incorporating supplementary information (intensity, gradient, etc.) into a refiner network to better refine raw disparity inputs. A discriminator network classifies disparities at different receptive fields and scales. Assuming a Markov Random Field for the refined disparity map produces better estimates of the true disparity distribution. Both fully supervised and semisupervised versions of the algorithm are proposed. The approach includes a more robust loss function to inpaint invalid disparity values and requires much less labeled data to train in the semi-supervised learning mode. The algorithm can be generalized to fuse depths from different kinds of depth sources. Experiments explored different fusion opportunities: stereo-monocular fusion, stereo-ToF fusion and stereo-stereo fusion. The experiments show the superiority of the proposed algorithm compared with the most recent algorithms on public synthetic datasets (Scene Flow, SYNTH3, our synthetic garden dataset ) and real datasets (Kitti2015 dataset and Trimbot2020 Garden dataset).
3 Task 1 : Early Detection of Signs of Depression 3 . 1

The 2018 CLEF eRisk is composed of two tasks: (1) early detection of signs of depression and (2) early detection of signs of anorexia. In this paper, we present the methods we developed when participating to these two tasks. We used two types of representations of the texts: one uses linguistic features and the other uses text vectorization. These representations are combined in different ways in models that are trained using a machine learning approach. These models are then used to built the 5 runs we submitted for task (1) and the 2 runs for task (2), which differences are also detailed in this paper. For task (1), best results were obtained when combining the methods based on features and text vectorization, and for task (2), the method based on text vectorization gives the best results.
Hydro-Muscle Actuated Exo-Legs for Therapy and Video Gaming

Ambulatory disabilities affects approximately 30.6 million people in the US over the age of 15 according to the 2010 US Census. Of these 30.6 million, about 10.8 million have the ability to walk a quarter mile continuously, but find it difficult doing so. The goals of this project were to design a device to be used therapeutically in order to help re-learn walking motions, to strengthen muscles, or to assist in everyday life. The device was also designed to be used with virtual reality (VR) systems to offer a source of physical input and feedback. To accomplish this task, our team built a wearable leg actuation assisting apparatus that outputs a minimum of ten percent of the average adult’s joint moments and is combinable to a VR system to fully engulf the user into a gaming environment.
Lambda-cyhalothrin efficiency on fruit borer control and quali-quantitative spraying aspects in a pinecone crop

In Brazil, the state of Bahia is one of the largest pinecone (Annona squamosa L.) growers; nevertheless, fruit borer (Cerconota anonella L.) presence limits production. This research aimed to test the efficiency of lambda-cyhalothrin in controlling fruit borer using different spray volumes; additionally, this research tested qualitative and quantitative operational aspects. Trials were carried out in pinecone orchards in Caraibas-BA, Brazil. Pesticide efficiency was tested by a randomized block experiment with six treatments and five replications. Treatments consisted of lambda-cyhalothrin application (1.5 g a.i. 100 L-1 water) with a surfactant (0.03% v v-1) at spray volumes of 100, 200, 268, 382 and 488 L ha-1 and one control (without spray). Pest infestation was assessed by counting symptomatic fruits for further percentage calculation. Five treatments with five replications were developed to evaluate spraying performance. These treatments consisted of an aqueous solution with a Brilliant Blue tracer at 0.15% (p v-1) and a surfactant at 0.03% (v v-1), using the same spray volumes as the first experiment. Qualitative assessments were performed on water-sensitive paper cards and were quantified through tracer deposit levels on leaves. Spray volumes between 100 and 382 L ha-1 with lambda-cyhalothrin were efficient to control Cerconota anonella in the pinecone crop, providing good quality application.
Empirical Mode Decomposition De-Noising Method Based on Improved Soft-Threshold

In this paper, an improved soft-threshold function is constructed, combined the improved function and empirical mode decomposition (EMD) methods, a new de-noising method has been proposed. Set the adaptive threshold for the intrinsic mode functions (IMFs) of the EMD, and then de-noise the each IMF respectively. Finally, the de-noised signal is reconstructed by the de-noised IMF components. Through the simulation results of quantitative analysis by signal-to-noise ratio (SNR) and mean square error (MSE), the algorithm in this paper has better de-noising effect. Also, this method can effectively improve the constant deviation between the original signal and the de-noised signal by traditional soft-threshold.
Creating an Interactive Visual Database of Piping Plovers (Charadrius melodus)

Piping plovers (Charadrius melodus) face many threats, substantially reducing their populations. Conservation strategies have included predator control and symbolic fencing, and complex records of plovers’ reproductive success have been kept for many beaches. In creating an interactive visual database with data from Massachusetts, the data becomes more comprehensible and conclusions can be drawn on the implications of conservation techniques. This information can be used to influence decisions about future conservation efforts at other breeding locations.
ROC Modelling Data of the Word Frequency Effect: A Formal Model of Visual Word Recognition

This article presents a formal statistical model for assessing the word frequency effect in recognition memory. This topic is relevant because word frequency is the best predictor of performance in recognition memory tasks. Signal Detection Theory was applied using high-frequency and low-frequency words as item-signals. Signal Detection Theory test assumes orthogonality of responses: hits, false alarms, correct rejections, and incorrect rejections. Ninety-six adult male and female students participated in two experiments: one conducted in the laboratory and the other in the class-room. The selected words for memory contained 3 to 5 letters and 1 or 2 syllables to control for length. Significant differences were found between high-frequency and low-frequency words in the number of false alarms for the two experiments. The differences were statistically significant in two experiments. The Cohen effect size was 0.6 and 0.45 respectively. The word frequency effect in first- and second-experiments was F (1, 46) = 4.13, MCE. = 2.34, p = 0.003 and F (1, 46) = 3.71, MCE. = 12.36, p = 0. 01 respectively. A formal model is presented based on the Receiver Operating Characteristic data to assess data trends for high- and low frequency words. Two differentiated models were obtained: a continuous model based on high frequency stimuli and a threshold model based on low frequency stimuli.
MOFs as porous hosts for generating singlet oxygen

We are investigating photoactive porous solids that produce single oxygen and oxidize adsorbed guest molecules in an effort to develop hetereogeneous catalytic materials for remediation of contaminated water sources. Toward that goal, we have synthesized porous metal-organic frameworks (MOFs) featuring photosensitizing porphyrins in the backbone of the MOF, investigated their structures, stabilities, and porous behavior, and demonstrated photolytic generation of singlet oxygen by monitoring oxidation of a model contaminant, 1,3-diphenylisobenzofuran, using spectroscopic and electrochemical methods. We have shown that immobilizing porphyrins in the backbone of MOFs inhibits photobleaching of the photosensitizer, thereby preventing degredation of the MOF and catalytic activity over time. We also have developed a strategy to seal the outer pores of MOFs as a means to trap adsorbed guests with MOFs.
Feasibility Study of SQp and SQs Attributes Application for Facies Classification

Formation evaluation is a critical requirement in oil and gas exploration and development projects. Although it may be costly, wireline logs need to be acquired to evaluate and understand the subsurface formation. Gamma ray and resistivity are the two main well-log data used for formation evaluation purposes. However, outside the well, formation evaluation becomes difficult, as these logs are not available. Hence, it is important to have other data equivalent to the gamma ray or resistivity logs, which can be derived from other technique, such as seismic data. As a consequence, the dependency on well-log data can be avoided. Thus, the complexity in formation evaluation outside the well, such as the determination of facies, lithology, and fluid content, as well as petrophysical properties can be solved accurately even without well-log data. The objective of this paper was to demonstrate an application of the SQp and SQs attributes for facies classification. These attributes were derived from attenuation attributes through rock physics approximation by using basic elastic properties: P-wave, S-wave, and density. A series of tests were carried out to show the applicability of these attributes on well-logs and real seismic data from offshore the Malaysia Peninsular. Simultaneous inversion was used in the data sets to produce the three-dimensional (3D) SQp and SQs attributes required as inputs of a neural network engine in defining the facies distribution. The results showed that the SQp attribute was very similar to the gamma ray, while the SQs attribute was similar to the resistivity responses even in different reservoir conditions, including low resistivity low contrast and coal masking environment. In conclusion, the SQp motif, which is similar to the gamma ray motif, can potentially be used for facies classification/identification. Together with the SQs attribute, the SQp attribute can be used as input for the facies classification workflow. The application of the SQp and SQs attributes successfully identified the gas sand distribution and separated it clearly from the brine distribution in an offshore Malaysian field.
Reduction of SOD Aggregation Using In Vitro and In Vivo ALS Models

ii ACKNOWLEDGEMENTS.iii LIST OF FIGURES.v INTRODUCTION.1 MATERIALS AND METHODS.5 UBE4B ASSAY RESULTS.10 MOUSE TRIAL RESULTS.21 DISCUSSION.25 REFERENCES.26 RESUME.31
Digital WPI Major Qualifying Projects ( All Years ) Major Qualifying Projects April 2018 Light Driven Actuators

Light is a clean form of energy. The ability to use light to cause mechanical motion is relatively a new area of research that can bring benefits such as remote control of actuators and micro-machines. Graphene is a 2D nanomaterial that has high mechanical strength, thermal conductivity, and broad optical absorption. Graphene nanoplatelets (GNPs) dispersed into a polymer not only improves mechanical strength and thermal conductivity but also enables highperformance photomechanical actuators. In this project, we dispersed (GNPs) into a Polydimethylsiloxane (PDMS) elastomer matrix to test the nanocomposite’s mechanical responses after being exposed to near-infrared light (NIR) in timed illumination cycles of on for 90 seconds and off for 50 seconds. Different concentration levels of GNP to PDMS (0.1-2 wt%) nanocomposites were made, and varying levels of pre-strain (3%-40%) were applied to each test sample before it underwent the illumination cycle. Highly stretched test samples showed reversible contraction while lowly stretched test samples showed reversible expansion.
Smart Lean Manufacturing in the Context of Industry 4.0: A Case Study

 Abstract — This paper introduces a framework to digitalize lean manufacturing tools to enhance smart lean-based manufacturing environments or Lean 4.0 manufacturing systems. The paper discusses the integration between lean tools and the powerful features of recent real-time data capturing systems with the help of Information and Communication Technologies (ICT) to develop an intelligent real-time monitoring and controlling system of production operations concerning lean targets. This integration is represented in the Lean 4.0 system called Dynamic Value Stream Mapping (DVSM). Moreover, the paper introduces the practice of Radio Frequency Identification (RFID) and ICT to smartly support lean tools and practices during daily production runs to keep the lean system alive and effective. This work introduces a practical description of how the lean method tools 5S, standardized work, and poka-yoke can be digitalized and smartly monitored and controlled through DVSM. A framework of the three tools has been discussed and put into practice in a German switchgear manufacturer.
Digital WPI Major Qualifying Projects ( All Years ) Major Qualifying Projects March 2014 Experimental Improvements to Regularity Clustering

Data clustering is an immensely powerful tool. The analysis of big data has led to many clustering techniques. Among these techniques is Regularity Clustering, a new technique based on Abel Prize winner Endre Szemerédi’s Regularity Lemma. Regularity Clustering has been shown to outperform industry standard clustering techniques in many circumstances. In this report we present new methods of executing Regularity Clustering. Among these methods one, which we call the most recurring construction method, outperforms the standard Regularity Clustering method by a significant margin. We also present empirical evidence indicating when Regularity Clustering performs well.