Miracle-dz/UniFAR-FTUs huggingface dataset:
A Micro Particle Image Velocimetry System for Velocity Field Measurement in a Microchip Droplet-Forming Flow

A micro particle image velocimetry (microPIV) system incorporating a trigger device that enables the repeat measurement of velocity fields around droplets generated in microfluidics has been developed. The system includes a microscope, a double-pulse laser system, a trigger system and a double shutter camera. Water droplets are generated in a continuous oil phase within a polydimethylsiloxane microchip using a co-flow focusing method. Fluorescent particles are incorporated into the oil phase as seeding particles, and the oil and water are pumped into the microchip through microbore tubes. As a droplet travels through a detection zone and passes the trigger point, the microPIV imaging system takes double images of the droplet. These double images are subsequently used in calculating the field using a double-frame crosscorrelation function and in-house software. The system significantly increases the calculation quality by using the average of 100 sets of the double PIV images.
Case-Based Story Generation through Story Amalgamation

Computational narrative explores techniques through which computers can analyze, understand and, most importantly, generate stories. This paper explores a CBR approach to story generation based on the idea of story amalgamation: given a target partial description to the story we want the system to generate, the system will retrieve a set of full stories (represented as cases), and then reuse them by merging them in a way that the result satisfies the target partial description. This story merging is performed via a formal operation we call an amalgam. We report on a preliminary study showing the potential of the approach.
Deep Learning for Orca Call Type Identification - A Fully Unsupervised Approach

Call type classification is an important instrument in bioacoustic research investigating group-specific vocal repertoire, behavioral patterns, and cultures of different animal groups. There is a growing need using robust machine-based techniques to replace human classification due to its advantages in handling large datasets, delivering consistent results, removing perceptualbased classification, and minimizing human errors. The current work is the first adopting a two-stage fully unsupervised approach on previous machine-segmented orca data to identify orca sound types using deep learning together with one of the largest bioacoustic datasets – the Orchive. The proposed methods include: (1) unsupervised feature learning using an undercomplete ResNet18-autoencoder trained on machineannotated data, and (2) spectral clustering utilizing compressed orca feature representations. An existing human-labeled orca dataset was clustered, including 514 signals distributed over 12 classes. This two-stage fully unsupervised approach is an initial study to (1) examine machine-generated clusters against human-identified orca call type classes, (2) compare supervised call type classification versus unsupervised call type clustering, and (3) verify the general feasibility of a completely unsupervised approach based on machine-labeled orca data resulting in a major progress within the research field of animal linguistics, by deriving a much deeper understanding and facilitating totally new insights and opportunities.
The Guidance Effects of Students with Internet Addiction in Taiwan

Aims: The aim of this study was to understand the individual guidance effects of internet addiction for elementary and junior school students. The guidance effects included variability of Internet access, Internet addiction, and depression after guidance. Methods: We trained 17 college students of the Health Psychology Department in Chang Jung Christian University, Taiwan, in counseling and guidance lectures for 12 hours and supervision sessions for 20 hours, then the college students gave guidance with 18 students of Internet addiction tendency (age: 9 -14 years old, each one had 3-8 sessions) in Taiwan. Participants’ scores of Chen Internet Addiction Scale (CIAS) (Chen, Weng, & Su, 2003) were more than 63 (which were Ko’s (2005) definition of Internet addiction CAIS scale scores that were more than 63 would have more tendency to have Internet addiction). We administered the pre-test (December, 2010) and posttest (September, 2011) with 18 Internet addiction tendency students by structured questionnaire including, Internet Access, Depression Scale, and CIAS after 4 months of guidance. Finally, we collected 14 copies. We used paired t-test to analysis data. Results: The total scores of the Depression Scale were not significant in pre-test and posttest. But depression-dysphoric mood, hopelessness, low self-esteem and cognition function in the dimension of depression had significantly decreased. CIAS total scores and the individual score in each dimension, including compulsive use, withdrawal, tolerance, problems of interpersonal relationships, and health /time management, had significant relationships between pre-test and post-test. Conclusions: Results show Internet addiction behavior could be helped by guidance with college students who have been trained and supervised.
How Statistical Learning Can Play Well with Universal Grammar

One motivation for Universal Grammar (UG) is that it allows children to acquire the linguistic knowledge that they do as quickly as they do from the data that’s available to them. A key legacy of Chomsky’s work in language acquisition is highlighting the separation between children’s hypothesis space of possible representations (typically defined by UG) and how children might navigate that hypothesis space (sometimes defined by UG). While statistical learning is sometimes thought to be at odds with UG, I review how statistical learning can both complement UG and help us refine our ideas about the contents of UG. I first review some cognitivelyplausible statistical learning mechanisms that can operate over a predefined hypothesis space, like those UG creates. I then review two sets of examples: (i) those where statistical learning allows more efficient navigation through a UG-defined hypothesis space, and (ii) those where statistical learning can replace prior UG proposals for navigating a hypothesis space, and in turn
Yogurt: microbiology, organoleptic properties and probiotic potential

The purpose of this chapter is to provide an overview of the nature of bacterial associations in yogurts, describe the interactions among the bacteria involved, and detail how bacterial metabolic activities impact the properties of the end product. We will focus on traditional yogurts; yogurts or fermented milk products that contain probiotic species (such as Bifidobacterium or Lactobacillus spp.), stabilizers, added aromas, or other additives will not be discussed.
Fast Large-Scale Trajectory Clustering

In this paper, we study the problem of large-scale trajectory data clustering, k -paths, which aims to efficiently identify k "representative" paths in a road network. Unlike traditional clustering approaches that require multiple data-dependent hyperparameters, k -paths can be used for visual exploration in applications such as traffic monitoring, public transit planning, and site selection. By combining map matching with an efficient intermediate representation of trajectories and a novel edge-based distance (EBD) measure, we present a scalable clustering method to solve k -paths. Experiments verify that we can cluster millions of taxi trajectories in less than one minute, achieving improvements of up to two orders of magnitude over state-of-the-art solutions that solve similar trajectory clustering problems.
FPGA Based Implementation of Digital PID Controller for a Motion Control of DC Motor Miss .

The main aim of this project is to design digital PID control algorithms using field programmable gate array (FPGA) technology for speed control of the motor. Implementation of digital controllers in embedded environment suffers from many problems like analog-digital signals interfacing, therefore control algorithms have limitations. This paper presents a technique for implementation of FPGA based digital ProportionalIntegral-Derivative (PID) controller for the motion control of a permanent magnet DC motor. The hardware implementation has been done on a Xilinx Spartan 3 FPGA chip. This technique is used for the generation of control input as a PWM signal for controlling motor driver circuit and then decoding the optical encoder data for using it to the speed feedback in the PID control loop.
EFFECTS OF FOCUS ON DURATION AND INTENSITY IN CHONGMING CHINESE

Prosodic focus is generally realised by expanded pitch range, lengthened duration and increased intensity on the focused components, while the postfocus components may be associated with a compressed pitch range and intensity, which is referred to as post-focus compression (PFC). However, controversy surrounds whether PFC exists cross-linguistically, and detailed studies on how focus influences duration and intensity are scarce. This study aims to contribute novel data to the prosodic typology literature by examining the effects of focus on duration and intensity in Chongming Chinese (CC). Twenty target words were embedded under different focus conditions, and the production data were submitted for linear-mixed effects models. Our results showed focus-induced change of duration and intensity (i.e., lengthened duration and a larger intensity range under focus) as well as PFC of duration and intensity range in CC.
Limited receptive area neural classifier for texture recognition of mechanically treated metal surfaces

The limited receptive area (LIRA) neural classifier is proposed for texture recognition of mechanically treated metal surfaces. It may be applied in systems that have to recognize position and orientation of complex work pieces during micromechanical device assembly as well as in surface quality inspection systems. The performance of the proposed classifier was tested on a specially created image database with four texture types corresponding to metal surfaces after milling, polishing with sandpaper, turning with lathe and polishing with file. The promising recognition rate of 99.8% was obtained. r 2007 Elsevier B.V. All rights reserved.
anostructured interfaces with site-specific bioreceptors for mmunosensing elmo

In this work, we propose a simple and effective approach to build nanostructured immunosensor platforms. The one-step strategy relies on i) the in situ formation of dithiocarbamates from the reaction between carbon disulfide and amine groups, present on protein A, ii) their attachment to gold nanoparticles (AuNPs), and iii) the linkage of the modified AuNPs to the electrode surface, which depends on the strong interaction between gold substrates and sulfur moieties. AuNPs and protein A are used to increase the surface coverage of Immunoglobulin G (IgG) and promote the oriented immobilization of the antibodies on the immunosensing interface. The modified gold surfaces with biomolecules were thoroughly characterized by a combination of techniques: UV–vis spectrophotometry, conventional ellipsometry and atomic force microscopy. The immunosensor performance was assessed in real-time, by surface plasmon resonance and by the highly sensitive total internal reflection imaging ellipsometry, through the specific biorecognition between anti-IgG and the immobilized IgG molecules. We demonstrate that the presence otal internal reflection imaging llipsometry of AuNPs improves the sensitivity of the anti-IgG specific detection, whereas the presence of co-adsorbed CS2 is responsible for blocking the undesired protein nonspecific adsorption to the gold substrate. Overall, we report a simple and innovative one-step method, to chemically modify gold surfaces with protein A and AuNPs, able to specifically detect antigen/antibody interactions with capability of preventing protein nonspecific adsorption. © 2017 Elsevier B.V. All rights reserved.
Internal tides a ff ect benthic community structure in an energetic submarine canyon o ff SW Taiwan

Submarine canyons are major conduits of terrestrial and shelf organic matter, potentially benefiting the seafloor communities in the food-deprived deep sea; however, strong bottom currents driven by internal tides and the potentially frequent turbidity currents triggered by storm surges, river flooding, and earthquakes may negatively impact the benthos. In this study, we investigated the upper Gaoping Submarine Canyon (GPSC), a highsediment-yield canyon connected to a small mountain river (SMR) off southwest (SW) Taiwan. By contrasting the benthic meiofaunal and macrofaunal communities within and outside the GPSC, we examined how food supplies and disturbance influenced the benthic community assemblages. The benthic communities in the upper GPSC were mainly a nested subset of the adjacent slope assemblages. Several meiofaunal (e.g. ostracods) and macrofaunal taxa (e.g. peracarid crustaceans and mollusks) that typically occurred on the slope were lost from the canyon. The polychaete families switched from diverse feeding guilds on the slope to motile subsurface deposit feeders dominant in the canyon. The diminishing of epibenthic peracarids and proliferation of deep burrowing polychaetes in the GPSC resulted in macrofauna occurring largely within deeper sediment horizons in the canyon than on the slope. The densities and numbers of taxa were depressed with distinct and more variable composition in the canyon than on the adjacent slope. Both the densities and numbers of taxa were negatively influenced by internal tide flushing and positively influenced by food availability; however, the internal tides also negatively influenced the food supplies. While the meiofauna and macrofauna densities were both depressed by the extreme physical conditions in the GPSC, only the macrofaunal densities increased with depth in the canyon, presumably related to increased frequency and intensity of disturbance toward the canyon head. The population densities of meiofauna, on the other hand, rebounded more rapidly due to their fast growth rate and short generation time and thus did not display bathymetric pattern in the canyon. To our knowledge, this is the first benthic ecological study in a submarine canyon connected to a highsediment-yield SMR. The biological responses to extreme physical conditions in the GPSC could have broad implications on understanding the anthropogenic and climate change impacts in the deep-sea ecosystems.
Quality Control of Healthcare Systems A general research

This paper targets the fact that with rising global population, there is a strong need to improve healthcare system to tackle new diseases and more number of patients efficiently and effectively. This requires proper management, especially Quality Management.Based on research, healthcare quality control needs to be improved and primarily focused on costs savings. Research is limited to various reviews, published papers, published articles by various authors and various organizations. This article gives an insight to students or anyone who wishes to learn more about the quality control in healthcare industry. The paper shows the various elements that impact the final outcome of quality control as a process in this sector. Keywords—Quality , Healthcare, Cost
Acoustic Indicators of Deception in Mandarin Daily Conversations Recorded from an Interactive Game

Being able to distinguish the differences between deceptive and truthful statements in a dialogue is an important skill in daily life. Extensive studies on the acoustic features of deceptive English speech have been reported, but such research in Mandarin is relatively scarce. We constructed a Mandarin deception database of daily dialogues from native speakers in Taiwan. College students were recruited to participate in a game in which they were encouraged to lie and convince their opponents of experiences that they did not have. After data collection, acoustic-prosodic features were extracted. The statistics of these features were calculated so that the differences between truthful and deceptive sentences, both as they were intended and perceived, can be compared. Results indicate that different people tend to use different acoustic features when telling a lie; the participants could be put into 10 categories in a dendrogram, with an exception of 31 people from whom no acoustic indicators for deception were found. Without considering interpersonal differences, our best classifier reached an F1 score of 53.37% in distinguishing deceptive and truthful segmentation units. We hope to present this new database as a corpus for future studies on deception in Mandarin conversations.
An Overview of Wireless Power Transmission ( WPT )

it is imperative to note that in our daily life electricity is an essential factor as it contributes largely to the success of activities; this has led to a greater demand for electricity transmission which happens to be the most essential component of any control system. It also has its setback as there is always a fraction of loss during transmission and as such it is important to have an efficient transmission of power; this has given rise to the wireless power transfer system. Regardless of the technological concerns, wireless power transfer system in its capacity will expunge the use of wires or cables by providing individuals the option of re-charging the dead batteries of devices effortlessly in the same manner as using a wireless communicator. A concise report and evaluation on the several methods of wireless power transmission is shown and discusses the advantages and disadvantages as well as the analysis and comparison of each method. Keywordscomponents; Wireless power transmission; Magnetic resonant; Radio frequency radiation; Inductive coupling
MULTIMODAL PERCEPTION OF PRAISING AND BLAMING MANDARIN SPEECH BETWEEN THE INTERLOCUTORS WITH FRIENDLY OR HOSTILE RELATIONSHIPS

This work investigated the role of multimodality and relationship between interlocutors in perception of Mandarin praising and blaming attitudes. The perceptual experiment found that the differences of accuracy between praising and blaming attitude were larger in friendly relationship than that in hostile. Moreover, praising attitude was identified better in audio channel than that in visual channel, while blaming attitude was discriminated more in visual channel than that in audio channel. This suggests that the hostile relationship between interlocutors was conveyed mainly by facial expression, either in praising or blaming speech.
Time-Specific Metalearners for the Early Prediction of Sepsis

Motivation: Accounting for complex clinical dynamics in sepsis patients while aiming at an automated analysis of hourly (non-)validated data is challenging. The algorithm has to deal with imprecise, incorrect and incomplete data in addition to being time aware.Methods: We aimed to build time-specific stacked ensembles and a non-specific XGBoost learner to predict sepsis 6 hours prior to the sepsis onset. The models were trained on a triple split of 40,336 ICU stays taken from the training sets of the 2019 PhysioNet/CinC Challenge. Data was cleaned and features were built based on rolling windows including several clinical scores and criteria, such as shock index, qSOFA, SOFA, SIRS, NEWS, cNEWS. Model performance was evaluated using task-specific utility functions. Furthermore, variable importance was assessed.Results and conclusion: Although no official score was obtained in the Challenge as team Sepsis2G, we found normalized utility score of 0.394 for our non-specific XG-Boost model on a held out subset of the training data. The threshold selection was displaced in time-specific meta-learners leading to an inferior performance. Most important variables included the assumed presence of ventilation, white blood cell count, partial thromboplastin time, blood urea nitrogen and rolling quantiles of the temperature. Partial SOFA-scores, cNEWS, and the shock index showed major importance in the ICU admission phase.
Specific regulation of permeability during leukocyte TEM by RhoGEFs and GAPs

Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva. nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.
Cocoa Farming and Difficulties in Adopting the Innovations of Intensive Agriculture in Boguedia (Ivory Coast)

The Ivorian economy is essentially based on agriculture, especially the coffee-cocoa duo. The country experienced growth in the 1970s, perceived by specialists as the "Ivorian miracle". But this euphoria turned into "an economic mirage", because of certain factors including the aging of plants, the slowdown in cocoa production. Faced with this situation, strategies are being developed by the National Center for Agronomic Research to significantly improve productivity. But they meet resistance. The objective of this research is to analyze cocoa farming and the difficulties related to the adoption of agricultural innovations. To achieve this, we selected Boguedia, a town located in Upper Sassandra, a field of investigation, because of intensive agriculture. This socio-anthropological research is both qualitative and quantitative. It is based on techniques (observation, focus group, registers) and data collection tools (interview guide, questionnaire). The research describes cocoa farming and shows its socio-economic value. It also analyzes the causes of the resistance of Boguedia populations to agricultural innovations. This situation of discomfort needs a critical analysis of the agricultural innovation policy.
ON THE EVIDENTIAL VALUE OF SCHOOL PSYCHOLOGY INTERVENTION RESEARCH

research and its utility and applicability for school-based practitioners. Nevertheless, American Psychological Association and National Association of School Psychologists training and practice standards specify that practitioners should demonstrate skills to apply research findings as a foundation for service delivery regardless of their level of training, and the responsibility to acquire and apply accurate knowledge about effective practices are considered to be an epistemic responsibility of the clinician (e.g., O’Donahue & Henderson, 1999). As stated by Lilienfeld et al. (2012), “all school psychologists, regardless of the setting in which they operate, need to develop and maintain a skill set that allows them to distinguish evidence-based from non-evidence based practices” (p. 8) and this notion is a foundational principle of the broader evidence-based practice movement. ON THE EVIDENTIAL VALUE OF SCHOOL PSYCHOLOGY INTERVENTION RESEARCH