Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic analyses of hoof lesions in Canadian Holsteins using an alternative contemporary group

A key goal of dairy herds is to reduce the incidence of hoof lesions, which can be achieved both by improving management practices, and through genetic selection. Previous research has shown that data collected by hoof trimmers can be used for genetic evaluation of hoof health. Generally, not all cows in the herd are trimmed during the lactation and the pre-selection process for which cows are presented or not to the hoof trimmer needs to be considered. The objective of this study was to estimate genetic parameters for individual hoof lesions in Canadian Holsteins using an alternative contemporary group, in order to consider all cows in the herd during the period of the hoof trimming sessions, also those that were not examined by the trimmer over the entire lactation. Data were recorded by 26 hoof trimmers serving 365 herds located in Alberta, British Columbia and Ontario, and trained to use a rugged touch-screen computerized lesion recording system. A total of 108,032 hoof trimming sessions from 53,654 cows were collected between 2009 and 2012. Hoof lesions included in the analysis were digital dermatitis, interdigital dermatitis, interdigital hyperplasia, sole hemorrhage, sole ulcer, toe ulcer, and white line lesion. All variables were analyzed as binary traits, as the presence or the absence of the lesions. At first, only cows that were examined by the hoof trimmers were analyzed. Heritabilities (SE) for digital dermatitis, interdigital dermatitis, interdigital hyperplasia, sole hemorrhage, sole ulcer, toe ulcer, and white line lesion were 0.067 (0.007), 0.015 (0.003), 0.036 (0.005), 0.017 (0.003), 0.038 (0.006), 0.006 (0.002), and 0.017 (0.002), respectively. In a second step, cows without a record but present in the herd during the period of the hoof trimming sessions were included in the analyses, and a “no-lesions” label was assigned to all hoof traits for that trimming session. Heritabilities (SE) for digital dermatitis, interdigital dermatitis, interdigital hyperplasia, sole hemorrhage, sole ulcer, toe ulcer, and white line lesion were 0.053 (0.005), 0.011 (0.002), 0.025 (0.004), 0.012 (0.002), 0.031 (0.004), 0.004 (0.001), and 0.012 (0.002), respectively. Despite the low heritability, differences between daughter groups were observed based on the best and worst breeding values of the sires in both the groups. The pre-selection process, which leads cows to be trimmed or not during the lactation, did not affect the heritability and the breeding values estimation.
Gerakan Sosial Baru di Ruang Publik Virtual pada Kasus Satinah

Munculnya gerakan sosial baru di ranah ruang virtual merupakan kajian menarik setelah Rheingold (1993) mencoba merumuskan konsep masyarakat virtual. Gerakan sosial baru saat ini mulai masuk di ruang publik virtual sebagai ruang berbagi untuk publik. Artikel ini akan menganalisis seberapa jauh gerakan sosial baru memasuki ruang publik virtual khususnya pada kasus Satinah. Hasil kajian menunjukkan bahwa ruang virtual telah mampu menjadi ruang publik bagi masyarakat untuk mempertahankan diri serta melakukan perlawanan melalui aktivitas kolektif warga yang digerakkan oleh aktor-aktor tertentu.
An overview of the “new” emergency management

In the aftermath of 9/11 and the creation of the Department of Homeland Security, it is tempting to suggest that emergency management (EM) has attained a new level of significance in the national consciousness. Indeed, the emergence of the profession and the creation of FEMA itself owe much to the national defense mania of the Cold War era. But, if the past is any indication, the national security concerns that periodically increase public awareness and political attentiveness to EM do not result in a broad commitment of new resources to the array of natural and manmade disasters that threaten communities. Aside from the increased attention on immediate security threats, often without new resources being made available to local governments, the commitment to comprehensive disaster planning is generally lacking. It could even be suggested that the current focus on national security holds as much potential to distract the EM profession as it does to increase its operational scope, but the current security crisis could also be an opportunity to recast EM as a more strategic component in the local communities it serves.National security concerns aside, the EM profession is presently confronting the challenge to manage new realities. This requires expanding the role of the EM function beyond its traditional scope. The emergency manager requires new skills, and the profession must be identified with the emergency manager as a proactive public actor as much as it is with institutions and technical functions. This suggests that political and organizational analysis, strategic thinking, and leadership—concepts that have already been applied to all other public management functions—may be increasingly important concepts of study for emergency managers. What follows is a new conceptual framework for the EM profession as well as a basic organizational theme for its implementation. The limitations of the “old EM” must be overcome for the profession to advance to the “new EM,” which requires a broader, strategic, and more proactive orientation.
Winding loss optimization for boost inductor design

This paper summarizes geometrical effects on inductor winding loss based on a fixed diameter method and core gap effects. Relevant DC winding resistance equations of different winding configurations are derived and an effective inductor design method is given to the ratio of alternating to direct current $\displaystyle \frac{\triangle I}{I_{av}}$ =k1 and ratio of skin depth to wire radius $\displaystyle \frac{\delta}{r}$. The core gap effect on the ac winding resistance can be minimized by increasing the distance far away from the gap, however the DC winding resistance will increase. The optimal distance between centre leg of a ferrite core and inductor winding, h, results in the minimum total winding resistance, which is validated by test and ANSYS FEM modelling.
Speech Recognition of Multi-Syllable Words Using Soft Computing Techniques

The performance of the speech recognition mainly depends on uncertain factors such as speaker's conditions and environmental effects. The present study deals with the speech recognition of a number of multi-syllable isolated Korean words using soft computing techniques such as back-propagation neural network, fuzzy inference system, and fuzzy neural network. Feature patterns for the speech recognition are analyzed with 12th order thirty frames that are normalized by the linear predictive coding and Cepstrums. Using four models of speech recognizer, actual experiments for both single-speakers and multiple-speakers are conducted. Through this study, the recognizers of combined fuzzy logic and back-propagation neural network and fuzzy neural network show the better performance in identifying the speech recognition.
Development of the MedFit Application: a behaviour change theoretically informed cardiac rehabilitation intervention

Background: Cardiovascular disease (CVD) is the leading cause of premature death and disability in Europe. Cardiac Rehabilitation (CR) can reduce the impact of CVD by lowering mortality and morbidity rates and promoting healthy active lifestyles. Yet adherence within CR is low. Research suggests that mHealth interventions are useful in supporting the self-management of chronic disease. The overall purpose of this research is to facilitate the development of a specially designed Android App called MedFit, which aims to enhance the likelihood of people with established CVD self-managing their disease through participation in an exercise-based rehabilitation programme. Methods: For the intervention development, the preliminary stages of the Medical Research Council’s (MRC) formative process [i) development and ii) feasibility/piloting were used. This was achieved by conducting a systematic literature review, adhering to PRISMA guidelines, to identify what behaviour change techniques (BCTs) are used in physical activity eHealth interventions for adults with CVD (study 1). Study two involved testing the feasibility and acceptability of the prototype application using five focus groups (N=26 CVD patients; average age 64 ± 8.2 years; 65 % male). The focus group script was developed using a questionnaire (N=119 CVD patients; Appendix B.3) based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) which identified the constructs that were the primary concerns for end users. Focus groups were transcribed verbatim and in-depth content analysis was performed. Results: Twenty-three studies were included in the systematic literature review. The average number of BCTs employed in the studies was 7.2 (range 1-14). The top three most frequently used BCTs were information about health consequences (78.3%), goal setting (behaviour) (73.9%) and self-monitoring of behaviour (47.8%) (study 1). In study 2 the focus group usability feedback included; add in a retrieve password function, play the exercise video continuously and remove leaderboard function. Four key themes were identified following content analysis, these were; support, app as a mentor/guide, translation of activity from gym to home and technology knowledge gap. This feedback was translated into feasible technical improvements through close collaboration with the technical team. Conclusion: This research describes in detail the design process, first alpha-version of the App and focus group feedback used to develop a CVD mHealth intervention.
Klasifikasi Posting Twitter Kemacetan Lalu Lintas Kota Bandung Menggunakan Naive Bayesian Classification

Abstrak Setiap hari server Twitter menerima data tweet dengan jumlah yang sangat besar, dengan demikian, kita dapat melakukan data mining yang digunakan untuk tujuan tertentu. Salah satunya adalah untuk visualisasi kemacetan lalu lintas di sebuah kota. Naive bayes classifier adalah pendekatan yang mengacu pada teorema Bayes, dengan mengkombinasikan pengetahuan sebelumnya dengan pengetahuan baru. Sehingga merupakan salah satu algoritma klasifikasi yang sederhana namun memiliki akurasi tinggi. Untuk itu, dalam penelitian ini akan membuktikan kemampuan naive bayes classifier untuk mengklasifikasikan tweet yang berisi informasi dari kemacetan lalu lintas di Bandung. Dari hasil uji coba, aplikasi menunjukan bahwa nilai akurasi terkecil 78% dihasilkan pada pengujian dengan sampel sebanyak 100 dan menghasilkan nilai akurasi tinggi 91,60% pada pengujian dengan sampel sebanyak 13106. Hasil pengujian dengan perangkat lunak Rapid Miner 5.1 diperoleh nilai akurasi terkecil 72% dengan sampel sebanyak 100 dan nilai akurasi tertinggi 93,58% dengan sampel 13106 untuk metode naive bayesian classification. Sedangkan untuk metode support vector machine diperoleh nilai akurasi terkecil 92% dengan sampel sebanyak 100 dan nilai akurasi tertinggi 99,11% dengan sampel sebanyak 13106. Kata kunci — Twitter, tweet, klasifikasi, naive bayesian classification, support vector machine Abstract Every day the Twitter server receives data tweet with a very large number, thus, we can perform data mining to be used for specific purpose. One of which is for the visualization of traffic jam in a city. Naive bayes classifier is an approach that refers to the bayes theorem, is a combination of prior knowledge with new knowledge. So that is one of the classification algorithm is simple but has a high accuracy. With this, in this research will prove the ability naive bayes classifier to classify the tweet that contains information of traffic jam in Bandung. The testing result, the program shows that the smallest value of the accuracy is 78% on testing by using a sample 100 record and generate high accuracy is 91,60% on the testing by using a sample 13106 record. The testing results with Rapid Miner 5.1 software obtained the smallest value of the accuracy is 72% by using a sample 100 records and the high accuracy is 93.58% by using a sample 13.106 records for naive bayesian classification. And for the method of support vector machine obtained the smallest value is 92% accuracy by using a sample 100 records and the high accuracy of 99.11% by using a sample 13.106 records. Keywords —Twitter, tweet, classification, naive bayesian classification, support vector machine
2D and 3D thermally bioprinted human MCF-7 breast cancer cells: A promising model for drug discovery.

2605 Background: Breast cancer (BC) is the second leading cause of cancer death following lung cancer. Bioprinting, the use of computer aided process to print biological living and non-living material to create patterns in 2D or 3D structures, is a novel technique that has been proposed to be used to develop tissue engineered solutions for a wide array of clinical applications, e.g., skin grafting. We investigate here if bioprinted breast cancer cells show some of the hallmarks of cancer tissues, and thus may represent good in vitro models for drug discovery. Methods: For this study, MCF-7 BC cells were cultured, stained, counted and turned into a bioink solution by suspending in phosphate buffered saline solution. The cells were bioprinted over a 96-well plate and pre-incubated for 18 hours in DMEM and RPMI media with 10% Fetal Bovine Serum and Charcoal Stripped Serum, respectively. After 18 hours of incubation the media was supplemented with Tamoxifen at 5µM, 10µM, 50µM, 90µM and 110µM concentrations. Cytotoxicity was measured 24 hours post-treatment using a differential nuclear staining assay and an INCell 2000 bioimager system. Results: Bioprinted cells exposed to high concentrations of Tamoxifen (90 µM and 110µM) exhibited a viability of 8.2% and 10.8%, respectively. Whereas viability of manually seeded cells at those concentrations was 0.11% and 0.05%. Viability of negative and positive controls was at 7.6% and 97.0% for the bioprinted samples and for the normally seeded cells was 4.9% and 98.8% respectively. Conclusions: In our study, we have established a novel 2D/3D breast tumor model applying bioprinting technology for drug discovery. The higher cell viability of MCF-7’s at high concentrations of Tamoxifen could be attributed to the hormesis effect and activation of chaperone proteins, e.g., HSP70 and HSP90, possibly caused by bioprinting. We hypothesize that bioprinted MCF-7 cells also show increased levels of chaperone proteins, which may in a way mimic their in vivo behavior. In this novel in vitro 2D/3D model, the bioprinted cells show a more biological relevant behavior than normally cultured cells. Insights into the cell behavior after bioprinting may elucidate how to build improved in vitro models for BC research.
Design principles for research & development performance measurement systems: a systematic literature review

Goal: This paper aims to set the foundation on which a performance measurement system for the R&D function will be developed, assuming it not only as an organizational division, but also as a comprehensive process in order to better evaluate its efficiency and effectiveness. Design/Methodology/Approach: This paper adopts a Design Science Research strategy as its methodological basis. It focuses on bringing guidelines from the body of organizational theory of knowledge to design effective management solutions for an R&D performance measurement system. Results: A set of well-defined Design Principles to guide performance measurement system designs for R&D management. Limitations of the investigation: Even though the design principles have been systematically obtained from the literature review, there was no adequacy test of these principles in practical cases, which should be conducted in future research. Practical Implications: Managers and leaders of R&D teams may use theory-grounded guidelines to design their performance systems and to adjust such systems to their specific needs. Originality/ Value: The main practical contribution of the study findings is to provide a comprehensive set of guidelines to design a R&D Performance Measurement System, rather than proposing another new complete theoretical framework to add to the literature.
1GBDT, LR & Deep Learning for Turn-based Strategy Game AI

This paper proposes an AI fighting strategies generation approach implemented in the turn-based fighting game StoneAge 2 (SA2). Our research aim is to develop such AI for choosing the logical skills and targets to the player. The approach trained the logistical regression (LR) model and deep neural networks (DNN) model, individually. And combined both output at inference process. Meanwhile, to transform the features into a higher dimension binary vector without any manual intervention or any prior knowledge, we put all category features into Gradient Boosted Decision Tree (GBDT) before LR component. The main advantage of this procedure is the approach combines the benefits of LR models (memorization of feature interactions) and DL (generation the unseen feature combination through low-dimensional dense feature) for the AI fighting system. In our experiment, we evaluated our model with some other AI strategies (Reinforcement Learning (RL), GBDT, LR, DNN) to against a robot script. The results shown that the players, participating in the experiment, are capable of using reasonable strategic skills on the different targets. As a consequence, the win rate (versus with the robot script) of our system is higher than the others. Finally, we productionized and evaluated the system on SA 2, a commercial mobile turn-based game.
Research on the Storage Management of Wireless Sensor Networks Based on Query Algorithm

For the research of a query algorithm which is suitable for large-scale wireless sensor network should consider the energy consumption of nodes and the storage consumption of nodes. Through the simulation experiment of this algorithm can make the user adjust the merger rate according to the specific situation of network and the query, so as to ensure that the multiple queries in the processing are not affected by the limited cyber source.
ENCRYPTION METHOD USING PASCAL’S TRIANGLE BASED SUBSTITUTION AND SIERPINSKI TRIANGLE BASED PERMUTATION

Text messages are often created, shared and a person sends at least ten messages a day. Because of its frequent usage those messages are not been encrypted. Thus it is unable to send confidential messages via SMS service. In this paper, we develop a new encryption technique using the notions of Pascal‟s Triangle and Sierpinski Triangle. The proposed method uses the Pascal‟s triangle for substitution and Sierpinski triangle for permutation. The method is simple and easy to implement in real time. It is difficult for the attackers to predict the original message contained in the ciphertext. The proposed method is not much vulnerable to brute force and letter frequency attacks
Hydrocelectomy: experience with inguinal approach in the adult

The usual approach for hydrocelectomy in the adult is the scrotal route. The most troublesome problem following this method is a very discomforting scrotal swelling which creates much difficulty for the patient and the managing surgeon. This problem can be avoided by performing hydrocelectomy with a procedure using the inguinal approach in the adult. Apart from almost eliminating this post-operative problem of scrotal discomfort from marked swelling this method enables inspection, discovering of testicular malignancy and more safely taking appropriate actions on it. It also enables easy inspection, discovery and performance of appropriate actions on any co-existing inguinal hernia.
SIP Security Using Public Key Algorithms

The Session Initiation Protocol (SIP) is a simple pro toc l designed to enable the invitation of users to multimedia sessions. This document is a companion draf t to draft-ietf-mmusic-sip-04.txt, which defines SIP but doesn’t specify any security mechanisms other t han possible protection by lower-level security mechanisms such as SSL. This leaves SIP transactions vul erable to attack and this document aims to extend the SIP protocol to address such security consid erations. This document is a product of the Multiparty Multimedia S ession Control (MMUSIC) working group of the Internet Engineering Task Force Comments are so licited and should be addressed to the working group's mailing list at confctrl@isi.edu and/or the authors. Internet Draft SIP Security March 12th 1998 Kirstein et al. Page [2] Table of
Classification of acute pancreatitis—2012: revision of the Atlanta classification and definitions by international consensus

Background and objective The Atlanta classification of acute pancreatitis enabled standardised reporting of research and aided communication between clinicians. Deficiencies identified and improved understanding of the disease make a revision necessary. Methods A web-based consultation was undertaken in 2007 to ensure wide participation of pancreatologists. After an initial meeting, the Working Group sent a draft document to 11 national and international pancreatic associations. This working draft was forwarded to all members. Revisions were made in response to comments, and the web-based consultation was repeated three times. The final consensus was reviewed, and only statements based on published evidence were retained. Results The revised classification of acute pancreatitis identified two phases of the disease: early and late. Severity is classified as mild, moderate or severe. Mild acute pancreatitis, the most common form, has no organ failure, local or systemic complications and usually resolves in the first week. Moderately severe acute pancreatitis is defined by the presence of transient organ failure, local complications or exacerbation of co-morbid disease. Severe acute pancreatitis is defined by persistent organ failure, that is, organ failure >48 h. Local complications are peripancreatic fluid collections, pancreatic and peripancreatic necrosis (sterile or infected), pseudocyst and walled-off necrosis (sterile or infected). We present a standardised template for reporting CT images. Conclusions This international, web-based consensus provides clear definitions to classify acute pancreatitis using easily identified clinical and radiologic criteria. The wide consultation among pancreatologists to reach this consensus should encourage widespread adoption.
A New Improved Boosting for Imbalanced Data Classification

As one of the most important component of artificial intelligence, machine learning is getting more and more attention. AdaBoost, a classic machine learning algorithm, is widely used. However, when faced with imbalanced data classification, AdaBoost’s recognition rate of minority samples is low due to ignoring class imbalance. In many cases, minority samples are of high value. For this shortage, combining the theory of margin and cost-sensitive idea, a new Boosting algorithm called CMBoost is proposed based on cost-sensitive margin statistical characteristics, which is firstly through optimizing margin statistical characteristics to improve formal algorithm and then extended by cost-sensitive. Experimental results on the UCI dataset show that the CMBoost algorithm is superior to AdaBoost for imbalanced data classification problem.