BehaviorDEPOT: a tool for automated behavior classification and analysis in rodents

Quantitative descriptions of animal behavior are essential to understand the underlying neural substrates. Fear conditioning in rodents is a widely used assay that allows neuroscientists to probe the neural mechanisms of memory. To date, quantification of freezing behavior, a proxy for fear memory strength, is usually performed by hand or with expensive and inflexible commercial software. To overcome these barriers, we developed BehaviorDEPOT (DEcoding behavior based on POsitional Tracking), a MATLAB-based application containing six independent modules. The Experiment Module runs fear conditioning experiments using an Arduino-based design that interfaces with commercial hardware. The Analysis Module classifies freezing and analyzes spatiotemporal behavioral statistics in user-defined ways. The remaining modules can develop custom classifiers. Of note, the Inter-Rater Module establishes reliable ground-truth human labels, making it broadly useful for scientists developing classifiers with any application. BehaviorDEPOT provides a simple, flexible, automated pipeline to move from pose tracking to reliably quantifying task-relevant behaviors.

Pengembangan modul praktikum berbasis inkuiri terbimbing pada peserta didik kelas XI MIA di SMAN 5 Makassar (Studi pada Materi Pokok Larutan Penyangga)

Penelitian ini merupakan penelitian pengembangan (research and development) yang bertujuan untuk menghasilkan modul praktikum berbasis inkuiri terbimbing yang bersifat valid, praktis dan efektif. Pengembangan modul praktikum ini mengacu pada model pengembangan 4-D oleh thiagarajan yang meliputi tahap pendefinisian (define), perancangan (design), pengembangan (develop), dan penyebarluasan (disseminate). Modul praktikum ini telah melalui tahap validasi oleh validator ahli dan telah melalui uji coba terbatas, serta mengalami revisi oleh pengembang sehingga menghasilkan modul praktikum yang bersifat valid, praktis dan efektif. Hasil penelitian pengembangan modul praktikum ini adalah : 1) penilaian kevalidan ahli materi sebesar 3,65 dengan kategori sangat valid, hasil penilaian tampilan modul sebesar 3,68 juga memperoleh kategori sangat valid. 2) respon peserta didik dan guru juga memperoleh 83,14% dan 88,98% dengan kategori sangat tinggi sehingga modul praktikum dikatakan praktis; 3) pada tahap uji coba terbatas kepada 32 peserta didik kelas XI MIA di SMAN 5 Makassar memperoleh masing-masing rata-rata 87,50% yang berada pada kategori tinggi, sehingga modul praktikum dikatakan efektif. Kesimpulan dari penelitian ini adalah modul praktikum berbasis inkuiri terbimbing yang dikembangkan dengan model 4D bersifat valid, praktis dan efektif untuk digunakan dalam pembelajaran. Kata kunci: Modul praktikum, Inkuiri terbimbing, Larutan penyangga ABSTRACT This study was a research and development that aimed to develop a experiment module based on guided inquiry which valid, effective, and practic. The development of this experiment module reffered development model of 4-D by thiagarajan that included are define, design, develop and disseminate of phases. This experiment module has validated by expert, and had been tried limitedly, and revised by order to obtain avalid, practical and effective experiment module. The result of this study were: 1) Validation of the validity of the material expert was 3.65 with a very valid category, the module display evaluation was 3.68 which very valid category; 2) students and teachers responses received 83,14% and 88.98% which very high category, so experiment module could be said practical; 3) in phase of tried limitedly to 32 students of class XI MIA SMAN 5 Makassar obtained the average score of students learning result was 87,50% which was high category. Experiment module could be said effective. The conclusion of this research was experiment module based on guided inquiry developed by 4D model was valid, practical, and effective to use on learning. Keywords: Experiment module, Buffer solution, Guided inquiry

Intelligent system for interactive online education based on cloud big data analytics

Based on the big data cloud computing platform with online teaching at the application scenario, the functional modules of the system are divided according to the user’s functional requirements for the system, and the system is briefly designed to determine the system architecture. The core functional modules of the system include an online experiment module, online classroom module, video course module, online examination module and basic function module. Using software engineering methods, the design process of the above functional modules is described, and the realization process of key functions is elaborated in detail. Taking into account the security requirements for video transmission in the video course module, the streaming media on-demand technology based on the RTMP protocol is adopted. In order to meet the highly interactive requirements of the online classroom module, the rich Internet application development technology based on Flex4.0 is adopted. A distributed Docker cluster is used in the online experiment module to provide students with an experimental environment. Taking into account the future business growth of the system and the need for dynamic expansion, the load balancing technology based on Nginx reverse proxy is adopted. In the test phase, the black box test method was used to test the system’s functions, and the system was non-functionally tested on three aspects of compatibility, security, and system performance. The online teaching platform is designed in this article not only has basic function modules, but also starts from the safety performance of the system. When designing the system module, a safety function module is added, and the user data are encrypted using the MD5 algorithm, and through access control technology and system backup Ensure data security. This article combines the convenience of online learning with the practicality of computer courses to create a set of one-stop teaching platforms with rich functions entered on online experiments. The system has good support for the key links in the teaching process, and can effectively improve the learning efficiency of students and the teaching efficiency of teachers.

Investigation of Corrosion Rate of Mild Steel in Fruit Juice Environment Using Factorial Experimental Design

Although little attention is paid to corrosion study in food processing and production industry, it is highly important to take a critical look at what transpires at the production stages and how these can affect human health due to contamination of the final product. This research employs the design of experiment module of a Minitab software to analyze the corrosion effect of mild steel in fruit juice environment. Coupon method was adopted to calculate the rate of corrosion in orange, pineapple, and cashew fluid for a duration of 25 days with measurement taken at 5-day intervals. The highest corrosion rate of 0.71 mmpy was observed in cashew fluid followed by pineapple fluid, and the least rate of 0.08 mmpy was observed in orange fluid. The generalized model equation was obtained to predict corrosion rate of mild steel in a similar environment. In general, design of experiment offers a better way to analyze corrosion experiment result, and this innovative idea is shown in this work.