Machine learning-guided directed evolution for protein engineering

Machine learning (ML)-guided directed evolution is a new paradigm for biological design that enables optimization of complex functions. ML methods use data to predict how sequence maps to function without requiring a detailed model of the underlying physics or biological pathways. To demonstrate ML-guided directed evolution, we introduce the steps required to build ML sequence-function models and use them to guide engineering, making recommendations at each stage. This review covers basic concepts relevant to using ML for protein engineering as well as the current literature and applications of this new engineering paradigm. ML methods accelerate directed evolution by learning from information contained in all measured variants and using that information to select sequences that are likely to be improved. We then provide two case studies that demonstrate the ML-guided directed evolution process. We also look to future opportunities where ML will enable discovery of new protein functions and uncover the relationship between protein sequence and function.Comment: Made significant revisions to focus on aspects most relevant to applying machine learning to speed up directed evolutio

Pengaruh Kepemimpinan Transformasional terhadap Organizational Citizenship Behavior melalui Kepuasan Kerja sebagai Variabel Intervening pada PT Kapitan Prima Mandiri

Perilaku karyawan yang diharapkan oleh or­ga­ni­sa­­si tidak hanya perilaku in-role, tetapi juga pe­ri­la­ku extra-role. Kepemimpinan transformasional dan ke­puas­an kerja me­ru­pa­kan fak­tor yang mempe­nga­ruh­i munculnya perilaku lebih tersebut. Metode pene­litian yang digunakan adalah metode kuan­titatif, dan pengumpulan data menggunakan angket pene­li­ti­an ter­hadap karyawan tetap 60 orang. Teknik analisis da­ta yang di­gu­na­kan da­lam penelitian ini adalah Par­t­ial Least Squ­a­re (PLS) de­ngan ban­tuan program a­pli­kasi SmartPLS. Hasil penelitian menunjukkan bahwa terdapat pengaruh sig­nifikan antara ke­pemimpinan trans­formasional dan organi­za­ti­o­n­al citizenship beha­vi­or. Pe­­ngaruh signifikan kepemimpinan transformasional dan kepuasan ker­­ja. Pe­ngaruh sig­nifi­kan antara ke­pu­asan kerja dan organizational citi­zen­ship beh­a­vi­or. Ke­pu­as­an kerja tidak dapat menjadi variabel inter­ven­ing antara kepe­mim­pinan transformasional dan or­ganizational citizenship beha­vi­or

Structural characterization of a first-generation articulated-truss joint for space crane application

A first-generation space crane articulated-truss joint was statically and dynamically characterized in a configuration that approximated an operational environment. The articulated-truss joint was integrated into a test-bed for structural characterization. Static characterization was performed by applying known loads and measuring the corresponding deflections to obtain load-deflection curves. Dynamic characterization was performed using modal testing to experimentally determine the first six mode shapes, frequencies, and modal damping values. Static and dynamic characteristics were also determined for a reference truss that served as a characterization baseline. Load-deflection curves and experimental frequency response functions are presented for the reference truss and the articulated-truss joint mounted in the test-bed. The static and dynamic experimental results are compared with analytical predictions obtained from finite element analyses. Load-deflection response is also presented for one of the linear actuators used in the articulated-truss joint. Finally, an assessment is presented for the predictability of the truss hardware used in the reference truss and articulated-truss joint based upon hardware stiffness properties that were previously obtained during the Precision Segmented Reflector (PSR) Technology Development Program

Understanding Usage Patterns for Mobile Phone Excessive Dependence

The advancement of mobile technology has transformed a phone from a simple communication tool to a powerful device for entertainment, socialization and work. The proliferation of mobile apps further changed people’s way of living and working. However, more and more users experience excessive mobile phone dependence. The traditional method to identify dependence uses survey instruments and interview. However, this approach is labour intensive and hard to scale. To address the issue, this research-in-progress paper aims to identity users’ phone usage pattern and propose an unobtrusive way of diagnosing users’ mobile phone dependence. We have developed an app to track users’ phone usage and preliminary analysis was performed based on the data collected over more than 20 days. Users showed different usage patterns over weekends and weekdays, and social app usage is a more significant indicator for mobile phone excessive dependence than general phone usage. Planned future analysis and potential contributions are discussed