Penggunaan Technology Acceptance Model Dalam Mengukur Kualitas Layanan Platform E-Commerce

Seiring dengan meningkatnya pertumbuhan ecommerce di Indonesia, ternyata jumlah pengaduan akan ketidakpuasan konsumen terhadap layanan ecommerce pun meningkat setiap tahunnya. Penelitian ini bertujuan menganalisis kualitas layanan ecommerce dalam meningkatkan kepuasan konsumen dengan technology acceptance model. Platform yang dianalisis dalam penelitian ini adalah Tokopedia dengan menggunakan bagan quality function deployment. Hasil analisis menunjukkan bahwa tingkat kepuasan konsumen masih berada di bawah tingkat harapan konsumen. Sistem yang user friendly, user interface yang simpel dan jelas, otomatisasi fitur saran, sistem pembayaran yang terintegrasi, dan membuat kolom pencarian terlihat jelas merupakan lima prioritas karakteristik teknis yang harus menjadi perhatian perusahaan karena sesuai dengan kebutuhan konsumen. Penelitian ini menyarankan kepada Tokopedia untuk melakukan evaluasi dan perbaikan secara berkala serta melakukan testing aplikasi secara rutin sehingga dapat meminimalisir terjadinya error dan bug. Tokopedia juga perlu lebih tanggap dengan keluhan pelanggan dan pihak pengembang bisa lebih update dalam menangani keluhan yang berkaitan dengan error dan ketidakstabilan aplikasi. Kata kunci: E-commerce, Kualitas Pelayanan, Technology Acceptance Model, Quality Function Deployment.

Developing Culturally Effective Strategies for Chinese to English Geotourism Translation by Corpus-Based Interdisciplinary Translation Analysis

As a new field of translation with its own special genre, geotourism has not yet been firmly established because geotourism translations are currently not of a sufficient professional standard. This situation does not provide geotourists with the genre’s full target of enjoyment, learning and engagement through science popularisation tourism activities. In order to better meet these three definitive purposes in geotourism, this study analyses the three basic categories of geotourism—geological features (GFs), geological processes (GPs) and cultural elements (CEs)—to determine effective strategies of geotourism translation from Chinese into English. Challenges in translation include scientific jargon, language style and cultural gaps. In this article, the advantages of Hu’s Eco-translatology theory are explained and used for minimising translation problems; and the corpus linguistics method, superior for quantitative and qualitative analysis, is utilised. As well, digital auxiliary tools Tmxmall (2014) and Sketch Engine (2003) were employed to facilitate corpus research. Through analysis, effective strategies in each of the key geotourism categories, GFs, GPs and CEs, were identified, shaped and recommended for future translators’ attention. In the results, literal translation, transliteration and free translation, addition and use of official UNESCO names were recommended to render GFs. Division and shift translation, literal translation and shift and division were recommended for GPs. Literal translation, transliteration and free translation and addition were recommended for CEs. Since this is an initial investigation in the genre of geotourism, this study has attempted to build a model platform for future study and wider research in geotourism translation and translation pedagogy for the improvement of geotourism translation quality.

943 3D in vitro tumor model platform rapidly assays immunotherapy efficacy with high content imaging and downstream phenotypic changes with flow cytometry and cytokine analysis

BackgroundCancer immunotherapy represents a burgeoning new direction for oncology therapeutic innovation, with the principal thesis of activating one’s own immune system to irradicate cancer as opposed to the injection of foreign cytotoxic agents like chemotherapy. The first generation of checkpoint inhibitors unleash cytotoxic T cells to locate and kill their tumor target, however, only a small subset of patients (e.g. ~30% of NSCLC patients1) respond favorably. In order to advance the next generation of immunotherapy to the clinic, we critically need models which more accurately represent the immunosuppressive tumor microenvironment (TME).MethodsHere, we describe a novel 3D in vitro tumor model platform which engineers the tumor, stromal, and immune cell compartments of the TME in an extracellular matrix hydrogel (VersaGel2) and a high throughput 96-well format. The system has been extensively tested across multiple solid tumor indications, such as colorectal, lung, pancreatic, breast, and others. Specifically for this study, we utilized NSCLC PDX cells from the Charles River compendium and cocultured with human dermal fibroblasts (HDF) and PBMCs to study the effects of checkpoint inhibitor monoclonal antibodies, Pembrolizumab (anti-PD1) and Atezolizumab (anti-PDL1), on T cell infiltration and T cell-mediated killing using high content imaging. Supernatants were analyzed for cytokines and the 3D models were subsequently digested for flow cytometry.ResultsThe 3D models demonstrated varying degrees of T cell infiltration and killing capacity across PDX in a dose-dependent manner to checkpoint inhibitors, and the inclusion of fibroblasts played a critical role in further modulating response. Moreover, the data revealed clinically-relevant levels of CD3+, CD4+, and CD8+ T cell subpopulations and cytokine secretions such as IFN-gamma.ConclusionsThese data suggest a novel 3D model platform for assaying immunotherapeutic efficacy as well as its mechanism of action in the context of the TME. Future studies will include applying this novel platform to additional tumor models and screening multiple forms of immunotherapy – such as small molecules, biologics, and cell and gene therapy – in drug discovery, preclinical testing, and precision medicine.ReferencesHaslam A, Prasad V. Estimation of the percentage of US patients with cancer who are eligible for and respond to checkpoint inhibitor immunotherapy drugs. JAMA Netw 2019;2(5):e192535.Hribar KC, Wheeler CJ, Bazarov A, Varshneya K, Yamada R, Buckley P, Patil CG. A simple three-dimensional hydrogel platform enables ex vivo cell culture of patient and PDX tumors for assaying their response to clinically relevant therapies. Mol Canc Ther 2019;18(3):718–725.

A runtime alterable epidemic model with genetic drift, waning immunity and vaccinations

We present methods for building a Java Runtime-Alterable-Model Platform (RAMP) of complex dynamical systems. We illustrate our methods by building a multivariant SEIR (epidemic) RAMP. Underlying our RAMP is an individual-based model that includes adaptive contact rates, pathogen genetic drift, waning and cross-immunity. Besides allowing parameter values, process descriptions and scriptable runtime drivers to be easily modified during simulations, our RAMP can used within R-Studio and other computational platforms. Process descriptions that can be runtime altered within our SEIR RAMP include pathogen variant-dependent host shedding, environmental persistence, host transmission and within-host pathogen mutation and replication. They also include adaptive social distancing and adaptive application of vaccination rates and variant-valency of vaccines. We present simulation results using parameter values and process descriptions relevant to the current COVID-19 pandemic. Our results suggest that if waning immunity outpaces vaccination rates, then vaccination rollouts may fail to contain the most transmissible variants, particularly if vaccine valencies are not adapted to deal with escape mutations. Our SEIR RAMP is designed for easy use by others. More generally, our RAMP concept facilitates construction of highly flexible complex systems models of all types, which can then be easily shared as stand-alone application programs.

Developing a Decision Support System for Water Resources Dispatching

Contradiction between water demand and water supply have a huge impact on social and economic development. This paper presents the development of a water resources dispatch decision support system. The system integrates models related to water dispatch such as streamflow forecast model, water allocation model and water dispatch model. Each model runs as an independent service and is registered in the model platform. The model platform interacts with the service layer and data layer through the model adapter. The model adapter is designed for converting the model input data sent by the service layer and the basic data and observation data queried by the data layer into the format required by the model. In case study, we took the Fu River Basin as an example to demonstrate an application of the system. The system realizes the complete process of data collection, streamflow forecast, water demand declaration, water distribution and water dispatch. User can get the recommended operation plan of the reservoir and the corresponding water supply result through the user interface. Process variables can also be viewed through the system, such as streamflow forecast results and water distribution results, etc. The proposed system can provide technical support and assistance for the decision makers, which also provide an effective demonstration for water resources management in other rivers.

Thermally active nanoparticle clusters enslaved by engineered domain wall traps

The stable assembly of fluctuating nanoparticle clusters on a surface represents a technological challenge of widespread interest for both fundamental and applied research. Here we demonstrate a technique to stably confine in two dimensions clusters of interacting nanoparticles via size-tunable, virtual magnetic traps. We use cylindrical Bloch walls arranged to form a triangular lattice of ferromagnetic domains within an epitaxially grown ferrite garnet film. At each domain, the magnetic stray field generates an effective harmonic potential with a field tunable stiffness. The experiments are combined with theory to show that the magnetic confinement is effectively harmonic and pairwise interactions are of dipolar nature, leading to central, strictly repulsive forces. For clusters of magnetic nanoparticles, the stationary collective states arise from the competition between repulsion, confinement and the tendency to fill the central potential well. Using a numerical simulation model as a quantitative map between the experiments and theory we explore the field-induced crystallization process for larger clusters and unveil the existence of three different dynamical regimes. The present method provides a model platform for investigations of the collective phenomena emerging when strongly confined nanoparticle clusters are forced to move in an idealized, harmonic-like potential.

Biofabrication of advanced in vitro and ex vivo cancer models for disease modeling and drug screening

Bioengineered in vitro models have advanced from 2D cultures and simple 3D cell aggregates to more complex organoids and organ-on-a-chip platforms. This shift has been substantial in cancer research; while simple systems remain in use, multi-tissue type tumor and tissue chips and patient-derived tumor organoids have grown rapidly. These more advanced models offer new tools to cancer researchers based on human tumor physiology and the potential for interactions with nontumor tissue physiology while avoiding critical differences between human and animal biology. In this focused review, the authors discuss the importance of organoid and organ-on-a-chip platforms, with a particular focus on modeling cancer, to highlight oncology-focused in vitro model platform technologies that improve upon the simple 2D cultures and 3D spheroid models of the past.

Chlorpyrifos Disrupts Acetylcholine Metabolism Across Model Blood-Brain Barrier

Despite the significant progress in both scientific understanding and regulations, the safety of agricultural pesticides continues to be called into question. The need for complementary analytics to identify dysregulation events associated with chemical exposure and leverage this information to predict biological responses remains. Here, we present a platform that combines a model organ-on-chip neurovascular unit (NVU) with targeted mass spectrometry (MS) and electrochemical analysis to assess the impact of organophosphate (OP) exposure on blood-brain barrier (BBB) function. Using the NVU to simulate exposure, an escalating dose of the organophosphate chlorpyrifos (CPF) was administered. With up to 10 μM, neither CPF nor its metabolites were detected across the BBB (limit of quantitation 0.1 µM). At 30 µM CPF and above, targeted MS detected the main urinary metabolite, trichloropyridinol (TCP), across the BBB (0.025 µM) and no other metabolites. In the vascular chamber where CPF was directly applied, two primary metabolites of CPF, TCP and diethylthiophosphate (DETP), were both detected (0.1–5.7 µM). In a second experiment, a constant dose of 10 µM CPF was administered to the NVU, and though neither CPF nor its metabolites were detected across the BBB after 24 h, electrochemical analysis detected increases in acetylcholine levels on both sides of the BBB (up to 24.8 ± 3.4 µM) and these levels remained high over the course of treatment. In the vascular chamber where CPF was directly applied, only TCP was detected (ranging from 0.06 μM at 2 h to 0.19 μM at 24 h). These results provide chemical evidence of the substantial disruption induced by this widely used commercial pesticide. This work reinforces previously observed OP metabolism and mechanisms of impact, validates the use of the NVU for OP toxicology testing, and provides a model platform for analyzing these organotypic systems.

A Spatial Quantitative Systems Pharmacology Platform spQSP-IO for Simulations of Tumor—Immune Interactions and Effects of Checkpoint Inhibitor Immunotherapy

Quantitative systems pharmacology (QSP) models have become increasingly common in fundamental mechanistic studies and drug discovery in both academic and industrial environments. With imaging techniques widely adopted and other spatial quantification of tumor such as spatial transcriptomics gaining traction, it is crucial that these data reflecting tumor spatial heterogeneity be utilized to inform the QSP models to enhance their predictive power. We developed a hybrid computational model platform, spQSP-IO, to extend QSP models of immuno-oncology with spatially resolved agent-based models (ABM), combining their powers to track whole patient-scale dynamics and recapitulate the emergent spatial heterogeneity in the tumor. Using a model of non-small-cell lung cancer developed based on this platform, we studied the role of the tumor microenvironment and cancer–immune cell interactions in tumor development and applied anti-PD-1 treatment to virtual patients and studied how the spatial distribution of cells changes during tumor growth in response to the immune checkpoint inhibition treatment. Using parameter sensitivity analysis and biomarker analysis, we are able to identify mechanisms and pretreatment measurements correlated with treatment efficacy. By incorporating spatial data that highlight both heterogeneity in tumors and variability among individual patients, spQSP-IO models can extend the QSP framework and further advance virtual clinical trials.