Longitudinal Time Scales Research Articles

How Does COVID-19 Impact the Supply Chain Management of the E-Commerce Industry in Indonesia?

COVID-19 had created a major shift in how conventional, brick-to-mortar, and any business in general to operate. With the changes occurring in the business industry, several factors are required for organizations to survive with the sudden change. One of the key elements is to implement the use of digital technology. With the ever growing phenomena of digitalization, implementing these matter becomes a necessity especially amid pandemic. In correspondence to the adaptation of the business sector, a growing industry has shed light during this age, which is e-commerce. Being a platform that is based electronically through the internet, the usage of e-commerce has grown significantly, especially in one of the world’s most overlooked e-commerce market, Indonesia. Being the biggest user of e-commerce in South East Asia, Indonesia has the potential to utilize this business sector to its fullest. The impact of the pandemic will directly impact the e-commerce businesses in Indonesia through its supply chain management sector. With the concurrent growth of digitalization and the regulations of COVID-19 in Indonesia, the supply chain management has the ability to improve its work processes by implementing digital technology. With the many variables of digital technology, implementing it to the functions of supply chain management will differ from business to business. This research will dissect the different utilization of digital technology in the supply chain management of e-commerce businesses in Indonesia. It will also investigate the impact that COVID-19 has on the e-commerce businesses in Indonesia. This research will utilize a descriptive design framework with a longitudinal time scale. It will consist both quantitative and qualitative data through only secondary method of research.

A systematic review and Bayesian meta-analysis of the development of turn taking in adult-child vocal interactions.

Fluent conversation requires temporal organization between conversational exchanges. By performing a systematic review and Bayesian multi-level meta-analysis, we map the trajectory of infants' turn-taking abilities over the course of early development (0 to 70months). We synthesize the evidence from 26studies (78 estimates from 429 unique infants, of which at least 152 are female) reporting response latencies in infant-adult dyadic interactions. The data were collected between 1975 and 2019, exclusively in North America and Europe. Infants took on average circa 1s to respond, and the evidence of changes in response over time was inconclusive. Infants' response latencies are related to those of their adult conversational partners: an increase of 1s in adult response latency (e.g., 400 to 1400ms) would be related to an increase of over 1s in infant response latency (from 600 to 1857ms). These results highlight the dynamic reciprocity involved in the temporal organization of turn-taking. Based on these results, we provide recommendations for future avenues of enquiry: studies should analyze how turn-by-turn exchanges develop on a longitudinal timescale, with rich assessment of infants' linguistic and social development.

PhyLoSTM: a novel deep learning model on disease prediction from longitudinal microbiome data.

Research shows that human microbiome is highly dynamic on longitudinal timescales, changing dynamically with diet, or due to medical interventions. In this article, we propose a novel deep learning framework 'phyLoSTM', using a combination of Convolutional Neural Networks and Long Short Term Memory Networks (LSTM) for feature extraction and analysis of temporal dependency in longitudinal microbiome sequencing data along with host's environmental factors for disease prediction. Additional novelty in terms of handling variable timepoints in subjects through LSTMs, as well as, weight balancing between imbalanced cases and controls is proposed. We simulated 100 datasets across multiple time points for model testing. To demonstrate the model's effectiveness, we also implemented this novel method into two real longitudinal human microbiome studies: (i) DIABIMMUNE three country cohort with food allergy outcomes (Milk, Egg, Peanut and Overall) and (ii) DiGiulio study with preterm delivery as outcome. Extensive analysis and comparison of our approach yields encouraging performance with an AUC of 0.897 (increased by 5%) on simulated studies and AUCs of 0.762 (increased by 19%) and 0.713 (increased by 8%) on the two real longitudinal microbiome studies respectively, as compared to the next best performing method, Random Forest. The proposed methodology improves predictive accuracy on longitudinal human microbiome studies containing spatially correlated data, and evaluates the change of microbiome composition contributing to outcome prediction. https://github.com/divya031090/phyLoSTM. Supplementary data are available at Bioinformatics online.

A60 Revealing the evolution of virulence in RNA viruses

A combination of high rates of mutation and replication, coupled with strong natural selection, ensures that RNA viruses experience rapid genotypic and phenotypic evolution. Such a ‘fast-forward’ evolution enables viruses to rapidly adapt to new host species, evade host immune responses, and to develop resistance to anti-viral drugs. Similarly, rapid evolution allows viruses to attain new levels of virulence, defined as the ability to cause severe disease in hosts. We hypothesize that distinct viral groups share genetic determinants that modulate virulence that have been acquired through convergent evolution. Thus, common patterns reflecting changing virulence-related specific viral groups could be detected. The main goals for this project are (1) to understand how genetic and phenotypic diversity can be generated among different viral groups by analyzing the variation patterns and determining the selective forces behind them (impact in viral fitness) and (2) to understand how fixed mutations can modulate virulence within different viral groups by performing comparison of strains with differing virulence within a longitudinal timescale. The subject of the study is key emerging and re-emerging virus families of medical importance. Such groups include: Coronaviridae (severe acute respiratory syndrome and Middle East respiratory syndrome-associated coronaviruses), Picornaviridae (Hepatitis A virus), Flaviviridae (Yellow fever, West Nile, Hepatitis C, Dengue, and Zika viruses), Togaviridae (Rubella and Chikungunya virus), Bornaviridae (Borna-disease virus), Filoviridae (Ebola and Marburg viruses), Paramyxoviridae (Measles, Nipah, and Hendra viruses), Rhabdoviridae (Lyssaviruses), Arenaviridae (Lassa virus), Bunyaviridae (Hanta- and Crimean-Congo hemorrhagic fever viruses), and Orthomyxoviridae (Influenza A viruses). Viral genomes collected at different time points, different hosts (human and their most closely related animal reservoirs) and different locations will be compiled. Extensive molecular evolutionary analyses will be carried out to infer gene expansion/contraction within groups, rates of evolution, and changes in selection pressure, including the detection of positive selected genes and sites (adaptive evolution). Positively selected sites will be mapped onto the viral protein structures to reveal their impact on function, and hence the location of potential virulence determinants. Virulence changes among particular viral strains and types will be defined and measured according to definitions based on an increase in: (1) transmissibility, (2) host tropism, (3) immune evasion, (4) morbidity and mortality, (5) drug resistance, and by the incorporation of epidemiological data to determine whether high or low virulence strains within different hosts and localities are spreading most efficiently in nature.

A time-resolved multi-omic atlas of the developing mouse stomach

The mammalian stomach is structurally highly diverse and its organ functionality critically depends on a normal embryonic development. Although there have been several studies on the morphological changes during stomach development, a system-wide analysis of the underlying molecular changes is lacking. Here, we present a comprehensive, temporal proteome and transcriptome atlas of the mouse stomach at multiple developmental stages. Quantitative analysis of 12,108 gene products allows identifying three distinct phases based on changes in proteins and RNAs and the gain of stomach functions on a longitudinal time scale. The transcriptome indicates functionally important isoforms relevant to development and identifies several functionally unannotated novel splicing junction transcripts that we validate at the peptide level. Importantly, many proteins differentially expressed in stomach development are also significantly overexpressed in diffuse-type gastric cancer. Overall, our study provides a resource to understand stomach development and its connection to gastric cancer tumorigenesis.

Monitoring of rest-activity rhythm in cancer patients paves the way for the adoption of patient-specific chronotherapeutic approach

The status and phases of the circadian timing system (CTS) can be ascertained through measuring several biological functions. Of those measurements, rest-activity rhythm is considered as a reliable circadian biomarker to evaluate the function of CTS among oncology population. Its amenable non-invasive monitoring over longitudinal time scale makes it more appropriate and convenient. Its use as reference rhythm for timing the medications is widely accepted in cancer and sleep clinics. Current mini review highlights the present knowledge on different actigraphy devices used for the measurement of circadian rest-activity rhythm. Further, this review presents recent data dealing with the status of circadian rest-activity rhythm in cancer patients and discusses its association with health-related patients’ quality of life. Application of this concept supports that the interventions with abilities to reverse CTS dysfunction in cancer patients might prolong their survival with improved and acceptable level of health-related quality of life.

Indigenous Youth Migration and Language Contact

Few studies ethnographically detail how Indigenous young people's mobility intersects with sociolinguistic transformation in an interconnected world. Drawing on a decade-long study of youth and language contact, I analyze Yup'ik young people's migration in relation to emerging language ideologies and patterns of language use in “Piniq,” (pseudonym), a Yup'ik village in Alaska, as villagers experienced a rapid language shift to English. Spatiotemporally situating young migrants’ experiences joining different peer groups at different times, I highlight how young people's linguistic repertoires and everyday negotiations of peer belonging in Piniq were intimately related to the accumulating (trans)local impacts of migration and schooling in the small but highly complex village context. I also show how taking youth migration and intragenerational, longitudinal timescales into account in rapidly transforming sociolinguistic settings can help bring into focus the layered simultaneity (Blommaert, 2005) of Indigenous youth language practice and the distributed nature of contemporary Indigenous linguistic ecologies. Implications for language planning are briefly discussed.

Solvation Dynamics and Electric Field Relaxation in an Imidazolium-PF6 Ionic Liquid: from Room Temperature to the Glass Transition

Time-resolved phosphorescence spectra and anisotropy of quinoxaline were measured in an ionic liquid, 1-butyl-3-methylimidazolium hexafluorophosphate (BMIM-HFP), in its supercooled state near the glass-transition temperature. The solvation dynamics results are compared with the rotational motion of the probe and with the dielectric behavior of the neat ionic liquid. The dynamics in the viscous state are highly dispersive and show a super-Arrhenius temperature dependence, as typical for glass-forming materials. Combined with room-temperature results, solvation dynamics is observed to follow the structural relaxation times in terms of eta/T for more than 10 decades, from subnanoseconds at room temperature to seconds near the glass-transition temperature T(g). The dielectric modulus relaxation follows this trend only for temperatures T > 1.2T(g) and departs significantly from eta/T in the 1.1T(g) > T > T(g) range. This deviation is reminiscent of the enhanced translational diffusion or fractional Stokes-Einstein behavior observed in many fragile supercooled liquids. Because the electric field relaxation in BMIM-HFP includes dc conductivity, this correlation function involves translational motion and thus displays the effect of enhanced diffusivity. A microscopic model is required for rationalizing the decoupling of solvation dynamics from the longitudinal time scales and the limitation of this effect to the viscous regime with T < 1.2T(g).

What is the solvent longitudinal time scale controlling electron transfer rates?

A theory for electron transfer rates in polar solvents is developed using an expansion of the density matrix in Liouville space and utilizing the analogy with the problem of nonlinear optical line shapes. The relevant solvent longitudinal time scale which controls the rate and the adiabaticity of electron transfer processes is precisely defined in terms of the solvent dielectric function ε(ω) for an arbitrary non-Debye solvent.