Value Of Information Research Articles

Genome-wide sequencing in children with epilepsy and developmental disorders

The progress of genetic diagnostic methods and a significant improvement in the quality of next-generation sequencing (NGS) have led to a revolution in the study of the genetics of epilepsy. Genome-wide sequencing (PSG) is the «gold standard» in genetic research in epilepsy.Material and methods. Genome-wide sequencing was performed in 168 probands aged from 1 month to 18 years with a suspected diagnosis of genetic epilepsy. PSG was prescribed to patients who, alongside with epilepsy, had delayed intellectual/speech development and/or motor disorders and behavioral disorders.Results. According to the results of PSG, genetic variants related to the phenotype of the disease were detected in 137 out of 168 (81.5%) children, variations in the number of DNA copies were noted in 14 out of 168 (8.3%) patients. Variants with unclear clinical significance were described in 35 of 137 (25.54%). In the remaining 102 out of 137 (74.45%) patients, the identified causative genetic variants were described as probably pathogenic and pathogenic. Monogenic developmental and epileptic encephalopathies (DEE) were detected in 37/137 or 27% of all patients, while the spectrum of these genetic encephalopathies was extremely wide (from DEE type 1 to DEE type 97). In 52/137 (37.9%) children, the presence of a specific genetic syndrome outside the framework of the DEE, classified in OMIM, was confirmed.Conclusion. The results confirm the high informative value of genome-wide sequencing in a group of children with a combination of epilepsy, intellectual, speech, motor and behavioral disorders. In most cases, the results allow either to prescribe a genotype-oriented symptomatic (less often pathogenetic) treatment, or rationally justify the tactics of further observation and examination, as well as to increase the effectiveness of medical and genetic counseling. The authors express their sincere gratitude to the Charity foundation for medical and social genetic aid projects «Life Genome” for assistance in conducting genome-wide sequencing of most of the described patients.

EXPRESS: Crowd-starting a Shared (Shuttle) Service with Customer Suggestions

Digital platforms have improved the effciency and quality of smart city operations by soliciting more customer inputs, for example, in the form of suggestions. One innovative option in urban transportation is the shared shuttle service, which lies between traditional public transportation and ride-hailing services. Platforms that offer these services can gather customer suggestions in a \crowd-starting" manner, which provides valuable insights into customer needs. However, this also presents a challenge in balancing service coverage and quality to meet customer needs implied by their suggestions. To address this issue, we introduce an optimization framework designed to maximize expected profit by leveraging customer response models which characterize how customers will respond to different service attributes and how their suggestions inform these responses. When estimating these response models, we present methods involving isotonic penalty and shrinkage tailored for handling small datasets. To demonstrate the practical implications, we apply our model to a shared shuttle service case study and discuss practical considerations, such as the value of information, the effectiveness of our estimation approaches, and the benefits of involving customers in the service design process.

Vacuum fine-needle aspiration biopsy as a method of early detection of thyroid cancer

Relevance. Malignant neoplasms of the thyroid gland account for 1–3% in the structure of oncological pathology in the territory of the Russian Federation. Fine needle aspiration biopsy of thyroid foci is an integral part of the examination and is included in both foreign and domestic recommendations. However, there is a problem of obtaining uninformative cytological conclusions, and the risk of obtaining false positive and false negative results remains.Objective. To determine the possibilities of using vacuum aspiration fine needle biopsy under ultrasound control in patients with focal thyroid pathology in a multidisciplinary hospital.Materials and methods. From 2021 to 2023, 331 patients with focal thyroid pathology were examined at the clinical base of the Department of Diagnostic and Minimally Invasive Technologies of the Clinical Hospital № 1 in Smolensk. All patients were divided into two clinical groups. Patients of both groups underwent a comprehensive examination, including palpation of the thyroid gland and lymph nodes of the neck, multiparametric ultrasound examination of the thyroid gland, including B – mode, color Doppler mapping, compression elastography, shear wave elastography, laboratory examination (calcitonin level, TSH, T3, T4, antibodies of TPO, AtTTP, thyroglobulin). In patients who had previously undergone surgical treatment, ultrasound was performed to determine areas of thyroid tissue, and additionally the level of thyroglobulin was determined as a marker of the recurrent process.Results. The median size of the thyroid formation was 15.2 (13.9–19.1) mm. Mainly multiple foci of thyroid gland were detected in both the control group – 106 (79.1%) and the main 107 (54.3%) patients, the share of single foci accounted for 28 (20.9%) of the control and 90 (45.7%) of the main groups. Fine – needle aspiration biopsy was performed using the «Free hand» method using type syringe with a volume of 10 ml. During the vacuum fine – needle aspiration biopsy, depending on the data of the multiparametric ultrasound examination, the level of negative pressure in the range from –0.3 bar to –0.8 bar was determined. At a pressure of –0.3 bar, 54 (27.4%) were performed,–0.5 bar – 126 (64.0%),–0.8 bar – 17 (8.6%) vacuum fine – needle aspiration biopsy.Conclusions. A device has been developed for the implementation of vacuum fine – needle aspiration biopsy with the creation of an improved technique for conducting vacuum fine – needle aspiration biopsy in focal thyroid pathology. The informative value of the method of routine fine – needle aspiration biopsy and vacuum fine – needle aspiration biopsy under ultrasound control in patients with focal thyroid pathology was evaluated. The sensitivity and specificity of fine – needle aspiration biopsy was 75.0% and 52.9%, respectively. The sensitivity and specificity of vacuum fine – needle aspiration biopsy during the study were 95.6% and 92.5%, respectively. The data obtained indicate the effectiveness of the method.

The Influence of Human Resource Competence, Implementation of Agency Level Financial Application Systems and Organizational Commitment on The Information Value of Central Government Financial Reports (Empirical Study in The Ministry of Industry in Java and Sumatera Regions)

This study aims to determine, test, and analyze the influence of human resource competence, implementation of agency-level financial application systems, and organizational commitment on the information value of central government financial reports in the ministries of industry in the Java and Sumatera regions. This research uses quantitative methods with an associative approach and documentary data collection by collecting, recording, reviewing and analyzing primary data in the form of respondents’ answers to the questionnaires given. This research took 70 samples as respondents from work units. The data analysis technique used is descriptive statistics which is used to explain the data description of all variables and Partial Least Square (PLS) regression analysis which is a Structural Equation Model (SEM) equation model. The results of this research show that human resource competence, application system implementation agency level finance, and organizational commitment influence the information value of central government financial reports.

Transforming the Discovery of Targeted Protein Degraders: The Translational Power of Predictive PK/PD Modeling.

Targeted protein degraders (TPDs), an emerging therapeutic modality, are attracting considerable interest with the promise to address disease-related proteins that are not druggable with conventional small molecule inhibitors. Despite their novel mechanism of action, the PK/PD relationship of degraders is still approached with a mindset deeply rooted in inhibitor drugs. Here, we establish how predictive mechanistic modeling specifically tailored to TPDs can significantly enhance the value of the available information during lead generation and optimization. By integrating the results from in vitro assays with routinely collected PK data, modeling accurately predicts degradation in vivo. These predictions transform the prioritization of compounds for in vivo studies as well as the selection of optimal dose schedules and most informative measurement time points with the least number of animals. Moreover, the comprehensive modeling framework (1) identifies the PK/PD driver of targeted protein degradation and subsequent downstream pharmacodynamic effects, and (2) uncovers the fundamental difference between degrader and inhibitor PK/PD relationships. The practical utility of our predictive modeling is demonstrated with relevant use cases. This framework will allow researchers to transition from current, mostly serendipity-based approaches to more sound model-informed decision making. Going forward, the presented predictive PK/PD modeling framework lays out a rational path to incorporate inter-species differences in the pharmacology and thus promises to help with getting the dose right in clinical trials.

Assessment of Dynamic Cerebral Autoregulation During Long-Term Exposure to High Altitude in Normal Subjects by Ultrasonography.

To evaluate changes in dynamic cerebral autoregulation (CA) during short-term and long-term exposure to high altitude with ultrasonography, and also study the sex differences in the response of CA to altitude. We assessed the differences in dynamic CA and measured with Doppler ultrasound of the bilateral internal carotid artery (ICA), vertebral artery (VA), and middle cerebral artery (MCA) and the values of basic information within 48 hours and at 2 years after arrival at Tibet in 65 healthy Han young Chinese volunteers, meanwhile, we compared the resistance index (RI) and pulsatility index (PI) of the right MCA at inhale oxygen 8 minutes when a newcomer with 2 years after arrival at Tibet. With 2 years of altitude exposure, the SaO2 of all subjects was above 90%, the mean PEF, DAP, and HR values decreased, HGB increased compared within 48 hours in same-gender groups. Comparisons of cerebral hemodynamics between before 2 years and after 2 years within male and female groups, the mean RI and PI values of bilateral MCA after 2 years were significantly higher than before 2 years, at the same time, the mean RI and PI values of bilateral ICA were significant differences (P < .05) between male groups, with regard to female groups, showed that the mean RI and PI values of bilateral VA were significant differences (P < .05). Comparisons of Right MCA hemodynamics between after oxygen uptake 8 minutes and 2 years, the mean RI and PI values were no significant difference within male and female groups (P > .05). Acute mountain sickness could result from an alteration of dynamic autoregulation of cerebral blood flow, but the impaired autoregulation may be corrected with the extension of time, furthermore, the response of CA to altitude in males and females are different.

Is tax-related information value relevant? Empirical study in the Canadian setting

Is tax-related information value relevant? Empirical study in the Canadian setting

On information value and decision analyses

This paper addresses value of information, structural health information, and decision analyses in built environment engineering. Decision analyses are used for the joint optimization of information collection and the identification of physical measures for the management and enhancement of the expected utility of built environment systems. To these ends, this paper contains (1) principal descriptions of decision scenarios and the model basis in conjunction with the objective functions, embedded in (a) a summary of the historical background and (b) the origins of the methods of decision and value of information analyses, (2) an overview of methods for decision analyses highlighting solution strategies to handle comprehensiveness and computational challenges, (3) principal application areas and case studies, and (4) insights into recent advances. The main insights and an outreach to potential future research perspectives are summarised at the end of this paper.

Microscope-integrated optical coherence tomography for in vivo human brain tumor detection with artificial intelligence.

It has been shown that optical coherence tomography (OCT) can identify brain tumor tissue and potentially be used for intraoperative margin diagnostics. However, there is limited evidence on its use in human in vivo settings, particularly in terms of its applicability and accuracy of residual brain tumor detection (RTD). For this reason, a microscope-integrated OCT system was examined to determine in vivo feasibility of RTD after resection with automated scan analysis. Healthy and diseased brain was 3D scanned at the resection edge in 18 brain tumor patients and investigated for its informative value in regard to intraoperative tissue classification. Biopsies were taken at these locations and labeled by a neuropathologist for further analysis as ground truth. Optical OCT properties were obtained, compared, and used for separation with machine learning. In addition, two artificial intelligence-assisted methods were utilized for scan classification, and all approaches were examined for RTD accuracy and compared to standard techniques. In vivo OCT tissue scanning was feasible and easily integrable into the surgical workflow. Measured backscattered light signal intensity, signal attenuation, and signal homogeneity were significantly distinctive in the comparison of scanned white matter to increasing levels of scanned tumor infiltration (p < 0.001) and achieved high values of accuracy (85%) for the detection of diseased brain in the tumor margin with support vector machine separation. A neuronal network approach achieved 82% accuracy and an autoencoder approach 85% accuracy in the detection of diseased brain in the tumor margin. Differentiating cortical gray matter from tumor tissue was not technically feasible in vivo. In vivo OCT scanning of the human brain has been shown to contain significant value for intraoperative RTD, supporting what has previously been discussed for ex vivo OCT brain tumor scanning, with the perspective of complementing current intraoperative methods for this purpose, especially when deciding to withdraw from further resection toward the end of the surgery.

Exploring the investment value of retail sales growth: Evidence from the China Retailer Alliance

This study investigates the investment value of retail sales growth using a unique dataset obtained from the China Ants Alliance, a retailer alliance in China. Leveraging this dataset, we construct a weekly sales growth rate index (SG) and draw significant conclusions about consumer-oriented firms. The hedge portfolios constructed based on this index earn a 0.206% excess weekly return. The predictability of the returns from the index persists after controlling for various firm characteristics. Sales growth also positively predicts firms’ fundamentals, such as revenue growth and cash flow surprises, highlighting the investment value of retail sales in predicting future cash flows and a firm’s revenue. Overall, we enrich the literature on consumer behavior information and stock pricing. We further expand the exploration of the investment value of nonfinancial information and provide a valuable reference for investors and the capital market.

A data-driven distributionally robust optimization approach for the core acquisition problem

Reusing electric vehicles (EV) batteries that reach the end of their useful first life is an environmental and cost-competitive option; however, the process of recycling EV batteries is not yet mature. Due to complex electrochemical reactions and physical conditions, the quality of used EV batteries (cores) is highly uncertain. The remanufacturer needs to make the acquisition decision under quality distributional ambiguity. Perfect quality distribution of cores cannot be known to the remanufacturer in practice. We develop distributionally robust optimization models based on phi-divergence measures and the imprecise Dirichlet model (DRO-IDM) to derive robust decisions. First, we find that the bounds of quality probability intervals are identified solely based on the collected data by introducing the imprecise Dirichlet model. The derived finite-sample boundary can reduce the scope of the uncertainty set and avoid the no-direction search issue. Second, our models can hedge against distributional uncertainty, reduce the probability of a robust solution that deviates from the optimal solution, and correct bias in decision making. Third, we extend the DRO-IDM to develop data-driven models, that can reassess the value of multisource quality information to improve the estimation accuracy of core quality and maximize the remanufacturer’s profit. Our study provides new insights for remanufacturers: the new remanufacturing process proposed in our work can assist remanufacturers in utilizing the values of cores without disassembly; the information-aware algorithm can offer the remanufacturing sector a valuable tool for efficiently filtering out invalid information in optimizing acquisition decisions; this capability empowers decision-makers to leverage multiple sources of information and expedite the process of digital transformation in remanufacturing; our approach can also provide a manner of integrating information fusion and distribution learning into remanufacturing.

The influence of energy-saving information in online reviews on green home appliance purchase behavior based on machine learning

The renewal of green home appliances is a crucial measure for households to save energy and reduce emissions. However, how online reviews, especially those relate to energy-saving, affect green home appliance purchase behavior (GHAPB) lacks exploration. In this paper, we investigate over 1 million online reviews on about 3,116 types of air conditioner from JD. By applying word2vec, we divide energy-saving related information in the following three types: norm information, environmental health information and price information, and construct dictionaries for each. Then, the effect value of energy-saving information is quantified from perspectives of breadth, depth and intensity through sentiment analysis. The influence of energy-saving information in online reviews on GHAPB is finally analyzed by linear regression and machine learning models. The results show that all energy-saving information has positive impact on GHAPB, and environmental health information is the most important one. In addition, the attributes of online reviews impose a greater influence on GHAPB, comparing with those of products. The in-depth exploration of energy-saving information in online reviews provides targeted recommendations for the manufacturer and the retailer to promote the adoption of green home appliances

Patients’ experiences of clinical trial participation involving a product remotely assessing study drug adherence

BackgroundThe participation of patients in clinical trials is crucial for the development of healthcare. There are several challenges in the recruitment of trial participants with acute medical conditions. The registry-based randomized DAPA-MI clinical trial recruited patients during hospitalization for myocardial infarction and provided study drugs in bottles with smart caps that used wireless technology to transmit monitoring data. This interview study aimed to investigate patients’ experience of participation in a clinical trial and their attitude to the new bottle cap technology. MethodsA subset of patients participating in the DAPA-MI trial were recruited from four hospitals in Sweden. Semi-structured interviews were conducted and analysed using manifest content analysis. ResultsVideo interviews were performed including 21 patients (four women and 17 men). The median age was 59 years (range 44–80). Four categories of patients’ experiences were identified. A willingness to contribute consisted of patients’ positive attitudes to participation and to be a part of development and research. The perception of information emphasized the value of the oral information as well as the importance of time for reflection. Be in a vulnerable condition highlighted the impaired ability to perceive and remember in the acute medical condition. Adaptation to a new technology described the overall positive experiences of the smart bottle cap to evaluate adherence. ConclusionsPatients’ experiences of trial participation were in general positive but some challenges in the acute setting of a myocardial infarction were revealed. The smart bottle cap was well accepted, despite some handling difficulties.

Neural mechanisms of information seeking.

We ubiquitously seek information to make better decisions. Particularly in the modern age, when more information is available at our fingertips than ever, the information we choose to collect determines the quality of our decisions. Decision neuroscience has long adopted empirical approaches where the information available to decision-makers is fully controlled by the researchers, leaving neural mechanisms of information seeking less understood. Although information seeking has long been studied in the context of the exploration-exploitation trade-off, recent studies have widened the scope to investigate more overt information seeking in a way distinct from other decision processes. Insights gained from these studies, accumulated over the last few years, raise the possibility that information seeking is driven by the reward system signaling the subjective value of information. In this piece, we review findings from the recent studies, highlighting the conceptual and empirical relationships between distinct literatures, and discuss future research directions necessary to establish a more comprehensive understanding of how individuals seek information as a part of value-based decision-making.

Urinary tract infections in pregnant women

Urinary tract infections (UTIs) are the most common pathology among pregnant women and are associated with maternal and foetal complications. According to some authors, the incidence of UTIs increased 4 times in the last decades of the 20th century. Escherichia coli is the most predominant pathogen causing up to 80% of UTIs, Klebsiella is ranked second causing up to 8% of UTIs, and pathogenic staphylococcus and mixed microflora are ranked third. To diagnose UTIs, laboratory, physical and radiological diagnostic methods are applied. According to most authors, informative value yielded by lab tests is more than 90%. The prescription of antibacterial chemotherapy should be based on the results of urine culture and sensitivity testing. Before the test results are obtained, broad-spectrum antibacterial drugs (ABs) are usually prescribed. The most commonly used therapy regimens are third-generation cephalosporins with dose adjustments, as may be necessary, after sensitivity is determined. Some authors recommend to continue treatment with urinary tract antiseptics after AB therapy is completed. The impaired urine output should be restored before AB therapy is prescribed. This review presents an analysis of the literature that was found in the databases PubMed (the National Library of Medicine), The Cochrane Library, as well as in the research citation databases (Scopus, Web of Science). The etiological factors and features of the pathogenesis of UTIs in pregnant women, as well as diagnostic standards, are described. The current guidelines for the treatment and prevention of UTIs in pregnant women are considered and antibacterial therapy regimens with current dosage forms are presented. The benefits of using cefixime dispersible forms are described in detail.

Stranger things: the vanishing of the Altmetric Attention Score values in information and library science

AbstractThis study investigates the Altmetric Attention Score (AAS) fluctuations and altmetrics source stability in Information Science &amp; Library Sciences publications, analyzing 26,474 documents from 2012 to 2021. It finds that 23.7% of these publications experienced AAS fluctuations over a year. Significant influences on AAS variability include Twitter mentions and policy documents, with Twitter mentions showing high volatility, affecting nearly 30% of papers. The removal of the Analysis &amp; Policy Observatory as a policy source led to a notable drop in policy document mentions. Various types of mention vanishing are identified, such as administrative decisions by altmetrics aggregators, technological issues, user actions on digital platforms, and natural changes on platforms like Wikipedia. In response, the study proposes modifications in the tracking and monitoring system of mentions to not overlook these vanishings. This aims to enhance the reliability and stability of altmetrics at a time when there is a call for their use in the research evaluation.

Intellectual capital information via Twitter: the effect on firm value

PurposeSocial media are emerging as the ideal channel for building one-to-many communication and disseminating intellectual capital (IC) information. Their rise is bringing out new research challenges to investigate the implications of their use. However, there needs to be more research contributions relating to the financial benefits of using social media for IC disclosure (ICD). This study aims to bridge this gap by analyzing, under the lens of signaling theory, the effect of ICD through Twitter on firm value.Design/methodology/approachThis study is based on a content analysis of tweets disseminated by 262 companies aimed at examining the amount of IC information disclosed and on a regression analysis aimed at analyzing the impact of this type of information on firm value.FindingsEmpirical results show that a large ICD via Twitter favors an increase in firm value. They also demonstrate that disclosing information relating to the three IC dimensions positively affects the firm value. These findings suggest that actively and comprehensively communicating IC information via Twitter can help improve the perception and evaluation of the company by investors and other stakeholders.Research limitations/implicationsThis study offers empirical evidence about the financial benefits associated with using social media as disclosure tools by companies. It also enriches the literature on the relationship between ICD and firm value and consolidates the goodness of the signaling theory as an ideal theoretical perspective to frame the relationship between IC information and firm value.Practical implicationsThis study offers important managerial implications for firms and investors. In light of the significant financial benefits, firms should use social media to disclose IC information and should seek to increase their visibility on such platforms to convey the information to a greater number of users. Investors should also heed social media when gathering IC information, combining the analysis of these platforms with that of traditional corporate documents.Originality/valueThis study enriches the limited literature on ICD via social media and extends knowledge about the relationship between IC information and firm value. In this regard, the originality also lies in the individual analysis of the impact of the three IC dimensions on firm value.

Directors with supply chain experience as heterogeneous network pipes: how does it affect M&amp;A efficiency

PurposeThe link between interlocking directors and mergers and acquisitions (M&amp;A) efficiency has been analyzed in an information asymmetry environment. Despite an abundance of evidence highlighting that interlocking directors do contribute to M&amp;A efficiency in an acquirer-target binary relationship, the target is embedded in a complex network of supplier-customer relationships, which implies that the acquirer needs to consider the value of suppliers, distributors and retailers in the target’s supply chain in improving M&amp;A efficiency. Through the lenses of acquirer-target multivariate relationships, this paper aims to examine how directors with supply chain experience (DSCs) act as heterogeneous network pipes to affect M&amp;A efficiency.Design/methodology/approachUsing a sample of 311 A-share listed firms on the Shanghai and Shenzhen stock exchanges in China during 2011–2020, this paper investigates the relationship between DSCs and M&amp;A efficiency by using ordinary least squares (OLS) regression.FindingsThrough empirical research, we verify a negative relationship between DSCs and M&amp;A duration and an inverted U-shaped relationship between both DSCs and M&amp;A performance, revealing the complexity of the relationship between experience and efficiency. Furthermore, drawing on upper echelon theory, the information value of DSCs will be greatly reduced when executives have overconfident psychological characteristics, which are mainly shown to negatively moderate the relationship between DSCs and M&amp;A performance. We also conduct multiple robustness tests and supplemental analyses to illustrate the robustness and boundaries of our findings. Finally, DSCs are likely more important in environments among growth and mature firms as well as high-growth industries.Originality/valueWe break through the assumption that interlocking directors contribute to M&amp;A efficiency in an acquirer-target binary relationship and examine the impact of DSCs on M&amp;A efficiency based on micro-empirical evidence from the value of target-related upstream or downstream industries, which extends the connotation of interlocking directors and enriches the study related to factors influencing M&amp;A efficiency.

Moderating role of board gender diversity and firm size on the relationship between free cash flow and corporate sustainability of Thai listed companies

This study seeks to explore the information value of free cash flow (FCF) on corporate sustainability and investigate the moderating effects of board gender diversity and firm size on the association between FCF and corporate sustainability of Thai listed companies. The dataset consists of companies listed on the Stock Exchange of Thailand (SET) in 2022. Multivariate regression analysis is executed in this study. Subsequently, PROCESS macro served to evaluate the proposed hypotheses. This study found that FCF has a significant positive relationship with corporate sustainability. As well, board gender diversity and firm size both moderate the relationship between FCF and corporate sustainability, such that the positive effect of FCF on corporate sustainability is stronger when the proportion of female boards diminishes, while firm size is smaller. However, when firms have a larger proportion of females on the boards of directors for all levels of firm size, free cash flow indicates that there is no statistically significant effect on corporate sustainability. This study contributes to FCF and sustainability literature by understanding the extent of corporate sustainability.

Post-earthquake building damage assessment: A multi-period inspection routing approach for Gaussian process regression

In the wake of seismic events, prompt and accurate building damage assessment is crucial to inform post-disaster interventions and recovery efforts. This paper advances a novel multi-period planning strategy for post-earthquake building inspections, conceptualizing the task as a multi-period orienteering problem (MPOP). In this framework, each building selected for inspection hosts a specific reward indicating its informative value for damage assessment. The objective is to design inspection routes that maximize damage information acquisition while adhering to time constraints. After data collection, we utilize a Gaussian process regression (GPR) model to estimate the damage in uninspected buildings. To validate our approach, we conduct an earthquake simulation with realistic building information from San Francisco. The experimental outcomes reveal that our multi-period damage assessment framework maintains robust performance across diverse scenarios and consistently surpasses conventional period-by-period inspection strategies, yielding enhanced damage information acquisition and greater precision in damage estimation. This outcome underscores the effectiveness of our proposed method in strengthening post-earthquake damage assessment and improving recovery planning.