Information Measures Research Articles

O-123 Trends and challenges in the practice of ART in China

Abstract China is a large country with a population of over 1.4 billion. In 1988, the first in-vitro fertilization-embryo transfer (IVF-ET) baby was born in Peking University Third Hospital. In the following 3 decades, assisted reproductive technology (ART) has developed rapidly in China, and the availability and accessibility of the ART service have improved markedly. In 2004 totally, only 37 institutions had passed the administrative licensing procedure to carry out ART. While in 2020, 536 institutions obtained the ART license. Since 2016, the total number of ART service cycles(Artificial insemination included)has exceeded 1 million, and the number of babies born has exceeded 300,000, accounting for about 2% of the total live births in China in 2016. At present, assisted reproductive technology has become one of the important medical interventions for the treatment of infertility in China, which has brought good news to infertile couples and their families, and has made great contributions to social harmony and family happiness. Cycles per million population (C/M) in 2009 was 120. In 2020, it has increased to 668, with more and more infertile couples having access to this technique in China. The success rate of assisted reproductive technology remained stable. In 2020, the clinical pregnancy rates (CPR)of conventional IVF and ICSI fresh embryo transfer cycles reached 52.4% and 49.4%, respectively, and the live birth rates were 43.0% and 40.6%, respectively. The clinical pregnancy rate and live birth rate of frozen-thawed embryo cycle were 51.3% and 40.5% per transfer. With the widespread application of embryo freezing technology, the cumulative live birth rate was estimated to reach 49.5% (CLBR estimate) in 2020. The safety monitoring indicators of assisted reproductive technology showed that since 2015, the multiple pregnancy rates of conventional IVF, ICSI and FET have decreased year by year, and have dropped to 22.4%, 21.4% and 17.6% in 2020, respectively. The incidence of moderate-severe ovarian hyper-stimulation syndrome (OHSS) and severe bleeding were also under control, within a reasonable range. Assisted reproductive technology, which involves many medical, social, ethical and legal issues, is a special clinical technology with limit application for medical indication. The Chinese government attaches great importance to the quality and safety management of assisted reproductive technology. A series of management documents such as the Administrative Measures for Human Assisted Reproductive Technology, the Regulations for Human Assisted Reproductive Technology and so forth, have been issued since 2001. Further improvement of key performance indicators (KPIs) correlated with ART quality and safety control is of the top priority and also challenging. In addition, the ART surveillance data in China is still aggregated data, which does not include important indicators such as age stratification, infertile factors or indications and delivery gestational age, maternal and infant outcomes, with some limitations for surveillance. Continuous improvement of data quality, and initiation of cycle-based data collection and security measures of case information are also challenging for the next step.

Spectroscopy of N = 50 isotones with the valence-space density matrix renormalization group

The recently proposed combination of the valence-space in-medium similarity renormalization group (VS-IMSRG) with the density matrix renormalization group (DMRG) offers a scalable and flexible many-body approach for strongly correlated open-shell nuclei. We use the VS-DMRG to investigate the low-lying spectroscopy of N=50 isotones, which are characteristic for their transition between single-particle and collective excitations. We also study electromagnetic transitions and show the advantage of the VS-DMRG to capture the underlying physics more efficiently, with significantly improved convergence compared to state-of-the-art shell-model truncations. Combined with an analysis of quantum information measures, this further establishes the VS-DMRG as a valuable method for ab initio calculations of nuclei.

A comparative evaluation of measures to assess randomness in human-generated sequences

Whether and how well people can behave randomly is of interest in many areas of psychological research. The ability to generate randomness is often investigated using random number generation (RNG) tasks, in which participants are asked to generate a sequence of numbers that is as random as possible. However, there is no consensus on how best to quantify the randomness of responses in human-generated sequences. Traditionally, psychologists have used measures of randomness that directly assess specific features of human behavior in RNG tasks, such as the tendency to avoid repetition or to systematically generate numbers that have not been generated in the recent choice history, a behavior known as cycling. Other disciplines have proposed measures of randomness that are based on a more rigorous mathematical foundation and are less restricted to specific features of randomness, such as algorithmic complexity. More recently, variants of these measures have been proposed to assess systematic patterns in short sequences. We report the first large-scale integrative study to compare measures of specific aspects of randomness with entropy-derived measures based on information theory and measures based on algorithmic complexity. We compare the ability of the different measures to discriminate between human-generated sequences and truly random sequences based on atmospheric noise, and provide a systematic analysis of how the usefulness of randomness measures is affected by sequence length. We conclude with recommendations that can guide the selection of appropriate measures of randomness in psychological research.

Bounding Quantum Correlations: The Role of the Shannon Information in the Information Causality Principle.

The Information Causality principle was proposed to re-derive the Tsirelson bound, an upper limit on the strength of quantum correlations, and has been suggested as a candidate law of nature. The principle states that the Shannon information about Alice's distant database gained by Bob after receiving an m bit message cannot exceed m bits, even when Alice and Bob share non-local resources. As originally formulated, it can be shown that the principle is violated exactly when the strength of the shared correlations exceeds the Tsirelson bound. However, we demonstrate here that when an alternative measure of information, one of the Renyi measures, is chosen, the Information Causality principle no longer arrives at the correct value for the Tsirelson bound. We argue that neither the assumption of particular 'intuitive' properties of uncertainties measures, nor pragmatic choices about how to optimise costs associated with communication, are sufficient to motivate uniquely the choice of the Shannon measure from amongst the more general Renyi measures. We conclude that the dependence of the success of Information Causality on mere convention undermines its claimed significance as a foundational principle.

Comparable but is it informative?Accounting information comparability and price synchronicity

Increasing accounting information comparability (AIC) theoretically facilitates investors’ analysis of firm performance and improves stock price informativeness by incorporating more firm-specific information. However, achieving the purported purpose empirically is subject to firms’ institutional environment and corporate governance. We propose that under weak legal systems and less developed market environments, higher AIC may adversely affect price informativeness due to managers’ incentives and ability to obfuscate information and investors’ “hallo” effect. Using a large sample from China, we show that the AIC is positively related to price synchronicity, an inverse measure of price informativeness. Additionally, the positive impact is significantly greater for firms located in regions with weak legal systems and less developed market environments. The positive relation is also significantly greater when the business environment and economic policy uncertainties are high.

Magnitudes of overweight and obesity among adult and associated factors in jigjiga town, Somali region, Ethiopia

Overweight and obesity are major worldwide health concerns, with serious consequences for mortality and morbidity. Overweight and obesity rates are frighteningly high in Sub-Saharan Africa, particularly Nigeria and Ethiopia, due to a variety of causes such as urbanization, greater affluence, and bad food habits. The purpose of this study was to determine the prevalence of overweight and obesity among people in Jigjiga Town, Somali Region, Eastern Ethiopia, as well as to investigate related factors in order to inform treatments and policy. A cross-sectional survey was done among persons aged 20 to 64 working in the government, non-governmental, and commercial sectors. Socio-demographic information, food habits, physical activity, and anthropometric measures were all recorded. The overall prevalence of overweight and obesity was shown to be 42.4 %, with significant correlations identified with profession and TV viewing habits. Employed people were less likely to be overweight or obese than those in commerce/trade, and those who watched TV for 2–3 h had a reduced risk than those who watched less than 2 h. The study found that khat chewing is significantly associated with an increased risk of overweight and obesity, with chewers being 1.56 times more likely to be overweight or obese compared to non-chewers. Additionally, there is an inverse relationship between snacking frequency and overweight/obesity risk; participants who snacked once a day were 2.5 times more likely to be overweight or obese than those who snacked three or more times a day. These findings highlight that khat chewing and snacking patterns are important modifiable risk factors for overweight and obesity in the studied population. These findings highlight the need of focused treatments targeting food choices, physical activity, and sedentary behavior in combating overweight and obesity in Eastern Ethiopia. Collaboration among academics, policymakers, healthcare professionals, and community stakeholders is critical for developing successful methods for promoting healthy lifestyles and lowering the region's overweight and obesity burden.

Vibrational Entanglement through the Lens of Quantum Information Measures.

We introduce a quantum information analysis of vibrational wave functions to understand complex vibrational spectra of molecules with strong anharmonic couplings and vibrational resonances. For this purpose, we define one- and two-modal entropies to guide the identification of strongly coupled vibrational modes and to characterize correlations within modal basis sets. We evaluate these descriptors for multiconfigurational vibrational wave functions which we calculate with the n-mode vibrational density matrix renormalization group algorithm. Based on the quantum information measures, we present a vibrational entanglement analysis of the vibrational ground and excited states of CO2, which display strong anharmonic effects due to the symmetry-induced and accidental (near-) degeneracies. We investigate the entanglement signature of the Fermi resonance and discuss the maximally entangled state arising from the two degenerate bending modes.

PMUs data based detection of oscillatory events and identification of their associated variable: Estimation of information measures approach

Information theory can be a useful tool for quantifying the perturbations in the associated state variables at the time of disturbance occurrence. The study introduces a framework for the spectral decomposition of multivariate information measures to detect initiation of low frequency oscillations (LFOs), caused due to physical events in the power grid. A frequency-specific quantification of the information is shared between a target variable and two source variables from their time series data. Initially, the approach is applied on different synthetic test signals having different oscillatory frequency modes and decay time constant. Then, approach is extended on PMUs signals. The combination of cross-spectral and information-theoretic approaches is applied for the multi-variable analysis of PMUs signals from the same bus. The interdependence among the frequency, voltage angle and voltage magnitude, corresponding to specific oscillations, manifested due to cause-effect relationships obtained in terms of statistics is estimated. The dynamics in terms of unique (interaction), redundant and synergetic information is determined with the contribution from two of these three signals as source variables to target variable (frequency/voltage angle). This provides a direct coupling to identify driver-response relationships between source variables and target variable to indicate the onset of LFOs, following physical events in power network. The extension of approach among the variables from different buses aids to identify the responsible area of event occurrence.

The representation, quantification, and nature of genetic information

Current genetics studies often refer to notions from information science. The purpose of this paper is to summarize and structure the different notions of information used in biology, as a step towards developing a taxonomy of information. Within this framework we propose an extension of Floridi’s conceptual model of information. We also make use of the concept of specified information and show that functional information and many other notions of information are either special cases of, or are closely related to, specified information. Since functionality of the proteins that genes code serves as an external and independent specification, this makes it possible to define genetic information in a way that includes semantic aspects. In particular, we discuss how to understand the qualitative aspects of genetic information, how to measure its quantitative aspects, and how variants of Shannon’s information measure can be applied to molecular sequence data of protein families. While a mathematical framework may not be able to incorporate all that is included within biological information, some aspects of it allow for statistical modelling. This is especially true if we restrict our focus on the discipline of genetics. The concept of genetic information is still disputed because it attributes semantic traits to what seems to be regular biochemical entities. Some researchers maintain that the use of information in biology is just metaphorical and may even be misleading. We argue that the foundation of the metaphorical view is relatively weak given the current findings in bioinformatics and show that the present understanding of genetics fits well into the context of the modern philosophy of information. The paper concludes that informational concepts have robust scientific applications at the level of genes.

Банковская паника в условиях цифровой трансформации общества: особенности возникновения и меры предотвращения

This article delves into the specifics of bank run emergence amidst society’s digital transformation, highlighting features such as rapid information transmission, increasing vulnerability risks of financial systems to new forms of fraud and cyber threats, utilization of artificial intelligence, and investments in payment systems and cryptocurrency. The banking system, as the main instrument of financial activity, is exposed to transformational changes, which necessitates its constant adaptation to new operating conditions, including to prevent uncontrolled panic reactions on the part of depositors, the consequences of which any financial organizations may face. The author proposes a few measures aimed at preventing or mitigating the consequences of bank runs in the financial sector, encompassing both urgent steps in the field of cybersecurity and risk management, as well as regulatory actions by the state and financial organizations. In general, the successful prevention of bank runs requires an integrated approach that includes information, technical and financial measures, as well as the development of an economic education system and an increase in financial literacy.

Testing the Mediating and Moderating Factors of the Link Between Religiosity and Vaccine Hesitancy: A Quantitative Study of Turkish Muslims

This study aims to examine the link between religiosity and vaccine hesitancy and whether this relationship is mediated by trust in science and scientists. The sample consisted of 571 Turkish Muslims. The participants' average age was 38.09 years (SD=11.3). The participants were asked to provide their demographic information and complete measures of vaccine hesitancy, religiosity, and trust in science and scientists. The findings indicate that (a) there is a significant positive correlation between religiosity and vaccine hesitancy, (b) trust in science and scientists has a mediating role in the relationship between religiosity and vaccine hesitancy, and (c) age has a significant moderating effect on the relationship between religiosity and vaccine hesitancy. The findings suggest that the role of religiosity in vaccine hesitancy functions through trust in science and scientists.

RIGHT TO ENVIRONMENTAL INFORMATION IN THE CONTEXT OF DIGITALIZATION

The article examines the legal signi cance of environmental information in a digital society and examines its characteristics such as reliability. It is this quality of information about the state of the environment that is enshrined in the Constitution of the Russian Federation. It is noted that reliable information about the state of the environment is information that is at the same time genuine (objective, undistorted, accurate), and su cient (not excessive, but not fragmentary and not selective), and relevant (timely), unbiasedly collected and analyzed by a competent subject. The de nition of the term “information on the state of the environment (environmental information)” included in the Federal Law “On Environmental Protection” in 2021 is also analyzed. It is concluded that the legal de nition of the term in question does not allow distinguishing environmental information from all other information. The right to environmental information is analyzed in relation to the modern system of information support for state environmental management. The necessity of establishing a regime of transparency of information on the state of the environment is substantiated. It is proposed to develop and implement an information mechanism in the eld of environmental protection - a system of information measures of in uence (interrelated legal means that mediate the processes of collection, accumulation, analysis, storage, provision and use of reliable environmental information) on people’s behavior in order to ensure environmental protection, rational use of natural resources, environmental safety of humans and other objects.

Trajectory Compression with Spatio-Temporal Semantic Constraints

Most trajectory compression methods primarily focus on geometric similarity between compressed and original trajectories, lacking explainability of compression results due to ignoring semantic information. This paper proposes a spatio-temporal semantic constrained trajectory compression method. It constructs a new trajectory distance measurement model integrating both semantic and spatio-temporal features. This model quantifies semantic features using information entropy and measures spatio-temporal features with synchronous Euclidean distance. The compression principle is to retain feature points with maximum spatio-temporal semantic distance from the original trajectory until the compression rate is satisfied. Experimental results show these methods closely resemble each other in maintaining geometric similarity of trajectories, but our method significantly outperforms DP, TD-TR, and CascadeSync methods in preserving semantic similarity of trajectories. This indicates that our method considers both geometric and semantic features during compression, resulting in the compressed trajectory becoming more interpretable.

A Novel Three-Parameter Nadarajah Haghighi Model: Entropy Measures, Inference, and Applications

The fitting and modeling of skewed, complex, symmetric, and asymmetric datasets is an exciting research topic in many fields of applied sciences: notably, lifetime, medical, and financial sciences. This paper introduces a heavy-tailed Nadarajah Haghighi model by compounding the heavy-tailed family and Nadarajah Haghighi distribution. The model obtained has three parameters that account for the scale and shape of the distribution. The proposed distribution’s fundamental characteristics, such as the probability density, cumulative distribution, hazard rate, and survival functions, are provided, several key statistical properties are established, and several entropy information measures are proposed. Estimation of model parameters is performed via a maximum likelihood estimator procedure. Further, different simulation experiments are conducted to demonstrate the proposed estimator’s performance using measures like the average estimate, the average bias, and the associated mean square error. Finally, we apply our proposed model to analyze three different real datasets. In our illustration, we compare the practicality of the recommended model with several well-known competing models.

Anterior N2 enhancement is not a general electrophysiological index of concealed information.

Event-related potentials (ERPs) have been used with the concealed information test (CIT) to detect concealed recognition of specific stimuli (i.e., "probes"). While most research has focused on the P300 component, which is larger for infrequent probes than for frequent control stimuli (i.e., "irrelevants"), some studies have investigated an earlier ERP component, the anterior N2, with mixed results. Although some studies have reported a larger anterior N2 for probes than irrelevants (N2 enhancement), other studies, including our own, have not found such an effect. The present study aimed to replicate and extend our previous findings using the same CIT paradigm and measurement parameters. Results of Bayesian analyses show strong evidence against the hypothesis of anterior N2 enhancement by probes, replicating our previous work. Bayesian analyses also show strong evidence against the hypothesis of N2 enhancement for the three components revealed by a temporal principal component analysis (PCA) conducted to disentangle potentially overlapping ERP effects. In conclusion, whereas the CIT has shown promise in detecting recognition of specific information, anterior N2 enhancement cannot be used as an electrophysiological measure of concealed information across CIT paradigms.

Risk factors and outcomes associated with external ventricular drain related hemorrhage

ObjectiveThe objective of this study was to determine risk factors predictive of external ventricular drain (EVD)-related hemorrhage and the association of such hemorrhages with mortality, discharge disposition, length of stay (LOS), and total cost. MethodsAfter Institutional Review Board approval, data was collected retrospectively for adult patients requiring EVD placement from 2015 to 2018 at the authors’ institution. Collected data included demographic patient information, peri-procedural factors, and relevant post-procedural measures. Computerized tomography (CT) images and associated radiologic reports were independently reviewed, identifying hemorrhages accompanying EVD placement. ResultsFrom this 487-patient sample, 85 (17.5 %) patients had hemorrhages, including asymptomatic hemorrhages identified on imaging alone. A univariable analysis of patient parameters in the overall cohort was performed to identify possible predictors of hemorrhage. Age (p = 0.002), Charlson Comorbidity Index (CCI) (p < 0.001), platelet count (p = 0.002), presence of uremia (p = 0.035), and the number of times the EVD was replaced (p < 0.001) were associated with hemorrhage in univariable models. The experience of the resident surgeon based on post-graduate year (PGY level) and the number of attempts/passes needed for EVD placement were not associated with hemorrhage risk. Significant predictor of hemorrhage confirmed in a multivariable analysis only included the number of times the EVD was replaced (OR = 2.78, adjusted p < 0.001). Outcomes between EVD-related hemorrhage versus no hemorrhage groups, including mortality, discharge disposition, LOS, and cost, were compared. EVD-related hemorrhage was found to be associated with increased mortality (OR = 3.58, adjusted p < 0.001) and decreased likelihood of discharge home (OR = 0.13, adjusted p = 0.030) in the associated multivariable regressions. ConclusionThe number of times an EVD was replaced was associated with EVD-related hemorrhage outcome. EVD-related hemorrhage is associated with increased mortality and a decreased likelihood of being discharged home.

Sampling bias corrections for accurate neural measures of redundant, unique, and synergistic information.

Shannon Information theory has long been a tool of choice to measure empirically how populations of neurons in the brain encode information about cognitive variables. Recently, Partial Information Decomposition (PID) has emerged as principled way to break down this information into components identifying not only the unique information carried by each neuron, but also whether relationships between neurons generate synergistic or redundant information. While it has been long recognized that Shannon information measures on neural activity suffer from a (mostly upward) limited sampling estimation bias, this issue has largely been ignored in the burgeoning field of PID analysis of neural activity. We used simulations to investigate the limited sampling bias of PID computed from discrete probabilities (suited to describe neural spiking activity). We found that PID suffers from a large bias that is uneven across components, with synergy by far the most biased. Using approximate analytical expansions, we found that the bias of synergy increases quadratically with the number of discrete responses of each neuron, whereas the bias of unique and redundant information increase only linearly or sub-linearly. Based on the understanding of the PID bias properties, we developed simple yet effective procedures that correct for the bias effectively, and that improve greatly the PID estimation with respect to current state-of-the-art procedures. We apply these PID bias correction procedures to datasets of 53117 pairs neurons in auditory cortex, posterior parietal cortex and hippocampus of mice performing cognitive tasks, deriving precise estimates and bounds of how synergy and redundancy vary across these brain regions.

Entropic Advancement To Education

Numerous scientific fields employ entropy, the Shannonian measure of disorder and inaccessible information. Current paper examines educational uses of entropy. The major objectives of this survey are to create a coherent perspective of the applicability of classical entropies and to provide a concise detailed explanation that blends technical pertinence with conceptual extraction from the most recent literature. What's more intriguing are the closing thoughts mixed with a few unsolved issues and the creation of a future work schedule in these areas.

Radiogenomics of homologous recombination deficiency (HRD) in breast cancer: Radiomics-based image biomarker for HRD.

554 Background: Homologous recombination deficiency (HRD) in breast cancer is an actionable target, with treatment efficacy potentially linked to timely detection. Notably, BRCA1 and BRCA2 are key genes implicated in HRD, and their pathogenic germline mutations are crucial criteria for the use of poly (ADP-ribose) polymerase inhibitors (PARPi). Although germline BRCA1/2 mutations are detectable in only a small fraction (1-5%) of breast cancers, recent whole-genome sequencing (WGS) studies have revealed that up to 22% of breast cancers also exhibit HRD-like genomic characteristics, suggesting a broader potential for HRD-targeted therapy. This has spurred the development of genomic-feature-based HRD identification methods. However, the invasive and costly nature of these methods poses a challenge. This has prompted our investigation into non-invasive image biomarkers for HRD identification. Methods: Invasive breast cancer patients were recruited from March 2021 to August 2022. Eligibility criteria included availability of fresh-frozen tumor tissue for WGS and suitability for dynamic contrast-enhanced (DCE) MRI to facilitate radiomics analysis. The association between HRD and radiomic features as well as clinicopathologic factors was investigated through rigorous genomic and statistical analysis. Results: This study encompassed 145 patients aged 20 to 69 years, of whom 16.6% (24 out of 145) were genomically identified as HRD. All patients harboring pathogenic germline mutations in BRCA1 (n=3) or BRCA2 (n=2), along with concomitant somatic LOH, exhibited HRD. A comprehensive analysis of 214 radiomic features revealed that tumor sphericity, informational measure of correlation 1 (IMC1), size-zone non-uniformity normalized (SZNN), and small area emphasis (SAE) derived from subtracted early dynamic T1-weighted imaging were significantly correlated with HRD. Moreover, these radiomic features demonstrated substantial diagnostic value, as evidenced by their ROC-AUC and PR-AUC performance against baseline models: Sphericity (ROC: 0.62, p=0.055; PR: 0.22, p=0.053), SAE (ROC: 0.63, p=0.052; PR: 0.32, p=0.007), SZNN (ROC: 0.63, p=0.04; PR: 0.30, p=0.007), and IMC1 (ROC: 0.62, p=0.067; PR: 0.29, p=0.02). Additionally, our findings suggest that these radiomic features are more directly related to HRD than to the triple-negative phenotype, which is commonly linked to HRD. Conclusions: We found that four radiomic features from MRI have significant predictive value for identifying HRD in breast cancer. Given their fair predictability and immediate availability, these features are ideally suited for a screening approach, potentially identifying more patients eligible for targeted treatment. This finding represents a significant advancement in the fields of radiology and precision oncology, opening new avenues for patient-specific treatment strategies.

Analyzing the Quality of Distorted Images by the Normalized Mutual Information Measure

This research explores how different types of distorting algorithms impact the Full-Reference image quality assessment, particularly when subjective quality evaluations are incorporated. We draw upon the TID2013 database, which contains 3000 images distorted by 24 distinct algorithms, in conjunction with Mean Opinion Scores (MOS) for quality ratings. We compare the results of Normalized Mutual Information (NMI) for image quality score with W2, based on Weibull distribution, the common PSNR similarity measure and MOS. We advocate for integrating of NMI into the repertoire of image quality assessment metrics.