Efficient Information Research Articles

The Dual Effect of Lithium Chloride on the Efficiency of Generating Mouse-Induced Pluripotent Stem Cells

Somatic cells can be reprogrammed into induced pluripotent stem cells (iPSCs) using certain factors. The low efficiency of the reprogramming, as well as the heterogeneity of iPSCs, limits the potential application for iPSCs in cell therapy. Here, we show that lithium chloride (LiCl), a known activator of the Wnt signaling pathway, reduces or enhances the efficiency of iPSC generation from mouse embryonic fibroblasts (MEFs) depending on the timing of its addition during the reprogramming. Our results not only demonstrate a method to improve the efficiency of iPSC formation by LiCL, but also indicate its dual role in this process.

Modeling ClO2-NOM Reactions for Predicting Byproduct Formation and Micropollutant Degradation in Surface Water.

Chlorine dioxide (ClO2) is a promising alternative disinfectant/oxidant to free chlorine in drinking water treatment, while it reacts with natural organic matter (NOM) to form free chlorine, chlorite ions (ClO2-), and chlorate ions (ClO3-) as byproducts. Predicting the ClO2 consumption and the formation of these byproducts using a kinetic model helps to balance the trade-off between disinfection/oxidation efficiency and byproduct formation. This study establishes a summative equation to describe the reaction between ClO2 and ClO2-reactive moieties in the NOM (CRNOM). The average molar yields of ClO2-, free chlorine, Cl-, and ClO3- from the reactions between ClO2 and nine NOM isolates are determined to be 0.576 ± 0.017, 0.258 ± 0.022, 0.141 ± 0.010, and 0.039 ± 0.002 per consumed ClO2, respectively. The bimolecular rate constants of CRNOM toward ClO2 (kCRNOM-ClO2) are comparable among nine NOM isolates (683 ± 57 M-1·s-1 at pH 7.0). The CRNOM concentrations and kCRNOM-ClO2 increase by 2-fold and 1.3-fold, respectively, as pH increases from 6.0 to 9.0, while pH barely affects the molar yields of inorganic products. A kinetic model is established and enables the accurate prediction of ClO2- and ClO3- formation and ofloxacin degradation during ClO2 oxidation in surface water.

PENERAPAN AI DALAM SISTEM INFORMASI MANAJEMEN UNTUK MENINGKATKAN EFISIENSI BISNIS (APPLICATION OF AI IN MANAGEMENT INFORMATION SYSTEM TO IMPROVE BUSINESS EFFICIENCY)

Increasing business efficiency is the main goal for every company. As technology develops, AI has emerged as a potential solution to increase efficiency in various aspects of business, including management information systems. This journal discusses the application of artificial intelligence in management information systems to improve business efficiency. It discusses how artificial intelligence can help in data processing, analysis, decision making, and automation of various business processes. Apart from that, this journal also discusses the challenges and opportunities faced in implementing artificial intelligence, as well as providing recommendations for effective implementation. It is hoped that this research can contribute to the development of smarter and more efficient management information systems, as well as help companies achieve more optimal business goals.

Exploring multifractality in African stock markets: A multifractal detrended fluctuation analysis approach

This paper investigates the multifractal behavior of the six largest African stock markets, including the Johannesburg, Casablanca, Botswana, Nigerian, Egyptian, and Regional Stock Exchanges. Despite the growing significance of these markets in the global economy, there is limited understanding of their underlying dynamics, particularly regarding their multifractal properties. This lack of knowledge raises concerns about the informational efficiency of these markets, as traditional models may not adequately capture the complexities of price movements. To achieve the goals of the study, the Multifractal Detrended Fluctuation Analysis (MF-DFA) method is applied to capture the multifractal dynamics, and shuffling and phase randomization techniques are performed to identify the sources of the multifractality of the six African stock markets. The empirical results, derived from the generalized Hurst exponents, Rényi exponents, and Singularity spectrum, show that all six stock markets display multifractal behavior, characterized by irregular and complex price movements that vary across different scales and timeframes. Additionally, the study finds that both long-term correlations and heavy-tailed distributions contribute to the observed multifractality. Long-term correlations lead to persistent price trends, challenging the Efficient Market Hypothesis (EMH), while heavy tails increase market unpredictability by raising the likelihood of extreme events like crashes or booms. The findings have significant practical implications for stakeholders in African stock markets, enabling investors and portfolio managers to enhance risk assessment and develop effective trading strategies while helping market regulators improve efficiency and stability through appropriate policies. Financial institutions can also refine risk management frameworks to better account for extreme events.

Prospects of using blockchain technology in the field of information protection in state institutions

Blockchain technologies are rapidly gaining popularity in various industries due to their ability to provide reliable data protection, transparency and decentralization. They become especially important in the telecommunications, where the storage, processing, transmission and management of data are of critical importance, especially the military industry. The implementation of blockchain technology can significantly increase the level of security, efficiency and reliability in the mentioned industry, solving the problems of centralization and vulnerability to attacks. The use of blockchain technologies, due to their decentralization, will significantly increase the security of information and communication systems, due to the distributed architecture, where data is stored on numerous independent nodes, which makes their mass destruction or modification difficult. The absence of a single point of failure reduces the risks of breaches, and consensus mechanisms provide verification and protection against unauthorized changes. In general, this technology allows for the creation of more stable, reliable and protected systems, which will significantly reduce the loss of personnel, equipment and property. The purpose of this scientific researching is to analyze the current state and existing problematic issues, which the authors propose to solve with the help of the development and implementation of blockchain technologies in the telecommunications industry, in particular, billing operations, roaming, user identity management, and the researching of the possibilities of automating processes using smart contracts, which will allow to increase the efficiency of information and communication systems, due to increasing the speed of data transmission and optimizing their work. Further scientific research, according to the authors, can be aimed at the possibility of scaling and reducing energy consumption of the using of blockchain technology, as well as its integration with other technologies, such as artificial intelligence and quantum technologies.

Predicting HCN, HCO^+, multitransition CO, and dust emission of star-forming galaxies. Extension to luminous infrared galaxies and the role of cosmic-ray ionization

The specific star formation rate of star-forming main sequence galaxies significantly decreased since $z 1.5$ because the molecular gas fraction and star formation efficiency decreased. The gas velocity dispersion decreased within the same redshift range and is apparently correlated with the star formation efficiency (inverse of the molecular gas depletion time). However, the radio--infrared (IR) correlation has not changed significantly since $z 1.5$. The theory of turbulent clumpy star-forming gas disks together with the scaling relations of the interstellar medium describes the large- and small-scale properties of galactic gas disks. We extend our previous work on the IR multitransition molecular line, and radio continuum emission of local and high-z star-forming and starburst galaxies to local and $z 0.5$ luminous IR galaxies. The model reproduces the IR luminosities, CO, HCN, and HCO$^+$ line luminosities, and the CO spectral line energy distributions of these galaxies. We derived CO(1-0) and HCN(1-0) conversion factors for all galaxy samples. The relation between the star formation rate per unit area and the H$_2$ surface density cannot be fit simply for all redshifts. The star formation efficiency, the product of the gas turbulent velocity dispersion, and the angular velocity of the galaxies are tightly correlated. Galaxies with lower stellar masses can in principle compensate their gas consumption via star formation by radial viscous gas accretion. The limiting stellar mass increases with redshift. The radio continuum emission is directly proportional to the density of cosmic-ray (CR) electrons, but the molecular line emission depends on the CR ionization rate via the gas chemistry. The normalization of the CR ionization rate we found for the different galaxy samples is higher by about a factor of three to five than the normalization for the solar neighborhood. This means that the mean yield of low-energy CR particles for a given star formation rate per unit area is higher by about three to ten times in external galaxies than was observed by Voyager I.

Examining the Information Efficiency of Indonesia Equity Market: Evidence from Earnings Announcements

The main objective of this study is to examine the semi-strong form of market efficiency in the Indonesia Equity Market on publicly available information. The study uses a market model to analyze the significance of abnormal returns before and after earnings releases. It analyzes the cumulative average abnormal returns of the daily trades before and after the earnings release. The study reveals that there are no significant abnormal returns during the pre-announcement periods, suggesting that there is no significant leakage of information before the disclosures. An analysis of the post-announcement documents reveals a delay in the market response, indicating that the market is inefficient in rapidly and accurately transmitting the information from earnings releases to investors. It also observes significant abnormal returns within the initial week of the release periods and a post-earnings announcement drift of up to 30 days. The findings indicate that the market does not possess the attributes of a semi-strong form of market efficiency. The results imply that the market’s financial reporting processes have the potential for digital technology improvement to enhance transparency, accountability, and information efficiency within the market.

On the universality of star formation efficiency in galaxies

We analyze high-resolution hydrodynamics simulations of an isolated disk dwarf galaxy with an explicit model for unresolved turbulence and turbulence-based star formation prescription. We examine the characteristic values of the star formation efficiency per free-fall time, ϵff, and its variations with local environment properties, such as metallicity, UV flux, and surface density. We show that the star formation efficiency per free-fall time in ≈10 pc star-forming regions of the simulated disks has values in the range ϵff≈0.01−0.1, similar to observational estimates, with no trend with metallicity and only a weak trend with the UV flux. Likewise, estimated using projected patches of 500 pc size does not vary with metallicity and shows only a weak trend with average UV flux and gas surface density. The characteristic values of ϵff≈0.01−0.1 arise naturally in the simulations via the combined effect of dynamical gas compression and ensuing stellar feedback that injects thermal and turbulent energy. The compression and feedback regulate the virial parameter, αvir, in star-forming regions, limiting it to αvir≈3−10. Turbulence plays an important role in the universality of ϵff because turbulent energy and its dissipation are not sensitive to metallicity and UV flux that affect thermal energy. Our results indicate that the universality of observational estimates of ϵff can be plausibly explained by the turbulence-driven and feedback-regulated properties of star-forming regions.

Meneroka Pengajian Al-Quran dan Tafsir di Media Sosial Menerusi Analisis Saluran YouTube

Abstract The digitalization era has witnessed various advancements in information and communication technology. In Malaysia, in particular, society has increasingly relied on new media channels to obtain quick and efficient information, such as social media. This involves issues related to religion, the economy, politics, and more. This article aims to examine YouTube channels that actively upload videos related to the Quran and exegesis for sharing with the audience. Additionally, it identifies the types of applications used in these videos. This study employs a qualitative method with a content analysis approach to gather data. The results reveal that out of 80 top-ranked Islamic channels on YouTube, 40 discuss the Quran and its branches of knowledge. Furthermore, there are a variety of video formats, including webinars, lectures, forums, debates, tutorials on Tajweed, Tarannum, and Qiraat, animations created with PowerPoint, Moovly, Powtoon, kinetic typography, GoAnimate, films, daily vlogs, games, and more. Therefore, through these discussions, it is hoped that Muslims can benefit from the information and knowledge obtained from YouTube sources while ensuring their authenticity and adherence to true Islamic teachings.

Is effective coordination the key to sustainable performance? A probe into integrated e-agri supply chains in India

PurposeThe study aims to assess how e-agri supply chain coordination (SCC), supply chain integration (SCI) and competitive capabilities (COC) impact both market performance (MO) and operational performance (OP). It particularly emphasizes the critical role of information flow for the benefit of farmers, intermediaries and end-consumers, shedding light on the broader implications of these factors within the agricultural supply chain.Design/methodology/approachData are collected online from farmers, intermediaries engaged in buying/supplying agri-products and consumers using a semi-structured questionnaire of 25 items adapted from the extant literature measuring SCC, SCI, COC, OP and MP. The survey instrument is validated for its reliability, convergent and discriminant validity tests. Purposive and convenient sampling is used for data collection. Finally, 280 responses were analyzed using SEM to conclude the study.FindingsFindings underscore information flow’s significance in the e-agri supply chain, addressing various stakeholders’ needs. Technical excellence, featuring robust transaction capabilities and cost-effective maintenance is pivotal. Enhanced supply chain coordination fosters integration and efficient information sharing, enhancing agricultural market performance and sectoral efficiency.Research limitations/implicationsThe study explores technology adoption, understands information flow and coordination impact, enhances efficiencies, empowers farmers and promotes transparency, sustainability and consumer benefits.Practical implicationsThe study promotes efficient information flow, digital adoption, collaborative planning, tech investment and enhanced responsiveness for agricultural sector managers.Social implicationsThe study bridges the rural-urban divide, empowering farmers, providing fair pricing, sustainable practices, transparency, informed consumers, responsible consumption and income distribution.Originality/valueThe novelty of this study lies in its comprehensive information flow study, new theoretical model and e-agri-specific sub-constructs that define coordination and integration, aiding efficiency and competitiveness.

The impact of emotional valence on the spatial scope of visual selective attention

The brain’s ability to prioritize behaviorally relevant sensory inputs (i.e., targets) while ignoring irrelevant distractors is crucial for efficient information processing. However, the role of emotional valence in modulating selective attention remains underexplored. This study examined how positive and negative emotions alter the spatial scope of visual selective attention using a modified Eriksen Flanker task. Participants viewed an emotional face cue (happy, angry, or neutral) randomly positioned on the screen and then identified the shape of a subsequent neutral target (bowtie or diamond) at the cued location. Adjacent stimuli either matched the target shape (congruent) or differed (incongruent). Results showed that happy faces increased susceptibility to distractors (i.e., a larger incongruency effect), suggesting a broadening of attentional scope, while angry faces reduced susceptibility (i.e., a smaller incongruency effect), indicating a narrowing of focus. Importantly, the magnitude of this emotion-driven attention modulation was negatively correlated with participants’ self-reported levels of psychological distress. Participants with higher stress and depression exhibited weaker attention broadening in response to positive cues. Together, the findings provide behavioral evidence of how emotional valence influences attention scope, offering potential insights into the dynamic interplay between psychological distress, emotional processing, and attention modulation.

Reprocessing of eXpendable BathyThermograph (XBT) profiles from the Ligurian and Tyrrhenian seas over the time period 1999–2019 with a full metadata upgrade

Abstract. The advent of open science and the United Nations Decade of Ocean Science for Sustainable Development are revolutionizing the ocean-data-sharing landscape for an efficient and transparent ocean information and knowledge generation. This blue revolution raised awareness on the importance of metadata and community standards to activate interoperability of the digital assets (data and services) and guarantee that data-driven science preserves provenance, lineage and quality information for its replicability. Historical data are frequently not compliant with these criteria, lacking metadata information that was not retained, crucial at the time of data generation and further ingestion into marine data infrastructures. The present data review is an example attempt to fill this gap through a thorough data reprocessing starting from the original raw data and operational log sheets. The data gathered using XBT (eXpendable BathyThermograph) probes during several monitoring activities in the Tyrrhenian and Ligurian seas between 1999 and 2019 have first been formatted and standardized according to the latest community best practices and all available metadata have been inserted, including calibration information never applied, uncertainty specification and bias correction from Cheng et al. (2014). Secondly, a new automatic quality control (QC) procedure has been developed and a new interpolation scheme applied. The reprocessed (REP) dataset has been compared to the data version, presently available from the SeaDataNet (SDN) data access portal, processed according to the pioneering work of Manzella et al. (2003) conducted in the framework of the European Union Mediterranean Forecasting System Pilot Project (Pinardi et al., 2003). The comparison between REP and SDN datasets has the objective to highlight the main differences derived from the new data processing process. The maximum discrepancy among the REP and SDN data versions always resides within the surface layer (REP profiles are warmer than SDN ones) until 150 m depth generally when the thermocline settles (from June to November). The overall bias and root mean square difference are equal to 0.002 and 0.041 °C, respectively. Such differences are mainly due to the new interpolation technique (Barker and McDougall, 2020) and the application of the calibration correction in the REP dataset. The REP dataset (Reseghetti et al., 2024; https://doi.org/10.13127/rep_xbt_1999_2019.2) is available and accessible through the INGV (Istituto Nazionale di Geofisica e Vulcanologia, Bologna) ERDDAP (Environmental Research Division's Data Access Program) server, which allows for machine-to-machine data access in compliance with the FAIR (findable, accessible, interoperable and reusable) principles (Wilkinson et al., 2016).

Advances in Infrared Detectors for In-Memory Sensing and Computing

In-memory sensing and computing devices integrate the functionalities of sensors, memory, and processors, offering advantages such as low power consumption, high bandwidth, and zero latency, making them particularly suitable for simulating synaptic behavior in biological neural networks. As the pace of digital transformation accelerates, the demand for efficient information processing technologies is increasing, and in-memory sensing and computing devices show great potential in AI, machine learning, and edge computing. In recent years, with the continuous advancement of infrared detector technology, infrared in-memory sensing and computing devices have also seen new opportunities for development. This article reviews the latest research progress in infrared in-memory sensing and computing devices. It first introduces the working principles and performance metrics of in-memory sensing and computing devices, then discusses in detail transistors and memristor-type devices with infrared band response, and finally looks forward to the development prospects of the field. Through innovation in new semiconductor materials and structures, the development trajectory of infrared in-memory sensing and computing devices has been significantly expanded, providing new impetus for the development of a new generation of information technology.

GISphere Knowledge Graph for Geography Education: Recommending Graduate Geographic Information System/Science Programs

ABSTRACTThe growing global interest in Geographic Information System/Science (GIS) programs has led to an increased demand for higher education in this field. However, students often struggle to identify suitable programs and faculty due to the overwhelming options and the lack of personalized guidance. This paper presents GISphere‐KG, an AI‐powered platform based on the GISphere project. It combines knowledge graph (KG) and large language models (LLMs) to enhance the search and recommendation of GIS‐related graduate programs. GISphere‐KG offers four key features: (1) interactive conversation that provides natural language responses to applicants' inquiries; (2) efficient information retrieval through semantic relationships built within the KG; (3) discovery of professors whose research interests align with those of the applicants, offering more choices within specific research fields; and (4) personalized program recommendations tailored to applicants' academic and career developments. Our platform aims to provide a user‐friendly tool that assists prospective students in achieving their career goals and enriching the geography community by attracting more talent and promoting global geography education.

The Impact of Shear on Disk Galaxy Star Formation Rates

Abstract Determining the physical processes that control galactic-scale star formation rates is essential for an improved understanding of galaxy evolution. The role of orbital shear is currently unclear, with some models expecting reduced star formation rates and efficiencies with increasing shear, e.g., if shear stabilizes gas against gravitational collapse, while others predicting enhanced rates, e.g., if shear-driven collisions between giant molecular clouds trigger star formation. Expanding on the analysis of 16 galaxies by C. Suwannajak et al., we assess the shear dependence of star formation efficiency (SFE) per orbital time (ϵ orb) in 49 galaxies selected from the PHANGS-ALMA survey. In particular, we test a prediction of the shear-driven giant molecular cloud​​​​​​ (GMC) collision model that ϵ orb ∝ (1–0.7β), where β ≡ d ln v circ / d ln r , i.e., SFE per orbital time declines with decreasing shear. We fit the function ϵ orb = ϵ orb,0(1 − α CC β) finding α CC ≃ 0.76 ± 0.16; an alternative fit with ϵ orb normalized by the median value in each galaxy yields α CC * = 0.80 ± 0.15 . These results are in good agreement with the prediction of the shear-driven GMC collision theory. We also examine the impact of a galactic bar on ϵ orb finding a modest decrease in SFE in the presence of a bar, which can be attributed to lower rates of shear in these regions. We discuss the implications of our results for the GMC life cycle and environmental dependence of star formation activity.

Diverting glial glycolytic flux towards neurons is a memory-relevant role of Drosophila CRH-like signalling

An essential role of glial cells is to comply with the large and fluctuating energy needs of neurons. Metabolic adaptation is integral to the acute stress response, suggesting that glial cells could be major, yet overlooked, targets of stress hormones. Here we show that Dh44 neuropeptide, Drosophila homologue of mammalian corticotropin-releasing hormone (CRH), acts as an experience-dependent metabolic switch for glycolytic output in glia. Dh44 released by dopamine neurons limits glial fatty acid synthesis and build-up of lipid stores. Although basally active, this hormonal axis is acutely stimulated following learning of a danger-predictive cue. This results in transient suppression of glial anabolic use of pyruvate, sparing it for memory-relevant energy supply to neurons. Diverting pyruvate destination may dampen the need to upregulate glial glycolysis in response to increased neuronal demand. Although beneficial for the energy efficiency of memory formation, this mechanism reveals an ongoing competition between neuronal fuelling and glial anabolism.

Investigation of Topological properties of Butterfly Networks by Irregularity Invariants

In the modern era, networks play a crucial role in connecting individuals, organizations, and devices, enabling efficient communication, collaboration, and information exchange across the globe. They serve as the backbone of the digital age, supporting the growth of technologies such as the internet, cloud computing, IoT, and social media. The examination of Quantitative Structure Activity/Property Relationships (QSPR) to analyse the network architecture uses topological indices as its main instrument. The butterfly network is a type of interconnection network that follows a specific geometric structure. It consists of multiple stages, with each stage connecting nodes in a binary pattern. The connections between nodes form a butterfly-like shape, hence the name. The butterfly network provides efficient routing and communication paths between nodes, making it suitable for parallel computing and distributed systems. With the aid of sixteen irregularity indices, we will examine and compare three butterfly networks in this article. We will then plot the findings to see how they depend on the various parameters.

Planet Mass Function around M Stars at 1–10 au: A Plethora of Sub-Earth Mass Objects

Small planets (≲1 M ⊕) at intermediate orbital distances (∼1 au) represent an uncharted territory in exoplanetary science. The upcoming microlensing survey by the Nancy Grace Roman Space Telescope will be sensitive to objects as light as Ganymede and unveil the small planet population at 1–10 au. Instrumental sensitivity to such planets is low, and the number of objects we will discover is strongly dependent on the underlying planet mass function. In this work, we provide a physically motivated planet mass function by combining the efficiency of planet formation by pebble accretion with the observed disk mass function. Because the disk mass function for M dwarfs (0.4–0.6 M ⊙) is bottom heavy, the initial planet mass function is also expected to be bottom heavy, skewing toward Ganymede and Mars mass objects, more so for heavier initial planetary seeds. We follow the subsequent dynamical evolution of planetary systems over ∼100 Myr varying the initial eccentricity and orbital spacing. For initial planet separations of ≥3 local disk scale heights, we find that Ganymede and Mars mass planets do not grow significantly by mergers. However, Earth-like planets undergo vigorous merging and turn into super-Earths, potentially creating a gap in the planet mass function at ∼1 M ⊕. Our results demonstrate that the slope of the mass function and the location of the potential gap in the mass function can probe the initial architecture of multiplanet systems. We close by discussing implications on the expected difference between bound and free-floating planet mass functions.

Mineral and Microbial Properties Drive the Formation of Mineral-Associated Organic Matter and Its Response to Increased Temperature.

A comprehensive understanding of the formation of mineral-associated organic matter (MAOM) is a prerequisite for the sustainable management of soil carbon (C) and the development of effective long-term strategies for C sequestration in soils. Nevertheless, the precise manner by which microbial and mineral properties drive MAOM formation efficiency and its subsequent response to elevated temperature at the regional scale remains unclear. Here, we employed isotopically labelled laboratory incubations (at 15°C and 25°C) with soil samples from a ~3000 km transect across the Tibetan Plateau to elucidate the mechanisms underlying MAOM formation and its temperature response. The results indicated that both mineral protection and microbial properties were critical predictors of MAOM formation across the geographic gradient. The efficiency of MAOM formation was found to increase with the content of iron (Fe) oxides and their reactivity [i.e., the ratio of poorly crystalline Fe oxides to total Fe oxides (Feo:Fed)] but to decrease with the relative abundance of Gammaproteobacteria and Actinobacteria across the plateau. Moreover, a notable decline in MAOM formation efficiency was observed under elevated temperatures, which was concomitant with a reduction in the content and reactivity of Fe oxides, as well as the microbial assimilation of the labelled substrate. The attenuation of mineral-organic associations was identified as the primary factor contributing to the warming-induced reduction in MAOM formation. These findings highlight the necessity of incorporating organo-mineral associations and microbial properties into Earth System Models to accurately project soil C dynamics under changing climate.

Division Managers’ Private Information and Capital Investment Efficiency: Exploiting External Social Connections as an Information Source

ABSTRACT We examine the relation between division-level information and capital investment in conglomerates, exploiting the external social connections of division managers (DMs) as an information source. We find that investment efficiency, proxied by investment sensitivity to relative divisional investment opportunities, is higher for divisions whose DMs are socially connected with the CEOs of industry peers than divisions without such connections. This effect is stronger when headquarters are more likely to delegate decisions (proxied by larger information distances between headquarters and the divisions and by greater division operational uncertainties), when the DMs’ information source is more useful (proxied by the closeness of DMs’ external social connections and the information quality from the connected external CEOs), and when the DM has greater influence in the conglomerate. Further, connected divisions exhibit higher profitability in the subsequent years than unconnected divisions. Our study sheds light on how division-level information influences internal capital allocation and performance. Data Availability: Data are available from the sources cited in the text. JEL Classifications: G30; G34; M40.