bluuebunny/crossref_metadata_2025 huggingface dataset:
Big Data as a reform opportunity for public sector and real economy: The case of Greece
Authors: Lotsis Sotiris , Georgousis Ilias , Papakostas George A.
Published: March 2024

Background The recent economic recession has hit Greece with economic, political, and social repercussions. Structural reforms in the real economy and public sector are considered to be of paramount importance for introducing a new consumption and production paradigm to achieve sustainable economic growth. Methods The present paper aims to highlight Big Data and the Internet of Things as part of the 4th Industrial Revolution as a potential enabler for the necessary leap in the 21st century for the Greek public sector on the theoretical basis of the Unified Growth Theory and the Washington Doctrine. In the present paper, an evaluation of the Greek public sector is attempted by using two different indices, the Digital Maturity Index of the Hellenic Federation of Enterprises (SEV), and the Digital Economy and Society Index (DESI) of the EU. Results Findings strongly indicate that the introduction of digital skills in the educational system along with vocational training of older groups regarding the use of digital public services is an important factor for digital services implementation in the case of Greece. Moreover, the findings also underlie that demand for digital public services is not merely a matter of economic power. Other causes that lie in cultural, geographical, and behavioural habits should also be considered. Conclusions Greece is not in the pole position regarding Big Data implementation. High-speed broadband, both fast and ultrafast, lacks widespread availability, while prices remain relatively high compared to other European countries. Internet user skills and advanced IT skills remain mostly misused in the private and the public sector, while business digitization, e-commerce, e-Government, and e-health remain relatively low.
Using X, Facebook QR codes to optimise recruitment to a feasibility trial Enhancing Men’s Awareness of Testicular Diseases (E-MAT) in a cluster randomised Study Within A Trial (SWAT): Lessons learned.
Authors: Shiely Frances , Cooke Eoghan , McCarthy Megan , Dahly Darren , Harrington Janas , Shorter Gillian W. , Davoren Martin P. , Hegarty Josephine , Murphy Aileen , Kirby Ann , Murphy David , Robertson Steve , Rovito Michael J. , Fitzgerald Serena , O'Connor Alan , O'Riordan Mícheál , Saab Mohamad M
Published: March 2024

Background Eight out of ten adults use social media, yet its efficacy in recruitment in clinical trials remains under-explored. The purpose of this SWAT was to determine which recruitment method, X, Facebook or QR code via posters, was more efficient and cost effective for recruiting participants to the host trial. Methods A cluster randomised cross-over design evaluated three recruitment strategies, X, Facebook and QR code. Seven Gaelic Athletic Association (GAA) clubs were randomised to receive either X, Facebook, or QR code. The seven clubs were re-randomised twice more, two weeks apart. There were two primary outcomes: 1. proportion of participants who consent to participate, relative to the number of players contacted; and 2. proportion of participants who consent to participate, relative to the number of players who clicked the link to register their interest. Results Fifty participants were randomised to three recruitment methods, and 47 were retained in the host trial. Participants mainly heard about the study through friends, with some engagement via social media platforms Facebook and X, and little to no engagement with the QR code. Primary outcomes were hindered by the inability to disaggregate data by GAA club. Economic outcomes revealed QR code as the costliest strategy, and while X was cheaper than Facebook in terms of the number of clicks, Facebook demonstrated better recruitment and retention and thus reduced the costs per participant. Conclusions While the inability to disaggregate data by club was a limitation, the study revealed that Facebook outperformed X and QR codes in terms of recruitment and participant retention and was thus considered to be more cost effective. The findings emphasise the importance of considering engagement patterns and cost-effectiveness in designing recruitment strategies for clinical trials, especially within the dynamic landscape of social media use.
The genome sequence of Tenthredo notha Klug, 1814, a sawfly
Authors: Falk Steven ,   University of Oxford and Wytham Woods Genome Acquisition Lab,   Darwin Tree of Life Barcoding collective,   Wellcome Sanger Institute Tree of Life programme,   Wellcome Sanger Institute Scientific Operations: DNA Pipelines collective,   Tree of Life Core Informatics collective, Broad Gavin R. ,   Darwin Tree of Life Consortium
Published: March 2024

We present a genome assembly from an individual female Tenthredo notha (Arthropoda; Insecta; Hymenoptera; Tenthredinidae). The genome sequence is 253 megabases in span. Most of the assembly (99.91%) is scaffolded into 20 chromosomal pseudomolecules. The mitochondrial genome was also assembled and is 19.8 kilobases in length. Gene annotation of this assembly on Ensembl has identified 10,235 protein coding genes.
AIIMS ICU Rehabilitation (AIR): development and description of intervention for home rehabilitation of chronically ill tracheostomized patients
Authors: Tripathy Swagata , Shetty Asha P. , Hansda Upendra , P Nanda Kumar , Sahoo Alok Kumar , V Mahalingam , Mahapatra Sujata , Mitra Jayanta Kumar , Rao P Bhaskar , Sanyal Kasturi , Panda Itimayee , N Guruprasad , Sahoo Jagannath , Eborral Helen , Lone Nazir , Haniffa Rashan , Beane Abi
Published: March 2024

Background The paucity of state-supported rehabilitation for chronically ill patients with long-term tracheostomies has ramifications of prolonged hospital-stay, increased burden on acute-care resources, and nosocomial infections. Few interventions describe home rehabilitation of adult tracheostomized patients. Almost none involve stakeholders. This paper describes the All-India Institute of Medical Sciences (AIIMS) ICU rehabilitation (AIR) healthcare intervention developed to facilitate home rehabilitation of chronically ill tracheostomized patients. Methods The AIR intervention development was based on the experience-based codesign theory (EBCD). A core research-committee studied prevalent knowledge and gaps in the area. Patients-carer and health-care stakeholders’ experiences of barriers and facilitators to home care resulted in an intervention with interlinked components: family-carer training, equipment bank, m-health application, and follow-up, guided by the Medical Research Council (MRC) framework. Healthcare stakeholders (doctors, nurses, medical equipment vendors) and patient-carer dyads were engaged to gather experiences at various stages to form smaller codesign teams for each component. Multiple codesign meetings iteratively allowed refinement of the intervention over one year. The Template for Intervention Description and Replication (TIDieR) checklist was used to report the AIR intervention. Results The first component comprised a minimum of three bedside hands-on training sessions for carers relating to tracheostomy suction, catheter care, monitoring oxygenation, enteral feeding, skincare, and physiotherapy, buttressed by pictorial-books and videos embedded in a mobile-application. The second was an equipment-bank involving a rental-retrieval model. The third component was a novel m-health tool for two-way communication with the core group and community of other patient-carers in the project for follow-up and troubleshooting. Home visits on days 7 and 21 post-discharge assessed patient hygiene, nutrition, physiotherapy, and established contact with the nearest primary healthcare facility for the future. Conclusions Findings support the EBCD-based development using active feedback from stakeholders. Assessment of feasibility, process and effectiveness evaluation will follow.
Exact Characterization of the Jointly Optimal Restocking and Auditing Policy in Inventory Systems with Record Inaccuracy
Authors: Chehrazi Naveed
Published: March 2024

We present a continuous-time stochastic model of an inventory system with record inaccuracy. In this formulation, demand is modeled by a point process and is observable only when it leads to sales. In addition to demand that can reduce the stock, an unobservable stochastic loss process can also reduce the stock. The retailer’s goal is to identify the restocking and auditing policy that minimizes the expected discounted cost of carrying a product over an infinite horizon. We analytically characterize the optimal restocking and jointly optimal auditing policy. We prove that the optimal restocking policy is a threshold policy. Our proof of this result is based on a coupling argument that is valid for any demand and loss model. Unlike the optimal restocking policy, the jointly optimal auditing policy is not of threshold type. We show that a complete proof of this statement cannot be obtained by solely resorting to the first-order stochastic dominance property of the Bayesian shelf stock distribution induced by the demand and loss process. Instead, our characterization of the jointly optimal auditing policy is based on proving that the dynamics of the shelf stock distribution constitute a (strictly) sign-regular kernel. To our knowledge, this is the first paper that characterizes the optimal policy of a complex control problem by establishing sign regularity of its underlying Markovian dynamics. Our theoretical results lead to a fast algorithm for computing the exact jointly optimal auditing/restocking policy over the problem’s entire state space. This enables comparative statics analysis, which allows us to determine how inventory record inaccuracy affects the economic significance of various cost drivers. This, in turn, allows us to determine when or, better, under what conditions auditing can be an effective tool for reducing the total cost.
Who Captures the Value from Organizational Ratings?: Evidence from Public Schools
Authors: Hasan Sharique , Kumar Anuj
Published: March 2024

Ratings of organizations and firms have become ubiquitous. These ratings, often produced by intermediaries (including private and public organizations), are designed to aid consumers and other stakeholders in their decision making while guiding rated organizations toward performance improvement or compliance. In doing so, these intermediaries introduce new information to markets. However, disparities may exist in the ability to strategically capture the value from such ratings, often due to differential access to complementary assets among stakeholders. Consequently, this differential ability can lead to outcomes contrary to the rating institutions’ intentions. Reflecting on this dynamic, we analyze how widespread access to a prevalent type of rating—school performance information, often produced to enhance transparency and equity in educational access—has affected existing economic and social disparities in America. We leverage the staged rollout of GreatSchools.org school ratings from 2006 to 2015 to answer this question. Across various outcomes and specifications, we find that the availability of school ratings has accelerated the divergence in housing values, income distributions, education levels, and racial and ethnic composition across communities. Affluent and more educated families were better positioned to strategically leverage this new information to capture educational opportunities in communities with top schools. The uneven benefits we observe highlight how ratings can unintentionally deepen existing inequalities, thereby complicating their intended impacts.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/stsc.2023.0113 .
Kaposi’s varicelliform eruption: a potentially life-threatening complication of atopic dermatitis
Authors: Martín-Galache María , Escalona-Gil Ana María , Posado-Domínguez Luis , Jiménez-Domínguez Alejandro , Arévalo-Cenzual Alicia , López-Ávila Francisco Javier , Consuegra-Llapur Eduardo
Published: March 2024

Introduction: Kaposi’s varicelliform eruption (KVE), also known as eczema herpeticum or eczema vaccinatum, is an acute dermatosis that affects patients with chronic dermatopathies. The diagnosis is primarily clinical and is characterised by the presence of a vesicular exanthema on physical examination. The exanthema subsequently evolves into crusted lesions with typical circular ulcerations in ‘punched-out’ areas on the skin affected by the underlying dermatopathy. Case description: We present the case of a 6-year-old patient who presented to the Paediatric Emergency department with skin lesions consistent with eczema herpeticum. The patient’s management was initially outpatient; however, due to the slow progression of the condition, hospitalisation and intravenous antiviral treatment were initiated. Discussion: KVE affects patients with chronic dermatoses, especially atopic dermatitis. It is important to know the clinical presentation for an early suspicion. KVE is a medical emergency that requires prompt diagnosis and treatment. It can progress to secondary viraemia, which can be fatal in up to 10% of immunocompetent individuals and up to 50% of immunocompromised individuals. It is important to be aware of this condition and to start early treatment with antivirals, especially given the high prevalence of atopic dermatitis in our population. This condition is one of the most serious complications that can occur in these patients.
Can your disaster-recovery process stand up to ransomware?
Authors: Lattimer Dan
Published: March 2024

Ransomware remains one of the biggest threats to organisations. And most firms have tried to improve their defences against falling victim to this kind of attack. However, when the worst happens, relatively few are able to deal with the consequences. Without the ability to recover, they have no choice but to pay the ransom. And if you think your back-ups will save you, you might be in for a shock.
Why the c-suite should care about anti-money laundering
Authors: Behdin Bion
Published: March 2024

Complying with anti-money laundering (AML) regulations isn't easy, and too often it slips down the compliance priority list. But it's important that organisations develop a strong AML culture, and this needs to start with guidance from the top.
A secure decentralised finance framework
Authors: Sahu Kavita , Kumar Rajeev
Published: March 2024

The Secure Decentralised Finance Framework (SDFf) presented in this research addresses the burgeoning security challenges within the realm of decentralised finance (DeFi). As DeFi continues to redefine traditional financial paradigms, it concurrently introduces vulnerabilities that demand urgent attention. This framework offers a comprehensive and integrated approach to fortify the foundations of decentralised financial ecosystems. Focused on key components such as smart contract security, decentralised identity, oracle integrity, liquidity pool protection, governance mechanisms and regulatory compliance, the framework aims to establish a resilient architecture capable of withstanding evolving threats. Through theoretical exploration and case studies, this research article provides a valuable resource for developers, researchers and industry stakeholders navigating the dynamic landscape of secure and sustainable DeFi.
Regulation of Extension for Temporary Buildings
Authors: Sim David Gyuhyeon
Published: March 2024

While the Building Act includes a separate provision (Article 20) for temporary buildings, distinct from (permanent) buildings, it does not offer a formal definition for these temporary constructions. As a result, there arises an interpretational challenge in distinguishing between temporary buildings and buildings. The commonly accepted perspective defines temporary buildings as structures that do not satisfy the criterion of “fixed on land,” one of the requirements for a building stipulated under Article 2 of the Building Act. However, the requirement of “fixed on land” cannot be uniformly evaluated based on a single standard; instead, it necessitates a comprehensive assessment considering factors such as scale, form, structure, materials, and purpose. Consequently, and practically, there may be instances where temporary buildings, which were initially not “fixed on land,” acquire this requirement as a result of expansion. It is obvious that building permits or notifications are required when extending temporary buildings to construct (permanent) buildings. However, further consideration is necessary regarding the content and scope of such permits or notifications. If the structure resulting from extending a temporary building satisfies all the requirements for a (permanent) building, the physical changes before and after the extension would constitute an extension under the Building Act, but in terms of granting building permissibility (“건축허용성”), the extension is comparable to a new construction and therefore should be treated the same as a new construction under the Building Act. Nevertheless, the fact that a building permit for a new construction is required to extend a temporary building does not necessarily imply that “constructing a (permanent) building through extending a temporary building” is not permissible.
Polar responses in Russian across modalities and across interfaces
Authors: Esipova Maria
Published: March 2024

abstract: This paper investigates gestures and prosody in polar responses in Russian as part of a larger research program of studying meaning as it is expressed through various channels and constrained at various levels of representation and their interfaces. Based on the data on head nods and a gestural–intonational cluster used to question the rationale behind the antecedent speech act in Russian responses, it argues that gestures and intonational contours should be treated on a par with spoken words and their parts when it comes to fitting them into typologies of meaning-encoding expressions in spoken language. It also shows, based on the data on linear placement of gestural and spoken polarity markers in Russian as well as prosodic grouping in Russian (and English) polar responses, that studying gestural content and prosodic properties of utterances can help us reveal various interface constraints in natural language.
The Acquisition of Russian Word-Initial Consonant Clusters in a Russian-American English Bilingual Child: An Overview of One Child’s Exceptional Production
Authors: Kistanova Ekaterina V.
Published: March 2024

abstract: The majority of approaches to the acquisition of phonology attempt to model discrepancies between child and adult speech, with less attention given to children whose pronunciation is accurate. This is especially true in the acquisition of consonant clusters, where models attempt to explain children’s “errors” or non-adult-like production in terms of articulatory difficulty or phonological markedness effects. In this study, dense longitudinal data from one child’s third year show exceptional production of Russian word-initial consonant clusters. Though other studies suggest that sonority sequencing plays a central role in consonant cluster acquisition, no support for sonority-based generalizations are found in the naturalistic speech data of a two-year-old bilingual Russian-American English girl, Ulijana. On the contrary, sonority reversals were acquired early, while ideal sonority clines were acquired late. Alternative explanations for observed patterns include frequency effects and the articulatory difficulty of segments.
Rapid and accurate identification of stem cell differentiation stages via SERS and convolutional neural networks
Authors: Zhang Xiao , Wan Jianhui , Huang Tao , Tang Ping , Yang Liwei , Bu Xiaoya , Zhang Weina , Zhong Liyun
Published: March 2024

Monitoring the transition of cell states during induced pluripotent stem cell (iPSC) differentiation is crucial for clinical medicine and basic research. However, both identification category and prediction accuracy need further improvement. Here, we propose a method combining surface-enhanced Raman spectroscopy (SERS) with convolutional neural networks (CNN) to precisely identify and distinguish cell states during stem cell differentiation. First, mitochondria-targeted probes were synthesized by combining AuNRs and mitochondrial localization signal (MLS) peptides to obtain effective and stable SERS spectra signals at various stages of cell differentiation. Then, the SERS spectra served as input datasets, and their distinctive features were learned and distinguished by CNN. As a result, rapid and accurate identification of six different cell states, including the embryoid body (EB) stage, was successfully achieved throughout the stem cell differentiation process with an impressive prediction accuracy of 98.5%. Furthermore, the impact of different spectral feature peaks on the identification results was investigated, which provides a valuable reference for selecting appropriate spectral bands to identify cell states. This is also beneficial for shortening the spectral acquisition region to enhance spectral acquisition speed. These results suggest the potential for SERS-CNN models in quality monitoring of stem cells, advancing the practical applications of stem cells.
Optical-coherence-tomography-based deep-learning scatterer-density estimator using physically accurate noise model
Authors: Seesan Thitiya , Mukherjee Pradipta , Abd El-Sadek Ibrahim , Lim Yiheng , Zhu Lida , Makita Shuichi , Yasuno Yoshiaki
Published: March 2024

We demonstrate a deep-learning-based scatterer density estimator (SDE) that processes local speckle patterns of optical coherence tomography (OCT) images and estimates the scatterer density behind each speckle pattern. The SDE is trained using large quantities of numerically simulated OCT images and their associated scatterer densities. The numerical simulation uses a noise model that incorporates the spatial properties of three types of noise, i.e., shot noise, relative-intensity noise, and non-optical noise. The SDE’s performance was evaluated numerically and experimentally using two types of scattering phantom and in vitro tumor spheroids. The results confirmed that the SDE estimates scatterer densities accurately. The estimation accuracy improved significantly when compared with our previous deep-learning-based SDE, which was trained using numerical speckle patterns generated from a noise model that did not account for the spatial properties of noise.
Long-term upgrade strategies in multiband and multifiber optical transport networks
Authors: Patri Sai Kireet , Paz Arantxa , Wenning Mario , Müller Jasper , Mas-Machuca Carmen
Published: March 2024

Flexible-grid optical transport networks (OTNs) are currently undergoing a massive scale upgrade to bandwidth variable transceivers (BVTs) to cater to the exponential Internet traffic growth. Network operators seeking to plan future capacity in a scalable manner can also add additional bands of operations or additional fibers in the OTN. We propose two strategies for planning multiband upgrades in OTNs, which use an integer linear programming (ILP) solution and a heuristic solution with a reinforcement learning (RL)-based extension. Network simulation studies on three differently sized OTNs show that the heuristic and its RL-based extension perform extremely close to the optimal ILP-based solution while reducing execution times drastically. Finally, a techno-economic study based on what we believe to be a novel cost model highlights the cost-per-bit-per-second savings through carefully planned upgrades.
Harnessing nonlinear frequency upconversion of Talbot effect with flexible Talbot lengths
Authors: Bachimanchi Harshith , Sarkar Saumya J. , Ebrahim-Zadeh M. , Samanta G. K.
Published: March 2024

We report on a simple experimental scheme demonstrating nonlinear frequency upconversion of the Talbot effect with controllable Talbot lengths at high conversion efficiency. Using a microlens array (MLA) as an array illuminator at 1064 nm onto a 1.2-mm-thick BiBO crystal, we have observed the second harmonic Talbot effect in green at 532 nm with a Talbot length twice that of the pump Talbot length. However, the Talbot length is constant for fixed parameters of the periodic object and the laser wavelength. With the formulation of a suitable theoretical framework, we have implemented a generic experimental scheme based on the Fourier transformation technique to independently control the Talbot lengths of the MLA in both the pump and the second harmonic, overcoming the stringent dependence of MLA parameters on the self-images. Deploying the current technique, we have been able to tune the Talbot lengths from z
T
 = 26 cm to z
T
 = 62.4 cm in the pump and z
T
 = 12.4 cm to z
T
 = 30.8 cm in the second harmonic, respectively. The single pass conversion efficiency of the Talbot images is 2.91% W−1, an enhancement of a factor of 106 as compared to the previous reports. This generic experimental scheme can be used to generate long-range self-images of periodic structures and also to program desired Talbot planes at required positions at both pump and upconverted frequency to avoid any mechanical constraints of experiments.
ICF-PR-Net: a deep phase retrieval neural network for X-ray phase contrast imaging of inertial confinement fusion capsules
Authors: Shi Kaijun , Zhang Xing , Wang Xin , Xu Jie , Mu Baozhong , Yan Ji , Wang Feng , Ding Yongkun , Wang Zhanshan
Published: March 2024

X-ray phase contrast imaging (XPCI) has demonstrated capability to characterize inertial confinement fusion (ICF) capsules, and phase retrieval can reconstruct phase information from intensity images. This study introduces ICF-PR-Net, a novel deep learning-based phase retrieval method for ICF-XPCI. We numerically constructed datasets based on ICF capsule shape features, and proposed an object–image loss function to add image formation physics to network training. ICF-PR-Net outperformed traditional methods as it exhibited satisfactory robustness against strong noise and nonuniform background and was well-suited for ICF-XPCI’s constrained experimental conditions and single exposure limit. Numerical and experimental results showed that ICF-PR-Net accurately retrieved the phase and absorption while maintaining retrieval quality in different situations. Overall, the ICF-PR-Net enables the diagnosis of the inner interface and electron density of capsules to address ignition-preventing problems, such as hydrodynamic instability growth.
Sum and difference frequency generation in a valley-photonic-crystal-like topological system
Authors: Tang Yi , Li Jia-Lin , Li Chao , Wu Jun-Fang
Published: March 2024

Nonlinear sum frequency generation (SFG) and difference frequency generation (DFG) are fundamental methods to obtain new light sources for various applications. However, most of the on-chip SFG and DFG are based on conventional resonators, lacking robustness against fabrication defects. Here, we demonstrate topologically protected SFG and DFG in a second-order topological photonic system. The mechanism is based on the nonlinear interaction between three high-Q corner modes inside dual topological band gaps. The frequency matching condition for SFG and DFG is precisely satisfied by designing a valley-photonic-crystal-like topological system, which provides more freedoms to tune the corner modes. The topological SFG and DFG are achieved with high conversion efficiency, and the underlying topological physics is revealed. This work opens up avenues toward topologically protected nonlinear frequency conversion, and can find applications in the fields of on-chip single-photon detections and optical quantum memories with robustness against defects.
Generation of pure transverse spin and nontrivial polarization structures of beams by dielectric metasurface
Authors: Chen Yuanlu , Yu Xinning , Guo Yuncheng , Wang Xiaogang , Huang Kaikai , Xu Bijun
Published: March 2024

Transverse spin, a spin component with unique characteristics, provides a new dimension for plenty of applications, such as optical trapping, imaging, and communication. Here, we analyze the pure transverse spin in the Bessel beam, which is solely present in the azimuthal direction. Based on a single layer dielectric metasurface, we efficiently generate Bessel beams with pure transverse spin in a compact optical system. As designed, the transverse spin is flexibly tunable by converting the polarization of the incident light. Furthermore, in the scattered Bessel beam, the local electromagnetic field oscillates around the transverse axis, which is perpendicular to the beam propagation. At certain positions, the local polarization ellipse degenerates into a perfect circle, resulting in a ring-periodic distribution of circularly polarized points (C points) in the beam. This suggests that the local polarization demonstrates a nontrivial periodic structure. This work deepens our understanding of spin-related physics and opens a new avenue for the study and application of transverse spins in ultracompact, flat, multifunctional nanophotonic platforms.
Optical proximity sensors using multiple quantum well didoes
Authors: Yuan Jialei , Gao Xumin , Xie Mingyuan , Shi Zheng , Cao Ziping , Wang Yongjin
Published: March 2024

InGaN/GaN multiple quantum well (MQW) diodes perform multiple functions, such as optical emission, modulation and reception. In particular, the partially overlapping spectral region between the electroluminescence (EL) and responsivity spectra of each diode results in each diode being able to sense light from another diode of the same MQW structure. Here, we present a noncontact, optical proximity sensing system by integrating an MQW-based light transmitter and detector into a tiny GaN-on-sapphire chip. Changes in the external environment modulate the light emitted from the transmitter. Reflected light is received by the on-chip MQW detector, wherein the carried external modulation information is converted into electrical signals that can be extracted. The maximum detection proximity is approximately 17 mm, and the displacement detection accuracy is within 1 mm. Based on the detection of distance, we extend the application of the sensor to vibration and pressure detection. This monolithic integration design can replace external discrete light transmitter and detector systems to miniaturize reflective sensor architectures, enabling the development of novel optical sensors.
Self-replicating artificial neural networks give rise to universal evolutionary dynamics
Authors: Shvartzman Boaz , Ram Yoav
Published: March 2024

In evolutionary models, mutations are exogenously introduced by the modeler, rather than endogenously introduced by the replicator itself. We present a new deep-learning based computational model, theself-replicating artificial neural network(SeRANN). We train it to (i) copy its own genotype, like a biological organism, which introduces endogenous spontaneous mutations; and (ii) simultaneously perform a classification task that determines its fertility. Evolving 1,000 SeRANNs for 6,000 generations, we observed various evolutionary phenomena such as adaptation, clonal interference, epistasis, and evolution of both the mutation rate and the distribution of fitness effects of new mutations. Our results demonstrate that universal evolutionary phenomena can naturally emerge in a self-replicator model when both selection and mutation are implicit and endogenous. We therefore suggest that SeRANN can be applied to explore and test various evolutionary dynamics and hypotheses.
p53 dosage can impede KrasG12D- and KrasQ61R-mediated tumorigenesis
Authors: Le Roux Özgün , Everitt Jeffery I. , Counter Christopher M.
Published: March 2024

Mice engineered with a G12D versus Q61R mutation in Kras exhibited differences in tumorigenesis. Namely, the incidence or grade of oral or forestomach squamous epithelial lesions was more prevalent in the KrasG12Dbackground while hematolymphopoietic disease was more prevalent in the KrasQ61Rbackground. Loss of theTrp53gene encoding the tumor suppressor p53 enhances the ability of oncogenic Kras to initiate tumorigenesis in carcinogen and genetic models of lung cancer. Conversley, an extra copy ofTrp53(Super p53) was recently shown to suppress Kras-induced tumorigenesis in a genetic model of this disease. Given this, we evaluated whether an extra copy ofTrp53would alter tumorigenesis upon global activation of a modifiedKrasallele engineered with either a G12D or Q61R mutation. We report that an increase in p53 dosage significantly reduced the incidence or grade of oral and forestomach squamous tumors induced by either G12D and Q61R-mutant Kras. The incidence of myeloproliferative disease was also significantly reduced with increased p53 dosage in theKrasQ61Rbackground. Both the percentage of mice with lung tumors and total number of adenomas per animal were unchanged. However, the incidence and grade of peripheral atypical alveolar hyperplasia was significantly decreased in both backgrounds with increased p53 dosage. Finally, the number of foci of bronchioloalveolar hyperplasia per animal significantly increased with increased p53 dosage in theKrasG12Dbackground. These results suggest that an extra copy of p53 can impede oncogenic Kras driven tumorigenesis in some tissues.
Product innovation design process combined Kano and TRIZ with AD: Case study
Authors: Rong Hui , Liu Wei , Li Jin , Zhou Ziqian
Published: March 2024

In the era of rapid product iteration, companies need simple and effective methods to guide the entire process of product innovation design and enhance their product innovation capabilities. Most research focused on improving one or several steps in the product design process. Although some scholars have proposed methods that guided the entire process, they combined more than three different theories, which increased the difficulty of theoretical learning and the complexity of practical implementation. This paper proposed a product innovation design process composed of three theoretical methods: Kano, Axiomatic Design (AD), and Theory of the Solution of Inventive Problems (TRIZ). This new process guided the entire product design process with fewer theoretical methods, reducing the difficulty of learning and implementation. The paper demonstrated the effectiveness of this method through the design practice of a portable two-wheeled self-balancing vehicle. Additionally, the discussion section explored the method’s potential from the design management perspective.
National-scale spatiotemporal patterns of vegetation fire occurrences using MODIS satellite data
Authors: Mupfiga Upenyu Naume , Mutanga Onisimo , Dube Timothy
Published: March 2024

As the risk of climate change increases, robust fire monitoring methods become critical for fire management purposes. National-scale spatiotemporal patterns of the fires and how they relate to vegetation and environmental conditions are not well understood in Zimbabwe. This paper presents a spatially explicit method combining satellite data and spatial statistics in detecting spatiotemporal patterns of fires in Zimbabwe. The Emerging Hot Spot Analysis method was utilized to detect statistically significant spatiotemporal patterns of fire occurrence between the years 2002 and 2021. Statistical analysis was done to determine the association between the spatiotemporal patterns and some environmental variables such as topography, land cover, land use, ecoregions and precipitation. The highest number of fires occurred in September, coinciding with Zimbabwe’s observed fire season. The number of fires significantly varied among seasons, with the hot and dry season (August to October) recording the highest fire counts. Additionally, although June, July and November are not part of the official fire season in Zimbabwe, the fire counts recorded for these months were relatively high. This new information has therefore shown the need for revision of the fire season in Zimbabwe. The northern regions were characterized by persistent, oscillating, diminishing and historical spatiotemporal fire hotspots. Agroecological regions IIa and IIb and the Southern Miombo bushveld ecoregion were the most fire-prone areas. The research findings also revealed new critical information about the spatiotemporal fire patterns in various terrestrial ecoregions, land cover, land use, precipitation and topography and highlighted potential areas for effective fire management strategies.
Construction and analysis of a network of exercise-induced mitochondria-related non-coding RNA in the regulation of diabetic cardiomyopathy
Authors: Wang Shuo , Li Jiacong , Zhao Yungang
Published: March 2024

Diabetic cardiomyopathy (DCM) is a major factor in the development of heart failure. Mitochondria play a crucial role in regulating insulin resistance, oxidative stress, and inflammation, which affect the progression of DCM. Regular exercise can induce altered non-coding RNA (ncRNA) expression, which subsequently affects gene expression and protein function. The mechanism of exercise-induced mitochondrial-related non-coding RNA network in the regulation of DCM remains unclear. This study seeks to construct an innovative exercise-induced mitochondrial-related ncRNA network. Bioinformatic analysis of RNA sequencing data from an exercise rat model identified 144 differentially expressed long non-coding RNA (lncRNA) with cutoff criteria of p< 0.05 and fold change ≥1.0. GSE6880 and GSE4745 were the differentially expressed mRNAs from the left ventricle of DCM rat that downloaded from the GEO database. Combined with the differentially expressed mRNA and MitoCarta 3.0 dataset, the mitochondrial located gene Pdk4 was identified as a target gene. The miRNA prediction analysis using miRanda and TargetScan confirmed that 5 miRNAs have potential to interact with the 144 lncRNA. The novel lncRNA-miRNA-Pdk4 network was constructed for the first time. According to the functional protein association network, the newly created exercise-induced ncRNA network may serve as a promising diagnostic marker and therapeutic target, providing a fresh perspective to understand the molecular mechanism of different exercise types for the prevention and treatment of diabetic cardiomyopathy.
A realistic mixture of ubiquitous persistent organic pollutants affects bone and cartilage development in zebrafish by interaction with nuclear receptor signaling
Authors: Guerrero-Limón Gustavo , Zappia Jérémie , Muller Marc
Published: March 2024

"Persistent organic pollutants (POPs)" have a plethora of deleterious effects on humans and the environment due to their bioaccumulative, persistent, and mimicking properties. Individually, each of these chemicals has been tested and its effects measured, however they are rather found as parts of complex mixtures of which we do not fully grasp the extent of their potential consequences. Here we studied the effects of realistic, environmentally relevant mixtures of 29 POPs on cartilage and bone development using zebrafish as a model species. We observed developmental issues in cartilage, in the form of diverse malformations such as micrognathia, reduced size of the Meckel’s and other structures. Also, mineralized bone formation was disrupted, hence impacting the overall development of the larvae at later life stages. Assessment of the transcriptome revealed disruption of nuclear receptor pathways, such as androgen, vitamin D, and retinoic acid, that may explain the mechanisms of action of the compounds within the tested mixtures. In addition, clustering of the compounds using their chemical signatures revealed structural similarities with the model chemicals vitamin D and retinoic acid that can explain the effects and/or enhancing the phenotypes we witnessed. Further mechanistic studies will be required to fully understand this kind of molecular interactions and their repercussions in organisms. Our results contribute to the already existing catalogue of deleterious effects caused by exposure to POPs and help to understand the potential consequences in at risk populations.
Examining factors related to low performance of predicting remission in participants with major depressive disorder using neuroimaging data and other clinical features
Authors: Wang Junying , Wu David D. , DeLorenzo Christine , Yang Jie
Published: March 2024

Major depressive disorder (MDD), a prevalent mental health issue, affects more than 8% of the US population, and almost 17% in the young group of 18–25 years old. Since Covid-19, its prevalence has become even more significant. However, the remission (being free of depression) rates of first-line antidepressant treatments on MDD are only about 30%. To improve treatment outcomes, researchers have built various predictive models for treatment responses and yet none of them have been adopted in clinical use. One reason is that most predictive models are based on data from subjective questionnaires, which are less reliable. Neuroimaging data are promising objective prognostic factors, but they are expensive to obtain and hence predictive models using neuroimaging data are limited and such studies were usually in small scale (N<100). In this paper, we proposed an advanced machine learning (ML) pipeline for small training dataset with large number of features. We implemented multiple imputation for missing data and repeated K-fold cross validation (CV) to robustly estimate predictive performances. Different feature selection methods and stacking methods using 6 general ML models including random forest, gradient boosting decision tree, XGBoost, penalized logistic regression, support vector machine (SVM), and neural network were examined to evaluate the model performances. All predictive models were compared using model performance metrics such as accuracy, balanced accuracy, area under ROC curve (AUC), sensitivity and specificity. Our proposed ML pipeline was applied to a training dataset and obtained an accuracy and AUC above 0.80. But such high performance failed while applying our ML pipeline using an external validation dataset from the EMBARC study which is a multi-center study. We further examined the possible reasons especially the site heterogeneity issue.
Changes in the intestinal microbiota of individuals with non-alcoholic fatty liver disease based on sequencing: An updated systematic review and meta-analysis
Authors: Cai Wenpin , Qiu Ting , Hu Weitao , Fang Taiyong
Published: March 2024

Background

Alterations in the composition and abundance of the intestinal microbiota occur in non-alcoholic fatty liver disease (NAFLD). However, the results are inconsistent because of differences in the study design, subject area, and sequencing methodology. In this study, we compared the diversity and abundance of the intestinal microbiota of patients with NAFLD and healthy individuals through a systematic review and meta-analysis.

Methods

Three databases (PubMed, EMBASE, and Cochrane Library) were searched from their inception to March 20, 2023. A meta-analysis was performed using Stata software to analyze variations in the richness and abundance of the intestinal microbiota in patients with NAFLD. The Newcastle-Ottawa Quality Assessment Scale (NOS) was used for quality assessment.

Results

A total of 28 articles were included. Shannon diversity was reduced in patients with NAFLD (SMD = -0.24 (95% CI -0.43–0.05, I2 = 71.7%). The relative abundance of Ruminococcus, Faecalibacterium, and Coprococcus all decreased, with total SMDs of -0.96 (95% CI -1.29 to -0.63, I2 = 4.8%), -1.13 (95% CI -2.07 to -0.19, I2 = 80.5%), and -1.66 (95% CI -3.04 to -0.28, I2 = 91.5%). Escherichia was increased in individuals with NAFLD (SMD = 1.78, 95% CI 0.12 to 3.45, I2 = 94.4%).

Conclusion

Increasing the species diversity and altering the abundance of specific gut microbiota, including Coprococcus, Faecalibacterium, Ruminococcus, and Escherichia, may be beneficial for improving NAFLD.
Early warning on safety risk of highly aggregated tourist crowds based on VGGT-Count network model
Authors: Liu Jingjing , Wu Gengan , Liu Yao
Published: March 2024

In the era of mass tourism, more and more people are attracted by internet-famous site. With people’s demand for travel surged, tourists are getting together in one scenic spot with doubling numbers, which easily leads to high concentration of tourists with uncontrollable security risks. It needs to be highly valued by the tourism department. Monitoring and issuing warnings for crowd density in scenic areas with Highly Aggregated Tourist Crowds (HATCs) is an urgent challenge that needs to be addressed. In this paper, Highly Aggregated Tourist Crowds is taken as the research objective, and a VGGT-Count network model is proposed to forecast the density of HATCs. The experimental outcomes demonstrated a substantial improvement in counting accuracy for the ShanghaiTech B and UCF-QNRF datasets. Furthermore, the model allows for real-time monitoring of tourist attractions, enabling advanced prediction of high concentrations in scenic areas. This timely information can alert relevant authorities to implement preventive measures such as crowd control and flow regulation, thereby minimizing safety hazards.
The influence of biased technical progress on employment scale of the circulation industry: Evidence from China
Authors: Wu Zhenqiu , Yue Biqing , Dai Yue , Ge Yujin , Lu Guangmei , Zu Fei
Published: March 2024

As a leading industry in the national economy, circulation industry can not only guide production and consumption, but also play a vital role in absorbing employment. With the progress of science and technology, technical change has penetrated into the circulation industry of China, which has not only improved its development, but also affected its employment. This paper uses the standardized supply-side system approach to measure the biased technical progress of circulation industry in China and investigates the influence of the biased technical progress index on the employment scale of circulation industry in China with panel regression model. We find that the overall technical progress in China’s circulation industry during 2004–2018 is biased toward capital, and the elasticity of substitution between capital and labor is less than 1. We also find capital-biased technical progress in China’s circulation industry is negatively related to the overall employment scale of circulation industry. The heterogeneity analysis indicates that the employment of non-state-owned units in circulation industry is significantly negatively affected by capital-biased technical progress, while state-owned units doesn’t.