Original Application Research Articles

Mid-quantile regression for discrete panel data

We propose novel quantile regression methods when the response is discrete and the data come from a longitudinal design. The approach is based on conditional mid-quantiles, which have good theoretical properties even in the presence of ties. Optimization of a ridge-type penalized objective function accommodates for the data dependence. We investigate the performance and pertinence of our methods in a simulation study and an original application to macroprudential policies use in more than one hundred countries over a period of seventeen years.

Identification of Periostin Positive Cell Population During the Long-Term Culture of Mouse Tendon-Derived Cells in Late Passage.

Tendon-derived cells exhibit phenotypic changes and gradually lose their proliferative capacity during serial passages in vitro. This study aimed to characterize the changes in the growth and stem cell characteristics of tendon-derived cells over a long-term culture. Mouse flexor digitorum profundus tendon-derived cells were obtained by enzymatic digestion and seeded at an initial density of 5,000/cm2. Cells were characterized by morphology, growth, senescence staining, trilineage differentiation assays, real-time polymerase chain reaction, immunocytochemistry, flow cytometry, and RNA sequencing analysis. Tendon-derived cells underwent a proliferative stage in the first three passages, followed by a gradual senescence. However, a novel cell population expressing periostin (Postn+) emerged during the long-term culture from passages 5-8, which possessed a high rate of proliferation without significant senescence over successive passages. Compared to early passage cells, Postn+ cells exhibited enhanced osteogenic differentiation potential and attenuated chondrogenic differentiation potential, decreased expression of SSEA-1, Oct3/4, tenomodulin, scleraxis, CD90.2, CD73, CD105, Sca-1, and CD44, and increased expression of collagen III and CD34. RNA-sequencing analysis of Postn+ and early passage cells identified 908 differentially expressed genes, with extracellular matrix-receptor interaction and focal adhesion as the top pathways, and integrins as hub genes. This study highlights the dynamics of tendon-derived cells during serial passages. We identify a Postn+ cell population during long-term culture in late passages, with high proliferative ability and prominent osteogenic differentiation potential. Further investigations are needed to elucidate the origin and potential applications of Postn+ tendon-derived cells.

Mineralogy, geochemistry, origin, and potential industrial applications of kaolin deposit from Hassi Abyad, Mauritania

The Hassi Abyad kaolin deposit is in the southern part of Mauritania, around 45 km east of the town of M'Bout. Hassi Abyad lies in the middle of the Mauritanides Shield, which consists of deformed and metamorphosed Precambrian and Paleozoic formations. Complementary geological, mineralogical, and geochemical studies have been carried out to help answer questions linked to the origin of these kaolin and to determine the potential suitability for different industrial applications. The mineralogical compositions showed that Hassi Abyad kaolin is mainly composed of kaolinite (61–96%) and other minerals such as chlorite, illite, muscovite, cronstedtite, quartz, rutile, magnetite, laumontite, and gibbsite. The average chemical composition of the kaolin samples is 35.84% Al₂O₃, 45.27% SiO₂, and 14.19% LOI. Other oxides occur in low concentrations (less than1%). The higher chemical indices of alteration CIA (99.5%) and CIW (99.6%) indicate that this kaolin deposit underwent a high degree of alteration during the process of kaolinization of the source rock. The absence of high temperature minerals such as pyrite, topaz and dickite, and the presence of high Ce + Y + La and Cr + Nb contents signifies that the development and evolution of this deposit are affiliated with supergene processes. This kaolin is derived from a lateritic material, proving that they are the source rock of this deposit. The geochemical and mineralogical characteristics indicate that Hassi Abyad kaolin is applicable in ceramics, paper, cosmetics, pharmaceutics, bricks making, and pottery.

Database Decomposition to satisfy the Least Privilege Principle in Healthcare

The Multilevel Database Decomposition Framework is a cybersecurity strategy to enhance system robustness and minimize the impact of data breaches with a focus on healthcare systems. With respect to more conventional normalization methods, the framework prioritizes robustness against cyber threats over mere data redundancy reduction. The key strategy of the framework is the decomposition of a database into smaller databases to restrict user access and mitigate the impact of successful intrusions by satisfying the least privilege principle in a more complete way. For this purpose, each database the decomposition produces is uniquely associated with a set of users and the decomposition ensures that each user can access all and only the data his/her operations need. This limits the potential impact of threat agents impersonating users to the information a compromised user can access.
 To prevent the propagation of an intrusion across the databases it produces, the framework can apply alternative allocation strategies by distributing the databases to distinct virtual or physical entities according to the security requirement of the original application. This flexibility in allocation management ultimately reinforces defenses against evolving cyber threats and it is the main advantage of the deposition.
 As a counterpart of better robustness, some tables will be replicated across the databases the decomposition returns and updates of these tables should be properly replicated to prevent inconsistencies among copies of the same table in distinct databases. The paper includes a performance analysis to evaluate the overheads associated with the alternative allocations. This offers insights into the framework implementation and adaptability to distinct security needs and to evaluate the framework effectiveness for healthcare data systems.

Enhancing User Experience in Music Streaming: A React.js and Context API Approach for Spotify Clone

The evolution of web technologies has revolutionized the way music streaming platforms operate. This research paper delves into the development and implementation of a Spotify clone using React.js and Context API. The study aims to explore the efficacy of these technologies in replicating the core functionalities of the renowned music streaming service while evaluating their advantages and limitations in the context of a clone project. The research methodology involves an in-depth examination of React.js and its application in building user interfaces, along with an analysis of the Context API for state management within the Spotify clone. The paper outlines the step-by-step process of creating the clone, highlighting key architectural decisions, data handling strategies, and user experience design considerations. Additionally, this paper investigates the performance metrics, scalability, and maintenance aspects of the React.js and Context API-based Spotify clone in comparison to the original platform. The study incorporates user feedback and usability testing to evaluate the similarity in functionality and user experience between the clone and the original application. The findings of this research contribute to the understanding of leveraging React.js and Context API in replicating complex applications like Spotify. Moreover, the paper discusses the potential implications and future directions for utilizing these technologies in developing similar web-based projects. Key Word: React JS, Context API, Spotify Clone, User Interface, State Management, Web Development

Semi-parametric Spatio-Temporal Hawkes Process for Modelling Road Accidents in Rome

AbstractWe propose a semi-parametric spatio-temporal Hawkes process with periodic components to model the occurrence of car accidents in a given spatio-temporal window. The overall intensity is split into the sum of a background component capturing the spatio-temporal varying intensity and an excitation component accounting for the possible triggering effect between events. The spatial background is estimated and evaluated on the road network, allowing the derivation of accurate risk maps of road accidents. We constrain the spatio-temporal excitation to preserve an isotropic behaviour in space, and we generalize it to account for the effect of covariates. The estimation is pursued by maximizing the expected complete data log-likelihood using a tailored version of the stochastic-reconstruction algorithm that adopts ad hoc boundary correction strategies. An original application analyses the car accidents that occurred on the Rome road network in the years 2019, 2020, and 2021. Results highlight that car accidents of different types exhibit varying degrees of excitation, ranging from no triggering to a 10% chance of triggering further events.

Assessment of genetically modified maize MON 89034 × 1507 × NK603 for renewal authorisation under Regulation (EC) No 1829/2003 (application GMFF-2022-3670).

Following the submission of dossier GMFF-2022-3670 under Regulation (EC) No 1829/2003 from Corteva Agriscience Belgium BV and Bayer Agriculture BV, the Panel on genetically modified organisms of the European Food Safety Authority was asked to deliver a scientific risk assessment on the data submitted in the context of the renewal of authorisation application for the herbicide-tolerant and insect-resistant genetically modified maize MON 89034 × 1507 × NK603, for food and feed uses, excluding cultivation within the European Union. The data received in the context of this renewal application contained post-market environmental monitoring reports, a systematic search and evaluation of literature, updated bioinformatic analyses and a search for additional documents or studies performed by or on behalf of the applicant. The GMO Panel assessed these data for possible new hazards, modified exposure or new scientific uncertainties identified during the authorisation period and not previously assessed in the context of the original application. Under the assumption that the DNA sequences of the events in maize MON 89034 × 1507 × NK603 considered for renewal are identical to the sequences of the originally assessed events, the GMO Panel concludes that there is no evidence in renewal dossier GMFF-2022-3670 for new hazards, modified exposure or scientific uncertainties that would change the conclusions of the original risk assessment on maize MON 89034 × 1507 × NK603.

Assessment of genetically modified maize MON 89034 × 1507 × MON 88017 × 59122 and 8 out of 10 of its subcombinations for renewal authorisation under Regulation (EC) No 1829/2003 (dossier GMFF-2022-9170).

Following the joint submission of dossier GMFF-2022-9170 under Regulation (EC) No 1829/2003 from Bayer Agriculture B.V. and Corteva Agriscience Belgium B.V., the Panel on genetically modified organisms of the European Food Safety Authority was asked to deliver a scientific risk assessment on the data submitted in the context of the renewal of authorisation application for the herbicide tolerant and insect resistant genetically modified maize MON 89034 × 1507 × MON 88017 × 59122 and 8 out of 10 of its subcombinations, for food and feed uses, excluding cultivation within the European Union. The data received in the context of this renewal application contained post-market environmental monitoring reports, an evaluation of the literature retrieved by a scoping review, a search for additional studies performed by or on behalf of the applicant and updated bioinformatics analyses. The GMO Panel assessed these data for possible new hazards, modified exposure or new scientific uncertainties identified during the authorisation period and not previously assessed in the context of the original application. Under the assumption that the DNA sequences of the events in maize MON 89034 × 1507 × MON 88017 × 59122 and 8 out of 10 of its subcombinations considered for renewal are identical to the sequences of the originally assessed events, the GMO Panel concludes that there is no evidence in renewal dossier GMFF-2022-9170 for new hazards, modified exposure or scientific uncertainties that would change the conclusions of the original risk assessment on maize MON 89034 × 1507 × MON 88017 × 59122 and 8 out of 10 of its subcombinations.

3D Non-Newtonian deposition flow and thermal simulations to evaluate the scale-up potential for material extrusion of single walled ABS parts with overhang

Material extrusion (MEX) is one of the most widely used additive manufacturing (AM) techniques for polymeric materials. In the present work, 3D simulations using Ansys Polyflow are employed to address two MEX challenges: (i) avoiding sub-optimal thermal control in the deposited part, with a too low temperature leading to a weak bond between individual strands and a too high temperature resulting in too much deformation, so that a dimensionally accurate part with the same mechanical properties of the bulk material can be printed; (ii) applicability for larger nozzle diameters away from the original application of a sub 1 mm size and going to 10 mm or more, implying a higher industrial relevance. Focus is on the scale-up potential for a single walled acrylonitrile butadiene styrene (ABS) part with an overhanging structure (e.g. 30 or 45°) and strand aspect ratios between 2 and 4, considering up to 4 layers in the simulations. The small scale results are experimentally validated, showcasing the relevance of accurate 3D deposition simulations at other scales with more difficult validation procedures. It is shown that upscaling of the MEX process changes the cooling mechanism from conduction to convection driven. It is further demonstrated how simulations can be used to predict the failure of a print at a given scale and how the printing speed can be adapted to avoid such failure.

Z2F: Heterogeneous graph-based Android malware detection.

Android malware is becoming more common, and its invasion of smart devices has brought immeasurable losses to people's lives. Most existing Android malware detection methods extract Android features from the original application files without considering the high-order hidden information behind them, but these hidden information can reflect malicious behaviors. To solve this problem, this paper proposes Z2F, a detection framework based on multidimensional Android feature extraction and graph neural networks for Android applications. Z2F first extracts seven types of Android features from the original Android application and then embeds them into a heterogeneous graph. On this basis, we design 12 kinds of meta-structures to analyze different semantic spaces of heterogeneous graphs, mine high-order hidden semantic information, and adopt a multi-layer graph attention mechanism to iteratively embed and update information. In this paper, a total of 14429 Android applications were detected and 1039726 Android features were extracted, with a detection accuracy of 99.7%.

BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification

ABSTRACT The accurate classification of non-coding RNA (ncRNA) sequences is pivotal for advanced non-coding genome annotation and analysis, a fundamental aspect of genomics that facilitates understanding of ncRNA functions and regulatory mechanisms in various biological processes. While traditional machine learning approaches have been employed for distinguishing ncRNA, these often necessitate extensive feature engineering. Recently, deep learning algorithms have provided advancements in ncRNA classification. This study presents BioDeepFuse, a hybrid deep learning framework integrating convolutional neural networks (CNN) or bidirectional long short-term memory (BiLSTM) networks with handcrafted features for enhanced accuracy. This framework employs a combination of k-mer one-hot, k-mer dictionary, and feature extraction techniques for input representation. Extracted features, when embedded into the deep network, enable optimal utilization of spatial and sequential nuances of ncRNA sequences. Using benchmark datasets and real-world RNA samples from bacterial organisms, we evaluated the performance of BioDeepFuse. Results exhibited high accuracy in ncRNA classification, underscoring the robustness of our tool in addressing complex ncRNA sequence data challenges. The effective melding of CNN or BiLSTM with external features heralds promising directions for future research, particularly in refining ncRNA classifiers and deepening insights into ncRNAs in cellular processes and disease manifestations. In addition to its original application in the context of bacterial organisms, the methodologies and techniques integrated into our framework can potentially render BioDeepFuse effective in various and broader domains.

Current status and progress of research on the ADP-dependent glucokinase gene.

ADP-dependent glucokinase (ADPGK) produces glucose-6-phosphate with adenosine diphosphate (ADP) as the phosphate group donor, in contrast to ATP-dependent hexokinases (HKs). Originally found in archaea, ADPGK is involved in glycolysis. However, its biological function in most eukaryotic organisms is still unclear, and the molecular mechanism of action requires further investigation. This paper provides a concise overview of ADPGK's origin, biological function and clinical application. It aims to furnish scientific information for the diagnosis and treatment of human metabolic diseases, neurological disorders, and malignant tumours, and to suggest new strategies for the development of targeted drugs.

Modelling and Design of a Novel Integrated Heat Exchange Reactor for Oxy-Fuel Combustion Flue Gas Deoxygenation

The concentration of residual O2 in oxy-fuel combustion flue gas needs to be reduced before CO2 transportation, utilization, or storage. An original application of the printed circuit heat exchanger (PCHE) for catalytic combustion with natural gas (catalytic deoxygenation) is described for reducing the residual O2 concentration. The PCHE design features multiple adiabatic packed beds with interstage cooling and fuel injection, allowing precise control over the reaction extent and temperature within each reaction stage through the manipulation of fuel and utility flow rates. This work describes the design of a PCHE for methane–oxygen catalytic combustion where the catalyst loading is minimized while reducing the O2 concentration from 3 vol% to 100 ppmv, considering a maximum adiabatic temperature rise of 50 °C per stage. Each PCHE design differs by the number of reaction stages and its individual bed lengths. As part of the design process, a one-dimensional transient reduced-order reactor model (1D ROM) was developed and compared to temperature and species concentration axial profiles from 3D CFD simulations. The final design consists of five reaction stages and four heat exchanger sections, providing a PCHE length of 1.09 m at a processing rate of 12.3 kg/s flue gas per m3 PCHE.

Dermal Regeneration Template in the Management and Reconstruction of Burn Injuries and Complex Wounds: A Review.

Dermal scaffolds have created a paradigm shift for burn and wound management by providing improved healing and less scarring, while improving cosmesis and functionality. Dermal regeneration template (DRT) is a bilayer membrane for dermal regeneration developed by Yannas and Burke in the 1980s. The aim of this review is to summarize clinical evidence for dermal scaffolds focusing on DRT for the management and reconstruction of burn injuries and complex wounds. A comprehensive search of PubMed was performed from the start of indexing through November 2022. Articles reporting on DRT use in patients with burns, limb salvage, and wound reconstruction were included with focus on high-level clinical evidence. DRT has become an established alternative option for the treatment of full-thickness and deep partial-thickness burns, with improved outcomes in areas where cosmesis and functionality are important. In the management of diabetic foot ulcers, use of DRT is associated with high rates of complete wound healing with a low risk of adverse outcomes. DRT has been successfully used in traumatic and surgical wounds, showing particular benefit in deep wounds and in the reconstruction of numerous anatomical sites. Considerable clinical experience has accrued with the use of DRT beyond its original application for thermal injury. A growing body of evidence from clinical studies reports the successful use of DRT to improve clinical outcomes and quality of life across clinical indications at a number of anatomical sites.

Article Review: Henri Fayol, Practitioner and Theoretician - Revered and Reviled by Mildred Golden Pryor and Sonia Taneja

The primary objective of this paper is to review an article titled “Henri Fayol, practitioner and theoretician - revered and reviled” written by Mildred Golden Pryor and Sonia Taneja (2010). Pryor and Taneja (2010) critically evaluate Fayol’s theory within the contemporary business context. They argued that Fayol’s theories are valuable and relevant for organizational leaders because Fayol was a practitioner who documented theoriesthat worked best for him and his co-workers. Even though, there are a few criticisms on Fayol’s theories still his theories are applicable with some advancement as a basement for the management implications for the contemporary business world. Pryor and Taneja (2010) compare Fayol’s work with the contribution of other scholars namely, Follett, Mintzberg, Taylor, and Porter’s, while evaluating the original and current interpretation and application of Fayol’s theories. Finally, Pryor and Taneja (2010) appreciate Fayol’s contribution specially the 14 principles of management due to its more optimistic features. Therefore, it is necessary for the students, teachers, and practitioners to understand the relevance of the theories and be able to utilize, Fayol’s principles and theories for improving the organizational performance and further studies. Keyword: Article review, Henri Fayol, Practitioner, Theoretician

Political representation, the environment, and Edmund Burke: A re-reading of the Western canon through the lens of multispecies justice

A major puzzle in contemporary political theory is how to extend notions of justice to the environment. With environmental entities unable to communicate in ways that are traditionally recognised within the political sphere, their interests have largely been recognised instrumentally: only important as they contribute to human interests. In response to the multispecies justice project's call to reimagine our concepts of justice to include other-than-human beings and entities, we offer a novel reading of Edmund Burke's account of political representation that, we argue, can be applied to the environment. Burke claimed that interests are ‘unattached’ to any actual class or group, and that it is the duty of the representative to represent these unattached interests. Beyond providing an original application of Burke's work, the paper offers an alternative to the ‘allure’ of authoritarian environmentalism, an alternative which conservative thinkers may use as an entryway into debates on environmental justice.

A copula formulation for multivariate latent Markov models

AbstractWe specify a general formulation for multivariate latent Markov models for panel data, where outcomes are possibly of mixed-type (categorical, discrete, continuous). Conditionally on a time-varying discrete latent variable and covariates, the joint distribution of outcomes simultaneously observed is expressed through a parametric copula. We therefore do not make any conditional independence assumption. The observed likelihood is maximized by means of an expectation–maximization algorithm. In a simulation study, we argue how modeling the residual contemporary dependence might be crucial in order to avoid bias in the parameter estimates. We illustrate through an original application to assessment of poverty through direct and indirect indicators in a cohort of Italian households.

A Comprehensive Review on the Anti-inflammatory Activity of Chalconesderived Moieties

Background: In recent decades, all-embracing research accounting for thousands of natural bioactive compounds have been detailed on behalf of their origin, pharmacological activity, active phytoconstituents, and therapeutic applications. Chalcones, secondary metabolites have shown therapeutic potential against various forms of inflammation, pain, and cancer in multiple research papers targeting their pathway inhibition and their significant therapeutic activity. Area Covered: Diverse aspects of chalcones have been focused on with their biological source, pathway inhibition, and pharmacological activity. Objectives: This study aims to focus on the chalcones being the origin of ethnopharmacological, possess extensive pharmacological activities, including anti-neoplastic, antimicrobial, anti-inflammatory, antioxidant, anti-acne, anti-aging, hepatoprotective, neuroprotective, psychoactive, anti-parasitic, and many others. Method: Chalcones display anti-inflammatory activity via COX-2, NO synthase, and TNF-α inhibition. Furthermore, comprehensive studies will be discussed with a viewpoint of the chalcones’s role in the alleviation of inflammation. According to recent advancements, chalcones clinically have been used in the treatment of inflammation, anti-aging, oxidative stress reduction, autophagy, and apoptosis. Conclusion: This article focuses on the molecular progression of inflammation and the chalcone role in combating inflammation by targeting inflammatory mediators and pathways.

Integrating probability and big non-probability samples data to produce Official Statistics

This paper introduces the pseudo-calibration estimators, a novel method that integrates a non-probability sample of big size with a probability sample, assuming both samples contain relevant information for estimating the population parameter. The proposed estimators share a structural similarity with the adjusted projection estimators and the difference estimators but they adopt a different inferential approach and informative setup. The pseudo-calibration estimators can be employed when the target variable is observed in the probability sample and, in the non-probability sample, it is observed correctly, observed with error, or predicted. This paper also introduces an original application of the jackknife-type method for variance estimation. A simulation study shows that the proposed estimators are robust and efficient compared to the regression data integration estimators that use the same informative setup. Finally, a further evaluation using real data is carried out.

DESpace: spatially variable gene detection via differential expression testing of spatial clusters.

Spatially resolved transcriptomics (SRT) enables scientists to investigate spatial context of mRNA abundance, including identifying spatially variable genes (SVGs), i.e. genes whose expression varies across the tissue. Although several methods have been proposed for this task, native SVG tools cannot jointly model biological replicates, or identify the key areas of the tissue affected by spatial variability. Here, we introduce DESpace, a framework, based on an original application of existing methods, to discover SVGs. In particular, our approach inputs all types of SRT data, summarizes spatial information via spatial clusters, and identifies spatially variable genes by performing differential gene expression testing between clusters. Furthermore, our framework can identify (and test) the main cluster of the tissue affected by spatial variability; this allows scientists to investigate spatial expression changes in specific areas of interest. Additionally, DESpace enables joint modeling of multiple samples (i.e. biological replicates); compared to inference based on individual samples, this approach increases statistical power, and targets SVGs with consistent spatial patterns across replicates. Overall, in our benchmarks, DESpace displays good true positive rates, controls for false positive and false discovery rates, and is computationally efficient. DESpace is freely distributed as a Bioconductor R package at https://bioconductor.org/packages/DESpace.