bluuebunny/crossref_metadata_2025 huggingface dataset:
An Alternative Pricing Of Regulatory Components Based On Adjustments In The Relationship Between Peak And Off-Peak Tariffs In Brazil
Authors: Eichkoff Henrique S. , Bernardon Daniel P. , Garcia Vinicius J. , Silva Daiana W. , Chiara Lucas M. , Butto Sebastian A. , Barbosa Solange M. K. , Pose Alejandre C. A.
Published: August 2023

This paper presents a proposed tariff methodology for regulatory components of the distribution system use (TUSD) based on adjusting the ratio of peak to off-peak tariffs (POPR) in Brazil. The main objective of this study is to provide the TUSD component (and energy consumption terms) with lower prices for customers that use electricity for irrigation activities, called "irrigator customers" in southern Brazil. The respective paper is motivated by the relevance of this type of consumer in these regions, and also by the low number of methodologies present in the literature related to this theme. Thus, this article deals with a specific subject of Brazilian electricity regulation that has not been studied very much. The proposed methodology considers for the calculations of the TUSD components, market data of the irrigator customers, in addition to the adjustment in the current POPR to regulate the prices between the peak and off-peak components. The proposed tariff calculation framework considers and compares two analysis methods to define the answer to the problem: (i) TUSD off-peak constant and (ii) Constant TUSD Revenue. The results show considerable reductions in the prices of the Peak Energy TUSD component, making it possible for this method to be employed in the future by power utilities to encourage these customers to use electricity on a larger scale during peak hours.
Functional Analysis And Performance Evaluation Of Decoder Decision Tree Generation Algorithms
Authors: Tadros Lillian
Published: August 2023

Instruction decoders are indispensable components of instruction set simulators and processor toolchains. The lengthy and elaborate manual implementation of decoders can be greatly alleviated by decoder generation tools. These need to handle the rising complexity of modern instruction sets, notably irregularities such as non-uniform opcodes and logic propositions on bit fields. In addition, decoder generators need to provide cost-optimized solutions, as the efficiency of the decoding module can have a substantial effect on the overall performance. This paper analyzes five published algorithms for decoder generators from two perspectives: First, in terms of functionality, we systematically assess how each tool handles different properties of modern instruction sets, highlighting properties that are challenging, unhandled by current algorithms or even result in functionally erroneous decoders. Second, we challenge seemingly intuitive definitions of decoder optimality using a sophisticated model of decision tree cost. We validate this analytical model against an experimental performance evaluation of generated decoders for SPARC, MIPS32 and ARMv7 platforms. For our analysis, we implemented all five algorithms after correcting the discovered conceptual errors and extending them to handle the above-mentioned ISAs. Our work reveals that state-of-the-art decoder generation tools are unable to fully and correctly handle complex ISAs and adopt an erroneous notion of optimality.
Time Series Prediction For The Housing Construction Market With The Use Of NARNet
Authors: Wotzka Daria , Suchacka Grazyna , Mach Lukasz , Fracz Pawel , Foltys Joachim , Maniu Ionela
Published: August 2023

The paper discusses the study to develop and tune parameters of a nonlinear autoregressive neural network (NARNet or NARNN) model for predicting the number of housing units. Predictions were made for the housing construction market in Poland, which is a dynamically growing European market. Three stages of the housing construction process have been taken into considerationThe paper discusses the study to develop and tune parameters of a nonlinear autoregressive neural network (NARNet or NARNN) model for predicting the number of housing units. Predictions were made for the housing construction market in Poland, which is a dynamically growing European market. Three stages of the housing construction process have been taken into consideration: permits issued for house construction, houses under construction, and completed new houses. Experimental results have shown that a NARNet model can be a very effective tool in the considered scenario. A network model using the Levenberg-Marquardt backpropagation training function achieved the best model fit, as well as the most accurate one-month predictions.
Periodic Review Inventory Management With Budget Constraints: Discrete-Event Simulation And Sensitivity Analysis
Authors: Lysova Natalya , Solari Federico , Caccamo Damiana , Suppini Claudio , Montanari Roberto
Published: August 2023

In this study, a periodically reviewed inventory system with an order-up-to-level policy and budget constraints is considered. A discrete-event simulation model is developed to identify the optimal operating conditions, in terms of reorder period (DT) and order up to level (OUTL). Two different scenarios, characterized by different unit costs, are considered. A sensitivity analysis is finally conducted to evaluate the impact of procurement lead time and budget constraints on optimal conditions. A linear correlation between optimal DT and optimal OUTL is found and the equation of the line is derived as a function of the average daily demand and procurement lead time.
Green Hydrogen, Industrial Symbiosis, And Blockchain: Enhancing Sustainability And Resilience In Supply Chains
Authors: Savian Fernando , Tomasin da Silva Leandro , Sellitto Miguel , Sauer Oliveira Henrique Luis , Neri Alessandro , Butturi Maria Angela
Published: August 2023

The purpose of this article is to present two types of optimization models for simultaneously increasing sustainability and resilience in industrial supply chains. Sustainability increases when the chain as a whole reduces its carbon footprint. Resilience increases when increasing the supply chain's ability to recover from disruptive events. In principle, the objectives are antagonistic. Some sustainability approaches advocate that efficiency should increase, reducing supply alternatives and, consequently, the chain's resilience. This article proposes to combine two supply strategies, green hydrogen and industrial symbiosis, and a management strategy, blockchain, which can simultaneously increase sustainability and resilience. Adding sources such as green hydrogen and reusing material and energy waste generated by members of the same or another supply chain reduce the carbon footprint (by replacing fossil fuels and virgin raw materials). It also reinforces the supply chain, adding redundant edges. The article discusses the requirements of two models to optimize the implementation, one based on mixed integer linear programming and the other based on agent-based simulation. A cloud information system based on blockchain technology ensures data reliability.
IOT-Based Business Process Management For Temperature-Controlled Logistics System Of Laboratory Specimens
Authors: Chanpuypetch Wirachchaya , Supeekit Tuangyot , Niemsakul Jirawan
Published: August 2023

The transportation of laboratory specimens and raw materials for advanced therapy medicinal products (ATMP) is challenging due to the need for strict temperature control and limited delivery periods. Such transportation must be conducted with care to prevent damage or compression, which may compromise the viability and stability of the specimens. Unlike other types of materials, transportation of specimens requires more complex control measures to ensure their usefulness in laboratory examinations and biological processes. Any damage or deterioration during transportation could significantly affect patient diagnosis and treatment. The transportation logistics system for these specimens contains sensitive personal information related to patient safety and life preservation. Hence, good control, tracking, and traceability are crucial to ensure safe transportation. This research recommends an IoT-based temperature-controlled logistics system for laboratory specimens, using Business Process Model and Notation (BPMN) to efficiently manage the transportation process. This system aims to maintain specimen stability and viability, thus ensuring the safety and quality of patient treatment. Thai transport and logistics service providers can implement this system to enhance transportation safety and quality.
A Modeling And Simulation Based Assessment Of Switching Fuels For A Norwegian Fishing Vessel
Authors: Hennum Tor , Kjerstad Oivind Kare , Nerheim Ann Rigmor , Skjong Stian , Ladstein Jarle
Published: August 2023

The Norwegian fishing industry is facing increasing pressure to find more sustainable energy solutions. In response to this, a modeling and simulation based case study of a representative Norwegian pelagic trawler/purse seiner is presented to evaluate the emission reduction potential of transitioning from traditional marine gas oil to alternative fuels. The objective is to begin developing a framework for calculating relevant parameters and key performance indicators, to support more detailed analysis of various fishing activities. A data based simulation model of the fishing vessel is presented, and some potential benefits and drawbacks of switching to some alternative fuels are demonstrated, from an energy perspective. While practical challenges related to this transition were not considered in detail, our results indicate that emission reductions are achievable. We also found that the simulation results aligned closely with real-world measurements, supporting the validity of our models. The study highlights the need for continued research and development of sustainable solutions for the Norwegian fishing industry.
Software-In-The-Loop Test Bench For The Evaluation Of The Coordinative Fleet Control Approach In Intralogistics
Authors: Rothmeyer Florian , Fottner Johannes
Published: August 2023

A system coordinator for the intelligent forwarding of transport orders enables the combination of several fleets of intralogistic transport vehicles such as robots in one material flow system without them having to exchange information with each other. Evaluating the operation of this coordinator requires a simulation environment that represents all adjacent systems, creating a Software-in-the-Loop (SiL) environment. This includes upstream systems, e.g. ERP or ME systems, several fleet controllers as well as a material flow system with all vehicles including their interactions and possible failures. In this article, the conceptual design of such an SiL system is presented. Additionally, a proof-of-concept demonstrates the fundamental functionality. Python is used for the system coordinator and the analysis, openTCS for the fleet controllers and Siemens Plant Simulation for the material flow simulation. The communication in between uses HTTP and raw TCP packets, respectively.
Data-Driven Simulation In Process Mining: Introducing A Reference Model
Authors: Pourbafrani Mahsa , van der Aalst Wil M.P.
Published: August 2023

Different approaches are proposed for simulating processes in process mining. There are open challenges while designing the simulation models of processes: (1) the quality of the designed models is mostly evaluated using simulation results, and the models themselves do not get validated, (2) the choice of process aspects to be considered in the simulation models of processes as simulation parameters is rather arbitrary, e.g., considering multitasking, and (3) the distinction between the acquiring simulation parameters step and the parameters' regeneration step is not defined. This paper aims to introduce a reference meta-model for simulation in process mining. We derive the meta-model using the provided insights from process mining and the required parameters from the simulation techniques for simulating processes, i.e., Discrete Event Simulation (DES). This model enables the creation of process simulations and the comparison of approaches in relation to the process aspects under consideration. We illustrate the use of the model in practice by developing an automatic simulation model generation approach based on the reference model.
Literature Review And Comparison Of Digital Twin Frameworks In Manufacturing
Authors: Galli Erica , Fani Virginia , Bandinelli Romeo , Lacroix Sylvain , Le Duigou Julien , Eynard Benoit , Godart Xavier
Published: August 2023

Industry 4.0 technologies have led to the affirmation of the Smart Manufacturing. In this paradigm Digital Twins (DTw) are defined as simulation models that are both getting data from the field and triggering actions on the physical equipment. With this paper, our aim is to extend the existing analysis of DTw in manufacturing from a technical and architecture point of view, trying to define correlations among DTw features. This work proposes a new framework, illustrating three reference architectures for the DTw that could help to define a guideline for the design and implementation of this technology. The results found are proposed as a driver for future research, aspiring to identify an architecture enabling a complete integration between DTw in manufacturing systems.
E-Waste Tracker: A Platform To Monitor E-Waste From Collection To Recycling
Authors: Artang Sara , Hameed Ibrahim A. , Ghasemian Afshin
Published: August 2023

E-waste stands for electronic devices, such as phones, computers, and televisions, that are disposed of when they reach the end of their useful lives. E-waste is becoming one of the most rapidly growing waste streams globally. The production of e-waste is rapidly increasing due to various factors, including the rapid advancement of technology, changing customer preferences, the widespread use of non-repairable parts, and deliberate planned obsolescence during the design of such products to encourage consumers to replace their products more often, boosting sales and profits. E-waste contains precious and rare metals such as gold, silver, copper, indium, and palladium. When these materials are not properly recovered, recycled, and reused, the production of new electronics will require the mining of finite natural resources, leading to environmental damage and the depletion of resources. As of early 2019, Norway has established an Extended Producer Responsibility (EPR) system, which requires producers and importers to finance and ensure proper collection and recycling of end-of-life (EoL) e-waste, resulting in an increase in the e-waste recycling rate to approximately 91% in Norway. However, electronic waste such as mobile phones and computers often goes unrecycled. Currently, 82% of Norwegian households have at least one extra mobile phone that they are not using. People may hesitate to dispose of their electronic waste and tend to stockpile it at home for several reasons. These include feeling emotionally attached to the item due to personal memories, not knowing where or how to dispose of it, being unaware of the potential environmental and health hazards associated with improper disposal and having concerns about the data security and personal information stored on the device. To address these issues, the paper introduces a cutting-edge tracking and tracing platform that features an intuitive user interface for both users and administrators. With the proposed platform, users and administrators can easily access essential information regarding their e-waste disposal. This convenient and efficient system offers a practical solution for tracking e-waste, thereby promoting trust between device owners and the disposal process. Furthermore, the platform incentivizes users by providing them with valuable information regarding their e-waste disposal, creating a positive impact on environmental sustainability.
Matrix Similarity Analysis Of Texts Written In Romanian And Spanish
Authors: Niewiarowski Artur , Plichta Anna
Published: August 2023

This publication presents the results of a study of similarity between texts written in Romanian and Spanish, using a matrix analysis method based on Levenshtein's edit distance. The method used in the study does not contain implemented language-dependent vocabulary rules and exhibits the feature of linguistic universality in terms of similarity analysis. The study was carried out on the basis of the commercial computer program Antyplagius, created by the New Data Mining Systems company, which performs similarity analysis exclusively using the aforementioned method. The texts being compared were taken from excerpts from Wikipedia translated by online translators of popular companies which are based on artificial intelligence solutions.
Evaluation Of Synthetically Generated Traces Towards A Data-Centre Digital Twin
Authors: Fernandez-Montes Alejandro , Fernandez-Cerero Damian , Jakobik Agnieszka , Bermejo Belen , Juiz Carlos
Published: August 2023

Several approaches exist to generate synthetic data centre traces for various purposes: from augmenting operating traces for data centre simulators and digital twins to forecasting the incoming workload to improve the data centre behaviour. The evaluation of the quality of synthetically generated multivariate time-series datasets, such as those related to data-centre traces, is not a trivial task, since complex patterns and correlation between variables may be present. This paper proposes a new multivariate time-series evaluation framework that computes a set of metrics and figures that can be used to measure the quality of synthetically generated data-centre traces. We then employ the proposed tool to compare two synthetic data centre traces with the original trace and assess their quality. These synthetic traces have been generated by means of Generative Adversarial Networks (GAN). In this work, we employ TimeGAN, a GAN model focused on the generation of multivariate time series traces. We finally show how the proposed framework provides us with a set of metrics consistent with the observable behaviour and numerical insights on the quality of the generated data centre traces, which are hard to acquire otherwise.
Detrended Fluctuation Analysis Of Sentiment Patterns In Literary Texts
Authors: Gaza Lukasz , Drozdz Stanislaw , Oswiecimka Pawel , Stanuszek Marek
Published: August 2023

Temporal correlations of the sentiment content in consecutive sentences is studied based on a large corpus of world-famous literary text in four major European languages (English, French, German and Spanish). For quantifying the related characteristics in terms of the Hurst exponents the Detrended Fluctuation Analysis (DFA) is employed. The results obtained provide a clear indication for the existence of persistent correlations as revealed by the Hurst exponents significantly larger than 1/2 in all the four languages studied. An extremely interesting and worth further more systematic study is the identified fact that in many texts the DFA indicates two different regimes of scaling and thus two different Hurst exponents. In those cases - quite universally - the cross-over occurs at the scale corresponding to about 200 sentences and the Hurst exponents at the scales above this value are even larger which indicates the presence of stronger long-range temporal correlations than those at the shorter scales.
Obstructive Sleep Apnea Identification Based On VGGish Networks
Authors: Serrano Salvatore , Patane Luca , Scarpa Marco
Published: August 2023

Sleep disorders are continuously growing in the population and can have a significant negative impact on everyday life. Economic and non-invasive systems able to support the diagnosis procedure will be more and more adopted in the next years. The aim of this work is to investigate the classification performance of a convolutional neural network, based on a VGG structure, to identify obstructive sleep apnea events. A recently developed dataset containing audio signals recorded from high-quality contact microphones placed on the trachea of the subjects under study has been adopted to perform transfer learning over a pre-trained VGGish network. Spectrogram images have been extracted from the audio signals to serve as inputs for the classification process. The importance of the time window selection has been also investigated and comparisons with other recent methods proposed in the literature are reported.
Prediction Of Chemical Plants Operating Performances: A Machine Learning Approach
Authors: Campanile Lelio , Di Bonito Luigi Piero , Iacono Mauro , Di Natale Francesco
Published: August 2023

Modern environmental regulations require rigorous optimization of operations in process engineering to reduce waste, pollution, and risks while maximizing efficiency. However, the nature of chemical plants, which include components with non-linear behavior, challenges the use of consolidated tuning and control techniques. Instead, ad-hoc, self-adapting, and time-variant controls, with a balanced tuning of parameters at both the subsystem and system level, may be necessary. Needed computing processes may require significant resources and high performance systems, if managed by means of traditional approaches and with exact solution methods. In this regard, domain experts suggest instead the use of integrated techniques based on Artificial Intelligence (AI), which include Explainable AI (XAI) and Trustworthy AI (TAI), which are unique in this industry and still in the early stages of development. To pave the way for a real-time, cost-effective solution for this problem, this paper proposes an AI-based approach to model the performance of a real chemical plant, i.e. a marine scrubber installed on a Ro-Ro ship. The study aims to investigate Machine Learning (ML) techniques which can be used to model such processes. Notably, this analysis is the first of its kind, at the best of the authors’ knowledge. Overall, the study highlights the potential of using ML-based techniques, to optimize environmental compliance in the shipping industry.
Genetic determinants of periosteum-mediated craniofacial bone regeneration: a systematic review
Authors: Okoturo Eyituoyo
Published: August 2023

Background: Periosteum-mediated bone regeneration (PMBR) is a recognized method for mandibular reconstruction. Despite its unpredictable nature and the limited degree to which it is understood, it does not share the concerns of developmental changes to donor and recipient tissues that other treatment options do. The definitive role of the periosteum in bone regeneration in any mammal remains largely unexplored. The purpose of this study was to identify the genetic determinants of PMBR in mammals through a systematic review.Methods: Our search methodology was designed in accordance with the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. We conducted a quality assessment of each publication, and evaluated the differences in gene expression between days 7 and 15.Results: A total of four studies satisfied the inclusion criteria. The subjects and tissues examined in these studies were Wistar rat calvaria in two studies, mini-pigs in one study, and calves and mice in one study. Three out of the four studies achieved the necessary quality score of ≥ 3. Gene expression analysis showed increased activity of genes responsible for angiogenesis, cytokine activities, and immune-inflammatory responses on day 7. Additionally, genes related to skeletal development and signaling pathways were upregulated on day 15.Conclusions: The results suggest that skeletal morphogenesis is regulated by genes associated with skeletal development, and the gene expression patterns of PMBR may be characterized by specific pathways.
Natural course of chronic subdural hematoma following surgical clipping of unruptured intracranial aneurysm by pterional approach
Authors: Kweon Su-Bin , Kim Suchel , Kwon Min-Yong , Kim Chang-Hyun , Kwon Sae Min , Ko Yong San , Lee Chang-Young
Published: August 2023

Objective: Chronic subdural hematoma (CSDH) is a neurological complication following clipping surgery. However, the natural course and ideal approach for the treatment of clipping-related-CSDH (CR-CSDH) have not been clearly established. We aimed to investigate the course of CR-CSDH using chronological radiological findings.Methods: We performed a retrospective analysis of 28 (3.8%) patients who developed CSDH among 736 patients who underwent surgical clipping using pterional approach for unruptured aneurysms at our institution between December 2010 and December 2018. Patients underwent follow-up CT scan 6–8 weeks after clipping surgery and decision to pursue surgical intervention rests upon the patient’s symptom based on the Markwalder’s grading scale (MGS) and numeric rating scale (NRS).Results: Of the 28 patients, 3 patients (10.7%) underwent surgery, while 25 (89.2%) showed spontaneous resolution of CR-CSDH. Eighteen patients (64.2%) had mild headache with MGS of 0–1. The mean maximum hematoma volume was 41.9±30.9 ml (5.8–135 ml), and 26 patients (92.8%) had homogeneous hematoma. The mean time to hematoma resolution was 126.7±52.9 days (46–228 days). Comparing group of CR-CSDH volume ≥43 ml or a midline shift ≥5 mm, the difference in presence of linear low-density area (p=0.002) and age (p=0.026) between the conservative and operative groups were found to be statistically significant.Conclusions: Most CR-CSDH cases spontaneously resolved within 4 months. Therefore, we suggest that close observation should be performed if patient’s symptoms are mild and special radiologic findings are present, despite its relatively large volume and midline shifting.
Adult-born granule cells improve stimulus encoding and discrimination in the dentate gyrus
Authors: Arribas Diego M , Marin-Burgin Antonia , Morelli Luis G
Published: August 2023

Heterogeneity plays an important role in diversifying neural responses to support brain function. Adult neurogenesis provides the dentate gyrus with a heterogeneous population of granule cells (GCs) that were born and developed their properties at different times. Immature GCs have distinct intrinsic and synaptic properties than mature GCs and are needed for correct encoding and discrimination in spatial tasks. How immature GCs enhance the encoding of information to support these functions is not well understood. Here, we record the responses to fluctuating current injections of GCs of different ages in mouse hippocampal slices to study how they encode stimuli. Immature GCs produce unreliable responses compared to mature GCs, exhibiting imprecise spike timings across repeated stimulation. We use a statistical model to describe the stimulus-response transformation performed by GCs of different ages. We fit this model to the data and obtain parameters that capture GCs’ encoding properties. Parameter values from this fit reflect the maturational differences of the population and indicate that immature GCs perform a differential encoding of stimuli. To study how this age heterogeneity influences encoding by a population, we perform stimulus decoding using populations that contain GCs of different ages. We find that, despite their individual unreliability, immature GCs enhance the fidelity of the signal encoded by the population and improve the discrimination of similar time-dependent stimuli. Thus, the observed heterogeneity confers the population with enhanced encoding capabilities.
MMP12 serves as an immune cell–related marker of disease status and prognosis in lung squamous cell carcinoma
Authors: Zhang Wei , Li Guo-Sheng , Gan Xiang-Yu , Huang Zhi-Guang , He Rong-Quan , Huang Hong , Li Dong-Ming , Tang Yu-Lu , Tang Deng , Zou Wen , Liu Jun , Dang Yi-Wu , Chen Gang , Zhou Hua-Fu , Kong Jin-Liang , Lu Hui-ping
Published: August 2023

Background

Worldwide, lung squamous cell carcinoma (LUSC) has wreaked havoc on humanity. Matrix metallopeptidase 12 (MMP12) plays an essential role in a variety of cancers. This study aimed to reveal the expression, clinical significance, and potential molecular mechanisms of MMP12 in LUSC.

Methods

There were 2,738 messenger RNA (mRNA) samples from several multicenter databases used to detect MMP12 expression in LUSC, and 125 tissue samples were validated by immunohistochemistry (IHC) experiments. Receiver operator characteristic (ROC) curves, Kaplan–Meier curves, and univariate and multivariate Cox regression analyses were used to assess the clinical value of MMP12 in LUSC. The potential molecular mechanisms of MMP12 were explored by gene enrichment analysis and immune correlation analysis. Furthermore, single-cell sequencing was used to determine the distribution of MMP12 in multiple tumor microenvironment cells.

Results

MMP12 was significantly overexpressed at the mRNA level (p < 0.05, SMD = 3.13, 95% CI [2.51–3.75]), which was verified at the protein level (p < 0.001) by internal IHC experiments. MMP12 expression could be used to differentiate LUSC samples from normal samples, and overexpression of MMP12 itself implied a worse clinical prognosis and higher levels of immune cell infiltration in LUSC patients. MMP12 was involved in cancer development and progression through two immune-related signaling pathways. The high expression of MMP12 in LUSC might act as an antigen-presenting cell–associated tumor neoantigen and activate the body’s immune response.

Conclusions

MMP12 expression is upregulated in LUSC and high expression of MMP12 serves as a risk factor for LUSC patients. MMP12 may be involved in cancer development by participating in immune-related signaling pathways and elevating the level of immune cell infiltration.
Life-expectancy changes during the COVID-19 pandemic from 2019–2021: estimates from Japan, a country with low pandemic impact
Authors: Munira Mst Sirajum , Okada Yuta , Nishiura Hiroshi
Published: August 2023

Background

The COVID-19 pandemic had a low impact on Japan in 2020, but the size of the epidemic increased considerably there in 2021. This study made a statistical analysis of life expectancy changes up to the end of 2021 in Japan.

Objective

We aimed to estimate changes in life expectancy from 2019 to 2021 associated with the COVID-19 pandemic. To do so, we decomposed the life expectancy changes from 2020–2021 into age-specific and cause of death-specific contributions.

Methods

We used the absolute number of deaths by age and prefecture in Japan to calculate life expectancy from 2019–21 at both national and prefectural levels, and also examined the correlation between life expectancy gap and annual number of COVID-19 cases, total person-days spent in intensive care, and documented deaths due to COVID-19. We used the Arriaga decomposition method to decompose national life expectancy changes from 2020 to 2021 into age and cause of death components.

Results

From 2019–2020, Japan’s national level life expectancy across the entire population was extended by 0.24 years. From 2020–2021, it shortened by 0.15 years. The life expectancy shortened more among women (0.15 years) than men (0.12 years). There was significant heterogeneity in life expectancy changes from 2020–2021 by prefecture. It ranged from the maximum shortening of 0.57 years in Tottori prefecture to the maximum extension of 0.23 years in Fukui. The regression analysis revealed the negative correlation between the life expectancy change and burden of COVID-19 at prefectural level. The decomposition of life expectancy changes at birth from 2020–2021 showed that losses in life expectancy were largely attributable to the mortality of the population over 70 years old. Changes in life expectancy among infants and working-age adults mostly contributed to lengthening overall life expectancy. Among leading major causes of death, deaths due to neoplastic tumor and cardiovascular diseases contributed to shortening life expectancy, whereas respiratory diseases did not.

Conclusion

The decades-long increasing trend in life expectancy was suspended by the COVID-19 pandemic. However, life expectancy changes from 2019–2020 and 2020–2021 were small in Japan. This may be attributable to the small epidemiological impact of COVID-19 during this time period, but nonetheless, the negative impact of COVID-19 on life expectancy was indicated in the present study. The chance of death accelerated in older people in 2021, but a smaller number of deaths than usual among infants and working age adults contributed to extended life expectancy, and the change in the cause of death structure under the COVID-19 pandemic also significantly contributed to shortening life expectancy.
Artificial intelligence in knowledge management: application insights and guidelines
Authors: Cossul Danielli , Ferreira Guilherme , Mueller Marciane , Mirandoli Roberto , Frozza Rejane
Published: August 2023

The development of digital technologies has aroused increasing interest among researchers and managers due to the inherent transformations in productive systems, where knowledge is recognized as a key element. In this context, this study represents an exploratory perspective that does not aim for exhaustiveness, but rather a specific deep dive into the application of artificial intelligence in knowledge management. The methodology employed combines literature review, bibliometrics, and brainstorming. Through a detailed analysis of 12 articles, it was identified that the scientific production on this subject is promising, showcasing new possibilities for knowledge management in a data-driven world. Additionally, the authors propose eight application guidelines for these concepts, which serve as transient observation points that vary according to the complexity of each organization, but when practiced, tend to result in improvements across any scenario. The empirical validation of these guidelines is suggested as future work.
Assessing the Suitability of Tomato Products as a Functional Ingredient in Paneer
Authors: Patel Zenith , Pinto Suneeta , Patel Sunil
Published: August 2023

This research involved the selection of suitable tomato products from amongst the puree, paste and powder for manufacture of tomato flavoured paneer. Paneer was prepared from milk standardized to 3% fat and 8.5% MSNF. The first part of the study was conducted to select the optimum level of tomato puree, paste and powder. From amongst different rate of addition (w/w of milk) of tomato products studied viz. 7.5, 10, 12.5 and 15% in case of puree and paste and 4, 5, 6 and 7% in case of powder, it was found that samples containing puree, paste and powder @ 10, 10 and 5 % were liked the most. In the next part of the study three batches of paneer viz. T1, T2 and T3 were prepared in which tomato puree, paste and powder were incorporated at 10, 10 and 5% respectively. Control (C) paneer was prepared from standardized milk.  It was found that the fat, FDM and pH of T1, T2 and T3 were significantly (P<0.05) lower than that of C, whereas moisture content of T1, T2 and T3 were significantly (P<0.05) higher than C. The recovery of fat, protein and TS in T1, T2 and T3 was significantly (P<0.05) lower than C, while no significant (P>0.05) difference was observed in yield of paneer. All the textural properties viz. hardness, springiness, cohesiveness, chewiness and gumminess of samples containing tomato products were significantly (P<0.05) lower compared to control. The overall acceptability score of T1 was significantly (P<0.05) higher than that of T2 and T3 but was significantly (P<0.05) lower compared to C. The Vitamin C, total dietary fiber and antioxidant capacity of T1 was significantly (P<0.05) higher compared to C. Hence, it was concluded that good quality tomato flavoured paneer can be prepared incorporating tomato puree @ 10% w/w of milk with better functional properties compared to control.
Potential of Precision Farming Technologies for Eco-Friendly Agriculture
Authors: Gawande Vaishnavi , Saikanth D. R. K. , Sumithra B. S. , Aravind S. Ashokh , Swamy G. Narayana , Chowdhury Manojit , Singh Bal Veer
Published: August 2023

Precision farming technologies have the potential to revolutionize agriculture by promoting eco-friendly practices. The review explores the potential advantages of precision farming technologies in achieving sustainable and environmentally conscious agriculture. The application of precision farming techniques allows for the targeted use of resources such as water, fertilizers, and pesticides, minimizing waste and reducing environmental impact. By incorporating advanced technologies like GPS, GIS, remote sensing, and data analytics, precision farming enables farmers to make informed decisions based on real-time data, leading to improved crop management and increased productivity. Additionally, precision farming promotes the adoption of site-specific management strategies, taking into account the unique characteristics of each field, optimizing resource allocation, and reducing the risk of environmental pollution. This review highlights the importance of precision farming in achieving eco-friendly agriculture and calls for further research and adoption of these technologies to promote sustainable farming practices.
Enhancing Crop Improvement through Synergistic Integration of Advanced Plant Breeding and Proximal Remote Sensing Techniques: A Review
Authors: Anand Kumar Jai , Nagre Sachin Prakash , Shrivastava M. K. , Amrate Pawan K. , Patel Teena , Katara Vijay Kumar
Published: August 2023

Accelerating crop improvement with enhanced adaptability to changing climatic conditions and meeting the ever-increasing global food demand requires urgent action. To achieve this, we must employ advanced molecular breeding techniques, such as marker-assisted selection, marker-assisted backcrossing, genomic selection, genome editing, and targeted mutation. However, these approaches demand the screening of large populations to identify potential genes and genotypes. Unfortunately, a significant bottleneck lies in the absence of high-throughput plant phenotyping methods that can rapidly and cost-effectively facilitate data-driven genotype selection in plant breeding. Traditional phenotyping methods, reliant on trained experts, are slow, expensive, labour-intensive, subjective, and often require destructive sampling. Proximal remote sensing technologies, including RGB imaging, thermal imaging, hyperspectral imaging, multispectral imaging, and fluorescence imaging, offer a non-destructive and rapid collection of detailed phenotypic data, providing valuable insights into various plant traits at different growth stages. High-throughput phenotyping platforms, such as Conveyor-Type Indoor, Benchtop-Type Indoor, Unmanned Aerial Platform (UAP), and Manned Aerial Platform (MAP), utilize a combination of the aforementioned remote sensing technologies. This review article aims to explore the integration of proximal remote sensing and molecular breeding approaches, showcasing how this synergistic approach can expedite crop improvement efforts. By emphasizing the benefits, challenges, and future prospects of this integrative approach, we hope to pave the way for sustainable and productive agriculture, ensuring food security in the face of changing environmental conditions.
The Development of the Real Time Target Simulator for the RF Signal of Electronic Warfare using VST and FPGA
Authors: Song Sanghun
Published: August 2023

In this paper, the target simulator for RF signals was developed by using VST(Vector Signal Transceiver) and set by real-time signal processing SW programs. A function to process RF signals using FPGA(Field Programmable Gate Array) board was designed. The system functions capable of data processing, raw signals monitoring, target signals(simulated range, velocity) generating and RF environments data analyzing were implemented. And the characteristics of modulated signal were analyzed in RF environment. All function of programs for processing RF signal have options to store signal data and to manage the data. The validity of the signal simulation was confirmed through verification of simulated signal results.
Drone based Magnetic Anomaly Detection to detect Ferromagnetic Target
Authors: Yim Sin Hyuk , Kim Donkyu , Yoon Ji Hun , Kim Bona , Bang Eun Seok , Shim Kyu Min , Lee Sangkyung , Oh Jong-shick
Published: August 2023

Drone based Magnetic Anomaly Detection measure a magnetic anomaly signal from the ferromagnetic target on the ground. We conduct a magnetic anomaly detection with 9 ferromagnetic targets on the ground. By removing the magnetic field measured in the absence of ferromagnetic targets from the experimental value, the magnetic anomaly signal is clearly measured at an altitude of 100 m. We analyze the signal characteristics by the ferromagnetic target through simulation using COMSOL multiphysics. The simulation results are within the GPS error range of the experimental results.
investigação sobre o emprego e a renda no Pólo de Informática em Ilhéus, Bahia
Authors: Lima Sérgio Ricardo Ribeiro
Published: August 2023

O objetivo deste estudo é caracterizar o emprego e a renda na indústria de fabricação de equipamentos para informática e de fabricação de periféricos para equipamentos de informática. Trata-se de uma análise comparativa entre quatro períodos: 2006/20082 , 2010, 2015 e 2019. O contexto histórico ampara-se no âmbito das políticas neoliberais, com a abertura da economia brasileira na década de 1990. Conclui-se que a crise econômica de 2007-2008 e o fim dos incentivos fiscais em 2010 levaram a forte redução no emprego e na renda. O período de análise dos dados mostrou que os incentivos fiscais, entre outros, favoreceram mais a valorização do capital do que o emprego, a renda e a melhoria do padrão de bem-estar dos trabalhadores.
Öğretmenlerin Örgütsel Adalet, Örgütsel Bağlılık ve İş Doyumu Algıları Arasındaki İlişki
Authors: KOCABAŞ Durmuş Ali , KARABAĞ KÖSE Esra
Published: August 2023

Araştırmanın amacı, ortaokullarda görev yapan öğretmenlerin örgütsel adalet, örgütsel bağlılık ve iş doyumu algıları arasındaki ilişkilerin incelemesidir. Çalışmanın evrenini 2021-2022 eğitim öğretim yılında Kırıkkale ilindeki ortaokullarda görev yapan 994 öğretmen oluşturmaktadır. Araştırma 371 öğretmenin katılımı ile yürütülmüştür. Veri toplama araçları olarak Örgütsel Adalet, Örgütsel Bağlılık ve İş Doyumu ölçekleri kullanılmıştır. Verilerin çözümlenmesinde betimsel istatistiklerle birlikte korelasyon, regresyon ve yol analizleri kullanılmıştır. Araştırmada öğretmenlerin örgütsel adalet algıları, örgütsel bağlıkları ve iş doyumları arasında anlamlı, pozitif ve orta düzeyde ilişki olduğu belirlenmiştir. Araştırma sonuçları, örgütsel adaletin iş doyumu üzerindeki örgütsel bağlılık aracılığıyla olan dolaylı etkisinin doğrudan etkisinden daha güçlü olduğunu göstermektedir.
Novel insights into molecular patterns of ROS1 fusions in a large Chinese NSCLC cohort: a multicenter study
Authors: Zhou Shengyu , Zhang Fayan , Xu Mengxiang , Zhang Lei , Liu Zhengchuang , Yang Qiong , Wang Chunyang , Wang Baoming , Ma Tonghui , Feng Jiao
Published: August 2023

ROS proto‐oncogene 1, receptor tyrosine kinase (ROS1) rearrangements are a crucial therapeutic target in non‐small cell lung cancer (NSCLC). However, there is limited comprehensive analysis of the molecular patterns of ROS1 fusions. This study aimed to address this gap by analysing 135 ROS1 fusions from 134 Chinese NSCLC patients using next‐generation sequencing (NGS). The fusions were categorized into common and uncommon based on their incidence. Our study revealed, for the first time, a unique distribution preference of breakpoints within ROS1, with common fusions occurring in introns 31–33 and uncommon fusions occurring in introns 34 and 35. Additionally, we identified previously unknown breakpoints within intron 28 of ROS1. Furthermore, we identified a close association between the distribution patterns of fusion partners and breakpoints on ROS1, providing important insights into the molecular landscape of ROS1 fusions. We also confirmed the presence of inconsistent breakpoints in ROS1 fusions between DNA‐based NGS and RNA‐based NGS through rigorous validation methods. These inconsistencies were attributed to alternative splicing resulting in out‐of‐frame or exonic ROS1 fusions. These findings significantly contribute to our understanding of the molecular characteristics of ROS1 fusions, which have implications for panel design and the treatment of NSCLC patients with ROS1 rearrangements.
FOXO1 promotes the expression of canonical WNT target genes in examined basal‐like breast and glioblastoma multiforme cancer cells
Authors: Pintor Shania , Lopez Alma , Flores David , Lozoya Brianda , Soti Bipul , Pokhrel Rishi , Negrete Joaquin , Persans Michael W. , Gilkerson Robert , Gunn Bonnie , Keniry Megan
Published: August 2023

Basal‐like breast cancer (BBC) and glioblastoma multiforme (GBM) are aggressive cancers associated with poor prognosis. BBC and GBM have stem cell‐like gene expression signatures, which are in part driven by forkhead box O (FOXO) transcription factors. To gain further insight into the impact of FOXO1 in BBC, we treated BT549 cells with AS1842856 and performed RNA sequencing. AS1842856 binds to unphosphorylated FOXO1 and inhibits its ability to directly bind to DNA. Gene Set Enrichment Analysis indicated that a set of WNT pathway target genes, including lymphoid enhancer‐binding factor 1 (LEF1) and transcription factor 7 (TCF7), were robustly induced after AS1842856 treatment. These same genes were also induced in GBM cell lines U87MG, LN18, LN229, A172, and DBTRG upon AS1842856 treatment. By contrast, follow‐up RNA interference (RNAi) targeting of FOXO1 led to reduced LEF1 and TCF7 gene expression in BT549 and U87MG cells. In agreement with RNAi experiments, CRISPR Cas9‐mediated FOXO1 disruption reduced the expression of canonical WNT genes LEF1 and TCF7 in U87MG cells. The loss of TCF7 gene expression in FOXO1 disruption mutants was restored by exogenous expression of the DNA‐binding‐deficient FOXO1‐H215R. Therefore, FOXO1 induces TCF7 in a DNA‐binding‐independent manner, similar to other published FOXO1‐activated genes such as TCF4 and hes family bHLH transcription factor 1. Our work demonstrates that FOXO1 promotes canonical WNT gene expression in examined BBC and GBM cells, similar to results found in Drosophila melanogaster, T‐cell development, and murine acute myeloid leukemia models.
Equity, diversity, and inclusion topics at a medical physics residency journal club
Authors: Fagerstrom Jessica M. , Windsor Cheyann , Zaks Daniel
Published: August 2023

A journal club program was initiated in a clinically focused, geographically distributed medical physics therapy residency program. This program currently supports two residents at different clinical sites, who regularly present at the new journal club. For one of the sessions, residents were assigned to present on topics related to the broad themes of equity, diversity, and inclusion (EDI) in the context of medical physics, radiation oncology, or medical oncology. As in other journal club sessions, residents were responsible for choosing their respective articles within required criteria and with approval from the program director. The session was executed in late 2022, with both residents leading and facilitating discussion for the residents, the residency program director, and all residency faculty members. This education case report will include the learning objectives for the journal club session, a description of the content covered in the session, discussion regarding the session's alignment with the original learning objectives, and ideas for program directors intending to include evidence‐based EDI topics in journal clubs.