Miracle-dz/UniFAR-FTUs huggingface dataset:
Warehouse Product Demand Forecasting Using Time Series Methods

Forecasting plays an essential role in supply chain operations as a lot of critical decisions are dependent on predicted future factors like product demand and sales. It may be necessary to make forecasts years in advance or only a few minutes. Forecasting is a crucial tool for efficient and productive planning, regardless of the situations or time frames involved. Given the significance of warehouses in supply chains, warehouse operations must be productive and profitable. Accurate projections not only help to reduce discrepancies between actual and anticipated sales, but they can also have an impact on other supply chain issues, such as managing excess and obsolete inventories. This paper showcases a comparative analysis of two time series models-Holt-Winters Smoothing Method and Seasonal ARIMA or SARIMA, for better prediction of fluctuating demand of products which in turn will contribute to the company’s betterment in multiple ways.
Exploitation des observations satellitaires IASI couplées à un modèle régional pour l'amélioration de la prévision des épisodes de pollution en ozone

Les observations satellitaires contribuent desormais a la surveillance de la composition tropospherique et a la prevision de la qualite de l'air, en fournissant une information quantitative sur l'ozone et ses precurseurs. L'objectif de ces travaux de these a ete d'exploiter le couplage entre les observations satellitaires IASI, qui a ete lance a bord du satellite MetOp en octobre 2006, et le modele CHIMERE, afin de documenter l'amelioration de la prevision de la qualite de l'air. Ces travaux s'appuient d'abord sur l'inversion des concentrations d'ozone a partir des spectres infrarouges mesures par l'instrument IASI pour restituer des colonnes totales d'ozone et des colonnes partielles d'ozone notamment dans la troposphere. Ces mesures ont ete validees par des observations independantes : les colonnes totales sont comparees a des mesures ultra-violettes fournies par l'instrument satellitaire GOME-2 (egalement a bord du satellite MetOp) et les instruments au sol du reseau Brewer-Dobson mais egalement des mesures infrarouges (TES et AIRS). Les colonnes partielles sont, elles, comparees a des mesures de ballons sonde. Un autre volet de mes travaux de these consiste a preparer l'assimilation des donnees IASI dans le modele CHIMERE, en utilisant un Filtre de Kalman d'Ensemble. Cette methode permet d'etablir les covariances des erreurs du modele a partir d'un ensemble de differentes configurations du modele. Dans ce contexte, un travail sur la construction d'un ensemble refletant au mieux la realite a ete entrepris. La qualite de l'ensemble a ete evaluee, dans la dimension verticale et en surface, a partir de differents outils, qui reposent tous sur des comparaisons aux observations.
Safety-Critical Systems in the Automotive Sector; Pros and Cons in the Current State-of-the-Art of Human Performance Assessment

Even though the possible replacement of workers with automation or robots seems to indicate a future loss in human workforce needs, most manufacturing lines still require human interaction, e.g., for maintenance, inspections, and operations. Due to this interaction, the human-machine interface and human reliability are critical performance factors for identifying and dealing with safety-critical scenarios and business continuity. This paper is based on a literature review on human performance assessment in the automotive sector. This review reports the pros and cons of the current human performance assessment and deployment methods and data at the current state-of-the-art. In the automotive sector, production systems are based on assembly lines where the automation process is becoming increasingly complex, which calls for additional capabilities for the workers’ operations and for analyzing safety-critical operations and making decisions. Artiﬁcial intelligence that made massive progress in science and technology can play a relevant role. Artiﬁcial intelligence is expected to support the decision-making for the management of safety-critical systems in an always more rapid and effective way, exploiting data from the shopﬂoor, both from equipment and operators’ monitoring. Moreover, independent artiﬁcial intelligence decisions, even in critical scenarios, will be the future target of the research. This work is an initial step in our research activity within the Collaborative Intelligence for Safety-Critical Systems (CISC) project. https://www.ciscproject. eu/
Food desert versus food oasis: An exploration of residents' perceptions of factors influencing food buying practices

Utilizing concept mapping, the primary goal of this dissertation research was to explore the range of factors that influence food buying practices. A total of twenty five participants from two low-income zip codes in Pittsburgh, PA completed the concept mapping process. The participants were recruited based on residential proximity to a supermarket. This dissertation is organized around the presentation of three manuscripts. The first manuscript presents an exhaustive review of the literature related to food deserts. The research presented in manuscript two identified perceptions of factors influencing food buying practices among residents of an urban food desert (n=12) compared to a food oasis (n=13). Results identified 121 unique statements that were grouped by participants into 12 clusters, or unique concepts. Analyses show that overall, the average cluster ratings for residents of the food desert were higher than residents of the food oasis. Research presented in manuscript three addressed how residents' perceptions of factors influencing food buying practices differ by food security status. Findings show that food insecure participants rated clusters higher than food secure participants. A secondary aim was to explore how important these factors are to hindering healthy eating based on food desert and food security statuses. Overall, cluster rankings were similar for food secure participants in a food desert and food secure participants in a food oasis. However, participants in the food desert rated all of the clusters higher than participants in the food oasis. In comparing food insecure participants in a food desert to a food oasis, findings show that although cluster rankings were different, average cluster ratings were similar. The public health significance of this study is that it contributes to our understanding of factors that influence food buying practices based on neighborhood and individual-level characteristics, an area that has received limited consideration. Based on findings from this research, areas for future research, and policy and program development have been uncovered to address the lack of access to healthy foods for urban residents of low-income areas.
Effect of Plastic Cling Film on the Shelf Life of Carrot

Carrot is an important crop with a wide range of colored roots with high post harvest losses due to perishable nature of the roots. The perishable nature of the roots is enhanced by bruising, microbes and water loss. The continuous water loss affects the cell structure rendering it a flaccid that results in the production of the unacceptable root types. The shelf life increase with the use of simple low cost packaging cling films has been studied in the present work under the refrigeration conditions. The results yielded a positive response towards the use of cling films over the roots in order decrease the losses incurred due to escaping tendency of moisture.
Editorial: Diagnosis and treatment of bone metastases

COPYRIGHT © 2023 Pu, Hu, Yang, Xia and Xia. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Editorial PUBLISHED 15 August 2023 DOI 10.3389/fonc.2023. 1247231
Screening and validation of differentially expressed genes in adipose tissue of patients with obesity and type 2 diabetes mellitus

White adipose tissue (WAT) plays a pivotal role in the onset of type 2 diabetes mellitus (T2DM) and obesity. Despite its significance the underlying pathogenesis and key genes associated with it remain elusive. In our study, we screened the differentially expressed genes (DEGs) in intra-abdominal WAT of T2DM patients with obesity, as well as those with simple obesity, aiming to lay a foundational theory for an in-depth investigation of T2DM pathogenesis and the identification of novel therapeutic targets. Gene expression datasets (GSE16415 and GSE71416) were retrieved from the Gene Expression Omnibus (GEO) database. We employed R for screening DEGs and conducted a functional enrichment analysis using the Metascape database. Combined Lasso regression and Boruta feature selection algorithms were used to identify key DEGs. Subsequently, these were cross-verified using the GSE29231 dataset. Samples and medical records were collected from clinical study participants. The mRNA and protein expressions of the key DEGs were verified using quantitative reverse transcription polymerase chain reaction and western blotting, respectively. We discerned a total of 130 DEGs, with 40 being upregulated and 90 downregulated. Functional and pathway enrichment analyses illuminated that these genes are instrumental in mediating metabolite and energy production, neutrophil-mediated immunity, and other associated biological processes. This includes their involvement in the tricarboxylic acid cycle, glycolysis/gluconeogenesis, peroxisome proliferator-activated receptors, and other signaling pathways. Two genes, CIDEA and FSCN1 emerged as key DEGs. The low expression of CIDEA and high expression of FSCN1 in the T2DM and obesity groups were verified in clinical samples (P < 0.05). We established that CIDEA and FSCN1 manifest significant differential expression in T2DM patients who are obese. This suggests their potential as risk assessment markers and therapeutic targets for T2DM.
A Version of Fundamental Theorem for the Ito-McShane Integral of an Operator-Valued Stochastic Process

In this paper, we formulate a descriptive definition or a version of fundamental theorem for the Ito-McShane integral of an operator-valued stochastic process with respect to a Hilbert space-valued Wiener process. For this reason, we introduce the concept of belated Mcshane dierentiability and a version of absolute continuity of a Hilbert space-valued stochastic process.
Discrete asynchronous Kalman filtering of navigation data for the Phoenix autonomous underwater vehicle

Abstract : The Phoenix Autonomous Underwater Vehicle must be able to accurately determine its position at all times. This requires: (1) GPS and differential GPS for surface navigation, (2) short baseline sonar ranging system for submerged navigation, and (3) mathematical modeling of position. This thesis describes a method of Kalman filtering to merge the GPS, differential GPS, short baseline sonar ranging, and the mathematical model to produce a single state vector of vehicle position and ocean currents. The filter operates in the extended mode for processing the nonlinear sonar ranges, and in normal mode for the linear GPS/DGPS data. This required installation of a GPS system and the determination of the different variances and errors between these systems. Phoenix now has a real time method of position determination using either position measuring system separately or combined. The results of this work have been validated by real world testing of the vehicle at sea, where position estimates accurate to within several meters were obtained.
Quality of life in the course of a one-year use of an advanced hybrid closed-loop system in adults with type 1 diabetes previously naïve to advanced diabetes technology

Aim To evaluate the effect of a one-year use of an advanced hybrid closed-loop (AHCL) system on the quality of life, level of anxiety, and level of self-efficacy in adults with type 1 diabetes (T1D) previously treated with multiple daily injections (MDI) and naïve to advanced diabetes technology Methods A total of 18 participants of a previously published 3-month randomized trial (10 men, 8 women; age 40.9 ± 7.6 years) who were switched directly from MDI/BMG to AHCL completed 12 months of MiniMed 780G™system use (a 3-month randomized trial followed by a 9-month follow-up phase). At month 6 of the study, patients were switched from the sensor GS3 (Continuous Glucose Monitoring) system, powered by Guardian™ Sensor 3) to GS4. Quality of life was assessed using the Polish validated version of the ‘QoL-Q Diabetes’ questionnaire. The level of anxiety was evaluated with the use of the State-Trait Anxiety Inventory (STAI). Self-efficacy was assessed with the General Self-Efficacy Scale (GSES). Results were obtained at baseline and at the end of the study. Results Significant increase in QoL was reported in the global score (p=0.02, Cohen d=0.61) and in as many as 11 out of 23 analyzed areas of life: being physically active (p=0.02, Cohen d = 0.71); feeling well (p<.01, Cohen d = 0.73); feeling in control of my body (p<.01, Cohen d = 0.72); looking good (p<.01, Cohen d = 1.07); working (p<.01, Cohen d = 1.12); sleeping (p=0.01, Cohen d = 0.66); eating as I would like (p<.01, Cohen d = 0.79); looking after or being useful to others (p= 0.02, Cohen d = 0.65); being active with pets/animals (p<.01, Cohen d = 0.95); being spontaneous (p=0.02, Cohen d = 0.67); and doing “normal” things (p=0.02, Cohen d = 0.67). Both state (p=0.04, Cohen d = 0.56) and trait (p=0.02, Cohen d = 0.60) anxiety decreased while the general self-efficacy increased (p=0.03, Cohen d = 0.76). No participant stopped the use of the pump. Conclusion Adult patients with T1D previously treated with MDI and naïve to modern technologies experienced significant improvement in their psychological well-being after transitioning to the AHCL system after 12 months of treatment.
Creating the Capacity for Organizational Change: Personnel Participation and Receptivity to Change

In a climate of continuous change, Extension organizations must find ways to navigate immediate challenges while developing capacity to thrive as future challenges and opportunities arise. To find ways, personnel's participation in planning was encouraged to increase openness to change as OSU Extension created and implemented its new Strategic Plan. Findings indicate that personnel from all levels of the organization who participated in the planning process were more receptive and less pessimistic about the plan and more motivated to make the plan a success. These findings suggest participation may help personnel cope with current changes as well as build capacity for future changes.
Evaluation of Remain Useful Life Prediction Models from a Resilience Perspective

The remaining useful life of components is crucial in maintenance planning. However, it is difﬁcult to determine whether or not a model is reliable and trustworthy. There is no clear instruction about how to evaluate a remaining useful life prediction model since the output results are not displayed in the physical system. Furthermore, the models may generate an inaccurate prediction due to missing or outlier data. The idea of resilience is presented to evaluate the performance of the remaining useful life prediction model in order to increase model dependability and robustness. This study offers a deﬁnition for the resiliency of remaining useful life prediction models. The study then provides methods for evaluating the models used for the remaining useful life prediction. The work could serve as a springboard for further research into topics such as resilience and life prediction models.
From Youthful Vigor to Aging Decline: Unravelling the Intrinsic and Extrinsic Determinants of Hippocampal Neural Stem Cell Aging

Since Joseph Altman published his pioneering work demonstrating neurogenesis in the hippocampus of adult rats, the number of publications in this field increased exponentially. Today, we know that the adult hippocampus harbors a pool of adult neural stem cells (NSCs) that are the source of life-long neurogenesis and plasticity. The functions of these NSCs are regulated by extrinsic cues arising from neighboring cells and the systemic environment. However, this tight regulation is subject to imbalance with age, resulting in a decline in adult NSCs and neurogenesis, which contributes to the progressive deterioration of hippocampus-related cognitive functions. Despite extensive investigation, the mechanisms underlying this age-related decline in neurogenesis are only incompletely understood, but appear to include an increase in NSC quiescence, changes in differentiation patterns, and NSC exhaustion. In this review, we summarize recent work that has improved our knowledge of hippocampal NSC aging, focusing on NSC-intrinsic mechanisms as well as cellular and molecular changes in the niche and systemic environment that might be involved in the age-related decline in NSC functions. Additionally, we identify future directions that may advance our understanding of NSC aging and the concomitant loss of hippocampal neurogenesis and plasticity.
Artificial Intelligence-Based Methods for Precision Cardiovascular Medicine

Precision medicine has the potential to revolutionize the way cardiovascular diseases are diagnosed, predicted, and treated by tailoring treatment strategies to the individual characteristics of each patient. Artificial intelligence (AI) has recently emerged as a promising tool for improving the accuracy and efficiency of precision cardiovascular medicine. In this scoping review, we aimed to identify and summarize the current state of the literature on the use of AI in precision cardiovascular medicine. A comprehensive search of electronic databases, including Scopes, Google Scholar, and PubMed, was conducted to identify relevant studies. After applying inclusion and exclusion criteria, a total of 28 studies were included in the review. We found that AI is being increasingly applied in various areas of cardiovascular medicine, including the diagnosis, prognosis of cardiovascular diseases, risk prediction and stratification, and treatment planning. As a result, most of these studies focused on prediction (50%), followed by diagnosis (21%), phenotyping (14%), and risk stratification (14%). A variety of machine learning models were utilized in these studies, with logistic regression being the most used (36%), followed by random forest (32%), support vector machine (25%), and deep learning models such as neural networks (18%). Other models, such as hierarchical clustering (11%), Cox regression (11%), and natural language processing (4%), were also utilized. The data sources used in these studies included electronic health records (79%), imaging data (43%), and omics data (4%). We found that AI is being increasingly applied in various areas of cardiovascular medicine, including the diagnosis, prognosis of cardiovascular diseases, risk prediction and stratification, and treatment planning. The results of the review showed that AI has the potential to improve the performance of cardiovascular disease diagnosis and prognosis, as well as to identify individuals at high risk of developing cardiovascular diseases. However, further research is needed to fully evaluate the clinical utility and effectiveness of AI-based approaches in precision cardiovascular medicine. Overall, our review provided a comprehensive overview of the current state of knowledge in the field of AI-based methods for precision cardiovascular medicine and offered new insights for researchers interested in this research area.
Relay-Assisted Multicast With Markov Mobility

In this paper, we investigate the capacity and delay tradeoff under multicast scheme in the MANET, based on a general Markovian mobility model. To reduce the delay of the network, we propose a relay-assisted multicast scheme. Specifically, a two-hop relay algorithm is developed, in which Lyapunov drift is utilized to derive the average packet delay. In addition, we utilize the cache in relay nodes and propose the two-hop relay algorithm with redundancy. Theoretical analysis indicates that the network delay is significantly decreased, whereas the capacity remains the same. To guarantee the fairness and efficiency of the network, a two-hop relay selection algorithm with redundancy is proposed to decide which packet to serve in a queue. Moreover, the minimum energy function is applied to characterize the energy consumption of each node. We accordingly derive the accurate minimum energy function under the proposed relay-assisted multicast scheme. Furthermore, we design an efficient minimum energy algorithm, which pushes the actual energy consumption arbitrarily close to the minimum energy function at the cost of increasing delay. Theoretical results show that the optimal energy-delay tradeoff is achieved in our proposed algorithm. Numerous experiments are carried out to evaluate the performance of our proposed algorithms, where the experimental results well conform our theoretical findings.
ENTREPRENEURIAL ECOSYSTEM OF INTERNATIONAL BUSINESS IN THE TRANSITION ECONOMY: THE CASE OF SOUTHERN REGION OF UKRAINE

This paper aims to analyse and evaluate the state of the entrepreneurial ecosystem of international business in the transition economy based on the evidence of the southern region of Ukraine. The tasks of the study are (i) to identify the presence of components of the international business ecosystem and their quality depending on the level of development of the transition economy (policy, markets, finance, human capital, culture, support); (ii) to assess the current state of the components of the international business ecosystem; (iii) to identify constraining factors for the functioning of the regional entrepreneurial ecosystem for their further consideration when adjusting the trajectory of the development of the transition economy. The model of Isenberg was used to observe the structure of the ecosystem. The international ratings (KOF Index of Globalization, Global Competitiveness Index, Doing Business, etc.), the data of the State Statistics Service of Ukraine, national laws, etc. were used for the qualitative measurement of the ecosystem performance. An online survey was conducted to assess the current state of the ecosystem and to identify the restraining factors of its functioning. The research results demonstrate that all domains of an international business ecosystem are in the process of formation. 80% of respondents rated domains’ performance at three points on a 5-point scale, indicating poor functioning the ecosystem. The respondents of the survey represent several industries but mostly agro-industrial complex. The restraining factors are ineffective government policy; business-unfriendly legislation; limited access to the infrastructure; insecurity of property rights; inefficient business support systems, etc. The research results show that almost all components of the ecosystem are less efficient in Ukraine than in Europe, except for the entrepreneurs’ intentions of networking and collaboration development. The paper proposed original research on the institutional context of the ecosystem in the transition economy. The study is built on the idea of the specific regional peculiarities of entrepreneurial ecosystems and the impact of transformational processes of the economy of the country. The results of the study can be used as a basis for a scientific focus on the policy of improving the entrepreneurial ecosystem. The article empirically expands the knowledge of entrepreneurial ecosystems and shows the potential and benefits of a complete integrated ecosystem for overall regional development.