Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of COVID-19 Pandemic on the Global Supply Chain Operations: A System Dynamics Approach

Epidemic outbreaks are one of the important sources of the risk in the global supply chains. Before the COVID-19 pandemic, global industries that were unprepared for disruptions experienced a decline due to the pandemic. A global supply chain is a complex system set of dynamics that could be analyzed by the system dynamics approach. In this article, the impact of the recent pandemic on the global supply chain is simulated in different scenarios. A system dynamic model is developed to carry out the simulations. In order to consider the impact of the pandemic on the exogenous and endogenous variables, a force majeure factor is defined in the model. Global features considered in this article are the export and import operations, the exchange rate and the rate of tariff. In this article, a scenario analysis is performed to analyze two important factors of the global supply chain: force majeure factor and delivery delay. Results showed that improving the flexibility of production capacity is one of the important strategies that global supply chain managers should pursue. JEL Codes: F23, P45, C15, C63, E37, F17
Research on the influence of harmonic on the operation characteristics of capacitor voltage transformers

Aiming at the distortion of CVT at the secondary side,this paper expounds the structure characteristics and working principle of CVT,analyzes the influence of stray capacitance and coupling capacitance on the high frequency of CVT from the aspect of system transfer function and the change of measurement difference caused by harmonic disturbance. In order to further understand the influence of harmonic on the operation characteristics of CVT,this paper establishes the model of CVT high frequency equivalent circuit including stray capacitance and coupling capacitance by Matlab to acquire the amplitude-frequency curve of CVT. The simulation result shows that the harmonic voltage in power grid,which will changes the measurement difference of CVT,is not suitable for directly measuring harmonic voltage.
THE EFFECT OF CLIMATE CHANGE ON THE AGRICULTURAL SECTOR IN TURKEY

After Industrial Revolution, severe increases were experienced in fossil fuel consumption due to increased energy needs. The endless struggle of humankind for interest and his/her ignorance of environmental devastation led greenhouse gas to accumulate in the atmosphere, global warming to be experienced and, depending on this, climatic change to form. This process experienced has caused many international and national studies to be conducted in the area of climatic change related to the different disciplines, and the issue has taken place in the top orders among the leading subjects in academic platforms. This study discussed the effect of climatic change in Turkey on the agricultural sector. The sectors dealt with the study the agricultural sector, and the effects of climatic changes were aimed to be introduced with an econometric model. In agricultural sector, the effects of climatic changes from the perspective of the product productivity were analyzed by means of the agricultural sector, the effects of climatic changes from the perspective of product productivity were analyzed through Granger Causality Test. In the study, the period of 1970 -2017 was based on. The study deals with the issue on a sectorial basis; additionally, its effect is evaluated on the basis of product productivity from the original aspect of the study. Setting out from the results obtained in the study, climatic policies directed to the agricultural sector for Turkey were formed. The effects of the process on the sector were explicitly introduced. Developing climatic policies directed to this sector was targeted to contribute to the literature. Keywords: Climate change, agricultural products, granger causality test, variance decomposition.
Providing Fault Detection from Sensor Data in Complex Machines That Build the Smart City

Household appliances, climate control machines, vehicles, elevators, cash counting machines, etc., are complex machines with key contributions to the smart city. Those devices have limited memory and processing power, but they are not just actuators; they embed tens of sensors and actuators managed by several microcontrollers and microprocessors communicated by control buses. On the other hand, predictive maintenance and the capability of identifying failures to avoid greater damage of machines is becoming a topic of great relevance in Industry 4.0, and the large amount of data to be processed is a concern. This article proposes a layered methodology to enable complex machines with automatic fault detection or predictive maintenance. It presents a layered structure to perform the collection, filtering and extraction of indicators, along with their processing. The aim is to reduce the amount of data to work with, and to optimize them by generating indicators that concentrate the information provided by data. To test its applicability, a prototype of a cash counting machine has been used. With this prototype, different failure cases have been simulated by introducing defective elements. After the extraction of the indicators, using the Kullback–Liebler divergence, it has been possible to visualize the differences between the data associated with normal and failure operation. Subsequently, using a neural network, good results have been obtained, being able to correctly classify the failure in 90% of the cases. The result of this application demonstrates the proper functioning of the proposed approach in complex machines.
High Pressure Processing Applications in Plant Foods

High pressure processing (HPP) is a cold pasteurization technology by which products, prepacked in their final package, are introduced to a vessel and subjected to a high level of isostatic pressure (300–600 MPa). High-pressure treatment of fruit, vegetable and fresh herb homogenate products offers us nearly fresh products in regard to sensorial and nutritional quality of original raw materials, representing relatively stable and safe source of nutrients, vitamins, minerals and health effective components. Such components can play an important role as a preventive tool against the start of illnesses, namely in the elderly. An overview of several food HPP products, namely of fruit and vegetable origin, marketed successfully around the world is presented. Effects of HPP and HPP plus heat on key spoilage and pathogenic microorganisms, including the resistant spore form and fruit/vegetable endogenous enzymes are reviewed, including the effect on the product quality. Part of the paper is devoted to the industrial equipment available for factories manufacturing HPP treated products.
Data-Enhancement Strategies in Weather-Related Health Studies

Although the relationship between weather and health is widely studied, there are still gaps in this knowledge. The present paper proposes data transformation as a way to address these gaps and discusses four different strategies designed to study particular aspects of a weather–health relationship, including (i) temporally aggregating the series, (ii) decomposing the different time scales of the data by empirical model decomposition, (iii) disaggregating the exposure series by considering the whole daily temperature curve as a single function, and (iv) considering the whole year of data as a single, continuous function. These four strategies allow studying non-conventional aspects of the mortality-temperature relationship by retrieving non-dominant time scale from data and allow to study the impact of the time of occurrence of particular event. A real-world case study of temperature-related cardiovascular mortality in the city of Montreal, Canada illustrates that these strategies can shed new lights on the relationship and outlines their strengths and weaknesses. A cross-validation comparison shows that the flexibility of functional regression used in strategies (iii) and (iv) allows a good fit of temperature-related mortality. These strategies can help understanding more accurately climate-related health.
Wnt Signaling Rescues Amyloid Beta-Induced Gut Stem Cell Loss

Patients with Alzheimer’s disease suffer from a decrease in brain mass and a prevalence of amyloid-β plaques. These plaques are thought to play a role in disease progression, but their exact role is not entirely established. We developed an optogenetic model to induce amyloid-β intracellular oligomerization to model distinct disease etiologies. Here, we examine the effect of Wnt signaling on amyloid in an optogenetic, Drosophila gut stem cell model. We observe that Wnt activation rescues the detrimental effects of amyloid expression and oligomerization. We analyze the gene expression changes downstream of Wnt that contribute to this rescue and find changes in aging related genes, protein misfolding, metabolism, and inflammation. We propose that Wnt expression reduces inflammation through repression of Toll activating factors. We confirm that chronic Toll activation reduces lifespan, but a decrease in the upstream activator Persephone extends it. We propose that the protective effect observed for lithium treatment functions, at least in part, through Wnt activation and the inhibition of inflammation.
Valorisation of phyto-biochars as slow release micronutrients and sulphur carrier for agriculture

ABSTRACT Slow release micronutrients and sulphur sources are required for higher use efficiency of fertilizers in agriculture. The present investigation was undertaken to examine the salt soluble, desorbed and specifically sorbed fractions of micronutrients and sulphur in nutrient enriched phyto-biochars incubated at 15, 25 and 35°C for 48 h after pyrolysis of Lantana sp. , Pinus sp. needles and wheat straw at 300 and 450 °C. The highest salt soluble fractions of Zn, Cu, Fe, Mn and B were recorded with pine needle biochar pyrolyzed at 300 °C, whereas that of S with lantana biochar pyrolyzed at 300 °C. The highest desorbed contents of Zn, Cu and Mn were with pine needle biochar (300 °C) and that of B and S with wheat straw biochar (450 °C) and lantana biochar (300 °C), respectively. An increase in incubation temperature from 15 to 25 °C increased the salt soluble contents of Zn and specifically sorbed contents of Fe and B but decreased salt soluble contents of Fe and B and desorbed amount of S significantly. Further, increase in incubation temperature from 25 to 35 °C significantly decreased the salt soluble contents of all nutrients except Mn and desorbed amount of S but increased specifically sorbed amount of Fe, B and S. Considering the salt soluble and desorbed contents of nutrients in enriched phyto-biochars, especially pine needle biochar pyrolyzed at 300 °C and treated with marginal or deficient nutrients for 2 d at 15–25 °C appeared to be suitable as a slow release fertilizer. GRAPHICAL ABSTRACT
A study on occurrence of paediatric diaphyseal fractures of femur in Indian population

Background: There was an increased interest in the operative treatment of paediatric fractures in the past two decades, although debate persisted over its indications. There is a little disagreement concerning the treatment of femur fractures in children less than 5 years (POP cast) and adolescents older than 15 years (locked intramedullary nailing). Controversy persists regarding the age between 5 to 15 years. Several treatment options for femoral shaft fractures in children and adolescents have been described. Children below the age of 3 can be treated with cast or extensional devices. In the past two decades the management of displaced femoral shaft fractures in older children has gradually evolved toward a more operative approach due to a more rapid recovery, faster reintegration of the patients and possible negative effects of immobilization even in children. Orthopaedic surgeons will continue to face the challenge to treat this age group with less morbidity at a lower cost, as no clear guidelines have been available until now despite efforts done initially by French surgeons, later on by European surgeons and recently by the Paediatric Orthopaedic Society of North America (POSNA). Conclusion: There was no significant association observed between clinical variables (age, gender, mode of injury, pattern of fracture and time interval between trauma and surgery) and incidence of complications.
Allometric models for estimating the leaf area of lisianthus (Eustoma grandiflorum) using a non-destructive method

Submitted on December 10 , 2020 and accepted on March 23 , 2021. 1 Universidade Federal de Viçosa, Departamento de Agronomia, Viçosa, Minas Gerais, Brazil. toshik.silva@ufv . br; marlon.dias@ufv . br; jgrossi@ufv.br; jgeraldo@ufv . br 2 Universidade Federal da Paraíba, Departamento de Fitotecnia e Ciências Ambientais, Areia, Paraíba, Brazil. j.everthon@hotmail.com. *Corresponding author: toshik.silva@ufv . br Allometric models for estimating the leaf area of lisianthus (Eustoma grandiflorum) using a non-destructive method
Tightening the Constraints on Form and Content for an Existing Computer Poet

Existing systems for the automated generation of poetry often attempt to simplify the task by taking advantage of free-form poetry - to avoid the need to achieve rigorous poetic form - and poetic licence - to avoid the need of conveying a specific message at a semantic level. This is acceptable as an initial step, but once acceptable solutions have been found for the simplified version of the problem, progress can be made towards higher goals by enriching the initial problem statement. The present paper describes an attempt where an existing computer poet, originally developed to produce poems in a given form but with no specific constraints on their content, is put to the task of producing a set of poems with tighter restrictions on both form and content. Alternative generation methods are devised to overcome the difficulties, and the various insights arising from these new methods and the impact they have on the set of resulting poems are discussed in terms of their potential contribution to better poetry generation systems.
Hash-Chain Fog/Edge: A Mode-Based Hash-Chain for Secured Mutual Authentication Protocol Using Zero-Knowledge Proofs in Fog/Edge

Authentication is essential for the prevention of various types of attacks in fog/edge computing. Therefore, a novel mode-based hash chain for secure mutual authentication is necessary to address the Internet of Things (IoT) devices’ vulnerability, as there have been several years of growing concerns regarding their security. Therefore, a novel model is designed that is stronger and effective against any kind of unauthorized attack, as IoT devices’ vulnerability is on the rise due to the mass production of IoT devices (embedded processors, camera, sensors, etc.), which ignore the basic security requirements (passwords, secure communication), making them vulnerable and easily accessible. Furthermore, crackable passwords indicate that the security measures taken are insufficient. As per the recent studies, several applications regarding its requirements are the IoT distributed denial of service attack (IDDOS), micro-cloud, secure university, Secure Industry 4.0, secure government, secure country, etc. The problem statement is formulated as the “design and implementation of dynamically interconnecting fog servers and edge devices using the mode-based hash chain for secure mutual authentication protocol”, which is stated to be an NP-complete problem. The hash-chain fog/edge implementation using timestamps, mode-based hash chaining, the zero-knowledge proof property, a distributed database/blockchain, and cryptography techniques can be utilized to establish the connection of smart devices in large numbers securely. The hash-chain fog/edge uses blockchain for identity management only, which is used to store the public keys in distributed ledger form, and all these keys are immutable. In addition, it has no overhead and is highly secure as it performs fewer calculations and requires minimum infrastructure. Therefore, we designed the hash-chain fog/edge (HCFE) protocol, which provides a novel mutual authentication scheme for effective session key agreement (using ZKP properties) with secure protocol communications. The experiment outcomes proved that the hash-chain fog/edge is more efficient at interconnecting various devices and competed favorably in the benchmark comparison.
Fusion of Multi-Intensity Image for Deep Learning-Based Human and Face Detection

For ordinary IR-illuminators in nighttime surveillance system, insufficient illumination may cause misdetection for faraway object while excessive illumination leads to over-exposure of nearby object. To overcome these two problems, we use the MI3 image dataset, which is established by multi-intensity IR-illumination (MIIR), as our benchmark dataset for modern object detection methods. We first provide complete annotations for the MI3 as its current ground-truth is incomplete. Then, we use these multi-intensity illuminated IR videos to evaluate several widely used object detectors, i.e., SSD, YOLO, Faster R-CNN, and Mask R-CNN, by analyzing the effective range of different illumination intensities. By including a tracking scheme, as well as developing of a new fusion method for different illumination intensities to improve the performance, the proposed approach may serve as a new benchmark of face and object detection for a wide range of distances. The new dataset (Dataset is available: https://ieee-dataport.org/documents/mi3) with more complete annotations and source codes (Codes are available: https://github.com/thesuperorange/deepMI3) is available online.
Lacydonia shohoensis (Annelida, Lacydoniidae) sp. nov. – a new lacydonid species from deep-sea sunken wood discovered at the Nishi-Shichito Ridge, North-western Pacific Ocean

Abstract Lacydonia Marion & Bobretsky, 1875 is the sole genus in the family Lacydoniidae Bergström, 1914. We herein describe the new species of Lacydonia shohoensis sp. nov. from 2042-m deep bottoms at Shoho Seamount of the Nishi-Shichito Ridge, the Northwest Pacific Ocean. It is most similar to L. anapaulae Rizzo et al., 2016 in having a depression on the median anterior region and lacking lateral lobes on the posterior margin of prostomium whereas it is distinguished by possessing pygidium dorsally pigmented with three reddish spots and non-pigmented pygidial lateral cirri equally elongated.
Compositional Effects on Indentation Mechanical Properties of Chemically Strengthened TiO2-Doped Soda Lime Silicate Glasses

TiO2 is an important oxide for property modifications in the conventional soda lime silicate glass family. It offers interesting optical and mechanical properties, for instance, by substituting heavy metals such as lead in consumer glasses. The compositional effects on the hardness, reduced elastic modulus and crack resistance as determined by indentation of chemically strengthened (CS) TiO2-doped soda lime silicate glass was studied in the current paper. The CS, which was performed by a K+ for Na+ ion exchange in a molten KNO3 salt bath at 450 °C for 15 h, yielded significant changes in the indentation mechanical properties. The hardness of the glass samples increased, and this was notably dependent on the SiO2, CaO and TiO2 content. The reduced elastic modulus was less affected by the CS but showed decrease for most samples. The crack resistance, an important property in many applications where glasses are subjected to contact damage, showed very different behaviors among the series. Only one of the series did significantly improve the crack resistance where low CaO content, high TiO2 content, high molar volume and increased elastic deformation favored an increased crack resistance.
Perceptions and Needs of Artificial Intelligence in Health Care to Increase Adoption: Scoping Review

Background Artificial intelligence (AI) has the potential to improve the efficiency and effectiveness of health care service delivery. However, the perceptions and needs of such systems remain elusive, hindering efforts to promote AI adoption in health care. Objective This study aims to provide an overview of the perceptions and needs of AI to increase its adoption in health care. Methods A systematic scoping review was conducted according to the 5-stage framework by Arksey and O’Malley. Articles that described the perceptions and needs of AI in health care were searched across nine databases: ACM Library, CINAHL, Cochrane Central, Embase, IEEE Xplore, PsycINFO, PubMed, Scopus, and Web of Science for studies that were published from inception until June 21, 2021. Articles that were not specific to AI, not research studies, and not written in English were omitted. Results Of the 3666 articles retrieved, 26 (0.71%) were eligible and included in this review. The mean age of the participants ranged from 30 to 72.6 years, the proportion of men ranged from 0% to 73.4%, and the sample sizes for primary studies ranged from 11 to 2780. The perceptions and needs of various populations in the use of AI were identified for general, primary, and community health care; chronic diseases self-management and self-diagnosis; mental health; and diagnostic procedures. The use of AI was perceived to be positive because of its availability, ease of use, and potential to improve efficiency and reduce the cost of health care service delivery. However, concerns were raised regarding the lack of trust in data privacy, patient safety, technological maturity, and the possibility of full automation. Suggestions for improving the adoption of AI in health care were highlighted: enhancing personalization and customizability; enhancing empathy and personification of AI-enabled chatbots and avatars; enhancing user experience, design, and interconnectedness with other devices; and educating the public on AI capabilities. Several corresponding mitigation strategies were also identified in this study. Conclusions The perceptions and needs of AI in its use in health care are crucial in improving its adoption by various stakeholders. Future studies and implementations should consider the points highlighted in this study to enhance the acceptability and adoption of AI in health care. This would facilitate an increase in the effectiveness and efficiency of health care service delivery to improve patient outcomes and satisfaction.
Can Body Mass Index Affect Height Growth at Menarche among Girls Receiving Treatment for Early Puberty? A Retrospective Study in Korean Girls

Gonadotropin-releasing hormone agonist (GnRHa) therapy is used to control puberty progression and it preserves height potential in patients with idiopathic central precocious puberty (ICPP). This study evaluated the correlation between weight and height gain at menarche following GnRHa treatment among girls with ICPP and relatively central early puberty (EP). We investigated height/weight trends and changes in height from diagnosis to menarche in girls with ICPP and EP treated with GnRHa. The mean difference in height (Δheight) from treatment cessation to menarche was 9.79 ± 3.53 cm. Girls were divided into girls with Δheight ≥ 9.79 cm (Group 1) and girls with Δheight < 9.79 cm (Group 2). Although near adult height was significantly higher in Group 1, the mean body mass index (BMI) and weight were significantly lower at diagnosis, treatment discontinuation, and menarche. The BMI and weight at the three time points were negatively correlated with height. Girls with higher BMI at all three time points had slower growth rates during the study period. Considering that BMI and body weight were closely related to Δheight, proper management of BMI and body weight of girls receiving early puberty treatment might contribute to growth during and after GnRHa treatment.