bluuebunny/crossref_metadata_2025 huggingface dataset:
Islamic Finance Practices in Micro, Small, and Medium Enterprises in Indonesia: A Systematic Literature Review
Authors: Hartanto Selamet , Suparyanto Tri , Azwar
Published: September 2023

This study analyzes Islamic finance practices in micro, small, and medium enterprises (MSMEs) in Indonesia from an Islamic economics perspective. This study employed a systematic literature review method following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The main data source was written material that analyzed the impact of Islamic finance practices on MSMEs in Indonesia. The findings demonstrate that Islamic finance practices positively influence the growth of MSMEs in Indonesia. This study indicates that Islamic finance practices have substantial potential for enhancing the well-being of MSMEs in the country. Noteworthy growth factors for MSMEs encompass Islamic business and economic ethics, innovation, and ethical and moral considerations. Islamic finance practices are a promising option for Indonesian MSMEs to enhance their business growth. Therefore, adopting Islamic finance practices can contribute to improving business performance and fostering MSMEs' growth. Future research may involve empirical studies to gain a more comprehensive understanding of Islamic finance practices in Indonesian MSMEs.
Identification of halophilic bacteria tolerant to heavy metals
Authors:   Universidad Autónoma del Estado de México, Rosas-Ramírez Jonathan Ricardo , Isaac-Olivé Keila ,   Universidad Autónoma del Estado de México, Moreno-Pérez Martín Pablo ,   Universidad Autónoma del Estado de México, Manzanares-Leal Gauddy Lizeth ,   Universidad Autónoma del Estado de México, Serment Guerrero Jorge Humberto ,   Instituto Nacional de Investigaciones Nucleares, Sandoval-Trujillo Ángel Horacio ,   Universidad Autónoma Metropolitana-Xochimilco, Ramírez-Durán Ninfa ,   Universidad Autónoma del Estado de México
Published: September 2023

Heavy metals released into the environment cause deterioration of environmental health. Their removal by biological means is a strategy under study. This research aimed to isolate and identify halophilic bacteria from saline-sodic soils and determine their tolerance to the metalloid As3+ and the heavy metals Cr6+, Hg2+, and Pb2+. The strains were grown on halophilic medium (HM), without and with the presence of each metal, at 10% NaCl, pH 8.0 ± 0.2, and 37 ºC. The strains with the highest tolerance to each metal were identified by 16S rRNA gene sequencing and phylogenetic analysis. The minimum inhibitory concentration (MIC) was subsequently determined. Seventy-five halophilic strains were isolated. The isolates with the highest tolerance were Salinicococcus spp. strains TX3SA-2MHG1 and TX3SA-4MHG1 [MIC (Hg2+) of 0.1 mmol/L]; Halomonas sp. strain TXO4B-1SG9 [MIC (Pb2+) of 7.0 mmol/L]; Nocardiopsis sp. strains TXO7B-1SG12 and TXV10-3SG5 [MIC (As3+) of 8.5 mmol/L], and Nocardiopsis sp. strain TXV7-8SG2 [MIC (As3+) of 27.25 mmol/L; MIC (Cr6+) 1250.0 mmol/L; MIC (Hg2+) 0.075 mmol/L and MIC (Pb2+) 7.5 mmol/L]. It was possible to obtain and identify isolates of halophilic metal tolerant bacteria.
Sistema experto difuso para la calificación preliminar de proyectos de captura y almacenamiento de CO2
Authors:   Instituto de Ingeniería UNAM, García-Benítez Silvia Raquel , Martínez-Meneses José Henrique ,   Instituto de Ingeniería UNAM
Published: September 2023

La captura y almacenamiento de dióxido de carbono (CAC), como el proceso que separa el emitido por la industria y fuentes relacionadas con la energía, lo transporta a un lugar de almacenamiento y lo aísla de la atmósfera a largo plazo, es una alternativa para la estabilización de las concentraciones atmosféricas de gases de efecto invernadero. La selección del sitio de captación-almacenamiento es una tarea compleja y multiparamétrica que requiere el manejo de un gran número de variables sobre el medio natural, la infraestructura y las repercusiones en el ambiente, entre otros parámetros, así como tomar en cuenta que el número de sitios de captura y almacenamiento a partir de los cuales es posible compilar experiencias para descartar o ratificar hipótesis, aún es reducido. Al respecto, en esta investigación se presenta un sistema experto difuso (SED) que ayuda a calificar la susceptibilidad de un contexto geográfico para el desarrollo de un proyecto de CAC con base en información preliminar del estado de la emisión, la disponibilidad de infraestructura para el transporte, el ambiente tectónico, las cualidades específicas de las formaciones geológicas involucradas y las condiciones geotérmicas y de presión, así como la hidrodinámica del sistema. El SED propuesto extrae las experiencias de expertos en el tema que han calificado entornos y jerarquizado su efectividad en la CAC y lo traduce en reglas claras que resultan en una calificación para cada sitio.
Proof of the Collatz Conjecture
Authors: Sukuşu Bülent
Published: September 2023

The Collatz conjecture (or 3n+1 problem) has been explored for about 86 years. In this article, we prove the Collatz conjecture. We will show that this conjecture holds for all positive integers by applying the Collatz inverse operation to the numbers that satisfy the rules of the Collatz conjecture. Finally, we will prove that there are no positive integers that do not satisfy this conjecture.
Questioning the Mechanistic-Universe Paradigm Using Chaotic Systems
Authors: Knoll Yehonatan
Published: September 2023

We humans are natural-born engineers. As such, we model after machines not only isolated, naturally occurring systems, but also the basic laws of physics, sharing with machines a local-evolution-of-state `grammar'. However, previous work by the author casts doubt upon this mechanistic paradigm, suggesting that it is to blame for the stubbornness of many open problems in physics. Simple experiments are therefore proposed to identify `non-machines'. In one experiment, `non mechanistic correlations' in the spirit of Bell are sought in a pair of separated but previously coupled (macroscopic) chaotic systems. In another it is tested whether chaotic systems could fuzzily `remember their future' in the sense that a future binary perturbation applied to them could be inferred from their present behavior with probability>1/2. Chaotic systems are chosen as candidates because the long-time application of their (deterministic) mechanistic description is conceptually groundless: All scales are significant and mutually coupled in that regime, down to scales governed by QM, yet the quantum-classical transition remains inexplicable---if only due to the measurement problem. Similarly for so-called non-deterministic chaotic systems, modeled as such purely for defying a short-time deterministic mechanistic description. Should a non mechanistic signature be found in such simple systems, the implications for science as a whole and life sciences in particular cannot be overstated.
Immunotherapy of Acute Myeloid Leukemia: A Work in Progress
Authors: Molica Matteo , Perrone Salvatore , Rossi Marco
Published: September 2023

In the last years, molecularly targeted agents and immune based treatments (ITs) have deeply changed the landscape of anti-cancer therapy. Indeed, ITs proved to be very effective in metastatic solid tumors, where outcomes were extremely poor with standard approaches. Such a scenario has been only partially reproduced in hematologic malignancies. In acute myeloid leukemia (AML), as innovative drugs are eagerly awaited in relapsed/refractory setting, different ITs have been explored, but the results are still unsatisfactory. In this work, we will discuss the most important clinical studies to date adopting ITs in AML, providing the bases to understand how this approach, although still in its infancy, may represent a promising therapeutic tool for the next future treatment of AML patients.
Melatonin Protects Bovine Spermatozoa by Reinforcing Their Antioxidant Defenses
Authors: Lavrentiadou Sophia N , Sapanidou Vasiliki , Tzekaki Elena , Margaritis Ioannis , Tsantarliotou Maria P
Published: September 2023

Cryopreserved semen is widely used in Assisted Reproductive Technologies (ART) enabling the conservation and broad use of genetically superior semen. The quality of semen post-thawing determines the success of ART and despite the great advances in cryopreservation methods, the quality of frozen/thawed semen is still sub-optimal. Post-thawing spermatozoa endure oxidative stress (OS) due to the high levels of reactive oxygen and nitrogen species, which are produced during the freezing/thawing process, and the depletion of antioxidants. To counteract this depletion, supplementation of sperm preparation medium with antioxidants has been widely applied. Melatonin is a hormone with diverse biological roles and a potent antioxidant, with an ameliorative effect on spermatozoa. In the present study, the effect of melatonin on bovine spermatozoa was evaluated during in vitro sperm handling and under oxidative conditions in terms of sperm quality parameters and antioxidant capacity. Melatonin (100 μΜ) improved the kinematic parameters of spermatozoa, enhanced viability and reinforced the antioxidant status of spermatozoa by increasing cellular GSH levels and inhibiting iNOS protein expression.
FPL: False Positive Loss
Authors: Kiaei Ali Akbar , Boush Mahnaz , Safaei Danial , Abadijou Sadegh , Baselizadeh Nima , Fayzi Ali , Bahadori Reza , Salari Nader
Published: September 2023

When training deep neural networks tasks, the most popular choices are cross-entropy loss. On the other hand, in general speaking, a decent loss function can take on shapes that are considerably more flexible and ought to be adapted for different activities and datasets. In most of the classification tasks, generally if the true class is not correctly recognized by the network (top1), that class is placed among the five classes with the highest probability (top5). This shows that the network does not necessarily recognize the correct class with a low probability, but a class similar to it (such as 3 vs. 8 in mnist) assigns a higher probability and this causes a mistake in that task. Accordingly, we proposed a loss function deals with the error of class that the neural network incorrectly recognized as correct, in addition to the correct class error. We call our proposed loss as False Positive Loss (FPL), with the intention of viewing and designing loss functions not only through the utilization of true class but also through the utilization of the value of false positive classes. One of the core properties of our proposed loss is full adaptability, which makes False Positive Loss be fully capable of getting reformulated by using other widely used loss functions formulas based on the task or the need of the users. Extensive experimental results demonstrate that our suggested loss function outperforms other well-known losses on a variety of tasks and datasets. As can be observed, the performance of our False Positive Loss is superior to that of the cross-entropy loss when it comes to tasks involving 2D picture classification. We have compared our loss with cross entropy as the most common classification loss function on some models (such as ResNet-18, ResNet-50 and Efficientnet-V2) through classification known as a basic computer vision task. with both random or pre-trained initial weights. As a result, in some cases the models with our loss outperform the same tasks with cross entropy from the viewpoint of some metric (i.e. accuracy and FP). For example, the resnet-50 on cifar-10 dataset with random initialization indicated a top1 accuracy of 94.93 with cross entropy and 95.25 with our loss, while for top5 accuracy the results are 99.86 and 99.87, respectively.
Monitoring Performanceof Sustainable Development Goals in the Italian Regions
Authors: D'Adamo Idiano , Gastaldi Massimo
Published: September 2023

The Sustainable Development Goals (SDGs) require collaboration among academia, indus-try, citizens, public administration and politics. Analysis and monitoring of the SDGs is a deci-sive step in evaluating possible corrective actions. In this regard, this paper assesses the perfor-mance of Italian regions in 2021 compared to the values recorded in 2020. An online survey among academics aims to support Multi-criteria decision analysis (MCDA) choices, which aims to calculate a sustainability score for Italian regions.
The results, based on 27 targets, show that the northern regions show better performance, with the province of Trento topping the list. This is followed by Valle d'Aosta and the province of Bolzano, confirming the trio that emerged in the previous year. A very interesting fact is the growth of the central regions, which overall tend to reach a value close to that of the northern regions. In particular, Toscana, Marche and Lazio stand out for a good performance. It is also confirmed that the southern regions occupy the last places in the ranking with the only excep-tion being Abruzzo.
The implications of this paper move toward a pragmatic approach that goes beyond the ideological in order to arrive at solutions and projects that are viewed with sharing by stake-holders. There is a need to foster collaboration between different territorial realities in order to achieve a social community in which young people have a role in which they can grow and share their ideas. Made in Italy is a target on which to enhance the SDGs to help make the Medi-terranean area a crossroads of the future global economy.
Role of Glucocorticoids and Glucocorticoid Receptors in Glaucoma Pathogenesis
Authors: Patel Pinkal D. , Kodati Bindu , Clark Abbot F.
Published: September 2023

Abstract: The glucocorticoid receptor (GR), including both alternative spliced isoforms (GRa and GRb), has been implicated in the development of primary open-angle glaucoma (POAG) and iatrogenic glucocorticoid-induced glaucoma (GIG). POAG is the most common form of glaucoma, which is the leading cause of irreversible vision loss and blindness in the world. Glucocorticoids (GCs) are commonly used therapeutically for ocular and numerous other diseases/conditions. One serious side effect of prolonged GC therapy is the development of iatrogenic secondary ocular hypertension (OHT) and OAG (i.e. GC-induced glaucoma (GIG)) that clinically and pathologically mimics POAG. GC-induced OHT is caused by pathogenic damage to the trabecular meshwork (TM), a tissue involved in regulating aqueous humor outflow and intraocular pressure. TM cells derived from POAG eyes (GTM cells) have lower expression of GRb, a dominant negative regulator of GC activity, compared to TM cells from age-matched control eyes. Therefore, GTM cells have a greater pathogenic response to GCs. Almost all POAG patients develop GC-OHT when treated with GCs, in contrast to a GC responder rate of 40% in the normal population. Increased expression of GRb can block GC-induced pathogenic changes in TM cells and reverse GC-OHT in mice. Endogenous expression of GRb in the TM may relate to differences in the development of GC-OHT among the normal population. A number of studies have suggested increased levels of endogenous cortisol in POAG patients as well as differences in cortisol metabolism, suggesting that GCs may be involved in the development of POAG. Additional studies are warranted to better understand the molecular mechanisms involved in POAG and GIG in order to develop new disease modifying therapies to better treat these two sight threatening forms of glaucoma.
Estimating Water Transparency in a Shallow Hypertrophic Lagoon (Albufera of Valencia, Spain) Using Sentinel-2 Images
Authors: Molner Juan V. , Soria Juan M. , Pérez-González Rebeca , Sòria-Perpinyà Xavier
Published: September 2023

In this study, we investigated water transparency estimation models in the hypertrophic lagoon of the Albufera of Valencia using Sentinel-2 images. Water transparency, a crucial environmental indicator, was assessed via Secchi disk depth (ZSD) measurements. Three optical models (R490/R560, R490/R705, R560/R705) were explored to establish a robust algorithm for ZSD estimation. Through extensive field sampling and laboratory analyses, weekly data spanning 2018 to 2023 were collected, including water transparency, temperature, conductivity, and chlorophyll-a concentration. Remote sensing imagery from the Sentinel-2 mission was employed, and images were processed using SNAP software. The R560/R705 model, calibrated for turbid lakes, emerged as the most suitable. The algorithm's calibration was validated with high correlation coefficients (R2) in both calibration (0.6149) and validation (0.916) phases, demonstrating the model's accuracy in estimating ZSD. This new algorithm significantly outperformed a previous approach, highlighting the importance of tailoring algorithms to specific water body characteristics. The study contributes to improved water quality assessment and resource management, underscoring the value of remote sensing in environmental research.
Awareness, Attitudes and Willingness to Donate Biological Samples to a Biobank: A Survey of a Representative Sample of Polish Citizens
Authors: Pronicki Łukasz , Czech Marcin , Gujski Mariusz , Boguszewska Natalia
Published: September 2023

Background: ; Biotechnology is developing at an ever-increasing pace, and the progressive computerisation of health care and research is making it increasingly easy to share data. One of the fastest growing areas is biobanking. However, even with the best equipment and the best trained staff, a biobank will be useless without donors. For this reason, we have decided to gauge Polish citizens' awareness and attitudes towards biobanking and their willingness to donate biological samples. Methods: The survey was conducted among a nationwide group of 1,052 Poles aged 18 and over where the totals for gender, age and place of residence were selected according to representation in the population of adult Poles. The survey was conducted using the Computer Assisted Web Interview (CAWI) technique. Results:; N=701 (66.6%) respondents indicated that they had heard of scientific studies in which samples of biological material such as blood, saliva or urine are collected. More than half of respondents (N=613, 58.3%) have a positive opinion regarding scientific research in which samples of biological material are taken. Only N=220 (20.9%) of respondents had previously encountered the term biobanking. N=687 (65.3%) respondents would participate in a scientific study that biobanked biological material and health information. Conclusions: The level of knowledge and awareness of biobanks and their role in scientific research and the health care system among Polish citizens is low and requires education and information activities.
Meat Juice and Oral Fluid as Alternative to Serum for Aujeszky Disease Monitoring in Pigs
Authors: Carella Emanuele , Caruso Claudio , Moreno Martin Ana , Di Blasio Alessia , Oberto Francesca , Vitale Nicoletta , Masoero Loretta
Published: September 2023

Aujeszky Disease Virus (ADV) is a double-stranded DNA virus with a lipoprotein envelope. The natural hosts of the infection are suidae, but the virus can infect many other mammals. The gold-standard method identified by the WOAH for the diagnosis of Aujeszky disease is ELISA method. The objective of this study was to compare the performance of meat juice and oral fluid matrices using a commercial ELISA kit designed for serum. A total of 80 blood and oral fluid samples were collected from four pig farms selected for this study. Diaphragm muscle samples of about 100 g and blood samples were collected from 213 animals at the abattoir. These biological matrices were collected from the same animals and tested using a competitive ELISA kit to detect antibodies against ADV. The relative accuracy of the meat juice compared to that of the serum was 96.7% (95% CI: 93.3%-98.7%), with 206 correct results out of 213. The relative accuracy of the oral fluid compared to that of the serum was 61.3% (95% CI: 49.7%-71.9%), with 58 correct results out of 80. Meat juice has a better combination of sensitivity and specificity than oral fluid. The usage of meat juice in routine diagnostic examinations could be achieved after further investigations to optimize the procedure.
The Impact of Tele-Education on Collaborative Care Between Neurology and Algology
Authors: Kocasoy Orhan Elif , Kamacı İbrahim , Çetingök Halil , Selekler Macit , Köknel Talu Gül , Ozyalcin Süleyman , Bölükbasi Okan , Ozge Aynur
Published: September 2023

Algologists and neurologists play a significant role in management of headache. The study aimed to compare the headache management approaches of algologist and neurologists and evaluate the impact of telehealth education on their practices. A questionnaire was developed and sent to algologists and neurologists through social media and email. Demographic information, diagnostic and treatment approaches to a headache case, and the impact of telehealth education were evaluated 82 algologists and 97 neurologists completed the survey. There was no significant difference between diagnosis. However, the examination methods differed, with the neurologists relying on history and the algologists suggesting further investigations. Both groups agreed on the application of prophylaxis treatment, with botulinum toxin administration and classical prophylactic agents being accepted in both groups. The newest preventive treatment method was used more frequently in the Neurologists. Participants reported that online meetings had a positive impact on their daily practices, with 48% stating that they were reflected in their practice. Those who attended online meetings marked more up- to-date treatment options such as CGRP antagonists and Botulinum toxin. The study showed that algologists and neurologists had similar approaches to headache management, with differences in examination methods and the use of newer preventive treatment methods. Telehealth education had a positive impact on the participants, improving their knowledge of up-to-date treatment options.
Distributional Response of the Rare and Critically Endangered Ilex nanchuanensis to Climate Change in East Asia
Authors: Chen Zhiming , Luo Zhuzhu , Li Guang , He Renyuan , Wang Shuqin , Li Liangliang
Published: September 2023

Global climate change, dominated by climate warming, is seriously affecting the balance of global ecosystems, but the risk of species extinction is particularly high in low-altitude mountain areas. To clarify the response of the endemic and critically endangered species Ilex nanchuanensis to climate change, this study used the MaxEnt model to simulate and predict the potential habitat of I. nanchuanensis during the Last Interglacial, Last Glacial Maximum, the current period, and two future periods (the 2050s and 2070s). The results showed that the hottest monthly minimum temperature is the most important climatic factor affecting the geographical distribution of I. nanchuanensis. Furthermore, I. nanchuanensis will be at risk of population shrinkage and extinction in the future, with the center of mass moving further northwest as concentrations of greenhouse gases increase, especially in the 2070s, when its geographical distribution shrinks the most under the RCP6 scenario. Global warming is causing habitat degradation for many species and will continue to migrate to higher altitudes and latitudes in the future, seriously affecting the global ecosystem balance. Therefore, to actively respond to the impacts of climate change, protected areas should be established around the geographical distribution centers of species, and core, buffer, and experimental areas should be scientifically and rationally delineated for the conservation and cultivation of germplasm resources.
Triclabendazole-Binding Pocket Identified in Fasciola hepatica Carboxylesterase B
Authors: Miranda-Miranda Estefan , Cossío-Bayúgar Raquel , Trejo-Castro Lauro , Aguilar-Díaz Hugo
Published: September 2023

The expression of the Fasciola hepatica Carboxylesterase type B (CestB) gene is induced in response to the anthelmintic triclabendazole (TCBZ), resulting in a significant increase in enzymatic specific activity. Furthermore, the amino acid sequence of CestB exhibits variations that could lead to substantial amino acid substitutions at the ligand-binding site. These substitutions have the potential to affect the interaction between the ligand and the protein, as well as the catalytic properties of the enzyme. The objective of this study was to identify new CestB polymorphisms in TCBZ-resistant parasites using 3D modeling against the metabolically oxidized form of the anthelmintic TCBZSOX. Our aim was to observe the formation of TCBZSOX-specific binding pockets that could potentially explain the resistance to anthelmintic agents. We identified a CestB polymorphism in a TCBZ-resistant strain of parasites exhibiting three radical amino acid substitutions at positions 147, 215, and 243, resulting in the formation of a TCBZSOX-affinity pocket capable of binding the anthelmintic drug. Additionally, our 3D modeling analysis revealed that these amino acid substitutions also had an impact on the configuration of the CestB catalytic site, affecting the enzyme's interaction with chromogenic carboxylic ester substrates and altering its catalytic properties; however, the identified TCBZSOX-binding pocket was located far from the enzyme's catalytic site, making the enzymatic hydrolysis of TCBZSOX theoretically impossible. Nonetheless, the increased affinity for the anthelmintic may explain a drug-sequestration type of anthelmintic resistance and lays the foundation for the development of a molecular diagnostic tool for identifying anthelmintic resistance in F. hepatica.
Predicting the Choice of Online or Offline Shopping Trips Using a Deep Neural Network Model and Time Series Data: A Case Study of Tehran, Iran
Authors: Dasoomi MohammadHanif , Naderan Ali , Allahviranloo Tofigh
Published: September 2023

This study investigates the factors influencing the choice of online and offline shopping trips and their impacts on urban transportation, environment, and economy in Tehran, Iran. A questionnaire survey was conducted to collect data from 1,000 active e-commerce users who made successful orders in both online and offline services in the last 20 days of 2021 in areas 2 and 5 of Tehran. A deep neural network model was developed to estimate the type of shopping trip based on 10 indicators, such as age, gender, car ownership, delivery cost, product price, etc. The performance of the model was compared with three other algorithms: MLP, decision tree, and KNN. The results showed that the deep neural network model had the highest accuracy of 95.63%. The most important factors affecting the choice of shopping trips were delivery cost, delivery time, and product price. This study provides insights for transportation planners, e-commerce managers, and policymakers to design effective strategies for reducing transportation costs, pollutant emissions, urban traffic, and increasing user satisfaction and sustainable development.
A Narrative Literature Review on the Role of Exercise Training in Managing Type 1 and Type 2 Diabetes Mellitus
Authors: Piras Alessandro , Raffi Milena
Published: September 2023

Diabetes mellitus (DM) is a metabolic disease characterized by chronic hyperglycemia associated with impaired carbohydrate, lipid and protein metabolism, with concomitant absence of insulin secretion or reduced sensitivity to its metabolic effects. Patients with diabetes mellitus have 30% more risk of developing heart failure and cardiovascular disease with respect to healthy people. Heart and cardiovascular problems are the first cause of death worldwide and the main complications which lead to high healthcare costs. Such complications can be delayed or avoided by taking prescribed medications in conjunction with a healthy lifestyle (i.e. diet and physical activity). The American College of Sports Medicine and the American Diabetes Association recommend that diabetic people reduce total sedentary time by incorporating physical activity in their weekly routine. This narrative literature review has the aim to summarize and present the main guidelines, pre-exercise cardiovascular screening recommendations, and considerations for patients with diabetes and comorbidities who are planning to participate in regular exercise regimens.
Fruits and Vegetables Yield Stability in Colombia: Identifying Strong National Cropping Systems
Authors: Parra-Londono Sebastian , Tigreros Jaime Andres , Montoya-Correa Carlos Alberto
Published: September 2023

In recent years the yield of fruits and vegetables have been decreasing in Colombia, threatening national food security. Analysis of crop production data may lead to identifying cropping systems that have shown better adaptability to changes in climatic and non-climatic factors associated with agricultural production. The open database AGRONET keeps data of the agricultural activities conducted in Colombia, allowing to find the information organized by crops, regions and years; each row of the database registers farm information in Colombia. Aiming to identify resilient crops systems, agricultural data of fruits and vegetables were analyzed. First, trends in crop production were studied by year and locations, detecting the regions and crops with highest yields in the period from 2006 until 2020. Then, mixed linear regression and principal components analysis were applied to elucidate the relation between non-climatic factors and crop yield. In Colombia, vegetable production was more efficient than fruits, observing yields of 10.23 and 13.33 t ha-1, respectively. On the other hand, the Colombian central region showed high yields for vegetables, while for fruits this was exhibited in northern and eastern locations. In the present study, yield variation responded to changes in the location of crop systems, while years had no effect on vegetable production. Furthermore, the price of the agricultural product and the cost of fertilizers were associated with the yield of the analyzed crops systems. In Colombia, carrot, cabbage, tomato papaya and pineapple are resilient crops whose yield increases especially by the regions where they are cultivated.
Low-cost Open Source Tool for Frugal Computer Simulation of Robotics Nonlinear Control
Authors: Torres Felipe J. , Martínez Israel , Aguirre Fabio A. , Garcia-Murillo Mario A. , Balvantín-García Antonio , Núñez Diego A.
Published: September 2023

Commonly, professors, students and researchers from universities around the world use software distributed under a license agreement for computer simulation purposes, which requires a computer with considerable hardware capabilities. Consequently, this implies a high cost to conduct simulations that require implementing numerical methods in all areas of engineering, particularly in the field of robotics and nonlinear control. This paper presents the design and results analysis of a low-cost and open-source frugal computer simulation tool with applications to robotic nonlinear control, for instance, for numerical simulations of manipulator robot control based on dynamic models. Using a single board minicomputer with with reduced computing power, Raspberry Pi, together with free software, GNU-Octave, trajectory tracking control simulations in the joint space of a Selective Conformal Assembly Robot Arm (SCARA) are achieved by solving a system of nonlinear differential equations, represented in matrix form, which includes the control law and the system model. The results of the proposed alternative are compared by running the same simulation code on a laptop computer using MATLAB and GNU Octave, which show minimal deviations and reasonable time complexity. Moreover, considering the frugality curve calculated for this approach, in addition to the low acquisition cost of the simulation software tool, it would allow the creation of a simulation laboratory in some universities with budgetary constraints for educational and research purposes.
The Metrization Problem in [0, 1]-Topology Peng
Authors: Chen Peng
Published: September 2023

The paper discusses the classification of fuzzy metrics based on their continuity conditions, dividing them into Erceg, Deng, Yang-Shi, and Chen metrics. It explores the relationships between these types of fuzzy metrics, concluding that a Deng metric in [0,1]-topology must also be Erceg, Chen, and Yang-Shi metrics. The paper also proves that the product of countably many Deng pseudo-metric spaces remains a Deng pseudo-metric space, and demonstrates some σ-locally finite properties of Deng metric space. Additionally, the paper constructs two interrelated mappings based on normal space and concludes that if a [0,1]-topological space is T1 and regular, and its topology has a σ-locally finite base, then it is Deng metrizable, and thus Erceg, Yang-Shi, and Chen metrizable as well.
Ni-Cu Ion-Exchange in Anolyte: An Efficacious Approach of Nickel Extraction
Authors: Tang Xiaowei , Ju Kunyu
Published: September 2023

Various methods including electrochemical purification, chemical precipitation, solvent extraction, and ion-exchange resins, have maturely been used for removal of copper from nickel anolyte. Interestingly, these approaches of copper removal from nickel anolyte by precipitation are well used as the primary industrial method in nickel production again. However, these methods suffer from several severe drawbacks in industrial practices. One is that a small amount of nickel precipitates with copper in slags，resulting in slag treatment difficulties. Second, this process requires an extremely high activity of the sulfide-based copper removal agents which results in high production costs; the short storage period of the copper removal agent is another drawback of this method. These have been the key challenges in the smelting process of nickel. Herein, we present a comprehensive review of the nickel removal methods used for nickel anolyte purification, electrochemical purification, chemical precipitation, solvent extraction, and ionexchange resins. The advantages and feasibilities of each technique in industrial applications are also explored and analyzed. Finally, we demonstrate that ion-exchange resin-based extraction method can pave a new path for metallurgical research on nickel.
Near-Infrared Spectroscopy and Chemometrics Methods to Predict the Chemical Composition of Cratylia Argentea
Authors: Abreu Lucas Freires , Lana Angela Maria Quintao , Climaco Leonardo Campos , Matrangolo Walter Jose Rodrigues , Barbosa Elizabete Pereira , Da Silva Karina Toledo , Rowntree Jason E , Da Silva Edilane Aparecida , Simeone Maria Lucia Ferreira
Published: September 2023

Cratylia argentea is a leguminous shrub with a great potential for livestock feeding in tropical areas. However, time consuming and labor-intensive methods of chemical analysis limits the understanding of its nutritive value. Near infrared spectroscopy (NIRS) is a low-cost technology that has been widely used in forage crops to fasten the assessment of its chemical composition. The objective of this study was to develop prediction models to assess crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF) and dry matter (DM) of Cratylia based on NIRS and partial least square analysis. A total of 155 samples were harvested at different maturity levels and used for model development, whereas 107 were used for calibration and 48 for external validation. The cross-validation presented Root Mean Square Error of Prediction of 0.77, 2.56, 3.43, and 0.42; a Ratio of Performance to Deviation of 4.8, 4.0, 3.8, and 3.4; an R2 of 0.92, 0.92, 0.87, and 0.84 for CP, NDF, ADF, and DM, respectively. Based on the obtained results, we conclude the ability to predict chemical parameters of Cratylia with the current model was accurate. This way, livestock producers and researchers may use it to fasten the assessment of Cratylia’s nutritive value.
Prediction of Daily Ambient Temperature and Its Hourly Estimation Using Artificial Neural Networks in Urban Allotment Gardens and in an Urban Park in Valladolid, Castilla y León, Spain.
Authors: Tomatis Francisco , Diez Francisco J. , Wilhelm M. Sol , Navas-Gracia Luis Manuel
Published: September 2023

Cities exemplify the evolving world with changing demographics and climates. Urban green spaces play a crucial role in improving the quality of life of people through their potential to mitigate temperatures. Therefore, comprehending their impact is of para-mount interest. Given the challenges in obtaining temperature data from urban locations, this study develops Artificial Neural Networks (ANNs) to predict daily and hourly temperatures in Valladolid, Spain, with a particular focus on urban allotment gardens and a forested urban park. ANNs were built and evaluated from various combinations of inputs (X), hidden neurons (Y) and outputs (Z) under the practical rule of "making net-works simple, to obtain better results". The best performing model was 6-Y-1 ANN archi-tecture with an impressive result of Root Mean Square Error (RMSE) = 0.42°C in the urban garden called Valle de Arán. However, other five ANN architectures were also tested (7-Y-5; 6-Y-5; 7-Y-1; 3-Y-Z and 2-Y-1). ANNs dedicated to urban temperature analysis hold immense potential for urban planning and research, aiding in under-standing the urban climate, forecasting future temperatures, identifying temperature mitigation strategies and even for managing urban crops
Drought Projections in Balochistan Using CORDEX-SA Data
Authors: Irshad Noman , Dars Ghulam Hussain , Ansari Kamran , Krakauer Nir , Ahmed Mansoor
Published: September 2023

Water resources planners and policymakers often ask questions about the future projections of drought characteristics (events, intensity, severity, duration, and peak) under different climatic scenarios. This study focused on quantifying the historical (1951-2005) and future (2026-2100) drought characteristics using the Standardized precipitation index (SPI) under RCP 4.5 and RCP 8.5 climate scenarios for the Balochistan province of Pakistan, an arid and drought-vulnerable region. Precipitation data of MPI-ESM-LR_RCA4 RCM was obtained from the Coordinated Regional Climate Downscaling Experiment South Asia (CORDEX-SA). The CORDEX-SA data was interpolated at 12-gauge stations and bias-corrected by the distribution mapping method using Asian Precipitation - Highly-Resolved Observational Data Integration towards Evaluation (APHRODITE) data. The drought characteristics were calculated based on standardized precipitation index (SPI), and intercompared between northern Balochistan (NB) and southern Balochistan (SB). It was found that the northern Balochistan (NB) region has suffered more droughts in the historical period and is also projected to have more severe and intense droughts than SB region. It was also found that with the increase of drought events, the duration reduces, which means that the higher the drought events at a station, the lower the drought duration. Government officials should focus more on managing the already few freshwater resources sustainably, given the increased likelihood of droughts in Balochistan due to climate change.
A Review in Childhood Acute Myeloid Leukemia: Diagnosis and Novel Treatment
Authors: Lin Pei-Chin , Tseng Serena , Lee Mu-En
Published: September 2023

Acute myeloid leukemia (AML) is the second common hematologic malignancy in children. The incidence of childhood AML is much lower than acute lymphoblastic leukemia (ALL), which makes the childhood AML a rare disease in children. The role of genetic abnormalities in AML classification, management and prognosis prediction is much more important than before. The WHO classification of myeloid neoplasms and the European LeukemiaNet (ELN) classification were both revised in 2022. The application of the new information in childhood AML will be upcoming in the next few years. The frequency of each genetic abnormality in adult and childhood AML is different, therefore, in this review we emphasize in well-known genetic subtypes in childhood AML, including Core-binding factor AML (CBF AML), KMT2Ar (KMT2A/11q23 rearrangement) AML, normal karyotypes AML with somatic mutations, unbalanced cytogenetic abnormalities AML, NUP98 11p15/NUP09 rearrangement AML and acute promyelocytic leukemia (APL). Current risk group classification, management algorithm in childhood AML and novel treatment modalities, such as targeted therapy, immune therapy, chimeric antigen receptor (CAR) T-cell therapy are reviewed. Finally, the indications of hematopoietic stem cell transplantation (HSCT) in AML are discussed.
Low-Crystallinity Index Chalcedony from Longhua, China: Characteristics and Formation
Authors: Yan Qiuli , Shi Guanghai
Published: September 2023

A low-crystallinity index chalcedony was found in the rhyolitic ignimbrite of the Late Jurassic Zhangjiakou Formation, located in Longhua County, Hebei Province, China. This chalcedony occurs as fillings along the fragile fractures of the host rock and is distinct from any other chalcedony deposits, such as the known basalt and carbonate-related types. The host rock is rhyolitic ignimbrite, comprising sanidine (50–70 vol.%), plagioclase (10–15 vol.%), quartz (8–10 vol.%), magnesian biotite (3–5 vol.%), and accessory minerals. The chalcedony appears as long lenticular veins and irregular-shaped bodies, occasionally containing small fragments of the surrounding rock at the boundary. It is colored in yellow, red, and/or white/colorless, with physical properties of specific gravity 2.55–2.56, reflection index of 1.54, Mohs hardness of 6.07–6.34, and weight loss of 1.97%–2.32% by heating. From the boundary to the inner center, its growth structure changes from comb-like macrocrystalline quartz to thin fiber crystallites and then to a relatively uniform cryptocrystalline phase, indicating precipitation from a crystalline to the cryptocrystalline sequence. Electron probe and Raman spectroscopy analyses reveal that the component minerals of the chalcedony are α-quartz and moganite and that the red inclusions are hematite. Quartz in chalcedony exhibits platelet shapes with tiny pores, which are cemented by nanograins, and such a structure is closer to that of opal. It’s crystallinity indexes (CIs) range ~1–3, as indicated by the X-ray diffraction patterns. This low CI and structural features, together with its occurrence, suggest a low temperature of 40°C–80°C during its formation. All these properties show a distinction from those of the most reported chalcedonies. This chalcedony is interpreted as an intermediate transitional type from normal chalcedony to opal, shedding new light on understanding microcrystalline silica mineral aggregate and exploration for a similar gem deposit.
Synthetic Graphic Well Log Generation Using an Enhanced Deep Learning Workflow: Imbalanced Multiclass Data, Sample Size, and Scalability Challenges
Authors: Jamshidi Gohari Mohammad Saleh , Niri Mohammad Emami , Sadeghnejad Saeid , Ghiasi-Freez Javad
Published: September 2023

The present study introduces an enhanced deep learning (DL) workflow based on transfer learning (TL) for producing high-resolution synthetic graphic well logs (SGWLs). To examine the scalability of the proposed workflow, a carbonate reservoir with a high geological heterogeneity has been chosen as the case study, and the developed workflow is evaluated on unseen data (i.e., blind well). Data sources include conventional well logs and graphical well logs (GWLs) from neighboring wells. During drilling operations, GWLs are standard practice for collecting data. GWL provides a rapid visual representation of subsurface lithofacies to establish geological correlations. This investigation examines five wells in a southwest Iranian oil field. Due to subsurface geological heterogeneities, the primary challenge of this research lies in addressing the imbalanced facies distribution. The traditional artificial intelligence strategies that manage imbalanced data [e.g., the modified synthetic minority oversampling technique (M-SMOTE) and Tomek link (TKL)] are mainly designed to solve binary problems. However, to adapt these methods to the upcoming imbalanced multiclass situation, one-vs.-one (OVO) and one-vs.-all (OVA) decomposition strategies and ad-hoc techniques are used. Well-known VGG16-1D and ResNet18-1D are used as adaptive very-deep algorithms. Additionally, to highlight the robustness and efficiency of these algorithms, shallow learning approaches of support vector machine (SVM) and random forest (RF) as conventional facies classification methods are also used. The other main challenge is the need for enough data points to train the very deep algorithms, resolved through TL. After identifying a blind well, the other four wells’ data are entered for model training. The average kappa statistic and F-measure, as appropriate imbalance data evaluation metrics, are implemented to assess the designed workflows’ performance. The numerical and visual comparison analysis shows that the VGG16-1D TL model performs better on the blind well data set when combined with the OVA scheme as a decomposition technique and TKL as a binary imbalance data combat tactic. An average kappa statistic of 86.33% and a mean F-measure of 92.09% demonstrate designed workflow superiority. Considering the prevalence of different imbalanced facies distributions, the developed scalable workflow can be efficient and productive for generating SGWL.
Educational Interventions for Imposter phenomenon: a PRISMA scoping review protocol
Authors: Siddiqui Zaha Kamran , Church Helen , Jayasuriya Raveen , Boddice Timothy , Lewis Chris , Tomlinson James
Published: September 2023

Background: IP is a subjective feeling of intellectual fraud that is predominant in high-achieving individuals regardless of gender. IP is associated with physical and mental health at the individual level. Literature suggests various hypothetical strategies to overcome IP, with limited research on how these strategies are being implemented in healthcare systems. To confront the possible impact of IP within healthcare, it is essential to explore existing educational interventions and understand how these equip individuals and institutions with skills to overcome the effects of IP across a wide variety of professional settings.
Aim: This scoping review aims to understand the educational interventions developed to equip high-performance individuals with skills to manage imposter phenomenon (IP).
Methods: The scoping review will comprise articles found by searching the MEDLINE (Ovid), Psych INFO, SCOPUS, and Web of Science databases, along with gray literature searched through Google Scholar. Studies will be assessed by two independent reviewers and screened against the inclusion criteria for eligibility to be included in the review. All published studies and gray literature, such as reports, commentaries, website content describing an educational intervention to IP, will be included in the scoping review. Interventions not addressing IP such as mimicking syndromes: Capgras syndrome, or isolated symptoms such as burnout will be excluded from the study. Furthermore, studies detailing prevalence of IP without any educational intervention will also be excluded.
Discussion: At an institutional level, IP threatens inclusion and diversity. This is due to the debilitating self-doubt that limits professionals from applying to leadership and management roles within healthcare. This review will provide healthcare professionals with a wider understanding of educational interventions available to tackle IP in their workplace. Further the review will highlight gaps for future research and innovation.