Future Insights Research Articles

P-636 Euploid blastocysts obtained in advanced maternal age women either in donor or autologous egg cycles showed similar live birth rates: a retrospective cohort study

Abstract Study question Do euploid blastocysts have the same implantation and live birth rate in autologous and donor egg cycles in patients with advanced maternal age (AMA)? Summary answer Euploid blastocysts transferred in AMA patients showed that implantation and live birth rates (LBR) were not significantly different between reproductively younger and older women. What is known already Aneuploidy rates increase steadily with age, reaching >80% in women >42 years old. The high prevalence of aneuploidies may provide an explanation for the low LBR achieved by assisted reproductive treatments, especially for women with AMA. Similarly, among oocyte donors, age is critical to achieving reproductive success independently of the recipients’ age. In donor cycles, recipients using oocytes from older donors had a statistically significantly lower LBR than younger donors. Currently, it still remains unclear whether the LBR differs between young donors versus old infertile patients in the context of euploid blastocyst transfers. Study design, size, duration Multicenter retrospective study with the preimplantation genetic test for aneuploidies (PGT-A) in both autologous and donor oocytes cycles between January 2018 and January 2021 was conducted at three different institutions (IVI-RMA, GeneraLife and Humanitas Fertility Center). 556 patients were included and matched 1:1 for the age of recipients, euploid blastocyst morphological quality, and day of development. In the frozen embryo transfers, endometrial preparation was done using hormonal replacement therapy (HRT) or natural cycles (NC). Participants/materials, setting, methods AMA patients older than 39 years underwent IVF. 556 patients who underwent autologous or donor oocyte cycles with at least one euploid blastocyst transferred were matched for oocyte age, blastocyst morphological quality and day of development. Blastocyst ploidy was assessed by aCGH or NGS analysis. Patients with uterine pathologies reported in the dataset were excluded. The primary outcome was LBR per first euploid blastocyst transfer. Outcomes were adjusted for confounders via logistic regression analyses. Main results and the role of chance 278 single euploid blastocysts tested by PGT-A were transferred in both autologous and donor oocyte cycles. No statistical differences were reported in the maternal age at transfer in the two groups (41.91 ± 2.03 and 41.75 ± 1.98, p = 0.55), endometrial thickness [(8.67, 95%CI: 8.45-8.88) and (8.36, 95%CI: 8.05-8.67)] and type of endometrial preparation (HRT or NC). Implantation rate and pregnancy rate were similar without statical difference in autologous or donor cycles, respectively [57.91%, (95%CI: 51.87-63.78) versus 56.83%, (95%CI: 50.79-62.74); p = 0.99)] and N = 158/278 (56.83%, 95%CI: 50.79-62.74) versus N = 161/278 (57.91%, 95%CI: 51.87-63.78), p = 0.86. The rate of ectopic pregnancy was not statistically different in both arms. Even the miscarriage rate was comparable in autologous N = 46/158, 16.55% (95%CI:12.38-21.45) versus donor group N = 45/161, 16.19%, (95%CI:12.06-21.05); p = 0.98. The LBR was not statistically different in autologous N = 111/278 (39.93%, 95%CI:34.13-45.95) and donor group 114/278 (41.01%, 95%CI:35.17-47.04), p = 0.86. No statistical difference was reported for gestational age and birthweight at delivery. The logistic regression analyzed as putative confounders: oocyte age, number of inseminated MII-oocytes, zygotes and euploid blastocysts, sperm parameters, endometrial preparation and endometrial thickness showed no statistical differences. Limitations, reasons for caution Despite the matched design, the retrospective nature is the major limitation of this study. Also, patients received PGT-A using NGS and CGH arrays technology. The aCGH analysis is less sensitive than more recent NGS technology. Lastly, the prevalence of adenomyosis could be underestimated due to retrospective data collection. Wider implications of the findings The dramatic decline in IVF treatment success is primarily caused by aneuploidies. Euploid blastocysts show LBR largely independent of oocyte age. Our study suggests no uterine effect of aging. The reproductive decline in women is mainly related to meiotic failure, therefore future insights should develop strategies to overcome chromosomal aneuploidies. Trial registration number NA

ARE GENERATIVE ADVERSARIAL NETWORKS CAPABLE OF GENERATING NOVEL AND DIVERSE DESIGN CONCEPTS? AN EXPERIMENTAL ANALYSIS OF PERFORMANCE

AbstractGenerative Adversarial Networks (GANs) have shown stupendous power in generating realistic images to an extend that human eyes are not capable of recognizing them as synthesized. State-of-the-art GAN models are capable of generating realistic and high-quality images, which promise unprecedented opportunities for generating design concepts. Yet, the preliminary experiments reported in this paper shed light on a fundamental limitation of GANs for generative design: lack of novelty and diversity in generated samples. This article conducts a generative design study on a large-scale sneaker dataset based on StyleGAN, a state-of-the-art GAN architecture, to advance the understanding of the performance of these generative models in generating novel and diverse samples (i.e., sneaker images). The findings reveal that although StyleGAN can generate samples with quality and realism, the generated and style-mixed samples highly resemble the training dataset (i.e., existing sneakers). This article aims to provide future research directions and insights for the engineering design community to further realize the untapped potentials of GANs for generative design.

Diverse Future Leadership Insight From Successful Managers [Women in Engineering

Diverse Future Leadership Insight From Successful Managers [Women in Engineering

Regulation of autophagy by plant‐based polyphenols: A critical review of current advances in glucolipid metabolic diseases and food industry applications

AbstractAutophagy is a complex self‐degrading process, and its imbalance adversely affects local (metabolically active organs) or systemic metabolism, resulting in metabolic dysfunction correlated with obesity, fatty liver, and type 2 diabetes. Polyphenols are plant secondary metabolites and their ingestion may offer beneficial effects on biological processes, including cell proliferation, cell cycle, apoptosis and autophagy. In this review, the effects of plant‐based polyphenols on autophagy and the underlying mechanisms in the regulation of glucolipid metabolic diseases (GLMDs) are examined in the context of potential health benefits. The available evidence, mainly from animal models, strongly supports that polyphenols improve the metabolic functions of different organs by acting on various molecular targets related to autophagic flux. Multiple autophagic pathways, including cAMP, AMPK, MAPK, AKT, SIRT1, PI3K, Nrf2/HO‐1, PINK1/Parkin, PPARδ, and miRNAs have been implicated in the improvement of GLMDs by polyphenols. Moreover, the potential utilization of polyphenol‐meditated autophagy in the food industry was discussed. The current review provides a comprehensive understanding of the prospective role and mechanisms of polyphenol‐regulated autophagy in GLMDs and opens up future insights into its application to the healthcare and food industries.

Toward Design and Implementation of Self-Balancing Robot Using Deep Learning

In the Internet of Things (IoT) era, an immense amount of sensing devices are obtained and produce various sensory data over time for a wide range of disciplines and applications. These devices will result in significant, fast, and real-time data streams based on the utilization characteristics. Utilizing analytics over such data streams to identify new information, model future insights, and make control decisions is a necessary process that makes IoT a worthy paradigm for businesses and a quality-of-life improving technology. This paper presents a study of digital agriculture and its significance in terms of the application of an IoT-based device — a two-wheeled self-balancing robot — followed by a thorough procedural explanation of the development of the device, which begins with the mathematical modeling of the system through the Euler–Lagrange method to obtain the equations of motion for the same and linearize the equation to define the control method to be used to balance the robot structure, all based on the concept of the inverted pendulum. Then paper discusses the suitable and the most efficient control method, which is the linear quadratic regulator (LQR), for these robots. Then deep learning-based LQR (DL-LQR) method is implemented in the robots performing the algorithm to balance it successfully.

Family tourism effects for low‐income families – Past reality for future insights

AbstractAlthough the benefits of tourism are recognized, there are still doubts about the potential effects of family tourism for specific types of families. This qualitative study aims to characterize past family tourism practices of a sample of low‐income families with children and examine its effects. Interviews were conducted, including adult(s) and children of each family. Results reveal that families reported important benefits and that differences between the perceptions of mothers and fathers exist. Further research is needed to consider different subtypes of families. Reflection on challenges faced by initiatives and research targeting this segment are presented.

How Big data Analytics Supports Project Manager in Project Risk Management – Cases from UAE Health Sector

Abstract
 
 Big data analysis allows analysts, researchers, and business users to make better and faster decisions using data that was previously inaccessible or used. Companies can use advanced analytics techniques such as text analysis, machine learning, predictive analytics, data mining, statistics, and natural language processing to gain new insights and insights from previously untapped data sources independently or with existing enterprise data. Significant challenges are still in how to deal with this data and maximize their use, so large data have become the clock that has become the most national, regional, and international institutions, and a broad range of database management, methodologies and measures that can be adopted for the exploitation of large data in all areas of life.
 This paper investigates the effects of big data analytics on project risk management with examples from Healthcare sector in UAE. Inclusive research has been done by searching approximately more than 20 references resulted in a literature review studied the effect of implementing data analytics in business, technology, industry, and society businesses aspects. A research methodology has been done by interviewing professionals from healthcare field investigating further the role of Data analytics in analyzing and managing data in healthcare, its benefits in predicting risks and improving healthcare outcomes and future insights.
 This research’s result reveals that collecting data and applying data analytics even in businesses or healthcare represent an important kind of digital transformation. An obvious finding from this research is that business intelligence and data analytics has been implemented widely in UAE healthcare sector by both government and privet sectors resulting in opportunities that develop and emphasize positive changes to this sector.

Concept drift from 1980 to 2020: a comprehensive bibliometric analysis with future research insight

Concept drift from 1980 to 2020: a comprehensive bibliometric analysis with future research insight

Recent Advances in Machine Learning-Based Models for Prediction of Antiviral Peptides.

Viruses have killed and infected millions of people across the world. It causes several chronic diseases like COVID-19, HIV, and hepatitis. To cope with such diseases and virus infections, antiviral peptides (AVPs) have been applied in the design of drugs. Keeping in view the significant role in pharmaceutical industry and other research fields, identification of AVPs is highly indispensable. In this connection, experimental and computational methods were proposed to identify AVPs. However, more accurate predictors for boosting AVPs identification are highly desirable. This work presents a thorough study and reports the available predictors of AVPs. We explained applied datasets, feature representation approaches, classification algorithms, and evaluation parameters of performance. In this study, the limitations of the existing studies and the best methods were emphasized. Provided the pros and cons of the applied classifiers. The future insights demonstrate efficient feature encoding approaches, best feature optimization schemes, and effective classification techniques that can improve the performance of novel method for accurate prediction of AVPs.

Protective Relaying Coordination in Power Systems Comprising Renewable Sources: Challenges and Future Insights

This article provides a comprehensive review of optimal relay coordination (ORC) in distribution networks (DNs) that include distributed generators (DGs). The integration of DGs into DNs has become a real challenge for power system protection, as the power flow changes from unidirectional to bidirectional, which complicates the relay settings. The introduction of DGs in DNs requires changes and modifications in the protective schemes to maintain proper operation, reliability, stability, and security of the system. This paper focuses on the impacts of DGs penetration into DNs, including the effects on protective scheme coordination. Various expressions for characterizing the overcurrent (OC) coordination problem, as well as related solution attempts, are discussed. Several optimization strategies and techniques are suggested by scientists to deal with coordination optimization problems aiming to achieve less computation time and better accuracy. All these efforts ultimately aim to define optimal relay settings to achieve ORC by generating the optimal setting of cascading relative OC relays. This comprehensive review provides a broad overview of the contributions of scholars in recent publications in this field, with more than 210 articles reviewed and analyzed. It is a valuable resource for other researchers in the same field who aim to tackle ORC problems in their future endeavors.

The trend of forest ecosystem services assessment in eastern India: a review for future research insights

Ecosystem services (ES) are becoming a burgeoning topic presently playing a crucial role in sustaining human well-being, socioeconomic growth, and addressing environmental management and sustainability. The purpose of our review was to overview research trends of the forest ecosystem services (FES) in eastern India and the research methodologies adopted to evaluate them. To systematically study the FES literature, 127 articles pertaining to the term FES during the period 1991 to 2021 were reviewed through a quantitative analysis. The analytical outcome emphasized (1) the research aspects of FES and its types along with regional distribution, (2) the scenario of FES in eastern India with respect to other ES and India, (3) the quantitative trend of FES research over 30years period, (4) the employed methodological approaches, and (5) the existing research gaps and prospects. Our findings suggest that the publication numbers are quite low in eastern India, as only 5 peer-reviewed articles were found on FES. The result also indicated that the majority of studies primarily focused on provisioning services (85.03%) and the survey/interview method gained more popularity as a primary data source. Most of the earlier studies employed basic assessments like product values or individual income. We also discussed the advantages as well as limitations of the employed methodologies. These findings further highlight the significance of valuing various FES collectively rather than individually and contribute to providing pertinent information for the FES literature scenario, which may help to strengthen forest management as well.

Molecular characterization of the SAUR gene family in sweet cherry and functional analysis of PavSAUR55 in the process of abscission

Small auxin up RNA (SAUR) is a large gene family that is widely distributed among land plants. In this study, a comprehensive analysis of the SAUR family was performed in sweet cherry, and the potential biological functions of PavSAUR55 were identified using the method of genetic transformation. The sweet cherry genome encodes 86 SAUR members, the majority of which are intron-less. These genes appear to be divided into seven subfamilies through evolution. Gene duplication events indicate that fragment duplication and tandem duplication events occurred in the sweet cherry. Most of the members mainly underwent purification selection pressure during evolution. During fruit development, the expression levels of PavSAUR16/45/56/63 were up-regulated, and conversely, those of PavSAUR12/61 were down-regulated. Due to the significantly differential expressions of PavSAUR13/16/55/61 during the fruitlet abscission process, they might be the candidate genes involved in the regulation of physiological fruit abscission in sweet cherry. Overexpression of PavSAUR55 in Arabidopsis produced earlier reproductive growth, root elongation, and delayed petal abscission. In addition, this gene did not cause any change in the germination time of seeds and was able to increase the number of lateral roots under abscisic acid (ABA) treatment. The identified SAURs of sweet cherry play a crucial role in fruitlet abscission and will facilitate future insights into the mechanism underlying the heavy fruitlet abscission that can occur in this fruit crop.

An Evaluation of Inequality of Enterprising Women in Developing Countries: A Case Study of Nepal

This study aims to analyze the existence of gender inequality in Nepalese society and the response of the government towards it through policy documents. It also explores the changing scenario of women representation in the political and public sector because of the government policies. This research provides a critical review of the government policies and social practices regarding affirmative action and gender equality in Nepal. This research further unravels the systematic review of policy documents and future insight into government policies to enhance the position of women in public sector employment.
 This research is based on secondary data and a descriptive method has been adopted to show the status of women in Nepal. Secondary data were taken from the academic published articles and policy documents of the Government of Nepal. This research has found that the Government of Nepal has taken up aggressive steps to ensure gender equality in each sector by increasing representation of women. The latest constitution of Nepal, 2007 and the second amendment of Civil Service Act, 1993 are the key policy documents from which, women representation in public sector has been increasing marvelously. Hence, the country has been moving towards gender equality and has impacted positively on society. It could be an example for other developing countries as well.

Evaluation of geosynthetic interface friction at low normal stress: comparison between two different test procedures

The interface friction between geosynthetics has previously been extensively studied with reference to medium-high contact stresses. The interface strength at low contact stress is a less investigated chapter whose importance, however, is evident for the stability of geosynthetic landfill barriers during the construction stage and of the covering systems. The inclined plane is the most used laboratory test for measuring the geosynthetic interface friction at normal stresses as low as 5 kPa. This type of test, however, is not free from criticalities, due to the non-uniformity of the contact stresses induced by the inclination of the plane. Alternatively, it is possible to extrapolate the results of the classic direct shear test, which, however, generally cannot be performed at such low contact stress values. The paper compares data results provided by inclined plane tests and an experimental apparatus capable of performing horizontal shear tests at a vertical stress of 5 kPa. The peculiarity of this device is to guarantee a constant growth rate of the tangential stress equivalent to what happens with the inclined plane test. The good agreement of the interface strength data obtained for two different geosynthetic interfaces leads the way for possible future innovations and insights on the topic.

Prioritization of heat transfer fluids in parabolic trough solar systems using CFD-assisted AHP-VIKOR approach

Parabolic trough solar collectors (PTSCs) are proven technologies and are used in various fields including concentrating solar power, integrated solar combined cycle, industrial process heat, air conditioning, and desalination. The selection of heat transfer fluid (HTF) is a part of the design consideration of concentrating solar technologies (CST) since its technical specifications have a significant effect on the system configuration, operating conditions, and levelized energy cost. Several HTFs including water, thermal oils, molten salts, and gases are already in use for PTSC systems, and others including liquid metals, ionic liquids, and nanofluids are still being tested. Each HTF has pros and cons; thermal and thermodynamic evaluations are practical to compare the performance of an HTF with that of its counterparts however they are insufficient to attribute a parabolic trough CST in terms of design concerns. This study has presented an integrated AHP-VIKOR (Analytical Hierarchy Process - VIekriterijumsko KOmpromisno Rangiranje) multi-criteria decision making (MCDM) approach assisted by computational fluid dynamics (CFD) to prioritize HTFs, particularly for CST and the results are compared to AHP-TOPSIS (Analytical Hierarchy Process - Technique for Order Preference by Similarity to Ideal Solution) for validation. While AHP is chosen to decide the criteria weights in the multi-criteria process, VIKOR is used as decision making to rank and prioritize alternatives. Water, Therminol VP-1, Solar salt, Hitec, Hitec XL, Liquid sodium, Lead-bismuth eutectic, Carbon dioxide, Air, and Helium are evaluated as the HTF inventory and a comprehensive CFD study is conducted to benchmark their thermal and thermodynamic properties in a high concentration PTSC in terms of solidification temperature, upper thermal stability, collector efficiency, pumping power consumption, receiver temperature gradient, and irreversibilities. In addition, other critical design considerations of HTFs including material cost, heat storage capability, material compatibility, operational safety aspects, operational maturity, and solar field control sophistication are taken into account in the MCDM process. Results show that the current parabolic trough CST should have priority for the HTFs of water and molten salt (Hitec) but molten metals and gaseous fluids would gain more insight in near future. This study presents an original perspective for deciding suitable HTFs in PTSC applications where thermal and thermodynamic analyses are limited.

Internet of Things: A Comprehensive Overview on Protocols, Architectures, Technologies, Simulation Tools, and Future Directions

The Internet of Things (IoT) is a global network of interconnected computing, sensing, and networking devices that can exchange data and information via various network protocols. It can connect numerous smart devices thanks to recent advances in wired, wireless, and hybrid technologies. Lightweight IoT protocols can compensate for IoT devices with restricted hardware characteristics in terms of storage, Central Processing Unit (CPU), energy, etc. Hence, it is critical to identify the optimal communication protocol for system architects. This necessitates an evaluation of next-generation networks with improved characteristics for connectivity. This paper highlights significant wireless and wired IoT technologies and their applications, offering a new categorization for conventional IoT network protocols. It provides an in-depth analysis of IoT communication protocols with detailed technical information about their stacks, limitations, and applications. The study further compares industrial IoT-compliant devices and software simulation tools. Finally, the study provides a summary of the current challenges, along with a broad overview of the future directions to tackle the challenges, in the next IoT generation. This study aims to provide a comprehensive primer on IoT concepts, protocols, and future insights that academics and professionals can use in various contexts.

Performance study of model predictive control with reference prediction for real-time hybrid simulation

The accuracy of real-time hybrid simulation (RTHS) is greatly influenced by the inevitable time delay and amplitude error due to the control plant dynamics. Several tracking controllers have been implemented to improve the overall performance, and among them, model predictive control (MPC) loses its prediction advantage due to the characteristic of real-time command calculation of RTHS. In this study, an improved tracking controller based on MPC controller combined with a polynomial-based forward reference prediction (MPC-RP) is proposed according to the principle of providing future data insight. First, the proposed controller is described, and the basic implementation procedure is presented. Then, validation tests were carried out to evaluate the tracking performance of the proposed controller based on the virtual RTHS benchmark problem. The results show that the MPC-RP controller has an effective delay compensation performance and a good amplitude error regulation capacity. It is also demonstrated that the MPC-RP controller has a great robust performance concerning control plant uncertainties, which ensures highly improved accuracy of RTHS.

Personalized antiseizure medication therapy in critically ill adult patients.

Precision medicine has the potential to have a significant impact on both drug development and patient care. It is crucial to not only provide prompt effective antiseizure treatment for critically ill patients after seizures start but also have a proactive mindset and concentrate on epileptogenesis and the underlying cause of the seizures or seizure disorders. Critical illness presents different treatment issues compared with the ambulatory population, which makes it challenging to choose the best antiseizure medications and to administer them at the right time and at the right dose. Since there is a paucity of information available on antiseizure medication dosing in critically ill patients, therapeutic drug monitoring is a useful tool for defining each patient's personal therapeutic range and assisting clinicians in decision-making. Use of pharmacogenomic information relating to pharmacokinetics, hepatic metabolism, and seizure etiology may improve safety and efficacy by individualizing therapy. Studies evaluating the clinical implementation of pharmacogenomic information at the point-of-care and identification of biomarkers are also needed. These studies may make it possible to avoid adverse drug reactions, maximize drug efficacy, reduce drug-drug interactions, and optimize medications for each individual patient. This review will discuss the available literature and provide future insights on precision medicine use with antiseizure therapy in critically ill adult patients.

High‐Entropy Nanomaterials for Advanced Electrocatalysis

High‐entropy alloys refer to near‐equimolar alloys of five or more elements and are receiving attention due to their unique physical and chemical properties. In electrocatalysis, they serve as active sites in multiple elements, favoring the optimized adsorption/desorption property toward the target reaction. High‐entropy nanomaterials (HENMs) are attractive candidates as electrocatalysts by taking advantage of a high surface‐to‐volume ratio and tailored composition. This review begins with the concept of high‐entropy materials and various strategies for designing electrocatalysts. Then, the recent advances in HENMs as electrocatalysts for various applications (water‐splitting reaction, carbon dioxide reduction reaction, alcohol oxidation reaction, etc.) are introduced with their catalytic performances. Finally, based on the current status of HENMs for electrocatalysis, the challenging aspects and the future insight of HENMs for advanced electrocatalysis are discussed and proposed.

Implementasi Pendidikan Karakter pada Siswa SMP

It is claimed that degradation moral happens to our young generation lately. Their behavior does not reflect the good conduct of our nation. This study is done to describe the characteristics of an ideal visioner leader and to describe the process of character education in school. Using qualitative etnografy approach, the writer explored various references to draw the conclusion. The ideal visioner leader is: a) having future insight, b) willing to take action to reach the goal, c) able to influence other people, d) able to formulate vision, e) able to realize vision inti action, f) commit to spiritual values, g) develop the relationship, h) innovative. The process of character education is integrated in all the scholl subjects and in other school activities.