Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of plasmatic extracellular vesicles by size

Extracellular vesicles (EVs) play a key role in many physiological and pathological processes [1]. EVs are a heterogeneous group of membrane-confined particles including endosome-derived exosomes and plasma membrane-originated microvesicles. The expanding field of extracellular vesicle research needs reproducible and accurate methods to characterize EVs [2]. EV profiling can be challenging due to the small size and heterogeneity. This protocol aims to provide a method to isolate EVs and facilitate high-precision particle quantitation by Nanoparticle Tracking Analysis (NTA)[3, 4]. NTA is commonly used to determine EV concentration and diameter [5, 6]. The protocol here described refers to the isolation of EVs from blood-plasma samples by using ultracentrifugation and then quantification and sizing of EVs with NTA by NanoSight NS300 system (Malvern Panalytical Ltd., Malvern, UK) provided with a syringe pump module enabling analysis in constant flow for improved sample statistics.
Speed reduction: a strategy for sustainable ship operations

ABSTRACT The selection of steaming speed is one of the main strategic decisions for ship operators under highly uncertain conditions. Speed reductions are of great benefit to the economy and environment in shipping operations. Since the inappropriate choice of steaming speed levels brought about a substantial financial and environmental impact on organisations, it is crucial to make precise decisions in the implementation of different levels of steaming speed. However, given its significance, the right pace of steaming for ship tankers benefiting the economy and the environment is still under investigation. Therefore, this study is undertaken to determine the most suitable steaming speed for chemical tankers under unpredictable operating conditions. To address this issue, an evaluation model based on the Analytic Hierarchy Process (AHP) and the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) is developed. The result indicates that extra slow steaming is the most acceptable steaming speed employing an integrated approach. This study envisages that the steaming speed of a ship can be considered as one of the strategies for a shipping company to reap financial and environmental benefits.
A Multifunctional Dual‐Salt Localized High‐Concentration Electrolyte for Fast Dynamic High‐Voltage Lithium Battery in Wide Temperature Range

In this work, a multifunctional 2m dual‐salt sulfolane (TMS)/ethyl acetate (EA)‐based localized high‐concentration electrolyte (LHCE) with 10 wt% fluorocarbonate (FEC) is reported. Its incorporation into a Li||Ni0.5Co0. 2Mn0.3O2 battery enables it to maintain nearly 89% capacity retention after 200 cycles with 1 C (200 mA g−1) charge/discharge current density charged to 4.6 V at 25 °C, showing good high‐voltage cyclic stability. A superior 10 C high‐rate performance with 65% (≈130 mAh g−1) specific capacity is also achieved. Furthermore, it still remains a liquid and exhibits good ionic conductivity even at −80 °C, and enables Li||Ni0.5Co0. 2Mn0.3O2 batteries to deliver more than 50% of their room‐temperature capacity at −40 °C and remains stable for over 200 cycles under the same condition as before, realizing outstanding low‐temperature fast‐charging/discharging performance. It also demonstrates compatibility with both lithium metal and graphite anode. All in all, this work provides a new idea for the design of a fast‐dynamic, high‐voltage, and low‐temperature lithium battery electrolyte. The findings of this work indicate that LHCEs made directly from the optimal high‐concentration electrolyte are not the most suitable approach, combining the diluent with an additive is necessary and effective.
Antibacterial activity with zeolitic nano-particles activated by Microwave plasma

Human wellbeing is jeopardized by microbial pollution. Antimicrobial compounds produced from a number of nanoparticles (NPs) were shown to have strong antimicrobial efficacy in studies. There are possible effects of nanostructured metal oxides on microbial contamination reduction are well established. This research aimed to look at the antimicrobial properties of zeolite (nanoparticles in zeolite) against E. coli (negative bacteria) and Staphylococcus aureus (positive bacteria). Real or synthetic crystalline Aluminum silicates with ion-exchanging properties are known as zeolites. The current search focuses on zeolites' uses in biomedical applications, Normal zeolites have been used in a variety of applications. Normal zeolites have been used in the pharmaceutical industry and medicine for many years. Since several biomedical processes are linked to ion exchange, adsorption, and catalysis, natural zeolites are poised to make major advances in these fields in the near future. Natural silicate compounds, such as zeolite, have been found to have a wide range of biological activities and have been used to treat diarrhea and as a vaccine is adjuvant. The search includes the usage of microwave plasma in enhancing the result of (NPS) solution of zeolite in three concentrations. The result of the Atomic Force Microscope (AFM) shows that the diameters of the particles become smaller with solution exposed to plasma and with increasing the time expose and the energy gap decrease over time exposing so the diameter of the inhibitions zone increase with increasing the time exposing to plasma.
The Description of Family Quality of Life in Parents with Empty-Nest Syndrome

The goal of this study is to obtain the description of family quality of life in parents with empty-nest syndrome. Empty-nest syndrome is a common phenomenon which occurs when child is grown up and decides to be live separately with the parent. The phenomenon takes place when child is entering the early adulthood phase and faced with various experiences which commonly occurs as an adult. Generally, an adult has the opportunity to get higher education in college, or to focus on their jobs and career, or to choose marriage with their romantic partner. When these things happen, parents who get used on raising and nurturing their child for years have the possibility on being ‘empty’ after child’s departure. This existing phenomenon calls to be studied to see the family quality of life with a couple of parents who experiences the empty-nest syndrome as the analysis unit. This study was studied using a phenomenological qualitative approach to explore the subjective understanding of parents in dealing with this phenomenon. Participants in this study were three pairs of parents who are in the middle adult development phase and live separately from their children because the children are married/working/studying. The interview process lasted for one month (November - December 2020). Data were obtained through interviews as a form of screening for signs of empty-nest syndrome experienced by subjects, then continued with interviews related to dimensions of family quality of life. The results showed that the subject's empty-nest syndrome affects the dimensions of the quality of family life, especially emotional well-being, which is marked by the subject's feelings of sadness 1-3 months after the child's departure. Other dimensions such as family interaction, parenting, and physical/material well-being also change in each subject.
Passivation Strategies through Surface Reconstruction toward Highly Efficient and Stable Perovskite Solar Cells on n-i-p Architecture

Perovskite solar cells have achieved remarkable enhancement in their performance in recent years. However, to get an entrance to the photovoltaic market, great effort is still necessary to further improve their efficiency as well as their long-term stability under various conditions. Among various types of approaches (including compositional engineering, dopant engineering, self-assembled monolayers (SAMs), et al.), interfacial engineering through passivation treatment has been considered as one of the most effective strategies to reduce the non-radiative recombination within the PSCs. Thus, this short review summaries recent efforts on chemical interfacial passivation strategies from a different perspective owing to their common phenomena of reconstructing the perovskite surface via the formation of three-dimensional perovskite, low-dimensional perovskite and synergistic effect provided by a mixed-salt passivation system, respectively.
An accident prediction architecture based on spatio‐clock stochastic and hybrid model for autonomous driving safety

Collaborative and autonomous driving vehicles combine hardware and software complex processes, also are heavily dependent on and influenced by the world of physical and cyber interactions. They have enabled many new features and advanced functionalities, such as stochastic and hybrid natures, mobile spatial topologies, and time‐critical dependability. However, the existing modeling and verification techniques have not established faith in proving correctness and safety. Spatial and time collision avoidance remains crucial obstacles on the path to becoming ubiquitous and dependable. In order to ensure safety, we first design an accident prediction architecture in system design‐time and run‐time stages. We apply it on collaborative and autonomous overtaking systems involving spatial‐ and time‐critical accident predictions. Then, we develop a novel and dedicated spatio‐clock stochastic specification language (SCSSL) to describe safety invariants and guards in domain‐specific autonomous driving systems. Next, we create the spatio‐clock stochastic and hybrid automata models based on SCSSL in order to model inherently stochastic and hybrid behaviors. To illustrate the effectiveness of spatio‐clock consistency stochastic specification and verification, we adopt statistical model checking natively to provide reliable predictions for the incoming collision instants and positions. Finally, we present an illustrative overtaking case study to verify spatio‐clock stochastic and hybrid related properties and ensure correct modeling, and demonstrate the significance of our proposed approach.
Recorded Business Meetings and AI Algorithmic Tools: Negotiating Privacy Concerns, Psychological Safety, and Control

Artificial intelligence (AI) algorithmic tools that analyze and evaluate recorded meeting data may provide many new opportunities for employees, teams, and organizations. Yet, these new and emerging AI tools raise a variety of issues related to privacy, psychological safety, and control. Based on in-depth interviews with 50 American, Chinese, and German employees, this research identified five key tensions related to algorithmic analysis of recorded meetings: employee control of data versus management control of data, privacy versus transparency, reduced psychological safety versus enhanced psychological safety, learning versus evaluation, and trust in AI versus trust in people. More broadly, these tensions reflect two dimensions to inform organizational policymaking and guidelines: safety versus risk and employee control versus management control. Based on a quadrant configuration of these dimensions, we propose the following approaches to managing algorithmic applications to recording meeting data: the surveillance, benevolent control, meritocratic, and social contract approaches. We suggest the social contract approach facilitates the most robust dialog about the application of algorithmic tools to recorded meeting data, potentially leading to higher employee control and sense of safety.
Interrelations between mental health, generic and thyroid-related quality of life in patients with Hashimoto’s thyroiditis receiving levothyroxine replacement

The assessment of health-related quality of life (QoL) in chronic conditions is considered as relevant, especially in patients with hypothyroidism where a high comorbidity with depressive and anxiety issues is reported. The present cross-sectional pilot study aims at: i) examining the correlation of thyroid-specific and generic measures of QoL in patients with Hashimoto’s Thyroiditis (HT); ii) investigating the associations of generic and thyroid-specific measures of QoL with depression and anxiety in patients with HT; iii) comparing generic and thyroid-specific measures of QoL in patients with HT versus controls. Twenty-one patients with serologically and/or ultrasonographically verified HT and sixteen controls with non-toxic goiter or post-surgical hypothyroidism were recruited for this study. Generic and disease-specific QoL were assessed by Health Survey Short Form-36 (SF-36) and Thyroid Patient Reported Outcome (ThyPRO) questionnaires, respectively, whereas depression and anxiety were measured through Beck Depression Inventory-second edition (BDI-II) and Hamilton Anxiety Rating Scale (HAM-A) questionnaires, respectively. Findings showed that ThyPRO and SF-36 scores were associated with each other only regarding the mental health domain, and that such QoL measures were consistently associated with depression levels but not with anxiety. Besides, no statistically significant difference was found between patients with HT and controls with regard to generic and thyroid-specific QoL. The present study suggests that generic and disease-specific measures of QoL can sufficiently assess the mental functioning domain and capture depressive symptoms, but only thyroid-specific measures (such as ThyPRO) can provide an accurate examination of physical aspects of QoL and the overall disease impact in patients’ lives. Besides, some methodological limitations should be taken into account in both using generic and disease-specific instruments with regard to their tendency to underestimate possible anxiety problems.
High-Dimensional Mahalanobis Distances of Complex Random Vectors

In this paper, we investigate the asymptotic distributions of two types of Mahalanobis distance (MD): leave-one-out MD and classical MD with both Gaussian- and non-Gaussian-distributed complex random vectors, when the sample size n and the dimension of variables p increase under a fixed ratio c=p/n→∞. We investigate the distributional properties of complex MD when the random samples are independent, but not necessarily identically distributed. Some results regarding the F-matrix F=S2−1S1—the product of a sample covariance matrix S1 (from the independent variable array (be(Zi)1×n) with the inverse of another covariance matrix S2 (from the independent variable array (Zj≠i)p×n)—are used to develop the asymptotic distributions of MDs. We generalize the F-matrix results so that the independence between the two components S1 and S2 of the F-matrix is not required.
Virtual Structure Formation Flight Control Based on Nonlinear MPC

A formation flight controller for unmanned aerial vehicles (UAV) capable of obstacle avoidance is designed in the framework of nonlinear model predictive control (MPC). The controller considers both input and state constraints. The formation flight controller is designed in a distributed way; each aircraft holds one. The formation architecture is based on the virtual structure approach. The objective function for each UAV is based on the tracking error and the relative distance to obstacles and other vehicles of the formation. The costs related to obstacle and inter-vehicle collision avoidance are added as penalties. Inter-vehicle collision avoidance is ensured using a priority strategy. The optimization problem is solved using sequential quadratic programming (SQP), which has better convergence. A simulation in a 3-D environment provided the results needed to evaluate the performance of the algorithm.
Contact and Non-contact Heart Beat Rate Measurement Techniques: Challenges and Issues

The heart is the most important organ in the human body as it circulates the blood throughout the body through blood vessels. In the human circulatory system, the heart beats according to the body’s physical needs. Therefore, the physical condition of a person can be determined by observing the heartbeat rate (HBR). There are plenty of methods that can be used to measure the HBR. Among the methods, photoplethysmography (PPG), electrocardiogram (ECG) and the oscillometric method are the standard methods utilised in medical institutes for continuous measurement of the HBR of a patient. Out of these three methods, PPG is the only method which has evolved to a non-contact imaging-based method from the conventional contact sensory based method. The incentive for developing the non-contact-based imaging PPG method in measuring the HBR provides the advantage of excluding the direct contact of sensors on specific body parts. This brings huge improvements to remote monitoring of healthcare especially for the purpose of social distancing. Moreover, the rapid progression of technology (particularly the interactive electronic gadgets advancement) also motivates researchers and engineers to create a mobile application using the PPG imaging method, which is feasible in measuring the HBR. Hence, this study seeks to review and present the fundamental concept, the present research and the evolution of the aforementioned methods in measuring the HBR.
Projection of Air Pollution in Northern China in the Two RCPs Scenarios

Air pollution in North China (NC) is an important issue affecting the economy and health. In this study, we used a regional climate model, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) to project air pollution in NC and investigate the variations of air pollutions response to future climate changes, which probably has an implication to strategy and control policy for air quality in NC. A comprehensive model evaluation was conducted to verify the simulated aerosol optical depth (AOD) based on MODIS and MISR datasets, and the model also showed reasonable results in aerosol concentrations. Future changes of air pollution in the middle of the 21st century (2031–2050) were projected in the two Representative Concentration Pathways (RCP4.5 and RCP8.5) and compared with the situation in the historical period (1986–2005). In the two RCPs, the simulated averaged PM2.5 concentration was projected with the highest values of 50–250 μg·m−3 over the Bohai Rim Economic Circle (BREC) in winter. The maximum AOD is in the Beijing–Tianjin–Hebei (BTH) region in summer, with an average value of 0.68. In winter, in the RCP4.5 scenario, PM2.5 concentration and AOD obviously declined in BTH and Shandong province. However, in the RCP8.5 scenario, PM2.5 concentration and AOD increased. Results indicated that air pollution would be reduced in winter if society developed in the low emission pathway. Precipitation was projected to increase both in the two RCPs scenarios in spring, summer, and winter, but it was projected to decrease in autumn. The planetary boundary layer height decreased in the two RCPs scenarios in the central region of NC in the summer and winter. The results indicated that changes of meteorological conditions have great impact on air pollution in future scenarios.
A Survey on the Recent Advances of Deep Community Detection

In the first days of social networking, the typical view of a community was a set of user profiles of the same interests and likes, and this community kept enlarging by searching, proposing, and adding new members with the same characteristics that were likely to interfere with the existing members. Today, things have changed dramatically. Social networking platforms are not restricted to forming similar user profiles: The vast amounts of data produced every day have given opportunities to predict and suggest relationships, behaviors, and everyday activities like shopping, food, traveling destinations, etc. Every day, vast data amounts are generated by the famous social networks such as Facebook, Twitter, Instagram, and so on. For example, Facebook alone generates 4 petabytes of data per day. The analysis of such data is of high importance to many aspects like recommendation systems, businesses, health organizations, etc. The community detection problem received considerable attention a long time ago. Communities are represented as clusters of an entire network. Most of the community detection techniques are based on graph structures. In this paper, we present the recent advances of deep learning techniques for community detection. We describe the most recent strategies presented in this field, and we provide some general discussion and some future trends.
The Analysis of Packaging Design Product Organic Food Eco Spirit Center

With high competition in the food and beverage industries, entrepreneurs give efforts to improve the quality of their packaging to satisfy and build good relationships with consumers through packaging design (packaging). A product must be different from the competitors, such as is through packaging design. The Eco Spirit Center organic food business has a weakness. It does not have a good packaging design. This research examined the packaging design process for the Eco Spirit Center. This research was qualitative research. The object of research was packaging design, conducted in Ciawi, West Java in July - December 2020. This research used design methodology. The data collection methods used were literature study and interviews. Packaging designs made for food; Sorghum Brownies (Brownies Sorgum), Layers of Pumpkin(Lapis Waluh), and Perfect Cassava(Singkong Mempur), for drinks were; Seruni (lemon lime/Sereh Jeruk Nipis) and Jagoramon (red ginger, lemon palm sugar/Jahe Merah Gula Aren Lemon). The packaging design had the theme of natural harmony (ecology) by processing illustrations, colors, typography, and media. Through good packaging design, it is expected that it can make each packaging easier and attract consumers.
The Impact of Gray-Listing on Capital Flows: An Analysis Using Machine Learning

The Financial Action Task Force’s gray list publicly identiﬁes countries with strategic deﬁciencies in their AML/CFT regimes (i.e., in their policies to prevent money laundering and the ﬁnancing of terrorism). How much gray-listing aﬀects a country’s capital ﬂows is of interest to policy makers, investors, and the Fund. This paper estimates the magnitude of the eﬀect using an inferential machine learning technique. It ﬁnds that gray-listing results in a large and statistically signiﬁcant reduction in capital inﬂows.
EFL TEACHER CANDIDATES’ ENGAGEMENT IN MOBILE-ASSISTED FLIPPED CLASSROOM

Many studies have explored the benefits of flipped classrooms in language learning, but a further investigation on the link between mobile-assisted flipped classrooms and EFL teacher candidates’ engagement in learning in an Indonesian context is needed. This research aimed at elaborating on how the implementation of mobile-assisted flipped classroom engaged EFL teacher candidates. With this goal in mind, we employed a case study design aiming at giving a holistic description of the case. It included multiple sources of data from online archives, observations, questionnaires, and Focus Group Discussion (FGD). We investigated the roles of the teacher and the students in the implementation of a mobile-assisted flipped classroom. The data from online archives, observations, questionnaires, and FGD show that a flipped course leads to EFL engagement. The discussion reveals how EFL teacher candidates experience different levels of emotional, behavioral, cognitive, social, and reflective engagements in various modes of learning and interactions. The study elaborates on the positive impact of mobile-assisted flipped language learning on engaging teacher candidates. This study also offers some implications and recommendations for teaching practitioners and future research.