Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaporation Patterns of Dextran–Poly(Ethylene Glycol) Droplets with Changes in Wettability and Compatibility

The dextran–PEG system is one of the most famous systems exhibiting phase separation. Various phase behaviors, including the evaporation process of the dextran–PEG system, have been studied in order to understand the physicochemical mechanism of intracellular phase separation and the effect of condensation on the origin of life. However, there have been few studies in dilute regime. In this study, we focused on such regimes and analyzed the pattern formation by evaporation. The specificity of this regime is the slow onset of phase separation due to low initial concentration, and the separated phases can have contrasting wettability to the substrate as evaporation progresses. When the polymer concentration is rather low (<5 wt%), the dextran–PEG droplets form a phase-separated pattern, consisting of PEG at the center and dextran ring of multiple strings pulling from the ring. This pattern formation is explained from the difference in wettability and compatibility between dextran and PEG upon condensation. At the initial dilute stage, the dextran-rich phase with higher wettability accumulates at the contact line of the droplet to form a ring pattern, and then forms multiple domains due to density fluctuation. The less wettable PEG phase recedes and pulls the dextran domains, causing them to deform into strings. Further condensation leads to phase separation, and the condensed PEG with improved wettability stops receding and prevents a formed circular pattern. These findings suggest that evaporation patterns of polymer blend droplets can be manipulated through changes in wettability and compatibility between polymers due to condensation, thus providing the basis to explore origins of life that are unique to the process of condensate formation from dilute systems.
EVALUATING THE REDUCTION OF HAZARDOUS WASTE CONTACT IN TABRIZ PETROCHEMICAL COMPLEX, FOCUSING ON PERSONAL PROTECTIVE EQUIPMENT METHOD

Tabriz petrochemical complex is located in northwest of Iran and west of Tabriz oil refinery and mostly produces raw plastics. In this study the implementation of Reduction of Hazardous waste Contact in this Complex with special emphasis on Personal Protective Equipment (PPE) is discussed. Accordingly different hazards threatening personnel, indoor and outdoor environment were determined. In order to identify hazardous waste generated in different parts of the complex, national, European, environmental protection agency (EPA) and Basel convention standards were taken in to consideration. Considering general frame of risk classified pyramid containing engineering controls, administrative controls and personal protective equipment (PPE),a couple of practical recommendations has been suggested to promote the security level. Personal protective equipment, suggested in this study are all manifested according to the Iranian Petroleum Standard (IPS). Despite perfect implementation of PPE method, it is recommended that incident insurance be taken in to consideration as the last mitigation effort.
Incidence of dystocia at piglet level in cloprostenol-induced farrowings and associated risk factors

Abstract Few studies have investigated risk factors for dystocia in swine, although this birthing abnormality can compromise welfare of both sows and piglets by increasing stillbirth rate and decreasing sow productivity. This study aimed to determine risk factors associated with dystocia at piglet level in cloprostenol-induced farrowings. A dystocia event was recorded when a birth interval exceeded 45 min or when manual extraction was applied. Data were collected from 898 piglets born from 77 Landrace × Yorkshire crossbred sows, which were induced for farrowing on day 114 of gestation. Generalized linear mixed models (GLMMs) were used to evaluate the association between dystocia and parity, gestation length, litter size, relative birth order (RBO (%) = 100 ⋅ birth order/litter size), birth weight, crown rump length, body mass index, ponderal index, piglet's sex, use of oxytocin, and stillbirth. Sows nested in farrowing batches were fitted as random factors in GLMMs. Incidence of dystocia at piglet and farrowing levels was 11.0 % and 75.3 %, respectively. The final multivariate model explained 20.1 % variation of dystocia. RBO had a quadratic effect on dystocia in which incidence of dystocia decreased from RBO ≤ 40 % to RBO = 60 %–70 %, and then increased to the end of parturition. Piglets with birth weight > 1700 g and stillborn piglets had higher odds of dystocia in comparison with piglets with a birth weight of 900–1700 g (OR = 2.63; 95 % CI = 1.66–4.18) and live-born piglets (OR = 2.62; 95 % CI = 1.12–6.15), respectively. This study indicates that dystocia is very common in cloprostenol-induced farrowings and suggests that the last one-third of parturitions is the most important stage to be supervised, and selection for homogenous litters and moderate high birth weight may reduce the rate of dystocia.
To Use or Not Use Car Sharing Mobility in the Ongoing COVID-19 Pandemic? Identifying Sharing Mobility Behaviour in Times of Crisis

Car sharing services have expanded in order to meet the new necessities of mobility worldwide in an innovative way. Before the COVID-19 pandemic, car sharing was a very popular mode of transportation among young adults in big cities. However, during this ongoing pandemic and with public transportation considered a super-spreading transmitter, the usage of car sharing is unclear. Therefore, the aim of this study, which is explorative in nature, is to investigate the usage, advantages, drivers, and barriers to car sharing during this ongoing pandemic era. To this end, 66 interviews were conducted among users of car sharing during the COVID-19 pandemic. The findings provide key information for the planning of car sharing operations and public transportation in the context of avoiding COVID-19 infection and respecting the recommendations of local governments. In addition, new emerging profiles of car sharing users in the ongoing pandemic are identified. This research provides relevant insights for both business practice and policy makers.
Factors Influencing High-Rise Gated Community Collective Action Effectiveness: Conceptualization of the Social-Ecological System (SES) Framework

Managing common property in gated communities is challenging. Although numerous studies have demonstrated that there are several determinants of collective action effectiveness and performances in gated communities, empirical research drawing on a multidimensional social-ecological system (SES) framework in quantitatively exploring relationships between institutional–physical–social factors and gated community collective action remains lacking. Therefore, based on Ostrom’s social-ecological system (SES) framework, this study attempts to identify factors influencing the self-organizing system (collective action) of gated communities in China. Using stratified purposive sampling, ten gated communities with various characteristics in the Taigu district were selected, in which questionnaires were then distributed to 414 households to collect valid data within the communities. Taking the ridge regression as a more robust predictive SES model with a penalty value of k = 0.1 and regularization, R Square of 0.882, this study, among 14 factors, ultimately identified six key institutional–social–ecological factors based on the descending standardized effect size, and they are: (i) types of community; (ii) presence of leaders; (iii) exclusiveness systems of a gated community; (iv) age of gated community; (v) strict enforcement of rules; and (vi) number of households that affect residents’ collective action in terms of community security, hygiene and cleanliness, and facility quality. The research findings provide urban managers and communities novel insights to formulate strategic policies towards sustainable housing and building management.
A Practical Guide to ISO 10993-5: Cytotoxicity

The international standards compiled as ISO 10993, and the FDA blue book memorandum (#G95-1) that is based on 10993-1, address the critical issue of ensuring device biocompatibility by identifying several types of tests for use in selecting device materials. Required for all types of devices, cellular toxicity testing is covered in 10993-5: "Tests for Cytotoxicity—In Vitro Methods. " This standard presents a number of test methods designed to evaluate the acute adverse biological effects of extractables from medical device materials. In performing these tests, laboratory technicians culture mammalian cells, usually of mouse or human origin obtained from a commercial supplier, in flasks using nutrient culture media. (The Latin term in vitro refers to the culturing of cells "outside of the body," or literally "in glass.") The lab techniques involved are much like those used to grow bacteria. Cultured mammalian cells reproduce by cellular division and can be subcultured to produce multiple large flasks of cells for use in evaluating materials. This article in MD&DI's continuing series on ISO 10993 provides an overview of cytotoxicity testing and discusses the benefits of performing such procedures.
Effects of Electromagnetic Heating on Quick Freezing

Purpose: Quick freezing is widely used in commercial food storage. Well-known freezing techniques such as individual quick freezing require a low-temperature coolant and small cuts for the heat-transfer efficiency. However, the freezing method for bulk food resembles techniques used in the 1970s. In this study, electromagnetic (EM) heating was applied to improve the quick freezing of bulk food. Methods: During freezing, the surface of food can be rapidly cooled by an outside coolant, but the inner parts of the food cool slowly owing to the latent heat from the phase change. EM waves can directly heat the inner parts of food to prevent it from freezing until the outer parts finish their phase change and are cooled rapidly. The center temperature of garlic cloves was probed with optical thermo sensors while liquid nitrogen (LN) was sprayed. Results: When EM heating was applied, the center cooling time of the garlic cloves from freezing until -10°C was 48 s, which was approximately half the value of 85 s obtained without EM heating. For the white radish cubes, the center cooling time was also improved, from 288 to 132 s. The samples frozen by LN spray with EM heating had a closer hardness to the unfrozen samples than the samples frozen by LN only. Conclusions: The EM heating during quick freezing functions to maintain the hardness of fresh food by reducing the freezing time from 0 to -10°C.
A Real 3D Embodied Dataset for Robotic Active Visual Learning

Active interaction with environments is one of the striking characteristics of robotic active vision, which allows robots to move to facilitate visual tasks. Recently, several embodied AI platforms have been proposed as the synthetic environments to study robotic active vision, without needing to interact in real world. However, by using synthetic data, model trained on these platforms will suffer performance degradation when applied in reality. In this letter, a real 3D embodied dataset is proposed for robotic active visual learning. The proposed dataset consists of real point cloud data densely collected in 7 real-world indoor scenes. In our embodied dataset, researchers are able to simulate the movements and interactions of robots in indoor environments and obtain real visual data, which will not lead to performance degradation in reality. Furthermore, we proposed a 3D divergency policy that can guide robots to move and collect data to improve visual performance in novel environments. The proposed policy is designed following a simple fact: a good 3D detector should produce consistent 3D detection results for the same object from different viewpoints. Therefore, our policy encourages the robot to explore the area where the detector generates different 3D bounding boxes for the same object and helps the robot improve its visual performance in novel scenes. The real 3D embodied dataset and source codes are available at: https://github.com/pioneer-innovation/Real-3D-Embodied-Dataset
Integrating GEDI and Landsat: Spaceborne Lidar and Four Decades of Optical Imagery for the Analysis of Forest Disturbances and Biomass Changes in Italy

Forests play a prominent role in the battle against climate change, as they absorb a relevant part of human carbon emissions. However, precisely because of climate change, forest disturbances are expected to increase and alter forests’ capacity to absorb carbon. In this context, forest monitoring using all available sources of information is crucial. We combined optical (Landsat) and photonic (GEDI) data to monitor four decades (1985–2019) of disturbances in Italian forests (11 Mha). Landsat data were confirmed as a relevant source of information for forest disturbance mapping, as forest harvestings in Tuscany were predicted with omission errors estimated between 29% (in 2012) and 65% (in 2001). GEDI was assessed using Airborne Laser Scanning (ALS) data available for about 6 Mha of Italian forests. A good correlation (r2 = 0.75) between Above Ground Biomass Density GEDI estimates (AGBD) and canopy height ALS estimates was reported. GEDI data provided complementary information to Landsat. The Landsat mission is capable of mapping disturbances, but not retrieving the three-dimensional structure of forests, while our results indicate that GEDI is capable of capturing forest biomass changes due to disturbances. GEDI acquires useful information not only for biomass trend quantification in disturbance regimes but also for forest disturbance discrimination and characterization, which is crucial to further understanding the effect of climate change on forest ecosystems.
A Novel Meander Bowtie-Shaped Antenna with Multi-Resonant and Rejection Bands for Modern 5G Communications

To support various fifth generation (5G) wireless applications, a small, printed bowtie-shaped microstrip antenna with meandered arms is reported in this article. Because it spans the broad legal range, the developed antenna can serve or reject a variety of applications such as wireless fidelity (Wi-Fi), sub-6 GHz, and ultra-wideband (UWB) 5G communications due to its multiband characterization and optimized rejection bands. The antenna is built on an FR-4 substrate and powered via a 50-Ω microstrip feed line linked to the right bowtie’s side. The bowtie’s left side is coupled via a shorting pin to a partial ground at the antenna’s back side. A gradually increasing meandering microstrip line is connected to both sides of the bowtie to enhance the rejection and operating bands. The designed antenna has seven operating frequency bands of (2.43–3.03) GHz, (3.71–4.23) GHz, (4.76–5.38) GHz, (5.83–6.54) GHz, (6.85–7.44) GHz, (7.56–8.01) GHz, and (9.27–13.88) GHz. The simulated scattering parameter S11 reveals six rejection bands with percentage bandwidths of 33.87%, 15.73%, 11.71, 7.63%, 6.99%, and 12.22%, respectively. The maximum gain of the proposed antenna is 4.46 dB. The suggested antenna has been built, and the simulation and measurement results are very similar. The reported antenna is expanded to a four-element design to investigate its MIMO characteristics.
The Development, Implementation, and Feasibility of a Circadian, Light, and Sleep Skills Program for Shipboard Military Personnel (CLASS-SM)

Service members face unique barriers to sufficient and high quality sleep. In the present study, a circadian, light, and sleep skills program for shipboard military personnel (CLASS-SM) was designed to encourage and inform strategies that support optimal sleep and circadian health in the context of those barriers. Phase 1 included program development and refinement via an iterative formative evaluation, including structured interviews with service members and feedback from veterans and experts, resulting in further tailoring to the population. In Phase 2, the highly tailored program was administered to shipboard personnel (n = 55), and acceptability indicators were measured. Sleep- and circadian-related knowledge (pre- and post-program) and the perceived relevance of, and satisfaction with, program content (post-program) were assessed. Before the intervention, most individuals were unaware that 7–9 h of sleep is recommended (72%) and had little understanding of the physiological effects of light; however, knowledge scores increased significantly post-program, from 51% to 88% correct (p < 0.0001). Reception was positive, with high reported satisfaction and relevance. Most individuals reported that they learned something new (89%), planned to use one or more learned strategies (100%), and intended to share learned information with others (85%); the physiological effects of light and circadian rhythms were the content areas most frequently reported as new and useful. The results demonstrate the need for, and feasibility of, the delivery of this program in operational environments.
ReCDroid+: Automated End-to-End Crash Reproduction from Bug Reports for Android Apps

The large demand of mobile devices creates significant concerns about the quality of mobile applications (apps). Developers heavily rely on bug reports in issue tracking systems to reproduce failures (e.g., crashes). However, the process of crash reproduction is often manually done by developers, making the resolution of bugs inefficient, especially given that bug reports are often written in natural language. To improve the productivity of developers in resolving bug reports, in this paper, we introduce a novel approach, called ReCDroid+, that can automatically reproduce crashes from bug reports for Android apps. ReCDroid+ uses a combination of natural language processing (NLP), deep learning, and dynamic GUI exploration to synthesize event sequences with the goal of reproducing the reported crash. We have evaluated ReCDroid+ on 66 original bug reports from 37 Android apps. The results show that ReCDroid+ successfully reproduced 42 crashes (63.6% success rate) directly from the textual description of the manually reproduced bug reports. A user study involving 12 participants demonstrates that ReCDroid+ can improve the productivity of developers when resolving crash bug reports.
Quality Assessment of Red Wine Grapes through NIR Spectroscopy

Red wine grapes require a constant follow-up through analytical chemistry to assure the greatest wine quality. Wet chemical procedures are time-consuming and produce residues that are hard to eliminate. NIR (near infrared radiation) spectroscopy has been referred as an accurate, rapid, and cost-efficient technique to evaluate quality in many fruit species, both in field and in industry. The main objective of this study was to develop predictive models using NIR spectroscopy to quantify important quality attributes in wine grapes. Soluble solids content (SSC), titratable acidity (TA), total phenolic content, total flavonoids, total anthocyanins, and total tannins were quantified in four red wine grape varieties, ‘Aragonês’, ‘Trincadeira’, ‘Touriga Nacional’, and ‘Syrah’. Samples were collected during 2017 and 2018 along véraison. Prediction models were developed using a near-infrared portable device (Brimrose, Luminar 5030), and spectra were collected from entire grapes under near field conditions. Models were built using a partial least square regression (PLSR) algorithm and SSC, TA, total anthocyanins, and total tannins exhibited a determination coefficient of 0.89, 0.90, 0.87, and 0.88, respectively. The Residual Prediction Deviation (RPD) values of these models were higher than 2.3. The prediction models for SSC, TA, total anthocyanins, and total tannins have considerable potential to quantify these attributes in wine grapes. Total flavonoids and total phenolic content were predicted with a slightly lower capacity, with R2 = 0.72 and 0.71, respectively, and both with a RPD of 1.6, indicating a very low to borderline potential for quantitative predictions in flavonoids and phenols models.
Vehicle-Assisted UAV Delivery Scheme Considering Energy Consumption for Instant Delivery

Unmanned aerial vehicles (UAVs) are increasingly used in instant delivery scenarios. The combined delivery of vehicles and UAVs has many advantages compared to their respective separate delivery, which can greatly improve delivery efficiency. Although a few studies in the literature have explored the issue of vehicle-assisted UAV delivery, we did not find any studies on the scenario of an UAV serving several customers. This study aims to design a new vehicle-assisted UAV delivery solution that allows UAVs to serve multiple customers in a single take-off and takes energy consumption into account. A multi-UAV task allocation model and a vehicle path planning model were established to determine the task allocation of the UAVs as well as the path of UAVs and the vehicle, respectively. The model also considered the impact of changing the payload of the UAV on energy consumption, bringing the results closer to reality. Finally, a hybrid heuristic algorithm based on an improved K-means algorithm and ant colony optimization (ACO) was proposed to solve the problem, and the effectiveness of the scheme was proven by multi-scale experimental instances and comparative experiments.
Machine Learning-Driven Multiobjective Optimization: An Opportunity of Microfluidic Platforms Applied in Cancer Research

Cancer metastasis is one of the primary reasons for cancer-related fatalities. Despite the achievements of cancer research with microfluidic platforms, understanding the interplay of multiple factors when it comes to cancer cells is still a great challenge. Crosstalk and causality of different factors in pathogenesis are two important areas in need of further research. With the assistance of machine learning, microfluidic platforms can reach a higher level of detection and classification of cancer metastasis. This article reviews the development history of microfluidics used for cancer research and summarizes how the utilization of machine learning benefits cancer studies, particularly in biomarker detection, wherein causality analysis is useful. To optimize microfluidic platforms, researchers are encouraged to use causality analysis when detecting biomarkers, analyzing tumor microenvironments, choosing materials, and designing structures.
Examining Female School Leaders’ Experience with Technology in Online Learning: insights from Indonesia

This paper examines female school leaders' experience in using technology in online learning at schools in rural areas in Jambi Province, Indonesia. We used semi-structured interviews and reflective journals to investigate female school leaders’ in leading the learning process during the pandemic. There were five female school leaders from rural areas in Jambi Province, Indonesia participated in this study. While the previous studies focus on examining teachers' online learning experience, this study emphasizes more on female school administrators in rural areas adjusting to the use of technology in the teaching and learning process. This study found that most of the school leaders in rural areas are in great need of attention on facilities and professional development focusing on the use of media and technology both in teaching and managing the school during the pandemic. The current study also argues that collaboration among teachers is imperative to make sure that the teachers and administrators are equipped with the knowledge and skills of how to use technology that improves the quality of education during online learning. This article contributes to both policymakers and practitioners in understanding the use of technology and leadership in online learning in rural areas.