Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel power management strategy based on combination of 3D droop control and EKF in DC microgrids

Correspondence Vahid Sabzpoosh, Center of Excellence for Power System Automation and Operation, Department of Electrical Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran, Iran. Email: vahid_sabzpoosh@elec.iust. ac.ir Abstract Voltage regulation and power management are necessary to maintain balance of supply and demand in DC microgrids. In such systems, power sharing is normally done through parallel operation of distributed energy resources equipped with droop controllers. However, low power sharing accuracy and not allowing the microgrid to maximise the available power from the renewable sources are two main problems associated with conventional droop control methods. In addition, the 2D droop method is a parameter-dependent method for extracting maximum available energy from renewable sources. In this paper, a novel power management strategy based on the optimal 3D droop coefficients is developed for a DC microgrid. Optimal state estimation is attained using a combination of extended Kalman filter and adaptive recursive least square method. Reference currents of renewable energy sources (wind and solar) and battery energy storage system are estimated using the proposed prediction based model. The proposed strategy not only increases the power sharing accuracy but also remains the bus voltage around a nominal value. The performance of the proposed method is evaluated for the considered DC microgrid in two different scenarios. Results show the high effectiveness and robustness of the proposed method. It has been concluded that precise estimation of the sources reference currents and 3D droop coefficients are critical for optimal power management and bus voltage regulation in DC microgrids.
Virology Nanomedicine SERS detection of thrombin by protein recognition using functionalized gold nanoparticles

We present a method based on surface-enhanced Raman spectroscopy and exploiting a proteinprotein recognition process able to detect thrombin at subpicomolar concentrations. Gold nanoparticles (NPs) were capped with a bifunctional molecule capable of forming a covalent link with the aromatic residues of the protein moiety. The typical vibrations of the diazo bond established between the bifunctional molecule and the target protein are found to be selectively enhanced by the conjugated gold NPs, and therefore constitutes the Raman marker. After the interaction of functionalized NPs with antithrombin as a sensitive recognition element, immobilized on a capture substrate, we have detected thrombin at a concentration of about 10 -13 M.
Sodium silicate-derived aerogels: effect of processing parameters on their applications

Inorganic silica aerogels derived from sodium silicate are voluminous three-dimensional open networks with exceptional properties such as a density as low as ∼100 kg m−3, high porosity (∼99%), low thermal conductivity (∼0.01 W m−1 K−1), high specific surface area (∼1000 m2 g−1), low refractive index (∼1.05) and high optical transmittance (∼95%) depending on their preparation conditions. They are processed through the sol–gel route, which is a reliable methodology to produce high-grade porous materials. Ambient pressure drying has been developed as a low-cost route for the preparation of sodium silicate-derived aerogels, overcoming the difficulties with the use of organosilane precursors and super critical drying. Silica aerogels can be hydrophobic or hydrophilic depending on their synthetic procedure and surface silanol groups. Owing to their unusual properties, these inorganic aerogels have been applied in both commercial and high-tech engineering applications such as thermal insulation, separation, coatings, optics, nuclear particle detection, sensing, and catalysis. This review provides information on the unique features of a wide array of silica aerogels and their potential applications and recent developments in the field of science and technology.
Effects of Semiarid Wheat Agriculture Management Practices on Soil Microbial Properties: A Review

Agricultural management decisions on factors such as tillage, fertilization, and cropping system determine the fate of much of the world’s soils, and soil microbes both mediate and respond to these changes. However, relationships between management practices and soil microbial properties are poorly understood, especially in semiarid regions. To address this knowledge gap, we reviewed research papers published between 2000 and 2020 that analyzed soil microorganisms in semiarid wheat fields. We aimed to determine if and how soil microbial properties reliably respond to management, and how these properties indicate long-term changes in soil health, carbon (C) sequestration, and crop yield. We found that reducing tillage increases microbial activity as much as 50% in upper soil layers and stratifies both bacteria and fungi by depth. Higher cropping intensity (reduced fallow) increases C storage, microbial activity, and biomass, and particularly fungal biomass, which can be three times greater under continuous wheat than wheat-fallow. Chemical and organic fertilizers both increase bacterial biomass, though only organic inputs provide lasting benefits by promoting C storage and increasing fungal as well as bacterial biomass. We found microbial properties to be sensitive indicators of long-term changes in soil health and productivity, and formed recommendations on appropriate sampling, analysis, and interpretation of microbial data depending on the system studied.
Novel Shape-Stabilized Phase Change Material with Cascade Character: Synthesis, Performance and Shaping Evaluation

Thermal Energy Storage (TES) materials, such as Phase Change Materials (PCMs) are proven to enhance the energy efficiency in many fields, such as automotive and building sectors, which correspond to the most energy intensive ones. Shape-stabilized PCM and cascade PCM are procedures to overcome the most important barriers when PCMs are applied since PCMs need to be encapsulated for their technical use: the leakage of the liquid phase, corrosion, low heat transfer and narrow temperature of application. In the present study, a novel shape stabilized PCM with cascade performance (cascade shape stabilized phase change material, CSS-PCM) is synthesized via dissolution, which allows up to 60 wt. % of a paraffin-PCM in the final composition. The novel CSS-PCM is based on a biopolymer, the polycaprolactone (PCL), a low melting temperature polyester as polymeric matrix and RT27 and Micronal DS 5040 acting as PCM. To evaluate the performance of the new TES materials developed, several techniques have been used: Differential Scanning Calorimetry (DSC), and Fourier-Transformed Infrared (FT-IR) spectroscopy were used to evaluate the thermophysical properties and the chemical properties of the different formulations. The CSS-PCM show an increment of storage capacity by increasing the PCM content, and the thermal reliability was also tested: some of the CSS-PCM formulations were stable for up to 500 thermal cycles. Finally, as a potential application of the new polymeric-based PCM 3D, a printing attempt was performed in order to analyze the viability of the formulations to be used as 3D printing material as a first proof of concept.
Suppression of the superconducting proximity effect in ferromagnetic-superconducting oxide heterostructures with ion-irradiation

The effect of ion irradiation on the proximity effect in YBa2Cu3O7−δ/La0.67Sr0. 33MnO3 and YBa2Cu3O7−δ/SrTiO3/La0.67Sr0. 33MnO3 heterostructures has been investigated using spin-polarized neutron reflectivity experiments. We demonstrate that the magnetization in the ferromagnetic (La0.67Sr0.33MnO3) layer at the interface is correlated with the suppression of the superconductivity in the YBa2Cu3O7−δ layer after irradiation, while the layer structure of the heterostructures remains intact. The evolution of the magnetization of the interfacial ferromagnetic layer studied as a function of temperature for both the irradiated heterostructures shows the absence of the proximity effect observed in the un-irradiated samples. The absence of a proximity effect is attributed to the suppression of the superconductivity, as seen in macroscopic magnetization measurements of the heterostructures after ion irradiation.
Oyster Mushroom (Pleurotus ostreatus) Cultivation Using Sawdust and Different Organic Manures

Aims: The aim was to evaluate the performance of cultivating oyster mushroom (Pleurotus ostreatus) using sawdust and different organic manures. Study Design: The experimental design used was the complete randomized design (CRD) and the Data obtained was subjected to Analysis of Variance (ANOVA) followed by Turkey’s Least Significant Difference(LSD) test to compare treatment means; differences was considered significant at 95% (P≤0.05) (SPSS Version 21 software). Place and Duration of Study: National Biotechnology Development Agency, South East Center, University of Nigeria, Nsukka between September 2019 and November 2019. Methodology: Saw dust was prepared as substrate with different organic manures and coded SD, Saw dust; SDP, Sawdust+ Poultry; SDC, Saw dust + cow dung; SDD, Saw dust+ pig dung) in the ratio of 100:0 and 50:50 respectively to cultivate oyster mushroom (Pleurotus ostreatus). Subsequently, the rate of growth, time of harvest, yield and average weight were recorded and proximate composition determined using standard methods. Original Research Article Orngu et al.; AFSJ, 20(5): 67-74, 2021; Article no.AFSJ. 67355 68 Results: Oyster mushroom harvested showed Moisture content ranged (4.63-7.14%), ash content (4.84-6.77%), crude fat (0.98-3.28%), fiber (16.02-18.23%), protein (19.27-33.41%) and carbohydrate (38.18%-48.89%). Average weight yield was highest in saw dust substrate (10.2g) with total yield (980g) and least average weight (7.5g) and total yield (105g) in sawdust and poultry litters substrate. Oyster mushroom from all the substrate differed significantly (p<0.05). Conclusion: Sawdust was the most suitable substrate for oyster mushroom cultivation though sawdust and pig dung combination can be a good alternative.
Local characteristics of the standing genetic diversity of European beech with high within-region differentiation at the eastern part of the range

Developing ‘climate smart forestry’ (CSF) indicators in mountain forest regions requires collection and evaluation of local data and their attributes. Genetic resources are listed among the core indicators for ‘forest biological diversity’. This study is a report on the evaluation of the standing genetic diversity within and across 12 pure beech stands (Fagus sylvatica L.) established within the CLIMO project, using nuclear microsatellite markers. The sampling sites were set along the species’ distribution range, including the Balkan region and extending towards the Iberian Peninsula. Cores or leaves from 20-23, old, mature trees per plot were sampled for DNA analysis. Genetic diversity indices were high across the range (HE = 0.74 - 0.81) with the highest in the Bosnian Mountains. Genetic divergence increased significantly with the geographical distance (Mantel test: r=0.81. p<0.001). Most of the stands exhibited an excess of heterozygotes, with the highest value at the Hungarian site (HO/HE = 1.177), where beech persists close to the eastern xeric limit of the species’ distribution. STRUCTURE revealed within–region differentiation in the Balkan Peninsula, where Bulgarian stand was the most outstanding. The genetic parameters of each stand could be assessed as a resource for CSF indicators interpreted especially at the local level.
COVID-19 and student well-being: Catholic school staff perspectives and experiences

Background: COVID-19 has dramatically changed how school communities operate. Many schools have had to navigate enforced closures and modify their usual teaching and learning practices. Furthermore, they have had to rethink how they address student well-being issues. In Australian Catholic schools, there is little data on the concerns of Catholic school staff during enforced school closures. Aims: This article describes findings from a study of the experiences and concerns of school staff in two Catholic primary school communities to understand how staff in these settings experienced and re-imagined or reinforced student well-being practices and processes. Methods: Data were collected by means of a survey assessing staff experiences and concerns, with a particular focus on student well-being. Results: Results indicated that enforced school closures were perceived as negatively affecting student well-being programmes with staff members being particularly concerned about students who were socially, educationally, culturally and economically disadvantaged. However, negative impacts were mitigated by a school culture underpinned by a pastoral and health-promoting perspective. Strong leadership in the face of systemic lethargy prompted schools to utilise their engagement and partnership arrangements for additional support. Conclusion: During forced school closures, an inclusive school ethos, environment and culture ensured an effective response to the diverse needs of staff, students and other school community members.
AI Landing for Sheet Metal-Based Drawer Box Defect Detection Using Deep Learning (ALDB-DL)

Sheet metal-based products serve as a major portion of the furniture market and maintain higher quality standards by being competitive. During industrial processes, while converting a sheet metal to an end product, new defects are observed and thus need to be identified carefully. Recent studies have shown scratches, bumps, and pollution/dust are identified, but orange peel defects present overall a new challenge. So our model identifies scratches, bumps, and dust by using computer vision algorithms, whereas orange peel defect detection with deep learning have a better performance. The goal of this paper was to resolve artificial intelligence (AI) as an AI landing challenge faced in identifying various kinds of sheet metal-based product defects by ALDB-DL process automation. Therefore, our system model consists of multiple cameras from two different angles to capture the defects of the sheet metal-based drawer box. The aim of this paper was to solve multiple defects detection as design and implementation of Industrial process integration with AI by Automated Optical Inspection (AOI) for sheet metal-based drawer box defect detection, stated as AI Landing for sheet metal-based Drawer Box defect detection using Deep Learning (ALDB-DL). Therefore, the scope was given as achieving higher accuracy using multi-camera-based image feature extraction using computer vision and deep learning algorithm for defect classification in AOI. We used SHapley Additive exPlanations (SHAP) values for pre-processing, LeNet with a (1 × 1) convolution filter, and a Global Average Pooling (GAP) Convolutional Neural Network (CNN) algorithm to achieve the best results. It has applications for sheet metal-based product industries with improvised quality control for edge and surface detection. The results were competitive as the precision, recall, and area under the curve were 1.00, 0.99, and 0.98, respectively. Successively, the discussion section presents a detailed insight view about the industrial functioning with ALDB-DL experience sharing.
Wrench-Closure Condition of Cable-Driven Parallel Manipulators

Cable-driven parallel manipulators (CDPM) have parallel structures that consist of moving platforms connected to the fixed platform through many flexible cables. The moving platform is driven by many winches, and because of the unidirectional property of cables (cables can only pull and not push in the moving platform), some specific workspaces of CDPM are limited and often do not exist (Gouttefarde and Gosselin 2006). Therefore, determining workspaces for CDPM become an important task, in order to easily plan the trajectory or control the robot. In this paper, we are interested in a set of poses of moving platforms, in which CDPM is always able to generate wrenches that balance any given external wrench exerted on the moving platform. This set of poses is also called wrench-closure workspace (WCW). In this work, we propose a novel procedure used to determine whether a pose of moving platform belongs to WCW. The condition used to check the feasibility of a certain pose in WCW is also called wrench closure condition (WCC). The proposed WCC is able to apply to completely or redundantly restrained CDPM. By analyzing the geometric properties of CDPM and applying the method used to check the feasibility of a system of inequalities, the algorithm used to check the presence of a given pose in WCW is established. To verify the performance of the proposed WCC, the test has been done in two different CDPMs that are clearly described in the introduction section.
Verdict spotting: investigating the effects of juror bias, evidence anchors and verdict system in jurors

The Scottish verdict of not proven represents a second acquittal verdict which is not legally defined. Existing research into the influence of the not proven verdict on jury decision making is modest. The main aim of the current study was therefore to investigate the influence of verdict systems (two vs three) on juror decision making. The effect of pre-trial bias and evidence anchors on juror judgements were also examined. One-hundred and twenty-eight mock jurors listened to two homicide vignettes and were asked to rate their belief of guilt of the accused and to give a verdict in both trials. The results suggest that pre-trial bias was a significant predictor of both verdict choice and belief of guilt, whereas evidence anchors were not a significant predictor of either. Finally, both guilty and not guilty verdicts were given with increased frequency in the two-verdict system when compared to the three-verdict system.
Mitigating Burnout Through Organizational Justice: Customer Support Workers’ Experiences of Customer Injustice and Emotional Labor

Employee burnout is a critical organizational concern that can be prevalent among customer support workers whose day-to-day tasks inherently include emotional labor. This study examines emotional labor and burnout among call center workers in customer service industries, specifically focusing on the influences of injustices from customers and supervisors. The findings demonstrate that: (a) customer injustice was associated with an increase in emotional labor, which in turn exacerbated customer support workers’ disengagement and exhaustion; (b) interpersonal justice perceived in the interactions with supervisors was negatively associated with disengagement; and (c) procedural justice perceived in supervisors’ decision-making processes was also negatively associated with disengagement. The findings indicate the mitigating role of interpersonal and procedural justice in reducing burnout among customer support workers.
Exploring the effectiveness of virtual compassionate presence sessions in reducing loneliness and isolation among assisted-living older adults: a pilot study

ABSTRACT This pilot study explored the effectiveness of virtual compassionate presence (CP) sessions in reducing loneliness and isolation among assisted-living older adults. Twenty-two older adults participated in 10-week virtual CP sessions facilitated by college students. We conducted in-depth semi-structured interviews with participants post-intervention. Participants reported a decreased feeling of loneliness, improved mood, and increased feeling of self-worth. The deep connections between the student facilitators and older adults seemed to enhance the older adults’ sense of meaning in life, easing their loneliness and isolation during this pandemic. A few participants reported improved memory. The findings support the need to promote programs that provide a space for older adults to share their life stories and experiences with the younger generation. Such interaction could enhance older adults’ mood, increase their sense of generativity and meaning, and positive feelings between the two generations.
Lumbopelvic sagittal standing posture associations with anthropometry, physical activity levels and trunk muscle endurance in healthy adults

Background: Various factors, inherited and acquired, are associated with habitual spinal postures. Objective: The purpose of this study was to identify the relationships between trunk muscle endurance, anthropometry and physical activity/inactivity and the sagittal standing lumbopelvic posture in pain-free young participants. Methods: In this study, 112 healthy young adults (66 females), with median (IQR) age of 20 years (18.2–22 years), without low back pain, injury or trauma were included. Lumbar curve (LC) and sacral slope (SS) angles were measured in standing with a mobile phone application (iHandy level). Anthropometric, physical activity/inactivity levels (leisure-time sport involvement and sitting hours/day) and abdominal (plank prone bridge test) and paraspinal (Sorensen test) isometric muscle endurance measures were collected. Results: LC and SS angles correlated significantly (r=0.80, p<0.001). Statistically significant differences for both LC (p=0.023) and SS (p=0.013) angles were identified between the male and female participants. A significant negative correlation was identified between the abdominal endurance time and LC (r=−0.27, p=0.004); however, the power of this result (56%) was not sufficiently high. The correlation between abdominal endurance and SS was non-significant (r=−0.17, p=0.08). In addition, no significant associations were identified between either of the sagittal lumbopelvic angles (LC–SS) in standing and the participants’ body mass index (BMI), paraspinal endurance, leisure-time sport involvement or sitting hours/day. Conclusion: The potential role of preventive exercise in controlling lumbar lordosis via enhancement of the abdominal muscle endurance characteristics requires further confirmation. A subsequent study, performed in a larger population of more diverse occupational involvement and leisure-time physical activity levels, is proposed.
Green and Efficient Processing of Wood with Supercritical CO2: A Review

Wood processing is a crucial step of wood utilization, but the adding of environmentally hazardous feedstocks and the use of unreasonable technology allow it to harm the environment and human health. Supercritical CO2 (scCO2) is a non-toxic, odorless, and safe solvent, which is widely used in studies and industrial production, but there is no review summarizing wood processing with scCO2. The unique structure and chemical properties of wood combined with scCO2 technology produce positive results. In this paper, wood processing with scCO2 is summarized, including wood impregnation, wood drying, wood thermochemical conversion, and wood extraction. The green and efficient characteristics of wood processing with scCO2 are explained in detail for researchers, engineers, and investors to provide a clean wood processing method. Further study is needed to reduce its energy consumption and commercialize it eventually.