Miracle-dz/UniFAR-FTUs huggingface dataset:
Primary Research on Assessment of Sustainable Development

The essential aspects that should be considered in assessing the progress towards sustainable development are defined as development and sustainability. Eight classes of possible assessment result are inferred. The coordinate system of sustainable development assessment, composed of sustainability indicator as X axis and development indicator as Y axis, is proposed. The defects of matrix framework of sustainable development indicators are shown, and a new kind of framework called pyramid framework is proposed in order to overcome those defects. Several indexes are analyzed and compared, then the human development index (HDI) is chosen to reflect the development aspect, and the ecological remainder, which is the difference between ecological space and ecological footprint, is chosen to reflect the sustainability aspect.
Dispersed reference interferometry for on-machine metrology

The reliance of emerging engineering and scientific applications on nanometre scale surfaces has led to the requirement for embedded metrology instrumentation for on-machine measurement in precision and ultra-precision manufacturing processes. In-situ measurement provides reduction in waste, cost and production cycle time of manufactured components however the presence of environmental noise and difficulties of integration make embedded metrology challenging. In this thesis a review of on-machine methods of optical metrology is provided and commercially available instruments are summarised. The requirement for highly miniaturised methods of distance and surface topography measurement for operation within volume limited manufacturing environments is presented and the necessity for smaller, faster probes with increased range, resolution and robustness outlined. The potential for dispersed reference interferometry (DRI) to exceed the capability of existing single-point remote fibre probing instruments is then introduced. DRI as a technique for single-point distance and surface topography measurement is first evaluated in a bulk optics configuration using a short coherence light source and chromatic dispersion within the reference arm. The resulting spectral interferograms have symmetry positions which are directly related to absolute surface position to yield measurement with a 279 nm axial resolution over a 285 μm axial range. Improvement of this resolution results from introduction of template matching, a signal processing technique which correlates a measured interferogram with a set of pre-calculated template interferograms resulting in a relative method of measurement with an axial resolution of 0.6 nm across the 285 μm axial range. Combination of this high resolution, relative measurement method with low resolution but absolute position data is then explored to improve the robustness of DRI to discontinuous and structured surfaces. Determination of high resolution wraparound order using low resolution absolute data is demonstrated over a 30 μm range, with extension to the full range of DRI expected as future improvements increase the measurement rate. Next a DRI topology is introduced which makes use of miniature common-path probes linked by fibre to a remote interrogation interferometer allowing reduction in size of the on-machine metrology apparatus. Modifications to the DRI are described to enable this common-path remote fibre probing, along with changes to the light source, spectrometer and dispersive element which allow extension of the range of DRI to 800 μm while maintaining nanometre axial resolution. Finally, a further work section offers insights into methods to improve miniaturisation of DRI probes as well as providing discussion of methods of hardware and signal processing optimisation to augment the instrument measurement rate.
The Synthesis Methodology and Characterization of Nanogold-Coated Fe3O4 Magnetic Nanoparticles

Core-shell nanostructures are widely used in many fields, including medicine and the related areas. An example of such structures are nanogold-shelled Fe3O4 magnetic nanoparticles. Systems consisting of a magnetic core and a shell made from nanogold show unique optical and magnetic properties. Thus, it is essential to develop the methodology of their preparation. Here, we report the synthesis methodology of Fe3O4@Au developed so as to limit their agglomeration and increase their stability. For this purpose, the impact of the reaction environment was verified. The properties of the particles were characterized via UV-Vis spectrophotometry, dynamic light scattering (DLS), X-ray diffraction (XRD), and Scanning Electron Microscopy-Energy Dispersive X-ray analysis (SEM-EDS technique). Moreover, biological investigations, including determining the cytotoxicity of the particles towards murine fibroblasts and the pro-inflammatory activity were also performed. It was demonstrated that the application of an oil and water reaction environment leads to the preparation of the particles with lower polydispersity, whose agglomerates’ disintegration is 24 times faster than the disintegration of nanoparticle agglomerates formed as a result of the reaction performed in a water environment. Importantly, developed Fe3O4@Au nanoparticles showed no pro-inflammatory activity regardless of their concentration and the reaction environment applied during their synthesis and the viability of cell lines incubated for 24 h with the particle suspensions was at least 92.88%. Thus, the developed synthesis methodology of the particles as well as performed investigations confirmed a great application potential of developed materials for biomedical purposes.
Syntax Acquisition in Healthy Adults and Post-Stroke Individuals: The Intriguing Role of Grammatical Preference, Statistical Learning, and Education

Previous work has provided contrasting evidence on syntax acquisition. Syntax-internal factors, i.e., instinctive knowledge of the universals of grammar (UG) for finite-state grammar (FSG) and phrase-structure grammar (PSG) but also syntax-external factors such as language competence, working memory (WM) and demographic factors may affect syntax acquisition. This study employed an artificial grammar paradigm to identify which factors predicted syntax acquisition. Thirty-seven healthy individuals and forty-nine left-hemispheric stroke patients (fourteen with aphasia) read syllable sequences adhering to or violating FSG and PSG. They performed preference classifications followed by grammatical classifications (after training). Results showed the best classification accuracy for sequences adhering to UG, with performance predicted by syntactic competence and spatial WM. Classification of ungrammatical sequences improved after training and was predicted by verbal WM. Although accuracy on FSG was better than on PSG, generalization was fully possible only for PSG. Education was the best predictor of syntax acquisition, while aphasia and lesion volume were not predictors. This study shows a clear preference for UG, which is influenced by spatial and linguistic knowledge, but not by the presence of aphasia. Verbal WM supported the identification of rule violations. Moreover, the acquisition of FSG and PSG was related to partially different mechanisms, but both depended on education.
Intercomparing atmospheric reanalysis products for hydrodynamic and wave modeling of extreme events during the open-water Arctic season

ABSTRACT The significant increase in the Arctic open-water extent along with the earlier sea-ice summer melt and later autumn freeze-up seasons observed in the last decades allow the formation of less fetch-limited waves and the further propagation of storm surges to new ice-free shores. Coupled hydrodynamic and wave models can be used to simulate these complex atmospheric–ocean interactions that often result in coastal flood hazards and extreme waves. However, the reliability of such simulations is intrinsically dependent on the quality of their main inputs, including wind and mean sea-level pressure products, which are usually extracted from reanalysis. This study evaluates the storm surge and significant wave height hindcasts from the coupled ADCIRC+SWAN numerical model forced by seven different reanalysis products during contrasting major storms. Model results show that the highest spatial resolution product CFSv2 led to the overall most accurate model simulations, performing particularly well at locations exposed to extreme surge and waves. Average root mean square error increases of up to 100 percent for storm surge and 157.55 percent for significant wave height were observed when using products other than CFSv2, thus highlighting the importance of selecting the proper wind and pressure reanalysis to be implemented as forcing in the hydrodynamic and wave numerical model.
An Enterprise Architecture-centred Approach towards Eco-Industrial Networking: A Case Study

: Circular Economy is one of the main avenues to tackle the ever-increasing effects of what is becoming the most urgent challenge of our times: climate change. Previous work has advocated a multidisciplinary approach towards the optimal enactment of Circular Economy through Eco-Industrial Networking, due to its many-faceted and complex aspects. This paper aims to further the research in the area by examining the practical application of the concepts proposed within a case study and drawing conclusions on applicability, potential pitfalls and improvements, while at the same time advocating a more Enterprise Architecture (EA)-centric stance due to its all-encompassing and integrating nature. Thus, a brief explanation of the theoretical background is followed by the description of the scenario and the proposed EA-focused concepts’ application in practice, including challenges and benefits of the chosen approach. Finally, a reflection is performed and conclusions are drawn together with suggestions for future applications and development of the method.
Knowledge management: an analysis of knowledge integrator effectiveness in managing organizational knowledge

This research study was a quantitative correlational study. An Internet-delivered knowledge management (KM) survey was sent to 4,027 participants. The sample was taken from business newsgroups and discussion groups. The response rate for completed surveys was 473 (11.7%). The main question addressed by this study was whether organizations are making the best use of their e-mail enablers for KM. This study was divided into three research questions to find an answer to this question. The three questions dealt with the degree to which organizations have implemented e-mail enablers, the degree to which the participants have used the e-mail enablers, and can the participants do more to capture knowledge with no additional cost to the organization. The study did find most (386 or 99%) organizations do not have a complete e-mail enabler KM solution. In fact, only 4 (1%) participants reported a complete solution while 58 (14.9%) reported a solution that is 50% to 85.7% complete. The study found e-mail KM enablers are effective in improving KM. Correlation of several KM variables was completed to see if the e-mail KM enablers were effective in improving KM capabilities. All of the correlations were significant and suggest e-mail KM enablers improve the ability for capturing knowledge. The study found 45.6% of the participants capture more knowledge than previous studies. There were 142 (30%) participants who reported transferring 71% or more of their daily use of organizational knowledge through their e-mail system. There were 74 (15.6%) participants who reported they transfer 61% to 70% of their daily use of organizational knowledge through their e-mail system. Almost all of the participants 469 (99.2%) transfer more than 10% of the knowledge they work with everyday through their e-mail system. Another result of this study was finding the amount of time to perform specific KM tasks using e-mail although this was not the primary focus. The time saved could be translated to dollar amounts by applying the cost per minute to the totals. The cost could then be used to predict an ROI for potential new KM implementations. Potential ROI is calculated in this study.
Laboratory Studies on the Rheotaxis of Fish under Different Attraction Flow Conditions

The damming of the river changes the structure of the original river ecosystem, and although fish passage plays an important role in maintaining the connectivity of the river ecosystem, the fish have difficulty finding the fish passage entrance during the upstream process. This paper studied the rheotaxis of fish under three different water flow conditions experimentally through recirculating water tanks. To better understand the response of Crucian carp (Carassius auratus) to water flow stimulation, the representative swimming trajectory, sensing success rate, attraction success rate, reaction time, and attraction time of the fish were analyzed by using a video monitoring system. The experimental results showed that fish responded differently to single-peak and lateral bimodal outflow conditions: (1) the single-peak outflow condition had a much better attraction effect than the lateral bimodal outflow condition, both in terms of sensing success rate and attraction success rate; (2) the fish swam mainly in the middle area of the lateral bimodal outflow condition, while the fish swam more evenly in the single-peak outflow condition. Therefore, setting the attraction current at the right time and near the entrance of the fish passage may help to improve the effect of fish attraction.
A Novel Electronic Chip Detection Method Using Deep Neural Networks

Electronic chip detection is widely used in electronic industries. However, most existing detection methods cannot handle chip images with multiple classes of chips or complex backgrounds, which are common in real applications. To address these problems, a novel chip detection method that combines attentional feature fusion (AFF) and cosine nonlocal attention (CNLA), is proposed, and it consists of three parts: a feature extraction module, a region proposal module, and a detection module. The feature extraction module combines an AFF-embedded CNLA module and a pyramid feature module to extract features from chip images. The detection module enhances feature maps with a region intermediate feature map by spatial attentional block, fuses multiple feature maps with a multiscale region of the fusion block of interest, and classifies and regresses objects in images with two branches of fully connected layers. Experimental results on a medium-scale dataset comprising 367 images show that our proposed method achieved mAP0.5=0.98745 and outperformed the benchmark method.
Darkweb Cyber Threat Intelligence Mining

The important and rapidly emerging new field known as 'cyber threat intelligence' explores the paradigm that defenders of computer networks gain a better understanding of their adversaries by understanding what assets they have available for an attack. In this book, a team of experts examines a new type of cyber threat intelligence from the heart of the malicious hacking underworld - the dark web. These highly secure sites have allowed anonymous communities of malicious hackers to exchange ideas and techniques, and to buy/sell malware and exploits. Aimed at both cybersecurity practitioners and researchers, this book represents a first step toward a better understanding of malicious hacking communities on the dark web and what to do about them. The authors examine real-world darkweb data through a combination of human and automated techniques to gain insight into these communities, describing both methodology and results.
Use of Hyperoncotic Human Albumin Solution in Severe Traumatic Brain Injury Revisited—A Narrative Review and Meta-Analysis

A significant proportion of patients with a severe traumatic brain injury (TBI) have hypoalbuminemia and require fluid resuscitation. Intravenous fluids can have both favorable and unfavorable consequences because of the risk of hyperhydration and hypo- or hyperosmolar conditions, which may affect the outcome of a TBI. Fluid resuscitation with human albumin solution (HAS) corrects low serum albumin levels and aids in preserving euvolemia in non-brain-injured intensive care units and in perioperative patients. However, the use of HAS for TBI remains controversial. In patients with TBI, the infusion of hypooncotic (4%) HAS was associated with adverse outcomes. The side effects of 4% HAS and the safety and efficacy of hyperoncotic (20–25%) HAS used in the Lund concept of TBI treatment need further investigation. A nonsystematic review, including a meta-analysis of controlled clinical trials, was performed to evaluate hyperoncotic HAS in TBI treatment. For the meta-analysis, the MEDLINE and EMBASE Library databases, as well as journal contents and reference lists, were searched for pertinent articles up to March 2021. Four controlled clinical studies involving 320 patients were included. The first was a randomized trial. Among 165 patients treated with hyperoncotic HAS, according to the Lund concept, 24 (14.5%) died vs. 59 out of 155 control patients (38.1%). A Lund concept intervention using hyperoncotic HAS was associated with a significantly reduced mortality (p = 0.002). Evidence of the beneficial effects of fluid management with hyperoncotic HAS on mortality in patients with TBI is at a high risk of bias. Prospective randomized controlled trials are required, which could lead to changes in clinical practice recommendations for fluid management in patients with TBI.
Research on belt foreign body detection method based on deep learning

Recently, accelerating the improvement in the level of iron ore mining has become extremely important for the sustainable development of the steel industry. Various foreign objects such as steel bars, wood, and plastic pipes easily appear on iron ore belt conveyors, which cause damage to equipment and harm the personal safety of mining workers. Accordingly, a lightweight detection model based on you only look once (YOLO)v3 is proposed in this study. This study first uses the median filter method to preprocess the belt foreign body image to remove the influence of dust and improve the clarity of ore edges. Second, we train the YOLOv3 belt foreign matter detection algorithm based on the selected data set to detect belt foreign matter and evaluate the model based on mean average precision (mAP) and other indicators. Finally, after implementing the sparse training based on the batch normalization (BN) layers, the channel-pruning and layer-pruning strategies are implemented to simplify the YOLOv3 model, followed by parameter fine-tuning. When the accuracy of the model is not affected, our model realizes smaller calculations, faster processing, and a smaller size compared to the original YOLOv3 model. Hence, the model effectively achieves real-time recognition of foreign matter on the ore conveyor belt.
Centenarian caregivers: perception of burden, sociodemographic data and physical activity

This study aimed to understand centenarian caregivers’ perception of care burden according to sociodemographic characteristics and physical activity level. This is a descriptive study that used a mixed data (quantitative and qualitative) approach. Sixty-seven caregivers of centenarians from municipalities in Santa Catarina participated in this study. Interviews were held for application of questions about sociodemographic data, transport-related and leisure-time physical activity, caregiver burden, and suggestions for improving care. The data were collected in the centenarian’s home where the caregiver worked. Quantitative data were analyzed using descriptive and inferential statistics and qualitative data by content analysis. The results showed that 58.2% of the caregivers were overburdened. Of these, 92.3% were females, 56.4% were 60-75 years old, 48.7% had 7 to 11 years of schooling, 53.8% were married, 66.7% were children of centenarians, the caregiving duration ranged from 1 to 5 years in 35.9%, and 69.2% cared for the older adult 24 hours/day. There was a statistically significant difference (p = 0.01) between the level of leisure-time physical activity and caregiving burden, with 64.9% of insufficiently active caregivers tending to be overburdened with the care demand. The suggestions of caregivers for improving centenarian care included having help from health professionals and relatives for care, infrastructure, and financial resources. Most burdened caregivers are insufficiently active and need assistance in taking care of their own health.
Position estimation for self-sensing magnetic bearings based on the current slope due to the switching amplifier

Abstract This paper presents a technique to estimate the rotor position for self-sensing magnetic bearings, based on the current slope, which is caused by the voltage switching of the PWM amplifier. In the early days of this research field, most approaches worked on the signal injection method. The hardware was comparable to those with position sensors, but the quality of the estimated position was much less than the measured one. Modern approaches all look into the switching ripple, which as an interrogation signal has the highest frequency and amplitude. But the varying duty cycle, which is unavoidable due to the position control, leads to a considerable decrease of the achievable signal performance. The proposed approach uses the discrete coil model and exploits directly the current slope, which separates the position detection from the issue of duty cycle changes. In order to simplify the system design, the current slope is calculated from the samples of current values. Thus, for the position estimation, no additional other hardware than that for a pure current control is needed. The position control of a single-axis magnetic actuator, using the proposed technique, was successfully implemented. Parasitic effects, which influence the experimental results, are discussed in detail.
The Value of Social Capital for the Success of SPAC IPOs

This paper explores the role of social capital in contributing to the success of a new breed of organizations known as ‘blank check companies’ or special purpose acquisition companies (SPACs) that are set up solely to target and acquire listed companies as a fast-track route to gain listing status in the stock market. The paper is a case study of Pershing Square Holdings Ltd., St. Peter Port, UK (PSH), which launched SPAC IPOs (Initial Public Offerings), Pershing Square Tontine Holdings Ltd., New York, NY, USA (PSTH), which succeeded in raising the largest capital from influential investors in 2020. Social capital theory is employed to provide theoretical structure for the analysis. Using annual reports, publicly available information on the internet, as well as social media platforms related to the company and its strategy, the authors critically analyse and highlight how the Tontine’s founder and his team utilized their structural, relational, and cognitive social capital to attract investors and gained recognition as the most successful SPAC IPO in the market in 2020. The authors found the ability to structure a SPAC IPO that departs from a typical SPAC, and the choice of timing to enter the SPAC market resulted in an over subscription and higher market valuation ratings of its IPO, as well as allowed the sponsor to be selective of its investors. This is the first study to address the significance of social capital at the individual and organizational level in creating value for SPAC IPOs. Potential investors can gain understanding and insights on the mechanics of SPAC IPOs and the importance of the founder’s social capital in ensuring successful investment. Successful SPAC IPOs will create interest in the marketplace and enhance the value of investment for investors and helped private companies to get listed faster.