Miracle-dz/UniFAR-FTUs huggingface dataset:
THE BANDWIDTH OF HEB MIXERS EMPLOYING ULTRATHIN NbN FILMS ON SAPPHIRE SUBSTRATE

We report on some unusual features observed during fabrication of ultrathin NbN films with high TcThe films were used to fabricate HEB mixers, which were evaluated for IF bandwidth measurements at 140 GHz. Ultrathin films were fabricated using reactive dc magnetron sputtering with a discharge current source. Reproducible parameters of the films are assured keeping constant the difference between the discharge voltage in pure argon, and in a gas mixture, for the same current. A maximum bandwidth of 4GHz at optimal LO and dc bias was obtained for mixer chip based on NbN film 35 A thick with Tc=- -11K.
Progress in Understanding Radiofrequency Heating and Burn Injuries for Safer MR Imaging

RF electromagnetic wave exposure during MRI scans induces heat and occasionally causes burn injuries to patients. Among all the types of physical injuries that have occurred during MRI examinations, RF burn injuries are the most common ones. The number of RF burn injuries increases as the static magnetic field of MRI systems increases because higher RFs lead to higher heating. The commonly believed mechanisms of RF burn injuries are the formation of a conductive loop by the patient’s posture or cables, such as an electrocardiogram lead; however, the mechanisms of RF burn injuries that occur at the contact points, such as the bore wall and the elbow, remain unclear. A comprehensive understanding of RF heating is needed to address effective countermeasures against all RF burn injuries for safe MRI examinations. In this review, we summarize the occurrence of RF burn injury cases by categorizing RF burn injuries reported worldwide in recent decades. Safety standards and regulations governing RF heating that occurs during MRI examinations are presented, along with their theoretical and physiological backgrounds. The experimental assessment techniques for RF heating are then reviewed, and the development of numerical simulation techniques is explained. In addition, a comprehensive theoretical interpretation of RF burn injuries is presented. By including the results of recent experimental and numerical simulation studies on RF heating, this review describes the progress achieved in understanding RF heating from the standpoint of MRI burn injury prevention.
Iris Segmentation based on an Optimized U-Net

Segmenting images of the human eye is a critical step in several tasks like iris recognition, eye tracking or pupil tracking. There are a lot of well-established hand-crafted methods that have been used in commercial practice. However, with the advances in deep learning, several deep network approaches outperform the handcrafted methods. Many of the approaches adapt the U-Net architecture for the segmentation task. In this paper we propose some simple and effective new modifications of U-Net, e.g. the increase in size of convolutional kernels, which can improve the segmentation results compared to the original U-Net design. Using these modifications, we show that we can reach state-of-the-art performance using less model parameters. We describe our motivation for the changes in the architecture, inspired mostly by the hand-crafted methods and basic image processing principles and finally we show that our optimized model slightly outperforms the original U-Net and the other state-of-the-art models.
Estimating the Emotional Information in Japanese Songs Using Search Engines

Several studies have shown that music can reduce unpleasant emotions. Based on the results of this research, several systems have been proposed to suggest songs that match the emotions of the audience. As a part of the system, we aim to develop a method that can infer the emotional value of a song from its Japanese lyrics with higher accuracy, by applying the technology of inferring the emotions expressed in sentences. In addition to matching with a basic emotion dictionary, we use a Web search engine to evaluate the sentiment of words that are not included in the dictionary. As a further improvement, as a pre-processing of the input to the system, the system corrects the omissions of the following verbs or particles and inverted sentences, which are frequently used in Japanese lyrics, into normal sentences. We quantitatively evaluate the degree to which these processes improve the emotion estimation system. The results show that the preprocessing could improve the accuracy by about 4%. Japanese lyrics contain many informal sentences such as inversions. We pre-processed these sentences into formal sentences and investigated the effect of the pre-processing on the emotional inference of the lyrics. The results show that the preprocessing may improve the accuracy of emotion estimation.
CO2‐stimulation of savanna tree seedling growth depends on interactions with local drivers

Woody encroachment in southern African savanna has been partly attributed to rising atmospheric [CO2] fertilising the growth of C3 trees but less so that of competing C4 grasses. However, growth conditions (resource availability, competition, rooting space and herbivory) must be suitable for the effects of elevated CO2 (eCO2) to be realised. This research investigated the interactions between the positive effect of eCO2 on tree seedling growth and limitations imposed by drought, herbivory and competition with C4 grasses. Seedlings of the prolific encroaching C3 tree Vachellia karroo were grown at ambient (400 ppm) or eCO2 (800 ppm) in Open‐Top Chambers and exposed to a variety of stresses typical of savanna systems. Photosynthetic, growth and allocation responses to eCO2 and other treatments were determined. Unsurprisingly, we show strong growth and water‐saving responses of V. karroo seedlings to eCO2 when in the absence of competition and herbivory. However, the addition of either grass competition or simulated herbivory in the first season of growth significantly moderated this stimulation, while neither drought nor shading diminished the eCO2 effect relative to similarly treated plants grown at ambient [CO2]. Synthesis. We demonstrate that eCO2‐induced C3 stimulation in encroaching savanna species such as V. karroo will be inconsistent across time and space. This research does not detract from the suggestion that increasing atmospheric CO2 is implicated in woody encroachment, but rather that eCO2 benefits to C3 tree seedlings are only realised when growth conditions are suitable. Inconsistencies in eCO2 response will translate into spatial and temporal variation in seedling responses to eCO2 and CO2‐driven woody encroachment, explaining some of the variability observed in woody encroachment across geographical regions and resource and herbivore gradients.
Agavins Impact on Gastrointestinal Tolerability-Related Symptoms during a Five-Week Dose-Escalation Intervention in Lean and Obese Mexican Adults: Exploratory Randomized Clinical Trial

Agavins are prebiotics and functional fiber that modulated the gut microbiota and metabolic status in obese mice. Here, we designed a placebo-controlled, double-blind, exploratory study to assess fluctuations in gastrointestinal (GI) tolerability-related symptoms to increasing doses of agavins in 38 lean and obese Mexican adults for five weeks and their impact on subjective appetite, satiety, metabolic markers, and body composition. All GI symptoms showed higher scores than placebo at almost every dose for both lean and obese groups. Flatulence caused an intense discomfort in the lean-agavins group at 7 g/day, while obese-agavins reported a mild-to-moderate effect for all five symptoms: no significant differences among 7, 10, and 12 g/day for flatulence, bloating, and diarrhea. Ratings for any GI symptom differed between 10 and 12 g/day in neither group. The inter-group comparison demonstrated a steady trend in GI symptoms scores in obese participants not seen for lean volunteers that could improve their adherence to larger trials. Only body weight after 10 g/day reduced from baseline conditions in obese-agavins, with changes in triglycerides and very-low-density lipoproteins compared to placebo at 5 g/day, and in total cholesterol for 10 g/day. Altogether, these results would help design future trials to evaluate agavins impact on obese adults.
The linear Lasso: A location model approach

We use location model methodology to guide the least squares analysis in the Lasso problem of variable selection and inference. The nuisance parameter is taken to be an indicator for the selection of explanatory variables, and the interest parameter is the response variable itself. Recent theory eliminates the nuisance parameter by marginalization on the data space and then uses the resulting distribution for inference concerning the interest parameter. We develop this approach and find that primary inference is essentially one‐dimensional rather than n‐dimensional, inference focuses on the response variable itself rather than the least squares estimate (as variables are removed), computation is relatively easy, a scalar marginal model is available, and ineffective variables can be removed by distributional tilt or shift.
Detection of Biological Pathogens Using Multiple Wireless Magnetoelastic Biosensors

A number of recent, high-profile incidences of food-borne illness spreading through the food supply and the use of anthrax by terrorists after the September 11, 2001 attacks have demonstrated the need for new technologies that can rapidly detect the presence of biological pathogens. A bevy of biosensors show excellent detection sensitivity and specificity. However, false positive and false negative signals remain one of the primary reasons that many of these newly developed biosensors have not found application in the marketplace. The research described in this dissertation focuses on developing a free-standing magnetoelastic based bio-sensing system using a pulse method. This method allows fast detection, eliminates the bias magnetic field that is necessary in current methods, makes the system more simply and suitable for in-field detection. This system has two pairs of transformer coils, where a measurement sensor and a control sensor can be put in each pair of coils. The control sensor is used to compensate for environmental variables. The effect of pulse power on the performance of the magnetoelastic sensors in the pulse system is studied. The system is found to have excellent stability, good detection repeatability when used with multiple sensors. This research has investigated and demonstrated a multiple sensors approach. Because it will involve the simultaneous measurement of many sensors, it will significantly reduce problems encountered with false positive indications. The positioning and interference of sensors are investigated. By adding a multi-channel structure to the pulse detection system, the effect of sensor interference is minimized. The result of the repeatability test shows that the standard deviation when measuring three 1 mm magnetoelastic sensors is around 500 Hz, which is smaller than the minimum requirement for actual spores/bacteria detection.
Chasing Theme Number Nine: Five Practical Strategies for Making Global Connections

This article explores practical avenues for making global connections within the social studies classroom. Drawing from my classroom experiences and utilizing the basic principles of global education outlined by Toni Fuss Kirkwood-Tucker (2009) as a conceptual frame, I attempt to bridge the gap between theory and practice. Such an endeavor aims to provide social studies teachers with five practical strategies for making global connections that can be readily employed in their middle and secondary social studies classrooms. These strategies discussed here include structured academic controversy, globalizing physical place, reading visual fine arts, incorporating the natural world, and sampling.
Engineered phosphorus dendrimers as powerful non-viral nanoplatforms for gene delivery: a great hope for the future of cancer therapeutics

During the past two decades, tremendous progress has been made in the dendrimer-based delivery of therapeutic molecules including, for instance, small molecules, macromolecules, and genes. This review deals with recent successes in the development of promising biocompatible phosphorus dendrimers, a specific type of dendrimer, to deliver genes to treat cancers.
Association between Noise Annoyance and Mental Health Outcomes: A Systematic Review and Meta-Analysis

To date, most studies of noise and mental health have focused on noise exposure rather than noise annoyance. The purpose of this systematic review and meta-analysis was to evaluate whether the available evidence supports an adverse association between noise annoyance and mental health problems in people. We carried out a literature search of Web of Science, PubMed, Scopus, PsycINFO, and conference proceedings published between 2000 and 2022. Thirteen papers met the inclusion criteria. We conducted meta-analyses of noise annoyance in relation to depression, anxiety, and general mental health. In the meta-analyses, we found that depression was approximately 1.23 times greater in those who were highly noise-annoyed (N = 8 studies). We found an approximately 55% higher risk of anxiety (N = 6) in highly noise-annoyed people. For general mental health (N = 5), highly annoyed participants had an almost 119% increased risk of mental health problems as assessed by Short Form (SF) or General Household Questionnaires (GHQ), but with high heterogeneity and risk of publication bias. In conclusion, findings are suggestive of a potential link between noise annoyance and poorer mental health based on a small number of studies. More evidence is needed to confirm these findings.
Impact of Two Neuronal Sigma-1 Receptor Modulators, PRE084 and DMT, on Neurogenesis and Neuroinflammation in an Aβ1–42-Injected, Wild-Type Mouse Model of AD

Alzheimer’s disease (AD) is the most common form of dementia characterized by cognitive dysfunctions. Pharmacological interventions to slow the progression of AD are intensively studied. A potential direction targets neuronal sigma-1 receptors (S1Rs). S1R ligands are recognized as promising therapeutic agents that may alleviate symptom severity of AD, possibly via preventing amyloid-β-(Aβ-) induced neurotoxicity on the endoplasmic reticulum stress-associated pathways. Furthermore, S1Rs may also modulate adult neurogenesis, and the impairment of this process is reported to be associated with AD. We aimed to investigate the effects of two S1R agonists, dimethyltryptamine (DMT) and PRE084, in an Aβ-induced in vivo mouse model characterizing neurogenic and anti-neuroinflammatory symptoms of AD, and the modulatory effects of S1R agonists were analyzed by immunohistochemical methods and western blotting. DMT, binding moderately to S1R but with high affinity to 5-HT receptors, negatively influenced neurogenesis, possibly as a result of activating both receptors differently. In contrast, the highly selective S1R agonist PRE084 stimulated hippocampal cell proliferation and differentiation. Regarding neuroinflammation, DMT and PRE084 significantly reduced Aβ1–42-induced astrogliosis, but neither had remarkable effects on microglial activation. In summary, the highly selective S1R agonist PRE084 may be a promising therapeutic agent for AD. Further studies are required to clarify the multifaceted neurogenic and anti-neuroinflammatory roles of these agonists.
Linking smallholder fish farmers to output markets: the dominance of collectors in aquaculture of Tam Giang lagoon, Central Vietnam

Market access plays an important role in increasing smallholder’s income; however, informal markets are typical in developing countries. Traders often dominate agricultural markets. In Vietnam aquaculture, collectors are important actors and act as an intermediary in linking farmers and buyers. This research aimed to explore and analysis the functions and the dominance of collectors in linking with smallholder fish farmers in Tam Giang lagoon, central Vietnam. The qualitative research is applied through 55 semi-structured interviews including smallholder fish farmers, collectors, wholesalers, retailers, officers of local government and second information from statistic data and reports. The research findings showed that linking of smallholder fish farmers to output market has dependence on collectors while all aquatic products have to pass on collectors before distributing to next buyers. Collectors always have strategies to maintain the relationship with smallholders and they always have an advantage status in aquaculture value chain. Collectors are also considered as a barrier of smallholder farmers to access potential marketing channels. Informal transaction and trust are characterized in the interaction between collectors and smallholders.
A Combined Convolutional Neural Network for Urban Land-Use Classification with GIS Data

The classification of urban land-use information has become the underlying database for a variety of applications including urban planning and administration. The lack of datasets and changeable semantics of land-use make deep learning methods suffer from low precision, which prevent improvements in the effectiveness of using AI methods for applications. In this paper, we first used GIS data to produce a well-tagged and high-resolution urban land-use image dataset. Then, we proposed a combined convolutional neural network named DUA-Net for complex and diverse urban land-use classification. The DUA-Net combined U-Net and Densely connected Atrous Spatial Pyramid Pooling (DenseASPP) to extract Remote Sensing Imagers (RSIs) features in parallel. Then, channel attention was used to efficiently fuse the multi-source semantic information from the output of the double-layer network to learn the association between different land-use types. Finally, land-use classification of high-resolution urban RSIs was achieved. Experiments were performed on the dataset of this paper, the publicly available Vaihingen dataset and Potsdam dataset with overall accuracy levels reaching 75.90%, 89.71% and 89.91%, respectively. The results indicated that the complex land-use types with heterogeneous features were more difficult to extract than the single-feature land-cover types. The proposed DUA-Net method proved suitable for high-precision urban land-use classification, which will be of great value for urban planning and national land resource surveying.
Fire Regimes and their Correlates in the Darwin Region of Northern Australia

A nine year fire history for the Darwin region was created from Landsat imagery, and examined to describe the fire regime across the region. 43% of the region burned each year, and approximately one quarter of the fires occur in the late dry season, which is lower than most other studied areas. Freehold land, which covers 35% of the greater Darwin region, has 20% long-unburnt land. In contrast, most publicly owned and Aboriginal owned land has very high fire frequency (60-70% per year), and only 5% long unburnt. It seems that much of the Freehold land is managed for fire suppression, while the common land is burnt either to protect the Freehold or by pyromaniacs. Generalized Linear Modelling among a random sample of points revealed that fire frequency is higher among large blocks of savannah vegetation, and at greater distances from mangrove vegetation and roads. This suggests that various kinds of fire break can be used to manage fire in the region. The overall fire frequency in the Darwin region is probably too high and is having a negative impact on wildlife. However, the relatively low proportion of late dry season fires means the regime is probably not as bad as in some other regions. The management of fire is ad-hoc and strongly influenced by tenure. There needs to be a clear statement of regional fire targets and a strategy to achieve these. Continuation of the fire mapping is an essential component of achieving the targets.
A Framework of Selecting Building Flooring Finishing Materials by Using Building Information Modeling (BIM)

Building materials selection is a critical process affected by many complicated factors. Due to the specific function of elements, alternatives to materials must be appropriately chosen as they differ in quality, performance, and cost. Implementing a Value Engineering (VE) process is challenging as it requires effort and several workshops. Thus, this study proposes a framework to automate the VE process of selecting building flooring material. The framework identified selected agreed criteria of flooring finishing materials measured based on agreed standard tests. The developed framework is distinguished from other current research using a combination of Analytic Hierarchy Process (AHP), Pairwise, and Function Analysis System Technique (FAST) methods to define the criteria ranking weight and include the building function. Furthermore, the framework is integrated with Building Information Modeling (BIM) that has been widely used in the Architecture, Engineering, and Construction industry (AEC). Finally, a case study of a residential house in Saudi Arabia was used to demonstrate the framework. The proposed framework was verified by using two questioners and expert consultations.
Task Partitioning and Orchestration on Heterogeneous Edge Platforms: The Case of Vision Applications

Running computer vision applications, such as 3-D simultaneous localization and mapping (SLAM), on mobile devices requires low-latency responses and a massive amount of computation. Edge computing has been introduced to move Cloud features closer to end users, providing necessary computing and network resources for end devices. The heterogeneous edge devices, with different hardware architectures (e.g., CPUs and GPUs) and runtime environments, provide diverse resources to support processing tasks from end devices, resulting in different costs and quality of services. How to partition these computing tasks and distribute them over these heterogeneous hardware nodes is still an open research question. Considering these inherently heterogeneous hardware architectures, new approaches for service orchestration and task scheduling are required to meet the service-level agreement and reduce the overall cost of the system (e.g., facility utilization cost). This article presents a system framework, EDGE VISION, for computer vision applications partitioning and orchestration on heterogeneous edge computing platforms considering both CPUs and GPUs. EDGE VISION abstracts the heterogeneous hardware resources and the task runtime environments and divides the application into separate tasks to be orchestrated and deployed into the heterogeneous edge nodes. We also propose two scheduling algorithms in our framework, minimum latency task scheduling and minimum cost task scheduling, aiming to minimize the processing latency and the overall system cost. We evaluate our framework by implementing the edge-based 3-D SLAM application in our real testbed with ten heterogeneous edge devices. Evaluations show that EdgeVision can efficiently minimize the processing latency and the system overall cost and achieve up to 30% decrease in task processing latency and 15% more cost saving compared to the State-of-the-Art baselines.