Miracle-dz/UniFAR-FTUs huggingface dataset:
Inkjet Printed Strain Gauges Fabricated Using AgNO3/Ethylene Glycol-Based Inks

The development of inkjet printed silver (Ag) strain gauges using particle-free inks composed of silver nitrate (AgNO3) and an ethylene glycol (EG) solvent is presented. As an alternative to thermal annealing, the fabrication process incorporates low-temperature, low-pressure Ar plasma exposure to form Ag structures from the printed ink. The effect of plasma exposure time on the gauge factor (GF) for inks composed of three forms of ethylene glycol (monoEG, diEG and triEG) that differ significantly in vapor pressure is investigated. For each solvent, the GF decreases with increasing plasma exposure time, providing a mechanism to tune the GF. With respect to solvent, the GF, surface roughness and porosity increase with decreasing solvent vapor pressure, providing a second mechanism to tune the GF. And while the highest gauge factors were observed in structures printed using inks with the lowest vapor pressure solvent (triEG), these structures lack the electrical stability required for sensing applications. However, electrically stable structures with an average gauge factor of $\sim 6$ were produced using the diEG ink.
Performance of tomato M7 mutant lines and their similarities to the parents based on SSR markers

Abstract. Arrufitasari PN, Sutjahjo SH, Wirnas D. 2022. Performance of tomato M7 mutant lines and their similarities to the parents based on SSR markers. Biodiversitas 23: 1239-1245. Tomato cultivation in the lowlands can be an alternative to increase tomato production so that high-yielding and lowland adaptive varieties are required. This study was aiming at determining the performance of M7 mutant lines and their similarities to the parents based on SSR markers. The experiments were conducted at KP Leuwikopo (250 m asl) and Plant Molecular Biology Laboratory, IPB University, Indonesia. The results showed that the G4 line had the highest productivity among the tested genotypes (36.72 ton ha-1) and significantly differed from all check varieties. The highest number of fruit per plant was 51.67 in the G7 line. On the other hand, G2, G3, G7, G8, and G10 lines had the lowest percentage weight and the number of fruits cracking and were not significantly different from the check varieties (Tora and Mawar). A total of 7 SSR primers detected 87 alleles with a range of 7-15 alleles per locus. The similarity between mutant lines and their parents ranged from 44-69%. The mutant most closely resembled the parent was the G3 line, while the most different based on molecular markers was the G9 line.
Radiation Efficiency of Surface Burning on a Foam Metal Matrix with Ceramic Coating

The modified empirical two-temperature model of surface burning on a foam metal matrix was proposed. The comparative experimental studies of radiation properties of both matrices without and with ceramic coating (alumina) were carried out. Measurement was conducted in different spectral ranges. The experimental results were compared with theoretical calculations. It was shown that the integral radiation efficiency of the matrix with ceramic coating was comparable with radiation efficiency of the matrix without any coating in the wide range of the firing rate and surpassed it on 30% - 40% at firing rate above 50 W/cm2.
INCIDENT SIGNAL PARAMETERS ESTIMATION ON ANTENNA UNIFORM LINEAR ARRAY

This paper presents a tool for the modeling, analysis, and simulation for extraction of the Directions of Arrival (DOA) of several signals impinging on uniform linear arrays. The first part of this paper describes the Multiple Signal Classification (MUSIC) technique of direction of arrival estimation and simulation method. The second part presents some illustrative simulation cases of MUSIC-DOA estimation by using Graphical User Interface ( GUI). Simulation results are analyzed by using Matlab program in order to conclude on the algorithm's accuracy and reliability. To demonstrate the versatility and accuracy of the developed tool, it is used to study the effect of changing a number of parameters related to the signal environment as well as the antenna array.
Experimental and Numerical Analysis of a PCM-Supported Humidification-Dehumidification Solar Desalination System

This work discusses the results of experimental and theoretical studies on a humidification-dehumidification (HDH) desalination system fully equipped with phase change materials (PCM). Transient simulation models for the individual components in the HDH system have been established and validated against experimental measurements. Using both experimental and simulation tools, a detailed heat and mass transfer analysis for the performance of the evaporator and condenser over a wide range of operation conditions under steady state has been performed and clearly documented using different types of packing materials. Furthermore, a yearly parameter analysis for the whole HDH plant has been performed under continuously varying weather conditions for two locations in Egypt. The overall performance analysis focuses on the optimum operation conditions of the HDH system with and without external PCM thermal buffer.
Assessing the Impact of an Industry-led Professional Development Workshop on the 21st Century 'Soft' Skills of CM Students at an HBCU

Dr. Andrea Ofori-Boadu is an Assistant Professor of Construction Management (CM) with the Department of Built Environment at North Carolina A & T State University. She has a Ph.D. in Technology Management, an M.Sc. in Industrial Technology, and a B.Sc. in Building Technology. Dr. Ofori-Boadu has over 20 years of relevant academic and industry experience. Her current research interests are in sustainability, bio-modified cements, and STEM education.
Short communication: ‘Crystal’ guava fruit quality in response to altitude variation of growing location

Abstract. Widyastuti RAD, Budiarto R, Warganegara HA, Timotiwu PB, Listiana I, Yanfika H. 2022. Short Communication: ‘Crystal’ guava fruit quality in response to altitude variation of growing location. Biodiversitas 23: 1546-1552. ‘Crystal’ guava is a popular fruit with high demand due to its delicious taste and super nutritious content. This study aimed to analyze the fruit production and quality of ‘Crystal’ guava in response to different altitudes of growing location, i.e., highland and lowland in the tropics. Ten individual guava trees were maintained in a nested design by small-scale farmers in both lowland (Brajaselebah orchard, 25 m asl) and highland (Gunung Batu orchard, 1000 m asl). The result showed that the altitude of the growing location affected the plant production and fruit quality of ‘Crystal’ guava. Although there was no significant difference in vegetative and generative shoot numbers among the two growing locations, there was a tendency for a dominant generative shoot in highland. Lowland orchards produced a significantly heavier fruit compared to highland orchards. ‘Crystal’ guava tree was able to produce 41 to 46 fruits per tree with a total fruit production of about 8.69 to 9.21 kg per tree. The significantly lower incidence of fruit smoothness in lowland compared to highland was affected by a significantly higher incidence of fruit scars in the lowland. Guava fruit from the lowland had a significantly higher TSS, while fruit from the highland contained a significantly higher vitamin C than lowland.
Topographic Modulation of the Wind Stress Impact on Eddy Activity in the Southern Ocean

Previous studies proposed that the increase in the eddy kinetic energy (EKE) in the Southern Ocean in recent decades is primarily caused by the strengthening of circumpolar surface westerlies. However, the spatial pattern of EKE change does not match the pattern of wind change. Here, we revisit the relationship between EKE and wind stress through an observational analysis and model experiments and show that the change in EKE is primarily determined by the mean flow. The increasing wind stress intensifies the circumpolar mean flow contributing to increasing EKE; yet strong EKE variations are generally confined downstream of major topographic features. This arises from the releasing of available potential energy as the mean flow passes through the topography. Our results indicate that the change in Southern Ocean eddy activity has a distinct localization characteristic due to the strong dynamical influence of topography.
Nonsmooth Dynamic Tracking Control for Nonlinear Systems With Mismatched Disturbances: Algorithm and Practice

This article addresses a dynamic tracking control issue for a class of nonlinear systems subject to mismatched disturbances. As an alternative control design algorithm for practitioners, a simple nonsmooth tracking scheme with a self-tuning scaling gain is proposed under a nonrecursive synthesis framework. In reference to the existing related works, a main distinguishable feature is that the scaling gain of the proposed regulation law can be adaptively adjusted subject to different perturbation levels; therefore, the control system is able to achieve an improved transient-time control performance while an accurate tracking objective is guaranteed. In addition, the proposed nonrecursive design philosophy is able to obtain the simplest state-feedback expression of the controller through essentially detaching the stability analysis with controller design procedure, i.e., without going through recursive determination steps of classical virtual controllers. The efficacy of the proposed method is validated by an illustrative numerical example and a real-life application to a dc–dc boost converter system.
The Impact of Long-Term Memory in the Iterated Prisoner's Dilemma

Long term memory stores critical data for long periods of time. In this paper we show that the addition of long term memory grants agents playing the iterated prisoner’s dilemma (IPD) a competitive advantage. This paper extends previous work [1] in which IPD players utilized a limited subset of previous game actions to drive gameplay. We introduce a novel representation of strategies for the IPD which consist of a pair of finite state machines one which records long term memory into a set of scalar variables, and a second which drives actions based on the memory data. Control agents act in much the same way but do not have access to long term memories.
A Parallel Strategy for Solving Sparse Linear Systems Over Finite Fields

In this paper we describe a number of parallel techniques that were applied to the problem of ﬁnding the null-spaces of thousands of large sparse matrices. This collection of matrices were derived from the discrete logarithm problem attack over the ﬁnite ﬁeld F 3 6 · 509 recently carried out by Adj et al. in [2]. Our software library was mainly executed in the supercomputer ABACUS [7], where in total 21, 870 large sparse linear algebra systems were processed. Solving those linear algebra problems involved a computational effort of over 138 core-years, requiring a memory space of over 645 gigabytes to store the corresponding vector solutions.
Resilience Metrics for Building-Level Electrical Distribution Systems with Energy Storage

The energy system infrastructure that delivers power to a building’s loads needs to be resilient to withstand and recover from extreme outages (e.g., grid faults that leave millions of people without power during severe weather events). Building-level electrical distribution systems (BEDSs) distribute power from a building’s energy sources—including the grid, solar photovoltaic (PV) panels, and batteries—to its loads, including lighting, HVAC, and plug loads. BEDS with storage can provide resilience by distributing local electricity supply to critical loads during an outage. Quantitative metrics are needed to assess the resilience improvements associated with new BEDS and storage system technologies. In this paper, we apply an existing metric, the probability of outage survival curve (POSC), to BEDS with storage and propose novel metrics that improve upon POSC. Through a simulation-based case study, we demonstrate how these metrics are impacted by the BEDS design and how they can be used to design a resilient system.
Development of a truss mount with focus on ease of installation

Products of Axis Communications, mostly premium class cameras and wall mounts, have previously been installed on trusses. However, Axis has not provided any means of installation so it has been up to the installers to create their own solutions. This report describes the research and development of Axis first truss mount. The aim of the master thesis was to both study the environment of the product and the intended user to make it a good fit for both the trusses and the users. The goal was to provide Axis with a concept solution prototype of both a product and a process of installation. To solve this, the authors applied Human-centered design in combination with the Double Diamond method. The whole method was iterated twice to provide the team with many opportunities to receive feedback. The first cycle focused on researching and the insights gained laid the foundation for the direction of development. Many concepts were developed and the cycle ended with choosing one solution and further developing it into a testable prototype. The prototype then acted as reference for the second round of research. Tests were conducted to see if the users used the product the intended way and if the team had understood the problem correctly. The final concept has made the process of installation easier through the possibility to, without tools, swiftly clamp the product in place to make it securely fastened for its own weight. This allows for the installation to be made in multiple steps that affords pausing in between. The concept has received good reviews from both users as well as employees at Axis.
HomeGuardian: Detecting Anomaly Events in Smart Home Systems

As a typical application of Internet of Things (IoT), home automation systems, namely, smart homes, provide a more convenient and intelligent life experience through event recognition, automation control, and remote device access. However, smart home systems have also given rise to new complications for security issues. As an event-driven IoT system, smart home environments are vulnerable to security attacks, and vulnerable devices are far-spread due to the quick development cycles. Attack vectors to smart homes inevitably manifest in abnormal event contexts. In this paper, we propose HomeGuardian, a context-based approach to identify abnormal events in smart homes. In our approach, we extract temporal context and environmental context from system logs, aggregate (embed) these hybrid contexts, and construct a learning-based classifier to identify the abnormal events. We develop a testbed to implement and evaluate our approach.
Biogeographic history predicts bee community structure across floral resource gradients in south‐east Australia

Plant populations are declining in their native ranges around the globe through the expansion of agriculture, urbanization, and plant invasions. We test the hypothesis that animal species that have spent more of their evolutionary history in a region are more dependent on native plants, particularly those plants that have spent more of their evolutionary history in the region, and are therefore more negatively impacted by native plant decline.
Image Geolocation Method Based on Attention Mechanism Front Loading and Feature Fusion

Image geolocation is an important technique for robotics and autonomous systems. The existing methods mainly extract local features from images directly and use global descriptors, which are aggregated by these local features, to retrieve candidate references from all references. Thus, the training efficiency is affected by the image noises and the accuracy is so limited that the further verification is extremely time consuming. To address these issues, this work proposes an image geolocation framework, which adds the noise filtering layer before local feature extraction. Based on this framework, an image geolocation method based on attention mechanism front loading and feature fusion is designed. In the noise filtering layer, the proposed method uses triplet attention to denoise images thus leading to higher training efficiency. In the feature aggregation layer, an improved SPP (spatial pyramid pooling) is designed to extract the local factors reflected by the position relationships among local features. Then, the local factors are incorporated with the global factors extracted by NetVLAD. The fused descriptors contain not only the statistic of the geometric elements but also the position relationships among them. The experimental results show that the proposed method outperforms NetVLAD in terms of the training convergence round and Recall@ N ( N = 1 , 5 , 10 , 20 ); especially, the convergence round of Recall@5 reduces from 25 to 10, the convergence round of Recall@10 reduces from 25 to 7, Recall@1 increases from 79.45% to 84.01%, and Recall@5 increases from 90.10% to 92.81%.
Exploring offending characteristics of young people with foetal alcohol spectrum disorder in Western Australia

Neurodevelopmental impairments resulting from Foetal Alcohol Spectrum Disorder (FASD) can increase the likelihood of justice system involvement. This study compared offence characteristics in young people with FASD to demographically matched controls (n = 500) in Western Australia. A novel approach (i.e. association rule mining) was adopted to uncover relationships between personal attributes and offence characteristics. For FASD participants (n = 100), file records were reviewed retrospectively. Mean age of the total sample was 15.60 years (range = 10–24), with 82% males and 88% Australian Aboriginal. After controlling for demographic factors, regression analyses showed FASD participants were more likely than controls to be charged with reckless driving (odds ratio, OR = 4.20), breach of bail/community orders (OR = 3.19), property damage (OR = 1.84), and disorderly behaviour (OR = 1.54). Overall, our findings suggest justice-involved individuals with FASD have unique offending profiles. These results have implications for sentencing, diversionary/crime prevention programs and interventions.
4DME: A Spontaneous 4D Micro-Expression Dataset With Multimodalities

Micro-expressions (ME) are a special form of facial expressions which may occur when people try to hide their true feelings for some reasons. MEs are important clues to reveal people's true feelings, but are difficult or impossible to be captured by ordinary persons with naked-eyes as they are very short and subtle. It is expected that robust computer vision methods can be developed to automatically analyze MEs which requires lots of ME data. The current ME datasets are insufficient, and mostly contain only one single form of 2D color videos. Researches on 4D data of ordinary facial expressions have prospered, but so far no 4D data is available in ME study. In the current study, we introduce the 4DME dataset: a new spontaneous ME dataset which includes 4D data along with three other video modalities. Both micro- and macro-expression clips are labeled out in 4DME, and 22 AU labels and five categories of emotion labels are annotated. Experiments are carried out using three 2D-based methods and one 4D-based method to provide baseline results. The results indicate that the 4D data can potentially benefit ME recognition. The 4DME dataset could be used for developing 4D-based approaches, or exploring fusion of multiple video sources (e.g., texture and depth) for the task of ME analysis in future. Besides, we also emphasize the importance of forming a clear and unified criteria of ME annotation for future ME data collection studies. Several key questions related with ME annotation are listed and discussed in depth, especially about the relationship between AUs and ME emotion categories. A preliminary AU-Emo mapping table is proposed with justified explanations and supportive experimental results. Several unsolved issues are also summarized for future work.
NAFLD: Mechanisms, Treatments, and Biomarkers

Nonalcoholic fatty liver disease (NAFLD), recently renamed metabolic-associated fatty liver disease (MAFLD), is one of the most common causes of liver diseases worldwide. NAFLD is growing in parallel with the obesity epidemic. No pharmacological treatment is available to treat NAFLD, specifically. The reason might be that NAFLD is a multi-factorial disease with an incomplete understanding of the mechanisms involved, an absence of accurate and inexpensive imaging tools, and lack of adequate non-invasive biomarkers. NAFLD consists of the accumulation of excess lipids in the liver, causing lipotoxicity that might progress to metabolic-associated steatohepatitis (NASH), liver fibrosis, and hepatocellular carcinoma. The mechanisms for the pathogenesis of NAFLD, current interventions in the management of the disease, and the role of sirtuins as potential targets for treatment are discussed here. In addition, the current diagnostic tools, and the role of non-coding RNAs as emerging diagnostic biomarkers are summarized. The availability of non-invasive biomarkers, and accurate and inexpensive non-invasive diagnosis tools are crucial in the detection of the early signs in the progression of NAFLD. This will expedite clinical trials and the validation of the emerging therapeutic treatments.
The Relationship between Stigma and Anxiety among Nurses during COVID-19 Pandemic

Background: Puskesmas as public health facility encounter challenges in facing COVID-19, including nurses who provides care for patients who faces challenges in this emergency. The frequent interaction of nurses with patients put nurses in a high risk of being exposed to COVID-19. This situation triggers a negative stigma towards nurses in the community which impacted a lot of nurses. Purpose: The purpose of this study is the relation between anxiety level and stigma on nurses during the COVID -19 pandemic. Methods: The study used a descriptive analytic study with a cross-sectional study design with 96 respondents from Puskesmas Jambi City. Statistical test used in this research is Chi Square. Results: Statistical test result shows that there is a significant relation between stigma and anxiety on nurses in Puskesmas Jambi city with p value=0.001. Conclusions: Nurses are COVID-19 front liners, who are always exposed with patients, along with the stigma that comes from the community. The stigma could affect the nurses psychologically. Therefore, more attention is needed regarding this matter. Increasing public knowledge regarding infectious disease is one of the first steps in handling this issue as it could change the public perception regarding COVID-19 and its urgently needed to eliminate the negative stigma against nurses. for the next study, it can be a reference and research more about other factors that cause anxiety in nurses during the COVID-19 pandemic
Reconfigurable negative group delay circuit with low signal attenuation

A novel circuit scheme is presented for the design of reconfigurable negative group delay circuit (RNGDC) with very low signal attenuation (SA), which is based on a lossy coupled‐line Microstrip (MS) resonator. Theoretical analysis indicates that reconfigurable characteristics in the proposed circuits can be obtained by tuning the resistance of the variable resistor, which is loaded at a specific point on the MS resonator. Based on the study of one‐stage RNGDC, a two‐stage RNGDC arranged in an anti‐symmetrical manner is designed to provide an extended reconfigurable negative group delay range. To validate the performance of the proposed circuit scheme, the prototypes of one‐stage and two‐stage RNGDC have been designed working at a center frequency of 1.73 GHz. Measured results of the two‐stage RNGDC exhibit a group delays variation of −2 ns to −10 ns with signal attenuation variation of −4.5 dB to −9.3 dB at the center frequency, which demonstrates much lower SA compared to the previously‐reported RNGDCs.