Miracle-dz/UniFAR-FTUs huggingface dataset:
Advancing Compilation of DNNs for FPGAs Using Operation Set Architectures

The slow-down of technology scaling combined with the exponential growth of modern machine learning and artificial intelligence models has created a demand for specialized accelerators, such as GPUs, ASICs, and field-programmable gate arrays (FPGAs). FPGAs can be reconfigured and have the potential to outperform other accelerators, while also being more energy-efficient, but are cumbersome to use with today's fractured landscape of tool flows. We propose the concept of an operation set architecture to overcome the current incompatibilities and hurdles in using DNN-to-FPGA compilers by combining existing specialized frameworks into one organic compiler that also allows the efficient and automatic re-use of existing community tools. Furthermore, we demonstrate that mixing different existing frameworks can increase the efficiency by more than an order of magnitude.
The Effect of Lost Data on the IoT Platform on the Formation of Fetal Heart Rate Graphs for Remote Diagnostic Purposes

FHR is the fetal heart rate from bpm recording detected by doppler, FHR monitoring is very important to monitor fetal health to avoid fetal distress or fetal death, FHR provides more in-depth information about how the baby is doing compared to traditional monitoring of the baby. IoT media is a medium for monitoring remote sensor values ​​using internet connections, but there are several obstacles, namely there are doubts about the data displayed by IoT media, namely the risk of missing or unsent data, this will be very dangerous if the data that is should be monitored by doctors as a reference for medical diagnosis and treatment is lost or not displayed on the IoT, because if there is missing data it will cause inaccurate diagnosis or health treatment decisions by doctors. The aim of this study to analyze the effect of lost data on the formation of the Fetal Heart Rate graph on the IoT platform as a medium for remote diagnosis. In addition, FHR data can be saved for further diagnosis by a doctor if needed. This study uses an ESP32 microcontroller which will also be used to send data to IoT (Thinger.io). The independent variable used in this study is FHR data before it is uploaded to the IoT, and the dependent variable is FHR data when it is uploaded to the IoT. The greatest data loss is at the farthest distance of 30 meters with a value of 62.47%. Based on the research that has been done, this study has the advantage that the results obtained from Doppler are close to the BPM value in humans. And also this research has developments that can be done in the future such as adding storage to the website that is used for monitoring, and placing the right position on Doppler so that the results are more stable.
Dielectronic Recombination of Iron L-Shell Ions

An experimental program to study low temperature dielectronic recombination (DR) in the iron L-shell ions Fe17+ to Fe23+ is currently in progress at the TSR heavy-ion storage ring in Heidelberg, Germany. L-shell iron ions play an important role in determining the line emission and thermal and ionization structures of cosmic photoionized plasmas. Successful modelling of these plasmas requires accurate ionization and recombination rates, particularly for low temperature DR which is the dominant recombination mechanism for most iron ions in photoionized plasmas. The dependence of DR on the detailed atomic structure makes it challenging to determine the needed DR rate coefficients theoretically, especially in many-electron systems. Our systematic survey of Li- to F-like Fe-ions is designed to produce high-resolution DR spectra which can be used to benchmark theory for ions of increasing complexity and to provide absolute low-temperature DR rates required in astrophysics.
Emotional Abuse Questionnaire: a validity and reliability study

ABSTRACT This study aims to evaluate the validity and reliability of the Emotional Abuse Questionnaire (EAQ) in Turkish. This psychometric study was conducted between 01/02/2021 and 31/04/2021, with 341 adolescents aged 12–19. Data were analyzed with SPSS and LISREL programs. Language validity of EAQ was determined to be appropriate after translation-back translation and expert opinion. The sample adequacy calculated for the EAQ was evaluated as very good Kaiser Mayer Olkin (KMO = 0.94, X2 = 4104,42). In the Confirmatory Factor Analysis (CFA), of the EAQ revealed that 29 of the 30 items were suitable for Turkish society, they preserved their 6-factor structure, and the factor loads of the items ranged from 0.40 to 0.87. and the CFA fit index values were within acceptable limits/perfect fit limits. In this study, Cronbach’s alpha reliability coefficient was found to be 0.94. The two half reliability levels of the scale were evaluated as 0.91. A strong and highly significant positive correlation was observed in the test-retest results (r = 0.92). Turkish adaptation of EAQ; It was concluded that it has sufficient internal reliability and validity to be able to evaluate emotional abuse and can be easily applied.
Using Radar Wind Observations to Improve Mesoscale Numerical Weather Prediction

Abstract A high-resolution radar data assimilation system is presented for high-resolution numerical weather prediction models. The system is under development at the Naval Research Laboratory for the Navy’s Coupled Ocean–Atmosphere Mesoscale Prediction System. A variational approach is used to retrieve three-dimensional dynamical fields of atmospheric conditions from multiple-Doppler radar observations of radial velocity within a limited area. The methodology is described along with a preliminary evaluation of the impact of assimilated radar data on model forecasts using a case study of a squall line that occurred along the east coast of the United States on 9 May 2003. Results from the experiments show a significant impact from the assimilated radar radial velocity data on the model forecast of not just dynamical but also hydrological fields at all model levels for the duration of the storm. A verification system has also been developed to assess the radar data assimilation impact, and the results show .
Performance of Shallots (Allium Ascalonicum L) in Peat Soil with Organic Fertilizer and Arbuscular Mycorrhizal Fungi (AMF)

Peat soil has the potential and is widely available to be used for shallot cultivation with good and proper management, peat land is classified as marginal land for various types of plants because the soil condition is saturated with water, reacts acidic and contains toxic organic acids and low nutrient status so the condition of plant root media that is not conducive to root development so that it becomes a limiting factor in shallot cultivation. Efforts to increase peatland productivity for shallot cultivation can be carried out by adding organic fertilizers and using rhizosphere microorganisms such as Abuscular Mycorrhizal Fungi (AMF), this study aims to get a dose of organic fertilizer and AMF which can increase shallot production on peat soil. The research method used a separate experimental design (Split Plot) Completely Randomized Design which consisted of 2 factors, namely: AMF treatment (M) main plot consisting of 2 levels (without AMF application and AMF application), the second factor was the dose of organic fertilizer (O) child plot consisting of 6 levels (0 tons ha-1 , 3 tons ha-1, 6 tons ha-1, 9 tons ha-1, 12 tons ha-1 and 15 tons ha-1) there were 12 treatments each repeated 3 times, which was carried out in January-April 2021 in Pontianak City with the parameters of observing plant height, number of leaves, number of tillers, harvested dry tuber weight, harvested dry plant weight and tuber diameter. and the number of leaves, while the AMF treatment independently had a significant effect on the observation of the number of tillers, the weight of harvested dry tubers, the weight of harvested dry plants and the treatment of organic fertilizer with a dose of 3 tons h-1 showed good results because they were not significantly different from the required mines 15, 12 and 6 tons ha-1 .
Investigating the effect strength of positive risk-taking barriers on discharge decisions in occupational therapy intermediate care: A factorial survey

Introduction: Positive risk-taking in occupational therapy intermediate care is a requirement, yet little is known about how positive risk-taking barriers influence discharge decisions at different experience levels. Method: A factorial survey was used to investigate positive risk-taking barriers (Limited Capacity, Risk Averse Family, Blame Culture and No Support). Participants self-categorised their experience level into Novice or Semi-expert or Expert before analysing four vignettes relating to recommending a home discharge for an older adult. Data were analysed using Multiple Regression and One-Way Analysis of Variance. Results: Seventy-four participants responded to two hundred eighty-one vignettes. The barriers that reduced the likelihood to recommend a home discharge for an older adult were ‘No Support’, Novices (β = −0.315, p = 0.002), Semi-experts (β = −0.313, p = 0.001) Experts (β = −0.254, p = 0.009); ‘Limited Capacity’, Novices (β = −0.305, p < 0.003), Semi-experts (β = −0.254, p = 0.006) Experts (β = −0.376, p = 0.001) and ‘Blame Culture’ Semi-experts (β = −0.240, p = 0.010). Novices were found to be less likely to recommend a home discharge by comparison. Conclusion: The ‘Limited Capacity’, ‘No Support’ and ‘Blame Culture’ barriers had the strongest effect and Novices were less likely to recommend a home discharge overall. These findings could inform future research and pre-registration Occupational Therapy education.
Share and Shout: Proto-Slogans in Online Political Communities

This paper proposes a methodology for investigating populism on social media by analyzing the emergence of proto-slogans, deﬁned as nominal utterances (NUs) typical of a political community on social media. We extracted more than 700.000 comments from the public Facebook pages of two Italian populist parties’ leaders (Matteo Salvini and Luigi Di Maio) during the week preceding the 2019 European elections (i.e., from May 20 to May 26, 2019). These comments have been automatically clustered and manually annotated to ﬁnd proto-slogans created by the parties’ supporters. Our manual annotation consists of four layers, namely: Nominal Utterances (NUs), a syntactic device widely used for slogans; Slogans for NUs with a slogan function; Top-down/Bottom-up , to recognize the slogans produced by the politicians and those produced by supporters; Proto-slogans , for NUs devoid of speciﬁc political content that nonetheless express partisanship and support for the leaders.
ROSAT OBSERVATIONS OF RX J1712.6-2414 : A DISCLESS INTERMEDIATE POLAR ?

We present ROSAT observations of the newly discovered polarized intermediate polar, RX 11712.6 2414. Whereas the polarimetry establishes the white dwarf spin period to be 927 s, we show that the X-ray variations occur at the 1003-s synodic (i.e., beat) period. This period is also sometimes seen in both the optical photometry and the radial velocities. New filtered polarimetry of RX 11712.6 2414 establishes a strong wavelength dependence in the circular polarization variations. We argue that these new observations support the contention that RX 11712.6 2414 is a discless accreting system, and the first clear case amongst the asynchronous intermediate
Measurement of trap length for an optical trap

The trap length along the beam axis for an optical trap formed with an upright, oil-immersion microscope was measured. The goals for this effort were twofold. It was deemed useful to understand the depth to which an optical trap can reach for purposes of developing a tool to assist in the fabrication of miniature devices. Additionally, it was desired to know whether the measured trap length favored one or the other of two competing theories to model an optical trap. The approach was to trap a microsphere of known size and mass and raise it from its initial trap position. The microsphere was then dropped by blocking the laser beam for a pre-determined amount of time. Dropping the microsphere in a free-fall mode from various heights relative to the coverslip provides an estimate of how the trapping length changes with depth in water in a sample chamber on a microscope slide. While it was not possible to measure the trap length with sufficient precision to support any particular theory of optical trap formation, it was possible to find regions where the presence of physical boundaries influenced optical traps, and determine that the trap length, for the apparatus studied, is between 6 and 7 micrometers. These results allow more precise control using optical micromanipulation to assemble miniature devices by providing information about the distance over which an optical trap is effective.
DEVELOPING STUDENTS' CREATIVITY IN TEACHING TEYL SUBJECTS DURING COVID-19 PANDEMIC

: The COVID-19 pandemic has influenced the education world, especially teaching and learning. Students must be equipped with four skills to survive in the global competition of the 21st century, namely Collaboration, Critical Thinking, Creativity, and communication (4C). One of the essential skills is creativity. Teachers have to provide learning activities for students to develop their skills. As a result, teachers must adapt to the condition by selecting the appropriate strategies. One of the strategies which can be applied during the pandemic is Project Based Learning. This study aims to describe the process of developing creativity in the students using Project Based Learning in the Teaching English to Young Learners (TEYL) course and the student's responses towards the strategy applied by the lecturer. This study is qualitative; the data were collected by documentation, observation checklist, and interviews. The subjects are lecturers and students taking TEYL courses for the 2020/2021 academic year. This study found that the lecturer employed blended learning to implement the teaching and learning process. She assigned the students a project: learning activities for young learners in the form of a book chapter. Through creating the project in TEYL courses, the students could develop their creativity, especially in fluency, flexibility, originality, and elaboration.
In-fibre Bragg gratings for ultrasonic medical applications

We investigate the feasibility of using in-fibre Bragg gratings to measure ultrasonic fields for medical applications. Two signal processing schemes for interrogating the gratings are described. Preliminary results for each scheme (one a homodyne approach, the other a heterodyne one) give noise-limited pressure resolutions of and atm respectively, each within a 1 Hz bandwidth. The second scheme, however, gives a more stable response.
Investigation of an adaptive sampling method for data interpolation using radial basis functions

An adaptive sampling method is presented for optimizing the location of data points in parameter space for multidimensional data interpolation. The method requires a small number of points to begin, and achieves a compromise between space‐filling updates and local refinement in areas where the data are nonlinear, as measured by the Laplacian. A smooth separation function quantifies the sample spacing, and this is blended with the Laplacian to form a criterion on which to assess potential new sample positions. Validation results are presented using two‐dimensional analytic test cases, which demonstrate that the method can recover known optimal designs and gives improvement over data‐independent approaches. In addition, a detailed analysis of the various model parameters is presented. Initial findings are very promising, and it is hoped that further work using the method to generate an aerodynamic database using CFD simulations will lead to a reduction in the number of points required for a given modelling accuracy. Copyright © 2010 John Wiley & Sons, Ltd.
Kolmogorov, Linear and Pseudo-Dimensional Widths of Classes of s-Monotone Functions in 𝕃 p , 0 < p < 1

Abstract Let ${{B}_{p}}$ be the unit ball in ${{\mathbb{L}}_{p}}$ , $0\,<\,p\,<\,1$ , and let $\Delta _{+}^{s}$ , $s\,\in \,\mathbb{N}$ , be the set of all $s$ -monotone functions on a finite interval $I$ , i.e., $\Delta _{+}^{s}$ consists of all functions $x\,:\,I\,\mapsto \,\mathbb{R}$ such that the divided differences $[x;\,{{t}_{0}},\,. \,,\,{{t}_{s}}]$ of order $s$ are nonnegative for all choices of $\left( s\,+\,1 \right)$ distinct points ${{t}_{0}},\,. \,. \,. \,,{{t}_{s}}\,\in \,I. $ For the classes $\Delta _{+}^{s}{{B}_{P}}\,:=\,\Delta _{+}^{s}\,\cap \,{{B}_{P}},$ we obtain exact orders of Kolmogorov, linear and pseudo-dimensional widths in the spaces ${{\mathbb{L}}_{q}},$ $0\,<\,q\,<\,p\,<\,1$ : $${{d}_{n}}(\Delta _{+}^{s}{{B}_{P}})_{{{\mathbb{L}}_{q}}}^{\text{psd}}\asymp {{d}_{n}}(\Delta _{+}^{s}{{B}_{P}})_{{{\mathbb{L}}_{q}}}^{\text{kol}}\asymp {{d}_{n}}(\Delta _{+}^{s}{{B}_{P}})_{{{\mathbb{L}}_{q}}}^{\text{lin}}\asymp {{n}^{-s}}. $$
Clinical, methodology, and patient/carer expert advice in pediatric drug development by conect4children

Many medicines are used “off‐label” in children outside the terms of the license. Feasible pediatric clinical trials are a challenge to design. Conect4children (c4c) is an Innovative Medicines Initiative project to set up a pan‐European pediatric clinical trial network aiming to facilitate the development of new medicines for children. To optimize pediatric trial development by promoting innovative trial design, c4c set up a European multidisciplinary advice service, including the voice of young patients and families, tailored to industry and academia. A network of experts was established to provide multidisciplinary advice to trial sponsors. Experts were selected to join clinical and innovative methodology expert groups. A patient and public involvement (PPI) database, to include the expert opinion of patients and parents/carers was formed. A stepwise process was developed: (1) sponsors contact c4c, (2) scoping interview takes place, (3) ad hoc advice group formed, (5) advice meeting held, and (6) advice report provided. Feedback on the process was collected. Twenty‐four clinical and innovative methodology expert groups (>400 experts) and a PPI database of 135 registrants were established. As of September 30, 2022, 36 advice requests were received, with 25 requests completed. Clinical and methodology experts and PPI representatives participated in several advice requests. Sponsors appreciated the advice quality and the multidisciplinary experts from different countries, including experts not known before. Experts and PPI participants were generally satisfied with the process. The c4c project has shown successful proof of concept for a service that presents a new framework to plan innovative and feasible pediatric trials.
Mid-push plasma armatures for long-rod electromagnetic gun projectiles

Ongoing research is addressing the concept of mid-pushing plasma armatures in large-bore rail guns. Testing began with solid Lexan projectiles which posed finite risk to the gun in the event of launch package breakup. Designs progressed to the launching of actual separating mid-riding aluminum sabots with steel projectiles representative of actual armor-penetrating flight-configured projectiles. The concept of launching mid-pushing sabots with plasma armatures was validated with these tests. A technique for deconvolution of signals from B-dot probes was developed to determine current distributions in the plasma armature. The technique has been applied to B-dot data from several tests. The results indicate a general tendency of the current to move aft of the projectile tail. This is fortunate, as it reduces the likelihood of arc attachment to conducting sabot/projectile structures and reduces the danger of generating extremely high unbalanced lateral pressures on the aft portion of the launch package. >
Towards a Machine Learning-Based Digital Twin for Non-Invasive Human Bio-Signal Fusion

Human bio-signal fusion is considered a critical technological solution that needs to be advanced to enable modern and secure digital health and well-being applications in the metaverse. To support such efforts, we propose a new data-driven digital twin (DT) system to fuse three human physiological bio-signals: heart rate (HR), breathing rate (BR), and blood oxygen saturation level (SpO2). To accomplish this goal, we design a computer vision technology based on the non-invasive photoplethysmography (PPG) technique to extract raw time-series bio-signal data from facial video frames. Then, we implement machine learning (ML) technology to model and measure the bio-signals. We accurately demonstrate the digital twin capability in the modelling and measuring of three human bio-signals, HR, BR, and SpO2, and achieve strong performance compared to the ground-truth values. This research sets the foundation and the path forward for realizing a holistic human health and well-being DT model for real-world medical applications.
Short- and Long-Term Effects of Underemployment on Workers’ Health: Empirical Analysis from the China Labor Force Dynamics Survey

Underemployment is a global problem. This study aimed to assess the short- and long-term effects of underemployment (hidden unemployment) on workers’ health, using data from the China Labor-force Dynamic Survey (CLDS) 2016 and 2014. Indicators reflecting workers’ self-rated health, mental health, prevalence of illness over time, and employment status were analyzed using logit regression models, propensity score matching methods, and instrumental variable methods. Empirical analyses showed that: (1) In the short-term, the impact on health is multidimensional, with underemployment significantly associated with a decline in workers’ self-rated health, an increase in the propensity for depression, and an increase in the prevalence of illness over a certain period of time. (2) In the long-term, the experience of underemployment two years in the past is associated with a current decline in workers’ mental health. That is, the negative effects of underemployment on workers’ mental health persist and do not disappear rapidly over time. The results demonstrated that underemployment is detrimental to workers’ health in the short- and long-term. In the context of epidemic prevention and control, the government and society should focus on this expanding group, establish labor protection mechanisms, and reduce the multiple effects of underemployment on workers’ health.
Use Coupled LSTM Networks to Solve Constrained Optimization Problems

Gradient-based iterative algorithms have been widely used to solve optimization problems, including resource sharing and network management. When system parameters change, it requires a new solution independent of the previous parameter settings from the iterative methods. Therefore, we propose a learning approach that can quickly produce optimal solutions over a range of system parameters for constrained optimization problems. Two Coupled Long Short-Term Memory networks (CLSTMs) are proposed to find the optimal solution. The advantages of this framework include: (1) near-optimal solution for a given problem instance can be obtained in few iterations during the inference, (2) enhanced robustness as the CLSTMs can be trained using system parameters with distributions different from those used during inference to generate solutions. In this work, we analyze the relationship between minimizing the loss functions and solving the original constrained optimization problem for certain parameter settings. Extensive numerical experiments using datasets from Alibaba reveal that the solutions to a set of nonconvex optimization problems obtained by the CLSTMs reach within 90% or better of the corresponding optimum after 11 iterations, where the number of iterations and CPU time consumption are reduced by 81% and 33%, respectively, when compared with the gradient descent with momentum.