Miracle-dz/UniFAR-FTUs huggingface dataset:
Face Recognition using Principal Component Analysis and Clustered Self-Organizing Map

—Face recognition is one of the cornerstones of the face processing schemes that composed the contemporary intelligent vision-based interactive systems between computers and humans. Instead of using neurons of the Self-Organized Map (SOM) neural network to cluster the facial data, in this work, we applied an agglomerative hierarchical clustering to cluster the neurons of the SOM network, which in turns, used to cluster the facial dataset. In prior, Principal Component Analysis (PCA) is employed to reduce the dimension of the facial data as well as to establish the initial state of SOM neurons. The design of the clustered-SOM recognition engine involves post-training steps that labeled the clustered SOM neurons resulting in a supervised SOM network. The effectiveness of the proposed model is demonstrated using the well-known ORL database. Using five images per person for SOM training, the proposed recognizer results in a recognition rate of 94.7%, whereas using nine images raise the recognition rate up to 99.33%. The facial recognizer has attained a notable reliability and robustness against the additive white Gaussian noise, where increasing the level of noise variance from 0 to 0.09, the recognition rate decreased only by 8%. Furthermore, time cost is analyzed, where using 200 images for training takes less than 4 seconds to be performed, whereas testing using a new set of 200 images takes less than 0.013 seconds which is competitive to many artificial intelligence and machine learning based schemes.
Dimensional Analysis of Inelastic Structures with Negative Stiffness and Supplemental Damping Devices

AbstractA negative stiffness device (NSD) has been proposed as an innovative way for seismic protection of structures. It was shown both numerically and experimentally to improve the performance of inelastic structures when it is appropriately designed for the given application. In order to systematically evaluate the effects of a NSD, dimensional analysis is used in this study to quantify the structural responses as the function of input ground motion characteristics, model parameters of structure and NSD, as well as supplemental damping. To facilitate this, a simplified yet parameterized numerical model is first proposed to mimic the observed responses of the tested prototype NSD. The dimensional analysis is then conducted on a single degree of freedom (SDOF) system equipped with both a NSD and a nonlinear damper. By comparing the dimensionless structural responses for the cases of (1) inelastic structure only, (2) inelastic structure with nonlinear damper, and (3) inelastic structure with both nonlinea.
Design and Comparative Study of Voltage Regulation-Based 2-Tap Flexible Feed-Forward Equalizer for Voltage-Mode Transmitters

Herein, the analog-based, 2-tap feed-forward equalization (FFE) voltage-mode transmitter using dual supply/ground voltage regulation is presented. In an FFE data modulator, the data are divided into transition and non-transition segments, and are transmitted to the main- and post-tap drivers. By using dual voltage regulation, flexible FFE strength adjustment is possible without process dependency, and the short-current path is eliminated, thus improving the overall energy efficiency. Furthermore, this structure with independent impedance calibration loops has good on-resistance and return loss characteristics, thereby securing signal integrity. In addition, by regulating the supply/ground voltages, the output swing and common-mode voltage can be adjusted independently. Therefore, our transmitter can serve multiple standards and channel environments with a single design. To verify the effectiveness of our method, we designed a prototype of the source-synchronous transmitter in a 65 nm CMOS process, and its performance was compared with that of a conventional FFE design. The simulation results show that the proposed design has better on-resistance, return loss, and FFE controllability, and it has an energy efficiency of 2.23 pJ/bit at 20 Gb/s.
Ventilation improvement for reducing individual exposure to cooking-generated particles in Chinese residential kitchen

This paper investigates the situation of residential kitchen ventilation and individual exposure in China and attempts to reduce the exposure through organizing local make-up airflow. Measurements were conducted in a kitchen chamber to reproduce the real exposure to the cooking-generated particles under the mode of natural make-up airflow surveyed. Measurements results show that an individual cooking in a kitchen could be exposed to a concentration of airborne particles at ∼10 mg/m3 within a simplified cooking process of oil heating, in the case of an experimental kitchen chamber with an open window or closed window/door. Local make-up airflow through upward make-up air supply or downward make-up air supply was further investigated to determine the effectiveness for reduction of the exposure level. When the air-supply velocity at the outlet of the upward make-up air supply or downward make-up air supply mode was well defined, the individual exposure level could be reduced by 2–3 orders of magnitude, as compared to the baseline case when all the make-up air was from open window. Intake fraction of cooking-generated particles could be as low as ∼10−5 and ∼10−6 under the two modes. This finding has illustrated that well-organized local make-up airflow could largely reduce an individual’s exposure to the cooking-generated particles in Chinese residential kitchen.
Estimating the Effect of Motivational Interventions in Patients with Eating Disorders: A Systematic Review and Meta-Analysis

Motivation to change behavior is seen as an important factor in achieving a better treatment effect in patients with eating disorders (ED). The aim of this systematic review was to assess whether motivational interviewing (MI) and motivational enhancement therapy (MET) might (1) increase motivation to change behavior and (2) improve eating disorder psychopathology (EDP) and body mass index (BMI) in patients with ED. To investigate this, a literature search was conducted on 9 March 2021 on four scientific databases: Cochrane, Embase (Ovid), MEDLINE (PubMed), and PsycInfo (EBSCO). A total of 2647 publications were identified and following a rigorous stepwise procedure to assess titles and abstracts and, thereafter, full texts of relevant publications, 13 studies were included in the data extraction and analyses. A few individual studies (n = 5) found a significant increase in motivation, two a decrease in ED symptoms (n = 2), while none found an effect on BMI. However, the meta-analysis of each outcome found effect sizes near zero, thereby confirming the results of previous narrative reviews that have described a lack of effect of MET/MI on motivation in ED. Since the individual studies differ substantially in design, and the outcomes were inconsistently assessed with regards to instruments and duration, the effect of MET/MI on motivation for behavioral change, ED psychopathology, and BMI is still unclear.
Mulan: A Multiple Residual Article-Wise Attention Network for Legal Judgment Prediction

Legal judgment prediction (LJP) is used to predict judgment results based on the description of individual legal cases. In order to be more suitable for actual application scenarios in which the case has cited multiple articles and has multiple charges, we formulate legal judgment prediction as a multiple label learning problem and present a deep learning model that can effectively encode the content of each legal case via a multi-residual convolution neural network and the semantics of law articles via an article encoder. An article-wise attention mechanism is proposed to fuse the two types of encoded information. Experimental results derived on the CAIL2018 datasets show that our model provides a significant performance improvement over the existing neural models in predicting relevant law articles and charges.
Development of a creeping locomotion snake robot

Biological snakes' diverse locomotion modes and physiology make them supremely adapted for the environment. The special structure of snakes and their unique movement offer them peculiar ability of climbing and moving even in some ill-conditioned environments, such as on the marshland or in narrow tubes. Using these snakes' noticeable features in robots is becoming more important for generating a new type of locomotor and expanding the function of robots. We introduce a 12-link snake-like robot, which is moved through the difference between normal and tangential friction. The propelling force of our robot is generated only by swinging its joints from side to side.
Energy demand and heart rate evaluation at different phases during a match along an official soccer competition Avaliação da demanda energética e frequência cardíaca em diferentes fases durante jogos ao longo de uma competição oficial de futebol.

1 Abstract - The purpose of the present study was to analyze the energy expenditure and heart rate (HR), expressed as mean and maximal heart rate (HR max ), along matches of an official soccer competition. Methods: Eighteen under-20 year old (U-20) soccer players from a first-division Brazilian soccer team were evaluated during 15 matches. The rela - tionship between HR and oxygen uptake (HR/VO 2 relationship) was established, and a linear regression equation was developed for each individual player participating in the study. This equation was then used to determine the oxygen uptake and the correspond - ing energy expenditure based on the HR values measured during the games. The HR was recorded at 5-second intervals, which were clustered in phases of 15 minutes (0-15 min, 15-30 min e 30-45 min) for each half time (first half (FH) and second half (SH)). Results: The players' oxygen uptake was 308.3 ± 11.9 LO 2 /game and the energy expenditure was 17.3±1.3 Kcal.min -1 and 1,542.9±125.1 Kcal/game. The results showed that there were significant differences between the HR and HR max identified in the first half (FH 15-30 min) compared to the second half (SH 0-15 min and SH 30-45 min), and at FH 30-45 min compared to SH 0-15 min (p<0.05). Conclusions: We concluded that soccer should be considered as an extremely arduous activity for U-20 players due to the high energy expenditure during the matches of an official championship. We also concluded that, during soccer games with young players, FH 15-30 min could be considered the most intense phase, because the highest values of HR and HR max usually occur at this phase.
Smart SOP’s Surveillance System using Deep Neural Network

The global pandemic Corona virus sickness 2019 had a devastating impact on the world, according to statistics received by the World Health Organization. A study shows that about 33 million people are affected by the virus and more than 1 million deaths are reported worldwide. Currently, there are no specific vaccines or treatments for COVID-19. Now, WHO recommends that wearing a mask and following the SOP’s can help us in preventing the spread of the virus. There are only few studies about face mask detection based on image analysis. To create a safe environment in public places, educational institutions, & shopping malls we are proposed an effective idea based on computer vision and AI which is focused on real-time automated monitoring through the camera to detect people whether they are wearing a mask or not, also checks body temperature by the sensorbased model. In this proposed system modern deep learning algorithms have been mixed with different techniques to detect the unmasked faces and temperature and generate warning alerts by capturing images of the people not wearing masks and if the person has temperature, then it will also generate an alert of having temperature. This system favors society in preventing the spread of the virus as it has already infected 33 million people worldwide. The goal is to evaluate the face detection through image processing to prevent society from the spread of global pandemic disease and pollution.
What factors contribute to environmental degradation in G11 economies? Emphasizing the importance of renewable and non-renewable energy sources

ABSTRACT This study explored the dynamic nexus between trade openness, non-renewable, renewable-energy consumption, urbanization, economic growth, and ecological footprint considering the Sustainable Development Goals (SDGs) 7 and 13 of ensuring access to reliable, renewable, and clean energy technology, as well as climate action, by employing a second-generation panel data technique for G11 economies from 1991 to 2018. The study used second-generation panel unit root tests, panel cointegration techniques, and the augmented mean group (AMG) approach to estimate the long-run magnitude of the parameters for this purpose. The empirical findings show that trade openness, economic growth, and urbanization all considerably increase the environmental deficit, but renewable energy use minimizes total environmental degradation in the long run. Furthermore, the Dumitrescu and Hurlin (D-H) causality test discovered that economic growth, non-renewable consumption, urbanization, and the EFP have long-term bidirectional correlation, whereas GDP, renewable energy consumption, and trade openness have long-term unidirectional causality. As a result, the industrial infrastructure of the G11 nations must be modernized, and renewable energy must be enhanced further.
A systems approach to assessing organisational viability in project based organisations

Purpose – Extant literature highlights the increasing inability of project-based organisations (PBOs) to meet infrastructure client’s expectations, particularly as it concerns the delivery of socio-economic outcomes during the delivery process. Unclear communication channels and poor processing of information especially as it pertains to client’s strategic objectives results in a misalignment of objectives among participating parties. As its central proposition, the purpose of this paper is to hold that unclear communication channels between parties within infrastructure project PBOs affects their degree of internal cohesion hence posing strong challenges to their overall viability. Design/methodology/approach – Applying the Viable Infrastructure Delivery Systems Model (VIDM); a model premised on the tenets of the Viable Systems Model, this qualitative study proceeds to assess a particular PBO within a developing country to understand its communication and control channels and to identify where gaps likely to affect the internal cohesiveness of the PBO, if any, existed. Whereas semi-structured interviews and project/policy documents were used as data collection tools, data were analysed using pre-set themes. Findings – According the study’s findings, an absence of a prevalent common identity was observed among the various parties to the PBO. Contractors’ capabilities to deliver on time and to budget based on their expertise remained pivotal within the PBO thus abandoning the attainment of the client’s pre-defined socio-economic objectives. Cases of faulty and ineffective organisational architecture, functional and communication issues were observed. Research limitations/implications – Based upon these findings, it is recommended that the VIDM be adopted at the commencement of the PBO lifecycle and used at various intervals by project managers and other stakeholders for assessing the levels of organisational viability. Originality/value – The methodology and findings resulting from this study represent information from fieldwork conducted by the author and as such have not been used elsewhere.
Study about Football Action Recognition Method Based on Deep Learning and Improved Dynamic Time Warping Algorithm

Artificial intelligence recognition of human actions has been used in various fields. This article is based on deep learning and improved dynamic time regularization algorithms to study football action postures. This paper proposes a hierarchical recurrent network for understanding team sports activities in image and position sequences. In the hierarchical model, this article integrates the proposed multiple human-centered features on the time series based on LSTM output. In order to realize this scheme, the holding state is introduced as one of the external controllable states in LSTM, and the hierarchical LSTM is extended to include the integration mechanism. Test outcomes demonstrate those adequacies of the recommended framework, which includes progressive LSTM human-centred benefits. In this study, the improvement of the reference model in the two-stream LSTM-based method is shown. Specifically, by combining human-centered features and meta-information (e.g., location data) into the postfusion framework proposed in the article, the article also proves that the action categories have increased, and the observations enhanced the robustness of fluctuations in the number of football players. The experimental data shows that 67.89% of the postures of football players through this algorithm can be recognized by the improved dynamic time warping algorithm.
Perspective on the Use of DNA Repair Inhibitors as a Tool for Imaging and Radionuclide Therapy of Glioblastoma

Simple Summary The current routine treatment for glioblastoma (GB), the most lethal high-grade brain tumor in adults, aims to induce DNA damage in the tumor. However, the tumor cells might be able to repair that damage, which leads to therapy resistance. Fortunately, DNA repair defects are common in GB cells, and their survival is often based on a sole backup repair pathway. Hence, targeted drugs inhibiting essential proteins of the DNA damage response have gained momentum and are being introduced in the clinic. This review gives a perspective on the use of radiopharmaceuticals targeting DDR kinases for imaging in order to determine the DNA repair phenotype of GB, as well as for effective radionuclide therapy. Finally, four new promising radiopharmaceuticals are suggested with the potential to lead to a more personalized GB therapy. Abstract Despite numerous innovative treatment strategies, the treatment of glioblastoma (GB) remains challenging. With the current state-of-the-art therapy, most GB patients succumb after about a year. In the evolution of personalized medicine, targeted radionuclide therapy (TRT) is gaining momentum, for example, to stratify patients based on specific biomarkers. One of these biomarkers is deficiencies in DNA damage repair (DDR), which give rise to genomic instability and cancer initiation. However, these deficiencies also provide targets to specifically kill cancer cells following the synthetic lethality principle. This led to the increased interest in targeted drugs that inhibit essential DDR kinases (DDRi), of which multiple are undergoing clinical validation. In this review, the current status of DDRi for the treatment of GB is given for selected targets: ATM/ATR, CHK1/2, DNA-PK, and PARP. Furthermore, this review provides a perspective on the use of radiopharmaceuticals targeting these DDR kinases to (1) evaluate the DNA repair phenotype of GB before treatment decisions are made and (2) induce DNA damage via TRT. Finally, by applying in-house selection criteria and analyzing the structural characteristics of the DDRi, four drugs with the potential to become new therapeutic GB radiopharmaceuticals are suggested.
Study on the Interaction between Serum Thyrotropin and Semen Parameters in Men

The effect of thyroid function on semen parameters has been studied in pathological conditions in small studies. With this research work, we aimed to study thyroid hormone effects on semen parameters in 130 men who were evaluated for couple subfertility. Our study was cross-sectional. We noted semen volume, sperm concentration, total sperm count, testosterone levels and thyrotropin (TSH) levels. The analysis included ordinary least squares regression (OLS-R), quantile regression (QR) and segmented line regression (SR). Using OLS-R, a weak negative correlation was found between the logTSH levels and semen volume (r = −0.16, r2 = 0.03, p = 0.05). In Q-R, each incremental unit increase in logTSH decreased the mean semen volume between −0.78 ± 0.44 and −1.33 ± 0.34 mL (40–60th response quantile) and between −1.19 ± 0.71 and −0.61 ± 0.31 mL (70–90th response quantile) (p = 0.049). With SR, a biphasic relationship of sperm concentration with TSH was noted (positive turning to negative, peaking at TSH = 1.22 μIU/mL). Thus, a weak negative association between the TSH levels and semen volume was noted, showing a trough within the usual normal range for TSH. Moreover, a biphasic relationship between the sperm concentration and TSH was also noted, peaking at approximately mid-normal TSH levels. Based on our results, TSH explained slightly less than 3% of the variation in semen volume and 7% of the sperm concentration (thus, other factors, which were not studied here, have a more important effect on it).
A new species of Petalacmis firefly from Bolivia, with a key to species (Coleoptera, Lampyridae)

﻿Abstract Petalacmis Olivier, 1908 is a poorly known genus of firefly endemic to South America and is currently the only member of the subfamily Lampyrinae, tribe Lampyrini known to occur on the continent. Here, we describe a new species, Petalacmistriplehornisp. nov. from Bolivia and compare it to the two other described species in the genus. A key to Petalacmis species based on male traits, as well as illustrations of morphological features, are given in detail for the first time. We present unique, previously neglected traits of Petalacmis species and compare them to other Lampyrinae.
Q‐switched neodymium‐doped fiber laser with a gold nanoparticle saturable absorber

A gold nanoparticle saturable absorber (SA) was successfully employed in a Neodymium‐doped fiber laser (NDFL) cavity for pulse generation via a Q‐switching mechanism for the first time. The SA device made by mixing the gold nanoparticles into PVA solution before being dried onto a fiber ferrule was included in the NDFL cavity, which was optimized to obtain Q‐switched pulses centered at 1089 nm wavelength. The pulse rate of the laser rose from 32.1 to 47.6 kHz while the pulse width fell from 8.7 to 5.8 µs as the 808 nm pump laser was varied from 67 to 114 mW. The output power also linearly improved from 4.16 to 5.07 mW as the pump strength boosted from 145.83 to 187.04 mW. The gold nanoparticles SA also offers excellent modulation depth of 5.6%, which is fit for SA purpose. The developed Q‐switched laser has numerous applications including, material micromachining, communication, sensing, and so on.
Bi-HRNet: A Road Extraction Framework from Satellite Imagery Based on Node Heatmap and Bidirectional Connectivity

Today, with the rapid development of the geographic information industry, automatic road extraction from satellite imagery is a basic requirement. Most existing methods have been designed based on binary segmentation. However, these methods do not consider the topological features of road networks, which include point, edge, and direction. In this study, a topology-based multi-task convolution network is designed, namely Bi-HRNet, which can effectively learn the key features of nodes and their directions. First, the proposed network learns the node heatmap of roads, and then the pixel coordinates are extracted from the node heatmap via non-maximum suppression (NMS). At the same time, the connectivity between nodes is predicted. To improve the integrity and accuracy of connectivity, we propose a bidirectional connectivity prediction strategy, which can learn the bidirectional categories instead of direction angles. The bidirectional categories are designed based on “top-to-bottom” and “bottom-to-top” strategies, which can improve the accuracy of the connectivity between nodes. To illustrate the effectiveness of the proposed Bi-HRNet, we compare our method with several methods on different datasets. The experiments show that our method achieves a state-of-the-art performance and significantly outperforms various previous methods.