Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemical Exposure to Polycyclic Aromatic Hydrocarbons and Hematological Evaluation among Petrol Pump Workers in Islamabad, Pakistan

Abstract Petroleum goods are extensively consumed in urban areas and cause hazardous effects on individuals related to petroleum related occupations. Chemical exposure of petrol pump workers to petroleum hydrocarbons such as polycyclic aromatic hydrocarbons (PAHs) is unprecedented in Pakistan. We conducted a prospective cohort study to analyze the risk of PAH exposure on hematological anomalies and health symptoms of petrol pump workers. Blood samples of 50 individuals were collected which include petrol pump workers (n = 30) and unexposed controls (n = 20). Serum phenanthrene and pyrene concentrations (µg ml−1) were estimated utilizing High Performance Liquid Chromatography (HPLC) whereas hematological parameters were analyzed by subjecting samples to count Hematocrit, Hemoglobin white and red cells in the blood. Correlation and binary logistic regression analyses were performed to depict association for individual’s exposure with demographic variables and for the prediction of eye-irritation as health risk symptom among petrol pump workers. Results show that hematological parameters are affected by occupational exposure to PAHs while eye-irritation is relatively significant for smokers than the nonsmokers in exposed group (OR = 0.109, 95%; C.I = 0.013–0.881) (p < 0.05). Our study concludes that phenanthrene and pyrene poses serious health risk among petrol pump workers owing to their inevitable PAH exposure.
Robot Navigation in Crowd Based on Dual Social Attention Deep Reinforcement Learning

Finding a feasible, collision-free path in line with social activities is an important and challenging task for robots working in dense crowds. In recent years, many studies have used deep reinforcement learning techniques to solve this problem. In particular, it is necessary to find an efficient path in a short time which often requires predicting the interaction with neighboring agents. However, as the crowd grows and the scene becomes more and more complex, researchers usually simplify the problem to a one-way human-robot interaction problem. But, in fact, we have to consider not only the interaction between humans and robots but also the influence of human-human interactions on the movement trajectory of the robot. Therefore, this article proposes a method based on deep reinforcement learning to enable the robot to avoid obstacles in the crowd and navigate smoothly from the starting point to the target point. We use a dual social attention mechanism to jointly model human-robot and human-human interaction. All sorts of experiments demonstrate that our model can make robots navigate in dense crowds more efficiently compared with other algorithms.
Manipulation of Microstructure and Mechanical Properties in N-Doped CoCrFeMnNi High-Entropy Alloys

Herein, we carefully investigate the effect of nitrogen doping in the equiatomic CoCrFeMnNi high-entropy alloy (HEA) on the microstructure evolution and mechanical properties. After homogenization (1100 °C for 20 h), cold-rolling (reduction ratio of 60%) and subsequent annealing (800 °C for 1 h), a unique complex heterogeneous microstructure consisting of fine recrystallized grains, large non-recrystallized grains, and nanoscale Cr2N precipitates, were obtained in nitrogen-doped (0.3 wt.%) CoCrFeMnNi HEA. The yield strength and ultimate tensile strength can be significantly improved in nitrogen-doped (0.3 wt.%) CoCrFeMnNi HEA with a complex heterogeneous microstructure, which shows more than two times higher than those compared to CoCrFeMnNi HEA under the identical process condition. It is achieved by the simultaneous operation of various strengthening mechanisms from the complex heterogeneous microstructure. Although it still has not solved the problem of ductility reduction, as the strength increases because the microstructure optimization is not yet complete, it is expected that precise control of the unique complex heterogeneous structure in nitrogen-doped CoCrFeMnNi HEA can open a new era in overcoming the strength–ductility trade-off, one of the oldest dilemmas of structural materials.
Tourism and Gross Domestic Product short-run causality revisited: A symbolic transfer entropy approach

We employ a symbolic transfer entropy panel data test in a large-scale data set to provide new insights on the worldwide short-term causality relations between growth and inbound tourists. Using a large data set on 145 countries from the World Bank Open Data website, we show that, despite the evidently strong correlation between these two magnitudes, claiming that the increases in inbound tourists Granger-cause positive shocks in GDP is not supported by the data. By contrast, the data seem to point out in the direction of a reverse causality in that it is GDP growth what drives international inbound tourists in the short run. JEL classification C12, C14, C33, C55.
Effects of Ca on Mechanical Properties of Magnesium Alloy AZ81

The microstructure and mechanical properties of aged AZ81 magnesium alloy with Ca addition have been investigated. The results show that with proper content of Ca addition, the microstructure of AZ81 magnesium alloy is refined. Meanwhile, high melting point granular compounds Al4Ca are formed, and the quantity of β-Mg17Al12 phase is reduced significantly. And the mechanical properties of AZ81 magnesium alloy are enhanced at room temperature and 150°C.
Implementation of Graphic Based Network Intrusion Detection System for Server Operation

Most of small startup companies are exposed to various dangers like hackings or DDoS attacks due to their poor knowledge in server operation and its security. In this project, we have implemented the Graphic Based Network Intrusion Detection System to assist users to operate the server more easily by offering them an intuitive interface for the purpose of stable server operation. When one runs individual or small sized startup business in Republic of Korea, they often overlook the possibility of security accidents or forgo security arrangements because of the costs. Consequently such companies suffer heavy damages in their businesses when they defenselessly exposed to the hackers, leading to serious security accidents. We expect that many companies could be relieved from such difficulties, and proposing our program to encourage the use. Moreover, since all of the network based attacks go through interface cards, it is possible to prepare for the diverse attacks with consistent updating. While network analysis tools are difficult to use and need professional skills, the system suggested in this paper has made it easier to be utilized by non-professional users showing the analysis results graphically and just checking them with mouse clicks. The system can be utilized in detection of intrusions and malignant Botnets, and enabling the use of network analysis tools which are easily adopted by the ordinary users. That is, by checking the information related to the Network Intrusion Detection with a graphic Based method, which does not require expert knowledge, the system can contribute to overall network security.
Minimizing Total Logistics Cost for Long-Haul Multi-Stop Truck Transportation

Whenever there is sufficient demand, companies generally prefer the full truckload (TL) option for long-distance transport, resulting in large and less frequent shipment operations that can be costly if inventory carrying costs are high. Less than truckload (LTL) is another option for transport when carrying costs are high and/or there is insufficient demand. Shipment consolidation provides another option that combines many of the benefits of both TL and LTL. Shipment consolidation is a cost-effective transport solution that combines different size shipments into a single truckload. Combining many loads as a single load brings together economies of scale and potential savings. Traditional routing techniques that minimize distance are not suitable for shipments that have different origins and destinations because it can be beneficial to travel further to minimize overall transport and inventory cost, or what is termed total logistics cost (TLC). Effective consolidation of multi-stop routes to minimize TLC requires routing procedures that are more computationally intensive to find beneficial combinations of loads into consolidated shipments. In this study, we have developed a saving-based procedure to determine consolidated route sequences that minimize the TLC of shipments. Twenty-one data sets were produced using real city coordinates and population densities in North Carolina to demonstrate the effectiveness of the procedure. The solutions of the proposed method are compared with the solutions of the traditional Clarke and Wright (C-W) algorithm. Although the traditional C-W algorithm provides very fast solution times, the proposed method has produced much better solution values.
A Proposal for Performance-based Assessment of the Learning of Machine Learning Concepts and Practices in K-12

Although Machine Learning (ML) is used already in our daily lives, few are familiar with the technology. This poses new challenges for students to understand ML, its potential, and limitations as well as to empower them to become creators of intelligent solutions. To effectively guide the learning of ML, this article proposes a scoring rubric for the performance-based assessment of the learning of concepts and practices regarding image classification with artificial neural networks in K-12. The assessment is based on the examination of student-created artifacts as a part of open-ended applications on the use stage of the Use-Modify-Create cycle. An initial evaluation of the scoring rubric through an expert panel demonstrates its internal consistency as well as its correctness and relevance. Providing a first step for the assessment of concepts on image recognition, the results may support the progress of learning ML by providing feedback to students and teachers.
How to Predict the Spread of COVID-19

For analysis tasks, time counts are of interest – values recorded at some, usually equidistant, points in time. The calculation can be performed at various intervals: after a minute, an hour, a day, a week, a month, or a year, depending on how much detail the process should be analyzed. In time series analysis problems, we deal with discrete-time, when each observation of a parameter forms a time frame. The same can be said about the behavior of Covid-19 over time.In this paper, we solve the problem of predicting Covid-19 diseases in the world using neural networks. This approach is useful when it is necessary to overcome difficulties related to non-stationarity, incompleteness, unknown distribution of data, or when statistical methods are not completely satisfactory. The problem of forecasting is solved with the help of the analytical platform Deductor Studio, developed by specialists of the company Intersoft Lab of the Russian Federation. When solving this problem, appropriate methods were used to clean the data from noise and anomalies, which ensured the quality of building a predictive model and obtaining forecast values for tens of days ahead. The principle of time series forecasting was also demonstrated: import, seasonal detection, cleaning, smoothing, building a predictive model, and predicting Covid-19 diseases in the world using neural technologies for 30 days ahead.
Industrial fabrication technology for CMOS infrared sensor arrays

We report a new technology for the industrial fabrication of CMOS infrared sensor arrays on suspended membranes. Gold lines made with the bumping technology of the IC manufacturer are used to thermally separate the sensor pixels. Further, the buckling problem of CMOS dielectric membranes was solved by finding an oxynitride passivation suitable for the fabrication of low-stress membranes. Finally, the influence of bulk crystal defects on the lateral back mask underetching was studied.
Screening for the Strain Galactomyces sp. Producing Bioflocculant by UV Mutagenesis

Strain Galactomyces sp. M-2 from activated sludge was used as parent strain and then UV mutation breeding was performed. Finally we obtained a quality strain UVM8 suitable for the production of bioflocculant which flocculating activity is 92.8%. It showed there is excellent stable flocculating activity for stain UVM8 in the flocculating stability experiment. Further studies showed the best flocculation effect was obtained when C/N ration is 20:2 and pH is 8 in the initial culture medium.
Motivational determinants of digital ticketing: the mediating effect of service satisfaction and the moderating effect of psychological discomfort

PurposeThe purpose of the study was (1) to examine the motivational composites determining consumers' continued intention to use digital ticketing via self-service technology (SST) by integrating service satisfaction and (2) to ascertain the differences between consumers according to their psychological discomfort toward technology.Design/methodology/approachData were collected using a structured questionnaire, and a total of 323 were included in the analysis. Partial least squares structural equation modeling (PLS-SEM) was utilized to test motivational determinants of digital ticketing. In addition, permutation-based multi-group analysis was performed to investigate the differences between consumers with high and low technology discomfort.FindingsBoth intrinsic and extrinsic motivation are positive predictors of continued intention to use digital ticketing, but only intrinsic motivation has a positive impact on continued intention through service satisfaction. Moreover, the relationship between intrinsic motivation, service satisfaction and continued intention was stronger for consumers with high psychological discomfort than those with low psychological discomfort.Originality/valueGiven the conspicuous characteristics of the digital ticketing process for sporting events, the insights gained from the study may be of assistance to researchers and practitioners in understanding sport consumers' ticket consumption behavior and the determinants of SST usage.
Energy Budgets From Collisionless Magnetic Reconnection Site to Reconnection Front

Collisionless magnetic reconnection occurs ubiquitously in space plasma environments and plays an important role in energy conversion therein. In collisionless magnetic reconnection, the reconnection site is usually unsteady and ejects reconnection fronts away from it. Using two‐dimensional particle‐in‐cell simulations, we study the energy budgets from the collisionless magnetic reconnection site to reconnection fronts. It is concluded that the reconnection rate cannot well reflect energy conversion of nonsteady state magnetic reconnection because energy conversion occurs predominantly at the reconnection fronts, whereas the reconnection rate can only represent the energy conversion at the reconnection site. We clarify the connection between the reconnection site and the reconnection fronts in terms of energy conversion. The reconnection site functions as a trigger and energy source that generates the outflow of Poynting flux, bulk kinetic energy flux, and enthalpy flux forming the reconnection fronts that move downstream. The well‐developed reconnection fronts are no longer related to the reconnection site. The energy income at the reconnection fronts is mainly the Poynting flux from their top and bottom boundaries, most of which is transformed to P¯⋅V flux flowing downstream out of the moving front through the work by the electric field. The work done by the electric force is compensated with the work done by the thermal pressure gradient, which guarantees that the released magnetic energy is mostly converted to thermal energy.
Millimeter-wave substrate integrated waveguide multibeam antenna based on the modified R-KR lens

In this paper, a new type of multibeam antenna based on the principle of modified R-KR lens and substrate integrated waveguide (SIW) technology was proposed. It consists of a SIW modified R-KR lens as the beam-forming network, a SIW longitudinal slot array antenna and a SIW phase shift network in between. A prototype with 15 input ports and a SIW slot array antenna was implemented at 30 GHz for generating 15 beams to cover the angle of (−59°, 59°) with 3dB beam width. The gains of the beams are distributed from 17.44dB to 20.2dB. This kind of multibeam antenna takes the advantages of low profile, low cost and high performance etc. and would be applied in the mobile satellite communication with beam switching and beam diversity technology.
Perancangan Online Market Place Makanan Tradisional Untuk Usaha Kecil dan Menengah di Surabaya

Perkembangan teknologi yang pesat di saat sekarang ini membawa konsekuensi terjadinya disrupsi, perubahan pola hidup dan perubahan gaya hidup menjadi efek yang dirasakan paling awal pada disrupsi, penggunaan teknologi menjadi syarat bagi sebuah bisnis untuk berkembang dan bertahan diantara ekosistem bisnis itu sendiri, dalam hal ini UKM menjadi sektor usaha yang rentan menghadapi era disrupsi, pembekalan dan penerapan teknologi bagi UKM menjadi syarat agar UKM dapat terus berkembang. Dalam hal pengembangan teknologi informasi ini maka perancangan mengambil objek pada Kampung Kue di Rungkut Penjaringan Kota Surabaya, Selama ini UKM di Kota Surabaya tersebut hanya dikenal melalui brosur maupun secara lisan kepada masyarakat. Hal ini dirasa kurang efektif karena membutuhkan waktu yang lama dan informasi yang didapat pun kurang lengkap. Oleh karena itu perancangan aplikasi online market place UKM Kampung Kue Rungkut Penjaringan sebagai media informasi, transaksi dan sebagai media yang mampu meningkatkan kredibilitas para pelaku usaha produksi makanan tradisional. Peranan aplikasi ini diharapkan menjadi bagian yang terintegrasi dengan branding Kampung Kue Rungkut Penjaringan, dimana salah satu branding yang dirancang adalah branding melalui media online, aplikasi Kampung kue diharapkan dapat menjadi pilihan konsumen jaman kini untuk mencari kebutuhannya.
Propagation and Bit Error Ratio Measurements for a Microcellular System

Propagation measurements are provided for highway and city centre microcells. Measurements along various motorways were taken with base station (BS) antennas at 10 m elevations. Pseudo-random binary sequences (PRBS) were transmitted via non-coherent FSK at 905 MHz. Low radiated power (16 mW into an 18-element Yagi) was used, and the signal level and bit error ratio (BER) were recorded by a mobile station (MS). The microcell length was found to be a function of the received field strength and, therefore, the BER. It was found that the cell lengths varied between 1 to 2 km for a BER of 10−3 or better. Although the PDF of the received signal was Rician the microcell length was determined using the more pessimistic Rayleigh PDF. Two and three microcell clusters were considered. An inverse fourth power law was observed, and the received signal power in the microcell varied linearly with radiated power. For power levels of only 1 μW, error free transmission was found to occur over a cell length of 400 m.Detailed measurements in the Harley Street area in Central London enabled us to study how signals propagate in a nearly rectilinear grid pattern of roads. A theoretical model was established that provided signal levels that were close to those measured. Experiments were performed with the base station at junctions, roundabouts and at major city arteries. The inverse fourth power loss characteristics occurred, and the radiation distribution was found to be relatively insensitive to antenna type as the street pattern was the dominant factor.
Development of Environmental-stress Tolerant Eucalyptus and Forest Plantations

紙・板紙の製造コストで最も大きな部分を占めるのは原料費である。 これまで原料費を低下させるために，安価な外材の調達を進める努力がなされてきたが，地球規模での環境問題が深刻化しつつあり，良質で安価な原料の安定確保は今後ますます重要な問題になってくると思われる。 このような状況の下，製紙各社はパルプの安定確保を目的に海外での産業植林を実施しており，植林面積は増加傾向にある。 また，さらなる植林木の生産性の改良のためには，ユーカリ新品種の開発が望まれている。 王子製紙では植林現場での実用性の高い選抜・交雑育種の実践に加えて，今後発展が期待できる遺伝子組換え技術を取り入れ，ユーカリを対象とする効率的な育種技術の開発を検討している。 これまで，ユーカリの組織培養技術である苗条原基法と早生分枝法を開発し，さらにこれらの技術を応用した遺伝子組換え技術を完成した。 現在，森林資源研究所ではパルプ品質と成長特性を遺伝子組換えによって改良する研究を行っている。 本発表では，植林環境における環境ストレスとして問題になっている乾燥や酸性土壌を研究対象として，ユーカリ交雑種（Eucalyptus grandis×urophylla）に乾燥ストレス耐性を与える効果が確認されている転写因子（DREB1A）遺伝子と酸性土壌耐性を付与する効果が確認されているクエン酸合成酵素遺伝子を導入した研究結果について紹介する。
Autonomous off-road navigation with end-to-end learning for the LAGR program

We describe a fully integrated real-time system for autonomous off-road navigation that uses end-to-end learning from onboard proprioceptive sensors, operator input, and stereo cameras to adapt to local terrain and extend terrain classification into the far field to avoid myopic behavior. The system consists of two learning algorithms: a short-range, geometry-based local terrain classifier that learns from very few proprioceptive examples and is robust in many off-road environments; and a long-range, image-based classifier that learns from geometry-based classification and continuously generalizes geometry to appearance, making it effective even in complex terrain and varying lighting conditions. In addition to presenting the learning algorithms, we describe the system architecture and results from the Learning Applied to Ground Robots (LAGR) program's field tests. © 2008 Wiley Periodicals, Inc.
The cooperative IGS RT-GIMs: a reliable estimation of the global ionospheric electron content distribution in real time

Abstract. The Real-Time Working Group (RTWG) of the International GNSS Service (IGS) is dedicated to providing high-quality data and high-accuracy products for Global Navigation Satellite System (GNSS) positioning, navigation, timing and Earth observations. As one part of real-time products, the IGS combined Real-Time Global Ionosphere Map (RT-GIM) has been generated by the real-time weighting of the RT-GIMs from IGS real-time ionosphere centers including the Chinese Academy of Sciences (CAS), Centre National d'Etudes Spatiales (CNES), Universitat Politècnica de Catalunya (UPC) and Wuhan University (WHU). The performance of global vertical total electron content (VTEC) representation in all of the RT-GIMs has been assessed by VTEC from Jason-3 altimeter for 3 months over oceans and dSTEC-GPS technique with 2 d observations over continental regions. According to the Jason-3 VTEC and dSTEC-GPS assessment, the real-time weighting technique is sensitive to the accuracy of RT-GIMs. Compared with the performance of post-processed rapid global ionosphere maps (GIMs) and IGS combined final GIM (igsg) during the testing period, the accuracy of UPC RT-GIM (after the improvement of the interpolation technique) and IGS combined RT-GIM (IRTG) is equivalent to the rapid GIMs and reaches around 2.7 and 3.0 TECU (TEC unit, 1016 el m−2) over oceans and continental regions, respectively. The accuracy of CAS RT-GIM and CNES RT-GIM is slightly worse than the rapid GIMs, while WHU RT-GIM requires a further upgrade to obtain similar performance. In addition, a strong response to the recent geomagnetic storms has been found in the global electron content (GEC) of IGS RT-GIMs (especially UPC RT-GIM and IGS combined RT-GIM). The IGS RT-GIMs turn out to be reliable sources of real-time global VTEC information and have great potential for real-time applications including range error correction for transionospheric radio signals, the monitoring of space weather, and detection of natural hazards on a global scale. All the IGS combined RT-GIMs generated and analyzed during the testing period are available at https://doi.org/10.5281/zenodo.5042622 (Liu et al., 2021b).