Miracle-dz/UniFAR-FTUs huggingface dataset:
GridTest: testing and metrics collection for Python

Creating reproducible testing and parameterization is a consistent challenge in research because it is hard to do (Koteska, Pejov, & Mishev, 2015). Researchers often don’t have the bandwidth to think about tests, and consequently, creating tools for this use case is often overlooked. GridTest (“GridTest on GitHub,” 2020) is a library that specializes in generating parameter grids. The grids are most obviously used for testing, but can extend to other use cases. In the context of testing, GridTest makes it easy to discover functions, classes, and arguments for Python scripts or modules, and then generate a template to easily populate. Outside of testing, grids can be created that are version controlled, programatically defined with functions, and easy to interact with from the command line or Python interpreter. Grids can be used with tests that can further be parameterized and configured to collect metrics for each case run. Both grid and test specifications are stored in a simple YAML configuration that the library helps to generate, and features include interactive debugging, interactive report generation, and provided metrics (Python decorators) that can assist with research.
Changes in Leaf Length, Width, Area, and Photosynthesis of Fruit Cucumber in a Greenhouse Production System

Changes in leaf length, width, area, weight, chlorophyll and carotenoids contents, and photosynthetic variables with different leaf positions were investigated in fruit cucumber. Plants were grown on rockwool slabs in an environmentally controlled greenhouse and irrigated by drip fertigation. Leaf measurements were conducted from the first to the 15th leaf (the oldest to the youngest). The results showed that fresh weight per unit leaf area decreased from the second to the 15th leaf. Changes in cucumber leaf length, width, and area followed quadratic models from the first to the 15th leaf. The quadratic models of leaf length, width, and area fit the measurements well, with R2 values of 0.925, 0.951, and 0.955, respectively. The leaf chlorophyll a and b and carotenoid contents increased from the oldest leaf (first leaf) to the youngest leaf and decreased after reaching the highest values. Changes in the net photosynthetic rate (Pn) also followed the quadratic model from the first to the 15th leaf, with R2 values of 0.975. The leaf transpiration rate (Tr) increased from the first to the 14th leaf. Our results revealed patterns in leaf growth and photosynthetic changes at different leaf positions in fruit cucumber and improved our understanding of the growth and development of fruit cucumber in the greenhouse production system.
RFAU: A Database for Facial Action Unit Analysis in Real Classrooms

Emotion analysis of students plays an important role in teaching effect evaluation. To develop robust algorithms for emotion analysis of students, a database from real classrooms is required. However, most existing databases were collected from adults and constructed in laboratory settings. In this article, we present a manually-annotated facial action unit database from juveniles in real classrooms. Our database has three main characteristics: (1) it provides numerous education-related action units data from primary and high schools, complementing the vacancy of the publicly available educational action unit databases; (2) it contains 256,220 manually-annotated facial images of 1,796 juveniles, frame-by-frame annotated with 12 action units and 6-level intensities for each action unit; (3) it covers many challenges in the wild, including various head poses, low facial resolution, illuminations, and occlusions, supplementing action unit databases in the wild for research. The baselines for action unit detection and action unit intensity estimation are provided for future references. Especially, we apply the weighted balance loss to solve imbalances within and between labels. Our database will be available to the research community: http://www.dlc. sjtu.edu. cn/rfau.
A brief analysis of gesture recognition in VR

With the rapid development of artificial intelligence technology, human‐computer interaction, as the core of virtual reality system, has become an increasingly important part of modern science and technology products. At present, human‐computer interaction is mainly based on contact, which must be completed through direct contact between hand and receiving equipment, rather than through indirect contact between hand and equipment. Direct interaction can not give full play to the advantages of flexible human hand, so gesture recognition becomes extremely important in interaction.
A Compact Circular Polarized Slot Antenna for Broadband Applications

A compact simple broadband circular V-shaped slot antenna microstrip antenna is proposed for circular polarization (CP). The Circular polarized patch consist Z type feed line on top of substrate and two right angle V shaped slotted cut on ground plane which is shown in backside of substrate. The multi response is achieved by using stub element in feed line Using stub element The broad CP and impedance bandwidths overlap by the symmetrically etched right angled V-shaped closed slot along the center line and the Z shaped feed line placed in a proper position. The proposed wideband CP antenna exhibits a much wider impedance bandwidth (1.61-4.85 GHz) of about 135.5% (S11 < −10 dB). The broadband CP antenna offers good gain over the entire frequency band of operation for Wireless applications. The proposed antenna possesses a high gain of 5.4 dB with the overall size is 44mm*50*1.6mm2. Proposed CP Broadband antenna covering UMTS, PCS, 2G,3G, WLAN, LTE, and WiMAX band applications.
Research on the technology of terrain classification and change detection based on deep learning

With the rapid development of urbanization in China, the change of land property is very rapid. The detection of land change is helpful to the government’s supervision and the development and protection of land resources. The traditional methods of land feature classification and change detection of remote sensing image generally adopt the methods of manual annotation and recognition. Due to the performance defects, they can not meet the requirements of remote sensing image business application. In this paper, the technology of satellite remote sensing image feature classification and change detection based on deep learning is proposed, and several demonstration cases of automatic classification and change detection system of buildings, roads, water bodies, forest land and other features based on high-resolution remote sensing image are formed. Relevant research results show that the technology can meet the requirements of remote sensing image classification and change detection, and the accuracy of the review is more than 90%. The method adopted can effectively solve the application needs of related fields.
Karakteristik Tepung Ampas Tahu yang Difermentasi dengan Lactobacillus plantarum terhadap kandungan Daidzein, Glycitein, dan Genistein

Animal feed should ideally be inexpensive and not competing with humans. Ampas know is a waste of the manufacture of tofu that contains protein and high energy. Its use has problems due to the existence of antinutrient and cannot be kept long. Lactobacillus Plantarum is a lactic acid (Gram-positive) bacteria used in the fermentation process to improve the quality of feed. The goal of fermentation is to remove the anti-nutrients that exist in the tofu pulp and increase the content of Isoflavone (Daidzin, Glycitein, and Genistein) and Isoflavone is a source of antioxidants important to growth. The study uses a Completely Randomized Design with 5 treatment of microbial culture concentrations of 1%, 5%, 10%, 15%, and 20% (V/w), respectively repeated 3 times. The result of analyzes in the pulp of tofu fermentation suggests that fermentation by Lactobacillus Plantarum can increase the content of Daidzein, Glycitein, and genistein with the highest value resulting from the use of L. Plantarum 20% respectively 191.21 + 24.9 μg/g, 85.96 μg/g, and 120.82 μg/g. It can be concluded that the higher the use of the concentration of L. Plantarum in tofu pulp can increase the levels of isoflavone, so it is advisable to conduct research with the concentration of L. Plantarum higher in tofu pulp
The role of autogenic halide gas in the production of metal borides

Synthesis of metal borides is typically undertaken at high temperature using direct combinations of elemental starting materials[1]. Techniques include carbothermal reduction using elemental carbon, metals, metal oxides and B2O3[2] or reaction between metal chlorides and boron sources[3]. These reactions generally require temperatures greater than 1200oC and are not readily suitable for an industrial setting nor scalable to bulk production.
Evaluation of SPAD meter values for estimating rice nitrogen status

A field experiment with six rice genotypes were conducted to relate SPAD chlorophyll meter readings to variables reflecting nitrogen (N) status at different developmental stages. These indices can be used to predict foliar N concentration in rice without significant interferences of rice genotypes and growth stages. Dependence of nitrogen content from mineral element in the soil was established at the same time. Investigations were guided on six fertilization variants (N1: 0; N2: 40; N3: 60; N4: 80; N5: 100; N6:150 kg N ha). The results indicated that nitrogen content influenced from presence and ratio mineral elements in the soil. SPAD value increased with increase in N level and growth stages upto FL stage. However no clear trend is observed among cultivars, since ratio of SPAD readings to predict rice N status is not influenced by rice genotypes and is based on the principle of N translocation from old to young leaves when the plant is nitrogen deficient.
Impact of Contact Scaling and Drag Calculation on the Accuracy of Coarse‐Grained Discrete Element Method

The accuracy of coarse-grained discrete element method (CGDEM) relies on appropriate scaling rules for contact and fluid-particle interaction forces. For fluidized bed applications, different scaling rules are used and compared with DEM results. The results indicated that in terms of averaged values as mean particle position and voidage profile, the coupling of computational fluid dynamics and CGDEM leads to accurate results for low scaling factors. Regarding the particle dynamics, the approach leads to an underestimation of RMS values of particle position indicating a loss of particle dynamics in the system due to coarse graining. The impact of cell cluster size on drag force calculation is studied. The use of energy minimization multiscale drag correction is investigated, and a reduced mesh dependency and good accuracy are observed.
Selective adsorption for removal of nitrogen compounds from hydrocarbon streams over carbon-based adsorbents

In order to explore the adsorptive denitrogenation of liquid hydrocarbon streams for producing ultraclean fuels, the adsorption performance of seven representative activated carbon samples and three activated alumina samples was evaluated in a batch adsorption system and a fixed-bed flow adsorption system for removing quinoline and indole from a model diesel fuel in the coexistence of sulfur compounds and aromatics. Different adsorbents show quite different selectivity toward basic and nonbasic nitrogen compounds (quinoline and indole) and sulfur compounds (dibenzothiophene and 4,6dimethyldibenzothiophene). The activated carbons generally show higher capacity than activated alumina samples for removing the nitrogen compounds. The adsorption capacity and selectivity of the activated carbons for nitrogen compounds were further correlated with their textural properties and oxygen content. It was found that (1) the microporous surface area and micropore volume are not a key factor for removal of the nitrogen compounds in the tested activated carbons; (2) the oxygen functionality of the activated carbons may play a more important role in determining the adsorption capacity for the nitrogen compounds since the adsorption capacity for nitrogen compounds increases with increase in the oxygen concentration of the activated carbons; and (3) the type of the oxygen-functional groups may be crucial in determining their selectivity for 40 various nitrogen or sulfur compounds. In addition, regeneration of the saturated adsorbents was conducted by the toluene washing followed by the heating to remove the remained toluene. The results show that the spent activated carbons can be regenerated to completely recover the adsorption capacity. The high capacity and selectivity of carbonbased adsorbents for the nitrogen compounds, along with their good regenerability, indicate that the activated carbons may be promising adsorbents for deep denitrogenation of liquid hydrocarbon streams.
Low-Load Resistance Training to Volitional Failure Induces Muscle Hypertrophy Similar to Volume-Matched, Velocity Fatigue

Supplemental Digital Content is Available in the Text. Abstract Terada, K, Kikuchi, N, Burt, D, Voisin, S, and Nakazato, K. Full title: Low-load resistance training to volitional failure induces muscle hypertrophy similar to volume-matched, velocity fatigue. J Strength Cond Res 36(6): 1576–1581, 2022—We investigated how resistance training (RT) to failure at low load affects acute responses and chronic muscle adaptations compared with low-load RT to velocity fatigue at equal work volume. Twenty-seven subjects performed 8 weeks of bench press twice weekly. Subjects were randomly assigned to one of 3 groups: low-load volitional failure (LVoF, n = 9), low-load velocity fatigue (LVeF, n = 8), and high-load (HL, n = 10). Resistance training comprised 3 sets to failure at 40% one repetition maximum (1RM) in the LVoF group, 3 sets to velocity fatigue (20% lifting velocity loss) at 40% 1RM in the LVeF group, and 3 sets of 8 repetitions at 80% 1RM in the HL group. We measured muscle strength, hypertrophy, endurance, and power at baseline and after the RT program. We also measured muscle swelling and blood lactate after each RT bout to investigate the acute response. There were no differences in total work volume between the LVoF and LVeF groups. Responses to RT were similar between LVoF and LVeF, whether looking at acute muscle swelling, increase in blood lactate, chronic hypertrophy, and strength gain. However, LVoF and LVeF RT triggered different responses to muscle function in comparison with HL training: LVoF and LVeF showed enhanced acute responses and greater chronic endurance gains, but lower chronic strength gains than HL. In conclusion, low-load RT to volitional failure induces muscle hypertrophy similar to volume-matched velocity fatigue.
A Low-Cost Method of Improving the GNSS/SINS Integrated Navigation System Using Multiple Receivers

GNSS (global navigation satellite system) and SINS (strap-down inertial navigation system) integrated navigation systems have been the apparatus for providing reliable and stable position and velocity information (PV). Commonly, there are two solutions to improve the GNSS/SINS integration navigation system accuracy, i.e., employing GNSS with higher position accuracy in the integration system or utilizing the high-grade inertial measurement unit (IMU) to construct the integration system. However, technologies such as RTK (real-time kinematic) and PPP (precise point positioning) that improve GNSS positioning accuracy have higher costs and they cannot work under high dynamic environments. Also, an IMU with high accuracy will lead to a higher cost and larger volume, therefore, a low-cost method to enhance the GNSS/SINS integration accuracy is of great significance. In this paper, multiple receivers based on the GNSS/SINS integrated navigation system are proposed with the aim of providing more precise PV information. Since the chip-scale receivers are cheap, the deployment of multiple receivers in the GNSS/SINS integration will not significantly increase the cost. In addition, two different filtering methods with central and cascaded structure are employed to process the multiple receivers and SINS integration. In the centralized integration filter method, measurements from multiple receivers are directly processed to estimate the SINS errors state vectors. However, the computation load increases heavily due to the rising dimension of the measurement vector. Therefore, a cascaded integration filter structure is also employed to distribute the processing of the multiple receiver and SINS integration. In the cascaded processing method, each receiver is regarded as an individual “sensor”, and a standard federated Kalman filter (FKF) is implemented to obtain an optimal estimation of the navigation solutions. In this paper, a simulation and a field tests are carried out to assess the influence of the number of receivers on the PV accuracy. A detailed analysis of these position and velocity results is presented and the improvements in the PV accuracy demonstrate the effectiveness of the proposed method.
Teachers’ experiences and understanding of executive functions in Irish primary school classrooms: Findings from a mixed-methods questionnaire

Executive functioning (EF) skills are crucial for young students to meet academic and social demands at school. EF skill development is particularly amenable to environmental influences in the early years. In classroom settings, teachers play a vital role in providing support to promote these skills. Research is limited regarding teachers’ understanding of EF domains and recognition of EF difficulties in students. Additionally, teachers’ experiences with managing neuropsychological reports that involve EF supports and interventions are unexamined. To assess levels of understanding and explore teachers’ experiences with EF and neuropsychological reports, an online questionnaire incorporating closed- and open-ended questions was developed. 106 primary school teachers in Ireland completed the questionnaire. Knowledge gaps for neuropsychological terminologies associated with EF were identified. Teachers recognised their role in supporting the promotion of executive skills, but issues with neuropsychological reports and resource limitations may restrict effective implementation of individualised supports and classroom-based interventions.
Thermophysical Properties of Matter - the TPRC Data Series. Volume 11. Viscosity

Abstract : The TPRC Data Series published in 13 volumes plus a Master Index volume constitutes a permanent and valuable contribution to science and technology. This 17,000 page Data Series should form a necessary acquisition to all scientific and technological libraries and laboratories. These volumes contain an enormous amount of data and information for thermophysical properties on more than 5,000 different materials of interest to researchers in government laboratories and the defense industrial establishment. Volume 11 in this 14 volume TPRC Data Series presents data and information on the viscosity of fluids and fluid mixtures, covering 12 elements (plus one isotope of hydrogen), 10 inorganic compounds, 36 organic compounds, 99 binary systems of fluid mixtures, eight ternary systems, three quarternary systems, and 19 multicomponent systems. In addition to the experimental data, recommended reference viscosity values are presented for the pure fluids, for saturated liquid, saturated vapor, and gaseous states. The fluid mixtures graphically smoother values are given as well.
Intrabronchial stents in heterogenous emphysema: a highly selected material followed 5 years

Background Endobronchial lung volume reduction (EBVR) with one-way valves introduced into the most diseased lobe of the lung is a non-invasive method to improve lung function in patients with severe heterogenous emphysema. The problem is to select the right patients for the procedure. Furthermore, the long-term effects have not been reported in most studies. Methods EBVR was performed in 35 patients with severely handicapping emphysema and with one radiologically clearly enlarged (at least 125%) target lung lobe and clearly visible and complete interlobar fissures on CT. Most of the successful survivors have then been followed for five years. Results Five (14%) were primary failures (defined as less than 15% increase of FEV1sec) and 10 (28%) were secondary failures (the valves were coughed up or removed for some reason). In the 21 successful l patients, the improvement of FEV1sec was in the mean 59%. Over the years, FEV1sec gradually decreased but was still higher 5 years later than initially. Of the successful group, 76% were still alive after 5 years, while only 50% were in the refused or failed groups. Conclusions With careful selection of patients remarkably good results in lung function can be achieved, and these improvements will last for years though slowly decrease. In addition, the results indicate an improvement in survival with successful EBVR procedure.
Neural Network-Based Voting System with High Capacity and Low Computation for Intrusion Detection in SIEM/IDS Systems

Integrating intelligence into intrusion detection tools has received much attention in the last years. The goal is to improve the detection capability within SIEM and IDS systems in order to cope with the increasing number of attacks using sophisticated and complex methods to infiltrate systems. Current SIEM and IDS systems have many processes involved, which work together to collect, analyze, detect, and send notification of failures in real time. Event normalization, for example, requires significant processing power to handle network events. So, adding heavy deep learning models will invoke additional resources for the SIEM or IDS tool. This paper presents a majority system based on reliability approach that combines simple feedforward neural networks, as weak learners, and produces high detection capability with low computation resources. The experimental results show that the model is very suitable for modeling a classification model with high accuracy and that its performance is superior to that of complex resource-intensive deep learning models.
INSTRUCTORS AND STUDENTS ON THE SAME PAGE: USABILITY OF INSTRUCTOR LOADED RESOURCES IN LMS SITES

Usability or ‘ease of use’ is a significant determinant of the user’s experience of an interactive system. The vast majority of university students worldwide use learning management systems (LMS) to access and interact with the course materials which instructors have loaded into the LMS. Students’ experience of their courses colors their experience of program and even of the institution. Providing a positive student experience is important to learning outcomes and to institutional competitiveness. Usability of learning resources also influences student motivation, engagement and learning. Ensuring usability of an LMS course built by instructors is important. However, a review of literature shows that the usability of instructor loaded resources in LMS is under-explored. The authors undertake a preliminary investigation of the usability of LMS instructor loaded resources. Adopting Jakob Nielsen’s ideas of mental models in usability, the authors conducted semi-structured interviews with five teaching academics and four students. The results show some mismatches between student and instructor mental models, reveal some students’ expectations of course sites, justify the need for participatory approaches to LMS course design, and provide impetus for further studies.