Miracle-dz/UniFAR-FTUs huggingface dataset:
IoT-Enabled Smart Agriculture: Architecture, Applications, and Challenges

The growth of the global population coupled with a decline in natural resources, farmland, and the increase in unpredictable environmental conditions leads to food security is becoming a major concern for all nations worldwide. These problems are motivators that are driving the agricultural industry to transition to smart agriculture with the application of the Internet of Things (IoT) and big data solutions to improve operational efficiency and productivity. The IoT integrates a series of existing state-of-the-art solutions and technologies, such as wireless sensor networks, cognitive radio ad hoc networks, cloud computing, big data, and end-user applications. This study presents a survey of IoT solutions and demonstrates how IoT can be integrated into the smart agriculture sector. To achieve this objective, we discuss the vision of IoT-enabled smart agriculture ecosystems by evaluating their architecture (IoT devices, communication technologies, big data storage, and processing), their applications, and research timeline. In addition, we discuss trends and opportunities of IoT applications for smart agriculture and also indicate the open issues and challenges of IoT application in smart agriculture. We hope that the findings of this study will constitute important guidelines in research and promotion of IoT solutions aiming to improve the productivity and quality of the agriculture sector as well as facilitating the transition towards a future sustainable environment with an agroecological approach.
Depression, Anxiety and Stress Among Dentists During COVID-19 Lockdown

The objective of this study was to investigate the levels of depression, anxiety, and stress among dentists during covid-19 lockdown and to investigate the relationship between stress and each mental health state. A cross-sectional survey on 269 dentists was conducted using DASS-21 and PHQ-9 questionnaires. Bivariate and multivariate models were constructed and the odds ratio (OR) was calculated to assess the strength of the association between an independent categorical variable and the outcome. Being unsatisfied with the job was associated with a statistically significant increase in DASS-21 score by an average of 5.9 points after adjusting for the possible confounding effect of the other independent variables included in the model. For each extra 10 years of clinical experience, there is a statistically significant reduction in DASS-21 score by an average of 1.3 points compared after adjusting for the possible confounding effect of the other independent variables included in the model. Stress, depression, and anxiety were prevalent during the pandemic among dentists. These psychological domains were modulated by several factors including marital status, gender, years of clinical experience, and degree of job satisfaction.
Comparison of different treatment methods on macro-micro characteristics of Yellow River silt solidified by MICP technology

Abstract The cementation of Yellow River silt into green and sustainable building materials through microbial induced calcium carbonate precipitation (MICP) is a novel technology with a wide range of applications. The MICP treatment of abandoned Yellow River silt was carried out by multiple-phase injection method and pre-mixing method in this paper. The effects of cementation solution concentration and treatment times on the chemical conversion efficiency were investigated, and the effectiveness of the two treatment methods in improving the mechanical properties of Yellow River silt was evaluated. The results showed that the chemical conversion efficiency of the pre-mixing method was about 5% higher than that of the multiple-phase injection method. With the increase of the cementation solution concentration and the treatment times, the unconfined compressive strength (UCS) of the samples treated by the pre-mixing method increased faster and the distribution of calcium carbonate (CaCO3) was more uniform. After ten treatments, the UCS of the samples treated by pre-mixing method exceeds 5 MPa with a relatively uniform CaCO3 content of 25%.
Design and Implementation of Portable Test System for UAV Based on Windows + RTX

Ground test system is an important part and parcel of UAS,and is mainly applied in the test of performance and technical analysis indicators of system and airborne equipment of UAS. We introduced a design and implementation of a test system based on a portable PXI bus computer. The test system was designed to satisfy users' requirements of being roboticized,portable and all-purpose. Application software of unit testing and integrated testing was compiled by Lab VIEW and ran on Windows OS. Simulation testing application software was designed and compiled by Simulink and Microsoft Visual Studio 2008 and ran on Windows + RTX OS.
Toward machine intelligence that learns to fingerprint polymorphic worms in IoT

Internet of Things (IoT) is fast growing. Non‐personal computer devices under the umbrella of IoT have been increasingly applied in various fields and will soon account for a significant share of total Internet traffic. However, the security and privacy of IoT and its devices have been challenged by malware, particularly polymorphic worms that rapidly self‐propagate once being launched and vary their appearance over each infection to escape from the detection of signature‐based intrusion detection systems. It is well recognized that polymorphic worms are one of the most intrusive threats to IoT security. To build an effective, strong defense for IoT networks against polymorphic worms, this study proposes a machine intelligent system, termed Gram‐Restricted Boltzmann Machine (Gram‐RBM), which automatically generates generic fingerprints/signatures for the polymorphic worm. Two augmented N‐gram‐based methods are designed and applied in the derivation of polymorphic worm sequences, also known as fingerprints/signatures. These derived sequences are then optimized using the Gaussian–Bernoulli RBM dimension‐reduction algorithm. The results, gained from the experiments involved three different types of polymorphic worms, show that the system generates accurate fingerprints/signatures even under “noisy” conditions and outperforms related methods in terms of accuracy and efficiency.
Fungal Infections of Implantation: More Than Five Years of Cases of Subcutaneous Fungal Infections Seen at the UK Mycology Reference Laboratory

Subcutaneous fungal infections, which typically result from traumatic introduction (implantation) of fungal elements into the skin or underlying tissues, can present as a range of different clinical entities including phaeohyphomycosis, chromoblastomycosis, subcutaneous nodules or masses, and genuine eumycetoma. Here, we mined our laboratory information management system for such infections in humans and domestic animals for the period 2016–2022, including (i) fungal isolates referred for identification and/or susceptibility testing; (ii) infections diagnosed at our laboratory using panfungal PCR approaches on infected tissue; and (iii) organisms cultured in our laboratory from biopsies. In total, 106 cases were retrieved, involving 39 fungal species comprising 26 distinct genera. Subcutaneous infections with Alternaria species were the most frequent (36 cases), which possibly reflects the ubiquitous nature of this common plant pathogen. A substantial proportion of Alternaria spp. isolates exhibited reduced in vitro susceptibility to voriconazole. Notably, a significant number of subcutaneous infections were diagnosed in renal and other solid organ transplant recipients post transplantation, suggesting that humans may harbour “inert” subcutaneous fungal elements from historical minor injuries that present as clinical infections upon later immunosuppression. The current study underscores the diversity of fungi that can cause subcutaneous infections. While most organisms catalogued here were responsible for occasional infections, several genera (Alternaria, Exophiala, Phaeoacremonuim, Scedosporium) were more frequently recovered in our searches, suggesting that they possess virulence factors that facilitate subcutaneous infections and/or inhabit natural niches that make them more likely to be traumatically inoculated.
Bee Products for Relieving Menopausal Symptoms

BACKGROUND: An overview of honey and other bee products and their health and biological health potentials was highlighted. AIM: The aim of the study was to help females alleviate their menopausal symptoms, when estrogen hormone levels decrease at the end of their fertility phase of life using natural bee products. SUBJECTS AND METHODS: Two groups of Egyptian women in the menopausal stage, suffering from different symptoms of menopause, participated as volunteers. Full clinical examination, Menopause Rating Scale, Beck anxiety score, and Beck depression score evaluations were recorded. Blood sampling and biochemical analysis were done including female sex hormones, and anti-inflammatory, and antioxidant markers. Participants consumed two tablespoon of the honey (32 ml) diluted in 250 ml of water once daily in the morning for 2 months. Control group received conventional clover honey while the other group consumed a calculated ratio of clover honey enriched with bee pollen, royal jelly, and bee gum. RESULTS: Subjects with a mean age of 49.51 ± 0.82 years who consumed enriched clover honey had significant improvement in somatic, psychological, urogenital, and anxiety score assessment and depression score evaluation. Data from this study group showed that the women experienced the disappearance of hot flushes, night sweats, generalized body pain, and psychological symptoms such as irritability, anxiety, depression, and disturbed sleeping. As for biochemical parameters, estradiol, free testosterone, the antioxidant marker malondialdehyde (MDA), and the anti-inflammatory marker interleukin-6 (IL-6) significantly improved at the end of the study. While the control group had mean age of 48.24 ± 0.74 years, they experienced significant improvement of the somatic subscale, depression score, and MDA, and there was no significant effect on urogenital symptoms, anxiety score, IL-6, or any of the female sex hormones. CONCLUSION: Adding Bee pollen, propolis, and royal jelly to the clover honey are more effective in slowing down menopausal symptoms.
Industrial Insert Robotic Assembly Based on Model-based Meta-Reinforcement Learning

The high-rigidity working environment in the industrial insert robotic assembly is likely to cause damage to the robot and parts, so it is difficult to use traditional position control methods under these circumstances. The combination of compliance control and reinforcement learning brings new ideas to this problem. In this paper, a robotic industrial insertion learning method based on model-based meta-reinforcement learning is proposed. By interacting with the environment and updating the dynamic model in real-time, the online adaptation of assembly tasks is realized. A simulation environment is used to train a neural network dynamics model, with a model-based reinforcement learning method. Finally, we compare our method with other methods in the real environment to verify the effectiveness of the algorithm.
Flexible Offloading of Service Function Chains to Programmable Switches

A Service Function Chain (SFC) is an ordered sequence of network functions (NFs). Though cost-effective, software-based NFs could introduce a significant performance penalty. In this paper, we present P4SFC, a high-performance and flexible SFC system that leverages the capability of emerging programmable switches. We seek to accelerate packet processing in SFC by offloading proper NFs to P4-capable switches. First, considering the current limitations of P4, we analyze the offloadability of NFs at different granularities in detail, and enable P4SFC to generate offloading strategies for both partially and fully offloadable SFCs. Second, to deploy new SFCs at runtime, we design a dynamic P4 data plane, of which the execution logic can be reconfigured at runtime without interrupting the existed execution logic. Third, to efficiently utilize the limited memory in programmable switches, we propose a state allocator to dynamically offload those NF states that bring the highest performance profits according to the recent flow distribution. We demonstrate the feasibility and practicality of P4SFC with our implementation on a commodity Tofino-based programmable switch. Experimental results show that P4SFC achieves significant performance improvement for real SFC implementations.
Effect of Recycled Aggregate Content on Water Permeability and Pore Structure of Pervious Concrete Pavement

The shortage of natural aggregate (NA) and a large amount of construction waste generation bring opportunities for the application of recycled aggregate (RA). To investigate the mechanical properties and permeability of Recycled Aggregate Pervious Concrete (RAPC), this study tested the compressive strength, tensile strength, flexural strength, porosity, permeability coefficient, and water retention of RAPC with different RA contents (0, 25%, 50%, 75%, and 100%) and analyzed the changes of these parameters with RA content. Among them, two methods were used for the calculation of porosity. The results showed that the porosity, permeability, and water retention of RAPC increased with the increase in RA content, but the compressive strength, splitting tensile strength, flexural strength, and uniaxial tensile strength decreased. According to the demand of pavement engineering, RAPC should have good water permeability while meeting the strength requirements, so the optimal RA content is 50%.
FOG temperature model-building and compensation based on Markov Chain

Temperature is one of the most important reasons that affect the FOG accuracy since the FOG components are sensitive to temperature. In order to eliminate temperature effect and improve precision, temperature modeling method is generally adopt. Based on the studying of the Markov process of stochastic process, we deduced the relationship between the first controlled Markov Chain and the difference equation in SISO system, and based on this, we established FOG temperature model. We utilized time homogeneous transition probability to identify the model and used Monte Carlo method to simulate the compensated output of FOG. Compared with the uncompensated output, we can see that the model based on the first controlled Markov Chain has good prediction effect and application prospect, and has significance to the engineering realization of FOG temperature compensation.
Analysis on skills and tactics of serve and return of service of Chinese badminton men doubles and foreign ones

AbstrcatServe,return of service and third receive of some athletes of men doubles were comparatively (analyzed) with the methods of literature study,video statistics,mathematic statistics and expert interview. The results showed that foreign athletes' line of serve and return of service were flexible and the third (receive) were in superior position.
Mycotoxins in Maize Silage from China in 2019

Animal feed (including forage and silage) can be contaminated with mycotoxins. Here, 200 maize silage samples from around China were collected in 2019 and analyzed for regulated mycotoxins, masked mycotoxins (deoxynivalenol, 3-acetyldeoxynivalenol, 15-acetyldeoxynivalenol, and deoxynivalenol-3-glucoside), and emerging mycotoxins (beauvericin, enniatins, moniliformin, and alternariol). Deoxynivalenol and zearalenone were detected in 99.5% and 79.5% of the samples, respectively. Other regulated mycotoxins were detected in fewer samples. The highest deoxynivalenol and zearalenone concentrations were 3600 and 830 μg/kg, respectively. The most commonly detected masked mycotoxin was 15-acetyldeoxynivalenol, which was detected in 68.5% of the samples and had median and maximum concentrations of 61.3 and 410 μg/kg, respectively. The emerging mycotoxins beauvericin, alternariol, enniatin A, enniatin B1, and moniliformin were detected in 99.5%, 85%, 80.5%, 72.5%, and 44.5%, respectively, of the samples but at low concentrations (medians <25 μg/kg). The samples tended to contain multiple mycotoxins, e.g., the correlation coefficients for the relationships between the concentrations of beauvericin and deoxynivalenol, deoxynivalenol and zearalenone, and zearalenone and beauvericin were 1.0, 0.995, and 0.995, respectively. The results indicated that there needs to be more awareness of the presence of one or more masked and emerging mycotoxins in maize silage in China.
How versatility performance influences perception of charismatic speech

The concept of vocal charisma has changed in the past decades from something that people have to something that people do, thereby stimulating research on how vocal charisma can be created and improved. Broadening the perspective on vocal charisma beyond the speaker’s performance itself to the context of the speech, we conducted acoustic-prosodic analyses of public speeches of two prominent Israelian politicians – Benjamin Netanyahu and Benny Gantz. The speech material consisted of 311–516 prosodic phrases per politician from the election campaigns 2019–2020 and, crucially, was balanced so as to include an equal number of pre- and post-election speeches. Results show a superiority of Netanyahu over Gantz in almost all facets of vocal charisma, although Gantz caught up over time. Moreover, unlike Gantz, Netanyahu showed a strong adaptation of his vocal charisma patterns to before- and after-election contexts. Scrutinizing this versatility difference, an additional perception experiment with 42 listeners and excerpts from the two politicians’ speeches was carried out. Results show that Netanyahu’s speech excerpts were, unlike those of Gantz, mainly rated as more charismatic in those contexts in which they were performed. Gantz’ post-election speech excerpts, by contrast, were primarily rated as not fitting into that context, i.e., as unfolding their charisma better in a pre-election context. Moreover, listeners also rated Netanyahu as overall more charismatic than Gantz. The combined production and perception evidence suggests the relevance of context in the evaluation and interpretation of vocal charisma signals.
Degree and Scope of the Fulfillment of Needs as Indicators of Living Standard and Life Quality

Abstract The aim of the paper was to review and analyze the theory and definition of human needs, as well as the direction of work on the selection of a set of indicators characterizing the standard of living and the quality of live of the population. The study used the method of back-up data analysis (desk research). The descriptive method and the technique of examining documents and describing their content were also applied. The basic empirical material was statistical data, mainly the results of household budget surveys. The study period was 2010–2020. The study indicated that work on sets of indicators characterizing the standard of living and the quality of life, their modification and improvement depending on the changing socio-economic situation are necessary for an effective cohesion policy. There is still no single universal definition of the concept and method of measuring the standard of living and the quality of life due to difficulties in defining indicators and variables. A set of indicators was also developed by Statistics Poland. It is an open set, which can be modified and improved depending on the changing socio-economic situation. The domains which were taken into account refer to the solutions adopted within the European Statistical System, however, they are not identical. Recently, research on the standard of living and the quality of life lays greater emphasis on subjective rather than objective indicators. The standard of living and the quality of life of the population should be monitored regularly, as this will help to adopt the sets of indicators comparable at different territorial levels.
A Testing Framework for Assessing Grid and Cloud Infrastructure Interoperability

The composition of grid and cloud computing infrastructures using equipment from different vendors to allow service enrichment and increase productivity is an important need in industry and for governmental institutions. Interoperability between equipment can be achieved using the gateway approach or the standardized interface approach. These approaches, as well as equipment need to be engineered and developed with the goal to allow problem-free interop- erations between involved equipment. A step towards such interoperation is the assessment of interoperability. Focusing on technical interoperability, we present a testing framework for the assessment of interoperability of grid and cloud computing infrastructures. This also includes the assessment of application deployment onto several infrastructures provided by different vendors, which is a key driver for market success. This testing framework is part of an initiative for standardizing the use of grid and cloud technology in the context of telecommunication at the European Telecommunications Standards Institute (ETSI). Following the test development process developed and used at ETSI, we developed a test architecture, test configura- tions, compliance levels, test purposes, interoperability test descriptions, test applications, and a test selection method that together build the testing framework. Its application is exemplified by the assessment of resource reservation and application deployment onto grid and cloud infrastructures based on standardized Grid Component Model descriptors. The presented testing framework has been applied successfully in an interoperability event. In this article, we present a testing framework for the assessment of the interoperability of grid and cloud infrastructure. Keywords-standardization; interoperability; GCM; grid; cloud; testing
Aerodynamic Force Control for Tilt-Wing eVTOL Using Airflow Vector Estimation

Research and development are active in electric vertical takeoff and landing (eVTOL) aircraft. In particular, tilt-wing eVTOL aircraft receives much attention as one of the most efficient configurations; however, they are likely to be unstable during the transition from hover to cruise because the lift and thrust have limitations depending on the airflow and tilt angle. This study proposes a new aerodynamic force control method using airflow vector estimation. The airflow vector is estimated by combining motor current, rotational speed, and Pitot-tube measurements. Aerodynamic force control is achieved through the proper design of a feedback controller using disturbance observers (DOBs) to cope with propeller-wing interference caused by the propeller slipstream. This method takes advantage of the motor control performance and is unique in which it monitors the airflow vector and actively changes the tilt angle to quickly obtain the desired acceleration. The effectiveness of the method is verified via simulations and experiments in a wind tunnel.