Miracle-dz/UniFAR-FTUs huggingface dataset:
Cumulative effects of Lithovit-standard, monopotassium-phosphate and acetyl salicylic acid applied at different growth stage of tomato salt-stressed plants

Abstract In the current study, different combinations of three products (Lithovit-Standard: Litho, monopotassium-phosphate: MKP and acetyl salicylic acid: ASA) were tested on tomato plants irrigated with five saline solutions (2, 4, 6, 8, and 10 dS/m). The aim was to determine the possible complementary effects of these products applied separately and in different sequence at vegetative (11DAT: days after transplantation), flowering (25DAT) and fruit formation (39DAT). Control salt-stress plants were not subjected to product application. The data showed that the combination Asp-Litho-MKP improved total chlorophyll content and reduced the most cell electrolyte leakage compared to control. ASP-MKP-Litho treatment improved fruit number by an average of three to four fruits compared to control at all EC levels and maximized weight of individual fruits under EC 2, 4, and 10 dS/m. Yields in plants treated with ASP-MKP-Litho were higher by almost two to three folds than those of control plants. Plants treated by ASP-MKP-Litho had the highest contents of N, P, K, Ca, and Mg at all ECs. It was concluded that the three products had complementary effects on salt-stressed tomato crop if applied in combination.
Bacillus licheniformis Reshapes the Gut Microbiota to Alleviate the Subhealth

Subhealth is a condition between health and disease that has become a common public health risk. Therefore, it is necessary to find more scientific therapies that can alleviate the symptoms of subhealth effectively. The gut microbiota is closely associated with subhealth. As a mature probiotic preparation, Bacillus licheniformis (B. licheniformis) can regulate gut microbiota balance, which indicates that B. licheniformis has the potential in regulating subhealth. This study produced the subhealthy rats by using chronic stress for 4 weeks to simulate psychological stress, with excessive antibiotics for 1 week to simulate bad living habits. Then, they were treated for 4 weeks with B. licheniformis. The results showed that B. licheniformis could recover the gut microbiota balance that had been destroyed by subhealth. The serum corticosterone and the proinflammatory cytokine tumor necrosis factor-α decreased after being treated by B. licheniformis. B. licheniformis also reduced glutamic acid and norepinephrine levels while increasing γ-aminobutyric acid and 5-hydroxytryptamine levels in the brain. In addition to the physiological changes, B. licheniformis decreased the anxiety-like behaviors of rats. Therefore B. licheniformis could alleviate the subhealth state, mainly by remodeling the gut microbiota, reducing inflammation, inhibiting the hypothalamic–pituitary–adrenal axis hyperactivity, regulating neurotransmitter levels, and easing a negative mood.
Dynamic response improvement of hybrid system by implementing ANN-GA for fast variation of photovoltaic irradiation and FLC for wind turbine

In this paper, dynamic response improvement of the grid connected hybrid system comprising of the wind power generation system (WPGS) and the photovoltaic (PV) are investigated under some critical circumstances. In order to maximize the output of solar arrays, a maximum power point tracking (MPPT) technique is presented. In this paper, an intelligent control technique using the artificial neural network (ANN) and the genetic algorithm (GA) are proposed to control the MPPT for a PV system under varying irradiation and temperature conditions. The ANN-GA control method is compared with the perturb and observe (P&O), the incremental conductance (IC) and the fuzzy logic methods. In other words, the data is optimized by GA and then, these optimum values are used in ANN. The results are indicated the ANN-GA is better and more reliable method in comparison with the conventional algorithms. The allocation of a pitch angle strategy based on the fuzzy logic controller (FLC) and comparison with conventional PI controller in high rated wind speed areas are carried out. Moreover, the pitch angle based on FLC with the wind speed and active power as the inputs can have faster response that lead to smoother power curves, improving the dynamic performance of the wind turbine and prevent the mechanical fatigues of the generator.
Face Biometric Spoof Detection Method Using a Remote Photoplethysmography Signal

Spoofing attacks in face recognition systems are easy because faces are always exposed. Various remote photoplethysmography-based methods to detect face spoofing have been developed. However, they are vulnerable to replay attacks. In this study, we propose a remote photoplethysmography-based face recognition spoofing detection method that minimizes the susceptibility to certain database dependencies and high-quality replay attacks without additional devices. The proposed method has the following advantages. First, because only an RGB camera is used to detect spoofing attacks, the proposed method is highly usable in various mobile environments. Second, solutions are incorporated in the method to obviate new attack scenarios that have not been previously dealt with. In this study, we propose a remote photoplethysmography-based face recognition spoofing detection method that improves susceptibility to certain database dependencies and high-quality replay attack, which are the limitations of previous methods without additional devices. In the experiment, we also verified the cut-off attack scenario in the jaw and cheek area where the proposed method can be counter-attacked. By using the time series feature and the frequency feature of the remote photoplethysmography signal, it was confirmed that the accuracy of spoof detection was 99.7424%.
PERFORMANCE EVALUATION OF SDN CONTROLLERS: FLOODLIGHT AND OPENDAYLIGHT

Software Defined Network is new network architecture. One of its components is the controller, which is the intelligent part of SDN. Many controllers such as Floodlight, Open Daylight, Maestro, NOX, POX and many others are released. The question is which controller can perform better in which situations. Many works were done to compare controllers regarding architecture, efficiency and controllers’ features. In this paper, two of the most popular controllers, Floodlight and OpenDaylight are compared in terms of Network QoS parameters such as delay and loss in different topologies and network loads. This paper can help researchers to choose the best controller in different use cases such as clouds and multimedia. The results with 95% confidence interval show that OpenDaylight outperforms Floodlight in low loaded networks and also for tree topology in mid loaded networks in terms of latency. Floodlight can outperform OpenDaylight in heavy loaded networks for tree topology in terms of packet loss and in linear topology in terms of latency. There is no significant difference in performance of Floodlight and OpenDaylight controllers in other cases.
Optical Intelligent Reflecting Surface for Mixed Dual-Hop FSO and Beamforming-Based RF System in C-RAN

Optical intelligent reflecting surface (IRS) is an emerging and low-cost technology that can establish a stable communication route in free space optical (FSO) transmission environment with obstacles. In this work, optical IRS-aided dual-hop mixed FSO and RF system is first proposed for cloud radio access network (C-RAN). Specifically, polar codes are introduced to combat turbulence and building sway induced fading in FSO link, and transmit beamforming (TBF) technique is designed to achieve optimal data-rate for RF link. Supposing that the IRS-aided FSO link is subject to exponentiated Weibull distribution with geometric and misalignment loss, whereas the RF link experiences the Fisher-Snedecor $\mathcal {F}$ composite fading, the analytical closed-form outage probability expression is derived in terms of Meijer G and Lauricella multivariate hypergeometric functions with decode-and-forward strategy. Exact closed-form average bit error rate expressions are obtained when the relay of C-RAN adopts single antenna and multiantenna beamforming techniques. On the basis of moment generating function of end-to-end signal-to-noise ratio, the ergodic capacity is obtained in terms of univariate and multivariate Fox H-functions over independent but not identically distributed Fisher-Snedecor $\mathcal {F}$ fading channels. The correctness of the analytical results is verified through Monte-Carlo simulations. We further provide an asymptotic analysis and discuss the achievable diversity orders.
Vertebral Osteomyelitis and Infective Endocarditis Co-Infection

Many cases of vertebral osteomyelitis (VO) and infective endocarditis (IE) co-infection have been reported, and it has been recognized that attention should be paid to the possibility of both diseases co-existing during diagnosis and treatment. However, the incidence, clinical status, and outcomes of IE in patients with VO remain unclear. For this study, the eligibility criteria for patient recruitment included all cases of VO at the five medical university hospitals. Patients with a history of spinal surgery were excluded from this study. Echocardiography was routinely performed for all patients with VO. IE was diagnosed according to the modified Duke criteria for definite endocarditis. We analyzed demographic data, underlying conditions, clinical features, laboratory data, echocardiography, radiologic images, treatments, and outcomes. VO was diagnosed in 59 patients and IE was diagnosed in seven patients (12%). There were no significant differences in the clinical features, microorganisms, or radiographic status between the VO-IE co-infection and VO-only groups. In this study, using routine echocardiography for VO, the IE prevalence was 12%. The lack of specific clinical features and laboratory findings may hamper the diagnosis of IE. Therefore, clinicians are always required to suspect IE in patients with VO.
Work-Life Stress during the Coronavirus Pandemic among Latina Farmworkers in a Rural California Region

Objectives: To examine the type and severity of stressors experienced among Latina farmworkers during the COVID-19 pandemic. Methods: A survey containing the Migrant Farmworker Stress Inventory was administered to 77 female-identifying Latina farmworkers working in a US–Mexico border region. A sub-sample of five participants participated in key-informant interviews. Data collection occurred in Summer 2021. Results: Nearly 40% of Latina farmworkers reported high stress levels indicative of clinical mental health risks. Health and safety concerns and experienced stressors identified included visible substance abuse and poor bathroom conditions at the field site, language barriers, and balancing work and home life demands. Conclusions: Latina farmworkers have unique health and safety needs, and COVID-19 has contributed to the experienced stressors. Understanding the familial and working environment sources of stress specific to female agriculture workers is imperative to implementing culturally and gender-responsive strategies to better support the health and safety of farming populations in future pandemics.
Neuropsychological Outcomes in Adult Patients and Survivors of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is believed to affect central nervous system functions through various indirect, and possibly direct, mechanisms. We are only now beginning to understand the possible effects of the virus on human cognition. This review summarizes extant yet limited literature on clinical neuropsychological findings in adult coronavirus disease 2019 (COVID-19) patients and survivors. Neuropsychological outcomes were often in the form of cognitive screen results, although various studies administered comprehensive batteries. With respect to screens, the Montreal Cognitive Assessment appeared relatively sensitive to cognitive dysfunction associated with COVID-19. Patients and survivors presented with weaknesses on screens and comprehensive batteries, although the pattern of these weaknesses was not specific to etiology. Broadly, weaknesses were suggestive of executive dysfunction, although more than one study did not detect significant impairment. Weaknesses should be interpreted cautiously due to potential confounds/contributing factors (weaknesses may partly reflect psychiatric sequelae; weaknesses may be over-interpreted due to inadequate assessment of premorbid functioning). Studies reported different approaches in defining impairment, likely contributing to variable findings. The current review discusses ongoing efforts to harmonize approaches to evaluating neuropsychological functioning globally, as well as emphasizes taking a comprehensive approach towards understanding how the disease affects cognition.
A kaleidoscope of photosynthetic antenna proteins and their emerging roles

Abstract Photosynthetic light-harvesting antennae are pigment-binding proteins that perform one of the most fundamental tasks on Earth, capturing light and transferring energy that enables life in our biosphere. Adaptation to different light environments led to the evolution of an astonishing diversity of light-harvesting systems. At the same time, several strategies have been developed to optimize the light energy input into photosynthetic membranes in response to fluctuating conditions. The basic feature of these prompt responses is the dynamic nature of antenna complexes, whose function readily adapts to the light available. High-resolution microscopy and spectroscopic studies on membrane dynamics demonstrate the crosstalk between antennae and other thylakoid membrane components. With the increased understanding of light-harvesting mechanisms and their regulation, efforts are focusing on the development of sustainable processes for effective conversion of sunlight into functional bio-products. The major challenge in this approach lies in the application of fundamental discoveries in light-harvesting systems for the improvement of plant or algal photosynthesis. Here, we underline some of the latest fundamental discoveries on the molecular mechanisms and regulation of light harvesting that can potentially be exploited for the optimization of photosynthesis.
Efficiency of domestic wastewater solar disinfection in recatos with different colors

The aim of this study was to evaluate the efficiency of domestic wastewater solar disinfection for agriculture reuse in solar reactors with different colors: black, white and raw concrete. After passing through a septic tank, the wastewater was conducted to the reactors until the water depth reaches 10 cm and it was exposed to sunlight for three consecutive days. The disinfection efficiency was evaluated by the concentration of E. coli, chemical oxygen demand, effluent temperature, global radiation, UV radiation, pH and total suspended solids and the data was analyzed by regression analysis. The results show that the effluent in different reactors had distinct temperatures: the highest rates were observed in the black reactor and the smallest in the white, however these differences were slight (on average 2 oC) and the statistical analysis did not show a significant difference (p ≤ 0.05) between the efficiency in the reactors. The collected data allowed the development of a mathematical model that represents the remaining population of fecal coliforms in wastewater after being exposed to a certain dose of solar radiation. In conclusion, the reactor color does not alter the disinfection efficiency and the most important process variables are the UV-A radiation and total suspended solids concentrations.
Mixed methods study to understand the experiences of adults with acquired brain injury and their family members who receive specialised rehabilitation

Abstract Background and Aim: Rehabilitation therapy is a key part of the recovery pathway for people with severe acquired brain injury (ABI). The aim of this study was to explore inpatients’ and their family members’ experiences of a specialist ABI rehabilitation service. Methods: A cross sectional, prospective mixed method study was undertaken at a metropolitan specialist ABI rehabilitation unit in Victoria, Australia. All inpatients and their family members of the service were invited to complete a satisfaction survey. Employing purposive sampling, semi-structured interviews were conducted with inpatients and/or their family members. Results: In total, 111 people completed the satisfaction survey and 13 were interviewed. High levels of satisfaction with the specialist service were reported; the majority of inpatients (74%) and family members (81%) rated the overall quality of care received in the service as ‘high’ or ‘very high’. Interviews revealed four main themes: (i) satisfaction with rehabilitation services, (ii) inconsistent communication, (iii) variable nursing care, and (iv) strengths and weakness of the rehabilitation environment. Overall, important components of a positive experience were being involved in decision making and discharge planning, effective communication and information processes, and being able to form therapeutic relationships with staff. Key sources of dissatisfaction for inpatients and family members related to inconsistency in care, accessing information about treatments in a format easily understood, and communication. Conclusion: Specialised rehabilitation is valued by inpatients and their family members alike. The findings highlight the importance of exploring inpatient experiences to optimise service delivery in a tailored, specialised rehabilitation programme.
Minimizing Global Buffer Access in a Deep Learning Accelerator Using a Local Register File with a Rearranged Computational Sequence

We propose a method for minimizing global buffer access within a deep learning accelerator for convolution operations by maximizing the data reuse through a local register file, thereby substituting the local register file access for the power-hungry global buffer access. To fully exploit the merits of data reuse, this study proposes a rearrangement of the computational sequence in a deep learning accelerator. Once input data are read from the global buffer, repeatedly reading the same data is performed only through the local register file, saving significant power consumption. Furthermore, different from prior works that equip local register files in each computation unit, the proposed method enables sharing a local register file along the column of the 2D computation array, saving resources and controlling overhead. The proposed accelerator is implemented on an off-the-shelf field-programmable gate array to verify the functionality and resource utilization. Then, the performance improvement of the proposed method is demonstrated relative to popular deep learning accelerators. Our evaluation indicates that the proposed deep learning accelerator reduces the number of global-buffer accesses to nearly 86.8%, consequently saving up to 72.3% of the power consumption for the input data memory access with a minor increase in resource usage compared to a conventional deep learning accelerator.
Improved Cognitive Vigilance Assessment after Artifact Reduction with Wavelet Independent Component Analysis

Vigilance level assessment is of prime importance to avoid life-threatening human error. Critical working environments such as air traffic control, driving, or military surveillance require the operator to be alert the whole time. The electroencephalogram (EEG) is a very common modality that can be used in assessing vigilance. Unfortunately, EEG signals are prone to artifacts due to eye movement, muscle contraction, and electrical noise. Mitigating these artifacts is important for an accurate vigilance level assessment. Independent Component Analysis (ICA) is an effective method and has been extensively used in the suppression of EEG artifacts. However, in vigilance assessment applications, it was found to suffer from leakage of the cerebral activity into artifacts. In this work, we show that the wavelet ICA (wICA) method provides an alternative for artifact reduction, leading to improved vigilance level assessment results. We conducted an experiment in nine human subjects to induce two vigilance states, alert and vigilance decrement, while performing a Stroop Color–Word Test for approximately 45 min. We then compared the performance of the ICA and wICA preprocessing methods using five classifiers. Our classification results showed that in terms of features extraction, the wICA method outperformed the existing ICA method. In the delta, theta, and alpha bands, we obtained a mean classification accuracy of 84.66% using the ICA method, whereas the mean accuracy using the wICA methodwas 96.9%. However, no significant improvement was observed in the beta band. In addition, we compared the topographical map to show the changes in power spectral density across the brain regions for the two vigilance states. The proposed method showed that the frontal and central regions were most sensitive to vigilance decrement. However, in this application, the proposed wICA shows a marginal improvement compared to the Fast-ICA.
Investigation of 2D Seismic DDA Method for Numerical Simulation of Shaking Table Test of Rock Mass Engineering

Since the basic theory of the discontinue deformation analysis (DDA) method was proposed, the DDA open source has gone through a long development process. At present, different kinds of programs have been widely applied in rock mass engineering such as slope, dam, and tunnel. This paper introduces the solution principle of DDA motion equations in detail, as well as the development status of the 2D open-source program. Numerical simulation of shaking table test of rock mass engineering using 2D DDA program is highlighted, and investigations of seismic wave pre-processing and seismic input method are carried out. First, based on the Newmark integration scheme, the integration algorithms of synthetic or measured seismic wave time history, correction function of seismic wave, and DDA simulation are unified. Then, three seismic input methods are implanted in the DDA program, and the applicability of various seismic input methods is discussed. On this basis, using the improved seismic 2D DDA program, a shaking table test of typical rock mass engineering is simulated. Through the comparison between the theoretical/test data and simulation results, the reliability of the improved DDA program in seismic response analysis is verified; the large mass method and the large stiffness method are more suitable for rigid foundation, such as shaking table test; the propagation of the seismic wave presents a significant amplification effect due to the reflection, refraction, and diffraction in the tunnel. The research results provide DDA theory and an open-source program for analyzing the seismic response of rock mass engineering.