Miracle-dz/UniFAR-FTUs huggingface dataset:
Privatization in Rural Water Supply and Customer Satisfaction: An Empirical Case Study in Vietnam

This article investigates the private sector participation in investment, management, and operation in rural water supply schemes in Vietnam. Different organizations manage rural water supply facilities, including the private sector, public sector, and others. This paper aims to compare the different characteristics affecting user satisfaction of water supply facilities managed by the private sector and the remaining sectors. An ordered logit model was utilized for calculation with the data collected from semi-structure questionnaires with 1200 households using water from rural water supply systems managed by different sectors in Vietnam. The results indicate that the water-user satisfaction with rural water supply projects managed by the private sector is higher than that in other sectors (community, cooperative, commune people’s committee), whereas there is no significant difference in customer satisfaction between systems managed by the public sector and the private sector (enterprise, private management). The water availability and quality of schemes greatly influence the customer satisfaction. Findings from this study provide considerable information for the private sector on how to improve the management and operation of water supply systems efficiently through customer satisfaction assessment.
Detection and segmentation of pulmonary nodules based on improved 3D VNet algorithm

Lung cancer has one of the highest incidence rate and mortality rates in the world. Therefore, the recognition and diagnosis of pulmonary nodules based on CT images is an essential index for the diagnosis of lung cancer. Therefore, the detection and segmentation of pulmonary nodules are of great significance in assisting doctors in detecting lung diseases. In this paper, the luna16 data set in the LIDC-IDRI (the lung image database consortium) initiated by the National Cancer Institute is used for research. Given a large amount of data and the diversity of types and sizes of pulmonary nodules in this data set, the detection, and segmentation of various pulmonary nodules are realized based on the improved deep neural network 3D VNet. The deeper the network, the stronger the expression ability and the better the performance. However, with the increase of network depth, there will be problems such as gradient dissipation and gradient explosion. The improved 3D VNet network improves this problem. More than 200000 lung CT images in the LUNA16 data set are preprocessed, such as image denoising and interpolation sampling, and then coarse segmentation images and mask images are generated. They are trained many times in the improved 3D VNet model, and the results with high detection accuracy are obtained. The experimental results show that the dice similarity coefficient (DSC) and IOU of the improved 3D Vnet network can reach 88.29% and 87.25%, which has a good effect on the current detection methods of pulmonary nodules.
Adventitious Shoot Regeneration from Leaf Explants in Sinningia Hybrida ‘Isa’s Murmur’

As a valuable ornamental plant, Sinningia hybrida ‘Isa’s Murmur’ (S. hybrida) has genetic flower diversity, which has great potential to develop different flower characters in the horticultural market. The present study focuses on establishing a practical approach for the sustainable propagation of S. hybrida. Compared with aseptic seeding leaves explants, field-grown leaves explants are more suitable for adventitious shoot regeneration. Adding 0.1 mg L−1 NAA and 2.0 mg L−1 TDZ could obtain the highest adventitious shoot proliferation coefficient (24.5), and the induction rate was 91.7%. The shoot proliferation coefficient (20.7) and the greatest shoot length and induction rate (95.3%) were achieved in 0.1 mg L−1 NAA and 2.0 mg L−1 BA medium, accompanied by rooting formation. Adding 0.5 mg L−1 GA3, 1.0 mg L−1 BA, and 0.2 mg L−1 IBA to MS medium can effectively prolong the regenerated buds for rooting. The best for rooting was 1/2 MS medium containing 0.3 mg L−1 IBA, with the maximum number of roots (13.4 per shoot) and survival rate for transplanting (100%). This work aims to build an efficient, definitive, and scalable protocol for S. hybrida regeneration useful for large-scale cultivation and even more protoplast fusion and genetic transformation to develop more colorful or fragrant flowers.
A novel 3.3 kV 4H-SiC trench PiN with enhanced conductance modulation effect

A novel 3.3 kV rated 4H-SiC trench PiN (T-PiN) structure, which features a trench P+ layer, is proposed and experimentally demonstrated. For the T-PiNs, dry etch onto the N-drift layer is added to the manufacturing process of conventional PiNs (Con-PiNs) before the Al ion implantation step. As the experimental results show, the forward current of the T-PiN diode with an active area of 5 mm × 5 mm has been improved by 32.3% at a voltage of 4 V. Apart from a slight sacrifice in breakdown voltage, the T-PiN is identical to the Con-PiN with regard to other static and surge current capabilities and dynamic characteristics. This superior forward conduction ability of the T-PiNs is a result of enhanced anode carrier injection caused by an enhanced conductance modulation effect and a larger anode carrier injection area. An enhanced conductance modulation effect model was also set up to quantify the increase in the proportion of current density in the T-PiN.
Tumor Stroma Ratio and Its Significance in Locally Advanced Colorectal Cancer

Colorectal cancer is the third leading cause of cancer-related death, and its incidence is rising in the younger patient population. In the past decade, research has unveiled several processes (underlying tumorigenesis, many of which involve interactions between tumor cells and the surrounding tissue or tumor microenvironment (TME). Interactions between components of the TME are mediated at a sub-microscopic level. However, the endpoint of those interactions results in morphologic changes which can be readily assessed at microscopic examination of biopsy and resection specimens. Among these morphologic changes, alteration to the tumor stroma is a new, important determinant of colorectal cancer progression. Different methodologies to estimate the proportion of tumor stroma relative to tumor cells, or tumor stroma ratio (TSR), have been developed. Subsequent validation has supported the prognostic value, reproducibility and feasibility of TSR in various subgroups of colorectal cancer. In this manuscript, we review the literature surrounding TME in colorectal cancer, with a focus on tumor stroma ratio.
3-D Deployment of VLC Enabled UAV Networks With Energy and User Mobility Awareness

The recent proliferation of light-emitting diodes (LEDs) in unmanned aerial vehicles (UAVs) for inspection, first response, environmental protection monitoring, surveillance and urban safety especially at night time, have paved the way for visible light communication (VLC) enabled UAVs. Since UAVs are power limited and size constrain ed devices, the utilization of visible light for communication and illumination in UAVs help in reducing energy and air-frame cost. Further, when the ground users are mobile, UAV placements require regular updates at optimized update intervals. Consequently, we propose energy and user mobility aware three-dimensional (3-D) deployment of VLC enabled UAV-base station (<inline-formula> <tex-math notation="LaTeX">$\mathrm {UB}_{\mathrm {v}}$ </tex-math></inline-formula>) so that maximum coverage of users while ensuring fairness is achieved. The farthest user and shifting UAV based solutions have been proposed for the joint optimization of <inline-formula> <tex-math notation="LaTeX">$\mathrm {UB}_{\mathrm {v}}$ </tex-math></inline-formula> placement and the update interval. The complexity of the proposed approaches is lower than the exhaustive-search based solution, thus, making the <inline-formula> <tex-math notation="LaTeX">$\mathrm {UB}_{\mathrm {v}}$ </tex-math></inline-formula> network energy-efficient. The <inline-formula> <tex-math notation="LaTeX">$\mathrm {UB}_{\mathrm {v}}$ </tex-math></inline-formula> coverage area to serve ground users has been enhanced with holographic light-shaping diffusers (LSD). The optimum angle of the LSD has been obtained based on LED optical transmitted power and desired <inline-formula> <tex-math notation="LaTeX">$\mathrm {UB}_{\mathrm {v}}$ </tex-math></inline-formula> maximum coverage. A novel red, green and blue (RGB) LED solution based on light sensitivity to the human eye is proposed to increase the coverage area for the night scenario. Moreover, we derive the analytical expressions to determine the maximum coverage radius and <inline-formula> <tex-math notation="LaTeX">$\mathrm {UB}_{\mathrm {v}}$ </tex-math></inline-formula> optimum altitude for the defined quality-of-service (QoS) metrics. Finally, the proposed <inline-formula> <tex-math notation="LaTeX">$\mathrm {UB}_{\mathrm {v}}$ </tex-math></inline-formula> network is evaluated in terms of update instant, service time and effective users covered.
Advances and Prospects in Topological Nanoparticle Photonics

Topological nanophotonics is a new avenue for exploring nanoscale systems from visible to THz frequencies, with unprecedented control. By embracing their complexity and fully utilizing the properties that make them distinct from electronic systems, we aim to study new topological phenomena. In this Perspective, we summarize the current state of the field and highlight the use of nanoparticle systems for exploring topological phases beyond electronic analogues. We provide an overview of the tools needed to capture the radiative, retardative, and long-range properties of these systems. We discuss the application of dielectric and metallic nanoparticles in nonlinear systems and also provide an overview of the newly developed topic of topological insulator nanoparticles. We hope that a comprehensive understanding of topological nanoparticle photonic systems will allow us to exploit them to their full potential and explore new topological phenomena at very reduced dimensions.
A High Accuracy Multi-rate Implementation of Resonant Integrator Using FPGA

Second Order Generalised Integrator or Resonant Integrator (RI) has wide range of applications. Forward and backward Euler’s approximation based two integrator realisation of RI is an easily implementable frequency adaptive method. However, it suffers from resonant frequency deviation due to discretization. The discretization methods that lead to accurate realisation of RI require online calculation or look up table of trigonometric functions to accommodate frequency variation. In this paper multi-rate computation based implementation of two integrator based RI has been proposed to minimize resonant frequency deviation. In this method no additional logic elements are consumed to achieve accurate resonant frequency location. This along with down-sampling leads to lesser phase lag of RI. The effect of quantization on resonant frequency deviation has been analysed for proper choice of calculation time. It is also shown that appropriate choice of down-sampling instants give a range of phase response characteristics around the nominal continuous time RI phase response. The accuracy of resonant frequency emulation has been experimentally veriﬁed by implementing a proportional resonant controller as current controller.
Bedrock surface topography of Latvia

ABSTRACT A new map and digital bedrock surface elevation model of Latvia is presented with a horizontal resolution of 250 m. The local bedrock comprises largely undisturbed layers of Palaeozoic and Mesozoic sedimentary rocks covered by up to 200 m thick Quaternary strata composed mostly of glacigenic and marine sediments. The bedrock surface elevation model and the corresponding map were created by tessellation interpolation of the bedrock surface based on more than 20,000 boreholes and constrained by the present land surface. The known locations of paleo-incisions buried under Quaternary cover are indicated. The new digital map has applications in hydrogeological, environmental, and civil engineering, and fundamental and applied research.
Vesicular Nanocarriers for Phytocompounds in Wound Care: Preparation and Characterization

The need to develop wound healing preparations is a pressing challenge given the limitations of the current treatment and the rising prevalence of impaired healing wounds. Although herbal extracts have been used for many years to treat skin disorders, due to their wound healing, anti-inflammatory, antimicrobial, and antioxidant effects, their efficacy can be questionable because of their poor bioavailability and stability issues. Nanotechnology offers an opportunity to revolutionize wound healing therapies by including herbal compounds in nanosystems. Particularly, vesicular nanosystems exhibit beneficial properties, such as biocompatibility, targeted and sustained delivery capacity, and increased phytocompounds’ bioavailability and protection, conferring them a great potential for future applications in wound care. This review summarizes the beneficial effects of phytocompounds in wound healing and emphasizes the advantages of their entrapment in vesicular nanosystems. Different types of lipid nanocarriers are presented (liposomes, niosomes, transferosomes, ethosomes, cubosomes, and their derivates’ systems), highlighting their applications as carriers for phytocompounds in wound care, with the presentation of the state-of-art in this field. The methods of preparation, characterization, and evaluation are also described, underlining the properties that ensure good in vitro and in vivo performance. Finally, future directions of topical systems in which vesicle-bearing herbal extracts or phytocompounds can be incorporated are pointed out, as their development is emerging as a promising strategy.
The Risk of Post-Traumatic Stress Disorder (PTSD) among Frontline Healthcare Workers in Saudi Arabia during the COVID-19 Pandemic: A Cross-sectional Study

Background: Frontline healthcare workers (HCWs) are at risk of developing post-traumatic stress disorder (PTSD) due to the nature of their work and, due to the additional stress and mental fatigue brought on by the COVID-19 pandemic, this risk has increased significantly. A proper understanding of the risk factors for PTSD in this context is crucial to the development of both preventive and corrective measures that will improve the psychological and emotional health of HCWs and reduce their predisposition to PTSD in the short and long term. This study was conducted to determine the prevalence and associated risk factors of PTSD among frontline HCWs in Riyadh, Saudi Arabia, during the COVID-19 pandemic. Methods: This cross-sectional survey study examined responses from emergency medical services personnel (paramedics, nurses, and physicians) in eleven large public hospitals in Riyadh, Saudi Arabia, between June 01 and July 01, 2020. The total number of respondents was 613. The PTSD Checklist for the Diagnostic and Statistical Manual of Mental Disorders (PCL-5), a self-administered tool, was used to diagnose PTSD. Additionally, demographic factors, such as age, gender, race, marital status, occupation, and years of experience, were identified, and the effects of these factors were assessed using statistical analysis. Results: The results revealed a prevalence of PTSD of 33.4% among participants. The highest prevalence was found among paramedics and nurses, while physicians had the lowest prevalence. The study also found statistically significant differences in PTSD scores based on marital status, job title, and years of experience. Half of the participants were aware of the availability of psychological/emotional support and perceived the process for obtaining that support to be clear and accessible. Conclusion: Frontline healthcare workers are at increased risk of developing PTSD, with the degree of risk significantly associated with marital status, job title, years of experience, and the accessibility of psychological/emotional support. Healthcare organisations within Saudi Arabia and elsewhere should use this information to strengthen their psychological and emotional support systems and reduce the risk of PTSD in their employees.
Inverse reinforcement learning for identification of linear-quadratic zero-sum differential games

In this paper, we address the inverse problem in the case of linear–quadratic zero-sum differential games. The problem is to evaluate an unknown cost function given the observed trajectories that are known to be generated by a stationary linear feedback Nash equilibrium pair. Using the observed data, we construct a game that is equivalent to the game that leads to the observed trajectories in the sense that the equilibrium feedback law of any of the two player is the same for that player in the original and constructed games. Towards this end, we introduce a model-based algorithm that uses the given trajectories to accomplish this task. The algorithm combines both inverse optimal control and reinforcement learning methods making extensive use of gradient descent optimization for the latter. The analysis of the algorithm focuses on the proof of its convergence and stability. Simulation results validate the effectiveness of the proposed algorithm.
Time domain analog neuromorphic engine based on high-density non-volatile memory in single-poly CMOS

Increasing the energy efficiency of deep learning systems is critical for improving the cognitive capability of edge devices, often battery operated, as well as for data centers, constrained by the total power envelope. Specialized architectures accelerated by analog vector-matrix multipliers (VMMs) can reduce by orders of magnitude the energy per operation, since the reduced precision of analog computation does not undermine the classification accuracy of the neural network. We show an analog vector-matrix multiplier fabricated with industry-standard 0.18 μm CMOS process, exploiting a single-transistor non-volatile analog memory cell and dedicated technology circuit co-design. The design is focused on implementation in neural networks performing offline training. The VMM performs the analog multiplication of a vector of inputs, encoded in the duration of time pulses, times a matrix of weights, encoded in the programmable currents of the memory cells. A 1.72 μm2 memory cell is realized with a single transistor with floating gate, which can be operated as a two-terminal analog memristive device with more than 64 programmable current levels and high Ihigh/Ilow ratio (> 103), tuned by the charge injected in the floating gate. A small-area charge amplifier is used to convert the multiply and accumulate operation result into a voltage. System-level projections based on our measurements and simulations provide a throughput of 333.17 GOps/s and an energy efficiency of 122.3 TOps/J, higher than comparable-precision VMMs reported in the literature, and an equivalent area per cell down to 2.15 μm2, lower than any similar state-of-the-art solution. Of critical importance in view of translation to industry, our proposal uses in a new way an industry-standard low-cost single-poly CMOS process flow.
Automatic Itinerary Planning Using Triple-Agent Deep Reinforcement Learning

Automatic itinerary planning that provides an epic journey for each traveler is a fundamental yet inefficient task. Most existing planning methods apply heuristic guidelines for certain objective, and thereby favor popular preferred point of interests (POIs) with high probability, which ignore the intrinsic correlation between the POIs exploration, traveler’s preferences, and distinctive attractions. To tackle the itinerary planning problem, this paper explores the connections of these three objectives in probabilistic manner based on a Bayesian model and proposes a triple-agent deep reinforcement learning approach, which generates 4-way direction, 4-way distance, and 3-way selection strategy for iteratively determining next POI to visit in the itinerary. Experiments on five real-world cities demonstrate that our triple-agent deep reinforcement learning approach can provide better planning results in comparison with state-of-the-art multiobjective optimization methods.
Expressing Adaptations to Take into Account in Generator-based Exercisers: An Exploratory Study about Multiplication Facts

: This paper intends to explore how the generation logic and the elements involved are expressed from the teachers’ viewpoint, in the context of learning games. We present an interview-based exploratory study: preparation, realization, analysis, and ﬁndings. From the results we also propose a dedicated metamodel to capture these expressed elements and logic. We evaluate this metamodel by developing a high-level generator component about the practice of times tables.
Community-based tourism in East Asia: A bibliometric research note

Community-based tourism (CBT) is part of East Asia’s tourism landscape as local communities seek to diversify their livelihoods towards tourism. However, little is known about the evolution of research surrounding CBT in the region. Through undertaking a bibliometric analysis of 401 Scopus-indexed articles, this research found that CBT practices have increasingly questioned the legitimacy and authenticity of its value to local communities. Findings also illustrated most studies centred on China, and co-authorship networks mostly occurring between research supervisors and their students. Theoretical and practical insights to advance CBT research in East Asia are proposed.
MAXIMIZING LIFETIME OF WIRELESS SENSOR NETWORK BY MINIMIZING DELAY

In this paper we discuss about how to elongate the lifetime of the wireless sensor networks. WSNs mainly has a problem to prolong the lifetime of the network because once the nodes are deployed, the batteries can neither be replaced nor recharged. In order to improve the lifetime of the WSN, we work to minimize the delay and energy consumption and maximize the lifetime. In our paper, we discuss about traffic congestion and developed some new formulae. This may increase delay as compared to (1), but traffic congestion will not occur. In this paper, we also discuss about power consumption ratio and the expected lifetime. Keywords-Sensor nodes, inactive mode, lifetime of the network, power consumption ratio.
Drought and UV Radiation Stress Tolerance in Rice Is Improved by Overaccumulation of Non-Enzymatic Antioxidant Flavonoids

Drought and ultraviolet radiation (UV radiation) are the coexisting environmental factors that negatively affect plant growth and development via oxidative damage. Flavonoids are reactive, scavenging oxygen species (ROS) and UV radiation-absorbing compounds generated under stress conditions. We investigated the biosynthesis of kaempferol and quercetin in wild and flavanone 3-hydroxylase (F3H) overexpresser rice plants when drought and UV radiation stress were imposed individually and together. Phenotypic variation indicated that both kinds of stress highly reduced rice plant growth parameters in wild plants as compared to transgenic plants. When combined, the stressors adversely affected rice plant growth parameters more than when they were imposed individually. Overaccumulation of kaempferol and quercetin in transgenic plants demonstrated that both flavonoids were crucial for enhanced tolerance to such stresses. Oxidative activity assays showed that kaempferol and quercetin overaccumulation with strong non-enzymatic antioxidant activity mitigated the accumulation of ROS under drought and UV radiation stress. Lower contents of salicylic acid (SA) in transgenic plants indicated that flavonoid accumulation reduced stress, which led to the accumulation of low levels of SA. Transcriptional regulation of the dehydrin (DHN) and ultraviolet-B resistance 8 (UVR8) genes showed significant increases in transgenic plants compared to wild plants under stress. Taken together, these results confirm the usefulness of kaempferol and quercetin in enhancing tolerance to both drought and UV radiation stress.