Miracle-dz/UniFAR-FTUs huggingface dataset:
Using UAV to Detect Solar Module Fault Conditions of a Solar Power Farm with IR and Visual Image Analysis

In recent years, solar energy has been regarded as one of the most important sustainable energy sources. Under the rapid and large-scale construction of solar farms, the maintenance and inspection of the health conditions of solar modules in a large solar farm become an important issue. This article proposes a method for detecting solar cell faults with unmanned aerial vehicle (UAV) equipped with a thermal imager and a visible light camera, and providing a fast and reliable detection method. The detection process includes a new concept of real-time monitoring of the detected area and analysis of the health of solar panels. An image process is proposed that may quickly and accurately detect the abnormality of a solar module. The whole process includes grayscale conversion, filtering, 3-D temperature representation, probability density function, and cumulative density function analysis. Ten cases in real fields have been studied with this process, including large scale solar farms and small size solar modules installed on buildings. Results show that the cumulative density function is a convenient way to determine the health status of the solar panel and may provide maintenance personnel a basis for determining whether replacement of solar cells is necessary for improving the overall power generation efficiency and simplify the maintenance process. It is worth noting that image recognition can increase the clarity of IR images and the cumulative chart can judge the defect rate of the cell. These two methods were combined to provide an instant, fast and accurate defect judgment.
A 45-W Two-Stage Wireless Fast Charger Using Unregulated Inductive Power Transfer

Most of the existing wireless offline chargers would employ redundant power conversion and isolation stages to charge a low-voltage battery, which leads to limited overall efficiency. In order to address the redundancy issue, this article proposes a wireless fast charger by using a two-stage configuration. An unregulated inductive power transfer (IPT) stage can not only offer galvanic isolation, but also provide high step-down voltage ratio, and then, only a simple buck converter is needed for voltage regulation. This article evaluates the influence of voltage gain on efficiency and voltage stress of an LCC-C compensated IPT stage. The zero-voltage-switching (ZVS) lost mechanism is also studied and evaluated by a proposed ZVS model. Finally, a 45-W fast charger prototype is designed for 264-V/12-V conversion. The measured peak efficiency is 78%, which is much higher than the Qi-based charger.
A Biologically Friendly, Low‐Cost, and Scalable Method to Map Permeable Media Architecture and Interstitial Flow

Porous media are ubiquitous, a key component of the water cycle and locus of many biogeochemical transformations. Mapping media architecture and interstitial flows have been challenging because of the inherent difficulty of seeing through solids. Previous works used particle image velocimetry (PIV) coupled with refractive index‐matching (RIM) to quantify interstitial flows, but they were limited to specialized and often toxic fluids that precluded investigating biological processes. To address this limitation, we present a low‐cost and scalable method based on RIM coupled PIV (RIM‐PIV) and planar laser induced fluorescence (RIM‐PLIF) to simultaneously map both media architecture and interstitial velocities. Our method uses irregularly shaped grains made of a fluorocarbon plastic with refractive index of 1.36 and specific gravity of 1.93. This allows using a water–glycerin solution for the RIM fluid. By using RIM‐PIV, we mapped media structure with 2% accuracy, which improved to 0.2% with RIM‐PLIF because of improved image contrast.
Landscape Of M6a RNA Methylation Regulators and Tumor Microenvironment Cell-Infiltration Characterization In Gastroesophageal Adenocarcinomas

Background: RNA N6-methyladenosine (m6A) modification plays a nonnegligible role in shaping individual tumor microenvironment (TME) characterizations. However, the landscape and relationship of m6A modification and TME cell infiltration remain unknown in gastroesophageal adenocarcinomas (GEA). Methods: We systematically examined the TME of GEA focusing on the distinct m6A modification patterns from the public databases. Intrinsic patterns of m6A modification were evaluated for associations with clinicopathological characteristics, underlying biological pathways, tumor immune cell infiltration, oncological outcomes and treatment responses. We generated a single-cell transcriptome atlas of the GEA sample inhouse to validate the role of the m6A modification pattern on TME.Results: We identified and validated the landscape of m6A regulators and tumor-infiltrating immune cells in GEA. Then, two distinct m6A modification patterns of GEA (cluster1/2 subgroup) were defined, and we correlated two subgroups with TME cell-infiltrating characteristics. Cluster2 subgroup correlates with a poorer prognosis, down-regulated PD-1 expression, higher risk scores and distinct immune cell infiltration. Additionally, PPI and WGCNA network analysis were integrated to identify key module genes closely related to immune infiltration of GEA to find immunotherapy markers. And COL4A1 and COL5A2 in brown module were significantly correlated to the prognosis, PD-1/L1 and CTLA-4 expression of GEA patients. Interesting, low COL5A2 expression was linked to an enhanced response to anti-PD-1 immunotherapy. Finally, a prognostic risk score was constructed using three m6A regulator-associated signatures that represented an independent prognosis factor for GEA. The single-cell transcriptome atlas of GEA sample validated the role of m6A modification pattern on TME and revealed that three m6A regulators are highly expressed in CD4+ T cells, CD8+ T cells, Tregs and Macrophages.Conclusions: Our work revealed m6A RNA methylation regulators are a type of vital participant in the malignant progression and TME diversity of GEA. m6A modification patterns of COL5A2 may be the potential biomarker contributes to predicting the response to anti-PD-1 immunotherapy.
Lessons learned from contemporary glioblastoma randomized clinical trials through systematic review and network meta-analysis: part 1 newly diagnosed disease

Abstract Background Glioblastoma (GB) is the most common malignant brain tumor with a dismal prognosis despite standard of care (SOC). Here we used a network meta-analysis on treatments from randomized control trials (RCTs) to assess the effect on overall survival (OS) and progression-free survival (PFS) beyond the SOC. Methods We included RCTs that investigated the addition of a new treatment to the SOC in patients with newly diagnosed GB. Our primary outcome was OS, with secondary outcomes including PFS and adverse reactions. Hazard ratio (HR) and its 95% confidence interval (CI) regarding OS and PFS were extracted from each paper. We utilized a frequentist network meta-analysis. We planned a subgroup analysis based on O6-methylguanine-DNA methyl-transferase (MGMT) status. We followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses. Results Twenty-one studies were included representing a total of 7403 patients with GB. There was significant heterogeneity among studies impacting important factors such as timing of randomization and sample size. A confidence analysis on the network meta-analysis results revealed a score of low or very low for all treatment comparisons, across subgroups. Allowing for the heterogeneity within the study population, alkylating nitrosoureas (Lomustine and ACNU) and tumor-treating field improved both OS (HR = 0.53, 95% CI 0.33–0.84 and HR = 0.63 95% CI 0.42–0.94, respectively) and PFS (HR = 0.88, 95% CI 0.77–1.00 and HR = 0.63 95% CI 0.52–0.76, respectively). Conclusions Our analysis highlights the numerous studies performed on newly diagnosed GB, with no proven consensus treatment that is superior to the current SOC. Intertrial heterogeneity raises the need for better standardization in neuro-oncology studies.
Intergrated metagenomics  and metabolomics analysis  discovers  nematicidal microbes, enzymes and metabolites  from the plant rhizosphere microbiota

Background: Root-knot nematode Meloidogyne incognita infects root systems of many crops resulting in huge decrease of crop production. Nematicidal microorganisms provides a safe and effective strategy to control M. incognita infection. In order to find microorganisms with high activity and new nematicidal metabolites, we collected the M. incognita infected tobacco rhizosphere soils (RNI) and non-infected tobacco rhizosphere soils (NS), and investigated their microbial community and network via metagenomics and metabolomics analysis. Results: Microbial networks of RNI soils were very different from the NS soils. Many nematicidal microorganisms were enriched in the NS soils, including isolates of Aspergillus , Achromobacter , Acinetobacter , Bacillus , Burkholderia , Comamonas , Enterobacter , Lysobacter , Microbacterium , Paenibacillus , Pantoea , Pseudomonas , Streptomyces and Variovorax. Enzymes analysis showed these nematicidal microorganisms can produce proteases, chitinase and lipases. The functions genes belonging to pathways of secondary metabolites biosynthesis and carbohydrate transport and metabolism were overrepresented in the rhizophere microbiota of NS soils comparing with the RNI soils. 102 metabolites contents were significantly different between the RNI and NS rhizosphere microbiota. 35 metabolites were overrepresented in the NS soils comparing the RNI samples, including acetophenone. Acetophenone showed high nematicidal (LC 50 = 0.66 μg/ml) and avoidance activity against M. incognita . Bacillus amyloliquefaciens W1 could produce acetophenone. Liquid culture of W1 could kill 98.8% of M . incognita J2 juveniles after treatment for 24 h.Conclusions: In general, the rhizophere microbiota of NS soils could produce volatile materials, multiple enzymes and secondary metabolites against nematode. Collectively, the microbiota of NS and RNI rhizophere differed significantly in microbial network structure, community composition, function genes and metabolites. Collectively, combination of multi-omics analysis and culture-dependent technology is powerful for finding nematicidal microorganisms and metabolites from soil.
Sonicated Zeolitic Imidazolate Frameork-8 derived Nitrogen-doped hierarchical nanoporous carbon for efficient capture and reversible storage of radioiodine

Iodine plays a significant role in industry and in chemical processes within living organisms. However, radioiodine exposure possess threats such as thyroid cancer to humans, when they are released into the environment when using nuclear technology and through nuclear accidents. Its capture and storage is critical to safeguard industrial applications while preventing environmental leakages. Herein we report efficient radioiodine capture using a hierarchical nitrogen-doped, large surface area, nanoporous carbon derived from ultrasonication of ZIF-8. The carbon exhibited high adsorption capacity of 434 wt% gravimetrically and 1418 mgg− 1 in cyclohexane solution with fast kinetics and high recoverability. We deduced the high adsorption capacity to be due to the large surface area with micro and mesopores, presence of hydroxyl groups acting as electron donors and the presence of nitrogen, which interacts strongly with the electron-deficient iodine (I2). Moreover, the process best fits the pseudo-second-order and Freundlich models with multilinearity observed with Webber-Morris model. Because of its comparatively lower cost, large surface area, facile preparation, good regeneration and fast kinetics, the as-prepared porous carbon shows exceptional promise as radioiodine adsorbent.
A Comparative Study of Aromatization Catalysts: The Advantage of Hybrid Oxy/Carbides and Platinum-Catalysts Based on Carbon Gels

This manuscript is focused on the relationship between sol-gel synthesis processes and the development of new active phases with fitted morphology, porosity and surface chemistry. The influence of the above parameters on the catalytic performance of the prepared materials for the aromatization of n-hexane to benzene is also evaluated. Different series of catalysts were prepared, either using noble metals (i.e., Pt) or metal oxides (i.e., Mo, W), as active phases. In both cases, the catalytic performance and stability of classical aromatization catalysts was significantly improved. Interesting one-pot carboreduction process of the metal oxide during carbonization is suggested as a real alternative for the preparation of high-performance aromatization catalysts, leading to the formation of less acidic and non-stoichiometric oxides and carbides.
Spatial and Temporal Variation in Composition in Multicomponent NAPL s

A numerical simulator has been developed to model the spatial and temporal variation of multicomponen t NAPL composition and dissolved phase concentrations in a groundwater environment. The model accounts for NAPL solidification that may result as constituent compounds reach their solubility limits in the organic liquid. Simulations were run for NAPL mixtures of polycyclic aromatic hydrocarbons (PAHs). Thirty-year simulations demonstrate that the NAPL slowly becomes depleted of the lower molecular weight compounds. The enrichment of the NAPL with respect to the more carcinogenic compounds implies limited reduction in human health risk, despite the continued reduction in overall NAPL volume.
Comparison between Intra-Arterial Thrombolysis and Intravenous Thrombolysis in Ischemic Stroke Patients: A Meta-Analysis

Background: To investigate the efficacy and safety between intra-arterial thrombolysis (IAT) and intravenous thrombolysis (IVT) in ischemic stroke patients. Methods: The full-texts comparing IAT and IVT in ischemic stroke patients were retrieved by PubMed, Embase and Cochrane Central Register of Controlled Trials databases. Review Manager 5.0 was adopted for conducting meta-analysis, sensitivity analysis and bias analysis. Results: A total of 6 studies including 440 patients with ischemic stroke were included. The results of meta-analysis suggested significant differences between IVT and IAT groups in complete recanalization (relative risk (RR) = 0.58, 95% confidence interval (CI) [0.48, 0.71], P < 0.00001; P for Heterogeneity = 0.70, I2 = 0%). But no significant differences were observed in the National Institutes of Health Stroke Scale (NIHSS) after treatment of symptomatic incidence of intracerebral hemorrhage (ICH) and mortality. Conclusions: Our study findings suggested that IAT is more efficient than IVT in direct clinical effects in ischemic stroke patients. Analysis of secondary outcome and safety showed no difference. Additional studies with larger sample sizes are strongly needed to further validate our findings.
Agricultural Innovations to Reduce the Health Impacts of Dams

Dams enable the production of food and renewable energy, making them a crucial tool for both economic development and climate change adaptation in low- and middle-income countries. However, dams may also disrupt traditional livelihood systems and increase the transmission of vector- and water-borne pathogens. These livelihood and health impacts diminish the benefits of dams to rural populations dependent on rivers, as hydrological and ecological alterations change flood regimes, reduce nutrient transport and lead to the loss of biodiversity. We propose four agricultural innovations for promoting equity, health, sustainable development, and climate resilience in dammed watersheds: (1) restoring migratory aquatic species, (2) removing submerged vegetation and transforming it into an agricultural resource, (3) restoring environmental flows and (4) integrating agriculture and aquaculture. As investment in dams accelerates in low- and middle-income countries, appropriately addressing their livelihood and health impacts can improve the sustainability of modern agriculture and economic development in a changing climate.
Cooperative Service Placement and Scheduling in Edge Clouds: A Deadline-Driven Approach

Mobile edge computing enables resource-limited edge clouds (ECs) in federation to help each other with resource-hungry yet delay-sensitive service requests. Contrary to common practice, we acknowledge that mobile services are heterogeneous and the limited storage resources of ECs allow only a subset of services to be placed at the same time. This paper presents a jointly optimized design of cooperative placement and scheduling framework, named JCPS, that pursues <italic>social cost minimization</italic> over time while ensuring diverse user demands. Our main contribution is a novel perspective on cost reduction by exploiting the <italic>spatial-temporal diversities</italic> in <italic>workload and resource cost</italic> among federated ECs. To build a practical edge cloud federation system, we have to consider two major challenges: <italic>user deadline preference</italic> and <italic>ECs’ strategic behaviors</italic>. We first formulate and solve the problem of spatially strategic optimization without deadline awareness, which is proved <inline-formula><tex-math notation="LaTeX">$\mathcal {NP}$</tex-math><alternatives><mml:math><mml:mi mathvariant="script">NP</mml:mi></mml:math><inline-graphic xlink:href="wang-ieq1-3061602.gif"/></alternatives></inline-formula>-hard. By leveraging user deadline tolerance, we develop a Lyapunov-based <italic>deadline-driven</italic> joint cooperative mechanism under the scenario where the workload and resource information of ECs are known for one-shot global cost minimization. The <italic>service priority</italic> imposed by deadline urgency drives time-critical placement and scheduling, which, combined with cooperative control, enables workloads migrated across different times and ECs. Given selfishness of individual ECs, we further design an auction-based cooperative mechanism to elicit <italic>truthful bids</italic> on workload and resource cost. Rigorous theoretical analysis and extensive simulations are performed, validating the efficiency of JCPS in realizing cost reduction and user satisfaction.
An Expert Elicitation of the Effects of Low Salinity Water Exposure on Bottlenose Dolphins

There is increasing concern over anthropogenically driven changes in our oceans and seas, from a variety of stressors. Such stressors include the increased risk of storms and precipitation, offshore industries and increased coastal development which can affect the marine environment. For some coastal cetacean species, there is an increased exposure to low salinity waters which have been linked with a range of adverse health effects in bottlenose dolphins. Knowledge gaps persist regarding how different time–salinity exposures affect the health and survival of animals. In such data-poor instances, expert elicitation can be used to convert an expert’s qualitative knowledge into subjective probability distributions. The management implications of this stressor and the subjective nature of expert elicitation requires transparency; we have addressed this here, utilizing the Sheffield Elicitation Framework. The results are a series of time response scenarios to estimate time to death in bottlenose dolphins, for use when data are insufficient to estimate probabilistic summaries. This study improves our understanding of how low salinity exposure effects dolphins, guiding priorities for future research, while its outputs can be used to support coastal management on a global scale.
Transport of Topological Edge States in 2D Zigzag Edge Tungsten Ditelluride Nanoribbon

In this paper, we have investigated the transport of topological edge states in 2D Zigzag edge Tungsten Ditelluride Nanoribbon (ZTDNR). We have found that zigzag edge nanoribbon (NR) of Tungsten Ditelluride develops topological edge states in the presence of intrinsic spin orbit interaction (SOC). We have used three band tight binding model for the electrons of dz2 , dxy, and dx2 - y2 orbitals with SOC for calculating band structure of NR and Non Equilibrium Greens Function (NEGF) formalism for transport in the NR. We have investigated transport in a pristine device, transport in the presence of a finite potential barrier, transport with constriction within the device and transport with edge imperfections.
Analyzing and Improving the Performance of a Particulate Matter Low Cost Air Quality Monitoring Device

Air quality (AQ) in urban areas is deteriorating, thus having negative effects on people’s everyday lives. Official air quality monitoring stations provide the most reliable information, but do not always depict air pollution levels at scales reflecting human activities. They also have a high cost and therefore are limited in number. This issue can be addressed by deploying low cost AQ monitoring devices (LCAQMD), though their measurements are of far lower quality. In this paper we study the correlation of air pollution levels reported by such a device and by a reference station for particulate matter, ozone and nitrogen dioxide in Thessaloniki, Greece. On this basis, a corrective factor is modeled via seven machine learning algorithms in order to improve the quality of measurements for the LCAQMD against reference stations, thus leading to its on-field computational improvement. We show that our computational intelligence approach can improve the performance of such a device for PM10 under operational conditions.
The effects of information structure in the processing of word order variation in the second language

Traditionally, it has been claimed that the non-canonical word order of passives makes them inherently more difficult to comprehend than their canonical active counterparts both in the first (L1) and second language (L2). However, growing evidence suggests that non-canonical word orders are not inherently more difficult to process than canonical counterparts when presented with discourse contexts that license their information structure constraints. In an eye-tracking experiment, we investigated the effect of information structure on the online processing of active and passive constructions and whether this effect differed in monolinguals and L1-Spanish–L2-English speakers. In line with previous corpus studies, our results indicated that there was an interaction between word order and information structure according to which passive sentences were much more costly to process with new–given information structure patterns. Crucially, we failed to find evidence that the effect of information structure on word order constraints in comprehension differed between monolingual and L2 speakers.