Miracle-dz/UniFAR-FTUs huggingface dataset:
Circulating MicroRNAs Regulating DNA Damage Response and Responsiveness to Cisplatin in the Prognosis of Patients with Non-Small Cell Lung Cancer Treated with First-Line Platinum Chemotherapy

The expression of microRNA (miR)-21, miR-128, miR-155, and miR-181a involved in DNA damage response (DDR) and tumor responsiveness to platinum was assessed by RT-qPCR in the plasma of patients with non-small cell lung cancer (NSCLC; n = 128) obtained prior to initiation of first-line platinum chemotherapy. U6 small nuclear RNA (snRNA) was used for normalization, and fold change of each miRNA expression relative to the expression in healthy controls was calculated by the 2−ΔΔCt method. MicroRNA expression levels were correlated with patients’ outcomes. Integrated function and pathway enrichment analysis was performed to identify putative target genes. MiR-128, miR-155, and miR-181a expressions were higher in patients compared to healthy donors. MiRNA expression was not associated with response to treatment. High miR-128 and miR-155 were correlated with shorter overall survival (OS), whereas performance status (PS) 2 and high miR-128 independently predicted for decreased OS. In the squamous (SqCC) subgroup (n = 41), besides miR-128 and miR-155, high miR-21 and miR-181a expressions were also associated with worse survival and high miR-155 independently predicted for shorter OS. No associations of miRNA expression with clinical outcomes were observed in patients with non-SqCC (n = 87). Integrated function and pathway analysis on miRNA targets revealed significant enrichments in hypoxia-related pathways. Our study shows for the first time that plasma miR-128 and miR-155 hold independent prognostic implications in NSCLC patients treated with platinum-based chemotherapy possibly related to their involvement in tumor response to hypoxia. Further studies are needed to investigate the potential functional role of these miRNAs in an effort to exploit their therapeutic potential.
Rheological fingerprinting as an effective tool to guide development of personal care formulations

Conventional rheological techniques in the linear viscoelastic region provide insights about the spatial configuration of the microstructural components of personal care formulations in their ‘at‐rest’ state. However, they fail to describe the textural experience associated with large and fast deformations during daily consumer application. In this study we present a non‐conventional rheological technique—large amplitude oscillatory shear (LAOS)—for probing the transformation of a material during its application. This technique is proposed a practical tool for formulators in their efforts to design products with desired textural attributes.
Historical AIS Data-Driven Unsupervised Automatic Extraction of Directional Maritime Traffic Networks

Vessel experience route analysis can provide empirical support for maritime traffic management. Recently, the application of the Automatic Identification System (AIS) provides multi-dimensional data about voyages and vessels. However, traditional route extraction methods do not take into account information such as the vessel traffic pattern and the density distribution in the channel. The experience routes obtained is not accurate enough. This paper proposes an unsupervised method for extracting vessel experience routes from historical AIS data. The method consists of three parts: vessel traffic pattern extraction, channel boundary extraction, channel triangle network construction and hottest route extraction. The method comprehensively considers the spatiotemporal information and density distribution of the vessel trajectories, and constructs a directional maritime traffic network which can effectively convert historical data into information supporting decision-making.
Isolation and identification of myxobacteria from soils and plant materials, with special reference to DNA base composition, quinone system, and cellular fatty acid composition, and with a description of a new species, Myxococcus flavescens.

Myxobacteria were isolated in Japan from soils, decaying plant materials, and tree bark. The isolation methods we have used are the rabbit dung method, placing soil on bacterial smears, the filter paper method, and the agar medium method. Placing soil on bacterial smears was easy to manage. Addition of dealkaline lignin stimulated formation of well- differentiated fruiting bodies on agar medium. This made it possible to investigate the morphology of fruiting bodies of myxobacteria on the agar medium in the laboratory. The myxobacteria isolated and purified were found to be strains of the genera Myxococcus and Archangium. Isolates were identified as Myxococcus stipitatus, Myxococcus fulvus, Myxococcus coralloides, and Archangium gephyra. A new species Myxococcus flavescens is proposed on the basis of morphological characteristics and production of diffusible light yellow pigment. All the tested strains gave positive reactions in catalase and urease. The DNA base composition of the myxobacteria examined ranged from 65 to 67mol% of guanine plus cytosine. The major quinone was menaquinone with 8 isoprenoid units (MK-8). The major cellular fatty acids were iso 15:0, iso 17:0, and 16:1.
UAV-Aided Wireless Communication Design With Energy Constraint in Space-Air-Ground Integrated Green IoT Networks

As more vehicles connect to the internet, they become an important and growing segment of Internet of Things (IoT). To enhance the performance of vehicle-to-network (V2N) communication with green objectives, satellite and unmanned aerial vehicle (UAV) are jointly applied to aid ground communication facility by leveraging the coordinated multi-point transmission technique. This paper investigates a novel architecture of V2N communication in the space-air-ground integrated IoT network consisted of ground base stations (BSs), a UAV as well as one satellite. In the V2N communication model, the UAV, receiving the requested data from the satellite, and BS cooperatively serve the ground vehicle. The goal of this paper is to maximize the achievable rate of the ground vehicle by jointly optimizing the transmit power allocations (i.e., UAV and ground BS) and UAV trajectory, subjecting to the UAV energy constraint, UAV transmission constraint as well as UAV mobility constraint. However, there exists an intractable issue of the formulated problem in a complicated non-convex form. To this end, we decompose it into two sub-problems by fixing UAV trajectory and the power allocations alternately. Specifically, the closed-form expressions are derived to solve the sub-problem with the given UAV trajectory. For the sub-problem with the given power allocations, the UAV trajectory is calculated by using successive convex approximation (SCA) technique. Through the alternation of two methods and iterative operation, the joint optimal solution to the problem is achieved. Finally, numerical results verify that UAV plays a pivotal role in overcoming the tradeoff between higher performance and green communication.
Multi-domain Mapping for Offshore Asset Inspection using an Autonomous Surface Vehicle

The offshore wind power industry is an emerging and exponentially growing sector, which calls to a necessity for a cyclical monitoring and inspection to ensure the safety and efficiency of the wind farm facilities. Thus, the multiple domains of the environment must be reconstructed, namely the emersed (aerial) and immersed (underwater) domains, to depict as much as possible the offshore structures from the wind turbines to the cable arrays. This work proposes the use of an Autonomous Surface Vehicle (ASV) to map both environments simultaneously producing a multi-domain map through the fusion of navigational sensors, GPS and IMU, to localize the vehicle and aid the registration process for the perception sensors, 3D Lidar and Multibeam echosounder sonar.The performed experiments demonstrate the ability of the multi-domain mapping architecture to provide an accurate reconstruction of both scenarios into a single representation using the odometry system as the initial seed to further improve the map with data filtering and registration processes.
Repellency and toxicity of extract from Francoeria crispa (Forsk.) to Eutetranychus orientalis (Klein) (Acari: Tetranychidae)

Laboratory bioassays were conducted to characterise the activity of the extract Francoeria crispa (Forsk.) (Family: Compositae) against the citrus brown mite, Eutetranychus orientalis (Klein). Ethyl acetate was tested for preparing the crude extract of F. crispa. The extract was tested for its toxicity against eggs and adult females of the pest E. orientalis. Ethyl acetate extract of F. crispa affected the behaviour, toxicity and fecundity of females under laboratory conditions. The extract had similar toxic effects on egg stage and adult females of E. orientalis (LC50 = 0.00050 g/ml), respectively. Leaf discs treated with increasing concentrations of ethyl acetate extract of F. crispa showed a high percentage of repellency (97.45%), respectively. Treated females with LC50 concentration of ethyl acetate extract showed a higher remarkable percentage of mortality as well as a reduction in the total number of eggs laid during 7 days. Ten isolated fractions of ethyl acetate crude extract from F. crispa were detected. The results clearly indicate that the isolate number (10) was the most toxic isolate on eggs and females of E. orientalis (LC50 = 0.00014 and 0.000125 g/ml), respectively.
CSPC-Dataset: New LiDAR Point Cloud Dataset and Benchmark for Large-Scale Scene Semantic Segmentation

Large-scale point clouds scanned by light detection and ranging (lidar) sensors provide detailed geometric characteristics of scenes due to the provision of 3D structural data. The semantic segmentation of large-scale point clouds is a crucial step for an in-depth understanding of complex scenes. Of late, although a large number of point cloud semantic segmentation algorithms have been proposed, semantic segmentation methods are still far from being satisfactory in terms of precision and accuracy of large-scale point clouds. For machine learning (ML) and deep learning (DL) methodologies, the semantic segmentation is largely influenced by the quality of training sets and methods themselves. Therefore, we construct a new point cloud dataset, namely CSPC-Dataset (Complex Scene Point Cloud Dataset) for large-scale scene semantic segmentation. CSPC-Dataset point clouds are acquired by a wearable laser mobile mapping robot. It covers five complex urban and rural scenes and mainly includes six types of objects, i.e., ground, car, building, vegetation, bridge, and pole. It provides large-scale outdoor scenes with color information, which has advantages such as the scene more complete, point density relatively uniform, diversity and complexity of objects and the high discrepancy between different scenes. Based on the CSPC-Dataset, we construct a new benchmark, which includes approximately 68 million points with explicit semantic labels. To extend the dataset into a wide range of applications, this paper provides the semantic segmentation results and comparative analysis of 7 baseline methods based on CSPC-Dataset. In the experiment part, three groups of experiments are conducted for benchmarking, which offers an effective way to make comparisons with different point-labeling algorithms. The labeling results have shown that the highest Intersection over Union (IoU) of pole, ground, building, car, vegetation, and bridge for all benchmarks is 36.0%, 97.8%, 93.7%, 65.6%, 92.0%, and 69.6%.
The ionotropic glutamate receptor GluA2 in complex with bicyclic pyrimidinedione-based compounds: when small compound modifications have distinct effects on binding interactions.

AMPA receptors comprise an important class of ionotropic glutamate receptors activated by glutamate in the central nervous system. These receptors have been shown to be involved in brain diseases, e.g. Alzheimer's disease and epilepsy. To understand the functional role of AMPA receptors at the molecular level and their potential as targets for drugs, development of tool compounds is essential. We have previously reported the synthesis of six bicyclic pyrimidinedione-based analogues of willardiine with differences limited to the pyrimidinedione-fused five-membered rings. Despite minor molecular differences, we observed >500-fold difference in binding affinity of the compounds at full-length GluA2. Here, we report binding affinities and the binding mode of these compounds at the ligand-binding domain of GluA2 using X-ray crystallography. The structures revealed similar binding modes, but with distinct differences in the interaction between GluA2 and the compounds. The methylene (2) and sulfur (3) containing compounds showed the greatest binding affinities. Changing the dihydrothiophene (3) into pyrrolidine (4), N-methyl pyrrolidine (5) or dihydrofuran (6) induced flexibility in the position of a binding-site water molecule and changes in the hydrogen-bonding network between compound, water and GluA2. This might be essential for explaining the reduced binding affinity of these compounds. The weakest binding affinity was observed when the aliphatic oxygen containing dihydrofuran (6) was changed into an aromatic furan system (7). Molecular docking studies revealed two possible orientations of 7, whereas only one binding mode was observed for the other analogues. This could likely contribute to the weakest binding affinity of 7 at GluA2.
Research on Routing Optimization of SDN Network Using Reinforcement Learning Method

The development of computer networks is making it become more complex and dynamic. How to achieve efficient package-routing in the SDN (Software Design Network) has become hot research field. SARSA-Learning is a typical Reinforcement Learning algorithm. Through the on-policy exploration and learning of the network environment, it can be used to derive the optimal decision in an unknown network environment, in this way, the network data routing and forwarding can be effectively completed. This paper yields a SARSA-Learning Routing algorithm with variable greedy function (Variable $\varepsilon$-Greedy function within SARSA-Learning Routing, V-S Routing). The V-S Routing algorithm preserves the efficiency of the SARSA-Leaning framework. The purpose of V-S Routing introduces a variable factor to $\varepsilon$-Greedy function. The V-S Routing algorithm can be dynamically calculated to represent the priority of the current state in the SDN network and to solve the problem of SDN network optimal route selection, which can avoid long package waiting queue and reduce SDN network congestion and improve the link transmission speed. The Variable $\varepsilon$-Greedy function makes the algorithm more suitable to the network environment, and it also makes V-S Routing algorithm having better generalization ability. The experimental results verify the effectiveness of the algorithm.
Awareness and Willingness to Pay for Moringa

Moringa (Moringa oleifera Lam) leaves are highly nutritious and contain essential amino acids; moringa is a complete protein source and contains essential vitamins, minerals, co-enzymes, and antioxidants. Moringa cultivation is gaining popularity, but not all Nigerians are aware of, or have access to, Moringa. This study examined awareness, willingness to pay, and factors that determine willingness to pay for Moringa of 131 randomly selected respondents. About 83% were aware of Moringa, and the average amount respondents were willing to pay was N314.89·kg−1 for fresh Moringa. Factors influencing willingness to pay were age, education, and preference of respondents for other vegetables. Though the level of awareness of Moringa is high, consumers preferred other vegetables.
Diet composition at weaning affects the rumen microbial population and methane emissions by lambs

The aim of this experiment was to investigate whether different diets at weaning determine the microbial populations established in the rumen, together with its methanogenic capacity, and whether these differences are consistent over a longer time period. Twenty ewes with single lambs were used in two periods. Period I: 10 lambs had access only to grass hay whilst with the dam and for 8 weeks after weaning (group H). The other 10 lambs had free access to concentrate and grass hay whilst with the dam and were fed with a 60 : 40 mix of concentrate and grass hay for 8 weeks after weaning (group C). Eight weeks after weaning, methane emissions were measured in polycarbonate chambers over a 3-day period. After methane emission measurements, five lambs from each group were randomly selected and slaughtered and samples of rumen content collected for measuring rumen fermentation parameters and for microbial enumeration (total and cellulolytic bacteria and methanogenic archeaea) by most probable number. Period II: the remaining 10 lambs were grouped together and fed the same diet (grass and concentrate) for 4 months. After this period, all animals were fed concentrate and grass hay (60 : 40) for 2 weeks and introduced in to the chambers to measure methane emissions over a 3-day period. After measurements, they were slaughtered and rumen samples collected and analysed as in Period I. Lambs from group H produced more (P = 0.04) methane than group C lambs (26.0 v. 22.5 L/kg DM intake) in Period I. Group H lambs also had less total bacteria (10.2 × 1010 v. 61.6 × 1010 cells; P = 0.284) but more cellulolytic bacteria (40.6 × 109 v. 10.0 × 109 cells; P = 0.098) and methanogenic archaea (37.1 × 109 v. 19.0 × 109 cells; P = 0.113) than group C lambs in Period I. The acetate to propionate ratio tended to be higher (P = 0.089) in group H lambs than in group C lambs (3.00 v. 2.35). In Period II, methane produced was not different (P > 0.05) between the groups (26.6. v. 25.7 L/kg DM intake by group C and H lambs, respectively). Microbial numbers and fermentation parameters were also similar in samples collected from both experimental groups in Period II. Our results show that the differences observed as a result of providing different diets at weaning disappear in the long-term. It may be appropriate to study a wider range of dietary treatments to better understand the factors determining the microbial populations establishing in the rumen.
Retinal microglia are critical for subretinal neovascular formation.

Abnormal subretinal neovascularization is characteristic of vision-threatening retinal diseases including macular telangiectasia (MacTel) and retinal angiomatous proliferation (RAP). Subretinal neovascular tufts and photoreceptor dysfunction are observed in very low-density lipoprotein receptor mutant mice (Vldlr-/-). These changes mirror those observed in MacTel and RAP patients, but the pathogenesis is largely unknown. In this study, we show that retinal microglia are closely associated with retinal neovascular tufts in Vldlr-/- mice and retinal tissue from MacTel patients; ablation of microglia/macrophages dramatically prevents formation of retinal neovascular tufts and improves neuronal function as assessed by electroretinography. VMD2-driven retinal pigmented epithelium (RPE)-specific knockouts of VEGF greatly reduced subretinal infiltration of microglia/macrophages, subsequently reducing NV tufts. These findings highlight the contribution of microglia/macrophages to the pathogenesis of NV, provide valuable clues regarding potential causative cellular mechanisms for subretinal neovascularization in MacTel and RAP patients, and suggest that targeting microglia activation may be a therapeutic option in these diseases.
Study on Effect of Installation Location on Lifetime of PV Inverter and DC-to-AC Ratio

The reliability improvement of a PV inverter is one of the important aspects to decrease the cost of PV energy. Furthermore, oversizing the PV arrays is a commonly applied strategy to achieve the cost of PV energy reduction but it may also have a negative impact on the cost of PV energy since it accelerates the wear-out of the PV inverter. Therefore, the lifetime of the PV inverter has to be considered to find a safe limit for the oversizing of the PV arrays but there is a lack of study on this effect. This paper studies the effect of the installation location on the lifetime of the PV inverter together with DC/AC ratio. The lifetime evaluation of NPC inverter is carried out with three installation locations inclusive of the effect of the cooling capacity. Furthermore, the impact of DC/AC ratio on the lifetime of the PV inverter is investigated by taking into account the influence of the installation location to show the importance of the lifetime of the PV inverter to select the optimum DC/AC ratio to minimize the cost of PV energy.
Characterization of rotor losses in High Speed Permanent Magnet Synchronous Machines

This paper presents a synthesis of the analysis and modelling of the rotor losses in high speed permanent magnets motors. Three types of losses are due to eddy currents in the conductive parts of the rotor. The analysis includes their characterization and the setup of a numerical model using finite element methods. The analysis is applied on a high speed PM motor for avionic application.
Are p53 inhibitors potentially useful therapeutics?

The tumor‐suppressor protein p53 is an intracellular protein critical in many biochemical cascades leading to cell death via apoptosis pathway or cell survival by arresting the cell cycle. Based on recent studies, which have characterized chemical inhibitors of p53 in the cancer therapy field as well in the pathogenesis of stroke and neurodegenerative disorders, this review concentrates on the development of drugs that inhibit p53 and their possible use as novel strategies for combating neurodegenerative diseases, cancer, and eventually HIV infection. Emphasis is mainly focussed on pifithrin‐α derivatives, which appear to be the most efficient p53 inactivators known to date since no such drugs are currently approved. Pifithrin‐α antagonises p53 at the post‐transcriptional level. The precise mechanism through which their effects are achieved, either by direct interaction of p53 or via indirect binding, remains to be elucidated. Moreover, Pft‐α derivatives are cyclized in situ in biological media into their corresponding dehydrated cyclic forms. These cyclic forms, also p53 inactivators, could represent new interesting scaffolds useful in the therapeutic treatment of p53‐related disease. Drug Dev Res 65:43–49, 2005. © 2005 Wiley‐Liss, Inc.
Max-min Placement optimization for UAV Enabled Wireless Powered Networks with Non-linear Energy Harvesting Model

In this paper, we investigate the placement optimization for unmanned aerial vehicle (UAV) enabled wireless powered transfer network under the non-linear energy harvesting model. To maintain fairness among users, we propose a max-min energy harvesting problem by optimizing the UAV’s placement based on a non-linear energy harvesting model. As the max-min problem is a non-convex problem, it is difficult to achieve the optimal solution efficiently. We propose two natural optimization algorithms based on bat algorithm and ant colony optimization algorithm to solve the max-min placement problem. Simulation results show that the two natural optimization algorithms are superior to the traditional grid search algorithm in terms of computation time.