Miracle-dz/UniFAR-FTUs huggingface dataset:
The Application of Sodium Carbonate in the Antisepsis and Preservation of Postharvest Early Mature Citrus unshiu Marc.

With early mature Citrus unshiu Marc in Gannan area as the test materials,the application effects of food additive sodium carbonate(Na2CO3) on the antisepsis and preservation of early mature Citrus unshiu Marc.were studied during 10 days normal temperature storage(20~25 ℃). The results showed that,the better preservative results were obtained from Na2CO3 added treatment than barely conventional chemical preservatives treatment,and the preservation treatment was 500 mg/L Belkute+500 mg/L Prochloraz+50 mg/L 2,4-D and using Na2CO3 to regulate the pH to 10.0. The effect of adding Na2CO3 on the pH of preservation solution was big,and the optimized pH was ranging from 10.0 to10.5. The most suitable concentration of Na2CO3 was about 1 g/kg,if the concentration was too high,there would cause the negative effect on citrus fruit.
Dual-Energy Computed Tomography for the Diagnosis of Mediastinal Lymph Node Metastasis in Lung Cancer Patients: A Preliminary Study

Objective This study explored the feasibility of dual-energy computed tomography (DECT) for the diagnosis of mediastinal lymph node (LN) metastasis in patients with lung cancer. Methods Forty-two consecutive patients with lung cancer, who underwent DECT, were included in this retrospective study. The attenuation value (Hounsfield unit) in virtual monochromatic images and the iodine concentration in the iodine map were measured at mediastinal LNs. The slope of the spectral attenuation curve (K) and normalized iodine concentration (in thoracic aorta) were calculated. The measurement results were statistically compared using 2 independent samples t test. Receiver operating characteristic curve analysis, net reclassification improvement, and integrated discrimination improvement were used to evaluate the diagnostic performance of DECT for mediastinal LN metastasis. Results A total of 74 mediastinal LNs were obtained, including 33 metastatic LNs and 41 nonmetastatic LNs. The attenuation value at the lower energy levels of virtual monochromatic images (40–90 keV), K, and normalized iodine concentration demonstrated a significant difference between metastatic LNs and nonmetastatic LNs. The attenuation value at 40 keV was the most favorable biomarker for the diagnosis of mediastinal LN metastasis (area under curve, 0.91; sensitivity, 0.94; specificity, 0.81), which showed a much better performance than the LN diameter-based evaluation method (area under curve, 0.72; sensitivity, 0.66; specificity, 0.82; net reclassification improvement, 0.359; integrated discrimination improvement, 0.330). Conclusions Dual-energy computed tomography is a promising diagnostic approach for the diagnosis of mediastinal LN metastasis in patients with lung cancer, which may help clinicians implement personalized treatment strategies.
Prediction of Patient Height and Weight With a 3-Dimensional Camera

Objective The aim of this study was to determine accuracy of height and weight prediction by a 3-dimensional (3D) camera. Methods A total of 453 patients whose computed tomography imaging used a 3D camera from December 19, 2018 to March 19, 2019 were retrospectively identified. An image of each patient was taken before the computed tomography by a 3D camera mounted to the ceiling. Using infrared imaging and machine learning algorithms, patient height and weight were estimated from this 3D camera image. A total of 363 images were used for training. The test set consisted of 90 images. The height and weight estimates were compared with true height and weight to determine absolute and percent error. A value of P < 0.05 indicated statistical significance. Results There was 2.0% (SD, 1.4) error in height estimation by the 3D camera, corresponding to 3.35 cm (SD, 2.39) absolute deviation (P = 1, n = 86). Weight estimation error was 5.1% (SD, 4.3), corresponding to 3.99 kg (SD, 3.11) absolute error (P = 0.74, n = 90). Conclusion Pictures obtained from a 3D camera can accurately predict patient height and weight.
Improving Web Application Vulnerability Detection Leveraging Ensemble Fuzzing

: The vast majority of online services we use nowadays provide their web application to the users. The correctness of the source code of these applications is crucial to prevent attackers from exploiting its vulnerabilities, leading to severe consequences like the disclosure of sensitive information or the degradation of the availability of the application. Currently, multiple existent solutions analyse and detect vulnerabilities in the source code. Attackers, however, do not usually have access to the source code and must work with the information that is made public. Their goals are clear – exploit vulnerabilities without accessing the code –, and they resort of black-box fuzzing tools to achieve such. In this paper, we propose an ensemble fuzzing approach to check the correctness of the web applications from the point of view of an attacker and, in a posterior phase, analyse the source code to correlate with the collected information. The approach focuses ﬁrst on the quality of fuzzers’ crawlers and afterwards on fuzzers capabilities of exploiting the results of all crawlers between them, in order to provide better coverage and precision in the detection of web vulnerabilities. Our preliminary results show that the ensemble performs better than fuzzers individually.
Unified Model for Paraphrase Generation and Paraphrase Identification

Paraphrase Generation is one of the most important and challenging tasks in the field of 1 Natural Language Generation. The paraphrasing techniques help to identify or to extract/generate 2 phrases/sentences conveying the similar meaning. The paraphrasing task can be bifurcated into 3 two sub-tasks namely, Paraphrase Identification (PI) and Paraphrase Generation (PG). Most of 4 the existing proposed state-of-the-art systems have the potential to solve only one problem at a 5 time. This paper proposes a light-weight unified model that can simultaneously classify whether 6 given pair of sentences are paraphrases of each other and the model can also generate multiple 7 paraphrases given an input sentence. Paraphrase Generation module aims to generate fluent and 8 semantically similar paraphrases and the Paraphrase Identification system aims to classify whether 9 sentences pair are paraphrases of each other or not. The proposed approach uses an amalgamation 10 of data sampling or data variety with a granular fine-tuned Text-To-Text Transfer Transformer (T5) 11 model. This paper proposes a unified approach which aims to solve the problems of Paraphrase 12 Identification and generation by using carefully selected data-points and a fine-tuned T5 model. 13 The highlight of this study is that the same light-weight model trained by keeping the objective of 14 Paraphrase Generation can also be used for solving the Paraphrase Identification task. Hence, the 15 proposed system is light-weight in terms of the model’s size along with the data used to train the 16 model which facilitates the quick learning of the model without having to compromise with the 17 results. The proposed system is then evaluated against the popular evaluation metrics like BLEU 18 (BiLingual Evaluation Understudy):, ROUGE (Recall-Oriented Understudy for Gisting Evaluation), 19 METEOR, WER (Word Error Rate), and GLEU (Google-BLEU) for Paraphrase Generation and 20 classification metrics like accuracy, precision, recall and F1-score for Paraphrase Identification 21 system. The proposed model achieves state-of-the-art results on both the tasks of Paraphrase 22 Identification and paraphrase Generation. 23
Circuit QED with Carbon-Nanotube-Based Superconducting Quantum Circuits

Matthias Mergenthaler, 2, ∗ Ani Nersisyan, Andrew Patterson, Martina Esposito, Andreas Baumgartner, Christian Schönenberger, G. Andrew D. Briggs, Edward A. Laird, 2 and Peter J. Leek † Clarendon Laboratory, Department of Physics, University of Oxford, Oxford OX1 3PU, United Kingdom Department of Materials, University of Oxford, Oxford OX1 3PH, United Kingdom Department of Physics, University of Basel, Klingelbergstrasse 82, CH-4056 Basel, Switzerland Department of Physics, Lancaster University, Lancaster LA1 4YB, United Kingdom (Dated: April 21, 2021)
Automatic Hierarchical Arrangement of Vector Designs

We present a method that transforms an unstructured vector design into a logical hierarchy of groups of objects. Each group is a meaningful collection, formed by proximity in visual characteristics (like size, shape, color, etc.) and spatial location of objects and models the grouping principles designers use. We ﬁrst simplify the input design by partially or completely ﬂattening it and isolate duplicate geometries in the design (for example, repeating patterns due to copy and paste operations). Next we build the object containment hierarchy by assigning objects that are wholly enclosed inside the geometry of other objects as children of the enclosing parent. In the ﬁnal clustering phase, we use agglomerative clustering to obtain a bottom-up hierarchical grouping of all objects by comparing and ranking all pairs of objects according to visual and spatial characteristics. Spatial proximity segregates far apart objects, but when they are identical (or near identical) designers generally prefer to keep (and edit) them together. To accommodate this, we detect near identical objects and group them together during clustering despite their spatial separation. We further restrict group formation so that z-order disturbances in the design keep the visual appearance unaffected for tightly-overlapping geometry. The generated organization is equivalent to the original design and the organization results are used to facilitate abstract navigation (hierarchical, lateral or near similar) and selections in the design. Our technique works well with a variety of input designs with commonly identiﬁable objects and structural patterns.
Intergenerational Exchange of Time and Money: Short-term Reciprocity in Parent-Child Relationships

Long-term concepts of parent-child reciprocity assume that the amount of support given and received is only balanced in a generalized fashion over the life course. We argue that reciprocity in parent-child relationships also operates in the short term. Our analysis of short-term reciprocity focuses on concurrent exchange in its main upward and downward currencies, time and money. Fixed-effects models with data from SHARE (N= 8,816 dyads) revealed that within a family, parents gave financial transfers to those children who supported them with time transfers of help and care. Reciprocal patterns emerged most clearly if parents were highly dependent, received intense support, and had sufficient financial opportunities to reciprocate. We conclude that short-term reciprocity eases the burden of late parent-child relationships.
Interactive Monte Carlo denoising using affinity of neural features

High-quality denoising of Monte Carlo low-sample renderings remains a critical challenge for practical interactive ray tracing. We present a new learning-based denoiser that achieves state-of-the-art quality and runs at interactive rates. Our model processes individual path-traced samples with a lightweight neural network to extract per-pixel feature vectors. The rest of our pipeline operates in pixel space. We define a novel pairwise affinity over the features in a pixel neighborhood, from which we assemble dilated spatial kernels to filter the noisy radiance. Our denoiser is temporally stable thanks to two mechanisms. First, we keep a running average of the noisy radiance and intermediate features, using a per-pixel recursive filter with learned weights. Second, we use a small temporal kernel based on the pairwise affinity between features of consecutive frames. Our experiments show our new affinities lead to higher quality outputs than techniques with comparable computational costs, and better high-frequency details than kernel-predicting approaches. Our model matches or outperfoms state-of-the-art offline denoisers in the low-sample count regime (2--8 samples per pixel), and runs at interactive frame rates at 1080p resolution.
Transcriptomic Analysis of Honey Bees Exposed to Organosilicone

Honey bees play an important role in agriculture and the decline of honey bee populations worldwide has generated concern. While the application of pesticides in agricultural settings is often implicated in the deterioration of honey bee population health , pesticide applications contain more than just pesticides; they also contain adjuvants that may have detrimental effects to bee health. One known effect of one type of adjuvant is the suppression of immunity-related genes and consequent increase of viral load in larvae. We investigate the effects of one class of adjuvant, organosilicone surfactants (OSS), on adult honey bee health. In a laboratory based bioassay, adult honey bees were fed various concentrations of an OSS (Xiameter® OFX-0309) , alone and with a pesticide (Alticor®) and a fungicide (Tilt®). While survival of the bees was not affected by feeding regimes , bees ate significantly less diet on average if they were fed OSS at certain concentrations indicating that bees that are exposed to these chemicals may suffer due to low food consumption. We then extracted and sequenced RNA from the bioassay bees to determine transcriptome profiles in bees from each feeding treatment. We found significant downregulation of some genes involved in metabolism in response to the pesticides and upregulation of a cytochrome P450 in response to the pesticides and OSS. In response to adjuvant exposure , serine protease snake was upregulated a protein involved in innate immunity via activation of the Toll receptor and Rel pathway. OSS appears to interact synergistically with pesticides to exacerbate deleterious changes in gene expression.
Microsoft Word-15240917-file00.docx

Yuanming Wang, Haiyan Huang, and Qiang Wu Key Laboratory of Systems Biomedicine (Ministry of Education), Center for Comparative Biomedicine, Institute of Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China; (YW, HH, QW) State Key Laboratory of Oncogenes and Related Genes, Shanghai Cancer Institute, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200240, China; (YW, HH, QW) Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Bio-X Center, School of Life Sciences and Technology, Shanghai Jiao Tong University, Shanghai 200240, China (YW, HH, QW) Molecular Pharmacology Fast Forward. Published on April 11, 2014 as doi:10.1124/mol.113. 091462
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces

The classical theory of reinforcement learning (RL) has focused on tabular and linear representations of value functions. Further progress hinges on combining RL with modern function approximators such as kernel functions and deep neural networks, and indeed there have been many empirical successes that have exploited such combinations in large-scale applications. There are profound challenges, however, in developing a theory to support this enterprise, most notably the need to take into consideration the exploration-exploitation tradeoff at the core of RL in conjunction with the computational and statistical tradeoffs that arise in modern function-approximation-based learning systems. We approach these challenges by studying an optimistic modification of the least-squares value iteration algorithm, in the context of the action-value function represented by a kernel function or an overparameterized neural network. We establish both polynomial runtime complexity and polynomial sample complexity for this algorithm, without additional assumptions on the data-generating model. In particular, we prove that the algorithm incurs an e O( FH p T ) regret, where F characterizes the intrinsic complexity of the function class F , H is the length of each episode, and T is the total number of episodes. Our regret bounds are independent of the number of states, a result which exhibits clearly the benefit of function approximation in RL.
IN SITU THERMAL INSPECTION OF AUTOMATED FIBER PLACEMENT OPERATIONS FOR TOW AND PLY DEFECT DETECTION

The advent of Automated Fiber Placement (AFP) systems have aided the rapid manufacturing of composite aerospace structures. One of the challenges that AFP systems pose is the uniformity of the deposited prepreg tape layers, which complicates detection of laps, gaps, overlaps and twists. The current detection method used in industry involves halting fabrication and performing a time consuming, visual inspection of each tape layer. Typical AFP systems use a quartz lamp to heat the base layer to make the surface tacky as it deposits another tape layer. The innovation proposed in this paper is to use the preheated base layer as a through-transmission heat source for inspecting the newly added tape layer in situ using a thermographic camera mounted on to the AFP hardware. Such a system would not only increase manufacturing throughput by reducing inspection times, but it would also aid in process development for new structural designs or material systems by providing data on as-built parts. To this end, a small thermal camera was mounted onto an AFP robotic research platform at NASA, and thermal data was collected during typical and experimental layup operations. The data was post processed to reveal defects such as tow overlap/gap, wrinkling, and peel-up. Defects that would have been impossible to detect visually were also discovered in the data, such as poor/loss of adhesion between plies and the effects of vacuum debulking. This paper will cover the results of our experiments, and the plans for future versions of this inspection system.
Toward a Synergistic Framework for Human-Robot Coexistence and Collaboration (HRC 2 )

—This paper presents a proof of concept for a synergistic framework for human-robot coexistence and collaboration (HRC 2 ). By exploiting the loco-manipulation potential of our recently developed MObile Collaborative robotic Assistant (MOCA), we developed a novel framework that distinguishes and suitably reacts to coexisting and collaborative human partners. The framework avoids any collisions or physical contacts with coexisting partners while enabling ergonomic physical interactions with the collaborative-identiﬁed ones. The selection of the collaborative partners is achieved through body gestures.
Finite element formulations for constrained spatial nonlinear beam theories

A new director-based finite element formulation for geometrically exact beams is proposed by weak enforcement of the orthonormality constraints of the directors. In addition to an improved numerical performance, this formulation enables the development of two more beam theories by adding further constraints. Thus, the paper presents a complete intrinsic spatial nonlinear theory of three kinematically different beams which can undergo large displacements and which can have precurved reference configurations. Moreover, the hyperelastic constitutive laws allow for elastic finite strain material behavior of the beams. Furthermore, the numerical discretization using concepts of isogeometric analysis is highlighted in all clarity. Finally, all presented models are numerically validated using exclusive analytical solutions, existing finite element formulations, and a complex dynamical real-world example.
Endoscopic identification of colorectal cancer margin by indocyanine green fluorescence imaging

AIM: We assessed whether indocyanine green (ICG) fluorescence is effective for endoscopic tattooing in colorectal cancer surgery using a photodynamic eye (PDE) camera and fluorescent endoscope. METHODS: Between June 2014 and February 2018, 39 patients-17 patients with early and 22 patients with advanced colorectal cancer respectively-were enrolled and underwent preoperatively colonoscopic tattooing using 0.5 mL/time (n = 28 cases) or 0.3 mL/time (n = 11 cases) of ICG three days before laparotomy or laparoscopic surgery. We observed lesions using a PDE camera or a fluorescent endoscope during laparotomy or laparoscopic surgery. Moreover, we assessed the fluorescent luminance and fluorescent size of resected lesions intra- and post-operatively, respectively. Patients’ medical records and operation videos were retrospectively assessed to evaluate the visibility, duration, and adverse effects of tattooing. RESULTS: It was possible to obtain a useful fluorescent image with ICG fluorescent labeling and to determine the resection range in all cases. No difference regarding the distance from cancer’s oral margin to the ICG oral margin according to the volume of ICG (0.5 mL/time vs. 0.3 mL/time) was observed, but a significant difference concerning the distance from cancer’s oral margin to the ICG oral margin between early colorectal cancer and advanced cancer was noted (p = 0.0038). CONCLUSION: In our experience, the ICG fluorescence imaging system seems to be simple, safe, and effective. However, the use of ICG fluorescence in endoscopic tattooing necessitates the exploration of additional information such as the volume of the ICG solution and the timing of the ICG injection.
Interoceptive Awareness: Metaphorical Mapping & Bodily Experiences for Insourcing Tuning

The growing HCI interest in the role of the body and bodily experiences in design has led to new interactive technologies or design methods harnessing them. Despite this interest, interoceptive awareness has been limitedly explored in HCI research. This paper offers a reflection on technologies and design methods supporting interoceptive awareness that I have explored and designed with my research group, with a focus on how these may support insourcing tuning .
The differences in the number of fibroblasts and blood vessels after the topical and systemic administration of Lactobacillus casei Shirota probiotics for the treatment of traumatic ulcers in Wistar rats (Rattus norvegicus)

Background and Aim: The use of drugs as a therapy for traumatic ulcers may lead to drug resistance and other side effects. Lactobacillus casei Shirota can affect the number of fibroblasts and blood vessels in wound healing. The aim of this study was to investigate the difference in the number of fibroblast cells and blood vessels after the topical and systemic administration of L. casei Shirota probiotics in Wistar rats with traumatic ulcer. Materials and Methods: Overall, 36 healthy male Wistar rats aged 2-3 months old and weighing 175-250 g in body weight were used as a sample. Traumatic ulcer was made on the labial fornix incisive inferior. The subject rats were divided into groups: (1) A control group over 3 days, (2) a group that used distilled water over 7 days, (3) a group that underwent topical treatment over 3 days, (4) a group that used probiotics administered topically over 7 days, (5) a group that underwent systemic treatment over 3 days, and (6) a group that took oral probiotics for the traumatic ulcers over 7 days. The number of fibroblasts and blood vessels was observed through a hematoxylin-eosin examination. Results: Based on the results of the study, a significant difference was observed in the number of fibroblasts (p=0.00) and blood vessels (p=0.018) in the 3-day topical group that underwent a 3-day systemic administration of probiotics compared with the number of fibroblast cells in the 7-day topical group and 7-day systemic group (p=0.00). Conclusion: Overall, significant differences were observed in the number of fibroblasts and blood vessels in Wistar rats with traumatic ulcer after undergoing the topical and systemic administration of L. casei Shirota probiotics.