Miracle-dz/UniFAR-FTUs huggingface dataset:
Unmet Nutritional and Psychological Needs of Cancer Patients: An Integrated Multi-Professional Model Approach

Simple Summary This paper reports the design and exploitation of an integrated approach aimed at addressing the nutritional and psychological needs of cancer patients. In particular, patients recruited for the study undertook a path through which their nutritional and psychological status was assessed, improved and reinforced, ultimately leading to ameliorating their quality of life and, eventually, the outcome of their disease. Abstract This paper presents a multi-professional integrated approach toward the recognition and management of the nutritional and psychological needs of cancer patients. In particular, the patients undertook a multi-professional, multistep process that included the collection of both personal and clinical data, the evaluation of anthropometric measures, nutritional status and psychometric indices, and an ensuing personalized nutritional prescription and psychological support, ultimately leading to combined nutritional and psychological interventions to control their adherence to a nutritional program and to consolidate motivation to change. Overall, 120 patients were recruited for the study. The majority (84.2%) were female. Breast cancer was by far the most frequent malignancy (52.5%), followed by colorectal (17.5%), pancreatic (9.2%), ovarian (9.2%) and lung (5.0%) cancers. The results of the nutritional and psychological screening at baseline indicated that only 35% of patients had a normal BMI, whilst a relatively high proportion (nearly 32%) was overweight or obese (25%). The INRAN and MEDI-LITE questionnaires, which were used to assess the eating habits and adherence to a Mediterranean diet, respectively, revealed a mixed prevalence of cereals/cereal-based, fresh/processed meat, and fish or fishery food, with a medium–low adherence to the Mediterranean diet in nearly 38% of patients. The BUT, HADS and SF-36 tests, which were used to assess psychological disturbances, showed that 37.5% of patients had disorders regarding body image, 29.2% had abnormal anxiety and 20.0% had a depressive state, while no significant association was observed between the SF-36 PCS and MCS and the patients′ characteristics. The results of the potential impact of this novel approach on the QoL of patients after completion of the course are awaited with expectation.
Preclinical Assessment of the Combination of PSMA-Targeting Radionuclide Therapy with PARP Inhibitors for Prostate Cancer Treatment

Prostate specific membrane antigen targeted radionuclide therapy (PSMA-TRT) is a promising novel treatment for prostate cancer (PCa) patients. However, PSMA-TRT cannot be used for curative intent yet, thus additional research on how to improve the therapeutic efficacy is warranted. A potential way of achieving this, is combining TRT with poly ADP-ribosylation inhibitors (PARPi), which has shown promising results for TRT of neuroendocrine tumor cells. Currently, several clinical trials have been initiated for this combination for PCa, however so far, no evidence of synergism is available for PCa. Therefore, we evaluated the combination of PSMA-TRT with three classes of PARPi in preclinical PCa models. In vitro viability and survival assays were performed using PSMA-expressing PCa cell lines PC3-PIP and LNCaP to assess the effect of increasing concentrations of PARPi veliparib, olaparib or talazoparib in combination with PSMA-TRT compared to single PARPi treatment. Next, DNA damage analyses were performed by quantifying the number of DNA breaks by immunofluorescent stainings. Lastly, the potential of the combination treatments was studied in vivo in mice bearing PC3-PIP xenografts. Our results show that combining PSMA-TRT with PARPi did not synergistically affect the in vitro clonogenic survival or cell viability. DNA-damage analysis revealed only a significant increase in DNA breaks when combining PSMA-TRT with veliparib and not in the other combination treatments. Moreover, PSMA-TRT with PARPi treatment did not improve tumor control compared to PSMA-TRT monotherapy. Overall, the data presented do not support the assumption that combining PSMA-TRT with PARPi leads to a synergistic antitumor effect in PCa. These results underline that extensive preclinical research using various PCa models is imperative to validate the applicability of the combination strategy for PCa, as it is for other cancer types.
Network Pharmacology and Molecular Docking Analysis on Mechanisms of Isobavachalcone in Parkinson’s Disease

Objective: To use bioinformatics methods to identify the target genes of isobavachalcone (ISO) in Parkinson’s disease (PD), and to construct pharmacology network to characterize the underlying mechanism of ISO in PD. Methods: Potential targets of ISO, as well as related genes of PD were obtained from the public databases, the potential targets and signaling pathways were determined by protein-protein interaction (PPI), gene ontology (GO) and KEGG pathway enrichment analyses. And the network among ISO, PD and their co-targets was constructed using Cytoscape 3.3. 0. AutoDock Tools and PyMOL software were applied for molecular docking. Results: 34 potential targets of ISO related to PD were predicted using the public databases. PPI network showed that AKT1, PTGS2, EGFR, HSP90AA1, APP, SNCA, ACHE, BACE1, AKR1B1, MAOB, ABCB1 and PTGES were considered to as hub genes. Through enrichment analysis, ISO was found to exert its potential therapeutic effects on PD through several pathways. Molecular docking showed that ISO might bind to the key PD-associated amyloid protein, α-synuclein. Conclusion: Altogether, this study preliminarily investigated the pharmacological effects of ISO on PD and its potential underlying therapeutic mechanisms mediated by multiple targets and pathways.
Selective Laser Melting of Free-Assembled Stainless Steel 316L Hinges: Optimization of Volumetric Laser Energy Density and Joint Clearance

Selective laser melting technology is one of the metal additive manufacturing technologies that can convert metal powder to complex parts without the assembly process. This study aims to optimize the volumetric laser energy density for printing 3D metal objects with hinges geometry. The material is stainless steel 316L powder. The volumetric laser energy densities ranging from 4.1 J/mm3 to 119.1 J/mm3 are applied to fabricate 3D free-assembled hinges with various clearances of 0.38 mm, 0.39 mm, 0.40 mm, and 0.41 mm and investigate the relationship between volumetric laser energy density and clearance. A multibody model, consisting of nine segments with eight hinges, is proposed to be printed with the optimized volumetric laser energy density. The optical microscope and the hardness test are performed to observe the porosity and hardness property of the SLMed object. The result shows that laser energy densities between 105.5 J/mm3 and 119.1 J/mm3 can produce the high densification of SLMed objects with a porosity defect of 0.24% to 0.20% and hardness in the range of 207 HV to 215 HV. The optimization of laser energy densities is in the range of 105.5 J/mm3 to 119.1 J/mm3, which can be used to fabricate the movable hinges with a minimum clearance size of 0.41 mm. The proposed dinosaur object is printed successfully and all joints are rotatable.
SOFT2: Stereo Visual Odometry for Road Vehicles Based on a Point-to-Epipolar-Line Metric

Accurate localization constitutes a fundamental building block of any autonomous system. In this article, we focus on stereo cameras and present a novel approach, dubbed SOFT2, that is currently the highest-ranking algorithm on the KITTI scoreboard. SOFT2 relies on the constraints imposed by the epipolar geometry and kinematics, i.e., it is developed for configurations that cannot exhibit pure rotation. We minimize point-to-epipolar-line distances, which makes the approach resilient to object depth uncertainty, and as the first step, we estimate motion up to scale using just a single camera. Then, we propose to jointly estimate the absolute scale and the extrinsic rotation of the second camera in order to alleviate the effects of varying stereo rig extrinsics. Finally, we smooth the motion estimates in a temporal window of frames by using the proposed epipolar line bundle adjustment procedure. We also introduce a multiple hypothesis feature-matching approach for self-similar planar surfaces that account for appearance change due to perspective. We evaluate SOFT2 and compare it to ORB-SLAM2, OV2SLAM, and VINS-FUSION on the KITTI-360 dataset, KITTI train sequences, Málaga Urban dataset, Oxford Robotics Car dataset, and Multivehicle Stereo Event Camera dataset.
On-orbit operations summary for the Deformable Mirror Demonstration Mission (DeMi) CubeSat

Microelectromechanical Systems (MEMS) Deformable Mirrors (DMs) are a key technology option for adaptive optics instruments for space applications because they provide high-precision wavefront control with small form-factor, low-power devices. The Deformable Mirror Demonstration Mission (DeMi) CubeSat demonstrated a MEMS DM in space for the first time in order to raise the Technology Readiness Level (TRL) of the technology for future space applications such as high-contrast imaging of exoplanets and optical communications. The DeMi payload demonstrated a 140-actuator MEMS DM from Boston Micromachines Corporation. DM performance was measured with a Shack Hartmann wavefront sensor (SHWFS). The DeMi CubeSat began on-orbit operations in July 2020 and has since met the mission goals of measuring individual actuator displacements to a precision of 12 nm and correcting wavefront errors in space to <100 nm RMS error. The DeMi mission has raised the TRL of MEMS DM technology from a 5 to a 9. This paper summarizes the DeMi payload design and the results from over a year of on-orbit operations. Individual actuator measurements from ground and space operations show the MEMS DM actuating in space with similar performance and measurement uncertainty to ground data with no dead or under-actuating actuators detected. Wavefront control experiments show the DeMi payload correcting thermal- and vibration-induced wavefront errors in space.
‘They can show you with their body’: affect, embodiment and access to learning

ABSTRACT Academic underachievement of students from disadvantaged backgrounds is an ongoing and unresolved problem. Schools serving vulnerable communities often fail to meaningfully engage their students who are often exposed to significant family and environmental adversities. However, where the educational landscape is overwhelmed with neoliberal processes of accountability and testing, education generally comes to be understood as a cognitive process with little attention to the bodily or affective dimensions of learning. This paper draws on new theoretical ideas in affect and embodiment to build a case for an embodied, affective and creative pedagogy for students who live with poverty and adversity. Specifically, I report on research that investigates how two teachers utilised Creative and Body-based (CBL) provocations to redesign curriculum for disadvantaged students in their sites. In utilising the analysis of two narrative portraits, I highlight examples of bodily affectivity as well as affective pedagogical practices that impact on students’ capacity to learn and teachers’ capacity to teach. Analysis suggests that embodied and creative approaches enable new forms of communication and learner identities through bodies, senses and imaginings. Such approaches provide much needed affective conditions that ‘hook’ students in, encourage dialogue and help them to realise their potential as learners. Outcomes of this work signal an epistemological and pedagogical shift toward understanding bodies and creativity as agents of learning and knowledge production. By engaging with notions of a ‘learning body’ potential exists to challenge neoliberal practices in complex classrooms and support young people to foster stronger connections, hope and a re-inspired aspiration to learn.
A Theoretical Scientific Programming Framework for Application of Linear Matrix Transformation in Plane Computer Graphics

Plane computer graphics are basic information carriers in many industrial scenarios, such as engineering simulation, automatic control, and software design. Plane computer graphics are generally a kind of digital signals guided by mathematical symbols, and each vertex of a plane computer graph forms a graph matrix. Therefore, linear matrix transformation serves as the most common algorithmic unit to realize various information processing operations. To improve ease of graph matrix computing in practical engineering scenarios, this paper proposes a theoretical scientific programming framework for application of linear matrix transformation in plane computer graphics. Firstly, theoretical basis of linear matrix transformation in homogeneous plane coordinates is displayed and analyzed. Then, the universal theorem about linear transformation of graph matrices is deduced, and corresponding proofs are also given. Finally, a case study is set up to demonstrate the main workflow of the proposed theoretical scientific programming framework. The simulative results reveal feasibility of the proposal.
Assembly, Annotation, and Comparative Whole Genome Sequence of Fusarium verticillioides Isolated from Stored Maize Grains

Fusarium verticillioides is a plant pathogenic fungus affecting a wide range of crops worldwide due to its toxigenic properties. F. verticillioides BIONCL4 strain was isolated from stored maize grain samples in India, and produces high amount of fumonisin B1 (FB1). We report a comparative genomic analysis of F. verticillioides, covering the basic genome information, secretome, and proteins involved in host–pathogen interactions and mycotoxin biosynthesis. Whole-genome sequencing (WGS) was performed using the Illumina platform with an assembly size of 42.91 Mb, GC content of 48.24%, and 98.50% coverage with the reference genome (GCA000149555). It encodes 15,053 proteins, including 2058 secretory proteins, 676 classical secretory proteins, and 569 virulence and pathogenicity-related proteins. There were also 1447 genes linked to carbohydrate active enzymes (CaZymes) and 167 genes related to mycotoxin production. Furthermore, F. verticillioides genome comparison revealed information about the species’ evolutionary history. The overall study helps in disease prevention and management of mycotoxins to ensure food safety.
Perturbation Theory for the Solution of Systems of Linear Equations

Abstract : We present expressions for absolute and relative errors in individual components of the solution to systems of linear equations. We consider three kinds of linear systems: non-singular, underdetermined of full row rank, and least squares of full column rank. No assumptions regarding the structure or distribution of the perturbations are required. Our expressions for component- wise relative errors allow the following conclusions: For any linear system there is at least one solution component whose sensitivity to perturbations is proportional to the condition number of the matrix; but - depending on the relation between right-hand side and matrix - there may exist components that are much better conditioned. For a least squares problem, the sensitivity of the components also depends on the right-hand side and may be as high as the square of the condition number. Least squares problems are therefore always more receptive to ill-conditioning than linear systems. In addition, we show that the component-wise relative errors for linear systems are reduced by column scaling only if column scaling manages to reduce the perturbations. Regarding underdetermined linear systems of full column rank, the problem of finding the minimal-norm solution can be formulated so that the same analysis as for least squares problems is applicable here as well. Finally, we define component-wise condition numbers that measure the sensitivity of the solution components to perturbations. They have simple geometric interpretations and can be command estimated as efficiently as the conventional condition numbers.
Implementation of Circular Business Models for Olive Oil Waste and By-Product Valorization

Mediterranean olive oil producers have multiple incentives for adopting circular business models and better resource management, facing water scarcity and huge amounts of waste, but also seeing new opportunities for value creation. This article aimed to understand how circular business models valorizing olive oil waste and by-products are implemented. Ten business cases from six Mediterranean countries were studied, mainly based on semi-structured interviews with enterprise managers. Data were analyzed according to the business model canvas elements, success factors, and barriers while considering the institutional context. The results highlight the diversity of activities, types of resources used, and partnerships and products offered in different market segments. The principles of biowaste conversion and circularity, such as cascading, upcycling, recycling, and recovering, are all applied. The key success factors comprise an environmental concern, knowledge about biotechnologies, markets and logistics, a long-term commitment to the sector, local availability of resources, legislation, subsidies, and product acceptance by consumers. The main barriers include a lack of specific public financial support, an insufficient knowledge transfer from research to olive oil producers, and a lack of articulation of needs for research by the enterprises. More public-private collaborations and multi-stakeholder projects are needed for further shifting to a circular economy in the olive oil sector.
Targeted Co-Delivery of Gefitinib and Rapamycin by Aptamer-Modified Nanoparticles Overcomes EGFR-TKI Resistance in NSCLC via Promoting Autophagy

Acquired drug resistance decreases the efficacy of gefitinib after approximately 1 year of treatment in non-small-cell lung cancer (NSCLC). Autophagy is a process that could lead to cell death when it is prolonged. Thus, we investigated a drug combination therapy of gefitinib with rapamycin—a cell autophagy activator—in gefitinib-resistant NSCLC cell line H1975 to improve the therapeutic efficacy of gefitinib in advanced NSCLC cells through acute cell autophagy induction. Cell viability and tumor formation assays indicated that rapamycin is strongly synergistic with gefitinib inhibition, both in vitro and in vivo. Mechanistic studies demonstrated that EGFR expression and cell autophagy decreased under gefitinib treatment and were restored after the drug combination therapy, indicating a potential cell autophagy–EGFR positive feedback regulation. To further optimize the delivery efficiency of the combinational agents, we constructed an anti-EGFR aptamer-functionalized nanoparticle (NP-Apt) carrier system. The microscopic observation and cell proliferation assays suggested that NP-Apt achieved remarkably targeted delivery and cytotoxicity in the cancer cells. Taken together, our results suggest that combining rapamycin and gefitinib can be an efficacious therapy to overcome gefitinib resistance in NSCLC, and targeted delivery of the drugs using the aptamer-nanoparticle carrier system further enhances the therapeutic efficacy of gefitinib.
Exploring the Hot News on the Internet Based on Recommendation Algorithm for College Students’ Ideological and Political Education

College students are the main group of Internet users. With the development of electronic technology and mobile communication technology in China, most college students can easily use computers to access the Internet, and almost all college students use mobile phones, and using mobile phones to access the Internet has become very common in Colleges and universities. The effect is more obvious, and it is easier for ideological and political educators to understand the real situation. In order to further improve the performance of the interest point recommendation algorithm, this paper proposes a time feature-oriented interest point recommendation algorithm. The basic methods of user-based collaborative filtering are given, the functions of spatio-temporal features are described, respectively, the corresponding model representation is given to fuse spatio-temporal features, and a joint recommendation algorithm is proposed. Experiments show that compared with other related algorithms, this algorithm has higher accuracy and recall and is more suitable for the recommendation service of points of interest.
Domain Invariant Feature Learning for Speaker-Independent Speech Emotion Recognition

In this paper, we propose a novel domain invariant feature learning (DIFL) method to deal with speaker-independent speech emotion recognition (SER). The basic idea of DIFL is to learn the speaker-invariant emotion feature by eliminating domain shifts between the training and testing data caused by different speakers from the perspective of multi-source unsupervised domain adaptation (UDA). Specifically, we embed a hierarchical alignment layer with the strong-weak distribution alignment strategy into the feature extraction block to firstly reduce the discrepancy in feature distributions of speech samples across different speakers as much as possible. Furthermore, multiple discriminators in the discriminator block are utilized to confuse the speaker information of emotion features both inside the training data and between the training and testing data. Through them, a multi-domain invariant representation of emotional speech can be gradually and adaptively achieved by updating network parameters. We conduct extensive experiments on three public datasets, i. e. , Emo-DB, eNTERFACE, and CASIA, to evaluate the SER performance of the proposed method, respectively. The experimental results show that the proposed method is superior to the state-of-the-art methods.
Enhancement of Syngas Production in Co-Pyro-Gasification of Biomass and Plastic Waste Materials: Computational Study

The process of co-pyro-gasification of biomass and plastics appears to have the potential for increasing syngas production for power generation and thus minimizing the impact of plastic waste on the environment. This study was based on co-pyro-gasification of selected natural/synthetic polymers and cocoa pod husks as biomass material to ascertain the optimal ratios for enhanced volatile yields. The results showed that gasification of pure biomass commenced at 1500 K, whereas gasification of mixed plastics and biomass started at much lower temperature of 1000 K accompanied with higher syngas yield. Single and multiple plastics produced the most syngas while double plastics had detrimental impact on syngas production. For instance, single plastics with polyethylene terephthalate achieved 65% increase in syngas yield. Mixed-plastics consisting of high-density polyethylene, low-density polyethylene, polypropylene, and polyethylene terephthalate, achieved an increase of 40% - 55% in syngas yield. Whereas antagonistic effects were observed in some double plastics systems such as polyethylene terephthalate and polypropylene. The results indicate that although plastics are instrumental in the thermodynamic equilibrium yields of syngas, the type of plastics and their groupings do also have a significant effect on the yields. Experimental study is recommended to validate the feed proportions for high syngas production.