Miracle-dz/UniFAR-FTUs huggingface dataset:
Immune Activity and Response Differences of Oncolytic Viral Therapy in Recurrent Glioblastoma: Gene Expression Analyses of a Phase IB Study

Purpose: Previously, clinical trials of experimental virotherapy for recurrent glioblastoma multiforme (GBM) demonstrated that inoculation with a conditionally replication–competent Δγ134. 5 oncolytic herpes simplex virus (oHSV), G207, was safe. Following the initial safety study, a phase Ib trial enrolled 6 adult patients diagnosed with GBM recurrence from which tumor tissue was banked for future studies. Patients and Methods: Here, we analyzed tumor RNA sequencing (RNA-seq) data obtained from pre- and posttreatment (collected 2 or 5 days after G207 injection) biopsies from the phase Ib study patients. Results: Using a Spearman rank-order correlation analysis, we identified approximately 500 genes whose expression pattern correlated with survival duration. Many of these genes were enriched for the intrinsic IFN-mediated antiviral and adaptive immune functional responses, including immune cell chemotaxis and antigen presentation to T-cells. Furthermore, we show that the expression of several T-cell–related genes was highest in the patient with the longest survival after G207 inoculation. Conclusions: Our data support that the oHSV-induced type I IFN production and the subsequent recruitment of an adaptive immune response differed between enrolled patients and showed association with survival duration in patients with recurrent malignant glioma after treatment with an early generation oHSV.
Behind the Wheel

Driving confidence is thought to influence driving exposure among older drivers and may affect driver safety. Studies to date have relied primarily on self-reported measures of driving exposure to explore this relationship. The objective of this study was to explore the relationship between confidence and actual driving exposure among drivers aged 75 years and older. A cross-sectional analysis of survey data (function, confidence, personal circumstances) and naturalistic measures of driving exposure was conducted with 380 older drivers in northwest Sydney, Australia. Driving exposure, including total distance traveled, radius of travel from home, average trip distance, and nighttime driving, was measured for 1 week. The mean age of participants was 80 years. More males (n = 230) than females (n = 150) were enrolled. Successful instrumentation was achieved for 362 of 380 vehicles. Driving confidence was found to be independently associated with the farthest distance traveled from home, average trip distance, and night driving. Older drivers with lower confidence took shorter trips, stayed closer to home, and were less likely to drive at night. This study provided evidence of a responsive process in which drivers with lower confidence and poorer function were found to have different patterns of driving—specifically, driving in familiar areas, during daylight hours, and closer to home. It is likely that drivers in later life change their driving patterns to preserve safety and mobility. This understanding will help policy makers and educators shape responsive programs that help older drivers drive safely for as long as possible.
Numerical simulations and experimental analysis of a vehicle cabin and its occupants subjected to a mine blast

When military vehicles are subjected to a mine blast, the vehicles will be damaged and the occupants will be injured. The main objective of this paper is to analyse the responses of the floor-plate of the vehicle cabin and of its occupants subjected to the blast using numerical and experimental methods. A numerical analysis of the floor-plate of the vehicle cabin and of its occupants in the event of mine detonation under the vehicle cabin with LS-DYNA software was carried out, the shock wave from the mine was modelled approximately using LS-DYNA and the vehicle driver was represented by using a Hybrid III dummy. The simulations obtained most of the details of the model including the stress, the displacement, the velocity, the variation in the energy of the cabin’s floor-plate, the overpressure and the response of the dummy. Moreover, four tests at full-scale were completed on the specific vehicle subjected to shock waves that originated from the detonation of four different equivalent mine surrogates. Two different kinds of sensor (pressure sensors and dummy sensors) were used to measure the overpressure of vehicle and the response of the dummy. A comparison of the results shows good agreement between the numerical simulations and the experiments. The results show that the combination of these two methods can be used in blast modelling with a reasonable degree of accuracy. Also, the results provide insight into the vulnerability of the vehicle cabin and its occupants to the effects of blast mines and provide a good foundation for a subsequent optimization study of the model.
Information Compensation Based on Pulse Coupled Neural Network

Image Fusion is an enhancement technique, which aims to combine the images acquired by different sensors and generate informative images in order to make the subsequent processing easier or to help make decisions. The image fusion mission is done by the image fusion algorithm which is based on Pulse Coupled Neural Network and Discrete Cosine Transform. After the image fusion, information loss appears in part of fusion results, so some positions become empty. To solve this problem, this paper designs a compensation framework for image fusion. This framework aims to obtain better subjective effects and objective indicators. By comparing with the image information compensation methods of different parameters and different frames, the image after the image information compensation of the pulse coupled neural network has got a good visual effect, and the index is relatively excellent.
Preserving Addressability Upon GC-Triggered Data Movements on Non-Volatile Memory

This article points out an important threat that application-level Garbage Collection (GC) creates to the use of non-volatile memory (NVM). Data movements incurred by GC may invalidate the pointers to objects on NVM and, hence, harm the reusability of persistent data across executions. The article proposes the concept of movement-oblivious addressing (MOA), and develops and compares three novel solutions to materialize the concept for solving the addressability problem. It evaluates the designs on five benchmarks and a real-world application. The results demonstrate the promise of the proposed solutions, especially hardware-supported Multi-Level GPointer, in addressing the problem in a space- and time-efficient manner.
An Empirical Study of the Impact of Hyperparameter Tuning and Model Optimization on the Performance Properties of Deep Neural Networks

Deep neural network (DNN) models typically have many hyperparameters that can be configured to achieve optimal performance on a particular dataset. Practitioners usually tune the hyperparameters of their DNN models by training a number of trial models with different configurations of the hyperparameters, to find the optimal hyperparameter configuration that maximizes the training accuracy or minimizes the training loss. As such hyperparameter tuning usually focuses on the model accuracy or the loss function, it is not clear and remains under-explored how the process impacts other performance properties of DNN models, such as inference latency and model size. On the other hand, standard DNN models are often large in size and computing-intensive, prohibiting them from being directly deployed in resource-bounded environments such as mobile devices and Internet of Things (IoT) devices. To tackle this problem, various model optimization techniques (e.g., pruning or quantization) are proposed to make DNN models smaller and less computing-intensive so that they are better suited for resource-bounded environments. However, it is neither clear how the model optimization techniques impact other performance properties of DNN models such as inference latency and battery consumption, nor how the model optimization techniques impact the effect of hyperparameter tuning (i.e., the compounding effect). Therefore, in this paper, we perform a comprehensive study on four representative and widely-adopted DNN models, i.e., CNN image classification, Resnet-50, CNN text classification, and LSTM sentiment classification, to investigate how different DNN model hyperparameters affect the standard DNN models, as well as how the hyperparameter tuning combined with model optimization affect the optimized DNN models, in terms of various performance properties (e.g., inference latency or battery consumption). Our empirical results indicate that tuning specific hyperparameters has heterogeneous impact on the performance of DNN models across different models and different performance properties. In particular, although the top tuned DNN models usually have very similar accuracy, they may have significantly different performance in terms of other aspects (e.g., inference latency). We also observe that model optimization has a confounding effect on the impact of hyperparameters on DNN model performance. For example, two sets of hyperparameters may result in standard models with similar performance but their performance may become significantly different after they are optimized and deployed on the mobile device. Our findings highlight that practitioners can benefit from paying attention to a variety of performance properties and the confounding effect of model optimization when tuning and optimizing their DNN models.
Towards Robustness of Deep Program Processing Models—Detection, Estimation, and Enhancement

Deep learning (DL) has recently been widely applied to diverse source code processing tasks in the software engineering (SE) community, which achieves competitive performance (e.g., accuracy). However, the robustness, which requires the model to produce consistent decisions given minorly perturbed code inputs, still lacks systematic investigation as an important quality indicator. This article initiates an early step and proposes a framework CARROT for robustness detection, measurement, and enhancement of DL models for source code processing. We first propose an optimization-based attack technique CARROTA to generate valid adversarial source code examples effectively and efficiently. Based on this, we define the robustness metrics and propose robustness measurement toolkit CARROTM, which employs the worst-case performance approximation under the allowable perturbations. We further propose to improve the robustness of the DL models by adversarial training (CARROTT) with our proposed attack techniques. Our in-depth evaluations on three source code processing tasks (i.e., functionality classification, code clone detection, defect prediction) containing more than 3 million lines of code and the classic or SOTA DL models, including GRU, LSTM, ASTNN, LSCNN, TBCNN, CodeBERT, and CDLH, demonstrate the usefulness of our techniques for ❶ effective and efficient adversarial example detection, ❷ tight robustness estimation, and ❸ effective robustness enhancement.
Synthesis, Characterization, and Biodegradation of Novel Starch Grafted Zincated Nanoclay Polymer Biocomposites

ABSTRACT Novel starch grafted zincated nanoclay polymer bio-composites (SZNCPBCs) were synthesized with variable percentages (8%, 10%, and 12%) of clay and nanoclay, acrylic acid, and acrylic amide as monomers, N,N-Methylene bisacrylamide (NNMBA) as crosslinker and ammonium persulfate (APS) as initiator. Clays, as well as SZNCPBCs were characterized viz. X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM), and Fourier transform infrared spectroscopy (FTIR). Nanocomposite containing 12% nanoclay showed the slowest release rate. However, 8% clay containing nanocomposite recorded higher Olsen-P content and equilibrium water absorbency. SZNCPBCs proved to be an innovative controlled release Zn fertilizer formulation. GRAPHICAL ABSTRACT
Defining and Cultivating International Mindedness: Perceptions and Perspectives of Students in the International Baccalaureate Middle Years Program

Abstract This article explores how international-mindedness is defined and cultivated in the International Baccalaureate (IB) Middle Years Program (MYP) schools in different regions of the world as young adolescents face their main developmental task of identity development. An online survey that contained demographic and open-ended questions was administered to MYP students. Mixed methods design and data analysis provided insight into the ways international-mindedness is experienced and developed within the IB community. Open-ended responses were analyzed using thematic analysis from which a grounded theory emerged. The most frequently mentioned themes in defining international-mindedness were understanding, awareness, and acceptance of different others. Respondents emphasized that family and school experiences were the main factors that influenced their international-mindedness with travel being frequently mentioned in both. Factors, such as make-up of participants’ families, their history of moving internationally, and the advice and modeling provided by parents and extended family as well as school experiences (e.g., field trips, debates, multicultural classrooms, curriculum focus) significantly contributed to their high self-ranked stance on the developmental continuum of international-mindedness. Consistency in responses across the regions demonstrate a paradigmatic understanding of international-mindedness among the respondents.
Mucins form a nanoscale material barrier against immune cell attack

The cancer cell glycocalyx serves as a major line of defense against immune surveillance. However, how specific physical properties of the glycocalyx contribute to immune evasion and how these properties are regulated are not well understood. Here, we uncover how the surface density, glycosylation, and crosslinking of cancer-associated mucins contribute to the nanoscale material thickness of the glycocalyx, and further analyze the effect of the glycocalyx thickness on resistance to effector cell attack. Natural Killer (NK) cell-mediated cytotoxicity exhibits a near perfect inverse correlation with the glycocalyx thickness of target cells regardless of the specific glycan structures present. NK cells expressing a chimeric antigen receptor (CAR) have an enhanced ability to breach the glycocalyx and kill target cells. Equipping the NK cell surface with a mucin-digesting enzyme also improves killing with a performance enhancement that rivals or exceeds CARs in some cases. Together, our results provide new considerations for improving cancer immunotherapies.
GABABR agonist baclofen promotes central nervous system remyelination

Promoting remyelination - the endogenous response by which lost myelin sheaths are regenerated - is considered as a potential neuroprotective strategy to prevent/limit the development of permanent neurological disability in patients with multiple sclerosis (MS). To this end, a number of clinical trials are investigating the potential of existing drugs to enhance oligodendrocyte progenitor cell (OPC) differentiation, the process that fails in chronic MS lesions. As we previously reported that oligodendroglia lineage cells express GABAB receptors (GABABRs) both in vitro and in vivo, and that GABABR-mediated signaling enhances OPC differentiation and myelination in vitro, here we focused on the remyelinating potential of the best-known GABABR agonist baclofen (Bac), already approved to treat spasticity in MS. We demonstrated that Bac increases myelin protein production following lysolecithin (LPC)-induced demyelination in cerebellar ex vivo slices. In addition, Bac administration enhanced OPC differentiation and remyelination in LPC-induced spinal cord lesions in adult mice. Thus, our results suggest that Bac should be considered as a potential therapeutic agent, not only to treat spasticity, but also to improve remyelination in patients with MS.
Olfactory Neuroblastoma: Surgical Treatment Experience of 42 Cases

Objective Our purpose was to estimate the safety and effectiveness of the endoscopic endonasal approach (EEA) in olfactory neuroblastoma (ONB) and determine whether preservation of the dura and olfactory bulb could be considered in selected patients. Methods We retrospectively reviewed patients diagnosed with ONBs between July 2010 and June 2021 at our institution, and collected data on demographic, disease stage, surgical approach, overall survival (OS), disease-free survival (DFS), and postoperative complications. Results The study sample included 42 patients (8 treated for recurrence and 34 initial cases), 28 of which were men and 14 were women with a median age of 47.19 years. The mean duration from the beginning of treatment and follow-up time was 8.91 and 51 months, respectively. Among the 42 patients, 32 had unilateral lesions, and the rest had bilateral lesions. Patient symptoms were predominantly nasal, and four patients presented without any symptoms. The modified Kadish staging was A in three patients, B in 14 patients, C in 17 patients, and D in 8 patients. According to the preoperative examinations, five patients had cervical lymph node metastasis, and no patients had distant metastases. EEA was used in 38 patients, cranioendoscopic approach in 3, and open craniofacial approach in 1. The 5-year OS and DFS rates were 89.1 and 79.2%, respectively. The 2-year OS and DFS rates were both 89.1%. The overall surgical complication incidence was 9.52% (one cerebrospinal fluid rhinorrhea, one cervical hematoma, and two epileptic seizures). Conclusion The present results support the importance of earlier treatment for advanced ONB and the fact that it is safe and efficacious to treat ONBs via EEA. The preservation of the dura can be considered for select patients—specifically those without skull base involvement and who underwent postoperative comprehensive therapy.
Temperature-Dependent Reproductive Success of Stickleback Lateral Plate Morphs: Implications for Population Polymorphism and Range Shifts Under Ocean Warming

Changing environments associated with rapid climate change can shape direct measures of fitness such as reproductive success by altering mating behavior, fecundity and offspring development. Using a polymorphic oceanic population of threespine stickleback (Gasterosteus aculeatus), we investigated whether a 4°C increase in sea surface temperature influenced clutch siring success, reproductive output, and offspring growth among lateral plate morphs. Since low plated morphs are thought to have a selective advantage in warmer environments, we predicted that low plated males should have higher clutch siring success in +4°C environments, and that thermal plasticity of traits (e.g., egg size, offspring growth) should reflect different trait optima in different environments among plate morphs. Parentage analysis of egg clutches revealed temperature-specific clutch siring success, in that low plated males sired more clutches in +4°C environments and completely plated males sired more clutches at ambient (seasonal) temperature. Both completely and low plated females laid larger eggs when acclimated to +4°C, but only completely plated females had smaller clutches at +4°C. Offspring of low and partially plated females grew much less at +4°C compared to those of completely plated females. Taken together, our results demonstrate that ocean warming could impact reproductive success at various levels, with differential effects depending on phenotype, in this case, lateral plate morph. Some traits (clutch siring success, egg size) showed better performance for low plated fish at +4°C, whereas others (e.g., growth) did not. Higher clutch siring success of low plated males at elevated temperature might indicate a future shift in plate morph composition for polymorphic stickleback populations, with potential implications for colonization ability during range shifts under climate change.
Developmental Trajectory of Inattention and Its Association With Depressive Symptoms in Adolescence: Peer Relationships as a Mediator

This study investigated the developmental trajectory of inattention symptoms as a predictor of later depressive symptoms in adolescence, and examined potential mediating role of peer relationships in this process. Participants were adolescents who were part of the large longitudinal panel study on Korean Youths, Korean Children & Youth Panel Survey 2010 (KCYPS 2010) of the National Youth Policy Institute (NYPI). Specifically, data were drawn from two cohorts of KCYPS that differed in participant age (Panel 1: 2003 birth cohort, n = 2,342, 48.2% girls; Panel 2: 2000 birth cohorts, n = 2,378, 40.0% girls). We analyzed data collected from 2010 to 2016 when children in panel 1 were 6–7 to 12–13 years old, and children in panel 2 were 9–10 to 15–16 years old. Results of latent growth modeling (LGM) were as follows. In Panel 1, the inattention symptoms increased from 9–10 to 12–13 years. Otherwise, the inattention symptoms decreased from 11–12 to 15–16 years in panel 2. Additionally, in both panels, initial status and slope of inattention significantly predicted later levels of depressive symptoms, and peer relationships partly mediated the association between inattention trajectory and depressive symptoms. The findings are discussed with respect to considering the growth of inattention and the quality of peer relationships as promising targets for early identification and intervention of depression in adolescents.