Miracle-dz/UniFAR-FTUs huggingface dataset:
Dendritic Cell Vaccination of Glioblastoma: Road to Success or Dead End

Glioblastomas (GBM) are the most frequent and aggressive malignant primary brain tumor and remains a therapeutic challenge: even after multimodal therapy, median survival of patients is only 15 months. Dendritic cell vaccination (DCV) is an active immunotherapy that aims at inducing an antitumoral immune response. Numerous DCV trials have been performed, vaccinating hundreds of GBM patients and confirming feasibility and safety. Many of these studies reported induction of an antitumoral immune response and indicated improved survival after DCV. However, two controlled randomized trials failed to detect a survival benefit. This raises the question of whether the promising concept of DCV may not hold true or whether we are not yet realizing the full potential of this therapeutic approach. Here, we discuss the results of recent vaccination trials, relevant parameters of the vaccines themselves and of their application, and possible synergies between DCV and other therapeutic approaches targeting the immunosuppressive microenvironment of GBM.
Analyzing the Coupling from Radiating Slots in a Double-Layered Radial Line Slot Array Antenna

This paper investigates power coupling out of radiating slots in a double-layered circularly polarised radial line slot array (RLSA) antenna. The antenna is composed of three plates which form a folded radial waveguide and supports inward-travelling waves. Top plate of the antenna has radiating slots. The slots are designed to intercept the currents on the radial waveguide and produce a circularly polarised broadside beam. The slot length is varied using coupling factor in order to achieve a uniform aperture distribution. The simulation results show that the antenna has fairly uniform phase distribution in its near field. The far-field result indicates a peak directivity of 26.4 dBic at 20 GHz with a good pattern quality and a side lobe level of -21.8 dB.
Novel Targets for Drug Use in Eosinophilic Granulomatosis With Polyangiitis

Eosinophilic Granulomatosis with Polyangiitis (EGPA) is a rare autoimmune disease characterized by medium and small vessels inflammation. Cardiac vasculitic involvement is one of the most severe manifestations with a significant impact on patients' long-term prognosis: anyway, a specific therapeutic approach for heart involvement in EGPA has not been explored yet. Current regimen consists of a long-term therapy with high dose of glucocorticoids, causing the well-known related-adverse events; immunosuppressive drugs are used in patients with severe manifestations, with some limitations. New therapeutic approaches are needed for patients with refractory disease or contraindications to conventional therapies. The quest for the ideal therapy is going toward a more and more personalized approach: on the one hand, efforts are made to use already existing therapies in the most appropriate way; on the other hand, new insights into EGPA pathogenesis allow the discovery of new targets, as demonstrated by mepolizumab and rituximab, targeting eosinophils, and B-cell compartments. This review summarizes the emerging therapies used in EGPA, focusing on the most recent studies on biologics and analyzing their efficacy and safety.
GhPLP2 Positively Regulates Cotton Resistance to Verticillium Wilt by Modulating Fatty Acid Accumulation and Jasmonic Acid Signaling Pathway

Patatin-like proteins (PLPs) have non-specific lipid acyl hydrolysis (LAH) activity, which can hydrolyze membrane lipids into fatty acids and lysophospholipids. The vital role of PLPs in plant growth and abiotic stress has been well documented. However, the function of PLPs in plant defense responses against pathogens is still poorly understood. Here, we isolated and identified a novel cotton (Gossypium hirsutum) PLP gene GhPLP2. The expression of GhPLP2 was induced upon treatment with Verticillium dahliae, the signaling molecules jasmonic acid (JA) and ethylene (ETH) in cotton plants. Subcellular localization revealed that GhPLP2 was localized to the plasma membrane. GhPLP2-silenced cotton plants were more susceptible to infection by V. dahliae, while the overexpression of GhPLP2 in Arabidopsis enhanced its resistance to V. dahliae, which was apparent as mild symptoms, and a decrease in the disease index and fungal biomass. The hypersensitive response, deposition of callose, and H2O2 accumulation triggered by V. dahliae elicitor were reduced in GhPLP2-silenced cotton plants. The overexpression of GhPLP2 in Arabidopsis resulted in the accumulation of linoleic acid (LA, 18:2) and α-linolenic acid (ALA, 18:3) and facilitated the biosynthesis of JA and JA-mediated defensive responses. GhPLP2 silencing in cotton plants consistently reduced the accumulation of linoleic acid (LA, 18:2) and α-linolenic acid (ALA, 18:3) and suppressed the biosynthesis of JA and the defensive responses mediated by JA. These results indicate that GhPLP2 is involved in the resistance of cotton to V. dahliae by maintaining fatty acid metabolism pools for JA biosynthesis and activating the JA signaling pathway.
Synthesis of 15N‐labelled 3,5‐dimethylpyridine

15N‐labelled pyridines are liquid‐ and solid‐state nuclear magnetic resonance (NMR) probes for chemical and biological environments because their 15N chemical shifts are sensitive to hydrogen‐bond and protonation states. By variation of the type and number of substituents, different target pyridines can be synthesized exhibiting different pK a values and molecular volumes. Various synthetic routes have been described in the literature, starting from different precursors or modification of other 15N‐labelled pyridines. In this work, we have explored the synthesis of 15N 15N‐labelled pyridines using a two‐step process via the synthesis of alkoxy‐3,4‐dihydro‐2H‐pyran as precursor exhibiting already the desired pyridine substitution pattern. As an example, we have synthesized 3,5‐dimethylpyridine‐15N (lutidine‐15N) as demonstrated by 15N‐NMR spectroscopy. That synthesis starts from methacrolein, propenyl ether, and 15N‐labelled NH4Cl as nitrogen source.
S1366728921000286jra 864..878

First-language research suggests that new words, after initial episodic-memory encoding, are consolidated and hence become lexically integrated. We asked here if lexical consolidation, about word forms and meanings, occurs in a second language. Italian–English sequential bilinguals learned novel English-like words (e.g., apricon, taught to mean “stapler”). fMRI analyses failed to reveal a predicted shift, after consolidation time, from hippocampal to temporal neocortical activity. In a pause-detection task, responses to existing phonological competitors of learned words (e.g., apricot for apricon) were slowed down if the words had been learned two days earlier (i.e., after consolidation time) but not if they had been learned the same day. In a lexical-decision task, new words primed responses to semantically-related existing words (e.g., apricon-paper) whether the words were learned that day or two days earlier. Consolidation appears to support integration of words into the bilingual lexicon, possibly more rapidly for meanings than for forms.
Exact and Approximate Variance-Stabilizing Transformations for Two-Color Microarrays

Motivation. Durbin et al (2002), Huber et al (2002) and Munson (2001) independently introduced a family of transformations (the generalizedlog family) which stabilizes the variance of microarray data up to the first order. However, for data from two-color arrays, tests for differential expression require that the variance of the difference of transformed observations be constant, rather than that of the transformed observations themselves. Results. We introduce a transformation within the generalized-log family which stabilizes, to the first order, the variance of the difference of transformed observations. We also introduce transformations from the “started-log” and log-linear-hybrid families which provide good approximate variance stabilization of differences. Examples using control-control data show that any of these transformations may provide sufficient variance stabilization for practical applications, and all perform well compared to log ratios. Contact. bpdurbin@wald.ucdavis. edu
Using Agreement Statements to Identify

This paper is concerned with the task of finding majority opinion (MO) in UK House of Lords (UKHL) case law by analysing agreement statements (AS) that explicitly express the appointed judges’ acceptance of each other’s reasoning. We introduce a corpus of 300 UKHL cases in which the relevant AS and MO have been annotated by three legal experts; and we introduce an AI system that automatically identifies this AS and MO with a performance comparable to humans.
Paper Title (use style: paper title)

In this paper, a decentralized PV-BES coordination control method for Plug-n-Play (PnP) dc microgrid (MG) is proposed. With proposed control method, PV units can operate under dc bus voltage control when battery energy storage (BES) units are saturated due to SoC limit or charging/discharging power limit. The mode transition and power sharing are based on a communication-less manner. By bypassing communication, the MG system can become more flexible and reliable. The proposed control system contains controllers for PV converter and BES converter, respectively. The PV converter controller can achieve seamless mode transition between MPPT control and droop control. BES converter controller has a decoupled feature that a high-pass-filter (HPF) path could improve MG dynamic performance under generation-dominating mode. The BES HPF compensation overcomes the issue of poor dynamic performance under PV-dominating mode and makes the system more resistive to PV parameter variation. The Detailed design, analysis and implementation of the proposed PV-BES coordination control is provided in this paper. Simulation and experimental results have been provided to verify the concept and analytical study. Keywords—dc microgrid, modular microgrid, decentralized control, droop control
A Compact Multi-Probe Reverberation Chamber for Over-the-Air Testing

─ In this paper, a compact multi-probe reverberation chamber (RC) is proposed for over-the-air (OTA) testing. 16 probe antennas are used to reduce the measurement time. Typical parameters of the RC, such as field uniformity (FU), quality factor (Q factor), and independent samples are given. Total radiated power (TRP) and pattern correlation measurements have been performed to validate the RC system. Index Terms ─ Compact, multi-probe RC, OTA.
Distal Technologies Impact, Telehealth and Mhealth, on Type 1 Diabetes Self-Management: A Narrative Review

Aim To evaluate the possible influences of new technologies on quality of life, disease and complications management (self-management) in children, teenagers and young adults with type 1 diabetes mellitus (T1DM). Research design Narrative review. Materials and methods We performed a research through scientific/medical database: PubMed, Cinahl, The Cochrane Library, Proquest Central, Phych INFO and UpToDate, applying the following filters: studies in humans, English language and most recent publication (from 2007 to 2017). Only those responding to the following selection criteria have been selected: 1. Quantitative studies. 2. Use of quantitative evaluation tools, monitoring quality of life and self-management. 3. Reference population of age group less than 65 years old. 4. Focus on usefulness, satisfaction and technologies influence on quality of life and disease self-management of T1DM subjects (outcomes). Results Among the selected articles, only 7 were fitting the inclusion criteria of this review. Overall, despite some studies did not show significant differences in quality of life, results showed an increased frequency in Self Monitoring Bloog Glucse (SMBG) and an improved metabolic control with the use of new technologies, especially in young teenagers with T1DM. Conclusion The different studies showed the potential advantages and the overall feasibility of using new apps on mobile technologies, that appear to be mostlyeffective in young teenagers affected by chronic disease, such as T1DM. These data suggest to identify new effective and acImpatto delle tecnologie distali, Telehealth e mHealth, sul self management del diabete di tipo 1: una revisione narrativa Distal technologies impact, Telehealth and mHealth, on type 1 diabetes self-management: a narrative
COVID-19 Pandemic and its Implications on Education Systems in Tanzania

COVID-19 pandemic has become the greatest health challenge the world has faced since the Second World War. COVID19 pandemic has affected the world economy as well as social sector (health and education). This study examines how COVID-19 pandemic has affected the Education system in Tanzania. Particularly, it examines the impact of the pandemic on the aspects of schools governance, mode of delivery, and the curriculum. This study sees that despite the challenges of the COVID-19 pandemic, learning should continue. In this study governments and other non-state actors are advised to offer a substantial intervention in the aim of retaining a resilient education system for the post pandemic period. The study suggests strategies such as trying any possible low technology solutions, maintaining motivation to teachers and makes them a focus to the response, focusing on the most vulnerable, and helping parents to manage the home learning environment. Moreover, the study suggests that schools should envision applying learning strategies which seem to be more effective during school closure, invest in technology and track progress.
Environmental Accounting and Sustainable Financial Performance: Evidence from the Nigerian Petroleum Industry

The issue of Environmental degradation has attracted much research attention in the environmental science literature but much is left to be done in the area of how accounting captures environmental degradation costs in the annual reports in relation to the effects it has on the sustainable financial performance of firms in developing countries especially Nigeria. This paper therefore re-examine the effect of the neglected but important issue of Environmental accounting in the context of how it affect sustainable financial performance of firms in Nigeria. Using data from ten petroleum companies operating in the Niger – delta part of Nigeria over a period of 48 years(19702017) analyzed through the lenses of ordinary least square regression method, our finding sugests that environmental operating costs and environmental prevention costs have significant and negative effect on the performance of petroleum firms in Nigeria. However, we found important differences in the correlates of firms capital expenditure on sustainable financial performance. The finding of this study therefore have important implications for policy.
Design aspects of Bi2Sr2CaCu2O8+δ THz sources: optimization of thermal and radiative properties

Impedance matching and heat management are important factors influencing the performance of terahertz sources. In this work we analyze thermal and radiative properties of such devices based on mesa structures of a layered high-temperature superconductor Bi2Sr2CaCu2O8+δ. Two types of devices are considered containing either a conventional large single crystal or a whisker. We perform numerical simulations for various geometrical configurations and parameters and make a comparison with experimental data for the two types of devices. It is demonstrated that the structure and the geometry of both the superconductor and the electrodes play important roles. In crystal-based devices an overlap between the crystal and the electrode leads to appearance of a large parasitic capacitance, which shunts terahertz emission and prevents impedance matching with open space. The overlap is avoided in whisker-based devices. Furthermore, the whisker and the electrodes form a turnstile (crossed-dipole) antenna facilitating good impedance matching. This leads to more than an order of magnitude enhancement of the radiation power efficiency in whisker-based, compared to crystal-based, devices. These results are in good agreement with presented experimental data.
The Influence of Active Removal from Working Memory on Serial Dependence

Flexible control of the contents of working memory (WM) includes removing no-longer-relevant information. Although simply withdrawing attention offers a “passive” mechanism, empirical findings suggest that it is also possible to actively remove information from WM. In this Registered Report we tested evidence that the bias (serial dependence) that an item exerts on the subsequent trial will be opposite in sign—attraction vs. repulsion — depending on whether it was passively or actively removed, respectively. A repulsive bias would be consistent with a specific mechanism for active removal: a rapid adaptation-like modification of perceptual circuitry. In a preliminary study, trials of two types were administered in pairs, multi-item WM followed by 1-item delayed recall, and we evaluated serial dependence of the latter on items from the former. In the first trial of each pair, two memoranda were presented, then one was designated irrelevant, then a third memorandum was presented. The critical manipulation was whether the third item was presented at the same location as the now “irrelevant memory item” (IMI). Overlap between the two should prompt the active removal of the IMI, whereas nonoverlap might prompt just the withdrawal of attention. Whereas the IMI exerted the expected attractive bias on 1-item recall in the no-overlap condition, we found an (unexpected) repulsive bias in the overlap condition. Because repulsive biases have been attributed to the adaptation-like modification of perceptual circuitry, replication of this result in this Registered Report would provide independent evidence for this mechanism for active removal from WM. Interpretation of the Stage 2 results are complicated by the fact that the approved Registered Report, carried out online, generated data that failed to meet a basic sanity check, and were therefore uninterpretable. Consequently, a follow-up lab-based experiment using procedures similar to the Registered Report generated results consistent with the hypothesis of principal theoretical interest: The IMI in the overlap condition exerted a repulsive bias on the subsequent trial.
Multi-Omic Graph Transformers for Cancer Classification and Interpretation

Next-generation sequencing has provided rapid collection and quantification of ‘big’ biological data. In particular, multi-omics and integration of different molecular data such as miRNA and mRNA can provide important insights to disease classification and processes. There is a need for computational methods that can correctly model and interpret these relationships, and handle the difficulties of large-scale data. In this study, we develop a novel method of representing miRNA-mRNA interactions to classify cancer. Specifically, graphs are designed to account for the interactions and biological communication between miRNAs and mRNAs, using message-passing and attention mechanisms. Patient-matched miRNA and mRNA expression data is obtained from The Cancer Genome Atlas for 12 cancers, and targeting information is incorporated from TargetScan. A Graph Transformer Network (GTN) is selected to provide high interpretability of classification through self-attention mechanisms. The GTN is able to classify the 12 different cancers with an accuracy of 93.56% and is compared to a Graph Convolutional Network, Random Forest, Support Vector Machine, and Multilayer Perceptron. While the GTN does not outperform all of the other classifiers in terms of accuracy, it allows high interpretation of results. Multi-omics models are compared and generally outperform their respective single-omics performance. Extensive analysis of attention identifies important targeting pathways and molecular biomarkers based on integrated miRNA and mRNA expression.
MOBILE ENERGY AWARE CLUSTER BASED MULTI-HOP USING HYBRID SWARM BASED ROUTING PROTOCOL FOR HIERARCHICAL HETEROGENEOUS WSNS

: Wireless Sensor Networks (WSNs) are becoming one of the demanding platforms. Environmental or physical conditions are sensed and monitored by sensor nodes and these data are transmitted to base station using multi-hop routing. For enhancing network lifetime and stability, various cluster-based solutions are designed in recent days. For homogeneous networks, various energy efficient solutions are developed and for data communication, distance parameter are used. When compared with location and flat based routing protocols, better performance is shown by hierarchical heterogeneous cluster based energy efficient routing protocols. This because of the presence of heterogeneity of nodes with respect to sensor node’s energy level and it enhances network’s lifetime. In recent works, mobile sensor nodes are used for enhancing WSNs performance and functionality. In this paper, authors proposed a novel concept of mobile sensor nodes and it is termed as Mobile Energy Aware Cluster Based Multi-hop routing protocol for hierarchical heterogeneous WSNs. It selects CHs according to newly proposed probability equation which selects only that sensor node as Cluster Head (CH) which has highest energy among other sensor nodes. In MEACBM, after sensor nodes deployment and clusters formation, whole network area is divided into sectors and inside every sector a mobile sensor node is placed which act as Mobile Data Collector (MDC) and it collects data from CHs. This technique helps in significantly reducing sensor nodes energy consumption of for transferring
Master Computer Science Automatic Segmentation of Recordings for Text-to-Speech model training

Text-to-speech (TTS) synthesis models have seen a rapid development and are able to generate human-like speech with a high inference speed. Customized voices in TTS are very desirable for commercial speech platforms. People who currently intend to let the TTS engine speak in their own voice face three challenges: 1) how to segment their speech; 2) how to align their speech with the text they read; 3) how to select the high quality components of self-made speech for training. It is very time-consuming to tackle these three challenges manually, since the training of most TTS engines requires at least 24-hour of recorded and annotated speech. Aligning the text and speech would be a very labor-intensive work. We present an automatic recording segmentation strategy (ARS) to segment speech and align the speech to its corresponding text automatically. The segmentation results of ARS achieve a lower word error rate (0.220) in comparison to the manual segmentation (0.347). Additionally, experimental results demonstrated that a Transformer TTS engine trained with an ARS-processed dataset obtains a word error rate of 0.632 and a mean opinion score of 2.833 after a reasonable training time.