Miracle-dz/UniFAR-FTUs huggingface dataset:
FusionNeoAntigen: a resource of fusion gene-specific neoantigens

Abstract Among the diverse sources of neoantigens (i.e. single-nucleotide variants (SNVs), insertions or deletions (Indels) and fusion genes), fusion gene-derived neoantigens are generally more immunogenic, have multiple targets per mutation and are more widely distributed across various cancer types. Therefore, fusion gene-derived neoantigens are a potential source of highly immunogenic neoantigens and hold great promise for cancer immunotherapy. However, the lack of fusion protein sequence resources and knowledge prevents this application. We introduce ‘FusionNeoAntigen’, a dedicated resource for fusion-specific neoantigens, accessible at https://compbio.uth. edu/FusionNeoAntigen. In this resource, we provide fusion gene breakpoint crossing neoantigens focused on ∼43K fusion proteins of ∼16K in-frame fusion genes from FusionGDB2.0. FusionNeoAntigen provides fusion gene information, corresponding fusion protein sequences, fusion breakpoint peptide sequences, fusion gene-derived neoantigen prediction, virtual screening between fusion breakpoint peptides having potential fusion neoantigens and human leucocyte antigens (HLAs), fusion breakpoint RNA/protein sequences for developing vaccines, information on samples with fusion-specific neoantigen, potential CAR-T targetable cell-surface fusion proteins and literature curation. FusionNeoAntigen will help to develop fusion gene-based immunotherapies. We will report all potential fusion-specific neoantigens from all possible open reading frames of ∼120K human fusion genes in future versions.
IMPACT OF SHOREFACE NOURISHMENT AND BREAKWATERS ON THE SEDIMENT PROCESSES OF THE LITHUANIAN NEARSHORE

Various measures have been used to protect coastal areas controlling beach erosion. During the last decades all over the world there has been many alternatives from engineering to soft coastal defence techniques, among which artificial beach nourishment and breakwaters are particularly popular. This study evaluates the changes of sediment processes in Lithuanian nearshore using two measures of shore protection: breakwaters and shoreface nourishment. The current study aims to estimate which measure is more effective in Lithuanian nearshore. For this purpose the calculations of sediment transport were done for breakwaters and nearshore berms separately (case study area is in Baltic Sea near Palanga). The analysis is based on the results of MIKE 21 modelling system (waves, hydrodynamic processes and sediment transport) under varying climatic conditions, especially in stormy weather that has the major impact on hydrodynamic and sediment processes.
Accelerated 2D Cartesian MRI with an 8‐channel local B0 coil array combined with parallel imaging

In MRI, the magnetization of nuclear spins is spatially encoded with linear gradients and radiofrequency receivers sensitivity profiles to produce images, which inherently leads to a long scan time. Cartesian MRI, as widely adopted for clinical scans, can be accelerated with parallel imaging and rapid magnetic field modulation during signal readout. Here, by using an 8‐channel local B0$$ {\mathrm{B}}_0 $$ coil array, the modulation scheme optimized for sampling efficiency is investigated to speed up 2D Cartesian scans.
Ibrutinib discontinuation and associated factors in a real-world national sample of elderly Medicare beneficiaries with chronic lymphocytic leukemia

Abstract Prior studies evaluating ibrutinib discontinuation are limited to clinical trials and selected medical centers and hence may not reflect real-world practice. This study used Medicare claims (2013–2019) to examine ibrutinib discontinuation and associated factors among elderly patients with chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL). Over a median follow-up of 2.1 years, two-thirds (65.2%) of the 11,870 new ibrutinib initiators were discontinued, with half (45.1%) of patients discontinuing within 12 months of initiation. Factors such as advanced age, lack of Part D low-income subsidy, evidence of prior CLL/SLL treatment, and cardiovascular comorbidities (e.g. atrial fibrillation) were associated with higher risk of discontinuation. Over a median of 1.2 years from discontinuation, 40% of discontinuers initiated another CLL/SLL treatment after ibrutinib discontinuation; 25% of patients restarted ibrutinib treatment at some point over follow-up. Our findings point to a large unmet need with the widely used BTKi ibrutinib and underscore the importance of ongoing development of efficacious and well-tolerated CLL/SLL therapies.
ASD2023: towards the integrating landscapes of allosteric knowledgebase

Abstract Allosteric regulation, induced by perturbations at an allosteric site topographically distinct from the orthosteric site, is one of the most direct and efficient ways to fine-tune macromolecular function. The Allosteric Database (ASD; accessible online at http://mdl.shsmu.edu.cn/ASD) has been systematically developed since 2009 to provide comprehensive information on allosteric regulation. In recent years, allostery has seen sustained growth and wide-ranging applications in life sciences, from basic research to new therapeutics development, while also elucidating emerging obstacles across allosteric research stages. To overcome these challenges and maintain high-quality data center services, novel features were curated in the ASD2023 update: (i) 66 589 potential allosteric sites, covering > 80% of the human proteome and constituting the human allosteric pocketome; (ii) 748 allosteric protein–protein interaction (PPI) modulators with clear mechanisms, aiding protein machine studies and PPI-targeted drug discovery; (iii) ‘Allosteric Hit-to-Lead,’ a pioneering dataset providing panoramic views from 87 well-defined allosteric hits to 6565 leads and (iv) 456 dualsteric modulators for exploring the simultaneous regulation of allosteric and orthosteric sites. Meanwhile, ASD2023 maintains a significant growth of foundational allosteric data. Based on these efforts, the allosteric knowledgebase is progressively evolving towards an integrated landscape, facilitating advancements in allosteric target identification, mechanistic exploration and drug discovery.
Efficacy and tolerability of add‐on stiripentol in real‐world clinical practice: An observational study in Dravet syndrome and non‐Dravet developmental and epileptic encephalopathies

Abstract Objective To assess efficacy and tolerability of stiripentol (STP) as adjunctive treatment in Dravet syndrome and non‐Dravet refractory developmental and epileptic encephalopathies (DREEs). Methods Retrospective observational study of all children and adults with DREE and prescribed adjunctive STP at Hospital Ruber Internacional from January 2000 to February 2023. Outcomes were retention rate, responder rate (proportion of patients with ≥50% reduction in total seizure frequency relative to baseline), seizure freedom rate, responder rate for status epilepticus, rate of adverse event and individual adverse events, reported at 3, 6, and 12 months and at final visit. Seizure outcomes are reported overall, and for Dravet and non‐Dravet subgroups. Results A total of 82 patients (55 Dravet syndrome and 27 non‐Dravet DREE) were included. Median age was 5 years (range 1–59 years), and median age of epilepsy onset was younger in the Dravet group (4.9 [3.6–6] months) than non‐Dravet (17.9 [6–42.3], P < 0.001). Median follow‐up time STP was 24.1 months (2 years; range 0.3–164 months) and was longer in the Dravet group (35.9 months; range 0.8–164) than non‐Dravet (17 months range 0.3–62.3, P < 0.001). At 12 months, retention rate, responder rate and seizure free rate was 68.3% (56/82), 65% [48–77%] and 18% [5.7–29%], respectively. There were no statistically significant differences between groups on these seizure outcomes. Adverse events were reported in 46.3% of patients (38/82), without differences between groups. Significance In this population of patients with epileptic and developmental encephalopathies, outcomes with adjunctive STP were similar in patients with non‐Dravet DREE to patients with Dravet syndrome.
Feasibility, safety, and efficacy of task-oriented mirrored robotic training on upper-limb functions and activities of daily living in subacute poststroke patients: a pilot study

BACKGROUND Robotic training with high repetitions facilitates upper-limb movements but provides fewer benefits for activities of daily living. Integrating activities of daily living training tasks and mirror therapy into a robot may enhance the functional gains of robotic training. AIM The aim of this study was to investigate the feasibility, safety, and efficacy of the task-oriented mirrored upper-limb robotic training on the upper-limb functions and activities of daily living of subacute poststroke patients. DESIGN This study is a single-blinded, active-controlled pilot study. SETTING The study was carried out at rehabilitation outpatient clinic and ward. POPULATION A total of 32 subacute poststroke patients were enrolled in the study. METHODS The enrolled patients were allocated into two groups in a ratio of 1:1. The experimental group received 4 weeks of task-oriented mirrored upper-limb robotic training, consisting of five sessions of 30-minute duration, along with 30 minutes of conventional training. The control group only received 60 minutes of conventional training. The outcome measures were the Fugl-Meyer Assessment Scale for Upper Extremity, Modified Barthel Index, Stroke Self-Efficacy Scale, System Usability Scale, and Quebec User Evaluation with Assistive Technology. RESULTS All patients completed the full training sessions without significant adverse events related to robotic training. The task-oriented mirrored upper-limb robotic training led to increased Fugl-Meyer Assessment Scale for Upper Extremity (difference: 10.38 points, P<0.001) and Modified Barthel Index (difference: 18.38 points, P<0.001) scores, both of which exceeded the minimal clinically important difference. Intergroup analysis showed significantly higher improvements in the Fugl-Meyer Assessment Scale for Upper Extremity total scores, shoulder, wrist, and hand scores; and Modified Barthel Index scores in the experimental group than in conventional training (all P<0.05). Both groups showed significant improvements in Stroke Self-Efficacy Scale scores after the intervention (both P<0.001), but without a statistically significant intergroup difference (P>0.05). Participants in the experimental group scored an average usability perception score of 74.74 (good) and an average satisfaction score of four or more out of five. CONCLUSIONS In general, task-oriented mirrored upper-limb robotic training appears feasible and safe for subacute poststroke rehabilitation, facilitating the recovery of upper-limb functions and activities of daily living. CLINICAL REHABILITATION IMPACT Task-oriented mirrored upper-limb robotic training shows promise for future clinical rehabilitation and clinical trials involving subacute poststroke patients.
Extreme acute radiation‐induced toxicity in a patient with polymorphous low‐grade adenocarcinoma of the nasopharynx and rare variants in DNA repair genes

Polymorphous low‐grade adenocarcinoma (PLGA) is an extremely rare finding in the nasopharynx. There are no guidelines for the treatment of PLGA in this localization. Radiotherapy may be administered to treat this malignancy; however, in radiosensitive individuals, it is associated with a risk of severe radiotherapy‐induced toxicity.
Упрощение рациональных функций для редукции с использованием соотношений интегрирования по частям и не только

We present FUEL (Fractional Universal Evaluation Library), a C++ library for performingrational function arithmetic with a flexible choice of third-party computer algebra systems as simplifiers. FUEL is an outgrowth of a C++ interface to Fermat which was originally part of the FIRE code for integration-by-parts (IBP) reduction for Feynman integrals, now promoted to be a standalone library with access to simplifiers other than Fermat. We compare the performance of various simplifiers for standalone benchmark problems as well as IBP reduction runs with FIRE. A speedup of more than 10 times is achieved for an example IBP problem related to calculation of the off-shell three-particle form factors in N = 4 supersymmetric Yang-Mills theory. Мы представляем C++ библиотеку FUEL (Fractional Universal Evaluation Library), предназначенную для выполнения арифметики рациональных функций с гибким выбором сторонних систем компьютерной алгебры в качестве упростителей. FUEL является развитием интерфейса C++ для Fermat, который изначально был частью кода FIRE для редукции соотношений интегрирования по частям (IBP) для интегралов Фейнмана, а теперь стал отдельной библиотекой с доступом к упростителям, отличным от Fermat. Мы сравниваем производительность различных упростителей для отдельных задач тестирования, а также для редукции IBP с помощью FIRE. Достигнуто ускорение более чем в 10 раз для примера редукции, связанной с вычислением трехпетлевых формфакторов вне оболочки светового конуса в N = 4 суперсимметричной теории Янга-Миллса.
Gaia Astrometry and MIKE+PFS Doppler Data Joint Analysis Reveals that HD 175167b is a Massive Cold Jupiter

HD 175167b is a cold (P b ∼ 1200 days) Jupiter with a minimum mass of Mpsini=7.8±3.5MJ orbiting a Sun-like star, first discovered by the Magellan Planet Search Program based on MIKE observations. Through a joint analysis of the MIKE data and the Gaia two-body orbital solution, Winn found a companion mass of M p = 14.8 ± 1.8 M J and suggested that it might be better designated as a brown dwarf. Additional publicly available radial velocity data from Magellan/PFS better constrains the model, and reveals that the companion is a massive cold Jupiter with a mass of M p = 10.2 ± 0.4 M J and a period of P b = 1275.8 ± 0.4 days. The planet orbit is inclined by i = 38. °6 ± 1. °7 with an eccentricity of 0.529 ± 0.002.
Non-standard bi-orders on punctured torus bundles

Results of Perron and Rolfsen imply that untwisted hyperbolic once-punctured torus bundles over the circle have bi-orderable fundamental groups. They do this by showing that the action of the monodromy preserves a"standard"bi-ordering formed using the lower central series of the free group. Here we investigate other bi-orderings that punctured torus bundle groups can have. We show that for every such bi-ordering, the largest and second largest proper convex subgroups match the corresponding convex subgroups for a standard bi-ordering. Moreover, if there exists a third largest convex subgroup, it must also match the third largest convex subgroup for a standard bi-ordering. However, we also show that these groups admit non-standard bi-orderings.
Faster Integer Points Counting in Parametric Polyhedra

In this paper, we consider the counting function $E_P(y) = |P_{y} \cap Z^{n_x}|$ for a parametric polyhedron $P_{y} = \{x \in R^{n_x} \colon A x \leq b + B y\}$, where $y \in R^{n_y}$. We give a new representation of $E_P(y)$, called a \emph{piece-wise step-polynomial with periodic coefficients}, which is a generalization of piece-wise step-polynomials and integer/rational Ehrhart's quasi-polynomials. It gives the fastest way to calculate $E_P(y)$ in certain scenarios. The most important cases are the following: 1) We show that, for the parametric polyhedron $P_y$ defined by a standard-form system $A x = y,\, x \geq 0$ with a fixed number of equalities, the function $E_P(y)$ can be represented by a polynomial-time computable function. In turn, such a representation of $E_P(y)$ can be constructed by an $poly\bigl(n, \|A\|_{\infty}\bigr)$-time algorithm; 2) Assuming again that the number of equalities is fixed, we show that integer/rational Ehrhart's quasi-polynomials of a polytope can be computed by FPT-algorithms, parameterized by sub-determinants of $A$ or its elements; 3) Our representation of $E_P$ is more efficient than other known approaches, if $A$ has bounded elements, especially if it is sparse in addition. Additionally, we provide a discussion about possible applications in the area of compiler optimization. In some"natural"assumptions on a program code, our approach has the fastest complexity bounds.
Fundamental Limits of Membership Inference Attacks on Machine Learning Models

Membership inference attacks (MIA) can reveal whether a particular data point was part of the training dataset, potentially exposing sensitive information about individuals. This article provides theoretical guarantees by exploring the fundamental statistical limitations associated with MIAs on machine learning models. More precisely, we first derive the statistical quantity that governs the effectiveness and success of such attacks. We then deduce that in a very general regression setting with overfitting algorithms, attacks may have a high probability of success. Finally, we investigate several situations for which we provide bounds on this quantity of interest. Our results enable us to deduce the accuracy of potential attacks based on the number of samples and other structural parameters of learning models. In certain instances, these parameters can be directly estimated from the dataset.
Inhomogeneous Polarization Transformation Reveals PT-Transition in non-Hermitian Optical Beam Shift

Despite its non-Hermitian nature, the transverse optical beam shift exhibits both real eigenvalues and non-orthogonal eigenstates. To explore this unexpected similarity to typical PT (parity-time)-symmetric systems, we first categorize the entire parametric regime of optical beam shifts into Hermitian, PT-unbroken, and PT-broken phases. Besides experimentally unveiling the PT-broken regime, crucially, we illustrate that the observed PT-transition is rooted in the momentum-domain inhomogeneous polarization transformation of the beam. The correspondence with a typical non-Hermitian photonic system is further established. Our work not only resolves a longstanding fundamental issue in the field of optical beam shift but also puts forward the notion of novel non-Hermitian spin-orbit photonics: a new direction to study non-Hermitian physics through the optical beam shifts.
High-$x$ quark density and their impact on $Z'$-boson dilepton searches t

In this proceeding, we study the influence of theoretical systematic uncertainties due to the quark density on LHC experimental searches for $Z'$-bosons. Using an approach originally proposed in the context of the ABMP16 PDF set for the high-$x$ behaviour of the quark density, we presents results on differential cross section and Forward-Backward asymmetry observables commonly used to study $Z'$ signals in dilepton channels.
Green Beamforming Design for Integrated Sensing and Communication Systems: A Practical Approach Using Beam-Matching Error Metrics

In this paper, we propose a green beamforming design for the integrated sensing and communication (ISAC) system, using beam-matching error to assess radar performance. The beam-matching error metric, which considers the mean square error between the desired and designed beam patterns, provides a more practical evaluation approach. To tackle the non-convex challenge inherent in beamforming design, we apply semidefinite relaxation (SDR) to address the rank-one relaxation issue, followed by the iterative rank minimization algorithm (IRM) for rank-one recovery. The simulation results showcase the effectiveness of our proposed optimal beamforming design, emphasizing the exceptional performance of the radar component in sensing tasks.
Prefix-Tuning Based Unsupervised Text Style Transfer

Unsupervised text style transfer aims at training a generative model that can alter the style of the input sentence while preserving its content without using any parallel data. In this paper, we employ powerful pre-trained large language models and present a new prefix-tuning-based method for unsupervised text style transfer. We construct three different kinds of prefixes, i.e., \textit{shared prefix, style prefix}, and \textit{content prefix}, to encode task-specific information, target style, and the content information of the input sentence, respectively. Compared to embeddings used by previous works, the proposed prefixes can provide richer information for the model. Furthermore, we adopt a recursive way of using language models in the process of style transfer. This strategy provides a more effective way for the interactions between the input sentence and GPT-2, helps the model construct more informative prefixes, and thus, helps improve the performance. Evaluations on the well-known datasets show that our method outperforms the state-of-the-art baselines. Results, analysis of ablation studies, and subjective evaluations from humans are also provided for a deeper understanding of the proposed method.
The inverse nullity pair problem and the strong nullity interlacing property

The inverse eigenvalue problem studies the possible spectra among matrices whose off-diagonal entries have their zero-nonzero patterns described by the adjacency of a graph $G$. In this paper, we refer to the $i$-nullity pair of a matrix $A$ as $(\operatorname{null}(A), \operatorname{null}(A(i))$, where $A(i)$ is the matrix obtained from $A$ by removing the $i$-th row and column. The inverse $i$-nullity pair problem is considered for complete graphs, cycles, and trees. The strong nullity interlacing property is introduced, and the corresponding supergraph lemma and decontraction lemma are developed as new tools for constructing matrices with a given nullity pair.
A study of the impact of generative AI-based data augmentation on software metadata classification

This paper presents the system submitted by the team from IIT(ISM) Dhanbad in FIRE IRSE 2023 shared task 1 on the automatic usefulness prediction of code-comment pairs as well as the impact of Large Language Model(LLM) generated data on original base data towards an associated source code. We have developed a framework where we train a machine learning-based model using the neural contextual representations of the comments and their corresponding codes to predict the usefulness of code-comments pair and performance analysis with LLM-generated data with base data. In the official assessment, our system achieves a 4% increase in F1-score from baseline and the quality of generated data.
Deep Learning Based Forecasting-Aided State Estimation in Active Distribution Networks

Operating an active distribution network (ADN) in the absence of enough measurements, the presence of distributed energy resources, and poor knowledge of responsive demand behaviour is a huge challenge. This paper introduces systematic modelling of demand response behaviour which is then included in Forecasting Aided State Estimation (FASE) for better control of the network. There are several innovative elements in tuning parameters of FASE-based, demand profiling, and aggregation. The comprehensive case studies for three UK representative demand scenarios in 2023, 2035, and 2050 demonstrated the effectiveness of the proposed approach.
Composer Style-specific Symbolic Music Generation Using Vector Quantized Discrete Diffusion Models

Emerging Denoising Diffusion Probabilistic Models (DDPM) have become increasingly utilised because of promising results they have achieved in diverse generative tasks with continuous data, such as image and sound synthesis. Nonetheless, the success of diffusion models has not been fully extended to discrete symbolic music. We propose to combine a vector quantized variational autoencoder (VQ-VAE) and discrete diffusion models for the generation of symbolic music with desired composer styles. The trained VQ-VAE can represent symbolic music as a sequence of indexes that correspond to specific entries in a learned codebook. Subsequently, a discrete diffusion model is used to model the VQ-VAE's discrete latent space. The diffusion model is trained to generate intermediate music sequences consisting of codebook indexes, which are then decoded to symbolic music using the VQ-VAE's decoder. The results demonstrate our model can generate symbolic music with target composer styles that meet the given conditions with a high accuracy of 72.36%.