bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel adaptive quantization methodology for 8-bit floating-point DNN training
Authors: Hassani Sadi Mohammad , Sudarshan Chirag , Wehn Norbert 
Published: February 2024

AbstractThere is a high energy cost associated with training Deep Neural Networks (DNNs). Off-chip memory access contributes a major portion to the overall energy consumption. Reduction in the number of off-chip memory transactions can be achieved by quantizing the data words to low data bit-width (E.g., 8-bit). However, low-bit-width data formats suffer from a limited dynamic range, resulting in reduced accuracy. In this paper, a novel 8-bit Floating Point (FP8) data format quantized DNN training methodology is presented, which adapts to the required dynamic range on-the-fly. Our methodology relies on varying the bias values of FP8 format to fit the dynamic range to the required range of DNN parameters and input feature maps. The range fitting during the training is adaptively performed by an online statistical analysis hardware unit without stalling the computation units or its data accesses. Our approach is compatible with any DNN compute cores without any major modifications to the architecture. We propose to integrate the new FP8 quantization unit in the memory controller. The FP32 data from the compute core are converted to FP8 in the memory controller before writing to the DRAM and converted back after reading the data from DRAM. Our results show that the DRAM access energy is reduced by 3.07$$\times $$
×
while using an 8-bit data format instead of using 32-bit. The accuracy loss of the proposed methodology with 8-bit quantized training is $$\approx 1\%$$

≈
1
%

for various networks with image and natural language processing datasets.
Profiling with trust: system monitoring from trusted execution environments
Authors: Eichler Christian , Röckl Jonas , Jung Benedikt , Schlenk Ralph , Müller Tilo , Hönig Timo 
Published: February 2024

AbstractLarge-scale attacks on IoT and edge computing devices pose a significant threat. As a prominent example, Mirai is an IoT botnet with 600,000 infected devices around the globe, capable of conducting effective and targeted DDoS attacks on (critical) infrastructure. Driven by the substantial impacts of attacks, manufacturers and system integrators propose Trusted Execution Environments (TEEs) that have gained significant importance recently. TEEs offer an execution environment to run small portions of code isolated from the rest of the system, even if the operating system is compromised. In this publication, we examine TEEs in the context of system monitoring and introduce the Trusted Monitor (TM), a novel anomaly detection system that runs within a TEE. The TM continuously profiles the system using hardware performance counters and utilizes an application-specific machine-learning model for anomaly detection. In our evaluation, we demonstrate that the TM accurately classifies 86% of 183 tested workloads, with an overhead of less than 2%. Notably, we show that a real-world kernel-level rootkit has observable effects on performance counters, allowing the TM to detect it. Major parts of the TM are implemented in the Rust programming language, eliminating common security-critical programming errors.
Fair concordance between Google Trends and Danish ornithologists in the assessment of temporal trends in Danish bird populations highlights the informational value of big data
Authors: Jensen Per M. , Danielsen Finn , Jacobsen Stine K. , Vikstrøm Thomas 
Published: February 2024

AbstractThe ongoing depletion of natural systems and associated biodiversity decline is of growing international concern. Climate change is expected to exacerbate anthropogenic impacts on wild populations. The scale of impact on ecosystems and ecosystem services will be determined by the impact on a multitude of species and functional groups, which due to their biology and numbers are difficult to monitor. The IPCC has argued that surveillance or monitoring is critical and proposed that monitoring systems should be developed, which not only track developments but also function as “early warning systems.” Human populations are already generating large continuous datasets on multiple taxonomic groups through internet searches. These time series could in principle add substantially to current monitoring if they reflect true changes in the natural world. We here examined whether information on internet search frequencies delivered by the Danish population and captured by Google Trends (GT) appropriately informs on population trends in 106 common Danish bird species. We compared the internet search activity with independent equivalent population trend assessments from the Danish Ornithological Society (BirdLife Denmark/DOF). We find a fair concordance between the GT trends and the assessments by DOF. A substantial agreement can be obtained by omitting species without clear temporal trends. Our findings suggest that population trend proxies from internet search frequencies can be used to supplement existing wildlife population monitoring and to ask questions about an array of ecological phenomena, which potentially can be integrated into an early warning system for biodiversity under climate change.
A Practical Approach for Employing Tensor Train Decomposition in Edge Devices
Authors: Kokhazadeh Milad , Keramidas Georgios , Kelefouras Vasilios , Stamoulis Iakovos 
Published: February 2024

AbstractDeep Neural Networks (DNN) have made significant advances in various fields including speech recognition and image processing. Typically, modern DNNs are both compute and memory intensive, therefore their deployment in low-end devices is a challenging task. A well-known technique to address this problem is Low-Rank Factorization (LRF), where a weight tensor is approximated by one or more lower-rank tensors, reducing both the memory size and the number of executed tensor operations. However, the employment of LRF is a multi-parametric optimization process involving a huge design space where different design points represent different solutions trading-off the number of FLOPs, the memory size, and the prediction accuracy of the DNN models. As a result, extracting an efficient solution is a complex and time-consuming process. In this work, a new methodology is presented that formulates the LRF problem as a (FLOPs vs. memory vs. prediction accuracy) Design Space Exploration (DSE) problem. Then, the DSE space is drastically pruned by removing inefficient solutions. Our experimental results prove that the design space can be efficiently pruned, therefore extract only a limited set of solutions with improved accuracy, memory, and FLOPs compared to the original (non-factorized) model. Our methodology has been developed as a stand-alone, parameterized module integrated into T3F library of TensorFlow 2.X.
Pattern electroretinography response in amblyopic adults
Authors: Fernandes Andresa , Pinto Nuno , Tuna Ana Rita , Brardo Francisco Miguel , Pato Maria Vaz 
Published: February 2024

Abstract
Introduction
Amblyopia is generally a unilateral disorder, defined by at least a difference of two lines of visual acuity between both eyes with the best-corrected visual acuity, a decrease in contrast sensitivity, and a decrease in stereopsis. Pattern electroretinogram (PERG) is a noninvasive technique that provides a retinal biopotential and is a highly sensitive indicator of changes in the macular area. Our aim was to evaluate if there are differences in the retinal response of an amblyopic eye compared with a normal eye (NE).

Methods
We evaluated twenty-four adult volunteers, twelve amblyopes (mean 43.42 ± 12.72 years old), and twelve subjects with NE (mean 35.58 ± 12.85 years old). None of the subjects in the two groups had comorbidities. A complete optometric examination was performed including parameters such as visual acuity (VA) by far and near with ETDRS chart, eye alignment with cover test, and evaluation of retinal cells response with PERG.

Results
The refractive error found in the NE group of subjects had a mean of − 0.95 ± 1.65D, while the amblyopic group showed a mean of − 2.03 ± 4.29D. The VA in amblyopic eyes had a mean of 0.38 ± 0.20 logMAR. Analyzing PERG data, we observed significant differences in the P50-N95 amplitudes of the amblyopic group compared with the NE group (p < 0.0001–amblyopic eye vs. NE; p = 0.039–fellow eye vs. NE).

Discussion
These findings suggest that amblyopic patients may also present other impairments beyond the visual cortex. PERGs seem to be an important complementary examination in the diagnosis of other impairments in amblyopia.
Molecule auto-correction to facilitate molecular design
Authors: Kerstjens Alan , De Winter Hans 
Published: February 2024

AbstractEnsuring that computationally designed molecules are chemically reasonable is at best cumbersome. We present a molecule correction algorithm that morphs invalid molecular graphs into structurally related valid analogs. The algorithm is implemented as a tree search, guided by a set of policies to minimize its cost. We showcase how the algorithm can be applied to molecular design, either as a post-processing step or as an integral part of molecule generators.
Graphical abstract
Recombinant IFN-γ1b Treatment in a Patient with Inherited IFN-γ Deficiency
Authors: Rosain Jérémie , Kiykim Ayca , Michev Alexandre , Kendir-Demirkol Yasemin , Rinchai Darawan , Peel Jessica N. , Li Hailun , Ocak Suheyla , Ozdemir Pinar Gokmirza , Le Voyer Tom , Philippot Quentin , Khan Taushif , Neehus Anna-Lena , Migaud Mélanie , Soudée Camille , Boisson-Dupuis Stéphanie , Marr Nico , Borghesi Alessandro , Casanova Jean-Laurent , Bustamante Jacinta 
Published: February 2024

Abstract
Purpose
Inborn errors of IFN-γ immunity underlie Mendelian susceptibility to mycobacterial disease (MSMD). Twenty-two genes with products involved in the production of, or response to, IFN-γ and variants of which underlie MSMD have been identified. However, pathogenic variants of IFNG encoding a defective IFN-γ have been described in only two siblings, who both underwent hematopoietic stem cell transplantation (HCST).

Methods
We characterized a new patient with MSMD by genetic, immunological, and clinical means. Therapeutic decisions were taken on the basis of these findings.

Results
The patient was born to consanguineous Turkish parents and developed bacillus Calmette-Guérin (BCG) disease following vaccination at birth. Whole-exome sequencing revealed a homozygous private IFNG variant (c.224 T > C, p.F75S). Upon overexpression in recipient cells or constitutive expression in the patient’s cells, the mutant IFN-γ was produced within the cells but was not correctly folded or secreted. The patient was treated for 6 months with two or three antimycobacterial drugs only and then for 30 months with subcutaneous recombinant IFN-γ1b plus two antimycobacterial drugs. Treatment with IFN-γ1b finally normalized all biological parameters. The patient presented no recurrence of mycobacterial disease or other related infectious diseases. The treatment was well tolerated, without the production of detectable autoantibodies against IFN-γ.

Conclusion
We describe a patient with a new form of autosomal recessive IFN-γ deficiency, with intracellular, but not extracellular IFN-γ. IFN-γ1b treatment appears to have been beneficial in this patient, with no recurrence of mycobacterial infection over a period of more than 30 months. This targeted treatment provides an alternative to HCST in patients with complete IFN-γ deficiency or at least an option to better control mycobacterial infection prior to HCST.
Enrichment of Immune Dysregulation Disorders in Adult Patients with Human Inborn Errors of Immunity
Authors: Segura-Tudela Alejandro , López-Nevado Marta , Nieto-López Celia , García-Jiménez Sandra , Díaz-Madroñero María J. , Delgado Ángeles , Cabrera-Marante Oscar , Pleguezuelo Daniel , Morales Pablo , Paz-Artal Estela , Gil-Niño Jorge , Marco Francisco M. , Serrano Cristina , González-Granado Luis I. , Quesada-Espinosa Juan F. , Allende Luis M. 
Published: February 2024

AbstractHuman inborn errors of immunity (IEI) comprise a group of diseases resulting from molecular variants that compromise innate and adaptive immunity. Clinical features of IEI patients are dominated by susceptibility to a spectrum of infectious diseases, as well as autoimmune, autoinflammatory, allergic, and malignant phenotypes that usually appear in childhood, which is when the diagnosis is typically made. However, some IEI patients are identified in adulthood due to symptomatic delay of the disease or other reasons that prevent the request for a molecular study. The application of next-generation sequencing (NGS) as a diagnostic technique has given rise to an ever-increasing identification of IEI-monogenic causes, thus improving the diagnostic yield and facilitating the possibility of personalized treatment. This work was a retrospective study of 173 adults with IEI suspicion that were sequenced between 2005 and 2023. Sanger, targeted gene-panel, and whole exome sequencing were used for molecular diagnosis. Disease-causing variants were identified in 44 of 173 (25.43%) patients. The clinical phenotype of these 44 patients was mostly related to infection susceptibility (63.64%). An enrichment of immune dysregulation diseases was found when cohorts with molecular diagnosis were compared to those without. Immune dysregulation disorders, group 4 from the International Union of Immunological Societies Expert Committee (IUIS), were the most prevalent among these adult patients. Immune dysregulation as a new item in the Jeffrey Model Foundation warning signs for adults significantly increases the sensitivity for the identification of patients with an IEI-producing molecular defect.
Post-transplant Inflammatory Bowel Disease Associated with Donor-Derived TIM-3 Deficiency
Authors: Baldrich Adrian , Althaus Dominic , Menter Thomas , Hirsiger Julia R. , Köppen Julius , Hupfer Robin , Juskevicius Darius , Konantz Martina , Bosch Angela , Drexler Beatrice , Gerull Sabine , Ghosh Adhideb , Meyer Benedikt J. , Jauch Annaise , Pini Katia , Poletti Fabio , Berkemeier Caroline M. , Heijnen Ingmar , Panne Isabelle , Cavelti-Weder Claudia , Niess Jan Hendrik , Dixon Karen , Daikeler Thomas , Hartmann Karin , Hess Christoph , Halter Jörg , Passweg Jakob , Navarini Alexander A. , Yamamoto Hiroyuki , Berger Christoph T. , Recher Mike , Hruz Petr 
Published: February 2024

AbstractInflammatory bowel disease (IBD) occurring following allogeneic stem cell transplantation (aSCT) is a very rare condition. The underlying pathogenesis needs to be better defined. There is currently no systematic effort to exclude loss- or gain-of-function mutations in immune-related genes in stem cell donors. This is despite the fact that more than 100 inborn errors of immunity may cause or contribute to IBD. We have molecularly characterized a patient who developed fulminant inflammatory bowel disease following aSCT with stable 100% donor-derived hematopoiesis. A pathogenic c.A291G; p.I97M HAVCR2 mutation encoding the immune checkpoint protein TIM-3 was identified in the patient’s blood-derived DNA, while being absent in DNA derived from the skin. TIM-3 expression was much decreased in the patient’s serum, and in vitro-activated patient-derived T cells expressed reduced TIM-3 levels. In contrast, T cell-intrinsic CD25 expression and production of inflammatory cytokines were preserved. TIM-3 expression was barely detectable in the immune cells of the patient’s intestinal mucosa, while being detected unambiguously in the inflamed and non-inflamed colon from unrelated individuals. In conclusion, we report the first case of acquired, “transplanted” insufficiency of the regulatory TIM-3 checkpoint linked to post-aSCT IBD.
A critical view on using “life not worth living” in the bioethics of assisted reproduction
Authors: Kandlbinder Agnes Elisabeth 
Published: February 2024

AbstractThis paper critically engages with how life not worth living (LNWL) and cognate concepts are used in the field of beginning-of-life bioethics as the basis of arguments for morally requiring the application of preimplantation genetic diagnosis (PGD) and/or germline genome editing (GGE). It is argued that an objective conceptualization of LNWL is largely too unreliable in beginning-of-life cases for deriving decisive normative reasons that would constitute a moral duty on the part of intending parents. Subjective frameworks are found to be more suitable to determine LNWL, but they are not accessible in beginning-of-life cases because there is no subject yet. Conceptual and sociopolitical problems are additionally pointed out regarding the common usage of clear case exemplars. The paper concludes that a moral requirement for the usage of PGD and GGE cannot be derived from the conceptual base of LNWL, as strong reasons that can be reliably determined are required to limit reproductive freedom on moral grounds. Educated predictions on prospective well-being might still be useful regarding the determination of moral permissibility of PGD and/or GGE. It is suggested that due to the high significance of subjective experience in the normativity of beginning-of-life bioethics, the discipline is called to more actively realize the inclusion of people with disabilities. This regards for instance research design, citation practices, and language choices to increase the accessibility of societal debates on the reproductive ethics of genetic technologies.
Pectolinarigenin regulates the tumor-associated proteins in AGS-xenograft BALB/c nude mice
Authors: Lee Ho Jeong , Kwon Young Sang , Lee Ju Hong , Moon Yeon Gyu , Choi Jungil , Hyun Moonjung , Tak Tae Kil , Kim Je-Hein , Heo Jeong Doo 
Published: February 2024

Abstract

Background
Pectolinarigenin (PEC) is a flavone extracted from Cirsium, and because it has anti-inflammatory properties, anti-cancer research is also being conducted. The objective of this work was to find out if PEC is involved in tumor control and which pathways it regulates in vivo and in vitro.

Methods
AGS cell lines were xenografted into BALB/c nude mice to create tumors, and PEC was administered intraperitoneally to see if it was involved in tumor control. Once animal testing was completed, tumor proteins were isolated and identified using LC–MS analysis, and gene ontology of the found proteins was performed.

Results
Body weight and hematological measurements on the xenograft mice model demonstrated that PEC was not harmful to non-cancerous cells. We found 582 proteins in tumor tissue linked to biological reactions such as carcinogenesis and cell death signaling. PEC regulated 6 out of 582 proteins in vivo and in vitro in the same way.

Conclusion
Our findings suggested that PEC therapy may inhibit tumor development in gastric cancer (GC), and proteomic research gives fundamental information about proteins that may have great promise as new therapeutic targets in GC.
The development of a custom RNA-sequencing panel for the identification of predictive and diagnostic biomarkers in glioma
Authors: Shirai Yukina , Ueno Toshihide , Kojima Shinya , Ikeuchi Hiroshi , Kitada Rina , Koyama Takafumi , Takahashi Fumiyuki , Takahashi Kazuhisa , Ichimura Koichi , Yoshida Akihiko , Sugino Hirokazu , Mano Hiroyuki , Narita Yoshitaka , Takahashi Masamichi , Kohsaka Shinji 
Published: February 2024

Abstract
Purpose
Various molecular profiles are needed to classify malignant brain tumors, including gliomas, based on the latest classification criteria of the World Health Organization, and their poor prognosis necessitates new therapeutic targets. The Todai OncoPanel 2 RNA Panel (TOP2-RNA) is a custom-target RNA-sequencing (RNA-seq) using the junction capture method to maximize the sensitivity of detecting 455 fusion gene transcripts and analyze the expression profiles of 1,390 genes. This study aimed to classify gliomas and identify their molecular targets using TOP2-RNA.

Methods
A total of 124 frozen samples of malignant gliomas were subjected to TOP2-RNA for classification based on their molecular profiles and the identification of molecular targets.

Results
Among 55 glioblastoma cases, gene fusions were detected in 11 cases (20%), including novel MET fusions. Seven tyrosine kinase genes were found to be overexpressed in 15 cases (27.3%). In contrast to isocitrate dehydrogenase (IDH) wild-type glioblastoma, IDH-mutant tumors, including astrocytomas and oligodendrogliomas, barely harbor fusion genes or gene overexpression. Of the 34 overexpressed tyrosine kinase genes, MDM2 and CDK4 in glioblastoma, 22 copy number amplifications (64.7%) were observed. When comparing astrocytomas and oligodendrogliomas in gene set enrichment analysis, the gene sets related to 1p36 and 19q were highly enriched in astrocytomas, suggesting that regional genomic DNA copy number alterations can be evaluated by gene expression analysis.

Conclusions
TOP2-RNA is a highly sensitive assay for detecting fusion genes, exon skipping, and aberrant gene expression. Alterations in targetable driver genes were identified in more than 50% of glioblastoma. Molecular profiling by TOP2-RNA provides ample predictive, prognostic, and diagnostic biomarkers that may not be identified by conventional assays and, therefore, is expected to increase treatment options for individual patients with glioma.
W-FENet: Wavelet-based Fourier-Enhanced Network Model Decomposition for Multivariate Long-Term Time-Series Forecasting
Authors: Wang Hai-Kun , Zhang Xuewei , Long Haicheng , Yao Shunyu , Zhu Pengjin 
Published: February 2024

AbstractAccurately predicting the future trend of a time series holds immense importance for decision-making and planning across various domains, including energy planning, weather forecasting, traffic warning, and other practical applications. Recently, deep learning methods based on transformers and time convolution networks (TCN) have achieved a surprising performance in long-term sequence prediction. However, the attention mechanism for calculating global correlation is highly complex, and TCN methods do not fully consider the characteristics of time-series data. To address these challenges, we introduce a new learning model named wavelet-based Fourier-enhanced network model decomposition (W-FENet). Specifically, we have used trend decomposition and wavelet transform to decompose the original data. This processed time-series data can then be more effectively analyzed by the model and mined for different components in the series, as well as capture the local details and overall trendiness of the series. An efficient feature extraction method, Fourier enhancement-based feature extraction (FEMEX), is introduced in our model. The mechanism converts time-domain information into frequency-domain information through a Fourier enhancement module, and the obtained frequency-domain information is better captured by the model than the original time-domain information in terms of periodicity, trend, and frequency features. Experiments on multiple benchmark datasets show that, compared with the state-of-the-art methods, the MSE and MAE of our model are improved by 11.1 and 6.36% on average, respectively, covering three applications (i.e. ETT, Exchange, and Weather).