Miracle-dz/UniFAR-FTUs huggingface dataset:
Biophysical neural adaptation mechanisms enable artificial neural networks to capture dynamic retinal computation

Adaptation is a universal aspect of neural systems that changes circuit computations to match prevailing inputs. These changes facilitate efficient encoding of sensory inputs while avoiding saturation. Conventional artificial neural networks (ANNs) have limited adaptive capabilities, hindering their ability to reliably predict neural output under dynamic input conditions. Can embedding neural adaptive mechanisms in ANNs improve their performance? To answer this question, we develop a new deep learning model of the retina that incorporates the biophysics of photoreceptor adaptation at the front-end of conventional convolutional neural networks (CNNs). These conventional CNNs build on ‘Deep Retina,’ a previously developed model of retinal ganglion cell (RGC) activity. CNNs that include this new photoreceptor layer outperform conventional CNN models at predicting primate and rat RGC responses to naturalistic stimuli that include dynamic local intensity changes and large changes in the ambient illumination. These improved predictions result directly from adaptation within the phototransduction cascade. This research underscores the potential of embedding models of neural adaptation in ANNs and using them to determine how neural circuits manage the complexities of encoding natural inputs that are dynamic and span a large range of light levels.
EXPLORING THE DISTRIBUTION OF SINGLE NUCLEOTIDE POLYMORPHISMS ACROSS HUMAN EXONS AND INTRONS

Among all types of mutations, single nucleotide polymorphisms are the most common type of genomic variation. In our study, we explore the counts of single nucleotide polymorphisms in particular exons and introns of the human genome based on the data set of 1,222 individuals of Polish origin that comprises 41,836,187 polymorphisms. In particular, chromosomes 1 and 22 were considered as representatives of two markedly different DNA molecules, since HSA01 represents the longest and HSA22 is one of the shortest chromosomes. The results demonstrate that outer (first, last) exons as well as the first introns harbour significantly more SNPs than other genic regions. The observed differences in counts reflect the distinct functional roles of those genomic units.
Fast and Robust Analytical Design of Equiripple Comb FIR Filters for Communication Purposes

A novel analytical design method for highly selective digital optimal equiripple comb FIR filters is presented. The equiripple comb FIR filters are optimal in the Chebyshev sense. The number of notch bands, the width of the notch bands and the attenuation in the passbands can be independently specified. The degree formula and the differential equation for the generating polynomial of the filter is presented. Based on the differential equation, a fast simple algebraic recursive procedure for the evaluation of the impulse response of the filter is described. Its arithmetic robustness outperforms by far the known analytical design method. Highly selective equiripple comb FIR filters with thousands of coefficients can be designed. One example demonstrates the efficiency of the filter design.
Aberrant EGFR and Chromosome 7 Associate with Outcome in Laryngeal Cancer

Objectives/Hypothesis: Epidermal growth factor receptor (EGFR) over‐expression has been reported as a prognostic indicator in laryngeal cancer; however, the association with disease outcome has been inconsistent among studies. Here, we use fluorescence in situ hybridization (FISH) in addition to immunohistochemistry to assess laryngeal squamous cell carcinoma (SCC) to determine whether FISH can better predict patient outcome.
Parametric Weighting of Parallel Data for Statistical Machine Translation

During the last years there is increasing interest in methods that perform some kind of weighting of heterogeneous parallel training data when building a statistical machine translation system. It was for instance observed that training data that is close to the period of the test data is more valuable than older data (Hardt and Elming, 2010; Levenberg et al., 2010). In this paper we obtain such a weighting by resampling alignments using weights that decrease with the temporal distance of bitexts to the test set. By these means, we can use all the available bitexts and still put an emphasis on the most recent one. The main idea of our approach is to use a parametric form or meta-weights for the weighting of the different parts of the bitexts. This ensures that our approach has only few parameters to optimize. We report experimental results on the Europarl corpus, translating from French to English and further verified it on the official WMT’11 task, translating from English to French. Our method achieves improvements of about 0.6 points BLEU on the test set with respect to a system trained on data without any weighting.
Resilient Consensus Control of Nonlinear Second-Order MASs Under DoS Attacks

This paper focuses on the coordinated control of multi-agent systems (MASs) and proposes an event-triggered control strategy to conserve computing resource and alleviate the impact of Denial of Service (DoS) attacks. MASs have become an important research topic due to its potential applications in various fields and the abilities of multiple agents to interact and cooperate enables them to perform complex tasks. However, DoS attacks can prevent agents from obtaining useful information and disrupt communication channels, leading to instability of the MASs. The proposed strategy allows agents to update their states only when certain triggering conditions are met, thus reducing communication frequency and improving efficiency and robustness. This paper proposes resilient controller for achieving practical consensus in second-order directed MASs under DoS attacks, demonstrating the feasibility of the scheme through Lyapunov functions and comparison principles. Simulation results show that the proposed method is effective in mitigating the impact of DoS attacks and achieving consensus.
In fl ammatory monocytes and Fc γ receptor IV on osteoclasts are critical for bone destruction during in fl ammatory arthritis in mice

IMMUNOLOGY Correction for “Inflammatory monocytes and Fcγ receptor IV on osteoclasts are critical for bone destruction during inflammatory arthritis in mice,” by Michaela Seeling, Ulrike Hillenhoff, Jean Pierre David, Georg Schett, Jan Tuckermann, Anja Lux, and Falk Nimmerjahn, which appeared in issue 26, June 25, 2013, of Proc Natl Acad Sci USA (110:10729–10734; first published June 10, 2013; 10.1073/pnas.1301001110). PNAS notes that a conflict of interest statement was omitted during publication. PNAS declares that “The editor, Jeffrey Ravetch, is a recent coauthor with an author (F.N.) of this publication, having last published a paper with him in 2010. ”
A Coal-Rock Cutting Hardness Recognition Model Based on CNN-PN

Existing methods for accurate recognition of coal-rock cutting hardness by shearer machines in complex environments face challenges in timely adjusting the drum speed and traction velocity to adapt to changes in coal-rock cutting hardness. In this paper, we propose a Coal-Rock Cutting Hardness Recognition Model based on Convolutional Neural Network (CNN) - Prototype Network (PN). Firstly, multiple sensor signals are utilized to generate high-dimensional data, which is then fed into CNN for feature extraction. Subsequently, the features extracted by the convolutional neural network are input into the PN, which calculates the embedding center distances for each category, obtaining representative prototype vectors. The similarity between prototype vectors is measured using Euclidean distance, and these prototype vectors form different groups. Thirdly, the Adam algorithm is employed to optimize the network model, enabling better adaptation to data distribution differences and improving training effectiveness. Finally, the proposed model is validated through experiments using collected data. Unlike traditional machine learning approaches that require extensive manual feature extraction and data preprocessing for coal-rock cutting hardness recognition, which affects recognition accuracy and efficiency, the proposed method overcomes these limitations and can directly classify raw multi-sensor data signals during coal-rock cutting by shearer machines while effectively recognizing coal-rock cutting hardness. Experimental results demonstrate an average recognition rate of 99.64% for the proposed model, indicating high recognition accuracy and good generalization performance.
A Method for Constructing Semantic Navigation Maps in Urban Environments

The field of modern autonomous driving and unmanned systems places significant importance on planning and semantic navigation tasks for autonomous vehicles. The successful execution of these tasks relies heavily on mapping and localization technologies. We propose a method to address the difficulty of using trajectory maps of autonomous vehicle cameras in complex environments for planning. The proposed method constructs a topological map that is convenient for subsequent planning and semantic navigation. To enhance the integration of trajectory maps with topological maps, we employ the ORB-SLAM2 algorithm to create the camera's trajectory map, and we extract the keyframe information to obtain frames from the data. These extracted keyframes are then fed sequentially into a junction recognition network that utilizes ResNet18 transfer learning. Then we connect the resulting nodes that are recognized as junctions to generate the camera's topological map. The integration of trajectory and topological maps has been found to be advantageous in improving the planning and navigation abilities of ground robots.
Flying to the Rescue: UAV-Assisted Urgent Alert Transmission in VANET

Safety applications are the cornerstone of the envisioned Vehicle Ad Hoc Network (VANET). Early transmission of alert messages following car accidents can avoid further potential crashes and save lives. However, the limited terrestrial coverage on highways, particularly in rural areas with low traffic density, hinders the deployment of this service. One promising solution involves integrating Unmanned Aerial Vehicles (UAVs), commonly known as drones, into VANETs to serve as flying relays. These UAVs can re-broadcast alert or warning messages between vehicles, bridging communication gaps. In this paper, we propose a unified UAVs-VANET architecture where UAVs relay messages among vehicles on rural highways. To evaluate our approach, we consider a case study involving a road accident on a Tunisian highway (Tunis - Bou Salem 75 km). We use the SUMO simulator in conjunction with NS3. The obtained results showed that 100% of vehicles are alerted within 3.85 seconds. The study also investigates how the number of deployed UAVs impacts the number of alerted vehicles.
Inside booters: An analysis on operational databases

Distributed Denial of Service (DDoS) attacks are an increasing threat on the Internet. One of the reasons is that Web sites selling attacks for prices starting from $1.00 are becoming popular. These Web sites, called Booters, facilitate attacks by making transparent the needed infrastructure to perform attacks and by lowering the knowledge to control it. As a consequence, any user on the Internet is able to launch attacks at any time. Although security experts and operators acknowledge the potential of Booters for DDoS attacks, little is known about Booters operational aspects in terms of users, attacks and infrastructure. The existing works that investigate this phenomenon are all restricted to the analysis of a single Booter and therefore provide a narrow overview of the phenomenon. In this paper we extend the existing work by providing an extensive analysis on 15 distinct Booters. We analyze their operational databases containing logs of users, attacks, and the infrastructure used to perform attacks. Among our findings we reveal that (i) some Booters have several database records completely equal, (ii) users that access Booters via proxies and VPNs performed much more attacks than those that accessed using a single IP address, and (iii) the infrastructure used to perform attacks is slightly different from what is known through existing work. The contribution of our work is to bring awareness of Booter characteristics facilitating future works to mitigate this phenomenon.
A Model for Precise and Uniform Pelvic- and Limb-Sparing Abdominal Irradiation to Study the Radiation-Induced Gastrointestinal Syndrome in Mice Using Small Animal Irradiation Systems

Background and Purpose: Currently, no readily available mitigators exist for acute abdominal radiation injury. Here, we present an animal model for precise and homogenous limb-sparing abdominal irradiation (LSAIR) to study the radiation-induced gastrointestinal syndrome (RIGS). Materials and Methods: The LSAIR technique was developed using the small animal radiation research platform (SARRP) with image guidance capabilities. We delivered LSAIR at doses between 14 and 18 Gy on 8- to 10-week-old male C57BL/6 mice. Histological analysis was performed to confirm that the observed mortality was due to acute abdominal radiation injury. Results: A steep dose–response relationship was found for survival, with no deaths seen at doses below 16 Gy and 100% mortality at above 17 Gy. All deaths occurred between 6 and 10 days after irradiation, consistent with the onset of RIGS. This was further confirmed by histological analysis showing clear differences in the number of regenerative intestinal crypts between animals receiving sublethal (14 Gy) and 100% lethal (18 Gy) radiation. Conclusion: The developed LSAIR technique provides uniform dose delivery with a clear dose response, consistent with acute abdominal radiation injury on histological examination. This model can provide a useful tool for researchers investigating the development of mitigators for accidental or clinical high-dose abdominal irradiation.
Genetic evaluation of persistency in extended lactations

In April 2023, a new breeding value for milk yield persistency was introduced for German Holsteins, Jerseys, Red Dairy Cattle, German black-and-white dual purpose, and red-and-white dual-purpose breeds. The aim is to allow selection of animals that are genetically suited for voluntarily extended lactations. The new breeding value was derived from the Random-Regression-Test-Day-Model (3 yield traits: protein-kg, fat-kg, milk-kg; 3 lactations each; 2nd order legendre polynomials in the genetic effect) that is used for routine genetic evaluations. The new trait is defined as the slope of the genetic Legendre polynomial between DIM 150 and 305 for each yield trait in each lactation. EBVs for fat and protein persistency are then combined according to their economic impact, using the same weights as for the overall yield index RZM: fat-kg:protein-kg weighted 1:2. The newly defined persistency index has a cumulative heritability of 0.34. Correlations of genomic breeding values to the traits that are included in the total merit index RZG are close to zero, except for RZM (0.24) and longevity RZN (0.18). Reliabilities for youngest genotyped animals without performance observations are approx. 0.60, which is lower than for the RZM. We observe a small positive genetic trend in the newly defined persistency trait in German Holsteins, which is expected, given the small but positive correlation to RZG that stems from the correlations to RZM and RZN.
The Arabidopsis TT2 Gene Encodes an R2R3 MYB Domain Protein That Acts as a Key Determinant for Proanthocyanidin Accumulation in Developing Seed

In Arabidopsis, proanthocyanidins specifically accumulate in the endothelium during early seed development. At least three TRANSPARENT TESTA (TT) genes, TT2, TT8, and TTG1, are necessary for the normal expression of several flavonoid structural genes in immature seed, such as DIHYDROFLAVONOL-4-REDUCTASE and BANYULS (BAN). TT8 and TTG1 were characterized recently and found to code for a basic helix-loop-helix domain transcription factor and a WD-repeat–containing protein, respectively. Here the molecular cloning of the TT2 gene was achieved by T-DNA tagging. TT2 encoded an R2R3 MYB domain protein with high similarity to the rice OsMYB3 protein and the maize COLORLESS1 factor. A TT2–green fluorescent protein fusion protein was located mostly in the nucleus, in agreement with the regulatory function of the native TT2 protein. TT2 expression was restricted to the seed during early embryogenesis, consistent with BAN expression and the proanthocyanidin deposition profile. Finally, in gain-of-function experiments, TT2 was able to induce ectopic expression of BAN in young seedlings and roots in the presence of a functional TT8 protein. Therefore, our results strongly suggest that stringent spatial and temporal BAN expression, and thus proanthocyanidin accumulation, are determined at least partially by TT2.
Genome-wide association analysis for feed efficiency in Angus cattle

Estimated breeding values for average daily feed intake (AFI; kg/day), residual feed intake (RFI; kg/day) and average daily gain (ADG; kg/day) were generated using a mixed linear model incorporating genomic relationships for 698 Angus steers genotyped with the Illumina BovineSNP50 assay. Association analyses of estimated breeding values (EBVs) were performed for 41 028 single nucleotide polymorphisms (SNPs), and permutation analysis was used to empirically establish the genome-wide significance threshold (P < 0.05) for each trait. SNPs significantly associated with each trait were used in a forward selection algorithm to identify genomic regions putatively harbouring genes with effects on each trait. A total of 53, 66 and 68 SNPs explained 54.12% (24.10%), 62.69% (29.85%) and 55.13% (26.54%) of the additive genetic variation (when accounting for the genomic relationships) in steer breeding values for AFI, RFI and ADG, respectively, within this population. Evaluation by pathway analysis revealed that many of these SNPs are in genomic regions that harbour genes with metabolic functions. The presence of genetic correlations between traits resulted in 13.2% of SNPs selected for AFI and 4.5% of SNPs selected for RFI also being selected for ADG in the analysis of breeding values. While our study identifies panels of SNPs significant for efficiency traits in our population, validation of all SNPs in independent populations will be necessary before commercialization.
Revisiting the Structure of the Anti-neoplastic Glucans of Mycobacterium bovis Bacille Calmette-Guérin

The attenuated strain of Mycobacterium bovis Bacille Calmette-Guérin (BCG), used worldwide to prevent tuberculosis and leprosy, is also clinically used as an immunotherapeutic agent against superficial bladder cancer. An anti-tumor polysaccharide has been isolated from the boiling water extract of the Tice substrain of BCG and tentatively characterized as consisting primarily of repeating units of 6-linked-glucosyl residues. Mycobacterium tuberculosis and other mycobacterial species produce a glycogen-like α-glucan composed of repeating units of 4-linked glucosyl residues substituted at some 6 positions by short oligoglucosyl units that also exhibits an anti-tumor activity. Therefore, the impression prevails that mycobacteria synthesize different types of anti-neoplastic glucans or, alternatively, the BCG substrains are singular in producing a unique type of glucan that may confer to them their immunotherapeutic property. The present study addresses this question through the comparative analysis of α-glucans purified from the extracellular materials and boiling water extracts of three vaccine substrains. The polysaccharides were purified, and their structural features were established by mono- and two-dimensional NMR spectroscopy and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry of the enzymatic and chemical degradation products of the purified compounds. The glucans isolated by the two methods from the three substrains of BCG were shown to exhibit identical structural features shared with the glycogen-like α-glucan of M. tuberculosis and other mycobacteria. Incidentally, we observed an occasional release of dextrans from Sephadex columns that may explain the reported occurrence of 6-substituted α-glucans in mycobacteria.
Sleep Health: Journal of the National Sleep Foundation

Objective: Sleep varies between individuals in response to sleep-wake history and various environmental factors, including light and noise. Here we report on the intranight variation of the ultradian nonrapid eye movement-rapid eye movement (NREM-REM) sleep cycle in 369 participants who have contributed to different laboratory studies from 1994 to 2020 at the Centre for Chronobiology, Basel, Switzerland
‐ Dimensional Polyoxovanadate Nanoclusters for Enhanced Water Oxidation Catalysis

The oxygen evolution reaction (OER) is critical in electrochemical water splitting and requires an efficient, sustainable and cheap catalyst for successful practical applications. A common development strategy for OER catalysts is to search for facile routes for the synthesis of new catalytic materials with optimized chemical compositions and structures. Here, we report nickel hydroxide Ni(OH) 2 two-dimensional (2D) nanosheets pillared with zero-dimensional (0D) polyoxovanadate (POV) nanoclusters as an OER catalyst that can
Triumph 2 Triumph 1 Scorpion S 1 : 10 senders S 2 : 20 senders R 2 : 20 receivers S 3 : 10 senders R 1 1 Gbps 10 Gbps

Cloud data centers host diverse applications, mixing workloads that require small predictable latency with others requiring large sustained throughput. In this environment, today’s state-of-the-art TCP protocol falls short. We present measurements of a 6000 server production cluster and reveal impairments that lead to high application latencies, rooted in TCP’s demands on the limited buffer space available in data center switches. For example, bandwidth hungry “background” flows build up queues at the switches, and thus impact the performance of latency sensitive “foreground” traffic. To address these problems, we propose DCTCP, a TCP-like protocol for data center networks. DCTCP leverages Explicit Congestion Notification (ECN) in the network to provide multi-bit feedback to the end hosts. We evaluate DCTCP at 1 and 10Gbps speeds using commodity, shallow buffered switches. We find DCTCP delivers the same or better throughput than TCP, while using 90% less buffer space. Unlike TCP, DCTCP also provides high burst tolerance and low latency for short flows. In handling workloads derived from operational measurements, we found DCTCP enables the applications to handle 10X the current background traffic, without impacting foreground traffic. Further, a 10X increase in foreground traffic does not cause any timeouts, thus largely eliminating incast problems.
Rapid Detection, Complete Genome Sequencing, and Phylogenetic Analysis of Porcine Deltacoronavirus

In February 2014, porcine deltacoronavirus (PDCoV) was identified in the United States. We developed a PDCoV real-time reverse transcription PCR that identified PDCoV in 30% of samples tested. Four additional PDCoV genomes from the United States were sequenced; these had ≈99%–100% nt similarity to the other US PDCoV strains.