Miracle-dz/UniFAR-FTUs huggingface dataset:
Nano Communication

In the quest of higher wireless data-rates, Terahertz (THz)-band (0.1-10 THz) communication is envisioned as a key wireless technology of the next decade. In parallel to the development of THz transceivers and antennas, simulation tools are needed to expedite the development of communication and networking protocols tailored to this novel networking paradigm, at a fraction of the cost. The few simulation platforms developed to date for THz communication networks do not capture the peculiarities of the THz channel or the capabilities of THz devices. In this paper, TeraSim, i.e., an open source network simulation platform for THz communication networks is presented. TeraSim is built as an extension for ns-3 , which is one of the most widely used teaching and education network simulation software. The simulator has been developed considering two major types of application scenarios, namely, nanoscale communication networks (average transmission range usually below one meter) and macroscale communication networks (distances larger than one meter). The simulator consists of a common channel module, separate physical and link layers for each scenario, and two assisting modules, namely, THz antenna module and energy harvesting module, originally designed for the macroscale and nanoscale scenario, respectively. The structure, relations and content of each module are presented in detail. Extensive simulation and test results are provided to validate the functionalities of the implemented modules. TeraSim is expected to enable the networking community to test THz networking protocols without having to delve into the channel and physical layers.
Organizational Learning As A Mechanism Of Artificial Intelligence In The Generation Of Sustainability

Globalization and the expansion of technologies have resulted in an era of rapid change that forces all organizations to constantly seek solutions to stay current. For this reason, and with the aim of exploring the contributions that artificial intelligence can generate for organizations, the most relevant aspects that resulted from the construction of a bibliographic review of research in the area, a consultation framework for all types of companies, are reviewed below. The selected material was designed to provide a user-friendly guide, especially for students and entrepreneurs who are new to artificial intelligence and data mining
UvA-DARE Making planning support systems matter : improving the use of planning support systems for integrated land use and transport strategy-making

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EAST: Extensible Attentional Self-Learning Transformer for Medical Image Segmentation

—Existing medical image processing models based on Transformers primarily rely on self-attention mechanisms to capture short-range and long-range visual dependencies. However, this approach has limitations in modeling the global context of full-resolution images, resulting in the loss of significant details. In order to address these issues, we propose an Extensible Attentional Self-learning Transformer (EAST) architecture for medical image segmentation. In EAST, tokenized images are input into an extensible attention module, enabling the training of multi-scale representations that effectively capture both fine-grained local interactions and coarse-grained global relationships. This allows for more comprehensive learning of semantic information. The obtained features are then passed through a self-learning module, further refining the representations of different samples to generate a more accurate feature map. To handle high-resolution images, the EAST architecture utilizes a U-shaped structure and skip connections for sequential processing of extensible attention feature maps. Experimental results on the Synapse dataset and ACDC dataset demonstrate the superior performance of our EAST architecture compared to other methods. Additionally, the EAST model is capable of capturing more detailed information, leading to precise localization of structures.
Adjuvant electrochemotherapy of malignant ocular melanoma in a dog

Melanocytoma and malignant melanoma are the most typical eye tumors in dogs and cats. Due to the presence of melanin, the general appearance is often highly pigmented in a nodular formation with well-defined borders. Electrochemotherapy (ECT) is a therapy combining reversible electroporation and anti-neoplastic drugs to enhance their cytotoxic effects through increasing cellular uptake by the electroporated tumor cells. In this article, the use of adjuvant ECT for the treatment of canine ocular melanoma is reported. The pre-surgical exams (blood count, renal and liver functions, echocardiogram, and electrocardiogram) were within the normal range, as were the chest radiography and abdominal ultrasound without signs of metastases. On the day of the surgery, an excisional biopsy of the tumor was performed without safety margins by keratectomy associated with conjunctivectomy and adjuvant ECT in the surgical site and peri-tumoral region. The animal was followed for approximately 7 months and remained without evidence of tumor recurrence. A complete resolution of corneal opacification was also observed. To our knowledge, this is the first report of the use of ECT in an ocular neoplasm. From a comparative oncology perspective, this report opens the way for future therapeutic approaches in superficial ocular cancers in veterinary and human medicine.
The neuronal chromatin landscape in adult schizophrenia brains is linked to early fetal development

Non-coding variants increase risk of neuropsychiatric disease. However, our understanding of the cell-type specific role of the non-coding genome in disease is incomplete. We performed population scale (N=1,393) chromatin accessibility profiling of neurons and non-neurons from two neocortical brain regions: the anterior cingulate cortex and dorsolateral prefrontal cortex. Across both regions, we observed notable differences in neuronal chromatin accessibility between schizophrenia cases and controls. A per-sample disease pseudotime was positively associated with genetic liability for schizophrenia. Organizing chromatin into cis- and trans-regulatory domains, identified a prominent neuronal trans-regulatory domain (TRD1) active in immature glutamatergic neurons during fetal development. Polygenic risk score analysis using genetic variants within chromatin accessibility of TRD1 successfully predicted susceptibility to schizophrenia in the Million Veteran Program cohort. Overall, we present the most extensive resource to date of chromatin accessibility in the human cortex, yielding insights into the cell-type specific etiology of schizophrenia.
scATAC-Ref: a reference of scATAC-seq with known cell labels in multiple species

Abstract Chromatin accessibility profiles at single cell resolution can reveal cell type-specific regulatory programs, help dissect highly specialized cell functions and trace cell origin and evolution. Accurate cell type assignment is critical for effectively gaining biological and pathological insights, but is difficult in scATAC-seq. Hence, by extensively reviewing the literature, we designed scATAC-Ref (https://bio.liclab.net/scATAC-Ref/), a manually curated scATAC-seq database aimed at providing a comprehensive, high-quality source of chromatin accessibility profiles with known cell labels across broad cell types. Currently, scATAC-Ref comprises 1 694 372 cells with known cell labels, across various biological conditions, >400 cell/tissue types and five species. We used uniform system environment and software parameters to perform comprehensive downstream analysis on these chromatin accessibility profiles with known labels, including gene activity score, TF enrichment score, differential chromatin accessibility regions, pathway/GO term enrichment analysis and co-accessibility interactions. The scATAC-Ref also provided a user-friendly interface to query, browse and visualize cell types of interest, thereby providing a valuable resource for exploring epigenetic regulation in different tissues and cell types.
Vestibular function, subjective complaints, perceived disability in daily life, and sports activities in patients with cochlear implants performed during childhood: a prospective cross-section study

Abstract Background Vestibular function (VF) in patients with cochlear implantation (CI) performed during childhood is underinvestigated Objective To study VF in patients receiving CI during childhood Material & Methods Sixty patients (22 females) from 7–34 years old, unilaterally (n = 21) and bilaterally (n = 39) implanted, were included. Deafness was congenital (n = 45), consequential to meningitis (n = 3), skull fracture (n = 1), perinatal CMV infection (n = 1), ototoxic drugs (n = 1), unknown etiology (n = 9). VF was measured between 1 to 22 years after implantation, including calorics, v-HIT, c-VEMPS. Dizziness handicap inventory (DHI), age at independent walking(IW), sport activities were also investigated. Results Nine CI-patients (15%) reported dizziness/vertigo either prior or months to years after surgery. Comparison between symptomatic (15%), asymptomatic (85%), uni-bilaterally CI-patients showed no significant difference on VF’s impairment for calorics (p = .603) and v-HIT (p = 1). Symptoms were not related to vestibular impairment. Age at implantation (p = 0.956), uni- bilateral (p = .32), simultaneous versus sequential (p = .134) did not influence IW age. DHI showed a tendency for being symptomatic at higher implantation age. Interval between CI, IWage, current age between surgery and vestibular evaluation did not have a significant effect on symptomatology. Conclusion & Significance This first middle to long-term evaluation of the VF in CI-patients, implanted in childhood, pointed out that 85% of patients were asymptomatic, with a mean time of >10 years after surgery. Vestibular impairment and symptoms seem to be mainly due to the underlying inner ear’s disease rather than surgery.
Undernutrition risk is independently associated with worsened indicators of hospital rehabilitation in COVID-19 patients

ABSTRACT Objective This study was designed to analyze the association between the risk of undernutrition and indicators of hospital rehabilitation in patients with COVID-19 while controlling for confounding variables. Methods This was an analytical study conducted by analyzing the medical records of patients with COVID-19. A total of 562 adult patients were eligible for the study. In addition to the risk of undernutrition (independent variable), indicators of hospital rehabilitation (dependent variables) were evaluated. These indicators included the length of hospital stay, clinical outcome (discharge or death), food intake, mobility (bedridden status), the use of mechanical ventilation, and the need for enteral nutrition. Pre-existing comorbidities (confounding/control variables) were grouped into cardiovascular, metabolic/endocrine, neurological, chronic obstructive pulmonary disease, and other categories (neoplasms, multiple sclerosis, and kidney disease). A dichotomization model was applied for data analysis. The Chi-Square test was used to verify the association between the risk of undernutrition and the dependent variables. Associations with a significance level of P < 0.05 were subjected to Poisson regression to identify the prevalence ratio. Results Patients at risk of undernutrition had a 90% higher chance of being bedridden and were 35 times more likely to experience a decrease in food intake. They also had an 89% higher chance of using invasive mechanical ventilation and a 91% higher chance of requiring enteral nutrition. Additionally, individuals at risk of undernutrition had a 73% higher chance of death. Adjustment for comorbidities did not alter these associations, demonstrating that the risk of undernutrition is independently associated with indicators of hospital rehabilitation. Conclusion The risk of undernutrition is independently associated with worsened indicators of hospital rehabilitation in patients with COVID-19, including higher prevalence of mortality.
Face Recognition with 3D Head Pose Estimation and Land Mark extraction Using Gabor Wavelets

D pose estimation is the problem of determining the transformation of an object in a 2D image which gives the 3D object. Automatic estimation of head relative to camera centered coordinate system is called head pose estimation. The need for 3D pose estimation arises from the limitations of feature based pose estimation where shape of the head changes due to light and different poses of head. For the detection of head pose, the basic spatial orientation of face are described in this paper.In 3D head pose estimation the faces are scanned and shape ,intensity of image is combined and is used for facial matching. In this paper Gabor jet wavelets is used for getting the accurate land marks for the detection of face. And for detection of head pose we use parametric linear subspace model (PPLS). There are many application of face recognition and head pose estimation such as security, communication and credit card verification to surveillance video image. Index Terms: 3D head pose, Parametric Linear Subspace Model (PPLS), Gabor Wavelets, and Face recognition. …
Small RNA Deep Sequencing of Circulating RNAs Discovers a Unique Panel of microRNAs as Feasible and Reliable Biomarkers of Non-Small Cell Lung Cancers in Northern Thailand

Objective: This study aimed to assess the practicality and reliability of utilizing microRNAs (miRNAs) as a potential screening and diagnosing tool for non-small cell lung cancers (NSCLCs) in Northern Thailand. Methods: Small RNA sequencing and a literature review was performed to obtain a list of serum miRNA candidates. Serum levels of these selected miRNA candidates were measured in patients with NSCLC and healthy volunteers by real-time RT-PCR and receiver operating characteristic curve (ROC) were used to assess diagnostic performance. Results: Sequencing data revealed 148 known miRNAs and 230 novel putative miRNAs in serum samples; 19 serum miRNAs were significantly downregulated and 242 were upregulated. Seven miRNAs selected according to sequencing data and 11 miRNAs according to previous reports were evaluated in training cohort (45 lung cancer patients, 26 controls) and 6 miRNAs were found differentially expressed (p < 0.05, Mann Whitney U test) and associated (p < 0.05, Chi-square test) with NSCLC development. Further analysis and verification identified an optimal combination of 4 miRNAs composed of hsa-miR23a, hsa-miR26b, hsa-miR4488 and novel-130 to provide the optimal AUC of 0.901±0.034. Detection of serum miRNA by real-time RT-PCR showed good reproducibility with the coefficient of variation (CV) ≤ 4%. The optimal screening miRNAs panel was primarily identified through sequencing data of local patient population, thus indicating that the etiology of NSCLCs may differ from one population to other and thus require a unique panel of miRNAs for their identification. Conclusion: Circulating miRNA is a feasible screening tool for NSCLCs. Nevertheless, populations with different lung cancer etiology may need to identify their own most suitable miRNA panel.
Differential effects of disulfide bond formation in TEM‐1 versus CTX‐M‐9 β‐lactamase

To investigate how disulfide bonds can impact protein energy landscapes, we surveyed the effects of adding or removing a disulfide in two β‐lactamase enzymes, TEM‐1 and CTX‐M‐9. The homologs share a structure and 38% sequence identity, but only TEM‐1 contains a native disulfide bond. They also differ in thermodynamic stability and in the number of states populated at equilibrium: CTX‐M‐9 is two‐state whereas TEM‐1 has an additional intermediate state. We hypothesized that the disulfide bond is the major underlying determinant for these observed differences in their energy landscapes. To test this, we removed the disulfide bridge from TEM‐1 and introduced a disulfide bridge at the same location in CTX‐M‐9. This modest change to sequence modulates the stabilities—and therefore populations—of TEM‐1's equilibrium states and, more surprisingly, creates a novel third state in CTX‐M‐9. Unlike TEM‐1's partially folded intermediate, this third state is a higher‐order oligomer with reduced cysteines that retains the native fold and is fully active. Sub‐denaturing concentrations of urea shifts the equilibrium to the monomeric form, allowing the disulfide bond to form. Interestingly, comparing the stability of the oxidized monomer with a variant lacking cysteines reveals the disulfide is neither stabilizing nor destabilizing in CTX‐M‐9, in contrast with the observed stabilization in TEM‐1. Thus, we can conclude that engineering disulfide bonds is not always an effective stabilization strategy even when analogous disulfides exist in more stable structural homologs. This study also illustrates how homo‐oligomerization can result from a small number of mutations, suggesting complex formation might be easily accessed during a protein family's evolution.
Continuous Condensed Triplet Accumulation for Irradiance‐Induced Anticounterfeit Afterglow

Afterglow room‐temperature emission that is independent of autofluorescence after ceasing excitation is a promising technology for state‐of‐the‐art bioimaging and security devices. However, the low brightness of the afterglow emission is a current limitation for using such materials in a variety of applications. Herein, the continuous formation of condensed triplet excitons for brighter afterglow room‐temperature phosphorescence is reported. (S)‐(‐)‐2,2′‐Bis(diphenylphosphino)‐1,1′‐binaphthyl ((S)‐BINAP) incorporated in a crystalline host lattice showed bright green afterglow room‐temperature phosphorescence under strong excitation. The small triplet–triplet absorption cross‐section of (S)‐BINAP in the whole range of visible wavelengths greatly suppressed the deactivation caused by Förster resonance energy transfer from excited states of (S)‐BINAP to the accumulated triplet excitons of (S)‐BINAP under strong continuous excitation. The steady–state concentration of the triplet excitons for (S)‐BINAP reached 2.3 × 10−2 M, producing a bright afterglow. Owing to the brighter afterglow, afterglow detection using individual particles with sizes approaching the diffraction limit in aqueous conditions and irradiance‐dependent anticounterfeiting can be achieved.
Normothermic ex vivo perfusion of deceased donor kidneys and its clinical potential in kidney transplantation outcomes

In recent years, normothermic machine perfusion (NMP) has emerged in conversation surrounding organ preservation and transplantation techniques with the goal of improving patient and clinical outcomes. This is in great attempt to address the rate of non-utilization and the shortage of available organs in kidney transplantation. This focus in mind, normothermic perfusion presents itself as a potential tool to mimic physiological conditions and improve current preservation methods, such as static cold storage. This review serves to improve understanding of the observed connection between the consequences of ischemia and reperfusion injury and traditional preservation techniques as well as how renal NMP may mitigate these issues. Previous studies suggest that reducing time in static cold storage methods by promoting the normothermic perfusion model results in decreased delayed graft function and post-transplant complications. This review also aims to present the immense clinical potential NMP has on future kidney transplantation success and what this means for the fields of nephrology and transplantation. While great strides have been made to evaluate normothermic perfusion’s impact on kidney graft viability and transplant success, future research into unified protocol, clinically relevant biomarkers, cost-utility analysis, and use with associated therapeutic and imaging modalities is paramount.
Interacting Diffusion Processes for Event Sequence Forecasting

Neural Temporal Point Processes (TPPs) have emerged as the primary framework for predicting sequences of events that occur at irregular time intervals, but their sequential nature can hamper performance for long-horizon forecasts. To address this, we introduce a novel approach that incorporates a diffusion generative model. The model facilitates sequence-to-sequence prediction, allowing multi-step predictions based on historical event sequences. In contrast to previous approaches, our model directly learns the joint probability distribution of types and inter-arrival times for multiple events. This allows us to fully leverage the high dimensional modeling capability of modern generative models. Our model is composed of two diffusion processes, one for the time intervals and one for the event types. These processes interact through their respective denoising functions, which can take as input intermediate representations from both processes, allowing the model to learn complex interactions. We demonstrate that our proposal outperforms state-of-the-art baselines for long-horizon forecasting of TPP.
Rainbow subgraphs of uniformly coloured randomly perturbed graphs

For a given $\delta \in (0,1)$, the randomly perturbed graph model is defined as the union of any $n$-vertex graph $G_0$ with minimum degree $\delta n$ and the binomial random graph $\mathbf{G}(n,p)$ on the same vertex set. Moreover, we say that a graph is uniformly coloured with colours in $\mathcal{C}$ if each edge is coloured independently and uniformly at random with a colour from $\mathcal{C}$. Based on a coupling idea of McDiarmird, we provide a general tool to tackle problems concerning finding a rainbow copy of a graph $H=H(n)$ in a uniformly coloured perturbed $n$-vertex graph with colours in $[(1+o(1))e(H)]$. For example, our machinery easily allows to recover a result of Aigner-Horev and Hefetz concerning rainbow Hamilton cycles, and to improve a result of Aigner-Horev, Hefetz and Lahiri concerning rainbow bounded-degree spanning trees. Furthermore, using different methods, we prove that for any $\delta \in (0,1)$ and integer $d \ge 2$, there exists $C=C(\delta,d)>0$ such that the following holds. Let $T$ be a tree on $n$ vertices with maximum degree at most $d$ and $G_0$ be an $n$-vertex graph with $\delta(G_0)\ge \delta n$. Then a uniformly coloured $G_0 \cup \mathbf{G}(n,C/n)$ with colours in $[n-1]$ contains a rainbow copy of $T$ with high probability. This is optimal both in terms of colours and edge probability (up to a constant factor).
On monic abelian trace-one cubic polynomials

We compute the asymptotic number of monic trace-one integral polynomials with Galois group $C_3$ and bounded height. For such polynomials we compute a height function coming from toric geometry and introduce a parametrization using the quadratic cyclotomic field $\mathbb Q(\sqrt{-3})$. We also give a formula for the number of polynomials of the form $t^3 -t^2 + at + b \in \mathbb Z[t]$ with Galois group $C_3$ for a fixed integer $a$.