Miracle-dz/UniFAR-FTUs huggingface dataset:
FLAMs: A self-replicating ex vivo model of alveolar macrophages for functional genetic studies

Alveolar macrophages (AMs) are tissue resident cells in the lungs derived from the fetal liver that maintain lung homeostasis and respond to inhaled stimuli. While the importance of AMs is undisputed, they remain refractory to standard experimental approaches and high-throughput functional genetics as they are challenging to isolate and rapidly lose AM properties in standard culture. This limitation hinders our understanding of key regulatory mechanisms that control AM maintenance and function. Here, we describe the development of a new model, fetal liver-derived alveolar-like macrophages (FLAMs), which maintains cellular morphologies, expression profiles, and functional mechanisms similar to murine AMs. FLAMs combine treatment with two key cytokines for AM maintenance, GM-CSF and TGFβ. We leveraged the long-term stability of FLAMs to develop functional genetic tools using CRISPR-Cas9-mediated gene editing. Targeted editing confirmed the role of AM-specific gene Marco and the IL-1 receptor Il1r1 in modulating the AM response to crystalline silica. Furthermore, a genome-wide knockout library using FLAMs identified novel genes required for surface expression of the AM marker Siglec-F, most notably those related to the peroxisome. Taken together, our results suggest that FLAMs are a stable, self-replicating model of AM function that enables previously impossible global genetic approaches to define the underlying mechanisms of AM maintenance and function.
Neural mechanisms to exploit positional geometry for collision avoidance

Visual motion provides rich geometrical cues about the three-dimensional configuration the world. However, how brains decode the spatial information carried by motion signals remains poorly understood. Here, we study a collision avoidance behavior in Drosophila as a simple model of motion-based spatial vision. With simulations and psychophysics, we demonstrate that walking Drosophila exhibit a pattern of slowing to avoid collisions by exploiting the geometry of positional changes of objects on near-collision courses. This behavior requires the visual neuron LPLC1, whose tuning mirrors the behavior and whose activity drives slowing. LPLC1 pools inputs from object- and motion-detectors, and spatially biased inhibition tunes it to the geometry of collisions. Connectomic analyses identified circuitry downstream of LPLC1 that faithfully inherits its response properties. Overall, our results reveal how a small neural circuit solves a specific spatial vision task by combining distinct visual features to exploit universal geometrical constraints of the visual world.
Mesh Network Reliability Analysis for Ultra-Reliable Low-Latency Services

In a mesh network, to ensure high reliability and low latency, we can explore path diversity. In other words, a packet can be transmitted using all active links in a network to reach the destination. Here, a critical, difficult issue is to calculate the end-to-end reliability of a mesh network, given the reliability of each active link. In this paper, we derive the mesh network reliability with a new approach, which is of lower computational cost and more scalable than the state-of-the-art. Based on a Markov model, the closed-form network reliability as a polynomial expression of link reliability is obtained using the Hop-State Algorithm (HSA). Furthermore, we propose two metrics to assist in selecting the links in a network for routing to ensure performance while reducing link cost. From the analysis and simulation evaluations, exploring path diversity can effectively support Ultra-Reliable Low-Latency (URLL) services.
Low-power high-frequency class-AB two-step sampling switched-current techniques

The development of a class-AB technique in two-step sampling switched currents (S/sup 2/I) is presented. The technique offers a significant improvement over the conventional class-A S/sup 2/I in terms of both linearity and a figure-of-merit combining speed, power consumption, and signal-to-noise ratio. In addition, it enables the S/sup 2/I scheme to operate at lower supply voltages responding to the demand for a supply reduction in modern digital CMOS processes. An experimental S/sup 2/I sample-and-hold circuit based on two parallel S/sup 2/I memories achieved better than -63 dB total harmonic distortion, 63.6 dB signal-to-noise ratio, and dissipated 1.45 mW at more than 120-MHz sampling rate and a supply voltage of 2.4 V. These indicate an overall improvement by a factor of about 2.9 in comparison with the test results obtained from the class-A S/sup 2/I sample-and-hold circuit designed to operate at exactly the same conditions.
RELATIONSHIPS BETWEEN REMOTELY SENSED REFLECTANCE DATA AND COTTON GROWTH AND YIELD

Remotely sensed electromagnetic reflectance data can provide at relatively low cost a set of detailed, spatially distributed data on plant growth and development. Vegetation indices based on algebraic combinations of different wavelength bands are especially useful in summarizing reflectance data. One of the most commonly used vegetation indices is the normalized difference vegetation index, or NDVI. The objective of this study was to determine whether measurements based on the NDVI could provide information useful for site-specific management of cotton. Aerial photographs were taken of replicated Acala cotton field experiments in California in which the treatment was water or nitrogen stress level. NDVI integrated over time showed a significant correlation with lint yield in those experiments in which there was a significant stress effect on yield. The spatiotemporal pattern of NDVI reflected stress factors and was approximately coincident with the onset of measurable water stress. NDVI tended to indicate the presence of nitrogen stress even in those cases where the stress did not result in a significant yield reduction. In a study of the correlation of NDVI with late season plant mapping indices NDVI was correlated with nodes above white flower and strongly correlated with nodes above cracked boll. An alternative vegetation index, the relative nitrogen vegetation index, was not better than NDVI as an indicator of nitrogen stress.
Pilot plan protocol for optimization of UV dose required to obtain an appropriate municipal wastewater disinfection

In this work a simple but comprehensive protocol for ultraviolet (UV) pilot plant studies was developed in order to meet the microbiological guidelines established by the Andalusian Regional Government (ARG) and Aguas de Jerez, Empresa Municipal, S.A. (AJEMSA). For this purpose, two pilot UV disinfection systems were tested at the municipal wastewater treatment plant in Jerez de la Frontera (Spain) over a period of thirteen months. Both pilot units were operated using unfiltered secondary wastewater. The results obtained from the pilot plant experiments suggest that an average UV dose of 50 mW s/cm 2 is sufficient to meet required microbiological quality standards. The quality of the unfiltered wastewater shows that turbidity and total suspended solids could serve as good indicators for UV transmittance variations. The key parameters for an optimum protocol definition are temporal wastewater characterization, the planning and executing of UV disinfection experiments, determining the hydraulic behaviour of the UV channel, calculating the UV dose applied and, finally, evaluating experimental data.
Codes in Star and Bubble-sort graphs

The objects under consideration are codes in Cayley graphs of the symmetric group, namely in Star and Bubble-sort graphs. The tables of optimal codes in the Star graphs S5 and S6 are presented. We suggest several infinite series of completely regular codes with covering radius 1 in the Bubble-sort graphs and enumerate the intersection arrays of these codes in the Star graphs $S_{5}, S_{6}$ and the Bubble-sort graphs B4 and B5. For obtaining the results of the paper, binary linear programming was used in a combination with traditional techniques.
Computational Modeling of Sarcomere Protein Mutations and Drug Effects on Cardiac Muscle Behavior

Hypertrophic and Dilated Cardiomyopathies are caused by inherited mutations in sarcomeric proteins: Myosin (M), Troponin (Tn), Tropomyosin (Tm) and Myosin Binding Protein-C (MyBP-C). A quantitative understanding of how mutations change protein behaviour, and hence cardiac muscle contraction, and how adaptations to these changes result in disease, could accelerate the design of novel personalized treatments and therapeutics. Newly developed multiscale computational tools, tightly interlaced with multiple experiments, can enhance efforts to correct the problems associated with cardiomyopathies and prevent or more effectively manage the disease. Using these computational tools, we examined the effects of mutations in myosin and troponin on cardiac muscle contractility and overall heart functional behaviour. We also examined the effects of potential therapeutics that modulate protein interactions and cardiac muscle contractility.
An Analysis of Feature Selection Techniques For COVID-19 Detection on Chest X-Ray Data

We are currently experiencing a worldwide health problem known as the coronavirus pandemic, many researchers are looking to help in any way they can to deal with the pandemic and the problems caused by it. In the context of machine learning research, it is possible to develop methods to assist with the screening of patients using different types of exams and machine learning techniques. In this paper, we investigate the use of different features selection methods with different classifiers to the task of covid-19 (and other five pathologies and healthy lungs) identification in chest x-rays images. The analysis of the experimental results shows that the application of feature selection methods can improve the detection of coronavirus as well as other pathologies.
Empirical Bayes Procedure for Ranking Sites for Safety Investigation by Potential for Safety Improvement

The identification of sites requiring investigation for possible safety treatment is one of the most important aspects of infrastructure safety management and has been the subject of considerable research aimed at improving the efficiency of the process. The more recent techniques use the empirical Bayes (EB) method for estimating the safety of specific sites. A refinement of the EB method that is conceptually sound and inherently simple to apply is the focus of this research. With this refinement, the EB estimate of the safety of a site is compared with its expected safety to determine the potential for safety improvement, which forms the basis for ranking sites for safety investigation. A comparative evaluation is provided of the proposed method against other EB methods and the more conventional ones, with data for signalized intersections and two-lane rural highway sections. The refined EB method is shown to be comparatively efficient.
Prediction of Evacuation Time for Emergency Planning Zone of Uljin Nuclear Site

The time for evacuation of residents in emergency planning zone(EPZ) of Uljin nuclear site in case of a radiological emergency was estimated with traffic analysis. Evacuees were classified into 4 groups by considering population density, local jurisdictions, and whether they ate residents or transients. The survey to investigate the behavioral characteristics of the residents was made for 200 households and included a hypothetical scenario explaining the accident situation and questions such as dwelling place, time demand for evacuation preparation transportation means for evacuation, sheltering place, and evacuation direction. The microscopic traffic simulation model, CORSIM, was used to simulate the behavior of evacuating vehicles on networks. The results showed that the evacuation time required for total vehicles to move out from EPZ took longer in the daytime than at night in spite that the delay times at intersections were longer at night than in the daytime. This was analyzed due to the differences of the trip generation time distribution. To validate whether the CORSIM model fan appropriately simulate the congested traffic phenomena assumable in case of emergency, a benchmark study was conducted at an intersection without an actuated traffic signal near Uljin site during the traffic peak-time in the morning. This study indicated that the predicted output by the CORSIM model was in good agreement with the observed data. satisfying the purpose of this study.
Periodic Analysis of Nonlinear Virtual Analog Models

We present a novel framework for analyzing virtual analog models in the periodic regime. It allows the derivation of the harmonic structure of the periodic response of a model, an essential quantity to learn how well it reproduces the timbre of the system of interest, and how much aliasing error is present in that response, a crucial concern for nonlinear models. We show how our approach, founded on the Galerkin method, performs that analysis effectively and reliably, for static and dynamic systems, and we perform a side-by-side numerical model comparison study for a diode clipper circuit with it. We also present a new stability result for anti-aliasing methods.
The Influence of the Characteristics of the Traffic Flow and the Structure of Vehicles on the Energy Consumption and Ecological Safety of Passenger Transportation : case of Vologda, Russia

The purpose of the study is to clarify the applied indicator of “dynamic vehicle dimensions” characterizing the size of a section of a city street occupied by a car during its movement. This indicator directly affects the value of the “dynamic passenger size”. In the case of relatively free traffic during between-peak times and when driving during rush hour, the indicators change quite a lot due to changes in average speed, deceleration during braking and the distance between cars. For the above cases, the specific values of energy consumption, travel time and financial costs for the movement of a conventional passenger by different modes of transport were calculated: a car, a bus on traditional fuel, a trolleybus, an electric bus, a bicycle and an electric scooter. The total contribution to environmental pollution with the current structure of the traffic flow has been determined and a forecast calculation has been made when it changes with an increase in the share of electric transport. The resulting refined mathematical model of energy consumption for the movement of one passenger, with refined variables, makes it possible to predict the effect of changing the structure of the traffic flow and its characteristics to assess promising approaches to reduce energy consumption in transport and improve the environmental situation.
Target Acquisition with UAVS: Vigilance Displays and Advanced Cueing Interfaces

Future Uninhabited Aerial Vehicles (UAVs) will require operators to switch quickly and efficiently from supervisory to manual control. Utilizing a vigilance task in which threat detections (critical signals) led observers to perform a subsequent manual target acquisition task, the present investigation revealed that the type of vigilance display might have important design implications for future UAV systems. A sensory display format resulted in more threat detections, fewer false alarms, and faster target acquisition times and imposed a lighter workload than a cognitive display format. Thus, the former may be the best display arrangement for future UAV controllers. Additionally, advanced visual, spatial audio, and haptic cueing interfaces enhanced acquisition performance over no cueing in the target acquisition phase of the task, and did so to a similar degree. This finding suggests that advanced cueing interfaces may also prove useful in future UAV systems and that these interfaces are functionally interchangeable.
Innovation by Information Technology Recombination: How Artificial Intelligence Progressive Web Apps Foster Sustainable Development

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Treatment of AML Relapse After Allo-HCT

With advances in allogeneic hematopoietic stem cell transplant (allo-HCT), disease relapse has replaced transplant-related mortality as the primary cause of treatment failure for patients with acute myeloid leukemia (AML). The efficacy of allo-HCT in AML is a consequence of a graft-versus-leukemia (GVL) effect that is mediated by T lymphocytes, and unique mechanisms of immune evasion underlying post-allo-HCT AML relapses have recently been characterized. Relapsed AML following allo-HCT presents a particularly vexing clinical challenge because transplant-related toxicities, such as graft-versus-host (GVHD) and infections, increase the risk of treatment-related morbidity and mortality. In general, the prognosis of relapsed AML following allo-HCT is poor with most patients failing to achieve a subsequent remission and 2-year survival consistently <15%. The two factors that have been found to predict a better prognosis are a longer duration of post-transplant remission prior to relapse and a lower disease burden at the time of relapse. When considered in combination with a patient’s age; co-morbidities; and performance status, these factors can help to inform the appropriate therapy for the treatment of post-transplant relapse. This review discusses the options for the treatment of post-transplant AML relapse with a focus on the options to achieve a subsequent remission and consolidation with cellular immunotherapy, such as a second transplant or donor lymphocyte infusion (DLI). While intensive reinduction therapy and less intensive approaches with hypomethylating agents have long represented the two primary options for the initial treatment of post-transplant relapse, molecularly targeted therapies and immunotherapy are emerging as potential alternative options to achieve remission. Herein, we highlight response and survival outcomes achieved specifically in the post-transplant setting using each of these approaches and discuss how some therapies may overcome the immunologic mechanisms that have been implicated in post-transplant relapse. As long-term survival in post-transplant relapse necessarily involves consolidation with cellular immunotherapy, we present data on the efficacy and toxicity of both DLI and second allo-HCT including when such therapies are integrated with reinduction. Finally, we provide our general approach to the treatment of post-transplant relapse, integrating both novel therapies and our improved understanding of the mechanisms underlying post-transplant relapse.
Nuchal Skinfold Thickness in Pediatric Brain Tumor Patients

Background Severe obesity and tumor relapse/progression have impact on long-term prognosis in pediatric brain tumor patients. Methods In a cross-sectional study, we analyzed nuchal skinfold thickness (NST) on magnetic-resonance imaging (MRI) follow-up monitoring as a parameter for assessment of nuchal adipose tissue in 177 brain tumor patients (40 World Health Organization (WHO) grade 1–2 brain tumor; 31 grade 3–4 brain tumor; 106 craniopharyngioma), and 53 healthy controls. Furthermore, body mass index (BMI), waist-to-height ratio, caliper-measured skinfold thickness, and blood pressure were analyzed for association with NST. Results Craniopharyngioma patients showed higher NST, BMI, waist-to-height ratio, and caliper-measured skinfold thickness when compared to other brain tumors and healthy controls. WHO grade 1–2 brain tumor patients were observed with higher BMI, waist circumference and triceps caliper-measured skinfold thickness when compared to WHO grade 3–4 brain tumor patients. NST correlated with BMI, waist-to-height ratio, and caliper-measured skinfold thickness. NST, BMI and waist-to-height ratio were associated with increased blood pressure. In craniopharyngioma patients with hypothalamic involvement/lesion or gross-total resection, rate and degree of obesity were increased. Conclusions NST could serve as a novel useful marker for regional nuchal adipose tissue. NST is highly associated with body mass and waist-to-height ratio, and easily measurable in routine MRI monitoring of brain tumor patients.
Modeling of alpha-particle-induced soft error rate in DRAM

Alpha-particle-induced soft error in 256 M DRAM was numerically investigated. A unified model for alpha-particle-induced charge collection and a soft-error-rate simulator (SERS) was developed. We investigated the soft error rate of 256 M DRAM and identified the bit-bar mode as one of dominant modes for soft error. In addition, for the first time, it was found that trench-oxide depth has a significant influence on soft error rate, and it should be determined by the tradeoff between soft error rate and cell-to-cell isolation characteristics.
NK Cells and Innate-Like T Cells After Autologous Hematopoietic Stem Cell Transplantation in Multiple Sclerosis

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system, in which autoreactive T and B cells play important roles. Other lymphocytes such as NK cells and innate-like T cells appear to be involved as well. To name a few examples, CD56bright NK cells were described as an immunoregulatory NK cell subset in MS while innate-like T cells in MS were described in brain lesions and with proinflammatory signatures. Autologous hematopoietic stem cell transplantation (aHSCT) is a procedure used to treat MS. This procedure includes hematopoietic stem/progenitor cell (HSPC) mobilization, then high-dose chemotherapy combined with anti-thymocyte globulin (ATG) and subsequent infusion of the patients own HSPCs to reconstitute a functional immune system. aHSCT inhibits MS disease activity very effectively and for long time, presumably due to elimination of autoreactive T cells. Here, we performed multidimensional flow cytometry experiments in peripheral blood lymphocytes of 27 MS patients before and after aHSCT to address its potential influence on NK and innate-like T cells. After aHSCT, the relative frequency and absolute numbers of CD56bright NK cells rise above pre-aHSCT levels while all studied innate-like T cell populations decrease. Hence, our data support an enhanced immune regulation by CD56bright NK cells and the efficient reduction of proinflammatory innate-like T cells by aHSCT in MS. These observations contribute to our current understanding of the immunological effects of aHSCT in MS.