Miracle-dz/UniFAR-FTUs huggingface dataset:
COMPOSITE VS. DISTRIBUTED CURVE NUMBERS: EFFECTS ON ESTIMATES OF STORM RUNOFF DEPTHS 1

ABSTRACT: The U.S. Department of Agriculture Curve Number (CN) method is one of the most common and widely used techniques for estimating surface runoff and has been incorporated into a number of popular hydrologic models. The CN method has traditionally been applied using compositing techniques in which the area weighted average of all curve numbers is calculated for a watershed or a small number of sub‐watersheds. CN compositing was originally developed as a time saving procedure, reducing the number of runoff calculations required. However, with the proliferation of high speed computers and geographic information systems, it is now feasible to use distributed CNs when applying the CN method. To determine the effect of using composited versus distributed CNs on runoff estimates, two simulations of idealized watersheds were developed to compare runoff depths using composite and distributed CNs. The results of these simulations were compared to the results of similar analyses performed on an urbanizing watershed located in central Indiana and show that runoff depth estimates using distributed CNs are as much as 100 percent higher than when composited CNs are used. Underestimation of runoff due to CN compositing is a result of the curvilinear relationship between CN and runoff depth and is most severe for wide CN ranges, low CN values, and low precipitation depths. For larger design storms, however, the difference in runoff computed using composite and distributed CNs is minimal.
Sound Source Identification Combining Compressed Sensing Sparse Sampling and Equivalent Source Method

A sound source identification method, combining compressed sensing(CS) sparse sampling and equivalent source method (ESM) is presented in this paper. Six monopoles were numerically simulated through 15×15 grid points and 8×8 ones under different frequency levels of 500, 1100 and 2000 Hz. Then an experiment was carried out with six speakers. Compared with the traditional ESM, CS based ESM has higher source localization accuracy in case of less data sampling points. The experiment demonstrates the feasibility and effectiveness of the proposed method in the sound sources localization and identification.
Atypical Cervical Potts Spine with Multiple Level Epidural Collection: A Case Series of Three Patients

Introduction: Cervical Pott’s constitutes about 10% of all Pott’s spine cases. In tuberculous spondylitis, initially there occurs destruction of vertebral bodies and further progression may result in adjacent abscesses, leading to cord compression. Objective is to excise the diseased focus and to provide spinal stability. Case Report: We are presenting 3 rare cases of cervical Pott’s spine with epidural collection at multiple levels in the cervical region without significant vertebral body destruction that were followed up for a period of 1 year postoperatively. Patients underwent single-level corpectomy and decompression from anterior aspect. In all three cases, we were able to decompress the cord and remove all the collections and also achieved spinal stabilization. Patients had a gradual and complete recovery of motor power within 6 months to 1 year after surgery. Conclusion: Technique used allows accurate visual assessment of the extent of the disease and allows complete decompression of the cord at multiple levels in cervical spine without causing much instability.
Tuberculosis among Yanomami communities from Alto Rio Negro,State of Amazonas, Brazil, 1990 to 2002

Background: Brazilian indigenous populations show high tuberculosis rates, which can be attributable not only to socio-economic conditions and poor access to health care services, but also to an intrinsic susceptibility of these individuals. We describe the distribution of tuberculosis cases in two Yanomami communities, and focus on the occurrence of familial clustering of TB cases. Methods: We have performed a descriptive study of TB cases in the Yanomami communities of Ariabu and Maturaca (Sao Gabriel da Cachoeira, AM, Brazil) between 1990 and 2002, based on medical records provided by health care professionals working in the area. The communities studied are located close to each other, separated by a river, but sharing the same environmental resources, with no differences in social, economic or housing conditions. Results: In this period, 101 cases of TB were registered, corresponding to an estimated annual incidence after active surveillance of 1,082/100,000 at Ariabu and 2,452/100,000 at Maturaca. Multicase families were significantly more frequent in Maturaca community, independent of family size, suggesting familial aggregation (p<0.001). Conclusions: Tuberculosis is a serious problem among the Yanomami. TB control in Yanomami communities will require improvement in housing conditions, active surveillance, contact tracing and diagnosis. Yanomami multicase families should be investigated as a potential group with hyper-susceptibility to tuberculosis.
Selenadiazole Inhibited Adenovirus-Induced Apoptosis through the Oxidative-Damage-Mediated Bcl-2/Stat 3/NF-κB Signaling Pathway

Human adenovirus type 7 (HAdV7) infection causes severe pneumonia, yet there are still no breakthroughs in treatment options for adenovirus, and the road to antiviral drug development faces major challenges. We attempted to find new drugs and we stumbled upon one: selenadiazole. Selenadiazole has been shown to have significant anti-tumor effects due to its unique chemical structure and drug activity. However, its effectiveness against viruses has not been evaluated yet. In our study, selenadiazole also showed superior antiviral activity. In vitro experiments, selenadiazole was able to inhibit adenovirus-mediated mitochondrial-oxidative-damage-related apoptosis, and in in vivo experiments, selenadiazole was able to inhibit apoptosis by modulating the apoptotic signaling pathway Bcl-2/Stat3/NF-κB, etc., and was able to largely attenuate adenovirus-infection-induced pneumonia and lung injury in mice. This study aims to describe a new antiviral treatment option from the perspective of anti-adenovirus-mediated oxidative stress and its associated apoptosis and to provide theoretical guidance for the treatment of clinical adenovirus infection to a certain extent.
The Role of the Oxidative State and Innate Immunity Mediated by TLR7 and TLR9 in Lupus Nephritis

Lupus nephritis (LN) is a severe complication of systemic lupus erythematosus (SLE) and is considered one of the leading causes of mortality. Multiple immunological pathways are involved in the pathogenesis of SLE, which makes it imperative to deepen our knowledge about this disease’s immune-pathological complexity and explore new therapeutic targets. Since an altered redox state contributes to immune system dysregulation, this document briefly addresses the roles of oxidative stress (OS), oxidative DNA damage, antioxidant enzymes, mitochondrial function, and mitophagy in SLE and LN. Although adaptive immunity’s participation in the development of autoimmunity is undeniable, increasing data emphasize the importance of innate immunity elements, particularly the Toll-like receptors (TLRs) that recognize nucleic acid ligands, in inflammatory and autoimmune diseases. Here, we discuss the intriguing roles of TLR7 and TLR9 in developing SLE and LN. Also included are the essential characteristics of conventional treatments and some other novel and little-explored alternatives that offer options to improve renal function in LN.
Enhancing Cyclone Intensity Prediction for Smart Cities Using a Deep-Learning Approach for Accurate Prediction

Accurate cyclone intensity prediction is crucial for smart cities to effectively prepare and mitigate the potential devastation caused by these extreme weather events. Traditional meteorological models often face challenges in accurately forecasting cyclone intensity due to cyclonic systems’ complex and dynamic nature. Predicting the intensity of cyclones is a challenging task in meteorological research, as it requires expertise in extracting spatio-temporal features. To address this challenge, a new technique, called linear support vector regressive gradient descent Jaccardized deep multilayer perceptive classifier (LEGEMP), has been proposed to improve the accuracy of cyclone intensity prediction. This technique utilizes a dataset that contains various attributes. It employs the Herfindahl correlative linear support vector regression feature selection to identify the most important characteristics for enhancing cyclone intensity forecasting accuracy. The selected features are then used in conjunction with the Nesterov gradient descent jeopardized deep multilayer perceptive classifier to predict the intensity classes of cyclones, including depression, deep depression, cyclone, severe cyclone, very severe cyclone, and extremely severe cyclone. Experimental results have demonstrated that LEGEMP outperforms conventional methods in terms of cyclone intensity prediction accuracy, requiring minimum time, error rate, and memory consumption. By leveraging advanced techniques and feature selection, LEGEMP provides more reliable and precise predictions for cyclone intensity, enabling better preparedness and response strategies to mitigate the impact of these destructive storms. The LEGEMP technique offers an improved approach to cyclone intensity prediction, leveraging advanced classifiers and feature selection methods to enhance accuracy and reduce error rates. We demonstrate the effectiveness of our approach through rigorous evaluation and comparison with conventional prediction methods, showcasing significant improvements in prediction accuracy. Integrating our enhanced prediction model into smart city disaster management systems can substantially enhance preparedness and response strategies, ultimately contributing to the safety and resilience of communities in cyclone-prone regions.
Exploring the Impact of Prompt Engineering on ChatGPT 3.5 Text Summarization: A BERT Score Evaluation

In the domain of Natural Language Processing (NLP), the technique of prompt engineering is a strategic method utilized to guide the responses of models such as ChatGPT. This research explores the intricacies of prompt engineering, with a specific focus on its effects on the quality of summaries generated by ChatGPT 3.5, an openly accessible chatbot developed by OpenAI. The study encompasses a comprehensive examination of 110 summaries produced from ten diverse paragraphs, employing eleven distinct summarization prompts under zero-shot setting. Evaluation is conducted using the BERT Score, a metric that offers a more contextually relevant assessment of summary quality. This study introduces an innovative approach to appraising the quality of summaries, setting it apart from prior investigations and delivering valuable insights into the nuances of prompt engineering's role within the NLP landscape. Ultimately, this inquiry illuminates the strengths and weaknesses associated with various prompts and their influence on ChatGPT 3.5's summarization capabilities, thereby making a significant contribution to the constantly evolving field of NLP and automated text summarization.
On a Magical Mystery Tour with 8-Bromo-Cyclic ADP-Ribose: From All-or-None Block to Nanojunctions and the Cell-Wide Web

A plethora of cellular functions are controlled by calcium signals, that are greatly coordinated by calcium release from intracellular stores, the principal component of which is the sarco/endooplasmic reticulum (S/ER). In 1997 it was generally accepted that activation of various G protein-coupled receptors facilitated inositol-1,4,5-trisphosphate (IP3) production, activation of IP3 receptors and thus calcium release from S/ER. Adding to this, it was evident that S/ER resident ryanodine receptors (RyRs) could support two opposing cellular functions by delivering either highly localised calcium signals, such as calcium sparks, or by carrying propagating, global calcium waves. Coincidentally, it was reported that RyRs in mammalian cardiac myocytes might be regulated by a novel calcium mobilising messenger, cyclic adenosine diphosphate-ribose (cADPR), that had recently been discovered by HC Lee in sea urchin eggs. A reputedly selective and competitive cADPR antagonist, 8-bromo-cADPR, had been developed and was made available to us. We used 8-bromo-cADPR to further explore our observation that S/ER calcium release via RyRs could mediate two opposing functions, namely pulmonary artery dilation and constriction, in a manner seemingly independent of IP3Rs or calcium influx pathways. Importantly, the work of others had shown that, unlike skeletal and cardiac muscles, smooth muscles might express all three RyR subtypes. If this were the case in our experimental system and cADPR played a role, then 8-bromo-cADPR would surely block one of the opposing RyR-dependent functions identified, or the other, but certainly not both. The latter seemingly implausible scenario was confirmed. How could this be, do cells hold multiple, segregated SR stores that incorporate different RyR subtypes in receipt of spatially segregated signals carried by cADPR? The pharmacological profile of 8-bromo-cADPR action supported not only this, but also indicated that intracellular calcium signals were delivered across intracellular junctions formed by the S/ER. Not just one, at least two. This article retraces the steps along this journey, from the curious pharmacological profile of 8-bromo-cADPR to the discovery of the cell-wide web, a diverse network of cytoplasmic nanocourses demarcated by S/ER nanojunctions, which direct site-specific calcium flux and may thus coordinate the full panoply of cellular processes.
Three-dimensional numerical study of shallow convective clouds and precipitation induced by land surface forcing

A state-of-the-art mesoscale atmospheric model was used to investigate the three-dimensional structure and evolution of shallow convective clouds and precipitation in heterogeneous and homogeneous domains. In general, the spatial distribution of clouds and precipitation is strongly affected by the landscape structure. When the domain is homogeneous, they appear to be randomly distributed. However, when the landscape structure triggers the formation of mesoscale circulations, they concentrate in the originally dry part of the domain, creating a negative feedback which tends to eliminate the landscape discontinuities, and spatially homogenize the land water content. The land surface wetness heterogeneity of the domain and the toted amount of water vapor present in the atmosphere (locally evapotranspired and/or advected) affect the precipitation regime. In general, the upward motion of mesoscale circulations generated by landscape heterogeneities is stronger than thermal cells induced by turbulence. Furthermore, their ability to transport moist, warm air to higher elevations increases the amount of water that can be condensed and precipitated. The evolution of shallow convective clouds and precipitation consists of a “build-up phase” during which turbulence is predominant and responsible for the moistening of the atmosphere. In heterogeneous domains, it is also responsible for the creation of horizontal pressure gradients leading to the generation of mesoscale circulations. This phase occurs during the morning hours. From about 1200 until 1600 LST, clouds develop and most of the precipitation is produced. This is the “active phase. ” After 1600 LST, the horizontal thermal and pressure gradients, which fed the energy necessary to create and sustain the mesoscale circulations, gradually disappear. This is the “dissipation phase. ” The differences and similarities obtained between three-dimensional and two-dimensional simulations were also studied. These simulations indicate that, unless the landscape presents a clear two-dimensional structure, the use of such a two-dimensional model is not appropriate to simulate this type of clouds and precipitation. Conversely, two-dimensional simulations can be confidently used, provided that the simulated domain presents a two-dimensional heterogeneity.
Debates, Dilemmas, and Discoveries

Integr Environ Assess Manag 2020:525–530 Debates, Dilemmas, and Discoveries (3D) offers rapid publication on compelling and timely issues. Contributions should answer the “so what? ” question and should encourage readers to think, challenge them to do better science, and motivate them to excel in the ways in which they apply science to environmental assessment and management. The new feature will provide a platform to: report on progress in fi eld and laboratory research explore new or emerging research questions provide opinions and perspectives on a range of environmental topics debate issues spotlight management policies and practices share challenges and insights on biology, chemistry, ecology, engineering and sustainability Guidelines and Submission: Manuscripts should be concise and written for a broad audience of policy makers, scientists, and business professionals. Manuscripts are limited to 1000 words and may include no more than 1 table or fi gure and up to 6 references. Manuscripts are subject to review and approval by the 3D Editors. Submit any questions and manuscripts directly to the 3D Editors (ieam3d@setac.org). In a Nutshell. Debates, Dilemmas, and Discoveries 525
Developing and deploying a new member of the dental team: a pediatric oral health therapist.

There are inadequate numbers of dentists able and willing to treat America's children, specifically children from low income and minority populations. This has led to the well-publicized disparities in oral health among children. In the early part of the 20th century New Zealand faced a significant problem with oral disease among its children and introduced a School Dental Service, staffed by allied dental professionals with two years' training in caring for the teeth of children, "school dental nurses. " A significant number of countries have adopted the model. This article reviews the history of attempts to develop such an approach in the United States. It advocates for the development and deployment of pediatric oral health therapists as a means of addressing the disparities problem that exists in America with such individuals being trained in children's dentistry in a two-year academic program. The article asserts that adding a pediatric oral health therapist to the dental team is one way in which the profession of dentistry can fulfill its moral obligation to care for the oral health of America's children and ensure that all children are treated justly. Recently, the American Association of Public Health Dentistry promulgated a strategic plan that endorsed such an approach.
Individual Differences in Movements in Response to Natural Disasters

Natural disasters requiring travel to safety include hurricanes, wildfires, floods, earthquakes, and tsunamis. Computational models and agent-based simulations of disaster evacuation and travel behavior have been developed to help disaster planners; however, these models may entail unrealistic assumptions regarding uniform human behavior. Many of these models assume people travel immediately after a disaster notification and that people travel straight out of the area likely to be affected. The present study provides two examples from Christchurch, New Zealand: a small scale but detailed measure of travel behavior after a real tsunami warning was issued and a larger scale study of self-report of considerations of leaving the city after a major local earthquake. In the tsunami study, 15% of the people actually moved towards the tsunami risk zones, not away. In the second study only 11.7% of the 206 people surveyed indicated thinking of leaving the city and they were significantly more likely to be female and high in trait neuroticism. Individual differences in responses to natural disasters need to be considered in disaster travel models.
Dynamical predictability of seasonal monsoon rainfall: problems and prospects

The conceptual basis and the current status of dynamical prediction of the seasonal mean monsoon rainfall are reviewed. The monsoon may be viewed as a combination of a planetary-scale wavenumber-one circulation and a regional fluctuating Hadley circulation. The planetary-scale component is governed primarily by the sea surface temperature in the Pacific, and is well simulated by general circulation models. These models, however, suffer from systematic errors in the simulation of the regional component, which seems to be sensitive to a number of physical processes. The simulation of the mean rainfall over the Indian region is quite sensitive to the initial conditions, whereas simulations over the Pacific or the Sahel are not. It is hypothesised that the internal dynamics play an important role in determining even the low-frequency variability over the Indian region. Evidence is presented that there are strong intraseasonal oscillations over the Indian region during the northern hemisphere summer, and that these oscillations are the result of the internal dynamics
of Clinical and Basic Cardiology

circulation and thus triglyceride enrichment of LDL by the increased CETP activity. After hydrolysis triglyceride enriched LDL become small dense and highly atherogenic lipoproteins [9]. The small dense LDL particles are more prone to oxidative modification than larger LDL subfractions, comparable to the increased oxidizibility of VLDL-subfractions prepared from patients with renal insufficiency [10].
Turbulent kinetic energy and its dissipation rate of the Indonesian throughflow region via Lombok and Savu Straits

Turbulent kinetic energy (TKE) and its dissipation rate are estimated at Lombok (115° 50’E, 8° 30 ¢ S) and Savu (122°E, 9° 30 ¢ S) strait of Indonesian Throughflow (ITF), in the upper and middle layers. It is the region having most complicated geometry of the world ocean. TKE is of the order of 10 3 m 2 s -2 in the upper layer whereas it is 10 -4 m 2 s -2 in the middle layer. Corresponding values of TKE dissipation rate are of the order of 10 -6 m 2 s -3 and 10 -8 m 2 s -3 .
Supplementary Material of U-RED: Unsupervised 3D Shape Retrieval and Deformation for Partial Point Clouds

Fig. 1 illustrates the detailed network architecture that we employed for U-RED, including parallel feature encoders (a), residual-guided retrieval network (b), graph attention based deformation network (c) and reconstruction head (d). Note that the reconstruction head is only used for joint training. The input point cloud is roughly calibrated to the canonical view by using arbitrary category-level pose estimators [2, 3, 7, 8]. Since the network itself has a certain resistance to rotational interference, we don’t need the estimated rotation results to be extremely accurate. In this paper, for fair comparisons, we follow ROCA [3]’s pose estimator. The parallel feature encoders are adopted for extracting point-wise and global features {F,G} from the target partial point cloud T , {F ,G} for the corresponding full shape T f (only in training) and {F,G} for sources shapes O in the database, as introduced in Sec. 3.1 of our main text. All encoders for T , T f and O share the same network architecture. The point-wise features are extracted by the MLP directly, while the corresponding global features are generated by applying max-pooling to the aforementioned point-wise features. Our residual-guided retrieval network is a 4-layers MLP with batch normalization [4]. The input of the retrieval network is the concatenation of partial features {F,G}, source shape features G and the normalized full shape indicator Ĝ . In training, Ĝ is the normalized G . During inference, Ĝ is replaced by G which is sampled on the surface of the unit sphere Ω. Taking these features, the retrieval network outputs the residual field R = {Ri ∈ R, i = 1, . ,M} to accomplish our noise-robust one-to-many retrieval. The deformation network utilizes an AGNN with crossattention and self-attention module as described in Sec. 3.3