Miracle-dz/UniFAR-FTUs huggingface dataset:
The changing carbon balance of tundra ecosystems: results from a vertically-resolved peatland biosphere model

An estimated 1700 Pg of carbon is frozen in the Arctic permafrost and the fate of this carbon is unclear because of the complex interaction of biophysical, ecological and biogeochemical processes that govern the Arctic carbon budget. Two key processes determining the region’s long-term carbon budget are: (a) carbon uptake through increased plant growth, and (b) carbon release through increased heterotrophic respiration (HR) due to warmer soils. Previous predictions for how these two opposing carbon fluxes may change in the future have varied greatly, indicating that improved understanding of these processes and their feedbacks is critical for advancing our predictive ability for the fate of Arctic peatlands. In this study, we implement and analyze a vertically-resolved model of peatland soil carbon into a cohort-based terrestrial biosphere model to improve our understanding of how on-going changes in climate are altering the Arctic carbon budget. A key feature of the formulation is that accumulation of peat within the soil column modifies its texture, hydraulic conductivity, and thermal conductivity, which, in turn influences resulting rates of HR within the soil column. Analysis of the model at three eddy covariance tower sites in the Alaskan tundra shows that the vertically-resolved soil column formulation accurately captures the zero-curtain phenomenon, in which the temperature of soil layers remain at or near 0 °C during fall freezeback due to the release of latent heat, is critical to capturing observed patterns of wintertime respiration. We find that significant declines in net ecosystem productivity (NEP) occur starting in 2013 and that these declines are driven by increased HR arising from increased precipitation and warming. Sensitivity analyses indicate that the cumulative NEP over the decade responds strongly to the estimated soil carbon stock and more weakly to vegetation abundance at the beginning of the simulation.
Computer Systems Based on Silicon Photonic Interconnects

We present a computing microsystem that uniquely leverages the bandwidth, density, and latency advantages of silicon photonic interconnect to enable highly compact supercomputer-scale systems. We describe and justify single-node and multinode systems interconnected with wavelength-routed optical links, quantify their benefits vis-a-vis electrically connected systems, analyze the constituent optical component and system requirements, and provide an overview of the critical technologies needed to fulfill this system vision. This vision calls for more than a hundredfold reduction in energy to communicate an optical bit of information. We explore the power dissipation of a photonic link, suggest a roadmap to lower the energy-per-bit of silicon photonic interconnects, and identify the challenges that will be faced by device and circuit designers towards this goal.
Effects of Varicella-Zoster Virus Glycoprotein E Carboxyl-Terminal Mutation on mRNA Vaccine Efficacy

Glycoprotein E (gE) is one of the most abundant glycoproteins in varicella-zoster virus and plays pivotal roles in virus replication and transmission between ganglia cells. Its extracellular domain has been successfully used as an antigen in subunit zoster vaccines. The intracellular C-terminal domain was reported to be decisive for gE trafficking between the endoplasmic reticulum, trans-Golgi network and endosomes and could influence virus spread and virus titers. Considering that the trafficking and distribution of mRNA vaccine-translated gE may be different from those of gE translated against the background of the viral genome (e.g., most gE in virus-infected cells exists as heterodimers with another glycoprotein, gI,), which may influence the immunogenicity of gE-based mRNA vaccines, we compared the humoral and cellular immunity induced by LNP-encapsulated mRNA sequences encoding the whole length of gE, the extracellular domain of gE and a C-terminal double mutant of gE (mutant Y569A with original motif AYRV, which targets gE to TGN, and mutants S593A, S595A, T596A and T598A with the original motif SSTT) that were reported to enhance virus spread and elevate virus titers. The results showed that while the humoral and cellular immunity induced by all of the mRNA vaccines was comparable to or better than that induced by the AS01B-adjuvanted subunit vaccines, the C-terminal double mutant of gE showed stable advantages in all of the indicators tested, including gE-specific IgG titers and T cell responses, and could be adopted as a candidate for both safer varicella vaccines and effective zoster vaccines.
Investigation into Path Loss Propagation at UHF Band in Low Latitude Region

Knowledge of propagation characteristics in the mobile channel is important to the design of a cellular system. It is a major component in the analysis and design of the link budget of a Telecommunication system. This paper deals with the outdoor path loss bahaviour. The study has been conducted in The Polytechnic, Ibadan at GSM frequency 900MHz so as to fit a suitable propagation model within the campus and environs. The experimental data collected from measurements were compared with Cost 231 Hata model, Erickson model and free space models. The results are in good agreement with Cost 231 Hata model. The accuracy of the results is estimated by determine the mean square error between the measured and estimated path loss of the empirical model. The mean square errors, at different height were 2.04, 2.71, 2.90, 1.46, and 1.61dBm. The results are in good agreement with the acceptable international range dBm (Wu and Yuan, 1998).
Novel Perspectives towards RNA-Based Nano-Theranostic Approaches for Cancer Management

In the fight against cancer, early diagnosis is critical for effective treatment. Traditional cancer diagnostic technologies, on the other hand, have limitations that make early detection difficult. Therefore, multi-functionalized nanoparticles (NPs) and nano-biosensors have revolutionized the era of cancer diagnosis and treatment for targeted action via attaching specified and biocompatible ligands to target the tissues, which are highly over-expressed in certain types of cancers. Advancements in multi-functionalized NPs can be achieved via modifying molecular genetics to develop personalized and targeted treatments based on RNA interference. Modification in RNA therapies utilized small RNA subunits in the form of small interfering RNAs (siRNA) for overexpressing the specific genes of, most commonly, breast, colon, gastric, cervical, and hepatocellular cancer. RNA-conjugated nanomaterials appear to be the gold standard for preventing various malignant tumors through focused diagnosis and delivering to a specific tissue, resulting in cancer cells going into programmed death. The latest advances in RNA nanotechnology applications for cancer diagnosis and treatment are summarized in this review.
Modeling and Control Method for High-power Electromagnetic Transmitter Power Supplies

High-power electromagnetic transmitter power supplies are an important part of deep geophysical exploration equipment. This is especially true in complex environments, where the ability to produce a highly accurate and stable output and safety through redundancy have become the key issues in the design of high-power electromagnetic transmitter power supplies. To solve these issues, a high-frequency switching power cascade based emission power supply is designed. By combining the circuit averaged model and the equivalent controlled source method, a modular mathematical model is established with the on-state loss and transformer induction loss being taken into account. A triple-loop control including an inner current loop, an outer voltage loop and a load current forward feedback, and a digitalized voltage/current sharing control method are proposed for the realization of the rapid, stable and highly accurate output of the system. By using a new algorithm referred to as GAPSO, which integrates a genetic algorithm and a particle swarm algorithm, the parameters of the controller are tuned. A multi-module cascade helps to achieve system redundancy. A simulation analysis of the open-loop system proves the accuracy of the established system and provides a better reflection of the characteristics of the power supply. A parameter tuning simulation proves the effectiveness of the GAPSO algorithm. A closed-loop simulation of the system and field geological exploration experiments demonstrate the effectiveness of the control method. This ensures both the system’s excellent stability and the output’s accuracy. It also ensures the accuracy of the established mathematical model as well as its ability to meet the requirements of practical field deep exploration.
Influence of Deep Neuromuscular Blockade on Perioperative Stress Response in Patients Undergoing Robot-Assisted Gastrectomy: A Prospective Double-Blinded Randomized-Controlled Trial

Attenuating the intraoperative stress response is crucial; however, the effect of neuromuscular blockade (NMB) on surgical stress is not completely understood. We aimed to investigate the effects of NMB on the perioperative stress response during robot-assisted gastrectomy. Patients were assigned to the deep or moderate NMB group. Serum cortisol, prolactin, and interleukin-6 (IL-6) levels and natural killer (NK) cell percentage were measured before anesthesia induction, 90 min after pneumoperitoneum, operation end (OPEnd), and postoperative day 1. Additionally, C-reactive protein (CRP) and albumin levels were estimated. Additionally, intraoperative heart rate variability was evaluated. The deep NMB group showed significantly lower levels of low-frequency/high-frequency (HF) ratio at OPEnd compared to the moderate NMB group (1.4 ± 0.2 vs. 2.2 ± 0.3, respectively; Bonferroni corrected p = 0.039). Furthermore, HF power in the deep NMB group was significantly higher at OPEnd than that in the moderate NMB group (45.2 ± 3.6 vs. 33.8 ± 4.0, respectively; Bonferroni corrected p = 0.044). However, no significant differences in cortisol, prolactin, IL-6, CRP, and albumin levels and NK cell percentage were found between the two groups. The degree of NMB may have similar effects on stress-related biological markers in patients undergoing robot-assisted gastrectomy.
Modeling Perception in Autonomous Vehicles via 3D Convolutional Representations on LiDAR

This paper proposes an algorithm to model and process streams of LiDAR data under an autonomous vehicle framework. LiDAR is assumed to be an exteroceptive sensor that allows the vehicle to have dynamic 3D scene perception of its surroundings. We employ an encoder-decoder architecture based on 3D-Convolutional layers called 3D Convolution Encoder-Decoder (3D-CED), together with a transfer learning strategy to extract a set of features from point clouds, which are relevant in the context of autonomous driving. The resulting features allow to make inferences of the future point cloud data and detect multiple abstraction level anomalies in controlled scenarios by utilizing a probabilistic switching dynamic model called High Dimensional Markov Jump Particle Filter (HD-MJPF). Moreover, a comparison is provided between piecewise linear, piecewise nonlinear, and nonlinear predictive models for anomaly detection at multiple abstraction levels. Our approach is evaluated with data collected from the LiDAR sensors of the autonomous vehicle while performing certain tasks in a controlled environment.
The Artists’ Critique on Crowdfunding and Online Gift-Giving

Abstract Crowdfunding is known as a funding solution for creative projects. Creators and business ventures consider crowdfunding as an outlet for promoting creative projects and raising funds. The literature and the media coverage overemphasized its benefits without taking into account key limitations for specific sectors. Based on exploratory, qualitative data gathering, this article investigates what artists expect from crowdfunding and what results from their successful engagement with this funding model. The findings organized in three sequential moments (pre-campaign, during and after) revealed that artists see crowdfunding as a contingent funding resort when other preferred methods are unavailable (subsidies, sponsorship, or labor market opportunities). While expecting to enter markets, artists remain restricted to their social networks, thus reaching successful, yet low funding targets. Artists report that the “investments” in their work resemble gift-giving practices of a costly nature. We interpret these findings as the result of a relative difficulty to reach out to other audiences and match one’s expectations with this funding model.
Stock Movement Prediction with Social Sentiments and Interactional Data: Integrating NLP and Bayesian Frameworks

Stock movement prediction has been a challenging and relevant task for both conventional machine learning and deep learning methods. Multiple approaches have been developed in the literature with the application of machine learning, specifically sentiment analysis with natural language processing. The majority of finance-based machine learning research has been done with a deterministic approach rather than a probabilistic approach. Decision making within the stock market is challenging because of its inherent stochastic nature and volatility. We show that by incorporating social interactional data, such as numbers of likes and dislikes of the social media comments, we can engineer a set of weights to derive a more accurate representation of social sentiments when aggregated across multiple comments. In this paper, we propose a general framework for social reinforcement of public investment sentiments, before presenting both a Naive and Bayesian approach for reinforcing sentiment scores with social interactional data, to improve stock movement predictions when used in conjunction with other models. As a side study, the duration of the impacts of the sentiments and their social reinforcement on the stock movement is examined.
License Plate Fault-Tolerant Characters Recognition Algorithm Based on Color Segmentation and BP Neural Network

According to the license plate recognition problem, this paper did the research about license plate location and characters recognition. It proposed two new algorithms, they separately are license location algorithm based on color segmentation and fault-tolerant characters recognition algorithm based on BP neural network. In the pre-processing stage, it proposed image enhancement algorithm which could make the image more easily analyzed by computer. In the location stage, it made utilization of color and shape information, and then proposed location algorithm. In the recognition stage, it fully made the consideration of characters fault-tolerant, and then made the use of improved BP neural network to recognize characters. Experiments show that the special license plate fault-tolerant characters recognition algorithm is more accurate than the original license plate recognition methods, and its recognition rate has been improved greatly.
The Utility of Scatter Feeding as Enrichment: Do Broiler Chickens Engage with Scatter–Fed Items?

Simple Summary In recent years, there has been increasing interest in providing an enriched environment to broiler chickens. Indeed, many welfare certification companies encourage or require enrichment to be provided. Most of these companies suggest the use of scatter feeding as enrichment material, though there is little scientific evidence to support the implementation of a scatter feeding program. One of the potential benefits of scatter feeding programs may be an observed increase in foraging behavior, and hence overall activity of the birds. This study aimed to understand the impact of scatter feeding on the foraging behavior of broilers. Six groups of broilers were provided with either dried mealworms, whole wheat, shredded cabbage, alfalfa pellets, wood shavings, or no scatter feeding. To maintain the birds’ interest in the enrichment, feed items were only scattered on the first three days of each week. Foraging and feeding behavior were observed via video for one-hour periods immediately after scattering, 2 h later, and 6 h later. Immediately following the scattering of feed items, broilers in all groups showed an increase in foraging, though this was most pronounced in the dried mealworm group. Foraging behavior decreased with age for all groups. The mealworm group also fed less during hour one compared to the later hours. These results did not provide evidence that scatter feeding encourages foraging behavior, except for a short-term effect of a high value food item. Therefore, future studies should examine the feed item and delivery in more detail. Abstract In recent years, welfare certification companies have encouraged the use of scatter feeding as enrichment material, though there is little scientific evidence to support a scatter feeding program. This study aimed to understand the impact of scatter feeding on the foraging behavior of broilers. One hundred eighty Ross 308 chicks were allocated into six treatment groups (six replicates/treatment). Broilers were scatter fed dried mealworms, whole wheat, shredded cabbage, alfalfa pellets, wood shavings, or no scatter feeding, respectively. Enrichment was provided on the first three days of each week. Total foraging, active foraging, and feeding were observed for one-hour periods immediately after scattering, 2 h later, and 6 h later. In all groups, broilers increased both total (p = 0.001) and active (p = 0.001) foraging, though this was most pronounced in the dried mealworm group. Across all groups, active foraging decreased with age (p = 0.001). The mealworm group also showed a corresponding decrease in feeding during hour one compared to the later hours (p = 0.001). These results did not provide evidence that scatter feeding encourages foraging behavior, except for a short-term effect of a high value feed item. This finding suggests that the item scattered and the delivery method should be studied further.
Photonic Encryption using All Optical Logic

With the build-out of large transport networks utilizing optical technologies, more and more capacity is being made available. Innovations in Dense Wave Division Multiplexing (DWDM) and the elimination of optical-electrical-optical conversions have brought on advances in communication speeds as we move into 10 Gigabit Ethernet and above. Of course, there is a need to encrypt data on these optical links as the data traverses public and private network backbones. Unfortunately, as the communications infrastructure becomes increasingly optical, advances in encryption (done electronically) have failed to keep up. This project examines the use of optical logic for implementing encryption in the photonic domain to achieve the requisite encryption rates. In order to realize photonic encryption designs, technology developed for electrical logic circuits must be translated to the photonic regime. This paper examines two classes of all optical logic (SEED, gain competition) and how each discrete logic element can be interconnected and cascaded to form an optical circuit. Because there is no known software that can model these devices at a circuit level, the functionality of the SEED and gain competition devices in an optical circuit were modeled in PSpice. PSpice allows modeling of the macro characteristics of the devices in context of a logic element as opposed to device level computational modeling. By representing light intensity as voltage, 'black box' models are generated that accurately represent the intensity response and logic levels in both technologies. By modeling the behavior at the systems level, one can incorporate systems design tools and a simulation environment to aid in the overall functional design. Each black box model of the SEED or gain competition device takes certain parameters (reflectance, intensity, input response), and models the optical ripple and time delay characteristics. These 'black box' models are interconnected and cascaded in an encrypting/scrambling algorithm based on a study of candidate encryption algorithms. We found that a low gate count, cascadable encryption algorithm is most feasible given device and processing constraints. The modeling and simulation of optical designs using these components is proceeding in parallel with efforts to perfect the physical devices and their interconnect. We have applied these techniques to the development of a 'toy' algorithm that may pave the way for more robust optical algorithms. These design/modeling/simulation techniques are now ready to be applied to larger optical designs in advance of our ability to implement such systems in hardware.
Electroless Ni/Au bumps for flipchip-on-flex and TAB applications

Tape Automated Bonding (TAB) and Flip Chip Bonding (FCB) of bumped dice have been used for a long time already, but only in the most demanding microelectronics assembly operations. This paper reports a low cost electroless Ni/Au wafer bumping process, specially developed for general purpose, high volume Flipchip-on-Flex applications. The bump height, shear strength and other reliability data are given. An assembly method is suggested where such Ni/Au bumped dice are reflow soldered or gang bonded on to the flexible substrate. As the nickel bumps will not collapse during the solder reflow, they are specially suited for high density assemblies like in many recent single and multi chip modules (SCM, MCM). Essential to the low cost and high volume of the assembly process is the fast pick and place operation combined with the one-pass reflow soldering of all components. In TAB applications hard, non-compliant Ni/Au bumps set the bonding parameters which totally differ from those used for soft gold bumps. Various examples of Ni/Au bumps in TAB applications are discussed. <<ETX>>
Overview of the MBMA/AISC Design Guide — Frame Design Using Web-Tapered Members

The Metal Building Manufacturers' Association (MBMA) and the American Institute of Steel Construction (AISC) are finalizing a new addition to the AISC Steel Design Guide series entitled Frame Design Using Web-Tapered Members (Design Guide). This document presents a comprehensive and up-to-date approach to the design of frames using web-tapered members. The methods provided are applications of, and extensions to, the 2005 AISC Specification for Structural Steel Buildings. The new Specification does not include an appendix with provisions for the design of tapered members, unlike previous AISC Specifications dating back to 1978. The new design guide is intended to fill that gap. The recommendations are based on current and recent research into the behavior of web-tapered members. A significant amount of this research was conducted by the document's coauthors at the Georgia Institute of Technology in the preparation of this document. The major sections of the Design Guide are: 1. Introduction, 2. Web-Tapered Member Behavior, 3. Design Basis, 4. Stability Design and Analysis Requirements, 5. Member Design, 6. Frame Design, 7. Annotated Bibliography, 8. Appendices.
NUMERICAL STUDY OF NOISE BARRIER DESIGNS

Noise barriers are commonly used for reduction of highway traffic noise. Optimising the acoustic performance of a barrier is an important task for those involved with designing cost effective barriers. In this paper numerical models for various barrier designs which have been developed using the finite element method are described. The acoustic performance of noise barriers with vertical, arrow, T-shape, Y-shape, wedge-shape and inclined profiles are compared. The effects of the locations of the source and receiver relative to the various noise barrier designs are examined.