Miracle-dz/UniFAR-FTUs huggingface dataset:
A "Domain Wall" Scenario for the AdS/QCD

We propose a scenario for bottom-up gravity dual picture of QCD-like theories, which consists of two near-AdS$_5$ domains separated by the ``domain wall'' at which the effective coupling relatively rapidly switches from small perturbative value at its UV side to strong at its IR side. Its consequence are corresponding jumps in 5-d masses of the bulk fields, related to different anomalous dimensions of the corresponding operators. Inclusion of both weakly and strongly coupled parts of bulk wave functions allows for consistent inclusion of QCD hard processes. We further discuss how transitions from strong to weak coupling in hard observables should look like, exemplified by pion diffractive dissociation, which seems to show this transition experimentally. Then we propose a dynamical mechanism for this jump related to instantons, which are point-like bulk objects located at/near the domain wall. We further argue that in the limit of large number of colors $N_c\to\infty$ the "domain wall" is becoming a true singularity. Instanton-induced contributions to correlators and partition function of the instanton ensemble is reformulated in the $AdS_5$ language. Among other applications are lowest mesons as collective vibrations of the ``domain wall''.
Carbon Sequestration in Turfgrass–Soil Systems

Plants are key components of the terrestrial ecosystem carbon cycle. Atmospheric CO2 is assimilated through photosynthesis and stored in plant biomass and in the soil. The use of turfgrass is expanding due to the increasing human population and urbanization. In this review, we summarize recent carbon sequestration research in turfgrass and compare turfgrass systems to other plant systems. The soil organic carbon (SOC) stored in turfgrass systems is comparable to that in other natural and agricultural systems. Turfgrass systems are generally carbon-neutral or carbon sinks, with the exception of intensively managed areas, such as golf course greens and athletic fields. Turfgrass used in other areas, such as golf course fairways and roughs, parks, and home lawns, has the potential to contribute to carbon sequestration if proper management practices are implemented. High management inputs can increase the biomass productivity of turfgrass but do not guarantee higher SOC compared to low management inputs. Additionally, choosing the appropriate turfgrass species that are well adapted to the local climate and tolerant to stresses can maximize CO2 assimilation and biomass productivity, although other factors, such as soil respiration, can considerably affect SOC. Future research is needed to document the complete carbon footprint, as well as to identify best management practices and appropriate turfgrass species to enhance carbon sequestration in turfgrass systems.
Viral Agents as Potential Drivers of Diffuse Large B-Cell Lymphoma Tumorigenesis

Among numerous causative agents recognized as oncogenic drivers, 13% of total cancer cases occur as a result of viral infections. The intricacy and diversity of carcinogenic processes, however, raise significant concerns about the mechanistic function of viruses in cancer. All tumor-associated viruses have been shown to encode viral oncogenes with a potential for cell transformation and the development of malignancies, including diffuse large B-cell lymphoma (DLBCL). Given the difficulties in identifying single mechanistic explanations, it is necessary to combine ideas from systems biology and viral evolution to comprehend the processes driving viral cancer. The potential for more efficient and acceptable therapies lies in targeted medicines that aim at viral proteins or trigger immune responses to either avoid infection or eliminate infected or cancerous cells. In this review, we aim to describe the role of viral infections and their mechanistic approaches in DLBCL tumorigenesis. To the best of our knowledge, this is the first review summarizing the oncogenic potential of numerous viral agents in DLBCL development.
Complex Mountain Road Extraction in High-Resolution Remote Sensing Images via a Light Roadformer and a New Benchmark

Mountain roads are of great significance to traffic navigation and military road planning. Extracting mountain roads based on high-resolution remote sensing images (HRSIs) is a hot spot in current road extraction research. However, massive terrain objects, blurred road edges, and sand coverage in complex environments make it challenging to extract mountain roads from HRSIs. Complex environments result in weak research results on targeted extraction models and a lack of corresponding datasets. To solve the above problems, first, we propose a new dataset: Road Datasets in Complex Mountain Environments (RDCME). RDCME comes from the QuickBird satellite, which is at an elevation between 1264 m and 1502 m with a resolution of 0.61 m; it contains 775 image samples, including red, green, and blue channels. Then, we propose the Light Roadformer model, which uses a transformer module and self-attention module to focus on extracting more accurate road edge information. A post-process module is further used to remove incorrectly predicted road segments. Compared with previous related models, the Light Roadformer proposed in this study has higher accuracy. Light Roadformer achieved the highest IoU of 89.5% for roads on the validation set and 88.8% for roads on the test set. The test on RDCME using Light Roadformer shows that the results of this study have broad application prospects in the extraction of mountain roads with similar backgrounds.
Observational Constraints, Stellar Models, and Kepler Data for theta Cyg, the Brightest Star Observable by Kepler

The V=4.48 F4 main-sequence star theta Cyg is the brightest star observable in the Kepler spacecraft field-of-view. Short-cadence (58.8 s) photometric data were obtained by Kepler during 2010 June-September. Preliminary analysis shows solar-like oscillations in the frequency range 1200- 2500 microHz. To interpret these data and to motivate further observations, we use observational constraints from the literature to construct stellar evolution and pulsation models for this star. We compare the observed large frequency separation of the solar-like oscillations with the model predictions, and discuss the prospects for gamma Doradus-like g-mode pulsations, given the observational constraints. We discuss the value of angular diameter measurements from optical interferometry for constraining stellar properties and the implications for asteroseismology.
Corrigendum: Explicit Construction of a Small ε -Net for Linear Threshold Functions

We give explicit constructions of ε -nets for linear threshold functions on the binary cube and on the unit sphere. The size of the constructed nets is polynomial in the dimension n and in 1 ε . To the best of our knowledge no such constructions were previously known. Our results match, up to the exponent of the polynomial, the bounds that are achieved by probabilistic arguments. As a corollary we also construct subsets of the binary cube that have size polynomial in n and a covering radius of n 2 − c (cid:112) n log n for any constant c . This improves upon the well-known construction of dual BCH codes that guarantee only a covering radius of n 2 − c √ n .
Efficacy of a Regression Method to Confirm VO 2 max in Middle-Aged and Older Adults: A Pilot Study

Verification testing following a maximal graded exercise test (GXT) has been shown to be effective at indicating whether VO 2 max was attained for middle-aged and older adults but performing two maximal efforts in a single day may not be practical or possible for certain individuals . PURPOSE : To evaluate the efficacy of a regression method for identifying a VO 2 plateau in order to confirm the attainment of VO 2 max. METHODS : Twenty-one recreationally active (VO 2 max: 21.8-50.3 ml/kg/min) middle-aged and older (46-76 yrs.) men (n=11) and women (n=10) completed an individualized ramp GXT on the cycle ergometer, and one hour later, a verification protocol at 105% of their maximal work rate (WR) achieved during the GXT. Verification criterion was met if the difference between the highest VO 2 during the verification was ≤2% greater than the VO 2 max achieved during the GXT. VO 2 plateau was identified by least-squares regression analysis of the 4 minutes immediately prior to the last 2 minutes of the VO 2 -WR curve. Modelled VO 2 max was extrapolated using the VO 2 -WR regression equation and the maximum WR achieved during the GXT. If the difference between modelled and actual VO 2 max was >50% of the slope for the linear portion of the VO 2 -WR relationship relative to the assigned protocol, then a plateau was observed. McNemar’s test of marginal homogeneity was used to detect differences in the proportion of paired data of individuals’ attainment of VO 2 max criteria. RESULTS : Of the 21 participants,15 (71.4%) met the verification criterion while 6 (28.6%) did not, compared to the regression method where 16 (76.2%) achieved the regression criterion while 5 (23.8%) did not. McNemar’s test revealed no significant difference between participants’ ability to achieve the regression and verification criteria (Χ 2 (1)=0, p =. 999). CONCLUSION : The regression method used in this study may be an effective strategy for determining VO 2 plateau and confirming that VO 2 max was attained during a GXT with middle-aged and older adults on a cycle ergometer. This time-efficient regression method is comparable with the verification criterion but does not require a second maximal test, which may be advantageous for those where the verification trial may not be practical.
Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning

Deriving a good variable selection strategy in branch-and-bound is essential for the efficiency of modern mixed-integer programming (MIP) solvers. With MIP branching data collected during the previous solution process, learning to branch methods have recently become superior over heuristics. As branch-and-bound is naturally a sequential decision making task, one should learn to optimize the utility of the whole MIP solving process instead of being myopic on each step. In this work, we formulate learning to branch as an offline reinforcement learning (RL) problem, and propose a long-sighted hybrid search scheme to construct the offline MIP dataset, which values the long-term utilities of branching decisions. During the policy training phase, we deploy a ranking-based reward assignment scheme to distinguish the promising samples from the long-term or short-term view, and train the branching model named Branch Ranking via offline policy learning. Experiments on synthetic MIP benchmarks and real-world tasks demonstrate that Branch Rankink is more efficient and robust, and can better generalize to large scales of MIP instances compared to the widely used heuristics and state-of-the-art learning-based branching models.
Thoughts on ITL’s Draft Paper on ML Explanation

Hi, I’m in EL, Systems Integration Division, where I’m ﬁnishing up a PhD on joint cognitive work (JCW). (I’ve been at NIST for many years, though.) JCW is about AI and people working together on cognitive tasks (as you might if you use tax preparation software to help do your income taxes). Explanation is an important part of JCW. I don’t use neural nets for JCW but Bayesian nets, which, of course, more directly explain. I have studied some of the philosophy of science of explanation (and that of causality, which can be related). My comments below are likely to reﬂect that bias, and also a systems engineering perspective. I hope they are helpful. I’m around, of course, if you’d like to meet virtually.
Control of a microﬂuidic separation process governed by the Zweifach-Fung eﬀect

: This paper presents a microﬂuidic process of separation of a ﬂuid containing particles. The control input is the ratio of ﬂowrates in the two daughter channels of a bifurcation, which due to the Zweifach-Fung eﬀect, has a direct but nonlinear eﬀect on the particle volume fractions in the channels. The dead-volumes of the device and its capillary tubings cause an input-varying delay of hydraulic type. The paper presents several control problems of practical importance and formulates some concise problem statements for future research along with ﬁrst simulation results.
IDN-Sum: A New Dataset for Interactive Digital Narrative Extractive Text Summarisation

Summarizing Interactive Digital Narratives (IDN) presents some unique challenges to existing text summarization models especially around capturing interactive elements in addition to important plot points. In this paper, we describe the first IDN dataset (IDN-Sum) designed specifically for training and testing IDN text summarization algorithms. Our dataset is generated using random playthroughs of 8 IDN episodes, taken from 2 different IDN games, and consists of 10,000 documents. Playthrough documents are annotated through automatic alignment with fan-sourced summaries using a commonly used alignment algorithm. We also report and discuss results from experiments applying common baseline extractive text summarization algorithms to this dataset. Qualitative analysis of the results reveals shortcomings in common annotation approaches and evaluation methods when applied to narrative and interactive narrative datasets. The dataset is released as open source for future researchers to train and test their own approaches for IDN text.
Practice of Epidemiology Multilevel Regression and Poststratification for Small-Area Estimation of Population Health Outcomes: A Case Study of Chronic Obstructive Pulmonary Disease Prevalence Using the Behavioral Risk Factor Surveillance System

A variety of small-area statistical models have been developed for health surveys, but none are sufficiently flexi-ble to generate small-area estimates (SAEs) to meet data needs at different geographic levels. We developed a multilevel logistic model with both state- and nested county-level random effects for chronic obstructive pulmonary disease (COPD) using 2011 data from the Behavioral Risk Factor Surveillance System. We applied poststratification with the (decennial) US Census 2010 counts of census-block population to generate census-block-level SAEs of COPD prevalence which could be conveniently aggregated to all other census geographic units, such as census tracts, counties, and congressional districts. The model-based SAEs and direct survey estimates of COPD prevalence were quite consistent at both the county and state levels. The Pearson correlation coefficient was 0.99 at the state level and ranged from 0.88 to 0.95 at the county level. Our extended multilevel regression modeling and poststratification approach could be adapted for other geocoded national health surveys to generate reliable SAEs for population health outcomes at all administrative and legislative geographic levels of interest in a scalable framework.
Inflations and its uncertainty in Some ECOWAS member states: Transfer entropy approach

This study examines the information flow between inflation and inflation uncertainty (IU) and intrastate inflationary trend among some ECOWAS member states. IU is measured using GARCH models and stochastic volatility model (SV). Transfer entropy was adopted to quantify the extent of information flow. The result showed information flow exists from inflation to the GARCH measure of IU. On the reverse flow from inflation uncertainty to inflation, there is no information flow except for Burkina Faso and Gambia which have asymmetric bidirectional flow between inflation and IU. Adopting SV measure for IU, there are no support for causality from inflation to IU for all the member states except Burkina Faso and Cabo Verde. For the reverse flow, causality exists in all the member states. On the pairwise inflation trend of member states, inflation trends are interconnected and that shocks in one country may transmit to others except for Gambia, Cote d’Ivoire and Burkina Faso. Specifically, Guinea, Liberia and Nigeria inflation shocks have the greatest effect on other WAMZ members within the study period, whereas inflation trend in Benin, Niger and Cote d’Ivoire are the most influential among WAEMU states. In conclusion, inflation - IU relationship is sensitive to how IU is measured leading to mixed findings. This study recommends the need for price stability among the ECOWAS member states. Given the interdependence among some members of each bloc of ECOWAS, policy synchronization on price stability could enhance the overall objective of single digit inflation and reduce the welfare effect of inflation uncertainty.
Research_9897464 1..24

Oxidation modulators regarding antioxidants and reactive oxygen species (ROS) inducers have been used for the treatment of many diseases. However, a systematic review that refers to delivery system for divergent modulation of oxidative level within the biomedical scope is lacking. To provide a comprehensive summarization and analysis, we review pilot designs for delivering the oxidative modulators and the main applications for inflammatory treatment and tumor therapy. On the one hand, the antioxidants based delivery system can be employed to downregulate ROS levels at inflammatory sites to treat inflammatory diseases (e.g., skin repair, bone-related diseases, organ dysfunction, and neurodegenerative diseases). On the other hand, the ROS inducers based delivery system can be employed to upregulate ROS levels at the tumor site to kill tumor cells (e.g., disrupt the endogenous oxidative balance and induce lethal levels of ROS). Besides the current designs of delivery systems for oxidative modulators and the main application cases, prospects for future research are also provided to identify intelligent strategies and inspire new concepts for delivering oxidative modulators.
Effect of plant growth-promoting rhizobacteria inoculation on tomato under commercial shade-house conditions

In the present study, the effect of the inoculation of Plant Growth Promoting Rhizobacteria (root-dwelling bacteria that promote plant growth through various mechanisms, commonly known by the acronym PGPR); LBEndo1 ( Bacillus paralicheniformis ), NFbEndo2M2 ( Acinetobacter guillouiae ), KBEndo3 ( Aeromonas caviae ), and KBEcto4 ( Pseudomonas lini ) were evaluated in tomato plants ( Solanum lycopersicum L. cv ‘Top1182’) into two soil preparations and the use of compost under commercial shade house conditions. Root weight of tomato plant were increased significantly by inoculation with LBEndo1 and KBEcto4 strains, 119.3 and 81.9%, respectively, on composted flatted soil conditions compared to tomato plants control uninoculated. The PGPR treatments also increased fruit number per plant on both soil condition preparations. KBEcto4 was the treatment with the highest number of fruits with 23 tomatoes plant -1 , compared with 18.6 fruits plant -1 control uninoculated on composted flatted soil conditions. The yield and marketable yields were also enhanced by the inoculation of LBEndo1 and KBEcto4 strains in both soil preparations. The plant growth promoting rhizobacteria and the use of organic fertilizer have the potential to be useful under shade house production and is a viable alternative to improving the yield of tomato.
Estimation of the Warfarin Dose

Warfarin is the most widely used oral blood anticoagulant agent worldwide; with more than 30 million prescriptions for this drug in the United States in 2004. The appropriate dose of warfarin is difficult to establish because it can vary substantially among patients, and the consequences of taking an incorrect dose can be severe. If a patient receives a dosage that is too high, they may experience excessive anti-coagulation (which can lead to dangerous bleeding), and if a patient receives a dosage which is too low, they may experience inadequate anti-coagulation (which can mean that it is not helping to prevent blood clots). Because incorrect doses contribute to a high rate of adverse effects, there is interest in developing improved strategies for determining the appropriate dose (Consortium, 2009). Commonly used approaches to prescribe the initial warfarin dosage are the pharmacogenetic algorithm developed by the IWPC (International Warfarin Pharmacogenetics Consortium), the clinical algorithm and a fixed-dose approach. In practice a patient is typically prescribed an initial dose, the doctor then monitors how the patient responds to the dosage, and then adjusts the patient’s dosage. This interaction can proceed for several rounds before the best dosage is identified. However, it is best if the correct dosage can be initially prescribed. This question is motivated by the challenge of Warfarin dosing, and considers a simplification of this important problem, using real data. The goal of this question is to explore the performance of multi-armed bandit algorithms to best predict the correct dosage of Warfarin for a patient without a trial-an-error procedure as typically employed.
Characteristics of coffee producers and plantations in the northern region of the state of Chiapas

Coffee is one of the most consumed agricultural products in the world. Mexico has a planted area of 710 431 ha and a production volume of 953 682 t. Despite its importance, in Mexico there is a lack of regional studies on the characteristics of coffee producers and plantations that serve as a basis for public policy decision-making. The objective of this work was to identify the characteristics of coffee producers and plantations in the municipality of Pantepec, Chiapas. A questionnaire of 76 questions was applied, which was divided into six blocks: informant data, plantation data, labor, financing and commercialization. The sample consisted of 61 producers from five localities of the municipality of Pantepec, Chiapas. The results indicate that producers are on average 41 years old and have low schooling. They have an area of less than two hectares, so the producers have to supplement their income with other activities. Eighty percent produce the landrace variety with renewed plantations, finding that 34.4% replanted two years earlier and 97% used between 100 and 600 new plants. Ninety-five percent of producers obtain yields between 0 and 600 kg ha -1 . Coffee cultivation is an activity that generates roots in the population, however, it requires options that give it added value to generate employment and income in the region of study.
ZDNS: a fast DNS toolkit for internet measurement

Active DNS measurement is fundamental to understanding and improving the DNS ecosystem. However, the absence of an extensible, high-performance, and easy-to-use DNS toolkit has limited both the reproducibility and coverage of DNS research. In this paper, we introduce ZDNS, a modular and open-source active DNS measurement framework optimized for large-scale research studies of DNS on the public Internet. We describe ZDNS's architecture, evaluate its performance, and present two case studies that highlight how the tool can be used to shed light on the operational complexities of DNS. We hope that ZDNS will enable researchers to better---and in a more reproducible manner---understand Internet behavior.