Miracle-dz/UniFAR-FTUs huggingface dataset:
Advancing Diagnostic Model Evaluation to Better Understand Water Shortage Mechanisms in Institutionally Complex River Basins

Water resources systems models enable valuable inferences on consequential system stressors by representing both the geophysical processes determining the movement of water and the human elements distributing it to its various competing uses. This study contributes a diagnostic evaluation framework that pairs exploratory modeling with global sensitivity analysis to enhance our ability to make inferences on water scarcity vulnerabilities in institutionally complex river basins. Diagnostic evaluation of models representing institutionally complex river basins with many stakeholders poses significant challenges. First, it needs to exploit a large and diverse suite of simulations to capture important human‐natural system interactions as well as institutionally aware behavioral mechanisms. Second, it needs to have performance metrics that are consequential and draw on decision‐relevant model outputs that adequately capture the multisector concerns that emerge from diverse basin stakeholders. We demonstrate the proposed model diagnostic framework by evaluating how potential interactions between changing hydrologic conditions and human demands influence the frequencies and durations of water shortages of varying magnitudes experienced by hundreds of users in a subbasin of the Colorado River. We show that the dominant factors shaping these effects vary both across users and, for an individual user, across percentiles of shortage magnitude. These differences hold even for users sharing diversion locations, demand levels or water right seniority. Our findings underline the importance of detailed institutional representation for such basins, as institutions strongly shape how dominant factors of stakeholder vulnerabilities propagate through the complex network of users.
A Multidepth Load-Balance Scheme for Clusters of Congested Cells in Ultradense Cellular Networks

Densely deploying small cells will be a solution to provide explosive data requirements in fifth-generation networks. Because users often cluster together in popular locations of an urban area, congested small cells in the popular sites are also gathered. Traditional load balancing schemes generally only consider neighboring cells when offloading users are not suitable for clusters of overloaded cells. This paper considers groups of overloaded cells in the load balancing problem. The objective is to maximize the quality-of-service satisfaction ratio. To solve the problem, we propose a multidepth offloading algorithm with the consideration of the radio resource allocation. The proposed multidepth offloading algorithm can be applied no matter that congested small cells are gathered or not. Compared with a previous offloading algorithm and a baseline, the simulation results show that our proposed algorithm can increase 16% QoS satisfaction ratio in a real user distribution and 13% QoS satisfaction ratio in a clustered user placement.
The Role of BLNK in Avian B-cell Development

BLNK is an adaptor protein that functions in B-cell receptor signalling, and is vitally necessary at signalling checkpoints of mammalian B-cell development. However, its importance to avian B-cell development remains unclear. To explore the function of BLNK in chickens, shRNAmediated RNA interference was delivered to a chicken B-cell line in vitro by replicationcompetent avian retrovirus (RCAS), and effective shRNA were determined. To observe an shRNA phenotype on chicken B-cell development, we simultaneously explored whether RCAS penetrance was correlated between red blood cells (RBC) and bursal B-cells by infecting chicken embryos with RCAS expressing a fluorescent tag. We found that RCAS penetrance was correlated between RBC and B-cells, which provides a system to observe any in vivo effects of BLNK shRNA on B-cell development. Furthermore, this system for observing BLNK function may be complemented by genetically-modified BLNK, particularly variants resistant to RNA
Rumen–reticulum organ mass and rumen mucosa surface area of white-tailed deer (Odocoileus virginianus) consuming two energy diets

Flexibility in gut morphology has fitness consequences in herbivores. To accommodate dietary variation in energy concentration, rumen–reticulum absorptive capacity and organ mass might also covary. We hypothesized that low energy diets result in greater food intake but lower volatile fatty acid concentrations. The consequence would be heavy rumen–reticulum organs and low absorptive capacity. We measured rumen–reticulum organ mass and absorptive capacity in captive white-tailed deer (Odocoileus virginianus (Zimmermann, 1780)) from central Texas, USA. Deer consumed a pelleted ration, ad libitum, of 1.77 kcal/g (low) or 2.67 kcal/g (standard) digestible energy from the time animals were weaned. In December, 4.5- and 5.5-year-old deer were euthanized, the rumen–reticulum was extracted, thoroughly rinsed, wrung out, and weighed. Four 1 cm × 3 cm samples were extracted from four regions of the rumen and mucosal surface area was measured. Our surrogate of food intake and mastication intensity was first molar height. Molar height was lower in animals consuming the low energy diet. Analyses indicated sex-specific responses. Males eating the low energy diet had heavier rumen–reticulum organs, but females did not. Females consuming the low energy diet had a lower surface enlargement factor, but males did not. The processes driving variation in rumen–reticulum morphology from dietary variation require further examination.
Towards Interpretable Reinforcement Learning with State Abstraction Driven by External Knowledge

Advances in deep reinforcement learning have demonstrated its effectiveness in a wide variety of domains. Deep neural networks are capable of approximating value functions and policies in complex environments. However, deep neural networks inherit a number of drawbacks. Lack of interpretability limits their usability in many safety-critical realworld scenarios. Moreover, they rely on huge amounts of data to learn efficiently. This may be suitable in simulated tasks, but restricts their use to many real-world applications. Finally, their generalization capability is low, the ability to determine that a situation is similar to one encountered previously. We present a method to combine external knowledge and interpretable reinforcement learning. We derive a rule-based variant version of the Sarsa(λ) algorithm, which we call Sarsa-rb(λ), that augments data with prior knowledge and exploits similarities among states. We demonstrate that our approach leverages small amounts of prior knowledge to significantly accelerate the learning in multiple domains such as trading or visual navigation. The resulting agent provides substantial gains in training speed and performance over deep q-learning (DQN), deep deterministic policy gradients (DDPG), and improves stability over proximal policy optimization (PPO). key words: reinforcement learning, symbolic reinforcement learning, reasoning about knowledge, interpretable reinforcement learning
Evaluation of Ground Displacements Caused by Installing Jet Grouted Columns Using Machine Learning Methods

During the jet grouting process, large volumes of high pressurized fluids injected into the soils will cause significant ground displacements, which may bring harmful impacts on surrounding environment. Therefore, it is essential to provide an accurate estimation of the ground displacement in the design stage. Based on multiple nonlinear regression (MNLR) and support vector regression (SVR), the prediction approaches are established, respectively. The column radius (Rc), Young’s modulus (E), and distance from column center to target point (LOA) are selected as the input parameters, while the displacement of target point A at the radial direction (δA) is taken as the output parameter. Comparisons results on the prediction performance of ground displacements indicate that the MNLR-based approach has a better prediction effect. The design charts of the MNLR-based approach for predicting the ground displacement are created, which will be helpful for the practicing engineers to get a quick estimation.
Naturally occurring melatonin: Sources and possible ways of its biosynthesis.

According to recent reports, the global market for melatonin is worth 700 million USD in 2018 and would reach 2,790 million USD by 2025, growing at a CAGR of 18.9% during 2019 to 2025. Having regard to the prevalence of sleep and circadian rhythm disorders and a clear tendency to increase the demand for melatonin, and the current lack of alternative green and cost-efficient technologies of its synthesis, the supply of this remedy will not be enough to guarantee melatonin supply and affordability on a global scale. The emergence of naturally occurring melatonin and its isomers in fermented foods has opened an exciting new research area; there are still, however, some obscure points in the efficient microbiological biosynthesis of melatonin. This review summarizes the research progress and recent evidence related to melatonin and its isomers in various foodstuffs. Additionally, one possible way to synthesize melatonin is also discussed. The evidence pointed out that the presence of melatonin and its isomers is not exclusive for grapes and grape-derived products, because it can be also found in sweet and sour cherries. However, different species of both Saccharomyces and non-Saccharomyces yeasts could be used to obtain melatonin and melatonin isomers in the process of alcoholic fermentation biotechnologically. The availability of L-tryptophan has been a key factor in determining the concentration of indolic compounds produced, and the utilization of probiotic lactic acid bacteria could help in the formation of melatonin isomers during malolactic fermentation. These approaches are environmentally friendly alternatives with a safer profile than conventional ones and could represent the future for sustainable industrial-scale melatonin production.
Digital Psychological Platform for Mass Web-Surveys

Web-surveys are one of the most popular forms of primary data collection used for various researches. However, mass surveys involve some challenges. It is required to consider different platforms and browsers, as well as different data transfer rates using connections in different regions of the country. Ensuring guaranteed data delivery in these conditions should determine the right choice of technologies for implementing web-surveys. The paper describes the solution to transfer a questionnaire to the client side in the form of an archive. This technological solution ensures independence from the data transfer rate and the stability of the communication connection with significant survey filling time. The conducted survey benefited the service of education psychologists under the federal Ministry of Education. School psychologists consciously took part in the survey, realizing the importance of their opinion for organizing and improving their professional activities. The desire to answer open-ended questions in detail created a part of the answers in the dataset, where there were several sentences about different aspects of professional activity. An important challenge of the problem is the Russian language, for which there are not as many tools as for the languages more widespread in the world. The survey involved 20,443 school psychologists from all regions of the Russian Federation, both from urban and rural areas. The answers did not contain spam, runaround answers, and so on as evidenced by the average response time. For the surveys, an authoring development tool DigitalPsyTools.ru was used.
Research on group behavior model based on neural network computing

Compute is a term coined from the etymology of French and Latin words computer and computare respectively, so is computing. This field of computing has grown enormously over the years. From the simple, traditional Turing machine invented in 1936 by Alan Turing to the current neural network (NN) computing. NNs, a field of artificial intelligence (AI) was exhilarated from the structure and inner workings of the brain. Just as the brain is, that is, an interconnection of neurons, so is the NN which is an interconnection of basic structures known as the perceptron. They do not differ much in structure. Their only difference is that one is artificial while the other is entirely biological. The hierarchical intricacies of the NN can be represented in three layers: the perceptron, artificial NN (ANN), and deep NN (DNN). With the influx of mental and behavioral disorders, basic surveillance, and the urgency to improve the mental health of people, studying the behavioral dynamics of people is requisite. CCTV and street cameras can only do so much, thus the need to employ the field of NN which makes use of supervised learning in training the models to perfect and automate surveillance. The results of this retrospective research indicate that the use of the NN model surpasses those of traditional methods in terms of efficiency and reliability.
Coevolutionary dynamics of polyandry and selfish genetic elements

Segregation distorters located on sex chromosomes are predicted to sweep to fixation and cause extinction via a shortage of one sex, but in nature they are often found at low, stable frequencies. One potential resolution to this long-standing puzzle involves female multiple mating (polyandry). Because many meiotic drivers severely reduce the sperm competitive ability of their male carriers, females are predicted to evolve more frequent polyandry and thereby promote sperm competition when a meiotic driver invades. Consequently, the driving chromosome’s relative fitness should decline, halting or reversing its spread. We used formal modeling to show that this initially appealing hypothesis cannot resolve the puzzle alone: other selective pressures (e.g. low fitness of drive homozygotes) are required to establish a stable meiotic drive polymorphism. However, polyandry and meiotic drive can strongly affect one another’s frequency, and polyandrous populations may be resistant to the invasion of rare drive mutants.
PHYSICAL-CHEMICAL CHARACTERIZATION, PHENOLIC CONTENT AND CONSUMER PREFERENCES OF Apis mellífera HONEY IN SOUTHERN JALISCO, MÉXICO

Apiculture in México has been used as an instrument for development of marginal rural communities because it generates a large number of jobs (Magaña et al., 2012). México is among the f irst producers and exporters of honey in the world; in 2015 it was in sixth place, producing 61,881t and third as an exporter, exporting 45,000t with a value of US$ 150×106 (SAGARPA, 2016). The state of Jalisco is the third producer of honey in México, contributing 10%. In this state, apiculture directly benefits 40,000 producers and indirectly 400,000 more people; over 42,000 families depend on this activity. It has become a generator of foreign currency in the hands of 800 to 1,000 beekeepers, 50% of whom are concentrated in the Southern and Southeastern part of the state. Of Jalisco’s honey producers, 58.5% have commercial and/or semi-commercial production. They are not limited to bulk production of this foodstuff but have a diversified and industrialized production (Contreras-Escareño et al., 2013). Honey is a sweet natural substance produced by bees (Apis mellifera L) from flower nectars, which are secretions or excretions that the bees suck out and transform using a combination of specific substances (Martin et al., 2014). The composition of honey is so varied that there are no (34mm). Antioxidant capacity showed values of 35.364 -16.371 and, 52.787 12. 189μM Trolox equivalent (TE)/100g honey, respectively. Total phenolic content varied between 62.131 and 136.841mg GA/100g. Of the studied population, 88% consumes honey; of these, 48% consume it because of its health benefits and 23% use it as a sweetener. Consumers prefer amber-toned honey of natural flavor and liquid consistency in presentations of 500 and 1000ml. Fifty-one percent of the consumers acquire honey directly from producers and 26% in commercial establishments. They are willing to pay US$ 3.33-4.44 per liter. Because of its quality, the honey studied from the municipalities of Southern Jalisco is suitable for commercialization in international markets, and could generate economic resources for the region. SUMMARY
Bypass fat: Applications and its production process for feeding ruminants in the tropic

The objective of this review is to describe the general aspects, the importance of protected fats in feeding of ruminants and review some aspects about their processing and obtaining in order to encourage the scientific community of the tropics to implement processes of research in this important area of animal production. The results of the use in ruminant feeding and the saponification flowcharts for making soap using sodium, potassium and calcium, for sheep tallow and for palm oil residue are evaluated. It is noticed that there is improvement in the production parameters with bypass fat, as well as the milk quality both in cattle, sheep and goats and reproductive parameters in dairy cattle, with decrease in the negative energy balance on the body condition of the animals, which improve evidenced postpartum conception rates and the reduction of open days. Likewise, the performance in meat production where an increase in weight gain and channel performance is recorded is also evaluated. A scientific space research in the search of methods of energy supplementation in ruminants in physiological stages of high requirements for the use of available resources in the tropics to potentiate ruminant production is stimulated. It is concluded that bypass fat have a positive effect on the productive and reproductive parameters of ruminant animals. However, it is necessary to perform the economic evaluation to establish the use rates.
Functional studies of Ci-Gsx gene in the developing central nervous system of Ciona intestinalis

Gsx genes encode for members of ParaHox family of transcription factor and are highly conserved throughout the animal kingdom. They are expressed mainly in the developing CNS in members of all major groups of metazoans. Gsx function, in the few organisms in which it has been investigated, is related re the specification of neural progenitors and in the regulation of the dorso-ventral patterning of the vertebrate neural rube. In the ascidian Ciona inlesrinalis, the model organism used in this work, a single Gsx ortholog has been identified, named Ci-gsx, whose zygotic expression is localized in the developing CNS, including the precursors of the ocellus photoreceptor cells. Clana ocellus, a pigmented multicellular photoreceptive organ, despite its simplicity, possesses functional and molecular similarities to vertebrate eye, thus representing a valuable tool to study the basic mechanisms of eye development. The aim of my PhD work has been the investigation of Ci-gsx function in the early specification of photoreceptor cells in Ciona intestinalis. To this end, I used targeted perturbation of Ci-gsx: activity. This study indicated that Ci-gsx is actually involved in the molecular pathway controlling photoreceptor cells differentiation, upstream of Ci-Rx, a key gene for ocellus development. In addition, a detailed analysis of the 5' Ci-gsx regulatory region allowed me to identify the minimal promoter region responsible for Ci-gsx expression. Furthermore, I demonstrated that a member of Sox. family is likely involved in Ci-gsx transcriptional activation. I also identified Ci-msxb as a possible repressor of Ci-gsx extpression in pigment cell lineage. My data insert a new piece in the genetic cascade controlling early specification of Ciona sensory organs and represent a first evidence of a potential implication of a Gsx ParaHox. gene in this process, thus opening new perspectives OD the role. still controversial. of Gsx gene in the ancestor of bilaterians.
Epigenetic Suppression of the CTNNA1 Gene, Encoding the α-Catenin Protein, which Is Located in the 5q31 Critical Deleted Region in Malignant Myeloid Disorders with del(5q).

Recurring interstitial loss of all or part of the long arm of chromosome 5, del(5q), is associated with myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). Although the affected genes have not been identified, two critical deleted regions (CDR) on 5q have been established, a proximal CDR located in 5q31, and another distal CDR in 5q32–33. We investigated the expression of 28 genes located in the 5q31 CDR, in enriched populations of normal hematopoietic stem cells (HSCs) and leukemic initiating cells (L-ICs) by the reverse transcription polymerase chain reaction (RT-PCR). Of the 28 5q CDR genes investigated, 12 (42%) were expressed in HSCs (CD34+Thy-1+CD38-Lin-), including HNRPA0 (Hs.77492), LOC51306 (Hs.82035), SMAP (Hs.5464), CDC23 (Hs.153546), LOC51307 (Hs.102469), LOC51780 (Hs.24125), EGRI (Hs.326035), ETF1 (Hs.77324), HSBPA9B (Hs.3069), CTNNA1 (Hs.178452), MATR3 (Hs.223745) and UBE2D2 (Hs.108332). We also isolated L-ICs (CD34+CD123+CD38-Lin-) from 11 cases of MDS/AML with 5q-, and investigated their expression levels of these 12 HSC genes. Expression of CTNNA1 was not detected in the L-ICs of 8 of the 11 cases of del(5q) MDS/AML using standard RT-PCR, while the other 11 genes were expressed in each patient at levels comparable to those of HSCs. Quantitative analysis of CTNNA1 expression in L-ICs by real-time RT-PCR confirmed expression levels
Proteostasis perturbation destabilizes respiratory complex assembly-intermediates via aggregation of subunits

Proteostasis is maintained by optimum expression, folding, transport, and clearance of proteins. Deregulation of any of these processes triggers widespread protein aggregation and loss of function. Here, we perturbed proteostasis by blocking proteasome-mediated protein degradation and investigated proteome partitioning from soluble to insoluble fraction. Aggregation of Respiratory Chain Complex (RCC) subunits highlights the early destabilization event as revealed by proteome redistribution. Sequence analyses followed by microscopy suggest that low complexity regions at the N-terminus are capable to facilitate aggregation of RCC subunits. As a result, respiratory complex assembly process is impaired due to destabilization of sub-complexes marking the onset of mitochondrial dysfunction and ROS accumulation. Redistribution of Histone proteins and their modifications indicated reprogramming of transcription as adaptive response. Together, we demonstrate susceptibility of RCC subunits to aggregation under multiple proteotoxic stresses providing an explanation for the simultaneous deregulation of proteostasis and bioenergetics in age-related degenerative conditions.