Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Dietary Replacement of Soybean Meal with Corn Distillers Dried Grain with Solubles on Growth Performance and Carcass Characteristics of Broilers

Xiaopeng Tang1*, Kangning Xiong1, Peng Peng2 and Dun Deng2* 1State Key Laboratory Cultivation for Karst Mountain Ecology Environment of Guizhou Province, School of Karst Science, Guizhou Normal University, Guiyang, China 2Tangrenshen Group, Liyu Industry Park, National High-tech Development Area, Zhuzhou, China Article Information Received 07 February 2020 Revised 30 March 2020 Accepted 23 April 2020 Available online 04 August 2021
Implementation and Verification of Cable Bending Stiffness in MoorDyn: Preprint

The relatively large motions experienced by floating wind turbines and wave energy converters pose a challenge for power cables, whose internal components provide significant bending resistance and are sensitive to deformation. The behavior and associated design considerations of power cables in these highly dynamic applications make coupled analysis relevant for design. Bending stiffness capabilities have recently been added to the lumped-mass mooring dynamics model MoorDyn to enable simulation of dynamic power cables. MoorDyn is a common modeling choice for floating wind energy simulation (often coupled with OpenFAST) and floating wave energy converter simulation (often coupled with WEC-Sim) but the model’s previous line elasticity formulation only considered axial stiffness. To properly capture the dynamics of power cables, a bending stiffness model has been added that approximates cable curvature based on the difference in tangent vectors of adjacent elements. The resulting bending moment is realized by applying forces on adjacent nodes, enabling cable modeling while leaving the underlying lumped-mass formulation unchanged. In this paper, the new bending stiffness implementation is verified in static conditions against analytical solutions and then in a dynamic power cable scenario in comparison with the commercial simulator OrcaFlex. The dynamic scenario uses prescribed motions and includes wave loadings on the cable. Results indicate correct implementation of bending stiffness and show close agreement with OrcaFlex.
Green Synthesized Palladium Coated Titanium Nanotube Arrays for Simultaneous Azo-Dye Degradation and Hydrogen Production

In this study, electrodes of titanium dioxide nanotube arrays (TNAs) were successfully synthesized by applying the anodic oxidation etching method, as well as the use of green synthetic technology to add reducing agents of tea or coffee to reduce metal palladium from palladium chloride. Synthesis of palladium modified TNAs (Pd/TNAs) was conducted by the microwave hydrothermal method after the metal palladium was reduced. In order to identify the surface structure, light absorption and elemental composition, TNAs and Pd/TNAs were characterized by X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD). Furthermore, to test the photocurrent density, electron resistance, and hydroxyl radicals by I-t plot, electrochemistry impedance spectroscopy (EIS), and electron paramagnetic resonance (EPR) were investigated. The photocurrent (4.0 mA/cm2) of Pd/TNAs-C (using coffee as the reducing agent) at +1.0 V (vs. Ag/AgCl) was higher than that of the pure TNAs (1.5 mA/cm2), illustrating that Pd/TNAs-C can effectively separate photogenerated electrons and holes. Pd/TNAs is a favorable material as a photoanode for the photoelectrochemical (PEC) removal of organic pollutants in wastewater.
Making Rewards More Rewarding: Sequential Learnable Environments for Deep Reinforcement Learning-based Sponsored Ranking Nishan Subedi, AdKdd 2021

Reinforcement Learning (RL) methods have risen in popularity among general ranking systems. However, despite having properties suitable for sponsored ranking problems, Reinforcement Learning methods remain under explored in this area. A major reason behind this gap is the dilemma of exploration: random exploration is prohibitively expensive in sponsored search ranking, with the potential to cause significant revenue loss. To address this concern, we study properties of a simulated environment for Reinforcement Learning in sponsored ranking. We demonstrate that by augmenting a learnable simulated environment based on intuitive design principles, we can significantly improve RL performances and boost the explainability of the model. We test our method with a Deep Deterministic Policy Gradient agent, and experimental results show our learned simulated environment outperforms existing methods. Furthermore, since our method is agent agnostic, it paves the way to a wide range of Reinforcement Learning applications to the sponsored ranking problem.
Natural Resource Management in Agriculture : The Analysis and Understanding

In today’s world, agriculture is quite exploitive in nature as far as the uninterrupted use of inorganic fertilizers and pesticides as well as unsustainable use of natural resources are concerned. It is a gospel truth that due to the rising population more and more food grains are necessary, but we must keep in mind that agricultural production and productivity cannot be increased by taking nature at a stake. This paper is prepared through extensive desk research, proper topical development and analysis of the found facts. By the use of several latest eco-friendly and climate smart agricultural methods like conservation agriculture, precision farming, low input farming, roof top gardening etc. the agricultural production and productivity can be increased without harming or exploiting the nature.
Explaining Security Management Evolution through the Analysis of CIOs’ Mental Models

Information Systems are a key factor for firms’ competitiveness. Thus, their efficient management has become a key concern and security management one of the most relevant issues. An empirical study has been developed to determine the characteristics of security management within Small and Medium sized Enterprises (SMEs). A summary of the main data from this study is presented. The results of this study have showed that the evolution of security management within firms has evolved through similar patterns of behaviour. Some phases have been defined to explain the evolution of security management within SMEs. The defined phases are: Growth, Integration, Formalization and Involvement. To explain these phases causal loop diagrams and behaviour over time graphs have been used. Both elements help to more accurately understand the mental models of the people in charge of managing the security of information systems.
Drug repurposing of metformin for Alzheimer disease: Combining causal inference in medical records data and systems pharmacology for biomarker identification

Metformin, an antidiabetic drug, triggers anti-aging cellular responses. Aging is the principal risk factor for dementia, but previous observational studies of the diabetes drugs metformin vs. sulfonylureas have been mixed. We tested the hypotheses that metformin improves survival and reduces the risk of dementia, relative to the sulfonylureas, by emulating target trials in electronic health records of diabetic patients at an academic-centered healthcare system in the US and a wide-ranging group of primary care practices in the UK. To address the potentially dual influences of metformin on dementia risk, that it might reduce the hazard of death and put more people at risk of developing dementia while reducing the hazard of dementia by slowing biological aging, we used a competing risks approach and carefully grounded that within a causal inference emulated trial framework. To identify candidate biomarkers of the actions of metformin in the brain that might mediate reduced dementia risk, we conducted an in-vitro systems pharmacology evaluation of metformin and glyburide on differentiated human neural cells through differential gene expression. We named our multi-dimensional approach DRIAD-EHR (Drug Repurposing in Alzheimer Disease-Electronic Health Records). In intention-to-treat analyses, metformin was associated with a lower hazard of all-cause mortality than sulfonylureas in both cohorts. In competing risks analyses, there was also a lower cause-specific hazard of dementia onset among metformin initiators. In in-vitro studies, metformin reduced human neural cell expression of SPP1 and APOE, two secreted proteins that have been implicated in Alzheimer disease pathogenesis and whose levels can be quantified in the CSF. Together, our findings suggest that metformin might prevent dementia in patients without type II diabetes. In addition, our results inform the design of clinical trials of metformin in non-diabetics and suggest a pharmacodynamic CSF biomarker, SPP1, for the action of metformin in the brain.
Investigation of the Trichomonas Hominis and Some other Parasites in Cases of Diarrhea Accompanying Children Arriving to the Obstetrics and Gynecology Hospital in Ramadi / Iraq

During the period from May / 2019 till May / 2020, T. hominies and some other intestinal parasites causing diarrhea in children under the age of six were investigated after samples collecting throughout months of the year and by 200 feacal samples, it was found from the study that 97 infected samples with intestinal parasites, and that the T. hominies and B. hominies parasites are the least prevalent primary parasites in the Iraqi environment, and the ratio reached 2% for both, while the most prevalent parasites were E. histolytica by 39.2%, while the rest of the other parasites were of varying values ​ ​ among them, The results showed that the rural areas were more infected than the urban areas, and that the age of 2-4 years was the most vulnerable age group for intestinal parasites, and the results also showed that the most months in which the prevalence of infection was found was in July, and that the males were more infected than the females.
ECOPHYSIOLOGICAL RESPONSES OF DIFFERENT PLOIDY LEVELS (TETRAPLOID AND HEXAPLOID), OF CENCHRUS CILIARIS ACCESSIONS, IN WATER DEFICIENCY CONDITIONS

Cenchrus ciliaris L. is a perennial grass species that is widely present in Tunisian arid ecosystems. The ability to adapt to water deficiency of two provenances of C. ciliaris with different ploidy levels hexaploid (6x) and tetraploid (4x) was studied. Soil Water Content (SWC), predawn leaf water potential (Ψp) and midday leaf water potential (Ψm), number of leaves (NL), and shoot phytomass production were measured. Experiments were carried out under semi-controlled conditions of Sfax region (South of Tunisia). The factors studied were: ploidy level and irrigation treatments. Three irrigation treatments were applied: control T200 (200 mm year), T100 (100 mm year) and T50 (50 mm year). In our experimental conditions, our results showed that Cenchrus ciliaris species exposed to different irrigation treatments exhibited a decrease in all measured parameters. Different strategies seem to be developed by both provenances under drought conditions. Therefore, as soil water content decreased, tetraploid (4x) plants showed more negative leaf water potential (Ψp and Ψm) compared to hexaploid (6x) ones. More leaf number as well as shoot phytomass production by 6x provenances, in water deficiency conditions, suggests the ability of these provenances to support low water supply.
Traditional knowledge and conservation status of some selected medicinal herbs from Uttarkashi district in Uttarakhand, Western Himalayas

Traditional knowledge has been used throughout the world including India as a practice of using local herbal drugs. Majority of the locals living in the district Uttarkashi of Uttarakhand state have poor connectivity and socio-economic status. These people are known to have indigenous experience about the medicinal plants of the area and use their age-old experiences and perceptions in the treatment and prevention of various ailments. Present paper documents the ethnobotanical information and conservation status of 82 medicinal herbs from the hilly district of Uttarakhand. Information gathered include, local name, plant parts used, mode of preparations, medium of administration, ailments cured along with distribution and conservation status. Majority of these plants were used for their roots and leaves. Most of them are herbs while trees and climbers were less frequently used. People living in remote areas have a vast treasure of knowledge, but they do not disclose it easily to outsiders. During surveys and interactions, it has been noticed that due to over exploitation, some medicinal herbs are at the verge of extinction which need to be conserved at the earliest.
Research on Application of Transfer Learning in Equipment Fault Diagnosis

In view of the complex and changeable operating conditions of equipment, and the different distribution of measured data, it is difficult to promote the application of fault diagnosis technology. Many scholars have introduced transfer learning to overcome the lack of training data for deep learning by transferring existing data and models in similar domains into the target domain, it has expanded the application of fault diagnosis technology. This paper introduces the related concepts of transfer learning, summarizes the current applications and existing problems of transfer learning in the field of fault diagnosis, and finally puts forward further research directions and suggestions in general detection, real-time detection, etc. The purpose is to better improve equipment support capabilities.
Public transport fare elasticities from smartcard data: A natural experiment in Stockholm Yaroslav Kholodov, TU Delft Erik Jenelius, KTH Royal Institute of Technology Oded Cats, TU Delft and KTH Royal Institute of Technology

Fare policy is an essential component of any public transport system. Changes in the fare structure will cause users to adjust travel habits, which may influence ridership and have substantial impacts on the economic, social, and environmental welfare of the region (Liu et al., 2019). Traditionally, travellers’ sensitivity to supply changes is estimated based on aggregated cross-sectional and time series analysis, or disaggregate stated preference surveys. The latter collect users’ direct responses on how they would change travel behaviour (e.g. by mode, frequency or time of day) due to a particular change (e.g., Whelan et al., 2008). However, passengers tend to overestimate their reaction to the policy and underestimate the cost of switching to alternative choices, which adds bias to the analysis (Linsalata and Pham, 1991). Disaggregated revealed-preference studies have until recently been rare and based on limited data samples (Wardman and Shires, 2003).
The Blockchain-based Internet of Things Development: Initiatives and Challenges

—The Internet was originally built based on trust. After several leaks of information, new risks and challenges are introduced. In recent years, we have used even more new devices based on the Internet. Among the main concerns reported on the literature, we need some special attention to trust, protection of data and privacy. In this scenario, a new paradigm has emerged, some information security based on transparency instead of current models of information security on closed and obscure approaches. Some initiatives have been emerging with Blockchain methods and technologies. In this paper, we propose to build an initial view of the model, as a result of our preliminary investigations, described in the Methodology as systematic mapping. The initial results allowed the perception of the initial requirements involved and open problems. We report on some frameworks, models, approaches, and other Blockchain-based Internet of Things (IoT) initiatives. We also evaluate the adherence of each paper to ten IoT key requirements. This work contributes to the new and still developing body of knowledge in the areas of security, privacy and trust. Our ﬁndings are useful not only for future studies in the Academy but also for companies from various sectors present in the Internet ecosystem. They can beneﬁt from the consolidated knowledge and use it to guide the deﬁnition of their development processes geared to the new paradigms of the IoT.
The Impact of E-service quality in P2P accommodations on Customer Behavior Intention: Evidence from Chinese Customers

Considering the lack of research for the Chinese consumer expectations and the sustainable approach of P2P accommodation industry, this study examines the interactions of e-service quality, eTrust and risk perception. Both qualitative and quantitative research methodologies were adopted in this study. Following construct definition, initial item production, scale purification, EFA, CFA, reliability and validity testing process, the constructs of e-service quality, eTrust perceived risk were established. This study also explored P2P accommodation services in a Chinese context; meanwhile, the interconnection among e-service quality, eTrust, perceived risk and behavior intention were uncovered. The intermediary role of eTrust and risk perception provided solutions to the improvement of e-service quality, emphasizing the importance of the “What to expect” and “What to avoid” factors. This study proposes a new and comprehensive conceptual framework for understanding the determinants and outcomes of e-service quality of P2P accommodation and, together with the findings, can serve as a basis for future research. P2P accommodation managers could use this scale to evaluate and identify their accommodation environment and communicate methods with customers, and adjust their current service strategies to target travelers from mainland China more effectively.
Modeling labels for conversion value prediction

In performance based digital advertising, one of the key technical tools is to predict the expected value of post ad click purchases (a.k.a. conversions). Some of the salient aspects of this problem such as having a non-binary label and advertisers reporting the label in different scales make it a much harder problem than predicting probability of a click. In this paper we ask what is a good way to model the label and extract as much information as possible from the features. We investigate three main issues that arise from advertiser reported labels and come up with new techniques to address them. The first issue is that the label scale can affect how the model capacity is devoted to different advertisers. The second issue is how outlier labels can cause over-fitting. Finally, we also show that the distribution of the label contains vital information and the we train our models to use them and not just rely on the mean.
Attachment and Its Impact over Three Generations.

BACKGROUND Attachment parameters affect the development of self-concept and relationship patterns. However, studies on the impact of attachment parameters on symptoms of the offspring in childhood are still lacking. We therefore investigated the influence of attachment parameters of the grandparents on those of the parents treated in a psychiatric hospital, and finally on the symptoms of their (grand)children. Furthermore, the impact of attachment factors on parenting style and on resilience of parents and children has been examined. SUBJECTS AND METHODS A sample of n=50 mother-child-dyads in an inpatient setting was examined using the questionnaires FEB (Questionnaire on the Parental Attachment; adult and child perspective), RQ2 (Relationship Questionnaire), EFB-K (Educational Questionnaire, short form), RS13 (Resilience Scale; adult and child perspective), and CBCL (Child Behavior Checklist). Regression analyses and correlation analyses were carried out. RESULTS On grandparents' level, attachment patterns predicted parents' attachment patterns (p=0.012): Grandfather's care (control) behavior correlated with more (less) mother's care for their own children (0.002 (0.005)). Control behavior of the grandfather was negatively correlated with the resilience of their daughters (p=0.033). On parents' level, a secure attachment style predicted a less overreacting parenting style (p=0.004), whereas an anxious-avoiding (p=0.035) or clinging attachment style (p=0.044) predicted an increased overreacting parenting style. On child's level, mental (esp. attentional (p=0.013) and externalizing (p=0.032)) symptoms correlated negatively with the level of care reported by the mother. CONCLUSION Functional attachment behavior at the grandparents' level correlated significantly with functional attachment behavior at the parental level, which in turn correlated with reduced mental symptoms at the child's level. The parenting style seems to play a mediator role for the development of attachment between mother and child, with resilience mediating between attachment and the onset of mental disorders. The results point to the crucial role of attachment parameters for mental development with corresponding implications for psychotherapy.
HooVer: A Framework for Verification and Parameter Synthesis in Stochastic Systems using Optimistic Optimization

This paper provides a new approach for probabilistic verification of control and dynamical systems in the scenario where there is a finite computational budget that must be used judiciously; it is based on leveraging multiarmed bandits theory from machine learning. We present an algorithm for formal verification and parameter synthesis of continuous state-space Markov chains, introduce our associated computational tool HooVer, and demonstrate their use on example applications. The problem class considered captures the design and analysis of a wide variety of autonomous and cyber-physical systems defined by nonlinear and black-box modules. In order to solve these problems, one has to maximize certain probabilistic objective functions over all choices of initial states and parameters. In this paper, we identify the assumptions that make it possible to view this problem as a multi-armed bandit problem. Based on this fresh perspective, we propose an algorithm Hierarchical Optimistic Optimization algorithm with Mini-batches (HOO-MB) for solving the problem that carefully instantiates an existing bandit algorithm— Hierarchical Optimistic Optimization—with appropriate parameters. As a consequence, we obtain theoretical regret bounds on sample efficiency of our solution that depend on key problem parameters like smoothness, near-optimality dimension, and batch size. The batch size parameter enables us to strike a balance between the sample efficiency and the memory usage of the algorithm. Experiments, using our open-source tool HooVer, suggest that the approach scales to realistic-sized problems and is often more sample-efficient compared to PlasmaLab—a leading tool for verification of stochastic systems. Specifically, HooVer has distinct advantages in analyzing models in which the objective function has sharp slopes. In addition, HooVer shows promising behavior in parameter synthesis for a linear quadratic regulator (LQR) example.
Design and performance analysis of ORC centrifugal pumps

The purpose of this work is to design and determine the performance of a prototype centrifugal pump impeller for an organic Rankine cycle (ORC) power plant of maximum power 100 kW. The centrifugal pump is especially designed to work on the same shaft as the corresponding ORC microturbine. The ORC unit works on R7100 (HFE7100) – a lowboiling fluid characterized by a zero ozone depletion potential coefficient. The pump has the following rated parameters: nominal flow rate of working fluid 4 kg/s, operating rotor speed 10 000 rpm. The pump designed by means of the 0D meanline method is subject to computational fluid dynamics (CFD) calculations and analysis. The obtained flow field results are discussed and performance characteristics of the pump are presented. The non-cavitating operational region is determined for the pump.