Miracle-dz/UniFAR-FTUs huggingface dataset:
Disarmed principals: institutional resilience and the non-enforcement of delegation

Abstract Governments across the world increasingly rely on non-state agents for managing even the most sensitive tasks that range from running critical infrastructures to protecting citizens. While private agents frequently underperform, governments as principals tend nonetheless not to enforce delegation contracts. Why? We suggest the mechanism of institutional resilience. A preexisting set of rules shapes non-enforcement through the combination of (i) its structural misfit with the delegation contract and (ii) asymmetric interdependence that favors the agent over time. To demonstrate the plausibility of our argument, we trace the political process behind Europe’s largest military transport aircraft, the A400M. Governments delegated the development and production of this complex program to a private firm, Airbus. They layered a ‘commercial approach’ onto traditionally state-run defense industries. Yet, resilience caused these new formal rules to fail and eventually disarmed principals. Our mechanism constitutes an innovative approach by theorizing an alternative path toward dynamic continuity.
Cytogenetic Screening of Karan Fries and Tharparkar Males for Selection of Elites at an Early Age

The importance of sire selection in the herd is reflected in the total genetic gain through sire-to-sire path and sire-to-dam path being more than 50 percent contribution. The present investigation was envisaged with the objective of screening chromosomes with conventional cytogenetic techniques in males of Tharparkar and Karan-Fries cattle and to find association between chromosomal anomalies and performance of males. 25 and 15 males of KF (Karan Fries) and TP (Tharparkar) respectively were utilized for cytogenetic and semen evaluation work at ICAR-National Dairy Research Institute, Karnal. Cytogenetic screening of animals could not show gross numerical and chromosomal aberrations, while fragile sites were revealed by induction with aphidicolin. The average percentage of fragile sites in autosomes and sex chromosomes were found 14.66 and 6.16 respectively in KF males, while in TP males average percentages were 7.66 and 4.9, respectively. Association study revealed that fragility in autosomal chromosomes had significant effect on the birth weights in KF males and no association was found between any libido and reproductive trait with the percent fragile sites either in autosomes or sex chromosomes. Cytogenetic screening is recommended at the initial stage for the propagation of only elite bull semen used for A.I. Association between autosomal fragility and birth weights although found highly significant but still need to be validated with large sample size.
Ovipositor mechanics of the braconine wasp genus Zaglyptogastra and the ichneumonid genus Pristomerus

The multiply-arched, apical quarter to half of the ovipositors of Zaglyptogastra species are capable of flexing ventrally through up to 180°. Flexion is achieved by ventral protrusion of the lower ovipositor valves relative to the upper one, an action which juxtaposes swollen lower valve sections with weak concave narrowings of the upper valve. The structural modifications associated with this flexion mechanism are described and similar ovipositor features are illustrated for the cremastine ichneumonid genus Pristomerus.
Are fungi necessary? How fungicides affect growth and survival of the orchid Lepanthes rupestris in the field

1 Mycorrhizal associations of tropical, epiphytic orchids have been studied in vitro, but the importance of the relationship has not been demonstrated in the field. We investigated the effect of fungicide treatment on seedlings and juveniles of the lithophytic orchid Lepanthes rupestris. As mycorrhizas, endophytes and pathogens coexist in orchids, fungicide treatment might have either a positive or negative effect on growth and survival of plants. 2 The experimental design included benomyl‐treated, propiconazole‐treated, and control plots. Each treatment consisted of about 140 2 × 2 cm plots divided among eight rocks, with one seedling or juvenile (occasionally two) per plot. Fungicides were applied every 2 weeks and plants were censused and measured every 3 months for 8–9 months. 3 Propiconazole‐treated plants had higher mortality, significantly fewer leaves, significantly fewer fungal colonies in their roots, and significantly fewer degraded pelotons than did control plants. Benomyl‐treated plants had significantly lower mortality than controls and significantly fewer fungi in leaves than control plants, and did not differ in number of degraded pelotons. There was little or no recruitment in any treatment. 4 Few potentially mycorrhizal fungi were isolated. Guignardia, Colletotrichum and Xylaria, which are generally endophytes, pathogens and/or saprotrophs, were more common. There was evidence of antagonism between Colletotrichum and Xylaria and between Colletotrichum and Guignardia. 5 Results suggest that fungi have both positive and negative effects on growth and survival of L. rupestris plants. However, conclusions about the importance of mycorrhizas are complicated by the simultaneous occurrence of a range of orchid–fungus interactions.
Inference of Local Regression in the Presence of Nuisance Parameters

Abstract We consider inference based on local estimating equations in the presence of nuisance parameters. The framework is useful for a number of applications including those in economic policy evaluation based on discontinuities or kinks and in real-time financial risk management. We focus on the criterion-function-based (in particular, empirical likelihood-based) inference, and establish conditions under which the test statistic has a pivotal asymptotic distribution. In the key step of eliminating nuisance parameters in the (possibly non-smooth) criterion function, we consider two different approaches based on either concentration or Laplace-type plug-in estimation. The former is natural, and the latter does not require optimization and can be computationally attractive in applications. Our framework can easily incorporate bias correction induced by localization, and the inference is robust to the identification strength of the parameter of interest. The high-level assumptions are illustrated with several examples. We also conduct Monte Carlo simulations and provide an empirical application which assesses heterogeneous effects of academic probation in college and gender differences under the quantile regression discontinuity design.
Minimizing The Number of Channel Switches of Mobile Users in Cognitive Radio Ad-Hoc Networks

Cognitive radio (CR) technology is envisioned to use wireless spectrum opportunistically when the primary user (PU) is not using it. In cognitive radio ad-hoc networks (CRAHNs), the mobile users form a distributed multi-hop network using the unused spectrum. The qualities of the channels are different in different locations. When a user moves from one place to another, it needs to switch the channel to maintain the quality-of-service (QoS) required by different applications. The QoS of a channel depends on the amount of usage. A user can select the channels that meet the QoS requirement during its movement. In this paper, we study the mobility patterns of users, predict their next locations and probabilities to move there based on its history. We extract the mobility patterns from each user’s location history and match the recent trajectory with the patterns to find future locations. We construct a spectrum database using Wi-Fi access point location data and the free space path loss formula. We propose a machine learning-based mechanism to predict spectrum status of some missing locations in the spectrum database. We formulate a problem to select the current channel in order to minimize the total number of channel switches during a certain number of next moves of a user. We conduct an extensive simulation combining real and synthetic datasets to support our model.
“This is why nobody knows who you are:” (Counter)Stories of Southeast Asian Americans in the Midwest

Despite the tremendous diversity of ethnicities, languages, religions, and cultures encapsulated within their pan-ethnic group, Asian Americans are commonly understood to be recent immigrants of East Asian descent who do not speak English (Lee & Ramakrishnan, 2019). While the greatest concentrations of Asian Americans are on the West Coast, the Midwest is the region with the second greatest growth. Half of the Midwestern states have experienced greater than 50% growth in their Asian American populations since 2000 (Hoeffel et al., 2012). Yet the population of Midwestern states remains nearly 83% White (U.S. Census Bureau, 2019), an overwhelming majority reflected in school systems throughout the region. The unfamiliarity with Asian American histories, cultures, and ethnicities to White Midwesterners presents a number of challenges, many of which manifest in schooling contexts. Although Iowa is commonly associated with cornfields and White farmers, Southeast Asian refugees have a remarkable history in this region that is largely unacknowledged. The recognition of this history, through inclusion in the school curriculum and the popular imagination, could be a powerful way to disrupt normative Whiteness and xenophobia in the region. This manuscript centers on the stories of five second-generation Southeast Asian Americans (SEAAs) from Central Iowa. Interviewees described a lack of understanding of their cultures and languages by their teachers and non-Asian communities. The insights and activism of these particular individuals suggest possibilities for educators to take transformational approaches toward more inclusive pedagogy and curriculum for future generations in Iowa and beyond.
Microsporogenesis, microgametogenesis and pollen morphology of Passiflora spp. (Passifloraceae)

Microsporogenesis, microgametogenesis and pollen morphology of six species of genus Passiflora L. belonging to three subgenera (Passiflora, Dysosmia, Decaloba) were studied with light and scanning microscopy; P. caerulea was also examined with transmission microscopy. The tapetum is secretory, microspore tetrads are tetrahedral and pollen grains are two-celled when shed. Small Ubisch bodies are attached to a peritapetal membrane; they are a product of tapetal activity and the rough endoplasmic reticulum (ERr) appears to be involved in their origin. The pollen grains of all the species are subspheroidal, zonocolpate, geminicolpate. Each pair of colpi anastomoses at the poles. The exine is semitectate, reticulate, heterobrochate. The muri are simplibaculate, wavy. The lumina have clavate bacula of varying height. The colpus structure is similar to that of the lumina but generally with fewer and smaller bacula. Lumina size and amount of bacula inside the lumina vary between subgenera. The grains from subgenera Passiflora and Dysosmia differ from those of Decaloba in their size and number of colpi. The pollen and microsporangium morphology of the species of subgenera Passiflora and Dysosmia are more similar than those of subgenus Decaloba. The results are discussed in relation to the current taxonomic classification. © 2002 The Linnean Society of London, Botanical Journal of the Linnean Society of London, 2002, 139, 383–394.
EFFECTS OF TEMPERATURE ON GROWTH, LIGHT ABSORPTION, AND QUANTUM YIELD IN DUNALIELLA TERTIOLECTA (CHLOROPHYCEAE) 1

The effects of growth temperature on the marine chlorophyte Dunaliella tertiolecta Butcher were studied to provide a more mechanistic understanding of the role of environmental factors in regulating bio‐optical properties of phytoplankton. Specific attention was focused on quantities that are relevant for modeling of growth and photosynthesis. Characteristics including chlorophyll a (chl z)‐specific light absorption (a*ph(λ)), C:chl a ratio, and quantum yield for growth (φμ) varied as functions of temperature under conditions of excess light and nutrients. As temperature increased over the range examined (12°‐28°C), intracellular concentrations of chl a increased by a factor of 2 and a*ph(λ) values decreased by more than 50% at blue to green wavelengths. The lower values of a*ph(λ) were due to both a decrease in the abundance of accessory pigments relative to chl a and an increase in pigment package effects arising from higher intracellular pigment concentrations. Intracellular pigment concentration increased as a consequence of higher cellular pigment quotas combined with lower cell volume. At high growth temperatures, slightly more light was absorbed on a per‐cell‐C basis, but the dramatic increases in growth rate from μ= 0.5 d−1 at 12° C to μ= 2.2 d−1 at 28°C were primarily due to an increase in φμ (0.015–0.041 mol C (mol quanta)−1). By comparison with previous work on this species, we conclude the effects of temperature on a*ph(λ) and φμ are comparable to those observed for light and nutrient limitation. Patterns of variability in a*ph(λ)and φμ as a function of growth rate at different temperatures are similar to those previously documented for this species grown at the same irradiance but under a range of nitrogen‐limited conditions. These results are discussed in the context of implications for bio‐optical modeling of aquatic primary production by phytoplankton.
Model-Based Actor-Critic Learning for Optimal Tracking Control of Robots With Input Saturation

As robots normally perform repetitive work, reinforcement learning (RL) appears to be a promising tool for designing robot control. However, the learning cycle of control strategy tends to be long, thereby limiting the applications of RL for a real robotic system. This article proposes model-based actor-critic learning for optimal tracking control of robotic systems to address this limitation. A preconstructed critic is defined in the framework of linear quadratic tracker, and a model-based actor update law is presented on the basis of deterministic policy gradient algorithm to improve learning efficiency. A low gain parameter is introduced in the critic to avoid input saturation. Compared with neural network-based RL, the proposed method including the preconstructed critic and actor, has rapid, steady, and reliable learning process, which is friendly for the physical hardware. The performance and effectiveness of the proposed method are validated using a dual-robot test rig. The experimental results show that the proposed learning algorithm can train multiple robots to learn their optimal tracking control laws within a training time of 200 s.
Development and usage of microsatellite markers for population analysis of Corbicula japonica in Japan

: Six novel microsatellite markers were developed in Corbicula japonica and used (along with an addi-tional locus that was previously reported for another species) for population analysis of this species in Japan. The samples were collected from 4 local populations: Lake Abashiri and Lake Oikamanai in Hokkaido, Lake Ogawara in Aomori Prefecture, and Lake Shinji in Shimane Prefecture. The genetic diversity of the Shinji population was lower than that of the other 3 populations. Pair-wise F ST analysis revealed signi ﬁ cant genetic differentiation among all of the local populations and suggested two groups: northern (Abashiri, Oikamanai, and Ogawara) and southern (Shinji). Bayesian clustering analysis also supported this grouping, and analysis of molecular variance showed a hierarchical population structure for the two groups when genetic differentiation was calculated using R ST . It is concluded that these local populations are genetically different from each other and that there is marked differentiation between geo-graphically distant populations. These results demonstrate that these new microsatellite markers are useful for esti-mating genetic diversity and population structure, and should aid future research on effective aquaculture systems and sustainable ﬁ sheries for this species.
Author Matching Using String Similarities and Deep Neural Networks

Author Name Disambiguation (AND) is one of the problems in the process of classification of publication data, where the introduction of the characteristics of each author is difficult to recognize because of the frequent changes in patterns in writing author names. In the world of publications, author classification is needed to classify authors with types and fields of science based on published papers, therefore in this paper the author will classify with the aim of providing definite values whether the author is with the paper title a and author a with the paper title b is the same person or not. The method used by the author is one branch of Deep Learning, namely the Deep Neural Network DNN). DNN is used because it has high data processing acceleration capabilities with the use of GPU technology. With this method, AND data classified by the author produces a high level of accuracy with a value of 98%.
Seasonal Patterns of Abundance, Growth, and Site Fidelity of Juvenile Steelhead in a Small Coastal California Stream

Abstract Populations of steelhead Oncorhynchus mykiss throughout the central California coast are currently listed as threatened under the federal Endangered Species Act. To better understand demographic processes during the juvenile freshwater stage, we quantified abundance, movement, and growth of juvenile steelhead among five reaches in a primary spawning area of Soquel Creek. We used mark-recapture methods to examine seasonal, density-dependent, and size-dependent patterns in these population metrics. Many trends were stronger in age-0 fish than in age-1 and older fish. Estimated survival and retention within a reach were generally highest in summer and lowest in winter-spring. Density dependence was evident only in age-0 fish, with lower survival occurring at higher densities. Survival was typically size-dependent, with lower survival of smaller fish in both age-classes. Immigration, based on movement of untagged fish into our sites between sampling periods, was higher in winter-spring compared with .
Systematic relationships of Nematomorpha based on molecular and morphological data

Abstract. We sequenced the 18S rRNA gene from 11 nematomorph species from 9 genera and derived hypotheses concerning the sister group of Nematomorpha and relationships within this taxon. The molecular and morphological data are consistent with the monophyly of Nematomorpha, a sister-group relationship between Nematomorpha and Nematoda, and a sister-group relationship between the marine genus Nectonema and all of the freshwater taxa, Gordiida. Hypotheses of relationships within Gordiida support the traditional taxa Gordiidae, Chordodidae, and Chordodinae but reject Parachordodinae and Spinochordodidae. The molecular results differ from those of previous morphological studies by suggesting a reduction of the two tail lobes at the posterior end of males in Chordodinae, monophyly of the genus Paragordionus, and paraphyly of the genus Chordodes.
Variability in pollination conditions, pollen dispersal patterns, and pollen relatedness: an example of a tropical emergent tree.

Recent understanding on biparental inbreeding depression teaches us that pollen relatedness to female gametes should be regarded as a significant aspect of pollen quality. Pollen relatedness is determined by pollen dispersal pattern and spatial genetic structure, however the former is possibly affected to varying degrees by certain variations in pollination conditions. Our recent study, which applied DNA microsatellite markers to study pollen dispersal patterns and pollen relatedness in a tropical emergent tree in two years, showed that the level of inbreeding differed affected by different types of pollinators. This infers that pollen of good quality dispersed under a particular pollination condition may play a significant role in population regeneration. Relationships between pollen dispersal patterns and various reproductive traits or conditions should be elucidated to better understand plant reproductive strategies.
EXACT NON-REFLECTING BOUNDARY CONDITIONS WITH AN FDTD SCHEME FOR THE SCALAR WAVE EQUATION IN WAVEGUIDE PROBLEMS

Modeling wave propagation often requires a truncation of the computational domain to a smaller subdomain to keep computational cost reasonable. The mere volume of papers on absorbing boundary conditions indicates that a perfect solution is not available. A method is proposed that is numerically exact, at least in the case of a time-domain finite-difference scheme for the scalar wave equation. The word ‘exact’ is used in the sense that there is no difference between a computation on the truncated domain with this method and one on an enlarged domain with reflecting boundaries that are placed so far away that their reflections cannot reach the original domain within the modeled time span. Numerical tests in 1D produce stable results with central difference schemes from order 2 to 24 for the spatial discretization. The difference with a reference solution computed on an enlarged domain with the boundary moved sufficiently far away only contains accumulated numerical round-off errors. Generalization to more than one space dimension is feasible if there is a single non-reflecting boundary on one side of a rectangular domain or two non-reflecting boundaries at opposing sides, but not for a corner connecting non-reflecting boundaries. The reason is that the method involves recursion based on translation invariance in the direction perpendicular to the boundary, which does not hold in the last case. This limits the applicability of the method to, for instance, modeling waveguides, or exactness has to be partially given up.
Fast Convergence Methods for Hyperbolic Systems of Balance Laws with Riemann Conditions

In this paper, we develop an accurate technique via the use of the Adomian decomposition method (ADM) to solve analytically a 2 × 2 systems of partial differential equation that represent balance laws of hyperbolic-elliptic type. We prove that the sequence of iteration obtained by ADM converges strongly to the exact solution by establishing a construction of fixed points. For comparison purposes, we also use the Sinc function methodology to establish a new procedure to solve numerically the same system. It is shown that approximation by Sinc function converges to the exact solution exponentially, also handles changes in type. A numerical example is presented to demonstrate the theoretical results. It is noted that the two methods show the symmetry in the approximate solution. The results obtained by both methods reveal that they are reliable and convenient for solving balance laws where the initial conditions are of the Riemann type.