Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Individualized Decision Rules Using Instrumental Variable Methods

Abstract There is an extensive literature on the estimation and evaluation of optimal individualized treatment rules in settings where all confounders of the effect of treatment on outcome are observed. We study the development of individualized decision rules in settings where some of these confounders may not have been measured but a valid binary instrument is available for a binary treatment. We first consider individualized treatment rules, which will naturally be most interesting in settings where it is feasible to intervene directly on treatment. We then consider a setting where intervening on treatment is infeasible, but intervening to encourage treatment is feasible. In both of these settings, we also handle the case that the treatment is a limited resource so that optimal interventions focus the available resources on those individuals who will benefit most from treatment. Given a reference rule, we evaluate an optimal individualized rule by its average causal effect relative to a prespecified reference rule. We develop methods to estimate optimal individualized rules and construct asymptotically efficient plug-in estimators of the corresponding average causal effect relative to a prespecified reference rule. Supplementary materials for this article are available online.
Edge-Computing-Enabled Unmanned Module Defect Detection and Diagnosis System for Large-Scale Photovoltaic Plants

The power efficiency of photovoltaic (PV) modules is highly correlated with their health status. Under dynamically changing environments, PV defects could spontaneously form and develop into fatal faults during the daily operation of PV power plants. To facilitate defect detection with less human intervention, a nondestructive, contactless, and automatical visual inspection system with the help of unmanned aerial vehicles and edge computing is proposed in this article. During the processing of the incoming data stream, the system may collect some new, unknown, and unlabeled defects that have not been identified yet in the existing database. To distinguish them from the existing ones, a deep embedded restricted cluster algorithm is designed to identify the unknown and unlabeled PV module defects in an unsupervised manner. Limited by the resources of edge devices and the availability of images of PV defects for training, we developed an online solution combined with deep learning, data argumentation, and transfer learning to properly address the issues of running resource-hungry applications on edge devices and lack of training samples faced by the deep learning approaches used in the field. In addition, pointwise convolution layers are introduced into the network to reduce the parameters and the size of the model. With the reduction of the network depth of the deep convolutional neural network model and the features transferred from the learned defects, the resource consumption of our proposed approach is significantly reduced, and thus can be used on a wide range of edge devices to complete defect detection in a timely manner with high accuracy. The experimental results clearly demonstrate the practicality and effectiveness.
Application of multiple-trait random regression animal model to predict genetic production traits in Iranian Holstein dairy cattle.

Genetic parameters of milk, protein and fat yield traits in Iranian Holstein dairy cattle were predicted using records gathered in Iran Breeding Centre during 2005 to 2010 across 79 production farms. Information included 276962 test day (TD) records belonged to 30729 primiparous dairy cows. Estimation with the assumption of residual variance homogeneity for whole lactation period was accomplished using restricted maximum likelihood (REML) method in the framework of multiple-trait random regression animal model. Estimated heritability for 305 day milk fat and protein yield showed almost similar results (0.32 to 0.33). For milk yield, predicted heritability as function of days in milk (DIM) resulted in higher value for the middle of DIM than both onset and end of milk production periods. Within traits, estimated correlations for consecutive TD records were higher and with increasing time interval among TD records. It became downwardly lower. Correlations between traits were calculated from covariance components for curve parameters estimated in multi-trait analysis. The range of genetic and permanent environment correlations across traits for 305 day production resulted in 0.76 to 0.93 and 0.87 to 0.97, respectively. The highest and lowest aforementioned parameters were observed among milk protein and milk fat yield, respectively.
Genética, ecologia e evolução de drosofilídeos (Insecta, Diptera) associados a flores

_______________________________________________________________________ This thesis is a study on flower-breeding species of drosophilids (Insecta, Diptera, Drosophilidae) based on a multi-approach with morphological, ecological, biogeographic, behavioural and molecular information on such organisms. A biodiversity inventory of flowerbreeding drosophilids was carried out in several localities in Brazil, with a broad sampling effort, comprising samples of flowers of 125 plant species, from 47 families. Overall, 56 plant species, from 18 families, showed to be hosts for drosophilid species, revealing a fauna still mostly unknown. Twenty-eight species were found, 12 of them being considered restrict flower-breeding species, six of uncertain biology and 10 opportunists. Approximately 40% (12 species) of the diversity found comprised undescribed species. This proportion raises to 2/3 if opportunist species are excluded. Within the opportunist species, nine species of Drosophila Fallén, 1823 and one of Zaprionus Coquillett, 1901 were found. The species of uncertain biology were represented by two species of Cladochaeta Coquillett, 1900, one of Rhinoleucophenga Hendel, 1917 and three of Scaptomyza Hardy, 1849. The restrict flower-breeding drosophilids constituted of eight species of the bromeliae group of Drosophila, two species of the subgenus Phloridosa Sturtevant, 1942 of Drosophila and two species of Zygothrica Wiedemann, 1830. A complete list of localities where each species was found is provided, including various new records. A list of host plants is also presented for each species. Four species of Drosophilidae were formally described: Rhinoleucophenga joaquina sp. nov., Drosophila anaeterrae sp. nov., D. solani sp. nov. and D. jurubeba sp. nov. Additionally, complements of description in a modern taxonomic view are provided for D. bromeliae Sturtevant, 1921 e D. bromelioides Pavan & Cunha, 1947. The bromeliae group of Drosophila was the most representative taxon, both in number of species and individuals. Eight species were found, six of them undescribed. Varying levels of niche breadth were observed, with polyphagous (D. bromelioides and D. bromeliae), olygophagous (D. anaeterrae sp. nov. and type III') and monophagous (D. solani sp. nov., D. jurubeba sp. nov., type IV' and type VI) species. The monophagous species showed a specialisation in Solanum flowers. Such ecological differences were linked with morphological differences, with bigger oviscapts and reduced (or modified) respiratory egg filaments with the increasing of the level of specialisation. Species of this group also could be divided in two geographic groups: species with a predominantly southern distribution (D. bromelioides, D. anaeterrae sp. nov., D. solani sp. nov. and D. jurubeba sp. nov.) and species with a predominantly northern distribution (D. bromeliae, type III', type IV' and type VI).
Graph-Based Blind Hyperspectral Unmixing via Nonnegative Matrix Factorization

Hyperspectral unmixing (HU) is a crucial step in the hyperspectral image (HSI) analysis. It aims at decomposing the observed spectrum at each pixel into a collection of constituent endmembers, weighted by their abundances. In a close spatial neighborhood, due to spatial autocorrelation, the abundances of an endmember tend to be similar to each other. Therefore, the spectra at the neighboring pixels are also very much alike. Recently, many studies have focused on graph-regularized nonnegative matrix factorization (NMF) approaches to address the blind HU problem. This is mainly because graph structures allow spatial–spectral relations to be effectively embedded in the NMF framework. This article takes one step further by defining each abundance map as a signal on a suitable graph, which enables the HU problem to be analyzed for the first time from a graph signal processing perspective. This article introduces a novel Laplacian regularizer based on the $l_{1}$ -norm, where graph spectral analysis is utilized to show that the regularizer has natural piecewise smooth (PWS) signal promotion and noise rejection capabilities. A graph-based blind HU algorithm is developed by incorporating this regularizer and an $l_{1/2}$ -abundance sparsity constraint into the NMF problem. Since the featured regularizer exploits the PWS property of abundance maps, the proposed method is effective in HU. The experiments conducted on synthetic and real HSIs demonstrate that it has superior performance compared with several popular HU algorithms.
Identification of novel regulatory elements in sequenced genomes by clustering and other data mining methods

In bacterial genomes a fraction of transcribed sequences do not code for proteins or structural RNAs, but have been shown to be involved in fundamental processes, such as regulation of gene expression, mRNA processing and stability or structural RNA maturation. In this thesis a systematic procedure to identify and classify families of repeated sequences sharing a common RNA secondary structure was applied to the study of 40 bacterial genomes. Sequences able to fold in a stable stem loop structure were clustered according to sequence similarity, and grouped within homogeneous families. The study led to the identification of 57 families of repeated sequences, sharing a common secondary structure and potentially coding for structured RNAs. All previously known such families have been detected by the used procedure, and are listed within the final set, together with 37 novel ones. Their location in relation to protein coding genes was evaluated, and a correlation was found between structure and positioning within intergenic regions. A new software tool is also described, Scaffolder, designed to help in high-throughput de novo genome sequencing by finding connections between contigs produced by random shotgun sequencing, and assisting the researcher in the whole process. The software, accessible both as a command line tool and as a web application, can guide all the final phases of genome assembly by storing the current assembly status, displaying networks of connected contigs and untangling multiply connected ones by a combination of computational and experimental procedures.
Ultimate attainment in heritage language speakers: Syntactic and morphological knowledge of Italian accusative clitics

Abstract The acquisition of a heritage language, normally the weaker language of early bilinguals, has been oftentimes defined as incomplete, especially for morphosyntax. As a result, these early bilinguals resemble late bilinguals more than native language speakers, calling into question the role of age of exposure. The effects of syntactic complexity on knowledge of morphosyntactic structures, however, have not been sufficiently considered hitherto. This study investigates age of exposure and syntactic complexity by comparing heritage, second language, and native language speakers on knowledge of Italian accusative clitics in three structures. An oral structural priming task and a speeded grammaticality judgment task find a discrepancy in the level of ultimate attainment heritage speakers reach for syntax and morphology. While their abstract representation of clitic structures approximates that of native language speakers more closely, their morphological knowledge of clitics aligns with second language speakers, suggesting early exposure has tangible effects only on syntactic knowledge. In turn, syntactic complexity affects the representation of clitic structures in a predictable manner, but is inconsequential to explicit knowledge of morphological forms in monolingual and bilingual speakers. Lack of age of exposure effects in the morphological domain are attributed to interface vulnerability.
Characterization of chitinase‐producing Serratia and Bacillus strains isolated from insects

Chitinases (EC 3.2.1.14) are enzymes that hydrolyze chitin by cleaving β‐1,4 N‐glycosidic bonds. These enzymes have been used for multiple applications in biotechnology, especially for controlling insect pests and phytopathogenic fungi. In the present study, we isolated two chitinase‐producing bacteria strains from insects (strain SCH‐1 from Moechotypa diphysis and strain SCH‐2 from Sphedanolestes impressicollis). Serratia sp. SCH‐1 was a short, rod‐shaped facultative anaerobe, while Bacillus strain SCH‐2 was a rod‐shaped endospore‐forming anaerobe. Strains SCH‐1 and SCH‐2 were identified as Serratia sp. and Bacillus sp. , respectively based on 16S rRNA gene sequencing. Strain SCH‐1 shared maximum homology (99.44%) with Serratia nematodiphila DZ0503SBS1 and Serratia marcescens subsp. sakuensis KRED. Strain SCH‐2 had a maximum homology of 99.24% with Bacillus thuringiensis ATCC 10792 and Bacillus toyonensis BCT‐7112. Serratia sp. SCH‐1 contained greater levels of saturated fatty acids, but the concentration of branched acids, especially iso‐C15:0, was highest in Bacillus sp. SCH‐2. Serratia sp. SCH‐1 possessed chitinase activity of 1.59 unit/mg protein after 5 days of incubation in culture medium. In contrast, Bacillus sp. SCH‐2 had a maximum activity of 0.84 unit/mg protein after 4 days of incubation. Chitinase isozymes produced by Serratia sp. SCH‐1 appeared as five bands with sizes of 20, 26, 36, 45 and 54 kDa. Bacillus sp. SCH‐2 showed a chitinase isozyme profile with three bands having sizes of 36, 45 and 50 kDa on SDS‐PAGE gels.
Sustainable Investment Project Evaluation

This paper concerns a current problem of multifaceted evaluation of investment projects. Information that contains the actual value of the initiated investment is often the basis for making decisions regarding its further implementation, especially when significant changes occur in the project’s environment. The process of project evaluation should therefore include all factors that may affect its value. However, there is a research gap regarding the insufficient development of methods of commercial real estate investment evaluation that integrate quantitative (financial) approaches and qualitative factors that influence the value of project, and also refer to the achievements in the scope of project management. The purpose of this paper is to introduce the integrated method of investment project evaluation based on the common valuation method (an income approach), supplemented by the results of the implementation of the Real Options Method (ROM) and complemented by the project sustainability factor. Case studies were carried out to prove that an exit option (resignation) can support the ongoing evaluation of the investment. Individual in-depth interviews (IDI) were conducted to examine the sustainability impact on its value. Three case studies involving commercial properties have verified the possibility of applying the proposed integrated method. The following findings were discovered as a result: nowadays, in the turbulent project environment, the common investment project valuation methods need to be extended to support the managerial decision regarding their further implementation and the securing of their flexibility. Also, sustainability has been recognized as a factor that increases the project value, which should be taken into account during the evaluation process. A comparative analysis indicates that the accuracy of the proposed new method delivers a more precise determination of the investment value than the common valuation methods.
Vehicle Counting at Road Intersections Using Video Data and Zone-Based Method with Additional Contour

The problem of counting vehicles and determining the directions of their movement at an intersection is considered. A new zone-based method for counting vehicles which uses an additional inner contour is proposed. The presence of an additional inner contour helps to partially expands zones of interest and increases our chances of catching a vehicle in time. YOLO and CSRT tracker are used for detection and tracking of objects. Full flowchart of the working process including detection, tracking and counting, is given. The algorithm for inner contour constructing is proposed and it is shown that this contour presence reduces the error in counting vehicles.
Trichome diversity of the family Caryophyllaceae from Western Himalaya and their taxonomic implication

Information about trichomes diversity and distribution of the family Caryophyllaceae is rare and the present work is intended to fill this knowledge lacuna. In the present work 62 taxa belonging to 19 genera were studied. For the analysis of trichomes diversity and vestiture type, dried plant specimens were rehydrated with water. The final illustrations of trichomes were made by using camera lucida. Six types of trichomes viz., Unicellular eglandular, Unicellular glandular, Multicellular uniseriate glandular, Multicellular uniseriate eglandular, Multicellular eglandular bifurcate and Multicellular multiseriate eglandular trichomes reported in the studied taxa. Diversity of trichome and their distribution does not play any significant role in the taxonomic delimitation either generic or tribal level of the family Caryophyllaceae. Although, few closely allied species can be distinguished from each other either on the basis of the presence of trichomes or vestiture patterns.
Applying Control Abstraction to the Design of Human-Agent Teams

Levels of Automation (LOA) provide a method for describing authority granted to automated system elements to make individual decisions. However, these levels are technology-centric and provide little insight into overall system operation. The current research discusses an alternate classification scheme, referred to as the Level of Human Control Abstraction (LHCA). LHCA is an operator-centric framework that classifies a system’s state based on the required operator inputs. The framework consists of five levels, each requiring less granularity of human control: Direct, Augmented, Parametric, Goal-Oriented, and Mission-Capable. An analysis was conducted of several existing systems. This analysis illustrates the presence of each of these levels of control, and many existing systems support system states which facilitate multiple LHCAs. It is suggested that as the granularity of human control is reduced, the level of required human attention and required cognitive resources decreases. Thus, it is suggested that designing systems that permit the user to select among LHCAs during system control may facilitate human-machine teaming and improve the flexibility of the system.
Related party transactions, disclosure and ownership structure in Brazil

* Accounting Department, Fluminense Federal University, Macaé, Rio de Janeiro, Brazil ** Corresponding author, Accounting Department, Federal University of Espírito Santo, Vitória, Espírito Santo, Brazil Contact details: Federal University of Espírito Santo, Av. Fernando Ferrari, 514, Vitória, ES, 29075-910, Brazil *** The COPPEAD Graduate Business School at the Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
Identification of molecular marker(s) for root length in rice (Oryza sativa L.)

Roots are important plant organs that supply water, nutrients, hormones and mechanical support (anchorage) to the crop plants and consequently affect economic yields. As the techniques available to measure root systems are laborious and time consuming, the present study of markers identification linked to greater root length offer an excellent opportunity for improving this root trait using marker assisted selection. Based on root pulling resistance and core sampling root scan data for root length, extreme DNA bulks (11 lines in each bulk) were prepared. Bulk segregant analysis followed by co segregation analysis revealed the markers HvSSR 01–80, HvSSR 01–87, HvSSR 05–31, RM242, RM135, RM499, RM232, RM296 and RM26334 associated with the trait. Among them RM242 marker located on chromosome 9, for root length is considered to be good for marker assisted selection.
Structural composition of βI‐ and βII‐proteins

Circular dichroism spectra of proteins are sensitive to protein secondary structure. The CD spectra of α‐rich proteins are similar to those of model α‐helices, but β‐rich proteins exhibit CD spectra that are reminiscent of CD spectra of either model β‐sheets or unordered polypeptides. The existence of these two types of CD spectra for β‐rich proteins form the basis for their classification as βI‐ and βII‐proteins. Although the conformation of β‐sheets is largely responsible for the CD spectra of βI‐proteins, the source of βII‐protein CD, which resembles that of unordered polypeptides, is not completely understood. The CD spectra of unordered polypeptides are similar to that of the poly(Pro)II helix, and the poly(Pro)II‐type (P2) structure forms a significant fraction of the unordered conformation in globular proteins. We have compared the β‐sheet and P2 structure contents in β‐rich proteins to understand the origin of βII‐protein CD. We find that βII‐proteins have a ratio of P2 to β‐sheet content greater than 0.4, whereas for βI‐proteins this ratio is less than 0.4. The β‐sheet content in βI‐proteins is generally higher than that in βII‐proteins. The origin of two classes of CD spectra for β‐rich proteins appears to lie in their relative β‐sheet and P2 structure contents.
Determinants of Effective E-Procurement System: Empirical Evidence from Indonesian Local Governments

This study investigates the effect of the Strategy-Technology-Organization-People-Environment (STOPE) variables on the effectiveness of e-procurement implementation in improving accountability, transparency, efficiency, and effectiveness of local governments in Indonesia. The population of this study is local government procurement services (or LPSE) in Indonesia. The sample, 96 LPSE, was selected using a simple random sampling method. The data was collected through questionnaires distributed via email to 289 LPSE. The respondents were 33 managers and 63 information technology professionals of local government procurement services (33% response rate). To test the hypothesis and data analysis, Partial Least Squares (PLS) was used. The findings show that strategies, objectives, integration between organizations and systems, and human resource assistance can improve the accountability, transparency, efficiency, and effectiveness of the government in implementing procurement activities
DEM analysis of undrained cyclic simple shear test on saturated sand

Liquefaction can be considered to occur in saturated sand widely under seismic load, which will cause serious disaster, including road damage, ground subsidence, cracking of houses. Thus, it is quite necessary to study the liquefaction characteristics of saturated sand. For this aim, the undrained simple shear test on saturated sand under cyclic loading were simulated by three-dimensional distinct element method (DEM), where the stress-strain relationship, excess pore pressure ratio, mechanical coordination number and contact normal direction were analyzed. The results show that the liquefaction of saturated sand is manifested by the accumulation of excess pore pressure ratio. In addition, the mechanical coordination number gradually reduces and the sample anisotropy slightly fluctuates before the saturated sand reaches initial liquefaction. When the specimen approaches initial liquefaction, the mechanical coordination number drops abruptly and the sample anisotropy obviously increases.