Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Rearranged Cholestane Glycoside with a d-Lactone Ring System from Ornithogalum saundersiae Bulbs

The bulbs of Ornithogalum saundersiae have been revealed to contain a variety of cholestane glycosides. Further chemical investigation of the MeOH extract of O. saundersiae bulbs have resulted in the isolation of a novel 24(23→22)abeo-cholestane glycoside with a δ-lactone system (1). The structure of 1 was elucidated on the basis of extensive spectroscopic analysis and the result of acid hydrolysis.
GODZILLIUS FUCHSI, A NEW SPECIES OF REMIPEDIA (GODZILLIIDAE) FROM ABACO ISLAND, BAHAMAS

We describe a new species of Godzillius, a remipede belonging to Godzilliidae, discovered from Dan’s Cave and Ralph’s Sink, two inland anchialine blue holes on Abaco Island, Bahamas. Godzillius fuchsi n. sp. is the second species assigned to this genus. Collected adult specimens have a relatively robust body, with lengths measuring 34 mm and up to 28 trunk segments. The new species is distinguished from G. robustus in particular by the varying construction of the terminal claw complex on the cephalic limbs; having seven large teeth on the maxillae; and six large teeth separated by seven smaller teeth on the maxillipeds. The status of G. fuchsi as a distinct species was validated using pairwise distance calculations of COI sequences and that of previously published Bayesian analyses from selected remipede taxa, including G. robustus. Dan’s Cave and Ralph’s Sink are in very close proximity and likely are hydrologically connected. Godzillius fuchsi is the fifth remipede to be recorded from Dan’s Cave.
Ingestão de matéria seca por novilhas de corte em pastagem de milheto

It was evaluate the dry matter (DM) herbage intake by beef heifers and the bite mass on a Pearl Millet (Pennisetum americanun (L.) Leeke) pasture. The experimental design was completely randomized with repeated measures in time, two leaf blade mass (600 and 1,000kg ha-1 of DM), which were maintained by continuous stocking with variable stocking rate, and three replicate areas. The herbage intake was evaluated using chromic oxide (Cr2O3) as a faecal production indicator and the acid detergent indigestible fiber as an internal indicator. The qualitative parameters evaluated in the forage were the neutral detergent fiber, in vitro organic mater digestibility and the crude protein content. The heavier bites were achieved in a Pearl Millet pasture managed with 1,000kg ha-1 of leaf blade dry matter (DM) even though the steers have eaten the same dry matter amount, 1.8% of live weight, in the two leaf blade mass. The Pearl Millet pasture managed with leaf blade herbage mass of 600 or 1,000kg ha-1 of DM provides to the grazing animals similar opportunity of herbage intake.
A Metadata Inference Method for Building Automation Systems With Limited Semantic Information

Metadata in most existing building automation systems (BASs) is inconsistent, incomplete, and nondescriptive. This situation is a major obstacle to the widespread use of data analytics to improve the operation of buildings. In this article, we put forward a method to infer zone-level metadata from features derived from BAS data. The method includes two steps: 1) classification of BAS points into different types (e.g., indoor temperature, indoor temperature set point, airflow, airflow set point, damper position, and radiator valve position) and 2) association of BAS points based on their functional relationships (i.e., grouping the sensors, actuators, and set points of each zone together). The metadata inference method was demonstrated with data from zones served by four different air handling units (AHUs) in two office buildings in Ottawa, ON, Canada. The results from this case study indicate that common zone-level BAS point types can be accurately classified and associated even in the absence of intuitive data labels. Note to Practitioners—This article was motivated by the problem of metadata normalization in existing buildings, in order to scale up the application of smart building solutions in the real world. Existing metadata normalization approaches mainly focused on inferring the point types of the metadata with both semantic (label) and numerical information (time series readings). In this article, we put forward a method to infer zone-level metadata with numerical information only. Methods for both types of classification and relationships’ association of the BAS points are investigated. The results from two office buildings indicate that the classification phase can achieve an average of 90% accuracy, while the association phase can obtain an average of 85% accuracy. The method was developed and demonstrated with a limited data set by using data exclusively from zone-level sensors, actuators, and set points. Future work is planned to extend the proposed method to more comprehensive BAS data sets with the system- and plant-level data as well.
Selection indices for yield improvement in bread wheat (Triticum aestivum L.)

The discriminant-function technique was used to construct selection indices in 48 genotypes of bread wheat (Triticum aestivum L.). Sixty-three selection indices involving grain yield per plant and its five components were constructed using the discriminant function technique. The efficiency of selection increased with the inclusion of more characters in the selection index. The index based on four characters viz., grain yield per plant, the number of grains per main spike, grain weight per main spike and biological yield per plant recorded the highest genetic gain and relative efficiency. The use of these indices is advocated for selecting high yielding genotypes of bread wheat.
Variation in the induced resin response of white spruce, Piceaglauca, to attack by Pissodesstrobi

La reaction de defense provoquee par l'attaque du charancon du pin blanc, Pissodes strobi Peck, et qui se manifeste par la production de resine a ete etudiee chez des epinettes blanches, Picea glauca (Moench) Voss, qui avaient subi des attaques d'intensite differente. La reaction etait la plus forte chez les arbres ou l'attaque n'avait pas reussi, c. -a-d. ou la ponte avait eu lieu mais ou les oeufs avaient ete tues et ou aucun adulte n'avait emerge. Les arbres ou l'attaque avait reussi avaient en moyenne une reaction equivalente a seulement 62% de celle des arbres ou l'attaque n'avait pas reussi. Les arbres qui n'avaient subi que l'activite trophique des charancons avaient une reaction beaucoup plus faible, equivalente a 42% de celle des arbres ou l'attaque n'avait pas reussi. Les arbres sains qui n'avaient pas ete attaques produisaient peu ou pas de resine. L'intensite de la reaction variait de facon non lineaire en fonction du nombre d'oeufs pondus, augmentant rapidement a partir de zero chez les arbres sains, etant maximale chez les arbres qui avaient entre 10 et 60 trous de ponte et diminuant a nouveau progressivement chez les arbres qui avaient un nombre plus eleve de trous de ponte. Pour un nombre donne de trous de ponte, les epinettes blanches resistantes avaient toujours une reaction de defense plus forte que les arbres susceptibles. Le nombre d'oeufs pondus sur une pousse terminale etait inversement relie a l'intensite de la reaction de defense et au moment de l'attaque. Moins d'oeufs etaient pondus sur les pousses terminales qui produisaient beaucoup de resine ou etaient attaquees tard en saison comparativement a celles qui produisaient moins de resine ou etaient attaquees tot en saison.
Monitoring and managing large deformation pit slope instabilities at a British Columbia copper mine

Pit slopes exhibiting large deformations due to weak and complex fault zones within an otherwise good quality rock mass are characteristic of an open pit mine in British Columbia, Canada. Following the introduction of a database with 26 pit slope instabilities, the paper describes one of the instabilities, which exhibited over 70 m of cumulative deformation over the course of one year without collapsing. Ground-based slope stability radar and prisms surveyed by a robotic total station continuously monitored the pit slope deformation rates as the instability area experienced acceleration events lasting several days as mining of the high slope progressed towards its final height of 320 m. Integrating ground-based radar and surface deformation monitoring with drone photogrammetry was instrumental in understanding the complex failure mechanism and successfully managing this instability.
Yield dynamics of canopy components in alfalfa-grass mixtures.

(.) A field study was conducted to describe the changes in canopy components of alfalfa-reed canarygrass (Phalaris arundinacea L.) and alfalfa-orchardgrass (Dactylis glomerata L.) mixtures. Alfalfa-grass mixtures of one row of grass between two rows of alfalfa and one row of alfalfa between two rows of grass were planted in a repeating pattern. Monocultures of each species and four binary mixtures were sampled for total, alfalfa and grass component, and stratified alfalfa yields were measured at 10, 20, 30, 40, and 50 d of spring and summer regrowth for 2 yr (.)
Corporate Social Performance: An Assessment Model on an Emerging Market

This paper investigates the priorities governing large companies in an emerging market regarding corporate social performance (CSP). The authors propose profile patterns of responsible managerial behavior and a framework for evaluating CSP relying on stakeholder theory. The study relies on a statistical analysis which is designed to examine the significance of corporate social responsibility (CSR) practice as it emerges from company business strategies. Taking the form of an empirical study involving 87 managers, this work relies on the cluster analysis theory, identifying six behavioral patterns when considering CSR practices: “lethargic”, “compliant, “pragmatist”, “auditor”, “formalist”, and “performer”. The cluster typology indicates the complexity of CSR practices and highlights the role of CSR in company strategy development. The proposed assessment model is intended to empower CSP diagnosis, while supporting management towards achieving sustainable growth.
Statistical control charts as a support tool for the management of livestock production

SUMMARY The concepts of control charts, an important tool in statistical process control, are commonly used for monitoring industrial production processes. In the context of precision livestock farming, their use has been demonstrated by many, although the statistical properties of livestock process data often do not comply with the basic assumptions of such control charts. The focus of the current review is on the most important aspects, recommendations, pitfalls and opportunities for the development and performance of control charts on livestock process data. An important hurdle to tackle is the statistical characteristics of the raw livestock process data which are mostly violating the control charts’ assumptions. An integrated approach, like synergistic control, appears to be promising in handling this issue. The availability of real-time on-farm validation of proposed systems will be crucial for lifting them from the potential level to direct practical relevance.
Relationship between family caregiver quality of life and the care provided to people living with dementia: protocol for a mixed methods study

Objective Family caregivers of people with dementia perform duties that are important for maintaining their loved one's overall well-being. However, it is not yet clear how these caregivers' quality-of-life affects their ability to meet the care demands of their loved ones. The purpose of this study is to utilize a mixed methods approach in investigating how family caregiver quality-of-life affects the care provided to people with dementia. Family caregivers will be recruited from the Rochester, New York area to participate in focus groups or one-on-one interviews. In addition to the qualitative data obtained, caregivers will complete questionnaires regarding their own quality-of-life (e.g., health status, socioeconomic) as well as the care provided to their loved ones with dementia (e.g., how the care provided meets the needs of the care recipient, time spent). A convergent mixed methods approach will be used to analyze the qualitative and quantitative data obtained. Results Data from the interviews will be transcribed verbatim and then analyzed qualitatively. Quantitative data from the questionnaires will be analyzed using IBM SPSS Statistics software. A convergent mixed methods approach will be applied to the datasets to help shed light on the relationship between family caregiver quality-of-life and the care provided to people living with dementia. Understanding of this relationship will make it possible to develop initiatives that better address caregiver needs.
THE IMPLEMENTATION OF THE SUSTAINABLE DEVELOPMENT GOALS AT THE LOCAL LEVEL. THE CASE OF THE DISTRICTS OF KUYAVIAN-POMERANIAN PROVINCE

The aim of the paper is to provide the objective assessment of progress in the implementation of the goals of the local sustainable development strategy by the districts of Kuyavian-Pomeranian Province. In order to achieve our aim, we have devised, using methods of taxonomic analysis, the synthetic indicator (taking a lot of different measures of sustainable development into account), which shows the degree of the accomplishment of goals adopted in the sustainable development goals. In the collective of units under study, there is a significant differentiation of the level of indicators analyzed within the framework of the sustainable development strategy. It must be emphasized that there are as many as 12 districts in the lower quartile of the distribution of the synthetic measure, i.e., its level was below 0.25. 11 self-government units were in the second quartile of the distribution, i.e., in range between 0.25 and 0.5 of the synthetic indicator. Relatively big taxonomic distances between synthetic measures for individual districts, with quite a large set of features, show significant differentiation among these parts of Kuyavian-Pomeranian Province in terms of local sustainable development. Despite the fact that the examined objects belong to the same administrative unit, which would appear to be relatively coherent, they do not develop at the same pace. Moreover, given a broad set of indicators, they differ significantly when it comes to the rate of their sustainable development. The findings of this paper highlight the use of multidimensional taxonomic analysis for measuring the progress of local units in the degree of the accomplishment of the sustainable development goals. First of all, it helps to show differences in the implementation of the development strategies across districts. What is more, it shows these differences on the basis of the complete set of diverse features rather than single parameters (e.g., pace of growth). Thus, the multidimensional approach is a lot more precise when it comes to showing differences among the examined objects.
Estimating the Social Gap With a Game Theory Model of Lane Changing

Changing lanes is a commonly-used technique for drivers to either overtake slow-moving cars or enter/exit highway ramps. Optional lane changes may save drivers travel time but increase the risk of collision with others. Drivers make such decisions based on experience and emotion rather than analysis, and thus may fail to select the best solution while in a dynamic state of flux. Unlike human drivers, autonomous vehicles can systematically analyze their surroundings and make real-time decisions accordingly. This paper develops a game theory-based lane-changing model by comparing two types of optimization methods. To realize our expectations, we need to first investigate the payoff function of drivers in discretionary lane-changing maneuvers and then quantify it in an equation of costs that trades-off safety and time-saving. After the evaluation for each alternative strategy combination, the results show that there exists a social gap in the discretionary lane-changing game. To deal with that problem, we provide some suggestions for future policy as well as autonomous vehicle controller designs, offering solutions to reduce the impact of disturbances and crashes caused by inappropriate lane changes, and also, inspire further research about more complex cases.
Foreign direct investment and firm innovation in selected sub-Saharan African Countries

Abstract The impact of innovation on every economy cannot be overemphasized. Hence, this study investigates empirically the impact of inward FDI on host firms’ innovation in Nigeria and South Africa using the World Bank Enterprise Survey dataset (WBES). In examining this relationship between FDI and firm innovation, two robust instrumental variable estimation techniques (two-stage least squares and limited information maximum likelihood) were employed so as to account for any endogeneity problems. The study establishes that while FDI positively influences firm innovation in Nigeria, it does not have any impact on firm innovation in South Africa. This study thus presents evidence that context is very crucial in the investigation of the link between FDI and innovation in Sub-Saharan Africa. It is thus recommended that FDI attraction into Africa should be selectively done with more focus on inflows from more advanced and innovative economies.
LITNET-2020: An Annotated Real-World Network Flow Dataset for Network Intrusion Detection

Network intrusion detection is one of the main problems in ensuring the security of modern computer networks, Wireless Sensor Networks (WSN), and the Internet-of-Things (IoT). In order to develop efficient network-intrusion-detection methods, realistic and up-to-date network flow datasets are required. Despite several recent efforts, there is still a lack of real-world network-based datasets which can capture modern network traffic cases and provide examples of many different types of network attacks and intrusions. To alleviate this need, we present LITNET-2020, a new annotated network benchmark dataset obtained from the real-world academic network. The dataset presents real-world examples of normal and under-attack network traffic. We describe and analyze 85 network flow features of the dataset and 12 attack types. We present the analysis of the dataset features by using statistical analysis and clustering methods. Our results show that the proposed feature set can be effectively used to identify different attack classes in the dataset. The presented network dataset is made freely available for research purposes.
Revision of Habrosaurus Gilmore (Caudata; Sirenidae) and relationships among sirenid salamanders

The sirenid salamander Habrosaurus is revised and redescribed based on skull elements and vertebrae from the middle Campanian–middle Palaeocene of the North American Western Interior. Habrosaurus differs from the Cenozoic (Eocene–Recent) sirenids Siren and Pseudobranchus in a suite of cranial and vertebral plesiomorphies, one vertebral character of uncertain polarity and five apomorphies describing the structure of the dentary, atlas and tooth crowns. Two species are identified based on dental characters: the type species H. dilatus (late Maastrichtian–middle Palaeocene) has stout marginal and palatal teeth with bulbous crowns and prominent wear facets, whereas H. prodilatus sp. nov. (middle Campanian) has chisel‐like marginal teeth (palatal teeth unknown) with weaker wear facets. Habrosaurus is argued to be the geologically oldest, undoubted sirenid and the sister‐taxon of Siren + Pseudobranchus. Replacement of marginal teeth with a broad, horny beak in Siren and Pseudobranchus and the broad, bulbous marginal and palatal teeth in H. dilatus are proposed to be convergent strategies for achieving a crushing bite. The chisel‐like teeth of H. prodilatus are interpreted as being transitional to the more specialized, crushing dentition of H. dilatus.
Using landscape characteristics to predict risk of lion attacks on humans in south‐eastern Tanzania

Human–carnivore conflict has profound impacts on carnivore populations and lives of rural communities. In Tanzania, African lions (Panthera leo) have attacked over 1000 people in the last twenty years. We developed a logistic regression model that predicts probability of lion attacks based on landscape characteristics, creating a risk map for two well-studied districts in Tanzania as well as for three neighbouring districts. Results indicate that probability of attack increases with proximity to villages and in areas with a large proportion of open woodland/bushland and crops. Attack risks are also affected by distance from protected areas and by changes in grassland, grassland with crops, wetlands and bare areas. The statistical model also predicted attacks at the ward level (an administrative unit below district) in the two study districts and three additional neighbouring districts. Thus, the technique has potential to identify underlying landscape-related causes of human–wildlife conflict and predict future high-risk areas. Resume Les conflits hommes-carnivores ont de profonds impacts sur les populations de carnivores et sur la vie des communautes rurales. En Tanzanie, les lions (Panthera leo) ont attaque plus de 1000 personnes au cours des 20 dernieres annees. Nous avons mis au point un modele de regression logistique qui predit la probabilite des attaques de lions en se basant sur les caracteristiques du paysage, dressant ainsi une carte des risques pour deux districts tres etudies de Tanzanie ainsi que pour trois districts voisins. Les resultats indiquent que la probabilite d'une attaque augmente avec la proximite des villages et dans les regions qui comptent une grande proportion de foret ouverte/brousse et de cultures. Le risque d'attaque est aussi influence par la distance par rapport aux aires protegees et par les changements qui touchent les prairies, les champs cultives, les zones humides et les zones denudees. Le modele statistique predisait aussi des attaques au niveau de la circonscription (niveau d'unite administrative sous celui du district) dans les deux districts etudies et dans les trois districts voisins. Cette technique est donc capable d'identifier des causes sous-jacentes de conflits hommes-faune sauvage liees au paysage et de predire les zones qui seront en grand danger a l'avenir.
Robust Subspace Clustering With Low-Rank Structure Constraint

In this paper, a novel low-rank structural model is proposed for segmenting data drawn from a high-dimensional space. Our method is based on the fact that all groups clustered from a high-dimensional dataset are distributed in multiple low-rank subspaces. In general, it’s a very difficult task to find the low-rank structures hidden in data. Different from the classical sparse subspace clustering (SSC) and low-rank representation (LRR) which all take two steps including building the affinity matrix and spectral clustering, we introduce a new rank constraint into our model. This constraint allows our model to learn a subspace indicator which can capture different clusters directly from the data without any postprocessing. To further approximate the rank constraint, a piecewise function is utilized as the relaxing item for the proposed model. Besides, under the subspace indicator constraints, the integer programming problem is avoided, which makes our algorithm more efficient and scalable. In addition, we prove the convergence of the proposed algorithm in theory and further discuss the general case in which subspaces don’t pass through the origin. Experiment results on both synthetic and real-world datasets demonstrate that our algorithm significantly outperforms the state-of-the-art methods.