Miracle-dz/UniFAR-FTUs huggingface dataset:
An Integrated Microclimate-Energy Demand Simulation Method for the Assessment of Urban Districts

Rapid urbanization and densification processes are changing microclimatic environments in cities around the world. Even though previous studies have demonstrated the impact of urban microclimate on space cooling and heating demand, modeling tools employed to support the design process largely overlook microclimatic conditions in assessing building energy performance, making use of data from weather stations often located in rural areas. This paper presents a computational approach for the quantitative analysis of building energy demand at the district scale, including interdependent factors such as local air temperature, relative humidity and wind speed, diversity in building geometry and materials. The method, which couples the microclimate model ENVI-met and the district-scale energy simulation tool City Energy Analyst, is applied to a case study in Zurich, Switzerland, in order to analyze the energy performance of the area on a hot summer day. The study contributes to advance a coupling approach between a microclimate simulation and an energy tool at the district scale. The results showed that the coupled assessment approach can deal with complex interactions between geometry, building materials and energy systems. The consideration of local microclimatic conditions led to a 5% increase in the space cooling demand on the selected day, while the simulated peak cooling load for each building was 8% higher on average. The variation in the space cooling demand was found to be mainly due to an increase in latent cooling demand. Moreover, the coupling method allowed a detailed analysis of energy demand variation at the building level showing that, when considering the local climate patterns, the space cooling demand of the individual buildings varied between −5% and +14% on the selected day. The proposed method represents a next step to reflect the mutual interactions between buildings and microclimate in urban districts and aims at supporting decision-making in the design process.
Factors influencing farmers decisions to technological adoption for enhancing livelihoods security in Rudraprayag district, Uttarakhand, India

This paper summarizes the results of an adoption study conducted in between 2014 and 2016 in district Rudraprayag, Uttarakhand, to determine the level and extent of adoption of selected technologies. This study aimed to identify reason of low adoption rates and policy lapses in adoption of technologies for future conduct of research and research-extension linkages. A sample of 604 household from 64 villages was randomly selected from three different blocks of the district to determine the distribution of adoption of the technologies. Semi-structured questionnaire and interview method were used to collect the primary data and survey questions used to identify the factors that affect farmer’s decision on adoption of technology. Adoption rate was highest for the cases of inorganic fertilizer (52.21%), improved seed (19.48%), bio/vermicompost (11.03%), polyhouse (9.93%), water harvesting tank (6.99). The high rates of adoption may be due to extensive diffusion of technology. The results of the logistic regression model show that the age and education of household head (HHAge and HHEdu), land size (TLand), institutional support for adopting the new technology (InsSupp) and farmers cosmopoliteness (Cosmopo) are the main determinants of the adoption of new farm technology. The model shows that after keeping the other variables constant, the effect of variables such as age and education of the household head, area of agriculture land, institutional support and cosmopoliteness, favours adoption. This study will assist the policy makers to develop and extent area specific suitable technology with proper technical know-how for higher extension and adoption of the technology.
ARTICULATION AND SPEAKING RATES IN BILINGUALS WITH REGARD TO TIME OF EXPOSURE TO ONE LANGUAGE

The basic aim of the research presented in this paper was to check whether the language proficiency level of bilingual children with Polish as one of their languages is also related to the pace of speech, which is the result of two specific parameters i.e. articulation rate and speaking rate. It was assumed that children who use Polish more rarely and mostly at home will display slower speaking and articulation rates when contrasted with children who use Polish both at home and at school on an everyday basis. Participants were thirty-two children who speak Polish as one of two languages, the first research group consisting of sixteen PolishFrench students at the age of 8.11 living in Wallonia. The second group consisted of sixteen Flemish-Polish students living in Flanders. Here the average age was 9.3 and subjects used Polish much less than their first group counterparts. The comparative analysis in cluded the following parameters essential for the description of the rate of speech: 1. basic: average speaking rate (phones/sec., sylla bles/sec, duration of pauses), average articulation rate (phones/ sec., syllables/sec.), average ratio of pauses in speech sample (number and percentage), 2. accessory: average duration of all pauses (sec.), average duration of proper pauses (sec.), average duration of filled pauses (sec.), average duration of semi-filled pauses (sec.). The numerical data from the research was obtained with the use of free Audacity software. The results showed that there were no statistically significant diffe rences between the two research groups in either the basic or the accessory speech rate parameters. In the Polish-French group the results were comparatively better but still statistically insignificant. It seems that the data obtained will confirm the need for conside rable caution in the evaluation of the competence of bilingual children with high language skills. Similar to children with imba lan ced bilingualism, these children may also, perhaps, require some extra time to deal with certain language tasks.
Field evaluation of mineral oils for insect pests management and yield of cowpea (Vigna unguiculata) (L) Walp in Abraka, Southern Nigeria.

Mineral oils have been successfully used as insecticides to control insect pests on several crops such as cotton in many parts of the world. Such work is yet to be reported in Nigeria. This study assayed the effectiveness of three mineral oils - premium motor spirit (PMS), dual purpose kerosene (DPK) and automotive gas oil (AGO) at 0.4% concentration in the management of four major insect pests of cowpea, namely the cowpea aphid, Aphis craccivora Koch, legume bud thrips, Megalurothrips sjostedti Tryb, legume pod borer, Maruca vitrata Fab. and pod sucking bugs. It also assessed influence of pests control on cowpea yield. The field trials were carried out during the early and late seasons on a public land about half kilometre to Campus 2 of Delta State University, Abraka, Southern Nigeria. The results indicated that all the tested mineral oils effectively controlled M. sjostedti damage in the early season. Similarly, AGO controlled M. vitrata and pod sucking bugs. DPK equally controlled coreid bugs. In the late season, A. craccivora and coreid bugs were reduced by all the mineral oils. In the early season, grain yields were high as follows: 1,342.90 kg ha-1, 963.30kg ha-1, 836.70 kg ha-1 and 917.80kg ha-1 for DPK, PMS, AGO and control respectively. In the late season, yields were 763.30kg ha-1, 634.60kg ha-1, 578.00kg ha-1 and 375.00kg ha-1 for AGO, PMS, DPK and control respectively. Grain yields were significantly higher (P<0.05) in the early than late season. Delay and reduced flowering were observed in the field. Elimination of these factors could improve the use of mineral oils in the cultivation of cowpea. The information given here can be used to strengthen the integrated pest management programme in the control of cowpea insect pests.
Prevalence Trends and Associated Modifiable Risk Factors of Peptic Ulcer Disease among Students in a University Community South-South Nigeria

Introduction: Peptic ulcer disease (PUD) is one of the commonest ailments of the alimentary system. It affects about 4 million of the world’s population annually, with incidence of complications in approximately 10–20%. PUD impacts negatively on the health-related quality of life of affected individuals while employers and healthcare systems are burdened with high economic cost of dealing with the disease. Established risk factors of PUD such as stress, smoking, and use of alcohol, coffee, and NSAIDs are commonly associated with university students and could impact on the disease prevalence. Therefore, determining the prevalence trends of established PUD and associated risk factors in risk populations is essential for clinical and epidemiological decision making. Objective: To investigate the prevalence trend and associated modifiable risk factors of PUD among students in Niger Delta University (NDU), Amassoma Bayelsa State, Nigeria. Methods: A hospital based retrospective survey design was employed. The medical records of students who accessed the NDU Medical Centre from January, 2014 to December, 2019 were assessed. Relevant data extracted from students’ case files were analysed with the aid of the Statistical Package for Social sciences (SPSS) version 23 and described statistically in terms of frequencies and percentages. Results: A total of 988 students were diagnosed of PUD from January, 2014 to December, 2019. More Christians (74.7%) and first year students (30.4%) had PUD. More females (55.6%) than males (44.4%) were diagnosed of PUD. Females had PUD than males in 2014 (64.1%), 2015 (61.5%), 2016 (56.2%) and 2018 (54.0%); while males had PUD than females in 2017 (52.0%) and 2019 (51.4%). Prevalence was highest among students within 17-21 years in 2014 (33.5%), 2015 (43.2%), and 2017 (32.4%) while in 2016, 2018 and 2019, prevalence was highest among 22-26 (33.3%), 27-31 (30.3% and 34.3%) respectively. Starvation, stress, NSAID use, alcohol consumption and cigarette smoking were the major modifiable risk factors of PUD documented. Starvation and stress were most common (100%) among students. Conclusion: PUD prevalence is low but risk factor association is enormous. Education aimed at reducing risk factor association may help change future prevalence trend in the positive direction.
Assessment of Heavy Metals in Milk Produced by Black-and-White Holstein Cows from Moscow

Milk must comply with quality standards for proper human nutrition. The purpose of this study was to conduct a comparative microbiological and elemental analysis of milk quality from Black-and-White Holstein cows. The studies were conducted on the basis of livestock farming in JanuaryOctober 2019, Moscow region, Russian Federation. The experiment included 60 cows, divided into 3 groups of 20 animals of full age. All cows were kept under identical conditions. The first group consisted of purebred Black-and-White cows; the second group included Holstein half breeds; and the third group included the third generation of Holstein crossbreeds. 500 samples of milk were taken from animals of each group. The second group exceeded in content of zinc by 0.5 times (p≤0.05). The third group was recorded with lower manganese by 2 times (p≤0.001) while the first group by 0.5 times (p≤0.05) compering to the second group. Milk in groups 3 and 2 had a significant excess of iron and copper concentrations by 1.52. 0 times (at p≤0.001), comparing to group 1. The milk in group 1 (purebred Black-and-White cows) exceeded TLV (threshold limit value) for lead (by 2.2 times) and cobalt (by 2.5 times). The milk in this group also had a higher cadmium content compering to the other two groups (by 1.3–2.7 times). Holstein crossbreeding helps to increase the concentration of cobalt, zinc and manganese. Lead and cadmium accumulate in the milk of purebred Black-and-White cows. Current Research in Nutrition and Food Science www.foodandnutritionjournal. org ISSN: 2347-467X, Vol. 08, No. (2) 2020, Pg. 410-415 CONTACT Vladimir Safonov vladimirsafonov1@rambler.ru Laboratory of Environmental Biogeochemistry, Vernadsky Institute of Geochemistry and Analytical Chemistry of Russian Academy of Sciences, Moscow, Russia. © 2020 The Author(s). Published by Enviro Research Publishers. This is an Open Access article licensed under a Creative Commons license: Attribution 4.0 International (CC-BY). Doi: http://dx.doi. org/10.12944/CRNFSJ.8. 2.06 Article History Received: 05 May 2020 Accepted: 11 August 2020
Dark Matter Search Results from the PICO-60 CF$_3$I Bubble Chamber

New data are reported from the operation of the PICO-60 dark matter detector, a bubble chamber filled with 36.8 kg of CF$_3$I and located in the SNOLAB underground laboratory. PICO-60 is the largest bubble chamber to search for dark matter to date. With an analyzed exposure of 92.8 livedays, PICO-60 exhibits the same excellent background rejection observed in smaller bubble chambers. Alpha decays in PICO-60 exhibit frequency-dependent acoustic calorimetry, similar but not identical to that reported recently in a C$_3$F$_8$ bubble chamber. PICO-60 also observes a large population of unknown background events, exhibiting acoustic, spatial, and timing behaviors inconsistent with those expected from a dark matter signal. These behaviors allow for analysis cuts to remove all background events while retaining $48.2\%$ of the exposure. Stringent limits on weakly interacting massive particles interacting via spin-dependent proton and spin-independent processes are set, and most interpretations of the DAMA/LIBRA modulation signal as dark matter interacting with iodine nuclei are ruled out.
The microbial ecology of marine sponge-associated microorganisms

ii Acknowledgements . iv Table of contents . v List of figures . viii List of Tables . x 1. General introduction . 1 1.1 Sponge morphology and function . 1 1.2 Sponge-associated microorganisms . 4 1.2.1 Diversity and specificity . 6 1.2.2 Stability of sponge-associated microbial communities (temporal, biogeographic, external pressures) . 12 1.3 Functional roles of sponge-associated microbes . 16 1.3.1 Photosynthesis . 17 1.3.2 Nitrogen cycling . 18 1.3.3 Other functions . 20 1.4 Biotechnological potential of sponges and sponge-associated microorganisms . 21 1.5 Research objectives: scope and aims of this thesis . 23 1.6 References . 26 2. Sponge-specific clusters revisited: a comprehensive phylogeny of sponge-associated microorganisms . 45 2.1 Abstract . 46 2.2 Introduction . 47 2.3 Results and Discussion . 48 2.4 Experimental procedures . 56 2.5 Acknowledgments . 58 2.6 References . 58 3. Evaluating methods for the preservation and extraction of DNA and RNA for analysis of microbial communities in marine sponges . 61 3.1 Abstract . 62 3.2 Introduction . 63 3.3 Materials and Methods . 65 3.3.1. Sample collection . 65 3.3.2 Preservation. 65 3.3.3 Extraction of nucleic acids . 66 3.3.4 Assessment of quality, quantity and composition of DNA and RNA . 67 3.3.5 Statistical analysis . 69 3.4 Results and Discussion . 69 3.4. 1 Preservation and extraction of DNA . 69 3.4. 2 Preservation and extraction of RNA . 70 3.4. 3 Recovery of mRNA . 74 3.4. 4 Impact of sample preservation and DNA/RNA extraction methods on DGGE-based assessments of bacterial community composition. 75 3.4. 5 Application of preservation and extraction protocol with other sponges . 76 3.5 Recommendations and concluding remarks . 77 3.6 Acknowledgements . 78 3.7 References . 79
Dynamic coalition formation processes: A generalization of subgame perfection based on stable set

We propose two versions of stable set as a solution concept that generalizes subgame perfection for dynamic coalition formation processes. Weakly stable set of paths (WSSP) and weakly conservative stable set of paths (WCSSP) is based on a dominance relationship which derives from a weak preference relation. The new solution concepts are closely related to OSSB and CSSB in the Theory of Social Situations. In game trees with single player moves, WSSP, like CSSB, selects paths that correspond to the set of perfect equilibrium paths. WCSSP, which is based on a more demanding dominance relation, refines this concept and eliminates paths that are dominated in the conventional (strategic) sense. Finally, we generalize WSSP drawing on Delver and Monsuur’s socially stable set, which always exists, and establish weakly socially stable set of paths (WSSSP). WSSSP, like WSSP, generalizes subgame perfection.
Conflict in Africa: Climate, Economic Shocks and Spill-Over Effects

This study examines the relationship between weather shocks, economic conditions and conflict in Africa. Reverse causality in the economic growth-conflict relationship is addressed by using precipitation and temperature variables as instruments for economic growth. Furthermore, the role of extractive and non-extractive commodity price shocks is examined. While previous studies rely on country-level data sets, this study exploits a panel dataset of African first-order administrative units covering the time period 1992-2010. Sub-national gross domestic product (GDP) data for Africa is either unavailable or of poor quality. For this reason, night-time light data from satellites is utilized to estimate economic growth at the sub-national level. Spatial econometric methods are applied to account for conflict spill-overs via political, geographical and ethnic ties. Estimation results provide no evidence that economic growth has a significant causal impact on violence, but reveal strong spill-over effects.
TRACE: Transform Aggregate and Compose Visiolinguistic Representations for Image Search with Text Feedback

The ability to efficiently search for images over an indexed database is the cornerstone for several user experiences. Incorporating user feedback, through multi-modal inputs provide flexible and interaction to serve fine-grained specificity in requirements. We specifically focus on text feedback, through descriptive natural language queries. Given a reference image and textual user feedback, our goal is to retrieve images that satisfy constraints specified by both of these input modalities. The task is challenging as it requires understanding the textual semantics from the text feedback and then applying these changes to the visual representation. To address these challenges, we propose a novel architecture TRACE which contains a hierarchical feature aggregation module to learn the composite visio-linguistic representations. TRACE achieves the SOTA performance on 3 benchmark datasets: FashionIQ, Shoes, and Birds-to-Words, with an average improvement of at least ~5.7%, ~3%, and ~5% respectively in R@K metric. Our extensive experiments and ablation studies show that TRACE consistently outperforms the existing techniques by significant margins both quantitatively and qualitatively.
Engineering Applications of Artificial Intelligence

In particular, the proposed two-stage algorithm improve several best known solutions (either a better NV or a better TD when NV are the same) from the state-of-the-art. To our knowledge, this is the first learning-based two-stage algorithm for solving VRPSPDTW reaching such a performance. Finally, we empirically analyze several critical components of the algorithm to highlight their impacts on the performance of the proposed algorithm.
Unsupervised Feedforward Feature (UFF) Learning for Point Cloud Classification and Segmentation

In contrast to supervised backpropagation-based feature learning in deep neural networks (DNNs), an unsupervised feedforward feature (UFF) learning scheme for joint classification and segmentation of 3D point clouds is proposed in this work. The UFF method exploits statistical correlations of points in a point cloud set to learn shape and point features in a one-pass feedforward manner through a cascaded encoder-decoder architecture. It learns global shape features through the encoder and local point features through the concatenated encoder-decoder architecture. The extracted features of an input point cloud are fed to classifiers f or shape classification and part segmentation. Experiments are conducted to evaluate the performance of the UFF method. For shape classification, the UFF is superior to existing unsupervised methods and on par with state-of-the-art DNNs. For part segmentation, the UFF outperforms semi-supervised methods and performs slightly worse than DNNs.
Standstill to the 'beat': differences in involuntary movement responses to simple and complex rhythms

Previous studies have shown that movement-inducing properties of music largely depend on the rhythmic complexity of the stimuli. However, little is known about how simple isochronous beat patterns differ from more complex rhythmic structures in their effect on body movement. In this paper we study spontaneous movement of 98 participants instructed to stand as still as possible for 7 minutes while listening to silence and randomised sound excerpts: isochronous drumbeats and complex drum patterns, each at three different tempi (90, 120, 140 BPM). The participants' head movement was recorded with an optical motion capture system. We found that on average participants moved more during the sound stimuli than in silence, which confirms the results from our previous studies. Moreover, the stimulus with complex drum patterns elicited more movement when compared to the isochronous drum beats. Across different tempi, the participants moved most at 120 BPM for the average of both types of stimuli. For the isochronous drumbeats, however, their movement was highest at 140 BPM. These results can contribute to our understanding of the interplay between rhythmic complexity, tempo and music-induced movement.
Spatial Transformer Point Convolution

Point clouds are unstructured and unordered in the embedded 3D space. In order to produce consistent responses under different permutation layouts, most existing methods aggregate local spatial points through maximum or summation operation. But such an aggregation essentially belongs to the isotropic filtering on all operated points therein, which tends to lose the information of geometric structures. In this paper, we propose a spatial transformer point convolution (STPC) method to achieve anisotropic convolution filtering on point clouds. To capture and represent implicit geometric structures, we specifically introduce spatial direction dictionary to learn those latent geometric components. To better encode unordered neighbor points, we design sparse deformer to transform them into the canonical ordered dictionary space by using direction dictionary learning. In the transformed space, the standard image-like convolution can be leveraged to generate anisotropic filtering, which is more robust to express those finer variances of local regions. Dictionary learning and encoding processes are encapsulated into a network module and jointly learnt in an end-to-end manner. Extensive experiments on several public datasets (including S3DIS, Semantic3D, SemanticKITTI) demonstrate the effectiveness of our proposed method in point clouds semantic segmentation task.