bluuebunny/crossref_metadata_2025_split huggingface dataset:
New incremental SVM algorithms for human activity recognition in smart homes
Authors: Nawal Yala , Oussalah Mourad , Fergani Belkacem , Fleury Anthony 
Published: March 2022

AbstractSmart homes are equipped with several sensor networks to keep an eye on both residents and their environment, to interpret the current situation and to react immediately. Handling large scale dataset of sensory events on real time to enable efficient interventions is challenging and very difficult. To deal with these data flows and challenges, traditional streaming data classification approaches can be boosted by use of incremental learning. In this paper, we presented two new Incremental SVM methods to improve the performance of SVM classification in the context of human activity recognition tasks. Two feature extraction methods elaborated by refining dependency sensor extraction feature and focusing on the last sensor event only have been suggested. On the other hand, a clustering based approach and a similarity based approach have been suggested to boost learning performance of the incremental SVM algorithms capitalizing on the relationship between data chunk and support vectors of previous chunk. We demonstrate through several simulations on two major publicly available data sets (Aruba and Tulum), the feasibility and improvements in learning and classification performances in real time achieved by our proposed methods over the state-of-the-art. For instance, we have shown that the introduced similarity-based incremental learning is 5 to 9 times faster than other methods in terms of training performances. Similarly, the introduced Last-state sensor feature method induces at least 5% improvement in terms of F1-score when using baseline SVM classifier.
Point line geometry in the tropical plane
Authors: Tewari Ayush Kumar 
Published: March 2022

AbstractWe study the classical result by Bruijn and Erdős regarding the bound on the number of lines determined by a n-point configuration in the plane, and in the light of the recently proven Tropical Sylvester-Gallai theorem, come up with a tropical version of the above-mentioned result. In this work, we introduce stable tropical lines, which help in answering questions pertaining to incidence geometry in the tropical plane. Projective duality in the tropical plane helps in translating the question for stable lines to stable intersections that have been previously studied in depth. Invoking duality between Newton subdivisions and line arrangements, we are able to classify stable intersections with shapes of cells in subdivisions, and this ultimately helps us in coming up with a bound. In this process, we also encounter various unique properties of linear Newton subdivisions which are dual to tropical line arrangements.
On the approximate purification of mixed strategies in games with infinite action sets
Authors: Hosoya Yuhki , Yu Chaowen 
Published: March 2022

AbstractWe consider a game in which the action set of each player is uncountable, and show that, from weak assumptions on the common prior, any mixed strategy has an approximately equivalent pure strategy. The assumption of this result can be further weakened if we consider the purification of a Nash equilibrium. Combined with the existence theorem for a Nash equilibrium, we derive an existence theorem for a pure strategy approximated Nash equilibrium under sufficiently weak assumptions. All of the pure strategies we derive in this paper can take a finite number of possible actions.
A DCRNN-based ensemble classifier for speech emotion recognition in Odia language
Authors: Swain Monorama , Maji Bubai , Kabisatpathy P. , Routray Aurobinda 
Published: March 2022

AbstractThe Odia language is an old Eastern Indo-Aryan language, spoken by 46.8 million people across India. We have designed an ensemble classifier using Deep Convolutional Recurrent Neural Network for Speech Emotion Recognition (SER). This study presents a new approach for SER tasks motivated by recent research on speech emotion recognition. Initially, we extract utterance-level log Mel-spectrograms and their first and second derivative (Static, Delta, and Delta-delta), represented as 3-D log Mel-spectrograms. We utilize deep convolutional neural networks deep convolutional neural networks to extract the deep features from 3-D log Mel-spectrograms. Then a bi-directional-gated recurrent unit network is applied to express long-term temporal dependency out of all features to produce utterance-level emotion. Finally, we use ensemble classifiers using Softmax and Support Vector Machine classifier to improve the final recognition rate. In this way, our proposed framework is trained and tested on Odia (Seven emotional states) and RAVDESS (Eight emotional states) dataset. The experimental results reveal that an ensemble classifier performs better instead of a single classifier. The accuracy levels reached are 85.31% and 77.54%, outperforming some state-of-the-art frameworks on the Odia and RAVDESS datasets.
Fully Roll-to-Roll Processed Efficient Perovskite Solar Cells via Precise Control on the Morphology of PbI2:CsI Layer
Authors: Li Hengyue , Zuo Chuantian , Angmo Dechan , Weerasinghe Hasitha , Gao Mei , Yang Junliang 
Published: March 2022

AbstractPerovskite solar cells (PSCs) have attracted tremendous attention as a promising alternative candidate for clean energy generation. Many attempts have been made with various deposition techniques to scale-up manufacturing. Slot-die coating is a robust and facile deposition technique that can be applied in large-area roll-to-roll (R2R) fabrication of thin film solar cells with the advantages of high material utilization, low cost and high throughput. Herein, we demonstrate the encouraging result of PSCs prepared by slot-die coating under ambient environment using a two-step sequential process whereby PbI2:CsI is slot-die coated first followed by a subsequent slot-die coating of organic cations containing solution. A porous PbI2:CsI film can promote the rapid and complete transformation into perovskite film. The crystallinity and morphology of perovskite films are significantly improved by optimizing nitrogen blowing and controlling substrate temperature. A power conversion efficiency (PCE) of 18.13% is achieved, which is promising for PSCs fabricated by two-step fully slot-die-coated devices. Furthermore, PSCs with a 1 cm2 area yield a champion PCE of 15.10%. Moreover, a PCE of 13.00% is obtained on a flexible substrate by the roll-to-roll (R2R) coating, which is one of the highest reported cells with all layers except for metal electrode fabricated by R2R process under ambient condition.
Foliar Spray of Biosynthesized Zinc Oxide Nanoparticles Alleviate Salinity Stress Effect on Vicia faba Plants
Authors: Mogazy Asmaa Mahmoud , Hanafy Rania Samy 
Published: March 2022

AbstractPrevious studies recorded positive impact of ZnO NPs on plants stressed with salinity. The current work was performed to study the effect of two different concentrations of biosynthesized ZnO NPs (50 and 100 mg L−1) on faba bean plants under salinity stress. The zinc oxide nanoparticles (ZnO NPs) were synthesized usingMenthaextract, and their shape and size were characterized using X-ray diffraction and transmission electron microscope while diffuse reflectance spectra were measured using UV–Vis spectrophotometer. The generated ZnO NPs were spherical with a particle size 9.4 nm and had a rod form with particle size 15.2 in length and 3.5 nm in width. The response of faba been plants to the foliar spray of ZnO NPs concentrations (0, 50, and 100 mg L−1) alone and in combination with salt stress at 150 mM NaCl was studied. Salinity induced reduction in faba bean root and shoot length and dry/fresh weights, while an enhancement was recorded in response to foliar treatment with ZnO NPs at 50 and 100 mg L−1either in presence or absence of salinity stress. The highest amounts of chlorophyll a, b, carotenoids, and total pigments were recorded in plants received 50 mg L−1ZnO NPs compared to the alternative control. Secondary metabolites (phenols, flavonoids, and tannins) were accumulated in salinity-stressed plants and further accumulation in response to ZnO NPs treatment was noticed. Amino acids, proline, glycine betaine, and total soluble sugars, as well as enzymatic and non-enzymatic antioxidant contents, increased almost onefold in salinity-stressed plants as compared to control plants while the 50 mg L−1ZnO NPs treatment resulted in higher accumulation of the previously mentioned substances. In contrast, plants oxidative stress was reduced in response to ZnO NPs treatments. The nitrogen, phosphorus, potassium, calcium, zinc, and iron contents of faba bean plants were recorded under salinity stress and in response to the two applied concentrations of ZnO NPs. Faba bean plants stressed with 150 MN NaCl showed growth decline that may be attributed to osmotic stress and low water availability imposed by salinity. The treatment of stressed plants with 50 mg L−1ZnO NPs induced an enhancement in plant growth as well as an accumulation of antioxidants, osmolytes, and secondary metabolites that could help plants overcome the negative effects of salinity.
Extraction of 40Ar-39Ar Ages from a Multicomponent Mixture: A Case Study From the Tatra Mountains, Poland
Authors: Kuligiewicz Artur , Skiba Michał , Szczerba Marek , Hall Chris M. , Bakowska Dorota 
Published: March 2022

AbstractExtraction of meaningful information on the timing of fault activity from clay gouges using radiometric dating methods, such as those based on the K-Ar system, can be challenging. One of the factors complicating interpretation of the radiometric dating results is the presence of multiple K-bearing components in the gouge material. In the current study, an attempt was made to develop a new interpretative method for K-Ar and 40Ar-39Ar dating, capable of handling a three-component mixture. In addition, the mineral composition of clay gouges from the Tatra Mountains (Poland), which has not been investigated before, is reported. The mineral compositions of the bulk clay gouge material and separated size fractions were determined by X-ray diffractometry and Fourier-transform infrared spectroscopy. The gouge samples were composed of quartz, dioctahedral mica (as a discrete phase and as a component of mixed-layered illite-smectite), and chlorite, commonly with plagioclase and more rarely with K-feldspar, dioctahedral smectite, calcite, anatase, or trace kaolinite. One feldspar-free sample containing three mica polytypes (1Md, 1M, and 2M1) was chosen for dating with the 40Ar-39Ar method. The results of 40Ar-39Ar dating were interpreted using three concepts: Illite Age Analysis (IAA), a method based on the MODELAGE software, and a newly developed three-component concept. The age values obtained with IAA were −14 Ma ± 31 Ma and 180 ± 91 Ma for authigenic (1Md) and inherited (1M + 2M1) components, respectively. The MODELAGE-based approach returned –4 ± 40 Ma and 165 ± 62 Ma. The three-component approach returned age values of polytypes as follows: 1Md, 15 ± 37 Ma; 1M, 135 ± 57 Ma; 2M1, 121 ± 56 Ma based on the medians and the interquartile ranges of non-normal distributions of Monte Carlo-simulated age values. The results obtained indicated that the 1Md polytype was probably formed during the most recent stage of fault activity, while 1M and 2M1 polytypes are of equal age, roughly.
Assessing social structure: a data-driven approach to define associations between individuals
Authors: Tavares Sara B. , Whitehead Hal , Doniol-Valcroze Thomas 
Published: March 2022

AbstractOur interpretation of animal social structures is inherently dependent on our ability to define association criteria that are biologically meaningful. However, association thresholds are often based upon generalized preconceptions of a species’ social behaviour, and the impact of using these arbitrary definitions has been largely overlooked. In this study we suggest a probability-based method for defining association thresholds using lagged identification rates on photographic records of identifiable individuals. This technique uses a simple model of emigration/immigration from photographable clusters to identify the time-dependent lag value between identifications of two individuals that corresponds to approximately 75% probability of being in close spatial proximity and likely associating. This lag value is then used as the threshold to define associations for social analyses. We applied the technique to a dataset of northern resident killer whales (Orcinus orca) in the Northeast Pacific and tested its performance against two arbitrary thresholds. The probabilistic association maximized the variation in association strengths at different levels of the social structure, in line with known social patterns in this population. Furthermore, variability in inferred social structure metrics generated by different association criteria highlighted the consequential effect of choosing arbitrary thresholds. Data-driven association thresholds are a promising approach to study populations without the need to subjectively define associations in the field, especially in societies with prominent fission–fusion dynamics. This method is applicable to any dataset of sequential identifications where it can be assumed that associated individuals will tend to be identified in close proximity.
Computer Architecture for Scientists
Authors: Chien Andrew A. 
Published: March 2022

The dramatic increase in computer performance has been extraordinary, but not for all computations: it has key limits and structure. Software architects, developers, and even data scientists need to understand how exploit the fundamental structure of computer performance to harness it for future applications. Ideal for upper level undergraduates, Computer Architecture for Scientists covers four key pillars of computer performance and imparts a high-level basis for reasoning with and understanding these concepts: Small is fast – how size scaling drives performance; Implicit parallelism – how a sequential program can be executed faster with parallelism; Dynamic locality – skirting physical limits, by arranging data in a smaller space; Parallelism – increasing performance with teams of workers. These principles and models provide approachable high-level insights and quantitative modelling without distracting low-level detail. Finally, the text covers the GPU and machine-learning accelerators that have become increasingly important for mainstream applications.
Call first, pay later: stimulating debtors to contact their creditors improves debt collection in the context of financial scarcity
Authors: Dewies Malte , Schop-Etman Astrid , Merkelbach Inge , Rohde Kirsten I. M. , Denktaş Semiha 
Published: March 2022

AbstractDebtors were stimulated to contact their creditors to negotiate a repayment plan. Contacting creditors was important because debtors were unlikely to repay the debt immediately and upon contacting, debtors could agree on a repayment plan to repay the debt in the long run. Using insights from scarcity theory and nudging techniques, a standard debt repayment letter was adapted and both letters were compared. Experimental results (N = 3,330) provide support for the use of nudging techniques as more debtors agreed on a repayment plan and response rates increased. The results underline the importance of stimulating debtors to contact their creditors.
A trickle-down model of organizational embodiment and the impact of supervisor neuroticism
Authors: Rice Darryl B. , Mchiri Ali , Massey MaQueba 
Published: March 2022

AbstractThe majority of supervisor organizational embodiment (SOE) research has focused on its role as an important boundary condition in the context of leadership and management studies. In a multi-source field study, we seek to extend this research stream by examining an antecedent and outcome of SOE. Specifically, we leverage social cognitive theory to develop and test a trickle-down model of organizational embodiment across three organizational levels (i.e., upper-level managers, middle-level supervisors, and lower-level employees). Subsequently, we propose and demonstrate that manager organizational embodiment (MOE) trickles down and positively impacts SOE. In turn, SOE trickles down and positively impacts employee organizational embodiment. Furthermore, supervisor neuroticism strengthens the relationship between MOE and SOE when supervisor neuroticism is relatively high compared to relatively low. The findings provide evidence for a trickle-down model of organizational embodiment. Theoretical contributions, practical implications, and future research are discussed.
Bayesian occupancy modelling of benthic Crustacea and the recovery of the European spiny lobster, Palinurus elephas
Authors: Jackson A.C. 
Published: March 2022

AbstractThere is ever-greater need for information about changing marine biodiversity, but such information is sparse at large spatial or temporal scales. Records about distributions of species collected by volunteers can fill gaps in knowledge that cannot yet be addressed by more structured sampling. Bayesian occupancy models show great promise for estimating trends in occurrence of species through time. This study uses the Sparta occupancy model with records from the Seasearch programme from coastal waters of Britain and Ireland during the period 2000–2020, focussing on three species of Crustacea (Cancer pagurus, Homarus gammarus and Palinurus elephas). Populations of P. elephas crashed in the 1970s, but now appear to be re-establishing in south-west England. The Sparta model provides evidence about recovery that is more robust than anecdotal reports or simple counts of records. Estimates of occupancy are made at different spatial scales and compared among species and areas. Trends in occupancy are compared qualitatively with patterns in fisheries landings data. Occupancy by P. elephas has increased drastically since 2014, a pattern not seen in the other two species. For each species, occupancy varied among areas and in some areas, patterns in estimates of occupancy were similar to trends in landings from fisheries. Citizen science records are increasingly recognized to have value which has not yet been fully exploited. Greater use should be made of the Seasearch dataset in order to provide population trends for benthic marine taxa. Such analyses will broaden our understanding of and taxonomic coverage of changes in biodiversity.
Surveys of the Angolan coast uncover the largest olive ridley sea turtle nesting population in the Atlantic and the largest non-arribada population globally
Authors: Morais Miguel , Tiwari Manjula 
Published: March 2022

AbstractKnowledge of the abundance and distribution of species is important for designing and prioritizing conservation and management activities. Despite numerous existing studies on the distribution and status of sea turtles, we still lack knowledge about certain populations, especially in Angola, which is considered to be the southernmost range of nesting sea turtles in the eastern Atlantic. This study provides an overview of the status, size and distribution of the olive ridley sea turtle Lepidochelys olivacea population nesting along the coast of Angola, and its relevance in the context of other olive ridley turtle nesting populations in the Atlantic. Aerial and ground surveys were conducted along 1,410 km of Angolan coastline and daily beach monitoring over 53.9 km of seven permanent study sites at a range of latitudes during 2011–2020. Angola hosts the largest olive ridley turtle nesting population in the Atlantic, and the largest non-arribada population globally. Although the population appeared relatively stable, the pressures from various threats on land (e.g. consumption of turtles and eggs) and at sea (captures in fishing gear) necessitate the development of a comprehensive management plan, improved and strengthened legislation and law enforcement, and a cohesive approach to conserving all sea turtle species in Angola.
‘Consubstantiality’ as a philosophical-theological problem: Victorinus’ hylomorphic model of God and his ‘correction’ by Augustine
Authors: Byers Sarah 
Published: March 2022

AbstractThis article expands our knowledge of the historical-philosophical process by which the dominant metaphysical account of the Christian God became ascendant. It demonstrates that Marius Victorinus proposed a peculiar model of ‘consubstantiality’ that utilised a notion of ‘existence’ indebted to the Aristotelian concept of ‘prime matter’. Victorinus employed this to argue that God is a unity composed of Father and Son. The article critically evaluates this model. It then argues that Augustine noticed one of the model's philosophical liabilities but did not publicly name Victorinus when he rejected it, thereby exemplifying the New Testament practice of private ‘rebuke’ (ἐλέγχɛιν).
Lost in Categorisation? Employment Subsidies – Bringing the Beneficiaries Back In
Authors: ROBERTSHAW DAVID KEITH 
Published: March 2022

AbstractEmployment subsidies are important active labour market policy (ALMP) tools, suited to a variety of labour market challenges. This paper engages with recent ALMP categorisation debates by appraising Cronert’s (2019) recent typology of employment subsidies. It uses empirical material to assess the typology’s explanatory power and produce insights to inform further typological development. The illustrative case of the British ‘Wage Incentive’ (2012-2014) is used to assess the typology’s analytical purchase. Cronert’s typology helpfully identifies key distinctions in the distributional profiles of employment subsidies, but further understanding of the category is impeded by the practice of defining them as demand-side interventions. The paper argues for a reappraisal of their supply-side characteristics, maintaining that the (potential) worker should be included in the analysis, and that employment subsidies’ relationship with training and job creation should be acknowledged. It proposes a redefinition of employment subsidies reflecting their real-world use, and suggests a framework for further exploring varieties of employment subsidy design from the perspective of beneficiaries.
Can't nobody tell me nothin’: ‘Old Town Road’, resisting musical norms, and queer remix reproduction
Authors: Stanfill Mel 
Published: March 2022

Abstract‘Old Town Road’, a genre-defying song fuelled by proliferating remixes, is a key site to unravel the position of remixes in contemporary popular music and culture. In this article, I examine mainstream press discourse about ‘Old Town Road’, finding that Lil Nas X's use of remixes to boost the song's popularity was generally seen as smart, while the racial politics of genre were contested but still powerful. Ultimately, the popular conversation around the song showed a sense that one key possibility of remixes is to resist the ways that genres normatively operate as straight lines of descent from musical forebears, instead engaging in a queer kind of reproduction, a joyful excess of proliferating versions.