Miracle-dz/UniFAR-FTUs huggingface dataset:
1 Bayesian Bias Correction of Satellite Rainfall 2 Estimates for Climate Studies 3

Advances in remote sensing have led to use of satellite-derived rainfall products to 9 complement the sparse rain gauge data. Although globally derived and some regional bias 10 corrected, these products often show large discrepancies with ground measurements attributed to 11 local and external factors that require systematic consideration. Decreasing rain gauge network 12 however inhibits continuous validation of these products. We propose to deal with this problem by 13 the use of Bayesian approach to merge the existing historical rain gauge information to create a 14 consistent satellite rainfall data that can be used for climate studies. Monthly Bayesian bias 15 correction is applied to the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS 16 v2) data to reduce systematic errors using a corresponding gridded (0.05°) rain gauge data over East 17 Africa for a period of 33 (1981–2013) years of which 22 years are utilized to derive error fields which 18 are then applied to an independent CHIRPS data for 11 years for validation. The bias correction is 19 spatially and temporally assessed during the rainfall wet months of March-May (MAM), June20 August (JJA) and October–December (OND) in East Africa. Results show significant reduction of 21 systematic errors at both monthly and yearly scales and harmonization of their cumulative 22 distributions. Monthly statistics showed a reduction of RMSD (29–56)% and MAE (28–60)% and an 23 increase of correlations (2–32) %, while yearly ones showed reductions of RMSD (9-23)%, and MAE 24 (7–27)% and increase of correlations (4–77)% for MAM months, reduction of RMSD (15–35)% and 25 MAE (16–41)% and increase in correlations (5–16)% for JJA months, and reduction of RMSD (3–35)% 26 and MAE (9–32)% and increase of correlations (3–65)% for OND months. Systematic errors of 27 corrected data were influenced by local processes especially over Lake Victoria and high elevated 28 areas. Large-scale circulations induced errors were mainly during JJA and OND rainfall seasons and 29 were reduced by the separation of anomalous years during training. The proposed approach is 30 recommended for generating long-term data for climate studies where consistencies of errors can 31 be assumed. 32
A Comparison between Two Types of Resistive Inspiratory Muscle Training Devices in Normal Subjects in Regards to Pulmonary Functions

Introduction: Inspiratory muscle training (IMT) devices improve respiratory muscle strength, endurance and exercise capacity on healthy subjects. Because of the limited availability of the effect of IMT devices on healthy subjects with minimal activity level, this study was conducted to evaluate the effects of POWERbreath-plus® and Threshold IMT® on healthy subjects by measuring pre and post Maximal inspiratory pressure (MIP), Maximal expiratory pressure (MEP), Peak Expiratory Flow Rate (PEFR) and Mandatory Voluntary Ventilation (MVV) and to compare their effectiveness. Method: In this quantitative comparative pilot study, 17 female subjects from Imam Abdulrahman Bin Faisal University were randomly assigned into four weeks of IMT program and were distributed into three groups Threshold Group (TG) (n=5), POWERbreath-plus Group (PG) (n=7) and Control Group (CG) (n=5). MIP, MEP, PEFR, MVV were measured prior and following training. Subjects were taught to use the device twice daily with 30 repetitions at 60% of their MIP at the first two weeks with gradual increase by 10% for the remaining two weeks, until reaching load of 80% of MIP. Results: MIP was improved significantly in both, TG and PG (p=0.005 and p=0.006, respectively), while no change was noticed in CG. For MEP, both TG and PG improved significantly with a p-value of (p=0.034 and p=0.208, respectively) while no improvements were observed in CG. PEFR proved to be significantly increased in PG (p=0.012), while there was no improvement in TG and CG. MVV showed improvement in both, TG and PG (p=0.023 and p=0.006, respectively), while no change was noticed in CG. Regarding MNOVA test, Threshold IMT® device shows to be superior to POWERbreath-plus® in increasing MIP significantly (p=0.000). Conclusion: In conclusion, this study suggests that Threshold IMT® and POWERbreath-plus® devices improve MIP and MVV, however, threshold devices may have the superiority in improving MIP but still more studies are needed.
Summary of Physical Properties Measured at Several Boreholes Penetrating through the Chelungpu Fault in Central Taiwan

On 20 September 1999, the Ms 7.6 Chi-Chi earthquake ruptured the Chelungpu fault in central Taiwan. After the earthquake, several boreholes of different depths were drilled. Those boreholes penetrated the fault plane. The physical (mechanical, thermal, hydraulic, electric, and magnetic) parameters were measured either on the core samples or through well-loggings. Results are significant for studies of the Chelungpu fault. However, the measured results are published in different articles and reports. It is not convenient for the earth scientists to take advantage of those results. Hence, those results are compiled and described in this paper. In addition, the correlations among a few parameters are also reported.
State anxiety change after a parachute jump and its determinants: gender, experience, and temperament features

Summary Study aim: To determine the role of gender and experience level as factors differentiating state anxiety before and after a parachute jump, and to ascertain relationships between state anxiety and temperament features. Material and methods: The research involved 143 parachutists (98 men and 45 women) aged from 17 to 49 years old, including 73 beginners and 70 advanced parachutists. The following questionnaires were applied: the Formal Characteristics of Behavior-Temperament Inventory by Zawadzki and Strelau, the Sensation Seeking Scale by Zuckerman, and the State-Trait Anxiety Inventory of Spielberger et al. Results: There was a significant decrease in state anxiety level after a parachute jump (before M = 32.66; after M = 28.57; p < 0.001). Its level is significantly higher in beginners than in experienced skydivers (p < 0.001). The level of experience is also a negative predictor of state anxiety level before the jump and its decrease after the jump. Conclusion: As experience grows, the positive adaptation to stress caused by parachute jump appears, which results with lowering the state anxiety level.
The Difficulty of Climate Change Adaptation in Manufacturing Firms: Developing an Action-Theoretical Perspective on the Causality of Adaptive Inaction

Climate change induces various risks for supply chains of manufacturing firms. However, surveys have suggested that only a minority of firms conducts strategic adaptations, which we define as anticipatory and target-oriented action with the purpose of increasing resilience to climate change. While several barrier-centered studies have investigated the causality of non-adaptation in industry, the examined barriers are often not problem-specific. Furthermore, it has been shown that even in cases when managers perceive no barriers to adaptation at all, strategic adaptations may still not be conducted. On this background, the present analysis focuses on the logic of adaptive inaction, which we conceive, in particular, as inaction with regard to strategic adaptations. Adopting an action-theoretical perspective, the study examines (a) which aspects may shape the rationality of adaptive inaction among managers, (b) which more condensed challenges of conducting strategic adaptations emerge for managers, and (c) how the theoretical propositions can be tested. For this purpose, the study employs an exploratory approach. Thus, hypotheses on such aspects are explored, which may shape the rationality of adaptive inaction among managers. Subsequently, predictions are inferred from the theoretical propositions, which allow testing their empirical relevance. Methodologically, the hypotheses are explored by reexamining existing explanatory approaches from literature based on a set of pretheoretical assumptions, which include notions of bounded rationality. As a result, the study proposes 13 aspects which may constrain managers in conducting adaptations in such a way, which serves the economic utility of the firm. By condensing these aspects, 4 major challenges for managers are suggested: the challenges of (a) conducting long-term adaptations, of (b) conducting adaptations at an early point in time, of (c) conducting adaptations despite uncertain effects of the measures, and of (d) conducting adaptations despite cross-tier dependencies in supply chains. Finally, the study shows how the propositions can be tested and outlines a research agenda based on the developed theoretical suggestions.
Kiskeya palassaina , new genus and new species of Saicinae (Heteroptera: Reduviidae) from the Dominican Republic

A new genus and a species of Saicinae, Kiskeya palassaina, n. gen., n. sp. , are described from the Dominican Republic. The armature of the fore leg of the nine apterous female specimens are unique among genera of Saicinae in consisting of spines on the fore femur, but of stiff setae on the fore tibia. A key to the New World genera is given. Digital macrophotographs, scanning electron micrographs, and illustrations are provided.
The boundaries and twist defects of the color code and their applications to topological quantum computation

The color code is both an interesting example of an exactly solved topologically ordered phase of matter and also among the most promising candidate models to realize fault-tolerant quantum computation with minimal resource overhead. The contributions of this work are threefold. First of all, we build upon the abstract theory of boundaries and domain walls of topological phases of matter to comprehensively catalog the objects realizable in color codes. Together with our classification we also provide lattice representations of these objects which include three new types of boundaries as well as a generating set for all 72 color code twist defects. Our work thus provides an explicit toy model that will help to better understand the abstract theory of domain walls. Secondly, we discover a number of interesting new applications of the cataloged objects for quantum information protocols. These include improved methods for performing quantum computations by code deformation, a new four-qubit error-detecting code, as well as families of new quantum error-correcting codes we call stellated color codes, which encode logical qubits at the same distance as the next best color code, but using approximately half the number of physical qubits. To the best of our knowledge, our new topological codes have the highest encoding rate of local stabilizer codes with bounded-weight stabilizers in two dimensions. Finally, we show how the boundaries and twist defects of the color code are represented by multiple copies of other phases. Indeed, in addition to the well studied comparison between the color code and two copies of the surface code, we also compare the color code to two copies of the three-fermion model. In particular, we find that this analogy offers a very clear lens through which we can view the symmetries of the color code which gives rise to its multitude of domain walls.
Social and Cognitive Factors Driving Teamwork in Collaborative Learning Environments

A team is more than a group of people in the same space, physical or virtual. In recent years, increasing attention has been devoted to the social bases of cognition, taking into consideration how social processes in groups and teams affect performance. This article investigates when and how teams in collaborative learning environments engage in building and maintaining mutually shared cognition, leading to increased perceived performance. In doing so, this research looks for discourse practices managing the co-construction of mutually shared cognition and reveals conditions in the interpersonal context that contribute to engagement in these knowledge-building practices. A comprehensive theoretical framework was developed and tested. The constructs in the model were measured with the Team Learning Beliefs & Behaviors Questionnaire and analyzed using regression and path analysis methodology. Results showed that both interpersonal and sociocognitive processes have to be taken into account to understand the formation of mutually shared cognition, resulting in higher perceived team performance.
Toward Robust Deep RL via Better Benchmarks : Identifying Neglected Problem Dimensions

We consider a wider sense of reproducibility in practice for deep reinforcement learning on control tasks, where it holds promise as a general purpose solution. However, unlike other branches of machine learning, for practical reasons only simulation data is used in RL benchmarks. This puts greater responsibility on experiment design for advances on benchmarks to translate to real-world performance. There has been a string of successes with solving ever more impressive-looking problems in the Mujoco physics simulator. However, while involving control with different agent dynamics, there is reason to believe that these benchmarks are in other respects fairly homogeneous, e.g. having deterministic state transitions with quadratic objectives. For instance, [9] recently showed that many of them are solvable by a simple linear policy and suggest widening the initial state distribution to avoid fragile "trajectory-centric" policies. We take this further and argue that the environments themselves should have both an inherent uncertainty, and more complex objectives. Autonomous robots and vehicles have to deal with a complex uncertain world that changes over time. To exemplify this we introduce a seemingly simple benchmark where randomly moving obstacles have to be avoided. This both precludes a trajectory-centric solution and involves a more difficult objective than commonly used. We show that this toy example actually has higher sample complexity than the Mujoco benchmarks. We further find that the level of robustness expected of real-world autonomous agents leads to requirements on tail-end convergence that is rarely given much consideration in benchmarks, resulting in difficult tuning problems. While some environment variation has recently been shown for e.g. complex humanoid agents in Mujoco, with training times increasingly requiring massive cloud infrastructure, we finally suggest that such toy examples designed to test different problem dimensions have an important role to play in research.
Universal Fault-Tolerant Logical Gates with Constant Time Overhead for Quantum Computation

A fundamental question in the theory of quantum computation is to understand the ultimate space-time resource costs for performing a universal set of logical quantum gates to arbitrary precision. To date, all proposed schemes for implementing a universal logical gate set, such as magic state distillation or code switching, require a substantial space-time overhead, including a time overhead that necessarily diverges in the limit of vanishing logical error rate. Here we demonstrate that non-Abelian anyons in Turaev-Viro quantum error correcting codes can be moved over a distance of order the code distance by a constant depth local quantum circuit followed by a permutation of qubits. When applied to the Fibonacci surface code, our results imply the possibility of a universal fault-tolerant logical gate set with constant time overhead, including classical computational resources, and without increasing the asymptotic scaling of the space overhead. The resulting space-time overhead is optimal for topological codes with local syndromes. Our result reformulates the notion of anyon braiding as an effectively instantaneous process, rather than as an adiabatic, slow process.
Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach

Abstract. Polarimetric radar-based hydrometeor classification is the procedure of identifying different types of hydrometeors by exploiting polarimetric radar observations. The main drawback of the existing supervised classification methods, mostly based on fuzzy logic, is a significant dependency on a presumed electromagnetic behaviour of different hydrometeor types. Namely, the results of the classification largely rely upon the quality of scattering simulations. When it comes to the unsupervised approach, it lacks the constraints related to the hydrometeor microphysics. The idea of the proposed method is to compensate for these drawbacks by combining the two approaches in a way that microphysical hypotheses can, to a degree, adjust the content of the classes obtained statistically from the observations. This is done by means of an iterative approach, performed offline, which, in a statistical framework, examines clustered representative polarimetric observations by comparing them to the presumed polarimetric properties of each hydrometeor class. Aside from comparing, a routine alters the content of clusters by encouraging further statistical clustering in case of non-identification. By merging all identified clusters, the multi-dimensional polarimetric signatures of various hydrometeor types are obtained for each of the studied representative datasets, i.e. for each radar system of interest. These are depicted by sets of centroids which are then employed in operational labelling of different hydrometeors. The method has been applied on three C-band datasets, each acquired by different operational radar from the MeteoSwiss Rad4Alp network, as well as on two X-band datasets acquired by two research mobile radars. The results are discussed through a comparative analysis which includes a corresponding supervised and unsupervised approach, emphasising the operational potential of the proposed method.
Energetic Cluster-Surface Impact: Study of Crater and Hillock Formation

In the present work the design, advantages and capabilities of a newly constructed cluster implantation and deposition apparatus (CIDA) supplied by a pulsed cluster source (PUCLUS) from gaseous precursors is described. Small positively charged clusters (up to 150 atoms / 50 molecules) of Ar, N2 and O2 produced by the source and accelerated in the energy range from 3.0 keV up to 18 keV / cluster ion were used in the first experiments on implantation of pyrolytic graphite, indium-tin-oxide and silicon substrates. The irradiated samples were studied by atomic force microscope. As a result of energetic cluster impact, nanosize hillocks, formed in the middle of the craters, were found on the surfaces. The shape and size of these structures were studied depending on a number of experimental parameters, namely: cluster size, implantation energy, type of substrate and impact angle. A model explaining crater and hillock formation on target surfaces is discussed.
Distribution and Relative Quantification of Key Genes Involved in Fixed Nitrogen Loss from the Arabian Sea Oxygen Minimum Zone

The Arabian Sea (AS) oxygen minimum zone (OMZ) is one of the largest pelagic low-oxygen environments in the open ocean. It is responsible for the removal of up to 60 Tg of nitrogen annually, roughly an eighth of the global fixed nitrogen sink. Although denitrification has long been believed to be the major process responsible for fixed nitrogen loss from the oceans, recent studies show that anaerobic ammonium oxidation (anammox) is potentially a more important process involved. We have investigated the phylogeny of both anammox and denitrifying microbes in the AS, and here we report on their diversity in terms of their characteristic genes. Denitrifiers were targeted using nirS and nirK genes and anammox bacteria with the 16S rRNA gene. The nirK gene was amplified from all the samples, but nirS gene could only be detected when nitrite was present. The distribution of phylotypes was related to the concentration of nitrite and the apparent stage of denitrification. Most nirK or nirS genes from the AS had low identities with other published sequences. The closest identities were to sequences from other water column denitrifying environments rather than sedimentary or terrestrial environments. Phylogenetic analysis of the nirS and nirK genes revealed overall lower diversity than the very high diversities reported from estuarine and sedimentary environments. 16S rRNA partial gene sequences revealed very limited diversity among anammox sequences. All the anammox sequences were >98% identical to each other and were similar to sequences from other marine and water column environments, which are distantly related to Scalindua sp. Quantification using quantitative polymerase chain reaction assays showed that both nirS genes and anammox 16S rRNA genes were more abundant at depths with higher nitrite concentrations. The presence and abundance of genes indicative of both processes suggest that both canonical denitrification and anammox likely occur in the OMZ of the AS. However, the abundance of the nirS gene, one of the genes responsible for canonical denitrification, was an order of magnitude higher than the abundance of the anammox 16S gene, indicating that denitrifiers are numerically dominant in this environment. The greater diversity of nirS and nirK genes relative to anammox genes both among and within stations also suggests that the denitrifier assemblages are more dynamic in response to environmental conditions.
Factors Affecting Growth and Mortality Pattern of Tharpakar Calves at Organised Dairy Farm

The present study was conducted to estimate the factors affecting the growth and mortality pattern in Tharparkar calves at organised dairy farm. The 8 year 6 month data set was analysed for the effect of season of birth, sex and period of birth on body weight at 0, 90, 180 and 360 days as well as mortality pattern of calves in different seasons. The seasons of birth had significant effect (P<0.05) on body weight at 180 and 360 days. The body weight was significantly higher (P<0.05) during winter and rainy season as compared to autumn at six month of age. The effect of sex was also significant (P<0.05) on body weight, where male calves were significantly (P<0.05) heavier as compared to females at 180 and 360 days. The birth weight was significantly (P<0.01) affected across the period of study. The calves with lesser birth weight led to higher mortality in rainy season (44.44%) as compared summer (19.23 %). The study revealed that winter and summer born calves has better growth and survivability under organised farming conditions.
Quantum simulation of partially distinguishable boson sampling

Boson Sampling is the problem of sampling from the same output probability distribution as a collection of indistinguishable single photons input into a linear interferometer. It has been shown that, subject to certain computational complexity conjectures, in general the problem is difficult to solve classically, motivating optical experiments aimed at demonstrating quantum computational "supremacy". There are a number of challenges faced by such experiments, including the generation of indistinguishable single photons. We provide a quantum circuit that simulates bosonic sampling with arbitrarily distinguishable particles. This makes clear how distinguishabililty leads to decoherence in the standard quantum circuit model, allowing insight to be gained. At the heart of the circuit is the quantum Schur transform, which follows from a representation theoretic approach to the physics of distinguishable particles in first quantisation. The techniques are quite general and have application beyond boson sampling.