Miracle-dz/UniFAR-FTUs huggingface dataset:
Existence of Z-Cyclic Triplewhist Tournaments for a Prime Number of Players

A Z-cyclic triplewhist tournament for 4n+1 players, or briefly a TWh(4n+1), is equivalent to a n-set {(ai, bi, ci, di) | i=1,? ,n} of quadruples partitioning Z4n+1? {0} with the property that ? ni=1{±(ai? ci), ±(bi? di)}=? ni=1{±(ai? bi), ±(ci? di)}=? ni=1{±(ai? di), ±(bi? ci)}=Z4n+1? {0}. The existence problem for Z-cyclic TWh(p)'s with p a prime has been solved for p? 1 (mod16). I. Anderson et al. (1995, Discrete Math.138, 31? 41) treated the case of p? 5 (mod8) while Y. S. Liaw (1996, J. Combin. Des.4, 219? 233) and G. McNay (1996, Utilitas Math.49, 191? 201) treated the case of p? 9 (mod16). In this paper, besides giving easier proofs of these authors' results, we solve the problem also for primes p? 1 (mod 16). The final result is the existence of a Z-cyclic TWh(v) for any v whose prime factors are all? 1 (mod4) and distinct from 5, 13, and 17.
Energy efficient Firmware Over The Air Update for TinyML models in LoRaWAN agricultural networks

Current agricultural practices fail to feed everyone correctly while being harmful to the environment and highly sensitive to climate change. Therefore, new and modern agriculture needs to be developed and overcome numerous challenges. Artificial Intelligence (AI) is one of the tools widely used in this new type of Agriculture called Precision Agriculture (PA) or Smart Farming (SF). Thanks to the Internet of Things (IoT) technologies, AI algorithms are fed with a vast amount of data to provide valuable insights for farmers, such as weather prediction, pest development detection, irrigation management, etc. AI algorithms are often executed in cloud servers, thus requiring IoT devices to offload their data to process. This creates privacy, latency, and security issues, but mostly, it requires a large quantity of energy for transmission. To overcome those issues, recent research brought new tools like Tiny Machine Learning (TinyML) to perform AI directly on the IoT devices and break free from the cloud. Despite promising results, such Smart devices cannot train new models on their constrained hardware and therefore need frequent updating to increase the model's accuracy over time, regarding the specific environment where the sensor is deployed. In the Agricultural domain, sensor devices are numerous and usually spread over vast geographical areas while running on battery. For this reason, Farms Wireless Sensor Network (WSN) use mostly Low Power Wide Area Network like LoRaWAN to communicate. Therefore Firmware Update Over the Air (FUOTA) is required. In this context, this paper proposes a study of the FUOTA process for a TinyML model using LoRaWAN in a specific agricultural scenario. A TinyML sensor prototype was built to evaluate the feasibility of FUOTA for tinyML devices using LoRaWAN. The system's energy consumption and Packet delivery ratio are then analyzed in a simulator with different network scenarios.
Book review

The study of human psychological development faces some of the most fascinating scientific problems of our day. It is through psychological development that our cognitive and linguistic skills arise. From contingency and statistical learning, early social smiling, joint attention and word learning, and onwards to theory of mind and more sophistication in language, children develop psychologically in their emotional, social and physical environments. Elucidating the mechanisms and processes underlying these developments is no small endeavour. It seems very likely that adequate understanding of psychological development will require extensive interdisciplinary collaboration. Plunkett (2005) suggested that the space of hypotheses available from conceptual theorizing and empirical study in this area might be too massive to narrow the scientific investigations. To narrow the hypothesis space, other constraints are needed. It is no surprise then that computational modelling, providing one form of constraint, is becoming conventional in developmental psychology (e.g. Elman et al. 1996, Plunkett et al. 1997, chapter 3 of Harris and Butterworth 2002, Shultz 2003, Parisi and Schlesinger 2004). Psychology, while having a rich corpus of empirical data, does not often include forms of deductive reasoning which allow inferences based on systems of mathematical or logical premises. Statistical inference, used in many psychological investigations, allows for inductive reasoning—but these inferences are not assured to be true. Modelling fulfils such a need, allowing for conclusions to be drawn based on ‘what if’ scenarios. What if a child had these types of environmental conditions, this mechanism for perceptual capacities, and that process for category learning? Given sufficient specificity, a model can be constructed to study the effects of the interaction of the hypothesized ‘what if’ environmental conditions and skills. Connectionist models, the general type of modelling addressed in the book, provide rough analogues of the neural systems in biological organisms, and are seen by some as a potential basis for ‘a general theory of development’ (Thelen and Bates 2003: 378). The book contains an introduction by the editor, Philip Quinlan, 11 chapters, and author and subject indices. Being methodologically oriented around the topic of connectionist modeling, it is perhaps not surprising that the range of approaches in the individual chapters varies considerably, as do the questions asked. Often, the chapters present summaries of previously published works, but
Ghana’s National Health Insurance Scheme: An Ordinal Probit Valuation of Willingness to Pay Higher Premiums for Improved Services

The importance of improved healthcare services under Ghana’s National Health Insurance Scheme (NHIS) is nationwide admitted. However, service improvement for insurance schemes comes with extra cost. To fill the funding gap, insurance schemes typically charge enhanced premiums. This requires clients’ approval and cooperation to implement. For this reason, this study was conducted to assess Ghana’s NHIS subscribers’ willingness to pay (WTP) enhanced premiums for improved services. Some socio-economic and demographic factors were used as covariates. WTP, being the dependent variable, was categorized into high WTP, moderate WTP, low WTP, and no WTP enhanced premiums. The likelihood of a client falling in a particular WTP category was examined using the Cumulative Ordinal Probit (COP) regression model. A likelihood ratio chi-square of 58.82 with p < 0.000 shows that the model was statistically significant, and fit for prediction. Results showed that age-groups 18-30, 30–45, unemployed, tertiary education, and level of income significantly influenced WTP. Predictions showed that for any average national health insurance user, the probability of being in high WTP, moderate WTP, low WTP and no WTP premium are respectively 0.51, 0.27, 0.11 and 0.12. Based on the results of this study, we recommend that Ghana’s NHIS should institute a progressive premium regime in order to cater for the different needs and financial abilities of clients, thus helping to fill the funding gap.
Sylvester-type quaternion matrix equations with arbitrary equations and arbitrary unknowns

In this paper, we prove a conjecture which was presented in a recent paper [Linear Algebra Appl. 2016; 496: 549--593]. We derive some practical necessary and sufficient conditions for the existence of a solution to a system of coupled two-sided Sylvester-type quaternion matrix equations with arbitrary equations and arbitrary unknowns $A_{i}X_{i}B_{i}+C_{i}X_{i+1}D_{i}=E_{i},~i=\overline{1,k}$. As an application, we give some practical necessary and sufficient conditions for the existence of an $\eta$-Hermitian solution to the system of quaternion matrix equations $A_{i}X_{i}A^{\eta*}_{i}+C_{i}X_{i+1}C^{\eta*}_{i}=E_{i}$ in terms of ranks, $~i=\overline{1,k}$.
Comparison of Design Parameters for Packet Optimized BASN Routing Schemes in terms of Bio-Medical Sensor Nodes

WBANs are used to monitor various parameters in mass applications and consider a key building block for the coming generation network. WBAN sensors face various issues like unreliable data delivery and energy depletion due to weak communication and unpredictable body movements. Hence, a consistent and maintainable communication of collected information from sensors to a monitoring hospital is extremely challenging. Thus, a more reliable data transmission mechanism is strongly desired for the optimization of available resources and overcome network reliability and instability issues in WBANs. Many routing schemes have been developed for BASNs but very less of them have considered packet optimization which is an important factor to be considered as design parameter. In this research, we have compared 4 different WBAN routing schemes versus deployed bio-medical sensor nodes. Four routing protocols are selected for packet optimization comparison namely: BTTA, iBTTA, LAEEBA and Co-CEStat for the same parameters settings.
Growth performance and economic appraisal of phase feeding at different stocking densities in sexed broilers.

The present study was undertaken to examine the growth performance and economic efficiency involving 1440 sexed broilers (720 of each sex), maintained in environmentally controlled broiler house under litter floor subjected to four different levels of phase-feeding at three different stocking densities (0.7, 0.6, 0.5 sq.ft). The birds in group- A were offered diet with 19% crude protein (CP) throughout the grow-out period of 42 days. Those in group-B were allotted broiler starter diet with 20% CP up to 28 days of age and then broiler finisher diet with 17% CP up to 42 days of age. The diet for birds in group-C was split into 03 phases i.e. 0-10, 11-26, 27-42 days furnishing with 21, 19 and 18 % CP, respectively. The birds in group D were maintained on 4 phase feeding regimes i.e. 0-10, 11-20, 21-34, 35-42 days, with CP levels of 21, 20, 18 and 17%, respectively. Weekly data on growth performance parameters were recorded and were analyzed using Completely Randomized Nested Design. The comparison of means was made using DMR test. The results revealed that birds maintained at 0.7 sq. ft. stocking density exhibited significantly (P<0.05) better body weight, FCR, uniformity, point spread and point index, while, significantly highest feed intake, body weight and improved FCR was recorded in 4-phase feeding program as compared to single, two and three phase feeding pattern but sex did not significantly influence these parameters. Higher profit was achieved in four phase feeding program at 0.7 sq. ft. stocking density.
Taxonomic level, trophic biology and the regulation of local abundance

1 Taxocenes — monophyletic ecological assemblages — are a key focus of macroecology. Abundance (individuals per area) is a basic property of taxocenes but has received less attention than diversity, although the two are probably related. Abundance reflects a taxocene’s ability to harvest and sequester available energy and divide it among individuals. This paper explores how two properties of all taxocenes — trophic makeup and taxonomic level (e.g. genus, tribe, subfamily, family … ) — may contribute to patterns of local abundance at geographical scales. 2 Forty-nine ground ant taxocenes, in habitats ranging from New World deserts to rain forests, were surveyed along a three-orders of magnitude productivity gradient using transects of 30 1-m2 quadrats at each site. Abundance — the number of nests per transect — varied over two orders of magnitude. 3 Over 80% of the genera collected were omnivores. However, herbivore, omnivore, and predator taxa were added to ant taxocenes in roughly 1 order of magnitude steps up the productivity gradient. Specialist detritivores were added last. 4 Net primary productivity and mean monthly temperature both consistently entered regression models predicting abundance. However, while productivity was the dominant predictor of abundance for higher taxa (families, subfamilies), temperature was the dominant predictor of abundance for lower taxa (tribes, genera). The answer to the question ‘What regulates the abundance of a taxocene? ’ is thus sensitive to the taxonomic level of analysis. 5 These data support the following scenario. Lower taxa are abiotic specialists given the insufficient number of genomes and generations required for the exploration of the entire abiotic envelope. Higher taxa, in contrast, consist of suites of abiotic specialists arrayed along the entire productivity gradient, with access to productivity everywhere the taxon occurs. If this scenario is true, individual species may respond to global changes in temperature; the higher taxa they belong to may most respond to global changes in productivity.
Transport of water against its concentration gradient: fact or fiction?

Water transport across cell membranes is central to most physiological functions. About 200 L of water move across epithelial cells each day in humans in order to maintain whole-body homeostasis; water transport in and out of organs such as the brain and eye are of major clinical importance. It is well established that the water transport is driven by ion transport, but how? Osmosis is not always the answer: water can be transported against considerable osmotic gradients, apparently without any external osmotic or hydrostatic driving forces. It is generally accepted that cotransporters of the symport type play a key role for the coupling between ion and water fluxes. Models of coupling are either molecular or based on unstirred layer effects, and can be distinguished by their response time: for molecular models, water transport follows changes of substrate transport instantaneously; in unstirred layer models there is a delay while the osmolarity changes in the solutions surrounding the cotransport protein. For cotransporters expressed heterologously in Xenopus oocytes, influx of water can be detected about 1 second after initiation of cotransport of ions and other substrates. This is 20 times faster than expected (and observed) for unstirred layer effects. Water transport in cotransporters is best explained by a molecular model in which ion and water fluxes are coupled by a mechanism within the protein. This would also clarify how cotransporters exploit the free energy in the ion fluxes for the uphill transport of water. WIREs Membr Transp Signal 2012, 1:373–381. doi: 10.1002/wmts.54 For further resources related to this article, please visit the WIREs website.
Archetypal landscapes for deep neural networks

Significance Deep neural networks have reached impressive predictive capability for many challenging tasks, yet it remains unclear why they work. Training neural networks involves minimizing a complex, high-dimensional, nonconvex loss function, yet, empirically, it proves possible to produce useful models without rigorous global optimization. To provide insight into this observation, we analyze the structure of the loss-function landscape of deep neural networks and show that it features either a single funnel or low barriers between minima. Such landscapes are relatively easy to optimize and are qualitatively different from the energy landscape of a structural glass. More generally, our results demonstrate how the methodology developed for exploring molecular energy landscapes can be exploited to extend our understanding of machine learning. The predictive capabilities of deep neural networks (DNNs) continue to evolve to increasingly impressive levels. However, it is still unclear how training procedures for DNNs succeed in finding parameters that produce good results for such high-dimensional and nonconvex loss functions. In particular, we wish to understand why simple optimization schemes, such as stochastic gradient descent, do not end up trapped in local minima with high loss values that would not yield useful predictions. We explain the optimizability of DNNs by characterizing the local minima and transition states of the loss-function landscape (LFL) along with their connectivity. We show that the LFL of a DNN in the shallow network or data-abundant limit is funneled, and thus easy to optimize. Crucially, in the opposite low-data/deep limit, although the number of minima increases, the landscape is characterized by many minima with similar loss values separated by low barriers. This organization is different from the hierarchical landscapes of structural glass formers and explains why minimization procedures commonly employed by the machine-learning community can navigate the LFL successfully and reach low-lying solutions.
RSS-based LTE Base Station Localization Using Single Receiver in Environment with Unknown Path-Loss Exponent

With the increasing demand for location-based services, localization technology research has recently intensified. Received signal strength (RSS)-based localization has the advantage of simplicity. However, as RSS-based localization requires the path-loss model parameters, it is difficult to use in place on which those parameters are unknown. In prior research, a transmitter localization algorithm with multiple stationary receivers was proposed for use under unknown path-loss exponent (PLE) conditions. However, if a mobile receiver is utilized, the localization would be possible with a single receiver alone. In this paper, we suggest a method of RSS-based LTE base station (BS) localization with a single mobile receiver when the PLE is unknown. We also propose an efficient mobile-receiver movement method to improve the PLE estimation and BS localization accuracy. Simulation results demonstrate the performance of the proposed methods.
Solving large-scale PDE-constrained Bayesian inverse problems with Riemann manifold Hamiltonian Monte Carlo

We consider the Riemann manifold Hamiltonian Monte Carlo (RMHMC) method for solving statistical inverse problems governed by partial differential equations (PDEs). The Bayesian framework is employed to cast the inverse problem into the task of statistical inference whose solution is the posterior distribution in infinite dimensional parameter space conditional upon observation data and Gaussian prior measure. We discretize both the likelihood and the prior using the H1-conforming finite element method together with a matrix transfer technique. The power of the RMHMC method is that it exploits the geometric structure induced by the PDE constraints of the underlying inverse problem. Consequently, each RMHMC posterior sample is almost uncorrelated/independent from the others providing statistically efficient Markov chain simulation. However this statistical efficiency comes at a computational cost. This motivates us to consider computationally more efficient strategies for RMHMC. At the heart of our construction is the fact that for Gaussian error structures the Fisher information matrix coincides with the Gauss–Newton Hessian. We exploit this fact in considering a computationally simplified RMHMC method combining state-of-the-art adjoint techniques and the superiority of the RMHMC method. Specifically, we first form the Gauss–Newton Hessian at the maximum a posteriori point and then use it as a fixed constant metric tensor throughout RMHMC simulation. This eliminates the need for the computationally costly differential geometric Christoffel symbols, which in turn greatly reduces computational effort at a corresponding loss of sampling efficiency. We further reduce the cost of forming the Fisher information matrix by using a low rank approximation via a randomized singular value decomposition technique. This is efficient since a small number of Hessian-vector products are required. The Hessian-vector product in turn requires only two extra PDE solves using the adjoint technique. Various numerical results up to 1025 parameters are presented to demonstrate the ability of the RMHMC method in exploring the geometric structure of the problem to propose (almost) uncorrelated/independent samples that are far away from each other, and yet the acceptance rate is almost unity. The results also suggest that for the PDE models considered the proposed fixed metric RMHMC can attain almost as high a quality performance as the original RMHMC, i.e. generating (almost) uncorrelated/independent samples, while being two orders of magnitude less computationally expensive.
An Overview of Fluoroquinolones

The fluoroquinolones are broad-spectrum bactericidal agents inhibiting DNA synthesis. They are active against gram positive and gram negative organisms like P. aeruginosa, Mycoplasma, Chlamydia, Staphylococciand a few of theStreptococci.They are useful in the treatment of pneumonia, urinary tract infections, bacterial diarrhea, and skin and soft tissue infections. The use of quinolones began with its first generation that consisted of nalidixic acid . From that time, a large number of newer fluoroquinolones having a variety of structures and a broader spectrum of activity have been developed forming the five generations. The more number of fluoroquinolones develo ped and its widespread usage is attributed to its high bioavailability and tissue penetration. Moreover, the development of resistance to the most commonly used antibiotics has led to the need for alternatives. The various derivatives of fluoroquinolone ha ve varying levels of activity depending on the various groups attached at different positions. Generating a derivative with increased activity will help to reduce the Minimum Inhibitory Concentration (MIC), thereby reducing the possibility of developing re sistance to it. This paper gives an overview of fluoroquinolones, their mechanism of action, their uses, resistance development and their adverse effects.
Management Accounting Practices and the Performance of Small and Medium-Sized Enterprises in Akwa Ibom State, Nigeria

Purpose: The study was designed to examine the effect of Management Accounting Practices (MAPs) on the performance on Small and Medium Scale Enterprises (SMEs) in Nigeria. Method: The survey research design approach was employed using a structured questionnaire to gather data from 40 purposively selected SMEs operators for the population pool. Data were analyzed using descriptive and inferential statistical tools using SPSS version 20. Result: Results showed a strong positive correlation between the dependent variable (firm performance) and independent variables (Costing System, Budgeting System, Performance Evaluation System, Decision Support System, and Strategy Management Accounting System). Implications: The study recommends that the SMEs should avail themselves more with contemporary MAPs to ensure the profitability and sustainability of the businesses.
Structure and Hardness of the Sputtered Al-Cu Thin Films System

The phase diagram of magnetron sputter-deposited Al-Cu thin films is simpler than the equilibrium diagram. Above 86.17 at. %Cu, the films are single ? Cu phase. Below, the microstructure consists of a mixture of the solid solution ? Al phase and an intermetallic compound phase, the previous ? (Al2Cu) phase for the 1.8 to 45.99 at. %Cu films and an unexpected (Cu3Al) phase for 49.07 to 66.64 at. %Cu films. We note the appearance of a phase separation (? Al + ? Cu + Cu3 Al) in 66.64 at. %Cu films. The microhardness and the young modulus of the sputtered films increase regularly with Cu concentration reaching a maximum (H ? 8000 MPa and E ? 200 GPa). This phenomenon of strengthening of aluminium by means of copper is essentially due to a combination of solid solution effects and grain size refinement.