jimnoneill/paper-to-field-training huggingface dataset:
An Approach to Modeling and Analyzing Reliability for Microservice‐Oriented Cloud Applications

Field: Computer Science (Physical Sciences)

Microservice architecture is a cloud‐native architectural style, which has attracted extensive attention from the scientific research and industry communities to benefit independent development and deployment. However, due to the complexity of cloud‐based platforms, the design of fault‐tolerant strategies for microservice‐oriented cloud applications becomes challenging. In order to improve the quality of service, it is essential to focus on the microservice with more criticality and maximize the reliability of the entire cloud application. This paper studies the modeling and analysis of service reliability in the cloud environment. Firstly, a formal description language is defined to model microservice, user request, and container accurately. Secondly, the reliability analysis is conducted to measure a critical microservice’s fluctuation and vibration attributes within a period, and the related properties of the constructed model are analyzed. Thirdly, a fault‐tolerant strategy with redundancy operation has been proposed to optimize cloud application reliability. Finally, the effectiveness of the method is verified by experiments. The simulation results show that the algorithm obtains the maximum benefits and has high performance through several experiments.
Metaverse gaming: analyzing the impact of self-expression, achievement, social interaction, violence, and difficulty

Field: Psychology (Social Sciences)

In the burgeoning landscape of metaverse gaming, understanding player behaviour and preferences is crucial for both academic and practical applications. This study delves into the dynamic realm of metaverse gaming, exploring the influence of various factors on user satisfaction and continuance intention. The primary purpose was to examine the roles of self-expression, challenge and achievement, social interaction, violence catharsis, and game difficulty in shaping player experiences in the metaverse. Employing Partial Least Squares Structural Equation Modeling (PLS-SEM) as the analytical method, the study analysed responses from 171 metaverse game users. The findings revealed intriguing patterns: while self-expression significantly impacts continuance intention, it does not affect immediate satisfaction. Challenge and achievement enhance satisfaction but not continuance intention, emphasizing the complex relationship between these constructs. Social interaction emerged as a critical factor positively influencing both satisfaction and continuance intention. Contrary to popular belief, violence catharsis did not significantly affect either satisfaction or continuance intention. Additionally, increased game difficulty was found to negatively impact both satisfaction and continuance intention. Satisfaction was shown to drive continuance intention. These insights bear significant implications for game developers and marketers, highlighting the need for nuanced game design strategies that emphasize social interaction and balanced challenges.
Introduction

Field: Arts and Humanities (Social Sciences)

(Neo)colonialism, anti-Black and Brown racism and patriarchy, especially at their intersection, have been selected as dimensions of a conceptual space within which to interrogate the scholarship in Sociolinguistics and to draw attention to the consequences of this scholarship. In this volume, we propose a counter-hegemonic Sociolinguistics from/of/with the South. One of the objectives of this project is to contribute to a form of scholarship in which “vertical universalism” (also known as imperial universalism) is replaced with “horizontal universalism,” which, by design, is expansive and non-exclusive (Bhambra & Holmwood, 2021; Diagne, 2020).
A PoP structure to support I/O over 2000

Field: Engineering (Physical Sciences)

The rapid growth of smartphones and tablets in mobile market demands the packaging technology to be in a thinner profile with small form factor and reduce power consumption. The PoP structure is widely used in the package of smart phones to connect memory and Application Processor. Even if TSV is the preferred structure for connecting memory and AP, the high cost of TSV process prohibit TSV for wide presence in the smart phone applications. Recently, I/Os of memory are required to increase from a few hundreds to more than 1000. For wide I/O2, I/Os more than 2000 may be required. We have demonstrated PoP connections over 1000 with pitch of 200 um in last year's ECTC conference with Unimicron HCP (High Copper Pillar) technology [1]. In preparation to meet future memory requirement and to evaluate the extendibility of Unimicron proposed HCP structure, a test vehicle has been built. The test vehicle consists of a PoP structure with a fine pitch of 100 μm that can support 2472 I/Os in 6 rows around the peripheral area of the die. The package size is in a 12×12 mm 2 CSP format. The target copper pillar height is 80 μm. The copper pillars with a designed diameter of 70 μm and space of 30 μm. The uniformity of copper pillar height is required to assure the reliable interconnections between the top memory die and the bottom AP. For a designed copper pillar height of 80 μm, tolerance of +/-15 μm is required. In this paper, a method to achieve the copper height uniformity of +/- 15 μm with 100 μm PoP pitch connection will be demonstrated.
Clinical significance of monitoring plasma levels of antipsychotics in the outpatients with schizophrenia

Field: Medicine (Health Sciences)

Objective The goal of this study was to explore the relationship between compliance and plasma levels of antipsychotics in the outpatients with schizophrenia Methods The compliance was assessed in 718 outpatients with schizophrenia who took one of those antipsychotics (chlorpromazine, perphenazine, clozapine or haloperidol) The plasma levels of antipsychotics in these patients were measured after two weeks and three months of treatment Results The compliance of patients who took clozapine or perphenazine was better than that who took chlorpromazine or haloperidol The rates of non compliance were as following: 5 4%, 10 5%, 19 5%, and 21 1% When the patients took similar doses of those antipsychotics (chlorpromazine, perphenazine or clozapine), the plasma levels of antipsychotics in complete compliance patients [chlorpromazine (380±120) μg/L ,perphenazine (248±152) μg/L,and clozapine (358±119) μg/L, respectively] were higher than that in incomplete compliance patients [(325±109)μg/L,(209±148)μg/L,and(317±111)μg/L, respectively] and non compliance patients [(264±103)μg/L,(123±117)μg/L,and(255±126)μg/L, respectively] The plasma levels of antipsychotics in incomplete compliance patients were higher than that in non compliance patients ( P 0 05～ 0 01) Furthermore, the significant correlation between doses and plasma levels of antipsychotics in the patients who took chlorpromazine, perphenazine and clozapine but not of haloperidol was found in the complete compliance patients ( P 0 05) Conclusion It is helpful to discriminate the compliance of patients with schizophrenia by monitoring their plasma levels of antipsychotics
Double diffusion encoded MRI to identify Alzheimer’s disease pathology in postmortem brainstem by Diffusion Tensor Subspace Imaging (DiTSI)

Field: Medicine (Health Sciences)

Motivation: Diffusion MRI may provide clinically relevant markers of degenerative pathology in Alzheimer's disease if the specificity of the frameworks can be improved. Double diffusion encoding frameworks are promising for their improved selectivity. Goal(s): Optimization of methods and initial description of alterations in postmortem brainstem imaging with diffusion MRI including single diffusion frameworks of DTI and MAP-MRI as well as the DDE DiTSI framework. Approach: High-resolution, high-quality diffusion MRI scans over a comprehensive encoding range were used to map metric in healthy and AD pathologic brain stem tissue Results: Four anisotropy metrics across the three frameworks were different in contrast and alteration with pathology. Impact: If double diffusion encoding MRI can be optimized for the detection of specific pathology in Alzheimer's disease and other brain disorders, a new class of improved imaging markers may be possible.
Bilateral Orbital Varices Associated With Habitual Bending

Field: Medicine (Health Sciences)

Orbital varices are uncommon lesions that usually are caused by congenital venous malformations and that are manifested by intermittent proptosis induced by changes in venous pressure. Maneuvers such as coughing, straining, forced expiration, bending forward, and Valsalva's maneuver can accentuate an orbital varix, which then can be confirmed by radiologic studies. Scanning techniques with Valsalva's maneuver can illustrate enlargement of the varix to confirm the diagnosis.1 We describe a yoga instructor who presented with complaints of unilateral intermittent proptosis and whose magnetic resonance imaging (MRI) scan illustrated an indeterminate unilateral lesion. The computed tomographic (CT) scan with Valsalva's maneuver demonstrated enlargement of an orbital varix on both the symptomatic and the opposite side.

Report of a Case.

A 62-year-old woman in excellent health had a 4-day history of intermittent, painless proptosis, which was accentuated when she bent forward. She had no visual complaints. Symptoms started about 1 year previously,
Miracle arguments and the demise of strong predictivism

Field: Arts and Humanities (Social Sciences)

Once again, let us begin with the fantasy of you suddenly becoming rich, and seeking financial advice. You choose an advisor with a long string of successful predictions about which investments will be successful over another who can merely accommodate the data with his theory. The successful predictions testify to the greater credibility of the predictor, you say. But how confident should you be that the predictor's theory is actually true? Could the predictor, say, have a false account of the causes of market fluctuations which for some reason happens to systematically generate true predictions? In this chapter we consider the role of predictive success in arguing for the truth of theory.
corner-cube absolute gravimeters sense the effects of Special Relativity?” arXiv:1205.5084

Field: Physics and Astronomy (Physical Sciences)

Abstract. Relativistic treatment of the finite speed of light correction in absolute gravimeters, as evolved by Rothleitner and Francis in Metrologia 2011, 48 442-445, following the initial publication in Metrologia 2011, 48 187-195, leads to spurious conclusions. The double Doppler shift implemented in the gravimeters obliterates the difference between its relativistic and non-relativistic formulation. Optical heterodyning used in Michelson-type interferometers makes the quadratic Lorenz-like term of the double Doppler shift discernable against the linear term, while in relativistic experiments the quadratic term has to be detected against the unit. The disturbance of the registered trajectory caused by the finite speed of light includes tracking signal delay as intrinsic part not reducible to the Doppler shifts. ar X iv
ChemInform Abstract: Iridoid Glycosides from Lagotis alutacea.

Field: Biochemistry, Genetics and Molecular Biology (Life Sciences)

Abstract The new iridoid glycoside, lagotisoside F (I), and three known analogs are isolated and evaluated for their cytotoxic activities against HL‐60, MCF‐7, A549, SW480, and SMMC‐7721 cells.
Short term implicit memory in lexical processing

Field: Psychology (Social Sciences)

A single recent presentation of an item can lead to substantial improvementin speed or accuracy of processing when that item is presented subsequently, a phenomenon referred to as repetition priming. This empirical finding has been considered within two general frameworks. The first can be termed a "perceptual" approach, in which the perception of the target occurs more easily due to a transient change in the state of the target's internal representation. The second can be termed a "memory" approach, in which priming is seen as an example of implicit memory, that is, as arising from subconscious, nondeliberate access to a trace of an earlier event. This thesis examined repetition priming for words and nonwords from both perspectives. A review of priming within a word recognition framework suggested that transient modifications of lexical representations might be able to endure for several seconds, allowing a short-lived priming effect for words and word-like nonwords. A review of priming within a memory framework suggested that there might exist a short-lived implicit memory form, with a duration similar to that of explicit working memory. Empirical work examined priming over short lags (generally 0-23 items intervening between repeats) using lexical decision and speeded naming tasks. A novel short-lived repetition effect was apparent, superimposed on standard long-lived priming. For words, this effect endured until lag 3 (8 seconds). More rapid decay was apparent for nonwords, producing a lag x lexicality interaction. Short term priming was distinguished from long term priming on the basis of decay rate, the effects of word frequency, and the effects of the proportion of repeated items in the list. Short term priming was distinguished from explicit working memory on the basis of the effects of lexical status and overall differences in speed and accuracy. Finally, short term priming was shown to decay through the effects of both spontaneous trace loss and interference. The effect of interference on nonword priming was particularly severe, and the relative effects of interference were shown to be responsible for the form of the lag x lexicality interaction. The results are interpreted as showing that a) short term priming reflects the operation of a novel memory form, namely, short term implicit memory, (b) this memory arises {for lexical items) within the perceptual system responsible for word recognition, possibly through transient modification of orthographic representations, and (c) the word recognition system therefore retains a number of partially-active words simultaneously. It is suggested that short term implicit memory might exist to allow the integration of successively­ presented stimuli across a short time window of perceptual processing.
Asymptotic theory of generalized information criterion for geostatistical regression model selection

Field: Mathematics (Physical Sciences)

Information criteria, such as Akaike's information criterion and Bayesian\ninformation criterion are often applied in model selection. However, their\nasymptotic behaviors for selecting geostatistical regression models have not\nbeen well studied, particularly under the fixed domain asymptotic framework\nwith more and more data observed in a bounded fixed region. In this article, we\nstudy the generalized information criterion (GIC) for selecting geostatistical\nregression models under a more general mixed domain asymptotic framework. Via\nuniform convergence developments of some statistics, we establish the selection\nconsistency and the asymptotic loss efficiency of GIC under some regularity\nconditions, regardless of whether the covariance model is correctly or wrongly\nspecified. We further provide specific examples with different types of\nexplanatory variables that satisfy the conditions. For example, in some\nsituations, GIC is selection consistent, even when some spatial covariance\nparameters cannot be estimated consistently. On the other hand, GIC fails to\nselect the true polynomial order consistently under the fixed domain asymptotic\nframework. Moreover, the growth rate of the domain and the degree of smoothness\nof candidate regressors in space are shown to play key roles for model\nselection.\n
Mass spectrometry of and standard enthalpies of formation of gaseous sodium tetrachloroaluminate and its dimer

Field: Chemistry (Physical Sciences)

Knudsen cell mass spectrometry was performed on vapors from a sample containing NaAlCl4(l) and NaCl(s) at an average temperature of 500 K. The vapor was analyzed using electron bombardment with 50 eV electrons. Several ions were detected which permitted the conclusion that the vapor consisted of AlCl3, Al2Cl6, NaAlCl4, and Na2Al2Cl8. Ion intensities were determined as a function of the temperature of the vapor in the Knudsen cell. Data were treated thermodynamically using the van’t Hoff equation. Statistical mechanical calculations were performed for NaAlCl4(g). The data yielded the following thermodynamic data: standard enthalpy of formation at 500 K of NaAlCl4(g), −997.8±6.0 kJ/mol; standard enthalpy of formation at 298.15 K of NaAlCl4(g), −994.8±8.0 kJ/mol; standard enthalpy of formation at 500 K of Na2Al2Cl8(g), −2174.7±8.0 kJ/mol.
3D Printing of Objects with Bulk Superhydrophobicity Using Self-Foaming Polydimethylsiloxane-Based Ink

Field: Materials Science (Physical Sciences)

Although bulk superhydrophobic material can maintain durable superhydrophobicity by its micro-nanostructure regeneration for promising application, the 3D printing is still challenging due to the requirement of a large amount of solvent and complicated fabrication processing. Herein, a solvent-free and self-foaming polydimethylsiloxane (PDMS)-based ink is developed for 3D printing bulk superhydrophobic objects. The ink incorporates thermally expandable microspheres (EMs) and polytetrafluoroethylene (PTFE) particles, enabling hierarchical roughness and low surface energy throughout the bulk. During thermal curing, EMs generate cellular pores (20-50 μm) and disrupt the formation of a dense skin layer in the cured PDMS ink, while PTFE particles migrate to the surface, achieving a Cassie-state superhydrophobicity with a water contact angle of 155° and a sliding angle of 9°. The printed foam exhibits exceptional durability, retaining superhydrophobicity after 1000 abrasion cycles due to self-similar porous structures. Rheological optimization ensures printability, and the lightweight foam (density of 0.16 g/cm3) demonstrates versatile applications, including waterproofing, oil-water separation, and waterproof buoyancy carrier for a drone (supporting 7× its weight). This work presents an environmentally benign and facile strategy for fabricating robust, bulk superhydrophobic materials with scalable 3D printing, advancing their potential in sustainable industrial and environmental applications.
Brain computer interface for analyzing emotions

Field: Computer Science (Physical Sciences)

Emotion is the subjective experience that reflects our mental states and can significantly affect our cognitive function and action tendencies. With the advances in artificial intelligence (AI) and brain-computer interface (BCI) technologies, the ability for computer applications to recognize human emotions can provide us more intelligent services, such as style-adjusting e-learning system , driver's fatigue detection, e-healthcare assistance, etc. To recognize human emotions using machines, scientists studied many different sources of signal. Literature shows that electroencephalograph (EEG) demonstrates promising characteristics in revealing high level brain activities, and its correlation with emotions is also profound. This made EEG-based emotion recognition a hot research area under BCI. However, the majority approaches have problems in achieving reliable recognition accuracies. Specifically, we face the following challenges: (i) the features extracted from EEG may not be good enough for recognizing emotional activities; (ii) EEG signal is extremely susceptible to noise and artifact interference, which may affect the recognition accuracy; and (iii) increasing feature dimension may enhance the recognition accuracy, but as a cost, the whole process will incur much more computation time. In this project, I investigated different features extraction methods from the literature and explored different techniques to process those features. I also compared the classification performance on different classifiers. To address the three challenges aforementioned, I propose a fast and robust EEG-based emotion recognition model that applies feature smoothing on a set of statistical features extracted from the raw EEG signals. I performed experiments on benchmarks affective EEG datasets and obtained convincing experimental results. The main contributions of this project are listed as follows. Firstly, I had a comprehensive study on related work, and identified the features that are suitable for emotion recognition and computationally simple to extract. Secondly, I propose a novel feature smoothing method that can enhance the quality of features and provided the theoretical proof on the effectiveness of this method. Lastly, the EEG-based emotion recognition model I proposed outperforms prior studies on benchmark affective EEG datasets. Compared to other studies on the DEAP and SEED datasets, my method kept the shortest processing time for features and achieved the highest classification accuracy.
Emergence of Zoonotic Myiasis in Vom and Bukuru Metropolis, Jos South LGA, Plateau State, Nigeria

Field: Veterinary (Health Sciences)

A study was carried out to establish the emergence of cutanous myiasis with its zoonotic implication in Vom andBukuru metropolis of Jos South Local Government Area of Plateau State. 6 individuals (3 males and 3 females)who were suspected to have boils on their skin were diagnosed to be 100% infested with the larvae ofCordylobia anthropophaga. Similarly, in an investigation of dogs, out of 510 dogs examined in EvangelicalChurch of West Africa and NVRI Veterinary clinics, 47(9.2%) dogs had larvae in their cutanous tissues. Of 300dogs from ECWA vet clinic 31 (10.3%) were positive, while 16 (7.6%) were positive from 210 dogs screened inNVRI vet clinic. All results were statistically significant at P< 0.05. In comparism, the larvae extracted fromhuman and dogs were all identified to be of Cordylobia anthropophaga. Of 184 Alsatian 13(7.1%) were positive,of 258 Mongrel 27(10.5%) were positive, 3(21.4%) among 14 Doberman were positive and of 54 Rottweiler4(7.4%) were positive. Out of the 47 positive cases, 31(66.0%) were female while 16 (34%) were males. Amongthe female positive cases Mongrel showed a prevalence of 18(58.1%). Infestation in July showed a highoccurrence of 22(46.8%). Secondary bacterial infection was encountered in two cases of human infestation.
A new species of nightjar (Caprimulgus) from Timor and Wetar, Lesser Sunda Islands, Wallacea

Field: Agricultural and Biological Sciences (Life Sciences)

The nightjars of the Caprimulgus macrurus complex are distributed from Pakistan to Australia and comprise six morphologically similar but vocally distinct species. Fieldwork on Timor and Wetar, Lesser Sunda Islands, has resulted in the discovery of a seventh species in the complex, which we describe as a new species. This species has previously been confused with Caprimulgus macrurus , Caprimulgus celebensis and Caprimulgus manillensis but it differs from these and all other species in the complex by at least 13 vocal characters. Discriminant function analysis correctly classified all recordings in the complex to species. Caprimulgus ritae is known from five adult museum specimens, which are the smallest in the complex and which differ from other species in the complex in several morphological characters. A molecular phylogenetic analysis indicated that C. ritae is sister to C. meesi from Flores and Sumba, and that these species together are sister to C. macrurus . C. ritae is a tropical forest specialist occurring from sea level to at least 1500 m (probably mostly below 1000 m). Lowland and montane forests on Timor are threatened. Wetar is one of the least developed islands in Indonesia, and retains >95% natural vegetation, dominated by Eucalyptus woodlands, with tropical forests in river gorges and slopes in upland areas. Pressure for development is accelerating throughout the range of C. ritae , and a detailed assessment of its conservation status is urgently needed.