Miracle-dz/UniFAR-FTUs huggingface dataset:
Delay Prediction for ASIC HLS: Comparing Graph-Based and Nongraph-Based Learning Models

While high-level synthesis (HLS) tools offer faster design of hardware accelerators with different area versus delay tradeoffs, HLS-based delay estimates often deviate significantly from results obtained from ASIC logic synthesis (LS) tools. Current HLS tools rely on simple additive delay models which fail to capture the downstream optimizations performed during LS and technology mapping. Inaccurate delay estimates prevent fast and accurate design-space exploration without performing time-consuming LS tasks. In this work, we exploit different machine learning models which automatically learn to map the different downstream optimizations onto the HLS critical paths. In particular, we compare graph-based and nongraph-based learning models to investigate their efficacy, devise hybrid models to get the best of the both worlds. To carry out our learning-assisted methodology, we create a dataset of different HLS benchmarks and develop an automated framework, which extends a commercial HLS toolchain, to extract essential information from LS critical path and automatically matches this information to HLS path. This is a nontrivial task to perform manually due to difference in level of abstractions. Finally, we train the proposed hybrid models through inductive learning and integrate them in the commercial HLS toolchain to improve delay prediction accuracy. Experimental results demonstrate significant improvements in delay estimation accuracy across a wide variety of benchmark designs. We demonstrate that the graph-based models can infer essential structural features from the input design, while incorporating them into traditional nongraph-based models can significantly improve the model accuracy. Such “hybrid” models can improve delay prediction accuracy by 93% compared to simple additive models and provide $175\times $ speedup compared to LS. Furthermore, we discuss key insights from our experiments, identifying the influence of different HLS features on model performance.
Hybrid MoM-circuit models to analyze the radiated susceptibility of multiconductor shielded cables within complex structures

Abstract This paper presents an analysis of the radiated susceptibility of multiconductor shielded cables within complex structures following a hybrid method using moments (MoM) circuit models. The MoM code was used to compute the currents on the shielding induced by an external electromagnetic field and incorporated into a circuit model. The proposed method can be employed for nonlinear loads. The method was tested on two cases: coaxial shielded cables inside a cavity and a car with complex wiring, including a coaxial cable, a twinax cable (a cable with two parallel wires), and a triaxial cable (a cable with three parallel wires), all of which are excited by an incident plane wave. The proposed method provides high accuracy and significant speed gain, and its results are in good agreement with those obtained in other studies.
Exploring the Use of Antibiotics for Dental Patients in a Middle-Income Country: Interviews with Clinicians in Two Ghanaian Hospitals

Background: Antimicrobial resistance is a global problem driven by the overuse of antibiotics. Dentists are responsible for about 10% of antibiotics usage across healthcare worldwide. Factors influencing dental antibiotic prescribing are numerous, with some differences in low- and middle-income countries compared with high-income countries. This study aimed to explore the antibiotic prescribing behaviour and knowledge of teams treating dental patients in two Ghanaian hospitals. Methods: Qualitative interviews were undertaken with dentists, pharmacists, and other healthcare team members at two hospitals in urban and rural locations. Thematic and behaviour analyses using the Actor, Action, Context, Target, Time framework were undertaken. Results: Knowledge about ‘antimicrobial resistance and antibiotic stewardship’ and ‘people and places’ were identified themes. Influences on dental prescribing decisions related to the organisational context (such as the hierarchical influence of colleagues and availability of specific antibiotics in the hospital setting), clinical issues (such as therapeutic versus prophylactic indications and availability of sterile dental instruments), and patient issues such as hygiene in the home environment, delays in seeking professional help, ability to access antibiotics in the community without a prescription and patient’s ability to pay for the complete prescription. Conclusions: This work provides new evidence on behavioural factors influencing dental antibiotic prescribing, including resource constraints which affect the availability of certain antibiotics and diagnostic tests. Further research is required to fully understand their influence and inform the development of new approaches to optimising antibiotic use by dentists in Ghana and potentially other low- and middle-income countries.
Lyapunov Optimization in Online Battery Energy Storage System Control for Commercial Buildings

The high instantaneous discharging capability of battery energy storage systems (BESSs) make them ideal candidates for reducing peak loads in commercial buildings. An efficient online BESS control algorithm can be beneficial for reducing the monthly electricity bill of individual commercial buildings. Conventional model-based BESS control algorithms rely heavily on accurate long-horizon net load forecast, which is difficult to obtain. To address this problem, we develop a Lyapunov optimization-based online BESS control algorithm and derive its theoretical performance bound. Comprehensive numerical study results using real world commercial building smart meter data in southern California show that our proposed Lyapunov optimization-based online control algorithm with time-varying weighting parameters yields higher savings in electricity cost and requires less computation time in comparison to the state-of-the-art baseline algorithms.
Microstructures and mechanical properties of α-Al2O3W and MWCNTs hybrid reinforced laminated Cu matrix composites

ABSTRACT The balance between strength and toughness is of great importance. In this paper, the microstructure and properties of laminated composites in X-Y direction were characterized and analyzed. The effect of the content of α-Al2O3w and MWCNTs on the laminated structure and properties was analyzed, and strengthening mechanisms and toughening mechanisms of the material were discussed. The laminated structure of traditional Cu matrix composites was designed by a combination of flake powder metallurgy and SPS sintering. Compared with spherical Cu, flake Cu can increase the interface contact between matrix and reinforcement phase, which is conducive to the formation of self-assembly of laminated structure in SPS sintering process. The strength and compressive elongation of 1.0 wt. % MWCNTs-1.0 wt. % α-Al2O3w/Cu hybrid laminated composites were the best, reaching 453.43 MPa, 50%, respectively. This is mainly due to the composites containing MWCNTs less than 1.0 wt. % had uniform microstructure and good interfacial bonding, and the loads were effectively transferred from Cu matrix to MWCNTs and α-Al2O3w. At the same time, the large grain size in the plane is favorable for dislocation movement, while the interlayer interface and nanocrystals hinder the combination of dislocation movement perpendicular to the plane to achieve a balance of strength and toughness. Graphical abstract
Knot Logic and Topological Quantum Computing with Majorana Fermions

This paper is an introduction to relationships between quantum topology and quantum computing. We take a foundational approach, showing how knots are related not just to braiding and quantum operators, but to quantum set theoretical foundations and algebras of fermions. We show how the operation of negation in logic, seen as both a value and an operator, can generate the fusion algebra for a Majorana fermion, a particle that is its own anti-particle and interacts with itself either to annihilate itself or to produce itself. We call negation in this mode the mark, as it operates on itself to change from marked to unmarked states. The mark viewed recursively as a simplest discrete dynamical system naturally generates the fermion algebra, the quaternions and the braid group representations related to Majorana fermions. The paper begins with these fundmentals. They provide a conceptual key to many of the models that appear later in the paper. In particular, the Fibonacci model for topological quantum computing is seen to be based on the fusion rules for a Majorana fermion and these in turn are the interaction rules for the mark seen as a logical particle. It requires a shift in viewpoint to see that the operator of negation can also be seen as a logical value. The quaternions emerge naturally from the reentering mark. All these models have their roots in unitary representations of the Artin braid group to the quaternions.
Catalytic co‐pyrolysis of low‐density polyethylene (LDPE) and lignin for jet fuel range hydrocarbons over activated carbon catalyst

The catalytic conversion of low‐density polyethylene (LDPE) and lignin over activated carbon into jet fuel range hydrocarbons was studied. A fixed bed furnace was used to investigate the impacts of temperature, LDPE to lignin ratio, and catalyst to feedstock ratio on the composition of bio‐oils, and up to 100 area% jet fuel range hydrocarbons can be acquired from the catalytic co‐pyrolysis of LDPE and lignin. The results showed that the activated carbon has an excellent catalytic performance to convert LDPE and lignin into jet fuel range hydrocarbons. The properties of activated carbon catalyst were characterized by nitrogen gas adsorption, Fourier transform infrared spectrometer, and scanning electron microscope. There is a synergistic effect between the higher pyrolysis temperature and the acid sites of activated carbon on the dissociation and conversion of alkanes to form the aromatics. In addition, the yield of jet fuel range hydrocarbons could be enhanced by the synergistic effect of LDPE on the catalytic conversion of lignin. This work provided an environment friendly, economical, convenient, simple, and effective route to acquire jet fuel range hydrocarbons from daily waste plastics and biomass.
Evaluating the Sustainability of the Olympic Transport System on the View of Regional Transport Development Pattern

The International Olympic Committee (IOC) proposed that the host city should consider sustainable development from the Games’ beginning to end, and that the host city should make full use of the Olympic infrastructure even after the Games. However, a less systematic evaluation of their sustainability exists, especially for the roads. The new connections built for the Olympic Games cost the most and influenced the host city directly. We apply spatial design network analysis (sDNA) with exploratory spatial data analysis (ESDA) to evaluate the sustainability of the new connections built for the Olympics Games in the 2022 Winter Olympic Games. The results show that the Games encourage the host cities’ governments to work towards a common goal, and directly benefits Beijing–Tianjin–Hebei transport coordinated development. In “Edge cities”, such as Hengshui, Qinhuangdao, Cangzhou, and Zhangjiakou, traffic accessibility has been promoted dramatically. The foreground network of the region development moved northward, from “Beijing–Shijiazhuang–Baoding” to “Beijing–Tangshan–Qinhuangdao”. These findings can be used for policy design, to keep the new connections running with long-term stability, and to constantly create better economic effects.
CEO Social Capital and the Value Relevance of Accounting Metrics

Using a unique dataset of CEO social capital between 1998 and 2017, we investigate the degree to which CEO social capital increases or decreases investors’ reliance upon traditional accounting metrics when valuing the equity of non-US firms. We find, ceteris paribus, that investors rely more heavily on the book value of equity, rather than on earnings per share, to value common stock when the firm is led by a CEO with greater social capital. These findings suggest that CEO social capital erodes investors’ confidence in the quality and relevance of earnings; CEOs with higher social capital are entrenched and may engage in rent-seeking behaviors. These findings are robust to country-level development, efficiency, corruption comparisons, and alternative model specifications.
LIPASE PRODUCTION FROM SOLID STATE FERMENTATION OF COPRA WASTE ASSOCIATED FUNGUS Aspergillus niger

Lipases are enzyme with versatile industrial applications can be produced by the solid-state fermentation (SSF) method and is an economical alternative for enzyme production assisted by fungus. In Malaysia, 5 million of copra waste were generated annually. Large amount of copra waste produced will cause an increasing amount of the waste dumped to the landfill. Copra waste is one of the potential substrates to produce lipase enzyme through SSF. Thus, the aim of this study is to optimize the lipase production by SSF associated by Aspergillus niger using the 23 full factorial design approach. In this study the factors affecting parameters that involved in the production of lipase enzyme such as temperature (25˚ and 35˚), substrates concentration (40% and 60%) and inoculum size of Aspergillus niger (1 and 9 petri dish) were determined. The maximum production of lipase was obtained after 120-hour incubation in SSF. The optimum condition for inoculum size of Aspergillus niger was 9 plates, 30°C of incubation temperature and 60 % moisture contents. The range of the concentration of lipase enzyme produced varied from 105 U/ml to 170 U/ml. When applied to the wastewater treatment, the reducing percentage of fat, oil and grease (FOG) in food processing wastewater is reduced from 219.4925mg/l to 169.467mg/l accounted to the amount of 34 % FOG removal. Lipase produced using copra waste as a substrate using SSF has the potential value to be developed in the future for various industry including wastewater treatment industry.
LITERARY REVISION OF AMBIENT INTELIGENCE FOR THE CARE OF THE ELDERLY AT SMART HOMES

Las personas tienen necesidades diversas y cambiantes a medida que envejecen y el número de personas que viven con alguna discapacidad está constantemente en aumento. Las casas inteligentes tienen un potencial único para proporcionar vida asistida, pero a menudo están diseñados de manera rígida con un problema específico y fijo en mente. Por esta razón se realiza una investigación con el fin de identificar esos componentes de la inteligencia ambiental aplicada en la domótica dirigida a la población del adulto mayor o pacientes que viven con alguna discapacidad física o mental. Se realizó una revisión de la literatura en tres (3) distintas bases de datos. de documentos publicados por diferentes universidades, revistas y asociaciones profesionales en el contexto internacional; la temática abordar fue sobre la inteligencia ambiental aplicada en la domótica. Dirigido a una población en específico que es el adulto mayor o pacientes que viven con alguna discapacidad debido a la edad. En esta investigación Se identificaron los objetivos principales, factores importantes y la confiabilidad de esta tecnología aplicada en los hogares inteligentes teniendo en cuenta la población a la que va dirigida.
Investigation of the effects of multiple pressures in the lower Danube basin

The main scope of the paper is the implementation of future scenarios in the Lower Danube basin, supporting the development of River Basin Management Plans and future environmental policies. The 800 000 km2 Danube River Basin extends across 19 countries, of which 14 are contracting parties of the ICPDR. The Lower Danube is occupied mostly by Romania, including the Danube Delta. The Danube Delta hydrological complex covers 5800 km2 comprising over 300 lakes, three main branches and a vast network of channels. Changes impacting significant ecosystem services such as recreation, fishing, flows, ecotourism, flood regulation, navigation and reed/wood resources have to be evaluated and the quantification of those elements must be performed in order to incorporate them into the modelling process.
Big Data for transportation and mobility: recent advances, trends and challenges

Big Data is an emerging paradigm and has currently become a strong attractor of global interest, specially within the transportation industry. The combination of disruptive technologies and new concepts such as the Smart City upgrades the transport data life cycle. In this context, Big Data is considered as a new pledge for the transportation industry to effectively manage all data this sector required for providing safer, cleaner and more efficient transport means, as well as for users to personalize their transport experience. However, Big Data comes along with its own set of technological challenges, stemming from the multiple and heterogeneous transportation/mobility application scenarios. In this survey we analyze the latest research efforts revolving on Big Data for the transportation and mobility industry, its applications, baselines scenarios, fields and use case such as routing, planning, infrastructure monitoring, network design, among others. This analysis will be done strictly from the Big Data perspective, focusing on those contributions gravitating on techniques, tools and methods for modeling, processing, analyzing and visualizing transport and mobility Big Data. From the literature review a set of trends and challenges is extracted so as to provide researchers with an insightful outlook on the field of transport and mobility.
Focus Issue on Legacy Information Systems and Business Process Change: On the Integrated Design and Evaluation of Business Processes and Information Systems

The role of information systems in influencing and enabling organisational design is widely acknowledged. Yet limited attention is paid to the theoretical legitimacy and conceptual basis of IS-enabled organisational change i.e., business engineering. In this paper we review business engineering’s reference disciplines critically: process-based organisational design, IS development, and IS evaluation. Findings from a case study of business engineering provide empirical support to the theoretical analysis. Synthesis of the conclusions of the review and the case study lead to a number of propositions and potential avenues for further research into the theoretically attractive and practically important field of aligning the design of organisational structures with the design of Information Systems intended to support them.
A Universal Decoupled Training Framework for Human Parsing

Human parsing is an important technology in human–robot interaction systems. At present, the distribution of multi-category human parsing datasets is unbalanced, and the samples present a long-tailed distribution, which directly affects the performance of human parsing. Meanwhile, the similarity between different categories leads the model to predict false parsing results. To solve the above problems, a general decoupled training framework called Decoupled Training framework based on Pixel Resampling (DTPR) was proposed to solve the long-tailed distribution, and a new sampling method named Pixel Resampling based on Accuracy distribution (PRA) for semantic segmentation was also proposed and applied to this decoupled training framework. The framework divides the training process into two phases, the first phase is to improve the model feature extraction ability, and the second phase is to improve the performance of the model on tail categories. The training framework was evaluated in MHPv2.0 and LIP datasets, and tested in both high-precision and real-time SOTA models. The MPA metric of model trained by DTPR in above two datasets increased by more than 6%, and the mIoU metric increased by more than 1% without changing the model structure.
A retrospective observational study of biomarker levels and severity assessment in pediatric community-acquired pneumonia

Multiple studies have investigated the role of biomarkers in predicting pneumonia severity in adults but minimal conclusive research exists for children. This study aimed to determine if the following biomarker levels, collected within 72 hours of hospital arrival: white blood cell count (WBC), platelet count, C-reactive protein (CRP), procalcitonin (PCT), neutrophil-lymphocyte ratio, neutrophil count, or band count associated with community-associated pneumonia (CAP) severity in children. Methods: A retrospective chart review was conducted on children (aged 60 days to 18 years) diagnosed with CAP, and admitted to a regional, tertiary hospital (Charleston, WV, USA) for 3 years (2015–2018). Patients were stratified into 2 severity cohorts, mild (no ICU care), and moderate/severe (required ICU care). Biomarker values were then compared between the severity cohorts and area under the curve (AUC), and cut-off values and performance characteristics were calculated. Results: A total of 108 patients met inclusion criteria with 46% having moderate/severe CAP. Elevated levels of CRP (51.7 mg/L in mild vs. 104.8 mg/L in moderate/severe, P = .003, PCT (0.29 ng/ml in mild vs. 4.02 ng/mL in moderate/severe, P = .001) and band counts (8% in mild vs. 15% moderate/severe, P = .009) were associated with increased pneumonia severity. In predicting moderate/severe CAP, PCT had the highest AUC of 0.77 (P = .001) followed by bands AUC of 0.69 (P = .009) and CRP AUC of 0.67 (P = .003). Cut-off for PCT of 0.55 ng/mL had a sensitivity of 83% and a specificity of 65%. Cut-off level of 53.1 mg/L for CRP had a sensitivity of 79% and specificity of 52%. Cut off level of 12.5% bands had a sensitivity of 61% and specificity of 71%. In a multivariable model controlled for patient demographics and other biomarker levels, only PCT levels significantly predicted moderate/severe CAP (adjusted odds ratio: 1.40 [95% CI, 1.14–1.73], P = .002). Conclusion: Biomarkers, in particular PCT, obtained early in hospitalization may perform as possible predictors for CAP severity in children and be beneficial in guiding CAP management. However, biomarkers in pneumonia should not drive severity assessment or patient management independent of clinical presentation.
RETRACTED: Safety Index Evaluation and Calibration of Load and Resistance Factors for Concrete Beams Under the Simultaneous Effects of Bending, Shear and Torsion

This article has been retracted at the request of the Editor-in-Chief due to extended similarites with a previously published paper (in Persian). The previously published paper is: F. Jafari, J. Akbari, A. Jahanpur, " Evaluation of Safety Index and Calibration of Load and Resistance Factors for Reinforced Concrete Beams under Bending, Shear and Torsion Demands", Journal of Structural and Contruction Engineering, Article 5, Vol. 3, No. 4, pp. 49-64, 2017 (in Persian) The authors of this paper failed to provide any reasoning regarding the case.
Classification Methods for MAGIC Telescope Images on a Pixel-by-pixel base

The problem of identifying gamma ray events out of charged cosmic ray background (so called hadrons) in Cherenkov telescopes is one of the key problems in VHE gamma ray astronomy. In this contribution, we present a novel approach to this problem by implementing different classifiers relying on the information of each pixel of the camera of a Cherenkov telescope, rather than using common Hillas parameter analysis. Separation between gamma-like and hadron-like events is tested by using Monte Carlo data samples of both types of events.