Miracle-dz/UniFAR-FTUs huggingface dataset:
About the Correlation between Logical Identified Faulty Gates and their Layout Characteristics

Electronics play a significant role in modern society in various areas of our daily lives. Companies producing embedded nano-electronic systems have responded to the ever-increasing demand for high-performance chips with the development and production of structurally complex design, both in terms of the number of gates they are composed of and how they are arranged on the silicon surface. Especially devices intended for safety-critical fields, such as the Automotive field, require a thorough and precise testing process before they are fielded. This paper proposes a correlation analysis between candidate faulty logical gates as possible sources of a given failure identified during the Manufacturing Test Flow and their layout characteristics on the silicon. It is meaningful feedback for manufacturers about the quality of their applied tests. The experimental results are reported for data regarding a production lot of an Automotive System-on-Chip belonging to the SPC58 family produced by STMicroelectronics.
A CONFLICT OF INTEREST: ANALYZING THE IMPACT OF THE INTEGRATED COASTAL MANAGEMENT (ICM) AND TOURISM PROMOTION ON THE ENVIRONMENT AND LIVELIHOOD

This study uses a qualitative research methodology approach to explore the conflict of interest among coastal resource users and the development process in Bagamoyo town. I used qualitative methodology to understand the Bagamoyo people and recognize their position, experiences and views within the society in which they function as main stakeholders. Case study was used as a preferred design for this study. The samples were purposively chosen to reflect the diversity of environmental conditions, socio-economic status and opportunities available to local coastal communities like fishing and farming. The total number of respondents interviewed for this study was thirty-three. I used narrative stories through in-depth interviews of the respondents, documented information and a focus group comprising of 10 respondents, who did not participate in the in-depth interviews, to discuss the issues. There have been a number of initiatives from international development agencies, governmental, and non-governmental organizations to sustainable coastal resource management in Tanzania. Special focus was given on the impact of the ICM policies on the coastal environment and livelihood of rural coastal communities in Bagamoyo town. Additionally, this study analysed the conflicts of interest in the development process and tourism policies and the impact of these conflicts on the coastal livelihood of the coastal communities (Bagamoyo town). The findings revealed that the majority of these people do not benefit adequately from the rich resources in their community. The study suggested good policy prescriptions in order to increase recognition of the role and status of local coastal communities, transparency and accountability in sustainable management of the coastal resources. Also, my findings suggest solutions that would clearly define the responsibility, authority, and capacity for ICM management and provides enabling conditions for the communities to be part of this endeavor.
Do Digital Technologies Support Entrepreneurship Growth? Evidence from Indonesian Muslim Women in Depok City

The main objective of this paper is to assess the impact of digital technologies on the entrepreneurial output of Muslim women in Indonesia. Using a questionnaire, we collected data from Muslim women entrepreneurs involved in digital entrepreneurship in Depok city. We applied multiple linear regression to analyze the data. We found that the use of e-commerce platforms and internet services affects positively the entrepreneurship growth of Muslim women in Indonesia. However, online payments have been found non-significant because of awareness of risk and security towards online payment system. One of the limitations of this research is the size of the sample. Obtaining data from Muslim women entrepreneurs was very difficult. Again, the case under study is limited to one country. Therefore, it is recommended for future research to use a large sample size and include more countries. Indonesian government should implement tax reduction policies in order to improve the growing sector of Muslim women entrepreneurs, which can help them to become empowered in society.
Performance of Intelligent Reflecting Surface Based-FSO Link Under Strong Turbulence and Spatial Jitter

Intelligent reflecting surfaces (IRSs) are an emerging technology that can be used to alleviate the requirements of a strict line of sight in free-space optical communication (FSO) systems. This paper investigates the performance of an IRS-assisted FSO system under the conditions of strong atmospheric turbulence fluctuations, taking into account the impact of the spatial jitter at the transmitter and the IRS. A closed-form for the bit-error rate (BER) has been derived. The impact of the strong atmospheric turbulence is characterized using the K-distribution. The obtained results demonstrate that the performance depends on the system configuration as well as the transmitter and IRS jitter. Furthermore, we show that optimal placement of the IRS can improve the BER.
SocialBit: protocol for a prospective observational study to validate a wearable social sensor for stroke survivors with diverse neurological abilities

Introduction Social isolation has been found to be a significant risk factor for health outcomes, on par with traditional risk factors. This isolation is characterised by reduced social interactions, which can be detected acoustically. To accomplish this, we created a machine learning algorithm called SocialBit. SocialBit runs on a smartwatch and detects minutes of social interaction based on vocal features from ambient audio samples without natural language processing. Methods and analysis In this study, we aim to validate the accuracy of SocialBit in stroke survivors with varying speech, cognitive and physical deficits. Training and testing on persons with diverse neurological abilities allows SocialBit to be a universally accessible social sensor. We are recruiting 200 patients and following them for up to 8 days during hospitalisation and rehabilitation, while they wear a SocialBit-equipped smartwatch and engage in naturalistic daily interactions. Human observers tally the interactions via a video livestream (ground truth) to analyse the performance of SocialBit against it. We also examine the association of social interaction time with stroke characteristics and outcomes. If successful, SocialBit would be the first social sensor available on commercial devices for persons with diverse abilities. Ethics and dissemination This study has received ethical approval from the Institutional Review Board of Mass General Brigham (Protocol #2020P003739). The results of this study will be published in a peer-reviewed journal.
Analysis of Multilayered Metamaterial Structures with Frequency Dependent Constitutive Parameters Using Wave Matrices Approach

Combined with the Kramers-Kronig (KK) extraction method, the wave matrices approach is used in this work to compute the scattering parameters of metamaterial unit-cell consisting of three stacked layers along the z-direction. The proposed semi-analytical approach is taking into account the frequency dependence of the constitutive parameters $(\varepsilon_{r}(\omega)$ and $\mu_{r}(\omega))$ of each layer and the loss introduced when the wave traveling through each one. The validity of this method is proved through full wave simulations and analytical calculations, where the comparison between the two results are in good agreement. This semi-analytical approach could also be used to impose some necessary conditions on the structure geometrical parameters in order to maximize and/or minimize the reflection and/or the transmission coefficients.
Strengthening conservation and utilization of ground-nut (Arachis hypogaea L.) genetic resources in West Africa

This paper describes the status of ground-nut (Arachis hypogaea L.) genetic resources conservation and utilization in West Africa. A proportion of ground-nut accessions conserved in the ICRISAT gene bank in Patancheru, India, were duplicated at ICRISAT, Niamey, Niger, to provide ready access to a greater range of diversity for crop improve­ment scientists. With support from the Common Fund for Commodities (CFC), 6000 accessions from 73 countries were assembled, representing the major bo­tanic types and maturity groups. These accessions were characterized and evaluated for desirable traits at select­ed locations in West Africa, India and Malawi. The accessions were screened for their reaction to important diseases, including rust, early and late leaf spots, ground-nut rosette virus and aflatoxin contamination. In the collection, 166 ac­cessions show resistance to rust, 80 to late leaf spot, 30 to early leaf spot, 150 to ground-nut rosette disease and 74 to Aspergillus flavus invasion and aflatoxin contamination. The germplasm has been documented in printed catalogues, digitally on CD-ROMs and posted on the Web. Procedures for the distribu­tion and exchange of germplasm were developed and 6371 samples were dis­tributed to users. With support from the World Bank, an additional room was constructed at the gene bank at Niamey to accommodate 13 deep freezers to conserve the entire global ground-nut germplasm and other species, especially pearl millet.
Overexpression of long noncoding rna LINC00882 is associated with poor prognosis in hepatocellular carcinoma

RNAs (lncRNAs) have been reported as promising biomarkers for tumor diagnosis and treatment. Materials and methods: In this study, we profiled expression patterns and dysregulation of lncRNAs in HCC tissues by analyzing two datasets GSE55191 and GSE64631 from Gene Expression Omnibus database firstly, each of which contains expression profiles of 3 primary HCC tissues and 3 normal liver tissues, respectively. Results: LncRNA 882 (LINC00882) is one of the lncRNAs that was significantly upregulated in HCC tissues compared with normal liver tissues. We verified the upregulation of LINC00882 in HCC by using two separate cohorts that contained 85 HCC tissues and paired adjacent noncancerous tissues and 86 HCC tissues and 89 independent noncancerous liver tissues, respectively. Discussion: We found that upregulation of LINC00882 is correlated with poorer prognosis of HCC patients. In vitro cell experiments demonstrated that knockdown of LINC00882 inhibits proliferation, migration and invasion of HCC cell lines. Conclusion: These results indicated that LINC00882 promotes HCC progression and could be a potential prognostic biomarker and therapeutic target for HCC.
WELID: A Weighted Ensemble Learning Method for Network Intrusion Detection

The requirements for intrusion detection technology are getting higher and higher, with the rapid expansion of network applications. There have been many studies on intrusion detection, however, the accuracy of these models is not high enough and time-consuming, making them unavailable. In this paper, we propose a novel weighted ensemble learning method for network intrusion detection (WELID). Firstly, data preprocessing and feature selection algorithms are used to filter out some redundant and unrelated features. Next, anomaly detection is performed on the dataset using different base classifiers, and a layered ten-fold cross-validation method is used to prevent program overfitting. Then, the best classifiers are selected for the use of a multi-classifier fusion algorithm based on probability-weighted voting. We compare the proposed model with lots of efficient classifiers and state-of-the-art models for intrusion detection. The results show that the proposed model is superior to these models in terms of accuracy and time consumption.
Imprint of massive neutrinos on Persistent Homology of large-scale structure

Exploiting the Persistent Homology technique and an associated complementary representation which enables us to construct a synergistic pipeline for different topological features quantified by Betti curves in reducing the degeneracy between cosmological parameters, we investigate the footprint of summed massive neutrinos ($M_{\nu}$) in different density fields simulated by the publicly available Quijote suite. Evolution of topological features in the context of super-level filtration on three-dimensional density fields, reveals remarkable indicators for constraining the $M_{\nu}$ and $\sigma_8$. The abundance of 2-holes is more sensitive to the presence of $M_{\nu}$, also the persistence of topological features plays a crucial role in cosmological inference and reducing the degeneracy associated with $M_{\nu}$ simulation rather than their birth thresholds when either the total matter density ($m$) field or those part including only cold dark matter+baryons ($cb$) is utilized. Incorporating the Betti-1 and Betti-2 for $cb$ part of $M^+_{\nu}$ simulation marginalized over the thresholds implies $5\%$ variation compared to the massless neutrinos simulation. The constraint on $M_{\nu}$ from $\beta_k$ and its joint analysis with birth threshold and persistency of topological features for total mass density field smoothed by $R=5$ Mpc h$^{-1}$ at zero redshift reach to $0.0172$ eV and $0.0152$ eV, at $1\sigma$ confidence interval, respectively.
Viscosity effects in density-stable miscible displacement flows: Experiments and simulations

We study characteristics of miscible displacement flows in inclined pipes with density-stable configuration, meaning the lighter fluid is pumped to displace the heavier fluid downward along the pipe. Experiments have been completed in a pipe covering a broad range of inclination angles, flow rates, and viscosity configurations. Viscosity contrast between the fluids is obtained by adding xanthan gum to water, while glycerol is used to achieve density difference. Novel instabilities appear in the case of shear-thinning displacements. Numerical simulations are performed using the finite volume package OpenFOAM. The unsteady three-dimensional Navier-Stokes equations are used with the volume of fluid method to capture the interface between the fluids. A number of numerical cases are compared against the experiments to benchmark the model favourably. The code allows us to examine in detail the 3D structure of the propagating front and other secondary flows.
Brain Tumour Detection Using Deep Learning Techniques

Brain tumours pose a significant health risk, and early detection plays a crucial role in improving patient outcomes. Deep learning techniques have emerged as a promising approach for automated brain tumor detection, leveraging the power of artificial intelligence to analyse medical images accurately and efficiently. This research study aims to explore the current state-of-the-art deep learning techniques for brain tumor detection, including Convolutional Neural Networks (CNNs) and their variants, and to evaluate their performance using various datasets. The results demonstrate the potential of deep learning in assisting radiologists and clinicians in accurately detecting brain tumours, leading to timely diagnoses and improved treatment planning.
Investigating the other race effect: Human and computer face matching and similarity judgements

ABSTRACT The other race effect (ORE) in part describes how people are poorer at identifying faces of other races compared to own-race faces. While well-established with face memory, more recent studies have begun to demonstrate its presence in face matching tasks, with minimal memory requirements. However, several of these studies failed to compare both races of faces and participants in order to fully test the predictions of the ORE. Here, we utilized images of both Black and White individuals, and Black and White participants, as well as tasks measuring perceptions of face matching and similarity. In addition, human judgements were directly compared with computer algorithms. First, we found only partial support for an ORE in face matching. Second, a deep convolutional neural network (residual network with 29 layers) performed exceptionally well with both races. The DCNN’s representations were strongly associated with human perceptions. Taken together, we found that the ORE was not robust or compelling in our human data, and was absent in the computer algorithms we tested. We discuss our results in the context of ORE literature, and the importance of state-of-the-art algorithms.
Do consumption-based asset pricing models explain serial dependence in stock returns?*

We show that the Bansal-Yaron, Campbell-Cochrane and Cecchetti-Lam-Mark models of asset prices cannot explain the serial correlation structure of stock returns. We show this by estimating these models and deriving expected returns from them and then testing whether the difference between observed and expected returns is a martingale difference sequence. We use variance ratio and rescaled range tests which we modify to account for the expected returns being functions of estimated parameters. We also use a weighted quantilogram test based on a bootstrap procedure robust to this estimation. The evidence against the BansalYaron and Campbell-Cochrane models is significant. While the evidence against the Cecchetti-Lam-Mark model is not in general significant, our point estimates strongly suggest its residuals are not a martingale difference sequence. Furthermore, a semi-parametric maximal predictability test suggests there is some evidence that the three models’ state variables struggle to explain the degree of predictability observed in the market return. A timing strategy designed to exploit predictability in the market can significantly outperform the market in certainty equivalent terms under the Bansal-Yaron model. The timing strategy may underperform the market by less than it ought to under the Campbell-Cochrane model. JEL classification: C58, G12
Sex-specific effect of P2Y2 purinergic receptor on glucose metabolism during acute inflammation

The sex of an animal impacts glucose sensitivity, but little information is available regarding the mechanisms causing that difference, especially during acute inflammation. We examined sex-specific differences in the role of the P2Y2 receptor (P2Y2R) in glucose flux with and without LPS challenge. Male and female wild-type and P2Y2R knockout mice (P2Y2R-/-) were injected with LPS or saline and glucose tolerance tests (GTT) were performed. P2Y2R, insulin receptor, and GLUT4 transporter gene expression was also evaluated. Female mice had reduced fasting plasma glucose and females had reduced glucose excursion times compared to male mice during GTT. P2Y2R-/- males had significantly decreased glucose flux throughout the GTT as compared to all female mice. Acute inflammation reduced fasting plasma glucose and the GTT area under the curve in both sexes. While both wild-type and P2Y2R-/- male animals displayed reduced fasting glucose in LPS treatment, female mice did not have significant difference in glucose tolerance, suggesting that the effects of P2Y2R are specific to male mice, even under inflammatory conditions. Overall, we conclude that the role for the purinergic receptor, P2Y2R, in regulating glucose metabolism is minimal in females but plays a large role in male mice, particularly in the acute inflammatory state.
FDR Control of Detected Regions by Multi-Scale Matched Filtering

Feature extraction from observed noisy samples is a common important problem in statistics and engineering. This paper presents a novel general statistical approach to the region detection problem in long data sequences. The proposed technique is a multi-scale kernel regression in conjunction with statistical multiple testing for region detection while controlling the false discovery rate (FDR) and maximizing the signal to noise ratio (SNR) via matched filtering. This is achieved by considering a one-dimensional (1D) region detection problem as its equivalent 0D (zero dimensional) peak detection problem. The detection method does not require a priori knowledge of the shape of the nonzero regions. However, if the shape of the non-zero regions is known a priori, e.g. rectangular pulse, the signal regions can also be reconstructed from the detected peaks, FDR Control of Detected Regions by Multi-Scale Matched Filtering Nezamoddin N. Kachouie, Xihong Lin, Armin Schwartzman D ow nl oa de d by [ N or th C ar ol in a St at e U ni ve rs ity ] at 0 0: 27 1 5 Ja nu ar y 20 16
Developing an IoT enabled smart classroom S3TH System

The advent of Internet of Things (IoT) technology has created new opportunities for instructors and students to improve the classroom experience. This paper describes a method for creating an IoT-based smart classroom that intends to improve learning, teaching experience, and security. The suggested system includes a variety of sensors, devices, and software applications for monitoring, controlling, and optimizing the classroom environment and activities. The smart classroom system, in particular, can manage attendance, automate lighting and temperature control, provide tailored feedback and recommendations to students, and facilitate interactive and collaborative learning. Moreover, the system enhances the security of the classroom by detecting and alerting to unauthorized access, potential hazards, and emergency situations. The implementation of the proposed IoT-based smart classroom is described, and results show that the smart classroom system can significantly improve the learning and teaching experience, enhance security, and reduce the workload of teachers. The paper concludes by highlighting the potential of IoT-based smart classrooms to transform education and outlining future research directions.
Terrain Characterisation and Design Wind Profiles for Hong Kong

Numerous wind profiles at different locations in Hong Kong have been obtained from topographical model studies undertaken in the CLP Power Wind/Wave Tunnel Facility (WWTF) at the Hong Kong University of Science and Technology (HKUST). The results of these studies confirm that the impact of adjacent buildings and surrounding topography on the site wind profile is noteworthy and support the addition of more representative wind profiles to the current wind code of Hong Kong, Code of Practice on Wind Effects in Hong Kong 2004 (HK Wind Code 2004), so as to more accurately reflect the site wind characteristics in different regions of Hong Kong. Mean wind speed profile and turbulence intensity profile for three terrain categories, namely deep open sea, harbour-front and built-up, are proposed to be adopted in the wind code of Hong Kong. A case study of wind-induced loads on generic tall buildings with a square cross-section and varying heights demonstrated that the proposed wind profiles provide a more accurate estimation of wind-induced loads on the test buildings compared with those determined based on the wind profiles of open sea terrain specified in HK Wind Code 2004.
Probing Crustal Anisotropy by Receiver Functions at the Deep Continental Drilling Site 2 KTB in Southern Germany 3 4

This article is protected by copyright. All rights reserved. 1 1 Probing Crustal Anisotropy by Receiver Functions at the Deep Continental Drilling Site 2 KTB in Southern Germany 3 4 Bianchi I. *, Bokelmann G. 5 *irene.bianchi@univie.ac. at 6 Department of Meteorology and Geophysics, University of Vienna, Austria 7 8
Fiber Optic Devices for High-Resolution Refractive Index Sensing

The paper describes a fiber optic Fabry-Perot (FP) refractive index (RI) sensors that provide performances required in gas sensing applications. Presented high-resolution FabryPerot Interferometer (FPI) sensors are based on open-path cells that can be integrated with the optical fiber in different ways. They can be fabricated as microcells on the fiber tip or along the optical fiber, or as external/extrinsic gas cells connected to the fiber. All presented configurations are based on low-finesse FPI as they allow for a simple and cost-efficient designs.