Miracle-dz/UniFAR-FTUs huggingface dataset:
Reliable Memristive Neural Network Accelerators Based on Early Denoising and Sparsity Induction

Implementing deep neural networks (DNNs) in hardware is challenging due to the requirements of huge memory and computation associated with DNNs' primary operation—matrix-vector multiplications (MVMs). Memristive crossbar shows great potential to accelerate MVMs by leveraging its capability of in-memory computation. However, one critical obstacle to such a technique is potentially significant inference accuracy degradation caused by two primary sources of errors—the variations during computation and stuck-at-faults (SAFs). To overcome this obstacle, we propose a set of dedicated schemes to significantly enhance its tolerance against these errors. First, a minimum mean square error (MMSE) based denoising scheme is proposed to diminish the impact of variations during computation in the intermediate layers. To the best of our knowledge, this is the first work considering denoising in the intermediate layers without extra crossbar resources. Furthermore, MMSE early denoising not only stabilizes the crossbar computation results but also mitigates errors caused by low resolution analog-to-digital converters. Second, we propose a weights-to-crossbar mapping scheme by inverting bits to mitigate the impact of SAFs. The effectiveness of the proposed bit inversion scheme is analyzed theoretically and demonstrated experimentally. Finally, we propose to use L1 regularization to increase the network sparsity, as a greater sparsity not only further enhances the effectiveness of the proposed bit inversion scheme, but also facilitates other early denoising mechanisms. Experimental results show that our schemes can achieve 40%-78% accuracy improvement, for the MNIST and CIFAR10 classification tasks under different networks.
Neurolocomotor Behavior and Oxidative Stress Markers of Thiazole and Thiazolidinedione Derivatives against Nauphoeta cinerea

Thiazolidine compounds NJ20 {(E)-2-(2-(5-bromo-2-methoxybenzylidene)hydrazinyl)-4-(4-nitrophenyl)thiazole} and NW05 [(2-(benzo (d) (1,3) dioxol-4-ylmethylene)-N-(4-bromophenyl)-thiosemicarbazone] potentiated the effect of norfloxacin in resistant bacteria; however, there are no reports on their effects on Nauphoeta cinerea in the literature. The objective of this work was to evaluate the behavioral effects and oxidative markers of NW05 and NJ20 in lobster cockroach N. cinerea. To evaluate the behavioral study, a video tracking software was used to evaluate the locomotor points and the exploratory profile of cockroaches in the horizontal and vertical regions of a new environment. The total concentration of thiol and reduced glutathione (GSH), substances reactive to thiobarbituric acid (TBARS), free iron (II) content and mitochondrial viability were determined. The antioxidant potential was evaluated by the DPPH method. Both substances induced changes in the behavior of cockroaches, showing a significant reduction in the total distance covered and in the speed. In the cell viability test (MTT), there was a significant reduction for NJ20 (1 mM). NJ20 caused a significant increase in total levels of thiol and non-protein thiol (NPSH), although it also slightly increased the content of malondialdehyde (MDA). Both compounds (NW05 and NJ20) caused a significant reduction in the content of free iron at a concentration of 10 mM. In conclusion, the compound NJ20 caused moderate neurotoxicity (1 mM), but had good antioxidant action, while NW05 did not show toxicity or significant antioxidant activity in the model organism tested. It is desirable to carry out complementary tests related to the antioxidant prospection of these same compounds, evaluating them at different concentrations.
Evidence of Impact from a National Digital Entrepreneurship Apprentice Program in Malaysia

Impact Digital Entrepreneurship Apprentice Program (IDEA@KPT) at Ministry of Higher Education Malaysia 2021 is a comprehensive nationwide six-month program. Forty-three teams consist of 43 Academic Supervisors, 129 institutes of Higher Learning students, and 43 Micro & Small Enterprises (MSE) owners conducted by Universiti Teknologi Malaysia. The program is aimed to develop capable students in maneuvering the digital business world. Students underwent an online Business and Digital Training, with apprenticeship and formal reportings. This article aims to present the impact of IDEA@KPT activities by analyzing 43 case studies produced in the program. A pre-codification scheme that concentrates on the study goals was the method for data collection. Before the program, all the teams were informed of the required components to ensure uniformity of the report. The evidence of significant gain and impact on the MSEs businesses was drawn from the components. Other than the components, analytics hindsight, visual appeal, persuasion ability, perception on paid ads, posting timing, and synergies beyond the digital world activities were gathered, providing richer information and insights that increase business value. Such lessons are beneficial to all parties as all businesses are demanded to utilize digital platforms nowadays.
Road traffic safety perception in Jordan

Abstract In the past 20 years, several safety measures were taken in an attempt to reduce traffic-related fatalities. Although reduction in deaths was occasionally noticed, the sustainability of that trend has never achieved. This study explores Jordan safety profile trying to explain the traffic safety trend. It examines road traffic safety perception of both public community and road specialist. Main turning points that may have contributed in explaining prevailing traffic safety conditions have been collected. A questionnaire is administered to two distinct groups of the Jordanian society (general public and road specialist) with a total of 167 subjects. The subjects were asked to evaluate the effectiveness of a list of safety measures. Results showed that government took effective but not sustainable measures (mainly enforcement and legislative). Other ineffective measures (administrative and engineering) were taken but they were not target oriented. The main focus of interviewed subjects in order to improve traffic safety in Jordan is to establish sustainable engineering measures and improving the vehicle fleet, driver licensing, and testing procedures. As a surprising result, enforcement measures were not considered as desirable as other measures.
Reactive Power Control and Optimization of Large Scale Grid Connected Photovoltaic Systems in the Smart Grid

In future smart grid, DC-AC inverter based renewable energy sources will greatly participate in not only the real power generation but also reactive power compensation. Among all the renewable energy sources, grid-connected photovoltaic (PV) systems have received much attention by engineers and researchers. Grid-connected PV systems with DC-AC inverters are able to supply real power to the utility grid as well as reactive power. The real power extracted by the DC-AC inverters is usually at the maximum power point (MPP) of the attached PV arrays and the reactive power is used to compensate the grid demand. However, the considerable number of DC-AC inverters and the complicated operating environment result in challenges in the control and optimization of both real and reactive power. For large scale grid-connected PV systems with multiple DC-AC inverters, due to the limited apparent power transfer capability of each inverter, the reactive power needs to be allocated among the DC-AC inverters in a proper way. In this thesis, an optimal strategy is proposed for the reactive power allocation in large scale grid-connected PV systems. The proposed method achieves the maximum reactive power transfer capability of the entire system by applying classic Lagrange multiplier method. The sufficient conditions of the optimal reactive power allocation strategy are provided and mathematically proved. Then, the optimal solutions of the reactive power allocation in the large scale PV systems are developed into a distributed ii optimization algorithm by using dual theory. The cost function of the optimization problem is proved to be convex and the original optimization problem is decomposed into multiple sub-problems. Each inverter only needs to solve the sub-problem subjected to it and then the optimal solutions of each sub-problem lead to the optimal solutions of the entire system. Later, control schemes are proposed by applying the balancing strategies for the reactive power. Reactive power balancing strategies have been discussed for uniform distribution and optimal distribution based on derived optimal solutions. Invariant sets are presented to denote the desired distribution of reactive power among inverters and stability analysis is conducted for the invariant sets for different conditions by using Lyapunov stability theory. Finally, the proposed optimal reactive power allocation strategies, the distributed optimization algorithm, and the reactive power balancing strategies are validated in case studies against a sample large scale grid-connected PV system.
Detection of Balenine in Mouse Plasma after Administration of Opah-Derived Balenine by HPLC with PITC Pre-Column Derivatization

We examined the absorption of balenine (Bal) in mouse blood after the administration of a high-purity Bal prepared from opah muscle. Using HPLC with phenyl isothiocyanate pre-column derivatization, we successfully isolated imidazole peptides and their constituents. We detected Bal and 3-methylhistidine (3-Me-His) in mouse blood 1 h after the administration of opah-derived Bal. The concentrations of Bal and 3-Me-His significantly increased to 128.27 and 69.09 nmol/mL in plasma, respectively, but were undetectable in control and carnosine (Car)-administrated mice. In contrast, β-alanine and histidine did not increase in mouse plasma 1 h after the administration of Car and opah-derived Bal. The present study is the first report on the absorption of food-derived Bal in mouse blood and serves as a pilot study for future clinical trials.
Acting as a Business Angel to Become a Better Entrepreneur: A Learning Innovation

TV shows such as “Dragons’ Den” and “Shark Tank” have become common teaching materials in entrepreneurial finance classrooms because they offer a window into the process of pitching to investors. TV exposure to pitch communication and business angels’ feedback is certainly a well-documented source of vicarious learning. It enables students to observe varying investment situations and learn from other entrepreneurs’ success as well as failure. Observation, however, does not replace direct experience. We combined vicarious learning and direct experience in order to enable students to learn how to take initial investment decisions, in practice. We originally proposed this training session in an entrepreneurship graduate program in France. This learning activity invites participants to become observers and actors in a real-life experience with entrepreneurs and angel investors. Students participate in a pitch session within a Business Angels Network (BAN). The BAN chooses entrepreneurs based on their applications and an evaluation meeting for the first round of a live pitch in their usual deal flow. Students are first spectators to the real-life pitch session, in which entrepreneurs face a team of five to 10 business angels (BAs). Then, students play the role of an active participant, making their own investment decisions in a report on each entrepreneurial project, as if they were BAs themselves.
What is the difference between the tall cell variant and the classic type of papillary thyroid carcinoma on ultrasonography?

Purpose The prevalence of the tall cell variant of papillary thyroid carcinoma (TCVPTC), which has a poor prognosis, has increased as its definition has been modified. We sought to investigate whether TCVPTC is different from the classic type on ultrasonography (US). Methods This study included 46 consecutive TCVPTC patients and 92 classic papillary thyroid carcinoma (PTC) patients who were confirmed surgically at the authors’ institution. The US findings and pathologic reports of these patients were retrospectively reviewed. US features based on the Korean Thyroid Imaging Reporting and Data System, preoperative US suspicion for lymph node metastasis, and the presence of capsular location were evaluated. Results Univariable and multivariable analyses identified that TCVPTC showed more frequent irregular tumor margin (odds ratio [OR], 6.62; 95% confidence interval [CI], 1.46 to 30.09; P=0.014) and capsular location (OR, 4.63; 95% CI, 1.49 to 14.41; P=0.008) than classic PTC. Capsular location was an independent predictor of TCVPTC for tumors less than or equal to 1.5 cm in size (OR, 4.23; 95% CI, 1.12 to 15.92; P=0.033). Irregular margin was an independent predictor of TCVPTC for tumors larger than 1.5 cm (OR, 10.46; 95% CI, 1.16 to 94.48; P=0.037). Extrathyroidal extension was not significantly different between the two groups. Conclusion The two key features of TCVPTC on US are frequent capsular location for tumors less than or equal to 1.5 cm in size and the higher likelihood of an irregular margin for tumors larger than 1.5 cm.
Integrating privacy debt and VSE's software developments

With the advent of regulations protecting users such as the General Data Protection Regulation, security and privacy concerns are playing a new role in small settings such as in very small entities. Their relevance is increasing, and privacy is being considered a Troy horse in software developments. In fact, privacy is a part of software architectural decisions, and they must be considered as a technical debt. The contributions of this paper are the following: a privacy debt definition with a principal and an interest, privacy‐related activities to be considered within the ISO/IEC 29110 basic profile, and the use of the net present value within this context. All these contributions help us to integrate privacy debt and VSE's software developments.
Toward a framework for risk monitoring of complex engineering systems with online operational data: A deep learning-based solution

A mathematical architecture is developed for system-level condition monitoring. This architecture is built toward performing end-to-end operation risk and condition monitoring. The streaming monitoring data is given to the architecture as the input and system-level and component-level operation health states are computed as the output. This architecture integrates fault trees as the system-level modeling method and Deep Learning (DL) as the components condition monitoring method. A number of different deep learning models are trained using both operation and maintenance data for the components. Then, the fault tree fuses the continuous components’ assessments to provide system-level health insight. The applicability of this architecture is tested by implementing it on a real-world mining stone crusher system. This approach is extendable to dynamic risk assessment of complex engineering systems. However, DL models should be used with caution for safety-critical applications. We show that having DL models with high accuracy is not enough for trusting their predictions. We discuss the calibration of DL-based condition monitoring models and demonstrate how they can improve the trustworthiness and interpretability of DL models in risk and reliability applications.
The Role and Perspective of Climate Smart Agriculture in Africa: A Scientific Review

Climate-smart agriculture (CSA) is gaining a wide acceptance as a laudable approach that can assist farmers to maximize the potential of the farming systems in Africa. A number of practices have been identified as CSA practices, and successful outcomes of CSA technologies are being reported. However, CSA uptake among African farmers remains low despite its proven potential. The aim of this paper is to analyse the state of CSA in Africa and identify the constraints to the uptake of the practices among smallholder farmers. This paper synthesizes a subset of literature between 2010 and 2020. The key findings are that the response to climate change and the pattern and extent of adoption of CSAs differs from one macro-area to another. Factors such as resource constraints, institutional instruments, climate and ecological settings, and farmers’ characteristics, such as farmers’ experience and access to extension services, are significant determinants of CSA adoption. Socioeconomic constraints, poor availability of data and mastery of CSA approach, inadequate labour, and the wide diversity of the farming systems in Africa are challenges militating CSA uptake in the system This paper argues that it is crucial to ensure that limited resources available are systematically harnessed to achieve the triple-win benefits of CSA. Furthermore, there is the need to identify and prioritize locally suitable CSA practices and provide an enabling environment needed for CSA uptake and sustenance in the African farming systems.
High-sensitivity GPS L1 signal analysis for indoor channel modelling

New applications of indoor positioning and navigation demand GPS-level performance but in environments where GPS suffers performance degradation and failures. Development of GPS technologies to function indoors requires means to validate receiver performance without the time, complexity, and cost required to field test each development. Propagation models that can accurately predict signal behaviour indoors could potentially be used in signal simulators to test hardware in the laboratory with repeatable results. A limited understanding of indoor GPS signal behaviour has prevented the creation of adequate propagation models to date. Existing models do not account for both fading and ranging errors that degrade GPS indoor performance. In this thesis, high-bandwidth raw GPS data are analyzed with high-sensitivity techniques to characterize fading and multipath characteristics in a pair of indoor environments. The measured behaviour suggests characteristics required for a novel channel model, and provides an estimate of the possible performance improvement gained in using these models as opposed to existing channel models.
The AD–AHP Planner: Incremental Path Planning for Robots Incorporating Decision Theory

Path planning for mobile robots in dynamic environments with many objectives to regard at once is challenging and often impossible. However recent outdoor robotic applications encounter many situations when such an approach is needed. This paper presents a path planning method for mobile robots that incorporates decision theory to guide the search. The method is able to handle an arbitrary number of objectives at the same time and also enables the incorporation of human logic into the planning process. All parts of the algorithm suit real– time implementation.
Efficient Nonlinear Energy Harvesting with Wrinkled Piezoelectric Membranes

Abstract We investigate the performance of a piezoelectric energy harvester with nonlinearity induced by wrinkles. Linear and nonlinear regimes are detected in the electric response of the device when sweeping the intensity of the external excitation. Those regimes are related to the activation of a nonlinear mechanical response that appears when increasing the excitation amplitude. The wrinkles have been found to improve the power density and the normalized power density, in a certain noise power range.
Understanding the Role of Surface Modification of Randomized Trabecular Titanium Structures in Bone Tissue Regeneration: An Experimental Study

Background and Objectives: Three-dimensional (3D) metallic trabecular structures made by additive manufacturing (AM) technologies promote new bone formation and osteointegration. Surface modifications by chemical treatments can improve the osteoconductive properties of metallic structures. An in vivo study in sheep was conducted to assess the bone response to randomized trabecular titanium structures that underwent a surface modification by chemical treatment compared to the bone response to the untreated specimens. Material and Methods: Sixteen specimens with a randomized trabecular titanium structure were implanted in the spongious bone of the distal femur and proximal tibia and the cortical bone of the tibial diaphysis of two sheep. Of them, eight implants had undergone a chemical treatment (treated) and were compared to eight implants with the same structure but native surfaces (native). The sheep were sacrificed at 6 weeks. Surface features of the lattice structures (native and treated) were analyzed using a 3D non-contact profilometer. Compression tests of 18 lattice cubes were performed to investigate the mechanical properties of the two structures. Excellent biocompatibility for the trabecular structures was demonstrated in vitro using a cell mouse fibroblast culture. Histomorphometric analysis was performed to evaluate bone implant contact and bone ingrowth. Results: A compression test of lattice cubic specimens revealed a comparable maximum compressive strength value between the two tested groups (5099 N for native surfaces; 5558 N for treated surfaces; p > 0.05). Compared to native surfaces, a homogenous formation of micropores was observed on the surface of most trabeculae that increased the surface roughness of the treated specimens (4.3 versus 3.2 µm). The cellular viability of cells seeded on three-dimensional structure surfaces increased over time compared to that on plastic surfaces. The histomorphometric data revealed a similar behavior and response in spongious and cortical bone formation. The percentage of the implant surface in direct contact with the regenerated bone matrix (BIC) was not significantly different between the two groups either in the spongious bone (BIC: 27% for treated specimens versus 30% for native samples) or in the cortical bone (BIC: 75% for treated specimens versus 77% for native samples). Conclusions: The results of this study reveal rapid osseointegration and excellent biocompatibility for the trabecular structure regardless of surface treatment using AM technologies. The application of implant surfaces can be optimized to achieve a strong press-fit and stability, overcoming the demand for additional chemical surface treatments.