Miracle-dz/UniFAR-FTUs huggingface dataset:
Corrosion Resistance of 3D Printed Ti6Al4V Gyroid Lattices with Varying Porosity

Corrosion of medical implants is a possible failure mode via induced local inflammatory effects, systemic deposition and corrosion related mechanical failure. Cyclic potentiodynamic polarisation (CPP) testing was utilized to evaluate the effect of increased porosity (60% and 80%) and decreased wall thickness in gyroid lattice structures on the electrochemical behaviour of LPBF Ti6Al4V structures. The use of CPP allowed for the landmarks of breakdown potential, resting potential and vertex potential to be analysed, as well as facilitating the construction of Tafel plots and qualitative Goldberg analysis. The results indicated that 60% gyroid samples were most susceptible to the onset of pitting corrosion when compared to 80% gyroid and solid samples. This was shown through decreased breakdown and vertex potentials and were found to correlate to increased lattice surface area to void volume ratio. Tafel plots indicated that despite the earlier onset of pitting corrosion, both gyroid test groups displayed lower rates of corrosion per year, indicating a lower severity of corrosion. This study highlighted inherent tradeoffs between lattice optimisation and corrosion behaviour with a potential parabolic link between void volume, surface area and corrosion being identified. This potential link is supported by 60% gyroid samples having the lowest breakdown potentials, but investigation into other porosity ranges is suggested to support the hypothesis. All 3D printed materials studied here showed breakdown potentials higher than ASTM F2129′s suggestion of 800 mV for evaluation within the physiological environment, indicating that under static conditions pitting and crevice corrosion should not initiate within the body.
Generation and stabilization of millimeter-wave signal employing frequency-quadrupling phase-locked optoelectronic oscillator

A novel scheme for the generation and stabilization of the millimeter-wave (mmW) signal is theoretically analyzed and experimentally demonstrated. By using the microwave photonics frequency-quadrupling technology and phase-locked optoelectronic oscillator, we generate the millimeter-wave signal with low phase noise and high stability without the frequency limitation of the electrical phase detector and the voltage-controlled microwave phase shifter. Finally, a 40-GHz mmW signal with the stability of 1.38 × 10−12 at the average time of 100 s is generated. The spurious suppression ratio reaches 97 dB, and the measured single-sideband phase noise is lower than -103 dBc/Hz at 10-kHz offset frequency.
Parasitism of Brook Trout (Salvelinus fontinalis) during the first month post-emergence in streams in southwest Nova Scotia

Parasite recruitment of recently emerged fry of brook trout (Salvelinus fontinalis) in three streams in southwestern Nova Scotia was documented. In early April, fry appeared to leave the protective gravel redds parasite free but began acquiring parasites within the next 2-4 weeks, with prevalence of infections of any given species reaching 21 to 46% by mid-May. The initial infections involved 1) directly transmitted ectoparasites Gyrodactylus colemanensis and Salmincola edwardsii and 2) food-borne endoparasites (Echinorhynchus lateralis and Crepidostomum sp.). Colonizing parasites found in the first month post-emergence varied by locality: at Bangor Creek, it involved G. colemanensis, E. lateralis, and Crepidostomum sp. , while at Germaine East, it involved only G. colemanensis and at Germaine North, only S. edwardsii. In each case, the initial colonizers reflected what was abundant locally and within a regional pool of 10 parasite species. Localized skin thickening and sometimes tissue erosion were evident at sites of attachment of S. edwardsii. Minor disruption of fin margins was seen with G. colemanensis. No pathology was associated with E. lateralis nor Crepidostomum sp. The predictable timing of emergence and ease of sampling fry of S. fontinalis near redds represents a convenient system with which to assess impact of initial parasitism on fish recruitment at the local level. Keywords: Echinorhynchus, Gyrodactylus, initial parasite colonization, regional parasite pool, Salmincola
Subclass Knowledge Distillation with Known Subclass Labels

This work introduces a novel knowledge distillation framework for classification tasks where information on existing subclasses is available and taken into consideration. In classification tasks with a small number of classes or binary detection, the amount of information transferred from the teacher to the student is restricted, thus limiting the utility of knowledge distillation. Performance can be improved by leveraging information of possible subclasses within the classes. To that end, we propose the so-called Subclass Knowledge Distillation (SKD), a process of transferring the knowledge of predicted subclasses from a teacher to a smaller student. Meaningful information that is not in the teacher’s class logits but exists in subclass logits (e.g., similarities within classes) will be conveyed to the student through the SKD, which will then boost the student’s performance. Analytically, we measure how much extra information the teacher can provide the student via the SKD to demonstrate the efficacy of our work. The framework developed is evaluated in clinical application, namely colorectal polyp binary classification. It is a practical problem with two classes and a number of subclasses per class. In this application, clinician-provided annotations are used to define subclasses based on the annotation label’s variability in a curriculum style of learning. A lightweight, low-complexity student trained with the SKD framework achieves an F1-score of 85.05%, an improvement of 1.47%, and a 2.10% gain over the student that is trained with and without conventional knowledge distillation, respectively. The 2.10% F1-score gap between students trained with and without the SKD can be explained by the extra subclass knowledge, i.e., the extra 0.4656 label bits per sample that the teacher can transfer in our experiment. The SKD framework can benefit from using more information to increase student performance, but it comes at the expense of the availability of subclass labels.
Identification of Reference Genes for RT-qPCR Analysis in Gleditsia microphylla under Abiotic Stress and Hormone Treatment

Gleditsia microphylla is an important galactomannan gums source plant with characteristics of drought resistance, barren tolerance, and good adaptability. However, the underlying molecular mechanisms of the biological process are not yet fully understood. Real-time quantitative PCR (RT-qPCR) is an accurate and convenient method to quantify the gene expression level and transcription abundance of suitable reference genes. This study aimed to screen the best internal reference genes in G. microphylla under abiotic stresses, hormone treatments, and different tissues. Based on the transcriptome data, twelve candidate reference genes were selected, and ultimately, nine of them were further evaluated by the geNorm, NormFinder, BestKeeper, and RefFinder algorithms. These results show that TATA-binding protein 1 (TBP1)and Eukaryotic translation initiation factor 4A1 (EIF4A1)were the two most stable reference genes, and glyceraldehyde-3-phosphate dehydrogenase A subunit, chloroplastic (GAPA)and glyceraldehyde-3-phosphate dehydrogenase B subunit, chloroplastic (GAPB)were the two most unstable reference genes across all samples under the given experimental conditions. Meanwhile, the most stable reference genes varied among the different groups and tissues. Therefore, this study suggests that it is better to use a specific reference gene for a particular case rather than using a common reference gene.
effect of the simple moving average on the movement of bank stock prices applied research in a sample of Iraqi private commercial banks

This study aims to identify one of the indicators of technical analysis, which is the simple moving average (SMA), and its impact on the movement of stock prices in private Iraqi commercial banks, by standing on the methods used in technical analysis and its various Models in general, and ways to benefit from them in determining the direction of stock prices in order to make the appropriate investment decision to buy or sell, diagnose the obstacles and difficulties that the participants face in predicting stock prices, and propose solutions and recommendations to overcome and overcome them from a scientific and practical perspective. Where the research community consisted of (25) Iraqi private commercial banks, while the research sample consisted of (5) banks with a rate of (20%) of the research community. The study used the analytical approach to the financial statements during the period between (1/2/ 2022-30/4/2022, where the financial data (banks stock prices) were calculated through the mathematical equation of the Simple Moving Average Index (SMA)) .
The impact of paleoclimatic changes on body size evolution in marine fishes

Significance General rules are useful tools for understanding how organisms evolve. Cope’s rule (tendency to increase in size over evolutionary time) and Bergmann’s rule (tendency to grow to larger sizes in cooler climates) both relate to body size, an important factor that affects the biology, ecology, and physiology of organisms. These rules are well studied in endotherms but remain poorly understood among ectotherms. Here, we show that paleoclimatic changes strongly shaped the trajectory of body size evolution in tetraodontiform fishes. Their body size evolution is explained by both Cope’s and Bergmann’s rules, highlighting the impact of paleoclimatic changes on aquatic organisms, which rely on their environment for temperature regulation and are likely more susceptible than terrestrial vertebrates to climatic changes.
Detection of Ventricular Fibrillation Using the Image from Time-Frequency Representation and Combined Classifiers without Feature Extraction

Due the fact that the required therapy to treat Ventricular Fibrillation (V F) is aggressive (electric shock), the lack of a proper detection and recovering therapy could cause serious injuries to the patient or trigger a ventricular fibrillation, or even death. This work describes the development of an automatic diagnostic system for the detection of the occurrence of V F in real time by means of the time-frequency representation (T F R) image of the ECG. The main novelties are the use of the T F R image as input for a classification process, as well as the use of combined classifiers. The feature extraction stage is eliminated and, together with the use of specialized binary classifiers, this method improves the results of the classification. To verify the validity of the method, four different classifiers in different combinations are used: Regression Logistic with L2 Regularization (L 2 R L R), adaptive neural network (A N N C), Bagging (B A G G), and K-nearest neighbor (K N N). The Hierarchical Method (HM) and Voting Majority Method (VMM) combinations are used. ECG signals used for evaluation were obtained from the standard MIT-BIH and AHA databases. When the classifiers were combined, it was observed that the combination of B A G G , K N N , and A N N C using the Hierarchical Method (HM) gave the best results, with a sensitivity of 95.58 ± 0.41%, a 99.31 ± 0.08% specificity, a 98.6 ± 0.04% of overall accuracy, and a precision of 98.25 ± 0.29% for V F . Whereas a sensitivity of 94.02 ± 0.58%, a specificity of 99.31 ± 0.08%, an overall accuracy of 99.14 ± 0.43%, and a precision of 98.59 ± 0.09% was obtained for V T with a run time between 0.07 s and 0.12 s. Results show that the use of T F R image data to feed the combined classifiers yields a reduction in execution time with performance values above to those obtained by individual classifiers. This is of special utility for V F detection in real time.
The Relationship of Physical Activity and Dietary Quality with Android Fat Composition and Distribution in US Adults

This study examined the relationship of physical activity (PA) and dietary quality to android fat composition and distribution using a national representative adult sample and determined sex-based differences in these relationships. It is a cross-sectional (n = 10,014) analysis of the 2011–2018 National Health and Nutrition Examination Survey and the US department of Agriculture’s Food Patterns Equivalents datasets. Variables utilized for this analysis include PA, 24-h dietary recalls, android percent fat, and android-gynoid (A/G) ratio measured by dual-energy X-ray absorptiometry. Multiple linear regression was performed to examine the relationship between PA and/or dietary quality and android percent fat and A/G ratio adjusted for confounding factors. The study results revealed that PA and/or dietary quality were inversely related to android percent fat and A/G ratio (p < 0.05), but the sex effect was only seen between PA and A/G ratio (p = 0.003). Participants who met PA recommendations and had higher dietary quality had 2.12% lower android fat than those who did not meet PA recommendations and had lower dietary quality (p < 0.001). Both PA and dietary quality are associated with android fat reduction regardless of sex. Given the direct connection between android fat and cardiovascular and metabolic diseases, it is important to increase both PA and dietary quality.
INFLUENCE OF DIFFERENT THERMAL ENVIRONMENTS ON THE PERFORMANCE OF LAYING HENS DURING THE INITIAL STAGE OF REARING

This study was conducted with the aim of assessing the effects of different ambient temperature values on the performance of laying birds from one to 42 days of age in order to obtain optimal comfort temperatures. A total of 864 laying hens were distributed in four climatic chambers with different temperature ranges. One of the chambers was maintained within the thermal range recommended by the literature and the others were maintained under temperatures that consisted of mild and moderate cold stress and moderate heat stress. The experiment was conducted according to a completely randomized design in a split-plot arrangement and six replications. The data were analyzed by means of the analysis of variance and regression. The final performance of birds with temperatures of 33, 28, 26, 23, 19, and 19 °C (for the first, second, third, fourth, fifth, and sixth week of age, respectively) presented better productive results, confirming the assertiveness regarding the best thermal comfort and welfare of laying birds during the rearing stage. The results showed that under conditions of cold thermal stress, birds presented a worse performance, thus affecting their development and productive efficiency.
Unravelling the Distinct Effects of Systolic and Diastolic Blood Pressure Using Mendelian Randomisation

A true discrepancy between the effect of systolic blood pressure (SBP) and diastolic blood pressure (DBP) on cardiovascular (CV) outcomes remains unclear. This study performed two-sample Mendelian randomization (MR) using genetic instruments that exclusively predict SBP, DBP or both to dissect the independent effect of SBP and DBP on a range of CV outcomes. Genetic predisposition to higher SBP and DBP was associated with increased risk of coronary artery disease (CAD), myocardial infarction (MI), stroke, heart failure (HF), atrial fibrillation (AF), chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM). Genetically proxied SBP exclusively was associated with CAD (OR 1.18, 95% CI: 1.03–1.36, per 10 mmHg), stroke (1.44[1.28–1.62]), ischemic stroke (1.49[1.30–1.69]), HF (1.41[1.20–1.65]), AF (1.28[1.15–1.43]), and T2DM (1.2[1.13–1.46]). Genetically proxied DBP exclusively was associated with stroke (1.21[1.06–1.37], per 5 mmHg), ischemic stroke (1.24[1.09–1.41]), stroke small-vessel (1.35[1.10–1.65]) and CAD (1.19[1.00–1.41]). Multivariable MR using exclusive SBP and DBP instruments showed the predominant effect of SBP on CAD (1.23[1.05–1.44], per 10 mmHg), stroke (1.39[1.20–1.60]), ischemic stroke (1.44[1.25–1.67]), HF (1.42[1.18–1.71]), AF (1.26[1.10–1.43]) and T2DM (1.31[1.14–1.52]). The discrepancy between effects of SBP and DBP on outcomes warrants further studies on underpinning mechanisms which may be amenable to therapeutic targeting.
Power System Inertia Estimation Using A Residual Neural Network Based Approach

The increasing penetration of non-synchronous generation into power grids is reducing the equivalent system inertia and leading to different frequency regulation and control challenges. Consequently, the monitoring and quantification of this inertia to implement actions that can keep it above critical levels have become a key issue for the stability of power systems. In this regard, a residual neural network (ResNet) based alternative is proposed and investigated in this paper to estimate the equivalent inertia of a sample system when synchronous generating units are displaced by converter-interfaced generators. The proposed ResNet model is trained according to the frequency of the center of inertia and the corresponding computed rates of change of frequency for a predefined time interval, where sudden generation outages and load step changes are considered under variations of total load demand and equivalent inertia reductions. The accuracy of the proposed approach is compared against the one achieved with the application of two traditional machine learning techniques, such as Support Vector Machine and Random Forest.
Development of Pump and Valves Combined Hydraulic System for Both High Tracking Precision and High Energy Efficiency

Generally, the valve controlled electro-hydraulic systems are able to achieve high motion tracking precision, but suffer from large amount of throttling losses. As an alternative, although the direct pump controlled systems are highly energy efficient, it is far more complicated to attain high tracking precision. In order to achieve both objectives of high precision tracking performance and high energy efficiency, a kind of novel pump and valve combined electro-hydraulic system is developed in this paper. The basic working principles are that the pump supplies the majority amount of flow driving the actuator in a highly efficient way, while the valves are involved to ensure the tracking precision. The controller with four parts is designed to handle the challenges from not only the common nonlinear properties of the hydraulic system, but also the additional flexibilities brought by the hardware combination. Two sets of comparative experiments are conducted to show the advantages of the proposed method by tracking both slow and fast motion reference trajectories. The results indicate that the proposed system is able to realize the same high level of tracking precision as the valve control method, but consumes about 35%–47% less of energy.
Classification of Many Abnormal Events in Radial Distribution Feeders Using the Complex Morlet Wavelet and Decision Trees

Monitoring of abnormal events in a distribution feeder by using a single technique is a challenging task. A number of abnormal events can cause unsafe operation, including a high impedance fault (HIF), a partial breakdown to a cable insulation, and a circuit breaker (CB) malfunction due to capacitor bank de-energization. These abnormal events are not detectable by conventional protection schemes. In this paper, a new technique to identify distribution feeder events is proposed based on the complex Morlet wavelet (CMW) and on a decision tree (DT) classifier. First, the event is detected using CMW. Subsequently, a DT using event signatures classifies the event as normal operation, continuous and non-continuous arcing events (C.A.E. and N.C.A.E.). Additional information from the supervisory control and data acquisition (SCADA) can be used to precisely identify the event. The proposed method is meticulously tested on the IEEE 13- and IEEE 34-bus systems and has shown to correctly classify those events. Furthermore, the proposed method is capable of detecting very high impedance incipient faults (IFs) and CB restrikes at the substation level with relatively short detection time. The proposed method uses only current measurements at a low sampling rate of 1440 Hz yielding an improvement of existing methods that require much higher sampling rates.
Corporate Governance research in Ghana through bibliometric method: review of existing literature

Abstract There has been a growing concern about corporate governance (CG) studies in Ghana amongst various scholars, but the same cannot be said of a specific discipline area. Therefore, this paper presents a review of research through the Scopus database. The objective is to use bibliometric analysis and VOSviewer network visualisation to explore multiple subject areas and provide the current state of CG research to understand the evolving trend of the research field through existing literature. In addition, it aims to use the scientific method to identify hotspot keywords direction, impactful corporate governance studies direction and provide some additional insight into the summary findings for future research. The study contributes to the extant literature by focusing on annual production, author’s network collaboration, journals, keywords co-occurrence, and impactful CG articles in Ghana. We found bibliometric analysis and network collaboration have uncovered the critical research domain and given more meaningful results. Moreover, research interest in corporate governance studies in Ghana has grown by yearly production, authors production, and citations. In addition, summary results find hotspot keywords are corporate social responsibility, corporate ownership, and firm performance. Furthermore, 40 papers resulted as most impactful and provided board structure and firm performance are the trending topics mostly studiedOn the other hand, a few keywords search areas are compliance, political connection, mandatory and voluntary disclosures, dividends, audit committee, and gender diversity.
BR-CIM: An Efficient Binary Representation Computation-In-Memory Design

Deep neural network (DNN) has recently attracted tremendous attention in various fields. But the computing operation requirement and the memory bottleneck limit the energy efficiency of hardware implementations. Binary quantization is proposed to relieve the pressure of hardware design. And the Computing-In-Memory (CIM) is regarded as a promising method to resolve the memory wall challenge. However, the binary computing paradigm is mismatched with the CIM scheme, which incurs complex circuits and peripheral to realize binary operation in previous works. To overcome previous issues, this work presents Binary Representation Computation-In-Memory (BR-CIM) with several key features. (1) A lightweight computation unit is realized within the 6T SRAM array to accelerate binary computing and enlarge signal margin; (2) The reconfigurable computing scheme and mapping method support extendable bit precision to satisfy the accuracy requirement of various applications; (3) Simultaneous computing and weight loading is supported by column circuitry, which shortens the data loading latency; Several experiments are conducted to estimate algorithm accuracy, the computing latency, and power consumption. The energy efficiency reaches up to 1280 TOPs/W for binary representation. And the algorithm accuracy achieves 97.82%/76.4% on MNIST/CIFAR-100 dataset.