Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrasonic-Assisted Surface Finishing of STAVAX Mold Steel Using Lab-Made Polishing Balls on a 5-Axis CNC Machining Center

The inconvenience of conventional wool ball polishing is that the surface finishing process should be equipped with a slurry container. The main objective of this research is to develop an ultrasonic-assisted surface finishing process for STAVAX mold steel on a 5-axis CNC machining center, by using new lab-made rubber polishing balls containing the abrasive aluminum oxide instead of the traditional wool ball polishing. In total, five types (type A to type E) of new rubber-matrixed polishing balls with a composite of nitrile butadiene rubber (NBR), an abrasive of aluminum oxide, and an additive of silicon dioxide have been developed. The performance of the composites with different grain sizes (0.05 μm to 3 μm) and concentrations of the abrasive of aluminum oxide have been investigated. The effects of multiple polishing passes on the surface roughness improvement for the lab-made polishing balls have also been investigated in this study. A surface roughness of Ra 0.027 μm on average was achieved by using the multiple polishing process of E-C-B-A. The volumetric wear of the lab-made polishing balls, using ultrasonic vibration-assisted polishing, can be improved from about 12.64% (type A) to 65.48% (type E) compared with the non-vibration-assisted polishing. The suitable combination of the ultrasonic vibration-assisted polishing parameters were an amplitude of 10 μm, a frequency of 23 kHz, a spindle speed of 5000 rpm, a feed rate of 60 mm/min, a stepover of 20 μm, a penetration depth of 180 μm, and a polishing pass of E-C-B-A, based on the experimental results. The surface roughness improvement on a test carrier with a saddle surface has also been presented by using the ultrasonic vibration-assisted polishing with the lab-made polishing balls.
Corporate governance systems and financial risks: A developing country evidence

Banks are one of the essential pillars of the financial sector (Alzuod & Alqhaiwi, 2022), however, banking is a high-risk industry (de Andres & Vallelado, 2008). The aim of this paper is to investigate the impact of the board’s structure and ownership structure on the financial risks of Jordanian commercial banks. Data was gathered manually from the financial reports. Notably, the study addressed two types of financial risks: liquidity risk and credit risk. The study sample included commercial banks listed on the Amman Stock Exchange (ASE) to cover the period 2014–2019. To achieve the study’s objectives, multiple regression analysis was run to test the hypotheses. The results reveal a negative, statistically significant impact of the board size, institutional ownership, and bank size on liquidity risk. The results also demonstrated a negative effect of board independence, ownership concentration, bank size, and CEO duality on credit risk. In sum, the results support previous studies that found a statistically significant role of corporate governance mechanisms in reducing financial risks. The study recommended the need to enhance foreign investment and institutional ownership.
Clinical characteristics of COVID-19 in patients with tuberculosis and factors associated with the disease severity

Background: Data on patients with COVID-19 who have pulmonary tuberculosis (TB) are limited. In this study, we compared the clinical characteristics of patients with COVID-19/TB and patients with COVID-19 only. In addition, we analyzed the links between the severity of COVID-19 disease and the clinical characteristics of patients with COVID-19/TB. Methods: We conducted a retrospective, anonymized, cross-sectional study of 111 patients who met in- clusion criteria for analysis (75 patients with COVID-19/TB and 36 patients with COVID-19). Results: Patients in both groups (COVID-19/TB vs COVID-19) mainly suffered from fever (72.0% vs 100%, p < 0.001), fatigue (76.0% vs 94.4%, p = 0.018), chest pain (72.0% vs 36.1%, p < 0.001), followed by cough (60.0% vs 97.2%, p < 0.001) and dyspnea (44.0% vs 63.9%, p = 0.05). In group COVID-19/TB the most frequently reported co-morbidities were chronic liver disease (17 [22.7%]), cardiovascular diseases (25 [33.3%]), and diseases of the nervous system (13 [17.3%]). Female gender, fever, dyspnea, pulmonary bilateral TB lesion, and three or more co-morbidities have a statistically signiﬁcant positive effect on the severity of the disease among patients with COVID-19/TB. Conclusion: It is important to perform rapid molecular testing and computed tomography to correctly distinguish COVID-19 and TB because of the similar clinical characteristics of both diseases. Bilateral pul- monary TB lesion and co-morbidity should be considered risk factors for severe COVID-19.
A Learning Approach to Minimum Delay Routing in Stochastic Queueing Networks

We consider the minimum delay routing problem in stochastic queueing networks where the goal is to find the optimal static routing policy that minimizes the average delay in the network. Previous works on minimum delay routing rely on knowledge of the delay function that maps the routing policies to their corresponding average delay, which is typically unavailable in stochastic queueing networks due to the complex dependency of the delay function on the distributional characteristics of network links. In this paper, we propose a learning approach to the minimum delay routing problem, whereby instead of relying on aprior information on the delay function, we seek to learn the delay function through observations. We design an algorithm that leverages finite-time observations of network queue lengths to approximate the values of the delay function, uses the approximate values to estimate the gradient of the delay function, and performs gradient descent based on the estimated gradient to optimize the routing policy. We prove that our algorithm converges to the optimal static routing policy when the delay function is convex, which is a reasonable condition in practical settings. We conduct extensive simulations to evaluate the empirical performance of our algorithm, demonstrating its superior delay performance over static policies and even dynamic policies such as Join-the-Shortest-Queue and BackPressure.
Biodegradation of Polycyclic Aromatic Hydrocarbons by Arthrobacter sp. UG50 Isolated from Petroleum Refinery Wastes

BIODEGRADATION OF POLYCYCLIC AROMATIC HYDROCARBONS BY ARTHROBACTER SP. UG50 ISOLATED FROM PETROLEUM REFINERY WASTES Elisabeth Koch Advisors: Dr. Jack T. Trevors University of Guelph, 2011 Dr. Hung Lee Dr. Les Stehmeier North American petroleum refineries use landfarming to dispose of hydrocarboncontaining wastes for bioremediation by indigenous soil microorganisms. In this study, we isolated PAH-degrading bacteria from landfarm soil by enrichment with hydrocarbon-containing effluent. One isolate, Arthrobacter sp. UG50, was capable of using phenanthrene and anthracene as sole carbon sources. The strain degraded phenanthrene (200 mg/L) within 24 h in pure culture at high cell density (10 8 cells/mL). Anthracene (50 mg/L) was slowly degraded, with 29% degraded within 21 days. The strain could not use naphthalene, pyrene, chrysene or benzo(a)pyrene as sole carbon sources, but could degrade pyrene (50 mg/L) cometabolically when phenanthrene was provided. Anthracene degradation (50 mg/L) was enhanced by phenanthrene, with 100% degraded within 6 days. The addition of strain UG50 to petroleum sludge in baffled flasks increased total hydrocarbon degradation and degradation of low concentrations of fluorene, phenanthrene, pyrene and chrysene compared to flasks with limited aeration or containing sludge alone.
Effect of Betulin Colloidal Particles on Proliferation and Cytokine Secretion of Human Skin Fibroblasts

The aim of the study was to obtain untreated and treated betulin colloidal particles and assess their effect on the viability, morphology, proliferation and cytokine secretion of human dermal fibroblasts. To improve bioavailability, betulin treatment was performed by an antisolvent precipitation technique. The average particle size after treatment in the aqueous dispersion decreased from 552.9 ± 11.3 to 278.2 ± 1.6 nm. Treated betulin colloidal particles showed no cytotoxicity up to a concentration of 400 µg·mL−1 in the colorimetric tetrazolium salt viability test (CCK-8). Moreover, the cell morphology was not changed in the presence of betulin colloidal particles at a concentration range from 0.78 to 400 µg·mL−1. The obtained results also show that betulin particles induce the secretion of the proinflammatory and angiogenesis-stimulating cytokine IL-8. However, further studies would be required to clarify the mechanism of IL-8 secretion induction.
The unity hypothesis revisited: can the male/female incongruent McGurk effect be disrupted by familiarization and priming?

The unity assumption hypothesis contends that higher-level factors, such as a perceiver’s belief and prior experience, modulate multisensory integration. The McGurk illusion exemplifies such integration. When a visual velar consonant /ga/ is dubbed with an auditory bilabial /ba/, listeners unify the discrepant signals with knowledge that open lips cannot produce /ba/ and a fusion percept /da/ is perceived. Previous research claimed to have falsified the unity assumption hypothesis by demonstrating the McGurk effect occurs even when a face is dubbed with a voice of the opposite sex, and thus violates expectations from prior experience. But perhaps stronger counter-evidence is needed to prevent perceptual unity than just an apparent incongruence between unfamiliar faces and voices. Here we investigated whether the McGurk illusion with male/female incongruent stimuli can be disrupted by familiarization and priming with an appropriate pairing of face and voice. In an online experiment, the susceptibility of participants to the McGurk illusion was tested with stimuli containing either a male or female face with a voice of incongruent gender. The number of times participants experienced a McGurk illusion was measured before and after a familiarization block, which familiarized them with the true pairings of face and voice. After familiarization and priming, the susceptibility to the McGurk effects decreased significantly on average. The findings support the notion that unity assumptions modulate intersensory bias, and confirm and extend previous studies using male/female incongruent McGurk stimuli.
SDN Application Backdoor: Disrupting the Service via Poisoning the Topology

Software-Defined Networking (SDN) enables the deployment of diversified networking applications by providing global visibility and open programmability on a centralized controller. As SDN enters its second decade, several well-developed open source controllers have been widely adopted in industry, and various commercial SDN applications are built to meet the surging demand of network innovation. This complex ecosystem inevitably introduces new security threats, as malicious applications can significantly disrupt network operations. In this paper, we introduce a new vulnerability in existing SDN controllers that enable adversaries to create a backdoor and further deploy malicious applications to disrupt network service via a series of topology poisoning attacks. The root cause of this vulnerability is that SDN systems simply process received Packet-In messages without checking the integrity, and thus can be misguided by manipulated messages. We discover that five popular SDN controllers (i.e., Floodlight, ONOS, OpenDaylight, POX and Ryu) are potentially vulnerable to the disclosed attack, and further propose six new attacks exploiting this vulnerability to disrupt SDN services from different layers. We evaluate the effectiveness of these attacks with experiments in real SDN testbeds, and discuss feasible countermeasures.
Rutaecarpine Ameliorates Murine N-Methyl-N’-Nitro-N-Nitrosoguanidine-Induced Chronic Atrophic Gastritis by Sonic Hedgehog Pathway

CAG is a burdensome and progressive disease. Numerous studies have shown the effectiveness of RUT in digestive system diseases. The therapeutic effects of RUT on MNNG-induced CAG and the potential mechanisms were probed. MNNG administration was employed to establish a CAG model. The HE and ELISA methods were applied to detect the treatment effects. WB, qRT-PCR, immunohistochemistry, TUNEL, and GES-1 cell flow cytometry approaches were employed to probe the mechanisms. The CAG model was successfully established. The ELISA and HE staining data showed that the RUT treatment effects on CAG rats were reflected by the amelioration of histological damage. The qRT-PCR and WB analyses indicated that the protective effect of RUT is related to the upregulation of the SHH pathway and downregulation of the downstream of apoptosis to improve gastric cellular survival. Our data suggest that RUT induces a gastroprotective effect by upregulating the SHH signaling pathway and stimulating anti-apoptosis downstream.
Renal Denervation as a Complementary Treatment Option for Uncontrolled Arterial Hypertension: A Situation Assessment

Uncontrolled arterial hypertension is a major global health issue. Catheter-based renal denervation has shown to lower blood pressure in sham-controlled trials and represents a device-based, complementary treatment option for hypertension. In this situation assessment, the authors, who are practicing experts in hypertension, nephrology, general practice and cardiology in the Republic of Ireland, discuss the current evidence base for the BP-lowering efficacy and safety of catheter-based renal denervation with different modalities. Although important questions remain regarding the identification of responders, and long-term efficacy and safety of the intervention, renal denervation has the potential to provide much-needed help to address hypertension and its adverse consequences. The therapeutic approach needs to be multidisciplinary and personalised to take into account the perspective of patients and healthcare professionals in a shared decision-making process.
Deep Convolutional Neural Networks and Transfer Learning Based Approach for Lung Cancer Detection from CT Scan Images

A recent WHO survey ranked lung cancer as the second most frequent reason for death worldwide. As a result, early detection of lung cancer has become essential, as early detection can save many lives. Modern approaches to deep learning and image processing have made the detection and treatment of lung cancer much more straightforward. The ability of convolutional neural networks (CNNs) and transfer learning-based models to identify Cancer from CT scan pictures are investigated in this research. Deep CNN models already trained, like ResNet50, MobileNetV2, and VGG19, were employed to extract the deep features. Two datasets were collected and merged to increase training and validation datasets. MobileNetV2 had a 97% accuracy rate. VGG19 had an almost 100% accuracy rate, but the Model suffered from overfitting. ResNet50 had a 78% accuracy rate, and CNN had 99% accuracy with overfitting issues. Among these networks, MobileNetV2 provided the highest level of accuracy with less overfitting compared to other models. These accuracies assist in detecting malignancies early before they cause physical side effects such as paralysis and other complications.
Pre-service Primary Teachers’ Views about Scientific Inquiry

While scientific inquiry is a critical goal in science education reform, worldwide research indicates that students and educators misunderstand it. The present study investigates the scientific inquiry views of 170 senior-year pre-service primary school teachers using the VASI (Views About Scientific Inquiry) questionnaire. This standardized tool assesses learners’ understanding of scientific inquiry. The analysis of student responses demonstrates that the sampled pre-service primary education teachers hold naïve views on several aspects of scientific inquiry. Findings show that participants seem to have difficulty understanding that scientific inquiry begins with a question and are unclear on whether a single procedure generates the same results or if scientific data is equivalent to scientific evidence. The inability of pre-service teachers to understand scientific inquiry confirms a lack of general consideration of its process, raising doubt over the opportunities for learners to adopt and engage in scientific inquiry. Consequently, the implications of curriculum reform are discussed.
Distributed robust‐multivariate‐observer‐based FDI attacks estimation for nonlinear multi‐agent systems with directed graphs

This article investigates the distributed robust estimation problem for false data injection (FDI) attacks in nonlinear multi‐agent systems with directed graphs. To approximate the realistic attack scenario, the case where both the actuator network channel and sensor network channel suffering from FDIs are considered, and the attack signals contain time‐varying circumstances. A novel distributed robust‐multivariate‐observer (DRMO) strategy is developed such that the online estimation of FDI attack dynamics can be realized with the partially unknown nonlinear dynamics, attack transient increments, and disturbances impact being eliminated. The designed DRMO scheme only depends on the received compromised/uncompromised measurement output information on the account that whole state information cannot be measured directly. Finally, two simulation examples, including a network of four one‐link flexible joint manipulator systems with comparisons to existing methods, are given to show the effectiveness of the proposed scheme.
FacER: Contrastive Attention based Expression Recognition via Smartphone Earpiece Speaker

Facial expression recognition has enormous potential for downstream applications by revealing users’ emotional status when interacting with digital content. Previous studies consider using cameras or wearable sensors for expression recognition. However, these approaches bring considerable privacy concerns or extra device burdens. Moreover, the recognition performance of camera-based methods deteriorates when users are wearing masks. In this paper, we propose FacER, an active acoustic facial expression recognition system. As a software solution on a smartphone, FacER avoids the extra costs of external microphone arrays. Facial expression features are extracted by modeling the echoes of emitted near-ultrasound signals between the earpiece speaker and the 3D facial contour. Besides isolating a range of background noises, FacER is designed to identify different expressions from various users with a limited set of training data. To achieve this, we propose a contrastive external attention-based model to learn consistent expression features across different users. Extensive experiments with 20 volunteers with or without masks show that FacER can recognize 6 common facial expressions with more than 85% accuracy, outperforming the state-of-the-art acoustic sensing approach by 10% in various real-life scenarios. FacER provides a more robust solution for recognizing facial expressions in a convenient and usable manner.
Vulnerable narcissistic leadership meets Covid-19: the relationship between vulnerable narcissistic leader behaviour and subsequent follower irritation

ABSTRACT Leaders’ vulnerable narcissism may cause followers irritation due to its antagonistic and neurotic nature. Based on conservation of resources theory, we propose and test a model of between-person and reciprocal within-person relations between weekly experiences of vulnerable narcissistic leader behaviours (VNLB) and followers’ irritation in subsequent weeks. We argue that in time of crisis and uncertainty, such as the COVID-19 pandemic and the lockdowns related to it, VNLB adds to follower irritation. We drew a sample from a population affected by workplace uncertainty, that is, the UK education sector during the first weeks of the Covid pandemic (N = 159). Five weeks of longitudinal data were collected. We conducted a random intercepts cross-lagged panel model and separated within- from between-person sources of variance in VNLB and follower irritation. Our findings show that VNLB positively related to follower irritation at the between-person level. The relationships at the within-person level of analysis were less clear. Experiences of VNLB resulted in follower irritation in subsequent weeks for some of the time lags, but not for others. We find limited indicators for a reciprocal relationship between VNLB and irritation. We discuss implications and link our findings to the study context of COVID-19 pandemic.
Meta-analysis of Shugan Jieyu Capsule for depression in patients with coronary heart disease

Introduction: Shugan Jieyu Capsule (SGJYC) has been prescribed to treat primary and secondary depression; however, whether it can benefit depression of patients with coronary heart disease (CHD) remains controversial. This meta-analysis aimed to evaluate the efficacy and safety of SGJYC in treating depression in patients with CHD. Patient concerns: A total of 644 CHD patients with depression were selected from China National Knowledge Infrastructure, Wanfang, China Biomedical Database, MEDLINE, the Cochrane library from their inceptions until June, 2021. Diagnosis: All patients with CHD or coronary artery disease were confirmed to suffer from depression based on recognized criteria. Intervention: Patients were assigned randomly to receive SGJYC-based regimens or conventional antidepressants alone. Outcomes: Meta-analysis of 6 studies showed that antidepressants (MD, 2.12; 95% confidence interval [CI], 0.73~3.50) or sertraline (MD, 2.15; 95%CI, 0.61~3.68) significantly alleviated depression level compared to SGJYC; however, SGJYC plus antihypertensive drugs (AHD) (MD, −8.33; 95%CI, −13.90 ~ −2.75) significantly improved depression symptoms compared to AHD. A significant difference in risk of adverse cardiac events (risk ratios [RR], 2.72; 95%CI, 1.07~6.94) between SGJYC and sertraline was detected in patients with simple CHD. Conclusions: SGJYC has a poor effect on depressive symptoms, and the effect of combination with AHD is better than AHD but its efficacy and cardiac safety are inferior to antidepressants.
Cellular Changes in Injured Rat Spinal Cord Following Electrical Brainstem Stimulation

Spinal cord injury (SCI) is a major cause of disability and pain, but little progress has been made in its clinical management. Low-frequency electrical stimulation (LFS) of various anti-nociceptive targets improves outcomes after SCI, including motor recovery and mechanical allodynia. However, the mechanisms of these beneficial effects are incompletely delineated and probably multiple. Our aim was to explore near-term effects of LFS in the hindbrain’s nucleus raphe magnus (NRM) on cellular proliferation in a rat SCI model. Starting 24 h after incomplete contusional SCI at C5, intermittent LFS at 8 Hz was delivered wirelessly to NRM. Controls were given inactive stimulators. At 48 h, 5-bromodeoxyuridine (BrdU) was administered and, at 72 h, spinal cords were extracted and immunostained for various immune and neuroglial progenitor markers and BrdU at the level of the lesion and proximally and distally. LFS altered cell marker counts predominantly at the dorsal injury site. BrdU cell counts were decreased. Individually and in combination with BrdU, there were reductions in CD68 (monocytes) and Sox2 (immature neural precursors) and increases in Blbp (radial glia) expression. CD68-positive cells showed increased co-staining with iNOS. No differences in the expression of GFAP (glia) and NG2 (oligodendrocytes) or in GFAP cell morphology were found. In conclusion, our work shows that LFS of NRM in subacute SCI influences the proliferation of cell types implicated in inflammation and repair, thus providing mechanistic insight into deep brain stimulation as a neuromodulatory treatment for this devastating pathology.