Miracle-dz/UniFAR-FTUs huggingface dataset:
Carbon nanotube/glycerol embedded low cost flexible sensor for large deflection sensing of continuum manipulators

Large deflection sensing is highly crucial for proper positioning and control of continuum robots during robot assisted minimally invasive surgery (MIS). Existing techniques suffer from eletromagnetic noise susceptibility, harmful radiation exposure, limited range, bio-incompatibility and necessity of expensive instruments. In the present study, we propose a multi-walled carbon nanotubes/polyglycerol based low cost, flexible and biocompatible sensor which could allow safer, faster and accurate angular deflection measurement of continuum robots for biomedical applications. Experimental results demonstrate that the sensor is stretchable up to 100%, provides a gauge factor up to 11.65, have response time around 8 ms, durability of −0.14% for cyclic loading and unloading and show very small creep up to ±0.0008 (±2.88%) . Furthermore, the sensor can measure continuum robot deflection up to ±150∘ with a sensitivity of 666.67 ohms/degree, with a maximum error of 1.67% and maximum hysteresis of 1.41%. Thus, wide range, low cost, fast response, and biocompatibility justify the potential of the proposed sensor for large deflection sensing of continuum robots during robot assisted MIS.
Detection of Novel Biomarkers in Saliva of Rheumatoid Arthritis Model Mice by Proteomics and Pathological Analysis

Rheumatoid arthritis (RA) is an autoimmune disease in which joints are gradually de-stroyed, and early diagnosis and treatment before joint deformation or destruction is im-portant. The detection of novel RA biomarkers in saliva may facilitate the early detection of RA before the onset of disease. In this study, we conducted a comprehensive proteomic analysis of salivary proteins from RA model mice. Proteins were identified by Western blotting and enzyme-linked immunosorbent assay in serum, saliva, and ankle joints from DBA/1JJmsSlc mice, a model of rheumatoid arthritis. Ankle joints and submandibular glands were hematoxylin and eosin stained and immunostained, and the results were compared with those of control mice. Citrullinated α1 antitrypsin (A1AT, 46 kDa) was commonly detected in saliva, serum, and ankle joints of severe RA model mice, and was confirmed by proteome analysis. Western blotting detected a band corresponding to 46 kDa in serum, saliva and ankle joints, and immunostaining of ankle joints with A1AT an-tibody showed a strong positive signal in the synovium. In DBA/1JJmsSlc mice, not only cyclic citrullinated peptide antibodies but also A1AT may be involved in protein citrulli-nation and contribute to the development and severity of RA.
FPGA-based hybrid accumulator architecture for digital chirp synthesis

The double accumulator architecture can be employed to generate chirp signals with the required linearity for both radar and sounder applications. However, all reported chirp generators use identical architecture for both accumulators. In this paper, a FPGA-based hybrid accumulator architecture with a dual clock suitable for HF radar and sounder applications is proposed. This design is shown to combine speed and flexibility.
Orthogonal Printed Microstrip Antenna Arrays for 5G Millimeter-Wave Applications

This article presents the design of a planar MIMO (Multiple Inputs Multiple Outputs) antenna comprised of two sets orthogonally placed 1 × 12 linear antenna arrays for 5G millimeter wave (mmWave) applications. The arrays are made of probe-fed microstrip patch antenna elements on a 90 × 160 mm2 Rogers RT/Duroid 5880 grounded dielectric substrate. The antenna demonstrates S11 = −10 dB impedance bandwidth in the following 5G frequency band: 24.25–27.50 GHz. The scattering parameters of the antenna were computed by electromagnetic simulation tools, Ansys HFSS and CST Microwave Studio, and were further verified by the measured results of a fabricated prototype. To achieve a gain of 12 dBi or better over a scanning range of +/−45° from broadside, the Dolph-Tschebyscheff excitation weighting and optimum spacing are used. Different antenna parameters, such as correlation coefficient, port isolation, and 2D and 3D radiation patterns, are investigated to determine the effectiveness of this antenna for MIMO operation, which will be very useful for mmWave cellphone applications in 5G bands.
Evaluation of correlation between vibration signal features and three-dimensional finite element simulations to predict cutting tool wear in turning operation

This article presents the correlation of vibration signal feature, that is, displacement due to vibration (microns) during the machining and three-dimensional finite element simulations in tool wear monitoring of a metal turning operation. Machining of AISI 1040 has been carried on using an uncoated inserts and online vibration signals acquired using a laser Doppler vibrometer. The measured tool wear forms correlate to features in the vibration signals in frequency domains. Analyses of the results suggested that the vibration signals’ features are effective for use in cutting tool wear monitoring and wear qualification. Present work demonstrates the three-dimensional finite element analysis to predict the workpiece displacements in feed direction and corresponding tool wear with the help of induced vibrations in face turning under dry machining conditions. Vibration-assisted turning model is developed and validated by comparing the simulation results with experimental results. In this research, three-dimensional finite element modelling and simulation issues for vibration-assisted turning are explored in detail. Machine dynamic effects are taken into account to predict the outcomes such as tool wear displacements and chip formation. The model can be implemented in an online tool wear monitoring system which predicts the actual state of tool wear in real time by correlating displacement variations during the machining. The correlation between the displacement due to vibration and flank wear has been evaluated through three-dimensional finite element modelling and simulation. Comparisons of simulations with experimental results demonstrate their predictive capability. From the results, useful conclusions may be drawn, and it can be stated that the proposed models can be used for industrial application.
Breast Cancer Surgery 10-Year Survival Prediction by Machine Learning: A Large Prospective Cohort Study

Simple Summary This study provided an analysis of machine-learning algorithms and the ability to predict 10-year survival after breast cancer surgery. The univariate analyses and the global sensitivity analysis provided in this study are especially helpful. This represents a novel opportunity for understanding the significance of a preoperative SF-36 PCS score, a preoperative SF-36 MCS score, postoperative recurrence, and tumor stage in predicting 10-year survival after breast cancer surgery and could lead to clinicians being better informed about the precision and efficacy of management for these patients. These results encourage a broader international validation of language models in clinical practice and emphasize that preoperative physical and mental functioning should always be an integral part of cancer care. Future studies may investigate further refinements of the machine-learning algorithms applied in this study and their potential for integration with other clinical decision-making tools. Abstract Machine learning algorithms have proven to be effective for predicting survival after surgery, but their use for predicting 10-year survival after breast cancer surgery has not yet been discussed. This study compares the accuracy of predicting 10-year survival after breast cancer surgery in the following five models: a deep neural network (DNN), K nearest neighbor (KNN), support vector machine (SVM), naive Bayes classifier (NBC) and Cox regression (COX), and to optimize the weighting of significant predictors. The subjects recruited for this study were breast cancer patients who had received breast cancer surgery (ICD-9 cm 174–174.9) at one of three southern Taiwan medical centers during the 3-year period from June 2007, to June 2010. The registry data for the patients were randomly allocated to three datasets, one for training (n = 824), one for testing (n = 177), and one for validation (n = 177). Prediction performance comparisons revealed that all performance indices for the DNN model were significantly (p < 0.001) higher than in the other forecasting models. Notably, the best predictor of 10-year survival after breast cancer surgery was the preoperative Physical Component Summary score on the SF-36. The next best predictors were the preoperative Mental Component Summary score on the SF-36, postoperative recurrence, and tumor stage. The deep-learning DNN model is the most clinically useful method to predict and to identify risk factors for 10-year survival after breast cancer surgery. Future research should explore designs for two-level or multi-level models that provide information on the contextual effects of the risk factors on breast cancer survival.
New Business Models on Artificial Intelligence—The Case of the Optimization of a Blast Furnace in the Steel Industry by a Machine Learning Solution

This article took the case of the adoption of a Machine Learning (ML) solution in a steel manufacturing process through a platform provided by a Canadian startup, Canvass Analytics. The content of the paper includes a study around the state of the art of AI/ML adoption in steel manufacturing industries to optimize processes. The work aimed to highlight the opportunities that bring new business models based on AI/ML to improve processes in traditional industries. Methodologically, bibliographic research in the Scopus database was performed to establish the conceptual framework and the state of the art in the steel industry, then the case was presented and analyzed, to finally evaluate the impact of the new business model on the operation of the steel mill. The results of the case highlighted the way the innovative business model, based on a No-Code/Low-Code solution, achieved results in less time than conventional approaches of analytics solutions, and the way it is possible to democratize artificial intelligence and machine learning in traditional industrial environments. This work was focused on opportunities that arise around new business models linked to AI. In addition, the study looked into the framework of the adoption of AI/ML in a traditional industrial environment toward a smart manufacturing approach. The contribution of this article was the proposal of an innovative methodology to put AI/ML in the hands of process operators. It aimed to show how it was possible to achieve better results in a less complex and time-consuming adoption process. The work also highlighted the need for an important quantity of data from the process to approach this kind of solution.
INNOVATIVE ENGINEERING TECHNIQUE OF OBJECT ORIENTED SOFTWARE DEVELOPMENT

Computer software is an engine of growth of socialeconomy development which requires new engineering techniques and strategies. The demand for quality in software applications has grown. Hence as software becomes more integrated into our lives, the effects of software failures become more acute. Testing is an essential part of software development providing an indicator of the quality of the software. Testing remains the primary way to improve reliability of software. Billions of dollars are spent on testing in the software industry, as testing usually accounts for more than half the cost of software development. The demand of new engineering technologies for quality in software applications has grown and awareness of software testing-related issues plays an important role of all testing levels. The unit level of testing has undergone the most recent and most dramatic change. With the introduction of new agile (aka, “lightweight”) development methods, such as XP (eXtreme Programming) came the idea of Test-Driven Development (TDD). The TDD is a software development engineering technique that melds program design, implementation and testing in a series micro-iterations that focus on simplicity and feedback. Programmer tests are created using a unit testing framework and are 100% automated. This paper contributes in the development of TDD framework for testing of unit, which includes new engineering concepts and the methodologies issues in form of TDD techniques using V design model especially for engineering education, industrial training and software development.
Shaping Patient Specific Surgical Guides for Arthroplasty to Obtain High Docking Robustness

Patient specific surgical guides (PSSGs) are used in joint replacement surgery to simplify the surgical process and to increase the accuracy in alignment of implant components with respect to the bone. Each PSSG is fabricated patient specifically and fits only in the planned position on the joint surface by the matching shape. During surgery, the surgeon holds the PSSG in the planned position and the incorporated guidance is used in making the essential cuts to fit the implant components. The shape of the PSSG determines its docking robustness (i.e., the range of forces that the surgeon may apply without losing the planned position). Minimal contact between the PSSG and the joint surface is desired, as this decreases the likelihood of interposition with undetected tissues. No analytical method is known from literature where the PSSG shape can be optimized to have high docking robustness and minimal bone-guide contact. Our objective is to develop and validate such an analytical method. The methods of motion restraint, moment labeling and wrench space-applied in robotic grasping and workpart fixturing-are employed in the creation of this new method. The theoretic approach is utilized in an example by optimizing the PSSG shape for one joint surface step-by-step. The PSSGs that arise from these optimization steps are validated with physical experiments. The following design tools for the analytical method are introduced. The optimal location for bone-guide contact and the application surface where the surgeon may push can be found graphically, respectively, by the use of the wrench space map and the application angle map. A quantitative analysis can be conducted using the complementary wrench space metrics and the robustness metric R. Utilization of the analytical method with an example joint surface shows that the PSSG's shape can be optimized. Experimental validation shows that the standard deviation of the error between the measured and calculated angular limits in the docking force is only 0.7 deg. The analytical method provides valid results and thus can be used for the design of PSSGs
Resilience to climate change: adaptation strategies for the water supply system of Formia and Gaeta (Province of Latina, Central Italy)

The aqueduct serving the municipalities of Formia and Gaeta (Latina province, Italy), an area under the enforcement and control responsibility of “ATO 4” Autorità d’Ambito Territoriale Ottimale – (Integrated Urban Water Management Agency), is supplied by two important karst springs. These springs, fed by the western Aurunci Mountains system are known as Mazzoccolo and Capodacqua having an average flow rates of 1100 l/s and 1300 l/s, respectively. Although these sources have been used since ancient Roman times and the quality of their water is excellent, variations in the precipitation regime, possibly related to worldwide climate changes, has exacerbated the following problems: a decrease in the flow rates of the springs caused by the reduction in winter rainfall, and an increase of turbidity due to concentrated rainfall events. In order to mitigate these problems, which affect a resident population of about 150,000 inhabitants, Acqualatina S.p.A. - the water utility company - promoted a series of geological and hydrogeological surveys. These studies aim at increasing the knowledge on the geological setting and to find additional sources to improve the existing supply. Within the framework of these activities, we studied a strategy aimed at diversifying the water supply by identifying new exploitable aquifers in the area, to reduce the aforementioned problems. This paper presents the results of research carried out before and during the construction of the water well field “25 Ponti” located in the coastal area of the plain of Formia. The research consisted in laboratory analyses of 130 groundwater samples and in monitoring of piezometric trends. The data show a seasonal variation in groundwater chemical composition caused also by aquifer exploitation, which in some periods of the year affects the regulated reserves. This seasonal phenomenon was however present in absence of pumping.
Intermittent Hypoxic Therapy Inhibits Allogenic Bone-Graft Resorption by Inhibition of Osteoclastogenesis in a Mouse Model

Systemic Intermittent Hypoxic Therapy (IHT) relies on the adaptive response to hypoxic stress. We investigated allogenic bone-graft resorption in the lumbar spine in 48 mice. The mice were exposed to IHT for 1 week before surgery or 1 week after surgery and compared with controls after 1 and 4 weeks. Complete graft resorption was observed in 33–36% of the animals in the control group, but none in the preoperative IHT group. Increased bone-graft volume was demonstrated by micro-computed tomography in the preoperative IHT group after 1 week (p = 0.03) while a non-significant difference was observed after 4 weeks (p = 0.12). There were no significant differences in the postoperative IHT group. Increased concentration of immune cells was localized in the graft area, and more positive tartrate-resistant acid phosphatase (TRAP) staining was found in controls compared with IHT allogenic bone grafts. Systemic IHT resulted in a significant increase of the major osteoclast inhibitor osteoprotegerin as well as osteogenic and angiogenic regulators Tgfbr3, Fst3l, Wisp1, and Vegfd. Inflammatory cytokines and receptor activator of nuclear factor kappa-B ligand (RANKL) stimulators IL-6, IL-17a, IL-17f, and IL-23r increased after 1 and 4 weeks, and serum RANKL expression remained constant while Ccl3 and Ccl5 decreased. We conclude that the adaptive response to IHT activates numerous pathways leading to inhibition of osteoclastic activity and inhibition of allogenic bone-graft resorption.
Power electronics in electric utilities: static VAR compensators

The author deals with dynamic VAR compensation of electric power systems, applying power electronics for reactive power generation and control. After an overview of the emergence and status of modern, solid-state VAR compensators in utility and industrial applications, it is shown how dynamic VAR compensation increased transmittable power by providing voltage support, transient stability improvement, and power oscillation damping in electric power transmission systems. Methods of reactive power generation and control using thyristor-controlled reactors, with fixed and thyristor-switched capacitors or modern gate-turn-off (GTO) power converters that can function without AC capacitors or reactors, are described. A summary is included of the control structure and operation to provide the desired characteristics and performance in power systems applications. >
Transient analysis of nonuniform transmission lines through the method of characteristics

The method of characteristics of partial differential equations (PDEs) theory has been previously applied to the analysis of transients on transmission lines with corona. It is proposed here that this method be applied also to the analysis of nonuniform lines. The advantages of doing this are illustrated by analyzing the nonuniformities caused by the sagging of conductors on an aerial line. Results from a similar field experiment are included for comparison purposes.
Scaling Behavior of Sub-100 nm InAlN/GaN HEMTs on Silicon for RF Applications

Due to the low cost and the scaling capability of Si substrate, InAlN/GaN high-electron-mobility transistors (HEMTs) on silicon substrate have attracted more and more attentions. In this paper, a high-performance 50-nm-gate-length InAlN/GaN HEMT on Si with a high on/off current (Ion/Ioff) ratio of 7.28 × 106, an average subthreshold swing (SS) of 72 mV/dec, a low drain-induced barrier lowing (DIBL) of 88 mV, an off-state three-terminal breakdown voltage (BVds) of 36 V, a current/power gain cutoff frequency (fT/fmax) of 140/215 GHz, and a Johnson’s figure-of-merit (JFOM) of 5.04 THz∙V is simultaneously demonstrated. The device extrinsic and intrinsic parameters are extracted using equivalent circuit model, which is verified by the good agreement between simulated and measured S-parameter values. Then the scaling behavior of InAlN/GaN HEMTs on Si is predicted using the extracted extrinsic and intrinsic parameters of devices with different gate lengths (Lg). It presents that a fT/fmax of 230/327 GHz can be achieved when Lg­ scales down to 20 nm with the technology developed in the study, and an improved fT/fmax of 320/535 GHz can be achieved on a 20-nm-gate-length InAlN/GaN HEMT with regrown ohmic contact technology and 30% decreased parasitic capacitance. This study confirms the feasibility of further improvement of InAlN/GaN HEMTs on Si for RF applications.
Long COVID Syndrome Presenting as Hyperferritenemia Associated Toxic Encephalopathy in a Deferoxamine Compliant Patient of Beta Thalassemia

Ferritin overload is a frequent problem encountered in patients with beta thalassemia amounting to various complications. One of rare but important complication of ferritin overload is ferritin overload induced toxic encephalopathy. Serum ferritin has been recognised as a important marker of inflammation and cytokine storm in COVID19.We present a case of Long COVID syndrome presenting as toxic encephalopathy in a case of beta thalassemia in spite of the patient being compliant to desferroxamine therapy.This report highlights the synergistic effect of Severe Acute Respiratory Syndrome Coronavirus. 2(SARS CoV 2) mediated neuroinflammation through direct viral invasion and the release of inflammatory cytokines including ferritin resulting in toxic encephalopathy in a beta thalassemia major patient who was already prone to develop hyperferritenemia.Ferritin functions as a pro-inflammatory cytokine and it’s level increases in both thalassemia and COVID-19 and the index case presented here had both the conditions predisoposing him to develop toxic encephalopathy even after being compliant to deferoxamine therapy. It is important to recognise and treat this condition in order to prevent mortality and morbidity in patients of beta thalassemia who contract COVID19.
Automatic Test Equipment: Its Role in Improving PCB Manufacture

Automatic Test Equipment (ATE) for both bare and loaded‐board testing has been in widespread use for some 14 years. During this time there have been a number of technological advances which have made these systems more efficient, easier to use, and more able to test complex circuits. In this period, however, the fundamental role of ATE has not changed. This role has been the detection and location of defects on the PCB, and the ATE is therefore monitoring or measuring the quality of the product. In the past year (1982/83) some new developments have taken place that have changed the fundamental role of ATE from defect detention to defect prevention. Information created by the ATE can now be utilised to determine the source of defects and correct the problem. The resulting lower number of defects increases the yield of good boards, reduces the amount of re‐work needed, increases the productivity of the PCB manufacturing area, and improves the quality of the end product. This move from ‘detection’ to ‘prevention’ turns the ATE into a ‘quality management’ device rather than simply a ‘quality monitoring’ device. This paper describes how such a quality management system operates, and the benefits to be derived from it.