Background: One challenge in implant dentistry is to reduce marginal bone resorption to avoid long-term esthetic and biological complications. Sub-gingival implant placement has been suggested as a suitable strategy. Methods: 38 healthy patients were enrolled to receive bone level (BL – Control group) or 2 mm sub-crestal (SC - Test group) conical connection, platform-switched implants. An immediate tissue level abutment was used in the Test group by following a One Time Abutment (OTA) restorative procedure. Marginal Bone Modification (MBM) was calcu-latied on standardized radiographs at surgery (T0), loading (T1), and 6 months (T2) and 12 months after loading (T3), and cathegorised in Bone Loss (BL) if the resorption occurred below the implant neck and Bone Remodeling (BR) if above. Pocket probing depth (PPD), Bleeding on probing (BoP) and Plaque Index (PI) were also collected. Results: The mean MBM in the test group after 12 months was 0.61mm, compared to 0.52mm in the control group. However, no BL was observed in the test group, as the MBM completely occurred above the implant neck as BR, whilst in the control group MBM corresponded in total to BL. The average PPD was 2.38mm in the test group and 3.04mm in the control group after 12 months, BoP 50% and 43%, PI 33% and 19.44% respectively. Conclusions: Sub-crestal conical connection, platform-switched implants could be a suitable clinical choice to avoid BL with exposure of the treated implants surfaces.

Palpation is a simple but effective method to differentiate tumors from healthy tissues. Development of miniaturized tactile sensors embedded on endoscopic or robotic devices are the key toward precise palpation diagnosis and the subsequent timely treatment. This paper reports on the fabrication and characterization of a novel tactile sensor with mechanical flexibility and optical transparency that can be easily mounted on soft surgical endoscopes and robotics. Utilizing the pneumatic sensing mechanism, the sensor offers a high sensitivity of 1.25 mbar and negligible hysteresis, enabling the detection of phantom tissues with different stiffnesses ranging from 0 to 2.5 MPa. Our configuration combining pneumatic sensing and hydraulic actuating also eliminates electrical wiring from the functional elements located at the robot end-effector, thereby enhancing the system safety. The optical transparency path in the sensors together with its mechanical sensing capability open interesting possibility in early detection of solid tumor as well as in the development of all in-one soft surgical robots that can perform visual/mechanical feedback and optical therapy.

In this systematic survey, an overview of non-conventional and soft-actuators is presented. The review is performed by using well-defined performance criteria with a direction to identify the exemplary applications in robotics. In addition to this, initial guidelines to measure the performance and applicability of soft actuators are provided. The meta-analysis is restricted to four main types of soft actuators: shape memory alloys (SMA), fluidic elastomer actuators (FEA), dielectric electro-activated polymers (DEAP) and shape morphing polymers (SMP). In exploring and comparing the capabilities of these actuators, the focus was on seven different aspects: compliance, topology, scalability-complexity, energy efficiency, operation range, performance and technological readiness level. The overview presented here provides a state-of-the-art summary of the advancements and can help researchers to select the most convenient soft actuators using the comprehensive comparison of the performance criteria.

This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz. Predictions show a convergence time with a 95% confidence interval of approximately 30 s.

In this paper, a new axial-type magnetic gear with auxiliary flux-enhancing structure (AFS-AMG) is proposed. Compared to conventional AFS-AMG, it has the higher torque density and higher permanent magnet (PM) utilization factor. Firstly, the design rules and operating principles of proposed AFS-AMG are elaborated. Then, the mapping relation between the radial-type magnetic gears (RMGs) and AMGs are elucidated. Compared to its counterpart in RMGs, AFS-AMGs achieve small size. Then, the geometrical parameters of AFS-AMGs are optimized to obtain the better electromagnetic performances, where the torque density per volume and per PM volume is adopted as the evaluation standard. Finally, three different AMG topologies are constructed in finite element analysis (FEA) software for comparison. It is proven that the AFS-AMG has the largest torque density per volume and per PM volume.

The article presents several innovative systems developed through student laboratory projects, including two autonomous vehicles, a four-legged walking robot, an active ankle-foot orthosis, a ball on beam balancing mechanism, a ball on plate system, and a manipulator arm—all powered by pneumatic artificial muscles (PAMs). Fluidic muscles offer significant potential in various mechatronic systems, robots, and manipulators due to their flexible, lightweight nature and compliance. Their ability to produce smooth and adaptable motions is particularly beneficial in applications requiring natural and human-like movement, such as rehabilitation and assistive devices. Although PAMs powered control systems face challenges with nonlinear phenomena, their biologically inspired design holds promise for future applications across various industries. These may include innovative applicability in industrial, automotive, and aerospace sectors, as well as use in sports, medical aids, entertainment, and animatronics. Incorporating self-made laboratory systems actuated by PAMs into control systems education offers a comprehensive learning opportunity that combines theoretical concepts with hands-on experience. This approach develops the necessary skills of future engineers, expanding their understanding of technical principles and preparing them for future challenges in engineering practice.

Intelligent fault diagnosis techniques have replaced the time-consuming and unreliable human analysis, increasing the efficiency of fault diagnosis. Deep learning model can improve the accuracy of intelligent fault diagnosis with the help of its multilayer nonlinear mapping ability. This paper has proposed a novel method named Deep Convolutional Neural Networks with Wide First-layer Kernels (WDCNN). The proposed method uses raw vibration signals as input (data augmentation is used to generate more inputs), and uses the wide kernels in first convolutional layer for extracting feature and suppressing high frequency noise. Small convolutional kernels in the preceding layers are used for multilayer nonlinear mapping. AdaBN is implemented to improve the domain adaptation ability of the model. The proposed model addresses the problem that currently, the accuracy of CNN applied to fault diagnosis is not very high. WDCNN can not only achieve 100% classification accuracy on normal signals, but also outperform state of the art DNN model which is based on frequency features under different working load and noisy environment.

The paper delineates the developed vision system of the UR5 cobot and the operating algorithm of the robotic quality control station. The hardware-software architecture of the developed robotic station was shown, consisting of a UR5 cobot equipped with a web camera and a stationary industrial camera with a lighting system. Image processing and analysis algorithms were described, the method of control and communication between the station components was discussed, and two operating scenarios were presented as a single robotic station and a robotic line. Based on the results obtained, the level of measurement noise, accuracy, and repeatability of the developed vision system were estimated.

In this paper, a method is developed for presenting a novel virtual torque sensor based on precise model and position measurements avoids the need of traditional strain gauges and amplifiers. More specifically, the harmonic drive compliance model and the Gaussian process regression (GPR) technique are used together to achieve virtual torque sensor measurement. While the harmonic drive compliance model provides the analytic part, the Gaussian process regression method is used to reconstruct the unmolded part based on motor-side and link-side joint angles as well as motor current. After an automatic offline calibration, the method allows for a lean online implementation. The virtual torque sensor measurement is compared with measurements of a commercial torque sensor, and the results have attested the effectiveness of the proposed method.

Antisense oligonucleotides (ASOs) are short oligodeoxynucleotides designed to bind to specific regions of target mRNA. ASOs can modulate pre-mRNA splicing, increase levels of functional proteins and decrease levels of toxic proteins. ASOs are being developed for the treatment of several diseases, including motor neuron diseases (MNDs), a group of neurodegenerative disorders characterised by the loss of motor neurons, including spinal muscular atrophy (SMA), amyotrophic lateral sclerosis (ALS) and spinal and bulbar muscular atrophy (SBMA). The biggest success has been the ASO known as nusinersen, the first effective therapy for SMA, able to improve symptoms and slow disease progression. Another success is tofersen, an ASO designed to treat ALS patients with SOD1 gene mutations. Both ASOs have been approved by the FDA and EMA. On the other hand, ASO treatment in ALS patients with the C9orf72 gene mutation did not show any improvement in disease progression. The aim of this review is to provide an up-to-date overview of ASO research in MND, from preclinical studies to clinical trials and, where available, regulatory approval. We highlight the successes and failures, underline the strengths and limitations of the current ASO research, and suggest possible approaches that could lead to more effective treatments.

Background: Tibial shaft fractures are the most common of long bone fractures. The gold standard for management is locked intramedullary nailing. The freehand method under fluoroscopic monitoring is the most often utilized method for distal screw locking. Electromagnetic guidance-based distal screw locking methods have gained popularity recently. The study's objective is to evaluate the system using electromagnetic tracking data against the free-hand technique. Methods: Sixty-three patients who received intramedullary nailing for tibial shaft fractures at our institute between January 2018 and May 2022, were included in this study. Two groups of patients were distinguished: Group FH underwent freehand distal locking and intramedullary nailing, while Group SS underwent electromagnetically guided locking. Radiation exposure period, as well as dose area product, were noted and statistically compared. Results: In terms of dose area product, a mean value of 43.57±31.57 cGy/cm2 in group FH and a mean value of 27.62±11.20 cGy/cm2 in group SS (p < 0.05) was assessed. Concerning the duration of surgery a mean value of 128.83±26.51 minutes was reported in group FH and a mean value of 126.42±48.31 minutes in group SS (p > 0.05). Conclusions: This study confirms the use of electromagnetic-guided locking distal screws reduces the total time of exposure to ionizing radiation, with no difference in operating time.

In patients with heart failure, the evaluation of left ventricular (LV) diastolic function is vital, offering crucial insights into hemodynamic impact and prognostic accuracy. Echocardiography stands as the primary imaging modality for diastolic function assessment, and using it effectively requires a profound understanding of the underlying pathology. This review covers four main topics: first, the fundamental driving forces behind each phase of normal diastolic dynamics, along with the physiological basis of two widely used echocardiographic assessment parameters, E/e' and mitral annulus early diastolic velocity (e'); second, the intricate functional relationship between the left atrium and LV in patients with varying degrees of LV diastolic dysfunction (LVDD); third, the role of stress echocardiography in diagnosing LVDD and the significance of parameter changes in this context; and fourth, the clinical utility of evaluating diastolic function from echocardiography images across diverse cardiovascular care areas.

Merkel cell carcinoma (MCC) is a rare, highly aggressive skin cancer characterized by two etiologies: the first one, observed in most cases, is attributed to Merkel cell polyomavirus (MCPyV), a DNA tumor virus, while the second one is due to ultraviolet (UV) radiation exposure. Currently, there are limited diagnostic, prognostic, and therapeutic biomarkers available for MCC. MicroRNAs (miRNAs) are small RNA molecules that do not code for proteins but regulate various cellular processes, including cell cycle progression, proliferation, differentiation, and apoptosis. The dysregulation of miRNAs has been associated with a wide range of cancers since they can act as either tumor suppressors or oncogenes. This paper aims to collect, summarize and re-organize the recent discoveries concerning miRNAs, whose dysregulation in the pathogenesis and progression of MCC is slowly emerging. Furthermore, the potential clinical applications of miRNAs as diagnostic biomarkers, possible differentiation between MCPyV-related and unrelated MCC, predictors of response to therapy and prognostics are also discussed. From this review, it emerges that miRNAs may have, in the near future, the potential to become clinically significant in improving the diagnostic accuracy, prognostic evaluation, and therapeutic options of MCCs. Finally, the new perspectives on the poorly explored field of artificial intelligence in MCC are provided.

Background: Patients with thromboembolic disease, prosthetic valves, or coagulation issues are commonly prescribed anticoagulants and antiplatelets. Although common professional oral hygiene might not represent a health concern for these patients, anticoagulant and antiplatelet medication might constitute a challenge for dentists and dental hygienists since possible prolonged bleeding might interfere with dental procedures. The aim of the present study was to investigate the bleeding time of different anticoagulants and antiplatelets during a professional hygiene session adapting the Ivy test to the oral environment; Methods: 93 consecutive patients undergoing professional oral hygiene were recruited. Debridement during oral hygiene was performed using ultrasonic mechanical instrumentation, and bleeding sites were assessed and treated with gentle pressure using sterile gauzes. The time for bleeding cessation was recorded. Patients were categorized into six groups based on their drug intake, Control: no anticoagulants or antiplatelets DTI: direct thrombin inhibitors (dabigatran) AntiXa: directa factor Xa inhibitors (endoxaban, apixaban, rivaroxaban) VKA: vitamin K antagonists (warfarin, acenocoumarol) SAPT: single anti-platelet therapy (acetylsalicylic acid or clopidogrel) DAPT: dual anti-platelet therapy (acetylsalicylic acid and clopidogrel). Bleeding time was measured in seconds and mean values were assessed among the different groups. Differences between groups were investigated with Kruskal-Wallis test followed by Dunn’s post-hoc correction for multiple comparisons or two-way ANOVA followed by Dunnett post-hoc; Results: Control patients presented the lowest bleeding time 50 sec, followed by AntiXa (98), SAPT (105), DTI (120), DAPT (190) and VKA (203). A statistically significant difference was present among control and DTI (p=0.004), VKA (p<0.001), DAPT (p<0.001). Conclusions: Based on the present outcomes, an increased risk of prolonged bleeding emerged in patients taking VKA and DAPT. However, bleeding did not interfere with the oral hygiene ses-sion The optimal period for dental treatment of these patients should be 2-3 hours before the next dose, without the need to temporarily suspend the medication.

Several pathotypes of enteric E. coli have been identified. The group represented by Shiga toxin-producing E. coli (STEC) is of particular interest. Raw milk and raw milk products are significant sources of STEC infection in humans; therefore, identifying pathogens at the herd level is crucial for public health. Most national surveillance programs focus solely on raw milk and raw milk cheeses that are ready for retail sale, neglecting the possibility of evaluating the source of contamination directly at the beginning of the dairy chain. In order to assess the viability of new molecular methodologies applied to raw milk filters enabling the identification of the presence of STEC serotypes in milk production and apply the same methods to identify the presence of these pathogens in calf feces we analyzed, through a commercial real-time PCR assay, a total of 290 samples coming from 18 different dairy herds; 88 bulk tank milk (BTM), 104 raw milk filters (RMF) and 98 calves’ feces samples. In total 3.4% of BTM, 41.4% of RMF and 73.4% of calves’ feces tested positive for stx presence, supporting our hypothesis that BTM is not a suitable matrix to assess the STEC presence at herd level, underestimating it. Our conclusion is that the surveillance program needs critical and extensive improvements such as RMF and calves’ feces analysis implementation in order to be more efficient in detecting and preventing STEC infections. The epidemiology of these infections and the characteristics of the pathogen clearly show how a One Health approach will be pivotal to improve our capabilities to control the spread of these infections.

The extensive collection of paper documents and books stored in the archives of universities worldwide is a hidden cultural heritage that is frequently inaccessible. To overcome this problem, the University of Genoa, Italy, seeks to collect, store, and digitize a wide variety of items, encompassing books, manuscripts, archival materials, and documents related to museum artifacts, which together form a cultural heritage of great importance and historical significance. To make such a cultural heritage accessible to both humans and machines, images and videos must be provided with alternate descriptions, metadata, and speech-to-text transcriptions while ancient texts, for which OCR techniques are often not effective, must be accompanied by word-for-word transcripts. This work presents the design of a transcription system for the “University Museum System” at the University of Genoa, Italy (SMA-UniGe), including user interface elements and users’ engagement techniques. The goal is to create an accessible digital heritage that can be enjoyed by all, facilitated by a community of digital volunteers who are eager to dedicate their time, have a great experience, socialize, and interact on the proposed transcription system. The system exploits gamification theory to transform the typically monotonous task of transcription into a captivating experience. This activity is in line with the so-called University third mission, i.e., the activity of public engagement that aims at generating knowledge outside the academic environment to the benefit of the social, cultural, and economic development.

The carbohydrate antigen Sda is expressed on cells and secretions of the vast majority of Caucasians. The epitope is formed by a terminal GalNAc residue β4-linked to a α3-sialylated galactose. Different carbohydrate chains N- or O-linked to glycoproteins can be terminated by this epitope. The final step of Sda biosynthesis is catalyzed by the GalNAc transferase B4GALNT2. In this review, we will discuss the multifaceted aspects of B4GALNT2/Sda biology. In particular, we will see its implications in fertility and pregnancy, in susceptibility to infectious diseases, in chronic kidney diseases and in Duchene muscular dystrophy. In particular, we will show its regulation and prognostic implications in cancer.

Osteosarcoma (OS) are the most prevalent malignant bone tumors in adolescents and young adults.. OS cells grow in a permissive local microenvironment which modulates their behavior and facilitates all steps in tumor development (e.g., proliferation/quiescence, invasion/migration, drug resistance) and contributes to their intrinsic heterogeneity. The lung parenchyma is the most common metastatic site in OS, and metastatic foci are frequently associated with a poor clinical outcome. Although multiple factors may be responsible for the disease, including genetic mutations (e.g., Rb, p53), the molecular mechanism of development of OS remains unclear and the conventional treatment for OS is still based on a sequential approach that combines chemotherapy and surgery. Also, despite the increase in clinical trials, the survival rates for OS have not improved. Non-specific targeting therapies thus show poor therapeutic effects with side effects at high doses. For these reasons, many efforts have been done to characterize the complex genome of osteosarcoma thanks to the whole exome analysis with the aim to identify predictive biomarkers to give to these patients a better therapeutic option. This review aims to summarize and discuss the main recent advances in OS molecular research for precision medicine.

Background: The aim of this experimental work was to confirm the individual uniqueness of lip prints, to verify the presence of recurrent patterns according to the Suzuki and Tsuchihashi classification and to search for characteristics that can be used in establishing the sex of a subject. Methods: Lip prints were taken from a sample of 172 volunteers using liquid lipstick and transparent adhesive tape and were digitally analyzed. Results: 59 prints (35.3%) were not considered for Suzuki and Tsuchihashi classification due to quality errors and the impossibility of visualizing lip wrinkles in one or more sextants, all the digitized prints revealed themselves to be unique after having been analyzed using superimposition. Qualitatively valid prints indicated a prevalence of Type II in both male and female and the presence of sex-linked features. A major problem was that the analysis of the same print by different operators often resulted in a different attribution of a Type. Conclusions: The potential of cheiloscopy lies mainly in the matching of prints, given their uniqueness, and can be a valid tool in gender determination but the absence of a database greatly limits its use. It is necessary to establish an acquisition protocol for taking and analyzing prints that could reduce the errors committed by the operator.

Background: Fiber-reinforced composites (FRCs) have been proposed as an alternative to traditional metal alloys for the realization of frameworks in full-arch implant supported prostheses. The aim of the present in vitro study was to evaluate the deflection under load of seven prostheses endowed with frameworks made of different materials, including different types of fiber reinforced composites (FRCs). Methods: A master cast with four implant analogues in correspondence of the two lateral incisors and the two first molars was used to create full-arch fixed prostheses with the same shape and different materials. Prostheses were made in different materials (framework+veneering material): gold alloy+resin (Au+R), titanium+resin (Ti+R), FRC with multi-directional carbon fibers+resin (ICFRC+R), FRC with unidirectional carbon fibers+composite (UCFRC+C), FRC with glass fibers+resin (GFRC+R), FRC with glass fibers+composite (GFRC+C), resin (R, full-acrylic prosthesis). Flexural tests were conducted using Zwick/Roell Z 0.5 machine and the deflection of the lower surface of the prosthesis was measured in order to obtain load/deflection graphs. Results: Greater rigidity and less deflection were recorded for UCFRC+C, GFRC+C, followed by Ti+R, and Au+R. The greatest deformations were observed for resin alone, ICFRC+R and GFRC+R. The results were slightly different in the incisal region probably due to the greater amount of veneering material in this area. Conclusions: When used to realize full-arch frameworks, Au and Ti allow a predictable mechanical behavior with gradual deformations with increasing load. UCFRC also demonstrated good outcomes and less deflection than ICFRCs when loaded. The GFRC full-arch framework may be a valid alternative, however showed greater deflections. Further studies are needed in order to evaluated how different prosthesis design and material thickness might affect the outcomes.

A review of literature, supporting the view on the psychophysical origins of some acceptance effects of cyber-physical systems (CPSs), is presented and discussed in the paper. Psychological effects like the reactance to a robot or the uncanny valley phenomenon suggest that CPSs are perceived as a special type of ‘being’, a phylogenetically emergent category, or a novel ontology in a philosophical sense, culturally developing as a function of the social brain. Justification of this view is provided by the psychophysically-relevant human responses to technologically and socially ambiguous stimuli on the one hand, and the probabilistic independence of the proposed ontology to similar ontologies, subjectively experienced by the human, on the other. The results of the presented in the paper analysis demonstrate the feasibility of the proposed hypothesis of ontological ‘near independence’ of the distribution of the probabilistic psychophysical processes in response to the cyber-physical stimulus as a socially evolving phenomenon.

This research presents the creation of a Virtual Reality experience for the Balzi Rossi museum, commemorating the centenary of Prince Albert I Grimaldi's archaeological work at the site. The project, a collaboration between the University of Genoa's 3D Lab Factory, Eurodrone, and the Balzi Rossi archaeological museum, aims to preserve and convey the site's heritage through advanced VR technology. Initially employing Unreal Engine 4, the team used photogrammetry for 3D reconstruction of the "Caviglione" and "Florestano" caves, notable for their ancient rock engravings. This first VR model, despite hardware limitations, provided an interactive exploration of the site. The subsequent development phase utilized Unreal Engine 5, incorporating Nanite technology for enhanced visual fidelity. This advancement resulted in a more detailed and immersive VR experience, presenting the Balzi Rossi cliff across different historical periods, including the Würm glaciation. Key to this phase was optimizing the VR experience for performance, focusing on stable frame rates and minimizing motion sickness, and integrating a multi-lingual interface for broader accessibility. Since November 2023, the VR setup at the Balzi Rossi Museum has been an educational and interactive feature, enabling visitors to explore the site's history virtually. This research demonstrates the potential of VR in cultural heritage preservation and education, providing a foundation for future technological improvements in the field.

(1) Background: Sleep disordered breathing represent a growing public health concern, especially among children and adolescents. Full-night polysomnography is considered the gold standard for diagnosing obstructive sleep apnea. Our goals are to identify personal and environmental risk factors for the onset and persistence of sleep respiratory disorders. We also want to investigate the differences in neuropsychological profiles; (2) Methods: This is an observational, retrospective cohort study. We collected information on adenoidectomy or adenotonsillectomy. We reviewed the clinical history and preoperative visits and collected data through a telephone questionnaire. Pediatric Sleep Questionnaire (PSQ) and the Pediatric Quality of Life Inventory (PedsQL) are questionnaires used for screening sleep respiratory disorders in children. The data were statistically analyzed it using SPSS version 22.0 for Windows (SPSS Inc., Chicago, IL); (3) Results: The study involved 138 patients, but only 100 parents participated. A higher percentage of patients with sleep disordered breathing were observed to have mothers who smoked during pregnancy. A smaller proportion of patients with sleep disordered breathing had a habit of using a pacifier. A rise in physical results is associated with a reduction in the PSQ at follow-up (p=0.051). An increase of overall academic achievement is associated with an average decrease in the PSQ at follow-up (p<0.0001). A more significant proportion of patients undergoing adenotonsillectomy were observed to have a history of prematurity and cesarean birth (4) Conclusions: These results provide essential information on the effectiveness and effects of adenotonsillectomy intervention compared to adenoidectomy intervention and the factors associated with SDB in children undergoing these interventions.

The relationship between pangolin-CoV and SARS-CoV-2 has been a subject of debate. Further evidence of a special relationship between the two viruses can be found by the fact that all known COVID-19 viruses have abnormally hard outer shell (low M disorder; i.e., low content of intrinsically disordered residues in the membrane (M) protein) that so far was found in CoVs associated with burrowing animals, such as rabbits and pangolins, in which transmission involves virus remaining in buried feces for a long time. While a hard outer shell is necessary for viral survival, a harder inner shell could also help. For this reason, the N disorder range of pangolin-CoVs, not bat-CoVs, more closely matches that of SARS-CoV-2 especially when Omicron is included. The low N disorder (i.e., low content of intrinsically disordered residues in the nucleocapsid (N) protein), first observed in pangolin-CoV-2017 amd later in Omicron, is associated with attenuation according to the Shell-Disorder-Model. Our experimental study revealed that pangolin-CoV-2017 and SARS-CoV-2 Omicron (XBB.1.16 subvariant) show similar attenuations with respect to viral growth and plaque formation. Subtle differences have been observed that are consistent with disorder-centric computational analysis.

Depth-sensing technology has led to broad applications of inexpensive depth cameras that can capture human motion and scenes in 3D space. Background subtraction algorithms can be improved by fusing color and depth cues, thereby allowing many issues encountered in classical color segmentation to be solved. In this paper, we propose a new fusion method that combines depth and color information for foreground segmentation based on an advanced color-based algorithm. First, a background model and a depth model are developed. Then, based on these models, we propose a new updating strategy that can eliminate ghosting and black shadows almost completely. Extensive experiments have been performed to compare the proposed algorithm with other, conventional RGB-D algorithms. The experimental results suggest that our method extracts foregrounds with higher effectiveness and efficiency.

This study aimed to demonstrate the potential role of Dual Energy CT in assessing Bone Mineral Density (BMD) in postmenopausal women. A retrospective study was conducted on 51 postmenopausal female patients who underwent DXA and DECT examinations for other clinical reasons. DECT images were acquired with spectral imaging using a 256-slice system. These images were processed and visualized using an HAP(fat) map. Statistical analysis was performed using the Bland-Altman method to assess agreement between DXA and DECT HAP(fat) measurements. Mean BMD, vertebral and femoral T-scores were obtained. For vertebral analysis, the Bland-Altman plot showed an inverse correlation (R2: -0.042; RMSE: 0.690) between T-scores and DECT HAP(fat) values for measurements from L1 to L4, while a good linear correlation (R2: 0.341; RMSE: 0.589) it was found for measurements at the femoral neck. In conclusion, we demonstrated the enhanced accuracy of BMD calculation through DECT, finding a statistically significant correlation only at the femoral neck where BMD results do not seem to be influenced by the overlap of the measurements on cortical and trabecular bone. This outcome could be beneficial in the future by reducing radiation exposure for patients already undergoing follow-up for chronic conditions.

Neonatal mortality remains a public health concern and timely identification and prompt intervention in the delivery room could improve the outcome in neonatal morbidity and mortality. We performed a retrospective study to help us finding the profile of the high-risk newborn regarding the need for NICU admission, necessary to establish a protocol regarding the mobilization of human and material resources for the urgent management of these situations. All deliveries and neonates born in Maternity of Bihor County Emergency Clinical Hospital from Romania were reviewed, including relevant maternal, foetal and perinatal data to identify risk factors that result in birth of newborns needing resuscitation at birth between 2012-2019. The number of births showed a downward trend but around 90% of the births were on term. The incidence of neonatal emergencies is increasing, the most frequently were respiratory, sepsis and other infections, cardiovascular emergencies, and extreme prematurity. It is noted that in 2021 the incidence of these neurological emergencies increased by three times compared to previous years. The neonatal and maternal risk factors associated with admission to the NICU were mother's age over 35 years, low level of education, second/more gestation, weight under 2500 g, Apgar score under 7, premature rupture of membranes, macrosomia and mother's infectious pathology. Accurate identification of risk factors and anticipation at the birth of a high-risk neonate would result in adequate preparation and prompt resuscitation of neonates who need some level of intervention and thus, reducing neonatal morbidity and mortality.

Controlling robots in space with necessarily low material and structural stiffness is quite challenging at least in part due to the resulting very low structural resonant frequencies. The frequencies are sometimes so low, the vary act of controlling the robot with medium or high bandwidth controllers lead to excitation of resonant vibrations. Biomimetics or biomimicry emulates models, systems, and elements of nature for solving such complex problems. Recent seminal publications have re-introduced the viability of optimal command shaping, and one recent instantiation mimics baseball pitching to propose control of highly flexible space robots. The readership will find a perhaps dizzying array of thirteen decently performing alternatives in the literature but could be left bereft selecting a method(s) deemed to be best suited for a particular application. Bio–inspired control of space robotics is presented in a quite substantial (perhaps not comprehensive) comparison, and the conclusions of the study indicate the top three performing methods based on minimizing control effort (i.e., fuel) usage, tracking error mean, and tracking error deviation include.

Background: Pancreatic neuroendocrine tumors (pNETs) represents a rare subset of pancreatic cancer. Functional tumors caused hormonal changes and clinical syndromes, while non-functional ones are often diagnosed late. Surgical management need a multidisciplinary planning, involving enucleation, distal pancreatectomy with or without spleen preserving, cen-tral pancreatectomy, pancreaticoduodectomy or total pancreatectomy. Minimally invasive ap-proach increased in the last decade compared to the open technique. The aim of this study is to analyze current diagnostic and surgical trends for pNETs, to identify better interventions and their outcomes. Methods: The study adhered to PRISMA guidelines, conducting a systematic review of literature from May 2008 to March 2022 across multiple databases. Several combinations of keywords was used ("NET", "pancreatic", "surgery", "laparoscopic", "minimally invasive", "robotic”, “enuclea-tion”,“parenchima sparing”) and relevant article references was manually checked. Manuscript quality was evaluated. Results: The study screened 3867 manuscripts, twelve studies were selected, primarily from Ita-ly, the United States, and China. A total of 7767 surgical treated patients was collected from 160 included centers. The mean age was 56,3 y.o. Enucleations (EN) and distal pancreatectomy (DP) was the most common performed surgery and represents 43.4% and 38.6% of the total interven-tions, respectively. Pancreatic fistula, post operative bleeding, re-operation and follow up was recorded and analyzed. Conclusions: Enucleation show better postoperative outcomes and lower mortality rates com-pared to pancreaticoduodenectomy (PD) or distal pancreatectomy (DP), despite similar risks of postoperative pancreatic fistula (POPF). DP was preferred over enucleation for pancreas body-tail, while laparoscopic enucleation is better for head pNETs.

The strong competition in the automotive industry has required manufacturers to implement lean production, both with methods and techniques specific to Industry 4.0. At the same time, universities must provide graduates with specific skills for applying these new production methods and techniques. In this context, a Lean Learning Factory was developed in the Pitesti University Center, which allows students to learn, experiment, and research, in an environment similar to that of enterprises, the new Lean Manufacturing methods and techniques, and Industry 4.0. The research presented in this study had as its objective identifying the minimum number of repetitions necessary to train operators who serve two differently organized workstations, one classic, the other including digital techniques, but on which the same assembly operation is performed. Several indicators were considered in the analysis, such as the number of errors, the number of stops, the effective duration of the work cycle, and the percentage ratio between the standard duration of cyclical activities and the effective duration of the work cycle. The evolution of these indicators was mathematically modelled by regression functions, using the least squares method. The obtained results also highlight the usefulness of applying the DOJO method as a Lean manufacturing-specific learning technique and the efficiency of implementing digital techniques in work organization.

Neurology is a quickly evolving specialty that requires clinicians to make precise and prompt diagnoses and clinical decisions based on the latest evidence-based medicine practices. In all Neurology subspecialties, Stroke and Epilepsy in particular, clinical decisions affecting patient outcomes depend on neurologists accurately assessing patient disability. Artificial intelligence (AI) can predict the expected neurological impairment from an AIS (Acute Ischemic Stroke), the possibility of ICH (IntraCranial Hemorrhage) expansion, and the clinical outcomes of comatose patients. This review article informs readers of artificial intelligence principles and methods. The article introduces the basic terminology of artificial intelligence before reviewing current and developing AI applications in neurology practice. AI holds promise as a tool to ease a neurologist’s daily workflow and supply unique diagnostic insights by analyzing data simultaneously from several sources, including neurological history and examination, blood and CSF laboratory testing, CNS electrophysiologic evaluations, and CNS imaging studies. AI-based methods are poised to complement the other tools neurologists use to make prompt and precise decisions that lead to favorable patient outcomes.

Tellurium exhibits exceptional intrinsic electronic properties. However, investigations into the modulation of tellurium's electronic properties through physical modification are notably scarce. Here, we present a comprehensive study focused on the evolution of the electronic properties of tellurium crystal flakes under plasma irradiation treatment by employing conductive atomic force microscopy and Raman spectroscopy. The plasma-treated tellurium experienced a process of defect generation through lattice broken. Prior to the degradation of electronic transport performance due to plasma irradiation treatment, a remarkable observation emerged: in the low-energy region of hydrogen plasma-treated tellurium, a notable enhancement in conductivity was unexpectedly detected. The mechanism underlying this enhancement in electronic transport performance was thoroughly elucidated by comparing it with the electronic structure induced by argon plasma irradiation. This study not only fundamentally uncovers the effects of plasma irradiation on tellurium crystal flakes, but also unearths an unprecedented trend of enhanced electronic transport performance at low irradiation energies when utilizing hydrogen plasma. This abnormal trend bears significant implications for guiding the prospective application of tellurium-based 2D materials in the realm of electronic devices.

Large datasets play a crucial role in the progression of surgical robotics, facilitating advancements in the fields of surgical task recognition and automation. Moreover, public datasets enable the comparative analysis of various algorithms and methodologies, thereby assessing their effectiveness and performance. The ROSMA (Robotics Surgical Maneuvers) dataset provides 206 trials of common surgical training tasks performed with the da Vinci Research Kit (dVRK). In this work, we extend ROSMA dataset with two annotated subsets: ROSMAT24, which contains bounding box annotations for instrument detection, and ROSMAG40, which contains high and low level gesture annotations. We propose an annotation method that provides independent labels for the right-handed tool and the left-handed tool. For instrument identification, we validate our proposal with a YOLOv4 model in two experimental scenarios. We demonstrate the generalization capabilities of the network to detect instruments in unseen scenarios. For gesture segmentation, we propose two label categories: high-level annotations that describe gestures at a maneuvers level, and low-level annotations that describe gestures at a fine-grain level. To validate this proposal, we have designed a recurrent neural network based on a bidirectional long-short term memory layer. We present results for four cross-validation experimental setups, reaching up to a 77.35% mAP.

Electromagnetic actuation can support many fields of technology, such as robotics or biomedical applications. In this context, fully understanding the system behavior and proposing a low-cost package for feedback control is challenging. Modeling the electromagnetic force is particularly tricky because it is a nonlinear function of the actuated object’s position and coil’s current. Measuring in real time the position of the actuated object with the precision required for accurate motion control is also nontrivial. In this study, we propose a novel, cost-effective electromagnetic set-up to achieve position control via visual feedback. We actuate vertically and under different experimental conditions a 10 mm diameter steel ball hanging on a low-stiffness spring, demonstrating good tracking performance (the position error remains within ±0.5 mm with a negligible phase delay in the best scenarios). The experimental results confirm the feasibility of the proposed set-up, which is characterized by minimum complexity and realized with off-the-shelf and cost-effective components. For these reasons, such a contribution helps to understand and apply electromagnetic actuation even further.

Zero-shot learning ability robotics enables robots to generalize their knowledge and perform tasks for which they have not been explicitly trained. This ability is extremely helpful because in classic learning approaches, robots are trained on specific tasks and require extensive data and labeled examples to perform accurately. However, in real-world scenarios, robots often encounter new or unseen tasks that were not part of their training data. We briefly survey works in this area to give the reader a perspective about progresses in this area.

Compared with the traditional robots on earth, space robotics present additional difficulties including complicated, multi–body dynamics (including anti–resonances absent with earthly robotic systems), space environmental forces and torques, communication delays, and high expense. Pointing accuracy requirements necessitate control algorithms that can accommodate flexible, multi–body dynamics particularly. The high cost of placing systems in space drives necessarily lightweight systems lacking structural stiffness. Natural frequencies of space robot vibration are often so low, the act of implementing control torques causes structural resonance. Seeking improved performance, this manuscript introduces and compares a dozen options, revealing seventy–percent reduction in tracking error may be achieved with only ten percent increase in control effort. Prequel work recommended tracking sinusoidal shaped trajectories while structurally filtering the first mode’s resonance and anti–resonance. The future research recommended in that prequel is manifest in this present work which recommends a simpler system of lower order, eliminating the notch compensation of the first resonance while no longer compensating the first anti–resonance.

Infrastructure monitoring, inspection, repair, and replacement in space is crucial for continued usage and safety, yet it is expensive, time-consuming, and technical very challenging. New robotics technologies and artificial intelligence algorithms are potentially novel approaches that may alleviate such demanding operations using existing or novel sensing technologies. Space structures must necessarily be very light weight due to high costs of placing robots in space. Several methods are proposed and compared to control highly flexible space robotics, where a key challenge is the presence of flexible resonant modes at frequencies so low as to reside inside typical feedback controller bandwidths. Such conditions imply the very action of sending control signals to the ultra-light weight robotics will cause structural resonance. Implementations of incrementally increasing order are offered, achieving over ninety percent performance improvement in trajectory tracking errors, while improvement using unshaped methods merely achieve twenty-four percent improvement in direct comparison (where the only modification is the proposed control methodology). Based on superior performance, single-sinusoidal trajectory shaping is recommended with a corollary benefit of preparing future research into applying deterministic artificial intelligence whose current instantiation relies on single-sinusoidal, autonomous trajectory generation.

In this work we report on our effort to design and implement an early introduction to basic robotics principles for children at kindergarten age. The humanoid robot Pepper, which is a great platform for human-robot interaction experiments, was presenting the lecture by reading out the contents to the children making use of its speech synthesis capability. One of the main challenges of this effort was to explain complex robotics contents in a way that pre-school children could follow the basic principles and ideas using examples from their world of experience. A quiz in a Runaround-game-show style after the lecture activated the children to recap the contents they acquired about how mobile robots work in principle. Besides the thrill being exposed to a mobile robot that would also react to the children, they were very excited and at the same time very concentrated. What sets apart our effort from other work is that part of the lecturing is actually done by a robot itself and that a quiz at the end of the lesson is done using robots as well. To the best of our knowledge this is one of only few attempts to use Pepper not as a tele-teaching tool, but as the teacher itself in order to engage pre-school children with complex robotics contents. We got very positive feedback from the children as well as from their educators.

Background: A new access technique was developed to reduce postoperative adverse events after the extraction of impacted maxillary wisdom teeth. Hence, this study aimed to assess the occurrence of adverse events after extraction of maxillary impacted wisdom teeth using traditional or modified access. Methods: Two different surgical incision designs were used for bilateral wisdom tooth extractions in 30 patients. The traditional incision was performed distal to the second molar in the center of the tuberosity, followed by a buccal releasing incision. After tooth extraction the wound was secured by sutures. The new technique consists of an oblique incision from the distal palatal aspect of the tuberosity towards the buccal aspect of the second molar. After tooth extraction, cyanoacrylate glue was used on the wound. Results: Lower pain was reported by patients at the site treated with the new technique (p<0.01). Edema, postsurgical bleeding, and hematoma were similar in both groups. The surgical time was shorter for the new technique (p<0.01). Conclusions: The new technique applied for the extraction of impacted maxillary wisdom teeth reduced postsurgical pain and the duration of surgery.

The problem addressed in this article consists of the motion control of a quadrotor, comprising model disturbances and uncertainties. In order to tackle model uncertainty, adaptive control based on reinforcement learning is used. The distinctive feature of this article, in comparison with other works on quadrotor control using reinforcement learning is the exploration of the underlying optimal control problem in which a quadratic cost and a linear dynamics allow an algorithm that runs in real time. Instead of identifying a plant model, adaptation is obtained by approximating the performance index given by the Q-function using directional forgetting recursive least squares that rely on a linear regressor build from quadratic functions of input/output data. The adaptive algorithm proposed is tested in simulation in a cascade control structure that drives a quadrotor. Simulations show the improvement in performance that results when the proposed algorithm is turned on.

In 1999, Molodtsov initiated the theory of soft sets as a new mathematical tool for dealing with uncertainties in many fields of applied sciences. In 2011, Shabir and Naz introduced and studied the notion of soft topological spaces, also defining and investigating many new soft properties as generalization of the classical ones. In this paper, we introduce the notions of soft separation between soft points and soft closed sets in order to obtain a generalization of the well-known Embedding Lemma to the class of soft topological spaces.

The impact of systemic vascular resistance (SVR) in hypertrophic (HCM) and amyloid cardio-myopathies has been seldom investigated. We studied pressure-strain loop derived myocardial work (MW) indices and SVR in patients with either sarcomere HCM or wild type transthyretin cardiac amyloidosis (ATTR), presented with heart failure and preserved left ventricular ejection fraction (HFpEF) at the outpatient cardiology units at Messina and Catania University Hospitals (Italy). Patients were in sinus rhythm and needed to have good transthoracic ultrasound imaging quality to undergo transthoracic strain-echocardiography. Other than conventional parameters, SVR and GWI (global work index) were measured. Based on cross-tabulation (a way to assess the ventricular-arterial coupling), the patients were then classified in 4 classes according to the cut-off values suggested by previous studies of 1,440 dyne/s/cm-5 for SVR (Stefadouros et al., 1973) and 1576 mm Hg% for GWI (Olsen et al., 2022). Sixty patients, 30 in each group, aged 61±16 years, 78% males, were studied. HCM were younger than ATTR patients and in a better clinical status (23% HCM vs 77% ATTR were NYHA class 3, p<0.001). Overall, 51 patients (85%) showed high SVR, of whom 21 were HCM (70%) and 30 ATTR (100%) (p<0.005). Both, SVR and GWI were impaired (the poorest class C) in 43% HCM patients (with greater left ventricular concentric hypertrophy) vs 93% of ATTR patients (in advanced NYHA class) (p<0.001). In conclusion, assessing SVR and GWI in HFpEF patients with HCM or ATTR can help clinicians to interpret the pathophysiological and clinical features of such complex diseases.

In this paper, we first define the concepts of r-fuzzy soft α-open (semi-open and δ-open) sets on fuzzy soft topological spaces based on the article Aygunoglu et al. (Hacet. J. Math. Stat., 43 (2014), 193-208), and the relations of these sets with each other are established. In addition, we introduce the concepts of fuzzy soft δ-closure (δ-interior) operators, and study some properties of them. Also, the concept of r-fuzzy soft δ-connected sets is introduced and studied with help of fuzzy soft δ-closure operators. Thereafter, we define the concepts of fuzzy soft α-continuous (β-continuous, semi-continuous, pre-continuous and δ-continuous) functions, which are weaker forms of fuzzy soft continuity, and some properties of these functions along with their mutual relationships are discussed. Moreover, a decomposition of fuzzy soft α-continuity and a decomposition of fuzzy soft semi-continuity is obtained. Finally, as a weaker form of a fuzzy soft continuity, the concepts of fuzzy soft almost (weakly) continuous functions are defined, and some properties are specified. Additionally, we explore the notion of continuity in a very general setting called, fuzzy soft (L, M, N, O)-continuous functions and a historical justification is introduced.

Classically the walk in biped robotics was obtained controlling balance during the whole step, i.e. guaranteeing that the pressure point under the soles always stayed in the polygon of the supporting feet. However, this assumed that the feet were able to transfer torque to the ground during the whole gait cycle. In spite of the fact that the amount of transferrable torque in the feet-ground contact is limited, it is possible only during some phases of the step, and the overall process is energetically inefficient. On the other side, starting from the passive motion of the rimless wheel falling on an inclined surface, and ending to the inverted pendulum with a compass, balance in the whole was proven in spite of dynamical instability inside each step. Along this line results of Foot Placement Estimation (FPE) in 2-D and 3-D showed how energy efficient walk was possible, emulating the human walk with a free fall on the swing foot and energy restitution at the foot collision with the ground for the next step. This model assumes pointy feet, so without torque transfer to the ground. In the realm of FPE, in previous papers the present author adopted the 3-D inverted pendulum in polar coordinates (Spherical Inverted Pendulum - SIP) to introduce omnidirectional walks with arbitrarily changing characteristics. No torque control was used during the step, i.e the pendulum was always in free fall at each step, the only control actions were at the beginning of the next step. These actions are: the change of angular velocities at the start of a new step, with respect to those given after the collision (emulating the torque action in the brief double stance period), to recover for the losses, and the preparation of the position in the frontal and sagittal planes of the swing foot for the next collision. The present paper improves this paradigm, proposing a general model to account for all characteristics of the biped and of the gait, with adding a minimum of dynamical complexity with respect to the SIP. This model allows, not only to walk omnidirectionally on a flat surface, but also to go up and down staircases.

3D/4D printing technologies are currently among the fastest growing, cutting edge fabrication technologies. The scale of their applications is vast and applicable to nearly all industries. 3D printing technologies are particularly popular in robotics, and especially in advanced design innovative solutions for areas such as manufacturing, space technology and medicine. The development of robotics, and in particular of the precision of manufactured components, such as actuators, pneumatic muscles, power transmission units, etc., means that new prototypes are still being made, where the use of 3D printers reduces the production time severalfold and allows for completing the necessary simulations and tests. In addition, the use of 3D printers allows for the production of thin-walled and cellular structures, which is a great advantage compared to conventional fabrication technologies. In the range of 3D printers available on the market, only a few selected technologies allow for actual use in the construction of advanced robot elements (muscles, vibration dampers, etc.). In the era of rapid growth of the precision of the available 3D printers and modern materials, 3D printing may soon become a major tool in robotics. This article presents an overview of 3D printing technologies and materials in terms of their application in robotics and provides examples of the use of 3D and 4D printing in prototyping and fabrication of robotic elements with particular emphasis on the current state of the art. The study considered the possibilities of using 3D/4D printing in robotics with the use of polymeric materials. The review of the literature and the research work currently being carried out in this area is very promising and it seems that 3D/4D printing in robotics is widely used and is still developing, which allows to conclude that in the near future the number of research works in this field will increase rapidly.

Crack inspection is important to monitor the structural health of pavement structures and to facilitate an easier rehabilitation process. Currently, pavement crack inspection is conducted manually, which is inefficient and costly at the same time. For solving the problem, this work has developed a robotic system for automated data collection and analysis in real-time. The robotic system navigates on the pavement and collects visual images from the surface. A deep learning-based semantic segmentation framework named RCDNet was proposed and implemented on the onboard computer of the robot to identify cracks from the visual images. Simulation results show that the deep learning model obtained 96.29% accuracy for predicting the images. The proposed robotic system was tested on both indoor and outdoor environments and was observed that it can complete inspecting a 3m × 2m grid within 10 minutes and a 2.5m × 1m grid within 6 minutes. This outcome shows that the proposed robotic method can drastically reduce the time of manual inspection. Furthermore, a severity map based on the results from visual images was also generated to provide an idea of which locations should be paid more attention to repair in a test grid.

Continuum robots play the role of end-effector in various surgical robots and endoscopic devices. The robots may be categorized as rigid or soft continuum robots (SCRs). While the SCRs have proven advantages such as safety and compliance, more research and development are required to enhance their capability for specific medical scenarios. This research aims at designing a soft robot considering concepts of geometric and kinematic similarities. The chosen application is a semi-invasive medical application known as Transesophageal Echocardiography (TEE), but the methodology can be implemented in other similar applications. Since established rigid carrier construction make use of principles we find as well embodied in vertebral spines, the paragon for soft robot solution can be the phylogenetic precursor of the spine, the Chorda dorsalis. The feasibility of fabrication of a soft endoscopic device derived from that paragon within a robotics laboratory was shown empirically by producing a three-segment pneumatic SCR. The kinematic model was proposed based on the method of transformation matrices, and an algorithm based on a self-organizing map (SOM) was proposed and applied to realize kinematic similarity. The simulation results indicate that the algorithm acting as an open-loop controller forces the soft robot tip to follow the desired path which in this case is the path of the rigid probe. It is concluded that the solution provides a soft robot that can surrogate and succeed the traditional rigid counterpart owing to size, workspace, and kinematics.

Proteins have the ability to adsorb on the surface of materials, such as soft contact lenses (SCLs), and can affect the hydrophobicity, roughness and surface properties of the contact lenses (CLs), which, in turn, can influence the friction between the lenses and the ocular surface. Excessive friction between contact lenses and the ocular surface can lead to discomfort for the wearer and may cause irritation or inflammation of the cornea, better known as corneal ulcers (keratitis). Bovine serum albumin (BSA) is often used as a standard protein in biocompatibility testing of materials, including contact lenses. One standard commercial contact lenses was tested under lubricated conditions to access the coefficient of friction (CoF), being the contact lubricated with a tear like fluid (TLF) solution containing six different concentrations of BSA. In all cases, a good linearity of the results of the friction force was verified, so the first friction law can be applied to determine the value of the coefficient of friction. It was found that friction increases with increasing protein concentration.

The present review compared the efficacy of soft tissue substitutes (STS) and autogenous free gingival graft (FGG) or connective tissue graft (CTG) in mucogingival procedures to increase keratinized tissue (KT) width around teeth and implants. Two independent examiners performed the electronic search on Medline and Cochrane Library based on the following PICO’s format: (P) adult patients; (I) soft tissue substitutes and FGG/CTG; (C) STS vs CTG; STS vs FGG; STS vs CTR; (O) KT width gain; (S) Systematic Reviews, Randomized Controlled Trials. Results showed that around teeth, all biomaterials showed superior performance compared to CAF alone for treating gingival recessions. However, when compared to CTG, ADM yields the most similar outcomes to the gold standard (CTG), even though in multiple recessions CTG still continue to be considered the most favorable approach. Use of STSs (acellular matrix or tissue engineered) in combination with an apically positioned flap resulted in a significantly less gain of KTW compared to what achieved with FGG and APF. Around dental implants, free gingival grafts were deemed more effective than soft tissue substitutes in enhancing keratinized mucosa width.

Background: Autism spectrum disorder (ASD) is a persistent neurodevelopment disorder frequently co-occurring with Attention-Deficit/Hyperactivity Disorder (ADHD) and behavior-related disorders. While behavioral therapy is the first-line option to manage ASD core symptoms, pharmacological therapy is sometimes needed to treat acute problems, such as agitation and aggressive behaviors. Recent guidelines recommend neuroleptics to reduce psychomotor agitation in people with ASD. However, since children with ASD are often drug-resistant, alternative treatments are often justified. Reports from literature showed that intra-venous valproate (IV-VPA) can be effective in reducing agitation in psychiatric patients, with lower frequency of adverse events compared to convention-al treatments. However, since findings are occasionally inconsistent, IV-VPA is not an approved option in clinical psychiatry. We aim at improving the knowledge on the IV-VPA treatment option in emergency psychiatry in the pediatric age. Methods: We report the case of a 11-year-old boy suffering from a complex neurodevelopmental condition, who experienced a psychotic episode with severe aggressive and disruptive behaviors, successfully treated with IV-VPA. Besides, we conducted an up-dated literature review on this topic. Conclusion: In our case, first-line therapies proved to be ineffective. On the contrary, IV-VPA led to a safe and prompt clinical success, in line with other reports. Based on our literature review, IV-VPA can be highly effective and can reduce the risk of adverse events that frequently occur with the use of high-dose standard medications in emergency psychiatry.

Background: The validation of laser usage during laparoscopic procedures, notably by Camran Nezhat in the late 1980s, has been significant. Lasers offer precision and depth control in tissue vaporization without bleeding. Surgical intervention remains central in managing endometrio-sis-associated pain and infertility, especially for patients unresponsive to hormonal therapy. Methods: This retrospective cohort study included 200 patients with SPE who underwent laparo-scopic laser vaporization. Surgery was performed using a CO2 laser, and histological confirma-tion of endometriosis was obtained for all cases. Pain scores and SF-36 questionnaire domains were assessed preoperatively and postoperatively. Fertility outcomes were evaluated among pa-tients desiring pregnancy. Results: Significant improvements in pain score and SF-36 questionnaire domains were ob-served postoperatively (p-value

In contemporary construction, the prevalence of vibration serviceability issues in lightweight and slender structures has become increasingly common, owing to advancements in building materials and construction methods. While these structures often meet the criteria for ultimate limit states, they can still elicit complaints due to excessive vibrations induced by human activity. To address this challenge, the Integral Resonant Control (IRC) technique has emerged as a favored approach for actively damping vibrations in various systems. This study introduces a fresh perspective on implementing a multi-input multi-output (MIMO) IRC scheme for active vibration control (AVC) specifically tailored for pedestrian structures utilizing inertial mass actuators. Building upon a common framework and design methodology outlined in previous research, this work presents a novel application of MIMO IRC for AVC. The designed controller is rigorously tested and implemented on a laboratory floor structure to validate its efficacy.

By combining stochastic variational inference with message passing algorithms we show how to solve the highly complex problem of navigation and avoidance in distributed multi-robot systems in a computationally tractable manner, allowing online implementation. Subsequently, the proposed variational method lends itself to more flexible solutions than prior methodologies. Furthermore, the derived method is verified both through simulations with multiple mobile robots and a real world experiment with two mobile robots. In both cases the robots shares the operating space and needs to cross each other’s paths multiple times without colliding.

In this manuscript, we first introduce some properties of r-fuzzy soft α-open sets in fuzzy soft topological spaces based on the manuscript Aygunoglu et al. (Hacet. J. Math. Stat. 2014, 43, 193-208). In addition, we define the concepts of fuzzy soft α-closure (α-interior) operators, and investigate some properties of them. Furthermore, the concept of r-fuzzy soft α-connected sets is defined and characterized with help of fuzzy soft α-closure operators. Thereafter, we introduce and study the concepts of fuzzy soft almost (weakly) α-continuous mappings, which are weaker forms of fuzzy soft α-continuous mappings, and we discuss some properties of fuzzy soft α-continuity. Moreover, we establish that fuzzy soft α-continuity → fuzzy soft almost α-continuity → fuzzy soft weakly α-continuity, but the converse may not be true. It is also we show that the composition is fuzzy soft almost α-continuous mapping if, is fuzzy soft α-continuous mapping and is fuzzy soft almost continuous mapping. Finally, some new types of compactness via r-fuzzy soft α-open sets are defined, and the relationships between them are examined.

In contemporary design practices, there is a disconnect between the design techniques used for early-stage design experimentation and performance analysis, and those used for the manufacture and construction. This study addresses the problems in developing an integrated digital design workflow and provides a research framework for integrating environmental performance requirements with robotic manufacturing processes on a construction site. The proposed method enables the user to import a design surface, identify design parameters, set several environmental performance goals, and thereafter simulate and select a robotic building strategy. Based on these inputs, design alternatives are developed and evaluated, considering their robotically simulated constructibility, in terms of their performance criteria. To validate the proposed method, the design is evaluated in an experiment wherein a double-skin facade perforation is generated using the proposed methodology. The results suggest a heuristic feature to improve the simulated robotic constructibility. Moreover, the functionality of the prototype is demonstrated.

We describe an interesting case report about a patient with hemophilia A with severe chronic elbow arthropathy who underwent multiple surgical because of his condition. We collected all the clinical and imaging findings, and we compared the decision-making flow chart and the surgery performed with the most recent indications, treatments and complications reported in the literature. The aim of this case report is to show how usually the hemophilic patient even if young usually comes to our attention from the beginning with complex and advance musculoskeletal disease. Elbow hemophilic arthropathy is a complex disease and the management in these patients could be more difficult than others because of the higher risk of complications rate after all surgical procedures, for this reason it’s very important to treat these patients in hub centers with expertise in well-coordinated multidisciplinary teams. The path from diagnosis to surgical treatment of hemophilic elbow arthropathy can be a risky one, as it happened in this case.

Two polyurethanes (PUs) were similarly synthesized by reacting a cycloaliphatic isocyanate with 1,4 butanediol and two polyols of different nature (polyester, polycarbonate diol) with molecular weights of 1000 Da. The PU made with polycarbonate diol polyol (YCD) was the only showing intrinsic self-healing at 20 °C. For assessing the mechanism of intrinsic self-healing of YCD, a structural characterization by molecular weights determination, infrared and X-ray photoelectronic spectroscopies, differential scanning calorimetry, X-ray diffraction, thermal gravimetric analysis and dynamic mechanical thermal analysis was carried out. It was concluded that the self-healing at 20 °C of YCD was due to non-covalent dynamic exchange interactions among the carbonate groups of the soft segments. Therefore, the chemical nature of the polyol played a key role in developing PUs with intrinsic self-healing at 20 °C.

Most common classifications for acetabular bone defects are based on radiographic two-dimension imaging, with low reliability and reproducibility. With the rise of modern processing techniques based on 3D modelling, methodologies for volumetric quantification of acetabular bone loss are available. Our study aims to describe a new methodology for quantitative assess-ment of acetabular defects, based on 3D modelling, focused on the surface analysis of the integrity of the main anatomical structures of the acetabulum represented by four corresponding sectors (posterior, superior, anterior, and medial). The defect entity is measured as the Area Increase Ra-tio (AIR) detected in all the sectors analyzed on three planes of view (frontal, sagittal and axial) compared to healthy hemipelvises. The analysis was performed on 3D-models from the CT-scan of six exemplary specimens with a unilateral pathological hemipelvis. AIR between the native and the pathological hemipelvis was calculated for each sector, for a total of 48 analysis (range, +0.93% - +171.35%). AIR of >50% were found in 22/48(45.8%) sectors and affected mostly the posterior, medial and superior sectors (20/22, 90.9%). Qualitative analysis showed consistency of the data with the morphological features of the defects. Further studies with larger samples are needed to validate the methodology and potentially develop a new classification scheme.

Lung cancer remains the main cause of global cancer-related deaths. Currently low-dose computed tomography (LD-CT) shows a 20% reduction of mortality. However, its clinical suitability is hindered by cost, radiation, and some false positives. Thus, the discovery non-invasive and less-expensive biomarker is urgent needed. In this scenario, proteins released in biological fluids could be considered interesting biomarkers for their role in cancer development. We conducted a pioneering case-control pilot study aimed at assessing the usefulness of Raf Kinase Inhibitory Protein (RKIP) and its phosphorylated form (pRKIP) as potential early-stage lung cancer biomarkers. Urine and Blood samples of two consecutive and independent cohorts of lung cancer patients and healthy controls were screened by means of a novel experimental ELISA assay designed to evaluate both forms of the biomarker. Although urinary levels of RKIP were not statistically different between the lung cancer group and high-risk healthy group, serum ones instead increased significantly in early stage LC patients and permitted to discriminate LC patients from both low-risk (HS) and high-risk healthy subjects (HR-HS) with an overall 93% accuracy (AUC 0.93) when LC was compared to HS and 74% (AUC 0.73) when it was compared to high-risk group. Of note, the analysis of RKIP/pRKIP ratio also showed a high accuracy (90% - AUC 0.95) in discriminating LC patients from HS and more importantly, it allowed to identify LC patients compared to HR-HS, with a higher accuracy (79% - AUC 0.79) than RKIP alone. We hypothesize that serum RKIP levels may be correlated to the activation of the immune systems against the tumor during the first phases of its development. Our study identified a preliminary, non-invasive, RKIP and pRKIP profile able to discriminate with high specificity and sensitivity the early-stage lung cancer patients from high-risk Healthy Subjects. These results, although preliminary, suggest the utility of measuring RKIP/pRKIP as potential new screening test for lung cancer and provide the basis for future validation studies.

Unmanned vehicles (UVs) have become increasingly important in various scenarios of civil and military operations. The present work aims at the conceptual design of a modular Amphibious Unmanned Ground Vehicle (A-UGV), that can be easily adapted for different types of land and/or water missions, with low monetary cost (&lt;5k€, without sensors). Basing the design on the needs highlighted in the 2021 review of the Strategic Directive of the Portuguese Navy, the necessary specifications and requirements are established for two mission scenarios. Then a market research analysis focused on vehicles currently available, and their technological advances, is conducted to identify existing UVs solutions and respective characteristics/capabilities of interest to the current work. To study and define the geometry of the hull and the configuration of the A-UGV itself, preliminary computational structural and fluid analyses are carried out to ensure it complies with the specifications initially established. As a result, one obtains a fully electric vehicle, with approximate dimensions of 1050×670×450mm (length-width-height), enabled with 6×6 traction capable of reaching 20km/h in land, possesses amphibious capabilities of independent propulsion in water up to 8kts, and with an estimated autonomy of over 60 minutes.

The rapid advancement of artificial intelligence (AI) and robotics has led to significant progress in various medical fields, including interventional radiology (IR). This review focuses on the research progress and applications of AI and robotics in IR, including deep learning (DL), machine learning (ML), and convolutional neural networks (CNNs) across specialties such as oncology, neurology, and cardiology. To ensure the breadth and depth of this review, we implemented a systematic literature search strategy, selecting research published within the last five years. We conducted searches in databases such as PubMed and Google Scholar to find relevant literature. Special emphasis was placed on selecting large-scale studies to ensure comprehensiveness and reliability of the results. We discuss the role of AI techniques used before, during, and after intervention treatments and the advantages of robotics in achieving precise operations and reducing intra-operative risks. Challenges faced in the implementation of these techniques are also addressed. Finally, we explore the future trends and potential applications of AI and robotics in interventional therapy, highlighting their potential to improve patient treatment outcomes and quality of life.

This paper presents a state machine based architecture which enhances flexibility and reusability of industrial robots, more concretely dual-arm multisensor robots. The proposed architecture, in addition to allowing absolute control of the execution, eases the programming of new applications by increasing the reusability of the developed modules. Through an easy-to-use graphical user interface, operators are able to create, modify, reuse and maintain industrial processes increasing the flexibility of the cell. Moreover, the proposed approach is applied in a real use case in order to demonstrate its capabilities and feasibility in industrial environments. A comparative analysis is presented for evaluating presented approach versus traditional robot programming techniques.

Background: clubfoot is a common congenital deformity. The Ponseti technique, involving early corrective manipulations followed by the application of long leg casts and Achilles tenotomy, is widely accepted as the preferred treatment. Rapid healing of the tendon after surgery has been documented, but the aspect regarding tendon structure and properties is not known. Three cases of Achilles tendon rupture in adolescent previously treated for clubfoot have been described in the literature. Since rupture is a rare event in this age group a possible correlation with previous surgery has been hypothesized. The primary aim of the study was to compare the ultrasound findings of the Achilles tendon, in patients treated for clubfoot, between patients treated with casting alone and the ones who underwent surgery (percutaneous tenotomy or Z-plasty lengthening). Methods: 22 asymptomatic patients, (34 feet) median age 12 years, previously treated for clubfoot, were recruited for this study; the patients underwent an Achilles tendon ultrasound examination during a follow-up outpatient visit. Results: a greater thickness and structural alterations with presence of hypoechoic areas of the operated tendons compared to those treated with plaster alone were observed (p value: 0.0498 and

In this article, we introduce the concept of soft intervals, soft ordering and sequences of soft real numbers, and some of their structural properties are studied. The notion of soft Lebesgue measure on the soft real numbers has been introduced. Also, a correspondence relationship has been established between the soft Lebesgue measure and the classical Lebesgue measure. Furthermore, we have studied some exciting results and relations between the soft Lebesgue measure and the Lebesgue measure of soft real sets.

Background and Objectives: High job strain is worsening the outcome in coronary artery disease, CAD. Severe dissatisfaction on workplace, imbalance between high demands , and low rewards, are affecting the quality of life, and diminishing the duration of life, especially in CAD patients. Our study included two samples : CAD patients (experimental group), and without CAD patients, but with traditional risk factors (control group). The main objective of the study was the role played by high sensitivity C reactive protein, hs CRP, and microalbuminuria, as mediators of job strain and CAD relationship. Secondary objectives were the following: identification of the most vulnerable patients( with significant job strain) and intervention towards this category, for cardiovascular events prevention (primary or secondary). Materials and Methods: The utilized methods were the following : clinical exam; electrocardiogram; echocardiogram; non contrast enhanced computed chest tomography; laboratory findings ( lipid profile, glycemia, hs CRP, microalbuminuria); type D scale, DS 14; depression questionnaire, PHQ-9; and satisfaction with work scale, SWWS. Results: The highest values for hs CRP and microalbuminuria were noticed in patients with the lowest Likert score, for both samples CAD, and without CAD patients. The highest job strain was noticed in females. More than half of CAD patients ,with low Likert scores, revealed myocardial infarction. Conclusions: Microalbuminuria and hs CRP were statistical significant in the study as intercessors, in job strain and CAD relationship. The most vulnerable patients for vascular events were females, in both groups : CAD and “CAD waiting desk”. In CAD sample, the vascular vulnerability was also increased by high job strain.

This article explores the implementation of high accuracy GPS denied Ad-Hoc localization. There is little research on Ad-Hock UWB-enabled localization systems with mobile and stationary nodes. This work aims to demonstrate the localization of bicycle-modeled robots in a non-static environment through a mesh network of mobile, stationary robots and ultra-wideband sensors. The non-static environment adds a layer of complexity when actors can enter and exit the node’s field of view. The method starts with an initial localization step where each unmanned ground vehicle (UGV) uses the surrounding, available anchors to derive an initial local or, if possible, global position estimate. The initial localization uses a simplified implementation of the iterative multi-iteration Ad-Hoc Localization System (AHLos). This estimate was refined using an unscented Kalman filter (UKF) following a constant turn rate and velocity magnitude model (CTRV). The UKF fuses the robot’s odometry and the range measurements from the Decawave ultra-wideband receivers stationed on the network nodes. Through this position estimation stage, the robot broadcasts to its neighbors its estimated position to help the others further improve their localization estimates and localize themselves. This wave-like cycle of nodes helping to localize each other allows the network to act as a mobile Ad-Hoc localization network.

Automation is the key aspect of science and technology field and refers to controlling the systems for efficient output requirements. The development of robotics and similar, technologies in 21st century is a vast topic of research and significant progress has been made on this field. This research study focuses on building a ribbon-cutting robot with a Bluetooth interface for event inaugurations. The entire system hinges on constructing a prototype that is mounted on a robotic car frame with four wheels and an Arduino controller. In this case, ribbons are cut using a nickel wire, and it may be paired with an Android device via Bluetooth or an application. The robot is one of the first steps toward the development of autonomous, cognitive robots and can be used in a variety of events. Efficient temperature monitoring is done with help of LM35 sensor and Bluetooth based communication in order to monitor the conditions and effectively control the actions for which robot is designed. The robot has significantly allowed authors for desired tests on ribbon cutting and final results obtained were very exciting for its desired application target. Ribbon-cutting robots find applications in various events, including inaugurations, exhibitions, and ceremonies. Their precision and novelty add value to such occasions.

Background Augmented reality (AR) in surgery can offer an enhanced view of reality through the superimposition of computer-generated digital images on the real environment. It allows surgeons to integrate image visualisation, improving operative efficiency, surgical outcomes, surgical training and patient education. This review aims to evaluate the current status of augmented reality in surgery, surgical training and potential future applications. Methods We performed a non-systematic review of available literature from January 2005 to August 2021 by searching PubMed, EMBASE and the Cochrane library using a combination of terms “augmented reality”, “virtual reality”, “surgery”, “simulation” and “training”. Articles considered for this review were identified by relevant search criteria including title, keywords, abstract, and full-text. Conclusions AR technologies present an exciting new trend with multiple potential applications in surgery. Intraoperative AR systems have shown promise in specialties involving fine movement of organs during surgical procedures, including Neurosurgery, Ears, Nose and Throat and Orthopaedic Surgery. AR has also exhibited the potential to enhance surgical training and improve knowledge acquisition; it can foster international collaborations via telesurgery and telepresence. In the near future, AR will likely work in symbiosis with surgeons, serving as a complex computer-human coalition which can improve patient outcomes, patient education and surgical training.

Opossums, native to the Americas, are unique marsupials with over 100 species. The Common Opossum and Virginia Opossum are notable species. They are nocturnal, omnivorous, and adapt to various habitats. Their reproduction involves a short gestation and marsupial pouch development. Despite their ecological benefits like seed dispersal and insect control, their proximity to human habitats exposes them to pathogens, posing public health risks. These include protozoa, helminths, and arthropods that can spread zoonotic parasites and vector-borne diseases. The marsupial immune system, including opossums, is complex, rivaling eutherian mammals. Key immune genes were identified in the grey short-tailed opossum genome. CD1 protein and VpreB surrogate light chain were also found. Marsupials are proposed as ideal models for studying developmental immunology. A West Indian opossum (Didelphis marsupialis) was found and examined. Blood tests revealed abnormalities, including a low white blood cell count and signs of anemia. The results contribute to understanding the species’ health and adaptability in the wild.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Background: Early postoperative airway management after laryngo-tracheal surgery is crucial. Acute respiratory failure due to glottis’ oedema may occur, requiring reintubation. This can prolong ventilatory assistance, jeopardizing the anastomosis. To date, only judicious steroid administration and fluid management are available to avoid more invasive procedures. High-Flow-Oxygen-Therapy(HFOT) is a noninvasive O2 support method providing humidification, warmed air, Positive-End-Expiratory-Pressure(AIRVO2). No data exist about HFOT use to prevent early complications after laryngo-tracheal surgery. Methods: Between Sept.2020-Sept.2022, 107 consecutive patients underwent laryngo-tracheal surgery received HFOT(Group A). Data and long-term results were compared with those of 80 patients operated between Sept.2018-Aug.2020(Group B), when HFOT was not available. All patients were operated in a single center. No pre- or post-operative settings changed, except for HFOT introduction. We analyzed and compared the risk for “delayed” reintubation (unexpected reintubation within the first 24-48 hours after extubating/laryngeal mask removal) in the two groups. Results: No patients reported HFOT-related adverse events. Control group(B) presented “delayed” reintubation in 37% (p= 0.027), Intensive Care Unit admission in 67%(p=0.005) and longer hospital stay(p=0.001) compared to HFOT group(A). Minor complications rate was 3% in both group and overall mortality was 0%. Re-stenosis was described in 4.6% of HFOT group, without a statistically significant difference (p=0.7006). Conclusions: Our study is the first to investigate HFOT use in patients undergoing laryngo-tracheal surgery, potentially representing a consistent innovation in the peri-operative management of these patients. With the limit of a retrospective series, we would suggest HFOT use for preventing post-operative reintubation rate, possibly reducing ICU admission and hospital stay.

Amylose content (AC) stands as a pivotal determinant of rice grain quality, primarily governed by the Waxy gene (Wx), with its allelic diversity significantly influencing AC variation. In the current culinary landscape, soft rice varieties, known for their low AC and superior palatability, are particularly sought after by consumers. Notably, many soft japonica rice varieties cultivated in southern China, including the Nangeng series, are characterized by the presence of the Wxmp allele, derived from the ancestral Wxmq allele. While both alleles are associated with reduced AC, there remains a paucity of detailed understanding regarding the interplay between specific functional single nucleotide polymorphisms (SNPs) within these alleles and the overarching rice grain quality. Employing site-directed mutagenesis, we engineered three distinct transgenic rice lines, each harboring either the Wxmp, Wxmq, or Wxb-5c alleles, against the background of the glutinous rice cultivar Nip(wx). This suite of transgenic rice showcased a gradation ingrain transparency inversely correlated to AC, delineating a sequence from Wxmq, signifying the lowest, through Wxmp, to Wxb-5c, indicating the highest. Consequently, this gradation in AC precipitated variations in other rice grain physicochemical attributes, such as the taste value of cooked rice, gel consistency (GC), and starch pasting properties. Furthermore, analyses of gene expression and enzyme activity revealed that the functional SNPs, Ex4-53G/A and Ex5-53T/C, lead to a decline in the GBSSI enzyme activity without affecting expression levels. These findings underscore the potential of harnessing these SNPs in breeding programs aimed at developing soft rice varieties endowed with enhanced culinary qualities.

Background and Objectives: The purpose of the study was to analyze the relationships between several clinical and biological factors, but also the tumor topography and surgical strategies used in patients with colorectal cancer. Materials and Methods: We designed an analytical, observational, retrospective study that included patients admitted to our emergency surgical department and diagnosed with colorectal cancer. The study group inclusion criteria were: patients admitted during 2020-2022; patients diagnosed with colorectal cancer (including the ileocecal valve); patients who benefited from a surgical procedure, either in emergency or elective. Results: In our study group, consisting of 153 patients, we accounted for 56.9% male patients and 43.1% female patients. The most common clinical manifestations were pain (73.2% of the study group), followed by abdominal distension (69.3% of the study group) and absence of intestinal transit (38.6% of the study group). A number of 69 patients were operated in emergency (45.1%), while 84 patients (54.9%) benefited from elective surgery. The most frequent topography of the tumor was the sigmoid colon, with 19.60% of the patients, followed by the colorectal junction, with 15.68% of the patients and superior rectum and inferior rectum, with 11.11% of the patients in each subcategory. The most frequent type of procedure was right hemicolectomy (21.6% of the study group), followed by rectosigmoid resection (20.9% of the study group). The surgical procedure was finished by performing an anastomosis in 49% of the patients, an ostomy in 43.1% of the patients, while for 7.8% of the patients, a tumoral biopsy was performed. Conclusions: Colorectal cancer remains one of the most frequent cancers in the world, with a heavy burden that involves high mortality, alterations in the quality of life of the patients and their families, and also the financial costs of the medical systems.

Clusterin (CLU) protein is involved in various pathophysiological processes including carcinogenesis and tumor progression. In recent years, the role of the secretory isoform has been demonstrated in tumor cells, where it inhibits apoptosis and favors the acquisition of resistance to conventional treatments used to treat cancer. To determine the possible therapeutic potential of inhibiting this protein, numerous studies have been carried out in this field. In this paper, we show the existing knowledge on the inhibition of this protein in different types of cancer and discuss the importance it could have in the development of new therapies directed against this pathology.

The advantage of FPGAs lies in the ability to implement a fully hardware solution for interfacing with various input/output (I/O) devices. Each block can work in parallel with all the others, simplifying the satisfaction of timing constraints. However, this hardware utilization consumes FPGA resources that could otherwise be allocated to the primary project. An alternative involves employing a small "soft-core" processor implementing I/O in software. With the goal to design and evaluate a new tiny soft-core processor optimized for FPGA resources in I/O , a novel processor named Baby8 is developed. It is an 8-bit CISC soft-core processor optimized for reduced FPGA resources including program size for 8-bit applications. The number of instructions is not large but any instruction can access arbitrary memory locations. The performance and resource utilization of the newly designed processor are evaluated and compared with a variety of other soft-core processors. The results demonstrate its competitive performance, achieving an average maximum clock frequency of approximately 57 MHz and a power consumption of around 2mW. Furthermore, it conserves nearly half of the FPGA resources in implementation.

The soft robot has many degrees of freedom, strong environmental adaptability and good human-computer interaction ability. As the end-effector of the soft robot, the soft gripper can grasp objects of different shapes without destructivity. Based on the theoretical analysis of the soft robot, the kinematics model of the flexible gripper and the theoretical model of the bending deformation of the air cavity were established. Accordingly, the relationship between the bending angle of the soft gripper and the air pressure was determined. Through the application of finite element software, the bending degree of pneumatic network multi-cavity soft gripper was simulated by finite element software, and the influence of structural parameters of soft actuator on bending deformation was determined. In addition, with the 3D technology conducting the printing of soft gripper fixtures and molds, the injection molding the actuator and the human-computer interaction interface controlling the movement of the gripper, the adaptability of the soft gripper in grasping object was verified. The result shows that the software gripper possesses good flexibility and can better grasp objects of different shapes.

Soft robotic manipulators consisting of serially-stacked segments combine actuation and structure in an integrated design. This design can be miniaturised while providing suitable actuation for applications such as minimally invasive surgery and for inspections in confined environments. The control of these robots, however, remains challenging, due to the difficulty in accurately modelling the robots, in coping with their redundancies, and in solving their full inverse kinematics. In this work, we explore a hybrid approach to control serial soft robotic manipulators that combines machine learning (ML) to estimate the inverse kinematics with a closed-loop control to compensate the remaining errors. For the ML part, we compare various approaches, including both kernel-based learning and more general neural networks. We validate the selected ML model experimentally. For the closed-loop control part, we first explore Jacobian formulations using both synthetic models and numerical approximations from experimental data. We then implement integral control actions using both these Jacobians, and evaluate them experimentally. In an experimental validation, we demonstrate that the hybrid control approach achieves setpoint regulation in a robot with 6 inputs and 4 outputs.

Collaborative robotics is a major topic in current robotics research posing new challenges, especially in Human-Robot Interaction. The crucial aspect in this area of research focuses on understanding the behavior of robots when engaging with humans, where reinforcement learning is a key discipline that allows us to explore sophisticated emerging reactions. This review aims to delve into the relevance of different sensors and techniques, with special attention to EEG (electroencephalography data on brain activity) and its influence on the behavior of robots interacting with humans. In addition, mechanisms available to mitigate potential risks during the experimentation process such as virtual reality will also be addressed. In the final part of the paper, future lines of research combining the areas of collaborative robotics, reinforcement learning, virtual reality and human factors will be explored, as this last aspect is vital to ensure safe and effective Human-Robot Interactions.

Commonly, professors, students and researchers from universities around the world use software distributed under a license agreement for computer simulation purposes, which requires a computer with considerable hardware capabilities. Consequently, this implies a high cost to conduct simulations that require implementing numerical methods in all areas of engineering, particularly in the field of robotics and nonlinear control. This paper presents the design and results analysis of a low-cost and open-source frugal computer simulation tool with applications to robotic nonlinear control, for instance, for numerical simulations of manipulator robot control based on dynamic models. Using a single board minicomputer with with reduced computing power, Raspberry Pi, together with free software, GNU-Octave, trajectory tracking control simulations in the joint space of a Selective Conformal Assembly Robot Arm (SCARA) are achieved by solving a system of nonlinear differential equations, represented in matrix form, which includes the control law and the system model. The results of the proposed alternative are compared by running the same simulation code on a laptop computer using MATLAB and GNU Octave, which show minimal deviations and reasonable time complexity. Moreover, considering the frugality curve calculated for this approach, in addition to the low acquisition cost of the simulation software tool, it would allow the creation of a simulation laboratory in some universities with budgetary constraints for educational and research purposes.

(1) Background: Surgical phases form the basic building blocks for surgical skill assessment, feedback and teaching. Phase duration itself and its correlation to clinical parameters has not yet been investigated. Novel commercial platforms provide phase indications but have not been assessed for accuracy yet. (2) Methods: We assess 100 robot-assisted partial nephrectomy videos for phase duration based on previously defined proficiency metrics. We develop an annotation framework and subsequently compare our annotations to an existing commercial solution (Touch Surgery, Medtronic™). We subsequently explore clinical correlations between phase durations and peri-operative parameters. (3) Results: Objective and uniform phase assessment requires precise definitions derived from an iterative revision process. Comparison to a commercial solution shows large differences in definitions across phases. BMI and duration of renal tumor identification correlate positively, as well as tumor complexity and both tumor excision and renorraphy duration. (4) Conclusions: Surgical phase duration can be correlated with certain clinical outcomes. Further research should investigate if retrieved correlations are also clinically meaningful. This requires increasing dataset sizes and facilitation through intelligent computer vision algorithms. Commercial platforms can facilitate this dataset expansion and help unlock the full potential, provided the disclosure of phase annotation details.

The daVinci Surgical Robot has revolutionized minimally invasive surgery by enabling greater accuracy and less invasive procedures. However, the system lacks advanced features and autonomy necessary for it to function as a true partner. To enhance its usability, we introduce the implementation of a ChatGPT-based natural language robot interface. Overall, our integration of a ChatGPT-enabled daVinci Surgical Robot has potential to expand the utility of the surgical platform by supplying a more accessible interface. Our system can listen to the operator speak and, through the ChatGPT-enabled interface, translate the sentence and context to execute specific commands to alter the robot’s behavior or to activate certain features. For instance, the surgeon could say (even in Spanish) “please track my left tool” and the system will translate the sentence into a specific track command. This specific error-checked command will then be sent to the hardware which will respond by controlling the camera of the system to continuously adjust to center the left tool in the field of view. We have implemented many commands including “Find my tools” (tools that are not in the field of view) or start/stop recording that can be triggered based on a natural conversational context. Here, we present details of our prototype system, give some accuracy results, and explore its potential implications and limitations. We also discuss how artificial intelligence tools (such as ChatGPT) of the future could be leveraged by robotic surgeons to reduce errors and enhance the efficiency and safety of surgical procedures and even ask for help.

In the present study. At first, some properties of r-fuzzy soft β-closed sets are introduced on fuzzy soft topological spaces based on the paper Aygunoglu et al. (Hacet. J. Math. Stat. 2014, 43, 193-208). Also, we define the closure and interior operators with respect to the classes of r-fuzzy soft β-closed and r-fuzzy soft β-open sets, and investigate some of their properties. In addition, the concept of r-fuzzy soft β-connected sets is introduced and characterized with help of fuzzy soft β-closure operators. Thereafter, some properties of a fuzzy soft β-continuity are studied. Furthermore, we introduce and study the concepts of fuzzy soft almost (weakly) β-continuous functions, which are weaker forms of a fuzzy soft β-continuity. Also, the relationships between these classes of functions are specified with the help of some illustrative examples. Finally, we explore new types of fuzzy soft functions called, fuzzy soft β-irresolute (strongly β-irresolute, β-irresolute open, β-irresolute closed and β-irresolute homeomorphism) functions, and discuss some properties of them. Also, we show that fuzzy soft strongly β-irresolute → fuzzy soft β-irresolute → fuzzy soft β-continuity, but the converse may not be true.

Knowledge graphs (KGs) play a crucial role in many applications, such as question answering, but incompleteness is an urgent issue for their broad application. Much research in knowledge graph completion (KGC) has been performed to resolve this issue. The methods of KGC can be classified into two major categories: rule-based reasoning and embedding-based reasoning. The former has high accuracy and good interpretability, but a major challenge is to obtain effective rules on large-scale KGs. The latter has good efficiency and scalability, but it relies heavily on data richness and cannot fully use domain knowledge in the form of logical rules. We propose a novel method that injects rules and learns representations iteratively to take full advantage of rules and embeddings. Specifically, we model the conclusions of rule groundings as 0-1 variables and use a rule confidence regularizer to remove the uncertainty of the conclusions. The proposed approach has the following advantages: 1) It combines the benefits of both rules and knowledge graph embeddings (KGEs) and achieves a good balance between efficiency and scalability. 2) It uses an iterative method to continuously improve KGEs and remove incorrect rule conclusions. Evaluations on two public datasets show that our method outperforms the current state-of-the-art methods, improving performance by 2.7% and 4.3% in mean reciprocal rank (MRR).

Confinement can induce substantial changes in the physical properties of macromolecules in suspension. Soft confinement is a particular class of restriction where the boundaries that constraint the particles in a region of the space are not well-defined. This scenario leads to a broader structural and dynamical behavior than the observed in systems enclosed between rigid walls. In this contribution, we study the ordering and diffusive properties of a two-dimensional colloidal model system subjected to a one-dimensional parabolic trap. Increasing the trap strength makes it possible to go through weak to strong confinement, allowing a dimensional transition from two- to one-dimension. The non-monotonic response of the static and dynamical properties to the gradual dimensionality change affects the system phase behavior. We find that the particle dynamics is connected with the structural transitions induced by the parabolic trap. In particular, at low and intermediate confinement regimes, complex structural and dynamical scenarios arise, where the softness of the external potential induces melting and freezing, resulting in faster and slower particle diffusion, respectively. Besides, at strong confinements, colloids move basically along one direction, and the whole system behaves structurally and dynamically similar to a one-dimensional colloidal system.

The reliability analysis allows to estimate the system's probability of detecting and identifying outlier. Failure to identify an outlier can jeopardise the reliability level of a system. Due to its importance, outliers must be appropriately treated to ensure the normal operation of a system. The system models are usually developed from certain constraints. Constraints play a central role in model precision and validity. In this work, we present a detailed optical investigation of the effects of the hard and soft constraints on the reliability of a measurement system model. Hard constraints represent a case in which there exist known functional relations between the unknown model parameters, whereas the soft constraints are employed for the case where such functional relations can slightly be violated depending on their uncertainty. The results highlighted that the success rate of identifying an outlier for the case of hard constraints is larger than soft constraints. This suggested that hard constraints should be used in the stage of pre-processing data for the purpose of identifying and removing possible outlying measurements. After identifying and removing possible outliers, one should set up the soft constraints to propagate the uncertainties of the constraints during the data processing. This recommendation is valid for outlier detection and identification purpose.

In this paper, we present the design, manufacturing and characterization of a soft textile-based clutch (TBC) that switches between locking and unlocking of its linear displacement by exploiting vacuum stimulation. The applied vacuum locks the relative sliding motion between two elaborated textile webbings covered by an elastic silicone rubber bag. Based on different fabrication techniques, such as silicone casting on textile, melt embossing for direct fabrication of miniature patterns on textile and sewing, we developed three groups of TBC samples based on friction and interlocking principles and we compared their performance in blocking configuration. The clutch with interlocking mechanism presented the highest withstanding force (150 N) respect to the one (54 N) recorded for the friction-based clutch. The simple and compact structure of the proposed clutch, together with the intrinsic adaptability of fabric with other clothing and soft materials, make it a proper solution for applications in soft wearable robotics and generally as locking and variable stiffness solution for soft robotic applications.

The human-centric approach is a leading trend for future production processes, and collaborative roboticists are key to its realization. This article addresses the challenge of designing a new cus-tom-made non-conventional machine or robot involving toolpath control (interpolated axes) with collaborative functionalities but by using “general-purpose standard" safety and motion control technologies. This is done on a non-conventional Cable-Driven Parallel Robot (CDPR). Safety is assured by safe commands to individual axes, known as Safe Motion Monitoring Functionalities, which limits the axes speed in the event of human intrusion. At the same time, the robot's Motion Controller applies an override to the toolpath speed to accommodate the robot's path speed to the axis’s limitations. The implementation of a new Pre-Warning Zone, prevent unnecessary stops due to the approach of the human operator. The article also details a real experiment that validates the effectiveness of the proposed strategy.

Recently, new semantic segmentation and object detection methods have been proposed for direct processing of three-dimensional (3D) LiDAR sensor point clouds. LiDAR can produce highly accurate and detailed 3D maps of natural and man-made environments and is used for sensing in many contexts due to its ability to capture more information and its robustness to dynamic changes in the environment. In addition, the cost of LiDAR sensors has decreased in recent years, which is an important factor for many application scenarios. The challenge with 3D LiDAR sensors like the Velodyne HDL-64E S2 is that they can output large 3D data at up to 1,300,000 points per second, which is difficult to process in real time when applying complex algorithms and models for efficient semantic segmentation. Most existing approaches are either only suitable for relatively small point clouds or rely on computationally intensive sampling techniques to reduce their size. As a result, most of these methods do not work in real-time in realistic field robotics application scenarios, making them unsuitable for practical applications. Systematic point selection is a possible solution to reduce the amount of data to be processed, but although it is memory and computationally efficient, it selects only a small subset of points, which may result in important features being missed. To address this problem, we propose a new approach to semantic segmentation in forestry that uses a systematic sampling method in which the local neighbors of each point are retained to preserve geometric details. Our approach has been shown to process up to 1 million points in a single pass. It outperforms the state of the art in efficient semantic segmentation in large datasets such as Semantic3D. We also present a preliminary study on the performance of LiDAR-only data, i.e., intensity values from LiDAR sensors without RGB values for semi-autonomous robot perception.

Biomimetic stimuli-responsive materials can respond to various external stimuli in the form of structural or morphological transformations by actively or passively converting input energy into mechanical energy. They are the core element of soft actuators for typical smart devices like soft robots, artificial muscles, intelligent sensors and nanogenerators. While significant progresses have been made in bioinspired stimuli-responsive materials, they have not yet achieved the remarkable properties in biological systems. In this review, we will discuss recent advances in biomimetic stimuli-responsive materials that are instrumental for soft actuators. Different stimuli-responsive principles for soft actuators are firstly discussed, including fluidic, electrical, thermal, magnetic, light and chemical stimuli. We further summarize the state-of-the-art stimuli-responsive materials for soft actuators and explore the advantages and disadvantages of using electroactive polymers, magnetic soft composites, hydrogels, liquid crystal elastomers, shape memory alloys and chemical-responsive materials. Finally, we provide a critical outlook on the field of stimuli-responsive soft actuators, and emphasize the challenges in the process of their implementation to various industries.

Plasmonics is the study of resonant oscillations of free electrons in metals caused by incident electromagnetic radiation. Surface plasmons can focus and steer light on the subwavelength scale. Apart from metals, plasmonic phenomena can be observed in soft matter systems such as electrolytes where resonant charge oscillations can be induced for ions in solution. Due to their larger mass, they are plasmon-active in a lower frequency regime and on a larger wavelength scale. Spatial confinement allows increasingly strong charge interactions and gives rise to nonlocality or spatial dispersion effects. These effects manifest as additional longitudinal propagation modes and are known to cause plasmonic broadening and resonance shifts in metal nanostructures. We derive and discuss the nonlocal optical response of ionic plasmons using a hydrodynamic, two-fluid model in a planar homogeneous three-layer system with electrolyte-dielectric interfaces. Studying such systems enables us to identify and understand plasmonic phenomena in biological and chemical systems.

Nowadays, the development or improvement of actuation mechanisms is a crucial topic for the achievement of dextrous manipulation using soft robots. Then, a primary target of research is the design of actuation and driving devices. Consequently, in this paper, we introduce a soft driving epicyclical mechanism that mimics human muscle behavior and fulfills motion requirements to achieve grasping gestures using a robotic finger. The prototype is experimentally assessed, and results show that our approach has enough performance for the implementation in grasping tasks. Furthermore, we introduce the basis for a new soft epicyclical mechanism merger with shape memory alloys to allow active stiffness control of the mechanism.

In order to improve contrast and restore color for underwater image captured by camera sensors without suffering from insufficient details and color cast, a fusion algorithm for image enhancement in different color spaces based on contrast limited adaptive histogram equalization (CLAHE) is proposed in this article. The original color image is first converted from RGB color space to two different special color spaces: YIQ and HSI. The color space conversion from RGB to YIQ is a linear transformation, while the RGB to HSI conversion is nonlinear. Then, the algorithm separately operates CLAHE in YIQ and HSI color spaces to obtain two different enhancement images. The luminance component (Y) in the YIQ color space and the intensity component (I) in the HSI color space are enhanced with CLAHE algorithm. The CLAHE has two key parameters: Block Size and Clip Limit, which mainly control the quality of CLAHE enhancement image. After that, the YIQ and HSI enhancement images are respectively converted backward to RGB color. When the three components of red, green, and blue are not coherent in the YIQ-RGB or HSI-RGB images, the three components will have to be harmonized with the CLAHE algorithm in RGB space. Finally, with 4 direction Sobel edge detector in the bounded general logarithm ratio operation, a self-adaptive weight selection nonlinear image enhancement is carried out to fuse YIQ-RGB and HSI-RGB images together to achieve the final fused image. The enhancement fusion algorithm has two key factors: average of Sobel edge detector and fusion coefficient, and these two factors determine the effects of enhancement fusion algorithm. A series of evaluate metrics such as mean, contrast, entropy, colorfulness metric (CM), mean square error (MSE) and peak signal to noise ratio (PSNR) are used to assess the proposed enhancement algorithm. The experiments results showed that the proposed algorithm provides more detail enhancement and higher values of colorfulness restoration as compared to other existing image enhancement algorithms. The proposed algorithm can suppress effectively noise interference, improve the image quality for underwater image availably.

Entropion is a condition characterized by the total or partial inversion of the eyelid margin, resulting in contact between the outer skin and the corneal or conjunctival surface, and sometimes both. This condition can affect various animals, including horses, pigs, goats, sheep, rabbits, felines, and particularly canines. It typically manifests in the lower lid's lateral portion but can affect any part of the lid. This contact between eyelashes or facial hair and the cornea or conjunctiva leads to severe irritation, causing self-inflicted trauma, as evidenced by clinical signs of pain, irritation, ulcerations, and vision loss. Entropion can be classified as primary (congenital or developmental) or secondary (spastic and scarring). Diagnosis relies on clinical signs, the animal's history, and its breed. It's essential to assess the degree of entropion in the dog without applying topical anesthesia. This study conducts a literature review on surgical techniques for correcting various types of entropion in canines.

Gastroesophageal (GE) junction adenocarcinoma is an aggressive malignancy of growing incidence and is associated with public health issues such as obesity and GERD. Management has evolved over the last 2 decades to incorporate a multidisciplinary approach including endoscopic intervention, and neoadjuvant chemotherapy/ chemoradiation and minimally invasive or more limited surgical approaches. Surgical approaches include esophagectomy, total gastrectomy, and more recently proximal gastrectomy. This review analyzes the evidence for and applicability of these varied approaches in management as well areas of continued controversy and investigation.

Abstract: The widespread and popular use of TADs for orthodontic anchoring has become a daily routine in clinical orthodontic treatment. However, as there have been many accidents over the past decade, safety action is needed to help reduce these accidents. We have advocated using the surgical guide and developed a procedure that can benefit patients and orthodontists. The first part of this paper is about the rationale for making the surgical guide for various implant placements that were observed. Due to their anatomical structure, some placements may require particular attention, which is focused on and discussed in length. The second part deals with fabricating the surgical guide in the laboratory procedure. The data from the intraoral SLT acquisition was extracted, and with the DICOM data from CBCT and in a 3-Shapes software, the guidance was designed. The detailed and step-by-step laboratory procedure, CAD/CAM, and 3D printers to make the surgical guide for TADs are explained. The procedure is performed in an easy-to-understand manner to make using the surgical guide possible for the daily practice of orthodontics (Pubmed).

Abstract We aim to describe the diagnosis and surgical management of urinary tract endometriosis (UTE). We detail current diagnostic tools including advanced transvaginal ultrasound, magnetic resonance imaging, and surgical diagnostic tools such as cystourethroscopy. While discussing surgical treatment options, we emphasize the importance of an interdisciplinary team, for complex cases that involve the urinary tract. While bladder DE is more straightforward in its surgical treatment, ureteral DE requires a high level of surgical skill. Specialists should be aware of the important entity of UTE due to the serious health implications for women. When UTE exists, it is important to work within a interdisciplinary radiological and surgical team.

INTRODUCTION Recently there has been a significant increase in age in the United States. It is necessary to better understand the physiological and surgical needs of these patients in order to optimize outcomes. The vast majority of procedures performed in adult patients are low-risk operations, such as laparoscopic cholecystectomy. Our aim is to investigate the outcomes, including length of stay, morbidity, mortality, re-admission and discharge disposition of the elderly population (>80) undergoing low-risk operations in our tertiary community hospital. METHODS A retrospective chart review was done at a tertiary community hospital. The time frame utilized was 2011-2015. Patients were excluded only on the basis of their age (< 80) at the time of operation. RESULTS There were a total of 30 patients who underwent laparoscopic cholecystectomy from 2011 to 2015. 21 patients (70%) were female and 9 (30%) were male. No patients were converted to an open procedure. The average age was 86.4 years and average ASA classification prior to surgery was 2.88. Higher ASA class, specifically those that were class III/IV were more likely to have an increased length of stay that was statistically significant. Overall age greater than 80 was an independent risk factor for transfer to a higher level of care upon discharge (SNF, LTAC, etc.), a surrogate marker for physical decompensation following surgery. CONCLUSIONS Routine surgery, such as the laparoscopic cholecystectomy, effects the elderly population in a more substantial way, and early recognition coupled with increased education for physicians regarding geriatric patients can help to reduce length of stay, morbidity, and overall physical and mental deconditioning.

Soft set theory is a mathematical tool for dealing with uncertainty. This paper investigates limits of interval type of soft sets (for short, it-soft sets). The concept of it-soft sets is first introduced. Then, limits of it-soft sets are proposed and their properties are obtained. Next, point-wise continuity of it-soft sets and continuous it-soft sets are discussed. Finally, an application for rough sets is given.

Underwater robotics equipped with visual detection systems have the function of detecting un-derwater artifacts, which is of great significance to deep-sea archaeology. Underwater artifacts are located in complex environments with poor imaging conditions, and the targets have chal-lenging problems such as breakage, stacking, and sediment burial, which causes the marine cul-tural target detection failures. To solve these problems, this paper proposes an underwater cul-tural target detection algorithm based on the deformable deep aggregation network model for underwater robotics exploration. To fully extract the target feature information of underwater targets in complex environments, this paper designs a multi-scale deep aggregation network with deformable convolutional layers. Besides, the BAM attention module is designed for fea-ture optimization, which enhances the potential feature information of the target while weak-ening the background interference information. Finally, the target prediction is achieved through feature fusion at different scales. The proposed algorithm has been extensively validat-ed and analyzed on the collected underwater artifact datasets, and the precision, recall, and mAP of the algorithm have reached 93.1%, 91.4%, and 92.8%, respectively. In addition, the present al-gorithm has been practically deployed on the underwater robotics. In the deep-sea tests, the ar-tifact detection frame rate reaches up to 19 fps, which satisfies the real-time target detection。

(1) Introduction: The COVID-19 pandemic presented unique challenges for patients and healthcare providers, especially for those working with obesity and related health problems. E-health has emerged as a crucial tool for the follow-up of users undergoing bariatric surgery during this period, allowing remote monitoring of users' health status and providing access to virtual consultation with health professionals. This study aims to analyze the impact of the use of telemedicine during the COVID-19 pandemic on the results of bariatric surgery and user satisfac-tion with this follow-up. (2) Method: Observational study with retrospective data collection. The variables were divided into several groups: health data, associated comorbidities, quality of life, quality of sleep and satisfaction with telemedicine monitoring. (3) Results: Surgery significantly affected weight loss, in general more than 75% loss of excess weight. Comorbidities, like the qual-ity of life, were reversed over time, with 50% of subjects maintaining excellent levels. Although most users were satisfied with the monitoring, the variables had no relationship. (4) Conclusions: The follow-up assured by telemedicine did not alter the results of bariatric surgery, which may allow us to infer that it may be an option to consider for regular monitoring of the post-bariatric surgery process.