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Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. Early detection plays a crucial role in improving patient outcomes and reducing mortality rates. In recent years, Raman spectroscopy has emerged as a promising tool for non-invasive cancer detection. This research introduces a new method for identifying colorectal cancer (CRC). It combines Raman spectroscopy, a technique that analyzes the molecular fingerprint of tissues, with a powerful deep learning algorithm called a dilated convolutional network (DCN). By combining these two tools, the researchers aim to improve the accuracy and reliability of diagnosing CRC. Intraoperative diagnostics and pathology need to distinguish tumors from normal tissues. This proposal explores Raman spectroscopy as a new surgical tool for identifying colorectal cancer during surgery. Raman spectroscopy offers a way to directly analyze the makeup of tissue, potentially revealing the presence of cancer. However, surrounding tissue can create background interference, making it difficult to detect the key signal. The authors suggest that high-quality data from Raman spectroscopy combined with advanced deep learning algorithms could be a solution to overcome this challenge. We collect a large Raman spectroscopy dataset from 26 colorectal cancer patients with Raman shifts from 385 to 1545 cm−1. Second, dilated convolutional networks classify colorectal cancer tumour tissues. Following the deep learning model's output, we proceed by visualizing and analyzing the identified fingerprint peaks. Our deep learning algorithm exceeds previous colorectal cancer detection methods with 99.1% accuracy. Colorectal cancer detection using Raman spectra is unique. Our ensemble DCN could classify colorectal tumour and normal tissue Raman spectra. [ABSTRACT FROM AUTHOR]

The Discrete Taylor Transform and Inverse Transform (D-TTIT) in one dimension was introduced in [1] for the first time. Employing simple toy models, the present work extends the ideas in [1] to two- (2D) and three dimensions (3D). Thereby, it is demonstrated that properly sampled (composite) monomials and properly calculated weighted discrete higher-order (mixed) derivative operators are bi-orthogonal in Cartesian Coordinates. Despite the fact that the underlying mathematics in higher dimensions becomes increasingly elaborate, it remains algorithmically tractable, and more importantly, automatable. Interpreted locally, D-TTIT in 2D and 3D has the potential of evolving into a surgical tool in numerical analysis. A comprehensive coverage of D-TTIT will be presented in [2]. Future work will extend the technique by considering functions in curved coordinates. [ABSTRACT FROM AUTHOR]

Surgeons play an important role in saving human lives. Recent studies have shown that surgeons are at higher risk of developing musculoskeletal disorders (MSDs). They work long hours and remain in awkward posture during surgery, resulting in MSDs, which in the long term could impact their quality of life and career. The main intention of this study is to review the existing articles and to identify the factors that lead to MSDs among the surgeons as well as to discuss suggested preventive measures. Twenty original research articles were reviewed, focusing on the factors that lead to MSDs and the symptoms experienced by the surgeons. In this review, it was found that the surgeons experienced posture-related problems owing to prolonged hours spent on performing surgeries. Surgeons experienced the most pain in the shoulders, neck, and at their back. More than 70% of the surgeons' experienced pain in the upper extremity, neck, and back. 30% of the surgeons need to take prescribed medication, have more rest, and attend physiotherapy sessions due to the pain or injury developed from performing surgical procedures. As the total number of hours spent during surgeries increased, the prevalence of MSD symptoms also increased. From this review, most authors stated that ergonomic practices are still minimal among the surgeons during surgery, even though they are aware of the importance of ergonomics in maintaining their well-being. Hence, countermeasures such as adopting a more ergonomic posture during surgery, adopting proper and regular exercise, as well as improving the design of surgical instruments and equipment to improve posture should be employed. [ABSTRACT FROM AUTHOR]

Coronavirus Disease 2019 can be transmitted from droplets or aerosol transmission that causes the vital of applying personal protective equipment (PPE) such as medical masks for medical or paramedic personnel. There are two technologies to make a medical mask, such as an ultrasonic sewing machine and a folding mask device. Through D-DART, The Disaster Management Center of Diponegoro University creates medical masks innovations with raw materials on the market, affordable. The research aims to design and build an ultrasonic sewing machine and a mask-folding device prototype. The invention is an experimental design that applies appropriate technology using inexpensive materials by locals and is easy to apply. The experiment results include the engine body and base, rollers, roller frames, and pneumatic knobs. The mask folding machine, currently, component designs have been carried out, including the frame, Roller for materials, Roller tensioner, Roller roller, Folding Jig, Sealer, Bearing housing, Bracket roller folding, Bracket roller tensioner, Bracket jig folding, and Measuring pads. All design processes can be executed and produce ultrasonic sewing machines and folding mask devices. There has been no research related to the quality of the mask created. A mask-making machine's price is high and hard to come by at the beginning of the pandemic. Appropriate technology in the form of a surgical mask making machine is a solution to meet the needs of masks even though they do not yet have a surgical mask standard. [ABSTRACT FROM AUTHOR]

The problem of transmission of infection through surgical instruments was ongoing in the health sector until the creation of the autoclave; however, the use of a standard autoclave is dependent on the availability of electricity, making it impossible to rely on in developing countries and remote areas. This has prompted researchers to develop the solar autoclave, with different designs emerging, most of which can achieve standard sterilisation. This study presents a design and model of a solar autoclave offering the ability to produce high-temperature wet steam under pressure (6 bars at 160 °C) at test intervals for approximately 22.5 minutes, generated from pure water contained in a steel cylinder. This is achieved by concentrating solar energy on the cylinder by means of a square spot Fresnel lens (31 cm * 31 cm) and an oval reflecting dish with a large diameter of 100 cm and a small diameter of 90 cm. The resulting steam is used as a heating element and is responsible for generating sterilisation steam from the water inside the sterilisation cylinder based on exchanging heat with it through a heat exchanger. The generation of sterilisation steam in the sterilising drum took 7 to 10 minutes, with such steam reaching 2.1 bars and 121 °C, giving a total time required to reach sterilisation conditions of about half an hour; adding 15 minutes for the sterilisation cycle gives a 45 minute duration for the full sterilisation cycle. Thus, assuming use of the machine from 8 am to 5 pm, at least nine sterilisation cycles per day can be undertaken. [ABSTRACT FROM AUTHOR]

The basic frequency, formants, pitch, and strength of an individual's voice are compared to a disguised voice using various masks in this study. The greatest obstacle arises when scenarios involving disguised speech samples are encountered for assessment and recognition. Such audio samples of anonymous callers are widespread in crimes such as abduction, blackmail, fake extortion, and many others, where the speaker makes a conscious effort to mask their identity due to fear of being discovered. Because the use of face masks during pandemics has resulted in voice-altering strategies that may mislead the identification of a person based on voice, the study was conducted on thirty male and female subjects from the Punjab region wearing various types of masks. As a result, the goal of this study is to compare the durability of features present in normal voice with sound from the same subject wearing various types of COVID-19 protective masks. The voices were analyzed using Praat software, and a comparison study was conducted. The results of spectrographic study of mono and stereo sounds of both male and female voices revealed considerable alterations in their overall spectrum. The entire study yielded significant results that may be useful to a forensic scientist studying instances involving voice identification and analysis.. [ABSTRACT FROM AUTHOR]

Retained surgical bodies (RSB) are any foreign bodies left inside the patient after a medical procedure. RSB is often caused by human mistakes or miscommunication between medical staff during the procedure. Infection, medical complications, and even death are possible consequences of RSB, and it is a significant risk for patients, hospitals, and surgical staff. In this paper, we describe the engineering process we have done to explore the design space, define a feasible solution, simulate, verify, and validate a state-of-the-art Cyber-Physical System that can significantly decrease the incidence of RSB and thus increase patients' survivability rate. This system might save patients' suffering and lives and reduce medical staff negligence lawsuits while improving the hospital's reputation. The paper illustrates each step of the process with examples and describes the chosen solution in detail. [ABSTRACT FROM AUTHOR]

Computer Aided Design (CAD) and 3D printing are increasingly bringing innovation to orthopedic surgery by allowing customization of surgical procedures. This study proposes the design and 3D printing of patient-specific surgical cutting guides (PSCG) that can be implemented in orthopedic surgery. Cutting guides are surgical tools that allow surgeons to perform cutting operations more accurately, achieving the desired result with high accuracy. During an osteotomy, for example, the surgeon will be able to better determine the position of the cutting line and its direction. This study aims to propose an advanced method of designing cutting guides for an orthopedic surgery procedure. Proposed tools are obtained by an additive manufacturing process that starts with a 3D model of the patient's bone obtained from CT scan images and ends by designing the patient-specific cutting guide model in a CAD environment. Virtual surgical planning (VSP) allows for increasing the surgeon's awareness for developing an orthopedic surgical strategy and allows for the design of cutting guides designed around the patient's specific anatomy. [ABSTRACT FROM AUTHOR]

Face authentication (FA) schemes are universally adopted. However, current FA systems are mainly camera-based and hence susceptible to face occlusion (e.g., facial masks) and vulnerable to spoofing attacks (e.g., 3D-printed masks). This paper exploits the penetrability, material sensitivity, and fine-grained sensing capability of millimeter wave (mmWave) to build an anti-spoofing FA system, named mmFace. It scans the human face by moving a commodity off-the-shelf (COTS) mmWave radar along a specific trajectory. The mmWave signals bounced off the human face carry the facial biometric features and structure features, which allows mmFace to achieve reliable liveness detection and FA. Due to the penetrability of mmWave, mmFace can still work well even if users wear masks. We explore a distance-resistant facial structure feature to suppress the impact of unstable face-to-device distance. To avoid inconvenient on-site registration, we also propose a novel virtual registration approach based on the core idea of cross-modal transformation from photos to mmWave signals.We implement mmFace with various antenna configurations and prototype two typical modes of mmFace. Extensive experiments show that mmFace can realize accurate FA as well as reliable liveness detection. [ABSTRACT FROM AUTHOR]

Cognitive ergonomics is considered with mental processes, such as perception, memory, reasoning, and motor response, as they affect interactions among humans and other elements of a system. The development of cognitive ergonomics discipline is a result of rapid technological advances, especially in the field where a machine is considered rather as an agent with which the human should cooperate than an assistant to the human operator. The increased complexity of technical means contributes the addition of information, system functionality and decision options resulting in an increased degree of sensory input and cognitive workload required by the workers. An example of working environment with processes that are performed with the use of complex and modern technical resources is operating room in which the surgical procedures are carried out. Particularly, the technologically new surgical equipment is the consequence of implementing alternative, to traditional, surgical procedures called minimally invasive surgery (MIS). Here the traditionally tools for open techniques are being replaced by MIS equipment. Taking this issue as a research background, the objective of this paper is to recognize problem of cognitive overload risk when using new and technologically advanced surgical equipment of MIS treatment. There were two methods implemented in the research. First method was direct observation and/or video registration of using MIS tools. Second method was an evaluation form for recognition of cognitive critical incidents. Based on this form, the in-depth analysis of cognitive overload within selected surgical procedures was performed. As a result, the certain risk factors included in four groups of cognitive overload were revealed. These groups are: (1) visual difficulties of operator; (2) manual difficulties within using MIS equipment; (3) loss of control in use of MIS equipment; (4) conflicts/collisions with other people or other medical equipment. The conclusions contain the description of cognitive ergonomics challenges that give the general framework for creating the cognitive centered design process. [ABSTRACT FROM AUTHOR]

Ecolab has a focused business in surgical drapes for both patients and equipment. The pathway for medical materials development supporting the surgical business at Ecolab is full of opportunities for new applications. A specific focus around new technologies and special material requirements in the areas of sterile barrier, absorbency, low dose radiation, ultrasound and robotics are explored. [ABSTRACT FROM AUTHOR]

Cyberknife (Accuracy Inc., Ca) is a robotic radio-surgery system that includes a compact 6 MV linac delivering up to 800 cGy per minute, and an automate arm to aim at any part of the body from any angle. An essential tool is the guidance system based on x-ray imaging cameras located on supports around the patient. A Cyberknife system has been operational at the Vicenza (Italy) Hospital for years and is mainly employed for treating benign and malignant tumors, and Arterior-Venous Malformations. In radiation therapy, delivery of high doses to targets that move with respiration is challenging because of possible spatial inaccuracies. The purpose of this work was to estimate the accuracy of the prediction algorithm used to compensate for system latency in a real-time respiratory tracking system. We have analyzed respiratory signals of 30 patients who had lung or liver Cyberknife treatments. The “Synchrony” (Accuracy Inc.) motion tracking system we use is based on the correlation between the position of LED markers, detected in real time, and the position of internal markers, sampled through x-ray imaging. The position of the external LED signals, though read in real time, must be predicted to compensate for a few hundred ms time lag in the feedback loop that redirects the beam to the current target position. The respiratory signals were described by employing their frequency power spectrum, as recently proposed by other authors. Prediction errors above 1.5 mm, lasting for periods longer than 5 seconds were observed for irregular breathers. These episodes correlate to the presence of a bimodal distribution in the power spectral density, and of very low frequencies contribution. A more refined approach would include a personalized choice of the prediction algorithm based on the very first minutes of treatment. Patient training aimed at reducing breathing irregularities might also result in improved spatial accuracy. [ABSTRACT FROM AUTHOR]

The article discusses the study on the surface and bulk properties of polypropylene fibers obtained from surgical meshes after manufacturing and implantation using mesh materials.