Miracle-dz/UniFAR-FTUs huggingface dataset:
Emerging technologies for engineering of extracellular vesicles

Extracellular vesicles (EVs) are lipid-bilayer membrane-enclosed vesicles that are secreted by all cell types. Natural EVs contain biological information such as proteins, nucleic acids, and lipids from their parent cells. Therefore, EVs have been extensively studied as diagnostic biomarkers and therapeutic tools under normal and pathological conditions. However, some drawbacks, including low yield, poor therapeutic effects, lack of imaging, and targeting capacity of natural EVs, still need to be improved. Emerging engineering technologies have rendered EVs new properties or functionalities that broadened their applications in the biomedical field. Herein, in this review, we gave a brief overview of advanced strategies for EV engineering. We focused on pre-treatment of parent cells to regulate their released EVs. Meanwhile, we summarized and discussed the direct modification of EVs to achieve drug loading, imaging, and targeting functionalities for downstream applications.
A method of point cloud data block registration with considering distance from point to surface

The number of scanner stations used to acquire point cloud data is limited, resulting in poor data registration. As a result, a cloud point block registration approach was proposed that took into account the distance between the point and the surface. When registering point cloud data, the invariant angle, length, and area of the two groups of point cloud data were afﬁne transformed, and then the block registration parameters of point cloud data were determined. A ﬁnite hybrid model of point cloud data was created based on the coplane four-point nonuniqueness during the afﬁne translation. On this basis, the point cloud data block registration algorithm was designed. Experimental results prove that the proposed method has great advantages in texture alignment, registration accuracy and registration time, so it is able to effectively improve the registration effect of point cloud data. The point cloud data block registration algorithm was built on this foundation. Experiments show that the suggested method has signiﬁcant improvements in texture alignment, registration accuracy, and registration time, indicating that it can signiﬁcantly improve point cloud data registration.
Impact of Space Environment on Human Body From an Otorhinolaryngologist Perspective: A Brief Review and Future Initiatives for Development of Healthcare, Education and Research Facility in India

Background: Microgravity in space causes changes in the physiology of human body and as a result makes them susceptible to various pathology. As a result astronauts suffer from health disorders which includes otorhinolaryngological disorders Aim: To gather information about the various otorhinolaryngological manifestations occuring in microgravity by compiling the available scattered data existing in literature Methods: This is a narrative review article. Using keywords a search was made on the internet, various databases such as googlescholar, pubmed to find out the description of various otorhinolaryngological manifestation in microgravity environment of space. A few proposals or initiatives are given at the end of the discussion so that more research can be conducted on this aspect of otorhinolaryngology Results: Studies have revealed that the microgravity environment leads to mastoid effusion, predisposes tosinusitis, causes cytoskeletal changes and altered gene expression in thyroid cancer cells, decreases salivary secretion,causes difficulty in airway management, affects temporomandibular joint function, causes impairment of balance. Regarding sleep some studies revealed that microgravity improves sleep whileother studies revealed that microgravity causes increase in sleep disturbances. Important future initiatives include establishment of world class health and research facility, National Health Programme forastronauts, Fellowship courses by NBEMS etc. Conclusion: Microgravity has a significant impact on mastoid, sinuses, sleep, thyroid cancer cells, salivation, airway, temporomandibular joint and balance. More research needs to be conducted on this topic
Association of Food Consumption According to the Degree of Processing and Sociodemographic Conditions in Older Adults

Several factors can impact food consumption in older adults, including those of sociodemographic, physiological, and chronic non-communicable diseases. This study aimed to evaluate the association of food consumption according to its degree of processing with sociodemographic conditions in community-dwelling older adults. Food intake was evaluated from 24-h recall data. All food items were classified according to the degree of processing into four groups as follows: in natura or minimally processed, culinary ingredients, processed, and ultra-processed foods. Food groups were considered dependent variables in a quantile regression model, adjusting for sex, age, schooling, ethnicity, and number of residents. Women and individuals with higher levels of education had lower consumption of in natura or minimally processed foods and higher consumption of ultra-processed foods. The yellow or indigenous ethnicity presented the lowest consumption of processed foods; older people who lived with three or more individuals had the highest consumption of culinary ingredients, whereas the older people who lived with one to two people had the highest consumption of processed foods and the lowest consumption of ultra-processed. These groups may be the target of educational and public policies to improve diet quality and contribute to quality of life in older ages.
Exploring the Multifaceted Applications of Ultrasound Imaging in Medical Diagnostics

Ultrasound imaging, commonly known as sonography, has become an indispensable tool in the arsenal of modern medicine for the diagnosis and monitoring of diseases. This article delves into the extensive applications of ultrasound technology across various medical specialties. We highlight the evolution of sonography from its rudimentary beginnings to the sophisticated, multi-dimensional imaging modality it is today. Special emphasis is laid on the principles of ultrasound imaging, the diverse techniques employed, and the advancements that have been made in this field. We explore its pivotal role in obstetrics and gynecology, cardiology, emergency medicine, musculoskeletal conditions, abdominal pathologies, and pediatric care. Each section provides insight into how ultrasound has enhanced the accuracy and efficiency of disease diagnostics, emphasizing case studies and real-world applications. The article further investigates emerging innovations, such as the integration of artificial intelligence and the development of contrast-enhanced methodologies, that promise to expand the potential of ultrasound imaging even further. By offering a panoramic view of the multifaceted uses of ultrasound in medical diagnostics, we underscore its value in improving patient care and forecast its future in the medical diagnostic landscape.
Quantitative Colorimetric Sensing of Carbidopa in Anti-Parkinson Drugs Based on Selective Reaction with Indole-3-Carbaldehyde

The quality of life of patients affected by Parkinson’s disease is improved by medications containing levodopa and carbidopa, restoring the dopamine concentration in the brain. Accordingly, the affordable quality control of such pharmaceuticals is very important. Here is reported the simple and inexpensive colorimetric quantification of carbidopa in anti-Parkinson drugs by the selective condensation reaction between the hydrazine group from carbidopa and the formyl functional group of selected aldehydes in acidified hydroalcoholic solution. An optical assay was developed by using indole-3-carbaldehyde (I3A) giving a yellow aldazine in EtOH:H2O 1:1 (λmax~415 nm) at 70 °C for 4 h, as confirmed by LC-MS analysis. A filter-based plate reader was used for colorimetric data acquisition, providing superior results in terms of analytical performances for I3A, with a sensitivity ~50 L g−1 and LOD ~0.1 mg L−1 in comparison to a previous study based on vanillin, giving, for the same figures of merit values, about 13 L g−1 and 0.2–0.3 mg L−1, respectively. The calibration curves for the standard solution and drugs were almost superimposable, therefore excluding interference from the excipients and additives, with very good reproducibility (avRSD% 2–4%) within the linear dynamic range (10 mg L−1–50 mg L−1).
Innovative Approaches to Water Allocation: The Potential for Water Markets

Exchange through markets is one way of allocating water. In many settings this method possesses a number of desirable attributes to a greater degree than alternative allocative mechanisms: flexibility, security, predictability, fairness …. Markets have shortcomings, too, especially related to quantity and quality return flow effects, but these can be mitigated through changes in the administrative framework of the water rights system. It is shown that an economically efficient water allocation system must integrate quantity and quality management and would be neither a priority nor a proportional rights system. However, the nature of the water rights system may not be very important if short-term rental markets are operative. The potential for intrastate and interstate water markets is discussed.
PePUT: A Unity Toolkit for the Social Robot Pepper

This paper introduces the Pepper Python Unity Toolkit (PePUT), a toolkit for controlling and using the social robot Pepper via Unity and Python. As toolkit components, we present implementations for the speech- and tablet-control, as well as animation and navigation, which can be directly used within Unity. With it, we provide the opportunity of a virtual testbed for the social robot Pepper. In addition, we highlight potential use cases for the components, in particular in a smart environment, as well as the use of PePUT as a research tool. The toolkit with the presented components and the source files are publicly available as open-source project 1 under the MIT license via GitLab for usage, replication, and extension.
SEGMENTASI 3D BERBASIS MODEL FASET MENGGUNAKAN METODE REGION GROWING TERMODIFIKASI

Segmentasi adalah pembagian area sebuah gambar menjadi beberapa bagian berdasarkan kemiripan fitur, seperti warna, tekstur, intensitas piksel, dan lain sebagainya. Pada penelitian ini Segmentasi diimplementasikan pada sebuah model faset 3D menggunakan Metode Region Growing yang diadopsi dari penerapan metode pada gambar 2D. Segmentasi dilakukan berdasarkan kemiripan fitur yang terkandung dalam model faset 3D tersebut. Fitur 3D diidentifikasi dan diekstrak menggunakan beberapa metode, yaitu Angle Deficit / Guass-Bonnet Scheme dan Spherical Image. Ekstraksi Fitur dilakukan pada setiap verteks dari model faset. Verteks yang menyusun model faset 3D menjadi basis implementasi metode segmentasi menggantikan piksel pada gambar 2D. Hasil penelitian menunjukkan segmentasi Region Growing pada model faset memiliki tingkat akurasi cukup tinggi, merentang antara 70% hingga 100%, bergantung dari kehalusan (smoothness) dan kompleksitas model faset 3D.
Mental health survey of medical personnel during pre-job training in a closed-loop management system during the COVID-19 pandemic

Object With the aim of enhancing prevention and regional control of epidemics, the mental health status of medical personnel was analyzed before the implementation of closed-loop management during the COVID-19 pandemic in the regional hospital representative. Methods In accordance with directives from the unified deployment of the national and regional health bureaus, and following the inclusion and exclusion criteria, from September 2021 to November 2022, all medical personnel assigned to a closed-loop working environment by Guangzhou Panyu Central Hospital were enrolled as research subjects through cluster sampling method. Using a cross-sectional survey method, relevant data such as age, gender, professional title, and mental health status were collected. The Patient Health Questionnaire-9 (PHQ-9) scale, the Generalized Anxiety Disorder-7 (GAD-7) scale, and the Insomnia Severity Index (ISI) scale were administered. Logistic regression analysis was used to study the influencing factors of depression, anxiety, and insomnia. Single factor logistic regression analysis was performed first, followed by multiple factor logistic regression analysis. Results A total of 500 valid responses were received. Depression was reported by a higher proportion of physicians than nurses. Anxiety was reported by higher proportion of men than women and by a higher proportion of physicians than nurses. Medical personnel under the age of 30 years reported fewer symptoms of insomnia than those over the age of 41 years, and medical personnel with intermediate professional titles reported more severe symptoms of insomnia than junior personnel. There was no significant difference between the results of the three questionnaires for medical personnel from other hospital departments or in the different type of closed-loop work environments. Conclusion During the pandemic, conducting psychological health assessments for medical personnel undergoing pre-job training in closed-loop management was beneficial for the timely detection of psychological problems. Although this study only conducted a cluster sampling survey and lacked comparative analysis on other medical institutions, it still suggested that it was necessary to strengthen timely psychological counseling and intervention for senior male physicians.
Bluetooth 5.0 Suitability Assessment for Emergency Response within Fire Environments

Natural disasters, such as wildfires, can cause widespread devastation. Future-proofing infrastructure, such as buildings and bridges, through technological advancements is crucial to minimize their impact. Fires in disasters often stem from damaged fuel lines and electrical equipment, such as the 2018 California wildfire caused by a power line fault. To enhance safety, IoT applications can continuously monitor the health of emergency personnel. Using Bluetooth 5.0 and wearables in mesh networks, these apps can alert others about an individual’s location during emergencies. However, fire can disrupt wireless networks. This study assesses Bluetooth 5.0’s performance in transmitting signals in fire conditions. It examined received signal strength indicator (RSSI) values in a front open-fire chamber using both Peer-to-Peer (P2P) and mesh networks. The experiment considered three transmission heights of 0.61, 1.22, and 1.83 m and two distances of 11.13 m and 1.52 m. The study demonstrated successful signal transmission with a maximum loss of only 2 dB when transmitting through the fire. This research underscores the potential for reliable communication in fire-prone environments, improving safety during natural disasters.
A Comprehensive Review of Postoperative Analgesics Used in Orthopedic Practice

Orthopedic surgeries, ranging from joint replacements to fracture fixations, are integral procedures that enhance the quality of life for countless individuals. Effective postoperative pain management is crucial in ensuring optimal patient recovery and satisfaction. This comprehensive review analyzes the diverse array of analgesic modalities employed in orthopedic practice for postoperative pain relief. The review systematically explores the pharmacological landscape of analgesics commonly used in orthopedic settings, including opioids, non-steroidal anti-inflammatory drugs, acetaminophen, and adjuvant medications. Emphasis is placed on their mechanisms of action, efficacy profiles, and potential adverse effects. Special attention is given to the evolving role of multimodal analgesia, which combines various agents to achieve synergistic pain control while minimizing individual drug-related complications. Furthermore, the review addresses the emerging trends and advancements in postoperative analgesia within orthopedics, such as integrating regional anesthesia techniques, peripheral nerve blocks, and novel pharmacological agents. A critical evaluation of evidence-based practices and recent clinical trials is incorporated to guide practitioners in making informed decisions regarding postoperative pain management. Consideration is also given to the individualized nature of pain experiences and the importance of patient-centric approaches. The review underscores the significance of tailoring analgesic regimens based on patient characteristics, surgical procedures, and potential complications, fostering a personalized and effective pain management strategy. In conclusion, this comprehensive review is valuable for orthopedic practitioners, anesthetists, and healthcare professionals involved in postoperative care. By synthesizing current knowledge and highlighting evolving trends, the review contributes to the ongoing dialogue on optimizing pain management strategies in orthopedic practice, ultimately improving patient outcomes and satisfaction.
Putting Robots in Context: Challenging the Influence of Voice and Empathic Behaviour on Trust

Trust is essential for social interactions, including those between humans and social artificial agents, such as robots. Several robot-related factors can contribute to the formation of trust. However, previous work has often treated trust as an absolute concept, whereas it is highly context-dependent, and it is possible that some robot-related features will influence trust in some contexts, but not in others. In this paper, we present the results of two video-based online studies aimed at investigating the role of robot voice and empathic behaviour on trust formation in a general context as well as in a task-specific context. We found that voice influences trust in the specific context, with no effect of voice or empathic behaviour in the general context. Thus, context mediated whether robot-related features play a role in people’s trust formation towards robots.
Identifying Requirements for the Implementation of Robot-Assisted Physical Therapy in Humanoids: A user-centered design approach

Bimanual humanoid assistive robots can be a valuable tool to improve access to physical therapy and multi-dimensional physical status monitoring for older adults living at home. However, at present, there is no implementation of end-effector robot-assisted rehabilitation in assistive social robots. Therefore, this paper illustrates the first steps of a user-centered design approach to develop such a robot for upper limb treatments and rehabilitation. Based on observation of geriatric rehabilitation and expert interviews with physical therapists, an online survey was conducted with 87 physical therapists. The first part of the questionnaire aimed to better understand the context of use, current practices, and goals of geriatric rehabilitation. Our findings suggest that integrating exercises that combine physical and cognitive skills and aim to improve specific activities of daily living (ADLs) are critical. Secondly, a KANO analysis was conducted to prioritize 20 potential features for the robot. Among these features, assist-as-needed (AAN) control for physical exercises, voice control for general settings, and the capability to perform treatments while the patient is seated or lying down were identified as essential or “must-have” features. Third, the possibility of an autonomously conducted weekly assessment of patients’ active range of motion (ROM) and weekly to monthly muscle function testing could allow the best possible monitoring of their functional status. Generally, applying a user-centered design approach allows an interdisciplinary team tasked with developing assistive robots to establish a common objective, based on which an initial prototype can be designed in the next step.
Anomaly detection of semiconductor processing equipment using equipment behaviour

As semiconductor design rules evolve, the required level of reliability for semiconductor processing equipment is increasing. It is impossible to detect anomalies simply by checking a single factor, the oxygen concentration, which is the most important indicator of the equipment performance. We extracted 16 features from the behaviour of oxygen concentration and pressure in the load area, and built univariate and multivariate models by using logistic regression with these features. The proposed method was able to detect anomalous equipment that could not be detected by monitoring only the oxygen concentration, and greatly shortened the processing lead time including adjustment.
Development of Bioactive Scaffolds for Orthopedic Applications by Designing Additively Manufactured Titanium Porous Structures: A Critical Review

We overview recent findings achieved in the field of model-driven development of additively manufactured porous materials for the development of a new generation of bioactive implants for orthopedic applications. Porous structures produced from biocompatible titanium alloys using selective laser melting can present a promising material to design scaffolds with regulated mechanical properties and with the capacity to be loaded with pharmaceutical products. Adjusting pore geometry, one could control elastic modulus and strength/fatigue properties of the engineered structures to be compatible with bone tissues, thus preventing the stress shield effect when replacing a diseased bone fragment. Adsorption of medicals by internal spaces would make it possible to emit the antibiotic and anti-tumor agents into surrounding tissues. The developed internal porosity and surface roughness can provide the desired vascularization and osteointegration. We critically analyze the recent advances in the field featuring model design approaches, virtual testing of the designed structures, capabilities of additive printing of porous structures, biomedical issues of the engineered scaffolds, and so on. Special attention is paid to highlighting the actual problems in the field and the ways of their solutions.
CONTROL OF STRUCTURE OVER THE DISSEMINATION GOLD DEPOSITS IN NORTHWEST SICHUAN PROVINCE

In the northwestern Sichuan Province,a major distribution area of fine disserminated gold deposits consisting of dozens of gold deposits have been found.The formation and distribution of gold-deposits were controlled by tectonic setting in the area. The gold deposits controlled by ore-forming structure were discussed in this paper.It showed that the concentration of gold occurred in the variation position of attitude of faults,at the intersection position of two sets of faults and at the intersection of structural lens and cataclasite.
A review of recent advance of ship detection in single-channel SAR images

Synthetic aperture radar (SAR) is an active microwave imaging sensor for high-resolution observation, with the ability of working in all-weather and all-day. Recently, SAR images have been widely used in many fields. Among them, ship detection in single-channel SAR images is a significant part of civilian and military fields. This article first discusses the characteristic of SAR images and the detectability of ships, then summarizes the recent advance of traditional and deep learning-based methods used for ship detection in single-channel SAR images. In addition, the characteristics and existing problems of various methods are discussed and their future development trends are predicted. Aiming at the problems of the large amount of calculation, multi-scale and densely docked ship detection in single-channel SAR images, an improved deep learning-based detection algorithm is proposed, which has achieved excellent performance on the SAR ship detection dataset (SSDD).