Search

Understanding the efficacy of digital biomarkers in vision-based human motion analysis is essential, not only for interpreting the computer-aided exam results but also for advancing the next generation of digital health tool solutions. This study extensively analyzes digitized neurological examination (DNE) biomarkers for detecting and documenting exam features of Parkinson's disease (PD) and other neurological disorders (OD). Collected over 113 participants, DNE-113, a multi-test DNE database of finger tapping, finger to finger, forearm roll, stand-up and walk, and facial activation tests, covering a broader range of neurological abnormalities beyond PD is first proposed. Subsequently, DNE-113 is integrated into pyDNE - a convenient open-source toolbox, streamlining the creation and assessment of digital biomarkers. This toolbox empowers us to assess the quality of DNE biomarkers across diverse classification tasks. We showcase the discriminative potency of DNE biomarkers, successfully characterizing abnormal signals in neurological patients. Our findings highlight not only the potential use cases but also the persisting challenges in constructing digital biomarkers for computer-aided movement analysis on PD and OD patients.

This paper presents the NOWJ team’s approach to the COLIEE 2023 Competition, which focuses on advancing legal information processing techniques and applying them to real-world legal scenarios. Our team tackled the four tasks in the competition, which involved legal case retrieval, legal case entailment, statute law retrieval, and legal textual entailment. We employ state-of-the-art machine learning models and innovative approaches, such as BERT, Longformer, BM25-ranking algorithm, and multi-task learning models. Our participation in the COLIEE 2023 has provided useful insights including the importance of the pre-processing and feature engineering, effectiveness of the multi-task models in combining different legal tasks to improve model’s performance. Although our team did not achieve state-of-the-art results, our findings identify areas for further research and improvements in legal information processing.

Higher penetration of renewable energy into the electrical grids using grid-connected converters requires robust control schemes to ensure the stable behavior of these converters during disturbances on the grid side. This paper proposes a robust H∞control scheme reinforced by the D-stability technique using linear matrix inequality (LMI)approach for a three-phase two-level grid-connected converter with LCLfilter. The design performance is validated both by simulations and experimental tests. The results indicate that the H∞control provides better response during disturbances in the grid such as variations in the grid voltage and short-circuit faults when compared to that of the conventional vector control scheme. An experimental validation is carried out by implementing the control scheme on an OPAL-RT-based realtime system to control the power injection of a grid-connected converter hardware setup. The experimental results match the simulation results and show the efficient performance of the proposed control scheme in providing the desired active/reactive power.

Purpose: Circulating tumor cell separation and analysis have played a critical role in cancer diagnosis, prognosis, and treatment. In this work, we aim to design and investigate a novel biochip that integrates dielectrophoresis, microfluidic technology to separate circulating tumor cells from blood cells. To create a dielectrophoresis-induced non-uniform electric field, a facing-electrode design was proposed and utilized, in which a slanted electrode array and a simple rectangular ground electrode are placed parallel on the top and bottom parts of the microfluidic channel, respectively. This design can reduce the particle position dependence in the microchannel and the complexity of the microfabrication process. Methods: The separation process, efficiency, and optimization of the proposed device were numerically investigated using the finite element method. Parametric research was conducted to comprehensively examine the impact of various operating and design factors on the cell movement and trajectories in the microfluidic device. Results: The results indicated the potential of the proposed biochip to ensure cancer cell separation from blood cells with high efficiency, high purity in a label-free, non-invasive, easy integration, and low-cost manner. Under the optimal conditions, the separation efficiency reached 92%, 88%, and 96% for human colon cancer cells (HT-29), red blood cells, and white blood cells, respectively. Conclusions: In this study, a novel DEP-based microfluidic chip was proposed to separate HT-29 tumor cells from blood cells and numerically investigated to verify the performance of the biochip design. Our findings could provide a foundation for further theoretical and practical investigations. The proposed system can separate cancer cells from red blood cells and white blood cells as well as offers numerous advantages, such as compact size, low voltage, high efficiency, non-invasiveness, and label-free nature. The tumor cell enrichment platform has the potential for application in cancer detection, analysis, and assessment.

Sign language recognition (SLR) is the task of recognizing human actions that represent the language, which is not only helpful for deaf–mute people but also a means for human–computer interaction. Although data from wearable sensors have been proven useful for this task, it is still difficult to collect such data for training deep fusion models. In this study, our contributions are twofold: 1) we collect and release a dataset for SLR consisting of both video and sensor data obtained from wearable devices and 2) we propose the first self-learning fusion model for SLR, termed STSLR, that utilizes a portion of annotated data to simulate sensor embedding vectors. By virtue of the simulated sensor features, the video features from video-only data are enhanced to allow the fusion model to recognize the annotated actions more effectively. We empirically demonstrate the superiority of STSLR over competitive benchmarks on our newly released dataset and well-known publicly available ones.

A practical artificial neural network tool is proposed for predicting the ultimate bending moments of reinforced concrete beams strengthened by the techniques of externally bonded fiber-reinforced polymer and near-surface mounted fiber-reinforced polymer. Accordingly, the testing database of 131 specimens was gathered for use in developing the artificial neural network model. In this regard, the breadth and height of the beam section, the compression strength of the concrete, the ratio of material reinforcement, and the elastic modulus of fiber reinforced polymer were regarded as input variables, whereas the ultimate bending moment was regarded as an output variable. The performance of the proposed artificial neural network model was compared to the current design model of the American Concrete Institute guide. The comparative analysis demonstrated that the proposed model made more accurate predictions than the current model. Based on the proposed model, a graphical user interface was created to facilitate the prediction of the ultimate bending moments of reinforced concrete beams with fiber-reinforced polymer strengthening.

Underwater sites affected by unexploded ordnance (UXO) pose significant risks to both human safety and environmental well-being. Sonar imaging is commonly employed to investigate such sites and aid in UXO remediation efforts. However, manually identifying and classifying potential targets in sonar data is challenging and time-consuming. Previous research has explored the use of machine-learning models to recognize and categorize targets; however, many of these approaches lack transparency and fail to consider the underlying physical acoustics. Additionally, acquiring sufficient training data for these models can often be problematic. In this study, we present a novel approach by designing neural networks that explicitly account for the unique physics involved in the problem domain. UXOs examined using low-frequency sound frequently exhibit resonant behavior, where the sound is reradiated after initial geometric scattering, owing to the elastic and compressional properties of the objects. Moreover, such resonant effects are typically absent in clutter objects, making them advantageous in discriminating UXOs from non-UXOs. Consequently, we propose several neural network architectures that leverage these resonant effects, utilizing 3D data obtained from a synthetic aperture sonar (SAS) imaging sonar. Our first proposal incorporates a recurrent neural network to model the physics-based correlation among adjacent time/spatial slices, originating from the resonant phenomena. For our second proposal, we employ intensity imagery of orthogonal projections of the 3D data cube, which capture shape-specific resonant scattering mechanisms unique to specific types of UXOs. To evaluate the effectiveness of our methods, we compare them against recent state-of-the-art (SOTA) algorithms using a real-world 3D SAS dataset. Remarkably, even when confronted with limited training data, our approaches consistently demonstrate superior results. Our findings highlight the significant potential of incorporating physical acoustics into neural network designs for UXO detection and classification, offering improved accuracy and efficiency in underwater remediation operations.

Purpose: Focused ultrasound with the presence of microbubbles has been shown to temporarily open the blood-brain barrier (BBB), which offers the potential to improve central nervous system disease treatment. Since BBB opening also highly correlates with the microbubble-induced stable cavitation, in this study, we aim to realize and implement the construction of cavitation-related passive mapping under the structure of a dual-mode phased array structure for the guidance of the focused ultrasound BBB-opening treatment. Methods: A sparse distributed (48 out of a total of 256) receiving configuration was implemented to be functioned as dual-mode transmitting and receiving in the structure. The centered transmission locates at 400 kHz, whereas its 0.5x subharmonics (200 kHz), fundamental (400 kHz), 1.5x ultraharmonic (600 kHz), and 2nd harmonics (800 kHz) have been received and characterized. We demonstrated the capability of correlating the signal intensity with a wide range of microbubble concentrations in the in-vitro setup. In in-vivo verifications, a total of 9 animal experiments have been conducted to implement the passive cavitation mapping to correlate the imaging intensity with the occurrence of the outcome to induce blood-brain barrier opening. Results: Ultraharmonics provided superior sensitivity and detectability to microbubble-related cavitation activity than the other selected frequency band, suggesting the potential in predicting BBB opening outcomes based on the passive image. Conclusion: Cavitation mapping implemented by dual-mode ultrasound phased array is feasible and can provide assure the treatment quality in opening the blood-brain barrier in the brain.

A Ni3Sn4is designed to accommodate high capacity and mechanical stability as a promising anode materials for fast charging. Intrinsic electrochemical activity of Ni in Ni3Sn4is vailed using electronic structure analysis in DFT frameworks

Measurements of low‐frequency physiological signals, such as heart rate and pulse waves, play an essential role in biomedical applications for the early diagnosis of abnormal cardiovascular activities. Recent advances in flexible mechanical electronics represent a novel concept of miniaturized, wearable sensors for heart rate measurement that can be used in ambulatory environments. However, most mechanical sensors require the sensing element to be placed directly on the skin surface, which can lead to performance degradation or device damage due to significant skin deformation or external forces from skin‐object interactions. This work addresses this challenge by developing soft, stretchable mechano‐acoustic sensing platforms where all sensing components are not directly subjected to skin movement or deformation. Instead, this design allows cardiovascular pulse waves to propagate through a hollow, flexible microchannel, to vibrate the piezoresistive sensing element. Experimental studies demonstrate a complete wireless sensing system capable of detecting pulse waves and heart rates, with results consistent with those of commercially available devices. The proposed sensing concept allows for the develop of other wireless and flexible sensing systems such as a flexible air‐channel pad for detecting swallowing patterns from users’ laryngeal movements, facilitating a non‐invasive and remote platform for potential monitoring, and assessment of dysphagia. This study presents a novel design for flexible and wearable mechano‐acoustic sensing platforms for monitoring low‐frequency physiological signals from human bodies. By employing nanothin film, piezoresistive Si cantilever to detect soundwaves propagated within soft air channels, the proposed sensing platforms are capable of wireless real‐time heart rate monitoring and swallowing patterns detection with high sensitivity while maintaining significant users’ comfort.

Hydrochemistry and stable isotope tracing approaches were applied to groundwater and surface waters (rivers, springs, stormwater drainage canals, and treated wastewater discharges) to study the spatiotemporal geochemical and stable isotope characteristics and their interactions. The analysis revealed spatiotemporal variations and interactions between groundwater and surface water. Ca-HCO3-type water dominated the study area; representing 70.7%, (summer) and 81% (winter) of the samples. The chemical and isotopic values presented some spatial differences but minimal temporal changes, except in Tuul River water downstream of Ulaanbaatar. The Tuul River was mostly characterized as Ca-HCO3-type water, but varied temporally and spatially, shifting to Ca-Na-HCO3-type water in summer and Na-Ca-HCO3-type in winter in the downstream region after wastewater discharge. Also, electrical conductivity (EC) values of Tuul River are increasing gradually with distance, and more than double in concentration after mixing with treated wastewater discharges and stormwater drainage canals, providing clear evidence of anthropogenic impacts. The similarity in the stable isotopes and chemical characteristics of floodplain groundwater and river water suggest that local recharge of the alluvial groundwater with Tuul River water, whereas distant groundwater quality exhibited higher levels of minerals and stable isotopes. Cluster analysis clearly indicated a connection between floodplain groundwater and river water, and also the effect of anthropogenic discharges associated with stormwater and treated wastewater discharges. The analysis results also show that cluster analysis is a useful approach for optimizing future spatial sampling strategies, and offers a reliable classification of sampling stations in the region, especially along Tuul River.

Recently, Ni-rich layered cathode materials have become the most common material used for lithium-ion batteries. From a structural viewpoint, it is crucial to stabilize the surface structures of such materials, as they are prone to undesirable side reactions and particle cracking in which intergranular microcracks form at the particle surfaces and then propagate inside. As a simplified engineering technique for obtaining Ni-rich cathode materials with high reversibility and long-term cycling stability, we propose a facile surface coating of piezoelectric LiTaO3onto a Ni-rich cathode material to enhance the charge transfer reaction and surface structural integrity. Based on theoretical and experimental investigation, we demonstrate that this surface protection approach is effective at enhancing the reversibility and mechanical strength of Ni-rich cathode materials, leading to a stable cycle performance at up to 150 cycles, even at 60 °C. Furthermore, the piezoelectric characteristics of the surface LiTaO3can enhance the rate capability of Ni-rich cathode materials at current densities of up to 2.0C. The results of this study provide a practical insight on the development of Ni-rich cathode materials for practical use in electric vehicle applications.

Skin cancer has emerged as one of the leading types of cancers in the world, causing a high impact on the global burden of health and the economy. Basal cell and squamous cell carcinoma are the localized forms of skin cancer with a high prevalence and can be treated with a high success rate. However, melanoma, a rare type of skin cancer with a high mortality rate, can metastasize and invade other parts of the body. Various skin cancer treatment approaches have been developed and advanced from localized to systemic treatment over the years to improve the low success rate associated with skin cancer, especially metastatic melanoma. The systemic treatment of skin cancer is highly benefitted by drug delivery systems (DDS) designed to function with much higher specificity and lower side effects than the direct treatment with drugs. While many nanomaterials based DDS have been developed in the past few years to take advantage of the small size and high functionality of nanomaterials, silica-based nanomaterials have recently emerged as the flexible DDS with a high biocompatibility, good clearance, a high drug loading capacity, and versatility to attach several drugs and targeting agents to its surface. In this review, recent progress in the treatment of melanoma using silica-based nanomaterials and their hybrids is discussed, highlighting the versatility and potential of these emerging nanomaterials as the DDS for delivering various molecules, including drugs and immunotherapy agents, peptides, and radio- and photo-active agents. The review also introduces various therapies available for the treatment of melanoma, including surgery, chemotherapy, targeted therapy, phototherapy, and immunotherapy and discusses the improvement in these therapies based on silica-based DDS. The review also highlights the role of silica nanomaterials and their hybrids in delivering combination therapy and the advantages of silica nanohybrids over pure silica-based DDS. Finally, we summarize the present status of silica-based nanomaterials in melanoma treatment and the current challenges that have to be solved for the clinical translation of these materials as DDS.

Smart biosensors attract significant interest due to real‐time monitoring of user health status, where bioanalytical electronic devices designed to detect various activities and biomarkers in the human body have potential applications in physical sign monitoring and health care. Bioelectronics can be well integrated by output signals with wireless communication modules for transferring data to portable devices used as smart biosensors in performing real‐time diagnosis and analysis. In this review, the scientific keys of biosensing devices and the current trends in the field of smart biosensors, (functional materials, technological approaches, sensing mechanisms, main roles, potential applications and challenges in health monitoring) will be summarized. Recent advances in the design and manufacturing of bioanalytical sensors with smarter capabilities and enhanced reliability indicate a forthcoming expansion of these smart devices from laboratory to clinical analysis. Therefore, a general description of functional materials and technological approaches used in bioelectronics will be presented after the sections of scientific keys to bioanalytical sensors. A careful introduction to the established systems of smart monitoring and prediction analysis using bioelectronics, regarding the integration of machine‐learning‐based basic algorithms, will be discussed. Afterward, applications and challenges in development using these smart bioelectronics in biological, clinical, and medical diagnostics will also be analyzed. Finally, the review will conclude with outlooks of smart biosensing devices assisted by machine learning algorithms, wireless communications, or smartphone‐based systems on current trends and challenges for future works in wearable health monitoring. This review summarizes key issues and offers suggestions for the novel use and integration of smart biosensors in real‐time health monitoring process, as well as provides insight into their material functionality and technological approaches. With smart established systems, bioelectronics can be able to accurately provide capabilities for diagnosing health conditions.

Increasing competition for resources in small-scale fisheries (SSFs) can lead to overharvesting and threatens their sustainability. Sustainable management policies require engaging multiple resource users in decision-making processes, capturing diverse interests, and creating a platform for collaborative activities. This paper combines participatory modelling and systems thinking approaches to develop a joint stakeholder understanding of system structure, feedback mechanisms, and system archetypes of a SSF system in the Tam Giang Lagoon, located along the central coast of Vietnam. The model revealed the extent to which the dynamics of this SSF system were governed by nonlinear and cyclic feedback loops between social and ecological components. To manage complexity, the interactions between reinforcing and balancing feedback loops were distilled into four key system archetypes—Limits to growth, Fixes that fail, Success to the successful, and Tragedy of the commons—that provide crucial lenses to identify leverage points for effective management. The findings suggest that the possibilities to avoid the dominance of undesirable archetypes in this highly contested fishery system remain limited for both local resource users and managers because of cultural and socioeconomic constraints. Reducing intensified resource exploitation and expanding livelihood alternatives for communities are key towards more sustainable pathways for this common-pool resource system and other similar ones. This case study demonstrates the usefulness of an analytical approach that integrates participatory modelling with systems thinking with the ultimate goal of improving communication and collaboration among multiple stakeholders in complex socio-ecological situations.

Abstract This paper deals with a structural optimization to maximize the no-load flux control capability of a double excitation synchronous machine (DESM). The air-gap flux in this machine type can be regulated by controlling the field currents. In this paper, this curve in the no-load condition is referred to as the flux control range (FCR). Maximizing the gap between the minimum-flux and maximizing the maximum-flux points of this curve is targeted to improve the controlling effectiveness of the field windings, and reduce field winding's copper losses. This gap is affected by two factors: the magnetic saturation and thermal limits of the machine. Thermal analyses are rarely focused for the DESM type in the literature. The contribution of this paper is to maximize the FCR gap taking into account the thermal limitation. In addition, a general guide for the DESM design will be also discussed. [ABSTRACT FROM AUTHOR]

Computer numerical control (CNC) machine tool plays an extremely significant role in any manufacturing industry due to its automation and high accuracy. Keeping the CNC machine tool at its highest performance to meet the demand of high accuracy machining is always significant. To maintain the accuracy of a machine tool over the time, it is important to measure and compensate the geometric error, one of the main error source of machine tool, especially when the machine get old. There are totally 21 geometrical errors in a 3-axis machine tool including three translational errors and three rotational errors for each axis and three perpendicular error (Squareness) within three axes of the machine. This paper presents an economical and simple method for measuring the geometric error of a 3-axis CNC machine tool based on the machining of actual samples. Three samples for each axis will be machined following a design cutting path. The samples will then be measured using a coordinate measuring machine (CMM). The collect data will be used for estimating the geometric errors. The volumetric errors will be then computed and verified through machining of 3D geometries.

Rapid development and wide adoption of mass spectrometry-based glycoproteomic technologies have empowered scientists to study proteins and protein glycosylation in complex samples on a large scale. This progress has also created unprecedented challenges for individual laboratories to store, manage, and analyze proteomic and glycoproteomic data, both in the cost for proprietary software and high-performance computing and in the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI), for proteomic and glycoproteomic data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignments to peptide sequences, false discovery rate estimation, protein inference, quantitation of global protein levels, and specific glycan-modified glycopeptides as well as other modification-specific peptides such as phosphorylation, acetylation, and ubiquitination. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open-source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at https://github.com/huizhanglab-jhu/ms-pycloud.

Haptic (touch) is important for effective interaction with the surroundings. In teleoperated surgical systems, its absence leads to reduced perception, making delicate tasks difficult and resulting in unexpected damage to surrounding tissues. To enhance safety, a force‐feedback system and haptic device are needed. However, existing haptic prototypes are associated with rigid, bulky, and heavy components, making effective communication with the skin problematic. This paper presents a teleoperated endoscopic surgical system with an integrated 3D force sensor and real‐time haptic feedback. A surgical robotic arm is remotely controlled by a soft haptic glove incorporated 3‐axis cutaneous device and a finger kinesthetic module. The 3D force sensor is constructed from hydraulic filament soft sensors that can induce pressure change under strain. To enable precise motion, the haptic glove is operated by a feedforward controller and a master‐slave architecture. Experiments with human subjects (n= 15) show that cutaneous and kinesthetic feedback significantly improves the user's performance (9.4 out of 10) compared to no haptic feedback (2.27 out of 10). Finally, subjects rank the new system as highly wearable, comfortable, and effective, which is expected to bridge a gap in the surgical field and support the future development of advanced teleoperated systems. This work introduces a teleoperated surgical system with integrated 3D force sensor and a soft wearable haptic display. The new system is expected to bridge a gap in the field of wearable haptic devices and support the future development of remote surgery.

In Van Phong Bay, Viet Nam, the economically important macroalgae sea grapes (Caulerpa lentillifera;Caulerpaceae, Bryopsidales) and the spotted babylon snail (Babylonia areolata) are cultivated in tidal ponds in close proximity. A co-culture in the same pond could benefit farmers by saving space and mitigating potential eutrophication. The study assessed the co-culture potential of sea grapes and spotted babylon snails held within the same system. In an outdoor experiment, three different treatments (algae and snails together, algae and snails spatially separated, only algae) were assessed for their effect on water quality, biomass properties and size increase of both organisms, photosynthetic efficiency, antioxidant activity, and total phenolic content of the macroalgae and survival of the snails. In a second (indoor) experiment, the influence of different snail densities on the physiological state of the macroalgae was investigated. In both experiments, the presence of the snails raised the concentrations of nitrogen oxides (NOx) and phosphate (PO4). The co-culture had a positive effect on both growth and physiology of the sea grapes. Sea grapes on trays and co-cultured with Babyloniashowed the highest increase in biomass. Babyloniagrowth and survival were not affected by spatial separation of the alga and high stocking densities could be implemented without negatively affecting the seaweed. The results are promising regarding the establishment of co-cultures and indicate the economic feasibility of integrating B. areolatasnails into C. lentilliferapond cultures.

Objective This study was performed to determine the outcomes of patients with coronavirus disease 2019 (COVID-19) who developed hypoxemic respiratory failure necessitating high-flow nasal cannula (HFNC) therapy and to identify the predictors of HFNC therapy success.Methods This retrospective observational study involved all patients treated with HFNC therapy at a center for COVID-19 in Viet Nam from August to October 2021.Results The study recruited 302 patients. Of these 302 patients, 171 (56.6%) underwent successful HFNC therapy, and the all-cause mortality rate was 33.44%. Non-critical COVID-19 and a higher respiratory rate–oxygenation (ROX) index at 48 hours after initiating HFNC therapy were independently correlated with HFNC therapy success. The statistically significant predictors of HFNC therapy success were younger age, non-critical COVID-19, a higher platelet count when starting HFNC therapy, and a higher ROX index at 24, 36, and 48 hours after HFNC therapy initiation.Conclusions HFNC therapy appears to be effective in patients with COVID-19 who develop respiratory failure requiring respiratory support. Non-critical COVID-19 and a higher ROX index measured 48 hours after HFNC therapy initiation might serve as predictive factors for the success of HFNC therapy.

Mammalian polymerase theta (Polθ) is a multifunctional enzyme that promotes error-prone DNA repair by alternative nonhomologous end joining (alt-NHEJ). Here we present structure–function analyses that reveal that, in addition to the polymerase domain, Polθ-helicase activity plays a central role during double-strand break (DSB) repair. Our results show that the helicase domain promotes chromosomal translocations by alt-NHEJ in mouse embryonic stem cells and also suppresses CRISPR–Cas9- mediated gene targeting by homologous recombination (HR). In vitro assays demonstrate that Polθ-helicase activity facilitates the removal of RPA from resected DSBs to allow their annealing and subsequent joining by alt-NHEJ. Consistent with an antagonistic role for RPA during alt-NHEJ, inhibition of RPA1 enhances end joining and suppresses recombination. Taken together, our results reveal that the balance between HR and alt-NHEJ is controlled by opposing activities of Polθ and RPA, providing further insight into the regulation of repair-pathway choice in mammalian cells.

Recently, early-strength concrete has been applied widely in high-rise buildings and rigid pavement maintenance due to its advantages in time and cost reduction, and its construction efficiency. Admixtures including setting accelerators and hardening accelerators, are usually used to achieve high early-strength concrete. However, the mechanism of those admixtures at the early age of cement hydration was not clearly examined. Hence, this research investigated the influence of setting accelerators, hardening accelerators and their combinations on the hydration of cement paste using the heat curing method for the application to rigid pavement maintenance, and precast concrete. By evaluating the differences between the setting time, early compressive strength, exothermic curves, XRD patterns, and Fe-SEM images of the cement paste with and without adding Potassium bromide (KBr), Calcium formate (Ca(HCOO)2), and their combination, the results indicated that the addition of setting accelerators such as Ca(HCOO)2had a significant effect on the setting behavior of cement paste instead of the compressive strength enhancement. Therefore, the addition of Ca(HCOO)2also had a low effect on the mechanical strength of the paste when increasing the curing temperature. In contrast, the addition of hardening accelerators such as KBr had a greater accelerating impact on the mechanical strength of the cement paste when increasing the curing temperature. Combining a setting accelerator and a hardening accelerator could greatly improve cement paste early-age compressive strength for both normal and heat curing. Based on the XRD analysis, and the Fe-SEM results, numerous hydration products were formed in early-age cement hydration by the addition of 2.0 % KBr with 3.0 % Ca(HCOO)2, especially in 8 h of 50 °C curing temperature. Hence, this combination significantly enhanced the early mechanical strength of the cement pastes.

In recent years, advances in modern technology have altered the practice of surgery from open to minimally invasive surgery (MIS) aided by robots. Teleoperated surgical robotic systems (TSRSs) provide numerous significant benefits for MIS over traditional approaches, including improved safety, more efficient and precise surgery, better cosmesis, shorter recovery time, and reduced postoperative pain. Existing TSRSs’ master consoles, with improvements in vision systems, designs, and control methods, have significantly enhanced human–robot interactions, resulting in safer and more accurate medical intervention operations. Despite advances, haptic technologies, including sensors, machine assistance, and intuitive devices for user interfaces, are still limited, resulting in less effective usage of TSRSs for surgical operations. This review presents a summary of the emerging TSRSs with a focus on their user interfaces. In addition, advanced sensing, haptic, smart garments, and medical image artificial intelligence (AI) assistance technologies are shown with their potential for use in master consoles of the TSRSs are shown. Finally, a discussion on the need for a smart human‐robot interface for TSRSs is given. Teleoperated surgical robotic systems (TSRSs) provide numerous significant benefits over traditional surgery. Herein, a summary of advanced user interfaces for the TSRSs, including new sensing, haptic, smart garments, and medical image artificial intelligence (AI) assistance technologies, is introduced. The technologies, challenges, and suggestions for the future development of a smart human‐robot interface for TSRSs are also given.

Polyvinylidene fluoride (PVDF) is a polymer prized for its unique material properties, including a high resistance to corrosive acids such as HCL and HF and its piezoelectric potential based on the proper microstructure arrangement. In this work, the effects of fused filament fabrication (FFF) routine parameters on printed PVDF film properties were investigated using a variety of experimental methods. The influence of in-fill angle (0°, 45°, and 90°) on the effective Young’s Modulus, Poisson’s ratio, and yield strength were evaluated using tensile testing and a digital image correlation (DIC) analysis. The phase content, in particular the β-phase amount, within the semi-crystalline PVDF films was determined as a function of processing parameters using the FTIR method. Considered parameters included the extrusion temperature, horizontal speed, in-situ applied hot end voltage, and bed material. Results showed that higher β-phase content was associated with lower extrusion temperatures, faster extrusion rates, and higher hot end voltages. While all “as printed” films demonstrated little to no measurable piezoelectricity, PVDF films printed with a high β-phase content and subjected to a post-printing corona poling procedure showed a small, but consistent piezoelectric response. Based on a static deflection cantilever beam experiment, the d31coefficient of the poled specimens was estimated at 1.19 pm/V.

Three short field surveys were conducted in the Phia Oac-Phia Den Nature Reserve to assess the species diversity and endemism of local bat fauna. In combination with data from a previous study, 24 bat species of 5 families, representing > 20% of the national bat diversity, were recorded in the study area. The occurrence of several bat species restricted to montane forests, that is, Murina chrysochaetes, Pipistrellus coromandra, and a potentially new species Rhinolophuscf. macrotis, suggests that Phia Oac is an important area for bat conservation in Vietnam and thus more comprehensive studies need to be performed.

Abstract: Machine tools have greatly improved in recent decades. Among them, miniaturized machine tools (mMTs) that have advantages in terms of reduced energy consumption, space requirements, costs, and other resources are becoming more and more popular in the area of micro scale parts manufacturing. However it is exceedingly difficult to calibrate an mMT due to its small size. This paper proposes a novel method for identifying the geometrical errors of a rotary axis of miniaturized 5-axis machine tools using two position sensitive detectors (PSDs) and a laser diode. This work not only reduces the complication of the system structure and setup but also solves the problem of assembly. We propose a method to determine errors based on the geometrical position of PSDs, laser beam path, and its readout signals after each angle of rotation. The homogenous transformation approach is used to find the individual error components. A system sensitivity analysis is also presented in this paper.

News briefs are presented on the textile industry and clothing trade in former Soviet republics. Production of processed textile fibers rose significantly in Uzbekistan in the first half of 2010. Vietnam and Uzbekistan signed a trade promotion agreement. Clothing exports from Georgia rose in 2009 for the 10th consecutive year.

Curcumin is a polyphenol from turmeric Curcuma longaL that has been proved to possess numerous biological and pharmaceutical activities, including anti-cancer properties. However, curcumin has only limited clinical applications due to the aqueous insolubility characteristic that reduces its biological availability. On the other hand, using nanoparticles as drug delivery system has potential as it increases solubility of hydrophobic substances such as curcumin. Furthermore, nanoparticles can protect and control release of drug. Therefore, the objective of this project is to prepare nanoparticles by polymeric encapsulating curcumin by 1-3/1-6 ?-glucan extracted from Vietnamese mushrooms to increase drug delivery efficiency and biological effect. Method of the preparation is nano-precipitation. The produced curcumin-?-glucan-nanoparticles (NanoGluCur) takes spherical shape with 60-70 nm in diameter. As expected, water solubility of curcumin increases about 180 times, from 0.6 ?g ml?1to 0.11 mg ml?1. Loading capacity of NanoGluCur is 18.16%. In vitrocytotoxicity and anti-tumor promoting effects of NanoGluCur were also investigated. Results revealed that NanoGluCur is able to inhibit the growth of two human cancer cell lines Hep-G2 and LU-1 with IC50values of 6.82 and 15.53 mg ml?1, respectively, while free curcumin expresses the activity with IC50values of 7.41 and 18.82 mg ml?1. At the concentration of 40 mg ml?1, NanoGluCur showed anti-tumor promoting effects in reducing tumor size by 59.93% and tumor density by 40.52%, while the percentages caused by pristine curcumin were 41.36% and 29.14%, respectively. These results demonstrated dual effect of 1-3/1-6 ?-glucan encapsulated curcumin nanoparticles: higher water solubility and better in vitroanti-cancer effects compared to free curcumin and 1-3/1-6 ?-glucan, expectedly. This observation can potentially open a new approach in research and manufacture of functional foods from medicinal mushrooms.

Recent results on a new multiple-quantum-well saturable absorber (SA) device allowing fast responding power stabilization are reviewed. Combined with the classical SA achieving extinction ratio improvement, it allows all-optical amplitude-shift-keying 2R signal regeneration. Furthermore its phase-preserving characteristics make it potentially useful to prevent phase noise accumulation in phase encoded signals.