Complementary use of visual and olfactory cues to assess capture of Bactrocera dorsalis (Hendel): Implementation and field verification via an IoT-based automatic monitoring system.

This study examined the effect of combining visual and olfactory cues to attract oriental fruit flies (OFFs). Six different colored light-emitting diodes (LEDs) served as a visual attractant and methyl eugenol served as olfactory bait to lure male flies. An internet of things (IoT)-based pest monitoring system, consisting of sensor nodes, a gateway, and automatic counting traps, was deployed in the field to automatically collect environmental data and pest counts. The results of the calibrated experiments indicated that green, yellow, or red LEDs exhibited better performance in attracting flies than white, purple, or blue LEDs or no LEDs. With an accurate combination of visual and olfactory cues, the proposed IoT-based pest monitoring system may be an effective tool in agricultural pest management, given its advantages for efficiently capturing OFFs in a labor and time saving manner, providing accurate information regarding increases in pest populations, and enabling long-term, real-time data collection.

Safety and immunogenicity of a thermostable ID93 + GLA-SE tuberculosis vaccine candidate in healthy adults.

Adjuvant-containing subunit vaccines represent a promising approach for protection against tuberculosis (TB), but current candidates require refrigerated storage. Here we present results from a randomized, double-blinded Phase 1 clinical trial (NCT03722472) evaluating the safety, tolerability, and immunogenicity of a thermostable lyophilized single-vial presentation of the ID93 + GLA-SE vaccine candidate compared to the non-thermostable two-vial vaccine presentation in healthy adults. Participants were monitored for primary, secondary, and exploratory endpoints following intramuscular administration of two vaccine doses 56 days apart. Primary endpoints included local and systemic reactogenicity and adverse events. Secondary endpoints included antigen-specific antibody (IgG) and cellular immune responses (cytokine-producing peripheral blood mononuclear cells and T cells). Both vaccine presentations are safe and well tolerated and elicit robust antigen-specific serum antibody and Th1-type cellular immune responses. Compared to the non-thermostable presentation, the thermostable vaccine formulation generates greater serum antibody responses (p < 0.05) and more antibody-secreting cells (p < 0.05). In this work, we show the thermostable ID93 + GLA-SE vaccine candidate is safe and immunogenic in healthy adults.

Real-time monitoring of deformed wing virus-infected bee foraging behavior following histone deacetylase inhibitor treatment.

Impairment in the learning/memory behavior of bees is responsible for the massive disappearance of bee populations and its consequent agricultural economic losses. Such impairment might be because of o both pesticide exposure and pathogen infection, with a key contributor deformed wing virus (DWV). The present study found that sodium butyrate (NaB) significantly increased survival and reversed the learning/memory impairment of DWV-infected bees. A next-generation sequencing analysis showed that NaB affected the expression of genes involved in glycolytic processes and memory formation, which were suppressed by DWV infection. In addition, we performed a large-scale movement tracking experiment by using a wireless sensor network-based automatic real-time monitoring system and confirmed that NaB could improve the homing ability of DWV-infected bees. In short, we demonstrated the mechanism of how epigenetic regulation can resume the memory function of honeybees and suggest strategies for applying NaB to reduce the incidence of colony losses.

Lie symmetry analysis of the effects of urban infrastructures on residential property values.

Due to the complexity of socio-economic-related issues, people thought of housing market as a chaotic nucleus situated at the intersection of neighboring sciences. It has been known that the dependence of house features on the residential property value can be estimated employing the well-established hedonic regression analysis method in teams of location characteristic, neighborhood characteristic and structure characteristic. However, to further assess the roles of urban infrastructures in housing markets, we proposed a new kind of volatility measure for house prices utilizing the Lie symmetry analysis of quantum theory based on Schrödinger equation, mainly focusing on the effects of transportation systems and public parks on residential property values. Based on the municipal open government data regularly collected for four cities, including Boston, Milwaukee, Taipei and Tokyo, and all spatial sampling sites were featured by United States Geological Survey (USGS) National Map, transportation and park were modelled as perturbations to the quantum states generated by the feature space in response to the environmental amenities with different spatial extents. In an attempt to ascertain the intrinsic impact of the location-dependent price information obtained, the similarity functions associated with the Schrödinger equation were considered to facilitate revealing the city amenities capitalizing into house prices. By examining the spatial spillover phenomena of house prices in the four cities investigated, it was found that the mass transit systems and the public green lands possessed the infinitesimal generators of Lie point symmetries Y2 and Y5, respectively. Compared statistically with the common performance criteria, including mean absolute error (MAE), mean squared error (MSE) and, root mean squared error (RMSE) obtained by hedonic pricing model, the Lie symmetry analysis of the Schrödinger equation approach developed herein was successfully carried out. The invariant-theoretical characterizations of economics-related phenomena are consonant with the observed residential property values of the cities internationally, ultimately leading to develop a new perspective in the global financial architecture.

A graph placement methodology for fast chip design.

Chip floorplanning is the engineering task of designing the physical layout of a computer chip. Despite five decades of research1, chip floorplanning has defied automation, requiring months of intense effort by physical design engineers to produce manufacturable layouts. Here we present a deep reinforcement learning approach to chip floorplanning. In under six hours, our method automatically generates chip floorplans that are superior or comparable to those produced by humans in all key metrics, including power consumption, performance and chip area. To achieve this, we pose chip floorplanning as a reinforcement learning problem, and develop an edge-based graph convolutional neural network architecture capable of learning rich and transferable representations of the chip. As a result, our method utilizes past experience to become better and faster at solving new instances of the problem, allowing chip design to be performed by artificial agents with more experience than any human designer. Our method was used to design the next generation of Google's artificial intelligence (AI) accelerators, and has the potential to save thousands of hours of human effort for each new generation. Finally, we believe that more powerful AI-designed hardware will fuel advances in AI, creating a symbiotic relationship between the two fields.

An Alternative Body Temperature Measurement Solution: Combination of a Highly Accurate Monitoring System and a Visualized Public Health Cloud Platform.

To quickly isolate suspected cases to control the epidemics, this study proposes a body temperature monitoring system with a thermography based on the Internet of Things (IoT) architecture. The collected data are transmitted to a back-end platform via wireless communication. Using the analyzed data, the platform provides services, such as instant alerts for any anomalies, infectious disease outbreak prediction, and risk level assessment for a given area, and it will be a great help to epidemic prevention. The mean absolute percentage error and root mean square error of the proposed monitoring system under an extensive series of experiments are 0.04% and 0.0204°C, respectively. It shows that the body temperature measured by the thermal imaging sensor in the system can accurately represent the actual body temperature after specific calibrations that take the environmental temperature into account. It can also be expanded to a decision supporting system to help schools or government agencies to make proper decisions to stop the spread of infectious diseases.

Intensive measures of luminescence in GaN/InGaN heterostructures.

The intensive measures of luminescence in a GaN/InGaN multiple quantum well system are used to examine the thermodynamics and phenomenological structure. The radiative /nonradiative transitions along with absorbed or emitted phonons that occur between the different quantum states of the electrons and holes associated with these processes make the quantum efficiency of a semiconductor nanosystem in an equilibrium state an extensive property. It has long been recognized that tuning of the indium (In) composition in InGaN interlayers gives the potential to obtain a spectrum in the near-infrared to near-ultraviolet spectral range. The thermodynamic intensive properties, including the Debye temperature, carrier temperature, and junction temperature, are the most appropriate metrics to describe the optical-related interactions inherent in a given heterostructure and so can be used as the state variables for understanding the quantum exchange behaviors. The energetic features of the quantum processes are characterized based on analysis of the intensive parameters as determined by means of electroluminescence (EL) and photoluminescence (PL) spectroscopy and current-voltage measurement and then correlated with the designed InGaN/GaN microstructures. According to the McCumber-Sturge theory, the EL and PL Debye temperatures obtained experimentally signal the strength of the electron-phonon and photon-phonon interaction, respectively, while the EL and PL carrier/junction temperatures correspond to the carrier localization. Higher EL Debye temperatures and lower EL carrier/junction temperatures reflect significantly higher luminescence quantum yields, indicative of electron-phonon coupling in the transfer of thermal energy between the confined electrons and the enhancement by excited phonons of heat-assisted emissions. On the other hand, the observation of low luminescence efficiency, corresponding to the lower PL Debye temperatures and higher PL carrier/junction temperatures, is attributed to photon-phonon coupling. These findings are in good accordance to the dependence of the EL and PL quantum efficiency on the In-content of the InGaN/GaN barriers, suggesting that the characteristic Debye and carrier/junction temperatures are intensive parameters useful for assessing the optical properties of a nano-engineered semiconductor heterostructure.

A Multichannel Calorimetric Simultaneous Assay Platform Using a Microampere Constant-Current Looped Enthalpy Sensor Array.

Calorimetric biochemical measurements offer various advantages such as low waste, low cost, low sample consumption, short operating time, and labor-savings. Multichannel calorimeters can enhance the possibility of performing higher-throughput biochemical measurements. An enthalpy sensor (ES) array is a key device in multichannel calorimeters. Most ES arrays use Wheatstone bridge amplifiers to condition the sensor signals, but such an approach is only suitable for null detection and low resistance sensors. To overcome these limitations, we have developed a multichannel calorimetric simultaneous assay (MCSA) platform. An adjustable microampere constant-current (AMCC) source was designed for exciting the ES array using a microampere current loop measurement circuit topology. The MCSA platform comprises a measurement unit, which contains a multichannel calorimeter and an automatic simultaneous injector, and a signal processing unit, which contains multiple ES signal conditioners and a data processor. This study focused on the construction of the MCSA platform; in particular, construction of the measurement circuit and calorimeter array in a single block. The performance of the platform, including current stability, temperature sensitivity and heat sensitivity, was evaluated. The sensor response time and calorimeter constants were given. The capability of the platform to detect relative enzyme activity was also demonstrated. The experimental results show that the proposed MCSA is a flexible and powerful biochemical measurement device with higher throughput than existing alternatives.

Magnetic Sensing through the Abdomen of the Honey bee.

Honey bees have the ability to detect the Earth's magnetic field, and the suspected magnetoreceptors are the iron granules in the abdomens of the bees. To identify the sensing route of honey bee magnetoreception, we conducted a classical conditioning experiment in which the responses of the proboscis extension reflex (PER) were monitored. Honey bees were successfully trained to associate the magnetic stimulus with a sucrose reward after two days of training. When the neural connection of the ventral nerve cord (VNC) between the abdomen and the thorax was cut, the honey bees no longer associated the magnetic stimulus with the sucrose reward but still responded to an olfactory PER task. The neural responses elicited in response to the change of magnetic field were also recorded at the VNC. Our results suggest that the honey bee is a new model animal for the investigation of magnetite-based magnetoreception.

A Hybrid Memetic Framework for Coverage Optimization in Wireless Sensor Networks.

One of the critical concerns in wireless sensor networks (WSNs) is the continuous maintenance of sensing coverage. Many particular applications, such as battlefield intrusion detection and object tracking, require a full-coverage at any time, which is typically resolved by adding redundant sensor nodes. With abundant energy, previous studies suggested that the network lifetime can be maximized while maintaining full coverage through organizing sensor nodes into a maximum number of disjoint sets and alternately turning them on. Since the power of sensor nodes is unevenly consumed over time, and early failure of sensor nodes leads to coverage loss, WSNs require dynamic coverage maintenance. Thus, the task of permanently sustaining full coverage is particularly formulated as a hybrid of disjoint set covers and dynamic-coverage-maintenance problems, and both have been proven to be nondeterministic polynomial-complete. In this paper, a hybrid memetic framework for coverage optimization (Hy-MFCO) is presented to cope with the hybrid problem using two major components: 1) a memetic algorithm (MA)-based scheduling strategy and 2) a heuristic recursive algorithm (HRA). First, the MA-based scheduling strategy adopts a dynamic chromosome structure to create disjoint sets, and then the HRA is utilized to compensate the loss of coverage by awaking some of the hibernated nodes in local regions when a disjoint set fails to maintain full coverage. The results obtained from real-world experiments using a WSN test-bed and computer simulations indicate that the proposed Hy-MFCO is able to maximize sensing coverage while achieving energy efficiency at the same time. Moreover, the results also show that the Hy-MFCO significantly outperforms the existing methods with respect to coverage preservation and energy efficiency.

Therapeutic outcomes of low-level laser therapy for closed bone fracture in the human wrist and hand.

OBJECTIVE: The therapeutic outcomes of low-level laser therapy (LLLT) on closed bone fractures (CBFs) in the wrist and hand were investigated in this controlled study. BACKGROUND DATA: Animal research has confirmed that LLLT increases osteocyte quantity; however, little research has been conducted to determine the effect of LLLT on the treatment of human bone fractures. METHODS: In this study, the therapeutic outcomes of administering 830 nm LLLT to treat CBFs in the wrist or hand were examined. Fifty patients with CBFs in the wrist and hand, who had not received surgical treatment, were recruited and randomly assigned to two groups. The laser group underwent a treatment program in which 830 nm LLLT (average power 60 mW, peak power 8 W, 10 Hz, 600 sec, and 9.7 J/cm(2) per fracture site) was administered five times per week for 2 weeks. Participants in a placebo group received sham laser treatment. The pain, functional disability, grip strength, and radiographic parameters of the participants were evaluated before and after treatment and at a 2-week follow-up. RESULTS: After treatment and at the follow-up, the laser group exhibited significant changes in all of the parameters compared with the baseline (p<0.05). The results of comparing the two groups after treatment and at the follow-up indicated significant between-group differences among all of the parameters (p<0.05). CONCLUSIONS: LLLT can relieve pain and improve the healing process of CBFs in the human wrist and hand.

Colonoscopy with magnetic control system to navigate the forepart of colonoscope shortens the cecal intubation time.

BACKGROUND: Colonoscopy is considered the most effective method for diagnosing colorectal diseases, but its application is sometimes limited due to invasiveness, patient intolerance, and the need for sedation. OBJECTIVE: The aim of this study was to improve the problem of loop formation and shorten the cecal intubation time of colonoscopy by using a magnetic control system (MCS). METHODS: Two experienced gastroenterologists, three trainees, and a novice repeated colonoscopy without or with MCS on three colonoscopy training model simulator cases. These cases were divided into introductory (case 2) and challenging levels (cases 4 and 5). The cecal intubation times were recorded. RESULTS: For all cases, the average cecal intubation times for the experienced gastroenterologists with MCS were significantly shorter than without MCS (case 2: 52.45 vs. 27.65 s, p < 0.001; case 4: 166.7 vs. 120.55 s, p < 0.01; case 5: 130.35 vs. 100.2 s, p < 0.05). Those of the trainees also revealed significantly shorter times with MCS (case 2: 67.27 vs. 51 s, p < 0.01; case 4: 253.27 vs. 170.97 s, p < 0.001; case 5: 144.1 vs. 85.57 s, p < 0.001). CONCLUSION: Conducting colonoscopy with MCS is safe and smooth, and shortens the cecal intubation time by navigating the forepart of the colonoscope. In addition, all diagnostic and therapeutic benefits of conventional colonoscopy are retained.

Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (WSN) framework.

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.

Effect of low-level laser stimulation on EEG.

Conventional laser stimulation at the acupoint can induce significant brain activation, and the activation is theoretically conveyed by the sensory afferents. Whether the insensible low-level Laser stimulation outside the acupoint could also evoke electroencephalographic (EEG) changes is not known. We designed a low-level laser array stimulator (6 pcs laser diode, wavelength 830 nm, output power 7 mW, and operation frequency 10 Hz) to deliver insensible laser stimulations to the palm. EEG activities before, during, and after the laser stimulation were collected. The amplitude powers of each EEG frequency band were analyzed. We found that the low-level laser stimulation was able to increase the power of alpha rhythms and theta waves, mainly in the posterior head regions. These effects lasted at least 15 minutes after cessation of the laser stimulation. The amplitude power of beta activities in the anterior head regions decreased after laser stimulation. We thought these EEG changes comparable to those in meditation.

Magnetic control system targeted for capsule endoscopic operations in the stomach--design, fabrication, and in vitro and ex vivo evaluations.

This paper presents a novel solution of a hand-held external controller to a miniaturized capsule endoscope in the gastrointestinal (GI) tract. Traditional capsule endoscopes move passively by peristaltic wave generated in the GI tract and the gravity, which makes it impossible for endoscopists to manipulate the capsule endoscope to the diagnostic disease areas. In this study, the main objective is to present an endoscopic capsule and a magnetic field navigator (MFN) that allows endoscopists to remotely control the locomotion and viewing angle of an endoscopic capsule. The attractive merits of this study are that the maneuvering of the endoscopic capsule can be achieved by the external MFN with effectiveness, low cost, and operation safety, both from a theoretical and an experimental point of view. In order to study the magnetic interactions between the endoscopic capsule and the external MFN, a magnetic-analysis model is established for computer-based finite-element simulations. In addition, experiments are conducted to show the control effectiveness of the MFN to the endoscopic capsule. Finally, several prototype endoscopic capsules and a prototype MFN are fabricated, and their actual capabilities are experimentally assessed via in vitro and ex vivo tests using a stomach model and a resected porcine stomach, respectively. Both in vitro and ex vivo test results demonstrate great potential and practicability of achieving high-precision rotation and controllable movement of the capsule using the developed MFN.

A QoS-guaranteed coverage precedence routing algorithm for wireless sensor networks.

For mission-critical applications of wireless sensor networks (WSNs) involving extensive battlefield surveillance, medical healthcare, etc., it is crucial to have low-power, new protocols, methodologies and structures for transferring data and information in a network with full sensing coverage capability for an extended working period. The upmost mission is to ensure that the network is fully functional providing reliable transmission of the sensed data without the risk of data loss. WSNs have been applied to various types of mission-critical applications. Coverage preservation is one of the most essential functions to guarantee quality of service (QoS) in WSNs. However, a tradeoff exists between sensing coverage and network lifetime due to the limited energy supplies of sensor nodes. In this study, we propose a routing protocol to accommodate both energy-balance and coverage-preservation for sensor nodes in WSNs. The energy consumption for radio transmissions and the residual energy over the network are taken into account when the proposed protocol determines an energy-efficient route for a packet. The simulation results demonstrate that the proposed protocol is able to increase the duration of the on-duty network and provide up to 98.3% and 85.7% of extra service time with 100% sensing coverage ratio comparing with LEACH and the LEACH-Coverage-U protocols, respectively.

Collaborative localization in wireless sensor networks via pattern recognition in radio irregularity using omnidirectional antennas.

In recent years, various received signal strength (RSS)-based localization estimation approaches for wireless sensor networks (WSNs) have been proposed. RSS-based localization is regarded as a low-cost solution for many location-aware applications in WSNs. In previous studies, the radiation patterns of all sensor nodes are assumed to be spherical, which is an oversimplification of the radio propagation model in practical applications. In this study, we present an RSS-based cooperative localization method that estimates unknown coordinates of sensor nodes in a network. Arrangement of two external low-cost omnidirectional dipole antennas is developed by using the distance-power gradient model. A modified robust regression is also proposed to determine the relative azimuth and distance between a sensor node and a fixed reference node. In addition, a cooperative localization scheme that incorporates estimations from multiple fixed reference nodes is presented to improve the accuracy of the localization. The proposed method is tested via computer-based analysis and field test. Experimental results demonstrate that the proposed low-cost method is a useful solution for localizing sensor nodes in unknown or changing environments.

Therapeutic effects of low-level laser on lateral epicondylitis from differential interventions of Chinese-Western medicine: systematic review.

BACKGROUND: Low-level laser therapy (LLLT) is a conservative treatment for lateral epicondylitis (LE), but it is also an alternative intervention between the very different approaches of Chinese and Western medicine. OBJECTIVE: The purpose of this study was to systematically review and meta-analyze the therapeutic effects of LLLT on LE. METHODS: We searched several electronic databases, including Medline, PubMed, and CINAHL, and explored studies that were randomized controlled trials on the therapeutic effects of LLLT on LE from 1990 to February 2009. These studies were systematically reviewed for the difference in therapeutic effects among various LLLTs on acupuncture points and on tender and myofascial trigger points (MTrPs). The reviewed therapeutic effects included pain, grip strength, range of motion (ROM), and weight tests, and were compared by meta-analysis. RESULTS: We selected ten articles, and in seven of them the irradiation was conducted on tender points or MTrPs in the experimental groups. In two other articles, the irradiation was conducted on acupuncture points, and the last one was conducted on both kinds of points. Only three articles provided sufficient data for meta-analysis. The results revealed that applying LLLT on tender points or MTrPs is an effective means to improve the effect size (ES) of pain release after treatment (pooled ES: 0.71, 95% CI: 0.82- approximately 0.60) and follow-up (pooled ES: 1.05, 95% CI: 1.16- approximately 0.94). LLLT application was also able to increase the grip force, ROM, and weight test (p < 0.05). CONCLUSIONS: We suggest that using LLLT on tender points or MTrPs of LE could effectively improve therapeutic effects.

A robust correlation estimator and nonlinear recurrent model to infer genetic interactions in Saccharomyces cerevisiae and pathways of pulmonary disease in Homo sapiens.

In order to identify genes involved in complex diseases, it is crucial to study the genetic interactions at the systems biology level. By utilizing modern high throughput microarray technology, it has become feasible to obtain gene expressions data and turn it into knowledge that explains the regulatory behavior of genes. In this study, an unsupervised nonlinear model was proposed to infer gene regulatory networks on a genome-wide scale. The proposed model consists of two components, a robust correlation estimator and a nonlinear recurrent model. The robust correlation estimator was used to initialize the parameters of the nonlinear recurrent curve-fitting model. Then the initialized model was used to fit the microarray data. The model was used to simulate the underlying nonlinear regulatory mechanisms in biological organisms. The proposed algorithm was applied to infer the regulatory mechanisms of the general network in Saccharomyces cerevisiae and the pulmonary disease pathways in Homo sapiens. The proposed algorithm requires no prior biological knowledge to predict linkages between genes. The prediction results were checked against true positive links obtained from the YEASTRACT database, the TRANSFAC database, and the KEGG database. By checking the results with known interactions, we showed that the proposed algorithm could determine some meaningful pathways, many of which are supported by the existing literature.