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In this study, an integrated system for remotely monitoring air pollution data was developed. This system combines vehicle exhaust emission data with driving information. It comprises an exhaust extraction device (EED), an improved On-Board Diagnostic II (OBDII) device, a mobile app, and a backend server database. The EED detects exhaust gases such as NOx, COx, and PM2.5 and transmits this information to the OBDII device through 2.4G communication. The OBDII device gathers vehicle driving information through a CAN 2.0 interface, integrates this information with vehicle exhaust emission data, and transmits the integrated information to the app through Bluetooth. The app forwards the integrated data to the backend database through 4G/5G communication for storage. Overall, this system provides a platform for the comprehensive collection, analysis, and application of big data pertaining to vehicle pollution sources and driving behavior. Analysis of actual driving experiments involving three vehicles revealed a correlation of over 80 % between vehicles’ revolutions per minute and CO2 and PM2.5 emissions, indicating that driving behaviors affect vehicle exhaust emissions. In summary, the proposed system not only stores relevant driving information in real time but also provides a platform for the future analysis of driving behavior and vehicle exhaust emissions.

This paper presents a joint source–channel image transmission model based on a modified trellis construction using variable-length and fixed-length codes. The model employs linear block trellis codes and a modified Bahl–Cocke–Jelinek–Raviv algorithm for decoding in the source channel. Additionally, this model utilizes a hierarchical tree and a parity-check matrix to combine the source and channel codes, reducing errors in the decoding process and enabling the decoding of longer sequences without substantial loss of quality.

Circular permutation (CP) is a protein sequence rearrangement in which the amino- and carboxyl-termini of a protein can be created in different positions along the imaginary circularized sequence. Circularly permutated proteins usually exhibit conserved three-dimensional structures and functions. By comparing the structures of circular permutants (CPMs), protein research and bioengineering applications can be approached in ways that are difficult to achieve by traditional mutagenesis. Most current CP detection algorithms depend on structural information. Because there is a vast number of proteins with unknown structures, many CP pairs may remain unidentified. An efficient sequence-based CP detector will help identify more CP pairs and advance many protein studies. For instance, some hypothetical proteins may have CPMs with known functions and structures that are informative for functional annotation, but existing structure-based CP search methods cannot be applied when those hypothetical proteins lack structural information. Despite the considerable potential for applications, sequence-based CP search methods have not been well developed. We present a sequence-based method, SeqCP, which analyzes normal and duplicated sequence alignments to identify CPMs and determine candidate CP sites for proteins. SeqCP was trained by data obtained from the Circular Permutation Database and tested with nonredundant datasets from the Protein Data Bank. It shows high reliability in CP identification and achieves an AUC of 0.9. SeqCP has been implemented into a web server available at: http://pcnas.life.nthu.edu.tw/SeqCP/.

Abstract This paper aims to develop a position tracking algorithm by which a rat in a radial arm maze can be accurately located in real time. An infrared (IR) night-vision camera was hung above the maze to capture IR images of the rat. The IR images were binarized and then duplicated for subsequent intersection and opening operations. Due to simple operations and a high robustness against the noise spots formed by the droppings of the rat, it took just minutes to process more than 9000 frames, and an accuracy above 99% was reached as well. The maze was intruded by an experimenter to further test the robustness, and the accuracy slightly fell to 98%. For comparison purposes, the same experiments were carried out using a pre-trained YOLO v2 model. The YOLO counterpart gave an accuracy beyond 97% in the absence and in the presence of the intruder. In other words, this work slightly outperformed the YOLO counterpart in terms of the accuracy in both cases, which indicates the robustness of this work. However, it took the YOLO counterpart an hour or so to locate a rat contained in the frames, which highlights the contribution of this work.

This paper presents a lower extremity exoskeleton as a rehabilitation tool that involves electronics, biomedicine and mechanism design. Using the rehabilitation tool, the paralyzed lower limb muscles and impaired neurons of a stroke patient can be well revitalized during repeated stand-to-sit-to-stand movements. The body of an exoskeleton user can be well stabilized using a zero-torque theory. As compared with a “without” exoskeleton counterpart, an average of 66.98% reduction was observed in the RMS value of electromyography signals across the vastus intermedius muscle among a group of 5 healthy subjects with the exoskeleton (p

The reliable prediction of electronic properties associated with graphene nanosystems can be challenging for conventional electronic structure methods, such as Kohn–Sham (KS) density functional theory (DFT), due to the presence of strong static correlation effects in these systems. To address this challenge, TAO (thermally assisted occupation) DFT has been recently proposed. In the present study, we employ TAO-DFT to predict the electronic properties of n-HGQRs (i.e., the hexagonal graphene quantum rings consisting of n aromatic rings fused together at each side). From TAO-DFT, the ground states of n-HGQRs are singlets for all the cases investigated (n = 3–15). As the system size increases, there should be a transition from the nonradical to polyradical nature of ground-state n-HGQR. The latter should be intimately related to the localization of active TAO-orbitals at the inner and outer edges of n-HGQR, which increases with increasing system size.

Cooperation, paying a cost to benefit others, is widespread. Cooperation can be promoted by pleiotropic ‘win-win’ mutations which directly benefit self (self-serving) and partner (partner-serving). Previously, we showed that partner-serving should be defined as increased benefit supply rate per intake benefit. Here, we report that win-win mutations can rapidly evolve even under conditions unfavorable for cooperation. Specifically, in a well-mixed environment we evolved engineered yeast cooperative communities where two strains exchanged costly metabolites, lysine and hypoxanthine. Among cells that consumed lysine and released hypoxanthine, ecm21 mutations repeatedly arose. ecm21 is self-serving, improving self’s growth rate in limiting lysine. ecm21 is also partner-serving, increasing hypoxanthine release rate per lysine consumption and the steady state growth rate of partner and of community. ecm21 also arose in monocultures evolving in lysine-limited chemostats. Thus, even without any history of cooperation or pressure to maintain cooperation, pleiotropic win-win mutations may readily evolve to promote cooperation.

Mutualisms can be promoted by pleiotropic win-win mutations which directly benefit self (self-serving) and partner (partner-serving). Intuitively, partner-serving phenotype could be quantified as an individual’s benefit supply rate to partners. Here, we demonstrate the inadequacy of this thinking, and propose an alternative. Specifically, we evolved well-mixed mutualistic communities where two engineered yeast strains exchanged essential metabolites lysine and hypoxanthine. Among cells that consumed lysine and released hypoxanthine, a chromosome duplication mutation seemed win-win: it improved cell’s affinity for lysine (self-serving), and increased hypoxanthine release rate per cell (partner-serving). However, increased release rate was due to increased cell size accompanied by increased lysine utilization per birth. Consequently, total hypoxanthine release rate per lysine utilization (defined as ‘exchange ratio’) remained unchanged. Indeed, this mutation did not increase the steady state growth rate of partner, and is thus solely self-serving during long-term growth. By extension, reduced benefit production rate by an individual may not imply cheating.

Currently, many ischemic stroke patients worldwide suffer from physical and mental impairments, and thus have a low quality of life. However, although rehabilitation is acknowledged as an effective way to recover patients' health, there does not exist yet an adaptive training platform for animal tests so far. For this sake, this paper aims to develop an adaptive escalator (AE) for rehabilitation of rats with cerebral ischemia. Rats were observed to climb upward spontaneously, and a motor-driven escalator, equipped with a position detection feature and an acceleration/deceleration mechanism, was constructed accordingly as an adaptive training platform. The rehabilitation performance was subsequently rated using an incline test, a rotarod test, the infarction volume, the lesion volume, the number of MAP2 positive cells and the level of cortisol. This paper is presented in 3 parts as follows. Part 1 refers to the escalator mechanism design, part 2 describes the adaptive ladder-climbing rehabilitation mechanism, and part 3 discusses the validation of an ischemic stroke model. As it turned out, a rehabilitated group using this training platform, designated as the AE group, significantly outperformed a control counterpart in terms of a rotarod test. After the sacrifice of the rats, the AE group gave an average infarction volume of (34.36 ± 3.8)%, while the control group gave (66.41 ± 3.1)%, validating the outperformance of the escalator-based rehabilitation platform in a sense. An obvious difference between the presented training platform and conventional counterparts is the platform mechanism, and for the first time in the literature rats can be well and voluntarily rehabilitated at full capacity using an adaptive escalator. Taking into account the physical diversity among rats, the training strength provided was made adaptive as a reliable way to eliminate workout or secondary injury. Accordingly, more convincing arguments can be made using this mental stress-free training platform.

Vehicle technology development drives economic development but also causes severe mobile pollution sources. Eco-driving is an effective driving strategy for solving air pollution and achieving driving safety. The on-board diagnostics II (OBD-II) module is a common monitoring tool used to acquire sensing data from in-vehicle electronic control units. However, different vehicle models use different controller area network (CAN) standards, resulting in communication difficulties; however, relevant literature has not discussed compatibility problems. The present study researched and developed the universal OBD-II module, adopted deep learning methods to evaluate fuel consumption, and proposed an intuitive driving graphic user interface design. In addition to using the universal module to obtain data on different CAN standards, this study used deep learning methods to analyze the fuel consumption of three vehicles of different brands on various road conditions. The accuracy was over 96%, thus validating the practicability of the developed system. This system will greatly benefit future applications that employ OBD-II to collect various types of driving data from different car models. For example, it can be implemented for achieving eco-driving in bus driver training. The developed system outperforms those proposed by previous research regarding its completeness and universality.

This study presents a noncontact electrocardiogram (ECG) measurement system to replace conventional ECG electrode pads during ECG measurement. The proposed noncontact electrode design comprises a surface guard ring, the optimal input resistance, a ground guard ring, and an optimal voltage divider feedback. The surface and ground guard rings are used to reduce environmental noise. The optimal input resistor mitigates distortion caused by the input bias current, and the optimal voltage divider feedback increases the gain. Simulated gain analysis was subsequently performed to determine the most suitable parameters for the design, and the system was combined with a capacitive driven right leg circuit to reduce common-mode interference. The present study simulated actual environments in which interference is present in capacitive ECG signal measurement. Both in the case of environmental interference and motion artifact interference, relative to capacitive ECG electrodes, the proposed electrodes measured ECG signals with greater stability. In terms of R–R intervals, the measured ECG signals exhibited a 98.6% similarity to ECGs measured using contact ECG systems. The proposed noncontact ECG measurement system based on capacitive sensing is applicable for use in everyday life.

For years, capacitive electrocardiogram (CECG) has been known to be susceptible to ambient interference. In light of this, a novel capacitive electrode was developed as an effective way to reduce the interference effect. This was done by simply introducing the capacitive elector in series with a 1 pF capacitor, and the 60 Hz common mode noise induced by AC power lines was cancelled using a capacitive right leg (CRL) circuit. The proposed electrode did as expected outperform two counterparts in terms of SNR, and particularly gave an up to 99.8% correlation between RRIs extracted from an ECG and a CECG signal, a figure far beyond 52% and 63% using the two counterparts. This capacitive electrode was originally designed for long-term noncontact monitoring of heart rate, and hopefully can be integrated to portable devices for other medical care services in the near future.

In this paper, an algorithm to extract respiration signals using a flexible projected capacitive sensing mattress (FPCSM) designed for personal health assessment is proposed. Unlike the interfaces of conventional measurement systems for poly-somnography (PSG) and other alternative contemporary systems, the proposed FPCSM uses projected capacitive sensing capability that is not worn or attached to the body. The FPCSM is composed of a multi-electrode sensor array that can not only observe gestures and motion behaviors, but also enables the FPCSM to function as a respiration monitor during sleep using the proposed approach. To improve long-term monitoring when body movement is possible, the FPCSM enables the selection of data from the sensing array, and the FPCSM methodology selects the electrodes with the optimal signals after the application of a channel reduction algorithm that counts the reversals in the capacitive sensing signals as a quality indicator. The simple algorithm is implemented in the time domain. The FPCSM system is used in experimental tests and is simultaneously compared with a commercial PSG system for verification. Multiple synchronous measurements are performed from different locations of body contact, and parallel data sets are collected. The experimental comparison yields a correlation coefficient of 0.88 between FPCSM and PSG, demonstrating the feasibility of the system design.

This paper presents a cost-effective sensor system for mattresses that can classify the sleeping posture of an individual and prevent pressure ulcers. This system applies projected capacitive sensing to the field of health care. The charge time (CT) method was used to sensitively and accurately measure the capacitance of the projected electrodes. The required characteristics of the projected capacitor were identified to develop large-area applications for sensory mattresses. The area of the electrodes, the use of shielding, and the increased length of the transmission line were calibrated to more accurately measure the capacitance of the electrodes in large-size applications. To offer the users comfort in the prone position, a flexible substrate was selected and covered with 16 × 20 electrodes. Compared with the static charge sensitive bed (SCSB), our proposed system-flexible projected capacitive-sensing mattress (FPCSM) comes with more electrodes to increase the resolution of posture identification. As for the body pressure system (BPS), the FPCSM has advantages such as lower cost, higher aging-resistance capability, and the ability to sense the capacitance of the covered regions without physical contact. The proposed guard ring design effectively absorbs the noise and interrupts leakage paths. The projected capacitive electrode is suitable for proximity-sensing applications and succeeds at quickly recognizing the sleeping pattern of the user.

This paper describes an infrared-sensing running wheel (ISRW) system for the quantitative measurement of effective exercise activity in rats. The ISRW system provides superior exercise training compared with commercially available traditional animal running platforms. Four infrared (IR) light-emitting diode/detector pairs embedded around the rim of the wheel detect the rat's real-time position; the acrylic wheel has a diameter of 55 cm and a thickness of 15 cm, that is, it is larger and thicker than traditional exercise wheels, and it is equipped with a rubber track. The acrylic wheel hangs virtually frictionless, and a DC motor with an axially mounted rubber wheel, which has a diameter of 10 cm, drives the acrylic wheel from the outer edge. The system can automatically train rats to run persistently. The proposed system can determine effective exercise activity (EEA), with the IR sensors (which are connected to a conventional PC) recording the rat exercise behavior. A prototype of the system was verified by a hospital research group performing ischemic stroke experiments on rats by considering middle cerebral artery occlusion. The experimental data demonstrated that the proposed system provides greater neuroprotection in an animal stroke model compared with a conventional treadmill and a motorized running wheel for a given exercise intensity. The quantitative exercise effectiveness indicator showed a 92% correlation between an increase in the EEA and a decrease in the infarct volume. This indicator can be used as a noninvasive and objective reference in clinical animal exercise experiments.