bluuebunny/crossref_metadata_2025 huggingface dataset:
Knocker
Authors: Gong Taesik , Cho Hyunsung , Lee Bowon , Lee Sung-Ju
Published: September 2019

While smartphones have enriched our lives with diverse applications and functionalities, the user experience still often involves manual cumbersome inputs. To purchase a bottle of water for instance, a user must locate an e-commerce app, type the keyword for a search, select the right item from the list, and finally place an order. This process could be greatly simplified if the smartphone identifies the object of interest and automatically executes the user preferred actions for the object. We present Knocker that identifies the object when a user simply knocks on an object with a smartphone. The basic principle of Knocker is leveraging a unique set of responses generated from the knock. Knocker takes a multimodal sensing approach that utilizes microphones, accelerometers, and gyroscopes to capture the knock responses, and exploits machine learning to accurately identify objects. We also present 15 applications enabled by Knocker that showcase the novel interaction method between users and objects. Knocker uses only the built-in smartphone sensors and thus is fully deployable without specialized hardware or tags on either the objects or the smartphone. Our experiments with 23 objects show that Knocker achieves an accuracy of 98% in a controlled lab and 83% in the wild.
Integrating Activity Recognition and Nursing Care Records
Authors: Inoue Sozo , Lago Paula , Hossain Tahera , Mairittha Tittaya , Mairittha Nattaya
Published: September 2019

In this paper, we introduce a system of integrating activity recognition and collecting nursing care records at nursing care facilities as well as activity labels and sensors through smartphones, and describe experiments at a nursing care facility for 4 months. A system designed to be used even by staff not familiar with smartphones could collected enough number of data without losing but improving their workload for recording. For collected data, we revealed the nature of the collected data as for activities, care details, and timestamps, and considering them, we show a reference accuracy of recognition of nursing activity which is durable to time skewness, overlaps, and class imbalances. Moreover, we demonstrate the near future prediction to predict the next day's activities from the previous day's records which could be useful for proactive care management. The dataset collected is to be opened to the research community, and can be the utilized for activity recognition and data mining in care facilities.
Exploring the Touch and Motion Features in Game-Based Cognitive Assessments
Authors: Intarasirisawat Jittrapol , Ang Chee Siang , Efstratiou Christos , Dickens Luke William Feidhlim , Page Rupert
Published: September 2019

Early detection of cognitive decline is important for timely intervention and treatment strategies to prevent further deterioration or development of more severe cognitive impairment, as well as identify at risk individuals for research. In this paper, we explore the feasibility of using data collected from built-in sensors of mobile phone and gameplay performance in mobile-game-based cognitive assessments. Twenty-two healthy participants took part in the two-session experiment where they were asked to take a series of standard cognitive assessments followed by playing three popular mobile games in which user-game interaction data were passively collected. The results from bivariate analysis reveal correlations between our proposed features and scores obtained from paper-based cognitive assessments. Our results show that touch gestural interaction and device motion patterns can be used as supplementary features on mobile game-based cognitive measurement. This study provides initial evidence that game related metrics on existing off-the-shelf games have potential to be used as proxies for conventional cognitive measures, specifically for visuospatial function, visual search capability, mental flexibility, memory and attention.
Face Recognition Assistant for People with Visual Impairments
Authors: Kianpisheh Mohammad , Li Franklin Mingzhe , Truong Khai N.
Published: September 2019

Although there are many face recognition systems to help individuals with visual impairments (VIPs) recognize other people, almost all require a database with the pictures and names of the people who should be tracked. These solutions would not be able to help VIPs recognize people they might not know well. In this work, we investigate the requirements and challenges that must be addressed in the design of a face recognition system for helping VIPs recognize people with whom they have weak-ties. We first conducted a formative study with eight visually impaired people. Using insights learned from the formative study, we developed a research prototype that runs on a mobile phone worn around the user's neck. The developed prototype is a wearable face recognition system that opportunistically captures and stores undistorted face images and contextual information about the user's interaction with each person to a database, without the user intervention, as she interacts with new people. We then used this prototype application as a technology probe---asking VIP participants to use the device in a realistic scenario in which they meet and re-encounter several new people. We analyze and report feedback collected from VIPs about the design and use of such a service.
GeoLifecycle
Authors: Kwon Young D. , Chatzopoulos Dimitris , ul Haq Ehsan , Wong Raymond Chi-Wing , Hui Pan
Published: September 2019

As Location-Based Social Networks (LBSNs) have become widely used by users, understanding user engagement and predicting user churn are essential to the maintainability of the services. In this work, we conduct a quantitative analysis to understand user engagement patterns exhibited both offline and online in LBSNs. We employ two large-scale datasets which consist of 1.3 million and 62 million users with 5.3 million reviews and 19 million tips in Yelp and Foursquare, respectively. We discover that users keep traveling to diverse locations where they have not reviewed before, which is in contrast to "human life" analogy in real life, an initial exploration followed by exploitation of existing preferences. Interestingly, we find users who eventually leave the community show distinct engagement patterns even with their first ten reviews in various facets, e.g., geographical, venue-specific, linguistic, and social aspects. Based on these observations, we construct predictive models to detect potential churners. We then demonstrate the effectiveness of our proposed features in the churn prediction. Our findings of geographical exploration and online interactions of users enhance our understanding of human mobility based on reviews, and provide important implications for venue recommendations and churn prediction.
Beyond Respiration
Authors: Liu Chen , Xiong Jie , Cai Lin , Feng Lin , Chen Xiaojiang , Fang Dingyi
Published: September 2019

Sleep sound-activities including snore, cough and somniloquy are closely related to sleep quality, sleep disorder and even illnesses. To obtain the information of these activities, current solutions either require the user to wear various sensors/devices, or use the camera/microphone to record the image/sound data. However, many people are reluctant to wear sensors/devices during sleep. The video-based and audio-based approaches raise privacy concerns. In this work, we propose a novel system TagSleep to address the issues mentioned above. For the first time, we propose the concept of two-layer sensing. We employ the respiration sensing information as the basic first-layer information, which is applied to further obtain rich second-layer sensing information including snore, cough and somniloquy. Specifically, without attaching any device to the human body, by just deploying low-cost and flexible RFID tags near to the user, we can accurately obtain the respiration information. What's more interesting, the user's cough, snore and somniloquy all affect his/her respiration, so the fine-grained respiration changes can be used to infer these sleep sound-activities without recording the sound data. We design and implement our system with just three RFID tags and one RFID reader. We evaluate the performance of TagSleep with 30 users (13 males and 17 females) for a period of 2 months. TagSleep is able to achieve higher than 96.58% sensing accuracy in recognizing snore, cough and somniloquy under various sleep postures. TagSleep also boosts the sleep posture recognition accuracy to 98.94%.
Combating Replay Attacks Against Voice Assistants
Authors: Pradhan Swadhin , Sun Wei , Baig Ghufran , Qiu Lili
Published: September 2019

Recently, there has been a surge in the popularity of voice-first devices, such as Amazon Echo, Google Home, etc. While these devices make our life more convenient, they are vulnerable to new attacks, such as voice replay. We develop an end-to-end system to detect replay attacks without requiring a user to wear any wearable device. Our system, called REVOLT, has several distinct features: (i) it intelligently exploits the inherent differences between the spectral characteristics of the original and replayed voice signals, (ii) it exploits both acoustic and WiFi channels in tandem, (iii) it utilizes unique breathing rate extracted from WiFi signal while speaking to test the liveness of human voice. After extensive evaluation, our voice component yields Equal Error Rate (EER) of 0.88% and 10.32% in our dataset and ASV2017 dataset, respectively; and WiFi based breathing detection achieves Breaths Per Minute (BPM) error of 1.8 up to 3m distance. We further combine WiFi and voice based detection and show the overall system offers low false positive and false negative when evaluated against a range of attacks.
Recruit Until It Fails
Authors: Sugrim Shridatt , Liu Can , Lindqvist Janne
Published: September 2019

Distinguishing identities is useful for several applications such as automated grocery or personalized recommendations. Unfortunately, several recent proposals for identification systems are evaluated using poor recruitment practices. We discovered that 23 out of 30 surveyed systems used datasets with 20 participants or less. Those studies achieved an average classification accuracy of 93%. We show that the classifier performance is misleading when the participant count is small. This is because the finite precision of measurements creates upper limits on the number of users that can be distinguished.

To demonstrate why classifier performance is misleading, we used publicly available datasets. The data was collected from human subjects. We created five systems with at least 20 participants each. In three cases we achieved accuracies greater than 90% by merely applying readily available machine learning software packages, often with default parameters. For datasets where we had sufficient participants, we evaluated how the performance degrades as the number of participants increases. One of the systems built suffered a drop in accuracy that was over 35% as the participant count increased from 20 to 250. We argue that data from small participant count datasets do not adequately explore variations. Systems trained on such limited data are likely to incorrectly identify users when the user base increases beyond what was tested. We conclude by explaining generalizable reasons for this issue and provide insights on how to conduct more robust system analysis and design.
Tracking Fatigue and Health State in Multiple Sclerosis Patients Using Connnected Wellness Devices
Authors: Tong Catherine , Craner Matthew , Vegreville Matthieu , Lane Nicholas D.
Published: September 2019

Multiple Sclerosis requires long-term disease management, but tracking patients through the use of clinical surveys is hindered by high costs and patient burden. In this work, we investigate the feasibility of using data from ubiquitous sensing to predict MS patients' fatigue and health status, as measured by the Fatigue Severity Scale (FSS) and EQ-5D index. We collected data from 198 MS patients who are given connected wellness devices for over 6 months. We examine how accurately can the collected data predict reported FSS and EQ-5D scores per patient using an ensemble of regressors. In predicting for both FSS and EQ-5D, we are able to achieve errors aligning with the instrument' standard measurement error (SEM), as well as strong and significant correlations between predicted and ground truth values. We also show a simple adaptation method that greatly reduces prediction errors through the use of just 1 user-supplied ground truth datapoint. For FSS (SEM 0.7), the universal model predicts weekly scores with MAE 1.00, while an adapted model predicts with MAE 0.58. For EQ-5D (SEM 0.093), the universal model predicts weekly scores with MAE 0.097, while an adapted model predicts with MAE 0.065. Our study represents the first sets of results showing that fatigue and health state of MS patients can be measured using data from connected wellness devices and a small number of background features, with promising prediction performance with errors within the accepted range of error in the widely used clinically-validated questionnaires. Future extensions and potential applications of our results can positively impact MS patient disease management and support clinical research.
sharedCharging
Authors: Wang Guang , Li Wenzhong , Zhang Jun , Ge Yingqiang , Fu Zuohui , Zhang Fan , Wang Yang , Zhang Desheng
Published: September 2019

Our society is witnessing a rapid vehicle electrification process. Even though being environmental-friendly, electric vehicles have not reached their full potentials due to prolonged charging time. Moreover, unbalanced spatiotemporal charging demand/supply along with the uneven number of charging stations between heterogeneous fleets make electric vehicle management more challenging, e.g., surplus charging stations across a city for electric buses but limited charging stations in some regions for electric taxis, which severely limit the charging performance of the whole electric vehicle network in a city. In this paper, we first analyze a large-scale real-world dataset from two heterogeneous electric vehicle fleets in the Chinese city Shenzhen. We investigate their mobility and charging patterns and then verify the practicability and necessity of shared charging. Based on the insights we found, we design a generic real-time shared charging scheduling system called sharedCharging to improve overall charging efficiency for heterogeneous electric vehicle fleets. Our sharedCharging also considers sophisticated real-world constraints, e.g., station spaces, availability of charging points, real-time timetable guarantee, etc. More importantly, we take the electric bus and electric taxi fleets as a concrete example of heterogeneous electric vehicle fleets given their different operating patterns. We implement and evaluate sharedCharging with streaming data from over 13,000 electric taxis and 16,000 electric buses, coupled with the charging station data in the Chinese city Shenzhen, which is the largest public electric vehicle network in the world. The evaluation results demonstrate that the proposed sharedCharging reduces the waiting time by 63.5% and reduces the total charging time by 15% on average for e-taxis.
FlexTouch
Authors: Wang Yuntao , Zhou Jianyu , Li Hanchuan , Zhang Tengxiang , Gao Minxuan , Cheng Zhuolin , Yu Chun , Patel Shwetak , Shi Yuanchun
Published: September 2019

In this paper, we present FlexTouch, a technique that enables large-scale interaction sensing beyond the spatial constraints of capacitive touchscreens using passive low-cost conductive materials. This is achieved by customizing 2D circuit-like patterns with an array of conductive strips that can be easily attached to the sensing nodes on the edge of the touchscreen. FlexTouch requires no hardware modification, and is compatible with various conductive materials (copper foil tape, silver nanoparticle ink, ITO frames, and carbon paint), as well as fabrication methods (cutting, coating, and ink-jet printing). Through a series of studies and illustrative examples, we demonstrate that FlexTouch can support long-range touch sensing for up to 4 meters and everyday object presence detection for up to 2 meters. Finally, we show the versatility and feasibility of FlexTouch through applications such as body posture recognition, human-object interaction as well as enhanced fitness training experiences.
Designing Drones
Authors: Wojciechowska Anna , Frey Jeremy , Mandelblum Esther , Amichai-Hamburger Yair , Cauchard Jessica R.
Published: September 2019

The last few years have seen a revolution in aerial robotics where personal drones are becoming pervasive to our environments and can be bought by anyone anywhere, including at local supermarkets. As they become ubiquitous to our lives, it is crucial to understand how they are perceived and understood by people. The robotics community has extensively theorized and quantified how robotic agents are perceived as social creatures and how this affects users and passersby. However, drones present different form factors that are yet to be systematically explored. This work aims to fill this gap by understanding people's perceptions of drones and how drones physical features correlate to a series of dimensions. We explored the quadcopters available on the 2018 market and built a dataset of 63 images that were evaluated in a user study (N=307). Using the study results, we present a model of how people understand drones based on their design and which physical features are better suited for people wanting to interact with drones. Our findings highlight that safety features have a negative effect on several dimensions including trust. Our work contributes a set of design guidelines for future personal drones and concludes on the implications for ubiquitous computing.
Investigating Gesture Typing for Indirect Touch
Authors: Yang Zhican , Yu Chun , Yi Xin , Shi Yuanchun
Published: September 2019

With the development of ubiquitous computing, entering text on HMDs and smart TVs using handheld touchscreen devices (e.g., smartphone and controller) is becoming more and more attractive. In these indirect touch scenarios, the touch input surface is decoupled from the visual display. Compared with direct touch input, entering text using a keyboard in indirect touch is more challenging because before the finger touch, no visual feedback is available for locating the touch finger. Aiming at this problem, in this paper, we investigate the feasibility of gesture typing for indirect touch since keeping the finger in touch with the screen during typing makes it possible to provide continuous visual feedback, which is beneficial for increasing the input performance. We first examine users' gesture typing ability in terms of the appropriate keyboard size and location in motor space and then compare the typing performance in direct and indirect touch mode. We then propose an improved design to address the uncertainty and inaccuracy of the first touch. Our evaluation result shows that users can quickly acquire indirect gesture typing, and type 22.3 words per minute after 30 phases, which significantly outperforms previous numbers in literature. Our work provides the empirical support for leveraging gesture typing for indirect touch.
ProxiTalk
Authors: Yang Zhican , Yu Chun , Zheng Fengshi , Shi Yuanchun
Published: September 2019

Speech input, such as voice assistant and voice message, is an attractive interaction option for mobile users today. However, despite its popularity, there is a use limitation for smartphone speech input: users need to press a button or say a wake word to activate it before use, which is not very convenient. To address it, we match the motion that brings the phone to mouth with the user's intention to use voice input. In this paper, we present ProxiTalk, an interaction technique that allows users to enable smartphone speech input by simply moving it close to their mouths. We study how users use ProxiTalk and systematically investigate the recognition abilities of various data sources (e.g., using a front camera to detect facial features, using two microphones to estimate the distance between phone and mouth). Results show that it is feasible to utilize the smartphone's built-in sensors and instruments to detect ProxiTalk use and classify gestures. An evaluation study shows that users can quickly acquire ProxiTalk and are willing to use it. In conclusion, our work provides the empirical support that ProxiTalk is a practical and promising option to enable smartphone speech input, which coexists with current trigger mechanisms.
ShoesHacker
Authors: Yu Tuo , Nahrstedt Klara
Published: September 2019

The past few years have witnessed the rise of smart shoes, the wearable devices that measure foot force or track foot motion. However, people are not aware of the possible privacy leakage from in-shoe force sensors. In this paper, we explore the possibility of locating an indoor victim based on the force signals leaked from smart shoes. We present ShoesHacker, an attack scheme that reconstructs the corridor map of the building that the victim walks in based on force data only. The corridor map enables the attacker to recognize the building, and thus locate the victim on a global map. To handle the lack of training data, we design the stair landing detection algorithm, based on which we extract training data when victims are walking in stairwells. We estimate the trajectory of each walk, and propose the path merging algorithm to merge the trajectories. Moreover, we design a metric to quantify the similarity between corridor maps, which makes building recognition possible. Our experimental results show that, the building recognition accuracy reaches 77.5% in a 40-building dataset, and the victim can be located with an average error lower than 6 m, which reveals the danger of privacy leakage through smart shoes. CCS Concepts: • Information systems~Mobile information processing systems; Location based services; • Human-centered computing~Mobile devices; Ubiquitous and mobile computing systems and tools; • Security and privacy~Domain-specific security and privacy architectures.
PDMove
Authors: Zhang Hanbin , Xu Chenhan , Li Huining , Rathore Aditya Singh , Song Chen , Yan Zhisheng , Li Dongmei , Lin Feng , Wang Kun , Xu Wenyao
Published: September 2019

The medicine adherence in Parkinson's disease (PD) treatment has attracted tremendous attention due to the critical consequences it can lead to otherwise. As a result, clinics need to ensure that the medicine intake is performed on time. Existing approaches, such as self-report, family reminder, and pill counts, heavily rely on the patients themselves to log the medicine intake (hereafter, patient involvement). Unfortunately, PD patients usually suffer from impaired cognition or memory loss, which leads to the so-called medication non-adherence, including missed doses, extra doses, and mistimed doses. These instances can nullify the treatment or even harm the patients. In this paper, we present PDMove, a smartphone-based passive sensing system to facilitate medication adherence monitoring without the need for patient involvement. Specifically, PDMove builds on the fact that PD patients will present gait abnormality if they do not follow medication treatment. To begin with, PDMove passively collects gait data while putting the smartphone in the pocket. Afterward, the gait preprocessor helps extract gait cycle containing the Parkinsonism-related biomarkers. Finally, the medicine intake detector consisting of a multi-view convolutional neural network predicts the medicine intake. In this way, PDMove enables the medication adherence monitoring. To evaluate PDMove, we enroll 247 participants with PD and collect more than 100,000 gait cycle samples. Our results show that smartphone-based gait assessment is a feasible approach to the AI-care strategy to monitor the medication adherence of PD patients.
Route Prediction for Instant Delivery
Authors: Zhang Yan , Liu Yunhuai , Li Genjian , Ding Yi , Chen Ning , Zhang Hao , He Tian , Zhang Desheng
Published: September 2019

Instant delivery has drawn much attention recently, as it greatly facilitates people's daily lives. Unlike postal services, instant delivery imposes a strict deadline on couriers after a customer places an order online. Therefore it is critical to dispatch the order to an appropriate courier to guarantee the timely delivery. Ideally couriers should choose the optimal routes with the lowest overdue rate (i.e., the rate of the deliveries that are not finished in time) and the minimal distance. In practice, however, decision-making of the couriers is quite complex because individuals have different psychological perception of the environments (e.g., distance) and delivery requirements (e.g., deadline). To well predict their behaviors, we design multiple features to model the decision-making psychology of individual couriers and predict couriers' route with a machine learning algorithm. In particular, we reveal that perceived distance is the main factor influencing couriers' decision, which should be modeled based on the subjective understanding of the actual distances. Our design is implemented, deployed and evaluated on Ele.me, which is one of the largest instant delivery platforms in the world. Experimental results show that the overdue rate can be reduced by 48.02%, which is a significant improvement.
Invisible QR Code Hijacking Using Smart LED
Authors: Zhou Anfu , Su Guangyuan , Zhu Shilin , Ma HuaDong
Published: September 2019

Quick response (QR) codes have found versatile usage in numerous applications, but have also posed severe security threats such as privacy leakage, phishing and even payment inception if the codes are hijacked. The hijacking is often assumed to be preventable by physically isolating the codes from possible attackers, e.g., putting the QR code inside a glass cabinet distant to outsiders. In this paper, we explore a new QR code hijacking attack, named Li-Man, that can subvert such protection using smart LED. The key idea is to illuminate a target victim QR code from afar using specialized flickering light waveforms, which can transform the code to be any other predefined malicious ones when being captured by smart-phone cameras, while keeping the attack invisible to human visual perception. Li-Man builds on a modeling framework that harnesses the disparity between camera and human imaging mechanisms. We develop a Li-Man simulator and also implement a prototype to verify the feasibility and threat level of Li-Man. Experiments demonstrate that Li-Man can successfully realize the invisible hijacking of QR codes from multiple hidden positions in constrained space. On the other hand, we propose and verify a primary countermeasure that is promising to defeat the Li-Man attack.
Regulation of Genomic Output and (Pluri)potency in Regeneration
Authors: Duncan Elizabeth M. , Sánchez Alvarado Alejandro
Published: September 2019

Regeneration is a remarkable phenomenon that has been the subject of awe and bafflement for hundreds of years. Although regeneration competence is found in highly divergent organisms throughout the animal kingdom, recent advances in tools used for molecular and genomic characterization have uncovered common genes, molecular mechanisms, and genomic features in regenerating animals. In this review we focus on what is known about how genome regulation modulates cellular potency during regeneration. We discuss this regulation in the context of complex tissue regeneration in animals, from Hydra to humans, with reference to ex vivo–cultured cell models of pluripotency when appropriate. We emphasize the importance of a detailed molecular understanding of both the mechanisms that regulate genomic output and the functional assays that assess the biological relevance of such molecular characterizations.
Prematurity blunts the feeding-induced stimulation of translation initiation signaling and protein synthesis in muscle of neonatal piglets
Authors: Naberhuis Jane K. , Suryawan Agus , Nguyen Hanh V. , Hernandez-Garcia Adriana , Cruz Stephanie M. , Lau Patricio E. , Olutoye Oluyinka O. , Stoll Barbara , Burrin Douglas G. , Fiorotto Marta L. , Davis Teresa A.
Published: September 2019

Postnatal growth of lean mass is commonly blunted in preterm infants and may contribute to short- and long-term morbidities. To determine whether preterm birth alters the protein anabolic response to feeding, piglets were delivered at term or preterm, and fractional protein synthesis rates (Ks) were measured at 3 days of age while fasted or after an enteral meal. Activation of signaling pathways that regulate protein synthesis and degradation were determined. Relative body weight gain was lower in preterm than in term. Gestational age at birth (GAB) did not alter fasting plasma glucose or insulin, but when fed, plasma insulin and glucose rose more slowly, and reached peak value later, in preterm than in term. Feeding increased Ksin longissimus dorsi (LD) and gastrocnemius muscles, heart, pancreas, and kidney in both GAB groups, but the response was blunted in preterm. In diaphragm, lung, jejunum, and brain, feeding increased Ksregardless of GAB. Liver Kswas greater in preterm than term and increased with feeding regardless of GAB. In all tissues, changes in 4EBP1, S6K1, and PKB phosphorylation paralleled changes in Ks. In LD, eIF4E·eIF4G complex formation, phosphorylation of TSC2, mTOR, and rpS6, and association of mammalian target of rapamycin (mTOR1) complex with RagA, RagC, and Rheb were increased by feeding and blunted by prematurity. There were no differences among groups in LD protein degradation markers. Our results demonstrate that preterm birth reduces weight gain and the protein synthetic response to feeding in muscle, pancreas, and kidney, and this is associated with blunted insulin- and/or amino acid-induced translation initiation signaling.
Intermittent fasting improves metabolic flexibility in short-term high-fat diet-fed mice
Authors: Dedual Mara A. , Wueest Stephan , Borsigova Marcela , Konrad Daniel
Published: September 2019

Four days of high-fat diet (HFD) feeding are sufficient to induce glucose intolerance and hepatic steatosis in mice. While prolonged HFD-induced metabolic complications are partly mediated by increased food intake during the light (inactive) phase, such a link has not yet been established in short-term HFD-fed mice. Herein, we hypothesized that a short bout of HFD desynchronizes feeding behavior, thereby contributing to glucose intolerance and hepatic steatosis. To this end, 12-wk-old C57BL/6J littermates were fed a HFD for 4 days either ad libitum or intermittently. Intermittent-fed mice were fasted for 8 h during their inactive phase. Initiation of HFD led to an immediate increase in food intake already during the first light phase. Moreover, glucose tolerance was significantly impaired in ad libitum- but not in intermittent HFD-fed mice, indicating that desynchronized feeding behavior contributes to short-term HFD-induced glucose intolerance. Of note, overall food intake was similar between the groups, as was body weight. However, intermittent HFD-fed mice revealed higher fat depot weights. Phosphorylation of hormone sensitivity lipase and free fatty acid release from isolated adipocytes were significantly elevated, suggesting increased lipolysis in intermittent HFD-fed mice. Moreover, hepatic mRNA expression of lipogenetic enzymes and liver triglyceride levels were significantly increased in intermittent HFD-fed mice. Importantly, food deprivation decreased respiratory exchange ratio promptly in intermittent- but not in ad libitum HFD-fed mice. In conclusion, retaining a normal feeding pattern prevented HFD-induced impairment of metabolic flexibility in short-term HFD-fed mice.
The Parkinson’s Disease Composite Scale Is Adequately Responsive to Acute Levodopa Challenge
Authors: Pintér Dávid , Martinez-Martin Pablo , Janszky József , Kovács Norbert
Published: September 2019

Background. The Parkinson’s Disease Composite Scale (PDCS) is a recently developed easy-to-use tool enabling a timely but comprehensive assessment of Parkinson’s disease (PD)-related symptoms. Although the PDCS has been extensively validated, its responsiveness to acute levodopa challenge has not been demonstrated yet. Objective. To investigate the correlation between changes in the motor examination part of the Movement Disorder Society-sponsored Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) and the PDCS motor scores during acute levodopa challenge and calculate a cutoff range on the PDCS indicating clinically relevant improvement. Methods. A consecutive series of 100 patients with parkinsonism were assessed using the motor examination sections of the MDS-UPDRS and the PDCS at least 12 hours after the last levodopa dose and after the administration of a single dose of a suprathreshold immediate formulation of levodopa/benserazide reaching the “best ON.” Results. There was a high correlation between changes in the MDS-UPDRS and the PDCS motor scores (Spearman’s rho = 0.73, p<0.001). Receiver operating characteristic analysis revealed that a 14.6%–18.5% improvement in the PDCS motor scores corresponds to a 20–30% improvement in the MDS-UPDRS motor examination. Conclusions. The PDCS can reliably and adequately respond to an acute levodopa challenge. Any improvements in PDCS motor scores exceeding the 14.6–18.5% threshold could represent a clinically relevant response to levodopa.
Synthesis and Cytotoxic Activity against K562 and MCF7 Cell Lines of SomeN-(5-Arylidene-4-oxo-2-thioxothiazolidin-3-yl)-2-((4-oxo-3-phenyl-3,4-dihydroquinazoline-2-yl)thio)acetamide Compounds
Authors: Nguyen Cong T. , Nguyen Quang T. , Dao Phuc H. , Nguyen Thuan L. , Nguyen Phuong T. , Nguyen Hung H.
Published: September 2019

Ethyl 2-((4-oxo-3-phenyl-3,4-dihydroquinazolin-2-yl)thio)acetate (3) which was synthesized starting from anthranilic acid (1) via 2-thioxo-3-phenylquinazolin-4(3H)-one (2) reacted with hydrazine hydrate to afford 2-((4-oxo-3-phenyl-3,4-dihydroquinazolin-2-yl)thio)acetohydrazide (4). Reaction of (4) with thiocarbonyl-bis-thioglycolic acid gave a new compound nameN-(4-oxo-2-thioxothiazolidin-3-yl)-2-((4-oxo-3-phenyl-3,4-dihydroquinazolin-2-yl)thio)acetamide (5). Knoevenagel condensation of (5) with appropriate aldehydes gave fourteen (Z)-N-(5-arylidene-4-oxo-2-thioxothiazolidin-3-yl)-2-((4-oxo-3-phenyl-3,4-dihydroquinazolin-2-yl)thio)acetamide compounds (6a–o) with moderate yield. The chemical structure of the compounds was elucidated on the basis of IR,1H-NMR,13C-NMR, and HR-MS spectral data. The 5-arylidene-2-thioxothiazolidinone compounds exhibited mild-to-moderate cytotoxic activity against both K562 (chronic myelogenous leukemia) cells and MCF7 (breast cancer) cells.
Small-Size Wide-Band Low-Profile “Pixel Antenna”: Comparison of Theoretical and Experimental Results in L Band
Authors: Rammal Mohamad , Majed Mohamad , Arnaud Eric , Andrieu Joel , Jecko Bernard
Published: September 2019

This paper presents a small (≈λ/2 × λ/2) low-profile (λ/10) planar antenna built to work on a very large frequency band (≥40%) for applications in Telecom, Radar, IoT, etc. This antenna is called a “Pixel Antenna” because it was first used as a pixel in an agile beam radiating surface. In this paper, the pixel antenna is used alone to design multiband or wide-band antennas keeping the same radiation pattern and polarization throughout the band. The working principle used to design the Pixel Antenna is deduced from the well-known EBG (electromagnetic band gap) antenna in its low-profile version which already has a bandwidth close to ≈20%. The aim of this present work is to double this bandwidth by simultaneously feeding two modes of the original EBG material. The theoretical and experimental results are compared for an L band application, exhibiting bandwidth from 1 GHz to 1.52 GHz (41%). In addition, good radiation patterns of pixel antenna stay constant over the entire useful band without any degradation of the antenna performance. This proposed antenna design can be used to obtain wide bandwidth for any chosen frequency band (S band, X band, C band, etc.) using frequency scaling.
Study on the Mitigative Effect of Controlled Permeable Formwork (CPF) Liner on Early-Age Shrinkage of Box-Girder Concrete
Authors: Ye Jianxiong , Yu Linwen , Chen Yong
Published: September 2019

Because of its high binder content and severe construction environment, early-age cracking is one of the most important threats to concrete used in continuous box-girder bridge structures. In this study, controlled permeable formwork (CPF) liner was used to mitigate the early-age shrinkage and reduce the early-age cracking risk of box-girder concrete. Early-age shrinkage was measured by a noncontact method and started at 30 min after adding mix water until 7 d. Internal relative moisture content and pore distribution tests were also carried out to reveal the working mechanism of CPF liner. The results show that covering the concrete surface with CPF liner decreased early-age shrinkage significantly. Under the temperature of 20°C and the relative humidity of 60%, two-surface-covering and three-surface-covering CPF liner on concrete decreased the shrinkage by 44% and 48%, respectively, at 7 d compared with concrete without CPF liner covered on it. The main reason is that CPF liner enhanced the internal relative moisture content and resulted in better performance of the surface concrete.
Massive Upper Body and Cervicofacial Subcutaneous Emphysema Following Robotic Myomectomy
Authors: Capone Joseph , De Ranieri Aladino , Knezevic Nebojsa N. , Lukić Ivan K. , Candido Kenneth , Gluncic Vicko
Published: September 2019

Subcutaneous emphysema is defined as the unintentional introduction of air or carbon dioxide in the subcutaneous tissues. The use of robotic surgical techniques has greatly expanded over the past decade specifically to treat intraperitoneal pathology. In general, advantages of these minimally invasive procedures are reported to decrease operating time, patient morbidity, and shorten hospital stay providing a safe alternative to traditional surgery. However, as with any surgery, potential complications may occur. We describe an unusual case of massive subcutaneous emphysema involving the upper body and cervicofacial region, with bilateral pneumothoraces following robotic intraperitoneal surgery. Written authorization was obtained from the patient.
The Conundrum of Septic Shock Imitators in Patients with Hematologic Cancers: Case Presentation and Possible Differential Diagnoses
Authors: Berlot Giorgio , Moratelli Giulia , Tarchini Martina , Battaglia Katiuscia , Grassi Paolo , Zarrillo Nadia , Colella Vincenzo , Bussani Rossana
Published: September 2019

The authors describe the case of a patient treated with several cycles of chemotherapy due to an advanced stage non-Hodgkin lymphoma. One daafter the last cycle, he was admitted to our Intensive Care Unit with a septic shock-like clinical picture which didn’t respond to the aggressive treatment and the patient died a few hours later. The autoptical findings cast some doubts on the diagnosis, and demonstrated the presence of other factors imitating its symptoms. In this article, the mimickers of septic shock are reviewed and discussed, as some of them require an aggressive immunosuppression instead of the recommended treatment for septic shock.
Evaluations of Biomarker Status Changes between Primary and Recurrent Tumor Tissue Samples in Breast Cancer Patients
Authors: Nguyen Thi Hoa , Nguyen Van Hung , Nguyen Thanh Long , Qiuyin Cai , Phung Thi Huyen
Published: September 2019

Background. Obtaining tumor specimens and re-evaluating targeted markers is recommended, if possible, in breast cancer patients who relapsed after curative treatment. The biomarker status changes in rebiopsied tumors have been demonstrated to have considerable clinical implications. Objectives. To identify the changes of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status between the primary and recurrent lesions. Materials and Methods. We conducted a study among 67 patients with recurrent breast cancer, recruited from January 2014 to September 2018 in the Vietnam National Cancer Hospital to compare ER, PR, and HER2 status between the primary and recurrent lesions. For each patient, a specimen of their primary tumor and another specimen of recurrent lesions underwent pathological assessment. Immunohistochemistry (IHC) was performed to determine ER, PR, and HER2 status in both specimens. Results. Biomarker status conversion rates (in both directions) between primary and recurrent tumors were 26.9% for ER, 38.8% for PR, and 22.4% for HER2. Overall, IHC subtypes (hormone receptor positive, HER2 amplified, and triple-negative) changed in 25 out of 67 (37.3%) cases. Conversion rates were not statistically significantly different between patients with different recurrent sites and times of recurrence. Eight out of 13 initially triple-negative patients (61.5%) had a change to positive status of either ER, PR, or HER2. Conclusion. A substantial discordance in ER, PR, and HER2 status were observed between primary breast cancer tissues and recurrent lesions. Rebiopsy could bring new therapeutic opportunities in the management of patients with recurrent breast cancer.
Characterization of Layer Number of Two-Dimensional Transition Metal Diselenide Semiconducting Devices Using Si-Peak Analysis
Authors: Zhang Xian
Published: September 2019

Atomically thin materials such as semiconducting transition metal diselenide materials, like molybdenum diselenide (MoSe2) and tungsten diselenide (WSe2), have received intensive interests in recent years due to their unique electronic structure, bandgap engineering, ambipolar behavior, and optical properties and have motivated investigations for the next-generation semiconducting electronic devices. In this work, we show a nondestructive method of characterizing the layer number of two-dimensional (2-D) MoSe2 and WSe2 including single- and few-layer materials by Raman spectroscopy. The related photoluminescence properties are also studied as a reference. Although Raman spectroscopy is a powerful tool for determining the layer number of 2-D materials such as graphene and molybdenum disulfide (MoS2), there have been difficulties in precisely characterizing the layer number for MoSe2 and WSe2 by Raman spectroscopy due to the uncertain shifts during the Raman measurement process and the lack of multiple separated Raman peaks in MoSe2 and WSe2 for referencing. We then compared the normalized Si peak with MoSe2 and WSe2 and successfully identified the layer number of MoSe2 and WSe2. Similar to graphene and MoS2, the sample layer number is found to modify their optical properties up to 4 layers.
Mouse IgG2a Antibodies Specific for the CommensalStreptococcus mitisShow Stronger Cross-Reactivity withStreptococcus pneumoniaethan IgG1 Antibodies
Authors: Shekhar Sudhanshu , Khan Rabia , Khan Ata Ul Razzaq , Petersen Fernanda Cristina
Published: September 2019

Here we show that mouse IgG2a and IgG1 antibodies specific for the commensalStreptococcus mitiscross-react with pathogenStreptococcus pneumoniaeserotypes 2 and 4, although the cross-reactivity conferred by IgG2a is stronger than that by IgG1 antibodies. These findings may be important for understanding theS. mitis-induced IgG isotype responses and have consequences for the development of an effective pneumococcal vaccine.
Identification of WNT16 as a Predictable Biomarker for Accelerated Osteogenic Differentiation of Tonsil-Derived Mesenchymal Stem Cells In Vitro
Authors: Kim Yu-Hee , Cho Kyung-Ah , Lee Hyun-Ji , Park Minhwa , Kim Han Su , Park Joo-Won , Woo So-Youn , Ryu Kyung-Ha
Published: September 2019

The application of mesenchymal stem cells (MSCs) for treating bone-related diseases shows promising outcomes in preclinical studies. However, cells that are isolated and defined as MSCs comprise a heterogeneous population of progenitors. This heterogeneity can produce variations in the performance of MSCs, especially in applications that require differentiation potential in vivo, such as the treatment of osteoporosis. Here, we aimed to identify genetic markers in tonsil-derived MSCs (T-MSCs) that can predict osteogenic potential. Using a single-cell cloning method, we isolated and established several lines of nondifferentiating (ND) or osteoblast-prone (OP) clones. Next, we performed transcriptome sequencing of three ND and three OP clones that maintained the characteristics of MSCs and determined the top six genes that were upregulated in OP clones. Upregulation of WNT16 and DCLK1 expression was confirmed by real-time quantitative PCR, but only WNT16 expression was correlated with the osteogenic differentiation of T-MSCs from 10 different donors. Collectively, our findings suggest that WNT16 is a putative genetic marker that predicts the osteogenic potential of T-MSCs. Thus, examination of WNT16 expression as a selection criterion prior to the clinical application of MSCs may enhance the therapeutic efficacy of stem cell therapy for bone-related complications, including osteoporosis.
A User-Oriented Pricing Design for Demand Response in Smart Grid
Authors: Zhou Yanglin , Cheng Lin , Ci Song , Yang Yang , Ma Shiqian
Published: September 2019

Demand response (DR) programs are designed to affect the energy consumption behavior of end-users in smart grid. However, most existing pricing designs for DR programs ignore the influence of end-users’s diversity and personal preference. Thus, in this paper, we investigate an incentive pricing design based on the utility maximization rule with consideration of end-users’ preference and appliances’ operational patterns. In particular, the utility company determines the pricing policy by trading off the budget revenue and social obligation, while each end-user aims to maximize their own utility profits with high satisfaction level by scheduling multiclass appliances. We formulate the conflict and cooperative relationship between the utility company and end-users as a Stackelberg game, and the equilibrium points are obtained by the backward induction method, which exists and is unique. At the equilibrium, the utility company adopts real-time pricing (RTP) scheme to coordinate end-users to fulfill the benefit of themselves, i.e., under such price, end-users automatically maximize overall utility profits of the overall system. We propose a distributed algorithm and an adaptive pricing scheme for the utility company and end-users to jointly achieve the best performance of the entire system. Finally, extensive simulation results based on real operation data show the effectiveness of the proposed scheme.