bluuebunny/crossref_metadata_2025 huggingface dataset:
Home transfusion: three decades of practice at a tertiary care hospital
Authors: García Dora , Aguilera Ana , Antolín Francisco , Arroyo José‐Luis , Lozano Miguel , Sanroma Pedro , Romón Iñigo
Published: September 2018

BACKGROUND

Hospital at Home (HH) provides specialized care at the patients’ homes. Keeping patients in familial surroundings can result in better outcomes reducing readmission to hospital, mortality, and costs of care. Home transfusion (HT) can be a key element in HH management but is scarcely deployed due to concerns about safety and cost. We have reviewed our HT practice to assess its feasibility and safety.

STUDY DESIGN AND METHODS

We prospectively reviewed data collected from 1985 to 2015, focusing specially on feasibility and procedural safety, looking for adverse events of transfusion. We also assessed the situation in similar hospitals in Spain with a survey about their practice.

RESULTS

A total of 613 patients received 2260 blood components in 2126 transfusion episodes. A total of 93% patients received fewer than 10 transfusions. Most patients were treated for blood diseases (32%) or cancers (20%). The rate of adverse effects was 2.68% and decreased significantly with time. Fever was the most common adverse reaction. Patients who received transfusion of more than one blood product in a day were at higher risk of adverse events. No errors or near‐miss events were detected, and no patient had to be readmitted to hospital for this cause. The survey on HT practices in similar hospitals showed great variation in practice.

CONCLUSION

HT is feasible, sustainable, and safe, when performed on selected patients by dedicated HH units with well‐trained staff, under specific protocols.
Development of Polysulfone/Activated Carbon Nanofibers Mixed Matrix Membrane for CO2/CH4 Separation
Authors: Jamian Z. , Tajuddin M. H. , Yusof N. , Che Othman F. E.
Published: September 2018

This study was performed primarily to investigate the effect of activated carbon nanofiber (ACNF) on carbon dioxide and methane separation performance of mixed matrix membrane (MMM). In this study, polysulfone (PSf)/ACNF mixed matrix membranes was fabricated using dry/wet inversion technique. The effect of PSf concentration and ACNF loading on the performance of mixed matrix membrane in terms of permeability and selectivity of CO2/CH4 gas separation was observed. The fabricated flat sheet mixed matrix membranes were characterized using Fourier Transform Infrared Spectroscopy (FT-IR) and Scanning Electron Microscopy (SEM) analysis. From the SEM observations, it shows that sponge like structures images were observed upon the addition of ACNFs in the PSf/ACNF membranes was slowly decreased due to increasing weight percentage of ACNF. FT-IR result indicating the presence of carboxyl group in MMM at wavelength 1750 cm-1. Meanwhile, the MMMs were further tested to pure permeation test using pure CO2 and CH4 gas, the CO2 permeance improved and the selectivity of CO2/CH4 increased after the addition of ACNFs.
Microfiltration Membrane Assisted CO2 Diffuser for Algae Cultivation
Authors: Muhammad Idris Lutfi U. A. , Hizam S. M. , Lau K. S. , Md Nordin N. A. H. , Bilad M. R. , Putra Z. A. , Wirzal M. D. H.
Published: September 2018

The aim of this paper is to cover on the feasibility of using algae as an alternative to capture CO2. As such, comparison between a membrane diffuser and a bubble diffuser in terms of its performance in the cultivation of algae has been made. This work utilized PVDF flat sheet membrane with only air and pure CO2 as the feed gas and the diffusion method used was compared between membrane diffuser and a bubble diffuser. In the experiment, the feed gas flows through the membrane diffuser in which the algae suspension utilized the CO2 for its growth. The biomass contents of four different samples have been determined using the dry weight of the algae suspension samples, which is obtained by drying the samples in an oven overnight at 105˚C. The algae suspension with the membrane diffuser was able to remove CO2 feasibly while showing better performance with respect to algae cultivation in comparison to the bubble diffuser. Results showed the maximum average biomass content of the samples that used membrane diffuser had higher value of 0.325 g/L when a 1:1 ratio of air and CO2 was used in the feed stream and 0.275 g/L when using pure air as the feed stream. Thus, it has been shown that membrane diffuser is better than a bubble diffuser owing to its larger effective surface area.
Pengurusan & Pentadbiran Guru Besar ke Arah Pencapaian Sekolah Ugama Teladan: Kajian Kes di Daerah Tutong, Brunei Darussalam
Authors: Zakaria Gamal Abdul Nasir , Nawi Aliff , Yusop Zatul Iradah
Published: September 2018

The purpose of this study is to identify the principals’ management and administration level and to discover the difficulties in management and administration encountered by the school authorities in the effort to qualify in achieving the exemplary school tittle among religious school in Tutong district, Brunei. 10 principals from the participating religious school were interviewed to collect comprehensive information. The data was then analyzed by using SPSS software to attain frequency, percentage and min score. Finding shows that the management level of religious school is in satisfactory level. The study also recognizes that there are a few difficulties that were encountered by the administers in the effort to achieve the exemplary school title. At the end of the study, a few suggestions were made to ensure that the management and administration process are performed more smoothly and thus will successfully achieve exemplary religious school title.
Secondary ion mass spectrometry for superconducting radiofrequency cavity materials
Authors: Tuggle Jay , Pudasaini Uttar , Stevie Fred A. , Kelley Michael J. , Palczewski Ari D. , Reece Charlie E.
Published: September 2018

Historically, many advances in superconducting radio frequency (SRF) cavities destined for use in advanced particle accelerators have come empirically, through the iterative procedure of modifying processing and then performance testing. However, material structure is directly responsible for performance. Understanding the link between processing, structure, and performance will streamline and accelerate the research process. In order to connect processing, structure, and performance, accurate and robust materials characterization methods are needed. Here, one such method, secondary ion mass spectrometry (SIMS), is discussed with focus on the analysis of SRF materials. In addition, several examples are presented, showing how SIMS is being used to further understanding of material-based SRF technologies.
Automatic classification of grouper species by their sounds using deep neural networks
Authors: Ibrahim Ali K. , Zhuang Hanqi , Chérubin Laurent M. , Schärer-Umpierre Michelle T. , Erdol Nurgun
Published: September 2018

In this paper, the effectiveness of deep learning for automatic classification of grouper species by their vocalizations has been investigated. In the proposed approach, wavelet denoising is used to reduce ambient ocean noise, and a deep neural network is then used to classify sounds generated by different species of groupers. Experimental results for four species of groupers show that the proposed approach achieves a classification accuracy of around 90% or above in all of the tested cases, a result that is significantly better than the one obtained by a previously reported method for automatic classification of grouper calls.
Magnetism and photo dual-controlled supramolecular assembly for suppression of tumor invasion and metastasis
Authors: Yu Qilin , Zhang Ying-Ming , Liu Yao-Hua , Xu Xun , Liu Yu
Published: September 2018

Tumor cell invasion and metastasis can be suppressed by (geo)magnetism- and photoresponsive supramolecular nanofibers.
Discovery and structural characterization of a therapeutic antibody against coxsackievirus A10
Authors: Zhu Rui , Xu Longfa , Zheng Qingbing , Cui Yanxiang , Li Shaowei , He Maozhou , Yin Zhichao , Liu Dongxiao , Li Shuxuan , Li Zizhen , Chen Zhenqin , Yu Hai , Que Yuqiong , Liu Che , Kong Zhibo , Zhang Jun , Baker Timothy S. , Yan Xiaodong , Hong Zhou Z. , Cheng Tong , Xia Ningshao
Published: September 2018

Isolation of the first neutralizing antibody of CVA10 and the mechanism underlying its potency against all three existing capsid forms.
Rapid eruption of the Columbia River flood basalt and correlation with the mid-Miocene climate optimum
Authors: Kasbohm Jennifer , Schoene Blair
Published: September 2018

U-Pb ages show Earth’s youngest flood basalt province erupted in 750 ka starting ~16.65 Ma during Miocene global warming.
Recent intensification of Amazon flooding extremes driven by strengthened Walker circulation
Authors: Barichivich Jonathan , Gloor Emanuel , Peylin Philippe , Brienen Roel J. W. , Schöngart Jochen , Espinoza Jhan Carlo , Pattnayak Kanhu C.
Published: September 2018

A recent increase in extreme flooding in Amazonia is linked to intensification of the atmospheric east-west Walker circulation.
The PTH/PTHrP-SIK3 pathway affects skeletogenesis through altered mTOR signaling
Authors: Csukasi Fabiana , Duran Ivan , Barad Maya , Barta Tomas , Gudernova Iva , Trantirek Lukas , Martin Jorge H. , Kuo Caroline Y. , Woods Jeremy , Lee Hane , Cohn Daniel H. , Krejci Pavel , Krakow Deborah
Published: September 2018

Disrupting the PTH/PTHrP-SIK3 pathway impairs degradation of DEPTOR, affects mTOR signaling, and leads to abnormalities in skeletal development.
Identifying and targeting residual leukemic cells
Authors: Chonghaile Tríona Ní
Published: September 2018

Targeting leukemia regenerating cells following chemotherapy can prevent relapse of the disease.
Attenuation of Influenza A Virus Disease Severity by Viral Coinfection in a Mouse Model
Authors: Gonzalez Andres J. , Ijezie Emmanuel C. , Balemba Onesmo B. , Miura Tanya A.
Published: September 2018

Viral infections in the respiratory tract can cause severe disease and are responsible for a majority of pediatric hospitalizations. Molecular diagnostics have revealed that approximately 20% of these patients are infected by more than one unrelated viral pathogen. To understand how viral coinfection affects disease severity, we inoculated mice with a mild viral pathogen (rhinovirus or murine coronavirus), followed 2 days later by a virulent viral pathogen (influenza A virus). This model demonstrated that rhinovirus can reduce the severity of influenza A virus, which corresponded with an early but controlled inflammatory response in the lungs and early clearance of influenza A virus. We further determined the dose and timing parameters that were important for effective disease attenuation and showed that influenza disease is also reduced by coinfection with a murine coronavirus. These findings demonstrate that coinfecting viruses can alter immune responses and pathogenesis in the respiratory tract.
First Identification and Genomic Characterization of a Porcine Sapelovirus from Corsica, France, 2017
Authors: Piorkowski Géraldine , Capai Lisandru , Falchi Alessandra , Casabianca François , Maestrini Oscar , Gallian Pierre , Barthélémy Karine , Py Odile , Charrel Rémi , de Lamballerie Xavier
Published: September 2018

We report the isolation and genomic characterization of a
Sapelovirus A
strain, or porcine sapelovirus (PSV), from a diarrheic Corsican piglet in France. It shares 87% nucleotide identity with a 2014 German isolate.
Targeting glucose control in preterm infants: pilot studies of continuous glucose monitoring
Authors: Thomson Lynn , Elleri Daniela , Bond Simon , Howlett James , Dunger David B , Beardsall Kathryn
Published: September 2018

Objective

Hyperglycaemia is common in very preterm infants and is associated with adverse outcomes. Preventing hyperglycaemia without increasing the risk of hypoglycaemia is difficult. Real time tracking with continuous glucose monitors (CGM) may improve glucose control. We assessed the feasibility and safety of CGM to target glucose control in preterm infants, to inform a randomised controlled trial (RCT).

Design

We performed a single centre study in very preterm infants during the first week of life. Accuracy was assessed by comparison of CGM with blood glucose levels (n=20 infants). In a separate pilot study of efficacy (n=20), real-time CGM combined with a paper guideline to target glucose control (2.6–10 mmol/L) was compared with standard neonatal care (masked CGM). Questionnaires were used to assess staff acceptability.

Results

No concerns were raised about infection or skin integrity at sensor site. The sensor performed well compared with point-of-care blood glucose measurements, mean bias of −0.27 (95% CI −0.35 to −0.19). Per cent time in target range (sensor glucose 2.6–10 mmol/L) was greater with CGM than POC (77% vs 59%, respectively) and per cent time sensor glucose >10 mmol/L was less with CGM than POC (24% vs 40%, respectively). The CGM also detected clinically unsuspected episodes of hypoglycaemia. Staff reported that the use of the CGM positively improved clinical care.

Conclusions

This study suggests that CGM has sufficient accuracy and utility in preterm infants to warrant formal testing in a RCT.
3D airway model to assess airway dead space
Authors: Nieves Ashley , Cozzo Ashley , Kosoff Zora , Traube Chani , Groves Alan M
Published: September 2018

High flow therapy works partly by washout of airway dead space, the volume of which has not been quantified in newborns. This observational study aimed to quantify airway dead space in infants and to compare efficacy of washout between high flow devices in three-dimensional (3D) printed airway models of infants weighing 2.5–3.8 kg. Nasopharyngeal airway dead space volume was 1.5–2.0 mL/kg in newborns. A single cannula device produced lower carbon dioxide (CO2) levels than a dual cannula device (33.7, 31.2, 23.1, 15.9, 10.9 and 6.3 mm Hg vs 36.8, 35.5, 32.1, 26.8, 23.1 and 18.8 mm Hg at flow rates of 1, 2, 3, 4, 6 and 8 L/min, respectively; p<0.0001 at all flow rates). Airway pressure was 1 mm Hg at all flow rates with the single cannula but increased at higher flow rates with the dual cannula.

Relative nasopharyngeal airway dead space volume is increased in newborns. In 3D-printed airway models, a single cannula high flow device produces improved CO2 washout with lower airway pressure.
MRI SPACE sequence confirmation of occluded MCA M2 dissection stump masquerading as a ruptured MCA aneurysm
Authors: Khattar Nicolas K , White Andrew C , Adams Shawn W , Aljuboori Zaid S , Wilder Michael J , Downs Richard K , James Robert F
Published: September 2018

Intracranial vascular pathologies often have overlapping clinical presentations. Dissected vessel occlusions and bifurcation aneurysms can appear similar on pretherapeutic imaging. The medical management of these two entities is drastically different. The patient is a 51-year-old man who presented with severe, sudden-onset headache. Initial presentation was consistent with a ruptured middle cerebral artery (MCA) aneurysm and surgical clipping was recommended. However, further review of radiographic findings could not definitively differentiate an aneurysmal origin of the symptoms as opposed to intracranial dissection followed by occlusion of the M2 branch of the MCA. MRI sampling perfection with application optimised contrasts using different flip angle evolution (SPACE) was performed and showed thin flow signalling distal to the dissected vessel stump confirming the diagnosis. Accurate diagnosis is a crucial step in directing treatment for intracranial vascular lesions. MRI SPACE is a simple tool in the diagnostic armamentarium to adequately direct treatment and avoid the potential for unnecessary interventions.
87-year-old woman with improved pulmonary function following accidental long-term inhalation therapy with dabigatran
Authors: Pönitz Volker , Evensen Karl Jakob
Published: September 2018

Accidental long-term dabigatran etexilate inhalation was associated with subtherapeutic dabigatran serum concentrations in an elderly female patient with restrictive lung disease. A significant improvement in her pulmonary function was noted without other therapy directed towards her bronchopulmonary disease.
Dental management of a patient with 22q11.2 deletion syndrome (22q11.2DS)
Authors: AlQarni Mohammed Ali , Alharbi Adel , Merdad Leena
Published: September 2018

22q11.2 deletion syndrome (22q11.2DS) is one of the most common microdeletion syndromes, with an incidence of approximately 1/2000–1/4000 live births; it is thought to be mainly attributable to a de novo deletion. The clinical phenotype of this syndrome is highly variable. Certain craniofacial and oral features are common to most patients with 22q11.2DS, including a high prevalence of dental caries; abnormalities of tooth shape, eruption and number; and enamel defects such as hypomineralisation and hypoplasia. This report focuses on the dental features and management of an 8-year-old boy with 22q11.2DS. Dental treatments were carried out under general anaesthesia. In summary, facial dysmorphism and common dental manifestations are typically noticeable in patients with this syndrome. Therefore, dentists need to be aware of the dental features of this condition in order to refer them to the adequate specialists. Cooperation among and experience with different specialties are mandatory to improve quality of life for patients with 22q11.2DS.
A rare cause of ascites in a renal transplant recipient
Authors: Kasinadhuni Ganesh , Sethi Jasmine , Krishnappa Darshan , Sharma Yash Paul
Published: September 2018

Thirty-five-year-old man, underwent renal transplantation 4 years back and was doing well. He now presented with complaints of ascites with engorged neck veins and dyspnoea on exertion for last 6 months. Examination showed elevated jugular venous pressure with two prominent descents, high pitched diastolic heart sound (pericardial knock). Echocardiography showed characteristic features of thickened pericardium, septal bounce, expiratory flow reversal in hepatic veins and phasic variation of mitral inflow, suggestive of constrictive pericarditis. The patient was started on empirical antitubercular therapy and diuretics. The patient symptomatically improved, but in view of persisting constrictive physiology he was planned for pericardiectomy.
Prescribing high-intensity interval exercise by RPE in individuals with type 2 diabetes: metabolic and hemodynamic responses
Authors: Viana Ariane Aparecida , Fernandes Bianca , Alvarez Cristian , Guimarães Guilherme Veiga , Ciolac Emmanuel Gomes
Published: September 2018

We tested the hypothesis that rating of perceived exertion (RPE) is a tool as efficient as the heart rate (HR) response to the cardiopulmonary exercise test (CPX) for prescribing and self-regulating high-intensity interval exercise (HIIE), and that metabolic and hemodynamic response to HIIE is superior than to continuous moderate-intensity exercise (MICE) in individuals with type 2 diabetes mellitus (T2DM). Eleven participants (age = 52.3 ± 3 years) underwent HIIE prescribed and self-regulated by RPE (HIIERPE; 25 min), HIIE prescribed and regulated by an individual’s HR response to CPX (HIIEHR; 25 min), MICE prescribed and self-regulated by RPE (30 min) and control (30 min of seated resting) intervention in random order. HR, blood pressure (BP), capillary glucose, endothelial reactivity, and carotid-femoral pulse wave velocity were assessed before, immediately after, and 45 min after each intervention. Exercise HR, speed, and distance were measured during exercise sessions. Twenty-four-hour ambulatory BP was measured after each intervention. Exercise HR, speed, and distance were similar between HIIERPE and HIIEHR. BP response was not different among HIIERPE, HIIEHR, and MICE. Capillary glycaemia reduction was greater (P < 0.05) after HIIERPE (48.6 ± 9.6 mg/dL) and HIIEHR (47.2 ± 9.5 mg/dL) than MICE (29.5 ± 11.5 mg/dL). Reduction (P < 0.05) in 24-h (6.7 ± 2.2 mm Hg) and tendency toward reduction (P = 0.06) in daytime systolic (7.0 ± 2.5 mm Hg) ambulatory BP were found only after HIIERPE. These results suggest that HIIE is superior to MICE for reducing glycaemia and ambulatory BP, and that the 6–20 RPE scale is a useful tool for prescribing and self-regulating HIIE in individuals with T2DM.
Orthogonal-state-based and semi-quantum protocols for quantum private comparison in noisy environment
Authors: Thapliyal Kishore , Sharma Rishi Dutt , Pathak Anirban
Published: September 2018

Private comparison is a primitive for many cryptographic tasks, and recently several schemes for the quantum private comparison (QPC) have been proposed, where two users can compare the equality of their secrets with the help of a semi-honest third party (TP) without knowing each other’s secret and without disclosing the same to the TP. In the existing schemes, secrecy is obtained by using conjugate coding, and considering all participants as quantum users who can perform measurement(s) and/or create states in basis other than computational basis. In contrast, here we propose two new protocols for QPC, first of which does not use conjugate coding (uses orthogonal states only) and the second one allows the users other than TP to be classical whose activities are restricted to either reflecting a quantum state or measuring it in computational basis. Further, the performance of the protocols is evaluated under various noise models.
Carbon-based materials for bipolar plates for low-temperatures PEM fuel cells — A review
Authors: Wlodarczyk Renata
Published: September 2018

The PEMFC (Polymer Exchange Membrane Fuel Cell) is one of the most researched generators in hydrogen technology. The PEMFCs offer low emissions, several applications in industry with high power density. The basic material for the construction of components in low-temperature fuel cells is carbon or its allotropic forms and carbon nanomaterials. Carbon materials are used to build diffusion layers of electrodes, as catalyst carriers, for the construction of covers/interconnectors and as fuel. In this work, the carbon materials used to build a single cell have been reviewed taking into account various methods of fabrication and modification of materials.
Solar-Assisted Heat Pump Drying of Coriander: An Experimental Investigation
Authors: Alishah Abbas , Kiamahalleh Mohammad Valizadeh , Yousefi Fereshteh , Emami Anita , Kiamahalleh Meisam Valizadeh
Published: September 2018

In this study, the solar-assisted heat pump dryer was designed, manufactured, tested and optimized for drying operations of coriander for its preservation. The heat of drying was mainly provided by a solar collector and a heat pump with two experimental modes of turned on and off. The air temperatures and velocity were identified as the critical drying variables. The responses of the experiments were evaluated in terms of coefficient of performance (COP), energy consumption and the specific moisture extraction rate (SMER). Dehumidification of coriander from the moisture contents of 0.9 to 0.1 kg/kg was considerable. The results demonstrated that utilizing heat pump noticeably decreases the drying time (down to [Formula: see text]25%), energy consumption (down to [Formula: see text]12%) and increases SMER (up to [Formula: see text]20%). The increasing of air flow rate and air temperature significantly led to decreasing the drying time and energy consumption, however, increasing the COP and SMER.
Five decades of settlement and subsidence
Authors: Edmonds Clive
Published: September 2018

During the late 1960s and 1970s consideration of land instability in Great Britain was dominated by coal mining-related problems. Subsequently, as the pace of development and infrastructure has increased, there has been a greater awareness regarding collapses due to mining for resources other than coal and also due to karstic features in soluble rocks. This has been highlighted by reference to national and regional studies. In addition, there has been an improvement in the number of recorded occurrences of sinkholes and crown holes. The hazard of ground collapse in certain geological settings, together with the size of collapses and resulting damage to development and infrastructure, has become more evident as case studies have been published. Whereas a range of subsidence triggers are evident, the principal causal agency is usually water from rainfall or leaking utilities. Wider-ranging studies, both in Britain and overseas, have identified ever broader causes of land instability, including those related to glacial and periglacial features, and also uncontrolled groundwater exploitation. This review provides a useful summary of land settlement and subsidence activity to warn practitioners where caution should be applied when carrying out ground investigations and providing design advice.
Relating Paths in Transition Systems
Authors: Dima Catalin , Maubert Bastien , Pinchinat Sophie
Published: September 2018

We revisit Janin and Walukiewicz’s classic result on the expressive completeness of the modal mu-calculus with respect to Monadic Second Order Logic (MSO), which is where the mu-calculus corresponds precisely to the fragment of MSO that is invariant under bisimulation. We show that adding binary relations over finite paths in the picture may alter the situation. We consider a general setting where finite paths of transition systems are linked by means of a fixed binary relation. This setting gives rise to natural extensions of MSO and the mu-calculus, that we call the MSO
with paths relation
and the
jumping mu-calculus
, the expressivities of which we aim at comparing. We first show that “bounded-memory” binary relations bring about no additional expressivity to either of the two logics, and thus preserve expressive completeness. In contrast, we show that for a natural, classic “infinite-memory” binary relation stemming from games with imperfect information, the existence of a winning strategy in such games, though expressible in the bisimulation-invariant fragment of MSO with paths relation, cannot be expressed in the jumping mu-calculus. Expressive completeness thus fails for this relation. These results crucially rely on our observation that the jumping mu-calculus has a tree automata counterpart: the
jumping tree automata
, hence the name of the jumping mu-calculus. We also prove that for
observable
winning conditions, the existence of winning strategies in games with imperfect information is expressible in the jumping mu-calculus. Finally, we derive from our main theorem that jumping automata cannot be projected, and ATL with imperfect information does not admit expansion laws.
Sprintz
Authors: Blalock Davis , Madden Samuel , Guttag John
Published: September 2018

Thanks to the rapid proliferation of connected devices, sensor-generated time series constitute a large and growing portion of the world's data. Often, this data is collected from distributed, resource-constrained devices and centralized at one or more servers. A key challenge in this setup is reducing the size of the transmitted data without sacrificing its quality. Lower quality reduces the data's utility, but smaller size enables both reduced network and storage costs at the servers and reduced power consumption in sensing devices. A natural solution is to compress the data at the sensing devices. Unfortunately, existing compression algorithms either violate the memory and latency constraints common for these devices or, as we show experimentally, perform poorly on sensor-generated time series.

We introduce a time series compression algorithm that achieves state-of-the-art compression ratios while requiring less than 1KB of memory and adding virtually no latency. This method is suitable not only for low-power devices collecting data, but also for servers storing and querying data; in the latter context, it can decompress at over 3GB/s in a single thread, even faster than many algorithms with much lower compression ratios. A key component of our method is a high-speed forecasting algorithm that can be trained online and significantly outperforms alternatives such as delta coding.

Extensive experiments on datasets from many domains show that these results hold not only for sensor data but also across a wide array of other time series.
FingerReader2.0
Authors: Boldu Roger , Dancu Alexandru , Matthies Denys J.C. , Buddhika Thisum , Siriwardhana Shamane , Nanayakkara Suranga
Published: September 2018

People with Visual Impairments (PVI) experience greater difficulties with daily tasks, such as supermarket shopping. Identifying and purchasing an item proves challenging for PVI. Using a user-centered design process, we understand the difficulties PVI encounter in their daily routines. Consequently, the previous FingerReader model was elevated to a new level. In contrast, FingerReader2.0 incorporates a highly integrated hardware design, as it is standalone, wearable, and not tethered to a computer. Software-wise, the prototype utilizes a deep learning system, relying on a hybrid, an on-board and a cloud-based model. The advanced design significantly extends the range of mobile assistive technology, particularly for shopping purposes. This paper presents the findings from interviews, several iterative studies, and a field study in supermarkets to demonstrate the FingerReader2.0's enhanced capabilities for those with varied levels of visual impairment.
Controlling Fine-Grain Sharing in Natural Language with a Virtual Assistant
Authors: Campagna Giovanni , Xu Silei , Ramesh Rakesh , Fischer Michael , Lam Monica S.
Published: September 2018

This paper proposes a novel approach to let consumers share data from their existing web accounts and devices easily, securely, and with fine granularity of control. Our proposal is to have our personal virtual assistant be responsible for sharing our digital assets. The owner can specify fine-grain access control in natural language; the virtual assistant executes access requests on behalf of the requesters and returns the results, if the requests conform to the owner's access control policies.

Specifically, we allow a virtual assistant to share any ThingTalk command--an event-driven task composed of skills drawn from Thingpedia, a crowdsourced repository with over 200 functions currently. Access control in natural language is translated into TACL, a formal language we introduce to let users express for whom, what, when, where, and how ThingTalk commands can be executed. TACL policies are in turn translated into SMT (Satisfiability Modulo Theories) formulas and enforced using a provably correct algorithm. Our Distributed ThingTalk Protocol lets users access their own and others' data through their own virtual assistant, while enabling sharing without disclosing information to a third party.

The proposed ideas have been incorporated and released in the open-source Almond virtual assistant. 18 of the 20 users in a study say that they like the concept proposed, and 14 like the prototype. We show that users are more willing to share their data given the ability to impose TACL constraints, that 90% of enforceable use cases suggested by 60 users are supported by TACL, and that static and dynamic conformance of policies can be enforced efficiently.
ParkLoc
Authors: Cherian Jim , Luo Jun , Ho Shen-Shyang
Published: September 2018

Locating a vehicle indoors (e.g., underground parking garages) has been a difficult problem to tackle, due to the unavailability of GPS and/or Wi-Fi signals. Current GPS-free indoor localization efforts often rely on infrastructure supports such as Wi-Fi or BLE beacons, whereas the smartphone-only proposals mostly require significant data collection and training efforts per garage. In this context, we propose ParkLoc, a novel lightweight smartphone-only solution for vehicular localization in GPS/Wi-Fi-deprived environments such as indoor parking garages. ParkLoc exploits the inherent planar graph structure of the navigable paths in parking facilities, in order to match a vehicle trajectory onto a sub-section of the map, by modeling these as sparse directed graphs. Exploiting an approximate graph matching method, ParkLoc is able to track a vehicle in real-time with a median error of 4.8m and localize a parked vehicle with a median error of 2m from the nearest parking space. Furthermore, ParkLoc adopts the popular GraphSLAM algorithm from robotics research; it learns the map graph from the observed trajectory graphs and a given set of bootstrap (seed) landmark nodes, in a semi-supervised manner. A key benefit of our approach is that ParkLoc works off-the-shelf without any expensive on-site training or sensor data collection per garage. A comprehensive evaluation of ParkLoc through extensive experiments performed in 4 different parking facilities reveals the promising performance of our graph-based approach for both localization and mapping.
HyRise
Authors: Elbakly Rizanne , Elhamshary Moustafa , Youssef Moustafa
Published: September 2018

Floor localization is an integral part of indoor localization systems that are deployed in any typical high-rise building. Nevertheless, while many efforts have been made to detect floor change events leveraging phone-embedded sensors, there are still a number of pitfalls that need to be overcome to provide robust and accurate localization in the 3D space.

In this paper, we present HyRise: a robust and ubiquitous probabilistic crowdsourcing-based floor determination system. HyRise is a hybrid system that combines the barometer sensor and the ubiquitous Wi-Fi access points installed in the building into a probabilistic framework to identify the user's floor. In particular, HyRise incorporates a discrete Markov localization algorithm where the motion model is based on the vertical transitions detected from the sampled pressure readings and the observation model is based on the overheard Wi-Fi access points (APs) to find the most probable floor of the user. HyRise also has provisions to handle practical deployment issues including handling the inherent drift in the barometer readings, the noisy wireless environment, heterogeneous devices, among others.

HyRise is implemented on Android phones and evaluated using three different testbeds: a campus building, a shopping mall, and a residential building with different floorplan layouts and APs densities. The results show that HyRise can identify the exact user's floor correctly in 93%, 92% and 77% of the cases for the campus building, the shopping mall, and the more challenging residential building; respectively. In addition, it can identify the floor with at most 1-floor error in 100% of the cases for all three testbeds. Moreover, the floor localization accuracy outperforms that achieved by other state-of-the-art techniques by at least 79% and up to 278%. This accuracy is achieved with no training overhead, is robust to the different user devices, and is consistent in buildings with different structures and APs densities.
Crowd-AI Camera Sensing in the Real World
Authors: Guo Anhong , Jain Anuraag , Ghose Shomiron , Laput Gierad , Harrison Chris , Bigham Jeffrey P.
Published: September 2018

Smart appliances with built-in cameras, such as the Nest Cam and Amazon Echo Look, are becoming pervasive. They hold the promise of bringing high fidelity, contextually rich sensing into our homes, workplaces and other environments. Despite recent and impressive advances, computer vision systems are still limited in the types of sensing questions they can answer, and more importantly, do not easily generalize across diverse human environments. In response, researchers have investigated hybrid crowd- and AI-powered methods that collect human labels to bootstrap automatic processes. However, deployments have been small and mostly confined to institutional settings, leaving open questions about the scalability and generality of the approach. In this work, we describe our iterative development of Zensors++, a full-stack crowd-AI camera-based sensing system that moves significantly beyond prior work in terms of scale, question diversity, accuracy, latency, and economic feasibility. We deployed Zensors++ in the wild, with real users, over many months and environments, generating 1.6 million answers for nearly 200 questions created by our participants, costing roughly 6/10ths of a cent per answer delivered. We share lessons learned, insights gleaned, and implications for future crowd-AI vision systems.
Beacon
Authors: Karkar Ravi , Kocielnik Rafal , Zhang Xiaoyi , Zia Jasmine , Ioannou George N. , Munson Sean A. , Fogarty James
Published: September 2018

Critical flicker frequency (CFF) is the minimum frequency at which a flickering light source appears fused to an observer. Measuring CFF can support early diagnosis of minimal hepatic encephalopathy (MHE), a condition affecting up to 80% of people with cirrhosis of the liver. However, adoption of CFF measurement in clinical practice has been hampered by the cost of a device for measuring CFF and the need for specialized training to administer the test. This paper presents Beacon, a portable, inexpensive device that enables people to measure their own critical flicker frequency. We adopt a mixed-methods approach to informing and evaluating the design of and potential opportunities for Beacon. We first report on a two-part formative study with 10 participants to evaluate the choice of certain parameters in the design of Beacon. We then report on a study of 41 healthy adults ranging from 18 to 99 years of age, finding that Beacon performs on par with Lafayette Flicker Fusion System, an established medical device, achieving a pearson correlation coefficient of 0.88. We finally report on a focus group with five hepatoligists who work with patients with cirrhosis of the liver, using our initial prototype development to examine their perspectives on potential opportunities and challenges in adoption of a device like Beacon. We discuss Beacon as an exploration of reframing critical flicker frequency measurement from a clinical screening tool into a self-administered self-tracking measure, thereby drawing upon and contributing to research in the health and personal informatics.
Al-light
Authors: Matsui Hidenori , Hashizume Takahiro , Yatani Koji
Published: September 2018

Inappropriate alcohol drinking may cause health and social problems. Although controlling the intake of alcohol is effective to solve the problem, it is laborious to track consumption manually. A system that automatically records the amount of alcohol consumption has a potential to improve behavior in drinking activities. Existing devices and systems support drinking activity detection and liquid intake estimation, but our target scenario requires the capability of determining the alcohol concentration of a beverage. We present Al-light, a smart ice cube to detect the alcohol concentration level of a beverage using an optical method. Al-light is the size of 31.9 x 38.6 x 52.6 mm and users can simply put it into a beverage for estimation. It embeds near infrared (1450 nm) and visible LEDs, and measures the magnitude of light absorption. Our device design integrates prior technology in a patent which exploits different light absorption properties between water and ethanol to determine alcohol concentration. Through our revisitation studies, we found that light at the wavelength of 1450 nm has strong distinguishability even with different types of commercially-available beverages. Our quantitative examinations on alcohol concentration estimation revealed that Al-light was able to achieve the estimation accuracy of approximately 2 % v/v with 13 commercially-available beverages. Although our current approach needs a regressor to be trained for a particular ambient light condition or the sensor to be calibrated using measurements with water, it does not require beverage-dependent models unlike prior work. We then discuss four applications our current prototype supports and future research directions.
Estimating the Physical Distance between Two Locations with Wi-Fi Received Signal Strength Information Using Obstacle-aware Approach
Authors: Nakatani Tomoya , Maekawa Takuya , Shirakawa Masumi , Hara Takahiro
Published: September 2018

This study presents a new method for estimating the physical distance between two locations using Wi-Fi signals from APs observed by Wi-Fi signal receivers such as smartphones. We assume that a Wi-Fi signal strength vector is observed at location A and another Wi-Fi signal strength vector is observed at location B. With these two Wi-Fi signal strength vectors, we attempt to estimate the physical distance between locations A and B. In this study, we estimate the physical distance based on supervised machine learning and do not use labeled training data collected in an environment of interest. Note that, because signal propagation is greatly affected by obstacles such as walls, precisely estimating the distance between locations A and B is difficult when there is a wall between locations A and B. Our method first estimates whether or not there is a wall between locations A and B focusing on differences in signal propagation properties between 2.4 GHz and 5 GHz signals, and then estimates the physical distance using a neural network depending on the presence of walls. Because our approach is based on Wi-Fi signal strengths and does not require a site survey in an environment of interest, we believe that various context-aware applications can be easily implemented based on the distance estimation technique such as low-cost indoor navigation, the analysis and discovery of communities and groups, and Wi-Fi geo-fencing. Our experiment revealed that the proposed method achieved an MAE of about 3-4 meters and the performance is almost identical to an environment-dependent method, which is trained on labeled data collected in the same environment.
Visual Attention-Based Access
Authors: Serim Bariş , Pfeuffer Ken , Gellersen Hans , Jacucci Giulio
Published: September 2018

During collaboration, individual users' capacity to maintain awareness, avoid duplicate work and prevent conflicts depends on the extent to which they are able to monitor the workspace. Existing access control models disregard this contextual information by managing access strictly based on who performs the action. As an alternative approach, we propose managing access by taking the visual attention of collaborators into account. For example, actions that require consensus can be limited to collaborators' joint attention, editing another user's personal document can require her visual supervision and private information can become unavailable when another user is looking. We prototyped visual attention-based access for 3 collaboration scenarios on a large vertical display using head orientation input as a proxy for attention. The prototype was deployed for an exploratory user study, where participants in pairs were tasked to assign visual attention-based access to various actions. The results reveal distinct motivations for their use such as preventing accidents, maintaining individual control and facilitating group awareness. Visual attention-based access has been perceived as more convenient but also less certain when compared to traditional access control. We conclude that visual attention-based access can be a useful addition to groupware to flexibly facilitate awareness and prevent conflicts.
RF-Based Fall Monitoring Using Convolutional Neural Networks
Authors: Tian Yonglong , Lee Guang-He , He Hao , Hsu Chen-Yu , Katabi Dina
Published: September 2018

Falls are the top reason for fatal and non-fatal injuries among seniors. Existing solutions are based on wearable fall-alert sensors, but medical research has shown that they are ineffective, mostly because seniors do not wear them. These revelations have led to new passive sensors that infer falls by analyzing Radio Frequency (RF) signals in homes. Seniors can go about their lives as usual without the need to wear any device. While passive monitoring has made major advances, current approaches still cannot deal with the complexities of real-world scenarios. They typically train and test their classifiers on the same people in the same environments, and cannot generalize to new people or new environments. Further, they cannot separate motions from different people and can easily miss a fall in the presence of other motions.

To overcome these limitations, we introduce Aryokee, an RF-based fall detection system that uses convolutional neural networks governed by a state machine. Aryokee works with new people and environments unseen in the training set. It also separates different sources of motion to increase robustness. Results from testing Aryokee with over 140 people performing 40 types of activities in 57 different environments show a recall of 94% and a precision of 92% in detecting falls.
Inferring Mobility Relationship via Graph Embedding
Authors: Yu Yanwei , Wang Hongjian , Li Zhenhui
Published: September 2018

Inferring social relationships from user location data has become increasingly important for real-world applications, such as recommendation, advertisement targeting, and transportation scheduling. Most existing mobility relationship measures are based on pairwise meeting frequency, that it, the more frequently two users meet (i.e., co-locate at the same time), the more likely that they are friends. However, such frequency-based methods suffer greatly from data sparsity challenge. Due to data collection limitation and bias in the real world (e.g., check-in data), the observed meeting events between two users might be very few. On the other hand, existing methods focus too much on the interactions between two users, but fail to incorporate the whole social network structure. For example, the relationship propagation is not well utilized in existing methods. In this paper, we propose to construct a user graph based on their spatial-temporal interactions and employ graph embedding technique to learn user representations from such a graph. The similarity measure of such representations can well describe mobility relationship and it is particularly useful to describe the similarity for user pairs with low or even zero meeting frequency. Furthermore, we introduce semantic information on meeting events by using point-of-interest (POI) categorical information. Additionally, when part of the social graph is available as friendship ground truth, we can easily encode such online social network information through a joint graph embedding. Experiments on two real-world datasets demonstrate the effectiveness of our proposed method.
BiLock
Authors: Zou Yongpan , Zhao Meng , Zhou Zimu , Lin Jiawei , Li Mo , Wu Kaishun
Published: September 2018

User authentication on smart devices is indispensable to keep data privacy and security. It is especially significant for emerging wearable devices such as smartwatches considering data sensitivity in them. However, conventional authentication methods are not applicable for wearables due to constraints of size and hardware, which makes present wearable devices lack convenient, secure and low-cost authentication schemes. To tackle this problem, we reveal a novel biometric authentication mechanism which makes use of sounds of human dental occlusion (i.e., tooth click). We demonstrate its feasibility by comprehensive measurement study, and design a prototype-BiLock with two Android platforms. Extensive real-world experiments have been conducted to evaluate the accuracy, robustness and security of BiLock in different environments. The results show that BiLock can achieve less than 5% average false reject rate and 0.95% average false accept rate even in a noisy environment. Comparative experiments also demonstrate that BiLock possesses advantages in robustness to noise and security against replay and observation attacks over existing voiceprinting schemes.