bluuebunny/crossref_metadata_2025 huggingface dataset:
Acupuncture for Fibromyalgia: An Open‐Label Pragmatic Study on Effects on Disease Severity, Neuropathic Pain Features, and Pain Catastrophizing
Authors: Di Carlo Marco , Beci Giacomo , Salaffi Fausto
Published: February 2020

The treatment of fibromyalgia syndrome (FMS) is still far from being optimally coded, and pharmacological strategies are often unsatisfactory. Acupuncture plays a role among nonpharmacological intervention approaches; however, there is still no clarity as to when to integrate it into therapy. The objective of this study is to explore the role of acupuncture, in terms of efficacy on main disease severity measures and pain features, in patients with nonresponsive disease, defining nonresponsive FMS characterized by a revised Fibromyalgia Impact Questionnaire (FIQ‐R) ≥39 and a Patient Health Questionnaire 15‐item (PHQ15) ≥5 despite optimal drug therapy. Patients were treated with weekly sessions, for a total of eight acupuncture sessions. At the baseline and at the end of the treatment cycle, a comprehensive clinical evaluation was carried out to evaluate improvements in terms of disease severity and impact on neuropathic pain features (measured with the painDETECT questionnaire (PDQ)) and pain catastrophizing (measured with the Pain Catastrophizing Scale (PCS)). At the end of the eight‐week treatment, patients experienced a significant improvement in all evaluated parameters (for FIQ‐R, PDQ, and PHQ15 p < 0.0001, for PCS p = 0.001). Of particular note is the effectiveness on manifestations that are difficult to treat such as neuropathic pain features and on negative psychological perceptions such as pain catastrophizing. It can be stated that acupuncture can be proposed also in phases of high severity of disease. Intervention with multimodal strategies, including acupuncture, could be of great benefit to patients.
Family Study Designs Informed by Tumor Heterogeneity and Multi-Cancer Pleiotropies: The Power of the Utah Population Database
Authors: Hanson Heidi A. , Leiser Claire L. , Madsen Michael J. , Gardner John , Knight Stacey , Cessna Melissa , Sweeney Carol , Doherty Jennifer A. , Smith Ken R. , Bernard Philip S. , Camp Nicola J.
Published: February 2020

Background:

Previously, family-based designs and high-risk pedigrees have illustrated value for the discovery of high- and intermediate-risk germline breast cancer susceptibility genes. However, genetic heterogeneity is a major obstacle hindering progress. New strategies and analytic approaches will be necessary to make further advances. One opportunity with the potential to address heterogeneity via improved characterization of disease is the growing availability of multisource databases. Specific to advances involving family-based designs are resources that include family structure, such as the Utah Population Database (UPDB). To illustrate the broad utility and potential power of multisource databases, we describe two different novel family-based approaches to reduce heterogeneity in the UPDB.

Methods:

Our first approach focuses on using pedigree-informed breast tumor phenotypes in gene mapping. Our second approach focuses on the identification of families with similar pleiotropies. We use a novel network-inspired clustering technique to explore multi-cancer signatures for high-risk breast cancer families.

Results:

Our first approach identifies a genome-wide significant breast cancer locus at 2q13 [P = 1.6 × 10−8, logarithm of the odds (LOD) equivalent 6.64]. In the region, IL1A and IL1B are of particular interest, key cytokine genes involved in inflammation. Our second approach identifies five multi-cancer risk patterns. These clusters include expected coaggregations (such as breast cancer with prostate cancer, ovarian cancer, and melanoma), and also identify novel patterns, including coaggregation with uterine, thyroid, and bladder cancers.

Conclusions:

Our results suggest pedigree-informed tumor phenotypes can map genes for breast cancer, and that various different cancer pleiotropies exist for high-risk breast cancer pedigrees.

Impact:

Both methods illustrate the potential for decreasing etiologic heterogeneity that large, population-based multisource databases can provide.

See all articles in this CEBP Focus section, “Modernizing Population Science.”
Long-term Consequences of Pelvic Irradiation: Toxicities, Challenges, and Therapeutic Opportunities with Pharmacologic Mitigators
Authors: Huh Jung Wook , Tanksley Jarred , Chino Junzo , Willett Christopher G. , Dewhirst Mark W.
Published: February 2020

A percentage of long-term cancer survivors who receive pelvic irradiation will develop treatment-related late effects, collectively termed pelvic radiation disease. Thus, there is a need to prevent or ameliorate treatment-related late effects in these patients. Modern radiotherapy methods can preferentially protect normal tissues from radiation toxicities to permit higher doses to targets. However, concerns about chronic small bowel toxicity, for example, still constrain the prescription dose. This provides strong rationale for considering adding pharmacologic mitigators. Implementation of modern targeted radiotherapy methods enables delivery of focused radiation to target volumes, while minimizing dose to normal tissues. In prostate cancer, these technical advances enabled safe radiation dose escalation and better local tumor control without increasing normal tissue complications. In other pelvic diseases, these new radiotherapy methods have not resulted in the low probability of normal tissue damage achieved with prostate radiotherapy. The persistence of toxicity provides rationale for pharmacologic mitigators. Several new agents could be readily tested in clinical trials because they are being or have been studied in human patients already. Although there are promising preclinical data supporting mitigators, no clinically proven options to treat or prevent pelvic radiation disease currently exist. This review highlights therapeutic options for prevention and/or treatment of pelvic radiation disease, using pharmacologic mitigators. Successful development of mitigators would reduce the number of survivors who suffer from these devastating consequences of pelvic radiotherapy. It is important to note that pharmacologic mitigators to ameliorate pelvic radiation disease may be applicable to other irradiated sites in which chronic toxicity impairs quality of life.
Quantitative Analysis of Left Ventricular Flow Dynamics in Latent Obstructive Hypertrophic Cardiomyopathy Using Vector Flow Mapping
Authors: Zhu Xiaoli , Xu Lei , Zuo Lei , Wang Jing , Wang Bo , Hu Rui , Zhou Mengyao , Zhao Xueli , Lei Changhui , Yang Qianli , Liu Liwen
Published: February 2020

Objectives: This study aimed to assess left ventricular (LV) energy loss (EL), circulation and vortex area using vector ﬂow mapping (VFM) in patients with latent obstructive hyper­trophic cardiomyopathy (LOHCM) and nonobstructive hypertrophic cardiomyopathy (NOHCM). Methods: Fourteen LOHCM patients, 10 NOHCM patients, and 11 healthy individuals were evaluated by transthoracic echocardiography. An offline VFM workstation was used to analyze the LV blood flow patterns and fluid dynamics. The hemodynamic parameters, EL, circulation, and vortex area in 7 cardiac phases were calculated and analyzed. Results: Compared with controls and NOHCM patients, EL was significantly higher in ­LOHCM patients during the rapid ejection phase, slow ejection (SE) phase, and isovolumetric relaxation phase (p < 0.05). LOHCM patients also showed increased circulation during SE compared to the other two groups (p < 0.05). The ability to discriminate between NOHCM and LOHCM was assessed by the area under the receiver-operating characteristic curve (AUC), and EL during SE was found to have the largest AUC (0.964); the best cutoff value was 6.34 J/m3/s, with a sensitivity of 100% and specificity of 80%. Conclusions: The VFM technique can detect abnormal changes of LV EL and vortex characteristics in hypertrophic cardiomyopathy patients. Compared with controls and NOHCM patients, the LOHCM patients have worse systolic and diastolic functions.
The Effect of Drug-Eluting Stents on Target Lesion Revascularization in Native Coronary Arteries: Results from the NORSTENT Randomized Study
Authors: Mølstad Per , Nordrehaug Jan Erik , Steigen Terje , Giil Lasse Melvaer , Wilsgaard Tom , Wiseth Rune , Bønaa Kaare H.
Published: February 2020

Background: The NORSTENT trial randomized 9,013 patients to percutaneous coronary intervention (PCI) with a drug-eluting stent (DES) or bare-metal stent (BMS) with 5-year follow-up. No difference was found in the composite primary outcome of death from any cause and nonfatal spontaneous myocardial infarction after a median of 5 years of follow-up. Secondary outcomes included repeat revascularizations, which were reduced by DES. We report the occurrence of target lesion revascularization (TLR) in time and across demographic and clinical subgroups in patients with lesions in native coronary arteries (n = 8,782). Results: Clinically driven TLR was performed on 488 (5.6%) of the 8,782 patients during 5 years of follow-up. Male gender, older age, visible thrombus in the lesion, and larger stent diameter were associated with less TLR; multivessel disease and longer stents were associated with a higher risk of TLR. There was a substantial and highly significant reduction of the risk of any TLR after 5 years in the DES group (hazard ratio [HR] 0.44, 95% confidence interval [CI] 0.36–0.52], p < 0.001). The effect of DES on TLR was limited in time to the first 2 years in the study with no evidence of a later rebound effect. The reduction in TLR after DES insertion was consistent across subgroups defined by gender, age, diabetes status, renal function, and lesion and stent characteristics. The number needed to treat with DES (vs. BMS) to prevent 1 TLR ranged from 4 to 110 across clinically relevant subgroups. Conclusion: DES have a time-limited effect on the rate of TLR, but with a substantial and highly significant reduction in the first 2 years after the procedure. This effect was found to be consistent across all important clinical subgroups.
Audiological Results with the SAMBA Audio Processor in Comparison to the Amadé for the Vibrant Soundbridge
Authors: Zimmermann Denise , Busch Susan , Lenarz Thomas , Maier Hannes
Published: February 2020

Background: Since its introduction in 1996, the Vibrant Soundbridge (VSB) has been upgraded with several improved generations of processors. As all systems are compatible, implanted patients can benefit from new technologies by upgrading to the newest processor type available. Objectives: The aim of this study was to compare the performance of the new (current) SAMBA processor with the previous Amadé processor. Methods: Twenty subjects monaurally implanted with a VSB and the Amadé processor tested the new SAMBA processor for a trial period of 4 weeks. We measured air conduction and bone conduction thresholds, unaided thresholds, and aided free field thresholds with both devices. Speech performance in quiet using the Freiburg monosyllabic test at 65 dB SPL (S0) was compared. The speech intelligibility in noise was determined using the Oldenburg sentence test measured in different listening conditions (S0NVSB/S0Ncontra) and microphone settings (omni/directional vs. adaptive directivity). Results: Word recognition scores in quiet with the SAMBA were still significantly lower than with the Amadé after the 4 weeks trial period but improved over the following year. Speech intelligibility with the SAMBA was significantly better than with the Amadé in omnidirectional mode and comparable with the Amadé in directional mode. Hence, the adaptive directionality provides an advantage in difficult hearing situations such as noisy environments. The subjective benefit was evaluated using the Abbreviated Profile of Hearing Aid Benefit and the Speech, Spatial and Qualities-C questionnaire. Results of the questionnaires demonstrate an overall higher level of satisfaction with the new SAMBA speech processor than with the older processor. Conclusion: The SAMBA enables similar speech perception in quiet but more flexible adaptation in acoustically challenging environments compared to the previous Amadé processor.
Nutritional Index as Prognostic Indicator in Patients Receiving Lenvatinib Treatment for Unresectable Hepatocellular Carcinoma
Authors: Hiraoka Atsushi , Kumada Takashi , Tada Toshifumi , Fukunishi Shinya , Atsukawa Masanori , Hirooka Masashi , Tsuji Kunihiko , Ishikawa Toru , Takaguchi Koichi , Kariyama Kazuya , Itobayashi Ei , Tajiri Kazuto , Shimada Noritomo , Shibata Hiroshi , Ochi Hironori , Kawata Kazuhito , Toyoda Hidenori , Ohama Hideko , Tsutsui Akemi , Itokawa Norio , Hayama Korenobu , Arai Taeang , Imai Michitaka , Nakamura Shinichiro , Michitaka Kojiro , Hiasa Yoichi , Kudo Masatoshi ,   Real-Life Practice Experts for HCC (RELPEC) Study Group and HCC 48 Group
Published: February 2020

Background/Aim: Few studies have examined the details of nutritional status in patients with unresectable hepatocellular carcinoma (u-HCC) undergoing systemic chemotherapy with lenvatinib. We evaluated the prognostic/predictive value of nutritional status using Onodera’s prognostic nutritional index (O-PNI) for overall survival among patients with u-HCC treated with lenvatinib. Methods: Three-hundred and seventy-five u-HCC patients treated with lenvatinib were enrolled (median age 72 years; Child-Pugh class A/B/C: n = 312/60/3; BCLC stage A/B/C/D: n = 2/159/212/2). We examined median survival time (MST) and time to progression (TTP) in all patients (n = 375), prognosis according to the O-PNI (high/low: >40/≤40) in 298 patients with lymphocyte findings, and the prognostic/predictive values of Child-Pugh stage, albumin-bilirubin (ALBI)/modified ALBI (mALBI) grade, and O-PNI for Chemotherapy grade (OPNIC grade 1/2/3: O-PNI >40/≤40 to >36/≤36). Results: The MST and TTP were 16.6 and 8.0 months, respectively. The MST and TTP according to the O-PNI (>40/≤40) were “not reached” (NR)/12.4 months (p < 0.001) and 10.0/6.1 months (p = 0.012), respectively. There was a good correlation noted between ALBI score and O-PNI (r = −0.939, p < 0.001). The predictive value of the O-PNI for mALBI grade 2a was 36.0 (specificity/sensitivity = 0.894/0.942; area under the curve [AUC] = 0.978), while that for mALBI grade 1 was 39 (specificity/sensitivity = 0.920/0.929; AUC = 0.972), which was very similar to a high O-PNI. The MST analyzed with the OPNIC in the 298 patients was NR/16.2/10.4 months for OPNIC grade 1/2/3 (p < 0.001), respectively, and the c-index was 0.632, the same as that for mALBI grade (0.632), while that for Child-Pugh class was 0.571. Conclusions: OPNIC grading might have a potential for easy substitution of mALBI grading. A good nutritional status (OPNIC grade 1) or mALBI grade 1 is the best indication for lenvatinib use, while with an OPNIC grade 3, lenvatinib might be not suitable.
What Can Twitter Tell Us about Skin Cancer Communication and Prevention on Social Media?
Authors: Vasconcelos Silva Carina , Jayasinghe Dilki , Janda Monika
Published: February 2020

Background: Skin cancer places a substantial burden on the health system in Australia. The modernisation of skin cancer prevention interventions by using social media may enhance their contemporary reach and relevance, especially among the youth. This study aimed to analyse Twitter posts in Australia to establish a baseline of skin cancer and sun-related communication trends. Methods: Tweets posted over the summer of 2018/2019 relating to relevant keywords and hashtags such as “slipslopslap” and “sunscreen” were analysed using quantitative and qualitative methods. The number of tweets, related communication patterns, and possible factors for sudden changes in tweet volume were studied. Results: Results showed that Australians are using Twitter to communicate about their sun-related and skin cancer experiences and to share advice and information on this matter. Overall, Australians use Twitter more frequently to talk about sunscreen (number of tweets between December 2018 and February 2019 = 5,842) and/or skin cancer (n = 3,936), but not so often to communicate about other sun-protective behaviours (n = 1,972) or skin cancer prevention campaigns (n = 108). The number of tweets is greatly affected by the increase in temperature. Celebrities, non-health-related organisations with a high number of followers, and individuals sharing their own skin cancer experiences achieve a substantial number of likes and retweets and thus influence on Twitter regarding skin cancer-related communication. Conclusions: The results allow deeper understanding of important determinants for effective social media use for health promotion and public health messaging in the future. Linking tweets with temperature, sharing by celebrities or non-health-related organisations and individuals with a high following can all contribute to greater spread of skin cancer and sun-related messages.
Recent Epidemiological Status of Ocular and Other Major Complications Related to Diabetes Mellitus in Japan
Authors: Kume Atsuki , Kashiwagi Kenji
Published: February 2020

Purpose: To investigate the epidemiological status of diabetes mellitus (DM)-related complications in Japan. Methods: The subjects were 3.11 million Japanese individuals who were registered in the Japanese claim database between 2005 and 2014. Subjects with a diagnosis associated with codes related to DM and/or DM-related complications as classified by the International Classification of Diseases version 10 and those who were prescribed any therapeutic agents for DM were considered to have DM. The status of ocular, renal, and neural complications was investigated. Results: A total of 66,923 patients with DM were included. The prevalence of subjects with DM was 3.8% in 2005 and 4.2% in 2014. The most frequent complication was diabetic retinopathy (23.6%, 95% CI: 21.7–25.5%), followed by diabetic nephropathy (14.8%, 95% CI: 14.0–15.6%) and diabetic neuropathy (4.9%, 95% CI: 4.5–5.3%). Among the subjects with ocular complications, 1.8% had proliferative diabetic retinopathy, 1.1% had diabetic macular edema (DME), 0.3% had neovascular glaucoma, and 1.5% had vitreous hemorrhage. Only DME significantly increased during the study period. The frequencies of the ocular and neural complications significantly decreased, while that of renal complications significantly increased during the study period. Conclusions: Ocular complications were the most common DM-related major complications in Japan. Notably, DME significantly increased in recent years.
Mechanism of Drug-Eluting Absorbable Metal Scaffold Restenosis
Authors: Ueki Yasushi , Räber Lorenz , Otsuka Tatsuhiko , Rai Himanshu , Losdat Sylvain , Windecker Stephan , Garcia-Garcia Hector M. , Landmesser Ulf , Koolen Jacques , Byrne Robert , Haude Michael , Joner Michael
Published: February 2020

Background:

The pathomechanisms underlying restenosis of the bioabsorbable sirolimus-eluting metallic scaffold (Magmaris) remain unknown. Using serial optical coherence tomography, we investigated causes of restenosis, including the contribution of late scaffold recoil versus neointimal hyperplasia.

Methods:

Patients enrolled in BIOSOLVE-II undergoing serial angiography and optical coherence tomography (post-intervention and follow-up: 6 months and/or 1 year) were analyzed. Patients were divided into 2 groups according to angiographic in-scaffold late lumen loss (LLL) <0.5 or ≥0.5 mm. End points were late absolute scaffold recoil and neointimal hyperplasia area as assessed by optical coherence tomography.

Results:

Serial data were available for analysis from 70 patients (LLL <0.5 mm: n=41; LLL ≥0.5 mm: n=29). Patient and lesion characteristics were comparable, and there was no significant difference in mean and minimal scaffold area between groups at post-intervention. Late absolute scaffold recoil was less among patients with LLL <0.5 mm (0.53±0.68 mm
2
) compared with those with LLL ≥0.5 mm (1.48±1.20 mm
2
;
P
<0.001). Neointimal hyperplasia area was smaller among patients with LLL <0.5 mm at follow-up (1.47±0.33 mm
2
) compared with patients with LLL ≥0.5 mm (1.68±0.34 mm
2
;
P
=0.013). In a matched-frame analysis (post-intervention and follow-up), late absolute scaffold recoil varied according to the underlying plaque type (lipid: 0.63±1.23 mm
2
; calcified: 0.81±1.44 mm
2
; and fibrous: 1.20±1.52 mm
2
;
P
<0.001), while there was no difference with regards to neointimal hyperplasia area (
P
=0.132).

Conclusions:

In addition to neointimal hyperplasia, late scaffold recoil contributed significantly to LLL of sirolimus-eluting absorbable metal scaffolds. The extent of late scaffold recoil was dependent on the underlying plaque morphology and was the highest among fibrotic lesions.

Registration:

URL:
https://www.clinicaltrials.gov
. Unique identifier: NCT01960504.
The Spirit in Word and Sacrament
Authors: Augustine Daniela C.
Published: February 2020

This article offers a constructive exploration of Eastern Orthodox liturgical pneumatology’s potential contributions toward the development of Pentecostal liturgical theology. It highlights two main themes: the organic continuity between word and sacrament as a proclaimed and ‘choreographed’, communally-enacted theology; and the catechetical significance of ‘visualized theology’ or ‘theology in images’ within the context of worship in the Spirit, constituting the life of the church as a continual Pentecost.
‘One Lord, One Faith, One Baptism’?
Authors: Baker Josiah
Published: February 2020

The emerging ecumenical activities of Classical Pentecostals affect and are affected by the relations between Oneness and Trinitarian Pentecostals. The commitments of Trinitarian Pentecostals to Oneness Pentecostals could hinder their involvement in ecumenical contexts that reject Oneness Pentecostals, while their increasing Trinitarian commitments could strain their already tenuous relationship with Oneness Pentecostals. This article is a programmatic essay that explores the emerging tension through its focal point of baptism, an important subject in intra-Pentecostal and ecumenical discourse. The author unpacks the origins of the problem facing Trinitarian Pentecostals before articulating why baptism is the proper locus for beginning to resolve the tension. He argues that the tensions for Pentecostals caused by the doctrine of God are best resolved by the further development by Pentecostals of their Trinitarian theology. The author concludes with necessary steps to be taken in this doctrinal formulation within intra-Pentecostal and ecumenical contexts.
The genus Vitex (Lamiaceae) in the flora of Cameroon

Authors: MEERTS PIERRE
Published: February 2020

The revision of the genus Vitex L. in Cameroon is presented. Sixteen taxa are accepted in Cameroon (15 species, 1 variety). One new variety is described (V. gabunensis var. daubyi). Three species are new to the flora of the country (V. ciliata, V. gabunensis, V. oxycuspis). Five new synonyms are proposed. Lectotypes are designated for V. grandifolia, V. bipindensis and V. zenkeri. In the current state of knowledge, two taxa are endemic to Cameroon (V. lokundjensis, V. yaundensis) and one taxon is a near-endemic, just extending to Nigeria (V. bogalensis). Two names remain unplaced because no original material has been found.
Catalogue of Croatian Freshwater Rhodophytes

Authors: KOLETIĆ NIKOLA , ALEGRO ANTUN , RIMAC ANJA , VUKOVIĆ NINA , ŠEGOTA VEDRAN
Published: February 2020

This paper summarises all available data on the flora of freshwater rhodophytes in Croatia, comprising 18 species from 13 genera—Audouinella, Bangia, Batrachospermum, Chroodactylon, Compsopogon, Hildenbrandia, Lemanea, Paralemanea, Pneophyllum, Polysiphonia, Porphyridium, Sirodotia and Thorea. Presented data are mostly a result of a comprehensive survey undertaken from 2009 to 2019 and including more than 600 freshwater locations—channels, streams, rivers, natural and artificial lakes. Additionally, all available published historical data, dating from 1890 onwards, as well as herbarium material from the ZA collection was overviewed and included in this study.
A new species of Protium (Burseraceae) from the Pacific Coast of Costa Rica

Authors: DE OLIVEIRA PERDIZ RICARDO , DALY DOUGLAS C. , VICENTINI ALBERTO , FINE PAUL V.A.
Published: February 2020

Protium santamariae is described and illustrated. The new species is restricted to the Pacific Coast of Costa Rica but shares morphological similarities with two South American species, P. kleinii and P. krukoffii. We provide a description, a distribution map, notes on its taxonomy, and a key to distinguish it from morphologically similar species.
Two new species of Cosmolaelaps Berlese (Acari: Laelapidae) from Sri Lanka
Authors: JOHARCHI OMID , ERMILOV SERGEY G. , KHAUSTOV ALEXANDER A.
Published: February 2020

Two new species of mites in the genus Cosmolaelaps (Laelapidae) are described from specimens collected from soil-litter in Sri Lanka—C. ceylonensis sp. nov. and C. trichiurus sp. nov. The genus Cosmolaelaps is reported for the first time from Sri Lanka.
A review of the linyphiid spider genus Proislandiana Tanasevitch, 1985 with description of a new high mountainous species from Turkey and Armenia (Araneae: Linyphiidae)
Authors: DIMITROV DRAGOMIR
Published: February 2020

A new species of the hitherto monotypic spider genus Proislandiana Tanasevitch, 1985 is described from the high altitude belt of Ararat Mountain (Turkey) and Aragats Mountain (Armenia). The genus Proislandiana is reviewed, its taxonomic relationships to the other genera are discussed. The diagnoses of the genus and its type species are revised. The distribution and the zoogeography of the two known Proislandiana species are summarized and discussed.
Traffic Anomalies in Surveillance Videos: Recent Trends
Authors: Prasath V. , Deepak K. , Chandrakala S.
Published: February 2020

There is an increasing demand for automated traffic surveillance with a wide range of threats in road safety and less man power to monitor them. Especially, detecting anomalous behavior in traffic surveillance is challenging because of the presence of occlusion, weather conditions,
and pose variations. This paper reviews the recent trends on vision based traffic anomaly detection. Various features, modeling techniques and data sets used in traffic anomaly detection are reviewed.
Segmentation and Three Dimensional Visualization of Mandible Using Active Contour and Visualization Toolkit in Craniofacial Computed Tomography Images
Authors: Varghese Jithy , Singh Tripty , Bhat Venkatraman , Kuriakose Moni
Published: February 2020

Three-dimensional representation of facial bone surface is needed in the virtual surgical planning for orthognathic surgery. Segmentation of facial bone surface from computed tomography images is first step in developing the 3D model. This paper focuses on segmentation of mandible bone
using active contour segmentation of Insight Segmentation and Registration Toolkit library. The results are given as 3D stereo lithographic image. The result is compared with the ground truth image segmented by an expert radiologist. Various evaluation metrics are used for finding the segmentation
accuracy and the result has given segmentation accuracy of 97.50%. Therefore, this method can be used as an initial step in automatic cephalometric land marking, an important task in virtual surgical planning for orthognathic surgery.
An Innovative and Implementable Approach for Online Fake News Detection Through Machine Learning
Authors: Anushaya Prabha T. , Aisuwariya T. , Vamsee Krishna Kiran M. , Vasudevan Shriram K.
Published: February 2020

One should recollect the USA 2015 and 2016 U.S. presidential election cycle dealt with numerous scandals which were triggered by the forged news articles that blowout through the social media like Twitter and Facebook. When it was found that these articles were purposefully uploaded
for financial and political gain, it’s become evident that bogus news has to be identified and removed to prevent public from being deceived for someone’s personal gain. This study builds a supervised machine language model to detect the fake news articles published during 2015
and 2016 U.S. election cycle. The data set contains identical number of bogusand factual news. The standard set of machine learning algorithms like K-Nearest Neighbors, Support Vector Machine, Naive Bayes and Passive Aggressive Classifier are trained using either the title or the content
of the article. There results show that the PAC classifier produces the highest accuracy of 94.63% over the other three classifiers using diagram term frequency.
Smart-Farming Using Internet of Things
Authors: Verma Shivam Kumar , Rajesh M. , Vincent Rajiv
Published: February 2020

In India, 47% of people are involved in the agriculture sector. A large part of the population of India depends upon the agriculture. In this work, we assemble a smart farming field screening system that helps farmers to take information about their field in the sense soil moisture,
humidity and temperature of the environment. And it allows smart irrigation to the field and gives a better result for doing agriculture and provide better profit for good crop production. In our work, we can use a different type of sensors and some wireless technologies like the Internet
of things (IoT) and an android application to provide a smart platform to farmers to read data from the sensors with the help of microcontroller and giving instructions in term of the graphical interface. Hence, we can use an IoT platform that gives the primary thing to access anywhere by
using the internet. The Wireless sensor network consists of sensors like moisture, humidity and temperature, and Infrared sensor. Using Bluetooth and GSM module for the clustering with sensors and other microcontroller devices are connected to the solar panel or battery for the power supply.
In this paper, we design an IoT platform for doing farming in an efficient way. That helps the farmers for real-time monitoring regarding their fields.
Bimodal Emotion Recognition Using Audio and Facial Features
Authors: Poorna S. S. , Devika Nair S. , Narayan Arsha , Prasad Veena , Himaja Parsi Sai , Kamath Suraj S. , Nair G. J.
Published: February 2020

A multimodal emotion recognition system is proposed using speech and facial images. For this purpose a video database is developed, containing emotions in three affective states viz. anger, sad and happiness. The audio and the snapshots of facial expressions acquired from the videos
constituted the bimodal input for recognizing emotions. The spoken sentences in the database included text dependent as well as text independent sentences in Malayalam language. The audio features included short-time processing of speech to obtain: energy, zero crossing count, pitch and Mel
Frequency Cepstral Coefficients. For facial expressions, the landmark features of face: eyebrows, eyes and mouth, obtained using Viola Jones Algorithm is used. The supervised learning methods K-Nearest Neighbor and Artificial Neural Network are used for emotion analysis. The system performance
is evaluated for 3 cases viz. using audio based features and facial features separately and for both features taken together. Further, the effect of text dependent and text independent audio is also analyzed. The result of the analysis shows that text independent videos (utilizing both modalities)
using K-Nearest Neighbor (highest accuracy 82.78%) is found to be more effective in recognizing emotions from the database considered.
Diversity in Recommender Systems: A Closer Look
Authors: Likhitha T. , Pulari Sini Raj
Published: February 2020

Recommender Systems are widely used in numerous areas where there is enormous data. It helps to analyse such vague information and present to the end user in a simplified form. Although there are many objectives of the recommender systems like diversity, accuracy, serendipity, novelty
etc., accuracy is mostly used in many cases to generate an effective system. But system will provide more desirable result by including more objectives along with accuracy. In this paper we discuss about the objective diversity and explored the existing diversity techniques and its applications
in various fields.
Ontology Based Clinical Decision Support System for Geriatrics
Authors: Jha Balanand , Abhishek Kumar , Deepak Akshay , Upadhyay Shubhnkar , Singh Avadhesh
Published: February 2020

This paper discusses an ontology based clinical decision support system for the specialty of Geriatric Medicine. We created a domain level ontology based on Handbook of Geriatrics and then mapped it to an upper level Basic Formal Ontology. The decision support system has been developed
in Prolog. For accessing this ontology, we created an interactive web and android application which acts as a front-end to the system. Both applications are able to display the ontology structure and to predict the disease based on the symptom entered. We have uploaded our ontology to Bio-Portal,
which is one of the most comprehensive biomedical ontology repository. It can be accessed using the URL https://bioportal.bioontology.org/ontologies/G-O.
OBDMR: An Ontology-Based Data Model for Railways
Authors: Abhishek Kumar , Singh M. P. , Shukla Deepika , Gupta Sachin
Published: February 2020

The domain of the railway system is vast and complex since it includes several sub-domains hierarchy in it. These sub-domains include different branches of technology and operational hierarchy. Many types of research are running on and have happened in this vast domain along with different
technologies. Among all available technologies ontology is the single one which talks about semantics and thus supports the decision support system. This paper proposes an OBDMR model for railway systems to integrate the information at the knowledge level. The paper has used railML (version
2.2) as a data resource as railML covers all the aspects of the railway system. railML (Railway Mark-up Language) is an open, XML-based data exchange format for data interoperability of railway application. The proposed ontology adds the semantics to the given data and even allows to infer
new information from current data which XML cannot do. OBDMR is capable of taking decisions by automated reasoning using software agents. A generic model proposed in this paper satiates the standards and specifications of most countries’ railway systems. A use-case for Indian Railways
is discussed with some examples.
Priority Based Time-Division Multiple Access Algorithm for Medium Range Data Communication in Very High Frequency Radios
Authors: Giriraja C. V. , Chirag V. , Sudheendra C. , Bellur Samarth S. , Ramesh T. K. , Meera K. N.
Published: February 2020

In this paper, A novel and efficient time division multiple access (TDMA) algorithm for military last-mile data communication is designed. A dynamic slot assignment method coupled with an out-of-band control mechanism is used for the proposed design. In out-of-band, there is a well-defined
control segment along with the data segment. So, if a new node specifically a high priority node arrives at the network, it can signal its arrival by a response in the designated mini-slots and can also check the slot in the network, if no idle slots are available. Assigning priority to the
nodes would also ensure the delivery of the important messages first. Query messages are broadcasted by the Central node in order to detect new nodes. This reduces nodes working time and also ensures that the nodes don’t interrupt any existing communication. Furthermore, we describe
the feasibility and the reliability of this algorithm for military’s last-mile (end user) data communication.
Gray Level Co-Occurrence Matrix (GLCM) Parameters Analysis for Pyoderma Image Variants
Authors: Gupta Chaahat , Gondhi Naveen Kumar , Lehana Parveen Kumar
Published: February 2020

Analysis of different visual textures present in the given images is one of the important perspectives of human vision for objects segregation and identification. Texture-based features are widely used in medical diagnosis for informal prediction of dermatological diseases. Dermatological
diseases are the most universal diseases affecting all the living beings worldwide. Recent advancements in image processing have considerably improved the classification, identification, and treatment of various dermatological diseases. Present paper reports the results of Gray Level Co-occurrence
Matrix (GLCM) based texture analysis of skin diseases for parametric variations. The investigations were carried out using three Pyoderma variants (Boil, Carbuncle, and Impetigo Contagiosa) using GLCM. GLCM parameters (Energy, Correlation, Contrast, and Homogeneity) were extracted for each
colour component of the images taken for the investigation. Contrast, correlation, energy, and homogeneity represent the coarseness, linear dependency, textural uniformity, and pixel distribution of the texture, respectively. The analysis of the GLCM parameters and their histograms showed
that the said textural features are disease dependent. The approach may be used for the identification of dermatological diseases with satisfactory accuracy by employing a suitable machine learning algorithm.
Benefits of Early Detection of Alzheimer’s Disease—A Machine Learning with Image Processing Approach
Authors: Kurtakoti Abhijit U. , Hiremath Namrata D. , Patil Nirmala S. , Rane Aishwarya
Published: February 2020

Nervous system, being the most critical part of the human body has attracted many neuro-surgeons to diagnose the neurological diseases which are of primary concern. It’s been a challenge since many years. The recent report of the World Health Organization’s declares that
neurological syndrome, such as, Alzheimer’s disease, affects around one billion human beings. As a consequence of neurological disorder there have been around 6.8 million deaths globally. Along with being an irremediable Disease it is at the same time a progressive brain disease which
gradually diminishes the cognitive ability and affects memory which in turn affects routine life. It is prevalent cause of dementia among the elderly. This paper presents the work which assesses the efficacy of classification using unsupervised learning along with the image processing employed
on the images of Magnetic Resonance Imaging scans to calculate the probability of early detection of Alzheimer’s disease. The whole brain atrophy is considered as strong diagnostic test for Alzheimer’s disease. The paper expresses the image processing methods such as pixel thresholding
and unsupervised learning methods like k-means clustering, and a tailored algorithm incorporated for this specific case. The algorithm has been implemented using platforms, OpenCV and R libraries (for k means clustering), which expedites the effectiveness of the developed prototype
which can be used in the hospitals/clinics, reducing the need for any proprietary software. The final output of the prototype can assist the doctors to diagnose Alzheimer’s disease at an early stage. These results can be co-related with psychiatric results for better understanding and
treatment required for Alzheimer’s disease.
Chaos Based Network Initialization Approach for Feed Forward Artificial Neural Networks
Authors: Masoood Sarfaraz , Doja M. N. , Chandra Pravin
Published: February 2020

Weight initialization of sigmoidal feed forward artificial neural network (SFFANN) and the Convolutional neural networks (CNN) has been a known factor which affects the learning abilities of the neural network. The uniform random weight initialization approach has been quite often used
as the conventional network weight initial technique, due to its simplicity. However, various researches have shown that the random technique may not be the ideal choice of weight initialization for these neural networks. In this work, we analyze two separate chaotic functions and explore
the possibilities of these being used as the weight initialization methods against the conventional random initialization technique for SFANNs as well as for the CNNs. For the SFFANNs, this analysis were done over 8 function approximation problems chosen for experimentation. The mean test
error values along with a two sample t-test results strongly suggest that the Chebyshev chaotic map based weight initialization technique outperforms the conventional random initialization technique for most of the problems under consideration and hence may be used as an alternative
weight initialization technique for the SFFANNs. For the CNN experiment, the MNIST dataset was used for analyzing the performance of the random and the Chebyshev based initialization scheme. Results strongly support the use of the Chebyshev chaotic map based initialization scheme as an alternate
to the conventional random initialization.
Comparative Assessment of Image Captioning Models
Authors: Mayank  , Gondhi Naveen Kumar
Published: February 2020

Image Captioning is the combination of Computer Vision and Natural Language Processing (NLP) in which simple sentences have been automatically generated describing the content of the image. This paper presents the comparative analysis of different models used for the generation of descriptive
English captions for a given image. Feature extractions of the images are done using Convolutional Neural Networks (CNN). These features are then, passed onto Recurrent Neural Networks (RNN) or Long Short-term Memory (LSTM) to generate captions in English language. The evaluation metrics used
to appraise the conduct of the models are BLEU score, CIDEr and METEOR.
Speech Interface for Controlling Micro Air Vehicle
Authors: Lakshmi P. , Veena S. , Rahul D. K. , Lokesha H.
Published: February 2020

This paper focuses on the development of the speech interface for controlling a Micro Air Vehicle (MAV). A speech interface in such control applications will have two distinct modules. One is the Automatic Speech Recognition (ASR) module and the other is the Natural Language Processing
(NLP) module. The ASR is developed using the models built using CMU Sphinx toolkit. The NLP scheme is proposed and developed using Natural Language Toolkit (NLTK). Understanding of the speech is very important in such kind of control applications. The NLP outcome is used to invoke the Ground
Control Station (GCS) commands. The results are validated in a Flight Gear simulator using Mission Planner GCS configured for MAV.
Study on the anti-inflammatory and lipid-lowering activities of novel chimeric peptide
Authors: Liu Cong , Tan Meijun , Cao Kaixiang , Yan Jingwei , Hu Kuikui , Zhang Feng
Published: February 2020

Acne was treated by combining the N-terminal of HPA3NT3 (where Lys in position 13 was replaced by Asn) and the C-terminal antibacterial peptide HAG of GLP-1 (32–36) amide pentapeptide after amino replacement. The minimal inhibitory concentration (MIC) was measured using the broth
dilution method to evaluate HAG’s antibacterial activity. HAG’s cytotoxicity was determined using water-soluble tetrazolium salt (WST-1). Interleukin-8 (IL-8) expression in human immortalized keratinocytes (HaCaT) cells stimulated by Propionibacterium acnes and treated with
HAG was measured by Enzyme-linked immunosorbent assay (ELISA). IL-8 and toll-like receptor 2 (TLR2) expression was detected using real-time reverse transcriptase polymerase chain reaction (qRTPCR) to analyze HAG’s anti-inflammatory effect in vitro. The total RNA was extracted
using SiO2 nanoparticles. Oil red O staining was used to detect the intracellular lipid drop of Sebaceous Gland Cell Line (SZ95), and ELISA was used to detect triglyceride levels. Hematoxylin-eosin (HE) staining was used to evaluate ear edema induced by Propionibacterium acne
in mice. The MIC of HAG in Propionibacterium acnes was 6.3 μg/mL, and 50 μg/mL of HAG showed cytotoxicity. HAG significantly reduced TLR2 and IL-8 expression in HaCaT cells. Oil red O staining showed that the lipid distribution of HAG-treated SZ95 and triglyceride
secretion decreased. HAG reduced ear swelling induced by Propionibacterium acnes. HAG has anti-bacterial and anti-inflammatory effects, excellent hypolipidemic function, and low cytotoxicity. Further development of HAG could be a promising and effective reagent for acne therapy.
The influence of the Rubrene thickness on the performance of white organic light-emitting devices
Authors: Zhao Lina , Jiang Xin , Lang Jihui , Jiang Wenlong , Zhang Gang , Xue Chuang , Zheng Liumenghan , Zhao Shuang
Published: February 2020

A group of white OLEDs (organic light-emitting devices), were fabricated using the blue yellow complementary principle. Among them, MCP(1,3-Bis(carbazol-9-yl)benzene) was used as the main material for the blue light layer, FIrPic(Bis(3,5-difluoro)-2-(2-pyridyl)phenyl-(2-carboxypyridyl)iridium(III))
as the phosphorescent object material, and Rubrene(5,6,11,12-Tetraphenylnaphthacene) as the fluorescent material for the yellow light layer. The device structure is NPB(N,N′-Bis(naphthalen-1-yl)-N,N′-bis(phenyl)-benzidine) (20 nm)/Rubrene (0.5 nm)/MCP (3 nm)/MCP:
FIrPic (30 nm, 10%)/Rubrene (z nm)/TPBi(1,3,5-Tris(1-phenyl-1Hbenzimidazol-2-yl) benzene)(10 nm)/Alq3(20 nm/LiF (0.6 nm)/Al (100 nm). By adjusting the thickness of Rubrene, the structure of the device was optimized and the performance of the device was improved. When the thickness of
Rubrene was 0.5 nm, the performance of the device was the best, the maximum efficiency was 6.41 cd/A, the maximum luminance was 8344 cd/m2. When the driving voltage changed from 5 V to 14 V, the device changed from warm white light to cold white light.
Development of a Probabilistic Subfreezing Road Temperature Nowcast and Forecast Using Machine Learning
Authors: Handler Shawn L. , Reeves Heather D. , McGovern Amy
Published: February 2020

In this study, a machine learning algorithm for generating a gridded CONUS-wide probabilistic road temperature forecast is presented. A random forest is used to tie a combination of HRRR model surface variables and information about the geographic location and time of day per year to observed road temperatures. This approach differs from its predecessors in that road temperature is not deterministic (i.e., provides a forecast of a specific road temperature), but rather it is probabilistic, providing a 0%–100% probability that the road temperature is subfreezing. This approach can account for the varying controls on road temperature that are not easily known or able to be accounted for in physical models, such as amount of traffic, road composition, and differential shading by surrounding buildings and terrain. The algorithm is trained using road temperature observations from one winter season (October 2016–March 2017) and calibrated/evaluated using observations from the following winter season (October 2017–March 2018). Case-study analyses show the algorithm performs well for various scenarios and captures the temporal and spatial evolution of the probability of subfreezing roads reliably. Statistical evaluation for the predicted probabilities shows good skill as the mean area under the receiver operating characteristics curve is 0.96 and the Brier skill score is 0.66 for a 2-h forecast and only degrades slightly as lead time is increased. Additionally, the algorithm produces well-calibrated probabilities, and consistent discrimination between clearly above-freezing and subfreezing environments.