Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparative Study of Drug Susceptibility Testing Techniques for Identification of Drug Resistant TB in a Tertiary Care Centre, South India

India tops the global list for Drug resistant Tuberculosis, but inadequate and expensive laboratory culture techniques have led to delay in the diagnosis and treatment. We studied the potential of an alternative method which could be cost-effective by combining the drugs in the same tube for identification of drug resistance. Drug Susceptibility Test (DST) results of 1000 sputum samples are got from suspected TB patients against INH (isoniazid) and Rifampicin by two techniques: a) a modified technique with both drugs in the same MGIT tube and b) a standard technique with the antibiotics in separate MGIT tubes for the diagnosis of MDR-TB (Multidrug Resistant). 39 samples were contaminated and were excluded from final analysis. 198 were smear positives by the concentrated Ziehl-Neelsen’s staining method. 219 were found to be culture positive out of which 195 were identified as M. tuberculosis complex. 40 (20.5%) strains were identified as MDR-TB by the conventional method and 39 were picked up by the modified DST. INH and Rifampicin mono-resistance accounted for 32 (16.4%) and 4 (2%) respectively. 99% concordance was observed between the two tests in categorizing MDR-TB. Similarly modified technique with combination of the second line Antibiotics-Ofloxacin, Kanamycin and Capreomycin was applied on the identified MDR strains in a stepwise manner. 6 (15%) were identified as Pre-XDR strains and 2 (5%) were found to be XDR-TB strains. This study implies that combining drugs in the same tube may be an equivalent and possibly a cost-effective alternative which needs to be explored further.
Treatment of hypopharyngeal carcinoma complicated with diabetic nephropathy: a case report and literature review

For elderly cancer patients with diabetic nephropathy, severe renal insufficiency leads to a very high risk of chemotherapy. Physicians and pharmacists must consider both the benefits of cancer treatment and the impact of antineoplastic drugs on patients’ residual renal function, and choose appropriate chemotherapy regimens to balance the efficacy and safety of drugs. We report a case of a patient who presented with dysphagia and sore throat with serum creatinine of 169 µmol/L and fasting blood glucose of 7.9 mmol/L on admission. The main diagnosis was hypopharyngeal carcinoma with diabetic nephropathy. The clinical pharmacist reviewed the literature and analyzed the pharmacological and pharmacokinetic characteristics of anti-tumor drugs in patients, and adjusted the chemotherapy regimen and dose according to the renal function of patients. To the best of our knowledge, this is the first reported case of hypopharyngeal carcinoma with severe renal insufficiency treated successfully with multimodality therapy in China. The purpose of this case is to optimize the anti-tumor treatment regimen and drug dose adjustment of hypopharyngeal carcinoma with severe renal insufficiency, so as to provide a reference for clinicians and clinical pharmacists to use drugs rationally.
From manpower to motor vehicles; development of patient transport

Amac: Bu calismanin amaci, hastalarin antik caglardan gunumuze gecisini evrimsel bir bakis acisiyla incelemek ve gelisimini etkileyen faktorleri ortaya koymaktir. Yontem: Bu calisma, tarihsel yaslardan gunumuze hasta ulasimini arastirmak icin kapsamli bir derleme olarak gerceklestirildi ve 2016-2019 arasinda yapildi. Bu amacla, eski zamanlardan gunumuze kadar hasta ulasimina iliskin tarihsel metinlerden, makalelerden ve kitaplardan web sitelerine kanit parcalari topladik ve inceleme bulgulari kronolojik olarak degerlendirildi. Bulgular: Calismada antik cagdan yalnizca bir veriye ulasilabildi, bu ilk veri Makedonya krali savas direktiflerinde yer almaktaydi, ikincisi deve, at gibi hayvanlar kullaniyordu, ucuncusu litre, araba ve vagonlardi ve bundan sonra teknoloji hasta arabalar, trenler, tekneler ve nihayet nakliye icin kullanilmis kara ve hava ambulanslari gelistirilmistir. Sonuc: Bu gelismeler tiptaki ilerlemelere paralel olarak gerceklesmistir ve bu yontemlerin incelenmesi tip tarihinin bir baska yonunu de ortaya koymaktadir. Ornegin, hasta tasima yontemleri, toplumlarin hasta ve/veya yaralilara verdigi deger, hasta refahinin nasil saglandigi ve tibbi mudahalenin nerede ve hangi kosullar altinda gerceklestigi hakkinda bilgi saglamaktadir. Ek olarak, bu calisma ayni zamanda hangi yontemlerin hangi cografyalarda kullanildigini, hangi sartlar altinda tercih edildigini aciklamakta ve savas zamanlarinda veya hastanin ilerleyisinde ortaya cikan buyuk salginlarda tip biliminin seviyesine iliskin detaylari sunmaktadir. Ambulansin tarihi, insanin tarihini kesfetmemize ve ayrica hastalara yardimci olacak yeni fikirleri gelistirmemize yardimci olmaktadir.
A novel interval‐based approach for quantifying practical parameter identifiability of a lithium‐ion battery model

Practical identifiability of battery model parameters, on which both modeling accuracy and robustness rely, is considered as a very important prerequisite for advanced onboard monitoring and control of Lithium‐ion batteries. In this paper, a novel confidence‐interval‐based approach is proposed for the quantification and assessment of the practical identifiability of a widely used second order battery equivalent circuit model (ECM). This method utilizes profile likelihood and likelihood ratio subset statistic to calculate each parameter's confidence interval, based on which a normalized index is further derived for facilitating quantification and fast comparison of the identifiability degree among different parameters. Using this approach, the practical identifiability of the second order ECM under lab‐collected experimental data is successfully evaluated, and the influences of several real‐world factors are systematically examined through extensive simulations. The results show that the open circuit voltage and ohmic internal resistance have a much larger degree of identifiability in all the investigated conditions. Some practically useful insights on performing battery parameter identification are also provided.
“You Gotta Have a Plan so You Won’t Get Caught”: Managing the Risks of Street Tagging

ABSTRACT Exploring offender decision-making is important to understanding criminal behavior as well as assisting in the creation of criminal justice policy. We analyzed interviews with 25 active juvenile street taggers to identify the sanction avoidance strategies they used to minimize the risk of detection and apprehension by law enforcement and other social control agents. The data suggested that despite the risks associated with street tagging, participants engaged in planning prior to their offending and relied on a number of strategies to reduce the chance of detection and arrest. The findings also revealed that efforts to be invisible to social control agents were complicated by their desire for visibility for their tags. This study expands the existing body of literature by examining active juvenile street taggers and suggests the need for scholars to continue to study restrictive deterrence techniques for varying types of offenders.
A Neural Network Model for Efficient Antonymy-Synonymy Classification by Exploiting Co-occurrence Contexts and Word-Structure Patterns

: Antonymy and synonymy are basic semantic relations between words. Automatically distinguishing between antonymy and synonymy is an important task in natural language processing. This task is hard because antonyms and synonyms tend to occur in highly similar contexts. Recent studies often focus on exploiting dense-vector representations of words to deal with this problem. In this paper, we present a study on antonymy-synonymy discrimination for the Vietnamese language. We propose a deep neural network model (DVASNet) that can utilize not only embedding representations of words but also co-occurrence contexts and specific patterns of Vietnamese word structure. Our experimental results showed that the proposed method achieved significant improvements in comparison with a number of state-of-the-art methods by 14% to 17% in terms of F1 score for both benchmark datasets.
Free and Low-Cost Twitter Research Software Tools for Social Science

Twitter is an important object of research in social science studies, and the emergence of numerous Twitter software tools has provided researchers with the possibility of gaining insights into Twitter data; however, at the same time, early stage researchers may experience difficulties in selecting the most suitable tool for their own projects. Due to personal or institutional financial constraints, the purchase of commercial software is not a wise investment for all researchers. Hence, this article aims to provide a review of nine different free-of-charge and low-cost software tools for studying Twitter and highlights their advantages and disadvantages, in order to serve as a guide for social science scholars. This review is divided into two parts: background information and data retrieval features of the software tools, and their data analysis features. At the end of the review, several recommendations and suggestions are made for the use of these tools.
A Polynomial Kernel Induced Distance Metric to Improve Deep Transfer Learning for Fault Diagnosis of Machines

Deep transfer-learning-based diagnosis models are promising to apply diagnosis knowledge across related machines, but from which the collected data follow different distribution. To reduce the distribution discrepancy, Gaussian kernel induced maximum mean discrepancy (GK-MMD) is a widely used distance metric to impose constraints on the training of diagnosis models. However, the models using GK-MMD have three weaknesses: 1) GK-MMD may not accurately estimate distribution discrepancy because it ignores the high-order moment distances of data; 2) the time complexity of GK-MMD is high to require much computation cost; 3) the transfer performance of GK-MMD-based diagnosis models is sensitive to the selected kernel parameters. In order to overcome the weaknesses, a distance metric named polynomial kernel induced MMD (PK-MMD) is proposed in this article. Combined with PK-MMD, a diagnosis model is constructed to reuse diagnosis knowledge from one machine to the other. The proposed methods are verified by two transfer learning cases, in which the health states of locomotive bearings are identified with the help of data respectively from motor bearings and gearbox bearings in laboratories. The results show that PK-MMD enables to improve the inefficient computation of GK-MMD, and the PK-MMD-based diagnosis model presents better transfer results than other methods.
Analysis of Quality of Work Life Effect on Organizational Citizenship Behavior with Work Satisfaction as A Variable Intervening

This research analyzes the influence of quality of work life on organizational citizenship behavior with job satisfaction as an intervening variable. This type of quantitative study with Structural Equation Modeling (SEM) analysis tool with AMOS-20 (Analysis of Moment Structure) device. The sample in this study was 105 Regional Secretariat Officer of the Bireuen District government. The results showed that quality of work life has significant effect on job satisfaction and organizational citizenship behavior. Job satisfaction has significant effect on organizational citizenship behavior. Job satisfaction is a partial mediation of the influence between quality of work life on organizational citizenship behavior.
A new species of Kurixalus (Anura: Rhacophoridae) from northern Vietnam with comments on the biogeography of the genus

ABSTRACT We describe a new species of rhacophorid frogs from Nghe An Province in northern Vietnam based on morphological and molecular evidences. Morphologically, Kurixalus gracilloides sp. nov. is distinguished from its congeners by a combination of the following diagnostic characters: body size small (snout–vent length 27.9–31.2 mm in males); head width subequal to head length; snout rounded with no dermal projection; canthus rostralis distinct, curved; vomerine teeth present; single internal vocal sac; iris golden-brown; small nuptial pad in finger I; dorsal surfaces golden-brown with a saddle-shaped dark marking; large dark spots on ventral surfaces absent; dermal fringes along outer edge of limbs; conical dermal appendage at the heel; skin on dorsum rough; skin on throat and chest granular; finger webbing rudimentary and toe webbing moderately developed, webbing formula I 2–2½ II 1½–3 III 1¾–3½ IV 3–1½ V. The new species is separated from all other congeners by uncorrected genetic distances ranging from 5.4% to 12.7% based on mitochondrial 16S rRNA gene. Phylogenetic analyses of mtDNA suggest that the new species is nested within a clade of Taiwanese and Yunnan Kurixalus with strong support values. The new species is currently known only from secondary bamboo forest in Pu Mat National Park, northern Vietnam, at elevations of 150 m asl. We suggest the new species should be considered as Near Threatened (NT) following the IUCN’s Red List categories. http://www.zoobank.org/urn:lsid:zoobank.org:pub:C1BF843F-2F31-4CED-B1F9-13A9035C77C9
Social sustainability of tourism in Iceland: A qualitative inquiry

ABSTRACT Sustainability research in tourism increasingly focuses on social issues such as the relationship between resident quality of life and community resilience through adaptive capacity. This study of resident and tourism relations in Iceland contributes to this growing body of literature. The research was supported by the Icelandic Tourist Board to meet the need to monitor the social sustainability of tourism in Iceland. Observation in public spaces showed disruption in daily routines for residents as physical infrastructure filled with tourists and the activities of tourism enterprises. In-depth interviews revealed residents’ awareness of potential benefits and problems with tourism, but a positive experience of and attitude toward tourists. A concern for the well-being of tourists was a theme in the interviews. However, residents were critical of the tourism industry and tourism management in both the private and public sector and questioned the sustainability of tourism growth. This leads us to consider the concepts of quality of life and resilience and responsible tourism as aspects of how communities experience and cope with tourism. We conclude that social sustainability, understood as both procedural and substantive, is a useful concept in addressing issues in tourism development.
NFV Data Centers: A Systematic Review

Recently, the widespread use of Network Function Virtualization (NFV) has meant a significant shift in communication and network cloud-based services. NFV increases network function, allocation, and flexibility, for the implementation of new network services, The benefits from optimizing resource allocation in NFV data center include automation of the operational processes, reducing the operational efforts, and lowering capital costs. Despite being a hot topic, NFV data centers are still in their early stages. In this sense, there are some aspects involved in the current NFV implementations that required further investigation, such as performance evaluation and managemen. This paper presents an in-depth analysis of NFV applications in data center. Therefore, a Systematic Literature Review (SLR) was conducted aimed at studying and synthesizing the available works in the NFV state-of-the-art. Consequently, about 1,408 papers have been analyzed and filtered, evidencing a total of 65 relevant studies. This paper documents the relevance of the 65 papers, as well as provides an indepth insight into the primary open research questions concerning NFV architecture. In particular, highlighting the need for consolidating the integration of NFV in data centers by solving problems related to performance, dependability, resource allocation, cost, management, and resource interoperability. Based on the conducted SLR, several research gaps and open challenges have been identified, allowing the authors to provide new propositions and suggested future research avenues. Finally, the obtained results have shown that there is a strong need for further collaboration between academia and industry to conduct quality research and advance NFV practical implementations.
Nexus of Financial Development, Innovation for Green Growth in ASEAN Countries

Albeit economic growth of global economies is increasing, nexus of green economic growth, innovation, and financial development needs to be thoroughly understood to make prudent economic policies for sustainability. The research question intends to identify the green growth promoting policies and impact of innovation and financial systems on sustainable economic growth. Rationale for the research is to provide pragmatic evidences to build up economic systems that lead green growth under the emission control and abatement. Empirical approach is used to (i) estimate augmented-Green-Solow model for ASEAN countries (ii) EKC is also estimated with Generalized Method of Moments (GMM) estimation to reveal the impact of financial development, innovation, and trade openness using World Bank data from 1980 to 2014. The empirical results indicate, across estimation methods and specifications, a strong correlation of the innovation, financial development and CO2 emissions per capita for green growth. Further, increase of innovation and financial structure leads the economies to be sustainable with increase of abatement cost with technological adaptation, and human capital. The implications of the study are to deliberate on the determinants of green growth to promote sustainable development in the economies. Finally, the paper guides policymakers to reform financial and innovation systems to achieve advancement in green technologies adapting sustainable economic policies for green growth.
Findings of an Audit of Music Therapy Referrals in a Specialist In-patient Setting for 16 Patients with Advancing Huntington's Disease

This article details the findings of an audit of referrals to a music therapy service in a specialist in-patient setting for 16 patients with advancing Huntington's Disease. Thirteen out of the sixteen patients were referred to music therapy; three were not referred. The findings indicated that the mean age at diagnosis of those referred was 45.62 years (SD = 10.73), and for those not referred 33.33 years (SD = 7.02). The mean age at time of referral was 60.54 years (SD = 9.35), and for those not referred 51 years (SD = 9). Comparisons between the mean ages of the two groups at time of referral revealed no significant difference (p = 0.13). However, those that were not referred were on average substantially younger than those referred. A strong relationship between age and age at diagnosis (r =0.85) was highlighted, and when a t-test to assess whether the average age at diagnosis was associated with whether a referral to music therapy was made or not during the time of the audit, the result was approaching significance (p = 0.08). Calculations of percentages resulted in identifying that patients were most likely to be referred due to a need for emotional expression (n = 10; 29%), and maintenance of communication skills and social relationships (n = 9; 26%). Infrequent referrals were made due to occupation (n = 5; 14%), physical presentation (n = 4; 11%), behaviour (n= 4; 11%), and cognitive factors (n = 3; 9%). The findings of the audit are discussed and compared with the literature to assist with understanding the role of music therapy with this population.
A Corpus Based Approach to Build Arabic Sentiment Lexicon

— Sentiment analysis is an application of artificial intelligence that determines the sentiment associated sentiment with a piece of text. It provides an easy alternative to a brand or company to receive customers' opinions about its products through user generated contents such as social media posts. Training a machine learning model for sentiment analysis requires the availability of resources such as labeled corpora and sentiment lexicons. While such resources are easily available for English, it is hard to find them for other languages such as Arabic. The aim of this research is to build an Arabic sentiment lexicon using a corpus-based approach. Sentiment scores were propagated from a small, manually labeled, seed list to other terms in a term co-occurrence graph. To achieve this, we proposed a graph propagation algorithm and compared different similarity measures. The lexicon was evaluated using a manually annotated list of terms. The use of similarity measures depends on the fact that the words that are appearing in the same context will have similar polarity. The main contribution of the work comes from the empirical evaluation of different similarity to assign the best sentiment scores to terms in the co-occurrence graph.
Left ventricular myocardial deformation: a study on diastolic function in the Chinese male population and its relationship with fat distribution.

Background Obesity has become an epidemic in China with its increased prevalence, especially in the male population. Disparities in fat distribution rather than increasing body mass index (BMI) confer the risk of different diseases, including cardiac abnormalities. Therefore, early detection of cardiac abnormalities is important for treatment to reverse the progression to heart failure. Nowadays, strain analysis based on cardiac magnetic resonance (CMR) imaging has been established to assess myocardial function in diverse cardiac diseases. We aimed to assess the relationship between fat distribution and subclinical diastolic dysfunction in obese Chinese men assessed by deformation registration algorithm (DRA)-based myocardial strain rate (SR) analysis. Methods A total of 115 male participants with different BMI underwent CMR scanning using a 1.5T MAGNETOM Aera (Siemens Healthcare, Erlangen, Germany) and computed tomography (CT) scan. All the participants were enrolled from September 2017 to April 2018. They were classified into 3 groups according to their BMIs with 23 and 27.5 kg/m2 being the cutoff values. A Trufi-Strain prototype software (version 2.0, Siemens Healthcare, Erlangen, Germany) was used to quantify SR in both early and late diastole from CMR cine images. Ratios of early and late SRs were calculated. Areas of epicardial and pericardial adipose tissue (EAT and PAT) were measured on a single 4-chamber-view slice of cine images. Volumes of visceral and subcutaneous adipose tissue (VAT and SAT) were acquired semi-automatically from CT images using the dedicated software Cardiac Risk2.0 (Siemens Healthcare). Waist and hip circumferences were manually measured (WC and HC). Analysis of variance or nonparametric tests, along with correlation and stepwise multivariate regression analysis models, was applied for statistical analysis. Results Peak late diastolic SRs were higher in obese men compared with their lean counterparts [-36.25±10.46 vs. -29.46±8.17, 66.97±18.58 vs. 45.62 (42.44, 55.96), and 56.81±15.07 vs. 41.40±6.41 for radial, circumferential, and longitudinal SRs, respectively; P<0.05]. All SR ratios in the obese subgroups were lower than those of lean men (3.12±1.14 vs. 4.63±1.24, 2.12±0.58 vs. 2.96±0.62 and 1.63±0.50 vs. 2.20±0.63 for radial, circumferential, and longitudinal directions, respectively; P<0.05). EAT was a significant predictor of diastolic function assessed by radial and circumferential SR ratios (β=-0.439 and -0.337 respectively; all P<0.001), while VAT was a significant predictor of circumferential and longitudinal SR ratios (β=-0.216 and -0.355, respectively, P<0.05). Conclusions Decreased LV diastolic function assessed by DRA-based SR analysis in obesity is associated with fat distribution. Furthermore, EAT and VAT might be better predictors of a decrease of diastolic function in obese Chinese men than BMI.