Miracle-dz/UniFAR-FTUs huggingface dataset:
Determination of Capsular Serotypes, Antibiotic Susceptibility Pattern, and Molecular Mechanism of Erythromycin Resistance among Clinical Isolates of Group B Streptococcus in Isfahan, Iran

Background: Documented streptococcal resistance to erythromycin has recently been raised. The aim of this study is to identify the molecular mechanism of erythromycin resistance among group B Streptococcus (GBS) strains and to correlate with the clinical origin of strains. Materials and Methods: A total number of 134 colonizing (n = 36), invasive (n = 36), noninvasive (n = 46), and asymptomatic (n = 16) GBS isolates were characterized by the detection of dltS gene, capsular serotyping, antibiotic susceptibility profiles using disc diffusion method, and screening of the ermB, ermTR, and mefA resistance genes. Results: The distribution of capsular serotypes was as follow: serotype III (24.6%), Ia (21.6%), V (17.9%), Ib (14.9%), II (8.9%), IV (8.9%), VI (1.5%), and VII (1.5%). From 134 GBS isolates, 51 (38%) isolates were resistant to erythromycin. The constitutive macrolide lincosamide streptogrmin B (MLSB) was the most common resistance phenotype (62.7%), followed by inducible MLSB (27.4%) and M phenotype (9.8%). Erythromycin resistance rate was higher among asymptomatic GBS strains (13/16, 81.2%). Serotype III was the most prevalent type among resistant isolates (41.1%). The ermB gene highly distributed among resistant strains (64.7%), followed by ermTR (21.5%) and mefA (9.8%). The ermB gene was related to constitutive MLSB phenotype (84.3%, P < 0.05) and serotypes III (61.9%), Ib (87.5%), and V (83.3%). All M phenotype strains harbored mefA gene and were in association with serotype Ia (90%). Conclusion: The current study suggests that ribosomal modification with erm genes is the main mechanism of erythromycin resistance. Because of relatively high prevalence of erythromycin resistance, double disc test highly recommended for GBS disease treatment and intrapartum prophylaxis among penicillin intolerant patients in our region.
Effect of deprivation and ethnicity on primary macula-on retinal detachment repair success rate and clinical outcomes: A study of 568 patients

Purpose Socio-economic deprivation and ethnic variation have been frequently linked to poorer health outcomes. We collected a large series of primary macula-on rhegmatogenous retinal detachment (RRD) cases and analysed the effect of socio-economic deprivation and ethnicity on both six-month retinal re-detachment rate and visual outcomes. Materials and methods Retrospective consecutive case series of 568 patients attending Birmingham and Midlands Eye Centre from January 2017–2020. Multiple Indices of Deprivation (IMD) deciles were used for deprivation status and split to two groups: IMD-A (Decile 1–5) and IMD-B (Decile 6–10). The two largest subgroups of ethnicities were compared, White and South Asians (SA). Results We report an overall retinal re-detachment rate of 8.5%. IMD-A re-detached significantly more than IMD-B (11.2% vs 6.0% respectively, p = 0.034). No statistical significance was found between White and SA re-detachment rate (9.1% and 5.6% respectively, p = 0.604). SA median age significantly lower at 49 years (IQR: 37–61) compared to White patients at 57 years (IQR: 50–65) (p = <0.001). IMD-A median age of 55 years (IQR: 46–64) was significantly lower to IMD-B median age of 58 years (IQR: 51–65) (p = 0.011). No differences in final visual outcomes were detected across all groups. Conclusion We demonstrated an increased retinal re-detachment rate in our more deprived patients according to IMD and a younger cohort of SA compared to White ethnicity. Further prospective studies are required to demonstrate the link between socio-economic deprivation and surgical success.
Reverse total shoulder arthroplasty (RTSA) versus open reduction and internal fixation (ORIF) for displaced three-part or four-part proximal humeral fractures: a systematic review and meta-analysis

Despite rapid medical technology development, various challenges exist in three- and four-part proximal humeral fracture (PHF) management. This condition has led to a notably increased use of the reverse total shoulder arthroplasty (RTSA); however, open reduction and internal fixation (ORIF) is still the most widely performed procedure. Thus, these two modalities are crucial and require further discussion. We aim to compare the outcomes of three- or four-part PHF surgeries using ORIF and RTSA based on direct/head-to-head comparative studies. We conducted a systematic review and meta-analysis based on the Cochrane handbook and PRISMA guidelines. We searched MEDLINE (PubMed), Embase (Ovid), and CENTRAL (Cochrane Library) from inception to October 2020. Our protocol was registered at PROSPERO (registration number CRD42020214681). We assessed the individual study risk of bias using ROB 2 and ROBINS-I tools, then appraised our evidence using the GRADE approach. Six head-to-head comparative studies were included, comprising one RCT and five retrospective case-control studies. We found that RTSA significantly improved forward flexion but was comparable to ORIF in abduction (p = 0.03 and p = 0.47, respectively) and more inferior in external rotation (p < 0.0001). Moreover, RTSA improved the overall Constant-Murley score, but the difference was not significant (p = 0.22). Interestingly, RTSA increased complications (by 42%) but reduced the revision surgery rates (by 63%) compared to ORIF (p = 0.04 and p = 0.02, respectively). RTSA is recommended to treat patients aged 65 years or older with a three- or four-part PHF. Compared to ORIF, RTSA resulted in better forward flexion and Constant-Murley score, equal abduction, less external rotation, increased complications but fewer revision surgeries. Cite this article: EFORT Open Rev 2021;6:941-955. DOI: 10.1302/2058-5241.6. 210049
Validation of Metacognitive Awareness Inventory from a Private Medical University in India

BACKGROUND: Metacognition is the awareness and the capability to regulate one's own thinking process. Metacognition is critical in medical education for clinical reasoning and management. Hence, the objective of this study is to evaluate the construct validity and reliability of the Metacognitive Awareness Inventory (MAI) among first-year medical and dental students, from a private medical university in India, using confirmatory analysis and internal consistency method. MATERIALS AND METHODS: This was a cross-sectional study using convenient sampling. Fifty-two-item MAI was administered to 933 first-year medical and dental students from a private medical university in India. Exploratory factor analysis (EFA), principal component analysis, Cronbach's α, and confirmatory factor analysis with global fit indices were performed. Structural equation modeling (SEM) was performed to evaluate the relationship between the structural path and factors using AMOS version 22. RESULTS: During EFA, 12 items with <0.40 factor loadings were trimmed sequentially. The remaining items with respective factors had a good internal consistency of ≥ 0.9. Comparative fit index (0.78), goodness-of-fit index (0.8), adjusted goodness of fit index (0.77), Tucker–Lewis index (0.7), standardized root mean square residual (0.06), and root mean square error of approximation (0.09) values showed that six-factor model fits to satisfactory. Pearson's correlation coefficient was found to be high between factors (>0.80). SEM for each item (observed) and factor (unobserved) illustrated the hypothesized model. CONCLUSION: The resultant 40-item model based on MAI designed by Schraw is a valid and reliable tool for assessing the metacognitive awareness of Indian students. Employing a valid and reliable tool in assessing the metacognitive awareness will help the academicians in incorporating appropriate curricular interventions.
Evaluation of smile characteristics of skeletal Class III compared to skeletal Class I female adults

OBJECTIVE: Esthetic enhancement plays an important role in orthodontic treatment. This study was conducted on females as most girls have their growth spurt at a younger age than boys do, so their demand to facial esthetics, especially those who have residual growth of mandible producing class III effect, requires full understanding to smile features helping in diagnosis and treatment planning for maximum patient satisfaction. MATERIALS AND METHODS: This study was conducted on 30 skeletal Class III and Class I female adults (18–30 years old) who were divided equally into two groups comprising 15 each. Two frontal digital photographs were taken for each subject, one at rest and the other in the posed smile position. Photographs were taken for each subject in the natural head position by a Canon EOS 1200 D camera set on a tripod at a distance of 1.5 m. The incisogingival height of the right maxillary central incisor was clinically measured using a vernier caliper to the nearest 0.1 mm. Photographs were uploaded on Photoshop software for standardization and then uploaded on the Digital Smile Design software (DSD) where the actual incisogingival height of the central incisor was used for automatic calibration. Esthetic components at rest and on smiling were measured for both groups; all linear variables were measured to the nearest 0.1 mm. RESULTS: Class III females tended to have wider smile widths, less gingival display, longer chin heights, shorter lower vertical dimensions, and a higher percentage of nonconsonant and flat smile arcs than Class I subjects. CONCLUSIONS: The components of the smile should be considered as a guide to help in planning and designing the mechanics during comprehensive orthodontic treatment.
No group differences in Traditional Economics Measures of loss aversion and framing effects in bipolar I disorder

Bipolar disorder (BD) is associated with impaired decision making, yet few studies have adopted paradigms from behavioral economics to decompose which, if any, aspects of decision making may be impacted. This may be particularly relevant for decision-making processes relevant to known difficulties with emotive dysfunction and corresponding reward dysregulation in BD. Participants with bipolar I disorder (BD; n = 44) and non-psychiatric healthy controls (CTL; n = 28) completed three well-validated behavioral economics decision making tasks via a remote-based survey, including loss aversion and framing effects, that examined sensitivity to probabilities and potential gains and losses in monetary and non-monetary domains. Consistent with past work, we found evidence of moderate loss aversion and framing effects across all participants. No group differences were found in any of the measures of loss aversion or framing effects. We report no group differences between bipolar and non-psychiatric groups with respect to loss aversion and framing effects using a remote-based survey approach. These results provide a framework future studies to explore similar tasks in clinical populations and suggest the context and degree to which decision making is altered in BD may be rooted in a more complex cognitive mechanism that warrants future research.
Developing management systems towards integrated manufacturing: a case study perspective

In manufacturing in recent years there has been a proliferation of management techniques to support the advances in manufacturing technologies. Different departments and functions often operate these management systems. Traditionally, systems such as quality management (ISO 9000 series), environmental management (ISO 14001), maintenance management (TPM and 5S), operations management (JIT and kaizen) and occupational health and safety management (BS 8800) are operated independently by quality, works engineering, maintenance and production departments. Clearly these management systems have to be brought together and combined in order for an organization to be able to develop an effective integrated manufacturing system. This paper outlines the need to bring these management systems together. It discusses a case study whereby such management systems, traditionally run by separate departments, have come together in order to contribute towards the development of an integrated manufacturing system.
The construction productivity debate and the measurement of service qualities

Since the 1960s, researchers have provided short-term and long-term explanations for low productivity growth in the construction industry. In retrospect, the main challenge appears to be the measurement of changes in heterogeneous input and output qualities. The aim here is to review earlier construction productivity research and to compare it with more recent approaches to quality measurement used when analysing services productivity, ultimately intending to provide guidance for using performance data from construction projects. Relying on the EU KLEMS database, industries with similar patterns of productivity growth are identified, primarily the business services industry. In services productivity analyses, the attempts to introduce output quality measures reflecting customer satisfaction are particularly interesting, as this creates a link to productivity effects on clients. A conclusion is that it should be possible to use the increasing volume of performance indicator data collected for construction project benchmarking for extending the range of output quality variables. However, resource constraints imply that it is infeasible to base industry productivity statistics on project level data reflecting customer satisfaction and customer productivity effects.
Forms of community participation and agencies’ role for the implementation of water‐induced disaster management: protecting and enhancing the poor

Water‐induced hazards and disasters are usually compounded by the mismanagement of local water resources. Since the community bears the burden of disaster and is the first responder to the event, it is imperative to build the capacity of the community to enhance their coping mechanism and resilience to prepare for and face the disaster. The best strategy for the immediate as well as the long term cost‐benefit and pro‐environmental implications that will ensure prevention, mitigation and rehabilitation of water‐induced disaster is to ensure strong community participation. This paper elucidates the different forms of community participation and their comparative advantages in a socio‐economic dimension, thereby poverty alleviation. Agencies’ roles are analyzed in response to community participation. It is hoped that these theoretical and practical tips will benefit both community and agencies to work out better performances in advance.
Machine learning caging order parameters in glasses

Kaihua Zhang, ∗ Xinyang Li, 3, ∗ Yuliang Jin, 3, † and Ying Jiang 4, ‡ School of Chemistry, Beihang University, Beijing 100191, China CAS Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China School of Physical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China Center of Soft Matter Physics and Its Applications, Beihang University, Beijing 100191, China
Identifying the Risks of Chronic Diseases Using BMI Trajectories

—Obesity is a major health problem, increasing the risk of various major chronic diseases, such as diabetes, cancer, and stroke. While the role of obesity identiﬁed by cross-sectional BMI recordings has been heavily studied, the role of BMI trajectories is much less explored. In this study, we use a machine learning approach to subtype individuals’ risk of developing 18 major chronic diseases by using their BMI trajectories extracted from a large and geographically diverse EHR dataset capturing the health status of around two million individuals for a period of six years. We deﬁne nine new interpretable and evidence-based variables based on the BMI trajectories to cluster the patients into subgroups using the k-means clustering method. We thoroughly review each clusters’ characteristics in terms of demographic, socioeconomic, and physiological measurement variables to specify the distinct properties of the patients in the clusters. In our experiments, direct relationship of obesity with diabetes, hypertension, Alzheimer’s, and dementia have been re-established and distinct clusters with speciﬁc characteristics for several of the chronic diseases have been found to be conforming or complementary to the existing body of knowledge.
Molecular Gas Properties and CO-to-H2 Conversion Factors in the Central Kiloparsec of NGC 3351

The CO-to-H2 conversion factor (α CO) is critical to studying molecular gas and star formation in galaxies. The value of α CO has been found to vary within and between galaxies, but the specific environmental conditions that cause these variations are not fully understood. Previous observations on ~kiloparsec scales revealed low values of α CO in the centers of some barred spiral galaxies, including NGC 3351. We present new Atacama Large Millimeter/submillimeter Array Band 3, 6, and 7 observations of 12CO, 13CO, and C18O lines on 100 pc scales in the inner ∼2 kpc of NGC 3351. Using multiline radiative transfer modeling and a Bayesian likelihood analysis, we infer the H2 density, kinetic temperature, CO column density per line width, and CO isotopologue abundances on a pixel-by-pixel basis. Our modeling implies the existence of a dominant gas component with a density of 2–3 × 103 cm−3 in the central ∼1 kpc and a high temperature of 30–60 K near the nucleus and near the contact points that connect to the bar-driven inflows. Assuming a CO/H2 abundance of 3 × 10−4, our analysis yields α CO ∼ 0.5–2.0 M ⊙ (K km s−1 pc2)−1 with a decreasing trend with galactocentric radius in the central ∼1 kpc. The inflows show a substantially lower α CO ≲ 0.1 M ⊙ (K km s−1 pc2)−1, likely due to lower optical depths caused by turbulence or shear in the inflows. Over the whole region, this gives an intensity-weighted α CO of ∼1.5 M ⊙ (K km s−1 pc2)−1, which is similar to previous dust-modeling-based results at kiloparsec scales. This suggests that low α CO on kiloparsec scales in the centers of some barred galaxies may be due to the contribution of low-optical-depth CO emission in bar-driven inflows.
Cross-lingual Adaption Model-Agnostic Meta-Learning for Natural Language Understanding

Meta learning with auxiliary languages has demonstrated promising improvements for cross-lingual natural language processing. However, previous studies sample the meta-training and meta-testing data from the same language, which limits the ability of the model for cross-lingual transfer. In this paper, we propose XLA-MAML, which performs direct cross-lingual adaption in the meta-learning stage. We conduct zero-shot and few-shot experiments on Natural Language Inference and Question Answering. The experimental results demonstrate the effectiveness of our method across different languages, tasks, and pretrained models. We also give analysis on various cross-lingual specific settings for meta-learning including sampling strategy and parallelism.
Classification of four qubit states and their stabilisers under SLOCC operations

We classify four qubit states under SLOCC operations, that is, we classify the orbits of the group SL(2,C)4 on the Hilbert space H4=(C2)⊗4 . We approach the classification by realising this representation as a symmetric space of maximal rank. We first describe general methods for classifying the orbits of such a space. We then apply these methods to obtain the orbits in our special case, resulting in a complete and irredundant classification of SL(2,C)4 -orbits on H4 . It follows that an element of (C2)⊗4 is conjugate to an element of precisely 87 classes of elements. Each of these classes either consists of one element or of a parameterised family of elements, and the elements in the same class all have equal stabiliser in SL(2,C)4 . We also present a complete and irredundant classification of elements and stabilisers up to the action of Sym4⋉SL(2,C)4 where Sym4 permutes the four tensor factors of (C2)⊗4 .
Improving the Chamberlin Digital State Variable Filter

The state variable filter configuration is a classic analogue design which has been employed in many electronic music applications. A digital implementation of this filter was put forward by Chamberlin, which has been deployed in both software and hardware forms. While this has proven to be a straightforward and successful digital filter design, it suffers from some issues, which have already been identified in the literature. From a modified Chamberlin block diagram, we derive the transfer functions describing its three basic responses, highpass, bandpass, and lowpass. An analysis of these leads to the development of an improvement, which attempts to better shape the filter spectrum. From these new transfer functions, a set of filter equations is developed. Finally, the approach is compared to an alternative time-domain based re-organisation of update equations, which is shown to deliver a similar result.
Self-Supervised Audio-Visual Representation Learning with Relaxed Cross-Modal Temporal Synchronicity

We present CrissCross , a self-supervised framework for learning audio-visual representations. A novel notion is introduced in our framework whereby in addition to learning the intra-modal and standard ‘synchronous’ cross-modal relations, CrissCross also learns ‘asynchronous’ cross-modal relationships. We show that by relaxing the temporal synchronicity between the audio and visual modalities, the network learns strong time-invariant representations. Our ex-periments show that strong augmentations for both audio and visual modalities with relaxation of cross-modal temporal synchronicity optimize performance. To pretrain our proposed framework, we use 3 different datasets with varying sizes, Kinetics-Sound, Kinetics-400, and AudioSet. The learned representations are evaluated on a number of downstream tasks namely action recognition, sound classiﬁcation, and retrieval. CrissCross shows state-of-the-art performances on action recognition (UCF101 and HMDB51) and sound classiﬁcation (ESC50). The codes and pretrained models will be made publicly available.
Attention Approximates Sparse Distributed Memory

While Attention has come to be an important mechanism in deep learning, there remains limited intuition for why it works so well. Here, we show that Transformer Attention can be closely related under certain data conditions to Kanerva’s Sparse Distributed Memory (SDM), a biologically plausible associative memory model. We conﬁrm that these conditions are satisﬁed in pre-trained GPT2 Transformer models. We discuss the implications of the Attention-SDM map and provide new computational and biological interpretations of Attention.
Voltage Generated Characteristics of Piezoelectric Ceramics Cymbal Transducer

In this study the relation between the generated open circuit output voltages of the piezoelectric ceramics Cymbal transducers with applied impact mechanical energy is studied. The output voltages of piezoelectric ceramics Cymbal transducers are increased with the increasing of the applied mechanical energy. Under the same impact mechanical energy, the generated open circuit output voltages of the piezoelectric ceramics Cymbal transducer is much higher than that of uncapped piezoelectric ceramics disk alone. The generated open circuit output voltages of the piezoelectric ceramics Cymbal transducer depend on the geometry parameters and the metal thickness of end-cap. The generated open circuit voltage of piezoelectric ceramics Cymbal transducer with thick metal thickness is small than that with thin metal thickness.