Implementing Innovation : Project Team Characteristics With Moderating Impact Of Dynamic Managerial Capabilities And Types Of Innovation.

Inovasi adalah asas daya saing utama untuk setiap organisasi. Ia merupakan pelantar untuk peningkatan prestasi dan kecekapan sesebuah organisasi. Innovation is the nexus of competition for all organizations. It serves as a platform to enhance organizational performance and effectiveness

Recruiting for Ideas: How Firms Exploit the Prior Inventions of New Hires

When firms recruit inventors, they acquire not only the use of their skills but also enhanced access to their stock of ideas. But do hiring firms actually increase their use of the new recruits’ prior inventions? Our estimates suggest they do, quite significantly in fact, by approximately 202% on average. However, this does not necessarily reflect widespread “learning-by-hiring.” In fact, we estimate that a recruit’s exploitation of her own prior ideas accounts for almost half of the above effect. Furthermore, although one might expect the recruit’s role to diminish rapidly as her tacit knowledge diffuses across her new firm, our estimates indicate that her importance is surprisingly persistent over time. We base these findings on an empirical strategy that exploits the variation over time in hiring firms’ citations to the recruits’ pre-move patents. Specifically, we employ a difference-in-differences approach to compare pre-move versus post-move citation rates for the recruits’ prior patents and the corresponding matched-pair control patents. Our methodology has three benefits compared to previous studies that also examine the link between labor mobility and knowledge flow: 1) it does not suffer from the upward bias inherent in the conventional cross-sectional comparison, 2) it generates results that are robust to a more stringently matched control sample, and 3) it enables a temporal examination of knowledge flow patterns.

In vitro evaluation of glass fiber post

Statement of problem: Techniques and recommendations for the restoration of endodontically treated teeth have changed from the use of custom cast metal post and core system to glass fiber-reinforced (GFRC) post and composite core system. Has this latest prefabricated glass fiber reinforced post and composite core system increased the fracture resistance of teeth and reduced the incidence of unrestorable root fractures. Purpose: The purpose of this study was to evaluate the incidence of root fracture and mode of failure of endodontically treated teeth restored with two different post and core systems. Material and methods: Forty maxillary central incisors were randomly divided into two groups. (n=20). All teeth received endodontic treatment. First group was restored with custom cast post and core system. Second group was restored with glass fiber post and composite core system. In Both the groups posts were cemented with adhesive resin cement. Compressive load was applied at an angle of 130 to the long axis of teeth at a cross head speed of 1 mm/min until fracture occurred. Data were analyzed with student 't' test P<.001. Results: The mean value for fracture resistance was (331.4025) N in Group -I Custom cast Ni-Cr post and core and (237.0625) N in Group -II Glass fiber reinforced post and composite core system. Students 't' test shows the significant difference in fracture resistance of two groups. Conclusion: This study showed that the incidence of root fracture was significantly higher in custom cast Ni-Cr post and core system than glass fiber post and composite core system. A more favourable mode of failure was observed in teeth restored with Group II glass fiber post system

Voxelotor: novel drug for sickle cell disease

Sickle cell disease (SCD), is an autosomal recessive disorder caused by mutation in the β‐chain of haemoglobin (Hb) that leads to production of sickle haemoglobin (HbS). The disease has a profound negative impact on health-related quality of life with increased propensity for complications. Current treatment options include drugs like hydroxyurea and L-glutamine that are currently on the market. However, none of these therapies target the underlying mechanism and have potential safety concerns. As oxygenated Hb is a potent inhibitor of HbS polymerization, increasing the proportion of oxygenated HbS may provide a disease‐modifying approach to SCD. Voxelotor is a novel therapy developed for the treatment of SCD by modulating the Hb affinity for oxygen. By forming a reversible covalent bond with the N‐terminal valine of the α‐chain of Hb, the drug results in an allosteric modification of Hb and thereby leading to an increase in oxygen affinity. Moreover, voxelotor prevents sickling of red blood cells (RBCs) and possibly interrupts the molecular pathogenesis of the disease. The drug is available in oral formulation with a recommended dosage of 1500 mg once daily. The onset of voxelotor is fast, shows rapid absorption and linear pharmacokinetics. Most common adverse reactions seen are headache, diarrhea and abdominal pain. Clinical trials for voxelotor have been positive, and results suggest that the drug may be a new safe and effective option for SCD treatment. With global blood therapeutics having already received US FDA approval in November 2019, voxelotor may soon be an addition to the mounting armoury of drugs against SCD

Numerical and experimental analysis of dual focus laser for high aspect ratio microdrilling

Laser drilling is the most efficient noncontact material removal process. In this research project, a simplified approach using "dual focus" has been proposed to improve the aspect ratio of the drilling. Dual focus drilling not only changes the kerf angle but also increases the depth of drilling due to redistribution of the intensity in the overlapping focusing region. The dual focus is achieved by focusing two wavelengths at two different foci along the optical axis, using a single lens. A theoretical study of dual beam propagation along the optical axis was done for the selection of the radius of curvature of the lens to achieve continuity within the two focusing regions to increase the aspect ratio. Modeling has been done with numerical approach to understand the impact of intensity distribution and optical parameters on the efficiency of dual wavelength drilling. Objective of the research work is to optimize the laser as well as optical parameters theoretically as well as experimentally with respect to dual wavelength drilling for obtaining high aspect ratio drilled holes with minimum power. The microdrilling station was setup with second harmonic generation to achieve dual wavelength with maximum conversion efficiency of 20%. Experiments were done individually with laser wavelengths of 532nm and 1064nm and with focusing both these wavelengths using a single lens at different pulse energies, on 500om thick silicon wafers. SEM observation of results proved that dual frequency drilling is more efficient compared to conventional drilling and results show excellent agreement with the results from the theoretical model

Keeping the faith: reflections on religious nurture among young British Sikhs

Although young Sikhs are regularly accused of not attending gurdwara and not being interested in Sikhism, many young Sikhs are now learning about Sikhism outside traditional religious institutions. Using data gathered as part of a research project studying the transmission of Sikhism among 18- to 30-year-old British Sikhs, this essay explores how young Sikhs are learning about Sikhism in their pre-adult life stage. Examining the influences of the family and the school environment and the various methods used in gurdwaras, this essay offers a retrospective look on the ways in which young Sikhs are nurtured and socialised into Sikhism, providing an understanding from the perspective of young Sikhs themselves about which methods actually work and why

Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson’s Disease Affected by COVID‐19: A Narrative Review

Background and Motivation: Parkinson’s disease (PD) is one of the most serious, non-curable, and expensive to treat. Recently, machine learning (ML) has shown to be able to predict cardiovascular/stroke risk in PD patients. The presence of COVID‐19 causes the ML systems to be-come severely non‐linear and poses challenges in cardiovascular/stroke risk stratification. Further, due to comorbidity, sample size constraints, and poor scientific and clinical validation techniques, there have been no well‐explained ML paradigms. Deep neural networks are powerful learning machines that generalize non‐linear conditions. This study presents a novel investigation of deep learning (DL) solutions for CVD/stroke risk prediction in PD patients affected by the COVID‐19 framework. Method: The PRISMA search strategy was used for the selection of 292 studies closely associated with the effect of PD on CVD risk in the COVID‐19 framework. We study the hypothesis that PD in the presence of COVID‐19 can cause more harm to the heart and brain than in non‐ COVID‐19 conditions. COVID‐19 lung damage severity can be used as a covariate during DL training model designs. We, therefore, propose a DL model for the estimation of, (i) COVID‐19 lesions in computed tomography (CT) scans and (ii) combining the covariates of PD, COVID‐19 lesions, office and laboratory arterial atherosclerotic image‐based biomarkers, and medicine usage for the PD patients for the design of DL point‐based models for CVD/stroke risk stratification. Results: We validated the feasibility of CVD/stroke risk stratification in PD patients in the presence of a COVID‐ 19 environment and this was also verified. DL architectures like long short‐term memory (LSTM), and recurrent neural network (RNN) were studied for CVD/stroke risk stratification showing powerful designs. Lastly, we examined the artificial intelligence bias and provided recommendations for early detection of CVD/stroke in PD patients in the presence of COVID‐19. Conclusion: The DL is a very powerful tool for predicting CVD/stroke risk in PD patients affected by COVID‐19. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

COVLIAS 2.0-cXAI: Cloud-Based Explainable Deep Learning System for COVID-19 Lesion Localization in Computed Tomography Scans

The previous COVID-19 lung diagnosis system lacks both scientific validation and the role of explainable artificial intelligence (AI) for understanding lesion localization. This study presents a cloud-based explainable AI, the "COVLIAS 2.0-cXAI" system using four kinds of class activation maps (CAM) models.Our cohort consisted of ~6000 CT slices from two sources (Croatia, 80 COVID-19 patients and Italy, 15 control patients). COVLIAS 2.0-cXAI design consisted of three stages: (i) automated lung segmentation using hybrid deep learning ResNet-UNet model by automatic adjustment of Hounsfield units, hyperparameter optimization, and parallel and distributed training, (ii) classification using three kinds of DenseNet (DN) models (DN-121, DN-169, DN-201), and (iii) validation using four kinds of CAM visualization techniques: gradient-weighted class activation mapping (Grad-CAM), Grad-CAM++, score-weighted CAM (Score-CAM), and FasterScore-CAM. The COVLIAS 2.0-cXAI was validated by three trained senior radiologists for its stability and reliability. The Friedman test was also performed on the scores of the three radiologists.The ResNet-UNet segmentation model resulted in dice similarity of 0.96, Jaccard index of 0.93, a correlation coefficient of 0.99, with a figure-of-merit of 95.99%, while the classifier accuracies for the three DN nets (DN-121, DN-169, and DN-201) were 98%, 98%, and 99% with a loss of ~0.003, ~0.0025, and ~0.002 using 50 epochs, respectively. The mean AUC for all three DN models was 0.99 (p < 0.0001). The COVLIAS 2.0-cXAI showed 80% scans for mean alignment index (MAI) between heatmaps and gold standard, a score of four out of five, establishing the system for clinical settings.The COVLIAS 2.0-cXAI successfully showed a cloud-based explainable AI system for lesion localization in lung CT scans