Search

This paper presents a deep and critical analysis of Singapore's new wave of state-built digital tools and services and how it connects to its larger smart urbanism project, also known as Smart Nation. The COVID-19 pandemic, and particularly Singapore's response, served as a real-world testing ground for smart urbanist strategies. In particular, we analysed the logic that emanates from these novel digital interventions, how they operate on the complex urban built environment and the population, and their effects on urban and citizenry morphologies. Next, we examined a series of state-led technological implementations that have emerged since the Covid-19 pandemic, providing digital solutions that assist citizens with the changing rhythms of everyday living, data-capturing sensors and gantries to aid authorities in contract tracing efforts and enforce vaccination differentiation measures, geospatial digital mapping of demographic data, in withal robotics for automated policing and cleaning activities; and the use of AI and automated data-driven tools in public health to improve service delivery and care to patients. While we are unable to exhaust every piece of technology for the purpose of this paper, these developments, along with their design thinking and operations, we argue, are helpful in revealing the contemporary conjectures of Singaporean digital urban idealism and the governing strategies of the state. By examining Singapore's response, this study aims to contribute to the ongoing discourse on smart urbanism, offering insights into how cities can leverage technology effectively while balancing technological innovation with privacy and public trust.

After the coronavirus disease 2019 (COVID-19) outbreak, the viral infection known as monkeypox gained significant attention, and the World Health Organization (WHO) classified it as a global public health emergency. Given the similarities between monkeypox and other pox viruses, conventional classification methods encounter difficulties in accurately identifying the disease. Furthermore, sharing sensitive medical data gives rise to concerns about security and privacy. Integrating deep neural networks with federated learning (FL) presents a promising avenue for addressing the challenges of medical data categorization. In light of this, we propose an FL-based framework using deep learning models to classify monkeypox and other pox viruses securely. The proposed framework has three major components: (a) a cycle-consistent generative adversarial network to augment data samples for training; (b) deep learning-based models such as MobileNetV2, Vision Transformer (ViT), and ResNet50 for the classification; and (c) a flower-federated learning environment for security. The experiments are performed using publicly available datasets. In the experiments, the ViT-B32 model yields an impressive accuracy rate of 97.90%, emphasizing the robustness of the proposed framework and its potential for secure and accurate categorization of monkeypox disease.

The FIDES Guide is a reliability prediction handbook published by a group of European defense and aerospace manufacturers under the supervision of the French Ministry of Defense. This paper evaluates the suitability of FIDES for predicting reliability. The evaluation is based on the fitness of the model used in FIDES for calculating the failure rate and the accuracy of its reliability predictions. The assessment makes use of the questionnaire in the IEEE Standard 1413, “IEEE Standard Framework for Reliability Prediction of Hardware.” The foundation of FIDES on the erroneous assumption of a constant failure rate for electronics, its omission of critical attributes (e.g., materials and geometry of components), and the subjectivity of certain inputs to the model make it inadequate for producing an accurate prediction.

Background: Prevalence of thyroid disorders during pregnancy has a wide geographic variation. There is paucity of data on prevalence of thyroid disorders in Indian pregnant women. Lower Assam consists of people of different culture and ethnicity. In a pilot study done in lower part of Assam among 1st trimester pregnant lady in which the prevalence was alarmingly high. Objective: The objective of the study is to find out prevalence of thyroid disorders among pregnant women in lower Assam. Materials and methods: The study was an out patient department (OPD) based randomized, prospective cohort, observational study over a period of one year. The 880 pregnant women between the age group of 18 to 45 years, who were attending the antenatal OPDs of Fakhruddin Ali Ahmed Medical College, were included in the study. Results: The mean age and thyroid stimulating hormone (TSH) level of study population was 23.70 ± 4.77 years and 2.83±4.02 mIU/ml respectively. The prevalence of thyroid dysfunction was 62.72%. Of this, prevalence of hypothyroidism was 61.70% and that of hyperthyroidism was 1.02%. The majority of the pregnant lady in their 1st trimester was suffering from hypothyroidism (58.6%) (TSH level 2.8± 3.2 mIU/). The prevalence of hypothyroidism is more in pregnant ladies whose age more than 30 yrs (63.8 %). Conclusion: In our study we found that more than 58.6% pregnant women in their first trimester were suffering from hypothyroidism. Thyroid disorders are common in pregnancy, and the screening for thyroid dysfunction should be done early in pregnancy.

The bathtub model has often been cited as a hazard rate profile that predicts not only human mortality but also the hazard rate of manufactured products. This article examines the inapplicability of the bathtub model to predict the hazard rate of electronic components, products, and systems. The article reviews various literature and uses numerous experiments and field failure data to support its argument. The factors affecting the hazard rate of electronics are then discussed, common hazard rate trends for electronics are identified, and recommendations for the assessment of hazard rates are given. This article recommends that a preconceived model of hazard rate over time should not be used.

Insulated gate bipolar transistor (IGBT) is widely used in power equipment, it generally works in complex circuit profiles and it is very difficult to measure or predict the thermal parameters of the module in real-time and evaluate the corresponding health status in the transient process. This paper develops a novel approach for solder-layer condition monitoring of IGBTs. In the approach a time-series nonparametric model of a power module is constructed, the current power and ambient temperature data are used to deduce the health state junction and case temperature. Three groups of time-series insulated gate bipolar transistors (IGBTs) data are used to train and verify the time-series nonparametric model for online conditions, the results show that the developed method has high accuracy. Compared with traditional methods, the time series non-parametric model method not only saves characteristic experiments but also saves the process of mathematical model construction. Besides, the proposed method also has the advantages of strong generalization and low equipment requirements which is useful for actual working conditions. Thereafter, another nonparametric model is built, the predicted junction temperature is used to estimate the collector voltage in the health state, and the percentage deviation of the measured collector voltage from the estimated voltage is used to do the state-of-health estimation of the IGBT and its accuracy is verified by the experiment result.

Abstract Background Elevated basal cortisol levels are present in women with primary and metastatic breast cancer. Although cortisol's potential role in breast‐to‐brain metastasis has yet to be sufficiently studied, prior evidence indicates that it functions as a double‐edged sword—cortisol induces breast cancer metastasis in vivo, but strengthens the blood‐brain‐barrier (BBB) to protect the brain from microbes and peripheral immune cells. Aims In this study, we provide a novel examination on whether cortisol's role in tumor invasiveness eclipses its supporting role in strengthening the CNS barriers. We expanded our study to include the blood‐cerebrospinal fluid barrier (BCSFB), an underexamined site of tumor entry. Methods and Results Utilizing in vitro BBB and BCSFB models to measure barrier strength in the presence of hydrocortisone (HC). We established that lung tumor cells migrate through both CNS barriers equally while breast tumors cells preferentially migrate through the BCSFB. Furthermore, HC treatment increased breast‐to‐brain metastases (BBM) but not primary breast tumor migratory capacity. When examining the transmigration of breast cancer cells across the BCSFB, we demonstrate that HC induces increased traversal of BBM but not primary breast cancer. We provide evidence that HC increases tightness of the BCSFB akin to the BBB by upregulating claudin‐5, a tight junction protein formerly acknowledged as exclusive to the BBB. Conclusion Our findings indicate, for the first time that increased cortisol levels facilitate breast‐to‐brain metastasis through the BCSFB—a vulnerable point of entry which has been typically overlooked in brain metastasis. Our study suggests cortisol plays a pro‐metastatic role in breast‐to‐brain metastasis and thus caution is needed when using glucocorticoids to treat breast cancer patients.

Abstract In this paper we discuss the Standard Model and new physics sensitivity of the Λ b → Λ ∗ 1520 → N K ¯ ℓ + ℓ − $$ {\Lambda}_b\to {\Lambda}^{\ast }(1520)\left(\to N\overline{K}\right){\mathrm{\ell}}^{+}{\mathrm{\ell}}^{-} $$ decay at low-recoil, where ℓ ± are massive leptons and N K ¯ = pK − n K ¯ 0 $$ N\overline{K}=\left\{{pK}^{-},n{\overline{K}}^0\right\} $$ . We provide a full angular distribution with a set of operators that includes the Standard Model operators and their chirality flipped counterparts, and new scalar and pseudo-scalar operators. The resulting angular distribution allows us to construct observables that we study in the Standard Model and in model-independent new physics scenarios. To reduce the hadronic effects emanating from the Λ b → Λ* (1520) transition form factors, we exploit the Heavy Quark Effective theory framework valid at low Λ ∗ (1520) recoil, i.e., large dilepton invariant mass squared q 2 ∼ O m b 2 $$ {q}^2\sim \mathcal{O}\left({m}_b^2\right) $$ . Working to the leading order in 1/m b and including O α s $$ \mathcal{O}\left({\alpha}_s\right) $$ corrections, we compute the ‘improved Isgur-Wise relations’ between the form factors. The relations correlate the form factors and thereby allow the description of this decay at the low-recoil region with a smaller number of independent form factors.

Insulated-gate bipolar transistors (IGBTs) are one of the most vulnerable components that account for a significant fraction of inverter and converter failures. This paper conducts a degradation analysis of IGBTs using run-to-failure measurements. Online assessment of the degradation state of IGBTs can prolong normal operation and enable proactive maintenance of the system. The research idea is to find a reliable and robust mechanism for IGBT degradation assessment. This paper developed a prediction interval-based degradation assessment methodology that accurately classifies different health states or degradation levels of IGBTs by adding prediction bounds and using them as a critical value for serious damage. It first computes the prediction interval and then uses the Mahalanobis distance to classify the state into degradation level 1 and degradation level 2, instead of just applying the base algorithm. The developed method outperforms distance-based classification schemes and self-organizing maps for online assessment of degradation levels. It only requires training of 1000 initial points which are assumed to be healthy. Furthermore, the generalizability of the method has been shown by validating the effectiveness of the proposed method on three other modules.

Abstract Inspired by the recent hints of lepton flavor universality violation in $$b\rightarrow s\ell \ell $$ b→sℓℓ and $$b\rightarrow c\ell \nu $$ b→cℓν transitions, we study lepton flavor violating exclusive $$\Lambda _b\rightarrow \Lambda \ell _1^+\ell _2^-$$ Λb→Λℓ1+ℓ2- ($$\ell _1\ne \ell _2$$ ℓ1≠ℓ2 ) decay, which is forbidden in the Standard Model. Starting from a general effective Hamiltonian for a $$b\rightarrow s\ell _1^+\ell _2^-$$ b→sℓ1+ℓ2- transition that includes vector and axial-vector operators, and scalar and pseudo-scalar operators, we derive a two-fold decay distribution of $$\Lambda _b\rightarrow \Lambda \ell _1^+\ell _2^-$$ Λb→Λℓ1+ℓ2- . The distribution helps us to construct the differential branching ratio and the lepton-side forward–backward asymmetry, which are studied in a vector leptoquark model. The parameter space of the vector leptoquark model is constrained by low energy observables.

When numerous well-known suppliers and original equipment manufacturers engage in deceptive practices, including falsifying product data or neglecting to report known defects, the fundamental question that arises is whether any claim from any company can be trusted. This paper sheds light on the importance of tackling supply chain fraud more rigorously. This paper discusses the current state of supply chain complexity and customer practices and then highlights the prevalence of fraud and its impact on all consumers. Examples of renowned companies that have either publicly acknowledged fraudulent practices or were caught in some level of deception in their supply of products are provided. Examining the different instances of fraud enabled us to identify cost reduction as a conjoint recurring cause, which formed the baseline to develop and suggest guidelines for fraud detection and risk mitigation.

This paper presents an optimized curing process for the shear strength achievement and retention for anisotropic conductive adhesive (ACA) flip-chip interconnections. The curing kinetics of ACA is first presented and then a curing degree (α) relationship between curing temperature T and curing time t is established. The influence of different curing degree states on the interfacial shear strength is then reported, including the effect of degree of curing on shear strength both before and after hygro-thermal aging.

This paper presents the various ways that lithium-ion batteries are being counterfeited, the problems that counterfeit batteries present, how they enter the consumer market, and the difficulties of detection. Simple external visual inspection of the battery is unreliable. As shown in the presented case study, even for the same brand batteries, their internal structures are different. The current counterfeit prevention methods focus on the manufacturing step. To reduce the risk of counterfeit batteries, device manufacturers and retail stores should characterize the batteries they receive. In addition, related authorities or organizations should set standards to enable a universal battery tracking method along the supply chain to prevent counterfeit lithium-ion batteries from entering the market.

To curb Covid-19 spread, Prime Minister Narendra Modi has announced a 21-day nationwide lockdown on 23 March 2020. The present study makes an attempt to estimate the state-wise and economic activity-wise economic loss of 21- day lockdown in India. The data on Net State Value Added (NSVA) by economic activity was collected for five years from the Reserve Bank of India. It was found that the percentage of the daily loss of Net State Value Added (NSVA) was considerably higher for the states of Chandigarh, Delhi and Karnataka. The manufacturing sector was expected to be the highest loser, followed by real estate, ownership of dwelling and professional services. In absolute terms, the loss was prominent in Maharashtra, Tamil Nadu and Karnataka. It is worth mentioning here that what could be the magnitude of the impact of a complete social and economic shutdown may not be easy to estimate, but it is likely to be far more severe.

Abstract We present a full angular distribution of the four body Λ b → Λ(→ N π)ℓ+ℓ− decay where the leptons are massive and the Λ b is unpolarized, in an operator basis which includes the Standard Model operators, new vector and axial-vector operators, and scalar and pseudo-scalar operators. The angular coefficients are expressed in terms of transversity amplitudes. We study several Λ b → Λ(→ pπ)τ +τ − observables in the Standard Model and in the presence of the new operators. For our numerical analysis, we use the form factors from lattice QCD calculations.

Abstract We study the rare $$\Lambda _b\rightarrow \Lambda \mu ^+\mu ^-$$ Λb→Λμ+μ- decay in the Standard Model and beyond. Beyond the Standard Model we include new vector and axial-vector operators, scalar and pseudo-scalar operators, and tensor operators in the effective Hamiltonian. Working in the helicity basis and using appropriate parametrization of the $$\Lambda _b \rightarrow \Lambda $$ Λb→Λ hadronic matrix elements, we give expressions of hadronic and leptonic helicity amplitudes and derive expression of double differential branching ratio with respect to dilepton invariant mass squared and cosine of lepton angle. Appropriately integrating the differential branching ratio over the lepton angle, we obtain the longitudinal polarization fraction and the leptonic forward-backward asymmetry and sequentially study the observables in the presence of the new couplings. To analyze the implications of the new vector and axial-vector couplings, we follow the current global fits to $$b\rightarrow s\mu ^+\mu ^-$$ b→sμ+μ- data. While the impacts of scalar couplings can be significant, exclusive $$\bar{B}\rightarrow X_s\mu ^+\mu ^-$$ B¯→Xsμ+μ- data imply stringent constraints on the tensor couplings and hence the effects on $$\Lambda _b\rightarrow \Lambda \mu ^+\mu ^-$$ Λb→Λμ+μ- are negligible.

This is Editorial

Introduction: Olanzapine is a commonly used antipsychotic. Prolactin elevation is a common adverse effect of anstipsychotics, and serum prolactin elevation is seen in about 30% patients treated with olanzapine. There are confounding results about dose dependency of olanzapine and prolactin elevation, and also the duration of treatment. Method: Fifty six patients, 36 male and 20 female, who were taking olanzapine for any condition for more than a month at a constant dose were enrolled in the study. Patients’ age, weight, body mass index (BMI), serum prolactin levels, and some biochemical values were recorded. Patients were taken from the review outpatient department (OPD) after due consent. Results: Five each in male and female groups showed elevation of serum prolactin (estimated to be high if >20 ng/dl for males, and >25 ng/dl for females.) In females, the elevation was found at lesser dose of olanzapine (13 mg/day, in males 18 mg/day) and early in the treatment (2.4 months vs. 9.7 months in males). Males tended to show raised prolactin with higher doses of olanzapine (mean 18 mg/day). Females (26.31%) also showed higher prevalence of prolactin elevation compared to males (13.51%). No other parameter was found to modify the prolactin levels. Conclusion: Olanzapine causes elevation of serum prolactin, though lesser degree than some other antipsychotics. Females are more prone to have raised serum prolactin with olanzapine compared to males. However, the elevation seems to be transient. Higher doses of olanzapine tend to cause elevation of serum prolactin. Serum prolactin estimation in patients taking olanzapine may be undertaken to maintain quality life, particularly in females.