Risks and opportunities for children's well-being in resource-constrained multigenerational households during COVID-19: Implications for school psychology interventions.

The coronavirus disease (COVID-19) pandemic had a global impact on family social and economic well-being. Individuals and families sought alternative living arrangements as a result of the financial crisis, health implications, and housing insecurity, with many joining multigenerational households. However, it is unknown how multigenerational family life affects children's well-being. Therefore, this qualitative study explored risks and resilience-building opportunities for children's psychological and social well-being in resource-constrained multigenerational households during the COVID-19 pandemic in South Africa. Five multigenerational families were selected through snowball sampling and case design. The three generations of participants were grandparents (n = 5), parents (n = 7), and children (n = 4). Data were gathered through a questionnaire and interviews. The study received institutional ethics approval. After thematic analysis, two themes and six sub-themes were identified. Risks were related to interpersonal conflict, family collective fear of COVID-19, and children's multiple other fears. Opportunities were identified as academic support, shared responsibilities, life skills and values acquisition, and family cohesion. Results demonstrated the potential risks and resilience-building opportunities multigenerational households present for children's psychosocial well-being. Multisystemic influences in a multigenerational household contribute to children's adjustment. These outcomes necessitate systemic school psychology interventions. Longitudinal studies are recommended to explore child well-being trends in multigenerational households in varying socioeconomic contexts.

Global dynamics of an SIS compartment model with resource constraints.

This paper formulates a mathematical framework to describe the dynamics of SIS-type infectious diseases with resource constraints. We first define the basic reproduction number that determines disease prevalence and analyze the existence and local stability of the equilibria. Subsequently, we analyze the global dynamics of the model, excluding periodic solutions and heteroclinic orbits, using the compound matrix approach. The analysis implies that the model can undergo forward and backward bifurcations depending on critical parameters. In the former scenario, the disease persists when the basic reproduction number under resource constraints exceeds one. In the latter scenario, the backward bifurcation creates bistability dynamics in which the disease may persist or become extinct depending on the initial level of infected individuals and the resource abundance.

Optimizing Urgency of Information through Resource Constrained Joint Sensing and Transmission.

Applications requiring services from modern wireless networks, such as those involving remote control and supervision, call for maintaining the timeliness of information flows. Current research and development efforts for 5G, Internet of things, and artificial intelligence technologies will benefit from new notions of timeliness in designing novel sensing, computing, and transmission strategies. The age of information (AoI) metric and a recent related urgency of information (UoI) metric enable promising frameworks in this direction. In this paper, we consider UoI optimization in an interactive point-to-point system when the updating terminal is resource constrained to send updates and receive/sense the feedback of the status information at the receiver. We first propose a new system model that involves Gaussian distributed time increments at the receiving end to design interactive transmission and feedback sensing functions and develop a new notion of UoI suitable for this system. We then formulate the UoI optimization with a new objective function involving a weighted combination of urgency levels at the transmitting and receiving ends. By using a Lyapunov optimization framework, we obtain a decision strategy under energy resource constraints at both transmission and receiving/sensing and show that it can get arbitrarily close to the optimal solution. We numerically study performance comparisons and observe significant improvements with respect to benchmarks.

Estimating optimal dynamic treatment strategies under resource constraints using dynamic marginal structural models.

Methods for estimating optimal treatment strategies typically assume unlimited access to resources. However, when a health system has resource constraints, such as limited funds, access to medication, or monitoring capabilities, medical decisions must account for competition between individuals in resource usage. The problem of incorporating resource constraints into optimal treatment strategies has been solved for point exposures (1), that is, treatment strategies entailing a decision at just one time point. However, attempts to directly generalize the point exposure solution to dynamic time-varying treatment strategies run into complications. We sidestep these complications by targeting the optimal strategy within a clinically defined subclass. Our approach is to employ dynamic marginal structural models to estimate (counterfactual) resource usage under the class of candidate treatment strategies and solve a constrained optimization problem to choose the optimal strategy for which expected resource usage is within acceptable limits. We apply this method to determine the optimal dynamic monitoring strategy for people living with HIV when resource limits on monitoring exist using observational data from the HIV-CAUSAL Collaboration.

Clinical use of neuro-imaging in psychiatric patients at the Charlotte Maxeke Johannesburg Academic Hospital.

BACKGROUND: Neuro-imaging is relatively new in psychiatry. Although the actual role of neuro-imaging in psychiatry remains unclear, it is used to strengthen clinical evidence in making psychiatric diagnoses. AIM: To analyse the records of inpatients referred for neuro-imaging (computerised tomography [CT] and/or magnetic resonance imaging [MRI] scans) to determine the proportion of abnormal neuro-imaging results and, if any, factors associated with abnormal neuro-imaging results. SETTING: This study was conducted at the Charlotte Maxeke Johannesburg Academic Hospital (CMJAH) situated in Johannesburg, South Africa. METHODS: This was a quantitative retrospective record review. All adult psychiatric inpatients who had undergone a CT and/or MRI scan during 01 January 2014 to 31 December 2015 were included. Out-patients or patients admitted in the medical wards were excluded from the study. All neuro-imaging referrals were identified from hospital records and their demographics, scan characteristics and diagnoses were subsequently captured. RESULTS: A total of 1040 patients were admitted to the CMJAH psychiatric unit, of which 213 (20.5%) underwent neuro-imaging tests. Of the 213 scans performed, 74 were abnormal, representing a yield of 34.7%. The most common reported pathology was atrophy (n = 22, 29.7%). There was no statistically significant association between age group (χ 2 = 3.9, p = 0.8), gender (χ 2 = 1.3; p = 0.5), psychiatric diagnoses and abnormal scans. However, there were trends towards an association with comorbid HIV infection (χ 2 = 3.476, p = 0.062) and comorbid substance abuse (χ 2 = 2.286, p = 0.091). CONCLUSION: This study supports the need for clear clinical indications to justify the cost-effective use of neuro-imaging in psychiatry. This study's high yield of abnormal CT scans, although similar to other studies, advocates that HIV positive testing and the presence of focal neurological signs will improve the yield further.

Lightweight and Resource-Constrained Learning Network for Face Recognition with Performance Optimization.

Despite considerable progress in face recognition technology in recent years, deep learning (DL) and convolutional neural networks (CNN) have revealed commendable recognition effects with the advent of artificial intelligence and big data. FaceNet was presented in 2015 and is able to significantly improve the accuracy of face recognition, while also being powerfully built to counteract several common issues, such as occlusion, blur, illumination change, and different angles of head pose. However, not all hardware can sustain the heavy computing load in the execution of the FaceNet model. In applications in the security industry, lightweight and efficient face recognition are two key points for facilitating the deployment of DL and CNN models directly in field devices, due to their limited edge computing capability and low equipment cost. To this end, this paper provides a lightweight learning network improved from FaceNet, which is called FN13, to break through the hardware limitation of constrained computational resources. The proposed FN13 takes the advantage of center loss to reduce the variations of the between-class features and enlarge the difference of the within-class features, instead of the triplet loss by using FaceNet. The resulting model reduces the number of parameters and maintains a high degree of accuracy, only requiring few grayscale reference images per subject. The validity of FN13 is demonstrated by conducting experiments on the Labeled Faces in the Wild (LFW) dataset, as well as an analytical discussion regarding specific disguise problems.

A retrospective study of death scene investigation practices for sudden unexpected death of infants (SUDI) in Cape Town, South Africa.

A death scene investigation (DSI) forms an integral part of the inquiry into death, particularly for sudden unexpected death of infants (SUDI). Global guidelines exist for DSI, however, previous studies have shown that South Africa does not routinely perform DSI for SUDI cases, nor is there a standard protocol in this regard. This was largely attributed to the large burden of SUDI cases as well as the lack of resources, due to South Africa being a developing country. This study assessed DSI practices at one of the largest mortuaries in Cape Town (Salt River Mortuary) to assess the scope of these practices within a resource-constrained context. Data were collected by retrospectively reviewing medico-legal case files (n = 454) from SUDI cases investigated at Salt River Mortuary over a two-year period. The results showed that SUDI death scenes were visited in 59.2% of cases at Salt River Mortuary, with poor and inconsistent levels of documentation. Death scenes were never investigated in cases where the infant was pronounced dead on arrival at a medical facility. The findings support the need for a locally relevant approach to DSI, coupled with specialized training for staff. Based on the limited resources, this should focus on the training of staff using the available resources and accurate use of documentation.

Validity of simple clinical and biological parameters as screening tool for sickle cell anemia for referral to tertiary center in highly resource constraints.

BACKGROUND: In the Democratic Republic of Congo, the incidence of sickle cell anemia (SCA) is estimated around 40 000 neonates per year. However, it is notoriously difficult to perform conventional electrophoresis in all hospitals and laboratories, especially at peripheral levels and rural area. A panel of multiple clinical and laboratory features that would enhance sickle cell disease were assessed for the detection of the disease in highly resource-scarce settings. METHODS: A prospective study was conducted in Kinshasa. Venous blood samples were drawn from each study participant in order to determine the hematologic parameters, the peripheral smears, and the hemoglobin electrophoresis. We used Cohen's κ statistic to examine the agreement of each variable and diagnosis of sickle cell disease. RESULTS: A total of 807 patients were screened for sickle cell disease. Among these 807 children, 36 (4.5%) were homozygous for Hb S disease. The presence of at least 8% erythroblasts (PPV: 91%, NPV: 99%, sensitivity: 83.3%, specificity: 99.6%, κ value: .86) and sickle cells (PPV:100%, NPV: 98%, sensitivity: 50%, specificity: 100%, κ value: .66) in the peripheral blood smear had an acceptable agreement for sickle cell disease. CONCLUSION: These two biological markers may guide the clinician in the decision-making to initiate the management of the children as a sickle cell patient, pending confirmation of the disease by electrophoresis techniques.

Economic Assessment in Resource-Constrained Systems: Individual-Level Simulation Model in Wet Age-Related Macular Degeneration and Diabetic Macular Oedema.

INTRODUCTION: Cost-effectiveness analyses typically ignore healthcare system resource constraints. Ophthalmology is affected by resource constraints because of increasing disease prevalence and the use of resource-intensive treatments. This study evaluated the impact of resource constraints on the cost-effectiveness of faricimab 6 mg, compared with aflibercept 2 mg and ranibizumab biosimilar 0.5 mg, for treating wet age-related macular degeneration (wAMD) or diabetic macular oedema (DMO) over a 5-year horizon. METHODS: A microsimulation model estimated the impact of resource constraints on patients visits, delays, costs and quality-adjusted life-year (QALY) losses due to treatment delays at a typical UK National Health Service eye hospital treating 1500 patients with wAMD and 500 patients with DMO. Patient characteristics, treatment regimens and treatment intervals were informed using published literature and expert opinion. Resource constraint was represented by limiting the number of available intravitreal injection appointments per week, with growing demand caused by rising disease prevalence. The model compared outcomes across three scenarios; each scenario involved treating all patients with one of the three treatments. RESULTS: Over 5 years, in a resource-constrained hospital, compared with aflibercept, faricimab use resulted in the avoidance of 12,596 delays, saved GBP/£15,108,609 in cost and avoided the loss of 60.06 QALYs. Compared with ranibizumab biosimilar, faricimab use resulted in the avoidance of 18,910 delays, incurred £2,069,088 extra cost and avoided the loss of 105.70 QALYs, resulting in an incremental cost-effectiveness ratio of £19,574/QALY. CONCLUSIONS: Accounting for resource constraints in health economic evaluation is crucial. Emerging therapies that are more durable and require less frequent clinic visits can reduce treatment delays, leading to improved QALY outcomes and reduced burden on healthcare systems. Faricimab reduced the number of delayed injections, leading to improved QALY outcomes for patients in a healthcare system with resource constraints. Faricimab is cost-saving when compared with aflibercept and cost-effective when compared with ranibizumab biosimilar.

Assessing the net benefit of machine learning models in the presence of resource constraints.

OBJECTIVE: The objective of this study is to provide a method to calculate model performance measures in the presence of resource constraints, with a focus on net benefit (NB). MATERIALS AND METHODS: To quantify a model's clinical utility, the Equator Network's TRIPOD guidelines recommend the calculation of the NB, which reflects whether the benefits conferred by intervening on true positives outweigh the harms conferred by intervening on false positives. We refer to the NB achievable in the presence of resource constraints as the realized net benefit (RNB), and provide formulae for calculating the RNB. RESULTS: Using 4 case studies, we demonstrate the degree to which an absolute constraint (eg, only 3 available intensive care unit [ICU] beds) diminishes the RNB of a hypothetical ICU admission model. We show how the introduction of a relative constraint (eg, surgical beds that can be converted to ICU beds for very high-risk patients) allows us to recoup some of the RNB but with a higher penalty for false positives. DISCUSSION: RNB can be calculated in silico before the model's output is used to guide care. Accounting for the constraint changes the optimal strategy for ICU bed allocation. CONCLUSIONS: This study provides a method to account for resource constraints when planning model-based interventions, either to avoid implementations where constraints are expected to play a larger role or to design more creative solutions (eg, converted ICU beds) to overcome absolute constraints when possible.

Evaluation of crop research institutes under data and resource constraints: An alternative approach.

The evaluation of crop research institutes in the developing world under limited data availability has not been assessed in the past due to resource constraints. The paper assesses the social benefits of rice research taking the case of a research institute from India following a new approach. The area coverage of the varieties was estimated to be 3.4 million ha and the gain in production was 6.2 million tonnes per year in India. The additional return obtained due to the adoption of these varieties was about ₹ 14,621 million (US$ 232 million) per year at constant 2014-5 prices. The return per rupee investment in the institute's research and extension was ₹ 17. This approach is recommended for the impact evaluation of other crop research institutes in India and the developing world under resource constraints.

Leveraging conscious and nonconscious learning for efficient AI.

Various interpretations of the literature detailing the neural basis of learning have in part led to disagreements concerning how consciousness arises. Further, artificial learning model design has suffered in replicating intelligence as it occurs in the human brain. Here, we present a novel learning model, which we term the "Recommendation Architecture (RA) Model" from prior theoretical works proposed by Coward, using a dual-learning approach featuring both consequence feedback and non-consequence feedback. The RA model is tested on a categorical learning task where no two inputs are the same throughout training and/or testing. We compare this to three consequence feedback only models based on backpropagation and reinforcement learning. Results indicate that the RA model learns novelty more efficiently and can accurately return to prior learning after new learning with less computational resources expenditure. The final results of the study show that consequence feedback as interpretation, not creation, of cortical activity creates a learning style more similar to human learning in terms of resource efficiency. Stable information meanings underlie conscious experiences. The work provided here attempts to link the neural basis of nonconscious and conscious learning while providing early results for a learning protocol more similar to human brains than is currently available.

Frequent, infinitesimal bottlenecks maximize the rate of microbial adaptation.

Serial passaging is a fundamental technique in experimental evolution. The choice of bottleneck severity and frequency poses a dilemma: longer growth periods allow beneficial mutants to arise and grow over more generations, but simultaneously necessitate more severe bottlenecks with a higher risk of those same mutations being lost. Short growth periods require less severe bottlenecks, but come at the cost of less time between transfers for beneficial mutations to establish. The standard laboratory protocol of 24-h growth cycles with severe bottlenecking has logistical advantages for the experimenter but limited theoretical justification. Here we demonstrate that contrary to standard practice, the rate of adaptive evolution is maximized when bottlenecks are frequent and small, indeed infinitesimally so in the limit of continuous culture. This result derives from revising key assumptions underpinning previous theoretical work, notably changing the metric of optimization from adaptation per serial transfer to per experiment runtime. We also show that adding resource constraints and clonal interference to the model leaves the qualitative results unchanged. Implementing these findings will require liquid-handling robots to perform frequent bottlenecks, or chemostats for continuous culture. Further innovation in and adoption of these technologies has the potential to accelerate the rate of discovery in experimental evolution.

Sustainable development goals applied to digital pathology and artificial intelligence applications in low- to middle-income countries.

Digital Pathology (DP) and Artificial Intelligence (AI) can be useful in low- and middle-income countries; however, many challenges exist. The United Nations developed sustainable development goals that aim to overcome some of these challenges. The sustainable development goals have not been applied to DP/AI applications in low- to middle income countries. We established a framework to align the 17 sustainable development goals with a 27-indicator list for low- and middle-income countries (World Bank/WHO) and a list of 21 essential elements for DP/AI. After categorization into three domains (human factors, IT/electronics, and materials + reagents), we permutated these layers into 153 concatenated statements for prioritization on a four-tiered scale. The two authors tested the subjective ranking framework and endpoints included ranked sum scores and visualization across the three layers. The authors assigned 364 points with 1.1-1.3 points per statement. We noted the prioritization of human factors (43%) at the indicator layer whereas IT/electronic (36%) and human factors (35%) scored highest at the essential elements layer. The authors considered goal 9 (industry, innovation, and infrastructure; average points 2.33; sum 42), goal 4 (quality education; 2.17; 39), and goal 8 (decent work and economic growth; 2.11; 38) most relevant; intra-/inter-rater variability assessment after a 3-month-washout period confirmed these findings. The established framework allows individual stakeholders to capture the relative importance of sustainable development goals for overcoming limitations to a specific problem. The framework can be used to raise awareness and help identify synergies between large-scale global objectives and solutions in resource-limited settings.

The Effect of Fangcang Shelter Hospitals under Resource Constraints on the Spread of Epidemics.

Since the outbreak of the COVID-19 pandemic, Fangcang shelter hospitals have been built and operated in several cities, and have played a huge role in epidemic prevention and control. How to use medical resources effectively in order to maximize epidemic prevention and control is a big challenge that the government should address. In this paper, a two-stage infectious disease model was developed to analyze the role of Fangcang shelter hospitals in epidemic prevention and control, and examine the impact of medical resources allocation on epidemic prevention and control. Our model suggested that the Fangcang shelter hospital could effectively control the rapid spread of the epidemic, and for a very large city with a population of about 10 million and a relative shortage of medical resources, the model predicted that the final number of confirmed cases could be only 3.4% of the total population in the best case scenario. The paper further discusses the optimal solutions regarding medical resource allocation when medical resources are either limited or abundant. The results show that the optimal allocation ratio of resources between designated hospitals and Fangcang shelter hospitals varies with the amount of additional resources. When resources are relatively sufficient, the upper limit of the proportion of makeshift hospitals is about 91%, while the lower limit decreases with the increase in resources. Meanwhile, there is a negative correlation between the intensity of medical work and the proportion of distribution. Our work deepens our understanding of the role of Fangcang shelter hospitals in the pandemic and provides a reference for feasible strategies by which to contain the pandemic.

[Effects of 24 Years Different Straw Return on Soil Carbon, Nitrogen, Phosphorus, and Extracellular Enzymatic Stoichiometry in Dryland of the Loess Plateau, China].

Exploring the biogeochemical cycle characteristics of soil carbon, nitrogen, and phosphorus in farmland in the dryland of the loess plateau can provide scientific basis and technical support for efficient crop production and sustainable land use. Here, based on a long-term (24 year) straw return field experiment in Shouyang, Shanxi province, the effects of different straw return regimes, i.e., straw mulching (SM), direct straw return (DS), animal-digested straw return (AS), and non-straw return (CK), on the stoichiometric ratio of soil elements and extracellular enzyme activities were studied. The vector angle and length were calculated to indicate the resource constraints faced by microorganisms. The vector angle was greater than 45° and less than 45°, indicating that microorganisms were limited by phosphorus and nitrogen, respectively. The greater the deviation from 45°, the greater the degree of limitation, and the longer the vector length, the more severely limited by carbon. The results showed that ① the soil C/N and C/P of long-term straw returning ranged from 9.81 to 14.28 and from 14.58 to 21.92, with the mean values of 12.36 and 17.51, respectively, which were 6.0% and 4.2% lower than that at the initial stage of the experiment. The soil N/P was distributed between 1.27 and 1.57, with an average of 1.42, which was 2.2% higher than that in the initial stage. The soil C/N and C/P ratios showed a trend of first decreasing and then increasing, the soil N/P ratio basically showed a flat trend, and there was no significant difference in soil element metering ratios between different straw returning treatments. ② Compared with the 24-year long-term non-straw return treatment, the activities of ß-1,4-glucosidase (BG) and ß-1,4-N-acetylglucosaminidase (NAG) in the soil of the long-term straw mulching treatment increased by 134.4% and 107.5% (P<0.05), the activities of BG and alkaline phosphatase (AP) in the soil of the long-term straw mulching treatment decreased by 59.3% and 59.5% (P<0.05), respectively, and the activities of NAG in the soil of the long-term straw mulching treatment increased by 102.8% (P<0.05). Under the long-term straw returning treatment, soil microorganisms were faced with carbon and phosphorus limitation as a whole. Long-term straw mulching aggravated microbial carbon limitation, and animal-digested straw return could alleviate the degree of carbon limitation. Compared with that in the 24-year long-term non-straw return treatment, soil EEAC/N could be significantly reduced by the animal-digested straw return treatment, and soil EEAC/P could be increased by the direct straw return treatment. The three straw returning methods had no significant indigenous effect on soil EEAN/P. The overall vector angle was greater than 45°, and the vector length increased by 3.8%-20.1% compared with that in the initial stage. ③ Correlation analysis showed that C and N inputs were significantly negatively correlated with BG activity; available nitrogen was significantly correlated with NAG activity, AP activity, and EEAC/N; C/P was significantly positively correlated with EEAC/N; there were significant correlations between N/P and NAG activity, AP activity, EEAC/N, and EEAC/P; and there was no significant correlation between EEAN/P and any environmental factors. In conclusion, the availability of soil nitrogen and phosphorus elements and N/P ratio had significant effects on soil extracellular enzyme activity and stoichiometric characteristics under different long-term straw returning treatments. In the future, more attention should be paid to the improvement of organic carbon and the promotion of nitrogen and phosphorus availability in farmland soil in soil-efficient cultivation and agricultural production activities.

A Survey of the Management of Diabetic Macular Oedema in Sub-Saharan Africa.

Background: There is minimal information about the availability of treatment for Diabetic macular oedema (DMO) in sub-Saharan Africa (SSA). The principal aim of this survey was to determine the 'real world' management of DMO amongst ophthalmologists working in SSA. Methodology: Questionnaires were distributed to members of retinal and ophthalmological societies in SSA. Results: Ninety-Three ophthalmologists from 24 countries participated with the majority working in Nigeria (51, 55%). Most were retina specialists (50, 54%) and consultants (67, 62%). Clinically significant macular oedema prompted treatment for 62 (67%) ophthalmologists, whilst visual acuity (81, 87%) and OCT changes (76, 82%) were more common reasons to treat DMO. Treatment included intravitreal anti-VEGF (91, 98%), laser (70, 75%), intravitreal steroid (57, 61%), topical drops (52, 56%), oral tablets (32, 34%) and surgery (20, 22%). The commonest intravitreal anti-VEGF agents used were bevacizumab (89, 96%) and ranibizumab (71, 76%). Intravitreal triamcinolone was used by 69 (74%), topical NSAIDs by 51 (55%), and acetazolamide tablets by 22 (24%) ophthalmologists as a treatment for DMO. Conclusion: Sub-Saharan African ophthalmologists commonly use intravitreal anti-VEGF, laser, intravitreal steroid, and topical NSAIDs to treat DMO. Economic constraints and/or the inability to maintain the intensive regimen required for successful intravitreal anti-VEGF therapy probably influence some treatment choices.

Doing more with less - How frugal innovations can contribute to improving healthcare systems.

The dominance of an innovation discourse laden with cutting edge and expensive technologies, may be preventing us from recognizing alternative and complementary perspectives, which could help cut healthcare costs while improving worldwide access to health services. One such complementary approach is that of frugal innovation. Frugal innovation, as a way to produce efficacious and affordable products using fewer resources to reach the underserved customers, has received increasing attention in the social sciences literature. Although frugal innovation is commonly associated with emerging economies, there is now a rising interest from healthcare providers in developed countries, to find and apply effective, and lower-cost solutions. Nonetheless, knowledge on frugal innovation and its role in healthcare is dispersed across different literatures which hampers researchers and practitioners to access a fuller, and integrated picture of the phenomenon. In this study, by synthesizing extant knowledge, we tackle the fragmentation of the phenomenon. We elucidate on who the actors are, what is being done, how are such innovations being developed, and what the outcomes are, providing a framework that lays out the underlying mechanisms of frugal innovation in healthcare (FIH). The midrange theory that we develop, provides a conceptual framework for researchers to undertake empirical observation and models to guide managerial practices. Furthermore, by providing a more unified perspective of frugal innovation in healthcare, we hope to initiate conversations on the development, adequacy and adoption of these innovations in healthcare services, which could increase affordability and access for the population while maintaining quality.

Differences in Phenotypic Plasticity between Invasive and Native Plants Responding to Three Environmental Factors.

The phenotypic plasticity hypothesis suggests that exotic plants may have greater phenotypic plasticity than native plants. However, whether phenotypic changes vary according to different environmental factors has not been well studied. We conducted a multi-species greenhouse experiment to study the responses of six different phenotypic traits, namely height, leaf number, specific leaf area, total biomass, root mass fraction, and leaf mass fraction, of native and invasive species to nutrients, water, and light. Each treatment was divided into two levels: high and low. In the nutrient addition experiment, only the leaf mass fraction and root mass fraction of the plants supported the phenotypic plasticity hypothesis. Then, none of the six traits supported the phenotypic plasticity hypothesis in the water or light treatment experiments. The results show that, for different environmental factors and phenotypes, the phenotypic plasticity hypothesis of plant invasion is inconsistent. When using the phenotypic plasticity hypothesis to explain plant invasion, variations in environmental factors and phenotypes should be considered.

Jugaad Trocar for a 5-mm Laparoscopic Cannula.

When we are practicing, especially in rural India, we often face problems of instrument failure or lost instrument, etc... which may sometimes necessitate abandoning the procedure just because of the lack of a single instrument. We do mobile laparoscopic surgery, carrying all the laparoscopic instruments to far-off places, as far as 60-80 km. On one such occasion, my staff had lost a 5-mm trocar, which had gone unnoticed until I posted a case for laparoscopic cholecystectomy. There was not much time to buy a new one and also it was difficult to procure from the dealer because of the COVID-19 situation. Just because of the lack of one instrument we were facing a situation of postponing laparoscopy!