Short Term Research Articles

Performance Scrutiny of Price Prediction on Blockchain Technology Using Machine Learning

Objective: This study, aiming to assess the accurateness of machine learning algorithms for the prediction of cryptocurrency prices, using blockchain technology, was conducted to attest to its effectiveness. The main goal is to evaluate the precision, solidity, and prospects of such models under variable and fragmented trading premises. Methodology: Dataset containing historical crypto prices, transaction volumes, emotions of investors, etc. is formed from different and various sources. Different machine learning approaches including linear regression, support vector machine, random forest, and deep learning networks will be used to construct the prediction model. The split of the dataset into training and testing subsets is performed to better evaluate and estimate the models' performance. Feature engineering techniques and parameter tuning are included in the process of making models more precise. Models are the ones which are the trained using historical data and then later tested out on the unseen data for the purpose of accurate results and generalization power. Results and Discussion: From the experiment it is evident that a shift of different machine learning algorithms exhibits differing outcomes. While certain models can yield admirable results in forecasting crypto prices in shorter terms, however, there are some models that are not capable of capturing the complicated impurities. Factors like data quality, function selection and model complexity are at the core of predictive power. The learning networks demonstrated the capability to reproduce nonlinearity and temporal relatedness in cryptocurrency value data. Conclusion: Cryptocurrency forecasting through blockchain technology involves the use of machine learning techniques which has a lot of potential. The success of these models also depends on the quality of the data, feature refinement and model choice. Research progress should focus on refining currently existing models, considering new data inputs, and introduction of advanced machine learning methods which should be able to increase forecast accuracy in rapidly changing cryptocurrency markets.

The organization dilemma: investing in effectiveness versus efficiency?

Purpose Every business company deals with the dilemma of how much to invest in long-term (LT) versus short-term (ST) problem (LTvST problem). LT operations increase the reputation of the company, and revenue is rewarded in the future. In contrast, ST operations result in immediate rewards. Thus, every organization faces the dilemma of how much to invest in LT versus ST activities. The former deals with the “what” or effectiveness, and the latter deals with the “how” or efficiency. The role of managers is to solve this dilemma; however, they often fail to do so, mainly because of a lack of knowledge. This study aims to propose a dynamic optimal control model that formulates and solves the LTvST problem. Design/methodology/approach This study proposes a dynamic optimal control model that formulates and solves the dilemma whether to invest in short- or LT operations. Findings This model is illustrated as an example of an academic institute that wants to maximize its reputation. Investing in effectiveness in the academy translates into investing in research, whereas investing in efficiency translates into investing in teaching. Universities and colleges with a good reputation attract stronger candidates and benefit from higher tuition fees. Steady-state conditions and insightful observations were obtained by studying the optimal solution and performing a sensitivity analysis. Originality/value To the best of the authors’ knowledge, this paper is the first one to explore the optimal strategy when trying to maximize the short and LT activities of a company and solve the LTvST problem. Furthermore, it is applied on universities where teaching is the ST activity and research the LT activity. The insights gleaned from the application are relevant to many different fields. The authors believe that the paper makes a significant contribution to academic literature and to business managers.

Trends in Cognitive Function Before and After Diabetes Onset: The China Health and Retirement Longitudinal Study.

Individuals with prevalent diabetes were known to have a higher risk of dementia and lower cognitive function. However, trends of cognitive function before diabetes and in the short term after new-onset diabetes remain unclear. This study included participants without baseline diabetes from the China Health and Retirement Longitudinal Study. Cognitive tests were conducted at baseline (wave 1) and at least one time from wave 2 (2013) to wave 4 (2018). Cognitive function was assessed using a global cognition score which was the summary measure of 4 cognitive tests. A linear mixed model was constructed to fit the trends in cognitive function before and after diabetes onset and the trends among nondiabetes. The threshold of statistical significance was p < 0.05. During the 7-year follow-up, 1,207 (9.7% of 12,422, 59.1 ± 8.6 years, 39.9% male participants) participants developed new-onset diabetes. The cognitive function of both the without diabetes group and the diabetes group declined annually during the follow-up. The annual decline rate of the diabetes group before diabetes onset was similar to that of the without diabetes group during the whole follow-up period. After diabetes onset, participants experienced statistically significant faster cognitive declines in global cognition (-0.023 SD/year; 95% CI -0.043 to -0.004; p = 0.019) and visuospatial abilities test (-0.036 SD/year; -0.061 to -0.011; p = 0.004), but not in tests of episodic memory (-0.018 SD/year; -0.041 to 0.004; p = 0.116), attention and calculation (-0.017 SD/year; -0.037 to 0.003; p = 0.090), or orientation (0.001 SD/year; -0.018 to 0.020; p = 0.894), compared with the cognitive slope before diabetes. In subgroup analysis, compared with those who developed diabetes between 45-54 years, those developing diabetes older (55-64 years, p for interaction = 0.701; 65-74 years, p for interaction = 0.996) did not demonstrate different rates of global cognitive decline after diabetes. Individuals experienced faster rate of cognitive decline in a few years after diabetes onset, but not during the prediabetes period. Age did not modify the effect of diabetes on postdiabetes cognitive decline. Efforts in eliminating the adverse impacts on cognition should be started on diagnosis of diabetes.

Birth Spacing and Parents' Physical and Mental Health: An Analysis Using Individual and Sibling Fixed Effects.

An extensive literature has examined the relationship between birth spacing and subsequent health outcomes for parents, particularly for mothers. However, this research has drawn almost exclusively on observational research designs, and almost all studies have been limited to adjusting for observable factors that could confound the relationship between birth spacing and health outcomes. In this study, we use Norwegian register data to examine the relationship between birth spacing and the number of general practitioner consultations for mothers' and fathers' physical and mental health concerns immediately after childbirth (1-5 and 6-11 months after childbirth), in the medium term (5-6 years after childbearing), and in the long term (10-11 years after childbearing). To examine short-term health outcomes, we estimate individual fixed-effects models: we hold constant factors that could influence parents' birth spacing behavior and their health, comparing health outcomes after different births to the same parent. We apply sibling fixed effects in our analysis of medium- and long-term outcomes, holding constant mothers' and fathers' family backgrounds. The results from our analyses that do not apply individual or sibling fixed effects are consistent with much of the previous literature: shorter and longer birth intervals are associated with worse health outcomes than birth intervals of approximately 2-3 years. Estimates from individual fixed-effects models suggest that particularly short intervals have a modest negative effect on maternal mental health in the short term, with more ambiguous evidence that particularly short or long intervals might modestly influence short-, medium-, and long-term physical health outcomes. Overall, these results are consistent with small to negligible effects of birth spacing behavior on (non-pregnancy-related) parental health outcomes.

Current Prospects in Rheumatoid Arthritis: Pathophysiology, Genetics, and Treatments.

An autoimmune inflammatory disease, rheumatoid arthritis (RA), predominantly affects the synovium joint lining, augmenting disability, early mortality, and socioeconomic difficulty. Therefore, current updates on pharmacological therapies are crucial for developing drugs to treat the disease at each stage. This review attempts to compile a thorough analysis of current developments in our knowledge of RA pathogenesis and disease-modifying drugs, with the aim of providing insights for next-generation RA therapeutics. According to the literature, the most successful drugs for treatment techniques described so far in this include (cs) DMARDs (sub-class of DMARDs), tsDMARDS (targeted synthetic DMARDS), and bDMARDs (biological DMARDs). However, current pharmacologic therapy (consisting of biological, conventional, and creative views of small molecule anti-rheumatic drugs that treat the disease or DMARD) remains the cornerstone of rheumatoid arthritis treatment with which significant progress toward disease remission has been accomplished. The pathobiology of RA involves cytokine messengers such as B and T-cells, and an intricate interplay of pro-inflammatory cytokines responsible for activating and developing effector cells, in turn, accountable for local disease and systemic symptoms. Despite the fact that the cause of rheumatoid arthritis is not known, new treatments have been created as a result of better approaches towards the biology of the disease. As they target molecules directly implicated in the genesis of rheumatoid arthritis, these drugs may be more effective, targeted, and less harmful in the short and long term than standard therapies.

Climate policies for carbon neutrality should not rely on the uncertain increase of carbon stocks in existing forests

The international community, through treaties such as the Paris agreement, aims to limit climate change to well below 2 °C, which implies reaching carbon neutrality around the second half of the century. In the current calculations underpinning the various roadmaps toward carbon neutrality, a major component is a steady or even expanding terrestrial carbon sink, supported by an increase of global forest biomass. However, recent research has challenged this view. Here we developed a framework that assesses the potential global equilibrium of forest biomass under different climate change scenarios. Results show that under global warming carbon storage potential in forest aboveground biomass gradually shifts to higher latitudes and the intensity of the disturbance regimes increases significantly almost everywhere. CO2 fertilization stands out as the most uncertain process, with different methods of estimation leading to diverging results by almost 155 PgC of above ground biomass at equilibrium. Overall, assuming that the sum of human pressures (e.g. wood extraction) does not change over time, that total forest cover does not change significantly and that the trend in CO2 fertilisation as it is currently estimated from satellite proxy observations remains, results show that we have reached (or are very close to reaching) the peak of global forest carbon storage. In the short term, where increased disturbance regimes are assumed to act quicker than increased forest growth potential, global forests might instead act as a carbon source, that will require even more effort in decarbonization than previously estimated. Therefore, the potential of forests as a nature-based solution to mitigate climate change brings higher uncertainties and risks than previously thought.

Morphological features of wound repair processes under low-level laser therapy in patients with diabetic foot syndrome

Purpose. To assess morphological features of tissue regeneration processes in lower extremities in patients with the diabetic foot syndrome after low-level laser therapy (LLLT).Materials and methods. The article presents a comparative retrospective analysis of the histological material of wound tissues in 125 patients with the diabetic foot syndrome (DFS). Studied material – histological sections of wound tissues stained with hematoxylin-eosin. The material was divided into two groups: main group – 65 micro-preparations of wound tissues of DFS patients who were treated traditionally plus LLLT; control group – 60 micro-preparations of wound tissues of DFS patients who had surgical wound debridement , then traditional comprehensive therapy with local wet-drying dressings.Results and discussion. The analysis of the obtained results has shown that LLLT promotes activation of cellular components and increases their number: macrophages, lymphocytes, fi broblasts. One can also see faster regenerative processes and granulation tissue formation as well as signifi cantly less area of wound surface, if to compare to the group of patients treated with traditional comprehensive wound management and local techniques.Conclusion. LLLT in the comprehensive management of patients with DFS purulent-necrotic forms can accelerate reparative processes in wound defects and signifi cantly reduce their area. It also helps to clean wounds, to reduce or eliminate infl ammatory processes within much shorter terms than under traditional care. LLLT stimulates production of granulation tissue and accelerates epithelialization as well.

An Analysis of the Relationship between Business Confidence and Macroeconomic Factors: Türkiye Case

Investor sentiment plays an important role in the all level of economic activities. Confidence as an indicator of investor sentiment has become an important and interesting concept in recent years. Confidence indicators are a way in assessing economic developments in the short term. The aim of this study is to analyze the long and short term relationship between the Real Sector Confidence Index and macroeconomic/financial variables for the period of January 2007 – December 2021. The Johansen Cointegration Test results prove a long-term cointegration relationship. Vector Error Correction Models for both macroeconomic and financial variables are statistically significant at the 5% level. In the short run, Manufacturing Capacity Utilization Ratio, Official Reserves, Domestic Debt Stocks, Real Exchance Rate, US Dollar/TRL Buying Rate, Non-Residents’ Stock Portfolio and Volatility Index have a statistically significant effect on the changes in Real Sector Confidence Index. Thus, this study informs investors to predict the effects of changes in the confidence index on financial instruments bilaterally and contribute to their investment decision.

Prediction and risk analysis of Cardio Vascular diseases in IoHT by enhanced CHIO-based Residual and dilated gated network with Attention Mechanism

Generally, computer networks automatically discover data based on the machine learning process. It is the execution of Artificial Intelligence (AI) without any specific program. Using both machine learning and AI, an effective optimization was done for Cardio Vascular Disease (CVD). CVD is associated with disorders that lead to hypertension and unexpected cardiac arrest. To promote good health and prevent risky situations, the Internet of Health Things (IoHT) helps to enhance the treatment's effectiveness. The most challenging task is to perform accurate heart disease prediction. Thus, a CVD prediction model is designed. At first, the needed information is collected from the benchmark dataset. After that, the pre-processing is done on the collected data using the data cleaning and scaling method. The pre-processed data are sent to the CVD prediction phase with the aid of Adaptive Residual and Dilated Long Short Term Memory with Attention Mechanism (ARDL-AM) and the parameters in this structure are optimized by the Enhanced Coronavirus Herd Immunity Optimizer (ECHIO). The obtained results from the ARDL-AM are used for the CVD prediction process. The simulations were carried out with various measures to calculate the recommended method's efficiency.

Analisis Integrasi Pasar Parsial untuk Komoditas Daging Ayam Broiler antar Berbagai Kabupaten/Kota di Provinsi Jambi

This research aims to determine the spatial market integration of broiler chicken meat commodities between various districts/cities in Jambi Province. The analysis method used is the VAR (Vector Autoregression) / VECM (Vector Error Correction Model) model. There is partial market integration in the long and short term for broiler chicken meat commodities between various regencies/cities in Jambi Province so that the price of broiler chicken meat in regencies/cities in Jambi Province influences each other not only in the current period but in relation to prices 1 to 2 days before. There is short and long-term spatial market integration for broiler chicken meat in districts/cities in Jambi Province. The price of broiler chicken meat in Jambi City causes changes in the price of broiler chicken meat in Batang Hari Regency, Kerinci Regency, Merangin Regency and West Tanjung Jabung Regency, and vice versa.

Ultra short term power load forecasting based on the fusion of Seq2Seq BiLSTM and multi head attention mechanism.

Ultra-short-term power load forecasting is beneficial to improve the economic efficiency of power systems and ensure the safe and stable operation of power grids. As the volatility and randomness of loads in power systems, make it difficult to achieve accurate and reliable power load forecasting, a sequence-to-sequence based learning framework is proposed to learn feature information in different dimensions synchronously. Convolutional Neural Networks(CNN) Combined with Bidirectional Long Short Term Memory(BiLSTM) Networks is constructed in the encoder to extract the correlated timing features embedded in external factors affecting power loads. The parallel BiLSTM network is constructed in the decoder to mine the power load timing information in different regions separately. The multi-headed attention mechanism is introduced to fuse the BiLSTM hidden layer state information in different components to further highlight the key information representation. The load forecastion results in different regions are output through the fully connected layer. The model proposed in this paper has the advantage of high forecastion accuracy through the example analysis of real power load data.

Abstract 1811: Efficient identification of new small molecules targeting succinate dehydrogenase in non-small cell lung cancer

Abstract Efficient lung cancer treatment remains challenging due to the lack of therapeutic targets. The succinate dehydrogenase (SDH) enzyme plays a critical metabolic role as an intermediate between the citric acid cycle and the electron transport chain associated with the cancer disease state. Although several existing compounds have been applied to target metabolic diseases in vitro, modulating SDH for lung cancer treatment is still elusive. By integrating the AtomNet® technology for compound identification with mitochondria- and cell-based enzyme activity assays, we identified four new small molecules from 96 predicted candidates. Cellular thermal shift assay confirmed that these small molecules bind directly to SDH subunits in lung cancer cells. Mechanistically, treatment with these small molecules increased cellular and mitochondrial reactive oxygen species, accumulated succinate, and DNA damage-induced apoptosis in lung cancer cell lines. Functionally, these small molecules reduced the growth, migration, and formation of 3D organoids in vitro in lung cancer cell lines, both in the short and long term. Our study sheds light on the function of SDH in metabolic dysfunction related to cancer and highlights the potential of modulating SDH as a viable therapeutic strategy for targeting lung cancer and other cancer types. LS, NS, and WCZ contributed equally to this work. Citation Format: Luis Silva, Nicholas Skiados, Nikitha Murugavel, Nastassja Luna, Karen Cover, Manish K. Gupta, Stephanie C. Contreras, Terrence E. O'Brien, Wen Cai Zhang. Efficient identification of new small molecules targeting succinate dehydrogenase in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1811.

Abstract 5559: The anti-tumor efficacy and immune effects of combining of ceralasertib, an oral ATR kinase inhibitor, with imipridones, in prostate cancer treatment in vitro and in vivo

Abstract Prostate cancer is the most common cancer and the second leading cause of cancer death among men in the United States. There is an estimated 10% to 50% of cases progress to metastatic castration resistant prostate cancer (mCRPC) state within 3 years of diagnosis. mCPRC remains lethal despite therapeutic advances. There is approximately 20% of mCRPC patients present somatic DNA damage repair (DDR) gene mutations. Ceralasertib, formerly known as AZD6738, is a potent and selective orally bioavailable inhibitor of the ataxia tenlangiectasia and Rad3-related (ATR) kinase, which is involved in DNA repair in response to DNA damage and replication stress. Preclinical studies have demonstrated ATRi sensitizing alterations in DNA damage response (DDR) genes. Ceralasertib’s antitumor activity as a monotherapy in treating prostate cancer is moderate. Thus, we combined ceralasertib with imipridones (ONC201 and ONC206), which target mitochondrial caseinolytic protease P (ClpP) and the integrated stress response, resulting in enhanced antitumor efficacy in vitro. Prior data have demonstrated sensitivity of 4 prostate cancer lines to ceralasertib and imipridones monotherapies, synergistic activities with the combination treatments, and immune enhancement effects with the combination treatments when co-cultured with NK92MI cell line. We proceeded to a short term in-vivo study validating the combination treatment efficacy. Preliminary results include cytokine profiling using the Luminex 200 technology to understand treatment induced changes in the tumor microenvironment (TME) from both in vitro and in vivo studies. Our results guide novel clinical trials for effective clinical responses in mCPRC patients. Citation Format: Yutong Linda Xia, Leiqing Zhang, Maryam Ghandali, Maximilian P. Schwermann, Wafik El-Deiry. The anti-tumor efficacy and immune effects of combining of ceralasertib, an oral ATR kinase inhibitor, with imipridones, in prostate cancer treatment in vitro and in vivo [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5559.

Primary study on frass fertilizers from mass-reared insects: Species variation, heat treatment effects, and implications for soil application at laboratory scale

Insect farming has gained popularity as a resource-efficient and eco-friendly method for managing organic wastes by converting them into high-quality protein, fat, and frass. Insect frass is a powerful organic fertilizer that enriches the soil with essential plant nutrients and enhances plant defense mechanisms through chitin stimulation. Given the importance of frass commercialization for many insect farmers and the use of increasingly diverse organic wastes as insect feedstocks, there is a need for legal guidelines to enable clean production practices. The recent introduction of a legal definition for frass and heat treatment requirements by the EU commission marks a significant step towards standardizing its quality; however, little is known about the processes shaping its nutritional profiles and contributing to its maturation. Our study addresses key knowledge gaps in frass composition and production practices. Here, we analyzed the physicochemical, plant-nutritional, and microbiological properties of black soldier fly, yellow mealworm, and Jamaican field cricket frass from mass-rearing operations and assessed the impact of hygienizing heat treatment on fertilizer properties and frass microbiota. The results showed that frass properties varied significantly across insect species, revealing concentrations of plant-available nutrients as high as 7000 μg NH4+-N, 150 μg NO2–NO3--N, and 20 mg available P per g of total solids. Heat treatment reduced microbial activity, biomass, and viable counts of pathogenic Escherichia coli and Salmonella spp. In terms of frass microbiome composition, alpha diversity showed no significant differences between fresh and heat-treated frass samples; however, significant differences in microbial community composition were observed across the three insect species. Despite heat treatment, soil application of frass reactivated and boosted soil microbial activity, inducing up to a 25-fold increase in microbial respiration, suggesting no long-term detrimental effects on microorganisms. These findings not only enhance our understanding of insect frass as a nutrient-rich organic fertilizer but also have implications for regulatory frameworks, underscoring its promising potential for soil health and nutrient cycling. However, it is important to recognize the primary nature of this research, conducted at laboratory scale and over a short term. Future studies should aim to validate these findings in agricultural settings and explore additional factors influencing frass properties and its (long-term) interaction with soil ecosystems.

The Cost of Developing and Implementing an Antepartum Referral Program for Penicillin Allergy Evaluation at a Single Academic Tertiary Care Hospital.

Approximately 10% of pregnant individuals report a penicillin allergy, yet most are not truly allergic. Allergy verification during pregnancy is safe and recommended; however, many hospitals lack the infrastructure to execute testing. Our aim was to evaluate the cost of developing and implementing a penicillin allergy referral program for pregnant individuals at an academic institution and to compare costs of care between patients who were referred and not referred through the program. We conducted an economic analysis of our institution's antepartum penicillin allergy referral program. We prospectively collected detailed resource utilization data and conducted the analysis from the program's perspective, accounting for costs related to program development, allergy verification, antibiotic cost, and delivery hospitalization. Costs were compared between patients who were referred for evaluation versus patients who were not referred using bivariate tests as well as quantile regression adjusting for baseline differences. A sensitivity analysis was performed for allergy testing cost. All cost estimates were inflation adjusted to 2021 U.S. dollars. The startup cost of program development and educational initiatives was $19,920, or $86 per patient. The median allergy evaluation cost was $397 (interquartile range: $303-$663). There was no significant difference in maternal (median: $13,579 vs. $13,999, p = 0.94) or neonatal (median: $3,565 vs. $3,577, p = 0.55) delivery hospitalization cost or antibiotic cost (median: $1.57 vs. $3.87, p = 0.10) between referred and nonreferred patients. Overall, the total cost per person did not differ significantly between study groups (median: $18,931 vs. $18,314, p = 0.69). The cost of developing a penicillin allergy referral program in pregnancy was modest and did not significantly alter short-term cost of care with potential for long-term cost benefit. Verification of a reported penicillin allergy is an integral part of antibiotic stewardship, and the pregnancy period should be utilized as an important opportunity to perform this evaluation. · The cost of developing and implementing an antepartum penicillin allergy referral program is modest.. · Program cost did not significantly alter short-term cost with a potential for long-term cost benefit.. · Penicillin allergy verification is an important part of antibiotic stewardship and should be expanded..

Exploring the Relationship Between CO2 Emissions and Fuel Consumption in Road Transport: Empirical Evidence from Chad

Over the period 2008-2019, this study examines the linear impact of petroleum product (PP) consumption in Chad, PP prices, the vehicle fleet and urbanisation on CO2 emissions  on the one hand, and on the other, it determines the causal links that exist between the various variables studied. This study opts for the augmented Dickey-Fuller and Phillips-Perron tests to verify the stationarity of the variables. The ARDL model is then estimated and diagnostic tests are performed to confirm the validity of the model. To confirm the existence of long-term relationships, the bounds test was applied. Finally, the Toda-Yamamoto causality test was used to capture the influences present between the series under study. The main results show that, in the long term, a 1% increase in gasoline consumption would lead to a 1.03% increase in CO2 emissions and the linear impact of diesel consumption is positive and insignificant on CO2 emissions. In the short term, gasoline and diesel consumption have a positive and insignificant impact on CO2 emissions. In terms of causality, there is a unidirectional causality from gasoline consumption to CO2 emissions  and a bidirectional causality between CO2 emissions and diesel consumption. This study is the first to simultaneously link CO2 emissions, PP consumption, PP prices, the vehicle fleet and urbanisation in general, and particularly in the case of Chad. It therefore adds to the literature on the simultaneous relationship between CO2 emissions, PP consumption, the car fleet and urbanisation in a global and restricted context.  This study could guide Chadian oil pollution management decision-makers in adopting policies related to the effects of PP consumption in the road transport sector.

Exploring the Nexus between CO2 Emissions, Trade, and Sustainable Economic Growth: A Novel NARDL Approach

This study investigates the nexus between CO2 emission, trade, Gross domestic product (GDP), and tourism in Pakistan during 1990-2019. We examined the asymmetric relationship between CO2 emission, international trade, Gross domestic product (GDP), and international tourism number of arrivals in Pakistan. Data Stationarity has been tested using the Augmented Dicky Fuller (ADF), Kwiatkowski-Phillips-Schmidt-Shin (KPSS), and Phillips-Perron (PP) tests for unit roots. We used the NARDL technique. Then a Granger Causality helped estimate the relationship between these environmental variables. If there is an asymmetric association between these variables, we estimate the non-linear auto-regressive distributed lag, which is the most applicable econometric estimate. The ARDL technique can potentially explore the dynamic nexus between CO2 emission, tourism, GDP, and trade. Our findings suggest a dynamic relationship between tourism, trade, CO2 emission, and GDP from Pakistan's perspective. The outcomes reveal that negative and positive shocks to trade, GDP, and tourism affect CO2 emissions in the short and long term. The Granger Causality findings also determined that causality is directed from Tourism toward CO2 emission, while unidirectional causality was found between CO2 emission and tourism. In this study, the graphs of the CUSUM and CUSUMQ determined the functional stability of the established relationship. This indicates that this model is a suitable and valuable strategy tool. Therefore, an increase or decrease in the macroeconomic series will cause variation in carbon emissions in Pakistan in the long -term. The finding benefits macro-level policymakers and will provide important insight for the relevant stakeholders.

“Cup-in-Cup” for revision cup in total hip arthroplasty – An innovative technique

In a revision hip surgery with isolated poly-ethylene liner wear along with a stable acetabular shell involves difficult decision of revising the entire acetabular component or just the liner. However, unavailability of the similar poly liner in a high risk patient can be dealt with a novel technique of cup in cup by retaining the stable shell and cementing a polyethylene liner over it. A 77-year-old male came with complains of pain in the right hip and limp of 4 months duration after 17 years of a revision hip surgery. Poly-ethylene liner was found worn out intraoperative with both the metal shell and the stem very stable. Same company poly liner was not available. In order to prevent the extensive revision in a high surgical risk patient and to prevent the blood and the bone loss, a new Elite poly-ethylene cement cup was cemented over the old stable cementless metal shell. At 3 years short term follow up patient is able to walk pain free independently. The “cup-in-cup” technique with cemented PE cup into a retained well-fixed and well-positioned metal shell is a good technique in high surgical risk patients and gives promising result at short term follow up.

Fine-Scale (10 m) Dynamics of Smallholder Farming through COVID-19 in Eastern Thailand

This study aims to understand the spatiotemporal changes in patterns of tropical crop cultivation in Eastern Thailand, encompassing the periods before, during, and after the COVID-19 pandemic. Our approach involved assessing the efficacy of high-resolution (10 m) Sentinel-2 dense image time series for mapping smallholder farmlands. We integrated harmonic regression and random forest to map a diverse array of tropical crop types between summer 2017 and summer 2023, including durian, rice, rubber, eucalyptus, oil palm, pineapple, sugarcane, cassava, mangosteen, coconut, and other crops. The results revealed an overall mapping accuracy of 85.6%, with several crop types exceeding 90%. High-resolution imagery demonstrated particular effectiveness in situations involving intercropping, a popular practice of simultaneously growing two or more plant species in the same patch of land. However, we observed overestimation in the majority of the studied cash crops, primarily those located in young plantations with open tree canopies and grass-covered ground surfaces. The adverse effects of the COVID-19 pandemic were observed in specific labor-intensive crops, including rubber and durian, but were limited to the short term. No discernible impact was noted across the entirety of the study timeframe. In comparison, financial gain and climate change appeared to be more pivotal in influencing farmers’ decisions regarding crop cultivation. Traditionally dominant crops such as rice and oil palm have witnessed a discernible decline in cultivation, reflecting a decade-long trend of price drops preceding the pandemic. Conversely, Thai durian has seen a significant upswing even over the pandemic, which ironically served as a catalyst prompting Thai farmers to adopt e-commerce to meet the surging demand, particularly from China.

Impact of the blood group on postoperative CRP and leukocyte levels after primary total hip and knee arthroplasty.

C-reactive protein (CRP)- and leukocyte levels are common parameters to evaluate the inflammatory response after orthopaedic surgery and rule out infectious complications. Nevertheless, both parameters are vulnerable to disturbing biases and therefore leave room for interpretation. Since blood groups are repeatedly discussed to influence inflammatory response, our aim was to observe their impact on CRP and leukocyte levels after total hip and knee arthroplasty (THA/TKA). Short term postoperative CRP and leukocyte levels of 987 patients, who received either primary TKH (n= 479) or THA (n= 508), were retrospectively correlated with their blood group. ABO, Rhesus and a combination of both blood groups were differentiated. CRP levels after TKA were significantly higher in blood type AB than in type A and O on day 2-4 and also than in type A on day 6-8. Leukocyte levels after THA were significantly higher in blood group type O than in type A on day 6-8 while still remaining in an apathological range. We observed no significant differences between Rhesus types and Rhesus types and CRP or leukocyte levels. We observed significantly increased CRP levels after TKA in patients with blood group AB. Since the elevated CRP levels do not account for early periprosthetic infection, surgeons should include this variation in their postoperative evaluation.