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Water security and food security in the Indus basin are highly interlinked and subject to severe stresses. Irrigation water demands presently already exceed what the basin can sustainably provide, but per-capita food availability remains limited. Rapid population growth and climate change are projected to further intensify pressure on the interdependencies between water and food security. The agricultural system of the Indus basin must therefore change and adapt to be able to achieve the associated Sustainable Development Goals (SDGs). The development of robust policies to guide such changes requires a thorough understanding of the synergies and trade-offs that different strategies for agricultural development may have for water and food security. In this study, we defined three contrasting trajectories for agricultural system change based on a review of scientific literature on regional agricultural developments and a stakeholder consultation workshop. We assessed the consequences of these trajectories for water and food security with a spatially explicit modeling framework for two scenarios of climatic and socio-economic change over the period 1980–2080. Our results demonstrate that agricultural system changes can ensure per capita food production in the basin remains sufficient under population growth. However, such changes require additional irrigation water resources and may strongly aggravate water stress. Conversely, a shift to sustainable water management can reduce water stress but has the consequence that basin-level food self-sufficiency may not be feasible in future. This suggests that biophysical limits likely exist that prevent agricultural system changes to ensure both sufficient food production and improve water security in the Indus basin under strong population growth. Our study concludes that agricultural system changes are an important adaptation mechanism toward achieving water and food SDGs, but must be developed alongside other strategies t

The purpose of this paper is to provide an overview of Pakistan's e-commerce industry— with a focus on the online retail sector. E-commerce has changed the face of business across the globe, redefining how organizations and consumers engage commercially. Pakistan's e-commerce market is still in its infancy but shows promise in terms of growth. This study delves into an evaluation of Pakistani laws related to consumer rights within the emerging digital economy of the country, specifically through e-commerce platforms. The essay has discussed various critical topics including product safety and consumer rights, as well as internet frauds— drawing from case studies and legal perception coupled with a review of existing literature which all point towards inadequacies present in the current system exacerbated by the overwhelming penetration of e-commerce. Thus, in order to ensure consumers’ safeguard in Pakistan’s developing digital economy, rigorous regulatory arrangement, proper consumer education, and stakeholder engagement are extremely recommended.

United Nations Agenda 2030 is a call to action for global issues, and sustainability is a challenge that faces everyone. The primary objective of this research is to offer first-hand insights about external financing for sustainability. In order to calculate the impact of foreign financing on eco-efficiency, the Sustainable Development Goals, and the Social, Economic, and Environmental Development of 46 Asian countries between 2000 and 2021, the study used auto-regressive distributed lag (ARDL) models. The estimation's results showed foreign direct investment failed to significantly impact any of the five models over the short- or long-term, remittances, official development assistance, foreign debt, and restriction are useful indicators for advancing social, economic, and environmental development toward eco-efficiency and sustainable development goals. The study also indicated Sustainable development Goals and Social Development are more significant as compared to the other three Models eco-efficiency, economic, and environmental development during the short run and long run. Further indicated South Eastern Asia and East Asia Region Countries have strong requirements for External finance as compared to other Asian regions and external finance had a highly significant relationship with eco-efficiency and Sustainable Development Goals in the short run and long run from 2000 to 2021. Study recommendations are cleared; the Government’s systems should be designed as UN Agenda-2030 that supports the direction toward World Future Sustainability.

United Nations Agenda 2030 is a call to action for global issues, and sustainability is a challenge that faces everyone. The primary objective of this research is to offer first-hand insights about external financing for sustainability. In order to calculate the impact of foreign financing on eco-efficiency, the Sustainable Development Goals, and the Social, Economic, and Environmental Development of 46 Asian countries between 2000 and 2021, the study used auto-regressive distributed lag (ARDL) models. The estimation's results showed foreign direct investment failed to significantly impact any of the five models over the short- or long-term, remittances, official development assistance, foreign debt, and restriction are useful indicators for advancing social, economic, and environmental development toward eco-efficiency and sustainable development goals. The study also indicated Sustainable development Goals and Social Development are more significant as compared to the other three Models eco-efficiency, economic, and environmental development during the short run and long run. Further indicated South Eastern Asia and East Asia Region Countries have strong requirements for External finance as compared to other Asian regions and external finance had a highly significant relationship with eco-efficiency and Sustainable Development Goals in the short run and long run from 2000 to 2021. Study recommendations are cleared; the Government’s systems should be designed as UN Agenda-2030 that supports the direction toward World Future Sustainability.

United Nations Agenda 2030 is a call to action for global issues, and sustainability is a challenge that faces everyone. The primary objective of this research is to offer first-hand insights about external financing for sustainability. In order to calculate the impact of foreign financing on eco-efficiency, the Sustainable Development Goals, and the Social, Economic, and Environmental Development of 46 Asian countries between 2000 and 2021, the study used auto-regressive distributed lag (ARDL) models. The estimation's results showed foreign direct investment failed to significantly impact any of the five models over the short- or long-term, remittances, official development assistance, foreign debt, and restriction are useful indicators for advancing social, economic, and environmental development toward eco-efficiency and sustainable development goals. The study also indicated Sustainable development Goals and Social Development are more significant as compared to the other three Models eco-efficiency, economic, and environmental development during the short run and long run. Further indicated South Eastern Asia and East Asia Region Countries have strong requirements for External finance as compared to other Asian regions and external finance had a highly significant relationship with eco-efficiency and Sustainable Development Goals in the short run and long run from 2000 to 2021. Study recommendations are cleared; the Government’s systems should be designed as UN Agenda-2030 that supports the direction toward World Future Sustainability.

In Malaysia, the button mushroom is recognized as a vegetable with high nutritional value and is easy to grow. To observe the mushrooms' growth, farmers are frequently required to check the crops, which are time-consuming and waste of human resources. Therefore, a detection and measurement system for button mushrooms has been developed based on image processing techniques using the convolutional neural network (CNN) algorithm model known as YOLOv4. Based on the results obtained from the preliminary experiments, the detection and measurement system demonstrate high accuracy in locating position of each button mushroom with only 5% deviation error in predicting the size of each button mushroom.

Currently, a number of techniques are available for detection of Brucella abortus (B. abortus) but these techniques are costly and specialized equipment are needed. Therefore, the development of a rapid, accurate, sensitive, and cost effective technique for identification of Brucella species is of high priority. Objective: The current research study was designed to detect Brucella species more rapidly. The current study area was conducted in district Lodhran, Punjab, Pakistan. Methods: A total 100 blood samples (50 cattle and 50 buffaloes) were collected. Serum samples were screened against B. abortus antibodies using Rose Bengal plate test (RBPT). The specific gene was designed by using NCBI website and whole genome of Brucella species. The primers were designed from Gene accession number 20404. Following primers were designed F3, B3, FIP, BIP, LF, LB, B4, and B5. The LAMP technique for BSCP31 gene was developed by using many concentrations of components and conditions. Results: The development and validation of LAMP assay for detection of B. abortus from bovine blood in the present study proved helpful in early detection of said pathogen in animal and humans. Conclusions: This study will be helpful in prevention and control of animal and human brucellosis in Pakistan.

In Malaysia, the button mushroom is recognized as a vegetable with high nutritional value and is easy to grow. To observe the mushrooms' growth, farmers are frequently required to check the crops, which are time-consuming and waste of human resources. Therefore, a detection and measurement system for button mushrooms has been developed based on image processing techniques using the convolutional neural network (CNN) algorithm model known as YOLOv4. Based on the results obtained from the preliminary experiments, the detection and measurement system demonstrate high accuracy in locating position of each button mushroom with only 5% deviation error in predicting the size of each button mushroom.

Introduction: Despite ambitious plans to quadruple hydropower generation in the Indus basin, a quantitative assessment of the impact of climate change on hydropower availability in the basin is missing. To address this gap, we combine downscaled CMIP6 projections with the Hydropower Potential Exploration (HyPE) model to quantify future hydropower potential available in the upper Indus basin. Methods: HyPE uses a spatial cost-minimization framework to evaluate four classes of hydropower potential, namely theoretical, technical, financial and sustainable, considering various constraints on the siting and sizing of two run-of-river hydropower plant configurations. Results: Under future discharge projections, all classes of potential increase while subbasin changes align with the spatial patterns projected in hydro-climatology. Theoretical potential changes by 3.9–56 %, technical potential by −2.3–46.8 %, financial potential by −8.8–50.4 % and sustainable potential by −6.1–49.7 %. A small decline is observed in the northwestern subbasins where increase in potential is lower than in the southeast. In contrast, with increasing variability in the Indian Summer Monsoon in the future, the southeastern subbasins have the strongest increase in sustainable potential accompanied by higher increase in plant size, decrease in costs and higher variability. The southeastern Satluj subbasin is the hotspot where sustainable potential has the highest increase of up to 145 %. The northwestern Kabul subbasin has the highest decrease of up to −27 %. The Swat subbasin has the lowest variability in sustainable potential while the Jhelum and Indus main subbasins remain the subbasins with the cheapest potential into the future. The performance of future sustainable portfolios differ from the performance of historical portfolios by −11.1–39.9 %. Discussion: Hence, considering future climate in the present-day planning of hydropower will lead to improved performance under a majority of scena

Irrigated wheat production is critical for food security in the Indus basin. Changing climatic and socio-economic conditions are expected to increase wheat demand and reduce irrigation water availability. Therefore, adaptation of irrigated wheat production is essential to achieve the interlinked Sustainable Development Goals for both water and food security. Here, we developed a spatial adaptation pathways methodology that integrates water and food objectives under future climate change and population growth. The results show that strategic combinations between production intensification, laser land leveling, and targeted expansion of irrigated areas can ensure wheat production increases and irrigation water savings in the short term. However, no adaptation pathways can ensure long-term wheat production within the existing irrigation water budget under rapid population growth. Adaptation planning for the Sustainable Development Goals in the Indus basin must therefore address both climatic and population changes, and anticipate that current food production practices may be unsustainable.

Cardiovascular diseases (CVDs) are considered one of the leading causes of death worldwide. Myocardial infarction (MI) is one of the deadliest cardiac diseases that require more consideration. Recently, cardiac magnetic resonance imaging (MRI) has been applied as a standard technique for assessing such diseases. The segmentation of the left ventricle (LV) and myocardium from MRI images is vital in detecting MI disease at its early stages. The automatic segmentation of LV is still challenging due to the complex structures of MRI images, inhomogeneous LV shape and moving organs around the LV, such as the lungs and diaphragm. Thus, this study proposed a convolutional neural network (CNN) model for LV and myocardium segmentation to detect MI. The layers selection and hyper-parameters fine-tuning were applied before the training phase. The model showed robust performance based on the evaluation metrics such as accuracy, sensitivity, specificity, dice score coefficient (DSC), Jaccard index and intersection over union (IOU) with values of 0.86, 0.91, 0.84, 0.81, 0.69 and 0.83, respectively

Wireless Capsule Endoscopy (WCE) allows direct visual inspecting of the full digestive system of the patient without invasion and pain, at the price of a long examination by physicians of a large number of photographs. This research presents a new approach to color extraction to differentiate bleeding frames from normal ones and locate more bleeding areas. We have a dual-system suggestion. We use entire color information on the WCE pictures and the pixel-represented clustering approach to get the clustered centers that characterize WCE pictures as words. Then we evaluate the status of a WCE framework using the nearby SVM and K methods (KNN). The classification performance is 95.75% accurate for the AUC 0.9771% and validates the exciting performance for bleeding classification provided by the suggested approach. Second, we present a two-step approach for extracting saliency maps to emphasize bleeding locations with a distinct color channel mixer to build a first-stage salience map. The second stage salience map was taken with optical contrast.We locate bleeding spots following a suitable fusion approach and threshold. Quantitative and qualitative studies demonstrate that our approaches can correctly distinguish bleeding sites from neighborhoods.

The association of Clinical Frailty Scale (CFS) with COVID-19 mortality has got prognostic value in some research work. National Institute for Heath and Care Excellence (NICE) guidelines suggest use of CFS in making important decisions regarding COVID-19 patients’ management. Objective: To determine the prognostic validity of clinical frailty score with COVID 19 severity among patients presenting to a tertiary care hospital. Methods: It was a comparative cross sectional study carried out at COVID-19 dedicated ICU, HDU and ward, Jinnah Hospital Lahore from January 2021 to June 2021. Forty-eight patients, fulfilling the inclusion criteria, were recruited for the study after informed consent. Subjects were categorized as low and high frailty on basis of CFS score and outcome was evaluated. Data were entered and analyzed using SPSS version 24.0. Results: Among forty-eight subjects included in study, in subjects with age range of 40 - 60 years, 58.3% were having low CFS score and 50.0% were having high score. In low score group, 54.2% had ward stay with nasal or face mask oxygen as compare to 25.0% in high score group. Forty five percent had HDU/CPAP/ BiPAP in low CFS score group as compare to 41.7% and 33.3% required invasive ventilation with high score. (p=.005). Conclusion: COVID-19 patients with high frailty have with increase severity of disease requiring ICU invasive ventilation and increased mortality compared with non-frail patients with COVID-19.

The association of Clinical Frailty Scale (CFS) with COVID-19 mortality has got prognostic value in some research work. National Institute for Heath and Care Excellence (NICE) guidelines suggest use of CFS in making important decisions regarding COVID-19 patients’ management. Objective: To determine the prognostic validity of clinical frailty score with COVID 19 severity among patients presenting to a tertiary care hospital. Methods: It was a comparative cross sectional study carried out at COVID-19 dedicated ICU, HDU and ward, Jinnah Hospital Lahore from January 2021 to June 2021. Forty-eight patients, fulfilling the inclusion criteria, were recruited for the study after informed consent. Subjects were categorized as low and high frailty on basis of CFS score and outcome was evaluated. Data were entered and analyzed using SPSS version 24.0. Results: Among forty-eight subjects included in study, in subjects with age range of 40 - 60 years, 58.3% were having low CFS score and 50.0% were having high score. In low score group, 54.2% had ward stay with nasal or face mask oxygen as compare to 25.0% in high score group. Forty five percent had HDU/CPAP/ BiPAP in low CFS score group as compare to 41.7% and 33.3% required invasive ventilation with high score. (p=.005). Conclusion: COVID-19 patients with high frailty have with increase severity of disease requiring ICU invasive ventilation and increased mortality compared with non-frail patients with COVID-19.

Creatinine is a chemical compound left over from energy-producing processes in your Healthy kidneys that filter creatinine out of the blood. Creatinine exits your body as a waste product in urine. Objective: To examine the impact of vigorous-intensity exercises on serum creatinine concentration among student athletes. Methods: Participants were categorized as the control group (CG=n-15) and the experimental group (EG=n-15). Eight-week self-made vigorous intensity exercise protocol was applied on EG. 5 ml blood was collected from each subject, and similarly, serum creatinine concentration was assessed through a serum creatinine test in a biochemistry laboratory. The results (pre and post-test) were statistically tested by independent t-test, mean, and paired sample t-test as statistical tools. Results: A statistically significant difference was found in the Creatinine level between the pretest and posttest scores of EG (P < 0.05) after the treatment. No significant difference was observed in Creatinine level in CG's pretest and posttest scores (P > 0.05). Conclusions: The study shows a considerable difference in the pre and post-test of the subjects of CG and EG, and thus it is shown that vigorous exercise has a positive impact on kidney functions, particularly on creatinine

Adequate intake of water is essential concerning the upkeep of body function. Water also hydrates discs between the vertebrae in the spine and foils tendons, ligaments, and muscles from becoming tight and stiff. Insufficient water intake may cause health problems, such as kidney stones and urinary tract infections (UTIs) in women, poor physical and psychological performance, improper salivary gland function, dehydration, etc. This commentary aims to unpin the facts about the causes, precautions, and management of risk factors associated with dehydration among athletes. Previous epidemiological studies have shown that exercise causes sweating and resultant loss of fluids, affecting an athlete physically and psychologically. In addition, previous studies have also demonstrated that dehydration negatively influences performance and causes high body temperature or glycogen use and the consequent reduction in muscle reserves. Likewise, the studies also showed that dehydration caused pain in joints and muscles, slowed the healing rate, and increased the chances of injuries. Based on the conclusion of previous studies, dehydration should be rehabilitated by fulfilling the fluid level in the body by consuming clean water, clear broths, ice pops and sports drinks. In severe conditions, oral rehydration therapy, intravenous (IV), is also suggested. The human body comprises 75% water inside cells, blood vessels and between the cells. Without water, living things cannot survive sufficient intake of water help the body to maintain its functions. Likewise, the body loses water throughout the day, as when we breathe, sweat, urinate, and defecate; the body restocks the water by drinking fluids. The body sometimes leads to a state of dehydration when intake is lower than consumption of the body, which causes headaches, lethargy, and constipation. Dehydration is a common problem concerned with fluid and electrolytes among the elderly. Frequently loss of water causes dehydration. Age

Knocked knees are a problem in children and adults, making it challenging to walk or run and causing knee pain. In this problem, the knees gradient inward while the ankles remain spaced apart. Objective: To analyse the impact of endurance exercises on knocked knees as a general health concern. Methods: The study participants were randomly selected from the department of sports science and physical education, University of Punjab, Pakistan. Subjects were categorized as a control group (CG) and an experiential group (EG). Each group was comprised of twenty subjects. All the subjects were informed about the risk and benefits of participation in the study. Thus, written informed consent was taken from each subject. In addition, Ethical approval (293/SPS) was also obtained from the University of the Punjab, Lahore, Pakistan. Results: The mean and standard deviation during the pre-test were 50.60±2.35, and the mean and standard deviation during the post-test was 53.05±2.33. The t value was 1.788, and Sig was .96. Therefore, the table shows no significant difference in CG in knee-knocking before and after training sessions imposed upon EG. The mean and standard deviation of EG during the pre-test was 50.00±2.07, and the mean and standard deviation of EG during the post-test was 58.35±2.20. The t value was 17.376, and Sig was .000. Therefore, there was a significant difference during pre- and post-test EG analysis in knee-knocking. Conclusion: Based on the analysis, the researcher concluded that exercise has a vital role in rehabilitating the knocked knee.

Creatinine is a chemical compound left over from energy-producing processes in your Healthy kidneys that filter creatinine out of the blood. Creatinine exits your body as a waste product in urine. Objective: To examine the impact of vigorous-intensity exercises on serum creatinine concentration among student athletes. Methods: Participants were categorized as the control group (CG=n-15) and the experimental group (EG=n-15). Eight-week self-made vigorous intensity exercise protocol was applied on EG. 5 ml blood was collected from each subject, and similarly, serum creatinine concentration was assessed through a serum creatinine test in a biochemistry laboratory. The results (pre and post-test) were statistically tested by independent t-test, mean, and paired sample t-test as statistical tools. Results: A statistically significant difference was found in the Creatinine level between the pretest and posttest scores of EG (P < 0.05) after the treatment. No significant difference was observed in Creatinine level in CG's pretest and posttest scores (P > 0.05). Conclusions: The study shows a considerable difference in the pre and post-test of the subjects of CG and EG, and thus it is shown that vigorous exercise has a positive impact on kidney functions, particularly on creatinine

Adequate intake of water is essential concerning the upkeep of body function. Water also hydrates discs between the vertebrae in the spine and foils tendons, ligaments, and muscles from becoming tight and stiff. Insufficient water intake may cause health problems, such as kidney stones and urinary tract infections (UTIs) in women, poor physical and psychological performance, improper salivary gland function, dehydration, etc. This commentary aims to unpin the facts about the causes, precautions, and management of risk factors associated with dehydration among athletes. Previous epidemiological studies have shown that exercise causes sweating and resultant loss of fluids, affecting an athlete physically and psychologically. In addition, previous studies have also demonstrated that dehydration negatively influences performance and causes high body temperature or glycogen use and the consequent reduction in muscle reserves. Likewise, the studies also showed that dehydration caused pain in joints and muscles, slowed the healing rate, and increased the chances of injuries. Based on the conclusion of previous studies, dehydration should be rehabilitated by fulfilling the fluid level in the body by consuming clean water, clear broths, ice pops and sports drinks. In severe conditions, oral rehydration therapy, intravenous (IV), is also suggested. The human body comprises 75% water inside cells, blood vessels and between the cells. Without water, living things cannot survive sufficient intake of water help the body to maintain its functions. Likewise, the body loses water throughout the day, as when we breathe, sweat, urinate, and defecate; the body restocks the water by drinking fluids. The body sometimes leads to a state of dehydration when intake is lower than consumption of the body, which causes headaches, lethargy, and constipation. Dehydration is a common problem concerned with fluid and electrolytes among the elderly. Frequently loss of water causes dehydration. Age

The association of Clinical Frailty Scale (CFS) with COVID-19 mortality has got prognostic value in some research work. National Institute for Heath and Care Excellence (NICE) guidelines suggest use of CFS in making important decisions regarding COVID-19 patients’ management. Objective: To determine the prognostic validity of clinical frailty score with COVID 19 severity among patients presenting to a tertiary care hospital. Methods: It was a comparative cross sectional study carried out at COVID-19 dedicated ICU, HDU and ward, Jinnah Hospital Lahore from January 2021 to June 2021. Forty-eight patients, fulfilling the inclusion criteria, were recruited for the study after informed consent. Subjects were categorized as low and high frailty on basis of CFS score and outcome was evaluated. Data were entered and analyzed using SPSS version 24.0. Results: Among forty-eight subjects included in study, in subjects with age range of 40 - 60 years, 58.3% were having low CFS score and 50.0% were having high score. In low score group, 54.2% had ward stay with nasal or face mask oxygen as compare to 25.0% in high score group. Forty five percent had HDU/CPAP/ BiPAP in low CFS score group as compare to 41.7% and 33.3% required invasive ventilation with high score. (p=.005). Conclusion: COVID-19 patients with high frailty have with increase severity of disease requiring ICU invasive ventilation and increased mortality compared with non-frail patients with COVID-19.

Creatinine is a chemical compound left over from energy-producing processes in your Healthy kidneys that filter creatinine out of the blood. Creatinine exits your body as a waste product in urine. Objective: To examine the impact of vigorous-intensity exercises on serum creatinine concentration among student athletes. Methods: Participants were categorized as the control group (CG=n-15) and the experimental group (EG=n-15). Eight-week self-made vigorous intensity exercise protocol was applied on EG. 5 ml blood was collected from each subject, and similarly, serum creatinine concentration was assessed through a serum creatinine test in a biochemistry laboratory. The results (pre and post-test) were statistically tested by independent t-test, mean, and paired sample t-test as statistical tools. Results: A statistically significant difference was found in the Creatinine level between the pretest and posttest scores of EG (P < 0.05) after the treatment. No significant difference was observed in Creatinine level in CG's pretest and posttest scores (P > 0.05). Conclusions: The study shows a considerable difference in the pre and post-test of the subjects of CG and EG, and thus it is shown that vigorous exercise has a positive impact on kidney functions, particularly on creatinine

Knocked knees are a problem in children and adults, making it challenging to walk or run and causing knee pain. In this problem, the knees gradient inward while the ankles remain spaced apart. Objective: To analyse the impact of endurance exercises on knocked knees as a general health concern. Methods: The study participants were randomly selected from the department of sports science and physical education, University of Punjab, Pakistan. Subjects were categorized as a control group (CG) and an experiential group (EG). Each group was comprised of twenty subjects. All the subjects were informed about the risk and benefits of participation in the study. Thus, written informed consent was taken from each subject. In addition, Ethical approval (293/SPS) was also obtained from the University of the Punjab, Lahore, Pakistan. Results: The mean and standard deviation during the pre-test were 50.60±2.35, and the mean and standard deviation during the post-test was 53.05±2.33. The t value was 1.788, and Sig was .96. Therefore, the table shows no significant difference in CG in knee-knocking before and after training sessions imposed upon EG. The mean and standard deviation of EG during the pre-test was 50.00±2.07, and the mean and standard deviation of EG during the post-test was 58.35±2.20. The t value was 17.376, and Sig was .000. Therefore, there was a significant difference during pre- and post-test EG analysis in knee-knocking. Conclusion: Based on the analysis, the researcher concluded that exercise has a vital role in rehabilitating the knocked knee.

Sports injuries are considered a global health problem that needs a special focus on public health to minimize the risk factors of sports injuries [1]. Sports Injuries refer to injuries commonly occurring during sports or exercise, but they are not only confined to sports. It can also appear in our routine life events. Suppose a factory worker can get tennis elbow injuries, and Painter gets shoulder injuries. Likewise, gardeners develop tendinitis even though they may not participate in sports [2]. The common sports injuries are sprains, strains, swollen muscles, shin splints, rotator cuff injuries, knee injuries, fractures, and dislocations. Based on nature, we can divide it into two types, i.e. intrinsic injuries and extrinsic injuries. Intrinsic injuries are those injuries which take place inside the body, while those injuries that take place outside the body are called outside injuries. Sports Injuries can occur in any part of the body, such as bones, joints, muscles, tendons, ligaments and cartilage [3]. Sports injuries may be categorized as chronic or acute sports injuries. Chronic or overuse injuries develop in sports where an athlete needs long-term repetitive motion, like long-distance running, cycling and swimming [4]. Chronic sports injuries include arthritis, tendonitis, tennis elbow, repetitive strain injury (RSI) and runner's knee [5]. Likewise, acute sports injuries consist of those injuries which happen suddenly. Wrist fractures. Ankle sprains. Shoulder dislocations are the best examples of acute sports injuries [5, 6]. In other words, those injuries which take place suddenly and need a short period of recovery are term as acute sports injuries, such as strain, sprain, dislocation and muscle aches etc. Similarly, those injuries that develop gradually and need more time for recovery are called chronic injuries [7]. Poor training, anatomical problems, muscle weakness, tendons, exercising ligaments, and unsafe environments are all causative factors of s

Cardiovascular diseases (CVDs) are considered one of the leading causes of death worldwide. Myocardial infarction (MI) is one of the deadliest cardiac diseases that require more consideration. Recently, cardiac magnetic resonance imaging (MRI) has been applied as a standard technique for assessing such diseases. The segmentation of the left ventricle (LV) and myocardium from MRI images is vital in detecting MI disease at its early stages. The automatic segmentation of LV is still challenging due to the complex structures of MRI images, inhomogeneous LV shape and moving organs around the LV, such as the lungs and diaphragm. Thus, this study proposed a convolutional neural network (CNN) model for LV and myocardium segmentation to detect MI. The layers selection and hyper-parameters fine-tuning were applied before the training phase. The model showed robust performance based on the evaluation metrics such as accuracy, sensitivity, specificity, dice score coefficient (DSC), Jaccard index and intersection over union (IOU) with values of 0.86, 0.91, 0.84, 0.81, 0.69 and 0.83, respectively.

Wireless Capsule Endoscopy (WCE) allows direct visual inspecting of the full digestive system of the patient without invasion and pain, at the price of a long examination by physicians of a large number of photographs. This research presents a new approach to color extraction to differentiate bleeding frames from normal ones and locate more bleeding areas. We have a dual-system suggestion. We use entire color information on the WCE pictures and the pixel-represented clustering approach to get the clustered centers that characterize WCE pictures as words. Then we evaluate the status of a WCE framework using the nearby SVM and K methods (KNN). The classification performance is 95.75% accurate for the AUC 0.9771% and validates the exciting performance for bleeding classification provided by the suggested approach. Second, we present a two-step approach for extracting saliency maps to emphasize bleeding locations with a distinct color channel mixer to build a first-stage salience map. The second stage salience map was taken with optical contrast.We locate bleeding spots following a suitable fusion approach and threshold. Quantitative and qualitative studies demonstrate that our approaches can correctly distinguish bleeding sites from neighborhoods.

Wireless Capsule Endoscopy (WCE) allows direct visual inspecting of the full digestive system of the patient without invasion and pain, at the price of a long examination by physicians of a large number of photographs. This research presents a new approach to color extraction to differentiate bleeding frames from normal ones and locate more bleeding areas. We have a dual-system suggestion. We use entire color information on the WCE pictures and the pixel-represented clustering approach to get the clustered centers that characterize WCE pictures as words. Then we evaluate the status of a WCE framework using the nearby SVM and K methods (KNN). The classification performance is 95.75% accurate for the AUC 0.9771% and validates the exciting performance for bleeding classification provided by the suggested approach. Second, we present a two-step approach for extracting saliency maps to emphasize bleeding locations with a distinct color channel mixer to build a first-stage salience map. The second stage salience map was taken with optical contrast.We locate bleeding spots following a suitable fusion approach and threshold. Quantitative and qualitative studies demonstrate that our approaches can correctly distinguish bleeding sites from neighborhoods.

Cardiovascular diseases (CVDs) are considered one of the leading causes of death worldwide. Myocardial infarction (MI) is one of the deadliest cardiac diseases that require more consideration. Recently, cardiac magnetic resonance imaging (MRI) has been applied as a standard technique for assessing such diseases. The segmentation of the left ventricle (LV) and myocardium from MRI images is vital in detecting MI disease at its early stages. The automatic segmentation of LV is still challenging due to the complex structures of MRI images, inhomogeneous LV shape and moving organs around the LV, such as the lungs and diaphragm. Thus, this study proposed a convolutional neural network (CNN) model for LV and myocardium segmentation to detect MI. The layers selection and hyper-parameters fine-tuning were applied before the training phase. The model showed robust performance based on the evaluation metrics such as accuracy, sensitivity, specificity, dice score coefficient (DSC), Jaccard index and intersection over union (IOU) with values of 0.86, 0.91, 0.84, 0.81, 0.69 and 0.83, respectively

—Cardiovascular diseases (CVDs) are considered one of the leading causes of death worldwide. Myocardial infarction (MI) is one of the deadliest cardiac diseases that require more consideration. Recently, cardiac magnetic resonance imaging (MRI) has been applied as a standard technique for assessing such diseases. The segmentation of the left ventricle (LV) and myocardium from MRI images is vital in detecting MI disease at its early stages. The automatic segmentation of LV is still challenging due to the complex structures of MRI images, inhomogeneous LV shape and moving organs around the LV, such as the lungs and diaphragm. Thus, this study proposed a convolutional neural network (CNN) model for LV and myocardium segmentation to detect MI. The layers selection and hyper-parameters fine-tuning were applied before the training phase. The model showed robust performance based on the evaluation metrics such as accuracy, sensitivity, specificity, dice score coefficient (DSC), Jaccard index and intersection over union (IOU) with values of 0.86, 0.91, 0.84, 0.81, 0.69 and 0.83, respectively.

Wireless Capsule Endoscopy (WCE) allows direct visual inspecting of the full digestive system of the patient without invasion and pain, at the price of a long examination by physicians of a large number of photographs. This research presents a new approach to color extraction to differentiate bleeding frames from normal ones and locate more bleeding areas. We have a dual-system suggestion. We use entire color information on the WCE pictures and the pixel-represented clustering approach to get the clustered centers that characterize WCE pictures as words. Then we evaluate the status of a WCE framework using the nearby SVM and K methods (KNN). The classification performance is 95.75% accurate for the AUC 0.9771% and validates the exciting performance for bleeding classification provided by the suggested approach. Second, we present a two-step approach for extracting saliency maps to emphasize bleeding locations with a distinct color channel mixer to build a first-stage salience map. The second stage salience map was taken with optical contrast.We locate bleeding spots following a suitable fusion approach and threshold. Quantitative and qualitative studies demonstrate that our approaches can correctly distinguish bleeding sites from neighborhoods.

Irrigated wheat production is critical for food security in the Indus basin. Changing climatic and socio-economic conditions are expected to increase wheat demand and reduce irrigation water availability. Therefore, adaptation of irrigated wheat production is essential to achieve the interlinked Sustainable Development Goals for both water and food security. Here, we developed a spatial adaptation pathways methodology that integrates water and food objectives under future climate change and population growth. The results show that strategic combinations between production intensification, laser land leveling, and targeted expansion of irrigated areas can ensure wheat production increases and irrigation water savings in the short term. However, no adaptation pathways can ensure long-term wheat production within the existing irrigation water budget under rapid population growth. Adaptation planning for the Sustainable Development Goals in the Indus basin must therefore address both climatic and population changes, and anticipate that current food production practices may be unsustainable.

Based on the perceptions of the local farmers, this study aims to assess the effects of socioeconomic factors and climatic change on the groundwater livelihood system, with a particular focus on in situ Persian wheels/dug wells. Farmers’ perceptions of climate change and how it is affecting their way of life in the Soan River Basin have also been evaluated to determine the most appropriate adaptive interventions. Information and literature about dug wells was unavailable, which stressed the need to carry out this survey. A structured close-ended questionnaire was designed and administered with as much quantitative data as possible. Random sampling opted for a 5 km buffer zone across the Soan River and its tributaries. Union councils having more than 50% of their area lying in the buffer zone were surveyed, and data was collected. Fifty UCs fell within this criterion, and six dug wells from each Union Council were surveyed. The results of our survey collecting local farmer’s perceptions determined that about 70% of respondents agreed about climate change in the Soan Basin of Pakistan, and 62% of farmers reported that climate change severely impacted their livelihood by affecting agricultural productivity and water availability. Ninety-two percent reported summer becoming hot, 72% highlighted that winters are becoming less cold, and 96% reported that average annual rainfall has decreased compared to 10 years before. About 72% of respondents indicated that available water in their dug wells had decreased, and 80% of respondents explained that their crop yield had decreased compared to 10 years before. Sixty percent preferred drip and 35% sprinkler irrigation as efficient water management practices to cope with water shortages. Ninety-five percent of farmers were ready to use solar pumps for irrigation to tame high pumping costs. The study recommends integrating solar pumping with drip and sprinkler irrigation systems to enhance farmers’ cropped area and productivity. T

Water security and food security in the Indus basin are highly interlinked and subject to severe stresses. Irrigation water demands presently already exceed what the basin can sustainably provide, but per-capita food availability remains limited. Rapid population growth and climate change are projected to further intensify pressure on the interdependencies between water and food security. The agricultural system of the Indus basin must therefore change and adapt to be able to achieve the associated Sustainable Development Goals (SDGs). The development of robust policies to guide such changes requires a thorough understanding of the synergies and trade-offs that different strategies for agricultural development may have for water and food security. In this study, we defined three contrasting trajectories for agricultural system change based on a review of scientific literature on regional agricultural developments and a stakeholder consultation workshop. We assessed the consequences of these trajectories for water and food security with a spatially explicit modeling framework for two scenarios of climatic and socio-economic change over the period 1980–2080. Our results demonstrate that agricultural system changes can ensure per capita food production in the basin remains sufficient under population growth. However, such changes require additional irrigation water resources and may strongly aggravate water stress. Conversely, a shift to sustainable water management can reduce water stress but has the consequence that basin-level food self-sufficiency may not be feasible in future. This suggests that biophysical limits likely exist that prevent agricultural system changes to ensure both sufficient food production and improve water security in the Indus basin under strong population growth. Our study concludes that agricultural system changes are an important adaptation mechanism toward achieving water and food SDGs, but must be developed alongside other strategies that

Cardiovascular diseases (CVDs) are considered one of the leading causes of death worldwide. Myocardial infarction (MI) is one of the deadliest cardiac diseases that require more consideration. Recently, cardiac magnetic resonance imaging (MRI) has been applied as a standard technique for assessing such diseases. The segmentation of the left ventricle (LV) and myocardium from MRI images is vital in detecting MI disease at its early stages. The automatic segmentation of LV is still challenging due to the complex structures of MRI images, inhomogeneous LV shape and moving organs around the LV, such as the lungs and diaphragm. Thus, this study proposed a convolutional neural network (CNN) model for LV and myocardium segmentation to detect MI. The layers selection and hyper-parameters fine-tuning were applied before the training phase. The model showed robust performance based on the evaluation metrics such as accuracy, sensitivity, specificity, dice score coefficient (DSC), Jaccard index and intersection over union (IOU) with values of 0.86, 0.91, 0.84, 0.81, 0.69 and 0.83, respectively

Wireless Capsule Endoscopy (WCE) allows direct visual inspecting of the full digestive system of the patient without invasion and pain, at the price of a long examination by physicians of a large number of photographs. This research presents a new approach to color extraction to differentiate bleeding frames from normal ones and locate more bleeding areas. We have a dual-system suggestion. We use entire color information on the WCE pictures and the pixel-represented clustering approach to get the clustered centers that characterize WCE pictures as words. Then we evaluate the status of a WCE framework using the nearby SVM and K methods (KNN). The classification performance is 95.75% accurate for the AUC 0.9771% and validates the exciting performance for bleeding classification provided by the suggested approach. Second, we present a two-step approach for extracting saliency maps to emphasize bleeding locations with a distinct color channel mixer to build a first-stage salience map. The second stage salience map was taken with optical contrast.We locate bleeding spots following a suitable fusion approach and threshold. Quantitative and qualitative studies demonstrate that our approaches can correctly distinguish bleeding sites from neighborhoods.

Cardiovascular diseases (CVDs) are considered one of the leading causes of death worldwide. Myocardial infarction (MI) is one of the deadliest cardiac diseases that require more consideration. Recently, cardiac magnetic resonance imaging (MRI) has been applied as a standard technique for assessing such diseases. The segmentation of the left ventricle (LV) and myocardium from MRI images is vital in detecting MI disease at its early stages. The automatic segmentation of LV is still challenging due to the complex structures of MRI images, inhomogeneous LV shape and moving organs around the LV, such as the lungs and diaphragm. Thus, this study proposed a convolutional neural network (CNN) model for LV and myocardium segmentation to detect MI. The layers selection and hyper-parameters fine-tuning were applied before the training phase. The model showed robust performance based on the evaluation metrics such as accuracy, sensitivity, specificity, dice score coefficient (DSC), Jaccard index and intersection over union (IOU) with values of 0.86, 0.91, 0.84, 0.81, 0.69 and 0.83, respectively.

Cardiovascular diseases (CVDs) are considered one of the leading causes of death worldwide. Myocardial infarction (MI) is one of the deadliest cardiac diseases that require more consideration. Recently, cardiac magnetic resonance imaging (MRI) has been applied as a standard technique for assessing such diseases. The segmentation of the left ventricle (LV) and myocardium from MRI images is vital in detecting MI disease at its early stages. The automatic segmentation of LV is still challenging due to the complex structures of MRI images, inhomogeneous LV shape and moving organs around the LV, such as the lungs and diaphragm. Thus, this study proposed a convolutional neural network (CNN) model for LV and myocardium segmentation to detect MI. The layers selection and hyper-parameters fine-tuning were applied before the training phase. The model showed robust performance based on the evaluation metrics such as accuracy, sensitivity, specificity, dice score coefficient (DSC), Jaccard index and intersection over union (IOU) with values of 0.86, 0.91, 0.84, 0.81, 0.69 and 0.83, respectively

Wireless Capsule Endoscopy (WCE) allows direct visual inspecting of the full digestive system of the patient without invasion and pain, at the price of a long examination by physicians of a large number of photographs. This research presents a new approach to color extraction to differentiate bleeding frames from normal ones and locate more bleeding areas. We have a dual-system suggestion. We use entire color information on the WCE pictures and the pixel-represented clustering approach to get the clustered centers that characterize WCE pictures as words. Then we evaluate the status of a WCE framework using the nearby SVM and K methods (KNN). The classification performance is 95.75% accurate for the AUC 0.9771% and validates the exciting performance for bleeding classification provided by the suggested approach. Second, we present a two-step approach for extracting saliency maps to emphasize bleeding locations with a distinct color channel mixer to build a first-stage salience map. The second stage salience map was taken with optical contrast.We locate bleeding spots following a suitable fusion approach and threshold. Quantitative and qualitative studies demonstrate that our approaches can correctly distinguish bleeding sites from neighborhoods.

Wireless Capsule Endoscopy (WCE) allows direct visual inspecting of the full digestive system of the patient without invasion and pain, at the price of a long examination by physicians of a large number of photographs. This research presents a new approach to color extraction to differentiate bleeding frames from normal ones and locate more bleeding areas. We have a dual-system suggestion. We use entire color information on the WCE pictures and the pixel-represented clustering approach to get the clustered centers that characterize WCE pictures as words. Then we evaluate the status of a WCE framework using the nearby SVM and K methods (KNN). The classification performance is 95.75% accurate for the AUC 0.9771% and validates the exciting performance for bleeding classification provided by the suggested approach. Second, we present a two-step approach for extracting saliency maps to emphasize bleeding locations with a distinct color channel mixer to build a first-stage salience map. The second stage salience map was taken with optical contrast.We locate bleeding spots following a suitable fusion approach and threshold. Quantitative and qualitative studies demonstrate that our approaches can correctly distinguish bleeding sites from neighborhoods.

Cardiovascular diseases (CVDs) are considered one of the leading causes of death worldwide. Myocardial infarction (MI) is one of the deadliest cardiac diseases that require more consideration. Recently, cardiac magnetic resonance imaging (MRI) has been applied as a standard technique for assessing such diseases. The segmentation of the left ventricle (LV) and myocardium from MRI images is vital in detecting MI disease at its early stages. The automatic segmentation of LV is still challenging due to the complex structures of MRI images, inhomogeneous LV shape and moving organs around the LV, such as the lungs and diaphragm. Thus, this study proposed a convolutional neural network (CNN) model for LV and myocardium segmentation to detect MI. The layers selection and hyper-parameters fine-tuning were applied before the training phase. The model showed robust performance based on the evaluation metrics such as accuracy, sensitivity, specificity, dice score coefficient (DSC), Jaccard index and intersection over union (IOU) with values of 0.86, 0.91, 0.84, 0.81, 0.69 and 0.83, respectively.

A remarkable surge in cooling demand is observed in the last decades. Currently, the cooling market is dominated by mechanical vapor compression chillers which are energy intensive and use harmful chemical refrigerants. Therefore, the current focus of the current research in cooling is the development of unconventional, sustainable cooling systems. In this regard, indirect evaporative coolers have shown significant potential (particularly under hot-dry climates) with high energy efficiency, low cost, water-based sustainable operation, and benign emissions. However, these systems are in the development stage and have not yet been fully commercialized because of certain design challenges. An innovative indirect evaporative cooler is proposed, fabricated, and experimentally tested in this study. Particularly, the study is focused on the development of heat transfer coefficient correlation for the system for commercial-scale design and expansion. This is because the earlier available correlation is based on simple airflow between parallel plates assumption and does not incorporate the effect of the evaporative potential of the system resulting in under/over-estimation of the heat transfer characteristics. The results showed that the proposed system achieved a temperature drop of 20 °C, a cooling capacity of around 180 W, and an overall heat transfer coefficient of up to 30 W/m2K. Moreover, the study presents an experiment-regression-based heat transfer coefficient correlation that satisfactorily captures the effect of outdoor air temperature and airflow rate ratio which are critical in the design of evaporative coolers. The proposed correlation showed a high (±5%) with experimental data thus making it suitable for the future design of IEC systems over assorted operating scenarios.

A remarkable surge in cooling demand is observed in the last decades. Currently, the cooling market is dominated by mechanical vapor compression chillers which are energy intensive and use harmful chemical refrigerants. Therefore, the current focus of the current research in cooling is the development of unconventional, sustainable cooling systems. In this regard, indirect evaporative coolers have shown significant potential (particularly under hot-dry climates) with high energy efficiency, low cost, water-based sustainable operation, and benign emissions. However, these systems are in the development stage and have not yet been fully commercialized because of certain design challenges. An innovative indirect evaporative cooler is proposed, fabricated, and experimentally tested in this study. Particularly, the study is focused on the development of heat transfer coefficient correlation for the system for commercial-scale design and expansion. This is because the earlier available correlation is based on simple airflow between parallel plates assumption and does not incorporate the effect of the evaporative potential of the system resulting in under/over-estimation of the heat transfer characteristics. The results showed that the proposed system achieved a temperature drop of 20 °C, a cooling capacity of around 180 W, and an overall heat transfer coefficient of up to 30 W/m2K. Moreover, the study presents an experiment-regression-based heat transfer coefficient correlation that satisfactorily captures the effect of outdoor air temperature and airflow rate ratio which are critical in the design of evaporative coolers. The proposed correlation showed a high (±5%) with experimental data thus making it suitable for the future design of IEC systems over assorted operating scenarios.

The concept of welfare has multidimensional perspectives in economic literature There is no consensus on the definition of economic welfare among experts as they have paradoxical and divergent views about multidimensional alternatives of the economy. Welfare in any particular region can be extracted from the average level of per capita income, income distribution, poverty, and human development in the region. The present study aims to present interregional comparisons, special attention has been paid to comparing the level of welfare among different regions of Pakistan. The measures acquired to present welfare are district-wise multidimensional poverty, the Gini coefficient, and the Human development index. Moreover, to explore further the Welfare index based on average income and Gini coefficient is calculated for each district across four provinces. The data employed from Pakistan Social and Living Standard Measurements (PSLM) 2005-06 and 2013-14 to measure the level of welfare in districts as well as in provinces. The overall findings elucidate that district-wise inequality exists in terms of income and living conditions to maintain quality of life. The deprivation is more in the majority of the districts in Balochistan and two-thirds of its total districts’ rank deteriorated in 2014-15 followed by KP and Sindh where the rank of one-half of the total districts declined. The welfare conditions of the Punjab districts are much better, and the Federal capital is at the top among all districts of Pakistan. Therefore, it is recommended that the redistribution of resources and allocation of funds through the Public Sector and private sector should be undertaken to reduce these disparities.

Wireless Capsule Endoscopy (WCE) allows direct visual inspecting of the full digestive system of the patient without invasion and pain, at the price of a long examination by physicians of a large number of photographs. This research presents a new approach to color extraction to differentiate bleeding frames from normal ones and locate more bleeding areas. We have a dual-system suggestion. We use entire color information on the WCE pictures and the pixel-represented clustering approach to get the clustered centers that characterize WCE pictures as words. Then we evaluate the status of a WCE framework using the nearby SVM and K methods (KNN). The classification performance is 95.75% accurate for the AUC 0.9771% and validates the exciting performance for bleeding classification provided by the suggested approach. Second, we present a two-step approach for extracting saliency maps to emphasize bleeding locations with a distinct color channel mixer to build a first-stage salience map. The second stage salience map was taken with optical contrast.We locate bleeding spots following a suitable fusion approach and threshold. Quantitative and qualitative studies demonstrate that our approaches can correctly distinguish bleeding sites from neighborhoods.

Wireless Capsule Endoscopy (WCE) allows direct visual inspecting of the full digestive system of the patient without invasion and pain, at the price of a long examination by physicians of a large number of photographs. This research presents a new approach to color extraction to differentiate bleeding frames from normal ones and locate more bleeding areas. We have a dual-system suggestion. We use entire color information on the WCE pictures and the pixel-represented clustering approach to get the clustered centers that characterize WCE pictures as words. Then we evaluate the status of a WCE framework using the nearby SVM and K methods (KNN). The classification performance is 95.75% accurate for the AUC 0.9771% and validates the exciting performance for bleeding classification provided by the suggested approach. Second, we present a two-step approach for extracting saliency maps to emphasize bleeding locations with a distinct color channel mixer to build a first-stage salience map. The second stage salience map was taken with optical contrast.We locate bleeding spots following a suitable fusion approach and threshold. Quantitative and qualitative studies demonstrate that our approaches can correctly distinguish bleeding sites from neighborhoods

Introduction: Despite ambitious plans to quadruple hydropower generation in the Indus basin, a quantitative assessment of the impact of climate change on hydropower availability in the basin is missing. To address this gap, we combine downscaled CMIP6 projections with the Hydropower Potential Exploration (HyPE) model to quantify future hydropower potential available in the upper Indus basin. Methods: HyPE uses a spatial cost-minimization framework to evaluate four classes of hydropower potential, namely theoretical, technical, financial and sustainable, considering various constraints on the siting and sizing of two run-of-river hydropower plant configurations. Results: Under future discharge projections, all classes of potential increase while subbasin changes align with the spatial patterns projected in hydro-climatology. Theoretical potential changes by 3.9–56 %, technical potential by −2.3–46.8 %, financial potential by −8.8–50.4 % and sustainable potential by −6.1–49.7 %. A small decline is observed in the northwestern subbasins where increase in potential is lower than in the southeast. In contrast, with increasing variability in the Indian Summer Monsoon in the future, the southeastern subbasins have the strongest increase in sustainable potential accompanied by higher increase in plant size, decrease in costs and higher variability. The southeastern Satluj subbasin is the hotspot where sustainable potential has the highest increase of up to 145 %. The northwestern Kabul subbasin has the highest decrease of up to −27 %. The Swat subbasin has the lowest variability in sustainable potential while the Jhelum and Indus main subbasins remain the subbasins with the cheapest potential into the future. The performance of future sustainable portfolios differ from the performance of historical portfolios by −11.1–39.9 %. Discussion: Hence, considering future climate in the present-day planning of hydropower will lead to improved performance under a majority of scenario

This archive contains preprocessed input data file setup for running the Hydropower Potential Exploration (HyPE) model for the Upper Indus basin. It contains inputs for running historical or future discharge scenarios. Preprocessed data are based on publicly available datasets described in supporting papers., This archive contains preprocessed input data file setup for running the Hydropower Potential Exploration (HyPE) model for the Upper Indus basin. It contains inputs for running historical or future discharge scenarios. Preprocessed data are based on publicly available datasets described in supporting papers.

The densely populated plains of the lower Indus Basin largely depend on water resources originating in the mountains of the transboundary upper Indus Basin. Recent studies have improved our understanding of this upstream-downstream linkage and the impact of climate change. However, water use in the mountainous part of the Indus and its hydropolitical implications have been largely ignored. This study quantifies the comparative impact of upper Indus water usage, through space and time, on downstream water availability under future climate change and socio-economic development. Future water consumption and relative pressure on water resources will vary greatly across seasons and between the various sub-basins of the upper Indus. During the dry season, the share of surface water required within the upper Indus is high and increasing, and in some transboundary sub-basins future water requirements exceed availability during the critical winter months. In turn this drives spatiotemporal hotspots to emerge in the lower Indus where seasonal water availability is reduced by over 25ĝ€¯% compared to natural conditions. This will play an important, but previously unaccounted for, compounding role in the steep decline of per capita seasonal water availability in the lower Indus in the future, alongside downstream population growth. Increasing consumption in the upper Indus may thus locally lead to water scarcity issues, and increasingly be a driver of downstream water stress during the dry season. Our quantified perspective on the evolving upstream-downstream linkages in the transboundary Indus Basin highlights that long-term shared water management here must account for rapid socio-economic change in the upper Indus and anticipate increasing competition between upstream and downstream riparian states.