Multiple Locations Research Articles

The Social Construction of Living Space: The Role of Place Attachment and Neighbourhood Perception

This study provides a comprehensive assessment of the social construction of living spaces by considering commonly studied variables such as sociodemographic characteristics, socioeconomic factors, and residential location. Additionally, it tests the significance of deeper sociological factors, specifically place attachment, bonds with the local community, and perceptions of the neighbourhood. An analysis, based on a description of the spatial structure of daily activities globally, the construction of living space dispersion indices, and a stepwise linear regression model, identified three types of living spaces: commuting spaces, self-realization spaces, and spaces of care, with different concentration and dispersion patterns. Commuting spaces are typically larger; self-realization takes place in the neighbourhood but is also frequently dispersed across multiple locations; and spaces of care are heavily concentrated. The analysis of subpopulations reveals distinct living space patterns based on two main factors: work and children. However, there are important differences in the age and gender composition of the subpopulations. The concentration/dispersion of living spaces is mainly driven by sociodemographic and socioeconomic factors, but place attachment measures significantly affect their construction. The results encourage further exploration of the subjective, experienced dimension of urban phenomena, going beyond the concept of “living spaces” to think of them as “lived-in spaces”.

Ultrasound-guided nerve hydrodissection of cervical nerve roots for cervical radicular pain in patients with mild and moderate to severe stenosis: a retrospective cohort study

Because fascial entrapment neuropathy can occur in multiple locations, ultrasound-guided nerve hydrodissection has become a key component of the treatment of cervical radicular pain. In this paper, we propose a combination of injectates used for nerve hydrodissection of the cervical nerve roots and compare the clinical outcomes of this treatment among patients with different severities of stenosis. This is a retrospective cohort study designed to compare outcomes between patients with mild stenosis and moderate to severe stenosis. Forty-four patients with mild cervical stenosis and 30 patients with moderate to severe cervical stenosis were consecutively enrolled into two groups. A 10-mL mixture in a single level consisting of 5% in Dextrose, 0.2% lidocaine (Xylocaine), and 4 mg betamethasone (Rinderon) was used for nerve roots hydrodissection. The two groups were compared with regard to their numeric rating scales (NRS) of pain, proportion of patients who exhibited a favorable outcome (a reduction of pain ≥ 50%), duration of patient exhibited a favorable outcome, and occurrence of serious complications and minor side effects. The follow-up period ranged from 3 to 20 months. The NRS of both groups improved significantly by 1 week, 1 month, 3 months, and final follow-up after the initial injection. Differences in the groups’ NRS, proportion of patients who exhibited a favorable outcome, duration of patient exhibited a favorable outcome, and occurrence of serious complications and minor side effects were nonsignificant. There were 4 patients (5.4%) experienced dizziness in that resolved without further treatment. Ultrasound-guided nerve hydrodissection of cervical nerve roots is a safe procedure that reduces pain associated with cervical radicular pain, even in patients with moderate to severe stenosis.

Evolution of Partial Resistance to Artemisinins in Malaria Parasites in Uganda

BackgroundPartial resistance of Plasmodium falciparum to the artemisinin component of artemisinin-based combination therapies, the most important malaria drugs, emerged in Southeast Asia and now threatens East Africa. Partial resistance, which manifests as delayed clearance after therapy, is mediated principally by mutations in the kelch protein K13 (PfK13). Limited longitudinal data are available on the emergence and spread of artemisinin resistance in Africa.MethodsWe performed annual surveillance among patients who presented with uncomplicated malaria at 10 to 16 sites across Uganda from 2016 through 2022. We sequenced the gene encoding kelch 13 (pfk13) and analyzed relatedness using molecular methods. We assessed malaria metrics longitudinally in eight Ugandan districts from 2014 through 2021.ResultsBy 2021–2022, the prevalence of parasites with validated or candidate resistance markers reached more than 20% in 11 of the 16 districts where surveillance was conducted. The PfK13 469Y and 675V mutations were seen in far northern Uganda in 2016–2017 and increased and spread thereafter, reaching a combined prevalence of 10 to 54% across much of northern Uganda, with spread to other regions. The 469F mutation reached a prevalence of 38 to 40% in one district in southwestern Uganda in 2021–2022. The 561H mutation, previously described in Rwanda, was first seen in southwestern Uganda in 2021, reaching a prevalence of 23% by 2022. The 441L mutation reached a prevalence of 12 to 23% in three districts in western Uganda in 2022. Genetic analysis indicated local emergence of mutant parasites independent of those in Southeast Asia. The emergence of resistance was observed predominantly in areas where effective malaria control had been discontinued or transmission was unstable.ConclusionsData from Uganda showed the emergence of partial resistance to artemisinins in multiple geographic locations, with increasing prevalence and regional spread over time. (Funded by the National Institutes of Health.)

Multi-scale assessment of roost selection by 'ōpe'ape'a, the Hawaiian hoary bat (Lasiurus semotus).

The Hawaiian hoary bat (Lasiurus semotus; Chiroptera: Vespertilionidae), commonly and locally known as 'ōpe'ape'a, is a solitary, insectivorous, and foliage-roosting species distributed across a wide range of habitats in lowland and montane environments. The species, as with many others in the Hawaiian archipelago, are facing a suite of challenges due to habitat loss and degradation, introduced predators and pests, and climate change. An understanding of the roost requirements of foliage-roosting tree bats is critical to their conservation as these habitats provide several important benefits to survival and reproduction. Because little is known about 'ōpe'ape'a roost ecology and considerable effort is needed to capture and track bats to roost locations, we examined resource selection at multiple spatial scales-perch location within a roost tree, roost tree, and forest stand. We used a discrete choice modeling approach to investigate day-roost selection and describe attributes of roost trees including those used as maternity roosts. 'Ōpe'ape'a were found roosting in 19 tree species and in an assortment of landcover types including native and non-native habitats. Our results are largely consistent with findings of other studies of foliage-roosting, insectivorous tree bats where bats selected roost locations that may offer protection and thermoregulatory benefits.

Perinephric Transplant Myelolipoma: A Case Report of a Rare Entity

Myelolipomas are benign tumors usually found in adrenal glands. They can also be found extra-adrenally, either in 1 or multiple locations. Perinephric transplant myelolipoma has rarely been reported in the English literature. There's only been 1 instance of such a case reported in a kidney transplant patient, which was found on the explanted kidney. We report a case involving an asymptomatic patient with an ill-defined perinephric transplant mass. The mass was then identified as myelolipoma on biopsy. The patient was then managed conservatively with serial imaging and laboratory testing. At the time of our report, the patient continues to have stable renal function and is doing well 24 months after the mass was first identified. We report the first case of perinephric transplant myelolipoma in a patient with ongoing stable renal allograft function. Based on our case report, we recommended that conservative management with serial imaging and routine testing be considered for patients with perinephric transplant myelolipoma.

Optimal Collaborative Scheduling of Multi-Aircraft Types for Forest Fires General Aviation Rescue

The scheduling of rescue aircraft needs to be studied in depth because of its criticality for the general aviation rescue of forest fires. This paper constructs a collaborative schedule optimization model for general aviation rescue under the condition of multiple aircraft, from multiple rally points to multiple fire points, targeting the shortest rescue time and the lowest rescue cost in the context of forest fires based on the simulation verification of a forest fire that broke out simultaneously in multiple locations in Liangshan Prefecture, Sichuan Province, China. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm was used to find the optimal set of solutions satisfying the objective function: four feasible solutions. Then, the optimal solution was solved based on the weighted TOPSIS method, which was the optimal solution for this rescue task. The simulation results show that unnecessary flight times can be reduced by optimizing the schedule plan. Under the premise of ensuring rescue timeliness, the utilization rate of rescue aircraft was improved, and rescue costs were further reduced. The presented work provides a theoretical reference for the efficient development of general aviation rescue.

Visual attention to features and space in mice using reverse correlation

Visual attention allows the brain to evoke behaviors based on the most important visual features. Mouse models offer immense potential to gain a circuit-level understanding of this phenomenon, yet how mice distribute attention across features and locations is not well understood. Here, we describe a new approach to address this limitation by training mice to detect weak vertical bars in a background of dynamic noise while spatial cues manipulate their attention. By adapting a reverse-correlation method from human studies, we linked behavioral decisions to stimulus features and locations. We show that mice deployed attention to a small rostral region of the visual field. Within this region, mice attended to multiple features (orientation, spatial frequency, contrast) that indicated the presence of weak vertical bars. This attentional tuning grew with training, multiplicatively scaled behavioral sensitivity, approached that of an ideal observer, and resembled the effects of attention in humans. Taken together, we demonstrate that mice can simultaneously attend to multiple features and locations of a visual stimulus.

Morpho-mechanical mapping of human dura mater microstructure

The human dura mater is known to impact vastly traumatic brain injury mechanopathology. In spite of this involvement, dura mater is typically neglected in computational and physical human head models. The lack of location-dependent microstructural and related mechanical data of dura mater may be considered a rationale behind this simplification. The anisotropic nature of dura mater under various loading conditions so far remains unelucidated. Furthermore, principal collagen fiber orientation is yet to be quantified for a morpho-mechanically-informed material model on the dura mater. This study aims to assess how location-dependent mechanical anisotropy is linked to principal collagen fiber orientation. Uniaxial extension tests were performed in a heated tissue bath for 60 samples from six individuals and correlated to the three-dimensional collagen structure in four individuals using second-harmonic generation (SHG) imaging. Failure stress and stretch at failure, elastic modulus, and a microstructurally motivated material model were integrated to examine local differences in dura mater morpho-mechanics. The quantitative observation of collagen fiber orientation and dispersion confirmed that collagen is highly aligned in the human dura mater and that both fiber orientation and dispersion differ depending on the location investigated. This observation provides a possible explanation for the previously observed isotropic mechanical behavior, as the main collagen fiber direction is not oriented along the anterior-posterior or medial-lateral direction at most of the mapped locations. Additionally, these site-dependent structural properties have implications for the mechanical load response and therefore potentially for the regional functions dura mater has to fulfill. The here chosen non-symmetrical fiber dispersion material model fits the data well and provides a comprehensive parameter base for further studies and future finite element models. Statement of significanceThe human dura mater greatly affects traumatic brain injury mechanisms, but it is often ignored in computational and physical head models. This is because there is a lack of detailed microstructural and mechanical data specific to the dura mater. Its anisotropic nature and collagen fiber orientation have not been fully understood, hindering the development of an accurate material model. Hence, this study combines morphological data on collagen fiber orientation and dispersion at multiple locations of human cranial dura mater, and links microstructure to location-specific load-displacement behavior. It provides microstructurally informed mechanical information towards realistic head models for predicting location-dependent tissue behavior and failure for assessing brain injury and graft material development.

IoT BASED SMART ENERGY METER USING LoRa TECHNOLOGY

The objective of this paper is to provide a brief overview of how smart energy meters can benefit from incorporating LoRa-WAN and IoT applications. This paper proposes the use of LoRa-WAN and IoT applications in smart energy meters to enable real-time monitoring and calculation of power consumption. In today's technology-driven world, power management is crucial for the efficient operation of digital systems, and excessive power consumption can lead to system failures. By incorporating a LoRa unit into the design, the system's communication range can be extended to multiple locations within the specified range, as LoRa supports the deployment of numerous nodes. Furthermore, LoRa's bi- directional communication capability enhances the system's functionality. Compared to Wi-Fi-based IoT systems, which typically require multiple access points to cover large areas, the proposed LoRa-based solution offers cost advantages. By implementing the suggested software version on the devices, users can monitor their power consumption remotely and take necessary actions to optimize energy usage. Keywords— Smart Energy Meters, LoRa-WAN, IoT applications, Power Consumption, Long-range Communication, Bi-directional Communication, Cost-effective Solution

Enhancing Indoor Air Quality Estimation: A Spatially Aware Interpolation Scheme

The comprehensive and accurate assessment of the indoor air quality (IAQ) in large spaces, such as offices or multipurpose facilities, is essential for IAQ management. It is widely recognized that various IAQ factors affect the well-being, health, and productivity of indoor occupants. In indoor environments, it is important to assess the IAQ in places where it is difficult to install sensors due to space constraints. Spatial interpolation is a technique that uses sample values of known points to predict the values of other unknown points. Unlike in outdoor environments, spatial interpolation is difficult in large indoor spaces due to various constraints, such as being separated into rooms by walls or having facilities such as air conditioners or heaters installed. Therefore, it is necessary to identify independent or related regions in indoor spaces and to utilize them for spatial interpolation. In this paper, we propose a spatial interpolation technique that groups points with similar characteristics in indoor spaces and utilizes the characteristics of these groups for spatial interpolation. We integrated the IAQ data collected from multiple locations within an office space and subsequently conducted a comparative experiment to assess the accuracy of our proposed method in comparison to commonly used approaches, such as inverse distance weighting (IDW), kriging, natural neighbor interpolation, and the radial basis function (RBF). Additionally, we performed experiments using the publicly available Intel Lab dataset. The experimental results demonstrate that our proposed scheme outperformed the existing methods. The experimental results show that the proposed method was able to obtain better predictions by reflecting the characteristics of regions with similar characteristics within the indoor space.

Context matters when using climate model projections for aquaculture

At present, specific guidance on how to choose, assess and interpret climate model projections for the aquaculture sector is scarce. Since many aspects of aquaculture production are influenced by the local farm-level environment, there is a need to consider how climate model projections can be used to predict potential future farming conditions locally. This study compared in-situ measurements of temperature and salinity from Norwegian salmon farms and fixed monitoring stations to simulations from a regional ocean climate model for multiple locations and depths in southern Norway. For locations considered in this study, a similar seasonal cycle in terms of phasing was visible for modelled and measured temperatures. For some depths and times of the year the modelled and measured temperatures were similar, but for others there were differences. The model tended to underestimate temperature. On occasion there were differences between average modelled and measured temperatures of several degrees and aquaculture users would need to consider the implications of using the modelled temperatures. As for salinity, the model does not include localized freshwater inputs, so the model overestimated salinity for locations close to shore and was not able to represent more brackish water conditions in shallower depths. It was not possible to draw a general conclusion as to whether the model was suitable for aquaculture purposes, as the similarities and differences between the modelled and measured values varied by variable, area, depth, and time. These findings made it clear that aquaculture users would have to implement a process to determine whether they could use climate model outputs for their specific purpose. A model vetting framework is presented that can be used to support decisions on the use of climate model projections for aquaculture purposes. The vetting framework describes four stages that can be used to establish the necessary context regarding the aquaculture requirements and model capabilities, and then check how the model is simulating the conditions of interest at farm sites. Although the focus was aquaculture, the findings are relevant for other sectors and the framework can guide use of climate models for more local-scale assessment and management in coastal locations.

IoT-Based Industrial Debug Message Display Using AWS, ESP8266 And C#

Purpose: In the industrial automation field, debugging is an essential part. Generally, most of the debugging we do in the product development phase and a little bit at the service time. The typical procedure to debug any electronic device is to display a “debug message” inside the terminal window. For this purpose, we commonly use various converters which convert from USB to other ports like RS232, RS485, etc. However, sometimes, we cannot connect our debug cable directly to the working devices. That would be better if the debug message is displayed on the working system terminal without any wire. Here we demonstrate a procedure to display the debug message without any wire. Using the IoT, we do that efficiently. The Code is available on GitHub. Interested researchers can download and continue further research on it. Design/Methodology/Approach: First, We need to create the IoT profile inside the AWS IoT cloud. Using the AWS IoT credential, We update the firmware of the Wifi module. Then it is installed inside the system, which we are debugging. The wifi module’s Transmit and receive pin will be connected to Device’s serial PIN (TX-RX, RX-TX). When the Device sends any debug message through the serial port, it is received by the Wifi module and will update the AWS cloud shadow register. We build an AWS IoT MQTT client in the C# (visual studio. NET). The IoT client fetches the updated data and notifies the UI main thread. One listbox is connected to it. Finally, the UI thread pushes the updated data into the Listbox's first row. Findings/Result: Sometimes, our Device needs to debug without any wire because there is no scope to connect it with the cables. So this procedure can help to debug wirelessly. This procedure has several advantages. Using this debug display eliminates to gets hazards from debugging systems. The debug message can be visible from a remote place. It is also possible to observe the message from multiple remote locations Opening multiple IoT Clients, and subscribing to the same IoT Topic. Originality/Value: The described procedure is a different way to display the debug message. Some advantages are available over traditional procedures. Using this procedure, the researcher can transmit real-time data. It can provide value to the researcher’s work. Using this procedure, the researcher can transmit their sensor data to a remote place. Furthermore, it can save to the remote server for future use. Paper Type: Experimental-based Research.

Sustainability Implications of Supply Chain Responsiveness

Problem definition: A critical decision made by firms is whether to adopt a responsive supply chain (prioritizing speed) or an efficient supply chain (prioritizing cost). We consider the environmental implications of this choice, distinguishing between responsiveness achieved via three pathways: responsive offshore supply chains increase speed by using expedited production and distribution methods; responsive nearshore supply chains increase speed by reducing the physical distance between source and destination for all production; and hybrid nearshore supply chains produce in multiple locations simultaneously, increasing speed by reducing distance on some portion of production. Methodology/results: Using a model wherein responsiveness increases fixed and marginal costs, decreases leadtimes, and changes the per-unit environmental impact of production and distribution, we identify several results. First, all types of responsiveness can decrease environmental impact relative to an efficient supply chain, showing any form of responsiveness has potential to improve sustainability. Second, despite this, all types of responsiveness can also increase environmental impact relative to an efficient supply chain, particularly if demand variability is high. This is precisely when responsiveness is most profitable to the firm, indicating a tension between firm and environmental preferences. Third, a win-win outcome in which responsiveness both maximizes firm profit and minimizes environmental impact is most likely to occur when demand variability is high and unsatisfied customers substitute with a product that generates high environmental impact. Fourth, the firm may have incentive to choose a supply chain that does not minimize (and may maximize) environmental impact, especially at low-to-moderate demand variability. Managerial implications: While responsive supply chains can improve sustainability, they also generate the potential for misalignment of profit and environmental performance. We discuss the implications of this for firms and for policymakers seeking to encourage firms to use supply chains that generate the least environmental impact. Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2022.0152 .

Using Bandit Algorithms to Maximize SARS-CoV-2 Case-Finding: Evaluation and Feasibility Study.

The Flexible Adaptive Algorithmic Surveillance Testing (FAAST) program represents an innovative approach for improving the detection of new cases of infectious disease; it is deployed here to screen and diagnose SARS-CoV-2. With the advent of treatment for COVID-19, finding individuals infected with SARS-CoV-2 is an urgent clinical and public health priority. While these kinds of Bayesian search algorithms are used widely in other settings (eg, to find downed aircraft, in submarine recovery, and to aid in oil exploration), this is the first time that Bayesian adaptive approaches have been used for active disease surveillance in the field. This study's objective was to evaluate a Bayesian search algorithm to target hotspots of SARS-CoV-2 transmission in the community with the goal of detecting the most cases over time across multiple locations in Columbus, Ohio, from August to October 2021. The algorithm used to direct pop-up SARS-CoV-2 testing for this project is based on Thompson sampling, in which the aim is to maximize the average number of new cases of SARS-CoV-2 diagnosed among a set of testing locations based on sampling from prior probability distributions for each testing site. An academic-governmental partnership between Yale University, The Ohio State University, Wake Forest University, the Ohio Department of Health, the Ohio National Guard, and the Columbus Metropolitan Libraries conducted a study of bandit algorithms to maximize the detection of new cases of SARS-CoV-2 in this Ohio city in 2021. The initiative established pop-up COVID-19 testing sites at 13 Columbus locations, including library branches, recreational and community centers, movie theaters, homeless shelters, family services centers, and community event sites. Our team conducted between 0 and 56 tests at the 16 testing events, with an overall average of 25.3 tests conducted per event and a moving average that increased over time. Small incentives-including gift cards and take-home rapid antigen tests-were offered to those who approached the pop-up sites to encourage their participation. Over time, as expected, the Bayesian search algorithm directed testing efforts to locations with higher yields of new diagnoses. Surprisingly, the use of the algorithm also maximized the identification of cases among minority residents of underserved communities, particularly African Americans, with the pool of participants overrepresenting these people relative to the demographic profile of the local zip code in which testing sites were located. This study demonstrated that a pop-up testing strategy using a bandit algorithm can be feasibly deployed in an urban setting during a pandemic. It is the first real-world use of these kinds of algorithms for disease surveillance and represents a key step in evaluating the effectiveness of their use in maximizing the detection of undiagnosed cases of SARS-CoV-2 and other infections, such as HIV.

Midblock Pedestrian Signal Safety Effectiveness

The midblock pedestrian signal (MPS) operates as a coordinated actuated vehicular traffic signal that enables pedestrians to cross at midblock. The MPS has been used in multiple locations, including for more than 40 years in Los Angeles. It differs from a typical pedestrian crossing signal by allowing the red display for vehicular traffic to flash at the same time as the pedestrian timing for the crossing, reducing delay to vehicular traffic. The research team built a database of crash and roadway characteristics data for treated and control sites located in three states (California, Utah, and Texas). Three control groups were considered: all control sites (included intersections with two, three, or four legs and traffic control signals); two-leg sites with any type of pedestrian traffic control other than the MPS; and two-leg sites with nonactive or not present pedestrian traffic control devices. It was found that the MPS is associated with a reduction in the number of crashes involving pedestrians and a reduction in the number of all fatal and injury crashes when the control group is two-leg sites with nonactive or not present pedestrian traffic control devices. The following crash modification factors for the MPS were identified: 0.554 for crashes involving pedestrians; and 0.660 for all crashes.

NDN-RBE: An Accountable Privacy Aware Access Control Framework For NDN

Abstract Named Data Networking (NDN) is an emerging network architecture. An important characteristic of NDN is its in-network cache, which enables Data packets to be available from multiple locations on the Internet. Hence the enforcement of access control mechanisms becomes even more critical in the NDN. This paper proposes a novel access control scheme referred to as Role-Based Encryption for NDN (NDN-RBE), which uses a broadcast encryption mechanism to achieve secure data access control. Our scheme uses the role inheritance property of the traditional Role-Based Access Control (RBAC) model to achieve efficient data access control over hierarchical content. This makes our scheme particularly suitable for large-scale real-world content-centric services like Netflix. Our scheme also supports additional design features such as anonymous signature-based authentication, batch signature verification and two types of privilege revocations. In addition, our formal security analysis demonstrates that our scheme is provably secure against Chosen Plaintext Attacks. Our performance and functionality comparison show that our scheme outperforms other notable existing works in terms of security, functionality, computation, communication and storage overhead. Furthermore, our experimental results show an improvement in content delivery time of the order of 15 percent compared with the other closely related works.

Investigation into the effect of multiple line dipoles magnetic field through LS-3 parabolic trough solar system

This paper simulates the LS-3 parabolic trough solar collector with Monte Carlo Ray Tracing and computational fluid dynamics methods. The heat flux is non-uniform around the absorber tube. Therefore, multiple line dipoles magnetic field location can effect on solar collector performance. There is no article that has investigated the effect of this parameter in the parabolic trough solar collector. Also, this collector is simulated for the first time for June 21 and December 21, and the heat flux distribution for it is provided by the Monte Carlo Ray Tracing method. The multiple line dipoles magnetic field leads to a decrease in the maximum temperature of the absorber tube wall by 2.3 %. The magnetic field intensity also affects the solar collector's performance. If the magnetic flux density is equal to 100 G, 75 G and 50 G, then the value of Performance Evaluation Criteria is equal to 1.47, 1.43 and 1.39, respectively. Finally, the magnetic field location affects the Nusselt number but does not affect the Darcy friction factor. For example, if the multiple dipoles magnetic field are placed at angles of 0, 30, 60, and 90°, then the Nusselt number ratio is 1.50, 1.42, 1.44, and 1.65, respectively.

An investigation on the impact of two vertically aligned drops on a liquid surface

The dynamics of two vertically coalescing drops and a pool of the same liquid have been investigated using a Coupled Level Set and Volume of Fluid (CLSVOF) method. Such a configuration enables us to study the dynamic interaction of an arbitrary-shaped liquid conglomerate, formed owing to drop–drop coalescence, with a pool. Similar to drop–pool and drop–drop interactions, partial coalescence is observed when a conglomerate interacts with a pool. The presence of the pool below the father drop is found to influence the coalescence characteristic of the two drops. At the same time, the movement of the capillary waves resulting from the interaction of two drops governs the coalescence dynamics of the conglomerate with the pool. As liquid interfaces interact and generate capillary waves at multiple locations, complex trajectories of capillary waves are observed, which play a crucial role in determining the pinch-off characteristics of the satellite during conglomerate–pool interaction. We examine the effect of the ratio of the diameters of the lower/father drop to the upper/mother drop (Dr) on the coalescence dynamics while maintaining the size of the mother drop constant. The variation in the coalescence dynamics due to change in Dr is quantified in terms of the residence time (τr), pinch-off time (τp) and the satellite diameter to conglomerate diameter ratio (Ds/Dc). The coalescence dynamics of the conglomerate is then compared with that of an equivalent spherical drop of the same volume and also with that of a drop initialized with the same shape as that of the conglomerate. Finally, the regions of complete and partial coalescence for the conglomerate–pool interactions are demarcated on the Weber number–diameter ratio (We−Dr) space.

In vivo Polycystin-1 interactome using a novel Pkd1 knock-in mouse model.

PKD1 is the most commonly mutated gene causing autosomal dominant polycystic kidney disease (ADPKD). It encodes Polycystin-1 (PC1), a putative membrane protein that undergoes a set of incompletely characterized post-transcriptional cleavage steps and has been reported to localize in multiple subcellular locations, including the primary cilium and mitochondria. However, direct visualization of PC1 and detailed characterization of its binding partners remain challenging. We now report a new mouse model with HA epitopes and eGFP knocked-in frame into the endogenous mouse Pkd1 gene by CRISPR/Cas9. Using this model, we sought to visualize endogenous PC1-eGFP and performed affinity-purification mass spectrometry (AP-MS) and network analyses. We show that the modified Pkd1 allele is fully functional but the eGFP-tagged protein cannot be detected without signal amplification by secondary antibodies. Using nanobody-coupled beads and large quantities of tissue, AP-MS identified an in vivo PC1 interactome, which is enriched for mitochondrial proteins and components of metabolic pathways. These studies suggest this mouse model and interactome data will be useful to understand PC1 function, but that new methods and brighter tags will be required to track endogenous PC1.

Investigating high throughput phenotyping based morpho-physiological and biochemical adaptations of indian pennywort (Centella asiatica L. urban) in response to different irrigation regimes

Indian pennywort (Centella asiatica L. Urban; Apiaceae) is a herbaceous plant used as traditional medicine in several regions worldwide. An adequate supply of fresh water in accordance with crop requirements is an important tool for maintaining the productivity and quality of medicinal plants. The objective of this study was to find a suitable irrigation schedule for improving the morphological and physiological characteristics, and crop productivity of Indian pennywort using high-throughput phenotyping. Four treatments were considered based on irrigation schedules (100, 75, 50, and 25% of field capacity denoted by I100 [control], I75, I50, and I25, respectively). The number of leaves, plant perimeter, plant volume, and shoot dry weight were sustained in I75 irrigated plants, whereas adverse effects on plant growth parameters were observed when plants were subjected to I25 irrigation for 21 days. Leaf temperature (Tleaf) was also retained in I75 irrigated plants, when compared with control. An increase of 2.0 °C temperature was detected in the Tleaf of plants under I25 irrigation treatment when compared with control. The increase in Tleaf was attributed to a decreased transpiration rate (R2 = 0.93), leading to an elevated crop water stress index. Green reflectance and leaf greenness remained unchanged in plants under I75 irrigation, while significantly decreased under I50 and I25 irrigation. These decreases were attributed to declined leaf osmotic potential, increased non-photochemical quenching, and inhibition of net photosynthetic rate (Pn). The asiatic acid and total centellosides in the leaf tissues, and centellosides yield of plants under I75 irrigation were retained when compared with control, while these parameters were regulated to maximal when exposed to I50 irrigation. Based on the results, I75 irrigation treatment was identified as the optimum irrigation schedule for Indian pennywort in terms of sustained biomass and a stable total centellosides. However, further validation in the field trials at multiple locations and involving different crop rotations is recommended to confirm these findings.