Qingdao operates an advanced 3D city map for smart urban management

https://en.people.cn/n3/2025/0530/c98649-20322033.html

A platform on real-scene 3D modeling of the city of Qingdao was launched in March 2021 under the leadership of the Qingdao Institute of Survey and Mapping

Qingdao’s varied topography – marked by hilly terrain and dramatic elevation changes – necessitated the use of oblique aerial imaging to capture raw imagery and build an accurate 3D model. The project team deployed manned fixed-wing aircraft equipped with 150-megapixel, five-lens oblique aerial cameras. The aerial survey covered the entire urban area, achieving a ground resolution of 15 centimeters and maintaining more than 70 percent image overlap to maximize accuracy.

In March 2022, following expert review, the project was officially launched for citywide application. Today, the platform covers Qingdao’s entire land area – 11,000 square kilometers – as well as 800 kilometers of coastline, 49 bays, and seven inhabited islands.

The 3D simulation platform has been shared with over 60 municipal departments. It supports more than 100 key functions, including disaster prevention and mitigation, urban planning, social governance, and urban renewal. The platform also underpins over 70 digital government service applications and records nearly 100 million uses annually. As an example, at the bureau’s headquarters, staff members examined two versions of a digital model for a former mining site in Qingdao’s West Coast New Area. The comparison revealed tangible signs of ecological restoration – more vegetation and a gentler slope. Qingdao is home to 898 legacy mine sites. In the past, inspecting these sites required a full month of on-the-ground efforts. Now, with the help of the 3D model, the same work takes just five days.

Since 2023, the city has carried out annual temporal updates to the city-scale 3D simulation platform, enabling it to track urban changes with precision and support data-driven lysis and evidence-based planning.

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https://english.news.cn/20260606/de8eff009a94407c8eeeb1fdab13d675/c.html

https://www.cell.com/cell/abstract/S0092-8674(26)00571-4?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0092867426005714%3Fshowall%3Dtrue

A joint research led by the CAS Institute of Oceanology in collaboration with the Hong Kong-based Chinese University of Hong Kong and Northwestern Polytechnical University in Xi’an deciphered the mechanism of ultra-long starvation tolerance in deep-sea isopods and provides an important paradigm for understanding how life balances growth and survival in extreme environments.

The deep sea is cold, dark, and almost entirely devoid of reliable nutrition, making long-term survival a remarkable evolutionary feat. To survive the abyss, the isopod possesses an enormous stomach that occupies about two-thirds of its body and acts like a deep-freeze pantry, allowing it to gorge when food is available and store the haul for months or even years. Second, it maintains an exceptionally low basal metabolic rate, essentially putting itself on permanent energy-saving mode. Together, these traits turn opportunistic binge eating into an ultra-long energy reserve.

In addition, a key gene involved in this metabolic slowdown, named ND1, is not originally part of the isopod’s own genome. The isopod “hijacks” it from an external symbiotic bacterium through horizontal gene transfer.

To verify ND1’s function, the researchers inserted the gene into zebrafish, nematodes, and human cells in the lab. Under normal temperatures, the gene recipients burned energy faster and became less tolerant of starvation. However, under cold conditions that mimic the isopod’s deep-sea home, ND1 suppressed energy metabolism, reduced mitochondrial activity, and boosted starvation endurance in zebrafish by a remarkable 37 percent.

This temperature-dependent switch solves the so-called “energy paradox” — how can a giant animal with high energy demands survive where food is extremely scarce? The ND1 acts as a metabolic thermostat, fine-tuning energy burn in response to environmental conditions. It provides a solution to the trade-off between body size and food scarcity.

http://english.cas.cn/newsroom/research-news/202606/t20260608_1161380.shtml

https://onlinelibrary.wiley.com/doi/10.1002/mlf2.70089

Researchers from the CAS Qingdao Institute of Bioenergy and Bioprocess Technology (QIBEBT) and Shenzhen Third People’s Hospital have developed a Ramanome-based phenotypic platform to improve the efficiency of bacteriophage evaluation for potential clinical use.

By combining Raman spectroscopy with a random forest model, the researchers introduced the Ramanome-based Phage Susceptibility Test (RPST). This phenotypic method reduces the turnaround time for host range verification to approximately one hour, compared to the 11–21 hours typically required by traditional plaque-based assays.

Bacteriophages offer a precise alternative to antibiotics in the fight against antimicrobial resistance. However, matching phages to clinical bacterial isolates remains challenging due to their narrow host ranges and the slow, qualitative nature of conventional assays.

The RPST framework monitors bacterial metabolic changes within 40 minutes of phage-host co-incubation and identifies four conserved Raman spectral biomarker regions linked to nucleic acids, proteins, and lipids. Combining these biomarkers into a Composite Infection Index (CII), the system achieved a 96.0% concordance rate across 25 phage-host pairs.

Unlike static assays, the continuous CII metric estimates the fraction of infected cells, enabling researchers to rank phage potency and determine the minimum MOI required to sustain infection.

While the method shows operational promise, the researchers acknowledge the need for large-scale, multi-center validation across different instruments to ensure long-term clinical reproducibility.

https://j.people.com.cn/n3/2026/0527/c94476-20460938.html

The Haier Group has announced an ultra-lightweight, artificial intelligence (AI)-powered exoskeleton robot designed to assist with movement. The company claims that using this robot can reduce physical energy expenditure by up to 37%.

The W3 features a “full carbon fiber + titanium alloy” design, resulting in a main unit weight of just 1.75 kilograms (kg). Equipped with the AI ​​Gait Algorithm 3.0 and built-in multi-dimensional sensors, the device can interpret a user’s movement intentions in milliseconds. Furthermore, it utilizes a “high-torque dual-motor + high-energy battery” system; the maximum assistive force per leg reaches 16 Newton-meters (N·m), effectively reducing the physical load on the body by approximately 5 kg.

According to Haier, the robot also features a “short-stride walking” mode designed to accommodate the specific gait characteristics of elderly individuals—namely, reduced muscle strength and a shortened stride length. By precisely compensating for muscle weakness, the device aims to enable a more stable and secure walking experience.

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