Explore the vast range of titles available.

Spin–orbit coupling is an essential mechanism underlying quantum phenomena such as the spin Hall effect and topological insulators 1 . It has been widely studied in well-isolated Hermitian systems, but much less is known about the role dissipation plays in spin–orbit-coupled systems 2 . Here we implement dissipative spin–orbit-coupled bands filled with ultracold fermions, and observe parity-time symmetry breaking as a result of the competition between the spin–orbit coupling and dissipation. Tunable dissipation, introduced by state-selective atom loss, enables us to tune the energy gap and close it at the critical dissipation value, the so-called exceptional point 3 . In the vicinity of the critical point, the state evolution exhibits a chiral response, which enables us to tune the spin–orbit coupling and dissipation dynamically, revealing topologically robust chiral spin transfer when the quantum state encircles the exceptional point. This demonstrates that we can explore non-Hermitian topological states with spin–orbit coupling. Spin–orbit coupling is an important feature of isolated quantum systems, but less is known about how it responds to dissipation. An experiment in a cold atomic gas now shows how these two effects enable topologically robust spin transfer.

The concept of non-Hermiticity has expanded the understanding of band topology, leading to the emergence of counter-intuitive phenomena. An example is the non-Hermitian skin effect (NHSE) 1 , 2 , 3 , 4 , 5 , 6 – 7 , which involves the concentration of eigenstates at the boundary. However, despite the potential insights that can be gained from high-dimensional non-Hermitian quantum systems in areas such as curved space 8 , 9 – 10 , high-order topological phases 11 , 12 and black holes 13 , 14 , the realization of this effect in high dimensions remains unexplored. Here we create a two-dimensional (2D) non-Hermitian topological band for ultracold fermions in spin–orbit-coupled optical lattices with tunable dissipation, which exhibits the NHSE. We first experimentally demonstrate pronounced nonzero spectral winding numbers in the complex energy plane with nonzero dissipation, which establishes the existence of 2D skin effect. Furthermore, we observe the real-space dynamical signature of NHSE in real space by monitoring the centre of mass motion of atoms. Finally, we also demonstrate that a pair of exceptional points are created in the momentum space, connected by an open-ended bulk Fermi arc, in contrast to closed loops found in Hermitian systems. The associated exceptional points emerge and shift with increasing dissipation, leading to the formation of the Fermi arc. Our work sets the stage for further investigation into simulating non-Hermitian physics in high dimensions and paves the way for understanding the interplay of quantum statistics with NHSE. A two-dimensional non-Hermitian topological band is created in an ultracold system of fermions, which exhibits the non-Hermitian skin effect.

The power of machine learning (ML) provides the possibility of analyzing experimental measurements with a high sensitivity. However, it still remains challenging to probe the subtle effects directly related to physical observables and to understand physics behind from ordinary experimental data using ML. Here, we introduce a heuristic machinery by using machine learning analysis. We use our machinery to guide the thermodynamic studies in the density profile of ultracold fermions interacting within SU( N ) spin symmetry prepared in a quantum simulator. Although such spin symmetry should manifest itself in a many-body wavefunction, it is elusive how the momentum distribution of fermions, the most ordinary measurement, reveals the effect of spin symmetry. Using a fully trained convolutional neural network (NN) with a remarkably high accuracy of ~94% for detection of the spin multiplicity, we investigate how the accuracy depends on various less-pronounced effects with filtered experimental images. Guided by our machinery, we directly measure a thermodynamic compressibility from density fluctuations within the single image. Our machine learning framework shows a potential to validate theoretical descriptions of SU( N ) Fermi liquids, and to identify less-pronounced effects even for highly complex quantum matter with minimal prior understanding. The detection of the effects of spin symmetry in momentum distribution of an SU(N)-symmetric Fermi gas has remained challenging. Here, the authors use supervised machine learning to connect the spin multiplicity to thermodynamic quantities associated with different parts of the momentum distribution.

Blurring the boundary between bosons and fermions lies at the heart of a wide range of intriguing quantum phenomena in multiple disciplines, ranging from condensed matter physics and atomic, molecular, and optical physics to high-energy physics. One such example is a multicomponent Fermi gas withSU(N)symmetry that is expected to behave like spinless bosons in the large-Nlimit, where the large number of internal states weakens constraints from the Pauli exclusion principle. However, bosonization inSU(N)fermions has never been established in high dimensions where exact solutions are absent. Here, we report direct evidence for bosonization in aSU(N)fermionic ytterbium gas with tunableNin three dimensions (3D). We measure contacts, the central quantity controlling dilute quantum gases, from the momentum distribution and find that the contact per spin approaches a constant with a1/Nscaling in the low-fugacity regime consistent with our theoretical prediction. This scaling signifies the vanishing role of the fermionic statistics in thermodynamics and allows us to verify bosonization through measuring a single physical quantity. Our work delivers a highly controllable quantum simulator to exchange the bosonic and fermionic statistics through tuning the internal degrees of freedom in any generic dimensions. It also suggests a new route toward exploring multicomponent quantum systems and their underlying symmetries with contacts.

The personalized recommendation of potential friends and book resources is important for improving the personalized service of digital campus. In this context, this paper proposes a recommendation method of potential friends and book classes based on collaborative filtering. The establishment of users profiles and the implicit rating prediction model by mining user demographic attributes and book borrowing features. It can improve social environment and utilization of library resources base on this method. The result shows that the model can effectively improve the quality of personalized service recommendation of potential friends and book resources.

Background: Common symptoms of Chronic Non-atrophic Gastritis (CNAG) include nausea, stomach distension, and abdominal pain. The Houtou Jianweiling Tablet (HTJWT) is a chinese patent medicine (CN1368229A) and it has been used clinically for more than 20 years with proven clinical efficacy in treating CNAG, prompted us to establish the clinical efficacy and safety of HTJWT on patients with mild to moderate CNAG symptoms in Pakistani population. Methods: This phase II, double-blind, randomized, parallel-controlled trial was conducted in a single center between November 2022 and February 2023 in Pakistan. In a ratio of 1:1, total 240 CNAG patients with erosion identified by pathological biopsy and gastroscopy were randomly assigned to control (Omeprazole) group ( n = 120) and the treatment (HTJWT) group ( n = 120). Patients in the treatment group received orally four HTJWT (0.38g/tablet), three times a day and one placebo of Omeprazole enteric-coated tablet prior to breakfast, daily. On the other hand, patients in the control group received one Omeprazole enteric-coated tablet (20 mg/tablet) prior to breakfast and four placebo of HTJWT, thrice a day. The patients consumed the investigated drugs (i.e., treatment and control) treatment regimen was followed for a duration of 28 days. The safety of the patients were evaluated through adverse events, serious adverse events and laboratory tests such as blood biochemistry, urine analysis, liver and renal function tests. Vital signs like; blood pressure, pulse rate, body temperature, respiratory rate for all the patients were recorded. The cardiac status of the patients were assessed through electrocardiogram (ECG). The primary efficacy indicators were the improvement rate of gastric distention and gastralgia as the main clinical symptoms. Secondary indicators were visual analogue score (VAS); improvement rate of secondary clinical symptoms and signs; improvement rate of total clinical signs and symptoms; the disappearance/remission rate of Gastric pain and, remission/disappearance time of gastric distension; and the negative conversion rate of Helicobacter pylori ( H. pylori ). The outcomes among each group were compared using the chi-square test. Results: Patients in both groups had good drug compliance (80%–120%), and there was no statistically significant difference in the patients’ baseline characteristics. The clinical improvement rate was found to be 91.1% in the treatment group and 91.0% in the control group with negligible variation among the two groups ( p = 0.9824; 95% confidence interval: -0.0781–0.0798). Similarly, hardly no difference was found in the negative conversion rate of H. pylori between the treatment group and the control group (i.e., 70.1% and 71.8% respectively, p = 0.8125). There were no significant differences in respiratory rate, vital signs, blood pressure, laboratory results for blood biochemistry, urine analysis, liver and renal function tests between the two groups. The ECG assessment carried out for the treatment and control group revealed no considerable difference. Margin variation in the disappearance time of gastric pain ( p = 0.1860) and remission rate ( p = 0.5784) between the two groups were observed. The control group exhibited a faster remission period for gastrointestinal discomfort indications as compared to treatment group ( p = 0.0430). Only one patient in the control group experienced mild to moderate adverse events, namely,; epigastric pain and dyspepsia. The results were consistent with the intention-to-treat and per-protocol analysis that included patients who were 100% compliant to the assigned therapy. Conclusion: The lower limit of confidence interval (CI, 95%) for the differences in the effective rate between the treatment and the control groups was found to be −0.0781 which is greater than −0.15, hence the treatment group is non-inferior to the control group. The therapeutic dosage used in the trial and treatment period did not cause any significant adverse event, and there were no obvious changes in the ECG profile, vital signs and biochemistry of the patients. Based on the clinical efficacy evaluation and reported adverse events, it can be concluded that the HTJWT is a safe and effective traditional chinese medicine for the treatment of patients suffering from chronic non-atrophic gastritis with mild to moderate symptoms. Clinical Trial Registration : [ www.clinicaltrials.gov ], identifier [NCT04672018].

One of the most interesting directions in quantum simulations with ultracold atoms is the expansion of our capability to investigate exotic topological matter. Using sophisticated atom-light couplings in an atomic system, scientists have demonstrated several iconic lattice models that exhibit non-trivial band topology in a controlled manner.With atom-light couplings in atomic systems, scientists have demonstrated several iconic lattice models that exhibit non-trivial band topology in controlled manners, which expands our capability to investigate exotic topological matter.

To investigate the species composition, reproductive dynamics, and hydrological drivers of fish resources in the early stage in the Guiping section of the Xunjiang River, we conducted a two-year survey (2022–2023) downstream of the Datengxia Dam. A total of 22,464 fish eggs and larvae were collected, representing 6 orders, 17 families, and 67 species, with Cyprinidae (58.2%) as the dominant family. Dominant species included Squaliobarbus curriculus, Gobiidae, Hemiculter leucisculus, and Culter, exhibiting significant interannual variation in abundance. The breeding season peaked from May to September, accounting for 94.6% of annual recruitment. Hydrological conditions strongly influenced reproductive output: the multiple flood pulse periods in 2022 (peak discharge: 29,000 m3/s) yielded 34.997 billion eggs and larvae, whereas reduced flows in 2023 (peak discharge: 12,200 m3/s) led to a 75.4% decline (8.620 billion). Redundancy analysis (RDA) revealed that discharge, water temperature, natural hydrological data, and dissolved oxygen were the primary environmental drivers, explaining 46.11% of variability in larval abundance (p < 0.001). Notably, the proportion of important economic fish, “four major Chinese carps”, plummeted from 4.9% (2022) to less than 0.1% (2023), indicating spawning ground function degradation. Our results demonstrate that flood pulses are essential for sustaining fish recruitment, particularly for pelagic spawning riverine fish like the four major Chinese carps. Their proportion plummeted to less than 0.1% in 2023, highlighting the urgent need for eco-hydrological management in the Xunjiang River.

Huangjing is becoming a new generation of crop. Polygonatum kingianum var. grandifolium (XHJ) is a variant of P. kingianum (DHJ), and they are treated as Huangjing. Unlike other Polygonatum species, the rhizome bud of XHJ can germinate both in spring and autumn, which contributes to its high rhizome yield. However, the molecular mechanism of the autumn shooting of XHJ was still unknown. In the present study, cellular observation, comparative targeted metabolome of phytohormones, and transcriptome analysis between XHJ and DHJ in autumn were conducted. Interestingly, ‘Diterpenoid biosynthesis’ (ko00904) and ‘Plant hormone signal transduction’ (ko04075) were commonly enriched by differentially accumulated phytohormones (DAPs) and differentially expressed genes (DEGs) in all tissues, which indicated the high auxin content, low cytokinin (CTK) content, and low abscisic acid/gibberellin (ABA/GA) ratio might contribute to the XHJ rhizome buds’ differentiation and germination in autumn. Moreover, according to the weighted gene co-expression network analysis (WCGNA), transcript factors (TFs) related to auxin, CTK, GA, and jasmonic acid (JA) metabolism were screened, such as AP2/ERFs , WRKY , and NAC , which deserve further research. In conclusion, we comprehensively illustrated the mechanism of XHJ natural autumn shooting through cytological, metabolic, and transcriptomic analysis, which improves our understanding of the high yield of XHJ rhizomes and the diversity of shooting mechanisms in Polygonatum to lay the foundation for the further development of the Huangjing industry.

The Yuanjiang River, situated in the upper reaches of the Red River, is a crucial component of a biodiversity hotspot in the mountains of southwestern China, supporting a high diversity of fish species. Nevertheless, systematic research on fish diversity in the Yuanjiang River is scarce, scattered, and outdated. In our study, we produced 764 DNA barcodes belonging to 64 fish morphospecies to evaluate fish diversity in the Yuanjiang River. Barcoding gap analysis and DNA-based delimitation approaches achieved a high identification success rate (>93%), indicating that DNA barcoding is a practical approach for delimiting fish in the Yuanjiang River. However, four species were characterized by high levels of intraspecific divergence, generating multiple clades and/or molecular operational taxonomic units (MOTUs), suggesting that these species might comprise undetected species. Meanwhile, two closely related species within the genus Schistura, i.e., S. callichroma and S. caudofurca, cannot be delimited by the DNA barcoding technique, which is indicative of recent speciation. In summary, this study established a reliable DNA barcode reference library for fish species in the Yuanjiang River and revealed previously unknown fish diversity.