Protocol for a comprehensive pipeline to study ancient human genomes.

Ancient genomics has revolutionized our understanding of human evolution and migration history in recent years. Here, we present a protocol to prepare samples for ancient genomics research. We describe steps for releasing DNA from human remains, DNA library construction, hybridization capture, quantification, and sequencing. We then detail procedures for mapping sequence reads and population genetics analysis. This protocol also outlines challenges in extracting ancient DNA samples and authenticating ancient DNA to uncover the genetic history and diversity of ancient populations. For complete details on the use and execution of this protocol, please refer to Tao et al.1.

S-Scheme heterojunction of Cs2SnBr6/C3N4 with interfacial electron exchange toward efficient photocatalytic NO abatement.

Photocatalytic technology is of great significance in environmental purification due to its eco-friendly and cost-effective operations. However, low charge-transfer efficiency restricts the photocatalytic activity of the catalyst. Herein, we report Cs2SnBr6/C3N4 composite catalysts that exhibit a robust interfacial electron exchange thereby enhancing photocatalytic nitric oxide (NO) oxidation. A comprehensive study has demonstrated the S-scheme electron transfer mechanism. Benefiting from the interfacial internal electric field, the C-Br bond serves as a direct electron transfer channel, resulting in enhanced charge separation. Furthermore, the S-scheme heterojunction effectively traps high redox potential electrons and holes, leading to the production of abundant reactive oxygen radicals that enhance photocatalytic NO abatement. The NO removal rate of the Cs2SnBr6/C3N4 heterogeneous system can reach 86.8 %, which is approximately 3-fold and 18-fold that of pristine C3N4 and Cs2SnBr6, respectively. The comprehensive understanding of the electron transfer between heterojunction atomic interfaces will provide a novel perspective on efficient environmental photocatalysis.

Effective model and electron correlations in trilayer nickelate superconductor La4Ni3O10.

Recently, signatures of superconductivity with critical temperature from 20 to 30 K have been reported in pressured trilayer nickelate La4Ni3O10through a pressure-induced structure transition. Here we explore the evolution of electronic structures and electronic correlations in different phases of La4Ni3O10under corresponding pressure regions, by using density functional theory (DFT) combined with dynamical mean-field theory (DMFT). Similar to bilayer superconductor La3Ni2O7, the electronic bands in superconducting La4Ni3O10are dominated by Ni-3dx2-y2and 3dz2orbits near the Fermi level, in contrast, the inner Ni-O plane in La4Ni3O10generates a doublet hole-pocket Fermi surfaces around the Brillouin-zone corner, meanwhile one branch of the Ni-3dz2bands is pushed very close above the Fermi level, which can induce an electron pocket through small electron doping. The DFT+DMFT simulations suggest that the electronic correlations only give minor modification to the Fermi surfaces, meanwhile the Ni-3dz2and 3dx2-y2states on outer Ni-O layers have considerable greater mass enhancements than on the inner layer. The sensitiveness of electronic structure under doping and unique layer dependence of correlation suggest a distinct superconducting mechanism with respect to bilayer La3Ni2O7. Based on the DFT and DFT+DMFT simulations, we eventually derive a trilayer effective tight-binding model, which can produce rather precise electronic bands and Fermi surfaces, hence can serve as an appropriate model to further study the superconducting mechanism and paring symmetry in trilayer La4Ni3O10.

Surface-Enhanced Raman Spectroscopy: Current Understanding, Challenges, and Opportunities.

While surface-enhanced Raman spectroscopy (SERS) has experienced substantial advancements since its discovery in the 1970s, it is an opportunity to celebrate achievements, consider ongoing endeavors, and anticipate the future trajectory of SERS. In this perspective, we encapsulate the latest breakthroughs in comprehending the electromagnetic enhancement mechanisms of SERS, and revisit CT mechanisms of semiconductors. We then summarize the strategies to improve sensitivity, selectivity, and reliability. After addressing experimental advancements, we comprehensively survey the progress on spectrum-structure correlation of SERS showcasing their important role in promoting SERS development. Finally, we anticipate forthcoming directions and opportunities, especially in deepening our insights into chemical or biological processes and establishing a clear spectrum-structure correlation.

The effectiveness of intervention in hepatitis C patients and improvement in their referral rate.

BACKGROUND: To investigate the effectiveness of the intervention with critical value management and push short messaging service (SMS), and to determine improvement in the referral rate of patients with positive hepatitis C antibody (anti-HCV). METHODS: No intervention was done for patients with positive anti-HCV screening results from 1 January 2015 to 31 October 2021. Patients with positive anti-HCV results at our hospital from 1 November 2021 to 31 July 2022 were informed vide critical value management and push SMS. For inpatients, a competent physician was requested to liaise with the infectious disease physician for consultation, and patients seen in the OPD (outpatient department) were asked to visit the liver disease clinic. The Chi-square correlation test, one-sided two-ratio test and linear regression were used to test the relationship between intervention and referral rate. RESULTS: A total of 638,308 cases were tested for anti-hepatitis C virus (HCV) in our hospital and 5983 of them were positive. 51.8% of the referred patients were aged 18-59 years and 10.8% were aged ≥75 years. The result of Chi-square correlation test between intervention and referral was p = .0000, p < .05. One-sided two-ratio test was performed for statistics of pre-intervention referral rate (p1) and post-intervention referral rate (p2). Normal approximation and Fisher's exact test for the results obtained were 0.000, p < .05, and the alternative hypothesis p1 - p2 < 0 was accepted. The linear regression equation was referral = 0.1396 × intervention + 0.3743, and the result model p = 8.79e - 09, p < .05. The model was significant, and the coefficient of intervention was 0.1396. CONCLUSIONS: The interventions of critical value management and push SMS were correlated with the referral rate of patients with positive anti-HCV.

Immune cells mediated the causal relationship between the gut microbiota and lung cancer: a Mendelian randomization study.

Introduction: The gut microbiota (GM) influences the occurrence and progression of lung cancer (LC), with potential involvement of immune cells (IC). We aimed to investigate the causal impact of GM on LC and identify potential immune cell mediators. Methods: The utilized data for the Genome-Wide Association Studies (GWAS) were summarized as follows: gut microbiota data from the Dutch Microbiome Project (DMP) (N = 7,738), lung cancer data from the Transdisciplinary Research in Cancer of the Lung (TRICL) and International Lung Cancer Consortium (ILCCO) (Ncase = 29,266, Ncontrol = 56,450) included four types of cancer: NSCLC, LUAD, LUSC, and SCLC, and immune cell data from European populations (N = 3,757). We employed bi-directional two-sample univariable Mendelian randomization (UVMR), multivariable Mendelian randomization (MVMR), and mediation analysis to assess the causal relationship between GM and LC and potential immune cell mediators. Results: Bi-directional UVMR analysis revealed that 24 gut microbiota species can affect LC, while LC can affect the abundance of 17 gut microbiota species. Mediation analysis demonstrated that six immune cells mediated the causal relationships of seven gut microbiota species on LC: "CCR7 on naive CD8+ T cell" mediated the causal relationship between s_Alistipes_putredinis and LUAD, with a mediation proportion of 9.5% and P = 0.018; "IgD- CD27- B cell %lymphocyte" mediated the causal relationships between g_Gordonibacter and s_Gordonibacter_pamelaeae with LUSC, with mediation proportions of 11.8% and 11.9%, respectively and P = 0.029; "CD20- CD38- B cell %lymphocyte" mediated the causal relationship between s_Bacteroides_clarus and SCLC, with a mediation proportion of 13.8% and P = 0.005; "CD20 on IgD+ CD38- unswitched memory B cell" mediated the causal relationship between s_Streptococcus_thermophilus and SCLC, with a mediation proportion of 14.1% and P = 0.023; "HLA DR on CD14- CD16+ monocyte" mediated the causal relationship between s_Bifidobacterium_bifidum and SCLC, with a mediation proportion of 8.7% and P = 0.012; "CD45 on Granulocytic Myeloid-Derived Suppressor Cells" mediated the causal relationship between f_Lactobacillaceae and SCLC, with a mediation proportion of 4.0% and P = 0.021. Conclusion: This Mendelian randomization study identified several specific gut microbiotas that exhibit causal relationships with lung cancer and potentially mediate immune cells.

Mechanism of muscle atrophy in a normal-weight rat model of type 2 diabetes established by using a soft-pellet diet.

Dietary factors such as food texture affect feeding behavior and energy metabolism, potentially causing obesity and type 2 diabetes. We previously found that rats fed soft pellets (SPs) were neither hyperphagic nor overweight but demonstrated glucose intolerance, insulin resistance, and hyperplasia of pancreatic ß-cells. In the present study, we investigated the mechanism of muscle atrophy in rats that had been fed SPs on a 3-h time-restricted feeding schedule for 24 weeks. As expected, the SP rats were normal weight; however, they developed insulin resistance, glucose intolerance, and fat accumulation. In addition, skeletal muscles of SP rats were histologically atrophic and demonstrated disrupted insulin signaling. Furthermore, we learned that the muscle atrophy of the SP rats developed via the IL-6-STAT3-SOCS3 and ubiquitin-proteasome pathways. Our data show that the dietary habit of consuming soft foods can lead to not only glucose intolerance or insulin resistance but also muscle atrophy.

Impact of co-substrate molecular weight on methane production potential, microbial community dynamics, and metabolic pathways in waste activated sludge anaerobic co-digestion.

Proteins and carbohydrates are important organics in waste activated sludge, and greatly affect methane production and microbial community composition in anaerobic digestion systems. Here, a series of co-substrates with different molecular weight were applied to investigate the interactions between microbial dynamics and the molecular weight of co-substrates. Biochemical methane production assays conducted in batch co-digesters showed that feeding high molecular weight protein and carbohydrate substrates resulted in higher methane yield and production rates. Moreover, high-molecular weight co-substrates increased the microbial diversity, enriched specific microbes including Longilinea, Anaerolineaceae, Syner-01, Methanothrix, promoted acidogenic and acetoclastic methanogenic pathways. Low-molecular weight co-substrates favored the growth of JGI-0000079-D21, Armatimonadota, Methanosarcina, Methanolinea, and improved hydrogenotrophic methanogenic pathway. Besides, Methanoregulaceae and Methanolinea were indicators of methane yield. This study firstly revealed the complex interactions between co-substrate molecular weight and microbial communities, and demonstrated the feasibility of adjusting co-substrate molecular weight to improve methane production process.

Spontaneous miscarriage and social support in predicting risks of depression and anxiety: a cohort study in UK Biobank.

BACKGROUND: It is still unclear whether social support can moderate the high risk of depression and anxiety due to spontaneous miscarriage. OBJECTIVE: This study prospectively investigated the associations of spontaneous miscarriage with risks of depression and anxiety, and evaluated the interactions between spontaneous miscarriage and the degree of social support in relation to depression and anxiety risks. STUDY DESIGN: A total of 179,000 participants from the UK Biobank with pregnancy experience and without depression or anxiety at baseline were included. Spontaneous miscarriage was defined by self-report from participants at enrollment or by International Classification of Diseases codes. The degree of social support was defined as the number of social support factors including living with a spouse or partner, participation in social activities, and confiding. Cox proportional hazards models were used to evaluate the joint association of spontaneous miscarriage and social support with the risks of depression and anxiety. RESULTS: During a median follow-up of 12.3 years, 4939 depression incidents and 5742 anxiety incidents were documented. For participants with 1, 2, and ≥3 spontaneous miscarriages, hazard ratios (95% confidence intervals) for depression were 1.10 (1.02-1.19), 1.31 (1.14-1.50), and 1.40 (1.18-1.67), respectively (P trend <.001), compared with participants without a history of spontaneous miscarriage, after adjustment for covariates. For anxiety, the hazard ratios (95% confidence intervals) were 1.07 (1.00-1.15), 1.04 (0.90-1.19), and 1.21 (1.02-1.44), respectively (P trend=.01). Moreover, we found that the risk of depression associated with a combination of spontaneous miscarriage and low degree of social support in later life was greater than the sum of the risks associated with each individual factor, indicating significant interactions on an additive scale (P interaction=.03). CONCLUSION: Spontaneous miscarriage is associated with higher risks of depression and anxiety, and the risk of depression is further increased when there is also low degree of social support.

Deep Learning-Assisted Spectrum-Structure Correlation: State-of-the-Art and Perspectives.

Spectrum-structure correlation is playing an increasingly crucial role in spectral analysis and has undergone significant development in recent decades. With the advancement of spectrometers, the high-throughput detection triggers the explosive growth of spectral data, and the research extension from small molecules to biomolecules accompanies massive chemical space. Facing the evolving landscape of spectrum-structure correlation, conventional chemometrics becomes ill-equipped, and deep learning assisted chemometrics rapidly emerges as a flourishing approach with superior ability of extracting latent features and making precise predictions. In this review, the molecular and spectral representations and fundamental knowledge of deep learning are first introduced. We then summarize the development of how deep learning assist to establish the correlation between spectrum and molecular structure in the recent 5 years, by empowering spectral prediction (i.e., forward structure-spectrum correlation) and further enabling library matching and de novo molecular generation (i.e., inverse spectrum-structure correlation). Finally, we highlight the most important open issues persisted with corresponding potential solutions. With the fast development of deep learning, it is expected to see ultimate solution of establishing spectrum-structure correlation soon, which would trigger substantial development of various disciplines.

Population dynamics and seasonal migration patterns of Spodoptera exigua in northern China based on 11 years of monitoring data.

Background: The beet armyworm, Spodoptera exigua (Hübner), is an important agricultural pest worldwide that has caused serious economic losses in the main crop-producing areas of China. To effectively monitor and control this pest, it is crucial to investigate its population dynamics and seasonal migration patterns in northern China. Methods: In this study, we monitored the population dynamics of S. exigua using sex pheromone traps in Shenyang, Liaoning Province from 2012 to 2022, combining these data with amigration trajectory simulation approach and synoptic weather analysis. Results: There were significant interannual and seasonal variations in the capture number of S. exigua, and the total number of S. exigua exceeded 2,000 individuals in 2018 and 2020. The highest and lowest numbers of S. exigua were trapped in September and May, accounting for 34.65% ± 6.81% and 0.11% ± 0.04% of the annual totals, respectively. The average occurrence period was 140.9 ± 9.34 days during 2012-2022. In addition, the biomass of S. exigua also increased significantly during these years. The simulated seasonal migration trajectories also revealed varying source regions in different months, primarily originated from Northeast China and East China. These unique insights into the migration patterns of S. exigua will contribute to a deeper understanding of its occurrence in northern China and provide a theoretical basis for regional monitoring, early warning, and the development of effective management strategies for long-range migratory pests.

Assessing Mechanical Properties and Response of Expansive Soft Rock in Tunnel Excavation: A Numerical Simulation Study.

This study investigates the dynamics of moisture absorption and swelling in soft rock during tunnel excavation, emphasizing the response to support resistance. Utilizing COMSOL numerical simulations, we conduct a comparative analysis of various strength criteria and non-associated flow rules. The results demonstrate that the Mohr-Coulomb criterion combined with the Drucker-Prager model under compressive loads imposes stricter limitations on water absorption and expansion than when paired with the Drucker-Prager model under tensile loads. Restricted rock expansion leads to decreased horizontal displacement and ground uplift, increased displacement in the tunnel's bottom arch, and significantly reduced displacement in the top arch. The study also considers the effects of shear dilation, burial depth, and support resistance on the stress and displacement of the surrounding rock. Increased shear dilation angles correlate with greater rock expansion, resulting in increased horizontal displacement and ground uplift. The research study concludes that support resistance is critical in limiting the movement of the tunnel's bottom arch and impacting the stability of the surrounding rock. Additionally, the extent of rock damage during the excavation of expansive soft rock tunnels is found to be minimal. Overall, this study provides valuable insights into the processes of soft rock tunnel excavation and contributes to the development of more efficient support systems.

Smoking timing, genetic susceptibility and the risk of incident type 2 diabetes: A cohort study from the UK Biobank.

AIM: To prospectively assess the association of smoking timing with the risk of type 2 diabetes (T2D) and examine whether smoking amount or genetic susceptibility might modify the relationship. MATERIALS AND METHODS: A total of 294 815 participants without diabetes from the UK Biobank, including non-smokers and smokers with data on the time from waking to first cigarette, were included. Cox proportional hazards models were used to evaluate the association between smoking timing and the risk of incident T2D. RESULTS: During a median follow-up time of 12 years, a total of 9937 incident cases of T2D were documented. Compared with non-smokers, a shorter time from waking to first cigarette was significantly associated with a higher risk of incident T2D (P for trend < .001). In the fully adjusted model, the hazard ratios (HRs) (95% confidence interval) associated with smoking timing were 1.46 (1.17-1.81) for more than 2 hours, 1.51 (1.21-1.87) for 1-2 hours, 1.58 (1.34-1.85) for 30-60 minutes, 1.86 (1.57-2.21) for 5-15 minutes and 2.01 (1.60-2.54) for less than 5 minutes. We found that even among those who reported being light smokers, those with the shortest time from waking to first cigarette had a 105% higher risk of T2D with an HR of 2.05 (1.52-2.76), which was comparable with heavy smokers. The genetic risk score for T2D did not modify this association (P-interaction = .51). CONCLUSIONS: Our findings indicate that shorter time from waking to first cigarette is significantly associated with a higher risk of incident T2D.

A Carbon-Caged Rhodamine Generating Nitrosoperoxycarbonate for Photoimmunotherapy.

Photoimmunotherapy is a promising cancer treatment modality. While potent 1-e- oxidative species are known to induce immunogenic cell death (ICD), they are also associated with unspecific oxidation and collateral tissue damage. This difficulty may be addressed by post-generation radical reinforcement. Namely, non-oxidative radicals are first generated and subsequently activated into powerful oxidative radicals to induce ICD. Here, we developed a photo-triggered molecular donor (NPCD565) of nitrosoperoxycarbonate (ONOOCO2 -), the first of its class to our knowledge, and further evaluated its feasibility for immunotherapy. Upon irradiation of NPCD565 by light within a broad spectral region from ultraviolet to red, ONOOCO2 - is released along with a bright rhodamine dye (RD565), whose fluorescence is a reliable and convenient build-in reporter for the localization, kinetics, and dose of ONOOCO2 - generation. Upon photolysis of NPCD565 in 4T1 cells, damage-associated molecular patterns (DAMPs) indicative of ICD were observed and confirmed to exhibit immunogenicity by induced maturation of dendritic cells. In vivo studies with a bilateral tumor-bearing mouse model showcased the potent tumor-killing capability of NPCD565 of the primary tumors and growth suppression of the distant tumors. This work unveils the potent immunogenicity of ONOOCO2 -, and its donor (NPCD565) has broad potential for photo-immunotherapy of cancer.

Titanium Self-Intercalation Induced Formation of Orthogonal (1 × 1) Edge/Surface Reconstruction in 1T-TiSe2: Atomic Scale Dynamics and Mechanistic Study.

Edges and surfaces play indispensable roles in affecting the chemical-physical properties of materials, particularly in two-dimensional transition metal dichalcogenides (TMDCs) with reduced dimensionality. Herein, we report a novel edge/surface structure in multilayer 1T-TiSe2, i.e., the orthogonal (1 × 1) reconstruction, induced by the self-intercalation of Ti atoms into interlayer octahedral sites of the host TiSe2 at elevated temperature. Formation dynamics of the reconstructed edge/surface are captured at the atomic level by in situ scanning transmission electron microscopy (STEM) and further validated by density functional theory (DFT), which enables the proposal of the nucleation mechanism and two growth routes (zigzag and armchair). Via STEM-electron energy loss spectroscopy (STEM-EELS), a chemical shift of 0.6 eV in Ti L3,2 is observed in the reconstructed edge/surface, which is attributed to the change of the coordination number and lattice distortion. The present work provides insights to tailor the atomic/electronic structures and properties of 2D TMDC materials.

One-step in-situ construction engineering of ZnO-Zn2SnO4 heterojunction for deeply photocatalytic oxidation of nitric oxide.

The generation of hazardous intermediates during the process of photocatalytic nitric oxide (NO) oxidation presents a tough issue. Herein, a one-step microwave strategy was employed to introduce oxygen vacancies (OVs) into zinc oxide-zinc stannate (ZnO-Zn2SnO4) heterojunction, resulting in an improvement in the photocatalytic efficiency for NO removal. The construction ZnO-Zn2SnO4 heterojunction with the OVs (ZSO-3) owns a significant contribution towards highly efficient electron transfer efficiency (99.7%), which renders ZSO-3 to exert a deep oxidation of NO-to-nitrate (NO3-) rather than NO-to-nitrite (NO2-) or NO-to-nitrogen dioxide (NO2). Based on the solid supports of experimental and simulated calculations, it can be found that OVs play an irreplaceable role in activating small molecules such as NO and O2. Moreover, the enhanced adsorption capacity of small molecules, which guarantees the high yield of active radical due to the formation of S-scheme heterojunction. This work illuminates a novel viewpoint on one-step in-situ route to prepare Zn2SnO4-based heterojunction photocatalyst with deep oxidation ability of NO-to-NO3-.

Phonon Thermal Transport in UO_{2} via Self-Consistent Perturbation Theory.

Computing thermal transport from first-principles in UO_{2} is complicated due to the challenges associated with Mott physics. Here, we use irreducible derivative approaches to compute the cubic and quartic phonon interactions in UO_{2} from first principles, and we perform enhanced thermal transport computations by evaluating the phonon Green's function via self-consistent diagrammatic perturbation theory. Our predicted phonon lifetimes at T=600 K agree well with our inelastic neutron scattering measurements across the entire Brillouin zone, and our thermal conductivity predictions agree well with previous measurements. Both the changes due to thermal expansion and self-consistent contributions are nontrivial at high temperatures, though the effects tend to cancel, and interband transitions yield a substantial contribution.

Association of white matter hyperintensities with BMD, incident fractures, and falls in the UK Biobank cohort.

Osteoporosis is the most common metabolic bone disease globally, which increases the healthcare service burden. Recent studies have linked higher white matter hyperintensities (WMH) to reduced BMD, increasing the risk of fractures and falls in older adults. However, limited evidence exists regarding the dose-response relationship between WMH and bone health in a larger and younger population. Our study aimed to examine the association of WMH volume with BMD, incident fractures and falls, focusing on dose-response relationship with varying levels of WMH volume. We included 26 410 participants from the UK Biobank. The association between WMH volume and BMD was analyzed using multiple linear regression. Cox regression models were used to estimate the hazard ratios of incident fractures and falls. Restricted cubic spline (RCS) fitted for linear and Cox regression models were employed to explore potential non-linearity. Over a mean follow-up time of 3.8 yr, we documented 59 hip fractures, 392 all fractures, and 375 fall incidents. When applying RCS, L-shaped relationships were identified between WMH volume and BMD across all 4 sites. Compared with those in the lowest fifth of WMH volume, individuals in the second to the highest fifths were associated with a reduction of 0.0102-0.0305 g/cm2 in femur neck BMD, 0.0075-0.0273 g/cm2 in femur troch BMD, 0.0173-0.0345 g/cm2 in LS BMD, and 0.0141-0.0339 g/cm2 in total body BMD. The association was more pronounced among women and younger participants under age 65 (Pinteraction < .05). Per 1 SD increment of WMH volume was associated with 36.9%, 20.1%, and 14.3% higher risks of incident hip fractures, all fractures, and falls. Genetically determined WMH or apolipoprotein E genotypes did not modify these associations. We demonstrated that a greater WMH was associated with BMD in an L-shaped dose-response manner, especially in women and those under 65 yr.

This study investigated the association between white matter hyperintensities (WMH) and bone health, focusing on BMD, incident fractures and falls. We included 26 410 participants from the UK Biobank and found that a greater WMH volume was associated with BMD in an L-shaped dose­response manner, especially in women and those under 65 yr. Additionally, per 1 SD increment of WMH volume was associated with 36.9%, 20.1%, and 14.3% higher risks of incident hip fractures, all fractures, and falls. These findings emphasize the significance of considering brain health when evaluating bone health.

[Medium and Long-term Carbon Emission Projections and Emission Reduction Potential Analysis of the Lingang Special Area Based on the LEAP Model].

Based on the existing statistical data of the Lingang Special Area in Shanghai and considering its future socio-economic development， industrial structure， and technological development， a LEAP-Lingang model was developed to analyze the evolution trends of energy demand and carbon emissions under the baseline scenario， low-carbon scenario， and enhanced low-carbon scenario. To enhance the prediction accuracy of the model， the Logistic population growth model was used to predict future population data， and the learning curve model was used to simulate the cost evolution trend of related carbon reduction technologies. In addition， an economic evaluation model for carbon reduction technologies was developed， and the economic costs and emission reduction potential of typical carbon reduction technologies were evaluated by drawing a marginal emission reduction cost curve. The results showed that under the enhanced low-carbon scenario， the renewable energy accounted for 69% of the primary energy consumption， and the electric energy accounted for 91% of the terminal energy demand in 2060. The Lingang Special Area could achieve carbon peak by 2030， and the carbon emissions in 2060 were predicted to decrease by 94% compared to that in the baseline scenario. In terms of contribution to emission reduction， clean energy substitution， industrial structure optimization， and terminal energy efficiency improvement played a key role in reducing carbon emissions near the port. In the medium term （until 2035）， they were predicted to contribute 35.1%， 27.3%， and 16.2% of carbon emissions， respectively， and in the long term （until 2060）， they should contribute 50.6%， 8.75%， and 7.7% of carbon emissions， respectively. Regarding specific carbon reduction technologies， hydrogen power generation； water electrolysis for hydrogen； and carbon capture， utilization， and storage （CCUS） technology were of great significance for achieving net-zero emissions， but the costs of emission reduction were relatively high. The research results can provide ideas and references for the low-carbon and green development of the Lingang Special Area and related areas.

Research on SPAD Estimation Model for Spring Wheat Booting Stage Based on Hyperspectral Analysis.

With the rapid progression of agricultural informatization technology, the methodologies of crop monitoring based on spectral technology are constantly upgraded. In order to carry out the efficient, precise and nondestructive detection of relative chlorophyll (SPAD) during the booting stage, we acquired hyperspectral reflectance data about spring wheat vertical distribution and adopted the fractional-order differential to transform the raw spectral data. After that, based on correlation analysis, fractional differential spectra and fractional differential spectral indices with strong correlation with SPAD were screened and fused. Then, the least-squares support vector machine (LSSSVM) and the least-squares support vector machine (SMA-LSSSVM) optimized on the slime mold algorithm were applied to construct the estimation models of SPAD, and the model accuracy was assessed to screen the optimal estimation models. The results showed that the 0.4 order fractional-order differential spectra had the highest correlation with SPAD, which was 9.3% higher than the maximum correlation coefficient of the original spectra; the constructed two-band differential spectral indices were more sensitive to SPAD than the single differential spectra, in which the correlation reached the highest level of 0.724. The SMA-LSSSVM model constructed based on the two-band fractional-order differential spectral indices was better than the single differential spectra and the integration of both, which realized the assessment of wheat SPAD.