页岩气井地质工程套管变形类型及影响因素研究进展

通过调研国内外大量页岩气井套管变形方面的文献,总结了页岩气井套管变形的类型,探讨了深、浅层页岩气套管变形影响因素差异及面临的问题,并提出了针对性的防治措施及下一步主要研究方向。研究结果表明:(1)页岩气井套管变形类型主要包括挤压缩径变形和剪切变形,深层页岩气井出现套管变形的概率较中浅层更大,主要为剪切变形。(2)造成套管变形的工程因素包括井筒降温、固井质量、套管疲劳、套管质量以及井眼狗腿度等,地质因素包括岩石力学特性、非均匀地应力以及天然裂缝/断层滑移等;深层页岩气井套管变形主要受天然裂缝/断层滑移的影响。(3)页岩气井套管变形风险防治措施包括控制井筒温度及注入强度,采用水泥环力学性能参数较低的水泥进行固井作业,适当减小套管外径、增大壁厚、提升钢级等提高套管质量,以及尽量让井轨迹平滑等;对深层页岩气井可通过将井眼水平段延伸方向与岩层层理方向设计为一致,掌握裂缝分布情况、尽量避开高风险剪切滑移层段,对不同级别滑移风险层段合理降低压裂规模、调整井筒方位等措施来降低套管剪切变形的风险。(4)页岩气井套管变形防治研究方向主要包括优选岩石力学特性好的压裂层段、最优井轨迹与地应力的关系分析、裂缝识别与评价、断层滑移量与套变量计算等方面。

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

Learning-based user association and dynamic resource allocation in multi-connectivity enabled unmanned aerial vehicle networks

Unmanned Aerial Vehicles(UAvs)as aerial base stations to provide communication services for ground users is a flexible and cost-effective paradigm in B5G.Besides,dynamic resource allocation and multi-connectivity can be adopted to further harness the potentials of UAVs in improving communication capacity,in such situations such that the interference among users becomes a pivotal disincentive requiring effective solutions.To this end,we investigate the Joint UAV-User Association,Channel Allocation,and transmission Power Control(J-UACAPC)problem in a multi-connectivity-enabled UAV network with constrained backhaul links,where each UAV can determine the reusable channels and transmission power to serve the selected ground users.The goal was to mitigate co-channel interference while maximizing long-term system utility.The problem was modeled as a cooperative stochastic game with hybrid discrete-continuous action space.A Multi-Agent Hybrid Deep Reinforcement Learning(MAHDRL)algorithm was proposed to address this problem.Extensive simulation results demonstrated the effectiveness of the proposed algorithm and showed that it has a higher system utility than the baseline methods.

Virtual Power Plants for Grid Resilience: A Concise Overview of Research and Applications

The power grid is undergoing a transformation from synchronous generators(SGs) toward inverter-based resources(IBRs). The stochasticity, asynchronicity, and limited-inertia characteristics of IBRs bring about challenges to grid resilience. Virtual power plants(VPPs) are emerging technologies to improve the grid resilience and advance the transformation. By judiciously aggregating geographically distributed energy resources(DERs) as individual electrical entities, VPPs can provide capacity and ancillary services to grid operations and participate in electricity wholesale markets. This paper aims to provide a concise overview of the concept and development of VPPs and the latest progresses in VPP operation, with the focus on VPP scheduling and control. Based on this overview, we identify a few potential challenges in VPP operation and discuss the opportunities of integrating the multi-agent system(MAS)-based strategy into the VPP operation to enhance its scalability, performance and resilience.

Guaranteed Cost Attitude Tracking Control for Uncertain Quadrotor Unmanned Aerial Vehicle Under Safety Constraints

In this paper,guaranteed cost attitude tracking con-trol for uncertain quadrotor unmanned aerial vehicle(QUAV)under safety constraints is studied.First,an augmented system is constructed by the tracking error system and reference system.This transformation aims to convert the tracking control prob-lem into a stabilization control problem.Then,control barrier function and disturbance attenuation function are designed to characterize the violations of safety constraints and tolerance of uncertain disturbances,and they are incorporated into the reward function as penalty items.Based on the modified reward function,the problem is simplified as the optimal regulation problem of the nominal augmented system,and a new Hamilton-Jacobi-Bellman equation is developed.Finally,critic-only rein-forcement learning algorithm with a concurrent learning tech-nique is employed to solve the Hamilton-Jacobi-Bellman equa-tion and obtain the optimal controller.The proposed algorithm can not only ensure the reward function within an upper bound in the presence of uncertain disturbances,but also enforce safety constraints.The performance of the algorithm is evaluated by the numerical simulation.

A New Definition of P-Value Involving the Maximum Likelihood Estimator

We present here an alternative definition of the P-value for statistical hypothesis test of a real-valued parameter for a continuous random variable X. Our approach uses neither the notion of Type I error nor the assumption that null hypothesis is true. Instead, the new P-value involves the maximum likelihood estimator, which is usually available for a parameter such as the mean μ or standard deviation σ of a random variable X with a common distribution.

Beyond Defense: Proactive Approaches to Disaster Recovery and Threat Intelligence in Modern Enterprises

As cyber threats keep changing and business environments adapt, a comprehensive approach to disaster recovery involves more than just defensive measures. This research delves deep into the strategies required to respond to threats and anticipate and mitigate them proactively. Beginning with understanding the critical need for a layered defense and the intricacies of the attacker’s journey, the research offers insights into specialized defense techniques, emphasizing the importance of timely and strategic responses during incidents. Risk management is brought to the forefront, underscoring businesses’ need to adopt mature risk assessment practices and understand the potential risk impact areas. Additionally, the value of threat intelligence is explored, shedding light on the importance of active engagement within sharing communities and the vigilant observation of adversary motivations. “Beyond Defense: Proactive Approaches to Disaster Recovery and Threat Intelligence in Modern Enterprises” is a comprehensive guide for organizations aiming to fortify their cybersecurity posture, marrying best practices in proactive and reactive measures in the ever-challenging digital realm.

Closing the Gap: Boosting Women’s Representation in Cybersecurity Leadership

The research consistently highlights the gender disparity in cybersecurity leadership roles, necessitating targeted interventions. Biased recruitment practices, limited STEM education opportunities for girls, and workplace culture contribute to this gap. Proposed solutions include addressing biased recruitment through gender-neutral language and blind processes, promoting STEM education for girls to increase qualified female candidates, and fostering inclusive workplace cultures with mentorship and sponsorship programs. Gender parity is crucial for the industry’s success, as embracing diversity enables the cybersecurity sector to leverage various perspectives, drive innovation, and effectively combat cyber threats. Achieving this balance is not just about fairness but also a strategic imperative. By embracing concerted efforts towards gender parity, we can create a more resilient and impactful cybersecurity landscape, benefiting industry and society.

Improved Units of Measure in Rotational Mechanics

The SI system of units in rotational mechanics yields correct numerical results, but it produces physically incorrect units of measure in many cases. SI units also violate the principle of general covariance—the general rule for defining continuous coordinates and units in mathematics and mathematical physics. After 30+ years of wrestling with these problems, the ultimate authority on units of measure has declared that Newton–meter and Joule are not equivalent in rotational mechanics, as they are in the rest of physics. This article proposes a simple modification to SI units called “Nonstandard International units” (“NI units”) until a better name is agreed upon. NI units yield correct numerical results and physically correct units of measure, and they satisfy the principle of general covariance. The main obstacle to the adoption of NI units is the consensus among users that the radius of rotation should have the unit meter because the radius can be measured with a ruler. NI units assigned to radius should have units meter/radian because the radius is a conversion factor between angular size and circumferential length, as in arclength = rθ. To manage the social consensus behind SI units, the author recommends retaining SI units as they are, and informing users who want correct units that NI units solve the technical problems of SI units.

Momentum as Translations at Conformal Infinity

Although General Relativity is the classic example of a physical theory based on differential geometry, the momentum tensor is the only part of the field equation that is not derived from or interpreted with differential geometry. This work extends General Relativity and Einstein-Cartan theory by augmenting the Poincaré group with projective (special) conformal transformations, which are translations at conformal infinity. Momentum becomes a part of the differential geometry of spacetime. The Lie algebra of these transformations is represented by vectorfields on an associated Minkowski fiber space. Variation of projective conformal scalar curvature generates a 2-index tensor that serves as linear momentum in the field equations of General Relativity. The computation yields a constructive realization of Mach’s principle: local inertia is determined by local motion relative to mass at conformal infinity in each fiber. The vectorfields have a cellular structure that is similar to that of turbulent fluids.

Analysis of Historic Pavement and Bridge Conditions and Alternative Funding Levels for the Michigan Department of Transportation

In 1997 the Michigan Department of Transportation (MDOT) established an ambitious set of condition targets for its pavements and bridges, and the Department received increased revenue from a 4-cent-per-gallon increase in the state motor fuels tax to help meet its targets. However, over time, actual revenue was less than both what was initially estimated as needed to meet the targets and what was projected from the tax increase. Consequently, actual conditions were projected to fall short of the target levels, so the department issued bonds to address the shortfall through 2012. To support deliberations on future funding, in 2013 MDOT performed an analysis of historic conditions to determine what additional fuel tax revenues would have been required beginning in 1997 to: replace bond revenues used to fund pavement and bridge projects from 1997 to 2012;and enable MDOT to meet its condition targets. The analysis was performed using data on actual pavement and bridge funding and conditions;as well as predicted funding and conditions for different hypothetical increases in fuel taxes. The analysis concluded that, in addition to the actual increase of 4 cents per gallon, a fuel tax increase of another 10 cents per gallon would have been required in 1997 to replace bond revenue used for pavement and bridges and allow MDOT to meet its condition targets. The analysis results were used to help inform the discussion of Michigan’s target asset conditions and funding, and demonstrate application of MDOT’s pavement and bridge management systems for performing historic analyses.

湖相页岩油地层岩相组合类型划分及其油气勘探意义——以博兴洼陷沙河街组为例

为实现陆相富有机质页岩油储层高效开发,以东营凹陷博兴洼陷沙三下—沙四上纯上亚段湖相页岩为研究对象,利用岩石薄片、全岩衍射以及主微量元素等多种地质资料,在厘清岩相类型和沉积古环境演化阶段及二者耦合关系的基础上,划分出8种岩相组合类型,并基于不同组合类型页岩油甜点评价参数对比分析,确定了优势组合类型及其平面分布特征。结果表明:(1)博兴洼陷沙三下—沙四上纯上亚段主要发育富有机质纹层状泥质灰岩和灰质泥岩、富有机质层状泥质灰岩和灰质泥岩以及含有机质块状泥质灰岩和灰质泥岩6种岩相类型;(2)沙四上纯上至沙三下地层,沉积古环境整体上呈现出古气候由干旱到湿润、古氧化还原性变化不大、古盐度由高到低、古物源由少到多的变化特征,显示出8个演化阶段,对应8种岩相组合类型;(3)岩相组合F和D分别为沙三下和沙四上纯上亚段有利岩相组合类型,整体产能高且与当前生产实践吻合性较好;平面上,前者主要分布在F159-F156-F160井区,后者主要FYP1-F116-F119和F156-F159-F161井区,为博兴洼陷页岩油富集高产区域。

渤海湾盆地沧东凹陷孔二段页岩储层特征及页岩油可动性评价

渤海湾盆地沧东凹陷孔二段页岩油资源丰富,但对于页岩油的储层特征、油气赋存、可动性及其关联性研究较少。为此,采用氩离子抛光-场发射扫描电镜、中子散射、高压压汞、低温氮气吸附等实验,对孔二段页岩油储层开展微观孔隙结构描述,对比抽提前后的孔体积之差与饱和-离心核磁共振结果,揭示了页岩油赋存及可动性特征。研究结果表明:孔二段页岩主要发育纳米级的粒间孔、溶蚀孔、有机质孔及微米级的微裂缝等储集空间;页岩油主要赋存于直径为20~40 nm和80~200 nm的孔隙中;长英质页岩具有较高的可动油饱和度,表明其具有更好的孔隙连通性和渗流能力,有利于页岩油的运移。页岩储层中矿物含量和孔隙结构共同控制了页岩油的可流动性。孔径小于50 nm的孔隙具有较大的比表面积,对页岩油的吸附能力较强,不利于页岩油的流动。该研究成果对页岩油的勘探开发具有重要指导意义。

Transcranial photobiomodulation with near-infrared light:a promising therapeutic modality for Alzheimer's disease

Transcranial photobiomodulation(tPBM) is a noninvasive neuromodulation technique that delivers near-infrared(NIR) light with low irradiance(i.e.,power density in mW/cm2) in the wavelength range of 800-1070 nm.Several recently published books or collected literature(Hamblin,2019;GonzalezLima,2021) and papers(Nizamutdinov et al. 2022)offer comprehensive reviews of the mechanism of action and potential clinical translations of tPBM for the treatment of a variety of diseases,including neurodegenerative diseases(Alzheimer’s disease(AD),and Parkinson’s disease),traumatic brain injury.

Practical prescribed-time tracking control for uncertain strict-feedback systems with guaranteed performance under unknown control directions

In this paper,we consider the practical prescribed-time performance guaranteed tracking control problem for a class of uncertain strict-feedback systems subject to unknown control direction.Due to the existence of unknown nonlinearities and uncertainties,it is challenging to design a controller that can ensure the stability of closed-loop system within a predetermined finite time while maintaining the specified transient performance.The underlying problem becomes further complex as the control directions are unknown.To deal with the above problems,a special translation function as well as Nussbaum type function are introduced in the prescribed performance control(PPC)framework.Finally,a PPC as well as preset finite time tracking control scheme is designed,and its effectiveness is confirmed by both theoretical analysis and numerical simulation.

Nutritional, Textural, Sensory Properties and Storage Stability Evaluation of Newly Formulated Strawberry Bar

An analytical study was conducted to develop a strawberry bar and analysis of the nutritional quality and storage stability of a newly formulated strawberry bar. In proximate analysis moisture, ash, pH, acidity, vitamin C, total phenolic content, and antioxidant of strawberry pulp were found 82%, 0.5%, 2.57, 1.38%, 49 mg/100g, 0.33%, 75.17% whereas, in the strawberry bar, it was found 18%, 0.71%, 2.10, 1.10%, 22 mg/100g, 0.14%, 56.13% respectively. For textural properties analysis, the textural profile of the strawberry bar such as hardness, factorability, viscosity, cohesiveness, adhesiveness, springiness, gumminess, chewiness, probe diameter, threshold, filtering range of strawberry bar was found 5.538 × 104 N/m, 0.000 N/m2, 1.687 × 104 N/m2, 0.6636, 2.908 × 103 J/m3, 0.8664, 3.675 × 104 N/m2, 3.184 × 104 N/m2, 20.000 mm, 5 N, 0.4 N respectively whereas the maximum level was 17.4 N at 29.628 seconds and the minimum level was -5.3 N at 30.166 seconds. The sensory evaluation of the strawberry bar was conducted based on nine-point hedonic scales. The sensory evaluation results indicated that the appearance of the strawberry bar was liked very much and the taste, texture, color, aroma, and overall acceptability of the strawberry bar were liked moderately by panelists. In microbiological analysis, the Total Viable Count (TVC) and Total Coliform Count (TCC) of the strawberry bar were found safe levels for up to third days. But on the sixth day, the TCC of the strawberry bar was not found and the TVC of the strawberry bar was found 17 × 104 cfu/g respectively which is higher than the permitted value (Gulf Standard: 105 cfu/g). From the microbial point of view, the newly formulated strawberry bar was safe to consume for up to 3 days but not for 6 days.

Occurrence of D-amino acids in natural products

Since the identified standard genetic code contains 61 triplet codons of three bases for the 20 L-proteinogenic amino acids(AAs),no D-AA should be found in natural products.This is not what is observed in the living world.D-AAs are found in numerous natural compounds produced by bacteria,algae,fungi,or marine animals,and even vertebrates.A review of the literature indicated the existence of at least 132 peptide natural compounds in which D-AAs are an essential part of their structure.All compounds are listed,numbered and described herein.The two biosynthetic routes leading to the presence of D-AA in natural products are:non-ribosomal peptide synthesis(NRPS),and ribosomally synthesized and post-translationally modified peptide(RiPP)synthesis which are described.The methods used to identify the AA chirality within naturally occurring peptides are briefly discussed.The biological activity of an all-L synthetic peptide is most often completely different from that of the D-containing natural compounds.Analyzing the selected natural compounds showed that D-Ala,D-Val,D-Leu and D-Ser are the most commonly encountered D-AAs closely followed by the non-proteinogenic D-allo-Thr.D-Lys and D-Met were the least prevalent D-AAs in natu-rally occurring compounds.

A Machine Learning-Based Distributed Denial of Service Detection Approach for Early Warning in Internet Exchange Points

The Internet service provider(ISP)is the heart of any country’s Internet infrastructure and plays an important role in connecting to theWorld WideWeb.Internet exchange point(IXP)allows the interconnection of two or more separate network infrastructures.All Internet traffic entering a country should pass through its IXP.Thus,it is an ideal location for performing malicious traffic analysis.Distributed denial of service(DDoS)attacks are becoming a more serious daily threat.Malicious actors in DDoS attacks control numerous infected machines known as botnets.Botnets are used to send numerous fake requests to overwhelm the resources of victims and make them unavailable for some periods.To date,such attacks present a major devastating security threat on the Internet.This paper proposes an effective and efficient machine learning(ML)-based DDoS detection approach for the early warning and protection of the Saudi Arabia Internet exchange point(SAIXP)platform.The effectiveness and efficiency of the proposed approach are verified by selecting an accurate ML method with a small number of input features.A chi-square method is used for feature selection because it is easier to compute than other methods,and it does not require any assumption about feature distribution values.Several ML methods are assessed using holdout and 10-fold tests on a public large-size dataset.The experiments showed that the performance of the decision tree(DT)classifier achieved a high accuracy result(99.98%)with a small number of features(10 features).The experimental results confirmthe applicability of using DT and chi-square for DDoS detection and early warning in SAIXP.

Thinking Out-of-Box in Addressing Communication and Service Delivery Challenges: Use of a Traditional Communication Method for Improving Immunization Coverage in Remote Rural Hard-to-Reach Areas of India

Sirmaur district in the state of Himachal Pradesh in India is a hard-to-reach area situated in the western Himalayas having an extreme landscape with snow-laden mountains and extensive river systems that makes the delivery of immunization services extremely challenging. Vaccinators needed a long walk through the hilly terrain to reach outreach sites. Community mobilizers were unable to go house to house to inform the caregivers to bring children to the site for vaccination. Caregivers were unaware when the vaccinators arrive at the site. As a result, many children missed vaccination or were not vaccinated timely. Age-appropriate vaccination coverage (according to national immunization schedule) in the Sirmaur district was the lowest in the state. Thinking out-of-box to address the communication barriers with the caregivers, the traditional drum beating was used, for the first time in India, in two blocks of the Sirmaur district (Rajpura and Shillai). The initiative was planned and implemented by the district health system with the support of the local community leaders. An exit interview was conducted to know the reach of the drum beating to caregivers, and a baseline and end line household survey was conducted to know the outcome of the initiative on age-appropriate vaccination coverage. Analysis of exit interviews data indicated a very high reach of a drum beating to the caregivers;more than 97% of caregivers in Rajpura and 100% in Shillai heard drum beating, and almost 95% of caregivers in Rajpura and 98% in Shillai knew the purpose of drum beating. Analysis of immunization data from baseline and end line surveys showed improvement in age-appropriate vaccination coverage for all vaccines in Rajpura (by 2.2% for BCG, 15.3% for Pentavalent 1, 14.9% for Pentavalent 2, 14.1% for Pentavalent 3, and 6.5% for Measles/MR). In Shillai, age-appropriate vaccination coverage improved for Pentavalent 1 (by 3.4%), Pentavalent 2 (by 5%) and Measles/MR (by 1.7%). In addition, dropout rates were reduced in both the blocks, particularly in Rajpura Pentavalent 1 to Measles dropout rate was reduced by 13.5%. Both health workers and community leaders had positive perceptions of the drum beating initiative. However, another important lesson learned from the initiative was that both the access and demand-side barriers need to be addressed for the desired improvement of age-appropriate immunization coverage. In Shillai, there was lower coverage improvement and a reduction in dropout rates attributed to vacant positions of vaccinators that caused an issue with access to immunization services to people.

On Prime Numbers between kn and (k + 1) n

In this paper along with the previous studies on analyzing the binomial coefficients, we will complete the proof of a theorem. The theorem states that for two positive integers n and k, when n ≥ k - 1, there always exists at least a prime number p such that kn p ≤ (k +1)n. The Bertrand-Chebyshev’s theorem is a special case of this theorem when k = 1. In the field of prime number distribution, just as the prime number theorem provides the approximate number of prime numbers relative to natural numbers, while the new theory indicates that prime numbers exist in the specific intervals between natural numbers, that is, the new theorem provides the approximate positions of prime numbers among natural numbers.