Unveiling the brain’s symphony:exploring the necessity and sufficiency of neural networks in behavior control

Since the pioneering work by Broca and Wernicke in the 19th century,who examined individuals with brain lesions to associate them with specific behaviors,it was evident that behaviors are complex and cannot be fully attributable to specific brain areas alone.Instead,they involve connectivity among brain areas,whether close or distant.At that time,this approach was considered the optimal way to dissect brain circuitry and function.These pioneering efforts opened the field to explore the necessity or sufficiency of brain areas in controlling behavior and hence dissecting brain function.However,the connectivity of the brain and the mechanisms through which various brain regions regulate specific behaviors,either individually or collaboratively,remain largely elusive.Utilizing animal models,researchers have endeavored to unravel the necessity or sufficiency of specific brain areas in influencing behavior;however,no clear associations have been firmly established.

MET receptor tyrosine kinase promotes the generation of functional synapses in adult cortical circuits

Loss of synapse and functional connectivity in brain circuits is associated with aging and neurodegeneration,however,few molecular mechanisms are known to intrinsically promote synaptogenesis or enhance synapse function.We have previously shown that MET receptor tyrosine kinase in the developing cortical circuits promotes dendritic growth and dendritic spine morphogenesis.To investigate whether enhancing MET in adult cortex has synapse regenerating potential,we created a knockin mouse line,in which the human MET gene expression and signaling can be turned on in adult(10–12 months)cortical neurons through doxycycline-containing chow.We found that similar to the developing brain,turning on MET signaling in the adult cortex activates small GTPases and increases spine density in prefrontal projection neurons.These findings are further corroborated by increased synaptic activity and transient generation of immature silent synapses.Prolonged MET signaling resulted in an increasedα-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid/N-methyl-Daspartate(AMPA/NMDA)receptor current ratio,indicative of enhanced synaptic function and connectivity.Our data reveal that enhancing MET signaling could be an interventional approach to promote synaptogenesis and preserve functional connectivity in the adult brain.These findings may have implications for regenerative therapy in aging and neurodegeneration conditions.

Call for Papers——Feature Topic Vol.22,No.3,2025 Special Issue of China Communications:Convergence of 6G empowered Edge Intelligence and Generative AI:Theories,Algorithms,and Applications

Generative artificial intelligence(AI),as an emerging paradigm in content generation,has demonstrated its great potentials in creating high-fidelity data including images,texts,and videos.Nowadays wireless networks and applications have been rapidly evolving from achieving“connected things”to embracing“connected intelligence”.Generative AI has been recognized as a fundamentally innovative technology to drive the advancement of intelligent wireless communications and networks.

Fuzzy inference system using genetic algorithm and pattern search for predicting roof fall rate in underground coal mines

One of the most dangerous safety hazard in underground coal mines is roof falls during retreat mining.Roof falls may cause life-threatening and non-fatal injuries to miners and impede mining and transportation operations.As a result,a reliable roof fall prediction model is essential to tackle such challenges.Different parameters that substantially impact roof falls are ill-defined and intangible,making this an uncertain and challenging research issue.The National Institute for Occupational Safety and Health assembled a national database of roof performance from 37 coal mines to explore the factors contributing to roof falls.Data acquired for 37 mines is limited due to several restrictions,which increased the likelihood of incompleteness.Fuzzy logic is a technique for coping with ambiguity,incompleteness,and uncertainty.Therefore,In this paper,the fuzzy inference method is presented,which employs a genetic algorithm to create fuzzy rules based on 109 records of roof fall data and pattern search to refine the membership functions of parameters.The performance of the deployed model is evaluated using statistical measures such as the Root-Mean-Square Error,Mean-Absolute-Error,and coefficient of determination(R_(2)).Based on these criteria,the suggested model outperforms the existing models to precisely predict roof fall rates using fewer fuzzy rules.

Case Report: Rhupus (The Association of Systemic Lupus Erythematosus and Rheumatoid Arthritis): About 2 Cases

Introduction: The association of systemic lupus erythematosus and rheumatoid arthritis (rhupus) is a rare clinical condition. Throughout the world, 287 cases of Rhupus have been described. We report two new observations of two patients who presented predominantly distal erosive polyarthritis with positive anti-Sm antibodies in one case and SmRNP in the other case. Observations: Case 1: 37 years old patient, with a recent diagnosis of pulmonary tuberculosis. She has since 8 months an inflammatory, bilaterally and symmetrical polyarthralgia without deformation or ankylosing synovitis, associated with malar erythema without other abnormalities. Immunological tests showed: positive Rheumatoid factor at 158 IU/ml, positive Anti-CCP at 550 IU/ml, and positivity of antinuclear at 1/1280 nuclear fluorescence with a strong presence of anti-Sm >8 IU/ml. The diagnosis of rhupus was concluded, without serious visceral involvement. Case 2: A 28-year-old patient, married with 3 children, with bilateral, symmetrical, deforming and chronic polyarthritis affecting large and small joints, which had been evolving for over 5 years without cutaneous abnormality associated. Paraclinical investigations showed: a biological inflammatory syndrome. Immunology was positive, with rheumatoid factors at 78 IU/ml, anti-CCP at 561 IU/ml, antinuclear antibodies at 1/1280 with positive anti-SmRNP and anti-SSA/Ro52, and a positive direct Coombs test. Joint ultrasound revealed tenosynovitis of the extensors and common flexors of the fingers, erosions and synovitis of multiple PPIs. The diagnosis of rhupus was based on the presence of 10 ACR criteria for RA and 8 ACR/EULAR 2019 criteria for SLE. Conclusion: Rheumatoid arthritis is a rare autoimmune disease combining features of both systemic lupus erythematosus and rheumatoid arthritis in the same patient, often sequentially. Despite a growing number of case reports and series, a consensus on the classification of SLE arthritis is still lacking, and diagnostic criteria for rhupus do not exist. These cases of rhupus must be recognized, as the vital and/or functional prognosis may be different from SLE alone or isolated RA.

Evaluating the Robustness of MDSS Maintenance Forecasts Using Connected Vehicle Data

The Indiana Department of Transportation (INDOT) adopted the Maintenance Decision Support System (MDSS) for user-defined plowing segments in the winter of 2008-2009. Since then, many new data sources, including connected vehicle data, enhanced weather data, and fleet telematics, have been integrated into INDOT winter operations activities. The objective of this study was to use these new data sources to conduct a systematic evaluation of the robustness of the MDSS forecasts. During the 2023-2024 winter season, 26 unique MDSS forecast data attributes were collected at 0, 1, 3, 6, 12 and 23-hour intervals from the observed storm time for 6 roadway segments during 13 individual storms. In total, over 888,000 MDSS data points were archived for this evaluation. This study developed novel visualizations to compare MDSS forecasts to multiple other independent data sources, including connected vehicle data, National Oceanic and Atmospheric Administration (NOAA) weather data, road friction data and snowplow telematics. Three Indiana storms, with varying characteristics and severity, were analyzed in detailed case studies. Those storms occurred on January 6th, 2024, January 13th, 2024 and February 16th, 2024. Incorporating these visualizations into winter weather after-action reports increases the robustness of post-storm performance analysis and allows road weather stakeholders to better understand the capabilities of MDSS. The results of this analysis will provide a framework for future MDSS evaluations and implementations as well as training tools for winter operation stakeholders in Indiana and beyond.

Development of a Novel Noise Reduction Algorithm for Smart Checkout RFID System in Retail Stores

This paper presents a smart checkout system designed to mitigate the issues of noise and errors present in the existing barcode and RFID-based systems used at retail stores’checkout counters.This is achieved by integrating a novel AI algorithm,called Improved Laser Simulator Logic(ILSL)into the RFID system.The enhanced RFID system was able to improve the accuracy of item identification,reduce noise interference,and streamline the overall checkout process.The potential of the systemfor noise detection and elimination was initially investigated through a simulation study usingMATLAB and ILSL algorithm.Subsequently,it was deployed in a small-scale environment to validate its real-world performance.Results show that RFID with the proposed new algorithm ILSL and AI basket is capable of accurately detecting the related itemswhile eliminating noise originating fromunrelated objects,achieving an accuracy rate of 88%.

Vascular endothelial growth factor/connective tissue growth factor and proteomic analysis of aqueous humor after intravitreal conbercept for proliferative diabetes retinopathy

AIM:To investigate the role of connective tissue growth factor(CTGF)and vascular endothelial growth factor(VEGF)in the protein profile of the aqueous humor in patients with proliferative diabetic retinopathy(PDR)following intravitreal injection of conbercept.METHODS:This study included 72 PDR patients and 8 cataract patients as controls.PDR patients were divided into 3 groups according to the intervals of 3,5,and 7d between intravitreal conbercept(IVC,0.5 mg/0.05 mL)injection and pars plana vitrectomy(PPV)performed.Aqueous humor samples were collected before and after IVC and PPV for VEGF and CTGF levels detected with enzyme-linked immunosorbent assay(ELISA).The differential proteomics of 10 patients who underwent PPV surgery 5d after IVC and 8 normal controls was studied,Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analysis were performed on the data,and the protein interaction network of 23 differential proteins was studied.RESULTS:Post-IVC,VEGF levels decreased and CTGF levels increased significantly in aqueous humor,with the CTGF/VEGF ratio rising significantly at all intervals.Liquid chromatography tandem mass spectrometry(LC-MS/MS)identified differentially expressed proteins between preand post-IVC samples.GO and KEGG analyses revealed involvement in immune response,stress response,complement and coagulation cascades,ferroptosis,and PPAR signaling pathways.PPI analysis highlighted key proteins like APOA1,C3,and transferrin(TF).ELISA assay confirmed the differential expression of proteins such as HBA1,SERPINA1,COL1A1,and ACTB,with significant changes in the IVC groups.CONCLUSION:The study demonstrates that IVC effectively reduces VEGF levels while increasing CTGF levels,thereby modifying the CTGF/VEGF ratio,and IVC significantly alters the protein profile in the aqueous humor of patients with PDR.Proteomic analysis reveals that these changes are associated with critical biological pathways and protein interactions involved in immune response,stress response,and cellular metabolism.

A New Malicious Code Classification Method for the Security of Financial Software

The field of finance heavily relies on cybersecurity to safeguard its systems and clients from harmful software.The identification of malevolent code within financial software is vital for protecting both the financial system and individual clients.Nevertheless,present detection models encounter limitations in their ability to identify malevolent code and its variations,all while encompassing a multitude of parameters.To overcome these obsta-cles,we introduce a lean model for classifying families of malevolent code,formulated on Ghost-DenseNet-SE.This model integrates the Ghost module,DenseNet,and the squeeze-and-excitation(SE)channel domain attention mechanism.It substitutes the standard convolutional layer in DenseNet with the Ghost module,thereby diminishing the model’s size and augmenting recognition speed.Additionally,the channel domain attention mechanism assigns distinctive weights to feature channels,facilitating the extraction of pivotal characteristics of malevolent code and bolstering detection precision.Experimental outcomes on the Malimg dataset indicate that the model attained an accuracy of 99.14%in discerning families of malevolent code,surpassing AlexNet(97.8%)and The visual geometry group network(VGGNet)(96.16%).The proposed model exhibits reduced parameters,leading to decreased model complexity alongside enhanced classification accuracy,rendering it a valuable asset for categorizing malevolent code.

The Launching Ceremony of the Silk Road People-to-People Connectivity Donation Activity"Care for the Future"Held in Yangon

The launching ceremony of the Silk Road Peopleto-People"Connectivity donation activity"Care for the Future was jointly held by China Foundation for Peace and Development and the Myanmar-Chinese Cooperation&Communication Centre in Yangon on January 16.The Yangjin Middle School in Yangon Province of Myanmar received football,volleyball,badminton,notebooks,LED lights and other school utensils and sporting goods.

Coordination of Regulation Devices for Damping Power Oscillations in a Dynamic Disturbance Context: A Fuzzy Logic-Based Approach Applied to the Electrical Grid of the Republic of Congo

This article presents a fuzzy logic-based approach to coordinate the control devices of the power system, such as Power System Stabilizers (PSS) and Static Synchronous Compensators (STATCOM), to damp power oscillations caused by dynamic disturbances. At first, we used the Lyapunov method to study the dynamic stability of the power grid in the Republic of Congo. This method allowed us to analyze the eigenvalues of the state variable matrix and highlight the eigenvalues in the complex plane. Secondly, we proposed a fuzzy logic-based controller to account for uncertainties existing near the thresholds. The inputs to this controller are the generator speed and generator rotor angle. We demonstrated the effectiveness and feasibility of this fuzzy control by applying it to the power grid of the Republic of Congo, with three power stabilizers and two STATCOMs. .

Simulation of Steel Reinforcement on the Nonlinear Behaviour of Slender Glulam Beam Columns by Using the Newton-Raphson Method

The current theory in NF EN 1995-1-1/NA of Eurocode 5, which is based on maximum deflection, has been investigated on softwoods. Therefore, this theory is not adapted for slender glulam beam columns made of tropical hardwood species from the Congo Basin. This maximum deflection is caused by a set of loads applied to the structure. However, Eurocode 5 doesn’t provide how to predict this deflection in case of long-term load for such structures. This can be done by studying load-displacement (P-Δ) behaviour of these structures while taking into account second order effects. To reach this goal, a nonlinear analysis has been performed on a three-dimensional beam column embedded on both ends. Since conducting experimental investigations on large span structural products is time-consuming and expensive especially in developing countries, a numerical model has been implemented using the Newton-Raphson method to predict load-displacement (P-Δ) curve on a slender glulam beam column made of tropical hardwood species. On one hand, the beam has been analyzed without wood connection. On the other hand, the beam has been analyzed with a bolted wood connection and a slotted-in steel plate. The load cases considered include self-weight and a uniformly applied long-term load. Combinations of serviceability limit states (SLS) and ultimate limit states (ULS) have also been considered, among other factors. A finite-element software RFEM 5 has been used to implement the model. The results showed that the use of steel can reduce displacement by 20.96%. Additionally, compared to the maximum deflection provided by Eurocode 5 for softwoods, hardwoods can exhibit an increasing rate of 85.63%. By harnessing the plastic resistance of steel, the bending resistance of wood can be increased by 32.94%.

Research on the prediction method for fluvial-phase sandbody connectivity based on big data analysis--a case study of Bohai a oilfield

The connectivity of sandbodies is a key constraint to the exploration effectiveness of Bohai A Oilfield.Conventional connectivity studies often use methods such as seismic attribute fusion,while the development of contiguous composite sandbodies in this area makes it challenging to characterize connectivity changes with conventional seismic attributes.Aiming at the above problem in the Bohai A Oilfield,this study proposes a big data analysis method based on the Deep Forest algorithm to predict the sandbody connectivity.Firstly,by compiling the abundant exploration and development sandbodies data in the study area,typical sandbodies with reliable connectivity were selected.Then,sensitive seismic attribute were extracted to obtain training samples.Finally,based on the Deep Forest algorithm,mapping model between attribute combinations and sandbody connectivity was established through machine learning.This method achieves the first quantitative determination of the connectivity for continuous composite sandbodies in the Bohai Oilfield.Compared with conventional connectivity discrimination methods such as high-resolution processing and seismic attribute analysis,this method can combine the sandbody characteristics of the study area in the process of machine learning,and jointly judge connectivity by combining multiple seismic attributes.The study results show that this method has high accuracy and timeliness in predicting connectivity for continuous composite sandbodies.Applied to the Bohai A Oilfield,it successfully identified multiple sandbody connectivity relationships and provided strong support for the subsequent exploration potential assessment and well placement optimization.This method also provides a new idea and method for studying sandbody connectivity under similar complex geological conditions.

Effects of dust,soiling,aging,and weather conditions on photovoltaic system performances in a Saharan environment—Case study in Algeria

Solar photovoltaic(PV)power represents one of the most promising future sources of energy in the world.Considered the cleanest form of energy,extensive research is being undertaken to widen its use.Notably,mega projects are being considered for installation in the Middle East and North Africa(MENA)region because of its high solar potential,with hopes of eventually feeding Europe from the PV electricity generated in this region and transported through high voltage direct current(DC)lines.However,current implementation of PV systems has shown that their reliability and efficiency depend upon surrounding environmental factors,such as the ambient temperature,wind,and rainfall,as well as soiling,pollution,and aging.The aim of this study was to investigate,through experimental tests,the effects of such factors on the power output of a grid connected PV station.The results showed that the output power and efficiency are deeply affected by various environmental factors,which are weather dependent.These findings may help us develop appropriate solutions to overcome these drawbacks.

From EBIT to SEBIT(Sustainable EBIT):Sustainable Performance Accounting(SPA)Using the Example of CO_(2) Accounting

Corporate sustainability reporting has become increasingly important in recent years.However,conventional approaches reach their limits when it comes to quantifying and measuring the actual sustainability performance of a company.This article presents a new approach:Sustainable Performance Accounting(SPA),which is based on an extension of bookkeeping by including ESG bookkeeping.SPA enables companies to systematically measure and manage their sustainability performance.The article provides an overview of the basics of SPA methodology and uses a comprehensive example showing how SPA can be implemented in practice.The article is aimed at interested readers from science and practice as well as decision-makers who are interested in future-oriented sustainability reporting.

Equilibrium configurations of the tethered three-body formation system and their nonlinear dynamics

This paper considers nonlinear dynamics of teth- ered three-body formation system with their centre of mass staying on a circular orbit around the Earth, and applies the theory of space manifold dynamics to deal with the nonlinear dynamical behaviors of the equilibrium configurations of the system. Compared with the classical circular restricted three body system, sixteen equilibrium configurations are obtained globally from the geometry of pseudo-potential energy sur- face, four of which were omitted in the previous research. The periodic Lyapunov orbits and their invariant manifolds near the hyperbolic equilibria are presented, and an iteration procedure for identifying Lyapunov orbit is proposed based on the differential correction algorithm. The non-transversal intersections between invariant manifolds are addressed to generate homoclinic and heteroclinic trajectories between the Lyapunov orbits. （3,3）- and （2,1）-heteroclinic trajecto- ries from the neighborhood of one collinear equilibrium to that of another one, and （3,6）- and （2,1）-homoclinic trajecto- ries from and to the neighborhood of the same equilibrium, are obtained based on the Poincar6 mapping technique.

Comparison the Performances of Three Earthing Systems for Micro-Grid Protection during the Grid Connected Mode

This paper presents, tests and compares three earthing systems (TT, TN and IT) for Micro-Grid (MG) protection against various fault types during the connected mode. The main contribution of this work is including the models of all the micro sources which interfaced to the MG by power electronic inverters. Inverters in turns are provided with current limiters and this also included in the inverter models to exactly simulate the real situation in the MG during fault times. Results proved that the most suitable earthing system for MG protection during the connecting mode is the TN earthing system. That system leads to a suitable amount of fault current sufficient to activate over current protection relays. With using TN system, Touch voltages at the faulted bus and all other consumer’s buses are less than the safety limited value if current limiter is included with the transformer of the main grid which connects MG. For the two others earthing systems (TT and IT), fault current is small and nearly equal to the over load current which make over current protection relay can not differentiate between fault current and overload current. All models of micro sources, earthing systems, inverters, main grid and control schemes are built using Matlab?/Simulink? environment.

Dynamic Analysis for the Global Performance of An SPM-Feeder-Cage System Under Waves and Currents

In the present study, the dynamic response of a coupled SPM-feeder-cage system under irregular waves and shear currents is analyzed. A numerical model is developed by using the commercial software Orca Flex. Hydrodynamics coefficients of the vessel are calculated by using a 3D diffraction/radiation panel program. First- and second-order wave forces are included in the calculations. Morison equation is used to compute the drag force on line elements representing the net. Drag coefficients are determined at every time step in the simulation considering the relative normal velocity between the structural elements and the fluid flow. The dynamic response of the coupled system is analyzed for various environments and net materials. The results of the study show the effects of solidity ratio of the net and vertical positions of the cage on the overall dynamic response of the system, confirming the viability of this type of configuration for future development of offshore aquaculture in deep waters.

CONNECTIONS AND GEODESIC CHARACTERISTIC OF EQUATIONSOF MOTION FOR CONSTRAINED MECHANICAL SYSTEMS

The geodesic characteristic of equations of motion for nonautonomous constrained mechanical systems is studied in the modern setting of global differential geometry. A necessary and sufficient condition for the dynamical flow of a nonautonomous mechanical system with geodesic characteristic was obtained with respect to a connection of 1-jet bundle. The dynamical flow concerning the non-autonomous case motion of an nonautonomous mechanical system with constraints can be always represented by the motion along the geodesic line of torsion-free connection on 1-jet bundle, which is different from the case in an autonomous mechanical system.

EXISTENCE OF BOUNDED SOLUTIONS ON THE REAL LINE FOR LINARD SYSTEM

The existence of monotone and non_monotone solutions of boundary value problem on the real line for Liénard equation is studied. Applying the theory of planar dynamical systems and the comparison method of vector fields defined by Liénard system and the system given by symmetric transformation or quasi_symmetric transformation, the invariant regions of the system are constructed. The existence of connecting orbits can be proved. A lot of sufficient conditions to guarantee the existence of solutions of the boundary value problem are obtained. Especially, when the source function is bi_stable, the existence of infinitely many monotone solusion is obtained.