Miracle-dz/UniFAR-FTUs huggingface dataset:
An Evaluation of Kenya in Regionalism and Implications for Peace and Security: Combating Insecurity and Conflict Transformation

This article is a critique of regionalization, combating insecurity and conflict transformation in Kenya. The objectives include: Unveiling regionalism influences on combating insecurity and conflict transformation, discovering if regionalism in Kenya is succeeding or failing in conflict transformation and thus creating a secure Kenya. Moreover, the article discusses the challenges facing regionalism in Kenya and possible remedies. The article focuses is on Kenya, one of the countries in East Africa. Regionalism is discussed focusing on international regional body; the East African Community (EAC). Secondary data was collected by reviewing accredited published journals, relevant books on the topic of study and postgraduate thesis. Collected information was analyzed in a descriptively design. Theoretically, the article adapts Roger Fisher and William Ury Harvard Principled Negotiation Theory (PNT) to explain the interaction of regionalism, the state and its regional antagonist in conflict transformation and mitigating insecurity. According to Fisher and Ury, “a good agreement is one which is wise and efficient, and which improves relationships”. Thus, wise agreements satisfy both parties’ interests and are fair and lasting. According to PNT, with most long-term clients, business partners and team members, the quality of the ongoing relationship is more important than the outcome of the particular negotiation. The research finds that; Kenya as a state seems not to be succeeding in accomplishing its objectives of achieving regional cohesion through regionalism. As a result, regionalism failure in Kenya has paved way to insecurity, latent conflicts and could escalate existing conflicts. In this regards, the article recommends that; Kenya as a state while intervening into regional issues and conflicts it should apply regionalism approaches rather than regionalization. Moreover, the author advocates for the Harvard based Principled Negotiation Theory (PNT) approach into interventions regarding; regionalism issues, regional policy making and implementation.
A Study of Time-of-Use Tariff Planning with Reduced Load Fluctuation Characteristics

In response to a large number of tram loads flooding into the power system, electricity prices have become the direct cause of users’ enthusiasm changing for electricity and load fluctuations. To decrease the load fluctuation of the power system and improve the earnings of electricity without damaging the electricity cost and enthusiasm of users, this paper proposes a time-of-use electricity price planning which consider the characteristics of power system users. By analyzing the user demand characteristics and the demand curve, the demand response (DR) load and non-response load decomposition plan are formulated. Then, based on the fluctuating demand of the power grid and the income from electricity sales, a multiobjective model is established which consider the DR load characteristics, and the multi-objective optimization algorithm is used to solve the model. Finally, the day-ahea d load forecast and demand response are analyzed to form a multi-objective value-oriented Pareto solution, and the time-of-use (TOU) tariff is selected according to the grid demand. The example analysis shows that the established model can be solved with high efficiency to achieve the target of decreasing load fluctuation, no harming the interests of users, and increasing the price of electricity sales.
Integrating Social Media Data and Historical Stock Prices for Predictive Analysis: A Reinforcement Learning Approach

—The reliance on data collection for assessing individual behavior and actions has intensified, particularly with the proliferation of digital platforms. People often use the Internet to express their opinions and experiences about various products and services on social media and personal websites. Concurrently, the stock market, a key driver of commercial and industrial growth, has seen a surge in research focused on predicting market trends. The vast array of information on social media regarding public sentiment towards current events, coupled with the known impact of financial news on stock prices, has led to the application of data mining techniques for understanding market volatility. This research proposes a novel method that integrates social media data, encompassing public sentiment, news, and historical stock prices, to predict future stock trends. The approach involves two primary phases. The first phase develops a sentiment analysis (SA) model using three dilated convolution layers for feature extraction and classification. Addressing the challenge of unbalanced classification, a reinforcement learning (RL)-based strategy is employed, wherein an agent receives varied rewards for accurate classification, with a bias towards the minority class. Additionally, a unique clustering-based mutation operator within a differential equation (DE) framework is introduced to initiate the backpropagation (BP) process. The second phase incorporates an attention-based long short-term memory (LSTM) model, merging historical stock prices with sentiment data. An experimental analysis of the study dataset is conducted to determine optimal values for significant parameters, including the reward function.
Design of the Dual Active Bridge Converter to Minimize RMS Current in Supercapacitor Interface Applications

In applications employing energy storage systems based on supercapacitors (SCs), there are challenges in designing the power converter to interface the SCs due to their inherent terminal voltage variation. Unlike other dc/dc topologies, the dual active bridge (DAB) topology is suitable for SC interfacing. However, to improve efficiency, a design strategy is required to mitigate conduction losses caused by the wide variation in SC terminal voltage. This paper proposes a DAB design methodology that defines an optimal turns ratio to minimize the RMS current over SC charging and discharging cycles. The design formulation aims to reduce the DAB RMS current for a general modulation scheme and is implemented for single phase-shift (SPS) modulation. Circuit simulations and experiments on a laboratory prototype with an output power of 250 W demonstrate the reduction in RMS current achieved by the proposed design.
FPGA-based Voltage Controller for a Three-Phase PWM Active Rectifier

In this study, we focused on designing a controller for the PWM Three-Phase Active Rectifier (TPAR) voltage output. We aimed to ensure a power factor close to unity by implementing a feedback control of the passive output of the dynamics of the exact static error (ESEDPOF). We utilized the SRF-PLL synchronization method to achieve this, which provided fast and accurate phase angle estimation. We used a low-cost FPGA-based development board (Nexys 2, with spartan 3E-1200) to process the arithmetic operations of the sync, controller, and modulator algorithms. All designed modules followed the 32-bit single-precision format, and we optimized the data flow of each algorithm to minimize the use of logical resources. In the closed-loop tests, we applied load changes at a desired reference voltage to verify the controller’s robustness. We also carried out power quality tests for the AC power supply, and we obtained satisfactory results that met the standard IEEE-519.
Heterogeneous Chiplet Solution for Non-volatile In-memory Computing Architecture

In order to overcome the memory wall problem, academia and industry have proposed AI accelerator architecture based on non-volatile in-memory computing (IMC) devices. However, this computing architecture has a low utilization rate of hardware resources, resulting in a large amount of buffer and memory computing device resource waste. Therefore, in order to better compatible with traditional convolutional neural networks and improve the utilization of hardware resources, this paper proposes a heterogeneous chiplet solution. This solution tries to meet the requirements of the size and depth of the feature map of different layers in the same convolutional neural network model for hardware resources, and greatly increases the utilization rate of hardware resources. Compared with the homogeneous solution, this solution improves the utilization rate of buffer resources by more than 50 %, and the increase of latency can be ignored.
An AI-Based Real-time Intrusion Detection System for Power Electronics-Dominated Grid: Attack on Inverters PQ Set-Points

This work presents a long short-term memory (LSTM) neural network based method for real-time detection of intruded power setpoints of grid-following inverters (GFLIs) in power electronics dominated grids (PEDG). The supervisory control layer in PEDG plays a crucial role in coordination and optimal dispatch of GFLIs. Thus, a compromised supervisory control layer and/or the communication line between the supervisory control and primary control layers can jeopardize the stable operation of the network. The attack vector considered in this paper manipulates active (P) and reactive (Q) powers setpoints. The proposed real-time intrusion detection system (IDS) is based on the effect of this attack vector on voltage, current, frequency and rate of change of frequency (ROCOF) sensed at inverters point of common coupling (PCC). Classifying the time series data into normal or anomalous types can help detect attacks on PQ setpoints in real-time. Various source and load disturbances along with anomaly/attack scenarios are considered for database creation and training the neural network. The proposed real-time IDS is then validated in the DER-based PEDG system. The neural network performance characteristics in terms of accuracy and loss proved it to be capable of effectively distinguishing anomalous behavior from regular fluctuations occurring in the PEDG.
Parity-Time-Symmetric Optoelectronic Oscillator Based on DPMZM With Single-Sideband Suppressed-Carrier Modulation

A Parity-time (PT) symmetric optoelectronic oscillator (OEO) based on dual-parallel Mach-Zehnder modulator (DPMZM) with single-sideband suppressed-carrier modulation is proposed and experimentally demonstrated. PT symmetry is realized in a single physical loop, where the gain and loss loops are formed by the beating between the optical carrier and the ±1st-order sideband. By adjusting the bias point voltage of the DPMZM, the gain and loss can be balanced to achieve single-mode oscillation. In our experiment, the system produces a microwave signal with a frequency of 10.79 GHz, which phase noise is about −111dBc/Hz when the offset frequency is 10kHz.
Simultaneous PM Temperature and Magnetization State Estimation in Variable Flux PMSMs Based on the PM Flux Linkage

In VF-PMSMs, PM temperature increase leads to a reduction on torque production capability and to a variation on coercive force in PMs, therefore affecting the magnetization state (MS) control. Due to this, PM temperature monitoring in VF-PMSMs is of upmost importance. However, available estimation methods cannot be extended to VF-PMSMs since they assume constant MS. This paper proposes a method for simultaneous MS and PM temperature estimation in VF-PMSMs.
Solving Random Satisﬁable 3CNF Formulas in Expected Polynomial Time ∗†

We present an algorithm for solving 3SAT instances. Several algorithms have been proved to work whp (with high probability) for various SAT distributions. However, an algorithm that works whp has a drawback. Indeed for typical instances it works well, however for some rare inputs it does not provide a solution at all. Alternatively, one could require that the algorithm always produce a correct answer but perform well on average. Expected polynomial time formalizes this notion. We prove that for some natural distribution on 3CNF formulas, called planted 3SAT, our algorithm has expected polynomial (in fact, almost linear) running time. The planted 3SAT distribution is the set of satisﬁable 3CNF formulas generated in the following manner. First, a truth assignment is picked uniformly at random. Then, each clause satisﬁed by it is included in the formula with probability p . Extending previous work for the planted 3SAT distribution, we present, for the ﬁrst time for a satisﬁable SAT distribution, an expected polynomial time algorithm. Namely, it solves all 3SAT instances, and over the planted distribution (with p = d/n 2 , d > 0 a suﬃciently large constant) it runs in expected polynomial time. Our results extend to k -SAT for any constant k .
Photonic Add-Drop-Gate Node Element Based on EML Technology

We propose a novel approach for reconfigurable photonic nodes in short-reach optical networks, which builds on unified component technology for several key functions. The need for fast transmission, reception, and switching components is addressed through use of a widely adopted technology that is particularly known for its cost efficiency: the externally modulated laser (EML). Through consequent use of EMLs as fast and versatile electro-optic node element in combination with a slower yet reconfigurable cross-connect matrix serving as interconnection between several elements, a node architecture can be synthesized on demand – such as known from field-programmable gate arrays that have revolutionized the field of programmable microelectronics. To prove the proposed multi-functional EML-based approach, we experimentally investigate the capabilities of this photonic transmitter as coherent receiver of dropped signals and as optical gate, being the basic element of fast switches. We first demonstrate the polarization-immune coherent homodyne reception of broadband 10 Gb/s on-off keyed signals without further need for digital signal processing. Transmission is shown at an optical budget of 24 dB and in presence of 12 side-channels. Moreover, the EML is applied as fast 1 × 1 switch by proving that gating at the sub-ns regime can be facilitated at a reception penalty of less than 1 dB.
Evaluation of Beef Palatability Following Extended Storage at Low Temperature

: Extending the shelf life of fresh meat without having an adverse effect on its quality attributes is critical to the meat industry to reduce waste, stabilize supply, and facilitate export. Low temperature (LT) storage of beef muscles at or slightly above their freezing point slows down microbiological spoilage while maintaining the product ’ s fresh status. This study evaluated the impact of 60, 75, or 90 d of LT storage ( − 2.7°C ± 0.3°C) on the palatability characteristics of steaks from inside rounds (IR), bone-in ribeyes, and striploins (SL) from 10 ( n = 10) upper two-thirds Choice beef carcasses. Two steaks fabricated from each subprimal were vacuum-packaged, wet-aged for 21 d (3°C), and frozen ( − 20°C) for Warner-Bratzler shear force (WBSF) and sensory analyses. These steaks served as the control with regard to storage condition and time. The remainder of each subprimal was fabricated into 3 portions, vacuum packaged, and randomly allocated to an LT storage time (60, 75, or 90 d). After each storage time, subprimals were fabricated into steaks, vacuum-packaged, and stored ( − 20°C) for WBSF and consumer sensory analyses. Consumers ( N = 238) evaluated cooked samples for juiciness, tenderness, flavor liking, and overall liking. Data were analyzed using a mixed model with storage time as the fixed effect and individual carcasses as the random blocking factor. The WBSF values decreased ( P < 0.05) with increased storage time for all the cuts. Similarly, consumer tenderness rating scores increased with the LT storage time, particularly in IR and SL steaks. However, storage time did not influence ( P ≥ 0.05) the juiciness, flavor, and overall liking of any of the cuts. The results of this study suggest it would be feasible to extend the storage time of beef while preserving or improving the sensory quality when held at optimal conditions above the freezing temperature.
Mapeo de los bosques tipo varillal utilizando imágenes de satélite rapideye en la provincia maynas, loreto, Perú

Los bosques tipo varillal albergan una diversidad biologica endemica y varias especies monodominantes, cuando estos bosques se ubican en los pantanos acumulan gran cantidad de carbono en el suelo. El objetivo del presente estudio fue elaborar el mapa de distribucion espacial de los varillales sobre arena blanca y sobre pantano en la provincia Maynas, Loreto, a escala 1/100,000, utilizando imagenes de satelite RapidEye y aplicando el algoritmo clasificador de Maxima Verosimilitud (MVS) en el programa ArcGIS version 10.1. Usamos siete categorias de clasificacion en tres escenas RapidEye y definimos las firmas espectrales respectivas basadas en 32 areas de entrenamiento de muestreo en campo. Se clasificaron las 206 escenas restantes utilizando el algoritmo MVS. El mapa fue validado utilizando 57 puntos de control entre varillales y otros tipos de bosque. Se determinaron 51,025 ha de varillales que representan 0.67% de la superficie de la provincia Maynas, distribuidas principalmente entre las cuencas de los rios Napo y Nanay y entre la ciudad de Iquitos y la boca del Rio Amazonas. Obtuvimos un 91.2% de exactitud en la clasificacion de los varillales. Las bandas borde rojo (BR) e ifrarrojo cercano (IRC) de las imagenes RapidEye diferenciaron mejor los varillales de los otros bosques. Se reportan nuevas areas de bosque de varillales sobre arena blanca y pantanos. En conclusion, las imagenes RapidEye son utiles para clasificar y diferenciar los varillales de otros tipos de bosque, siendo el mapa de los varillales util para la exploracion de nuevos sitios en el estudio de almacenamiento de carbono en el suelo.
The Demand for Youth : Implications for the Hours Volatility Puzzle

The employment and hours worked of young individuals fluctuate much more over the business cycle than those of prime-aged individuals. Understanding the mechanism underlying this observation is key to explaining the volatility of aggregate hours over the cycle. We argue that the joint behavior of age-specific hours and wages in the U.S. data point to differences in the cyclical characteristics of labor demand. To articulate this view, we consider a production technology displaying capital-experience complementarity. We estimate the key parameters governing the degree of complementarity and show that the model can account for the behavior of age-specific hours and wages while generating a series of aggregate hours that is nearly as volatile as output.
Does Manganese In�uence Grass Litter Decomposition on a Hawaiian Rainfall Gradient?

13 Plant litter is a well-defined pool of organic matter in which the influence of Mn on decomposition 14 (both decomposition rate, and the mix of compounds ultimately transferred to soil organic matter) 15 has been clearly demonstrated in temperate forests. However, no similar study exists on grasslands, 16 and the effect of foliar Mn versus soil-derived Mn on litter decomposition is poorly known. We 17 used 5-month and 12-month field and 10-month laboratory experiments to evaluate organic-matter 18 decomposition on the Kohala rainfall gradient in areas with different foliar and soil Mn 19 abundances, and on which a single plant species dominates primary production and the litter pool. 20 Chemical imaging analyses of decomposed litter revealed that Mn 2+ oxidized to Mn 3+ and Mn 4+ 21 on grass litter during decompositions — hallmarks of Mn-driven OM oxidation. However, these 22 transformations and Mn abundance did not predict greater litter mass loss through decomposition. 23 These observations demonstrate that the importance of Mn to an ecosystem’s C cycle does not rely 24 solely on the metal’s abundance and availability.
Study of protection factors of skull base with loaded mandible

PURPOSE: The stress distribution of the mandible and temporal bone under impact loading was analyzed by finite element method for investigating the protection factors of skull base.METHODS: According to the obtained CT image of the head from a healthy male adult and the related anatomic studies,a 3-D finite element model with the anatomic structures of the temporal bone,mandible,temporomandibular joint,main ligaments and masticatory muscles was established.A concentrated force was applied to the chin of mandible.The angle of the force with the horizontal line was 0°,30°,54° and the magnitude of the force was 1000N,2000N,3000N,respectively.The stress distribution of the mandible and temporal bone under different loading conditions was analyzed.RESULTS: The stress of temporal bone was always less than that of mandible whatever the direction or the magnitude of the force was.With the alteration of force directions,the region of peak stress in mandible changed,which mainly lied on the condyle and the interior surface of anterior part of the mandible,while the region of peak stress in the temporal bone did not change,which lied on the anterior wall of external acoustic meatus.The stress of the roof of the glenoid fossa was not the largest in the temporal bone.CONCLUSIONS: Due to the buffer effect of the disc,the stress of temporal bone was always less than that of the mandible.When the chin was loaded in the sagittal direction,the region of peak stress in the temporal bone was the anterior wall of external acoustic meatus,not the weak part of the roof of glenoid fossa,so as to avoid the temporal bone being destructed severely.
Salmonella immunotherapy engineered with highly efficient tumor antigen coating establishes antigen-specific CD8+ T cell immunity and increases in antitumor efficacy with type I interferon combination therapy

ABSTRACT Bacteria-based cancer therapy employs various strategies to combat tumors, one of which is delivering tumor-associated antigen (TAA) to generate specific immunity. Here, we utilized a poly-arginine extended HPV E7 antigen (9RE7) for attachment on Salmonella SL7207 outer membrane to synthesize the bacterial vaccine Salmonella-9RE7 (Sal-9RE7), which yielded a significant improvement in the amount of antigen presentation compared to the previous lysine-extended antigen coating strategy. In TC-1 tumor mouse models, Sal-9RE7 monotherapy decreased tumor growth by inducing E7 antigen-specific immunity. In addition, pairing Sal-9RE7 with adjuvant Albumin-IFNβ (Alb-IFNβ), a protein cytokine fusion, the combination significantly increased the antitumor efficacy and enhanced immunogenicity in the tumor microenvironment (TME). Our study made a significant contribution to personalized bacterial immunotherapy via TAA delivery and demonstrated the advantage of combination therapy.