Heat acclimation is a critical strategy for preventing heatstroke in military personnel, but traditional heat acclimatization relies on natural environments, unfeasible for military training. This study aimed to establish mobile cabin-type thermal rooms in basic-training troops and evaluate the effects of active and passive heat acclimation training in new soldiers. Mobile cabin-type thermal rooms were constructed in basic-training troops. New soldiers underwent heat tolerance tests, and those identified with poor heat tolerance were randomized into active or passive training groups. Following heat acclimation training, participants were re-evaluated, and physiological responses were compared between groups. A total of 1326 male new soldiers participated in the heat tolerance test; 134 (10.1%) were identified with poor heat tolerance. Among them, 70 were assigned to the active training group and 64 to the passive group. All participants completed training and subsequently passed the heat tolerance test. Both groups showed significant improvements in core physiological and stress indices (P < .05), with no statistical differences between groups (P > .05). However, the rise in core temperature and heart rate occurred faster in the passive group, while a higher proportion of soldiers reported comfort in the active group (P < .05). Mobile cabin-type thermal rooms provide a reliable, rapid method for screening and training heat tolerance in basic-training troops. Both active and passive heat acclimation improved heat tolerance, but active training offered better subjective comfort. This approach enables safe and effective preparation for military personnel in hot environments.
Paddy leaf disease (PLD) detection has grown more difficult, yet early detection might prevent significant losses due to decreased crop yield. However, existing models struggle to accurately classify diseases under difficult circumstances like intricate backgrounds, fluctuating lighting, and overlapping leaves. Additionally, existing models do not incorporate efficient optimization strategies, leading to suboptimal accuracy and poor generalization on unseen data. To address these challenges, a novel deep learning-based YOLO-LEAFNET method for PLD detection utilizing IGT-YOLO, integrating the YOLOv8 disease detection with the Improved Gorilla Troops (IGT) optimization. The input paddy leaf images are pre-processed using Bilateral Contrast Limited Adaptive Histogram Equalization (B-CLAHE) to enhance image quality and improve local contrast while preserving disease boundaries. YOLOv8 model is utilized to detect and classify paddy leaf diseases by accurately localizing affected regions with bounding boxes. Then, the IGT algorithm boosts the disease detection accuracy by optimizing YOLOv8 through effective hyperparameter tuning. The proposed YOLO-LEAFNET method effectiveness was evaluated using recall, F1 score, specificity, accuracy, and precision. B-CLAHE enhanced noise-free images improve contrast and detection accuracy, while the IGT-YOLO model ensures scalable, efficient early diagnosis of paddy leaf diseases with 99.07% accuracy. The YOLO-LEAFNET enhanced the total accuracy by 3.21%, 5.25%, and 1.98% related to CNN, DeepRice, and FasterR-CNN, respectively.
The deployment of distributed energy resources (DERs) into power systems significantly improves their efficiency and reliability. Nanogrids (NGs), as small-scale systems that integrate DERs at the building level, require effective energy management to achieve optimal economic operation. This manuscript proposes an enhanced energy management system (EMS) for grid-connected NGs that combines day-ahead and real-time scheduling to minimize daily energy cost while maintaining the balance between power supply and demand. The day-ahead scheduling consists of two stages: first, applying demand-side management (DSM) using the load shifting approach with the day-ahead pricing curve; and second, determining the optimal powers of the DERs within the NGs. These resources are dynamically adjusted in real time to account for uncertainties in renewable generation, grid electricity prices, and load variations. Since energy scheduling is a complex, nonlinear optimization problem with multiple constraints, a recently developed metaheuristic technique, the Artificial Gorilla Troops Optimizer (AGTO), is proposed to obtain efficient solutions, and it is compared with different techniques such as the Honey Badger Algorithm (HBA), Aquila Optimizer (AO), and Particle Swarm Optimization (PSO). Simulation results show that the proposed AGTO-based EMS for grid-connected NGs achieves superior cost efficiency, saving approximately 15.83% compared to other approaches when determining the optimal setpoints of diesel generators and batteries, considering DSM in day-ahead scheduling.
The efficient incorporation of distributed generators optimal DG in distribution networks represents a fundamental strategy for ensuring economical and efficient power system operation. The optimal DG problem can be described as a Mixed Discrete-Continuous Optimization Problem (MDCOP). In this study, a new hybrid approach combining Gorilla Troops Optimization and Genetic Algorithm, namely the Hybrid GTO-GA, is proposed. The proposed hybrid is utilized to decide the optimal sizing and location of DG units in distribution networks to reduce power losses and ameliorate the voltage profile, either individually (i.e., single-objective) or simultaneously (i.e., multi-objective). The effectiveness of the suggested hybrid GTO-GA approach is examined using 23 test functions and applied to two practical test systems of different sizes: the IEEE 33-bus distribution system and a real 143-bus system. The simulation findings display that the hybrid GTO-GA approach ensures better convergence and improved exploration of the search space compared to standalone GTO and GA algorithms. It has also proven effective in significantly reducing economic losses by minimizing power loss and voltage deviation. In the IEEE 33-bus system, yearly economic losses decreased from 91,988.14 $ to 13,773.960 $, resulting in savings of 78,214.18 $. Similarly, in the real143-bus system, losses were reduced from 177,898.08 $ to 32,401.56 $, yielding savings of 145,496.52 $.
Polycyclic aromatic hydrocarbons (PAHs) are combustion pollutants that are released into the environment through natural events and anthropogenic activities. Exposures to PAHs occur in military personnel during garrison (non-combat) and active deployment (combat) environments. Exposures that occur at low levels during deployment could lead to health issues, post-deployment. A scoping review was conducted to address the pathways of exposure, and the adverse effects caused by PAHs in active-duty personnel and veterans. Out of 50,171 scientific publications screened from 5 databases, 296 studies were identified that focused on the relationship between exposure to PAHs from various point sources and debilitating health issues reported in veterans. The findings revealed that in combat conditions, PAHs are released into the environment through explosions caused by bombing, artillery fire, and missile attacks on military installations, petrochemical industries, oil well fires set by saboteurs, and burn pits used to incinerate ammunition waste and military base refuse. Significant exposure of troops to PAHs occurred during active combat in the Operation Desert Shield, Operation Desert Storm, and Operation Enduring Freedom campaigns launched against hostile forces. The PAH releases contaminated not only the affected service personnel and staff, but also the surrounding environment. The coastal environment, including its flora and fauna, were affected by oil tanker fires, petroleum storage tanks that caught fire during conflict and subsequent release of PAHs into the marine environment. The human health effects resulting from PAH exposures included severe lung-, kidney-, and reproductive dysfunctions, as well as an increased risk of cancer, mostly manifested in Veterans as part of the Gulf War Syndrome. The Exposome approach utilizing the omics-based biomarkers to characterize individual service member profile with wearable monitors (wrist bands and sensors) to characterize the external environment when combined with biomonitoring studies holds significant promise for treatment of troops during combat and post deployment.
Modern large-scale combat operations (LSCO) combine high-tech weapons such as drones and advanced sensors, with low-tech tactics like trench warfare and massed infantry assaults. The Russian invasion of Ukraine illustrates key LSCO features: limited cover and concealment, high casualty rates, and little opportunities for respite or recovery. Such conditions place extraordinary psychological demands on service members. Beyond preparing troops with tactical training, this environment requires explicit practice of mental skills under operational stress. This paper presents findings from the Operational Resilience Training (ORT) program, a U.S.-Norwegian collaboration designed to build mental readiness for LSCO. ORT has been delivered to Ukrainian service members rotating in and out of frontline duty. The course follows a "crawl, walk, run" progression: instruction ("crawl"), structured field practice ("walk"), and high-intensity simulations that test skills under duress ("run"). This approach allows trainees to internalize and apply mental skills such as controlled breathing, attention control, and peer support during the preparation, performance and recovery phases of a mission. Evaluation data indicate that ORT is well-received and leads to significant increases in confidence of abilities to help oneself and others manage combat stress. Anecdotal reports suggest that ORT techniques are being successfully applied in real combat settings by both novice and experienced personnel. Thus, the current paper describes ORT skills and implementation practices aimed at maintaining performance and well-being among troops in current and future LSCO environments.
Closed traumatic rupture of both flexor tendons in a finger in absence of any disease is a rare entity to confront. We present a case of closed traumatic rupture of both flexor digitorum profundus and flexor digitorum superficialis in zone II right little finger in a 24 years old healthy male. The injury was caused due to sudden extension force in a flexed finger. Primary repair of only flexor digitorum profundus was performed with complete functional recovery at four months of follow up. This injury, though rare, is sustained due to forceful extension of the flexed little finger, a mechanism of injury very possible in troops actively deployed in operations in difficult conditions. Prompt recognition and appropriate treatment are required for optimal functional outcome.
Obligate bipedalism is a defining trait of the human lineage, yet the selective pressures underlying its emergence and fixation remain debated, particularly within the woodland-grassland mosaic environments associated with early hominins. Modern semi-terrestrial primates inhabiting comparable ecosystems provide a useful model for evaluating candidate functional contexts of early bipedal behavior in the human lineage. Here, we present the first systematic description of bipedal behavior in chacma baboons (Papio ursinus griseipes). Using all-occurrence sampling across two troops of baboons in Gorongosa National Park, Mozambique, we recorded 231 bipedal bouts over 12 observation days. Bipedalism was predominantly postural and most frequently occurred in vigilance contexts. Several social contexts of bipedalism were recorded, including play, grooming, socio-sexual mounting, and attempted infant snatching. Arboreal bipedalism was rare and primarily linked to foraging. Rates and contexts of bipedalism varied across age-sex classes. Infants and juveniles exhibited higher bipedalism rates than other classes and expressed the broadest bipedal context repertoire. Vigilance was the only context prompting bipedalism across all age-sex classes. We discuss these patterns to evaluate how multi-contextual, socially-relevant and age- and sex-structured bipedalism behavior in baboons may inform reconstructions of early hominin bipedalism.
Craniofacial trauma in warfare is most commonly associated with ballistic injuries; however, close combat may also produce blunt facial trauma through the use of rifle butts or other striking weapons. During the Battle of Kumyangjang-ni in 1951, soldiers of the Turkish Brigade engaged troops of the Chinese People's Volunteer Army in intense close combat. Historical accounts report that many fallen enemy soldiers exhibited severe injuries to the mandible, giving rise to the nickname "rifle-butt battle." Although these observations were not documented in formal medical reports, biomechanical considerations suggest that a rifle butt could deliver sufficient blunt force to produce mandibular fractures, particularly in the body, angle, or condylar regions. The prominent anatomic position of the mandible makes it especially susceptible to such impacts. Historical accounts of close combat, such as those reported in the Battle of Kumyangjang-ni, illustrate mechanisms of blunt mandibular trauma that remain relevant to modern craniofacial surgeons managing facial injuries caused by interpersonal violence and blunt assault.
Modern interconnected power systems with high penetration of renewable energy sources (RES) and large‑scale use of electric vehicles (EVs) experience recurring frequency and voltage disturbances. Accordingly, the main objective in this work is to overcome this limitation in a power system under coordinated load frequency control (LFC) and automatic voltage regulation (AVR), which requires highly accurate control strategies. Fuzzy logic‑based controllers are among the most promising approaches for disturbance rejection, control precision, system stability, and robust performance. However, their performance is often limited because the selection of crisp ranges (i.e., the universes of discourse of the fuzzy variables) is usually set heuristically. In this paper, the crisp output range of a Fuzzy Proportional Integral Derivative Double Derivative (FPIDD2) controller, which is based on a previous study, is reconfigured while maintaining the original rule base and membership function structure unchanged. This reconfiguration is presented to change the controller's response by recentering (shifting) the zero output membership function rightward, thereby improving control sensitivity and dynamic performance. The effectiveness of the proposed approach is validated via MATLAB simulation on a multi‑area interconnected power system under realistic operating conditions, including stochastic input fluctuations due to renewable energy source penetration and electric vehicle participation, as well as nonlinear constraints such as generation ramp‑rate limits and governor dead zones. Several metaheuristic optimizers, including Particle Swarm Optimization (PSO), Gorilla Troops Optimizer (GTO), and Marine Predators Algorithm (MPA), are used to further evaluate the robustness of the proposed method. The results demonstrate that optimized FLC configuration with modified crisp ranges significantly improves controller sensitivity, damping characteristics, and robustness. Consequently, the Integral of Time- Absolute Error (ITAE) is reduced by up to 69% compared to the original controller configuration.
The growing demand for concrete poses a significant environmental challenge, but alkali-activated high-performance concrete (AA-HPC) offers a more sustainable alternative by potentially reducing carbon emissions and ecological harm. This study explores the latest developments in machine learning (ML) applications aimed at predicting the compressive strength of AA-HPC, with a focus on minimizing experimental expenses, construction duration, and environmental impact. Among nine evaluated ML models, the combination of extreme gradient boosting (XGBoost) with the African vultures optimization algorithm (AVOA) emerged as the most effective. AVOA proved highly efficient in optimizing model parameters, achieving the lowest root mean square error (RMSE) during hyperparameter tuning. On the training dataset, XGB-AVOA reached an R2 of 0.994 and an RMSE of 2.368, while on the testing dataset, it maintained superior performance with an R2 of 0.975 and an RMSE of 5.664. These findings highlight AVOA's strength in fine-tuning XGBoost compared to alternative optimizers such as grey wolf optimizer (GWO), whale optimization algorithm (WOA), social spider optimization (SSO), and gorilla troops optimizer (GTO). To support practical implementation, a graphical user interface (GUI) has also been developed, allowing researchers to efficiently utilize the XGB-AVOA model for accurate, cost-effective, and time-saving predictions in laboratory environments.
Interconnected power systems are frequently exposed to load disturbances, parameter uncertainties, nonlinear effects, and dynamic coupling between frequency and voltage regulation loops, which make it difficult to maintain stable and well-coordinated operation. Conventional control strategies may suffer from slow damping, large oscillations, and reduced robustness when applied to such highly coupled environments. To address this problem, this paper proposes a novel cascaded controller for the coordinated regulation of Load Frequency Control (LFC) and Automatic Voltage Regulation (AVR) in a two-area interconnected power system. The proposed controller combines a two-degree-of-freedom proportional-derivative controller with filtered derivative action (2DOF-PDf) and an inner leaky tilt-integral (LTI) stage to improve transient shaping, damping, and robustness while reducing sensitivity to disturbances and parameter variations. The controller parameters are optimally tuned using the Crayfish Optimization Algorithm (CrOA) based on the Integral of Time-weighted Squared Error (ITSE) criterion. The effectiveness of CrOA is first verified through comparison with several well-known optimization methods, including the Chimp Optimization Algorithm (ChOA), Dingo Optimization Algorithm (DOA), Sine Cosine Algorithm (SCA), Gorilla Troops Optimizer (GTO), and Gradient-Based Optimizer (GBO). The proposed control scheme is then assessed under various operating scenarios, including step load disturbances, stochastic load variations, practical nonlinearities such as Generation Rate Constraint (GRC) and Governor Dead Band (GDB), time-varying voltage reference tracking, and parametric uncertainty of up to ± 40%. MATLAB/Simulink results demonstrate that the proposed CrOA-tuned cascaded (2DOF-PDf)-(LTI) controller provides faster damping, smaller frequency and tie-line power deviations, and more accurate terminal-voltage regulation than several benchmark controllers, including Proportional-Integral-Derivative (PID), Tilted Integral Derivative (TID), Fractional-Order Proportional-Integral-Derivative (FOPID), and Fractional-Order Proportional-Integral with Proportional-Integral-Double Derivative Squared (FOPI-PIDD2) controllers. Overall, the proposed controller offers a robust and effective solution for coordinated frequency and voltage regulation in interconnected power systems.
While the mission of the United States military medical corps has always been to care for combat wounded and military troops, the passage of the 1956 Dependents' Medical Care Act extended the provision of medical services to military dependents into that mission. Our nation's goals have also included military humanitarian assistance in peace and war, which contributes to operational readiness. Given the global reach of the United States military, this support serves patients in all corners of the planet. Neonatal and pediatric patients have benefited significantly from the military development of global transport, Extracorporeal Membrane Oxygenation, and Pediatric Critical Care Air Transport Teams. This article highlights the development of these programs. Colleen M. Fitzpatrick, MD, MPA, FACS, FAAP served as a pediatric surgeon in the United States Air Force from 2008 to 2016. Additionally, she completed her general surgery training and research on active duty at Wilford Hall Medical Center, Lackland AFB from 1999 to 2006. During her military tenure, she was initially stationed at Wilford Hall Medical Center and Brooke Army Medical Center at the San Antonio Military Medical Center. She was then stationed at the Center for the Sustainment of Trauma and Readiness Skills, St. Louis at St. Louis University where she completed her military commitment. During her time on active duty, she served at the Pediatric Surgery Consultant to the US Air Force Surgeon General, and she deployed to Bagram Airfield, Afghanistan, in support of Operation Enduring Freedom.
Millions of U.S. troops and supporting personnel have been deployed to military bases in the Middle East. Essentially all personnel on military bases were exposed to the combustion emissions generated by open pit waste burning. Chronic multisymptom illness (CMI) is a term advanced to characterize the complex health effects of inhalation exposures to military burn pits (BP). Because of the diversity of geography, environmental conditions, and deployment operations, it is very challenging to estimate the number of Veterans affected by CMI, but it has been reported to be in the range of ~ 40-60%. Despite this overwhelming number of patients, the underlying causes of CMI remain to be identified. The purpose of this study was to replicate BP combustion and deliver these representative emissions to a whole-body inhalation exposure chamber with Sprague Dawley rats. We hypothesized that because the microcirculation is a critical component of health and disease, that normal microvascular function may be disrupted after BP inhalation exposures. A surrogate BP emission generator was used to combust mixtures of wood, rubber, plastic and jet fuel. Resultant emissions were complex mixtures of volatile organic chemicals, polyaromatic hydrocarbons, fine and ultrafine particles. The particle aerodynamic count median diameter was 113 nm with a geometric standard deviation of 2.21. The particle mobility diameter was 78.1 nm with a geometric standard deviation of 1.69. The aerosol mass-size size distribution had a mass median aerodynamic diameter of 288 nm with a geometric standard deviation of 1.72 nm. Rats were exposed for ~ 4 h/d at BP emission concentrations of 15.4 ± 1.6 mg/m3, for 2, 3, or 6 days. Twenty-four hours later, the spinotrapezius muscle was prepared for intravital microscopy. Tissues were also harvested from different rats in these groups for thorough mechanistic analyses. After 3-6 days of exposure, endothelium-dependent arteriolar dilation was abolished. Adrenergic vasoconstrictor sensitivity was augmented by as much as 50% in the BP exposure groups. Bronchoalveolar lavage revealed robust pulmonary inflammation and cellular infiltration. High-performance liquid chromatography with plasma samples demonstrated significant increases (> 50%) in circulating xanthine oxidase, a known driver of oxidative stress, disruptor of vascular nitric oxide, and thus mediator of endothelial dysfunction. After 3 days of BP exposure, RNA sequencing tissue analyses revealed transcriptional markers of lung inflammation as well as an altered transcriptional immune response in both the lung and spleen. BP inhalation exposure also led to elevated RNA transcripts for the vascular growth factor Vegfa and the immune cell trafficking factor Icam1 in brain hippocampal tissue. These initial microvascular observations demonstrate disruption of typical function and mechanisms that may link pulmonary insult with diverse systemic syndromes characteristic with CMI in Veterans.
Potentially more than 100,000 US troops were exposed to organophosphorus (OP) nerve agents when an ammunition bunker at Khamisiyah, Iraq was destroyed shortly after the end of the 1991 Gulf War (GW). We previously reported evidence of differences in brain structure and function in GW veterans with predicted exposure to the Khamisiyah plume compared to veterans without predicted exposure. Here, we investigate the effects of predicted exposure to the Khamisiyah plume on brain functional connectivity in the default mode network (DMN). Forty-one GW veterans (19 with and 22 without predicted exposure) underwent structural and resting-state magnetic resonance imaging (MRI) on a 3 Tesla scanner. Differences in DMN connectivity between veterans with and without predicted Khamisiyah exposure were examined using a left posterior cingulate cortex (PCC) seed-based analysis in AFNI. FreeSurfer was used to derive quantitative estimates of total hippocampal volume. The veterans were also assessed with the Conners Continuous Performance Test (CPT). Compared to veterans without predicted exposure, those with predicted Khamisiyah exposure demonstrated weaker connectivity between the left PCC and a cluster in the caudal right anterior cingulate cortex (ACC). Veterans with predicted exposure also had smaller left hippocampal volume compared to unexposed veterans. Although the cross-sectional nature of this study precludes conclusions about causality, the finding of decreased DMN functional connectivity in GW veterans with predicted Khamisiyah exposure warrants replication in a larger, independent sample. If confirmed, this result would add to the literature suggesting persistent differences in brain function between deployed GW veterans with and without predicted Khamisiyah exposure and argue for further investigation into the long-term effects of GW-deployment related exposures.
The implementation of multiple distributed energy resources (DER) into the radial distribution networks which includes Photovoltaic (PV) systems, Electric Vehicle Charging Stations (EVCSs), and Battery Energy Storage Systems (BESS) presents a number of challenges that include voltage regulation and power loss as well as the challenges in managing load demand. In this paper, the author presents a superior optimization model that employs a new Hybrid Sine Cosine Gorilla Search Algorithm (HSCGSA) to effectively coordinate the addition of PV units, EVCS charging loads and BESS in the radial distribution systems. The offered approach will seek to maximize the position and size of DERS to reduce active and reactive power losses and ensure the stability of the voltage throughout the network. The HSCGSA is a hybrid approach to enhancement of the exploratory ability of the Sine Cosine Algorithm (SCA) and the exploitation power of the Gorilla Troops Optimizer (GTO), which provides a balanced solution to the intricate and complex optimization problems involving multiple planning criteria. The performance of the proposed algorithm is validated through simulations on IEEE 33-bus, 69-bus, and 118-bus radial distribution systems. The results demonstrate that the proposed HSCGSA significantly improves system performance compared with the conventional Genetic Algorithm (GA). For the IEEE 33-bus system, the active power loss is reduced from 3477.166 kW to 1577.06 kW, representing a reduction of approximately 54.6%, while the minimum bus voltage improves from 0.9224 pu to 0.9706 pu. In the IEEE 69-bus system, the active power loss decreases from 3859.99 kW to 1381.28 kW, corresponding to a reduction of about 64.2%, along with a substantial enhancement in the voltage stability index. Similarly, in the IEEE 118-bus system, the active power loss is reduced from 2279.42 kW to 608.55 kW, achieving nearly 73% reduction when multiple DER units are optimally allocated. These results confirm that the proposed HSCGSA provides superior capability for optimal placement and sizing of PV units, EV charging stations, and battery energy storage systems in radial distribution networks.
This paper presents a novel hybrid control strategy that integrates a Fuzzy Proportional–Integral–Derivative Double Derivative (FPIDD²) controller with a conventional PIDD² controller for Load Frequency Control (LFC) and Automatic Voltage Regulation (AVR) in multi-area interconnected power systems, respectively. The proposed FPIDD²+PIDD² hybrid scheme enhances the overall dynamic stability and robustness of power systems operating under high renewable energy penetration. Controller parameters are optimally tuned using different metaheuristic algorithms, namely the Particle Swarm Optimization (PSO), Gorilla Troops Optimizer (GTO), and Marine Predators Algorithm (MPA). The proposed hybrid controller’s performance is evaluated against conventional PID and standalone PIDD² controllers under various disturbances, including step load changes, random load variations, and renewable energy fluctuations, where control performance is evaluated based on the Integral of Time-weighted Absolute Error (ITAE) criterion. Within the simulated test cases, the proposed FPIDD²+PIDD² controller achieves notable performance improvement, reducing ITAE by up to 94% and 90% compared to conventional PID and standalone PIDD² controllers, respectively. These results confirm the hybrid controller’s smooth transient response, enhanced damping, and improved robustness against nonlinearities and system uncertainties.
In June 2023, the Kakhovka Hydroelectric Power Plant's dam was destroyed by Russian troops, leaving large areas downstream flooded and an area upstream dried-up. Therefore, the objectives of this screening-level study were (i) to determine the content of organic pollutants in the alluvial soils that have dried-up and soils that are above the old water level, and (ii) to determine the pattern of accumulation of organic pollutants in the dried-up zone. The alluvial soils within the city of Zaporizhzhia were sampled from the superficial, 30 cm, layer in six areas in the dried-up zone, drained after the dam's breach, and also in six areas in the floodplain above the former water level. The composition of organic pollutants was determined using the method of gas chromatography-mass spectrometry. The distribution of organic pollutants in the soils was analyzed based on the hygrophilicity index that we proposed, which was calculated as a ratio of the amount of compound in the soils of the dried-up zone to its amount in the dried-up zone and in unflooded areas together. We identified 155 organic compounds, 24 of which are hazardous toxicants that contaminate the environment. Those compounds were represented by polycyclic aromatic hydrocarbons, acid esters, aromatic heterocycles, and other compounds. This ecological pollution jeopardizes the urban landscapes of Zaporizhzhia and other setllemens on the banks of the former Kahovka Reservoir and the health of people in southern Ukraine.
Published research on primate rehabilitation and release (R&R) is limited and studies suggest that released mortality is generally high. We investigated factors affecting survival and behavior of a rehabilitated troop of vervet monkeys (Chlorocebus pygerythrus rufoviridis) released into Kasungu National Park in Malawi in 2016 by the Lilongwe Wildlife Trust (LWT). Estimated troop survival 9 months after release was 45% when dispersing-age male disappearances were considered emigrations, which is comparable to other vervet monkey R&R. Using a combination of linear modeling, survival analysis, and social network analysis, we considered social rank, forest strata use, antipredator behavior, troop cohesion and social connectedness, and behavioral diversity across release phases as potential factors influencing survival. Our results suggest that socially connected individuals and juveniles were more likely to survive, with these factors more significant than sex, social rank, and antipredator behavior. Unexpectedly, antipredator behavior significantly decreased after release, which may be a factor linked to increased predation. Also unexpectedly, behavioral diversity decreased post-release, likely due to a significant increase in locomotion upon release and limitations with our ethogram. The observed mortality patterns suggest that R&R troops may benefit from pre-release training with platform feeders that encourage canopy use. When possible, individual life history data (e.g., captive-born, orphaned) should be collected at rescue and rehabilitation stages to help inform caretakers of unique needs. LWT's extensive pre- and post-release monitoring provides vital insights into the factors influencing this troop's survival. We urge other rehabilitation centers to follow this strategy to improve R&R programs.